An Approach for Using Load Duration
1 Curves in the Development of TMDLs

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An Approach for Using Load Duration Curves in
             the Development of TMDLs
                       EPA 841-B-07-006
                         August 2007
                    Watershed Branch (4503T)
              Office of Wetlands, Oceans and Watersheds
               U.S. Environmental Protection Agency
                    1200 Pennsylvania Ave. NW
                     Washington, DC 20460
                      Document posted at:
             http://www.epa.gov/owow/tmdl/techsupp.html

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An Approach for Using Load Duration Curves in the Development of TMDLs
                   U.S. Environmental Protection Agency

                                   August 2007
                 Office of Wetlands, Oceans, & Watersheds
                   U.S. Environmental Protection Agency
This guide provides an overview on the use of duration curves for developing Total
Maximum Daily Loads (TMDLs). It is written for TMDL practitioners who are familiar
with relevant technical approaches and legal requirements.  The guide describes basic
steps needed to develop duration curves, which identify  loading capacities, load  and
wasteload allocations, margins  of  safety,  and seasonal variations.   The guide also
discusses some considerations and limitations in using the approach, and includes several
case examples.

The duration curve approach allows  for characterizing water quality concentrations (or
water quality data) at different flow regimes.  The method provides a visual display of the
relationship  between  stream flow and loading  capacity.   Using the duration curve
framework,  the frequency  and magnitude  of  water quality  standard exceedances,
allowable loadings, and size of load reductions are easily presented and can be better
understood.

The duration  curve approach is particularly applicable  because stream  flow is  an
important factor in the determination of loading capacities.  This method accounts for
how stream flow patterns affect changes in water quality over the course of a year (i.e.,
seasonal variation that must be considered in  TMDL development). Duration curves also
provide a means to link water quality concerns with key watershed processes that may be
important considerations in TMDL development.  Basic principles of hydrology can help
identify the relative importance of factors such as water storage or storm events, which
subsequently affect water quality.

Water quality analysts should assess the appropriateness of using this  framework to
develop a particular TMDL.  An underlying premise of the  duration curve approach is
correlation of water quality  impairments to flow conditions.   The duration  curve alone
does not consider specific fate and transport mechanisms, which may vary depending on
watershed or pollutant characteristics.  Such processes may include sediment attenuation,
plant uptake  of nutrients, chemical  transformations, or bioaccumulation.  Practitioners
should consider using a separate analytical tool to develop a TMDL when factors other
than flow significantly affect a water body's loading capacity.
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An Approach for Using Load Duration Curves in the Development of TMDLs
                                    Disclaimer

This document provides technical information to TMDL practitioners who are familiar
with the relevant technical approaches  and legal requirements pertaining to developing
TMDLs and refers to statutory and  regulatory provisions that contain legally binding
requirements. This document does not substitute for those provisions or regulations, nor
is it a regulation itself. Thus, it does not impose legally binding requirements on EPA or
States, who retain the discretion to adopt approaches on a case-by-case basis that differ
from  this  information.  Interested  parties  are  free to  raise  questions  about  the
appropriateness of the application of this information  to a particular situation, and EPA
will consider whether or not the technical approaches are appropriate in that situation.
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An Approach for Using Load Duration Curves in the Development of TMDLs


                             Table of Contents

1.     DEVELOPMENT OF FLOW DURATION CURVES	1
  a.     What is a Flow Duration Curve?	1
  b.     Where to Get Flow Information	2
  c.     Duration Curve Intervals and Zones	2

2.     DEVELOPMENT OF LOAD DURATION CURVES AND TMDLs	3
  a.     Numeric Water Quality Targets	3
  b.     Interpreting Load Duration Curves to Assess Water Quality	5
  c.     Margin of Safety	6
  d.     Development of Allocations	7
  e.     Seasonal Variation	9
  f.     Summary	11

3.     APPROPRIATE USE OF LOAD DURATION CURVES	12
  a.     Appropriate When Flow is Primary Driver	12
  b.     Water Quality Standards Designed for All Flow Regimes	12

4.     CONSIDERATIONS	13
  a.     Source Characterization	13
  b.     Large Scale Watershed Situations	13
  c.     Range of Flows Versus Single Condition	14
  d.     Storm Events and Hydrograph Separation	15
  e.     Utility in Identifying Potential Source Areas	16

5.     CONNECTING TO IMPLEMENTATION AND RESULTS	17

APPENDICES

A.    LOAD DURATION CURVE TMDLs - CASE EXAMPLE	19
B.    ADDITIONAL EXAMPLES OF USING LOAD DURATION CURVE APPROACH	37
C.    TARGETING POTENTIAL SOLUTIONS AND CONNECTING TO IMPLEMENTATION	55
D.    ACRONYMS AND REFERENCES	65


                               List of Figures

Figure 1-1     General Form of the Flow Duration Curve	1
Figure 1-2     General Form of the Flow Duration Curve	3
Figure 2-1     Nitrate Loading Capacity Using Duration Curve Framework	4
Figure 2-2     Ambient Water Quality Data Using a Duration Curve Framework	5
Figure 2-3     Example TMDL Using Duration Curve Framework	9
Figure 2-4     Mississippi River Seasonal Flow Patterns	10
Figure 2-5     Mississippi River Monthly Variation	10
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An Approach for Using Load Duration Curves in the Development of TMDLs
                           List of Figures (cont.)

Figure 4-1    Fraction Analysis of Storm Flow Relative to Total Streamflow	15
Figure 5-1    Duration Curve with Contributing Area Focus	17
Figure 5-2    Documenting Erosion Control Program Results	18
Figure B-1    Chloride Loading Capacity Using Duration Curve Framework	38
Figure B-2    Nitrate Loading Capacity Using Duration Curve Framework	39
Figure B-3    Phosphorus Loading Capacity Using Duration Curve Framework	40
Figure B-4    Example Sediment Rating Curve	41
Figure B-5    Sediment Loading Capacity Using Duration Curve Framework	42
Figure B-6    Bacteria Loading Capacity Using Duration Curve Framework	43
Figure B-7    Concentration-Based TMDL	44
Figure B-8    TSS Loading Capacity Using Duration Curve Framework	45
Figure B-9    Middle Fork LeBuche River TMDL Using Duration Curve Framework . 47
Figure B-10   Bacteria Loading Capacity Using Duration Curve Framework	48
Figure B-ll   Development of E. Coli Upper Target	49
Figure B-12   Development of Daily Value Based on Monthly Target	50
Figure B-13   Relationship Between 30-day Geometric Mean and Daily Target	51
Figure B-14   Monthly Bacteria Loading Capacity Using Duration Curve Framework . 53
Figure C-1    Duration Curve as General Indicator of Hydrologic Condition	57
Figure C-2    Duration Curve with Contributing Area Focus	58
Figure C-3    Duration Curve with Targeted Activity Focus	59
Figure C-4    Duration Curve with Delivery Mechanism Focus	60
Figure C-5    Documenting Program Results Using Duration Curve Framework	63
Figure C-6    Documenting Program Results Using Duration Curve Framework	63
                               List of Tables

Table 2-1    Approaches for Developing TMDL "Margin of Safety"	6
Table 2-2    Example TMDL Using Duration Curve Framework	8
Table 4-1    Example Source Area / Hydrologic Condition Considerations	16
Table 5-1    Example TMDL Summary Using Duration Curve Framework	18
Table B-l    Calculation of Chloride Loads	38
Table B-2    Calculation of Phosphorus Loads	39
Table B-3    Calculation of Bacteria Loads	43
Table B-4    Middle Fork LeBuche River TMDL Summary	46
Table B-5    Werbaldo Creek TMDL Summary	51
Table B-6    Swamp Creek Monthly Mean Flows	52
Table C-l    Example Management Practice / Hydrologic Condition Considerations... 62
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An Approach for Using Load Duration Curves in the Development of TMDLs
1.     DEVELOPMENT OF FLOW DURATION CURVES

la.    What is a Flow Duration Curve?

Flow duration curve analysis looks at the cumulative frequency of historic flow data over
a specified period. A flow duration curve relates flow values to the per cent of time those
values have been met or exceeded.  The use of "percent of time " provides  a uniform
scale ranging  between 0 and 100.   Thus, the full range of stream flows is considered.
Low flows are exceeded a majority of the time, while floods are exceeded infrequently.

A basic flow  duration curve runs  from high to low along the x-axis, as illustrated in
Figure 1-1. The x-axis represents the duration amount, or "percent of time ", as in a
cumulative frequency distribution.  The y-axis represents the flow value (e.g., cubic feet
per second) associated with that "percent of time " (or duration).

Flow duration curve development typically uses daily average discharge rates, which are
sorted  from the  highest value to the lowest (Figure  1-1).  Using this convention,  flow
duration intervals are expressed as a percentage, with zero corresponding to the highest
stream discharge in the record (i.e., flood conditions)  and 100 to the lowest (i.e., drought
conditions). Thus, a flow duration  interval of sixty associated with a stream discharge of
440 cubic feet per second (cfs) implies  that sixty percent  of all  observed daily average
stream discharge values equal or exceed 440 cfs.

                Figure 1-1.  General Form of the Flow Duration Curve
                           Salt Creek near Greenview, TT,
                                 Flow Duration Curve
                                 USGSGage: 055S2000
                                                     Dry
                                                   Conditions
                                                 1 ' ' I ' ' '  ' I
             0     10
                       20
                            Flow Duration Interval (%)
     USGS Flow Data
                                                                 1,804 square miles
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An Approach for Using Load Duration Curves in the Development of TMDLs
lb.    Where to Get Flow Information

Information on  river flows across  the  United States is
readily  available from  the  U.S.   Geological   Survey
(USGS). Stream flow conditions on any given day can be
highly variable, depending on watershed characteristics
and  weather  patterns.    Due to  the  wide  range  of
variability that can occur in stream flows,  hydrologists
have long been  interested in knowing the percentage of
days in a year when given flows occur. The mechanics of
constructing  the flow  duration  curve  in  Figure  1-1
involved three steps.  Daily average flow data was first
downloaded  from  the  USGS   National  Web   site
(http://waterdata.usgs.gov/nwis/sw).   Data was then read
into  a spreadsheet to determine duration curve intervals
covering the full range of flows.  Lastly, flow duration
curve information was copied from the spreadsheet into a
graphics package to create the labeled display.
Not all waters or watersheds have gaging stations or flow data available. In such cases
estimation techniques are needed (USEPA, 2007). For instance, it may be appropriate to
use flow data of a similar, representative water body to develop the duration curve, based
on regression methods or drainage area ratios.  The use of rainfall / runoff models can
also be used to develop stream flow estimates for use in a duration curve analysis.

Ic.    Duration Curve Intervals and Zones

Duration curve analysis identifies intervals, which can be used as a general indicator of
hydrologic condition (i.e., wet versus dry  and to what degree).  Flow duration curve
intervals can be grouped  into several broad categories or zones.  These zones provide
additional insight about conditions  and patterns associated  with the  impairment.  A
common way to look at the duration  curve is by dividing it into five zones, as illustrated
in Figure 1-1:  one representing high flows (0-10%), another for moist conditions (10-
40%), one covering mid-range flows  (40-60%), another for dry conditions (60-90%), and
one representing low flows (90-100%).

This particular approach places the midpoints of the moist, mid-range, and dry zones at
the 25th, 50th, and  75th percentiles  respectively (i.e., the quartiles). The high zone is
centered at the 5th percentile, while the low zone is centered at the 95th percentile. Other
schemes can be used, depending  on  local hydrology and the  water quality issues being
addressed by assessment efforts.  For example, Figure 1-2 shows a flow duration curve
for a stream in the arid Southwest, where there is no flow more that half the time.  In this
case, an alternative approach might consider use of  two, three, or four zones, depending
on the water quality concerns being addressed by the TMDL.  Again, the benefit of using
zones is to provide insight regarding patterns associated with concerns.
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An Approach for Using Load Duration Curves in the Development of TMDLs
                Figure 1-2.  General Form of the Flow Duration Curve

                           Rio Puerco near Guadalupe, NM
                                 Flow Duration Curve
                                 USGSGage: 08334000
              X
         s
         o
69 eft
                               3.8 eft
                                               Dry Conditions with
                                                   No Flow
                                              I ' '  ' ' I ' ' ' ' I ' ' '
                   10    W    30    40    50     60    70    80

                             Flow Duration Interval (%)
                                                              90
       USGS Flow Data
                                                                   100
                                                                 420 square miles
2.     DEVELOPMENT OF LOAD DURATION CURVES AND TMDLs

Flow duration curves serve as the foundation for development of load duration curves, on
which  TMDLs can be based. A load duration curve is developed by multiplying stream
flow with  the  numeric water quality  target (usually a water quality criterion)  and a
conversion factor for the pollutant of concern.  The following section provides a general
discussion of the elements to be addressed in developing a TMDL using the load duration
curve framework.  A specific case  study is presented in Appendix A, which illustrates
how this framework was applied to develop a fecal coliform TMDL.

2a.    Numeric Water Quality Targets

The numeric water  quality target  represents the quantitative  value  used to  measure
whether or not the applicable water quality standard (WQS) is attained.  Generally, the
target is the water quality criterion  contained in the WQS for the  pollutant of concern.
The target may be constant across all flow conditions (e.g., chloride, nitrate, phosphorus,
or bacteria).  The  target could also  vary with flow (e.g., sediment). Because the water
quality  criterion is crucial in the development of the loading capacity, the absence of
numeric criteria poses  challenges  (e.g., sediment, nutrients).  As efforts continue to
develop and adopt numeric sediment and/or nutrient criteria, practitioners should evaluate
whether an appropriate interim or site-specific, numeric  endpoint can be identified prior
using the duration framework for TMDLs.  Otherwise, alternative analytical  methods
should be explored.
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An Approach for Using Load Duration Curves in the Development of TMDLs
Numeric water quality targets are translated into TMDLs through the loading capacity.
EPA's current regulation defines loading capacity as "the greatest amount of loading that
a water can receive without violating water quality standards".  The loading capacity
provides a reference, which helps guide pollutant reduction efforts needed to bring a
water into compliance with standards.

Basic hydrology represents  a logical starting point to identify a loading capacity.  First,
loads are directly proportional to flows (i.e., load equals flow times concentration times a
conversion factor).  Second, water quality  parameters  are often related to stream flow
rates.  For instance, sediment concentrations typically increase with rising flows as a
result of factors such as channel scour from higher velocities. Other parameters, such as
chloride, may be more concentrated at low flows and  more diluted by increased water
volumes at higher flows.

Flow patterns play  a major role when  considering loading capacities in TMDL
development, regardless of the technical approach used.   Duration curves, however,
provide the added benefit of looking at the full range of flow conditions.  Figure 2-1
illustrates  an  example  loading  capacity  curve  developed using  a  duration  curve
framework based on the flow duration curve shown in Figure 1-1. A sample calculation
is  shown at one point along the curve corresponding to a flow duration interval of 60
using a nitrate target of 10 mg/L.  Appendix B provides specific details on how loading
capacity duration curves are developed for use in TMDLs.

       Figure 2-1.  Nitrate Loading Capacity Using Duration Curve Framework

                            Salt Creek near Greenview, IL
                                 Load Duration Curve
         10000
          1000
 ^
"a
              High
              Flows
                  Moist
                Conditions
Mid-range
  Flows
  Dry
Conditions
Low
Flows
                                         440 eft  * 10 mg/L  * 0.002695
                                              = 11.86 tons /day
                  10
                            Flow Duration Interval
                                                                  1,804 square miles
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An Approach for Using Load Duration Curves in the Development of TMDLs
2b.    Interpreting Load Duration Curves to Assess Water Quality

When using the duration curve framework in the context of developing a TMDL, it is
important to keep in mind that the entire duration curve should be applied to account for
the various flow regimes.   Ambient  water quality data, taken with some measure  or
estimate of flow at the time of sampling, can be  used to compute  an instantaneous load.
Using the relative percent exceedance from the flow duration curve that corresponds to
the stream discharge at the time the water quality sample was taken, the computed load
can be plotted in a duration  curve format (Figure 2-2).

