INTEGRATION OF GEOSPATIAL TECHNIQUES FOR MAPPING GROUNDWATER POTENTIALITIES IN EL-QAA PLAIN, SOUTHWEST SINAI, EGYPT

Groundwater represents the essential source of fresh water in most arid regions, such as the Sinai Peninsula. Exploration of groundwater resources in dry lands requires survey of vast areas with conventional land-based techniques. This study performs criteria for groundwater probabilities in the southwestern part of Sinai Peninsula by mapping Groundwater Potential (GWP) using advanced remote sensing and geospatial techniques along with field validation, as a complemented tool for the conventional land-based methods. The main goal of this work is delineating groundwater recharging by identifying and examining the influence of physiographic variables that affecting groundwater storage. Therefore, multi-sensors remote sensing data from ASTER, Landsat-8, MODIS, Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), and Radarsat-1 were used to construct several geospatial thematic layers (variables). These layers include elevation, slope, curvature, drainage density, topographic wetness index, surface roughness, frequency of thermal anomaly, accumulated precipitation, Land Use/Land Cover (LULC) and lineament density. All variables were arranged and weighted based on their contributions in groundwater recharge through infiltration and percolation processes of near surface aquifers. The Simple Additive Weight (SAW) method was adopted for computing the variables weights and producing the GWP map. This aggregated map was then classified into 5 classes, from very high to very low potentiality zones. The highest GWP zone was defined along Wadi El-Awaj, the northern part of Wadi Araba, and near the outlets of several wadies south of El-Tour City. The GWP was observed to be associated with low terrain, high surface ruggedness, increased drainage and lineament densities, and relatively close to thermal anomalies in wadi deposits and adjacent sandy areas. The results were validated by field observations including, soil infiltration rate, water wells data and vegetation patterns in the study area. Based on the outcomes, remote sensing data along with geospatial techniques can provide a powerful tool for groundwater probabilities in arid lands, and thus can be applied in regions with similar conditions, such as the Middle East countries.