NCCOS Assessment: A Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD, 2023-06-01 to 2025-09-30

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Freitag, Amy; Auerswald, Katherine; Pope, Bria; Regan, Seann; Sudol, Taryn, 2025, "NCCOS Assessment: A Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD, 2023-06-01 to 2025-09-30", https://doi.org/10.7910/DVN/HZDQEF, Harvard Dataverse, V2

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Description	This dataset includes census block group level component scores of various indices from the National Centers for Coastal Ocean Science (NCCOS) Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD. Indices included in this archived dataset include SoVI®, ecosystem services valuation, structural exposure, population projections, urban heat hazard, and flood hazard. Each component score is aggregated to the block group level geography provided by the U.S. Census Bureau. Additionally, intermediary raster-based datasets on stormwater flooding hazard are provided, as well as spatial data on wetlands and protected areas. This assessment uses a geospatial, indicator-driven approach to integrate data from a variety of sources related to community risk in Baltimore, MD and the surrounding 5 counties of Baltimore, Harford, Howard, Anne Arundel, and Queen Anne’s. SoVI® was derived from Census data and applied to each block group. Stormwater flooding potential was calculated using an application of the “FIGUSED” methodology based on locally relevant datasets. This methodology incorporates seven indicators frequently used to identify areas of high flooding potential. These indicators are: “F” – flow accumulation, “I”– rainfall intensity, “G” – geology (hydrologic soil groups), “U” –land use, “S” – slope, “E” – elevation, and “D” – distance from the drainage network. For each of these indicators, a value of 1 corresponds to higher flood potential, while values closer to zero (or null) correspond to lower flood potential. The final raster dataset ranges from 0-7, and all data were resampled to a 30 meter resolution grid and also applied to each block group. A structural exposure index was calculated by aggregating each contributing indicator to the block group. An ecosystem service value index was created by averaging a total ecosystem service valuation model across each block group. Sea level rise projections and storm surge estimates from the National Oceanic Atmospheric Administration were calculated at the block group level. An urban heat index was derived using a combination of sensor data from Johns Hopkins University (for Baltimore City) and remotely sensed data, in conjunction with land use/land cover data, for suburban and rural areas. Both raster and block group aggregations are available. Additionally, data on wetland extent and protected areas are included in the archival package.
Subject	Social Sciences
Keyword	Atlantic Ocean, Chesapeake Bay, Social Science, Coastal Change: Vulnerability, Mitigation, and Restoration, Atlantic Ocean, Geospatial, Maryland
Notes	Coastal communities are exposed to numerous climate-related hazards, all of which are projected to increase in intensity and frequency in the coming decades. The way these hazards are experienced depends on a variety of factors that make coping with and recovering from natural hazards more difficult for some communities than others. Maryland faces growing pressure from water hazards, including storm surge, sea level rise, and stormwater. With its extensive coastline, the Chesapeake Bay makes managing floodwaters a key priority moving forward. The varied and dense populations on the Western Shore mean that the intersection of multiple vulnerabilities and climate hazards presents a high risk of cascading and compounding hazard events.
License/Data Use Agreement	CC0 1.0

