Ethiopia is a country that heavily relies on rainfall-aided cultivation which is carried out by small-scale landowners, leaving it very vulnerable to climate change and fluctuation. The primary goal of this research is to investigate how climate change affects maize yield in Wolaita zone of Ethiopia. The authors were employed a linear regression method to evaluate the relationship between climate parameters and maize yield. Sen's slope magnitude estimator and the Mann-Kendal trend test were used to assess the significance of climate change. The outcome demonstrated that the temperature extreme indices of warm days and the length of warm days were considerably higher by 37.5% and 3.7% of days per year, however, cold days and cold spells were significantly decreased. Over the 1981-2021 periods, there was a significant upward pattern in TXx and TNn at an average of 0.033°C and 0.034°C. There was a considerable decline of 2.3% in the simple daily precipitation intensity index and 33% decreased in extremely heavy precipitation, respectively. The correlation analysis's findings indicated that growing period precipitation and maize outputs were positively correlated, but negatively correlated with maximum and minimum temperatures. Extreme temperature and precipitation were more explained a maize yield than average climate patterns. 12.4%, 14.76%, 13.08%, and 7.95% of maize output variability was attributed by the growing season mean climate conditions, which include precipitation, mean, minimum, and maximum temperature. The variability of maize output was explained by combined impact of precipitation and temperature extremes were 67.7% and 45.0%, respectively. Therefore, livelihood diversification and relevant policy formulation are suggested to adapt inevitable climate change by implementing irrigation and resistant varieties to improve maize yield production.

Rainfall, a critical determinant of agriculture, water resources, and socioeconomic stability, was analyzed for seasonal and annual variability in the Dawuro Zone, Ethiopia, from 1991 to 2020. Using time series data from seven meteorological stations and four virtual stations, statistical methods such as the Coefficient of Variation (CV), Standard Anomaly Index (SAI), Sen’s Slope Estimator, and Modified Mann-Kendall test were employed, alongside Inverse Distance Weighted interpolation in ArcGIS for spatial analysis. The study revealed significant variability, with Tocha recording the highest mean annual rainfall (1998 mm) and Tercha the lowest (1399.5 mm). Tercha exhibited the least consistent rainfall, while Gasechere showed the highest variability (CV 31.82%, SD 600.37 mm). The Kiremt season (June-September) contributed the most to annual rainfall, with Tocha receiving 973.99 mm and Tercha 696.03 mm, while the Belg (February-May) and Bega (October-January) seasons showed lower contributions and higher variability, particularly at Gena Bossa and Gasechere. Spatially, the southwest, south, and southeast regions received higher rainfall, while the north and northeast experienced the lowest amount. This study investigates the onset, cessation, and duration of the rainy season in the Dawuro Zone, Ethiopia, from 1991 to 2020, with particular attention to the Kiremt season (June-September). The start of the rainy season, characterized by heavy rainfall, varies considerably, from mid-September to late September, with delays in years like 1994, 2000, and 2015 (around September 27-28) and earlier starts in 1992 and 2006 (around September 19-20). Cessation dates, occurring between mid-December and late December, show similar variability, with longer seasons ending around December 19-20 (e.g., 1995, 2005, 2015) and shorter ones around December 15-16 (e.g., 2000, 2010). The length of the growing season ranges from 90 to 110 days, reaching a maximum of 106-108 days in 1994, 2002, and 2016, and decreasing to 96-98 days in 1998 and 2012. This variability, driven by factors such as the Inter-Tropical Convergence Zone and El Niño-Southern Oscillation, presents challenges for agricultural planning by affecting crop selection and increasing the risk of failure due to shortened seasons or waterlogging in extended ones. The next study will consider the association between seasonal rainfall variability and global systems like El Niño-Southern Oscillation, Indian Dipole oscillation, and other global systems over the study area. The study recommends expanding meteorological stations, integrating findings into regional policies for sustainable agriculture and water management, and enhancing early warning systems to address the variable rainfall patterns across the Kiremt, Belg, and Bega seasons.

