Sustainable groundwater management decisions require an understanding of the spatial distribution and seasonal fluctuations of site-specific water budget computations. This study aims to estimate the spatiotemporal distribution of recharge in the upper Awash sub-basin where the groundwater is experiencing intensive abstraction for domestic, industrial, and irrigation water uses. We estimated the spatial and long-term average monthly, seasonal, and annual groundwater recharge using a GIS-based spatially distributed water balance WetSpass-M model. Distributed grid maps of physical parameters (land-use land cover, soil, and slope) and monthly climatological records (rainfall, maximum and minimum temperature, wind speed) were used as model inputs. The WetSpass-M model estimated recharge is validated with the independently computed recharge using the automated digital filtering baseflow separation method. Attributed mainly to variability in soil texture and land use, the annual precipitation (1,032 mm) is distributed as evapotranspiration (45%), surface runoff (42%), and groundwater recharge (11%). Forest and grass areas with loamy sand, have high recharge, while built-up areas with clay soil have low recharge. August to September is estimated to have the largest recharge, while November to December has the lowest. Understanding the spatial and seasonal variability of groundwater recharge is important for sustainable utilization, proper management, and planning of groundwater resources.

  • The new WetSpass-M model configuration is used to estimate the spatiotemporal distribution of recharge.

  • Distributed grid maps of physical parameters and monthly climatological records are used as model inputs.

  • The variability of recharge is mainly governed by variability in soil texture and land-use changes.

  • Future numerical models can include the precise results of spatially and seasonally distributed groundwater recharge.

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