Groundwater Quality Index Mapping for Irrigation Purposes in the El Hezma‐El Hmila Aquifer (Medenine, Tunisia)

• Published in: Clean : soil, air, water Vol. 50; no. 9
• Main Authors: Ben Brahim, Fatma, Msaddki, Hadhom, Bouri, Salem
• Format: Journal Article
• Language: English
• Published: Weinheim Wiley Subscription Services, Inc 01.09.2022
• Subjects: Aquifers; Boolean algebra; Boolean logic model; Data analysis; Decision analysis; El Hezma‐El Hmila‐Tunisia; Geographic information systems; Geographical information systems; Geology; Groundwater; Groundwater quality; hydrochemistry; Hydrogeology; Information systems; Irrigation; Irrigation water; IWQI; Remote sensing; Soil water; specific ionic‐toxicity; Surveys; Water quality; Water quality assessments; Tunisia
• ISSN: 1863-0650; 1863-0669
• DOI: 10.1002/clen.202100203

In the El Hezma‐El Hmila region (Southeastern Tunisia), the Mio‐Plio‐quaternary aquifer is subject to excessive extraction of groundwater, leading to drops in potentiometric surfaces and a subsequent degradation of groundwater quality. Therefore, surveys have been conducted to provide some basic information on groundwater suitability. The assessment of the water quality for agricultural purposes is the principal aim of this study. To achieve this objective, an integrated approach to processing hydrogeological and geochemical data is used. The analytical physicochemical data from wells in the study area are processed with the geographic information system (GIS) using a multi‐criteria decision analysis (MCDA), simulationsgraphics, and an irrigation water quality index (IWQI). The two obtained IWQI maps based on GIS‐MCDA show different quality classes. In fact, using the weighted linear combination (WLC), only two classes (medium and low suitability with 11.5 and 88.5% of the study area, respectively) are displayed, whereas the Boolean logic model reveals four classes (good, permissible, doubtful, and unsuitable) for irrigation purposes. In this regard, the obtained results areconsidered an appropriate tool for agricultural planning as well as a guide for decision makers to identify areas where irrigation can be suitable without affecting both soil and water quality. Multi‐influence hazards are combined in a GIS environment to generate an index value andestimate irrigation water quality index (IWQI) classes through two numerical multi‐criteria decision models. Groundwater suitability maps obtained via Boolean logic integration show higher confidence levels and greater flexibility in the spatial distribution of water quality classes than the weighted linear combination (WLC) method.