Final Nutrient Total Maximum Daily Load 

For Newnans Lake, 

Alachua County, Florida 

Xueqing Gao and Douglas Gilbert 

Watershed Assessment Section 

Florida Department of Environmental Protection 

2600 Blair Stone Road, MS 3555 

Tallahassee, FL 32399-2400 

September 22, 2003 
 

i

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 and 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 water quantity calibration........... 36 

WMM Flow Calibration.................................................................. 39 

WMM calibration and Simulation of Watershed Loadings............. 41 

Atmospheric Loading to the Lake.................................................. 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................................................................................................ 71 
 

ii

List of Figures 

Figure 1 General Location of Watershed.................................................. 3 

Figure 2 Newnans Lake Sub-basins......................................................... 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 runoff and precipitation........................... 38 

Figure 12 Correlation between Baseflow 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 Landuse.... 53 
 

iii

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 Variation 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 Landuses 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 discharge, 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 Loadings by Landuse................................ 45 

Table 23 1997 Sub-basin TN Loadings by Landuse................................ 45 

Table 23 1998 Sub-basin TN Loadings by Landuse................................ 46 

Table 23 1999 Sub-basin TN Loadings by Landuse................................ 46 

Table 23 2000 Sub-basin TN Loadings by Landuse................................ 47 

Table 24 1996 Sub-basin TP Loadings by Landuse................................ 47 

Table 24 1997 Sub-basin TP Loadings by Landuse................................ 48 

Table 24 1998 Sub-basin TP Loadings by Landuse................................ 48 

Table 24 1999 Sub-basin TP Loadings by Landuse................................ 49 

Table 24 2000 Sub-basin TP Loadings by Landuse................................ 49 

Table 25 1996-2000 Percent 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 Concentrations of Lake by Year......... 58 

Table 31 Flow, TN, and TP Concentrations by Landuse.......................... 59 

Table 32 Bathtub Calibration Results ....................................................... 61 

Table 33 Long-Term TSI Measured vs. Predicted.................................... 61 

Table 34 TN, TP, Chla, and TSI after eliminating 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 Critical Conditions........................................ 68 
 

iv

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 Statutes, 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), Florida 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 290

38’42”, Longitude 82013’8”, 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 constructed 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 “Documentation 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.htm

 
 

3

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 needed 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 the 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 threshold 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 may 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 recognition 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 modeling to estimate the natural 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 its 
 

5

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 traditional point sources. In contrast, the term 

“nonpoint sources” was used to describe intermittent, rainfall driven, diffuse sources of pollution 

associated with everyday human activities, including 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 until 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 Creek 

sub-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. 

" ́

" ́

" ́ " ́

" ́

Hatchett Creek

LittleHatchett Creek

Prairie Creek

Newnans

Lake

HC

LHC

NL

1 0 1 2 Miles

N
 

8

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 include 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 surface 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 Sources
 

9

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 watershed management strategies on water quality (WMM 

User’s Manual: 1998). While the strength of the model 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 assumption 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) RL = [Cp + (CI – Cp) IMPL] * I 

Where: 

RL = total average annual surface runoff from land use L (in/yr); 

IMPL = fractional imperviousness of land use L; 

I = long-term average annual precipitation (in/yr); 

CP = pervious area runoff coefficient; and 

CI = 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 ML is computed for each land use L by the following equation: 

(2) ML = EMCL * RL * K 

Where: 

ML = loading factor for land use L (lbs/ac/yr); 

EMCL = event mean concentration of runoff from land use L (mg/L); EMC varies 

by land use and pollutant; 

RL = 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 area 
 

10

(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 pollutant 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 rate 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 the 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 is 

significantly 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 evaporation 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 = (CHLATSI + NUTRTSI)/2 

Where: 

CHLATSI = 16.8 + 14.4 × LN (CHLA)] 

TNTSI = 56 + [19.8 × LN(TN)] 

