Reconstruction of Pleistocene Ice-Dammed Lake Outburst Floods in the Altai Mountains, Siberia (GSA Special Paper 386)

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THE GEOLOGICAL SOC lEn' Of AMERICA

Special Paper 386

Reconstruction of Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

Jürgen Herget Geographisches Institut der Universitat Bonn Meckenheimer Allee 166 D-53115 Bonn Germany

Special Paper 386 3300 Penrose Place, P.O. Box 9140

Boulder, Colorado 80301-9140 USA

2005

Copyright © 2005, The Geological Society of America, Inc. (GSA). All rights reserved. GSA grants permission to individual scientists to make unlimited photocopies of one or more items from this volume for noncommercial purposes advancing science or education, including classroom use. For permission to make photocopies of any item in this volume for other noncommercial, nonprofit purposes, contact the Geological Society of America. Written permission is required from GSA for all other forms of capture or reproduction of any item in the volume including, but not limited to, all types of electronic or digital scanning or other digital or manual transformation of articles or any portion thereof, such as abstracts, into computer-readable and/or transmittable form for personal or corporate use, either noncommercial or commercial, for-profit or otherwise. Send permission requests to GSA Copyright Permissions, 3300 Penrose Place, P.O. Box 9140, Boulder, Colorado 80301-9140, USA. Copyright is not claimed on any material prepared wholly by government employees within the scope of their employment. Published by The Geological Society of America, Inc. 3300 Penrose Place, P.O. Box 9140, Boulder, Colorado 80301-9140, USA www.geosociety.org Printed in U.S.A. GSA Books Science Editor: Abhijit Basu Library of Congress Cataloging-in-Publication Data Herget, Jürgen. Reconstruction of Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia / Jürgen Herget p. cm. -- (Special papers ; 386) Includes bibliographical references. ISBN 0-8137-2386-8 (pbk.) 1. Paleohydrology--Altai Mountains. 2. Glacial lakes--Altai Mountains. 3. Geology, Stratigraphic--Pleistocene. I. Title II. Special papers (Geological Society of America) ; 386. QE39.5.P27H47 2005 551.48’09517’3--dc22. QC884.5.E8319613 2004 551.6947—dc22 2004063583 Cover: Fluvial gravel dunes in north-western Chuja Basin near Chagan-Uzun village. Photo by P. Borodavko.

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Contents Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aims . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structure of the Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 2. Ice-Dammed Lakes and Jökulhlaups. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Classification of Ice-Dammed Lakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Mode of Drainage and Outburst Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Hydrographs of Jökulhlaups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Occurrence and Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 3. Altai Mountains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Location and Geology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Current Climate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Quaternary of Altai Mountains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 4. Evidence of Jökulhlaups in the Altai Mountains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Previous Studies and Reviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Flood-Related Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Lake Sediments and Shorelines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Ice Dam and Failure Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Giant Bars and Indication of Flow Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.4 Secondary Lakes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.5 Gravel Dunes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.6 Erosional Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.7 Boulder Deposits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Criticism on Occurrence of Jökulhlaups in the Altai Mountains . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Open Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Chapter 5. Reconstruction of the Floods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Uniform Flow Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Hydraulic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Data from the Altai Mountains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.4 Paleohydraulic Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Flow Calculation by HEC-RAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Hydraulics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

41 41 41 41 42 42 44 44 44 45

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Contents 5.2.3 Paleostage Indicators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 5.2.4 Paleohydraulic Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.2.4.1 Previous water level calculations of Pleistocene outburst floods . . . . . . . . . . . . . . . . . 47 5.2.4.2 Previous water profile calculations for the flood in the Altai Mountains . . . . . . . . . . . 49 5.2.4.3 Calculations for mixed flow regime . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.2.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 5.3 Velocity Head Calculations using Run-Up Sediments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.2 Hydraulics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 5.3.3 Run-Up Sediments in Chuja and Katun Valley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 5.3.4 Paleohydraulic Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 5.3.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 5.4 Correlation of Lake Volume and Peak Discharge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 5.4.2 Hydraulics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 5.4.3 Volume of Ice-Dammed Lake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.4.4 Paleohydraulic Calculation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.5 Boulder Transport . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.5.2 Hydraulic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 5.5.3 Boulders near Inja Village . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5.5.4 Paleohydraulic Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 5.5.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 5.6 Gravel dunes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.6.2 Hydraulic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.6.3 Dune Data for Paleohydraulic Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 5.6.4 Paleohydraulic Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 5.6.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5.7 Obstacle marks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5.7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5.7.2 Hydraulic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.7.2.1 Submerged obstacles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.7.2.2 Bridge piers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.7.3 Examples of Obstacle Marks in Chuja and Katun Valleys . . . . . . . . . . . . . . . . . . . . . . . . . 92 5.7.4 Paleohydraulic Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 5.7.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100 Chapter 6. Review of Dynamics of the Altai Jökulhlaups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Appendices. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Table A1. Location and Characteristics of Flood Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 Table A2. Bar Surfaces and Levels from Topographic Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 References Cited . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

Geological Society of America Special Paper 386 2005

Reconstruction of Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Jürgen Herget* Geographisches Institut der Universität Bonn, Meckenheimer Allee 166, D-53115 Bonn, Germany

ABSTRACT In the Siberian Altai Mountains, where the sources of the River Ob are located, ice-dammed lake outburst floods, so-called jökulhlaups, occurred in Pleistocene times. Valley glaciers extended within the upper Chuja River catchment and dammed the river upstream of the village of Aktash, which generated ice-dammed lakes in the intramountainous Kuray and Chuja Basins. Indicated by shorelines and ice-rafted boulder deposits, the maximum lake level reached an altitude of 2100 m above sea level, which reveals a maximum lake volume of 607 km3. The failure of the ice dam caused outburst floods, which left traces by giant bars, fluvial gravel dunes, and boulder deposits. Run-up sediments deposited in front of local obstructions along the valley slopes indicate a maximum depth of flow of 400 m above the valley bottom. Like the giant bars, they consist of characteristic relatively fine suspension gravels. Occasionally, secondary lakes are formed in tributary valleys that were blocked by giant bar deposits. The alternation of lacustrine deposits and suspension gravels in the tributary Injushka valley near Inja village give evidence for at least three large outburst floods. Age estimations by a variety of dating methods, such as luminescence methods, exposure dating, and accelerator mass spectrometry radiocarbon applied on different flood features and lake sediments, indicate that the outburst floods occurred between 40 ka and 13 ka. This estimation should be taken as preliminary, as problems occurred with the different dating techniques, resulting in partly contradictory results. This study focuses on the paleohydraulic reconstruction of the flood rather than describing flood-related features in detail. Seven different approaches are applied to estimate the discharge of the floods. Several new methods are developed within the study, partly based on previous approaches carefully considering the hydraulic background. Data for paleohydraulic estimations are obtained during repeated field trips by observations, surveys, and sedimentological investigations in Chuja and Katun valleys. Peak discharge is estimated by the elevation of the surfaces of the giant bars indicating the depth of flow and additionally by the run-up sediments, which reveal information about the velocity head of the flood flow along the valleys. A value of 10 × 106 m3/s is estimated for peak discharge, which is considerably less than previous estimations derived. Dimensions of gravel dunes and obstacle marks obtain information of flow conditions during the decreasing flood. The application of regression formulae between drained lake volume and peak discharge, an established method to estimate discharges of jökulhlaups, and estimation of flow velocity considering flow *herget @giub.uni-bonn.de Herget, J., 2005, Reconstruction of Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia: Geological Society of America Special Paper 386, 118 p. For permission to copy, contact [email protected]. ©2005 Geological Society of America.

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J. Herget competence indicated by transported boulders yield problems as the magnitude of the outburst floods and the size of the boulders are beyond the level of experience. Based on the estimated peak discharge and the drained volume of water for the lake, the duration of a flood is estimated to be on the order of days, clearly less than one week. Considering the time needed to refill the lake after an outburst event leads to the rough estimation that recurrence intervals of floods are on the order of centuries. Open questions are intensively discussed throughout the study. For example, the relation of flood features to individual floods of the repeated outbursts is not possible unequivocally at the current state of knowledge. Further studies are required to obtain information on the extension and failure process of the ice dam, which would allow detailed modeling of the dynamics of the jökulhlaups. Also, methodological problems of dating techniques must be solved to develop a chronology of the floods in the Altai Mountains. Keywords: ice-dammed lake, glacial lake, jökulhlaup, outburst flood, paleohydrology, paleohydraulic, Altai.

Geological Society of America Special Paper 386 2005

Chapter 1 INTRODUCTION

fluvial gravel dunes were carried out (Carling, 1996a), deriving valuable information beyond the previously given first estimations of peak discharge. New findings in the field provide further information on the floods that seem to be promising for a possible closer view on the flood’s characteristics.

Problem The Pleistocene ice-dammed lake outburst floods in the Altai Mountains have been characterized as having been Earth’s greatest floods with an estimated peak discharge of 18 × 106 m3/s (Baker et al., 1993). This estimation slightly exceeds the peak discharge of the Lake Missoula flood, another Pleistocene outburst flood, and is nearly two orders of magnitude larger than current floods of the world’s largest rivers caused by rainfall or ice jams (Fig. 1). As illustrated by Figure 1, floods caused by geological processes are the largest if they are arranged by causative processes. The estimated magnitude of the floods in the Altai Mountains drew attention to the phenomenon, and several studies on the sedimentology of lake and flood features were carried out. In the framework of these studies, first paleohydraulic interpretations of

Aims The aim of the presented study is to increase the amount of flood indicators in order to develop a reconstruction of the outburst floods from the ice-dammed lake as detailed as possible. Several different kinds of flood and flow indicators are investigated and interpreted by varying methods to gain estimations on the characteristics of the outburst flood. Giant fluvial bars along the pathway of the flood indicate the water level during the outburst floods. A survey of their locations and heights allows calculation of the depth of flow for nearly 100 km of the uppermost course of the flood. These paleostage indicators reveal a

Figure 1. Quaternary floods with discharges >100,000 m3/s, arranged by causative process (modified after various sources from O’Connor et al., 2002, Fig. 3 therein).

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more accurate and detailed water level estimation than a previous attempt at the location of the former ice dam (Baker et al., 1993). Different calculation procedures are applied on the giant bars considering their characteristics that allow a closer view to the dynamic and nature of the outburst flood. In addition, channel bed forms such as gravel dunes and obstacle marks are surveyed to obtain quantitative information on their shape and geometry as they reflect another stage of flow conditions. Competence of flow is indicated by the dimension of boulders transported, while the correlation of drained lake volume with peak discharge of the outburst flood is an estimation attempt without any physical basis but which has previously been applied with sufficient accuracy. All together, seven different attempts are applied to estimate the paleohydraulics of the floods. This study is a paleohydraulic reconstruction rather than a paleohydrological investigation, which typically focuses on rainfall-runoff relationships (Carling et al., 2003). Considering that no direct observation of the Pleistocene event could be made, the studied flood is no sufficient subject for fluid-mechanical approaches. Hence, one would be disappointed if advanced or detailed analysis were expected, as occasionally relatively rough estimations are needed for assumptions of different parameters. Floods of the magnitude of 106 m3/s react less sensitively to uncertainties of estimated parameters, as will be documented by sensitivity analysis. Besides a limitation on basic hydraulic parameters such as flow velocity, depth of flow, discharge, and flow conditions are chosen. Calculations of further parameters usually require high accuracy of these parameters, which would lead to increasing uncertainty considering that typically magnitudes of values are obtained only. Methods The hydraulic calculation methods of this study are explained in detail in Chapter 5. Knowledge of the basic nomenclature of hydraulics is required (e.g., Chanson, 1999; Kay, 1998; French, 1985; Chow, 1959), while details on the background for the modeling are given in the text. Methods applied in the field and in different laboratories are briefly mentioned below. References for dating methods and special technologies are given. Different survey techniques are applied, depending on the scale of the investigated feature and available instruments. The location of the surfaces of giant bars is determined by the global positioning system (GPS). The simple handheld receiver used obtains an accuracy of the horizontal position of about ±100 m, while the vertical accuracy depends on the number and spatial configuration of the received signal from the navigation satellites; typically it is less than for the horizontal position (Bauer, 1994; Hartl and Thiel, 1996; Letham, 1995). As the most detailed topographic maps available for the area of investigation are of a scale of 1:50,000, the accuracy is sufficient to determine the location of the bars investigated in the field on the map. As detailed maps are the subject of secrecy in Russia, topographic

maps are obtained from a company in the United States. Subjects of potential sensitive character (data on the size of bridges and width of roads) are removed on the maps presented within the study to respect the classification of the maps by Russian administration. Measurements of heights are carried out by the use of barometric altimeters. Carefully used, altimeters with digital display indicate relative difference of height with an accuracy of ±1 m, while absolute altitude is given within a range of ±5 m (Kahmen, 1993). This level of precision is achieved by consideration of trigonometric and height points from topographic maps on which the altimeters were calibrated. Measurements of the height of a bar are carried out twice, on the way up to the bar surface and again on the way down. The phenomenon of drift of elevations indicated by the altimeter due to changes of air pressure during the day is compensated by noticing the time of measurements and repeated calibration of the instrument. Occasionally, giant bars on the opposite side of rivers are not accessible due to the limited number of bridges. To estimate the elevation of their surface the vertical angle between a known elevation and the bar surface is determined by inclinometer measurements. The distance between the bars on the different sides of the valley are determined by topographic maps, and the difference in elevation is calculated by trigonometric formulae. Tests for known points and difference revealed a sufficient accuracy that cannot be improved by considering the slope of the bars given by distances of contour lines in topographic maps. To increase the density of data points, bar surface elevations occasionally are taken from topographic maps. This way is chosen only in cases where no other method can be used in a reliable way and only for locations that are observed in the field. The values for the elevation of the bar surfaces are of an accuracy of ±10 m, as interpolation of contour lines usually does not allow better estimations due to steep slopes. All data of bar surfaces and levels and several other locations of importance are listed in Table A2, where comments on methods of value determination are given for the individual points. The dimensions of gravel dunes are determined by theodolite measurements with prism mirror in profile lines normal to the highest dune crests in orientation to the dune field. The surveyed profile lines of gravel dunes are presented as figures in Section 5.6. This theodolite is also used to determine the shape of a scour hole and the related obstacle and the tilt angle of some shorelines in Chuja Basin. Several samples were taken to determine the age of flood features by different dating methods. The applied method and laboratory numbers are given in the text. Samples of organic material are investigated by radiocarbon dating in the laboratories of the Geological Institute of the Siberian Branch of the Russian Academy of Science (Novosibirsk) and Beta Analytics (Miami, USA). Some samples contain enough final carbon to be dated directly by 14C activity. On two samples, the accelerator mass spectrometer (AMS) technology

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia was applied to count the isotopes, as the final carbon content after sample treatment was not sufficient for the direct method. Samples dated by 14C AMS are marked. General information on radiocarbon dating is given, for example, by Wagner (1995). Optically stimulated luminescence techniques are also applied on some samples to determine the time of coverage of the samples taken from gravel dunes and giant bars. Previously unpublished results on samples investigated at Desert Research Institute (Reno, USA) by infrared stimulated luminescence (IRSL) on feldspar are kindly provided by P. Carling. Other samples analyzed by B. Mauz (Department of Geography, University of Bonn) were dated based on quartz. Details related to individual samples are mentioned in the text. A review on the method in general is given, for example, by Aitken (1998). Exposure dating is applied on an eroded bedrock surface of granite measuring the content of isotopes 10Be and 26Al. By this method, the degree of modifications in the isotope spectrum of the rock surface indicates the duration of exposure toward cosmic rays (Cerling and Craig, 1994; Gosse and Phillips, 2001). The investigations were carried out at the Cosmogenic Isotope Laboratory of the University of Washington (Seattle, USA) by G. Balco. Preliminary results of experimental investigation considering the inheritance phenomenon of previous exposure by taking samples at different depths from one location (Anderson et al., 1996; Repka et al., 1997) are also mentioned.

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Sedimentological investigations are beyond the scope of this study, but for some hydraulic calculations grain size data are required and were taken in the field. For coarse gravels, adequate sampling is a problem of volume and resulting weight (Gale and Hoare, 1992). Samples of 10–30 kg were taken and analyzed at the Department of Geography and Geology, State University Tomsk. Nevertheless, an underestimation of the coarse fraction cannot be excluded, as they might have been underrepresented due to limited sample volume. Structure of the Study The focus of the presented study is the reconstruction of the flood rather than discussion and analysis of the Quaternary environment of the Altai Mountains. After a brief introduction on the nature of ice-dammed lake outburst floods, in general a review of the relevant characteristics of the area of investigation is presented. This is followed by a description of the evidence of ice-dammed lakes and outburst floods during the Pleistocene in the Altai Mountains, including new findings and datings. Main parts of this study are the chapters on the paleohydraulic reconstruction of the flood by application of different techniques on various indicators and different approaches. The estimated discharges are discussed and compiled to a hydrograph of the flood based on available data.

Geological Society of America Special Paper 386 2005

Chapter 2 Vinogradov (1977), and Tweed and Russell (1999) who consider numerous preceding studies and reviews.

ICE-DAMMED LAKES AND JÖKULHLAUPS A general definition of ice-dammed lakes is given by Blachut and Ballantyne (1976, p. 1) as “a substantial body of standing water, located in, on, under or at the margin of a glacier, such that its existence is in some way dependent on damming by glacier ice.” This definition includes a differentiation of the position of an ice-dammed lake to the glacier or ice sheet and associates ice-dammed lakes to the group of glacier lakes (Schweizer, 1957) and naturally dammed lakes (Costa and Schuster, 1988). Frequently, ice-dammed lakes drain abruptly through, below, or over the ice dam causing a considerable flood in the valleys downstream. These floods are called jökulhlaup after the Icelandic expression for glacier-flood, but glacier lake outburst floods are also known as aluviones in South America, débâcles in France, and chhugümha in Nepal (Tweed and Russell, 1999, p. 81). In this chapter, a brief review on the classification of icedammed lakes, their drainage mechanisms, and the hydrology of jökulhlaups is given and illustrated by several recent or historic as well as Pleistocene examples. More detailed reviews are previously given, for example, by Blachut and Ballantyne (1976),

2.1 Classification of Ice-Dammed Lakes Tweed and Russell (1999) developed a classification of the different types of ice-dammed lakes (Fig. 2) considering the spatial relation of the water body to the ice and potential jökulhlaup routings. Previous classifications by Hutchinson (1957), Blachut and Ballantyne (1976), and Costa and Schuster (1988) are considered and developed further. The nine different types of ice-dammed lakes illustrated in Figure 2, their characteristics, drainage triggers, and routing characteristics are listed in Table 1. This kind of classification is followed by further details on the relation of ponded water and ice by, for example, considering if supraglacial lakes are located at nunataks or crevasses or if marginal ponding occurs on ice or land (Blachut and Ballantyne, 1976). Blachut and Ballantyne also developed a numerical classification for computer databases. Routing characteristics obviously depend on the type of lake at local topographical and glaciological conditions. The drainage

Figure 2. Ice-dammed lake topographic settings and potential jökulhlaup routing (modified after Tweed and Russell, 1999, Fig. 2a therein). Compare Table 1 for characteristics of the different types marked by capital letters.

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itself can be a relatively slow continuous process or an abrupt event, depending on the outburst mechanism, which is only partly characteristic for individual types of lakes.

•

2.2 Mode of Drainage and Outburst Mechanisms Ice-dammed lakes will start to drain if critical thresholds depending on the lake topography and ice conditions are reached. Drainage is triggered by different processes that are interrelated with water escape routes, and therefore difficult to distinguish. Previous studies revealed eight drainage processes with related triggers (Tweed and Russell, 1999, p. 87f.): • Subglacial volcanic activity is a dominant trigger for the formation of subglacial water bodies, characteristically draining by flotation of the glacier cover or generating or enlarging sub- and englacial conduits especially by raised water temperature. The tremor related to volcanic activity disrupts the glacier and increases the number of possible routings by fracturing the ice. This is a typical formation process of jökulhlaups in Iceland (Björnsson, 1992), well studied, for example, during the 1996 outburst of Grimsvötn below Vatnajökull (e.g., Gudmundsson et al., 1997). During this event, supraglacial outburst at the glacier surface is observed at ice fractures (Roberts et al., 2000, 2002; Waller et al., 2001). • Seismic activity is assumed to trigger outburst floods by weakening the ice dam of a previously developed lake. On the other hand, no occurrence of jökulhlaups triggered by earthquakes is documented. For example, the magnitude 7 earthquake in Alaska in 1964 did not influence the stability of the ice dams damming more than 700 lakes in Alaska (Post, 1967; Post and Mayo, 1971).

•

•

Ice-dammed lakes will drain by overspill if either the ice dam height or the lowest topographic control is reached by rising lake-water level. If overspill occurs at the ice dam itself, draining lake water will rapidly incise into the glacier surface and form a continuously enlarging spillway, giving a large outburst flood. If a rising water level reaches the elevation of the topographic control point, drainage will start slowly, and any further inflow might be released this way without any large flood event. The Glen mechanism proposes an ice-dammed lake drainage initiation mechanism that depends on the depth of the lake (Glen, 1954). At a depth y of water, the horizontal stress component on the wall of the ice dam exceeds the vertical stress by an amount of pressure p = (ρw – ρi) g × y, where ρi is density of ice, ρw density of water, and g acceleration of gravity. It is argued that at a lake depth of ~200 m, the hydrostatic pressure of the water exerted on the dam is sufficient to begin to force a hole through the ice by plastic deformation. Once formed, this hole will enlarge by frictional melt widening, and the lake begins to drain. In practice, several ice-dammed lakes, which did not drain, are observed at this critical depth of water. A main problem seems to be the time necessary for a deformation of the moving glacier to weaken the ice dam (Listol, 1956, p. 123; Stenborg, 1969, p. 37). Hence, the Glen mechanism appears to be a more theoretical attempt that has hardly ever been observed under natural conditions. Ice dam flotation will occur if the lake depth exceeds 90% of the height of the ice dam, due to the difference in density of water and ice. Drainage is dominantly subglacial with tunnel-widening processes enhancing drainage and maintaining a route.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Flotation processes additionally depend on the density of the ice dam, which might be decreased by crevasses or increased by considerable amounts of debris. If the ice dam is frozen to its bed, no flotation might occur. Also, friction of ice to the adjacent valley slopes could be a stress, decreasing the possibility of uplift of the glacier. Due to the mentioned factors of influence, flotation is rarely found to happen when the depth of lake reaches the 90% threshold (Tweed and Russell, 1999, p. 92). • The water of the lake might be connected with englacial drainage conduits within the ice dam. If the pressure within these conduits decreases, for example, by the end of the ablation season, the englacial drainage systems will get in function to drain the lake. This process is called siphoning. An outburst event is hardly ever caused by this effect, but if considerable melt widening occurred, the discharge through the ice dam might increase rapidly. • Subglacial cavity formation might happen if the tensile stress due to the speed of ice flow around an obstacle at the glacier bed exceeds the ability of the ice to close the cavity in response to normal or cryostatic pressure. Decreasing flow velocity of the ice or increasing thickness closes the cavities again. It is suggested by Knight and Tweed (1991) that periodic cavity formation caused by fluctuations of glacier movement velocity may be responsible for triggering ice-dammed lake drainage. • Subaerial dam breaches are common in recent icedammed lakes in the Swiss Alps (Haeberli, 1983). Typically, the initial breach occurs at the ice-rock contact at the valley slopes and enlarges by frictional melting similar to melt widening at en- and subglacial conduits. Ice dam breaches result in the largest jökulhlaups, and they differ in magnitudes from most other drainage processes. The prediction of the dynamics of ice dam failure and related drainage is a difficult task as several threshold conditions must kept stable. For instance, melt widening of englacial conduits can be compensated by internal ice movement if the current decreases during drainage due to sinking lake-water level. Also, a combination of triggers and drainage processes appears realistic and might even change during a drainage event. Initial overspill of the ice dam would lead to incision into the barrier that thins and finally might fail completely in the form of a subaerial breach. Also, initial piping through the ice dam is observed being followed by subaerial breach, which is caused by the failure of the enlarging conduit’s roof (Heinsheimer, 1954, 1958). Depending on the regional background and dimensions of outburst floods, some of the processes listed above are described as uncommon or rare in previous studies. For example, controversial discussions came up on the question whether outburst events are related to the season of the year. The more general review presented here reveals that this depends on additional regional aspects. If an ice-dammed lake is fed by meltwater accumulating in spring and summer, water pressure of the lake

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against the ice dam will increase at this time and a sequence of repeat outburst events will show most frequent occurrence in summertime (e.g., Tulsequah Lake in Canada; Host and Dorava, 1999). Ice-dammed lake formation and drainage is obviously independent of seasons if caused by volcanic activity. 2.3 Hydrographs of Jökulhlaups Depending on the drainage process, wide variations of jökulhlaups can be observed. The “usual” appearance is one in which flow increases to peak discharge on a steeply rising limb, representing progressive enlargement of ice tunnels by flowing water. For subaerial breach outbursts, the rise is considerably faster than for en- or subglacial drainage. The broad variety of ice-dammed lake settings, dam configurations, drainage triggers, and water routings leads to a diversity of drainage-related hydrographs lasting for hours up to months (Fig. 3). The ideal type of a jökulhlaup hydrograph could undergo modifications by temporary blockage of the drainage conduits or pathway of the flood by truncated icebergs in narrow valleys downstream of the ice dam (Richardson, 1968a). Drainage of supraglacial lakes through subglacial conduits results usually in less steep hydrographs and may be unnoticed if added to a relatively large meltwater release of the glacier. Comparable long-lasting drainage is also typical for lakes dammed by large ice shields, where the sub- and englacial system of conduits is more complex. Subglacial caldera lakes are short-lasting events. Their difference in water temperature influences the speed of enlargement of the glacial drainage system. Subglacial volcanic eruptions release water depending on the melting rate in direct relation to the frequency of volcanic activity. Empirical relations between peak and mean discharge given by Desloges et al. (1989) illustrate difficulties to generally characterize the hydrograph of jökulhlaups, as the determined ratios of Qmax/Qmean vary between 2 and 6. Usually, ice-dammed lake outburst floods occur repeatedly by the rebuild of the ice dam and the refill of the lake. After a drainage event, the en- or subglacial conduits and cavities close due to the ice movement or the glacier extending over the volcano. Also, after overspill drainage or subaerial breach the ice barrier rebuilds if changed climate conditions do not prevent this. Dependent on local conditions, recurrence intervals vary from one year (e.g., Tulsequah Lake; Host and Dorava, 1999) to decades (e.g., Grimsvötn; Björnsson, 1992) to centuries for large ice-dammed lakes of Pleistocene times. 2.4 Occurrence and Distribution Jökulhlaups are found on all continents with glaciers or glaciations throughout time. Well-known outburst floods occurred in historic and recent times in the European Alps, for example, in upper Ötztal from Vernagtferner (Patzelt, 1994; Krainer and Spieler, 1999), at Großer Aletschgletscher from Lake Märjelen

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Figure 3. Hydrograph types for ice-dammed lake drainage (modified after Tweed and Russell, 1999, Fig. 2c therein).

(Lütschg, 1915), and several other glaciers in Switzerland (Haeberli, 1983; Johnson, 1997). Other current events are known from: • Norway (Listol, 1956; Elvehoy et al., 2002) • Spitzbergen (Schöner and Schöner, 1997) • Iceland (Björnsson, 1992; Tomasson, 2002) • Greenland (Scholz et al., 1988) • Canadian Arctic (Maag, 1969) • Alaska (Post and Mayo, 1971; Mayo, 1989) • Canada (Clague and Evans, 1994, 2000) • Cascade Range (Walder and Driedger, 1994) • South America (Bruce et al., 1987) • Nepal (Fushimi et al., 1985; Mool, 1995) • Bhutan (Richardson and Reynolds, 2000) • Karakoram (Hewitt, 1982; Xiagsong, 1992) • Tien Shan (Jinshi, 1992) • Antarctica (Goodwin, 1988) This list of references is far from being complete. A similar distribution is found for Pleistocene ice-dammed lakes at the Laurentide Ice Shield (Teller and Kehew, 1994), with Lake Agassiz (Teller and Clayton, 1983; Teller et al., 2002), Lake Souris (e.g., Lord, 1991), Lake Wisconsin (Clayton and Attig, 1989),

and Lake Missoula (Baker and Bunker, 1985) as most prominent examples. Pleistocene outburst floods by dam failure are also described from Scandinavia (Elfström, 1987), the Hindukush Mountains (Cornwell, 1998), Siberia (Grosswald and Rudoy, 1996), and the Altai Mountains (Butvilovsky, 1993; Rudoy, 1998, 2002; Carling et al., 2002). Pleistocene ice-dammed lakes drained by spillways are, for example, the Baltic Sea (Strömberg, 1992; Brunnberg, 1995), the continental-scale lake(s) in Siberia (Arkhipov et al., 1995; Grosswald, 1998, 1999), and local lakes along the Laurentide Ice Shield (e.g., Kehew and Lord, 1987) or at the margin of the Scandinavian Ice Shield (Thome, 1983; Klostermann, 1992; Herget, 2002). From several other Pleistocene glaciations the occurrence of ice-dammed lakes is evident, but the drainage process is unknown or not the subject of the investigation, for example, in Siberia (Mangerud et al., 2001), Scotland (Benn, 1989; Gordon, 1993; Brazier et al., 1999), or Germany (Müller, 1964; Gassert, 1975; Pilger, 1991; Schlaak, 1993; Junge, 1998). In some studies, Pleistocene ice-dammed lake outburst floods are assumed to have caused geomorphological structures such as the British Channel (Smith, 1985) or forms previously interpreted as drumlins (Shaw, 1989; Rains et al., 1993; Shaw

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia et al., 2000). Suggestions are made to explain the occurrence of Heinrich events by subglacial outburst floods (Johnson and Lauritzen, 1995) or the potential influence of large-scale events on ocean currents and climate (Shoemaker, 1991, 1992). Those interpretations are a subject of current discussions (e.g., Walder, 1994; Baker, 2002; Teller et al., 2002). Among the best-studied Pleistocene jökulhlaups are those from Lake Missoula, located in the northwestern United States (Baker, 1973a, 1973b; Baker and Nummedal, 1978; Baker and Bunker, 1985; Allen et al., 1991; Alt, 2001). This event is frequently compared with the outburst floods in the Altai Mountains (Baker, 1997, 2001, 2002; Butvilovsky, 1993; Carling et al., 2002; Rudoy, 1998, 2002); hence a brief description based on the previously mentioned references is given to get an impression of what might be the expected characteristics of the jökulhlaups in the Altai Mountains. During the last glaciation a lobe of the Laurentide Ice Shield in the northwestern United States blocked the course of Clark Fork River in western Montana and caused the generation of an ice-dammed lake, named after the city of Missoula located within the previous lake basin. The maximum lake level was at an elevation of 1265 m. The lake volume reached >2100 km3 of water. During the maximum stage the lake depth at the dam was 635 m. Ca. 16–12 ka, repeated outburst floods occurred, flooding extended areas of eastern Washington and draining through

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a complex network of channels along the Columbia River valley toward the Pacific Ocean (Fig. 4). Peak discharges of the outburst flood are estimated as 17 ± 3 million m3/s for the area near the dam around Spokane, while downstream at Wallula Gap a value of 10 ± 2.5 million m3/s was determined using hydraulic calculations (O’Connor and Baker, 1992). The duration is estimated to have been on the order of days (O’Connor and Baker, 1992). The exact number of floods is still a subject of discussion on the validity of evidence. While Waitt (1980, 1985) interprets stacked rhythms of sediments as an indicator for at least 40 separate outburst floods from Lake Missoula, for example, Baker and Bunker (1985) doubt this and draw attention to the unverified assumptions for this scenario. Considering varying routings of the outburst floods, the estimated number of jökulhlaups increases up to ~100 separate last-glacial events with peak discharges reaching locally perhaps 25–30 × 106 m3/s (Waitt et al., 2000). Investigations on the magnetic polarity of deposits along the pathway of the Lake Missoula flood in southeastern Washington reveal evidence for even Early Pleistocene giant floods, which is assumed as an indicator of hundreds of jökulhlaups in the area during the entire Pleistocene (Bjornstad et al., 2001). Traces of outburst floods reaching the Pacific Ocean from the mouth of Columbia River are found even 1100 km away from the coastline with ages as old as 32 ka (Zuffa et al., 2000).

Figure 4. Location of the Pleistocene Lake Missoula flood in the northwestern United States (modified after Baker and Bunker, 1985, Fig. 1 therein). Lake Bonneville, located in Utah, was a Pleistocene lake that filled the tectonic basin of the current Salt Lake. The lake drained by overspill of an alluvial fan at Red Rock Pass and caused a single flood along Snake and Columbia Rivers with a peak discharge of ~106 m3/s (O’Connor, 1993).

Geological Society of America Special Paper 386 2005

Chapter 3 ALTAI MOUNTAINS

Basins, are studied. The downstream end in Katun valley is given by a gorge section of Katun River, which limits access to the river upstream of Chemal. Kuray Range in the north of Kuray and Chuja Basins reaches heights of up to 3446 m. South of the basins, Northern and Southern Chuja Ranges are located with peaks of up to 4177 m. Both ranges are glaciated today. In Kuray Range, only local cirque glaciers north of the village of Aktash exposed to the north are still active, while in Northern and Southern Chuja Ranges extended valley glaciers exist. For the entire Altai Mountains the current ice coverage is ~909 km2 (Carling et al., 2002, p. 19). North of Inja village mountain peaks only occasionally reach an altitude of 2500 m. The highest mountain of the Siberian Altai Mountains is Mount Belucha located in the upper Katun catchment with a summit at 4506 m. The mean slope of Katun River today is ~2‰ around Inja village, which is located at an elevation of 765 m. In comparison, Chuja valley is much steeper with a mean slope >6‰ until a first decrease is reached in the area around Aktash at an elevation of 1140 m. A narrow steep gorge section separates the through-valley area around Aktash from Kuray Basin, located at an elevation between 1480 and 1570 m. Up to the outlet of Chuja Basin at ~1724 m another moderately steep reach follows. Chuja Basin itself is tilted and reaches an elevation of the bottom of the basin at the eastern part of nearly 2000 m near the village of Tashanta. The geological structure of the Altai Mountains is very complex, due to intense tectonic activity from Late Paleozoic to Cenozoic times. Different periods of activity can be distinguished in relation to plate tectonics indicating the decay of a Paleoasian ocean (Buslov et al., 1993), but is also influenced by the collision

In the following chapter, a brief review on the area of investigation is given. A focus is laid on aspects of relevance for the subject of Pleistocene ice-dammed lake outburst floods. For comparison with Pleistocene conditions, some information about current climate is given. The origin of the name “Altai” is not finally clear. It could either be based on Turk languages with the meaning of “high mountains” or be derived from the Mongolian word “Altyn” with the meaning of “six,” possibly “six mountains” (Bussemer, 1999, p. 14). A problem is the varying transliteration, changing with time and languages (Selegei, 2001). 3.1 Location and Geology The area of investigation is located in the Siberian Altai Mountains in southwestern Siberia, close to the borders to Kazakhstan, Mongolia, and a small part also to China (Fig. 5). The mountain range stretches between 85°–90° E and 49°–52° N and extends 1700 km farther to the southeast toward Mongolia, where the name changes to Mongolian Altai and Gobi Altai. At the confluence of the Rivers Bija and Katun near the city of Bijsk, the rivers form the River Ob. The headwaters of both rivers are located in the Altai Mountains, where their watersheds mark the border to the neighboring states (Fig. 6). Particularly the valleys of the lower Katun and Chuja Rivers are investigated. From downstream of Inja village up to the headwaters of Chuja River, the traces of outburst floods from icedammed lakes, formed in Pleistocene times in Kuray and Chuja

Figure 5. Location of the area of investigation in southwestern Siberia.

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Figure 6. Catchments of Katun and Bija Rivers in the Altai Mountains.

Figure 7. Scheme of geological complexes of the Altai Mountains and adjacent areas (simplified after Berzin and Kungurtsev, 1996, Fig. 1 therein). 1—platforms (a—basement, b—sedimentary); 2—continental rifts; 3—passive margins; 4—oceanic (a—ophiolites, b—oceanic islands and uplifts with silica-carbonate cover, c—deepwater volcanic-sedimentary); 5–8—subductions of island arcs and backarc basins; 9—active continental margins (a—volcanogenic-sedimentary, b—intrusive); 10—anatectic granitoids and granite-gneiss domes; 11—molasse (frontal and intermontane); 12—superimposed depositional troughs; 13—flood basalts; 14—faults (a—over- and underthrusts, b—strike-slip faults, c—others).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia of the Indian and Eurasian plates (Delvaux et al., 1995). For the Altai Mountains and adjacent areas, the modern mosaic-block structure is illustrated by Figure 7. This complex pattern of geological complexes even increases by consideration of different ages and petrology of bedrock. Along the area of investigation along Katun and Chuja valleys, this can be illustrated by Figure 8. As illustrated in Figure 8, rocks of Lower Paleozoic age are most dominant. Their characteristic green-magenta color influences the peculiar appearance of the landscape. The rise of the Altai Mountains started in the Middle Tertiary by reactivating the complex pattern of the Paleozoic faults, resulting in a graben and horst structure, for example, in upper Chuja valley (Buslov et al., 1999). Also, several extended plateau areas in different elevations have developed, seldom found as frequently as in the Altai Mountains (Franz, 1973, p. 341). Kuray and Chuja Basins are tectonically initiated depressions, which are filled with sediments up to more than 1000 m (Delvaux et al., 1995). The total vertical relative movement is ~2500 m. The upper parts of the sediment accumulation were investigated in detail by Bojarskaja et al. (1978), who dated several samples up to the depth of 210 m.

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Ages older than 1000 ka could be determined by luminescence dating and paleomagnetics. Tectonic activity continues until today as revealed by investigations of Novikov et al. (1998), who found that frequent earthquakes with magnitudes of up to 7.0 in upper Chuja Basin (Zhalkovskii et al., 1998; Zhang et al., 1999) are responsible for widespread landsliding in this area. However, landslides can also be caused by permafrost decay, observed in some locations along Chagan-Uzun valley. Additional information on the geomorphology and bedrock geology is given by, for example, Nechorosev (1966), Protsyuk (1978), Chernov et al. (1988), Aplonov (1995), and Selegei et al. (2001). 3.2 Current Climate For Kosh-Agach village, located in Chuja Basin, climate parameters are presented in Figure 9, clearly showing the continental characteristics of the climate. Measured data for temperature and precipitation also serve as a basis for estimations of Pleistocene climatic conditions. Additionally, the general continental climate of this part of Central Asia is responsible for these extreme conditions.

Figure 8. Geological sketch map along Katun and Chuja Rivers (simplified after Buslov et al., 1993, Fig. 6 therein). 1—Neogene/Quaternary sediments; 2—sandstone, mudstone, limestone (C); 3—basalt, tuff (D); 4—dacite, andesite, tuff (D); 5—basalt. rhyolite, limestone, mudstone, conglomerate (D); 6—intrusions (granodiorite, diorite) (D); 8—limestone, mudstone (S); 9—sandstone, mudstone, marl (O); 10—conglomerates, sandstones (O); 11—granite-gneiss dome; 12—granite-gneiss dome; 13—flysch (C); 16—olistostrome (C); 17—paleoguyots (C); 20—basalt, tuff (C); 21—basalt (C); 22—schists (C); 23—basalt, tuff (C); 24—layered gabbro-pyroxenite; 25—granite (C–P); 26—faults and thrusts; 27—thrusts; 28—road (Chujska Tract) with C—Carboniferous, D—Devonian, O—Ordovician, P—Permian, S—Silurian.

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Figure 9. Temperature and precipitation in Kosh-Agach. Precipitation data are provided by EOS (2000) from a database from various Russian sources. Years with missing data for individual months are left out; hence the number of years with monthly precipitation data is reduced to n = 44. Temperature data are taken from Gidrometeorologitcheskoe Izdatelstvo (1970). The extreme values are taken from tables on a daily basis, while the mean temperature are mean monthly values over 15 yr.

