skip to main content

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Thursday, January 16 until 2:00 AM ET on Friday, January 17 due to maintenance. We apologize for the inconvenience.


Title: Dynamic Modeling of Inland Flooding and Storm Surge on Coastal Cities under Climate Change Scenarios: Transportation Infrastructure Impacts in Norfolk, Virginia USA as a Case Study
Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable of resolving urban drainage infrastructure within the city. The modeling approach is demonstrated in quantifying the impact of possible future climate scenarios on transportation infrastructure within Norfolk, Virginia, USA. A series of combined storm events are modeled for current (2020) and projected future (2070) climate scenarios. The results show that pluvial flooding causes a larger interruption to the transportation network compared to tidal flooding under current climate conditions. By 2070, however, tidal flooding will be the dominant flooding mechanism with even nuisance flooding expected to happen daily due to SLR. In 2070, nuisance flooding is expected to cause a 4.6% total link close time (TLC), which is more than two times that of a 50-year storm surge (1.8% TLC) in 2020. The coupled flood model was compared with a widely used but physically simplistic bathtub method to assess the difference resulting from the more complex modeling presented in this study. The results show that the bathtub method overestimated the flooded area near the shoreline by 9.5% and 3.1% for a 10-year storm surge event in 2020 and 2070, respectively, but underestimated the flooded area in the inland region by 9.0% and 4.0% for the same events. The findings demonstrate the benefit of sophisticated modeling methods compared to more simplistic bathtub approaches, in climate adaptive planning and policy in coastal communities.  more » « less
Award ID(s):
1951745 1735587
PAR ID:
10339200
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Geosciences
Volume:
12
Issue:
6
ISSN:
2076-3263
Page Range / eLocation ID:
224
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    This study investigates the sensitivity of the Calcasieu Lake estuarine region to channel deepening in southwest Louisiana in the USA. We test the hypothesis that the depth increase in a navigational channel in an estuarine region results in the amplification of the inland penetration of storm surge, thereby increasing the flood vulnerability of the region. We run numerical experiments using the Delft3D modeling suite (validated with observational data) with different historic channel depth scenarios. Model results show that channel deepening facilitates increased water movement into the lake–estuary system during a storm surge event. The inland peak water level increases by 37% in the presence of the deepest channel. Moreover, the peak volumetric flow rate increases by 291.6% along the navigational channel. Furthermore, the tidal prism and the volume of surge prism passing through the channel inlet increase by 487% and 153.3%, respectively. In our study, the presence of the deepest channel results in extra 56.72 km2of flooded area (approximately 12% increase) which is an indication that channel deepening over the years has rendered the region more vulnerable to hurricane-induced flooding. The study also analyzes the impact of channel deepening on storm surge in estuaries under different future sea-level rise (SLR) scenarios. Simulations suggest that even the most conservative scenario of SLR will cause an approximately 51% increase in flooded area in the presence of the deepest ship channel, thereby suggesting that rising sea level will cause increased surge penetration and increased flood risk.

     
    more » « less
  2. Abstract

    Sea‐level rise is leading to increasingly frequent coastal floods globally. Recent research shows that changes in tidal properties and storm surge magnitudes can further exacerbate sea‐level rise‐related increases in flood frequencies. However, such non‐stationarity in tide and storm surge statistics are largely neglected in existing coastal flood projection methodologies. Here we develop a framework to explore the effect that different realizations of various sources of uncertainty have on projections of coastal flood frequencies, including changes in tidal range and storminess. Our projection methodology captures how observed flood rates depend on how storm surges coincide with tidal extremes. We show that higher flood rates and earlier emergence of chronic flooding are associated with larger sea‐level rise rates, lower flood thresholds, and increases in tidal range and skew surge magnitudes. Smaller sea‐level rise rates, higher flood thresholds and decreases in sea level variability lead to commensurately lower flood rates. Percentagewise, changes in tidal amplitudes generally have a much larger impact on flood frequencies than equivalent percentagewise changes in storm surge magnitudes. We explore several implications of these findings. Firstly, understanding future local changes in storm surges and tides is required to fully quantify future flood hazards. Secondly, existing hazard assessments may underestimate future flood rates as changes in tides are not considered. Finally, identifying the flood frequencies and severities relevant to local coastal managers is imperative to develop useable and policy‐relevant projections for decisionmakers.

     
    more » « less
  3. Storm surge flooding caused by tropical cyclones is a devastating threat to coastal regions, and this threat is growing due to sea-level rise (SLR). Therefore, accurate and rapid projection of the storm surge hazard is critical for coastal communities. This study focuses on developing a new framework that can rapidly predict storm surges under SLR scenarios for any random synthetic storms of interest and assign a probability to its likelihood. The framework leverages the Joint Probability Method with Response Surfaces (JPM-RS) for probabilistic hazard characterization, a storm surge machine learning model, and a SLR model. The JPM probabilities are based on historical tropical cyclone track observations. The storm surge machine learning model was trained based on high-fidelity storm surge simulations provided by the U.S. Army Corps of Engineers (USACE). The SLR was considered by adding the product of the normalized nonlinearity, arising from surge-SLR interaction, and the sea-level change from 1992 to the target year, where nonlinearities are based on high-fidelity storm surge simulations and subsequent analysis by USACE. In this study, this framework was applied to the Chesapeake Bay region of the U.S. and used to estimate the SLR-adjusted probabilistic tropical cyclone flood hazard in two areas: One is an urban Virginia site, and the other is a rural Maryland site. This new framework has the potential to aid in reducing future coastal storm risks in coastal communities by providing robust and rapid hazard assessment that accounts for future sea-level rise. 
    more » « less
  4. Abstract

    The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low‐lying coastal areas. Climate change could increase the level of compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under current and future climate conditions. A copula‐based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea‐level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal‐riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal‐riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal‐riverine stations along the Contiguous United States coast with long‐term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.

     
    more » « less
  5. Abstract

    Coastal urban areas like New York City (NYC) are more vulnerable to urban pluvial flooding particularly because the rapid runoff from extreme rainfall events can be further compounded by the co-occurrence of high sea-level conditions either from tide or storm surge leading to compound flooding events. Present-day urban pluvial flooding is a significant challenge for NYC and this challenge is expected to become more severe with the greater frequency and intensity of storms and sea-level rise (SLR) in the future. In this study, we advance NYC’s assessment of present and future exposure to urban pluvial flooding through simulating various storm scenarios using a citywide hydrologic and hydraulic model. This is the first citywide analysis using NYC’s drainage models focusing on rainfall-induced flooding. We showed that the city’s stormwater system is highly vulnerable to high-intensity short-duration “cloudburst” events, with the extent and volume of flooding being the largest during these events. We further showed that rainfall events coupled with higher sea-level conditions, either from SLR or storm surge, could significantly increase the volume and extent of flooding in the city. We also assessed flood exposure in terms of the number of buildings and length of roads exposed to flooding as well as the number of the affected population. This study informs NYC’s residents of their current and future flood risk and enables the development of tailored solutions to manage increasing flood risk in the city.

     
    more » « less