Technical Support Document for U.S. EPA’s Proposed Rule 

for Numeric Nutrient Criteria for Florida’s Inland 

Surface Fresh Waters 
TSD for U.S. EPA’s Proposed Numeric Nutrient Criteria for FL Inland Surface Fresh Waters

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Disclaimer 

This document is intended to provide technical support to EPA in developing and establishing 

numeric water quality criteria for nutrients under the Clean Water Act (CWA) pursuant to 

Section 303(c)(4), in order to protect aquatic life in the State of Florida from the effects of 

nutrient over-enrichment. This document constitutes scientific information regarding the 

development of numeric criteria for Florida’s inland fresh waters (lakes, streams, springs, and 

canals) reflecting ambient concentrations of nutrients that are protective of aquatic life. The 

information provided herein does not substitute for the CWA or EPA’s regulations; nor is this 

document a regulation itself. Thus, this document cannot and does not impose any legally 

binding requirements on EPA, States, Authorized tribes, the regulated community, or any other 

party, and might not apply to a particular situation or circumstance. This document does not 

constitute a determination by the Administrator under CWA Section 303(c)(4)(B) that new or 

revised water quality standards are needed in the State of Florida. 
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List of Contributing Authors 

Tiffany Crawford, U.S. Environmental Protection Agency1

Ed Decker, U.S. Environmental Protection Agency1

Erica Fleisig, U.S. Environmental Protection Agency1

Richard Greene, U.S. Environmental Protection Agency1

James Hagy, U.S. Environmental Protection Agency1

F. James Keating, U.S. Environmental Protection Agency1

Jan Kurtz, U.S. Environmental Protection Agency 

Jacques Oliver, U.S. Environmental Protection Agency1 

Lauren Petter, U.S. Environmental Protection Agency1

Danielle Salvaterra, U.S. Environmental Protection Agency1

Dan Scheidt, U.S. Environmental Protection Agency1

Dana Thomas, U.S. Environmental Protection Agency1

Timothy Wool, U.S. Environmental Protection Agency1

Lester Yuan, U.S. Environmental Protection Agency1

Jeroen Gerritsen, Tetra Tech1

Jon Harcum, Tetra Tech1

Ann Lincoln, Tetra Tech 

Michael Paul, Tetra Tech1

Lei Zhang, Tetra Tech 

Andrew Bartlett, Florida Department of Environmental Protection 

Russel Frydenborg, Florida Department of Environmental Protection 

Joy Jackson, Florida Department of Environmental Protection 

Daryll Joyner, Florida Department of Environmental Protection 

Denise Miller, Florida Department of Environmental Protection 

Frank Nearhoof, Florida Department of Environmental Protection 

Grover Payne, Florida Department of Environmental Protection 

Emily Peffer, Florida Department of Environmental Protection 

Kenneth Weaver, Florida Department of Environmental Protection 

Nijole Wellendorf, Florida Department of Environmental Protection 

Leska Fore, Statistical Design 

Xu-Feng Niu, Florida State University 

 

1

 U.S. EPA Florida Nutrient Criteria Technical Workgroup for Inland Waters 
TSD for U.S. EPA’s Proposed Numeric Nutrient Criteria for FL Inland Surface Fresh Waters

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Scope and Purpose of this Document 

This document consists of scientific information that EPA gathered and considered as it 

developed its proposed rule for numeric nutrient criteria for Class I and III surface freshwaters in 

the State of Florida. Specifically, this document and the appendices consist of chemical, 

physical, and biological data, meta-data, methods and analyses considered in developing numeric 

nutrient criteria for specific inland surface waters in Florida (i.e., lakes, streams, springs, and 

canals). EPA used this information to develop scientifically-defensible proposed numeric 

nutrient criteria to protect designated uses in these waters. The designated uses for these waters 

are, “Recreation, Propagation and Maintenance of a Healthy, Well-Balanced Population of Fish 

and Wildlife” (F.A.C. 62-302.400). Portions of the information contained in this document were 

also considered by the Florida Department of Environmental Protection as part of its process to 

develop numeric nutrient water quality criteria under state law. 
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Foreword 

Excess nitrogen and phosphorus loadings, or nutrient pollution, are a leading cause of water 

quality degradation in the nation’s waters. Nutrient pollution may result in harmful algal blooms, 

reduced spawning grounds and nursery habitats, fish kills, oxygen-starved hypoxic or "dead" 

zones, and public health concerns related to impaired drinking water sources and increased 

exposure to toxic microbes such as cyanobacteria. Nutrient problems can exhibit themselves 

locally or much further downstream, leading to degraded estuaries, lakes and reservoirs, and to 

hypoxic zones where fish and aquatic life can no longer survive. 

