A globally applicable framework for compound flood hazard modeling

Abstract

Abstract. Coastal river deltas are susceptible to flooding from pluvial, fluvial, and coastal flood drivers. Compound floods, which result from the co-occurrence of two or more of these drivers, typically exacerbate impacts compared to floods from a single driver. While several global flood models have been developed, these do not account for compound flooding. Local-scale compound flood models provide state-of-the-art analyses but are hard to scale to other regions as these typically are based on local datasets. Hence, there is a need for globally applicable compound flood hazard modeling. We develop, validate, and apply a framework for compound flood hazard modeling that accounts for interactions between all drivers. It consists of the high-resolution 2D hydrodynamic Super-Fast INundation of CoastS (SFINCS) model, which is automatically set up from global datasets and coupled with a global hydrodynamic river routing model and a global surge and tide model. To test the framework, we simulate two historical compound flood events, Tropical Cyclone Idai and Tropical Cyclone Eloise in the Sofala province of Mozambique, and compare the simulated flood extents to satellite-derived extents on multiple days for both events. Compared to the global CaMa-Flood model, the globally applicable model generally performs better in terms of the critical success index (−0.01–0.09) and hit rate (0.11–0.22) but worse in terms of the false-alarm ratio (0.04–0.14). Furthermore, the simulated flood depth maps are more realistic due to better floodplain connectivity and provide a more comprehensive picture as direct coastal flooding and pluvial flooding are simulated. Using the new framework, we determine the dominant flood drivers and transition zones between flood drivers. These vary significantly between both events because of differences in the magnitude of and time lag between the flood drivers. We argue that a wide range of plausible events should be investigated to obtain a robust understanding of compound flood interactions, which is important to understand for flood adaptation, preparedness, and response. As the model setup and coupling is automated, reproducible, and globally applicable, the presented framework is a promising step forward towards large-scale compound flood hazard modeling.

Regional assessment of extreme sea levels and associated coastal flooding along the German Baltic Sea coast

“…The use of remote sensing products for flood extent validation may be better suited for smaller, connected floodplains, where the above limitations can be more easily addressed. The strong potential for such applications has previously been shown by Eilander et al (2023) and Vousdoukas et al (2016). We show that the focus on specific areas with connected flood extents would also result in a higher agreement between the SAR imagery and our simulation (Fig.…”

“…We used the flood extent derived from S-1 SAR imagery (acquired at 17:08 UTC on 2 January 2019) to evaluate the validity of the flood extents simulated with the coastal inundation model. The suitability of SAR imagery for validating coastal flood extents has previously been described in Eilander et al (2023). SAR imagery was acquired 1.5 to 3 h after the modelled peak of the surge in Schleimünde (18) (entrance of the ca.…”

A multiscale modelling framework of coastal flooding events for global to local flood hazard assessments

“…Considering that HydroMT and SFINCS are capable of handling compound flooding induced by pluvial and fluvial drivers (Eilander et al, 2023), there is potential for future enhancements of MOSAIC to incorporate the modelling of compound events. Furthermore, MOSAIC currently makes use of offline coupling for both the local-high resolution model and the SFINCS model.…”

“…To build the SFINCS models and couple them with GTSM, MOSAIC makes use of the HydroMTv1.0.0 (Hydro Model Tools) package (Eilander et al, 2023).…”

Satellite Video Remote Sensing for Flood Model Validation

“…Indeed, many regions around the world lack comprehensive and high-quality data of commensurate coverage that can be used to validate these models (Rollason et al, 2018). A handful of studies that exemplify the validation of 2D models include those by Bernhofen et al (2018), Eilander et al (2023), and Wing et al (2017). These studies utilized satellite-derived flood extents to validate global flood models, which offer a macro-level understanding of flood risk and do not capture the fine-scale intricacies of local flood dynamics.…”