NC0024937_Fact Sheet_20240130

Fact Sheet
NPDES Permit No. NCO024937
Permit Writer/Email Contact: Nick Coco, [e-mail]
Date: 1/25/2024
Division/Branch: NC Division of Water Resources/NPDES Municipal Permitting
Fact Sheet Template: Version 09Jan2017
Permitting Action:
❑X Renewal
❑ Renewal with Expansion
❑ New Discharge
❑ Modification (Fact Sheet should be tailored to mod request)
Note: A complete application should include the following:
• For New Dischargers, EPA Form 2A or 2D requirements, Engineering Alternatives Analysis, Fee
• For Existing Dischargers (POTW), EPA Form 2A, 3 effluent pollutant scans, 4 2nd species WET
tests.
• For Existing Dischargers (Non-POTW), EPA Form 2C with correct analytical requirements based
on industry category.
Complete applicable sections below. If not applicable, enter NA.
1. Basic Facility Information
Facility Information
Applicant/Facility Name:
Charlotte Water/Sugar Creek Water Resource Recovery Facility (WRRF)
Applicant Address:
5100 Brookshire Blvd., Charlotte, NC 28216
Facility Address:
5301 Closeburn Road, Charlotte, NC 28210
Permitted Flow:
20.0 MGD (Outfall 001) & 8.0 MGD (expansion Outfall 002)
Facility Type/Waste:
MAJOR Municipal; 92% domestic, 8% industrial'
Facility Class:
Grade IV Biological Water Pollution Control System
Treatment Units:
Mechanical bar screens, grit removal, belt conveyor system, primary clarifiers, aeration
basins, fine bubble diffusers, blowers, pH adjustment, secondary clarifiers, RAS/WAS
pumping, UV disinfection, deep bed sand filtration, cascade aeration, EQ basins, odor
scrubbing
Pretreatment Program (Y/N)
Y, LTMP
County:
Mecklenburg
Region
Mooresville
*Based on permitted flows.
Briefly describe the proposed permitting action and facility background.- Charlotte Water has applied for
an NPDES permit renewal at 20.0 MGD for the Sugar Creek WRRF. This facility serves a population of
approximately 179,100 residents, as well as 11 significant industrial users (SIUs), including 5 categorical
industrial users (CIUs), via an approved pretreatment program. Treated domestic and industrial
wastewater is discharged via primary Outfall 001 into Little Sugar Creek, a class C waterbody in the
Catawba River Basin. Outfall 001 is located approximately 9 miles upstream of the North Carolina -South
Carolina border. The facility also has future capacity Outfall 002 into Little Sugar Creek with the same
designations as Outfall 001. This future capacity outfall is permitted for 8.0 MGD. Charlotte Water has
requested continuation of the future capacity Outfall 002. Upon construction of the 8.0 MGD facility, due
to both facilities operating in one permit, the same operator of record shall be responsible for both
facilities for eDMR reporting purposes.
Page 1 of 16

As noted in the application, Charlotte Water currently has plans for improvements to the UV disinfection
system with an estimated construction completion in 2025.
Inflow and Infiltration (I/I): Charlotte Water estimates approximately 1.913 MGD of I/I is experienced at
the McAlpine Creek WWMF. Charlotte Water provided a robust collection system maintenance plan that
is currently being followed to minimize I/I experienced throughout their system, which includes manhole
inspections, smoke testing, CCTV, flow monitoring and pipe rehabilitation/replacement.
Sludge disposal: Biosolids residuals are permitted, managed, and disposed under a contract with Synagro.
Land application and land filling are the means for ultimate use of the residuals. This is managed under
permit WQ0000057.
2. Receiving Waterbody Information:
Receiving Waterbody Information
Outfalls/Receiving Stream(s):
Outfall 001 — Little Sugar Creek, Outfall 002 — Little Sugar
Creek (not in use)
Stream Segment:
11-137-8a
Stream Classification:
C
Drainage Area (m12):
40.8
Summer 7Q10 (cfs)
3.4
Winter 7Q10 (cfs):
5.5
30Q2 (cfs):
8.7
Average Flow (cfs):
47
IWC (% effluent):
90%
2022 303(d) listed/parameter:
Yes; listed as exceeding criteria for benthos and fish
community'
Subject to TMDL/parameter:
Yes- Statewide Mercury TMDL implementation; Fecal
coliform TMDL for Irwin Creek (DM 1000/10 ml); SC
DHEC ongoing development on nutrient TMDL in the
Catawba basing
Basm/HUC:
Catawba River/0305010301
USGS Topo Quad:
G15NW
'Little Sugar Creek is also listed in the 2022 Integrated Report as exceeding criteria for both turbidity and
fecal coliform.
2Please see attached for the 2020 SCDHEC Lower Catawba River Basin — 2020 Nutrient Study.
3. Effluent Data Summary
Effluent data for Outfall 001 is summarized below for the period of May 2019 through August 2022.
Table 1. Effluent Data Summary Outfall 001
Permit
Parameter
Units
Average
Max
Min
Limit
Flow
MGD
14.8
34.1
5.3
MA 20.0
WA 7.5
CBOD summer
mg/1
2.2
10.9
2
MA 5.0
WA 15.0
CBOD winter
mg/1
2.7
22.6
2
MA 10.0
Page 2 of 16

NH3N summer
mg/1
0.2
3
0.1
WA 3.0
MA 1.0
WA 6.0
NH3N winter
mg/I
0.8
12
0.1
MA 2.0
WA 45.0
TSS
mg/1
3.2
56.4
2.5
MA 30.0
pH
SU
7.2
7.7
6.1
0>pH<
6.9.0
(geometric)
Fecal coliform
9/100 ml
(ge 2 3 an)
2350
1
WA 400
MA 00
DM 1000
DO
mg/1
8.7
10.1
7.8
DA >6.0
Monitor &
Conductivity
umhos/cm
465
684
217
Report
Monitor &
Temperature
° C
22.4
28.1
14.8
Report
TN
mg/l
12.1
29.6
5.7
Monitor &
Report
TP
mg/1
1.4
3.4
0.1
Monitor &
Report
TP Load
lbs/day
403
495.37
288.68
826.0
Monitor &
Total Copper
ug/1
3
6
2
Report
Monitor &
Total Silver
ug/1
< 1
< 1
< I
Report
Total Nickel
ug/1
3.5
24
2
Monitor &
Report
Total Hardness
mg/1
72
130
46
Monitor &
Report
MA -Monthly Average, WA -Weekly Average, DM -Daily Maximum, DA=Daily Average
* annual rolling average of combined discharge of 3 facilities: Sugar Creek WRRF, Irwin Creek WRRF, and
McAlpine Creek W WMF
4. Instream Data Summary
Instream monitoring may be required in certain situations, for example: 1) to verify model predictions
when model results for instream DO are within 1 mg/1 of instream standard at full permitted flow; 2) to
verify model predictions for outfall diffuser; 3) to provide data for future TMDL; 4) based on other
instream concerns. Instream monitoring may be conducted by the Permittee, and there are also
Monitoring Coalitions established in several basins that conduct instream sampling for the Permittee (in
which case instream monitoring is waived in the permit as long as coalition membership is maintained).
If applicable, summarize any instream data and what instream monitoring will be proposed for this
permit action: The current permit requires instream monitoring for several locations: Irwin Creek,
McAlpine Creek, Sugar Creek, and Little Sugar Creek. All of these receiving streams are a part of the
facility and facility owner's (Charlotte Water) instream monitoring program for Sugar Creek WRRF,
Irwin Creek WRRF, and McAlpine WWMF (see stream map attached in factsheet attachments).
Page 3 of 16

Instream monitoring for all parameters for Irwin Creek WRRF's receiving streams, Irwin Creek and
Sugar Creek, will be maintained in McAlpine Creek WWMF's permit (NC0024970).
For the Sugar Creek WRRF renewal, instream data for LSC1 (upstream) and LSC3 (downstream) were
analyzed for the period of May 2019 through August 2023. Little Sugar Creek stations (LSC1 and LSC3)
monitor for dissolved oxygen, conductivity, copper, zinc, and temperature. In addition to the instream
monitoring requirements in the permit, Charlotte Water conducted sampling at both stations for multiple
parameters that overlap with requirements at other stations. The data has been summarized in Table 3
below.
Table 3. Instream Monitoring Data Summary Sugar Creek WRRF
Parameter
Units
Upstream (LSC1)
Downstream (LSC3)
Average
Min
Max
Average
Min
Max
Temperature
° C
20.3
4.8
26.7
22.0
8
28.5
DO
mg/1
8.5
7
12.6
7.8
6.4
11.4
Conductivity
µmhos/cm
210
87
444
323
102
507
Total Copper
mg/1
3.7
2
14
3.5
2.1
11
Total hardness
mg/1
82.4
31
100
79.3
30
110
Total Chromium
µg/l
5.2
< 5
12
5.0
5
5.7
Total Zinc
µg/l
11.6
10
29
20.9
10
33
pH
S M.
7.2
6.3
7.8
7.1
6.6
7.6
NO2+NO3
mg/1
0.8
< 0.5
1.1
9.4
5.2
20
TKN
mg/l
0.4
0.3
0.5
0.8
0.3
1.3
Ammonia
mg/1
-
-
-
< 20
< 20
< 20
TP
mg/l
<0.1
<0.1
<0.1
1
0.4
1.6
Orthophosphate
mg/l
0.05
< 0.05
0.07
0.9
0.29
1.5
Students t-tests were run at a 95% confidence interval to analyze relationships between upstream
and downstream samples. A statistically significant difference is determined when the t-test p-value
result is < 0.05.
Downstream temperature was not greater than 29 degrees Celsius [per 15A NCAC 02B .0211 (18)] at
either instream monitoring location during the period reviewed. Downstream temperature was greater
than upstream temperature by more than 2.8 degrees Celsius on 17 occasions during the period reviewed.
Review of concurrent effluent temperature for these 17 occasions demonstrated a consistent relationship
between elevated effluent temperatures and elevated downstream temperature. Effluent temperature does
appear to have the potential to influence instream temperature, particularly during winter months.
Additionally, it was concluded that a statistically significant difference exists between upstream (LC I)
and downstream (LC3) temperature.
It was concluded that a statistically significant difference exists between upstream (LC I) and downstream
(LC3) DO. However, downstream DO did not drop below 5 mg/L [per 15A NCAC 02B .0211 (6)] during
the period reviewed.
Instream pH was between 6.0 and 9.0 standard units [per 15A NCAC 02B .0211 (14)] at both monitoring
locations during the period reviewed.
It was concluded that a statistically significant difference exists between upstream and downstream
conductivity, TKN, NO2+NO3, TP, Orthophosphate and total zinc with downstream concentrations being
consistently higher than upstream concentrations.
Page 4 of 16

It was concluded that no statistically significant difference exists between upstream (LSC1) and
downstream (LSC3) copper. Additionally, downstream total copper was not observed at levels greater
than the standard of 24.2 ug/L (calculated based on average reported upstream hardness of 82.4 mg/L and
EPA Default Partition Coefficient of 0.348) during the period reviewed.
No changes were made to Little Sugar Creek instream monitoring requirements. All instream monitoring
for all parameters for the Sugar Creek WRRF's receiving stream, Little Sugar Creek, and the Irwin Creek
WRRF's receiving streams, Irwin Creek and Sugar Creek, will be maintained in McAlpine Creek
WWMF's permit (NC0024970) along with McAlpine Creek instream monitoring requirements. Please
note that, while no changes have been made to the instream monitoring requirements listed in the permit
for Little Sugar Creek, instream summaries will be provided for McAlpine Creek, Sugar Creek and Irwin
Creek in the applicable permit reviews.
Is this facility a member of a Monitoring Coalition with waived instream monitoring (YIN): NO
Name of Monitoring Coalition: NA
5. Compliance Summary
Summarize the compliance record with permit effluent limits (past 5 years): The facility reported no limit
violations from 8/2018 — 8/2023.
Summarize the compliance record with aquatic toxicity test limits and any second species test results
(past 5 years): The facility passed 18 of 18 quarterly chronic toxicity tests, as well as all 4 second species
chronic toxicity tests conducted from February 2019 to May 2023.
Summarize the results from the most recent compliance inspection: The last facility inspection conducted
in February 2022 reported that the facility was compliant.
6. Water Quality -Based Effluent Limitations (WQBELs)
Dilution and Mixing Zones
In accordance with 15A NCAC 213.0206, the following streamflows are used for dilution considerations
for development of WQBELs: 1Q10 streamflow (acute Aquatic Life); 7Q10 streamflow (chronic Aquatic
Life; non -carcinogen HH); 30Q2 streamflow (aesthetics); annual average flow (carcinogen, HH).
If applicable, describe any other dilution factors considered (e.g., based on CORMIX model results): NA
If applicable, describe any mixing zones established in accordance with I5A NCAC 2B. 0204(b): NA
Oxygen -Consuming Waste Limitations
Limitations for oxygen -consuming waste (e.g., BOD) are generally based on water quality modeling to
ensure protection of the instream dissolved oxygen (DO) water quality standard. Secondary TBEL limits
(e.g., BOD= 30 mg/1 for Municipals) may be appropriate if deemed more stringent based on dilution and
model results.
If permit limits are more stringent than TBELs, describe how limits were developed.- The current permit
limitations for CBOD are based on a 1991 agreement with Charlotte Water to upgrade Sugar Creek
WRRF, Irwin Creek WRRF, and McAlpine Creek WWMF to meet more restrictive advanced tertiary
limits for CBOD, ammonia and TSS in order for Charlotte Water to expand their plants. This agreement
was based on the receiving stream having reached its assimilative capacity for some parameters at the
time. The limits took effect in 1995. No changes were made from the previous permit limits.
Page 5 of 16

Ammonia and Total Residual Chlorine Limitations
Limitations for ammonia are based on protection of aquatic life utilizing an ammonia chronic criterion of
1.0 mg/l (summer) and 1.8 mg/1(winter). Acute ammonia limits are derived from chronic criteria,
utilizing a multiplication factor of 3 for Municipals and a multiplication factor of 5 for Non -Municipals.
Limitations for Total Residual Chlorine (TRC) are based on the NC water quality standard for protection
of aquatic life (17 ug/1) and capped at 28 ug/l (acute impacts). Due to analytical issues, all TRC values
reported below 50 ug/1 are considered compliant with their permit limit.
Describe any proposed changes to ammonia and/or TRC limits for this permit renewal: The permit does
not currently set limits or monitoring requirements for TRC due to the facility employing UV treatment
for disinfection. However, in the event of an emergency where chlorination is required as a backup or
temporary means of disinfection at the facility, a TRC limit and monitoring requirement have been added
to the permit based on the review in the attached WLA spreadsheet. Please note that TRC monitoring is
only required in the event that chlorine is used at the plant.
The current limitations for ammonia are based on protection of aquatic life utilizing an ammonia chronic
criterion of 1.0 mg/l (summer) and 1.8 mg/l (winter). Acute ammonia limits are derived from chronic
criteria, utilizing a multiplication factor of 3 for Municipals and a multiplication factor of 5 for Non -
Municipals. The ammonia limits have been reviewed in the attached WLA for toxicity and have been
found to be protective. No changes were made.
Reasonable Potential Analysis (RPA) for Toxicants
If applicable, conduct RPA analysis and complete information below.
The need for toxicant limits is based upon a demonstration of reasonable potential to exceed water quality
standards, a statistical evaluation that is conducted during every permit renewal utilizing the most recent
effluent data for each outfall. The RPA is conducted in accordance with 40 CFR 122.44 (d) (i). The NC
RPA procedure utilizes the following: 1) 95% Confidence Level/95% Probability; 2) assumption of zero
background; 3) use of detection limit for "less than" values; and 4) streamflows used for dilution
consideration based on 15A NCAC 2B.0206. Effective April 6, 2016, NC began implementation of
dissolved metals criteria in the RPA process in accordance with guidance titled NPDES Implementation of
Instream Dissolved Metals Standards, dated June 10, 2016.
A reasonable potential analysis was conducted on effluent toxicant data collected between May 2019 and
November 2022. Pollutants of concern included toxicants with positive detections and associated water
quality standards/criteria. Based on this analysis, the following permitting actions are proposed for this
permit:
• Effluent Limit with Monitoring. The following parameters will receive a water quality -based
effluent limit (WQBEL) since they demonstrated a reasonable potential to exceed applicable
water quality standards/criteria: None
• Monitoring Only. The following parameters will receive a monitor -only requirement since they
did not demonstrate reasonable potential to exceed applicable water quality standards/criteria,
but the maximum predicted concentration was >50% of the allowable concentration: None
• No Limit or Monitoring: The following parameters will not receive a limit or monitoring, since
they did not demonstrate reasonable potential to exceed applicable water quality
standards/criteria and the maximum predicted concentration was <50% of the allowable
concentration: Total Arsenic, Total Cadmium, Total Chromium, Total Copper, Total Cyanide,
Total Lead, Total Molybdenum, Total Nickel, Total Selenium, Total Silver, Total Zinc
• POTW Effluent Pollutant Scan Review: Four effluent pollutant scans (2020, 2021, 2022 and
2023) were evaluated for additional pollutants of concern.
Page 6 of 16

o The following parameter(s) will receive a water quality -based effluent limit (WQBEL)
with monitoring, since as part of a limited data set, two samples exceeded the allowable
discharge concentration: None
o The following parameter(s) will receive a monitor -only requirement, since as part of a
limited data set, one sample exceeded the allowable discharge concentration: None
o The following parameters will not receive a limit or monitoring, since they did not
demonstrate reasonable potential to exceed applicable water quality standards/criteria and
the maximum predicted concentration was <50% of the allowable concentration: Total
Beryllium, Total Phenolic Compounds, Bis (2-Ethylhexyl) Phthalate
If applicable, attach a spreadsheet of the RPA results as well as a copy of the Dissolved Metals
Implementation Fact Sheet for freshwater/saltwater to this Fact Sheet. Include a printout of the RPA
Dissolved to Total Metal Calculator sheet if this is a Municipality with a Pretreatment Program.
Toxici . Testing Limitations
Permit limits and monitoring requirements for Whole Effluent Toxicity (WET) have been established in
accordance with Division guidance (per WET Memo, 8/2/1999). Per WET guidance, all NPDES permits
issued to Major facilities or any facility discharging "complex" wastewater (contains anything other than
domestic waste) will contain appropriate WET limits and monitoring requirements, with several
exceptions. The State has received prior EPA approval to use an Alternative WET Test Procedure in
NPDES permits, using single concentration screening tests, with multiple dilution follow-up upon a test
failure.
Describe proposed toxicity test requirement: This is a Major POTW, and a chronic WET limit at 90%
effluent will continue on a quarterly frequency at both outfalls.
Mercury Statewide TMDL Evaluation
There is a statewide TMDL for mercury approved by EPA in 2012. The TMDL target was to comply
with EPA's mercury fish tissue criteria (0.3 mg/kg) for human health protection. The TMDL established a
wasteload allocation for point sources of 37 kg/year (81 lb/year), and is applicable to municipals and
industrial facilities with known mercury discharges. Given the small contribution of mercury from point
sources (-2% of total load), the TMDL emphasizes mercury minimization plans (MMPs) for point source
control. Municipal facilities > 2 MGD and discharging quantifiable levels of mercury (>1 ng/1) will
receive an MMP requirement. Industrials are evaluated on a case -by -case basis, depending if mercury is a
pollutant of concern. Effluent limits may also be added if annual average effluent concentrations exceed
the WQBEL value (based on the NC WQS of 12 ng/1) and/or if any individual value exceeds a TBEL
value of 47 ng/1
Table 4. Mercury Effluent Data Summary
2019
2020
2021
2022
2023
# of Samples
8
13
13
13
9
Annual Average Conc. n /L
1.7
0.8
0.7
0.93
0.91
Maximum Conc., n /L
5.7
1.9
09
2.36
1.32
TBEL, n /L
47
WQBEL, n /L
13.3
Describe proposed permit actions based on mercury evaluation: Since no annual average mercury
concentration exceeded the WQBEL, and no individual mercury sample exceeded the TBEL, no mercury
limit is required. Since the facility is > 2.0 MGD and reported quantifiable levels of mercury (> 1 ng/1),
the mercury minimization plan (MMP) condition has been maintained. Charlotte Water submitted their
MMP with their 2022 Pretreatment Annual Report.
Page 7 of 16

Other TMDL/Nutrient Manaaement Strateav Considerations
If applicable, describe any other TNDDLs/Nutrient Management Strategies and their implementation
within this permit: A fecal coliform TMDL was established in February 2002 and the permit contains a
1000/100 mL fecal coliform daily maximum. On February 22, 2023, during the preparation of the
NC0024970 McAlpine Creek WWMF permit renewal, the Division contacted South Carolina's
Department of Health and Environmental Control (DHEC) regarding whether the daily maximum fecal
coliform requirements under the TMDL were sufficient in protecting the South Carolina E. coli standard,
as the discharge is above the SC/NC border. During their evaluation, SCDHEC considered the
NC0024970 McAlpine Creek WWMF, NC0024937 Sugar Creek WRRF and NC0024945 Irwin Creek
WRRF discharges. On April 5, 2023, SCDHEC informed the Division that based on the NC TMDL and
the actual effluent data, they do not object to the limits for the 3 NC facilities based on fecal coliform
bacteria as the indicator. As such, the fecal coliform limits have been maintained.
A bubble limit for total phosphorus is included for Irwin Creek WRRF, Sugar Creek WRRF, and
McAlpine Creek WWMF. As stipulated by the 2002 Settlement Agreement between Charlotte -
Mecklenburg Utilities (CMU), the South Carolina Department of Health and Environmental Control (SC
DHEC) and the North Carolina Division of Water Quality (NC-DWQ), now North Carolina Division of
Water Resources, Charlotte Water's McAlpine Creek WWMF, Sugar Creek WRRF and Irwin Creek
WRRF must comply with a combined 12 month rolling average limit of 826.0 lbs/day as of February 28,
2006.
Charlotte Water has asked the Division to revise the Sugar, Irwin, and McAlpine Creek permits to
improve the uniformity of their nutrient conditions. As outlined in the 2021 internal Memorandum
"Charlotte Water Permits — Proposed Uniform Nutrient Conditions" (attached), changes have been made
to the nutrient language and permit conditions for each of these permits to apply more consistent
terminology, units of measure, and parameter codes for the various measures of TP, apply consistent
methods for calculation of TN and TP loads and require reporting of interim calculation results, to make it
easier to see how the final results were derived.
Changes include:
Section A.(1.): Added Total Monthly Flow (TMF) reporting, created separate rows for TP
concentration and mass, applied new parameter names in the table and footnotes to improve
clarity, provided clearer linkage between the limits page, footnotes, and the other TP special
conditions.
Special Condition A.(7.): Applied the new parameter names and added linkage to the limits page
and calculations condition.
• Special Condition A.(8.): Applied the new terminology and described the calculations for each
measure of TP used on the limits page. Clarified how the combined TP loads would be calculated
and where they would be reported.
The changes will not affect the TN and TP limits or monitoring requirements for the facilities.
Other WQBEL Considerations
If applicable, describe any other parameters of concern evaluated for WQBELs: The bubble limit for total
phosphorus was analyzed for Irwin Creek WRRF, Sugar Creek WRRF, and McAlpine Creek WWMF.
There were no compliance concerns for the period analyzed (January 2018- August 2022) and the three
facilities stayed below their total phosphorus rolling average bubble limit.
Page 8 of 16

If applicable, describe any special actions (HQW or ORW) this receiving stream and classification shall
comply with in order to protect the designated waterbody: NA
If applicable, describe any compliance schedules proposed for this permit renewal in accordance with
I5A NCAC 2H 0107( c)(2)(B), 40CFR 122.47, and EPA May 2007 Memo: NA
If applicable, describe any water quality standards variances proposed in accordance with NCGS 143-
215.3(e) and I5A NCAC 2B. 0226 for this permit renewal: NA
7. Technology -Based Effluent Limitations (TBELs)
Municipals (if not applicable, delete and skip to Industrials)
Are concentration limits in the permit at least as stringent as secondary treatment requirements (30 mg/1
CBODS/TSS for Monthly Average, and 45 mg/l for CBODS/TSS for Weekly Average). YES
If NO, provide a justification for alternative limitations (e.g., waste stabilization pond). NA
Are 85% removal requirements for CBODS/TSS included in the permit? YES
If NO, provide a justification (e.g., waste stabilization pond). NA
8. Antidegradation Review (New/Expanding Discharge)
The objective of an antidegradation review is to ensure that a new or increased pollutant loading will not
degrade water quality. Permitting actions for new or expanding discharges require an antidegradation
review in accordance with 15A NCAC 2B.0201. Each applicant for a new/expanding NPDES permit
must document an effort to consider non -discharge alternatives per 15A NCAC 2H.0105( c)(2). In all
cases, existing instream water uses and the level of water quality necessary to protect the existing use is
maintained and protected.
If applicable, describe the results of the antidegradation review, including the Engineering Alternatives
Analysis (EAA) and any water quality modeling results: NA
9. Antibacksliding Review:
Sections 402(o)(2) and 303(d)(4) of the CWA and federal regulations at 40 CFR 122.44(1) prohibit
backsliding of effluent limitations in NPDES permits. These provisions require effluent limitations in a
reissued permit to be as stringent as those in the previous permit, with some exceptions where limitations
may be relaxed (e.g., based on new information, increases in production may warrant less stringent TBEL
limits, or WQBELs may be less stringent based on updated RPA or dilution).
Are any effluent limitations less stringent than previous permit (YESINO): NO; however, based on the
reasonable potential analysis (RPA) showing no reasonable potential to violate state water quality
standards, the monitoring requirements for total silver, total copper and total nickel have been removed
from the permit.
If YES, confirm that antibacksliding provisions are not violated: NA
10. Monitoring Requirements
Monitoring frequencies for NPDES permitting are established in accordance with the following
regulations and guidance: 1) State Regulation for Surface Water Monitoring, 15A NCAC 2B.0500; 2)
NPDES Guidance, Monitoring Frequency for Toxic Substances (7/15/2010 Memo); 3) NPDES Guidance,
Reduced Monitoring Frequencies for Facilities with Superior Compliance (10/22/2012 Memo); 4) Best
Professional Judgement (BPJ). Per US EPA (Interim Guidance, 1996), monitoring requirements are not
considered effluent limitations under Section 402(o) of the Clean Water Act, and therefore anti -
backsliding prohibitions would not be triggered by reductions in monitoring frequencies.
Page 9 of 16

For instream monitoring, refer to Section 4.
Charlotte Water was granted 2/week monitoring for CBOD, ammonia, TSS and fecal coliform based on
2012 DWR Guidance Regarding the Reduction of Monitoring Frequencies in NPDES Permits for
Exceptionally Performing Facilities during their 2017 renewal. Charlotte Water has requested
continuation of this monitoring frequency reduction as part of their renewal application. The last three
years of the facility's data for these parameters have been reviewed in accordance with the criteria
outlined in the guidance. Based on this review, 2/week monitoring frequency has been maintained for
CBOD, ammonia, TSS and fecal coliform.
To identify PFAS concentrations in waters classified as Water Supply (WS) waters, monitoring
requirements are to be implemented in permits with pretreatment programs that discharge to WS waters.
While there are no WS waters designated by the Division downstream of the discharge, the discharge
point is upstream of the border between North Carolina and South Carolina. Since all waters in South
Carolina are deemed suitable for drinking water uses with appropriate treatment, and to ensure PFAS
contamination does not cross State lines, and as the Sugar Creek WRRF has a pretreatment program,
monitoring of PFAS chemicals has been added to the permit. Currently, EPA Method 1633 is in its 4th
draft form and not yet published in the Federal Register as a final methodology. As the Sugar Creek
WRRF accepts influent wastewater from several industrial facilities that are potential sources of PFAS via
the approved pretreatment program, and since an EPA method for sampling and analyzing PFAS in
wastewater is not currently available, influent and post -filtration PFAS monitoring has been added to the
permit at a quarterly frequency using the Draft Method 1633. Upon evaluation of laboratory availability
and capability to perform the draft analytical method, it was determined that the sampling may be
conducted using the 31d draft method 1633 or more recent. Sampling using the draft method shall take
effect the first full calendar quarter following 6 months after the effective date of the permit to provide
Charlotte Water time to select a laboratory, develop a contract, and begin collecting samples. Effective 6
months after EPA has a final wastewater method in 40 CFR136 published in the Federal Register,
Charlotte Water shall conduct effluent monitoring using the Final Method 1633 and is no longer required
to conduct influent and post -filtration monitoring.
In addition to monitoring at the wastewater management facility, Charlotte Water shall identify and
monitor SIUs suspected of discharging PFAS compounds within 6 months of the permit effective date.
Charlotte Water shall update their Industrial Waste Survey- (IWS) to identify indirect dischargers of
PFAS contributing to concentrations experienced at the Sugar Creek WRRF. A summary of information
learned during this process will be provided as part of the 2024 Pretreatment Annual Report (PAR).
Within 6 months of completion of the IWS, Charlotte Water shall begin sampling of indirect dischargers
identified as potential PFAS sources. Sampling conducted at SIUs and indirect dischargers shall also be
conducted at a quarterly frequency. This is a summary of the PFAS requirements. For a detailed outline of
the specific PFAS requirements, see Special Condition A.(8.) PFAS Monitoring Requirements.
As the Sugar Creek WRRF accepts influent wastewater from several industrial facilities that are potential
sources of 1,4-dioxane via the approved pretreatment program, and as no additional sampling has been
conducted for 1,4-dioxane at this facility as identified in the chemical addendum submitted by Charlotte
Water, monthly effluent monitoring for 1,4-dioxane as well as a 1,4-dioxane reopener condition have
been added to the permit. After a 24-month sampling period, the Permittee may request the Division
conduct a review of submitted data for assessment and approval of a 1,4-dioxane monitoring frequency
reduction from monthly to quarterly.
The statement, "There shall be no discharge of floating solids or visible foam in other than trace
amounts," was removed during the 2017 renewal. This statement has been standard language in NPDES
permits since the program's inception and is still used widely by state and federal permitting authorities.
Page 10 of 16

Because it is subjective, it is hardly suitable as the basis for an enforcement action; instead, we would rely
on the permittee's monitoring reports to establish and quantify any limits exceedances. Part of its value is
that it provides a measure of effluent quality and possible water quality impacts. A DWR inspector who
notices such an issue at a discharge can address the matter while on site rather than waiting days or weeks
for effluent monitoring to be reported. As such, the statement has been added back into the permit in
Section A.(1.).
11. Electronic Reporting Requirements
The US EPA NPDES Electronic Reporting Rule was finalized on December 21, 2015. Effective
December 21, 2016, NPDES regulated facilities are required to submit Discharge Monitoring Reports
(DMRs) electronically. While NPDES regulated facilities would initially be required to submit additional
NPDES reports electronically effective December 21, 2020, EPA extended this deadline from December
21, 2020, to December 21, 2025. The current compliance date, effective January 4, 2021, was extended as
a final regulation change published in the November 2, 2020 Federal Register. This permit contains the
requirements for electronic reporting, consistent with Federal requirements.
12.Summary of Proposed Permitting Actions:
Table 5. Current Permit Conditions and Proposed Changes Outfall 001
Parameter
Current Permit
Proposed Change
Basis for Condition/Change
Flow
MA 20.0 MGD
No change
15A NCAC 2B .0505
Total Monthly
No requirement
Monitor and
For calculation of TP loadings
Flow
Report Monthly
CBOD5
Summer:
No change
WQBEL. 1991 agreement with Charlotte
MA 5.0 mg/1
Water to upgrade Sugar Creek WRRF, Irwin
WA 7.5 mg/1
Creek WRRF, and McAlpine Creek
Winter:
WWMF, Surface Water Monitoring, 2012
MA 10.0 mg/1
DWR Guidance Regarding the Reduction of
WA 15.0 mg/1
Monitoring Frequencies in NPDES Permits
Monitor and report
for Exceptionally Performing Facilities
2/Week
NH3-N
Summer:
No change
WQBEL. 2023 WLA review; Surface Water
MA 1.0 mg/1
Monitoring, 2012 DWR Guidance
WA 3.0 mg/1
Regarding the Reduction of Monitoring
Winter:
Frequencies in NPDES Permits for
MA 2.0 mg/1
Exceptionally Performing Facilities
WA 6.0 mg/1
Monitor and report
2/Week
TSS
MA 30.0 mg/1
No change
TBEL. Secondary treatment standards/40
WA 45.0 mg/1
CFR 133 / 15A NCAC 2B .0406; Surface
Monitor and report
Water Monitoring, 2012 DWR Guidance
2/Week
Regarding the Reduction of Monitoring
Frequencies in NPDES Permits for
Exceptionally Performing Facilities
Fecal coliform
MA 200 /100ml
No change
WQBEL. State WQ standard, 15A NCAC
WA 400 /100ml
2B .0200; 2002 TMDL for fecal, results in
DM 1000/100ml
DM; Surface Water Monitoring, 2012 DWR
Monitor and report
Guidance Regarding the Reduction of
2/Week
Monitoring Frequencies in NPDES Permits
for Exceptionally Performing Facilities
Page 11 of 16

DO
> 6 mg/1
No change
WQBEL. 1995 Level B model; Surface
Monitor and report
Water Monitoring, 15A NCAC 2B. 0500
Daily
pH
6 — 9 SU
No change
WQBEL. State WQ standard, 15A NCAC
Monitor and report
2B .0200; Surface Water Monitoring, 15A
Daily
NCAC 2B. 0500
Conductivity
Monitor and report
No change
Surface Water Monitoring, 15A NCAC 2B.
Daily
0500
Temperature
Monitor and report
No change
Surface Water Monitoring, 15A NCAC 2B.
Daily
0500
Total Residual
No requirement
DM 19 ug/L
WQBEL. 2023 WLA review and Surface
Chlorine
Monitor and
Water Monitoring, 15A NCAC 2B. 0500
report Daily
Total Nitrogen
Monitor and report
No change
Surface Water Monitoring, 15A NCAC 2B.
Monthly
0500
TKN
No requirement
Monitor and
For calculation of Total Nitrogen
report Monthly
NO3+NO2
No requirement
Monitor and
For calculation of Total Nitrogen
report Monthly
Total
826.0 lbs/day bubble
No change; Add
WQBEL. Required TP nutrient limits per
Phosphorus
limit for Irwin Creek
separate row for
2002 permitting strategy agreement with
WRRF (NC0024945),
lb/mo and lb/yr
Charlotte -Mecklenburg Utilities (CMU), the
Sugar Creek WRRF
reporting
South Carolina Department of Health and
(NC0024937), and
Environmental Control (SC DHEC) and the
McAlpine Creek
North Carolina Division of Water Quality
WWMF (NC0024970)
(NC-DWQ); Surface Water Monitoring,
Monitor and report
15A NCAC 2B. 0500
Monthly
Total Hardness
Quarterly monitoring
No change
Hardness -dependent dissolved metals water
Upstream (managed in
quality standards approved in 2016
NC0024970 McAlpine
Creek WWMF permit)
and in Effluent
Total Silver
Monitor and report
Remove
Based on results of RPA; All values non -
Quarterly
requirement
detect < 1 ug/L - no monitoring required
Total Copper
Monitor and report
Remove
Based on results of RPA; No RP, Predicted
Quarterly
requirement
Max < 50% of Allowable Cw - No
Monitoring required
Total Nickel
Monitor and report
Remove
Based on results of RPA; No RP, Predicted
Quarterly
requirement
Max < 50% of Allowable Cw - No
Monitoring required
Monitor and
Report Monthly
1,4-dioxane
No requirement
and reopener
Based on PT Program — industrial facilities
condition; 24-
linked to 1,4-dioxane
month sampling
reassessment
Page 12 of 16

Add Special
Evaluation of PFAS contribution:
PFAS
No requirement
Condition A.(8.)
PFAS Monitoring
pretreatment facility; Discharge above
Requirements
NC/SC border
Toxicity Test
Chronic limit, 90%
No change
WQBEL. No toxics in toxic amounts. 15A
effluent
NCAC 213.0200 and 15A NCAC 213.0500
Effluent
Three times per permit
No change;
40 CFR 122
Pollutant Scan
cycle
conducted in
2025, 2026, 2027
Mercury
MMP Special Condition
No change; revise
WQBEL. Consistent with 2012 Statewide
Minimization
wording towards
Mercury TMDL Implementation.
Plan (MMP)
its maintenance
Electronic
Electronic Reporting
No change
In accordance with EPA Electronic
Reporting
Special Condition
Reporting Rule 2015.
MGD — Million gallons per day, MA - Monthly Average, WA — Weekly Average, DM — Daily Max
Table 6. Current Permit Conditions and Proposed Changes Outfall 002
Parameter
Current Permit
Proposed Change
Basis for Condition/Change
Flow
MA 8.0 MGD upon receipt
No change
15A NCAC 213 .0505
of engineer's certification
for expansion
Total Monthly
No requirement
Monitor and
For calculation of TN and TP loadings
Flow
Report Monthly
CBOD5
Summer:
No change to
WQBEL. 1991 agreement with
MA 5.0 mg/1
limits; Monitor
Charlotte Water to upgrade Sugar Creek
WA 7.5 mg/1
and report daily
WRRF, Irwin Creek WRRF, and
Winter:
with option for
McAlpine Creek WWMF, Surface
MA 10.0 mg/1
reduction to
Water Monitoring, 2012 DWR
WA 15.0 mg/1
2/week after 6
Guidance Regarding the Reduction of
Monitor and report 2/Week
months of daily
Monitoring Frequencies in NPDES
sampling and no
Permits for Exceptionally Performing
limit violations
Facilities
NH3-N
Summer:
No change to
WQBEL. 2023 WLA review; Surface
MA 1.0 mg/1
limits; Monitor
Water Monitoring, 2012 DWR
WA 3.0 mg/1
and report daily
Guidance Regarding the Reduction of
Winter:
with option for
Monitoring Frequencies in NPDES
MA 2.0 mg/1
reduction to
Permits for Exceptionally Performing
WA 6.0 mg/1
2/week after 6
Facilities
Monitor and report 2/Week
months of daily
sampling and no
limit violations
TSS
MA 30.0 mg/1
No change to
WQBEL. 1995 Level B model, Surface
WA 45.0 mg/1
limits; Monitor
Water Monitoring, 2012 DWR
Monitor and report 2/Week
and report daily
Guidance Regarding the Reduction of
with option for
Monitoring Frequencies in NPDES
reduction to
Page 13 of 16

