This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries. Please reference the metadata for contact information.

This dataset (2012-2020) is a compilation of the Land Use/Land Cover datasets created by the 5 Water Management Districts in Florida based on imagery -- North West Florida Water Management District (NWFWMD) 2019, Suwannee River Water Management District (SRWMD) 2019-2020, St. John's River Water Management District (SJRWMD) 2013-2016, 2013 (Dec 2012 – Mar 2013) - Duval, Bradford, 2014 (Dec 2013 – Mar 2014) - Alachua, Baker, Clay, Flagler, Lake, Marion, Nassau, Osceola, Polk, Putnam, St. John’s, 2015 (Dec 2014 – Mar 2015) - Brevard, Indian River, Okeechobee, Seminole, Volusia, 2016 (Dec 2015 – Mar 2016) - Orange, South West Florida Water Management District (SWFWMD) 2020 and South Florida Water Management District (SFWMD) 2017-2019. Codes are derived from the Florida Land Use, Cover, and Forms Classification System (FLUCCS-DOT 1999) but may have been altered to accommodate region differences.

The Functional Wetlands dataset is based on wetlands identified in the Cooperative Land Cover Map v3.3. Functional wetlands are defined as those in a more natural state and the prioritization is based on overlap with a Land Use Intensity index and FNAI Potential Natural Areas. For more information see the Conservation Needs Assessment Technical Report: https://www.fnai.org/conslands/florida-forever. Value 1 = Priority 1 (Highest); Value 2 = Priority 2; Value 3 = Priority 3; Value 4 = Priority 4; Value 5 = Priority 5; Value 6 = Priority 6Data download page

Geospatial data about St Lucie County, Florida National Wetlands Inventory. Export to CAD, GIS, PDF, CSV and access via API.

This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries. Please reference the metadata for contact information.

The AHF system has been deployed in a series of survey campaigns to collect over 60,000 points covering Everglades National Park, Loxahatchee National Wildlife Refuge, Water Conservation Areas 2 and 3, portions of Big Cypress National Preserve, as well as areas along the Lake Okeechobee littoral zone. Since the AHF System is able to penetrate Everglades vegetation and water cover, it has provided an unprecedented regional view of Everglades topographic gradients and sub-water surface structure. These data are now being used to simulate Everglades water flow with higher resolution and greater accuracy, to estimate water depths in real-time for field study planning, and as input for habitat models used to forecast the effects of water level changes on various important species. The elevation data collected through this project also formed the basic input to generate a regional topographic surface that is the basis for the Everglades Depth Estimation Network (EDEN). These high accuracy elevation data are made available to anyone through the South Florida Information Access website (http://sofia.usgs.gov) data exchange pages.

MAP Activity Accomplishment The USGS Airborne Height Finder (AHF) System was used to perform topographic surveys in Water Conservation Area 3A within the extents of the Lone Palm Head and North of Lone Palm Head 7.5-minute topographic map quadrangles as specified in the MAP/COE Interagency Agreement. The AHF system has been used throughout South Florida for elevation data collection because traditional surveying methods are too difficult, too costly, or simply impossible to use in the harsh wetland environment and broadly inaccessible terrain of the Florida Everglades. This is especially true considering the shear size of the hydrodynamic and biological modeling domains. The AHF is a helicopter-based instrument that uses a GPS receiver, a computer, and a mechanized plumb bob to make measurements. These data were post processed to the reference stations that are part of the AHF geodetic control network. For reasons of accuracy, these reference stations are located no more then 15 kilometers from the helicopter during AHF operations. The GPS data were post processed using Ashtech’s PNAV On The Fly (OTF) software to obtain the trajectory of the AHF platform. These results are then processed through an in-house software package that separates the actual survey points and results from the trajectory. The points are manually checked to ensure data accuracy and completeness. Digital elevation models (DEMs) were then generated from the elevation point data. Existing elevation data derived from LiDAR data for this area were replaced with AHF derived DEMs for reasons of vertical accuracy. The DEMs have been posted on the South Florida Information Access (SOFIA) website: http://sofia.usgs.gov/exchange/desmond/desmondelev.html.

