4.7 Article

Assessment of groundwater vulnerability and pollution risk using AVI, SPI, and RGPI indexes: applied to southern Gabes aquifer system, Tunisia

Journal

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-022-19309-5

Keywords

AVI; Vulnerability; Sensitivity; Aquifer; SPI; RGPI; South Gabes; Tunisia

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The Southern Gabes aquifer in southeastern Tunisia is a vital water source for various socio-economic sectors, but it is facing pollution risks due to excessive abstraction and human activities. This study assesses groundwater vulnerability and maps out the areas at risk. The results show a high pollution risk in the study area, highlighting the need for proactive measures to protect and sustainably develop the groundwater resources.
Southern Gabes aquifer is part of coastal Jeffara plain located in southeastern Tunisia. It consists a semi-arid area in which groundwater is the main source to water supply for several socio-economic sectors. Southern Gabes aquifer suffers from excessive abstraction and heavy anthropogenic pressures that make local groundwater resources threatened by pollution risks. This study aims to assess groundwater vulnerability, evaluate, and delineate groundwater risk regions. For this, a 17 water samples were carried out in the study area and chemical compositions were analyzed. A well-known AVI model has been used to assess aquifer vulnerability and new algorithms of sensitivity to pollution index (PSI) and risk groundwater to pollution index (RGPI) were implemented and used to assess, classify, and map groundwater pollution risk. Results reveal that study area suffers from high risk. Forty one percent of the total surface of study area has a very high risk. Nonetheless, only 30% of study area has a low to insignificant risk to pollution which necessitates taking severe precautions to protect the southern Gabes aquifer system. The method used in this study seems giving more precise results compared to conventional approaches. Moreover, this method allows assessing the pollution risk with flexible and reliable algorithm even with limited dataset. Hence, the poor natural protective capacity of study area needs a rapid intervention by local authorities in order to develop proactive solutions to protect and preserve groundwater resources from pollution risks and establish a long-term program for groundwater resources sustainable development.

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