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Citation: Wani SP, Sahrawat KL and Kaushal K Garg (eds.). 2011. Use of High Science Tools in Integrated Watershed Management. Proceedings of the National Symposium, 1–2 Feb 2010, NASC Complex, New Delhi, India. Patancheru 502 324, Andhra Pradesh, India: International Crops Research Institute for the Semi-Arid Tropics. ISBN 978-92-9066-540-3. CPE 169. 328 pp.
Acknowledgement We sincerely thank Department of Land Resources (DoLR), Ministry of Rural Development, Government of India, for sponsoring the symposium. We are grateful to National Bank for Agriculture and Rural Development (NABARD), Sir Dorabji Tata Trust (SDTT), Sir Ratan Tata Trust (SRTT) for co-sponsoring the event. We thank the help of Mr Prabhat Kumar, Director, Business and &RXQWU\5HODWLRQV,&5,6$7/LDLVRQ2I¿FHIRUFRRUGLQDWLQJWKHZRUNVKRS We thank Ms N Shalini for language editing; Mr KNV Satyanarayana, Mr Arun Pal and Ms Jyothi for administrative support; Mr Y Prabhakar Rao and 0V16UL/DNVKPLIRUORJLVWLFDOVXSSRUW DQG&RPPXQLFDWLRQ2I¿FH,&5,6$7 for production of this report.
Organizing Committee Co-Chairs SP Wani Prabhat Kumar Members
P Pathak Kaushal Garg Arun Pal KNV Satyanarayana
Secretarial Support Y Prabhakara Rao Jyoti Sharma N Sri Lakshmi © International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), 2011. All rights reserved. ICRISAT holds the copyright to its publications, but these can be shared and duplicated for noncommercial purposes. Permission to make digital or hard copies of part(s) or all of any publication for non-commercial use is hereby granted as long as ICRISAT is properly cited. For any clarification, please contact the Director of Communication at
[email protected]. ICRISAT’s name and logo are registered trademarks and may not be used without permission. You may not alter or remove any trademark, copyright or other notice.
Use of High Science Tools in Integrated Watershed Management Proceedings of the National Symposium 1–2 February 2010 NASC Complex, New Delhi, India
Editors SP Wani, KL Sahrawat and Kaushal K Garg
Organized by
in collaboration with
Department of Land Resources Ministry of Rural Development, Government of India
Sponsored by Sir Dorabji Tata Trust (SDTT) Sir Ratan Tata Trust (SRTT) Mumbai, Maharashtra, India
and
National Bank for Agriculture and Rural Development Mumbai, Maharashtra, India
2011
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Harnessing New Science Tools through IWMP to Unlock Potential of Rain-fed Agriculture Suhas P Wani, AVR Kesava Rao and Kaushal K Garg ,QWHUQDWLRQDO&URSV5HVHDUFK,QVWLWXWHIRUWKH6HPL$ULG7URSLFV ,&5,6$7 3DWDQFKHUX$QGKUD3UDGHVK,QGLD
Abstract Semi-Arid Tropics (SAT) are characterized by highly variable rainfall, poor soils, low yields and poor developmental infrastructure. Watershed management is now an accepted strategy for development of rainfed agriculture in these areas. New science tools like remote sensing, geographical information systems (GIS), water balance, simulation modeling, information and communication technology (ICT) are currently being used very widely in irrigated and well-endowed areas. Importance of these tools in the SAT areas is now well understood and recognized. Application of new science tools in rain-fed agriculture opens up new vistas for development through integrated watershed management programs (IWMP). ICRISAT in partnership with national agricultural research systems and advanced research institutes in Asia has applied new science tools for enhancing the productivity of rain-fed systems in the SAT through science-led development. The remarkable developments in space technology currently offers satellites, which provide better spatial and spectral resolutions, more frequent revisits, stereo viewing and on board recording capabilities. High spatial and temporal resolution satellite data could be effectively used for watershed management and monitoring activities at land ownership level. Techniques are also successfully used for preparing detailed thematic maps, watershed development plans and continuous monitoring of the natural resources in rain-fed areas. Synergy of GIS and Web Technology allows access to dynamic geospatial watershed information without burdening the users with complicated and expensive software. Use of smart sensor network along with GIS, RS, simulation modeling and ICT opens up new opportunities for developing intelligent watershed management information systems. These tools can help in improving the rural livelihoods and contribute substantially to meet the millennium development goals of halving the number of hungry people by 2015 and achieving food security through enhanced use HI¿FLHQF\RIVFDUFHQDWXUDOUHVRXUFHVVXFKDVODQGDQGZDWHULQWKH tropical countries. 1
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Figure 1. Simulated potential, experimental and province mean pod yields and yield gap of rain-fed groundnut in (a) spring and (b) autumn-winter seasons at selected sites in northern Vietnam.
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Figure 2. Distribution of different soil orders in the production systems in India.
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Figure 3. A close view of WiFS images of part of Vidisha district, Madhya Pradesh, during mid-rainy, late-rainy and post-rainy seasons
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Figure 4. Spatial distribution of various land use and land cover categories in Madhya Pradesh.
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Figure 5. Spatial distribution of rainy season fallows in districts of Madhya Pradesh.
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Figure 6. Spatial distribution of rice-fallows in Indo Gangetic Plains of South Asia.
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Figure 7. Availability of phosphorus in selected districts of Karnataka.
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Figure 8. Satellite Data and DEM of watershed in part of Nalgonda district, Andhra Pradesh. 24
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Figure 11. Drought monitoring at benchmark watersheds in Andhra Pradesh during 2004.
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Figure 12. Guna watershed, Madhya Pradesh. 36
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Figure 13. Landuse and cropping pattern of Adarsha watershed, Kothapally, Andhra Pradesh.
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Figure 14. Thematic maps depicting soils and land use plan in Adarsha watershed, Kothapally, Andhra Pradesh.
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Figure 15. Information and communication technology services enabled at Addakal, Mahabubnagar district, Andhra Pradesh, India.
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Abstract Watershed-based development has been the prime strategy for rain-fed regions of India since 1980s to conserve natural resources, enhance agricultural production and improve rural livelihoods. Although soil and water conservation was initially the primary objective of watershed program that saw large public investments since inception, its focus later shifted to people’s participation, equity and livelihood security, particularly from the mid nineties. One of the major goals of the watershed program is also regeneration of degraded lands. Many of these interventions need modern tools like GIS and remote sensing so that planning, prioritization and monitoring becomes more science based and the methodology and approaches can become universally applicable. Application of GIS, remote sensing and use of GPS for monitoring and evaluating watershed projects is a recent development. Two exercises in this direction were initiated in CRIDA wherein relevant sustainability LQGLFDWRUVZHUHGHYHORSHGWKDWFRXOGEHTXDQWL¿HGDQGPRQLWRUHGXVLQJ these tools and the outcome of these studies have been presented in this paper. The bio-physical parameters were temporally evaluated from two standpoints – the pre- and the post-project implementation SKDVHV 7KH LQGLFDWRUV ZHUH JHRUHIHUHQFHG LQ WKH ¿HOG XVLQJ *36 and changes in NDVI and land cover were analyzed to assess if agricultural development within treated watersheds were sustainable. Utility of Geomatics for developing criteria for watershed selection, as indicated in various guidelines including the recent Common Guidelines of 2008, cannot be overemphasized. Major bio-physical parameters that include potential runoff and soil erosion besides SHUFHQWDJH RI LUULJDWHG DUHD HWF FRXOG EH TXDQWL¿HG DQG XVHG DV indicators for monitoring and evaluation in the post-project phase. Lack of information on these parameters at watershed - level, as evidenced earlier have been made-up to a large extent through application of
49
better resolution data and generation of surrogate indicators. With the availability of DEM datasets in public domain and with the availability of GIS software, it is now possible to estimate certain parameters that have a direct bearing on potential runoff and soil loss, thus providing a scope for characterization of watersheds as mentioned earlier. The paper also presents an example of use of DEM dataset in GIS environment for prioritization of watersheds based on runoff -potential and soil loss parameter at the district- level.
Introduction Application of Geomatics in CRIDA Watershed Program 8VH RI WRROV RI *HRPDWLFV OLNH *,6 56 *36 VSHFWURUDGLRPHWHU LQ WDQGHP ZLWK WKH FRQYHQWLRQDO WRROV OLNH FLYLO VXUYH\ ZLWK WRWDO VWDWLRQ VRLODQDO\VLVVRFLRHFRQRPLFVXUYH\DQG35$KDYHEHHQLQYRJXHLQ &5,'$ VLQFH ZKHQ WKH ,&$5 ± ,QVWLWXWH 9LOODJH /LQNDJH SURJUDP ,9/3 ZDVODXQFKHGDW1DOODYHOOL .DW\DOHWDO ,Q WKHVH WRROV ZHUH XVHG WR GHYHORS VXLWDEOH /DQG 8VH 3ODQ IRU ZDWHUVKHGV DFURVV VL[WHHQ FHQWHUV LQ ¿IWHHQ DJURHFRORJLFDO VXE UHJLRQV $(65 DFURVVWKHFRXQWU\XQGHUWKH1$7300/83SURJUDP IRU UDLQIHG HFRV\VWHPV 7KHVH WRROV ZHUH XVHG WR GHYHORS PRQLWRU .DXVKDO\D .DXVKDO\D HW DO 9LWWDO DQG HYDOXDWH ZDWHUVKHGSURMHFWVIXQGHGE\1$%$5'XQGHU,:0,VWXG\LQ.ULVKQD %DVLQDQGXQGHUWKH1DWLRQDO)HOORZ6FKHPHE\.DXVKDO\DHWDO 6FRSHRIDSSOLFDWLRQRI*,6DQG56IRUZDWHUVKHGGHYHORSPHQWLQFOXGH Ɣ ODQGXVH±UHVRXUFHLQYHQWRU\DQGSODQQLQJIRURSWLPXPXVH Ɣ GHOLQHDWLRQDQGSULRULWL]DWLRQRIZDWHUVKHGV±DXWRPDWHGZDWHUVKHG GHOLQHDWLRQ GUDLQDJH EDVLQ PRUSKRORJLFDO DQDO\VLV VWUHDP RUGHU GUDLQDJHGHQVLW\EDVLQVORSHDQGVKDSHFLUFXODULW\FXPXODWLYHDUHD GLVWULEXWLRQK\SVRPHWULFFXUYHV Ɣ LGHQWL¿FDWLRQRIYXOQHUDEOHDUHDV Ɣ UDLQIDOOUXQRIIPRGHOLQJ Ɣ LPSOHPHQWDWLRQ RI GHYHORSPHQW SURJUDP LQ UDLQIHG DUHDV IRU UHVRXUFHFRQVHUYDWLRQ±ODQGXVHSODQQLQJ Ɣ VRLOIHUWLOLW\DQGLWVTXDOLW\DVVHVVPHQW 50
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Resource Inventory and Planning for Technology Upscaling ,Q ,&$5ODXQFKHGWKH,QVWLWXWH9LOODJH/LQNDJH3URJUDP ,9/3 ZLWK D YLHZ WR GHPRQVWUDWH WHFKQRORJLHV QHFHVVDU\ IRU DOO FURSSLQJ V\VWHPV ZLWKLQ WKH YLOODJH $ SUHUHTXLVLWH IRU LPSOHPHQWDWLRQ RI WKH SURJUDP ZDV WKH LGHQWL¿FDWLRQ RI FURSSLQJ V\VWHPV $ FRQYHQWLRQDO DSSURDFK ZRXOG JLYH LQIRUPDWLRQ RQ WKH W\SH RI FURSSLQJ V\VWHPV DYDLODEOHLQWKHYLOODJHZLWKRXWDQ\SHUVSHFWLYHRQUHVRXUFHLQYHQWRU\ 7KURXJK *,6 H[LVWLQJ FURSSLQJ V\VWHPV ZHUH VXSHULPSRVHG RQ SUHYDLOLQJ VRLO DQG ZDWHU UHVRXUFHV DQG VXLWDEOH WHFKQRORJLHV ZKLFK FRXOGPDNHLPSDFWZHUHLGHQWL¿HGIRUGHPRQVWUDWLRQSXUSRVH7KHZRUN ZDVFDUULHGRXWDW1DOODYHOOLLQ
Watershed Delineation and Prioritization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
Figure 1. Characterization of NRM status using Geomatics.