2/week after 6
Permits for Exceptionally Performing
months of daily
Facilities
sampling and no
limit violations
Fecal coliform
MA 200 /100ml
No change to
WQBEL. State WQ standard, 15A
WA 400 /100ml
limits; Monitor
NCAC 2B .0200; 2002 TMDL for fecal,
DM 1000/100ml
and report daily
results in DM; Surface Water
Monitor and report 2/Week
with option for
Monitoring, 2012 DWR Guidance
reduction to
Regarding the Reduction of Monitoring
2/week after 6
Frequencies in NPDES Permits for
months of daily
Exceptionally Performing Facilities
sampling and no
limit violations
DO
> 6 mg/1
No change
WQBEL. 1995 Level B model; Surface
Monitor and report Daily
Water Monitoring, 15A NCAC 2B.
0500
pH
6 — 9 SU
No change
WQBEL. State WQ standard, 15A
Monitor and report Daily
NCAC 2B .0200; Surface Water
Monitoring, 15A NCAC 2B. 0500
Conductivity
Monitor and report Daily
No change
Surface Water Monitoring, 15A NCAC
2B. 0500
Temperature
Monitor and report Daily
No change
Surface Water Monitoring, 15A NCAC
2B. 0500
Total Residual
No requirement
DM 19 ug/L
WQBEL. 2022 WLA review and
Chlorine
Monitor and
Surface Water Monitoring, 15A NCAC
report Daily
2B. 0500
Total Nitrogen
Monitor and report Monthly
No change
Surface Water Monitoring, 15A NCAC
2B. 0500
TKN
No requirement
Monitor and
For calculation of Total Nitrogen
report Monthly
NO3+NO2
No requirement
Monitor and
For calculation of Total Nitrogen
report Monthly
Total
826.0 lbs/day bubble limit
No change; Add
WQBEL. Required TP nutrient limits
Phosphorus
for Irwin Creek WRRF,
separate row for
per 2002 permitting strategy agreement
Sugar Creek WRRF, and
lb/mo and lb/yr
with Charlotte -Mecklenburg Utilities
McAlpine Creek WWMF
reporting
(CMU), the South Carolina Department
Monitor and report Monthly
of Health and Environmental Control
(SC DHEC) and the North Carolina
Division of Water Quality (NC-DWQ);
Surface Water Monitoring, 15A NCAC
2B. 0500
Total Hardness
Quarterly monitoring
No change
Hardness -dependent dissolved metals
Upstream (managed in
water quality standards approved in
NC0024970 McAlpine
2016
Creek WWMF permit) and
in Effluent
Page 14 of 16

Total Silver
Monitor and report Quarterly
Remove
Based on results of RPA; All values
requirement
non -detect < 1 ug/L - no monitoring
required
Total Copper
Monitor and report Quarterly
Remove
Based on results of RPA; No RP,
requirement
Predicted Max < 50% of Allowable Cw
- No Monitoring required
Total Nickel
Monitor and report Monthly
Remove
Based on results of RPA; No RP,
requirement
Predicted Max < 50% of Allowable Cw
- No Monitoring required
Monitor and
Report Monthly
1,4-dioxane
No requirement
and reopener
Based on PT Program — industrial
condition; 24-
facilities linked to 1,4-dioxane
month sampling
reassessment
Add Special
Evaluation of PFAS contribution:
PFAS
No requirement
Condition A.(8.)
PFAS Monitoring
pretreatment facility; Discharge above
Requirements
NC/SC border
Toxicity Test
Chronic limit, 90% effluent
No change
WQBEL. No toxics in toxic amounts.
15A NCAC 213.0200 and 15A NCAC
213.0500
Effluent
Three times per permit cycle
No change;
40 CFR 122
Pollutant Scan
conducted in
2025, 2026, 2027
Mercury
MMP Special Condition
No change; revise
WQBEL. Consistent with 2012
Minimization
wording towards
Statewide Mercury TMDL
Plan (MMP)
its maintenance
Implementation.
Electronic
Electronic Reporting Special
No change
In accordance with EPA Electronic
Reporting
Condition
I Reporting Rule 2015.
MGD — Million gallons per day, MA - Monthly Average, WA — Weekly Average, DM — Daily Max
13. Public Notice Schedule:
Permit to Public Notice: 12/6/2023
Per 15A NCAC 2H .0109 & .0111, The Division will receive comments for a period of 30 days following
the publication date of the public notice. Any request for a public hearing shall be submitted to the
Director within the 30 days comment period indicating the interest of the parry filing such request and the
reasons why a hearing is warranted.
14. NPDES Division Contact
If you have any questions regarding any of the above information or on the attached permit, please
contact Nick Coco at [phone] or via email at [e-mail].
15. Fact Sheet Addendum (if applicable)
The draft was submitted to the Charlotte Water, EPA Region IV, and the Division's Mooresville Regional
Office, Aquatic Toxicology Branch, Operator Certification Program, Pretreatment Coordinator and South
Carolina DHEC for review. Comments were received from the Catawba Riverkeeper on January 10,
2024. The comments and Division responses are provided in the attached addendum to the fact sheet.
Page 15 of 16

Comment were received by Charlotte Water on January 5, 2024. In their comments, Charlotte Water
requested:
• Change the facility's name from Sugar Creek Wastewater Treatment Plant (WWTP) to Sugar
Creek Water Resource Recovery Facility (WRRF) in accordance with the provided name change
form (attached).
o Response: The name change has been made throughout the permit documents.
• Correct a typo in the facility component list that misspells "phosphorus" as "phosphorous."
o Response: The typo has been corrected.
• Correct a typo in the facility component list that states "RAS" instead of "RAW" pump station.
o Response: The typo has been corrected.
• Add "If not previously submitted to NCDWR" to Special Condition A.(7.)(c)(110 regarding the
results of the 2nd species testing, since the EPA Municipal Application Form 2A does not require
the submittal of toxicity testing results if they were previously submitted to the permitting
authority.
o Response: Submittal of the 2nd species testing results with the application helps the
permitting staff better track when these tests are completed and ensure that the testing
requirements are complied with. This is not necessary for the quarterly testing with the
primary species, but is useful for the additional species tests. As such, the language has
not been changed at this time.
• Correct the Special Condition A.(8.) dates to accurately reflect the 6-month effective date.
o Response: The dates have been corrected.
Were there any changes made since the Draft Permit was public noticed (Yes/No): YES
If Yes, list changes and their basis below:
• The facility's name has changed in accordance with the name change request submitted by the
Permittee on January 8, 2024.
16. Fact Sheet Attachments (if applicable):
• RPA Spreadsheet Summary
• NPDES Implementation of Instream Dissolved Metals Standards — Freshwater Standards
• NH3/TRC WLA Calculations
• BOD & TSS Removal Rate Calculations
• Mercury TMDL Calculations
• WET Testing and Self -Monitoring Summary
• Compliance Inspection Report
• 2003 TRC Policy
• 2021 Internal Memo Charlotte Water Permits — Proposed Uniform Nutrient Conditions
• Requested Additional Information
• Name Change Form
• Email Correspondence related to Outfall 002
• SCDHEC Correspondence
• Charlotte Water comments
• Catawba Riverkeeper comments and Division responses
Page 16 of 16

McClatchy
The Beaufort Gazette
The Belleville News -Democrat
Bellingham Herald
Centre Dailv Times
Sum Herald
Idaho Statesman
Bradenton Herald
The Charlotte Observer
The State
Ledger -Enquirer
Durham I The Herald -Sun
Fort Worth Star -Telegram
The Fresno Bee
The Island Packet
The Kansas City Star
Lexington Herald -Leader
The Telegraph - Macon
Merced Sun -Star
Miami Herald
El Nuevo Herald
AFFIDAVIT OF PUBLICATION
The Modesto Bee
The Stuff News - Mvrtle Beach
Raleigh News & Observer
Rock Hill I The Herald
The Sacramento Bee
San Luis Obispo Tribune
Tacoma I The News Tribune
Tri-City Herald
The Wichita Eagle
The Olympian
Account #
Order Number
Identification
Order PO
Amount
Cols
Depth
19489
496942 i_
Print Legal Ad-IPL01506860 - IPLO150686
$621.44
2
25 L
Attention: Demery Cynthia
DEPARTMENT OF WATER RESOURCES - RALEIGH
1617 MAIL SERVICE CENTER
RALEIGH, NC 276991617
[e-mail]
Public Notice
North Carolina Environmental
Management Commission/NPDES Unit
1617 Mail Service Center
Raleigh, NC 27699-1617
Notice of Intent to Issue a NPDES Wastewater Permit NCO024937 Sugar Creek
WWTP The North Carolina Environmental Management Commission proposes
to issue a NPDES wastewater discharge permit to the person(s) listed below.
Written comments regarding the proposed permit will be accepted until 30 days
after the publish date of this notice. The Director of the NC Division of Water Re-
sources (DWR) may hold a public hearing should there be a significant degree of
public interest. Please mail comments and/or information requests to DWR at the
above address. Interested persons may visit the DWR at 512 N. Salisbury Street,
Raleigh, NC 27604 to review the information on file. Additional information on
NPDES permits and this notice may be found on our website: https://deq.nc.gov/
pub lic-notices-hearings,or by calling [phone]. Charlotte Water [5100
Brookshire Blvd., Charlotte, NC 28216] has requested renewal of NPDES permit
NCO024937 for its Sugar Creek Wastewater Treatment Plant, located in Mecklen-
burg County. This permitted facility discharges treated municipal and industrial
wastewater to Little Sugar Creek, a class C water in the Catawba River Basin.
Currently CBOD, ammonia, fecal coliform, dissolved oxygen, pH, total residual
chlorine, and total phosphorous loading are water quality limited. This discharge
may affect future allocations in this segment of Little Sugar Creek.
IPLO150686
Dec 6 2023
North Carolina } SS
Mecklenburg County }
Before the undersigned, a Notary Public of said
County and State, duly authorized to administer
oaths affirmations, etc., personally appeared,
being duly sworn or affirmed according to law,
cloth depose and say that he/she is a
representative of The Charlotte Observer
Publishing Company, a corporation organized and
doing business under the laws of the State of
Delaware, and publishing a newspaper known as
The Charlotte Observer in the city of Charlotte,
County of Mecklenburg, and State of North
Carolina and that as such he/she is familiar with
the books, records, files, and business of said
Corporation and by reference to the files of said
publication, the attached advertisement was
inserted. The following is correctly copied from
the books and files of the aforesaid Corporation
and Publication.
1 insertion(s) published on:
12/06/23
In Testimony Whereof I have hereunto set my hand
and affixed my seal on the 22nd day of December,2023
Notary Public in and for the state of Texas, residing in
Dallas County
=,
�'`' "'• x:* ;"•- S_TE=1HiATCG_HER
My NiEor
•, f wf
Extra charge for lost or duplicate affidavits.
Legal document please do not destroy!

Coco, Nick A
From: Sypolt, Shannon <[e-mail]>
Sent: Friday, January 5, 2024 5:00 PM
To: Coco, Nick A
Cc: Lockler, Joseph; Montebello, Michael J
Subject: [External] Sugar Creek WRRF (NC0024937) NPDES Permit - Charlotte Water Formal Comments
Follow Up Flag: Flag for follow up
Flag Status: Flagged
CAUTION: External email. Do not click links or open attachments unless verified. Report suspicious emails with the Report Message
buutton
located on your Outlook menu bar on the Home tab.
Good afternoon Nick,
Please let this email serve as CLTWater's formal comments for the Sugar Creek WRRF final permit
(NC0024937). CLTWater is providing the following five comments for your consideration:
1. Charlotte Water is in the process of changing all Wastewater Treatment Plant (WWTP) facility names to
Water Resource Recovery Facilities (WRRF's). CLTWater is requesting that the name of Sugar Creek
Wastewater Treatment Plant (WWTP) be changed to "Sugar Creek Water Resource Recovery Facility"
(WRRF) in the issuance of Sugar's fact sheet and final permit. Since our conversation yesterday, I have
located the facility name change form on NCDWR's website and am working on completing this form
with the required signature. I will send you the completed form in a separate email early next week.
In the equipment list on Page 2 of 17, "Biological and Chemical Phosphorous Removal" should be only
"Chemical Phosphorus Removal" since the enhanced biological phosphorus removal (EBPR) that
occurs is just a bonus of the MLE process to remove nitrogen and is not by design.
In the equipment list on Page 2 of 17, "RAS" needs to be changed to "RAW" since the WAS and RAS are
the same pump station and the RAW pump station is a separate pump station at Sugar Creek that is
critical to this facility's operation. The RAW pump station pumps primary solids from Sugar Creek to
McAlpine Creek for digestion, dewatering, and further processing.
4. In Section A.(7.)(c)(iii) CLTWater requests that NCDWR adds "if not previously submitted to NCDWR,
results of the 2nd species tests shall ............" since the EPA Municipal Application Form 2A questions
(3.20 and 3.26) do not require the inclusion/resubmission of this information in Table E. as a part of
the permit application if this information was previously submitted to the NPDES permitting
authority. See application section questions and answers below:

EPA Ident ficalion Number
NPIDES Permit Number
Facility Name
Form Approved 4af05118
110009715995
NCO036277
McDowell Creek 4VWTP
OMB No. 2040-ODN
3.19
Has the POTW conducted either (1) minimum of fo u r q ua rte-Hy WET tests for one year preceding this permit application
ar (2) at least four annual WET tests in the past 4.5 years?
0. Yes ❑ No 4 Complete tests and Table E and SKIP to
Item 3115
3.21D
Have you previ ously su bmitted the results of the above tests to your NPDES permitting authority?
0 Yes No 4 Provide results in Table E and SKIP to
Item :i.1b.
3.21
Indicate the dates the data were submitted to your NPIDES permitting authority and provide a summary of the results.
Date(s)Submitted
lr�rut+D�vmrrt
Summary of Results
�+
All WET tests passed during this permitting cycle. WET tests were
completed on these dates: 01/15120, 04/15/20, 07103/20, 09/30/20,
01/06/21, 04/14121, 07114/21, 10/06/21, 01/12/22, 04/13/22, 07/13/22,
10/05/22,01/13/23,04119/23,07/19/23, 10/04/23
0
3.22
Regardless of how you provided your WET testing data to the NPIDES permitting authority, did any of the tests result in
toxialty?
:r
❑ Yes D No 4 SKIP to Item 3.26.
3.23
Describe the causes) of the toxicity:
.r
m
w
3.24
Has the treatmentworks conducted atoxicity reduction evaluation?
❑ Yes ❑ No i SKIP to Item 3.26.
3.25
Provide details of any toxicity reduction evaluations conducted.
3.26
Have you completed Table E for all applicable outfails and attached the results to the application package?
Yes 0 Not applicable because previously submitted
Intormation to the W-ULS permwing autnorrry.
5. Assuming a permit effective date of March 1, 2024, in section A.8(b), the date for influent and post -
filtration monitoring should be changed from August 1, 2024 to October 1, 2024. That would be the
first full quarter 6 months after the effective date of March 1, 2024. The date should also be changed in
A.8(c)(ii) from August 1, 2024 to October 1, 2024.
Please let us know if you have any questions or if you need any further information concerning our
comments. Thank you for your assistance with this permit renewal.
Respectfully,
Shannon Sypolt
Water Quality Program Administrator
Environmental Management

ROY COOPER
cown,,,,
"A MICHAEL S. REGAN
A-C
LINDA CULPEPPER
I'vWer 1,1F' ollrc ,S Ll�rrim hin•rror
CNVIRONFIEN TAL QUMI..ITY
• • 1,.III IQ
.1
Permit Number: NCO024937
1. Facility Name: Sugar Creek Wastewater Treatment Plant (WWTP)
II. NEW OWNER/NAME INFORMATION:
1. This request for a name change is a result of:
a. Change in ownership of property/company
_X_b. Name change only - Rebranding to change facility name from "Sugar Creek Wastewater
Treatment Plant" (WWTP) to "Sugar Creek Water Resource Recovery Facility" (WRRF).
c. Other (please explain):
2. New facility name (name to be put on permit):
Sugar Creek Water Resource Recovery Facility (WRRF)
3. New owner's or signing official's name and title: Steven Joseph Lockler - Operations Chief
4. Mailing address: 5100 Brookshire BLVD City: Charlotte
State: NC Zip Code: 28216 Phone: [phone]
E-mail address: Joseph.Lockle1( charlottenc.gov
THIS APPLICATION PACKAGE WILL NOT BE ACCEPTED BY THE DIVISION UNLESS ALL OF THE
APPLICABLE ITEMS LISTED BELOW ARE INCLUDED WITH THE SUBMITTAL.
REQUIRED ITEMS:
1. This completed application form
2. Legal documentation of the transfer of ownership (such as a property deed, articles of
incorporation, or sales agreement)
[see reverse side of this page for signature requirements]
State of North Carolina I Environmental Quality I Water Resources
1617 Mail Service Center I Raleigh, NC 27699-1617
919 807 6300 919-807-6389 FAX
littps:Hdeq. nc.gov/about/cl ivi sions/water-resources/water-resources-perm its/Nvastewater-branch/npdes-NvasteNvater-permits

NPDES Name & Ownership Change
Page 2 of 2
I, Steven Joseph Lockler , attest that this application for a name/ownership change
has been reviewed and is accurate and complete to the best of my knowledge. I understand
that if all required parts of this application are not completed and that if all required supporting
information and attachments are not included, this application package will be returned as
incomplete.
Signature: 2-- Date: 01.08.24
THE COMPLETED APPLICATION PACKAGE, INCLUDING ALL SUPPORTING
INFORMATION & MATERIALS, SHOULD BE SENT TO THE FOLLOWING ADDDRESS:
NC DNPDES
1617 Mail Service Center
-,aleigh, North Carolina 6•.,
-1614
Version 1112017

CATAWBA
RIVERKEEPER®
January loth, 2024
NCDEQ-DWR
Water Quality Permitting Section
1617 Mail Service Center
Raleigh, NC 27699-1617
Dear Water Quality Permitting Section,
The Catawba Riverkeeper Foundation is a member -funded environmental nonprofit that educates,
advocates, and protects the Catawba-Wateree River and all its tributaries. Our organization
represents over 7,000 active members who rely on the watershed for drinking water, recreation, and
electricity. Little Sugar Creek is a class C urban tributary to the Catawba and currently not meeting
water quality criteria for benthos, fish community, fecal coliform, and turbidity. The discharge is
located on a popular section of greenway which parallels the stream for several miles downstream.
We appreciate the opportunity to comment on the Sugar Creek WWTP NPDES permit (NC0024937)
and strongly support the additions of PFAS monitoring and floating solids/visible foam in the draft.
Additionally, we make the following recommendations:
• Monitor and limit turbidity
The receiving stream section is currently exceeding criteria for turbidity, (2022
Integrated Report classification 4i). While there is a 2005 TMDL for turbidity in place
limiting total suspended solids (IR 4t), that document does not actually apply to Little
Sugar Creek. "As shown in Table 3, assessment of 1997-2004 turbidity data indicate less
than 10% exceedance at six of the seven ambient stations and thus attainment of water
quality standards at those locations. Based on the infrequent nature of the turbidity
violations, the development of a TMDL in McAlpine Creek, Sugar Creek, Little Sugar
Creek, Irwin Creek, Henry Fork, and Mud Creek is an inappropriate management
response."
The discharge should be monitored and limited to ensure it does not contribute to
turbidity exceedances per 15A N.C. Admin. Code 213.0404 (explaining water quality -based
limits should be imposed when a discharge has "a reasonable potential to cause or
contribute to exceedance of applicable water quality standards."
• Increase monitoring frequency and reduce daily maximum fecal coliform to
400col/100mL
Although Little Sugar is a class C water, the new greenway has exponentially increased
its visibility and public exposure. Despite warning signs at many of the most appealing
locations, users and their dogs frequently recreate in the water. This trend will continue
as the greenway is expanded. Local municipalities and nonprofits are planning to
establish a Sugar Creek Blueway downstream. As effluent can make up 90% of the
creeks volume, and to reflect the new use, monitoring frequency should be daily, with a
maximum of 400col/100mL.
A WATERKEEPER ALLIANCE° Member
115 Willow Drive McAdenville NC 28211
Phone: [phone] Fax: [phone]
www.catawbariverkeeper.org

• Monitor discharge E. coli in addition to fecal coliform
For the last 38 years, the EPA has recommended using E. coli instead of fecal coliform
as an indicator of pathogens. The information would provide downstream users with a
better indicator of risk and water quality.
• Establish limits PFAS and 1,4 Dioxane to meet drinking water standards
While we commend the department for the new monitoring requirements, downstream
intakes and subsistence anglers need more than information. We recommend
establishing limits based off the latest EPA drinking water standards and risk
determinations.
• Establish limits for Total Nitrogen
More than 30 sites downstream and across the state line are impaired from excess
nutrients. Since 2014 residents of Lake Wateree have seen rapidly expanding
cyanobacteria (Microseira wollie) impact their lake. Recent reports from NCDEQ (Catawba
River Basin Nutrient Study, 2018), and NC Cooperative Extension (attached, 2023) point to
Sugar Creek and specifically Charlotte's WWTPs as being outsized contributors.
Additionally, phytoplankton analysis from the University of South Carolina (attached, 2019)
shows that nitrogen is likely the limiting nutrient in these systems.
While this will undoubtedly be addressed in the upcoming Lower Catawba Nutrient TMDL
we recommend that North Carolina begin requiring facilities in the watershed to start
reducing their total nitrogen export immediately. The plan has been in development since
at least 2001. Finalization, possible litigation, and implementation will take years to
implement. In the meantime, downstream residents are dealing with harmful algal blooms
of increasing frequency, duration and magnitude.
For the River,
Brandon Jones
Catawba Riverkeeper
A WATERKEEPER ALLIANCE° Member
115 Willow Drive McAdenville NC 28211
Phone: [phone] Fax: [phone]
www.catawbariverkeeper.org

Sugar Creek WRRF Fact Sheet Addendum NC0024937
Comments to the draft permit NC0024937, which was public noticed for 30-day comment period on
12/6/2023, were provided by the Catawba River Keeper on 1/10/2024 with several requests. Individual
comments by the Catawba River Keeper and Division responses are provided below.
1. Turbidity
a. The discharge should be monitored and limited to ensure it does not contribute to
turbidity exceedances in the receiving stream.
Response: Elevated turbidity levels are more commonly observed in the receiving stream
during rainfall events, which is common for urban environments. This is noted in the final
report of Characterizing Water Quality Status, Trends and Potential Watershed
Management Opportunities from National Pollutant Discharge Elimination System
(NPDES) Stormwater Data submitted as part of your comments. Stormwater and other
non -point sources of turbidity are likely the cause of elevated turbidity during rainfall
events.
Due to review of the discharge monitoring reports demonstrating low discharges of TSS
from this facility, turbidity requirements have not been added to the permit at this time.
2. Fecal Coliform
a. Fecal coliform monitoring should be increased and the daily maximum should be reduced
to 400/100mL.
Response: Fecal coliform monitoring in the effluent is consistent with the 2012 DWR
Guidance Regarding the Reduction of Monitoring Frequencies in NPDES Permits for
Exceptionally Performing Facilities. Review for approval of a 2/week monitoring
frequency demonstrated that the 3-year geometric mean was less than 50% of the
monthly average permit limit, no more than 20 sampling results were over 200% of the
weekly average limit during the previous 3 years of sampling and no more than two non -
monthly average limit violations occurred during the previous year. As the facility has
achieved compliance with these criteria, reduced monitoring is allowable. While the
permittee has requested maintenance of the reduced monitoring as a permit
requirement, Charlotte Water conducts daily monitoring for fecal coliform and reports
the results in their electronic discharge monitoring reports. Additionally, the 1000/100mL
fecal coliform daily maximum limit is a result of the 2002 TMDL. On February 22, 2023,
during the preparation of the NC0024970 McAlpine Creek WWMF permit renewal, the
Division contacted South Carolina's Department of Health and Environmental Control
(DHEC) regarding whether the daily maximum fecal coliform requirements under the
TMDL were sufficient in protecting the South Carolina E. coli standard, as the discharge is
above the SC/NC border. During their evaluation, SCDHEC considered the NC0024970
McAlpine Creek WWMF, NC0024937 Sugar Creek WRRF and NC0024945 Irwin Creek
WWTP discharges. On April 5, 2023, SCDHEC informed the Division that based on the NC
TMDL and the actual effluent data, they do not object to the limits for the 3 NC facilities
based on fecal coliform bacteria as the indicator. As such, the daily maximum fecal
coliform limit have been maintained at 1000/10mL.

Sugar Creek WRRF Fact Sheet Addendum NCO024937
3. E. coli
a. DEQ should require monitoring for E. coli instead of fecal coliform as an indicator of
pathogens to provide downstream users better information.
Response: The Division is in the process of developing an E. coli standard. In the
meantime, discussion with SCDHEC indicated that the fecal coliform limits in the Sugar
Creek WRRF permit are currently protective of the E. coli standard downstream in SC.
4. PFAS and 1,4-dioxane
a. DEQ should establish limits for PFAS and 1,4-doxane based off the latest EPA drinking
water standards.
Response: The Division has implemented a special condition requiring investigation into
the facility's industrial users, influent and post -filtration wastewater to identify PFAS
concentrations at the Sugar Creek WRRF. Charlotte Water is conducting a full-scale
investigation into each of their wastewater treatment facilities to identify sources of
PFAS. The Division's assessment of PFAS is ongoing.
As no 1,4-dioxane data are available for review, monthly effluent monitoring for 1,4-
dioxane as well as a 1,4-dioxane reopener condition have been added to the permit. After
data are available for Division review, further permitting actions may be considered.
5. Nitrogen
a. DEQ should add total nitrogen limits to protect downstream sites from excess nutrients,
including Lake Wateree prior to the in -development Lower Catawba Nutrient TMDL.
Response: As you have noted, SCDHEC is currently in the process of assessing nutrient
reductions by means of a Lower Catawba Nutrient TMDL which would include some
dischargers in North Carolina. The development of the TMDL will inform the Division of
the necessary limitations required to address nutrient loadings downstream. SCDHEC was
provided a copy of the draft permit for review and did not object to the permit as is. As
such, no changes have been made regarding total nitrogen limits at this time. Upon
completion of the modeling efforts and development of the TMDL, this may change.

Coco, Nick A
From:
Cantrell, Wade <[e-mail]>
Sent:
Wednesday, April 5, 2023 12:47 PM
To:
Coco, Nick A
Cc:
Green, Brenda A.; Waldner, Susan; Montebello, Michael J; Varlik, Banu; Behm, Pamela
Subject:
Re: [External] Re: E. coli in NC permits
Follow Up Flag: Follow up
Flag Status: Flagged
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Report Spam.
Nick -
Thanks for the opportunity to provide feedback. After reviewing permit limits, the NC TMDL and the actual
effluent data (summarized in the tables below), we do not object to the draft limits for the 3 NC facilities
based on fecal coliform bacteria as the indicator. This conclusion is based on (1) the general consistency of of
SC and NC permit limits which account for the relationship between fecal coliform and E coli as determined in
the DHEC Pathogen Indicator Study circa 2009 and (2) the extensive effluent data record showing a de
minimus number of samples greater than 400 fecal coliform.
It is possible that new information or comments arising during development of the SC E coli TMDL could cause
another look, but based on what we know now, we do not believe any changes to proposed bacteria limits are
necessary at this time.
Thanks!
Wade

Limits Comparison
Measure
Previous SC FC
Standard/Permits
Current SC E. coli
Standard/Permits
Current NC
(Permits
Current NC
TMDL
Monthly Average or G M
2-00
126
200
Weekly Average
400
Daily Max
4-00
349*
1000
"Not to Exceed"
4-00
Soo*
100C
*one sample >349 is not a violation if � 1) the sample did not exceed 800 AND
(2} 2 additional samples within 48 hours do not exceed 349
**Appears TM DL used dynamic model wit adjusted time series for continuous point sources
with maximum concentration adjusted dowvn to 1000, but not su re.
Effluent DMR Data Summary
Effluent DM R Summary of Fecal Coliform
NC Permit # POR
NCO0 4937 11412000 - 1 /30/ 022
NCO0 4970 11512000 - 1 /30/ 022
NCO0 4945 11412000 - 1 /30/ 022
Effluent DM R Summary of Fecal Coliform
NC Permit #
POR
NCO0 4937
1111201 - 1 /30/ 022
NCO0 4970
1121201 - 1 /30/2022
NCO0 4945
1121201 - 1 /30/ 022
Wade Cantrell
303d, Modeling & TMDL Section Manager
Division of Water Quality - Bureau of Water
S.C. Dept. of Health & Environmental Control
Office: [phone]
Connect: www.scdhec.aov Facebook Twitter
HI
n
n >400
% >400
Max
5674
94
1.70%
15000
5695
56
0.98%
40000
5505
69
1. 5%
6500
n
n >400
% >400
Max
498
3
0.1 1/o
710
498
5
0. 0%
891
495
2
0.08%
6000
From: Coco, Nick A <[e-mail]>
Sent: Tuesday, March 14, 2023 1:12 PM
To: Cantrell, Wade <[e-mail]>
Cc: Green, Brenda A. <[e-mail]>; Waldner, Susan <[e-mail]>; Montebello, Michael J
<[e-mail]>
Subject: RE: [External] Re: E. coli in NC permits
2

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***
Hi Wade,
Sorry — took a second to dig it up. The attached should be the FC TMDL. These 3 are already drafted, and one of the
internal review comments was to check with you regarding e. coli, so I'd say a response as soon as is reasonable on your
end, considering your own workloads and responsibilities. Is end of March too soon?
Thanks,
Nick Coco, PE (he/him/his)
Engineer 111
NPDES Municipal Permitting Unit
NC DEQ / Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
**Email is preferred but I am available to talk by via Microsoft Teams**
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617
r.- � :�
NORTH CAROLINA ��D,
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.
From: Cantrell, Wade <[e-mail]>
Sent: Tuesday, March 14, 2023 12:21 PM
To: Coco, Nick A <[e-mail]>
Cc: Green, Brenda A. <[e-mail]>; Waldner, Susan <[e-mail]>; Montebello, Michael J
<[e-mail]>
Subject: Re: [External] Re: E. coli in NC permits
CAUTION: External email. Do not click links or open attachments unless you verify. Send all suspicious email as an attachment to
Report Spam.
Great, thanks Nick. Last thing, just if you have a link to NC FC TMDL would be helpful, if not we might already
have it or can dig around.
We are ramping up an E. coli TMDL for our side of Sugar Creek and good to think about these questions
now. I'd like for our TMDL project manager to take a look. When do you need response?
Wade Cantrell
303d, Modeling & TMDL Section Manager
Division of Water Quality - Bureau of Water
S.C. Dept. of Health & Environmental Control

Office: [phone]
Conne www.scdhec.gov Facebook Twitter
❑
From: Coco, Nick A <[e-mail]>
Sent: Tuesday, March 14, 2023 12:11 PM
To: Cantrell, Wade <[e-mail]>
Cc: Green, Brenda A. <[e-mail]>; Waldner, Susan <[e-mail]>; Montebello, Michael J
<[e-mail]>
Subject: RE: [External] Re: E. coli in NC permits
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***
Hi Wade,
Please see attached for the data requested. I've included effluent and instream data (for fecal — maintained in the
McAlpine Creek DMR for all sites) for NCO024970 McAlpine Creek WWMF, NCO024945 Irwin Creek WWTP and
NCO024937 Sugar Creek WWTP. While the McAlpine Creek WWMF is the permit in question, each of the three facilities
are owned and operated by Charlotte Water, are currently in the renewal drafting process and discharge just above the
state border in about the same area. I figured offering more info couldn't hurt. Feel free to ignore extraneous info.
Please let me know if there is anything else you need.
Thanks again for looking into this,
Nick Coco, PE (he/him/his)
Engineer ///
NPDES Municipal Permitting Unit
NC DEQ / Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617
D�E QNORTH CAROLINA
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.
From: Cantrell, Wade <[e-mail]>
Sent: Tuesday, March 14, 2023 11:50 AM
To: Coco, Nick A <[e-mail]>

Cc: Green, Brenda A. <[e-mail]>; Waldner, Susan <[e-mail]>
Subject: [External] Re: E. coli in NC permits
CAUTION: External email. Do not click links or open attachments unless you verify. Send all suspicious email as an attachment to
Report Spam.
Hi Nick -
Brenda asked us (303d/TMDL/WLA section) to look at your question below. Thanks for reaching out. Would it
be possible to get DMR data for this facility, say flow and bacteria going back to 2000 or as available in your
database? Also, do you have a link for the NC FC TMDL? Would like to check a couple of things and give
feedback asap.
Thanks,
Wade
Wade Cantrell
303d, Modeling & TMDL Section Manager
Division of Water Quality - Bureau of Water
S.C. Dept. of Health & Environmental Control
Office: [phone]
Connect: www.scdhec.gov Facebook Twitter
0
From: Green, Brenda A. <[e-mail]>
Sent: Monday, March 13, 2023 1:46 PM
To: Cantrell, Wade <[e-mail]>
Subject: Fwd: E. coli in NC permits
Will you take a look at the original question from NC and give me any feedback? Thanks!
Get Outlook for iOS
From: Siddiqui, Mohammed <[e-mail]>
Sent: Thursday, March 9, 2023 12:14:29 PM
To: Green, Brenda A. <[e-mail]>; Clarke, Shawn <[e-mail]>
Subject: Re: E. coli in NC permits
McAlpine creek south of the border is impaired
Use: AL/Rec
Cause: Bio/Ecoli
Also there is a d/s intake S29106
and a little further down is S12101
Sohail Siddiqui, P.L.
Environmental Engineer, Domestic Wastewater Permitting Section, Bureau of Water
S.C. Dept. of Health & Environmental Control
Office: [phone]
Fax: [phone]
Connect: www.scdhec.gov Facebook Twitter

J
From: Green, Brenda A. <[e-mail]>
Sent: Thursday, March 9, 2023 10:43 AM
To: Clarke, Shawn <[e-mail]>
Cc: Siddiqui, Mohammed <[e-mail]>
Subject: Fw: E. coli in NC permits
This is one I didn't see. I think we would want e.Coli limits since they are close.
Brenda Green
Manager, Domestic Wastewater Permitting Section
Bureau of Water
S.C. Dept. of Health & Environmental Control
Office: [phone]
Fax: [phone]
Connect: www.scdhec.gov Facebook Twitter
0
From: Coco, Nick A <[e-mail]>
Sent: Wednesday, March 1, 2023 2:19 PM
To: Green, Brenda A. <[e-mail]>
Cc: Montebello, Michael J <[e-mail]>
Subject: RE: E. coli in NC permits
*** Caution. This is an EXTERNAL email. DO NOT open attachments or click links from unknown senders or unexpected email.
***
Hi Brenda,
I was wondering if you were able to give this email some thought. I'll be sending you a copy of the draft permit as well
once it makes it to that stage, but wanted to make sure I addressed this particular item before sending it out for
comment.
Thanks,
Nick Coco, PE (he/him/his)
Engineer 111
NPDES Municipal Permitting Unit
NC DEQ / Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617

D E
C1110)
NORTH CAROLINA
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.
From: Coco, Nick A
Sent: Wednesday, February 22, 2023 9:58 AM
To: Green, Brenda A. <[e-mail]>
Cc: Montebello, Michael J <[e-mail]>
Subject: E. coli in NC permits
Hi Brenda,
I hope you're doing well.
I'm currently working through the renewal of the McAlpine Creek WWMF NPDES permit NC0024970. This is a major
discharger (64.0 MGD permitted flow) which discharges above the NC/SC border. As you may know, this particular
facility is subject to a fecal coliform TMDL, which requires the facility to meet a daily maximum limitation of 1000/100ml-
in addition to the standard MA of 200/100ml- and WA of 400/100mL. In the peer review process, it was brought to my
attention that SC has E.coli standards to uphold as well and it was suggested I reach out to you to either ensure that the
fecal coliform TMDL is protective of the SC water uses or ask what type of E.coli considerations should be made for this
discharge. Would you be able to share some insight here?
Thanks so much in advance for your time and any guidance you can provide.
Best,
Nick Coco, PE (he/him/his)
Engineer ///
NPDES Municipal Permitting Unit
NC DEQ / Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617

