This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel ...depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high‐quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69–0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high‐frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national‐scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near‐future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time.
Plain Language Summary
We develop a method to estimate past, present, and future flood risk for all properties in the conterminous United States whether affected by river, coastal or rainfall flooding. The analysis accounts for variability within environmental factors including changes in sea level rise, hurricane intensity and landfall locations, precipitation patterns, and river discharge. We show that even for a conservative climate change trajectory we can expect locally significant changes in the land area at risk from floods by 2050, and by this time defenses protecting 2,200 km2 of land may be compromised. The complete dataset has been made available via a website (https://floodfactor.com/) created by the First Street Foundation in order to increase public awareness of the threat posed by flooding to safety and livelihoods.
Key Points
First complete high‐resolution flood hazard analysis of conterminous US flood risk from all major sources (fluvial, pluvial, and coastal)
In validation tests the model achieved Critical Success Index scores of 0.69–0.82, similar to many local custom‐built 2D models
By 2050, flood hazard increases for the Eastern seaboard and Western states, but decreases or changes little for the center and South‐West
The significant increase in the Arctic open-water extent along with the earlier sea-ice summer melt and later autumn freeze-up seasons observed in the last decades allow the formation of less ...fetch-limited waves and the further propagation of storm surges to new ice-free shores. Coupled hydrodynamic and wave models can be used to simulate these complex atmospheric-ocean interactions that often result in coastal flood hazards and extreme waves. However, the reliability of such simulations is intrinsically dependent on the quality of their main inputs, including wind and mean sea-level pressure products, which are usually extracted from reanalysis. This study evaluates the storm surge and significant wave height hindcasts from the coupled ADCIRC+SWAN numerical model forced by seven different reanalysis products during contrasting major storms. Model results show that the highest spatial resolution product CFSv2 led to the overall most accurate model simulations, performing particularly well at locations exposed to extreme surge and waves. Average root mean square error increases of up to 100 percent for storm surge and 157.55 percent for significant wave height were observed when using products other than CFSv2, thus highlighting the importance of selecting the proper wind and pressure reanalysis to be implemented as forcing in the hydrodynamic and wave numerical model.
The Southern Brazilian Coast is highly susceptible to storm surges that often lead to coastal flooding and erosive processes, significantly impacting coastal communities. In addition, climate change ...is expected to result in expressive increases in wave heights due to more intense and frequent storms, which, in conjunction with sea-level rise (SLR), has the potential to exacerbate the impact of storm surges on coastal communities. The ability to predict and simulate such events provides a powerful tool for coastal risk reduction and adaptation. In this context, this study aims to investigate how accurately storm surge events can be simulated in the Southwest Atlantic Ocean employing the coupled ADCIRC+SWAN hydrodynamic and phase-averaged wave numerical modeling framework given the significant data scarcity constraints of the region. The model’s total water level (TWL) and significant wave height (Hs) outputs, driven by different sources of meteorological forcing, i.e., the Fifth Generation of ECMWF Atmospheric Reanalysis (ERA 5), the Climate Forecast System Version 2 (CFSv2), and the Global Forecast System (GFS), were validated for three recent storm events that affected the coast (2016, 2017, and 2019). In order to assess the potentially increasing storm surge impacts due to sea-level rise, a case study was implemented to locally evaluate the modeling approach using the most accurate model setup for two 2100 SLR projections (RCP 4.5 and 8.5). Despite a TWL underestimation in all sets of simulations, the CFSv2 model stood out as the most consistent meteorological forcing for the hindcasting of the storm surge and waves in the numerical model, with an RMSE range varying from 0.19 m to 0.37 m, and an RMSE of 0.56 m for Hs during the most significant event. ERA5 was highlighted as the second most accurate meteorological forcing, while adequately simulating the peak timings. The SLR study case demonstrated a possible increase of up to 82% in the TWL during the same event. Despite the limitations imposed by the lack of continuous and densely distributed observational data, as well as up to date topobathymetric datasets, the proposed framework was capable of expanding TWL and Hs information, previously available for a handful of gauge stations, to a spatially distributed and temporally unlimited scale. This more comprehensive understanding of such extreme events represents valuable knowledge for the potential implementation of more adequate coastal management and engineering practices for the Brazilian coastal zone, especially under changing climate conditions.
