17:15 〜 19:15
[HCG24-P03] Assessing Hydrological Uncertainty in the Lake Tana Sub-Basin of the Blue Nile, Ethiopia Using CMIP5, CMIP6, and CORDEX Models
キーワード：Hydrological Uncertainty, Water balance, Lake Tana sub-basin, CMIP5/6
This study examines the uncertainties in hydrological variables within the Lake Tana sub-basin, Blue Nile, specifically focusing on precipitation, evapotranspiration, runoff, and soil moisture. Given the inherent limitations of climate models, the research evaluates the performance of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in representing the basin’s hydrological processes. The analysis utilizes datasets from Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6) and Coordinated Regional Climate Downscaling Experiment (CORDEX) spanning 1976–2005, employing bilinear interpolation to standardize spatial resolution to a 1° × 1° grid. Three ensemble members are selected for CMIP5 and CMIP6, while a single ensemble member represents CORDEX.
Findings reveal that CORDEX exhibits the highest level of uncertainty, followed by CMIP5, whereas CMIP6 demonstrates greater consistency. Model-related uncertainty is the dominant source of variation in hydrological variables, with soil moisture, precipitation, total runoff, and evapotranspiration exhibiting the most significant uncertainties. Notably, uncertainty in soil moisture is most pronounced in the areas surrounding Lake Tana and its adjacent wetlands. Despite advancements in climate modeling, significant biases persist, particularly in regions with complex terrain.
Reducing these uncertainties requires continuous refinement of hydrological process simulations. This study underscores the importance of high-resolution downscaling techniques, particularly the Weather Research and Forecasting (WRF) model, in improving regional climate projections. The findings contribute to a better understanding of hydroclimatic variability in the Upper Blue Nile Basin and provide valuable insights for hydrological research and water resource management strategies.
Findings reveal that CORDEX exhibits the highest level of uncertainty, followed by CMIP5, whereas CMIP6 demonstrates greater consistency. Model-related uncertainty is the dominant source of variation in hydrological variables, with soil moisture, precipitation, total runoff, and evapotranspiration exhibiting the most significant uncertainties. Notably, uncertainty in soil moisture is most pronounced in the areas surrounding Lake Tana and its adjacent wetlands. Despite advancements in climate modeling, significant biases persist, particularly in regions with complex terrain.
Reducing these uncertainties requires continuous refinement of hydrological process simulations. This study underscores the importance of high-resolution downscaling techniques, particularly the Weather Research and Forecasting (WRF) model, in improving regional climate projections. The findings contribute to a better understanding of hydroclimatic variability in the Upper Blue Nile Basin and provide valuable insights for hydrological research and water resource management strategies.