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H1
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
REASONABLE POTENTIAL ANALYSIS
H2
Use"PASTE SPECIAL
Use"PASTE SPECIAL
Effluent Hardness
Values" then "COPY"
Upstream
Hardness
Values" then "COPY"
.Maximum data
. Maximum data
points = 58
points = 58
Date
Data
BDL=1/2DL
Results
Date
Data BDL=1/2DL
Results
5/9/2019
71
71
Std Dev.
18.6576
1
5/21/2019
100
100
Std Dev.
15.9129
6/7/2019
59
59
Mean
72.0357
2
6/17/2019
83
83
Mean
82.3846
7/13/2019
55
55
C.V.
0.2590
3
7/18/2019
91
91
C.V.
0.1932
8/11/2019
63
63
n
56
4
8/7/2019
62
62
n
52
9/9/2019
53
53
10th Per value
52.50 mg/L
5
9/12/2019
96
96
10th Per value
62.10 mg/L
10/8/2019
53
53
Average Value
72.04 mg/L
6
10/8/2019
99
99
Average Value
82.38 mg/L
11/6/2019
130
130
Max. Value
130.00 mg/L
7
11/14/2019
63
63
Max. Value
100.00 mg/L
12/12/2019
89
89
8
12/19/2019
74
74
1/10/2020
74
74
9
1/9/2020
91
91
2/8/2020
79
79
10
2/4/2020
89
89
3/8/2020
97
97
11
3/16/2020
100
100
4/6/2020
110
110
12
4/6/2020
100
100
5/6/2020
89
89
13
5/11/2020
92
92
5/12/2020
130
130
14
6/1/2020
94
94
6/10/2020
67
67
15
7/7/2020
77
77
7/16/2020
59
59
16
8/3/2020
84
84
8/7/2020
49
49
17
9/15/2020
88
88
9/19/2020
72
72
18
10/5/2020
98
98
10/11/2020
46
46
19
11/2/2020
50
50
11/9/2020
46
46
20
12/8/2020
90
90
12/8/2020
70
70
21
1/11/2021
91
91
1/13/2021
84
84
22
2/3/2021
90
90
2/11/2021
70
70
23
3/8/2021
100
100
3/12/2021
66
66
24
4/12/2021
80
80
4/10/2021
67
67
25
5/17/2021
94
94
5/16/2021
68
68
26
6/14/2021
81
81
6/7/2021
72
72
27
7/6/2021
91
91
7/13/2021
100
100
28
8/9/2021
81
81
8/4/2021
100
100
29
9/7/2021
94
94
8/18/2021
84
84
30
10/4/2021
84
84
9/16/2021
76
76
31
11/9/2021
84
84
10/15/2021
67
67
32
12/14/2021
68
68
11/20/2021
64
64
33
1/19/2022
62
62
12/19/2021
61
61
34
2/9/2022
68
68
1/10/2022
56
56
35
3/2/2022
82
82
2/8/2022
84
84
36
4/13/2022
94
94
3/9/2022
82
82
37
5/9/2022
87
87
4/7/2022
60
60
38
6/1/2022
91
91
5/13/2022
65
65
39
7/20/2022
63
63
6/11/2022
52
52
40
8/8/2022
41
41
7/24/2022
55
55
41
9/7/2022
51
51
8/15/2022
67
67
42
10/17/2022
94
94
9/13/2022
82
82
43
11/9/2022
78
78
10/12/2022
51
51
44
12/12/2022
85
85
11/9/2022
54
54
45
1/10/2023
93
93
11/17/2022
70
70
46
2/8/2023
95
95
12/16/2022
66
66
47
3/8/2023
100
100
1/14/2023
62
62
48
4/3/2023
87
87
2/12/2023
91
91
49
5/1/2023
65
65
2/15/2023
92
92
50
6/20/2023
31
31
3/13/2023
87
87
51
7/3/2023
88
88
4/18/2023
71
71
52
8/1/2023
70
70
5/10/2023
75
75
53
6/8/2023
47
47
54
7/14/2023
63
63
55
8/12/2023
62
62
56
57
58
-1-
24937 rpa, data
10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par01 & Par02
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
Use"PASTE SPECIAL
Arsenic
Values" then "COPY"
. Maximum data
points = 58
Date
Data
BDL=1/2DL
Results
5/9/2019
<
5
2.5
Std Dev.
0.0000
6/7/2019
<
5
2.5
Mean
2.5000
7/13/2019
<
5
2.5
C.V.
0.0000
8/11/2019
<
5
2.5
n
56
9/9/2019
<
5
2.5
10/8/2019
<
5
2.5
Mult Factor =
1.00
11/6/2019
<
5
2.5
Max. Value
2.5 ug/L
12/12/2019
<
5
2.5
Max. Pred Cw
2.5 ug/L
1/10/2020
<
5
2.5
2/8/2020
<
5
2.5
3/8/2020
<
5
2.5
4/6/2020
<
5
2.5
5/6/2020
<
5
2.5
5/12/2020
<
5
2.5
6/10/2020
<
5
2.5
7/16/2020
<
5
2.5
8/7/2020
<
5
2.5
9/19/2020
<
5
2.5
10/11/2020
<
5
2.5
11/9/2020
<
5
2.5
12/8/2020
<
5
2.5
1/13/2021
<
5
2.5
2/11/2021
<
5
2.5
3/12/2021
<
5
2.5
4/10/2021
<
5
2.5
5/16/2021
<
5
2.5
6/7/2021
<
5
2.5
7/13/2021
<
5
2.5
8/4/2021
<
5
2.5
8/18/2021
<
5
2.5
9/16/2021
<
5
2.5
10/15/2021
<
5
2.5
11/20/2021
<
5
2.5
12/19/2021
<
5
2.5
1/10/2022
<
5
2.5
2/8/2022
<
5
2.5
3/9/2022
<
5
2.5
4/7/2022
<
5
2.5
5/13/2022
<
5
2.5
6/11/2022
<
5
2.5
7/24/2022
<
5
2.5
8/15/2022
<
5
2.5
9/13/2022
<
5
2.5
10/12/2022
<
5
2.5
11/9/2022
<
5
2.5
11/17/2022
<
5
2.5
12/16/2022
<
5
2.5
1/14/2023
<
5
2.5
2/12/2023
<
5
2.5
2/15/2023
<
5
2.5
3/13/2023
<
5
2.5
4/18/2023
<
5
2.5
5/10/2023
<
5
2.5
6/8/2023
<
5
2.5
7/14/2023
<
5
2.5
8/12/2023
<
5
2.5
24937 rpa, data
- 2 - 10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par03
Date Data
1 5/6/2020 <
2 8/4/2021 <
3 11/9/2022 <
4 2/15/2023 <
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
Beryllium
BDL=1/2DL
Results
2 1
Std Dev.
2 1
Mean
2 1
C.V. (default)
2 1
n
Mult Factor =
Max. Value
Max. Pred Cw
Par04
Use"PASTE SPECIAL
Values" then "COPY"
.Maximum data
points = 58
1.0000
0.6000
4
2.59
1.00 ug/L
2.59 ug/L
Date Data
1 5/9/2019 <
2 6/7/2019 <
3 7/13/2019 <
4 8/11/2019 <
5 9/9/2019 <
6 10/8/2019 <
7 11/6/2019 <
8 12/12/2019 <
9 1/10/2020 <
10 2/8/2020 <
11 3/8/2020 <
12 4/6/2020 <
13 5/6/2020 <
14 5/12/2020 <
15 6/10/2020 <
16 7/16/2020 <
17 8/7/2020 <
18 9/19/2020 <
19 10/11/2020 <
20 11/9/2020 <
21 12/8/2020 <
22 1/13/2021 <
23 2/11/2021 <
24 3/12/2021 <
25 4/10/2021 <
26 5/16/2021 <
27 6/7/2021 <
28 7/13/2021 <
29 8/4/2021 <
30 8/18/2021 <
31 9/16/2021 <
32 10/15/2021 <
33 11/20/2021 <
34 12/19/2021 <
35 1/10/2022 <
36 2/8/2022 <
37 3/9/2022 <
38 4/7/2022 <
39 5/13/2022 <
40 6/11/2022 <
41 7/24/2022 <
42 8/15/2022 <
43 9/13/2022 <
44 10/12/2022 <
45 11/9/2022 <
46 11/17/2022 <
47 12/16/2022 <
48 1/14/2023 <
49 2/12/2023 <
50 2/15/2023 <
51 3/13/2023 <
52 4/18/2023 <
53 5/10/2023 <
54 6/8/2023 <
55 7/14/2023 <
56 8/12/2023 <
57
58
Cadmium
BDL=1/2DL
Results
1
0.5
Std Dev.
1
0.5
Mean
1
0.5
C.V.
1
0.5
n
0.5
0.25
0.5
0.25
Mult Factor =
0.5
0.25
Max. Value
0.5
0.25
Max. Pred Cw
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
0.5
0.25
Use"PASTE SPECIAL
Values" then "COPY"
. Maximum data
points = 58
0.2679
0.2425
56
1.00
0.500 ug/L
0.500 ug/L
-3-
24937 rpa, data
10/23/2023

Par07
REASONABLE POTENTIAL ANALYSIS
Par10
Use"PASTE SPECIAL
Total Phenolic Compounds Values" then "COPY" Chromium, Total
. Maximum data
points = 58
Date Data
1 5/6/2020 <
2 8/4/2021 <
3 11/9/2022 <
4 2/15/2023 <
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
BDL=1/2DL
Results
50 25
Std Dev.
0.0000
50 25
Mean
25.0000
50 25
C.V. (default)
0.6000
50 25
n
4
Mult Factor =
2.59
Max. Value
25.0 ug/L
Max. Pred Cw
64.8 ug/L
Date
Data
BDL=1/2DL
Results
1
5/9/2019
<
5
2.5
Std Dev.
2
6/7/2019
<
5
2.5
Mean
3
7/13/2019
<
5
2.5
C.V.
4
8/11/2019
<
5
2.5
n
5
9/9/2019
<
5
2.5
6
10/8/2019
<
5
2.5
Mult Factor =
7
11/6/2019
<
5
2.5
Max. Value
8
12/12/2019
<
5
2.5
Max. Pred Cw
9
1/10/2020
<
5
2.5
10
2/8/2020
<
5
2.5
11
3/8/2020
<
5
2.5
12
4/6/2020
<
5
2.5
13
5/6/2020
<
5
2.5
14
5/12/2020
<
5
2.5
15
6/10/2020
<
5
2.5
16
7/16/2020
7.1
7.1
17
8/7/2020
<
5
2.5
18
9/19/2020
<
5
2.5
19
10/11/2020
<
5
2.5
20
11/9/2020
<
5
2.5
21
12/8/2020
<
5
2.5
22
1/13/2021
<
5
2.5
23
2/11/2021
<
5
2.5
24
3/12/2021
<
5
2.5
25
4/10/2021
<
5
2.5
26
5/16/2021
<
5
2.5
27
6/7/2021
<
5
2.5
28
7/13/2021
<
5
2.5
29
8/4/2021
<
5
2.5
30
8/18/2021
<
5
2.5
31
9/16/2021
<
5
2.5
32
10/15/2021
<
5
2.5
33
11/20/2021
<
5
2.5
34
12/19/2021
<
5
2.5
35
1/10/2022
<
5
2.5
36
2/8/2022
<
5
2.5
37
3/9/2022
<
5
2.5
38
4/7/2022
<
5
2.5
39
5/13/2022
<
5
2.5
40
6/11/2022
<
5
2.5
41
7/24/2022
<
5
2.5
42
8/15/2022
<
5
2.5
43
9/13/2022
<
5
2.5
44
10/12/2022
<
5
2.5
45
11/9/2022
<
5
2.5
46
11/17/2022
<
5
2.5
47
12/16/2022
<
5
2.5
48
1/14/2023
<
5
2.5
49
2/12/2023
<
5
2.5
50
2/15/2023
<
5
2.5
51
3/13/2023
<
5
2.5
52
4/18/2023
<
5
2.5
53
5/10/2023
<
5
2.5
54
6/8/2023
<
5
2.5
55
7/14/2023
<
5
2.5
56
8/12/2023
<
5
2.5
57
58
Use"PASTE SPECIAL
Values" then "COPY"
. Maximum data
points = 58
2.5821
0.2381
56
1.00
7.1 pg/L
7.1 pg/L
24937 rpa, data
-4- 10/23/2023

REASONABLE POTENTIAL ANALYSIS
Pal 1 1Paf12
Copper
Date
Data
BDL=1/2DL
Results
1
5/9/2019
3.1
3.1
Std Dev.
2
6/7/2019
2.3
2.3
Mean
3
7/13/2019
3.2
3.2
C.V.
4
8/11/2019
3.8
3.8
n
5
9/9/2019
3.6
3.6
6
10/8/2019
3.3
3.3
Mult Factor =
7
11/6/2019
2.9
2.9
Max. Value
8
12/12/2019
2.4
2.4
Max. Pred Cw
9
1/10/2020
3.9
3.9
10
2/8/2020
2.9
2.9
11
3/8/2020
2.4
2.4
12
4/6/2020
3.6
3.6
13
5/6/2020
4.3
4.3
14
5/12/2020
3.8
3.8
15
6/10/2020
4.1
4.1
16
7/16/2020
2.6
2.6
17
8/7/2020
2.5
2.5
18
9/19/2020
2.2
2.2
19
10/11/2020
2.8
2.8
20
11/9/2020
2.9
2.9
21
12/8/2020
2.6
2.6
22
1/13/2021
2.9
2.9
23
2/11/2021
3.1
3.1
24
3/12/2021
2.4
2.4
25
4/10/2021
2.7
2.7
26
5/16/2021
3
3
27
6/7/2021
3.5
3.5
28
7/13/2021
2.4
2.4
29
8/4/2021
3.8
3.8
30
8/18/2021
3.2
3.2
31
9/16/2021
2.5
2.5
32
10/15/2021
2.5
2.5
33
11/20/2021
3
3
34
12/19/2021
<
2
1
35
1/10/2022
3.1
3.1
36
2/8/2022
<
2
1
37
3/9/2022
3.2
3.2
38
4/7/2022
2.8
2.8
39
5/13/2022
2.7
2.7
40
6/11/2022
3.9
3.9
41
7/24/2022
4.6
4.6
42
8/15/2022
3.1
3.1
43
9/13/2022
3.2
3.2
44
10/12/2022
2.7
2.7
45
11/9/2022
3.4
3.4
46
11/17/2022
<
2
1
47
12/16/2022
<
2
1
48
1/14/2023
<
2
1
49
2/12/2023
2.4
2.4
50
2/15/2023
2.8
2.8
51
3/13/2023
2.3
2.3
52
4/18/2023
<
2
1
53
5/10/2023
4.1
4.1
54
6/8/2023
3.3
3.3
55
7/14/2023
3
3
56
8/12/2023
6
6
57
58
Use"PASTE SPECIAL
Values" then "COPY"
.Maximum data
points = 58
2.9071
0.3252
56
1.01
6.00 ug/L
6.06 ug/L
Cyanide
Date
Data
BDL=1/2DL
Results
1 5/9/2019
<
10
5
Std Dev.
2 6/7/2019
<
10
5
Mean
3 7/12/2019
<
10
5
C.V.
4 8/12/2019
<
10
5
n
5 9/9/2019
<
10
5
6 10/8/2019
<
10
5
Mult Factor =
7 11/6/2019
<
10
5
Max. Value
8 12/12/2019
<
10
5
Max. Pred Cw
9 1/10/2020
<
10
5
10 2/7/2020
<
10
5
11 3/9/2020
<
10
5
12 4/6/2020
<
10
5
13 5/6/2020
<
10
5
14 5/12/2020
<
10
5
15 6/11/2020
<
10
5
16 7/16/2020
<
10
5
17 8/7/2020
<
10
5
18 9/18/2020
<
10
5
19 10/12/2020
<
10
5
20 11/9/2020
<
10
5
21 12/8/2020
<
10
5
22 1/13/2021
<
10
5
23 2/11/2021
<
10
5
24 3/12/2021
<
10
5
25 4/9/2021
<
10
5
26 5/17/2021
<
10
5
27 6/7/2021
<
10
5
28 7/13/2021
<
10
5
29 8/4/2021
<
10
5
30 8/18/2021
<
10
5
31 9/16/2021
<
10
5
32 10/15/2021
<
10
5
33 11/19/2021
<
10
5
34 12/20/2021
<
10
5
35 1/10/2022
<
10
5
36 2/8/2022
<
10
5
37 3/9/2022
<
10
5
38 4/7/2022
<
10
5
39 5/13/2022
<
10
5
40 6/10/2022
<
10
5
41 7/25/2022
<
10
5
42 8/15/2022
<
10
5
43 9/13/2022
<
10
5
44 10/12/2022
<
10
5
45 11/9/2022
<
10
5
46 11/17/2022
<
10
5
47 12/16/2022
<
10
5
48 1/13/2023
<
10
5
49 2/13/2023
<
10
5
50 2/15/2023
<
10
5
51 3/13/2023
<
10
5
52 4/18/2023
<
10
5
53 5/10/2023
<
10
5
54 6/8/2023
<
10
5
55 7/14/2023
<
10
5
56 8/11/2023
<
10
5
57
58
Use"PASTE SPECIAL
Values" then "COPY"
. Maximum data
points = 58
5.00
0.0000
56
1.00
5.0 ug/L
5.0 ug/L
-5-
24937 rpa, data
10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par14 I IPar16
Lead
Date
BDL=1/2DL
Results
1
5/9/2019
< 5
2.5
Std Dev.
2
6/7/2019
< 5
2.5
Mean
3
7/13/2019
< 5
2.5
C.V.
4
8/11/2019
< 5
2.5
n
5
9/9/2019
< 5
2.5
6
10/8/2019
< 5
2.5
Mult Factor =
7
11/6/2019
< 5
2.5
Max. Value
8
12/12/2019
< 5
2.5
Max. Pred Cw
9
1/10/2020
< 5
2.5
10
2/8/2020
< 5
2.5
11
3/8/2020
< 5
2.5
12
4/6/2020
< 5
2.5
13
5/6/2020
< 5
2.5
14
5/12/2020
< 5
2.5
15
6/10/2020
< 5
2.5
16
7/16/2020
< 5
2.5
17
8/7/2020
< 5
2.5
18
9/19/2020
< 5
2.5
19
10/11/2020
< 5
2.5
20
11/9/2020
< 5
2.5
21
12/8/2020
< 5
2.5
22
1/13/2021
< 5
2.5
23
2/11/2021
< 5
2.5
24
3/12/2021
< 5
2.5
25
4/10/2021
< 5
2.5
26
5/16/2021
< 5
2.5
27
6/7/2021
< 5
2.5
28
7/13/2021
< 5
2.5
29
8/4/2021
< 5
2.5
30
8/18/2021
< 5
2.5
31
9/16/2021
< 5
2.5
32
10/15/2021
< 5
2.5
33
11/20/2021
< 5
2.5
34
12/19/2021
< 5
2.5
35
1/10/2022
< 5
2.5
36
2/8/2022
< 5
2.5
37
3/9/2022
< 5
2.5
38
4/7/2022
< 5
2.5
39
5/13/2022
< 5
2.5
40
6/11/2022
< 5
2.5
41
7/24/2022
< 5
2.5
42
8/15/2022
< 5
2.5
43
9/13/2022
< 5
2.5
44
10/12/2022
< 5
2.5
45
11/9/2022
< 5
2.5
46
11/17/2022
< 5
2.5
47
12/16/2022
< 5
2.5
48
1/14/2023
< 5
2.5
49
2/12/2023
< 5
2.5
50
2/15/2023
< 5
2.5
51
3/13/2023
< 5
2.5
52
4/18/2023
< 5
2.5
53
5/10/2023
< 5
2.5
54
6/8/2023
< 5
2.5
55
7/14/2023
< 5
2.5
56
8/12/2023
< 5
2.5
57
58
Use"PASTE SPECIAL
Values" then "COPY"
.Maximum data
points = 58
2.5000
0.0000
56
1.00
2.500 ug/L
2.500 ug/L
Molybdenum
Date
Data
BDL=1/2DL
Results
1 5/9/2019
<
5
2.5
Std Dev.
2 6/7/2019
<
5
2.5
Mean
3 7/13/2019
<
5
2.5
C.V.
4 8/11/2019
<
5
2.5
n
5 9/9/2019
<
5
2.5
6 10/8/2019
<
5
2.5
Mult Factor =
7 11/6/2019
<
5
2.5
Max. Value
8 12/12/2019
<
5
2.5
Max. Pred Cw
9 1/10/2020
<
5
2.5
10 2/8/2020
<
5
2.5
11 3/8/2020
<
5
2.5
12 4/6/2020
<
5
2.5
13 5/6/2020
<
5
2.5
14 5/12/2020
<
5
2.5
15 6/10/2020
<
5
2.5
16 7/16/2020
<
5
2.5
17 8/7/2020
<
5
2.5
18 9/19/2020
7.7
7.7
19 10/11/2020
<
5
2.5
20 11/9/2020
<
5
2.5
21 12/8/2020
<
5
2.5
22 1/13/2021
<
5
2.5
23 2/11/2021
<
5
2.5
24 3/12/2021
<
5
2.5
25 4/10/2021
<
5
2.5
26 5/16/2021
<
5
2.5
27 6/7/2021
<
5
2.5
28 7/13/2021
<
5
2.5
29 8/4/2021
<
5
2.5
30 8/18/2021
<
5
2.5
31 9/16/2021
<
5
2.5
32 10/15/2021
<
5
2.5
33 11/20/2021
<
5
2.5
34 12/19/2021
<
5
2.5
35 1/10/2022
<
5
2.5
36 2/8/2022
<
5
2.5
37 3/9/2022
<
5
2.5
38 4/7/2022
<
5
2.5
39 5/13/2022
<
5
2.5
40 6/11/2022
<
5
2.5
41 7/24/2022
<
5
2.5
42 8/15/2022
<
5
2.5
43 9/13/2022
<
5
2.5
44 10/12/2022
<
5
2.5
45 11/9/2022
<
5
2.5
46 11/17/2022
<
5
2.5
47 12/16/2022
<
5
2.5
48 1/14/2023
<
5
2.5
49 2/12/2023
<
5
2.5
50 2/15/2023
<
5
2.5
51 3/13/2023
<
5
2.5
52 4/18/2023
<
5
2.5
53 5/10/2023
<
5
2.5
54 6/8/2023
<
5
2.5
55 7/14/2023
<
5
2.5
56 8/12/2023
<
5
2.5
57
58
Use"PASTE SPECIAL
Values" then "COPY"
. Maximum data
points = 58
2.5929
0.2680
56
1.01
7.7 ug/L
7.8 ug/L
-6-
24937 rpa, data
10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par17 & Par18
Date Data
1 5/9/2019
2 6/7/2019
3 7/13/2019
4 8/11/2019
5 9/9/2019 <
6 10/8/2019
7 11/6/2019
8 12/12/2019
9 1 /10/2020
10 2/8/2020
11 3/8/2020
12 4/6/2020
13 5/6/2020
14 5/12/2020
15 6/10/2020
16 7/16/2020
17 8/7/2020
18 9/19/2020
19 10/11 /2020
20 11 /9/2020
21 12/8/2020
22 1/13/2021 <
23 2/11/2021
24 3/12/2021
25 4/10/2021
26 5/16/2021
27 6/7/2021
28 7/13/2021
29 8/4/2021
30 8/18/2021
31 9/16/2021
32 10/15/2021
33 11 /20/2021
34 12/19/2021
35 1 /10/2022
36 2/8/2022 <
37 3/9/2022
38 4/7/2022
39 5/13/2022
40 6/11/2022
41 7/24/2022
42 8/15/2022
43 9/13/2022
44 10/12/2022 <
45 11 /9/2022
46 11 /17/2022
47 12/16/2022 <
48 1 /14/2023
49 2/12/2023
50 2/15/2023
51 3/13/2023
52 4/18/2023
53 5/10/2023
54 6/8/2023
55 7/14/2023
56 8/12/2023
57
58
Nickel
BDL=1/2DL
Results
3.1
3.1
Std Dev.
2.8
2.8
Mean
2.5
2.5
C.V.
3.4
3.4
n
2
1
2.9
2.9
Mult Factor =
3
3
Max. Value
2.6
2.6
Max. Pred Cw
2.2
2.2
3.7
3.7
2.7
2.7
2.5
2.5
24
24
4.5
4.5
3.2
3.2
6.9
6.9
3
3
3
3
2.8
2.8
2.3
2.3
2.3
2.3
2
1
2.8
2.8
2.6
2.6
3.8
3.8
3.4
3.4
3.3
3.3
5.4
5.4
11
11
4.5
4.5
4
4
2.9
2.9
2
2
3
3
2.8
2.8
2
1
3.4
3.4
2.6
2.6
3
3
2.9
2.9
3.6
3.6
2.1
2.1
2.4
2.4
2
1
2.6
2.6
2.6
2.6
2
1
2.1
2.1
2.5
2.5
2.7
2.7
2.7
2.7
2.5
2.5
3
3
3.3
3.3
3.2
3.2
3.6
3.6
Use"PASTE SPECIAL
Values" then "COPY"
.Maximum data
points = 58
3.1672
3.4054
0.9301
56
1.02
24.0 pg/L
24.5 pg/L
Par19
Selenium
Date
Data
BDL=1/2DL
Results
1
5/9/2019
<
5
2.5
Std Dev.
2
6/7/2019
<
5
2.5
Mean
3
7/13/2019
<
5
2.5
C.V.
4
8/11/2019
<
5
2.5
n
5
9/9/2019
<
5
2.5
6
10/8/2019
<
5
2.5
Mult Factor =
7
11/6/2019
<
5
2.5
Max. Value
8
12/12/2019
<
5
2.5
Max. Pred Cw
9
1/10/2020
<
5
2.5
10
2/8/2020
<
5
2.5
11
3/8/2020
<
5
2.5
12
4/6/2020
<
5
2.5
13
5/6/2020
<
5
2.5
14
5/12/2020
<
5
2.5
15
6/10/2020
<
5
2.5
16
7/16/2020
<
5
2.5
17
8/7/2020
<
5
2.5
18
9/19/2020
<
5
2.5
19
10/11/2020
<
5
2.5
20
11/9/2020
<
5
2.5
21
12/8/2020
<
5
2.5
22
1/13/2021
<
5
2.5
23
2/11/2021
<
5
2.5
24
3/12/2021
<
5
2.5
25
4/10/2021
<
5
2.5
26
5/16/2021
<
5
2.5
27
6/7/2021
<
5
2.5
28
7/13/2021
<
5
2.5
29
8/4/2021
<
5
2.5
30
8/18/2021
<
5
2.5
31
9/16/2021
<
5
2.5
32
10/15/2021
<
5
2.5
33
11/20/2021
<
5
2.5
34
12/19/2021
<
5
2.5
35
1/10/2022
<
5
2.5
36
2/8/2022
<
5
2.5
37
3/9/2022
<
5
2.5
38
4/7/2022
<
5
2.5
39
5/13/2022
<
5
2.5
40
6/11/2022
<
5
2.5
41
7/24/2022
<
5
2.5
42
8/15/2022
<
5
2.5
43
9/13/2022
<
5
2.5
44
10/12/2022
<
5
2.5
45
11/9/2022
<
5
2.5
46
11/17/2022
<
5
2.5
47
12/16/2022
<
5
2.5
48
1/14/2023
<
5
2.5
49
2/12/2023
<
5
2.5
50
2/15/2023
<
5
2.5
51
3/13/2023
<
5
2.5
52
4/18/2023
<
5
2.5
53
5/10/2023
<
5
2.5
54
6/8/2023
<
5
2.5
55
7/14/2023
<
5
2.5
56
8/12/2023
<
5
2.5
57
58
Use"PASTE
SPECIAL -Values"
then "COPY".
Maximum data
points = 58
2.5000
0.0000
56
1.00
2.5 ug/L
2.5 ug/L
-7-
24937 rpa, data
10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par20 I IPar21
Silver
Date
Data
BDL=1/2DL
Results
1
5/9/2019
<
1
0.5
Std Dev.
2
6/7/2019
<
1
0.5
Mean
3
7/13/2019
<
1
0.5
C.V.
4
8/11/2019
<
1
0.5
n
5
9/9/2019
<
1
0.5
6
10/8/2019
<
1
0.5
Mult Factor =
7
11/6/2019
<
1
0.5
Max. Value
8
12/12/2019
<
1
0.5
Max. Pred Cw
9
1/10/2020
<
1
0.5
10
2/8/2020
<
1
0.5
11
3/8/2020
<
1
0.5
12
4/6/2020
<
1
0.5
13
5/6/2020
<
1
0.5
14
5/12/2020
<
1
0.5
15
6/10/2020
<
1
0.5
16
7/16/2020
<
1
0.5
17
8/7/2020
<
1
0.5
18
9/19/2020
<
1
0.5
19
10/11/2020
<
1
0.5
20
11/9/2020
<
1
0.5
21
12/8/2020
<
1
0.5
22
1/13/2021
<
1
0.5
23
2/11/2021
<
1
0.5
24
3/12/2021
<
1
0.5
25
4/10/2021
<
1
0.5
26
5/16/2021
<
1
0.5
27
6/7/2021
<
1
0.5
28
7/13/2021
<
1
0.5
29
8/4/2021
<
1
0.5
30
8/18/2021
<
1
0.5
31
9/16/2021
<
1
0.5
32
10/15/2021
<
1
0.5
33
11/20/2021
<
1
0.5
34
12/19/2021
<
1
0.5
35
1/10/2022
<
1
0.5
36
2/8/2022
<
1
0.5
37
3/9/2022
<
1
0.5
38
4/7/2022
<
1
0.5
39
5/13/2022
<
1
0.5
40
6/11/2022
<
1
0.5
41
7/24/2022
<
1
0.5
42
8/15/2022
<
1
0.5
43
9/13/2022
<
1
0.5
44
10/12/2022
<
1
0.5
45
11/9/2022
<
1
0.5
46
11/17/2022
<
1
0.5
47
12/16/2022
<
1
0.5
48
1/14/2023
<
1
0.5
49
2/12/2023
<
1
0.5
50
2/15/2023
<
1
0.5
51
3/13/2023
<
1
0.5
52
4/18/2023
<
1
0.5
53
5/10/2023
<
1
0.5
54
6/8/2023
<
1
0.5
55
7/14/2023
<
1
0.5
56
8/12/2023
<
1
0.5
57
58
Use"PASTE SPECIAL
Values" then "COPY"
.Maximum data
points = 58
0.5000
0.0000
56
1.00
0.500 ug/L
0.500 ug/L
Zinc
Date Data
BDL=1/2DL
Results
1 5/9/2019
43
43
Std Dev.
2 6/7/2019
35
35
Mean
3 7/13/2019
46
46
C.V.
4 8/11/2019
49
49
n
5 9/9/2019
34
34
6 10/8/2019
34
34
Mult Factor =
7 11/6/2019
37
37
Max. Value
8 12/12/2019
39
39
Max. Pred Cw
9 1/10/2020
46
46
10 2/8/2020
32
32
11 3/8/2020
39
39
12 4/6/2020
34
34
13 5/6/2020
27
27
14 5/12/2020
31
31
15 6/10/2020
39
39
16 7/16/2020
57
57
17 8/7/2020
52
52
18 9/19/2020
37
37
19 10/11/2020
42
42
20 11/9/2020
51
51
21 12/8/2020
38
38
22 1/13/2021
44
44
23 2/11/2021
49
49
24 3/12/2021
49
49
25 4/10/2021
44
44
26 5/16/2021
48
48
27 6/7/2021
33
33
28 7/13/2021
32
32
29 8/4/2021
44
44
30 8/18/2021
33
33
31 9/16/2021
36
36
32 10/15/2021
46
46
33 11/20/2021
48
48
34 12/19/2021
47
47
35 1/10/2022
48
48
36 2/8/2022
23
23
37 3/9/2022
48
48
38 4/7/2022
35
35
39 5/13/2022
41
41
40 6/11/2022
48
48
41 7/24/2022
47
47
42 8/15/2022
38
38
43 9/13/2022
35
35
44 10/12/2022
46
46
45 11/9/2022
47
47
46 11/17/2022
34
34
47 12/16/2022
26
26
48 1/14/2023
25
25
49 2/12/2023
26
26
50 2/15/2023
30
30
51 3/13/2023
27
27
52 4/18/2023
17
17
53 5/10/2023
41
41
54 6/8/2023
38
38
55 7/14/2023
49
49
56 8/12/2023
40
40
57
58
Use"PASTE SPECIAL
Values" then "COPY"
. Maximum data
points = 58
39.3571
0.2161
56
1.00
57.0 ug/L
57.0 ug/L
-8-
24937 rpa, data
10/23/2023

REASONABLE POTENTIAL ANALYSIS
Par22
Use"PASTE SPECIAL
Bis(2-Ethylhexyl) Phthalate
Values" then "COPY"
. Maximum data
points = 58
Date Data
BDL=1/2DL
Results
1
5/6/2020 <
5
2.5
Std Dev.
0.0000
2
8/4/2021 <
5
2.5
Mean
2.5000
3
11/9/2022 <
5
2.5
C.V. (default)
0.6000
4
2/15/2023 <
5
2.5
n
4
5
6
Mult Factor =
2.59
7
Max. Value
2.500000 pg/L
8
Max. Pred Cw
6.475000 pg/L
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
24937 rpa, data
- 9 - 10/23/2023

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Permit No. NC0024937
NPDES Implementation of Instream Dissolved Metals Standards - Freshwater Standards
The NC 2007-2015 Water Quality Standard (WQS) Triennial Review was approved by the NC
Environmental Management Commission (EMC) on November 13, 2014. The US EPA subsequently
approved the WQS revisions on April 6, 2016, with some exceptions. Therefore, metal limits in draft
permits out to public notice after April 6, 2016 must be calculated to protect the new standards - as
approved.
Table 1. NC Dissolved Metals Water Q ality Standards/A uatic Life Protection
Parameter
Acute FW, µg/l
(Dissolved)
Chronic FW, µg/1
(Dissolved)
Acute SW, µg/1
(Dissolved)
Chronic SW, µg/l
(Dissolved)
Arsenic
340
150
69
36
Beryllium
65
6.5
---
---
Cadmium
Calculation
Calculation
40
8.8
Chromium III
Calculation
Calculation
---
---
Chromium VI
16
11
1100
50
Copper
Calculation
Calculation
4.8
3.1
Lead
Calculation
Calculation
210
8.1
Nickel
Calculation
Calculation
74
8.2
Silver
Calculation
0.06
1.9
0.1
Zinc
Calculation
Calculation
90
81
Table 1 Notes:
FW= Freshwater, SW= Saltwater
Calculation = Hardness dependent standard
Only the aquatic life standards listed above are expressed in dissolved form. Aquatic life
standards for Mercury and selenium are still expressed as Total Recoverable Metals due to
bioaccumulative concerns (as are all human health standards for all metals). It is still necessary
to evaluate total recoverable aquatic life and human health standards listed in 15A NCAC
213.0200 (e.g., arsenic at 10 µg/l for human health protection; cyanide at 5 µg/L and fluoride at
1.8 mg/L for aquatic life protection).
Table 2. Dissolved Freshwater Standards for Hardness -Dependent Metals
The Water Effects Ratio (WER) is equal to one unless determined otherwise under 15A
NCAC 02B .0211 Subparagraph (11)(d)
Metal
NC Dissolved Standard, µg/I
Cadmium, Acute
WER* 11.136672-[ln hardness](0.041838)} eA10.9151 [In hardness]-3.1485}
Cadmium, Acute Trout waters
WER* {1.136672-[ln hardness](0.041838)} of 0.9151[In hardness]-3.6236}
Cadmium, Chronic
WER* {1.101672-[ln hardness](0.041838)} e^{0.7998[ln hardness]-4.4451}
Chromium III, Acute
WER*0.316 e^{0.8190[ln hardness]+3.7256}
Chromium III, Chronic
WER*0.860 e^{0.8190[ln hardness]+0.6848}
Copper, Acute
WER*0.960 e^{0.9422[ln hardness]-1.7001
Copper, Chronic
WER*0.960 e^{0.8545[In hardness]-1.7021
Lead, Acute
WER*{1.46203-[ln hardness](0.145712)1 • of 1.273[ln hardness]-1.4601
Lead, Chronic
WER* {1.46203-[ln hardness](0.145712)1 • of 1.273[ln hardness]-4.705}
Nickel, Acute
WER*0.998 e^{0.8460[ln hardness]+2.255}
Nickel, Chronic
WER*0.997 e-10.8460[ln hardness]+0.0584}
Page 1 of 4

Permit No. NCO024937
Silver, Acute
WER*0.85 • e^{1.72[ln hardness]-6.59}
Silver, Chronic
Not applicable
Zinc, Acute
WER*0.978 e^{0.8473[ln hardness]+0.8841
Zinc, Chronic
WER*0.986 e-10.8473[ln hardness]+0.8841
General Information on the Reasonable Potential Analysis (RPA)
The RPA process itself did not change as the result of the new metals standards. However, application of
the dissolved and hardness -dependent standards requires additional consideration in order to establish the
numeric standard for each metal of concern of each individual discharge.
The hardness -based standards require some knowledge of the effluent and instream (upstream) hardness
and so must be calculated case -by -case for each discharge.
Metals limits must be expressed as `total recoverable' metals in accordance with 40 CFR 122.45(c). The
discharge -specific standards must be converted to the equivalent total values for use in the RPA
calculations. We will generally rely on default translator values developed for each metal (more on that
below), but it is also possible to consider case -specific translators developed in accordance with
established methodology.
RPA Permitting Guidance/WOBELs for Hardness -Dependent Metals - Freshwater
The RPA is designed to predict the maximum likely effluent concentrations for each metal of concern,
based on recent effluent data, and calculate the allowable effluent concentrations, based on applicable
standards and the critical low -flow values for the receiving stream.
If the maximum predicted value is greater than the maximum allowed value (chronic or acute), the
discharge has reasonable potential to exceed the standard, which warrants a permit limit in most cases. If
monitoring for a particular pollutant indicates that the pollutant is not present (i.e. consistently below
detection level), then the Division may remove the monitoring requirement in the reissued permit.
1. To perform a RPA on the Freshwater hardness -dependent metals the Permit Writer compiles the
following information:
• Critical low flow of the receiving stream, 7Q10 (the spreadsheet automatically calculates
the 1 Q 10 using the formula 1 Q 10 = 0.843 (s7Q 10, cfs) 0.993
• Effluent hardness and upstream hardness, site -specific data is preferred
• Permitted flow
• Receiving stream classification
In order to establish the numeric standard for each hardness -dependent metal of concern and for
each individual discharge, the Permit Writer must first determine what effluent and instream
(upstream) hardness values to use in the equations.
The permit writer reviews DMR's, Effluent Pollutant Scans, and Toxicity Test results for any
hardness data and contacts the Permittee to see if any additional data is available for instream
hardness values, upstream of the discharge.
If no hardness data is available, the permit writer may choose to do an initial evaluation using a
default hardness of 25 mg/L (CaCO3 or (Ca + Mg)). Minimum and maximum limits on the
hardness value used for water quality calculations are 25 mg/L and 400 mg/L, respectively.
If the use of a default hardness value results in a hardness -dependent metal showing reasonable
potential, the permit writer contacts the Permittee and requests 5 site -specific effluent and
upstream hardness samples over a period of one week. The RPA is rerun using the new data.
Page 2 of 4

