Mapping Groundwater Potential (GWP) in the Al-Ahsa Oasis, Eastern Saudi Arabia Using Data-Driven GIS Techniques

Author:

Hassaballa Abdalhaleem12,Salih Abdelrahim3ORCID

Affiliation:

1. Department of Natural Resources, Faculty of Agriculture, King Faisal University, Al-Ahsa P.O. Box 420, Saudi Arabia

2. Agricultural and Biological Engineering Department, Faculty of Engineering, University of Khartoum, Khartoum 11111, Sudan

3. Department of Geography, Faculty of Arts, King Faisal University, Al-Ahsa P.O. Box 420, Saudi Arabia

Abstract

Searching for new sources of water is becoming one of the most important aspects of scientific research, especially in areas prone to drought, like Saudi Arabia. The study aim was to delineate groundwater potential zones within the Oasis of Al-Ahsa, in Saudi Arabia’s eastern region, and to identify the optimum factors that control the availability of groundwater zones. This was achieved through examining the effect of ten environmental variables on groundwater recharge, namely: slope, topographic wetness index (TWI), land cover (LC), elevation, lineament density (Ld), drainage density (Dd), rainfall, geology, and soil texture. The variables were prepared from a variety of data sources, including spatial data (i.e., DEM and Landsat-8 image), in addition to other complementing data sources for appropriate parameters extraction. Two weighted overlay methods were used, namely the simple additive weight (SAW) as well as the optimum index factor (OIF) in order to categorize the optimal set of parameters for computing GWP and identifying its zones. Two GWP maps were obtained and validated through comparison with the locations of existing wells at GWP zones. The study findings have assured the cogency of the SAW map, where it was found that nearly 45–48% of the resultant zones were characterized as in the “moderate” class, whereas around 21–37% of the entire zones area were classified within the “high” class. The soil texture parameter was determined as being the most influencing parameter for GWP mapping followed by the “geology” parameter; however, the “lineament density” (Ld) was the least important factor. Furthermore, the OIF method has facilitated the identification of the optimal parameter combination for delineating groundwater potential (GWP) zones, which included “Ld”, “land cover”, and “TWI”. The study findings and methodology can serve as a potential model for other similar regions, supporting sustainable water resource management locally as well as globally.

Funder

Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia

Publisher

MDPI AG

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