• Jella Kiran Scientist SC, Telangana State Remote Sensing Applications Centre
  • P. Kesava Rao CGARD, NIRD&PR, Hyderabad
  • Balaji Narasimhan IIT Madras, Chennai



Climate Change, Water Resources, SWAT Model, Krishna Basin.


The Krishna, one of the longest rivers in southern India with a cultivable area, 77 per cent is experiencing steady changes in atmosphere with erratic rainfall, increased humidity and decreased temperatures. The prime objective is hydrological assessment of future monsoon and its uncertainties for sustainable crop production and irrigation water management practices in a changing climate. The impact of future climate change is assessed using calibrated and validated ArcSWAT modelling tool. The Basin on an average receives 800 mm rainfall in the monsoon period with least of 300mm in the south and a maximum of 2000mm in the west. The basin has surface water potential of 78.1 km3 and groundwater potential of 26.41 km3. The hydrological assessment of the basin based on the IPRC model shows that by midcentury there would be increase in flash floods with prolonged dry spells. The assessment on spatial and temporal distribution of water availability, precipitation, PET and soil water suggests the need for eco-friendly adaptation technologies along with a planned irrigation development to capture in abundance and supply in the deficient period, when the demand is more and a need for efficient crop model to understand and assist the flooding situation.


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How to Cite

Kiran, J., Rao, P. K., & Narasimhan, B. (2018). ASSESSMENT OF ANTICIPATED CLIMATE CHANGE IMPACT ON WATER RESOURCES IN KRISHNA BASIN. Journal of Rural Development, 37(2), 285–298.


Arnold JG, Srinivasan R, Muttiah RS, Williams Jr. (1998), Large area hydrologic modeling and assessment part I: model development, Journal of the American Water Resources Association, 34 (1): 73–89.

Arnold, J. G., and P. M. Allen. (1996), Estimating hydrologic budgets for three Illinois watersheds, Journal of Hydrology, 176(1 4): 57 77

Bhuiyan, S. I. (1992), Water management in relation to crop production: Case study on rice, Outlook on Agriculture, 21: 293-299.

Biggs, T. W.; Gaur, A.; Scott, C. A.; Thenkabail, P.; Rao, P. G.; Krishna, G. M.; Acharya, S.; Turral, H. (2007), Closing of the Krishna Basin: Irrigation, Streamflow Depletion and Macroscale Hydrology, IWMI Research Report 111.Colombo, Sri Lanka: International Water Management Institute.

Brouwer, C., K. Prins and M. Heibloem. (1989), Irrigation water management: Irrigation scheduling, Training Manual No.4., FAO, (Accessed on January 14, 2013).

Easterling, W. E., N.J. Rosenburg, M.S. McKenney, C. A. Jones, P. T. Dyke and J. R. Williams. (1992), Preparing the erosion productivity impact calculator (EPIC) model to simulate crop response to climate change and the direct effects of CO2. Agricultural and Forest Meteorology, 59: 17-34.

Gosain, A. K., Sandhya Rao, R. Srinivasan and N. Gopal Reddy (2005), Return-flow assessment for irrigation command in the Palleru river basin using SWAT model, Hydrological Processess, 19, pp 673-682

Monteith, J. L. (1965), Evaporation and environment. In Proc. The State and Movement of Water in Living Organisms, 19th Symposia of the Society of Experimental Biology, 205-234, Swansea, UK. Cambridge, UK, Cambridge University Press.

Neitsch, S. L., J. G. Arnold, J. R. Kiniry, and J. R. Williams. (2005), Soil and Water Assessment Tool theoretical documentation and User’s Manual, Version 2005: version 2005. USDA, Soil And Water Research Laboratory/ Blackland Research Center, Texas, USA.

Reddy,R. S., Shiva Prasad, C. R., and C. S. Harindranath (1996), “Soils of Andhra Pradesh for Optimising Land Useâ€, NBSS Publ. 69 (Soils of India Series 8), National Bureau of Soil Survey and Land Use Planning, Nagpur India, 94 pp. + 27 plates+six-sheet soil map (1:500,000 scale).

Savva, P. A., and K. Frenken. (2002), Crop water requirements and irrigation scheduling, Irrigation Manual – Module 4, FAO, Harare, 132pp.

Saxton, K. E., and W. J. Rawls. (2006), Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Social Science Society of American Journal, 70:1569–1578.

Srinivasan, R., Ramanarayanan, T.S., Arnold, J.G., Bednarz, S.T., (1998), Large area hydrologic modeling and assessment part II: model application, Journal of American Water Resources Association,34, 91- 101.

Teutschbein, C., and J. Seibert. (2012), Bias correction of regional climate model simulations for hydrological climate-change impact studies: Review and evaluation of different methods, Journal of Hydrology, 456457(16): 12-29.

Thenkabail, P.S., Biradar C.M., Noojipady, P., Dheeravath, V., Li, Y.J., Velpuri, M., Gumma, M., Reddy, G.P.O., Turral, H., Cai, X. L., Vithanage, J., Schull, M., and Dutta, R. 2009b. Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium, International Journal of Remote Sensing, 30(14): 3679-3733.July, 20, 2009.

Thatte, C.D., A.C. Gupta, and M.L. Baweja (2009), Water Resources Development in India, Indian National Committee on Irrigation and Drainage, New Delhi.

Van der Hoek,W.; R. Sakthivadivel; M. Renshaw; J. B. Silver; M. H. Birley; F. Konradsen. (2001), Alternate wet/dry irrigation in rice cultivation: A practical way to save water and control malaria and Japanese encephalitis? Research Report 47, Colombo, Sri Lanka, International Water Management Institute.