EPA recommends that States adopt numeric nutrient criteria for two causal parameters, such as 

total nitrogen (TN) and total phosphorus (TP), and two response parameters, such as chlorophyll 

a (chl. a) and clarity, into their water quality standards to protect against the effects of nutrient 

pollution. State water quality standards are the foundation for protecting the quality of the 

nation’s surface waters and are the cornerstone of the water quality-based control program 

mandated by the CWA. Standards describe the desired condition of a waterbody and consist of 

three principal elements: (1) the “designated uses” of the state’s waters (e.g., fishing, aquatic life, 

drinking water); (2) “criteria” specifying the amounts of various pollutants, in either numeric or 

narrative form, that may be present in those waters without impairing the designated uses; and 

(3) anti-degradation policies providing for protection of existing water uses and limitations on 

degradation of high quality waters. In the case of Florida lakes and flowing waters, the current 

relevant designated uses of these waters with regard to numeric nutrient criteria are “Recreation, 

Propagation and Maintenance of a Healthy, Well-Balanced Population of Fish and Wildlife” 

(F.A.C. 62-302.400). Numeric nutrient criteria must ensure that these uses are attained, and, that 

downstream uses are protected. 

EPA recognizes that nutrients are essential for life, and that some waters are naturally enriched at 

high levels. It is the excess nutrient levels, resulting from human disturbance and activities that 

lead to accelerated eutrophication that is the endpoint of concern in establishing protective 

numeric nutrient criteria. 

Numeric nutrient water quality standards drive water quality assessments and watershed 

protection management. They support improved development of National Pollution Discharge 

Elimination System (NPDES) permits and Total Maximum Daily Loads (TMDLs) for nutrients. 

They also create state- and community-developed environmental baselines that more effectively 

measure progress and support broader partnerships based on nutrient trading, best management 

practices (BMPs), land stewardship, wetlands protection, voluntary collaboration, and urban 

storm water runoff control strategies. 
TSD for U.S. EPA’s Proposed Numeric Nutrient Criteria for FL Inland Surface Fresh Waters

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Contents 

Disclaimer ....................................................................................................................................... i

List of Contributing Authors ....................................................................................................... ii

Scope and Purpose of this Document......................................................................................... iii

Foreword....................................................................................................................................... iv

Chapter 1: Methodology for Deriving U.S. EPA’s Proposed Criteria for Lakes ................ 1-1

1a. Methodology for Proposed Lake Classification.............................................................1-1 

i. Background............................................................................................................. 1-1 

ii. Data Used for Analysis.......................................................................................... 1-2 

iii. Data Analysis for Classification........................................................................... 1-2 

iv. Other Classification Variables.............................................................................. 1-3 

v. Color and Alkalinity/Specific Conductance Results.............................................. 1-3 

1b. Methodology for Proposed Chlorophyll a Criteria.........................................................1-4 

i. Trophic State and Aquatic Life Use ....................................................................... 1-4 

ii. Reference Condition .............................................................................................. 1-8 

iii. Other Efforts to Establish Chlorophyll a Thresholds ........................................... 1-9 

1c. Methodology for Proposed TP and TN Criteria in Lakes ............................................1-13 

1d. Duration and Frequency for Proposed Lakes Criteria..................................................1-15 

1e. Application of Lake-specific Ambient Calculation Provision for Alternative TP 

and TN Criteria.............................................................................................................1-17 

1f. Alternatives Considered by U.S. EPA..........................................................................1-18 

i. Single Value Approach to Derive Lakes Criteria - Derive TN and TP Criteria 

Using Correlations Associated with the Regression Line or Upper Bound of 

the 50th Percentile Prediction Interval ................................................................. 1-18 

ii. Additional Modification to Proposed Lakes Classification................................. 1-19 

iii. Modification to Include Upper Percentile Criteria with an Associated Ten 

Percent Exceedance Frequency ........................................................................... 1-20 

Chapter 2: Methodology for Deriving U.S. EPA’s Proposed Criteria for Streams............. 2-1

2a. Methodology for Stream Classification: U.S. EPA’s Nutrient Watershed 

Regions (NWRs) ............................................................................................................2-1 

i. Developing a Regionalization Scheme................................................................... 2-1 

ii. Ecoregional and Biological Regionalization Schemes for Florida........................ 2-1 

iii. Refinement of Regionalization for Nutrient Criteria Development ..................... 2-2 

iv. Development of the Nutrient Watershed Regions ................................................ 2-2 

2b. The Use of the Stream Condition Index as an Indicator for Establishing 

Biologically Healthy Conditions....................................................................................2-3 
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i. Development of the Stream Condition Index ......................................................... 2-4 

ii. Establishing Healthy Biological Conditions in Streams––Stream Condition 

Index: Application of the Reference Site Approach ............................................. 2-5 

iii. Biological Condition Gradient Approach............................................................. 2-5 

iv. Evaluation of BCG Calibration Information ........................................................ 2-7 

v. Selecting the Threshold between Healthy and Unhealthy Biological 

Conditions ............................................................................................................. 2-8 

