Geology topics

Nicholas M. Enwright

Publications and source records attributed to Nicholas M. Enwright.

At least 19 recordsLinked to original sources

USGS2026

Forecasting marsh resilience in the Plum Island Estuary: Integrating uncertainty to inform coastal management

Salt marshes provide critical ecosystem services yet face increasing threats from accelerated relative sea-level rise (SLR). The long-term persistence of these habitats depends on their ability to vertically accrete and laterally migrate into adjacent uplands. Predicting the location and viability of these future marsh corridors is therefore a primary challenge for coastal managers; one often hindered by uncertainties in future water levels and topographic data accuracy, particularly in vegetated wetlands where light detection and ranging (lidar) data systematically overestimate elevation. This study applies an uncertainty-informed modeling framework to forecast marsh resilience in the Plum Island Estuary, Massachusetts. We integrated the Sea Level Affecting Marshes Model (SLAMM) with a Monte Carlo error analysis, generating an ensemble of bias-corrected digital elevation models (DEMs) alongside three probabilistic SLR scenarios (Intermediate, Intermediate High, High) through 2100. We synthesized these simulations into a “marsh fate” classification map to distinguish between resilient core habitats, vulnerable zones requiring intervention, and likely migration corridors. While the marsh platform exhibits resilience under Intermediate scenarios, a critical tipping point emerges under the High SLR scenario. In this case, accelerating inundation overwhelms accretion capacities, driving a landscape-scale regime shift. By integrating the interacting uncertainties of SLR trajectories and initial marsh elevation, we project 2100 net marsh coverage outcomes ranging from a 10.5% gain to a 23.2% loss. These results demonstrate that incorporating elevation uncertainty is essential for detecting non-linear threshold behaviors that deterministic models often miss. The resulting framework empowers managers with a spatially explicit tool to prioritize land acquisition and restoration efforts in the face of climate uncertainty.

Massachusetts↗

USGS2026

Incorporating wetland drowning thresholds to assess the spatiotemporal variability in potential wetland migration and submergence from sea-level rise

In the coming decades sea-level rise rates could exceed the upper bounds of coastal wetland vertical movement leading to wetland submergence. Consequently, understanding the spatiotemporal variability of wetland migration and submergence at regional and national scales can inform decision making. In this study, we developed an approach that addresses elevation error in digital elevation models for wetlands, incorporates uncertainty in current and future water levels, and utilizes recent literature on coastal wetland drowning thresholds. We used our framework to predict wetland change with sea-level rise for the middle and upper Texas coast—a region that is experiencing some of the highest relative sea-level rise rates in the United States. Our elevation-based approach produced contemporary wetland maps that had a high level of agreement (> 87–91%) with existing national wetland maps. For the intermediate relative sea-level rise scenario, extensive change is predicted within the study area by 2100, including a net decrease in coverage of irregularly oceanic-flooded wetlands (-37%) and regularly oceanic-flooded wetlands (-23%). The wetland migration space of these two wetland zones is largely made up of existing wetlands (> 70%), but also includes other upland areas, such as pasture/hay and grassland. By breaking down our results for the full region and two distinct focal areas, we highlight the spatiotemporal variability of wetland change. Our scalable approach provides natural resource managers with information for developing location-specific strategies for balancing the trade-offs associated with wetland change from sea-level rise.

Texas↗

USGS2026

Towards a refined definition of “tidal influence” for the coastal wetland sciences

The astronomical tide relates to lunar (and to a lesser extent solar) influences on rising and falling water bodies, and is a key control of many coastal processes. However, tides manifest along coastal margins in different ways to muddle application beyond Sir Isaac Newton’s first descriptions. Here, we argue that tide, or specifically “tidal,” has not been adequately defined for the coastal wetland sciences to facilitate contemporary interdisciplinary distinction for rapidly changing coastlines and future climate adaptation planning. We provide a brief history of the tidal concept, and we describe tides in a diversity of uncommonly recognized marginal coastal environments. Common astronomical tide manifestations are described through hydrographic examples, then expanded to include those tidal environments exposed additionally to fluvial, meteorological (wind), or groundwater influences. Our expanded definition of “tidal” is intended to be a forward-looking construct as environments will inevitably change with sea-level rise, water extraction, and anthropogenic flow alteration. Our definition of wetland tidal influence, which we broaden, includes those “wetlands affected by astronomic water level fluctuations within coastally restricted environments causing frequent or infrequent surface inundation or groundwater tidal variation that affects the biogeochemistry of the soil (e.g., ion exchange capacity, oxygen state, mineralization processes)”. Astronomic water level fluctuations are often amplified or dampened by non-astronomical events, such as wind. Expanding the definition of what is considered tidal by the scientific community is critical for improved understanding of coastal wetland function and the suite of ecosystem services they provide people and society, including climate mitigation opportunity, management, and adaptation.

