WATER RESOURCES EXPLORATION AND MANAGEMENT BASED ON REMOTE SENSING AND GEOPHYSICAL DATA ANALYSIS: AL-NAQAB WATERSHED, EAST CENTRAL SINAI, EGYPT

This study integrates remote sensing and geophysical data to identify the hydrological conditions of the Naqab reservoir watershed. The main objectives of this study are identification and the interpretation of subsurface structures and their impact on groundwater flow, the relationships between structures and groundwater and the optimum way for watershed management in this sub-basin. Geophysical data including, ground magnetic survey and 1D electrical resistivity sounding helped in identifying the lithology and delineating zones of groundwater occurrence. The magnetic data delineated the basement rock, aided in characterizing the geometry of the subsurface structures that control the land surface features and constrain groundwater flow system. The interpreted subsurface structure elements include six sets of faults trending NE-SW, NW-SE, NWW-SEE, NEE-SWW, N-S and E-W. The basement depth was estimated at zero at the southern part and about 5187 m at the northern part. Two aquifer systems were characterized, the shallow aquifer of the Wata Formation (Upper Cretaceous) and the deep aquifer of the Malha Formation (Lower Cretaceous). The probability of groundwater occurrence increases towards the central part of the study area to north direction, where the thickness of the sedimentary basin reaches its maximum at the center of the study area. Different trends of faults were interpreted from the geo-electrical cross-sections along two transects. Three patterns of faults were characterized including step faults, graben faults and horst faults. These faults could be indicated on the geo-electrical section by a marked difference in the layers* thicknesses. The magnetic data confirmed the locations of the faults delineated by the electrical resistivity profiles. The outlined faults are trending mainly in NE-SW, NW-SE, NWW-SEE, NEE-SWW and E-W directions. Lineament structures delineation and drainage pattern analysis were evaluated and interpreted from the analysis of remote sensing (RS) data and geographic information system (GIS) technique. The SRTM-DEM (Shuttle Radar Topographic Mission-Digital Elevation Model) was also utilized to automatically identify and extract drainage network. Interpretation and analysis of the inferred lineament structures indicate the presence of a number of main lineament populations that trends: NE-SW, NW-SE, NNW-SSE, NWW-SEE, E-W and N-S. Meanwhile, the interpretation and analysis of drainage pattern network indicate the presence of t