The STORMTOOLS Coastal Environmental Risk Index (CERI) has historically been used to assess the damage to residential and commercial structures from coastal flooding, including the effects of sea level rise (SLR) in RI. In the present study, CERI was extended to address the impact of flooding for 100 yr storm, including the effects of SLR, to the newly renovated Warren, RI wastewater treatment facilities (WWTF), located on the tidal Warren River, using FEMA HAZUS damage curves. The analysis shows that the average damage for 100 yr flooding, across all components of the facility, increases with sea level from 16% (0 ft SLR), 23% (2 ft SLR), 26% (3 ft SLR), to 28% (5 ft SLR). The primary settling and chlorination tanks are at most risk and the aeration and reaction tanks at least risk. In an effort to validate the FEMA HAZUS WWTF damage curves, CERI was applied to predict flood damage during the 3 day, March/April 2010 flooding event (500 yr) to the Cranston, Warwick, and West Warwick WWTF located on the Pawtuxet River, RI. The predictions of the damage to each WWTF from this event were compared to observations of the damage made by the plant operators. The percent damage was estimated by comparing the cost of the damage to the assessed value of the facility. Using the FEMA HAZUS damage curves for the observed level of inundation (7 to 8 ft) predicted that the Warwick and West Warwick facility damage ranged from 15 to 45% with an average value of about 30%. The Cranston WWTF damage was very low (<1%) because of the elevation of the facility. The observed damage for the 2010 flood event was approximately 21% for the Warwick facility and 18% for the West Warwick facility, between the FEMA HAZUS lower and average values. Damage to the Cranston facility was consistent between FEMA HAZUS and observed values at <1%.

Storm-surge models are commonly used to assess the impacts of hurricanes and coastal storms in coastal areas. Including the impact of the projected future sea level rise (SLR) in these models is a necessary step for a realistic flood risk assessment. Commonly, SLR is superimposed linearly on the simulated water elevation. This approach, while efficient, may lead to inaccuracies. Furthermore, developing a new model with updated data (e.g., boundary conditions, bathymetry) that include the effects of SLR (i.e., nonlinear approach) is time consuming. We compare the linear and nonlinear approaches to include the effect of SLR in predicting maximum water/flood elevations (MWE) as a result of storm surge. After a simplified theoretical analysis, a number of idealized cases based on the typical coastal bodies of water are modeled to assess the impact of SLR on MWE using the linear superposition and nonlinear approaches. Additionally, two case studies are carried out: Narragansett Bay, RI, and Long Island Sound, CT (USA). Results show that for the idealized cases with variable depth, in general, the linear superposition of SLR to MWE is conservative (i.e., predicts a larger flood elevation) relative to the nonlinear approach. However, if a constant depth is considered, results are not consistent (i.e., linear superposition can overestimate or underestimate MWE, and the results depended on the geometry). The simulated MWE from the Narragansett Bay simulation confirms the outcome of idealized cases showing that linear assumption is conservative up to 10% relative to the nonlinear approach. For this study, Hurricane Sandy and a synthetic storm from the US Army Corps of Engineers North Atlantic Comprehensive Coastal Study (NACCS) dataset are simulated. Long Island Sound model results are also consistent with the idealized case. In general, based on the results of the idealized and real case studies, a discrepancy of up to 10% between the linear and nonlinear approaches is expected in estimation of MWE which can be under- or over-estimation of flood elevation, depending on the geometry.

To help the selection of suitable sites for development of offshore wind projects in the US on the coasts of California, Oregon and Hawaii, the Bureau of Ocean Energy Management (BOEM) funded this study to assess the potential geo-hazards in this region. First, a comprehensive review of potential threats to the sites based on historic events is provided. The geospatial indexing for the call areas are then calculated based on weights associated with inputs, consisting of: sea floor slope, soil type, and seismicity (peak ground acceleration data of 500 year event). Finally, suitability indices are provided for each region. To perform a suitability analysis using geospatial indexing, all input factors are first standardized into a common scale, then a weighted overlay function is applied. Each of the criteria in the analysis is multiplied by the weights defined based on their importance in the region and then added together and suitability maps for each lease block are developed. Comprehensive maps of geohazards and geological data, suitability index maps and suitability rankings for the area of interest are being generated and presented online. This paper focuses on the floating windfarm call areas offshore California, including Humboldt, Morro Bay and Diablo Canyon, and presents the new approach for evaluating, integrating and indexing geospatial geohazard data for offshore windfarms, and the state-of-the-art suitability analysis approach. This new method can be also beneficial in the other parts of the world (e.g. East Asia), and similar concept can be implemented to evaluate the suitability of sites, based on the hazards in the area of interest.

