Hurricane Sandy, one of the largest Atlantic hurricanes on record, made landfall as an extratropical cyclone on the coast of New Jersey (29 October 2012) along a track almost perpendicular to the coast. Ten days later a northeaster caused heavy precipitation and elevated water levels along the coast. Two years of pre-storm monitoring and research in marshes of Barnegat Bay and the Delaware Estuary provided an opportunity to evaluate the impacts of Hurricane Sandy and the succeeding northeaster across the region. Peak water levels during Sandy ranged from 111 to 184 cm above the marsh surface in Barnegat Bay and 75 to 135 cm above the marsh surface in the Delaware Estuary. Despite widespread flooding and damage to coastal communities, the storm had modest and localized impacts on coastal marshes of New Jersey. Measurements made on the marsh platform illustrated localized responses to the storms including standing biomass removal, and changes in peak biomass the following summer. Marsh surface and elevation changes were variable within marshes and across the region. Localized elevation changes over the storm period were temporary and associated with subsurface processes. Over the long-term, there was no apparent impact of the 2012 storms, as elevations and regression slopes pre- and several months post-storm were not significant. Vegetation changes in the summer following the fall 2012 storms were also variable and localized within and among marshes. These results suggest that Hurricane Sandy and the succeeding northeaster did not have a widespread long-term impact on saline marshes in this region. Possible explanations are the dissipation of surge and wave energy from the barrier island in Barnegat Bay and the extreme water levels buffering the low-lying marsh surface from waves, winds, and currents, and carrying suspended loads past the short-statured marsh grasses to areas of taller vegetation and/or structure. These findings demonstrate that major storms that have substantial impacts on infrastructure and communities can have short-term localized effects on coastal marshes in the vicinity of the storm track.
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Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints
Compound flooding may result from the interaction of two or more contributing processes, which may not be extreme themselves, but in combination lead to extreme impacts. Here, we use statistical methods to assess compounding effects from storm surge and multiple riverine discharges in Sabine Lake, TX. We employ several trivariate statistical models, including vine‐copulas and a conditional extreme value model, to examine the sensitivity of results to the choice of data pre‐processing steps, statistical model setup, and outliers. We define a response function that represents water levels resulting from the interaction between discharge and surge processes inside Sabine Lake and explore how it is affected by including or ignoring dependencies between the contributing flooding drivers. Our results show that accounting for dependencies leads to water levels that are up to 30 cm higher for a 2% annual exceedance probability (AEP) event and up to 35 cm higher for a 1% AEP event, compared to assuming independence. We also find notable variations in the results across different sampling schemes, multivariate model configurations, and sensitivity to outlier removal. Under data constraints, this highlights the need for testing various statistical modelling approaches, while the choice of an optimal approach remains subjective.
more » « less- Award ID(s):
- 1929382
- NSF-PAR ID:
- 10447969
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Flood Risk Management
- Volume:
- 14
- Issue:
- 4
- ISSN:
- 1753-318X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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