Assessing the impact of climate change on streamflow in catchments across the United States, using an easily reproducible modeling approach

Abstract

In this thesis, an easily reproducible modeling approach was developed for assessing the climate change impact on streamflow. This approach was tested by using it to assess the impact of climate change on streamflow in 5 different contrasting catchments across the United States. Many studies show that climate change is expected to influence streamflow regimes all over the world. However, these studies are often difficult to reproduce because the modeling approaches used are usually only locally applicable. In the approach used in this study, hydrological model calibration and validation were done using open-accessible ERA5 forcing together with observed streamflow data provided by the GRDC. The model performed best in a mountainous catchment, while the worst performance was found in a dry catchment and a catchment containing several lakes. The low performances here are mainly caused by imperfect forcing data used for calibration and the neglection of lake processes. The climate change impact analysis used forcing from two CMIP6 models with the SSP245 and SSP585 scenarios. The projections showed significant changes in streamflow in colder regions, which are most likely related to changing snow melt processes. The main finding in warmer regions is that streamflow is generally expected to decrease in the drier periods. Changes of streamflow in these regions are most likely related to changes in precipitation and evaporation processes. However, results remain very uncertain due to disagreements between climate models and sometimes doubtful performance of the hydrological, caused by oversimplification of the model and imperfect ERA5 calibration data. The designed modeling approach facilitates reproducibility of climate change impact analyses in a wide range of catchments using different climate models and scenarios. Its use makes it easier to expand similar analyses to a large ensemble of these aspects.