scholarly journals Estuarine bed-sediment-quality data collected in New Jersey and New York after Hurricane Sandy, 2013

Data Series ◽  
10.3133/ds905 ◽  
2015 ◽  
Author(s):  
Jeffrey M. Fischer ◽  
Patrick J. Phillips ◽  
Timothy J. Reilly ◽  
Michael J. Focazio ◽  
Keith A. Loftin ◽  
...  
Keyword(s):  
New York ◽  
New Jersey ◽  
Sediment Quality ◽  
Hurricane Sandy ◽  
Quality Data ◽  
Bed Sediment

Regional variability in bed-sediment concentrations of wastewater compounds, hormones and PAHs for portions of coastal New York and New Jersey impacted by hurricane Sandy

2016 ◽  
Vol 107 (2) ◽  
pp. 489-498 ◽  
Author(s):  
Patrick J. Phillips ◽  
Catherine A. Gibson ◽  
Shawn C. Fisher ◽  
Irene J. Fisher ◽  
Timothy J. Reilly ◽  
...  
Keyword(s):  
New York ◽  
New Jersey ◽  
Hurricane Sandy ◽  
Bed Sediment ◽  
Regional Variability

Regional assessment of persistent organic pollutants in resident mussels from New Jersey and New York estuaries following Hurricane Sandy

2016 ◽  
Vol 107 (2) ◽  
pp. 432-441 ◽  
Author(s):  
Kelly L. Smalling ◽  
Ashok D. Deshpande ◽  
Heather S. Galbraith ◽  
Beth L. Sharack ◽  
DeMond Timmons ◽  
...  
Keyword(s):  
New York ◽  
New Jersey ◽  
Organic Pollutants ◽  
Persistent Organic Pollutants ◽  
Hurricane Sandy ◽  
Regional Assessment

Exposure, Social Vulnerability and Recovery Disparities in New Jersey after Hurricane Sandy

2014 ◽  
Vol 01 (01) ◽  
pp. 1450002 ◽  
Author(s):  
Susan L. Cutter ◽  
Ronald L. Schumann ◽  
Christopher T. Emrich
Keyword(s):  
New York ◽  
New Jersey ◽  
Water Depth ◽  
Social Vulnerability ◽  
Flood Hazard ◽  
Damage Zone ◽  
Hurricane Sandy ◽  
Housing Tenure ◽  
Government Support ◽  
Small Business Administration

Hurricane Sandy's 80 mph wind speeds did not achieve major hurricane status on the Saffir-Simpson scale, yet the storm had extreme consequences for the New York metropolitan area. Post-event recovery has been quite variable across the region, especially in New Jersey. This paper examines the progression of recovery at two time intervals — 6 months and 1 year after the storm made landfall. Based on in situ observations of reconstruction and repair within the surge damage zone along New Jersey's coast (N = 765 locations or points), we hypothesize that the timing and distribution of recovery is based on exposure (water depth, prior flood experience, building heights), vulnerability (social vulnerability, seasonal occupancy), and government support (FEMA assistance, Small Business Administration loans). Predictions of recovery (recovered, not recovered) based on these input measures is quite good at 6 months (80 percent correctly predicted) with slight improvements at 1 year (82 percent correctly predicted). The model is much better at predicting recovered points than recovering. In terms of the individual factors predicting recovery the level of exposure is the most significant, statewide. Within the two most affect counties — Monmouth and Ocean — only water depth and building height were significant predictors. Housing tenure (seasonal occupancy) was an important predictor of the location and timing of recovery for the first 6 months, especially in Monmouth County, but became insignificant thereafter. Government support in the form of FEMA individual assistance grants was a significant predictor statewide in both time periods. Clearly other factors are influencing the pace and location of recovery including confusion surrounding flood hazard zones and insurance. Those factors influencing the lack of recovery for the roughly 20 percent of our observations awaits further, more detailed analyses.

The impact of onsite wastewater disposal systems on groundwater in areas inundated by Hurricane Sandy in New York and New Jersey

2016 ◽  
Vol 107 (2) ◽  
pp. 509-517 ◽  
Author(s):  
Irene J. Fisher ◽  
Patrick J. Phillips ◽  
Kaitlyn M. Colella ◽  
Shawn C. Fisher ◽  
Tristen Tagliaferri ◽  
...  
Keyword(s):  
New York ◽  
New Jersey ◽  
Hurricane Sandy ◽  
Wastewater Disposal ◽  
Onsite Wastewater ◽  
The Impact

Comparison of wastewater-associated contaminants in the bed sediment of Hempstead Bay, New York, before and after Hurricane Sandy

2016 ◽  
Vol 107 (2) ◽  
pp. 499-508 ◽  
Author(s):  
Shawn C. Fisher ◽  
Patrick J. Phillips ◽  
Bruce J. Brownawell ◽  
James P. Browne
Keyword(s):  
New York ◽  
Hurricane Sandy ◽  
Bed Sediment ◽  
Before And After

Street-Scale Modeling of Storm Surge Inundation along the New Jersey Hudson River Waterfront

2015 ◽  
Vol 32 (8) ◽  
pp. 1486-1497 ◽  
Author(s):  
Alan F. Blumberg ◽  
Nickitas Georgas ◽  
Larry Yin ◽  
Thomas O. Herrington ◽  
Philip M. Orton
Keyword(s):  
New York ◽  
New Jersey ◽  
High Resolution ◽  
Hydrodynamic Model ◽  
Hudson River ◽  
Ocean Model ◽  
Hurricane Sandy ◽  
Water Levels ◽  
Spatial And Temporal Variation ◽  
Inundation Model

AbstractA new, high-resolution, hydrodynamic model that encompasses the urban coastal waters of New Jersey along the Hudson River Waterfront opposite New York City, New York, has been developed and validated for simulating inundation during Hurricane Sandy. A 3.1-m-resolution square model grid combined with a high-resolution lidar elevation dataset permits a street-by-street focus to inundation modeling. The waterfront inundation model is a triple-nested Stevens Institute Estuarine and Coastal Ocean Hydrodynamic Model (sECOM) application; sECOM is a successor model to the Princeton Ocean Model family of models. Robust flooding and drying of land in the model physics provides for the dynamic prediction of flood elevations and velocities across land features during inundation events. The inundation model was forced by water levels from the extensively validated New York Harbor Observing and Prediction System (NYHOPS) hindcast of that hurricane.Validation against 56 watermarks and 16 edgemarks provided via the USGS and through an extensive crowdsourcing effort consisting of photographs, videos, and personal stories shows that the model is capable of computing overland water elevations quite accurately throughout the entire surge event. The correlation coefficient (R2) between the watermark observations and the model results is 0.92. The standard deviation of the residual error is 0.07 m. Comparisons to the 16 flood edgemarks suggest that the model was able to reproduce flood extent to within 20 m. Because the model was able to capture the spatial and temporal variation of water levels in the region observed during Hurricane Sandy, it was used to identify the flood pathways and suggest where flood-preventing interventions could be built.

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