TN2TSI = 10 × [5.96 + 2.15 × LN(TN + 0.0001)] 

TPTSI = [18.6 × LN(TP × 1000)] –18.4 

TP2TS = 10 × [2.36 × LN(TP × 1000) – 2.38] 

The procedure addresses limiting nutrient considerations by calculating NUTRTSI: 

If TN/TP > 30 then NUTRTSI = TP2TSI

If TN/TP < 10 then NUTRTSI = TN2TSI 

If 10 < TN/TP < 30 then NUTRTSI = (TPTSI + TNTSI)/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 changes 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 water 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, and 
 

13

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 Numbering
 

14

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 calculated 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 results are listed in Table 4. 
 

15

Figure 4. Locations of water quality stations

#

#

##

#

#

# #

#

#

#

# # # #

##

#

#

#

#

#

#

#

Hatchett Creek

LittleHatchett Creek

Prairie Creek

HC

LHC

Gainesville NL

1 0 1 2 Miles

N
 

16

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 phosphorus 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 

1st quarter 3.56± 0.55 0.123± 0.018 167.4± 32.5 82± 3 

2nd quarter 3.44± 0.72 0.122± 0.019 207.1± 40.4 74± 9 

3rd quarter 2.82± 0.29 0.108± 0.017 138.0± 28.0 78± 4 
 

17

4th quarter 3.20± 0.38 0.110± 0.013 182.9± 37.5 82± 3 

Quarterly mean for the verified period 

1st quarter 4.65± 0.87 0.148± 0.034 243.7± 45.5 89± 4 

2nd quarter 4.88± 1.02 0.162± 0.028 294.1± 36.8 94± 4 

3rd quarter 3.13± 0.44 0.135± 0.031 163.8± 31.6 83± 3 

4th 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, ranging 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 observed 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 ± 2,658 
 

18

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) 

1st quarter 65.7 ± 0.4 33,383 ± 2,773 

2nd quarter 65.5 ± 0.3 31,792 ± 1,950 

3rd quarter 65.2 ± 0.3 30,083 ± 2,122 

4th 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 relatively 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 19992000

TN concentration (mg/L)

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Lake volume 

(acre-foot)

TN

Lake volume

0.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

198919901991199219931994199519961997199819992000

TP concentration (mg/L)

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Lake volume 

(acre-foot)

TP

Lake volume
 

20

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 19992000

Chla concentration (mg/L)

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Lake 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 2000

TSI

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

Lake volume 

(acre-foot)

TSI

Lake volume
 

21

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 ± 0.031 
 

22

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 concentration for the two inlet streams – Hatchet Creek 

and Little Hatchet Creek - were not significantly 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 significantly 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 historical 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 the 

late 1980s and early 1990s to about 30 in 1990s, indicating a gradual shift from nitrogenphosphorus co-limitation to phosphorus limitation. 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 increase of TN concentrations in the lake might 

not be caused solely by the current surface runoff, 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 mouth 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 

" ́

" ́

" ́ " ́

" ́

Hatchett Creek

Lower-LHC

Prairie Creek

Newnans

Lake

Lower-HC

Upper-HC

NL

02240783

02240806

02240810

02240902

Upper-LHC

Lower-LHC

02240800

1 0 1 2 Miles

N
 

25

Hatchet 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 Climate 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 

Station 
 

27

Table 9. Annual precipitation at Gainesville Regional Airport 

Year Annual Precipitation 

(in/year)

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) 

1st quarter 10.40 ± 2.53 

2nd quarter 10.47 ± 2.60 

3rd quarter 17.32 ± 1.49 

4th 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 weather 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 4188.14 
 

29

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). Using 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 impervious 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 defined in Harper’s review. Therefore, some 

extrapolations were made between the landuse categories in this study and the landuse 

categories 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 was 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 the 

watershed 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 tank 
 

34

þ

Lower-HC

Upper-HC

Lower-LHC

NL

Upper-LHC

N

6 0 6 12 Miles

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

obtained. 

