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NC 43 CONNECTOR
FROM NC 55 TO US 17
CRAVEN COUNTY, NORTH CAROLINA
TIP PROJECT NO. R-4463
STATE PROJECT NO. 8.2231201
INDIRECT AND CUMULATIVE IMPACT
WATER QUALITY STUDY REPORT
PREPARED FOR:
North Carolina Department of Transportation
Division of Highways
Project Development and Environmental Analysis Branch

..
FEBRUARY 2006

Prepared by:
s~
Stantec Consulting Services Inc.
807 Jones Franklin Road, Suite 300
Raleigh, NC 27608
February 2006

NC 43 Connector
ICI Water Quality Study
Table of Contents
1 Introduction ........................................................................................ .....................1-1
1.1 Transportation Project Overview ................................................ .....................1-1
1.2 ICI Modeling Study Description .................................................. .....................1-2
2 Existing Water Quality Conditions ...................................................... .....................2-1
2.1 Neuse River Basin Water Quality Initiatives ............................... .....................2-1
2.1.1 Neuse River NSW Management Strategy ........................... .....................2-1
2.1.2 Neuse River Estuary TMDL ................................................. .....................2-1
2.1.3 Water Quality Improvement ................................................. .....................2-2
2.2 Notable Features and Development Considerations .................. .....................2-2
2.2.1 Water Resources ................................................................. .....................2-2
2.2.2 Wetlands .............................................................................. .....................2-3
2.2.3 Groundwater Resources ...................................................... .....................2-3
2.2.4 Soils ..................................................................................... .....................2-4
2.2.5 Protected Species ............................................................... .....................2-4
2.2.6 Fishery Resources ............................................................... .....................2-4
2.2.7 Natural Areas ................................................................:...... .....................2-5
2.2.8 Infrastructure ....................................................................... ..................... 2-5
2.2.9 Other Development Considerations ..........:......................... .....................2-5
2.3 Stormwater Management ........................................................... .....................2-5
3 Watershed Modeling Approach .......................................................... .....................3-1
3.1 Objectives and Model Selection ................................................. .....................3-1
3.2 The GWLF Model ....................................................................... .....................3-2
3.2.1 Hydrology ............................................................................ .....................3-2
3.2.2 Erosion and Sedimentation ................................................. .....................3-3
3.2.3 Nutrient Loading .................................................................. .....................3-4
3.2.4 Input Data Requirements ..................................................... .....................3-4
4 GWLF Model Development ...............:................................................ .....................4-1
4.1 Delineation of Subwatersheds .................................................... .....................4-1
4.2 Land Use Scenarios ................................................................... .....................4-1
4.2.1 Existing Land Use ................................................................ .....................4-1
4.2.2 No Build and Build Scenarios ............................................... ....................4-3
4.2.3 Build-Enhanced Scenario ..................................................... ....................4-3
4.2.4 Scenario Comparisons ......................................................... ....................4-4
4.2.5 Modellmperviousness .......................................................... ....................4-9
4.3 Surface Water Hydrology ............................................................. ....................4-9
4.3.1 Precipitation .......................................................................... ..................4-10

4.3.2 Eva otrans iration Cover Coefficients .................................
p P
..................4-1
0
4.3.3 Antecedent Soil Moisture Conditions .................................... ..................4-10
4.3.4 Runoff Curve Numbers ......................................................... ..................4-10
4.3.5 Curve Numbers for Cluster Development ............................. ..................4-11
4.4 Groundwater Hydrology ............................................................... ..................4-12
4.4.1 Recession Coefficient ........................................................... ..................4-12
4.4.2 Seepage Coefficient ........:.................................................... ..................4-12
4.4.3 Available Soil Water Capacity .............................................. ..................4-13
4.4.4 Initial Saturated and Unsaturated Storage ........................... ..................4-14
4.5 Erosion and Sediment Transport ................................................. ..................4-14
4.5.1 Soil Erodibility (K) Factor ...................................................... ..................4-14
4.5.2 Length-Slope (LS) Factor ..................................................... ..................4-14

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4.5.3 Cover (C) and Management Practice (P) Factors ................
4.5.4 Sediment Delivery Ratio .......................................................
4.5.5 Sedimentation from Urban Land Uses .................................
4.6 Nutrient Loading ..........................................................................
4.6.1 Solid Phase Nutrients :..........................................................
4.6.2 Dissolved Groundwater Nutrients .........................................
4.6.3 Runoff Concentrations and Build-up Rates ..........................
4.7 Consideration of Existing Environmental Regulations .................
4.7.1 Neuse River Nutrient Sensitive Waters Management Rules
4.7.2 Coastal Stormwater Management Program .........................
4.8 Model Implementation .................................................................
GWLF Model Results and Discussion ................................................
