20220826 14374500 FALSE VA_Tracts_PhysVulnAug2015_wm 002 -9314702.826600 -8375940.450800 4375302.483600 4788621.140200 1 20.993 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.6'><WKT>PROJCS[&quot;WGS_1984_Web_Mercator_Auxiliary_Sphere&quot;,GEOGCS[&quot;GCS_WGS_1984&quot;,DATUM[&quot;D_WGS_1984&quot;,SPHEROID[&quot;WGS_1984&quot;,6378137.0,298.257223563]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Mercator_Auxiliary_Sphere&quot;],PARAMETER[&quot;False_Easting&quot;,0.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,0.0],PARAMETER[&quot;Standard_Parallel_1&quot;,0.0],PARAMETER[&quot;Auxiliary_Sphere_Type&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> 20230412 20351900 20230412 20351900 150000000 5000 1.0 FGDC FGDC CSDGM Metadata Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.1.9270 Physical Risk/Vulnerability - Virginia Coastal Census Tracts 2017-06-01T00:00:00 Karinna Nunez Virginia Institute of Marine Science Gloucester Point Virginia 23062 karinna@vims.edu US (804) 684-7273 Physical Vulnerability Index Center for Coastal Resources Management (CCRM). 2015. Physical Vulnerability Index. Virginia Institute of Marine Science, College of William and Mary, Gloucester Point, Virginia. Contact: Karinna Nunez (karinna@vims.edu) 1 -83.675399 -75.242353 39.465844 36.540875 Physical vulnerability based off Tide Range (inverse), percent area under 3.05 m (10 ft or floodable area), Relative Wave Exposure (calculated using NOAA's WEMo tool), percent of area under 10 ft developed, and Volume/area of area under 10 ft (inverse). The final scores were calculated at the census tract scale in order to connect to socioeconomic data. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>The Center for Coastal Resources Management at the Virginia Institute of Marine Science has developed a Coastal Physical Index (CPI) for the Chesapeake Bay region. CPI provides a broad perspective on the vulnerability of the Tidewater region, creating a composite measure of general flood impact rather than the threat of any one particular storm track. While there have been a number of efforts to categorize physical risk, the analysis behind this physical vulnerability index allows for application at a variety of scales such as the county or US Census tract level. Calculating physical risk for geopolitically defined boundaries generates values that can be directly tied to relevant socio-economic data, increasingly identified as a critical element of overall coastal vulnerability. The CPI draws on data sources that are generally widespread or replicable across different areas, which should allow transfer beyond the Chesapeake Bay region for use in coastal management at multiple scales. The capability to calculate vulnerability values at both the relative and absolute levels allows exploration of how vulnerability differs within various spatial contexts. CPI is a robust platform for examining the broad relationships between the impacts of coastal flooding and physical characteristics.</SPAN></P><P><SPAN /></P></DIV></DIV></DIV> coastal vulnerability physical vulnerability human geography census tract Center for Coastal Resources Management at the Virginia Institute of Marine Science File Geodatabase Feature Class 20.993 dataset EPSG 8.8(9.3.1.2) 1893 Simple FALSE 1893 TRUE FALSE VA_Tracts_PhysVulnAug2015_wm Feature Class 1893 OBJECTID OBJECTID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. GEO2010 GEO2010 String 11 0 0 Census tract ID for 2010 census. STUSAB STUSAB String 2 0 0 State of census tract (Maryland or VIrginia) ind_dev ind_dev Single 4 0 0 Physical Index factor of developed land in floodable area. standardized sub-10 ft developed land cover on 0 to 1 scale. ind_vol ind_vol Single 4 0 0 Physical Index factor of volume of tract land per tract area below 3.05 m (10ft). Inversed (ie 1 - valued) after being standardized from 0 to 1 ind_s10ar ind_s10ar Single 4 0 0 Physical Index factor of percent of land below 10 ft/3.05 m ind_tr ind_tr Single 4 0 0 Physical factor for tide range. Inversed after the tide range was was standardized from 0 - 1. ie 0.25 becomes 0.75. Values with 0 m tide range were kept at 0. ind_rwe ind_rwe Single 4 0 0 mean Relative wave energy standardized from 0 to 1. PhysTot PhysTot Single 4 0 0 total Physical index summed off of pInd_dev, pInd_vol, pIndPct_10, TRIndRel, RWE_std Phys_Ind Phys_Ind Single 4 0 0 final physical vulnerability score based off of NewPhysTot standardized from 0 to 1. PhysIndDef PhysIndDef String 50 0 0 Physical Index Risk category IndexRange IndexRange String 50 0 0 Physical Index range for risk categories. Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. Esri Positive real numbers that are automatically generated. Shape_Area Shape_Area Double 8 0 0 Area of feature in internal units squared. Esri Positive real numbers that are automatically generated. tract_name tract_name String 255 0 0 2010 Census track name 20230412 Karinna Nunez Virginia Institute of Marine Science Gloucester Point Virginia 23062 karinna@vims.edu US (804) 684-7273 Karinna Nunez Physical Vulnerability Index Construction: Delineating the basic geographic boundaries in terms of community social datasets supports developing an equivalent physical index to capture multiple angles of vulnerability context. The physical vulnerability index focuses on elevation, land use, wave exposure, and tide range, and developed land. While the other factors are common in the literature, incorporating the developed land further focuses the study on the application at human community scales. Vulnerability calculations that did not naturally have a maximum for 1 were standardized against the highest value in the area. For consideration of census tracts with the most floodable areas, geospatial analyses targeted the vulnerabilities of those areas