E. Robert Thieler

Geology of the Wrightsville Beach, North Carolina shoreface: Implications for the concept of shoreface profile of equilibrium

Abstract Nearly 300 km of 3.5 kHz subbottom profile and 100 kHz sidescan-sonar data, a suite of over 100 short (~2 m) percussion cores and vibracores have been collected on the shoreface and inner continental shelf off Wrightsville Beach, North Carolina. Sidescan-sonar images were analyzed for acoustic backscatter to delineate the surface sediment distribution. Groundtruth data for the sidescan-sonar interpretations were provided by surface grab samples. Cross-shore sediment transport by combined waves and currents is the predominant sedimentologic signature on this shoreface. The shoreface is dominated by a shore-normal system of rippled scour depressions that begin in 3–4 m water depth and extend to the base of the shoreface about 1 km offshore, at 10 m depth. The depressions are 40–100 m wide, and up to 1 m deep. They are floored by coarse, rippled shell hash and gravel; some are separated by rock-underlain fine sand ridges. On the inner shelf, the bathymetric and sedimentary fabrics become shore-oblique, due to a series of relict ridges with 1–2 m of relief. The ridges are coarse on their landward sides and covered on their seaward flanks by thin veneers of fine sand. Field evidence from the Wrightsville Beach shoreface demonstrates that a shoreface equilibrium profile as defined by Dean (1991) and others does not exist here. For example: (1) the grain size varies widely and inconsistently over the profile; (2) shoreface profile shape is controlled predominantly by underlying geology, including Tertiary limestone outcrops and Oligocene silts; and (3) sediment transport patterns cannot be explained by simple diffusion due to wave energy gradients, and that transport occurs seaward of the assumed engineering “closure depth” of 8.5 m. This has several implications for the application of equilibrium profile-based numerical models used to investigate coastal processes and design coastal engineering projects at Wrightsville Beach. The most important practical implication is that a number of assumptions required by existing analytical and numerical models (e.g., Dean, 1991; genesis ; sbeach ) used for the design of shore protection projects and large-scale coastal modeling over decadal time scales cannot be met.

Catastrophic meltwater discharge down the Hudson Valley: A potential trigger for the Intra-Allerød cold period

Glacial freshwater discharge to the Atlantic Ocean during de- glaciation may have inhibited oceanic thermohaline circulation, and is often postulated to have driven climatic fluctuations. Yet attributing meltwater-discharge events to particular climate oscil- lations is problematic, because the location, timing, and amount of meltwater discharge are often poorly constrained. We present ev- idence from the Hudson Valley and the northeastern U.S. conti- nental margin that establishes the timing of the catastrophic drain- ing of Glacial Lake Iroquois, which breached the moraine dam at the Narrows in New York City, eroded glacial lake sediments in the Hudson Valley, and deposited large sediment lobes on the New York and New Jersey continental shelf ca. 13,350 yr B.P. Excess 14 C in Cariaco Basin sediments indicates a slowing in thermohaline circulation and heat transport to the North Atlantic at that time, and both marine and terrestrial paleoclimate proxy records around the North Atlantic show a short-lived (,400 yr) cold event (Intra- Allerod cold period) that began ca. 13,350 yr B.P. The meltwater discharge out the Hudson Valley may have played an important role in triggering the Intra-Allerod cold period by diminishing thermohaline circulation.

