## Final Nutrient Total Maximum Daily Load

For Newnans Lake,
Alachua County, Florida

Xueqing Gao and Douglas Gilbert

Watershed Assess ment Section
Florida Department of Environmental Protection

2600 Blair Stone Road, MS 3555

Tallahassee, FL 32399-2400

September 22, 2003i 

## Table of Contents

Table of Contents...................................................................................... i List of Figures............................................................................................ ii List of Tables............................................................................................. iii Acknowledgements................................................................................... iv 1. Introduction................................................................................ 1 1.1 Purpose of report............................................................................ 1 1.2 Identification of water body........................................................... 1 2. Description of Standards..................................................................... 4 3. Statement of Problem............................................................................ 4 4. Assessment of Sources......................................................................... 5 4.1 Types of Sources............................................................................ 5 4.2 Estimating Watershed Loadings of TN and TP using WMM......... 5 Strategy to determine loadings a nd assimilative capacity.............. 5 Breakdown of sub-basins and Landuses....................................... 6 Potential Sources of TN and TP..................................................... 8 Estimating Watershed TN and TP

.................. ............ ................. 8 4.3 Lake Modeling using Bathtub Model.............................................. 10 Bathtub Model................................................................................. 10 Steady State Assumption for Lake.................................................. 11 Bathtub Data Requirements .......................................................... 11 Calculation of Trophic State Index.................................................. 12 Error and Variability Analysis.......................................................... 12 4.4 TMDL Scenario Development........................................................ 13 Available Data and Data Use ........................................................ 13 5. Results.................................................................................................. 13 5.1 Data Analysis................................................................................ 13 Historical trend of trophic status of Newnans Lake........................ 14 TN and TP Inlet and Outlet Concentrations................................... 21 5.2 Estimating TN and TP sub-basin loadings Using WMM............... 23 Preparing rainfall data for WMM wate r quantity calibration........... 36 WMM Flow Calibration.................................................................. 39 WMM calibration and Simulation of Watershed Loadings............. 41 Atmospheric Loading to the Lak e.............

.................. ................... 56 5.3 Establishing Relationship between TN and TP loading to the Lake and In-Lake Concentrations............................................ 56 Calibrating Bathtub Model............................................................. 59 TSI from Model Predictions vs. TSI from Measured Data............. 61 Natural Background...................................................................... 63 6. Newnans Lake TMDL........................................................................... 64 6.1 Load Allocation................................................................................ 65 6.2 Wasteload Allocation...................................................................... 66 6.3 Margin of Safety............................................................................ 66 7. Evaluation of Un-ionized Ammonia..................................................... 67 8. Next Steps:............................................................................................ 67 9. Recommendations................................................................................. 68 References............................................................................................... 69 Appendix A................................................................................................ 71ii 

### List of Figures
Figure 1 General Location of Wa tershed.................................................. 3 Figure 2 Newnans Lake Sub-basi ns......................................................... 7 Figure 3 Bathtub Conceptual Scheme...................................................... 10 Figure 4 Location of Data Stations........................................................... 15 Figure 5-A Lake TN Concentration vs. Volume........................................ 19 Figure 5-B Lake TP Concentration vs. Volume........................................ 19 Figure 5-C Lake Chla Concentration vs. Volume..................................... 20 Figure 5-D Lake TSI vs. Volume.............................................................. 20 Figure 6 USGS Gauging Stations and sub-basin delineation’s................ 24 Figure 7 Location of Weather Station....................................................... 26 Figure 8 Distribution of Landuses in Sub-basins...................................... 30 Figure 9 Location of Groundwater Well.................................................... 34 Figure 10 Location of Point Source.......................................................... 36 Figure 11 Correlation between runo ff and precipitation........................... 38 Figure 12 Correlation between Basefl ow and Precipitation..................... 39 Figure 13-A Sub-basin TN Loadings....................................................... 44 Figure 13-B Sub-basin TP loadings........................................................ 44 Figure 14 1997 TN Percent Contribution by Sub-basin and Landuse.... 50 Figure 15 2000 TN Percent Contribution by Sub-basin and Landuse.... 51 Figure 16 1997 TP Percent Contribution by Sub-basin and Landuse.... 52 Figure 17 2000 TP Percent Contribution by Sub-basin and Landus 

### e.... 53iii 

### List of Tables

Table 1 Lake Basin Landuse and acreage................................................ 8 Table 2 Data Types and Period of Record................................................ 13 Table 3 Annual Average Lake TN, TP, Chla, and TSI............................... 16 Table 4 Seasonal Variat ion of Lake TN, TP, Chla, and TSI...................... 16 Table 5 Lake Annual Average Stage and Volume..................................... 17 Table 6 Lake Quarterly Average Stage and Volume................................. 18 Table 7 Lake Inlet and Outlet Annual Average TN Concentrations........... 21 Table 8 Lake Inlet and Outlet Annual Average TP Concentrations........... 21 Table 9 Annual Precipitation..................................................................... 27 Table 10 Quarterly Precipitation............................................................... 27 Table 11 Sub-catchment Stream flow and Baseflow ............................... 28 Table 12 Sub-catchment Landuse s and area........................................... 28 Table 13 Sub-basin Landuses and area................................................... 29 Table 14 Percent Directly Connected Impervious Area by Landuse ........ 31 Table 15 TN and TP Landuse based Event Mean Concentration............. 32 Table 16 Percent suspended TN and TP by Landuse and Sub-basin...... 33 Table 17 Point Source Daily dischar ge, TN and TP Concentration.......... 35 Table 18 Adjusted Effective Rainfall......................................................... 38 Table 19 WMM Water Quantity Calibration.............................................. 40 Table 20 Annual Flow from Sub-basins.................................................... 40 Table 21 WMM Water Quality Calibration................................................ 41 Table 22 TN and TP Sub-basin Loadings................................................ 42 Table 23 1996 Sub-basin TN Load ings by Landuse................................ 45 Table 23 1997 Sub-basin TN Load ings by Landuse................................ 45 Table 23 1998 Sub-basin TN Load ings by Landuse................................ 46 Table 23 1999 Sub-basin TN Load ings by Landuse................................ 46 Table 23 2000 Sub-basin TN Load ings by Landuse................................ 47 Table 24 1996 Sub-basin TP Load ings by Landuse................................ 47 Table 24 1997 Sub-basin TP Load ings by Landuse................................ 48 Table 24 1998 Sub-basin TP Load ings by Landuse................................ 48 Table 24 1999 Sub-basin TP Load ings by Landuse................................ 49 Table 24 2000 Sub-basin TP Load ings by Landuse................................ 49 Table 25 1996-2000 Perc ent TN and TP by Sub-basin........................... 54 Table 26 Atmospheric Loading to the Lake............................................. 56 Table 27 Comparison of TN and TP Concentration of sources to In-Lake and Lake outflow Concentrations................................................ 57 Table 28 Physical Characteristics of Newnans Lake by Year.................. 57 Table 29 Precipitation and Evaporation by Year...................................... 58 Table 30 Measured TN, TP, Chla Conc entrations of Lake by Year......... 58 Table 31 Flow, TN, and TP Concentrations by Landuse.......................... 59 Table 32 Bathtub Calibration Resu lts ....................................................... 61 Table 33 Long-Term TSI Measured vs. Predicted.................................... 61 Table 34 TN, TP, Chla, and TSI after e liminating internal recycling......... 62 Table 35 Flow, TN and TP of surface runoff natural background............. 63 Table 36 Natural Background TN, TP , Chla, and TSI............................... 63 Table 37 TMDL Components.................................................................... 65 Table 38 Source Evaluation Critic al Conditions........................................ 68iv 

## Acknowledgments

This study could not have been accomplished without the significant contributions from other staff within the Watershed Assessment Section. Particular appreciation to Barbara Donner for her contributions. All of the basin delineation’s, landuse aggregations, and much of the data gathering are a result of her efforts. Additional appreciation to Dr. TS Wu for his assistance and insights on modeling and to Dr. Paul Lee for his assistance in understanding the groundwater system. The Department also recognizes the substantial support and assistance provided by the St. Johns River Water Management District staff, particularly their contributions towards understanding the issues, history, and processes at work in the Newnans Lake watershed.1 

### 1. Introduction

1.1 Purpose of Report
This report represents the efforts to develop a nutrient TMDL for Newnans Lake (Lake) and to assess the impact of proposed total nitrogen reductions on the concentration of unionized ammonia in the Lake. The Lake, located in Central Florida near Gainesville (Figure 1), was verified as impaired by nutrients based on elevated levels of the Trophic State Index for lakes, and was included on the verified list of impaired waters for the Ocklawaha Basin that was adopted by Secretarial Order on August 28, 2002.
According to Section 303(d) of the federal Clean Water Act (CWA) and the Florida Watershed Restoration Act, Chapter 403, Florida Statut es, the Florida Department of Environmental Protection (DEP) is required to submit to EPA on a recurring basis lists of surface waters that do not meet applicable water quality standards (impaired waters). The methodologies used by the state for the determination of impairment are established in Rule 62-303, Identification of Impaired Surface Waters (IWR), Florid a Administrative Code (FAC).
Once a water body or water body segment has been verified as impaired and referenced in the Secretarial Order Adopting the Verified List of Impaired Waters, work on establishment of the Total Maximum Daily Load (TMDL) begins. The TMDL process establishes the allowable loadings of pollutants or other quantifiable parameters for a waterbody based on the relationship between pollution sources and in-stream water quality conditions, so that states can establish water quality based controls to reduce pollution from both point and nonpoint sources and restore and maintain the quality of their water resources (USEPA, 1991)
1.2 Identification of Water Body
Newnans Lake is located in a topographical region of the state that is known as the Central Lowlands (Clark et al. 1964, Latitude 29 0 38’42”, Longitude 82 0 13’8”, Figure 1). The geology of the area is dominated by the Hawthorn formation, which is relatively impermeable and acts as a confining layer separating surface water from the influence of the Floridian Aquifer. Poorly drained soil, which is dominated by Pomona-Wachula-Newnans series, and low elevation gradients of the area result in moderately high sheetflow and poorly defined channels. Ponds and wetlands occur throughout the area. The major sources of water to the lake include surface runoff, subsurface flow, and direct rainfall (Canfield 1981).
The lake has an average surface area of about 7,200 acres and is a typical shallow basin lake. The maximum depth is not more than 12 feet, and the mean depth is approximately 5 feet (Nordilie, 1979). A large drainage area north of the lake supplies inflow via two major streams: Hatchet Creek and Little Hatchet Creek. The lake has a single major surface-water outlet, Prairie Creek. Once water leaves the lake, it is split into two parts

. Based on long-term USGS flow measurements (1942-1991), about 41% of the flow from Newnans lake goes to the south into Paynes Prairie, and the rest flows towards Orange Lake by way of Camp’s Canal (Gottgens and Montague 1987). In 1966, a weir was constr ucted at the outlet of Newnans Lake by the Alachua County Recreation and Water Conservation and Control Authority (ACRWCCA) to increase the water level. The weir was altered in 1976 by the Florida Game and Fresh Water Fish Commission (FGFWFC) to include removable boards for lake management purposes.2 Boards were removed from the weir for five months in 1989 to increase lake level fluctuations and were totally removed in 1991 to increase lake level fluctuation.
For assessment purposes, the State of Florida has been divided into water body assessment polygons termed Water Body Ids or WBIDs. Additional information about the derivation and use of these WBIDs is provided in the “Document ation For The 2002 Update To The State Of Florida’s 303(d) List” dated October 1, 2002, and GIS shapefiles of the WBIDs can be obtained from the following website:

http://www.floridadep.org/water/watersheds/basin411/downloads.htm3 Figure 1. The general location and landuse types of Newnans Lake watershed.4 

### 2. Description of Applicable Water Quality Standards and Criteria
Newnans Lake is classified as a Class III Freshwater body, with a designated use of recreation, propagation and maintenance of a healthy, well-balanced population of fish and wildlife. The Class III water quality criteria applicable to the observed impairment is the narrative nutrient criterion (nutrient concentrations of a body of water shall not be altered so as to cause an imbalance in natural populations of aquatic flora or fauna). Because the nutrient criterion is narrative only, a nutrient related target was ne eded to represent levels at which imbalance in flora or fauna are expected to occur. For this TMDL, the IWR threshold for impairment for lakes, which is based on a trophic state index (TSI), was used as the water quality target.
The TSI originally developed by R. E. Carlson (1977) was calculated based on Secchi depth, chlorophyll concentration, and total phosphorus concentration and was used to describe a lake’s trophic state. Carlson’s TSI was developed based on the assumption that the lakes were all phosphorus limited. In Florida, because the local geology produced a phosphorus rich soil, nitrogen can be the sole or co-limiting factor for phytoplankton population in some lakes. In addition, because of the existence of dark-water lakes in the state, using Secchi depth as an index to represent lake trophic state can produce misleading results. Therefore, the TSI was revised to be based on chlorophyll a , total nitrogen, and total phosphorus concentrations.
The Florida-specific TSI was determined based on t he analysis of data from 313 Florida lakes. The index was adjusted so that a chlorophyll a concentration of 20 ug/L was equal to a TSI value of 60. A TSI of 60 was then set as the th reshold for nutrient impairment for most lakes (for those with a color higher than 40 platinum cobalt units) because, generally, the phytoplankton may switch to communities dominated by blue-green algae at chlorophyll a levels above 20 ug/L. These blue-green algae are often an unfavorable food source to zooplankton and many other aquatic animals. Some blue-green algae may even produce toxins, which could be harmful to fish and other animals. In addition, excessive growth of phytoplankton and the subsequent death of these algae may consume large quantity of dissolve oxygen and result in anaerobic condition in lakes, which makes conditions in the impacted lake unfavorable for fish and other wildlife. All of these processes ma y negatively impact the health and balance of native fauna and flora.
Because of the amazing diversity and productivity of Florida lakes, some lakes have a natural background TSI that is different from 60. In reco gnition of this natural variation, the IWR allows for the use of a lower TSI (40) in very clear lakes, a higher TSI if paleolimnological data indicate the lake was naturally above 60, and the development of site-specific thresholds that better represent the levels at which nutrient impairment occurs. For this study, the Florida Department of Environmental Protection (DEP) used modeli ng to estimate the natur al background TSI by setting land uses to natural or forested land, and then compared the TSI to the IWR thresholds. If the natural background TSI is higher than 60, then the natural background TSI will be used as the water quality target for the TMDL because it is unreasonable to abate the natural background condition. If the natural background TSI is lower than 60, then the IWR threshold (a TSI of 60) will be established as the target for TMDL development (since Newnans Lake has a mean color greater than 40 platinum cobalt units, the IWR threshold for impairment is 60).



### 3. STATEMENT OF PROBLEM
Analyses of pollen and diatoms in several sediment cores from the lake indicate that the lake was formed between 5000 and 8000 years ago and that it has been eutrophic throughout its5 history (Holly 1976). However, water quality data from the last 15 years indicates that the lake has experienced accelerated eutrophication and elevated TSIs (SJRWMD 2002) (Table 3). Based on data in the DEP database (IWR-data), the long-term (1989 – 2000) average concentrations of total phosphorus (TP), total nitrogen (TN), and chlorophyll a (Chla) were 0.120 mg/L, 3.323 mg/L, and 173.4 μg/L, respectively. The TP, TN, and Chla concentrations were even higher for the verified period for the IWR assessment (1995 –2000), with mean values of 0.151 mg/L, 4.340 mg/L, and 249 ug/L, respectively. The mean color of the lake was calculated as 69 platinum-cobalt units. The average TSI for the verified period is 89.3, well above the IWR annual average TSI threshold for nutrient impairment for lakes.



