Real-time reservoir operation for water supply considering middle-range operational ensemble forecasts of precipitation in Japan

Abstract:

Ensemble hydro-meteorological predictions are considered to be useful for robust reservoir operation as they include multiple possible hydrological scenarios in the target river basin in the future as well as dispersion of the scenarios, which provides information on uncertainty contained in the prediction. Although operational ensemble hydro-meteorological predictions have been available in many regions, they have not yet been widely used in the actual reservoir management due to difficulty in the handling such complex information. To facilitate effective utilization of ensemble hydro-meteorological predictions in the reservoir management, a real-time reservoir operation method for water supply was developed considering operational ensemble forecasts of precipitation in Japan. One-week and one-month ensemble predictions of precipitation (EPPs) provided by Japan Meteorological Agency with respectively 51 and 50 ensemble members were employed here. In the method, an ensemble prediction of daily precipitation in the target river basin was firstly estimated for the coming one month from forecasted EPPs at grid point around the target river basin by using a multivariable regression model. An ensemble streamflow prediction was then estimated by use of Hydro-BEAM, a distributed rainfall-runoff model. Reservoir operation for drought management was then optimized considering the streamflow prediction for the coming one month by using stochastic dynamic programming techniques to consider stochastic nature of ensemble streamflow prediction. Water release was finally conducted according to the optimized operation strategy, updating EPPs and ensemble streamflow prediction in real time. The proposed method was applied to water supply operation of Sameura Reservoir in the Yoshino River basin in Japan, demonstrating improvement in its operation when considering both one-week and one-month ensemble forecasts of precipitation.