Abadefar et al. (2025) Integrated approach to identify suitable sites for percolation tanks to enhance groundwater in Kesem sub-basin

Identification

• Journal: Journal of Hydrology Regional Studies
• Year: 2025
• Date: 2025-12-09
• Authors: Demelash Debebe Abadefar, Daniel Wonde Mebrie, Negash Tessema
• DOI: 10.1016/j.ejrh.2025.103026

Research Groups

• Water Resource and Irrigation Engineering Department, Woldia Institute of Technology, Woldia University, Ethiopia
• Water Resource and Irrigation Engineering Department, Haramaya Institute of Technology, Haramaya University, Ethiopia

Short Summary

This study identified suitable sites for percolation tanks to enhance groundwater recharge in the Kesem sub-basin, Ethiopia, using an integrated Geographic Information System (GIS), remote sensing (RS), the Soil and Water Assessment Tool (SWAT), and Fuzzy Analytical Hierarchy Process (FAHP) framework. The analysis revealed that only 3.26 % of the sub-basin is classified as very highly suitable for percolation tank development.

Objective

• To delineate suitable sites for percolation tanks to enhance groundwater recharge in the Kesem sub-basin of Ethiopia's Awash Basin.
• To model runoff using the SWAT model for accurate hydrological representation of the basin.
• To determine the relative importance of influencing factors using the FAHP.
• To generate a composite suitability map through fuzzy overlay analysis in GIS.

Study Configuration

• Spatial Scale: Kesem sub-basin of the Awash River Basin, Ethiopia, covering approximately 2325 square kilometers. Geographically located between 39°09′36″ E to 39°52′48″ E longitude and 8°55′12″ N to 9°12′36″ N latitude.
• Temporal Scale:
  • Hydro-meteorological data: 1988–2017 (rainfall: 1988–2017; streamflow: 1993–2012).
  • SWAT model simulation: 1988–2017 (warm-up: 1988–1990; calibration: 1996–2005; validation: 2006–2012).
  • Satellite imagery: Landsat-8 OLI_TIRS image from 2022.

Methodology and Data

• Models used:
  • Soil and Water Assessment Tool (SWAT) for runoff simulation and hydrological modeling.
  • Fuzzy Analytical Hierarchy Process (FAHP) for multi-criteria decision-making and weight assignment.
  • Geographic Information System (GIS) and Remote Sensing (RS) for spatial analysis, data integration, and mapping.
  • Fuzzy Membership functions (Small, Large, Linear, Gaussian) for data standardization.
  • Fuzzy Gamma overlay (γ = 0.9) for integrating thematic layers.
• Data sources:
  • Satellite: Landsat-8 OLI_TIRS image (United States Geological Survey, USGS, 2022, 30 meter spatial resolution) for Land Use Land Cover (LULC) and lineament density. Digital Elevation Model (DEM) (Alaska, 12.5 meter spatial resolution) for slope, stream order, drainage density, and topographic wetness index.
  • Observation/Hydro-meteorological: Stream flow (cubic meters per second), rainfall (millimeters), temperature (degrees Celsius), relative humidity (percent), sunshine hour (hours), and wind speed (meters per second) from four meteorological stations and one hydrological station (Ethiopian Ministry of Water and Energy, Ethiopian National Meteorological Agency, 1988–2017).
  • Secondary data: Geological data (Ethiopian Ministry of Mine), Soil data (Ethiopian Ministry of Agriculture).

Main Results

• The SWAT model demonstrated strong performance for runoff simulation with a Nash–Sutcliffe Efficiency (NSE) of 0.77 and a coefficient of determination (R²) of 0.79 during calibration, and NSE of 0.77 and R² of 0.76 during validation.
• The most sensitive SWAT parameters identified were ALPHABF.gw (baseflow alpha-factor), CN2.mgt (SCS runoff curve number), and OVN.hru (Manning’s “n” value for overland flow).
• The suitability analysis for percolation tanks classified the Kesem sub-basin as follows:
  • Very highly suitable: 3.26 % (75.41 square kilometers)
  • Highly suitable: 9.55 % (221.03 square kilometers)
  • Moderately suitable: 17.56 % (406.54 square kilometers)
  • Low suitability: 30.66 % (709.87 square kilometers)
  • Very low suitability: 38.98 % (902.55 square kilometers)
• Validation using existing groundwater recharge structures showed that 60 % were located in very highly suitable zones, 20 % in highly suitable zones, and 20 % in moderately suitable zones, confirming the model's accuracy.
• The FAHP-derived weights indicated rainfall (14.4 %), runoff (10.9 %), and lithology (10.3 %) as the most influential criteria for percolation tank site selection.

Contributions

• This study introduces a novel integrated framework combining hydrological modeling (SWAT), fuzzy-based Multi-Criteria Decision-Making (FAHP), and spatial analysis (GIS/RS) for a holistic evaluation of groundwater recharge potential.
• It overcomes limitations of conventional methods by using FAHP for dynamic weighting of factors, reflecting environmental complexity and managing uncertainty in expert judgments.
• The research provides actionable insights by identifying priority zones for percolation tank construction, serving as a practical decision-support tool for regional water management and rainwater harvesting planning.
• The developed approach is scalable and transferable to other data-scarce and climate-vulnerable basins, supporting sustainable groundwater management and climate-resilient development strategies in Ethiopia and similar regions.

Funding

This research did not receive any external funding. The work was supported solely through staff time and institutional resources provided by Woldia University and Haramaya University.

Citation

@article{Abadefar2025Integrated,
  author = {Abadefar, Demelash Debebe and Mebrie, Daniel Wonde and Tessema, Negash},
  title = {Integrated approach to identify suitable sites for percolation tanks to enhance groundwater in Kesem sub-basin},
  journal = {Journal of Hydrology Regional Studies},
  year = {2025},
  doi = {10.1016/j.ejrh.2025.103026},
  url = {https://doi.org/10.1016/j.ejrh.2025.103026}
}