Primary lakes in north and central Florida developed from GNIS, USGS 1:24k Hydrography data, 1994 DOQQs, and USGS DRGs and reviewed by DEP and WMD personnel.

Lake Okeechobee is located in south Florida and is bounded by the Kissimmee River Basin to the north and Everglades National Park to the south. Lake Okeechobee is the largest lake (1890 km2) in Florida and encompasses a drainage area of over 14,200 km2. The lake provides agricultural water supply, back-up water supply for urban areas, flood protection to adjacent communities, critical bird and fisheries habitats, is part of the Okeechobee Waterway navigation canal, and boating recreation. Over the past 100 years, land use change and population increases have adversely impacted the health of the lake mostly by extreme water level fluctuations and excessive nutrient loading mostly from agricultural activities. High-resolution bathymetric mapping was conducted in 2001 in Lake Okeechobee by the USGS, in cooperation with SFWMD. High-resolution, acoustic bathymetric surveying is a proven method to map sea and lake floor elevations. Survey tracklines were spaced 1000 meters apart and orientated in a north-south direction. Tracklines collected in an east-west orientation (intersecting tracklines) functioned to serve as a cross-check and to assess the relative vertical accuracy of the survey. Ideally, vertical data values at the crossing should be exactly the same. In reality, this is not always the case due to random errors of survey system. Several perimeter survey lines were also collected. Soundings were collected along each trackline at 3-meter spacing. Approximately 1,550 kilometers of survey lines were collected. In shallow areas, data was collected in a minimum of 0.6 meters water depth except where there is potential damage to the bottom environment or the boat/motors was a significant possibility. This report serves as an archive of processed single-beam bathymetry data that were collected in Lake Okeechobee, Florida in 2001. Geographic information system data products include XYZ data, bathymetric contours, USGS quadrangle maps, and associated formal Federal Geographic Data Committee (FGDC) metadata.

