Bayesian system for probabilistic river stage forecasting

被引:136
作者
Krzysztofowicz, R
机构
[1] Univ Virginia, Dept Syst Engn, Charlottesville, VA 22904 USA
[2] Univ Virginia, Dept Stat, Charlottesville, VA 22904 USA
基金
美国海洋和大气管理局;
关键词
Bayesian analysis; stochastic processes; statistical analysis; probability; rivers; floods;
D O I
10.1016/S0022-1694(02)00106-3
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The purpose of this analytic-numerical Bayesian forecasting system (BFS) is to produce a short-term probabilistic river stage forecast based on a probabilistic quantitative precipitation forecast as an input and a deterministic hydrologic model (of any complexity) as a means of simulating the response of a headwater basin to precipitation. The BFS has three structural components: the precipitation uncertainty processor, the hydrologic uncertainty processor, and the integrator. A series of articles described the Bayesian forecasting theory and detailed each component of this particular BFS. This article presents a synthesis: the total system, operational expressions, estimation procedures, numerical algorithms, a complete example, and all design requirements, modeling assumptions, and operational attributes. (C) 2002 Elsevier Science B.V. All rights reserved.
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页码:16 / 40
页数:25
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