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Based on drainage density
Based on hypsometric integral (erosion potential is known qualitatively)
Figure 2. Geomorphological characterization of watersheds for prioritization – a case study of Mahabubnagar district. 53
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Table 2. Estimation of priority area for treatment based on runoff potential – higher drainage density – more water harvesting. 7KUHVKROGDUHD KD
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Figure 3. Satellite images with varying ground resolution – Sakaliseripalli watershed. 57
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Figure 4. Thematic maps of soil quality, agricultural productivity and soil loss potential of Sakaliseripalli watershed.
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59
Table 3. List of sustainability indicators constructed for the study. 3OODUVRI6XVWDLQDELOLW\
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Figure 5. Assessing temporal variations in LULC & degradation.
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References Katyal JC, Kaushalya Ramachandran, Narayana Reddy M DQG Rama Rao CA. ,QGLDQ$JULFXOWXUH 3UR¿OH RI ODQG UHVRXUFHV FURS SHUIRUPDQFHV DQGSURVSHFWVLQ 5HJLRQDO/DQG&RYHU&KDQJHV6XVWDLQDEOH$JULFXOWXUHDQG WKHLU ,QWHUDFWLRQV ZLWK *OREDO &KDQJH ZLWK IRFXV RQ 6RXWK$VLDQ FRXQWULHV 3URFRIDQ,QWHUQDWLRQDO:RUNVKRSKHOGLQ&KHQQDL,QGLD± 'HF RUJDQL]HGE\&267('±,&68±81(6&2±,%1SS± Katyal JC, Kaushalya Ramachandran, Narayana Reddy M, Mahipal DQG Ram Mohan I. 0LFURZDWHUVKHG EDVHG GHYHORSPHQW SURJUDPPH IRU 1DOODYHOOLYLOODJHLQ55'LVWULFW$3LQVHPLDULGSDUWRI,QGLDLQ*HRJUDSKLFDO ,QIRUPDWLRQ6\VWHPVDQG5HPRWH6HQVLQJ$SSOLFDWLRQV HG ,90XUDOLNULVKQD 3URF ,QWHUQDWLRQDO &RQIHUHQFH RQ 5HPRWH VHQVLQJ DQG *,6 ,&25* +\GHUDEDG±-XQH SS± Kaushalya Ramachandran. 8VLQJ *,6 IRU :DWHUVKHG 'HYHORSPHQW WR DXJPHQW :DWHU +DUYHVWLQJ LQ 6HPLDULG 7HOHQJDQD$3 ,QGLD *,6 ,QGLD ±
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Figure 6. Estimating seasonal variations in crop vigour using NDVI as a indicator.
Kaushalya Ramachandran, Gayatri M, Bhasker V, Srinivas G, Venkatravamma K, Srinivas T DQG Sankar Rao M. (YDOXDWLQJ /LYHOLKRRG 6HFXULW\ RI )DUP +RXVHKROG LQ 7UHDWHG :DWHUVKHG LQ 6HPLDULG 5HJLRQIndian J. Dryland AgricRes. & Dev ± Kaushalya Ramachandran, Mandal UK Sharma KL, Gayatri M, Baskar Venkatravamma K DQG Kartik P. 0HWKRGRORJ\IRUHYDOXDWLQJOLYHOLKRRG VHFXULW\ RI IDUP KRXVHKROGV LQ WUHDWHG ZDWHUVKHGV ,QGLDQ -RXUQDO RI 6RLO &RQVHUYDWLRQ ±
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Use of Hi-Science Tools in IWMP Rita Teaotia and Ram Kumar *XMDUDW6WDWH:DWHUVKHG0DQDJHPHQW$JHQF\ *DQGKLQDJDU*XMDUDW,QGLD
Abstract Gujarat has been at the forefront of watershed development program in the country, both in terms of quantity and quality. By the end of the year 2008, more than 8000 micro-watershed projects involving more than Rs.25000 million have been either completed or on going in the state. However, a lot remains desired in overall project planning, implementation and post project management so as to make the program sustainable. Considering the different concerns regarding project management, the New Common Guidelines for Watershed Program has prescribed for use of high science tools like application of Remote Sensing & Geographic information System (GIS), Management Information System (MIS) and other Information & Communication Technologies. Accordingly, the Government of Gujarat has undertaken the Integrated Watershed Management Program (IWMP) incorporating the available high science tools; GIS is a major part of the whole process. The Gujarat State Watershed Management Agency (GSWMA), the nodal agency at the state level for IWMP in collaboration with Bhaskaracharya Institute of Space Applications and Geo-informatics (BISAG) has taken initiative in this regard by integrating GIS based data at both micro and macro level planning.
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Prioritization of the watersheds:7KLV WDVN ZDV ZLWK WKH UHVSHFWLYH GLVWULFW DXWKRULWLHV ZKLFK ZHUH JUDQWHG SURMHFWV E\ WKH *RYHUQPHQW RI ,QGLD PDLQO\ EDVHG RQ VRFLRHFRQRPLF SDUDPHWHUV :LWKRXW DQ\ VFLHQWL¿F FULWHULD RU VFLHQWL¿F WRROV WKH GLVWULFW DXWKRULWLHV FKRVH WKH YLOODJHVWREHWDNHQXSXQGHUWKHSURMHFWVHLWKHURQWKHEDVLVRIWKHLU FRQVFLHQFH RU VRPH SROLWLFDO FRQVLGHUDWLRQV 7KH SULRULWL]DWLRQ ZDV QHYHUVFLHQWL¿FRUREMHFWLYH Technical inconsistencies: 6RPH RI WKH WHFKQLFDO LQFRQVLVWHQFLHV LQSURMHFWLPSOHPHQWDWLRQFDPHIURPLPSURSHUVLWHVHOHFWLRQIRUZDWHU KDUYHVWLQJ VWUXFWXUHV DQG RWKHU HQJLQHHULQJ ZRUNV DV WKH WHFKQLFDO SHUVRQVGLGQRWKDYHVXI¿FLHQWNQRZOHGJHRIWKHJHRK\GURORJ\RIWKH DUHD People vs. technical experts dilemma:7KHH[HUFLVHRISODQQLQJDQG LPSOHPHQWDWLRQLQWKHSDVWJHQHUDWHGFRQÀLFWEHWZHHQWKHSHRSOHOLYLQJ LQWKHSURMHFWDUHDDQGWKHWHFKQLFDOSHUVRQQHOUHJDUGLQJVLWHVHOHFWLRQ DQGDSSURSULDWHLQWHUYHQWLRQVLQSURMHFWDUHDV Developing a scienti¿c action plan::LWKRXWDSURSHU*,6RIWKHDUHD DVFLHQWL¿FDFWLRQSODQZDVGLI¿FXOWWRDUULYHDW$WEHVWWKHFRQFHUQHG SHUVRQVZRXOGFRPHXSZLWKVRPHDFWLYLWLHVZKLFKVRPHWLPHVSURYHG WREHXQVXLWDEOHIRUWKHDUHDLQWKHORQJUXQ Preparation of detailed project report: 7KHUH ZDV QR HVWDEOLVKHG PHFKDQLVP IRU GHWDLO SURMHFW UHSRUW SUHSDUDWLRQ :LWKRXW WKH YLOODJH OHYHO*,6EDVHGPDSVWKHDFWLRQSODQZDVQHYHUPDSSHG7KLVPDGH WKHUHOHYDQFHRI'35OLPLWHG Monitoring and evaluation: 3RRU TXDOLW\ '35V OHG WR SRRU TXDOLW\ PRQLWRULQJ DQG HYDOXDWLRQ PHFKDQLVP WR VWDUW ZLWK :LWKRXW DQ DSSURSULDWH0,6WKHWDVNEHFDPHWRXJKDQGLWZDVGRQHDUELWUDULO\DQG UDQGRPO\ Impact assessment:$Q\NLQGRILPSDFWDVVHVVPHQWLQWKHSRVWSURMHFW SHULRG ZDV WRR KHDYLO\ GHSHQGHQW RQ VRFLRHFRQRPLF UHVHDUFKHV 7KHVHVWXGLHVKDYHWKHLUOLPLWDWLRQVORRNLQJDWWKHQDWXUHDQGHQRUPLW\ RIWKHWDVN
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Planning 3ODQQLQJRIDZDWHUVKHGGHYHORSPHQWSURMHFWLQYROYHVWKHXVHRI*,6LQ YDULRXVDVSHFWVRISULRULWL]DWLRQGHYHORSPHQWRIDFWLRQSODQDQGODWHUIRU PRQLWRULQJDQGHYDOXDWLRQRIWKHVHSURMHFWV7KHLQLWLDOSURFHVVLQYROYHG FUHDWLRQRIGLIIHUHQWVSDWLDOOD\HUVIURPWKHQRQVSDWLDOGDWDVHWFROOHFWHG IURPYDULRXVVRXUFHV'XHWRWKHIRFXVSURYLGHGE\WKH6WDWH*RYHUQPHQW WR WKH QHHG IRU VFLHQWL¿F SODQQLQJ DQG PDQDJHPHQW VXEVWDQWLYH GDWD ZDVDOUHDG\PDSSHGDQGDYDLODEOHZLWK%,6$* 7DEOH Table 1. Various GIS datasets used and their sources.