Trajectory and fate modeling of the oil released during the Deepwater Horizon blowout was performed for April to September of 2010 using a variety of input data sets, including combinations of seven hydrodynamic and four wind models, to determine the inputs leading to the best agreement with observations and to evaluate their reliability for quantifying exposure of marine resources to floating and subsurface oil. Remote sensing (satellite imagery) data were used to estimate the amount and distribution of floating oil over time for comparison with the model’s predictions. The model-predicted locations and amounts of shoreline oiling were compared to documentation of stranded oil by shoreline assessment teams. Surface floating oil trajectory and distribution was largely wind driven. However, trajectories varied with the hydrodynamic model used as input, and was closest to observations when using specific implementations of the HYbrid Coordinate Ocean Model modeled currents that accounted for both offshore and nearshore currents. Shoreline oiling distributions reflected the paths of the surface oil trajectories and were more accurate when westward flows near the Mississippi Delta were simulated. The modeled movements and amounts of oil floating over time were in good agreement with estimates from interpretation of remote sensing data, indicating initial oil droplet distributions and oil transport and fate processes produced oil distribution results reliable for evaluating environmental exposures in the water column and from floating oil at water surface. The model-estimated daily average water surface area affected by floating oil >1.0 g/m 2 was 6,720 km 2 , within the range of uncertainty for the 11,200 km 2 estimate based on remote sensing. Modeled shoreline oiling extended over 2,600 km from the Apalachicola Bay area of Florida to Terrebonne Bay area of Louisiana, comparing well to the estimated 2,100 km oiled based on incomplete shoreline surveys.

Model predictions of oil transport and fate for the 2010 Deepwater Horizon oil spill (Gulf of Mexico) were compared to field observations and absolute and relative concentrations of oil compounds in samples from 900 to 1400 m depth <11 km from the well. Chemical partitioning analyses using quantitative indices support a bimodal droplet size distribution model for oil released during subsea dispersant applications in June with 74% of the mass in >1 mm droplets that surfaced near the spill site within a few hours, and 1-8% as <0.13 mm microdroplets that remained below 900 m. Analyses focused on 900-1400 m depth <11 km from the well indicate there was substantial biodegradation of dissolved components, some biodegradation in microdroplets, recirculation of weathered microdroplets into the wellhead area, and marine oil snow settling from above 900 m carrying more-weathered particulate oil into the deep plume.

Based on oil fate modeling of the Deepwater Horizon spill through August 2010, during June and July 2010, ~89% of the oil surfaced, ~5% entered (by dissolving or as microdroplets) the deep plume (>900 m), and ~6% dissolved and biodegraded between 900 m and 40 m. Subsea dispersant application reduced surfacing oil by ~7% and evaporation of volatiles by ~26%. By July 2011, of the total oil, ~41% evaporated, ~15% was ashore and in nearshore (<10 m) sediments, ~3% was removed by responders, ~38.4% was in the water column (partially degraded; 29% shallower and 9.4% deeper than 40 m), and ~2.6% sedimented in waters >10 m (including 1.5% after August 2010). Volatile and soluble fractions that did not evaporate biodegraded by the end of August 2010, leaving residual oil to disperse and potentially settle. Model estimates were validated by comparison to field observations of floating oil and atmospheric emissions.