Failure rate”, which defines the frequency at which 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 Well
 

35

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 includes 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 concentrations 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 2.17 
 

36

%

×

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 that 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 oversimplification 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 Park 
 

37

(4) Q = k*(P – P0) 

Where, 

Q is the surface runoff produced by a given amount of annual precipitation 

k is equivalent to [Cp + (CI – Cp) IMPL] of Equation (1), which is the runoff coefficient of 

landuse category L. 

P is the annual precipitation 

P0 is the base precipitation value below which Q is zero. 

Equation (4) can be rewritten as: 

(5) Q = k*P – k*P0

Comparing Equation (5) to Equation (1), which is 

(1) R = [Cp + (CI – Cp) IMPL] * I 

It is obvious that Equation (1) fails to take into account –k*P0, which is the portion of rainfall that 

will never contribute to surface runoff. Therefore, 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 (R2

 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*P0 of 

Equation (5). P0 was then calculated as the quotient between the intercept (k*P0 = - 9.4) and 

the slope (k = 0.29) of the correlation line and equaled 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 original 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 P0 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, P0 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 P0. 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

R2

 = 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 observations, 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

R2

 = 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 659 967 
 

41

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-basins. 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 adjusting 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 and 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, and 
 

43

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

Year

Contribution of TN (lbs/year

0

10

20

30

40

50

60

70

Annual 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

Year

Contribution of TP (lbs/year)

0

10

20

30

40

50

60

70

Annual precipitation (in/year)

New nans Lake

Little Hatchett Creek

Hatchett Creek

Annual Precipitation
 

45

Table 23. Contribution of TN from different 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/A 
 

46

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/A 
 

47

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/A 
 

48

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/A 
 

49

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/A 
 

50

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

Baseflow 18.9%

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

Baseflow 30.7%

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

Baseflow 19.1%

6.4%

Septic tank

2.9%

Medium density 

residential 

6.1%

High density 

residential

Transportation 0.7%

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 sub-watershed; C: Newnans Lake sub-watershed. 

 

A

Forest/Rural 

Open

Baseflow 25.8%

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 

High density 1.7%

residential

0.2%

Transportation 

and 

communication

1.6%

Rangeland

2.2%

B

Point source

Septic tank 5.4%

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

Transportation 1.9%

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

Baseflow 0.8%

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

Urban Open 0.9%

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 from 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 residential 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-basin 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 source 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 through 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 values 
 

57

(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 concentrations in all identified sources to the TN and 

TP concentrations of lake water and outflow 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, and 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 

(km2

) (m) (m) 

1996 25.50 1.55 1.55 

1997 24.69 1.55 1.55 
 

58

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 

(hm3/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/m2

/day determined in a study conducted 

at Lake Okeechobee (James and Bierman 1995) was used in this study. The TN rate used in 

this study was 11.3 mg N/m2

/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, the 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 depth 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 and 

phosphorus 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 errors 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 adopted in this study to calibrate the decay rate 

due to the sedimentation. Typical calibration 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. Results 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 statistical 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 conditions have been specified in an unbiased manner. 

Once an appropriate sedimentation model is selected, 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 predicted 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 recycling 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 into 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 comparing 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 and TP loadings from internal 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 about 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 residential, 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 P0), 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 

(Hm3

/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 and 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 65.4 
 

64

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 historically been expressed as the sum of all point 

source loads (Waste Load Allocations), nonpoint source loads (Load allocations), and an 
 

65

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 ≅ ∑ WLAswastewater + ∑ WLAsstormwater + ∑ LAs + MOS 

It should be noted that, in this modified equation, 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 expressed 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 nonpoint 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 regulations [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 percent for TN and 59 percent for TP. It should be 

noted that the LA allocation includes loading from stormwater discharges regulated by the 
 

66

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, use 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, rather 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 Chla 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 that 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 natural background and the loading capacity as defined by EPA regulation (40 