### 4.0 Assessment of Sources
4.1 Types of Sources
An important part of the TMDL analysis is the identification of source categories, source subcategories, or individual sources of nutrients in the Newnans Lake watershed and the amount of pollutant loading contributed by each of these sources. Sources are broadly classified as either “point sources” or “nonpoint sources.” Historically, the term point sources has meant discharges to surface waters that typically have a continuous flow via a discernable, confined, and discrete conveyance, such as a pipe. Domestic and industrial wastewater treatment facilities (WWTFs) are examples of tradi tional point sources. In contrast, the term “nonpoint sources” was used to describe intermittent, rainfall driven, diffuse sources of pollution associated with everyday human activities, incl uding runoff from urban land uses, runoff from agriculture, runoff from silviculture, runoff from mining, discharges from failing septic systems, and atmospheric deposition.
However, the 1987 amendments to the Clean Water Act redefined certain nonpoint sources of pollution as point sources subject to regulation under EPA’s National Pollutant Discharge Elimination Program (NPDES). These nonpoint sources included certain urban stormwater discharges, including those from local government master drainage systems, construction sites over five acres, and from a wide variety of industries (see Appendix A for background information about the State and Federal Stormwater Programs).
For the purposes of allocating pollutant load reductions (see Section 6) required by a TMDL, the term “point source” will be used to describe traditional point sources (such as domestic and industrial wastewater discharges) AND stormwater systems requiring an NPDES stormwater permit. However, the methodologies used to estimate nonpoint source loads do not distinguish between NPDES stormwater discharges and non-NPDES stormwater discharges, and as such, this section does not make any distinctions between the two.
4.2 Estimating TN and TP loadings using WMM
Overall Strategy to Determine Loadings and Assimilative Capacity
The goal of the nutrient TMDL development for Newnans Lake is to identify the maximum allowable TP and TN loadings to the lake so that the lake will meet the water quality standard and maintain its function and designated use as a Class III water. Specifically, the goal is interpreted in this study as a TSI of 60 or the natural background TSI if the natural background is higher than 60. While TMDL development is a very complex process, the process used for this TMDL can be divided into three main steps:6 1. TN and TP loadings from various point and nonpoint sources in the Newnans Lake watershed were estimated using the Watershed Management Model (WMM). 2. Loading estimates from the WMM were entered into the Bathtub eutrophication model to establish the relationship between TN and TP loadings and in-lake TN, TP, and Chla concentrations. The model results for in-lake TN, TP, and Chla were used to calculate TSI-predicted (TSI-P) for several different loading scenarios discussed later. 3. The loadings to the lake were adjusted unti l the TSI-P calculated from the model results was less than 60, and the TN and TP loadings that resulted in a TSI below 60 were the nutrient TMDL for Newnans Lake.

Breakdown of Sub-basins and Landuses
The Newnans Lake watershed drains an area of about 74,730 acres. For modeling purposes, the watershed was broken into three sub-basins (Figure 2). These sub-basins are Little Hatchet Creek sub-basin (LHC – the area discharging directly into Little Hatchet Creek), Hatchet Creeksub-basin (HC – the area discharging directly into Hatchet Creek), and Newnans Lake subbasin (NL – the area discharging directly into Newnans Lake).7 Figure 2. Sub-basins of Newnans Lake watershed. LHC, HC, and NL represent Little Hatchet Creek, Hatchet Creek, and Newnans Lake sub-basins, respectively. "  ́

"  ́

"  ́

"  ́

"  ́ H

a t c h e t t C

r e e

k

L i t t l e

H

a t c h e t t C

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### Prairie Creek Newnans Lake HC

LHC

NL

1 0 1 2 Miles N8 Landuse categories in each sub-basin were aggregated using the simplified level 1 codes tabulated in Table 1. The spatial distribution of different landuse types of the Newnans Lake watershed is demonstrated in Figure 1.

Table 1. Classification of landuse categories of Newnans Lake

Code Landuse Urban Open Acreage
1000 Urban Open 2366

Low density resident 3348 Medium density resident 1891 High density resident 205 2000 Agriculture 3444 3000 Rangeland 1935 8000 Transportation, communication, and utilities 1524 4000 Forest/rural open 39134
5000/6000 Water/Wetland 20883

Source assessment: potential sources of TN and TP in Newnans Lake watershed
The TN and TP loadings to Newnans Lake are generated from both nonpoint and point sources.
Nonpoint sources addressed in this study in clude TN and TP loadings from surface runoff, stream baseflow, precipitation directly on the surface of the lake, and the contribution from leaking septic tanks. TN and TP loadings through surface runoff were estimated using the Watershed Management Model (WMM) based on the imperviousness and event mean concentration (EMC) of TN and TP from the different landuse types of the watershed. The spatial distribution and acreage of different landuse categories were identified using the St. Johns River Water Management District (SJRWMD) 1995 landuse coverage (scale 1:40,000) contained in the DEP GIS library. Methods used to estimate the TN and TP loadings from stream baseflow, precipitation directly on the su rface of the lake, and the contribution from leaking septic tanks are described in detail in Section 5.2.
Brittany Estates Mobile Home Park (Permit number: FL0040215) was the only point source discharger identified in the Newnans Lake watershed. The facility was identified using the Permit Compliance System (PCS). The facility discharges into Little Hatchet Creek, which in turn flows into Newnans Lake. Detailed information about the TN and TP loading capacity of this facility is discussed in Section 5.2.
Estimating Watershed TN and TP Loading from Nonpoint Sources9 WMM development was originally funded by DEP under contract to Camp Dresser and McKee (CDM). CDM further refined and developed the model to its present state. WMM is a watershed model designed to estimate annual or seasonal pollutant loadings from a given watershed and evaluate the effect of watershe d management strategies on water quality (WMM User’s Manual: 1998). While the strength of the mo del is its capability to characterize pollutant loadings from nonpoint sources, such as those through stormwater runoff, stream baseflow, and leakage of septic tanks, the model also handles point sources such as discharge from wastewater treatment facilities. Estimation of pollution load reduction due to partial or full-scale implementation of onsite or regional best management practices (BMP) is also part of the functions of this model. The fundamental assump tion of the model is that the stormwater runoff from any given landuse is in direct proportion to annual rainfall and is dictated by the portion of the landuse category that is impervious and the runoff coefficients of both pervious and impervious area. The governing equation is:
(1) R L = [C p + (C I – C p ) IMP L ] * I

Where: R L = total average annual surface runoff from land use L (in/yr); IMP L = fractional imperviousness of land use L; I = long-term average annual precipitation (in/yr); C P = pervious area runoff coefficient; and C I = impervious area runoff coefficient.
The model estimates pollutant loadings based on nonpoint pollution loading factors (expressed as lbs/ac/yr) that vary by land use and the percent imperviousness associated with each land use. The pollution loading factor M L is computed for each land use L by the following equation:
(2) M L = EMC L * R L * K

Where: M L = loading factor for land use L (lbs/ac/yr); EMC L = event mean concentration of runoff from land use L (mg/L); EMC varies by land use and pollutant; R L = total average annual surface runoff from land use L computed from Equation (1) (in/yr); and K = 0.2266, a unit conversion constant.
Data required for WMM application include:

• Area of all the landuse categories and the area served by septic tanks

• Percent impervious area of each landuse category

• EMC for each pollutant type and landuse category

• Percent EMC of each pollutant type that is in suspended form

• Annual precipitation

• Annual baseflow and baseflow concentrations of pollutants

• Point source flows and pollutant concentrations.

Calibration of WMM was conducted on both runoff quantity and quality. This was a two-step procedure since the water quality calibration is a function of the predicted runoff volumes. Calibration of water quantity is usually achieved through adjusting the pervious and impervious area runoff coefficients. Typical ranges of runoff coefficients are 0.05 – 0.30 for pervious area10 (WMM User’s Manual: 1998) and 0.85 – 1.0 for impervious area (Linsley and Franziani, 1979). After the water quantity calibration, water quality was calibrated by adjusting the pollutant delivery ratio – the percent quantity of pollutant in the surface runoff that is eventually delivered to the destination waterbody. In this study, the range of the pollutant delivery ratio was estimated using the method developed by Roehl (1962) that correlates the delivery ratio to watershed area. The calibration results will be presented and discussed in Section 5.
4.3 Lake Modeling Using the Bathtub Model
Bathtub eutrophication model
The Bathtub eutrophication model is a suite of empirically derived steady state models developed by the U. S. Army Corps of Engineering (ACOE) Waterways Experimental Station. The primary function of these models is to estimate nutrient concentrations and algal biomass resulting from different patterns of nutrient loadings. The procedures for selection of the appropriate model for a particular lake are described in the Users Manual. The empirical prediction of lake eutrophication using this approach typically can be described as a two stage procedure using the following two categories of models (Walker 1999):

• Nutrient balance model. This type of model relates in-lake nutrient concentration to external nutrient loadings, morphometry, and hydrology.

• Eutrophication response model. This type of model describes relationships among eutrophication indicators within the lake, including nutrient levels, Chla, transparency, and hypolimnetic oxygen depletion.
Figure 3 describes the concept scheme used by Bathtub to relate external loading of nutrients to the in-lake nutrient concentrations and the physical, chemical, and biological response of the lake to the level of nutrients.
Figure 3. Bathtub concept scheme

Loading of nutrients (Flow and Concentration)

Physical characters of the lake In-lake nutrient Chla, Secchi (Surface area and mean depth) Concentrations (TN&TP) DO

Hydraulic characters of the lake (Water residence time)

The nutrient balance model adopted by Bathtub assumes that the net accumulation of nutrients in a lake is the difference between nutrient loadings into the lake from various sources and the nutrients carried out through outflow and losses of nutrient through whatever decay process occur inside lake:11 (3) Net accumulation = Inflow – Outflow – decay
Equation (3) is solved by assuming that the pollut ant dynamics in the lake is at a steady state, i.e. the net accumulation of the pollutant in the lake equals zero.
In this study, “inflow” included TN and TP loadings though stormwater surface runoff from various landuse categories, baseflow, a point source, leakage of septic tanks, atmosphere precipitation, and potential loadings from internal recycling from the sediment of the lake. Nutrient outflow was considered primarily through the outflow stream. To address nutrient decay within the lake, Bathtub provided several alternatives depending on the inorganic/organic nutrient partitioning coefficient and reaction kinetics. The major pathway of decay for TN and TP in the model is through sedimentation to the bottom of the lake.

Prediction of the eutrophication response by Bathtub also involves choosing one of several alternative models depending on whether the algal communities are limited by phosphorus or nitrogen, or co-limited by both nutrients. Scenarios that include algal communities limited by light intensity or controlled by the lake flushing ra te are also included in the suit of models. In addition, the response of chlorophyll a concentration to the in-lake nutrient level is characterized by two different kinetic processes: linear or exponential. The variety of models available in Bathtub allows the user to choose specific models based on the particular condition of the project lake.
One feature offered by Bathtub is the “calibration factor.” The empirical models implemented in Bathtub are mathematical generalizations about lake behavior. When applied to data from a particular reservoir, measured data may differ from predictions by a factor of two or more. Such differences reflect data limitations (measurement or estimation errors in the average inflow and outflow concentrations), unique features of th e particular lake (Walker 1999), and unexpected processes inherent to the lake. The calibration factor offered by Bathtub provides model users with a method to calibrate the magnitude of lake response predicted by the empirical models. The model calibrated to current conditions against measured data from the lake can then be applied to predict changes in lake conditions likely to result from specific management scenarios under the condition that the calibration factor remains constant for all prediction scenarios.
Steady State Assumption for the Lake
Before Bathtub could be used to establish a relationship between TN and TP loadings and the in-lake TN, TP, and Chla concentrations, the input and output of TN and TP were analyzed to examine the presumption of steady state. Usually , if the input of TN and TP to the lake issignificantly lower than the output, internal recycling is assumed. Based on reviewing the IWRdata, the Department concluded that internal recycling was occurring during the verified period and that the Lake was not at steady state during most of this period. In this study, the rate of TN and TP internal recycling for Newnans Lake was not available and therefore literature published values were adopted (James and Bierman 1995).
Data requirement for running Bathtub
Data requirement for Bathtub model includes:

• Physical characteristics of the lake (surface area, mean depth, length, and mixed layer depth)

• Meteorological data (precipitation and evapor ation retrieved from Climate Interactive Rapid Retrieval Users System of National Climate Data Center)12 • Measured water quality data (TN, TP, and Chla concentrations of the lake water, TN and TP concentrations in precipitation, etc.)

• Loading data (flow and TN and TP concentrations of the flow from various point and nonpoint sources, flux of TN and TP from internal recycling, and flow and TN and TP concentrations of outflow water)

• Coefficient of variance (CV) of all the measured data
Calculation of Trophic State Index (TSI)
TSI values were calculated using the procedures outlined in Florida’s 1996 305(b) report: TSI = (CHLA TSI + NUTR TSI )/2 Where: CHLA TSI = 16.8 + 14.4 × LN (CHLA)] TN TSI = 56 + [19.8 × LN(TN)] TN2 TSI = 10 × [5.96 + 2.15 × LN(TN + 0.0001)] TP TSI = [18.6 × LN(TP × 1000)] –18.4 TP2 TS = 10 × [2.36 × LN(TP × 1000) – 2.38] The procedure addresses limiting nutrient considerations by calculating NUTR TSI : If TN/TP > 30 then NUTR TSI = TP2 TSI If TN/TP < 10 then NUTR TSI = TN2 TSI If 10 < TN/TP < 30 then NUTR TSI = (TP TSI + TN TSI )/2

Error and variability analysis
The distinction between “error” and “variability” is important. Error refers to a difference between a measured and a predicted mean value and is usually described as: the absolute value of |measurement – prediction/measurement. Variability refers to spatial or temporal fluctuations in measurement around the mean. Spatial variability is not usually included in the variability analysis of empirical modeling efforts. Empirical modeling variability analysis usually concentrates on those ch anges caused by temporal fluctuation.
Variability is frequently described using the mean coefficient of variance (CV), which is defined as the standard error (SE) of the estimate expressed as a fraction of the predicted value (Walker 1999). In this study, model estimates were presented as mean ± 1SE whenever a CV could be determined.
When WMM was calibrated against measured wate r quantity and quality data, only error analysis was conducted. This was because the variability analysis of WMM required CVs for the EMC of TN and TP from different landuse categories and the CV for the suspended fraction of TN and TP from different landuse categories. Because we did not have these CVs, the variability analysis was not conducted with WMM. Additionally, WMM does not have a place to input CVs of the measured annual precipitation and baseflow. WMM calibration was conducted using all the years for which we have data and efforts were made to make sure that the error between model estimates and measured data were no greater than 10% for all the years.
Bathtub allows the input of the CV for both measured data and model predictions from WMM. Therefore, both error and variability analyses were conducted with Bathtub. To accomplish this, several years of measured data from the non-model variables (precipitation, lake volume, and13 evaporation) and the WMM predictions (TN, TP, and flow) were averaged and the mean values and CVs of these data were entered to Bathtub as input.
4.4 TMDL Scenario Development for Newnans Lake
Once WMM and Bathtub model calibrations were achieved (results discussed in the next section), the TMDL of the lake was developed through evaluating TSIs of the following scenarios: A. TSI of current condition B. TSI after the internal recycling was addressed C. TSI after both the internal recycling and all the human landuse categories (urban open, low, medium, and high density residential, agriculture and rangeland, and transportation, communication, and utilities) were removed
Scenario C was considered the natural background condition of the lake. The TN and TP loadings that result in a TSI of 60 would typically be considered as the TMDL of the lake. However, if the TSI of Scenario C were higher than 60, it would become the new target TSI threshold for the lake.

Available Data and Data Use
Model calibration and simulation of this study requires a historical record of several types of data. These data types and their availability are listed in Table 2.

Table 2. Data types that are required to have historical records and the period these data are availability
Data type Available time period Precipitation 1990 – 2000
Stream flow 1996 –2000 Lake stage 1996 –2000 Stream water quality data 1995 – 2000

Lake water quality data 1989 –2000

Because calibration of the model requires that data from the different types be in the same time period, 1996 to 2000 were chosen as the years from which data were used for model calibration.