The National Wetland Inventory (NWI) from 2005 was produced by Great Lakes/Atlantic Region Office (GLARO) of Ducks Unlimited with funding provided by EGLE. The NWI 2005 was an update to the original 1978 NWI Layer produced by US Fish and Wildlife Service, and utilized 1998 and 2005 imagery to map wetland loss/change over time. Classification of wetlands is based on the Cowardin Wetland Classification system with a minimum mapping unit of 1/10 acre. The NWI+ data includes hydrogeomorphic classification of wetlands in addition to the normal Cowardin wetland classification, and includes functional assessment information of each wetland in the attribution. The full report on this dataset is available by request to the Wetlands, Lakes, and Streams Unit.

Field Name

Descriptions

NWICode

The wetland classification codes are a series of letter and number codes that have been developed to adapt the national wetland classification system to map form. These alpha-numeric codes correspond to the classification nomenclature that best describes a particular wetland habitat. For example, PFO1A = Palustrine (P), Forested (FO), Broad-leaved Deciduous (1), Temporarily Flooded (A).

HGMCode

Code for the Landscape Level Assessment. Combines each of the coded types. For example TEBAVR = Terrene Basin Vertical Flow

Acres

Size of the wetland polygon.

NWIKey

Unique Identifier Key used in the 2005 NWI update.

ImageDate

Date of the imagery in which the wetland polygon was mapped from.

VegOrNotVeg

Is the wetland vegetated or open water (non veg).

EGLEType

Type of wetland open water, emergent, forested, shrub scrub etc.

Modifier

Wetland modifier identifying excavated, ditched, impounded etc.

Landform

The type of geological feature in which the wetland resides. Slope (SL) Wetlands occurring on a slope of 5% or greater. Island (IS) A wetland completely surrounded by water. Fringe (FR) Wetland occurs in the shallow water zone of a permanent waterbody. *NWI water regime F, G, and H Floodplain (FP) Wetland occurs on an active alluvial plain along a river and some streams. *Modifiers FPba (Basin) and FPfl ( Flat) Basin (BA) Wetland occurs in a distinct depression. *NWI water regime C and E Flat (FL) Wetland occurs on a nearly level landform. *NWI water regime A and B

Landscape_Position

Landscape position values are determined by cross referencing NWI with hydrology and topography. NWI polygons that spatially intersect a stream/river in the National Hydrography Dataset (NHD) are classified as lotic. Lotic type wetlands can be further refined to indicate their adjacency to a stream or a river (lotic stream or lotic river). High resolution NHD data was used to differentiate rivers from streams in this analysis. A NHD classification completed by MDNR, Institute for Fisheries Research separated rivers by temperature gradient (cold, cool, warm) and size, based on average water flows (cubic feet per second or CFS). This dataset was used in the LLWFA analysis to mark this distinction. NWI Polygons that are determined to be within the basin of a lake are classified as lentic. Identifying the extent of a lake basin, and thus which wetlands fall within it, is done with the assistance of digital elevation models (DEM). NWI Polygons that don’t intersect surface water features or aren’t spatially located within a lake basin are classified as terrene

Waterbody_Type

Waterbody type classification is the simplest of the 4 LLWW descriptors. Ponds, lakes, and rivers are classified as such based explicitly on NWI Cowardin code. Lakes and ponds were separated at the 5-acre mark, all open-water polygons less than or equal to 5 acres were classified as ponds, while all open-water polygons larger than 5 acres were classified as lakes. The 5 acre cutoff was chosen to remain consistent with previously existing EGLE regulations. High resolution NHD data was used to differentiate rivers from streams in this analysis. A NHD classification completed by MDNR, Institute for Fisheries Research separated rivers by temperature gradient (cold, cool, warm) and size, based on average water flows (CFS) This dataset was used in the LLWFA analysis to mark this distinction.

