The use of Artificial Neural Networks in the modeling of socioeconomic category of Integrated Water Resources Management (Case study: Saf-Saf River Basin, North East of Algeria)

This research work has an objective to determine the effective variables in socioeconomic category of Integrated Water Resources Management for Saf-Saf river basin characterized by fast growing demand of urban and rural populations and the demand of economic sectors including industry and agriculture. In this paper, the artificial neural network models were used to model and predict the relationship between water resources mobilization and socioeconomic variables in the Saf-Saf river basin. The study area chosen is Saf-Saf river basin and real data were collected from 30 municipalities for reference year 2010. The results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the most effective variable on water resources mobilization and use. The model evaluation shows that the correlation coefficients are more than 94 % for training, verification, and testing data. The model aims to link the water resources mobilization and driving forces variables with the objective to strengthen the Integrated Water Resources Management approach.