Coastal flooding is a global phenomenon that results in severe economic losses, threatens lives, and impacts coastal communities worldwide. While recent developments in real-time flood forecasting ...systems provide crucial information to support coastal communities during coastal disasters, there remains a challenge to implement such systems in data-poor regions. This study demonstrates an operational real-time coupled surge wave guidance system for the coastal areas of Southern Brazil. This system is based on the recently developed integrated flood (iFLOOD) model, which utilizes the coupled hydrodynamic and phase-averaged ADCIRC–SWAN wave numerical model, driven by astronomical tides and atmospheric forcing from the Global Forecast System (GFS). This numerical modeling framework can simulate water levels and waves with a lead time of 84 h. A version of the coupled ADCIRC–SWAN model calibrated for Brazil, i.e., iFLOOD-Brazil, was operationally implemented (i.e., twice a day) over a period of 4 months (April to September 2020) for normal daily weather validation, as well as during a recent “bomb” cyclone that strongly impacted the southern coast of the country in June 2020. The real-time water levels and waves forecasted by iFLOOD-Brazil showed promising results against observations, with root mean square error (RMSE) values of 0.32 m and 0.68 m, respectively, for normal daily weather. Additionally, the RMSE values were 0.23 m for water levels and 1.55 m for waves during extreme weather, averaged over eight water level and two wave recording stations. In order to improve real-time predictions, a bias correction scheme was introduced and was shown to improve the water level and wave forecasts by removing the known systematic errors resulting from underestimation of astronomical tides and inadequate initial boundary conditions. The bias-corrected forecasts showed significant improvements in forecasted wave heights (0.47 m, 0.35 m) and water levels (0.17 m, 0.28 m) during daily and extreme weather conditions. The real-time iFLOOD-Brazil forecast system is the first step toward developing an accurate prediction model to support effective emergency management actions, storm mitigation, and planning in order to protect these economically valuable and socially vulnerable coastal areas.
The study of modern hurricane deposits is useful in both identifying ancient hurricane deposits in the rock record and predicting patterns of deposition and erosion produced by future storm events. ...Hurricane deposits on carbonate platforms have been studied less frequently than have been those along continental coasts. Here we present observations of the characteristics of deposition and scour caused by Hurricane Irma on Little Ambergris Cay, a small uninhabited island located near the southeastern edge of the Caicos platform in the Turks and Caicos Islands. Hurricane Irma passed directly over Little Ambergris Cay on 7 September 2017 as a Category 5 hurricane. We described and sampled multiple types of hurricane deposits and determined that the washover fans were the best sedimentological records for hurricane conditions, as they were subject to very little reworking over time. We compared different model predictions of storm tide and wave height with eyewitness reports and distributions of scour. Examining the washover fans allowed for the construction of a conceptual model for hurricane deposits formed in a high‐energy storm event on a carbonate platform. Characteristics of the washover fans were their small size, the lack of sedimentary structures, and very well sorted sediment. The size and distribution of carbonate boulders eroded and transported by the storm are consistent with depth‐averaged flow velocities in the range of 1.5–5.3 m/s. The strength of the storm and the low‐lying topography, distinct features of a carbonate platform setting, contributed to high levels of sediment bypass and high flow velocities, resulting in small, unstructured deposits.