### 5. RESULTS

5.1 Data Analysis Formatted: Bullets and Numbering14 Historical trend of trophic status of Newnans Lake
Monthly TN, TP, and Chla concentrations for Newnans Lake from 1989 through 2000 were retrieved from the IWR-data. The locations of the individual stations from which water quality data were collected are shown in Figure 4. Analysis of the data indicated that the spatial variation between stations across Newnans Lake is not significant. Therefore, data from all the stations within Newnans Lake were pooled together and treated as data collected from one station. Quarterly mean values for TN, TP, and Chla concentrations were calculated based on the monthly data and quarterly TSIs were calcul ated based on the quarterly mean values of TN, TP, and Chla concentrations. Quarterly TN, TP, Chla, and TSI values were then used to calculate annual mean values.
The seasonal trend of TN, TP, Chla, and TSI were examined by calculating the long-term quarterly mean values based on the quarterly mean values of each year (1989 – 2000). The quarterly means for the verified period were calculated using the data from 1995 through 2000.The individual annual mean TN, TP, Chla, and TSI values are listed in Table 3 and the longterm quarterly TN, TP, Chla, and TSI resu lts are listed in Table 4.15 Figure 4. Locations of water quality stations # #

## #

#

# #

# # # # # # #
# #

#

# #

# #

# # 

### H

a

t c

h e t t C

r e

e

k L i t t l e

H

a

t c

h e t t C

r e e

k



### Prairie Creek HC

LHC

NL 

## Gainesville

1 0 1 2 Miles N16 As shown in Table 3, the long-term annual average of TN, TP, and Chla concentrations are 3.32 mg/L, 0.120 mg/L, and 173.4 μg/L, respectively. The long term TSI is 79 ± 4. Long-term average TN/TP ratio is about 29, indicating that the algal communities in this lake may be either co-limited by both nitrogen and phosphorus, or phos phorus limited. For the verified period, the TN, TP, and Chla concentrations are 4.34 ± 0.73 mg/L, 0.151 ± 0.03 mg/L, and 249.0 ± 26.2 μg/L, respectively. The TSI of the verified period is 89 ± 3. Based on these data, the lake is eutrophic and exceeded the IWR TSI threshold of 60 for lakes.

Table 3. Annual averages of TN, TP, Chla, and TSI values of Newnans Lake from 1989 through 2000. Data represent mean ± 1SE (n=4)

TN TP Chla TSI (mg/L) (mg/L) (μg/L) 1989 1.56 ± 0.11 0.082 ± 0.006 45.1 ± 13.1 63 ± 6 1990 1.57 ± 0.47 0.081 ± 0.008 32.1 ± 4.3 58 ± 9 1991 1.87 ± 0.17 0.070 ± 0.012 62.1 ± 19.7 70 ± 2 1992 3.00 ± 0.47 0.083 ± 0.017 68.1 ± 15.8 57 ± 19 1993 2.52 ± 0.46 0.110 ± 0.005 132.4 ± 14.2 79 ± 1 1994 3.31 ± 0.32 0.099 ± 0.006 245.9 ± 45.0 88 ± 4 1995 4.10 ± 0.13 0.120 ± 0.007 271.8 ± 26.6 93 ± 1 1996 3.80 ± 0.15 0.111 ± 0.008 272.2 ± 24.8 90 ± 1 1997 3.81 ± 0.09 0.126 ± 0.008 261.8 ± 18.6 89 ± 1 1998 2.36 ± 0.09 0.089 ± 0.003 120.5 ± 27.4 77 ± 1 1999 4.26 ± 0.10 0.172 ± 0.012 269.6 ± 14.1 90 ± 1 2000 7.70 ± 0.12 0.291 ± 0.013 298.8 ± 11.3 97 ± 1 Mean-L 3.32 ± 0.49 0.120 ± 0.018 173.4 ± 30.4 79 ± 4 Mean-V 4.34 ± 0.73 0.151 ± 0.030 249.0 ± 26.2 89 ± 3 Mean-P 2.31 ± 0.31 0.088 ± 0.006 97.6 ± 32.8 69 ± 5 Notes:

• Mean-L represents results of record mean

• Bolded data were annual means for the verified period.

• Mean-V: mean values for the modified verified period (January of 1995 through December of 2000)

• Mean-P: mean values for the pre-verified period (1989 through 1994)

Table 4. Seasonal variation of TN, TP, Chla, and TSI in Newnans Lake
TN TP Chla TSI (mg/L) (mg/L) (μg/L) General long-term quarterly mean 1 st quarter 3.56 ± 0.55 0.123 ± 0.018 167.4 ± 32.5 82 ± 3 2 nd quarter 3.44 ± 0.72 0.122 ± 0.019 207.1 ± 40.4 74 ± 9 3 rd quarter 2.82 ± 0.29 0.108 ± 0.017 138.0 ± 28.0 78 ± 417 4 th quarter 3.20 ± 0.38 0.110 ± 0.013 182.9 ± 37.5 82 ± 3 Quarterly mean for the verified period 1 st quarter 4.65 ± 0.87 0.148 ± 0.034 243.7 ± 45.5 89 ± 4 2 nd quarter 4.88 ± 1.02 0.162 ± 0.028 294.1 ± 36.8 94 ± 4 3 rd quarter 3.13 ± 0.44 0.135 ± 0.031 163.8 ± 31.6 83 ± 3 4 th quarter 4.10 ± 0.57 0.135 ± 0.025 294.0 ± 30.5 91 ± 3 Data represent mean ± 1SE. n equals to 12 years for the general long-term quarterly mean values and 6 for quarterly mean values for the verified period.
TN, TP, and Chla concentrations of the lake were relatively constant and low from 1989 through 1991 (Table 3). The TN concentration ranged from 1.58 to 1.87 mg/L, TP concentration from 0.070 to 0.082 mg/L, and Chla concentration from 32.1 to 62.1μg/L during this period of time. The TSI was relatively low during this period, rangin g from 58 to 70. At this time, the lake could be considered high mesotrophic to eutrophic.
Starting from 1991, a significant increase in TN was observed. The increase continued until 1995. During this period, the average TN concentration jumped from 1.87 mg/L to 4.10 mg/L, a more than 2-fold increase. Elevated levels of TP were also observed, which increased from 0.070 mg/L in year 1991 to 0.120 mg/L in 1995, about a 70% increase. Chla increased by more than a factor of 4 from 62.1 μg/L in 1991 to 271.8 μg/L during this period. The TSI reached 93 in 1995, and the lake had become hyper-eutrophic .
The in-lake TN, TP, and Chla concentrations held fairly constant from 1995 through 1997. A significant drop of TN, TP, and Chla was observe d in 1998, followed by a dramatic increase again for TN and TP concentrations in 1999 and 2000. The Chla concentrations remained relatively constant during these two years, although a large intra-year variation was observed. The TSI remained high, around 90 throughout the period.
Although a dramatic change of annual TN, TP, and Chla concentrations was observed between years, seasonal variation was not very obvious. TN, TP, Chla, and TSI values of the different quarters were not significantly different from each other throughout an average year (Table 4).
To explain the annual variation, stage data of Newnans Lake collected from 1989 through 2000 were converted to lake volumes using the Elevation – Lake Volume curve of Newnans Lake developed by the St. John River Water Management District (Robison 1997). The annual average stage elevation and lake volume are listed in Table 5. The long-term quarterly average stage elevation and lake volume calculated based on data from 1989 through 2000 are listed in Table 6.

Table 5. Annual average stage elevation and volume of Newnans Lake. Data represent mean SE (n=4) Stage elevation Lake volume (feet) (acre-foot)
1989 65.5 ± 0.3 33,000 ± 1,732
1990 65.6 ± 0.2 33,125 ± 1,390
1991 66.0 ± 0.4 35,250 ± 2,65818 1992 65.9 ± 0.5 34,000 ± 2,739
1993 65.9 ± 0.3 34,000 ± 1,472
1994 65.9 ± 0.4 34,250 ± 2,454
1995 65.4 ± 0.2 31,500 ± 1,323
1996 65.5 ± 0.3 32,000 ± 1,957
1997 65.3 ± 0.3 31,100 ± 1,797
1998 66.7 ± 0.3 39,750 ± 1,886
1999 64.2 ± 0.1 22,275 ± 427
2000 62.7 ± 0.2 14,250 ± 1,336

mean 65.4 ± 0.5 31,208 ± 2,982

According to Table 5, stage elevation and volume of Newnans Lake were high in 1998 and low in 2000. However, seasonal variation of stage elevation and volume of the lake was not obvious. According to Table 6, long-term quarterly average stage elevation and lake volume are not significantly different between all the four quarters in the average year (1996 – 2000). An inverse relationship between the lake volume and TN, TP, and Chla concentrations was observed during 1997 – 2000. TN, TP, Chla, and TSI levels were significantly lower when the lake volume was significantly higher, and vise versa (Figure 5 – A, B, C, D). Chla concentration did not increase as dramatically as TN and TP concentrations in 2000. This was probably because the algal communities were limited by density dependent factors. For example, when algal biomass was too high, self-shading effects or simply lack of sufficient space could limit any further increase in algal biomass.

Table 6. Quarterly average stage elevation and volume of Newnans Lake. Data represent mean SE (n=6). Stage elevation Lake volume (feet) (acre-foot)
1 st quarter 65.7 ± 0.4 33,383 ± 2,773
2 nd quarter 65.5 ± 0.3 31,792 ± 1,950
3 rd quarter 65.2 ± 0.3 30,083 ± 2,122
4 th quarter 65.2 ± 0.4 29,575 ± 2,236

No clear long-term seasonal trend was found with the lake volume (Table 6). This was consistent with the findings that TN, TP, Chla , and TSI did not show significant variation between different quarters of an average year.
From examining Figures 5 – A, B, C, and D, lake volume alone obviously can not explain the variation of TN, TP, and Chla concentrations for the entire period from 1989 through 2000. This is especially true for the dramatic increase of TN, TP, and Chla concentrations observed during 1991 – 1995, because the lake volume stayed re latively constant during this period.19 

### Figure 5-A TN concentration vs. volume of Newnans Lake

Figure 5-B. TP concentration vs. volume of Newnans Lake 0.000 1.000 2.000 3.000 4.000 5.000 6.000 7.000 8.000 9.000 10.000

19891990 1991 19921993 19941995 19961997 1998 19992000TN concentration (mg/L)

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000Lake volume(acre-foot) TN
Lake volume

0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350

198919901991199219931994199519961997199819992000TP concentration (mg/L)

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000Lake volume(acre-foot) TP
Lake volume20 

### Figure 5-C. Chla concentration vs. volume of Newnans Lake

Figure 5-D. TSI vs. lake volume of Newnans Lake 0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0

1989 19901991 1992 19931994 1995 19961997 1998 19992000Chla concentration (mg/L)

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000Lake volume(acre-foot) Chla
Lake volume

0.0 20.0 40.0 60.0 80.0 100.0 120.0

1989 19901991 1992 1993 19941995 1996 1997 19981999 2000TSI

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000Lake volume(acre-foot) TSI
Lake volume21 However, the inverse relationship between TN, TP, and Chla concentration and lake volume during 1997 – 2000 indicates the importance of the lake volume on the overall water quality of the lake. Recall that the major sources of water for Newnans Lake includes surface runoff, baseflow, and direct precipitation into the lake. Therefore, the inverse relationship between water quality indices and lake volume during the period studied suggests that the TN and TP concentrations of these sources may be lower than the in-lake concentrations, and that internal recycling from nutrients stored in the bed could play a role in the observed degree of eutrophication.

TN and TP concentrations of inlet and outlet streams of Newnans Lake
TN and TP data for Hatchet Creek (inlet), Little Hatchet Creek (inlet), and Prairie Creek (outlet) were also retrieved from the IWR-Data database. Annual average TN and TP concentrations of these streams are listed in Table 7 and Table 8, respectively.
Except for one TN and TP measurement in each of 1996 and 1997, no data were found for Little Hatchet Creek in the period from 1995 through 1998. Therefore, the long-term annual averages of TN and TP concentrations for this stream were calculated based on only two years of data (1999 and 2000). For Prairie Creek, year 2000 data were missing and the long-term annual averages for the creek were calculated based on data from 1995 through 1999.

Table 7. Annual average TN concentration of Hatchet Creek, Little Hatchet, and Prairie Creek. Data represent mean ± SE. Unit: mg/L Inlet Streams Outlet Stream
Hatchet Creek Little Hatchet Creek Prairie Creek

1995 1.32 ± 0.13 ---- 4.686 ± 0.282
1996 0.97 ± 0.97 ---- 4.185 ± 0.482
1997 0.91 ± 0.09 ---- 4.440 ± 0.619
1998 0.86 ± 0.07 ---- 2.097 ± 0.277
1999 0.98 ± 0.09 0.840 ± 0.184 4.744 ± 0.362
2000 1.05 ± 0.18 1.015 ± 0.060 ---- Mean 1.02 ± 0.07 0.927 ± 0.088 4.030 ± 1.103

Table 8. Annual average TP concentration of Hatchet Creek, Little Hatchet, and Prairie Creek. Data represent mean ± SE. Unit: mg/L Inlet Streams Outlet Stream
Hatchet Creek Little Hatchet Creek Prairie Creek

1995 0.09 ± 0.01 ---- 0.223 ± 0.097
1996 0.09 ± 0.01 ---- 0.138 ± 0.03122 1997 0.10 ± 0.01 ---- 0.143 ± 0.028
1998 0.11 ± 0.04 ---- 0.117 ± 0.020
1999 0.18 ± 0.01 0.254 ± 0.035 0.242 ± 0.074
2000 0.16 ± 0.02 0.375 ± 0.060 ---- Mean 0.12 ± 0.02 0.314 ± 0.060 0.172 ± 0.056

The long-term annual averages of TN concentrat ion for the two inlet streams – Hatchet Creek and Little Hatchet Creek - were not significantl y different from each other and were about 1 mg/L (Table 7). This concentration was significantly lower than the in-lake concentration, which was about 4 mg/L (Table 3). The TN concentration in Prairie Creek, the outlet stream, was also about 4 mg/L. This concentration was significantly higher than the TN concentration in two inlet streams, but was not significantly different from the in-lake concentration.
The long-term annual average TP concentrations in Hatchet Creek and Prairie Creek were similar (Table 8) and were similar to the in-lake TP concentration. TP concentration in Little Hatchet Creek, however, was significantly higher than all the other waterbodies. It was difficult to interpret the high TP concentration in Little Hatchet Creek because we had only two years of data. Although the influence from human activities is high in the Little Hatchet Creek sub-basin, the TN concentration from this stream was not si gnificantly different from Hatchet Creek. This made it equivocal to pinpoint human activity as the cause of high TP in Little Hatchet Creek.

Several trends can be identified from the histor ical water quality data of Newnans Lake and its inlet and outlet streams. 1) There was a rapid increase in TN and TP concentration in Newnans Lake from 1991 through 1995. The TN more than doubled during this 5-year period, while the increase of TP concentration was milder, about 70%. What caused this increase remains unclear, but the change in the lake volume alone could not explain this dramatic change in nutrient concentrations

. 2) The long-term TN/TP ratio of the lake was about 29, suggesting that algal communities were co-limited by nitrogen and phosphorus. This ratio increased from around 20 in thelate 1980s and early 1990s to about 30 in 1990s, indicating a gradual shift from nitrogenphosphorus co-limitation to phosphorus limi tation. The trend was caused by the more rapid in-lake increase of TN than TP during the 1991 – 1995 period. The dramatic increase of chlorophyll a concentration in this period (more than 4 times) could be a synergistic effect from the increase of TN and TP concentrations at the same time. 3) Pre-1991 data indicated that the lake might have been mesotrophic to eutrophic, but not hypertrophic. This was indicated by TSIs between 60 – 70 in the late 1980s and early 1990s. Given this, the current high TSI of more than 90 should be reversible. 4) The significantly lower TN concentration in the inlet streams than the in-lake and outlet TN concentration suggests that the rapid incr ease of TN concentrations in the lake might not be caused solely by the current surface ru noff, baseflow, and direct precipitation into the lake. This is consistent with the finding that when the lake volume increased, TN, TP, Chla concentrations and TSI all decreased. Again, we suspect that the increase of TN in the lake could have been caused by an increase in the internal recycling within the lake.23 To evaluate the importance of landuse patterns and internal recycling to the trophic status of the lake, WMM and Bathtub were used to estimate the loading of TN and TP from various sources and the influence of these loadings to the TSI of the lake.
5.2 Estimating TN and TP Sub-basin loadings using WMM

Further breakdown of LHC and HC

As it was described in Section 4, the Newnans Lake watershed was subdivided into three subbasins, including LHC, HC, and NL. WMM was used to estimate the TN and TP loading from various point and nonpoint sources from these sub-basins. To estimate the TN and TP loading into Newnans Lake from LHC and HC, flow data at the mouth of the Hatchet Creek and Little Hatchet Creek and the TN and TP concentrations of each creek were used (Figure 6).24 Figure 6. USGS gauging stations and further breakdown of Hatchet Creek into Upper Hatchet Creek (Upper-HC) and Lower Hatchet Creek (Lower-HC) and Little Hatchet Creek into Upper Little Hatchet Creek (Upper-LHC) and Lower Little Hatchet Creek.

