Integrated approach for groundwater potential exploration in Abbay River Basin, East Africa

Abstract

AbstractThis paper presents and examines groundwater potential zones with the help of remote sensing and GIS methods for controlling and investigating the geospatial data of each parameter. Groundwater is a very important source for water supply and others, considering its availability, quality, cost, and time-effectiveness to develop. It is virtually everywhere and yet variable in quantity. Because of several conditions, such as rapid population growth, urbanization, industrialization, and agricultural development, groundwater sources are under severe threat. Climate change plays an important role in the quality and quantity of groundwater potential. In addition, climate change severely affects parameters that influence groundwater recharge. Unreliable exploitation and poor quality of surface water resources tend to increase the decline in groundwater levels. Hence, it is necessary to identify groundwater potential zones that can be used to optimize and monitor groundwater resources. This study was conducted in the Abbay River Basin and identifies the location of groundwater potential for developing new supplies that could be used for a range of purposes in the study area, where groundwater serves as the main source for agricultural purposes rather than surface water. Seven selected parameters—lineament density, precipitation, geology, drainage density, land use, slope, and soil data—were collected, processed, resampled, projected, and reclassified for hydrological analysis. For the generation of groundwater zones, weightage was calculated using an analytical hierarchy method, reclassified, ranked, and overlaid with GIS. The obtained results of weightage were lineament density (37%), precipitation (30%), geology (14%), drainage density (7%), land use land cover (5%), slope (4%), and soil (3%). The consistency ratio estimated for this study was 0.089, which was acceptable for further analysis. Based on the integration of all thematic layers and the generated groundwater potential zones, the map was reclassified into five different classes, namely very good, good, moderate, poor, and very poor. The results of this study reveal that 1295.33 km2 of the study area can be considered very poor, 58,913.1 km2 is poor, 131,323 km2 is moderate, 18,557 km2 is good, and 311.5 km2 is very good. Any groundwater management project performed in the better regions would offer the greatest value. A similar study would be valuable before planning any water resource development activity, as this would save the expense of comprehensive field investigations. This study also demonstrates the importance of remote sensing and GIS techniques in mapping groundwater potential at the basin scale and suggests that similar methods could be applied across other river basins.