Assessing climate and land use impacts on surface water yield using remote sensing and machine learning.

Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spatial climate variability and land use/land cover (LULC) changes on surface water yield and availability in the Gilgel Gibe watershed, Ethiopia, from 1993 to 2023. Utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) hydrological models, machine learning, and remote sensing techniques, this study assessed variations in water resources and their impacts on basin water yield. This study utilized Landsat (30 m), MODIS (500 m-1 km), and 4 km resolution climate datasets from the United States Geological Survey (USGS) and NASA POWER for large-scale climate and land-use analyses from 1993 to 2023. An ensemble of machine learning models, including Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), were used to evaluate the effects of climate variability and land use on annual water yield. The study revealed significant land cover changes over a 30-year period. Shrubland decreased from 1,108.37 km (21.54%) in 1993 to 295.22 km (5.74%) in 2023. Grasslands and wetlands also showed declining trends. In contrast, water bodies increased from 12.51 km (0.24%) to 41.57 km (0.81%), primarily due to the construction of the Gilgel Gibe hydroelectric dam, and forested areas slightly decreased from 626.73 km (12.18%) to 534.18 km (10.38%). The surface runoff decreased to 15.78% in 2021 and 15.28% in 2022, whereas the water yield dropped from 1.22% in 1993 to 0.83% by 2023. This study also showed a reduction in lateral flow and higher evapotranspiration levels in 2000 and 2017. The decrease in runoff can be attributed to the loss of wetlands and grasslands, reduced precipitation, and regulatory effects of hydropower operations. In contrast, elevated evapotranspiration levels were primarily attributed to temperature extremes, vegetation stress, and potential increases in irrigation practices. These findings underscore the importance of climatic elements in regulating river discharge and the necessity for smart land use planning to prevent negative environmental consequences on water resources.