Waterflow_Path

Water flow path, otherwise known as hydrodynamics, is classified by automated and manual interpretation of the intersection of NHD surface water features and NWI. Automated methods include intersecting NHD and NWI to capture throughflow wetlands (in-stream wetlands), both natural and artificial. A distinction is drawn in NHD between natural stream/river features and artificial canal/ditch features. Vegetated NWI wetlands that don’t intersect any surface water body are classified as isolated. Detailed coding was developed in an effort to differentiate intermittent, artificial, and perennial connections between wetlands and other surface waterbodies. Any wetland classified as lentic (Landscape Position) is automatically assigned a water flow path of bidirectional, accounting for the tidal effects of lakes on adjacent wetlands

Landform1

A secondary code used to determine type of floodplain and if a vegetated wetland is associated with a pond. Associated w/Pond (pd) Basin (ba) Flat (fl)

Landscape1

Field used to display if a wetland falls within a Headwater area Headwater (hw)

HMValues

All function Values combined to perform the count.

FunCount

Number of Functions each wetland could be performing.

FloodWaterStorage

Function field for Flood Water Storage H (2) = High M (1) = Moderate

StreamflowMaintenance

Function field for Streamflow Maintenance H (2) = High M (1) = Moderate

NutrientTransformation

Function field for Nutrient TransformationH (2) = High M (1) = Moderate

SedimentRetention

Function field for Sediment Retention H (2) = High M (1) = Moderate

ShorelineStabilization

Function field for Shoreline Stabilization H (2) = High M (1) = Moderate

FishHabitat

Function field for Fish Habitat. H (2) = High M (1) = Moderate

StreamShading

Function field for Stream Shading H (2) = High M (1) = Moderate

WaterfowlWaterbirdHabitat

Function field for Waterfowl and Water Bird Habitat. H (2) = High M (1) = Moderate

ShorebirdHabitat

Function field for Shorebird Habitat. H (2) = High M (1) = Moderate

InteriorForestBirdHabitat

Function field for Interior Forest Bird Habitat. H (2) = High M (1) = Moderate

AmphibianHabitat

Function field for Amphibian Habitat. H (2) = High M (1) = Moderate

CORIWetlandsSpecies

Function field for Conservation of Rare Imperiled Wetland Speices H (2) = High M (1) = Moderate

GroundWaterInfluence

Function field for Ground Water Influence H (2) = High M (1) = Moderate

CarbonSequestration

Function field for Carbon Sequestration H (2) = High M (1) = Moderate

PathogenRentention

Function field for Pathogen Retention 1 = Wetlands that intersect 303d listed streams, 2 = Wetlands within a 500 ft buffer of 303d streams, 3 Streams that intersect wetlands that filter Pathogens, 4 wetlands within a 500 ft buffer that filter pathogens. For historical wetlands this would be showing best areas to do potential restoration.

For more information about this content reach out to Jeremy Jones at jonesj28@michigan.gov.

A hierarchical vegetation classification model (10 m resolution) was developed for southwest Florida wetlands using a fusion of multispectral and synthetic aperture radar (SAR) remotely sensed imagery. Sentinel-1 and 2 imagery were obtained from Dec 2015-Sept 2017, split into wet and dry seasons, and processed for a range of vegetation and multi-temporal indices for a total of 26 predictor layers. Training datasets included polygons developed from field surveys and high resolution imagery collected from 2010 - 2018. The domain was first split into estuarine and interior wetlands, then an open water, forest, or grassland model (high level) was developed for each wetland type. Finally, classification model that included species and community-level classes (fine level) was created. Mean overall accuracy was 0.90 and 0.80 for the high and low level models, respectively.

