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<p>Climate change increasingly threatens water resources in semi‑arid, rain‑fed regions such as Nigeria’s Benue River Basin. This study evaluates climate‑induced variability in river discharge and groundwater recharge within the basin using the physically based ArcSWAT model to assess climate-driven variability in monthly river discharge from 1990 to 2024, integrating terrain, land cover, soils, and multi-source climate data, supported by Google Earth Engine remote sensing. Rigorous calibration (1990–2000) and validation (2001–2012) using the SUFI-2 algorithm confirmed strong model performance (R<sup>2</sup> = 0.99/0.85, NSE = 0.98/0.82), effectively capturing topography-driven runoff, soil–water interactions, and evapotranspiration dynamics. Results reveal pronounced seasonal contrasts, with peak discharges in August (145&#xa0;m<sup>3</sup>/s) and extremely low flows (&lt; 2 m<sup>3</sup>/s) during February–May, intensifying dry-season water stress. A marked January–July flow decline indicates shifts in atmospheric–hydrologic linkages. Spatial analysis shows greater discharge losses in upstream forested sub-basins than in downstream zones. Climate projections under RCP4.5 and RCP8.5 suggest mean annual streamflow reductions of 11.1% and 18.5%, with dry-season declines reaching 25%. Coupling CA-Markov land use simulations with CMIP6 ensemble projections enhanced ArcSWAT’s forecasting accuracy under future scenarios. Combined land climate impacts led to up to 30% dry-season flow reduction and increased hydrological variability across sub-basins. As one of the few physically based long-term assessments in West Africa, the study underscores the compounded effects of land use and climate change on water resources. Urgent adaptive strategies such as aquifer recharge, climate-smart irrigation, and decentralized water storage are recommended. Future research should integrate groundwater and socio-economic water-use modeling to better inform resilient, sustainable basin-scale water management.</p>

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ArcSWAT-based modeling of climate-driven changes in discharge and groundwater recharge in Nigeria’s Benue basin

  • 期刊论文

  • 发表日期：

    2026年2月6日

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  • John Ayuba Godwin,
  • Shruti Singh,
  • Ishaku Joshua Dibal,
  • Rajesh Kumar,
  • Jagvir Singh

摘要

Climate change increasingly threatens water resources in semi‑arid, rain‑fed regions such as Nigeria’s Benue River Basin. This study evaluates climate‑induced variability in river discharge and groundwater recharge within the basin using the physically based ArcSWAT model to assess climate-driven variability in monthly river discharge from 1990 to 2024, integrating terrain, land cover, soils, and multi-source climate data, supported by Google Earth Engine remote sensing. Rigorous calibration (1990–2000) and validation (2001–2012) using the SUFI-2 algorithm confirmed strong model performance (R2 = 0.99/0.85, NSE = 0.98/0.82), effectively capturing topography-driven runoff, soil–water interactions, and evapotranspiration dynamics. Results reveal pronounced seasonal contrasts, with peak discharges in August (145 m3/s) and extremely low flows (< 2 m3/s) during February–May, intensifying dry-season water stress. A marked January–July flow decline indicates shifts in atmospheric–hydrologic linkages. Spatial analysis shows greater discharge losses in upstream forested sub-basins than in downstream zones. Climate projections under RCP4.5 and RCP8.5 suggest mean annual streamflow reductions of 11.1% and 18.5%, with dry-season declines reaching 25%. Coupling CA-Markov land use simulations with CMIP6 ensemble projections enhanced ArcSWAT’s forecasting accuracy under future scenarios. Combined land climate impacts led to up to 30% dry-season flow reduction and increased hydrological variability across sub-basins. As one of the few physically based long-term assessments in West Africa, the study underscores the compounded effects of land use and climate change on water resources. Urgent adaptive strategies such as aquifer recharge, climate-smart irrigation, and decentralized water storage are recommended. Future research should integrate groundwater and socio-economic water-use modeling to better inform resilient, sustainable basin-scale water management.