Abstract

Water resources become more and more threatened by the increasing request related to the population growth, especially in agricultural regions. This article focused on the design of a geo-model monitoring network controlling groundwater quality in the fast-growing agricultural area of Souassi, Central eastern Tunisia. The studied area is known for its dry climate conditions and information scarcity while they are most needed. In this case, the integrated approach based on the Exploratory Factor Analysis coupled to the Confirmatory Factors Analysis and geostatistics were performed in order to detect the most relevant factors intervening in the groundwater quality and their spatial variability in the shallow aquifer of Souassi. This investigation is based on data set of nine parameters (EC, Ca, Mg, Na, K, HCO3, SO4, Cl and NO3) determined in 30 samples from wells tapping the shallow aquifer of Souassi. The PCA results allowed illustrating that the groundwater quality in Souassi shallow aquifer is affected by both natural and anthropogenic factors. Developing the SEM led to identifying the most meaningful factors controlling the water mineralization. The geospatial interpolation using kriging technique enabled us to locate areas with high salinity values corresponding to the natural discharge zone of the aquifer as well as areas with high rate of nitrate coinciding essentially with olive fields in the central zone. Under limited database, the results allow highlighting the risk zones in the aquifer. This could assist in establishing sustainable agricultural activities while helping to solve environmental degradation of water resources in the study area.

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