Permit No. NCO024937
The overall hardness value used in the water quality calculations is calculated as follows:
Combined Hardness (chronic)
_ (Permitted Flow, cfs *Avg. Effluent Hardness, mg/L) + WOW, cfs *Avg. Upstream Hardness, ma/L)
(Permitted Flow, cfs + s7Q10, cfs)
The Combined Hardness for acute is the same but the calculation uses the 1Q10 flow.
3. The permit writer converts the numeric standard for each metal of concern to a total recoverable
metal, using the EPA Default Partition Coefficients (DPCs) or site -specific translators, if any
have been developed using federally approved methodology.
EPA default partition coefficients or the "Fraction Dissolved" converts the value for
dissolved metal at laboratory conditions to total recoverable metal at in -stream
ambient conditions. This factor is calculated using the linear partition coefficients
found in The Metals Translator: Guidance for Calculating a Total Recoverable
Permit Limit from a Dissolved Criterion (EPA 823-B-96-007, June 1996) and the
equation:
_Cdiss - I
Ctotal I + f [Kpo] [ss(i+a)] [10 6]
Where:
ss = in -stream suspended solids concentration [mg/1], minimum of 10 mg/L used,
and
Kpo and a = constants that express the equilibrium relationship between dissolved
and adsorbed forms of metals. A list of constants used for each hardness -dependent
metal can also be found in the RPA program under a sheet labeled DPCs.
4. The numeric standard for each metal of concern is divided by the default partition coefficient (or
site -specific translator) to obtain a Total Recoverable Metal at ambient conditions.
In some cases, where an EPA default partition coefficient translator does not exist (le. silver), the
dissolved numeric standard for each metal of concern is divided by the EPA conversion factor to
obtain a Total Recoverable Metal at ambient conditions. This method presumes that the metal is
dissolved to the same extent as it was during EPA's criteria development for metals. For more
information on conversion factors see the June, 1996 EPA Translator Guidance Document.
5. The RPA spreadsheet uses a mass balance equation to determine the total allowable concentration
(permit limits) for each pollutant using the following equation:
Ca = (s7Q10 + Qw) (Cwgs) - (s7Q10) (Cb)
Qw
Where: Ca = allowable effluent concentration (µg/L or mg/L)
Cwqs = NC Water Quality Standard or federal criteria (µg/L or mg/L)
Cb = background concentration: assume zero for all toxicants except NH3* (µg/L or mg/L)
Qw = permitted effluent flow (cfs, match s7Q10)
s7Q10 = summer low flow used to protect aquatic life from chronic toxicity and human
health through the consumption of water, fish, and shellfish from noncarcinogens (cfs)
* Discussions are on -going with EPA on how best to address background concentrations
Flows other than s7Q10 may be incorporated as applicable:
IQ10 = used in the equation to protect aquatic life from acute toxicity
Page 3 of 4

Permit No. NC0024937
QA = used in the equation to protect human health through the consumption of water,
fish, and shellfish from carcinogens
30Q2 = used in the equation to protect aesthetic quality
The permit writer enters the most recent 2-3 years of effluent data for each pollutant of concern.
Data entered must have been taken within four and one-half years prior to the date of the permit
application (40 CFR 122.21). The RPA spreadsheet estimates the 95th percentile upper
concentration of each pollutant. The Predicted Max concentrations are compared to the Total
allowable concentrations to determine if a permit limit is necessary. If the predicted max exceeds
the acute or chronic Total allowable concentrations, the discharge is considered to show
reasonable potential to violate the water quality standard, and a permit limit (Total allowable
concentration) is included in the permit in accordance with the U.S. EPA Technical Support
Document for Water Quality -Based Toxics Control published in 1991.
7. When appropriate, permit writers develop facility specific compliance schedules in accordance
with the EPA Headquarters Memo dated May 10, 2007 from James Hanlon to Alexis Strauss on
40 CFR 122.47 Compliance Schedule Requirements.
The Total Chromium NC WQS was removed and replaced with trivalent chromium and
hexavalent chromium Water Quality Standards. As a cost savings measure, total chromium data
results may be used as a conservative surrogate in cases where there are no analytical results
based on chromium III or VI. In these cases, the projected maximum concentration (95th %) for
total chromium will be compared against water quality standards for chromium III and
chromium VI.
9. Effluent hardness sampling and instream hardness sampling, upstream of the discharge, are
inserted into all permits with facilities monitoring for hardness -dependent metals to ensure the
accuracy of the permit limits and to build a more robust hardness dataset.
10. Hardness and flow values used in the Reasonable Potential Analysis for this permit included:
Parameter
Value
Comments (Data Source)
Average Effluent Hardness (mg/L)
[Total as, CaCO3 or (Ca+Mg)]
77.53
Average from June 2018 to
November 2022 samples
Average Upstream Hardness (mg/L)
[Total as, CaCO3 or (Ca+Mg)]
83.81
Average from June 2018 to
November 2022 samples
7Q10 summer (cfs)
3.4
Historical; Previous Fact Sheet
1 Q 10 (cfs)
2.84
Calculated in RPA
Permitted Flow (MGD)
20.0
NPDES Files
Date: 1/13/2023
Permit Writer: Nick Coco
Page 4 of 4

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Coco, Nick A
From: Sypolt, Shannon <[e-mail]>
Sent: Monday, February 13, 2023 4:08 PM
To: Coco, Nick A
Cc: Montebello, Michael J; Macomber, Maggie; Lockler, Joseph
Subject: RE: [EXT]RE: [External] RE: Additional Information Request: Irwin & Sugar Creek NPDES Permit
Renewal Applications
Follow Up Flag: Follow up
Flag Status: Flagged
CAUTION: External email. Do not click links or open attachments unless you verify. Send all suspicious email as an attachment to
Report Spam.
Hi Nick,
Per you request below and pertaining to confirmation that our application remains accurate, to the best of our
knowledge, no additional parameters have been sampled for since our original application was submitted. Therefore no
additional parameters have been identified in the effluent and no chemical addendum sheets are necessary. Thank you.
Shannon Sypolt
Water Quality Program Administrator
Environmental Management
CHARLOTTE W6TER
4222 Westmont Drive / Charlotte, NC 28217
P: 704-336-4581 / C: 704-634-6984 / charlottewater.org
From: Coco, Nick A <[e-mail]>
Sent: Monday, February 6, 2023 3:59 PM
To: Sypolt, Shannon <[e-mail]>
Cc: Montebello, Michael J<[e-mail]>; Macomber, Maggie
<[e-mail]>; Lockler, Joseph <[e-mail]>
Subject: [EXT]RE: [External] RE: Additional Information Request: Irwin & Sugar Creek NPDES Permit Renewal Applications
Hi Shannon,
Thank you for getting this to us and thank you for the call last week to discuss the status of these permits.
To justify that the application remains accurate with regard to which parameters have been sampled for at each of these
facilities, please verify that no additional parameters have been sampled for, before or after the application was
submitted, and therefore no additional parameters have been identified in the effluents of each plant and no chemical
addendum sheets are necessary.
Thanks again,

Nick Coco, PE (he/him/his)
Engineer ///
NPDES Municipal Permitting Unit
NC DEQ/ Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617
ir. DE Q:>
NORTH CAROLINA
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.
From: Sypolt, Shannon<[e-mail]>
Sent: Friday, February 3, 2023 4:57 PM
To: Coco, Nick A <[e-mail]>
Cc: Montebello, Michael J<[e-mail]>; Macomber, Maggie
<[e-mail]>; Lockler, Joseph<[e-mail]>
Subject: [External] RE: Additional Information Request: Irwin & Sugar Creek NPDES Permit Renewal Applications
CAUTION: External email. Do not click links or open attachments unless you verify. Send all suspicious email as an attachment to
Report Spam.
Hi Nick,
Per your request below please see the following additional information:
1) Please see the attached monitoring frequency reduction request summary for Irwin and Sugar Creek
2) 1 have confirmed with our Pretreatment Program Supervisor that no SIU's in our Pretreatment Program have
been sampled for 1,4 Dioxane. Additionally, we have not collected any 1,4 Dioxane samples from Irwin,
Sugar, or McAlpine.
3) Regarding the chemical addendum submission, Charlotte Water believes we have met the requirement
needed to properly submit this information as outlined on NCDWR's website and we have previously
certified our application as being true, accurate, and complete. Please see the information below that we
are referring to:

DES Individual Permit Applicz X l SIL 2018-5 (5B 99) X I +
i deq.nc.gov/about/divisions/water-resources/water-quality-permitting/npdes-wastewater/npdes-permitting-process/npdes-indiv
man uracruring, vuarer Ireacmenr rlanrs,etc.). Iryou area ppiying for a Nt-ut--iuenerat
click the link found on side bar to the right. Please make sure your application is comr
submission.
Please submit 1 original and 2 copies of your application package to the following mai
Division of Water Resources
Water Quality Permitting Section - NPDES
1617 Mail Service Center
Raleigh, NC 27699-1617
EPA Updates -All EPA applications below have been updated. As of February 1, 2020, F
any previous versions and use the updated forms below. Tips for filling out the new ap
can be found here. If you completed an application priorto Feburary 1, 2020, please cc
and attach it as an addendum to your application.
Chemical Addendum Form- As required by Session Law 2018-5, Senate Bill 99, Sectioi
applicantshall nowsubmit documentation of any additional pollutants forwhich ther
methods with the permit application if their discharge is anticipated. The list of pollute
found in 40 CFR Part 136, which is incorporated by reference. If there are additional po
certified methods to be reported, please submit the Chem !cat Addend um to NPDES Af
with you rapplication and, if applicable, list the selected certified analytical method us
no additional pollutants to report, this form is not required to be included with your a
requirement applies to all NPDES facilities. The Chemical Addendum to NPDESApplic
required for any type of facility with an NPDES permit; depending on whether those ty
are found in your wastewater.

6.2
Certification 5fatement
l oerfify tinder penalty of faw that this document and alf affachments were prepared under my direction or supervision in
accordance with a system designed to assure that qualified personnel property gather and evaluate the informafion
submitted. Based on my inquiry of the person orpersons who manage the sysforn, or those persons directly responsible
for gathering the information, the informafion submiffed is, to the hest of my knowledge and belief, true, accurate, and
complete. f am aware that there are significant penalties for submfltfng false information, including the possibility of fine
and imprisonment for knoWng violations.
Name (print or type first and last name)
Official Lille
—SnC6t)D--1KJ e A.---J,:h,'LfL
-!)OpUI I Y2.i-C
Signature
Date signed
C-� A
If you have any questions concerning the information contained in this email, or if you need any further information, just
let me know. Thank you for the opportunity to provide this additional information. Happy Friday!!!
Respectfully,
Shannon Sypolt
Water Quality Program Administrator
Environmental Management
CHARLOTTE 1tTER
4222 Westmont Drive / Charlotte, NC 28217
P: 704-336-4581 / C: 704-634-6984 / charlottewater.org
From: Coco, Nick A <[e-mail]>
Sent: Friday, January 13, 2023 1:50 PM
To: Sypolt, Shannon<[e-mail]>
Cc: Montebello, Michael J <[e-mail]>
Subject: [EXT]RE: [External] RE: [EXT]Additional Information Request: NCO024970 McAlpine Creek NPDES Permit
Application
Hi Shannon,
I hope all is well.
I'm making good progress on the 3 renewals for McAlpine Creek WWMF, Irwin Creek WWTP and Sugar Creek WWTP. I
was hoping you could just provide me with the monitoring frequency reduction request and criteria check for the Irwin
and Sugar Creek plants. I also wanted to clarify the chemical addendum. We will need the addendum for each of these
facilities. I know that you had mentioned that the addendum was not necessary since no additional monitoring had been
conducted, but we will need that written on the chemical addendum form and signed (anywhere on the form will do). If
no additional sampling was conducted, you can just note that no additional sampling was conducted and therefore no
additional parameters were identified.

One last question I have is related to 1,4-dioxane. Has Charlotte Water conducted any monitoring of 1,4-dioxane at
these 3 plants? It appears that each facility has at least one industry type linked to use of 1,4-dioxane in their
pretreatment programs.
Thanks in advance for your time and help on this,
Nick Coco, PE (he/him/his)
Engineer ///
NPDES Municipal Permitting Unit
NC DEQ/ Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617
ir. D, E
ti;
NORTH CAROLINA
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.
From: Sypolt, Shannon<[e-mail]>
Sent: Tuesday, October 4, 2022 10:00 AM
To: Coco, Nick A <[e-mail]>
Cc: Macomber, Maggie <[e-mail]>; Lockler, Joseph <[e-mail]>;
Montebello, Michael J<[e-mail]>; Jarrell, Jackie <[e-mail]>; Smith, Reid
<[e-mail]>
Subject: [External] RE: [EXT]Additional Information Request: NCO024970 McAlpine Creek NPDES Permit Application
CAUTION: External email. Do not click links or open attachments unless you verify. Send all suspicious email as an attachment to
Report Spam.
Good morning Nick,
Please see the following responses, and their associated attached documents, for the information that you have
requested in your email below:
1. Please see the five attached PPA's that were completed since McAlpine's last permit renewal. Although
McAlpine's permit only required three PPA's be performed during the last permit cycle, CLTWater conducts
PPA's annually at all of our facilities.
2. Our biosolids permit number is WQ0000057.
3. The estimated average daily volume of I&I is 4.176 MGD.
4. McAlpine WWMF would like to continue reduced monitoring frequencies (2x/week) for conventional
parameters. Please see the attached spreadsheet that demonstrates McAlpine WWMF has met all the
requirements for reduced monitoring frequencies as an "Exceptionally Performing Facility".

5. To the best of our knowledge, all samples collected at McAlpine WWMF that are covered under a method listed
in 40 CFR Part 136 and run by a state certified lab, have been reported to NCDWR on our monthly DMR's. No
additional pollutants with methods listed in 40 CFR Part 136 have been analyzed, therefore, the Chemical
Addendum form was not submitted in our application.
6. Per your request, please see the attached CLTWater Mercury Minimization Plan.
7. The treatment unit components list submitted in our permit application is accurate and represents all
permanent treatment units currently present at McAlpine.
If you have any questions concerning the information contained in this email, or if you need any additional information,
please feel free to contact me directly. Thank you for your assistance with the renewal of McAlpine's NPDES permit.
Respectfully,
Shannon Sypolt
Water Quality Program Administrator
Environmental Management
CHARLOTTE W6TER
4222 Westmont Drive / Charlotte, NC 28217
P: 704-336-4581 / C: 704-634-6984 / charlottewater.org
From: Coco, Nick A <[e-mail]>
Sent: Tuesday, September 13, 2022 11:47 AM
To: [e-mail]
Cc: Jarrell, Jackie <[e-mail]>; Montebello, Michael J <[e-mail]>
Subject: [EXT]Additional Information Request: NC0024970 McAlpine Creek NPDES Permit Application
Hi Kim,
I hope all is well on your end.
I have begun reviewing the NPDES renewal application for NC0024970 McAlpine Creek WWTP and have the following
comments:
1. Please provide the 3 effluent pollutant scans taken during this permit period.
2. Please provide the permit number associated with Charlotte Water's sludge disposal agreement with Synagro.
3. Please provide the estimated average daily volume of I&I. It appears this wasn't noted on the attachment or in
the application.
4. Charlotte Water was granted 2/week monitoring for BOD, ammonia, TSS and fecal coliform based on 2012 DWR
Guidance Regarding the Reduction of Monitoring Frequencies in NPDES Permits for Exceptionally Performing
Facilities. The renewal application does not include a request for continuation of this monitoring frequency
reduction. If this is a mistake, and Charlotte Water would like to continue 2/week monitoring for these
parameters, please submit a request to continue this requirement and include confirmation of the approval
criteria outlined in the attached guidance document.
5. As required by Session Law 2018-5, Senate Bill 99, Section 13.1(r), every applicant shall now submit
documentation of any additional pollutants for which there are certified methods with the permit application if
their discharge is anticipated. The list of pollutants may be found in 40 CFR Part 136, which is incorporated by
reference. If there are additional pollutants with certified methods to be reported, please submit the Chemical
Addendum to NPDES Application table with your application and, if applicable, list the selected certified
analytical method used. If there are no additional pollutants to report, this form is not required to be included
with your application. This requirement applies to all NPDES facilities. The Chemical Addendum to NPDES

Application will be required for any type of facility with an NPDES permit, depending on whether those types of
pollutants are found in your wastewater. Please fill out, sign and submit the Chemical Addendum to NPDES
Application.
6. Please provide a copy of the Mercury Minimization Plan prepared for this facility, per Special Condition A.(10) of
the current permit.
7. Please verify the accuracy of this component list for the McAlpine Creek WWTP:
• F law equaii7aflon
+ 4crocning
• Grii rr.moval
■ Nmary clan IbLrs
# IAardtiorl bwins
a 9.ecoMary clarifiers
■ Biolplical and chemical phoupherub,rcmavnl
■ Allkrrlizw WJilivn for nit6 i+:xOn
■ Chlrmin�rti�xr
+ Dr�hlorinslion
+ Ana>erobic sludgc digestion
+ Ccntrifugm and gravity sludge thickencm
R.Wd mod filters
Thank you in advance for all of your help with this. If you have any questions for me along the way, please do not
hesitate to reach out.
Best,
Nick Coco, PE (he/him/his)
Engineer 111
NPDES Municipal Permitting Unit
NC DEQ/ Division of Water Resources / Water Quality Permitting
Office: [phone]
[e-mail]
"Email is preferred but I am available to talk by via Microsoft Teams"
Physical Address: 512 North Salisbury St.,Raleigh, NC, 27604
Mailing Address: 1617 Mail Service Center, Raleigh, NC, 27699-1617
DE
NORTH CAROLINA
Department of Environmental Quality
Email correspondence to and from this address is subject to the North
Carolina Public Records Law and may be disclosed to third parties.

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NH3/TRC WLA Calculations
Facility: Sugar Creek WWTP
PermitNo. NC0024937
Prepared By: Nick Coco
Enter Design Flow (MGD): 20
Enter s7Q10 (cfs): 3.4
Enter w7Q10 (cfs): 5.5
Total Residual Chlorine (TRC)
Daily Maximum Limit (ug/1)
s7Q10 (CFS)
3.4
DESIGN FLOW (MGD)
20
DESIGN FLOW (CFS)
31
STREAM STD (UG/L)
17.0
Upstream Bkgd (ug/1)
0
IWC (%)
90.12
Allowable Conc. (ug/1)
19
More stringent than current limit.
Apply limit.
Ammonia (Summer)
Monthly Average Limit (mg NH3-N/1)
s7Q10 (CFS)
3.4
DESIGN FLOW (MGD)
20
DESIGN FLOW (CFS)
31
STREAM STD (MG/L)
1.0
Upstream Bkgd (mg/1)
0.22
IWC (%)
90.12
Allowable Conc. (mg/1)
1.1
Less stringent than current limit. Maintain
Ammonia (Winter)
Monthly Average Limit (mg NH3-N/1)
Fecal Coliform
w7Q10 (CFS)
5.5
Monthly Average Limit:
2001100- DESIGN FLOW (MGD)
20
(If DF >331; Monitor)
DESIGN FLOW (CFS)
31
(If DF<331; Limit)
STREAM STD (MG/L)
1.8
Dilution Factor (DF)
1.11 Upstream Bkgd (mg/1)
0.22
IWC (%)
84.93
Allowable Conc. (mg/1)
2.1
Less stringent than current limit. Maintain
Total Residual Chlorine
1. Cap Daily Max limit at 28 ug/I
to protect for acute toxicity
Ammonia (as NH3-N)
1. If Allowable Conc > 35 mg/l, Monitor Only
2. Monthly Avg limit x 3 = Weekly Avg limit (Municipals)
3. Monthly Avg limit x 5 = Daily Max limit (Non-Munis)
If the allowable ammonia concentration is > 35 mg/L, no limit shall be imposed
Fecal Coliform
1. Monthly Avg limit x 2 = 400/100 ml = Weekly Avg limit (Municipals) = Daily Max limit (Non -Muni)

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United States Environmental Protection Agency
Form Approved.
EPA Washington, D.C. 20460
OMB No. 2040-0057
Water Compliance Inspection Report
Approval expires 8-31-98
Section A: National Data System Coding (i.e., PCS)
Transaction Code NPDES yr/mo/day Inspection Type Inspector Fac Type
1 IN i 2 15 I 3 I NCO024937 I11 121 22/02/22 I17 18 i,. i 19 i G i 201
6
21111111111111111111111111111111111111111111 J
Inspection
Work Days Facility Self -Monitoring Evaluation Rating B1 CA ---------------------- Reserved -------------------
67
72 i n, i 73 LLI74 71
2.0 70 Lis J i 71 1ty, L
J 1 1 1 1 L L j80
Section B: Facility Data
Name and Location of Facility Inspected (For Industrial Users discharging to POTW, also include
Entry Time/Date
Permit Effective Date
POTW name and NPDES permit Number)
09:10AM 22/02/22
17/10/01
Charlotte -Sugar Creek WWTP
5301 Closeburn Rd
Exit Time/Date
Permit Expiration Date
Charlotte NC 28217
12:55PM 22/02/22
22/05/31
Name(s) of Onsite Representative(s)/Titles(s)/Phone and Fax Number(s)
Other Facility Data
William McDonaldAllen/ORC/704-553-2121/
Name, Address of Responsible Official/Title/Phone and Fax Number
Contacted
Angela D Charles,5100 Brookshire Blvd Charlotte NC
282163371 /Di recto r/704-336-5911 / No
Section C: Areas Evaluated During Inspection (Check only those areas evaluated)
Permit 0 Flow Measurement Operations & Maintenar Records/Reports
Self -Monitoring Progran 0 Sludge Handling Dispos Facility Site Review Effluent/Receiving Wate
Laboratory
Section D: Summary of Finding/Comments (Attach additional sheets of narrative and checklists as necessary)
(See attachment summary)
Name(s) and Signature(s) of Inspector(s) Agency/Office/Phone and Fax Numbers Date
Wes Bell DWR/MRO WQ/704-663-1699 Ext.2192/
Signature of Management Q A Reviewer Agency/Office/Phone and Fax Numbers Date
Andrew Pitner DWR/MRO WQ/704-663-1699 Ext.2180/
EPA Form 3560-3 (Rev 9-94) Previous editions are obsolete.
Page#

NPDES yr/mo/day Inspection Type
31 NC0024937 I11 12I 22/02/22 117 18 ICI
Section D: Summary of Finding/Comments (Attach additional sheets of narrative and checklists as necessary)
On -site Representatives:
The following Charlotte Water personnel were in attendance during the inspection: Mr. Billy Allen, Ms.
Donna Slachciak and Mr. Doug Wise.
Page#

Permit: NCO024937 Owner -Facility: Charlotte -Sugar Creek VWVTP
Inspection Date: 02/22/2022 Inspection Type: Compliance Evaluation
Permit
Yes
No
NA
NE
(If the present permit expires in 6 months or less). Has the permittee submitted a new
0
❑
❑
❑
application?
Is the facility as described in the permit?
0
❑
❑
❑
# Are there any special conditions for the permit?
0
❑
❑
❑
Is access to the plant site restricted to the general public?
0
❑
❑
❑
Is the inspector granted access to all areas for inspection?
0
❑
❑
❑
Comment: Charlotte Water implements a Division approved Industrial Pretreatment Program.
The Division received Charlotte Water's renewal package on 12/1/21.
The last compliance inspection (bio-monitoring) at this facility was performed by DWR
-4-- -- ni-1 i)n
Record Keeping
Are records kept and maintained as required by the permit?
Is all required information readily available, complete and current?
Are all records maintained for 3 years (lab. reg. required 5 years)?
Are analytical results consistent with data reported on DMRs?
Is the chain -of -custody complete?
Dates, times and location of sampling
Name of individual performing the sampling
Results of analysis and calibration
Dates of analysis
Name of person performing analyses
Transported COCs
Are DMRs complete: do they include all permit parameters?
Has the facility submitted its annual compliance report to users and DWQ?
(If the facility is = or > 5 MGD permitted flow) Do they operate 24/7 with a certified
operator on each shift?
Is the ORC visitation log available and current?
Is the ORC certified at grade equal to or higher than the facility classification?
Is the backup operator certified at one grade less or greater than the facility
classification?
Is a copy of the current NPDES permit available on site?
Facility has copy of previous year's Annual Report on file for review?
Yes No NA NE
■
❑
❑
❑
■
❑
❑
❑
■
❑
❑
❑
■
❑
❑
❑
■
❑
❑
❑
•
❑
❑
❑
•
❑
❑
❑
•
❑
❑
❑
■ ❑ ❑ ❑
■ ❑ ❑ ❑
■ ❑ ❑ ❑
■ ❑ ❑ ❑
❑ ❑ ❑ ■
Comment: The records reviewed during the inspection were organized and well maintained.
Discharge monitoring reports (eDMRs) were reviewed for the period January 2021
through December 2021. No limit and/or monitoring violations were reported.
Page# 3

Permit: NCO024937
Inspection Date: 02/22/2022
Record Keeping
Owner - Facility: Charlotte -Sugar Creek WWTP
Inspection Type: Compliance Evaluation
Laboratory
Are field parameters performed by certified personnel or laboratory?
Are all other parameters(excluding field parameters) performed by a certified lab?
# Is the facility using a contract lab?
# Is proper temperature set for sample storage (kept at less than or equal to 6.0
degrees Celsius)?
Incubator (Fecal Coliform) set to 44.5 degrees Celsius+/- 0.2 degrees?
Incubator (BOD) set to 20.0 degrees Celsius +/- 1.0 degrees?
Yes No NA NE
Yes
No
NA
NE
•
❑
❑
❑
•
❑
❑
❑
•
❑
❑
❑
•
❑
❑
❑
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❑
■
❑
❑
❑
■
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Comment: Influent and effluent analyses (including field) are performed under Charlotte Water's
Environmental Services Laboratory Certification #192. ETT and ETS (chronic toxicity)
have also been contracted to provide analytical support.
Influent Sampling
Yes
No
NA
NE
# Is composite sampling flow proportional?
■
❑
❑
❑
Is sample collected above side streams?
0
❑
❑
❑
Is proper volume collected?
0
❑
❑
❑
Is the tubing clean?
0
❑
❑
❑
# Is proper temperature set for sample storage (kept at less than or equal to 6.0
■
❑
❑
❑
degrees Celsius)?
Is sampling performed according to the permit?
■
❑
❑
❑
Comment: The subject permit requires influent BOD and TSS composite samples. Facility staff
Perform weekly (at a minimum) aliquot verifications on the sampler.
Effluent Sampling
Is composite sampling flow proportional?
Is sample collected below all treatment units?
Is proper volume collected?
Is the tubing clean?
# Is proper temperature set for sample storage (kept at less than or equal to 6.0
degrees Celsius)?
Is the facility sampling performed as required by the permit (frequency, sampling type
representative)?
Yes No NA NE
■ ❑ ❑ ❑
• ❑ ❑ ❑
• ❑ ❑ ❑
• ❑ ❑ ❑
■ ❑ ❑ ❑
■ ❑ ❑ ❑
Comment: The subject permit requires composite and grab effluent samples. Facility staff
Perform weekly (at a minimum) aliquot verifications on the sampler.
Page# 4

Permit: NCO024937
Inspection Date: 02/22/2022
Owner -Facility: Charlotte -Sugar Creek VWVTP
Inspection Type: Compliance Evaluation
Upstream / Downstream Sampling Yes No NA NE
Is the facility sampling performed as required by the permit (frequency, sampling type, ■ ❑ ❑ ❑
and sampling location)?
Comment:
Operations & Maintenance Yes No NA NE
Is the plant generally clean with acceptable housekeeping? 0 ❑ ❑ ❑
Does the facility analyze process control parameters, for ex: MLSS, MCRT, Settleable ❑ ❑ ❑
Solids, pH, DO, Sludge Judge, and other that are applicable?
Comment: The wastewater treatment facility appeared to be properly operated and well
maintained. Facility staff incorporate a comprehensive process control program with all
measurements being properly documented and maintained on -site. In-depth operation
and maintenance records are also maintained on -site.
Approximately eleven (11) SCADA stations are located throughout the treatment plant
site.
Bar Screens
Yes
No
NA
NE
Type of bar screen
a.Manual
❑
b.Mechanical
Are the bars adequately screening debris?
0
❑
❑
❑
Is the screen free of excessive debris?
0
❑
❑
❑
Is disposal of screening in compliance?
0
❑
❑
❑
Is the unit in good condition?
0
❑
❑
❑
Comment:
Grit Removal
Yes
No
NA
NE
Type of grit removal
a.Manual
❑
b.Mechanical
Is the grit free of excessive organic matter?
0
❑
❑
❑
Is the grit free of excessive odor?
0
❑
❑
❑
# Is disposal of grit in compliance?
0
❑
❑
❑
Comment: Screenings and grit are disposed at a permitted landfill.
Pump Station - Influent Yes No NA NE
Is the pump wet well free of bypass lines or structures? 0 ❑ ❑ ❑
Page# 5

Permit: NCO024937
Inspection Date: 02/22/2022
Owner -Facility: Charlotte -Sugar Creek VWVTP
Inspection Type: Compliance Evaluation
Pump Station - Influent
Yes
No
NA
NE
Is the wet well free of excessive grease?
0
❑
❑
❑
Are all pumps present?
■
❑
❑
❑
Are all pumps operable?
0
❑
❑
❑
Are float controls operable?
0
❑
❑
❑
Is SCADA telemetry available and operational?
0
❑
❑
❑
Is audible and visual alarm available and operational?
❑
❑
0
❑
Comment:
Equalization Basins
Yes
No
NA
NE
Is the basin aerated?
❑
❑
0
❑
Is the basin free of bypass lines or structures to the natural environment?
0
❑
❑
❑
Is the basin free of excessive grease?
0
❑
❑
❑
Are all pumps present?
■
❑
❑
❑
Are all pumps operable?
■
❑
❑
❑
Are float controls operable?
0
❑
❑
❑
Are audible and visual alarms operable?
❑
❑
0
❑
# Is basin size/volume adequate?
0
❑
❑
❑
Comment: The facility is equipped with two twenty (20) million gallon (MG) equalization basins.
Primary Clarifier
Yes
No
NA
NE
Is the clarifier free of black and odorous wastewater?
0
❑
❑
❑
Is the site free of excessive buildup of solids in center well of circular clarifier?
0
❑
❑
❑
Are weirs level?
0
❑
❑
❑
Is the site free of weir blockage?
0
❑
❑
❑
Is the site free of evidence of short-circuiting?
0
❑
❑
❑
Is scum removal adequate?
0
❑
❑
❑
Is the site free of excessive floating sludge?
0
❑
❑
❑
Is the drive unit operational?
0
❑
❑
❑
Is the sludge blanket level acceptable?
0
❑
❑
❑
Is the sludge blanket level acceptable? (Approximately'/4 of the sidewall depth)
0
❑
❑
❑
Comment: Three of four primary clarifiers were in service
Chemical Feed Yes No NA NE
Page# 6

Permit: NCO024937
Inspection Date: 02/22/2022
Owner -Facility: Charlotte -Sugar Creek VWVTP
Inspection Type: Compliance Evaluation
Chemical Feed
Yes
No
NA
NE
Is containment adequate?
0
❑
❑
❑
Is storage adequate?
■
❑
❑
❑
Are backup pumps available?
0
❑
❑
❑
Is the site free of excessive leaking?
0
❑
❑
❑
Comment:
Aeration Basins
Yes
No
NA
NE
Mode of operation
Ext. Air
Type of aeration system
Diffused
Is the basin free of dead spots?
0
❑
❑
❑
Are surface aerators and mixers operational?
0
❑
❑
❑
Are the diffusers operational?
0
❑
❑
❑
Is the foam the proper color for the treatment process?
0
❑
❑
❑
Does the foam cover less than 25% of the basin's surface?
❑
0
❑
❑
Is the DO level acceptable?
0
❑
❑
❑
Is the DO level acceptable?(1.0 to 3.0 mg/1)
0
❑
❑
❑
Comment: Each aeration basin is equipped with an anoxic zone (with mixing) and oxic recycle
system to reduce nutrient levels. Magnesium hydroxide is added to maintain
appropriate alkalinity/pH levels. The foam was greater than 25% of the basin's
surface: however, no foam carryover was observed in the final clarifiers.
Secondary Clarifier
Yes
No
NA
NE
Is the clarifier free of black and odorous wastewater?
0
❑
❑
❑
Is the site free of excessive buildup of solids in center well of circular clarifier?
0
❑
❑
❑
Are weirs level?
0
❑
❑
❑
Is the site free of weir blockage?
0
❑
❑
❑
Is the site free of evidence of short-circuiting?
0
❑
❑
❑
Is scum removal adequate?
0
❑
❑
❑
Is the site free of excessive floating sludge?
0
❑
❑
❑
Is the drive unit operational?
0
❑
❑
❑
Is the return rate acceptable (low turbulence)?
0
❑
❑
❑
Is the overflow clear of excessive solids/pin floc?
0
❑
❑
❑
Is the sludge blanket level acceptable? (Approximately'/4 of the sidewall depth)
0
❑
❑
❑
Comment: All six final clarifiers were in service
Page# 7

Permit: NC0024937
Inspection Date: 02/22/2022
Owner - Facility: Charlotte -Sugar Creek WWTP
Inspection Type: Compliance Evaluation
Pumps-RAS-WAS
Yes
No
NA
NE
Are pumps in place?
■
❑
❑
❑
Are pumps operational?
■
❑
❑
❑
Are there adequate spare parts and supplies on site?
0
❑
❑
❑
Comment:
Filtration (High Rate Tertiary)
Yes
No
NA
NE
Type of operation:
Down flow
Is the filter media present?
❑
❑
❑
Is the filter surface free of clogging?
❑
❑
❑
Is the filter free of growth?
❑
❑
❑
Is the air scour operational?
❑
❑
❑
Is the scouring acceptable?
❑
❑
❑
Is the clear well free of excessive solids and filter media?
❑
❑
❑
Comment: All ten tertiary filters were in service.
Disinfection - UV
Yes
No
NA
NE
Are extra UV bulbs available on site?
0
❑
❑
❑
Are UV bulbs clean?
0
❑
❑
❑
Is UV intensity adequate?
0
❑
❑
❑
Is transmittance at or above designed level?
0
❑
❑
❑
Is there a backup system on site?
0
❑
❑
❑
Is effluent clear and free of solids?
0
❑
❑
❑
Comment:
Flow Measurement - Effluent
Yes
No
NA
NE
# Is flow meter used for reporting?
0
❑
❑
❑
Is flow meter calibrated annually?
0
❑
❑
❑
Is the flow meter operational?
0
❑
❑
❑
(If units are separated) Does the chart recorder match the flow meter?
❑
❑
❑
Comment: The flow meter is calibrated twice per year and was last calibrated on 1/24/22 by
CITI,
LLC
Effluent Pipe
Yes No NA NE
Page# 8

Permit: NCO024937
Inspection Date: 02/22/2022
Owner -Facility: Charlotte -Sugar Creek WWTP
Inspection Type: Compliance Evaluation
Effluent Pipe
Yes
No
NA
NE
Is right of way to the outfall properly maintained?
0
❑
❑
❑
Are the receiving water free of foam other than trace amounts and other debris?
0
❑
❑
❑
If effluent (diffuser pipes are required) are they operating properly?
❑
❑
❑
Comment: The effluent appeared clear with no floatable solids and foam (entrained air). The
foam dissipated less than fifty yards downstream of the discharge outfall.
The
receiving stream did not appear to be negatively impacted.
Solids Handling Equipment
Yes
No
NA
NE
Is the equipment operational?
0
❑
❑
❑
Is the chemical feed equipment operational?
❑
❑
0
❑
Is storage adequate?
❑
❑
■
❑
Is the site free of high level of solids in filtrate from filter presses or vacuum filters?
❑
❑
0
❑
Is the site free of sludge buildup on belts and/or rollers of filter press?
❑
❑
0
❑
Is the site free of excessive moisture in belt filter press sludge cake?
❑
❑
0
❑
The facility has an approved sludge management plan?
0
❑
❑
❑
Comment: The primary sludge and waste activated sludge are pumped separately to the
Charlotte Water/McAlpine Creek WWTP for continued treatment and disposal. The
bio-solids are land applied under the authority of Permit No. W00000057.
Standby Power
Is automatically activated standby power available?
Is the generator tested by interrupting primary power source?
Is the generator tested under load?
Was generator tested & operational during the inspection?
Do the generator(s) have adequate capacity to operate the entire wastewater site?
Is there an emergency agreement with a fuel vendor for extended run on back-up
power?
Is the generator fuel level monitored?
Yes No NA NE
• ❑ ❑ ❑
• ❑ ❑ ❑
• ❑ ❑ ❑
❑ ❑ ❑ ■
■ ❑ ❑ ❑
■ ❑ ❑ ❑
■ ❑ ❑ ❑
Comment: The facility is equipped with three backup generators. The generators are serviced on
a quarterly basis by a contracted company (Carolina CAT).
Page# 9

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Coco, Nick A
From: Sypolt, Shannon <[e-mail]>
Sent: Monday, July 3, 2023 9:44 AM
To: Coco, Nick A
Subject: [External] Sugar Creek WWTP (NC0024937) - CLTWater Response to NCDWR's Request for
Additional Information Regarding Outfall #002
Follow Up Flag: Follow up
Flag Status: Flagged
CAUTION: External email. Do not click links or open attachments unless verified. Report suspicious emails with the Report Message
button located on your Outlook menu bar on the Home tab.
Good morning Nick,
Please see the information that you requested regarding Sugar's Outfall #002 for the completion of the Sugar WWTP
NPDES permit renewal package:
Charlotte Water is requesting that the authorization to discharge from Outfall #002 remain in the Sugar Creek WWTP
(Sugar Creek) NPDES permit. This is to address the approaching need for expanding the facility that will likely occur
within the authorization period of the next permit cycle. In 2007, Charlotte Water began an expansion study and design
that would increase the capacity of Sugar Creek to 28 MGD. This expansion would allow CLTWater to eliminate or
minimize future flow transfers from Sugar Creek to McAlpine Creek WWMF. The design of the expansion to 28 MGD
was stopped at the 90 percent milestone in 2009 due to the downturn in the economy and slowed growth in the flows
to Sugar Creek during that time. Since then, flows have steadily increased. The Sugar Creek expansion report identified
the need for the following facilities to be constructed on the west side of Sugar Creek: two (2) Primary Clarifiers,
Additional Chemical Storage and Feed Facilities, four (4) Aeriation Basins, blower building, two (2) final clarifiers, effluent
filter structure, UV Disinfection Structure, Reclaimed Water Facility, and Cascade Aeration. Charlotte Water's
Wastewater System Master plan was completed in December of 2022 and identified the need for Charlotte Water to
resume planning for the expansion of Sugar Creek. The current and existing facility will continue to operate as Charlotte
Water constructs additional facilities on the western side of Sugar Creek's plant property to increase total capacity to 28
MGD.
Respectfully,
Shannon Sypolt
Water Quality Program Administrator
Environmental Management
CHARLOTTE Wj,TER
4222 Westmont Drive / Charlotte, NC 28217
P: 704-336-4581 / C: 704-634-6984 / charlottewater.org

