Hydrological multi-model forecast based on Bayesian Theory
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Abstract:
Hydrological forecast is very important for flood control, drought resistance and water resources regulation. It is usually based on model simulation. Each hydrological model has its own characteristics and feasible basin. Multi-model hydrological forecast is one of the effective methods to reduce the forecasting uncertainty. This paper chose three commonly used hydrological models: time-variant gain hydrological model, Xin’anjiang model, and Sacramento model. The case study was on Feilaixia basin of Pearl River. The three hydrological models were used for independent simulation with the same input and initial value. Then, BMA and SMA were run on the three models’ results. The research results show that the BMA results are better than the results from single model simulation.
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