The mean annual temperature for Kosh-Agach is –6.0 °C, and the mean annual precipitation for the period of observation is 117 mm. These values are confirmed by review maps of the climate of the Altai Mountains by Protsyuk (1978, p. 60f.). These climatic conditions—rather low mean annual air temperature and

very dry conditions—can partly be explained by the topography of the location of Kosh-Agach. It is situated in the center of Chuja Basin surrounded by high mountain ranges. Even along the crests of Northern and Southern Chuja Ranges, the annual amount of precipitation is <800 mm (Fig. 10). As illustrated in Figure 10, moisture usually transported by winds from the west direction leads to higher annual precipitation in the mountain ranges west of Chuja River catchment, which is indicated by annual amounts >1000 mm, locally reaching up to 1500 mm (Franz, 1973, p. 344). Recent investigations obtained values of 800–1000 mm for the Southern Chuja Range, measured by snow deposition in high mountain areas (P. Borodavko, 2002, personal commun.). The extreme cold winter temperatures are a result of cold air accumulating within Chuja and Kuray Basins. This leads to the development of discontinuous permafrost in the area, which is indicated by palsa, pingos, and small-scale polygon structures in fine-grained soils in the entire Chuja catchment upstream of the Aktash area (cf., e.g., Krivonosov, 1978). 3.3 Quaternary of the Altai Mountains

Figure 10. Annual precipitation in the Altai Mountains (modified after Protsyuk, 1978, p. 66).

The focus of the following chapter is laid on the last glaciation because for the Altai Mountains, it is not clear how many glacial cycles occurred (after Okishev from Carling et al., 2002, p. 19). Terminology of glaciations, interglacial stages, and especially stadials varies a lot, from local expressions named after rivers in the Altai Mountains (Franz, 1973, Table 60 therein, after various Russian sources), to expressions for western Siberia (Arkhipov, 1984) which are changed through time (Arkhipov, 1998). The discussion about a universal nomenclature is

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

characterized as traditional by Arkhipov (1998, p. 29), who gives an overview of the stratigraphy of the Late Pleistocene of western Siberia (Table 2). According to Arkhipov (1998), the last glaciation can be related to the Weichselian/Würmian Glaciation of Central Europe and the Wisconsin Glaciation of North America. This Zyryanka Glaciation consists of two independent glaciations. Evidence for the differentiation is mainly based on lacustrine sediments and paleosoils for the Karginian Interstadial and ice-dammed lake sediments and alluvial deposits for the stadials. Due to missing dated deposits, the limit between Karginian Interstadial and Ermakovo Glaciation is not distinct (Table 2). The beginning of the Holocene warming is set on the established level at 10 ka. As characteristic for high mountain areas, the actual warming occurred later in higher elevations. Blyakharchuk et al. (2001) found the warming indicated by initial growth of Pinus sibirica at 8220 ± 65 yr B.P. at an altitude of 1985 m at Uzun Kol, ~20 km north of Aktash.

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A large discrepancy exists on the question of the maximum extension of the glaciation in the Altai Mountains during the Last Glacial Maximum (LGM). Bussemer (2001) compares the findings of five different authors (Fig. 11). The descriptions vary between a more or less extended valley glaciation up to a nearly complete ice coverage of the area. All authors agree that glaciation did not occur in Chuja Basin. Rudoy (1998, 2002) assumes an extension of the glaciation even north of Gorno-Altajsk (Fig. 15). According to Svitoch and Khorev (1978, p. 170), Ermakovo Glaciation was the maximum glaciation in the Altai Mountains in the last 500 k.y., when the glaciers even reached the low mountain areas between 100 ka and ca. 60 ka. The different theories on ice sheet extensions are of importance for the dimension of the ice dam assumed to have blocked the flow of Chuja River downstream of Kuray Basin. Additional details on this aspect are given in Chapter 4 on evidence of the jökulhlaups along Chuja and Katun valleys. For an estimation of last glacial climate conditions, several investigations were carried out in the Altai Mountains and adjacent areas. Last Glacial Maximum climate reconstructions for the territory of the former Soviet Union and Mongolia (Frenzel et al., 1992; Tarasov et al., 1999) show a difference from current conditions of –10 °C for mean winter temperature and –4 °C for summer temperature. The amount of annual precipitation decreased by ~300 mm (Tarasov et al., 1999) to 100 mm, respectively (Frenzel et al., 1992). Grunert et al. (2000) investigated the water balance of endoreic lakes in Uvs Nuur Basin in western Mongolia close to the Siberian Altai Mountains for the last glacial and Holocene. They found characteristic dry and cold climate conditions during the LGM followed by a wetter period during the late

Figure 11. Comparison of the extension of glaciation at the Last Glacial Maximum in the Altai Mountains according to different authors (modified after Bussemer, 2001, Fig. 2 therein). Considered are descriptions by Bogachkin (1981), Okishev (1982), Protsyuk (1978), and Butvilovsky (1993).

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glacial. For western Kazakhstan located east of the Altai Mountains, Kremenetski et al. (1997) determine a similar amount of annual precipitation as today and confirm the estimations by Grunert et al. (2000) for late glacial climate conditions. Estimations of the snowline depression resulting from changed climate conditions show a relatively large range of values (Table 3). The range of values estimated might be explained by the different methods applied. Additionally, the diversity is influenced by the aspect of the glaciers. Okishev (1982, p. 110) found a difference of elevations of snowlines of 1000 m depending on the individual mountain range within the Altai Mountains and the local aspect. The following estimations for the Altai Mountains result from further climate calculations based on snowline depression: A decrease of snowline altitude of 100 m needs an increased amount of precipitation of 180 mm for unmodified temperature conditions, while for summer temperature a value of –0.6 °C is needed to achieve a similar depression for constant precipitation (after Tronov from P. Borodavko, 2002, personal commun.). A computer simulation of a coupled atmosphere-ocean general circulation model (Bush and Philander, 1999) provides additional information about the climate conditions of the Last Glacial Maximum. On this continental-scale model, the mean annual near-surface temperature during the LGM for the area of Altai Mountains is estimated to have been 8 °C less than today (Bush and Philander, 1999, Fig. 3 therein), a value in a corresponding magnitude to the values for deviations from current values for winter and summer temperatures after Tarasov et al. (1999) mentioned above. Furthermore, Bush and Philander (1999, Fig. 11 therein) found a west wind direction as dominant for the LGM, with

lower mean velocity compared to present-day conditions. This result of their modeling is in contradiction to the traditional concept of a cold anticyclone over Central Asia so that the prevailing winds came from northern to northeastern directions (Velichko, 1984). Further details on regional characteristics of the Pleistocene in the Altai Mountains are given, for example, by Okishev (1982), Butvilovsky (1993), and Carling et al. (2002). Other authors present more general aspects such as the onset of Late Pleistocene glaciation (Galabala, 1997; Karabanov et al., 1998), dated loess deposits at adjacent areas (e.g., Frechen and Yamskikh, 1999), or Paleolithic occupation of the Altai Mountains by man (e.g., Christian, 1998; Clark et al., 1990). Note that the outburst floods from ice-dammed lakes in the Altai Mountains are not related to the continental-scale icedammed lakes of Siberian streams during the Pleistocene by ice sheet cover of the river’s mouth at the Arctic Ocean (e.g., Arkhipov et al., 1995; Grosswald, 1999; Mangerud et al., 2001), even if those lakes are assumed to have extended temporarily upstream along Ob River up to the confluence of Bija and Katun Rivers (Arkhipov et al., 1995, Fig. 4 therein). Recently this scenario has been considered as completely or partly critical by several investigations (e.g., Sher, 1995; Larsen et al., 1999; Georgiadi, 2000).

Geological Society of America Special Paper 386 2005

Chapter 4 EVIDENCE OF JÖKULHLAUPS IN THE ALTAI MOUNTAINS

4.1 Previous Studies and Reviews Among the first reviews on ice-dammed lakes in the Altai Mountains are the publications by Popov (1967) and Deviatkin (1965). While Deviatkin (1965) focuses on Chuja and Kuray Basins, Popov (1967) gives a review of moraine-dammed and ice-dammed lakes of most parts of the upper Katun catchment including Chuja valley. The fundamental digest of the Quaternary of the Altai Mountains by Okishev (1982) is the first source of a more detailed analysis of lake sediments, for example, in Chuja Basin. Okishev’s previous students Butvilovsky and Rudoy deal with the question where the water of the former lake has gone and propagated outburst floods. Summaries of their investigations are given by Butvilovsky (1993) and Rudoy (1998, 2002). After several years of geological mapping, Butvilovsky (1993) summarized his findings in an overview map on ice-dammed lakes and outburst floods in the Altai Mountains and surroundings (Fig. 14).

The subject of the present study is the hydraulic reconstruction of the outburst flood, derived from currently known and validated related features along Chuja and Katun valleys. Hence, aspects of mainly regional interest are of minor importance for this study. Further detailed information is provided by the selected references. A review of the locations of the main jökulhlaup indicators is given by maps of the area of the ice-dammed lakes in Chuja and Kuray Basins (Fig. 12) and the first part of the flood’s pathway along Chuja and Katun valleys down to the confluence of Big Ilgumen and Katun Rivers (Fig. 13). Those maps give an overview for orientation. A more detailed description is presented in the following subchapters and partly in the presentation of the analyzed sediments and forms in the subchapters on methods and results of the reconstruction of jökulhlaups (Chapter 5).

Figure 12. Overview map of the former ice-dammed lake in Chuja and Kuray Basins.

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Figure 13. Overview map of the pathway of the jökulhlaups along Chuja and Katun valleys.

Figure 14. Sketch map of the paleogeographical situation in the Altai Mountains and surrounding areas during the last glaciation (modified after a sketch by Butvilovsky, unpublished).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Figure 14 is a simplified version of a larger-scale map by Butvilovsky (1993), where several additional details are mentioned. Within the Altai Mountains, numerous ice-dammed lakes are postulated, and the lake in Chuja and Kuray Basins (approximately 50° N, 88° E) is one among several others. The pathway of the outburst floods toward the West Siberian Plain becomes part of a continental-scale concept of the drainage during the last glaciation. Partly based on the map by Butvilovsky (1993), Rudoy focused his own investigations on the central part of the Altai Mountains. His results are also summarized in an overview map (Fig. 15). As opposed to Butvilovsky’s (1993) generalized overview, Rudoy (2002) focuses on the time close to the end of the last glaciation ~14,000 yr B.P. Comparing the two maps, the amount and extension of ice-dammed lakes is less according to Rudoy. However, in Figure 15 the glaciers extend down into lower Katun and Bija valleys indicating an ice sheet glaciation for the Last Glacial Maximum (LGM), while in Figure 14 a dominant valley glaciation is shown by generalizing the entire last glaciation. Both authors focus obviously on comparing the outburst floods in the Altai Mountains with the well-known Lake Missoula flood

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(e.g., Baker and Bunker, 1985). They introduced several special expressions from the Lake Missoula flood into the Russian language and gave various examples for outburst flood features found in the Altai Mountains that should strengthen the similarity of Missoula and Altai jökulhlaups. Details are discussed in the following chapters. Doubts on the reliability of the reports by Butvilovsky (1993) and Rudoy (1998, 2002) comes up as the evidence of some features cannot be confirmed by independent investigations or evidence for their interpretations is missing (e.g., Carling et al., 2002, p. 20; Okishev, 1999, p. 76; P. Borodavko and S. Parnachov, 2002, personal commun.; and results of own investigations). For the jökulhlaups along Chuja and Katun valleys, several aspects are discussed in subsequent chapters. Initiated by international contacts by Rudoy, first reviews and preliminary results of detailed investigations are given by western scientists (e.g., Baker et al., 1993; Rudoy and Baker, 1993; Carling, 1996a, 1996b; Carling et al., 2002). Their findings are documented and discussed in detail in different chapters throughout this report. Due to limited access to previous studies by other Russian scientists, mainly reviews by Rudoy are quoted in the form of variants of Figure 15.

Figure 15. Paleoglaciohydrologic sketch of the Altai Mountains ca. 14 ka (modified after Rudoy, 2002, Fig. 2 therein). 1—boundary of glacier complex; 2— probable limit of ice spread at the Last Glacial Maximum; 3—ice-dammed lakes; 4—spillways; 5—gravel dunes; 6—direction of outburst floods; 7—maximum lake boundaries; 8—locations of largest Diluvial terraces and ramparts (giant bars); 9—modern glaciers; 10— “dry” waterfalls. Numbers in the map are for names of individual ice-dammed lakes: 1—Chuja Lake; 2—Kuray Lake; 3—Uimon Lake; 4—Jaloman Lake; 5— Ulagan Lake; 6—Teletskoye Lake; 7— Julukul Lake; 8—Jassater Lake; 9— Tarkhat Lake; 10—Bertek Lake; 11— Abay Lake; 12—Kane Lake.

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This brief review cannot give a complete overview on all previous studies on the features currently interpreted as belonging to the outburst floods. Older Russian studies especially have a limited availability. Hence, for the history of research on the subject, the reader is referred to the review papers previously mentioned and the detailed investigations listed below. 4.2 Flood-Related Features 4.2.1 Lake Sediments and Shorelines Evidence for Pleistocene lakes in Chuja and Kuray Basins is given by lacustrine sediments and extended areas of shorelines along the slopes of the basins. Secondary lakes generated by the blockage of tributary valleys along Chuja and Katun valleys are described separately. Exposures of lake sediments along Chagan-Uzun valley in Chuja Basin are the subject of detailed investigations by Okishev (1982), Okishev et al. (1978), Borodavko (1999), and Okishev and Borodavko (2001a, 2001b). They found altogether 4740 varves of a thickness between 6 mm and 60 mm for summer layers and 1–13 mm for winter layers. The thickness is interpreted as an indicator for varying water depth and water supply. The sediments are poor in pollen, and the few local findings are considered as reworked or transported from different areas (B. Ammann, 2001, written commun.). The drainage of the lake by outburst floods did not leave any traces in the investigated lake sediments, which is considered an argument against outburst floods of the lakes in general. Near the village of Beltir, two individual units of varves can be divided with ages of 25.3 ± 0.6 ka (MGU IOAN-65, radiocarbon) and older than ca. 45 ka (Beta 147107, radiocarbon). They are separated by a layer of glaciofluvial sediments and deposited on top of a moraine of an age of 58 ± 6.7 ka (MGU-KTL-93, thermoluminescence on feldspar) (Fig. 16). For Kuray Basin, Rudoy (2002, p. 138) assumes a final drainage before 10,845 ± 80 yr B.P. (CO AH-2346, radiocarbon). This assumption is based on dated vegetation remnants from soil development in lake bottom sediments in western Kuray Basin at an elevation of ~1800 m.

Among the first detailed descriptions of shorelines in Chuja and Kuray Basins are the articles by Popov (1962, 1967). For the shorelines located at the southeastern margin of Kuray Basin, Popov (1962, p. 81f.) mentions lateral extensions of several kilometers and vertical spans of 200–220 m. Typical vertical distances between the dozens of shorelines for different locations vary between 1 and 8 m and only occasionally reach higher values. Unfortunately, due to intensive cultivations in parts of Kuray Basin since the investigations by Popov (1962), the shorelines are today not as distinctive as documented by him. Comparable investigations are carried out in Chuja Basin, where Okishev and Borodavko (2001a) found 34 shorelines extending over a vertical distance of nearly 200 m. Characteristic vertical distances are 2–5 m. The highest shoreline is found at an altitude of 2100 m (Okishev, 1999, p. 81; Carling et al., 2002, p. 22). Rudoy (2002, p. 130) and gives an unconfirmed value of 2200 m. This elevation limits the maximum depth of a lake to 650 m and allows estimations of the extension and volume of the ice-dammed lake in the connected Chuja and Kuray Basins. According to data from topographic maps, the area covered by the lake during the maximum stage can be estimated as 2633 km2 (Fig. 17) with a related maximum volume of 607 km3 (Fig. 18). These values are similar to those given by Okishev and Borodavko (2001a) (Amax = 2653 km2, Vmax = 594 km3) but are considerably less than those of Rudoy (1998, 2002). The latter merges assumed data for an Early Pleistocene ice-dammed lake in the area with late glacial field evidence (cf. Rudoy and Baker, 1993, p. 54). Studies on shorelines at the southeastern margin of Chuja Basin near triangulation point 2137 reveal decimeter-thick units of poorly sorted, angular, pebble gravels interspersed with lenses of fine sand several centimeters thick (Carling et al., 2002, p. 22f.). The lowest shoreline is radiocarbon dated as 32,190 ± 260 yr B.P. (after Moody from Carling et al., 2002, p. 23). Strandlines on the 58 ka moraine in Chagan-Uzun valley (Fig. 16) reveal another estimation for the age of the lake (Popov, 1962; Okishev et al., 1978). In addition, the number of shorelines at different altitudes indicates fluctuations of the lake level and several pre- and postlake glacier oscillations in

Figure 16. Sketch of cross section of Chagan-Uzun valley near Beltir with two units of dated lake sediments (modified from Okishev and Borodavko, 2001b, Fig. 2 therein). 1—current river sediments; 2—younger lake sediments; 3—older lake sediments; 4—glaciofluvial sediments; 5—glacial deposits; 6—bedrock.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

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Figure 17. Depth-area relationship of the ice-dammed lake in Kuray and Chuja Basins.

Figure 18. Depth-volume relationship of the ice-dammed lake in Kuray and Chuja Basins.

Chagan-Uzun valley. Other locations aggravate the development of a chronology of lake stages and outburst floods at the present state of knowledge. A glacier reaching the connection between Chuja and Kuray Basins from Kuehtanar valley, for example, is assumed to have built a temporary ice dam, inhibiting a continuous development of a single lake in both valleys. The dynamics of this glacier reaching the valley bottom at an altitude of 1778 m are not studied in detail yet. Considering this aspect and based on additional unpublished dated samples and correlating them with the elevation of their location, Borodavko (2002, personal commun.) evolved a preliminary model of lake stage development from Late Pleistocene to Early Holocene (Fig. 19).

According to a hypothesis by Borodavko (2002, personal commun.), at the beginning of the first stage, the lakes in Kuray and Chuja Basins were separated until the water surface of Kuray Lake reached an elevation of nearly 1800 m, hence the location of the ice dam responsible for the lake in Chuja Basin. During the further increase of water depth, the two lakes merged. The maximum lake depth and extension was reached sometime between 45 ka and 35 ka. The first and second stage of the lake are separated by a drainage event that could be considered as a single event after a previous slow drainage until 35 ka or as several events with temporary refilling up to the levels indicated by dated lake sediments. An argument for longtime stable water

Figure 19. Hypothetical model of ice-dammed lake dynamics in Chuja and Kuray Basins (modified after P.S. Borodavko, 2002, personal commun.). The model is partly based on the elevation of dated lake sediments in Chuja and Kuray Basins.

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levels would be the above-mentioned missing disturbance of lake sediments in Chagan-Uzun village. A second maximum stage is reached ca. 25 ka with subsequent lowering of the lake level not indicated by dated elevations yet. At the end of the Pleistocene, a third stage began again with separated lakes in Kuray and Chuja Basins. The scenario of lake dynamics is based only on the evidence of dated lake sediments. Therefore, further investigations are needed to increase the sequence of dated lake levels for excluding additional drainage events in between the lake stages illustrated in Figure 19. At least the final stage is doubtless since at several locations along Chuja valley relatively young readvances of valley glaciers are indicated by moraine deposits in low elevations (Fig. 12). These sediments must have been deposited after the outburst floods; otherwise, they would have been washed out by the flood. Hence, the drainage of the last lake of Early Holocene times was not by a catastrophic event. A subject of discussion is the phenomenon of obviously tilted shorelines, especially in Chuja Basin. While in Kuray Basin a longshore tilting of ~1°–2° can be observed (Carling et al., 2002, p. 23), surveys in Chuja Basin revealed tilt angles of up to 4°. What seems strange are especially tilted shorelines running through horizontal ones as illustrated in Figure 20. All tilted shorelines are decreasing in altitude toward the northwest. An established explanation is the consideration of tectonic uplift after the development of the shorelines (after Svitoch and Khorev from Carling et al., 2002, p. 23). Crossing of tilted with more or less horizontal shorelines can be interpreted as an indicator for different generations of shorelines, but further interpretations of, for example, last and penultimate glaciation shorelines would be purely speculative at the current state of knowledge. For some locations, also depositional processes associated with the residual direction of drift could explain parts of this previously not systematically investigated phenomenon. Consideration of this aspect is of importance for reliable estimations of ice dam thickness indicated by maximum elevation of shorelines up to ~90 km east of the previous ice dam. As the tilted shorelines rise in elevation toward the southeast, a systematic

overestimation of lake depths might occur, especially for older lakes in the area (cf. Rudoy, 1998, 2002). Additional aspects mentioned in previous reviews appear hypothetical or even doubtful. For the “Jaloman Lake” postulated by Rudoy (1998, 2002) and Butvilovsky (1993) (Figs. 14 and 15) no evidence can be confirmed. The lake should have existed between the confluence of Chuja and Katun Rivers along the entire area of investigation within Katun valley down to the confluence with Kadrin River, where a glacier is supposed to have blocked Katun River. Within a lake of this extension, at least at some backwater locations, fine lacustrine sediments should have been deposited, but none have been found until present. Within the giant bar deposits, fine sediments are typically missing, except for some small locations where laminated fine sands and silts indicate local ponding (cf. chapter on giant bars and secondary lakes for details). In addition, for Uimon Lake (Fig. 14), located in the upper catchment of Katun River, evidence could not be found during preliminary investigations. Within the entire basin no shorelines are visible nor could lake sediments be found yet. Note that previously Popov (1967, Fig. 1 therein) indicated uncertainty about the existence of such a lake by a question mark. 4.2.2 Ice Dam and Failure Mechanism The exact extension during time of the ice dam responsible for the lake in Kuray and Chuja Basins is an unsolved problem for the investigations of the phenomenon. While Butvilovsky (1993) (Fig. 14) and Rudoy (1998, 2002) (Fig. 15) present an ice-covered reach of Chuja valley of ~50 km length downstream of Kuray Basin, Deviatkin (1965) (Fig. 21) introduces a concept of valley glaciation with different individual glaciers unifying in Chuja valley around Chibit and Aktash during all stages of the last glaciation. During all different Upper Pleistocene stages, valley glaciers reached the area of the ice dam from Sarulukul ice dome and additionally from Mashej and Belgebash valleys, but extended only during the upper Pleistocene maximum glaciation farther downstream along Chuja valley.

Figure 20. Tilted and horizontal shorelines in Chuja Basin. Horizontal shorelines (black arrows) are crossed by a tilted shoreline (white arrows) at central Chuja Basin southeast of Kosh-Agach.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

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Figure 21. Schematic map of Pleistocene glaciations in southeastern Altai (modified after various sources from Deviatkin, 1965, Fig. 45 therein). 1—extension of Upper Pleistocene maximum glaciation; 2—extension of first postmaximum glaciation in Upper Pleistocene; 3—extension of second postmaximum glaciation in Upper Pleistocene; 4—recent glaciation; 5—extension of Upper Pleistocene lacustrine basins; 6—ice dome centers; 7—mountain range; 8—direction of movement of glacier; 9—terminal or retreat moraine; 10—limits (a—validated, b—assumed); 11—nonglaciated areas. Names of ice domes: 1—Bertek; 2—Tarkhatin; 3—Dzhulukul; 4—Sajgonysh; 5—Ulagan; 6—Sarulukul.

The concept of the blockage of Chuja valley by extended ice sheets is described by Okivshev (1982, Fig. 1 therein) as the confluence of two lobes of ice sheets from Kuray and Northern Chuja Ranges overflowing local ranges in between and unifying with an ice thickness of ~800–850 m above the valley bottom. Only for the final degradation of the last glaciation in the Altai Mountains, Butvilovsky (1993, appended map therein) sketches a valley glacier reaching the area of Aktash from the north and spreading out through the valley and its tributaries (Fig. 14). Estimation of the related ice extension during the forming and failure of the ice dam is a difficult task even on the background of the presented previous investigations. The slopes of

the mountains and valleys around Aktash and Chibit are obviously glacially formed (partly visible in Fig. 22). An upper limit is found to be at an altitude of ~2200 m, while dense vegetation cover, a complex topography, and mass movement processes at the mountain slopes make specification difficult. The previous valley of Chuja River via Aktash was blocked by glaciers, and it might be assumed that Chuja Gorge is initialized by the outburst flood and incises further by regular current stream power. Parts of the former Chuja valley are covered by glacial and glaciofluvial deposits. Additional details and features of the previous dam site and its surroundings are not investigated in detail yet. For example,

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Figure 22. Glacier-formed reach of Chuja valley near Chibit. Chuja Gorge reaches the former river course via Aktash close to the village of Chibit. The two courses are separated by Mount Belkenek, whose slopes like those of the surrounding mountains are formed by glaciers. Note the abrupt limitation of glacial and glaciofluvial deposits at the outlet of the former Chuja valley. View is toward the southeast against the direction of flow.

sandur sediments being deposited against the slope of the former Chuja valley near its upstream beginning are currently the subject of further studies (P. Carling, 2001, personal commun.). They are possibly related to laminated sediments being interpreted as delta deposits partly investigated by Okishev and Borodavko (2001a, Fig. 11 therein). Our preliminary investigations revealed lateral and terminal moraine deposits in the Chuja Gorge, lower Mashej, Belgebash, and Chuja River valleys near Yarbalik village, which are concordant with partly unpublished investigations by Russian scientists (P. Borodavko, 2002, personal commun.). Dating these features as well as surveying their extension and elevation could provide additional information on the previous ice dam. At the current state of knowledge, an ice-sheet–like glaciation could be assumed for the LGM, whereas during later stages valley glaciation might have been more characteristic for Chuja valley. Considering the altitude of shorelines in upper Chuja Basin of 2100 m, the thickness of the ice dam must have been at least 650 m. This value is based on the elevation of the recent Chuja valley at the inlet to Chuja Gorge of 1450 m. The upstream extension of the ice dam can be limited by the locations of the gravel dune fields of Baratal and Kara Kol immediately upstream of the separation of the two courses of Chuja valley around Mount Belkenek (Fig. 12). The downstream extension is less certain. The most upstream giant bar is located at the confluence of Ajgulak and Chuja Rivers (Fig. 13). Hence, there is a range of possible downstream glacier extension of ~10 km between the villages of Chibit and Yarbalik. A young glacier advance is revealed by moraine deposits in Chuja valley close to the village of Yarbalik. This advance must have been a postflood event, otherwise the moraine would have been washed out by the outburst flood. On the other hand, Chuja River was blocked again during this advance, but no catastrophic outburst resulting in ice dam destruction occurred. Hence, continuous drainage of at least

smaller ice-dammed lakes in Chuja valley or even subglacial flow of Chuja River cannot be excluded completely, but the evidence described in the following chapters reveals that large-scale jökulhlaups also occur. Because of unknown characteristics of the ice dam, specifications on the outburst mechanism are speculative. Novikov and Parnachev (2000) and Butvilovsky (2000, personal commun.) assume earthquakes as triggers of ice-dammed lake outburst floods in the Altai Mountains. Even if current investigations confirm previous documentations of high seismic activity in upper Chuja valley (Rogozhin et al., 1999; Protsyuk, 1978, p. 28), earthquakes have never been found to trigger ice-dammed lake outburst floods (Tweed and Russell, 1999, p. 90). Even the powerful Alaskan earthquake of 1964 had no influence on glacier integrity (after Post, 1967, from Tweed and Russell, 1999). Rudoy (1998, p. 222) goes even further by describing the failure of the ice dam by earthquakes caused by so-called “limnoisostasy.” He claims that the pressure of large lakes on Earth’s crust causes initial fracturing, especially in the case of rapid drainage and consequent rapid pressure release. After the drainage of the lake the pressure reduces, but isostatic rebound is limited by the wedged crust units, which cause distinct earthquake activity. This could still be active while the next ice dam is being formed by pulsating glaciers. Rapid warming events during the Pleistocene are assumed to account for the catastrophic breaching of glacial barriers and the rapid drainage of ice-dammed lakes (Carling et al., 2002, p. 24). However, further dated features of the jökulhlaups in the Altai Mountains are needed to confirm this correlation. The ice supply to the dam was predominantly from Sarulukul ice dome, which is indicated by larger glacier extension throughout all the detailed glaciation maps mentioned above. Therefore, the ice dam could be assumed to have been stronger

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia at the northern side along the former Chuja valley via Aktash than the southern side supported by Mashej Glacier. Also, the orientation of the dune fields of Baratal and Kara Kol suggest a failure of the ice dam along the current Chuja Gorge, as has been previously assumed by Baker et al. (1993). Among the possible outburst processes listed in Chapter 2, overspill and initial piping might also be taken into consideration for the outburst process. Overtopping of the ice dam, especially at the southern side of Mashej Glacier, appears plausible, because the surface slope of the glacier—or ice cap for outbursts during intensive glaciation—is oriented with the direction of flow. At the northern margin, overflow appears less reasonable, as the damming ice was supplied from the north. Hence, the ice surface rises in this direction. Once the surface of the ice dam was reached by the lake and initial overflow occurred, supraglacial erosion soon might have widened the channel. Speculation about erosion of fractured ice illustrates a fast growth of the channel resulting in a steeply rising hydrograph. Piping through englacial conduits is also reasonable. While widening of the conduits by thermal erosion or friction heating is less plausible to cause a giant outburst flood draining most or all of the lake, a failure of the roofs of the pipes could have led to rapidly rising discharge. This imaginable sequence of processes is previously described for the outburst floods of Lago Argentino by Heinsheimer (1958). An interesting problem could be a speculation of the glacier behavior from Kuehtanar valley that is assumed to have temporarily separated the lake within Kuray and Chuja Basins (Fig. 19). This ice dam seems to have blocked the drainage of Chuja Basin and was furthermore influenced by a rising lakewater level downstream in Kuray Basin. Under those special circumstances, flotation of the ice dam, usually fixed by friction on the valley slopes, might not be excluded.

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4.2.3 Giant Bars and Indication of Flow Conditions Gravel deposits are found along the pathway of the flood throughout Chuja and Katun valleys, while the most upstream one is located at Ajgulak valley, ~4 km downstream of Yarbalik village (Fig. 13). These are located in tributary valleys forming barriers, similar to point bars at the inner bank of valley bends and as infill of alcoves at the valley slopes. Characterization as giant bars is established due to their height of up to 120 m and their extension of up to 5 km along the valleys and up to more than 2 km inside tributary valleys. Intensive fieldwork reveals, in contradiction to the statement of Rudoy (2002, p. 126) of general inclination of bar surfaces toward the bedrock side of the valley, that six different types of bars can be distinguished by their surface morphology (Fig. 23). The differentiation of types of giant bars illustrated in Figure 23 is based on observations of 55 bars along Chuja and upper Katun valleys. Characteristics of all locations are listed in Table A1 (see Appendix, p. 104). The relation of bar surface to “bedrock” should be read as orientation toward lateral valley slope or tributary valley; hence, especially for bars deposited in tributary valleys, the slope of bedrock is inflated. The qualitative classification leads to the following main characteristics of the different types considering their lateral shape: • Bar surfaces are classified as horizontal if their plane surface shows no obvious inclination. As this classification is carried out in a qualitative way, a continuous transition to bar surfaces rising/inclined toward bedrock should be considered. • Rising surfaces of bars toward the lateral valley slope are typically located at the outer banks of valley bends or at locations slightly exposed toward the main current of the flood. • Inclined bar surfaces toward the valley margin are found in two typical locations. Relatively small bars are located at

Figure 23. Sketch of morphological differentiation of giant bars (not to scale).

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Figure 24. Review of different types of giant bars around Little Jaloman village. The bar marked by “A” is separated by the giant bar between Little Jaloman and Inja villages by postflood incision of Little Jaloman River. Bar “A” (no. 8 in Table A1) has a relatively horizontal surface near Katun valley but is inclined toward the tributary valley. Also horizontal near the main flood channel, bar “B” (no. 10 in Table A1) is slightly rising toward the valley slopes. At location “C”, a bar in the form of a ramp is deposited, while in higher elevations run-up sediments are located. The difference in elevation above the current Katun valley bottom between the surface of bar “A” and the highest run-up sediments is 150 m. Direction of flow was toward the background.

Figure 25. Example of giant bar with lateral ridge. At Kok-Kumak, the bar at the right side of the river at the confluence of Big Jaloman and Katun Rivers (no. 63–65 in Table A1) has a maximum elevation of 915 m. The bar surface lowers from this ridge toward a mountain slope down to 865 m. The lower level is inclined against the general slope of the valley. Direction of flow was left to right in Figure 25A and toward the background in Figure 25B. Note the rising bar surface of Big Jaloman bar along the direction of flow, visible in the background of Figure 25A. The bedrock surface visible in Figure 25B consists of granite and is dated as 17,100 ± 1100 yr B.P. by exposure dating using 10Be and 26Al. As identical ages could be determined for both isotopes, a simple exposure history can be assumed (G. Balco, 2001, written commun., and 2002, unpublished data prepared for this study). Considering the local topography, a temporary coverage by rock or soil appears less plausible; hence 17 ka appears a reliable age for the exposure of the bedrock surface. By comparing these data with those from other flood-related features, its younger exposure might be explained by postflood erosion of parts of the giant bar.

•

the inner banks of valley bends and can be considered as a kind of point bar. In addition, very large bars located at the mouth of tributaries have surfaces inclined toward the inner side of the tributary valley. Occasionally, bar surfaces consist of the lateral ridge of bar sediments toward the valley. Due to the dimension of the ridges with heights of up to 50 m and missing natural sediment sections, the sedimentological relation to the main bar body is uncertain. It seems to be possible that these ridges have some similarity to natural levees deposited on flood plains, as all ridges are located on point-bar locations. On the other hand, postflood erosion of parts of the bars cannot be excluded.

•

•

Ramp-type bars are located occasionally on steep slopes in narrow valley sections where more extended bar types could not be accumulated. Even though they are significantly smaller and thinner than other giant bars, they disturb the straight inclination of the bedrock by considerable sediment accumulation. Run-up sediments form a thin layer of gravel not identical with the bedrock they rest on. This layer characteristically has a thickness of several decimeters and influences the valley slope morphology to a minor degree only. They are deposited on locations exposed toward the flood, such as downstream flanks at the outlet of tributary valleys, local obstructions at the valley slopes by bedrock ridges, or at the

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outer banks of valley bends. Run-up sediments are typically the highest deposits of the flood and hence are valuable paleostage indicators. In some locations, the steepness of the bedrock slope limits the possibility for gravel accumulation; therefore, ramps could not develop. Selected examples of giant bars illustrate the different character of bars (Figs. 24–28), including one example where local topography influenced the bar surface further. On the bar surfaces kettle holes are occasionally found, for example, on the bars at Belyj Bom in Chuja valley and the giant bar between Inja and Little Jaloman villages (no. 42 and 13 in Table A1). These features of relatively small-scale terrace surface morphology indicate transport of ice blocks from the failed dam (e.g., Fay, 2002; Maizels, 1992). Due to the different relationship of the types of bars toward the main current in the channel, explanations for their generation vary. However, except for run-up sediments, they can be characterized as a kind of slack-water deposit because all types of bars are typically located in backwater positions (cf., e.g., Kochel and Baker, 1988). In contrast, run-up bars are deposited in locations exposed toward the main current of the flow in valleys and indicate energy of flow by their height of deposition above other bars nearby. A detailed analysis of the hydraulic background is given in Section 5.2. The deposition of the backwater bars can be explained by eddy formation at local valley cross-sectional extensions leading to sedimentation of the sediment load (simFigure 26. Ramp-type bar in Chuja valley. Within the small and steep tributaries in Chuja valley, deposition of ramp-type bars like in Dejljugem valley (no. 58 in Table A1) is characteristic. Direction of flow was left to right.

Figure 27. Bar surface with related runup sediments in the lower Chuja valley. The example of the bar at upper YalbakTash (no. 34 in Table A1) illustrates the difference in elevation of the highest bar surface (in the front, 1015 m) and run-up sediments in front of a local valley obstruction (in the back, 1139 m). Direction of flow was toward the background.

30

J. Herget Figure 28. Scoured bar surfaces downstream of a bedrock ridge in the lower Chuja valley (no. 32 in Table A1). The bar shows a scoured surface downstream of a bedrock ridge at a tributary mouth. Downstream of the ridge, the bar surfaces rise parallel to the direction of flow (left to right). This frequently observed phenomenon can be explained by a hydraulic jump formed by flow over the ridge resulting in scouring immediately downstream, similar to flow over a sill (e.g., Hoffmans and Verheij, 1997, p. 40f.). Hence, the conservation of the form indicates a fast waning of the final flood, as deposition in the protected backwater area downstream of the ridge did not compensate the scour effect by deposition when the ridge was not submerged anymore.

plified and generalized after Carling et al., 2002, p. 27f.) (Fig. 29). Proximal to the ice-dammed lake, coarse sediments such as pebble gravels up to cobbles or even boulders are deposited in subparallel sheets some decimeters to 2 m thick and inclined upwards into the tributary valley. Imbrication indicates a transport as bed load into the tributaries. For example, in Katun valley the bars at Inja and Little Jaloman villages developed as longshore bar and point bar, respectively (Fig. 13). They consist of fine gravels with horizontal bedding up to slight inclination toward the tributary valley, which are interpreted to be transported in suspension. Their steep slopes toward the main channel

indicate postdepositional lateral erosion during the decreasing flood stage. In contrast to the bars in Chuja valley, the inner margin gently declines toward the tributary. They also consist of subparallel sheets, which decrease in thickness from ~10 m at the outer margin to ~1 m at the inner one. The bar at Little Jaloman is investigated in detail (Parnachov, 1999), obtaining detailed analysis of the sedimentary structure. The sedimentary sheets consist of 11 identical stacked rhythms of upward-fining sediments (Fig. 30), only occasionally interrupted by isolated cobbles and boulders. These rhythmites imply, by their monotonous repetition of the facies in each superimposed

Figure 29. Sketch of the sedimentary structure of giant bars in Chuja and Katun valleys (modified on the basis of Carling et al., 2002, Figs. 11b and 14 therein).

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Figure 30. Stacked sediment sheets forming a giant bar at Little Jaloman. The horizontally bedded sediment layer consists of upward-coarsening silts and sands to gravels. Below and above the unit, identical sheets are deposited. Optically stimulated luminescence dating of quartz from a layer of fine sands and silts similar to those visible in the figure (below pen) resulted in no reliable age. It seems the sediment had not been adequately zeroed before burial and furthermore consists of minerals difficult to date. An alternative explanation would be an age of the deposition of the sample sediments older than 100 ka (B. Mauz, 2002, written commun.). One sample (BN 245) was collected right at the base of the giant bar of Little Jaloman exposed along Little Jaloman River (no. 62 in Table A1), the other one in the same section as the sediment unit of the figure (BN 244). Similar problems occurred by infrared stimulated luminescence (IRSL) on fine silt feldspars from three samples collected in the same section and from the base of the giant bar at the confluence of Chuja and Katun Rivers. The samples from Little Jaloman bar show stratigraphic reversal in dates (103 ± 13 ka located above 63 ± 8.2 ka, PCARL00-1 and PCARL00-2). Assuming an inset of the sampled sediments, which are not located in direct vertical succession, could be another explanation. For those conditions, the bar would be much older than previously assumed, but no discordance is found during repeated investigation of the section at Little Jaloman. The time of deposition of the sample from the giant bar at the confluence of Chuja and Katun Rivers (no. 21 in Table A1) is given as 86 ± 16 ka (PCARL00-3) (P. Carling, 2001, written commun., based on analysis by G. Berger). Another sample of fine silts and sands assumed to contain minimal organic matter is radiocarbon dated by application of accelerator mass spectrometry (AMS), which results in an age of 20,050 ± 80 yr B.P. (Beta 159974). The sample was taken from a sand-silt layer at an elevation of 765 m, hence from about the center of the bar deposits.

succession, repetitive flow control rather than alternations in sediment supply (Carling et al., 2002, p. 29). At the current state of knowledge, it is not exactly known whether the giant bars have been eroded between repeated outburst floods. The sequence of rhythmites is interpreted as evidence for repeated outburst floods (Parnachov, 1999; Novikov and Parnachev, 2000) but could also indicate pulsing during a single flood event (cf., e.g., Carling et al., 2002). Ages of different parts of a giant bar such as the one at Little Jaloman could reveal clarification even if time resolution cannot obtain evidence of pulsating flow. A similar discussion is carried out for the floods of the outburst of Lake Missoula. Waitt (1980, 1985) and Waitt et al. (2000) interpret stacked sediment sheets along the pathway of the flood as indicators for separate flood events, resulting in an estimated number of floods of ~100 (Waitt et al., 2000). Baker and Bunker (1985, p. 24f.) analyzed and discussed this interpretation on a regional background and found that all arguments and indicators need several individual unverified assumptions to reveal evidence of the concept of a high number of jökulhlaups from Lake Missoula. At the current state of knowledge a similar investigation to estimate the number of outburst floods along Chuja and Katun valleys appears critical.