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Figure 1. Planning from macro level to the micro level.
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Table 2. Criteria & weightage for prioritization set by DoLR.
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Figure 2. Various spatial layers.
Figure 3. Final prioritization.
Figure 4. Map depicting the planned areas for the whole of 18 years. 79
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Conclusion 7KH 1HZ &RPPRQ *XLGHOLQHV IRU WKH ,:03 SURJUDP KDYH HQYLVDJHGDQHZDQGKROLVWLFDSSURDFKWRQDWXUDOUHVRXUFHPDQDJHPHQW 7KHIDFWRURIFRQYHUJHQFHDQGXVHRIKLJKVFLHQFHWRROVKDVUHVXOWHGLQ FRPSUHKHQVLYH SODQQLQJ LPSOHPHQWDWLRQ PRQLWRULQJ DQG HYDOXDWLRQ 7KHVLJQL¿FDQFHRIWKHQHZDSSURDFKOLHVLQH[WHQGLQJWHFKQRORJ\WR HQKDQFHUXUDOOLYHOLKRRGV7KLVKDVUHVXOWHGLQLPSDUWLQJWUDQVSDUHQF\ DQGHI¿FLHQF\LQLPSOHPHQWLQJWKHVHSURMHFWV8VHRI*,6IRUSODQQLQJ WKDW LQWHJUDWHV FRQYHUJHQFH ZLWK 15(*6 DQG RWKHU JRYHUQPHQW VFKHPHV VWUHQJWKHQV FRRUGLQDWLRQ DPRQJ GHSDUWPHQWV 7KLV KHOSV LQUHGXFLQJGXSOLFDWLRQRIZDWHUVKHGGHYHORSPHQWDFWLYLWLHV%OHQGLQJ RI WUDGLWLRQDO NQRZOHGJH ZLWK VFLHQWL¿F SURFHVV KHOSV LQ SODQQLQJ DQG GHYHORSPHQW RI WKH LQWHJUDWHG ZDWHUVKHG PDQDJHPHQW SURJUDP LQ D VXVWDLQDEOHPDQQHU
Box-2: Case Study: Impact assessment of watershed development in Idar Taluka (Code: 5F2D4b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Acknowledgement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
References Government of India. *XLGHOLQHV IRU :DWHUVKHG 0DQDJHPHQW 'HSDUWPHQWRI/DQG5HVRXUFHV0LQLVWU\RI5XUDO'HYHORSPHQW Government of India. 7HFKQLFDO JXLGHOLQHV IRU 0DSSLQJ ,QWHJUDWHG UHVRXUFH LQIRUPDWLRQ V\VWHP IRU GHVHUW DUHDV 1DWLRQDO 5HPRWH 6HQVLQJ $JHQF\+\GHUDEDG-DQXDU\ Government of India. 1HZ &RPPRQ *XLGHOLQHV IRU :DWHUVKHG 'HYHORSPHQW3URMHFWV'HSWRI/DQG5HVRXUFHV0LQLVWU\RI5XUDO'HYHORSPHQW NREGA. 15(*$ 3HUVSHFWLYH 3ODQ *XLGHOLQH 'HSDUWPHQW RI 5XUDO 'HYHORSPHQW0LQLVWU\RI5XUDO'HYHORSPHQW*RYHUQPHQWRI,QGLD Joint Convergence Guideline. 5HSRUWRIWKH7DVN)RUFHRQ&RQYHUJHQFH 'HSDUWPHQWRI5XUDO'HYHORSPHQW0LQLVWU\RI5XUDO'HYHORSPHQW*RYHUQPHQW RI,QGLD Watershed Atlas. 1990 'H¿QLWLRQRI:DWHUVKHG http://cgwb.gov.in/watershed/about-ws.html http://www.esri.com/what-is-gis/index.html Watershed Management-T V R Murthy, New age publication, 1995
Use of Modeling in Watershed Planning Alok K Sikka1, DR Sena3, VN Sharda2 and RS Kurothe3 1DWLRQDO5DLQIHG$UHD$XWKRULW\1HZ'HOKL,QGLD &HQWUDO6RLO :DWHU&RQVHUYDWLRQ5HVHDUFK 7UDLQLQJ,QVWLWXWH .DXODJDUK5RDG'HKUDGXQ8WWDUDNKDQG,QGLD &HQWUDO6RLO :DWHU&RQVHUYDWLRQ5HVHDUFK 7UDLQLQJ,QVWLWXWH 5HVHDUFK&HQWUH9DVDG±$QDQGGLVWULFW*XMDUDW,QGLD
Abstract Integrated watershed management has emerged as a powerful concept in development planning for agriculture and rural development in India. Importance of integrated planning of natural, animal and social resources for enhanced productivity and livelihood is evident from the increased outlay of watershed programs in the XIth Five Year Plan. Comprehensive Assessment of Watershed Programs in India by the ,&5,6$7OHGFRQVRUWLXPKDVFOHDUO\VKRZQWKHEHQH¿WRIVFLHQWL¿FDOO\ planned and systematically implemented watershed projects. Now all the watershed programs of different ministries/departments are being implemented following the new Common Guidelines for Watershed Development Projects effective from April 2008. The guidelines emphasize using new science and technology inputs, including Remote Sensing (RS), Geographic Information System (GIS) and modeling to bring about a paradigm shift in preparing detail project reports (DPRs) for implementation of the watershed development programs. Integrated watershed planning is done on the basis of its resource inventory, which includes the analysis of the present status or conditions (i.e., bench mark analysis) of its natural resources (soils, topography, drainage, land use, water resources, forest, vegetation, etc.), animal/ livestock resources, socio-economic and livelihood conditions and human resources and the type/extent of problem and needs of the watershed area and the community. Modeling application requires spatial data at watershed scale. Creation of a spatial database is WKHUHIRUHWKH¿UVWDQGYHU\LPSRUWDQWVWHSLQZDWHUVKHGSODQQLQJWRSXW maps and baseline data in place, followed by spatial analysis using analytical tools to help identify special features, problems, needs and FULWLFDODUHDVDQG¿QDOO\SUHSDUHDFWLRQSODQRU'35IRUGHYHORSPHQW of the watershed. The advances in remote sensing in collecting spatially variable data at higher resolution, GPS and capabilities of GIS in storing, retrieving and
90
manipulating data have shown tremendous potential in circumventing problems of the conventional and time-taking techniques in watershed planning. Integrating and collating data from multiple sources, conventional and/or remote sensing and others, with GIS, can lead to important operational applications including better opportunities for use of modeling in watershed planning. Use of modeling as a tool in conjunction with spatial data manipulation in GIS for estimating runoff, soil erosion and sedimentation, land FDSDELOLW\ FODVVL¿FDWLRQ ODQG XVH SODQQLQJ LGHQWLI\LQJ FULWLFDO DUHDV needing treatment within the watershed for optimized investments, planning, location and design of various soil and water conservation, water harvesting and other such interventions, and analysis of best management practices (BMPs) in preparing watershed plan, has been presented in the paper. Opportunities of using data from free sources in watershed planning have also been presented. Use of distributed modeling to address issue of upstream–downstream FRQÀLFWV DQG FRPSOHPHQWDULWLHV RI ZDWHUVKHG GHYHORSPHQW SURMHFWV are also discussed. Need for identifying and integrating the analytical biophysical and socio-economic models to GIS through user interface in a modular modeling frame work to develop decision support systems (DSS) and web-enabled system is emphasized to help automate the watershed planning process and simulate the effects of various watershed intervention scenarios.
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Figure 5. GIS (free open source) delineated contours derived from ASTER data draped in Google earth and a 3D DEM derived from it. (Prepared by D R Sena as an example).
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Figure 6. Google resources translated into useful baseline information for DPR preparation (CSWCRTI, 2008).
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Application of Econometic Methods for Assessing the Impact of Watershed Programs K Palanisami1, D Suresh Kumar2 and Suhas P Wani3 1
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Abstract Watershed programs in India are contributing to water resources development, agricultural production and ecological balance. Impact DVVHVVPHQWRIZDWHUVKHGGHYHORSPHQWSURMHFWLQFOXGHV L GHYHORSLQJ a framework to identify what impacts to assess and (ii) developing a framework to look after the indicators together and assessing the overall impact of the project. The nature of watershed technologies and their impact on different sectors pose challenges to the evaluation SURFHVV 0RUH VSHFL¿FDOO\ PDMRU FKDOOHQJHV LQFOXGH L FKRLFH RI methodologies, (ii) selection of indicators, (iii) choice of discount rate, LY TXDQWLI\LQJ EHQH¿WV LQ XSVWUHDP DQG GRZQVWUHDP Y GH¿QLQJ WKH]RQHRILQÀXHQFHDQG YL H[WHQWRIQDWXUDODQGDUWL¿FLDOUHFKDUJH FRQYHQWLRQDO PHWKRGV XVLQJ ¿QDQFLDO PHDVXUHV DWWHPSW WR TXDQWLI\ the impacts in an isolated manner. In order to evaluate the impacts of watershed programs in a holistic manner, the Economic Surplus (ES) approach has been applied. The economic surplus incorporates both consumer surplus and producer surplus. The consumer surplus LV WKH DPRXQW WKDW FRQVXPHUV EHQH¿W E\ EHLQJ DEOH WR SXUFKDVH D product for a price that is less than they would be willing to pay. The SURGXFHUVXUSOXVLVWKHDPRXQWWKDWSURGXFHUVEHQH¿WE\VHOOLQJDWD market price mechanism that is higher than they would be willing to sell for. In the case of watershed programs, producers are mainly the IDUP KRXVHKROGV ZKR SURGXFH WKH JRRGV XVLQJ WKH EHQH¿WV RI WKH watershed interventions such as soil and moisture conservation, water table increase and livestock improvement activities and consumers are mainly the other stakeholders in the region, viz. non-farm households representing the labourers, business people and people employed in non-agricultural activities. The ES method is demonstrated using the data from a cluster of 10 watersheds in the Coimbatore district of Tamil Nadu. The distributional effects of watershed programs are also captured through the ES method. The results of the conventional method had indicated that the BCR is 1.23, IRR is 14% and NPV is Rs 567912. The results of the ES method had indicated that the BCR is 1.93, the IRR is 25 % and the NPV is Rs 2271021. The conventional 106
evaluation method had thus underestimated the watershed impacts. Hence, possibilities of using the ES methodology in the future watershed evaluation programs could be examined.
