@phdthesis{Falter2016,
  author    = {Falter, Daniela},
  title     = {A novel approach for large-scale flood risk assessments},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-90239},
  school      = {Universit{\"a}t Potsdam},
  pages     = {95},
  year      = {2016},
  abstract  = {In the past, floods were basically managed by flood control mechanisms. The focus was set on the reduction of flood hazard. The potential consequences were of minor interest. Nowadays river flooding is increasingly seen from the risk perspective, including possible consequences. Moreover, the large-scale picture of flood risk became increasingly important for disaster management planning, national risk developments and the (re-) insurance industry. Therefore, it is widely accepted that risk-orientated flood management ap-proaches at the basin-scale are needed. However, large-scale flood risk assessment methods for areas of several 10,000 km² are still in early stages. Traditional flood risk assessments are performed reach wise, assuming constant probabilities for the entire reach or basin. This might be helpful on a local basis, but where large-scale patterns are important this approach is of limited use. Assuming a T-year flood (e.g. 100 years) for the entire river network is unrealistic and would lead to an overestimation of flood risk at the large scale. Due to the lack of damage data, additionally, the probability of peak discharge or rainfall is usually used as proxy for damage probability to derive flood risk. With a continuous and long term simulation of the entire flood risk chain, the spatial variability of probabilities could be consider and flood risk could be directly derived from damage data in a consistent way. The objective of this study is the development and application of a full flood risk chain, appropriate for the large scale and based on long term and continuous simulation. The novel approach of 'derived flood risk based on continuous simulations' is introduced, where the synthetic discharge time series is used as input into flood impact models and flood risk is directly derived from the resulting synthetic damage time series. The bottleneck at this scale is the hydrodynamic simu-lation. To find suitable hydrodynamic approaches for the large-scale a benchmark study with simplified 2D hydrodynamic models was performed. A raster-based approach with inertia formulation and a relatively high resolution of 100 m in combination with a fast 1D channel routing model was chosen. To investigate the suitability of the continuous simulation of a full flood risk chain for the large scale, all model parts were integrated into a new framework, the Regional Flood Model (RFM). RFM consists of the hydrological model SWIM, a 1D hydrodynamic river network model, a 2D raster based inundation model and the flood loss model FELMOps+r. Subsequently, the model chain was applied to the Elbe catchment, one of the largest catchments in Germany. For the proof-of-concept, a continuous simulation was per-formed for the period of 1990-2003. Results were evaluated / validated as far as possible with available observed data in this period. Although each model part introduced its own uncertainties, results and runtime were generally found to be adequate for the purpose of continuous simulation at the large catchment scale. Finally, RFM was applied to a meso-scale catchment in the east of Germany to firstly perform a flood risk assessment with the novel approach of 'derived flood risk assessment based on continuous simulations'. Therefore, RFM was driven by long term synthetic meteorological input data generated by a weather generator. Thereby, a virtual time series of climate data of 100 x 100 years was generated and served as input to RFM providing subsequent 100 x 100 years of spatially consistent river discharge series, inundation patterns and damage values. On this basis, flood risk curves and expected annual damage could be derived directly from damage data, providing a large-scale picture of flood risk. In contrast to traditional flood risk analysis, where homogenous return periods are assumed for the entire basin, the presented approach provides a coherent large-scale picture of flood risk. The spatial variability of occurrence probability is respected. Additionally, data and methods are consistent. Catchment and floodplain processes are repre-sented in a holistic way. Antecedent catchment conditions are implicitly taken into account, as well as physical processes like storage effects, flood attenuation or channel-floodplain interactions and related damage influencing effects. Finally, the simulation of a virtual period of 100 x 100 years and consequently large data set on flood loss events enabled the calculation of flood risk directly from damage distributions. Problems associated with the transfer of probabilities in rainfall or peak runoff to probabilities in damage, as often used in traditional approaches, are bypassed. RFM and the 'derived flood risk approach based on continuous simulations' has the potential to provide flood risk statements for national planning, re-insurance aspects or other questions where spatially consistent, large-scale assessments are required.},
  language  = {en}
}