Hilary F. Stockdon

Estimation of wave phase speed and nearshore bathymetry from video imagery

A new remote sensing technique based on video image processing has been developed for the estimation of nearshore bathymetry. The shoreward propagation of waves is measured using pixel intensity time series collected at a cross-shore array of locations using remotely operated video cameras. The incident band is identified, and the cross-spectral matrix is calculated for this band. The cross-shore component of wavenumber is found as the gradient in phase of the first complex empirical orthogonal function of this matrix. Water depth is then inferred from linear wave theorys dispersion relationship. Full bathymetry maps may be measured by collecting data in a large array composed of both cross-shore and longshore lines. Data are collected hourly throughout the day, and a stable, daily estimate of bathymetry is calculated from the median of the hourly estimates. The technique was tested using 30 days of hourly data collected at the SandyDuck experiment in Duck, North Carolina, in October 1997. Errors calculated as the difference between estimated depth and ground truth data show a mean bias of-35 cm (rms error - 91 cm). Expressed as a fraction of the true water depth, the mean percent error was 13% (rms error - 34%). Excluding the region of known wave nonlinearities over the bar crest, the accuracy of the technique improved, and the mean (rms) error was-20 cm (75 cm). Additionally, under low-amplitude swells (wave height H _<1 m), the performance of the technique across the entire profile improved to 6% (29%) of the true water depth with a mean (rms) error of-12 cm (71 cm).

Sea-cliff erosion as a function of beach changes and extreme wave runup during the 1997–1998 El Niño

Abstract Over time scales of hundreds to thousands of years, the net longshore sand transport direction along the central California coast has been driven to the south by North Pacific winter swell. In contrast, during the El Nino winter of 1997–1998, comparisons of before and after airborne lidar surveys showed sand was transported from south to north and accumulated on the south sides of resistant headlands bordering pocket beaches. This resulted in significant beach erosion at the south ends of pocket beaches and deposition in the north ends. Coincident with the south-to-north redistribution of sand, shoreline morphology became prominently cuspate with longshore wavelengths of 400–700 m. The width and elevation of beaches were least where maximum shoreline erosion occurred, preferentially exposing cliffs to wave attack. The resulting erosional hotspots typically were located in the embayments of giant cusps in the southern end of the pocket beaches. The observed magnitude of sea cliff retreat, which reached 14 m, varied with the number of hours that extreme wave runup exceeded certain thresholds representing the protective capacity of the beach during the El Nino winter. A threshold representing the width of the beach performed better than a threshold representing the elevation of the beach. The magnitude of cliff erosion can be scaled using a simple model based on the cross-shore distance that extreme wave runup exceeded the pre-winter cliff position. Cliff erosion appears to be a balance between terrestrial mass wasting processes, which tend to decrease the cliff slope, and wave attack, which removes debris and erodes the cliff base increasing the cliff slope.

Hurricanes 2004: An Overview of Their Characteristics and Coastal Change

Four hurricanes battered the state of Florida during 2004, the most affecting any state since Texas endured four in 1884. Each of the storms changed the coast differently. Average shoreline change within the right front quadrant of hurricane force winds varied from 1 m of shoreline advance to 20 m of retreat, whereas average sand volume change varied from 11 to 66 m3 m−1 of net loss (erosion). These changes did not scale simply with hurricane intensity as described by the Saffir-Simpson Hurricane Scale. The strongest storm of the season, category 4 Hurricane Charley, had the least shoreline retreat. This was likely because of other factors like the storms rapid forward speed and small size that generated a lower storm surge than expected. Two of the storms, Hurricanes Frances and Jeanne, affected nearly the same area on the Florida east coast just 3 wk apart. The first storm, Frances, although weaker than the second, caused greater shoreline retreat and sand volume erosion. As a consequence, Hurricane Frances may have stripped away protective beach and exposed dunes to direct wave attack during Jeanne, although there was significant dune erosion during both storms. The maximum shoreline change for all four hurricanes occurred during Ivan on the coasts of eastern Alabama and the Florida Panhandle. The net volume change across a barrier island within the Ivan impact zone approached zero because of massive overwash that approximately balanced erosion of the beach. These data from the 2004 hurricane season will prove useful in developing new ways to scale and predict coastal-change effects during hurricanes.

Extraction of Lidar-Based dune-crest Elevations for use in Examining the Vulnerability of Beaches to Inundation during Hurricanes

Abstract The morphology of coastal sand dunes plays an important role in determining how a beach will respond to a hurricane. Accurate measurements of dune height and position are essential for assessing the vulnerability of beaches to extreme coastal change during future landfalls. Lidar topographic surveys provide rapid, accurate, high-resolution datasets for identifying the location, position, and morphology of coastal sand dunes over large stretches of coast. An algorithm has been developed for identification of the crest of the most seaward sand dune that defines the landward limit of the beach system. Based on changes in beach slope along cross-shore transects of lidar data, dune elevation and location can automatically be extracted every few meters along the coastline. Dune elevations in conjunction with storm-induced water levels can be used to predict the type of coastal response (e.g., beach erosion, dune erosion, overwash, or inundation) that may be expected during hurricane landfall. The vulnerability of the beach system at Fire Island National Seashore in New York to the most extreme of these changes, inundation, is assessed by comparing lidar-derived dune elevations to modeled wave setup and storm surge height. The vulnerability of the beach system to inundation during landfall of a Category 3 hurricane is shown to be spatially variable because of longshore variations in dune height (mean elevation = 5.44 m, standard deviation = 1.32 m). Hurricane-induced mean water levels exceed dune elevations along 70% of the coastal park, making these locations more vulnerable to inundation during a Category 3 storm.

