The impacts of this increase in sea level, will vary from place-to-place and depend on a range of factors, including the human response. To initiate a national assessment of sea level rise impacts, the U.S. Environmental Protection Agency (EPA) is working with state, county, and local officials to identify the lands likely to receive shoreline protection. Those judgments incorporate state policies and regulations, local concerns, land-use data, and general planning judgment. The resulting data distinguishes areas likely to receive shoreline protection (e.g., beach nourishment and armoring with seawalls or dikes) from the areas where shores will probably retreat naturally, either because the cost of holding back the sea is greater than the value of the land, or because there is a current policy of allowing the shore to retreat. This data should be used in conjunction with information contained in the corresponding planning report.
Through the development of data on the likelihood of shoreline protection, this research seeks to (1) improve future assessments of the impacts of climate change through incorporation of a richer understanding of local land use policies and trends; (2) improve the understanding among federal, state, and local levels of government on the effect of current coastal policies on coastal development and conservation; and (3) identify opportunities for policy refinement to facilitate a more efficient response to rising seas that limits the impact on coastal property, wetlands, and recreational resources.
For more information on the goals of the study and this data set, please refer to the Introduction section of the report.
Users should display wetlands and the outside-of-study-area layers on top of this data set. This study only focused on dry land that is either below the 20-foot contour or within 1000 feet of the shore. The response data for lands located outside of the study area or beneath non-tidal wetlands is typically misleading and has not been reviewed. Wetlands data and the outside-of-study-area data layers are available separately.
For additional information on sea level rise planning, see EPA publications available at: <http://risingsea.net/ERL> or <http://risingsea.net/NJ.html>. The maps associated with this data are at <http://plan.risingsea.net>
For most localities, the national land use data, with a scale of 1:250,000, served as the core data source. Stakeholder reviews generally were undertaken with county-scale maps at approximately a 1:200,000 scale, although the corrections were often based on features such as roads where the scale of our data was better. Conservation land used to identify specific conservation lands, and other special purpose data sets, generally had a scale of 1:24,000 or better). Nevertheless, those data sets do not dominate the analysis, and hence we recommend that users of our data treat this data as having a scale of 1:250,000 or better, for most jurisdictions.
We did have better data, however, for four jurisdictions along the Potomac River: Alexandria, Fairfax, Prince William, and Stafford. In general the input data had a scale of 1:24,000 or better, and the stakeholder corrections were few. Therefore, we suggest that those maps can be viewed as having a scale of 1:50,000 or better. Although we also had high resolution local data from King George, most of the map designations were based on the site-specific knowledge provided by the local planner through annotations made on 1:100,000 scale maps. Therefore, we recommend a scale of 1:100,000. Finally, although Arlington did not provide local data, our map designations were based on road networks and other features where data was better than 1:100,000.
In the Hampton Roads area, we also had high resolution local data from Gloucester County, as well as the urban Hampton Road PDC localities: Chesapeake, Hampton, Newport News, Norfolk, Portsmouth, and Virginia Beach). These local data were better than 1:24,000. Although a few hand edits were made at the 1:100,000 scale, they were not sufficiently numerous so as to deteriorate the scale to worse than 1:50,000. The maps for the remaining Hampton Roads jurisdictions were based on annotations to 1:100,000 scale maps or better, and were often based on features with scales of 1:24,000 (e.g roads). Therefore, the maps for those jurisdictions (Isle of Wight, James City, Poquoson, Suffolk, Surry, York) are useful at a scale of 1:100,000.
The Land cover data is available at University of Virginia Library Online;<http://fisher.lib.virginia.edu/nlcd/browse_county.html> metadata available at <http://fisher.lib.virginia.edu/collections/gis/nlcd/helps/nlcd_meta.html>
We reviewed the VIMS assessment of lands likely to be protected in a worst-case scenario. That effort had opened the door to consideration of the sea level rise issue by local planners, but the output data was focused on the worst-case scenario, rather than the likely range of sea level rise. Therefore, we met with the same planners created a new draft set of planning maps using land use data, road layers, and the VIMs assessment. For a list of data acquired and the source of the data, please refer to Table 2 and Appendix B of the "Which Lands Will Require Shore Protection As Sea Level Rises in Virginia" planning report.
Using the additional data collected, we then prepared sample maps that identified existing residential, commercial, and industrial lands and then conducted interviews with each of the planning representatives from the original localities. State and local officials had not previously assessed the areas that might ultimately be protected under a 1-3 foot sea level rise, aside from a few areas with well-known erosion problems. Nevertheless, the primary question for this study involves many of the same issues that planners routinely consider, most importantly: which areas will become densely developed, and which areas will be placed off-limits to development.