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References Department of Land Resources 5HSRUW RI WKH7HFKQLFDO &RPPLWWHH RQ:DWHUVKHG3URJUDPPHVLQ,QGLD)URP+DUL\DOLWR1HHUDQFKDO,'HSDUWPHQW
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Recent Developments in Vadose Zone Hydrology: Opportunities and Challenges for Sustainable Utilization of Water and Nutrients for Enhancing Productivity BS Das ,QGLDQ,QVWLWXWHRI7HFKQRORJ\ ,,7 .KDUDJSXU:HVW%HQJDO,QGLD
Abstract Declining total land area under cultivation, increasing demand for land for non-agricultural use, demand for food grains, large gap between actual and potential yields, and recent trends in weather anomalies call for an urgent action to identify ways and means for improving DJULFXOWXUDO SURGXFWLYLW\ (I¿FLHQW DQG LQWHOOLJHQW XVH RI ZDWHU DQG nutrients has a potential opportunity to improve agricultural productivity LQDVPXFK DV WKHLU SUHYDLOLQJ XVH HI¿FLHQFLHV DUH ORZ )RU H[DPSOH ERWKWKHXVHHI¿FLHQFLHVIRUZDWHUDQGQLWURJHQIRUDPDMRUFURSVXFK as rice are in the order of 25%. For the past two decades, several developments in vadose zone hydrology have opened opportunities WR LPSURYH ZDWHU DQG QXWULHQW XVH HI¿FLHQFLHV 6SHFL¿FDOO\ ORZFRVW sensors and user-friendly simulation models are becoming reliable aids for making informed agricultural decisions on how much and KRZIUHTXHQWO\ERWKZDWHUDQGQXWULHQWVKDYHWREHDSSOLHGWRVSHFL¿F crops, making precision farming a reality. A summary of these two products are discussed in this document with the objective to identify RSSRUWXQLWLHVDQGUHVHDUFKQHHGVVSHFL¿FWR,QGLDQDJULFXOWXUH
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Use of Agroclimatic Datasets for Improved Planning of Watersheds AVR Kesava Rao, Suhas P Wani and Piara Singh ,QWHUQDWLRQDO&URSV5HVHDUFK,QVWLWXWHIRUWKH6HPL$ULG7URSLFV ,&5,6$7 3DWDQFKHUX$QGKUD3UDGHVK,QGLD
Abstract Maximizing agricultural production from rain-fed areas in a sustainable manner is the need of the day to feed the ever-increasing population. Integrated watershed management with focus on productivity enhancement and livelihood improvement is one of the high priority DUHDV LGHQWL¿HG DQG SURPRWHG IRU SURGXFLQJ ERWK WDQJLEOH DQG QRQ WDQJLEOH EHQH¿WV WR WKH LQGLYLGXDOV DV ZHOO DV IRU FRPPXQLWLHV DV D whole. Reliable and long-term data on agroclimate, soils, crop varieties and crop production at taluk/block/district-level for several years are needed for undertaking climatic analyses and to understand variations in agricultural productivity and changes in the cropping patterns. Data on crop phenology, growth and yield characters are needed to quantify crop-weather relationships and for validating crop-growth simulation models. Agroclimatic datasets need to be developed at individual watershed level and climatic analyses help in assessing rainwater KDUYHVWLQJSRWHQWLDOHI¿FLHQWODQGXVHSODQQLQJGHWHUPLQLQJVXLWDELOLW\ of crops, risk analysis of climatic hazards, adoption of farming methods and choice of farm machinery. In this paper, results of climatic analysis of selected watersheds in India with respect to water balance and length of rain-fed crop-growing period, yield gap analysis of some important crops are presented and discussed. Use of agroclimatic datasets goes much beyond agroclimatic analysis of watersheds. Current issues like end-of-the-season crop yield forecasting, climatic change impact assessment, crop insurance to farming community, maintaining quality of produce to compete with international market, sustainability of the yield and environment are also to be addressed. Enhancing climate awareness among the rural stakeholders using new IT tools is the need of the hour.
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Figure 1. Projected climate change impact on LGP at Solapur.
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Figure 3. Sorghum yield simulations at Aurangabad, Maharashtra.
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References Allen RG, Pereria LS, Dirk Raes DQG Martin Smith. &URS (YDSRWUDQVSLUDWLRQ±*XLGHOLQHVIRUFRPSXWLQJFURSZDWHUUHTXLUHPHQWV)$2 ,UULJDWLRQDQG'UDLQDJHSS Bhatia VS, Singh Piara, Wani SP, Kesava Rao AVR DQG Srinivas K.
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Abstract Management and utilization of natural resources - land and water have assumed the prime importance in the wake of increasing pressure on them. In this context, the watershed approach has gained momentum all over the world for addressing environmental issues and implementing various developmental programs. Though watershed represents a hydrological unit of an area, it is also considered as D ELRSK\VLFDO DQG VRFLRHFRQRPLF XQLW IRU HI¿FLHQW SODQQLQJ DQG management of natural resources. These developmental activities in any watershed, focuses not only on management of rain water, reducing soil loss, runoff and increasing productivity but also focuses RQVRFLDODQG¿QDQFLDOXSOLIWPHQWRIWKHZDWHUVKHGFRPPXQLW\)RUDQ HI¿FLHQWH[HFXWLRQRIDQ\DFWLYLW\HI¿FLHQWSODQQLQJLVIRUHPRVW 7RDFFRPSOLVKHI¿FLHQWSODQQLQJJHRVSDWLDOWHFKQRORJLHVOLNHUHPRWH sensing, GPS and GIS are being increasingly used to address various aspects of watershed developmental programs namely preparation of EDVHPDSVQDWXUDOUHVRXUFHLQYHQWRU\DWGLIIHUHQWVFDOHVLGHQWL¿FDWLRQ of critical issues with respect to soils/water/crops, generation of action plans and impact assessment. Several studies were conducted on watershed planning with reference to natural resources and cropping systems planning. Stereo data obtained from aerial and satellite platforms play an immense role in obtaining terrain height information in the watershed. Essentially the height information thus extracted is represented in the form of Digital Elevation Model (DEM). When clubbed with drainage information, hydrological DEM can be generated which inturn is useful to delineate watersheds automatically as well as hydrological modeling of watershed. Besides, high spatial resolution data are increasingly being used to monitor various soil conservation activities, and to assess watershed performance. During recent years, with the development of communication WHFKQRORJ\ WHFKQLTXHV KDYH HPHUJHG IRU UHDO WLPH ¿HOG GDWD collection and transmission, which will be of immense use for real time monitoring of watershed activities. A large network of Automatic 156
Weather Stations across India is being created with state-of-the-art communication tools to serve the data on web in almost real time. The revolution in electronic circuits made it possible to attach a radio to almost any electronic device and remotely communicate with it. This has ushered new ideas of developing sensor web where these sensors can communicate with each other and use the information intelligently as a single system. The sensor network can function independently and collaboratively to provide parameters need to measure in the ¿HOG %\ DGGLQJ PDFKLQH LQWHOOLJHQFH WKHVH QHWZRUNV FDQ SHUIRUP LPSRUWDQW ¿HOG GHFLVLRQV DXWRPDWLFDOO\ 7KH GHYHORSPHQWV LQ PLFUR nano satellites and their networking with ground based sensors; the data can be used for real time applications in watershed management. Further, Geoinformatics and web GIS tools can bring major impact on the watershed management.
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References Annonynous. ZZZVDWLPDJLQJFRUSFRP6327B'(0B3URGXFWB 'HVFULSWLRQBYSGI$FFHVVHGRQ-DQ Bharadwaj SP. 6RLOHURVLRQDQGLWVFRQWUROLQ'RRQYDOOH\ZLWKVSHFLDO UHIHUHQFHWRDJULFXOWXUHODQGV3URF6\PSRQµ5HVRXUFHVVXUYH\IRUODQGXVH SODQQLQJDQG(QYLURQPHQWFRQVHUYDWLRQ¶,QGLDQ3KRWRLQWHUSUHWDWLRQ,QVWLWXWH 'HKUDGXQ2FWREHUSS Bonde WC. 1985. 0DUU\ FRQVHUYDWLRQ DJURQRP\ IRU VXVWDLQHG SURGXFWLRQ In 1DWLRQDOVHPLQDURQµ6RLOFRQVHUYDWLRQDQGZDWHUVKHGPDQDJHPHQW¶1HZ 'HOKLSS
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Abstract Integrated Watershed Development (IWD) has been in practice for a very long time and it has received special attention in the recent past with the advent of technological tools for planning, implementation, monitoring and impact studies. IWD itself has gone through varieties of changes in the approaches for development and implementation and so is the case with respect to the possible use of technologies. Of late, the use of space based inputs from remote sensing and Geographic Information System (GIS) technology have helped IWD GLUHFWO\ 6DWHOOLWH UHPRWH VHQVLQJ LV SDUWLFXODUO\ RI VLJQL¿FDQW XVH in characterizing the terrain, understanding the existing landuse, generating soil maps, estimating ground water/water resource SRWHQWLDODQG¿QDOO\LQWHJUDWLQJDOOWKHVHXQGHUWKHJHRVSDWLDOGRPDLQ with base layers and other infrastructure layers. Such an integration of multi-thematic GIS layers with socio-economic data and ground knowledge helps in deriving action plans, which could be a guiding factor for further implementation at grass roots. With the availability of very high resolution satellite images and hence large scale thematic mapping possibilities, it is even possible to address developmental DVSHFWV DW IDUPHUV¶ ¿HOG OHYHO WKURXJK FDGDVWUDO RYHUOD\V 6XFK DWWHPSWVKDYHEHHQPDGHQRWRQO\IRUSURYLGLQJORFDOHVSHFL¿FDFWLRQ plans for IWD, but also for systematic monitoring and management. The advantage of using such techniques is in bringing about greater transparency amongst implementers and other stakeholders, which in WXUQKHOSVLQEHWWHUH[HFXWLRQWKXVUHVXOWLQJLQRSWLPDOEHQH¿WVWRWKH farming community. Close monitoring of IWD programs need many parameters/indicators to be studied in detail throughout the project lifetime. While some of the parameters/indicators are amenable through Management Information System (MIS) databases, the others are obtained through *,6WHFKQRORJ\:LWKWKHDYDLODELOLW\RIFRQQHFWLYLW\IURPWKH¿HOGOHYHO (villages) through taluk, district and state level users, it is possible to establish web-based information and decision support systems
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for closer and effective monitoring of such developmental programs. 6SHFL¿F VRIWZDUH WRROV DQG WHFKQLTXHV IRU ORFDOH VSHFL¿F DFWLRQ plan preparation (also popularly known as DPR preparation at subdistrict level in a state), web based GIS and MIS tools for on-line project monitoring and multi-temporal remote sensing data for impact assessment have been successfully used as in watershed development programs of Karnataka. Considering the success achieved in this program, similar attempts are being extended to a few other states in the country. Innovative use of space inputs, information technology and GIS has helped in successfully testing such technologies under operational scenarios. It is now required to emulate more such projects and also integrate such tools and technologies at national level programs like Integrated Watershed Management Program of DoLR, 0R5'DQGRWKHU&HQWUDODQGVWDWHPLQLVWULHVWRLPSURYHWKHHI¿FLHQF\ DQGGHULYHEHWWHUUHVXOWVZKLOHKHOSLQJLQSURYLGLQJULFKEHQH¿WVWRWKH grass root level farming community.