Two USGS gauging stations located at the mout h of the two inlet streams (SiteID: 02240800 and 02240810, Figure 6) were identified in this study. However, no flow record could be found for the two stations. Therefore, flow records of two other stations located in the upper reaches of Hatchet Creek and Little Hatchet Creek (SiteID: 02240783 and 02240806, Figure 6) were used for WMM water quantity calibration. To do this, the Hatchet Creek sub-basin was further subdivided into the Upper Hatchet Creek sub-basin (Upper-HC) and the Lower Hatchet Creek sub-basin (Lower-HC), and the Little Hatchet Creek sub-basin was divided into the Upper Little "  ́

"  ́

"  ́

"  ́

"  ́ 

### H

a t c h e t t C

r e e

k

L o w

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- L H

C



### Prairie Creek Newnans Lake Lower-HC

Upper-HC

NL 

### 02240783

02240806

02240810

02240902 Upper-LHC Lower-LHC



### 02240800

1 0 1 2 Miles N25Hatchet Creek sub-basin (Upper-LHC) and the Lower Little Hatchet Creek sub-basin (LowerLHC). Both upper sub-basins were delineated so that they terminate at the flow gauging station.
After the water quantity of WMM was calibrated, surface runoff of the Hatchet Creek sub-basin and Little Hatchet Creek sub-basin was estimated by applying the calibrated parameters to the entire area of the two sub-basins. Water quality calibration of WMM was conducted against the data retrieved from the IWR-data (Table 7 and 8 )

. Data required for estimating TN and TP loadings from point and nonpoint sources using WMM
To calibrate the water quantity of WMM, the following data were collected: A. Rain precipitation data from the weather station located at the Gainesville regional airport (UCAN 3964, COOP 083326, Figure 7) were retrieved from the Climate Interactive Rapid Retrieval User System (CIRRUS) hosted by the Southeast Regional Clim ate Center. Annual average precipitation and seasonal variation are listed in Table 9 and Table 10, respectively.26 % q



## Gainesville Lower-HC Upper-HC

Lower-LHC

NL Upper-LHC N

6 0 6 12 Miles

Figure 7. Location of the Gainesville Regional Airport NOAA weather station 

### NOAA Weather Station27 Table 9. Annual precipitation at Gainesville Regional Airport Year Annual Precipitation ( in /y ear )

1996 54.65
1997 58.22
1998 45.62
1999 38.34
2000 34.39

Table 10. Long-term average quarterly precipitation. Data represent mean ± SE (n=5) Quarter Quarterly Precipitation (in/quarter)

1 st quarter 10.40 ± 2.53
2 nd quarter 10.47 ± 2.60
3 rd quarter 17.32 ± 1.49
4 th quarter 8.10 ± 3.37

B. Daily flow data of two USGS gauging stations (SiteID: 02240783 and 02240806) were provided by USGS Florida Integrated Science Center. Of the data that we received, data sets for 1996, 1997, 1998, and 2000 were complete for Station 02240783 (located on Hatchet Creek). Data for Station 02240806 (located on Little Hatchet Creek) were only available for 1996. Data of all the other years were excluded from this study because of the significant amount of missing records.
The flow records for 1998 for Station 02240783 were not included in this study because the aggregated annual flow of this year was more than three times higher than annual flows for 1996 and 1997 even though the annual precipitation for 1998 was actually lower than 1996 and 1997 (Table 9). This decrease in precipitation in 1998 was confirmed by examining the records from several other weat her stations located in proximity to the Gainesville Regional Airport. Further, examining the geology of Newnans Lake watershed indicated that it was not very likely that the flow in the two streams could be significantly influenced by the Floridian Aquifer because the project area is confined by the Hawthorn formation (Copeland et al. 1991). There were also no drastic changes in landuse within the project area within a single year that would explain the sudden increase in surface runoff. Therefore, we considered 1998 flow data at Station 02240783 not reliable and excluded it from this study. The flow data for the two gauging stations were aggregated into annual flow data and are listed in Table 11.28 Table 11. Annual stream flow and baseflow of Upper Hatchet Creek and Upper Little Hatchet Creek Unit: acre-foot/year Upper Hatchet Creek Upper Little Hatchet Creek
Stream flow Baseflow Stream flow baseflow

1996 17216 5292 3293 1220
1997 19633 6494 ---- ----
1998 ---- ---- ---- ----
1999 ---- ---- ---- ----
2000 1079 397 ---- ----

C. The streams baseflow were obtained through conducting baseflow separation on the daily stream flow data, using the Hydrograph Separation Program (HYSEP) version 2.2 developed by USGS. The Local minimum method was used for the baseflow separation (Sloto and Crouse 1996). The aggregated annual baseflow data of the two streams is listed in Table 11.

D. Areas of different landuse categories in each sub-basin were obtained by aggregating GIS landuse coverage based on the simplified level 1 code listed in Table 1. Acreage of each landuse category for Upper-HC and Upper-LHC (the two sub-basins whose surface runoff was used for WMM water quantity calibration) is listed in Table 12. Acreage of each landuse category of HC, LHC, and NL is listed in Table 13. Percent distributions of each landuse category in HC, LHC, and NL are shown in Figure 8.

Table 12. Area of each landuse category of Upper-HC and Upper-LHC
Unit: acre Upper-HC Upper-LHC Forest/Rural Open 19120.31 1964.86 Urban Open 643.63 589.76 Agriculture 1028.32 116.66 Low Density Residential 1265.53 4.15 Medium Density Residential 166.40 441.15 High Density Residential 26.28 79.84 Communication and Transportation 132.94 190.15 Rangeland 393.38 128.81
Water/Wetlands 5785.94 672.76
Total 22352.74 4188.1429 Water/wetland and Forest/rural open dominated the landuse in all the three sub-basins (Figure 8). Hatchet Creek had the highest percentage of Water/wetland and Forest/rural open area, which accounted for 85.5% of the total area of this sub-basin. Water/wetland and Forest/rural open accounted for 69.5% and 76.2% of total area for Little Hatchet Creek and Newnans Lake sub-basins, respectively. Among the human landuse categories, residential appeared to be important in all the three sub-watersheds,

Table 13. Area of each landuse category of HC, LHC, and NL
Unit: acre HC LHC NL
Forest/Rural Open 26220.09 5415.89 7497.64 Urban Open 734.58 865.48 765.77 Agriculture 1880.69 142.37 1420.55 Low Density Residential 1970.12 94.59 1283.36 Medium Density Residential 386.03 441.15 1063.86 High Density Residential 28.83 83.10 93.28 Communication and Transportation 307.35 1065.97 150.24 Rangeland 654.31 636.54 644.02
Water/Wetlands 8902.87 2161.97 9818.15
Total 41084.86 10907.04 22736.89

and accounted for 5.8%, 5.7%, and 10.7% of the total area for Hatchet Creek, Little Hatchet Creek, and Newnans Lake sub-basins, respectively. The highest percent landuse area occupied by Transportation/communication was found in Little Hatchet Creek sub-basin, which accounted for about 10% of the total area of the basin. This was mainly caused by the land area used by Gainesville Regional 

### Airport. In no sub-basin were human landuse categories significantly higher than 30% of the total area. Little Hatchet Creek had the highest percent area of human landuse, which accounted for 30.5% of sub-basin area. For Hatchet Creek and Newnans Lake sub-basin, percent of human landuse was 14.0% and 23.8%, respectively.30 Figure 8. Percent distribution of different landuse categories in HC (A), LHC (B), and NL (C) sub-basins A

Forest/Rural Open 63.8%

Urban Open

1.8% Water/Wetlands 21.7%

Agricultural

4.6% Low density residential

4.8% Medium density

residential

0.9% Rangeland

1.6% Transportation/ Communication 0.7% High density residential

0.1%

B

Urban Open 7.9% Medium density

residential

4.0%
Low density residential

0.9% Agricultural 1.3% Rangeland

5.8%

Transportation/ Communication 10.0% High density residential

0.8% Water/Wetlands 19.8%

Forest/Rural Open 49.7%

C

Forest/Rural Open 33.0%
Water/Wetlands 43.2%

Urban Open 3.4%

Agricultural

6.2% Low density residential

5.6% Rangeland

2.8%

High density residential

0.4% Medium density residential

4.7% Transportation/ Communication 0.7%31 In summary, the percent distribution of different landuse categories had some overall similarity across all three sub-watersheds. Water/wetland and Forest/rural open area dominated the entire Newnans Lake watershed. This overall similarity of landuse distribution provided us with the basis to extrapolate some model parameters calibrated in one sub-basin to the others, when local data were not available for developing the TMDL.

E. Percent impervious area of each landuse category is a very important parameter in estimating surface runoff using WMM. Nonpoint pollution monitoring studies throughout the U.S. over the past 15 years have shown that annual “per acre” discharges of urban stormwater pollution are positively related to the amount of imperviousness in the landuse (WMM User’s Manual 1998). Ideally, impervious area is considered as the area that does not retain water and therefore, 100% of the precipitation falling on the impervious area should become surface runoff. In practice, the runoff coefficient for impervious area typically ranges between 95 to 100%. Impervious runoff coefficients lower than this range were observed in the literature, but usually this number should not be lower than 80%. For pervious area, the runoff coefficient usually ranges between 10 to 20%. However, values lower than this range were also observed (WMM User’s Manual: 1998). In this study, impervious and pervious runoff coefficients were adjusted to fit model estimates to measured data in the process of WMM water quantity calibration.
It should be noted that the impervious area percentages do not necessarily represent directly connected impervious area (DCIA). Us ing a single-family residence as an example, rain falls on rooftops, sidewalks, and driveways. The sum of these areas may represent 30% of the total lot. However, much of the rain that falls on the roof drains to the grass and infiltrates to the ground or runs off the property , and thus does not run directly to the street. For WMM modeling purpose, whenever the area of the watershed that contributes to the surface runoff was considered, DCIA was used in place of impervious area. Because local values were not available, DCIAs used in this study were collected from literature published values or results from other studies (Table 14).

Table 14 Percent direct connected impervi ous area for different landuse categories Landuse Categories DCIA Reference Forest/Rural Open 0.5% WMM User’s Manual: 1998 Urban Open 0.5% WMM User’s Manual: 1998 Agriculture 3.7% Brown 1995 Low Density Residential 12.40% Brown 1995 Medium Density Residential 18.70% Brown 1995 High Density Residential 29.60% Brown 1995 Communication and Transportation 36.20% Brown 1995 Rangeland 3.7% CDM
Water/Wetlands 30% Harper and Livingston 1999

F. Local Event mean concentrations (EMC) of TN and TP for different landuse categories were not available and therefore were obtained from literature values (Table 15).32 EMCs of TN and TP for most landuse categories were cited from a review prepared by Harper (1994). EMCs for Agriculture, Low Density Residential, and Water/Wetlands were directly provided by the review. However, EMCs for Urban Open, Medium Density Residential, High Density Residential, Transportation and

Table 15. Event mean concentration of TN and TP for different landuse categories Unit: mg/L Landuse Categories TN TP Reference Forest/Rural Open 1.85 0.33 CDM 1990 Urban Open 1.18 0.15 Harper 1994 Agriculture 2.32 0.334 Harper 1994 Low Density Residential 1.77 0.177 Harper 1994 Medium Density Residential 2.29 0.30 Harper 1994 High Density Residential 2.42 0.49 Harper 1994 Communication and Transportation 2.08 0.34 Harper 1994 Rangeland 2.32 0.334 Harper 1994
Water/Wetlands 1.6 0.19 Harper 1994

Communication, and Rangeland were not directly defin ed in Harper’s review. Therefore, some extrapolations were made between the landuse categories in this study and the landusecategories defined by Harper’s review. Basically, the Urban Open area was treated as the LowIntensity Commercial area in Harper’s review . Medium Density Residential was treated as Single Family area; High Density Residential wa s treated as Multi-Family area; Transportation and Communication was treated mainly as Highway; and Rangeland was treated the same as general Agriculture.
G. Not all the TN and TP are transported by the stormwater in the dissolved form. The percentage of the total EMC represented by TN and TP attached to suspended particles is allowed to be defined in WMM. Percent suspended TP values were calculated from total phosphorus (TP) and dissolved phosphorus (DP) values of various landuse categories determined in a study conducted by CDM (not published). These values were used for all three sub-watersheds. No percent suspended TN values were available for this study. Therefore, the same value was assigned to all the landuse categories and was adjusted to fit the estimated TN concentration to the actual measurement in each sub-basin. Because percent suspended TN was used as an adjustable parameter in the process of model calibration, Hatchet Creek and Little Hatchet Creek sub-basins had different values of percent suspended TN. The percent TN for Hatchet Creek sub-basin was applied in estimating the TN loading from Newnans Lake sub-basin. Values for percent TP and TN in suspended form adopted in this study are listed in Table 16.33 Table 16. Percent TP and TN in suspended form for different landuse categories. HC,LHC, and NL represent Hatchet Creek, Little Hatchet Creek, and Newnans Lake subwatershed, respectively. Landuse Categories TP TN
HC LHC NL Forest/Rural Open 92% 33% 45% 33% Urban Open 55% 33% 45% 33% Agriculture 32% 33% 45% 33% Low Density Residential 25% 33% 45% 33% Medium Density Residential 40% 33% 45% 33% High Density Residential 55% 33% 45% 33% Communication and Transportation 63% 33% 45% 33% Rangeland 32% 33% 45% 33%
Water/Wetlands 47% 33% 45% 33%

H. The Sediment delivery ratio determines how much TN and TP attaching to suspended particles will be delivered to the destination waterbody eventually. In this study, the range of sediment delivery ratio was estimated using the correlation between delivery ratio and watershed area developed by Roehl (1962). Because of the difference in total area of thewatershed for each sub-basin, Hatchet Creek, Little Hatchet Creek, and Newnans Lake subbasins were assigned different sediment delivery ratios, which were 0.18, 0.21, and 0.19, respectively.

I. TN and TP concentrations of baseflow were treated as the TN and TP concentration of the groundwater in the project area. The only well found for the entire project area is located in the Little Hatchet Creek watershed (Figure 9). The TN and TP concentration of the well were obtained from the Florida Groundwater Quality Monitoring Network ( http://tlhdwf2.dep.state.fl.us/ambient/triennial/) . At the time this project was carried out, TN and TP concentrations were only available for 1997 for the well, which was 0.22 mg/L for TN and 0.06 mg/L for TP. These values were used as the baseflow TN and TP concentrations throughout the entire period from 1996 through 2000.



### J. To estimate the TN and TP loadings from leakage of septic tanks , WMM incorporates the concept of “septic tank failure loading rate”, which defines the percent increase of TN and TP loadings from Low Density Residential areas under septic tank leakage. The typical range of septic tank failure loading rate for TP is about 160% to 250 % , for TN is 140% to 200%. To provide a Margin of Safety, this study adopted the high end of the range, which was 200% for TN and 250% for TP, respectively (WMM User Manual: 1998). Another value required by WMM to estimate the influence from leaking septic tanks on TN and TP loading is the “septic tank34 þ 

## Lower-HC Upper-HC

Lower-LHC

NL Upper-LHC N

6 0 6 12 Miles

Figure 9. Location of a surficial well from wh ich the baseflow TN and TP concentrations were obtained.

Failure rate”, which defines the frequency at wh ich septic tanks may fail. Studies conducted on the water quality of the Ocklawaha River Basin found that annual frequency of septic tank repairs was about 0.97% (Basin Status Report 2001). For average annual conditions, it is conservative to assume that septic tank systems failures would be unnoticed or ignored for five years before repair or replacement occurred (WMM User Manual: 1998). Therefore, the septic tank failure rate used in this study was calculated by multiplying repairing frequency (0.97%) by 5 (years) and was about 5%. 