Under the STORMTOOLS initiative, maps of the impact of sea level rise (SLR) (0 to 12 ft), nuisance flooding (1–10 yr), 25, 50, and 100 yr storms, and hindcasts of the four top ranked tropical storms have been developed for the coastal waters of Rhode Island (RI). Estimates of the design elevations, expressed in terms of the Base Flood Elevation (BFE) and thus incorporating surge and associated wave conditions, have also been developed, including the effects of SLR to facilitate structural design. Finally, Coastal Environmental Risk Index (CERI) maps have been developed to estimate the risk to individual structures and infrastructure. CERI employs the BFE maps in concert with damage curves for residential and commercial structures to make estimates of damage to individual structures. All maps are available via an ArcGIS Hub. The objective of this senior design capstone project was to develop STORMTOOLS Design Load maps (SDL) with a goal of estimating the hydrostatic, hydrodynamic, wave, and debris loading, based on ASCE/SEI 7–16 Minimum Design Standards methods, on residential structures in the RI coastal floodplain. The resulting maps display the unitized loads and thus can be scaled for any structure of interest. The goal of the maps is to provide environmental loads that support the design of structures, and reduce the time and cost required in performing the design and the permitting process, while also improving the accuracy and consistency of the designs. SDL maps were generated for all loads, including the effects of SLR for a test case: the Watch Hill/Misquamicut Beach, Westerly, along the southern RI coast. The Autodesk Professional Robot Structural Analysis software, along with SDL loading, was used to evaluate the designs for selected on-grade and pile-elevated residential structures. Damage curves were generated for each and shown to be consistent with the US Army Corps of Engineers empirical damage curves currently used in CERI.

STORMTOOLS coastal environmental risk index (CERI) was applied to communities located along the southern coast of Rhode Island (RI) to determine the risk to structures located in the flood plain. CERI uses estimates of the base flood elevation (BFE), explicitly including the effects of sea level rise (SLR); details on the structure types, from the E911 emergency data base/parcel data, and associated first floor elevation (FFE); and damage curves from the US Army Corp of Engineers North Atlantic Coast Comprehensive Study (NACCS) to determine the damages to structures for the study area. Surge levels and associated offshore waves used to determine BFEs were obtained from the NACCS hydrodynamic and wave model predictions. The impacts of sea level rise and coastal erosion on flooding were modeled using XBeach and STWAVE and validated by observations at selected locations along the coastline. CERI estimated the structural damage to each structure in the coastal flood plain for 100 yr flooding with SLR ranging from 0 to 10 ft. The number of structures at risk was estimated to increase approximate linearly from 3700 for no SLR to about 8000 for 10 ft SLR, with about equal percentages for each of the four coastal communities (Narragansett, South Kingstown, Charlestown, and Westerly, Rhode Island (RI)). The majority of the structures in the flood plain are single/story residences without (41%) and with (46%) basements (total 87%; structures with basements are the most vulnerable). Less vulnerable are structures elevated on piles with 8.8% of the total. The remaining are commercial structures principally located either in the Port of Galilee and or Watch Hill. The analysis showed that about 20% of the structures in the 100 yr flood plain are estimated to be damaged at 50% or greater. This increases to 55% of structures as SLR rises to 5 ft. At higher SLR values the percent damaged at 50% or greater slowly declines to 45% at 10 ft SLR. This behavior is a result of the number of homes below MSL increasing dramatically as SLR values moves higher than 5 ft and thus being removed from the structures damaged pool. Generalized CERI risk maps have developed to allow the managers to determine the broad risk of siting structures at any location in their communities. CERI has recently become available as a mobile phone App, facilitating the ability of state and local decision makers and the public to determine the risk of locating a selected building type at any location in their communities.

In March 2010, a sequence of three major rainfall events in New England (United States) led to a record-breaking flooding event in the Pawtuxet River Watershed with a peak flow discharge of about 500-year return period. After development of hydrological and hydraulic models, a number of factors that played important roles in the impact of this flooding and other extreme events including river structures (reservoirs, historical textile mill dams, and bridges) were investigated. These factors are currently omitted within risk assessments tools such as flood insurance rate maps. Some management strategies that should be considered for future flood risk mitigation were modeled and discussed. Furthermore, to better understand possible future risks in a warmer climate, another extreme flood event was simulated. The synthetic/hypothetical storm (Hurricane Rhody with two landfalls) was created based on the characteristics of the historical hurricanes that severely impacted this region in the past. It was shown that while the first landfall of this hurricane did not lead to significant flood risk, the second landfall could generate more rain and flooding equivalent to a 500-year event. Results and the methodology of this study can be used to better understand and assess future flood risk in similar watersheds.

