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In this article, a part of Wadi Al-Sahba, Saudi Arabia, is tested for revealing and modelling potential area of groundwater using integrated data derived from remote-sensing, geology and hydrology through GIS-based analytical hierarchy process method. Nine thematic maps e.g. geology, stream-networks, topography, slope, lineaments, depressions, radar intensity, rainfall and land use/cover that control the occurrence of groundwater were weighted and combined to quantify the potential area of groundwater resources. The output prospection map revealed five predicting zones of groundwater (GPZs) are very low (11.55%), low (28.18%), moderate (29.14%), high (22.41%) and very high (8.73%). The most predicted areas are covering wide part of Al Kharj and downstream of Wadi Al-Sahba. Information derived from well data (# 59), thermal sensor and interferometric SAR coherence change detection data are validated the prospective map. Overall, integration of remote sensing data has the capability for revealing and predicting potential areas of groundwater resources.

Revealing potential areas of water resources using integrated remote-sensing data and GIS-based analytical hierarchy process