Wetlands↗

USGS2026

Loss and transformation of coastal wetlands due to global change in the conterminous United States: Past, present, and future

Coastal wetlands are being transformed by global change, impacting the ecological and societal benefits provided by these ecosystems. Synthesizing knowledge of historical and expected future transformations in coastal wetlands can help inform forward-looking planning and stewardship efforts. Here, we review anticipated future ecological transformations in coastal wetlands of the conterminous United States and contrast them with past transformations. We examine trends at the national scale but focus in detail on the following six wetland-rich regions: (1) Everglades, (2) Mississippi River delta, (3) Chesapeake Bay, (4) San Francisco Estuary, (5) Puget Sound, and (6) Great Lakes. This review is among the first to integrate and compare coastal wetland transformations in the Great Lakes with their oceanic counterparts. Between 1850 and 1970, wetland losses across the nation were high because coastal wetlands were viewed as flooded wastelands needing to be drained, filled, or excavated to make room for other land uses. Over the last 50 years, growing public and scientific appreciation of the ecological and societal benefits provided by coastal wetlands has fostered tremendous gains in wetland restoration and legal protection. Looking to the future, climate change and accelerated sea-level rise have become critical threats to coastal wetlands and are emerging as major drivers of ecological loss and transformation. This review synthesizes regional knowledge regarding past, present, and future changes to help coastal scientists, environmental managers, and the public better anticipate and prepare for future coastal wetland transformations due to climate change, accelerated sea-level rise, land-use change, and other aspects of global change.

conterminous United States↗

USGS2026

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana↗

USGS2025

Inundation processes, barrier island breaching, and structure impacts during Hurricane Michael (2018)

We demonstrate the increased ability to forecast hurricane impacts with a coupled numerical modeling system by simulating ocean waves, water levels, currents, sediment transport, and structural damage to predict inundation, coastal morphological change, and residential building impacts. The Coupled-Ocean-Atmosphere-Waves-Sediment-Transport (COAWST) modeling system is applied to simulate Hurricane Michael (category 5, 2018) that made landfall near Tyndall Air Force Base, FL, in the northern Gulf of America, causing severe devastation and flooding. Atmospheric forcings from the Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) are used to drive the ocean and wave models on a series of nested grids. Results identify that coastal inundation at Mexico Beach is due to surge from winds and waves, supplemented by pulses of infragravity wave motions that propagate landward into the inundation region. Seed lines observed on interior building walls also demonstrate variable changes in water level. In addition, a machine learning model was applied to hindcast structure damages, caused mostly by waves and winds, with a 72% accuracy estimate of substantial damage in proximity of landfall. The storm also created a breach across Cape San Blas, the adjacent barrier spit, due to large surge and low dune elevations. Dune locations with vegetated land cover are shown to reduce wave-energy dissipation and reduce erosion, whereas locations without land cover had increased breaching potential. The breach occurred during the maximum ocean-side water level, and the delayed high water on the bay side allowed a pressure gradient to drive flow seaward and promote breach development.

Florida↗

USGS2025

Understanding abundances and behaviors of shorebirds in coastal Louisiana

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.

BioRxiv↗

USGS2024

Projected sea-level rise and high tide flooding at San Juan National Historic Site, Puerto Rico

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at San Juan National Historic Site, Puerto Rico, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

San Juan National Historic Site↗

USGS2024

Projected sea-level rise and high tide flooding at Dry Tortugas National Park, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Dry Tortugas National Park, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗

USGS2024

Projected sea-level rise and high tide flooding at Biscayne National Park, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Biscayne National Park, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗

USGS2024

Projected sea-level rise and high tide flooding at Big Cypress National Preserve, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Big Cypress National Preserve, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗

USGS2024

Assessing the vertical accuracy of digital elevation models by quality level and land cover

The vertical accuracy of elevation data in coastal environments is critical because small variations in elevation can affect an area’s exposure to waves, tides, and storm-related flooding. Elevation data contractors typically quantify the vertical accuracy of lidar-derived digital elevation models (DEMs) on a per-project basis to gauge whether the datasets meet quality and accuracy standards. Here, we collated over 5200 contractor elevation checkpoints along the Atlantic and Gulf of Mexico coasts of the United States that were collected for project-level analyses produced for assessing DEMs acquired for the U.S. Geological Survey’s Three-Dimensional Elevation Program. We used land cover data to quantify non-vegetated vertical accuracy and vegetated vertical accuracy statistics (overall and by point spacing bins) and assessed elevation error by land cover class. We found the non-vegetated vertical accuracy had an overall root mean square error of 6.9 cm and vegetated areas had a 95th percentile vertical error of 22.3 cm. Point spacing was generally positively correlated to elevation accuracy, but sample size limited the ability to interpret results from accuracy by land cover, particularly in wetlands. Based on the specific questions a researcher may be asking, use of literature or fieldwork could assist with enhancing error statistics in underrepresented classes.

