Structure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimensional (3D) spatial products from both singular and repeated collections of shoreline aerial imagery. The products can be used for real-time hazard guidance and future forecasting and recovery endeavors.

Large geomorphic changes to barrier islands may occur during inundation, when storm surge exceeds island elevation. Inundation occurs episodically and under energetic conditions that make quantitative observations difficult. We measured water levels on both sides of a barrier island in the northern Chandeleur Islands during inundation by Hurricane Isaac. Wind patterns caused the water levels to slope from the bay side to the ocean side for much of the storm. Modeled geomorphic changes during the storm were very sensitive to the cross‐island slopes imposed by water‐level boundary conditions. Simulations with equal or landward sloping water levels produced the characteristic barrier island storm response of overwash deposits or displaced berms with smoother final topography. Simulations using the observed seaward sloping water levels produced cross‐barrier channels and deposits of sand on the ocean side, consistent with poststorm observations. This sensitivity indicates that accurate water‐level boundary conditions must be applied on both sides of a barrier to correctly represent the geomorphic response to inundation events. More broadly, the consequence of seaward transport is that it alters the relationship between storm intensity and volume of landward transport. Sand transported to the ocean side may move downdrift, or aid poststorm recovery by moving onto the beach face or closing recent breaches, but it does not contribute to island transgression or appear as an overwash deposit in the back‐barrier stratigraphic record. The high vulnerability of the Chandeleur Islands allowed us to observe processes that are infrequent but may be important at other barrier islands.

We describe and demonstrate algorithms for treating cohesive and mixed sediment that have been added to the Regional Ocean Modeling System (ROMS version 3.6), as implemented in the Coupled Ocean–Atmosphere–Wave–Sediment Transport Modeling System (COAWST Subversion repository revision 1234). These include the following: floc dynamics (aggregation and disaggregation in the water column); changes in floc characteristics in the seabed; erosion and deposition of cohesive and mixed (combination of cohesive and non-cohesive) sediment; and biodiffusive mixing of bed sediment. These routines supplement existing non-cohesive sediment modules, thereby increasing our ability to model fine-grained and mixed-sediment environments. Additionally, we describe changes to the sediment bed layering scheme that improve the fidelity of the modeled stratigraphic record. Finally, we provide examples of these modules implemented in idealized test cases and a realistic application.

Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier‐island evolution emphasize ocean‐side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36‐km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm‐surge model results and observations of high‐water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co‐located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post‐storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within 2 months. This event represents a volumetric setback in the overwash/rollover behavior required for barrier transgression, but the new ponds and lowland habitats may provide beneficial habit for endangered species and will likely persist for years.

Segmentation, or the classification of pixels (grid cells) in imagery, is ubiquitously applied in the natural sciences. Manual methods are often prohibitively time‐consuming, especially those images consisting of small objects and/or significant spatial heterogeneity of colors or textures. Labeling complicated regions of transition that in Earth surface imagery are represented by collections of mixed‐pixels, ‐textures, and ‐spectral signatures, can be especially error‐prone because it is difficult to reliably unmix, identify and delineate consistently. However, the success of supervised machine learning (ML) approaches is entirely dependent on good label data. We describe a fast, semi‐automated, method for interactive segmentation of N‐dimensional (x, y, N) images into two‐dimensional (x, y) label images. It uses human‐in‐the‐loop ML to achieve consensus between the labeler and a model in an iterative workflow. The technique is reproducible; the sequence of decisions made by human labeler and ML algorithms can be encoded to file, so the entire process can be played back and new outputs generated with alternative decisions and/or algorithms. We illustrate the scientific potential of segmentation of imagery of diverse settings and image types using six case studies from river, estuarine, and open coast environments. These photographic and non‐photographic imagery consist of 1‐ and 3‐bands on regular and irregular grids ranging from centimeters to tens of meters. We demonstrate high levels of agreement in label images generated by several labelers on the same imagery, and make suggestions to achieve consensus and measure uncertainty, ideal for widespread application in training supervised ML for image segmentation.

Particle settling velocity and erodibility are key factors that govern the transport of sediment through coastal environments including estuaries. These are difficult to parameterize in models that represent mud, whose properties can change in response to many factors, including tidally varying suspended sediment concentration (SSC) and shear stress. Using the COAWST (Coupled Ocean-Atmosphere-Wave-Sediment Transport) model framework, we implemented bed consolidation, sediment-induced stratification, and flocculation formulations within an idealized two-dimensional domain that represented the longitudinal dimension of a micro-tidal, muddy, partially mixed estuary. Within the Estuarine Turbidity Maximum (ETM), SSC and median floc diameter varied by a factor of four over the tidal cycle. Downstream of the ETM, the median floc size and SSC were several times smaller and showed less tidal variation (~20% or less). The suspended floc distributions only reached an equilibrium size as a function of SSC and shear in the ETM at peak tidal flow. In general, flocculation increased particle size, which reduced SSC by half in the ETM through increased settling velocity. Consolidation also limited SSC by reduced resuspension, which then limited floc growth through reduced SSC by half outside of the ETM. Sediment-induced stratification had negligible effects in the parameter space examined. Efforts to lessen the computation cost of the flocculation routine by reducing the number of size classes proved difficult; floc size distribution and SSC were sensitive to specification of size classes by factors of 60% and 300%, respectively.