@phdthesis{,
    author = {Teklu Toni, Abebe},
    title = {Modeling Basin Dynamics under Changing Climate and LULC on Hydrological Processes in Wabi Shebele River Basin, Ethiopia},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2024},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {Climate change, LULC, Headwater catchment, SWAT, GCMs, WSRB},
    abstract = {Climate change has become a noticeable mega-trend in the 21ˢᵗ century, with widespread adverse effects on the environment and socioeconomic development. In Ethiopia, where over 85% of the population depends on agriculture, the vulnerability to climate change is high. The agrarian sector faces significant threats from shifting weather patterns and long-term climatic variations, impacting the livelihoods of millions in the country. Thus, this study aimed on assessing hydroclimatic trends, climate change, and the potential impacts of future climate change and land use land cover (LULC) dynamics on headwater catchments in the Wabi Shebele River Basin (WSRB) in Ethiopia. Historical hydro-climatic variability and trends were analyzed using the modified MK test and the Sen Slope estimator. Rainfall and maximum temperature exhibited mixed trends, while minimum temperature showed a clear increasing trend, except in the highland part of the basin. Streamflow displayed mixed trends across seasons and gauging stations. To project future climate change, eight CMIP6 Global Climate Models (GCMs) were employed under four shared socioeconomic pathways (SSPs) scenario. Future climate data were downscaled and bias-corrected, revealing an anticipated increase in mean annual precipitation, maximum and minimum temperatures across various Agro-Climatic Zones (ACZs). Notably, the rate of change in minimum temperature exceeded that of maximum temperature in most ACZs. The research also investigated land use land cover changes using Landsat images and the Semi-Automatic Classification Plugin. Significant transformations were observed over the past 30 years, including the depletion of natural vegetation and an increase in cultivated and built-up areas. Future projections using the Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) model indicated further increases in built-up areas, dense shrubs, grasslands, agricultural land, and barren land, with reductions in water bodies, forestland, and open shrublands. The SWAT model, a semi-distributed river basin model, was calibrated and validated to simulate hydrological processes. The model effectively captured streamflow pattern within acceptable ranges. Hydrological responses to climate change and land use land cover alterations in six headwater catchments were predicted using the calibrated model. The results demonstrated that observed changes contributed to increased streamflow, with projected climate changes exerting a greater impact than observed land use land cover changes. The combined impact of climate and land use land cover changes resulted in a substantial increase in streamflow across all studied headwater catchments. Overall, valuable insights into the complex interactions between hydroclimatic variabilities, climate and land use land cover changes, and their cumulative effects on streamflow in the WSRB were provided by this study.},
    note = {},
    
    school = {Universität der Bundeswehr München},
    
}