Little Troublesome Creek TMDL final

Total Maximum Daily Load for Fecal Coliform Bacteria
to Little Troublesome Creek, North Carolina
April, 2002
Cape Fear River Basin
Prepared by:
NC Department of Environment and Natural Resources
Division of Water Quality
1617 Mail Service Center
Raleigh, NC 27699-1617
[phone]
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TABLE OF CONTENTS
1.0 Introduction … … … … … … … … … … … … … … … … … … … … … … … ….2
1.1 Watershed Description … … … … … … … … … … … … … … … … ….4
1.2 Water Quality Monitoring Program… … … … … … … … … … … … …5
1.3 Water Quality Target … … … … … … … … … … … … … … … … … …6
2.0 Source Assessment … … … … … … … … … … … … … … … … … … … … … …7
2.1 Point Source Assessment… … … … … … … … … … … … … … … … …7
2.2 Nonpoint Source Assessment….… … … … … … … … … … … … … …8
2.2.1 Livestock… … … … … … … … … … … … … … … … … … … …8
2.2.2 Miscellaneous Sources… … … … … … … … … … … … … … …9
2.2.3 Failed Septic Systems… … … … … … … … … … … … … … …..10
2.2.4 Urban Development/Sanitary Sewer Overflows… … … … ….10
2.2.5 Wildlife … … … … … … … … … … … … … … … … … … … ….14
2.3 Source Assessment Conclusion … … … … … … … … … … … … … ….15
3.0 Modeling Approach… … … … … … … … … … … … … … … … … … … … …..15
3.1 Model Framework… … … … … … … … … … … … … … … … … … ….15
3.2 Model Setup… … … … … … … … … … … … … … … … … … … … …..16
3.2.1 Instream Decay Rate … … … … … … … … … … … … … … ….17
3.3 Hydraulic Calibration… … … … … … … … … … … … … … … … … ….17
3.4 Water Quality Calibration… … … … … … … … … … … … … … … …..19
3.4.1 Prediction Uncertainty… … … … … … … … … … … … … … …20
3.4.2 Calibration Results… … … … … … … … … … … … … … … ….21
3.5 Critical Conditions… … … … … … … … … … … … … … … … … … ….24
3.6 Water Quality Model Results… … … … … … … … … … … … … … …..25
4.0 Total Maximum Daily Load… … … … … … … … … … … … … … … … … … …26
4.1 Reduction Target… … … …. … … … … … … … … … … … … … … …..27
4.1.1 Margin of Safety … … … … … … … … … … …...… …...28
4.2 Allocation … … … … … … … … … … … … … … … … ….28
4.3 Seasonal Variation … … … … … … … … … … … … … … … … …..30
5.0 Summary and Future Considerations … … … … … … … ….… … … … … …..30
5.1 Monitoring… … … … … … … … … … … … … … … … … … … … … ….30
5.2 Implementation… … … … … … … … … … … … … … … … … … … …..31
6.0 Public Participation… … … … … … … … … … … … … … … … … … … … … …31
References Cited… … … … … … … … … … … … … … … … … … … … … … … … … …32
Appendix I.Observed Data… … … … … … … … … … ….… … … … … … … … …..35
Appendix II.Model Calibration Information… … … … … … … … … … … … … ….38
Appendix III.Stream Channel Cross Sections for Subwatersheds… … … … … … …40
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Total Maximum Daily Load for fecal coliform bacteria to Little Troublesome Cr.
1.0 INTRODUCTION
On the 2000 North Carolina 303(d) list, the North Carolina Division of Water Quality
(DWQ) has identified a 5.0-mile segment (16-7b) of Little Troublesome Creek in the Cape
Fear Basin as impaired by fecal coliform bacteria. The impaired segment is located between
the Reidsville WWTP and Little Troublesome Creek’s confluence with the Haw River. This
section of the stream is located in subbasin 03-06-01 and is designated as a class C water.
Class C waters are freshwaters that are protected for secondary recreation, fishing, and
propagation and survival of aquatic life.
Section 303(d) of the Clean Water Act (CWA) requires states to develop a list of waters not
meeting water quality standards or which have impaired uses. This list, referred to as the
303(d) list, is submitted biennially to the U.S. Environmental Protection Agency (EPA) for
review. The 303(d) process requires that a Total Maximum Daily Load (TMDL) be
developed for each of the waters appearing on Part I of the 303(d) list. A TMDL is the
maximum amount of a pollutant (e.g., fecal coliform) that a waterbody can receive and still
meet water quality standards, and an allocation of that load among point and nonpoint
sources. The objective of a TMDL is to estimate allowable pollutant loads and allocate to
known sources so that actions may be taken to restore the water to its intended uses
(USEPA, 1991). Generally, the primary components of a TMDL, as identified by EPA
(1991, 2000a) and the Federal Advisory Committee are as follows:
Target identification or selection of pollutant(s) and endpoint(s) for consideration. An endpoint
is an instream numeric target. The pollutant and endpoint are generally associated
with measurable water quality related characteristics that indicate compliance with
water quality standards. North Carolina indicates known problem pollutants on the
303(d) list.
Source assessment. Sources that contribute to the impairment should be identified and loads
quantified, to the extent that that is possible.
Reduction target. Estimation or level of pollutant reduction needed to achieve water quality
goal. The level of pollution should be characterized for the waterbody, highlighting
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how current conditions deviate from the target endpoint. Generally, this component
is identified through water quality modeling.
Margin of safety. The margin of safety addresses uncertainties associated with pollutant loads,
modeling techniques, and data collection. Per EPA (2000a), the margin of safety
may be expressed explicitly as unallocated assimilative capacity (portion of TMDL)
or implicitly through conservative assumptions. The margin of safety should be
included in the reduction target
Allocation of pollutant loads. Allocating available pollutant load (TMDL), and hence pollutant
control responsibility, to the sources of impairment. The wasteload allocation
portion of the TMDL accounts for the loads associated with existing and future
point sources. The load allocation portion of the TMDL accounts for the loads
associated with existing and future nonpoint sources. Any future nonpoint source
loading should remain within the TMDL that is calculated in this assessment; in
other words, this TMDL does not leave allocation for future sources.
Seasonal variation. The TMDL should consider seasonal variation in the pollutant loads and
endpoint. Variability can arise due to streamflows, temperatures, and exceptional
events (e.g., droughts, and hurricanes).
Critical conditions. Critical conditions occur when fecal coliform levels exceed the standard by
the largest amount. If the modeled load reduction is able to meet the standard
during critical conditions, then it should meet the standard at all, or nearly all, times.
Section 303(d) of the CWA and the Water Quality Planning and Management regulation
(USEPA, 2000a) require EPA to review all TMDLs for approval or disapproval. Once EPA
approves a TMDL, then the waterbody may be moved to Part III of the 303(d) list.
Waterbodies remain on Part III of the list until compliance with water quality standards is
achieved. Where conditions are not appropriate for the development of a TMDL,
management strategies may still result in the restoration of water quality.
The goal of the TMDL program is to restore designated uses to water bodies. Thus, the
implementation of bacteria controls will be necessary to restore designated uses in Little
Troublesome Creek. Although an implementation plan is not included as part of this
TMDL, reduction strategies are needed. The involvement of local governments and
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agencies will be critical in developing an implementation plan and reduction strategies.
DWQ will seek to begin development of the implementation plan during public review of
the TMDL.
1.1 Watershed Description
Little Troublesome Creek, located in the upper Cape Fear River basin, drains into the Haw
River about fifteen miles northeast of the City of Greensboro (see Figure 1). The creek’s
watershed lies entirely within Rockingham County and is slightly less than 12 square miles in
area. The City of Reidsville (2000 population of 14,485) covers approximately the upper
half of the watershed. DWQ has an ambient water quality monitoring site (Storet number
B0160000) near the creek’s confluence with the Haw; this appears as a dot near the base of
the watershed in Figure 1.
Figure 1.
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The land use/land cover characteristics of the watershed were determined using
1996 land cover data that were developed from 1993-94 LANDSAT satellite imagery. The
North Carolina Center for Geographic Information and Analysis, in cooperation with the
NC Department of Transportation and the United States Environmental Protection Agency
Region IV Wetlands Division, contracted Earth Satellite Corporation of Rockville, Maryland
to generate comprehensive land cover data for the entire state of North Carolina. Tabulated
land cover/land use data for the Little Troublesome watershed are shown in Table 1.