Giant bars at the Chuja and Katun River confluence and at Little Jaloman village are found to reach down to the current water level. Hence, the valley must have been incised down to the recent level of the mean water level of Katun River at the point of time of the flood. Statements on whether this incision occurred during the flood itself or prior to the flood with previously deposited fluvial sediments washed out are speculative at the current state of knowledge. Most of the giant bars show several distinct levels between the top of the bar and the valley bottom (Fig. 31). Due to missing sections of adequate size it is not known if these levels are erosional structures or accumulations of separate bar units. These different levels are assumed to represent temporary, more or less stationary, water levels of the subsiding flood. The configuration of giant bars at the confluence of Chuja and Katun Rivers indicates a temporary blockage of drainage from upper Katun valley (Fig. 32). This bar configuration indicates that flow from the outburst flood was much stronger than the discharge of upper Katun River. Its channel was blocked by deposited suspension gravel. Only by postflood incision, the drainage of upper Katun valley became possible again. Suspension gravel partly forming bars and covering bedrock topography are also found upstream of the rivers’ confluence (Fig. 13). The uppermost location is ~8 km upstream of the village Inegen at an altitude of 943 m (no. 17–21 in Table A1) where the Katun River leaves a gorge

Figure 31. Terrace levels and vertical succession of bars upstream of Belyj Bom. Different bar surfaces and terrace levels are marked by arrows. The bars are located in Chuja valley immediately upstream of Belyj Bom village (no. 45–47 in Table A1). Direction of flow was right to left.

Figure 32. Bar configuration at the confluence of Chuja and Katun Rivers. Giant bars block Katun River, while Chuja valley is without obstructions by bars down to Katun River. Grid lines are 1 km for scale. Svitoch (1978, p. 155) gives a thermoluminescence (TL) age of suspension gravel at the confluence of 148 ± 16.7 ka (MGU-KTL-89). The sample was taken from the bar south of the last bend of Chuja River upstream of the confluence. Previously, this age was characterized to be of questionable validity and is related to the terrace successions of the inner parts of the valleys (cf. text for controversial interpretation of the sedimentological interpretation of the sampling location).

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Figure 33. Inja terrace level in Katun valley upstream of the Big Ilgumen confluence in relation to giant bars. Giant bars are marked by white arrows. Their visible surfaces are ~60 m above Inja terrace. Katun River incised ~50 m into this bed-load terrace level. Alluvial fans are superimposed. View is against the direction of flow.

section. This deposit indicates a flow down from Chuja valley and farther up- and downstream within Katun valley. The deposition of the bars in Katun valley indicates a backwater location at the lowest part of Katun valley; hence, flow continues from Chuja to lower Katun valley with flooding in the upper part of Katun valley. The valley bottoms of lower Chuja and Katun valleys are formed by a terrace sequence with a main level called Inja terrace typically ~50–60 m above mean river water level (Fig. 33). This main level is developed throughout the area of investigation from the Big Ilgumen River confluence up to the village of Belyj Bom in Chuja valley. Farther upstream this main level fades out in several single terrace levels. Giant bar deposits extend beneath the terrace of coarse cross-bedded gravels up to boulders toward the center of the valley. These terraces are interpreted as insets of previously deposited giant bars. Within previous investigations, these terraces have not been studied in detail, except by Ivanovskij (1998), who reviewed previous Russian studies and investigated details

of low levels of the terraces in Chuja valley. Carling et al. (2002, p. 31f.) give higher values for the characteristic depth of incision of the current water level into the main terrace level. For the contact between bedrock and a low silty sand layer at the base of the terrace gravels, Carling et al. (2002, p. 31) dated the deposition by infrared stimulated luminescence (IRSL) to 47.2 ± 6.7 ka (no laboratory number is mentioned). Individual large foresets could be observed by him at the confluence of Little Jaloman and Katun Rivers and close to the village of Iodro in Chuja valley. They are interpreted as originally constituting a largely unmodified Gilbert-type delta, similar to that described for glaciofluvial deposition into standing water. Considering this sedimentary structure and the coarse gravels and boulders the terrace consists of, it might be regarded as the bed-load-transported equivalent of the suspension gravel of the outburst flood. In the equivalent elevation of this bed-load terrace (753 m at this location), suspension gravels are found showing a large-scale cross-bedded sediment structure in a gravel pit at Little Jaloman village (Fig. 34). This sedimentary structure is extraordinary

Figure 34. Cross-bedded suspension gravels at Little Jaloman. Cross-bedded units are tens of meters wide. Height of section is 8 m (no. 79 in Table A1). View is against the direction of flow.

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for suspension gravels forming the giant bars and could not be observed at any other place. The cross-bedded sediment structure can be interpreted as being deposited by a braided river channel pattern during the falling limb of the flood reworking the lateral margins of the giant bars. At the end of the flood, all valleys were entirely filled with sediments up to the level of the bed-load terrace. A speculative (!) scenario strengthening the meaning of the braided river deposition could be as follows: Last stages of the flood and also “normal” discharge of Katun River laterally eroded the giant bars, which led to a sediment overload due to the minimal erosion resistance of the fine-grained suspension gravel. Immediately after this stage, incision into the bed-load terrace occurred, and the river incised to its current depth on the surface of bedrock. The valleys appeared as they look today. A date of the deposition of the cross-bedded suspension gravels would mark the final stage of the last flood flowing down Chuja and Katun Rivers, as younger floods reaching the level of the surface of Inja terrace without any doubt would erode the suspension gravels that are closest to the center of the valley. Unfortunately, previous attempts to date the sediments within the section failed (cf. Fig. 30 caption). The sedimentary structure of the giant bars and the bed-load terraces allow conclusions on flow conditions of the outburst flood. The giant bars with their large amount of transported suspension load could lead to the assumption of hyperconcentrated or at least high-density currents. On the other hand, the obvious horizontal bedding is a doubtless indicator of a relatively clearwater flood (Costa, 1988b). This is also indicated by the normal grading structure and the missing of the dominant occurrence of matrix-supported boulders as characteristic sediment (Knudsen

and Russell, 2002). Even though a considerable sediment share in the flood must be assumed, classical hydraulic calculation procedures for water flow can be applied (Coleman, 1981). For the bed-load terrace compared with a Gilbert-type delta deposit by the steep bar-front progradation, Carling et al. (2002) describe a scenario of hyperconcentrated flow prograding beneath relatively clear-water flow containing the suspension load. Due to the very complex tectonic and petrographic conditions in the Altai Mountains (Figs. 7 and 8), the origin of the sediments forming the giant bars cannot be determined. Probably heavy mineral or isotope studies of local rock provinces could lead to an answer on this question. A longitudinal profile along Katun and Chuja valleys illustrates locations and elevations of giant bars and their erosional levels along the uppermost path of the flood (Fig. 35). The elevation of the highest bar surfaces and run-up sediments above the mean current water level indicates a depth of the flood of >300 m. 4.2.4 Secondary Lakes To provide a clear separation from the ice-dammed lake in Kuray and Chuja Basins, lakes in tributary valleys and local valley expansions along the flood’s pathway are characterized as secondary lakes. In Sargalchuk valley, ~5 km upstream of Belyj Bom in Chuja valley, a lake still exists today (Fig. 13). In years with sufficient precipitation, the lake—dammed by a giant bar—contains water throughout the year. Usually it drains by percolation through the fine gravels of the bar, while a lateral breach incised in the bar by previous overflow remains dry during the current discharge regime of Sargalchuk catchment.

Figure 35. Longitudinal profile along Katun and Chuja Rivers between the Big Ilgumen River confluence and the former ice dam with locations and elevations of giant bars and related levels. Information about individual types of bars and related levels is left out to provide clarity. The bed-load terraces are drawn as continuous line of the uppermost level of Inja terrace, even though locally this terrace level is incomplete due to postflood erosion by Chuja and Katun Rivers. Most bars are investigated by determination of their elevation by altimeter and determination of the location by GPS. Occasionally, bar surfaces are added by altitudes estimated from topographic maps. These additional sources of data were needed where bars on the opposite side of the rivers could not be reached due to missing bridges and access roads. The data, bar characteristics, and additional local observations are listed in the Appendix.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia In the valley of Inja River, near the village of Injushka, a sequence of three units of lake sediments interbedded with suspension gravels characteristic for the giant bars is exposed in several gullies and sections along the river (Fig. 36). The lake sediments are found at elevations between 799 and 830 m and vary in thickness in different sections throughout the location. The uppermost lacustrine sediments of silty clay are partly exposed at the surface. They have previously been dated by radiocarbon and luminescence methods as 23–46 ka (after Svitoch and Khorev from Carling et al., 2002, p. 30). More detailed dating revealed a higher temporal resolution for single units using radiocarbon dating (after Barishnikov from Carling et al., 2002, p. 30) and infrared stimulated luminescence (IRSL) (Carling et al., 2002, p. 30) (Table 4). These lake sediments prove that Inja valley was repeatedly blocked by the giant bar at the confluence with Katun River. In fact, three flood events can be distinguished. Obviously, the bar deposited by an outburst flood blocked the course of Inja River, and a lake formed in Inja valley until the surface of the bar was reached and the lake drained through an incised trench. The subsequent flood reached Inja valley again, either by overtopping the remnants of the giant bar or through the trench of Inja River, and deposited suspension gravel on the lacustrine sediments. By filling the new lake, the cycle repeats until the final flood when the lake sediments are left uncovered on the surface. It seems possible and plausible that more than three outburst floods occurred throughout Pleistocene times, but according to the current state of knowledge, obvious evidence is only given for three events. Rudoy (1998, p. 232) postulates numerous jökulhlaups in the Altai Mountains and characterizes the occurrence of ice-dammed lake outburst floods as “… normal exogenous process of relief formation …” but gives no evidence for the repeated floods.

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In Katun valley immediately downstream of the confluence with Chuja River, horizontally bedded silts are deposited as a local unit in between suspension gravels (Fig. 37). These sediments of limited lateral extension are partly covered by colluvium and can be interpreted as lacustrine sediments in a local pond on the surface of a giant bar at an elevation of 787 m. For additional tributaries along Chuja and Katun valleys, temporary lakes behind giant bars could have existed, but no evidence by lake sediments has been found yet. This missing lake evidence could be by higher discharge in larger valleys such as Little and Big Jaloman valleys, leading to earlier incision through the dams of the giant bars. So either there was no time for thick units of lacustrine deposits to develop or they have been eroded completely. 4.2.5 Gravel Dunes Gravel dunes are fluvial bed-form features that are found frequently within the area of the previous ice-dammed lake and along the flood’s pathway (Figs. 12 and 13). Four dune fields are located in Kuray Basin (Baratal and Kara Kol at the western margin and Akturu and Kuray in the south) and two at the northwestern part of Chuja Basin (Chagan-Uzun and Chuja Basin). Typically, they are located at the former lake bottom indicating the

Figure 36. Lake sediments in Injushka valley interbedded with suspension gravel. Lake sediments in the sequence of sediments are marked by white arrows

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Figure 37. Lacustrine sediments in Katun valley downstream of the confluence of Chuja and Katun Rivers. Approximately 40 m below the marked unit of lacustrine sediments (no. 26 in Table A1), a similar set is exposed at the slope of the gully, which is not visible in the figure. Direction of flow was right to left. The sediments are dated as 28 ± 2 ka by optically stimulated luminescence on quartz (BN 246). (Diagonal lines are electric power lines).

direction of drainage current, but they are also found in tributary valleys and steps of valley slopes in high elevations above the current river. In Chuja valley, only weakly developed bed forms near Iodro village are found on one terrace level, which might be interpreted as gravel dunes. In Katun valley, fluvial dunes are found between Inja and Little Jaloman villages and downstream of the main area of investigation. Even in the forelands of the Altai Mountains, gravel dunes are found near the village of Platovo, ~20 km downstream of Gorno-Altajsk. The first interpretation of these forms as fluvial bed forms is given by Speransky in 1937 (after Carling et al., 2002, p. 25). However, several Russian scientists present other interpretations, especially for the Kuray dune field, which has been investigated most intensively due to its extension over several square kilometers and the height of the dunes of up to 16 m. Deviatkin (1965, Fig. 54 therein) interprets the dunes as erosional forms trenching glaciofluvial sediments in front of a terminal moraine. This interpretation cannot be confirmed as there is no uniform slope of the troughs between the dune crests. Furthermore, this explanation cannot be applied to other dune fields. Also, the interpretation by Okishev (1982, p. 74f.) as a glacial deposit, such as ribbed moraine or Rogen moraine, fails by considering the homogenous shapes, the sedimentology of sorted well-rounded fluvial gravels (cf., e.g., Benn and Evans, 1998, p. 437f.), and the missing transferability to other locations. A detailed analysis of the different locations partly based on previous work by Carling (1996a, 1996b) is given in the context of Section 5.6, where also paleohydraulic interpretations are carried out based on morphological and partly sedimentological characteristics of the individual dune fields. Due to missing sections of adequate dimension within the large gravel dunes, the internal sedimentological structure could only partly be investigated. In the following section new age estimations as supplement to previous studies are presented.

The dune field in Chuja Basin located near shorelines at the northwestern margin could be dated twice due to good sections along incised ephemeral creeks reaching the area from Kuray Range in the north. A layer of organic sediment, probably part of a paleosoil profile, is dated by AMS radiocarbon as 35,870 ± 490 yr B.P. (Beta 159972). Optically stimulated luminescence dating of a silt layer nearby reveals an age of ca. 28 ka (BN 243). More precise values cannot be given due to the limited amount of material after treatment of the sample. The ephemeral creeks cover parts of the dune field with alluvial fans. Plant material sampled from one of these fans gives evidence for their young age by an AMS radiocarbon age of 1870 ± 40 yr B.P., resulting in a calibrated age of A.D. 60–240 (Beta 159973). Balco (2000, written commun.) carried out experiments on cosmogenic-isotope dates of several gravel dunes by considering inheritance effects of previous exposures of the gravels that are forming the dunes. Preliminary results charged with methodological problems give dates for Kuray dune field of 12,700 ± 2000 yr B.P. and for the dunes at Platovo of 17,900 ± 1700 yr B.P. by interpreting contents of the isotope 10Be. According to Balco, these dates can be seen as indicators of the last flood from Kuray Basin along Chuja and Katun Rivers, which occurred in the time range of 15 ± 2 ka. This age conflicts with an estimation by thermoluminescence (TL) dating for the dunes at Platovo of 36 ± 4 ka (Carling et al., 2002, p. 24). While the TL age from Platovo and the AMS 14C date from Chuja dune fields fit remarkably well, other dating methods reveal problematic estimations of the period the dunes were formed. Methodological problems of luminescence and exposure dating are not finally solved to allow these methods to be applied as standard routines for the complex fluvial environment conditions generating gravel dunes. Similar problems are found for luminescence dating of the suspension gravels, as previously mentioned (Fig. 30). As the Pleistocene high mountain environment of the

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia ice-dammed lake and the related traces of the outburst floods are poor in organic remnants, the application of radiocarbon dating can only be carried out exceptionally. Hence, dating techniques applicable under the conditions of the floods in the Altai Mountains urgently need further improvement to increase the knowledge of spatial and temporal variation of jökulhlaups. According to Butvilovsky (1993, appended map therein), fluvial dunes are found even north of Platovo. For an extended area of hundreds of square kilometers between the cities of Gorno-Altajsk and Bijsk at the confluence of Katun and Bija Rivers, he presents a coverage of fluvial dunes larger than any dune field found elsewhere in the Altai Mountains. Unfortunately, no details about the special characteristics of these dunes are given, except that they consist of sandy sediments (V. Butvilovsky, 2000, personal commun.). As skepticism is advisable about these dunes and their connection to the outburst floods in the Altai Mountains, an interpretation as ordinary aeolian dunes independent of the jökulhlaups also appears plausible. 4.2.6 Erosional Forms Large-scale erosional forms, such as the Channeled Scabland characteristic for the North American analogue of the Lake Missoula flood (e.g., Bretz, 1925; Baker, 1978b), are missing for the floods in the Altai Mountains. This can mainly be attributed to the different topography of these two areas flooded by jökulhlaups. While the Channeled Scabland was formed on an inundated plateau of mainly volcanic rock (Swanson and Wright, 1978), along Chuja and Katun valleys the outburst flood was canalized into the previously incised river valleys. The only large-scale erosional feature related to the outburst floods is Chuja Gorge upstream of Chibit. As explained in Section 4.2.2, it seems plausible that the outburst occurred along this gorge section of the valley. Even if the outburst might have enlarged this valley section considerably (cf. Rudoy, 2002, p. 131), this reach must at least partly have been incised previously because it was filled by glacier ice from Mashej valley, which in turn was part of the ice dam. Rudoy (1998, 2002) documents the similarity of the Lake Missoula flood and the jökulhlaups in southern Siberia, especially by the examples from the Altai Mountains. In addition to descriptions of erosional forms from other catchments within the Altai Mountains, he postulates a so-called “Chagan Scabland” in the upper catchment of Chagan-Uzun River in southwestern Chuja Basin (Rudoy, 2002, Fig. 13 therein). Over a length of 10 km, a complex network of dry channels and shallow gullies incised up to 50 m deep into glacier-polished bedrock of weakly metamorphosed schist. These scabland forms are related to the postulated outburst by a small ice-dammed lake upstream that should have occurred not later than 3000 yr B.P., hence in Holocene time. In that case, their generation cannot be related to the outburst flood along Chuja and Katun valleys. In Pleistocene times, the upper part of the catchment was covered by glaciers from Southern Chuja Range (Figs. 12, 14, 15, and 21). Hence, incision of subglacial drainage channels during the period of

37

glaciation into the low-resistance schist similar to Nye channels cannot be excluded definitely either (cf., e.g., Benn and Evans, 1998, p. 110f., for a review). Butvilovsky (1993) uses the expression “scabland” for all erosional forms he relates to the Pleistocene outburst floods in the Altai Mountains. This generalization leads to misunderstandings (cf. Okishev, 1997, and discussion below), as a classical Channeled Scabland like from the Lake Missoula flood (Baker and Nummedal, 1978) was not formed in the Altai Mountains. Spillways connecting different modern-time catchments are also assumed to be in function during the existence of the icedammed lake in Chuja and Kuray Basins by Rudoy (1998, 2002) (Fig. 15). Most of them are related to a maximum extension of the lake up to an elevation of 2200 m that cannot be confirmed by other investigators as previously mentioned in the chapter on lake shorelines. Local spillways within the former lake basin existed and were active in the course of the drainage of the lake. During high stages of the ice-dammed lake, the modern-time channel network was submerged up to a level of 2100 m. During the lowering of the water level during outburst floods, the current locally did not follow the slope of the valley but was directed toward the breach within the ice dam. Evidence for this process can be found, for example, by the location and orientation of the gravel dune field of Baratal close to the location of the ice dam, described in detail in Section 5.6. Butvilovsky (1993, appended map therein) related numerous landslides to Pleistocene outburst floods throughout the Altai Mountains. They are partly drawn in Figure 14. For the floods caused by the lake in the upper Chuja catchment, they are located in the narrow valley reach between Chuja and Kuray Basins and in Chuja valley immediately downstream of the ice dam. The landslides between Chuja and Kuray Basins have been intensively investigated by Rusanov (1997), who found lacustrine sediments upstream of the landslide debris. These deposits from five different locations indicate lake depths of >16 m and contain pollen and indicators of cryoturbation, leading to an age estimation of Late Pleistocene to Early Holocene. Relating landslides to jökulhlaup occurrence is weak evidence for floods, as landslides also might have occurred after the outburst floods, being typical phenomena of high mountain environment with steep valley slopes. At least for the landslides between Chuja and Kuray Basins, their association with the flood is doubtable as debris from slope failures would have been washed out or at least reworked. So, the lacustrine sediments investigated by Rusanov (1997) probably indicate postflood events. Furthermore, the stream power of the initial stage of the flood might have weakened fractured bedrock at the valley slopes, which might have led to landslides during the decrease of the flood. Scoured or polished bedrock surfaces on mountain and valley slopes at elevations below the surfaces of the highest giant bars nearby are frequently observed along Chuja and Katun valleys (e.g., Figure 37 where the visible giant bar is not the highest

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at the location). As many other processes might be responsible for local missing soil cover or smooth bedrock surfaces, this aspect cannot be considered as a flood-related erosional form. Clearly flood-related is a local scour hole around a bedrock hill in Chuja Basin close to the confluence of Chagan-Uzun and Chuja Rivers. The scour hole has a depth of >8 m with a length of 90 m and an associated width of nearly 400 m, and shows characteristics of a typical obstacle mark in front of the 50 m high hill. Due to its value as a paleohydraulic indicator, further details are given in Section 5.7. 4.2.7 Boulder Deposits Boulder fields that can be related to the ice-dammed lake and the jökulhlaups are found occasionally as ice-rafted deposits and as fluvially transported sediment. Within Kuray Basin, erratic boulders can be found close to the location of the former ice dam at an altitude of 1560–1600 m, which is located ~140–160 m above the current water level of Chuja River (Okishev and Borodavko, 2001a). They are interpreted as ice-rafted debris that has been transported within the previous ice-dammed lake. The location and elevation of the deposits do not allow further interpretations of the lake level during the time of deposit. In addition, northeast of the village of Kokorya in Chuja Basin, a field of erratic boulders is deposited at an elevation of 2000 m (Fig. 38). The local topography obviously indicates stranded boulders on the gentle slope of the local pass crest between Chuja Basin and connected basins in the north. Petrographic analysis revealed an origin of the boulders at the southern margin of Chuja Basin (P. Borodavko, 2001, personal commun.). The striation on the surface of the boulders reveals their predepositional ice contact, and the altitude confirms the elevation of the water level of the ice-dammed lake of at least 2000 m. Between the villages of Inja and Little Jaloman in Katun valley, a field of boulders deposited on the bed-load terrace level is investigated in detail. The maximum diameter of boulders was determined as >13 m. Due to local topographic conditions,

a deposition by mass movement processes from the adjacent mountains can be excluded. Most of the boulders are relatively well rounded and show a streamlined shape, which can be interpreted as an indicator of postdepositional corrasion by the suspension load of the flood. The boulders are valuable indicators of paleoflow conditions by applying a flow competence approach. A detailed description and further analysis will be given in Section 5.5. Numerous additional locations of erratic boulders are given by Butvilovsky (1993, appended map therein). As all locations are within the Pleistocene ice sheets, these boulders reveal no dislocation by outburst floods. The occurrence of boulders in areas far away from their bedrock source has long been recognized as firm evidence for glacial transportation (cf., e.g., Benn and Evans, 1998, p. 575f., for a review). 4.3 Criticism on Occurrence of Jökulhlaups in the Altai Mountains Especially Okishev, who investigated the Quaternary glaciations of the Altai Mountains for 40 years (cf. references in Okishev, 1982), contradicts the occurrence of outburst floods described by Butvilovsky (1993) and Rudoy (1998, 2002). His main arguments are (Okishev, 1999; Okishev and Borodavko, 2001a): 1. There is no evidence of significant erosion of Chuja and Katun valleys by the floods. 2. Accumulative forms are described without discussion of deposition processes. 3. No scabland is formed like the Channeled Scabland of the Lake Missoula flood. 4. No traces of the outburst floods within moraines at valley bottoms are found. 5. Sections of lacustrine sediments in Chuja Basin show no indication of abrupt lake drainage. He summarizes that the evidence of a large ice-dammed lake in Chuja and Kuray Basins is obvious, but no giant outburst flood occurred (Okishev, 1999, p. 85).

Figure 38. Ice-rafted boulders near Kokorya village: overview and glacier striation on boulder surface.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia All arguments given by Okishev have been discussed above. A statement summarizing the more detailed discussion is given to clarify arguments against Okishev’s general criticism of Pleistocene jökulhlaups along Chuja and Katun valleys: 1. Erosion along the valleys of Chuja and Katun Rivers is distinguished to divide from non-jökulhlaup-specific erosion in the high mountain environment. Polished mountain slopes or landslides are no significant indicator for the outburst floods. 2. The deposition process of the giant bars, run-up sediments, and gravel dunes—note the different interpretation of the forms by Okishev—is described and hydraulically interpreted in Sections 5.1, 5.2, and 5.6. 3. The generation of a scabland similar to the Channeled Scabland of the Lake Missoula flood would require similar geological and environmental conditions, which are not given. It seems to be critical that Butvilovsky (1993) and Rudoy (1998, 2002) closely relate the jökulhlaups in the Altai Mountains to the outburst flood of Lake Missoula. Even if there is principally a close relationship of the two large-scale ice-dammed lake outburst floods, different environmental conditions should be considered to allow variations. 4. The moraines in the valley bottoms of Chuja River and its tributaries are deposited by Holocene postflood glacier advances of relatively small magnitude. At current knowledge it might be assumed that these glacier advances did not block the river courses to form ice-dammed lakes with outburst floods of a magnitude similar to the Pleistocene events. A continuous subglacial flow during this state might also be assumed. 5. The missing obvious disturbance of lake sediments in Chuja valley is no significant argument against outburst floods in general, as jökulhlaups do not necessarily show a continuous recurrence interval. Especially for the Last Glacial Maximum with a maximal thickness and extension of glaciers and ice sheets, this appears plausible. Without previous investigation, and especially without the late verification of the incidence of the giant outburst flood of Lake Missoula, the reliability of a comparable event in the Siberian Altai Mountains would be considered less. For the Lake Missoula flood it took about 50 years after first publications by Bretz (1925) until the concept became established (Baker, 1973a, 1973b). Reviews on the history of research of the Lake Missoula flood given by Baker and Nummedal (1978) and Baker and Bunker (1985) reveal the number of established points of view of scientists and even philosophical aspects that first have to be overcome to let the giant outburst flood become widely accepted. 4.4 Open Questions In the previous subchapters, frequently mentioned uncertainties characterize the current state of knowledge about the outburst floods along Chuja and Katun valleys. Recently started

39

investigations and preliminary results published show valuable progress on the knowledge of gravel dunes, lake sediments, and giant bars’ sedimentology and morphology. Other subjects are currently not investigated in detail, such as the bed-load terraces in lower Chuja and Katun Rivers, the relationship of tilted to horizontal shorelines in Chuja Basin, and especially the chronology of the repeated outburst floods. While progress has also been made by successful dating of several samples from gravel dunes, lake sediments, bar surfaces, and the giant bars themselves, methodological problems occurred, which need further efforts. This applies for luminescence dating, for example, where new data do not compare to previous results. Also, data on loess samples from elevations below the water level of the outburst floods indicated by the surfaces of the giant bars (ca. 20 ka; F. Lehmkuhl, 2002, personal commun.) increase confusion about the age of the floods. Unfortunately, these dates and the stratigraphic position of the sampled location could not be considered in detail in this study, as they are not published yet. On the other hand, Carling (1996b, p. 649) determined TL dates for a loess deposit between dune crests at the Little Jaloman dune field of 7.4 ± 0.8 ka and 6.2 ± 0.7 ka, which suggests a Holocene deposition of loess. Another open question is the correlation of the outburst floods from the investigated area along Chuja and Katun Rivers to the foreland of the Altai Mountains, the upper catchment of Katun River, and valley systems nearby, where traces of Pleistocene jökulhlaups have also been described by Butvilovsky (1993) and Rudoy (1998, 2002). First reviews could not confirm the existence of any gravel dunes in Bashkaus valley (Carling et al., 2002, p. 20), and the evidence of an ice-dammed lake in Uimon Basin in the upper Katun catchment seems to be doubtful—but these are only preliminary impressions. Also, the pathway of the flood in lower Katun valley down to the confluence with Bija River is uncertain or at least not investigated in detail to distinguish jökulhlaup sediments from regular fluvial deposits. Several dated samples exist (e.g., Markova, 1978) and could be supplemented with our data. An example illustrates the difficulties arising: Remnants of wood from a terrace level in Katun valley located in higher elevation than the gravel dunes of Platovo nearby are younger than these—12,510 ± 160 yr B.P. (radiocarbon dating, SOAH-4484) to 36,000 ± 4000 yr B.P. (TL dating; Carling et al., 2002, p. 24). The older age fits to previous radiocarbon dates by Maloletko (after Carling et al., 2002, p. 24). The problem is whether the broad range (a) gives evidence for a long period of flooding probably associated with jökulhlaups in the upper catchment (Carling et al., 2002, p. 24), (b) is unspecific until detailed sedimentological analysis for all fluvial deposits in lower Katun valley is carried out, or (c) is caused by mixing age estimations obtained by the application of different dating methods. If the last and well-established explanation is chosen, practically no consistent data set exists, as all previous dates are carried out by different methods in different laboratories throughout the world. So, there are also open questions concerning the regional aspect.

Geological Society of America Special Paper 386 2005

Chapter 5 RECONSTRUCTION OF THE FLOODS where v is the mean velocity of flow, C is the roughness coefficient, R is the hydraulic radius, S is the slope, and x and y are empirical exponents (Chow, 1959; French, 1985; Naudascher, 1992; Chanson, 1999, and additional references quoted there). The Manning and Gauckler-Manning-Strickler equations are similar, except for algebraic transformations influencing the value of the roughness coefficient. Because it has been more commonly applied, the Manning formula (Manning, 1891) is preferred in this study. In standard form, the Manning formula is defined as

Seven different attempts to reconstruct the Pleistocene outburst floods along Chuja and Katun Rivers are applied. In the first four approaches, peak discharge of the flood is the target value of estimation. While uniform flow equations applied for single cross sections or longer reaches of the valley by the application of the HEC-RAS software package and the hydraulic interpretation of run-up sediments are physically based with a minor number of empirical elements, the correlation of lake volume with estimated peak discharge by regression equations is of purely empirical character. The second group of attempts estimates discharge values of an unspecific stage of the floods. Different flood features such as boulder deposits, gravel dunes, and obstacle marks are analyzed for whether and how they can be used to obtain further information on the flood’s characteristics. Most of the methods are developed further from previous applications, especially for the large-scale floods in the Altai Mountains. Information on previous use or comparable attempts in other studies is given in the subchapters on each method. All following chapters are of the same structure. After an introduction on the subject or method in general, the hydraulic background is explained in an overview. This is followed by a documentation of the considered data from the individual flood features in the valleys of Chuja and Katun Rivers. The calculation itself is introduced by a review of previous applications of the method in other paleohydraulic investigations. The estimated values for discharge and flow velocity are finally discussed for validity and interpreted in the context of the dynamics of the floods.

v = n–1 R 2/3 S 1/2 where n is the Manning roughness coefficient. For the other variables refer to the explanation above. 5.1.2 Hydraulic Background The restriction of uniform flow conditions for the Manning formula implies that depth of flow, cross-sectional area, flow velocity, and discharge are constant along the investigated channel reach (Chow, 1959, p. 89). Therefore, the slope of the energy grade line, the slope of the water surface, and the slope of the channel bottom are parallel. For practical purposes, this limitation is applied more liberally, resulting in the restriction to gradually varied flow. Hence, a mean velocity of flow of the considered channel reach is calculated, which requires that the investigated channel reach is relatively homogenous. On the other hand, also for critical flow conditions, Manning’s equation can be applied if special circumstances are considered (Jarrett, 1984; Tinkler, 1997). The factors of the Manning formula can be determined or estimated in different ways. The frequent application of the equation leads to several further investigations of the characteristics and relations of the elements of the formula, which can only be reviewed within this study. Considering the theoretical background, the slope-factor S of the equation is the slope of the energy grade line. On the background of uniform flow conditions, frequently the mean water surface slope or averaged channel bed slope is applied. Strictly speaking, these alternative slopes are only applicable for smooth water surfaces and plane channel bottoms. French (1985, p. 115) draws attention to detailed studies for channels with bed forms, which demand a more complex analysis. The hydraulic radius R is determined as the ratio of crosssectional area A to wetted perimeter P:

5.1 Uniform Flow Calculation 5.1.1 Introduction An obvious approach to estimate flow velocity for the outburst floods along Chuja and Katun valleys is the application of empirical equations. Several empirical relationships of factors influencing flow velocity and—in the case of the given crosssectional area—discharge have been developed. Reviews on the different approaches, some of them for strictly defined boundaries, are given, for example, by Chow (1959), Henderson (1966), and Bray (1979). General attempts for uniform flow became established, for example, by the well-known Chezy, Manning, and Gauckler-Manning-Strickler equations, which are of similar principal form: v=CRxSy

R = A / P. 41

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The most crucial parameter to determine is the roughness coefficient n. This coefficient encompasses all elements potentially reducing flow velocity in the channel reach. Factors affecting Manning’s roughness coefficient are surface roughness, vegetation, channel alignment, silting and scouring, obstructions, size and shape of the channel, stage and discharge, and transported sediments (according to Chow [1959, p. 101f.], Arcement and Schneider [1984], and French [1985, p. 117f.] where details are listed and discussed). In addition, some of the above factors may vary seasonally. Uncertainty about the roughness coefficient leads to several approaches for its objective or at least retraceable determination: • descriptive lists of channel conditions with ranges of n (e.g., by Chow, 1959, p. 108f.) • databases with photographs for comparison of channel conditions (Barnes, 1967) • empirical formulae relating to grain size distributions (e.g., Strickler, 1923) • formulae with combinations of grain size and hydraulic radius (e.g., Limerinos, 1970) • formulae with combinations of grain size and sinuosity (e.g., Cowan, 1954) Experiences resulted in software solutions to estimate the n value (Jarrett and Petsch, 1985) and manuals with information about additional investigations (Arcement and Schneider, 1984). For natural channels, n values vary between 0.025 and 0.150, and for flood plains between 0.025 and 0.200 (Chow, 1959, p. 112f.). The highest values are found for channels or flood plains with dense vegetation. Substituting mean flow velocity in the continuity equation, discharge can be calculated directly from the Manning equation. Note that the cross-sectional area is already determined as an element of the hydraulic radius. The merged form of the equations can be written as

but it should be considered that the method is described slightly differently in the literature, for example, by regarding whether changes in the channel reach contraction and expansion or not. A major disadvantage of the slope-area method not only in the context of this study is that it can only be applied for locations of paleostage indicators (O’Connor and Webb, 1988). The giant bars, used as water surface indicators of the flood along Chuja and Katun valleys, have been deposited only in backwater locations such as the mouths of tributary valleys, where the cross-sectional area is extended. These large cross-sectional areas lead to a systematic overestimation of the discharge. The contracted valley reaches in between cannot be considered; hence the presumption of uniform flow is not met. Also, the energy loss of the intervening constrictions and expansions cannot be considered, which further increases the overestimation of discharge (cf. Jarrett, 1987). On the background of the advances of the step-backwater method (Baker and Bunker, 1985, p. 12) applied by the use of the HEC-RAS model (Section 5.3) the application of this method is forsaken. 5.1.3 Data from the Altai Mountains As a paleostage indicator of the flood along Chuja and Katun valleys, the surfaces of the giant bars are suitable. Due to the assumed different depositional process, the run-up sediments are excluded (cf. Section 5.2). The locations of the bars and drawdown levels are illustrated in Figure 39. The points with suspension gravels below the bed-load terrace surface indicate that this level is deposited later during the flood. For the estimation of the maximum discharge of the flood, it might therefore be assumed that the valleys were clear of sediments down to the current water level of the rivers. For some of the drawdown levels along the slopes of the bars, this might not hold true. The point of time of bed-load terrace level formation cannot be determined, rendering the depth of flow during all stages of the flood uncertain.

Q = A n–1 R 2/3 S 1/2 where Q is the discharge, and the other variables are as above. Applying the Manning formula and other uniform flow equations, flow velocities for a discrete point can be calculated. This method is called the conveyance-slope method (Barnes and Davidian, 1978; Cook, 1987). The so-called slope-area method is based on the Manning formula and allows an energy-balanced calculation of discharge along a channel reach (Chow, 1959, p. 146f.; Barnes and Davidian, 1978, p. 156f.; Cook, 1987, p. 34f.). For at least two cross sections with known water levels, the discharge for an assumed flow is calculated. For this discharge, the velocity head between the two profiles can be determined and considered for energy grade line slope between the two sections. A second discharge is calculated based on this slope, and the improved velocity head is regarded. This iterative solution is continued until the assumed and calculated discharge merge. Chow (1959, p. 147) and Baker (1973a, p. 17f.) give details of the procedure of computation,

5.1.4 Paleohydraulic Calculations Uniform flow equations such as the Manning formula and the slope-area method are intensively applied to calculate discharges, especially for creeks and rivers in remote areas and to estimate peak discharges for limited observed flood events. Mainly in the United States, it was the favorite method for decades (cf. numerous references, e.g., Baker, 1987; Jarrett, 1984, 1987). For the estimation of peak discharges of the Pleistocene Lake Missoula flood, Bretz (1925) and Pardee (1942) applied the uniform flow equation after Chezy, mainly because no other suitable methods were available. By the application of the slopearea method for the Lake Missoula flood, Baker (1973) determined a value that was later assumed to overestimate peak discharge by ~30% (Baker and Bunker, 1985, p. 12). Nevertheless, at least for a first approximation of the magnitude of the flood in the Altai Mountains, the Manning equation will be suitable if the calculated values are interpreted carefully.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

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Figure 39. Location and elevation of bars along Chuja and Katun valleys for uniform flow calculation. The connection along the highest bar surface levels is a best-fit line by eye. While the slope is similar to the recent mean valley slope in Chuja valley, in Katun valley a steeper slope is estimated. Note that this slope is determined in Katun valley by two points only. The bars used to estimate the flow velocity and discharge are marked by black arrows.