Vegetation mapping will monitor the spatial extent, pattern, and proportion of plant communities within major landscape regions of the Greater Everglades Wetlands. Specific landscape changes to be monitored that pertain to the CERP include the following: · Changes in the extent and orientation of sloughs, tree islands, and sawgrass ridges as flow patterns, flow volumes, hydroperiods, and water quality are modified in the ridge and slough landscape · Changes in the extent and distribution of cattail as flow patterns, flow volumes, hydroperiods, and water quality are modified in the ridge and slough landscape · Changes in the extent and distribution of exotic plant communities · Changes in the distribution and configuration of tidal creeks, salt marshes, and mangrove forests as changing flow patterns and volumes interact with sea level and salinity in the mangrove estuaries of Florida Bay and the Gulf of Mexico · Changes in the distribution of plant communities in calcitic wetlands, including tussock-forming Muhlenbergia and sawgrass communities in the major breeding locations of the Cape Sable seaside sparrow, as hydrologic gradients change · Changes in the distribution of plant communities of eastern Big Cypress with the removal of L-28 and hydroperiod restoration in the Kissimmee Billy Strand Regional landscape patterns will be monitored using a combination of a transect and sentinel site sampling design (Section 3.1.3.1) and a stratified random sampling design (Section 3.1.3.10). Aerial photo-interpretation is currently the best tool available to produce dependable and accurate maps of the Everglades (Welch et al. 1995, Doren et al. 1999, Rutchey and Vilchek 1999, Richardson and Harris 1995). Aerial photography of the greater Everglades wetland system at a scale of 1/24,000 will be purchased at three-year intervals. Photography will be interpreted and ground-truthed to produce vegetation maps at three-year intervals for the randomly selected cells. Additional cells will be mapped to supplement the stratified random cells along the alignments of the coastal, marl prairie -slough, and WCA gradients that are described above. The vegetation classification scheme of Jones et al. (unpublished report) will be used to identify major plant communities that are defined by typical dominant species.

This data release includes geospatial data for irregularly flooded wetlands and high marsh and salt pannes/flats along the northern Gulf of Mexico coast from Texas to Florida. Specifically, this release includes seven products: (1) a map highlighting the continuous probability that an area is an irregularly flooded wetland; (2) a map of irregularly flooded wetland probability reclassified into four bins; (3) a map delineating high marsh and salt pannes/flats; (4) a map from Lake Pontchartrain, Louisiana to the Florida Big Bend delineating the coverage of irregularly flooded wetlands that have Juncus roemerianus (Black needlerush) as the dominant vegetation species; (5) a spatial metadata file showing what elevation data were used for specific locations; (6) a supplemental version of the high marsh and salt pannes/flats map that has a second class for high marsh for parts of Texas where succulents and Distichlis spicata were dominant species; and (7) a dataset of supplemental proje ...

FEMA Flood ZonesFlorida Wetlands

Domestic wastewater facilities that are permitted for wastewater to wetland discharge in Florida. These facilities are regulated by the Florida Department of Environmental Protection Domestic Wastewater Program. This data is intended to be used for general informational and planning purposes. For questions pertaining to this map, please contact Diana Turner at diana.m.turner@dep.state.fl.us.

The Comprehensive Everglades Restoration Plan (CERP - www.evergladesplan.org), authorized as part of the Water Resources and Development Act (WRDA) of 2000 (U.S. Congress 2000), is an $US8-10 billion hydrologic restoration project for south Florida. CERP includes 68 separate projects to be managed over the next 30 years by the South Florida Water Management District (SFWMD) and the U. S. Army Corps of Engineers (USACE). Restoration Coordination and Verification (RECOVER) is a system-wide program within the CERP to organize and provide scientific and technical support for design, implementation, and assessment of the restoration program. It is the role of RECOVER to develop a system-wide monitoring and assessment plan that will document how well the CERP is meeting its objectives for ecosystem restoration.

Vegetation mapping will be used to document changes in the spatial extent, pattern, and proportion of plant communities within the landscape. This map represents the 2009 baseline land-cover vegetation map of northern Everglades National Park and Big Cypress National Preserve..