By displaying instantaneous loads calculated from  ambient water quality data and the
daily average flow on the date  of the sample (expressed as a flow duration  curve
interval),  a pattern develops,  which  describes the  characteristics of the water quality
impairment. Loads that plot above the curve indicate an exceedance of the water quality
criterion, while those below the load duration curve show compliance.

The pattern of impairment can be examined to see if it occurs across all flow conditions,
corresponds strictly to high flow events, or conversely, only to low flows.  Impairments
observed in the  low flow zone typically indicate the influence of point sources,  while
those further left generally  reflect potential nonpoint source contributions.  This concept
is illustrated in Figure 2-2. Data may also be separated by season (e.g.,  spring runoff
versus summer base flow).  For example, Figure 2-2 uses a "+" to  identify those ambient
samples collected during primary contact recreation season (April - October).

     Figure 2-2.   Ambient Water Quality Data Using a Duration Curve Framework
                  I Group by Hydrologic Condition      |
 Identify
  - Storm flows
  - Season
                  10    20    30    40    SO    60    70

                          Flow Duration Interval
90    100
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An Approach for Using Load Duration Curves in the Development of TMDLs


The utility of duration curve zones for pattern analysis can be further enhanced to
characterize wet-weather concerns.  Some measure or estimate of flow is available to
develop  the  duration curves.   As a result,  stream discharge measurements on  days
preceding collection of the ambient water quality sample may also be examined.  This
concept is illustrated in Figure 2-2 by comparing the flow on the day the sample was
collected with the flow on the preceding day.  Any one-day increase in flow (above some
designated  minimum threshold) is assumed to be the result of a surface runoff event
(unless the stream is regulated by an upstream reservoir). In Figure 2-2, these samples
are identified with a shaded diamond.

2c.    Margin of Safety

A "margin of safety" (MOS) is typically  expressed  either  as unallocated assimilative
capacity  or as conservative analytical assumptions used in establishing the TMDL (e.g.,
derivation  of numeric  targets,  modeling  assumptions  or  effectiveness  of  proposed
controls). The "margin of safety" may be explicitly stated as an added, separate quantity
in the TMDL  calculation.  The  "margin  of safely"  may  also be  implicit,  as in
conservative  assumptions.  Table 2-1 presents six common approaches for incorporating
a "margin  of safety" into TMDLs.  Some States may have established approaches for
determining the MOS either explicitly or implicitly as a step in their TMDL development
process (as indicated in Table 2-1).  These approaches  should be taken into consideration
when identifying the MOS using a duration curve framework.

          Table 2-1.  Approaches for Developing TMDL "Margin of Safety"
       Type of                                .        ,
  T»/T    -eve*                            Approaches
  Margin of Safety                             vv
       Explicit
Set numeric targets at more conservative levels than analytical
results indicate
Add a safety factor to pollutant loading estimates
Do not allocate part  of available loading capacity; reserve for
MOS
       Implicit
Conservative assumptions in derivation of numeric targets
Conservative assumptions  when developing  numeric model
applications
Conservative   assumptions   when   analyzing   prospective
feasibility of practices and restoration activities.
Using a duration curve framework, one option could be to identify an explicit "margin of
safety" for each listed reach and corresponding set of flow zones. For example, one way
to define the MOS could be based on the difference between the loading capacity as
calculated  at the  mid-point of each of the five flow zones, and the loading capacity
calculated at the minimum flow in each zone.  Given that the loading capacity is typically
much less  at the  minimum flow of a zone as compared to the mid-point, a substantial
"margin of safety" is provided. The "margin of safety" ensures that allocations will not
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An Approach for Using Load Duration Curves in the Development of TMDLs
exceed the load associated with the minimum flow in each zone.  This approach also
allows for recognition that the uncertainty associated  with  effluent limits and  water
quality may vary across different flow conditions.  For instance, because of changes in
variability  at different flow regimes, the uncertainty may be greater under high flow
conditions than at low flow (or vice versa).

Because  the allocations  are  a direct function  of flow,  accounting for potential  flow
variability is an appropriate way to address the "margin of safety".  Although minimum
flows over  long  periods  of  record  at the USGS gage  sites  are typically used  when
defining the MOS for the low flow zone, the effect of point source discharges on effluent
dominated  streams should also be considered.  Adjustments to the MOS may be needed
to account for situations where the only flow under low flow conditions is treatment plant
discharges.

An explicit "margin of safety" identified using a duration curve framework is basically
unallocated assimilative capacity intended to account for uncertainty (e.g., loads from
tributary  streams, effectiveness of controls, etc.).  As new information becomes available,
this  unallocated capacity may be  attributed to nonpoint sources including  tributary
streams (which could then be added to the load allocation);  or it may be attributed to
point sources (and become part of the waste load allocations).

2d.    Development of Allocations

Allocations represent those portions of a receiving water's loading capacity attributed to
point sources (waste load  allocations) or to nonpoint sources and  natural  background
(load allocations).  Allocations are a key part of the TMDL; they represent the basic road
map to water quality standards attainment.  The duration curve framework provides a
reasonable way to  define allocations  because  it  allows adjustments,  which reflect
differences in the types of sources that may be dominant under various flow conditions.

For  instance, in effluent dominated streams wastewater treatment  facilities (WWTFs)
exert a significant influence  on water quality at low flows.   Under a duration  curve
framework, the allocation or portion of the loading capacity attributed to WWTFs can be
greater in the low flow zone.  Similarly, runoff from nonpoint sources tends to  dominate
water quality under high  flow conditions.  Thus, the allocation or portion of the loading
capacity for nonpoint sources can be greater under moist and high flow conditions using a
duration curve framework.

Waste load allocation development for continuous point source discharges is relatively
straightforward using a duration curve framework.   Consideration  of pollution control
measures is typically done in  conjunction with NPDES permit development.  Waste load
allocations (WLAs)  can be expressed  at one level  across the entire duration  curve, or
WLAs may be tiered to specific flow levels and the corresponding flow duration interval.
Common methods used for allocating waste loads described in TMDL guidance (EPA,
1991) include equal percent removal, equal effluent concentrations, and hybrid methods.
These allocation schemes can easily be applied to a duration curve framework.
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An Approach for Using Load Duration Curves in the Development of TMDLs
Storm water and nonpoint sources of pollutants, on  the other hand, present  a  greater
challenge because pollutants are transported to surface  waters by a variety of mechanisms
(e.g., runoff, snowmelt, groundwater infiltration).  Best management practices (BMPs)
generally focus on source control and / or delivery reduction.  Common methods in use to
develop  either WLAs for storm water or load allocations for nonpoint sources are also
applicable  under a  duration  curve framework.   Examples include consideration  of
jurisdictional area, land use, or impervious cover.

An advantage of the duration curve  framework is that allocations can be adjusted by
zone. This may be needed to account for different source areas and delivery mechanisms
that may dominate under different  flow  conditions.  Table 2-2 summarizes the  TMDL
framework using the duration curve  approach, showing the TMDL (equivalent to the
loading capacity), the "margin of safety", and the amount available for allocations (both
load and waste load).

             Table 2-2.  Example TMDL Using Duration Curve Framework
Segment
ID
Q21-01
Name
TMDL
Component
Quepote Brook



KorstonDPW (WWTP)
Loburn (WWTP)
KorstonDPW (MS4/P1)
Loburn (MS4/P2)
TMDL
MOS
LA
WLA
WLA
WLA
WLA
Duration Curve Zone
(Expressed as T-org/day)
High
Moist
Mid
Dry
Low

19.87
4.31
9.18
0.12
0.05
3.81
2.40
9.37
3.92
3.10
0.12
0.05
1.33
0.85
4.09
0.76
1.88
0.12
0.05
0.80
0.48
2.20
0.66
0.79
0.12
0.05
0.36
0.22
1.29
0.77
0.35
0.12
0.05
0.00
0.00
Figure 2-3 illustrates a TMDL using a duration curve framework. Waste load allocations
are specified for municipal treatment plants that reflect NPDES permit limits. In the case
of both Table 2-2 and Figure 2-3, these waste load allocations are based on technology-
based effluent limits at facility design flows. The waste load allocations are  constant
across all flow conditions and ensure that water quality standards will be attained.

Waste load  allocations are also identified for municipal separate storm  sewer systems
(MS4),  which reflect increased loads under higher flow conditions.  In the Figure 2-3
example,  storm  water waste load allocations for MS4 communities  are  based on the
percent jurisdictional area approach.  In this case, three percent of the watershed falls
within the jurisdiction of MS4 communities.  Thus, the MS4 wasteload allocation is three
percent of the available allocation for each zone.   The remaining ninety-seven percent is
designated for nonpoint sources and natural background as load allocation for each zone.
Load allocations and MS4 waste load allocations have been determined at the mid-point
of each zone based on appropriate portions.  The allocation curves are  determined by
interpolating between these points.
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An Approach for Using Load Duration Curves in the Development of TMDLs
           Figure 2-3.  Example TMDL Using Duration Curve Framework
                                    Jones River
                                  TMDL Summary
         10000
                Waste Load Allocation — Wastewater Treatment Facilities
                  I	1	1	1	1	1	1	1	1
                  10
20
30
40
SO
60
70
80
90    100
                            Flow Duration Interval (%,
2e.    Seasonal Variation

The Clean Water Act (CWA) §303(d) states that in identifying TMDLs: "such load shall
be established at a level necessary to implement the applicable water quality standards
with  seasonal  variations".   Seasonal  variation  in flow is  a  key part of  TMDL
development.  Figure 2-4 shows an example of seasonal  flow patterns  using monthly
statistics for the Mississippi River at Winona.  Flow is expressed as a unit area rate (i.e.,
cubic feet per second (cfs) per square mile). Unit area rates, determined by dividing the
drainage area at the gage into the flow, enable a consistent way to compare flows from
watersheds of different sizes.

Another way to view seasonal  variation is through the use of  flow duration  curves.
Figure 2-5 illustrates monthly flow data expressed  as duration curve intervals  for the
Mississippi River at Winona.  The "box and whisker" format allows analysis of general
patterns by conveying information on the distribution of the data.  For example, April
flows for the Mississippi River at Winona and its tributaries are typically in the high and
moist zones (median flow around 9%). Accordingly, consideration of seasonal variation
in TMDL development and implementation planning to address water quality concerns in
April would focus  on  source areas typical of these  conditions.   For this region, moist
conditions in April  generally reflect more saturated soil conditions, when upland  sources
such as cultivated fields exert a greater influence on stream flow and water quality.
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An Approach for Using Load Duration Curves in the Development of TMDLs
                  Figure 2-4.  Mississippi River Seasonal Flow Patterns
                               Mississippi River at Winona
                                        (1970-2004)
          2.0
          1.5--
        g.
          0.5 --
          0.0


                         r
90th
75th
                                                                            Median
                                                                            25th
                                                                            10th
                                                          Watershed Size: 59,200 square miles
                    Figure 2-5.  Mississippi River Monthly Variation
                               Mississippi River at Winona
                                        (1970 - 2004)
Flow Duration Interval (%)
3 00 Ot -t*. W
3 O O O O O
Month
|-J-| | | — | Median = 9%
T0II-
1 *

;
J Median = 46%

1
^
/
1

y
T


^

1
^






April-Oct Zone
|^ 	 |»OUi |


pc



^-LTSthJ
^— 1 Median |

*^^]
-^

/f/gA
Moist
Mid
Dry
Low


* Aierage

                                                          Watershed Size: 59,200 square mites
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   August 2007

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An Approach for Using Load Duration Curves in the Development of TMDLs
Conversely, August and September flows generally fall in the mid-range zone (median
flow around 46%).  Flows from tributary rivers to the upper Mississippi are even lower,
typically falling into the dry zone during these months.  This shifts TMDL development
and implementation planning to  source areas representative of these conditions.   For
these tributaries to the Mississippi River, source assessment and implementation planning
might focus on wastewater treatment plant discharges or activities that have a direct
influence on streamside riparian areas (e.g., straight pipes and livestock access).

2f.     Summary

The use of duration curves provides a technical framework for identifying "daily loads"
in TMDL development, which  accounts for  the  variable nature  of water  quality
associated with different stream flow rates. Specifically, a maximum daily concentration
limit can be used with basic hydrology and a duration curve to identify a TMDL that
covers the full range of flow conditions. With this approach, the maximum "daily load"
can be identified for any given day based on the stream flow. Identification of a loading
capacity  using the duration curve framework is driven by  the flow duration curve and a
water quality  criterion or target value.  The target  may be constant across all  flow
conditions (e.g., chloride) or the target may vary with flow  (e.g., sediment rating curves).

Under the duration curve framework, the loading capacity is essentially the curve itself.
The loading capacity, which sets the "total maximum daily load" on any given day, is
determined by the flow on the particular day of interest.  The use of duration curve zones
can help provide a simplified summary through the identification of discrete loading
capacity  points by  zone. Using a duration  curve framework, an  explicit "margin of
safety"  can be identified for each listed reach and corresponding set of flow zones.
Allocations within the TMDL are set in a way that reflects dominant concerns associated
with appropriate hydrologic conditions.

Appendix  B includes  example  calculations  for chloride,  nitrate,  phosphorus,  total
suspended  solids, and bacteria.  Appendix B also provides a  discussion  on ways the
duration  curve framework can be used to address different averaging periods (other than
daily) in identifying loading capacities, particularly where a concentration-based target
exists (expressed as monthly, seasonal, or annual average values).
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An Approach for Using Load Duration Curves in the Development of TMDLs
3.     APPROPRIATE USE OF LOAD DURATION CURVES

A few words about the appropriate use of the duration curve approach follow. First and
perhaps most importantly,  water quality analysts should assess the  appropriateness  of
using this framework to develop a particular TMDL. Practitioners should also consider
the suitability of using it as the sole basis for assessment versus supplementing its use
with other analytical tools, such as water quality models.

3a.    Appropriate When Flow is Primary Driver

An underlying premise of the  duration curve approach is correlation of water  quality
impairments to flow conditions.  The duration curve alone does not consider specific fate
and  transport  mechanisms, which may vary depending on  watershed or pollutant
characteristics.  Such  processes may include sediment  attenuation, plant uptake  of
nutrients, or chemical transformations.

The  duration  curve  is more appropriate in  cases where flow is a primary driver  in
pollutant delivery mechanisms, and other processes are a relatively insignificant part of
the total loading.  Flow, in many cases, is the principal force behind habitat modification,
stream bank erosion, and other concerns preventing attainment of designated uses.  Use
of a duration  curve in flow-induced nonpoint source situations more generally reflects
actual loadings than in cases where flow is only one of many components influencing the
overall loading. Practitioners should consider using a separate analytical tool to  develop
a TMDL  when factors other  than  flow significantly affect a water body's  loading
capacity.  For example, use of the duration curve approach may not work in situations
involving lakes or large coastal embayments, where factors other than stream flow exert a
major effect on observed water quality conditions.

3b.    Water Quality Standards Designed for All Flow Regimes

Another assumption behind the duration curve framework is that applicable water quality
standards  are  protective of the  designated  use(s) over the  entire flow  regime.  For a
majority of pollutants, water quality criteria do not identify  specific restrictions.  When
these special conditions exist, practitioners should  evaluate the appropriateness of the
duration curve method, or determine if there is a means to work within those provisions.

