19970093 Ver 1_Monitoring Report_20030721

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BASELINE WATER QUALITY MONITORING FINAL REPORT
NORTH CAROLINA GLOBAL TRANSPARK
LENOIR COUNTY, NORTH CAROLINA
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Prepared for: f?j?j?c 1 ??43
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North Carolina Global TransPark Authority
Lenoir County, North Carolina
Prepared by:
EcoScience, Corporation
1101 Haynes Street, Suite 101
Raleigh, North Carolina 27604
June 2003
EcoScience
1101 Haynes Street Suite 101 Raleigh, NC 27604 Telephone: [phone] Fax: [phone]
July 11, 2003
Mr. John Dorney
N.C. Division of Water Quality
DENR - Wetlands/401 Unit
1621 Mail Service Center
Raleigh, North Carolina 27699-1621
I I */V, -
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Re: North Carolina Global TransPark - Water Quality Monitoring 01-090.02
Dear John:
On behalf of the North Carolina Global TransPark (NCGTP) Authority, we are pleased to
provide you with our Baseline Water Quality Monitoring Final Report for NCGTP. This
report represents 2.5 years of water quality sampling at key locations in NGTP waterways
(Stonyton Creek and Briery Run). The purpose of this work was to obtain hydrologic and
nutrient-concentration information necessary to establish pre-project, or baseline, nutrient
loadings for runoff constituents, primarily Total Nitrogen and Total Phosphorus. A
secondary objective was to conduct a modeling exercise to identify for the Stonyton
Creek watershed: 1) appropriate nutrient loading coefficients (ExCo values) for different
land use types, and 2) to develop an applicable nutrient transport coefficient under
existing hydrologic conditions. This work is in keeping with mandates expressed in the
NCGTP 401 Water Quality Certification and the Baseline Water Quality Monitoring
Program submitted by our firm and approved by the Division of Water Quality (DWQ).
We would appreciate your review of this document and would be happy to answer any
questions you may have. Upon completion of your review, we would also like to request
a meeting to discuss future water quality monitoring expectations by DWQ at the
NCGTP site. I will call you within 30 days to discuss this matter. By copy of this letter,
we are also providing this report to the U.S. Army Corps of Engineers for review.
Sincerely,
ECOSCIENCE CORPORATION
keMcCrain, Ph.D., CEP
President
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cf, J?_?
dy
cc: Ms. Darlene Waddell, NCGTP
Mr. Scott Jones, COE '?
Re: NC Global Transpark Report
Subject: Re: NC Global Transpark Report
Date: Tue, 05 Aug 2003 12:46:31 -0400
From: Trish MacPherson <[e-mail]>
To: dave penrose <[e-mail]>
Since there was just one paragraph about benthic data, I don't have many
comments, except to say that I would agree with that paragraph if it
were referring to a coastal A type stream. Stonyton Creek, per your
comments in 4D is not a true flowing stream, and even the report says it
has a restricted flow regime. The lack of EPT taxa is not necessarily C
an indication of poor conditions, rather it indicates a lack of flow.
We did not rate our one benthos sample for just that reason. It appears IN
this data has been taken out of context. o/O
?00
Jay's Unit would provide better comments on the bulk of the report, so
I'll ask him to look at it-if he doesn't want to, I'll return to you.
dave penrose wrote:
> Hey Guys,
> Larry Eaton sent you a copy of the baseline WQ monitoring report for the
> Global Transpark project in Lenoir county (EcoScience). John's asked me
> to coordinate the responses back to EcoScience. When you get the report
> please look it over for accuracy and comment to me. I'll prepare the
> response letter. I'll be out of the office all of next week, so please
> try to get me your reveiws by August 20th. Thanks.
> Dave
Trish Finn MacPherson
NCDWQ
1621 Mail Service Center
Raleigh, NC 27699-1621
919-733-6946 x238 FAX [phone]
1 of 1 8/5/03 2:27 PM
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EXECUTIVE SUMMARY
' Land-use changes associated with North Carolina Global TransPark (NCGTP) development may alter
hydrological and nutrient dynamics of a sizable watershed within the Neuse River Basin. An
' environmental sampling protocol, as spelled out in the Revised Baseline Water Quality Monitoring
Program for NCGTP (EcoScience 2000), calls for the establishment of NCGTP-wide, pre-project
(baseline) nutrient loading rates for future, post-project comparison. This is the final report for the
baseline effort, which documents annual loading rates within the Stonyton Creek and Briery Run
' watersheds, the two prevalent NCGTP watersheds expected to receive the majority of initial development.
This report includes the methodology used during data collection and analysis, and expands upon the
' processes presented in the interim Baseline Water Quality Monitoring Report (EcoScience Corporation
2002).
Analysis of baseline water-quality and discharge data for seven sub-watersheds within NCGTP reveals
' that average annual flow rates within separate reaches ran ec from 0. Z4 to 6 Q6 cubic feet per second
(cfs) (20.1 to 171.6 liters per second [Is]) for the Stonyton Creek drainage and from 1.66 to 2.35 cfs (47.0
to 66.5 is) for the Bnary _.Run drainage. Base?w?y?R?o-,~-,?µ?J-.pVM??-?.?.-.?. µ??LL
don these discharge values and the corresponding measured
nutrient concentrations at each station, we estimated average, annual nitrogen loading for the various sub-
watersheds within NCGTP to range between 1,990 to 11,486 kilograms per year (kg/yr). Average, annual
TN and TP loading for the BriarY Run at the most downstream monitoring location (BR 06 and BR 08
'
combined) was estimated to be 1/yr, and 438 kg/yr, respectively. Average, annual TN and TP
' loading for Stonyton Creek at the most downstream monitoring location (SC3-11) was estimated to be
10,262 k / and 1.J,?,61 kg/yr, res ectiveIX. Flow regimes within the two subject drainages were notably
' different: Stonyton Creek has a restricted flow regime caused by numerous beaver impoundments, while -,
the Briary Run drainage is relatively free flowing. Consequently, flow rates of Stonyton Creek are nearly
' 40-percent less than that of similar-sized sub-watersheds within the Briery Run drainage. In fact, while
watershed size increases over 20 percent in the furthest downstream reach of Stonyton Creek (between
' NC 58 and E. N. Dickerson Road), total nitrogen loading unexpectedly decreases 11 percent (11,486 to
10,262 kg/yr) and total phosphorus decreases 4 percent (1,311 to 1,261 kg/yr). This observed reduction of
' total nitrogen and phosphorus loading in Stonyton Creek is presumably due to predominant low flow
conditions, which in turn heighten sedimentation, denitrification, and removal of adhered phosphorus
compounds.