We asked the planners to identify general categories of lands that would be protected or lost under different scenarios. Those general categories corresponded to a designation in a GIS dataset, which enabled us to create a generalized sea level response map by applying a "decision rule" to the data.
When creating the planning maps, the study authors limited the area mapped to a defined study area. We intended to include all dry lands that are either below the 20-foot (NGVD) elevation contour, or land within 1000 feet of the shore. Because the USGS maps in much of the region have contour intervals of 20 feet, this was the only way to be certain that we included all the land that might be vulnerable. We include land within 1000 feet of tidal wetlands or open water, to account for possible erosion. In spite of that intention, however, we lacked an accurate definition of the 20-ft contour. Prior to implementing the stakeholder review we integrated an outside-of-study-area data set that ICF consulting created for use in the project based upon the coastal elevation data referenced above. In addition, this layer also incorporates a 1000 foot buffer from the mean high water line to ensure that we would be able to display response information for cliff areas immediately adjacent to the coast.
Although our study area extends to the 20-foot contour, most uses of these maps will probably not extend to such a high elevation. For example, if one wanted to analyze the area protected from inundation with a one meter rise in sea level, one need only consider the land within one meter above the ebb and flow of the tides (see the elevation data available at <http://maps.risingsea.net/data.html>.
This analysis employed ArcView 3.x for the GIS work. As a result, where necessary, IEc reprojected data to NAD1983 UTM Zone 18N. In later steps of the analysis, IEc used ArcGIS software that automatically reprojects the data ("on the fly") to the StatePlane coordinate system. Thus, for new data added after this step, the data projections may have varied. During the final stage of the analysis; however, all data were projected to the same coordinate system for finalization.
To map the likelihood of shoreline protection in each county, we added the GIS data and stacked the data in the corresponding priority of the decision rules. The planning report includes tables that list the drawing order of the GIS data. For example, GIS data depicting site-specific differences are displayed above the more general decisions (e.g., existing developed land shown as certain to be protected, undeveloped lands shown as unlikely to be protected). Where necessary, a single layer may be included multiple times at different locations in the drawing order with different components displayed. For example, land use data provides information on different land categories. We might display the data at the bottom of the project to show all undeveloped land as shore protection unlikely and then add a second instance of the data further up in the drawing order to show all developed land as shore protection almost certain. For cases where planners identified site-specific decision rules during the initial planning meetings, we created separate data layers by selecting the corresponding area from the land use data and exporting the polygon(s) as a new layer. We then added the site-specific layers in the correct drawing order location and set the symbology to match the appropriate color for the protection scenario (for information on the protection responses and corresponding color used for display, see the attribute information for the Scenario field).
The study authors urge users of this data to refer to the planning report for additional information on the methods and data.
The initial Virginia study focused only on counties adjacent to the Atlantic Ocean and Chesapeake Bay. In this step, we expanded the study to include counties adjacent to the tidal rivers that feed into Chesapeake Bay. To expand the study, Dan Hudgens, Pratap Penumali, and the EPA project manager interviewed representatives from the individual counties and, based upon the input they provided and the state-wide GIS data layers, prepared county-specific maps. For information on the data used for specific counties, readers should refer to the planning report.
After creating the draft maps, we produced hardcopies of each county map on 11x 17" paper and distributed copies to each of the individuals interviewed under steps 1 through 3. These maps included ESRI major road data for reference purposes. The corresponding scale of the paper maps ranged from approximately 1:150,000 to 1:250,000 depending upon the size of county. During additional meetings with the planners, Will Nuckols and the EPA project manager solicited feedback on the maps to identify necessary changes. To the extent possible, they asked planners to identify changes by drawing a polygon around each area. They then noted the change that was needed for these areas. In some cases, planners only provided an oral description of changes needed. In those cases, Nuckols or Titus translated the suggested change onto a draft map
In most cases, Kassakian implemented each change by selecting the polygon(s) that existed within the area and exporting these selected polygons as a new shapefile. We revised the likelihood of protection identified in the layer attributes and added the new layer to the county project. In the case of the Hampton Roads area, however, the map changes were made by Kevin Wright and Britt Poole of ICF Incorporated.
When the boundaries of the site-specific change did not overlap with the boundaries of land use polygons, IEc used ArcGIS's edit functions. All edits were then implemented through heads-up digitizing using ArcGIS software. When possible we would first identify all the polygons in the land use data for which a portion of the area extended into the site-specific change. After exporting these polygons into a separate layer, we would then edit the new layer. Alternatively, in some cases, we used the edit function to create a new polygon in the shapefile. When using the edit function we would identify the boundaries of the area using available landmarks such as roads and manually create or split the polygons. In the few cases where roads could not serve as a landmark, we zoomed into the area involved (typically at a screen scale of 1:10,000 to 1:50,000 and made the edit based upon the shape of nearby features such as shoreline or wetlands. The resulting data were then added to the appropriate GIS project.