Drought is a complex natural hazard resulting from meteorological and hydrological phenomena. Meteorological drought, defined by precipitation shortfalls, frequently precedes hydrological drought, decreasing surface and groundwater availability. The Upper Baro Watershed, an important agricultural and hydrological hub in Ethiopia, is becoming more vulnerable to climate change-induced droughts. This article investigates the comprehensive assessment of the meteorological and hydrological drought, focusing on their roles in the hydrological cycle, the transition from meteorological to hydrological drought, and the consequences for water resources management. The Standardized Precipitation Index (SPI) and the Stream Drought Index (SDI) are used to perform a thorough evaluation of the hydrological and meteorological drought characteristics of historical and projected future drought in the upper Baro watershed. Historical model data from 1985 to 2014, along with estimates under the SSP2-4.5 and SSP5-8.5 emission scenarios for the middle of the century (2041-2070) and end of the century (2071-2000). The association between the SPI and SDI indices was studied over 30 years across the basin. Overlapping periods of 3, 6, 9, and 12 months were discovered. This study analyzes the top four climate models, including MPI-ESM1-2-HR, FGOLAS-g3, GFDL-ESM4, and INM-CM4-8. These models are assessed based on the upper Baro watershed. The findings reveal that in the study area, the MPI-ESM1-2-HR and INM-CM4-8 models are the best-performing climate models for the upper Baro watershed under the future climate scenarios SSP2-4.5 and SSP5-8. The comprehensive assessment of the meteorological and hydrological drought under SSP2-4.5 and SSP5-8.5 climate scenarios. The findings show that in mid-century (2041-2071), under the SSP2-4.5 and SSP5-8.5 emission scenarios, moderately wet to severely dry conditions will occur. Additionally, by the end of the century (2071-2100), under the SSP2-4.5 and SSP5-8.5 emission scenarios, moderately dry to severe drought conditions will emerge over the upper Baro watershed. The findings suggest that both the SPI and SDI indices are capable of catching major droughts in the upper Baro watershed over the last 30 years. The study recommended that understanding this link is crucial for successful drought monitoring, forecasting, and mitigation efforts.

Recent studies indicate climate change-driven extreme weather events have led to frequent flooding in many East African countries, including Ethiopia. This study evaluates climate extremes and their association with floods in the Baro Akobo River Basin, Ethiopia, using CMIP6 climate models and HEC-HMS hydrological modeling. We use daily precipitation and temperature from 30 meteorological stations, and 12 CMIP6 Global Climate Models (GCMs) under two shared socioeconomic pathways (SSPs), SSP2-4.5 and SSP5-8.5 scenarios. The GCMs are evaluated at the daily time scale with observed data over the period from 1985 to 2014, resulting in MPI-ESM1-2-HR, INM-CM4-8, FGOALS-g3, and GFDL-ESM4 the top four best-performing models in the basin. We utilize the Expert Team Climate Change Detection Indices (ETCCDI) to assess climate extremes in the basin, focusing on five precipitation-based and four temperature-based indices due to their anticipated correlation with flood events. We then simulate peak discharge at the basin’s outlet using the HEC-HMS hydrological model to correlate annual maximum peak flow (Q_max) with climate extreme indices. The results show that during the mid-century (2041–2070), all precipitation extremes, except for Consecutive Wet Days (CWD), demonstrate a strong correlation with Q_max, characterized by correlation coefficients ranging from 0.54 to 0.87 under both scenarios. In contrast, by the end of the century (2071–2100), CWD and the Maximum 1-day precipitation (Rx1day) exhibit a weak correlation; however, Total Precipitation (PRCPTOT), Maximum 5-day precipitation (Rx5day), and Numbers of Heavy Precipitation Days (R10mm) display strong correlations, ranging from 0.55 to 0.85 for both scenarios. All temperature extremes have a relatively strong positive correlation with Q_max except for the coldest night temperature (TNn) during the mid-century in both scenarios. During the end-century, except for the Warmest Night Temperature (TNx), all temperature extremes negatively correlate with Q_max. The results further reveal an increasing trend in PRCPTOT, Rx5day, and R10mm during the mid and end of the century, suggesting a greater likelihood of heavy precipitation events that may elevate the flooding risk in the basin. ,. Therefore, further research is recommended to evaluate the extent and impact of the anticipated flooding in the basin, which will help devise appropriate mitigation strategies.