For file geodatabase download,Click Here. The South Florida Water Management District (District or SFWMD) and the U.S. Army Corps of Engineers have built six large treatment wetlands, referred to as Stormwater Treatment Wetlands (STAs), in the Everglades Agricultural Area (EAA) as part of a State and Federal initiative to protect the Everglades (Chimney and Goforth, 2001; Sklar et al., 2005). These treatment wetlands are intended to reduce high phosphorus concentrations in surface runoff coming from the EAA before this water reaches the northern portion of the present-day Everglades, i.e., the Water Conservations Areas. Each STA is subdivided into a number of treatment cells by interior levees. Treatment wetlands reduce the concentration of water-borne pollutants through natural bio-geochemical processes (Kadlec and Wallace, 2009). Wetland biogeochemistry, in turn, is intimately associated with the extent and condition of the wetland’s vegetation community (Reddy and DeLaune, 2009). Because of the important relationship between wetland treatment performance and vegetation, the vegetation communities in the STAs have been monitored throughout their operational histories. This effort was mandated as a condition of STA operating permits and by the Process Development and Engineering section of the District’s Long Term Plan (Burns & McDonnell, 2003). The vegetation communities in the STAs have been monitored using two different approaches: (1) vegetation maps were prepared for each STA based on the spatial distribution of different vegetation types interpreted from aerial photographs and (2) field surveys were conducted at a network of sites within each wetland to catalog plant taxa and assess vegetation areal coverage of the dominant taxa. The field-survey program was initiated as a cost-effective alternative to mapping for characterizing the plant community.For information about the imagery collection access this file: 2012 Imagery Collection in STAsFor details how the data was processed see the Lineage section.

Tidal flats are non-vegetated areas of sand or mud protected from wave action and composed primarily of mud transported by tidal channels. An important characteristic of the tidal flat environment is its alternating tidal cycle of submergence and exposure to the atmosphere. This GIS data set was created to show a statewide representation of unvegetated tidal flats, compiled from the best available sources. The sources included individual seagrass mapping studies and National Wetlands Inventory (NWI) data for Florida. The NWI was ERASEd using more recent data sources that showed some areas were indeed vegetated. See Source Information for more details on how each source was used.

The EnviroAtlas Tampa, FL Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue and near infrared) aerial photography from April-May 2010 at 1 m spatial resolution. Eight land cover classes were mapped: impervious surface, soil and barren, grass and herbaceous, trees and forest, water, agriculture, woody wetland, and emergent wetland. The area mapped is defined by the US Census Bureau's 2010 Urban Statistical Area for Tampa, and includes the cities of Clearwater and St. Petersburg, as well as additional out-lying areas. An accuracy assessment using a stratified random sampling of 600 samples (100 per class) yielded an overall accuracy of 70.67 percent and an area weighted accuracy of 81.87 percent using a minimum mapping unit of 9 pixels (3x3 pixel window). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

This data set serves as documentation of land cover and land use (LCLU) within the South Florida Water Management District as it existed in 2017-19. Land Cover Land Use data was updated from 2014-16 LCLU by photo-interpretation from 2017-19 aerial photography and classified using the SFWMD modified FLUCCS classification system. Features were interpreted from the county-based aerial photography (4 in - 2 ft pixel), see imagery year in the "AERIAL DATE" field. The features were updated on screen from the 2014-16 vector data. Horizontal accuracy of the data corresponds to the positional accuracy of the county aerial photography. The minimum mapping unit for classification was 0.5 acres for wetlands and 5 acres for uplands. This data is partial and is not considered complete until the entire SFWMD has been completed.Photointerpretation Key: https://geoext.geoapps.sfwmd.gov/TPubs/2014_SFWMD_LULC_Photointerpretation_Key.pdf