Flow velocities and discharges are estimated for six of the highest bar surfaces along Chuja and Katun valleys (cf. Fig. 39). Two values for the slope S are tested: the slope of the current valley (6.0‰ and 2.2‰) and the slope of the connection between the bar surfaces (6.1‰ and 4.3‰), which makes a difference in Katun valley only. Strictly speaking, for Katun valley the calculations for the steeper slope are in contradiction to the presumption of uniform flow, as the slope of the water surface and slope of the valley bottom are not parallel. As the conditions of the valley are uncertain for the different stages of the flood, this inaccuracy might be acceptable and could be considered as gradually varied slope. The cross-sectional area A and wetted perimeter P are determined from topographic maps in order to determine the hydraulic radius R. Several bars considered in this calculation are located >1 km inside tributary valleys. Considering this location of the bar by determination of the cross-sectional area would lead to an enormous overestimation. Like for the HEC-RAS modeling (Section 5.3.3), these ineffective areas of flow are excluded by modeling an imagined vertical wall on this side of the valley’s cross section, reaching from the last representative point up to the elevation of the bar surface. By this modification, the error of a systematic overestimation of the cross-sectional area can be eliminated. The roughness coefficient n is difficult to estimate, as all guidelines are developed for floods of river channel scale, a significantly smaller dimension than the valley-filling floods along Chuja and Katun valleys. Experiences can be transferred from previous studies on floods of a comparable magnitude. Interpretation of these investigations came out in an estimated mean

value of n = 0.04, also applied for the step-backwater calculations by the HEC-RAS model (cf. Section 5.3.4.3). To test the sensitivity of the estimated value additionally a roughness coefficient of n = 0.07 is considered. Parameter values for the calculations for different bar surfaces and related flow velocities and discharges on the basis of equations 2 and 3 are listed in Table 5. To determine the conditions of flow, additionally the Froude number Fr is calculated. The results of the calculation of flow velocity and discharge by the Manning formula indicate sensitivity on the estimated roughness coefficient n. For the lower values of n = 0.04, occasionally supercritical conditions of flow are reached as Fr is slightly larger than 1.0. In the less steep Katun valley, critical flow conditions are reached for the steeper value for the slope derived from the connection of the surfaces of the bars. As the bars are not located in sections of valley constrictions, and supercritical conditions of flow are not plausible over a longer distance along the valley (Jarrett, 1984; O’Connor and Webb, 1988; O’Connor, 1993), this result might be seen as an indicator for a more plausible value of n = 0.07. Calculated flow velocities for similar slopes are in a close range within Chuja and Katun valleys, respectively. On the basis of n = 0.07, a mean flow velocity of ~33 m/s can be estimated for Chuja valley and slightly less in Katun valley due to the gentler slope. The variety of calculated discharges increases due different cross-sectional areas with a range of 216,000 m2 up to 358,000 m2. For Chuja valley, a mean discharge of 9.2 × 106 m3/s can be estimated, while for Katun valley, the calculated mean discharge decreases to 7.8 × 106 m3/s for the slope indicated by the surface of the bars. This difference is less significant than it

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might appear, because for Katun valley only two bar surfaces are considered, and one of them is located at the confluence of Chuja and Katun Rivers. Averaging the calculated values along both valleys, the mean flow velocity and discharge can be estimated as v ≈ 31 m/s and Q ≈ 8.7 × 106 m3/s, with a mean deviation of ~13% for velocity and ~25% for discharge. 5.1.5 Discussion To estimate the magnitude of the flood by the calculation of a mean flow velocity using Manning’s formula, the problem of systematic overestimation of the cross-sectional area has been solved by modeling a vertical wall at locations where the bars used as paleostage indicators are located inside tributary valleys. Still critical is the necessary assumption of the roughness coefficient, as it significantly influences calculated flow velocities. Although, the value of n = 0.07 is an assumption, it appears plausible in a sensitivity analysis by calculating flow conditions. Assuming the water level being identical with the surface of the bars might appear as a source of significant error, too. On the other hand, the range of 25% for modeled discharges for the different locations is larger than the underestimation of depth of flow by the assumption, which is quantified to influence the calculated discharge by <20% (Kochel et al., 1982; Baker, 1987). Even if the variability of the calculated discharge is within a satisfying range for estimating the magnitude of the flood, it

should be noted that a minimum number of locations is desired to minimize error derived from uncertain representative character of single locations. The narrow range of calculated flow velocities indicates that this presumption is fulfilled. Principally, such calculations are possible for all paleostage indicators illustrated in Figure 39. As the connection of the different levels along the flood’s pathway cannot be estimated and especially their position within the flood’s hydrograph is uncertain, this approach is not considered further. 5.2 Flow Calculation by HEC-RAS 5.2.1 Introduction Quantitative modeling of the outburst floods in Chuja valley could be carried out by three different kinds of computersupported models: detailed physically based outburst models, general dam failure models, and hydraulic calculation models for general channel flow. Detailed physically based models of ice-dammed lake outburst floods consider individual features of the glacier and lake basin influencing the scale and characteristics of the outburst floods. For ice-dammed lakes, models are developed, for example, by Spring and Hutter (1981), Clarke (1982), and Walder and Costa (1996) and were applied on volcanically triggered jökulhlaups in Iceland (Spring and Hutter, 1981) as well as recent outburst floods in Alaska (Clarke, 1982; Walder and

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Costa, 1996) and Canada (Clarke and Waldron, 1984; Flowers and Clarke, 2000) and even the Pleistocene flood draining Lake Missoula (Clarke et al., 1984). Development and application of these kinds of models require solid experience in hydraulics and glacier physics and is additionally limited by available data. While several assumptions on ice conditions and outburst mechanism must be made, their application is limited to selected wellstudied examples (e.g., Walder and Costa, 1996, p. 715). As the knowledge about the ice dam in Chuja valley is limited at present and no general available software packages can be used, it is not possible to use this kind of model within this study. Models for the simulation of floods resulting from dam failure are developed frequently, as this is a serious problem for engineers being responsible for the safety of constructed earthen or concrete dams. An overview of early approaches is given by Rajar (1978) and Fread (1991). The U.S. National Weather Service developed several continuously updated versions of the models BREACH (Fread, 1991), DAMBRK (Fread, 1984), SMPDBK (Fread et al., 1991), and the current version of FLDWAV (Fread and Lewis, 1998), which replaces all of the previous models. While the mentioned models are used most frequently, additional software is mentioned and compared for validity by Wurbs (1987). These models were applied to model the floods from failed constructed and natural dams (e.g., Carling and Glaister, 1987), and even from ice-dammed lakes (Fernández et al., 1991). Like for the detailed models mentioned above, a critical aspect of their application on the Pleistocene outburst flood in the Altai Mountains is the assumption of several parameters, for example, the time considered for complete breach development. This parameter is elementary as it controls the size of the breach area during a certain point of time ruling the form of the unsteady outburst flood wave. Any kind of assumption must be calibrated, under ideal conditions in the identical catchment for floods of comparable scale. This is impossible for the large-scale jökulhlaup in the Altai Mountains. Uncontrolled tests cannot give any information, as only speculations are possible for interpretation of the flood wave derived from assumed triggering parameters. Several hydraulic calculation models are used to estimate discharges of paleofloods from paleostage indicators such as, for example, slack-water deposits, silt and debris lines, impact scars, and scour lines. Most frequently applied are models based on the step-backwater method (O’Connor and Webb, 1988), especially different versions of HEC-2 by the Hydrologic Engineering Center of the U.S. Army Corps of Engineers (HEC, 1985). This model was developed to determine water level and several hydraulic parameters for a given discharge for a channel with known geometry. In paleohydrological applications, discharge as input variable is iteratively improved until the modeled water level fits with the paleostage indicators. The main advantage of applying of these kinds of models is the amount of flow energy losses associated with variations in geometry and roughness along a channel, while, for example, the Manning equation can only give information for a single cross section. The current version of the model HEC-RAS 3.0 (Hydrologic Engineering Cen-

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ter—River Analysis System) (Brunner, 2001a, 2001b) is used in this study to estimate discharge and hydraulic parameters of the floods along Chuja and Katun valleys. 5.2.2 Hydraulics HEC-RAS allows one-dimensional steady- and unsteadyflow river hydraulics calculations under sub- and supercritical conditions and supersedes the previous HEC-2 software package (Brunner, 2001b). The basic computational procedure is based on the solution of the one-dimensional energy equation. Energy losses are evaluated by friction (Manning equation) and contraction or expansion by coefficients multiplied by the change in velocity head. The momentum equation is applied in situations where the water surface profile varies rapidly, including mixed flow regime calculations with hydraulic jumps, hydraulics of bridges, and profiles at river confluences. As the channel is divided into short reaches and the computation is carried out step-by-step from one cross section to the next regarding the energy loss for the determination of the water level, it is a classical step method (cf. Chow, 1959, p. 262f.). The general one-dimensional energy equation is written as

where y1 and y2 are depths of water at cross sections, z1 and z2 are elevations of the main channel at cross sections, v1 and v2 are mean velocities at cross sections, α1 and α2 are energy coefficients at cross sections regarding the uneven distribution of velocities over a cross section, g is the acceleration of gravity, and he is the energy head loss. Figure 40 illustrates the terms of the equation.

Figure 40. Representation of terms of the energy equation for flow between two cross sections (after Brunner, 2001b, Fig. 2.1 therein, modified).

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The energy head loss he between two cross sections is composed of friction losses in addition to contraction or expansion losses. The equation for energy head loss can be expressed as

where L is the reach length, Sf is the friction slope between two sections, and C is the expansion or contraction loss coefficient. The friction slope is determined by the Manning equation, which can be written for metric units and transformed to determine Sf as

where n is Manning’s roughness coefficient, and R is the hydraulic radius. Note that these equations are simplified variants of the equations used in the model. As weighting elements within cross sections can be considered by HEC-RAS, the equations given above differ from the expressions given by Brunner (2001b). A brief overview on the theory of hydraulic modeling is given by O’Connor and Webb (1988), while detailed background is presented, for example, by Chow (1959). For the application of the model, the user must give information on the channel geometry, the channel characteristics such as Manning’s roughness coefficient n, the contraction and expansion coefficients (summarized in C in the equations above), and an initial stage of the water surface or discharge. The unknown water surface elevation at a cross section is determined by an iterative solution of the equations for energy balance and energy head loss. The computational procedure is as follows: first, assumption of a water surface elevation at the cross section of interest and determination of the corresponding conveyance and velocity head. With these values, the friction slope and energy head loss are calculated and the water level at the cross section of interest can be determined. This value is compared with the initial assumption and, if found to vary beyond a level of tolerance, recalculated. The level of tolerance has a default of 0.1 m, and the number of iterations is set to 20. The result can be characterized as “minimum error water surface” (Brunner, 2001b, p. 2–12). The determined energy grade line level is the quantitative basis for the calculation of the water level and additionally derived parameters such as flow velocity, discharge, shear stress, and others. HEC-RAS was developed for gradually varied flow. A warning is given if the energy head loss exceeds a default value, and the insertion of additional cross sections is suggested. For hydraulic jumps, where the flow situation is rapidly varying, the momentum equation is used. The functional form of the momentum equation used in HEC-RAS is given by the expression

where the variables are used as in the energy balance equation, and additionally Q1 and Q2 are discharges at cross sections, β1 and β2 are the momentum coefficients that account for a varying velocity distribution, A1 and A2 are cross-sectional areas, and S0 is the slope of the channel. For details on the varying application of this basic equation under different conditions, compare Brunner (2001b). The assumptions intrinsic to HEC-RAS’s way of modeling gradually varied one-dimensional flow requires the following presumptions of flow conditions and channel parameters (cf. O’Connor, 1993): • For steady flow conditions, the flow is steady enough for constant discharge to be of sufficient duration to have simultaneously affected the entire channel of the river. • Cross sections are spaced adequately to regard all variations in channel geometry (roughness, contraction, expansion, change of slope), so the flow conditions vary gradually from one section to the next. • The one-dimensional modeling requires flow perpendicular to the cross sections. Expansions and contractions of the valley might involve knickpoints within the cross section to achieve this requirement, depending on the scale of the channel. Consequently, areas of ineffective flow in downstream directions, such as tributary mouths where flow separation and development of eddies can be assumed, have to be excluded from the model channel. 5.2.3 Paleostage Indicators Paleostage indicators along Chuja and Katun valleys can be seen in the run-up sediments, the bar surfaces, and the overtopped bedrock ridges. They contain different information about water levels during the outburst floods (cf. Chapter 4). The run-up sediments indicate maximum water levels by the elevation of the thin layer of suspension gravels on the bedrock surfaces of the valley slopes above the valley bottom. Their deposition can be assumed during two different stages of the floods: (a) An initial peak discharge of short duration occurs immediately after the failure of the ice dam. This level might not have lasted long enough to form the larger bar. Also, it is imaginable that the slopes of the valley are too steep to allow the deposition of a solid bar. (b) As run-up sediments are found only in alcoves of slopes at the outer bank at valley bends or on floodexposed slopes in tributary valleys, they might also be regarded as indicators of the bow wave of a flow reaching the front of an obstacle (cf. Fig. 76 in the section on obstacle marks). Hence, they indicate the minimum higher elevation of the energy grade line of flow. The velocity head of the flow leads to a local rise of the water level, but the mean water level is below the deposited suspension load (cf. chapter on run-up sediments). The bar surfaces and heights of the overtopped bedrock ridges both indicate minimum water levels. The top of the bar surfaces must have been below the water surface to allow deposition of the suspension load to form bars up to the final height.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia This water level must have lasted for a time sufficient to form the bar. The bedrock ridges at the confluence of the main valleys with tributaries indicate occasionally a water level above their highest crests by scour phenomena of the bars downstream of the ridges. While the flow was running over the crests, a hydraulic jump was formed leading to a high-turbulence zone immediately downstream where the flow energy was too high for the deposition of the transported suspension gravels. As the depth of the current over the ridges cannot be estimated, the height of the ridges is a minimum level of the flood. An overview on the locations and height of the bars and run-up sediments was already given in Chapter 4. A list of the locations and their characteristics is in Table A1. Cross sections are derived from topographic maps in the scale of 1:50,000, as no other sufficient source of geometric data of the valleys is available; the data are adopted from Agatz (2002). The flood is modeled along Chuja and Katun valleys from the area of the former ice dam near the village of Yarbalyk down to the confluence of Katun and Big Ilgumen Rivers. Two hundred forty-four cross sections for a distance of 84.8 km were measured. To accomplish the presumption of gradually varied flow, the modeled reaches of the valleys must be relatively homogenous. Hence, three units are separated and modeled independently, because clear changes in valley characteristics require this: • the broad and less steep Katun valley up to the confluence with Chuja River (valley km 0–30; 2.2‰) • the straight and relatively steep lower part of Chuja valley (valley km 30–44; 6.0‰) • the winding upper part of Chuja valley (valley km 44–85; 6.0‰) The area of the confluence itself is left out of modeling as the conditions of flow change abruptly in this section. (Tests by the model confirmed later the impossibility of finding model parameters producing a flow confirming paleostage indicators up- and downstream of the confluence in a combined model run.) The cross sections are located at each significant change of valley conditions determined by eye. They are numbered from the downstream to the upstream border of the modeled valleys. Narrowing and widening of the valley derived from contour lines of the maps are marked as knickpoints within the profiles to conserve the rectangular orientation of the cross sections to the contours. Areas of ineffective flow are determined by large widening of the valley’s cross section regarding the maximum level of flow indicated by run-up sediments. These areas are separated by a continuous straight line connecting locations of mean valley width up- and downstream, a method established previously by Jarrett and Malde (1987) and O’Connor (1993). This modification has been for 77 of the 244 cross sections. The areas of ineffective flow are not taken into account for hydraulic calculations. Reaches with extended ineffective areas of flow and those with current landslides or other significant slope erosion phenomena are excluded as locations of cross sections. It is assumed that for

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the chosen measured cross sections, the postflood modifications by erosional or depositional processes is negligible. For the example of the lower reach of Chuja valley, the locations of cross sections, their knickpoints, and the separation of ineffective areas of flow are illustrated in Figure 41. The giant bars in Katun valley cause another problem for the estimation of paleoflow cross-sectional areas derived from current topography. Their suspension gravels fill parts of the previously open valley and lead to an assumed smaller cross-sectional area than it originally was during the initial stage of the flood. Considering them as part of the valley cross section would lead to an underestimation of the peak discharge due to a decreased cross-sectional area. On the other hand, sedimentological analysis and some datings suggest that during the repeated floods through Katun valley, the bars were not eroded completely (cf. Chapter 4). The amount of reworked gravel and the modification of the bar topography during a subsequent flood flow is unknown. Also, the bedrock topography underneath the giant bars has not been investigated yet. This problem is overcome by a compositional solution: The cross sections at areas of the extended giant bars especially in Katun valley are modeled as linear surfaces reaching from the bottom of the bars toward the inner channel up to the upper end of the bars at the contact between the bars and the surface of the bedrock of the valley slope. This solution is exemplarily illustrated in Figure 42. As exemplified in Figure 42, the lateral extension of the bed-load terrace and the bedrock morphology in the deepest parts of the valley are also unknown. From several locations in Katun valley it its known that the suspension gravels are found below this terrace level. Hence, it can be assumed that during the peak discharge of the flood, previously deposited sediments were cleaned out from the valley bottom, because the highest shear stress occurred in the central section of the channel. The refill took place later during the flood, and for example, the gravel dunes between the villages of Little Jaloman and Inja were formed. To be able to model the maximum discharge of the flood, the valley bottom is assumed to be uncovered with sediments, leading to a larger cross-sectional area. 5.2.4 Paleohydraulic Calculation In addition to the aspects of paleostage indicators from Chuja and Katun valleys and the mentioned problems with the cross sections at giant bar locations, many different aspects of modeling have to be considered before individual hydraulic calculations can be carried out. Experience of previous application of comparable hydraulic calculation software, especially the estimation of coefficients, is documented first. Also, earlier calculations have been carried out and should be discussed in detail. As a consequence, this chapter needs further differentiation into subchapters. 5.2.4.1 Previous water level calculations of Pleistocene outburst floods. The importance of computer models for paleo-

Figure 41. Location of cross sections along the lower Chuja valley (after Agatz, 2002, Fig. 20 therein, modified). The numbers of the cross sections along the mean valley axis are counted from down- to upstream. The maximum level of flow, indicated by the run-up sediments, is marked along the contour level by a dashed line. The areas of ineffective flow at significant expansions of the valley are separated by a line estimated by eye. Grid lines are 1 km for scale.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

Figure 42. Modeled cross section and problems of its determination.

hydrological studies is emphasized by Baker (1998). HEC-2 is used frequently for the estimation of paleofloods of different scales and varying local conditions such as the Grand Canyon (O’Connor et al., 1994) and the British Uplands (Carling and Grodek, 1994), presently arid and semiarid areas (Ely and Baker, 1985; O’Connor et al., 1986; Partridge and Baker, 1987; Webb et al., 1988; Greenbaum et al., 2000), glacial floods such as the outburst of Lake Bonneville (O’Connor, 1993) and Lake Missoula (Craig, 1987; O’Connor and Baker, 1992; Benito, 1997), and even for the ice-dammed lake in Chuja valley (Baker et al., 1993; Agatz, 2002). A closer look at the modeling of outburst floods from the glacial Lake Missoula, Lake Bonneville, and Chuja Lake is useful, because these modeled flows can be compared by range of scale with the flood along Chuja and Katun valleys. In the context of this chapter, a focus is laid on the modeling parameters used and on the experiences of previous users of HEC-2. The preceding paleohydraulic calculation for Chuja valley by Baker et al. (1993) and Agatz (2002) is also compared, considering local conditions and general assumptions. Due to the complex topography of the flood’s pathway related to the drainage of Lake Missoula with narrow sections, flow separations, and areas of temporal ponding, hydraulic modeling must be carried out for specific locations, and the results cannot be compared directly. Unfortunately, Craig (1987) and Baker et al. (1993) give no information of the used modeling parameters, in this case the values of Manning’s n and the contraction and expansion coefficients c and e, summarized as C in the energy head loss equation above (Table 6). All previous users of HEC-2 or HEC-RAS listed in Table 6 agree that varying Manning’s roughness coefficient n is of minor influence for the modeled water level. This could also be confirmed by Ely and Baker (1985) and other references quoted therein for relatively small floods. The users chose different ways of estimating Manning’s roughness coefficient. While Jarrett and Malde (1987), O’Connor (1993), O’Connor and Baker (1992), and Benito (1997) derive values from experience on smallerscale floods and use empirical relations such as the equation by Limerinos (1970), Agatz (2002) includes this value into her iterative solution to find the best-fit value by eye. The second

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approach appears plausible, because no experiences based on measurements such as normal-scale channels are available, as previously noted by O’Connor and Baker (1992, p. 268) and O’Connor (1993, p. 15). Regarding the size of channel bed sediments, estimation of the roughness coefficient (Limerinos, 1970) appears a vain attempt, given that the depth of flow is on the order of 102 m. However, as illustrated in Table 6, the estimated values of Manning’s n for the main channel flow vary between 0.03 and 0.05 and are assumed to increase at local obstacles only. By considering the weak influence of this coefficient on flows of large magnitude, the variety and different chosen ways are of minor importance for modeling a large-scale jökulhlaup. The contraction and expansion coefficients c and e have to be estimated in all cases. Previous applications containing sensitivity analysis reveal typical values of 0 < c < 0.3 and 0.3 < e < 0.7. Considering the interpretation given by Brunner (2001b) for river-channel-scale flow, the energy loss effects of narrowing and widening of valley-scale flow can be compared to the effect of typical bridge constructions in smaller scale. Expansions that might be characterized as “abrupt” are excluded in most cases, because ineffective areas of flow are excluded from modeling. By consideration of different values of the coefficients, O’Connor (1993, p. 15) found an uncertainty for his modeled results for the Lake Bonneville flood of generally <25%. In the studies listed in Table 6, different models are used to estimate paleoflood characteristics. O’Connor (1993, p. 29) characterizes the model J 635 (Shearman, 1976) used by Jarrett and Malde (1987) as being comparable with HEC-2, because of the identical calculation method of step-backwater. Even while Brunner (2001b, Appendix C therein) emphasizes that the HECRAS software differs significantly from the superseded HEC-2 package, no differences of the two computer programs are mentioned that prevent a comparison derived by the two computer programs in the context of Table 6 and this study. 5.2.4.2 Previous water profile calculations for the flood in the Altai Mountains. Baker et al. (1993) have used HEC-2 for a first estimation of the discharge of the outburst flood in Chuja valley. They have modeled the river reach at the inlet to a gorge section of the valley south of Aktash. Seven cross sections are derived from topographic maps in the scale of 1:50,000 (Rudoy, 2002, p. 137, mentions a scale of the maps of 1:25,000) and additionally ten cross sections were interpolated due to a complex topography of the area by a method not mentioned. Locations of spillways and gravel dunes are used as paleostage indicators (Fig. 43). They calculated a discharge of at least 18 × 106 m3/s with a depth of flow of ~400 m and determined a hydraulic jump in the upper part of Chuja Gorge, where the flow conditions changed from sub- to supercritical conditions. This hydraulic jump is caused by the prominent flow constriction of the gorge section of the valley in combination with a significant knickpoint of the valley slope. An abrupt failure of the entire ice dam, consisting of glacier tongues from Modjoi valley (also transcripted as Mazhoj

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

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Figure 43. Location of modeled jökulhlaup through Chuja Gorge and calculated water surface profiles by Baker et al., 1993 (modified after Baker et al., 1993, Figs. 1c and 3).

or Mashej valley) and in the dry valley southeast of Aktash, is assumed. Some aspects of the modeling by Baker et al. (1993) appear worth drawing attention to. The chosen location for the paleodischarge calculation is doubtful, because a closer look at the area reveals that the dimension of the ice dam was underestimated. It is not plausible that an ice dam of a height of at least 650 m, indicated by the altitude of the recent valley bottom at ~1450 m and the altitude of lake sediments in Chuja Basin up to 2100 m, only covers a small area at the confluence of the current Chuja and Mashej valleys (Fig. 12). Our investigations in the area lead to the assumption that the Pleistocene ice dam extended from the area around the inlet into Chuja Gorge down to the village of Jarbalyk over a distance of ~15 km. With a minimum thickness of 650 m, the whole area in between was ice-covered, leading to an estimated ice fill of Chuja Gorge. Even if no evidence is given about the previous extension of the ice dam, the flow modeled by Baker et al. (1993) cuts across the area of the ice dam itself over a distinct length. In consequence, the assumption of a completely ice-free and unblocked area downstream of the inlet into Chuja Gorge inherent to the modeled channel reach appears critical. On the other hand, no obvious facts and evidence of the erroneous character of this indirect assumption can be given, and therefore the frequently quoted value of the peak discharge of the outburst flood might be justified. Also, the missing paleostage indicators downstream of the calculated hydraulic jump could be seen as critical, because the validation of the use of HEC-2 for a large-scale flood with rapidly varying flow conditions from one cross section to the next is not sure. It would have been helpful to verify the calculated water levels by additional paleostage indicators. But when Baker et al. (1993) carried out their investigations, no additional data from

the surroundings were available. The next paleostage indicators were found ~20 km downstream, beyond the extension of the ice dam assumed in this study. Agatz (2002) calculated water profiles for Chuja and Katun valleys by HEC-RAS and used run-up sediments and bar surfaces as paleostage indicators. The method is principally similar to that described in Section 5.2.3, except that the overtopped ridges indicating paleostages of the water surface are left out. She determined the water levels between run-up sediments and bar surfaces for Katun, lower Chuja, and upper Chuja valleys separately and searched iteratively for the best-fitting values for the coefficients by eye. In Chuja valley, the flow conditions are assumed to be supercritical throughout the valley. The background for this hypothesis is the assumed abrupt failure of the ice dam at the upper end of the modeled reach. A giant initial flood wave is thought to run through the dry valley with a water level indicated by the run-up sediments. A discharge of 20.5 × 106 m3/s results in a sufficient height of the longitudinal water level profile, and the coefficients n, c, and e are iteratively modified until the best fit by eye of the undulated water surface with the paleostage indicators is found (n = 0.05, c = 0.0, and e = 0.5). For the upper Chuja valley the same discharge results in the indicated height of the water surface, but the coefficients have to be modified (n = 0.03, c = 0.05, and e = 0.1). For a discharge similar to the values calculated for Chuja valley, in Katun valley most run-up sediments are found to be submerged or are located high above the calculated water level profile for 20.5 × 106 m3/s at supercritical conditions of flow (Agatz, 2002, p. 42f.). This finding cannot be modified by adapting the coefficients. Agatz dismisses the possibility of a larger flood through Katun valley, because of missing indica-

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tors of a higher water level in Chuja valley. According to Agatz, the reason for a progressive lowering of the discharge of the initial flood wave is due to the broadening of Katun valley, in contrast to the narrow Chuja valley and the cumulative effects of water being able to enter temporary storage in the backflooded side valleys, such as the Big and Little Jaloman and Inja valleys, found throughout the Chuja-Katun River system. The flow could have changed to subcritical conditions in Katun valley, because of the gentler slopes of Katun valley and its

alignment normal to Chuja valley generating a hydraulic rise at the confluence area. Unfortunately, the storage capacity of the tributary valleys and Katun valley upstream of the confluence for an assumed water level has not been estimated. For subcritical flow conditions in Katun valley, the maximum possible discharge resulting in a water level that reaches the highest run-up sediments, a discharge of 10 × 106 m3/s, is calculated, and coefficients are determined as n = 0.04, c = 0.1, and e = 0.3 (Fig. 44).

Figure 44. Water surfaces profiles for Chuja and Katun valleys calculated by Agatz (2002) (modified after Agatz, 2002, Figs. 27, 29, and 32).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Strong oscillations of >100 m are computed for supercritical conditions of flow in Chuja valley. For the straight lower Chuja valley, the iteratively estimated expansion coefficient e is higher than for the curved reach upstream. Also, the roughness coefficient is determined to be larger. It must be considered that the solution by Agatz (2002) is determined iteratively and therefore cannot be interpreted on the basis of the channel conditions. For supercritical flow conditions, Brunner (2001b) comments that high coefficients of c and e result in a strong oscillation of the computed water surface. For river-channel-scale flow he limits the range of these coefficients to c < 0.1 and e < 0.2 (Table 6) but probably did not consider the highly energetic current environment of an ice-dammed lake outburst flood. Trieste (1992) draws attention to the question of dominant supercritical flow in high-gradient channels. He found that supercritical conditions may occur for short distances and normally change back to subcritical flow because of extreme energy dissipation by hydraulic jumps, turbulence, and obstructions. Thus, even large flows in steep natural channel reaches usually alternate between supercritical and subcritical, a mixed flow regime. On the other hand, he did not exclude dominant supercritical flow conditions “… in unusual situations…” (Trieste, 1992, p. 1117), and a mountain valley with a mean slope of channel bed of 6‰ located downstream of a failed dam draining a lake of ~650 m depth instantaneously might be seen as one. More critical is the assumed retention effect reducing the discharge of 20.5 × 106 m3/s in Chuja valley to 10 × 106 m3/s in Katun valley by ponding mainly in Katun valley upstream of the confluence with Chuja River and, additionally, in the tributaries along the modeled valley reach. A rough estimation of the storage capacity of Katun valley upstream of the confluence for an assumed water level of 1000 m gives a volume of the valley according to the recent topography of ~9.4 × 109 m3 (volume derived from 1:50,000 topographic maps). For the supercritical discharge bisected at the confluence, it would have taken ~16 min to fill Katun valley. The remaining flow might additionally be partly reduced by ponding in the tributaries of Inja, Little Jaloman, and Big Jaloman Rivers (cumulative storage capacity of ~5 × 109 m3 for a water level of 1000 m). For the assumption that the supercritical peak discharge did not last longer than 16 min, the explanation by Agatz (2002) for the bisected discharge in Katun valley might be seen as acceptable. On the other hand, the flow from the ice-dammed lake must decrease immediately to 106 m3/s after this short period of time to fit to the computed water level in Katun valley, where no retention capacity would have remained. Even if jökulhlaups of instantaneous dam failures are known to show steep hydrographs, these unsteady dynamics seem to be very abrupt. Within 16 min at a discharge of 20.5 × 106 m3/s a volume of ~19 km3 would be drained from the lake in Chuja valley. For an estimated volume of the lake of 607 km3, this equals 3% of the stored volume. For the unrealistic hypothetical condition of a permanent discharge of 10 × 106 m3/s, the drainage of the ice-dammed lake would have taken

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~16 h only. Clearly, an unsteady flow simulation will be required in the future to estimate the flood duration. Another explanation for the computed higher discharge in Katun valley compared to Chuja valley for supercritical conditions can be seen in another source of the flood. Previously, Butvilovsky (1993) and Rudoy (1998, 2002) mentioned icedammed lakes in Katun catchment upstream of the confluence with Chuja River. Especially Lake Uimon and Lake Abay in the upper Katun catchment and Lakes Jassater, Tarkhat, and Bertek in the catchment of Argut River, a tributary of Katun River, might be regarded as sources of additional outburst floods not running through Chuja valley (cf. Chapter 4 for details). Evidence for these lakes could not be verified yet. Glacial lake outburst features previously mentioned by Butvilovsky and Rudoy could not be confirmed by Carling et al. (2002). Therefore, the possibility of additional jökulhlaup pathways in the Altai Mountains cannot be considered in detail at the current state of proven knowledge. In any case, continuous supercritical flow conditions in the wide and gently sloped Katun valley are of limited plausibility, especially as there would also be a backwater effect where the Katun valley turns sharply into a narrow gorge at the junction to the Big Ilgumen River. 5.2.4.3 Calculations for mixed flow regime. As a consequence of the discussion of previous hydraulic calculations mentioned above, the conditions of flow are assumed to be a mixed flow regime. Depending on variations between the cross sections, the current might change locally from sub- to supercritical flow and vice versa. For the HEC-RAS calculations, this assumption minimizes complications if occasionally supercritical conditions of flow occur. In a manner similar to Benito (1997), locations of critical or even supercritical conditions are checked for plausibility. Based on experience from previous studies (Table 6), the coefficients are n = 0.04, c = 0.2, and e = 0.4 throughout the three separately calculated reaches. These values are in the range of plausibility. “Critical depth” is used as a boundary condition for the steady flow modeling. It might be seen as a challenge to make use of the ability of HEC-RAS to route unsteady flow through the valleys of Chuja and Katun Rivers. For Lake Missoula an initial dynamic unsteady flood wave is assumed (Craig, 1987; O’Connor and Baker, 1992), which without any doubt must have been the case for the investigated outburst flood, too. Problematic is the unknown hydrograph of the flood resulting from the dam failure. As mentioned before, even the geometry and extension of the ice dam are not definitely known or are at least assumed differently. Therefore, modeling an outburst flood through a dam based on assumptions only to derive an initial hydrograph appears to be a speculative task. A steady flow is calculated by confirmation of the assumptions by O’Connor and Baker (1992, p. 274) that the well-developed paleostage indicators were formed during steady flow conditions after the passage of the initial flood wave. Modeling starts with the lower part of Chuja valley, reaching from the confluence with Katun River up to the part where a

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Figure 45. Water level profiles for lower Chuja valley calculated for mixed flow conditions. As mentioned before, the confluence area of Chuja and Katun Rivers had to be excluded from calculations due to rapidly varying flow conditions, which cannot be taken into account in HEC-RAS. Therefore, the profiles start nearly 2 km upstream of the confluence. Note that due to lateral extension of bars and run-up sediments, the correlations of oscillations of the water surface and location of paleostage indicators should not be interpreted in detail.

stronger curvature of the valley influenced flow conditions (about valley km 30–44). This reach of the valley is chosen as a reference section, because of the straight and smooth channel, minimizing problems of valley contraction and expansion (cf. Fig. 41). In Figure 45, longitudinal water level profiles for different discharges are illustrated. A minimum discharge of 10 × 106 m3/s is required to achieve a depth of flow overtopping the ridges at the downstream end of the calculated reach. For this water level elevation, the farthest downstream location of run-up sediments is already reached. The maximum water level surface is limited by run-up sediments and is reached for a discharge of ~12 × 106 m3/s. These simulated values for discharge cannot be compared with those of Agatz (2002) (Fig. 44) because different conditions of flow were assumed. Also, Agatz (2002) used an iterative way to find best-fitting values of the coefficients to modify oscillations of the water surface level to the locations of paleostage indicators. For a mean discharge within the range given above, 11 × 106 3 m /s, the following additional hydraulic parameters are calculated by HEC-RAS for mixed flow conditions (Table 7). For the upper Chuja valley, upstream of valley km 44 to the area of the former ice dam near the village of Jarbalyk, similar

water level calculations for mixed flow conditions returned a discharge between 9 and 10 × 106 m3/s (Fig. 46). The mean discharge of 11 × 106 m3/s from the reach downstream results in a water level surface above the level of the highest run-up sediments. To reach the height of the overtopped ridge, a minimum discharge of 9 × 106 m3/s for the assumed conditions of flow is required, while the elevation of run-up sediments limit it to ~10 × 106 m3/s. This maximum value for the upper Chuja valley is identical with the minimum discharge for the lower Chuja valley. Note that at the downstream end of the selected valley reach, the highest bar surfaces are reached. For a discharge of 10 × 106 m3/s, HEC-RAS models the following additional hydraulic parameters, calculated for mixed flow conditions (Table 8). A discussion on the cause of the slight discrepancy between the two reaches should consider calculations for the lowest reach of the investigated flood’s pathway in Katun valley (Fig. 47). The minimum discharge derived from the elevation of paleostage indicators of lower Chuja valley (10 × 106 m3/s) results in a calculated water level above the highest run-up sediments in Katun valley downstream. A plausible water level limited by the altitude of the run-up sediments is obtained by discharges between 8 × 106 m3/s and 9 × 106 m3/s. The value of

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Figure 46. Water level profiles for the upper Chuja valley calculated for mixed flow conditions. Note that due to lateral extension of bars and run-up sediments, the correlations of oscillations of the water surface and location of paleostage indicators should not be interpreted in detail.

Figure 47. Water level profiles for Katun valley modeled for mixed flow conditions. As mentioned before, the confluence area of Chuja and Katun Rivers had to be excluded from calculations due to rapidly varying flow conditions, which cannot be taken into account in HEC-RAS. Therefore, the profiles start nearly 2 km downstream of the confluence. A similar problem occurs at the downstream end, where the valley continues in the very narrow reach of a gorge and the drawn water level surfaces end farther upstream. Note that due to lateral extension of bars and run-up sediments, the correlations of oscillations of the water surface and location of paleostage indicators should not be interpreted in detail.

10 × 106 m3/s calculated for subcritical conditions for Katun valley by Agatz (2002) (cf. Fig. 44) cannot be reached due to higher energy loss coefficients c and e assumed in this calculation, compared to those determined iteratively by Agatz (2002). For a mean value of discharge of ~9 × 106 m3/s, HEC-RAS models the following additional hydraulic parameters for mixed flow conditions (Table 9). Sensitivity tests revealed that the assumed mixed flow regime is not critical to the simulations of HEC-RAS. As critical

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conditions are reached nowhere within the modeled reaches (cf. Tables 7–9), the program stays within calculation procedures for subcritical flow conditions. The modeled discharge for the lower Chuja valley is slightly higher than the maximum discharge for Katun valley and at the upper limit for upper Chuja valley. The difference is ~106 m3/s. Four different aspects could be considered to explain the discrepancy of the modeled discharges within the three different reaches. • Ponding of parts of the discharge at the confluence of Chuja and Katun valleys, and farther downstream within the reach of Katun valley, might be excluded to explain the decreased plausible discharge between Chuja and Katun valleys. If this effect is assumed to have a significant influence, it would already have occurred during the initial period of flow with the dynamic wave running down the valleys. All storage capacity would have been used up and no further volume would have been available for the following period of steady subcritical flow. On the other hand, the movement of the initial flood wave (wave celerity) might have been too fast to fill all upstream parts of tributary valleys. Therefore, it might be speculated that some volume in the tributaries and Katun valley upstream of the confluence still was available for retention effects during later stages of the flood. But this effect cannot explain the difference between the upper and the lower Chuja valley either. • The identical coefficients for roughness, contraction, and expansion for all reaches despite possible conditions could be regarded as a source of error. On the other hand, representing the different conditions of the valley reaches by varying energy loss coefficients would lead to the lowest values for the straight and relatively smooth part of lower Chuja valley. This would even increase the calculated differences, as the other two sections are somewhat more curved, and would obtain higher values for the coefficients leading to a reduced flow capacity, which is limited by the elevation of the paleostage indicators. • From the quantitative point of view, the calculated differences are not very large, especially considering that all given values are rounded estimations. They are obtained by fit by eye of the simulated water surface profiles, and the differences are within the uncertainty range for assumed coefficients of 25% provided by O’Connor (1993, p. 15). • Most plausible seems to be the explanation that the highest paleostage indicators are only assumed to belong to the same stage of the flood within the three reaches. As indicated by the run-up sediments in Katun valley (Fig. 46), the phenomenon of deposition of run-up sediments also occurred during lower stages of the flood. Otherwise it cannot be explained why this kind of deposit is to be found at elevations below the highest paleostage indicators. Even the highest water level markers within the sepa-

rated reaches, and especially from one part of the flood’s pathway to the next, do not necessarily belong to the same stage of the flood’s hydrograph. The tendency of paleostage indicators to mark lower water levels and related lower discharges in the upper Chuja valley in comparison to the lower reach of the valley can be explained by their location close to the former ice dam. During early stages of the flood after the failure of the ice dam, high-turbulence unstable flow conditions could be expected for the upper Chuja valley, caused by changing flow conditions from the basin-like character of the valley bottom upstream of Jarbalyk to the steeper Chuja valley. Additionally, parts of the valley still must have been filled by ice, which might have been transported partly into the narrow valley, leading to constantly changing cross-sectional areas in the valley, because of its melting and reworking. Under those environmental conditions, no steady water level might have developed over a period of time sufficient to form paleostage indicators. During later stages with declining discharge, the ice jam of the valley decreased, and the flow conditions became stable enough to deposit parts of the sediment load in lower elevations. For the lower values in Katun valley, it is more difficult to find an explanation. Parts of the difference might be seen in a ponding effect as discussed above. Also, the steeper upper parts of most sections of the valley might have had some influence. They are much steeper than the slopes below an altitude of ~1000 m and therefore have fewer locations for the deposition of run-up sediments of a higher water surface level. Due to postflood degradation of the slopes, this effect cannot be verified and remains speculative. Note that the >1 km wide bedload terrace in Katun valley is assumed to have formed after the simulated water level. Assuming the opposite would even decrease cross-sectional areas and result in lower calculated discharges for Katun valley. This terrace level also exists with a significant minor extension in the lower Chuja valley. Sensitivity analysis by Agatz (2002, personal commun.) revealed a negligible influence of the terrace level for Chuja valley but reduced the calculated discharges for Katun valley more than for the upstream reach of the flood’s pathway. 5.2.5 Discussion By paleostage indicators in Chuja and Katun valleys, a maximum discharge for the outburst flood of ~10 × 106 m3/s can be estimated for subcritical flow conditions. This average value considers calculations by Agatz (2002) and slightly different values for the separated reaches of the flood’s pathway. For supercritical conditions during the initial stage of the flood, Agatz (2002) estimated a possible peak discharge of 20.5 × 106 m3/s for Chuja valley. This value is in excess of the first estimation of 18 × 106 m3/s by Baker et al. (1993) from another location with limited water level markers, but also influenced by supercritical conditions of flow. For these higher estimations, evidence for a similar discharge downstream in Katun valley is missing. Preliminary estimations preserve skepticism about

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia a potential influence of retention effects by ponding in Katun valley upstream of the confluence with Chuja valley and in the tributary valleys farther downstream. Assuming subcritical conditions of flow is a conservative idea and appears more reliable. An advantage of the step-backwater method is the physically based simulation along a valley reach instead of interpretation of local evidence and transferring a derived value farther up and down (Carling et al., 2003). The assumption of the energy loss coefficients is less critical than might be expected, because for floods of very large scale, their potential error is of minor influence on the scale of the modeled discharge. Additional critical aspects for the application of HEC-RAS on the floods along Chuja and Katun valleys such as, for example, neglecting the hydraulic influence of sediment transport, bed level changes, and the only localized reflection of paleostage indicators of hydraulic effects are discussed by Carling et al. (2003). The authors come to the conclusion that it is imperative to model at the level of complexity for which data are available. With additional assumptions, it might be possible to increase this level, which indeed is desired. On the other hand, additional assumptions contain other sources of error; hence the postulated increase of accuracy must be carefully analyzed. But this is a difficult task, as data or experiences for calibration are limited. A potential problem is the assumed simultaneous genesis of paleostage indicators of comparable elevation. Different topographies of the valley slopes of the separately calculated valley reaches might influence the altitude of the highest paleostage indicators. This can lead to slightly different estimations of peak discharges within one valley. The knowledge of repeated outburst floods from draining and refilling ice-dammed lakes in Kuray and Chuja Basins makes this situation even more complex. As the different paleostage indicators cannot be related to specific jökulhlaups, they must be assumed to belong to one single flood event. 5.3 Velocity Head Calculations Using Run-up Sediments 5.3.1 Introduction Run-up sediments, previously described in Chapter 4, are found frequently along the valleys of Chuja and Katun Rivers. They are located at the outer banks of valley bends, at slopes of tributary valleys, and in alcoves in front of relatively small valley obstructions. This kind of fluvial deposit has not been described in the literature before. They indicate a level of the flood that is reached only in locations that were exposed toward the flood’s pathway. Therefore, they cannot be integrated into the group of slack-water deposits (e.g., Kochel and Baker, 1988; Baker and Kochel, 1988) such as the giant bars. They have not been deposited in backwater locations protected from the main current of the flow. Run-up sediments consist of a thin layer of suspension gravel covering the bedrock surface, only smoothing the surface topography but not forming a deposition

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of a thickness that modifies the local topography. A speculative approach of interpretation as postflood alluvial fan can be excluded because of the missing catchment area of the deposited sediments. At the current state of knowledge, run-up sediments are interpreted as indicators of locations where the flow reached a local obstruction and was forced to raise the water level due to the energy balance of flow. Their higher elevation indicates the minimum height of the energy grade line above the water level, as they must be deposited below or at this level. This rise of the water level can be compared with a bow wave in front of an obstacle such as a bridge pier. The current within this wave prevents the deposition of large amounts of suspension load; hence, no bar of relevant volume can be formed. The height of run-up sediments above the mean water level indicates the transfer of kinetic energy into potential energy. This height indicates the velocity of flow in front of the obstruction. As run-up sediments can be found in various elevations along the channel, they must have been deposited throughout the entire flood event. Hence, they only occasionally can be related to each other and do not belong to a specific stage of the flood. 5.3.2 Hydraulics Based on the energy equation after Bernoulli, total energy of flow is constant along the channel. The total energy of flow H consists of three elements:

where (y + z) = potential energy with y depth of flow and z elevation above datum ρ / (p g) = pressure energy with ρ density of water, p pressure, and g acceleration of gravity v2 / (2 g) = kinetic energy with v velocity of flow and g acceleration of gravity Due to the fact that all these elements are expressed by a unit of length, they are also called elevation head, pressure head, and velocity head and result in an energy head. For free surface flow, pressure energy is zero, which simplifies the equation to

This equation illustrates that in the case of sudden drop of velocity, all kinetic energy is transferred into potential energy, and the water level rises. Other energy losses such as heat or sound are neglected in this case (after Chow, 1959; Haan et al., 1993; Kay, 1998). Due to nonuniform distribution of velocity within open channel flow, an energy coefficient α can be introduced to calculate the change of height of the water level from total loss of kinetic energy (Chow, 1959, p. 27). This coefficient is also called velocity-head coefficient (Hulsing et al., 1966; Jarrett, 1984) or

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Coriolis coefficient (Chow, 1959, p. 27). The equation of the velocity head vh can be then written as

Values for the energy coefficient α are larger than unity, except for uniform flow. For known velocity distribution within a channel, α can be calculated (Chow, 1959, p. 28f.; Henderson, 1966, p. 19f.), otherwise it can be taken from experiences (Table 10). Generally speaking, the energy coefficient α is higher for small or steep channels and lower for large or flat streams of considerable depth (Chow, 1959, p. 27f.). Jarrett (1984, p. 1536) confirms this tendency using data for high-gradient streams and mentions a slight tendency for α to decrease with discharge and depth and to increase with channel roughness, slope, and particle size. Derived from experience, the effect of an increased velocity head vh is small compared with other uncertainties; therefore, α is often assumed to be unity (Chow, 1959, p. 28; Heinemann and Paul, 1998, p. 160 and 165), which means it can be neglected. Henderson (1966, p. 20f.) comments that values of α are sparse and not always consistent. Therefore, he neglects their application for single-channel flow. Since energy coefficients only represent second-order corrections, knowledge of experimental values appears insufficient to him. Also, Barnes and Davidian (1978, p. 159) suggest a value of α = 1 for flow in single channels. Based on this physical background, methods for measuring flow velocity have been developed. For flow in pipes, the well-known pitot tube is used to measure flow velocity. This tube was installed in a pipe to transform the pressure at the stagnation point at the inlet of the tube into a water level above. Its elevation above the mean water level indicates the velocity head (Kay, 1998). For open channel flow, the velocity-head rod was developed and has been found to measure flow velocity with

accuracy better than 10% (Wilm and Storey, 1944; Peterson and Cromwell, 1993). It is qualified as valuable especially for flow conditions with considerable sediment transport where common current meters cannot be used. On the other hand, the method is not reliable when applied to small-magnitude flows, as lower values of the velocity head are difficult to measure accurately. The velocity of flow v can be determined by a given velocity head vh using a simple transformation.

