Climate change affects ecosystems, agriculture, human health, forestry, and water resource availability. This study is mainly aimed at assessing the climate change effect on the water resources of the Kessie Watershed in the Upper Blue Nile Basin, Ethiopia. The updated Coupled Model Intercomparison Project Phase 6 (CMIP-6) data outputs were used. The three climate model outputs: ACESS_ESM1-5, FGOALS_g3, and GFDL_ESM4 with two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) scenarios, were used. The climate model output rainfall and temperature data were downscaled to the station level through bias correction. The catchment hydrology was represented by the SWAT—Soil and Water Assessment Tool—through calibration and validation. Future temperatures and rainfall change were evaluated by the Mann–Kendall trend test and Sen’s slope estimator. Future climate change trend analysis and streamflow simulation were done on two time horizons: the 2050s (2041–2070) and the 2080s (2071–2100). The baseline streamflow data (1985–2014) were used as a reference. The global climate model projection data indicated mean annual precipitation and temperatures show a slight increase for the future in both scenarios for all climate model outputs. According to the SSP2-4.5 and SSP5-8.5 scenarios, respectively, mean annual precipitation is expected to increase by 5% and 4.89% in the 2050s and 10.13% and 6.8% in the 2080s based on ACCESS_ESM1-5; 4.7% and 3.8% in the 2050s and 4.3% and 4.84% in the 2080s based on FGOALS_g3; and 4.67% and 3.81% in the 2050s and 4.67% and 3.81% based on GFDL_ESM4 models data. Yearly average maximum temperature may increase by 3.62 °C and 1.87 °C in the 2050s and 3.31 °C and 2.99 °C in the 2080s based on ACCESS ESM1-5, 1.76 °C and 1.25 °C in the 2050s and 3.44 °C and 2.61 °C in the 2080s based on FGOALS-g3, and 2.15 °C and 3.83 °C in the 2050s and 1.37 °C and 2.66 °C in the 2080s based on GFDL-ESM4 model data. Similarly, the mean annual minimum temperature is also expected to increase by 2.73 °C and 1.90 °C in the 2050s and 5.63 °C and 4.52 °C in the 2080s based on ACCESS ESM1-5, 3.04 °C and 2.43 °C in the 2050s and 3.55 °C and 4.36 °C in the 2080s based on FGOALS-g3, and 2.31 °C and 3.29 °C in the 2050s, and 3.16 °C and 3.87 °C in the 2080s based on GFDL-ESM4 model data. The streamflow is also expected to increase. In the 2050s, simulated annual streamflow is expected to increase from 12.1 to 21.8% and 9.8 to 15.4% in SSP2-4.5 and SSP5-8.5, respectively, whereas in the 2080s, the change is expected to increase from 15.14 to 24.08% and 13.08 to 41% in SSP2-4.5 and SSP5-8.5, respectively. Future water resource potential of the case study watershed seems able to support irrigation and other projects.

This study investigates the utility of satellite-based rainfall products and the performance of bias correction methods in one of the sub-basins of the Upper Blue Nile Basin (Main Beles basin). Four satellite rainfall products are used: Climate Prediction Center (CPC) MORPHing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42V7 (TMPA 3B42V7), and Climate Forecast System Reanalysis (CFSR). The performance of the satellite rainfall products (SRPs) was compared using three bias correction methods (Delta, Empirical Quantile Mapping (EQM), and Quantile Mapping (QM)) on five metrological stations. Six statistical criteria were used to evaluate these methods on the period 2003–2016 at daily and monthly scales. The results showed that SRPs and bias correction methods of CMORPH_QM (r = 0.538) and TMPA_3B42V7_EQM (r = 0.95) data showed good performance, while PERSIANN_EQM (r = 0.348) and PERSIANN_Delta (r = 0.83) performed worst at daily and monthly time scales, respectively. This study assessed the importance of SRPs and bias correction methods to use in data scarce regions for water resources planning and other related sectors.

This study identifies groundwater potential zones (GWPZs) in the Borkena watershed, Ethiopia, using Geographic Information Systems (GIS), remote sensing, and the Analytical Hierarchy Process (AHP). Ten critical parameters elevation, slope, drainage density, land use/land cover (LULC), rainfall, soil type, aspect, curvature, lineament density, and geology were integrated to produce a GWPZ map. The results show that areas with slopes between 0° and 6.3°, elevations below 1500 m, and specific soil and lithological characteristics exhibit high groundwater potential, covering approximately 340 km². Additionally, 453 km² and 867 km² were identified as moderate and medium potential zones, respectively. Most existing studies focus on the technical and spatial aspects of delineating potential zones without explicitly addressing how these findings contribute to broader sustainability goals, particularly in the context of long-term water security, climate resilience, and socioeconomic development. This gap is significant given that effective groundwater management directly supports multiple Sustainable Development Goals (SDGs), especially SDG 6 (Clean Water and Sanitation), SDG 2 (Zero Hunger), and SDG 13 (Climate Action) But, This study underscores the effectiveness of multi-criteria decision-making (MCDM) and geospatial technologies in groundwater resource assessment and supports Sustainable Development Goals (SDGs), particularly SDG 6 (Clean Water and Sanitation), SDG 2 (Zero Hunger), and SDG 13 (Climate Action), by informing sustainable water resource planning and management.