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Figure 1. Pictorial view of data collection and analysis.
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Figure 2. Geospatial data layers for participatory action plan preparation.
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Figure 3. Community level GIS Technology for PRA and action plans.
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Map 1. Selected rain-fed districts for crop productivity enhancement under Bhoochetana project in Karnataka. Table 2. Timeline for execution of activities in Bhoochetana districts. DFWLYLW\FRYHUDJHLQGLVWULFWV $FWLYLW\
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Table 4. Rabi cropping planned and area of sowing completed in different districts during rabi season 2009. 7DUJHWDUHD KD
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207
Field Days )LHOGGD\VZHUHFRQGXFWHGIRUJURXQGQXWIDUPHUVLQ.XUXEDUDPDOOXUX YLOODJHRQWK6HSWHPEHU DQGIRUPDL]HIDUPHUVLQ.DEXUYLOODJH RQ WK 6HSWHPEHU LQ +DYHUL GLVWULFW 'R$ VWDII DORQJ ZLWK & 0 8GDVLWKH+RQ0LQLVWHURI3XEOLF:RUNV'HSDUWPHQWYLVLWHGWKH¿HOGV RI+DYHULDQGREVHUYHGDFOHDULPSURYHPHQWLQFURSJURZWKDQG\LHOG DVDUHVXOWRIWHFKQRORJ\LQWHUYHQWLRQVLQWKH%KRRFKHWDQDSURMHFW
Kharif Season Crop Planning 2010 'XULQJkharifWKHSURMHFWZDVVFDOHGRXWLQQLQHQHZGLVWULFWVIRU SURGXFWLRQHQKDQFHPHQWRIUDLQIHGFURSVDIWHUVRLOGLDJQRVWLFVWXGLHV DQG DZDUHQHVV FDPSDLJQV WR IDUPHUV DQG RWKHU VWDNHKROGHUV DERXW VRLOKHDOWKLQWKHVHDGGLWLRQDOGLVWULFWV$WDUJHWRIODNKKHFWDUHVZHUH DOPRVW FRYHUHG ZLWK LPSURYHG SURGXFWLRQ HQKDQFHPHQW WHFKQRORJLHV DVDSDFNDJHLQDVPDQ\DVYLOODJHVLQGLVWULFWVRI.DUQDWDND
Results of Participatory Crop Yield Estimates Crop Season 2009 5DLQIDOO LQ DOO WKH VL[ GLVWULFWV ZDV PRQLWRUHG DQG LW ZDV HUUDWLF ZLWK HDUO\PRQVRRQVKRZHUVIROORZHGE\ORQJGU\VSHOOH[WHQGLQJXSWR GD\V LQ .RODU &KLNEDOODSXU DQG7XPNXU DIIHFWLQJ FURS SHUIRUPDQFH ,Q +DYHUL DQG 'KDUZDG UDLQIDOO GLVWULEXWLRQ ZDV QRUPDO GXULQJ WKH VHDVRQ+RZHYHUKHDY\UDLQIDOODWWKHHQGRIVHDVRQZKHQWKHFURSV ZHUHUHDFKLQJPDWXULW\KDGDIIHFWHGFURSKDUYHVWLQJ3DUWLFLSDWRU\FURS FXWWLQJH[SHULPHQWVE\DMRLQWWHDPRIRI¿FLDOVRI'R$8$6VDQG,&5,6$7 XQGHUWRRNWKHFURSFXWWLQJH[SHULPHQWVDORQJZLWKSDUWLFLSDWLRQRIIDUP IDFLOLWDWRUVLQGLYLGXDOIDUPHUVDQGVWDNHKROGHUVUHFRUGHGREVHUYDWLRQV LQWKHIDUPHUV¶SUDFWLFHDVZHOODVLPSURYHGPDQDJHPHQWLQIDUPHUV¶ ¿HOGVRI¿YHYLOODJHVLQHDFK RIDOOWKHVL[GLVWULFWVIRU\LHOGHVWLPDWLRQ IRUVHOHFWHGFURSV :LWK%KRRFKHWDQDLQLWLDWLYHJURXQGQXWSRG\LHOGVLQFUHDVHGDFURVVDOO taluksRIVL[GLVWULFWVLQWKHUDQJHRIWRZKLFKYDULHGIURPWKH ORZHVWLQFUHDVHRILQ0XONDOPXUtalukRI&KLWUDGXUJDWRWKHKLJKHVW
\LHOGLQFUHDVHRILQ+XEOLtalukRI'KDUZDGGLVWULFW5DJLIDUPHUV KDUYHVWHGDQDGGLWLRQDORQHWRQRIJUDLQ\LHOGDQGWKDRIIRGGHU E\ DGRSWLQJ LPSURYHG PDQDJHPHQW DORQJ ZLWK EDODQFHG QXWULWLRQ LQ .RODU:HLJKWHGPHDQJUDLQ\LHOGLQFUHDVHDFURVV.RODU7XPNXUDQG &KLWUDGXUJDGLVWULFWVYDULHGIURPWR 0DL]HJUDLQ\LHOGLQFUHDVHLQIDUPHUV¶¿HOGVZLWKLPSURYHGPDQDJHPHQW ZDV EHWZHHQ LQ GLIIHUHQW taluks RI +DYHUL DQG WR LQ GLIIHUHQW taluks RI &KLWUDGXUJD 2Q DQ DYHUDJH IDUPHUV KDUYHVWHG JUDLQ\LHOGRIWRQVDQGWKDRIIRGGHUDGGLWLRQDOO\ZLWKLPSURYHG PDQDJHPHQW³EDODQFHGQXWULWLRQ´FRPSDUHGWRJUDLQDQGIRGGHU\LHOGV ZLWK IDUPHUV¶ PDQDJHPHQW LQ +DYHUL ,Q 'KDUZDG IDUPHUV KDUYHVWHG JUDLQ \LHOGV LQ WKH UDQJH RI WR NJ KD ZLWK LPSURYHG PDQDJHPHQWDQGWKHVHHG\LHOGLQFUHDVHDFURVVWKHGLVWULFWZDV RYHUIDUPHUV¶PDQDJHPHQW
Farmers' Management
Improved management+Micronutrients
2500
-1
Pod yield (kg ha )
3000
2000 1500 1000
Dharwad
Haveri
Chitradurga
Tumkur
Chikkaballapur
0
Kolar
500
Groundnut
Groundnut pod yield increase (district-wise) with improved management compared to farmers’ management in six districts of Karnataka during kharif 2009.(Source. Annual Progress Report 2009-10, 2010) 209
Farmers' Management
Improved management+Micronutrients 39%
44%
7000
-1
Grain Yield (kg ha )
8000
6000 5000 66%
4000
36%
35%
39%
3000 2000
Ragi
Maize
Dharwad
Haveri
Chitradurga
Chitradurga
Tumkur
0
Kolar
1000
Soybean
Crops
Grain yield increase in selected crops (district-wise) with improved PDQDJHPHQW FRPSDUHG WR IDUPHUV¶ PDQDJHPHQW LQ ¿YH GLVWULFWV RI Karnataka during kharif 2009. (Source. Annual Progress Report 200910, 2010) ,QWHQVHPRQLWRULQJE\VWDWHOHYHOKLJKSRZHUFRRUGLQDWLRQFRPPLWWHHDW UHJXODULQWHUYDOVIDFLOLWDWHGE\,&5,6$7WRHQVXUHJRRGFRRUGLQDWLRQRI DOOVWDNHKROGHUVWRLPSOHPHQWWHFKQRORJLHVLQWKHSURMHFWUHVXOWHGLQ VXFFHVVIXOLPSOHPHQWDWLRQDQGFURS\LHOGLQFUHDVHVEHWZHHQ IRUIDUPHUVDFURVVVL[GLVWULFWVLQWKH¿UVW\HDU 'XULQJ rabi VHDVRQ FKLFNSHD VHHG \LHOG LQFUHDVHG E\ LQ &KLWUDGXUJD VRUJKXP JUDLQ \LHOG LQFUHDVHG E\ LQ +DYHUL DQG LQ 'KDUZDG GLVWULFWV ZLWK LPSURYHG PDQDJHPHQW RYHU IDUPHUV¶ PDQDJHPHQW6XQÀRZHUVHHG\LHOGLQFUHDVHGE\ZLWKLPSURYHG PDQDJHPHQWFRPSDUHGWRIDUPHUV¶PDQDJHPHQW$FWXDO\LHOGLQFUHDVH ZDVDERXWNJKDZLWKVXQÀRZHURUFKLFNSHD
210
Table 5. District-wise crop yield increase in farmers’ ¿elds with improved management compared to farmers’ management under Bhoochetana project, 2009. )DUPHUV PDQDJHPHQW
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211
Table 6. Additional income to farmers on additional rupee invested for improved management during 2009 crop season
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Farmers' Management
-1 Rabi crop seed/grain yield (kg )
2000
Improved Management
43% 51% 23% 34%
1500 38%
1000
500
0 Sunflower
Rabi sorghum
Haveri
Chickpea Chitradurga
Chickpea
Rabi sorghum
Dharwad
Grain yield increase in selected crops (district-wise) with improved management compared to farmers’ management in three districts of Karnataka during kharif 2010. (Source. Annual Progress Report, 2010)
212
Crop Season 2010 'XULQJkharifVHDVRQUDLQIDOOKDVEHHQDERYHQRUPDOLQDOOWKHVHGLVWULFWV DQGLQVRPHGLVWULFWV6KRUWGXUDWLRQOHJXPHVDQGUDJLDUHDIIHFWHGE\ LQFHVVDQWUDLQVDWKDUYHVWLQJDQG\LHOGORVVHVDOVRPHQWLRQHGE\IDUPHUV kharifFURSKDUYHVWLQJDQGFURSFXWWLQJH[SHULPHQWIRU\LHOGHVWLPDWLRQV KDYHEHHPFRPSOHWHGLQDOOVL[WHHQGLVWULFWV(DUO\\LHOGHVWLPDWHVIRU VKRUWGXUDWLRQFURSVOLNHEODFNJUDPJUHHQJUDPJURXQGQXWVR\EHDQ DQGUDJLDYDLODEOHKHQFHSUHVHQWHGLQWKLVSDSHUWRJLYHDJOLPSVHRI UDLQIHGFURSVUHVSRQVHWRLPSURYHGPDQDJHPHQWGXULQJUDLQ\VHDVRQ $FFRUGLQJWRHDUO\HVWLPDWHVDYDLODEOHJURXQGQXWSRG\LHOGVLQFUHDVHG E\ DQG UHVSHFWLYHO\ LQ .RODU DQG +DYHUL ZLWK LPSURYHG PDQDJHPHQW FRPSDUHG WR IDUPHUV¶ PDQDJHPHQW )DUPHUV LQ +DYHUL EHQH¿WHG E\ JRRG FURS KDUYHVW RI QHDUO\ W KD RI JURXQGQXW SRG \LHOGZKLFKZDVKLJKHUE\ NJKDLQWKHLPSURYHGPDQDJHPHQW 5HVSRQVHRIUDJLFURSWRLPSURYHGPDQDJHPHQWLQ.RODUZDVYHU\JRRG ZLWK JUDLQ \LHOG LQFUHDVH DQG VR\EHDQ VHHG \LHOG LQFUHDVH ZDV RYHUIDUPHUV¶PDQDJHPHQWLQ+DYHULGLVWULFW Farmers' Management
Improved Management
38%
-1 Grain yield (kg ha ha-1) )
1200
900
31%
600
52%
57%
300
0 Bidar
Bijapur
Yadagir
Gadag
Green gram