### Surficial Well35 K. There is one permitted point source, Brittany Estates Mobile Home Park, in the Little Hatchet Creek sub-basin (Figure 10). The facility is permitted (Permit number: FL0040215) to discharge up to 0.06 million gallons per day (MGD) annual average daily flow into Little Hatchet Creek. The permit for the facility incl udes effluent nutrient limitations for organic nitrogen (6.4 mg/L max a 3.2 mg/L annual average), nitrate (12.0 mg/L maximum, with no annual average limit), and total ammonia (4.8 mg/L maximum and 2.4 mg/L annual average). Based on these limitations, the total nitrogen limits are 23.2 mg/L maximum and 5.6 mg/L annual average. No limitations are contained in the permit for phosphorus. Existing daily discharge and the TN concentration of the discharge from 1996 through 2000 were retrieved from the EPA Permit Compliant System (PCS) database. Records of TP concentration in the discharge were only found for 1999 and 2000 (St. John River Water Management District 2003). The average annual TP concentration was calculated based on these records and assigned to all the years from 1996 through 2000. The daily discharge and the TN and TP concentrations of the discharge are listed in Table 17.

Table 17. Daily discharge and TN and TP conc entrations in the discharge from Brittany Estates Mobile Home Park Daily Discharge TN TP (MGD) (mg/L) (mg/L)
1996 0.028 16.97 2.17
1997 0.024 17.29 2.17
1998 0.025 7.51 2.17
1999 0.022 2.95 2.17
2000 0.024 4.44 2.1736 % ×



### Gainesville Lower-HC Upper-HC

Lower-LHC

NL Upper-LHC N

6 0 6 12 Miles

Figure 10. Location of Brittany Estates Mobile Home Park discharging into the Little Hatchet Creek.

Preparing rainfall data for WMM water quantity calibration

As it has been discussed in section 4, WMM uses Equation (1) to estimate the surface runoff from precipitation data. Equation (1) assumes th at the amount of surface runoff is in direct proportion to precipitation, which implies that all the rainfall contributes to the surface runoff to some extent. This assumption, however, is an ov ersimplification of the ambient condition, in which a certain amount of rainfall is retained by soil and never contributes to the surface runoff. In other words, when the precipitation value is lower than a certain threshold, no surface runoff will form (Viessman, et al. 1989). This can be described using the following equation: 

### Brittany Estates Mobile Home Park37 (4) Q = k*(P – P 0 )

Where, Q is the surface runoff produced by a given amount of annual precipitation k is equivalent to [C p + (C I – C p ) IMP L ] of Equation (1), which is the runoff coefficient of landuse category L. P is the annual precipitation P 0 is the base precipitation value below which Q is zero.
Equation (4) can be rewritten as:
(5) Q = k*P – k*P 0 Comparing Equation (5) to Equation (1), which is
(1) R = [C p + (C I – C p ) IMP L ] * I It is obvious that Equation (1) fails to take into account –k*P 0 , which is the portion of rainfall that will never contribute to surface runoff. Theref ore, using Equation (1), WMM may overestimate the surface runoff, especially for dry years during which the majority or even all of the rainfall is retained in the watershed and very little or even no surface runoff will be produced.
To address this problem, this study analyzed the correlation between the annual rainfall and areal annual surface runoff (the difference between stream flow and baseflow divided by the area of the watershed) using the three years that we had complete data sets in the Upper-HC sub-basin (1996, 1997, and 2000). A strong linear correlation was found between annual rainfall and areal annual surface runoff (R 2 was almost 1, Figure 11). The form of the correlation was identical to the form of Equation (5). Therefore, the slope of the correlation line was equivalent to k of Equation (5), and the intercept of the correlation is equivalent to k*P 0 of Equation (5). P 0 was then calculated as the quotient between the intercept (k*P 0 = - 9.4) and the slope (k = 0.29) of the correlation line and e qualed 32.6 inches/year. This value, according to Viessman, et al. (1989), was the base precipitation value below which surface runoff would be zero.
Before the actual measured precipitation was used for WMM calibration and simulation, this value (32.6 inches/year) was subtracted from the or iginal precipitation observations to created a set of “adjusted precipitation values” (Table 18), which were equivalent to I in Equation (1), and were used for WMM model calibration and simulation. Although P 0 was only characterized using the data from the Upper-HC sub-basin due to insufficient data availability, considering the overall similarity of the landuse pattern, P 0 was assumed the same for all the other sub-basins in the project area, and so were all the adjusted annual precipitation values.38 Figure 11. Correlation between areal annual surface runoff and annual precipitation.

Table 18. Adjusted annual precipitation calculated based on P 0. Bold values were baseflow interpolated using the correlation between areal annual baseflow and annual precipitation.

Annual

Flow Annual Baseflow Areal annual

flow Areal annual baseflow Areal annual runoff Annual precipitation Adjusted annual precipitation Acre-foot Inches/year

1996 17216 5292 9.24 2.84 6.40 54.65 22.03
1997 19633 6494 10.54 3.49 7.05 58.22 25.60
1998 ---- ---- ---- 1.72 ---- 45.62 13.00
1999 ---- ---- ---- 0.72 ---- 38.34 5.72
2000 1079 397 0.58 0.21 0.37 34.39 1.77 y = 0.29x - 9.46 R 2 = 1.00

0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 Annual precipitation (in/year)areal annual runoff(in/year)39 Figure 12. Correlation between areal annual baseflow and annual precipitation.
A tight correlation was also observed between annual baseflow and annual precipitation using the data from 1996, 1997, and 2000 (Figure 12). This allowed predictions of the annual baseflow of 1998 and 1999 (Table 18), which was required for WMM model simulation.

WMM flow calibration
WMM flow calibration was conducted using the data from 1996, 1997, and 2000 for the UpperHC sub-basin, and 1996 data for the Upper-LHC sub-basin. Calibration was primarily conducted through adjusting the runoff coefficients for pervious and impervious landuse area to fit the estimates to the actual measurements. Because we calibrated the model against ALL the years from which data were available, a criterion had to be set up to define the point of best fit of model estimates to observations. The error between model predictions and measured observations (the quotient between the prediction-measurement difference and the observations) was used to determine the best fit. For the Upper-LHC, WMM water quantity calibration was only conducted for 1998 because it is the only year with data.. Table 19 lists obse rvations, WMM predictions, errors, and pervious and impervious runoff coefficients from both Upper-HC and Upper-LHC sub-basins. From the table it can be seen that the model predicted the measured flows within 11 percent. The model tended to under predict wetter years.

WMM flow simulation for the entire area of Hatchet Creek, Little Hatchet Creek, and Newnans Lake sub-basin
The pervious and impervious runoff coefficients calibrated above were used to estimate the annual stream flow of Hatchet Creek and Little Hatchet Creek derived from the surface runoff of the entire area of the two sub-watersheds. Annual precipitation, percent impervious area, and areal annual baseflow were kept the same as when WMM was calibrated. For the flow simulation of Little Hatchet Creek, the annual flow contributed by the Brittany Estates Mobile Home Park was included into the model. Also, using the precipitation data for 1998 and 1999 and the model parameters calibrated for the Upper-HC sub-basin, stream flows for 1998 and y = 0.1348x - 4.4343 R 2 = 0.9977

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 Annual precipitation (in/year)areal annual baseflow(in/year)40 1999 were simulated for Hatchet Creek. Using the same procedure, stream flows for 1997, 1998, 1999, and 2000 were also simulated for Little Hatchet Creek. Surface runoff and baseflow from the Newnans Lake sub-basin were simulated using all the model parameters calibrated against the data from Upper-HC sub-basin. Simulated WMM estimates from all the three sub-watersheds are listed in Table 20.

Table 19. Results of WMM water quantity calibration.
Measured annual flow Estimated annual flow Pervious runoff coefficient Impervious runoff coefficient Error

Acre-foot For Upper Hatchet Creek

1996 17216 15273 0.17 0.95 11%
1997 19633 18102 0.17 0.95 8%
1998 ---- ---- ---- ---- ----
1999 ---- ---- ---- ---- ----
2000 1079 1193 0.17 0.95 11% For Upper Little Hatchet Creek

1996 3293 3236 0.19 0.95 2%
1997 ---- ---- ---- ---- ----
1998 ---- ---- ---- ---- ----
1999 ---- ---- ---- ---- ----
2000 ---- ---- ---- ---- ----

Table 20. Estimated annual flow of Hatchet Creek and Little Hatchet Creek and the water directly contributing to Newnans Lake from its immediate surrounding sub-watershed. Unit: Acre-foot/year Hatchet Creek Little Hatchet Creek Newnans Lake
1996 27322 8100 12037
1997 32400 9588 13988
1998 16274 4836 7103
1999 7096 2116 3125
2000 2133 659 96741 WMM Water Quality Calibration and Simulation of Watershed Loadings
WMM water quality calibration for HC and LHC sub-basins was conducted using data from the entire Hatchet Creek and Little Hatchet Creek sub-bas ins. The calibrated model was then used to estimate the TN and TP loading from HC, LHC, and NL sub-basins. For Hatchet Creek, measured TN and TP concentrations were available from 1996 through 2000. These data were used for model calibration. After the best fit between predicted and measured concentrations was achieved, model estimates of TN and TP loadings from this sub-basin were also obtained. Therefore, no extra model simulation for TN and TP was needed. For Little Hatchet Creek, TN and TP concentrations were available for 1999 and 2000. Therefore, calibration was conducted using the data from these two years, and the calibrated model was used to estimate TN and TP loadings for all the other years. Due to the overall similarity in landuse between the HC and NL sub-basins, the model as calibrated for HC was applied to estimate the TN and TP loadings directly discharging into Newnans Lake from the NL sub-basin.

The WMM user’s manual recommends that WMM calibration on water quality be through adjusting the sediment delivery ratio while keeping all the other model parameters unchanged (WMM User’s Manual 1998). This approach was not used in this study because it could produce a sediment delivery ratio that was unacceptably high. Instead, the sediment delivery ratio was calculated using the delivery ratio to watershed area correlation characterized by Roehl (1962). Using this technique, delivery ratios for HC, LHC, and NL sub-basins were calculated as 0.18, 0.21, and 0.19, respectively.
After the sediment delivery ratio was defined, no further parameter adjustment was conducted for TP. TN concentration was calibrated by adj usting the percent TN attached to suspended particles. The results of model calibration are shown in Table 21, and estimated TN and TP loadings from each sub-watershed are listed in Table 22.

Table 21. Results of WMM water quality calibration Unit: mg/L Measured concentrations WMM predictions Error
TN TP TN TP TN TP
Hatchet Creek

1996 0.970 0.086 0.936 0.095 3.3% 11.1%
1997 0.910 0.099 0.922 0.095 1.0% 4.3%
1998 0.860 0.110 0.929 0.095 7.9% 13.7%
1999 0.980 0.184 0.935 0.095 4.8% 48.5%
2000 1.050 0.161 0.957 0.096 9.3% 40.4%
Little Hatchet Creek

1996 ---- ---- ---- ---- ---- ----
1997 ---- ---- ---- ---- ---- ----42 1998 ---- ---- ---- ---- ---- ----
1999 0.840 0.250 0.903 0.132 7% 48%
2000 1.010 0.370 1.107 0.194 9% 48%

Table 22. TN and TP loadings from HC, LHC, and NL sub-basins Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake
TN TP TN TP TN TP
1996 69539 7049 20628 2545 46517 5183
1997 81197 8297 23679 2928 54270 6081
1998 41126 4184 11911 1564 27500 3072
1999 18040 1826 5175 757 12071 1343
2000 5550 556 1856 346 3717 410

As shown in Table 21, in all the modeling cases, the error between measured and estimated TN concentrations was less than 10%, indicating an overall good fit. WMM estimated TP concentrations reasonably well in 1996, 1997, and 1998 for the HC sub-basin, with an error between measured and estimates ranging from 4.3 – 13.7% for these three years. However,the error of estimates for TP was relatively high for 1999 and 2000 for both HC and LHC subbasins. Error in these years ranged from 40 to 48%, and the predictions were always lower than observations. It should be noted that the error was relatively constant for both years and in both sub-basins. Considering that 1996, 1997, and 1998 were three relatively wet years and 1999 and 2000 were dry years, the high error of model predictions in 1999 and 2000 implies that sources of TP were underestimated a nd the sources may somehow be related to the amount of precipitation that these sub-basins received. Because the error held relatively constant for both years and in both sub-basins, it is possible that the high error was caused by a source of TP that had a more or less similar influence on the entire project area. In our case, one possible source was the TP in baseflow. As discussed in the previous section, the TP concentration in baseflow was only available for 1997 and was assumed to be constant for all the modeling years. Whether TP concentration in baseflow will change significantly with the change of rainfall remains unknown and is one uncertainty associated with this study.
The combined total loading of TN and TP from HC, LHC, and NL sub-basins correlated well with the annual precipitation. The higher the rainfall, the higher the total TN and TP loadings, and vise versa. The highest loading for both TN and TP came from the HC sub-basin, with the second highest from the NL sub-basin, and the least from LHC sub-basin (Table 22, Figure 13- A and Figure 13-B). This is consistent with the area of the three sub-basins and suggests that loadings from surface runoff dominated the loadings from all the sources.
TN and TP loadings from different landuse categories are listed in Tables 23 and 24. Figures 14, 15, 16, and 17 show the percent contribution of TN and TP from different landuse categories in the wettest year (1997) and the driest year (2000), respectively. Baseflow, septic tanks, and43 point sources are not classical landuse categories. They were included to offer a complete picture of sources of TN and TP loadings. The graphs show how, the amount of annual precipitation influences the relative importance of TN and TP contribution from different point and nonpoint sources.44 

### Figure 13-A. Contribution of TN loading from Hatchet Creek, Little Hatchet Creek, and Newnans Lake sub-basins.

Figure 13-B. Contribution of TP loading from Hatchet Creek, Little Hatchet Creek, and Newnans Lake Sub-watersheds. 0 20000 40000 60000 80000 100000 120000 140000 160000 180000

1996 1997 1998 1999 2000
YearContribution of TN (lbs/year

0 10 20 30 40 50 60 70Annual precipitation (in/year) New nans Lake
Little Hatchett Creek
Hatchett Creek Annual Precipitation

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

1996 1997 1998 1999 2000
YearContribution of TP (lbs/year)

0 10 20 30 40 50 60 70Annual precipitation (in/year) New nans Lake
Little Hatchett Creek
Hatchett Creek Annual Precipitation45 

### Table 23. Contribution of TN from di fferent landuse categories in 1996 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 30716 6248 8823 Urban open 549 637 575 Agriculture 3160 232 2397 Low density residential 3387 153 2216 Medium density residential 1017 1080 2814 High density residential 102 269 331 Transportation/communication 1053 3318 517 Rangeland 1099 1036 1087
Water/wetland 20955 4652 23214
Baseflow 5817 1544 3219 Septic tank 1685 16 1323
Point source N/A 1444 N/A

Table 23-continue. Contribution of TN from different landuse categories in 1997 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 35693 7260 10253 Urban open 638 740 668 Agriculture 3672 269 2786 Low density residential 3935 178 2575 Medium density residential 1182 1255 3271 High density residential 118 312 385 Transportation/communication 1224 3856 601 Rangeland 1277 1204 1263
Water/wetland 24350 5406 26976
Baseflow 7148 1898 3956 Septic tank 1958 18 1537
Point source N/A 1283 N/A46 Table 23-continue. Contribution of TN from different landuse categories in 1998 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 18126 3687 5207 Urban open 324 376 339 Agriculture 1864 137 1415 Low density residential 1999 90 1308 Medium density residential 600 637 1661 High density residential 60 158 195 Transportation/communication 621 1958 305 Rangeland 649 612 641
Water/wetland 12366 2745 13699
Baseflow 3523 935 1949 Septic tank 995 9 781
Point source N/A 576 N/A

Table 23-continue. Contribution of TN from different landuse categories in 1999 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 7975 1622 2291 Urban open 143 165 149 Agriculture 820 60 622 Low density residential 879 40 575 Medium density residential 264 280 731 High density residential 26 70 86 Transportation/communication 273 862 134 Rangeland 285 269 282
Water/wetland 5441 1207 6027
Baseflow 1495 397 828 Septic tank 437 4 344
Point source N/A 198 N/A47 Table 23-continue. Contribution of TN from different landuse categories in 2000 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 2468 502 709 Urban open 44 51 46 Agriculture 254 19 193 Low density residential 272 12 178 Medium density residential 82 88 226 High density residential 8 22 27 Transportation/communication 85 267 42 Rangeland 88 83 87
Water/wetland 1684 374 1865
Baseflow 430 114 238 Septic tank 136 1 107
Point source N/A 325 N/A