Remote Sensing Letters↗

USGS2024

Projected sea-level rise and high tide flooding at De Soto National Memorial, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at De Soto National Memorial, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗

USGS2024

Projected sea-level rise and high tide flooding at Timucuan Ecological and Historic Preserve, Florida

Introduction National parks and preserves in the South Atlantic-Gulf Region contain valuable coastal habitats such as tidal wetlands and mangrove forests, as well as irreplaceable historic buildings and archeological sites located in low-lying areas. These natural and cultural resources are vulnerable to accelerated sea-level rise and escalating high tide flooding events. Through a Natural Resources Preservation Program-funded project during 2021–23, the U.S. Geological Survey, in collaboration with the National Park Service, estimated the probability of inundation at Timucuan Ecological and Historic Preserve, Florida, and several other parks under various sea-level rise scenarios and contemporary high tide flooding thresholds. The maps produced for this effort can be used to assess potential habitat change and explore how infrastructure and cultural resources within the park may be exposed to future flooding-related hazards.

Florida↗

USGS2023

An introduction to the evaluation of restoration for avian species at Caminada Headland and Whiskey Island in Louisiana

Barrier islands are crucial for protecting Louisiana’s coastal communities and ecosystems as they reduce coastal erosion and help safeguard native flora and fauna. Along the Louisiana shoreline, these islands are mostly long and thin, running parallel to the shoreline. The islands typically consist of the following components: 1) a sandy beach facing the Gulf of Mexico; 2) vegetated and non-vegetated dunes; 3) overwash areas; 4) swales; 5) upland shrubs; 6) wetland shrubs, such as black mangrove (Avicennia germinans); 7) backbay marshes; and 8) tidal flats. Dune vegetation and vegetation along the back-barrier help bind and collect sediment, which create and maintain wetlands on the north side of the barrier islands. Barrier islands provide various ecological services including: 1) buffering waves to decrease storm impacts; 2) protecting wetlands that provide suitable reproductive habitat and nursery grounds for fish and shellfish; and 3) providing critical habitat for birds and sea turtles (Barbier 2013).

Louisiana↗

USGS2023

Site occupancy of focal shorebird species at Whiskey Island and Caminada Headland, Louisiana 2012–2020

Coastal restoration through island construction and augmentation is an increasingly common management method in the northern Gulf of Mexico, but evaluating the impacts to shorebird species is difficult. Shorebirds are mostly migratory and many aspects of their life history, including reproduction in some species, occur in other places. In addition, counts or observations of shorebirds made at any given time represent only a portion of the population and that proportion may change with site conditions such as time of day and weather. Dynamic occupancy models can account for imperfect detection and produce estimates of the proportion of area occupied over time as a way to track trends in bird utilization over time. In this chapter we report on occupancy trends for five focal shorebird species from Caminada Headland and Whiskey Island: American Oystercatcher ( Haematopus palliatus ), Piping Plover ( Charadrius melodus ), Red Knot ( Calidris canutus ), Snowy Plover ( Charadrius nivosus ), and Wilson’s Plover ( Charadrius wilsonia ). We examined up to nine years of surveys at the two sites to model long-term trends in occupancy rates from a period spanning before, during, and after restoration. Our objective was to determine if there was change in occupancy over time (trend) during the restoration period. Field sampling was conducted as described in Chapter 1 for the five focal species in this chapter. To create spatial units for occupancy analysis we used a grid of 53 unique cells at Caminada Headland and 26 unique cells at Whiskey Island. All observations of the species were located into spatial units using GIS and presence of each species in each cell was determined for each visit within a sampling season. Sampling seasons were defined for species as the period of time where they were most likely to be using the study area, and corresponded with wintering (August–May), breeding (April–August), or staging (March–October). We did not include covariates for initial occupancy or colonization and site survival because these were small sites with homogenous habitat. We did account for time of year within a season by treating survey date as a covariate of detection probability and allowed it to vary throughout the season. We tested for a trend in occupancy over time by determining if the estimated slope through the series of annual occupancy estimates was significantly different from 0. We conducted 153 total surveys at Caminada Headland from 11 January 2013 to 5 June 2019, and 213 total surveys at Whiskey Island from 7 August 2012 to 19 August 2020. The number of surveys per year varied by species and site and range from 6–23 per species annually at Caminada Headland and 11–28 per species annually at Whiskey Island. Occupancy trends were able to be assessed for all species at both sites, with the exception of the American Oystercatcher, which were only observed in sufficient numbers to estimate occupancy at Whiskey Island. We found a significant positive trend in occupancy from 0.325 to 0.741 for American Oystercatcher at Whiskey Island. There was no significant trend in Piping Plover occupancy at Caminada Headland where occupancy was consistently high (0.910 to 0.947). At Whiskey Island, Piping Plover occupancy estimates increased from 0.574 to 0.908 during the study period which was a significant increase. At Caminada Headland and Whiskey Island Red Knot occupancy varied from 0.482 to 0.891 and 0.350 to 0.742, respectively, but showed no significant trend over the study period. Snowy Plover occupancy at Caminada Headland increased significantly from 0.295 to 0.785 over the study period. Snowy Plover occupancy also increased significantly at Whiskey Island from 0.442 to 0.906. Wilson’s Plover occupancy declined slightly during the study period from 0.946 to 0.935 at Caminada Headland, and from 0.858 to 0.736 at Whiskey Island, but the decline was not significant at either site. We found no evidence that occupancy declined significantly for any of the species during the period prior to, during, and after restoration. We did find a significant increasing trend in occupancy for Snowy Plover at Caminada Headland and a significant increasing trend for American Oystercatcher, Piping Plover, and Snowy Plover at Whiskey Island. Our modeling results indicate that sampling such as this is sufficient for occupancy modeling and can provide a robust metric for comparison over time or among sites. In future research we plan to investigate the sample size needed to detect a trend. We are currently conducting a power analysis to determine the minimum amount of sampling necessary to have power to detect a trend based on the detection probabilities from this study.

