A multi-model approach for long-term runoff modeling using rainfall forecasts

Authors:
Alexandre G. Evsukoff;Marcio Cataldi;Beatriz S. L. P. de Lima
Affiliations:
COPPE/Federal University of Rio de Janeiro, P.O. Box 68506, 21941-972 Rio de Janeiro, RJ, Brazil;Universidade Federal Fluminense, Departamento de Engenharia, Agrícola e do Meio Ambiente, Niterói, RJ, Brazil and Operador Nacional do Sistema Elétrico, ONS, Rio de Janeiro, RJ, Bra ...;COPPE/Federal University of Rio de Janeiro, P.O. Box 68506, 21941-972 Rio de Janeiro, RJ, Brazil
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

This work presents the development of a rainfall-runoff model for the Iguacu River basin in the south of Brazil. The model was developed to support the operational planning of hydroelectric power plants and is intended to compute natural flow predictions based on meteorological rain forecasts. A recurrent fuzzy system model was employed, with parameters estimated by a genetic algorithm using observed rainfall as input. This work presents the recurrent fuzzy model within a multi-model approach, where the input data are furnished as an envelope, resulting in a prediction envelope that has demonstrated the ability to produce robust results.