Table 24. Contribution of TP from different landuse categories in 1996 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 1845 472 547 Urban open 53 71 55 Agriculture 458 39 348 Low density residential 369 19 241 Medium density residential 123 150 340 High density residential 16 48 51 Transportation/communication 115 426 57 Rangeland 159 172 158
Water/wetland 2095 539 2328
Baseflow 1587 421 878 Septic tank 230 3 180
Point source N/A 185 N/A48 Table 24-continue. Contribution of TP from different landuse categories in 1997 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 2144 549 636 Urban open 61 83 64 Agriculture 532 45 404 Low density residential 429 22 280 Medium density residential 143 174 395 High density residential 18 55 59 Transportation/communication 134 495 66 Rangeland 185 200 183
Water/wetland 2435 625 2706
Baseflow 1950 518 1079 Septic tank 267 3 209
Point source N/A 158 N/A

Table 24-continue. Contribution of TP from different landuse categories in 1998 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 1089 279 323 Urban open 31 42 33 Agriculture 270 23 205 Low density residential 218 11 142 Medium density residential 72 88.6 201 High density residential 9 28 30 Transportation/communication 68 251 34 Rangeland 94 102 93
Water/wetland 1236 318 1374
Baseflow 961 255 532 Septic tank 136 2 106
Point source N/A 165 N/A49 Table 24-continue. Contribution of TP from different landuse categories in 1999 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 479 123 142 Urban open 14 18 14 Agriculture 119 10 90 Low density residential 96 5 63 Medium density residential 32 39 88 High density residential 4 12 13 Transportation/communication 30 111 15 Rangeland 41 45 41
Water/wetland 544 140 605
Baseflow 408 108 226 Septic tank 60 < 1 47
Point source N/A 146 N/A

Table 24-continue. Contribution of TP from different landuse categories in 2000 Unit: lbs/year Hatchet Creek Little Hatchet Creek Newnans Lake Forest/rural open 148 38 44 Urban open 4 6 4 Agriculture 37 3 28 Low density residential 30 2 19 Medium density residential 10 12 27 High density residential 1 4 4 Transportation/communication 9 34 5 Rangeland 13 14 13
Water/wetland 168 43 187
Baseflow 117 31 65 Septic tank 18 < 1 14
Point Source N/A 159 N/A50 Figure 14. Percent contribution of TN from different landuse categories in 1997. A: Hatchet Creek sub-watershed; B: Little Hatchet Creek sub-watershed; C: Newnans Lake sub-watershed. A

Forest/Rural Open 44.0% Baseflow

8.8%

Water/Wetlands 30.0% Septic tank 2.4%

Medium density

residential

1.5% High density residential

0.1% Transportation and communication 1.5%

Rangeland

1.6%

Low density residential

4.8% Agricultural

4.5% Urban Open 0.8%

C

Water/Wetlands 49.7% Forest/Rural Open 18.9% Baseflow

7.3% Septic tank 2.8%

Medium density residential

6.0%

High density residential

0.7% Transportation and communication 1.1% Rangeland

2.3% Low density residential

4.7% Agricultural

5.1% Urban Open

1.2% B

Water/Wetlands 22.8% Urban Open 3.1%

Agricultural

1.1%
Low density residential

0.8% Rangeland

5.1%

Highways 16.3% High density residential

1.3% Medium density residential

5.3% Septic tank

0.1% Forest/Rural Open 30.7% Baseflow

8.0% Point source 5.4%51 A

Forest/Rural Open 44.5% Baseflow

7.7%

Water/Wetlands 30.3% Septic tank 2.5%

Medium density

residential

1.5% High density residential

0.1% Transportation and communication 1.5% Rangeland 1.6%

Low density residential

4.9% Agricultural 4.6% Urban Open 0.8%

C

Water/Wetlands 50.2% Forest/Rural Open 19.1% Baseflow

6.4% Septic tank 2.9%

Medium density residential

6.1%

High density residential

0.7% Transportation and communication 1.1% Rangeland

2.3% Low density residential

4.8% Agricultural

5.2% Urban Open

1.2%

Figure 15. Percent contribution of TN from different landuse categories in 2000. A: Hatchet Creek sub-watershed; B: Little Hatchet Creek sub-watershed; C: Newnans Lake sub-watershed. B

Water/Wetlands 20.1% Baseflow

6.2% Urban Open 2.8%

Agricultural

1.0% Low density residential

0.7%

Rangeland

4.5%
Transportation and communication 13.4% High density residential

1.2% Medium density residential

4.7% Septic tank

0.1% Forest/Rural Open 27.0% Point source

17.5%52 Figure 16. Percent contribution of TP from different landuse categories in 1997. A: Hatchet Creek sub-watershed; B: Little Hatchet Creek s ub-watershed; C: Newnans Lake sub-watershed. A

Forest/Rural Open 25.8% Baseflow 23.5% Septic tank 3.2%

Low density residential

5.2% Agricultural

6.4%

Water/Wetlands 29.3% Urban Open 0.7%

Medium density

residential

1.7% High density residential

0.2% Transportation and communication 1.6% Rangeland

2.2% B

Point source

5.4% Septic tank

0.1%

Baseflow 17.7% Agricultural 1.5% Urban Open

2.8% Forest/Rural

Open 18.7%

Low density residential

0.8%
Water/Wetlands 21.4% Medium density residential

6.0% High density residential

1.9% Transportation and communication 16.9% Rangeland

6.8% C

Urban Open 1.1% Forest/Rural

Open 10.5% Septic tank

3.4%

Baseflow 17.7% Agricultural 6.6%
Low density residential

4.6%

Water/Wetlands 44.5% Medium density residential

6.5%

High density residential

1.0%

Transportation and communication 1.1% Rangeland

3.0%53 Figure 17. Percent contribution of TP from different landuse categories in 2000. A: Hatchet Creek sub-watershed; B: Little Hatchet Creek sub-watershed; C: Newnans Lake sub-watershed. A

Forest/Rural Open 26.7%

Water/Wetlands 30.3% Low density residential

5.3% Agricultural

6.6% Urban Open

0.8% Baseflow 21.1% Septic tank 3.2%

Medium density residential

1.8% High density residential

0.2% Transportation and communication 1.7% Rangeland

2.3% B

Forest/Rural

Open 11.0%

Water/Wetlands 12.5% Low density residential

0.4% Agricultural

0.9% Urban Open

1.7%

Septic tank

0.0%
Baseflow 9.0% Point source

46.0% Medium density residential

3.5% High density residential

1.1%

Transportation and communication 16.6%

Rangeland

4.0% C

Septic tank

3.4%
Baseflow 15.8% Urban Open 1.1% Forest/Rural

Open 10.7%

Agricultural 6.8%

Low density residential

4.7%

Water/Wetlands 45.6% Medium density residential

6.7% High density residential

1.0%

Transportation and communication 1.1% Rangeland

3.1%54 Before the percent contribution of TN and TP fr om each landuse category is discussed, it is important to remember that the relative TN and TP contribution by each sub-basin [Hatchet Creek (HC), Little Hatchet Creek (LHC), and Newnans Lake (NL ) ] were significantly different. The percent contribution of TN were 49.3% to 51.1%, 14.7% to 17.6%, and 33.0% to 34.2% for the HC, LHC, and NL sub-basins, respectively (Table 25). Annual precipitation appeared to influence the percent contribution of TN from these sub-basins. Percent TN contribution from LHC increased from about 15% to about 18%, while contributions from HC and NL sub-basins decreased from about 51% and 34% to 49% and 33%, respectively. The percent TP contribution followed the similar trend. About 42% to 48% and 31% to 35% of total TP load were from HC and NL sub-basin respectively, while 16.9% to 26.4% of the TP was from LHC sub-basin. Annual precipitation appeared to influence the percent TP contribution more than TN concentration. In the driest year 2000, the contribution of TP from LHC sub-basin increased from about 17% to 19% to about 26%, suggesting the influence from the point source.

Table 25. Percent contribution of TN and TP from HC, LHC, and NL sub-basins

HC sub-basin LHC sub-basin NL sub-basin
TN TP TN TP TN TP
1996 50.9% 47.7% 15.1% 17.2% 34.0% 35.1%
1997 50.9% 47.8% 15.0% 16.9% 34.1% 35.1%
1998 51.1% 47.4% 14.9% 17.7% 34.1% 34.8%
1999 51.1% 46.5% 14.7% 19.3% 34.2% 34.2%
2000 49.3% 42.4% 17.6% 26.4% 33.0% 31.3%

Non-human landuse categories appeared to dominate the TN loading in both HC and NL subbasins. The combined percent TN contributions from Water/wetlands and Forest/rural open area accounted for between 74.0% to 74.8% of the total TN loading from HC sub-basin and between 68.6 to 69.3% from NL sub-basin. Percent TN loadings from human landuse categories, including Agriculture, Rangeland, Low, Medium, and High residential area (including septic tanks), Urban open, and Transportation and communication, accounted for 17.2% to 17.5% for HC sub-basin, and 24.1% to 24.3% for NL sub-basin. Baseflow contributed 7.7% to 8.8% TN from HC sub-basin and 6. 4% to 7.3% from NL sub-basin. No active point source was identified in these two sub-basins. This explains the findings that the amount of annual precipitation did not significantly influence the percent TN distribution among non-human landuse categories, human-landuse categories, and baseflow.
Among the human landuse categories, TN loading from residential areas appears to be predominating. Residential TN loading accounted for 6.4% to 6.5% of the total TN loading in HC sub-basin and 11.4% to 11.6% in NL sub-basin. If the influence of leaking septic tanks were considered, TN loading from residential areas would account for 8.8% to 9.0% and 14.2% to 14.5% in HC and NL sub-basins, respectively. Medium density residential contributed the highest percentage of TN from residential areas in the NL sub-basin, accounting for 6.0% to 6.1% of the total TN loading. Low density reside ntial area was the second largest residential TN contributor in NL sub-basin, accounting for 4.7% to 4.8% of the total TN loading. The largest residential TN contributor in the HC sub-basi n was the low density residential area, which accounted for 4.8% to 4.9% of the total TN loading.55 The largest TN contributor of non-residential human landuse category was Agriculture. It accounted for 4.5% to 4.8% of the total TN loading in both HC and NL sub-basins. The percent TN contribution from different landuse categories in HC and NL sub-basin was not significantly influenced by annual precipitation.
The distribution of percent TN loading across different landuse categories was different in LHC sub-basin from those in HC and NL sub-basins and was also significantly influenced by the annual precipitation. The combined TN loading from non-human landuse categories accounted for 53% of the total TN loading from the sub-basin in the wettest year of 1997, but decreased to 44.1% in the driest year of 2000. Percent TN contribution of baseflow was also influenced by the rainfall. In the wet year, baseflow TN loading comprised 7.9% of the total TN loading and 5.8% in the dry year. Combined TN loading from human landuse categories increased when the annual precipitation decreased, from 39.1% in the wet year to 50.1% in the dry year. The reason for the difference was the change of the percent TN loading from the point source. In the wet year, the TN loading from the point s ource accounted for only 6.3%, while in the dry year, the percentage increased to 22.8%.
Another large TN contributor in LHC sub-basin was the Transportation and communication landuse category. It accounted for 16.1% of the total TN loading in the wet year and 13.4% in dry year. TN loading from this landuse category was primarily from the Gainesville Regional Airport. Combined percent TN loading from all residential landuses in this basin accounted for 7.2% of the total loading in the wet year and 6.1% in the dry year. Influence from septic tanks on the TN loading appeared low. In both wet and dry years, percent TN loading from septic tanks was about 0.1%.
Percent TN loading from Agriculture was lower in LHC sub-basin than the other two sub-basins. Agriculture TN loading only accounted for 1.1% in the wet year and 0.9% in the dry year. Contributions from Rangeland and Urban open landuse categories were higher than those from the other two sub-basins. Rangeland contributed 5.0% and 4.2% TN in the wet year and dry year respectively. Urban open contributed 3.1% and 2.6% TN in wet and dry years, respectively. Although a significant change of the percent contribution from different landuse categories was observed in the LHC sub-basin, because the TN loading from this sub-basin only accounted for 15% to 17% of the TN loading from the entire Newnans Lake watershed, changes of the percent distribution within the LHC sub-basin should not influence the overall pattern of the TN loading from the watershed to the lake.
Distribution of percent TP loading from different landuse categories within all sub-basins followed the general pattern of percent TN loading (Figure 16 and 17). However, some differences are noted below. The TP loading from baseflow accounted for a significant portion of the total TP loading in all three sub-basins. In the wet year, baseflow accounted for 23.5%, 17.7%, and 17.7% for HC, LHC, and NL sub-basins respectively. In the dry year, it accounted for 21.1%, 9.0% and 15.8% for the three sub-basins respectively. Like the percent TN loading from the point source, percent TP loading from the point source comprises of a significant portion of the total TP loading in LHC sub-basin and its percentage of the total was greatly influenced by the annual precipitation. In the wet year, TP loading from the point source accounted for about 5.4% of the total TP loading from the sub-basin. In the dry year, however, the percent contribution from the point source jumped to about 46.0% and became one of the major sources of TP contributors in LHC sub-basin.56 Atmospheric loading of TN and TP into Newnans Lake
One source of TN and TP loading to Newnans Lake that was not considered by WMM was the TN and TP falling directly into Newnans Lake th rough precipitation. In this study, atmospheric loading of TN and TP was calculated by multiplying the amount of precipitation directly falling on to the lake surface (calculated by multiplying annual precipitation by surface area of the lake) by the TN and TP concentration of the rainfall. Because no data for the TN and TP concentration of rainfall was available for the project area, published values were used in this study, which were 0.1 mg/L and 0.05 mg/L for TN and TP respectively (Stites, et al 2001). Calculated annual TN and TP loadings are tabulated in Table 26. Table 26. Atmosphere loading of TN and TP into Newnans Lake Unit: lbs/year
TN TP
1996 7802 3901
1997 8048 4024
1998 7133 3567
1999 5039 2520
2000 4208 2104
Mean 6446 3223

SE 770 385
CV 12% 12%

5.3 Establishing the relationship between TN and TP loading and in-lake TN, TP, and Chla concentrations
Input and output analysis on TN and TP dynamics of Newnans Lake
Before the Bathtub eutrophication model could be used to establish a relationship between TN and TP loadings to the lake and the in-lake TN, TP, and Chla concentrations, other possible sources of TN and TP needed to be considered. In this study, one specific concern was whether internal recycling of nutrients was significant, and as such, should be included in the model.
To address this question, the TN and TP concentrations in all the sources were analyzed and compared to the TN and TP concentration of the lake and outlet stream. If the TN and TP concentrations in all the sources were significantly lower than the in-lake and outlet concentrations, an assumption of internal recycling is warranted.
Table 27 lists TN and TP concentrations of all the sources characterized in this study and the TN and TP concentrations of the lake and the outlet stream. Among these values, concentration of the water from two inlet streams and surface runoff from NL sub-basin were model predictions. These model predictions are final results after the influence from landuse patterns, baseflow input, septic tank leakage, and point sources were taken into account. Concentrations of the precipitation directly into Newnans Lake were literature-cited values57 (Stites, et al 2001). The in-lake concentration and the concentration of the outflow stream were based on measured data. Based on Table 27, TN and TP concentrations in all the sources were lower than the in-lake and outflow concentrations. Therefore, it was reasonable to include internal recycling as a process for both TN and TP in the Bathtub application.

Table 27 Comparison of TN and TP concentrati ons in all identified sources to the TN and TP concentrations of lake water and ou tflow stream. Data represent mean ± 1 SE (n=5). All the means were calculated based on either model predictions or measured data in the period from 1996 through 2000. Unit: mg/L TN TP
Hatchet Creek 0.936 ± 0.013 0.101 ± 0.001
Little Hatchet Creek 0.955 ± 0.086 0.139 ± 0.022
NL surface runoff 0.978 ± 0.012 0.111 ± 0.001 Precipitation 0.100 0.05
Newnans Lake 4.388 ± 0.887 0.158 ± 0.036
Prairie Creek 4.030 ± 1.103 0.172 ± 0.056

Data required for calibrating Bathtub eutrophication model
The relationship between TN and TP loading and the in-lake TN and TP concentrations was established through fitting the Bathtub predictions with the measured TN and TP concentrations of the lake. To calibrate the model, the following data were required: 1. Physical characteristics of the lake (surface area, mean depth, and mixed layer depth) 2. Meteorological data (precipitation and evaporation) 3. Measured water quality data (TN, TP, a nd Chla concentrations of the lake water) 4. Loading data (flow and TN and TP concentrations of the flow from various point and nonpoint sources).
Because Bathtub allows both error and variability analysis, whenever there were historical data, long-term average and coefficient of variance (CV) of the average was calculated and entered into the model as input. All the data that were required for model calibration are listed in Tables 28 through 31.