A possible scenario of a flow provision is where criteria explicitly state applicability at
the 7Q10 flow.  This reduces the importance of the criteria during the remaining flows
(e.g., moderate to wet weather).  In this example, the utility of the duration curve method
is better  suited as a diagnostic  tool identifying magnitude  and frequency of concerns
across all flows. Similarly, the State adopted water quality standards may include a  flow
exemption  (e.g., high flows), which should be considered when using the duration curve
framework for TMDL  development.  Another situation may be where the bacteria
criterion applies only during the swimming season.  In order to work within this type of
provision,  the  duration  curve  could be analyzed for just the relevant months  or  time
period.
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An Approach for Using Load Duration Curves in the Development of TMDLs
4.     CONSIDERATIONS

This section discusses  some  potential  concerns and  considerations with utilizing the
duration curve approach to develop TMDLs.
4a.    Source Characterization

The duration curve method, by itself, is limited in the ability to track individual source
loadings or relative  source  contributions within a watershed. Additional  analysis is
needed to identify pollutant contributions from different types of potential sources  and
activities (e.g., construction  zone versus agricultural  area)  or individual sources of a
similar source category (e.g., WWTF #1 versus WWTF #2). Without such analysis, it
could be difficult to distinguish WLAs and LAs for individual sources.

Practitioners  interested  in  more precise  source  characterization  should  consider
supplementing the duration  curve framework with a  separate  analysis.   An  added
analytical tool might aid  in evaluating allocation scenarios and  tracking individual
sources or source categories.  This could allow for improved targeting of monitoring and
restoration activities.

Information about individual sources could also be made available,  where existing load
contributions  and  reductions are  central to evaluating potential  water quality trading
options.  For example, a duration curve analysis might highlight the importance of low
flow, point source issues.  Depending on the manner in which the analysis is applied, the
resulting TMDL could be based on the assumption that all point sources should be treated
the same (i.e., the same loading  from  each source despite their relative location  in the
watershed and existing effluent loads).

Use of a separate or supplemental analysis is also beneficial in cases  where bacteria pose
a water quality  problem.   In this context, applying a duration  curve in concert with
microbial or bacterial source tracking data might allow for distinction of various bacteria
sources (i.e.,  domestic  pet, human, geese, deer, etc.).  This  information  can provide
direction on how the TMDL loadings could be allocated. For instance, practitioners may
choose to impose load reductions to sources that are anthropogenic  or controllable,  and
carry over wildlife sources at existing loading rates.
4b.    Large Scale Watershed SituationsError! Bookmark not defined.

Depending on the pollutant of concern as well as the number and types of sources, it can
be beneficial  to  divide a watershed into subwatersheds as a first step  in the TMDL
development  process.  Basically,  a  duration curve  analysis  is  performed for  each
subwatershed, resulting in multiple, more refined loading capacity curves and subsequent
allocations.   Working on a subwatershed level is important  in addressing issues with
relative source contributions or spatial variations in the loading  capacity, and can be
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An Approach for Using Load Duration Curves in the Development of TMDLs
useful in  calculating  more site-specific allocations.   The following examples illustrate
when it might be necessary to discern  relative  source contributions, isolate impaired
waters, or address spatial variation.

    •   Discerning relative  source contributions.   In  cases involving  multiple point
       sources within a watershed, where each point source has a different effect on the
       receiving water, it might be useful to evaluate each point source individually (i.e.,
       divide the watershed so that some or all of the point sources are isolated).  The
       resulting  duration curves  could  show that the loading of  one point  source
       comprises a larger portion its relative loading capacity than another, potentially
       highlighting the relative impact of each point source.  When there  are multiple
       nonpoint  source  loadings,  applying  the   duration  curve  framework  on  a
       subwatershed scale may also help  to reveal more localized impacts.

    •   Isolating impaired waters.  Sometimes only a few tributaries within  a watershed
       are impaired,  warranting  a TMDL  analysis on a smaller  scale.   Rather than
       evaluating the entire watershed, isolating the impaired tributaries into individual
       subwatersheds  can  allow for a more meaningful,  site-specific  duration  curve
       analysis.

    •   Addressing spatial variation in loading capacity.  Larger watersheds comprised of
       multiple second and third order  streams often  exhibit a range  of  assimilative
       capacities in different parts of the watershed.  An illustration  of an extreme case is
       the differing loading capacities of a headwater stream versus a first-order stream
       near the mouth of a watershed.  As such, it might be advantageous to divide a
       larger watershed into smaller units.

It is important to note that subwatersheds  are interconnected, which may  need to be
accounted for on a case-by-case basis.  Also, dealing with ungaged, headwater streams
could present some obstacles in constructing a duration curve, as there is usually less data
available on such waters.

4c.    Range of Flows Versus Single Condition

Summarizing a duration or loading capacity curve into a single point may be practicable
from  an implementation  standpoint, but could negate the strength of the duration curve
framework.  One aspect of concern regarding this practice is the  selection of a single
condition  (i.e., one point as opposed to using the entire  curve).  Some TMDLs focus on
capturing  the magnitude of the highest observed exceedance.  However, such TMDLs
may  be  overly protective  of the water quality  standard,  potentially  inviting issues
regarding reasonable  assurance.  Alternatively, some TMDLs focus  on the average or
median flow exceedance value, potentially resulting in allocations that are not protective
enough during higher flow events. For this reason  it is appropriate to apply the entire
duration curve in the  context of a TMDL.  Another option is to categorize  the duration
curve into several zones, allowing the resultant TMDL to adequately capture different
types of flow events.
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An Approach for Using Load Duration Curves in the Development of TMDLs
4d.    Storm Events and Hydrograph Separation

Surface  runoff  following rain  events  can be  one of  the  most  significant transport
mechanisms of sediment and other nonpoint source pollutants. Precipitation is obviously
the driving mechanism responsible  for  storm  flows and  associated  surface runoff.
Rainfall / runoff models, such as HSPF, SWAT, or SWMM, are generally used to provide
detailed estimates of the timing and magnitude of storm flows. However, these can also
be very rigorous and time-consuming approaches.

Use of duration curves can help provide another method to examine general watershed
response patterns. Streamflow hydrographs can be separated into base-flow and surface-
runoff components (Sloto and Grouse, 1996).  The base-flow  component is traditionally
associated  with groundwater  discharge   and  the   surface-runoff  component  with
precipitation  that enters the stream as overland flow.   Information  from hydrograph
separation can be displayed using duration  curve intervals to examine the percentage (or
fraction) of total flow that consists of base flow and storm flow.

Figure 4-1  illustrates the potential  effect that storm flows may exert across the range of
flow conditions,  grouped by duration curve zone using data for the LaPlatte River.  In
Figure 4-1, surface runoff has its greatest effect during  high flow conditions (median
value of 61 percent).   In such cases, sediment and other pollutants delivered to stream
systems associated with surface erosion will also be greatest during high flows.

       Figure 4-1. Fraction Analysis of Storm Flow Relative to Total Streamflow

                           LaPlatte River at Shelburne Falls
                         Storm Flow Duration Curve (1990-2005)
             High
             Flows
Mid-range
  Flows
                         Note:  Increased fraction of surface runoff
                               under high flow conditions
            0    10    20    30    40    50    60    70    80    90    100

                           Flow Duration Interval (%)
      USGS Gage Duration Interval & Hydrograph Separation                      44.6 square miles
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An Approach for Using Load Duration Curves in the Development of TMDLs
4e.    Utility in Identifying Potential Source AreasError! Bookmark not defined.

Duration curves are based on the entire range of flow conditions observed for any given
drainage.  A major advantage of their use is the ability to consider the general hydrologic
condition of  the  watershed,  and  subsequently,  to enhance  development  of  source
assessments.   Pollutant delivery mechanisms likely to exert the  greatest  influence on
receiving waters (e.g.,  point source discharges,  surface  runoff) can  be matched with
potential source areas appropriate for those conditions (e.g., riparian zones, impervious
areas, uplands).  Table 4-1 illustrates an approach, as a simple example, which could be
used to  assess  source  areas based on  the  potential relative importance of delivery
mechanisms under the range of hydrologic conditions.

       Table 4-1.   Example Source Area / Hydrologic Condition Considerations
Contributing Source Area
Point Source
On- site waste water systems
Riparian Areas
Storm water: Impervious Areas
Combined sewer overflows
Storm water: Upland
Bank erosion
Duration Curve Zone
High
Flow




H
H
H
Moist


H
H
H
H
M
Mid-
Range

H
H
H
H
M

Dry
M
M
H
H



Low
Flow
H






Note: Potential relative importance of source area to contribute loads under given
hydrologic condition (H: High; M: Medium)
Table 4-1  describes an array of potential contributing source areas common to many
watersheds where TMDLs are being developed.  This table provides an organizational
framework, which can be used to guide source assessment efforts.  For instance, point
sources tend  to  have the  most  dominant  effect on  water quality under  low flow
conditions.  Thus, Table 4-1 identifies the low flow zone as a relative high priority for
assessment of point sources.

Similarly, surface runoff from upland sources tends  to exert a  greater effect on water
quality during higher flow conditions (e.g., high, moist,  mid-range zones).  Accordingly,
Table 4-1 identifies these zones as a relative  high priority for assessment of storm water
sources from upland areas.

Ambient water quality monitoring data displayed in a duration curve  framework (as
shown earlier in  Figure 2-2) coupled with the Table 4-1 format can also  help identify
potential source  areas more likely  to  dominate under the different zones.   Patterns
associated with certain source categories are often apparent when visually assessing data
by flow conditions.
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An Approach for Using Load Duration Curves in the Development of TMDLs
5.     CONNECTING TO IMPLEMENTATION AND RESULTS

A major advantage of the duration curve framework in TMDL development is the ability
to provide meaningful  connections  between allocations and  implementation efforts.
Because the flow duration interval  serves as a general indicator of hydrologic condition
(i.e., wet versus dry and to what degree), allocations and reduction targets can be linked
to source areas, delivery mechanisms, and the appropriate set of management practices.
The use of duration curve zones (e.g., high flow, moist, mid-range, dry,  and low flow)
allows the development of allocation tables, which can be used to summarize potential
implementation actions that most effectively address water quality concerns.

In general, wasteload allocations from WWTPs exert a significant influence under low
flows.  For total sediments, high flow conditions may result in  stream bank erosion and
channel processes playing a greater role.  For urban watersheds, water quality  concerns
during mid-range flows and moist conditions might be best addressed through low impact
development techniques or site construction BMPs,  as  illustrated in Figure 5-1.  For
agricultural areas, appropriate implementation efforts might include activities under such
provisions  as the Conservation Reserve Program  (CRP)  and Conservation Reserve
Enhancement Program (CREP).

Appendix C provides  an expanded discussion  on the utility of the duration  curve
framework in targeting potential solutions and connecting to  implementation  and results.
Included is a form similar to Table 4-1, which could be used  to assess  and target the
management options appropriate for the different flow conditions.

              Figure 5-1. Duration Curve  with Contributing Area Focus
                           Willow Creek near Turkey Gap
                                                                 100
                            Flow Duration Interval (%)

      TARGETED Activities:  Construction Site Runoff Control
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An Approach for Using Load Duration Curves in the Development of TMDLs
A common challenge faced  by TMDL  practitioners  is explaining how allocations
translate into potential actions. Table 5-1 uses a duration curve framework to summarize
TMDL  targets in a way  that highlights  implementation opportunities.   Figure 5-2
illustrates how a  duration curve framework can be used to document results following
implementation of erosion controls,  showing those zones where  "on the ground" efforts
were most effective.  These summaries can be combined  with  other basic  elements of
watershed planning to help guide problem solving discussions in a meaningful way.

        Table  5-1. Example TMDL Summary Using Duration Curve Framework
TMDL
SUMMARY
TMDL1
Allocations
Margin of Safety
Implementation
Opportunities
Loads expressed as (tons per day)
High
173.35
118.32
55.03
Post
Development
BMPs
Streambank
Stabilization
Moist
67.20
48.24
18.96

Mid-Range
40.21
34.47
5.74

Erosion Control Program

Dry
27.57
21.83
5.74

Riparian Buffer Protection

Low
18.96
6.90
12.06

Municipal WWTP
Note: 1- Expressed as a "daily load"; represents the upper range of conditions needed to attain
and maintain applicable water quality standards
             Figure 5-2.  Documenting Erosion Control Program Results

                                    Quail Fork
                    10
                         20
                             30
                                  40
                                      50
                                                70
                                                    80
                                                         90
                                                             100
                            Flow Duration Interval (%)
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An Approach for Using Load Duration Curves in the Development of TMDLs
                           APPENDIX A

                Load Duration Curve TMDLs —
                            Case Example
                Pee Dee River Basin, South Carolina
                        Fecal Coliform TMDL
This appendix describes a case example where load duration curves were used to support
TMDL development.  The example is taken from a fecal coliform TMDL prepared by the
South Carolina Department of Health and Environmental Control (DHEC), which was
developed to address  impairments in sixteen segments of thirteen waters in the Pee Dee
River Basin (Hills Creek, Lynches River, North and South Branch of Wildcat Creek, Flat
Creek, Turkey Creek, Nasty Branch, Gulley Branch, Smith Swamp, Little Pee Dee River,
Maple Swamp, White Oak Creek, and Chinners Swamp).

The full TMDL document, available at:

      http://www.scdhec.gov/environment/water/tmdl/docs/tmdl peedee fc.pdf

provides  background information  on  the waterbodies, including water quality and
pollutant  source assessments.   Sections 4  and  5 (titled  "Technical Approach and
Methodology" and "TMDL Calculations")  of the Pee Dee River Basin TMDL are
excerpted into this technical appendix.  These sections describe how the duration curve
framework was used.

Section 4 provides an explanation of steps used to perform TMDL calculations.  Section
5 describes the results of these calculations and how this information was used to address
each component of the TMDL.
                            Pee Dee River Basin
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An Approach for Using Load Duration Curves in the Development of TMDLs


                                  SECTION 4
           TECHNICAL APPROACH AND METHODOLOGY

       A TMDL is defined as the total quantity of a pollutant that can be assimilated by a
receiving water body while achieving the WQS. A TMDL is expressed as the sum of all
WLAs (point  source loads),  LAs  (nonpoint source loads), and  an appropriate MOS,
which attempts to account for uncertainty concerning the relationship  between effluent
limitations  and water quality.

       This definition can be expressed by the following equation:

              TMDL = E WLA + E LA + MOS

The objective  of the TMDL is to estimate allowable pollutant loads and to allocate these
loads to the known pollutant sources in the watershed so the appropriate control measures
can be implemented and the WQS achieved.  40 CFR § 130.2 (1) states that TMDLs can
be expressed in terms of mass per time, toxicity, or other appropriate measures. For fecal
coliform, TMDLs are expressed as cfu per day where possible or as percent reductions,
and represent the maximum one-day load the stream can assimilate while still attaining
the WQS.

4.1    Using  Load Duration Curves to Develop TMDLs

       LDCs are graphical analytical tools that illustrate the relationships between stream
flow and water quality  and assist in  decision making regarding this relationship. Flow is
an important factor affecting the loading and concentration of fecal coliform. Both point
and nonpoint source  loads of pollutants to streams may be affected by changes in flow
regime. Given an understanding of the potential loading mechanisms of fecal coliform,
and how those mechanisms relate  to flow conditions, it is possible to infer and quantify
the major contributing sources of pollutants to a stream by examining the relationship
between flow  and pollutant concentration or load.  Of critical importance is  that the
incremental watershed LDC approach makes effective use of existing data.  The lack of
instream flow data  at  most  water  quality monitoring locations  would typically  be
identified as a  significant data gap for application of watershed and water quality models.
However, since the incremental watershed  LDC approach makes use  of drainage area
ratio-based flow estimates, the lack of flow information at these locations is not limiting.
The incremental watershed approach also allows for assessment  of land use, soil,  and
source contribution differences between observation points.  The fecal coliform  TMDLs
presented in this report are designed to be protective  of typical  flow  conditions.  The
following discussion provides an overview of the approach used  to develop LDCs  and
TMDL calculations. Results and calculations are presented in Section 5.
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An Approach for Using Load Duration Curves in the Development of TMDLs
4.2    Explanation of Steps Used to Perform TMDL Calculations

       The  following  discussion provides a  summary of the steps involved in the
calculation of the key components of the fecal coliform TMDLs presented in Section 5 of
this report.

