Thème : Use of Artificial Neural Networks for Modeling TDS in Groundwater in The Berrahal Region-Annaba (NE Alegria)
Présentation : In this research, we created a model for predicting total dissolved solids variables in groundwater wells as a function of groundwater quality status variables in the Berrahal region, such as temperature (T), pH, electrical conductivity (EC), sodium (Na+), potassium (K+), bicarbonates (HCO3-), sulphates (SO42-), and copper (Cu2+). Artificial neural networks were used to approximate the relationship between these different variables. The performance of two artificial networks were evaluated to determine which would be most effective in predicting total dissolved solids (TDS) concentrations in groundwater wells in the Berrahal region, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks. Prediction results show that the neural network approach has good and wide applicability for modelling TDS in groundwater wells in the Berrahal region.
Thème : Multi-tracer approach to understand nitrate contamination and groundwater-surface water interactions in the Mediterranean coastal area of Guerbes-Senhadja, Algeria
Présentation : https://doi.org/10.1016/j.jconhyd.2022.104098
Thème : Impact des rejets urbains et industriels sur la qualité des eaux de la plaine de la Meboudja (Algérie)
Présentation : To cite this article: Nabil Bougherira, Azzedine Hani, Fayçal Toumi, Nadjib Haied & Larbi Djabri (2017) Impact des rejets urbains et industriels sur la qualité des eaux de la plaine de la Meboudja (Algérie), Hydrological Sciences Journal, 62:8, 1290-1300, DOI: 10.1080/02626667.2015.1052451 To link to this article: https://doi.org/10.1080/02626667.2015.1052451