5.1 Hydrology .....................................................................................
5.2 Pollutant Loading .........................................................................
5.3 Verification of Model Results .......................................................
5.3.1 Pollutant Loading Comparison .............................................
5.3.2 Streamflow Comparison .......................................................
Stream Erosion Risk Analysis .............................................................
6.1 Technical Approach .....................................................................
6.2 Results .........................................................................................
Conclusions ........................................................................................
References ..........................................................................................
Appendix .............................................................................................
9.1 GWLF Model Inputs .....................................................................
9.1.1 Nutrient and Sediment Files .................................................
9.1.2 Transport Files ......................................................................
9.2 Land Use Scenarios ....................................................................
9.3 Runoff Volume Analysis ...............................................................
5
6
7
8
9
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4-16
4-16
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9-25
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Tables
Table 4.2.1 Land Use Categories and Estimated Imperviousness ...................... ....4-4
Table 4.3.1 Surface Water Hydrology Input Parameters ..................................... ....4-9
Table 4.3.2 Curve Numbers for Land Use and Soil Hydrologic Groups .............. ..4-11
Table 4.4.1 Groundwater Input Parameters ......................................................... ..4-13
Table 4.5.1 Rural Sediment Transport Input Parameters .................................... ..4-15
Table 4.5.2 Cover (C) and Management Practice (P) Factors ............................. ..4-15
Table 4.6.1 Nutrient Loading Input Parameters ................................................... ..4-17
Table 4.6.2 Nutrient Runoff and Buildup Rates for Existing Land Uses .............. ..4-18
Table 5.1.1 Seven-Year Total Nitrogen Loads (tonnes) for All Subwatersheds .. ....5-3
Table 5.1.2 Seven-Year Total Phosphorus Loads (tonnes) for All Subwatersheds.5-3
Table 5.1.3 Seven-Year Total Sediment Loads (tonnes) for All Subwatersheds. ....5-3
Table 5.2.1 Comparison of Model Loading Rates to the Literature ...................... ...5-7
Table 6.2.1 Storm Flow Volumes (cubic meters) for the One-Year, 24-Hour Storm6-2

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Figures
Figure 1.1.1 Project Vicinity .................................................................... ..................1-1
Figure 1.2.1 Project Study Area .............................................................. ..................1-3
Figure 3.2.1 Schematic of GWLF Model Processes ............................... ..................3-3
Figure 4.2.1 Build Land Use Scenario .................................................... ..................4-5
Figure 4.2.2 No-Build Land Use Scenario ............................................... ..................4-6
Figure 4.2.3 Build-Enhanced Land Use Scenario ................................... ..................4-7
Figure 4.2.4 Existing Land Use ............................................................... ..................4-8
Figure 5.2.1 Mean Annual Total Nitrogen Loading Rates ....................... ..................5-4
Figure 5.2.2 Mean Annual Total Phosphorus Loading Rates ................. ..................5-4
Figure 5.2.3 Mean Annual Sediment Loading Rates .............................. ..................5-5
Figure 5.2.4 Total Nitrogen (TN), Total Phosphorus (TP), and Sediment Loading Over
the Seve n-Year Model Simulation Period ............................................. ..................5-5
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Executive Summary
The North Carolina Department of Transportation (NCDOT) 2004-2010 Transportation
Improvement Program (TIP) includes the extension of NC 43 from NC 55 to US 17 just
west of New Bern in Craven County, North Carolina. This project is referred to as the NC
43 Connector (TIP Project No. R-4463) and is proposed as a four-lane, median-divided,
partial control of access facility on a new location. The approximate length of the project
is 4.5 miles (7.2 kilometers).,
An Indirect and Cumulative impacts (ICI) Assessment was developed in January 2005 to
provide comprehensive information on the potential long-term, induced impacts of the
proposed project (NCDOT, 2005b). In response to NC Division of Water Quality
(NCDWO) comments on the ICI Assessment and in preparation for an Individual Section
401 Water Quality Certification, a water quality modeling analysis has been conducted to
quantify the project's ICIs on water resources. The focus of the analysis is on the
potential increases in stormwater runoff and nonpoint source loads of nitrogen,
phosphorus, and sediment resulting from various future development scenarios
associated with the roadway.
