article · Discover Environment
This study assessed groundwater potential (GWP) and quality trends in Fogera Woreda, Ethiopia, using an integrated geospatial method that used remote sensing, GIS-based multi-criteria decision analysis (MCDA), and water quality indexing (WQI). Land use/land cover (derived from Sentinel-2 imagery), soil type, lithology, drainage density, lineament density, slope, and rainfall were the seven thematic layers that were examined using weighted overlay analysis (WOA) to delineate GWP zones (very low to very high) using weights derived from the Analytical Hierarchy Process (AHP). The available physicochemical analysis of 35 samples measuring fluoride (F⁻), calcium (Ca2⁺), magnesium (Mg2⁺), nitrate (NO₃⁻), and iron (Fe) in accordance with WHO and Ethiopian criteria was used concurrently to evaluate the quality of the groundwater. The findings showed a substantial correlation between permeable lithologies and dense drainage networks, with 68% of the studied area being within moderate to high GWP zones. According to water quality examination, 82% of samples met drinking requirements; nevertheless, there were localized abnormalities, such as high NO₃⁻ (up to 45 mg/l) in agricultural regions and F⁻ (up to 2.1 mg/l) in volcanic aquifers. Clear relationships between land use (especially intensive farming that uses a lot of irrigation) and hotspots for groundwater pollution were shown using spatial interpolation maps. Critical priority zones for mitigation actions were determined by integrating GWP and WQI data using a GIS overlay. This study offers a reproducible framework for assessing conjunctive groundwater resources in semi-arid regions, highlighting the necessity of focused geogenic contaminant monitoring, sustainable farming methods to lessen nitrate leaching, and community education initiatives to mitigate water quality threats in communities that are at risk. For planners of water resources in the Blue Nile Basin and other agro-ecological environments, the methodological approach and results provide insightful information.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1007/s44274-026-00622-6
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.