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Note: This description is taken from a draft report entitled "Creation of a Database of Lakes in the St. Johns River Water Management District of Northeast Florida" by Palmer Kinser. Introduction“Lakes are among the District’s most valued resources. Their aesthetic appeal adds substantially to waterfront property values, which in turn generate tax revenues for local governments. Fish camps and other businesses, that provide lake visitors with supplies and services, benefit local economies directly. Commercial fishing on the District’s larger lakes produces some income, , but far greater economic benefits are produced from sport fishing. Some of the best bass fishing lakes in the world occur in the District. Trophy fishing, guide services and high-stakes fishing tournaments, which they support, also generate substantial revenues for local economies. In addition, the high quality of District lakes has allowed swimming, fishing, and boating to become among the most popular outdoor activities for many District residents and attracts many visitors. Others frequently take advantage of the abundant opportunities afforded for duck hunting, bird watching, photography, and other nature related activities.”(from likelihood of harm to lakes report).ObjectiveThe objective of this work was to create a consistent database of natural lake polygon features for the St. Johns River Water Management District. Other databases examined contained point features only, polygons representing a wide range of dates, water bodies not separated or coded adequately by feature type (i.e. no distinctions were made between lakes, rivers, excavations, etc.), or were incomplete. This new database will allow users to better characterize and measure the lakes resource of the District, allowing comparisons to be made and trends detected; thereby facilitating better protection and management of the resource.BackgroundPrior to creation of this database, the District had 2 waterbody databases. The first of these, the 2002 FDEP Primary Lake Location database, contained 3859 lake point features, state-wide, 1418 of which were in SJRWMD. Only named lakes were included. Data sources were the Geographic Names Information System (GNIS), USGS 1:24000 hydrography data, 1994 Digital orthophoto quarter quadrangles (DOQQs), and USGS digital raster graphics (DRGs). The second was the SJRWMD Hydrologic Network (Lake / Pond and Reservoir classes). This data base contained 42,002 lake / pond and reservoir features for the SJRWMD. Lakes with multiple pools of open water were often mapped as multiple features and many man-made features (borrow pits, reservoirs, etc.) were included. This dataset was developed from USGS map data of varying dates.MethodsPolygons in this new lakes dataset were derived from a "wet period" landcover map (SJRWMD, 1999), in which most lake levels were relatively high. Polygons from other dates, mostly 2009, were used for lakes in regionally dry locations or for lakes that were uncharacteristically wet in 1999, e.g. Alachua Sink. Our intension was to capture lakes in a basin-full condition; neither unusually high nor low. To build the data set, a selection was made of polygons coded as lakes (5200), marshy lakes (5250, enclosed saltwater ponds in salt marsh (5430), slough waters (5600), and emergent aquatic vegetation (6440). Some large, regionally significant or named man-made reservoirs were also included, as well as a small number of named excavations. All polygons were inspected and edited, where appropriate, to correct lake shores and merge adjacent lake basin features. Water polygons separated by marshes or other low-ground features were grouped and merged to form multipart features when clearly associated within a single lake basin. The initial set of lake names were captured from the Florida Primary Lake Location database. Labels were then moved where needed to insure that they fell within the water bodies referenced. Additional lake names were hand entered using data from USGS 7.5 minute quads, Google Maps, MapQuest, Florida Department of Transportation (FDOT) county maps, and other sources. The final dataset contains 4892 polygons, many of which are multi-part.Operationally, lakes, as captured in this data base, are those features that were identified and mapped using the District’s landuse/landcover scheme in the 5200, 5250, 5430, 5600 classes referenced above; in addition to some areas mapped tin the 6440 class. Some additional features named as lakes, ponds, or reservoirs were also included, even when not currently appearing to be lakes. Some are now very marshy or even dry, but apparently held deeper pools of water in the past. A size limit of 1 acre or more was enforced, except for named features, 30 of which were smaller. The smallest lake was Fox Lake, a doline of 0.04 acres in Orange county. The largest lake, Lake George covered 43,212.8 acres.The lakes of the SJRWMD are a diverse set of features that may be classified in many ways. These include: by surrounding landforms or landcover, by successional stage (lacustrine to palustrine gradient), by hydrology (presence of inflows and/or outflows, groundwater linkages, permanence, etc.), by water quality (trophic state, water color, dissolved solids, etc.), and by origin. We chose to classify the lakes in this set by origin, based on the lake type concepts of Hutchinson (1957). These types are listed in the table below (Table 1). We added some additional types and modified the descriptions to better reflect Florida’s geological conditions (Table 2). Some types were readily identified, others are admittedly conjectural or were of mixed origins, making it difficult to pick a primary mechanism. Geological map layers, particularly total thickness of overburden above the Floridan aquifer system and thickness of the intermediate confining unit, were used to estimate the likelihood of sinkhole formation. Wind sculpting appears to be common and sometimes is a primary mechanism but can be difficult to judge from remotely sensed imagery. For these and others, the classification should be considered provisional. Many District lakes appear to have been formed by several processes, for instance, sinkholes may occur within lakes which lie between sand dunes. Here these would be classified as dune / karst. Mixtures of dunes, deflation and karst are common. Saltmarsh ponds vary in origin and were not further classified. In the northern coastal area they are generally small, circular in outline and appear to have been formed by the collapse and breakdown of a peat substrate, Hutchinson type 70. Further south along the coast additional ponds have been formed by the blockage of tidal creeks, a fluvial process, perhaps of Hutchinson’s Type 52, lateral lakes, in which sediments deposited by a main stream back up the waters of a tributary. In the area of the Cape Canaveral, many salt marsh ponds clearly occupy dune swales flooded by rising ocean levels. A complete listing of lake types and combinations is in Table 3. TypeSub-TypeSecondary TypeTectonic BasinsMarine BasinTectonic BasinsMarine BasinCompound dolineTectonic BasinsMarine BasinkarstTectonic BasinsMarine BasinPhytogenic damTectonic BasinsMarine BasinAbandoned channelTectonic BasinsMarine BasinKarstSolution LakesCompound dolineSolution LakesCompound dolineFluvialSolution LakesCompound dolinePhytogenicSolution LakesDolineSolution LakesDolineDeflationSolution LakesDolineDredgedSolution LakesDolineExcavatedSolution LakesDolineExcavationSolution LakesDolineFluvialSolution LakesKarstKarst / ExcavationSolution LakesKarstKarst / FluvialSolution LakesKarstDeflationSolution LakesKarstDeflation / excavationSolution LakesKarstExcavationSolution LakesKarstFluvialSolution LakesPoljeSolution LakesSpring poolSolution LakesSpring poolFluvialFluvialAbandoned channelFluvialFluvialFluvial Fluvial PhytogenicFluvial LeveeFluvial Oxbow lakeFluvial StrathFluvial StrathPhytogenicAeolianDeflationAeolianDeflationDuneAeolianDeflationExcavationAeolianDeflationKarstAeolianDuneAeolianDune DeflationAeolianDuneExcavationAeolianDuneAeolianDuneKarstShoreline lakesMaritime coastalKarst / ExcavationOrganic accumulationPhytogenic damSalt Marsh PondsMan madeExcavationMan madeDam

A point feature class representing the random site selections within small lakes comprising the small lake sample frames from the cycle 1 to the most recent Status Network cycle. Refer to https://floridadep.gov/DEAR/Watershed-Monitoring-Section for more information on the Status monitoring network.

