Implementation of Real-Time Flood Prediction and its Application to Dam Operations by Data Integration Analysis System

Abstract

Despite recent advances in hydrological models and observation technology, the prediction of floods using advanced models and data has not yet been fully implemented for practical use. The major issues in prediction originate from the underlying uncertainty of the initial conditions of the basin and the accuracy of the precipitation forecast. Effective transmission of flood information to corresponding authorities is also necessary when considering countermeasures against an oncoming flood. We present in this article a data archive and model integrated system to overcome these issues. The system realizes flood forecasting by employing a land surface model coupled with hydrological model and an ensemble precipitation forecast model to address the accuracy of initial conditions and precipitation. While the Water and Energy Budget Based Distributed Hydrological Model (WEB-DHM) rigorously estimates the physical state of the basin, the ensemble precipitation forecast model analyzes historical errors in forecasts and returns precipitation ensembles reflecting the uncertainty in the forecast specifically regarding the target basin. A combination of these models yields an ensemble of streamflow forecasts. We further develop a virtual reservoir simulator to enhance the proactive use of forecast information to support decision-making by reservoir managers. These models are integrated into the Data Integration Analysis System (DIAS). The feasibility of the system for practical use is tested against data from recent typhoon events.