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At least 109 records · Page 6Linked to original sources

USGS2023

Monitoring and modeling dispersal of a submerged nearshore berm at the mouth of the Columbia River, USA

A submerged, low-relief nearshore berm was constructed in the Pacific Ocean near the mouth of the Columbia River, USA, using 216,000 m 3 of sediment dredged from the adjacent navigation channel. The material dredged from the navigation channel was placed on the northern flank of the ebb-tidal delta in water depths between 12 and 15 m and created a distinct feature that could be tracked over time. Field measurements and numerical modeling were used to evaluate the transport pathways, time scales, and physical processes responsible for dispersal of the berm and evaluate the suitability of the location for operational placement of dredged material to enhance the sediment supply to eroding beaches onshore of the placement site. Repeated multibeam bathymetric surveys characterized the initial berm morphology and dispersion of the berm between September 22, 2020, and March 10, 2021. During this time, the volume of sediment within the berm decreased by about 40%to 127,000 m 3 , the maximum height decreased by almost 60%, and the center of the deposit shifted onshore over 200 m. Observations of berm morphology were compared with predictions from a three-dimensional hydrodynamic and sediment transport model application to refine poorly constrained model input parameters including sediment transport coefficients, bed schematization, and grain size. The calibrated sediment transport model was used to predict the amount, timing, and direction of transport outside of the observed survey area. Model simulations predicted that tidal currents were weak in the vicinity of the berm and wave processes including enhanced bottom stresses and asymmetric bottom orbital velocities resulted in dominant onshore movement of sediment from the berm toward the coastline. Roughly 50% of the berm volume was predicted to disperse away from the initial placement site during the 169 day hindcast. Between 9 and 17% of the initial volume of the berm was predicted to accumulate along the shoreface of a shoreline reach experiencing chronic erosion directly onshore of the placement site. Scenarios exploring alternate placement locations suggested that the berm was relatively effective in enhancing the sediment supply along the eroding coastline north of the inlet. The transferable monitoring and modeling framework developed in this study can be used to inform implementation of strategic nearshore placements and regional sediment management in complex, high-energy coastal environments elsewhere.

Oregon, Washington↗

USGS2024

Skill assessment of a total water level and coastal change forecast during the landfall of a hurricane

The Total Water Level and Coastal Change Forecast (TWL&CC Forecast) provides coastal communities with 6-day notice of potential elevated water levels and coastal change (i.e., dune erosion, overwash, or inundation) on sandy beaches that threatens safety, infrastructure, or resources. This continuously operating model provides hourly information for select regions along U.S. Gulf of Mexico and Atlantic Ocean coastlines. The objective of this work is to assess the skill of forecasts during a period of elevated water levels along the coasts of North Carolina (NC) and South Carolina, USA caused by Hurricane Isaias in August 2020, using a combination of observations and model hindcasts. Water levels and waves were observed throughout the storm at three locations near Wrightsville Beach, NC, which provided information to assess forecast skill; a wave buoy offshore, a tide gage at a local pier, and a pressure sensor deployed at the pier. In addition to observations, the non-hydrostatic phase-resolving model SWASH (Simulating WAves till SHore) was forced with hourly wave energy spectra derived from a coupled Delft3D-SWAN simulation during the peak of Isaias, to complement observations by computing nearshore wave height and wave-induced setup and runup at the shoreline. During the storm peak, SWASH-simulated water levels at the sensor position were comparable to those at the maximum landward extent (bias = −0.05 m; gain = 0.26; r 2 = 0.99), suggesting that observations at the USGS sensor location were a useful proxy for total water level (TWL; sum of tide, surge and wave runup) at the shoreline that are predicted by the TWL&CC Forecast. The TWL forecast at Wrightsville Beach was consistent with observations from the USGS sensor (bias = −0.38 m and −0.74 m, scatter index = 0.22 and 0.28 for the two forecast model grids considered, respectively; weighted regression considering model uncertainty explained 95 percent of variability in observed TWL). Observed TWL was within the confidence interval of the TWL&CC Forecast for the 5 h at the storm peak. Forecast mean water levels (MWL; sum of tide, surge and wave setup) and tide gage observations were also consistent (bias = 0.07 m and 0.02 m for the forecast model grids; scatter index = 0.46; r 2 = 0.80). Forecast MWL at the storm peak was within 0.06 m of the observed MWL from the tide gage for both sites. In the region where Isaias made landfall, eight additional pressure sensors were compared to the peak TWL forecast (bias = 0.14 m; scatter index = 0.18). Forecast TWL explained 90 percent of observed variability in TWL when considering uncertainty of the forecast with a weighted regression. The results demonstrate that wave-driven water levels contributed a significant portion of the forecast TWL during Isaias (52 percent during the three peak hours of the storm), and that TWL were represented using the forecast model. Mean absolute error of the coastal change forecast and observed overwash is 0.4 and 0.14 for the two forecast model grids considered. The skill demonstrated by this computationally efficient method indicates that the forecasting system can provide fast and reliable predictions of TWL across hundreds of km of coastline at sub-km resolution, days to hours in advance of when storms threaten coastal regions.