During the formation of this geographic dataset, developed land was identified using the
proportion of synthetic cover present; low density developed was 50-80% synthetic cover,
and high density developed was 80-100% synthetic cover (Earth Satellite Corporation, 1997).
Assuming that synthetic cover is impervious, and that all non-developed land cover classes
have 1% impervious cover, the Little Troublesome Cr. watershed is estimated to have 9-13%
impervious surface.
Table 1. Land use/land cover in Little Troublesome Cr. watershed.
Land Use/Land Cover Little Troublesome Cr. Watershed Acres
High Density Developed 389 (5.2%)
Low Density Developed 644 (8.6%)
Cultivated 189 (2.5%)
Managed Herbaceous 1895 (25.4%)
Forest 4329 (58.1%)
Total 7446
The USGS 14-digit hydrologic unit code (HUC) for Little Troublesome Cr. is
03030002010030.
1.2 Water Quality Monitoring Program
There are three sources of fecal coliform data for this project: 1) ambient monitoring data; 2)
data from NPDES permit requirements (DMR data); and 3) special study data. More
information on each of these is provided below.
Little Troublesome Cr. was listed as impaired based on data from the previously mentioned
ambient monitoring station, which is located on SR 2600 (Mizpah Church Rd.) or about 1
mile upstream from the confluence with the Haw River.
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Additional data exist from upstream/downstream monitoring by the Reidsville Wastewater
Treatment Plant. The plant monitored fecal coliform in Little Troublesome Cr. above their
discharge at SR 2670 (S. Scales St.) and below their discharge at SR 2600 (ambient site) on a
weekly to thrice weekly (June-Sept.) basis until October 1998. At that time, the plant began
to shunt the wastewater downstream and discharge it to the Haw River. Subsequently,
monitoring of Little Troublesome Cr. by the treatment plant ceased. These data were used
primarily to gage the relative impact on instream fecal coliform levels by the City of
Reidsville.
The final bacteria monitoring in Little Troublesome Cr. was conducted by DWQ’s
Environmental Sciences Branch in the spring of 2001. In this study, 10 samples were
collected from four separate sites, including SR 2670 (upstream DMR site) and SR 2600
(ambient site), over a six and one-half week period. The purposes of this study were to
evaluate whether the creek was complying with the state fecal coliform standard, and to
provide information on potential bacteria source areas in the watershed.
Only the ambient monitoring and special study data were used in model calibration, because
DWQ chose to not mix data analyzed by separate laboratories (DMR data are analyzed
separately). Also, future monitoring will be done by DWQ through the ambient monitoring
program, so it seems most appropriate to base the TMDL on these data. Each of the three
data sources provides information for the source assessment portion of this document. The
monitoring data used for calibration may be seen in Appendix I.
1.3 Water Quality Target
The North Carolina fresh water quality standard for fecal coliform in Class C waters (T15A:
02B.0211) states:
Organisms of the coliform group: fecal coliforms shall not exceed a geometric mean
of 200/100ml (membrane filter count) based upon at least five consecutive samples
examined during any 30 day period, nor exceed 400/100 ml in more than 20 percent
of the samples examined during such period; violations of the fecal coliform
standard are expected during rainfall events and, in some cases, this violation is
expected to be caused by uncontrollable nonpoint source pollution; all coliform
concentrations are to be analyzed using the membrane filter technique unless high
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turbidity or other adverse conditions necessitate the tube dilution method; in case of
controversy over results, the MPN 5-tube dilution technique will be used as the
reference method.
The instream numeric target, or endpoint, is the restoration objective expected to be reached
by implementing the specified load reductions in the TMDL. The target allows for the
evaluation of progress towards the goal of reaching water quality standards for the impaired
stream by comparing the instream data to the target. For this TMDL the water quality target
is the geometric mean concentration of 200cfu/100ml over a 30-day period. A geometric
mean is obtained by calculating the average of the log values of the individual samples;
basically, the geometric mean will discount higher values so that it should be lower than the
arithmetic mean (average of measurements, no log taken). Cfu stands for colony-forming
units; it may also be referred to as simply ‘counts’ in this assessment. In this TMDL, DWQ
will consider the entire model period to address the portion of the standard that limits the
percentage of instantaneous excursions over 400cfu/100ml to twenty percent.
In order to evaluate the fecal coliform model, monitor water quality conditions and assess
progress of the TMDL, an evaluation location was established for the Little Troublesome
Cr. watershed. The evaluation location of this watershed is Little Troublesome Cr. at SR
2600, which is the location of the ambient monitoring station.
2.0 SOURCE ASSESSMENT
A source assessment is used to identify and characterize the known and suspected sources of
fecal coliform bacteria in the watershed. DWQ completed a source assessment and used it
to develop the water quality model for the TMDL calculation.
2.1 Point Source Assessment
General sources of fecal coliform bacteria are divided between point and nonpoint sources.
Currently, there are no facilities in the watershed that discharge waste through the National
Pollutant Discharge Elimination System (NPDES), which is considered to be the regulatory
approach for all but the smallest of point sources. Recall that the Reidsville WWTP moved
their discharge to the Haw River from Little Troublesome Cr. in October, 1998.
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2.2 Nonpoint Source Assessment
Nonpoint sources of fecal coliform bacteria include those sources that can not be identified
as entering the waterbody at a specific location (e.g., a pipe). Nonpoint source pollution
includes urban, agricultural and background (e.g., forest, wildlife) sources. Fecal coliform
bacteria may originate from human and non-human sources. Table 2 lists the potential
human and animal nonpoint sources of fecal coliform bacteria (Center for Watershed
Protection, 1999). The nonpoint sources of fecal coliform bacteria in Little Troublesome
Cr. include wildlife, livestock (via grazing animals, there is no land application of manure),
urban development (stormwater), failing septic systems, and sewer line systems (illicit
connections, leaky sewer lines and sewer system overflows).
Table 2. Potential sources of fecal coliform bacteria in urban and rural watersheds (Center
for Watershed Protection, 1999).
Source Type Source
Human Sources Sewered watershed Combined sewer overflows
Sanitary sewer overflows
Illegal sanitary connections to
storm drains
Illegal disposal to storm drains
Non-sewered watershed Failing septic systems
Poorly operated package plant
Landfills
Marinas
Non-human Sources Domestic animals and urban wildlife Dogs, cats
Rats, raccoons
Pigeons, gulls, ducks, geese
Livestock and rural wildlife Cattle, horse, poultry
Beaver, muskrats, deer, waterfowl
2.2.1 Livestock
DWQ derived initial estimates for cattle, hogs, horses, sheep and chickens by first
determining the ratio of managed herbaceous land cover (pastureland) in Little Troublesome
Cr. watershed to the same land cover in Rockingham Co. Second, DWQ multiplied this
ratio by the 1997 Agricultural Census of Rockingham Co. estimates for each species of
livestock (Agriculture Census, 2001). Mr. Ben Chase, the Rockingham County agriculture
extension agent, reviewed the initial estimates and offered his best professional judgment for
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the final estimates (Chase, 2001). The final estimates are 275 beef cattle, 50 horses, 12 sheep
and 100 ostrich. There are two ostrich farms in the watershed below the City of Reidsville.
There are no confined animal operations in the watershed, so the livestock waste will be
applied to pastureland only (versus collected manure from confined operations applied to
cropland).
Cattle, including both dairy and beef cows, and horses graze on pastureland and deposit
feces onto the land. During a rainfall runoff event, a portion of the fecal material that
contains coliform bacteria is transported to the streams. Cattle in the stream will be treated
separately (in the miscellaneous sources section which follows), because it is necessary to
calibrate instream fecal coliform sources as a whole.
2.2.2 Miscellaneous Sources
The combination of cattle in stream, point sources with general permits, and illicit discharges
(e.g., straight pipes) are called ‘miscellaneous sources’ in the TMDL allocation; in the model,
they are treated as a constant, instream source of bacteria. It is necessary to separate these
instream sources from land based ones, because they are defined as one instream source
through modeling. That is, it is difficult to determine individual estimates for the fecal
coliform that originates from cattle in the stream, point sources with general permits (no
monitoring requirement) and illicit discharges, but it is possible to estimate them
cumulatively in the model, during periods of low streamflow. To some extent, DWQ
attempted to calibrate this variable.