1

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assessed and transport rate coefficients were derived through modeling efforts that compared model
' outputs with direct measurement results. One of the two loading coefficient sets, in conjunction with a
transport rate coefficient of 0.5, produced loading values very similar to those measured via in-stream
nutrient sampling. Thus, the applied model and the these input variables may be considered appropriate
for estimating nitrogen lc-ding in the Stonyton Creek watershed. , However, it should be noted that the
trans ort model results are largely based upon the existing hydrologic conditions as the affect nutrient
'
rate within Ston on Creek. Of loading
coefficients applied in the model,
yt agricultural lands simulated the
' highest levels of nitrogen annually, which suggests that agricultural lands within NCGTP contribute a
higher nutrient load to Stonyton Creek than do other land use types. Thus, development that converts
agriculture into other land uses will likely lessen future nitrogen loading into the Stonyton Creek
wate-`rrsed.- Finally, it will be imperative that Best Management Practices be applied to all forthcoming
development to facilitate nitrogen removal processes during storm-water runoff events.
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TABLE OF CONTENTS
Page
1.0 INTRODUCTION ....................................................................................................................... 1
2.0 STUDY SITE ............................................................................................................................. 4
3.0 METHODS ................................................................................................................................. 4
3.1 NCGTP Watershed and Land-Use Delineation ................................................................ 4
3.2 Water-Sampling Schedule and Continuous Monitoring ................................................... 7
3.3 Stage-Discharge Relationship ........................................................................................... 9
3.4 Determination of Discharge at Un-Gaged Locations ........................................................ 9
3.5 In-Situ Nutrient-Load Estimations .................................................................................... 12
3.6 Modeling of Watershed Nutrients ..................................................................................... 12
4.0 RESULTS, DISCUSSION, AND FUTURE CONSIDERATIONS ........................................... 18
5.0 REFERENCE .............................................................................................................................. 23
LIST OF FIGURES
Figure 1: Site Location ....................................................................................................................... 2
Figure 2: Land Cover ......................................................................................................................... 5
Figure 3: Monitoring Locations ......................................................................................................... 8
Figure 4: Stage-Discharge Relationships ........................................................................................... 10
Figure 5: Discharge Time Series ........................................................................................................ 11
Figure 6: MODGTP Model Schematics ............................................................................................. 17
Figure 7: In-situ versus Model Loading Comparison ........................................................................ 20
LIST OF TABLES
Table 1: Sub-Watershed Size and Land-Coverage Type .................................................................. 6
Table 2: Nutrient Loading Rates per Sub-Watershed ....................................................................... 13
Table 3: Nutrient Loading Coefficient (ExCo) Values Applied in Model ....................................... 16
iii

LIST OF APPENDICES
' Appendix 1: Water Quality Results
Appendix 2: Discharge-Loading Relationships
' Appendix 3: Macro-invertebrate Data

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BASELINE WATER QUALITY MONITORING REPORT
' NORTH CAROLINA GLOBAL TRANSPARK
LENOIR COUNTY, NORTH CAROLINA
1.0 INTRODUCTION
' As development associated with the North Carolina Global TransPark (NCGTP) intensifies, land-use
changes will occur that may substantially alter regional hydrologic and nutrient dynamics. Development
' so far has primarily surrounded the Kinston Regional JetPort, located north of the town of Kinston in
Lenoir County, North Carolina (Figure 1). However, future development will include airfield facilities
' and related taxiways designed to support the incremental development of adjacent industrial park
facilities. The airfield structures will be a component of an inter-modal transportation facility that will
provide time-critical distribution of goods and services to commercial, agricultural, industrial, and
military clients.
In a steady-state, natural environment, long-term nutrient budgets for a given area would be in balance.
However, as land-uses change, so do input and delivery of nutrients, as well as the downstream transport
' rates of nutrients within local waterways. Furthermore, differing land coverage types load nutrients into
waterways at distinctly different rates (Dodd et al. 1992), and agricultural lands typically produce loading
' at high rates because of fertilizer application, erosion, removal of vegetation, livestock wastes, etc.
Therefore, conversion of NCGTP-agricultural lands into other land-use types through smart development
' may lessen nutrient additions into local waterways. The apriori rationale is that the proposed land-use
conversions of agricultural fields into other, more environmentally sound uses, coupled with a basinwide
' approach to stormwater management by the NCGTP Authority (Authority), will create an environment
favorable to reduced nutrient loading and off-site delivery conditions. The baseline results compiled
within this document, when compared with future nutrient-monitoring efforts, should be used to assess
the above rational.
This task requires methods that spatially and temporally reflect a continuous, complex interaction
between natural and anthropogenic forcing mechanisms. The introduction and transport of nutrients
' (namely nitrogen and phosphorus) into and along waterways involves many processes (Schlesinger 1997).
Nutrients, primarily nitrogen, are constantly deposited into rivers and their watersheds through