Coastal Engineering↗

USGS2020

Methane oxidation dynamics in a karst subterranean estuary

Chemical gradients between fresh, brackish and saline waters shape biogeochemical reactions and organic matter transformation within subterranean estuaries. In the Yucatán Peninsula’s karst subterranean estuary (KSE), methane and dissolved organic matter generated during the anaerobic decomposition of tropical forest vegetation are transported into flooded cave networks where microbial consumption greatly reduces their concentrations in the groundwater. To test the hypothesis that chemoclines associated with salinity gradients of the KSE are sites of methane oxidation, we obtained methane concentration and δ 13 C profiles of unprecedented vertical resolution from within a fully-submerged cave system located 6.6 km inland from the coastline using the ‘OctoPiPi’ (OPP) water sampler. Along a 12–24 cm thick low-salinity-halocline at ∼4.5 m water depth, salinity increased from fresh to brackish (0.2–1.8 psu), methane concentrations decreased, and δ 13 C values increased, as expected for microbial methane oxidation. The underlying brackish water had elevated oxygen concentrations compared to the always anoxic freshwater, suggesting that aerobic methane oxidation is the dominant process facilitating methane consumption. By contrast, as salinity increased from 1.8 to 36 psu through a 24–36 cm thick high-salinity-halocline between the meteoric lens and the saline groundwater at ∼20 m water depth, methane concentrations and δ 13 C values were constant. Conservative mixing and kinetic isotope models incorporating the methane data confirm a hotspot for microbial methane oxidation at the low-salinity-halocline. At least 98% of methane originating in the anoxic freshwaters was removed before its transport via channelized flow towards the coastline. These findings provide novel insight into the spatial constraints of methane dynamics within a karst subterranean estuary.