Table 28. Physical characteristics of Newnans Lake
Lake surface area Mean depth Mixed layer depth (km 2 ) (m) (m)
1996 25.50 1.55 1.55
1997 24.69 1.55 1.5558 1998 27.92 1.81 1.81
1999 23.47 1.16 1.16
2000 21.85 1.02 1.02
Mean 24.69 1.42 1.42

SE 1.02 0.14 0.14
CV 4% 10% 10%

Note: Because Newnans Lake is a shallow lake with a relatively large surface area, wind mixing is strong and thermal stratification does not form in the summer. Therefore, the “Mixed layer depth” was assumed equal to the mean depth of the lake.

Table 29. Precipitation and evaporation Unit: m/year Precipitation Evaporation
1996 1.388 1.330
1997 1.479 1.474
1998 1.159 1.587
1999 0.974 1.606
2000 0.874 1.661 Mean 1.175 1.532

SE 0.116 0.059
CV 10% 4%

Table 30. Measured TN, TP, and Chla concentrations of Newnans Lake Unit: ppb TN TP Chla
1996 3803 111 272.2
1997 3813 126 261.8
1998 2364 89 120.5
1999 4262 172 269.6
2000 7700 291 298.7
Mean 4388 158 245.0

SE 888 36 32.0
CV 20% 23% 13%59 Table 31. Flow and TN and TP concentrations of different sources

Flow TN TP
mean SE CV Mean SE CV Mean SE CV

(hm 3 /yr) (ppb) (ppb) Forest/Rural Open 9.68 3.25 34% 1326.2 0.0 0% 83.00 0.001 0.0% Urban Open 0.60 0.20 34% 823.0 0.4 0% 83.60 0.079 0.1% Agricultural 0.96 0.32 34% 1686.1 0.3 0% 245.93 0.095 0.0% Low density residential 1.25 0.42 34% 1288.6 0.1 0% 140.91 0.017 0.0% Medium density residential 0.85 0.28 34% 1627.3 0.2 0% 203.13 0.046 0.0% High density residential 0.12 0.04 34% 1684.4 0.7 0% 273.64 0.254 0.1% Transportation, Communications, and Utilities 0.98 0.33 34% 1393.4 0.2 0% 170.48 0.045 0.0%

Rangeland 0.56 0.19 34% 1625.7 0.2 0% 246.85 0.085 0.0%
Water/Wetlands 11.86 3.98 34% 1155.0 0.0 0% 117.39 0.001 0.0%
Baseflow 13.81 4.74 34% 220.0 0.0 0% 60.00 0.000 0.0%
Point source 0.03 0.00 4% 9912 3072 31% 2182.01 41.65 1.9%

Note: a) Bathtub does not allow direct input of loading. Therefore, data presented here are flow and TN and TP concentration of the flow. b) Flows for each source presented are calculated by aggregating individual flows from all the three sub-basins (Hatchet Creek, Little Hatchet Creek, and Newnans Lake sub-basin) and then averaging throughout the period from 1996 to 2000. c) TN and TP concentrations presented for each source were calculated by adding TN and TP loadings from all the three sub-basins (Hatchet Creek, Little Hatchet Creek, and Newnans Lake sub-basin), dividing the sum by the total flow over all the three sub-basins, and then averaging throughout the period from 1996 to 2000.
Calibrating the Bathtub eutrophication model
To calibrate the model, each source of TN and TP was designated as an independent tributary. Flow and TN and TP concentrations of the flow were defined for each tributary as listed in Table 30. The TN flux from the sediment is not defined in Table 30 because in Bathtub, internal recycling is characterized differently from regular point and nonpoint sources. Instead of being defined by flow and the pollutant concentration of the flow, internal recycling is expressed as a sediment releasing rate. Because information on internal recycling of TN and TP were not available for Newnans Lake, a TP rate of 0.665 mg P/m 2 /day determined in a study conducted at Lake Okeechobee (James and Bierman 1995) was us ed in this study. The TN rate used in this study was 11.3 mg N/m 2 /day. This value was calculated by multiplying the TP rate by 17,60 which is the sediment TN/TP ratio of Newnans Lake characterized by Brenner and Whitmore (1998).
Bathtub provides alternative models for estimating the influence of sedimentation on the in-lake TN and TP concentrations. In this study, th e settling velocity model was chosen for both TN and TP. This model assumes that the sedimentation of TN and TP is in first-order kinetics and should linearly correlate with the in-lake TN and TP concentration. The model also assumes that the sedimentation is influenced by the dept h of the lake. The deeper the lake, the slower the sedimentation. This model fit the condition of Newnans Lake because the lake is relatively shallow and large in surface area. Continued wind mixing prevents the lake from forming thermal stratification, which would otherwise prevent the particles from being re-suspended once settled down to the bottom. Continued wind mixing through the entire water column also reduces particle settling rate by continuously bringing the settled particle back in to water column. These processes produce a relatively low settling rate in Newnans Lake. Other sedimentation models provided by Bathtub assume second-order kinetics, which fit reasonably well with lakes that form thermal stratification during the summer. However, these models would overestimate the sedimentation of Newnans Lake, and in turn cause underestimation of the in-lake TN and TP concentration.
Bathtub provides two chlorophyll a responding models based on the assumption of nitrogen andphosphorus co-limitation: Model 1 and 3. Model 1 assumes that algal communities are colimited not only by nitrogen and phosphorus, but also by light intensity. This model seemed to fit the situation for Newnans Lake because the lake had a very high chlorophyll concentration, which would be expected to lead to self-shading. However, application of this model yielded Chla concentrations much lower than the measured data. Therefore, in simulating Chla response, Model 3 was used. This model assumes that the primary production of the lake was co-limited by nitrogen and phosphorus, but not by light intensity (Walker 1999). This could be the case in Newnans Lake because the lake is large and shallow. Wind mixing could constantly stir the entire water column and bring the algal cells in the deeper water up to the surface so that no cells would be permanently shaded. Using this model, a reasonable fit between predicted and measured Chla was achieved.
Calibration factors were applied to fit TN and TP predictions to the measured data. Two calibration methods are provided by Bathtub for phosphorus and nitrogen: Method 0 calibrates decay rates and Method 1 calibrates concentration. In the first case, the calibration factors are applied to estimated sedimentation rates in computing nutrient balances. In the second case, the factors are applied to estimated concentrations. In Method 0, it is assumed that the error is attributed primarily to the sedimentation model. In Method 1, the error source is unspecified (some combination of input error and sedimentation model error). The latter may be used when predicted nutrient profiles are insensitive to erro rs in predicted sedimentation rate because the mass balance is dominated by inflow and outflow terms (low hydraulic residence times) (Walker 1999). In this study, because wind mixing could significant lower the sedimentation rate over the default sedimentation rate (based on data from lakes that form thermal stratification), it was assumed that the error of the model predictions came mainly from the error associated with the sedimentation model. Therefore, Method 0 was adopt ed in this study to calibrate the decay rate due to the sedimentation. Typical calibrat ion factors for TN and TP recommended by the Bathtub user’s manual are 0.5 – 2.0 for TP and 0. 33 – 3 for TN. In this study, 0.5 and 2 were used for calibrating TP and TN, respectively. Re sults of model calibration are shown in Table 32.61 Table 32. Bathtub calibration results

Measured Estimated Error T statistics
Mean CV mean CV 1 2 3 TP (mg/l) 0.158 0.23 0.160 0.38 1% -0.07 -0.06 -0.04 TN (mg/l) 4.39 0.20 4.34 0.55 1% 0.05 0.04 0.02 Chla (μg/l) 245 0.13 243 0.54 1% 0.05 0.02 0.01

Bathtub provides for statisti cal comparisons between observed and predicted concentrations. These are computed using three alternative measures of error: observed error only, T(1); error typical of model development data set, T(2); and observed and predicted error, T(3). Tests of model applicability are normally based upon T(2) and T(3). If their absolute values exceed 2 for the comparison of area-weighted mean concentrations, there is less than a 5% chance that nutrient sedimentation dynamics in the reservoir are typical of those in the model development data set. This assumes that input condition s have been specified in an unbiased manner. Once an appropriate sedimentation model is sele cted, T(1) can be used as a basis for deciding whether calibration is appropriate. If the absolute value of T(1) exceeds 2, then there is less than a 5% chance that the observed and predicted means are equal, given the error in the observed mean (Walker 1999). In this case, no T value for TN, TP and Chla predictions was higher than 2. Therefore, the model was considered calibrated properly.
TSI from Bathtub predictions vs. TSI based on measured data

The TSI was calculated based on Bathtub estimated TN, TP, and Chla concentrations. Because the mean values of model predictions for TN, TP, and Chla all have associated CV values estimated by Bathtub (Table 32), TSIs calculated based on model estimated TN, TP, and Chla include the mean, the maximum possible value, and the minimum possible value (Table 33).

Table 33. TSI calculated based on model pr edicted and measured TN, TP, and Chla concentrations
TSI calculated based on model predictions TSI calculated based on measured data Mean 88 89
Maximum 95 91
Minimum 76 87

As shown in Table 33, the mean predicted TSI is very similar to measured values and the range of TSIs calculated based on model estimated TN, TP, and Chla appeared to overlap with the

mean ± 1 SE of the TSIs calculated based on measured data. Therefore the model predications were considered adequate estimates of measured values. Table 33 also indicates that the TSI calculated based on model estimated TN, TP, and Chla concentrations had a range of 19 TSI units

.62 Evaluation of influence from the internal re cycling on the trophic status of Newnans Lake
In addition to calibrating the model, the significance of internal recycling of TN and TP during the verified period on the trophic status of Newnans Lake was examined in this study. No data were available on sediment TN and TP levels during the verified period or on how the rate of translocation of TN and TP from the sediment in to the water column correlate with sediment TN and TP in this lake over this period. Given the lack of this information, the importance of the TN and TP internal recycling was examined by com paring the current TSI to the TSI calculated under the situation that the internal recycling of TN and TP was completely eliminated. All the calibrated model parameters were kept the same during the calculation except that the TN and TP sediment flux rate was reset to 0. Additionally, when calculating the TSI, the CVs associated with the TN, TP, and Chla concentrations were all kept the same. The model estimated TN, TP, and Chla concentrations without loadings from internal recycling and the TSI calculated based on these data are listed in Table 34.

Table 34. TN, TP, Chla, and TSI values after nutrient loading from the internal recycling was eliminated

Current model estimates Estimate without internal recycling
Mean CV Mean CV TP (mg/l) 0.160 0.38 0.069 0.38 TN (mg/l) 4.34 0.55 1.00 0.55 Chla (μg/l) 243 0.54 63.4 0.54
Mean TSI 88 67.4
Max TSI 95 74.2
Min TSI 76 55.6

As Table 33 shows, by completely removing the TN and TP loading from internal recycling from Bathtub, TN in the lake drops 77% from 4.34 mg/l to 1.00 mg/l. Considering the 55% CV associated with the result, the TN concentration returned to its level in the late 1980s and early 1990s. The same thing happened to the TP concentration, although in a relatively milder way. It drops about 56% from 0.160 mg/l to 0.069 mg/l, returning to its level around the late 1980s and early 1990s. The Chla concentration dropped 74%, from the current 243 μg/l to about 63.4 μg/l. The mean TSI value calculated based on the TN, TP, and Chla concentrations after the loading from internal recycling was totally removed was 67.4. Due to the CV associated with TN, TP, and Chla concentrations, the calculated TSI had a range from 55.6 to 74.2, which was not significantly different from the TSI level at late 1980s and early 1990s.

When the model simulation was run with the TN an d TP loadings from inte rnal recycling set to 0, the TN and TP ratio was checked to ensure that it did not violate the assumptions of the calibrated model. The ratio should be between 10 and 30 so that the algal community of the lake was still under the co-limitation by phosphorus and nitrogen. The TN/TP ratio after we assumed 0 loading from internal recycling was ab out 16, which met the model assumption. This ratio was also similar to the TN/TP ratio around late 1980s and early 1990s, indicating a situation approaching nitrogen limitation.63 Evaluating the Natural Background TSI of Newnans Lake
The background TN and TP loading without the loadings generated from the existing level of human activities were estimated using the following procedures: 1. The loadings from internal recycling of TN and TP were completely removed. 2. All the man-made landuse categories (Urban open, Agricultural, Low-density residential, Medium density residential, High density resi dential, Transportation and communication, and Rangeland) in all the three sub-basins were evaluated as Forest/rural open. All the loadings from septic tanks and point sources were also removed. 3. TN and TP loadings through surface runoff were then estimated using the calibrated WMM, a long-term average precipitation of 13.6 inches/year (adjusted with P 0 ), and a long-term average areal baseflow of 1.8 inches/year. 4. Flow of Forest/rural open, Water/wetland, and baseflow from all the three sub-basins including HC, LHC, and NL were then aggregated. 5. TN and TP concentrations from Forest/rural open, Water/wetland, and baseflow were calculated by dividing the total loadings from the three sub-basins by the total flow from the three sub-basins (Table 35).

Table 35. Flow and TN and TP concentrations of surface runoff from Forest/rural open, Water/wetland, and Baseflow

Flow TN concentration TP concentration (Hm 3 /year) (ppb) (ppb) Forest/rural open 13.36 1321.48 82.67
Water/wetland 11.86 1152.54 116.97
Baseflow 13.81 220.00 60.00

6. The flow and TN and TP concentration of surface runoffs from Forest/rural open, Water/wetland, and baseflow were then entered into Bathtub to estimate the in-lake TN, TP, and Chla concentrations. 7. The TSI was calculated based on the predicted TN, TP, and Chla concentrations. This TSI was considered the natural background TSI of Newnans Lake and any further reduction of the TSI of the lake by additional reductions in the loadings was not considered. The resulting TN, TP, and Chla concentration and TSI are listed in Table 36.

Table 36. TN, TP, and Chla concentrations an d TSI after all the human landuse categories and loadings from internal recycling were removed TP (mg/l) 0.060 TN (mg/l) 0.936
TN/TP 16 Chla (μg/l) 54.9
Mean TSI 65.464 Max TSI 72.1
Min TSI 53.5

As shown in Table 36, TN, TP, and Chla concentrations decreased an additional 5%, 13%, and 13%, respectively, when all the loadings from human landuse categories were removed compared to the model estimates when the loadings from internal recycling were totally removed without changing the current landuse pattern (Table 34). Mean TSI value decreased from 67.4 to 65.4, about 3% lower than before the loadings from human influences were completely removed.
Determination of Assimilative Capacity
As mentioned previously, the IWR thresholds for nutrient impairment in lakes was used as the water quality target for the lake. Rule 62-303.352(1), FAC, specifies for lakes with an average color of 60 or greater that the annual average TSI should be 60 or less, unless paleolimnological information indicates the annual average natural TSI of the lake was greater than 60. Based on results contained in Brenner and Whitmore 1998, the range of diatom-inferred TP concentrations for historical lake water quality in Newnans Lake is 0.036 to 0.077 mg/L. The paleolimnological results did not address TN and Chla concentrations so that a TSI could not be calculated from the published data. However, model estimates for the natural background annual average TSI ranged between 54.9 and 72.1 (mean of 65.4) and the predicted TP concentration for the natural background condition was 0.06 mg/L. Because the natural background TP determined by modeling is within the range of natural background TP determined by the paleolimnological study, use of the natural background TSI determined from the modeling is acceptable evidence that the natural background TSI of the lake was greater than 60. Therefore, maintaining the TSI of the Lake within the range of TSIs established as natural background became the target for the load allocation component of the TMDL.
The TN and TP loadings from major sources to Newnans Lake during the period of this study are listed in Table 38. The total annual average loadings to the Lake for the current condition are 315,510 lbs/year for TN and 25,732 lbs/year for TP. To evaluate natural background, the impact of loadings from all human based nonpoint sources were removed by resetting the landuses to Forest/open and all the loadings from septic tanks were removed. The loadings from this scenario became the natural background case. The annual TN and TP loadings to the lake dropped to 85,470 lbs/year and 10,924 lbs/year, respectively. This represents a 74% reduction of TN and a 59% reduction of TP loadings. After this loading reduction is achieved, the TSI of the lake is predicted to decrease to about 65 (with a range from 53 to 72). Because 65 is the natural background condition of the lake, no further reduction in loading was considered necessary in this study. The total allowable loading (assimilative capacity) is 10,924 lbs/year for TP and 85470 lbs/year for TN. This corresponds to reductions from the existing loadings of 74 percent for TN and 59 percent for TP.



