Identification of Groundwater Potential Zone Area Mapping Using Remote Sensing and Gis Techniques, Thecase of Enderta District, Tigray Ethiopia

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Addis Ababa University


Groundwater is a respected and significant natural resource in the world and it is the most fundamental for the growth and development of one country. However, estimating the potential of groundwater potential zone has still uncertainty due to the natural surroundings of groundwater. Therefore, this study aims to use the timely and cost effective remote sensing and geographical information system (GIS) methods for allocating, classify groundwater prospect zone in the Enderta District. To prepare GWPZAM use eight factors as a thematic map derived from Landsat 8 Operational Land Imager (OLI) Satellite image of the year 2016, SRTM Digital Elevation Models (DEM) with 30 m spatial resolution and secondary sources were utilized in this research. These were rainfall, slope, geomorphology, lithology, lineament density, drainage density, and Land-use/land-cover and soil texture. The methods to assess the identification of groundwater potential zone was using weight overlay analysis and Analytical Hierarchy Process (AHP) algorithm. All thematic layers were reclassified knowledge-based analysis that was reviewed from different kinds of literature. Then the weight for each factor was assigned rendering to their relative significance as per suitable based on Saaty's scale of AHP. The important factors result show that rainfall and slope have a higher weight and lithology has the lowest weight for identifying the possible of groundwater potential zone in the study area, respectively. The GIS method output results were validated by conducting field survey by randomly selecting wells in different places using GPS instruments. Coordinates of each of the well locations were obtained and plotted in the database. The spatial variation of the potential zones indicates that groundwater occurrence is controlled by structures, landforms and slope.



Groundwater Potential, Groundwater, Gis, Remote Sensing, Ahp