Importance of Coastal Change Variables in Determining Vulnerability to Sea- and Lake-Level Change

Abstract In 2001, the U.S. Geological Survey began conducting scientific assessments of coastal vulnerability to potential future sea- and lake-level changes in 22 National Park Service sea- and lakeshore units. Coastal park units chosen for the assessment included a variety of geological and physical settings along the U.S. Atlantic, Pacific, Gulf of Mexico, Gulf of Alaska, Caribbean, and Great Lakes shorelines. This research is motivated by the need to understand and anticipate coastal changes caused by accelerating sea-level rise, as well as lake-level changes caused by climate change, over the next century. The goal of these assessments is to provide information that can be used to make long-term (decade to century) management decisions. Here we analyze the results of coastal vulnerability assessments for several coastal national park units. Index-based assessments quantify the likelihood that physical changes may occur based on analysis of the following variables: tidal range, ice cover, wave height, coastal slope, historical shoreline change rate, geomorphology, and historical rate of relative sea- or lake-level change. This approach seeks to combine a coastal systems susceptibility to change with its natural ability to adapt to changing environmental conditions, and it provides a measure of the systems potential vulnerability to the effects of sea- or lake-level change. Assessments for 22 park units are combined to evaluate relationships among the variables used to derive the index. Results indicate that Atlantic and Gulf of Mexico parks have the highest vulnerability rankings relative to other park regions. A principal component analysis reveals that 99% of the index variability can be explained by four variables: geomorphology, regional coastal slope, water-level change rate, and mean significant wave height. Tidal range, ice cover, and historical shoreline change are not as important when the index is evaluated at large spatial scales (thousands of kilometers).

Global and regional sea level rise scenarios for the United States

Environmental issues and disasters/Climatic and atmospheric; Environmental issues and disasters/Flood

Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network

Predictions of coastal evolution driven by episodic and persistent processes associated with storms and relative sea-level rise (SLR) are required to test our understanding, evaluate our predictive capability, and to provide guidance for coastal management decisions. Previous work demonstrated that the spatial variability of long-term shoreline change can be predicted using observed SLR rates, tide range, wave height, coastal slope, and a characterization of the geomorphic setting. The shoreline is not sufficient to indicate which processes are important in causing shoreline change, such as overwash that depends on coastal dune elevations. Predicting dune height is intrinsically important to assess future storm vulnerability. Here, we enhance shoreline-change predictions by including dune height as a variable in a statistical modeling approach. Dune height can also be used as an input variable, but it does not improve the shoreline-change prediction skill. Dune-height input does help to reduce prediction uncertainty. That is, by including dune height, the prediction is more precise but not more accurate. Comparing hindcast evaluations, better predictive skill was found when predicting dune height (0.8) compared with shoreline change (0.6). The skill depends on the level of detail of the model and we identify an optimized model that has high skill and minimal overfitting. The predictive model can be implemented with a range of forecast scenarios, and we illustrate the impacts of a higher future sea-level. This scenario shows that the shoreline change becomes increasingly erosional and more uncertain. Predicted dune heights are lower and the dune height uncertainty decreases.

Using a Bayesian network to predict barrier island geomorphologic characteristics

Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles uncertainty, which is intrinsic to future sea level rise, storminess, or anthropogenic processes (e.g., beach nourishment and other forms of coastal management). The BN was developed and tested at Assateague Island, Maryland/Virginia, USA, a barrier island with sufficient geomorphic and temporal variability to evaluate our approach. We tested the ability to predict dune height, beach width, and beach height variables using inputs that included longer-term, larger-scale, or external variables (historical shoreline change rates, distances to inlets, barrier width, mean barrier elevation, and anthropogenic modification). Data sets from three different years spanning nearly a decade sampled substantial temporal variability and serve as a proxy for analysis of future conditions. We show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the most skillful predictions of dune height, beach width, and beach height depend on including multiple input variables simultaneously. The predictive relationships are robust to variations in the amount of input data and to variations in model complexity. The resulting model can be used to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline change rates may differ from those observed historically.

