Evaluation of the Impacts of Land Use/Land Cover and Climate Change on Flood Occurrence in the Gumara Watershed Upper Blue Nile Basin Ethiopia
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Date
2025-08-01
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Addis Ababa University
Abstract
Floods are among the most destructive natural hazards worldwide, with their frequency and intensity exacerbated by changes in land use/land cover (LULC) and climate. Vegetation cover and climatic variables are also interlinked, further influencing hydrological processes. Thus, this study evaluated the impacts of LULC and climate changes on flood occurrence and explored the relationships between vegetation cover and climate variables. Extreme rainfall analysis and vegetation‒climate relationships were assessed at the basin scale in the Upper Blue Nile (UBN) Basin of Ethiopia, whereas LULC change detection and flood modelling were conducted at the watershed scale in the Gumara watershed, which is located in the UBN Basin. The study comprises four interrelated specific objectives. First, the performances of eight CMIP5 and eight CMIP6 general circulation models (GCMs) in reproducing observed extreme rainfall indices (ERFIs) for the baseline period (1981–2005) were evaluated. The GCMs were assessed via statistical metrics (correlation, RMSE, and PBIAS) and ranked via the technique for order preferences by similarity to ideal solution (TOPSIS). The four best-performing models (MIROC5, MRI-CGCM3, CanESM2, and MPI-ESM-LR from CMIP5 and MPI-ESM1-2-LR, MRI-ESM2-0, CNRM-CM6-1, and BCC-CSM2-MR from CMIP6) were bias-corrected, and their ensembles were used for projecting extremes for the future period (2031–2080) under the RCP4.5, RCP8.5, SSP2-4.5, and SSP5-8.5 scenarios. Second, historical and future LULC changes were analysed in the Gumara watershed. LULC maps for 1985, 2000, 2010, and 2019 were generated via a random forest classifier on the Google Earth Engine (GEE) platform, which achieved high overall accuracies. Future LULC maps for 2035 and 2065 under business-as-usual (BAU) and governance (GOV) scenarios were projected via the Cellular Automata–Markov (CA-Markov) model. The results revealed considerable expansion of cultivated land and settlements under BAU and a relative increase in forest cover under GOV. Third, rainfall-runoff modelling was conducted in the Gumara watershed via the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS) for various return periods and combined LULC and climatic scenarios. CombinedThe combined impacts of LULC and climate changes on annual maximum (AM) flows were quantified, indicating an increasing trend under future scenarios. In particular, the highest flow is expected under the SSP5–8.5 (2056–2080) climate scenario combined with the BAU-2065 land use scenario. Additionally, flood source area identification (FSAI) was performed in this part of the study on the basis of the unit flood response (UFR) approach to prioritize subwatersheds contributing most to peak flows. Finally, flood inundation mapping was conducted by integrating synthetic aperture radar (SAR)-based change detection and thresholding methods on the GEE platform and HEC-RAS 2D hydrodynamic modelling. Sentinel-1 SAR images were used to map flood inundation from 2017–2021, and the HEC-RAS model was calibrated and validated via SAR-derived flood inundation maps. Future inundation maps indicated increased flood extents, primarily attributed to LULC and climate changes. Overall, this study provides a comprehensive assessment of how coupled LULC and climate changes influence flood risk and how climatic variables affect vegetation cover. The findings offer a scientific basis for flood risk management, watershed conservation planning, and policy formulation under future climate and land development scenarios. Moreover, the methods and results presented herein provide a valuable framework for similar studies in other regions undergoing rapid environmental and climatic changes
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Keywords
Flood Occurrence, Land Use/Land Cover Change, Climate Change, CMIP5, CMIP6, Extreme Rainfall Indices, HEC-HMS, HEC-RAS, SAR, GEE, Gumara Watershed, Upper Blue Nile Basin