       Step  1:  Develop  Flow  Percentiles  for each WQM Station.   Direct  flow
measurements are not available for all of the WQM stations addressed in this report.  This
information,  however,  is vitally  important to understanding  the  relationship between
water quality and stream flow.  Therefore, to characterize flow, in  some cases flow data
were derived from a flow estimation model for each relevant watershed.  Flow data to
support development of flow duration curves will be derived for each SCDHEC WQM
station from USGS daily flow records (USGS 2005b) in the following priority:
       i)  In cases where a USGS flow gage coincides with,  or occurs within one-half
          mile upstream or downstream of a SCDHEC WQM station and simultaneous
          daily flow data  matching the water quality  sample date are  available,  these
          flow measurements will be used.
       ii) If flow measurements  at the coincident gage are missing for some dates  on
          which water quality  samples were collected, gaps in  the flow record  will  be
          filled, or the record  extended, by  estimating flow  based on measured
          streamflows at a nearby gage.  First, the most appropriate nearby stream gage
          is identified.  All flow data  are first log-transformed  to linearize the data
          because flow data are highly skewed.  Linear regressions  are then developed
          between  1) daily streamflow  at the  gage to be filled/extended;   and  2)
          streamflow at all gages within 93  miles  (150  kilometers) that have at least
          300 daily  flow  measurements  on  matching dates.  The station with the
          strongest flow relationship, as indicated by the highest correlation coefficient
          (r-squared value), is selected  as the  index gage.  R-squared indicates the
          fraction of the variance in flow explained by the regression. The regression is
          then used to estimate flow at the gage to be filled/extended from flow at the
          index station.   Flows will not be estimated based  on regressions  with
          r-squared values less than 0.25, even if that is the best regression. This value
          was selected based on familiarity with using regression analysis in estimating
          flows. In some cases, it will be necessary to fill/extend flow records from two
          or more index gages.  The flow record will be filled/extended to the extent
          possible based  on the strongest index gage (highest r-squared  value), and
          remaining gaps  will be filled  from successively weaker index gages  (next
          highest r-squared value), and so forth.
       iii) In the event no coincident flow data are available for a WQM station, but flow
          gage(s) are present upstream and/or downstream, flows will be estimated for
          the WQM station  from an upstream or downstream gage using a watershed
          area ratio method derived by delineating subwatersheds,  and relying on the
          Natural Resources Conservation Service runoff curve numbers and antecedent
          rainfall condition.  Drainage subbasins will first be delineated for all impaired
          303(d)-listed WQM stations, along with all USGS flow stations located in the
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An Approach for Using Load Duration Curves in the Development of TMDLs
       Step 2:  Develop Flow Duration Curves.  Flow duration  curves serve as the
foundation of LDC TMDLs.  Flow duration curves are graphical representations of the
flow regime of a stream at a given site.  The flow duration curve is an important tool of
hydrologists, utilizing  the historical hydrologic record  from stream gages  to  forecast
future recurrence frequencies.

       Flow duration curves are a type of cumulative distribution function.  The  flow
duration curve represents the fraction of flow observations that exceed a given flow at the
site of interest.  The observed flow values are first ranked from highest to lowest, then,
for each observation, the percentage of observations exceeding that flow is calculated.
The flow rates for each 5th percentile for each WQM station are provided in Appendix D.
The flow value is read from the ordinate (y-axis), which is typically on a logarithmic
scale  since the high  flows would  otherwise  overwhelm  the  low  flows.   The  flow
exceedance frequency  is read  from  the  abscissa,  which  is  numbered from  0  to
100 percent, and may or may not be logarithmic. The lowest measured flow occurs at an
exceedance frequency  of 100 percent, indicating that flow has equaled or exceeded this
value 100 percent of the time, while the highest measured flow is found at  an exceedance
frequency  of  0 percent.  The  median flow occurs at a flow exceedance frequency of
50 percent.

       While the number of observations required to develop a flow duration curve is not
rigorously  specified, a flow duration curve is usually  based on more than 1 year of
observations, and encompasses inter-annual and seasonal variations.  Ideally, the drought
and flood of record are included in the observations.  For this purpose, the long term  flow
gaging stations operated by the USGS are ideal.

       A  typical semi-log flow duration curve exhibits a sigmoidal shape,  bending
upward near a flow duration of 0 percent and downward at a frequency near 100 percent,
often with a relatively constant slope in between.  However, at extreme low and  high
flow values, flow duration curves may exhibit a "stair step" effect due to the USGS  flow
data rounding conventions  near the limits of quantitation.   The  extreme high  flow
conditions  (<10th percentile) and low flow conditions (>95 percentile) are  not considered
in development of these TMDLs.   The overall slope of the  flow duration curve is an
indication of the flow variability of the stream.

       Flow  duration  curves  can  be  subjectively  divided  into  several  hydrologic
condition classes.  These hydrologic classes facilitate  the diagnostic and analytical  uses
of flow and LDCs.  The hydrologic classification scheme utilized in the development of
these TMDLs is presented in Table 4-1.
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An Approach for Using Load Duration Curves in the Development of TMDLs
                    Table 4-1    Hydrologic Condition Classes
Flow Duration
Interval
0-10%
10-40%
40-60%
60-90%
90-100%
Hydrologic Condition
Class*
High flows
Moist Conditions
Mid-Range Conditions
Dry Conditions
Low Flows
              Source:  Cleland2003.

Step 3:  Estimate Current Point Source Loading.  In SC,  NPDES permittees that
discharge treated  sanitary wastewater must meet  the  state WQS for fecal  coliform
bacteria at the point of discharge (see discussion in Section 2).  However, for TMDL
analysis it is necessary to understand the relative  contribution of WWTPs to the overall
pollutant loading and their general compliance with required effluent limits.  The fecal
coliform load  for continuous point source dischargers was estimated by multiplying the
monthly  average flow rates by the monthly geometric mean using a conversion factor.
The data were extracted from each point source's DMR from 1998 through 2004.  The
90th percentile value of the monthly loads was used to express the estimated existing load
in counts/day.   The current pollutant loading from each permitted point source discharge
as summarized in Section 3 was calculated using the  equation below.
         Point Source Loading = monthly average flow rates (mgd) * geometric mean of
         corresponding fecal coliform concentration * unit conversion factor
         Where:

         unit conversion factor = 37,854,120 100-ml/million gallons (mg)

       Step 4:  Estimate Current Loading  and Identify  Critical Conditions.  It is
difficult to estimate current nonpoint  loading  due to lack of specific water quality and
flow information that would assist in estimating the relative proportion of non-specific
sources within  the watershed.   Therefore,  existing instream loads  were used as  a
conservative surrogate for  nonpoint  loading.  It  was calculated  by multiplying  the
concentration  by the flow  matched to the specific  sampling date.   Then using  the
hydrologic flow intervals shown in Table 4-1, the 90th percentile nonpoint loading within
each of the intervals would then represent the nonpoint loading estimate for that interval.
Existing  loads have been estimated  using a regression-based relationship developed
between observed fecal coliform loads and flow or flow exceedance percentile.

       In many cases, inspection of the LDC will reveal  a  critical condition related to
exceedances of WQSs. For example, criteria exceedances may occur more frequently in
wet weather, low flow conditions, or after large rainfall events.  The critical conditions
are such that  if WQSs  were met under those conditions, WQSs would likely be met
overall. Given that the instantaneous fecal coliform  criterion indicates that no more than
10 percent of samples should exceed 400 cfu/100 ml, it is appropriate to evaluate existing
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An Approach for Using Load Duration Curves in the Development of TMDLs


loading as the 90th percentile of observed fecal coliform concentrations.  Together with
the MOS, the reduction calculated in this way should ensure that no more than 10 percent
of samples will exceed the criterion.

       Existing loading is calculated as the 90th percentile of measured  fecal coliform
concentrations under each hydrologic condition class multiplied by the flow at the middle
of the flow exceedance percentile. For example, in calculating the existing loading under
dry conditions  (flow  exceedance percentile = 60-90%), the 75th percentile exceedance
flow is multiplied by the 90th percentile of fecal coliform concentrations measured under
the 60-90* percentile flows.  The "high flow" or "low flow" hydrologic conditions will
not be selected as critical conditions because these extreme flows are not representative
of typical conditions, and  few observations are typically available to reliably estimate
loads under these conditions. This methodology results in multiple estimates of existing
loading.   However, TMDLs  are typically expressed as a load or concentration under a
single  scenario.   Therefore, these  TMDLs will  assume that if the highest percent
reduction associated  with  the  difference between the existing  loading  and the LDC
(TMDL) is achieved, the WQS will be attained under all other flow conditions.

       Step  5:   Develop  Fecal Coliform Load  Duration  Curves  (TMDL).  Load
duration curves  are based on flow duration  curves,  with the  additional  display  of
historical pollutant load observations  at  the  same location,  and the associated  water
quality criterion or criteria.  In lieu of flow, the ordinate is expressed in terms of a fecal
coliform load (cfus/day).  The curve represents the single sample water quality criterion
for fecal coliform (400 cfu/100 ml) expressed in terms of a load through multiplication by
the continuum of flows historically observed at the site.  The points represent individual
paired  historical observations of fecal coliform concentration and flow.  Fecal coliform
concentration data used for each  WQM station are provided in Appendix A.  The fecal
coliform load  (or the y-value of  each point) is  calculated by multiplying the fecal
coliform WQS  by the instantaneous  flow (cfs) from  the  same site and time,  with
appropriate volumetric and time unit conversions.

       TMDL (cfu/day) = WQS * flow (cfs) * unit conversion factor

       Where:  WQS = 400 cfu/WOml

       unit conversion factor = 24,465,525 ml*s/ft3 *day

       The flow exceedance  frequency (x-value of each point) is  obtained by looking up
the historical exceedance frequency of the measured flow, in other words, the percent of
historical observations that equal or exceed the measured flow.  It should be noted that
the site daily average stream  flow is often used if an instantaneous flow measurement is
not available.  Fecal coliform loads representing exceedance of water quality criteria fall
above the water quality criterion line.
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An Approach for Using Load Duration Curves in the Development of TMDLs


       Step 6:  Develop LDCs with MOS. An LDC depicting slightly lower estimates
than the TMDL is developed to represent the TMDL with MOS.  An explicit MOS is
defined for each TMDL by establishing an LDC using 95 percent of the TMDL value
(5 percent of the 400 cfu/100 ml instantaneous water quality criterion) to slightly reduce
assimilative capacity in the watershed, thus providing a 5 percent MOS. The MOS at any
given percent flow exceedance, therefore, is defined as the difference in loading between
the TMDL and the  TMDL with MOS.

       Step 7:  Calculate WLA.  As previously stated, the pollutant load allocation for
point sources is defined by the WLA.  A point  source  can  be either a wastewater
(continuous) or stormwater (MS4) discharge.  Stormwater point sources  are typically
associated with urban  and industrialized areas, and recent USEPA  guidance includes
permitted stormwater discharges as point source discharges and, therefore, part of the
WLA.

       The LDC approach recognizes  that the assimilative capacity of a water body
depends on the flow, and that maximum allowable loading will vary with flow condition.
TMDLs can be  expressed in terms of maximum allowable concentrations, or as different
maximum loads allowable under different flow conditions, rather than single maximum
load values.  This concentration-based approach meets the  requirements  of 40 CFR,
130.2(i) for expressing  TMDLs "in terms of mass per time, toxicity, or other appropriate
measures" and is consistent with USEPA's Protocol for Developing Pathogen TMDLs
(USEPA 2001).

       WLA for  WWTP.   Wasteload  allocations may be  set to  zero in cases  of
watersheds with no existing  or  planned  continuous  permitted point sources.   For
watersheds with permitted point sources, wasteloads may be derived from NPDES permit
limits. A WLA may be calculated for each active NPDES wastewater discharger using a
mass balance approach  as shown in the equation below.  The permitted average flow rate
used for each point source discharge and the water quality criterion concentration  are
used to estimate the WLA for each wastewater facility.  All  WLA values for each
subwatershed are then summed to represent the total  WLA for the watershed.

       WLA (cfu/day) = WQS *flow * unit conversion factor

       Where: WQS = 400 cfu/lOOml

       flow (mgd)  = permitted flow or design flow (if unavailable)

       unit conversion factor = 37,854,120 100-ml/mg

       WLA for MS4s.   Because a WLA for each MS4 cannot be calculated as an
individual value, WLAs for MS4s are expressed  as a percent reduction goal (PRG)
derived from the LDC for nonpoint sources.  The method for estimating the percent
reduction of fecal coliform loading is described in Step 8.
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An Approach for Using Load Duration Curves in the Development of TMDLs
       Step 8: Calculate LA. Load allocations can be calculated under different flow
conditions as the water quality target load minus the WLA.  The LA is represented by the
area under the LDC but above the WLA.  The LA at any particular flow exceedance is
calculated as shown in the equation below.

       LA = TMDL - MOS - £WLA

       However, to express the LA as an individual value, the LA is derived using the
equation above but at the median point of the hydrologic condition  class requiring the
largest percent reduction as displayed in the LDCs provided in Appendix E.  Thus, an
alternate method for  expressing the LA is to calculate a PRG for fecal coliform. Load
allocations are calculated as  percent reductions from current estimated  loading levels
required to meet water quality criteria.

       Step 9: Estimate WLA Load  Reduction.  The WLA load reduction was not
calculated because it was assumed that the continuous  dischargers (NPDES  permitted
WWTPs) are adequately regulated under existing permits and,  therefore,  no WLA
reduction would be required. For the MS4 permittees, the percent reduction was assumed
to be the same as the nonpoint load reduction.

       Step 10:   Estimate LA Load Reduction.  After existing loading estimates are
computed for the three different  hydrologic  condition classes  described in  Step 2,
nonpoint load reduction  estimates for  each WQM station  are calculated by  using the
difference between estimated  existing loading  (Step 5)  and the LDC  (TMDL).   This
difference is expressed as a percent reduction, and the hydrologic condition class with the
largest percent reduction is selected as the critical  condition and the overall PRG for the
LA.

       Results of all these calculations are discussed in Section 5.
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An Approach for Using Load Duration Curves in the Development of TMDLs


                                  SECTION 5
                          TMDL CALCULATIONS

5.1    Results of TMDL Calculations

       The calculations and results of the TMDLs for the 303(d)-listed WQM stations in
the Pee Dee  River Basin are provided in this section.  The methods for deriving these
results are specified in Section 4.  The Lynches River and various tributaries contributing
to WQM  station PD-113 are interstate water bodies. The TMDLs established in Section
5.7 of this report for WQM station PD-113  are achievable if WQS for fecal coliform are
met at the state line.

5.2    Critical Conditions and Estimated Loading

       USEPA regulations at 40 CFR 130.7(c) (1) require TMDLs to  take into account
critical  conditions for stream  flow,  loading, and water quality parameters.   Available
instream WQM data were evaluated with respect to flows  and magnitude of water quality
criteria  exceedance using LDCs.  Load duration curve analysis involves using measured
or estimated  flow data, instream criteria, and fecal coliform concentration data to assess
flow conditions in which water quality exceedances are occurring (SCDHEC 2003). The
goal of flow weighted concentration analysis is to compare instream observations with
flow values to evaluate whether  exceedances generally  occur during low  or high flow
periods (SCDHEC 2003).

       To calculate the fecal coliform load  at the WQS, the instantaneous fecal coliform
criterion  of 400cfu/100ml is multiplied  by the flow  rate  at  each  flow exceedance
percentile, and a unit conversion factor (24,465,525 ml*s /ft *day).  This calculation
produces  the maximum fecal coliform load  in the stream  without  exceeding  the
instantaneous standard over the range of flow conditions.  The allowable fecal coliform
loads at the WQS establish the TMDL and are plotted versus flow exceedance  percentile
as an LDC.   The x-axis indicates the flow exceedance  percentile, while  the  y-axis is
expressed in terms of a fecal coliform load.

