A polygon feature class of Federal Emergency Management Agency (FEMA) flood hazard zones within Miami-Dade County. The data depicts the inundation limits representing flood risk information and supporting data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

A line feature class of the county flood criteria boundaries within Miami-Dade County. The purpose of the Miami-Dade County Flood Criteria Map is to determine the minimum ground surface elevation of developed properties, crown/grade of roads, and secondary canal banks based on a 10-year, 24-hour storm event, 2060 scenario with SLR, and the minimum top elevation of seawalls, unless higher elevations are required by other regulatory applicable standards. Available for review and comment October 22, 2021 through December 22, 2021.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

A table of the Flood Zones.Updated: Every 10 yrs

Flood Zones dataset current as of 2012. Identify the boundaries of the Flood Zone area.

Urban growth models have increasingly been used by planners and policy makers to visualize, organize, understand, and predict urban growth. However, these models reveal a wide disparity in their attention to policy factors. Some urban growth models capture few if any specific policy effects (e.g.,as model variables), while others integrate certain policies but not others. Since zoning policies are the most widely used form of land use control in the United States, their conspicuous absence from so many urban growth models is surprising. This research investigated the impacts of zoning on urban growth by calibrating and simulating a cellular automaton urban growth model, SLEUTH, under two conditions in a South Florida location. The first condition integrated restrictive agricultural zoning into SLEUTH, while the other ignored zoning data. Goodness of fit metrics indicate that including the agricultural zoning data improved model performance. The results further suggest that agricultural zoning has been somewhat successful in retarding urban growth in South Florida. Ignoring zoning information is detrimental to SLEUTH performance in particular, and urban growth modeling in general.

A polygon feature class of the Federal Emergency Management Agency (FEMA) Flood Insurance Rate Map (FIRM) map panels for Miami-Dade County.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

A polygon feature class of the Federal Emergency Management Agency (FEMA) Flood Zones for Miami-Dade County (1994).Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The Floodplain Mapping/Redelineation flood risk boundaries are derived from the engineering information Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).

A line feature class of the county flood criteria boundaries within Miami-Dade County, adopted by the County Commission in 1982.Updated: Every 10 yrs The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

The flooding extent polygons are based on wave-driven total water levels for the coral reef-lined coast of Florida. The wave and sea level conditions were propagated using the XBeach open-source model (available at https://oss.deltares.nl/web/xbeach) over 100-m spaced shore-normal transects modified to account for base, mean elevation, and mean erosion scenarios. The impact of future coral reef degradation on coastal protection was examined for two different seafloor elevation-change scenarios based on DEM projections of the study area out 100 years from 2001 using either 1) historical rates of mean elevation-change as a conservative change model, or 2) historical rates of mean erosion. Methods describing the generation of the 'mean elevation' and 'mean erosion' scenarios are described in detail in Yates and others (2018, 2019a, and 2019b). The greater colonization results in higher rugosity and thus hydrodynamic roughness via friction and was parameterized per van Dongeren and others (2013) and Quataert and others (2015). Where the locations along each transect were coincident with one of the damage-assessment locations, a reduction in roughness, and/or an increase in profile depth were applied. The changes to bathymetry and roughness were then carried on to each XBeach model run to ascertain the change in flooding during large storm events due to the projected reef degradation. These flood extents can be combined with economic, ecological, and engineering tools to provide a rigorous financial valuation of the projected future coastal protection benefits of Florida’s coral reefs.

