It is important to understand variations in hydro-meteorological variables to provide crucial information for water resource management and agricultural operation. This study aims to provide comprehensive investigations of hydroclimatic variability in the Bilate watershed for the period 1986 to 2015. Coefficient of variation (CV) and the standardized anomaly index (SAI) were used to assess the variability of rainfall, temperature, and streamflow. Changing point detection, the Mann–Kendell test, and the Sen’s slope estimator were employed to detect shifting points and trends, respectively. Rainfall and streamflow exhibited higher variability in the Bega (dry) and Belg (minor rainy) seasons than in the Kiremt (main rainy) season. Temperature showed an upward shift of 0.91 °C in the early 1990s. Reduction in rainfall (−11%) and streamflow (−42%) were found after changing points around late 1990s and 2000s, respectively. The changing points detected were likely related to the ENSO episodes. The trend test indicated a significant rise in temperature with a faster increase in the minimum temperature (0.06 °C/year) than the maximum temperature (0.02 °C/year). Both annual mean rainfall and streamflow showed significant decreasing trends of 8.32 mm/year and 3.64 mm/year, respectively. With significant increase in temperature and reduction in rainfall, the watershed has been experiencing a decline in streamflow and a shortage of available water. Adaptation measures should be developed by taking the increasing temperature and the declining and erratic nature of rainfall into consideration for water management and agricultural activities.

This study aims to assess the potential impacts of climate change on hydrometeorological variables and drought characteristics in the Ethiopian Bilate watershed. Climate projections under two Representative Concentration Pathways (RCP4.5 and RCP8.5) were obtained from the Coordinated Regional Downscaling Experiment (CORDEX) Africa for the near future (2021–2050) and far future (2071–2100) periods. The Soil and Water Assessment Tool (SWAT) model was applied to assess changes in watershed hydrology with the CORDEX-Africa data. The Standardized Precipitation Index (SPI), Streamflow Drought Index (SDI), and Reconnaissance Drought Index (RDI) were calculated to identify the characteristics of meteorological, hydrological, and agricultural droughts, respectively. Due to a significant rise in temperature, evapotranspiration will increase by up to 16.8% by the end of the 21st century. Under the RCP8.5 scenario, the annual average rainfall is estimated to decrease by 38.3% in the far future period, inducing a reduction of streamflow of up to 37.5%. Projections in reduced diurnal temperature range might benefit crop growth but suggest elevated heat stress. Probabilities of drought occurrence are expected to be doubled in the far future period, with increased intensities for all three types of droughts. These projected impacts will exacerbate water scarcity and threaten food securities in the study area. The study findings provide forward-looking quantitative information for water management authorities and decision-makers to develop adaptive measures to cope with the changing climate.

The Omo Gibe River Basin is the largest basin in southwestern Ethiopia. It’s frequently exposed to flooding driven by natural and human-induced factors, threatening ecosystems, human life, and property. This study develops an integrated flood hazard assessment by combining statistical and fuzzy logic approaches within a GIS framework. Despite growing risks, assessments integrating ensemble modeling, multi-factor interactions, spatio-temporal analysis, and comparative evaluation of fuzzy overlay methods remain limited. To address this gap, frequency ratio and fuzzy logic were applied to assess flood susceptibility across three decades. Prior to modeling, multicollinearity among flood conditioning factors was assessed using the Variance Inflation Factor (VIF) and tolerance values. Flood inventory maps were generated from the Modified Normalized Difference Water Index, ground truth and an existing datasets; 70% of flood locations were used for training and 30% reserved for validation. Five fuzzy overlay operators were evaluated using Receiver Operating Characteristic curves, Fuzzy Gamma achieving the highest performance (success rate 89.52%, prediction accuracy 91.42%). Very high flood hazard zones expanded from 5.68% in 1986 to 9.05% in 2006 due to intense rainfall and inadequate land-use management, then declined to 5.53% in 2024 following the development of hydrological infrastructure and improved basin management. This study advances hazard modeling by addressing uncertainty and multicollinearity, providing a validated, data-efficient approach for flood mapping in data-scarce regions. The findings support Sustainable Development Goals 11.5 and provide evidence-based insights for floodplain zoning, infrastructure planning, and resilience building. Future research should incorporate climate change scenarios and socio-economic vulnerability to strengthen long-term flood risk management.

The aim of this study was to look at the potential effects of climate change on the Bilate watershed’s crop water requirements (CWRs). Under two climate scenarios (RCP4.5 and RCP8.5), the CWR was anticipated for 2021–2050 and 2071–2100. The power transformation (PT) and variance scaling (VARI) methods were employed to correct biases in the rainfall and temperature climate variables, respectively. The CROPWAT 8.0 model was used to simulate CWRs and crop irrigation requirements (CIRs) for both the current and future periods. The estimated results for 2071–2100 reveal a drop in effective rainfall ( Pe ) of 29.6%–38% under RCP 4.5 and 24.7%–43.3% under RCP 8.5. CWRs would increase by 12.3–51 mm under RCP 4.5 and 16.3–62 mm under RCP 8.5 per growing season, but the rates of decrease/increase would vary by crop. Similarly, the anticipated irrigation requirements for the following crops increased when compared to the baseline period: wheat (from 68.1 to 81.6 mm), tomato (from 163 to 193 mm), sorghum (from 80 to 102 mm), maize (from 121 to 134 mm), cotton (from 163 to 192 mm), cabbage (from 193 to 221 mm), soybean (from 104 to 120 mm), and banana (from 95 to 135 mm). The study’s findings are important in demonstrating how climate change has a detrimental impact on crop water availability in the Bilate watershed, as well as in improving water resource management planning.

The Abaya Chamo sub basin is susceptible to drought of moderate to severe intensity, which significantly impacts the sub basin’s agricultural production and local community life. We investigate drought characteristics in the Abaya Chamo sub basin using data from 1981 to 2021 and a variety of drought indices, including the Standardized Precipitation Evapotranspiration Index (SPEI) to identify meteorological drought, the Standardized Stream flow Index to assess hydrological drought, and the Standardized Soil Moisture Index (SSMI) to evaluate agricultural drought. The results indicate that all indices captured historical drought episodes, with only minor variations. Additionally, the findings show that the proportion of dry months exceeded that of rainy months between 1981 and 2021, showing that aridity increased during this period. We also identify drought trends that vary by watershed and by drought type. This study reveals that the sub basin experienced the maximum drought intensity, as computed using the SPEI, SSI, and SSMI, with index values of -2.5, -2.8, and − 2.4, respectively. The Gelana catchment experienced the most severe drought, while the Bilate catchment faced less severe drought. Overall, the study indicates severe to moderate drought of substantial magnitude that varied across the sub basin. These findings will guide drought planning and management in the Abaya Chamo sub basin and raise stakeholders’ awareness of how precipitation, runoff, and soil moisture can be used to describe drought. Consequently, the study suggests that stakeholders and policymakers implement early warning systems and adaptive measures for water resource management, and develop comprehensive drought risk management plans to improve regional food security.