Predictability of extreme floods

• Applicant: Professor Dr.-Ing. Uwe Haberlandt
• Subject Area: Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
• Term: from 2017 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 278017089

The overall goal of the proposed research in the second phase will remain the investigation of the predictability of extreme floods as function of their catchment and climate drivers considering different space and time scales. Prediction of floods will be defined here as the estimation of flood probability distributions for unobserved locations and/ or future time - periods. Predictability refers then to the quantification and attribution of the uncertainty of this flood prediction. Predictability is extended to the quantification and attribution of the uncertainty of the estimation of multivariate and non-stationary flood probability distributions. Three work packages will be proposed. The first is dealing with the predictability of multivariate flood properties considering non-stationarity from data. The data based univariate regional flood frequency analyses will be extended to multivariate ones, i.e. taking into account flood volume and duration beside the peak flows. The second one is exploring stochastic weather generation using radar data considering non-stationarity. The weather generator which has been developed in phase one will be further advanced by utilizing weather radar data and employed to downscale future climate. It will be applied to generate rainfall and climate scenarios for the model based flood simulations in the third work package. This is investigating the predictability of multivariate flood properties considering non-stationarity from modelling. Flood prediction from modelling will also be extended to the analyses of the multivariate and non-stationarity flood frequency analyses. The outcomes of the three work packages may eventually result in a new generalized statistical model for prediction of flood frequencies directly from rainfall frequencies conditioned on catchment and climate.

• DFG Programme: Research Units
• Subproject of: FOR 2416: Space-Time Dynamics of Extreme Floods (SPATE)