Key Points
Hurricane deposits on a carbonate platform have characteristics unique to this geological setting
High storm surges and flow velocities cause sediment bypass that leaves behind small, unstructured deposits
The identification of massive carbonate beds adjacent to erosional features may aid in identifying storm events in the rock record
Coastal flooding operational forecasting in the US is limited to short-range temporal scales (3–7 days), which limits the response time for emergency preparation and planning. The sub-seasonal ...prediction project (SubX), which produces weather forecasts with a lead time of up to four weeks, provides an opportunity to assess the potential for creating probabilistic flood forecasts with longer lead times. Using the ADCIRC hydrodynamic model for coastal storm surge, two major hurricanes, Isabel (2003) and Katrina (2005), were used as case studies to test coastal flood predictions induced by wind and pressure fields generated from five global weather models within SubX. The storm surges simulations are forced by Sea Level Pressure (SLP) and 10 m winds fields from SubX models for a lead-time of up to 30 days before storm landfall. The subseasonal surge forecasts are evaluated temporally and spatially at 1–4 weeks lead-time against the NOAA tide gages observations and a verification dataset derived by forcing the storm surge model with wind and pressure fields from the NCEP-Reanalysis. The results are evaluated in terms of lead-time and forecast skill metrics. The storm surge forecast skill is measured using the mean square error skill score (MSESS) relative to the verification dataset and an approximate of the climatology. A skill score greater than 0.55 is considered here useful for flood forecasting. The multi-model ensemble (MME) mean surge forecasts driven by several members of SubX models demonstrate skill greater than 0.55 up to a 4-day and 10-day lead for Katrina and Isabel, respectively. A sharper decrease in MSESS was noted from week 1 to week 3 lead-times for Katrina, in comparison to Isabel. Some ensemble members forecasted hurricanes and storm surges as early as 3–4 weeks lead-time. However, due to the offsets developed in the timing and magnitude of the peak at these lead-times, and based on a sample size of only two events, it is hard to establish the significance of these longer lead-time results. While a follow up study involving flood reforecasts over the entire SubX reforecast period (1999–2015) is needed to support more robust statistics of the forecast skill, our case studies demonstrate the feasibility of probabilistic flood forecasting at subseasonal timescales using the SubX models.
Wave–vegetation interaction is implemented in the WAVEWATCH III (WW3) model. The vegetation sink term followed the early formulations of Dalrymple et al. (Journal of Waterway, Port, Coastal, and ...Ocean Engineering, 1984, 110, 67–79), which focused on monochromatic waves and vegetation approximated as an array of rigid, vertical cylinders, and was later expanded by Mendez and Losada (Coastal Engineering, 2004, 51, 103–118) for random wave transformations over mildly sloping vegetation fields under breaking and nonbreaking conditions assuming a Rayleigh distribution of wave heights. First, validation is carried out for 63 laboratory cases (
Anderson and Smith, 2014
) with homogeneous vegetation fields for single and double-peak wave spectra. Then, a field case application is conducted to assess the wave attenuation in a wetland environment with spatially variable vegetation fields during stormy conditions. The case study uses data collected at the Magothy Bay located in the Chesapeake Bay, United States, during Hurricanes Jose and Maria in 2017. The domain decomposition parallelization and the implicit scheme have been used for the simulations to efficiently resolve complex shorelines and high-gradient wave zones, incorporating dominant physics in the complicated coastal zone, including wave breaking, wave–current interaction, bottom friction and scattering, wave–vegetation interaction, and nonlinearity (
Abdolali et al., 2020
). The lab validation and field application demonstrate that WW3 is an effective tool for evaluating the capacity of wetland natural or nature-based features to attenuate wave energy to achieve coastal flood risk reduction.
Real-time flood forecasting computational frameworks that can dynamically integrate oceanic, coastal and estuarine processes are becoming essential to provide accurate and timely information for ...emergency response and planning in largely populated estuaries during extreme events. This study presents a newly developed real-time total water flood guidance system that is fully automated based on the coupled surge-wave (ADCIRC + SWAN) model and provides water level forecasts in the Chesapeake Bay for a lead-time of 84 h twice a day displayed on a web-based public interface. This system improved the current total water level predictions in the Bay (RMSE < 0.12 m) when compared to the existing operational forecasting systems over the period of 6 months (Jan’19-Jun’19). Furthermore, we demonstrated that a bias correction scheme and a multi-member ensemble forecast improve the overall flood prediction. Results suggests that this framework can improve our current capacity to predict total water levels in large estuaries.