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FIGURE
Global TransPark SITE LOCATION
CAROLINA GLOBAL TRANSPARK Ckd by:
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Lenoir County
North Carolina Date:
JUNE 2003 1
Management Plan , Project: 01-090.02

atmospheric deposition of up-wind sources. These sources, in addition to anthropogenic inputs (i.e.
fertilizers, livestock/septic inputs, etc.) are incorporated into a watershed's nutrient cycling processes,
' stimulating vegetative growth. However, surplus nutrients unused by the ecosystem are washed into
waterways along with leaf litter and other loose organic matter during runoff events (nutrient load). The
amount of nutrients washed into the receiving waterways is a function of proximity, ease (duration) of
transport, and the watershed's on-land, nutrient consumption/degradation rates. Once land based
nutrients arrive into surrounding waterways, they enter an aquatic nutrient cycle (are recycled) while
being transported downstream. Also, depending upon the hydrodynamics and rate of bio-degradation, a
' portion of the nutrients may escape the recycling process through sedimentation and denitrification. The
degree of nutrient removal via these processes greatly determines the rate that the remaining, unprocessed
' nutrients are transported downstream (transport rate) of a given reach. Thus, the nutrient transport rate is
inversely related to the degree of nutrient uptake/removal for a given reach of stream.
' As spelled out in the Revised Baseline Water Quality Monitoring Program (EcoScience 2000) for
NCGTP, EcoScience Corporation has been tasked to document baseline water quality conditions within
NCGTP waterways prior to anticipated, large-scale development. The objective of the Revised Baseline
Water Quality Monitoring Program was to obtain the hydrologic and nutrient-concentration information
' necessary to estimate baseline, in-situ nutrient-loading (kilograms per year) within the major waterways
of NCGTP, namely Briary Run and Stonyton Creek. A secondary objective of the study was to conduct a
modeling exercise to identify for the Stonyton Creek watershed 1) appropriate nutrient loading
coefficients (ExCo values) for different land use types, and 2) an applicable nutrient transport coefficient
under existing hydrologic conditions.
' In order to fulfill the objectives of the monitoring program, a tiered approach was utilized, which included
data collection of stream velocities and physical/chemical properties, followed by time-series processing
and analysis and annual nutrient load calculations, and finally, comparison of the estimated, in-situ
nutrient load (for Stonyton Creek) with the model output using different ExCo values and in-stream
' transport rates of nitrogen. Baseline studies extended from August 2000 to March 2003 and represent
"pre-project" conditions at the NCGTP site.

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2.0 STUDY SITE
The Authority has designated NCGTP to ultimately include approximately 6,154 hectares situated around
the existing Kinston Regional JetPort (Figure 1). The area encompasses approximately 2,337 hectares
where the primary airfield, air cargo facilities, and industrial infrastructure will be concentrated as
approved under a Section 404 Permit issued by the Army Corps of Engineers (COE) and 401 Water
Quality Certification issued by the North Carolina Division of Water Quality (DWQ). The remaining
3,817 hectares include adjacent areas slated for future outgrowth that may be associated with NCGTP.
Project location and development infrastructure for NCGTP has been detailed in the Airport Master Plan
(NCGTPA 1993) and a Final Environmental Impact Statement (NCGTPA 1997).
The NCGTP Site has been subdivided into four watersheds: 1) Stonyton Creek (SC), 2) Briery Run (BR),
3) Wheat Swamp (WS), and 4) Gum Swamp (GS). As shown in Figure 2, these watersheds have been
further segregated into 37 preliminary sub-watersheds with separately estimated land-coverage
distinctions. Table 1 depicts the name and area by land-coverage type for each sub-watershed.
Baseline nutrient-sampling activities focused mainly on Stonyton Creek and to a lesser extent Briery Run,
both of which are slated to receive the majority of initial development. Initial development is expected to
include the primary airfield, air cargo facilities, and initial industrial infrastructure. Briery Run and
' Stonyton Creek are fairly disturbed in that long reaches of each have been straightened and are lacking
forested riparian vegetation. Agricultural fields and fragments of deciduous forests dominate current
' land-use practices within both watersheds. In addition, the majority of Stonyton Creek within the
NCGTP boundary is heavily impacted by beaver dams that restrict flow and encourage prolonged
flooding into the adjacent floodplain.
3.0 METHODS
3.1 NCGTP Watershed and Land-Use Delineation
A Geographic Information System (GIS)-based analysis of geo-referenced digital files of 1998 aerial
orthophotography, USGS quadrangles, 14-digit hydrologic units, and river watershed and sub-watershed
' boundaries allowed for precise delineation of the four watersheds, sub-watersheds, and land-coverage
types within the NCGTP boundary (Figure 2, Table 1). These data sets, provided by the Center for

