Hilary F. Stockdon

Predictions of total water levels, the elevation of combined tides, surge, and wave runup at the shoreline, are necessary to provide guidance on potential coastal erosion and flooding. Despite the importance of early warning systems for these hazards, existing real-time meteorological and oceanographic forecast systems at regional and national scales, until now, have lacked estimates of runup necessary to predict wave-driven overwash and erosion. To address this need, we present an approach that includes wave runup in an operational, national-scale modeling system. Using this system, we quantify the contribution of waves to potential dune erosion events along 4,700 km of U.S. Atlantic and Gulf of Mexico sandy coastlines for a one-year period. Dune erosion events were predicted to occur at over 80% of coastal locations, where waves dominated shoreline total water levels, representing 73% of the signal. This shows that models that neglect the wave component underestimate the hazard. This new, national-scale operational modeling system provides communities with timely, local-scale (0.5 km resolution) coastal hazard warnings for all wave conditions, allowing for rapid decision-making related to safety and emergency management. The modeling system also enables continued research into wave-driven processes at a broad range of coastal areas.

Hurricane Matthew, the strongest Atlantic hurricane of the 2016 hurricane season, made land-fall south of McClellanville, S.C., around 1500 Coordinated Universal Time (UTC) on October 8, 2016. Hurricane Matthew affected the States of Florida, Georgia, South Carolina, and North Carolina along the U.S. Atlantic coastline. Numerous barrier islands were breached, and the erosion of beaches and dunes occurred along most of the South Atlantic coast. The U.S. Geological Survey (USGS) fore-casted potential coastal-change effects—including dune erosion and overwash that can threaten coastal resources and infrastructure—to assist with pre-storm management decisions. Following the storm, oblique aerial photography was collected, and lidar topographic survey missions were flown. These two datasets were used to document the changes that resulted from the storm and to validate coastal change forecasts. Comparisons of pre- and post-storm photographs were used to characterize the nature, extent, and spatial variability of hurricane-induced coastal changes. Analyses of pre- and post-storm lidar eleva-tions were used to quantify magnitudes of change in shoreline positions, dune elevations, and beach volumes. Erosion was observed along the coast from Florida to North Carolina; however, the coastal response exhibited extensive spatial variability, as would be expected over such a large region.

To better understand how individual processes combine to cause flooding and erosion events, we investigate the relative contribution of tides, waves, and nontidal residuals to extreme total water levels (TWLs) at the shoreline of U.S. West Coast sandy beaches. Extreme TWLs, defined as the observed annual maximum event and the simulated 100 year return level event, peak in Washington, and are on average larger in Washington and Oregon than in California. The relative contribution of wave‐induced and still water levels (SWL) to the 100 year TWL event is similar to that of the annual maximum event; however, the contribution of storm surge to the SWL doubles across events. Understanding the regional variability of TWLs will lead to a better understanding of how sea level rise, changes in storminess, and possible changes in the frequency of major El Niños may impact future coastal flooding and erosion along the U.S. West Coast and elsewhere.

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.

Beaches serve as a natural buffer between the ocean and inland communities, ecosystems, and natural resources. However, these dynamic environments move and change in response to winds, waves, and currents. During extreme storms, changes to beaches can be great, and the results are sometimes catastrophic. Lives may be lost, communities destroyed, and millions of dollars spent on rebuilding. During storms, large waves may erode beaches, and high storm surge may shift the erosive force of the waves higher on the beach. In some cases, the combined effects of waves and surge may cause overwash (when waves and surge overtop the dune, transporting sediment inland) or flooding. Buildings and infrastructure on or near a dune can be undermined during wave attack and subsequent erosion. A number of strong northeast storms—storms with winds tending to blow from the northeast direction—referred to as nor’easters, have hit the mid- and northeast Atlantic coast of the...

"iCoast -- Did the Coast Change?" is a U.S. Geological Survey (USGS) research project that integrates crowdsourcing and citizen science techniques to develop a web application that allows interested volunteers to tag USGS oblique aerial photographs with qualitative information about the geomorphological changes to the coastline after Hurricane Sandy. iCoast has been collaboratively designed with coastal scientists to ensure that the crowdsourced data produced from iCoast can be used to help validate USGS predictive models of coastal change and to educate the public about coastal erosion after extreme storms. Different mechanisms for interacting with different crowds have been strategically implemented. Various sociotechnical challenges and unexpected outcomes have emerged.

Low‐lying barrier islands are ubiquitous features of the world's 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.