These data were automated to provide an accurate high-resolution historical shoreline of Lake Okeechobee, Florida suitable as a geographic information system (GIS) data layer. These data are derived from shoreline maps that were produced by the NOAA National Ocean Service including its predecessor agencies which were based on an office interpretation of imagery and/or field survey. The NGS...

Hydrology polygon features in Lee County, Florida digitized from aerial photography.

The Florida Fish and Wildlife Conservation Commission (FWC) collected annual trawl data at 27 open-water sites from 1987 to 1991 (Bull et al. 1995). Nearly 37,000 fish were recorded in 438 10-minute open-water trawls (Bull et al. 1995). Seven species accounted for 98% of the total number and total fish biomass. Clustering of sites based on mean catch of the primary species expressed as number and weight produced four distinct groups. The groups were labeled as the northeast shore, northwest shore, south-southwest shore and open water area. Areal fish distribution patterns also were compared using analysis of variance (ANOVA) and Tukey’s HSD post hoc test. Within the four groups there were significant differences in the distribution of certain fish species. In addition to the open-water trawl sites, the FWC has utilized electrofishing techniques to collect annual largemouth bass (Micropterous salmodies) (LMB) data from 22 near-shore and interior marsh locations since 1999 (Havens et al. 2004). Although the trawl and electrofishing data provide some baseline information, still there is limited data regarding temporal changes in the community structure, density and condition of the primary sport fish LMB, black crappie (Pomoxis nigromaculatus), bluegill (Lepomis macrochirus) and redear (Lepomis microlophus) sunfish) and other fish species in Lake Okeechobee. During this study, fish species will be collected from 49 historic sampling locations. Fish assemblages in the 27 open water regions of the lake will be sampled with an Otter Trawl net. The 22 near-shore and interior marsh sites will be sampled utilizing electrofishing gear. Ancillary data, including water temperature, dissolved oxygen, pH, turbidity, conductivity, and sediment/aquatic plant type will be recorded at the 49 sampling locations.
The two historic sets of non-MAP data will be used to help establish baseline conditions for the near-shore, interior marsh and open-water fishery. It is appropriate to include the non-MAP data in our analysis as current sampling will occur at the historical locations and sampling methods will be similar. We anticipate significant spatial differences in fish abundance and biomass will exist at the near-shore, interior marsh and open water sites. Therefore, similar statistical tests including cluster analysis and analysis of variance should be used to evaluate temporal changes in the near-shore and open water fishery. Detailed statistical analysis should be conducted at a minimum of every three years to evaluate long-term trends and establish relationships between fish distribution, condition, and community structure and environmental conditions including habitat and water depth.
The objectives of this project are to evaluate temporal changes in Lake Okeechobee’s fishery by determining annual changes in the areal distribution, condition, density and community structure (year classes) of all major fish species found in the near-shore, interior marsh and open-water regions of the lake. Ancillary data including water temperature, dissolved oxygen, pH, turbidity, conductivity, and sediment type also will be recorded.

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A point feature class representing the random site selections within large lakes comprising the large lake sample frames from Cycle 2 to the current Status Network cycle. Refer to https://floridadep.gov/dear/watershed-monitoring-section/content/status-monitoring-network for more information on the Status monitoring network.

Digital surfaces and thicknesses of selected hydrogeologic units of the Floridan aquifer system were developed to define an updated hydrogeologic framework as part of the U.S. Geological Survey Groundwater Resources Program. This map layer shows areal and linear water features of Florida, Georgia, South Carolina, and Alabama. The original file was produced by joining the individual State hydrography layers from the 1:2,000,000- scale Digital Line Graph (DLG) data produced by the USGS. This map layer was formerly distributed as Hydrography Features of the United States. This is a revised version of the January 2003 map layer.

These data provide an accurate high-resolution shoreline compiled from imagery of Intracoastal Waterway, Wetappo Creek South Prong to Lake Wimico, FL . This vector shoreline data is based on an office interpretation of imagery that may be suitable as a geographic information system (GIS) data layer. This metadata describes information for both the line and point shapefiles. The NGS attributio...