A polygon feature class of the Coastal A Zone boundaries. Developed to aid the spatial location of the Coastal A Zones in Miami-Dade County for permitting purposes. Based on the Miami-Dade County Digital Flood Insurance Rate Map (DFIRM), effective September 11, 2009 published by FEMA and the ASCE 24 guidelines. 'Coastal A� Zone according to FEMA, is the area landward of a V Zone or landward of an open coast without mapped V Zones. In a coastal A Zone, the principal source of flooding will be astronomical tides, storm surges, seiches or tsunamis and not riverine flooding. During base flood conditions, the potential for breaking wave heights between 1.5 feet and 3.0 ft, will exist.Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This dataset, called FloodPop, contains estimates of the population and housing in high flood hazard areas in the contiguous US at the Census block, tract, county, and state levels as well as classified building footprints and validation data. The dataset corresponds with the forthcoming manuscript entitled “High-resolution estimates of the US population in high fluvial flood hazard areas”.

Note: The folders building_footprints.gdb, building_footprints_df, and validation/ buildings_w_lu.gdb contain modified building footprints from Overture Maps (https://overturemaps.org/), including information from OpenStreetMap (https://www.openstreetmap.org/), USA Structures, the National Structure Inventory, and the US release of Microsoft Building footprints. The data in building_footprints.gdb, building_footprints_df, and validation/buildings_w_lu.gdb are made available under the Open Database License (ODbL) v1.0 (https://opendatacommons.org/licenses/odbl/1-0/), while the rest of the repository is made available under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/) .

Contents

fp_summaries: FloodPop results in tabular and geospatial formats. Each file in this folder has columns from the original census dataset at the corresponding spatial scale and similar added columns.

Files • blocks_by_state.gdb: An Esri file geodatabase containing a feature class of FloodPop results at the Census block level for each state. State abbreviations are at the beginning of the feature class name. • cartographic.gdb: An Esri file geodatabase containing feature classes representing cartographic tract, county, and state level FloodPop estimates. The feature classes should be used for visualization but not used for analysis. • summaries.gdb: An Esri file geodatabase containing feature classes representing tract, county, and state level FloodPop estimates. The feature classes can be used for analysis. • summary_csvs: Comma Separated Value (CSV) files containing FloodPop estimates for Census blocks, tracts, counties, and states. This folder also contains a CSV (state_res_or_not_summary.csv) that summarizes the sources of building classifications by state, parsing out the count and area of buildings for residential (res_or_not = 1), non-residential (res_or_not = 0), and unknown (res_or_not = -1) buildings.

Added columns For files in the fp_summaries folder, estimates of the population, total housing units, and occupied housing units were appended to census data boundaries. Census variables “p1_001n” (total population), “h1_001n” (total housing units), and “h1_002n” (occupied housing units) were added to all census boundaries. Then, columns were added for each census variable intersecting each scenario of estimated flood hazard (SFHA, best-available SFHA, and either SFHA). Lower and upper bounds were calculated for population and occupied housing units but not for total housing units as block-level counts for total housing units did not have privacy noise added. Columns related to population use the prefix “pop_”, total housing units uses “tot_hu_”, and occupied housing units uses “occ_hu_”. An example of the naming convention for population estimate columns is below, and this was replicated for total housing units (without upper and lower bounds) and occupied housing units: • pop_sfha: Estimated population within the FEMA Special Flood Hazard Area (SFHA). • pop_sfha_low: Lower bounds (90% CI) of estimated population within the FEMA Special Flood Hazard Area (SFHA). • pop_sfha_high: Upper bounds (90% CI) of estimated population within the FEMA Special Flood Hazard Area (SFHA). • pop_best_sfha: Estimated population within the FEMA SFHA (if mapped by FEMA) or the estimated SFHA (if not mapped by FEMA). • pop_best_sfha_low: Lower bounds (90% CI) of estimated population within the FEMA SFHA (if mapped by FEMA) or the estimated SFHA (if not mapped by FEMA). • pop_best_sfha_high: Upper bounds (90% CI) of estimated population within the FEMA SFHA (if mapped by FEMA) or the estimated SFHA (if not mapped by FEMA). • pop_either_sfha: Estimated population within either the FEMA SFHA or estimated SFHA. • pop_either_sfha_low: Lower bounds (90% CI) of estimated population within either the FEMA SFHA or estimated SFHA. • pop_either_sfha_high: Upper bounds (90% CI) of estimated population within either the FEMA SFHA or estimated SFHA.

