title: WEPP and ANN models for simulating soil loss and runoff in a semi-arid Mediterranean region.
abstract: This paper presents the use of both the Water Erosion Prediction Project (WEPP) and the artificial neural network (ANN) for the prediction of runoff and soil loss in the central highland mountainous of the Palestinian territories. Analyses show that the soil erosion is highly dependent on both the rainfall depth and the rainfall event duration rather than on the rainfall intensity as mostly mentioned in the literature. The results obtained from the WEPP model for the soil loss and runoff disagree with the field data. The WEPP underestimates both the runoff and soil loss. Analyses conducted with the ANN agree well with the observation. In addition, the global network models developed using the data of all the land use type show a relatively unbiased estimation for both runoff and soil loss. The study showed that the ANN model could be used as a management tool for predicting runoff and soil loss.
authors.affiliation: Laboratoire de Génie Civil et géo-Environnement (LGCgE), Université des Sciences et Technologies de Lille, 59655, Villeneuve d'Ascq, France.
authors.forename: Issa
authors.initials: I
authors.lastname: Albaradeyia
authors.forename: Azzedine
authors.initials: A
authors.lastname: Hani
authors.forename: Isam
authors.initials: I
authors.lastname: Shahrour
mesh_terms: D003247:Conservation of Natural Resources / Q000379:methods*; D055593:Geological Phenomena; D007557:Israel; D015233:Models, Statistical; D016571:Neural Networks, Computer; D012987:Soil / Q000737:chemistry*
chemical_list: D012987:Soil