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Citation Metadata

Persistent Identifier	doi:10.7910/DVN/HZDQEF
Publication Date	2025-03-26
Title	NCCOS Assessment: A Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD, 2023-06-01 to 2025-09-30
Alternative URL	https://coastalscience.noaa.gov/project/assessing-community-risk-in-relation-to-flood-hazards-in-the-baltimore-maryland-metro-area/
Other Identifier	NOAA InPort: https://www.fisheries.noaa.gov/inport/item/75313
Author	US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)0009-0001-1764-1213 CSS, Inc., under contract to NOAA NOS National Centers for Coastal Ocean Science0009-0001-7938-1146 Pope, BriaFlorida Agricultural and Mechanical University, NOAA Center for Coastal and Marine Ecosystems CSS, Inc., under contract to NOAA NOS National Centers for Coastal Ocean Science0000-0002-1034-0282 Sudol, TarynMaryland Sea Grant
Point of Contact	Use email button above to contact. Freitag, Amy (US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)) NCCOS Data Manager (US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS))
Description	This dataset includes census block group level component scores of various indices from the National Centers for Coastal Ocean Science (NCCOS) Community Risk Assessment of Flooding and Heat Hazards in Baltimore, MD. Indices included in this archived dataset include SoVI®, ecosystem services valuation, structural exposure, population projections, urban heat hazard, and flood hazard. Each component score is aggregated to the block group level geography provided by the U.S. Census Bureau. Additionally, intermediary raster-based datasets on stormwater flooding hazard are provided, as well as spatial data on wetlands and protected areas. This assessment uses a geospatial, indicator-driven approach to integrate data from a variety of sources related to community risk in Baltimore, MD and the surrounding 5 counties of Baltimore, Harford, Howard, Anne Arundel, and Queen Anne’s. SoVI® was derived from Census data and applied to each block group. Stormwater flooding potential was calculated using an application of the “FIGUSED” methodology based on locally relevant datasets. This methodology incorporates seven indicators frequently used to identify areas of high flooding potential. These indicators are: “F” – flow accumulation, “I”– rainfall intensity, “G” – geology (hydrologic soil groups), “U” –land use, “S” – slope, “E” – elevation, and “D” – distance from the drainage network. For each of these indicators, a value of 1 corresponds to higher flood potential, while values closer to zero (or null) correspond to lower flood potential. The final raster dataset ranges from 0-7, and all data were resampled to a 30 meter resolution grid and also applied to each block group. A structural exposure index was calculated by aggregating each contributing indicator to the block group. An ecosystem service value index was created by averaging a total ecosystem service valuation model across each block group. Sea level rise projections and storm surge estimates from the National Oceanic Atmospheric Administration were calculated at the block group level. An urban heat index was derived using a combination of sensor data from Johns Hopkins University (for Baltimore City) and remotely sensed data, in conjunction with land use/land cover data, for suburban and rural areas. Both raster and block group aggregations are available. Additionally, data on wetland extent and protected areas are included in the archival package.
Subject	Social Sciences
Keyword	Atlantic Ocean https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Chesapeake Bay https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Social Science https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Coastal Change: Vulnerability, Mitigation, and Restoration https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Atlantic Ocean https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Geospatial https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/ Maryland https://coastalscience.noaa.gov/about/ (NCCOS Discovery Keywords) https://coastalscience.noaa.gov/about/
Notes	Coastal communities are exposed to numerous climate-related hazards, all of which are projected to increase in intensity and frequency in the coming decades. The way these hazards are experienced depends on a variety of factors that make coping with and recovering from natural hazards more difficult for some communities than others. Maryland faces growing pressure from water hazards, including storm surge, sea level rise, and stormwater. With its extensive coastline, the Chesapeake Bay makes managing floodwaters a key priority moving forward. The varied and dense populations on the Western Shore mean that the intersection of multiple vulnerabilities and climate hazards presents a high risk of cascading and compounding hazard events.
Language	English
Producer	National Centers for Coastal Ocean Science (US DOC; NOAA; NOS) (NCCOS) http://coastalscience.noaa.gov/
Contributor	Project Member: Fredrika Moser, Maryland Sea Grant Project Member: Erin Crowley-Champoux, Maryland Sea Grant Project Member: Sasha Land, Maryland Department of Natural Resources Project Member: Nicole Carlozo, Maryland Department of Natural Resources Project Member: Elliott Campbell, Maryland Department of Natural Resources Project Member: George Edmonds, Maryland Department of Natural Resources Research Group: Julie Reichert-Nguyen, Chesapeake Bay Program Resilience Working Group Research Group: Jamileh Soueidan, Chesapeake Bay Program Resilience Working Group Research Group: Claire Cambardella, Baltimore Urban Waters Partnership Research Group: Amanda Rockler, Baltimore Urban Waters Partnership Related Person: Nancy Fonti, Baltimore Urban Waters Partnership Related Person: Elizabeth Andrews, William & Mary Law School
Funding Information	US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS): https://ror.org/05ba43f71
Distributor	NCCOS Data Manager (US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS))
Depositor	Alva, Amanda
Deposit Date	2025-03-21
Date of Collection	Start Date: 2023-06-01; End Date: 2025-09-30
Data Type	Community Risk
Software	ArcGIS Pro, Version: 3.4.0 SPSS