Additional columns for block-level results • out_sfha_area: Building footprint area (m2) that does not intersect the SFHA. • within_sfha_area: Building footprint area (m2) that intersects the SFHA. • ratio_area_sfha: The ratio of total building footprint area that intersects the SFHA. • out_est_sfha_area: Building footprint area (m2) that does not intersect the estimated SFHA. • within_est_sfha_area: Building footprint area (m2) that intersects the estimated SFHA. • ratio_area_est_sfha: The ratio of total building footprint area that intersects the estimated SFHA. • out_best_sfha_area: Building footprint area (m2) that does not intersect the best-available SFHA. • within_best_sfha_area: Building footprint area (m2) that intersects the best-available SFHA. • ratio_area_best_sfha: The ratio of total building footprint area that intersects the best-available SFHA. • out_either_sfha_area: Building footprint area (m2) that does not intersect either SFHA. • within_either_sfha_area: Building footprint area (m2) that intersects either SFHA. • ratio_area_either_sfha: The ratio of total building footprint area that intersects either SFHA. • ci_low: Lower bounds estimate (90% CI) of block population. • ci_high: Upper bounds estimate (90% CI) of block population. • ci_low_hu: Lower bounds estimate (90% CI) of block occupied housing units. • ci_high_hu: Upper bounds estimate (90% CI) of block occupied housing units.

validation: Folder containing geodatabases used for the presented validation exercises that focus on Mecklenburg County, NC, Miami-Dade County, FL, and Sacramento, CA. • buildings_w_lu.gdb: Modified Overture Maps building footprints for the validation area with land use classifications from local datasets. • input_cities.gdb: Parcels with classified land use from local datasets. • sj_cities.gdb: Parcels that intersect modified Overture Maps building footprints for the validation area. • validation_blocks.gdb: FloodPop estimates for census blocks that intersect modified Overture Maps building footprints for the validation area.

building_footprints.gdb: An Esri file geodatabase containing classified building footprint feature classes for each state used to create FloodPop estimates. Each footprint contains information on building classification, presence within the SFHA, estimated SFHA, and FEMA study footprint, and Census block. State abbreviations are at the beginning of the feature class name.

building_footprint_dfs: Folder containing a tabular version (Parquet format) of building footprints for each state. State abbreviations are at the beginning of the file name.

The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). In addition to the preceding, required text, the Abstract should also describe the projection and coordinate system as well as a general statement about horizontal accuracy.

Updated FEMA Flood Mapping for Broward County, FL. This is a preliminary assessment of updates to Flood Zones from December 2019.

A raster dataset of the county flood criteria boundaries within Miami-Dade County. The purpose of the Miami-Dade County Flood Criteria Map is to determine the minimum ground surface elevation of developed properties, crown/grade of roads, and secondary canal banks based on a 10-year, 24-hour storm event, 2060 scenario with SLR, and the minimum top elevation of seawalls, unless higher elevations are required by other regulatory applicable standards. Available for review and comment October 22, 2021 through December 22, 2021.Download County Flood Criteria Raster

Flooding extent polygons based on wave-driven total water levels for the coral reef-lined coasts of Florida and Puerto Rico. The wave and sea-level conditions were propagated using the XBeach open-source model (available at https://oss.deltares.nl/web/xbeach) over 100-m spaced shore-normal transects modified to account for base and post-storm scenarios. In situ observations following Hurricanes Irma and Maria by Viehman and others (2018, 2020a, and 2020b) were used to create maps of damage to reefs Transect depth profiles were modified to reflect post-storm conditions. Higher coral cover results in higher rugosity and thus hydrodynamic roughness via friction and was parameterized per van Dongeren and others (2013) and Quataert and others (2015). Where the locations along each transect were coincident with damage, a reduction in roughness and/or an increase in profile depth were applied according to the level of recorded damage. The changes to bathymetry and roughness were then carried on to each XBeach model run to ascertain the change in flooding during large storm events due to the damage of the reefs. These flood extents can be combined with economic, ecological, and engineering tools to provide a rigorous financial valuation of the coastal protection benefits lost by Florida’s and Puerto Rico’s coral reefs due to damage during the 2017 hurricanes.