Ox Bel Ha cave system↗

USGS2013

Geomorphic and human influence on large-scale coastal change

An increasing need exists for regional-scale measurements of shoreline change to aid in management and planning decisions over a broad portion of the coast and to inform assessments of coastal vulnerabilities and hazards. A recent dataset of regional shoreline change, covering a large portion of the U.S. East coast (New England and Mid-Atlantic), provides rates of shoreline change over historical (~ 150 years) and recent (25–30 years) time periods making it ideal for a broad assessment of the regional variation of shoreline change, and the natural and human-induced influences on coastal behavior. The variable coastal landforms of the region provide an opportunity to investigate how specific geomorphic landforms relate to the spatial variability of shoreline change. In addition to natural influences on the rates of change, we examine the effects that development and human modifications to the coastline have on the measurements of regional shoreline change. Regional variation in the rates of shoreline change is a function of the dominant type and distribution of coastal landform as well as the relative amount of human development. Our results indicate that geomorphology has measurable influence on shoreline change rates. Anthropogenic impacts are found to be greater along the more densely developed and modified portion of the coast where jetties at engineered inlets impound large volumes of sediment resulting in extreme but discrete progradation updrift of jetties. This produces a shift in averaged values of rates that may mask the natural long-term record. Additionally, a strong correlation is found to exist between rates of shoreline change and relative level of human development. Using a geomorphic characterization of the types of coastal landform as a guide for expected relative rates of change, we found that the shoreline appears to be changing naturally only along sparsely developed coasts. Even modest amounts of development influence the rates of change and the human imprint override the geomorphic signal. The study demonstrates that human activities associated with creating and maintaining coastal infrastructure alter the natural behavior of the coast over hundreds of kilometers and time spans greater than a century. This suggests that future assessments of vulnerability, based largely on rates of change along developed coastlines, need to take the role of human alterations into account.

Geomorphology↗

USGS2019

Assessing patterns of annual change to permafrost bluffs along the North Slope coast of Alaska using high-resolution imagery and elevation models

Coastal permafrost bluffs at Barter Island, on the North Slope, Beaufort Sea Coast of Alaska are among the most rapidly eroding along Alaska’s coast, having retreated up to 132 m between 1955 and 2015. Here we quantify rates and patterns of change over a single year using very-high resolution orthophotomosaics and co-registered surface elevation models derived from a survey-grade form of structure-from-motion photogrammetry from a fixed-wing, manned aircraft. The resulting elevation models were validated with over 10,000 ground check points and found that 95% agreed to within 20 cm, before accounting for real differences in the ground surface due to seasonality, vegetation, and checkpoint acquisition errors. This data set provides the most detailed and accurate measurements of coastal change to date along the Alaskan coast and the method is scaleable to more extensive coastlines. Between July 2014 and July 2015, the bluffs retreated an average of 1.3 m, and a maximum of 8.1 m, with an associated net volume loss of 38,100 ± 300 m3 (1.3 m3/m). This average retreat over this single year was slightly less than the 60-year mean rate of change of -1.5±0.1 m/yr, suggesting the 2014-2015 year represented relatively typical to slightly below average conditions. Most of the bluff material (70%) was lost during the 3 summer months (July to Sept) of 2014 and the remaining 30% between the late-summer and following winter-spring. The pattern of change was predominantly landward retreat of the top of the bluffs, removal of the debris apron and subsequent niching at the base of the bluffs during mid to late summer (July to Sept) followed by erosion of the bluff face and deposition of debris at the base of the bluff through the remainder of the year (Sept to the following July). Drivers of the observed change are likely a combination of thermal erosion on the bluff face throughout the summer and episodic thermo-mechanical removal of material, niching, and undercutting of the base associated with high-water levels driven by low-pressure storms and westerly winds. These patterns and high rates of change are believed to be broadly representative of coastal permafrost bluffs found along many high-latitude coastlines worldwide.

Alaska↗

USGS2015

A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

Great Lakes↗

USGS2017

Ecosystem features determine seagrass community response to sea otter foraging

Comparing sea otter recovery in California (CA) and British Columbia (BC) reveals key ecosystem properties that shape top-down effects in seagrass communities. We review potential ecosystem drivers of sea otter foraging in CA and BC seagrass beds, including the role of coastline complexity and environmental stress on sea otter effects. In BC, we find greater species richness across seagrass trophic assemblages. Furthermore, Cancer spp. crabs, an important link in the seagrass trophic cascade observed in CA, are less common. Additionally, the more recent reintroduction of sea otters, more complex coastline, and reduced environmental stress in BC seagrass habitats supports the hypotheses that sea otter foraging pressure is currently reduced there. In order to manage the ecosystem features that lead to regional differences in top predator effects in seagrass communities, we review our findings, their spatial and temporal constraints, and present a social-ecological framework for future research.

