Riktad osäkerhetsminskning inom hydrologisk klimatforskning för robusta avrinningssimuleringar
Tidsperiod: 2018-01-01 till 2021-12-31
Projektledare: Claudia Teutschbein
Bidragstyp: Bidrag för anställning eller stipendier
Budget: 3 180 000 SEK
Much of the present effort to understand and project climate change impacts on water resources is based on complex serial modeling chains, which typically involve choosing a greenhouse gas emission scenario and a global climate model, whose simulations are then used to drive regional climate models (RCMs). Then, RCM-simulated variables are commonly used as input to hydrological models, which in turn provide streamflow simulations in a changing climate. However, previous research has identified five major knowledge gaps in such serial modeling chains:Considerable biases in RCM-simulated variables call for bias correction methods, which typically do not maintain physical links among variables.Present bias correction methods rely on the crucial (but likely not met) assumption of bias stationarity.Hydrological model structure uncertainty is large and it is unclear how the research community can benefit in the best way from hydrological multi-model ensembles.The effects of model representation of specific processes (e.g., evapotranspiration) on the overall hydrologic model response still remains vague.Stationary hydrological model parameters do not allow a response to physical changes in the catchments caused by climate change.Thus, the proposed project aims at filling these existing knowledge gaps and at strengthening the basis for robust projections of future hydrological climate change impacts by developing new dynamic and multi-dimensional methods to reduce uncertainties.