       To estimate existing loading, the loads associated with individual fecal coliform
observations  are paired with the flows estimated at the  same site on the same date.  Fecal
coliform  loads  are  then  calculated  by  multiplying  the measured  fecal   coliform
concentration by the estimated flow rate and a unit conversion factor of 24,465,525 ml*s /
ft3*day.  The  associated flow exceedance percentile is then matched with  the  measured
flow from the tables provided in Appendix D. The observed fecal coliform loads are then
added to the LDC plot as points.  These points represent individual ambient water quality
samples  of  fecal  coliform.    Points  above the  LDC  indicate  the  fecal   coliform
instantaneous standard was exceeded at the time of sampling.   Conversely, points  under
the LDC indicate the sample met the WQS.
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An Approach for Using Load Duration Curves in the Development of TMDLs
       The LDC approach recognizes that the assimilative capacity of a water body
depends on the flow, and that maximum allowable loading varies with flow condition.
Existing loading, and load reductions  required to meet the TMDL water quality target,
can also be calculated under different flow conditions.  The difference between existing
loading and the water quality target is used to calculate the loading reductions required.
Given that the  instantaneous fecal  coliform criterion  indicates that no  more  than
10 percent of samples should exceed 400 cfu/100 ml, it is appropriate to  evaluate existing
loading as the 90l percentile of observed fecal coliform concentrations.  Together with
the MOS, the reduction calculated in this way should ensure that no more than 10 percent
of samples will exceed the criterion.
       Existing loading is calculated as the 90th percentile of measured fecal coliform
concentrations under each hydrologic condition class multiplied by the flow at the middle
of the flow exceedance percentile. For example, in calculating the existing loading under
dry  conditions  (flow  exceedance  percentile  = 60-90 percent),  the  75th  percentile
exceedance flow is multiplied by the 90th percentile of fecal  coliform  concentrations
measured under 60-90th percentile flows.

       After existing  loading   and percent  reductions  are  calculated  under  each
hydrologic condition class, the critical condition for each TMDL is identified as the flow
condition requiring the largest  percent  reduction.  However,  the  "high flow"  (<10th
percentile flow exceedance) or "low flow" (> 90th percentile flow exceedance) hydrologic
conditions will not be selected as critical conditions because these extreme flows are not
representative of  typical  conditions,  and few observations  are available to  reliably
estimate loads  under  these  conditions.   In the example shown in Table 5-1 for WQM
station PD-333,  the  critical  condition  occurs  under  "Moist  Conditions,"  when  a
93 percent loading reduction is required to meet the WQS.

 Table 5-1     Estimated Existing Fecal Coliform Loading for Station PD-333 (Hills
                     Creek with Critical Condition Highlighted
Hydrologic
Condition
Class*
High Flows
Moist
Conditions
Mid-Range
Conditions
Dry
Conditions
Low Flows
Estimated
Existing
Loading
(cfu/100
ml)
6.54E+11
2.53E+12
7.10E+10
1.82E+11
1.08E+11
Percent
Reduction
Required
NA
93%
NA
70%
NA
                     * Hydrologic Condition Classes are derived from
                     Cleland2003.
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An Approach for Using Load Duration Curves in the Development of TMDLs
       The LDC for WQM  station PD-333  shown in Figure 5-1 indicates actual fecal
coliform loads are exceeding the instantaneous load of the WQS during "moist"  and
"dry" flow conditions.  LDCs similar to Figure 5-1 for all of the 303(d)-listed WQM
stations in this report used to estimate existing loading and identify critical conditions are
provided in Appendix E.  The LDCs were developed for the time period from January
1990 through October 2002 if data were available.
 Figure 5-1    Estimated Fecal Coliform Load and Critical Conditions, Station PD-
                                 333 (Hills Creek)

                Fecal Coliform Load Duration Curve 1990-2000, Station PD-333
   1.E+09
                      20
                             30
                                    40     50     60
                                   Flow Exceedance Percentile
                                                         70
                                                                80
                                                                       90
                                                                              100
                  •Load at WQ Criterion
                                   Load at WQ Target  A FC Observations
                                                               90 Percentile FC Load
       The existing instream fecal coliform load (actual or estimated flow multiplied by
observed fecal coliform concentration) is compared to the allowable load for that flow.
Any existing loads above the allowable LDCs represent an exceedance of the WQS.  For
a low flow loading situation, there are typically observations in excess of criteria at the
low flow side of the chart.  For a high flow loading situation, observations in excess of
criteria at the high flow side of the chart are typical. For water bodies impacted by both
point and  nonpoint sources, the "nonpoint source critical condition" would typically
occur during high flows, when rainfall runoff would contribute the bulk of the pollutant
load, while the "point source critical condition" would typically occur during low flows,
when treatment plant effluents  would dominate the base flow of the impaired water.
Based  on these characteristics, critical conditions for each WQM station are summarized
in Table 5-2.
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An Approach for Using Load Duration Curves in the Development of TMDLs
  Table 5-2
Summary of Critical Conditions for each WQM Station as derived
            from Load Duration Curves
SCDHEC
WQM
Station
PD-333
PD-113
PD-179
PD-180
PD-342
PD-066
PD-040
PD-098
PD-239
PD-065
PD-187
PD-320
PD-030A
PD-030
PD-037
PD-352
Moist
Conditions
















Mid-
Range
Conditions
















Dry
Conditions
















       The existing load for each WQM station was derived from the critical condition
line depicted on the  LDCs described above and provided in Appendix E.  Estimated
existing loading  is derived from the 90th percentile of observed fecal  coliform loads
corresponding to the critical condition identified  at each  WQM  station  identified  in
Table 5-2.  This estimated loading is indicative  of loading from all sources including
continuous point source dischargers,  leaking sewer lines, MS4s, SSOs,  failing OSWD
systems, land application fields, wildlife, pets, and livestock. The total estimated existing
load for each station is provided in Table 5-3.

          Table 5-3     Estimated Existing Loading at each WQM Station

SCDHEC
WQM
Station

PD-333
PD-113
PD-179
PD-180
PD-342
90th
Percentile
Load
Estimation
(cfu/day)
2.53E+12
3.15E+12
7.76E+11
2.31E+11
3.72E+11

Flow
Exceedance
Percentile

25
25
25
25
75
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An Approach for Using Load Duration Curves in the Development of TMDLs
SCDHEC
WQM
Station
PD-066
PD-040
PD-098
PD-239
PD-065
PD-187
PD-320
PD-030A
PD-030
PD-037
PD-352
90th
Percentile
Load
Estimation
(cfu/day)
1.36E+13
1.37E+11
4.31E+ 11
1.63E+11
1.51E+12
2.54E+11
1.33E+12
1.05E+13
6.61E+11
7.54E+11
3.08E+11
Flow
Exceedance
Percentile
25
50
75
25
50
75
75
75
50
50
75
5.3    Waste Load Allocation
       Table 5-4  summarizes the WLA  of the NPDES-permitted facilities within the
watershed  of each WQM  station.   The WLA  for  each  facility is derived from the
following equation:
       WLA = WQS * flow * unit conversion factor (#/day)
              Where: WQS = 400 cfu/lOOml
             flow (cfs) = permitted flow
             unit conversion factor = 37,854,120 100-ml/mg
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An Approach for Using Load Duration Curves in the Development of TMDLs
    Table 5-4    Wasteload Allocations (WLA) for NPDES Permitted Facilities
Water Quality Monitoring Station / Permittee
HUC 3050106020
PD-333 Hills Creek at S-13-105
Pageland Northwest WWTP
HUC 3040202030
PD-179 North Branch Wildcat Creek at S-29-39 1 Mile
South of Tradesville
Buford High School WWTP
HUC 3040202050
PD-066 Upper Lynches River
Jefferson WWTP
HUC 3040204030
PD-030A Little Pee Dee River Below JCT with Maple SWP
Dillon Little Pee Dee WWTP (Outfall 001)
NPDES Permit
Number


SC0021504


SC0030210


SC0024767


SC0021776
Flow
(mgd)


0.3


0.035


0.15


4.0
Load
(cfu/day)


4.54E+09


5.30E+08


2.27E+09


6.06E+10
* Ceased Discharging in 1999.

       When there are no NPDES WWTPs discharging into the contributing watershed
of a WQM station, then the WLA for continuous point sources is zero.  See Subsection
4/2 (Step 7) and Section 5.7 for an explanation of how the WLA for NPDES dischargers
is depicted in a LDC.

       The cities of Sumter and Florence are the only MS4s within the watersheds of this
report. Because of insufficient data, it is not possible to express a WLA for MS4s as a
load or concentration; therefore,  the WLA is expressed as a PRG.  Each MS4 was
assigned a PRG equal to the PRG identified in the LA for each WQM station.  The PRGs
that will serve as a component of the WLA are provided in Table 5-5.  When multiple
WQM stations fall under one MS4 jurisdiction, multiple PRGs can occur. In these cases
the highest PRG is selected  as the overall reduction requirement incorporated into the
TMDL of each station.  For example, by reviewing the LDCs in Appendix E, Stations
PD-098 and PD-040 have PRGs of 94 and 75 percent, respectively.  Therefore, using a
conservative approach, the  highest reduction  goal of  94 percent is  selected and
incorporated into the TMDLs (see Table 5-5) for WQM  stations PD-098 and PD-040.
The PRGs in this TMDL  report apply also to the fecal coliform WLAs attributable to
those areas of the watershed which are covered or will be covered under NPDES MS4
permits.  Compliance by those municipalities within  the terms of their individual MS4
permits will fulfill  any obligations they  have toward implementing TMDLs for fecal
coliform.
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An Approach for Using Load Duration Curves in the Development of TMDLs
     Table 5-5     WLA for MS4 Entities in Turkey Creek and Gulley Branch
                                   Watersheds
MS4 Entity
Sumter
Florence
WQM Stations
PD-098, PD-040
PD-065
Percent Reduction Goal
94
99
5.4    Load Allocation

       As discussed in Section 3, nonpoint source fecal coliform loading to the receiving
streams of each WQM station originate from a number of different sources. For a select
group of WQM stations (Table 3-3, Table 3-10, and Table 3-19)  nonpoint  sources of
fecal  coliform  loading is the sole reason the primary  contact recreation use is not
supported.   As  discussed  in  Section 4,  nonpoint source loading was  estimated and
depicted for all flow conditions using LDCs (See Figure 5-1  example and Appendix E).
Figure 5-1, the LDC for PD-333, displays  the relationships between the TMDL water
quality target, the MOS, and the PRO that can serve as an alternative for expressing the
LA.  The data analysis and the LDCs demonstrate that exceedances at many of the WQM
stations are the result of nonpoint source loading  such as failing OSWD systems, leaking
sewer lines, cattle in streams, and fecal  loading from land  application fields, wildlife and
pets transported by runoff  events.   The LAs, calculated  as the difference between the
TMDL, MOS, and WLA,  for each WQM station are presented in Table 5-6.  Where
MS4s are present then the LA is not calculated and is expressed as a PRG.
5.5    Seasonal Variability

       Federal  regulations  (40 CFR  §130.7(c)(l))  require  that TMDLs  take  into
consideration seasonal variation in watershed conditions and pollutant loading. Seasonal
variation was accounted for in these TMDLs by using more than 5 years of water quality
data (1990-2002) whenever possible  and by using the longest  period of USGS flow
records when estimating flows to develop flow exceedance percentiles.

5.6    Margin of Safety

Federal regulations  (40 CFR  §130.7(c)(l)) require that TMDLs include an MOS.  The
MOS is a conservative measure incorporated into the TMDL equation that accounts for
the uncertainty  associated with calculating the allowable fecal coliform pollutant loading
to ensure WQSs  are attained.  USEPA guidance allows for use of implicit  or explicit
expressions of the  MOS, or  both.    When  conservative  assumptions are  used in
development of the TMDL, or conservative factors are used in the calculations, the MOS
is implicit.   When  a  specific  percentage  of  the TMDL is  set aside to account for
uncertainty, then the MOS is considered explicit.
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An Approach for Using Load Duration Curves in the Development of TMDLs
For  the  explicit  MOS the water  quality target  was  set at 380 cfu/100 ml for the
instantaneous  criterion, which  is 5 percent lower than the water quality  criterion of
400 cfu/100 ml.  The net effect  of the TMDL with MOS is that the assimilative capacity
of the watershed  is slightly reduced.  These TMDLs incorporates an explicit MOS by
using a curve  representing 95 percent of the TMDL as the average MOS.  The MOS at
any given percent flow exceedance, therefore, can be defined as the difference in loading
between  the TMDL and the TMDL with MOS. For consistency, the explicit MOS at
each WQM station will be expressed as a numerical value derived from the same critical
condition as the  largest load reduction goal at the  respective 25th,  50th,  or  75th flow
exceedance percentile (see Table 5-6).

There are other conservative elements utilized in these TMDLs that can be recognized as
an implicit MOS such as:

       •  The  use of instream fecal coliform  concentrations to estimate existing
           loading; and

       •  The highest PRG for nonpoint sources, based on the LDC used.

This conservative approach to  establishing the MOS will ensure that both the 30-day
geometric mean and instantaneous fecal coliform bacteria standards can be achieved and
maintained.
5.7    TMDL Calculations

The fecal coliform  TMDLs for the 303(d)-listed WQM stations covered in this report
were derived using LDCs.  A TMDL is expressed as the sum of all WLAs (point source
loads), LAs (nonpoint source loads), and an appropriate MOS, which attempts to account
for uncertainty concerning the relationship between effluent limitations and water quality.
This definition can be expressed by the following equation:

                          TMDL = Z WLA + ZLA + MOS

For each WQM station the TMDLs presented in this report are expressed in cfus per day
or as a percent reduction.  The TMDLs are presented  in fecal coliform counts to be
protective of both the instantaneous, per day, and geometric mean, per 30-day, criteria.
To express a TMDL as an individual value, the LDC is used to derive the LA, the MOS,
and the TMDL based on the median percentile of the critical condition (i.e., the median
percentile of the  hydrologic condition class requiring the  greatest percent reduction to
meet the instantaneous criterion which is the water quality target).  The WLA component
of each TMDL is the sum of all WLAs within the contributing watershed of each WQM
station which is  derived from each  NPDES facilities' maximum design flow and the
permitted 1-day maximum concentration of 400 cfu/100 ml. When MS4s do not exist in
the contributing watershed, the LDC and  the simple equation of:

                   Average LA = average TMDL - MOS - £ WLA
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An Approach for Using Load Duration Curves in the Development of TMDLs
can provide an individual value for the LA in cfu per day which represents the area under
the TMDL target line and above the WLA line.  Percent reductions necessary to achieve
the water quality target are also provided  for all  WQM stations as another acceptable
representation of the TMDL.   Like the LA, the percent reduction is  derived from the
median percentile of the critical condition (i.e.., the median percentile  of the hydrologic
condition class requiring the greatest percent reduction to meet the instantaneous criterion
which is the water quality target).  Table 5-6 summarizes the TMDLs for each WQM
station, and Figures 5-2 through 5-17 present the LDCs for each station depicting the
TMDL, MOS, and WLA (if applicable).

