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Abstract

Groundwater is a vital resource for domestic, agricultural, and industrial activities, as well as for ecosystem services. Despite this, the resource is under significant threat, due to increasing contamination from anthropogenic activities. Therefore, to ensure its reliability for present and future use, effective management of groundwater is important not only in terms of quantity (i.e. abstraction) but also quality. This can be achieved by identifying areas that are more vulnerable to contamination and by implementing protective measures. To identify the risk and delineate areas that are more exposed to pollution, various groundwater vulnerability assessment techniques have been developed across the globe. This paper presents an overview of some of the commonly used groundwater vulnerability assessment models in terms of their unique features and their application. Special emphasis is placed on statistical methods and overlay-index techniques. The assessment of the literature shows that statistical methods are limited in application to the assessment of groundwater vulnerability to pollution because they rely heavily on the availability of sufficient and quality data. However, in areas where extensive monitoring data are available, these methods estimate groundwater vulnerability more realistically in quantitative terms. Many works of research indicate that index-overlay methods are used extensively and frequently in groundwater vulnerability assessments. Due to the qualitative nature of these models, however, they are still subject to modification. This study offers an overview of a selection of relevant groundwater vulnerability assessment techniques under a specificset of hydro-climatic and hydrogeological conditions.
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Authors and Affiliations

Simeneh Shiferaw Moges
1
ORCID: ORCID
Megersa Olumana Dinka
1
ORCID: ORCID

  1. University of Johannesburg, Faculty of Engineering and the Built Environment, Department of Civil Engineering Sciences, PO Box 524, Auckland Park, 2006 Johannesburg, South Africa

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