British Columbia, California↗

USGS2004

Geochemical characterization of tarballs on beaches along the California coast. Part I - Shallow seepage impacting the Santa Barbara Channel Islands, Santa Cruz, Santa Rosa and San Miguel

Tarballs are common along the southern California coastline. This study investigates tarballs from beaches along this coastline, with a focus on Santa Cruz, Santa Rosa, and San Miquel Islands in the Santa Barbara Channel. The tarballs were fingerprinted using biomarker and stable carbon isotope parameters, and then grouped according to genetic similarities. The data show that the tarballs are of natural and not anthropogenic origin and that all originate from source rock within the Miocene Monterey Formation via shallow seeps offshore. Sterane biomarker parameters were found to vary widely in the sample set. Biodegradation, especially of the regular steranes, is the primary process impacting the biomarker distributions in a large group of samples. The most common tarball occurrences appear to come from offshore seepage near the west end of Santa Cruz Island. Another major group most likely was transported north from near Santa Monica Bay. Several individual occurrences of some of these tarball groups also were found on beaches as far north as Pt. Reyes and as far south as San Diego, indicating significant long-distance dispersal by ocean currents. This study begins a library of tarball fingerprints to be used as a database to help distinguish between natural and anthropogenic tar occurrences all along the California coast, and to compare shallow seepage with future samples of deeper production oils from the same area.

Organic Geochemistry↗

USGS2022

Ocean acidification in the Gulf of Mexico: Drivers, impacts, and unknowns

Ocean acidification (OA) has resulted in global-scale changes in ocean chemistry, which can disturb marine organisms and ecosystems. Despite its extensively populated coastline, many marine-dependent communities, and valuable economies, the Gulf of Mexico (GOM) remains a relatively understudied region with respect to acidification. In general, the warm waters of the GOM are better buffered from acidification compared to higher latitude seas, yet long-term acidification has been documented in several GOM regions. OA within the GOM is recognized as spatially variable, particularly within the coastal zone where numerous physical and biogeochemical processes contribute to carbonate chemistry dynamics. The historical progression of OA within the entire GOM is difficult to assess because only a few dedicated long-term monitoring sites have recently been established, and full-water column observations are limited. However, environmental drivers on smaller scales that affect GOM acidification were found to include freshwater, nutrient, and carbonate discharge from large rivers; ocean warming, circulation and residence times; and episodic extreme weather events. GOM marine ecosystems provide essential services, including coastline protection and carbon dioxide removal, and habitats for many marine species that are economically and ecologically important. However, organismal and ecosystem responses to OA are not well constrained for the GOM due to a lack of studies examining the specific effects of OA on regionally relevant species under contemporary and projected conditions. Tackling the vast number of remaining scientific unknowns in this region can be best coordinated through regional capacity networks, such as the Gulf of Mexico Coastal Acidification Network (GCAN), working to achieve a system-wide understanding of Gulf OA and its impacts. Here we synthesize the current peer-reviewed literature on GOM acidification across the ocean-estuarine continuum and identify critical knowledge, research, and monitoring gaps that require future attention.

Progress in Oceanography↗

USGS2005

Stable isotope ratios in swale sequences of Lake Superior as indicators of climate and lake level fluctuations during the Late Holocene

Beach ridges along the coastline of Lake Superior provide a long-term and detailed record of lake level fluctuations for the past 4000 cal BP. Although climate change has been invoked to explain these fluctuations, its role is still in debate. Here, we reconstruct water balance by employing peat samples collected from swale deposits present between beach ridge sequences at two locations along the coastline of Lake Superior. Carbon isotope ratios for Sphagnum remains from these peat deposits are used as a proxy for water balance because the presence or absence of water films on Sphagnum controls the overall isotope discrimination effects. Consequently, increased average water content in Sphagnum produces elevated ??13C values. Two maxima of Sphagnum ??13C values interpreted to reflect wetter conditions prevailed from 3400 to 2400 cal BP and from about 1900 to 1400 cal BP. There are two relatively short drier periods as inferred from low Sphagnum ??13C values: one is centered at about 2300 cal BP, and one begins at 1400 cal BP. A good covariance was found between Sphagnum ??13C values and reconstructed lake-levels for Lake Michigan in which elevated carbon isotope values correlate well with higher lake levels. Based on this covariance, we conclude that climate exerts a strong influence on lake levels in Lake Superior for the past 4000 cal BP. ?? 2005 Elsevier Ltd. All rights reserved.

