COMPARATIVE ANALYSIS OF EROSION MODELING TECHNIQUES IN A BASIN OF VENEZUELA <a href="http://dx.doi.org/10.4090/juee.2010.v4n2.081104">(doi: 10.4090/juee.2010.v4n2.081104)</a>

Abstract

This paper investigates a comparative analysis of erosion modeling techniques based on deterministic models, both empirically based and process-based models. The empirical modeling is based on statistical and artificial intelligence techniques. In the first, two types of statistical regression model structures are investigated, a linear multiple regression model structure and a nonlinear multiple regression model structure. In the second, tools such as artificial neural networks and fuzzy inference system are used. The physical process-based modeling involves the calibration, validation and testing of the models components: WEPP, DWEPP, EUROSEM and CIHAM-UC. The input and output variables of models were collected during rainy and dry ( irrigation) seasons in Chirgua River Basin, Venezuela for two years (2008-2009). 97 rainfall storms and 300 irrigation events were measured. Satisfactory fit was found in the techniques investigated, R² close to 0.7.