### 6.0 Determination of TMDL
The objective of a TMDL is to allocate loads among all of the known pollutant sources throughout a watershed so that appropriate control measures can be implemented and water quality standards achieved. A TMDL has historic ally been expressed as the sum of all point source loads (Waste Load Allocations), nonpoint source loads (Load allocations), and an65 appropriate margin of safety (MOS), which takes into account any uncertainty concerning the relationship between effluent limitations and water quality:

TMDL = ∑

 WLAs + ∑

 LAs + MOS
This equation has changed slightly in response to the evolution of the NPDES Stormwater Program, such that the WLA has been broken out into separate subcategories for wastewater discharges and stormwater discharges:

TMDL ≅ ∑

 WLAs wastewater + ∑

 WLAs stormwater + ∑

 LAs + MOS
It should be noted that, in this modified equat ion, the various components of the TMDL may not sum up to the value of the TMDL because a) the WLA for stormwater is typically based on the percent reduction needed for all nonpoint sources and is accounted for within the LA, and b) TMDL components can be expressed in different terms [for example, the WLA for stormwater is typically expressed as a percent reduction and the WLA for wastewater is typically expressed as a mass per day].
WLAs for stormwater discharges are typically ex pressed as “percent reduction” because it is very difficult to quantify the loads from MS4s (given the numerous discharge points) and to distinguish loads from MS4s from other nonp oint sources (given the nature of stormwater transport). The permitting of stormwater discharges is also different than the permitting of most wastewater point sources. Because stormwater discharges cannot be centrally collected, monitored and treated, they are not subject to the same types of effluent limitations as wastewater facilities and are instead required to meet a performance standard of providing treatment to the “maximum extent practical” through the implementation of Best Management Practices.
This new approach is consistent with federal regul ations [40 CFR § 130.2(I)], which state that TMDLs can be expressed in terms of mass per time (e.g. pounds per day), toxicity, or other appropriate measure . The TMDL for Newnans Lake (Table 37) is expressed in terms of pounds per year and percent reduction.


### Table 37 TMDL Components

WLA
WBID Parameter Wastewater (lbs/year) Stormwater LA (lbs/year) MOS TMDL (lbs/year) Percent Reduction

2705B TN 3,104 NA 82,366 Implicit 85,470 74

2705B TP 386 NA 10,538 Implicit 10,924 59



### 6.1 Load Allocation

The allowable LA is 10,538 lbs/year for TP and 82,366 lbs/year for TN. This corresponds to reductions from the existing loadings of 74 perc ent for TN and 59 percent for TP. It should be noted that the LA allocation includes loading from stormwater discharges regulated by the66 Department and the Water Management Districts that are not part of the National Pollutant Discharge Elimination System (NPDES) Stormwater Program (see Appendix A).
The Department recognizes that the absolute value of these loading numbers may be significantly different from the absolute loads calculated by other models, based on analysis using data from other sources, us e of different assumptions, and/or differing interpretation of the results of other researchers. However, the Department is very confident in the relative percent load reductions required to return the lake to a healthy condition and the estimated concentrations of TN (0.97 mg/L), TP (0.062 mg/L), and Chla (57.6 ug/L) that would be expected in a healthy Newnans Lake.

6.2 WasteLoad Allocation
NPDES Stormwater Discharges
As noted in Sections 4 and 6.1, load from stormwater discharges permitted under the NPDES Stormwater Program are placed in the WLA, rath er than the LA. This includes loads from municipal separate storm sewer systems (MS4). However, based on the information provided by EPA, no MS4 area was found overlapping the Newnans Lake watershed and no stormwater loads were assigned to the WLA.
NPDES Wastewater Discharges
To evaluate the impact of the point source in the basin, additional model runs were made for natural background under average, wet, and dry years with the point source added back in at the maximum permit limits and modeled as if it discharged directly to the lake. The results are shown in Table 38. Under critical conditions (dry year), the point source would increase the TSI of the lake from 62 to 64, with an increase in Ch la concentrations of 6.6 ug/L (from 40.4 to 47.0 ug/L). This TSI of 64 under critical conditions for the point source is still under the mean TSI of 65.4. Under average natural background conditions, the point source would increase the TSI of the lake by less than 1 TSI unit from 65.4 to about 65.7 (rounded to 65 and 66). This would increase the Chla concentration in the lake by only 2.7 ug/L. Under wet year conditions there was no change in the TSI of the Lake by the addition of the point source and Chla only increased by 1.5 ug/L.
Given the small projected changes in TSI and Chla and that the point source was evaluated as if it discharged directly into the lake with no consideration of any assimilation that might occur in Little Hatchet Creek, the Department concluded t hat the facility as currently permitted will not cause or contribute to violations of state water quality standards in Newnans Lake. Therefore no reduction in the loadings from the facility are warranted. As no load reductions are proposed for the point source, Brittany Estates loadings are set at 386 lbs/year for TP and 3,104 lbs/year for TN.
6.3 Margin of Safety


### By setting the target TSI as natural background, the Department is using the difference between natura l background and the loadi ng capacity as defined by EPA regulation (40 C.F.R. 130.2(f)) as part of the implicit margin of sa fety. EPA defines the loading capacity as the greatest amount of a pollutant that a water can receive without violating water quality standards. Additional implicit margin of safety exists due to conservative67 

### assumptions used in the modeling process. For example, it was assumed that 100 percent of the loadings from the single point source were transported by Little Hatchet Creek into the lake.

7.0 Evaluation of TMDL on Un ionized Ammonia in Newnans Lake
Newnans Lake was placed on the Planning List for Unionized Ammonia following the procedures established in Rule 62-303, FAC. While not verified as impaired for this parameter, the impact on unionized ammonia of reducing TN as a part of the nutrient TMDL was examined. The mean TN concentration for the verified period is 4.34 mg/L. The annual average concentration of TN in the Lake once the TMDL is achieved has been calculated as 0.94 mg/L. The current ratio between total ammonia and TN is 0.06 (based on the quarterly means from 1989 – 2000). Based on this ratio, the annual average total ammonia concentration in the Lakeafter the TMDL is achieved was calculated as (0.94 * 0.06) 0.06 mg/L. The current ratio of unionized ammonia to TN is 0.01 (based on the quarterly means from 1989 – 2000). Based on this ratio, the annual average un-ionized ammonia concentration in the Lake after the TMDL is achieved was calculated as (0.94 * 0.01) 0.01 mg/L. This value is below the un-ionized ammonia criterion of 0.02 mg/L specified in Rule 62-302.530, FAC. This indicates that under the TMDL for TN, the Lake the annual average un-ionized ammonia concentration will meet water quality standards.

8.0 NEXT STEPS: IMPLEMENTATION PLAN DEVELOPMENT AND BEYOND
Following adoption of this TMDL by rule, the next step in the TMDL process is to develop an implementation plan for the TMDL, which will be a component of the Basin Management Action Plan for the Newnans Lake Basin. This document will be developed in cooperation with local stakeholders and will attempt to reach consensus on more detailed allocations and on how load reductions will be accomplished.
The Basin Management Action Plan (B-MAP) will include:

o Allocations among the affected parties.

o A description of the load reduction activities to be undertaken.

o Timetables for project implementation and completion.

o Funding mechanisms that may be utilized.

o Any applicable signed agreements.

o Local ordinances defining actions to be taken or prohibited.

o Local water quality standards, permits, or load limitation agreements.

o Monitoring and follow-up measures.
It should be noted that TMDL development and im plementation is an iterative process, and this TMDL will be re-evaluated during the BMAP development process and subsequent Watershed Management cycles. The Department acknowledges the uncertainty associated with TMDL development and allocation, particularly in estimates of nonpoint source loads and allocations for NPDES stormwater discharges, and fully expects that it may be further refined or revised over time. If any changes in the estimate of the assimilative capaci ty AND/OR allocation between point and nonpoint sources are required, the rule adopting this TMDL will be revised, thereby providing a point of entry for interested parties.68Table 38 Source Evaluation Critical ConditionsAverage = long-term average rainfall, NB = Natural Background, @E = existing condition, PS = Point SourceCurrentConditionAverageNBAverageNB +PS @EAverageNB + PS @Permit limitsAverageNBWet YearNB + PS @EWet YearNB + PS@PermitlimitsWet YearNBDry YearNB + PS @EDry YearNB + PS @Permit LimitsDry YearTP annual load (kg/year)Precipitation 1450 1450 145014501826 1826 1826 1079 1079 1079Watershed 3997 3330 333033306307 6307 6307 422 422 422Point source 66 0 661750 66 175 0 66 175Internalrecycling6114 0 000 0 0 0 0 0total loading 11627 4780 484549548133 8199 8308 1501 1566 1675TN annual Load (kg/year)Precipitation 2900 2900 290029003652 3652 3652 2158 2158 2158Watershed 37164 34461 344613446164932 64932 64932 4441 4441 4441Point source 297 0 29714080 297 1408 0 297 1408Internalrecycling102751 0 000 0 0 0 0 0total loading 143113 37361 376593876968584 68881 69992 6599 6897 8007Water QualityTP (mg/L) 0.160 0.060 0.0610.0620.063 0.063 0.064 0.040 0.042 0.044TN (mg/L) 4.34 0.94 0.940.970.80 0.81 0.82 0.97 1.00 1.15TN/TP 27 16 151613 13 13 24 24 2667Chla 243.0 54.9 55.757.650.0 50.4 51.5 40.4 42.5 47.0TSI 88 65 666665 65 65 62 62 6468 

### 9.0 Recommendations
Prior to formally allocating nonpoint source load reductions to specific areas or landuses, additional information regarding the quality and quantity of water reaching the lake and its point of origin are needed. Additional data are required to improve model estimates of the water and nutrient budgets for the basin and the lake. The Department plans to continue to work closely with the SJRWMD and other interested parties to produce an accurate accounting of the sources of the nutrients that are currently impacting the lake before load reductions are allocated. The overall strategy should include studies and efforts that focus on determining if control or removal of loadings generated by internal recycling of TN and TP would significantly decrease the time it would take for the Lake to return to a more natural condition.69 

### REFERENCES
Basin Status Report. 2001. Ocklawaha. Di vision of Water Resource Management, Florida Department of Environmental Protection

Brenner, M. and T. J. Whitmore. 1998. Hist orical sediment and nutrient accumulation rates and past water quality in Newnans Lake. Final Report for St. Johns. River Water Management District.
Brown, M. T. 1995. South Dade Watershed Project. University of Miami/SWFWMD
Canfield, D. E. Jr. 1981. Chemical and trophic state characteristics of lakes in relation to regional geology. Final report submitted to Coop. Fish and Wildlife Research Unit, University of Florida: 444 pp.
CDM. 1990. Point and non-point source loading assessment, phase I. Report to Sarasota Bay Nation al Estuary Program.
Clark, W., R. Musgrove, C. Menke, and J. Cagle. 1964. Interim report on the water resources of Alachua, Bradford, Clay, and Union counties, Florida. Florida Geological Inform. Circular # 35, State Board of Conservation, Division of Geology, Tallahassee, Florida: 170 pp.
Copeland, R., T. Gardner, J. Craft, W. Schmidt, C. M. Browner, H. L. Rhodes, and C. C. Aller. 1991. Florida’s ground water quality monitoring program hydrogeological framework. Department of Environmental Regulation.
Gido, K. B. 2002. Interspecific comparisons and potential importance of nutrient excretion by benthic fishes in a large reservoir. Transactions of the American Fisheries Society 131 : 260 – 270.
Gottgens, J. F. and C. L. Montague. 1987. Orange, Lochloosa and Newnans Lakes, a survey and preliminary interpretation of environmental research data. Special Publication SJ 87-SP3, Department of Environmental Engineering Sciences, A. P. Black Hall, University of Florida, Gainesville, FL.
Harper, H. H. 1994. Stormwater loading rate parameters for central and south Florida. Environmental Research & Design, Inc.
Harper, H. H. and E. H. Livingston. 1999. Everything you always wanted to know about stormwater management practices but were afraid to ask. Biennial Stormwater Research Conference, Tampa, Florida.
Holly, J. B. 1976. Stratigraphy and sedimentary history of Newnans lake. M. S. thesis, university of Florida: 102 p.
James, R. T. and V. J. Bierman Jr. 1995. A preliminary modeling analysis of water quality in lake Okeechobee, Florida: Calibration results. Water Research 29 : 2755 – 2766.70 

### Linsley, R. U., and J. B. Franzini. 19 97. Water Resources Engineering, McGrow-Hill Book Co.
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Robison, C. P., G. B. Hall, C. Ware, and R. B. Hupalo. 1997. Water management alternatives: effects on lake levels and wetlands in the Orange Creek basin. Appendixes. Page 15. Special publication SJ97-SP8. St. Johns River Water Management District.
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Sloto, R. A. and M. Y. Crouse. 1996. HYSEP: A computer prog ram for streamflow hydrograph separation and analysis: U.S. Geological Survey Water-Resources Investigations Report 96-4040.
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Stites, D. L., M. Coveney, L. Battoe, E. Lowe, and V. Hoge. 2001. An external phosphorus budget for Lake Apopka, 1989-1994. Division of Environmental Sciences, Department of Water Resources, St. Johns River Water Management district, Palatka, Florida.
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Viessman, W. Jr., G. L. Lewis, and J. W. Knapp. 1989. Introduction to hydrology. 3 rd 

### edition. Harper Collins Publ isher. New York. Page 160.
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### Appendix A
In 1982, Florida became the first state in the country to implement statewide regulations to address the issue of nonpoint source pollution by requiring new development and redevelopment to treat stormwater before it is discharged. The Stormwater Rule, as outlined in Chapter 403 Florida Statutes (F.S.), was established as a technology-based program that relies upon the implementation of BMPs that are designed to achieve a specific level of treatment (i.e., performance standards) as set forth in Chapter 62-40, Florida Administrative Code (F.A.C.).
The rule requires Water Management Districts (WMDs) to establish stormwater pollutant load reduction goals (PLRGs) and adopt them as part of a SWIM plan, other watershed plan, or rule. Stormwater PLRGs are a major component of the load allocation part of a TMDL. To date, stormwater PLRGs have been established for Tampa Bay, Lake Thonotosassa, Winter Haven Chain of Lakes, the Everglades, Lake Okeechobee, and Lake Apopka. No PLRG has been developed for Newnans Lake at the time this study was conducted.
In 1987, the U.S. Congress established section 402(p) as part of the Federal Clean Water Act Reauthorization. This section of the law amended the scope of the federal NPDES to designate certain stormwater dischar ges as “point sources” of pollution. These stormwater discharges include certain discharges that are associated with industrial activities designated by specific Standard Industrial Classification (SIC) codes, construction sites disturbing five or more acres of land, and master drainage systems of local governments with a population above 100,000 [which are better known as “municipal separate storm sewer systems” (MS4s)]. However, because the master drainage systems of most local government s in Florida are interconnected, EPA has implemented the MS4 permitting program on a county-wide basis, which brings in all cities (incorporated areas), Chapter 298 urban water control districts, and the DOT (Department of Transportation) throughout the 15 counties meeting the population criteria.
An important difference between the EPA and the state stormwater permitting programs is that the EPA program covers existing di scharges while the state program focuses on new discharges. Additionally, Phase 2 of the NPDES stormwater permitting program will expand the need for these permits to construction sites between one and five acres, and to local governments with as few as 10,000 people. These revised rules require that these additional activities obtain permits by 2003. While these urban stormwater discharges are now technically referred to as “point sources” for the purpose of regulation, they are still diffuse sources of po llution that can not be easily collected and treated by a central treatment facility similar to other point sources of pollution, such as domestic and industrial wastewater discharges. The DEP recently accepted delegation from EPA for the stormwater part of the NPD ES program. It should be noted that most MS4 permits issued by EPA in Florida includ e a reopener clause that allows permit revisions to implement TMDLs once they are formally adopted by rule.