Soil and Water Assessment Tool reveals dominant baseflow in semi-arid catchment with sand dams in Kenya

Abstract

Increasing water scarcity and climate variability threaten rural livelihoods in semi-arid regions. Sand dams are widely used as Nature-based Solutions (NbS) to retain water within the sandy matrix of ephemeral riverbeds, yet their catchment-scale hydrological effects remain insufficiently quantified. We applied the Soil and Water Assessment Tool (SWAT+) in a 22.35 km 2 ungauged ephemeral catchment in Makueni County, Kenya, containing 22 sand dams. The model combined open Earth observation and geospatial datasets to characterize baseline hydrology for 1990–2024. Future hydrological responses were explored under an RCP4.5 climate scenario through 2099, while a third scenario tested the feasibility of representing sand dams as in-channel SWAT+ reservoir objects. The baseline simulation indicates an evapotranspiration-dominated catchment with strong subsurface flow contributions, with modeled baseflow accounting for approximately 70% of total streamflow. Under RCP4.5, increased precipitation is partitioned predominantly into enhanced percolation and subsurface flow, strengthening the modeled baseflow contribution while also increasing localized surface-runoff peaks. Representing sand dams as standard reservoir objects enabled the analysis of spatial and seasonal differences among individual structures and their cascade behavior, but produced highly episodic storage dynamics and substantial quantitative uncertainty. The results demonstrate the potential of open-data-supported hydrological modeling for characterizing ungauged semi-arid catchments and exploring sand-dam networks at the catchment scale. At the same time, the SWAT+ reservoir formulation cannot adequately reproduce key sand-dam processes, particularly porous-media storage and sediment-related subsurface dynamics. The findings should therefore be interpreted primarily in terms of hydrological patterns and model behavior and not as as precise estimates of sand-dam performance, highlighting the need for improved model representation and field-based validation.