Author(s): Daisuke Nohara

Linked Author(s): Daisuke Nohara

Keywords: Reservoir operation; Preliminary release; Ensemble prediction; Flood management; Water use

Abstract: Changes in hydrological systems under changing climate may result in more frequent occurrence of extreme floods and droughts. The increase in extreme floods and droughts could threaten existing water resources management systems such as reservoir systems. More integrated operation of water resources systems is therefore needed to adequately deal with these extreme water-related disasters with existing systems. Considering the circumstances described above, this work investigated an optimal method for prior release operation of a multi-purpose reservoir considering operational medium-range ensemble hydrological forecast in order to enhance flood management capability of the reservoir without sacrificing its functions for water supply or power generation. In the proposed method, ensemble prediction of basin rainfall for the coming eight days is estimated from the grid point values of One-Week Ensemble Forecast of precipitation provided by Japan Meteorological Agency. Ensemble prediction of reservoir inflow for the coming eight days is then calculated by use of the Hydro-BEAM, a distributed rainfall-runoff model. The optimized timing and amount of prior release from the reservoir are determined with consideration of ensemble inflow prediction based on the accuracy analysis of ensemble hydrological prediction considered, maximizing the effect of prior release operation in management of large-scale floods while minimizing long-term impacts on water use by securing water recovery after the flood event as much as possible. A case study applied to the simplified Hiyoshi Reservoir, a multi-purpose reservoir located in the upper Katsura River in Japan, showed the potential effectiveness of prior release operation in flood management while impacts of prior release on water supply and power generation were not very significant in the simulation period.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022389

Year: 2022