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 up 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, which consists of the local high-resolution 2D hydrodynamic flood model SFINCS, which is automatically set up from global datasets and loosely coupled with a global hydrodynamic river routing and flood model, as well as a global surge and tide model to account for interactions between all drivers. To test the framework, we simulate two historical compound flood events, cyclones Idai and Eloise, in the Sofala province of Mozambique, and compare the flood extent to observations from remote sensing and to the global quasi 2D CaMa-Flood model. The results show that while the global and local model have similar skill in terms of the critical success index, they result in rather different flood maps. On the one hand, the local model has a higher hit ratio due to the representation of direct coastal and pluvial flooding (rain on grid) and a higher floodplain connectivity. It also shows a faster response to coastal drivers within the estuaries and more realistic flood depth maps. On the other hand, the local model has a higher false alarm ratio, which is partly explained by the inclusion of direct pluvial flooding without sufficient representation of small scale (subgrid) drainage capacity. To showcase a possible application of the framework, we also determine the dominant flood drivers and transition zones between flood drivers for both events. 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 get 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.

Human displacements from tropical cyclone Idai attributable to climate change

“…Quantifying this additional effect would require a river flood model capable of reproducing the observed flood extent and associated inundation depths, and ideally coupled with a coastal flood model to capture the interaction between river flood and storm surge. Even though globally-applicable frameworks for compound flood hazard modeling are under construction, and have recently been tested for TC Idai (Eilander et al, 2022), evaluations of fluvial flood models reveal important shortcomings in data-scarce regions such as Mozambique (Bernhofen et al, 2018;Mester et al, 2021). Quantifying the role of river flooding in TC-induced displacement thus is a timely challenge.…”

Modeling compound flood risk and risk reduction using a globally-applicable framework: A case study in the Sofala region

“…In this case study, we consider five flood drivers: discharge at the Buzi and Pungwe rivers, rainfall, storm surge and wind setup. We therefore use the approach by Couasnon et al (2022), in which the marginal distributions of each driver (see section 2.2), the dependence between drivers, and the co-occurrence of different drivers are simulated separately. The approach consists of three steps.…”

“…The change in flood risk when accounting for compound events does not only depend on the dependence between drivers, but also the co-occurrence rate, duration of and time lags between drivers, and the hydrodynamics of the estuaries (Harrison et al, 2021;Serafin et al, 2019). Here we used the events-based method proposed by Couasnon et al (2022) (e.g. Zheng et al, 2014;Lucey and Gallien, 2022) to find out which approach is most appropriate for different applications.…”

“…Only a few studies have performed a compound flood risk assessment using combined hydrodynamic, statistical and impact modeling (e.g. Lamb et al, 2010;Bates et al, 2021;Couasnon et al, 2022). Furthermore, compound flood studies that measure the effectiveness of flood risk reduction measures often use simplified flood risk assessments.…”

A Hybrid Framework for Rapidly Locating Transition Zones: A Comparison of Event‐ and Response‐Based Return Water Levels in the Suwannee River FL

“…Hydraulic/hydrodynamic models have been used to identified transition zones during historical events (Eilander et al., 2022; Gori, Lin, & Smith, 2020; Stephens et al., 2022) and hypothetical scenarios based on past storms (Bilskie & Hagen, 2018; Santiago‐Collazo et al., 2021; Shen et al., 2019). At the catchment scale, hydraulic models such as the Hydrologic Engineering Center‐River Analysis System (HEC‐RAS) (HEC, 2002) provide robust estimates of along‐river water levels (Loveland et al., 2021).…”