Accurate measurement of precipitation is vital to investigate the spatial and temporal patterns of precipitation at various scales for rainfall-runoff modeling. However, accurate and consistent precipitation measurement is relatively sparse in many developing countries like Ethiopia. Nevertheless, satellite precipitation products may serve as important inputs for modeling in an area with scarce field data for a wide range of hydrological applications. In this study we evaluate the high-resolution satellite rainfall products for hydrological simulation, the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA_3B42v7) satellite rainfall products for stream flow simulation at daily temporal and 0.25° × 0.25° spatial resolution. The study area is located in Dabus watershed, Abbay basin, Ethiopia. We applied a nonlinear power law to remove the systematic error of satellite precipitation estimates for input into HEC-HMS hydrological model for runoff generation. The performance of the satellite rainfall and hydrological model was evaluated using Nash–Sutcliffe efficiency (ENS), coefficient of determination (R2), relative volume error (RVE), and percentage error of peak flow objective functions. The result of HEC-HMS model performance revealed R2 of 0.78, ENS of 0.69 for CHIRPS_2 and R2 of 0.79, ENS of 0.76 for TMPA_3B42v7 satellite rainfall products during calibration periods. Our result indicated that the HEC-HMS model well predicated catchment runoff for both satellite precipitation products. The study shows that the model performance was significantly improved when bias-corrected satellite rainfall input replaced than the original uncorrected satellite products. Overall, our study showed that gauge-based simulation outperformed than satellite in terms of all objective functions over the study area.

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In Ethiopia soil erosion and land degradation has become a key issue, because of roughed and steep slope topography that soil erosion become accelerating. The main objective of this study was to identify soil erosion hotspot areas in Dengora and Meno watersheds using Revised Universal Soil Loss Equation (RUSLE) and Multi Criteria Decision Analysis (MCDA) techniques. To achieve such objective RUSLE model was used to estimate potential soil losses by utilizing information on Soil, land use/cover, topography, and climatic data. MCDA technique considered land use, soil type, topographic wetness index, stream power index and potential location of gullies. The factors were weighted using pair-wise comparison matrix and weights were combined using Weighted Overlay. Based on RUSLE model, the average annual soil loss of Dengora and Meno watersheds were reaches up to 223.97and 256.09-ton ha-1yr-1 respectively. In Dengora watershed 70.4%, 18.7%, 10.74% and 0.14% and Meno watershed 76%, 16.54%, 7.3% and 0.14% of the total watershed area slightly, moderately, highly and very highly sensitive to soil erosion respectively. On the other hand, GIS based MCDA technique reveals that in Dengora watershed 9.7%, 64.5%, 18% and 7.8% and Meno watershed 6.1%, 71.3%, 23.23% and 0.375% of the total watershed area was highly, moderately, slightly and currently not sensitive to soil erosion respectively. Based on validation, field level observation, MCDA model prediction was more accurate than RUSLE. Both of the watersheds were at moderate risk. Bottomlands of the watersheds under were highly sensitive areas for erosion. Therefore, immediate attention for soil and water conservation practices.

This study was conducted in the Lower Areb small-scale irrigation scheme for one crop season from March to May 2018 to evaluate the hydraulic performance of the scheme by estimating the hydraulic performance indicators, physical performance indicators, and maintenance performance indicators. The primary data including water flow rate, soil physical properties, and water infiltration were collected. The secondary data collected were climatic, crop data, and data from different reports and design documents including the irrigation water users' interviews. The hydraulic performance of the irrigation scheme 2 | P a g e was evaluated by estimating adequacy, efficiency, dependability, and equity indicators at nine selected offtakes; three each at the head, middle, and tail reaches of the scheme. The physical performance and maintenance indicators were determined using the irrigation ratio, the sustainability of the irrigated area, the effectiveness of infrastructure, and the water surface elevation ratio. The data were analyzed by using CROPWAT 8.0, ARC GIS 10.1 software, and Microsoft Excel 2013. The overall average values of adequacy, efficiency, dependability, and equity were found to be 0.89. 0.91, 0.096 and 0.07 respectively. Therefore, dependability, equity, and efficiency were under good condition and adequacy was under fair condition. The irrigation ratio and sustainability of irrigated areas were 54% and 123% respectively. The effectiveness of infrastructure and water surface elevation ratios were 73.33% and 94% respectively.

In Ethiopia soil erosion and land degradation has become a key issue, because of roughed and steep slope topography that soil erosion become accelerating. The main objective of this study was to identify soil erosion hotspot areas in Dengora and Meno watersheds using Revised Universal Soil Loss Equation (RUSLE) and Multi Criteria Decision Analysis (MCDA) techniques. To achieve such objective RUSLE model was used to estimate potential soil losses by utilizing information on Soil, land use/cover, topography, and climatic data. MCDA technique considered land use, soil type, topographic wetness index, stream power index and potential location of gullies. The factors were weighted using pair-wise comparison matrix and weights were combined using Weighted Overlay. Based on RUSLE model, the average annual soil loss of Dengora and Meno watersheds were reaches up to 223.97and 256.09-ton ha-1yr-1 respectively. In Dengora watershed 70.4%, 18.7%, 10.74% and 0.14% and Meno watershed 76%, 16.54%, 7.3% and 0.14% of the total watershed area slightly, moderately, highly and very highly sensitive to soil erosion respectively. On the other hand, GIS based MCDA technique reveals that in Dengora watershed 9.7%, 64.5%, 18% and 7.8% and Meno watershed 6.1%, 71.3%, 23.23% and 0.375% of the total watershed area was highly, moderately, slightly and currently not sensitive to soil erosion respectively. Based on validation, field level observation, MCDA model prediction was more accurate than RUSLE. Both of the watersheds were at moderate risk. Bottomlands of the watersheds under were highly sensitive areas for erosion. Therefore, immediate attention for soil and water conservation practices.