Climate change is one of the current global threats and the topmost challenges. This study aims to investigate the climate change effect on streamflow in the Gelana watershed using the soil and water assessment tool (SWAT) model for three consecutive periods of 2031–2050, 2051–2070, and 2071–2090. Climate variables were downscaled from two regional climate models (RCMs) (RACMO22T and RCA4) from CORDEX-Africa under representative concentration pathway (RCP4.5 and RCP8.5) scenarios. RCMs were evaluated using four statistical indicators and performed very well. Power transformation and distribution mapping methods were used to correct biases of precipitation and temperatures, respectively. The 19 SWAT model-sensitive parameters were transferred from the gauged donor watersheds to the ungauged watershed outlet by using the principal component analysis coupled with the stepwise multiple linear regression. The ensemble mean of RCMs revealed that the maximum and minimum temperatures and potential evapotranspiration were predicted to increase up to 3.48 °C, 4.19 °C, and 17.85%, respectively, in the period of 2071–2090 under the RCP8.5 scenario. These changes translate to possible reductions in the mean annual rainfall and streamflow up to 15.12 and 44.14%, respectively, with a consequent higher decline of surface runoff by 22.23%, groundwater by 42.54%, and water yield by 35.89% in the period of 2051–2070 under the RCP4.5 scenario. The projected rainfall and streamflow are expected to face a higher decline in wet seasons. Detections of trends in hydro-climatic variables were performed by using the Mann–Kendall test. Hence, these projection scenarios should be of interest to river users and water resource managers in the Gelana watershed.

Urban drainage infrastructures are facing critical challenges due to a lack of integrated asset management, periodic maintenance, improper design, and construction methodologies. The objective of this study is to understand the urban drainage challenges and assess the failure causes and their impacts to recommend possible mitigation measures. Drainage failure causes and impacts are analyzed using the analytical hierarchy process (AHP) qualitative multicriteria decision model after conducting technical group discussions, interviews, and technical field surveys. The assessment was performed by taking representative samples from both cross- and longitudinal drainage infrastructures. The AHP analysis results showed that approximately 35.5% and 28.6% of failure causes are debris and various solid wastes for cross- and longitudinal drainage structures with correlation coefficients of 0.93 and 0.95, respectively. The result showed that design and construction defects are the second major failure causes. The research results showed that urbanization has a direct relationship with major drainage failure causes, resulting from man-made debris and solid waste clogging. On the other hand, drainage failure caused by siltation, drifts, and vegetation is higher in newly developing semi-urban and agricultural areas. The number of barrels in cross-drainage structures also contribute significantly to cross-drainage failure by creating a flow barrier due to the intermediate columns. The drainage failure impact assessment result showed that both cross- and longitudinal drainage failures primarily impact road pavement following transport disruption and traffic accidents, accounting for 38.5%, 18%, and 16%, respectively. Our research recommended that the mitigation measures for drainage failure are proper asset management and maintenance, appropriate construction supervision, and awareness creation, with weights of 36.3%, 15.5%, and 15.3%, respectively. As a drainage problem mitigation measure, the longitudinal drainage analysis results showed that the provision of a combination of cross-fall slopes, gutter slopes, and local depressions at the inlets can contribute to an increase in the trapping efficiency of the drainage system by 50%, which can reduce surface flooding substantially.

Climate change is becoming a global concern, dictating the water resource availability of a certain region. This study focuses on the impact of climate change on the streamflow of the Melka Wakena reservoir in the Upper Wabi Shebelle sub-basin using a Soil Water Analysis Tool (SWAT). The climate model variables (precipitation and temperature) are obtained from the Coordinated Regional Downscaling Experiment (CORDEX-Africa) and applied under representative concentration pathway (RCP4.5) and (RCP8.5) scenarios. Bias correction was applied to the climate variables before transferring to the hydrological model (SWAT) to simulate discharge. The performance measures R2, NSE, and Percent Bias (PBIAS) for calibration and validation were 0.69, 0.65, and −5.10 and 0.65, 0.61, and −9.81, respectively. Streamflow was simulated for two consecutive periods from 2021 to 2050 and from 2051 to 2080 for both scenarios and compared with the base period from 1986 to 2015 to explore the impact of climate change on inflows to the reservoir. The result obtained showed that the precipitation was predicted to be mildly decreasing, whereas overall annual flow was projected to be insignificantly decreasing under RCP4.5 and RCP8.5 scenarios. The impact of climate change on the water resource of the study area was predicted to be a statistically insignificant reduction.

Modeling soil erosion, sediment yield, and runoff are crucial for managing reservoir capacity, water quality, and watershed soil productivity. However, the monitoring and modeling of soil erosion and sedimentation rates in developing countries such as Ethiopia is not well practiced; thus, the reservoir capacity is diminishing at faster rates. In this study, the soil erosion, sediment yield, and runoff in the Megech watershed, Upper Blue Nile Basin, Ethiopia were modeled using the physically-based geospatial interface, the Water Erosion Prediction Project (GeoWEPP). The GoWEPP model was calibrated and validated at the Angereb sub-watershed and simulated to representative sites to capture the spatiotemporal variability of soil erosion and sediment yield of the Megech watershed. The model parameter sensitivity analysis showed that the hydraulic conductivity (Ke) for all soil types was found to be the dominant parameter for runoff simulation, while rill erodibility (Kr), hydraulic conductivity (Ke), critical shear stress (τc), and inter rill erodibility (Ki) were found to be sensitive for sediment yield and soil loss simulation. The model calibration (2000–2002) and validation (2003–2004) results showed the capability of the GeoWEPP model; with R² and NSE values, respectively, of 0.94 and 0.94 for calibration; and 0.75 and 0.65 for validation. In general, the results show that the sediment yield in the study watershed varied between 10.3 t/ha/year to 54.8 t/ha/year, with a weighted mean value of 28.57 t/ha/year. The GeoWEPP model resulted in higher sediment value over that of the design sediment yield in the study basin, suggesting the implementation of the best watershed management practices to reduce the rates of watershed sediment yield. Moreover, the mean soil loss rate for the Angerb sub-watershed was found to be 32.69 t/ha/year.

This study evaluated the best management practices on how to manage soil losses from catchment and reduce sediment load into a dam reservoir. This study aimed to evaluate the relationship of runoff, soil loss, and sediment yield with best management practice (BMP) scenarios in the GeoWEPP environment for the selected three micro-watersheds (hot spot areas) in the Megech watershed, upper Blue Nile Basin. The impacts of four agricultural BMP scenarios, including forest five years old, corn, soybean; wheat, alfalfa (4 yr) no till; corn, soybean, wheat, alfalfa (4 yr) conservation till; and winter wheat mulch till, on soil loss, runoff, and sediment yield were quantified. The results revealed that soil loss ranges between 41.45–66.11 t/ha/year and sediment yield rates ranges between 36.5–54.8 t/ha/year with the baseline situation (conventional tillage condition) were found to be higher than the tolerable soil loss (10 t/ha/year) in the region. Implementing BMPs on the crop land of the micro-watersheds has positive impacts on all variables’ runoff, soil loss, and sediment yield reductions. Among the implemented BMPs, forests with a five-year perennial (agroforestry) option showed the highest rate of reduction for all runoff, soil loss, and sediment yield, but no cost benefit analysis was included in this study to choose among the BMPs. This study also identified that agricultural BMPs play a great role in reducing runoff, soil loss, and sediment yield in the Megech watershed to minimize on- and off-site impacts. In general, it is important to consider how cost benefit analysis will change throughout project’s implementation among the selected BMP scenarios at the watershed level in the future.