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Environmental and Engineering Geoscience

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Remote Sensing and GIS Approach for Water-Well Site Selection, Southwest Iran

¹ Department of Remote Sensing and GIS, Shahid Chamran University, Ahvaz, Iran
² Department of Geology, Shahid Chamran University, Ahvaz, Iran
³ Department of Remote Sensing and GIS, Shahid Chamran University, Ahvaz, Iran
⁴ Kentucky Geological Survey and Department of Earth and Environmental Sciences, University of Kentucky, Lexington, KY, 40506-0107

The Pabdeh-Lali Anticline of northern Khuzestan province is located in southwestern Iran and occupies 790 km². This structure is situated in the Zagros folded belt. As a result of well-developed karst systems in the anticlinal axis, the water supply potential is high and is drained by many peripheral springs. However, there is a scarcity of water for agriculture and population centers on the anticlinal flanks, which imposes a severe problem in terms of area development. This study combines remotely sensed (RS) data and a geographical information system (GIS) into a RSGIS technique to delineate new areas for groundwater development and specific sites for drilling productive water wells. Toward these goals, RS data were used to develop GIS layers for lithology, structural geology, topographic slope, elevation, and drainage density. Field measurements were made to create spring-location and groundwater-quality GIS layers. Subsequently, expert choice and relational methods were used in a GIS environment to conjunctively analyze all layers to delineate preferable regions and 43 individual sites in which to drill water wells. Results indicate that the most preferred areas are, in preferential order, within recent alluvial deposits, the Bakhtiyari Conglomerates, and the Aghajari Sandstone. The Asmari Limestone and other units have much lower potential for groundwater supplies. Potential usefulness of the RSGIS method was indicated when six out of nine producing wells recently drilled by the Khozestan Water and Power Authority (which had no knowledge of this study) were located in areas preferentially selected by this technique.

Key Words: Remote Sensing • GIS • Groundwater Supply • Desert • Iran