Quaternary Science Reviews↗

USGS2020

Testing glacial isostatic adjustment models of last-interglacial sea level history in the Bahamas and Bermuda

Part of the spatial variation in the apparent sea-level record of the last interglacial (LIG) period is due to the diverse response of coastlines to glacial isostatic adjustment (GIA) processes, particularly where coastlines were close to the Laurentide Ice Sheet during the past two glacial periods. We tested modeled LIG paleo-sea levels on New Providence Island (NPI), Bahamas and Bermuda by investigating emergent coral patch reefs and oolitic/peloidal beach deposits. Corals with closed-system histories collected from patch reefs on NPI have ages of 128-118 ka and ooids/peloids from beach ridges have closed-system ages of 128-116 ka. Elevations of patch reefs indicate a LIG paleo-sea level of at least ∼7 m to ∼9 m above present. Beach ridge sediments indicate paleo-sea levels of ∼5 m to ∼14 m (assuming subsidence, ∼7 m to ∼16 m) above present during the LIG. Some, though not all of these measurements are in good agreement with GIA models of paleo-sea level that have been simulated for the Bahamas. On Bermuda, corals with closed-system histories collected from marine deposits have ages of 126-114 ka. Although coral-bearing marine deposits on Bermuda lack the precise indication of paleo-sea level provided by patch reefs and oolitic beach ridges, these sediments nevertheless provide at least a first-order estimate of paleo-sea level. Paleo-sea level records on Bermuda are consistently lower (∼2 m to ∼7 m) than what GIA models simulate for the LIG. The reason for the reasonable agreement with models for the Bahamas and poor agreement for Bermuda is not understood, but needs further investigation in light of the probability of a higher sea level in the near future.

Quaternary Science Reviews↗

USGS2003

Stratigraphic framework of sediment-starved sand ridges on a mixed siliciclastic/carbonate inner shelf; west-central Florida

Seismic reflection profiles and vibracores have revealed that an inner shelf, sand-ridge field has developed over the past few thousand years situated on an elevated, broad bedrock terrace. This terrace extends seaward of a major headland associated with the modern barrier-island coastline of west-central Florida. The overall geologic setting is a low-energy, sediment-starved, mixed siliciclastic/carbonate inner continental shelf supporting a thin sedimentary veneer. This veneer is arranged in a series of subparallel, shore-oblique, and to a minor extent, shore-parallel sand ridges. Seven major facies are present beneath the ridges, including a basal Neogene limestone gravel facies and a blue-green clay facies indicative of dominantly authigenic sedimentation. A major sequence boundary separates these older units from Holocene age, organic-rich mud facies (marsh), which grades upward into a muddy sand facies (lagoon or shallow open shelf/seagrass meadows). Cores reveal that the muddy shelf facies is either in sharp contact or grades upward into a shelly sand facies (ravinement or sudden termination of seagrass meadows). The shelly sand facies grades upward to a mixed siliciclastic/carbonate facies, which forms the sand ridges themselves. This mixed siliciclastic/carbonate facies differs from the sediment on the beach and shoreface, suggesting insignificant sediment exchange between the offshore ridges and the modern coastline. Additionally, the lack of early Holocene, pre-ridge facies in the troughs between the ridges suggests that the ridges themselves do not migrate laterally extensively. Radiocarbon dating has indicated that these sand ridges can form relatively quickly (???1.3 ka) on relatively low-energy inner shelves once open-marine conditions are available, and that frequent, high-energy, storm-dominated conditions are not necessarily required. We suggest that the two inner shelf depositional models presented (open-shelf vs. migrating barrier-island) may have co-existed spatially and/or temporally to explain the distribution of facies and vertical facies contacts. ?? 2003 Elsevier B.V. All rights reserved.

