Compound Effects of Flood Drivers and Wetland Elevation Correction on Coastal Flood Hazard Assessment

Abstract

Compound flooding frequently threatens life and assets of people who live in low‐lying coastal regions. Co‐occurrence or sequence of extremes (e.g., high river discharge and extreme coastal water level) is of paramount importance as it may result in flood hazards with potential impacts larger than each extreme in isolation. Here, we use a coupled approach, that is, bivariate statistical analysis linked to hydrodynamic modeling, to quantify compounding effects of flood drivers and generate flood hazard maps near Savannah, Georgia. Also, we integrate wetland elevation correction in digital elevation models to improve hydrodynamic simulations of compound events and hence the accuracy of flood hazard (inundation and velocity) maps. Using statistical measures, we analyze compounding effects of terrestrial/coastal flood drivers and wetland elevation correction on maximum floodwater height (MFH) and velocity (MFV) for 50‐year return period scenarios. In addition, we compare our results to MFH and MFV patterns of Hurricane Matthew that hit the West Atlantic Coasts on October 2016. The statistical measures indicate significant differences among the scenarios, partly explained by wetland elevation correction. Inundation and velocity maps suggest that a proposed composite, that is, synthesis of marginal Q, marginal H, and “AND” scenarios, can lead to the lowest average underestimation of MFH (−0.35 m) and overestimation of MFV (0.20 m/s) within wetland areas. We conclude that a thorough compound flooding assessment should leverage statistical analysis and hydrodynamic modeling of extremes including corrections of coastal digital elevation models.

Compound Inundation Impacts of Coastal Climate Change: Sea-Level Rise, Groundwater Rise, and Coastal Precipitation

“…Flow motion in coastal watersheds during rainfall events can cause inundation in additional areas that a static analysis of compound effects is unable to identify. It is important to note that there has been an attempt in recent literature to understand the compound effects of flooding sources due to their catastrophic impacts on coastal communities, but those efforts are limited to extreme events, and do not include precipitation-based flooding, as our study did [32,55,56]. In previous literature, coastal storms are typically considered with SLR inundation without understanding the interconnections of SLR to groundwater rise [57].…”

“…Although, this study did not consider the effect of SLR and subsequent impacts, e.g., groundwater rise. Muñoz, Moftakhari [32] assessed the compound effect of high river discharge and extreme coastal water level in Savannah, Georgia, USA. They used a bivariate statistical analysis linked to hydrodynamic modeling to quantify compounding effects of flood drivers.…”

“…Co-occurrence is of paramount importance as it may result in flood hazards with potential impacts larger than each extreme in isolation. Muñoz, Moftakhari [32] used a bivariate statistical analysis linked to hydrodynamic modeling, to quantify compounding effects of flood drivers and generate flood hazard maps near Savannah, Georgia, USA. Using statistical measures, they analyzed compounding effects of terrestrial/coastal flood drivers and wetland elevation correction on maximum floodwater height, and velocity for 50-year return period scenarios.…”

A cross-scale study for compound flooding processes during Hurricane Florence

“…We will also examine the coastal responses to the event and the close connection between watershed and coastal ocean. The existing modeling efforts on compound flooding (Chen et al, 2010;Cho et al, 2012;Dresback et al, 2013;Chen and Liu, 2014;Ikeuchi et al, 2017;Kumbier et al, 2018;Pasquier et al, 2018;Wing et al, 2019;Muñoz et al, 2020) often focus on a subset of the processes (storm surges, tides, waves, fluvial flooding, pluvial flooding, and potential baroclinic effects), leaving gaps in accurately representing the complex interactions among them (Santiago-Collazo et al, 2019). What distinguishes this study from traditional compound flooding simulations is a holistic approach that includes interrelated processes in different regimes and on multiple temporal/spatial scales in a single modeling framework.…”

Review of Estimating the Probability of Compound Floods in Estuarine Regions

“…Also, the multivariate statistical methods used to estimate the probability of compound flood events e.g. regression type models (Serafin et al 2019), standard copulas (Muñoz et al 2020), Vine copula (Bevacqua et al 2017) and conditional exceedance models (Jane et al 2020) should so be discussed or at least listed. The selection of design events i.e.…”