Drought is a frequent occurrence in semidesert areas of southern Ethiopia that significantly affect regional, social, economic, and environmental conditions. Lack of rainfall monitoring network, instrument measurement, and failure are major bottlenecks for agro-and hydroclimate research in developing countries. The objectives of this study were to evaluate the performance of CHIRPS rainfall product and to assess meteorological drought using SPI for the period 2000 to 2020 over Gamo Zone, southern Ethiopia. The performance of CHIRPS v2 was assessed and compared to station observations (2000–2020) in the study domain to derive SPI on a three-month timescale. The Pearson correlation coefficient (R), bias, probability of bias (PBias), mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and Nash simulation efficiency (NSE) values across the zone for CHIRPS v2 were found to be 0.88, 1.02, 2.56, 0.25, 22.41, 33.14, and 0.77, respectively. The results indicate that CHIRPS performed good ability to analyze the drought characteristics in the Gamo Zone. The spatial and temporal distribution method of meteorological drought has been evaluated using the Climate Data Tool (CDT). The Standardized Precipitation Index (SPI) was computed using the gamma distribution method. The magnitude of (SPI-3) of monthly and seasonal (MAM) meteorological drought in the zone from 2000 to 2020. The result shows that the known historic drought years (2014, 2015, 2010, 2009, and 2008) were indicated very well. Furthermore, sever and extreme droughts were observed in 2008 and 2009 with drought duration of 6.7 and 6.3, respectively, in most areas of the zone. Hence, this study revealed that CHIRPS can be a useful supplement for measuring rainfall data to estimate rainfall and drought monitoring in this region.

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.

Climate change poses a significant threat to water resources in Taiwan, particularly impacting agricultural areas. This study investigates the influence of climate change on the occurrence of consecutive dry days (CDD) using historical data (1960–2014) and Coupled Model Intercomparison Project phase 6 (CMIP6) future projections (SSP1‐2.6 to SSP5‐8.5). Our analysis of historical trends reveals a strong spatial dependence of variation in seasonal CDD, with increasing trends (0.5–1.5 days per decade) in southern and central Taiwan during autumn, in contrast to decreasing trends (−0.5 days per decade) in southern Taiwan during winter. Projections suggest that under high‐emission scenarios (SSP3‐7.0 and SSP5‐8.5), prolonged CDD will occur across most of Taiwan during the dry seasons (spring, autumn, winter) by the late 21st century. An SSP5‐8.5 scenario could lead to a further increase of 1.2 days per decade. This projected increase in seasonal CDD is linked to anticipated changes in the East Asian monsoon system, including seasonal precipitation patterns and atmospheric circulation. In contrast, projected low‐emission scenarios (SSP1‐2.6 and SSP2‐4.5) suggest a return towards baseline spring CDD levels, and the potential for persistence of the spring rainband over Taiwan. Furthermore, correlation analysis demonstrates a consistent link between atmospheric oscillations (i.e., AMO, PDO and ENSO) and prolonged spring CDD in specific regions in Taiwan. These findings suggest that monitoring climate indices informs spring drought mitigation strategies in Taiwan.