Hydrological modeling for climate-change impact assessment:
Research Group: Prof. Jan Seibert
How will future climate change affect evapotranspiration, precipitation and runoff regimes?
The sensitivity of regional hydrology to variability in climate conditions makes future climate change projections essential for the assessment of possible threats related to variations in the hydrologic cycle. Only with information about future changes in the patterns of main drivers of the hydrologic cycle (e.g., temperature, water vapor and precipitation) it is possible to analyze future changes in river streamflow. This information can be provided by global climate models (GCMs) that are generally used to simulate complex climate processes at a rather coarse scale with grid resolutions of currently 100-250 km. For regional impact studies, however, such a resolution is insufficient, because it is lacking detailed regional information. Typical hydrological models require fine-scale climate parameters and, thus, downscaling procedures are required in order to overcome the scale issue. A variety of downscaling methods is available to transfer large-scale climate variables to a regional scale, including statistical and dynamical approaches. Yet, there are significant differences in their performance. Although both GCMs and RCMs have been frequently used in recent years to provide hydrologists with climate parameter for hydrological predictions at global and local scales, this is still a relatively new field of research. Coherent scientific standards have not yet been established and there is no such thing as ‘common practice’ in terms of how to best apply climate model simulations for impact studies. The quality of climate model output is still a much debated subject amongst climate modelers. Furthermore, the uncertainties involved in the modeling process are still a common problem for impact analyses.
Although researchers nowadays are aware of the uncertainty and variability introduced at different parts of the modeling chain, it is still difficult to handle, decrease and interpret them in a proper way. Therefore, focus of this project is on the assessment of climate change impacts on regional hydrology with consideration of uncertainties in the modeling chain and variability of the resulting hydrological simulations. For this, several different ways of transferring large-scale information from climate models to the catchment scale for hydrological climate change impact studies are evaluated. The variability of seasonal streamflow and flood peak predictions caused by the use of different approaches to downscale precipitation and temperature data from different GCMs for meso-scale catchments in Sweden are investigated. We are using the downscaled higher-resolution precipitation and temperature values to simulate daily streamflow for a control period (1961-1990) and a future period (2071-2100) with the rainfall-runoff model HBV.