•iFLOOD is a prototype surge-wave operational guidance system for the Chesapeake Bay.•iFLOOD provides a Web-based public interface for data visualization and situation awareness.•Water level guidance from iFLOOD showed less bias than two official flood forecast systems.•Ensemble-based forecast with iFLOOD out-performs all current official flood forecasts.
Flooding is one of the major natural hazards affecting communities along the US coastal areas and operational flood forecasting provides crucial information in anticipation of extreme events. ...Although the current operational forecasting systems continue to develop and improve, these systems still lack a comprehensive numerical modeling framework to accurately simulate coastal-river-urban-estuarine processes in real-time. Another challenge faced by existing operational flood guidance systems is the limited lead-time (i.e. 3 days in Mid-Atlantic). In this dissertation, two main goals are defined to improve flood forecasting and lead-time: 1) improve the current capacity to represent complex hydrodynamics in coastal-river-urban-estuarine environments to accurately forecast floods; and 2) explore ways for increasing the lead-time of flood forecasting to support emergency operations. First, we evaluated the performance of existing coastal guidance systems in the Chesapeake Bay and implemented a prototype operational forecast system. This system was further refined, the integrated flood guidance system (iFLOOD, https://iflood.vse.gmu.edu/), by using a coupled ADCIRC+SWAN modeling framework along with bias correction and ensemble predictions. In order to further improve the flood forecasts in complex coastal-river-urban-estuarine environments, such as the tidal Potomac River, we developed a stand-alone integrated real-time total water level forecast system using multiple input boundaries (tides, storm surge, river flows, urban runoff, and local forcing). Second, we analyzed the viability of a subseasonal flood-forecasting framework based on NOAA experimental weather forecasts (SubX) to extend the forecast lead-time. Our 6-month evaluation of iFLOOD showed improved capability to predict total water levels compared to two official existing coastal guidance systems. Furthermore, through the development of an integrated coastal-river-urban forecast framework for the Potomac River, we showed significant improvements in the total water level predictions in tidal rives. In regards to increasing the lead-time of flood forecasts, we showed that SubX-based ensemble predictions extended flood forecasts lead-time to nearly 10 days for Hurricane Isabel, encouraging the development of a subseasonal forecast system. This study further advances the current flood prediction operational capacity by integrating complex hydrodynamic processes in large estuaries and associated tidal rivers to accurately forecast water levels. In addition, this study highlighted the potential of extending the lead-time of flood forecast to support emergency preparation and planning.
Coastal wetlands provide a series of ecosystem services, including flood risk reduction. However, the flood risk reduction from such a complex ecosystem is dependent on incoming extreme ...hurricane-driven hydrodynamic and wave conditions. This study develops a numerical modeling-based approach for investigating coastal wetlands exposure to storm surge and waves during hurricanes by combining maximum water depth (
MWD
) and significant wave height (
MHs
) model outputs with the National Wetland Inventory for the Albemarle-Pamlico Estuarine System. Results show that various hurricanes lead to similar bimodal and bidirectional spatiotemporal flood patterns as a function of the lagoon’s geometry and storm track, with most overland hydrodynamic extremes impacting western Pamlico Sound and the bayside-Outer Banks. Clear positive dependency between
MWD
and
MH
S
were observed over most wetland classes, with significantly higher magnitudes over estuarine emergent vegetation. In contrast to
MWD
, sharp
MH
S
attenuation was found as the water propagates inland, leading to high
MWD
but lower
MH
S
eventually reaching palustrine woody vegetation hundreds of meters away from the coastline. Improved understanding of how storm surge dynamics move across the bays and through the different wetland types, demonstrates the importance of considering the bay-side flood impacts over the coastal vegetation. The spatially distributed
MWD
and
MH
S
estimates, along with the temporal patterns identified through the use of the
T
Max
, allow coastal managers and engineers to better understand where, when, and by how much, the estuarine APES wetlands are more likely to be exposed to high water depths and waves.
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