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Geographic Information and Analysis (CGIA), enabled area calculations of the different land-coverage
types within each sub-watershed (Table 1) for use in subsequent ExCo-loading estimations.
3.2 Water-Sampling Schedule and Continuous Monitoring
The backbone for the analysis is chemical/nutrient concentration and discharge data for targeted reaches
of the NCGTP watersheds. Together, these data allow numerous ecological investigations, including a
quantitative assessment of in-situ nutrient loading rates during the baseline period within Stonyton Creek
and Briery Run. Physical and chemical water measurements at seven locations and discharge at three
locations were collected from August 2000 through March 2003. Figure 3 illustrates the positions of the
water-sampling locations and continuously recording flow sensors (gage sites).
Stream physical and chemical properties were directly sampled at the seven sites shown in Figure 3. In
order to better detect short-term changes in discharge (both baseflow and discharge events) and chemical
concentrations, the original mid-month water-sampling routine was changed in the fall of 2001 to a
bimonthly sampling regime that targeted rain-event activity. All necessary chemical analysis was
performed at a DWQ-certified laboratory in Kinston, North Carolina. Concentration measurements
include ammonia, nitrate, TKN nitrogen (organic and ammonia nitrogen), total phosphorus, total
suspended solids (TSS), turbidity, and fecal coliform (Appendix 1). Stream discharge information was
based on stream-velocity and water-level (stage) data collected at three stations (Figure 3), two of which
(BR08 and SC07) were also water-sampling locations. Velocity and stage data were recorded with 2150
Isco flow modules (gages), which employ an acoustic doppler current profiler (ADCP) for measuring
average velocity and a differential pressure transducer to measure level of the water column.
Measurements of channel cross-sectional area were made at each gage site so that water depth
measurements could be correlated to water column cross-sectional area. The flow modules were
programmed to store stage and velocity measurements at 15-minute intervals. Stored data were retrieved
and entered into a database once per month.
3.3 Stage-Discharge Relationship
In order to determine stream discharge at each of the three gage sites, it was first necessary to develop a
stage-discharge relationship, which ascertains discharge from recorded stage and velocity. Determining
discharge was accomplished by multiplying the 15-minute logged stage values (in cross-sectional area of
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' the water column, [fe]) times the corresponding logged water velocity (ft/sec) values to obtain a resultant
discharge value, cubic feet per second (cfs), basically:
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A mathematical stage-discharge relationship was then developed by plotting stream stage (ft) and
' discharge (cfs) time series during periods when the full range of stage was recorded over a short time
period, primarily during and following rain events (Gordon et al. 1992). This procedure is noted to
' produce more reliable results than a Manning's analysis (Bovee and Milhous 1978), and allows
instantaneous discharge estimates based on stage measurements alone. Although it is not necessary to
' determine a stage-discharge relationship if velocity is continuously measured, it was found to be required
for this study because velocity measurements were not always reliable (due to sensor obstructions in the
.stream channel such as sedimentation, vegetation, logs, etc). Figure 4 graphically illustrates power-
function regression equations that determine the volume of water that will discharge (y-axis) at a given
' stage (x-axis) for each gage location. Computed discharge time series (Figure 5) show discharge (1-hour
intervals) for each gage site gage as a function of time (x-axis).
3.4 Determination of Discharge at Un-Gaged Locations
Due to the limited number of gages, discharge could be physically measured at only a few reaches. Since
discharge information was needed at each of the seven nutrient sample sites, two techniques were
' employed to approximate discharge at ungaged sites. The first technique utilized a drainage-area ratio
between gaged and ungaged sites to obtain discharge for the ungaged sites. This method was used for the
' Briery Run sites and on the Stonyton Creek sites when only one gage was in operation. This is an
accepted technique for estimating flow downstream of USGS gaging stations and assumes that as
' watershed size increases along a given stream reach, discharge will increases proportionally (Robbins and
Bales 1995).
' The second method was applied on Stonyton Creek when both gages were in operation. This method did
' not allow mid-reach discharge estimations to be higher or lower than the bounding upstream- or
downstream-gage values. Basically, this method fits a regression line between two points of known
' watershed size and discharge located upstream and downstream of the ungaged site (watershed size [x-
axis] and discharge value [y-axis] for the two end points). The regression equation is then used to
estimate discharge at the un-gaged site where watershed size is known.

Figure 4: Stage - Discharge Relationships for NCGTP Gaged Stream Reaches
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Figure 5: Discharge Time Series for NCGTP Gaged Reaches
Briery Run Sub-Watershed 08 Discharge
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0 50
25
6K- ILI L 11 1L.
0
8/1/00 12/1/00 4/1/01 8/1/01 12/1/01 4/1/02 8/1/02 12/1/02 4/1/03
Stonyton Creek Sub-Watershed 07 Discharge
ou
40
30
a)
ca
20 -
10
0
8/1/00 12/1/00 4/1/01 8/1/01 12/1/01 4/1/02 8/1/02 12/1/02 4/1/03
Stonyton Creek Sub-Watershed Reference Discharge
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c?
t
N 100
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8/1/2000 12/1/2000 4/1/2001 811/2001 12/1/2001 4/1/2002 8/1/2002 12/1/2002 4/1/2003

3.5 Nutrient-Loading Estimations
Results from the water-sampling schedule produced concentration values for many different chemical and
physical parameters. In-stream nutrient-load (Table 2) was calculated at all seven water-sampling sites
' (including two of the three gage sites) for 41 separate sampling dates (Appendix 1). This was
accomplished by first multiplying the measured total nitrogen (TN) and total phosphorus (TP)
concentrations (milligrams per liter [mg/1]) by the discharge (converted from cfs to liters per second [Is])
at the time of each sampling, followed by a conversion of these values to TN and TP loading rates,
' kilograms per day (kg/d). Steps in the conversion process are shown below.
' Discharge (cfs) x 28.32 = Discharge (Is),
Discharge (Is) x TN/P (mg/1) = Load (mg/s)
Load (mg/s) x 0.0864 = Load (kg/d)
Discharge-loading relationship multipliers were then generated through a linear-regression analysis
between a scatter plot of discharge and loading rates for each sample date (n = 41) and at each of the
seven sampling sites (Appendix 2). These mulipliers, based on data collected on the 41 sampling dates,
' were then used to convert average daily discharge values to average TN and TP, in-situ loading rates for
an entire year (kg/yr).
3.6 Modeling of Watershed Nutrients
' Past investigations (D? odd et al. 1992• DWQ 1998) have attempted to determine theoretical in-situ
' loading rates (ExCo values, expressed in unit mass/area/time) for a given stream reach based on
knowledge of drainage area of upstream land-coverage types. The development of Export Coefficient
' (ExCo) values is a tool that can be used by land developers and managers for making preliminary
estimates of potential loading scenarios. ExCo values may be determined by in-situ measurements for
' surface and/or groundwater contributions to streams, although prior investigations have reported
coefficients based on surface runoff alone. Another method combines both sources of input to calculate
ExCo values that may be higher than the surface-only method, depending upon dilution effects of the
' groundwater source (Bachman et al. 1998).

