Assessment and Estimation of Groundwater Recharge Using SWAT Model in Upper Wabe Shebele River Basin, South-Eastern Ethiopia

Abstract

In Upper Wabe Shebelle River Basin, groundwater is a key resource that supplements surface water to meet the demands of humans and the ecosystem. Therefore, it is essential to quantify groundwater recharge rate which is crucial for water resource development and management. This study utilized the SWAT (Soil and Water Assessment Tool) model to quantify the groundwater recharge rate and its spatial distribution in the Upper Wabe Shebele river basin of southeastern Ethiopia, aiming for improved groundwater resource planning and management. Hydro-meteorological data from, 2000 to 2018 was utilized for SWAT model calibration, and validation purposes. The performance evaluation showed acceptable ranges of model evaluation indicators (R² = 0.65–0.88, NSE = 0.58–0.77, PBIAS = 5.13–14.0). The spatial average annual groundwater recharge decreases from the highlands (315 mm/year) to the central plains (101 mm/year), with both seasonal and annual variations closely mirroring precipitation patterns throughout the catchment. The simulated water budget of the entire watershed revealed that approximately 214.60mm of the mean annual precipitation that occurs in the watershed was attributed to groundwater recharge. This quantity represents approximately 22.33% of the mean annual precipitation in the watershed. Ultimately, the variability of groundwater recharge is primarily driven by changes in precipitation. The remaining precipitation is partitioned into evapotranspiration (549.55mm), surface runoff (180.10mm) and (14.75mm) allocated to baseflow. The long-term annual water balance from 2000 to 2018 indicated that evapotranspiration is the most dominant factor accounting for approximately 57.19% of the mean annual precipitation in the catchment. In generally, findings of this study reveal that groundwater recharge in the Upper Wabe Shebelle River Basin exhibits significant seasonal and annual variability, and these variations were principally driven by fluctuations in precipitation. By utilizing the SWAT model, it provides valuable insights that can inform sustainable water management practices in the catchment area.