This project consists of 5 files, a ReadMe (text) and four geospatial shapefiles generated in ArcPro 3.0.4. (ESRI). Two shapefiles depict the distribution and spatial extent of artificial water features (AWFs, e.g., reservoirs, stormwater retention ponds) in the 1950s and in 2007 in the Tampa Bay Watershed. The other two depict the distribution and spatial extent of wetlands in the 1950s and in 2007 in the Tampa Bay Watershed. We used a combination of heads-up digitizing (while observing 1950s aerial black and white aerial imagery) and reference to ancillary datasets to map wetlands and AWFs in the 1950s. We based the wetlands 2007 map off the land use land cover dataset published by SWFWMD (2008). We similarly based the 2007 AWF dataset on the SWFWMD LULC dataset but additionally digitized AWF features while referencing aerial imagery and products supplied by the Mosaic Company.Additional method descriptions can be found in Rains et al. 2013 (wetland datasets, https://link.springer.com/article/10.1007/s13157-013-0455-4) and in Rains et al. (2023) titled Reorganizing the waterscape: asymmetric loss of wetlands and gain of artificial water features in a mixed-use watershed (AWF and change datasets). We initially developed the two wetland datasets, in collaboration with the Balmoral Group, to support a wetland area change analysis in the Tampa Bay Watershed. We subsequently used these datasets in our present work (Rains et al. 2023) to analyze change in wetland distribution, configuration, and geometry (e.g., perimeter length). The wetland datasets are not meant as a map of jurisdictional wetlands.

Statistical analyses and maps representing mean, high, and low water-level conditions in the surface water and groundwater of Miami-Dade County were made by the U.S. Geological Survey, in cooperation with the Miami-Dade County Department of Regulatory and Economic Resources, to help inform decisions necessary for urban planning and development. Sixteen maps were created that show contours of (1) the mean of daily water levels at each site during October and May for the 2000-2009 water years; (2) the 25th, 50th, and 75th percentiles of the daily water levels at each site during October and May and for all months during 2000-2009; and (3) the differences between mean October and May water levels, as well as the differences in the percentiles of water levels for all months, between 1990-1999 and 2000-2009. The 80th, 90th, and 96th percentiles of the annual maximums of daily groundwater levels during 1974-2009 (a 35-year period) were computed to provide an indication of unusually high groundwater-level conditions. These maps and statistics provide a generalized understanding of the variations of water levels in the aquifer, rather than a survey of concurrent water levels. Water-level measurements from 473 sites in Miami-Dade County and surrounding counties were analyzed to generate statistical analyses. The monitored water levels included surface-water levels in canals and wetland areas and groundwater levels in the Biscayne aquifer. Maps were created by importing site coordinates, summary water-level statistics, and completeness of record statistics into a geographic information system, and by interpolating between water levels at monitoring sites in the canals and water levels along the coastline. Raster surfaces were created from these data by using the triangular irregular network interpolation method. The raster surfaces were contoured by using geographic information system software. These contours were imprecise in some areas because the software could not fully evaluate the hydrology given available information; therefore, contours were manually modified where necessary. The ability to evaluate differences in water levels between 1990-1999 and 2000-2009 is limited in some areas because most of the monitoring sites did not have 80 percent complete records for one or both of these periods. The quality of the analyses was limited by (1) deficiencies in spatial coverage; (2) the combination of pre- and post-construction water levels in areas where canals, levees, retention basins, detention basins, or water-control structures were installed or removed; (3) an inability to address the potential effects of the vertical hydraulic head gradient on water levels in wells of different depths; and (4) an inability to correct for the differences between daily water-level statistics. Contours are dashed in areas where the locations of contours have been approximated because of the uncertainty caused by these limitations. Although the ability of the maps to depict differences in water levels between 1990-1999 and 2000-2009 was limited by missing data, results indicate that near the coast water levels were generally higher in May during 2000-2009 than during 1990-1999; and that inland water levels were generally lower during 2000-2009 than during 1990-1999. Generally, the 25th, 50th, and 75th percentiles of water levels from all months were also higher near the coast and lower inland during 2000-2009 than during 1990-1999. Mean October water levels during 2000-2009 were generally higher than during 1990-1999 in much of western Miami-Dade County, but were lower in a large part of eastern Miami-Dade County.

This EnviroAtlas dataset describes the percentage of each block group that is classified as impervious, forest, green space, wetland, and agriculture. Impervious is a combination of dark and light impervious. Forest is a combination of trees and forest and woody wetlands. Green space is a combination of trees and forest, grass and herbaceous, agriculture, woody wetlands, and emergent wetlands. Wetlands includes both Woody and Emergent Wetlands.This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).