12

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' Modeling efforts allow a numeric approach of assigning nutrient loading rates to particular land-cover
types. In doing so, the hydrodynamics of the stream need to be quantified to determine water transit times
' and nutrient decay rates. If nutrients were conservative compounds (i.e. not biochemically influenced),
generation of ExCo values would be a fairly straightforward task. However, nutrient compounds are
volatile, and as already discussed, in-stream processes readily remove nutrients from the water column
through particulate deposition and denitrification processes. Both of these processes result in a net
removal/decay of the amount of `deliverable' load to a given point downstream witch can be
quantitatively defined as a transport coefficient k.
' Prior studies have derived in-stream transport variables for nitrogen under a variety of conditions with
' the more advanced simulations assigning transport values dependent upon stream depth and discharge
(Preston and Brakebill 1999; Preston et al. 1996). More simplistic approaches apply a global value valid
for an entire watershed (DWQ 1998), while others only perform budget computations that report
differences between source-loading and downstream outputs (Goolsby et al. 1997). In any case, the in-
stream loss of nitrogen is dependent upon the dimension of the stream and flow velocity, and will
therefore vary accordingly (Preston et al. 1996; Preston and Brakebill 1999; Showers et al. 2002).
' The importance of a model application in this study was to determine, by means of comparison, which
TN-ExCo value set and transport rate coefficient are applicable to the Stonyton Creek watershed. These
' values could then be extrapolated to other tracts within the NCGTP boundary. The hypothesis behind the
model application is that if the input ExCo values and transport rate coefficient produce nitrogen loading
' rates (kg/ha/yr) similar to that of the measured, in-situ loading results, then the selected input values can
be considered appropriate for estimating future loading rates within GTP, given the hydrolologic regime
' remains similar to that of existing conditions. Consideration of changes in the hydrologic regime are
important because transport rate of nutrients, a major component of the model, is greatly affected by
' variation in stream cross-sectional area and water velocity.
' A numeric model, herein referred to as MODGTP, was created using EXTEND software (EXTEND
2000). The, model is a simplified, spatially referenced, regression model (Preston et al. 1996) that
' attempts to ascertain loading based upon surface and groundwater nutrient contributions combined.
MODGTP follows the basic form:
I Li- r(i=1, N) [Mlc(i),ExCo(i) x e (-krrz)] + [Up x e (-kt)]

14

where,
' L _ load in reach(j) ;
N total number of considered reaches;
MloEXco = ExCo values representing nutrient load as a function of percent land-
use coverage for the reach(j) sub-watershed
k = in-stream transport constant;
' t = time in days to travel through reach(j);
e = base of natural logarithms
' Up = delivered, cumulative nutrient load from adjacent, upstream reach.
The ExCo values chosen for MODGTP are those suggested by DWQ (1998). Two different sets of ExCo
' values were used for comparison to the in-situ loading rates; specifically the DWQ median and high-end
range sets (Table 3). Each ExCo value represents the nitrogen loading rate associated with a given land
' use, as a function of kilograms nitrogen per hectare per year (kg/ha/year). To compare these two sets of
suggested loading rates with the in-situ loading rates, the area (ha) of each land use type (for each
' Stonyton Creek sub-watershed) was measured and multiplied by the corresponding ExCo values of each
set, and then input into the model (Table 3). A transport rate coefficient k was selected for each set of
' ExCo values by finding the integer that produced a "best fit" loading rate output (when compared to the
in-situ loading rate of each sub-watershed).
' A graphic illustration of MODGTP is shown in Figure 6. The graphic is composed of three sections: the
' yellow-, blue-, and green-shaded areas. The yellow shade lists ExCo values for specific land-coverage
types and the chosen transport rate coefficient. The blue shade quantifies the length of time required for
' water to flow between monitoring stations - a parameter based upon discharge and cross-sectional areas
that generates a velocity, and subsequently a transit time when applied over a given reach. Lastly, the
green shade uses results from the yellow and blue shades to compute TN load at each monitoring station
' and an amount transported to the successive, downstream monitoring station. Model-result performance, 7
y??S
which will be discussed in the next section, will compare TN loads generated in the green-shade
' component of MODGTP with in-situ loads derived from field-collected data (Table 2).
?/
' The major assumptions in MODGTP are that 1) no land-surface influences spatially affect TN-delivery
rates to streams, 2) all loading for a specific sub-watershed is input midway between the neighboring up
' and downstream monitoring sites, and 3) ExCo and transport rate coefficients are constant for all sub-
watersheds.
15

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4.0 RESULTS, DISCUSSION, AND FUTURE CONSIDERATIONS B v?
1 Analysis of baseline water-quality and discharge data r seven sub-watersheds within NCGTP reveals
that average annual flow rates within separate re es ranged from 0.74 to 6.06 cfs (20.1 to 171.61s) for
1 the Stonyton Creek drainage and from 1.66 2.35 cfs (47.0 to 66.51s) for the Briary Run drainage (Table
2). Based on these dis value and the corresponding measured nutrient concentrations at each
1 station, we estimat average ual nitrogen loading for the various sub-watersheds within NCGTP to
range between 1,99 to , 86 kg/yr. Average, annual TN and TP loading for the Briary Run at the most
1 downstream monitoring location (BR 06 and BR 08 combined) was estimated to be 6,358 kg/yr and 438
kg/yr, respectively. Average, annual TN and TP loading for Stonyton Creek at the most downstream
1 monitoring location (SC3-11) was estimated to be 10,262 kg/yr and 1,261 kg/yr, respectively.
1 In-situ estimates of average, long-term TN and TP loading along Stonyton Creek show down-river
decreases (Table 2). Between monitoring sites SC4-10 and SC3-11, TN loads fall 11 percent from 11,486
1 to 10,262 kg/yr, while TP loads decrease 4 percent from 1,311 to 1,261 kg/yr. These mid-reaches of
----------------------
Stonyton Creek have numerous beaver - and therefore have large
1 cross-sectional areas and impart sluggish flow velocities.

1 In some cases when extended high water has caused impacted, low-lying sections of stream channel,
h
l
i
l
nd bi
h
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e
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e a
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e, pro
uc
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e
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ose
match those of ponds. This ponding action encourages a very high rate of in-stream nutrient loss (Rice et
1 al. 1998) through increased sedimentation and deposition of organic matter. Organic matter deposition
removes particulate forms of nitrogen, and sedimentation transfers particulate forms of phosphorus from f

1 the water column to the bottom layer (Pinckney et al. 1998). Organic matter loading also spurs biological d/dC?01rr"OC?
-
oxygen demand (BOD) near the sediment interface, promoting anoxia coverage and further reducn oof
1 TN through denitrification processes (Paerl et al. 1998). Supporting this idea, extremely low dissolved
oxygen and low turbidity conditions are frequent at the downstream monitoring site SC3-11 (Appendix
1 1)
1 Nutrient loads (per unit area) in Briery Run appear to be somewhat elevated when compared to those of
Stonyton Creek (Table 2). Unlike Stonyton Creek Briery Run is relatively free of beaver impoundments,
1 and therefore has relatively unimpeded flow (discharge nearly 40-percent higher across a normalized
range of watershed sizes). Stonyton Creek, on the other hand, has numerous impoundments that maintain