2c. Methodology for Calculating In-stream Protection Values: The Nutrient 

Watershed Region Distribution Approach .....................................................................2-8 

i. Methods for Calculating Attaining Site Distributional Statistics ........................... 2-8 

ii. SCI Data Preparation ............................................................................................. 2-8 

iii. Site Average Water Chemistry............................................................................. 2-9 

iv. Identifying Impaired WBIDs................................................................................ 2-9 

v. Identifying Biologically Unhealthy Site List....................................................... 2-10 

vi. Removing Sites................................................................................................... 2-10 

vii. Calculating Distributional Statistics .................................................................. 2-10 

viii. 75th Percentiles for Site Average Data – In-stream Protective Values............. 2-11 

ix. Distribution of Nutrient Concentrations among Nutrient Regions..................... 2-11 

2d. Duration and Frequency for Proposed Streams Criteria ..............................................2-12 

2e. Protection of Downstream Estuaries and Lakes...........................................................2-13 

i. Downstream Protection of Lakes.......................................................................... 2-13 

ii. Downstream Protection of Estuaries ................................................................... 2-17 

iii. Delineation of Florida’s Estuaries and their Watersheds ................................... 2-22 

2f. Alternative Approach Considered by U.S. EPA ..........................................................2-30 

i. FDEP’s Benchmark Distribution Approach and the Calculation of 

Benchmark Distribution Approach and Selection of Percentiles from the 

Benchmark Distribution ...................................................................................... 2-30 

ii. Identification of Least-Disturbed Streams........................................................... 2-31 

iii. Verification Process for Selection of Benchmark Sites...................................... 2-31 

iv. LDI score of ≤ 2.................................................................................................. 2-32 

v. Screening against the 303(d) List of Impaired Waters ........................................ 2-33 

vi. Screening against the 0.35 mg/L Proposed Nitrate-Nitrite Threshold................ 2-34 

vii. Verification of Surrounding Land Use by Examining High-Resolution 

Aerial Photographs .............................................................................................. 2-34 

viii. Obtaining Input from FDEP District Biologists............................................... 2-34 

ix. Field Evaluation Process, Including Watershed Assessment and Biological 

Appraisal of Benchmark Sites............................................................................. 2-35 

x. Results of Benchmark Screening Process............................................................ 2-36 

xi. Analysis of Nutrient Benchmark Sites Biological Data ..................................... 2-36 
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xii. Calculation of Benchmark Derived Nutrient Criteria........................................ 2-37 

Chapter 3: Methodology for Deriving U.S. EPA's Proposed Criteria for Springs 

and Clear Streams.......................................................................................................... 3-1

3a. Basis for Nitrate-Nitrite Criteria.....................................................................................3-4 

i. Criteria Development Methods............................................................................... 3-6 

ii. Laboratory Studies................................................................................................. 3-6 

iii. Field Surveys ........................................................................................................ 3-7 

iv. TMDL Development Activities............................................................................ 3-8 

v. Analysis of Nutrient Gradient Study Rapid Periphyton Data.............................. 3-10 

vi. Summary and Conclusions ................................................................................. 3-10 

3b. Duration and Frequency for Proposed Springs Criteria ...............................................3-11 

3c. Alternative Approach Considered by U.S. EPA ..........................................................3-12 

i. Nitrate-Nitrite Criteria for all Waters as an Independent Criterion...................... 3-12 

Chapter 4: Methodology for Deriving U.S. EPA’s Proposed Criteria for Canals............... 4-1

4a. Other Analyses Conducted and Considered by U.S. EPA in the Derivation of 

Proposed Numeric Nutrient Criteria for Canals .............................................................4-4 

4b. Duration and Frequency for Proposed Canals Criteria ..................................................4-5 

4c. Alternative Approach Considered by U.S. EPA ............................................................4-6 

i. Stressor-Response Approach .................................................................................. 4-6 

ii. Calculation of TP Criteria for the EAA Using a Downstream Protection 

Approach ............................................................................................................... 4-8 

iii. Upper Percentile Criterion with Low Exceedance Frequency ............................. 4-9 
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Tables 

Table 1-1. Warm-water TSI Categories (after Salas and Martino 1991)................................... 1-22 

Table 1-2. Relationship between Chl. a, TP, and TN, as Described by Florida’s TSI.............. 1-22 

Table 1-3. Summary of the Linear Multiple Regression between Ln Transformed Chl. a

and Ln Transformed TP and TN in Colored Florida Lakes................................................. 1-22 

Table 1-4. TP and TN Criteria Ranges for Clear (< 40 PCU) and Colored Florida Lakes 

(> 40 PCU)........................................................................................................................... 1-23 

Table 1-5. Summary Statistics (Mean and SD) of Nutrient Variables for Acidic, Alkaline 

