Climate predictions using recent and high-resolution climate models are becoming important for effective decision-making and for designing appropriate climate change adaptation and mitigation strategies. Due to highly variable climate and data scarcity of the upper Blue Nile Basin, previous studies did not detect specific unified trends. This study discusses, the past and future climate projections under CMIP6-SSPs scenarios for the basin. For the models’ validation and selection, reanalysis data were used after comparing with area-averaged ground observational data. Quantile mapping systematic bias correction and Mann–Kendall trend test were applied to evaluate the trends of selected CMIP6 models during the 21st century. Results revealed that, ERA5 for temperature and GPCC for precipitation have best agreement with the basin observational data, MRI-ESM2-0 for temperature and BCC-CSM-2MR for precipitation were selected based on their highest performance. The MRI-ESM2-0 mean annual maximum temperature for the near (long)-term period shows an increase of 1.1 (1.5) °C, 1.3 (2.2) °C, 1.2 (2.8) °C, and 1.5 (3.8) °C under the four SSPs. On the other hand, the BCC-CSM-2MR precipitation projections show slightly (statistically insignificant) increasing trend for the near (long)-term periods by 5.9 (6.1)%, 12.8 (13.7)%, 9.5 (9.1)%, and 17.1(17.7)% under four SSPs scenarios.

In Ethiopia, the impacts of climate change are expected to have significant consequences for agriculture and food security. This study investigates both past (1981–2010) and future (2041–2070) climate trends and their influence on the length of the growing season (LGS) in the North-Western Ethiopian highlands. Climate observations were obtained from the National Meteorological Agency of Ethiopia, while the best performing and highest resolution models from the CMIP5 experiment and RCP6 (Coupled Models Intercomparison Project and representative concentration pathway 6) were used for the analysis. Standard statistical methods were applied to compute soil water content, evaluate climate variability and trends, and assess their impact on the length of the growing season. Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show that the region has experienced cooler years than hotter years in the past. However, in the future, the coolest years are expected to decrease by −1.2 °C, while the hottest years will increase by +1.3 °C. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to receive similar rainfall in the future. On the other hand, the rainfall amount in the season February to May (FMAM) is expected to assist only with early planting. For the season October to January (ONDJ), the rainfall amount may help lengthen the growing season of JJAS if properly utilized; otherwise, the season has the potential to destroy crops before and during the harvesting time. The soil water content changes in the future remain close to those of the past period. The length of growing seasons has less variable onset and cessation dates, while in the future, the length of the growing period (LGP) of 174 to 177 days will be suitable for short- and long-cycle crops, as well as double cropping, benefiting crop production yield in the North-Western Ethiopian highlands in the future.

Flood-attributed damages to infrastructure and public safety are expected to escalate in the future due to climate change, land use change, and associated hydrologic changes. In recent years, the reliability of flood forecasts has increased due to the availability of meteorological and hydrological data and advancements in flood prediction science. However, there is limited effort to apply emerging advanced hydrological models for flood prediction in poorly gauged watersheds. The overall objective of this study is to demonstrate applicability of climate model products to generate reliable flood predictions for data-limited and flood-prone areas. In this study, the most recent high-resolution climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were evaluated to assess the impacts of projected climate change on the flood-prone areas of the Lake Tana basin, Ethiopia. The ensemble means of the top five CMIP6 climate model forcing data were used to calibrate and validate a free open-source, spatially distributed hydrological model known as Wflow_sbm. Model-independent multi-algorithm optimization and parameter estimation tool is implemented for calibration and validation of Wflow. In terms of simulating runoff and flood events, application of Wflow_sbm to the Lake Tana basin provided promising results. This study serves as a major step towards the development and implementation of climate model product-driven hydrological model to assess flooding damages of future climate projections within the poorly gauged Lake Tana basin.

In Ethiopia, climate change risks are anticipated to have significant consequences for agriculture and food security. This study investigated the past (1981-2010) and the future (2041-2070) climate change trends and their influence on crop length of growing seasons in North-Western (NW) Ethiopian highlands. Climate data were obtained from National Meteorological Agency of Ethiopia and the most valid and high resolution CMIP5 rcp6 (Coupled models Intercomparison Project representative concentration path six) model data were extracted and applied for the analysis purpose. Standard statistical methods are then applied to compute soil water content as well as to evaluate climate variability and trends and their impact on crop Length of Growing Season (LGS). Maximum temperature (tasmax) and minimum temperature (tasmin) inter-annual variability anomalies show the region has experienced coolest years than hottest years during the past. However, in the future the coolest years will highly decrease by -1.2oC while the hottest years increase by +1.3oC. During the major rainfall season (JJAS), the area has received an adequate amount of rainfall in the past and is very likely to get similar rainfall in the future. Whereas the February to May (FMAM) season assists only for early planting and October to January (ONDJ) season for lengthen growing season of JJAS if properly utilized. Otherwise, the season will have the possibility to destroy crops before and during the harvesting time. The soil water content change in the future remains close to past condition, The length of growing seasons has less variable onset and cessation dates while the projected length of growing period (LGP) 174 to 177 days will be suitable for short, long cycle crops and double cropping that could benefit crop production yield of NW-Ethiopian highlands in the future.