Precipitation extremes will increase in a warming climate, but the response of flood magnitudes to heavier precipitation events is less clear. Historically, there is little evidence for systematic increases in flood magnitude despite observed increases in precipitation extremes. Here we investigate how flood magnitudes change in response to warming, using a large initial-condition ensemble of simulations with a single climate model, coupled to a hydrological model. The model chain was applied to historical (1961–2000) and warmer future (2060–2099) climate conditions for 78 watersheds in hydrological Bavaria, a region comprising the headwater catchments of the Inn, Danube and Main River, thus representing an area of expressed hydrological heterogeneity. For the majority of the catchments, we identify a ‘return interval threshold’ in the relationship between precipitation and flood increases: at return intervals above this threshold, further increases in extreme precipitation frequency and magnitude clearly yield increased flood magnitudes; below the threshold, flood magnitude is modulated by land surface processes. We suggest that this threshold behaviour can reconcile climatological and hydrological perspectives on changing flood risk in a warming climate.

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This study assesses the change of the seasonal runoff characteristics in 98 catchments in central Europe between the reference period of 1981–2010, and in the near future (2011–2040), mid future (2041–2070) and far future (2071–2099). Therefore, a large ensemble of 50 hydrological simulations featuring the model WaSiM-ETH driven by a 50-member ensemble of the Canadian Regional Climate Model, version 5 (CRCM5) under the emission scenario Representative Concentration Pathway (RCP 8.5) is analyzed. A hierarchical cluster analysis is applied to group the runoff characteristics into six flow regime classes. In the study area, (glacio-)nival, nival (transition), nivo-pluvial and three different pluvial classes are identified. We find that the characteristics of all six regime groups are severely affected by climate change in terms of the amplitude and timing of the monthly peaks and sinks. According to our simulations, the monthly peak of nival regimes will occur earlier in the season and the relative importance of rainfall increases towards the future. Pluvial regimes will become less balanced with higher normalized monthly discharge during January to March and a strong decrease during May to October. In comparison to the reference period, 8% of catchments will shift to another regime class until 2011–2040, whereas until 2041–2070 and 2071–2099, 23% and 43% will shift to another class, respectively.

This study introduces a holistic approach for the hydrological modelling of peak flows for the major Bavarian river basins, referred to as Hydrological Bavaria. This approach, intended to develop a robust modelling framework to support water resources management under climate change conditions, comprises a regionalized parameterization of the water balance simulation model (WaSiM) for 98 catchments in high temporal (3 h) and spatial (500 m) resolution using spatially coherent information and an automatized calibration (dynamically dimensioned search–simulated annealing, DDS-SA) for storage components. The performance of the model was examined using common metrics (Nash & Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE)). The simulations provided the means for the calculation of a level of trust (LOT) by comparing observed and simulated high flows with a five, ten, and 20-year return period. These estimates were derived by the Generalized Pareto Distribution (GPD) applying the peak over threshold (POT) sampling method. Results show that the model overall performs well with regard to the selected objective measures, but also exhibits regional disparities mainly due to the availability of meteorological inputs or water management data. For most catchments, the LOT shows moderate to high confidence in the estimation of return periods with the hydrological model. Therefore, we consider the holistic modelling approach applicable for climate change impact studies concerned with dynamic alterations in peak flows.

<p>In recent years, heavy precipitation and flash flood events frequently occurred in Germany. The project HiOS (reference map for surface runoff and flash floods) focusses on the analysis of these events using conceptual lumped precipitation runoff models, distributed raster-based water balance models (LARSIM and WaSiM), as well as a hydrodynamic model internally coupled with infiltration routines (TELEMAC-2D). The objective of our research is to analyze which factors and processes foster flash floods, and how they may be represented in models. We show a comprehensive methodological comparison using simulation results of some events in Bavaria. These do not include erosion and log jam scenarios.</p><p>The catchments distributed across whole Bavaria considering a variety of catchment characteristics and varying in size between 1.2 and 164km². All models are driven by 5 minute pseudo-calibrated radar precipitation data of the German Weather Service (YW product), which are available for entire Germany in a 1km² raster. The distributed water balance models are available using high-resolution cell grids. WaSiM uses a regular grid size of 50m, whereas LARSIM is run using 100m cells and an embedded hydrological response unit scheme. All TELEMAC-2D meshes are built with a standard mesh size of 5m in the catchment and 2m in the settled area of interest, while important hydrodynamic structures are resolved more in detail.</p><p>We want to highlight the variety of applied hydrological and hydrodynamic model approaches of runoff generation and concentration, whereby both, simple conceptual and complex physical methods are included. Runoff generation processes are represented using the SCS-CN method, a modified Lutz-Südbayern approach, a Xinjiang-bucket model combined with a Green&Ampt infiltration routine, as well as a layer-resolving Richards model. Beyond that, some of these consider silting up and soil crack formation. Runoff concentration processes are assessed by constant translation, Strickler flow time index method, a combination of Williams and Kalinin-Miljukov method, as well as finally with two-dimensionally resolved shallow water equations.</p><p>As expected, runoff generation is influenced by land use and soil parametrization. However, the amount of created runoff differs a lot changing the method of simulation. Furthermore, the runoff volume reacts quite sensitive to small changes in the preceding saturation conditions. Runoff concentration is influenced by slope, retention capacity of the flood plain, the network of drainages, as well as the formation of polders by water-crossing structures such as traffic infrastructure. Our results therefore clearly show the individual characteristics of extreme events depending on the catchment properties, which are reflected by the demands concerning the modelling techniques. The findings of this study illustrate the importance of improved radar-derived precipitation observations as well as the need for a spatially distributed and layered soil moisture product to enhance flash flood modelling using hydrological models.</p>