Grain yield increase in green gram (district-wise) with improved management compared to farmers’ management in four districts of Karnataka during kharif 2010. (Source. Annual Progress Report, 2010) 213
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Acknowledgements :H DUH WKDQNIXO WR %KRRFKHWDQD VWDII RI 'R$ VWDII RI :DWHUVKHG 'HYHORSPHQW 'HSDUWPHQW VWDII RI 8$6 %DQJDORUH 5DLFKXU DQG 'KDUZDG VWDII RI 5\WKX 6DPSDUND .HQGUDV 56.V LQ HDFK taluk IDUPIDFLOLWDWRUVDQGIDUPHUVIRUWKHLUVXSSRUWDQGZRUNLQJDVWHDPIRU WKH VXFFHVVIXO LPSOHPHQWDWLRQ RI WKH SURMHFW LQ D FRQVRUWLXP PRGH FRQYHUJLQJDFWLYLWLHVRIRWKHUDFWLYLWLHVDOVRLQWRWKLVSURMHFWDFWLYLW\
References Sahrawat KL, Wani SP, Rego TJ, Pardhasaradhi G DQG Murthy KVS. :LGHVSUHDGGH¿FLHQFLHVRIVXOSKXUERURQDQG]LQFLQGU\ODQGVRLOVRI,QGLDQ VHPLDULGWURSLFV&XUUHQW6FLHQFH
215
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220
Table 1. Summary of bene¿ts from the sample watersheds. 3DUWLFXODUV
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Watersheds (%)
80.0 70.0
67.5
60.0 50.0 40.0 30.0 20.0 10.0 0.0
13.2
12.2
0.6 <1
1 to 2
2 to 3
3 to 4
2.6
3.9
4 to 5
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Benefit-cost ratio
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41.4
Watersheds (%)
40.0 35.0
30.2
30.0 25.0 20.0 15.0 5.0
11.1
8.6
10.0
6.8
1.9
0.0 <10
10 to 20
20 to 30
30 to 40
40 to 50
>50
Internal rate of return (%)
Figure 2. Distribution (%) of watersheds according to internal rate of return.
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Table 2. Summary of bene¿ts from the sample watersheds according to people's participation 3HRSOH VSDUWLFLSDWLRQ ,QGLFDWRU
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Hydrological Modeling of a Micro Watershed using GIS-based Model SWAT: A Case Study of Kothapally Watershed in Southern India Kaushal K Garg and Suhas P Wani ,QWHUQDWLRQDO&URSV5HVHDUFK,QVWLWXWHIRUWKH6HPL$ULG7URSLFV 3DWDQFKHUX$QGKUD3UDGHVK,QGLD
Abstract Rain-fed agriculture in arid or semi arid tropics is complex, diverse, risk prone, and characterized by low levels of productivity and low input usages. Kothapally, a micro watershed of 450 ha area is located approximately 25 km upstream of Osman Sagar in Musi catchment of Southern India. Rainfall in this region is highly erratic both in terms of total amount and its distribution over time. ICRISAT consortium with national partners (Central Research Institute for Dryland Agriculture (CRIDA), National Remote Sensing Agency (NRSA) now NRSC, and District Water Management Agency (DWMA), in Hyderabad, Andhra Pradesh,); and non-governmental organizations (NGOs) started community based watershed development program in Kothapally YLOODJHLQ 6LQFHWKHRQVHWRIWKHSURJUDPZDWHUÀRZVDQGFURS parameters in the area have been monitored, creating database of hydrological data and crop yield information. This data was analyzed with the Soil and Water Assessment Tool (SWAT) to study the water EDODQFH IRU GLIIHUHQW ZDWHU PDQDJHPHQW RSWLRQV ,Q DGGLWLRQ ÀRZ UHGXFWLRQ DQG VRLO ORVV IURP WKH ¿HOGV ZDV HYDOXDWHG WR DVVHVV WKH downstream impacts on the Osman Sagar reservoir. It was found WKDW GLIIHUHQW ZDWHU PDQDJHPHQW DSSURDFKHV VLJQL¿FDQWO\ FKDQJHV the water balance of the system. Check-dams increase groundwater recharge which can be used for supplementary irrigation of the monsoon crop, and especially the second crop when rainfall is almost nil. Both check-dams and in-situ soil water management reduces the RXWÀRZ IURP WKH V\VWHP ,QVLWX VRLO ZDWHU PDQDJHPHQW LQFUHDVHV evapotranspiration, which can be expected when more water is LQ¿OWUDWHG LQWR WKH VRLO 0RQVRRQDO DQDO\VLV VKRZV WKDW ZDWHUVKHG management practices reduced surface runoff from 27% to 11%, LPSURYHGJURXQGZDWHUDYDLODELOLW\IURP WRLQFUHDVHG(7ÀRZ from 53% to 66% of total rainfall, and reduced soil loss from 1.5 t ha-1 to 2.5 t ha-1 compared to pre-development stage. This program has built resilience in the agricultural systems, and has improved the livelihoods of the farmers. Keywords: Hydrological modeling, SWAT, water balance, sediment transport, resilience, watershed management. 241
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Figure 1. (A) Location of Kothapally watershed in Musi sub-basin of Krishna river basin, down stream reservoirs and Hyderabad city; (B) Stream network, location of storage structures, open wells, meteorological station, and residential area in Kothapally watershed. 243
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Methodology Input Data and Model Setup 6:$7 UHTXLUHV WKUHH EDVLF ¿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Scenario Development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
Results Water Balance of Different Water Intervention Scenarios 'LIIHUHQW ZDWHU LQWHUYHQWLRQV VLJQL¿FDQWO\ FKDQJH WKH ZDWHU EDODQFH FRPSRQHQWV LQ ZDWHUVKHG )LJXUH %HIRUH WKH LQWURGXFWLRQ RI WKH ZDWHUVKHG GHYHORSPHQW SURJUDP VFHQDULR IRXU DSSUR[LPDWHO\ RI WKH UDLQIDOO EHFDPH HYDSRUWUDQVSLUDWHG (7 ZKLOH VRPH UHFKDUJHG WKH JURXQGZDWHU DTXLIHU DQG ZDV ORVW IURP WKH ZDWHUVKHG ERXQGDU\ DV RXWÀRZV GXULQJ WKH ¿UVW FURSSLQJ VHDVRQ :KHQWKHZDWHUVKHGGHYHORSPHQWSURJUDPZDVLQSODFHWKHDPRXQW RIZDWHUOHDYLQJWKHZDWHUVKHGDV(7KDGLQFUHDVHGWRDURXQG JURXQGZDWHUUHFKDUJHZDVDOVRKLJKHUWKDQSUHYLRXVO\ZKLOHRXWÀRZV IURPWKHZDWHUVKHGZDVQRZOHVVWKDQRIWKHWRWDOZDWHUEDODQFH VFHQDULR RQH &RQVWUXFWLQJ FKHFNGDPV VXEVWDQWLDOO\ LQFUHDVHG JURXQGZDWHUUHFKDUJH VFHQDULRWKUHH ZKLOHLQVLWXSUDFWLFHVUHVXOWHG LQDKLJKHU(7VLQFHPRUHZDWHUZDVDYDLODEOHDVVRLOPRLVWXUHLQWKH ¿HOGVDQGKLJKHUJURXQGZDWHUUHFKDUJH VFHQDULRWZR
Sediment Transport and Soil loss 7KH DYHUDJH VRLO ORVV IURP WKH ZDWHUVKHG KDV EHHQ OHVV WKDQ W KDLQDOO\HDUVH[FHSWLQZKHQ.RWKDSDOO\H[SHULHQFHGDKHDY\ GRZQSRXURIPPZLWKLQKRXUVLQ$XJXVWZKLFKFUHDWHGHQRUPRXV 247
Outflow
GW recharge
ET
Change in Soil MC
100%
Percentage of Total rainfal
80%
60%
40%
20%
0% Scenario1
Scenario2
Scenario3
Scenario4
-20%
Figure 2. Water balance for the four different water management scenarios for WKH¿UVWFURSSLQJVHDVRQ IURP-XQHWR'HF VFHQDULR LQVLWXFKHFNGDPV VFHQDULR LQVLWX QR FKHFNGDPV VFHQDULR QR LQVLWX FKHFNGDPV VFHQDULR QRLQVLWXQRFKHFNGDPV*:UHFKDUJH JURXQGZDWHUUHFKDUJH (7 HYDSRWUDQVSLUDWLRQ
DPRXQWVRIUXQRIIDQGVRLOORVVIURPWKHZDWHUVKHGERXQGDU\6LPXODWLRQV VXJJHVWWKDWRQDYHUDJHPPRIVRLOZDVORVWIURPWKHHQWLUHZDWHUVKHG GXHWRWKLVH[WUHPHHYHQW$VRLOORVVPDSIRUVKRZVWKDWVRLOLV ORVWIURPDODUJHDUHDRIWKHZDWHUVKHG )LJXUH 6RLOVDUHGHSRVLWHGLQ WKRVHPLFURZDWHUVKHGVZKHUHFKHFNGDPVZHUHEXLOWVLQFHWKHFKHFN
Figure 3. Soil loss in different micro-watersheds of Kothapally area in year 2000. Gray colour in map shows soil loss and crossed lines shows its deposition (also shown by negative numbers).