Two modeling tools were used to quantify impacts on water resources: the Generalized
Watershed Loading Function (GWLF) watershed model and the SCS Curve Number
Method. The GWLF model (Haith and Shoemaker, 1987; Haith et al., 1992) was
selected to simulate long-term loading of nonpoint source pollutants. An additional
parameter, runoff from the one-year, 24-hour storm event, was evaluated using the SCS
Curve Number Method (SCS, 1986) to assess the potential risk of downstream channel
erosion.
Predictions from the modeling analyses suggest that if the roadway is constructed (Build
Scenario) storm event runoff volume and nutrient loading would increase (see figure
summarizing results on next page). The increases are mitigated to some extent by
existing regulations governing the jurisdiction including the Neuse Nutrient Sensitive
Water (NSW) rules. One of the most critical parameters for the Neuse River Estuary,
nitrogen, increases. overall by nearly two metric tonnes per year (or about 4.5%) under
the Build Scenario. Individual subwatershed increases ranged trom 2 to 16%.
Additional measures proposed by the City of New Bern simulated in an Enhanced-Build
Scenario were effective in providing further mitigation resulting in overall decreases in
storm event runoff and pollutant loading to near or below levels predicted without the
roadway. This scenario resulted in only a 1 percent overall increase in total nitrogen over
the No Build Scenario. The other modeled constituents were predicted to decrease 1 to
8%.
These results are particularly important for total nitrogen considering the impairment
status of the Neuse Estuary and its existing TMDL (total maximum daily load). The
analysis suggests that implementation of additional conservation measures proposed by
the City of New Bern would be protective of downstream water quality and be consistent
with the TMDL.

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500
450
400
350
^ No Build
^ Build
^ Enhanced Build
v, 300
a~
~ 250
0
~ 200
150
100
50
0
TN TP Sediment x 10
Total Nitrogen (TN), Total Phosphorus (TP), and Sediment Loading in Metric Tonnes
Over the Seven-Year Model Simulation Period
vi

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INTRODUCTION
1.1 Transportation Project Overview
The North Carolina Department of Transportation (NCDOT) 2004-2010 Transportation
Improvement Program (TIP) includes the extension of NC 43 from NC 55 to US 17 just
west of New Bern in Craven County, North Carolina. This project is referred to as the NC
43 Cohnector (TIP Project No. R-4463) and is proposed as a four-lane, median-divided,
partial control of access facility on a new location. The approximate length of the project
is 7.2 kilometers (4.5 miles). Figure 1.1.1 shows the vicinity of the proposed project.
Full movement intersections are proposed at NC 43/55 and US 17. An interchange is
proposed with US 70. Four access points are included in the project's design: two
between US 17 and US 70 and two between US 70 and NC 43/55 (one of these being
the intersection at Bosch Boulevard).
The purpose of and need for this project is based on the economic development of
Craven County and on projected traffic volumes. A new connection between US 17, NC
43, and the proposed US 17 Bypass (TIP Project No. R-2301 A & B) would help promote
economic development in Craven County by providing a transportation infrastructure
capable of accommodating future development which would result in job creation. The
proposed connector would provide a more direct route for truck traffic to access US 70
from the north, which would reduce truck traffic on Glenburnie Road between NC 43/55
and US 70.
PITT
LENOIR

ICI P
Figure 1.1.1. Vicinity Map
ICI Water Oualiry Study
NC 43 ConneIXOr
NC Department IN TranspMatian
TIP No. R-0463, Craven County, NC
0 2.5 5 10 Mlles ONS
v
Figure 1.1.1 Project Vicinity
1-1

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ICI Water Quality Study
1.2 ICI Modeling Study Description
An Indirect and Cumulative Impact (ICI) Assessment was developed to provide
comprehensive information on the potential long-term, induced impacts of the proposed
project (NCDOT, 2005b). The assessment was conducted in accordance with federal
Council on Environmental Quality (CEQ) regulations and follows the systematic
procedures contained in Guidance for Assessing Indirect and Cumulative Impacts of
Transportation Projects in North Carolina (NCDOT, 2001). In response to NC Division of
Water Quality (NCDWQ) comments on the ICI Assessment and in preparation for an
Individual Section 401 Water Quality Certification, the NCDOT contracted with Stantec to
conduct water quality modeling to quantify the project's ICIs on water resources. The
focus of the analysis is potential increases in stormwater runoff and nonpoint source
loads of nitrogen, phosphorous and sediment resulting from various future development
scenarios associated with the roadway.
