Impact of Geospatial Data Enhancements for Regional-Scale 2D Hydrodynamic Flood Modeling: Case Study for the Coastal Plain of Virginia

Morsy, Mohamed M.; Lerma, Natalie R.; Shen, Yawen; Goodall, Jonathan L.; Huxley, Chris; Sadler, Jeffrey M.; Voce, Daniel; O’Neil, Gina L.; Maghami, Iman; Zahura, Faria Tuz

doi:10.1061/(asce)he.1943-5584.0002065

Cited by 8 publications

(4 citation statements)

References 43 publications

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“…The CoastFLOOD model incorporates both solutions, i.e., considering the friction effect of the floodplain terrain on the inundation flow either by defining a distributed, effective, grid-scale Manning's n on each cell of the model's raster domain or by proposing a representative "global" effective grid-scale n coefficient (on the entire domain or large homogenous parts of it). By integrating the relevant literature [74,80,[94][95][96][97][98][99][100][101], we created a detailed collective ensemble of proposed Manning coefficient n values discretized at 36 increments (Table 2). These values are specifically fitted to 2-D coastal floodplain flows and refer to the most common and less likely types of (natural or artificial) ground material.…”

Section: Model Parameterizationmentioning

confidence: 99%

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

et al. 2023

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Storm surges due to severe weather events threaten low-land littoral areas by increasing the risk of seawater inundation of coastal floodplains. In this paper, we present recent developments of a numerical modelling system for coastal inundation induced by sea level elevation due to storm surges enhanced by storm tides. The proposed numerical code (CoastFLOOD) performs high-resolution (5 m × 5 m) raster-based, storage-cell modelling of coastal inundation by Manning-type equations in decoupled 2-D formulation at local-scale (20 km × 20 km) lowland littoral floodplains. It is fed either by outputs of either regional-scale storm surge simulations or satellite altimetry data for the sea level anomaly. The presented case studies refer to model applications at 10 selected coastal sites of the Ionian Sea (east-central Mediterranean Sea). The implemented regular Cartesian grids (up to 5 m) are based on Digital Elevation/Surface Models (DEM/DSM) of the Hellenic Cadastre. New updated features of the model are discussed herein concerning the detailed surveying of terrain roughness and bottom friction, the expansion of Dirichlet boundary conditions for coastal currents (besides sea level), and the enhancement of wet/dry cell techniques for flood front propagation over steep water slopes. Verification of the model is performed by comparisons against satellite ocean color observations (Sentinel-2 images) and estimated flooded areas by the Normalized Difference Water Index (NDWI). The qualitative comparisons are acceptable, i.e., the modelled flooded areas contain all wet area estimations by NDWI. CoastFLOOD results are also compared to a simplified, static level, “bathtub” inundation approach with hydraulic connectivity revealing very good agreement (goodness-of-fit > 0.95). Furthermore, we show that proper treatment of bottom roughness referring to realistic Land Cover datasets provide more realistic estimations of the maximum flood extent timeframe.

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Section: Model Parameterizationmentioning

confidence: 99%

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

et al. 2023

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“…However, the requirements of this type of modelling impose significant constraints (spatial resolution of the topographic reference frame, calculation time, etc. ), which limits them to very localised applications [78]. Notably, improvements in census data collection and processing methods, as well as the incorporation of open data principles in legislation and practices for data dissemination in many countries (e.g.…”

Section: Scale and Granularitymentioning

confidence: 99%

Systemic vulnerability of coastal territories to erosion and marine flooding: A conceptual and methodological approach applied to Brittany (France)

Berre

Meur-Férec

Cuq

et al. 2022

International Journal of Disaster Risk Reduction

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“…It is also important to note that the sensitivity of the model results to surface roughness parameters, especially bottom friction, has been debated [18]. However, when spatially distributed bottom friction coefficients are used as calibration or data assimilation variables in overland flow models, the optimal or recovered values often deviate substantially from their initial values [16,19]. This indicates that their influence is non-negligible, and if we seek to disaggregate the contributions of the many complex phenomena in overland flood flows, surface roughness should be parameterized as descriptively as possible.…”

Section: Introductionmentioning

confidence: 99%

Hydraulic Bottom Friction and Aerodynamic Roughness Coefficients for Mangroves in Southwest Florida, USA

Medeiros

2023

JMSE

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Mangroves are a natural feature that enhance the resilience of natural and built coastal environments worldwide. They mitigate the impacts of hurricanes by dissipating energy from storm surges and waves, as well as reducing wind speeds. To incorporate mangroves into storm surge simulations, surface roughness parameters that accurately capture mangrove effects are required. These effects are typically parameterized using Manning’s n bottom friction coefficient for overland flow and aerodynamic roughness length (z0) for wind speed reduction. This paper presents the suggested values for these surface roughness parameters based on field observation and a novel voxel-based processing method for laser scanning point clouds. The recommended Manning’s n and z0 values for mangroves in southwest Florida are 0.138 and 2.34 m, respectively. The data were also used to retrain a previously developed random forest model to predict these surface roughness parameters based on point cloud statistics. The addition of the mangrove sites to the training data produced mixed results, improving the predictions of z0 while weakening the predictions of Manning’s n. The paper concludes that machine learning models developed to predict environmental attributes using small datasets with predictor features containing subjective estimates are sensitive to the uncertainty in the field observations.

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Impact of Geospatial Data Enhancements for Regional-Scale 2D Hydrodynamic Flood Modeling: Case Study for the Coastal Plain of Virginia

Cited by 8 publications

References 43 publications

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

Systemic vulnerability of coastal territories to erosion and marine flooding: A conceptual and methodological approach applied to Brittany (France)

Hydraulic Bottom Friction and Aerodynamic Roughness Coefficients for Mangroves in Southwest Florida, USA

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