Characterizing Water Quality Status, Trends and Potential
Watershed Management Opportunities from National Pollutant
Discharge Elimination System (NPDES) Stormwater Data
Final Report
Prepared for:
NC Land & Water Fund (formerly NC Clean Water Management Trust Fund)
Prepared by:
Barbara Doll1°2, PhD, PE
Extension Assistant Professor & Extension Specialist
Jack Kurki-Fox2, PhD, PE
Research Associate
Daniel E. Line2, PE
Extension Specialist
1NC Sea Grant, 2NC State Bio & Ag Engineering
May 2023
NC STATE UNIVERSITY
Bio . • • - - Sea rant
E N G I N E E R I N G • North Carolina

NC STATE UNIVERSITY
Executive Summary
In an effort to identify future monitoring, management and planning decisions to protect and
restore urban stream water quality, NC State University evaluated trends and conducted analysis
and modeling using water quality monitoring data collected by Charlotte -Mecklenburg Storm
Water Services (CMSWS). The analyses focused on data collected during the period of 2007 to
2020. In addition, publicly available data from USGS and Mecklenburg County were also
evaluated. Pollutant concentrations and loads were compared amongst monitoring site locations
and to relevant state water quality standards using simple statistical tools. Point source and
nonpoint source loads were compared in watershed subbasins with larger point source pollutant
contributions. Trend analysis of individual sites were conducted using the US Geological
Survey's WRTDS regression -based statistical package, which accounts for variations in pollutant
loads that are due to time, discharge and season. Two water quality pollutant load tools, the Soil
& Water Assessment Tool (SWAT) and EPA's Spreadsheet Tool for Estimating Pollutant Loads
(STEPL), were used to develop total nitrogen and total phosphorus loads for four stream
monitoring stations to see how model predicted loads compared to the loads estimated from
measured water quality and flow. The SWAT model was used to evaluate potential water quality
implications of increasing urban tree cover. Findings of this effort were used to develop
recommendations for how CMSWS could modify their sampling program to improve the value
of the data for management purposes.
Major wastewater discharges were estimated to account for 75% of the total nitrogen load and
47% of the total phosphorus load in the Charlotte -Mecklenburg study area. Estimates of areal
non -point source loads were generally in the lower range reported from previous studies for
urban areas. Trends in nutrient concentrations were widely variable, decreasing in some areas
and increasing in others. There was not a significant relationship between changes in land cover
and trends in nutrient concentrations. However, the impact of land cover was evident in other
areas as there were significant relationships between land cover and discharge, the number of
bankfull events, and macroinvertebrate metrics.
The SWAT model and STEPL nutrient loading tool produced reasonable estimates for long-term
average annual nutrient loading in watersheds without substantial point sources. However, the
aggregate nature of these tools limits their usefulness outside of largescale planning level
exercises.
The water quality criteria thresholds were exceeded most often for copper and fecal coliform.
The copper criterion was exceeded in —80% of the sites with over 80% of the criteria
exceedances occurring during stormflow. The levels reported for other metals were of less
concern with Nickel, Zinc and Lead never exceeding the standard. Fecal coliform exceeded the
aquatic life standard in about 80% of the samples, which is typical for urban streams. Nitrate
levels were high (>I0 mg/L) in all watersheds that have wastewater treatment plants.
It was possible to predict sediment and nutrient concentrations from continuous water quality
(DO, Turbidity, Specific Conductivity, Temp, and pH) and hydrology (flow, rainfall) variables
Charlotte Water Quality Summary Report
Land and Water Fund

NC STATE UNIVERSITY
with reasonable accuracy (R2 —0.6 to 0.9). However, the goodness of fit varies by site,
constituent, and by the magnitude of the dependent water quality parameter.
The information that can be gained and inferences drawn might be improved by
changes/additions to monitoring programs. There is considerable uncertainty regarding the
estimates of nutrient loading and trends because the calculations are based on monthly grab
samples. Conducting continuous flow -proportional sampling (yielding event mean
concentrations) of stream discharge would greatly improve how well the concentration data
represents actual conditions; however, short of this, increasing the grab sampling frequency
would also help better characterize stream water quality leading to an improved understanding of
loading and trends. This could be achieved by reducing the number of sampling locations. Load
estimates would also be improved by increased sampling during stormflow. Reducing the
number of sampling locations could also improve the quality of the continuous water quality
probes as more resources could be dedicated to calibration and upkeep of fewer probes. To
investigate the source of the very high fecal coliform levels in most streams, bacteria tracing
could be undertaken to determine if fecal contamination originated from pets, wildlife, or people
(septic systems and sanitary sewers). Water quality monitoring of nearby undisturbed (or
minimally disturbed) watersheds could provide a basis of comparison for the values observed in
Charlotte streams and help to assess the effectiveness of restoration.
Charlotte Water Quality Summary Report
Land and Water Fund
2

NC STATE UNIVERSITY
Table of Contents
1 Introduction.............................................................................................................................
5
2 Methods...................................................................................................................................6
2.1 Streamflow Trends...........................................................................................................
8
2.2 Land Cover Trends...........................................................................................................
9
2.3 Weighted Regression on Time, Discharge, and Season ...................................................
9
2.3.1 Load Apportionment...............................................................................................
11
2.4 Soil and Water Assessment Tool Modeling...................................................................
11
2.5 STEPL Loading..............................................................................................................
13
2.6 Characterizing Water Quality.........................................................................................
13
2.6.1 Criteria Exceedance................................................................................................
13
2.7 Macroinvertebrate Data Analysis...................................................................................
14
2.8 Overall Water Quality Snapshot....................................................................................
14
2.9 Predicting Water Quality from Continuous Parameter Measurements ..........................
15
3 Results...................................................................................................................................15
3.1 Land Cover Changes......................................................................................................
15
3.2 Streamflow Trends.........................................................................................................
20
3.2.1 Daily Streamflow....................................................................................................
20
3.2.2 Changes in the Occurrence of Bankfull Flow .........................................................
23
3.3 Water Quality Overview................................................................................................
24
3.4 Water Quality Criteria Exceedance................................................................................
30
3.5 Macroinvertebrates.........................................................................................................33
3.5.1 Regression of Macroinvertebrates and Water Quality Variables ...........................
36
3.6 Overall Water Quality Snapshot....................................................................................
36
3.7 Predicting Water Quality from Continuous Parameters Measurements ........................
38
3.8 WRTDS: Concentration Trends- TN, TP and Nitrate ....................................................
40
3.9 WRTDS-K: Nutrient Loading........................................................................................
46
3.9.1 Total Load Apportionment.....................................................................................
46
3.10 Sediment Loading..........................................................................................................
49
3.11 Watershed Nutrient Loading Predictions.......................................................................
51
3.11.1 STEPL Loads..........................................................................................................
51
3.11.2 SWAT MODEL......................................................................................................
53
Charlotte Water Quality Summary Report
Land and Water Fund
3

NC STATE UNIVERSITY
3.12 Quality Assurance Project Plan(QAPP)........................................................................
54
4 Conclusion............................................................................................................................
56
5 Recommendations.................................................................................................................56
6 References.............................................................................................................................58
7 Appendices............................................................................................................................60
7.1 Appendix A. Load Calculations.....................................................................................
60
7.1.1 Beale Ratio Estimator.............................................................................................
60
7.1.2 Estimated Observed TSS Loads from Continuous Sampling compared to WRTDS-
KTSS loads..........................................................................................................................
61
7.2 Appendix B: Water Quality Regression Equations........................................................
64
7.3 Appendix C: Flow Duration Curves...............................................................................
71
7.4 Appendix D. Water Quality Boxplots............................................................................
73
7.5 Appendix E. Comparison of Continuous Data to Grab Samples ...................................
81
7.5.1 Turbidity.................................................................................................................
81
7.5.2 Specific Conductivity, Dissolved Oxygen and pH .................................................
83
7.5.3 Temperature............................................................................................................
88
7.6 Appendix F. Comparison of WWTP Estimated Loads to DMR Reported Loads.........
89
Charlotte Water Quality Summary Report
Land and Water Fund
4

NC STATE UNIVERSITY
1 Introduction
Properly managing stormwater is one of the most important tasks facing large municipalities.
Stormwater runoff from urban centers can contribute to contamination and impairment of
downstream water bodies by transporting pollutants such as sediment, chemicals, nutrients and
debris. As North Carolina continues to grow and build more dwellings for its expanding urban
populations, the impervious area associated with the expansion of metropolitan areas will also
increase, leading to increased stormwater pollution as well as runoff volume.
Polluted stormwater runoff is commonly transported through municipal separate storm sewer
systems (MS4s) - a conveyance system that can include storm drains, pipes and ditches - and
typically discharged untreated into local water bodies. To prevent harmful pollutants from being
washed or dumped into MS4s, the Clean Water Act was amended in 1990 to require certain
operators (e.g., municipalities) to obtain National Pollutant Discharge Elimination System
(NPDES) permits and develop stormwater management programs (SWMPs). The Phase I
regulation passed in 1990 and required medium and large cities and certain counties with
populations of 100,000 or more to obtain NPDES permit coverage for their stormwater
discharges. In 1999, the NPDES stormwater rules further expanded to smaller urban
communities as well as many public universities, transportation departments, hospitals and
prisons designated as Phase II MS4s. In 1993, the City of Charlotte was issued its Phase I MS4
permit. Later, in 2005, Mecklenburg County and the six towns surrounding Charlotte in the
County were issued a Phase II permit. (USEPA, 2019). To date, the NC Department of
Environmental Quality (DEQ) oversees 109 MS4 Phase II permits that cover 122 urban entities
throughout North Carolina.
Through its NPDES permit, Charlotte -Mecklenburg Storm Water Services (CMSWS) is
responsible for managing the surface water quality of more than 3,000 miles of streams, the
majority of which are designated by the state as "impaired", meaning that they are not clean
enough to support swimming, fishing, or diverse and abundant aquatic life. The impairment is
largely due to the impacts of historical stormwater management practices and urbanization. To
address this impairment, CMSWS has developed and implemented many nationally recognized
innovative surface water quality management programs with a goal of improving the quality and
usability of surface waters including both streams and lakes. As part of their MS4 permit,
CMSWS was required to implement water quality sampling of streams to establish and track
water quality in their permit jurisdiction. Grab samples are collected at 34 streams distributed
throughout the Charlotte -Mecklenburg metropolitan area. The monitoring stations are co -located
with USGS gauging stations. The samples are collected monthly during varied flow conditions;
however, the bulk are collected during baseflow conditions. Almost 15,000 water samples are
collected per year and are routinely screened for 20 different parameters. A Continuous
Monitoring and Alert Notification Network (CMANN) is maintained throughout Charlotte and
Mecklenburg County that is comprised of automated water quality probes (YSI) at 35 locations.
The samplers measure five parameters per hour, 24 hours a day, which totals approximately 1.5
million measurements a year. In addition, macroinvertebrate communities are annually sampled
at 34 locations.
Charlotte Water Quality Summary Report
Land and Water Fund

NC STATE UNIVERSITY
The overall goal of this project was to use Charlotte's extensive water quality datasets in
combination with other publicly available data to identify future monitoring, management and
planning decisions that North Carolina municipalities can employ to better protect and restore
urban stream water quality. A secondary goal was to identify and evaluate various data
assessment tools, approaches and models that municipalities could apply to help track, interpret
and manage water quality data. Specific objectives of the data analyses and modeling effort
include:
1. Identify potential water quality trends over time.
2. Identify predictors of water quality condition (e.g., land use, buffer width, point sources,
BMP density, tree cover density, etc.)
3. Test water quality models and pollutant load calculation tools for use in urban streams
4. Identify shortcomings in the data and potential improvements regarding sampling
locations, frequency or protocols.
2 Methods
Charlotte Mecklenburg Stormwater Services (CMSWS) provided water quality and
macroinvertebrate data from 1990s to 2021 for sites in their monitoring network. However, the
analysis primarily focused on the period of 2007 to 2021 as sampling was more consistent and
comprehensive post 2006. The sites in CMSWS's monitoring network and the type of sampling
methods used are shown in Figure 1 and Table 1. NCSU used the CMSWS water quality data in
conjunction with data from the U.S. Geological Survey, Mecklenburg County GIS, and other
publicly available sources to evaluate trends in streamflow, water quality and land cover,
estimate and model nutrient loads, evaluate relationships between land cover and water quality,
and predict water quality.
Charlotte Water Quality Summary Report
Land and Water Fund
6

NC STATE UNIVERSITY
I�IC 14A
roll
MC17
MY1B
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Monitoring Type
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Japan, METI, Esri China (Hong Kong), swisstopo, © OpenStreetMap
contributors, and the GIS User Community
Figure 1. Site locations and monitoring.
Charlotte Water Quality Summary Report
Land and Water Fund

NC STATE UNIVERSITY
Table 1. Site, USGS flow monitoring coverage and drainage area.
Site
Name
USGS Gage #
USGS Start
Drainage Area (mil)
MC14A
Long Creek near Rhyne, NC
0214291555
1998
31.5
MC17
Paw Creek at Wilkinson Boulevard
0214295600
1994
10.4
MC2
Trib to McDowell Creek
-
-
6.8
MC22A
Irwin Creek Near Charlotte
02146300
1962
30.7
MC25
Coffey Creek near Charlotte
02146348
1998
9.14
MC27
Sugar Creek at NC-51 near Pineville
02146381
1994
63.5
MC29A1
Little Sugar Creek at Medical Center Dr
02146409
1994
11.8
MC30A
Edwards Branch at Sheffield Dr
0214643820
2004
1.03
MC33
Briar Creek Above Colony Rd
0214645022
1995
19
MC36
Tributary to McAlpine Cr
-
-
2.7
MC38
McAlpine Cr at Sardis Rd
02146600
1974
38.6
MC4
McDowell Creek
0214266000
1996
26.3
MC40A
Four Mile Creek nr Pineville
02146670
2018
17.8
MC40C
Four Mile Creek upstream
-
-
4.0
MC42
McMullen Creek at Sharon View Rd
02146700
1962
6.95
MC45
McAlpine Creek below McMullen Creek
02146750
1974
92.4
MC45B
McAlpine Creek at SR-2964
0214676115
2005
95.9
MC47A
Steele Creek at SR-1441
0214678175
1998
6.91
MC49A
Little Sugar Creek at Pineville
02146530
1997
49.2
MC50
Gar Creek at SR-2074 near Croft
0214266080
2002
3.55
MC51
Six Mile Creek near Pineville
0214685800
2007
20.3
MC66
Beaverdam Creek at Windy Gap
0214297160
2003
4.47
MY10
Clarke Creek near Harrisburg, NC
02124080
2003
21.9
MY11B
Mallard Creek below Stony Creek
0212414900
1994
34.6
MY12B
Back Creek at SR1173
02124269
2009
7.45
MY13
Reedy Creek below I-485
0212430293
2007
12.6
MY13A
Reedy Creek at SR 2803
0212427947
2001
2.5
MY14
Duck Creek
-
-
2.5
MY1B
West Branch Rocky Branch
0212393300
2004
20.8
MY713
McKee Creek at SR-2804
0212430653
2007
5.76
MY8
Clear Creek at SR-3183
0212466000
2002
12.6
MY9
Goose Creek at SR-1524
0212467451
2009
8.5
2.1 Streamflow Trends
Trends in streamflow/discharge at each of the USGS gages at the watershed outlets were
evaluated as discharge influences nutrient loading. Several methods were used to evaluate
streamflow trends. First, the daily streamflow trend analysis methods in the USGS's EGRET R
package was employed to identify trends in daily median flow. Second, the USGS Rainmaker R
package was used to delineate individual storm events over the period of continuous (5 to 25
Charlotte Water Quality Summary Report
Land and Water Fund

NC STATE UNIVERSITY
min) streamflow record (varied by site) to determine if the magnitude and number of storm
events is changing over time. The peak discharge for each storm event was then compared to the
bankfull discharge from the regional curve equations for rural areas (Doll et al., 2002) and longer
return period (5-yr, 10-yr, and 25-yr) events based on USGS regional regression equations. The
rural regional curve was used for all sites for two reasons; (1) to evaluate the departure from
`undisturbed' conditions and (2) to provide for a standard basis of comparison.
2.2 Land Cover Trends
Land cover and development trends over the last fifteen years were examined to determine if
recent landuse changes may have impacted in -stream water quality in Mecklenburg County. Two
sources of data were used to examine change in land cover and development trends: The USGS
Land Change Monitoring, Assessment, and Projection Dataset (USGS, 2021) and the Charlotte
Mecklenburg County tax parcel records — the year built in the tax records was used to evaluate
trends. The land cover and parcel data were summarized by catchment for each year and also the
area within the floodplain and within a range of buffer distances from the stream.
2.3 Weighted Regression on Time, Discharge, and Season
The USGS weighted regression on time, discharge, and season regression model (WRTDS) was
used to estimate nutrient loading and evaluate trends in concentration. The WRTDS regression
equation is expressed as:
In(c) _ (30 + F'1t + (32 ln(Q) + (33 sin(21n) + (34 cos(21n) + c
Where c is the concentration, Q is the daily mean discharge, t is time, and betas are regression
coefficients. WRTDS load and concentration estimates can be improved by adding a Kalman
filter, which accounts for the autocorrelation of model residuals.
For accurate WRTDS estimates, water quality samples need to be representative of
concentrations and discharge across the flow duration curve. WRTDS is designed for large water
quality data sets (>200 samples has been suggested) collected over long time periods (>10
years). However, (Rowland et al., 2021) suggested that reliable estimates of concentration and
flux can be obtained from a minimum of 60 samples collected over 10 or more years. In
addition, WRTDS is intended for use in watersheds where the daily mean flow is not
substantially different than the maximum daily flow. Thus, it is not well -suited for small, or
flashy urban watersheds; however, there are no proven methods of estimating load for these
streams with monthly grab samples.
For the most part, samples were well -distributed across the flow duration curves for most of the
sites. For example, flow duration curves with sample results overlain for site MC 14A are shown
in Figure 2. Other sites also indicated a relatively even number of samples collected across the
distribution of flow (Figure 3).
Charlotte Water Quality Summary Report
Land and Water Fund
9

NC STATE UNIVERSITY
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101
LL 10'
101
10,
0 25 50 75 100
Percent Exceedance (%)
Figure 2. MCI4A flow duration curves with TP and TKN sample results.
MC14A MC17 MC22A MC25 MC27
TP (mgJL)
02
0.1
TKN (mg/L)
2.5
2.0
15
10
05
30 -
?0 - ii�l�ll 1�11111�II 11111�1�I 1111111111 IIIIIII■11
0
MC29A1 NIC30A MC33 MC30 MC4
30 -
0
�1■1111� 1�■�I�IIII IIIIIIIIII II�IIIIIII ��11111�11
M C45 MC47A m49. MC50 IAC51
30 -
"1°_ �11111 1111��1111 �I.IIIIII 111�1111111111111111
MC66 MY10 rdY11B NY12B MY13
30 -
20-
10-�i1111111im 11111111111111111111
MY1B MY7B MY8 MY9 0 o00000 0
30 -
20 _ &M I" d" hdIM1
........... ........ 0 o Percent (°%} o ........ 0
Figure 3. Histogram of flow percentile at which grab samples were collected.
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NC STATE UNIVERSITY
WRTDS has been applied by others in non -ideal conditions. For example, Barr and Kalkhoff
(2021) used WRTDS to estimate loading and trends in small (5 to 9.5 mi2), developed
watersheds in Missouri. To help minimize the effect of small watersheds, we removed
catchments of less than 5 mi2 from the analysis. In addition, without more frequent sampling,
there are no methods that have been proven to provide accurate load estimates in flashy
watersheds with only monthly samples. For this study trends were calculated using regular
WRTDS, for load calculations WRTDS-K was used.
2.3.1 Load Apportionment
The WRTDS-K loads were apportioned between wastewater and non -point sources using the
following methods and assumptions. First, the total loads for the catchment with the WWTP and
the nearest upstream catchment were calculated using WRTDS-K. Then the areal export rate for
the upstream catchment was calculated by dividing the total load by the catchment area. Finally,
the WWTP load estimated as:
WWTP load = total catchment load — nearest upstream catchment load
— areal export rate * (total catchment area
— nearest upstream catchment area)
These estimated WWTP loads were also compared the WWTP loads reported in the Discharge
Monitoring Reports (DMR) (see Appendix F)
2.4 Soil and Water Assessment Tool Modeling
SWAT is a process -based, semi -distributed parameter hydrology and water quality model that is
used to simulate the impacts of land use and land management on streamflow and nutrient export
at the catchment scale (Gassman et al., 2007; Neitsch et al., 2011). The watershed is partitioned
into subbasins that are further subdivided into hydrologic response units (HRU) - unique
combinations of land use, soil and land slope in each model subbasin. Runoff and sediment and
nutrient loads are generated at the HRU scale, aggregated at the subbasin tributaries, and routed
downstream through the watershed channel network to produce outputs at a daily time step.
QSWAT, an add -on for QGIS was used to create the SWAT models. Model inputs are included
in Table 2. The SWATplusR R package was used for model calibration. The models were
calibrated to daily streamflow using the USGS gage at the outlet of each catchment. For nutrient
loading, the models were calibrated to the monthly WRTDS-K generated loads. Four catchments
were selected for SWAT modeling: MC14A, MC22A, MY10, and MY11B (Table 3 and Figure
4). These sites represented a range of developed and forested land cover.
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NC STATE UNIVERSITY
Table 2. SWAT Model Inputs
Elevation
Soils
Land Cover
Rainfall
Temperature, Solar
Radiation, Wind
Speed, Relative
Humitidy
Atmospheric
Deposition
Streamflow
Source
Link
NC Emergency
https:Hsdd_nc.gov/
Management Lidar
USDA SSURGO
https://www_nres_usda_gov/wps/portal/nres/
(30m)
detail/soils/survey/?cid=nres 142p2_053627
2016 NLCD (30m)
https://www_mrlc_gov/data
USGS
https://www2.usgs.gov/water/southatlantic/
nc/realtime/rainfall.php
NC State Climate
https:Hclimate.ncsu.edu/
Office
Clean Air Status
https://www_epa_gov/castnet
and Trends
Network
CASTNET
USGS
https://waterwatch.usgs.gov/index.php?id=
real&sid=w ma &r=nc
Table 3..S'WAT Model Properties
Catchment
DA (sq. mi.)
Subbasins
HRUs
Land Cover
MC14A
31.5
19
350
68% Developed
23% Forest
5% Ag
4% other
MC22A
30.7
22
500
88% Developed
8% Forest
4% other
W10
21.8
25
500
3 1 % Developed
46% Forest
17% Ag
6% other
MY11B
34.7
20
500
75% Developed
17% Forest
4% Ag
4% other
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NC STATE UNIVERSITY
Modeled Catchments g+11
♦ USGS Rain Gages
NHD Flowlines
Jr7C14A
I &1
MC22A
4 re .,r`• p
.,xi So E HERE,G F1 US I�nlermap TP.
=e.. NRC �sF J P MEFI. E GM1' H 9 KErpWCREMEN,p E yK E
0 2-5 70 km cap caeca. uses. rao_NPs NRcnN cg aP Ic1�Nadsater
� N� om s y E J p , ME�rls use corn aft al, fat
- o`pens reem�ap o�mr aurora, and y
OMod dCatcdmen�
NLCID Lane cover
0 y .dy Wetlands
Q shrumscrun
Dpen Voter
E=] M ved Eoreat
oHer�apenone
oNay/Haet�re
Evergreen Ehrest
- Emergent Merbapeuaus Wetlands
ODeveloped, Open Space
- Developed, Med Intensity
- Developed, Low Intensity
- Developed, High Intensity
cntti�ataa craps
- Darren Lang
l °n 6ou RzsE - ERE armin. lA9G&lMennap_INtl REME RNRC E
a\ P rrE(ca P un
5- - 70 km NracdN G a ICNPK�ee u�, `,re s ey.
4 1 . '� Esr cntne (fn ng Kon91, [u.rbn seeelMen canted rare,
Figure 4. Rain gage stations used in swat model (left) and NLCD land cover (right).
2.5 STEPL Loading
The US EPA's Spreadsheet Tool for Estimating Pollutant Loads (STEPL version 4.4b) is a
pollutant loading tool for estimating annual nitrogen, phosphorus and sediment loads using
watershed land cover, soils, management, and average annual runoff data.
Land cover for input into the STEPL tool was based on 2016 NLCD land cover and hydrologic
soil group was extracted from 2020 SSURGO soils data. Because the land use categories in
STEPL and the NLCD were not the same, combining and/or re -categorizing was necessary. All
`Forest', `Wetlands', and `Shrub/scrub' areas were combined into a single land use category of
`Forest' for input into STEPL since all three land covers do not generate N and P. Similarly, the
`Water', `Barren', and `Herbaceous' were combined into a `User defined' category. Rainfall data
from the station ` NC-Mecklenburg_Mean' in STEPL was selected, which specified an annual
rainfall of 45 inches and 105 rain days per year.
2.6 Characterizing Water Quality
Water quality was related to land cover and other factors using some simple graphical
techniques. For example, boxplots of water quality results for each site were prepared in relation
to different land cover metrics.
2.6.1 Criteria Exceedance
Water quality results were compared to the North Carolina water quality standards for the
protection of aquatic life and other specific use thresholds. Metals were filtered to only include
dissolved results from 2015 to present as this is when the hardness dependent dissolved aquatic
life criteria was implemented by NCDEQ. To determine if flow impacted criteria exceedance,
each sample was characterized as occurring during stormflow or baseflow. To separate
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NC STATE UNIVERSITY
stormflow and baseflow, a re -scaled LOWESS-smoothed window minima approach was used on
the aggregated hourly streamflow time series for each site.
2.7 Macroinvertebrate Data Analysis
Macroinvertebrate metrics were plotted over time and trends were evaluated. Multivariate
ordination (principal component analysis) methods were employed to identify latent variables
that had an influence on community metrics. In addition, a linear mixed effects model was used
to evaluate if the number of EPT taxa could be predicted from flow and water quality variables.
Predictor variables for each EPT sampling event included: the median and minimum streamflow
over the preceding 30-days, the percent watershed development, and the mean and maximum
water temperature, mean specific conductivity, and turbidity in the preceding 30-days.
2.8 Overall Water Quality Snapshot
Assessing the quality of surface water based solely on concentration/level data is problematic for
several reasons including unaccounted differences in discharge; however, concentration/level
data can provide a quick initial measure of the quality of the stream or river. Further, while
comparisons of single parameters provide valuable information, a method of presenting the
composite conditions at a site is often more insightful when considering overall stream
condition/quality. We propose a possible method of graphically presenting the overall water
quality at a site by aligning "quality" thresholds with a color gradient. The objective of this
approach is to provide additional information to complement the current index used by CMSWS
- the Stream Use -Support Index. To develop this graphical method, concentrations corresponding
to different "quality thresholds" were developed based on literature values (Table 4). Next, the
values were mapped in ArcGIS for each site using custom symbols. The thresholds are
adjustable, and this was only meant as a demonstration of a methodology for presenting a
snapshot of multivariate data in a consumable format.
Table 4. Water quality thresholds used for presenting water quality snapshot.
Parameter
Excellent
Good
Okay
Poor
Problem
Source
TN (mg/L)
<0.6
0.6-1.0
1.0-2.2
2.5-7.5
>7.5
(Mcnett et al., 2009; USGS,
2010)
TP (mg/L)
<0.05
0.05-
0.12
0.12-
0.25
025-0.6
>0.6
(Mcnett et al., 2009; USGS,
2010)
Fecal Coliform
(MPN/100 mL)
<100
100-200
200-400
400-
1000
>1000
NC Standards
Turbidity (NTU)
<10
10-25
25-50
50-100
100
NC Standards
pH
6.5-8.0
6-9
6-9
4-6, 9-
10
<4,>10
NC Standards
DO (m /L)
>8
5-8
5-8
4-5
<4
NC Standards
Temp (°C)
<26
26-27.5
27.5-29
29-32
>32
NC Standards
Copper (# > WQ
criteria)
0
1-2
3-4
5-6
>6
NC Standards
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NC STATE UNIVERSITY
2.9 Predicting Water Quality from Continuous Parameter Measurements
CMSWS currently uses data from their continuous monitoring network (DO, pH, turbidity,
temperature, specific conductivity) and USGS data (flow and rainfall) to predict fecal coliform
levels based on regression equations for selected catchments. We used a similar approach to
develop equations to predict nutrients and sediment for selected watersheds. The lab sample
results were matched with the manual field measurements (DO, Temp, pH, Spec. Cond., and
Turbidity) and stream discharge. In addition, the stream discharge two hours prior to the sample
and the stream discharge at the time of the sample were used to calculate a ratio that indicated if
the hydrograph was rising or falling at the time of the sample. In addition, the rainfall in the 24,
48, and 72 hours preceding the sample was calculated. All the variables were log -transformed. A
stepwise variable selection procedure based on minimizing Akaike Information Criteria was
used.
3 Results
3.1 Land Cover Changes
The total number of structures in each catchment over time is shown in Figure 5 and the structure
density is shown in Figure 6. The area nearer the center of the city indicates substantial
development starting in the 1940s, with development increasing in the 1960s and 1970s. In the
outer suburban catchments, development started to take off in the early 1980s. The maximum
development generally occurred during three periods: The 1960s and 1970s in Charlotte, in the
late 1990s and early 2000s, and in a few sites along the edges of the city (MC17, MY8, MY13,
and MY1B), the peak development has occurred in the last decade. The 2008 housing crisis is
evident as development slowed abruptly around this time in some catchments (e.g., MY11B,
MC14A, and MC51). Development over the last 20 to 30 years has mostly resulted in clearing of
forests with more limited conversion of agriculture to residential areas (Figure 8).
The data extracted from tax parcels allowed for a more granular view of changes that is not
possible using other land cover sources. For example, the total number of structures located in
the floodplain is shown in Figure 9. The most structures located on floodplain parcels are in
catchments developed earliest in the Charlotte area (e.g., MC27, MC49A, MC45). The more
recently developed catchments have less structures in the floodplain (also a much smaller area),
and very little change over the last 15 years. The recent regulations that restrict floodplain
development seem to be limiting this type of building.
While there is likely some inaccuracies with regard to older development and some parcels may
contain multiple structures that were built in different years, the parcel data provides an
opportunity to track development at a much finer scale in terms of overall numbers and spatial
location (Figure 10).
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NC STATE UNIVERSITY
Total Structures
MC14A MC17 MC27 MC4 MC45
8,000 40,000 20,000 00,000
15,000 6,000
30,000 15,000 60,000
10,000 4,000
20,000 10,000 40,000
5,000 2,000 10,000 5,000 20,000
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0© o 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
o ri a m m o" o ri a m m o" o ri a m m o ri o� a m m o ri o ri a m m o ri
m m m m m o o m m m m m o o m m m m m o o m m m m m o o m m m m m o o
RIC47A MC49A
60,000
m 2,000 40,000
0 1,000 20,000
� 0 0
E
o YY10 YY11B
s 6,000 25,000
20,000
4,000 15,000
10,000
F 2,000 5,000
4 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
MY1B
6,000
4,000
2,000
0
MY7B
3,000
2,000
1,000
0
gC50
300
200
100
0
MY12B
6,000
4,000
2,000
C
MY&
3,000
2,000
1,000
0
Year
MC51
15,000
10,000
5,000
0
MY13
6,000
4,000
2,000
0
MY9
3,000
2,000
1,000
0
Figure 5. Total number of structures extracted from county tax data.
Structure Density
MC14A MC17
500 500
400 400
300 300
200 200
100 100
0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
MC47A MC49A
500 500
400 400
% 300 300
m 200 200
3
u 100 100
m
0 0
m
m pY10 MY11B
500 500
400 400
a 300 300
200 200
100 100
� C 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
MY1B MY7B
500 500
400 400
300 300 I
200 00
100 100
0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0
MC27
500
400
300
200
100
0
MC50
500
400
300
200
100
C
MY12B
500
CO
300
200
100
0
MY&
500
400
300
200
100
0
Year
MC4
500
400
300
200
100
0
IYC51
500
400
300
200
100
0
YY13
500
400
300
200
100
0
MY9
500
400
300
200
100
0
Figure 6. Structures density extracted from county tax data.
RIC66
1,500
1,000
500
0--j
YY14
400
200
0
M C45
500
400
300
210
100
0
NC66
500
400
300
200
100
0
MY14
500
400
300
200
100
0
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NC STATE UNIVERSITY
Relative Development
MC14A MC17
1.00 1.10
0.75 0.75
50
0 00-0 0 0 0 0 0 0a 00
0 0 0 0 0 0 0
MC47A MC49A
1.00 1 00
00.50
.75 'I I ` 0.7Flo
5 � 0.zs - �, J o 25
.. JJihIY�l IiY� 1
0.00 0.00
a
m k1Y10 NY11B
.W 1.00 1.10
0.75 11 0.75 1
00
0 0 0 0 0 0 050
0 0 0 0 0 0 0
W 16 11178
1.00 1 00
075 075
0.00 0.00
0 0 0 0 0 0 0 0 0 0 0 0 0 0
MC27 M04 MC45
1.00 1.00 1.00
0.7.7..75
25 025 02500o0 WlL■thiVj00 Go-
00
MC50 k1051 MC66
t00 1.00 1.00
0.75 0.75 0.75
11.25-
O. Flo0.50 +1y ` 0.50
0.00 0.00 ..._.__ill Vtl� 0.00
UY12B KY13 k1Y14
1.00 1.00 1.00
0.75 pp 0.75 0.75
0 25
025
025-
0.00 l �� 0 00 lYJlu�� �� 0 00 �Ld,J l Yl
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
MYB Ill
t00 1.00
075 lI IVYII 075
.0.25
050
00 00 000.00 -
f Year
Figure 7. Relative development over time. A value of one represents the year with the
maximum number of structures built in a given catchment.
Land Cover - Watershed
Back Crook(MY12B) Beaverdam Crook Clarke Crook Clear Crook(MYB) Duck Crook(MY14)
100 100 too 100 100
75 75 75 75 75-
50- 50 50 50 ~� 50
25 25 !� 25 25 25-
0- 0- 0- 0 0
Gar Creek(MC50) Goose Creek(MY9) 111He Sugar Creek(MC49A Long Creek(MC14A) Mallard Creek (MY113)
100 100 109 100 100
75 75 75 75 75
50 50 50 50 5,0
25 l 25 25 25
0 0 9 0 0
McAlpine Creek(MC45) McDowell Creek(MC4) McKee Creek(MY7B) Paw Creek(MC17) Reedy Creek(MY13)
m 100 100 too 100 100
J
75 75 75 75 ------- 75
25 25 25 25 25
f
0 0 0 0 0
Rockyl`Z-r(Ml Six Mile Creek(MC51) Steel a Creek(MC47A) Sugar Creek(MC27)
100 100 100 100
75 75 75 ------- 75
50 50 50 50
25- 25 � 25 25 L
0 J 0 0 0
Year
Figure 8. Land cover breakdown over time by catchment.
Lard Cover
Barren
- Cropland
- ❑eveloped
- Forest
Grass
- Water
Wetlands
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NC STATE UNIVERSITY
100-Year Floodplain Structure Density
MC14A MC17 YC27 MCA MC45
200
100
0
o N v m m o N o N v m m o N o N v m m o N o N v m m o N o N v m m o N
m m m m m o o m m m m m o o m m m m m o o m m m m m o o m m m m m o 0
�E MC47A MC49A AIC50 NC51 MC66
Y
m 200
[] 100
2 0
C
rW
C
o MY10 NY11B KY12B UY13 MY14
m
m
❑ 200
C
W 100
d
o
O N V m m O N O N V m m O N O N V m m O N O N V m m O N O N V m m O N
01 01 01 01 01 o O o1 01 01 01 01 O o 01 01 01 01 01 O O o1 01 01 01 rn O O o1 01 01 01 01 O O
200
100
0
MY1B MY -TB NY8 NY9
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
rn rn m rn rn o o rn rn rn rn m o o rn m rn rn rn o o rn m rn rn rn o 0
N �� � � � � � N N � � Year � N N � � � � � N N
Figure 9. Structure density on parcels located in the 100 year^ floodplain over time.
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18