5.3.3 Run-up Sediments in Chuja and Katun Valleys The maximum elevation of the water level is given by the highest location of run-up sediments, indicating mean depth of flow y plus height of the velocity head vh. The velocity head itself can be quantified only for a given mean depth of flow or a mean undisturbed water level surface, which must be estimated in the case of the flow through Chuja and Katun valleys. The maximum possible height of the velocity head is assumed to be the difference in elevation of a run-up sediment and the highest bar surface nearby, which represents the minimum water elevation. This assumption implies that the run-up sediment and the related bar surface are deposited during the same stage of the flood. There is a tendency for overestimation of the velocity head by this assumption due to the unknown depth of flow above the bar surfaces. Therefore, additionally, an arbitrarily chosen elevation of the undisturbed mean water level is assumed to be half the distance between the highest bar surface nearby and the top of the run-up sediments. For these two heights of the velocity head, vh (bar) and vh (assumed), flow velocity is calculated and analyzed for plausibility. For this range of depth of flow above bar surfaces, the mean value for small-scale floods of 12%–25% is considered, however, to be influenced by local conditions (Jarrett and England, 2002).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Altitudes of bar surfaces and run-up sediments are surveyed along Chuja and Katun valleys. For this calculation, only locations of run-up sediments with bar surfaces nearby are chosen. Some locations of run-up sediments mentioned in the Appendix are excluded for this part of the study due to missing doubtless related bar surfaces nearby. Thirteen locations along Chuja and Katun valleys are found to meet the requirements. The locations and elevations of bars, run-up sediments, and the additional assumed water surface level are shown in Figure 48. Values for the velocity head vary for both conditions of mean water level in a broad range: 39 m < vh (bar) < 137 m and 19 m < vh (assumed) < 69 m. As velocity head is a channel-sidespecific indicator of local flow velocity during a specific stage of the flood, further statistics about the values are inconsequential. 5.3.4 Paleohydraulic Calculation The method to derive estimations for flow velocity from paleostage indicators, which are influenced by a bow wave in front of a local obstruction, has not been previously applied in paleohydrological studies. Costa (1984, p. 305) mentions mudlines on trees, hills, and canyon walls that could be interpreted as run-up indicators of mudflows and debris flows but does not carry out any further calculations. The energy coefficient α for the flow along Chuja and Katun valleys is assumed to be α = 1.3. Justifications for this assumption are taken from the literature (Table 10) for a current of considerable depth running through a moderately steep valley at

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high discharge. For the velocity heads shown in Figure 48, flow velocities for the two water levels can be estimated (Fig. 49). Flow velocities estimated from both water levels are within the expected range considering the magnitude of the flood as estimated previously by uniform flow calculation and HEC-RAS modeling. For vh (bar), flow velocities vary between 24 m/s and 45 m/s, and for the higher water level with vh (assumed), 17 m/s < v < 32 m/s are calculated. It is evident that, for the lower water levels near the surfaces of the bars, a higher kinetic energy is required to reach the run-up sediments by velocity head. These flow conditions of higher kinetic energy can be expressed with the Froude number. For lower water levels, Froude numbers occasionally >1.0 are derived: 0.48 < Fr < 1.17, and for higher water level, Froude numbers are determined as 0.32 < Fr < 0.69. The broad bed-load terrace filling the valley bottom is assumed to have been deposited up to the current thickness later. Therefore, the depth of flow to determine Froude numbers reaches from the current river channels up to the water level of the flood stage forming the run-up sediments. To achieve subcritical conditions of flow, the energy coefficient α must be increased to a value of α = 1.8, resulting in Froude number 0.40 < Fr < 0.99 for the lower water level and 0.28 < Fr < 0.58 for the higher one. For this value of the energy coefficient, flow velocities vary between 21 m/s and 39 m/s for the lower, and 15 m/s < v < 27 m/s for the higher water surface. None of these values appears critical, as all data are within the expected magnitude. This sensitivity analysis reveals that, con-

Figure 48. Locations of run-up sediments and bar surfaces indicating velocity heads along Chuja and Katun valleys. The maximum possible velocity head vh (bar) is limited by the difference in elevation of the run-up sediments and the bar surfaces. Its value is given in the figure. The velocity head for the assumed mean water level, vh (assumed), is half of this value.

Figure 49. Estimated mean flow velocities derived from velocity heads indicated by run-up sediments for two local water levels along Chuja and Katun valleys.

Figure 50. Locations of run-up sediments for the estimation of flow velocity by calculated velocity heads in Katun valley north of Big Jaloman River. Direction of flow of the flood was south to north. Note the extended areas of ineffective flow upstream of some locations, causing difficulties to determine the related crosssectional area of flow. Cutting these areas off and calculating the margin as vertical wall is an unsatisfying task, because the location of the run-up sediment would be excluded from the cross-sectional area. Grid lines are 1 km for scale.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia sidering the scale of the flood, the calculated flow velocities and Froude numbers are of lower sensitivity to modifications of the energy coefficient α. The required assumption of a value for α is not a critical aspect for the application of the method for largemagnitude floods. However, supercritical conditions of flow might have occurred at locations of valley obstructions. The calculation of discharge Q based on the continuity equation Q = v × A (with estimated flow velocity v) is occasionally a difficult task, due to problems of determination of the related cross-sectional area A. As some of the considered runup sediments are located at prominent valley obstructions with large ineffective areas of flow, the related cross-sectional area cannot be determined. For the locations from Katun valley, the five selected locations of run-up sediment with the bar surfaces nearby are illustrated in Figure 50. The cross-sectional areas can be derived from 1:50,000 topographic maps, and the discharge for the two different water levels is calculated (Table 11). For the determination of the cross-sectional areas, the narrowing of the valley by bars must be considered, while the lowest bed-load terrace is assumed to accumulate up to the current level during the final stage of the flood. The area below the lowest parts of the bars is assumed to be free of sediments with a triangular shape down to the current valley bottom.

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The calculated discharges are within the expected magnitude of the outburst flood. The small difference between discharges of higher and lower water level elevation is remarkable. The lower water level with the smaller associated cross-sectional area is compensated by higher flow velocities to reach the height of the run-up sediments from a lower water surface elevation. Only occasionally the flow velocity increases by an amount that results in a higher discharge for the lower water surface elevation. This effect might be influenced by steep valley slopes, which lead to a smaller decrease of cross-sectional area at a decreased water level than for valley sections with gentle slopes. On the other hand, the differences in many cases are within the range of accuracy, so it does not seem to be significant to assume the height of the water surface for the estimated discharge. Clearly, these conclusions require validation from surveyed flood events either of smaller measurable scale in natural channels or by flume experiments. 5.3.5 Discussion The method to estimate flow velocities resulting in discharges from investigated data of the velocity head seems to be a valid approach to determine the magnitude of a flood. The results are within the range of the expected values for the main stage of the flood forming the giant bars and run-up sediments of ~10 ×

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106 m3/s. The estimated parameters of energy coefficient α and surface of the undisturbed water level appear to have a minor impact on the estimated discharge. Depending on the local topography with extended areas of ineffective flow in tributary valleys, occasionally the determination of the related cross-sectional area is complicated and impedes the calculation of discharge from the estimated velocity of flow. Due to the nature of obstructions such as ridges at tributary confluences causing the water level to rise, the valley cross sections show a significant modification in width, which varies the cross-sectional area of flow for a given water surface elevation by several hundred percent. The roughness of the surface of the valley slopes might lead to an underestimation of the kinetic energy of the flow. Parts of the energy to raise the water level at the local obstructions might be dissipated to overcome the roughness of the obstruction’s surface. This effect might lead to a decreased elevation of the deposited suspension load indicating the height of the risen water surface in the presence of unquantified surface roughness. Unfortunately, the influence of this speculated effect cannot be determined. Validation of the method is highly desired to assess the accuracy. Wilm and Storey (1944) found errors for the application of the velocity-head rod method for the determination of flow velocity of <10%, but this value results from flows of much lower magnitude and partly from flume experiments. 5.4 Correlation of Lake Volume and Peak Discharge 5.4.1 Introduction Jökulhlaups typically occur in remote areas, where no gauge stations are installed to determine discharges. Usually, no data are available for locations of the outburst, so estimates are needed to predict peak discharges. Often, only the volume of the drained lake and approximations of the peak discharges are known. At least estimations of these data are possible for most places, regarding information from topographic maps and indicators of water levels of previous floods. Regressions were determined between these two values and were applied to possible magnitudes of expected floods from the outburst of ice-dammed lakes. Discussions of the data to develop the regressions and different mathematical solutions led to several slightly different equations. Among the studies on the magnitude of jökulhlaups, Clague and Mathews (1973) are the first to find an odd relationship between the drained volume of ice-dammed lakes and the observed peak discharge of the outburst flood. By extending their data set up to ten pairs between available water storage V (106 m3) and instantaneous peak discharge Qmax (m3/s), they found a remarkably good regression: Qmax = 75 V 0.67 with r2 = 0.96 Clague and Mathews excluded jökulhlaups resulting from volcanic activity but included estimations of peak discharge of

the drainage of Lake Missoula, the North American pendant of the Pleistocene outburst floods in the Altai Mountains. The authors have used estimated peak discharges given by Bretz (1925) and Pardee (1942) of Qmax = 1.87 × 106 m3/s and V = 2 × 106 m3. The regression line is shown in Figure 51. Against the background of new estimations for the Lake Missoula flood by Baker (1973a, 1973b), and stimulated by lower modeled discharges for this Pleistocene jökulhlaup with computer models, Beget (1986) improved the relationship. First, he excluded the previous discharge data for the Lake Missoula flood and determined the regression between the variables by considering additional data from historic jökulhlaups, including some volcanically triggered events from Iceland. He extended the investigated jökulhlaups to a data set of n = 21, which contained some examples that have also been considered by Clague and Mathews: Qmax = 0.0067 V 0.69 with r2 = 0.86 For the obtained equation the independent variable V is given in m3. It is remarkable that excluding the data of the Lake Missoula flood does not influence the derived regression significantly (Fig. 51). Even if Beget (1986) could increase the estimated peak discharge for the Lake Missoula flood up to 2.1 × 106 m3/s, it is within 10% of the value given by Baker (1973). Beget (1986) argues that lower values are more realistic and the regression method provides an independent check on other techniques used to study outburst floods, especially for prehistoric times. Also, Costa (1988a) modified the basic relationship of Clague and Mathews by excluding the Lake Missoula flood and regarding several other observed jökulhlaups. His data set (n = 21, V in 106 m3) partly overlaps with examples used by previous authors but regards relatively small events quoted by Haeberli (1983), who observed a slight overestimation of peak discharges by applying the Clague-Mathews equation on historic jökulhlaups in the Swiss Alps: Qmax = 113 V 0.64 with r2 = 0.80 Desloges et al. (1989) studied the statistical problem that log-log relationships derived from least-squares regression analysis become biased during back-transformation of the logarithmic coefficients (Miller, 1984). The bias is associated with prediction of Qmax using the antilogged regression in which the geometric mean—not the arithmetic mean—of the dependent variable Qmax constrains the predictive equation (Ferguson, 1986). Since the geometric mean is always lower than the arithmetic mean, the equation implicitly underestimates peak discharges, in the case of the previous equation by as much as 38%. An unbiased estimate (a′) for the coefficient a in the power relationship log Qmax = a′ + b logV takes the form a′ = a exp(5.302 σ2/2), where σ is the standard error of the estimate or residual error for the regression results. The greater the degree of scatter about the regression line, the larger the correction factor.

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Figure 51. Selected published relationships of drained lake volume and peak discharge of jökulhlaups.

Given a σ2 of 0.42 in this problem, the correction factor is 1.59, and the new form of the equation by Costa (1988a) is Qmax = 179 V 0.64 with r2 = 0.80 with V given in 106 m3. Walder and Costa (1996) move further by considering two different outburst mechanisms of ice-dammed lakes: drainage through subglacial tunnels and nontunnel events. Tunnel-drainage floods are indicated by conduits in the ice after the outburst event and by associated missing evidence of ice-marginal drainage, or of mechanical collapse of parts of the ice dam. For nontunnel events, erosion of the ice between the adjacent rock and the glacier are most common. Movement of the entire ice dam or partial failure also occur occasionally, while lakes dammed by cold-based glaciers typically drain by overtopping the ice dam by supraglacial flow. For all processes except cold-based glaciers, Walder and Costa (1996) comment that initial drainage through sub- or englacial tunnels cannot be excluded. For details on outburst mechanisms in general compare Section 2.1. The substantially enlarged data set studied by Walder and Costa (1996) contains some problematic aspects, for example, a tendency toward decreasing dimensions of outburst floods from repeatedly observed ice-dammed lakes. The authors have averaged those values and argue in detail why they have excluded several data sets from the literature, even if they have been regarded in previous attempts of formulating a regression equation—for details compare Walder and Costa (1996, p. 702f., Table I, and appendix therein). They also considered the statistical problem of bias influencing regression parameters, as did like Desloges et al. (1989), and conclude that a comparison of

the obtained equation with those of Clague and Mathews (1973), Beget (1986), and Costa (1988a) would be misleading. For V given in 106 m3, they derive for tunnel drainage events Qmax = 46 V 0.66 with r2 = 0.70 and for nontunnel drainage Qmax = 1100 V 0.44 with r2 = 0.58 The equations shown in Figure 51 are similar, except those for nontunnel drainage of Walder and Costa (1996). The exponents vary between 0.64 and 0.69, which leads to more or less parallel lines in the log-log scale of the figure. Walder and Costa (1996) comment that their equations would cause a misleading impression in direct comparison with those not considering the bias through data transfer from arithmetical to logarithmic scale and back, and this comment is also valid for the equation of Desloges et al. (1989). They first applied the method in the context of jökulhlaups. Regarding statistical methods, the comment is right. On the other hand, the equation of Costa (1988a), not considering the bias (!), also differs from those given previously by the factor for multiplying lake volume, but not significantly by the exponent. This example gives evidence for significant influence of the chosen data set. The consideration of the bias alters the final regression equation. Still, the principal character of the relationships stays similar, as the exponent, which has more influence, is not changed. This is confirmed by the equation for nontunnel drainage of Walder and Costa (1996), where the different data set caused a significantly

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different exponent. As a consequence and by taking into account that the data set of considered jökulhlaups will always be limited and its representative character is definitely problematic, the different regression might be compared directly. In addition, the consideration of volcanically triggered jökulhlaups also influences the derived regression equation less than might be expected, as the equation of Beget (1986) reveals. While this could be seen as an assumed indicator that different physical processes triggering the outburst itself have no significant influence on the resulting outburst flood, the separation of outburst processes by Walder and Costa (1996) does not confirm this assumption. Their regressions on tunnel and nontunnel drainage vary significantly. These contradictory interpretations can be explained by regarding the different characteristics of the two data sets. For example, Schöner and Schöner (1997) have selected data sets of jökulhlaups of “progressive enlargement” outburst process and excluded those of “sudden breaks” (terminology after Haeberli, 1983) from previously published sources. Their equation (Q = 65 V 0.70 with r2 = 0.93, respectively Q = 72 V 0.70 for the unbiased form) is nearly identical with previously developed equations. On the other hand, Popov (1987) gives a relationship of Q = 0.0048 V 0.896 for outburst floods from the Tien Shan Mountains, which differs significantly from equations shown in Figure 51. Unfortunately, no data are listed, nor is r2 mentioned. The range of data (n = 6) is 103 m3 < V < 107 m3 and ~4 m3/s < Q < 104 m3/s. Due to the limited information, the equation cannot be included in Figure 51. From the range of considered data and the mathematical expression, the graph of the equation is steeper and valid for lower values of V and Q. Especially for large events in all previous studies, the range of data is very limited, and Pleistocene outburst floods, except for the Lake Missoula flood in the study of Clague and Mathews (1973), are excluded. In this study an additional regression is determined by focusing on large events in historical, Holocene, and Pleistocene times. While volcanically influenced events are excluded here, a separation according to outburst mechanisms such as done by Walder and Costa (1996) is not possible, as in most cases only speculations about it for the prehistoric events are possible. The arbitrarily chosen threshold value to separate large events is a drained lake volume V > 109 m3 ( = 1 km3). To increase the number of events, repeated outbursts of the same lake basins are regarded as individual events, because the frequency of outbursts of remote ice-dammed lakes and especially prehistoric events is not known. The selected jökulhlaups are listed in Table 12. The intensive research on the glacial Lake Missoula flood becomes a challenge in the context of the regression searched in this study, as the numerous studies resulted in many different estimated discharge values. While reconstructed maximum lake volumes range from 2167 km3 to 2514 km3 (Baker and Bunker, 1985), estimated discharges vary between 0.13 × 106 m3/s and 21.3 × 106 m3/s (O’Connor and Baker, 1992). The background of this large range of data is the complex pathway of the Lake Mis-

soula flood, with several locations restricting discharge because of narrow valley branches leading to ponding upstream. Also, splitting of the flow occurred when the flow was deep enough to get spillways in use. In addition to the different discharges resulting from the flood-plain conditions, the different methods applied for their estimation must be examined. Finally, the number of outburst floods is still under discussion, and doubts might come up if water level indicators from different locations belong to the same flood event. Whereas Bretz (1925) assumed a single flood, sedimentary indicators for up to ~100 separate floods are interpreted controversially (Waitt, 1985; Baker and Bunker, 1985; Waitt et al., 2000). Consequently, the highest estimated values resisting a critical discussion (Qmax = 17 × 106 m3/s; O’Connor and Baker, 1992) and an average maximum value (Q = 10 × 106 m3/s; Baker and Costa, 1987) are both considered and related to the broadly accepted drained volume of V = 2184 km3. By it the range of peak discharges of different outburst floods is considered, too. Several other well-known Pleistocene outburst floods are not regarded here, because the relevance of related failure of moraines or other sedimentary dams cannot be determined without doubts (e.g., Lord and Kehew, 1987; Clayton and Attig, 1989) or the glacial lake was definitely not dammed by ice, such as, for example, the Lake Bonneville flood (O’Connor, 1993). Also, ice-dammed lakes of continental scale are not examined, because the drainage channel cannot be determined with sufficient accuracy and the outburst event could last for more than one year, becoming a relatively permanent drainage process instead of an outburst event (e.g., Teller et al., 2002; Mangerud et al., 2001; Grosswald, 1999; Johnson and Lauritzen, 1995; Shoemaker, 1992). Furthermore, examples that are discussed controversially on their validity are left out (e.g., Rudoy, 2002). The large-scale jökulhlaups listed in Table 12 are used to determine a new regression equation for these kinds of events (V given in km3): Qmax = 6645 V 0.98 with r2 = 0.93 Statistical tests confirm the significance of the correlation. The data with the regression equation are illustrated in Figure 52. The regression was shown in Figure 51 for comparison. In this equation, the bias is not regarded. This is based on (a) comments by Ferguson (1986, p. 76), who argues with the scientific background of the problem he applied the correction for (solute load in rivers in comparison to bed load), and (b) confusion of previous application of the method to the estimation of peak discharges of jökulhlaups. For example, the equation to determine the bias factor given by Desloges et al. (1989) is different from that of Ferguson (1986), and the transformation by Desloges et al. (1989) cannot be retraced quantitatively. Even when focusing on large events, the upper range of outburst floods is given by regarding the flood from glacial Lake Missoula. Using the newly derived equation for the Lake Mis-

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

soula data, the effect of underestimation of events on the upper range of scale is indicated. The calculated discharge is 12.4 × 106 m3/s instead of 13.5 × 106 m3/s for the mean value of the two regarded discharge values for this event. Sophisticated statistical methods should not be applied for the rough estimation of peak discharges derived from regression equations based on other estimations or observed events. A simple test reveals why: The drained volume as independent variable given in 106 m3 for the jökulhlaups of Table 12 (instead of 109 m3) results in the equation Qmax = 7.66 V 0.98. The difference of estimated peak discharges using the two different equations derived from the identical data set varying only in the unit magnitude of the independent variable rises from nearly 30 m3/s for low drained volumes up to ~50,000 m3/s for the Lake Missoula flood. The difference of scale for independent and dependent variables by a factor of 106 is established throughout all previous regression equations. Consequently, for the application of the equations, it is important to give the drained volume V in the dimension that the equation has been developed for. From a statistical point of view, this phenomenon might be seen as a problem and one might think about testing data distribution and the search for theoretically better-fitting expressions for the assumed relationship. But as the data for the correlation are already just estimations, the quality

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of the data is not sufficient for the application of more sophisticated statistical methods. On the other hand, regarding the scale of the estimated peak discharge, the shown inaccuracy appears negligible, as the accuracy of the estimated input lies within this range. Consequently, this example reveals that a further physical interpretation of the parameters of the regression equations appears as a doubtful endeavor (cf. Section 5.4.2). Other correlations to estimate peak discharge of the burst of an ice-dammed lake are applied, too. For different reasons, they are not considered for flood estimations in the Altai Mountains. Due to a slight overestimation of the peak discharge by applying the Clague-Mathews equation on historic glacier floods in the Swiss Alps, Haeberli (1983) developed a regression in the form of Q = V/t, where t is an empirical time constant derived from observed floods. As the regarded floods are relatively small in scale and t shows a large variety for the five chosen examples (816 < t < 2500), this concept should not be applied for largescale outburst floods. In his review on floods from dam failures, Costa (1988a) found that the relation between peak discharge and the height of the dam for an ice-dammed lake is poor. This is explained by the several different ways of drainage through the dam. The relation between the so-called dam factor (product of height of

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Figure 52. Relationship between drained volume and peak discharge of large-scale jökulhlaups (V > 1 km3).

dam and lake volume) and observed Q max yields a better correlation with r 2 = 0.79, based on the same data set as before. While Costa (1988a) focused on smaller events, this approach should not be applied further, as the accuracy for large-scale floods cannot be estimated. Baker et al. (1993, Fig. 4 therein) modified the equations of Costa (1988a) by regarding their estimated peak discharges for Lake Missoula and also for the Chuja valley flood. As estimated peak discharge for the Chuja valley flood is used as independent variable for the equation, it cannot be used again in the context of this study. The authors mainly used the equation for comparison with observed or well-known floods to illustrate the higher magnitude of the Lake Missoula and Chuja valley floods. Reasons similar to those for Costa (1988a) prevent the application of the equation of Costa and Schuster (1988) regarding “potential energy” (the product of dam height, volume of lake and the specific weight of water) as independent variable. Even if the equation differs from the dam factor by Costa (1988a), this is influenced statistically by the constant of specific weight and mainly the chosen jökulhlaups data for the development of the equation. 5.4.2 Hydraulics As has been mentioned above, the derived equations are only rough estimations of a statistical relationship between drained volume of water and peak discharge of jökulhlaups. They are indicators for a correlation but should not be interpreted further in the context of a physical meaning of the magnitude of the exponent. Several examples of misuse of regres-

sion equations in general are demonstrated and explained by Williams (1983a) together with a warning about interpreting regression equations beyond a purely statistical relationship. However, occasionally a physical explanation of exponents from regression analysis in the context of jökulhlaups prediction is assumed (Costa and Schuster, 1988, p. 1065) and occasionally tried. Clague and Mathews (1973) developed their regression by plotting the measured cumulative volume drained during jökulhlaups of six different lakes. These figures show different forms, but can all be expressed in terms of Q t = K (Vt) b, where K and b are individual parameters of each event. (In a second step they found that peak discharges are located on a straight line in the log-log scale figure and developed their well-known regression equations.) While they wondered about an explanation for the relationship, Clarke (1982) in his physically based outburst model for ice-dammed lakes speculates about a relationship between the variety of the observed parameters b with the model previously developed by Nye (1976) and characterizes it as “mysterious.” In these models, V is part of a term related to other parameters with an exponent in a range comparable to the black-box regression equations: 0.5 < b < 1.5. Walder and Costa (1996, p. 707) explain that an exponent in the range of 0.8–1.33 corresponds to the case in which tunnel enlargement is caused by the flow through the ice dam. For the lower values it is caused by thermal energy of lake water; for the upper limit it is caused solely by viscous energy dissipation. Walder and Costa (1996) also suggest that there is no empirically indicated relationship between Q max and the average hydraulic gradient of the drainage tunnel through the

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia ice dam. While one of the exponents in their multiple-regression analysis is even negative, also a statistical test reveals a missing significance of the correlation. A physically based explanation for the magnitudes of the coefficient and the exponent of the regression equations is still missing. Its existence appears doubtful, as the selection of the small number of jökulhlaups that can be quantified in sufficient details seems to have an overwhelming influence on the resulting form of the equation. 5.4.3 Volume of Ice-Dammed Lake Values for the maximum volume of the ice-dammed lake in Kuray and Chuja Basins from the literature vary from 594 km3 (Okishev and Borodavko, 2001b), to at least 1000 km3 (Rudoy and Baker, 1993), and up to 3500 km3 (Rudoy, 1998, 2002). Partly, this difference can be explained by a varying assumption for maximal lake depth. Our estimations based on topographic maps of scale 1:200,000 assume the extension of the lake from upstream of the divide of the old Chuja valley via Aktash and the recent course via Chuja Gorge at 1450 m up to an altitude of 2100 m in Kuray and Chuja Basins (cf. Fig. 12). This lake with a maximum depth of 650 m had a volume of 607 km3, a value similar to the one determined by Okishev and Borodavko (2001b). 5.4.4 Paleohydraulic Calculation Applications for the estimation of peak discharge derived from the volume of ice-dammed lakes are carried out frequently for several ice-dammed lakes. Mostly the equation of Clague and Mathews (1973) was used and found to confirm discharges estimated by other methods (e.g., Clarke, 1982; Clarke and Waldron, 1984; Sturm et al., 1987; Berthling and Sollid, 1999). Over- or underestimation of the peak discharge determined by other methods or even measurements lead to the development of other regressions with carefully selected jökulhlaups. Typically, these modifications are similar to the initial equation of Clague and Mathews (1973) (Fig. 51). Deviations are mainly important for relatively small lakes, while for large ones deviations might be within the range of accuracy of the estimated parameters of the lake volume and the discharge of the outburst flood. Only if orders of magnitude of difference are detected, one might think about other factors influencing the obtained result, for example, data distribution and outburst mechanism.

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Rudoy and Baker (1993) used regression equations to estimate peak discharges for the outburst floods in the Altai Mountains for a drained volume of ~1000 km3. By the application of the regression equations by Clague and Mathews (1973), Beget (1986), and Costa (1988a), they yield discharges between 4 and 9 × 106 m3/s, which they assume to err on the low side, because of the small-scale jökulhlaups the equations are derived from. By comparison with other Pleistocene jökulhlaups, Baker et al. (1993) argue that the outburst floods of the ice-dammed Lake Missoula and Chuja Lake are underestimated. The abrupt failure of the ice dam, instead of the continuous enlargement of the lake outlets of the compared dams, should lead to larger peak discharge than the calculated one. They found that the floods resulting from the failure of the ice-dammed Lake Missoula and Chuja lake also statistically fit better with those from the failure of constructed rather than glacial (ice or earthen) dams. Using the estimated lake volume of 607 km3 for the estimation of the peak discharge of the outburst flood by the regression equations mentioned previously yields in the values presented in Table 13. In fact, only the equation of Clague and Mathews (1973) and the one developed for large-scale jökulhlaups in this study should be applied for estimating peak discharge on the order of km3 of drained volume, as this is the range of data they are derived from. While the previously developed equations vary in the estimated peak discharge by a factor of three, the results are between a factor of four and one order of magnitude less than the result from the new equation for large events. 5.4.5 Discussion The application of the regression equations has been discussed critically for the lack of consideration of translation and retention effects of floods according to the channel’s topography (e.g., Clague and Evans, 2000; Rudoy, 2002). The wide range of peak discharge values for the Lake Missoula flood illustrates this problem. This general problem cannot be solved, as the indicators of previous water levels (for example, slack-water deposits) are too poor in accuracy to quantify this effect, and individual catchment parameters must be calibrated on gauged floods of comparable scale to calculate the effect. On the other hand, the data from the 1929 flood in the upper Indus catchment demonstrate that even nearly 1200 km downstream of the failed dam, the maximum rise of the water level was >8 m (Mason et

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al., 1930; Hewitt, 1982, Table 6 therein). Even from the algebraic formulation of the equations in the general form of Q/V it is evident that the estimated peak discharge occurs “somewhere” downstream of the failed dam. As the method is a statistical estimation of the magnitude of peak discharge, this limitation of accuracy might be accepted. The problem of different magnitude of events for determining the regression equation (e.g., Rudoy and Baker, 1993) could be solved by developing a new equation especially for large outburst floods with V > 109 m3. Still, the jökulhlaup from glacial Lake Missoula determines the upper range of events, and the next smaller flood is about one order of magnitude less for drained volume, and two orders of magnitude less for peak discharge. It can be assumed that the outburst floods in the Altai Mountains are underestimated by the developed regression equations like those from Lake Missoula. This is caused by the characteristics of the data set, leading to a slight underestimation of the Lake Missoula flood by the application of the regression equation. As the regression line is determined at the upper end by the data for the Lake Missoula flood only, and the equation underestimates these values, this might be transferred to the outburst floods in the Altai Mountains. As the regression equation is very sensitive to modifications of the data set, a further physical interpretation of the algebraic expression should be avoided. One could argue about looking at additional events, which were excluded in this study. This would modify the data distribution and in turn lead to another algebraic form of the regression equation, which would have to be interpreted in another way. Also, a separation of the data set according to the outburst mechanism is not possible for Pleistocene events, as for them only assumptions are available at the current state of knowledge. These problems cannot be solved by more sophisticated statistical methods. The quality or accuracy of data is poor (as indicated by the use of well-rounded numbers only), or the outburst flood passed through a complex terrain, making it difficult to give one representative number. For most prehistoric and Pleistocene events a detailed differentiation like for the Lake Missoula flood is not possible. Therefore, the given characteristics are mostly rough estimations, which should not be interpreted too far. 5.5 Boulder Transport 5.5.1 Introduction The attempt to derive information about a flood from the sediments transported is a proximate idea. The correlation of grain size transported with the magnitude of flow expressing the competence of flow is obvious and can be expressed by correlating different hydraulic parameters such as flow velocity v, shear stress τ, unit stream power ω, discharge Q, or even depth of flow y (Costa, 1983). In many cases, the competence of flow is expressed as minimum velocity for the erosion of particles of a given size (e.g., Zepp, 2002, p. 141). A closer look reveals a characteristic threshold flow, while competence can be expressed

as the maximum particle size transportable by a flow (Richards, 1982, p. 79). This previously recognized difference of definition (Baker and Ritter, 1975) could become important if coarse material of a given grain size might not be erodible in a specific reach, but the drag force of the flow is strong enough to keep it in transport. The relationship between competence and grain size of the sediment depends on various factors of the flow and the sediment itself, which have to be in balance. As this strength of flow depends on characteristics of the sediments such as density, grain size distribution, geometry of particle, exposure of grain, compaction, and cohesion, envelope curves of threshold values for minimum values of initial movement are commonly determined. As not all factors of influence on the initial movement of particles can be quantified in applied studies, the degree of empirical elements in equations to calculate necessary flow conditions varies. Hence, the range of validity of estimated equations must be considered carefully, as no final, universal, readily applicable formula has been determined (cf. Raudkivi, 1982, p. 12). The correlation can be carried out by physically based equations with minor empirical elements (e.g., Bradley and Mears, 1980; Carling, 1983; Zanke, 1982) or purely empirical relations such as the well-known graph of Hjulström (1935) or the equations derived from studies, for example, by Costa (1983) or Williams (1983b) (cf., e.g., Graf, 1971, and Novak, 1973, for additional references). 5.5.2 Hydraulic Background According to the DuBoys equation, the shear stress τ0 acting on a particle at initial movement depends on the specific weight of water γf, depth of flow (which can be expressed as hydraulic radius R), and the slope of the channel S (Knighton, 1998): τ0 = γf R S If this threshold value of shear stress is reached, the drag and lift forces of the flow equal the gravitational and frictional forces acting on the particle. The lift force results from the difference in flow velocity between the top and bottom of a particle, which sets up a pressure gradient that tends to move the particle vertically upwards. Turbulent eddying in the wake of the particle, which acts directly upwards close to the bed, supports the uplift force (Fig. 53). Investigating paleoflow velocities required to transport boulders, Bradley and Mears (1980) developed a physically based equation for sliding, where all forces acting on a boulder (Fig. 53) are balanced to determine the threshold velocity of initial movement. The drag force FD is expressed as FD = CD’ An (γf vcb2 / 2) where An = cross-sectional area of boulder perpendicular to flow CD’ = adjusted drag coefficient

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia vcb = velocity at channel bottom γf = specific weight of fluid

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velocity for boulder movement at the channel bed, vcb, can be solved from these equations as

The lift force FL is FL = CL Ap (γs vcb2 / 2) where Ap = cross-sectional area of boulder parallel to flow CL = lift coefficient vcb = velocity at channel bottom γs = specific weight of particle The resisting force FR consists of the submerged weight of the boulder considering a static friction coefficient minus the component of submerged weight acting down the channel slope: FR = (γs – γf) Vb g (Csf cos S – sin S) where γs = specific weight of particle γf = specific weight of fluid Vb = boulder volume S = slope of channel Csf = static friction coefficient It could be determined that even slopes of 100‰ are of negligible influence compared to drag and lift forces of the flow, and hence slope data can be eliminated from the equation. The balance of forces can be expressed as FD + FL = FR. In a modified form, derived by Costa (1983) by consideration of values for the coefficients from various sources, the equation of the critical

Figure 53. Forces acting on a submerged particle (modified after Knighton, 1998, Fig. 4.4B therein).

where CD′ = adjusted drag coefficient ( = 1.05 for a shape factor of 0.60) CL = lift coefficient ( = 0.178) Csf = static friction coefficient ( = 0.7) d = boulder diameter in m g = gravity constant ( = 9.81 m/s2) γf = specific weight of fluid ( = 9800 N/m2) γs = specific weight of particle ( = 25,970 N/m2) In this modification, the shape of the boulders is modeled to be that of a cube. Even with this rough simplification, it is useful to calculate volume and area of a boulder, which influences the drag force and the drag force coefficient CD. The channel bottom velocity vcb represents the velocity of flow about one-third of a boulder diameter above the mean bed level, for which the lift coefficient is CL = 0.178. The mean velocity of flow v within a channel can be estimated as v = 1.4 vcb This estimation is based on a value given by Baker (1973a, p. 26), who assumes an underestimation for very deep flows. The factor is confirmed by Zanke (1982, p. 170), while Costa (1983) mentions a factor of 1.2, and Bradley and Mears (1980) mentions 1.3. The equations given above illustrate the complexity of the physical background of particle movement in fluvial channels. Within this brief review of the hydraulic background, a focus is laid on aspects of relevance for boulders. The subject is explained on a more general level and higher degree of complexity, for example, by Chanson (1999), Graf (1971), Graf and Altinakar (1998), Hoffmans and Verheij (1997), Richards (1982), or Zanke (1982). Another equation for threshold velocities of initial particle movement was developed by Zanke (1982, p. 170). As several hydraulic parameters are kept as variables, the influence of empirical elements is less than in other equations. For the mean velocity of flow in a channel and noncohesive sediments, his equation can be written as

where ρ′ = relative density ( = 1.65) g = gravity constant ( = 981 cm/s2) d = particle diameter (cm) v = kinematic viscosity ( = 0.01519 cm2/s)

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Zanke (1982) determined a satisfying correlation with the curve of the diagram by Hjulström (1935), which indicates validity mainly for fine sediments up to gravels. A good correlation of sediments up to 33 cm with the Hjulström curve is found by Helley (after Graf in Zanke, 1982). This equation is chosen in this study from numerous other attempts (cf. Graf, 1971). Numerous empirical relations between competence of flow and different hydraulic parameters are developed but are limited to smaller sediments up to gravels. For example, Novak (1973) illustrates the failure of empirical relations to estimate river competence for coarse sediments using the example of the modified Hjulström-type curve from Sundborg (1967). Unfortunately, Novak (1973) erred by drawing the Sundborg (1967) curve and shifted the curve of “critical erosion velocity” (upper one) and “cessation of movement” (lower one) one order of magnitude of flow velocity below the values originally given by Sundborg (1967, Fig. 1 therein). Therefore, the interpretation by Novak (1973, p. 23) that this curve “… fails to adequately predict coarse sediment competency…” is still right, but if it is extrapolated to coarser sediments, it overestimates instead of underestimates flow velocities. On the other hand, the scatter of data points increases considerably for particles of d > 1000 mm (Fig. 54). Four groups of empirical equations, based purely on statistical analysis, are considered here, as they are focused on coarse sediments. The following equation (Costa, 1983, p. 991) is recommended for steep channels and grain sizes 50 mm < d < 3200 mm and is derived from previously developed equations as an arithmetic average. The mean velocity of flow given in m/s can be estimated as v = 0.18 d 0.487 where the diameter d is expressed as the intermediate axis of the particle given in mm. This equation considers the widest range of particles’ diameters of all empirical equations found in the literature.

