Delineation of groundwater potential zones in KwaZulu-Natal, South Africa using remote sensing, GIS and AHP. (September 2022)

• Record Type: Journal Article
• Authors: Moodley, Tyrone; Seyam, Mohammed; Abunama, Taher; Bux, Faizal
• Is Part Of: Journal of African earth sciences. Volume 193(2022)
• Publication Date: 2022-09
• Subjects: Groundwater potential -- AHP -- Remote sensing -- Thematic layers -- GIS -- Weighted overlay -- South Africa -- KwaZulu-Natal province; Earth sciences -- Africa -- Periodicals; Earth sciences -- Middle East -- Periodicals; Geology -- Africa -- Periodicals; Geology -- Middle East -- Periodicals; Sciences de la terre -- Afrique -- Périodiques; Sciences de la terre -- Moyen-Orient -- Périodiques; Géologie -- Afrique -- Périodiques; Géologie -- Moyen-Orient -- Périodiques; Earth sciences; Geology; Africa; Middle East; Periodicals; Electronic journals; 556.05
• DOI: 10.1016/j.jafrearsci.2022.104571
• Languages: English
• ISSNs: 1464-343X

Abstract

Abstract: The present study aimed to spatially identify groundwater potential (GWP) zones in KwaZulu-Natal (KZN), South Africa (SA) using Geographic Information Systems (GIS) and remote sensing-based multi-criteria analysis. This study is the first to utilise these tools in delineating groundwater in KZN, which is a process dominated by outdated, expensive, and time-consuming in-situ methods. Remote sensing images were used instead of traditional data sampling, which provided a cheaper, faster, and sufficient way of acquiring specific information in data-scarce KZN. Remotely sensed spatial thematic layers viz. geology, lineament density, slope, drainage density, rainfall, land use/land cover, and evapotranspiration were processed and developed using GIS and weighted using the Analytical Hierarchy Process (AHP). The thematic layers were subsequently aggregated using the GIS Weighted Overlay Method to develop a groundwater potential index map. Indices from the map were correlated with 113 borehole logs using the Receiver Operating Characteristic Curve (ROC) and Area Under the Curve (AUC) to validate the results. The resultant GWP map computed that approximately 47.3 Km 2 (2%) of the total area falls under Excellent GWP, 24405.4 Km 2 (27.45%) under good GWP, 50950.5 Km 2 (57.3%) under moderate GWP, and the poor and very poor GWP zones constitute around 13380.8 Km 2 (15.1%) and 135.6 Km 2 (1%) of KZN. The spatial mapping revealed that the AHP-based GWP map exhibited a very good correlation with borehole data (AUC = 72.6%, n = 113), indicating the accuracy of the AHP as a rating method. The use of freely available remote sensing data and modeling techniques provided a relatively inexpensive groundwater identification method that can successfully replace the rudimentary methods. Highlights: First study to spatially locate groundwater in South Africa using remote sensing. Step by step remote sensing image processing. Cost effective groundwater exploration in a data scare region.