1 elevated water levels and in turn reduce groundwater input over time (Fetter 1996).
1 18

r

7

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Additional water quality data would help improve the precision of the discharge-loading algorithms
illustrated in Appendix 2. These relationships, which are responsible for determining in-situ loading
values at the monitoring sites, need to include more nutrient concentration data for high-flow events.
Doing so would require automated instruments that are programmable for collecting samples at elevated
water levels, but these instruments are both costly and labor intensive. Although current results indicate a
linear response of nutrient loading to discharge, it is thought that baseflow and event-driven loading
responses may be distinctly different, and possibly non-linear, with respect to discharge (Preston and
Brakebill 1999).
Nutrient loading will also vary depending upon season and groundwater nutrient concentrations. Prior
studies have quantified loading rates as a function of such phenomena and are based on intense sampling
regimes and large data sets (Cohn et al. 1989).
Nutrient loading rates produced by MODGTP for each sub watershed are shown in Table 3. Performance
comparisons between annual in-situ (Table 2) and MODGTP TN-loading rates for each sample site are
shown in Figure 7, and reveal surprisingly similar curves. Results using the high-end ExCo values with a
transport rate coefficient of 0.5 produce the closest match, and are on average within 9 percent of the in-
situ levels. However, the median values and a transport rate coefficient of 0.35 underestimated in-situ
loading by as much as 25 percent for SC5-8 and 20 percent for - 0; therefore, this set was considered
unacceptable. Interestingly, results using high-end ExCo values estimated loads that are higher than in-
._
situ values at the smallest (SC06 and SC07) and largest (SC3-11) watershed points, but slightly
underestimated loading in the mid reach sub-watersheds (SC4-10 and SC5-8). These errors indicate one
of two scenarios - either the high-end ExCo values are too high for the furthest upstream and downstream
reaches, or the transport rate of total nitrogen fluctuates spatially along the entire stream reach.
Nonetheless, since MODGTP produces both higher and lower loading values when compared to the in-
situ measured loads, it is implied that, along Stonyton Creek, there is a non-homogeneous relationship
between ExCo values and transport rates. Also notable, MODGTP results show a considerably higher
load when compared to the in-situ values at the furthest downstream site (SC3-11; 11,341 vs. 10,262
kg/yr, respectively), most likely due to underestimation of the transport rate coefficient for the reach
(presumably because the stream reach is heavily impounded and would therefore present higher in-stream
decay of nutrients). The transport rate coefficient of 0.5, which equates to a nearly 39-percent reduction
of deliverable total nitrogen per day, is considerably higher than those derived by DWQ (1998), but
mimics values reported by other nutrient-modeling efforts for similar low-flow streams (Preston et al.
1996; Preston and Brakebill 1999).
19

Figure 7: In-situ TN loads versus MODGTP results for Stonyton Creek with median
and high-end DWQ 1998 ExCo values over a range of in-stream losses (k)
12000
10000
S, 8000
rn
m 6000
0
J
H 4000
2000
0
0

Symbol Data vs MODGTP
1 11,486
_ 10,262
-? Symbol Data vs field results
9.265 . ...:
. 9,968
7,867 I SC3-11
SC4-10
5,924 .. '
ExCo rDWQ Medianl (ka/ha/vr)
Cultivated = 15.2
-SC07 SC5-8 Forest/Wet =1.9
SC06 I Industrial = 14.6
1 2,214 .. Herbaceous = 4.9
1,990 Residential = 8.3
• 2,215 k (in-stream loss) = 0.35
1,652
12000
10000
S 8000
rn
'a 6000
0
J
H 4000
2000
2 4 6 8 10 12 14 16 18 20
Watershed Area (sq. km.)
2 4 6 8 10 12 14 16 18 20
Watershed Area (sq. km.)

' Based on the ExCo values for the various land use types in t set, (Table 3), it can be deduced
that within Stonyton Creek, agricultural lands export ne _ 1 40 percent 44e annual nitrogen loading for
all land uses combined. Because MODGTP results close -situ results, this infers that, within
NCGTP, impending development that converts agriculture into other land uses will likely lessen future
nitrogen loading within the Stonyton Creek watershed. However, it should again be noted that this
projection is based upon the current, low flow conditions. Also, it is imperative that Best Management
Practices be applied to all forthcoming development to facilitate nitrogen removal processes during
storm-water runoff events.
Besides nutrient-loading trends, a few general relationships emerge when comparing the other measured
' variables (Appendix 1). At all of the monitoring locations, lower oxygen levels were witnessed during
the late spring and summer seasons of 2001 and early fall of 2002. For example, water temperature at
' SC3-11 peaked to 78.8 degrees Fahrenheit (26.0 degrees Celsius) in June of 2001, which generally
correlates to the lowest oxygen levels (0.56 milligrams per liter [mg/1]). This is a result of physical and
' aquatic biological processes that lower oxygen storage capacity and enhance microbial respiration rates.
In addition, nitrate levels during these periods were generally depressed throughout the Stonyton Creek
watershed, reflected by numerous non-detectable (nd) concentrations (Appendix 1). This is an expected
' response to low-flow, low-oxygenated bottom waters where anaerobic respiration and denitrofication
processes are encouraged.
Turbidity and total suspended solids (TSS) are closely related since both are a measure of similar
' parameters. These quantities are expected to show a bimodal response to discharge, with high values
during both high- and low-flow events (as seen during the fall of 2001). This phenomenon is related to
' heightened concentration of sediments, either from runoff and erosion during high-flow periods, or from
increased concentrations during low-water situations. Comparison with the discharge time series (mostly
' low-flow conditions) upholds this relationship as shown at SC4-10 on October 31, 2001, when turbidities
were at their highest levels to date and under extremely low-flow conditions (170 normalized turbidity
' units [NTU]) and TSS (138.0 mg/1). Similar supporting evidence is found at SC3-11 during the severe
drought condition surrounding the August 22, 2002 sampling event, when highest levels of turbidity and
' TSS were measured at that site (170 NTU and 98 mg/l respectively).
Macroinvertebrate data from a 1993 monitoring schedule by DWQ on Stonyton Creek near the vicinity of
' the gage located offsite (SC Reference) has been included to assist in the establishment of a baseline
biological standard (Appendix 3). Sample results indicate low taxonomic diversity within the waterway,
21

