A methodology for assessing flood risk from multiple sources

Abstract

Antecedent catchment conditions can affect the severity of flooding, and floods are typically worse when multiple flood sources superimpose. Over one million properties in the UK are at risk of flooding from multiple sources, however, groundwater, fluvial and pluvial flood sources are usually considered separately due to their differing characteristics. This PhD study was composed of two parts: (1) developing a methodology for assessing the risk of flooding from multiple sources, including the creation of a groundwater-surface water modelling system and (2) conducting a national assessment identifying catchments with potential for flooding from multiple sources. The modelling system used 1000 years of synthetic weather data to create realistic meteorological inputs for a physically-based, spatially-distributed hydrological catchment model (SHETRAN-GB). The hydrological model then simulated 1/30, 1/100 and 1/1000 year catchment conditions, which were used as inputs for a high resolution hydraulic model (HiPIMS). The hydraulic model then routed rainfall, stream flow and groundwater emergence to generate a detailed and comprehensive assessment of flood risk. Sensitivity tests compared the flood extents and depths from different methods of integrating groundwater and surface water conditions from the hydrological model into the hydraulic model to find the best method for linking the models. The capability of a national automated hydrological model to simulate groundwater levels was tested at five case study catchments using open source hydrogeological datasets. Automated model configurations were unable to reproduce historical groundwater levels, however simple automated improvements did increase performance. Improved parameterisation of a basic subsurface increased model performance more than the introduction of more complex geology, although the latter was found to be erroneous in places. Correlations between observed and simulated groundwater levels ranged significantly but were as high as 0.9 at some locations. At one case study site, the model domain was given subsurface boundary conditions and increased from its topographic watershed to the estimated groundwater catchment. This dramatically increased the model’s performance and its sensitivity to parameters. The automated setups provided a useful modelling base, but local calibration, improved hydrogeological parameters, subsurface boundary conditions and the use of groundwater domains are necessary for producing good simulations in catchments containing groundwater. New indexes were derived for classifying flow regimes to aid the identification of catchments likely to benefit from the developed methodology, and an initial 29 multisource catchments were identified out of a total of 435 analysed. Multisource catchments are distributed around the UK but are typically confined to areas with permeable bedrock, thus are most commonly found in the South of England. This research demonstrated that the inclusion of groundwater in the flood risk assessment increased the flood hazard by prolonging the flood duration from hours to days but did not notably increase flood depths. Furthermore, the patterns of flood extent changed depending on the proportion of the flood waters that were derived from the subsurface. In summary, this study provides a methodology for the better quantification, mapping and understanding of multisource flood risk, and identifies catchments that are likely to benefit from the approach.