STORMTOOLS Coastal Environmental Risk Index (CERI) predicts the coastal flooding damage to individual structures using coastal flooding levels, including the effects of sea level rise (SLR), provided in terms of the base flood elevation (BFE), specifications of the structure of interest (type and first floor elevation) and the associated damage functions from the U.S. Army Corp of Engineers (USACE), North Atlantic Coast Comprehensive Study (NACCS). CERI has been applied to selected coastal communities in Rhode Island, including those in Narragansett Bay and along the southern Rhode Island shoreline. Users can access the results of CERI via ArcGIS online at the CERI website. The objective of this effort was to develop, test, distribute, and evaluate a mobile phone application (App) that allows the user to assess the risk from coastal flooding and the associated damage at the individual structure level using the CERI methodology. The App is publicly available and has been developed for both iOS and Android operating systems. Environmental data to support the App, in terms of 100 y flood BFE maps, including the effects of SLR and the selected site grade elevation, are provided in the application by the URI Environmental Data Center (EDC). The user enters the location and type of the structure of interest (residential number of stories, with or without basement, pile supported or commercial building and the first-floor elevation (FFE)) and the desired SLR. The App then calculates the percent structural damage based on the specified environmental conditions and structure specifications. The App can be applied to any structure at any coastal location within the state. The CERI App development project has been guided by an Advisory Board made up of key constituents involved in coastal management and development in the state. The effort included extensive testing of the App by various user groups. The App structure makes it simple and straightforward to transfer to coastal and inland flooded areas in other locations, requiring only the specification of BFEs and grade elevations.

Coastal hazard at the residential scale, resulting from the combined effects of storm surge and waves including dynamic set-up and wave runup, is assessed for the local 100-year Synthetic Design Storm (SDS) in Narragansett, RI, USA, based on high resolution (2 m) simulations with the nonlinear phase-resolving Boussinesq wave model FUNWAVE. The accuracy of wave-flow-structure interaction modeling is improved using a built-up DEM, defined by adding coastal structures to the bare-earth DEM. In addition, bathymetry and topography are modified to reflect post-storm conditions based on simulating the same storm with the morphodynamic model XBeach. Comparisons of FUNWAVE results with those of the phase-averaged model STWAVE, for the same storm conditions, show that including individual wave effects increases the inundated area by 13% and maximum water levels (TWL) across the shoreline by 11%, in average; however, in high runup areas (such as along exposed structures), the predicted maximum water levels can increase by up to 100%. FUNWAVE predicts maximum runups on the order of ∼1.5Hs (with Hs the offshore significant wave height), which is consistent with empirical formulae for steep seawalls (Van der Meer, 2002), and these occur at the most exposed structures, which historical records show have been periodically damaged by large storms. The maximum momentum forces predicted by FUNWAVE are much larger than those derived from STWAVE simulations (based on linear wave theory and assuming Rayleigh distributed waves), and also occur on the most exposed structures. The study provides a quantitative assessment of the local coastal hazard associated with the selected SDS at the scale of individual structures, and stresses the importance of accurately modeling individual wave effects, runups and associated forces in coastal hazard assessment modeling studies.

Many coastal communities in the US use base flood elevation (BFE) maps for the 100-year return period, specified on Federal Emergency Management Agency (FEMA) Flood Insurance Rate Maps (FIRMs), to design structures and infrastructure. The FIRMs are increasingly known to have serious problems in accurately specifying the risk coastal communities face, as most recently evidenced during hurricanes Harvey and Irma in 2017 and Florence and Michael in 2018. The FIRM BFE maps also do not include the impact of sea level rise, which clearly needs to be considered in the design of coastal structures over the next several decades given recent National Oceanic and Atmospheric Administration (NOAA) sea level rise (SLR) projections. Here, we generate alternative BFE maps (STORMTOOLS Design Elevation (SDE) maps) for coastal waters of Rhode Island (RI) using surge predictions from tropical and extratropical storms of the coupled surge-wave models from the US Army Corp of Engineers, North Atlantic Comprehensive Coast Study (NACCS). Wave predictions are based on application of a steady state, spectral wave model (STWAVE), while impacts of coastal erosion/accretion and changes of geomorphology are modeled using XBeach. The high-resolution application of XBeach to the southern RI shoreline has dramatically increased the ability to represent the details of dune erosion and overtopping and the associated development of surge channels and over-wash fans and the resulting landward impact on inundation and waves. All methods used were consistent with FEMA guidelines for the study area and used FEMA-approved models. Maps were generated for 0, 2 ft (0.6 m), 5 ft (1.5 m), 7 ft (2.1 m), and 10 ft (3.1 m) of sea level rise, reflecting NOAA high estimates at various times for the study area through 2100. Results of the simulations are shown for both the southern RI shoreline (South Coast) and Narragansett Bay, to facilitate communication of projected BFEs to the general public. The maps are hosted on the STORMTOOLS ESRI Hub to facilitate access to the data. They are also now part of the RI Coastal Resources Management Council (CRMC) risk-based permitting system. The user interface allows access to all supporting data including grade elevation, inundation depth, and wave crest heights as well as corresponding FEMA FIRM BFEs and associated zones.