The present analysis focuses on a previously defned 31-km2 (12-mil) ICI project study
area with some variation to account for localized watershed hydrology (Figure 1.2.1).
Seven subwatersheds covering 54 km2 (21 mil) were delineated for water quality
modeling purposes. The model study area contains portions of the following
municipalities: New Bern, Trent Woods, River Bend, and Craven County.
The modeling analysis simulated potential increases in nonpoint source loads of
nitrogen, phosphorous and sediment resulting from various future development
scenarios associated with the roadway. The Generalized Watershed Loading Function
(Haith and Shoemaker, 1987; Haith et al., 1992) model was selected for simulation
purposes. An additional parameter, storm event runoff, was evaluated using a separate
assessment tool, the SCS Curve Number Method (SCS, 1986), to assess the risk of
downstream channel erosion. The modeling tools were used to quantify the impacts of
various development scenarios associated with the roadway.
A particular focus in the analysis was the potential increase in predicted pollutant loads
to the adjacent Neuse and Trent Rivers, which have been designated as impaired for
chlorophyll a, an indicator of algal growth, by the NC Department of Environment and
Natural Resources (NCDENR).
1-2

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Figure 1.2.1. Project Study Area
ICI Water Quality Study - NC 43 Connector
TIP No. R-4483, Craven County, NC
r!~ 1 North Carolina
~,, - - , ~) Department of Transportation
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0 1 2 Miles
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2 EXISTING WATER QUALITY CONDITIONS
2.1 Neuse River Basin Water Quality Initiatives
Water quality in the Neuse River estuary has been a concern for over a century.
Nitrogen loading has been increasing in the Neuse River Basin, corresponding with
increases in chemical fertilizer use in the early 1960's and animal feeding operations in
the 1970's (Stow et al., 2001). Total nitrogen concentrations increased in the river until
about 1990 but more recently have been declining. Stow et al. (2001) estimated that
nonpoint sources (NPS) accounted for 75% of total nitrogen loadings while point sources
accounted for 25%. Lunetta (2005) determined that agricultural land uses contributed to
55% of the total annual NPS nitrogen loadings, followed by forested land and urban
land. However, he found that on a unit area basis, high and medium density urban
development were the greatest contributors of NPS-N. Elevated nutrient levels have led
to frequent algal blooms, hypoxic conditions and fish kills in the estuary. As a result, the
Neuse River Basin was listed as impaired by chlorophyll a on North Carolina's 303(d) list
in the early to mid-1990's.
2.1.1 Neuse River NSW Management Strategy
Water quality research in the Neuse River Basin expanded after extensive fish kills in
1995. Low dissolved oxygen levels associated with eutrophication were determined to
be a probable cause. Although, a number of fish kills were also attributed to a
dinoflagellate known as Pfiesteria piscicida; thought to thrive in poor water quality
situations (NCDWQ, 2002a). In 1997, the North Carolina Environmental Management
Commission (EMC) adopted a mandatory plan, the Neuse River Nutrient Sensitive
Waters (NSW) Management Strategy, to control both point and nonpoint sources of
pollution in the Neuse River basin (NCDWQ, 2002b). With the exception of the riparian
buffer rules, these rules became effective in 1998. The buffer rules became effective in
2000. The overall goal of these rules was to reduce average annual load of nitrogen (a
key nutrient contributing to excess algal growth) delivered to the Neuse River Estuary by
30% by the year 2001. The baseline for average annual load of nitrogen from which the
reduction is to be achieved is 1991 through 1995 (NCDWQ, 2002b).
The Neuse River NSW Management Strategy is made up of a number of rules regulating
various items such as wastewater discharges, urban stormwater management,
agricultural nitrogen reduction, nutrient management, and protection and maintenance of
riparian areas (NCDWQ, 2002b). Currently, the NCDENR Division of Water Quality
(NCDWQ) is responsible for administering and enforcing these rules.
2.1.2 Neuse River Estuary TMDL
A TMDL (Total Maximum Daily Load) is defined as a calculation of the maximum amount
of a pollutant that a waterbody can receive and still meet water quality standards, and an
allocation of that amount to the pollutant's sources. A TMDL provides a detailed water
quality assessment that offers the scientific foundation for an implementation plan. All
states are required by Section 303(d) of the Clean Water Act to develop TMDLs for
water bodies that are impaired. This list of impaired water bodies is also known as the
North Carolina 303(d) list.