Lakes, and Colored Lakes, Meeting Annual Criteria .......................................................... 1-23 

Table 1-6. Single Observation Criteria for Nutrient Variables Derived Using Both Mean 

Observed SD and Modeled SD, for Lakes Meeting Respective Criteria............................. 1-24 

Table 2-1. Distributional Statistics of Stream TP and TN by Estuarine Watershed and 

Aggregated by U.S. EPA NWR........................................................................................... 2-39 

Table 2-2. Results of Interval and Equivalence Tests Conducted on Reference Sites with 2 

SCI Results........................................................................................................................... 2-40 

Table 2-3. Average Values for Metrics at an SCI Score Equivalent to BCG Category 2, and 

Average Values for Metrics Near the SCI score of Impairment.......................................... 2-40 

Table 2-4. Distributional Statistics of TN and TP Based on Site Average Values. The 

Instream Protective Criteria are the 75th Percentile Values (in mg/L). Note: The Mean 

and Standard Deviations are in Natural Logarithm Units.................................................... 2-40 

Table 2-5. TP Thresholds for Lakes Used in Vollenweider Model Screening.......................... 2-41 

Table 2-6. Summary of TN Load Estimates to Florida Estuaries, Normalized to Estuary 

Area (g N m2

/y; SE: Standard Error) ................................................................................... 2-41 

Table 2-7. Application of Downstream Protection Methodology to Estimate TN Criteria in 

Stream Reaches that Ensure Protection of Downstream Waters ......................................... 2-42 

Table 2-8. Characteristics of Florida Estuaries and their Watersheds as Delineated by the 

NOAA CAF ......................................................................................................................... 2-43 

Table 2-9. Average TN Loads to Florida Estuaries Normalized to 2002 .................................. 2-44 

Table 2-10. Information on Downstream River Gage Stations in Florida Estuarine 

Watersheds........................................................................................................................... 2-45 

Table 2-11. Selected Results for Florida Estuaries from NEEA (Bricker et al. 2007).............. 2-47 

Table 2-12. Summary of Nutrient-related Listings for Estuarine Waters on Florida’s 1998 

303(d) List of Impaired Waters............................................................................................ 2-48 

Table 2-13. Seasonal 90th Percentile (P90) and Geometric Mean Surface (depth < 1.5 m) 

Chl. a in Florida Estuaries ................................................................................................... 2-49 
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Table 2-14. FDEP TMDLs, Marine WBIDs Considered, and the Date Completed or 

Drafted ................................................................................................................................. 2-50 

Table 2-15. TMDL Thresholds, Chl. a, BOD, Nutrient Loads and Percent Reduction ............ 2-51 

Table 2-16. Regional TP and TN Criteria for Florida Streams.................................................. 2-52 

Table 2-17. Parameters Monitored During the Benchmark Stream Survey .............................. 2-53 

Table 2-18. Summary of Information Collected from Field-verified Nutrient Benchmark 

Sites...................................................................................................................................... 2-54 

Table 2-19. Summary of the Regional Data Outlier Analysis and Exclusions for the Florida 

Stream Nutrient Benchmark Data Set.................................................................................. 2-55 

Table 4-1. Distributional Statistics Computed from the Natural Logarithm Transformed 

Data at Sites Located in WBIDs not Listed as Nutrient Impaired....................................... 4-10 

Table 4-2. Distributional Statistics Computed from the Natural Logarithm Transformed 

Data Using All Data............................................................................................................. 4-11 

Table 4-3. Quantile Regression Results for Matched Annual Geometric Mean Chlorophyll 

and Nutrient Data................................................................................................................. 4-12 

Table 4-4. Results of “Not to Exceed” Criteria Computations.................................................. 4-12 

Figures 

Figure 1-1. Relationship between Ln transformed chl. a and TP in clear lakes by nutrient 

region. Note, over the entire range of data, that the lakes exhibit a similar chlorophyll 

response to TP independent of region.................................................................................. 1-24 

Figure 1-2. Relationship between Ln transformed chl. a and TN in clear lakes by nutrient 

region. Note, over the entire range of data, that the lakes exhibit a similar chlorophyll 

response to TN independent of region................................................................................. 1-25 

Figure 1-3. Box plots of chl. a by season in clear (left panel) and colored (right panel) 

lakes. .................................................................................................................................... 1-25 

Figure 1-4. Regression analyses of annual geometric mean chl. a concentration and 

nutrients in colored and clear lakes, showing grouping of the two lake classes and the 

different regression lines...................................................................................................... 1-26 

Figure 1-5. Scatter plot of annual geometric mean chl. a concentration and nutrients of 

clear lakes, showing acidic (< 50 mg/L CaCO3) and alkaline lakes. Acidic and alkaline 

groups were combined in a single regression. ..................................................................... 1-27 