When cattle or horses have access to streams, feces may be deposited directly into a stream.
There are reaches immediately above the ambient monitoring site at SR 2600 where fencing,
designed to exclude livestock from the stream channel, is not totally effective (Yocum,
2001). Also, livestock often have access to small drainages in their pastures. Loads
attributed to livestock in streams were included as an hourly point source of constant flow
and load. Initial loads were based on the beef cattle population in the watershed and
literature values for fecal coliform bacteria produced daily per beef cattle (ASAE, 1998); this
amounted to 2.5 x 1011 counts/hour. Since this is a calibrated variable, illicit discharges and
point sources with general permits are assumed to be included in this estimate. In other
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words, what is being fit to the model, through calibration, is a constant instream source of
fecal coliform.
2.2.3 Failed Septic Systems
Failing septic systems have been cited as a potential source of fecal coliform bacteria to
water bodies (USEPA, 2000). The Division of Environmental Health has estimated that
Rockingham County has approximately 5,800 housing units on septic systems (DEH, 1999).
In the Little Troublesome Creek watershed, household waste from the city of Reidsville is
treated at the municipal treatment plant, while household waste south of the City of
Reidsville (see Figure 1 on page 3 for city extent) is treated using septic systems. Using a
ratio of the area of the watershed divided by the area of the county, DWQ estimates that
there are 112 septic systems in the lower Little Troublesome Cr. watershed. Additionally,
DWQ assumed that, on average, there are 4.5 people per system. Septic system failure rate
data in North Carolina are very limited. A study conducted in 1981 by the North Carolina
Office of State Budget and Management suggested that approximately 11% of systems that
were surveyed experienced malfunctions or failures over a year (DEH, 2000). Assuming the
average concentration of septic waste reaching the stream is 1.0 x 104 counts/100 ml and
that the septic overcharge flow rate is 70 gallons/day/person (Horsely & Whitten, 1996), the
contribution from failing septic systems is 5.96 x 107 counts/hour. DWQ also assumed that
60% of the septic overcharge reached the stream channel; this estimate is not scientifically
based and was selected as a seemingly moderate to high number for transport from a failing
septic system to the stream network. The loading rate from septic systems using these
assumptions was 2.57 x 1010 counts/30 days.
2.2.4 Urban Development/Sanitary Sewer Overflows
Fecal coliform bacteria can originate from various urban sources. These sources include pet
waste, runoff through stormwater sewers, illicit discharges/connections of sanitary waste,
leaky sewer systems and sanitary sewer overflows.
Fecal coliform accumulation rates on urban land cover were derived using the following:
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1) the proportions of each subwatershed that are covered by high and low density
developed land cover (see Figure 2 on the following page for subwatershed delineation);
2) the types of urban land use that occur in each subwatershed (e.g., residential, and heavy
and light commercial);
3) the fecal coliform build-up (accumulation) rates for each land-use in 2), as calculated
from instream stormwater samples collected by the United States Geological Survey
(USGS) from December 1993 to September 1997 in Mecklenburg County (Bales et al.,
1999). In the USGS study, each of the urban land uses was paired with a sample site.
The land use descriptions and calculated accumulation rates for fecal coliform may be
seen in Table 3.
Table 3. Rate of accumulation and maximum storage of fecal coliform by land use (from
Bales et al., 1999).
Land Use Rate of Accumulation
(count per acre per day)
Maximum Storage
(count per acre)
Residential 6.86 x 109 1.44 x 1010
Heavy Commercial 2.68 x 109 5.63 x 109
Light Commercial/Light Industrial 3.20 x 1010 6.72 x 1010
Woods/Brush 5.48 x 109 1.15 x 1010
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Figure 2.
To derive accumulation rates for each of the three Little Troublesome Cr. subwatersheds,
DWQ calculated the proportion of low and high-density land cover in each subwatershed.
Using local knowledge of the watershed, the land cover data was converted into the four of
land use classes referenced by the USGS study (see Table 4). By combining the proportions
of the four land classes with the accumulation rates, DWQ assigned a comprehensive urban
accumulation rate of fecal coliform for each subwatershed. These accumulation rates are
important model parameters that describe how much fecal coliform is generated on each
land use; actual fecal coliform loading to the stream network is determined through
subsequent modeling. Essentially, the model tracks fecal coliform build-up through the
accumulation rate and simulates fecal coliform wash-off as precipitation falls. More
description of the model appears later in this document.
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Table 4. Estimated conversion from NC GIS land use/land cover to land use in USGS
study. Note that this is for urban (developed) land cover only*
Subwatershed Land cover classification
(from GIS database)
Land use classification
(estimated)
Northeast tributary 47.3% high density developed,
52.7% low density developed
27% light commercial/industrial
20% heavy commercial
40% light residential
13% woods/brush
Upper L. Troublesome Cr.12.8% high density developed,
87.2% low density developed
8% light commercial/industrial
5% heavy commercial
72% light residential
15% woods/brush
Lower L. Troublesome Cr.67.5% high density developed,
32.5% low density developed
30% light commercial/industrial
35% heavy commercial
25% light residential
10% woods/brush
This information yielded initial estimates of accumulation and maximum storage by
subwatershed shown in Table 5.
Table 5. Initial (pre-calibration) estimates of accumulation and storage.
Subwatershed Rate of Accumulation
(count per acre per day)
Maximum Storage
(count per acre)
Northeast tributary 1.26 x 1010 2.28 x 1010
Upper L. T. Cr.8.46 x 109 1.52 x 1010
Lower L. T. Cr.1.28 x 1010 2.31 x 1010
Since these numbers are based on studies in somewhat distant watersheds (Mecklenburg
Co.), they were subject to calibration in the model.
The city of Reidsville owns and operates a wastewater treatment plant and sewage collection
system. From 1997-2001, Reidsville reported eleven sanitary sewer overflows (SSOs) of
greater than 1000 gallons, including five SSOs of greater than 50,000 gallons. DWQ did not
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explicitly account for SSOs in the modeling; rather, DWQ used a relatively high (compared
to other land uses), constant value for urban interflow fecal coliform concentration in the
calibration model, which, along with the constant miscellaneous instream source input (cattle
in stream, illicit discharges, point sources with general permit), may account for leaky sewers
and infrequent SSOs.
2.2.5 Wildlife
Wildlife can be a source of fecal coliform bacteria in forested, wetland, pasture and cropland
areas. Wildlife deposit fecal material in these areas, which can be transported to a stream in
a rain event. Wildlife in Rockingham County area includes deer, turkey, beaver, raccoons,
squirrels, and birds (including waterfowl). DWQ derived population density estimates for all
but squirrels and non-waterfowl; consequently, these animals were not included in the
model.
DWQ obtained estimates for deer and turkey population densities from the North Carolina
Wildlife Resources Commission (WRC, 2001). These estimates are 30-45 deer per square
mile and 16-25 turkey per square mile. The lower ends of the ranges (30 and 16) were
applied to cropland and pastureland, and the higher ends of the ranges (45 and 25) were
applied to forestland.
Beaver estimates were developed by applying the best professional judgment of a NC
Wildlife Resources Commission furbearer biologist, George Straighter, who is familiar with
Rockingham Co. and the Little Troublesome Cr. watershed. Mr. Straighter offered that
there is: 1) about one beaver dam every ¼ mile of linear stream in the lower reaches of Little
Troublesome Cr.; 2) one beaver den per dam; and 3) that there are 6-8 beaver per den
(Straighter, 2001). From this, DWQ estimated that there are 12 beaver per square mile of
one specific forestland type, bottomland forest/hardwood swamp, which is identified in the
NC GIS land use/land coverage.
There was very little basis for estimating populations of raccoon, duck and geese density –
this is one of many areas of uncertainty in the model. DWQ considered that there are 5
geese and 10 ducks per square mile of cropland and forestland (none on pastureland), and
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that there are 10 raccoons per square mile of cropland, forestland and pastureland. The
numbers for geese, duck and raccoon are not scientifically based and are intended as a rough,
moderate estimate.