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The first phase of the TMDL for Total Nitrogen to the Neuse River estuary was
conditionally approved in July 1999. The second phase was completed by DWQ and
approved by the EPA in 2001. The premise for developing the TMDL is that a portion of
the Neuse River is impaired for chlorophyll a, an indicator of excessive Eutrophication as
a result of nutrient loading. The Neuse River TMDL supported the nitrogen reduction
goal set forth by the earlier Neuse River NSW Management Strategy. As discussed in
the following section, instream nitrogen reductions are on target to meet established
goals.
2.1.3 Water Qualitylmprovement
A declining trend in nitrogen is attributed to the implementation of the 1997 Neuse River
NSW Management Strategy outlined above (Harped, 2003). According to an update of a
trend analysis by Stow and Borsuk (2003), long-term flow-adjusted nutrient data in the
lower Neuse River show a 27% reduction in instream nitrogen from the 1991-1995 base
period to 2003 (USEPA, 2005). This decrease was accomplished by reducing point
source loads, installing both agricultural and urban BMPs, implementing fertilizer
management plans, removing cropland from production, and implementing urban
stormwater management plans, among other initiatives. Any future development within
the project area would also be subject to the Neuse River NSW Nutrient Management
Strategy rules.
The Neuse River Estuary, along with the Pamlico River Estuary, has historically been
documented with the largest number of fish kills in North Carolina. In 1997, NCDWQ
established the Neuse River Rapid Response Team in New Bern, NC to better
investigate fish kill events in the Neuse River Estuary (NCDWQ, 2000). Fish kills can
occur from natural water quality fluctuations, pollutant-induced water quality conditions,
or a mixture of both. In the 2004 Annual Report of Fish Kill Events (NCDWQ, 2004c),
eight fish kill events were reported for the entire Neuse River Basin, a decrease from a
peak of 37 events in 2001. Seven of these events occurred in the Neuse River below
New Bern from May to September 2004 and accounted for 99% of the fish mortality
reported statewide for the year. According to the report, that portion of the Neuse River
has historically been a trouble spot for fish kill activity. The majority of those events were
associated with significant drops in dissolved oxygen (DO) levels (hypoxic conditions).
These events occur in North Carolina's estuaries as nutrient and organic loading and
water column stratification deplete DO levels during the warmer months. Sudden shifts
in wind conditions can cause mixing of the water column allowing the hypoxic layers to
upwell into the shallower depths of the River. Data from the DWQ Environmental
Sciences Section website indicates that similar trends continued in 2005 (NCDWQ,
2006).
2.2 Notable Features and Development Considerations
This section discusses the most notable features and development considerations of the
project study area and vicinity.
2.2.1 Water Resources
The model study area lies within the Neuse River Basin, Hydrologic Unit 03020204.
Portions of the study area drain to Caswell Branch, Deep Branch, and various unnamed
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tributaries, which flow into the Neuse River. Waterbodies in the southern portion of the
project study area include Hayward Creek, Rocky Run, Wilson Creek and its unnamed
tributaries, which drain to the Trent River. In addition, the project study area is
transected by an extensive drainage ditch system.
NCDWQ classifies Caswell Branch, Hayward Creek, Rocky Run, and Wilson Creek as
Class C waters (NCDWQ 2005c), which are best suited for aquatic life survival and
propagation, fshing, wildlife, secondary recreation, and agriculture. These streams have
also been assigned the supplemental classifications of nutrient sensitive waters (NSW)
and swamp waters (Sw). NSWs require limitations on nutrient input and are included in
the Neuse River NSW Management Strategy. Swamp waters are designed as such due
to their low velocities and other natural characteristics that are different from adjacent
streams. In the vicinity of the project area, the Trent River is classified as SB Sw NSW
waters and the Neuse River is SC Sw NSW (NCDWQ 2005c). The SC classification
indicates that the tidal salt waters are protected for secondary recreation (boating and
fishing) and aquatic life propagation and survival while the SB classification protects tidal
salt waters for primary recreation (swimming). None of the waters in the vicinity of the
project area are classified as SA waters, which are protected for shellfishing. Portions of
the Trent River and Neuse River in the project area are on the State's 303(d) list of
impaired waterbodies (NCDWQ 2004a).