Storm-surge and wave models are routinely used to assess the impact of hurricanes/cyclones for emergency preparedness. Although these models are forced by wind fields, generated by meteorological models in hindcast or forecast mode, selecting a wind model that can accurately resolve the wind field, especially near the hurricane/cyclone core, is a challenging task. This study used several wind hindcast models to force a coupled wave and storm-surge model for selected hurricanes, including Bob (1991), Irene (2011), and Sandy (2012). The resulting simulated storm-surge and wave parameters were compared with observations at a number of observational stations. The wind models include the European Center for Medium-Range Weather Forecasts (ECMWF), the Northeast Coastal Ocean Forecasting System (NECOFS) based on the Weather Research and Forecasting (WRF) model, and parametric wind based on National Hurricane Center (NHC) data sets. The results show that a wind model that has an error in prediction of peak wind speed of more than 20% (when compared with observations) can lead to significant errors in hydrodynamic simulations; using a poor wind model can result in errors as high as 50% for storm-surge and wave predictions. Further, although no single best wind model for all hindcast applications can be recommended (for every region), a wind model that can simulate the environmental wind field and the internal structure of a hurricane (e.g., NECOFS in this study) can better address this uncertainty compared with conventional parametric wind models. The location of a hurricane track relative to the region of interest is a key factor in selecting the proper wind model.

Misquamicut is a coastal community located in Westerly, Rhode Island with a high density of structures that is at risk from inundation, wave, and wind damage from large storm events. The area has suffered significant damage from storms in the past such as the Hurricane of 1938, Hurricane Carol in 1954, and most recently, Superstorm Sandy in 2012. This area is also highly susceptible to sea level rise (SLR), which is predicted to be as high as 7 feet by the year 2100 (NOAA, 2017). A tool called the Coastal Environmental Risk Index (CERI) was used to estimate damage to structures located in Misquamicut due to a 100 year storm event with and without 7 feet of sea level rise. Using CERI, four mitigation strategies were evaluated to improve resiliency of the community: basement window plugs, dune restoration and reinforcement, a tide gate, and elevation of structures.

Page 13 Coastal communities on the East Coast of the United States (US) are likely to experience a greater impact from tropical storms in the future.1 In addition to sea level rise (SLR), a number of studies have related climate change to an increase in the number of higher intensity tropical storm activity (Holland and Bruyere 2014; Yoshida et al. 2017). Along the barrier beaches and barrier islands bordering the U.S. East Coast, severe storms often cause widespread dune and beach erosion, resulting in beach recession and damage to infrastructure. As beaches erode, the natural protection they provide to coastal Numerical simulation of coastal erosion and its mitigation by living shoreline methods: A case study in southern Rhode Island

Oil spill modeling of the 2010 Deepwater Horizon discharge was performed to evaluate the fate of the oil in subsurface waters of the Gulf of Mexico. The oil fate model Spill Impact Model Application Package (SIMAP) was used to estimate rise rate of oil droplets, dissolution of oil constituents, movements of oil droplets and dissolved components, and degradation of hydrocarbon components in the deep-sea. As sampling during April–July 2010 was primarily performed within 20 km of the spill site, model predictions were compared to field data from within a 25-by-25-km box centered on the wellhead. Concentrations of soluble and semisoluble hydrocarbon components predicted by the model agreed well with chemical measurements when compared as frequency distributions within varying depth zones of the water column. The results showed that the soluble hydrocarbons primarily dissolved near the release depth, while semisoluble compounds were partially dissolved at depth and as droplets rose.

