No abstract

To assist in siting of offshore renewable energy facilities (wind, wave, and in-stream tidal, and ocean current), a marine spatial planning-based approach is proposed. The first level (Tier #1) screening determines the potential energy resource to be exploited and then identifies areas that are prohibited from siting because there is a direct, irreconcilable conflict, as determined by a stakeholder process and vetted by regulators. Areas that remain after these exclusions are implemented are candidates for facility siting. The next step involves considering technical (engineering and economic) attributes of the proposed energy development that further restricts the area under consideration. Finally, Tier #2 screening (not addressed here) evaluates other use conflicts such as recreational and commercial fishing areas, marine mammal feeding and breeding grounds and transit paths, bird migratory paths, feeding, and nesting areas, and similar issues that must be considered in facility siting.To facilitate the application of technology constraints on siting, two methods are proposed, a Technology Development Index (TDI) and a Principal Components - Cluster Analysis (PCCA). The TDI method, developed by the authors and presented in this paper, is the ratio of the Technical Challenge Index (TCI) to the Power Production Potential (PPP) of the energy extraction device. TCI is a measure of how difficult it is to site the device at a given location plus a measure of the distance to the closest electrical grid connection point. The PPP is an estimate of the annual power production of one of the devices. The site with the lowest TDI represents the optimum location. In practice, the study area is gridded and the TDI (TCI and PPP) is calculated for each grid. The method explicitly accounts for the spatial variability of all input data. Simulations can be performed either deterministically or stochastically, using a Monte Carlo method, so that uncertainties in the underlying input data are reflected in the estimated values of the TDI. The later approach allows detailed assessment of the sensitivity of the estimates to the input data and formulations of the TCI and PPP. The results are presented in the form of contours of TDI. The method can be applied to any offshore renewable energy type or extraction system once the technical attributes are specified.The PCCA approach uses several spatially varying variables that describe the key attributes of the siting decision (e.g., water depth, power production potential, distance to shore, and seabed conditions). The principal components are first determined from the gridded data and then clusters are identified. Finally, the clusters are mapped to the study area. The attributes and spatial distribution of clusters provide insight into the optimum locations for development.The two methods were employed in identifying potential areas for siting of a wind farm in coastal waters of Rhode Island, assuming lattice jacket support structures for the wind turbines. Both methods give consistent results and show locations where the ratio of technical challenge to power production is minimized.

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.

No abstract

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.