The flooding extent polygons are based on wave-driven total water levels for the coral reef-lined coast of Florida. The wave and sea level conditions were propagated using the XBeach open-source model (available at https://oss.deltares.nl/web/xbeach) over 100-m spaced shore-normal transects modified to account for base, mean elevation, and mean erosion scenarios. The impact of future coral reef degradation on coastal protection was examined for two different seafloor elevation-change scenarios based on DEM projections of the study area out 100 years from 2001 using either 1) historical rates of mean elevation-change as a conservative change model, or 2) historical rates of mean erosion. Methods describing the generation of the 'mean elevation' and 'mean erosion' scenarios are described in detail in Yates and others (2018, 2019a, and 2019b). The greater colonization results in higher rugosity and thus hydrodynamic roughness via friction and was parameterized per van Dongeren and others (2013) and Quataert and others (2015). Where the locations along each transect were coincident with one of the damage-assessment locations, a reduction in roughness, and/or an increase in profile depth were applied. The changes to bathymetry and roughness were then carried on to each XBeach model run to ascertain the change in flooding during large storm events due to the projected reef degradation. These flood extents can be combined with economic, ecological, and engineering tools to provide a rigorous financial valuation of the projected future coastal protection benefits of Florida’s coral reefs.

The flooding in the greater New Orleans area that resulted from Hurricanes Katrina and Rita in September, 2005, left behind accumulations of sediments up to many centimeters thick on streets, lawns, parking lots, and other flat surfaces. These flood sediment deposits have been the focus of extensive study by the US Environmental Protection Agency (EPA) and Louisiana Department of Environmental Quality (LDEQ) due to concerns that the sediments may contain elevated levels of heavy metals, organic contaminants, and microbes.

The U.S. Geological Survey (USGS) is characterizing a limited number of flood sediment samples that were collected on September 15-16 and October 6-7, 2005, from the greater New Orleans area by personnel from the USGS Louisiana Water Science Center in Baton Rouge. Small samples (< 3 pints each) of wet to dry flood sediment were collected from 11 localities around downtown New Orleans on September 15, 2005, and two large samples (40 pints each) of wet flood sediment were collected from the Chalmette area on September 16. Twelve additional samples (8-10 pints each) were collected from New Orleans, Slidell, Rigolets, and Violet on October 6 and 7.

The USGS characterization studies of these flood sediments are designed to produce data and interpretations regarding how the sediments and any contained contaminants may respond to environmental processes. This information will be of use to cleanup managers and DoI/USGS scientists assessing environmental impacts of the hurricanes and subsequent cleanup activities.

[Summary provided by the USGS.]

Large amounts of rain fell on southern Maine from the afternoon of April 15, 2007, to the afternoon of April 16, 2007, causing substantial damage to houses, roads, and culverts. This report provides an estimate of the peak flows on two rivers in southern Maine - the Mousam River and the Little Ossipee River because of their severe flooding. The April 2007 estimated peak flow of 9,230 ft per second at the Mousam River near West Kennebunk had a recurrence interval between 100 and 500 years; 95-percent confidence limits for this flow ranged from 25 years to greater than 500 years. The April 2007 estimated peak flow of 8,220 ft per second at the Little Ossipee River near South Limington had a recurrence interval between 100 and 500 years; 95-percent confidence limits for this flow ranged from 50 years to greater than 500 years.

[Summary provided by the USGS.]

Public Facing Web Application for Flood Zone in Brevard County