NC STATE UNIVERSITY
. •;��:•, ,"ire
2000-2010
Figure 10. Spatial representation of development by decade in Mecklenburg County based on
parcel tax records. (Yellow represents existing development for the start of each time period
and red represents new development that occurred during each time period presented)
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NC STATE UNIVERSITY
3.2 Streamflow Trends
3.2.1 Daily Streamflow
Median daily streamflow has increased from 2-10% per year since the early 2000s for a majority
(18/26) of the streams in the Charlotte area (Figure 12). No sites indicated a significant decline in
median daily flow. Five sites indicated a significant increase in maximum daily flow (Figure 13).
The increase in streamflow appear to be related to changes in development (Figure 11), which is
not surprising given that urbanization alters runoff patterns. The changes in median daily
streamflow may also be the result of changes in rainfall. However, the non -uniform changes to
streamflow across the study area likely indicate that changes in discharge are not solely due to
changes in rainfall, but to a combination of factors.
0
f4
6 OD
0
LL
c
V Nr
W
C
Cn N
C
[i3
U
AM
■ MY7B
■ MY12B
■ !f C51
■ MY9
■ MC47A ' MY18
■ MC25' MC14A
■iq&§3'2A
■ MY11 B
■ MYs
a
0 10 20 30 40 50 60
Change in Developed Area 2000 - 2017°Io}
• MY9
• MC50
• MC22A
• 1AC29A1
0 hIC` 1
0 10 20 30 40 50 60
Change in Developed Area 2000 - 2017
Figure 11..S'treamflow trends versus change in development.
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NC STATE UNIVERSITY
} 0 2.5 5 10 Miles
Figure 12. Trends in median daily streamflow.
Trend (% Per Year)
Not Significant
<2.5%
2.5 - 5%
- 5 - 7.5%
- 7.5 - 10%
arge - Change in
-aily Median
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO,'USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), swisstopo, © OpenStreetMap
contributors, and the GIS User Community
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NC STATE UNIVERSITY
0 2.5 5 10 Miles
Trend (% Per Year)
Not Significant
<4 %
4-8%
- 8 - 12%
- 12 - 16%
arge - Change in
ily Maximum
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO,'USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), swisstopo, © OpenStreetMap
contributors, and the GIS User Community
Figure 13. Trends in maximum daily streamflow.
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NC STATE UNIVERSITY
3.2.2 Changes in the Occurrence of Bankfull Flow
The average number of times the flow exceeded the bankfull flow rate (from the Piedmont rural
regional curve (Doll et al., 2002)) was strongly correlated with percent development (r=0.76,
p<0.01). For background, in undeveloped areas bankfull flow is expected to occur about 1.5 to 2
times per year, which is similar to some of the less developed sites (MY10, MY13A, and MC50)
(Figure 14). For the most developed sites the bankfull discharge threshold was exceeded more
than ten times per year on average. This is not to state that overbank flow occurred more than ten
times per year in these systems (these streams are likely incised and enlarged in many cases), but
rather to illustrate that compared to undeveloped areas, the magnitude of channel forming
discharge (i.e. bankfull discharge) occurs substantially more often due to development. A
similar relationship was observed for the 5-, 10-, and 25-year discharges (r>0.44 and p<0.03).
The substantially greater number of bankfull events in developed catchments has been observed
in many other studies (Doll et al., 2020). Of the 17 sites that had a long enough streamflow
record to analyze, 12 sites indicated a significant increase in the number of average annual events
that exceed the bankfull threshold (Figure 15). Some of the sites did indicate a coinciding
increase in developed areas (e.g., MC14A, MC17, MY10, and MY11B). While other sites show
very little change in development, indicating that the changes in streamflow may be more related
to changes in precipitation.
20
N
C
W
-5 1=
M
0
a�
E
D
Z 10
M CPA
M C�2A
MV2
M C47A
W41k
MY�16 rdC�38
MW7
MC'25
MY;2B
MJ8 MYg MC1dA MC�17
M1�13
M
M B M M �i 1
50 75 100
Total Development (NLCD - open, low, med, high) (%)
Figure 14. Number of mean annual bankfull events versus catchment percent development.
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NC STATE UNIVERSITY
MC14A MC17 MC22A MC25 MC27
-100
30 -
-75
20 - • - 50
10- ' • • • • -25
0- pl=U U48 • • • p-vat=0-va 255 •• • • pl=Ufl44 •P-•:sl �0001 .•• • • p-val=UU37 • • -0
-va
MC33
MC32
MC4
MC42
MC45
-100
m 30-
•
•
-75
r 20-
•
m
50
m
10-
m
> O
P-vat=0.039
•
P-va1=0.371
p-va1=U.R3
• •
oval=DAM
• •
p-va1=0.637
m
0 m
o
_
Y
MC47A
MC49A
MC50
MY10
MY11D
�
-100m
30 -
A-
m
•
- 75 --
n 20-
• ,
•
m
- 50 a
10-
• •
• , .
, ,
-25
2 0-
• P- I 0•
-va pt=0.317
P-val=U.C23 •
• P-vaI -DA 3
• p-vat-0.002 •
-0
2000 2005 2010
2C15 2C2C9000 2CC5 2010
2015 202C9CCC 2005 2010 2015
2020
MY1B
MY8
-10C
30
-75
20-
-50
10-
-25
0-
P-vat=0.015
p-va1=9.157 •
• -0
2000 2005 2010 2015 2022000 2005 2010 2015 2C2C
year
Figure 15. Average annual number of bankfull flow exceedance and percent of developed
land in the catchment (red lines). The gray shaded area is the 95% confidence bounds.
3.3 Water Quality Overview
Overall, ambient baseflow water quality concentrations did not raise any major concerns for
most parameters in catchments without WWTP discharges. There was considerable variability in
concentrations observed at each site (Figure 16 through Figure 19 and Appendix D) with the
highest concentrations occurring in stormflow samples. In general, sediment, metals, TP, and
TKN concentrations were correlated with stream discharge at most locations. Nitrate did not
appear to be correlated with discharge (see Figure 20). There did not appear to be any seasonal
patterns nor was there a discernible relationship between median or maximum water quality
concentrations and catchment land use (see Figure 16 through Figure 19 and Appendix D).
Elevated levels of nitrate (>10 mg/1) frequently occurred during baseflow in streams receiving
WWTP effluent. Downstream of the WWTPs. TP and nitrate concentrations tended to decrease
during stormflow due to dilution (e.g., Figure 21).
The pollutant of most concern was fecal coliform bacteria, which is typical for urban streams
(e.g., Peters, 2009). High levels of fecal coliform, in at least some samples, were observed at all
sites, but neither maximum nor median concentrations were correlated with catchment
development. Possible sources of bacteria include wildlife, pets, leaking sewer pipes or septic
systems. Sediment levels also do appear to be a concern, as indicated by peak levels of turbidity
far exceeding the 50 NTU criteria during most storm events. However, particularly in urban
Charlotte Water Quality Summary Report
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24

NC STATE UNIVERSITY
catchments, elevated turbidity can be caused by pollutants other than sediment, as a result,
elevated turbidity is common for streams in developed catchments.
1.25
1 00
D 75
E
0.50
D.25
0.00
— PerrE�� oe„eiopea
T i i t i • t � i � � i< if i
i • t t t i � • i i t
100
75
0
so
Q
25
Site
Figure 16. TP sample results for non-WWTP locations sorted by catchments development.
J
m
rA
Percent Developed
7.5 —
• � i
5.0
2.5 • _ — • . .
00
$ jEL 1�i $ i
75
25
m m m c U m m Qo Q Q Q Q
Site
Figure 17. Nitrate sample results for non- WWTP locations sorted by catchments development.
Charlotte Water Quality Summary Report
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25

NC STATE UNIVERSITY
40000
J
E
0 30000
0
r�
i1
E
0 20000
10000
0
T
Pe rce nt D eve lope d
T
J.�������:
100
75
0
❑
50 2
25
0
N
0
m
a
m m m U m m o Q m Q Q Q
g U U U U U U U U U U U U U
Site
Figure 18. Fecal Coliform sample results for non-WWTP locations sorted by catchment
development.
40
30
10
— Percent Developed
� 1 •
0
m
60
a
m
Q
29-
mm m �U mmo a a Q a
YY������������
Site
Figure 19. Copper sample results for non-WWTP locations sorted by catchment development.
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26

NC STATE UNIVERSITY
0
E
�3
�o
I'
IZ
09
02
7'
-2
25 50 75
Percent Exceedance (%)
25 50 75
Percent Exceedance (%)
25 5o 75
Percent Exceedance (%)
0 25 5o 75 100
Percent Exceedarce (%)
TS5 (mgli-)
zoo
100
Copper(uglL)
20
15
10
5
TP (ni
0.2
0.1
TKN (ri
25
2.0
1.5
10
0.5
Nitrate (mglL)
0.5
04
0.3
0.2
0.1
0 25 50 75 100
Percent Exceedarce (%)
Figure 20. Example of flow duration curves with water quality results showing relationship
between flow and concentration for MC14A.
Charlotte Water Oualitv Summary Report
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27

NC STATE UNIVERSITY
The influence of stramflow conditions on water quality parameters was clearly captured with
the continuous YSI probe data as shown for McMullen Creek in Figure 21. Turbidity increased
while specific conductivity declined during stormflow. Small dips in pH can also be observed
during flow events. Diurnal variation in temperature and dissolved oxygen were also captured
from the continuous monitoring data. Continuous turbidity monitoring also indicated that the 50
NTU water quality standard is likely exceeded during most rainfall events (Figure 22), which is
common for urban streams.
MC42
�
M
N
i0
tC
O
N
0
Date
Figure 21: Specific Conductivity, Turbidity, pH, Dissolved Oxygen and Temperature Data
from YSI Probe versus USGS measured Flow for McMullen Creek (MS 42).
Charlotte Water Quality Summary Report
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28

NC STATE UNIVERSITY
O
MC47A
!an k.lar 'Ray Jul Sep Nov Jan
0
C.
CO
0
C.
to
O a
d
O
CO,
N
4
Figure 22: Turbidity values fi°om YVI probes for .Vteele Creek (MC47A)
MC14A
f,IC17
LIC22A
MC25
MC27
0.3-
•.••
•
.
3-•
P? 0.6r
0.3-R=0A
0.4-R=.986
0.3-R=0.69
R=-0.18
0.2-
0.1-
00 r i .
•
0.1-`Z�
0.3
• 0.1+`
0.12-+'
• • •
+
2
1 •����� '�
0.0
0.0-
0.0
0.0
0-
0 200 400 600 000
0 50 100 150 200
0 250 500 75010001250
0 100 200
300
0 250 500 750 1000
M C29A1
M C30A
MC33
MCM
MC4
0.5-
• '
0.4- +
Q=039
0.4-
. '
R'=0_S
.••
R=072
•
0.3- '
R=0.72
0.4-;R=C.72
0.3.
0.3
. . . •
0.2
+
0.1
0.1 -
0.1
0.1-f
_,
0.1
0.1
0.0-
0.0-00.0-
0.0-,
0 100 200 300 400 500
0 10 20
30
0 100 200 300
0 200 400
600
0 100 200 300 400 500
MC45
MC47A
M C49A
MC50
M051
0.5-
0.4-
•
R; 0.68
0.5-•
0.4-R=0.4$
4-•
3
R=-0.35
1.25-
1.00-
R=0.77
.
•
03 R=0.7 ~ •
0
- 0.2-
0.1
..
. _•
0.3-'
•.3
0.2- %
0.1
. 2-
1
0.75-
0.50
0.25-
.
02- ..k .
•
0.1
~
. +.
0.0
0.0-
0-
0.00
0 560100015002000
0 100 260
0 250 500 750 1000
0 20 40
60
0 100 200 300
MC66
MY10
MY11B
MY12B
MY13
0.4-
.
.
.
1.25-.
0.3-
R=0.54
0.9-h=025
0.3
fj-0.7.
0.4-
R-077
1.00- F2=0.27
0.2-.f
.
0.6 + ••
.
0.3
0.2
0.1
'.p •
.
•
0.3-
0.2
ef �• .
�
0.75-
0.50-+
0.1-I;
•
..
a
0.1
0.25-JR• •
0.0
- -
0.0--
0.0
0.0--
0.00-,
0 25 50 75 100 0 200 400
600
0 250 500 750 1000
0 50 100
0 50 100 150
MY1B
MY76
MYS
MY9
06
0.3
0.75-Rw
0.84
R=049
02
R=0.65
Ri0.15
0.50-
0.4- .
.
�.
0.2-
.
• •
0.25-�
.. %
0.2- • ;
` 0.1=�'••
0.1=
` • •
0.00-
0.0-
0.0
0.0
0 100 200 300
0 20 40 60
80
0 100 200
0 20 40 60
80
Discharge (cfs)
Figure 23. Correlation between TP and streamflow showing negative correlation for sites with
WWTP discharges (MC49A and MC27).
Charlotte Water Quality Summary Report
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29

NC STATE UNIVERSITY
3.4 Water Quality Criteria Exceedance
The acute water quality standards for chromium, lead, zinc, and nickel were not exceeded since
2015 at any of the 28 sites with flow monitoring. The standard for copper was exceeded at most
of the sites (21/28) during the period of 2015 to 2021 (Table 5). Most (-89%) of the exceedances
occurred during stormflow events (Figure 22).
Fecal coliform bacteria levels in about 80% of the samples exceeded the aquatic life standard of
200MPN/100ml. Exceedance of the standard occurred during both stormflow and baseflow
conditions, but was slightly more common during storm flow (88% vs 76%) (Figure 23).
Turbidity exceeded the NC standard of 50 NTU during most storm events, which is typical for
streams in developed areas. Baseflow turbidity levels were generally much lower.
Table 5. Exceedance of Water Quality Criteria
Parameter
Water Quality Exceedance
Co er*
22/28
Zinc*
0/28
Nickel*
0/28
Lead*
0/28
Chromium*
0/28
Fecal Coliform
28/28
Turbidity
28/28
*Acute threshold for dissolved metals
Charlotte Water Quality Summary Report
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30

NC STATE UNIVERSITY
N
I
0 1.5 3 6 Miles
li
Aquatic Life WQ Thresholds
e
Storm Sample
Baseflow Sample
Exceeds standards
WWTP Discharge
rr^" Domestic < 0.1 MGD
'�'A' Municipal > 15 MGD
Copper (site median - ug/L)
< MDL (2.0 ug/L)
2 - 2.5
2.5 - 3
3 - 3.5
3.5 - 4
�4-4.5
Acute WQ Threshold
Exceedance - Copper
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), (c) OpenSt4dtMia�p contributors, and
the GIS User Community
Figure 24. Water quality threshold exceedance and background median concentration for
Copper.
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31

NC STATE UNIVERSITY
ut
Japan, METIsri, EChina (Hang Kong), (c) Open5treetMap contributors, and
the GIS User Community
Figure 25. Water quality threshold exceedance and background median concentration for
Fecal Coliform.
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32

NC STATE UNIVERSITY
3.5 Macroinvertebrates
The sites were all characterized as `Good -Fair' to `Poor' according to the median NC Biotic
Index (NCBU) (Figure 24). The NCBI has declined over the last 10 to 15 years at six of the
sites, there was no significant trend at 18 sites, and a potentially positive trend at one site.
Interestingly, while the NCBI was generally steady or declined, the number of EPT taxa
observed during each sampling has increased at I 1 sites, declined at two and no significant trend
at 12 sites (Figure 25).
NC Biotic Index by year
M014A MC17 MC22A PC25 MC27
8-
7 • . . • ..
5- Mann -Kendall µval-9.194 Mann-Kentlall p~va I-9.626 Mann -Kendall p-1-0.3H Mann -Kendall p-val-O.019 Mann -Kendall p-val-9.229
MC29A1 MC30A MC33 MC39 MC4
3
6
5- Mann -Kendall µval=0.002 Mann -Kendall µvat=a82 Mann -Kendall µval=0423 I.lenn-Kendallp-vat=0. 013 Mann -Kendall µvat=0339
MC42 MC45 MC47A MC49A MC50
C)7 • • • • .
Z fi-
5- Mann -Kendall µvat=0.11a 1.1ann-Kendall µvat=0. 345 Mann -Kendall µval=09C Mann -Kendall µvat=0.779 Mann -Kendall µvat=0204
MC51 MC66 MY10 MY11 B MY12B
6- • ••
5- Mann -Kendall µvat=0.059 Mann -Kendall µval=0.033 Mann -Kendall µva1=0.022 Mann -Kendall µva1=0.13 Mann -Kendall µvat=0 d01
MY13 MY16 MY71] MYO MY9
8-
7 .
5- Mann -Kendall µvat=0.381 Mann -Kendall µ.al=8.124 Mann -Kendall µval=0r • Mann -Kendall µvat=0.506 Mann -Kendall µvat=6.102
o r, o �2 o o �r, o �r, o o �r, o �2
Year
Figure 26. NC Biotic Index by year for all maeroinvertebrate monitoring sites.
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33

NC STATE UNIVERSITY
EPT Taxa by year
MC14A
30 -
Mann-Kentlall p-val- 0 012
20 -
10-
. .
••
0-
MC29A1
30 -
Mann-Kentlall µval= 0.001
20 -
10-
0-
MC42
30 -
Mann -Kendall d_ al =
m2o-
F-
lt lo-
w
o-
MC51
30 -
Mann-Kentlall µveal= 0.031
20 -
10-
. .
0-
MY13
30 -
Mann -Kendall µeel = 0.0�
20 -
10 - .
0-
MC17 MC2 -A MC25 MC27
Mann -Kendall p-va1=0.277 Mann -Kendall p-va1=9.153 Mann -Kendall p-va1=0.153 Mann -Kendall o-val=0.045
MC3OA
MC33
MC3O
MC4
Mann-Kentlall p~va1=O333
Mann-Kentlall µva1=0.002
1Aann-Kentla11 µval=0
Mann-Kentlall µval=-0.015
MC47A
M049A
MC50
M045
Mann -Kendall p.val=0.40fi
Mann -Kendall µval=-0.017
Mann -Kendall o-val=-0.-0OS
�­_Kndall.al
MC66
MY10
MY11B
MY12B
Mann-Kentla 11 Vv I-0043
Mann -Kendall µvet=0.305
Mann-Kentla 11 Vv I-0OUT
Mann-Kentla 11 V-1=0.003
MY1B
MY713
MYB
MY9
Mann-Kentlall o-va1= 0 DO
Menn-Kentlall µvet = 0.197
Mann -Kendall 0-va1 = 0.409
Mann -Kendall 0-va1
= 0.96
.. �, �-, � �, �-,
�•, `" Year
Figure 27. Number of EPTtaxa by year for all macroinvertebrate monitoring sites.
PCA indicated there was not clear separation among the sites based on the watershed impervious
cover percentage or land cover and there appeared to be some change in the relative locations of
sites from year to year (Figure 26). However, the least (e.g., MY8) and most developed (e.g.,
MC27, MC30A) catchments tended to consistently be the greatest distance apart in
multidimensional space; there was substantial overlap for most of the other sites. The first two
principal components explained about 80 to 90% of the variance between the different sites.
PCA for multiple years of data (2015-2020) clustered by site indicated there was again
substantial overlap among most of the sites (Figure 27). There was distinct clustering of a few
sites (MC50, MY8, MC30A, and to some extent MC27). MY8 had the lowest average
impervious cover (<3%), and MC27 and MC30A both have greater than 85% developed land
while MC50 was about 70% developed (mostly low density and open space) but consistently had
some of the best rating for NCBI and EPT taxa. Running PCA on the mean macroinvertebrate
metrics indicated some potential differences in community composition in the least developed
sites relative to the more developed sites (Figure 27).
While PCA indicated some differences in macroinvertebrate community composition for the
sites on the ends of the catchment development spectrum and potentially with the least developed
catchments, the land cover nearest the stream also appeared to be a simpler predictor of species
metrics. For example, the median number of EPT taxa was significantly correlated with the land
Charlotte Water Quality Summary Report
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34

NC STATE UNIVERSITY
cover within a 100 foot buffer adjacent to the stream; increasing development inside the buffer
genrally resulted in lower total EPT taxa (Figure 28).
2015
MC17
-0.4 -
-0.2 0'0 02 0 4 0'6
PC1 (75.1 %)
2017
0.50-
MC50
MY13 M�fl1
0.25
2016
MC14A
0.4 - %___ ?_
MY8 Y B C27
% Impervious
a 02
TOT MC49A pp°1C30A
MC42
%Impervious
low
3
low
mod
0.0-
MC
mod
mod -high
high
N
M04.
med high
high
(L
P 4My10 �
BI
-02
M I M045
P1C5]
sha n M 1B
sim san
-0.4
-0.2 0.0 02 04
PC1 (70.28%)
2018
0.50-
MC27
%Impervious a
11 025 -MY8 M C 14A
low N �1 17
mod C MC33 M�
mod -high N 0.00- TOT_ MC51
high U
4 _131
-025- MC31
sim�rson -0.50- simi5ton
-0'50 -025 0.60 0.25 -0.4 -62 0'0 02
PC1 (58.19%) PC1 (63.03%)
Figure 28. PCA results for maeroinvertebrate indices by individual year.
1.5
1.0
ZIP 0.5
N
a 0.0
-0s
_1-0
-1.5
a
3°
m
N_
N
U
a
°% Impervious
low
mod
mod -high
high
Development
1°w
med
med-high
high
` -04 -02 0.0 02 0.4
PC1 (669%) PC1 (73-43%)
Figure 29. PCA results for macroinvertebrate indices for individual years from 2015-2020 (a)
and for median indices values over the same period (b).
Charlotte Water Quality Summary Report
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35

NC STATE UNIVERSITY
15
10
m
x
a
w
Land Cover - 100 foot Stream Buffer
Developed
Forest
R=—D.55,p=0.014
R=0.46,p=0.05
25 75 100 0 25 50 75 100
Land Cover Percent(%)
Figure 30. Median number of EPT taxa versus land cover in the 100 feet stream buffer.
3.5.1 Regression of Macroinvertebrates and Water Quality Variables
The regression of EPT taxa with water quality and land cover variables did not produce a strong
fit (Marginal R2 / Conditional R2 = 0.07 / 0.68). The r-squared results indicate that the water
quality and flow variables account for less than 10% of the variability in EPT taxa count, while
site -to -site variability accounts for about 60% of the variability. There are likely other variables
that influence the number of EPT taxa that need to be further investigated. In addition, some of
the spread in the EPT data is likely a result of sampling variability.
3.6 Overall Water Quality Snapshot
An example of the overall water quality snapshot is shown in Figure 29. The objective of this
figure is to present a lot of information in an easily consumable format that can be interpreted by
someone without extensive knowledge of water quality (i.e., the greater number darker red slices
of the pie, the worse condition the water quality). According to the figure, fecal coliform is a
concern at all the sites, maximum summer temperature is also a concern at most of the sites as it
generally exceeds the state standard of 30 degrees C. DO is generally good as are pH levels.
These parameters and thresholds are not meant as suggestions, only as an illustration of the
concept.
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36

NC STATE UNIVERSITY
u -1.1do Z.o o miles
I1 1 11
TP
TN
Copper
Temp.
dity Snapshot
enl P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadasler NLOrdnance Survey, Lsn
Japan, METI, Esri China (Hong Kong), (c) OpenSireetMap contributors, and
the GIS User Community
Figure 31. Overall water quality snapshot for average conditions from 2016 to 2020.
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37

NC STATE UNIVERSITY
3.7 Predicting Water Quality from Continuous Parameters Measurements
Multiple linear regression was tested at eight sites. Overall, MLR produced good fits for most of
the parameters tested as dependent variables. Although there was wide variability from site to
site (Table 6, Table 7, and Figure 30). Sediment parameters indicated the best overall fit at all
sites. TP and TN regression quality was variable but produced better fits in sites with higher
concentrations (presence of WWTP). The poorest fit was for nitrate, particularly at sites with
lower concentrations. Nitrate is also the parameter that tended to be least flow dependent. The
regression equations tended to over -predict TN, TP and nitrate at lower concentrations and under
predict values at higher concentrations (Figure 30), however, it is unclear why.
The best combination of variables (as determined by stepwise variable selection using AIC)
varies by site for a given parameter. A common set of variables could also be tested as the
regression fit did not drastically improve as a result of applying the stepwise variable selection
method. See the appendix for equations and results from other sites. The relationships may be
improved or made more accurate by adding more samples at higher flows; the samples primarily
occurred during lower flows relative to peak or near peak storm flows. In addition, better model
fits may be achieved using random forest or predicative models that might be able to better
explain the water quality relationships observed in the data. For example, the multiple linear
regression model fit tended to under -predict for higher concentrations, whereas a more -robust
model that can account for nonlinear behavior may perform better.
Table 6. Summary of the range of r-squared for regression equations.
Parameter
W for MLR
TSS
0.75
— 0.91
SSC
0.65
— 0.9
TP
0.12
— 0.78
TN
035
— 0.75
NOs
0.19
— 0.83
Fecal Coliform
0.59
— 0.71
Table 7. Regression Equations for Predicting Sediment, Nutrient, and Fecal Coliform.
Site
Equations
R2
MC45
logio(TSS) —log i offurb)+logi o(rain24)+Iog i o(flow)+Iog i o(rain72)+Iog i o(flow ratio)+ logio(DO)
0.81
logio(SSC) = logio(Turb)+logio(rain24)+ log io(DO)+logio(rain72)+logio(flow ratio)
0.81
logio(TP) = logio(Turb)+logio(DO)+ logio(flow_ratio)+logio(flow)+logio(SpCond)+ logio(temp)
0.78
logio(TN) = logio(Turb)+logio(DO)
0.58
logio(NO3) = logio(Turb)+logio(Rain48)+ logio(flow ratio)
0.32
logio(Fecal) = log i o(SpCond)+logio(Rain24)+ logio(flow)+ logio(DO)
0.59
MC27
to io TSS to io Turb +lo io rain24 +lo io flow + to io tem
g ( )— g ( ) g ( ) g ( ) g ( P)
0.91
logio(SSC) = logio(Turb)+logio(rain24)+ log io(flow)+logio(rain72)+logio(temp)
0.90
logio(TP) = logio(flow)+logio(rain24)
0.12
logio(TN) = logio(flow)+logio(SpCond)+ logio(flow ratio)+logio(Rain48)+ logio(rain24)
0.75
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38

NC STATE UNIVERSITY
1og10(NO3) = log io(flow)+logio(SpCond)+ logio(flow ratio)+logio(Rain48)+ logio(rain24)
0.83
log10(Fecal)= log 10(turb)+log10(Rain24)+ log10(temp)
0.60
MC14A
logio(TSS) = log io(Turb)+logio(rain24)+logio(flow)+ logio(DO)+log10(rain72)
0.81
logio(SSC) = logio(Turb)+logio(rain24)+ log io(temp)+logio(rain72)+logio(SpCond)
0.86
logio(TP) = logio(flow)+logio(flow ratio)+ logio(temp)+logio(DO)+logio(SpCond)+ logio(Turb)+
0.77
logio(TN) = logio(Turb)+logio(SpCond)+ logio(DO)+logio(temp)
0.65
1og10(NO3) = logio(Turb)+logio(SpCond)+ logio(temp)+ logio(rain24)
0.45
log10(Fecal)= log 10(turb)+1og10(Rain24)+ log 10(temp)+logio(DO)
0.69
MC 17
logio(TSS)- log io(Turb)+logio(rain24)+logio(flow)+ logio(1)0)+1og10(rain72)+logio(flow ratio)
0.82
logio(SSC) = logio(Turb)+logio(rain24)+ logio(flow ratio)+logio(rain48)+logio(SpCond)
0.85
logio(TP) = logio(flow ratio)+ logio(rain24)+logio(DO)+logio(SpCond)+ logio(Turb)
0.76
logio(TN) = logio(Turb)+logio(SpCond)+ logio(DO)+logio(temp)
0.65
log10(NO3) = logio(Turb)+logio(flow)+ logio(flow ratio)+ logio(SpCond)
0.32
log10(Fecal) - log 10(Turb)+lo 10(Rain24)+ to io(DO)
0.69
MC49A
logio(TSS) = log io(Turb)+logio(rain24)+logio(flow)+ logio(DO)+log10(rain72)
0.83
logio(SSC) = logio(Turb)+logio(rain24)+ log io(flow)+logio(rain72)+logio(DO)
0.85
logio(TP) = logio(flow ratio)+ logio(flow)+logio(DO)
0.58
logio(TN) = logio(flow)+logio(SpCond)+ logio(flow ratio)
0.69
log10(NO3) = logio(flow)+ logio(rain72)+ logio(SpCond)
0.72
log10(Fecal)= log 10(Turb)+log10(Rain24)+ logio(DO)+log10(temp)+ logio(SpCond)
0.71
MY1113
logio(TSS) = log io(Turb)+logio(rain24)+logio(flow ratio)
0.75
logio(SSC) = logio(Turb)+logio(rain24)+logio(flow ratio)
0.65
logio(TP) = logio(flow ratio)+ logio(flow)+logio(DO)+logio(Turb)
0.78
logio(TN) = logio(flow)+logio(SpCond)+ logio(flow ratio)+logio(DO)+
0.35
log10(NO3) = logio(flow ratio)+ logio(DO)+ logio(SpCond)+logio(Turb)
0.19
log10(Fecal)= log 10(Turb)+1og10(Rain24)+ logio(DO)+log10(rain48)+ logio(SpCond)+ log10(Rain72)
0.70
MC22A
logio(TSS) = log io(Turb)+logio(rain72)+logio(flow)+logio(SpCond)
0.81
logio(SSC) = logio(Turb)+logio(rain24)+logio(flow)+ logio(rain72)+logio(SpCond)
0.84
logio(TP) = logio(flow)+logio(DO)+logio(Turb)+logio(rain72)+ logio(temp)
0.77
logio(TN) = logio(flow)+logio(SpCond)+ logio(flow ratio)+logio(Turb)
0.60
log10(NO3) = logio(flow ratio)+ logio(flow)+ logio(SpCond)+logio(rain72)
0.53
log10(Fecal)= log 10(Turb)+log10(Rain24)+ logio(DO)+ logio(SpCond)
0.65
Charlotte Water Quality Summary Report
Land and Water Fund
39

NC STATE UNIVERSITY
d
E
Z m
M C49A-TSS
Rsgr = 0.33
0 50 100 150 200 250
O bserved TSS (mgrL)
MC49A-TP °
0.53
0 1 2 3 4
C bserved TP (mg _)
MC49A-NO3 °
B
9 0® °
MC49A-SSC
Rsgr = 0.85
S °
50 100 150 200 250 300
Observed S5C (mgfL)
MC49A-TN
° Rsgr=0o09 ° oB s0 fop O°
° 00
°� ddbb o
5 10 15
Observed TN (mg�L)
M C49A - Fecal Coliform
Rsgr =o .71
� 0
0 5 10 15 0 10000 20000 30033 40000
Observed NC3 (mA) Observed Fecal Culiform (MPNA 00 mL)
Figure 32. Example of fitted vs observed values from MLR equations
3.8 WRTDS: Concentration Trends- TN, TP and Nitrate.
WRTDS trends for flow weighted TN, TP, and nitrate flow -weighted concentrations are
presented in Table 8, Figure 31, Figure 32, and Figure 33. Mean TN concentrations at the stream
monitoring stations ranged from less than 0.53 mg/l in some of the less developed watersheds to
over 15 mg/L in the streams with major WWTP effluent (Figure 31). In catchments with minor
WWTPs, mean concentrations ranged from 1.2 to 7.4 mg/L. The maximum mean concentration
was about 1.3 mg/L in the catchments without WWTPs. Mean values in catchments without
WWTPs did not exceed the `fair' designation for macroinvertebrate health from (Mcnett et al.,
2009), and most of the sites were in the "good" to "excellent'' range. However, not surprisingly,
most of the sites' mean concentrations were greater than the national background level for
streams in undisturbed areas (USGS, 2010).
Trends for TN were only calculated in 13 of the catchments due to the high number of sample
results below the Minimum Detection Limit (this was primarily the result of more than 40% of
TKN results censored at many stations). The WRTDS analysis indicated the change in flow -
weighted concentration ranged from -50 to +50% over the last 15 years, with 4 of the 13 sites
having no statistically significant trend in concentration (Figure 31 and Table 8). Statistically
significant increasing trends were noted in two of the developing northern catchments (MY10,
MY12B) and two of the sites with major WWTPs (MC49A, MC45B).
Charlotte Water Quality Summary Report
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40

NC STATE UNIVERSITY
Mean nitrate flow -weighted concentrations ranged from 0.22 to 0.8 mg/L in the catchments
without major WWTPs. Where WWTPs were present, mean nitrate levels ranged from 5.9 to
15.9 mg/L. In catchments with minor WWTPs, mean concentrations ranged from 0.7 to 7.0 mg/L
(Figure 32). These very high nitrate levels occur because the WWTPs do not have permit limits
for nitrate, only ammonium. Therefore, the treatment plants' primary goal is reducing
ammonium and the most economical way to do this is through nitrification. Most of the sites
without WWTP effluent fell in the `Good to Fair' or better range from Mcnett et al. (2009), with
about a third of the sites in the `Excellent' range. Four of the sites' mean concentrations were
actually below the background level for streams reported by USGS (2010).
The WRTDS calculated trends in nitrate flow -weighted concentration ranged from -66% to
+96% over the past 10 to 15 year of monitoring, with significant positive trends at 11 stations,
negative trends at 8 stations and no detectable trend at 4 stations (Figure 32 and Table 8). For the
most part, the greatest changes in concentration were in areas along the northern and western
suburbs where the most recent development has occurred. Two of the three catchments with
major WWTPs showed increasing (7.5 and 38%) nitrate concentrations.
Total phosphorus mean concentrations ranged from 0.04 to 0.14 mg/L in the catchments without
WWTPs (Figure 33). Mean concentrations were 0.4 to 1.1 in streams with major WWTPs. In
catchments with minor WWTPs, mean concentrations ranged from 0.1 to 0.95 mg/L. The
WWTP impacted sites were generally in the fair to poor range from (Mcnett et al., 2009). Most
of the streams fell below the `Good -Fair' level. Similar to TN, mean concentrations for all sites
were above the national background level for streams (USGS, 2010).
Trends for TP flow -weighted concentrations ranged from -63 to +64%. Concentrations were
decreasing at 12 stations, increasing at 4 stations, and no trend was detectable at 7 stations
(Figure 33 and Table 8). All the sites with WWTPs indicated significant decreasing
concentrations, which may be due to improved treatment processes at the plants.
Overall, only one site indicated significantly increasing concentrations for TN and TP. Five
stations indicated decreasing trends for both constituents. There was not a significant relationship
between change in land cover and the trend in nutrient loads or concentrations for any site.
Charlotte Water Quality Summary Report
Land and Water Fund
41

NC STATE UNIVERSITY
TN (mean - mg/L)
< 0.75
0.75 - 1
1- 1.5
1.5-3
3-5
5-8
>8
TN Trend (06 - 21)
- 75 - 100% Increase
50 - 75% Increase
A25 - 50% Increase
A0 - 25% Increase
0 - 25% Decrease
25 - 50% Decrease
� Y12
17 50 - 75% Decrease
r! Y13A
- 75 - 100% Decrease
1
Y13
Trend Likelihood
33 e
As Likely as Not
I�M 3
� Likely
�
1 Very likely
C38 MYf4,
Highly likely
WWTP
_- Domestic < 0.1 MGD
6
B Municipal > 15 MGD
N
0 2.5 5 10 Miles
WRTDS Results - TN
Concentration
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey; Esri
Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the
GIS User Community
Figure 33. WRTDS results for TN showing mean concentration, the trend in concentration
and the strength of the trend Catchments without trends information did not have enough
data points to run WRTDS or the catchment was less than 5 square miles.
Charlotte Water Quality Charlotte Water Quality Summary
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42

NC STATE UNIVERSITY
Nitrate (mean - mg/L)
< 0.25
0.25 - 0.5
0.5 - 0.75
0.75 -1
1-3
3-5
5-8
8-10
10-16
1
Nitrate Trend (06 - 21 )
- 75 - 100% Increase
50 - 75% Increase
0 25 - 50% Increase
0 0 - 25% Increase
Y12
'7 0 - 25% Decrease
Y13A
'7 25 - 50% Decrease
�J
1
Y13 '
7 50 - 75% Decrease
B
33
-
75 - 100% Decrease
�3
Trend Likelihood
As Likely as Not
MYt'a';0
Likely
A Very likely
Highly likely
r
WWTP
o
Domestic < 0.1 MGD
aOA
"N Municipal > 15 MGD
N
I
10'
0 2.5 5 10 Miles
WRTDS Results -
Nitrate Concentration
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esn
Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the
GIS User Community
Figure 34. WRTDS results for Nitrate showing mean concentration, the trend in
concentration and the strength of the trend Catchments without trends information did not
have enough data points to run WRTDS or the catchment was less than 5 square miles.
Charlotte Water Quality Summary Report
Land and Water Fund
43

NC STATE UNIVERSITY
TP (mean - mg/L)
< 0.05
0.05 - 0.15
M
0.15 - 0.25
I-..,nriatulls
0.25 - 0.5
0.5 - 0.75
c
0.75 -1
',Ww
1 - 1.2
TP Trend (06 - 21)
4
Y
-
75 - 100% Increase
0 50 - 75% Increase
C
0 25 - 50% Increase
Q0 - 25% Increase
MC1
0 - 25% Decrease
17 25 - 50% Decrease
Y12 17 50 - 75% Decrease
M 22A
Y13A ' - 75 - 100% Decrease
Al
r'
Y13 Trend Likelihood
B
,f
33
As Likely as Not
--
M'. 3,
Likely
WW
A Very likely
s
C27
M
C38 MY 'd Highly likely
A
WWTP
M
VIM Domestic < 0.1 MGD
MC47A
k.?
� s
Municipal > 15 MGD
M _5
s
0
r� 40A
a
t'
t
:
N
M
WRTDS Results - TP
I
Concentration
0 2.5
5
10 Miles
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey; Esri
Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the
GIS User Community
Figure 35. WRTDS results for TP showing mean concentration, the trend in concentration
and the strength of the trend Catchments without trends information did not have enough
data points to run WRTDS or the catchment was less than 5 square miles.
Charlotte Water Quality Summary Report
Land and Water Fund
44

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NC STATE UNIVERSITY
3.9 WRTDS-K: Nutrient Loading
3.9.1 Total Load Apportionment
Figure 34 and Figure 35 show the WRTDS-K TN and TP load proportions for each watershed
and the relative contributions coming from non -point sources and WWTPs. TN export rates
ranged from 1 to 7.5 lb/ac/yr (Figure 34). This generally fell in the lower range of studies from
urban and residential areas (Line et al., 2002). The highest export rates were observed for MY10,
which also showed increasing TN and TP concentrations over time, and for MC49A, the most
intensely developed catchment.
TP export rates ranged from 0.14 to 2.0 lbs/ac/yr. The highest export rates generally coincided
with the sites with the higher TN export rates, although correlation between TP and TN was low
(r=0.18) (Figure 35). The export rates were in the range of previously reported values for urban
and residential areas (Line et al., 2002).
The three largest catchments (MC4513, MC27, and MC49A) account for 88% of the total TN
load and 71% of the total TP load for Mecklenburg County (Figure 36). Major WWTP effluent
in these three catchments dominated the nutrient loading. WWTPs were estimated to account for
75% of the TN load and 47% of the TP load for the Charlotte Mecklenburg County study area.
Charlotte Water Quality Summary Report
Land and Water Fund
46