100 90 Soil loss WKD (ton/ha)
80
Scenario-1
70
Scenario-4
60 50 40 30 20 10 0 0
50
100
150
200
250
300
Daily rainfall (mm) )LJXUH5DLQIDOOYVVRLOORVV VFHQDULR LQVLWXFKHFNGDPV SRVW ZDWHUVKHGGHYHORSPHQW VFHQDULR QRLQVLWXQRFKHFNGDPV QR watershed development).
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249
Discussion Water Management Interventions Improve the Resilience of Small-scale Tropical Agricultural Systems %HFDXVH RI WKH ZDWHUVKHG GHYHORSPHQW SURJUDPV WKH OLYHOLKRRGV RI WKH IDUPHUV LQ WKH .RWKDSDOO\ YLOODJH KDYH LPSURYHG $JULFXOWXUDO \LHOGVDUHRQWKHLQFUHDVHDQGIDUPHUVDUHQRZDEOHWRVDYHVRPHRI WKH LQFRPHV JHQHUDWHG E\ WKH IDUP DQG WR UHLQYHVW LQ WKH EXVLQHVV %HFDXVHRIGLYHUVL¿FDWLRQRIVRXUFHVRILQFRPHGXHWRPRUHRIIIDUP DFWLYLWLHVWKHLUUHVLOLHQFHWRH[WHUQDOVKRFNVKDVEHHQLPSURYHG0RUH VSHFL¿FDOO\WKHZDWHULQWHUYHQWLRQVKDYHUHGXFHGWKHLQKHUHQWULVNVLQ DJULFXOWXUHLQWKHVHPLDULG]RQHSRVHGE\KLJKUDLQIDOOYDULDELOLW\DQG IUHTXHQW GU\VSHOOV WKHUHE\ EXLOGLQJ UHVLOLHQFH LQ WURSLFDO DJULFXOWXUH :LWK D PRUH HUUDWLF SUHFLSLWDWLRQ XQGHU IXWXUH FOLPDWH FKDQJH ZDWHU PDQDJHPHQWLQWHUYHQWLRQVLQWURSLFDODJULFXOWXUHDUHOLNHO\WREHRIHYHQ JUHDWHULPSRUWDQFH
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Conclusions :DWHUVKHG LQWHUYHQWLRQV LQ DJULFXOWXUH LQ WKH IRUP RI LQVLWX DQG H[ VLWX ZDWHU KDUYHVWLQJ V\VWHPV DUH LPSRUWDQW IRU EXLOGLQJ UHVLOLHQFH LQ WURSLFDODJULFXOWXUHEXWPD\DWWKHVDPHWLPHFDXVHQHJDWLYHLPSDFWVWR GRZQVWUHDPV\VWHPVEHFDXVHRIUHGXFHGZDWHUÀRZV7KHZDWHUVKHG LQWHUYHQWLRQVLQWKH.RWKDSDOO\YLOODJHUHVXOWHGLQKLJKHULQ¿OWUDELOLW\DQG ZDWHUKROGLQJ FDSDFLW\ RI WKH VRLO DV ZHOO DV LQFUHDVHG JURXQGZDWHU OHYHOV ZKLFK HQDEOHG VXSSOHPHQWDU\ LUULJDWLRQ RI WKH PRQVRRQ FURS WREULGJHGU\VSHOOVDQGIXOOLUULJDWLRQRIDVHFRQGGU\VHDVRQFURSRQ RIWKH¿HOGV6RLOORVVKDVGHFUHDVHGE\DIDFWRUWHQEHFDXVHRIWKH ZDWHUVKHGGHYHORSPHQWSURJUDPZKLFKLVH[SHFWHGWRKDYHSRVLWLYH LPSDFWV RQ LQVWUHDP ULYHU HFRORJ\ DQG WKH OLIHVSDQ RI WKH UHVHUYRLU GRZQVWUHDP &DVH VWXG\ RI .RWKDSDOO\ ZDWHUVKHG KDV VKRZQ WKDW LQWHJUDWHGZDWHUVKHGPDQDJHPHQWDSSURDFKKDVEXLOWUHVLOLHQFHLQWKH DJULFXOWXUDOV\VWHPVDQGKDVLPSURYHGWKHOLYHOLKRRGVRIWKHIDUPHUV
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References Immerzeel WW, Gaur A DQG Zwart SJ. ,QWHJUDWLQJUHPRWHVHQVLQJDQG DSURFHVVEDVHGK\GURORJLFDOPRGHOWRHYDOXDWHZDWHUXVHDQGSURGXFWLYLW\LQ DVRXWK,QGLDQFDWFKPHQW,Q $JULFXOWXUDO:DWHU0DQDJHPHQW Reddy VR, Shiferaw B, Bantilan MCS, Wani SP DQG Sreedevi TK. &ROOHFWLYH$FWLRQ IRU ,QWHJUDWHG :DWHUVKHG 0DQDJHPHQW LQ 6HPL$ULG ,QGLD 6WUDWHJLF 3ROLF\ DQG ,QVWLWXWLRQDO 2SWLRQV 6WUDWHJLF $VVHVVPHQWV DQG 'HYHORSPHQW 3DWKZD\V IRU $JULFXOWXUH LQ WKH 6HPL$ULG 7URSLFV ,Q *OREDO 7KHPH RQ ,QVWLWXWLRQV 0DUNHWV 3ROLF\ DQG ,PSDFWV 3ROLF\ %ULHI 1R $QGKUD 3UDGHVK ,QGLD ,QWHUQDWLRQDO &URSV 5HVHDUFK ,QVWLWXWHIRUWKH6HPL $ULG7URSLFV Sreedevi TK, Shiferaw B DQG Wani SP. $GDUVKD :DWHUVKHG LQ .RWKDSDOO\ 8QGHUVWDQGLQJ WKH GULYHUV RI KLJKHU LPSDFW *OREDO 7KHPH RQ $JURHFRV\VWHPV5HSRUW1R$QGKUD3UDGHVK,QGLD ,QWHUQDWLRQDO&URSV 5HVHDUFK,QVWLWXWHIRUWKH6HPL$ULG7URSLFV
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Figure 1. Sediment concentration variation with time during two runoff events at BW7 watershed, ICRISAT Center, Pantancheru, Andhra Pradesh, India (Pathak et al. 2004)
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Figure 2. Clock-based automatic sediment sampler for small agricultural watersheds
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Figure 3. Depth integrating sediment sampler for small agricultural watersheds
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Figure 4. Schematic diagram of the depth integrating sediment sampler
Figure 5. Working principle of the sediment sampler
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Figure 6. Microprocessor based automatic sediment sampler.
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Figure 7. Single and multiple level sensors of control unit
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Figure 8. A drum-type mechanical runoff recorder. 262
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Figure 11. Flow chart of SCS curve runoff model (Pathak et al. 1989).
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Figure 12. Runoff model comparison of measured and simulated daily runoff in two Vertisol watersheds at ICRISAT Center, Patancheru, Andhra Pradesh.
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Figure 15. Probabilities of obtaining 20, 40, 60 and 100 mm cumulative runoff in Kacharam watershed (based on 26 years of simulated data).
