No abstract

Salinization is an environmental issue that affects different regions worldwide. Geochemical approaches and statistical tools are combined to investigate the origin and process of groundwater salinization in Menzel Habib shallow aquifer. The inland aquifer from Menzel Habib area is in the northwest of Gabès, southeastern Tunisia. A total of twenty-five water samples were selected and collected in the study area. Physicochemical parameters (electrical conductivity, pH, total dissolved solids) were measured in situ, and major ions (Na, Mg, Ca, K, Cl, SO 4 , HCO 3 , F, and Br) were determined. The obtained results show a Na-Cl groundwater dominant facies (60%), Na-SO 4 (36%), and mixed water type (4%). Thus, a correlation between total dissolved solids and major ions shows the contribution of SO 4 , Cl, Na, Ca, and Mg in groundwater salinization. The salinization of groundwater is due to the dissolution of Triassic evaporites, which are related to the tectonic context of the region, and to the cationic exchange. Furthermore, statistical approaches, especially principal component analysis, reveal that the high groundwater mineralization is due to the evaporite dissolution. Multiple linear regression leads to establish a model linking total dissolved solids to the different chemical elements involved in groundwater salinization.Keyword Salinization . Groundwater . Geochemical approaches . Principal component analysis . Multiple linear regression .

Groundwater is an important source for irrigation uses in many arid and semi-arid regions such as Menzel Habib area. In this work, the groundwater quality for irrigation water was investigated based on conventional indices notably Electrical Conductivity (EC), Sodium Absorption Ratio (SAR), Soluble Sodium Percentage (SSP), Magnesium Adsorption ratio (MAR), Kelly Ratio (KR) and Permeability index (PI). The water quality for irrigation was also evaluated by Simsek method. However, a proposal fuzzy logic model has been developed to avoid uncertainties associated to the classical methods. The results obtained on thirty-six groundwater samples, indicated that 3% of these samples are classified as “good” for irrigation, 3% are “good to permissible”, 33% “permissible”, 36% “permissible to unsuitable” and 25% with an “unsuitable” quality. The application of fuzzy logic approaches has more reliable results with the definition of seven classes to evaluate the groundwater quality for agricultural irrigation.