Figure 1-6. The relationship between chl. a concentrations (note the log scale) and the 

percent cyanobacteria in 1,364 lake samples collected for Florida’s statewide 

probabilistic monitoring program. ....................................................................................... 1-28 

Figure 1-7. Relationship between the residual error in the TP and TN chlorophyll model 

and (A) period of record geometric mean lake color and (B) annual geometric mean 

lake color. Note that both relationships exhibit a significant negative slope....................... 1-28 
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Figure 1-8. CART analysis, using a least-squares fitting method, of the residual error from 

the TP and TN model for chl. a response in colored Florida lakes. The analysis 

demonstrates that colored lakes can be split into two large groups, using the first CART 

split, where the chl. a response to TP and TN differs because of the confounding effect 

of color. *Proportion reduction in error............................................................................... 1-29 

Figure 1-9. Relationship between Ln transformed chl. a and TP in moderately colored lakes 

by nutrient region. Note, over the entire range of data, that the lakes exhibit a similar 

chlorophyll response to TP independent of region. ............................................................. 1-30 

Figure 1-10. Relationship between Ln transformed chl. a and TN in moderately colored 

lakes by nutrient region. Note, over the entire range of data, that the lakes exhibit a 

similar chlorophyll response to TN independent of region. ................................................ 1-31 

Figure 1-11. Regression analyses annual geometric mean chl. a concentrations and annual 

geometric mean (A) TP and (B) TN concentrations in moderately colored (> 40–140 

PCU) Florida lakes. Note that the x axis and y axis are both expressed on a log-scale. ..... 1-32 

Figure 1-12. Regression analyses annual geometric mean chl. a concentrations and annual 

geometric mean (A) TP and (B) TN concentrations in highly colored (> 140 PCU) 

Florida lakes. Note that the x axis and y axis are both expressed on a log-scale. ............... 1-33 

Figure 1-13. Regression analyses annual geometric mean chl. a concentrations and annual 

geometric mean (A) TP and (B) TN concentrations in clear Florida lakes. Note that x 

axis and y axis are both expressed on a log-scale................................................................ 1-34 

Figure 1-14. Variance in Lake Okeechobee color data from eight pelagic stations, averaged 

over varying time periods. ................................................................................................... 1-35 

Figure 1-15. Distribution of average log alkalinity in clear Florida lakes (log scale). 

Alkalinities of 20 and 50 mg/L shown by arrows................................................................ 1-35 

Figure 1-16. Scatterplots of mean TP, TN, Chl. a, and specific conductance on lake 

alkalinity. Vertical solid lines are the estimated change points, and vertical dashed lines 

denote the 95% confidence intervals for the change points. Wavy dashed lines are 

LOESS nonlinear regressions and confidence intervals. ..................................................... 1-36 

Figure 1-17. Scatter plot of annual geometric mean chl. a concentration and nutrients of 

clear lakes, showing separation of acidic and alkaline lakes with classification 

breakpoint at 20 mg/L CaCO3. Compare to Figure 1-5. Acidic and alkaline groups were 

combined in a single regression. a: TN; b: TP..................................................................... 1-37 

Figure 1-18. Relationship between specific conductance and alkalinity in clear lakes. 

(a) The curve shows loess fitted line, and the vertical lines show change point and its 

90% confidence limits; (b) The curve shows median quantile fit, and the red dot is the 

intercept of the quantile regression line with specific conductance = 200 μS/cm............... 1-38 

Figure 1-19. Cumulative frequency distribution of mean TP concentrations in acidic and 

alkaline lakes that meet the annual average criteria. A specific conductance > or < 250 

μS/cm is applied as a threshold for classifying high- or acidic lakes.................................. 1-38 

Figure 1-20. Density distribution function of normal distribution for acidic (left) and 

alkaline lakes (right) ............................................................................................................ 1-39 
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Figure 2-1. Level IV subecoregions for Florida’s small/wadeable streams. ............................. 2-56 

Figure 2-2. Stream bioregions of Florida................................................................................... 2-57 

Figure 2-3. Location of the Peace River and Bone Valley Member geologic formations......... 2-58 

Figure 2-4. Box plots of stream TN, TP, and TN:TP molar ratio in Florida watersheds. ......... 2-59 

Figure 2-5. NWRs in Florida. .................................................................................................... 2-60 

Figure 2-6. Typical macroinvertebrate response to organic loading associated with primary 

wastewater treatment typical in the 1950s and 1960s.......................................................... 2-61 

Figure 2-7. Photo of Hester-Dendy samplers used for determining the Shannon-Weaver 

diversity index...................................................................................................................... 2-61 

Figure 2-8. Factors affecting biological community composition. To conclude that human 

factors are primarily responsible for biological degradation, reasonable knowledge of 

the influence of natural factors is essential.......................................................................... 2-62 

Figure 2-9. Sub-ecoregions of Florida, which were aggregated into three bioregions, based 

on multivariate measures of taxonomic similarity............................................................... 2-62 

