Evaluating the impact of climate change on sediment yield has become one of the major topics in climate research. The purpose of this study was to investigate sediment yield contribution to lake volume change under changing climatic conditions in the Central Rift Valley Basin. The ensemble mean of five regional climate models (RCMs) in the coordinated regional climate downscaling experiment (CORDEX)-Africa was considered for the purpose of this study. The climate variables (precipitation, minimum and maximum temperatures) in RCMs were bias corrected against observed data (1985–2016) using linear scaling (LS), power transformation (PT), variance of scaling (VS), and quantile mapping (QM). Two emission scenarios, the Representative Concentration Pathways, RCP4.5 and RCP8.5, were considered for the future scenario period (2041–2070). Better results were obtained when the ensemble values of the bias correction methods were used. Hence, the projected values of climate variables after bias correction were used in the Soil and Water Assessment Tool (SWAT) hydrological model to estimate the sediment yield contribution to lake volume change due to climate change. The results show that the average projected precipitation will decrease by 7.97% and 2.55% under RCP4.5 and RCP8.5, respectively. On average, the maximum temperature will increase by 1.73 °C and 2.36 °C under RCP4.5 and RCP8.5, respectively, while the minimum temperature will increase by 2.16 °C and 3.07 °C under RCP4.5 and RCP8.5, respectively. The average annual sediment yield contributions to Lake Ziway were 431.05 ton/km² and 322.82 ton/km² for the Meki and Ketar rivers, respectively, in the historical period (1985–2010). The study also reveals that the annual sediment yield that was estimated for the Meki River was 323 ton/km² and 382 ton/km² under RCP4.5 and under RCP8.5, respectively. The sediment estimations for the Ketar River were 157 ton/km² and 211 ton/km² under RCP4.5 under RCP8.5, respectively. This will decrease the rate of volume change in Lake Ziway by 38% under RCP4.5 and by 23% under RCP8.5. The results show that the life expectancy of the lake is likely to increase under climate change scenarios. This will help water resources managers make informed decisions regarding the planning, management, and mitigation of the river basins.

It is anticipated that climate change will impact sediment yield in watersheds. The purpose of this study was to investigate the impacts of climate change on sediment yield from the Logiya watershed in the lower Awash Basin, Ethiopia. Here, we used the coordinated regional climate downscaling experiment (CORDEX)-Africa data outputs of Hadley Global Environment Model 2-Earth System (HadGEM2-ES) under representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5). Future scenarios of climate change were analyzed in two-time frames: 2020–2049 (2030s) and 2050–2079 (2060s). Both time frames were analyzed using both RCP scenarios from the baseline period (1971–2000). A Soil and Water Assessment Tool (SWAT) model was constructed to simulate the hydrological and the sedimentological responses to climate change. The model performance was calibrated and validated using the coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS). The results of the calibration and the validation of the sediment yield R², NSE, and PBIAS were 0.83, 0.79, and −23.4 and 0.85, 0.76, and −25.0, respectively. The results of downscaled precipitation, temperature, and estimated evapotranspiration increased in both emission scenarios. These climate variable increments were expected to result in intensifications in the mean annual sediment yield of 4.42% and 8.08% for RCP4.5 and 7.19% and 10.79% for RCP8.5 by the 2030s and the 2060s, respectively.

Assessing available water resources and their potential for irrigation water use is vital for sustainable agricultural development and planning. This is particularly of interest in developing countries like Ethiopia, where a small portion of largely accessible land for surface irrigation applications has been utilized, despite the majority of the population relying on agricultural productivity. This study utilized the Dhidhessa River Basin (Ethiopia) as a case study and analyzed the main challenges to balance the sustainable water resources utilization and enhance agricultural productivity of the basin. The study mainly focused on estimating the available water resources and their potential for surface irrigation water use in the basin. This was achieved by utilizing Geographic Information System (GIS)-based tools, a hydrological Soil and Water Assessment Tool (SWAT) model, and a Crop Water and Irrigation Requirements Program of FAO (CROPWAT) model. While the SWAT estimated the water availability in the basin, GIS-tools such as Model Builder were used to map the irrigation potential of the basin. For irrigation water potential assessment, we selected six crops (cabbage, maize, tomato, pepper, groundnut and sugarcane) and estimated their irrigation water requirements using the CROPWAT model. We developed the SWAT model for the period from 1986 to 2012 using the available hydro-meteorological and geo-spatial data. Due to many parameters used in the model, we first performed a parameter sensitivity analysis and identified the most essential/sensitivity parameters via Sequential Uncertainty Fitting-II (SUFI-2). The identified sensitive parameters were subsequently used for model calibration (1989–2000) and validation (2001–2012) procedures achieved via SUFI-2. SWAT was able to reproduce the observed monthly streamflow values with a coefficient of determination (R²) and Nash-Sutcliffe Coefficient (NSE) of 0.85 and 0.87 for the calibration period and 0.91 and 0.89 for the validation period, respectively. The findings generally indicated a “good” performance of the model in simulating the hydrology. The annual available water of the basin is 9.26 billion cubic meters (BCM) whereas the 70% and 80% dependable flow is 7.56 and 6.97 BCM, respectively. Based on the Model Builder of ArcGIS, the SWAT estimated available water can potentially irrigate an area of 259,028 ha for slope less than 8%, 643,162 ha for slopes less than 15% and 1,023,581 ha for slopes less than 30%. Moreover, the irrigation water requirements were calculated by the CROPWAT model for the six selected crops indicated that although the need for irrigation water varies depending on the season, the potential irrigation area of the Dhidhessa River Basin is greater than its irrigated land. Therefore, it is concluded that the basin’s surface irrigation systems need to be expanded to enhance the agricultural productivity and improve the livelihood of the basin’s communities and similar basins elsewhere.

Evaluating climate change impacts and the suitability of potential land resources is crucial for sustainable irrigated agricultural systems. This study applied a multi-criteria analysis supported by the Geographic Information System (GIS) application to produce irrigation suitability maps for the Anger River basin’s (Ethiopia) irrigation command area to optimize its irrigation system. Six irrigation suitability factors, such as distance to water sources (rivers), slope, land use/land cover, soil texture, drainage, and depth, including climate change impacts, were used. These factors were spatially analyzed using a comparison matrix and overlying the factors with 30 m resolutions to estimate the potential irrigable area. About 40% of the study area was classified as moderately to highly suitable for surface water irrigation systems. Moreover, we found that a large proportion of the study area is suitable for surface irrigation system, suggesting the relevance of implementing an enhanced irrigation system for improving the surface irrigation water productivity of the basin. However, future climate change is predicted to negatively affect the irrigation suitable area due to water scarcity. Therefore, this study provides useful information on the irrigation suitability and potential of the study area that could be used to facilitate the water resource development and food security plans.