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ABSTRACT
Rainfall is the main source of water in India. Management of water and utilisation for various purposes is based upon its availability. Rainfall is the main component of any hydrological process and a key input factor for any rainfall-runoff model. Rainfall forecasting plays a major role to forecast the floods in advance with sufficient lead time. The accuracy of simulation of flow depends on the precision of rainfall data. Grey theory is widely used for forecasting in the field of hydrology. Grey model better handles the random and insufficient data. Adaptive grey model is an advancement of grey model where the trend of data set is considered. As rainfall is highly random, accurate and realistic forecasts are made with the knowledge of trends and patterns of the measured data. Hence, the adaptive grey model is used in this study to forecast the rainfall using previously measured rainfall. The model is applied to 15 storm events of Peechara watershed, Telangana, India. Both the individual and cumulative rainfall is considered in forecasting and the results showed the models’ performance better by considering cumulative rainfall. The performance of the model is tested using Nash–Sutcliffe Efficiency (E), Root Mean Square Error (RMSE) and Correlation Coefficient (CC). It is observed that E >0.85, RMSE <0.2 and CC >0.9 for all the events in the watershed. The results obtained from this research work are quite significant and very much useful for flow forecasting in the watersheds.
Acknowledgements
Authors are thankful to the DST-WTI, India for the financial assistance to carryout this work through project no. DST/TM/WTI/2K12/47(G).
Disclosure statement
No potential conflict of interest was reported by the authors.