with elevations below 3.05 meters (10 ft) above sea level. Elevation vulnerability=ratio of area under 3.05 m To further systematically subdivide risk among the lower elevation areas, volume to surface area ratios were also calculated for areas of the communities below 3.05 meters. The calculation of this factor served somewhat as an equivalent to coastal slope, characterizing how relatively floodable the sub-3.05 m area is. Those areas with lower ratios are areas that might be at highest risk with respect to where flood waters might fully inundate. Data from the USGS National Elevation Dataset (NED) were used to generate a digital elevation model (DEM) for Virginia and Maryland. Different geoprocessing tools in ArcGIS v10.0 were applied to create a DEM for the study area corresponding to elevations between 0 and 3.05 m above sea level. Algorithms written for the ArcGIS Model Builder iterated and calculated the volume and area between those elevations in each of the corresponding tracts. Lowland vulnerability=1-(((volume of geographic area below 3.05 m)/(area of geographic area below 3.05 m)))/(3.05 m) In order to analyze land cover across the region, Coastal Change Analysis Program (C-CAP) data were downloaded from the National Oceanic and Atmospheric Administration (NOAA) Coastal Services Center. For this study, 2001 C-CAP data for Virginia and Maryland sub-3.05 m elevation areas were converted and processed in ArcGIS v10.0. C-CAP land cover classifications were reclassified into 4 different land cover types: Agriculture, Developed Areas, Natural Nontidal Areas, and Wetlands. An ArcGIS spatial model was built to calculate percentage of each land use category per geographic area. Development vulnerability = (sub-3.05 m area developed land cover)/(Total area below 3.05 m) The wave exposure component was generated with the Wave Exposure Model (WEMo) created by Fonseca and Malhotra (2007). The updated Version 4 estimates wave energy based on shorelines, bathymetry and wind data. Using linear wave theory and tracing of rays along fetch in along different compass directions, WEMo calculates Representative Wave Energy (RWE) in J/m, or the wave energy in one wavelength per unit wave crest width. The model was run along the 0.5-meter contour line along the Chesapeake Bay’s shorelines, with points spaced approximately every 2000 meters. The 0.5-meter contour line was selected to ensure smooth functionality given data quality in shallower water and the model performance limits. The model ran in RWE mode with the water level raised 1 meter to simulate wave conditions under storm surge scenarios. Wind data were combined for a five-year period ranging from 2010 – 2014, with WEMo analysis selecting for the top 5% of winds from each wind directions. The wind data placed the values in a realistic context under a mix of annual conditions, including wind fields from two substantial tropical cyclones passing through (Hurricane Irene and Hurricane Sandy) as well as the 2013 nor’easter. Three National Ocean Service buoy sites were utilized for wind data for the Bay, including wind data from York River East Rear Range Light for the lower Bay latitudes (from southern Virginia just past the state line along the western shore above the Little Wicomico River or 36°43'51.233" to 37°53'55"N), Cove Point LNG Pier for the Mid-Bay latitudes (Little Wicomico River up to the mouth of the Choptank River or 38°39'20"N, and Tolchester Beach for the Upper Bay latitudes (the Choptank mouth up through the Susquehanna or 39°36'32"N). WEMo points were assigned to tract shorelines and the mean value was calculated for each area’s shoreline. For purposes of this study, any Atlantic facing counties were assigned the maximum mean value among Chesapeake coastal counties. tract with both open ocean and Bay shorelines were given the average of the maximum and the RWE value calculated for the bay shore. For any tracts with shorter shorelines skipped by the 2000-meter point distance, values were assigned by the nearest point/nearest similar neighbor. Wave Exposure vulnerability = area mean Representative Wave Energy Local tidal range also affects coastal communities risk relationship with the water, as people build structures around the regular variations in water levels. Communities with smaller tidal ranges were considered more vulnerable to coastal flooding. That conclusion concurs with other assessments in the literature such as McLaughlin and Cooper (2010) but contrasts with Kumar et al. (2010) and others who consider higher tides representative of more coastal energy. Tide levels are just as likely to be low as high during a flood event, and therefore much of the extra water added by storm surge and other events is relatively less at shorelines where the extra volume of water (or most of it) will fall within the tide range at times. The mean tidal range per tract was incorporated in this index. The output of the hydrodynamic model SCHISM (Zhang and Baptista 2008) fed the tidal range calculations. This model calculates the tidal range along the Chesapeake Bay, using the 2D depth-averaged configuration calibrated against all tidal gauges inside and outside the Bay. The model grid consists of 1.8 million triangles (i.e. unstructured grid) and covers the entire US east coast with focus on the Chesapeake Bay. It has a variable resolution in space: ~25 km in the open ocean, ~1.5 km along the open coast, 500 m along the main channel of the Bay, 150-300 m along channels of tributaries, ~50 m near the shoreline, and ~100m on dry land. In a few select areas where the model does not continue all the way up certain tributaries to their tidal extent, values were extended from the furthest extent alongside any available water level data. Tide vuln=1-(Great diurnal tide range)/(Greatest tide range in region)