Delineation of groundwater potential (GWP) in the northern United Arab Emirates and Oman using geospatial technologies in conjunction with Simple Additive Weight (SAW), Analytical Hierarchy Process (AHP), and Probabilistic Frequency Ratio (PFR) techniques

William Abrams, Eman Ghoneim, Roger Shew, Todd LaMaskin, Khalid Al-Bloushi, Saber Hussein, Mostafa AbuBakr, Esam Al-Mulla, Meshgan Al-Awar, Farouk El-Baz

Research output: Contribution to journalArticlepeer-review

34 Citations (Scopus)

Abstract

In the United Arab Emirates (UAE) and Oman, an arid climate coupled with rising populations have placed increased demand on scarce water resources. This study performs groundwater prospecting in the northern UAE and Oman by delineating Groundwater Potential (GWP), the relative likelihood of a location to accumulate groundwater, by modelling the influence of physiographic variables affecting groundwater accumulation. Remote sensing data from ASTER, Landsat-8, Shuttle Radar Topography Mission (SRTM), and Tropical Rainfall Measuring Mission (TRMM) were used to map relevant physiographic variables including elevation, slope, curvature, drainage density, Topographic Wetness Index, lithology/land cover, lineament density, rainfall, and groundwater-induced cool thermal anomaly frequency (GW CTA). Three different techniques were used for the GWP model including Simple Additive Weight (SAW), Probabilistic Frequency Ratios (PFR), and the Analytical Hierarchy Process (AHP). The three derived GWP maps were assessed through validation by comparing the locations of 645 water wells, 49 natural springs, and field observations of groundwater features to GWP zones. The SAW and AHP maps were deemed valid with agreement to moderate or greater potential zones for wells at 98% and 92% and springs at 63% and 86% respectively, and all field observation locations for both maps. Based on the SAW and AHP maps, the highest GWP is located in the Dubai/Sharjah emirates due to optimal runoff accumulation, infiltration conditions, and subsurface storage capacity. Findings of this study demonstrate integration of remote sensing data with the adopted geospatial techniques is a practical method of groundwater prospecting in similarly data scarce, arid environments.

Original languageEnglish
Pages (from-to)77-96
Number of pages20
JournalJournal of Arid Environments
Volume157
DOIs
Publication statusPublished - Oct 2018

Keywords

  • ASTER
  • Cool thermal anomaly
  • GIS
  • Geohydrology
  • Hydrology
  • MODIS
  • remote sensing

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecology
  • Earth-Surface Processes

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