  Table 5-6     TMDL Summary for Select WQM Stations in Pee Dee River Basin
                 (HUCs 03040202, 03040205, 03040201, 03040204)
SCDHEC
WQM
Station
WLAs
(cfu/
day)
MS4 WLA
(Percent
reduction)
LA (cfu/day
or%
reduction)
MOS
TMDL
(cfu/day or
%
reduction)
Percent
reduction
Lynches River HUC 03040202020
PD-333
4.54E+09
NA
1.80E+11
9.74E+09
1.95E+11
93
Upper Lynches River HUC 03040202030
PD-113
PD-179
PD-180
0
5.30E+08
0
NA
NA
NA
5.99E+11
1.13E+11
1.12E+11
3.15E+10
5.97E+09
5.92E+09
6.30E+11
1.19E+11
1.18E+11
81
85
51
Upper Lynches River HUC 03040202040
PD-342
0
NA
1.62E+11
8.51E+09
1.70E+11
57
Upper Lynches River HUC 03040202050
PD-066
2.27E+09
NA
2.56E+12
1.35E+11
2.69E+12
81
Tributary to Pocotaligo River HUC 03040205080
PD-040
PD-098
PD-239
0
0
0
94
94
NA
3.44E+10
2.70E+10
1.54E+11
1.81E+09
1.42E+09
8.12E+09
3.62E+10
2.84E+10
1.62E+11
75
94
5
Tributary to Pee Dee River HUC 03040201 130
PD-065
PD-187
PD-320
0
0
0
99
NA
NA
1.39E+10
8.74E+10
4.22E+11
7.34E+08
4.60E+09
2.22E+10
1.47E+10
9.20E+10
4.44E+11
99
66
68
Little Pee Dee River HUC 03040204030
PD-030A
PD-030
6.06E+10
0
NA
NA
4.90E+12
2.51E+11
2.61E+11
1.32E+10
5.22E+12
2.64E+11
53
62
Little Pee Dee River HUC 03040204070
PD-037
0
NA
7.16E+10
3.77E+09
7.54E+10
91
Little Pee Dee River HUC 03040204090
PD-352
0
NA
1.90E+11
9.98E+09
2.00E+11
39
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
                        Figure 5-2     TMDL for PD-333 Hills Creek
                    Fecal Coliform Load Duration Curve 1990-2000, Station PD-333
     1.E+13
     1.E+12
     1.E+11
   o
   O
     1.E+10
     1.E+09
                   10      20
                                   30       40       50      60      70
                                          Flow Exceedance Percentile
                                                                                    90      100
                       •Load at WQ Criterion ~  ~ Load at WQ Target  A  FC Observations ^^"Wasteload Allocation
     1.E+14
     1.E+13
                       Figure 5-3    TMDL for PD-113 Lynches River
                    Fecal Coliform Load Duration Curve 1990-2002, Station PD-113
   8
     1.E+09
                   10      20      30       40       50      60      70      80
                                          Flow Exceedance Percentile
                                                                                    90      100
                       •Load at WQ Criterion ~  ~ Load at WQ Target  A  FC Observations ^^^Wasteload Allocation
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August 2007

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An Approach for Using Load Duration Curves in the Development of TMDLs
                             APPENDIX  B
                   Additional Examples of Using
                 Load Duration Curve Approach
This technical  appendix discusses  basic  application  of duration  curves  in  TMDL
development  and  provides  several examples,  including the  derivation  of loading
capacities, wasteload allocations, and load allocations.  The duration curve framework is
well suited as a tool to support TMDL development because flow data is an important
factor in the determination of loading capacities. This technical appendix also provides a
discussion  on ways the duration  curve  framework can  be  used to address different
averaging periods (other than daily) in identifying loading capacities, particularly where a
concentration-based target exists (expressed as monthly, seasonal,  or annual average
values).
Bl.   LOADING CAPACITY

Calculation of the loading capacity for impaired segments identified on the §303(d) list is
an important first step  in the TMDL development process.  EPA's current regulation
defines loading capacity as "the greatest amount of loading that a water can receive
without violating water quality standards ".  The loading capacity provides a reference,
which helps guide pollutant reduction efforts needed to bring a water into compliance
with standards.
Chloride represents a good starting point to describe the use of duration curves in TMDL
development because of its conservative nature as a pollutant. For example, Kansas has
established 860 mg/L as the water quality criterion for chloride to protect aquatic life. To
illustrate key steps, the flow duration curve for the Arkansas River (based on daily
average stream discharge data) starts the process of identifying a loading capacity for
chloride using the duration curve framework.

In-stream loads for chloride, expressed as tons per day, are calculated using the equation
summarized in Table B-l.  The  loading capacity for the Arkansas River is shown in
Figure B-l. It is derived directly from the water  quality  criteria (860  mg/L) and the
duration curve using the  "flow to load" calculation described  in Table  B-l across the
range of all daily average flows.  Load capacity calculations for other parameters (e.g.
nutrients, bacteria, sediment) are developed in a similar fashion.
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An Approach for Using Load Duration Curves in the Development of TMDLs
                       Table B-l.  Calculation of Chloride Loads
Load (tons per day) = Flow (cfs) * Concentration (ntg/L) * Factor
multiply by 86,400 to convert
multiply by 7.48 to convert
divide by 453,592 to convert
multiply by 3.7854 to convert
divide by 2,000 to convert
multiply by 0.002695 to convert
seconds per day
ft3
mg
liters
pounds
(ft3 / sec) * (mg/L)
•»
•»
•»
•»
•»
•»
ft3 / day
gallons / day
pounds
gallons
tons
tons / day
       Figure B-l.  Chloride Loading Capacity Using Duration Curve Framework

                            Arkansas River near Hutchinson
                       Load Duration Curve (Aquatic Life Criteria—Acute)
          100000
        l-
        o
            10
               High
               Flows
  Moist
Conditions
Mid-range
  Flows
  Dry
Conditions
                               1,100 cfs * 860 mg/L * 0.002695
                                     = 2,549 tons /day
 Low
Flows
                             97 eft  * 860 mg/L  * 0.00269S
                                   = 225 tons/day
                                                    -H
                   10    20    30    40     SO    60     70    SO

                             Flow Duration Interval (%)
                                       90
                               100
                                                                 31,724 square miles
Nutrients  have been the focus of TMDL efforts to address a variety of water quality
problems including eutrophication, aquatic life impairments, and drinking water supply
concerns.   Duration curves can be used to support TMDL development where numeric
targets  exist for either nitrogen or phosphorus (similar to the chloride example).   A
loading capacity for nitrate in the  Sangamon River is depicted in Figure B-2 using the
drinking water maximum contaminant level (MCL) of 10 mg/L.  It is derived directly
from the MCL (10 mg/L) and the duration curve using the  "flow to load" calculation
described in Table B-l across the range of all daily average flows.
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An Approach for Using Load Duration Curves in the Development of TMDLs
        Figure B-2.  Nitrate Loading Capacity Using Duration Curve Framework

                              Sangamon River near Fisher
                                  Load Duration Curve
          1000
           100
        a
        "w
        83
           0.1
           0.01
          0.001
              High
              Flows
    Moist
  Conditions
        Mid-range
          Flows
                   Dry
                 Conditions
             Low
             Flows
                 217 eft  * lOmg/L *  0.002695
                       = 5.84 tons /day
17eft  * lOmg/L *  0,002695
     = 0.46 tons/day
                   10
  20
30
40
70
80
90
100
                             Flow Duration Interval (%
                                                                    240 square miles

Figure B-3 shows the total phosphorus loading capacity  curve for  the Portneuf River
using the TMDL target of 75 ng/L.  In this example, loads are expressed as pounds per
day (as described in Table B-2). Again, loading capacities developed using the duration
curve  framework  provides information  that  adds a  focus  to  discussions regarding
allocations  and implementation planning, particularly  when used in conjunction  with
ambient water quality  monitoring data.
                     Table B-2.  Calculation of Phosphorus Loads
Load (tons per day) = Flow (cfs) * Concentration (fig/L) * Factor
multiply by 86,400 to convert
multiply by 7.48 to convert
divide by 1,000 to convert
divide by 453,592 to convert
multiply by 3.7854 to convert
multiply by 0.005393 to convert
seconds per day
ft3
Mg
mg
liters
(ft3 / sec) * (ug/L)
•»
•»
•»
•»
•»
•»
ft3 / day
gallons / day
mg
pounds
gallons
pounds / day
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                                            August 2007

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An Approach for Using Load Duration Curves in the Development of TMDLs


     Figure B-3.  Phosphorus Loading Capacity Using Duration Curve Framework

                             Portneuf River at Pocatello
                                 Load Duration Curve
          100000
          10000 •
        B,
       •3
        9
        k.
 c
JS
D-

 M
•*•*
 O
           1000
           100 •
            1.
            01
               High
               Flows
                   Moist
                 Conditions
Mid-range
  Flows
   Dry
Conditions
        Low
       Flows
                               356 cfs * 75 ug/L  * 0.005393
                                    = 144 pounds / day
                     116 eft  * 75ug/L * 0.005393
                         = 46.9 pounds /day
                        +
                      +
   +
+
+
              0     10    20    30    40    SO    60    70    §0    90    100

                            Flow Duration Interval (%)
                                                                 1,250 square miles

Sediment concerns have long challenged TMDL practitioners for several reasons.  First,
States typically do not have established numeric criteria for sediment, instead relying on
narrative components of their water quality standards.  Second, sediment problems can
result from changes in processes that influence  either  surface  or  channel erosion.
Sediment concerns are also associated with changes that affect the capacity of watersheds
to store and transport sediment throughout the  drainage network.  TMDL assessments
typically consider the influence of land management activities on changes in erosion
processes, water discharge amounts and timing, as well as channel form (EPA, 1999).

There is a wide range in methods that have  been  employed towards sediment TMDL
development.  Some use fixed numeric targets,  often based on values  recommended by
the European  Inland Fisheries Advisory Commission (EIFAC), which could be used to
establish categories  of risk to fisheries.   With this approach, the process outlined to
generate loading capacities described for chloride, nitrate, and phosphorus (Figures B-l
to B-3) would be applied.

The "Protocolfor Developing Sediment TMDLs" (EPA, 1999) indicates the suitability of
using sediment targets, which relate concentrations to stream flow for  reference streams
that reflect unimpaired conditions.  A target can be identified by developing a sediment
rating curve for an appropriate reference stream based on the regression slope, by plotting
flow against suspended sediment concentration.  Figure B-4 illustrates an example rating
curve for a reference stream.
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
                    Figure B-4.  Example Sediment Rating Curve

                                     Flat Brook
                       Regression Analysis (1968 - 2001 Monitoring Data)
         C 100
         u
         E
        •3
        -o
         c
                                                   y=0.0934x
                                                          0*94
= ft 0934 * (335 
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An Approach for Using Load Duration Curves in the Development of TMDLs


      Figure B-5.  Sediment Loading Capacity Using Duration Curve Framework

                                     Flat Brook
                     Load Duration Curve (derivedfrom sediment rating curve)
          10000
        a
        •w
        tn
        K
        ,S  100
        B
        O)
       •a
       •B
        §  0.1
High
flows
  Moist
Conditions
Mid-range
  flows
  Dry
Conditions
               335 eft * 16.9 m^L * 0.002695
                     = 15.3 tons/day
                    32cfs * 2.07 mg^L * 0.002695
                         = 0.18 tons/day
                        +
               +
           -I-
   +
+
+
        Low
       flows
    10    20    30    40    50    £0    70    SO

              Flow Duration Interval (%)
                                                               90    100
                                                                   64 square miles
Bacteria   is  a major  pollutant leading to  §303(d) listings and subsequent  TMDL
development.  Typically, loads are expressed as chemical mass per time, such as pounds
per day.  Given the nature of bacteria measurements (e.g., counts per 100 milliliters), an
appropriate expression of loads for bacteria TMDLs is  organisms per day.   Table B-3
describes an approach used  in TMDL development to  calculate  bacteria loads, which
includes  needed conversion factors.

Loading  capacities calculated  in this  manner result in extremely large numbers  (i.e.,
numbers of organisms in the billions, trillions, or quadrillions per day).  In order to avoid
difficulties of communicating information associated with large counts (e.g., macro
numbers  of microorganisms), bacteria loading  capacities are  expressed  as  million
organisms per day (mega- or M-org/day), billion organisms per day (giga- or G-org/day),
or trillion organisms  per day (tera- or T-org/day), similar to computer abbreviations of
MB for megabytes, GB for gigabytes, or TB for terabytes.

As an example, waters designated for  support of immersion recreation in South Dakota
must  achieve a daily maximum fecal coliform concentration of 400 cfu / lOOmL between
May  and September.  Figure B-6 shows an example  "daily maximum" loading capacity
curve for Split Rock Creek using the 400 cfu / 100 mL  target  and a duration curve
derived with daily average flows.  This load duration curve  is based on daily average
flows measured between May and September, in order to  ensure consistency with the
water quality criterion for fecal coliform.
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
                        Table B-3.  Calculation of Bacteria Loads
Load (org/day) = Concentration (org/lOOmL) * Flow (cfs) * Factor
multiply by 3785.2 to convert
divide by 100 to convert
multiply by 7.48 to convert
multiply by 86,400 to convert
divide by 1,000,000,000
multiply by 0.02446 to convert
mL per gallon

gallon per ft3
seconds per day
billion
(org/lOOmL) * ft3 / sec
•»
•»
•»
•»
•»
•»
org / 100 gallon
org / gallon
org / ft3
ft3 / day
G-org
G-org / day
       Figure B-6.  Bacteria Loading Capacity Using Duration Curve Framework

                                Split Rock Creek at Corson
                            Load Duration Curve (May-September)
         « 100000
             1000
         E
         O   100
         S3
         u
         
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An Approach for Using Load Duration Curves in the Development of TMDLs
B2.   MULTIPLE AVERAGING PERIODS

Connecting to "Non-Daily" Targets — Sediment

The following  sediment example  represents  one type of problem where an array  of
different approaches can bring multiple averaging periods into the technical analysis.
The duration  curve framework can accommodate different averaging periods (other than
daily) in identifying loading capacities, particularly where a concentration-based target
exists (expressed as monthly, seasonal, or annual average values).

Figure B-7 illustrates an example TMDL developed to attain the water quality  criteria
expressed as  an annual average concentration of 25 mg/L total suspended solids (TSS).
Figure B-7 portrays this TMDL in the context of existing conditions, both individual
measurements and the current annual average (40.4 mg/L).  Use of these "non daily"
averaging period TMDLs is one way to account for variability.

                     Figure B-7.  Concentration-Based TMDL
                            Middle Fork LeBuche River
                            TMDL versus Existing Conditions
          1000
        JE
 sfi
-a
•— 100
 o
QC
        •a
        c
        a.
        E«
        as
        o
        H<  i
                    TMDL (AnnualAverage) - 25 mg/L
                     %.                             I     i
              • *   *         X •*
              >!•.«.«.,..« *X-  - -
             ,»'*j».,*     *  ./V  <
                                                      . V
                                         .
                           '.*'*•**.
                                          *
*•*»  •  t  *., t.»v  *..  •   ".It • *. •      *T
  ••,  .*.;,»  v •  *• ..v  •  /v*.     •   »•
   .         »•• *          *      x»  .
                                                  mCurrent Average

                                                  — TMDL
                                      Current Average = 40.4 mg/L
                                        Needed Reduction = 38%
           Jan-79
                           Jan-89

                            Month
                                             Jan- 99
Statistical methods, which consider patterns and variability in a consistent manner, offer a
way to connect targets that use multiple averaging periods. Using an approach described
in EPA's  "Technical Support Document for Water Quality-Based Toxics Control" (1991
TSD), the maximum daily concentration for the Middle Fork LeBuche River is 213 mg/L
total suspended  solids (based  on achieving an annual  average  of  25 mg/L with  a
coefficient of variation of 1.164). In-stream loads for TSS, expressed as tons per day, are
calculated using the equation summarized in Table B-l.  The loading capacity for the
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
Middle Fork LeBuche River is shown in Figure B-8. It is derived directly from the daily
concentration  target  (213 mg/L) and  the  duration  curve using  the  "flow to load"
calculation described in Table B-l across the range of all daily average flows.

         Figure B-8.  TSS Loading Capacity Using Duration Curve Framework

                             Middle Fork LeBuche River
                                 Load Duration Curve
          10000
        c
        o
IS
o
           100
        c
        
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An Approach for Using Load Duration Curves in the Development of TMDLs
appropriate source areas, delivery mechanisms, and water quality management control
strategies to address short term problems.  Similarly, average values within each zone can
be calculated and compared to the long term average (or "non daily") benchmark curve.
In the case of the M.F. LeBuche TMDL, benchmarks are exceeded under high flows,
moist conditions, and mid-range flows.