O’Connor (1993, p. 56) correlates data of mean velocity estimated by step-backwater calculations with intermediate axes of boulders transported by the Pleistocene Lake Bonneville flood. The considered boulders had intermediate axes varying from 10 to 624 cm, while the largest measured long diameter of a transported boulder was 1120 cm. O’Connor determined a correlation of r2 = 0.52 for the 75 considered measurement sides in the form of v = 0.29 d 0.60 with v given in m/s and d in cm. Williams (1983b) determined approximated envelope lines for transported particles in a range of 10 mm < d < 1500 mm in log-log scale diagrams of intermediate particle diameters (mm) versus mean velocity of flow (m/s) from various references. For the upper envelope line of initial particle movement he gives v = 0.46 d 0.50 for 15 < d < 500 mm and for the lower limiting line of particle movement he estimates v = 0.065 d 0.50 for 10 < d < 1500 mm His upper envelope line can be interpreted as maximum velocity of flow for initial particle movement under uncertain factors of a high resisting force FR, while the lower line is empirically estimated for conditions more favorable to initial movement. Torpen (1956) summarizes experiences with the dimension of riprap for channel bank protection. As interpolation from various sources, it can be expressed as d = 0.08 vcb2 for the bottom velocity of overturning of coarse particles (vcb in ft/s and d in inches) and d = 0.6 vcb2

Figure 54. Data of competence of flow for coarse particles (modified on the basis of Novak, 1973, Fig. 6 therein). Data for streams, Pleistocene floods, recent floods, and engineering works from various sources are compared with the curve of flow competence by Sundborg (1967) with d for mean particle size in mm and v for velocity of flow in cm/s.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia for the bottom velocity for initial sliding of coarse particles (units like above). Originally, the equations were determined by regarding the weight of stones and were modified by Novak (1973) by assuming spheres for the shape of particles. The use of competence as a paleohydraulic indicator is further complicated by the possible influence of macroturbulence (Matthes, 1947; Jackson, 1976). This secondary circulation phenomenon occurs in deep, high-gradient flows and creates an upward vortex increasing lift forces on particles in a channel considerably. It is assumed to be caused by flow separation and is compared to tornadoes in the atmosphere. Large amounts of sediments are observed to be moved by the vortex, even concrete slabs of boulder size that are far beyond the shear stress energy of tractive flow (after Tiffany from Jackson, 1976, p. 555). Due to limited knowledge about the phenomenon, its influence cannot be quantified but is considered occasionally (Scott and Gravlee, 1968; Baker, 1973a, 1973b). An overview of the fluid mechanics is given by Jackson (1976). Baker (1978a, p. 77) considered this effect by the limitation to “smaller scabland boulders” up to ~2 m in mean diameter when estimating a regression equation for shear stress versus particle size (cf. Baker and Ritter, 1975). This threshold value is also mentioned by Costa (1983, p. 1000). 5.5.3 Boulders near Inja Village The subject of investigation are the boulders found ~2 km downstream from Inja village. They are deposited on a higher terrace level of the broad bed-load terrace ~10 m above the mean surface. The location is the only one of boulder deposits definitely belonging to the outburst flood. Figure 55 gives an impression of the location. Most boulders are well rounded but occasionally fractured due to postdepositional weathering. The fractured components

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are not displaced, except some tilting by gravity. The boulders consist of crystalline rock. Many are streamlined with a parallel orientation of their keel lines. The steepness of the stoss slope varies between 20° and 30°. It is assumed that the streamlined form was caused by corrasion of the transported suspension gravels while the boulders were already deposited. Figure 56 illustrates this phenomenon, which is discussed in detail in Chapter 6. The size of 26 boulders was investigated. Due to lacking alternatives, the circumference of very symmetrical boulders was measured by tape, which allows calculation of the mean diameter. Considering the size of the boulders, their shape below the current surface cannot be considered. For the five largest boulders an average diameter of 11.3 m and a value of d50 = 11.0 m can be determined. The largest boulder of all has a diameter of dmax = 13.5 m. 5.5.4 Paleohydraulic Calculations The competence of flow is frequently applied to estimate paleohydraulic flow conditions (e.g., Birkeland, 1968; Malde, 1968; Bradley et al., 1972; Church, 1978; Bradley and Mears, 1980; Costa, 1983; Lord and Kehew, 1987; O’Connor, 1993; Alcoverro et al., 1999; reviews of additional studies are given, for example, by Williams, 1983b, and Elfström, 1987). A universal guideline to estimate depth of flow, flow velocity, and discharge from measured particle diameter, slope of channel bed, and water surface width was developed by Williams (1983b). The deposition of the boulders near Inja cannot be related to a specific stage of the flood. As the shape of the boulders is modified by transported suspension gravels, and because they are deposited on the bed-load terrace level, which is assumed to have been formed after the peak of the flood, their transport must

Figure 55. Central part of the boulder field near Inja village. In the background the giant bar between Inja and Little Jaloman villages is visible. Note people for scale. Direction of flow was from left to right.

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Figure 56. Streamlined boulder near Inja village Direction of flow was from left to right.

have occurred some time on the falling limb of the hydrograph. No related depth of flow can be deduced with a minimum level of reliability, and hence no discharge can be calculated. Also, calculations based on the elementary DuBoys equation for critical shear stress are not possible, because a distinct water level as an element of the hydraulic radius must be known. Estimations by the guideline prepared by Williams (1983) are not suitable either, as data must be derived from regression equations, developed for particle size considerably smaller than the boulders in Katun valley. The previously listed equations for the estimation of flow velocity are applied for the boulders near Inja. Even if occasionally the range of particle size that the empirical equations are derived from is transcended, the relation is used for comparison of the results with other approaches. The calculated mean diameter of the boulders derived from the measured circumference is assumed to be similar to the intermediate axis used for parameter

of grain size in some of the equations. For d50 = 11.0 m, estimated flow velocities applying the equations mentioned above are listed in Table 14. 5.5.5 Discussion As indicated in the review of the hydraulic background of boulder transport, none of the considered equations in Table 14 is independent of empirical elements. Strictly speaking, none of the equations is valid to estimate the flow velocity for the transport of the boulders deposited near Inja, considering their extraordinary size. Theoretically, the physically based equation of Bradley and Mears (1980) provides a solid background. Its application already includes some empirical elements such as the coefficients for the quantification of drag, lift, and resistant forces introduced by the modification by Costa (1983). Due to limited knowledge about macroturbulence effects, at least the transformation from

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia critical shear velocity at the channel bottom to mean velocity of flow within the channel is purely empirical. Baker (1973a) assumes an upper range for neglecting this effect for a particle size of ~2 m. The equation of Zanke (1982) is a quantification of the Hjulström curve, which was developed for smaller particles up to gravels. It is not surprising that the linear extrapolation leads to very high mean velocities of flow. A tendency of overestimation is indicated by the comparison of the Hjulström-type curve by Sundborg (1967), but due to increased scatter of the rare data for particles with d > 1000 mm, this interpretation is crude (Fig. 54). The empirical relations of Costa (1983) and O’Connor (1993) result in comparable estimated mean velocities of flow. Although the range of validity is exceeded in both cases, the magnitude of estimated flow velocity is similar to the physically based equation of Bradley and Mears (1980). The exceeding of the range of validity for the empirical equations by Williams (1983) is considerably larger than for the previous examples, and the estimated flow velocities vary significantly from these examples. Both values appear less plausible in the review of the results by the other equations, but the large difference between the estimated flow velocities, considering low and high resistance force respectively, illustrates the influence of this factor. Unfortunately, it cannot be quantified, as the origin of the boulders is uncertain. It appears less plausible that boulders of the given size are eroded from the valley bottom during the flood, as erosion of fractured rock from the valley slopes is another possible origin. Therefore, the source location of the boulders deposited downstream of Inja village remains a subject of speculation. The estimated flow velocities derived by engineers to build up resistive riprap (Torpen, 1956) are slightly higher for overturning of boulders than the estimations by earth scientists. Even if spheres are assumed, which could be moved most easily among all possible shapes, a considered classical safety factor, such as rounding-up all values, might explain this difference. The value for initial sliding seems to consider low resistance forces. A systematic underestimation of flow velocities due to the missing accounting for the influence of suspension load on the density of the flow appears less plausible, regarding the magnitude of the transported boulders. On the other hand, a systematic overestimation might occur, due to the unknown influence of effects of the macroturbulence phenomenon. As they are uncertain in their characteristics, previously the use of large boulders as indicators of paleohydraulic flow conditions was refused (Baker, 1973a, 1973b, 1978a). Considering the topographic conditions of the location of the boulder field near Inja village, other transport mechanism than by the current of the flood flow can be excluded. The nearest mountain slopes possible as origin of mass displacement or bank erosion of rock forming the boulders by corrasion of transported suspension gravel (note the streamlined shape of several boulders!) are ~1.5 km upstream. Adjacent to the boulder is the giant

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bar between Inja and Little Jaloman. Even if the boulders are not transported over a longer passage, they must have been displaced by the flow itself. A deposition as ice-rafted debris can also be excluded, as the topography does not give any evidence for the descent of icebergs or ice floes. The extension of the boulder field of ~1 km along Katun valley also excludes this interpretation. As mentioned above, the boulders were not transported during the peak of the flood, as they are deposited on the bed-load terrace, which was definitely deposited after the peak. The flow velocity indicated by the transported boulders therefore does not represent the peak discharge, but an uncertain stage during the falling limb of the hydrograph. Based on the variety of the estimated flow velocities and uncertain additional effects acting on the boulders’ transport, no definite mean velocity can be given. Even while obvious arguments are missing, the flow velocity can be estimated to be ~20 m/s, as this value is indicated by the different applied equations. Considering this background of uncertainty, no further calculations based on an assumed flow velocity appear suitable, for example, estimating the depth of flow by rearranging the Manning equation or a calculation using unit shear stress of flow (Costa, 1983, p. 992f.). However, the orientation of the keel line of the boulder investigated in detail with a related obstacle mark (Section 5.7) indicates that the giant bar between Little Jaloman and Inja did not reach its final extension when the boulder was deposited. The lateral height of the bar toward the valley (80 m above the bed-load terrace) indicates the minimal depths of flow. From topographic maps a cross-sectional area of 150,000 m2 can be estimated. For an assumed flow velocity of 20 m/s a minimum discharge during the deposition of the boulders of Qmin = 3 × 106 m3/s can be taken as rough estimation. 5.6 Gravel Dunes 5.6.1 Introduction Gravel dunes are one bed-form feature among several others resulting from the drag force exerted by water flow on the bed as well as the sediment motion induced by the flow onto the sediment grains (Chanson, 1999). This complex interactive process is affected by the predominant parameters of bed slope, depth of flow, velocity of flow, sediment size, and particle fall velocity. Bed forms differ in size and orientation to flow and can be classified by those main characteristics (Table 15). Some bed forms are similar by characteristics listed in Table 15 but differ in their generation and hydraulic background. In this study, a focus is laid on transverse bed forms as found along the pathway of the flood in Chuja and Katun valleys. An overview of the subject in general is given, for example, by Allen (1968, 1982). 5.6.2 Hydraulic Background At low velocities, the bed material does not move, as the critical shear stress is not reached. For depth of flow exceeding

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~1 m, sediments coarser than ~0.15 mm, and mean velocity of flow above ~0.4 m/s, bed forms become ubiquitous (Ashley, 1990). By increasing the stream power (product of shear stress τ and flow velocity v), different bed forms develop for given mean sediment diameters. As channel bed forms are dynamic features, they change with increasing or decreasing stream power (Fig. 57). The smallest bed forms are ripples; only occasionally up to 60 cm long from trough to trough and usually <10 cm high. If the sediment grains exceed a threshold of coarseness, a plain bed is preserved with the grains being displaced. At increased stream power conditions, the also increased flow velocity, rate of bed material transport, and turbulence lead to an abrupt transition to the larger bed forms of dunes. Their length is >60 cm and can reach several meters. With increased depth of flow their size can also increase further, such as the dunes of the channel bed of Parana River, Brazil, with length of ~100 m and heights of ~4 m described by Santos and Stevaux (2000). The crests of ripples and dunes can show different forms, varying from straight lines to a lunate pattern and tend to become discontinuous with increasing stream power. They are characterized as two-dimensional forms if their geometry can adequately be described by one transect parallel to the flow. Otherwise, they are called three-dimensional bed forms, as they have to be defined in three dimensions. Threedimensional dunes and ripples frequently show merging crests, which make it difficult to separate individual units. At further increase of stream power, ripples tend abruptly and dunes gradually to form plane beds again. This stage is called upper-stage or upper-regime plain bed and clearly depends on the coarseness of grain size. The differentiation on upper and lower regime is based on the bed forms, where ripples and dunes indicate the low- and high-energy bed forms the upper regime. For Froude number Fr = 1, standing waves on the water surface are parallel to bed forms on the channel bed. If stream power is increased above this threshold value, antidunes are generated. They do not exist as a continuous train of waves but gradually build up with time from a plane bed with growing water surface waves that become unstable and break or subside. Antidunes are characterized by surface

waves and bed forms that are in phase. The interaction with the channel bottom leads to an upstream movement of the antidunes at the channel bottom against the direction of flow, while ripples and dunes migrate downstream. This brief qualitative review on the dynamics of channel bed forms in the fluvial environment is derived from descriptions given by Ashley (1990), Chanson (1999), and Reineck and Singh (1980). As expected from the variety of factors influencing bedform generation and dynamics, transformations are not always sharp at well-defined thresholds. Several bed-form alterations are gradual as previously indicated, even if bed forms can be defined by geometric thresholds. Comparison with data derived from flume experiments and observations in natural rivers show scatter of bed forms, which can be limited to ranges of parameters characteristic for a specific bed-form pattern within a stability field with more or less distinct limits (Fig. 58). Further information on bed forms and their generation and dynamics are presented, for example, by Allen (1968, 1982, 1985), Allen (1997), Best (1996), Graf (1971), Henderson (1966), or Wieprecht (2001). In the numerous studies on the subject, some confusion came up based on different definitions and notations by the authors; a reviewing update for clarification is given by Ashley (1990) and Fleming (1988). For example, the expression “dunes” is used in both the fluvial and aeolian environment and could be clarified by the adjective “subaqueous” if limited for the fluvial environment or “aeolian,” “marine,” and “estuarine” for further specifications (Ashley, 1990). In German geomorphology, traditionally “Dünen” (German for dunes) is limited on the aeolian environment (e.g., Hinze et al., 1989; Zepp, 2002), even while engineers and occasionally earth scientists use the expression also in the fluvial environment (e.g., Ahnert, 1996; Dietz, 1972; Fleming, 1988; Wieprecht, 2001; Zanke, 1982). As illustrated in Figures 57 and 58, few data are available for bed forms in gravel-bed rivers. Reasons for this limited information are difficulties of monitoring or reproducing experimentally deep and fast flows in which large-amplitude dunes might develop. Carling (1999) gives a review of studies on subaqueous gravel dunes. Evaluating numerous references, he confirms the

Figure 57. Schematic representation of various bed forms and their relationship to grain size and stream power (modified after Reineck and Singh, 1980, Fig. 2 therein). a—straight-crested ripples and dunes; b— undulatory ripples and dunes; c—linguoid ripples and dunes; d—lunate ripples and dunes. The names of bed forms are modified according to Ashley (1990).

Figure 58. Plot of mean velocity against median sediment size showing stability fields of bed phases (modified after Ashley, 1990, Fig. 1 therein). The values for median sediment size and mean flow velocity have been standardized on to 10 °C water temperature. The data are derived from flume experiments.

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missing relationship between grain size and dune forms, which is similar to sandy dunes. Due to their definition based on dimension, gravel ripples do not exist. Carling gives empirical equations for upper limits of dune steepness, which are reached if a dune is in equilibrium with flow: hd = 0.0073 ld 1.5 for two-dimensional gravel dunes, where hd is the height of the dune, and ld is the length of the dune. For three-dimensional dunes hd = 0.18 ld 0.84 is given, where variables are as above. In previous studies, flow conditions for specific bed forms are well defined, but thresholds for the transition of bed forms have not been the subject of systematic investigation. Relating Froude number (Fr)

where v = mean velocity of flow g = acceleration of gravity y = depth of flow and the nondimensional bed shear stress for initial motion θ (Shields parameter)

The threshold values listed in Table 16 are of preliminary character, due to limited information of data of specific range, which requires additional empirical investigations (see Carling, 1999, and Carling and Shvidchenko, 2002, for details). Probable stages of gravel dune development (Fig. 59) typical for the examples from the Altai Mountains are described by Carling (1996b). From an initial gravel whaleback, the dune grows until near equilibrium with steep cross-beds subparallel to the lee slope. Sandy toesets develop intermittently. Coarse gravel sheets moving up the stoss slope deliver a range of grain size up to the crest. Overpassing blocks stall on the stoss slope. With waning flow, coarse stoss-slope gravels are replaced by a mix of fine gravel sheets. Due to the degrading of the crest, the crossbeds within the gravel dune are steeper than the final lee slope. A cover layer of final bed load and fine sediments develops as the dune stabilizes. Later, aeolian deposits can reduce the depth of the troughs. 5.6.3 Dune Data for Paleohydraulic Reconstruction A detailed report about the morphology and sedimentology of several gravel dune fields along the pathway of the flood has previously been given by Carling (1996b). Based on characteristics investigated by him and additional new data on geometry of new locations, information necessary for a paleohydraulic reconstruction is presented here. After a description of seven individual locations, data of the dune dimensions and grain sizes are given. Additional data are given previously by Carling (1996a, 1996b).

where τ0 = mean bed shear stress ρ′ = relative density g = acceleration of gravity di = characteristic grain-size percentile to grain size, he estimates threshold values for the transition of different bed forms in gravel-bed rivers (Table 16).

Figure 59. Probable gravel dune development (modified after Carling, 1996b, Fig. 14 therein).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Chuja Basin. Between the villages of Chagan-Uzun and Ortolyk in the northwestern part of Chuja Basin, a dune field developed near the bottom of the former lake in the basin. It is located north of Chuja River and limited toward the west by the ephemeral Tyultujaryk Creek. The altitude is ~1820 m, and the dunes are oriented in a northwestern direction toward the outlet of the basin (Fig. 60). Along the slopes of Chuja Basin north of the dune field, strandlines indicate different stages of the lake. The dunes are of two-dimensional character and consist of homogenous gravels of a maximum diameter of ~8 cm, typically ~5 cm. Unfortunately, detailed grain size data are not available. A survey along the dunes reveals a mean height of the dunes of hdm = 2.3 m and a mean length ldm = 59 m with a range of 1.3 m < hd < 4.0 m and 43 m < ld < 76 m (Fig. 61). Chagan-Uzun. Near the village of Chagan-Uzun at the outlet of Chuja Basin, a dune field developed on the former lake bottom. It is located east of Chagan-Uzun River at a mean elevation ~1760 m, is oriented toward the northwest to the outlet of Chuja Basin, and consists of two-dimensional dunes (Fig. 62). As illustrated in Figure 62, the flow pathway was south of the hill instead of through the valleys of Chagan-Uzun or Chuja Rivers. The dunes consist of coarse gravels of usually ~20 cm with maximum diameters of 25 cm; data from a grain size analysis are unfortunately not available. These grain size data vary from those for the sediments at the obstacle mark at the bedrock hill

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nearby, where d50 = 4.4 cm and the armoring layer consists of well-rounded boulders of up to 60 cm (Section 5.7). A survey along the dune field illustrates the dimensions of the dunes, which are the largest of the flood’s pathway along Chuja and Katun valleys. Height of dunes varies between 6.3 m and 23.0 m with lengths of 139 m < ld < 320 m. The mean values are hdm = 16.0 m and ldm = 207 m. If the smallest dune is left out, the mean height increases to hdm = 17.9 m (Fig. 63). The slope of the dune field is difficult to estimate from the survey. Values of S = 0.026 and S = 0.008 are derived by connection of the crests and troughs respectively. From topographic maps, a value of S = 0.013 could be estimated, and therefore a mean value of S = 0.015 is chosen as representative value. Due to the steep slope for the flow passing over the hills visible in the background in Figure 62, critical or even supercritical conditions of flow cannot be excluded. So, the dunes near Chagan-Uzun could be antidunes, even if the slope of the dune field is less steep than, for example, for the previously described dunes farther upstream in Chuja Basin. Due to missing sections of adequate dimensions, the large proportions of the dunes, and the coarse gravels they consist of, the supposed generation as antidunes cannot be finally proved. Necessary evidence, for example, by foreset beds dropping upstream, could not be documented yet. The survey of the dunes reveals two superimposed dunes on the stoss slope of a larger one ~400 m from the beginning

Figure 60. Aerial photograph of the dune field in northwestern Chuja Basin.

Figure 61. Survey data from the dune field in northwestern Chuja Basin (flow direction was right to left).

Figure 62. Photo of the dune field near Chagan-Uzun village (photo by P. Borodavko). View to the eastern direction across Chagan-Uzun River (trees for scale) with Chuja River left in the background. Flow was top right to bottom left.

Figure 63. Survey data from the dune field near Chagan-Uzun village (flow direction was right to left).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia of the profile (Fig. 63). This occurrence of secondary dunes is exceptional for the dunes in the Altai Mountains (cf. Carling, 1996b, p. 659), at least at this scale. One interpretation of speculative character could be that during a high-energy early stage of the flood, first the large (anti-)dunes formed, which could not be decreased due to a rapidly waning flow. Later, parts of the gravels of the antidune’s surface were reworked, and dunes were generated by the flow. The dune fields of Kuray Basin, Akturu, Kara Kol, and Baratal are located at the western part of the former ice-dammed lake. The locations are shown in Figure 64. For the Akturu dune field, sufficient data for paleohydraulic estimations are not available. Therefore, this dune field is not described in detail. Kuray Basin. Within the center of Kuray Basin east of Tyute River, an extended dune field developed on the bottom of the former lake. It consists of two-dimensional dunes and covers the basin over a length of ~3.3 km with a span of 2.4 km in front of Northern Chuja Range. The dunes are oriented in an eastern direction and are located at an elevation of ~1520–1550 m. At the eastern margin of the basin, strandlines indicate different levels of the Pleistocene lake (Fig. 65). The dunes have been intensively investigated by Carling (1996a, 1996b). He surveyed maximum heights for the dunes of hdmax = 16 m with a related length of ldmax = 200 m. The sediments forming the dunes are characterized as d50 = 3.2 cm, d84 = 25 cm, and dmax ≈ 50 cm. Even boulders with diameters of 300 cm were observed and assumed to have been transported over the dunes. Baratal. The dune field of Baratal is located in a northeastern tributary valley of Chuja valley, ~6 km east of the upstream

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extension of the former ice dam at an altitude of ~1720 m. It consists of two-dimensional dunes, which are oriented in a western direction, while the valley itself is oriented in a southwestern direction. The dunes are deposited on the slope of the valley and were formed by a current during the drainage of the ice-dammed lake, which was different from the orientation of the valley. The flow ran through a spillway and continued over a ridge leading to the curious situation of a flow running uphill according to current topography (Figs. 66 and 67). Remarkable is the increasing dune size along the flood’s pathway uphill and the missing of any bed forms at the valley’s slope downhill from the spillway. The dunes are relatively small with 0.6 m < hd < 2.0 m and 30.3 m < ld < 46.5 m. A speculative attempt of interpretation could be seen in a decreasing stream power by reaching higher elevations along the slope. The flow conditions might have changed from the upper regime of (super-?) critical conditions of flow (resulting in a plane bed from the spillway down to the valley) to the lower regime along the hill slope (resulting in the generation of dunes). Consequently, a hydraulic rise from super- to subcritical conditions of flow might have occurred in the deepest parts along the surveyed profile. There also is an obvious asymmetry of the shape of the dunes with gentle stoss slopes and steep lee slopes. According to the model of Carling (1996b) illustrated in Figure 59, this can be interpreted as an indicator of a rapidly waning flow, which did not diminish dune dimensions from the stadium of equilibrium shape. This aspect is of importance for paleohydrological reconstruction, discussed in detail in the following chapter.

Figure 64. Overview map of the locations of the dune fields of Kuray, Akturu, Kara Kol, and Baratal. The maximum extension of the ice-dammed lake in Kuray Basin is indicated by the mark of the 2100 m contour line. For this stage of the lake, a minimum ice dam height of 2100 m is required; hence valley glaciation filled most parts of the area downstream of the dam. Most parts of the mountain ranges around Kuray Basin might be assumed to have been ice-covered at this specific time; for clarification this extension of valley glaciers is not shown in the figure. The direction of flow during the drainage of the basin is indicated by the orientation of the dunes and marked by arrows. A discussion of the reasons of the complex flow pattern is provided in Section 5.6.5.

Figure 65. Aerial photograph of the dune field in Kuray Basin.

Figure 66. Photo of the Baratal dune field. The dune field is located on the slope rising from the valley bottom. The valley itself is oriented toward the right from the point of view. The morphology of the dunes is difficult to determine, but the dunes are easy to detect by the change of the vegetation cover. Direction of flow was toward the front.

Figure 67. Survey data from the dune field at Baratal (flow direction was right to left).

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Detailed grain size analysis could not be carried out, but an investigation of the dune sedimentology in the field yields mean diameters of gravels of ~4 cm, with the largest gravels being at d max ≈ 12 cm. Kara Kol. The dune fields of Kara Kol are located on the opposite side of Chuja valley from Baratal dune field within the extension of the former lake. It consists of two-dimensional and three-dimensional dunes, which are oriented toward the northwest. The lower dune field is located at an altitude of 1680 m (Fig. 68), the higher one at ~1880 m. According to Carling (1996b), the maximum height is up to 3 m with a related maximum length of ~70 m. The maximum grain size of the sediments is given by him as d max = 10 cm with a value of d50 ≈ 1 cm. Toward Chuja valley, the lower dune field is partly separated by a bedrock ridge with a maximum elevation of 1700 m. This ridge led to flow separation for depths of

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flow over the dune field of <20 m. Hence, estimated discharges from the dune field cannot be related to Chuja valley beneath. Little Jaloman. Between the villages of Inja and Little Jaloman, a dune field of mainly three-dimensional dunes is deposited (Fig. 69). It is located on a level of the broad bedload terrace, which is connected with the boulder field ~1.5 km farther upstream (Section 5.5). Its orientation is parallel to the recent valley orientation, and the altitude is ~760 m. The highest dune is hdmax ≈ 3 m with a related length of ~38 m (Carling, 1996b). The diameter of the sediments reaches d max ≈ 20 cm. Platovo. The dune field near the village of Platovo is located in the lower Katun valley ~200 km downstream of the main area of investigation in the foothills of the Altai Mountains. The dunes are two-dimensional, oriented toward the northwest. The altitude of the dune field is ~240 m (Fig. 70).

Figure 68. Photo of the lower Kara Kol dune field. Direction of flow was right to left.

Figure 69. Photo of Little Jaloman dune field. Bus for scale. Direction of flow was right to left.

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A survey by Carling (1996b) reveals maximum heights of the dunes of slightly less than 3 m with related length of ~70 m. The mean diameter of gravels forming the dunes is ~10 cm, but gravels up to 20 cm can be found. The ~11 m thick river terrace below the dunes consists of coarser material. The main data of the different dune fields are summarized and completed with data on their span and the width of the valley derived from aerial photographs and topographic maps in an overview in Table 17. Based on previous studies, Carling (1999) derived the limit of maximum steepness for two-dimensional gravel dunes at equilibrium stage by an envelope curve given as hd = 0.0073 ld 1.5 and found that several previously investigated dunes of the Altai Mountains reached an equilibrium stage (Carling, 1996b). For the additionally investigated dune fields of this study, the reaching of equilibrium stage can be confirmed (Fig. 71). For the dunes with data located significantly below the curve, it can be expected that either the dunes never reached the equilibrium stage, for example, due to limited sediment supply

(Fleming, 1988), or they were diminished during the waning flow (Fig. 59). Not considered due to limited data for paleohydraulic reconstruction are the dune fields at Akturu (located within Kuray Basin, Fig. 64) and south of Chemal (central reach of Katun valley, ~100 km downstream of the main area of investigation). As previously mentioned, further information on selected dune fields is given by Carling (1996a, 1996b), and also by Butvilovsky (1993) and Rudoy (2002). 5.6.4 Paleohydraulic Calculations Bed forms are frequently used as indicators of paleoflow conditions, and equations describing relations are derived on a physical and empirical basis. Most of the previous studies are carried out for sediments finer than the cobbles building the dunes in the Altai Mountains (e.g., Fralick, 1999; Harms, 1969; Middleton, 1965; Southard, 1971) or need input data not available for paleoflows (e.g., McLean et al., 1999). Also for jökulhlaups, interpretations beyond pure descriptions (e.g., Post and Mayo, 1971; Clague and Evans, 1994) by paleohydraulic analysis were made (Baker, 1973a, 1978b; Shaw, 1989; Perchanok, 1980; Koster, 1978; Carling, 1996a).

Figure 70. Photo of the dune field near Platovo village. Most parts of the dune field are covered by dense pine forest. Direction of flow was left to right.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia

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Figure 71. Steepness of selected surveyed two-dimensional gravel dunes in the Altai Mountains. The data set could be expanded by a more tolerant definition of dune geometry. For example, dune length can also be defined as distance from crest to crest and dune height given as mean depth of trough related to the neighboring crests. Tests with this tolerant definition reveal principally the same result: All data points are located below the equilibrium stage curve. For the sake of simplicity and clarity, only the classically defined values (those shown in Figure 61) are considered in the figure. From the original literature considered by Carling (1999), it is not clear if the equilibrium stage equation is also valid for antidunes. Hence, the data points for the assumed antidunes at Chagan-Uzun could be regarded as uncertain. But as this characteristic can only be assumed at the current state of knowledge and the data fit to the derived limit, this aspect does not seem to be critical.

Baker (1973a, 1978b) related different hydraulic parameters derived by other methods to the gravel dunes along the Lake Missoula flood’s pathway. He used dune dimensions for further interpretation, not for estimating flow velocity itself. His findings are considered by the studies of Carling (1996a, 1996b, 1999). Shaw (e.g., 1989) interprets drumlins in Canada as indicators of a broad subglacial meltwater flood with a discharge on the order of 106 m3/s and a flood volume of ~84,000 km3. Within his complex model of interacting erosional and depositional fluvial processes, drumlins could be seen as subglacial fluvial bed forms, but this interpretation is in controversial discussion (see Benn and Evans, 1998, p. 440f., for a review). According to Young (1985, p. 141), Perchanok (1980) estimates the peak discharge of the prehistoric outburst flood from the ice-dammed Lake Donjek (Yukon Territory, Canada) by channel geometry and the characteristics of giant ripple marks as larger than estimations by the use of the regression equation by Clague and Mathews (1973). Further details of the unpublished report are not known. Koster (1978) developed calculations of paleohydraulic significance for transverse rips. Transverse rips are small-scale transverse bed forms of large clasts of heights of one to two particle diameters that occur as series in shallow, high-energy fluvial systems. His calculations are based on flow competence

and threshold values for flow conditions necessary to form the special kind of bed form. Carling (1996a) characterizes his paleohydraulic model for the estimation of flow velocity and discharge, based on the gravel dunes of Kuray Basin, as preliminary, as further refinement and testing seem to be needed. Important sources of information for the model are the process studies by Dinehart (1992) on the evolution of coarse gravel bed forms. Mainly based on physical concepts by considering grain and form roughness and flow separation in the wake of the modeled dune, Carling transfers the observations on several stages of the generation of the largest gravel dune of Kuray dune field. He derives flow velocities of 1.5 m/s to 8 m/s, resulting in discharges of 2 × 104 m3/s to 7.5 × 105 m3/s over the span of the dune field. Even though the model was developed for cases of limited input data, it cannot be applied for the other dune fields mentioned above, as important variables cannot be quantified. The main problem is grain size data for the dune fields, as flow competence, grain shapes, and form factors of the dunes are key elements. Based on the Prandtl–von Karman universal velocity distribution law, Zanke (1982, p. 60) gives an equation for estimating mean flow velocity v over large bed forms:

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where v* = shear velocity ( = (τ0 / ρw) 0.5 with τ0 for shear stress and ρw for density of water) yc = depth of flow above dune crest hd = height of dune (Table 17) The shear stress τ0 to determine shear velocity v* can be estimated for the gravel dunes from the threshold values for the transition of bed forms (Table 16) by transformation of the equation of the Shields parameter and substitution of τ0 in the equation defining shear velocity:

where τ0 = mean bed shear stress ρ′ = relative density ( = 1.65) ρw = density of water ( = 1.00) g = acceleration of gravity ( = 9.81 m/s2) θ = Shields parameter (Table 16) di = characteristic grain-size percentile For each dune field, shear velocity on the dune crest can be estimated based on the given grain size, while dmax is regarded as characteristic to avoid systematic underestimation of shear velocity. Considering the given maximum height of each dune field, hdmax, the equation on mean flow velocity over large bedforms after Zanke (1982, p. 60) can be simplified to a relation v = f (yc), where the data for hdmax and dmax (intrinsic in v*) of each dune field given in Table 17 characterize the individual proportional factor. For each dune field, curves can be derived for the relation

of depth of flow over the dune crests and mean velocity of flow (Fig. 72). Baratal dune field is excluded in this part of the study, due to the dune being deposited on the hill slope, where the flow was running uphill, which demands completely different ways of calculation. Due to the logarithmic character of the curves, a limit of the range of the flow velocity forming the dunes is already given. For the depth of flow, the range is still large. Estimating the depth of flow over dunes is the greatest uncertainty in any dune model (Carling, 1996a, p. 175). Carling (1996a) applied an approach of Vanoni and Hwang (1967) for two-dimensional coarse-sand dunes of maximum steepness on Kuray dune field and found a depth of flow between 40 m and 50 m. This range remains, as several fitting and correlation coefficients have to be estimated. Our approaches of application fail due to the algebraic structure of the equation, where slight modifications of parameters that have to be assumed modify the calculated depth of flow by magnitudes. This attempt was therefore not followed further, considering the quality of input data and variety of dune parameters within single dune fields. Several empirical attempts are developed, based on shear stress. Koster (1978) applied them successfully for small-scale bed forms such as transverse ribs, where height of the investigated bed forms is dimensioned on the order of centimeters. Raudkivi (1982, p. 34f.) gives an overview on empirical relationships of dune shape to depth of flow:

(after Führböter, 1979) (Raudkivi, 1982) ld = 2 π y (Yalin, 1977)

Figure 72. Relationship of depth of flow above dune crests and mean velocity of flow. The figure illustrates related mean flow velocities over the entire depth of flow (including the depth below dune crests) with depth of flow above the crests. Therefore, no vertical velocity distributions are shown, like for the classical style of diagram where abscissa and ordinate are exchanged. This aspect also explains why the values for flow velocity do not rise from a value of zero for theoretical flow velocity at the bottom. The curves are drawn on the basis of θ = 0.30. Arrows along the curves indicate plausible ranges of depth of flow derived from empirical relationships; see text for details.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia The equations above are derived from fine-sediment investigations, which renders them invalid for gravel bed forms. As no other relationships are available, the equations are applied to limit the range of uncertainty for the possible depth/velocity ratios in Figure 71. It was found that the first relation always gives the greatest depths, for the large dunes of Kuray and Chagan-Uzun dune fields by nearly one order of magnitude. The other equations were found to overlap with the first equation for smaller dunes. By balancing this still contradictory approach, a compromise is chosen, to mark ranges as most plausible, where the equations are overlapping for given dune size data. Those ranges are marked by arrows in Figure 72. Based on mean values for the ranges of flow velocity v and depth of flow over dune crests, yc, discharges forming the dune fields can be estimated by considering the span of each dune field and the estimated width of the valley sections given in Table 17. Due to the wide ranges for the uncertain depth of flow, these values are to be seen as magnitudes only (Table 18). The discharges given for the entire valley cross section are given to draw attention to the fact that the preserved lateral extension of the dune field does not represent the whole width of the valley at the elevation of the dune fields. As previously mentioned at the description of the locations, some dune fields are laterally eroded by present-day river activity. It must also be considered that dunes at the inner side of the valley section might have been diminished during the falling limb of the flood. The transfer of the estimated flow velocity from the dune field to the entire cross section of valley gives a rough estimation for the discharge of the flood during the stage of forming the dunes. Surely, it is more precise to keep to the span of the dunes as Carling (1996a) did, but this limitation could lead to misinterpretation of the estimated discharges (cf. Rudoy, 2002, p. 136). It must be accentuated that the estimated discharge gives magnitudes only. While flow velocity can be estimated within a minor distinct range, depth of flow could vary over a wide range of related values, considering the accuracy of velocity values. Sensitivity analyses were carried out to test the influence of increased density factors and lower or higher threshold values of the Shields parameter θ. Different combinations of the factors are found to decrease mean flow velocity over the dunes up to 20% for the worst case. On the other hand, there is a tendency of underestimation of the transported grain size, which already results in an underestimation of the flow velocity. Due to missing

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systematic analysis of grain sizes of most gravel dunes, which is related to the principal problem of taking a representative sample of coarse material, which requires samples of several dozen kilograms for each sample, the coarsest particles might not be considered adequately (Carling, 1996b; Gale and Hoare, 1992). Hence, values for shear velocity v* are assumed to be underestimated by an unknown amount, which in return is assumed to compensate uncertainties of other factors. As previously mentioned (in Section 5.6.3), the dune field at Chagan-Uzun is assumed to consist of antidunes. This assumption is based on the topography of the location, as the flow during the drainage of Chuja Basin was accelerated by passing over the mountains upstream of the dunes toward the outlet of the basin. Along the downward flow on the mountains’ slopes, a hydraulic jump is assumed to be formed, which accelerated the flow to supercritical conditions. Under those upper-regime conditions, dunes are no longer stable and transform to antidunes. Within previous paleohydraulic calculations, this assumption is neglected, and flow over the dune field is estimated like for the other locations. For two-dimensional antidunes, Kennedy (1961, 1963) gives the theoretically derived and empirically confirmed relation

where all variables are as previously mentioned. The equation can be transformed to estimate flow velocity v for the given wavelength ld of the antidunes, as suggested by Kennedy (1963, p. 530). The data from the survey of the dune field illustrated in Figure 63 reveal length of dunes of 139 m < ld < 320 m, resulting in a mean length of ldm = 207 m. These values are determined by measuring the distance from trough to trough and crest to crest. For these wavelengths a flow velocity with a range of 14.7 m/s < v < 22.3 m/s can be determined, with an average value of v = 18.0 m/s. This velocity of flow is more than twice the estimated value when assuming the dunes to be formed by lower-regime flow. From sedimentary structures or any other preserved evidence, the separation of dunes and antidunes is not possible; hence a classification of the nature of the dune field must be left open. Based on investigations in Rio Grande River, an empirical relation of depth of flow to the length of standing waves can be expressed in the form of

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where both variables are given in feet (after Nordin from Simons et al., 1965). Even though the relation is limited on 3 ft < ld < 20 ft, no further statistical parameter is given and it must be assumed that the length of the standing waves is identical with the length of the antidunes. This empirical ratio is applied to give at least a vague idea of depth of flow. For the range of length of antidunes given above, depths of flow of 33 m < y < 76 m, with a mean depth of y = 49 m, can be estimated. These estimated values are quite similar to the depths estimated by the empirical relation for dunes, which is not a surprising result as the factor is within the range of the values given by Raudkivi (1982). Considering the estimated higher flow velocities, assuming the dunes of Chagan-Uzun to be formed as antidunes by upperregime flow, results in larger estimations for discharge. For flow over the whole extent of the dune field, 2.9 × 105 m3/s < Q < 10.2 × 105 m3/s can be estimated, while for a rough estimation of flow through the entire valley cross section, discharge rises up to 12.1 × 105 m3/s < Q < 42.4 × 105 m3/s. 5.6.5 Discussion The gravel dunes formed during the outburst flood of the ice-dammed lake in Kuray and Chuja Basins can be interpreted as indicators for the magnitude of flow. As they are dynamic bed forms, they adapt their dimensions and characteristics during different stages of the flood; hence, the preserved dimensions indicate the last stage of the flood flow strong enough to modify them. Consequently, the flow velocities and discharges indicated cannot be compared, as they are possibly generated at different stages of the flood. So, the dunes definitely do not indicate peak discharges of the flow, due to the mentioned dynamic nature of bed forms as misinterpreted by Rudoy (2002, p. 136). Without any doubt, depth of flow was larger than estimated for the stage of the generation of the dunes. Flow velocity and discharge might have been larger at the locations of the dune fields too, but information on this previous stage cannot be derived from the preserved gravel dunes. A critical aspect is the uncertain estimation for the depth of flow, because the chosen method limits the estimation of flow velocity to the distinct range. The estimated discharge is therefore a rough assessment of magnitude only. Compared with the more sophisticated approach by Carling (1996a), the estimations are of a similar magnitude, which is documented in the analysis of the Kuray dune field. An advantage of the approach used here over the method of Carling (1996a) seems to be the simplicity of the calculations, which avoids assumptions for empirical coefficients that can only be guessed at the present stage of experiences with gravel dunes as paleohydraulic indicators. Other estimated parameters such as density of flow are needed in both approaches and are found to be of minor influence for the results, considering the magnitude of flow. Based on the orientation of the dune fields within Kuray Basin, Butvilovsky (1993) and Rudoy (1998, 2002) assumed

giant eddies, which should have had a radius of >10 km. Rudoy (2002, p. 130) suggests flow separation phenomena as reasons of the large vortex, but does not mention any details. The indicator of special focus is the orientation of the Akturu and Kuray dune fields to the east, which is against the general flow condition (Fig. 64). A more plausible explanation can be given by consideration of the estimated depths of flow of up to ~50 m during the stage of dune generation and the topography of Kuray Basin itself. North of the Akturu and northwest of the Kuray dune field, local hills reach heights of nearly 1800 m. Based on the elevation of the Kuray dune field of <1600 m and considering the depth of flow of 50 m, the direction of flow obviously was influenced by those hills. During the falling stage of the lake level in Kuray Basin, the flow was directed in eastern directions by the hills forming a local divide at the southern margin of the basin. The curious orientation of the dune field can easily be explained by considering the depth of flow during the generation of the dunes. 5.7 Obstacle Marks 5.7.1 Introduction In general, obstacle marks are sedimentary structures resulting from deformation of flow induced by obstacles (Karcz, 1968, p. 1000). In front, around, and in the lee of obstacles the sediment cover of the surface is deformed by currents and shows features of scouring and deposition. This principal pattern is similar in fluvial, coastal, submarine, and aeolian environments. According to Allen (1982, p. 173), first descriptions of obstacle marks were given in the 19th century on littoral sandstone and modern beaches. Obstacle marks, whose sediments are displaced by currents, are clearly distinct from potholes, which are erosional forms caused by different processes (cf., e.g., Parker, 1997; Goudie et al., 1994). In the fluvial environment, they are described, for example, by Peabody (1947), McKee (1954), Friend (1965), Dzulynski and Walton (1965), Sengupta (1966), Karcz (1968), Slatt and Hoskin (1968), Conybeare and Crook (1968), Klimek (1973), Baker (1973a, 1973b), Fahnestock and Bradley (1973), Picard and High (1973), Potter and Pettijohn (1977), Futterer (1977, 1978), Reineck and Singh (1980), Allen (1982), Elfström (1987), Russell (1993), Bunte and Poesen (1994), and Fay (2002). Different expressions for the phenomenon came in use, as studies were carried out by different disciplines. Earth scientists established the expressions “obstacle mark” (e.g., Karcz, 1968; Reineck and Singh, 1980; Allen, 1982; Paola et al., 1986; Russell, 1993), “scour mark” (e.g., Allen, 1965; Richardson, 1968b; Baker, 1973b; Elfström, 1987), “scour hole” (Baker, 1973a; Underwood and Lambert, 1974), and “comet mark” for special large-scale obstacle marks (Werner et al., 1980), with the first expression being used most frequently. In engineering sciences, the expression “local scour” is commonly used (e.g., Shen, 1971; Breusers et al., 1977; Breusers and Raudkivi, 1991; Hoffmans and Verheij, 1997; Melville and Coleman, 2000;

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia Richardson and Davis, 2001), and a focus is laid on scouring processes and forms around bridge piers. According to Allen (1982, p. 185), no generally accepted classification of obstacle marks had been established, so he distinguishes three broad categories: current crescents, current shadows, and scour-remnant ridges. Current crescents are U-shaped furrows formed around obstacles as currents eddied past them, ranging from wholly erosional to wholly depositional in character. Current shadows are depositional forms in the lee position of an obstacle, while scour-remnant ridges are residual forms created by erosional processes downstream. An overview of the variety of current crescents and shadows formed by unidirectional currents is given by Allen (1982, Figs. 5–10 therein), grouping them by current strength, grade of sediment transport, and nature of flow boundary as factors influencing the morphology of obstacle marks in a qualitative way (Fig. 73). In the context of Figure 73, Allen (1982) unfortunately gives no information about different environments being characteristic for types of obstacle marks or thresholds of influencing factors. Theoretically, additions could be made to Allen’s list by

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considering additional conditions such as, for example, noncohesive bed sediments below a sand-laden flow. In accordance to the subject of this study, a focus is laid on unidirectional currents in the fluvial environment. Additional information on processes forming obstacle marks in special nonfluvial environments, their different appearance, and scale is given, for example, by Allen (1965, 1982), Werner et al. (1980), Hoffmans and Verheij (1997), and other references mentioned above. Karcz (1968) presents qualitative observations of fluvial obstacle marks at the bottom of ephemeral streams in the Negev Desert. His observations and results from field experiments confirm many aspects of the overview given by Allen (1982) and contribute important conclusions: • Dimensions of scour depend mainly on the size of the obstacle and supply of sediments. • Sometimes single furrows have developed downstream of the obstacle. • Downstream ends of current crescents diverge at slow flow conditions, converge or even merge in coarse material, or trend parallel to each other.