Marine Geology↗

USGS2014

The effects of spilled oil on coastal ecosystems: Lessons from the Exxon Valdez spill

Oil spilled from ships or other sources into the marine environment often occurs in close proximity to coastlines, and oil frequently accumulates in coastal habitats. As a consequence, a rich, albeit occasionally controversial, body of literature describes a broad range of effects of spilled oil across several habitats, communities, and species in coastal environments. This statement is not to imply that spilled oil has less of an effect in pelagic marine ecosystems, but rather that marine spills occurring offshore may be less likely to be detected, and associated effects are more difficult to monitor, evaluate, and quantify (Peterson et al ., 2012). As a result, we have a much greater awareness of coastal pollution, which speaks to our need to improve our capacities in understanding the ecology of the open oceans. Conservation of coastal ecosystems and assessment of risks associated with oil spills can be facilitated through a better understanding of processes leading to direct and indirect responses of species and systems to oil exposure. It is also important to recognize that oil spilled from ships represents only ~9% of the nearly 700 000 barrels of petroleum that enter waters of North America annually from anthropogenic sources (NRC, 2003). The immediate effects of large spills can be defined as acute, due to the obvious and dramatic effects that are observed. In contrast, the remaining 625 000 barrels that are released each year can be thought of as chronic non-point pollution, resulting from oil entering the coastal ocean as runoff in a more consistent but much less conspicuous rate. In this chapter, we primarily address the effects of large oil spills that occur near coastlines and consider their potential for both acute and chronic effects on coastal communities. As described below, in some instances, the effects from chronic exposure may meet or exceed the more evident acute effects from large spills. Consequently, although quantifying chronic effects from low exposure rates can be challenging and time-consuming, the results of such efforts provide insights into the understudied effects of chronic non-point oil pollution.

Alaska↗

USGS2008

Coastal strategies to predict Escherichia coli concentrations for beaches along a 35 km stretch of southern Lake Michigan

To understand the fate and movement of Escherichia coli in beach water, numerous modeling studies have been undertaken including mechanistic predictions of currents and plumes and empirical modeling based on hydrometeorological variables. Most approaches are limited in scope by nearshore currents or physical obstacles and data limitations; few examine the issue from a larger spatial scale. Given the similarities between variables typically included in these models, we attempted to take a broader view of E. coli fluctuations by simultaneously examining twelve beaches along 35 km of Indiana's Lake Michigan coastline that includes five point-source outfalls. The beaches had similar E. coli fluctuations, and a best-fit empirical model included two variables: wave height and an interactive term comprised of wind direction and creek turbidity. Individual beach R2 was 0.32-0.50. Data training-set results were comparable to validation results (R2 = 0.48). Amount of variation explained by the model was similar to previous reports for individual beaches. By extending the modeling approach to include more coastline distance, broader-scale spatial and temporal changes in bacteria concentrations and the influencing factors can be characterized. ?? 2008 American Chemical Society.

Environmental Science & Technology↗

USGS2011

New products from the shuttle radar topography mission

New data products with broad applicability to the Earth sciences are now available from the Shuttle Radar Topography Mission (SRTM). SRTM, a joint project of the National Geospatial-Intelligence Agency (NGA) and NASA, flew aboard the Space Shuttle Endeavour on an 11-day mission in February 2000 with the goal of collecting a near-global data set of high-resolution elevation data [ Fan and Kobrick , 2000]. Data from the mission have been available to researchers for several years, but newly available products offer enhanced usability and applicability. Final products include elevation data resulting from a substantial editing effort by the NGA in which water bodies and coastlines were well defined and data artifacts known as spikes and wells (single pixel errors) were removed. This second version of the SRTM data set, also referred to as ‘finished’ data, represents a significant improvement over earlier versions that had nonflat water bodies, poorly defined coastlines, and numerous noise artifacts. The edited data are available at a one-arc-second resolution (approximately 30 meters) for the United States and its territories, and at a three-arc-second resolution (approximately 90 meters) for non-U.S. areas.