Data Source	Baltimore Office of Sustainability. (2015). Urban heat island sensors. Retrieved from https://www.baltimoresustainability.org/urban-heat-island-sensors/; Baltimore Metropolitan Council. (2024). Housing & Development. Retrieved October 4 from https://bmcpulse.org/pulseweb/housing-development/; Cutter, S. L., & Emrich, C. T. (2017). Social Vulnerability Index (SoVI®): Methodology and limitations. Hazards and Vulnerability Research Institute.; Campbell, E., Marks, R., & Conn, C. (2017). Accounting for Maryland's ecosystem services: Integrating the value of nature into decision making. https://data.imap.maryland.gov/maps/1931c85a49774daea99fa6644d8acc9e/about; Chesapeake Conservancy, University of Vermont Spatial Analysis Lab, & US Geological Survey. (2022). One-meter Resolution Land Cover Change Dataset for the Chesapeake Bay Watershed 2013/14 - 2017/18 (https://cicgis.org/portal/apps/webappviewer/index.html?id=bdf7ca3e249a40fd9a9d83d6e16100ea&extent=-88.252,35.0981,-62.3462,45.7489; ESRI Business Analyst. (2023). Business locations [Data source: Data Axle]. Accessed 02/12/24.; Federal Emergency Management Agency. (2024, March 4). National Risk Index for Natural Hazards. Retrieved April 16, 2024, from https://www.fema.gov/flood-maps/products-tools/national-risk-index; Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope-Evros region, Greece. Science of the Total Environment, 538, 555–563. https://doi.org/10.1016/j.scitotenv.2015.08.055; Maryland iMAP. (2024). MD iMAP Portal. https://data.imap.maryland.gov/. Accessed 2/12/24.; NASA. (2025). Sea level projection tool. Retrieved February 25, 2025, from https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool; National Park Service. (n.d.). Cultural resources planning and compliance. Retrieved March 5, from https://www.nps.gov/orgs/1027/cultresplan.htm; National Park Service. (2017). National Register of Historic Places. Retrieved July 12, 2018, from https://www.nps.gov/subjects/nationalregister/data-downloads.htm; Natural Resources Conservation Service. (2024). Soil Survey Geographic Database (SSURGO). U.S. Department of Agriculture. Retrieved from https://www.nrcs.usda.gov/resources/data-and-reports/soil-survey-geographic-database-ssurgo; NOAA Fisheries. (2022). Oyster reef habitat. Retrieved August 3, from https://www.fisheries.noaa.gov/national/habitat-conservation/oyster-reef-habitat; NOAA Meteorological Development Laboratory. (n.d.). SLOSH Display (Potential Storm Surge). Retrieved February, from https://vlab.noaa.gov/web/mdl/sdp; NOAA Meteorological Development Laboratory. (n.d.). SLOSH Model. Retrieved February 25, from https://vlab.noaa.gov/web/mdl/slosh; NOAA National Hurricane Center. (n.d.-a). Sea, lake, and overland surges from hurricanes (SLOSH). https://www.nhc.noaa.gov/surge/slosh.php; NOAA National Hurricane Center. (n.d.-b). Storm Surge Maximum of the Maximum (MOM). https://www.nhc.noaa.gov/surge/momOverview.php; NOAA National Weather Service. (n.d.). NOWData - NOAA online weather data. Retrieved from https://www.weather.gov/wrh/Climate?wfo=lwx; NOAA Office for Coastal Management. (2024, March 13). Sea level rise data download. National Oceanic and Atmospheric Administration National Ocean Service. https://coast.noaa.gov/slrdata/; NOAA Tides and Currents. (2025). Coastal inundation dashboard. Retrieved from https://tidesandcurrents.noaa.gov/inundationdb/inundation.html?id=8574680#flooddays; PRISM Climate Group. (n.d.). PRISM gridded climate data. Retrieved from https://prism.oregonstate.edu/; Trust for Public Land. (2019). Urban heat island severity for U.S. cities (2019). Retrieved from https://hub.arcgis.com/datasets/TPL::urban-heat-island-severity-for-u-s-cities-2019/about; U.S. Census Bureau. (2021). American Community Survey 5-Year Estimates: Comparison Profiles 5-Year. Retrieved October 4, from http://api.census.gov/data/2022/acs/acs5; U.S. Census Bureau. (2021). TIGER/Line with selected demographic and economic data. Retrieved from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-data.html; U.S. Census Bureau. (2023, July 1). QuickFacts: Baltimore city, Maryland. Retrieved October 4, from https://www.census.gov/quickfacts/fact/table/baltimorecitymaryland/PST045223; U.S. Department of Homeland Security. (2023). Homeland infrastructure foundation-level data (HIFLD). Retrieved from https://hifld-geoplatform.hub.arcgis.com/; U.S. Environmental Protection Agency. (2022). Soil runoff potential (Indicator reference sheet). https://www.epa.gov/system/files/documents/2022-03/soil-runoff-potential-indicator-reference-sheet-20220306.pdf; U.S. Environmental Protection Agency, Office of Research and Development. (2016). Updates to the demographic and spatial allocation models to produce Integrated Climate and Land Use Scenarios (ICLUS) Version 2.; United States Geological Survey. (2020). National Hydrography Dataset. Retrieved December 15, 2024, from https://www.usgs.gov/core-science-systems/ngp/national-hydrography/access-national-hydrography-products; United States Geological Survey. (2021). United States Geological Survey 3D Elevation Program 1 arc-second Digital Elevation Model. Retrieved December 15, 2024, from https://catalog.data.gov/dataset/1-arc-second-digital-elevation-models-dems-usgs-national-map-3dep-downloadable-data-collec; United States Geological Survey. (2024). Protected Areas Database of the United States (PAD-US). Retrieved from https://www.sciencebase.gov/catalog/item/652d4f80d34e44db0e2ee45c; United States Geological Survey. (2024). USGS National Water Information System: Mapper and data retrieval. Retrieved from https://data.usgs.gov/datacatalog/data/USGS:77ae0551-c61e-4979-aedd-d797abdcde0e; United States Geological Survey National Hydrography. (2020). National hydrology dataset flowline data. Retrieved October 2024, from https://www.usgs.gov/national-hydrography/access-national-hydrography-products
Documentation and Access to Sources	Use Limitation: NOAA makes no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA cannot assume liability for any damages caused by any errors or omissions in these data. Data License: These data were produced by NOAA and are not subject to copyright protection in the United States. NOAA waives any potential copyright and related rights in these data worldwide through the Creative Commons Zero 1.0 Universal Public Domain Dedication (CC0 1.0).

Geospatial Metadata

Geographic Coverage	United States, Maryland, Baltimore
Geographic Unit	Census Block Group, 30 x 30 meter raster grid
Geographic Bounding Box	-77.188030 -75.737639 39.723687 38.706644

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