4.7 Article

Bayesian system for probabilistic river stage forecasting

期刊

JOURNAL OF HYDROLOGY
卷 268, 期 1-4, 页码 16-40

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ELSEVIER
DOI: 10.1016/S0022-1694(02)00106-3

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Bayesian analysis; stochastic processes; statistical analysis; probability; rivers; floods

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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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