EGU23-2455, updated on 17 Oct 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Global high-resolution climate change projection and its impacts on global hydrology and hydrological extremes

Solomon Hailu Gebrechorkos, Julian Leyland, and Stephen Darby
Solomon Hailu Gebrechorkos et al.
  • University of Southampton, School of Geography and Environmental Science, Southampton, United Kingdom of Great Britain – England, Scotland, Wales

Hydroclimate extremes have a large societal impact if not appropriately monitored and if site-specific adaptation measures are not developed and modified. The impact of hydroclimate extremes such as floods is projected to increase in the future, demanding site-specific adaptation measures to reduce the impacts. Assessing historical and future changes in local scale hydroclimate extremes and estimating trajectories of change requires higher resolution climate projections than those output from Global Climate Models (GCMs). To improve the coarse resolution and bias of climate data from GCMs, we used a statistical downscaling model. The statistical downscaling model, Bias Correction/Constructed Analogues with Quantile mapping reordering (BCCAQ), provides high-resolution climate data suitable for hydrological extremes. Here, we downscaled seven variables (air pressure, precipitation, air temperature, relative humidity, and maximum and minimum temperature) from 18 CMIP6 GCMs under three SSPs (Shared Socioeconomic Pathways). The downscaled global high-resolution climate data is available at The Centre for Environmental Data Analysis (CEDA,

We used the global hydrological model, WBMsed, with the downscaled climate data and future population projections and dam scenarios to assess changes in hydrology. The downscaling model is calibrated at 0.25° resolution during the historical period (1981-2014) using a high-resolution climate dataset (e.g., MSWEP for precipitation) and showed a strong correlation (>0.85) for monthly climatology of the seven downscaled variables. The climate data used to calibrate the downscaling models, particularly for precipitation, is selected after a comprehensive evaluation of multiple precipitation datasets for simulating river discharge globally. Based on data from ~2400 stations, MSWEP was found to outperform other precipitation datasets in most of the stations.  The results, based on the downscaled data and WBMsed model, shows a mixed change in river discharge in the future; an increase in the Middle East, Africa, Central and South-Eastern USA and a decrease in parts of Europe, South-western USA, and Northern South America) in the 2050s and 2080s. The global average annual river discharge will be higher than the reference period (1981-2014) in the periods 2015-2040, 2041-2070 and 2071-2100 by more than 6%, 9%, and 13%, respectively. Sediment flux, on the other hand, shows a high spatial variability dominated by a decrease in larger rivers and an increase in smaller rivers. Overall, this high-resolution global scale impact assessment study will help identify potential and risk areas for different sectors and allow the development of climate change adaptation measures at a local scale to minimize the impacts of future changes.



How to cite: Gebrechorkos, S. H., Leyland, J., and Darby, S.: Global high-resolution climate change projection and its impacts on global hydrology and hydrological extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2455,, 2023.