A New Automated Method for Improved Flood Defense Representation in Large‐Scale Hydraulic Models

Abstract

The execution of hydraulic models at large spatial scales has yielded a step change in our understanding of flood risk. Yet their necessary simplification through the use of coarsened terrain data results in an artificially smooth digital elevation model with diminished representation of flood defense structures. Current approaches in dealing with this, if anything is done at all, involve either employing incomplete inventories of flood defense information or making largely unsubstantiated assumptions about defense locations and standards based on socioeconomic data. Here, we introduce a novel solution for application at scale. The geomorphometric characteristics of defense structures are sampled, and these are fed into a probabilistic algorithm to identify hydraulically relevant features in the source digital elevation model. The elevation of these features is then preserved during the grid coarsening process. The method was shown to compare favorably to surveyed U.S. levee crest heights. When incorporated into a continental-scale hydrodynamic model based on LISFLOOD-FP and compared to local flood models in Iowa (USA), median correspondence was 69% for high-frequency floods and 80% for low-frequency floods, approaching the error inherent in quantifying extreme flows. However, improvements versus a model with no defenses were muted, and risk-based deviations between the local and continental models were large. When simulating an event on the Po River (Italy), built and tested with higher quality data, the method outperformed both undefended and even engineering-grade models. As such, particularly when employed alongside model components of commensurate quality, the method here generates improved-accuracy simulations of flood inundation. Plain Language SummaryTraditional flood risk assessments are carried out using computer models built with local data, but their spatial coverage is impaired by how expensive and time-consuming they are to produce. Recent advances in data availability, understanding of necessary physical process representation, and computational capacity have enabled hydraulic models of the entire globe to be built in an automated fashion at a fraction of the financial and human cost. However, their accuracy can be significantly impaired by a lack of information on flood defenses. As the model is built, elevation data are coarsened to reduce the number of calculations required to simulate flooding over such wide areas. This results in flood defense structures being smoothed out of the terrain information used in the model. Publicly available defense inventories are of insufficient coverage to ameliorate this issue. In this paper, a method is presented, which automatically detects levee-like features in high-resolution elevation data and accurately represents their heights during this necessary coarsening process. Simulating flood inundation over this "defended" topography results in high correspondence between local models and observations for test cases in the United States and Italy, with improve...

Simulating historical flood events at the continental-scale: observational validation of a large-scale hydrodynamic model

“…Not unexpectedly we find model skill varies considerably between events, suggesting that the testing of flood inundation models across a spatial scale imbalance (i.e., benchmarking continental-global scale models against a handful of localised test cases) is prone to a misleading evaluation of its usefulness. Previous studies suggest that the continental model employed here can replicate the extent of highquality, local-scale models of large flood events within error (Wing et al, 2017(Wing et al, , 2019Bates et al, 2020). Similarly, this analysis illustrates the very close match between flood extents derived from field data collected during the flood events and the maximum flood extent simulated by the continental model.…”

“…They compared their model to FEMA's large, yet incomplete, database of 100-year flood maps, charting a convergence of skill between the large-scale model and the engineering approach espoused by FEMA. Wing et al (2019) furthered this examination with statewide engineering models from the Iowa Flood Center, coming to similar conclusions. While these studies provide useful indications of large-scale model accuracy, they are fundamentally limited in their characterisation of skill through model intercomparisons.…”

Mapping the Sensitivity of Population Exposure to Changes in Flood Magnitude: Prospective Application From Local to Global Scale

“…On a local scale, the standard of flood protection is considered using a highresolution digital elevation model in the inundation model. The exact river morphology is hardly represented in global scale flood models (Wing et al, 2019). Therefore, the FLOPROS database of flood protection standards was used to consider the effects of measures in river engineering and flood protection.…”

Changes in the exposure of California’s levee-protected critical infrastructure to flooding hazard in a warming climate

“…For such a study, we need to have a runoff dataset with a higher temporal and spatial resolution that takes into account the changes in both the climate and the land use and land cover of the levee protected regions. Therefore, we also need to invest in developing the local and global hydraulic models (Wing et al 2019, Johnson et al 2020 with forcing from the GCMs to get a higher temporal and spatial resolution runoff datasets.…”