2.3 Source Assessment Conclusion
All of the aforementioned source assessment data were entered into a spreadsheet called
Fecal Tool, which calculates accumulation rates on the different land covers, and loading
from direct sources such as leaking septic systems and cattle in the stream. TetraTech, Inc.
developed Fecal Tool. Output from this spreadsheet was used as the initial estimates for the
corresponding parameters in the water quality model. Some of the input values calculated in
spreadsheet were later altered through calibration (e.g., urban coliform accumulation values).
3.0 MODELING APPROACH
An important component of the TMDL is to establish the relationship between instream
water quality and sources of fecal coliform. A model that simulates or statistically
characterizes hydrology and water quality is a helpful tool for this purpose. Models provide
the relative contribution of the sources, as well as the predictions of water quality resulting
from changes in these source contributions; these are the basic elements of Total Maximum
Daily Load determination.
3.1 Model Framework
The model selected for this TMDL needed to meet several objectives:
1) To simulate watershed loading and instream transport of fecal coliform bacteria, and to
capture some of the temporal and spatial variation that those processes demonstrate.
2) To simulate instream fecal coliform concentrations over several years, so that critical
conditions (definition on page 2) may be identified. Critical conditions will be the basis
for this TMDL.
3) To evaluate seasonal effects on the production and fate of fecal coliform bacteria.
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EPA’s BASINS software includes a model, Nonpoint Source Model (NPSM), that is suited
for TMDL development. NPSM is based on another model, the Hydrologic Simulation
Program – FORTRAN (HSPF).
NPSM (HSPF) is a dynamic watershed model capable of simulating nonpoint source runoff
and associated pollutant loads. It does this by tracking water and fecal coliform in the
watershed. Specifically, modules named PWATER and IWATER are used to calculate the
components of the water budget, and to predict the runoff from pervious and impervious
areas, respectively (EPA, 1993). The model considers the following hydrologic processes:
precipitation, interception, surface runoff, interflow, groundwater, evaporation and
evapotranspiration; these processes are simulated by fluxes or storages within subroutines of
model. Fecal coliform is simulated in the PQUAL and IQUAL modules (from pervious and
impervious land segment) using simple relationships with water. Fecal coliform occurs in
both the surface and subsurface outflow, though the former is considered to be more
complex in the model. On the surface, fecal coliform can be affected by adhesion to the
soil, and by light, wind, temperature and direct human influence. The approach is to
simulate fecal coliform using basic accumulation (build-up) and depletion rates, in concert
with depletion by wash-off; in other words, fecal coliform outflow from the surface is a
function of the water flow and the amount of fecal coliform in storage (EPA, 1993).
Constant rates are assumed for subsurface loading from the different land use categories.
Also, NPSM (HSPF) performs flow routing and pollutant decay in stream reaches. It does
this through the RCHRES module. Here, flow is assumed to be unidirectional and decay is
assumed to be first-order in nature (see section 3.2.1 below). Finally, NPSM allows discrete
simulation of the required components of the TMDL (e.g., WLA and LA components).
Because it meets the objectives stated above, DWQ chose NPSM as the model for this
TMDL.
3.2 Model Setup
Little Troublesome Creek was delineated into three subwatersheds (see Figure 2) based on
Reach File 3 (RF3) stream coverage and a digital elevation model of the area. The farthest
downstream point of the delineation was the DWQ ambient water quality sampling station,
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B0160000, or Little Troublesome Cr. at SR 2600 near Reidsville. Dewberry and Davis
Consultants compiled hourly meteorological data from a weather station near Greensboro
(See Figure 3 for specific location and its proximity to Little Troublesome Cr. watershed).
The meteorological data begin on 7/1/1996 and end on 8/11/2001. DWQ measured
stream channel cross sections at each of the three subwatershed locations (Appendix 3).
3.2.1 Instream Decay Rate
Once fecal coliform bacteria reach a waterbody, environmental factors influence the extent
of their growth and decay. Physical factors that influence the bacteria populations include
photo-oxidation, adsorption, flocculation, coagulation, sedimentation and temperature
(USEPA, 1985). Chemical toxicity, pH, nutrient levels, algae and the presence of fecal
matter may also influence the fecal coliform population. The water quality model utilizes a
first order decay rate to calculate instream decay of fecal coliform bacteria.
Ct = Coe-kt
Ct= coliform concentration at time t (cfu/100ml)
Co= initial coliform concentration (cfu/100ml)
k= decay rate constant (day-1)
t = exposure time (days)
Bacterial die-off has been modeled as a first-order decay equation, using a decay rate
between 0.7/day and 1.5/day (Center for Watershed Protection, 1999). Another study
found that the median decay rate for fecal coliform was 1.15/day (Lombardo, 1972); that
value was used in the Little Troublesome Cr. model for the existing condition and allocation
runs.
3.3 Hydraulic Calibration
Because NPSM is driven by precipitation and by the subsequent treatment of the water
budget, it is important to calibrate the hydraulic parameters prior to calibrating the water
quality parameters. In the hydraulic calibration, simulated streamflows were compared to
the historic streamflow data recorded at a continuous stream gage. There is not a
continuous gage in Little Troublesome Cr., so instead DWQ used one at Reedy Fork near
Oak Ridge (USGS 02093800), which is nearby (see Figure 3 below). To calibrate the model,
hydraulic parameters, including infiltration, upper and lower zone storage, groundwater
18
storage and recession, interflow, and evapotranspiration, were adjusted within a
recommended range until the simulated and observed hydrographs were as close as possible.
DWQ determined the best match by assessing statistical fit (R2 and root mean squared error,
descriptions below).
Figure 3.
Reidsville
Little Troublesome Cr. watershed
Haw River
Greensboro
Weather Station
$T
Reedy Fork stream discharge gage
9 0 9 18 Miles
N
Regional view of important model sites
A four-year period from 1/1/97 to 12/31/00 was used as the calibration period for the
hydraulic parameters. Relative fit of the modeled flow compared to the recorded flow is
shown in Figure 4 below. The hydraulic parameters used to calibrate the model developed at
the Reedy Fork gage were assumed to apply to the Little Troublesome Creek watershed, and
were used to develop the water quality model for Little Troublesome Creek watershed.
Two conventional statistics for assessing model fit are R2 and the root mean squared error.
R2 is a measure of the variability in the observed data that is explained by the model. The
closer it is to one, the better. For the Reedy Fork hydraulic calibration, using log base 10
values, the four-year R2 is 0.628; this is a typical level of prediction for hydrologic models.
19
The root mean squared error (RMSE) is the standard deviation of the model residuals, which
are the difference between the model predictions and observed data. A lower RMSE is
better, though its value is relative to what the model attempts to predict; the mean of the
observed data is a good measure to compare. In this application, the RMSE is 0.187 and the
observed mean is 1.20 (log base 10 values), which indicates moderate precision.
Figure 4. Simulated and observed flows recorded at USGS 02093800 Reedy Fork, 1997-
2001.
Upon applying the Reedy Fork calibration parameters to the Little Troublesome Cr. model,
predicted runoff yielded a median flow of 10 cubic feet per second (cfs) and mean flow of
15.7 cfs. This compares favorably with a USGS estimate of mean streamflow of 12 cfs for
Little Troublesome Cr., which comes from a low flow study conducted for DWQ in 1987.
3.4 Water Quality Calibration
Once the hydraulic calibration is complete, water quality is calibrated by adjusting parameters
until simulated and observed fecal coliform concentrations achieve acceptable agreement.
To calibrate the model, several parameters were adjusted including the accumulation rates of
fecal coliform bacteria, wash-off rates, maximum storage of fecal coliform bacteria and
contributions from direct sources. By matching the trends in simulated and observed
Reedy Fork Hydraulic Calibration
1
10
100
1000
1/
1
/
9
7
3/
1
/
9
7
5/
1
/
9
7
7/
1
/
9
7
9/
1
/
9
7
11
/
1
/
9
7
1/
1
/
9
8
3/
1
/
9
8
5/
1
/
9
8
7/
1
/
9
8
9/
1
/
9
8
11
/
1
/
9
8
1/
1
/
9
9
3/
1
/
9
9
5/
1
/
9
9
7/
1
/
9
9
9/
1
/
9
9
11
/
1
/
9
9
1/
1
/
0
0
3/
1
/
0
0
5/
1
/
0
0
7/
1
/
0
0
9/
1
/
0
0
11
/
1
/
0
0
Fl
o
w

(
c
u
b
i
c

f
e
e
t

p
e
r

s
e
c
o
n
d
)
Observed Flow (cfs)NPSM Flow (cfs)
20
concentrations resulting from peak and base flows, the model may be a reasonable predictor
of instream water quality.