This dataset serves as documentation of vegetation in the littoral zones around Lake Kissimmee, Florida using digital aerial photography. The Vegetation communities were mapped using digital aerial imagery acquired from an Intergraph DMC Sensor in June 2015 (Lake Kissimmee). Mapping was accomplished through the use of Esri software supplimented with fieldwork. Each distinct community of emergent and floating vegetation was mapped according to the Florida Land Use, Cover and Forms Classification System (FLUCCS) as modified by FWC for the purposes of mapping lake vegetation.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Benthic macroinvertebrates play an important role in the Lake Okeechobee ecosystem. They provide food resources for fish, contribute to sediment nutrient recycling, and can serve as sensitive indicators of water quality (Jonasson 1969, Brinkhurst 1965, Warren et al. 1995). Given these overall MAP goals, the evaluation of benthic invertebrate communities of the Lake Okeechobee pelagic region was implemented with the following objectives: 1. Sample Lake Okeechobee sublittoral zone benthic invertebrate communities in three areally dominant habitat zones (mud, sand, peat) twice annually for a three year period, duplicating the timing, locations, and methods of Warren et al. (1995).

1. Use results from sampling to evaluate the pelagic region benthic invertebrate community structure, thereby establishing a baseline for future evaluation and comparison. Elements of community structure to be documented include: taxonomic composition, taxa richness, absolute abundance, relative abundance, diversity (Shannon’s equation, as per Krebs 1999), and evenness (as per Pielou 1977).

2. Compare current (2005-08) pelagic region benthic invertebrate community structure with corresponding structural elements of the 1987-96 study period. Based upon these comparisons, identify changes in invertebrate community structure and speculate on the implications to future invertebrate community health as well as the overall health of the Lake Okeechobee ecosystem.

3. Relate results from the study to CERP hypotheses and apply conclusions to the adaptive management process.

The intent of maintaining continuity with the methods and sampling sites utilized during the 1987-1996 FWC sublittoral zone evaluation (Warren 1991, Warren et al. 1995) was to supplement the pre-CERP implementation baseline (2005-2008 study) with additional data collected over a longer term and over a broader range of environmental conditions.

Benthic macroinvertebrate communities of the Lake Okeechobee pelagic zone were sampled by the Florida Fish and Wildlife Conservation Commission (FWC) on a quarterly (February, May, August, November) basis in 1987-1988 and then semi-annually (January and July) through 1996. Since 1996, invertebrate communities have been sampled intermittenly, with the last collection occurring in June 2000. Sampling was conducted at 18 fixed sites, with six sites each in mud (northern and mid-lake), sand (western), and peat (southern) habitat zones. Three pseudo-replicate samples were collected at each of the 18 sites during every sampling event, yielding 18 samples per habitat zone and a total of 54 samples. Samples were collected with a petite ponar dredge.

The water levels in Lake Okeechobee were at record low levels in the summer of 2001 making hydrographic surveying ideal in that less area must be covered by boat to fully map the lake floor. This condition also allowed the upper elevations of the lake, which were now exposed, to be mapped by traditional survey techniques or airborne topographic LIDAR technology. Conversely, due to the very flat slope of the lake floor, much of the lakebed was less than 0.6m (2') deep making surveying by any method very difficult at best.

This polygon feature class defines the extent and type of littoral vegetation within the northwestern marsh portion of Lake Okeechobee circa 2015. A grid-based approach was used to identify the dominant vegetation type within each 100 sq meter (1 hectare) area. Dominant vegetation types were photointerpreted from 12 inch stereoscopic aerial imagery collected May-June 2015 (1 hectare). SFWMD conducted an internal accuracy assessment of the map. The assessment was conducted both on the softcopy stereo vegetation mapping work station and in the field via helicopter flights. Dominant (VegLabel1) vegetation classes were tallied up to calculate each dominant class' contribution toward the total percent of all the classified grid cells.

Stressed Lakes for 2015. This service is for the Open Data Download application for the Southwest Florida Water Management District.

The map is a composite image of spectral bands 3 (630-690 nanometers, red), 4 (775-900 nanometers,near-infrared), and 5 (1,550-1750 nanometers, middle-infrared) and the new panchromatic band (520-900, green to near-infrared) acquired by the Landsat 7 enhanced thematic mapper (ETM) sensor on February 05, 2000.