Mapping, monitoring, and modeling: USGS Coastal and Marine Geology activities along the Northeast coast

Transcription

1 Mapping, monitoring, and modeling: USGS Coastal and Marine Geology activities along the Northeast coast Coastal and Marine Geology Program Woods Hole Coastal and Marine Science Center St. Petersburg Coastal and Marine Science Center U.S. Department of the Interior U.S. Geological Survey

2 Contributors Woods Hole Coastal and Marine Science Center -Walter Barnhardt, John Warner, Maitane Olabarrieta, Bill Schwab, Rob Thieler, Neil Ganju St. Petersburg Coastal and Marine Science Center - Joe Long, Nathaniel Plant, Hilary Stockdon, Cheryl Hapke

3 USGS Coastal and Marine Geology Program Provide the Nation With Reliable Impartial Scientific Information Research Focus is on Coastal and Submerged Lands Understand Geologic Processes that Create, Modify & Maintain the Coast and Ocean Floor Image courtesy of IVS ( - Etopo5 Data

4 USGS Coastal and Marine Geology Program Research and mapping designed to: Describe marine and coastal systems Understand the processes that create, modify, and maintain these systems Develop predictive models to support resource management decisions

5 Research Capabilities Topo-bathymetric LiDAR: EAARL-B Assessing sand resources: offshore bathymetry and geologic framework Understanding oceanographic processes: measurements and numerical modeling Probabilistic assessments: Bayesian modeling of geomorphic change likelihood Coastal hazards: storm tide monitoring (WRD)

6 EAARL-A Research Capabilities: Experimental LiDAR Originally developed during at NASA Goddard Space Flight Center, Wallops Flight Facility Green wavelength, sub-aerial and submerged topography in the same overflight Short (~1.3 ns) laser pulse; low pulse energy (60 µj) Narrow beam divergence and radically narrow receiver FOV(1.5-2 mrad), as compared with conventional bathy systems EAARL-B Enhanced mapping of shallow and turbid environments sample rate, pulse width (700 ps FWHM), >5x increase in laser pulse energy Outgoing beam optically segmented into 3 small footprint beamlets High spatial resolution where surface refraction and water column scattering are minimal Deep water channel (channel 4) with wider FOV

7 Research Capabilities: Offshore bathymetry and geologic framework (A) (B)

8 Research Capabilities: Numerical modeling

9 Research Capabilities: Numerical modeling

10 Research Capabilities: Bayesian modeling

11 Research Capabilities: storm tide monitoring

12 Results of interest to USACE effort Coastal geomorphic changes Conceptual models of sediment transport Coupled numerical modeling strategies Likelihood of barrier island change Extreme subtidal water levels and coastal flooding

13 Post-Sandy LiDAR collection

14 Results of interest to USACE effort Coastal geomorphic changes Conceptual models of sediment transport Coupled numerical modeling strategies Likelihood of barrier island change Extreme subtidal water levels and coastal flooding

15 Results of interest to USACE effort Coastal geomorphic changes Conceptual models of sediment transport Coupled numerical modeling strategies Likelihood of barrier island change Extreme subtidal water levels and coastal flooding

16 Coupled numerical modeling strategies Importance of passing wave height to atmospheric model

17 Coupled numerical modeling strategies Importance of passing currents to wave model

18 Process-Based Storm Response Model water levels beach/dune morphology offshore wave forcing; water levels XBEACH: High resolution numerical simulation of waves, water levels, overwash, inundation, dune and beach change

19 Hurricane Isaac: Chandeleur Islands, LA Pre-Storm Measured Post-Storm Measured Modeled

20 Results of interest to USACE effort Coastal geomorphic changes Conceptual models of sediment transport Coupled numerical modeling strategies Likelihood of barrier island change Extreme subtidal water levels and coastal flooding

21 Hurricane Sandy Real-Time Forecast of Coastal Erosion % of coast very likely to experience coastal change : Dune erosion (inner ) Overwash (middle) Inundation (outer) Long Island, NY New Jersey Delmarva New York New Jersey Delaware Maryland Virginia

22 Successful prediction of inundation: USGS models indicated a 61% likelihood of inundation at this location on Fire Island. NOAA imagery shows a breach in the island. Fire Island National Seashore, NY EROSION Probability of coastal change Likely As likely as not Unlikely

23 Increased vulnerability to future storms: Pre-Sandy (2010) vulnerability 20% of Fire Island was likely to overwash during Hurricane Sandy. Post-Sandy (2012) vulnerability 70% of Fire Island is likely to overwash during conditions similar to Sandy.

24 Identifying Future Risks Global forcing using the latest climate models Drives global and regional wave models Scaled down to local hazards projections

25 USGS linkages to USACE effort Provide updated topo-bathy data wherever possible Share modeling strategies, forcing data, and assessment data sets (water levels, currents, waves, etc) Provide parallel products to jointly assess coastal vulnerability Share data and model output from regional efforts (Fire Island, Barnegat Bay, Assateague Island)

26 Identifying Future Risks wave run-up wave set-up storm surge seasonal effects tide difference sea level rise h R h wv h ss h se h tide h slr swash zone 2 m m 1.0 m 0.3 m 2 m 1 m breaker zone H decreases rapidly due to breaking d br waves increase in height towards breaking zone (shoaling) H br MSL (datum) SLR only SLR + annual storm Stinson Beach 50 cm SLR