Long-Term Runoff Modeling Using Rainfall Forecasts with Application to the Igua‡u River Basin

被引:13
|
作者
Evsukoff, Alexandre Goncalves [1 ]
de Lima, Beatriz S. L. P. [1 ]
Ebecken, Nelson F. F. [1 ]
机构
[1] Univ Fed Rio de Janeiro, COPPE, BR-21941972 Rio De Janeiro, Brazil
关键词
Rainfall-runoff model; Catchments; Runoff; Recurrent fuzzy system; Data mining; NEURAL-NETWORKS; FUZZY; PREDICTION; FEEDFORWARD; SYSTEM;
D O I
10.1007/s11269-010-9736-3
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This work presents the development of a rainfall-runoff model for the Igua double dagger u River basin in southern Brazil. The model was developed to support the operation planning of hydroelectric power plants and is intended to predict the natural flow based on meteorological rain forecasts. A recurrent fuzzy system model was employed with parameters estimated by a genetic algorithm using observed rainfall as input. The model performs well using observed rainfall as input; however, its performance using predicted rainfall as input decays with the forecasting horizon, illustrating the effect of meteorological prediction errors. The prototype implementing the model has been used for dispatch planning by the Brazilian Electric System Operator.
引用
收藏
页码:963 / 985
页数:23
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