Report↗

USGS2021

Assessing habitat change and migration of barrier islands

Barrier islands are dynamic environments that experience gradual change from waves, tides, and currents, and rapid change from extreme storms. These islands are expected to change drastically over the coming century due to accelerated sea-level rise and changes in frequency and intensity of storm events. The dynamic nature of barrier islands coupled with the importance of these environments make it critical for natural resource managers to understand how habitats on barrier islands are changing or may change over time to determine when and where management actions may be needed. In this study, we applied a habitat change assessment framework, which included exploring areal coverage and distribution changes and change component analysis. Change component analysis, which breaks differences into net gain/loss and allocation difference (i.e., habitat oscillation), has not previously been used to study barrier island habitat evolution. Here, we demonstrate the approach using habitat predictions from a geomorphic modeling effort on Dauphin Island, Alabama (USA). We explored differences of habitat predictions for potential island configurations with and without a beach and dune restoration action under future conditions related to sea level and storminess. We found a potential linkage between landward migration of barrier islands and exchange, an output of change component analysis. The hypothesis may be tested to explore whether this linkage applies over space and time and whether the approach is applicable to monitoring landward migration of coastal wetlands. Collectively, our results highlight the utility of change component analysis for monitoring and quantifying barrier island habitat change and migration.

Alabama↗

USGS2021

Developing bare-earth digital elevation models from structure-from-motion data on barrier islands

Unoccupied aerial systems can collect aerial imagery that can be used to develop structure-from-motion products with a temporal resolution well-suited to monitoring dynamic barrier island environments. However, topographic data created using photogrammetric techniques such as structure-from-motion represent the surface elevation including the vegetation canopy . Additional processing is required for estimating bare-earth elevation, which is critical for understanding the underlying geomorphology of these islands. In this study, we used a vegetation and elevation survey to produce bare-earth digital elevation models from structure-from-motion-derived elevation products for two sites on Dauphin Island, Alabama (USA). One site was exposed to high wave energy and included a mix of beach, dune, and barrier flat habitats that were dominated by supratidal/upland herbaceous vegetation. The second site was exposed to low wave energy and was dominated by intertidal marsh. Aerial imagery was collected in late fall of 2018 and spring of 2019. We tested several machine learning algorithms for predicting and removing elevation bias for vegetated areas using predictors that included spectral indices from unoccupied aerial systems-based multispectral imagery and landscape position information (e.g., relative topography and distance from shore). Models were developed for each site and season. We also explored how well the model from one season generalized to data from a different season for the same site. For developing initial digital surface models, we found that utilizing a minimum bin algorithm, as opposed to interpolation, led to lower elevation bias. For bias removal, Gaussian process regression performed the best and led to a root mean square error for the bare-earth digital elevation models of around 0.10 m for the high energy site and 0.15 m for the low energy site. Compared to the digital surface models, the root mean square error for the bare-earth digital elevation models was reduced by at least 29 percent for the high energy site and 69 percent for the low energy site. For all models, common predictors included surface elevation, vegetation greenness, and distance from the shoreline. The models produced comparable results when trained using data from a different season. The error estimates for all analyses were within published elevation standards for lidar data for vegetated areas. With calibration, this approach could be portable to other areas or data, such as aerial lidar (conventional or unoccupied), to provide an efficient and repeatable framework for monitoring geomorphology or provide baseline elevations for predicting changes to these environments under future conditions.

Alabama↗