GSA 2020 Connects Online

Paper No. 234-3
Presentation Time: 6:00 PM

DEVELOPING A MOBILE FLOOD WARNING APPLICATION FOR THE CHARLESTON, SC REGION


COZAD, Connor D.1, WESTBROOK, Cole1, LEVINE, Norman S.2, KEMPTON, Julia Quinn1, BRAUD, Alex2, AFFONSO, Lancie A.1 and KNAPP, Landon C.2, (1)Department of Computer Science, College of Charleston, 66 George Street, Charleston, SC 29424, (2)Department of Geology and Environmental Geosciences, College of Charleston, 202 Calhoun Street, Charleston, SC 29424

One of the most visible manifestations of global warming and climate change in the Charleston region is the rising sea level. In Charleston, this is seen as tidal inundation of roads and property. The issue is exacerbated when intense precipitation coincides with high tides. Impassable streets pose a hazard to drivers and pedestrians. This can be especially dire for those who try to drive through the waters. The goal of this project, funded by the South Carolina Sea Grant Consortium, is to develop a map application that shows current and predicted street inundation across Charleston County, South Carolina. This app will be used by citizens, first responders, and municipalities to more safely navigate the tidal flooding prevalent across the county.

The project examines several sources of readily available tide and precipitation data. Data from the National Oceanic and Atmospheric Administration, the National Weather Service, crowdsourcing websites, and proprietary agencies were considered. Historical data from each source was collected (data mined), processed (cleaned), and analyzed for use in the app. The data sources were chosen based on a variety of factors, including their accuracy, resolution, and refresh frequency. Once chosen, the selected data sources are reformatted for integration into an ArcGIS environment. Scripts were integrated into layers part of a ArcGIS WebApp. The app’s graphical user interface allows the user to view current and predicted street inundation for major flooding events, such as king tides, tropical cyclone storm surges, or other intense precipitation events. Currently the app is using crowd sourced information for validation and work continues on developing a platform independent downloadable interface for users.