Through model calibration, DWQ estimates that the constant instream source (see
miscellaneous sources, Section 2.2.2) is 2.7 x 1011 counts/30 days. Cattle in the stream, illicit
discharges and point sources with general permits are assumed to be included in this
estimate.
DWQ focused calibration of urban coliform accumulation rates on the upper two
watersheds (Upper Little Troublesome Cr. and Northeast tributary), where a higher
percentage of urban land cover and where some subwatershed-specific data from a special
study exist. Also, the general calibration (using evaluation location) was helpful in adjusting
accumulation and maximum storage rates. Consequently, these values decreased by
approximately 81% from the values shown in Table 5. It seems rather evident that the
Charlotte values are much too high for the Little Troublesome Cr. watershed. DWQ also
calibrated urban interflow concentration, which was considered as a constant value in the
model.
The calibration period for the water quality model spanned October, 1996 into August,
2001. The beginning time was limited by the meteorological file, which began in July, 1996.
DWQ allowed three months for the model to stabilize before comparing predicted and
observed data.
3.4.1 Prediction Uncertainty
The inability to accurately simulate specific observed data points can sometimes be
attributed to more specific aspects of a model, such as differences in rainfall at the
meteorological gage and in the watershed, or illicit point discharges. More often though, the
lack of agreement between modeled and observed fecal coliform is due to the general high
degree of uncertainty associated with predicting any water quality variable, especially fecal
coliform. Prediction uncertainty comes from a number of sources, including (from
Reckhow and Chapra, 1983 and Reckhow, 1995):
· Gaps in our scientific knowledge.
21
· Natural variability – spatial and temporal variability in chemistry, hydrology and ecology
is great. Model predictions are on a much coarser scale than what occurs in nature.
· Measurement error – measurement of fecal coliform in the field and laboratory has
error.
· Aggregation error – with increased endpoint specificity (space and time), the uncertainty
associated with the prediction increases.
· Model error:
· Mis-specification – model expressions that characterize processes may be wrong.
· Error in parameters – reaction rates may be inappropriate.
· Error in model inputs – e.g., loading terms such as accumulation rate of bacteria
have error.
Unfortunately, many water quality models employed for TMDL analysis, including NPSM,
are not adept at characterizing prediction uncertainty. With these models, all we know is
that the uncertainty is certain to be large. Emphasizing an adaptive management approach is
one way to address this. Specifically, the model may guide initial decision making, but
continued observation of the watershed and creek, as fecal coliform controls are
implemented (e.g., exclusion fencing, leaky sanitary sewer repair), is expected to be our best
approach for determining the appropriate level of management.
3.4.2 Calibration Results
Fecal coliform samples collected at B0160000 (the ambient monitoring station) between
October, 1996 and August, 2001 were compared to simulated concentrations and rainfall
collected at the meteorological stations. The results are shown in Figures 5 and 6. Graphical
results indicate that the model does a fair job at simulating the response of fecal coliform
bacteria over time with variations in flow.
22
Figure 5. Simulated versus observed fecal coliform concentrations from 10/1997–3/1999.
10
100
1000
10000
10/1/96 1/9/97 4/19/97 7/28/97 11/5/97 2/13/98 5/24/98 9/1/98 12/10/98 3/20/99
0
1
2
3
4
5
6
7
8
9
10
RAINFALL (IN/DAY)MODEL OUTPUT OBSERVED DATA

23
Figure 6. Simulated versus observed fecal coliform concentrations from 3/1999-8/2001.
The model calibration statistics for fecal coliform are not nearly as good as those for the
hydraulic calibration. The R2 in this case is 0.164 and the RMSE is 0.464, with an observed
mean of 2.27 (again, these are based on log base 10 values). The low R2 indicates a lack of
predictive power. On the other hand, the relatively small RMSE suggests that the model
may predict the mean fairly well, but there may be a lot of individual scatter about the mean.
To resolve this discrepancy, DWQ examined modeling efficiency, which is calculated using
the following formula:
å
åå
=
==
-
÷÷
ø
ö
çç
è
æ ---
n
i
n
i
n
i
OOi
OiPiOOi
1
2
2
11
2
)(
)()(
where:
Oi = ith observation
Pi = ith prediction
10
100
1000
10000
3/21/99 6/29/99 10/7/99 1/15/00 4/24/00 8/2/00 11/10/00 2/18/01 5/29/01 9/6/01
0
1
2
3
4
5
6
7
8
9
10
RAINFALL (IN/DAY)MODEL OUTPUT OBSERVED DATA

24
O_ = mean of the observations
The closer to 1 the better.
if > 0, then the model predicts better than the mean of the observations
if < 0, then the mean of the observations does better than the model
The modeling efficiency for the Little Troublesome Cr. coliform model is –0.577. This
means that the model predictive precision is low. The recommendation for adaptive
management is the best approach for overcoming this problem.
3.5 Critical Conditions
In terms of the TMDL, critical conditions occur within the calibrated model when fecal
coliform levels exceed the standard by the largest amount. The Little Troublesome Cr. fecal
coliform monitoring data indicate that elevated fecal coliform levels occur throughout the
year, during both dry and wet weather conditions. The model was run for a nearly five year
simulation period (October, 1996 into August, 2001). The highest 30-day geometric mean of
the predicted daily fecal coliform concentration, 280 colonies per 100 ml, occurred between
June 22 and July 21, 2001. Rain was recorded in Greensboro on 11 days during that 30-day
period. Additionally, the critical period was preceded by a somewhat dry spell (1.81 and 2.52
inches of precipitation in April and May, respectively) and the largest amount of rain that fell
during a single day of the critical period was 0.67 inches. In other words, a relative
abundance of fecal coliform was probably available for wash-off during the critical period.
Also, wash-off during the critical period appears to have occurred in a piecemeal fashion,
which maintained high concentrations through the 30 days by limiting dilution, as well as
mass wash-off.
25
Figure 7. Rolling 30-Day Geometric Mean of Predicted Daily Fecal Coliform
Concentrations (cfu/100 ml)
3.6 Water Quality Model Results
Loading rates representing existing conditions were determined in the following manner:
1) The calibrated model was rerun for the entire, nearly 5-year period.
2) Simulated fecal coliform concentrations for the nearly 5-year period were plotted as
rolling 30-day geometric mean concentrations and compared to the standard criteria of
200 counts/100mL (see Figure 7 above).
3) From Figure 7, DWQ determined critical conditions, which is the highest 30-day
geometric mean during the model run. June 21-July 22, 2001 as described above.
4) The simulated daily fecal coliform loads from sources such as runoff from all lands,
leaking septic systems and miscellaneous sources were summed for the 30-day critical
period. These values represent existing loads and are shown in Table 6. Please see
source assessment section on page 8 for more information on how these loads were
calculated.
DWQ separated the principal coliform source categories, as used in NPSM, in Table 6; these
include runoff from all lands, leaking septic systems and miscellaneous sources. Runoff
0
100
200
300
400
10/1/96 4/19/97 11/5/97 5/24/98 12/10/98 6/28/99 1/14/00 8/1/00 2/17/01 9/5/01
DATE
PREDICTED (EXISTING)WATER QUALITY STANDARD

26
from all lands includes estimated fecal coliform load from deposits by livestock and
wildlife, as well as an estimate of loading from urban areas. Leaking septic systems only
estimates loading related to septic systems. Miscellaneous sources is an estimate of
loading from livestock in the stream, from point sources with general permits, as well as
from unknown, or illicit, instream sources. According to the model, storm-driven runoff
from all land provides the largest load of fecal coliform bacteria to the stream. Loads from
miscellaneous sources are constant loads that are applied directly to the stream; these sources
will have the greatest impact on instream water quality during periods of low flow.
Table 6. Summary of predicted existing coliform loads in the Little Troublesome Cr.
watershed.
