Open AccessGroundwater Potential Zone Mapping Using Analytical Hierarchy Process and GIS in Muga Watershed, Abay Basin, Ethiopia
Author(s) -
Melese Tadele,
Belay Tatek
Publication year - 2022
Publication title -
global challenges
Language(s) - English
Resource type - Journals
ISSN - 2056-6646
DOI - 10.1002/gch2.202100068
Subject(s) - thematic map , drainage density , watershed , topographic wetness index , groundwater , analytic hierarchy process , groundwater recharge , geospatial analysis , land cover , elevation (ballistics) , hydrology (agriculture) , structural basin , lineament , environmental science , geology , remote sensing , land use , digital elevation model , aquifer , cartography , computer science , geomorphology , geography , mathematics , engineering , civil engineering , geotechnical engineering , operations research , tectonics , paleontology , geometry , machine learning
Groundwater is an important resource that contributes significantly to the total annual water supply. The purpose of the present study is to assess and delineate the groundwater recharge zone using geospatial technology through an analytical hierarchal process (AHP) method in to the Muga watershed, Abay Basin. Remote sensing satellite images and the corresponding data are used for the preparation of thematic layers, viz., geology, rainfall, slope, soil, curvature, topography wetness index, elevation, drainage density, land use land cover, and lineament density of the study watershed. All thematic layers are integrated with a multicriteria evaluation technique. Weighted overlay index analysis is carried out to give rank for each parameter. The weight is assigned for each thematic layer depending on the AHP technique. The reliability of the output is checked by the calculated consistency index and consistency ratio which is reasonably acceptable (0.044 < 0.1). Verification is done by considering the groundwater well locations in the validation datasets. The receiver operating characteristic curve and area under curve (=82.9%) are used to explore the prediction accuracy.