In addition to providing the needed linkage between the  "daily load" and the applicable
water quality standards, the duration curve framework provides  the groundwork for the
transition from the TMDL to implementation efforts.  Reduction estimates  can  be
developed  for each duration  curve  zone benchmark,  which serve  to  guide  problem
solving  discussions  on appropriate  management strategies  (based   on knowledge
associated  with  likely  source areas,  delivery mechanisms, and  appropriate  control
measures that correspond to particular hydrologic  conditions). As shown in Table B-4,
implementation opportunities are highlighted that correspond to the flow conditions best
suited for the array of control options.
              Table B-4. Middle Fork LeBuche River TMDL Summary
TMDL
SUMMARY
TMDL1
Allocations
Margin of Safety
Benchmark
Reduction Estimate
Implementation
Opportunities
Loads expressed as (tons per day)
High
173.35
118.32
55.03
20.35
63%
Post
Development
BMPs
Streambank
Stabilization
Moist
67.20
48.24
18.96
7.89
27%
Mid-Range
40.21
34.47
5.74
4.72
19%

Erosion Control Program

Dry
27.57
21.83
5.74
3.24
0%

Riparian Buffer Protection
Low
18.96
6.90
12.06
2.22
0%

Municipal WWTP
Notes: 1. Expressed as a "daily load"; represents the upper range of conditions needed to
attain and maintain applicable water quality standards
2. Based on annual average target identified in the applicable water quality
standards
3 . Developed using long-term fixed station ambient water quality monitoring data
EPA 841-B-07-006
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August 2007

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An Approach for Using Load Duration Curves in the Development of TMDLs
  Figure B-9.  Middle Fork LeBuche River TMDL Using Duration Curve Framework
                             Middle Fork LeBuche River
                                 Load Duration Curve
         10000
       "a
       >-
       D. 1000
          0.1
              High
              Flows
  Moist
Conditions
        Mid-range
         Flows
                  Dry
                Conditions
 Low
 Flows
                             TMDL (daily maximum based on 213 mg/L)
                  Benchmark (boxed on 25 mg/L animal average)
                                                                        -TMDL
                                                                      « All Data
                                                                      -,- Apr-Oct
                                                                      » >50%SF
                                                                     • • -SOU
                 10
20
30
40    SO    60    70
90    100
                          Flow Duration Interval
Connecting to "Non-Daily" Targets — Bacteria

Many State water quality standards for pathogens include a 30-day or monthly geometric
mean averaging period and an upper limit (either a single sample maximum or no more
than a  set  percent  exceedance  value).   A  challenge  facing TMDL  practitioners  is
identifying the  appropriate target  that will protect  both criteria  values.   Michigan's
applicable water quality  standards (WQS) for bacteria, for instance, focus on E. Coli and
indicate that all waters  be protected for total body  contact recreation  from May 1  to
October 31. Target levels for TMDL development are derived from Rule 62 of the WQS,
which state that:

       "R 323.1062 Microorganisms.
       Rule 62.  (1)  All waters of the state protected for  total body contact
       recreation shall not contain more than 130 E.  coli per 100 milliliters (ml),
       as a 30-day geometric mean.  ... At no time shall the waters of the state
       protected for total body contact recreation contain more than a maximum
       of 300 E. coli per 100 ml. "

When the duration is expressed as a daily  average or "never to exceed" value, the daily
target is explicitly stated in the applicable water quality criteria (USEPA, 2007).  For
example, using Michigan's bacteria criteria, the "daily" value is the maximum of 300 E.
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
Coli per 100 mL to protect for total body contact recreation.  Procedures described in
Table B-3 and Figure B-6 are then used to develop the loading capacity using a duration
curve framework. Another example is shown in Figure B-10.

      Figure B-10.  Bacteria Loading Capacity Using Duration Curve Framework

                                 Werbaldo Creek
                                 Load Duration Curve
          1000
              High
              Flows
             \
  Moist
Conditions
Mid-range
  Flows
             Dry
           Conditions
                              Low
                             Flows
           3.94 eft  * 300org/100L * 0.02446
                 = 28.9 G-org/ day
                       1.31 eft  * 300 org/lOOmL  * 0.02446
                              = 9.64 G-org/day
                       •4-
                 4-
10
20
30
40
SO
         60
                            TO
                                                          80
90
100
                            Flow Duration Interval (%)
TMDLs must be established at a level necessary to attain and maintain the applicable
water quality standards.  In the case of the Werbaldo Creek E. Coli example (Figure B-
10), this includes both a not to exceed value and a 30-day geometric mean of 130 per 100
mL. Material in EPA's November 2004 promulgation of water quality criteria for coastal
recreational waters elaborates on the intended purpose behind each of the two criteria
values. In particular, the preamble of the coastal recreational water rule states:

       "the geometric mean is the  more relevant value for ensuring that appropriate
       actions  are taken to protect and improve water quality because  it is a more
       reliable measure, being less subject to random variation " (EPA, 2004).

The rule provides a context for multi-value bacteria criteria with respect to Clean Water
Act implementation programs, such as TMDLs and NPDES permit requirements. This
context is to meet the geometric mean criteria for bacterial indicators,  such as E. coli,
enterococci, or fecal coliform.

For this reason, a linkage analysis may be needed to demonstrate consistency between the
not to exceed value used as the "daily" TMDL target and the 30-day geometric mean.
EPA's development of ambient water quality criteria for bacteria, specifically E. Coli,
EPA 841-B-07-006
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An Approach for Using Load Duration Curves in the Development of TMDLs
defines the statistical relationship between these two criteria values.  This relationship
can be used to demonstrate that attaining the maximum daily target in the TMDL will
also achieve the 30-day geometric mean criteria.

The concepts used to develop the "not to exceed value ", often referred to as the single
sample maximum (SSM),  are described  in the "Ambient Water Quality  Criteria for
Bacteria — 1986".  The method used to develop the SSM values for E. Coli in the 1986
document is based on a recognition of the inherent variability that occurs in water quality.
In particular, the relationship between the 30-day geometric mean and the SSM is based
on  the  assumption  that bacteria data can be  described using  a log-normal  frequency
distribution.  The method used to identify the upper target values in the 1986 document
provides a way to develop a linkage analysis, which describes the connection between the
"daily" value and the 30-day geometric mean.

Specifically,  the  log-normal distribution has  been  used  to  identify upper  targets in
conjunction with geometric mean and a measure of variability (in this case, a log standard
deviation). Figure B-l 1 illustrates this concept for E. Coli bacteria.  As shown in Figure
B-ll, upper targets are based on the assumption of a log-normal distribution using a log
standard deviation of 0.4 centered on 130 cfu /100 mL, i.e. the target geometric mean.

                 Figure B-ll.  Development of E. Coli Upper Targets
                      Example Log-Normal Frequency Distribution
        o
       U
                      Log-Normal Criteria Curve (LNCC)

                         Geometric Mean = 130 cfu / lOOmL
                         Log Standard Deviation = 0.4
                  82% : (full body contact recreation)
             o%
                  109/o   20%
                             30%
                                  40%
                                       50%
                                            60%
                                                  70%
                                                       80%
                                                            90%   100%
                              Frequency Interval (%)
Figure B-l2 illustrates the same concept for E. Coli bacteria where the applicable criteria
is simply a geometric mean (no single sample maximum).  As shown in Figure B-12, the
1-day monthly maximum is based on the same assumptions behind development of the E.
Coli criteria, specifically a log-normal distribution using a log standard deviation of 0.4
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An Approach for Using Load Duration Curves in the Development of TMDLs


centered on 130 cfu / 100 mL (i.e. the target geometric mean).  The daily target is set at
the recurrence interval associated with a 30-day averaging period using percentiles along
the curve,  specifically  96.8%  [e.g., (30/31)%, or (k/k+l)% where k is the number of
averaging period days]. Note that the "daily" target set in the Werbaldo Creek TMDL is
much lower than one based solely on the 30-day geometric mean criteria using the same
assumptions behind establishing the single sample maximum (e.g., 300 versus 713).

         Figure B-12.  Development of Daily Value Based on Monthly Target
                      Example Log-Normal Frequency Distribution
       E
                      Log-Normal Criteria Curve (LNCQ

                         Geometric Mean = 130 cfu / lOOmL
                         Log Standard Deviation = 0.4
                 F.L= 96.8% (1-day maximum recurrence
                           over 30-day period)
             o%
                  10%   20%
                            30%
                                 40%
                                       50%
                                            fiO%
                                                 70%
                                                      80%
                                                            90%   100%
                             Frequency Interval
Using a "daily" target of 300 organisms per 100 mL is more restrictive than one based on
a geometric mean of 130 using the same assumptions behind development of the E. Coli
criteria.  The linkage analysis can also use these same assumptions to determine the 30-
day geometric mean that corresponds to a "daily"  target of 300 E. Coli per 100 mL.
Figure B-13 shows the graphic results of this analysis, indicating that the resultant 30-day
geometric mean will be 54.6.  Thus, a daily target of 300 will be protective of the 30-day
geometric mean in the water quality standards.

Table B-5  provides a summary of the Werbaldo Creek TMDL using a  duration  curve
framework based on multiple averaging periods (similar to the sediment example in
Table B-4).  The 30-day geometric mean  must be met before full compliance with the
bacteria water quality standards is achieved in Werbaldo Creek.  Based  on the linkage
analysis, the 30-day geometric mean component of the water quality criteria will be met
provided  the  maximum daily target  is met.   If subsequent data  or information
demonstrates that, for some reason, the maximum  daily target is met and the 30-day
geometric mean is not met, the TMDL should be  revised with allocations lowered to
ensure attainment of both criteria values.
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An Approach for Using Load Duration Curves in the Development of TMDLs




     Figure B-13.  Relationship Between 30-day Geometric Mean and Daily Target

                     Example Log-Normal Frequency Distribution
      o
      U
                      Log-Normal Criteria Curve (LNCC)


                        Geometric Mean = 54.6 cfu / lOOmL

                        Log Standard Deviation = 0.4
                F.L= 96.8%  (1-day maximum recurrence

                          over 30-day period)
            0%
                 10%  20%   30%   40%   50%   60%   70%   80%   90%   100%
                             Frequency Interval (%)
                    Table B-5.  Werbaldo Creek TMDL Summary
TMDL SUMMARY
TMDL1
Allocations
Margin of Safety
Benchmark2
Reduction Estimate3
Implementation
Opportunities
Loads expressed as (G-orgper day)
High
77.15
53.84
23.30
130
92%
Moist
28.93
20.09
8.84
130
90%
Long-term CSO
Control Program
Mid-Range
16.07
12.86
3.21
130
75%
Dry
9.64
6.91
2.73
130
40%
Low
5.87
4.26
1.61
130
20%

Riparian Protection

Illicit Discharge Detection &
Elimination

Address on-site wastewater
disposal problems
Notes: 1. Expressed as a "daily load"; represents the upper range of conditions
needed to attain and maintain applicable water quality standards
2. Based on the 30-day geometric mean identified in the applicable water
quality standards
3. Developed using ambient water quality monitoring data
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An Approach for Using Load Duration Curves in the Development of TMDLs
Use of Monthly Duration Curves.   In order to ensure consistency with the geometric
mean criterion,  30-day  or monthly mean flows can also  be used to identify loading
capacities that  supplement daily load targets.  This  approach offers another way  to
develop a quantitative analysis of seasonal variation indicative of the 30-day or monthly
target in the water quality standards (i.e., larger loads  in months with higher flows and
smaller loads in months with lower flows).  Table B-6 summarizes a portion of individual
monthly  mean  flow values using USGS data for Swamp Creek near Kenmore, WA.
Summary statistics  for each month using the full record are included at the bottom  of
Table B-6.

As seen in Table B-6, seasonal patterns reflect higher flows in late fall and early winter
(e.g., December, January) with a transition to lower flows in summer months.  However,
interannual variation is  another factor to consider when identifying loading capacities.
Average values for the same month can vary by as much as  an order of magnitude due to
varying weather conditions (e.g., an unusually dry December or an abnormally wet June),
as shown in  Table  B-6  for the Swamp Creek.  Flow  duration curves developed using
individual monthly average values (as opposed to daily average flows) provide a way to
consider interannual  variation.   The  duration curve framework  uses a  frequency
distribution based on all individual months over the same  period (such as all  values in
Table B-6). Figure B-14 shows the loading  capacity curve for Swamp Creek using the
frequency distribution of mean monthly flows.

                   Table B-6. Swamp Creek Monthly Mean Flows

1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Maximum
Average
Median
25th %
10'"%
Minimum
Individual Monthly Mean Flows (cfs)
Jan
27.1
63.5
42.5
94.1
87.7
46.6
24.8
110.4
80.0
41.3
58.5
27.1
140.5
77.0
83.5
55.5
35.6
22.7
Feb
79.2
80.0
57.3
105.7
89.8
66.7
40.9
56.4
59.9
18.7
53.1
79.2
105.7
62.5
57.5
51.5
35.4
18.7
Mar
33.2
59.2
30.3
68.6
57.5
71.8
29.0
25.3
79.0
46.1
74.8
33.2
115.1
56.6
54.3
38.2
29.8
25.3
Apr
39.0
41.3
34.6
48.3
28.8
38.9
31.1
19.8
25.9
48.4
23.1
39.0
50.7
34.6
34.6
29.7
22.2
15.9
May
11.0
15.8
22.5
13.7
17.8
30.2
19.9
24.0
15.6
22.4
17.4
11.0
30.2
18.5
17.4
15.5
14.0
11.0
June
5.7
21.9
20.8
8.4
12.2
19.3
26.7
7.7
7.8
22.6
10.8
5.7
26.7
12.8
11.3
8.0
6.5
5.7
July
6.0
10.1
14.0
10.2
13.5
8.4
6.7
10.3
6.8
6.4
7.0
6.0
14.0
7.7
6.7
6.0
5.0
4.3
Aug
5.5
9.2
6.9
7.6
12.5
7.5
7.4
5.1
6.4
5.4
6.6
5.5
13.0
7.1
6.7
5.3
4.3
3.6
Sept
7.5
8.8
15.4
12.3
13.0
12.9
10.0
9.1
6.0
8.7
5.1
7.5
22.8
10.3
9.6
7.0
5.4
5.1
Oct
14.4
7.6
53.9
18.5
10.3
13.4
35.1
18.0
5.8
10.1
22.1
14.4
53.9
15.5
12.7
9.1
7.2
5.8
Nov
14.9
37.1
74.2
24.9
91.1
80.6
26.1
66.1
13.1
42.2
26.3
14.9
91.1
38.7
26.3
24.4
14.7
11.1
Dec
86.5
69.5
131.2
110.0
59.2
86.1
23.8
61.4
54.1
35.6
42.2
86.5
131.2
72.9
69.5
55.6
39.1
16.4
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An Approach for Using Load Duration Curves in the Development of TMDLs
  Figure B-14.  Monthly Bacteria Loading Capacity Using Duration Curve Framework

                                   Swamp Creek
                                 Load Duration Curve
        B 100
        ^
I  '
 o
— 0.1
 u
 
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An Approach for Using Load Duration Curves in the Development of TMDLs
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An Approach for Using Load Duration Curves in the Development of TMDLs
                            APPENDIX C
                Targeting Potential Solutions and
                  Connecting to Implementation
Traditional approaches towards TMDL development tend to focus on targeting a single
value, which depends on a water quality criterion and design flow.  The single number
concept does not work well when dealing with impairments  caused by NFS pollutant
inputs (Stiles, 2001). One of the more important concerns regarding nonpoint sources is
variability in  stream flows, which  often causes different source  areas and loading
mechanisms to dominate under different flow regimes. Because NFS pollution is often
driven  by runoff events, TMDL  development  should  consider factors  that ensure
adequate water quality across a range of flow conditions.