Figure 2-10. The BCG model (from Davies and Jackson 2006). .............................................. 2-63 

Figure 2-11. Regression line with 90% confidence interval showing the relationship 

between the mean BCG score and SCI score....................................................................... 2-63 

Figure 2-12. BCG tier assignments modeled with a proportional odds logistic regression. ..... 2-64 

Figure 2-13. Plot of TP concentration of grab samples taken at all sites sampled for 

biological condition (SCI sites). Concentrations are in milligrams per liter. ...................... 2-65 

Figure 2-14. Plot of TP concentration of grab samples taken from sites sampled for 

biological condition (SCI sites) that met the SCI threshold of 40. Map symbols and 

units as in Figure 2-13. Also shown are histograms of TP concentrations and 

cumulative (hatched line) and empirical (solid line) percent frequencies of TP 

concentrations in biologically healthy sites by nutrient region. .......................................... 2-66 

Figure 2-15. Plot of TN concentration of grab samples taken at all sites sampled for 

biological condition (SCI sites). Concentrations are in milligrams per liter. ...................... 2-67 

Figure 2-16. Plot of TN concentration of grab samples taken from sites sampled for 

biological condition (SCI sites) that met the SCI threshold of 40. Map symbols as in 

Figure 2-15. Also shown are histograms of TN concentrations and cumulative (hatched 

line) and empirical (solid line) percent frequencies of TN concentration in biologically 

healthy sites by nutrient region............................................................................................ 2-68 

Figure 2-17. Critical stream TP concentration for inflows into clear, low-conductivity lakes 

to meet lake criterion of 0.010 mg/L TP. Area below the curve results in lake TP below 

the lake criterion. Streamflow is 100% of inflow into lake. Dashed line: Panhandle 75th 

percentile proposed instream protective value. For residence times less than 11 years, 

stream TP concentration of 0.042 mg/L will result in lake TP > 0.010 mg/L (shaded 

area)...................................................................................................................................... 2-69 
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Figure 2-18. Critical stream TP concentrations for stream inflows into clear, lowconductivity lakes. Blue (lower curve): streamflow is 100% of lake water input; this is 

the same curve shown in Figure 2-17. Red (middle curve): streamflow is 50% of lake 

water input. Green (upper curve): streamflow is 10% of lake water input. Horizontal 

dashed lines: 75th percentile proposed instream protective values for TP regions. ............. 2-69 

Figure 2-19. Critical stream TP concentrations for stream inflows into clear, highconductivity lakes. Blue (lower curve): streamflow is 100% of lake water input. Red 

(middle curve): streamflow is 50% of lake water input. Green (upper curve): streamflow 

is 10% of lake water input. Horizontal dashed lines: 75th percentile proposed instream 

protective values for TP regions. .......................................................................................... 2-70 

Figure 2-20. Critical stream TP concentrations for stream inflows into colored lakes. Blue 

(lower curve): streamflow is 100% of lake water input. Red (middle curve): streamflow 

is 50% of lake water input. Green (upper curve): streamflow is 10% of lake water input. 

Horizontal dashed lines: 75th percentile proposed instream protective values for TP 

regions.................................................................................................................................. 2-70 

Figure 2-21. Summary of TN load estimates from watersheds to estuaries in Florida (kg/y). 

Current TN load and the background TN load were derived from the USGS regional 

SPARROW model for the SAGT basins. Protective loads were computed by reducing 

the anthropogenic contribution of the current load by 50%. ............................................... 2-71 

Figure 2-22. Map showing the spatial distribution of the fraction of TN delivered to 

estuarine waters in watersheds of Florida’s estuaries. The map is based on a spatial join 

of incremental watersheds within the ERF1 stream network and Florida’s waterbodies 

(WBIDs)............................................................................................................................... 2-72 

Figure 2-23. Map showing Florida estuaries and their watersheds as delineated by the 

NOAA CAF. ........................................................................................................................ 2-73 

Figure 2-24. Land use characteristics of Florida estuarine watersheds as reported by NEEA 

(Bricker et al. 2007). ............................................................................................................ 2-74 

Figure 2-25. Fraction of delivered anthropogenic TN load (i.e., TN loading delivered to 

estuaries attributed to point sources, fertilizer, manure, and urban land use) resulting 

from each of those sources. Point source loads include those discharging directly to 

estuaries. Data are from the SAGT regional SPARROW model (Hoos and McMahon 

2009) and McMahon et al. (2007). ...................................................................................... 2-74 

Figure 2-26. Time series of atmospheric wet deposition of nitrogen at three NADP 

monitoring sites in Florida................................................................................................... 2-75 

Figure 2-27. TN yield (i.e., per km2

 of watershed area) from atmospheric sources (left axis) 

and the fraction of loads from all sources contributing to watershed loading contributed 

by atmospheric deposition (right axis). All data were derived from the SAGT regional 

