Improving water supply outlooks in Korea with ensemble streamflow prediction

Abstract

The purpose of this study is to propose an alternative forecasting approach for improving the current water supply outlook in Korea. Using a rainfall-runoff model, the existing technique for the water supply outlook in Korea produces monthly low, average, and high runoff forecasts. The proposed technique is called Ensemble Streamflow Prediction (ESP), and is currently implemented by the National Weather Service in the U.S.A. ESP appears particularly valid in Korea where the historical rainfall record is much more comprehensive than the historical streamflow record. This study applies ESP to runoff forecasting for a river basin in Korea to examine its applicability. An ensemble of one-month ahead runoff forecasts at the Gongju gauging station in the Keum River basin, Korea, was generated for each month. The resulting ESP forecasts were compared with the corresponding observed runoff data as well as the existing forecasts. Although this study is limited to one case study, the following conclusions can be made: (1) the ESP technique dominates the existing forecasting techniques in terms of both systematic and random errors; and (2) ESP is more accurate when high flows occur.