NC STATE UNIVERSITY
MC66
MC4 1 0
<1%,Mcau
'r 144 2441 MY�1B � .
Non -point Source TN Export
Iblacrelyr
�1-2
2-4
4-6
_ 6-8
Total Study Area TN Sources
0)
0 Non -point source TN
- WWTP TN
Other Catchments
MY12Bt1%
MY13
MY7B
L 64 0 f
C45B
,1%
MY91 <1%
<1% l
N TN Loading
MC51 i
Sources. Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
0 1.5 3 6 Miles FAO, NIPS, NRCAN, GeoBase, IGN, Kadaster NIL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), swisstopo. © OpenStreetMap
contributors, and the CIS User Community
Figure 36. Proportion of the Charlotte Mecklenburg study area's entire TN load that is
contributed by each of the 18 watershed catchments including the relative contribution from
non point source and WWTP loads, and non point source TN areal export rates. Percentages
shown are proportion of the total TN load for the study area.
Charlotte Water Quality Summary Report
Land and Water Fund
47

NC STATE UNIVERSITY
MY1
>r
MC4 2°/u
4
MC50
<l%
1
t MY9
54% /
Non -point Source TP Export
Iblacrelyr
< 0.5
0.5 - 1
1 - 1.5
- 1.5-2
Total Study Area TP Sources
f)
Non -point Source TP
- WWTP TP
Other Catchments
1 MfY12B" `
MC17 5%
MY13
< 19;
MY7B
MC66 MC27 -- MC49A 24%
<:I!% MY8
<I°/o
MY9 <1%
1%
MC47A
MC45B 25'i
N '
MC51
.3 3 6 Miles Sources' Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), swisstopo, © OpenStFbetMap
contributors, and the GIS User Community
Figure 37. Proportion of the Charlotte Mecklenburg study area's entire TP load that is
contributed by each of the 18 watershed catchments including the relative contribution from
non point source and WWTP loads, and non point source TP areal export rates. Percentages
shown are proportion of the total TP load for the study area.
Charlotte Water Quality Summary Report
Land and Water Fund
48

NC STATE UNIVERSITY
Total TN Load Total Nitrogen Source
Sim
Creek
IMC271
MCAJpiee
GreBk
(MC45B)
■ WVVrP ■Nonpofnt Source
Total TP Load
a-0.
Coed
tin
McAlpine
Creek
(MC468)
Figure 38. TN and TP load apportionment and non point source — WWTP load breakdown.
3.10 Sediment Loading
Suspended sediment loads are presented in Figure 37. The sediment loads were similar to the
ranges reported by Aulenbach et al. (2022) and Aulenbach et al. (2023) for streams in the Atlanta
area. The loads were not correlated with watershed development or recent changes in
development. However, these estimates have a high degree of uncertainty due to the high number
of samples below the detection limit, which were outside the recommended range for WRTDS.
The locations with the highest SSC export rates (MY1B, MY8) also contain some of the highest
percentage of agricultural land. Other potential sources include streambank erosion and land
disturbance associated with development. As is typical, the highest sediment concentrations were
observed during stormflow (Figure 38).
Charlotte Water Quality Summary Report
Land and Water Fund
49

NC STATE UNIVERSITY
N
MY1 B
MC4�
'MY
10
MC56
MC14A
f
�MC17
MC66
MC47A
I
0 1.252.5 5 Miles
l 1 c i l i i t
Figure 39. SSC sediment export rates.
Sediment Export (SSC)
Ibslacrelyr
- <500
500 - 1000
1000-2000
2000 - 4000
- 4000 - 6000
n Not Calculated
I I",. I
Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS,
FAO, NPS, NRCAN, GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri
Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap'cbntributors, and
the GIS User Community
Charlotte Water Quality Summary Report
Land and Water Fund
50

NC STATE UNIVERSITY
SSC by Storm and Season
MC14A
MC17
MC22A
MC25
YC27
MC29A1
400 -
300-
200 -
100-
•
i
� � -�
. 11 IiI
tb -�L .� -❑
1
_b
.
.
�� � aS ��
• . :
l
�LJ f +� -t
i '
i= • • a
-LJ
MC30A
MC33
MC38
MC4
UC40A
MC42
400 -
300 -
•
•
200 -
100-
t 1- b
• ; •
•�
- +
�� �� -�
-� -� -- -�
l
-+ a ,
0 -B
�b �� �i
�LJ
MC45
MC45B
MC47A
MC49A
MC50
MC51
_400-
Flow
6300-
200-
_
•
•
•
•
base
N100
• •
aG =
•
• i
-b _I
+�
= t�
i_ +�
s:
storm
_
� _- -!
_+ -1
•b -+ +-
�❑ -o
�M •o
�_ �i �3
MC66
NY10
YY71B
uri2B
UY13
YY130k
400 -
300 -
'
200 -
100
• '
n i .
• _ •
' •
i
n - Id
11
rJ
_
,L l�
�
i� JL ;�
�
-a6 ��
_o �i. �8 ��
J iF� j+ ��
i
NY1B
MY7B
MY8
MY9
E -
c E -
400 -
_
E LL
300-
200 -
100-
.
•
.
E d -
E -
LL
E -
d � E LL
E
d � E LL
Storm Sample
Figure 40. SSC concentration by season and flow.
3.11 Watershed Nutrient Loading Predictions
3.11.1 STEPL Loads
STEPL and WRTDS annual TN and TP loads are shown in Figure 39. The difference in STEPL
and WRTDS TN loads ranged from -24% to 80%, with median of 11%. The difference was less
than 30% for 13 of 17 sites. The difference in TP loading ranged from -83% to 82%, with a
median of -1%. Only 10 of 17 sites showed a difference between the WRTDS and STEPL loads
of less than 30%. The differences in STEPL and WRTDS TN and TP export were strongly
correlated (r=0.78). Because there is very little row crops or animal agriculture in these
catchments, the STEPL predicted loads are essentially a function of the urban land in the
catchment (Figure 40).
Charlotte Water Quality Summary Report
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51

NC STATE UNIVERSITY
400,000
350,000
L 300,000
a 250,000
7 200,000
z 150,000
100,000
50,000
0
60,000
50,000
—40,000
30,000
a 20,000
10,000
0
Total Nitrogen: STEPL vs. WRTDS
C 0
c
co
o
�,
N
o
rIn
o
o
co co
c
N
co
CDLO
NIn
n
�i
co r
1
N � M a¢ m M
C C U C C C
C
■STEPL ❑WRTDS
Total Phosphorus: STEPL vs. WRTDS
r
o o p7 co CD
o o co
N ca CO c? C
co
Q CD m Q'] Q U7 r OD CO C7 Q [� CD
C C C C C C
❑STEPL ❑WRTDS
0
Figure 41. Comparison of annual STEPL and WRTDS generated TN and TP loads.
400000
350000
300000
L
a
250000
200000
0
150000
J 100000
50000
0
a STE P L N ❑ STEPL-P
0
Rz = 0.98
Or
D� Rz = 0.86
D.....................{7
® R,, ................
0 10000 20000 30000 40000 50000 60000
Urban Land (ac)
Figure 42. Correlation between STEPL loads and urban land area.
Charlotte Water Quality Summary Report
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52

NC STATE UNIVERSITY
3.11.2 SWAT MODEL
The SWAT models were calibrated to daily mean streamflow and monthly TN and TP loads
(WRTDS-K). For daily streamflow, the Nash Sutcliffe Efficiency ranged from 0.73 to 0.89 and
the percent bias ranged from -14% to 17% (Table 9). The goodness of fit statistics generally
indicated good to very good agreement between the modeled and observed streamflow (Moriasi
et al., 2007). However, daily mean flow was generally underestimated for high flow days. The
calibration statistics for TN and TP generally indicated less agreement between the modeled and
observed nutrient loads, which is typical. These results generally indicated that the SWAT model
can provide reasonable replication of longer -term nutrient loading for these more developed
watersheds. Performance could likely be improved by inputting more detailed land management
practices such as more precise fertilizer application on lawns and other turf grass surfaces.
The calibrated SWAT model and STEPL provided reasonable results compared to WRTDS-K
estimated loads (Figure 42), with the exception of the catchment with a WWTP discharge
(MY10). However, it is important to remember that these estimates are based on monthly grab
samples and daily average flow (WRTDS-K), daily time steps (SWAT) and annual averages
(STEPL). However, the relatively close agreement was encouraging and indicates these tools
may be appropriate for large scale planning level management questions.
Table 9. SWAT Model Hydrology Calibration Results.
Daily streamflow
Total Nitrogen
Total Phosphorus
Site
NSE
PBIAS
NSE
PBIAS
NSE
PBIAS
MC14A
0.84
-2.9%
0.77
-14.6%
0.82
3.1%
MC22A
0.89
-13.9
0.74
1.5%
0.86
-21.7%
MY10
0.74
16.5
0.50
-34.1%
0.63
-48.3%
W11B
0.73
6.4
0.57
1.2%
0.66
28%
r�
Observed
Simulated
u�
N
Ln
0
I MC22A-Irwin Crk. nr Charlotte I
I
y I
V 1
it
III
i
� I lii I III
i�
I�i ili
ffffl
ii i
i j
h
�
i�����,lli�t�ilt_iii�A:ii
�'.d�,F li._�4.-4I�.__�5�u„�:"'_��_n•,��_A,-r-SI
___•'__••_�'__'�'y�-,.
_}h
2014 2015 2016
Figure 43. Observed versus SWAT simulated daily mean streamflow for MC22A.
Charlotte Water Quality Summary Report
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53

NC STATE UNIVERSITY
TIP Comparison
30,000 140,000
� c
TN Comparison
25,000 120,000
n a o 100,000
o c')
m 20,000 g N
m
'n C7 N a
80,000
❑WRTDS
- 15,000 a 60,000
❑STEPL
❑ ❑
d 10,000
❑SWAT
z 40,000
5,000 20,000
0 0
ELLJ
MC14A MC22A VY10 MY11B
MC14A MC22A MY10 VY11B
a�
oN
Figure 44. Comparison of WRTDS-K, STEPL and SWAT nutrient loading.
3.11.2.1 Testing Management Changes with SWAT
The SWAT model was modified by changing land cover to evaluate the impacts of conversion to
forest. While strategies like this would be difficult to implement considering the cost of housing
and land, there is a push towards expanding urban forest cover in already developed areas. Also,
this exercise provides a point of comparison for evaluating other nutrient management mitigation
strategies. An example of this type of analysis is shown in Figure 43, where the reduction in
nutrient load is shown in response to conversion of developed land to forest. These results
indicate that a substantial area of developed land would need to be converted to forest in order to
achieve large nutrient reductions. More detailed modeling may reveal greater benefits.
oImpact
of Forest Conversion
12°%
10°%
a
0 8°%
❑
5%
o
❑ ❑ TP
4°%
= a TN
2°%
a�
2 00%
a
0°% 10°% 20°% 30°% 40°%
Percent of Urban Land Converted to
Forest
Figure 45. Impact of forest conversion on nutrient loading.
3.12 Quality Assurance Project Plan (QAPP)
The Charlotte -Mecklenburg Storm Water Services QAPP is clear and comprehensive, as
such it provides an excellent resource for the water quality monitoring program. The relatively
minor additions outlined below are recommended only to help expand the monitoring protocol to
include samples collected over time. From the data NCSU received the stream sampling program
Charlotte Water Quality Summary Report
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54

NC STATE UNIVERSITY
is based mainly on collecting monthly grab samples. While grab samples are the easiest, and
least expensive sampling technique, they often do not represent the concentrations of water
quality parameters in small streams over time, particularly for urban streams like most in
Mecklenburg County. This is primarily because discharge and pollutant loads are typically much
greater during relatively short -duration storm events, which are not adequately characterized by
grab sampling. For example, a monitoring study of tributaries to Fall Lake showed that about 20
percent of the water delivered to the Lake resulted from flows which occur during just one
percent of the time, and 40 percent of the water delivered came during about 5 percent of the
time. This disparity between water delivery and the time during which it occurs leads to an over-
representation of low -flow conditions and an under -representation of high flow conditions when
sampling occurs during a regular time intervals (i.e., monthly) rather than at flow intervals.
Grab samples are typically better at characterizing water quality for non -storm or baseflow
conditions. In contrast, flow -proportional sampling provides a more accurate representation of
water quality for storm discharge in many urban streams. Therefore, more flow -proportional
sampling is recommended. This can be performed in two ways: 1) integrated flow meter
combined with an automated sampler or 2) timed interval sampling, which could be continuous
or initiated at the start of a storm event. For method 1), a stage -discharge rating table is required.
For method 2), a sampler with multiple bottles is needed so that aliquots of timed samples could
be manually composited based on how much discharge occurred between samples. A single
automated sampler with multiple sample bottles could be programmed to collect relatively
frequent samples of non -storm baseflow and flow -proportional samples of storm event flow.
Samples could be preserved in the machine and retrieved weekly or bi-weekly for transport to a
laboratory for analysis (this would necessitate adding the acid preservation as summarized
below). This longer holding time in the sampler might necessitate a longer maximum holding
time till analysis. The 28-day maximum holding times reported in Standard Methods can be
extended for up to 7 days as those reported are conservative being shorter than the actual
maximum holding times for the analytes. In fact, a U.S. EPA study of wastewater and drinking
water samples (Prentice and Bender, 1987), found that experimentally determined MHTs were
longer than 28 days (MHTs evaluated were up to 32 days) for TKN, NH3-N, NOx-N, and TP
when cooled to <40 C and spiked with H2SO4 to pH<2. This agreed with a study by USGS
(Patton and Gilroy, 1998), which documented no statistically significant effect on TKN, NH3-N,
NOx-N, and TP concentrations in thousands of surface and groundwater samples (collected from
across the U.S.) stored (<4° C and H2SO4 to pH<2) for up to 35 days (35 days was the longest
MHT tested).
In section B2. Sample preservation' of the QAPP the following paragraph could be added:
For certain parameters (e.g. TKN, NH3-N, NOx-N, and TP) samples may be preserved in non -
refrigerated automated samplers using acid (H2SO4) placed in the sampling bottle at the start
of the collection routine. These samples can be preserved in the sampler for up to 2-weeks in
this manner (Line, 2015; Kotlash and Chessman, 1998; Burke et al., 2002); however, samples
must be cooled to <4 deg C for continued storage until analysis. The maximum holding times
should start with the first sample/aliquot collected.
However, automated sampling protocols as described above require dedicated staff with
extensive training and experience. If this is not feasible given staff and budget constraints, then
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NC STATE UNIVERSITY
more frequent grab sampling including sample collection during storm events could serve as a
substitute for improving pollutant load estimates. Setting up weather and USGS flow alerts for
each gaging station could improve the likelihood of capturing storm event samples.
4 Conclusion
Major wastewater discharges were estimated to account for 75% of the TN load and 47% of the
TP load generated by the entire Charlotte Mecklenburg study area. Non -point source loads were
generally in the lower range when compared to values reported from previous studies for urban
areas. Trends in nutrient concentrations were widely variable; decreasing in some areas and
increasing in others. There was not a significant correlation between changes in land cover and
trends in nutrient concentrations. However, land cover was significant to discharge, the number
of bankfull events, and macroinvertebrate metrics.
The SWAT model and STEPL nutrient loading tool produced reasonable estimates for long-term
average annual nutrient loading in watersheds without substantial point sources. However, the
aggregate nature of these tools limit their usefulness outside of largescale planning level
exercises.
The water quality criteria thresholds were exceeded most often for copper and fecal coliform.
Copper criteria was exceeded in —80% of the sites with over 80% of the criteria exceedances
occurring during stormflow. Other metals were far less of a concern with Nickel, Zinc and Lead
never exceeding the standard. Fecal coliform exceeded the aquatic life standard in about 80% of
the samples, which is typical for urban streams. Nitrate levels were high (>10 mg/L) in all sites
that have wastewater treatment plants.
It was possible to predict sediment and nutrient concentrations from continuous water quality
(DO, Turbidity, Specific Conductivity, Temp, and pH) and hydrology (flow, rainfall) variables
with reasonable accuracy (R2 —0.6 to 0.9). However, the goodness of fit varies by site,
constituent, and by the range of dependent water quality parameter.
5 Recommendations
We recommend that municipalities first carefully refine their monitoring objectives and then
tailor the sampling protocols, assessment methods and data analyses strategically to address each
specific objective. However, selecting the overall goals for the waterways in the municipal
jurisdiction should first be identified before outlining these specific objectives. Meeting state
water quality standards defined by each waterway's designated uses and meeting the
requirements of the NPDES stormwater permit would naturally be a first priority. Goals and
objectives would also be tailored to individual waterways based on their current condition and
use classification, but future aspirations for improvement could also be defined. Recreational and
drinking water resources would likely have objectives and associated sampling protocols specific
to these special designations. However, many urban streams are no longer fit for fishing and
swimming due to impairment by fecal coliform, metals or other contaminants. So, returning
these waterways to a condition safe for full use and enjoyment by the local community may be a
targeted improvement goal. While this may be a lofty goal for most urban streams, targeting this
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goal could greatly affect the management, monitoring and perhaps more importantly, the
community attitudes towards this waterway. A list of five potential objectives to consider
including the data collection and analysis approaches to match each objective are provided below
in Table 10 below.
Table 10: Potential Water Quality Monitoring Objectives, Data and Methods
Objective
Monitoring Data/Method
Data Analysis Methods
1. Verify that observed
Grab; YSI probe
Follow state standards for
water quality is suitable for
sampling and data analysis
intended uses
when regulated. Otherwise,
compare the range of measured
data (box plots) to water
quality standards.
2. Determine trends in the
Grab; YSI probe, and
USGS WRTDS model
quality of the aquatic
macroinvertebrate
environment
sampling
3. Impact monitoring of
Grab and
Calculate and compare total
point sources and other
macroinvertebrate
pollutant loads from
contaminant sources
sampling upstream and
contaminant sources to non -
downstream of
point sources (e.g. TN & TP)
contaminant sources
4. Estimate nutrient or
Grab and YSI probe
Compare concentrations by
pollutant fluxes discharged
sampling
season and for baseflow vs.
by rivers
stormflow
5. Monitor background
Grab; YSI probe and
Compare concentrations &
quality of the aquatic
macroinvertebrate
loadings (pounds per acre)
environment to compare
sampling at CMSWS sites
from the watersheds
and assess results of impact
and in nearby undisturbed
monitoring
watersheds
Grab and YSI probe
Compare concentrations &
6. Determine if SCMs are
having a positive effect on
sampling in case study
loadings (pounds per acre)
water quality
watersheds with varied
from the watersheds
levels of SCM intensity
and type
In addition, the recommendations below are intended to improve the quality and value of the data
that is collected:
Increase Sampling Frequency: The collection of flow -proportional samples of stream
discharge over time should be employed as this is the best method of characterizing
stormwater flow/discharge. Alternatively, at least the frequency of grab sampling should
be increased in order to provide the data needed to more accurately calculate nutrient and
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NC STATE UNIVERSITY
sediment loads, which would improve the evaluation of trends in loading over time.
Monthly grab sample data are not adequate for this data analysis, particularly in urban
systems. If resources are limited, the number of sites could be reduced in order to
increase the sampling frequency. In addition, a greater effort should be focused on
collecting samples during peak storm flows. All types of models or methods that estimate
loading require that sampling be completed across a range of flows. Lacking samples
during the highest flows misses critical information, particularly for parameters that are
highly flow dependent (e.g., sediment). In addition, the regression models that were
developed to predict nutrients and sediment loads for this study may be improved or
better tested with samples collected during a larger range of flows.
Characterize Background Water Quality: Consider monitoring nearby undisturbed (or
minimally disturbed) watersheds to characterize background water quality. This allows
for the qualification of the values observed in Charlotte and helps to assess the impacts of
restoration or impact monitoring activities. Nearby nature preserves could be scouted for
high quality streams or NC DEQ could be contacted to identify high quality streams with
similar watershed sizes in the vicinity of Charlotte.
Improve Completeness of BMP database: The contributing area value is missing from
about 55% of the locations in the BMP database. Infilling this data could provide for
better watershed to watershed comparisons and enable modeling evaluations.
Identify the Specific Sources of Bacteria: Fecal coliform contamination is a concern in
all the streams in the Charlotte area, which is typical for urban streams. Fecal source
tracing could be implemented to determine whether the coliform bacteria originate from
wildlife, pets or human waste. The finding could help guide management decisions such
as fixing leaking sewers pipes or efforts to reduce pet waste reaching streams.
Improve the Maintenance and the Capability of the Continuous Monitoring Probes:
There were many gaps in the YSI datasets which may be the result of sensor fouling.
More resources could be dedicated to more frequent cleaning and calibration or the
number of sensors could be reduced. This is particularly true for turbidity. The turbidity
sensors also only measure to 1000 NTU, which appears to be exceeded during many
storm events. YSI now makes turbidity probes that measure to 4000 NTU. Having more
complete turbidity datasets could potentially be used along with turbidity-TSS
relationships to estimate sediment loads.
6 References
Aulenbach, B.T., Henley, J.C., and Hopkins, K.G. 2023. Hydrology, water -quality, and
watershed characteristics in 15 watersheds in Gwinnett County, Georgia, water years
200220: U.S. Geological Survey Scientific Investigations Report 2023-5035, 106 p.,
https:Hdoi.org/10.3133/sir2O235035.
Aulenbach, B.T., Kolb, K., Joiner, J.K., and Knaak, A.E. 2022. Hydrology and water quality in
15 watersheds in DeKalb County, Georgia, 201216: U.S. Geological Survey Scientific
Investigations Report 2021-5126, 105 p., https:Hdoi.org/10.3133/sir2O2l5l26.
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NC STATE UNIVERSITY
Barr, M., Kalkhoff, S. (2021). Water -Quality Trends of Urban Streams in Independence,
Missouri, 2005 18. Reston, VA.
Burke, P.M., Hill, S., Iricanin, N., Douglas, C., Essex, P., Tharin, D. 2002. Evaluation of
Preservation Methods for Nutrient Species Collected by Automatic Samples.
Environmental Monitoring and Assessment 80:149-173.
Cochran, W. (1977). Sampling Techniques. John Wiley & Sons.
Doll, B. A., Wise -Frederick, D. E., Buckner, C. M., Wilkerson, S. D., Harman, W. A., Smith, R.
E., Spooner, J. (2002). Hydraulic geometry relationships for urban streams throughout the
Piedmont of North Carolina. Journal of the American Water Resources Association, 38(3),
641-651. https:Hdoi.org/10.1111/j.1752-1688.2002.tb00986.x
Gassman, P. W., Reyes, M. R., Green, C. H., Arnold, J. G. (2007). The Soil and Water
Assessment Tool: Historical Development, Applications, and Future Research Directions.
Transactions oftheASABE, 50(4), 1211-1250. https:Hdoi.org/10.13031/2013.23637
Kotlash, A. R., & Chessman, B. C. (1998). Effects of water sample preservation and storage on
nitrogen and phosphorus determinations: Implications for the use of automated sampling
equipment. Water Res., 32(12), 3731-3737.
Line, D. E., White, N. M., Osmond, D. L., Jennings, G. D., Mojonnier, C. B. (2002). Pollutant
Export from Various Land Uses in the Upper Neuse River Basin. Water Environment
Research, 74(1), 100-108. https:Hdoi.org/10.2175/106143002XI39794
Line, D.E. 2016. Effects of Livestock Exclusion and Stream Restoration on the Water Quality of
a North Carolina Stream. TRANS of the ASABE 58(6):1547-1557.
Mcnett, J. K., William,;, Hunt, F., Osborne, J. A. (2009). Establishing Storm -Water BMP
Evaluation Metrics Based upon Ambient Water Quality Associated with Benthic
Macroinvertebrate Populations. Journal of Environmental Engineering, 136(5), 535-541.
https:Hdoi.org/10.1061/(ASCE)EE.1943-7870.0000185
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., Veith, R. L.
(2007). Model evaluation guidelines for systematic quantification of accuracy in watershed
simulations. Transactions of the ASABE, 50(3), 885-900.
Neitsch, S. L., Arnold, J. G., Kiniry, J. R., Williams, J. R. (2011). Soil and Water Assessment
Tool Theoretical Documentation Version 2009. College Station, TX.
Patton, C.J. and E.J Gilroy. 1998. U.S. Geological Survey nutrient preservation experiment -
experimental design, statistical analysis, and interpretation of analytical results. U.S.
Geological Survey Water -Resources Investigations Report 98-4118. Denver, CO.
Peters, N. E. (2009). Effects of urbanization on stream water quality in the city of Atlanta,
Georgia, USA. Hydrological Processes, 23, 2860-2878. https:Hdoi.org/l0.1002/hyp
Prentice, H.S. and D.F. Bender. 1987. Development of preservation techniques and
establishment of maximum holding times: Inorganic constituents of the National
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Pollution Discharge Elimination System and Safe Drinking Water Act. U.S.
Environmental Protection Agency. Research and Development. Washington, D.C.
EPA/600/54-86/043.
Rowland, F. E., Stow, C. A., Johnson, L. T., Hirsch, R. M. (2021). Lake Erie tributary nutrient
trend evaluation: Normalizing concentrations and loads to reduce flow variability.
Ecological Indicators, 125, 107601. https://doi.org/10.1016/J.ECOLIND.2021.107601
USGS. (2010). The quality of our Nation's waters Nutrients in the Nation's streams and
groundwater. Reston, VA.
USGS. (2021). LCMAP Viewer. Retrieved January 7, 2022, from
https:Heros.usgs.gov/lcmap/viewer/index.html
7 Appendices
7.1 Appendix A. Load Calculations
7.1.1 Beale Ratio Estimator
Because of the concerns and limitations of WRTDS in small watersheds, we calculated annual
loads using another method — the Beale Ratio Estimator (BRE) for comparison. The BRE
(Cochran, 1977) maybe better suited for systems with "flashy" hydrology because it uses
instantaneous flow (15 minute) and concentration to calculate load. Like other methods, the BRE
relies on the collection of samples across a range of flows to produce accurate results.
This comparison was completed to examine the range of loading estimates and the differences
between WRTDS and BRE because it is not possible to determine which method is more
accurate given that we do not have flow -proportional or more frequent sampling that would give
a better idea of the "true" load. The ratio of annual WRTDS estimated load to the annual BRE
load was calculated for each site. The median ratios for each site versus watershed size are
shown in Figure 44.
There is substantially more variability in the smaller catchments; however, WRTDS generally
seem to be larger than BRE loads. There was greater variability for the difference in loads for TP
than TN. For the three largest watersheds the long-term average loads were similar. The larger
the watersheds, the less "flashy" the hydrology and less difference there is between the daily
average flow and daily maximum flow. However, this is not to say that the BRE is more accurate
in smaller watersheds as we do not know the actual observed loads.
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Total P
0
0
0
0
00 O 0
0 00
0 0 00
0
0 0 0
0 0
0
0 20 40 60 80
Drainage Area (sq. mi.)
Total N
O
40 0 0
poi 0
0 GD
D 0 00 0 0
0
0
0
0 20 40 60 80
Drainage Area (sq. mi.)
Figure 46. Comparison of WRTDS-k and Beale Ratio calculated TN and TP loads related to
catchment area.
7.1.2 Estimated Observed TSS Loads from Continuous Sampling compared to WRTDS-
K TSS loads.
TSS loads were estimated by developing regression equations to calculate TSS from continuous
turbidity measurements. The data was log -transformed and values below the detection limit were
removed. The regression equations for the 18 sites resulted in R2 of 0.61 to 0.95 (Figure 45). The
continuous turbidity measurements from the YSI probes were then input into the regression
equations to obtain estimated TSS concentration. The TSS loads were then calculated by
multiplying the estimated TSS concentration by the flow from the USGS gages. The loads were
then summarized by month for periods with at least 90% complete records. There are some
issues with this approach. Namely that turbidity regularly exceeds 1000 NTU during storm
events and therefore the observed loads are likely underestimated. In addition, there was not a
high percentage of months with complete data. There were 18 to 48 months (-13 to 33%) of
complete data across the sites over a 12-year period from 2008 to 2020. These regression
equations could likely be improved with additional continuous variables (e.g., DO, Temp,
Specific Conductivity), however the periods of complete data would have been further reduced
by data gaps in the other continuous parameters
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MC14A
MC17
MC22A
3-
y=-0.15+0.96x Ra",=0.77
y=-0.23+0.98x
R ei=0.82
y=-0.069+0.91 x R d
-0.81
Y '
1-
Z•� . •
d
•�•.
of
C-
MC27
MC29A1
MC33
3-
y=-0.32+1.1x Rgd�-0s95
y=-0.15+0.98x
Rgdj =0.88
y=-0.6+0.91x Rgdj=0.78
06
2-
1-
'
w„
0-
MC38
MCA
MC42
3-
y=-0.042+0.86x R tl.=073
y=-0.21+x
R tl =0.84
y=-0.017+0.8x R d.=078
2 -
(A 0 -
H
o
MC45
MC49A
MC50
03-
y=-026+1.1 x Rd- 084
y=-0.067+0.99x
R dJ=0.84
y=-0.015+0.83x R tl,=0.69
1 -
. •
. .+fir �•
o-
Myl0
MY11 B
MY13
3
y=-0.14+0.93x Ra,,=0.74,
y=-0.23+099x
RLJ=fl.73,
y=-0.15+x R' =0.88
0-
MY1B
MY7B
MY8
3-
y=-628+1.1x R' -0.9
adjadj
y=-0.088+0.84x
R' -065N
y=-0.11+077x Rgdj=661
2-
+
•i
�
0
1 3
0
1 2
3 0 1
2 3
log 10{Turbidly)
Figure 47. Regression of TSS vs Turbidity.
The difference in "observed" TSS and WRTDS loads were widely variable across sites (Figure
46). The WRTDS loads were generally greater than the observed loads for larger monthly
observed loads. Whereas observed loads were generally greater than WRTDS loads for lower
loads. BRE loads were mostly lower than the observed loads (Figure 47).
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11CW MC17 MC22A MC27 ' NC29AI
4e+06- 4e+05- '
6e+O6- ' ' 6e+O6- • •
6e+06- fie+05-
'
4e+O6- 4e+06- 4e+05-
2e+06- 2e+05- • 2e+06- 2e+06- . • 2e+05- • ,
Oe+00 Oe+00- • Oe+00 " 0e+00- Oe+00- �•S
RKM MC38 YC4 YC42 YC45
8e+05- • 1.0e+06- , 6e+05-
m6e+05- 7.5e+05- 1e+06- 1.5e+06-
Y"4e+05- • , 5.00+05- 5e+05 4e+05- , 1.Oe+06-
•
0 2e+O5- • 25e+O5_ • , 2e+05- • 5.Oe+05- •t. ',
-j Oe+00- • 4•' O.Oe+00- • 0e+00- • 0e+00 0.0 a+00- 4
F
a o ri m o ri a m o n
s o 6 o 6 M1
UC49A MC50 Uylo YY77B MY16
fA 5e+06- • • • 20e+O6- • 3e+06- '
4e+O6- 3e+05- 6e+O6-
~ 3e+06- • 2e+05- 4e+06- 1.50+06- ' 6e+O6-
2e+O6 - • , • 1.Oe+06 - 4e+06 -
ie+O6- • 2e+O6- 5.0 a+05- , 2e+O6-
Oe+00-, • Oe+00- Oe+pO 0.0 a+00- Oe+00
IfIfTB YY8
4e+05- • 4e+O6-
3e+05- 3e+O6-
2e+05- 2e+O6-
1e+05- ie+O6-
Oe+00� 0e+00
N N Observed' Monthly TSS Load (kg)
Figure 48. WRTD.S' monthly T.S'.S' load versus "observed" monthly AS loads. The red line is
the 1:1 line.
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MC14A MC17 UC22A MC27
' 2.0e+05-
9e+05- . 1e+05- 7.5e+06-
1.5e+05 -
6e+05- • 1.0e+05- 5.0e+06-
5e+04 -
3e+05- 5.0e+04- . 2.5e+06-
Oe+00- ' Oe+00- • • ~'A • • • 0.Oe+00- �•: •.. . O.Oe+00- • w. h. b.
MC29A1 kKM UC39 YC4
1.2e+05-' 3e+06- '
1.5e+05- 9.0 a+04 -
1.5e+06-
6.0 a+04 -
1.0e+05- • ' • 1.0e+06- 2e+06-
�
5.0e+04- 3.0e+04- 5.0e+05- 1e+06-
J O.Oe+00- .�.i! •' �• • O.Oe+00- �'~•��*•• • • • O.Oe+00- • .•.L... .. Oe+00- M ..
fA
F o cv v m o ci v m o ci v m o „
0
m MC45 MC49A MC50 MY10
B' . 1.0e+05- . 8e+03-
m 7.5e+05- - ' • 2.0e+05-
7.5e+046e+03-
m 5.0e+05- • . 5.0e+04- 4e+03- 1.5e+05-
1.Oe+05-
• r
2.5e+05- • ' . • • 1v. . 2e+03- ' 5.0e+04-
O.Oe+00- •'�• • Oe+00- O.Oe+00-
o n o n o � ci m o 0 0 n o 0 o ci
YY71B YYIB YY7B MY8
5e+05- ' '
9e+05- 6e+05-
4e+05- 4e+04-
3e+05- 6e+05- . • 4e+05-
2e+05- 2e+04-
3e+05- 2e+05-
1e+05- ..
Oe+00- •• • Oe+00- Oe+00- " • Oe+00-
'Observed' Monthly TSS Load (kg)
Figure 49. Beale Ratio Estimator monthly TSS load versus "observed" monthly TSS loads.
The red line is the 1:1 line.
7.2 Appendix B: Water Quality Regression Equations
Regression equations for predicting nutrient and sediment concentrations from continuous water
quality variables are included below.
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E
m o
M C4ZTSS
o
o
o
0 50 100 150 200
Observed TSS [mgfL]
o
M C45 - TP
Rsgr = 0.78
o
o 8 ® oo ° 0 0
B
0.1 0.2 0.3 0.4 0.E
Observed TP [mgfL]
o
MC45-NO3
o Rsgr=0o.32 o 0
_0
8 o 0
° °®°o °
°® �o ° ° °
o
a°
1A CZSSC
Rs
° 0
0 50 100 150 200 250 300 350
Observed SSC [mgfL]
M C45-TN
Rsgr = 0.58 0 8 0 0
® ° 0
en 00 0
8
0.5 1.0 1.5 2.0
0 bserved TN [mgfL]
M C45- Fecal Culifurm
Rsgr = 0.s9
o
o
o
° °
o
0.0 0.5 1.0 1.5 0 s000 10000 15000 20000 250-o-0 30000 35000
Observed NO3 [mgfL] Observed Fecal Coliform [M PN1100 mL]
Figure 50. Regression fit vs observed water quality results for MC45.
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E
m
LL
o
MC27-TSS
Rsgr = 0.91
o
o
0 og
0 100 200 300 400 S00
Observed TSS [mglL)
o MC27-TP
o o ° ° 0 9Boo Rsgr=0.14 m
E
o E
m
0°
a m o; 0 ° 6 o o Z
a m g °08 ° ao :
o
LL O °o o LL
o
0.0 0.5 1.0 1.5 2.0 2.E 3.0
Observed TP [mg1L]
� m
E
❑ m
a v
E
M C27-SSC
Rsgr = 0.9
o
00
0 100 200 300 400 S00 600
Observed SSC [mg1L]
M C27-TN ° ° 0° °
Rsgr = 0.75 �oo ° ° oq4 $° °
° 0 8 ° ° %0
° S$
® °
2 4 6 8 10 12
0 bserved TN [mg1L]
0 2 4 6 8 10 12 0 10000 2a000 30000
Observed NO3 (mgfL) Observed Fecal Culifurm (M PNi1 CC mLl
Figure 51. Regression fit vs observed water duality results for MC27.
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LL
°
Id C14A-SSC °
Rsgr = O.SS
0 °
0 o 0° 0
00 0 °
0 50 100 150 200 250 300 0 50 100 150 200 250 300
Observed TSS (mgfL) Observed SSC (mgfL)
0.00 0.05 110 0.15 0.20 0.25 0.30
Observed TP (mgfL)
N]
E
o
o
LL
J
E
0
V
MC14A-TN
Rsgr = 0.65 0000
0 °
o0o 0 °o ® °
0
o080 o
8 0
0oo
0.5 1.0 1.5 2.0 2.5 3.0
0 bserved TN (mgf-)
o
M C14A/CDIfDrm
o
o
cgo
0.1 0.2 0.30.4 0.5 5000 10000 15000
Observed NO3 (mgf-) Observed Fecal Coliform [Id PNA CC mLl
Figure 52. Regression fit vs observed water duality results for MC14A.
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67

NC STATE UNIVERSITY
°
MC17-TSS
Rsgr = 0.82
oo
o
o
0 50 100 150 200 250 300
Observed TSS (mgfL)
o
o C17-TP
Rsgr=U.76
o
o
o
° o0 o
o 00 o
ooro °
1.0 0.1 0.2 0.3
Observed TP (mglL)
M C17-NO3 o oo ° ° °
Rsgr = 0.32 ° ° °
o
o o ° B o o o° °o o
o
80°00�60° °°og°o°®o®08 0 8o00o®80 0 °
o
8
Z m
°
1.1Z—
o
R0 o00
0 50 100 150 200 250 300
Observed SSC (mgfL)
o
o
MC17-TN
Rsgr = 0.35
o
o
8o
0 2 4 6 8 10 12
Observed TN (mgfL)
o
M C17- Fecal CDlifurm o
Rsgr = 0.69 °
oo
o
oo
m° oo
o
0.1 0.2 0.3 0.4 0.` 5000 10000 15000
Observed NO3 (mglL) Observed Fecal Coliform (MPN1100 mL)
Figure 53. Regression fit vs observed water duality results for MCI 7.
Charlotte Water Quality Summary Report
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68