'Cape capture': Geologic data and modeling results suggest the Holocene loss of a Carolina Cape

For more than a century, the origin and evolution of the set of cuspate forelands known as the Carolina Capes—Hatteras, Lookout, Fear, and Romain—off the eastern coast of the United States have been discussed and debated. The consensus conceptual model is not only that these capes existed through much or all of the Holocene transgression, but also that their number has not changed. Here we describe bathymetric, lithologic, seismic, and chronologic data that suggest another cape may have existed between Capes Hatteras and Lookout during the early to middle Holocene. This cape likely formed at the distal end of the Neuse-Tar-Pamlico fluvial system during the early Holocene transgression, when this portion of the shelf was flooded ca. 9 cal (calibrated) kyr B.P., and was probably abandoned by ca. 4 cal kyr B.P., when the shoreline attained its present general configuration. Previously proposed mechanisms for cape formation suggest that the large-scale, rhythmic pattern of the Carolina Capes arose from a hydrodynamic template or the preexisting geologic framework. Numerical modeling, however, suggests that the number and spacing of capes can be dynamic, and that a coast can self-organize in response to a high-angle-wave instability in shoreline shape. In shoreline evolution model simulations, smaller cuspate forelands are subsumed by larger neighbors over millennial time scales through a process of ‘cape capture.’ The suggested former cape in Raleigh Bay represents the first interpreted geological evidence of dynamic abandonment suggested by the self-organization hypothesis. Cape capture may be a widespread process in coastal environments with large-scale rhythmic shoreline features; its preservation in the sedimentary record will vary according to geologic setting, physical processes, and sea-level history.

Coastal sedimentary research examines critical issues of national and global priority

An international conference was held recently in Honolulu, Hawaii, to examine and plan for coastal sedimentary research in the United States and globally. Participants agreed that sedimentary coastal environments constitute a critical national and global resource that suffers widespread degradation due to human impacts. Moreover, human population growth and inappropriate development in the coastal zone are escalating public asset losses due to coastal hazards and placing large numbers of communities at growing risk (Figure 1).

UAS-SfM for Coastal Research: Geomorphic Feature Extraction and Land Cover Classification from High-Resolution Elevation and Optical Imagery

The vulnerability of coastal systems to hazards such as storms and sea-level rise is typically characterized using a combination of ground and manned airborne systems that have limited spatial or temporal scales. Structure-from-motion (SfM) photogrammetry applied to imagery acquired by unmanned aerial systems (UAS) offers a rapid and inexpensive means to produce high-resolution topographic and visual reflectance datasets that rival existing lidar and imagery standards. Here, we use SfM to produce an elevation point cloud, an orthomosaic, and a digital elevation model (DEM) from data collected by UAS at a beach and wetland site in Massachusetts, USA. We apply existing methods to (a) determine the position of shorelines and foredunes using a feature extraction routine developed for lidar point clouds and (b) map land cover from the rasterized surfaces using a supervised classification routine. In both analyses, we experimentally vary the input datasets to understand the benefits and limitations of UAS-SfM for coastal vulnerability assessment. We find that (a) geomorphic features are extracted from the SfM point cloud with near-continuous coverage and sub-meter precision, better than was possible from a recent lidar dataset covering the same area; and (b) land cover classification is greatly improved by including topographic data with visual reflectance, but changes to resolution (when <50 cm) have little influence on the classification accuracy.

Smartphone-Based Distributed Data Collection Enables Rapid Assessment of Shorebird Habitat Suitability

Understanding and managing dynamic coastal landscapes for beach-dependent species requires biological and geological data across the range of relevant environments and habitats. It is difficult to acquire such information; data often have limited focus due to resource constraints, are collected by non-specialists, or lack observational uniformity. We developed an open-source smartphone application called iPlover that addresses these difficulties in collecting biogeomorphic information at piping plover (Charadrius melodus) nest sites on coastal beaches. This paper describes iPlover development and evaluates data quality and utility following two years of collection (n = 1799 data points over 1500 km of coast between Maine and North Carolina, USA). We found strong agreement between field user and expert assessments and high model skill when data were used for habitat suitability prediction. Methods used here to develop and deploy a distributed data collection system have broad applicability to interdisciplinary environmental monitoring and modeling.