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References Ajay Kumar. 0RGHOLQJ UXQRII VWRUDJH IRU VPDOO ZDWHUVKHGV 0WHFK WKHVLV$VLDQ,QVWLWXWHRI7HFKQRORJ\%DQJNRN7KDLODQGSS Bruno Basso, Ritchie J T DQG Pathak P. $VVHVVLQJK\GURORJ\DQGFURS SURGXFWLRQLQDVSDWLDOO\YDULDEOHODQGVFDSHXVLQJGLJLWDOWHUUDLQPRGHOLQJ)LQDO UHSRUWRI0LFKLJDQ6WDWH8QLYHUVLW\±,&5,6$7-RLQW&ROODERUDWLYH5HVHDUFK 1DWXUDO 5HVRXUFHV 0DQDJHPHQW 3URJUDP ,&5,6$7 3DWDQFKHUX $QGKUD3UDGHVK,QGLDSS GoI (Government of India) &RPPRQ JXLGHOLQHV IRU ZDWHUVKHG GHYHORSPHQW SURMHFWV 1DWLRQDO 5DLQIHG$UHD$XWKRULW\ 15$$ 0LQLVWU\ RI /DQG5HVRXUFHV*RYHUQPHQWRI,QGLD1HZ'HOKL,QGLDSS Krishna JH. 5XQRII SUHGLFWLRQ DQG UDLQIDOO XWLOL]DWLRQ LQ WKH VHPLDULG WURSLFV 3K'WKHVLV 'HSDUWPHQWRI$JULFXOWXUDO DQG ,UULJDWLRQ (QJLQHHULQJ 8WDK6WDWH8QLYHUVLW\/RJDQ8WDK86$ Pathak P DQG Sudi R. 0DQXDO RI RSHUDWLRQ DQG LQVWUXFWLRQ 0LFURSURFHVVRUEDVHG DXWRPDWLF VHGLPHQW VDPSOHU *OREDO 7KHPH RQ$JUR (FRV\VWHPV,&5,6$73DWDQFKHUX$3,QGLDSS Pathak P, Laryea KB DQG Sudi R. $UXQRIIPRGHOIRUVPDOOZDWHUVKHGV LQ WKH VHPLDULG WURSLFV 7UDQVDFWLRQV RI $PHULFDQ 6RFLHW\ RI $JULFXOWXUDO (QJLQHHUV Pathak P, Wani SP, Singh Piara DQG Sudi R. 6HGLPHQWÀRZEHKDYLRXU IURP VPDOO DJULFXOWXUDO ZDWHUVKHGV$JULFXOWXUDO :DWHU 0DQDJHPHQW Pathak P. 5XQRIIVDPSOHUIRUVPDOODJULFXOWXUDOZDWHUVKHGV$JULFXOWXUDO :DWHU0DQDJHPHQW ± 274
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Innovative Micro¿nance and Micro-enterprise Development in Integrated Watershed Development P Biswabandhu Mohanty 1DWLRQDO%DQNIRU$JULFXOWXUHDQG5XUDO'HYHORSPHQW 1$%$5' 0XPEDL0DKDUDVKWUD,QGLD
Abstract The enterprise of rain-fed agriculture is perceived as highly risky due to vagaries of nature, i.e., wide variation in quantum and distribution of rainfall. Therefore, farmers have, over the time, evolved and adopted a ‘low risk and low return’ strategy. This high risk of rain-fed agriculture and low risk-bearing ability of rain-fed farmer is a major issue in rainfed agriculture. Moreover, bankers are not comfortable to lend to rain-fed agriculture because of the high percentage of bad loans, and they call this nonperforming assets (NPAs). This is a risk cost to the bankers. NABARD had initiated efforts to promote credit in rain-fed areas WKURXJKPHDVXUHVOLNHSURYLVLRQRIFHQWSHUFHQWUH¿QDQFHORZHUUDWH RILQWHUHVWRQUH¿QDQFHHWF NABARD has been involved in implementation of watershed projects as a project holder under the Indo-German Watershed Development Programme (IGWDP) in Maharashtra since 1992. SHG-Bank Linkage Programme, which was launched by NABARD in 1992, is the SUHGRPLQDQW PLFUR¿QDQFH GHOLYHU\ PRGHO LQ WKH FRXQWU\ FDWHULQJ WR 86 million rural households through 6.1 million SHGs. The program has become a national movement and has the potential and promise RIVHUYLQJDOOWKHH[FOXGHGSHRSOHDQGSODFHVIRUSURYLGLQJ¿QDQFLDO services and promoting livelihoods. The rain-fed zones, tribal and forest areas, watershed areas, drylands, hilly tracks, etc., are the testing grounds for the bankers and development agencies for SURPRWLQJPLFUR¿QDQFHDQGPLFURHQWHUSULVHGHYHORSPHQW
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Impact of Climate Change on Dryland Sorghum in India K Boomiraj1, Suhas P Wani2 and PK Aggarwal3 1
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Abstract This paper presents results of climate change impacts on sorghum in semi arid tropics (SAT) regions of India and adaptation strategies to overcome the impact. The main objective of the paper is how to use crop simulation model to assess the climate change impact and how best we can reduce the impact through integrated watershed approach. InfoCrop, a generic dynamic crop model, provides integrated assessment of the effect of weather, variety, pests, and soil management practices on crop growth and yield, on soil nitrogen and organic carbon dynamics in aerobic, anaerobic conditions, and also greenhouse gas emissions. The model has reasonably predicted phenology, crop growth yield. Sorghum crop was found to be sensitive to changes in carbon dioxide (CO2) and temperature. Future climate change scenario analysis showed that sorghum yields (CSH 16 and CSV 15) are likely to reduce at Akola, Anantpur, Coimbatore and Bijapur. But yield of CSH 16 will increase little in Gwalior (0.1%) at 2020 and there after it will reduce. At Kota, the sorghum yield is likely to increase at 2020 (3.3 & 1.7 % in CSH 16 and CSV 15, respectively) and no change at 2050 and yield will reduce at 2080 in both varieties. The increase in yield at Gwalior and Kota at 2020 will be due to reduction in maximum temperature and increase in rainfall from the current. Adoption of adaptation measures like one irrigation (50mm) at 40-45 days after sowing would be better for rain-fed kharif sorghum in the selected location of the SAT regions. The yield gap between district average and simulated rain-fed potential is so wide at Akola, Anantpur, Bijapur and Kota compared with Coimbatore and Gwalior. If we bridge the yield gap, we can overcome the climate change impact. Integrated Genetic and Natural Resource Management (IGNRM) through watershed management would be an appropriate method to bridge the yield gap to sustain the sorghum yield and food security. Key words ,QIR&URS6LPXODWLRQ:DWHUVKHG$GDSWDWLRQ'U\PDWWHU Leaf area index, Maturity, India, SAT.
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Climate Change Impact Assessment Climate change scenarios ,PSDFW RI SURMHFWHG FOLPDWH FKDQJH VFHQDULRV ZDV DVVHVVHG E\ UXQQLQJ WKH UHJLRQDO YDOLGDWHG PRGHO IRU DQG 7KH IXQFWLRQV ZHUH IURP WKH RXWSXW RI WKH +DG&03$DVFHQDULRZKLFKKDVFRQWLQXRXVSRSXODWLRQULVHDORQJZLWK UHJLRQDOO\RULHQWHGHFRQRPLFGHYHORSPHQW3URMHFWHGWHPSHUDWXUHULVH GXULQJ WKH VRUJKXP JURZLQJ VHDVRQ LV JLYHQ LQ 7DEOH IRU GLIIHUHQW ORFDWLRQV3URMHFWHGUDLQIDOODOVRYDULHGLQDOOVL[UHJLRQVGXULQJkharif VHDVRQ 7DEOH ,PSDFWRIFKDQJLQJFOLPDWHRQVRUJKXPFURS\LHOGLQ $VFHQDULRZDVDVVHVVHG Table 2. Projected mean temperature rise (°C) and rainfall changes during sorghum growing season in A2a scenarios. 0D[WHPS & /RFDWLRQ
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Figure 1. Simulated per cent change in yields (CSH 16) in HadCM3 – A2a scenarios of climate change without and with adaptation.
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References Aggarwal PK. ,PSDFWRIFOLPDWHFKDQJHRQ,QGLDQDJULFXOWXUH ,PSDFWV DGDSWDWLRQDQGPLWLJDWLRQ,QG-$JULF6FL.78 Aggarwal PK, Kalra N, Chander S and Pathak H. D ,QIR&URS $ G\QDPLF VLPXODWLRQ PRGHO IRU WKH DVVHVVPHQW RI FURS \LHOGV ORVVHV GXH WR SHVWVDQGHQYLURQPHQWDOLPSDFWRIDJURHFRV\VWHPVLQWURSLFDOHQYLURQPHQWV ,3HUIRUPDQFHRIWKHPRGHO$JULFXOWXUDOV\VWHPV89 Aggarwal PK, Banerjee B, Daryaei MG, Bhatia A, Bala A, Rani S, Chander S, Pathak H DQG Kalra N. E,QIR&URS $G\QDPLFVLPXODWLRQPRGHOIRU WKHDVVHVVPHQWRIFURS\LHOGVORVVHVGXHWRSHVWVDQGHQYLURQPHQWDOLPSDFW RIDJURHFRV\VWHPVLQWURSLFDOHQYLURQPHQWV,0RGHOGHVFULSWLRQ$JULFXOWXUDO V\VWHPV89 Dayakar Rao B. 6RUJKXP FXOWLYDWLRQ LQ ,QGLD 3DVW DQG )XWXUH ,Q 6RUJKXP,PSURYHPHQWLQWKHQHZPLOOHQQLXPE\5HGG\%HOOXP965DPHVK 6$VKRN.XPDU$DQG*RZGD&// HGV ,QWHUQDWLRQDO&URS5HVHDUFK ,QVWLWXWHIRU6HPL$ULG7URSLFV,6%1 33 Easterling WE, Aggarwal PK, Batima P, Brander, KM, Erda L, Howden SM, Kirilenko A, Morton J, Soussana JF, Schmidhuber J, DQG Tubiello FN. )RRG )LEUH DQG )RUHVW 3URGXFWV &OLPDWH &KDQJH In: ,PSDFWV $GDSWDWLRQDQGYXOQHUDELOLW\&RQWULEXWLRQRI:RUNLQJ*URXS,,WRWKH)RXUWKH $VVHVVPHQW5HSRUWRIWKH,QWHU*RYHUQPHQWDO3DQHORQ&OLPDWH&KDQJHSS Gangadhar Rao D, Katyal J C, Sinha S K and Srinivas K. ,PSDFWVRI FOLPDWH&KDQJHRQVRUJKXPSURGXFWLYLW\LQ,QGLD 6LPXODWLRQVWXG\$PHULFDQ 6RFLHW\RI$JURQRP\66HJRH5G0DGLVRQ:,86$&OLPDWH &KDQJH DQG $JULFXOWXUH $QDO\VLV RI 3RWHQWLDO ,QWHUQDWLRQDO ,PSDFWV $6$ 6SDFLDO3XEO1R SS± IPCC. &OLPDWHFKDQJHLPSDFWVDGDSWDWLRQDQGYXOQHUDELOLW\WHFKQLFDO VXPPDU\ RI :RUNLQJ *URXS ,, WR )RXUWK $VVHVVPHQW 5HSRUW RI ,QWHU JRYHUQPHQWDO 3DQHO RQ &OLPDWH &KDQJH 3DUU\ 0/ &DQ]LDQL 2) 3DXOWLNRI -3 YDQ GHU /LQGHQ 3- DQG +DQRQ &( HGV &DPEULGJH 8QLYHUVLW\ 3UHVV &DPEULGJH8.SS
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[email protected]
ICRISAT-Liaison Of¿ce CG Centers Block NASC Complex Dev Prakash Shastri Marg New Delhi 110 012, India Tel +91 11 32472306 to 08 Fax +91 11 25841294
ICRISAT-Nairobi (Regional hub ESA) PO Box 39063, Nairobi, Kenya Tel +254 20 7224550 Fax +254 20 7224001
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ICRISAT-Niamey (Regional hub WCA) BP 12404, Niamey, Niger (Via Paris) Tel +227 20722529, 20722725 Fax +227 20734329
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ICRISAT-Bamako BP 320 Bamako, Mali Tel +223 20 223375 Fax +223 20 228683
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ICRISAT-Bulawayo Matopos Research Station PO Box 776, Bulawayo, Zimbabwe Tel +263 383 311 to 15 Fax +263 383 307
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ICRISAT-Lilongwe Chitedze Agricultural Research Station PO Box 1096 Lilongwe, Malawi Tel +265 1 707297, 071, 067, 057 Fax +265 1 707298
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ICRISAT-Maputo c/o IIAM, Av. das FPLM No 2698 Caixa Postal 1906 Maputo, Mozambique Tel +258 21 461657 Fax +258 21 461581
[email protected]
www.icrisat.org ISBN: 978-92-9066-540-3
CPE 169
241-2011
