Browsing by Author "Adane Abebe (PhD)"

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    Assessment of Surface Water Potential and Demand of Upper Genale River Basin under the Impact of Climate and Land Use Land Cover Change, Ethiopia
    (Addis Ababa University, 2024-08) Mehari Shigute; Tena Alamirew (PhD); Adane Abebe (PhD)
    Understanding how climate and land-use changes affect water availability and demand in a watershed is crucial for planning and managing water resources effectively. This study addresses this need by examining the Upper Genale River Basin in Ethiopia. It investigates long-term trends in rainfall and temperature to inform agricultural water management. It also analyzes the impact of land use land cover (LULC) change on water flow and future climate change on water resources. Finally, the study assesses the potential for developing water resource systems and future water demand scenarios, providing valuable insights for adaptation and mitigation strategies in the basin. To achieve these objectives, long-term climate data from the Ethiopian National Meteorological Service Agency (NMA) were collected, and 30 m-resolution Landsat imageries were used to assess the impact on watershed hydrology and analyze the dynamics of LULC change. Future climate scenarios for the 2021-2050 and 2051-2080 time periods were developed using four different GCM-RCM combinations from the CORDEX-Africa projections under the RCP 4.5 and RCP 8.5 scenarios. Additionally, to investigate water resource demand and allocation under current and future scenarios, socioeconomic data (population, livestock, irrigation) was collected from federal and regional sources. The Coefficient of Variation (CV), Standard Rainfall Anomaly (SRA), and Precipitation Concentration Index (PCI) were used to evaluate the observed climate characteristics of rainfall and temperature. In addition, the MannKendall test and Sen's slope estimator were used to assess the trend and magnitude of changes in rainfall and temperature. The Soil and Water Assessment Tool (SWAT) model was calibrated and validated in SWAT-CUP using the sequential uncertainty fitting (SUFI-2) algorithm using monthly measured flow data. The model performed well, with a coefficient of determination (R2 ) > 0.74, NashSutcliffe efficiency (NSE) > 0.72, and percent bias (PBIAS) ranging from -5% to 5% for the calibration and validation periods. The annual, winter, spring, summer, and autumn rainfall variability in the basin was high, with coefficients of variation (CVs) of 20%, 89%, 30%, 45%, and 32%, respectively. The standardized rainfall anomalies indicated that the basin had a drier season than a wet season. The mean length growing season ranges in 43 to 79 days in Belg and 38 to 170 days in Kiremt seasons. Most rainfall stations showed no significant increasing trend in annual, summer, and autumn rainfall, but there was a decreasing but statistically insignificant trend in spring rainfall at all stations except Bensadaye, Bore, Telamokentise, and Yirba Muda. The analysis result also shows to minimize yield reduction and crop failure during spring and autumn supplementary irrigation is essential. For instance, maize and sorghum varieties require supplementary irrigation of up to 202 mm and 252 mm, XXII respectively. Over the past 30 years, annual and seasonal maximum and minimum temperatures in the basin have been increasing trend in most stations, and the landscape has changed significantly. Satellite images analyses show that settlements, cultivated land, and bare land have all increased in area from 0.16% to 0.28%, 24.4% to 47.1%, and 0.16% to 0.62%, respectively, while forests, shrublands, and grasslands have decreased from 29.6% to 13.5%, 23.9% to 19.5% and 21.8% to 18.9%, respectively, in the area. These changes in LULC have affected the water cycle in the basin, leading to increased runoff and total water yield, and decreased lateral and groundwater flow. Under the two RCPs, annual and seasonal precipitation is expected to decrease while temperatures rise during the 2030s (2021- 2050) and 2060s (2051-2080). The simulation result indicated a significant change in hydrological aspects. Under MPI-ESM-LR, EC-EARTH, and MIROC5 climate models, the study area's total water yield, surface runoff, ground waterflow, and lateral flow all decrease annually. However, all climate models (MPI-ESM-LR, EC-EARTH, CNRM-CM5, and MIROC5) show an increase in evapotranspiration of up to 8.1% due to an increase in temperatures. The decrease in rainfall and increase in temperatures will reduce annual water yield, surface runoff, ground waterflow, and lateral flow by up to 39.8%, 39%, 50%, and 40%, respectively, for the entire study basin. The observed and predicted annual and seasonal rainfall variability, as well as rising temperatures and LULC modification over the study area, have a significant impact on hydrological processes, resulting in droughts, flooding, and extreme water loss due to evaporation. These changes have consequences for agricultural and livestock production, domestic water supply, and municipal services. In addition, the WEAP model was used to evaluate water demand and allocation under different scenarios, the results predict a dramatic rise in water demand across the upper Genale River basin by 2050, driven by population growth, irrigation expansion, and the climate change. Water scarcity is expected to worsen, especially for irrigation, due to combined pressures from increasing consumption, potential climate change impacts, and limited water resources. As a result, natural resource managers, policymakers, and stakeholders in the study area will be better able to design and implement effective and sustainable land use planning and water resource management in order to deal with the ongoing impacts of climate, LULC change, and variability. It is also critical to develop strategic adaptation measures and a longterm approach to climate risk management.
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    Evaluating the Land Use and Land Cover Change Impact on Streamflow Kulfo Catchment
    (Addis Ababa University, 2021-09) Assebe Anja; Adane Abebe (PhD)
    Stream flow is one of the major hydrological cycle components which can be altered and /or affected by different factors. From these, the Land Use Land Cover change is one of the main factors to alter and change the stream flow characteristics. Therefore, in this study, the LULC change impact on the stream flow was evaluated using the SWAT model for the case of Kulfo catchment which is situated in the Southern part of Ethiopia. Sensitivity, calibration, and validation were also conducted using sequential uncertainty fitting–version 2 (SUFI-2) in SWAT-CUP (Calibration and Uncertainty program) using historical streamflow data for each of the land use land cover years. Four different algorithms (SVM, CART, RF, and Navia's) which are existed in the Google Earth Engine were compared and the best performed was selected to generate the time-series LULC maps of, (1986, 2000, 2016, and 2020), the study area. The accuracy of these algorithms was evaluated corresponding to GCPs collected from the field. High resolution (30m) Landsat images which are thematic mapper (TM), Enhanced thematic mapper plus (ETM+), and Operational land imager (OLI) were used with the aid of historical trends and ground-based data used to train and validate the LULC maps generated from Google Earth Engine platform. As a result, the SVM algorithm was performed better in LULC classification than other algorithms which are compared in this study. In the analysis period of this study, the Vegetation land cover area has decreased from 18.81% to 3.1%, the agricultural land was increased from 19.44% to 57.12%, whereas the shrub land area has been decreased from 34.18% to 14.73%. Therefore, the effect of these LULC changes on stream flow was evaluated using Soil & water assessment tool (SWAT) model and high mean monthly and seasonal streamflow variability was observed in the analysis period of this study. These variabilities were increased from 6.72% to 7.85% monthly. In seasonal variability, the stream flow has decreased trend for all of the seasons (Kiremt, Belg, and Bega) from the year 2016 to 2020 whereas increased trend for the period of 2000 to 2016 (Kiremt, Belg and Bega). The Results from the calibration resulted in an acceptable range (0.6, 0.8, 0.75, and 0.75 for NSE and 0.75, 0.76, 0.79, and 0.81 for R2) between observed and simulated streamflow respectively. The results of validation were also fallen in the acceptable range (0.72, 0.6, 0.74, and 0.75 for NSE and 0.8, 0.75, 0.73, and 0.8 for R2) observed and simulated streamflow respectively.