The Sea Level Rise Inundation Tool User Guide

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The Sea Level Rise Inundation Tool User Guide Prepared by Center for Coastal Resources Management Virginia Institute of Marine Science College of William and Mary September, 2015

The Sea Level Rise Inundation Tool User Guide Introduction A number of different techniques have been developed to model sea level rise and communicate the output of those modeling efforts to the broad audience of stakeholders (NOAA, 2012; USACOE, 2013). These tools vary in content, complexity and delivery format. Nearly all applications require a highly accurate 3 D topographic surface to map and compute inundation areas, and most deliver data through some type of 2 D map service. The Sea Level Rise Inundation Tool, developed by the Center for Coastal Resources Management (CCRM) at the Virginia Institute of Marine Science (VIMS), is one of several tools generated to support a new era of coastal resource management planning in Virginia which promotes resiliency of coastal resources through strategic planning and shoreline best management practices. Information pertaining to sea level rise and shoreline best management practices is locality specific and under development. This document focuses on the methods and use of the Sea Level Rise Inundation Tool. More information about the guidance being prepared for local governments as the Commonwealth moves forward with its 2011 environmental policy pertaining to coastal resource management planning can be found at this website: http://ccrm.vims.edu/ccrmp/index.html. The remainder of this document pertains to the Sea Level Rise Inundation Tool; one of several applications developed by CCRM to support coastal resource management in Virginia. Methodology The data used for generating 3 D surfaces for this analysis came from multiple sources, and only the best available data were used. Two major software platforms were also required to process the data and develop the visualization tool for desktop viewing. ESRI software (ArcGIS Desktop 10, ArcGIS Server 10, Image Server) and Microsoft software (Microsoft Visual Studio 2010 Professional) was used to process data, generate sea level rise flood rasters, create the visual interface and other visible data layers, and serve them in a GIS web mapping applications.

2 Creating the topographic surface First, LIDAR (Light Detecting and Ranging) data was acquired from the Virginia Geographic Information Network (VGIN) and individual localities. LIDAR is the most accurate source for elevation data and was used wherever available. Where LIDAR was unavailable, elevation data from the Virginia Base Mapping Program (VBMP) was used. The VBMP mass points and breakline data have a vertical accuracy of 0.66 ft (1:2400) and 0.33 ft (1:1200) depending on location and meet the National Standard for Spatial Data Accuracy (NSSDA). After processing the source data into consistent projections, datums, and units, the data were merged into seamless elevation surfaces for larger regions, and then clipped to the boundary of individual localities. All data were projected, when necessary, to Virginia State Plane HARN with units of feet. Either Virginia State Plane North or Virginia State Plane South was chosen depending on the locality s geographic location. Vertical units were converted, when necessary, from meters to feet. The use of English rather than metric units was a decision based on the preferred system elected by the majority of the end users; in this case local government personnel. A shoreline digitized from the VBMP imagery (2006-2007, 2009, or 2013) was used as the shoreline boundary of the localities. The elevation values on these surfaces were initially referenced to the widely used NAVD88 vertical datum, which is referenced to a fixed benchmark based on land. However, due primarily to tidal influence, sea level at a given time will vary by location when referenced to the NAVD88 datum. In practice, this means that a water level value that is constant in the NAVD88 datum applied across a large coastal area will generate inaccurate land inundation zones. When modeling coastal inundation with sea level rise, it is more accurate to reference the coastal land elevations to tidal datums (i.e. mean sea level, mean high water, etc.) since water level variation is primarily dependent on the tidal cycle. Tidal datums are local (i.e. vary along the coast) and take this tidal variation into account. Therefore, for this application, it is useful to convert the land elevation surfaces from the NAVD88 datum reference to a tidal datum reference. We chose to use the mean high water (MHW) reference, and all flood zones in the sea level rise tool are at MHW. NOAA s Coastal Services Center provided the necessary adjustment data to convert land elevation surfaces from the NAVD88 reference to the MHW reference. This adjustment data were generated using a tool developed by NOAA called VDatum, which is used to convert between different vertical reference systems. When generating the inundation areas, we were concerned only with the flood area caused by sea level rise. In general, a surface will contain sinks, or sunken depressions, in the topography which will be susceptible to flooding through rain or runoff. Flooding in these sinks

is not associated with the sea level rise of interest here, and is hydrologically isolated from the flooding caused by sea level rise. Before running the model to extract the inundation zones, a GIS operation known as filling was executed on the elevation surfaces. This operation will fill in all of these isolated sinks on the surface so they do not appear as part of the inundation zones due to sea level rise.