I

H
171,

C

with only one species (Stenomena modestum) from the EPT (Ephemeroptera, Plecoptera, and Trichoptera)
metric. EPT diversity is directly correlated to water quality, and these results indicate relatively poor
conditions within downstream, off-site reaches of Stonyton Creek. A similar macroinvertebrate
community is also thought to exist within upstream reaches of Stonyton Creek. Future sampling is
planned on Stonyton Creek near NC 58 to better assess the on-site biological conditions at this location.
Whatever the case, planned restoration activities of Stonyton Creek at NC 58 are expected to enhance
EPT diversity by reducing bank erosion and associated sedimentation, increasing in-stream structures that
provide aquatic habitat, and increasing flow velocity (which encourages physical renewal processes of
oxygen levels within the water column). Future biological-monitoring results will be coupled with
biochemical data to assess the strength of EPT diversity as a function of existing and future stream water-
quality conditions. lot.>
001- ©? I
l
a
22

5.0 REFERENCES
' Bachman, L.J., B.D. Lindsey, J.W. Brakebill, and D.S. Powars, 1998. Ground-water discharge and base-
flow nitrate loads of nontidal streams and their relation to a hydrogeomorphic classification of the
Chesapeake Bay watershed, Middle Atlantic Coast: USGS Water-Resources Investigations
Report 98-4059, 71 p.
Bovee, K.D. and R. Milhous, 1978. Hydraulic simulation in in-stream flow studies: theory and
techniques. In-stream Flow Information Paper 5, FW/OBS-78/33, US Fish and Wildlife Service,
' Office of Biological Services.
Brakebill, J.W. and S.D. Preston, 1999. Digital data used to relate nutrient inputs to water quality in the
Chesapeake Bay watershed, Version 1.0: USGS Open-File Report 99-60.
Cohn, T.A., L.L. Delong, E.J. Gilroy, R.M. Hirsch, and D.K. Wells, 1989. Estimating constituent loads:
' Water Resources Research, v. 25, n. 5, p. 937-942.
' Dodd, R.C., G. McMahon, and S. Stichter. 1992. Watershed Planning in the Albemarle-Pamlico
Estuarine System: Annual Average Nutrient Budgets. North Carolina Department of Natural
Resources Report No. 92-10.
Division of Water Quality (DWQ). 1998. Neuse River Basinwide Water Quality Management Plan. N.C.
Department of Environment and Natural Resources, Water Quality Section, Raleigh, NC.
' EcoScience Corporation, 2000. Revised Baseline Water Quality Monitoring Report. Unpublished
' document for North Carolina Transpark Authority.
EXTEND Software, 2000. Version 4.0.1, Imagine That, Inc., San Jose, California.
' Fetter, C. W., 1994. Applied Hydrogeology, Third Edition. Prentice-Hall, Inc., Upper Saddle River,
New Jersey.
Goolsby, D.A., W.A. Battaglin, R.P. Hooper, 1997. Sources and transport of nitrogen in the Mississippi
River Basin. Proceedings of the American Farm Bureau Federation Workshop, July 14-15, 1997,
' St. Louis, Missouri.
I Gordon, N.D., T.A. McMahon, and B.L. Finlayson, 1992. Stream Hydrology: An Introduction for
Ecologists. John Wiley and Sons, New York, NY.
NCGTPA, 1993. Airport Master Plan. North Carolina Global TransPark Authority, Raleigh, NC.

23

' NCGTPA, 1997. Final Environmental Impact Statement: Initial Development of the North Carolina
Global TransPark, Kinston, Lenoir county, North Carolina, North Carolina Global TransPark
' Authority, Raleigh, NC.
Paerl et al. 1998. Ecosystem responses to internal watershed organic matter loading: Consequences for
' hypoxia and fish fills in the eutrophying Neuse river Estuary, North Carolina. Marine Ecology
Progress Series 166: 17-25.
Pinckney, J.L., T.L. Richardson, and H.W. Paerl, 2000. Neuse River Estuary Modeling and Monitoring
Project, Chapter 4, Final Report: Monitoring Phase, Water Resources Research Institute, Raleigh,
North Carolina, 190 p.
' Preston, S.D. and J.W. Brakebill, 1999. Application of spatially referenced regression modeling for the
evaluation of total nitrogen loading in the Chesapeake Bay watershed. USGS Water Resources
' Investigations Report 99-4054.
' Preston, S.D., Smith, R.A., Schwarz, G.E., Alexander, R.B., and Brakebill, J.W., 1998, Spatially
Referenced Regression Modeling of Nutrient Loading in the Chesapeake Bay: Proceedings of the
First Federal Interagency Hydrologic Conference: Las Vegas, Nevada, (April 19-23), 1998, 8 p.
' Rice, J.M. et al. 1998. Trend detection in land use and water quality data for the Herrings marsh Run
watershed. Unpublished.
' Robbins J.C. and J.D. Bales 1995. Simulation of hYdrodYnamics and solute transport in the Neuse
' River estuary, North Carolina: U.S. Geological Survey Open-File Report 94-511, 85 p.
Robbins, J.C. and B.F. Pope, 1996. Estimation of flood-frequency characteristics of small urban streams
' in North Carolina. Water-Resources Investigations Report 96-4084
Schlesinger, W. H., 1997. Biogeochemistry: An Analysis of Global Change. Academic Press, Second
Edition, 588 pp.
Showers, W.J., B. Usry, and B. Genna, 2002. Groundwater/surface interactions and nitrogen flux rates on
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Spruill, T.B., Eimers, J.L., and Morey, A.E, 1996. Nitrate-nitrogen concentrations in shallow ground
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' Virginia: U.S. Geological Survey Fact Sheet FS-241-96, 4 p.

j
24

E

APPENDIX 1
Water Quality Results

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APPENDIX 2
Discharge-Loading Relationships

