Evaluation of groundwater quality in intensive irrigated zone of Northeastern Tunisia
2020
Ibn Ali, Zouheira | Gharbi, Asma | Zairi, Moncef
Accurate and reliable prediction of groundwater quality is a critical component in water resources management and sustainable utilization. The multilayered Nadhour-Saouaf aquifer system in Northeastern Tunisia is intensively exploited. It is the main source of freshwater for domestic, agricultural, and industrial needs. The current study aims to identify groundwater and surface waters geochemistry and its suitability for irrigation and drinking purposes. A total of 31 groundwater samples and three surface water samples were collected and analyzed for the major elements, nitrates and physicochemical parameters. Hydrochemical facies are of mixed Ca–Mg–Cl and Na–Cl types for water of the Oligocene reservoir level and of a mixed Ca–Mg–Cl facies type for the Miocene and Plio-Quaternary waters. The water suitability for drinking purpose was evaluated based on World Health Organization, Tunisian standards guidelines and Drinking Water Quality Index (DWQI). The evaluation showed considerable deterioration in groundwater quality at some location. A large proportion (68%) of samples is unsuitable for drinking purpose based on WHO guidelines. The waters sampled from the dams are not directly useful for drinking and need specific treatment. However, DWQI results show that “Good water’’ class dominates in the study area. The suitability of groundwater for irrigation was evaluated based on the irrigation quality parameters such as sodium absorption ratio, sodium proportion, Permeability Index, Kelly's ratio, Magnesium hazard and Irrigation Water Quality Index (IWQI). Groundwater samples classified, based on previously parameters, reveal that 42% are unsafe for irrigation. Subsequently, multiple linear regression is used for DWQI and IWQI simulation. The model results showed a great correspondence between distribution maps of estimated and measured DWQI and IWQI. Hence, the developed models provide a simpler and easy alternative to other methods used for suitability estimation and prediction.
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