Climate change threatens South Florida communities primarily in the area of sea level rise (SLR). Government agencies at federal, state, and local levels have taken actions to monitor, project, and plan for this change. Development of resilient community against sea level rise has become a priority at all levels of planning.
The Carbon-Neutral City Baseline Scenarios Tool has been developed by the Florida International University GIS Center, FIU MBUS and the Geomatics program of the University of Florida. The core team includes Thomas Spiegelhalter (CRUNCH PI), Jennifer Fu (GIS Project Manager), Levente Juhász (technical lead), Hartwig Hochmair (geodata harmonization and visualization), Sheyla De Santana (geo-data preparation), Boyuan Guan (IT infrastructure), Jorge Sotolongo (Design and UX), Julian Gottlieb (Web design), Shrikanth Namuduri Damian Ferrer and Parry Gabriel (data collection and transformation). The funding partner is XXX. Keqi Zhang and Yuepeng Li from FIU’s International Hurricane Research Center provided advise on SLR inundation modeling and use of storm surge SLOSH models.
This tool allows users to select a geographic area within the boundaries of the City of Coral Gables and to slide through different scenarios of sea level rise (SLR) between 1 and 8 feet and hurricane category 1 to 5 storm surges. The application visualizes the extent of flooded areas in response to these scenarios and returns associated statistics about their potential impact on local residents, properties, street network, key facilities, and other infrastructure. The tool is intended for use by city governments and their residents as well as the general public to identify areas of vulnerability so that the City may better plan and invest for the development of a resilient community.
The SLR scenarios were developed using a bath tub model. A detailed description of the algorithm used can be found in (Zhang et al. 2011). The application shows inundated areas for a selected rise in sea level. The Digital Elevation Model (DEM) used in the computations is derived from 2015 Lidar data of Miami-Dade County given in the NAVD88 vertical datum. The original raster DEM dataset was resampled to a raster DEM at a 5m resolution with mean higher high water (MHHW) as a reference surface (tidal datum).
The storm surge scenarios are based on the "Sea, Lake, and Overland Surges from Hurricanes" (SLOSH) model for the Miami basin developed by the by National Hurricane Center (NHC)1. All SLOSH storm surge heights are referenced to the NAVD88 vertical datum. The application uses the Maximum of the Maximum Envelope of High Water (MOM) grid layer at high tide. This model is intended to capture the worst-case high water value at a particular location for hurricane evacuation planning.
Socio-economic statistics are based on Census 2010 block level and 2018 Miami-Dade County Property Appraiser datasets.
The data and maps in this tool illustrate the scale of potential inundation and storm surge mainly on elevation, and do not account for land cover type, drainage structure, rainfall, soil type, etc. Water levels are shown as they would appear during the highest high tides (excludes wind driven tides), also known as MHHW (mean higher high water – see http://co-ops.nos.noaa.gov/datum_options.html for a definition). Inundated areas are determined by simple linear addition of SLR inundation depth values and inundation depth from Storm Surge Scenarios. Due to the nonlinear interaction between storm surge and SLR in shallow water (Zhang et al. 2013), SLR and storm scenarios visualized together are therefore likely an underestimation of the potential worst inundation extent. The maps and data are intended to reflect risk or vulnerability estimation but not for the purpose of forecast, and certainly not a flood map for a given storm. In case of an actual storm, please visit the National Hurricane Center or National Weather Service Web sites.
The following factors were approximated in correlation to population estimates: Building Floor Area, Water Consumption, Carbon Sequestration, Greenhouse Gas Emissions, Service Infrastructure, Demography, Properties, and Land Use. The formula was based on the estimated population from the baseline and is multiplied as follows: ½ for 2040, 2 for 2070, and 4 for 2100. The data is based on the assumption of self-sustained living systems as a scenario solution where outsourced energy, food, and water are minimized to decrease anthropogenic impact and rising sea levels. Sustainable mitigation strategies were not accounted for in estimates; therefore current approximations may be lower or higher than predicted. Sea level rise effects for the years 2040, 2070, and 2100 are based on NOAA’s 2017 Projections of High Scenarios and the University of Florida GeoPlan Center’s SLR inundation surfaces.
The data and maps in this tool are provided "as is", without any warranties whatsoever including, without limitation, any warranty as to its performance, merchantability or fitness for any particular purpose. The entire risk associated with the results and performance of this tool and its associated data is assumed entirely by the user. This tool should be used strictly as a reference tool and not for navigation, permitting, or any legal purposes.
Zhang, K., Dittmar, J., Ross, M., and Bergh, C. (2011). Assessment of sea level rise impacts on human population and real property in the Florida Keys. Climatic Change, 107, 129–146.
Zhang, K., Li, Y., Liu, H., Xu, H., and Shen, J. (2013). Comparison of three methods for estimating the sea level rise effect on storm surge flooding. Climatic Change, 118 (2), 487–500.
Made with in sunny Miami. This app the following open source software and libraries:
Data Sources: NOAA, National Hurricane Center, U.S. Census, Miami Dade County GIS, Miami-Dade County Property Appraiser, Florida Department of Transportation, HERE Navstreets, City of Coral Gables, FIU GIS Center