Streamflow Forecasting for Han River Basin, Korea

Abstract

A multisite river‐flow forecasting model is presented in this work for the Han River Basin, Korea. Seventeen locations on the Han River are simultaneously considered for real‐time flow forecasting. A linear stochastic model based on the ARMAX class of models is developed for each forecasting location, and the Kalman filter is used to forecast and update optimal estimates of the flows. Two other filters are used to update the model parameters and noise statistics in real time. The structure of the models, in flexible black‐box forms, provide for several exogenous inputs, including precipitation, antecedent soil moisture effect, natural inflows from upstream subcatchments, and controlled releases from reservoirs. This work extends the real‐time forecasting models introduced by Awwad and Valdés in 1992 to include meteorological terms essential to carrying out multiple‐step‐ahead hydrologic forecasting. It introduces the rainfall‐runoff process as part of an adaptive stochastic model, with the catchment's response coefficients updated on‐line as information becomes available. The software developed for this application is part of and compatible with a comprehensive model being developed by the U.S. Army Corps of Engineers and the Han River Flood Control Center for the Han River Basin.