What is Necessary to Forecast River Flows Reliably?

by Carlos E. Puente, Univ of California, United States,

Document Type: Proceeding Paper

Part of: Computerized Decision Support Systems for Water Managers


The problem of forecasting river flows employing conceptual rainfall-runoff models is reviewed stressing the important connections that exist among data requirements, model structure, and forecasting methodology. A stochastic filtering framework is used to study the relative importance of the above properties in real world case studies. In particular, the following scenarios and their effects on runoff forecasting are investigated: (a) under and over prediction of rainfall; (b) inclusion or exclusion of a soil moisture accounting component; (c) minimum runoff absolute residuals vs. maximum likelihood as estimating criteria for filter and model parameters; and (d) linear vs. nonlinear channel routing.

Subject Headings: Forecasting | Streamflow | River flow | Rainfall-runoff relationships | Mathematical models | Hydrologic models | Filters | Case studies

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