Bayesian Processor of Hydrologic Probabilistic Forecasting

摘要

Rational decision-making requires that the total uncertainty about hydrologic pre-dictand be quantified in terms of a probability distribution, conditional on all available information and knowledge. Hydrology knowledge is embodied in a deterministic catchment model. It was presented that a Bayesian Forecasting System (BFS) for producing a probabilistic forecast of a hydrologic predictand via any deterministic catchment model. The BFS decomposed the total uncertainty about hydrologic variates into input uncertainty and hydrologic uncertainty, which were quantified independently and then integrated into a predictive distribution. In the paper, the usual methods were presented for input uncertainty process and hydrologic uncertainty process, and the properties of the BFS were concluded. At last, the hot focuses on research of the BFS were discussed.