Runoff from all lands1
(counts/30 days)
Leaking septic systems
(counts/30 days)
Miscellaneous sources2
(counts/30 days)
Instream conc.3
(counts/100 ml)
1.20 x 1013 2.57 x 1010 2.70 x 1011 280
1 Includes livestock in pasture, wildlife, and urban runoff.
2 Includes livestock with stream access and illicit discharges.
3 Maximum simulated concentration during the critical period (geometric mean).
4.0 Total Maximum Daily Load
A Total Maximum Daily Load is the maximum amount of a pollutant that a water body can
receive and still meet water quality standards, and an allocation of that amount among point
and nonpoint sources. A TMDL comprises the sum of wasteload allocations (WLA) for
point sources, load allocations (LA) for nonpoint sources, and a margin of safety. This
definition is expressed by the equation:
TMDL = S WLAs + S LAs + MOS
The objectives of the TMDL are to estimate allowable pollutant loads, and to allocate to the
known pollutant sources in the watershed, so the appropriate control measures can be
implemented and the water quality standard can be achieved.
The TMDL will be expressed in units of counts/30 days, as this is the period over which the
water quality target/standard is evaluated.
27
The two main components of a TMDL, the reduction target, including a margin of safety,
and the allocation strategy will be presented in the following sections.
4.1 Reduction Target
Using the calibrated water quality model, DWQ applied load reductions to the bacteria
sources until the simulated 30-day geometric mean for fecal coliform bacteria concentrations
did not exceed the 170 counts/100 ml (standard is 200 counts/100 ml, however, see margin
of safety section below) at any time. Thus, with no predicted exceedances of the standard,
the model fulfills the TMDL criterion of allowing the maximum load while still achieving
water quality standards. The predicted 30-day geometric means, after DWQ applied the load
reductions in the model, can be seen as the allocation line in Figure 8. The model predicts
that a 40 percent reduction from existing loads must be taken to achieve the instream water
quality (TMDL) criterion.
Figure 8. Reduction of fecal coliform from existing loading to TMDL allocation (both as
rolling 30-day geometric mean).
0
100
200
300
10/1/96 4/19/97 11/5/97 5/24/98 12/10/98 6/28/99 1/14/00 8/1/00 2/17/01 9/5/01
DATE
FE
C
A
L

C
O
L
I
F
O
R
M

(
#
/
1
0
0

m
L
)
PREDICTED (EXISTING)WATER QUALITY CRITERION TMDL ALLOCATION

28
To assess the instantaneous portion of the fecal coliform standard, DWQ considered
observed data and predictions from the full modeling period. The observed data from 1995
to 2001 show that 21% of the samples were over 400 counts/100 ml. The calibrated model
has 24% of the daily predictions over 400 counts/100 ml. The TMDL model that meets the
geometric mean part of the fecal coliform standard (overall about a 40% reduction) drops
the percent of daily predictions above 400 counts/100 ml to 20% over the nearly 5 year
model period.
4.1.1 Margin of Safety
A TMDL requirement is that a margin of safety must be included to provide further
insurance that the impaired waterbody will meet its designated uses once load reductions are
realized. The margin of safety may be accounted for implicitly, through conservative (more
protective of water quality) model assumptions, or explicitly, by reserving a portion of the
allocated load. The Little Troublesome Cr. TMDL includes explicit and implicit margins of
safety; more explanation on the margin of safety follows below.
In Figure 8, observe that the target for the rolling 30-day geometric mean of fecal coliform is
170 counts/100 ml, instead of the standard of 200 counts/100 ml. By using this lower
target, DWQ provides an explicit margin of safety for the Little Troublesome Cr. TMDL.
This explicit margin of safety may be interpreted to account for 15% greater assurance of
achieving the instream water quality target.
[(200-170)/200]*100 = 15%
Also, an implicit margin of safety is included because the model assumes that bacteria
delivered from the land surface do not decay as it travels from its source to the stream
network.
4.2 Allocation
The allocation strategy for the Little Troublesome Cr. fecal coliform TMDL is limited to
nonpoint sources, as there are no permitted point sources in the watershed. An allocation
29
scenario that predicts compliance with the instream water quality criterion and the required
reductions from the individual categories may be seen in Table 7.
Table 7. Allocation strategy by major nonpoint sources for TMDL conditions
Runoff from all lands
(counts/30 days)
Leaking septic systems
(counts/30 days)
Miscellaneous Sources
(counts/30 days)
Instream f.c. concentration1
(counts/100 ml)
7.42 x 1012 1.54 x 1010 1.62 x 1011 170
40% reduction 40% reduction 40% reduction 39% reduction
1 Maximum simulated instream concentration during critical period. Percent reduction
represents the difference in simulated instream concentration between the existing loads
(Table 6., 280 counts/100 ml) and TMDL allocation scenario (Table 7., 170 counts/100
ml).
The nonpoint sources are summed to produce a wasteload allocation (WLA), which is
displayed in Table 8 below.
Tables 8 and 9. Allocation strategy by TMDL components for Little Troublesome Cr.
In terms of load:
Wasteload allocation (WLA)
(counts/30 days)
Load allocation (LA)
(counts/30 days)
Explicit Margin of safety
(MOS)
(counts/30 days)
TMDL
(counts/30 days)
0 7.60 x 1012 1.34 x 1012 8.94 x 1012
In terms of concentration:
Wasteload allocation (WLA)
(counts/100 ml)
Load allocation (LA)
(counts/100 ml)
Explicit Margin of safety
(MOS)1
(counts/100 ml)
TMDL
(counts/100 ml)
0 170 30 200
1 Explicit margin of safety is equal to 15.0% since the instream water quality target is
reduced to 170 counts/100 ml from 200 counts/100 ml (e.g., [(200-170)/200] = 15%).
30
The implicit margin of safety, from the assumption that fecal coliform bacteria do not decay
as they are transported from the land surface to the stream network, is not quantified nor
included in the tables above. Basically though, by not including this decay, the listed load
allocation is higher than if the decay were included. Consequently, the actual (expected) load
allocation will be lower than what is shown in Tables 8 and 9; therein lies the implicit margin
of safety.
4.3 Seasonal variation
DWQ used a nearly 5-year simulation period to assess the TMDL. This longer period allows
for consideration of seasonal variation. Additionally, some of the loading rates varied
monthly within the model.
5.0 SUMMARY AND FUTURE CONSIDERATIONS
The sources of fecal coliform in the Little Troublesome Cr. watershed include urban sources
in the Reidsville area, livestock grazing on agricultural lands, and wildlife in the forested areas
of the watershed. The Nonpoint Source Model in EPA’s Basins software was used to
simulate instream fecal concentrations and to allocate the fecal coliform loads to the various
sources. In order for the water quality target to be met, the final allocation of the fecal
coliform requires the major sources (not wildlife as that is considered part of background) to
reduce loading by approximately 40%. DWQ considers the major sources to be runoff from
urban area, possibly including leaking sewer lines, miscellaneous instream sources
(particularly illicit discharges and cattle in the stream) and septic systems. Based on the
special study monitoring which is shown in Appendix I, and the model results, it appears to
be most important to reduce fecal coliform loading from the urban areas in and around the
City of Reidsville. More minor sources include pastureland, where a 10% reduction in
loading is expected.
5.1 Monitoring
Fecal coliform monitoring will continue on a monthly interval at the ambient monitoring site
(SR2600). The continued monitoring of fecal coliform concentrations will allow for the
evaluation of progress towards the goal of reaching water quality standards. In addition to
this data collection, further fecal coliform monitoring may be considered. Additional
31
monitoring could focus on fecal coliform source assessment in the watershed; this would
further aid in the evaluation of the progress towards meeting the water quality standard.
Also, a synoptic survey or two of instream fecal coliform during storm events may improve
model calibration during those important loading events.
To comply with EPA guidance, North Carolina may adopt new bacteria standards utilizing
Escherichia coli (E. coli) and enterococci in the near future. Thus, future monitoring efforts
to measure compliance with this TMDL should include E. coli and enterococci. Per EPA
recommendations (EPA, 2000b), if future monitoring for E. coli/enterococci indicates the
standard has not been exceeded, these monitoring data may be used to support delisting the
water body from the 303(d) list. If a continuing problem is identified using E.
coli/enterococci, the TMDL may be revised.