Cl.   "BOTTOM UP" APPROACHES
An important key to the success of the TMDL program,
in terms of engaging the public, is building linkages to
other  programs,  such  as  nonpoint   source  (NFS)
management.    Many  successful  efforts to  develop
TMDLs have involved the §319 program as a way to
utilize  local  groups  in  data  collection,  analysis,  and
implementation.  Watershed analysis has been used to
build a "bottom up " approach,  which defines one way to
establish  a meaningful,  value-added framework  linking
water quality concerns to proposed solutions.   TMDL
development using a "bottom up " approach considers the
interaction  between  watershed  processes,  disturbance
activities,  and  available methods  to  reduce  pollutant
loadings,  specifically BMPs.
A "bottom up " approach capitalizes on the networks of programs and authorities across
jurisdictional lines.  Information on management measures related to both source control
and delivery reduction methods is linked to conditions  for which specific restoration
strategies may be most appropriate. This information can then be incorporated into the
allocation part of TMDL development using a duration curve framework.
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C2.   PROBLEM SOLVING FRAMEWORK

The "two Ps"  - practical approaches and partnerships - are critical  to  successful
watershed planning and implementation.  On the practical side, a "bottom  up " approach
must overcome the challenge of translating detailed technical concepts and information
into "plain English ".  On the partnership side, key stakeholders must be engaged in the
process, so that meaningful results with measurable improvements are achieved.

A problem solving framework, constructed around a set of fundamental  questions,  can
help focus development of practical approaches and encourage participation among  key
partners. A basic set of questions using a "bottom up" approach to address water quality
problems often includes:
              WHY the concern?
              WHAT reductions are needed?
              WHERE are the sources?
              WHO needs to be involved?
              WHEN  will actions occur?
These simple, practical questions can be easily used to keep assessment efforts connected
with implementation activities. Methods to communicate technical information, such as
duration curves, can be an important part of the problem solving process.

C3.   ENGAGING STAKEHOLDERS
Public   involvement   is   fundamental   to
successful    TMDL    development     and
implementation.    Duration  curves  provide
another way of presenting water quality data,
which characterizes  concerns  and  describes
patterns  associated with impairments.   As  a
communication tool,  this framework can help
elevate   the   importance   of   monitoring
information to stakeholders.
The extended use of monitoring information and the alternative way to present TMDLs
using duration curves offers  an opportunity  for  enhanced targeting,  both in  field
investigation efforts and implementation planning. As an assessment and communication
tool, duration curves can help narrow potential debates, as well as inform the public and
stakeholders  so  they  become engaged in the process.   Duration  curves  offer  an
opportunity  for enhanced targeting,  both in TMDL development  and in water quality
restoration efforts.  In  particular, duration curves can add value to the TMDL process  by
identifying:
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      • targeted participants (e.g., NPDES permitees) at critical flow conditions;
      • targeted programs (e.g., Conservation Reserve Program);
      • targeted activities (e.g., conservation tillage or contour farming); and
      • targeted areas (e.g., bank stabilization projects).
                                                                   Targeted Participants
Figure C-l represents the first of several hypothetical
examples to illustrate the potential use  of duration
curves, both  as  a  diagnostic  indicator and  as a
communication  tool for  targeting  in  the  TMDL
process.   The target curve in Figure  C-l is  derived
using  flow  duration  intervals  that  correspond  to
stream discharge values and numeric criteria for E.
Coli.
The area circled on the right side of the duration curve represents hydrologic conditions
where the target is exceeded.   In  this example,  wastewater treatment plants exert a
significant influence  at low flows.  Duration curves support a  "bottom  up" approach
towards TMDL development and restoration efforts by identifying targeted participants,
in the case of Figure C-l, point  sources. For urban watersheds,  water quality concerns
experienced during low flow conditions might involve detecting illicit connections under
an  MS4  stormwater program.   In an agricultural setting  showing similar patterns,
potential solutions could include livestock management through riparian fencing or off-
site watering BMPs.

       Figure C-l.  Duration Curve as General Indicator of Hydrologic Condition

                                Pipe Creek below Elfton
                               Sample Load Duration Curve
                 a    ID    20    30    40    50    GO    70

                               Flow Duration Interval

       TARGETED Participants: Point Sources
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An Approach for Using Load Duration Curves in the Development of TMDLs
Figure C-2 illustrates the added value duration
curves can  provide by highlighting potential
contributing areas.  As seen in this hypothetical
example, the target is met when the hydrologic
condition of the watershed  is  above  a  flow
duration interval of 70 (generally low flow and
dry  conditions).   Problems   start to  develop
under  mid-range  flows  and  sometimes  dry
conditions, as indicated by the circled area.
Wet-weather events  can range  from high  flows and moist conditions after severe
thunderstorms  to  lower  surface  runoff volumes following light rains.   Watershed
conditions, land use, and proximity of source areas to streams should also be considered.
For this particular watershed (Figure C-2), the  increased load may be the  result of
pollutant delivery associated with rainfall and runoff from riparian areas.  In more urban
watersheds, runoff from impervious areas could also contribute  flow and pollutants in
response to light rain, exhibiting a pattern similar to Figure C-2.

Duration curves can be used as a diagnostic tool, which supports a "bottom up " approach
towards  TMDL development and  water quality restoration  by  identifying  targeted
programs, namely those focused on riparian protection.  In agricultural areas, such as the
Willow Creek example watershed (Figure C-2), this might include  activities such as the
Conservation Reserve Program (CRP) and Conservation Reserve Enhancement Program
(CREP).

              Figure C-2.  Duration Curve with Contributing Area Focus
                              Willow Creek near Turkey Gap
                                Sample Load Duration Curve
                               Flow Duration Interval (%)

           TARGETED Programs: Riparian Buffers (&g. CRP, CREP)
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An Approach for Using Load Duration Curves in the Development of TMDLs
The focus on contributing areas is further illustrated
with another hypothetical example,  shown in Figure
C-3, where total suspended  solids  associated with
surface erosion  is the pollutant of concern.  Here,
the duration curve is  expressed in terms of yield to
show  how  distributions  derived  from  a flow
duration curve can be extended to  other measures,
again as a simple targeting tool.
In the Chicken Run example (Figure C-3), observed values only exceed the target when
the hydrologic condition of the watershed is below 55 (generally higher flows).  For the
Chicken Run example watershed, duration curves can be used to support a "bottom up "
approach towards TMDL development.

Chicken Run is also an agricultural watershed.  Wet-weather events expected to deliver
pollutants under moist conditions are generally  associated with more saturated soils.  In
addition to riparian areas,  a larger portion of the watershed drainage area is potentially
contributing runoff.

In this  case, consideration might be  given  to  targeted activities  such as  conservation
tillage,  contour strips,  and grassed waterways.  For urban watersheds, water quality
concerns  experienced during  mid-range  flows  and  moist  conditions  might be best
addressed through site  construction BMPs under  an MS4 storm water  management
program (SWMP).  Critical area ordinances are another set of management measures that
would address water quality concerns under  these flow conditions.  Thus, water quality
data and  a duration curve framework can  help  guide  local implementation efforts to
achieve meaningful results.

               Figure C-3.  Duration Curve  with Targeted Activity Focus
                              Chicken Run above \ It. Pleasant
                                 Sample Yield Duration Curve
                               Flow Duration Interval (%)

             TARGETED Activities: Contour Strips, Conser\'ation Tillage
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Figure  C-4  illustrates  another  hypothetical
example,   where  transport   and   delivery
mechanisms  that  occur  under  high  flow
conditions   typically   include   stream  bank
erosion and channel processes.  Targeted areas
for water quality improvement might consider
bank   stabilization   efforts.     For  urban
watersheds, targeted areas might involve post
development  BMPs   intended  to   address
channel protection.
            Figure C-4.  Duration Curve with Delivery Mechanism Focus

                         Rock Creek near Moose Junction
                            Sample Yield Duration Curve
        1000
        0.001
                                                               90
                                                                     100
                          Flow Duration Interval
 TARGETED Areas:  Streambank Erosion, Bank Stability
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An Approach for Using Load Duration Curves in the Development of TMDLs
CONNECTING TO IMPLEMENTATION AND RESULTS

A major advantage of the duration curve framework in TMDL development is the ability
to provide meaningful  connections  between allocations  and  implementation efforts.
Because the flow duration interval (FDI) serves  as  a  general indicator of hydrologic
condition (i.e., wet versus dry and to what degree), allocations and reduction targets can
be linked to source  areas, delivery mechanisms, and the appropriate set of management
practices.  The use of duration curve zones (e.g., high flow,  moist, mid-range, dry, and
low flow) allows the development of allocation tables, which can be used to summarize
potential implementation actions that most effectively address water quality concerns.

                      Connections to Management Practices

Development of wasteload allocations for continuous point source discharges is relatively
straightforward using a duration curve framework, when compared to either storm water
or nonpoint sources.  Consideration  of pollution control measures is typically done in
conjunction with NPDES permit development.  Wasteload allocations (WLAs) can be
expressed at one level across the entire duration curve, or WLAs may be tiered to specific
flow levels  and the corresponding flow duration interval.  Storm water or nonpoint
sources, on the other hand, present a much greater challenge because pollutants are
transported  to  surface waters by a variety  of mechanisms (e.g., runoff,  snowmelt,
groundwater infiltration).  Best management practices (BMPs) generally focus on source
control and / or delivery reduction.  Table C-l illustrates an approach, which could be
used to assess  the management options in a way that considers the potential relative
importance of hydrologic conditions.

                              Documenting Results

Figure C-5 illustrates the advantage of the duration  curve framework in documenting
results using Charles River data. This location has been monitored since 1989. Based on
this water quality information, significant  reductions  in bacteria loads to the river have
occurred over the past ten years through CSO controls plus illicit discharge detection and
elimination.  These improvements are reflected in  the data  using  a duration  curve
framework, particularly  in the moist, mid-range, and dry zones.  Individual allocations
can help focus implementation efforts to address remaining  problems  that occur  under
high flow conditions.

Figure C-6 illustrates another example of the advantage of this framework using Big
Sioux River data.  This location has been monitored by the State of South Dakota since
1974. As noted in Figure C-6, significant reductions in bacteria loads  to the river have
occurred over the past fifteen years. These improvements are reflected in the data using a
duration curve framework, particularly in the high, moist, mid-range, and dry zones.  The
duration curve  framework can help  focus efforts to  address remaining  problems with
management strategies most appropriate for those flow conditions.
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An Approach for Using Load Duration Curves in the Development of TMDLs
   Table C-l.  Example Management Practice / Hydrologic Condition Considerations
Management Practice
Bacteria Source Reduction
Remove Illicit Discharges
Address Pet & Wildlife Waste
Combined Sewer Overflow Management
Combined Sewer Separation
CSO Prevention Practices
Septic System Management
Managing Private Systems
Replacing Failed Systems
Installing Public Sewers
Storm Water Infiltration / Retention
Infiltration Basin
Infiltration Trench
Infiltration / Biofilter Swale
Storm Water Detention
Created Wetland
Low Impact Development Practices
Disconnecting Impervious Areas
Bioretention
Pervious Pavement
Green Roof
Rain Gardens
Agricultural Management Practices
Managing Manure Application
Pasture / Grazing Management
Managing Barnyards
Managing Recreational Sources
Designate No Discharge Areas
Address Discharges from Boats
Other
Point source controls
Riparian buffers
Pet waste education & ordinances
Note: Potential relative importance of mai
given hydrologic condition (H: Hig
Duration Curve Zone
High

































Moist































H
M
Mid-
Range






























M
H
H
Dry






























H
H
H
Low






























H


lagement practice effectiveness under
h; M: Medium; L: Low)
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An Approach for Using Load Duration Curves in the Development of TMDLs
     Figure C-5.  Documenting Program Results Using Duration Curve Framework

                            Charles River — Watertown Dam
                       Load Duration Curve (1989 - 2004 Monitoring Data)
              High
                         Moist
Mid-range
                                                                Low
                        20    30     40    50    60    70     SO

                           Flow Duration Interval (%)
                         90
100
     Figure C-6.  Documenting Program Results Using Duration Curve Framework
                               Big Sioux River at Brandon
                       Load Duration Curve (1974 - 2005 Monitoring Data)
                High
                           Moist
 Mid-range
                                                                 Low
                    10    20    30    40    SO    £0    70

                             Flow Duration Interval
                     80    90   100
                                                                   3,72 9 square miles
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An Approach for Using Load Duration Curves in the Development of TMDLs
                            APPENDIX D
                    Acronyms and References
ACRONYMS

7Q10
90th
ALC
ARA
BMP
BST
CFR
cfs
cfu
C.L.
cms
CREP

CRP
CSO
CWA
DC
EIFAC
EPA
FDI
F.I.
FR
geo. mean
GIS
GM
G-org
GWLF
HSPF
LA
LC
LDC
LNCC
MCL
MOS
the 7-day average low flow occurring once in 10 years
90th percentile
aquatic life criteria
antibiotic resistance analysis
best management practice
bacteria source tracking
Code of Federal Regulations
cubic feet per second
colony forming units
confidence level
cubic meters per second
Conservation Reserve Enhancement Program (U.S. Department of
Agriculture)
Conservation Reserve Program (U.S. Department of Agriculture)
combined sewer overflow
Clean Water Act
duration curve
European Inland Fisheries Advisory Committee
U.S. Environmental Protection Agency
flow duration interval
frequency interval
Federal Register
geometric mean
geographic information system
geometric mean
billion organisms
generalized watershed loading function
hydrological simulation program - FORTRAN
load allocation
load (duration) curve
load duration curve
log-normal criteria curve
maximum contaminant level
margin of safety
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An Approach for Using Load Duration Curves in the Development of TMDLs
MS4
NPDES
NFS
org
PS
Q-based
R. curve
SF
SS
SWAT
SWMP
TMDL
T-org
TSD
TSS
USGS
WLA
WQ
WQS
WWTF
WWTP
Z-90th
ZMC
7Q10
municipal separate storm sewer system
National Pollutant Discharge Elimination System
nonpoint source
organisms
point source
flow data-based
regression (or rating) curve
storm flow
suspended sediment
soil and water assessment tool
storm water management program
total maximum daily load
trillion organisms
technical support document
total suspended solids
U.S. Geological Survey
waste load allocation
water quality
water quality standard
wastewater treatment facility (also referred to as a WWTP)
wastewater treatment plant (also referred to as a WWTF)
90th percentile of a particular zone
zone median concentration
Lowest streamflow for 7 consecutive days that occurs on average once
every 10 years
REFERENCES

Bonta, J.V. March 2002. Framework for Estimating TMDLs with Minimal Data. ASAE
      Proceedings  of  the  Watershed  Management to  Meet  Emerging  TMDL
      Regulations Conference. Fort Worth, TX. pp. 6-12.

Cleland, B.R.  June 2007.  TMDL Development From the  "Bottom Up" - Part IV:
      Connecting to Storm Water Management Programs.   National TMDL Science
      and Policy 2007 — WEF Specialty Conference. Bellevue, WA.

Cleland, B.R. November 2003. TMDL Development From the "Bottom Up" - Part III:
      Duration  Curves  and Wet-Weather Assessments. National TMDL Science and
      Policy 2003 -- WEF Specialty Conference. Chicago, IL.

Cleland, B.R. November 2002.  TMDL Development From the "Bottom Up" - Part II:
      Using Duration  Curves to  Connect  the Pieces.  National TMDL Science and
      Policy 2002 -- WEF Specialty Conference. Phoenix, AZ.
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Hornberger, G.M., J.P. Raffensperger, P.L. Wiberg, and K.N. Eshleman.  1998. Elements
       of Physical Hydrology. Johns Hopkins University Press. Baltimore, MD. 302 p.

Leopold, L.B.  1994. A View of the River. Harvard University Press.  Cambridge, MA.

Linsley, R.K., M.A. Kohler, and J.L. Paulus.  1982.  Hydrology for Engineers (3rd ed.).
       McGraw-Hill. New York, NY.

Mehan, G.T. November 2001.  Testimony on TMDL Program before Subcommittee on
       Water  Resources  and  Environment   -  U.S.   House  of  Representatives.
       Washington, DC.

Rosgen, D.L.  1996. Applied River Morphology.  Wildland Hydrology.  Pagosa  Springs,
       CO.

Searcy, James, K.  1959. Flow-Duration Curves; Manual of Hydrology: Part 2. Low-
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EPA 841-B-07-006                        67                             August 2007

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EPA 841-B-07-006                         68                             August 2007

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