2.2.2 Wetlands
A majority of the project study area is designated as wetlands, according to USFWS
National Wetland Inventory (1994) and NC Division of Coastal Management (NCDCM
1999) mapping. However, the actual acreage of field-verified wetlands [within the project
corridor] was much less than mapped. These conditions are largely attributed to
declining groundwater levels and extensive ditching, which have altered the natural
hydrologic regime of the project study area. As a result, most of the jurisdictional
wetlands are located in the southern portion of the project study area, where ditching is
less prevalent. The wetlands of the surrounding project study area are generally
characterized as pocosins and headwater systems, which act as natural detention and
infiltration areas. Many of these wetlands are terrestrially isolated from large
waterbodies, which makes them important habitat for amphibians.
2.2.3 Groundwater Resources
Groundwater in the Coastal Plain physiographic region of North Carolina flows through
several confined and unconfined aquifer systems. The three most influential aquifers in
the project study area are the surficial aquifer, the Castle Hayne aquifer, and the
Cretaceous aquifers of the Black Creek and Peedee geologic formations.
The surficial aquifer is the unconfined, saturated portion of the upper layer of sediments.
The Castle Hayne aquifer, which underlies the eastern half of the Coastal Plain, is the
most productive aquifer in the state. It is confined below the surficial aquifer, within thick
sedimentary rack formations. Recharge to the Castle Hayne aquifer is rather slow, as
most recharge is captured by the surficial aquifer or moves laterally to streams.
Approximately 3 cm (1 inch) per year reaches the Castle Hayne (Giese et al., 1997). The
Peedee formation of the Late Cretaceous age consists of dark clays mixed with fine to
medium grained sands with a few thin limestone inclusions. The Black Creek formation
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of the Late Cretaceous age also consists of dark clays and sands and is not
hydrologically distinguishable from the overlying Peedee formation (LeGrand, 1960).
Groundwater data collected by the USGS indicate that water table depths in the vicinity
of the project study area have been steadily dropping over the last thirty years. This is
primarily due to the fact that groundwater withdrawals have exceeded the recharge rate
for both the surficial and Cretaceous aquifers. Craven County is within the Central
Coastal Plain Capacity Use Area and has been taking measures to reduce its
dependence on the Cretaceous aquifer; the City currently withdraws 15.9 million liters
per day or 4.2 million gallons per day from this aquifer. The City of New Bern has plans
for a new water treatment facility that would draw from the currently untapped Castle
Hayne aquifer, which would satisfy astate-mandated 25% reduction in withdrawals from
the Cretaceous aquifer. In addition, the Martin Marietta New Bern quarry, located
northeast of the project study area, which ceased mining operations in 1996, has
initiated a reclamation program that has raised groundwater levels in the immediate
vicinity by up to 10 feet.
2.2.4 Soils
The soils of the project study area are generally characterized as hydric soils (USDA,
1989). According to the soil survey, those soils have severe development limitations due
to their low permeability and strength. In addition, the majority of the soils in the project
study area are classified as prime, unique, or statewide important farmlands.
2.2.5 Protected Species
In accordance with provisions of the Endangered Species Act (ESA) of 1973, the project
study area was evaluated for threatened and endangered species habitat. Five species
are listed as endangered or threatened for Craven County: sensitive jointvetch
(Aeschynomene virginica), bald eagle (Haliaeetus leucocephalus), leatherback sea turtle
(Dermochelys coriacea), West Indian manatee (Trichechus manatus), red-cockaded
woodpecker (Picoides borealis), and American alligator (Alligator mississippiensis)
(USFWS, January 2006). The American alligator is listed as "Threatened Due to Similar
Appearance" [T(S/A)] to provide protection to the American crocodile (Crocodylus
aeutus), but is not protected under Section 7 of the ESA. The project study area does
not contain suitable habitat for any of these protected species (NCDOT, 2005a). There
are seventeen Federal Species of Concern (FSCs) listed far Craven County. There is
suitable habitat for several FSCs. The project study area may also host a population of
black bear (Ursus americanus).
2.2.6 Fishery Resources
The Trent River and its tributaries may provide habitat for anadromous fish including
river herring (Alosa pseudoharengus), striped bass (Morone saxatilis), and American
shad (Alosa sapidissima). The NC Division of Marine Fisheries (NCDMF) stated that
there are no known anadromous fish spawning areas or nursery areas within Hayward
Creek or the adjacent areas of the Trent River (NCDMF, 2003). Bachelor Creek is an
important spawning area for river herring and there is a river herring nursery area at the
convergence of Bachelor Creek and the Neuse River. The Trent River also contains
habitat suitable for estuarine species such as spot (Leiostomus xanthurus), croaker
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ICI Water Quality Study
(Micropogonias undulatus), and menhaden (13revoortia tyrannus). These species are
also important for their commercial and recreational value.