NC STATE UNIVERSITY
E
°z
o
:MC49A TSS °
0.33o
0 50 100 150 200 250
Observed TSS (mgfL)
0 0°0° MC49A-TP o
0 9 §.@ o Rsgr=0.5S
oo
m o000
� s °B�°°°° °
io
m°
0 1 2 3 4
Observed TP (mgVL)
o
MC49A-NO3 o
Rsgr = 0.72 o ° o ® 8
B
B ® g ° o
o ° °8°8 0� 9 8 g °
o o
d o o
o m
o® o
M MA - SSC o
Rsgr = 0.85
o
o
0 8 o
o
o 0
0 50 100 150 200 250 300
Observed SSC (mgfL)
oo
MC49A-TX1,
o
000 o 0 o 0
o Rsgr_0oo9k°omo
o
o0oo
,p°
o
o°
0
5 10 15
0 bserved TN (mgf-)
o
M C49A - Fecal Coliform
Rsgr =o .71 0 0 o
oo0
°o
C 5 10 1F 0 10000 20000 30000 40000
Observed NO3 (mgYL) Observed Fecal Coliform CUM ml-)
Figure 54. Regression fit vs observed water duality results for MC49A.
Charlotte Water Quality Summary Report
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69

NC STATE UNIVERSITY
0
o
E o
a
Z o
o
MC22A-TSS
Rsgr = 0.51
o
o
o
o
o
0 s0 100 150 200 250 30C
0 bserved TSS (mgfL)
0
M C22A - TP
Rsgr -0.77
o
° °
$B °o
oo
o
3.0 0.1 0.2 0.3 0.4
Observed TP CmgfL1
o
MC22A-NO3
Rsgr = 0.53 o
o 0 o
o
o °� °
84g o80 o ° °
000
o ° °� o
M C22A-SSC
Rsgr = O.Sd
$ 0 0 o
0 s0 100 150 200 250 300 350
Observed SSC (mgfL)
o
M - TN
R7o
8 o CP
oG
® °
00
o °
1 2 3 4 5
Observed TN Cmg�L]
M C22A- Fecal Califarm
Rsgr = O.ss °
°0 0
0 80 °
09 % ° °
o
0.2 0.4 0.6 0.13 1.0 1.2 1.4 0 5000 10000 15000 20000 25000
Observed NOS (mq L) Observed Fecal Culifurm (M PN1100 mL)
Figure SS. Regression fit vs observed water duality results for MC22A.
Charlotte Water Quality Summary Report
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70

NC STATE UNIVERSITY
7.3 Appendix C: Flow Duration Curves.
E
m
�.
z r
i
I
I
I
I
I
1
i_
I
1
I
i
I
I
1
1
1.
I
I
r
-1-
1
i
-j
(SP) MOB j (SP) MOl-A (SP) MOB j
Figure 56. Example of flow duration curves for MCI 7.
C
z
rY-
i
l
1
1
1
1
i
I
I
1
I
I
(SP) MOB j
I
M
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71

NC STATE UNIVERSITY
J J
J
O m
b
z
�(s)a) M01=1
T
(910) M01=1
f (SM Mali
(s)a) M01=1
J
F-
J
J
U)
N
2N O
U
m
d
_
i
f
�
w v
o
J
�
f
r
T
U
1
dt
U
C
K
C
C
f1
L
d
U
N
�
$
a
1
ME
Isla) Mold r (S)a) M01=1 (s)a) M01=1 (W) M01=1
Figure 57. Example of flow duration curves for MO4A.
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72

NC STATE UNIVERSITY
7.4 Appendix D. Water Quality Boxplots
o0
— Percent Developed
40
• T 75
30
O
U • • m
20 Q
• . • . . 25
t � • t t
t
LL! —LLLLLC:
0 T� 0
Me3 E§- m� ee�mmo��
> r i Y ,
Site
Figure 58. Boxplots of copper results sorted by catchment development.
00
30
— Percent Developed
100
75
O
50 a
Q
25
o m m m �n
raj � y � } V �
Site
Figure 59. Boxplots of zinc results sorted by catchment development.
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73

NC STATE UNIVERSITY
40000
30000
}_
O
U
U
if 20000
10000
— Percent Developed
JL
Site
Figure 60. Boxplots of fecal coliform results sorted by catchment development.
1.5
� 1 a
rn
E
s
z
0.5
• — Percent Developea •
1 i— 1 i i i i 1-- 1 1 1 i! i i 1 1 IA111 1,
ion
75
e'
0
50 �
0
N
Q
25
100
75
O
50 �
a
c
Wi
Site
Figure 61. Boxplots of ammonium results sorted by catchment development.
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74

NC STATE UNIVERSITY
E
0
Z
7.5
5.0
25
0.0
— Percent Developed �
Site
Figure 62. Boxplots of nitrate results sorted by catchment development.
1.25
1.00
0.75
a
H
0.50
0.25
0.00
o M m o m .-,
Site
Figure 63. Boxplots of total phosphorus results sorted by catchment development.
Charlotte Water Oualitv Summary Report
• — Percent oe�eioved •
i r t • • t i i t � t � i � . �
i • i t t ! t • t i � i
100
25
0
100
75
0
50
0
25
Land and Water Fund
75
0

NC STATE UNIVERSITY
400
300
E
to
~ 200
100
— Percent Developed
• • • • • • • • • • • • • • • •
Site
Figure 64. Boxplots of total suspended solids results sorted by catchment development.
100
75
0
O
50ID
ID
0
a
Q
25
Charlotte Water Quality Summary Report
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76

NC STATE UNIVERSITY
MC14A
M017
MC22A
RIC25
MC27
R = 0_39
12.5-.
10.0 - R = U_a97
.
4- R = 0_36
15
_ �_M37
3
.
,j4 = 0_32
2 _
7.5-
3-
10-
•
2-
1
...
. t•
.
5.0-
2.5-
2-
_ .� •
1
5
•
1•.,
•
+
•.. •
fop
0.0-.r
•
0�
,' •.
0 200 400 600 800
0 50 100 150 200
0 250 500 750100(1250
0 100 200
300
0 250 500 750 1000
MC29A1
M C30A
M C33
M C38
M C4
•`
R -0.39
R.. = �!55
1.5-
. •
'.
1oo-
.
R0.62
2
1
R
• • •
1.5
1. o*
0.5 •
% •
0.5-k
.R
0.4-
'
0.50-
•
025-
0 100 200 300 400 500
0 10 20
30
0 100 200 300
0 200 400
600
0 100 200 300 400 500
MC45
MC47A
MC49A
MC54
MC51
b) 1.5
R = �_46
3 R = 0_38
R = 0_26
3-
R = 0_82
+
1 oa
F? 048
2-,
1 •
3 -
2-• . ..
• •
2-�
1
.
`o
0.75-
0.50
+
• %
0.5
.
• ,
'
1- .ti ti.
• .
125-
t
0 500100015002000
0 100 200
0 250 500 750 1000
0 20 40
60
0 100 200 300
MCBS
MY10
MY11B
MY12B
MY13
2.0
.
%
.
.
.
1.5-R=0.2
2_R=0.32
1.2- 0.58
1.5-L2=a.65
1.5-f?
0.55
1.0-
•
1 ++ ,�+
•
•
�. •
V
1.0-
'
1.-
0.5
+
0.5
.
:
0A
0.5
,
0 25 50 75 100 0 200 400
600
0 250 500 750 1000
0 50 100
0 50 100 150
RM B
MY7B
NYa
MY9
2 -
•
R-- 0_79
•
1.5 - = 0_52
•
1.00 - 0_58
1.6-
•
R = 0.49
%R
1.2 -
1
+ ..
1.0-0 • ,
`
0.75- ..
0.50- +
0.8-"••
• •
. .
0.5
'
0.4
•
0.25-
•
0 100 200 300
0 20 40 60
80
0 100 200
0 20 40 60
80
Discharge (cfs)
Figure 65. Correlation between TKN and streamflow.
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77

NC STATE UNIVERSITY
MC14A
M017
M C22A
MC25
MC27
0.5-
0.4-
•
= 0-18
•
•
0.9 - R
0-18
= -0.11
1.0-
1.0
•
= G-083
10 - = -0.49
0.3
0.2
�. •
`' '
0.6 •
0.3
,
• •
•
•
•
0.5- r %
0.5�.p
••5
•
0.1
•
�, •., •,
0.0 -
0.0
0-1
200 400 600 800
0
50 100 150 200
0 250500750100d250
0 100 200
300
0 250 500 7501000
MC29A1
MC30A
MC33
MC38
MC4
•
1.00- •
as
•
40-'
=-0.28
0.75-
0.014
0.9- =(].11
1.5-
R=0.15
30- F?=-0.019
1.0
0.50-
0.6- • •
1.0
20-
0.5-
• • ,
0.25-
• ,
•
0.3- : ` • ,
0.5 -
/
•
10-
0.0 -
0 100 200 300 400 500
0
10 20
30
0 100 200 300
0 200 400
600
0 100 200 300 400 500
MC45
MC47A
MC49A
MC50
MC51
J
Col .5
+
0.8 •
=
0.094
15- _
3-+
R =
•
F?= 0-18
-2
o.s
-0-48
2
-a-018
0.75
m 1.0-
•
+
0.4 - .
10-
_
0.50- •
• • • • + •
�• ••
•
z0.0
0-!
0
0 500100015002000
0
100 200
0 250 500 750 1000
0 20 40
60
0 100 200 300
MCBS
MY10
MY11B
MY12B
MY13
•
•
6_#R=-0.059
2.5-.
2.0-{?=-0.053
1.0-f?
•
G.O38
•
3 R=-0.075
3-R=0.015
2
4=
1.5-
1.0-�
•
2 i
1L's
2-
0.5- .
0.5
1-�
0 25 50 75 100 0
200 400
600
0 250 500 750 1000
0 50 100
0 50 100 150
RM B
MYTB
MYa
MY9
•
10.0-•
1.00-+
•
0.6-
=0-1ra
7.5 R=-0-034
0.75- _ -07
2_
1
0.2-
2.5-
0.25- * •
• :
• •
0 100 200 300
0
20 40 60
80
0 100 200
0 20 40 60
80
Discharge (cfs)
Figure 66. Correlation between nitrate and streamflow.
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78

NC STATE UNIVERSITY
MC14A
MC17
300- , •
300-
200-
, 200-
~
100-
100 -
•
•, +
0- r
0-
0 200 400 600 800
0 50 100 150
M C29A1
M C30A
300-=L1.66
• 300-=0.413
200-
200 -
,.
100- • • •
100-
..
0 100200300400500
0 10 20
M C45
MC47A
:7r 250- •
100-
•
6b200- R = 0_45
75-
R =4.7-A
E 150 -
: +
� 100- •
'
50 -
•
U3 50 - ,
' 25-
0- 1
0-
0 500100015002000
0 100 200
M C6 6
MY10
3o0- R=0.51 •
600-
R 0.58.•
200-
400-
100-
200-
0 25 50 75
100
0 200 400
MY1B
MY7B
•
750-R=4.82
400 -
300-
•
500 - •
200-
250- •• ' • „
100 -
�
0-
0-
0 100 200
300
0 20 40 6C
MC22A
MC25
MC27
300-
+ 300-
0200
aoo
+
R = 488
R = 0.79
-
R = 0_82
-
,+
200 -
•
, 300-
+
100-
•
;
100-
y , '
�
200-
100-
,e. ,•• +
~*
0-0-
0-�
0-
w
00
0 250 500 7501003250
0 100 200
300 0 250 500 750 1000
MC33
M C38
M C4
150-
• +
i? = 0.75
200 -
150-
•
R = 0.72
300-
,
.
R = 0.73
100-
• + '
• 100-
+� `
200-+
4 •++
• 50-
' S •
50-
`• .
+
100-
• .
0-
0-
0-
,
30
0 100 200 300
0 200 400
500
0 100200 300 400 500
MC49A
MC50
MC51
• 200 -
R = ()_8 ,
200 -
R = fl_82
75-
14 = 0_56
100-;
••
:
+%
150-
100-
50 -
,
+ +
50-+�
25 -
• , , ,
' +
M
0-
0-
0-
t
0 250 500 7501000
0 20 40
60
0 100 200 300
MY11B
'MY12B
MY13
600-
a
200-0
•
600-
•
400-R=0.62
, 150-R=0.76
+=0.73
400-
200 -
+ ' '
100-
m
200-
'
•'� • +
•
+'
50-
0 +
0-
o -"'1
.
0-
600
0 250 500 7501000
0 50 100
0 50 100 150
MYS
MY9
+ 9o-R=0.54
200-R=082
,
'
60-•
0-
0-1
80
0 100 200
0 20 40 60
80
Discharge (cfs)
Figure 67. Correlation between AS and streamflow.
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79

NC STATE UNIVERSITY
MC14A
MC17
MC22A
MC25
MC27
10-R=4.26
12-R=0_26
10-R=0.31
10-R=0.4
30-R10.083
8-
.
20-
,
0 200 400 600 800
0 25 50 75
0 100 200 300 400
0 50 100 150
0 250 500 750 1000
M C29A1
M C30A
MC33
M C38
M C4
30- •
20- '
16- •
12.5- •
•
15-��0.24 ,
12-R=0.43
1o.o-R=0.43
12-R=0.37 •
20-R=0.22
10 :
s
7.5- ,
'
8-
10'.
P-, +
5 ,�
», +. • . .
4
5.0-• •
2.5 - 1r+ ,
_ ••
4�, • �� •,
0 100200 300400 500
0 5 10 15
20
0 100 200 300
0 200 400 600
0 100 200 300 400 500
MC45
M C47A
M C49A
M C50
MC51
0.4
j?�= 0.12
30 - R 0.049
s - _ 0.36
5 - R = 0550
_
D •
2-�
•
10-
"`. �
4 _
2-r•
• •
2-�
0 500100015002000
0 100 200
0 250 500 750 1000
0 20 40 60
0 100 200 300
MC66
MY10
MY11B
MY12B
MY13
12.5 - •
.
•
1o.o-f4=0.027
6_R=0.27
R=0.16
5-R 0.31
30_0.027
10
5.0
20
10 ap . .
'
'
1
4 &a `+ ' • '
5 - % • •
X. `
3 - • ` •
2.5 it
- ,
0 25 50 75 100
0 200 400
600 0 200 400 600
0 25 50 75
0 50 100 150
MY1B
MY7B
MY8
L"9
12=�-39
4_Ra0.36
12 R=4.16
6-R� 0.37 '
5-0%
+
_
3- •
4 . . •
2 �
4_�IF�. �
2 i
0 100 200 300
0 20 40 60
80
0 100 200
0 20 40 60 80
Discharge (cfs)
Figure 68. Correlation between Cu and streamflow.
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80

NC STATE UNIVERSITY
M C14A
MC17
M C22A
MC25
MM
15000 -
R 0.35
20000- '
� = 0.29
30000-0
R = 0.2
20000 -
•
R = 0_11
•
30000 - R = 0.35
-
10000+
5•
000 -
,•
,
+ �
15000-
10000- ti "
5000 -� • •
20000- •
10000 '10000-
•
15000-•
5000 -
20000-'
10000 -ice••
+ .
•
. 0 s
a,
+. ••
••
.. •..
o
r
0-
0
0-
0
0 200 4-00 600 800
0 50 100150 200 0 2505007501001250
0 100 200 300
0 250 500 7501000
M C29A1
M C30A
MC33
M C38
MC4
40000-'
- 0.069
60000-6
R = 0.12
•
40000 - R = 0.3
30000 -
•
z0.37
60000- •
R = 0.19
30000
-
•
40000- ,
30000- %
20000-
• •
40000-
20000
_ 10000-
20000-
20000-._• '
10000-•
• •
20000-
J 0
0-
0
0-
0
E
0
0 100200300400500
0 10 20
30 0 100 200 300
0 200 400 600
0 100200300400500
0
M C45
M C47A
M C49A
MC-50
MC51
n_
30000 -
•
R = -0 42
gpppp-�
R = 0.096
40000 •
R = 0.34
40000-`
R- 0.29
20000 •
R — 067 +
••
40000-
30000- •
30000-
15000 -
20000
010000-
'
,'• ,
•
20000-�60
20000- '
10000- ••
20000- •' •
10000-11 • •
10000 •
5000- ,• • • ; •
0-
0-
•
0-
0
%
AP
0-
0
0
0 500100015012000
0 100 200
0 250 500 7501000
0 20 40 60
0 100 200 300
m
c�
MC66
MY10
MY11B
MY12B
MY13
•
25000- •
•
•
•
30000-
10000-
R = 0.14
20000- = 0.44
40000 - ;� = 0.12
20000 -
R 0-52
R = 0.24
0
15000 - •
20000 -
5000 -
• , •
10000 - •• . +
20000 - '
10000 -L
•, +• `
00
10000-
0-
0 25 50 75 100
0 200 400
600 0 250 500 7501000
0 50 100
0 50 100 150
MY1B
MYTB
MY8
MY9
•
60000- •
•
•
60000 -
R = 0.47
R = 0.42
F - 0.23
15000 -
Re= 0.37
40000-
20000
40000_
,
10000-
'
'
20000-
•
20000- •6,
10000-
•
0 1fl0 200 300
0 20 40 60
80 0 100 200
0 20 40 60 80
Discharge (cfs)
Figure 69. Correlation between fecal coliform and streamflow.
7.5 Appendix E. Comparison of Continuous Data to Grab Samples.
The continuous water quality parameter monitoring (temperature, specific conductivity, pH,
dissolved oxygen, and turbidity) data had many gaps and long periods when data was not
collected. In addition, there are periods of time when the reading appears questionable (excessive
noise and possible drift).
To evaluate quality of the YSI data we compared it to measurements collected with newly
calibrated instruments during site visits to collect grab samples. Data from 2008 to 2021 was
used for this exercise. The comparisons were somewhat limited by the numerous gaps in the
dataset when field measured parameters did not have a corresponding result from the YSI probe.
7.5.1 Turbidity
The comparison of the continuous and field collected turbidity data is provided in Figure 68. The
black line on the plot represents a 1:1 line. While many of the comparison pairs are grouped near
the 1:1 line, there are notable outliers where there is a difference of 100s of NTUs between the
YSI probe and the field measured data. The mean absolute error between the measurement
Charlotte Water Quality Summary Report
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81

NC STATE UNIVERSITY
methods ranged from 5 to 38 NTUs across the sites. The differences are likely due to the probes
fouling and then not reading accurately or beginning to drift.
Figure 69 provides an example of the gaps in the YSI collected continuous turbidity data. In
addition to gaps in the record (only about 50% of the manual measurements had corresponding
measurements from the continuous probes) and some problematic comparison with grab
samples, the turbidity sensors do not capture the full range of observed values. This is
problematic if the goal is to use turbidity as a surrogate for sediment monitoring. The installed
probes measure over the range of 0-1000 NTU. During stormflow events turbidity regularly
(almost every stormflow event) exceeds 1000 NTU. Newer turbidity probes can measure up to
4000 NTU. The grab samples are primarily collected during baseflow or near baseflow
conditions, limiting the comparisons.
Turbidity
MC14A
MC17
MC22A MC25
MC27
MC29A1
1250-
1000- R2=0.33
R2=0.17
R2=0.82 fie=0.6
R2-0.7
R2=0.88
750 - MAE=7.9
MAE=26.8
MAE= 18.2 ldAE= 32.8
MAE= 14.8
MAE=9.5
500-
250-
•
•
0 �kY51 I #Fie d = 0.54
#YSI# #Gie = 0.52
#YSI ?#Fie d = 0.57 #Y91 I #F iE d = 0.55
#YSJ I #Field = 0.53
#YSII #Fed = 0.d9
MC30A
MC33
MC38 MC4
MC40A
MC42
1250-
1000 R2=Q.72
R2=0.3
R2=0.35 R2=0.29
R2=0.93
R2=0.87
750- MAE= 9.6
MAE= 31.2
MAE= 17.4 MAE= 22.7
MAE= 5.4
MAE= 6
500-
250 - •
•
. •
0_ #YSII#Field =0.d9
#Y&I!#Field =0.54
#YSII#Field =0.51 #YSI+#Field =0.5T
#YSII#Field =0.1fi
#YSII#Field =0.51
5�
MC45
-
MC47A
MC49A MC50
MC51
MC58
1000- R2=0.43
R2=0.43
R2=0.57 R2=0.71
R2=Q.91
R2-0.2
�3 MAE= 11.1
MAE= 6.fi
MAE= 24.7 MAE= 5
MAE= 3.5
MAE= 18.fi
H 750-
500-
m
a 250-
.
E 0- YSI 1 #Field = O.d1
m
/FY51 I #Fie Id = 0.39
#YSLI #Field = 0.4d #YSII #Field = O.d7
#YSII #Field = 0.44
#YS,I I #Fie Id = 0.33
MY10
MY11B
MY13 MY13A
MY1B
MYTB
m 1250 -
i71000- R2=0.8
R2=0.15
R2=0.92 R2=0.92
R2-0.4
R2=0.49
750- MAE= 13.9
MAE=16.8
MAE=9.7 IdAE=1Q.2
MAE=3S.8
MAE=14.5
500-
250-
0- WSI 1 #Fie M = 0.47
AYSI 1 #Field =j1.61
#YSII #Fie M = 0.43 #YSI 1 #Field = 0.4
IkY511 Meld = 0.5•
#YSI 1 #Field = 0.61
0 250 500 750 10000 250 500 750 10000 250 500 750 10000 250 500 750 1000
We
MY9
1250-
1000 R2=0.96
R2=0.23
750- MAE= 4.9
MAE= 9.2
50 0 -
250-
0 - #YSI I #Field = 0.58
#YSI I #Fie ld
0 250 500 750 10000
250 500 750 1000
YSI - Turbidity (NTU)
Figure 70. YSI measured and field collected turbidity comparison for all sites. The black line
is a 1:1 line and the red number is the percentage of field measured data for which there is a
corresponding continuous data point
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0
C.
o2
0
o -
m
j
o
F
o -
z
o
�
F
o -
�
O
O -
CV
O -
•
•
YSI
grab sample
2015 2016 2017
Figure 71. YSI measured and field collected turbidity data for site MYIB from 2015 to 2018.
7.5.2 Specific Conductivity, Dissolved Oxygen and pH
Specific conductivity, DO and pH continuous YSI measurements showed varying levels of
agreement with the field based manual measurements. The greatest differences between the
manual measurements and YSI continuous probes generally occurred at low discharge (Figure
73), indicating that the differences may be related to fouling due to stagnant conditions. The
manual field measurements of specific conductivity, DO and pH had a higher percentage of
matching automated measurements than for turbidity; 60-80% of field measurements had
corresponding automated measurements. Issues with gaps in the data are shown in Figure 74 and
potential sensor drift is illustrated in Figure 75.
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Specific Cond,
MC14A
MC17
MC22A
MC25
MC27
MC29A1
750-
R2=0.75 •
MAE= 13.5
R2=0.7
1,1AE= 16.1
R2=0.38
I1AE= 28
R2=0.35
MAE=23.9
R2=0.87
MAE= 15.2
R2=0.45
MAE= 38.2
500 -
•
250
.
•
•
M '
0 _
#YSI J #Field = d.63
#YSI J #Field = O.fiH
#YSI J #Field = G.63
W111 #Field = d.58
' #Y511 #Field = 0.fi9
#YSI J #Field = G.fi7
MC30A
MC33
MC38
MC4
MC40A
MC42
R2=0.53
R2=0.35
R2=0.77
R2=0.7
R2=0.fi2
R2=0.92
750- MAE= 18.9
MAE= 1S
MAE= 15.2
MAE= 10.6
MAE= 1d.7
MAE= 11.8 .
500-
•
E250 -
- •
• • .
•
0 _
#BSI J #Field = d.46
#YSI J #Field = 0.7
• Y511 #Field = 11.fi
#Y51 i #Field = 0.7
•
#Y511 #Field = 0.14
YIf #Field = 0.69
a
MC45
MC47A
MC49A
MC50
MC51
MC66
C)750-
0
R2=0.78
MAE= 17.4
R2=0.S5
MAE= 15.9•
R2=0.87
MAE= 20.9
R2=0.78
MAE= 10.7
R2=0.9
MAE= 7.3
R2=0.21
MAE= 24.8
a 500
•
250 -
0-
SI J #Field = U.66
#YS'I J #Field = U.58
*YSI J #Field = 0.69
#YSI J #Field = U.5
#YSI J #Field = U.61
#YSI 1 #Field = U.47
m
MY10
MY11B
MY13
MY13A
MY1B
MY7B
750 -
R2=0.48
MAE= 17.3
R2=0.59
MAE= 15.3
R2=0.43
IdAE= 22.5
R2=0.59
MAE= 1, .6
R2=0.36
MAE= 26.5
R2=0.84
MAE= 9.4
0 500 -
250
•
0 _
S'I 1 #Field = U.68
SI I #FI#Id = U.74
SI 1 #Field = 0.66
YSI 1 #Field = U.49
YSI I #Field = U.57
YSI 1 #Field = 0.73
MY&
MY9
0 200 400 600
0 200 400 500
0 200 400 500
0 200 400 500
750-
R2=0.46
MAE= 11.1
R2=0.82
MAE= 7.4
500-
250-
0-
AKSI J *Field = d.68
YSI J #Field = 0.57
0 200 400 600
0 200 400 600
YSI - Spec. Cond juslcm)
Figure 72. YSI measured and field collected specific conductivity comparison for all sites. The
black line is a 1:1 line and the red number is the percentage of field measured data for which
there is a corresponding continuous data point.
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PH
MC14A MC17 MC22A MG25 MC27 MG29A1
•
R2=0.22 •'• R2�0.01 R2-04 "� • R2=Q.Q7 R2=0.25 R2=Q.13
8 - MAE= 0.3 • MAE= 0.3 MAE= 6.3 ' '• MAE= 0. MAE= 4.2 + • MAE= 0.3 • • _
• • •+: •• • : • • + .y •
7-
6 #YSI ! #Fie d = U.75 #YSI ! #Feld = 0.83 #YSI 1 #Fed = U.S3 #YSI 1 #Fed = U.75 #YSI ! #Field = O.83 #YSI I #Field = U.78
MC30A MC33 MC39 Mid MC40A MC42
R2=Q.0ER•• R2=0.31 R2=4.15 R2=0.12 R2=4.11 R2=U.22
8 - MAE�O • MAE= 0.2 MAE= 0.2 ' MAE= 0.3 • MAE= 4.3 MAE= U.3 •
7- . • r
6 - im'SI �#Field = 0.62 #YSI ! #Field = 0.84 #YSI I #Field = 0.66 #YSI I #Field = 0.95 #YSI.1 #Field = 0.29 �#YSIU#FekJ = U.88
= MC45 MC47A
a
R2-024 R2=0.2
m 8 - MAE= 6.3 ' MAE= 0.3
E
m7- •
U) •
6 - #YSII #Field = 0 78 #Y.SI ! *Field
[7
MY10 MY11B
R2 = 0.23 R2
8 - MAE= 0.3 V MAE= 0.3.
i• 7- •
6- #YSII#Field =4).83 #YSI!#Field
MYa MY9
R2=0.18 R2=039
8 - MAE= 0.3 MAE= 6.3 •
7-
6- #YSI 1 #Field = D.& ?SI I #Field - 0.66
6 7 8 9 6 7 8 9
MC49A MC50 MC51 MC66
R2=0.08 R2=U.12 R2=0.26 R2=0.1i
MAE= 0.2 • • MAE=OT MAE= D.3 : • MAE= 0.4
•
#YSI 1 #Field = U.75 #YSI 1 #Field = 0.61 #YSI 1 #Field = 0.66 #YSII #Field = U.56
MY13 MY13A MY1B MY7B
R2 0 =0.08 R2=QG.S.3 R2=.04 R2=0.03
MAE= 0.2 MAE= MAE--�}.3 MAE: 0.j�
#YSII #Field = U.73 #YSI I #Field = U.56 #YSI I #Field - 0.74 .1111 #Field - U.83
6 7 8 9 6 7 8 9 6 7 8 9 6 7 8 9
YSI - pH
Figure 73. YSI measured and field collected pH comparison for all sites. The black line is a
1:1 line and the red number is the percentage of field measured data for which there is a
corresponding continuous data point.
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Dissolved Oxygen
RIC14A MC17 MC22A MC25 MC27 MC29A1
R2=0.93 R2=0.7 R2=0.77 R2=0.35 R2=0.77 R2=0.81
15 •
MAE=*. MAE= U.8 : MAE= G.7 • MAE= O.fi • • MAE= U.5 MAE= 0.5 • •
•
5 #YSI1 #Field = 9.&1 #YSI1 #Field = U.fiB9.72 #'l511 #Field = 9.62 #YS11#Field = 9.72 #YSI I #Field = 9.72
MC30A MC33 MC38 MC4 Mr-40A MC42
•
R2=0.57 R2=0.64 R2=G.89 • R2=0.83 R2=G.89 R2=4.82 •
15 MAE= 1.3 • t MAF•= 0.7 • MAE= G.5 • MAE= 0.5 MAE=1.1 = MAE= 1 •'
10-
5- • • •• • •
#YSI I #Field = 0.47 #Y511 #Field = 0.75 SI1 #Field = G.fi2 #Y51 f #Field = 0.71 / #Y5I1 #Field = 0.22 YSI I #Field = 0.72
J
E MC45 MC47A MC49A MC50 MC51 M066
R2=G.9 R2=0.91 R2=G.79 R2=G.W R2=G.92 R2=G.6
15 MAE= G.7 • • MAE= G.9 MAE= G.5 MAE= G.5 MAE- G.5 • • MAE= 1.4
10 • • S
E 5- �• •
YSl f #Field = U.fid #YSI1 #Field = 0.55 #YSI1 #Field = O.fifi #YSI I #Field = 0.47 Y511 #Field = 0.62 • #YSI I #Field = U.32
MY10 MY11B MY13 MY13A MY1B MY7B
U R2=0.79 R2=G.87 R2=0.55 • R2=0.71 • R2=0.71 • R2=0.86
15 MAE= 0.3 • MAE= 0.6 MAE= 4.8 • • • MAE= 0.6 MAE= 4.6 • • MAE= G.7 •
10- • ti
•
•
5- •
P I #Field = U.6S #YSI1 #Field = 0.68 #YSI I #Field = U.58 #YSI I #Field = U.49 #YSI I #Field = U.61 #YSI I #Field = U.75
MY9 MY9 0 5 10 15 0 5 10 15 0 5 10 15 0 5 10 15
R2=4.84 R2=0.7615- •
MAE= 0.6 • MAE= 0.9
• •
t
10- • • .
5- • •
#Y311 #Field = U.71 #71 #Field = 0.57
0 5 10 15 0 5 10 15
YSI - Da (mg/L)
Figure 74. YSI measured and field collected dissolved oxygen comparison for all sites. The
black line is a 1:1 line and the red number is the percentage of field measured data for which
there is a corresponding continuous data point.
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o-
MC14A MC17 MC22A MC25 MC21
9-
6-
0 •
• •
• •
M4 M.'F�
i
0 100 200 300 400
0 50 100 150
0 250 500 750 1000 12500 100 200
300 0 100 200 300 400 500
MC29A1
MC30A
MC33
MC38
MC4
9-
6-
y
`
ii•
0 50 100 150 200
0 5 10 15
20 0 100 200 300
0 1(0 200
3U0 0 100 260 300 400 500
MC42
MC45
MC47A
Mr"
MC50
m g-
6-
0-•' •
�iY •
. w
44
i.. f
F
0 50• 100 150
0 300 600 900
0 50 100
0 250 500
750 0 5 10 15 20•
MC51
MC66
MY10
MY11B
MY13
9-
0 - L . .
` •
•
M
.. w
0 100 200
300 0 25 50 75
1000 100 200 300
0 50 100
150 0 50 100 150
MY1B
MY713
MYS
M19
9-
6-
0- �• .
. &Lee•••
L i •
i
0 100 200
0 10 20 30 40
50 0 100 200
Flow (Cfs)
0 10 20 30
40
Figure 75. Difference between YSI
automated measurements
and field measured DO versus
streamflow at the
time of sampling.
a
a
L"
— YSI
• grab sample
0
0
v
o
o
a
C)
a
a
6V
as
a
U)
0
2008 2009 2010 2011 2012 2013
Figure 76. YSI measured and field collected specific conductivity data for site MY8 from 2008
to 2013.
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NC STATE UNIVERSITY
0
OD
0
w
L�
QD
0
QD
YSI
+ grab sample
+
�41 IYI.� i �,! J�✓V + 1�1� . ++, 14I ��� I7� IN1 +k + J +Ml
2013 2014 2015
Figure 77. YSI measured and field collected pH data for site MY8 front 2013 to 2015.
7.5.3 Temperature
YSI continuous temperature measurements had the least difference and highest correlation when
compared to the manual field measurements (Figure 76). This is not surprising given temperature
probes are typically stable and not susceptible to fouling or drift.
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Temperature
MC14.A
MC17
MC22A
MC25
MC27
MC29A1
30-
•
•
2
R2=0.99
R2=0.99
R2=0.98
•
R2=0.5R
R2=0.99
20 _
MAE= 0.4
MAE= 0.4
MAE= 0.6 •
MAE= 0.`
MAE= 0.4
10-
•
X.85
0 _
#Y511 #Field = U.79
#YSI I #Field = U.BS
•#Y511 #Field = 0.SS
#YSI I #Pied = U.S
NYSI1 #Field = U.S7
MCWA
MC33
MCM
MC4
MC40A
MC42
30-
R2=0.99
R2=0.99
R2=0.99
R2=0.84
R2=0.99
20-
MAE= 0.5
MAE= 0.d
MAE= 0.4
MAE= 0.7
MAE=0.4
10-
>MAE=G.4
0-
#Y511#Field = 9.65
#YS11 #Field = 0.9#Field
= U.7
#YSI i #Fiel] = 3.87
• #YSI I #FIeIA = U.31
• #YSI I #Field
n
MC45
MC47A
MC49A
MC50
MC51
MC66
m30-R2=U.98
~ 20_
MAE= 0.6
R2=1
MAE=0.3
R2=0.99
MAE= 0.4
R2=0.96
MAE=0.6 •
R2=0.99
MAE= 0.4
R2=0.99
MAE= 0.5
10-
•
•
fA 0_
NY51I#Field =U.82
#YSII#Field =0.7
#Y511#Field =U.B
#YtI1#Fiek1J =0.69
#YSI1#Field =U.75
#YSII#Field =0.6
n
r
MY1D
MY11B
MY13
MY13A
MY1B
MY713
U 30-
R2=0.99
R2=0.99
R2=0.99
R2=0.99
R2=0.98
R2=1
20-
MAE= 0.5
MAE= 0.4 •
MAE= 0.4
MAE= 0.5
MAE= 0.6
MAE= 0.3
10-
•
0 _
#YSI I #Field = U.85
#YSI I #Field = 0.84
#YSI 1 #Field = U.78
#YSI I #Field = U.6
#YSI I #Field = 0.78
#YSI I #Field = U.9
0 10 20 30
0 10 20 30
0 10 20 30
0 10 20 30
MY&
MY9
30-
R2=&98
R2=0.99
20 -
MAE= 0.5 •
MAE= 0.4
10-
0-
#YSI I *Field = 0.84
#YSI 1 #Field = 0.67
0 10 20 30
0 10 20 30
YSI-Temp ('C)
Figure 78. YSI measured and field collected temperature comparison for all sites. The black
line is a 1:1 line and the red number is the percentage of field measured data for which there
is a corresponding continuous data point.
7.6 Appendix F. Comparison of WWTP Estimated Loads to DMR Reported Loads.
The WWTP loads that were calculated using WRTDS-K and the load apportionment method
described in section 2.3.1 were compared to the TN and TP DMR loads available from the
EPA's Enforcement and Compliance History Online (ECHO) tool. ECHO data as loads were not
reported after 2015 for the Irwin Creek WWTP and missing/incomplete records were common
for TP loads. Despite these issues, the DMR loads were very similar to the loads calculated using
the WRTDS-K and the load apportionment estimate (Figure 77).
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McAlpine Creek - TN
4,500,000
-
100,000
4,000,000
-
90,000
3,500,000
-
:2
80,000
0 3,000,000
0
70,000
2,500,000
60,000
2,000,000
50,000
40,000
m 1,500,000
m
30,000
Q 1,000,000
Q
20,000
500,000
10,000
0
0
yo ti~ yti ti'' ti� ti5 tid tit ti y°' y°
�o do �o do ,yo ,yo do ,yo ,yo ,yo ,yo
■ NCSU- WRTDS-K ■ ❑MR
Sugar Creek - TN
1,000,000
_ 900,000
800,000
m 700,000
0
c 600,000
~ 500,000
3; 400,000
300,000 j!jNfl 11
c
a 200,000
100,000
0
y° titi titi ti3 ti& Spa y�O tiA ti(b ti� do
,yo do ,yo do ,yo do ,yo do ,yo ,yo ,yo
800,000
- 700,000
n
600,000
0
500,000
a
400,000
300,000
200,000
C
Q 100,000
0
■NCSU- WRTDS-K ■ ❑MR
Irwin Creek - TN
ti ti ti ti ti ti ti� ti ti ti
■ NCSU- WRTOS-K ■ ❑MR
120,000
100,000
0 80,000
a
McAlpine Creek - TP
�°
ti�
titi
ti�
ti°`
tih
ti°
ti�
ti�
tig
ti°
do
do
,yo
,yo
do
do
do
,yo
do
,yo
,yo
■NCSU- WRTDS-K ■ ❑MR
Sugar Creek - TP
� 60,000
� 40,000
c
a zo,oao
0
ti� tit ti� P ti°
,yo ,yo ,�o ,yo ,yo
180,000
160,000
140,000
a
0 120,000
100,000
S0,000
60,000
40,000
Q
20,000
0
■ NCSU- WRTDS-K ■ ❑MR
Irwin Creek - TP
,ycP ,yoti tioti ,yoti tioti ,yoti ,yoti ,�oti ,�oti ,yoti tioti
■ NCSU- WRTDS-K ■ AMR
Figure 79. Comparison of TN and TP WWTP loads generated using WRTDS K and
watershed load apportionment to loads reported from DMRs.
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