Title of article :
Bayesian system for probabilistic river stage forecasting
Author/Authors :
Roman Krzysztofowicz، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2002
Abstract :
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.
Keywords :
Stochastic processes , Bayesian analysis , Statistical analysis , probability , Floods , Rivers
Journal title :
Journal of Hydrology
Journal title :
Journal of Hydrology