2.2.7 Natural Areas
The NCDCM has classified areas in and around the Trent River as "public trust waters"
and "estuarine waters' Areas of Environmental Concern (AECs). These waters are
within the watersheds of the Rocky Run, Hayward Creek, and Wilson Creek. Mitchell
Island, located south of the project study area, is an estuarine island protected as an
estuarine AEC.
The Croatan National Forest is south of the project study area, bound on its north side
by the Trent River. The National Forest and the project study area are along the Atlantic
Flyway of migratory birds; the project study area may provide migratory habitat.
2.2.8 Infrastructure
The project study area is bound by several highways including NC 55, NC 43/55, US 17,
and the proposed US 17 Bypass. US 70 roughly bisects the project study area. The
undeveloped regions of the project study area are served by a system of logging roads.
An active railroad and two large power lines traverse the project study area.
Water service from the City of New Bern is currently supplied to the Greenbrier
community and to properties along NC 55, NC 43, Glenburnie Road, and US 17. Sewer
service from the City is available in Greenbrier and along NC 55, NC 43, Glenburnie
Road, and US 17, although sewer lines on US 17 do not extend as far west as the water
lines along US 17.
2.2.9 Other Development Considerations
Most land to the north, east, and south of the project study area is moderately to highly
developed by residential and commercial properties within the City of New Bern and the
Town of Trent Woods. Land to the west of the project study area is predominantly
undeveloped; however, construction of the proposed (access controlled) US 17 Bypass
would create a development constraint for the project study area by preventing direct
access from the project study area.
The US Environmental Protection Agency (USEPA) classifies approximately seven
acres of the Amital Spinning property along Bosch Boulevard as an archived Superfund
site (TEXFI - NCD981928088). Any development in this area would require the removal
of hazardous substances.
2.3 Stormwater Management
Although New Bern is not a community subject to the new NPDES Phase II Stormwater
Rules (Randall, personal communication, 2005), the City is subject to the Stormwater
rules contained within the Neuse River NSW Management Strategy discussed in section
2.1.1 and the coastal stormwater rules. Both sets of rules will lessen the impact that
future development will have on water quality.
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The Neuse stormwater rules require the development of stormwater management plans
for each of the fifteen largest local governments within the basin. The local government
stormwater plans must be consistent with the overall 30% nitrogen reduction goal of the
Neuse River NSW Management Strategy (NCDWQ, 2002b). The plan also outlines a
review and approval process for stormwater management on new developments, public
education, identification and elimination of illegal discharges, and identification of retrofit
sites within existing developments (HDR, 2001). The City of New Bern requires that
each new development must meet a nitrogen export performance standard with a
provision for mitigation offset payments. The City also requires that all new development
control water runoff so that there is no net increase in the peak discharge from the
predevelopment conditions for either the 1-year, 24-hour storm or the 10-year, 24-hour
storm. Variances may be granted for various reasons including limits on impervious area
(HDR, 2001).
The State stormwater Management Program was established in 1988 under the
authority of the EMC and North Carolina General Statute 143-214.7. This program,
codified in 15A NCAC 2H.1000, affects development activities that require either a
Erosion and Sediment Control Plan (for disturbances of one or more acres) or a CAMA
major permit within twenty coastal counties including Craven. The program also applies
to development draining to Outstanding Resource Waters (ORW) or High Quality Waters
(HOW).
The coastal stormwater rules require developments to protect sensitive waters by
maintaining a low density of impervious surfaces, maintaining vegetative buffers, and
transporting runoff through vegetative conveyances. Low density development
thresholds for the study area (non-SA waters) are 30%,built upon area. High density
development requires the installation of BMP's to collect and treat stormwater runoff
from the 1 inch rainfall event and remove 85% of the TSS. A 30-foot (9.1-meter)
minimum setback from perennial waters and shorelines is also required.
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3 WATERSHED MODELING APPROACH
3.1 Objectives and Model Selection
The objective of this modeling analysis is to quantify the changes in pollutant loads
resulting from potential land use changes induced within the project study area by
construction of the NC-43 Connector. The analysis will not quantify impacts to pollutant
loading relative to existing conditions, but rather quantify changes relative to a land use
scenario predicted to develop without construction of the roadway.