SPARROW watershed model (Hoos and McMahon 2009). ............................................... 2-75 

Figure 2-28. Area of estuarine watershed area (%) accounted for and that unaccounted for 

by river gage stations in Florida estuarine watershed.......................................................... 2-76 
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Figure 2-29. LDI results for 5570 stations by sub-ecoregion for initial candidate reference 

site evaluation. Sites scoring above 2 on the LDI were eliminated from further 

consideration (except for a single site in the Bone Valley Region that, due to the 

sparseness of reference sites, was accepted at an LDI of 2.2). ............................................ 2-76 

Figure 2-30. Relationship between nutrient loading (nitrogen in panel (a), phosphorus in 

panel (b)) and the LDI in the St. Marks watershed, Florida (after Brown and Vivas 

2003). The arrow is the LDI value at 2.0, the benchmark site threshold............................. 2-77 

Figure 2-31. Depiction of land use area (light yellow) included in an LDI calculation............ 2-78 

Figure 2-32. Relationship between the LDI and Stream Condition Index across the entire 

range of LDI......................................................................................................................... 2-78 

Figure 2-33. Benchmark site LDI vs. Average SCI score. In contrast to Figure 2-32, note 

the lack of correlation between SCI and LDI values of minimally disturbed sites (LDI 

≤ 2, with one exception where LDI was 2.2)....................................................................... 2-79 

Figure 2-34. Benchmark site SCI vs. TN. Note the lack of correlation between SCI and TN 

throughout the range of benchmark sites. This indicates that there are no adverse effects 

from establishing nutrient criteria at the upper 90th percentile of the benchmark 

distribution. Sites scoring less than 40 on the SCI (after QA review) were excluded 

from the benchmark data set for calculation of the final nutrient distribution. ................... 2-79 

Figure 2-35. Benchmark site SCI vs. TP. Note the lack of correlation between SCI and TP 

throughout the range of benchmark sites. This indicates that there are no adverse effects 

from establishing nutrient criteria at the upper 90th percentile of the benchmark 

distribution. Sites scoring less than 40 on the SCI (after QA review) were excluded 

from the benchmark data set for calculation of the final nutrient distribution. ................... 2-80 

Figure 3-1. Changes in NO3 concentration in Weeki Wachee Spring discharge and 

population of Hernando County, Florida. Note that NO3 concentrations follow a pattern 

very similar to the population curve with a 10- to 15-year lag............................................ 3-13 

Figure 3-2. Increased NO3 concentrations in discharges from 13 selected first-magnitude 

springs (Alexander, Chassahowitzka Main, Fanning, Ichetucknee Main, Jackson Blue, 

Madison Blue, Manatee, Rainbow Group composite, Silver Main, Silver Glen, Volusia 

Blue, Wakulla, and Wacissa #2 Springs) between the 1970s and the early 2000s. 

Source: Scott et al. 2004. ..................................................................................................... 3-13 

Figure 3-3. Relationship between mean nitrate/nitrite (NOx) concentration and mean 

periphyton cell density from sampling sites on the Suwannee, Santa Fe, and 

Withlacoochee rivers. Source: Mattson et al. 2006. ............................................................ 3-14 

Figure 3-4. Relationship between mean nitrate/nitrite (NOx) concentration and mean 

periphyton biomass from sampling sites on the Suwannee, Santa Fe, and 

Withlacoochee Rivers. Source: Mattson et al. 2006............................................................ 3-14 

Figure 3-5. Change point analysis for data from the 13 stations at the Suwannee River 

System (mean cell density vs. mean NOx). Change point = 0.44 mg/L. The 95% 

confidence interval for the change point based on 1000 bootstrapping samples is 0.378 

to 0.629. ............................................................................................................................... 3-15 
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Figure 3-6. Change point analysis for data from the 13 stations At the Suwannee River 

System (mean biomass vs. mean NOx). Change point = 0.44. The 95% confidence 

interval for the change point based on 1000 bootstrapping samples is 0.441 to 0.584 

μg/L...................................................................................................................................... 3-15 

Figure 3-7. Relationship between mean nitrate plus nitrite concentration and mean 

periphyton abundance for sampling sites on the Suwannee, Santa Fe, and 

Withlacoochee rivers. Values with NO3 concentrations above and below 0.35 mg/L are 

shown in different colors. Red dotted lines are at 0.23 mg/L and 0.44 mg/L, 

representing results from lab and field................................................................................. 3-16 

Figure 3-8. Relationship between mean nitrate plus nitrite and mean periphyton biomass 

for sampling sites on the Suwannee, Santa Fe, and Withlacoochee Rivers. Values with 

nitrate concentrations above and below 0.35 mg N/L are shown in different colors. Red 

dotted lines are at 0.23 mg N/L and 0.44 mg N/L, representing results from lab and 

field studies, respectively..................................................................................................... 3-16 