Figure 73. Varieties of current crescent and shadow formed by unidirectional currents, depicted in the plane of symmetry (x/y) and in plan (x/z) (Allen, 1982, Figs. 5–10 therein, modified). A: Sand-laden flow: wholly erosional with current crescent fading downstream and forming a scourremnant ridge downstream in cohesive sediments. B: Fast sand-laden flow: erosional with current crescent fading downstream and deposition of a current shadow downstream of obstacle on cohesive sediments. C: Erosive flow: erosional with current crescent of limited extension and deposition of a current shadow as so-called sand delta accumulating downstream on noncohesive sediments. D: Fast flow with bed load only: wholly depositional with a crescent-formed accumulation of sediments in front and around the obstacle on cohesive sediments. E: Fast flow with suspended and bed loads: wholly depositional with a crescent-formed accumulation of sediments in front, at, and around the obstacle and current shadow on cohesive sediments. F: Fast sand-laden flow: wholly erosional with scour-remnant ridge in cohesive sediments only (cf. B). G: Fast sand-laden flow: erosional without current crescent but a scour-remnant ridge in cohesive sediments covered by a current shadow (cf. B and F).

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Edges of current crescents are sometimes diffuse, leading to irregularly formed scour holes, typically related with asymmetric forms of obstacles. • In the central part of the eroded crescent, the down-current slope equals the angle of repose of the sediment. • In coarser sediment, the crescents are sometimes lined or filled in with small pebbles. • The spacing of obstacles has significant influence on obstacle marks. • Imperfectly developed current shadows of different size and shape sometimes developed behind large boulders in coarsegrained streambeds normal to flow; they could perhaps be explained by limited sediment supply. The mainly qualitative observations of Karcz were limited to small-scale features in the range of 10–3–101 m in shallow (<10 cm) and slow (<0.1 m/s) flow. Baker (1973b) and Russell (1993) explain scouring in front of and behind an obstacle qualitatively by very high velocities of the current, even for nonsubmerged obstacles. Flume experiments of Werner et al. (1980) reveal a dominant influence of the relation between grain size of the sediments around a submerged obstacle and the critical velocity of their erosion on the dimension of scour holes. They observed an extension of the scour hole up to 100 times the obstacle’s diameter downstream from the obstacle itself. Some scour features were unstable during the flow and influenced by local currents at sedimentary bed features such as ripples and dunes. Therefore, the authors limit their observations to low-turbulence conditions. 5.7.2 Hydraulic Background 5.7.2.1 Submerged obstacles. Based on explanations by Shen (1971) and Best (1996) single obstacles within a flow can create up to four vortex systems as a result of flow separation phenomena (Fig. 74). A horseshoe vortex system is generated by a boundary layer “rolling down” in front of the obstacle (Fig. 74A), increasing the bed pressure (Brayshaw et al., 1983) and resulting in scouring of bed material in front of the obstacle. The slope of this scour hole depends on the local repose angle of the sediments and adjusts to these conditions by collapses of sediments into the depression (Melville and Coleman, 2000, p. 189). The horseshoe vortex develops as the result of separation of flow at the upstream rim of the initial scour hole excavated by the downward flow in front of the obstacle. On the flanks of the obstacle, high local shear stress of the vortices extend the area of erosion to the wings. Unstable shear layers generated at the surface of the obstacle force the horseshoe vortex system to rise downstream (Shen, 1971, p. 23–25). As they rise, their vortices entrain sediments at the flanks of the scour hole. Behind the obstacle the wake vortex system develops as the horseshoe vortex system begins to rise, and the axis is tilted from its horizontal orientation. According to Karcz (1973a), in the near wake close to the obstacle, separation leads to two shear layers, which envelope a slowly recirculating low-pressure region,

which is believed to be the site of deposition of the current shadow. Near its closure, the shear layer becomes unstable and rolls into a pair of larger vortices (Fig. 74B). At very low Reynolds numbers (<50) this system is stable, but it starts to grow and shed alternately in a regular mode at increasing turbulence (80–90 < Re < 150–300; Shen, 1971, p. 23–25), forming the so-called “von Karman Street” and shedding with a frequency that can be expressed by the Strouhal number (Best, 1996, p. 79). At Re > 3000, this wake vortex system appears like a turbulent wedge (Karcz, 1973a) and increases to an almost chaotic stage at higher Reynolds numbers (Shen, 1971, p. 23–25). This analysis fits to the qualitative observation of an unstable current system even under steady flow conditions (Karcz, 1968, 1973b). The trailing vortex system (Fig. 74C) is composed of one or more discrete vortices attached to the top of the obstacle (Shen, 1971; Breusers et al., 1977). These vortices form when finite pressure differences exist between two surfaces meeting at a corner, resulting in a three-dimensional flow separation downstream of the obstacle. A fourth vortex system (Fig. 74C) could develop from the interaction of the trailing and wake vortex system in the far wake downstream of the obstacle. It is of secondary order, as it results from vortex systems generated by the obstacle directly, but has no direct contact with the obstacle itself. Also, the different scale of the vortex systems, especially in relation to the size of the obstacle, should be considered (Fig. 74): Even if Best (1996)—who uses a different terminology—mentions a different origin of the system, the interpose of the wake vortex system between the fourth system, the obstacle, and the horseshoe vortex system is evident. Confusion arises from the literature on the subject, as many different and even additional expressions for the vortex systems are used (e.g., standing, hairpin, wake shed, or cast-off vortices), and the meaning is overlapping (e.g., the horseshoe vortex system around the obstacle is merged with the wake system as focus is given to the currents near the obstacle where the scour occurs). In addition, three of the vortex systems appear as horseshoe forms in plan view (Fig. 74 and Karcz, 1973b), which increases the difficulties in comparing the descriptions from different authors. Shen (1971) comments that any, all, or none of the first three vortex systems can develop, depending on characteristics of the obstacle and free stream conditions. The distinction of four separate vortex systems as the result of flow separation phenomena is somehow theoretical, as under natural conditions turbulence (expressed by Reynolds numbers) will usually be too high for a distinctive separation of the systems. 5.7.2.2 Bridge piers. In engineering sciences, currents around isolated obstacles in rivers are studied intensively, as the collapse of bridges in many cases was caused by the failure of bridge piers by local scour at their grounding. Therefore, there is serious need to understand causes and processes of this phenomenon, and consequently numerous investigations in the field, in flumes, and by numerical models were carried out (compare the reviews with numerous references given by, e.g., Shen, 1971;

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Figure 74. Vortex systems associated with an isolated obstacle (modified on the basis of Best, 1996, Fig. 3.9 therein). A: The rolling down of the boundary layer in front of the obstacle. B: A horseshoe vortex system forms in front of the obstacle and extends toward the flanks. Downstream of the obstacle the horseshoe vortex system switches into the wake vortex system. C: A trailing vortex system develops from three-dimensional flow separation downstream of the obstacle and far-wake a fourth vortex system forms, resulting from the interaction of the trailing and wake vortex systems.

Breusers et al., 1977; Breusers and Raudkivi, 1991; Hoffmans and Verheij, 1997; Olsen and Kjellesvig, 1998; Melville and Coleman, 2000; Tseng et al., 2000). Especially some flume experiments with submerged or free-surface obstacles are difficult to apply in the field, as they are valid only for the limited range of conditions they are calibrated on (Johnson, 1995) and scale effects are frequently not regarded (Ettema et al., 1998). For other relationships, it can be impossible to measure input data in the field, especially during floods. According to the authors, the results typically fit to empirical relationships gained in the field. On the other hand, Johnson (1995) qualifies these allegations for some cases by comparing several equations with a consistent data set. Finally, guidelines and computer software on how to calculate and handle the problem are established (e.g., Richardson and Davis, 2001; Landers et al., 1996). Physically based equations, empirical relationships, data from flume experiments, or at least sketches of the current

system around a bridge pier were also used by earth scientists studying submerged or free-surface obstacles in the natural fluvial environment (e.g., Karcz, 1968; Underwood and Lambert, 1974; Allen, 1982; Russell, 1993; Fay, 2002). Some special boundary conditions valid for local scour around bridge piers are sometimes not regarded, especially the missing flow over the obstacle/pier, which can be of influence on currents downstream of an obstacle (Fig. 75). Karcz (1973a, p. 154) mentions the missing consideration of the current over the obstacle by modeling the flow like for a bridge pier, but estimates it as less important, as a tipping vortex at the rear top part of an obstacle would produce a linear scour in the obstacle lee. This kind of “inverse” obstacle mark—erosion downstream of the obstacle, not regarded in the overview by Allen (1982) (cf. Fig. 73)—occurs if the initial horseshoe vortex system does not develop (Shen, 1971, p. 23–25).

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Figure 75. Flow pattern around a bridge pier (modified after Bradley and McCutcheon from Russell, 1993, Fig. 2 therein). In principle, the pattern is similar to a simplified version of submerged obstacles (Fig. 74). The downflow in front of the pier is connected with the horseshoe vortex on the channel bed. Downstream, a wake vortex system develops, which rises directly toward the free surface of flow without any alternating shedding. As the pier is not submerged, no trailing vortex occurs, and therefore no interaction of this with the wake vortex system takes place, and the fourth vortex system does not form. In front of the pier at the water surface, a bow wave or surface roller (Melville and Coleman, 2000) forms, rotating in counter direction of the horseshoe vortex system, and causes a rising of the water level as the current reaches the pier.

The literature is surprisingly poor on obstacle mark studies with definitely submerged obstacles in a noncohesive erodible channel bed. Additionally, studies are qualitative and cannot be transferred. For paleohydrological reconstructions, advantage can be taken by following the advanced experiences of engineers of effects of specific parameters on local scour at bridge piers. Modeling of the complexity of the current systems at an obstacle is a very difficult task even under defined conditions. The following simplified list of factors is restricted to parameters of importance for paleohydrological reconstruction in fluvial environments (from various sources after Melville and Coleman, 2000, p. 193f., if no other references are given): • Effect of flow intensity, v/vc: Local scour at obstacles can occur under live-bed or clear-water conditions. Clear-water scour occurs for velocities up to the threshold velocity for general bed movement, so there is no sediment transport into the scour hole from upstream. Live-bed scour occurs when sediment is continuously supplied to the scour hole, and the equilibrium depth is attained when there is a balance between the sediment supply and that transported out of the hole. Clear-water scour conditions exist when the flow intensity v/vc < 1, where v is the mean flow velocity, and vc is the critical mean velocity at the threshold condition for sediment movement. Within the scour hole the horseshoe vortex system creates a flow velocity large enough to produce a shear stress to move the sediment, which is at least vc. Carstens (1966, p. 30) gives a relation of vc = 2 v for irrotational flow around a vertical cylinder under clear-water conditions; this ratio is generally confirmed by Hoffmans and Verheij (1997, p. 125). Live-bed scour is consequently defined by v/vc > 1. Scour depth variations under those conditions are a consequence

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of the size and steepness of the bed features occurring at particular flow velocities. The steeper and higher the bed forms, the lesser the observed scour depth, because the sediment supplied with the passage of a given bed form is not fully removed from the scour hole prior to the generation of the next bed form. The maximum live-bed scour depth occurs at about the transition flat bed condition when the bed forms are very long and of negligible height. The magnitude of the scour depth fluctuations due to bed-form migration is approximately equal to the half-amplitude of the bed forms. Effect of flow depth: The scour process at piers is influenced by the relation of pier width b to depth of flow y. Wide obstacles in shallow flow, such as walls, caissons, oil storage tanks, or oil-drilling platforms founded on the ocean floor, produce a scour hole with two depressions on the flanks of the obstacle, rather than one hole with the deepest scour occurring on the axis of symmetry in front of the obstacle (Melville and Coleman, 2000, Fig. 6.9 therein; Carstens, 1976; Carstens and Sharma, 1975). According to Hoffmans and Verheij (1997, p. 95), at a relationship of b/y < 0.5 a connected horseshoe vortex system exists on both flanks of the pier. As the ratio increases to 0.5 < b/y < 1.5 the connection becomes weaker and does not exist for b/y > 1.5. In this case, two separate scour holes develop on both sides of the pier. This phenomenon is caused by the strength of the downflow in front of the pier and its connection with the horseshoe vortex system formed by the currents on the flanks of the pier. If the distance between these currents—determined by the width of the pier—is too large, no support for scouring by the downward flow is given. This is caused

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by the missing connection of the current systems, leading to a decreased flow velocity of the downward current, and results in its decreased shear stress, making this flow ineffective in generating scour in front of the pier. For shallow flows, the scour depth increases with the depth of flow until a threshold is reached, and no further incision occurs. This effect correlates with the width of the pier, too. Flume experiments reveal a changing relationship between the depth of scour ys and the ratio of pier width b to the depth of flow y. For narrow piers, scour depth is proportional to pier width and is independent of flow depth; for wide piers, scour depth is related to flow depth without influence of pier width. For intermediate sizes, both factors influence scour depth (Table 19). In deeper flows with relatively narrow piers (b/y < 0.7), the strength of the horseshoe vortex system and associated flow down in front of the pier is related to the transverse size of the pier. Thus, the scour depth depends on the pier size. For intermediate size of piers or flow depths, the depth of flow influences local scour depth when the horseshoe vortex is affected by the formation of the bow wave. The two vortices have opposite directions of rotation. As long as they do not interfere with each other, the local scour depth is independent of flow depth like at narrow piers. With decreasing flow depth, the bow wave becomes more dominant and influences the horseshoe vortices to become weaker. Thus, the local scour depth is reduced for shallower flow. Effect of sediment coarseness: In general, studies on local scour at bridge piers were carried out with noncohesive sediments, as this is characteristic for river channel beds. In cohesive sediments, the similar processes occur, and scour depth will be similar, but it will take several times longer to form (Richardson and Davis, 2001). In coarse sediments with a ratio of obstacle widths to median grain size of b/d50 < 50, parts of the downward current in front of an obstacle can flow inside the porous bed and dissipate some energy. This reduces the energy of the horseshoe vortex system and results in a limited scouring effect. At b/d50 < 8 individual particles become large in relation to the obstacle and produce an individual current system, reducing the effect of the pier. The side slope of the scour hole depends on the local repose angle of the sediments as it adjusts to stable conditions by collapses of sediments into the depression (Melville and Coleman, 2000, p. 189). At high-velocity conditions, the sides of the scour hole can temporarily be nearly verti-

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cal (Jain and Fischer, 1980). As the repose angle depends on grain size, the angle of the slopes of the scour hole is influenced by the coarseness of sediments. These avalanching sediments also explain fluctuations of the live-bed scour depth (Raudkivi, 1991, p. 62) in addition to channel bed forms moving into the scour hole by the flow. Effect of sediment nonuniformity, σg: The degree of nonuniformity of sediments can be expressed as the geometric standard deviation of particle size distribution σg = d84/d50 (Hoffmans and Verheij, 1997, p. 120). For σg > 1.3–1.5 armoring occurs on the channel bed and in the scour hole and reduces the scour depth. Around the threshold condition of mean velocity of flow to critical mean velocity for sediment movement, v/vc ≈ 1, armoring occurs on the channel bed in front of the scour hole and at its base. The armored bed in the erosion zone at the base of the scour hole significantly reduces the local scour depth. Conversely, at high values of v/vc, when the flow is capable of entraining most grain sizes within the nonuniform sediment, the effect reduces. At intermediate values of v/vc, the effect of σg reduces progressively with increasing flow velocity between these two limits, as more and more of the grains are transported by the flow. Effect of obstacle shape: The effect of bridge pier shape on scour depth is a classical subject of numerous studies resulting in various lists of correction factors for shapes different from cylindrical (e.g., Melville and Coleman, 2000, p. 203; Raudkivi, 1991, p. 73f.; Hoffmans and Verheij, 1997, p. 119). The factor depends on the degree of a streamlined contour of the obstacle. Highest values are obtained for sharp-edged rectangular shapes (1.5) continuously decreasing as, for example, semicircular nooses smooth the shapes toward the ideal cylindrical form (1.0). Elliptic and lenticular shapes produce less scour depth as the coefficients decrease down to 0.8–0.6. Obstacles with a tapered shape toward the water surface decrease scour depth to ~0.8 (Raudkivi, 1991, p. 74) as the flow downward in front of the obstacle becomes weaker. Effect of obstacle alignment: Streamline effects of obstacle shapes are negated if the flow does not hit the obstacle at the smallest and smoothest flank, as long as it is not cylindrical. Under natural conditions, obstacles are deposited under optimal streamlined conditions, as the drag of flow leads to an oriented transport and deposition (Futterer, 1977, 1978). As the angle of alignment increases, the scour depth grows because the effective frontal width increases.

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J. Herget For rectangular obstacles with a length/width ratio of 16/1, scour depth could increase by a factor of up to 7 if the flow reaches the obstacle at the long instead of the small side. Asymmetric forms of the scour hole and the current shadow can be caused if the smallest width of a symmetrical obstacle is not normal to the flow. For obstacle marks in natural environments, this effect is of importance, as, for example, in braided-river environments, where such differences of alignment can occur. Effect of time: The process of scouring is asymptotic. Under clear-water conditions, the scour depth develops asymptotically toward the equilibrium depth of scour; the equilibrium depth of a scour hole is reached in a matter of days for flumes or weeks for rivers. In a live-bed environment, the equilibrium depth is reached faster, as the flow velocities are higher; afterwards the scour depth oscillates due to the passage of bed features past the obstacle. In flumes, equilibrium conditions for live-bed scour can be reached within minutes (Raudkivi, 1991, p. 70). According to the shape of the hydrograph of a passing flood, a live-bed scour hole generated during rising or peak flood conditions may increase beyond if the recession period lasts long enough to prevail near threshold conditions. Therefore, all effects on the process and depth of local scour presume steady flow. Effect of Froude number, Fr: In flume experiments, Boyer and Roy (1991) found a relationship between the Froude number and the shape of the currents around a nonsubmerged spherical obstacle, which can be assumed to form scour and current shadow shapes comparable to those of a bridge pier (Fig. 76). At low velocities with low Froude numbers, the frontal bow wave is bent around the obstacle but forms a wide angle, leaving a large low-pressure zone on the sides of the obstacle. This zone allows a secondary vortex, which

can be related to the wake vortex system, to detach from the horseshoe vortex system immediately surrounding the obstacle. The secondary vortex produces a zone of erosion marked by a furrow and zones of sedimentation in the shear layers. In principle, deposition occurs more or less like a widespread current shadow. As velocity increases, the sedimentary structure becomes a simple current crescent with a small sand shadow tail in the lee of the obstacle, and the area of deposition between the surface wave and the secondary vortex practically disappears. This is explained to be caused by the refraction angle of the wave, which becomes more acute and gradually surrounds the obstacle, thereby constraining the lateral expansion of the secondary vortex. For high Froude numbers, Raudkivi (1982, p. 168) mentions the accumulation of transported sediments in front of a pier instead of scouring; unfortunately no threshold is mentioned. Additional data lists, figures for illustration, and equations for quantifying the effects mentioned before are presented by Melville and Coleman (2000), but space is limited in this study to expand the overview on factors influencing local scour at bridge piers. As the focus is laid on single isolated obstacles, the effect of adjacent obstacles is left out (cf., e.g., Bunte and Poesen, 1994). As the failure of bridge piers due to scouring is the motive to study this phenomenon, it is not surprising that investigations of the depositional area in the current shadow are very limited. 5.7.3 Examples of Obstacle Marks in Chuja and Katun Valleys Obstacle marks belonging to the jökulhlaups were found in two places in the Chuja and Katun valleys. One is formed around a boulder in the boulder field near the village of Inja in Katun valley, the other at a bedrock hill at the eastern margin of Chuja Basin near the village of Chagan-Uzun.

Figure 76. Synthetic diagram of current shapes around a free surface obstacle at flows of different Froude number (Boyer and Roy, 1991, Fig. 9 therein, modified). The velocity of flow was changed from 0.28 cm/s to 0.45 cm/s, which changes the Froude number Fr from 0.89 to 1.52 at a shallow depth of flow of 1.0 cm and 0.9 cm respectively. The spherical obstacle had a diameter of 7.2 cm and was half buried in noncohesive sand with d50 = 0.56 mm.

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Figure 77. Sketch map of the obstacle mark at a boulder near Inja village based on surveyed data. Surveyed points are marked by different symbols. While the left margin of the scour hole can be determined by a change of the vegetation cover, the right margin is destroyed by the ditch. The extension of the scour hole at the right side of the boulder is assumed according to symmetry.

Obstacle mark around the boulder near Inja village. The obstacle mark and the boulder near Inja village were surveyed by theodolite, revealing data for a map of the location (Fig. 77). The minimum width of the boulder is 10.8 m, its length measures 13.8 m, and the height above the surface is 3.1 m (Fig. 78). The scour hole is filled with loess, which is assumed to be deposited after the flood events. A fluvial refill of the scour hole can be excluded, as no indicators for this could be found during investigations of the exposed sedimentary structure of the fill (cf. Underwood and Lambert, 1974). The maximum surface width of the scour hole is ~24.3 m and can easily be separated from the surrounding gravel of the channel bed by a different vegetation cover. Parts of the scour hole are exposed in an artificial ditch, which allows a view of some parts of the internal structure (Fig. 79). The median grain size of the channel bed around the boulder is d50 = 14 mm, with a geometric standard deviation of σg = 6.8 (Fig. 80). Armoring at the boundary layer between the gravel bed and the loess fill of the scour hole was not observed. Like many of the boulders in the area, the surface of the well-rounded boulder is streamlined. The orientation of the keel line is indicated in Figure 77 by an arrow. The boulder is of a relatively symmetric shape. The maximum depths of the scour hole below the surface are 2.27 m and 1.30 m, while the frontal part of the boulder and modifications by the

Figure 78. Surveyed profile of the boulder along the keel line.

ditch prevent the determination of the ultimate scour depth and its extension. Consequently, the survey points of the scour depth in Figure 77 do not mark the lateral extension of the scour hole. It might be assumed that the boulder is tilted into the scour hole in its front during the erosional process, as there is evidence for this frequent plunging effect from the literature (e.g., Johansson, 1963; Sengupta, 1966; Futterer, 1978). In the wake of the boulder, a gravel hump with a maximum height of 0.5 m is deposited, which can be regarded as current shadow. Downstream, this hump and the loess cover are fading out, making it difficult to determine their distal termination.

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Figure 79. Photographs of the obstacle mark at a boulder near Inja village. A: The bottom of the scour hole exposed at the wall of the ditch is clearly visible through the separation of the loess fill of the scour hole at the gravels of the channel bed. At the right side of the boulder, the gravel hump is indicated by a change of vegetation cover. Parts of the boulder field near Inja village and of the giant bar between Inja and Little Jaloman villages are visible in the background. Flow direction is from left to right. B: The frontal extension of the boulder into the scour hole is visible. View is approximately along the keel line, and flow direction was toward the background.

Figure 80. Grain-size parameter of the channel bed at local scour locations.

The orientation of the keel line on the boulder surface in relation to the gravel hump in the lee of the boulder is problematic, as they are not in line. Theoretically, this could be caused by: • an asymmetric obstacle mark development, • the tilting of the boulder with a potential rotational move, or • a modification of the direction of flow between the time of forming the smooth streamlined surface of the boulder and the scouring at the boulder later. An asymmetric form of the obstacle mark is less plausible, because the boulder is well rounded; its symmetry on the surface is not significantly unaligned with the direction of flow (which is determined by the orientation of the valley), and no other obstacles nearby influence the current system. The missing influence of the unaligned orientation of the boulder can be quantified

in a worst-case sensitivity study: The relationship of boulder length to width along the smoothest profile along the keel line gives 13.8 m / 10.8 m = 1.28; the angle between the keel line and the direction of flow is ~45° (cf. Fig. 77). According to Melville and Coleman (2000, p. 207), the factor of increasing scour depth for unaligned bridge piers under the given conditions is ~1.14 (rough interpolation, as the nomogram data start for a length/ width ratio of 2). This factor would increase the maximum depth of 1.30 m to 1.48 m, which is significantly less than the surveyed depth of 2.27 m. This calculation is only valid if an asymmetric obstacle mark is assumed, which characteristically occurs under unaligned conditions. A slight turn of the boulder during the abrupt plunge into the scour hole in front cannot be excluded, as Futterer (1977, Table 7

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia therein) documents turns of a nautilus shell of 90° during the forward movement against the direction of flow into the scour hole. After this, the shape of the scour hole in her flume experiments became asymmetric as the nautilus shell came into a nonstreamlined position. But this turn was forced by a shift of the balance point of the obstacle, because the shell filled with sediments from the suspension load of the flow. Therefore, these data cannot be used as evidence for the assumed turn of the boulder out of the streamlined position against the flood. According to Kelling and Williams (1967), no data about values of the assumed horizontal turn can be transferred directly from their flume experiments on the reorientation of pebbles during a flood. High velocities of flow, leading to a strong angular deviation during single flood waves, would cause mobile bed forms on the channel bottom during a continuous flow, which block the horizontal turn of pebbles. Also, Fahnestock and Haushild (1962) only describe vertical rotation of pebbles and cobbles of 90°–270° by their movement into the scour hole in front. Consequently, the high value of >45° between the streamline on the boulder surface and the tangent at

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the inner edge of the current shadow near the boulder seems to be too high for a turn of a boulder of these dimensions. The most plausible explanation seems to be to consider that the directions of flow being responsible for the streamlined surface of the boulder and for the location of the current shadow in its wake do not have to be identical, as these features might be formed during different periods of the flood. One can assume a deposition of the boulder in an early stage after the peak of the flood. During this time the giant bar between the villages of Inja and Little Jaloman, visible in the background of Figure 79, was not finally deposited. Therefore, parts of the valley—now covered by the bar—were free for the discharge. By a look at a topographic map (Fig. 81), this open valley is oriented NW instead of NNE like today. The shift of the orientation of the valley to NNE is caused by the deposition of the bar, extending from the slopes of the mountains on the left side of the valley into the main course, during the initial stage of the falling limb of the flood. While the flow was directed NW, the suspension load formed the streamline of the boulder, and later the scour hole at the boulder

Figure 81. Map of the location of the boulder near Inja and adjacent area. The distance of grid lines equals 1 km. The gravel dunes ~1 km downstream of the boulder are not related to the scour phenomenon. Their orientation along the valley direction after the deposition of the giant bar indicates that they are younger than the initial phase of deposition of the giant bar between the villages of Inja and Little Jaloman.

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was formed while the flow was already sent NNE. This change of flow directions fits with the orientation of the two features (Fig. 77), and no horizontal turn of the boulder must be assumed. The ultimate depth of the scour hole could not be determined, as drilling equipment for a depth of >2 m was not available. On the other hand, the location of the observed maximum depths contains important information on the characteristics of

the scouring process, and thus on the conditions of flow forming the scour hole as it is preserved. The maximum observed depth of 2.27 m is not situated in front of the boulder, but at the flank. The surveyed depth in front of the boulder is only 1.30 m. Both points are in the center of the horizontal extension of the scour hole at the flanks of the boulder, showing a comparable distance from the boulder’s circumfer-

Figure 82. Photographs of the scour hole around a bedrock hill near Chagan-Uzun village. A: The direction of flow is indicated by the arrow. The deepest parts of the scour hole in front of the hill are indicated by dark green vegetation. Beyond the hill, the step down to the incised valley of Chuja River is visible. Confluence of Chagan-Uzun and Chuja River with Chagan-Uzun village in the background. B: The separation of the scour hole and the antidunes is obvious. Chuja River is located in front and Chagan-Uzun River in the background beyond the antidunes. Flow was approximately left to right.

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ence, while the right side of the extension of the scour hole can only be estimated. This obviously indicates a shallow flood in comparison to the boulder’s width, as the position of the deepest parts of the scour hole on the flanks of an obstacle is characteristic for such conditions. Obstacle mark near Chagan-Uzun village. Near the confluence of the Rivers Chagan-Uzun and Chuja at the village of Chagan-Uzun, a scour hole has formed around a bedrock hill (Fig. 82). This obstacle mark is located in the former lake basin at the western margin of Chuja Basin (Fig. 83). The hill and the scour hole were surveyed by tape, revealing a height of the hill of ~50 m. The rock of the hill is highly weathered, forming a coarse surface of the slopes and a debris mantle at some locations at the foot of the hill. This weathering restricts information of the shape of the hill during the scouring flood to a description of its rough dimensions, even though there is an obvious steeper slope of the hill on the lee side than in the wake. The scour hole has a maximum depth of 8.1 m and a length of 91.5 m. The ground is partly covered with well-rounded boulders of up to 0.6 m in mean diameter. The thickness of this layer is ~0.5 m and can be characterized as an armoring layer. This fits with the grain size data of the channel bed (the median diameter is d50 = 44 mm), while the geometric standard deviation σg reaches a value of 8.3 (Fig. 80). The hole extends along the whole width of the hill for nearly 400 m but terminates immediately at the flanks of the hill. At this point, a weakly developed current shadow sets in and reaches a maximum height in the wake of

the hill of ~4 m. Due to the gentle slopes of the current shadow and its relatively coarse material, its extension is not clearly determinable in the field. At the eastern side of the hill the River Chuja has eroded parts of the wake area behind the hill, but due to the symmetry of the scour hole a development of a current shadow might be assumed here as well. Regarding the orientation of the scour hole in front of the hill, the flow must have reached the hill from a southwestern direction. The flow forming the scour hole was coming from the area west of the mountain “1941.0” instead of through the recent Chuja valley farther east (Fig. 83). The inset of the current shadow immediately at the flanks of the hill supports this interpretation. This direction of flow is comparable with the orientation of the antidunes west of the hill toward the valley of the River Chagan-Uzun, even if a steep angle between the directions is observed. While the antidunes are oriented directly toward the outlet of Chuja Basin beyond the village of ChaganUzun, the flow at the hill had a slight tendency toward the east. The antidunes are clearly separated from the obstacle mark area by a more or less plain or only slightly undulated surface (Fig. 82B). It might be interpreted as an indicator that the antidunes blocked the main course of the falling limb of the flow out of Chuja Basin and sent it in a slightly eastern direction before turning again to the north beyond the hill. The current might not have been strong enough to modify the antidunes during the waning flood. But clearly, the recent form of the obstacle mark developed after the forming of the antidunes.

Figure 83. Map of the scour hole location near Chagan-Uzun village and adjacent area. While the antidunes indicate a direction of flow toward the north, the hill with the scour hole and an altitude of 1775.1 m was reached by a current of northeastern direction. Obviously, the flow was coming from the area west of the mountain “1941.0” instead of through the recent Chuja valley. Grid line distances equal 1 km.

