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The Krishna river delta is one of the most fertile regions in the country and it is the source of irrigation in the states of Maharashtra, Karnataka, Telangana and Andhra Pradesh. The basin receives abundant rainfall during South West Indian Summer Monsoon, often causes severe flooding. An early warning system for flood prediction helps to prevent such disasters. It has a number of regulating structures for storage and management of floods; however, an efficient flood forecasting model is important for the operation of regulating structures. The present study is an attempt to develop a flood forecast model for 180 km reach of Krishna River from P.D. Jurala Dam to Srisailam Dam and the tributary Tungabhadra River for reach of 250 km till Tungabhadra Dam. The performance of the simulated model is assessed using MIKE 11 and results are found to be satisfactory. The average correlation coefficient and Nash–Sutcliffe model efficiency coefficient (NSE) for the Mantralayam station during the validation period for the water level parameter are found to be 0.88 and 0.85, respectively, and for the Srisailam station, the inflow parameter values are 0.94 and 0.93, respectively. The estimated water levels and flows appeared to be realistic, thus indicating a satisfactory model performance. The present work aims to develop a flood warning model for community preparedness against occurrence of extreme events such as floods. This, in turn, increases the understanding of risks and appropriate flood responses.

Intricate flood flow advancement modelling in the krishna river sub basin, India