Forecasting Hurricane Impact on Coastal Topography

Extreme storms can have a profound impact on coastal topography and thus on ecosystems and human-built structures within coastal regions. For instance, landfalls of several recent major hurricanes have caused significant changes to the U.S. coastline, particularly along the Gulf of Mexico. Some of these hurricanes (e.g., Ivan in 2004, Katrina and Rita in 2005, and Gustav and Ike in 2008) led to shoreline position changes of about 100 meters. Sand dunes, which protect the coast from waves and surge, eroded, losing several meters of elevation in the course of a single storm. Observations during these events raise the question of how storm-related changes affect the future vulnerability of a coast.

Predictions of barrier island berm evolution in a time‐varying storm climatology

Low-lying barrier islands are ubiquitous features of the worlds coastlines, and the processes responsible for their formation, maintenance, and destruction are related to the evolution of smaller, superimposed features including sand dunes, beach berms, and sandbars. The barrier island and its superimposed features interact with oceanographic forces (e.g., overwash) and exchange sediment with each other and other parts of the barrier island system. These interactions are modulated by changes in storminess. An opportunity to study these interactions resulted from the placement and subsequent evolution of a 2 m high sand berm constructed along the northern Chandeleur Islands, LA. We show that observed berm length evolution is well predicted by a model that was fit to the observations by estimating two parameters describing the rate of berm length change. The model evaluates the probability and duration of berm overwash to predict episodic berm erosion. A constant berm length change rate is also predicted that persists even when there is no overwash. The analysis is extended to a 16 year time series that includes both intraannual and interannual variability of overwash events. This analysis predicts that as many as 10 or as few as 1 day of overwash conditions would be expected each year. And an increase in berm elevation from 2 m to 3.5 m above mean sea level would reduce the expected frequency of overwash events from 4 to just 0.5 event-days per year. This approach can be applied to understanding barrier island and berm evolution at other locations using past and future storm climatologies.

Vulnerability of National Park Service Beaches to Inundation during a Direct Hurricane Landfall: Cumberland Island National Seashore

Cumberland Island National Seashore, a barrier-island coastal park in Georgia, is vulnerable to the powerful, sand-moving forces of hurricanes. Waves and storm surge associated with these strong tropical storms are part of the natural process of barrier-island evolution and can cause extensive morphologic changes in coastal parks, leading to reduced visitor accessibility and enjoyment. The vulnerability of park beaches to inundation, and associated extreme coastal change, during a direct hurricane landfall can be assessed by comparing the elevations of storminduced mean-water levels (storm surge) to the elevations of the crest of the sand dune that defines the beach system. Maps detailing the inundation potential for Category 1-5 hurricanes can be used by park managers to determine the relative vulnerability of various barrier-island parks and to assess which areas of a particular park are more susceptible to inundation and extreme coastal changes.

Changing the Paradigm of Response to Coastal Storms

Federal, state, and local agencies mounted a massive preparation and response to post–tropical storm Sandy, which made landfall along the northern New Jersey coast on 29 October 2012. The data collected and knowledge gained in response to Sandy are unprecedented and provide critical information to agencies, local emergency responders, and coastal managers and planners.

Probabilistic Assessment of Beach and Dune Changes

The recent availability of spatially-dense airborne lidar data makes assessment of the vulnerability of beaches and dunes to storm impacts practical over long reaches of coast. As an initial test, elevations of the tops (D high ) and bases (D low ) of foredune ridges along a 55-km reach on the northern Outer Banks, NC were found to have considerable spatial variability suggesting that different parts of the barrier island would respond differently to storms. Comparing statistics of storm wave runup to D high and D low , we found that net erosion due to overwash and dune retreat should be greatest at the northern and southern ends of the study area and least in the central section. This predicted spatial pattern of storm-induced erosion is similar to the spatial pattern of long-term erosion of the shoreline which may be controlled by additional processes (such as gradients in longshore transport) as well as the cross-shore processes considered here. However, consider feedback where at erosional hot spots there is a deficit of sand (caused by gradients in longshore transport) which lead to lower dunes and enhanced erosional cross-shore processes, such as overwash. Hence, the erosional hot spots would be exacerbated, further increasing the vulnerability of the beach and dunes to net erosion.

Testing model parameters for wave‐induced dune erosion using observations from Hurricane Sandy

Models of dune erosion depend on a set of assumptions that dictate the predicted evolution of dunes throughout the duration of a storm. Lidar observations made before and after Hurricane Sandy at over 800 profiles with diverse dune elevations, widths, and volumes are used to quantify specific dune erosion model parameters including the dune face slope, which controls dune avalanching, and the trajectory of the dune toe, which controls dune migration. Wave-impact models of dune erosion assume a vertical dune face and erosion of the dune toe along the foreshore beach slope. Observations presented here show that these assumptions are not always valid and require additional testing if these models are to be used to predict coastal vulnerability for decision-making purposes. Observed dune face slopes steepened by 43% yet did not become vertical faces, and only 50% of the dunes evolved along a trajectory similar to the foreshore beach slope. Observations also indicate that dune crests were lowered during dune erosion. Moreover, analysis showed a correspondence between dune lowering and narrower beaches, smaller dune volumes, and/or longer wave impact.