Integrated and Adaptable Approach to Mapping Benthic Habitats to Support Offshore Wind Development off the Mid-Atlantic Outer Continental Shelf

Four annual (2019–2022) benthic surveys were acquired to support Site Characterization and subsequent permitting processes. High-Resolution Geophysical data were collected concomitantly with the 2020 benthic survey data and used to refine subsequent 2021 and 2022 benthic survey designs. Benthic survey data consisted of grab sample tests (grain size), macrofaunal taxonomy, sediment profile and plan view imagery (SPI-PV), video imagery from each grab station, and towed video transects. Acoustic data products were processed and interpreted to create polygons of seafloor sediment coverage over the ASOW study area and ground-truthed with physical sampling, video, and digital still imagery to refine and validate acoustic data into a mappable model of essential fish and benthic habitats.

Seafloor morphology and seabed sediment interpretations were coalesced into a benthic habitat model that displayed substrates consisting mostly of mobile sand sheets, with interspersed areas of gravelly sand and discrete patches of gravel. Overlying the substrate model was a range of benthic features and morphologies, including sand ridges, sand waves, megaripples, ripples, areas of depressional marks, hummocky seafloor, interbedded surficial sediments, irregular seafloor, and localized relief features. From these data, classified maps of Coastal Marine Ecological Standard (CMECS) substrates and fish habitats were made. Additional CMECS classification of benthic biotic components were mapped, showing the taxonomic communities that are present in each substrate.

Seabed sediment modeling and morphological trends were dynamically studied and compiled into an interpreted and GIS-friendly dataset that enabled rapid online transfer to subject matter experts tasked with quantifying the benthic ecosystem across the development area. The methods and modeling that were produced by expert refinement of geophysical data to reflect the physically observed habitat structures allowed for dynamic minimum mapping unit variability while also isolating and identifying key areas of interest for benthic researchers and regulators. This mapping process led to an efficient and unified approach for all teams, saving project time and expense.