Flood forecasting is a significant tool for river basin management and early flood warning systems. The aim of the present study was to develop annual time series flood forecasting models for River Jhelum in Kashmir Valley by the application of autoregressive integrated moving average (ARIMA) modelling approach. Annual peak flow at three principal flood monitoring sites of Jhelum, namely, Sangam, Ram Munshi Bagh and Asham were predicted using historical peak flow time series data. ARIMA models were developed for forecasting 1-year ahead floods. The prediction accuracy of the developed models was evaluated in terms of root mean square error (RMSE), the mean absolute error (MAE), the mean absolute percentage error (MAPE) and the Nash-Sutcliffe efficiency (NSE). RMSE values for Sangam, Ram Munshi Bagh and Asham stations were 112.31, 61.08 and 126.12 cumecs, respectively, and MAE values were 83.00, 48.50 and 104.25 cumecs at these stations. Also, the MAPE values were 10.70%, 6.19% and 10.78% for Sangam, Ram Munshi Bagh and Asham stations, respectively. NSE values for Sangam, Ram Munshi Bagh and Asham stations were 0.84, 0.87 and 0.85, respectively. Low values of RMSE, MAE and MAPE along with high values of NSE at all sites suggest the suitability of the developed models for flood forecasting in River Jhelum. The lead time of forecast obtained by this method was 1 year, which is much longer as compared to the conventional rainfall-runoff models.
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The authors are thankful to College of Agricultural Engineering and Technology, SKUAST-Kashmir, for providing all facilities to carry out the research. The authors also acknowledge the Planning and Design Division of Irrigation and Flood Control Department, Jammu and Kashmir, for providing discharge data of the Jhelum River.
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Parvaze, S., Khan, J.N., Kumar, R. et al. Temporal flood forecasting for trans-boundary Jhelum River of Greater Himalayas. Theor Appl Climatol (2021). https://doi.org/10.1007/s00704-021-03562-8