5.2 Implementation
An implementation plan is not included in this TMDL. The involvement of local
governments and agencies will be needed in order to develop the implementation plan. If
local cooperation is secured, and indications are that local interest is positive, then DWQ will
assist in developing the implementation plan. Thus far, DWQ contributed to a local
planning agency’s proposal for Section 319 funds to implement the Little Troublesome fecal
coliform TMDL.
6.0 PUBLIC PARTICIPATION
The City of Reidsville was notified of DWQ’s intention to develop the Little Troublesome
Cr. fecal coliform TMDL. The county extension service supplied agricultural information to
aid in the source assessment portion of the TMDL.
To publicly notice the Little Troublesome fecal coliform TMDL, DWQ submitted a legal
advertisement to the newspapers for Greensboro and Reidsville. The advertisement
appeared in each of these newspapers on March 14, 2002. Additionally, DWQ electronically
distributed a draft of the TMDL and public comment information to the known interested
parties on March 12, 2002. Finally, DWQ held a public meeting in Reidsville on March 21,
32
2002 to present the TMDL and offer opportunity for questions and comments by the
public. The advertised comment period was 30 days, and DWQ did not receive any
comments by April 22, 2002.
33
References Cited
Alabama Department of Environmental Management. 2001. Draft Big Nance Creek
TMDL Development for Fecal Coliform. Prepared by the Water Quality Branch and Tetra
Tech, Inc.
Albertin, K.P. TetraTech, Inc. 2001-2002. Personal communication.
Anderson, W.H. TetraTech, Inc. 2001-2002. Personal communication.
American Society of Agricultural Engineers (ASAE). 1998. ASAE Standards, 45th Edition,
Standard Engineering Practices Data.
Bales, J.D., Weaver, J.C., and Robinson, J.B. 1999. Relation of Land Use to Streamflow and
Water Quality at Selected Sites in the City of Charlotte and Mecklenburg County, North
Carolina, 1993-1998. U.S. Geological Survey, Raleigh NC. Water Resources Investigations
Report 99-4180.
Canale, R.P., Auer, M.T., Owens, E.M., Heidtke, T.M., and S.W. Effler. 1993. Modeling
Fecal Coliform Bacteria-II. Model Development and Application. Wat. Res. 27(4):703-714.
Center for Watershed Protection. 1999. Microbes and Urban Watersheds: Concentrations,
Sources and Pathways. Watershed Protection Techniques 3(1): 554:565.
Chase, B. Rockingham County Agriculture Extension. 2001. Personal communication.
Davis, M. USEPA, Region IV. 2001-2002. Personal communication.
City of Reidsville Contractor (Environmental Waste Recycling, Inc.). 1998. 1998 Annual
Monitoring Reports to the NC-DENR Division of Water Quality on the Land Application
of Biosolids Program.
City of Reidsville Contractor (Synagro Southeast, Inc.). 1999. 1999 Annual Monitoring
Reports to the NC-DENR Division of Water Quality on the Land Application of Biosolids
Program.
City of Reidsville Contractor (Synagro Southeast, Inc.). 2000. 2000 Annual Monitoring
Reports to the NC-DENR Division of Water Quality on the Land Application of
Biosolids Program.
Division of Environmental Health (DEH). NCDENR. 1999. North Carolina On-Site
Wastewater Non-Point Source (NPS) Pollution Program.
www.deh.enr.state.nc.us/oww/non-pointsource/NPS.htm
Division of Environmental Health (DEH). NCDENR. 2000. Report on the Proper
Maintenance of Septic Tank Systems in Accordance with Section 13.5 of HB 1160 (Clean
Water Act of 1999). March 15, 2000.
34
Horner, 1992. Water Quality Criteria/Pollutant Loading Estimation/Treatment
Effectiveness Estimation. In R.W. Beck and Associates, Covington Master Drainage Plan,
King County Surface Water Management Division, Seattle, Washington.
Horsley and Witten. 1996. Identification and evaluation of nutrient and bacterial loadings
to Maquiot Bay, New Brunswick and Freeport, Maine. Final Report. Casco Bay Estuary
Project, Portland, ME.
Lombardo, P.S. 1972. Mathematical Model of Water Quality in Rivers and Impoundments.
Hydrocomp, Inc., Mountain View, California.
McDaniel, A.H. Dewberry & Davis Consultants, Inc. 2001. Personal communication.
Mecklenburg County Department of Environmental Protection and NC Department of
Environment and Natural Resources. 2001. Fecal Coliform Total Maximum Daily Load for
the Irwin, McAlpine, Little Sugar and Sugar Creek Watersheds, Mecklenburg County, North
Carolina.
North Carolina Department of Agriculture. 2001. Agricultural Statistics Division-County
Statistics. www.ncagr.com/stats/cntysumm/ and http://govinfo.library.orst.edu/cgi-
bin/ag-state?North+Carolina.
North Carolina State University (NCSU). 1994. Livestock Manure Production and
Characterization in North Carolina. North Carolina Cooperative Extension Service. College
of Agriculture and Life Sciences, Raleigh, NC.
NC Wildlife Resources Commission. 2001. Estimates for deer and turkey populations in
Rockingham Co. NC Department of Environment and Natural Resources, Raleigh, NC.
Reckhow, K.H. and S.C. Chapra. 1983. Engineering Approaches for Lake Management.
Volume I: Data Analysis and Empirical Modeling, Ann Arbor Science Pub. Inc.
Reckhow, K.H. 1995. Duke University Water Quality Modeling course notes.
Smith, P. Reidsville Wastewater Treatment Plant. 2001. Personal communication.
Stow, C.A. Duke University. 2002. Personal communication.
Straighter, G. NC Wildlife Resources Commission. 2001. Personal communication.
Tetra Tech, Inc. 2001. Fecal Tool User’s Guide. Draft report submitted to USEPA.
Fairfax, Virginia.
U.S. Environmental Protection Agency (USEPA). 1991. Guidance for Water Quality-Based
Decisions: The TMDL Process. Assessment and Watershed Protection Division,
Washington, DC.
35
U.S. Environmental Protection Agency, Federal Advisory Committee (FACA). Draft final
TMDL Federal Advisory Committee Report. 4/28/98.
U.S. Environmental Protection Agency (USEPA). 2000a. Revisions to the Water Quality
Planning and Management Regulation and Revisions to the National Pollutant Discharge
Elimination System Program in Support of Revisions to the Water Quality Planning and
management Regulation; Final Rule. Fed. Reg. 65:43586-43670 (July 13, 2000).
U.S.Environmental Protection Agency (USEPA). 2000b. Implementation Guidance for
Ambient Water Quality Criteria for Bacteria – 1986. DRAFT. Office of Water. EPA-
823-D-00-001.
U.S. Environmental Protection Agency (USEPA). 1985. Rates, constants, and kinetics
formulations in surface water quality modeling (II ed.). Athens, GA: EPA-600-3-85-040.
U.S. Environmental Protection Agency (USEPA). 1998. Better Assessment Science
Integrating Point and Nonpoint Sources (BASINS), Version 2.0 User’s Manual. Office of
Water, Washington DC. EPA-823-B-98-006.
U.S. Environmental Protection Agency (USEPA). 1993. Hydrologic Simulation Program –
FORTRAN. User’s Manual for Release 10. Office of Research and Development,
Washington DC. EPA-600-R-93-174.
U.S.Environmental Protection Agency (USEPA). 2001. Protocol for Developing Pathogen
TMDLs. Office of Water, Washington DC. EPA 841-R-00-001.
U.S. Environmental Protection Agency (USEPA). 2001. Total Maximum Daily Load
Development for Fecal Coliform in the Crooked Creek Watershed, Cullman County,
Alabama. USEPA Region IV, Atlanta, Georgia.
U.S.Environmental Protection Agency (USEPA). 2000. BASINS Technical Note 6.
Estimating Hydrology and Hydraulic Parameters for HSPF. Office of Water, Washington
DC. EPA 823-R-00-012.
http://www.epa.gov/waterscience/basins/tecnote6.html
United States Geological Survey (USGS). 2001. Water Resources of the United States.
NWIS web online hydrologic data: http://water.usgs.gov.
Yocum, T. NC Division of Water Quality. 2001. Personal communication.