C.F.R. 130.2(f)) as part of the implicit margin of safety. 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 conservative 
 

67

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 Unionized 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 Lake 

after 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 implementation 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 capacity 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. 
68

Table 38 Source Evaluation Critical Conditions 

Average = long-term average rainfall, NB = Natural Background, @E = existing condition, PS = Point Source 

Current 

Condition 

Average 

NB 

Average 

NB + 

 PS @E 

Average 

NB + PS @ 

Permit limits 

Average

NB 

Wet Year 

NB + PS @E 

Wet Year 

NB + PS 

@Permit 

limits 

Wet Year 

NB 

Dry Year 

NB + PS @E 

Dry Year 

P

TP annual load (kg/year) 

Precipitation 1450 1450 1450 1450 1826 1826 1826 1079 1079 Watershed 3997 3330 3330 3330 6307 6307 6307 422 422 Point source 66 0 66 175 0 66 175 0 66 Internal recycling

6114 0 0 0 0 0 0 0 0 

total loading 11627 4780 4845 4954 8133 8199 8308 1501 1566 

TN annual Load (kg/year) 

Precipitation 2900 2900 2900 2900 3652 3652 3652 2158 2158 Watershed 37164 34461 34461 34461 64932 64932 64932 4441 4441 Point source 297 0 297 1408 0 297 1408 0 297 Internal recycling

102751 0 0 0 0 0 0 0 0 

total loading 143113 37361 37659 38769 68584 68881 69992 6599 6897 

Water Quality 

TP (mg/L) 0.160 0.060 0.061 0.062 0.063 0.063 0.064 0.040 0.042 TN (mg/L) 4.34 0.94 0.94 0.97 0.80 0.81 0.82 0.97 1.00 TN/TP 27 16 15 16 13 13 13 24 24 
67

Chla 243.0 54.9 55.7 57.6 50.0 50.4 51.5 40.4 42.5 TSI 88 65 66 66 65 65 65 62 62 
 

68

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. Division of Water Resource Management, 

Florida Department of Environmental Protection 

Brenner, M. and T. J. Whitmore. 1998. Historical 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 National 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. 1997. Water Resources Engineering, McGrow-Hill 

Book Co. 

Nordlie, F. G. 1976. Plankton communities of three central Florida lakes. Hydrobiologia 

48 (1): 65-78 

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. 

Roehl, J. W. 1962. Sediment source areas, delivery ratios, and influencing 

morphological factors. International association of Scientific Hydrology. 59: 202-

213. Symposium of Bari, October 1-8, 1962 

Schaus, M. H., M. J. Vanni, T. E. Wissing, M. T. Bremigan, J. E. Garvey, R. A. Stein. 

1997. Nitrogen and phosphorus excretion by detritivorous gizzard shad in a 

reservoir ecosystem. Limnology and Oceanography 42: 1386 – 1397. 

Sloto, R. A. and M. Y. Crouse. 1996. HYSEP: A computer program for streamflow 

hydrograph separation and analysis: U.S. Geological Survey Water-Resources 

Investigations Report 96-4040. 

St. John River Water Management District. 2002. Assessment of pollution sources in the 

Newnans Lake Watershed. 99-0128.000/Report/TOC.Doc 

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. 

User’s Manual: Watershed management model, Version 4.1 1998. Rouge River national 

wet weather demonstration project. Wayne County, Michigan. PRO-NPSTM27.02. 

Viessman, W. Jr., G. L. Lewis, and J. W. Knapp. 1989. Introduction to hydrology. 3rd

edition. Harper Collins Publisher. New York. Page 160. 

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prediction: User manual. Instruction Report W-96-2. U.S. Army Corps of 

Engineers. Washington, DC. 
 

71

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 discharges 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 governments 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 discharges 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 pollution 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 NPDES program. It should be noted that most 

MS4 permits issued by EPA in Florida include a reopener clause that allows permit 

revisions to implement TMDLs once they are formally adopted by rule.