Eos, Transactions, American Geophysical Union↗

USGS2021

Saltwater intrusion intensifies coastal permafrost thaw

Surface effects of sea-level rise (SLR) in permafrost regions are obvious where increasingly iceless seas erode and inundate coastlines. SLR also drives saltwater intrusion, but subsurface impacts on permafrost-bound coastlines are unseen and unclear due to limited field data and the absence of models that include salinity-dependent groundwater flow with solute exclusion and freeze-thaw dynamics. Here, we develop a numerical model with the aforementioned processes to investigate climate change impacts on coastal permafrost. We find that SLR drives lateral permafrost thaw due to depressed freezing temperatures from saltwater intrusion, whereas warming drives top-down thaw. Under high SLR and low warming scenarios, thaw driven by SLR exceeds warming-driven thaw when normalized to the influenced surface area. Results highlight an overlooked feedback mechanism between SLR and permafrost thaw with potential implications for coastal infrastructure, ocean-aquifer interactions, and carbon mobilization.

Geophysical Research Letters↗

USGS2023

A model integrating satellite-derived shoreline observations for predicting fine-scale shoreline response to waves and sea-level rise across large coastal regions

Satellite-derived shoreline observations combined with dynamic shoreline models enable fine-scale predictions of coastal change across large spatiotemporal scales. Here, we present a satellite-data-assimilated, “littoral-cell”-based, ensemble Kalman-filter shoreline model to predict coastal change and uncertainty due to waves, sea-level rise (SLR), and other natural and anthropogenic processes. We apply the developed ensemble model to the entire California coastline (approximately 1,760 km), much of which is sparsely monitored with traditional survey methods (e.g., Lidar/GPS). Water-level-corrected, satellite-derived shoreline observations (obtained from the CoastSat toolbox) offer a nearly unbiased representation of in situ surveyed shorelines (e.g., mean sea-level elevation contours) at Ocean Beach, San Francisco. We demonstrate that model calibration with satellite observations during a 20-year hindcast period (1995–2015) provides nearly equivalent model forecast accuracy during a validation period (2015–2020) compared to model calibration with monthly in situ observations at Ocean Beach. When comparing model-predicted shoreline positions to satellite-derived observations, the model achieves an accuracy of <10 m RMSE for nearly half of the entire California coastline for the validation period. The calibrated/validated model is then applied for multi-decadal simulations of shoreline change due to projected wave and sea-level conditions, while holding the model parameters fixed. By 2100, the model estimates that 24%–75% of California's beaches may become completely eroded due to SLR scenarios of 1.0–3.0 m, respectively. The satellite-data-assimilated modeling system presented here is generally applicable to a variety of coastal settings around the world owing to the global coverage of satellite imagery.

JGR Earth Surface↗

USGS2023

A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments

The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models that carry out supervised (i.e., human-guided) pixel-based classification, or image segmentation, have transformative applications in spatio-temporal mapping of dynamic environments, including transient coastal landforms, sediments, habitats, waterbodies, and water flows. However, these models require large and well-documented training and testing datasets consisting of labeled imagery. We describe “Coast Train,” a multi-labeler dataset of orthomosaic and satellite images of coastal environments and corresponding labels. These data include imagery that are diverse in space and time, and contain 1.2 billion labeled pixels, representing over 3.6 million hectares. We use a human-in-the-loop tool especially designed for rapid and reproducible Earth surface image segmentation. Our approach permits image labeling by multiple labelers, in turn enabling quantification of pixel-level agreement over individual and collections of images.

Scientific Data↗