Authors: J. Drake, E. Marty, K. Gandhi, M. Welch-Devine, B. Bledsoe, M. Shepherd, L. Seymour, C. Fortuin and C. Montes.

Abstract: It is well understood that natural disasters interact to affect the resilience and prosperity of communities and disproportionately affect low income families and communities of color. However, given the lack of a common theoretical framework, it is rare for these interactions to be well understood or quantified. As an example, we consider the interaction of severe weather events (e.g., hurricanes and tornadoes) and epidemics (e.g., COVID-19). Observing events unfolding in southeastern U.S. communities has caused us to conjecture that the interactive effects of catastrophic disturbances and stressors might be much more considerable than previously recognized. For instance, hurricane evacuations increase human aggregation, a key factor that affects the transmission of acute respiratory infections like SARS-CoV-2. Similarly, weather damage to health infrastructure could significantly reduce a community’s ability to provide services to people sick with COVID-19 and other diseases. As globalization and human population and movement continue to increase and weather events due to climate change are becoming more intense and severe, such complex interactions are expected to magnify and significantly impact environmental and human health.

Authors: H. Selsor, B. Bledsoe and R. Lammers.

Abstract: Urban flooding is a growing threat due to land use and climate change. Vulnerable populations tend to have greater exposure to flooding as a result of historical societal and institutional processes. Most flood vulnerability studies focus on a single large flood, neglecting the impact of small, frequent floods. Therefore, there is a need to investigate inequitable flood exposure across a range of event magnitudes and frequencies. To explore this question, we develop a novel score of inequitable flood risk by defining risk as a function of frequency, exposure, and vulnerability. This analysis combines high-resolution, parcel-scale compounded fluvial and pluvial flood data with census data at the census block group scale. We focus on six census tracts within Athens-Clarke County, Georgia that are highly developed with diverse populations. We define vulnerable populations as non-Hispanic Black, Hispanic, and households under the poverty level and use dasymetric mapping techniques to calculate the over-representation of these populations in flood zones. Inequitable risks at each census tract (approximately neighborhood scale) were estimated for multiple (e.g., 5-, 10-, 20-, 50-, and 100-year) flood return periods. Results show that the relatively greatest flood risk inequities occur for the 10-year flood and not at the largest event. We also found that the size of inequity is dynamic, depending on the flood magnitude. Therefore, addressing a range of events including smaller, more frequent floods can increase equity and reveal opportunities that may be missed if only one event is considered.

Authors: F. Santiago-Collazo, M. Bilskie, P. Bacopoulos and S. Hagen.

Abstract: Low-gradient coastal watersheds are susceptible to flooding caused by various flows such as rainfall-runoff, astronomical tides, storm surges, and riverine flows. Compound flooding occurs when at least one coastal flood driver occurs simultaneously or in close succession with a pluvial and/or fluvial flood driver, such as during a tropical cyclone event. This study presents a one-dimensional (1-D), reduced-order physics compound inundation model tested over an idealized coastal watershed transect under various forcing conditions (e.g., coastal and pluvial) that varied in magnitude, time, and space. This study aims to evaluate each flooding mechanism and the associated hydrodynamic responses by performing a sensitivity analysis and developing a non-linear equation that could correlate the flood drivers with the severity of its flood. Compound inundation levels are affected by the magnitude and timing of each flooding mechanism. Results highlight the need to consider momentum exchange during a compound event and the importance of reduced-physics approaches that can improve the interaction between flood drivers when paired with a moving coupling node approach. The desire is a more holistic compound inundation model that can be a critical tool for decision-makers, stakeholders, and authorities who provide evacuation planning to save human lives and enhance resilience.

Authors: T. Stephens and B. Bledsoe.

Abstract: Recent catastrophic flood events, increasing flood losses, and climate change challenge current reliability estimates defined by the probability that flood levels will not exceed protection measures over a planning horizon. These estimates depict an expected reliability that mask uncertainty in streamflow and the capacity of river channels and floodplains. We described reliability as a random variable whose distribution depends on uncertainty and nonstationarity in annual maximum flood (AMF) distributions and flow capacity uncertainty. Numerical experiments quantified the impacts of nonstationarity and variance in AMFs and flow capacity uncertainty on estimates of flood protection reliability, thereby providing the first examination of their interacting effects. The distribution of reliability along a regulatory floodplain boundary was quantified through a bootstrap scheme that accounts for nonstationarity and uncertainty in AMFs and flow capacity uncertainty. Results indicated that accounting for uncertainty in flow capacity substantially reduces reliability compared to estimates based solely on flood likelihood; the divergence is greater in the presence of nonstationary AMFs. The distribution of reliability along the regulatory floodplain boundary was spatially heterogeneous due to within-reach variation in flow capacity uncertainty. Quantifying the distribution of reliability for flood protection measures enables transparent communication and selection of a desired confidence level that is commensurate with a contextually appropriate risk tolerance. Similarly, we show that a desired level of confidence in reliability can be specified to estimate a design flood protection level. These results reveal how the combined impacts of uncertainty and nonstationarity can impact reliability estimates and confidence in those estimates.

Authors: V. Hewageegana, M. Bilskie, C.B. Woodson and B. Bledsoe.

Abstract: Coastal wetlands are an effective natural and nature-based feature to mitigate coastal flood hazards. While the sheltering and attenuation offered by wetlands are recognized, the protection level varies based on wetland and storm characteristics. Here we focus on the effects of the spatial scales of the coastal wetlands (i.e., channel geometry, marsh elevation-gradient) and the temporal scales of storm forcing (i.e., storm surge amplitude and duration) on peak water level attenuation. The study was conducted by performing hydrodynamic simulations on an idealized marsh geometry. One hundred seventy-one hydrodynamic simulations were conducted by varying wetland features under variable hydrodynamic forcing. Increased tidal channel area enhances water flow across marshes by reducing the capacity of vegetated platforms to resist propagation of a storm surge. The level of surge attenuation and channel area shows a non-linear relationship. Storm scales also affect surge attenuation for a given channel geometry. Higher amplitudes and lower surge durations provide greater attenuation of peak water levels. The level of attenuation and surge scales also show a non-linear correlation. A multivariate scaling relationship was developed that successfully integrates the combined effects of channel geometry and surge scales on water level attenuation by salt marsh. This research provides guidance to engineers and coastal managers on salt marsh’s flood hazard reduction benefits.