The fact that the review took place at a scale smaller than 1:100,000 probably reduced the resolution for those jurisdictions where we had land use data with scales of 1:24,000 or better. However, the deterioration was not severe because. the types of changes that the officials sought were generally for relatively large areas corresponding to the size of parks and new communities. The primary source of error for these maps is not the precision of well-defined boundaries, but rather the uncertainty of how land use will evolve in undeveloped areas.
During this step, the EPA project manager performed a final review of the GIS data and planning report. This review sought to identify map changes that were still needed. These changes usually involved cases where the requested stakeholder review changes had not been implemented correctly, or the GIS data failed to recognize recent development or newly planned development and the resulting map showed an area as less likely to be protected than anticipated (for example, a recent development might show as unlikely to be protected because the land use data did not reflect the presence of residences that would likely protect their land if ever threatened).
Using the same approach described in step 4, Britt Poole and Kevin Wright of ICF Consulting then made the necessary edits and incorporated the data into the GIS projects.
ICF Consulting received protection scenario data, by county, from Industrial Economics (IEc). Prior to finalizing the data, ICF created a series of "transfer confirmation maps", which the EPA manager reviewed to confirm that the maps were unchanged.
ICF then developed several geoprocessing models, using ESRI's Model Builder, to "flatten" the data into single state-wide files. The process of flattening the data involves combining or unioning each of the source data layers together to create the single file.
The models take the data layers that collectively create a state's sea level rise protection scenarios and flatten them into a single file. During the flattening process, all files are projected into an appropriate projection for the state. The models assign common attributes of shore protection, an appropriate source, whether or not it is military owned land, county name, state name, and if it is to override wetland data. Counties are flattened individually and then another model is used to combine all counties into a single state layer. Any edits that have been made to the protection scenarios are flattened and all attributes are verified.
Using this "flattened data", ICF created 1:100,000 "comparison maps" for the EPA manager to review. Those maps explicitly highlighted areas that had been erroneously masked (as wetland or high ground) during previous phases of the study, and hence not received the same level of scrutiny as most of the study area. The comparison maps included 1:24,000 TIGER road layer data.
The project manager examined the comparison maps and made three types of corrections.
First, these maps used better elevation and wetlands data (refer to the mask and wetlands in the <http://maps.risingsea.net/data.html>). The new data unveiled areas that had been covered by the draft elevation and wetlands masks, for two reasons. (a) the newer wetlands data often reclassified wetlands to dry land due to development and other land use changes taking place after the older (NWI) wetlands data was created and (b) the new elevation mask was more accurate (based upon a 20ft contour from a 1:24,000 data set). The revised elevation data led to new lands being identified as under 20 feet in elevation. The EPA project manager reviewed the unveiled areas (which had not been previously viewed by planning staff) to ensure that the designations fit with the decision rules noted by the planners. To identify the changes, he identified anomalies in the map such as unveiled blue areas existing in an otherwise brown area, unveiled blue areas with substantial road layers, unveiled brown areas with no roads, or unveiled red or brown areas surrounded by wetlands in an area where local officials had indicated that future development is unlikely. He also examined the unveiled lands to locate conservation lands (light green or blue). If the conservation land matched with the decision rules identified for the county, then no change was implemented. If the conservation land did not match the decision rules, he requested the map changes necessary to correct the situation.
Second, the project manager looked for lands that would not be protected due to our decision rules, but would be inherently protected by the protection of nearby lands. For example, if a land area were shown as unlikely to be protected but surrounded by land almost certain to be protected, then the protection level for the surrounded polygon would be set to match the nearby area. If an area was on high ground (and thus only at risk of erosion), then only the adjacent property closest to the shoreline had to be at the higher protection category to be changed. On lower ground, where properties could become inundated from any direction, the polygon had to be surrounded by a higher protection level to be changed.
Along relatively high ground shores, where erosion is the primary risk, protecting shorefront developed lands has the direct effect of protecting undeveloped inland farms, whether or not protection is otherwise expected for that land use category. In lower areas, lands can be submerged from the back side even if shorefront homes are protected. For those areas, he edited the protection designation only if a polygon is entirely surrounded by land that are more likely to be protected.
Finally, the project manager examined areas with substantial road networks that were designated blue. If the report assumed that such areas will not be developed, he changed those areas to red, except that if the area was immediately adjacent to a brown area, he changed it to brown.
ICF then implemented the final changes by selecting the corresponding polygons in the final response data and changing the source and scenario response fields accordingly.