The objective of this paper is to present the results of a study on the effects of storm surge and sea level rise on the coastal town of Wickford, Rhode Island, and an evaluation of possible mitigation strategies. The analysis included estimating the 100 year still water elevation for Wickford, recreating FEMA’s FIRMs using the Coastal Hazard Analysis Modeling Program, and using a simplified surge model to evaluate flooding from different scenarios of storm surge associated with a given return period and varying amounts of sea level rise. The use of vertical barriers placed at key locations was evaluated and illustrated effectively both the reduction in flooded areas and the limitations of the mitigation strategies.

ABSTRACT While coupled ice-ocean models provide reliable hindcasts and large-scale predictions of ice conditions and movements in the Arctic, to date, operational models have not been implemented with sufficient spatial resolution or skill to define sea ice characteristics and dynamics needed for high resolution oil spill trajectory forecast modeling. Recently (2015) Nansen Environmental and Remote Sensing Centre (NERSC) researchers updated their modeling approach and rheology used for pack ice. They found that using the newly developed Elasto-Brittle (EB) model showed significant improvement in performance over the present Elastic-Viscous-Plastic (EVP) modeling approach used in the operational forecast and reanalysis versions of their TOPAZ4 coupled ice-ocean model. NERSC also integrated a wave-in-ice model (WIM) into a newly updated version of TOPAZ, to characterize waves in the Marginal Ice Zone (MIZ). RPS ASA’s oil transport and fate models OILMAP and SIMAP (OIL/Spill Impact Model Application Package) were updated, integrating the NERSC ice modeling products for use in transport and oil weathering algorithms. Oil trajectory model simulations, using the existing publically-available TOPAZ4 and updated ice model products, were compared with available in situ drifter data for the Beaufort Sea from the International Arctic Buoy Programme (IABP). The goal was to evaluate model performance (skill) against drifters that were trapped in the pack ice where the EB/EVP rheology applies. The comparisons show that model-based trajectories increasingly diverged from observations over days and weeks due to cumulative errors. The model using EB rheology more closely agreed with the IABP observations than TOPAZ with EVP, and the updated TOPAZ showed improved model performance over TOPAZ4. However, model skill was degraded by time-averaging of ocean and ice model vectors before input to the oil spill model. Demonstrated improvement of oil-in-ice spill modeling would help meet the needs for Arctic oil spill response in the coming decades. While the accuracy of individual oil model trajectories projected weeks to months into the future would be expected to be low, in the event of a spill, forecasts could be updated frequently (on a time scale of hours to days) with satellite information, aircraft observations, drifter data, and other observations to improve reliability. The overall transport patterns and results of an ensemble of trajectories would provide useful information for planning and risk assessments based on typical current and ice movement patterns.

A source–pathway-receptor method is used to assess the risk of the coastal community of Charlestown, RI, USA, to the 100-year storm, including effects of sea level rise (SLR) and shoreline/dune erosion. The 100-year storm is simulated using a chain of stochastic and physics-based models combined with a scenario-based approach. Storm surge and wave spectral parameters, obtained from the U.S. Army Corps of Engineers’ North Atlantic Coast Comprehensive Study (NACCS), are used as boundary conditions for high-resolution wave simulations, performed in the coastal and inundation zones using the steady-state spectral wave model STWAVE. Selected scenarios are defined to assess the magnitude of the variability in predicted damage resulting from the uncertainty in SLR, erosion rate, and time at which the 100-year storm would occur. Erosion rates are based on empirical analyses of historic rates of shoreline change, SLR measurements, and coastal erosion theory. The risk is measured in terms of damage to individual houses, based on damage curves developed in the U.S. Army Corps of Engineers, NACCS study. In addition, remediation scenarios are explored, demonstrating that a combination of dune replenishment and an increase in the residential resilience by elevating structures can significantly diminish the risk to the coastal community.