Remote Sensing (Dec 2020)

Identification of Groundwater Potential Zones Using Remote Sensing and GIS Techniques: A Case Study of the Shatt Al-Arab Basin

  • Hadi Allafta,
  • Christian Opp,
  • Suman Patra

DOI
https://doi.org/10.3390/rs13010112
Journal volume & issue
Vol. 13, no. 1
p. 112

Abstract

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Rapid population growth has raised the groundwater resources demand for socio-economic development in the Shatt Al-Arab basin. The sustainable management of groundwater resources requires precise quantitative evaluation, which can be achieved by applying scientific principles and modern techniques. An integrated concept has been used in the current study to identify the groundwater potential zones (GWPZs) in the Shatt Al-Arab basin using remote sensing (RS), geographic information system (GIS), and analytic hierarchy process (AHP). For this purpose, nine groundwater occurrence and movement controlling parameters (i.e., lithology, rainfall, geomorphology, slope, drainage density, soil, land use/land cover, distance to river, and lineament density) were prepared and transformed into raster data using ArcGIS software. These nine parameters (thematic layers) were allocated weights proportional to their importance. Furthermore, the hierarchical ranking was conducted using a pairwise comparison matrix of the AHP in order to estimate the final normalized weights of these layers. We used the overlay weighted sum technique to integrate the layers for the creation of the GWPZs map of the study area. The map has been categorized into five zones (viz., very good, good, moderate, poor, and very poor) representing 4, 51, 35, 9, and 1% of the study area, respectively. Finally, for assessing the effectiveness of the model, the GWPZs map was validated using depth to groundwater data for 99 wells distributed over the basin. The validation results confirm that the applied approach provides significantly solid results that can help in perspective planning and sustainable utilization of the groundwater resources in this water-stressed region.

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