Figure 3-9. The mean cell density of Van Dam eutrophic indicator diatoms increases with 

increasing nitrate plus nitrite concentrations. The red dotted lines are at 0.23 mg/L and 

0.44 mg/L, representing results from lab and field studies, respectively. ........................... 3-17 

Figure 3-10. An example of the full-range confidence interval procedure to develop a 

nitrate plus nitrite criterion. The full confidence interval procedure resulted in a 

protective threshold of 0.33 mg/L. The upper half of confidence interval method 

yielded a protective threshold of 0.38 mg/L. The average of these complementary 

methods resulted in the final protective threshold of 0.35 mg/L. ........................................ 3-17 

Figure 4-1a. Location of EAA and EvPA.................................................................................. 4-12 

Figure 4-1b. STATSGO soil orders for southern Florida.......................................................... 4-12 

Figure 4-2. Site locations (n=513) with canal water quality data evaluated in this document.. 4-13 

Figure 4-3. Site locations (n=72) with chlorophyll data evaluated in this document................ 4-14 

Figure 4-4. Site locations (n=72) with chlorophyll data evaluated in this document together 

with Florida WBIDs that FDEP has identified as nutrient-impaired................................... 4-15 

Figure 4-5. Sites located within WBIDs not listed as nutrient-impaired................................... 4-16 

Figure 4-6. a) Bivariate plot of annual geometric mean chlorophyll as a function of TP by 

canal region, b) bivariate plot with fitted linear regression and 90% prediction interval, 

c) regression analysis statistics, and d) residual plots from regression analysis.................. 4-17 

Figure 4-7. a) Bivariate plot of annual geometric mean chlorophyll as a function of TP by 

canal region excluding the EvPA, b) bivariate plot with fitted linear regression and 90% 

prediction interval, c) regression analysis statistics, and d) residual plots from

regression analysis. .............................................................................................................. 4-18 

Figure 4-8. Bivariate plot of annual geometric mean chlorophyll as a function of TP with 

fitted linear regression and 90% prediction interval for a) EAA (not statistically 

significant), b) EvPA, c) West Coast, and d) East Coast. (Residual plots for the EvPA, 

West Coast, and East Coast were visually examined and found to have constant 

variance, independence, and normal distribution.) .............................................................. 4-19 
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Figure 4-9. EvPA regression analysis statistics for annual geometric mean chlorophyll as a 

function of TP and residual plots......................................................................................... 4-20 

Figure 4-10. West Coast regression analysis statistics for annual geometric mean 

chlorophyll as a function of TP and residual plots. ............................................................. 4-20 

Figure 4-11. East Coast regression analysis statistics for annual geometric mean 

chlorophyll as a function of TP and residual plots. ............................................................. 4-21 

Figure 4-12. a) Bivariate plot of annual geometric mean chlorophyll as a function of TN by 

canal region, b) bivariate plot with fitted linear regression and 90% prediction interval, 

c) regression analysis statistics, and d) residual plots from regression analysis.................. 4-22 

Figure 4-13. Bivariate plot of annual geometric mean chlorophyll as a function of TN with 

fitted linear regression and 90% prediction interval for a) EAA (not statistically 

significant), b) EvPA (not statistically significant), c) West Coast, and d) East Coast. 

(Residual plots for the West and East Coasts were visually examined and found to have 

independence and normal distribution. The variance associated with the West Coast 

residuals did show a tendency to increase as a function of TN.)......................................... 4-23 

Figure 4-14. West Coast regression analysis statistics for annual geometric mean 

chlorophyll as a function of TN and residual plots.............................................................. 4-24 

Figure 4-15. East Coast regression analysis statistics for annual geometric mean 

chlorophyll as a function of TN and residual plots.............................................................. 4-24 

Figure 4-16. Bivariate plot of annual geometric mean chlorophyll as a function of TN and 

TP across all regions together with Spearman’s rho correlation coefficient, LOESS 

smoother (black line, f=0.7), and quantile regression results (blue line and blue text)....... 4-25 

Figure 4-17. Bivariate plot of annual geometric mean chlorophyll as a function of TP for 

the EvPA together with Spearman’s rho correlation coefficient, LOESS smoother 

(black line, f=0.7), and quantile regression results (blue line and blue text)....................... 4-26 

Figure 4-18. Bivariate plot of annual geometric mean chlorophyll as a function of TN and 

TP for the West Coast together with Spearman’s rho correlation coefficient, LOESS 

smoother (black line, f=0.7), and quantile regression results (blue line and blue text)....... 4-27 

Figure 4-19. Bivariate plot of annual geometric mean chlorophyll as a function of TN and 

TP for the East Coast together with Spearman’s rho correlation coefficient, LOESS 

smoother (black line, f=0.7), and quantile regression results (blue line and blue text)....... 4-28