Baipenzhu Reservoir Inflow Flood Forecasting Based on a Distributed Hydrological Model

For reservoir basins, complex underlying surface conditions, short flood confluence times, and concentrated water volumes make inflow forecasting difficult cause forecast accuracies to be low. Conventional models can no longer meet the required accuracy values for control operations. To give full play role of reservoirs in maximize use resources, high-precision is urgently needed as a support mechanism. In this study, Baipenzhu Reservoir Guangdong Province was selected study case, an scheme designed by physically based distributed hydrological model, Liuxihe model. The results show that model has strong applicability studied basin simulation are very accurate. This also found different Digital Elevation Model (DEM) data sources certain impact on structure but constructed both simulate process well. At same time, reflect spatial variation rainfall well, using Particle swarm optimization (PSO) algorithm optimize initial parameters greatly reduce uncertainty forecasts. According China’s information standards, schemes two rated Grade A used real-time basin.