Open Access Open Access  Restricted Access Subscription or Fee Access

Groundwater Level Predicted in the Saïss Plain (Northern Morocco) using Artificial Intelligence Techniques

Abdelhamid El ibrahimi, Abdennasser Baali


This study describes the application of artificial intelligence techniques and Wavelet-Artificial Neural Network (SWT) models for the prediction of groundwater levels. The coupling of discrete wavelets (SWT) method and artificial neural networks with perceptron multilayers (ANN-PMC) is proposed. The relative performance of the SWT-ANN-PMC model has been regularly compared to artificial neural network (ANN-PMC) and multiple linear regression (MLR) models. Precipitation, temperature and average groundwater level are the variables introduced to explain and validate the models, with a monthly time step for the period March 1980 to March 2014 at two sites in the Plain of Saïss. The results of the study indicate the potential of SWT-ANN-PMC models in the prediction of groundwater levels. It is recommended that further studies should explore this proposed methodology, which may in turn be used to facilitate the development and implementation of more effective strategies for the sustainable management of groundwater


artificial neural networks, ANN-PMC, SWT-ANN-PMC, groundwater level, MLR, the Plain of Saïss.

Full Text:


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.