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PREDICTION AND MODELING OF THE RAINFALL-RUNOFF TRANSFORMATION OF A TYPICAL URBAN BASIN USING ANN AND GP 

Authors: Julian Dorado a;  Juan R. Rabu(N)tildeal a;  Alejandro Pazos a;  Daniel Rivero a;  Antonino Santos a; Jeroacutenimo Puertas b
Affiliations:   a University of A Coru(n)tildea, Department of Information and Communications Technologies, A Coru(n)tildea, Spain.
b University of A Coru(n)tildea, Department of Hydraulics Engineering, A Coru(n)tildea, Spain.
DOI: 10.1080/713827142
Publication Frequency: 10 issues per year
Published in: journal Applied Artificial Intelligence, Volume 17, Issue 4 April 2003 , pages 329 - 343
Formats available: PDF (English)
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Abstract

This paper proposes an application of Genetic Programming (GP) and Artificial Neural Networks (ANN) in hydrology, showing how these two techniques can work together to solve a problem, namely for modeling the effect of rain on the runoff flow in a typical urban basin. The ultimate goal of this research is to design a real-time alarm system to warn of floods or subsidence in various types of urban basins. Results look promising and appear to offer some improvement for analyzing river basin systems over stochastic methods such as unitary hydrographs.
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