4 Selecting the sea level rise scenarios The next stage of the process was to generate the sea level rise flood areas. The sea level rise scenarios used in this analysis were based on the 2014 National Climate Assessment. This study produced four scenarios which represent plausible trajectories for local sea level based on a combination of factors. These scenarios were modified by incorporating an estimation of land subsidence in southeastern Virginia (Figure 1). Figure 1. National Climate Assessment Sea Level Rise Scenarios The lowest or historic scenario is simply a projection of observed long term rates of sea level rise going back a century or more, and contains no acceleration. The highest scenario is based on estimated consequences from global warming combined with the maximum possible contribution from ice sheet loss and glacial melting (a practical worst case scenario based on current understandings). The high scenario is based on the upper end of projections from semi empirical models using statistical relationships in global observations of sea level and air temperature. The low scenario is based on the IPCC fourth Assessment model using conservative assumptions about future greenhouse gas emission. The original National Climate Assessment scenarios are for global sea level rise only. To incorporate subsidence in southeast Virginia into the analysis, we added a constant 2.7mm/yr (0.11 in/yr) to the projections. This is the value one gets from the Seawells Point tide record which has a long term average rate of rise of 4.44mm/yr (0.17 in/yr), and then subtracting the average global sea level rise rate of 1.7mm/yr (0.07in/yr). We are now displaying the historic and highest scenarios in our web applications for all posted localities, as Current and

5 Accelerated scenarios, respectively. Some localities also include an intermediate rate which is extracted from values that fall between the green and the yellow curve illustrated in Figure 1. The precise values we used for projected sea level rise are shown in Table 1: Year Current (ft) High (ft) Accelerated (ft) Generating the flood levels 2020 0.45 0.66 0.84 2040 0.77 1.41 1.94 2060 1.09 2.39 3.44 2080 1.41 3.60 5.35 2100 1.74 5.03 7.67 Table 1. Inundation rates used in the sea level rise tool Following the procedure carried out above, the surface model is already referenced to MHW. Therefore, when the sea level rise inundation values for the different years are applied to the surface the result represents the change in flood level of MHW over time. The Raster Calculator tool in ArcGIS Spatial Analyst was used to extract all raster cells below the flood level for the Current, High, and Accelerated scenarios and for all years. The resulting rasters were used as the flood zones visible in the web application. After generating all the flood rasters for a given locality, a raster collection called a mosaic dataset was created for each scenario and for each locality. The appropriate flood rasters for the three scenarios were then added to the respective mosaic datasets (i.e. each locality has a mosaic dataset for each scenario, and each of those mosaic datasets contains flood rasters for years 2020, 2040, 2060. 2080, 2100). The mosaic dataset format allows for the creation of a time slider tool, as seen in the web application. The time slider is a GIS visualization tool provided by ESRI, which allows for easy visualization of a time series of rasters. The various flood levels represent the inland intrusion of MHW over time. The increase in flood levels is associated with sea level rise and subsidence using values reported in Table 1. At this time, flooding does not consider storm surge. Creating the visualization tool To create a time slider, an image service must first be created from the mosaic dataset. The image service is a GIS dataset which allows one to serve raster data efficiently in a web