5.7.4 Paleohydraulic Calculations Previously, obstacle marks have been occasionally used for paleohydraulic estimations. For different reasons all studies are semiquantitative or only qualitative. Obstacle marks from ephemeral streams are investigated by Karcz (1968), who gives qualitative relationships between the geometric elements of the obstacle, the crescent scour hole depth, and dimension of the current shadow in a scale range of 10–50 cm by plotted data sets. He compares the flow system around the mostly submerged (!) obstacles with those around bridge piers. Elfström (1987) observed an upstream accumulation with a downstream scour hole at a boulder of 4 m mean diameter. He did not carry out any calculations, as the knowledge about flow characteristics did not seem to be sufficient, and further basic research on the subject was requested. Along the pathway of the Lake Missoula flood; Baker (1973a, p. 41) surveyed a scour hole on the upstream and downstream side of an 18 × 11 × 8 m boulder, but only gives principal comments on the processes forming scour holes around obstacles. He explains the missing current shadow in the wake of the boulder by very high flow velocities reinforcing the current system downstream of the boulder, up to a strength for acting erosively on the bed material (Baker, 1973b, p. 145). From obstacle marks around grounded ice blocks in Greenland, Russell (1993) describes scour in front and occasionally at the flanks of obstacles while deposition occurs in the current shadow

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J. Herget approaching the obstacles near Inja and Chagan-Uzun can be estimated as

as either downstream tapering ridges or mound-like forms transverse to the paleoflow direction. Application of empirical relationships derived from bridge pier investigations between ice block size and scour depth lead to an overestimation of scour depth. Finally, he could only determine the depth of flow in the range between the height of the sediments in the current shadow and 0.5–0.9 times the diameter of the ice block, as they would start rolling or even floating in deeper flow. As the obstacle mark patterns at Inja and Chagan-Uzun are similar to those around bridge piers, paleohydraulic calculation may be based on experience from engineering sciences. The similarity is evident for both locations: The scour holes are in front and at the flanks of the obstacles—never in the wake, as it is described for currents of special conditions flowing over (!) obstacles exclusively. Sediment accumulations, which can be accounted for as current shadows, are deposited in the wake of the obstacle, characteristic for scouring at nonsubmerged obstacles, too. As forming of a scour hole principally depends on time, the leftover scour dimension represents the flow condition during the final stage of the jökulhlaups. Even if a scour was produced during deeper flow conditions before, it was modified in relation to shallower flow later. This is the scour shape observed in the field today. First, information about effects influencing scour characteristics at bridge piers are checked for suitable information of flow conditions during the scouring process. In a second step, the empirical relations for the determination of scour depth are checked for applicability. Flow velocity. Flow velocity can be determined by regarding the relationship between the grain size of the eroded sediments and the flow velocity of the horseshoe vortex system. The velocity of flow critical for erosion at the bottom of the scour hole is identical with the velocity for channel bottoms in general, vcb, and therefore can be determined by an equation after Mavis and Laushey from Zanke (1982, p. 170):

For the boulder near Inja an assumption of a maximum flow velocity based on this method is not possible, as no armoring layer is observed. The maximum velocity for the location of the boulder can be estimated based on the assumption that the suspension load deposited as the giant bar between the villages of Inja and Little Jaloman was not in transport anymore because of decreased flow velocity during the formation of the scour hole. The missing of another keel line in the direction of flow over the boulder toward the current shadow supports this assumption. Consequently, the velocity of flow was below the threshold for transport related to the grain size of the giant bar. This value is given by the equation for the critical mean velocity vc for the setting of erosion for a given grain size by Zanke (1982, p. 170) (cf. Section 5.5):

vcb = 15.2 d50 4/9 ρ′ 1/2

vc = 2.8 (ρ′ g d)0.5 + 14.7 υ / d

where the velocity is given in cm/s, d50 is the mean diameter of eroded sediment in mm, and ρ′ is the relative density ( = 1.65). For the sediments at the scour holes at Inja (d50 = 14 mm) and Chagan-Uzun (d50 = 44 mm), the critical velocities are 63 cm/s and 105 cm/s. These velocities are lower than the mean velocity in a channel for erosion at the channel bed like given by the Hjülström diagram, because of the logarithmic vertical velocity distribution for fully turbulent flow. As the flow velocity of the horseshoe vortex system is calculated, mean velocities of the flow cannot be applied here. In this case, the rotational vortex system makes it too complicated to apply physically based equations regarding drag force and bed shear velocity. As the mean velocity of flow is about half of the critical velocity vc of the horseshoe vortex system (Carstens, 1966, p. 30; Hoffmans and Verheij, 1997, p. 125), the flow velocity

With values of 1.65 for the relative density of the sediments, ρ′, acceleration of gravity g = 981 cm/s2, kinematic viscosity υ = 0.01519 cm2/s at an assumed temperature of water of 5 °C, maximum grain size of the suspension gravel of the giant bar of dmax = 1.6 cm, and a mean grain size d50 = 0.13 cm, the maximum velocity of flow can be determined as

minimum v (Inja) ≈ 0.3 m/s minimum v (Chagan-Uzun) ≈ 0.5 m/s These values are minimum velocities, as the horseshoe vortex system might have been faster than the minimum velocity required to erode the scour hole for the given grain size of the sediments. The armoring layer of the scour hole near Chagan-Uzun can give a rough estimation of the maximum flow velocity possible, as the boulders of a mean diameter of 0.6 m are not transported. As detailed information on the grain size distribution of the armoring layer is missing, the estimation analogue to the method above is a crude approximation only. The boulder size of ~0.6 m yields vcb = 335 cm/s; therefore, the maximum mean flow velocity can be assumed as 1.7 m/s: maximum v (Chagan-Uzun) = 1.7 m/s

maximum v (Inja dmax) = 1.4 m/s maximum v (Inja d50) = 0.4 m/s In the above equation, the cohesion of the sediments is neglected, which is acceptable for the coarse material. Also, a direct transition from the critical velocity for erosion to deposition is implied, and the conditions for transport are skipped. By comparison with the classical diagram by Hjülström this is

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia acceptable, as even for the logarithmically scaled diagram this range of velocity is very small for grain sizes >2 mm. Depth of flow. Minimum values for the depth of flow y can be derived from the height of the current shadow, as this was deposited during the flow forming the scour hole: minimum y (Inja) = 0.5 m minimum y (Chagan-Uzun) ≈ 4 m The depth of flow during formation the obstacle marks is indicated by the location of the deepest part of the scour hole at a nonsubmerged bridge pier or other obstacle. As mentioned above, the deepest parts of the scour hole at the boulder near Inja are situated at the flanks. This is typical for shallow flow conditions, as this geometry of the scour hole is influenced by the ratio of obstacle width b to depth of flow y. As the scour hole in front of the boulder is less deep than at the side but is not interrupted, a ratio of 0.5 < b/y < 1.5 can be assumed. From surveyed data in Figure 77, the width of the boulder normal to the direction of flow can be estimated as ~13 m. This yields a depth of flow of 8.7–26 m. For these values, the boulder of 3.1 m height would have been submerged during the scouring process. A ratio of 4.3 is needed to keep the boulder nonsubmerged, but this value is significantly higher than the threshold number of 1.5 for two separated scour hole depressions. However, this empirical relationship derived from bridge pier investigations cannot be applied for the scour at the boulder. Confusion arises from the fact of the symmetry of the scour hole in relation to the width of the hill near Chagan-Uzun, too. As symmetric scour holes in front of wide nonsubmerged obstacles form only if b/y < 0.5, this relationship leads by a given width of the obstacle of 392 m to a minimum depth of flow of nearly 800 m. As the maximum altitude of the lake level was at 2100 m and the altitude of the surface around the hill is ~1725 m, the water surface during the flow forming the scour hole should have been theoretically at ~2500 m, which is clearly too high. The hill with a height of 50 m would be definitely submerged, which does not fit to the presumptions of the applied relationship. Considering the hill like an abutment in a river channel cannot solve the problem, as the deepest parts of the scour hole at such kind of obstacle form at the flank (e.g., Melville and Coleman, 2000, p. 191). As the deepest part of the scour hole is located in front of the hill and decreasing depths occur in both directions along the face of the hill, no other assumed direction of flow could solve the problem. The dimensions of the obstacles and scour holes are beyond experiences on processes forming obstacle marks and beyond empirical data from engineering sciences. Other theoretical solutions derived from fluid mechanics (e.g., Lamb and Britter, 1984; Raudkivi, 1990; Schlichting and Gersten, 1997) cannot be applied, as more input data are needed than can be assumed

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seriously for paleohydraulic analysis. To find applicable information on the relation between scour holes and obstacle width, basic research is needed, especially for large obstacles and the influence of submergence. Froude number. The Froude number of the currents at the obstacles at Inja and Chagan-Uzun has not been very high, as no deposition of transported sediments can be observed. Unfortunately, there are no threshold values given in the literature to quantify the maximum Froude number. The flow pattern around a nonsubmerged obstacle depends on the Froude number. As shown in Figure 76, the different shape of the current shadow and extension of the scour hole can retain the flow condition of local scouring processes. At the boulder near Inja, the scour hole extends clearly beyond the flanks of the boulder, and the current shadow consists of a single tail in the wake (Fig. 77). Even though the pattern is not identical, as the tail is not connected directly with the boulder, the principal appearance can be related to those for Fr >> 1. On the other hand, this assumption of supercritical flow in the location of the continuously broad and gently sloped valley bottom downstream of Inja village provokes skepticism, as subcritical conditions of flow are expected. Assuming a Froude number of Fr = 1.5, as in the experiment of Boyer and Roy (1991), and adopting the maximum flow velocity of v = 1.4 m/s from the interpretation of the missing keel line in the direction of the flow, the depth of flow y can be estimated: Fr = v / (g y)0.5 ⇔ y = (v / Fr)2 / g The depth of flow would be calculated as ~0.09 m, which is clearly too low to form a scour hole with a depth of >2 m and a current shadow of 0.5 m height. Lower velocities even decrease the calculated depth of flow. At the hill near Chagan-Uzun, the configuration of the scour hole and current shadow indicates subcritical flow conditions with Fr < 1, as the scour hole terminates at the flanks of the hill and the current shadow covers a broad area in the wake (cf. Figs. 76 and 82). After the flood, erosion by Chuja River deleted the eastern edge of the scour hole and parts of the current shadow, but the remaining features indicate former conditions of the flow. The application of the relationship mentioned above derives a depth of flow of 0.37 m for a maximal velocity of flow of v = 1.7 m/s (indicated by the gravels of the armoring layer) and Fr = 0.89 given by Boyer and Roy (1991) (cf. Fig. 76). Compared with the height of the current shadow of ~4 m, this depth is clearly too shallow, as well. A scale problem of the transfer of the generalized experience of relation between the shape of the current shadow and Froude number must be assumed, even if Boyer and Roy (1991, Table I therein) observed scour depths up to more than three times the depth of flow.

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Empirical relationships for bridge piers. Numerous empirical relationships for the determination of the depth of a scour depending on mainly the bridge pier width have been developed; overviews are given, for example, by Melville and Coleman (2000), Hoffmans and Verheij (1997), Johnson (1995), or Breusers and Raudkivi (1991). Controversially discussed is the importance of the different factors controlling depth of scour and the range of validity of the equations, which is frequently not mentioned. This can be illustrated by the established experience of the ratio between depth of scour ys and width of pier b being in the range of 0.3 < ys/b < 2.5 (Raudkivi, 1991, p. 67; Melville and Coleman, 2000, p. 240), which is beyond any significance for a first step. For the scour holes in the Altai Mountains, the ratio of scour depth to obstacle width is ~0.02 for the location near Chagan-Uzun and 0.17 for the boulder near Inja. This comparison indicates that the empirical relationships for the local scour at bridge piers are not suitable for the calculation of the obstacle marks investigated here. Ignoring this indication of limited validation of the equations resulted in values that are clearly unrealistic. Additionally, as the empirical equations were improperly used to solve for independent variables, as the dependent values such as scour depth are given from evidence in the field. Williams (1983a) warns about the misuse of regression equations and documents that the error involved can amount to several hundred percent. Calculation of discharge. With plausible values determined above, a rough calculation of the discharge through Katun and Chuja valleys while the obstacle marks are formed will be carried out. For the location of the boulder near Inja, minimum depth of flow is given by the height of the current shadow as y = 0.5 m. The maximum velocity of flow is given through the missing transport of the coarsest grains of the suspension load, forming the keel line on the surface of the boulder. While on one side the absolute minimum value is chosen, the still realistic-appearing value for velocity of flow v = 1.4 m/s might compensate an underestimation of depth of flow. The width of the valley at the given altitude is about w = 1160 m, given by a little terrace step toward the west and the valley slope at the opposite side of Katun River. Therefore, the discharge of the flow forming the scour hole at the boulder near Inja can be estimated as about Q = v w y ≈ 800 m3/s.

At the bedrock hill near Chagan-Uzun, the minimum depth of flow is about y = 4 m, indicated by the height of the current shadow. The maximum flow velocity is 1.7 m/s, given by the grain size of the armoring layer of the scour hole. The width of the valley is ~1700 m, while the flow with a depth of 4 m was limited by the antidunes and the valley slope at the other side of the recent Chuja River. A discharge of 11,500 m3/s can be estimated. 5.7.5 Discussion The value of the obstacle marks as an indicator for the paleohydrology of the jökulhlaups in the Altai Mountains is limited. The reasons are firstly the unknown point of time the scour holes are formed during the flood’s hydrograph. Assumptions of correlated other indicators (e.g., antidunes near Chagan-Uzun with the scour hole nearby) are neglected, as paleohydraulic estimation would be based mainly on them, not on the obstacles marks themselves. The estimated flow velocities and discharges indicated by the scour holes are conservative estimations. As scour holes are dynamic fluvial forms, they indicate only the last part of the flow, being still strong enough for their formation. Theoretically, the complete disappearance of the scour hole could happen if the discharge decreased rapidly and the depressions were refilled by transported sediments of the final stage of the flood. Therefore, the falling limb of the hydrograph must have been steep enough to avoid this. On one hand, this appearance is characteristic for ice-dammed lake outburst floods (cf. Chapter 2); on the other hand, it has been observed frequently in other fluvial environments where obstacle marks can be observed on channel beds after floods. Discharge calculations by the use of obstacle marks as an indicator for hydraulic conditions are a difficult task at the current state of knowledge of the processes involved. Many experiences are gained by investigation of local scour at bridge piers. But piers are not submerged, and therefore no flow over these obstacles occurs. For submerged obstacles, knowledge of hydraulic conditions of the three-dimensional flow is still limited, especially in applied earth sciences beyond studies in pure fluid mechanics, which request unavailable input data. Further basic investigations are needed, mainly flume experiments with sub- and supercritical flow over submerged obstacles with varied depth of flow over an erodible noncohesive channel bed.

Geological Society of America Special Paper 386 2005

Chapter 6 REVIEW OF DYNAMICS OF THE ALTAI JÖKULHLAUPS Based on the previously given analysis of flood indicators, a chronology of their generation with related interpretation of the flood’s dynamics can be derived. Elements of the floods that cannot be modeled at the current state of knowledge can also be considered qualitatively. The mechanism of the ice dam’s failure seems to be a subject of speculation due to missing information on the dam itself. The dam extended from the inlet of Chuja Gorge to the area downstream of Chibit village over a length of ~20 km (Fig. 13). It is not definitely known whether the dam consisted of a solid unified block of ice or of several glacier lobes along the valley mouths in the area. The results of previous research on the Quaternary glaciations of the Altai Mountains differ, and our investigation could not be developed to a certain statement on the nature of the ice dam. A subaerial breach of the entire solid mass of ice seems to be difficult to imagine, even if such scenario is given for the Lake Missoula flood with an even larger dam, due to the significantly lower peak discharges for alternative drainage processes (O’Connor and Baker, 1992, p. 277). Assuming the dam consisted of several glacier lobes covering the areas only partly up to 600 m, subaerial breach seems to be more plausible. The development of the initial flood wave might have been retarded by other glacier lobes downstream of the ice dam at the mouth of Mashej valley. Alternatively, overspill or conduit roof failure after initial englacial drainage related to a rapidly increasing discharge can also be considered as a realistic drainage process for a large solid ice dam. Due to missing information on the ice dam and its failure mechanism, modeling of the initial flood wave (e.g., Vischer and Hager, 1998, p. 271f.; Stansby et al., 1998; Clark, 1982) is a difficult task that could mainly be based on assumptions for parameters of the glacier and lake-water conditions. However, the stream power of the initial flood wave can be expected to have eroded all deposits along the flood’s pathway in Chuja and Katun valleys, such as previously developed river terraces. The valleys were stripped down to the bedrock surface at the valley flows, as indicated by the deposition of characteristic suspension gravels at the elevation of the current mean water level of the rivers that are flowing in bedrock channels. Missing exposures of suspension gravel near the river channel along Chuja valley can be explained by the significantly steeper slope of the valley and absence of extended backwater locations in deeper elevations. Also, by stream power of the initial flood wave the bedrock of the valley slopes can be expected to be eroded, leading

to an increasing load of suspension gravel along the valleys. This suspension load is deposited in backwater areas and at the inner bank of valley bends. Run-up sediments dropped in front of local obstructions indicate the maximum depth of flow of ~400 m during peak discharge. They are related to the surfaces of giant bars indicating the minimum water level of this stage. For both paleostage indicators, a peak discharge on the order of 10 × 106 m3/s can be estimated by different methods. This value of peak discharge is considerably less than the previous estimations by Baker et al. (1993) and Butvilovsky (1993). The calculations are based on a significantly increased amount of paleostage indicators distributed along nearly 90 km downstream of the ice dam area. Simultaneously, bed load is transported initially like foresets of a Gilbert-type delta downstream along the valleys (Carling et al., 2002, p. 31f.). After the filling of the lowest part the valleys with this bed load, the related deposits are already reworked by the continuous flow, which is why only locally the large foreset structures are preserved. Even if the process of the formation of the broad bed-load terrace (Inja Terrace) has not been investigated in detail yet, the boulders near Inja village are obviously deposited at the final stage of the bed-load terrace formation. They are found on the surface of the terrace level without any indicator of coverage. During this stage of the flood, the suspension gravels must still have been transported, as they are the only source of material to cause corrasion leading to the streamlined surface of the boulders. The keel line of the boulder with the obstacle mark investigated in detail is not oriented along the current direction of the valley, which is fixed by the lateral extension of the giant bar between the villages of Inja and Little Jaloman. Hence, this bar did not reach its maximum final recent extension when the boulder was deposited. A discharge of ~3 × 106 m3/s is roughly estimated as minimum discharge for the stage of flood when the boulders were deposited and the formation of giant bar nearby was terminated. The estimation of the competence of flow is limited due to uncertain macroturbulence effects leading to an overestimation of related hydraulic parameters. On the same level of the bed-load terrace as the boulders, the gravel dunes at Little Jaloman village are formed. The generation of this bed form indicates that bed-load transport might have been at the final stage but did not conclude completely. Probably the generation of the dune field was mainly based on a reworking process, as the discharge for the generation of this dune field is estimated as 0.5–0.9 × 105 m3/s. The other dune fields, except those located upstream of Chemal and at Platovo, are located in the basin of the former lake. They are generated sometimes during the drainage process of the lake at relatively

101

102

J. Herget

low water depths compared to the maximum volume of the lake. Their orientation is influenced by local topographic conditions, while previously the occurrence of giant eddies was derived from their orientation against the general slope of the valley and basin system. At least during this stage the secondary lakes are formed behind the giant bars. The flood did not reach the highest parts of the giant bars anymore; therefore, discharge from tributary valleys accumulated behind them. Probably, also water from the flood itself was stored in the tributary valleys. At different stages of the falling limb of the flood’s hydrograph, the levels at the slopes of several giant bars are formed, and run-up sediments at local obstructions in lower elevations are deposited. During the final stage, the flow was a relatively thin layer of a few meters depth eroding the giant bars laterally on the level of the surface of the bed-load terrace. This final erosional process is indicated by the braided river structure of the suspension gravel in one section near Little Jaloman village. The final process related with the flood itself is the generation of the obstacle mark at the boulder near Inja village. A discharge of only ~800 m3/s is estimated for the generation of the scour hole in clear water without suspension gravel transport. During the further decrease of the discharge back to preflood conditions, the rivers began to incise into the bed-load terrace level and form a river channel similar to the present conditions. Significant lateral erosion did not occur, as indicated by the missing structures of a meandering river. In several previous paleoflood reconstructions, dynamic features such as gravel dunes and obstacle marks and also deposits consisting of large boulders were related to peak discharge derived by methods other than the interpretation of the features themselves. Gravel dunes and obstacle marks grow up parallel to the increasing flow

and decay again during the reduction of the current. Hence, their dimensions and geometries indicate an unspecific stage of the decreasing flood. During the final stage of the flood, boulders are still transported and cannot be related to flow conditions of the peak of the hydrograph. The duration of the outburst flood is difficult to estimate. Unrealistic assumptions of a constant peak discharge of 10 × 106 m3/s results in a minimum continuance of 16 h. Without any doubt, this is an implausibly short period to drain a lake of a volume of 607 km3 at its maximum stage. For present-day jökulhlaups, a ratio of peak discharge to mean discharge of 2–6 (Desloges et al., 1989) is found. Applying this ratio to the peak discharge of the floods along Chuja and Katun valleys results in estimations for the mean discharge of 1.7 × 106 m3/s to 5 × 106 m3/s. Assuming the values as realistic estimations results in a duration of the drainage of the entire ice-dammed lake at maximum stage of 1.5–4 d. Even if the validity of the empirical relation is not given, the results seem to be realistic compared to the larger outburst flood from Lake Missoula, which is assumed to have had duration on the order of days (O’Connor and Baker, 1992). Nevertheless, the floods draining the entire ice-dammed lake in Kuray and Chuja Basins do not seem to have lasted longer than one week. Considering the peak discharge and drained volume of water, a schematic hydrograph of the flood can be drawn as illustrated in Figure 84. Based on these two limitations only, the duration of the flood is ~2.5 d. This simplistic approach does not consider any ponding effect in tributary valleys. Therefore, an increased base flow must be assumed that extends the flood’s duration. Recurrence intervals of outburst floods depend on the water balance of the catchment area and the rebuild of glaciers after a

Figure 84. Hypothetical hydrograph of the outburst flood based on peak discharge and drained volume.

Pleistocene ice-dammed lake outburst floods in the Altai Mountains, Siberia jökulhlaup. Both parameters are difficult to estimate for Pleistocene conditions at the current state of knowledge. A rough estimation based on several simplifications and assumptions can support at least an impression of magnitudes. The mountain crests around Chuja and Kuray Basins receive an annual amount of precipitation under current climate conditions of ~800 mm, which is estimated to be reduced by ~300 mm during the Pleistocene (cf. Chapter 3). The mean annual amount of precipitation for the last glacial of ~500 mm is comparable to current values from Aktru Glaciological Station, located at an altitude of nearly 2000 m in Northern Chuja Range (Burakov, 1987). The catchment area upstream of the location of the ice dam at the inlet of Chuja Gorge can be estimated from topographic maps as ~9300 km2. By the unrealistic assumption of no evaporation loss and stationary glacier dynamics, an annual amount of precipitation of 4.6 km3 is derived. Assuming further that no leakage of water through the ice dam occurred, a complete refill of the lake to the maximum volume of 607 km3 would take ~130 yr. Considering losses by evaporation or leakage of the dam would significantly increase the duration to refill the lake. The recurrence interval of jökulhlaups draining the entire lake is therefore on the order of centuries, while smaller outburst events are assumed to have occurred meanwhile (Carling et al., 2002; Rudoy, 1998, 2002). At the current state of knowledge, it is not sure whether all flood features belong to the same flood or are generated by different events. Beyond evidence of at least three large-scale outburst floods by the intersection of suspension gravels and lake sediments in Injushka valley, different approaches are considered to estimate the number of floods along Chuja and Katun valleys (Chapter 4 on evidence of the floods). Due to missing dated deposits and the temporal resolution, correlation between lake dynamics and the occurrence of jökulhlaups is not possible. Based on current age determinations, the jökulhlaups occurred along Chuja and Katun valleys between 40 ka and 13 ka. This rough estimation is based on partly contradictory results by the application of luminescence, exposure, and AMS 14C dating and should be taken as preliminary due to methodological problems.

103

ACKNOWLEDGMENTS Several people and institutions supported the investigations by either scientific cooperation in the field or its logistic and financial support, and by valuable comments and contributions in discussions and last but not least on the preparation of the submitted version of the study. Financial support was kindly provided by Deutsche Forschungsgemeinschaft DFG, which allowed the purchase of detailed topographic maps and covered the costs of several datings and traveling to Siberia. Additionally, the Department of Geography of Ruhr-University Bochum financially supported a visit at Tomsk State University, which allowed access to Russian publications and scientific exchange with numerous Russian scientists not involved directly in the studies in the field. For cooperation in the field and valuable comments on different aspects of the study, the author thanks Heike Agatz, Greg Balco, Pavel Borodavko, Vladimir Butvilovsky, Paul Carling, Trayle Kulshan, Julia Lanz, Herbert Liedtke, Peter Martini, Ula Moody, and Sergei Parnachov. Logistic maintenance during the field trips was provided by several students and drivers of the Department of Geography and Geology of Tomsk State University. Several samples were dated by different methods and intensively discussed by Greg Balco, Barbara Mauz, and the staff of Beta Analytics International. Inc. Pavel Borodavko, Vladimir Butvilovsky, and Julia Jinguel kindly supported the access to Russian publications and helped on translations. Karla Bareiss Valle, Johannes Flacke, Stefan Harnischmacher, Kirsten Hennrich, Susanne Karnbeck, and Harald Zepp found time for discussion of several aspects related to the study and provided technical support on the preparation of the study. Victor Baker, Paul Carling, Jürgen Hagedorn, Kirsten Hennrich, Jim O’Connor, and Harald Zepp reviewed previous versions of the manuscript and improved the clarity of the text. For hospitality and support in many aspects, special thanks to Anna and Alex Genina, their relatives, and Sergei Parnachov.

104

Appendix TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES Point no.

Valley km 0.65

2

0

Name of location Bar at Yankuba (5IHKy6a) Basin

Latitude Longitude

Altitude (m)

N 50 36 09.9

819

• rising towards mountain

889

• surveyed by inclinometer 889

E 86 29 18.9

Suspension gravel at opposite side of Big llgumen River

Character of bar surface, location, elevation of levels (in m), and comments

• section of gravels at the road at 735 m • run-up sediments

(liJJhryMeHh)

3

1.6

N 50 35 17.8

845

• run-up sediments

E 86 30 09.3

4

2.9

Karasu Creek Basin

N 50 34 31.2

Kapacy

E 86 00 31.7

Te Mojn (Engl. camel neck)

N 50 33 46.5

several

• 815 horizontal • 885 run-up sediments • section at 774 for location of deepest gravels

5

5.6

several

E 86 32 45.5

Te-MoHH

• 851 highest point on lee side, surface inclines inside valley • 920 horizontal at luff slope • 975 run-up sediments, luff

6

7

9.35

12.35

Kezek-Dzhala

several

Ke3eK-)J)KaJJa

N 50 32 56.6 E 86 33 54.3

Big Jaloman valley

N 50 31 26.5

several

• 806 horizontal

E 86 32 55.8

8

9

15.35

Around Little Jaloman village, west of confluence of Katun and L. Jaloman Rivers

14.8

N 50 29 26.1

• 893 run-up sediments

• 814 horizontal, rising in direction of flow • 931 run-up sediments

818

• horizontal, inclined towards Little Jaloman valley

832

• horizontal

850

• horizontal, slightly rising towards mountain

E 86 34 30.9

N 50 29 33.2 E 86 33 53.8

10

14.7

N 50 29 27.4

•

E 86 33 24.9

11

14.6

N 50 29 44.5

888

• ramp, exposed towards flood

• run-up sediments

E 86 33 20.5

12 13

14

14.6

N 50 29 56.1

965

20.65

E 86 33 20.6 N 50 28 16.3

several

23.45

Between lnja and L. Jaloman villages above boulder field

Bar above lnja village, Urochishhe Ojuk Ypo'IHI..l.le 0IOK

E 86 37 06.4

• 833 rising towards mountain (cf. no. 62) • 880 top of bar • 1017 run-up sediments

N 50 26 49.0 E 86 37 57.3

several

• 880 inclined towards mountain • 833 lowest part between lateral ridge and mountain • 852 higher one of two levels • 775 lower level

15

23.45

• 1030 run-up sediments on opposite side of Katun River (continued)

Appendix

105

TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES (continued) Point no. 16 16A 17

18

19

20

Valley km 23.1

Name of location lnjushka village, lake sediments

23.1

lnja River valley at lnja

30.8 (32.8 Katun)

Katun valley upstream of confluence with Chuja River

46.65 Katun

(Valley km are given for Katun valley upstream of confluence with Chuja River)

44 Katun

41.05 Katun

Latitude Longitude

Altitude (m)

N 50 26 57.6 E 86 39 08.0

830

• highest level of lake sediments (details are not listed here, cf. chapter 4)

758

• deepest point with visible suspension gravel

N 50 22 26.6

several

E 86 40 05.1

22

22A 23

30.81 (34.2 Katun) 27.4

N 50 15 18.0 E 86 43 07.2

943

• max. altitude with suspension gravel

N 5016 35.1 E864151.9

898

• suspicious hill of suspension gravel with a height of 7 m on the horizontal surface

N 50 18 13.3

several

N 50 21 48.8

Bar, upper Bulan-Koby

N 50 24 14.4

(EynaH-Ko6bi)

E 86 3719.5

?

26.8

Bar, lower Bulan-Koby (EynaH-K06bi)

24

28.8

Bar at Born BachiktuKaja (EoM Ea'IMKTy-Kal!) downstream Chuja junction

• 822 bedrock outcrop in bar surface • 915 highest suspension gravel

several

E 86 40 56.1

27.41

• 885 horizontal (2nd level) • 900 highest part of horizontal

E 86 42 02.6

21

Character of bar surface, location, elevation of levels (in m), and comments

• 731 water level • 738 deepest visible suspension gravel

925

• horizontal

962

• opposite side of river from no. 22

N 50 24 52.0 E 86 36 42.5

910

• •

N 50 24 42.3

971

• horizontal, no run-up sediments

936

• deeper than no. 24 because of overtopped ridge

horizontal, without run-up sediments polished bedrock surface

E 86 39 28.2

24A

29.1

Bar at Born BachiktuKaja, downstream of Chuja junction

25

29.8

Suspension gravel near water level Katun River

N 50 23 58.7 E 86 39 43.0

730

• gravels inclined (24-28°) against slope of valley, covered by colluvium

26

30.45

Horizontally bedded silts

N 50 23 59.3 E 86 40 21.3

787

• horizontal varved sediments (higher one of two sections), small pond, dated

27

64

Bar at Lake Sargaljuk

N 50 19 30.5 E 87 03 28.4

several

Capr3.JlblllKYK

• 1150 top of the bar, inclined towards valley • max. lake level 1105 • dry spillway 111 0

28

58.45

Bar, Sirnakh Cb!pHax

N 50 21 55.4 E 87 00 28.6

several

• 1185 rising towards valley • 1078 small extended lacustrine sediments

(cf. no. 49)

(continued)

106

Appendix TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES (continued) Point no. 29

Valley km 32.7

Name of location Bar Ak-Uzuk (Engl. "White Pass")

Longitude

Latitude

Altitude (m)

Character of bar surface, location, elevation of levels (in m), and comments

N 50 24 50.0

several

• 965 rising towards mountain, upstream of overtopped ridge

E864119.7

AK-Y3yK 30

31

32.65

35.7

• 1040 run-up sediments

Big bar "Camel neck" (Te-MoHH), left side of Chuja R. Bar

several

N 50 24 51.9

several

38.1

33

39

34

41.4

Bar, left (!) side of Chuja River

1000

Bar, lower Yalbak-Tash

N 50 24 53.4

5!n6aK-Taw

E 86 47 07.5

Bar, upper Yalbak-Tash

N 50 24 32.8

5!n6aK-Tarn

E 86 49 06.1

• 989 horizontal, gently rising towards mountain

•

E 86 44 11.8 32

• 915 horizontal • 965 small bar a little bit upstream Chuja R.

several

several

1090 run-up sediments

• bar surface eroded by standing wave downstream of bedrock ridge

• • •

990 ramp 1123 run-up sediments (opposite side of no. 32)

• 1015 horizontal • 1139 strongly developed run-up sediments, separated from bar surface by small ridge • several levels: 1011, weak 993 inclined towards mountain 940 gently rising downstream Chuja River (downstream of ridge)

34A

41.9

Bar, Apshijak-Tu

1054

• weakly developed

1012

• horizontal, no run-up sediments

1115

• horizontal, gently rising towards mountain

1069

• ramp, no run-up sediments

989

• horizontal, gently rising downstream Chuja R.

953

• level consists of weakly developed gravel dunes (?), surface gently rising downstream Chuja R., inclined towards mountain

933

• lowest level, gently rising towards mountain, lateral ridge of gravels (2-3 m) parallel at the edge towards highest fluvial terrace

1210

• run-up sediments

AnrnH~K-Ty

35

43.4

Bar, Agar-Kak

N 50 24 16.6 E 86 50 48.4

Arap-KaK 36

37

38

50.75

48.1

54.3

Bar, Cheredash

N 50 24 58.5

qepe11aw

E 86 56 36.2

Bar, Karanalu-Kobi

N 50 25 20.3

Kapa11any-Ko611

E 86 54 25.3

Bar, immediately upstream of lodro village

N 50 23 46.5 E 86 59 09.9

Ho11po 39

54.75

N 50 23 30.7 E. 86 59 20.1

40

55.15

N 50 23 19.5 E 86 59 31.6

41

56.8

Bar

N 50 23 56.3 E 87 0019.5

42

59.15

Bar, lttu-Kaya, at Belyj Bom Hrry-Kalla (Engl.: the rock with a hole)

N 50 22 38.5 E 87 02 39.1

several

• • • •

1175 horizontal, with kettle hole 1116 next level 1055 weakly developed 1034 rising towards tributary valley

(continued)

Appendix

107

TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES (continued) Point no. 43

44 45

Valley km 58.15

56.4 61.8

Name of location

Longitude

Latitude

Altitude (m)

Character of bar surface, location, elevation of levels (in m), and comments

Bar, Aslakhtu-Tuk (Engl. mushroom) AcnaxTy-TyK

N 50 22 31.4

1055

• rising towards mountain

Water level at calibration point 880

N 50 23 09.5

886

• water level, calibration point is at different locations in maps 50k I 200k

Bars, many different levels, described as seen from opposite side of Chuja River

N 50 21 12.7

several

• (A) 1141 highest part top left side, small extension, ramp

E 87 02 03.8

E 87 00 04.0 E 87 03 43.2

• (C) 1122 ramp below A and B, extend along the whole bar length

(upstream of Belyj Born village) 46

N 50 21 06.2

62

several

E 87 03 47.9

• (B) 1149 horizontal, gently rising towards mountain, at other end of C • (G) 994 horizontal below C, extend along the whole bar length

47

62.5

N 50 20 48.7

several

E 87 03 44.4

• staircase of four levels upstream of those mentioned before, same bar • (D)1141 ramp • (E) 1078 ramp • 104 7 very small extension • (F) 1011 horizontal

48

49

62.7

57.95

Bar, Kogor

N 50 20 44.8

Korop

E 87 03 55.9

Bar Sirnakh CblpHax

N 50 22 12.5

1172

• horizontal, gently rising towards tributary valley

several

• 1188 horizontal, gently rising towards tributary valley

E 87 0019.0

• 11 08 horizontal

(cf. no. 28)

• 1072 horizontal, lateral ridge of gravels (diameter up to 10 em) with height of 7 m at the edge towards Chuja valley • 1035 uncertain level 50

53.4

Bar lodrushka (tributary valley at lodro village)

N 50 24 39.5

several

E 86 59 08.3

• 1040 horizontal, lee location against flood • 1128 rising towards mountains, luff location against flood

Y!"pywKa

• 1228 run-up sediments 52

52.45

Bar, left side of river

N 50 24 01.0

53

51.25

Bar, forested, left side of river

N 50 23 44.8

Bar Aktarligan AKTapn&IraH

N 50 20 34.2

937

• horizontal, lateral ridge at downstream end of bar

1097

• rising toward mountain

E 86 57 41.6

54

65.95

E 86 56 31.4 several

E 87 05 30.1

• 1174 rising towards mountain • 1232 run-up sediments • 1128 horizontal • 1087 weak developed level

55

67.6

Bar, Tutugoj

N 50 20 48.4

TyTyroil

E 87 06 56.7

several

• 1252 rising towards mountain • 1171 horizontal • 1147 level inclined parallel(!) with Chuja River, maybe connected with level 1114 at opposite side of tributary creek • 1050 horizontal

(continued)

108

Appendix TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES (continued) Point no. 56

Valley km 70.2

Name of location Bar

Longitude

Latitude

Altitude (m)

Character of bar surface, location, elevation of levels (in m), and comments

N 50 20 25.3

several

• • • • •

E 87 09 48.7

57

73.6

Bar

N 50 19 57.6

several

E 87 11 37.9

58

74.4

Bar, Dejljugem

1223 horizontal 1262 run-up sediments 1091 rising parallel (!) to Chuja River 101 0 horizontal 1196 rising gently towards mountain, no run-up sediments

•

1112 rising towards mountain

•

1094 uncertain level

•

1052 horizontal

1280

• opposite side of river from no. 57, ramp surface

1248

• opposite side of river from no. 57, rising towards mountain

):lelimoreM 59

71.85

Bar, Salgadu Tutugoj Canra,11y TyTyroii

61

62

79

16.4

Bar upstream of confluence with Ajgulak River AlirynaK

E 87 15 01.9

N 50 21 40.8

Section of suspension gravel at Little Jaloman River

E 86 35 24.0

N 50 2914.1

several

several

•

1119 top of berm on the edge towards the slope

•

1113 level below berm, horizontal

•

1081 horizontal

• bar at Little Jaloman is inclined towards the valley • 865 highest level, horizontal in Katun valley, morphologically separated from sediments at section • 815 upper edge of section • 805 below highest gravel layer • 800 above next gravel layer • 785 gravel layer • 765 sand layer 3 m above next gravel layer (dated sample) • 750 silt layer • 730 valley bottom

63

13.1

Bar, Kok-Kumak (blue sands) KoK-KyMaK

N 50 30 49.3 E 86 34 20.3

760

• level between slope of bar and river terraces, horizontal, maybe connectable with 765 braided river (cf. no. 79)

Right side of Katun River at confluence with Big Jaloman River

(continued)

Appendix

109

TABLE A1. LOCATION AND CHARACTERISTICS OF FLOOD FEATURES (continued) Point no. 64

Valley km 13

Name of location Bar, Kok-Kumak (blue sands)

Longitude

Latitude

Altitude (m)

Character of bar surface, location, elevation of levels (in m), and comments

N 50 30 50.4

several

• 915 top of bar

E 86 34 42.4

• 870 inclined parallel to Katun River

KoK-KyMaK

• 860 horizontal, gently rising towards mountain

64A

11.7

N 50 31 33.4 E 86 34 52.2

855

• downstream end of level 860 (cf. above): slope 3.8%o

65

12.75

N 50 30 54.1 E 86 34 47.4

865

• lateral ridge between bar and mountain, bedrock surface (location of exposure dating sample); outlet of depression is at upstream (!) side at 855

66

9.65

Bar, Anijakh Creek

N 50 32 30.7

several

AHHliX

E 86 35 53.7

• 810 horizontal, gently rising towards mountain, lufflocation towards flood • 875 run-up sediments

Run-up sediments, Saldzhar Creek Ca.lb!llKap

N 50 33 45.1 E 86 35 35.6

1010

• highest part of run-up sediments, ridge downstream was overtopped, ramp area (luff location)

18.65

Gravel dunes between lnja and Little Jaloman villages

N 50 29 21.4 E 86 37 35.2

770

• level of gravel dunes

69

19.85

Boulder field downstream of lnja village

N 50 28 40.3 E 86 37 48.6

775

• level of boulders (same level as dune field, cf no. 68), about 10m above lnja Terrace level

78

16.05

Section of suspension gravel in L. Jaloman Valley

N 50 29 35.5 E 86 3515.9

722

• deepest part of visible suspension gravels, sand layer inclined towards valley below single silt layer and suspension gravels, location of dated sample

79

16.15

Gravel pit at Little Jaloman village

N 50 29 51.1 E 86 35 28.6

753

• gravel pit in suspension gravel with a braided river sediment structure, 765 is at top of pit, 753 base of pit

67

8.3

68

Note: Listed in this table are mainly locations and elevations of giant bars, related terrace levels, and run-up sediments. Locations are numbered to simplify identification of locations mentioned in the text. Latitude and longitude are determined by GPS and are given in "dd mm ss.s" based on WGS 1984. The accuracy of altitudes is about± 5 m for points determined by altimeter. Altitudes include calculations for improved data quality. Slopes that have been exposed to the current of the flood are characterized as "luff," the opposite side to "lee." If names of locations are known, they are additionally given in Cyrillic letters to avoid confusion caused by different transliteration, which occurred frequently in previous publications.

110

Appendix TABLE A2. BAR SURFACES AND LEVELS FROM TOPOGRAPHIC MAPS

Point no.

Valley km

Location

Top of bar between points no. 5 and no. 6 Top of bar near point no. 6

Altitude (m a.s.l.) (contour level in topographic map) 860 820

80 81

7 10

82

17.3 22.15

Highest part of bar between Little Jaloman and lnja villages Highest part of bar between lnja and lnjushka villages, north of lnja River

29.8 32.3

Bar surface at Chuja-Katun River confluence, north of point no. 26 Highest part of bar at Chuja-Katun River confluence, south of point no. 30

35.7

Bar surface in lower Chuja valley, south of river, opposite side of river from point no.31 Bar surface in lower Chuja valley, south of river, Ujuk Creek valley (Y10K)

1100

Bar surface in lower Chuja valley, downstream of point no. 37 Bar surface in lower Chuja valley, downstream of point no. 37

1120 1120

Bar surface in lower Chuja valley, south of river, Katandoj Creek valley (KaTaH)1oii)

1100

83 84 85 86 87

45

88

47.3 47.75

89 90

49

890 880 1020 1010 980

91 92

49.1 57

Bar surface in lower Chuja valley, upstream of point no. 37 Bar surface in Chuja valley, upstream of point no. 41

1140 1160

93 94

59.6 70

Bar surface (rising towards mountain) in Chuja valley, south of river at Belyj Bom Bar surface in Chuja valley, between points no. 55 and no. 56 Bar level in Chuja valley, Modorlu Creek valley (Mo11opny)

1180 1240

Bar surface in Katun valley upstream of confluence, east side of river, Terebety Creek valley (Tepe6enr)

900

Bar surface upstream of lnegen village, east side of river

835

95

76.8

96

35.3 Katun

97

41 Katun

1220

Note: Altitudes are conservative estimations. Only locations of known topography are considered. Mainly because of limited access to the locations, the surfaces have not been surveyed in the field. Interpolations between the 20 m intervals of contour lines are carried out; accuracy of data in the table is not better than ± 10 m.

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Contents Abstract Chapter t. Introduction Problems Aims Methods Structure of the Study Chapter 2. Ice-Dammed Lakes and j okulhlaups Class11ication of Ice-Dammed Lakes Mode of Drainage and Outburst Mechanisms Hydrographs of jokulhlaups Occurrence and Distribution Chapter 3. Altai Mountains Location and Geology Current Climate Quaternary of Al£ai Mountains Chapter 4. Evi dence of jokulhlaups in the Al tai Mountains Previous Studies and Reviews Flood-Related Features Lake Sed•mems and Shorelines Ice Dam and Failure Mechamsm Giam Bars and lndicauon of Flow Conditions Secondary Lakes Gravel Dunes Erosiona l Forms Bou lder Deposits Criticism on Occurrence of jokulhlaups in the Altai Mountains Open Questions Chapter 5. Reconstruction of the Floods Un1form Flow Calculation Introduction llydraulic Background Data from the Altai Mountains Palcohydraulic Calculations Discussion Flow Calculation by HEC-RAS lmroduction Hydraulics Paleostage Indicators Paleohydraulic Calculauon Previous water level calculations of Pleistocene outburst noods Previous water prolile calculations for the nood in the Altai Mountains Calculations for mixed now Discussion

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Velocity Head Calculations usmg Run-Up Sedimems Introduction Hydraulics Run-Up Sed1mems m Chuja and Katun Valley Paleohydraulic Calculanon Discussion Correlation of Lake Volume and Peak Discharge Introduction Hydraulics Volume of Ice-Dammed Lake Paleohydraulic Calculation DISCUSSion Boulder Transpon Introduction Hydraulic Background Boulders nea r lnja Village Paleohydraulic Calculations Discussion Gravel dunes Introduction Hydraulic Background Dune Data for Paleohydrauhc Reconstruction Paleohydraulic Calculauons Discussion Obstacle marks lmroducuon Hydraulic Background Submerged obstacles Bridge piers Examples of Obstacle Marks in Chuja and Katun Valleys Paleohydraulic Calculations Discussion Chapter 6. Review of Dynamics of the Altai j okulhlaups Acknowledgments Appendices Table A 1. Location and Characteristics of Flood Features Table A2. Bar Surfaces and Levels from Topographic Maps References Cited

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