36
APPENDIX I. OBSERVED DATA
Table A. Data from DWQ Ambient Station – Little Troublesome Cr. at SR 2600
DATE Fecal Coliform (#/100 ml)DATE Fecal Coliform (#/100 ml)
1/9/95 230 9/30/98 430
2/8/95 60 10/27/98 120
3/14/95 20 11/17/98 130
4/10/95 70 1/20/99 82
5/25/95 410 5/11/99 320
6/26/95 240 6/8/99 150
7/25/95 1600 7/12/99 230
9/25/95 3400 8/11/99 200
10/31/95 850 9/22/99 1700
12/4/95 45 10/11/99 840
12/7/95 18 11/22/99 120
1/17/96 200 12/29/99 10
2/26/96 140 2/16/00 45
3/28/96 3500 3/28/00 140
4/16/96 3000 4/25/00 1600
5/22/96 2000 5/23/00 210
6/11/96 3300 6/1/00 420
7/22/96 820 7/24/00 310
8/22/96 100 8/8/00 680
9/26/96 91 8/17/00 210
10/30/96 160 8/22/00 110
11/25/96 250 8/30/00 130
12/18/96 54 9/11/00 190
1/29/97 54 9/12/00 250
2/13/97 82 9/27/00 170
3/13/97 360 10/31/00 350
4/24/97 200 11/28/00 210
5/29/97 200 12/28/00 28
6/23/97 210 1/18/01 100
7/23/97 340 2/12/01 150
8/25/97 220 4/4/01 140
9/30/97 110 4/10/01 76
10/30/97 73 4/17/01 79
11/17/97 36 4/19/01 120
1/5/98 18 5/3/01 270
1/29/98 220 5/8/01 140
2/16/98 10 5/9/01 240
3/18/98 310 5/16/01 4260
4/14/98 72 5/23/01 5120
5/27/98 2200 5/31/01 390
7/29/98 310 6/18/01 310
7/30/98 340 7/31/01 300
8/27/98 370 8/21/01 130
Shaded values are from DWQ special study in April and May, 2001
37
Summary of Little Troublesome Creek Fecal Coliform Data from DWQ Special Study
(for station locations see map on next page)
Station Description Dates Number of Days Observations Geometric Mean
L.T. Cr. at SR 2670 4/10/2001 to 5/9/2001 30 15 258
L.T. Cr. at SR 2670 4/17/2001 to 5/16/2001 30 15 748
L.T. Cr. at SR 2670 4/19/2001 to 5/23/2001 35 15 1733
L.T. Cr. at SR 2670 5/3/2001 to 5/31/2001 29 15 1146
L.T. Cr. at SR 2536 4/10/2001 to 5/9/2001 30 15 396
L.T. Cr. at SR 2536 4/17/2001 to 5/16/2001 30 15 644
L.T. Cr. at SR 2536 4/19/2001 to 5/23/2001 35 15 1049
L.T. Cr. at SR 2536 5/3/2001 to 5/31/2001 29 15 1358
L.T. Cr. at SR 2598 4/10/2001 to 5/9/2001 30 15 141
L.T. Cr. at SR 2598 4/17/2001 to 5/16/2001 30 15 342
L.T. Cr. at SR 2598 4/19/2001 to 5/23/2001 35 15 607
L.T. Cr. at SR 2598 5/3/2001 to 5/31/2001 29 15 739
L.T. Cr. at SR 2600 4/10/2001 to 5/9/2001 30 15 135
L.T. Cr. at SR 2600 4/17/2001 to 5/16/2001 30 15 301
L.T. Cr. at SR 2600 4/19/2001 to 5/23/2001 35 15 694
L.T. Cr. at SR 2600 5/3/2001 to 5/31/2001 29 15 883
All Stations 4/10/2001 to 5/9/2001 30 210
All Stations 4/17/2001 to 5/16/2001 30 481
All Stations 4/19/2001 to 5/23/2001 35 936
All Stations 5/3/2001 to 5/31/2001 29 1114
Note that the SR 2670 and SR 2536 sites drain the primarily urban (especially northeast
tributary subwatershed, or SR 2536) headwaters of the Little Troublesome Cr. watershed.
Those samples tend to be higher than the samples from lower in the watershed. This
provides evidence that the City of Reidsville (e.g., stormwater runoff, leaky sewer pipes, etc.)
is likely to be a primary source of fecal coliform in the Little Troublesome Cr. watershed.
Consequently, management efforts should focus there.
38
US-29
Little Troublesome Cr.
DWQ ambient site
Reidsville
X X
X
1
2
ROCKINGHAM COUNTY
x3
4
Little Troublesome coliform sampling sites
X sample sites
1 SR 2670 (S Scales St.)2 SR 2536 (Turner Rd.)
3 SR 2598 (Cook Florist Rd.)
4 ambient site on SR 2600 or Mizpah Ch Rd
39
APPENDIX II. MODEL CALIBRATION INFORMATION
Calibrated Hydraulic Parameters for HSPF application to Little Troublesome Cr.
Parameter Description/Units Calibration value Typical range*
LZSN Lower zone nominal storage (inches)7.0 3 - 8
INFILT Soil infiltration rate (in./hr.)0.10 0.01 – 0.25
LSUR Length of assumed overland plane
(ft.)
300 200 - 500
SLSUR Slope of assumed overland plane 0.035 0.01 – 0.15
AGWRC Groundwater recession rate ( /day)0.99-forest,
0.96-nonforest
0.92 – 0.99
UZSN Upper zone nominal storage (inches)0.56 0.10 – 1.0
INTFW Interflow inflow (no units)0.60 Default is 0.75
IRC Interflow recession coefficient 0.40 0.5 – 0.7
LZETP Lower zone evapotranspiration 0.20 0.2 – 0.7
* From Basins Technical Note 6 – Estimating Hydrology and Hydraulic Parameters for HSPF
40
Calibrated Water Quality Parameter for HSPF application to Little Troublesome Cr.
Land use/PARAMETER ACQOP*SQOLIM WSQOP IOQC
Urban (NE tributary)2.36 x 109 4.27 x 109 0.7 1.12 x 106
Urban (Upper L.T. Cr.)1.59 x 109 2.85 x 109 0.7 1.12 x 106
Urban (Lower L.T. Cr.)2.4 x 109 4.33 x 109 0.7 1.12 x 106
Pasture (Upper L.T. Cr.)*
monthly values
4.36 x 109 to
8.61 x 109
6.54 x 109 to
1.29 x 1010
1.5 10,000
Pasture (Lower L.T. Cr.)
monthly values
4.76 x 109 to
9.14 x 109
7.14 x 109 to
1.64 x 1010
1.5 10,000
Cropland 2.77 x 107 4.99 x 107 1.5 10,000
Cropland (Lower L.T. Cr.)#
monthly values
2.77 x 107 to
1.51 x 108
4.16 x 107 to
2.27 x 108
1.5 10,000
Upland Forest 3.88 x 107 6.98 x 107 2.8 5,000
Bottomland Forest 4.54 x 107 8.46 x 107 2.8 5,000
ACQOP is the accumulation rate in count/acre/day
SQOLIM is the maximum storage rate in count/acre
WSQOP is the surface runoff rate removing 90% of pollutant in inches
IOQC is the interflow concentration in count/acre/day
These values were calculated in Fecal Tool
* Monthly values exist for pasture because cattle were assumed to spend varying amounts of time in
the stream, depending on the air temperature.
# Monthly values exist for cropland because sludge from the treatment plant was assumed to be
applied on this land use two months out of the year. Reductions are not expected from either
cropland or land applied sludge, as it is assumed that they are part of the background loading (only
cropland sources of coliform are wildlife and land applied sludge is an already regulated process).
41
APPENDIX III. Stream Channel Cross Sections for Subwatersheds
Outlet of Upper Little Troublesome Cr. subwatershed
at SR 2670
-1
0
1
2
3
4
5
6
7
8
9
0 5 10 15 20 25 30 35 40
Ft.
Ft
.
Bank Full
Water Level
Outlet of Northeast tributary at SR 2536
0
1
2
3
4
5
6
Horizontal distance (ft.)
Bank full
Water level
42
Outlet of Lower Little Troublesome Cr.,
DWQ ambient site at SR 2600
0
1
2
3
4
5
6
7
8
0 10 20 30 40 50 60
Ft.
Ft
.
Bank Full
Water Level