Appendix 2: Discharge - Loading Relationships
TN: BR06 Sub-Watershed
90
75
60
v
rn
a 45
m
0
J
30
15
1•
A
0
0 3 6 9 12 15 18
• TN Concentration (mg/1) Discharge (cfs)
• TN Load (kg/day)
TN Load = 3.58 * Discharge
12
10
$ Z
n
0
6 P
3
cQ
4
2
0
21 24 27 30
TP: BR06 Sub-Watershed
15--
12--
ca
9
0)
6
a
H
3--
0 r= a I i
0 3 6 9 12 15 18
• TP Load (kg/day) Discharge (cfs)
TP Load = 0.34 * Discharge
21 24 27 30

Appendix 2: Discharge - Loading Relationships
TN: BR08 Sub-Watershed
1/5
150
125
15, co
Y 100
0 75
ZJ
~ 50
25
0
3.5
3.0
2.5
Z
2.0 0
3
1.5 3
(D
1.0
0.5
0.0
0 3 6 9 12 15 18 21 24 27 30
• TN Concentration (mg/1) Discharge (cfs)
• TN Load (kg/day)
- TN Load = 4.89 * Discharge
TP: BR08 Sub-Watershed
10
I•
8
m
6
rn
Y
cc
4
a-
2
0 3 6 9 12 15 18 21 24 27 30
• TP Load (kg/day) Discharge (cfs)
TP Load = 0.27 * Discharge
0
•
•

Appendix 2: Discharge - Loading Relationships
TN: SC06 Sub-Watershed
120
100
80
0)
_0 60-
m
0
J
F 40
20
0 M i i
0 2 4 6 8 10
• TN Concentration (mg/1) Discharge (cfs)
• TN Load (kg/day)
TN Load = 7.37 * Discharge
-6
-5
- 4 -1
Z
0
-3 0
3
-2 1
?0
12 14 16
TP: SC06 Sub-Watershed
10
8
a
ca
6
rn
CU
4
a
1-
2
0

0 2 4 6 8 10
• TP Load (kg/day) Discharge (cfs)
TP Load = 0.69 * Discharge

Appendix 2: Discharge - Loading Relationships
TN: SC07 Sub-Watershed
100-
80-
60-
Y
v
m
0
40-
F
20
0
0 3 6 9
• TN Concentration (mg/1) Discharge (cfs)
? TN Load (kg/day)
- TN Load = 4.74 * Discharge
•

• ?
• ?
? ? •
TP: SC07 Sub-Watershed
10
8
m
6
rn
Y_
CU
J 4
a
F-'

10
8
6 z
n
0
4
2
0
12 15

2
AA
0 OPM i i
0 2 4 6 8 10
? TP Load (kg/day) Discharge (cfs)
TP Load = 0.36 * Discharge
12 14 16 18

Appendix 2: Discharge - Loading Relationship
TN: SC5-8 Sub-Watershed
LL5
200
175
C::Z 150
Y 125
v
100
Co
J
75
50
25
0
?
•
12.0
10.5
9.0
7.5
6.0
4.5
3.0
1.5
0.0
0 3 6 9 12 15 18 21 24 27 30
• TN Concentration (mg/1) Discharge (cfs)
? TN Load (kg/day)
TN Load = 6.99' Discharge
TP: SC5-8 Sub-Watershed
15
?
12
-51
m
v 9
rn
.0
(0
J 6

3
? ?
?
o r
0 3 6 9 12 15 18 21 24 27 30
? TP Load Discharge (cfs)
TP Load = 0.59 " Discharge
z
n
0
3

Appendix 2: Discharge - Loading Relationship
TN: SC4-10 Sub-Watershed
YVV
360
320
280
cc
240
rn
-Nd
200
ca
160
120
80
40
0
A
8
6
Z
n
4 O
co
2
i i . 0
40 45 50
0 5 10 15 20 25 30 35
E TN Concentration (mg/1) Discharge (cfs)
TN Load (kg/day)
TN Load = 6.31 * Discharge
TP: SC4-10 Sub-Watershed
20
16
A
ca
12
rn
v
m
J 8
a -
F_
4
0 A-- i '
0 5 10 15 20 25 30
A TP Load (kg/day) Discharge (cfs)
TP Load = 0.72 * Discharge
A
35 40 45 50

Appendix 2: Discharge - Loading Relationships
TN: SC3-11 Sub-Watershed
3VV
275
250
225
200
m
Y 175
150
CO
0 125
100
75
50
25
0
4
3
A z
Z
n
0
2 ?
cn
1
0
50
0 5 10 15 20 25 30 35 40 45
• TN Concentation (mg/1) Discharge (cfs)
• TN Load (kg/day)
- TN Load = 4.64 " Discharge
TP: SC3-11 Sub-Watershed
4V
35
30
-0a 25
rn
20
0
J 15
a
F-
10
5
0
Ai
0 5 10 15 20 25 30 35 40 45 50
EA TP Load (kg/day) Discharge (cfs)
TP Load = 0.57' Discharge

F

APPENDIX 3
Macroinvertebrate Data
I
i1-1

L7

1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Appendix 3: Macro-Invertebrate Taxon List From Stonyton Creek
Taxon
EPHEMEROPTERA
Stenomena modestum
COLEOPTERA
Stenelmis spp.
Number Collected
1
1
ODONATA
Hetaerina spp.
DIPTERA: CHIRONOMIDAE
Orthocladius obumbratus
Chironomus spp.
Dicrotendipes nervosus
Dicrotendipes simpsoni
Diplocladius cultriger
Genus Na nocladius
Hydrobaenus spp.
Natarsia spp.
Polypedilum illinoense
Parachironomus spp.
Phaenopsectra flavipes
MISC. DIPTERA
Prosimulium mixtum
Tipula spp.
OLIGOCHAETA
Enchytraeidae
Lumbriculidae
Nais spp.
Spirosperma ferox
CRUSTACEA
Cambaridae
Lirceus spp.
GASTROPODA
Campeloma decisum
Menetus dilatatus
Physella spp.
1
3
3
3
3
3
1
3
1
10
10
1
3
1
10
3
1
3