6 mapping application. The image service is served with Image Server, an ESRI product which, in this application, was used as an extension of ArcGIS Server. A time slider was created from each image service which allows visualization, as a time series, of the flood rasters populating the image service. Other data layers visible in the web applications come from ESRI s own online image services or standard map services we created from our own data for use with ArcGIS Server. The web applications were developed in Microsoft Visual Studio 2010 Professional. ESRI provides a series of development tools for GIS functionality that are integrated into Visual Studio; these tools allow development of GIS web mapping applications that run in the Silverlight framework. Using the Tool All the sea level rise web applications are run with Microsoft Silverlight. Silverlight is a plug in for web browsers that allows them to run rich internet applications, including multimedia and animations. Users running Microsoft Office V. 7 or below will have to download the Silverlight plug in from the Internet (http://www.microsoft.com/silverlight/). The user is generally prompted to do this when trying to open the application for the first time. Silverlight is built into Microsoft Office 10. Macintosh users who need to download Silverlight should go to this site: https://www.macupdate.com/app/mac/26623/silverlight. When the tool opens the user has the opportunity to select a basemap in the lower half of the Data Layer box. The default view uses the Street Map. Two other choices are available including the most recent, publicly available, Virginia Base Mapping Program s (VBMP) high resolution imagery. All three layers can be selected, and the adjacent slide bars can be used to control the transparency of the layer (Figure 2).

7 Figure 2. Basemaps are selected at the bottom of the Data Layers box shown by the red arrow. The black arrow indicates the user has selected to view sea level rise using the Current rate. Next, the user must select the sea level rise (SLR) scenario he/she wishes to view. In Figure 2, the black arrow highlights where that selection is made. Three choices are available: Current, High, and Accelerated. Within the box, the selected scenario will show up in black above the time slide bar. Shown in the lower right of Figure 2 is the tool to zoom, and pan your map within the map viewer. The tool includes a red slider bar to zoom in and out, red arrows to move you north, south, east or west (Figure 3), and a button in the center to send you back to the previous map extent. Use this function to zoom to your area of interest. Note, if you change the sea level rise scenario selected; the base map will be redrawn for the locality, and you will need to zoom to your area of interest again. Figure 3. Zoom and Pan Tool The Sea Level Rise tool is developed to observe inundation over time under a user define rate of sea level rise. After the user has zoomed to the area of interest, and selected his/her sea level rise scenario, the time slider bar located in the Data Layer window is used to step through time and observe the land area inundated as the MHW mark shifts inland due to sea level rise. The arrow on the left of the slide bar (see indicator in Pink) allows for a continuous automated animation through time. The pair of arrows on the right side of the bar (see indicator in Green) allows the user to manually step forward and back in time at 20 year intervals to observe the inundation (Figure 4).

8 The time slider bar begins in 2012, when the model was developed. The map window displays MHW water levels at the year indicated on the time slider. The projected scenario flood levels are generated at 20 year increments beginning with the year 2020 and ending with the year 2100. There are two ways to move through time: a manual step button and an automated animation button, as illustrated in the figure. The modeling that is described above does not account for any changes in the land surface or the submerged bottom due to shifting sediments, erosion, or accretion. Like in a bathtub, the model simply raises water in the basins over a fixed surface and uses the MHW line as the starting point. The output of the model is expressed as a zone of inundation illustrated in light blue. Figure 5 is an example of a time series of inundation using the High rate of sea level rise (Table 1) for an area in Northampton County, Virginia. The years 2012, 2080, and 2100 are shown.

9 Figure 5 a. 2012 Figure 5 b. 2080 Figure 4 c. 2100 Figure 5. An inundation time series. More information about sea level rise and flooding in Virginia can be found in this 2012 study prepared by CCRM: http://ccrm.vims.edu/recurrent_flooding/recurrent_flooding_study_web.pdf. References Parris, A., P. Bromirski, V. Burkett, D. Cayan, M. Culver, J. Hall, R. Horton, K. Knuuti, R. Moss, J. Obeysekera, A. Sallenger, and J. Weiss. 2012. Global Sea Level Rise Scenarios for the US National Climate Assessment. NOAA Tech Memo OAR CPO 1. 37 pp. National Oceanic and Atmospheric Administration (NOAA), 2012. Sea Level Rise Viewer, http://www.csc.noaa.gov/digitalcoast/tools/slrviewer/. United States Army Corps of Engineers (USACOE), 2013. Sea Level Rise Calculator, http://www.corpsclimate.us/ccaceslcurves.cfm.