Two land use scenarios, referred to from here out as the Build and No Build Scenarios,
were developed for and presented in the 2005 Indirect & Cumulative Impact Assessment
Technical Memorandum (NCDOT, 2005b) submitted under separate cover to NCDOT in
January 2005. The reader is referred to the aforementioned report for detailed rationale
supporting their development. Some modifications to the two land use scenarios were
necessary to correspond with watershed boundaries and to reflect new information
provided by the City of New Bern. These are discussed in subsequent chapters. A third
land use scenario, referred to as Build-Enhanced, was developed specifically for the
present analysis. This scenario reflects modifications to the Build Scenario proposed by
the City of New Bern to reduce impacts such as additional open space preservation,
residential clustering, and additional buffering of waterbodies.
The parameters of interest in this study are sediment, total nitrogen (TN), total
phosphorus (TP), and storm event runoff volume. The Generalized Watershed Loading
Function (Haith and Shoemaker, 1987; Haith et al., 1992) model was selected to
simulate long-term nutrient and sediment loads from catchments draining the project
study area. Storm event runoff was evaluated using a separate assessment tool, the
SCS Curve Number Method (SCS, 1986) to assess the risk of downstream channel
erosion.
Fecal coliform bacteria is not considered explicitly in the current study for two primary
reasons: waters in the vicinity of the project area are not classified as SA and
downstream waters are not impaired for fecal coliform. While sections of the Trent and
Neuse Rivers located immediately downstream of the project area are closed to shellfish
harvesting by the NCDEH, they are not classified as SA waters for shellfishing or
marketing purposes. The Neuse River receives an SA classification at the bend in the
estuary near Minnesott Beach, approximately 15 to 20 miles downstream of the project
area. The impaired SA waters in the subbasin consist of small tidal creeks that flow into
the Neuse River below the bend, such as Dawson, Clubfoot, Green, and Pierce Creeks.
Small areas (<40 hectares) at the mouths of three of these creeks are included in the
impairment. Nonetheless, though an explicit accounting of fecal coliform loading is not
provided, the impact of scenarios on fecal coliform loads should be consistent with the
trends seen in the modeled constituents given that many of the sources and transport
processes are similar.
The Generalized Watershed Loading Function (GWLF) is a continuous simulation model
with a complexity in the mid-range of watershed models, falling between detailed
mechanistic models like the Soil & Water Assessment Tool (Neitsch et al., 2001) or the
Hydrologic Simulation Program -Fortran (Bicknell et al., 1985) and simpler, empirical
methods such as export coefficient- or event mean concentration-driven such as PLOAD
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(USEPA, 2001). The model does not contain instream transport or transformation
algorithms.
GWLF is applicable as an assessment tool with or without formal calibration, the process
of adjusting a model's parameters to fit an observed data set. This feature of the model
is important for the present study given that water quality and flow data were not
available from the study area to allow comparisons of observed and predicted values.
GWLF has been utilized in several successful applications to watershed studies,
including some in coastal North Carolina (Dodd and Tippett, 1994; Swaney et al., 1996;
Lee et al., 1999; CH2M Hill, 2003; NCDOT, 2005c) and was used for the watershed
modeling component of the Jordan Reservoir Nutrient TMDL (NCDWO, 2005a).
The BasinSim 1.0 version of GWLF was selected for this modeling analysis. BasinSim
is an updated version of GWLF developed by a team of researchers at the Virginia
Institute of Marine Science with a grant from NOAA Coastal Zone Management (Dai et
al., 2000). The updates consist primarily of an improved graphical user interface and the
addition of numerous software utilities to edit input and manage and display GWLF
results.
3.2 The GWLF Model
This section provides an overview of the mathematical basis used in GWLF. The
discussion is a summary, largely drawn from the GWLF Version 2.0 User Manual (Haith
et al., 1992). Figure 3.2.1 is a schematic illustration of the structure of the GWLF model
from Dai et al. (2000).
GWLF provides the ability to simulate continuously runoff, sediment, and nutrient (N and
P) loading from a watershed given variable-size source areas (i.e., agricultural, forested
and developed land). The model uses daily steps for weather data and water balance
calculation. The model is considered a combined distributed/lumped parameter
watershed model. For surface loading, it is distributed in the sense that it allows multiple
land use/cover scenarios, but each area is assumed to be homogenous with regard to
various attributes considered by the model. The model does not spatially distribute the
source areas, but simply aggregates the loads from each area into a watershed total; in
other words there is no spatial routing. For sub-surface loading, the model also acts as a
lumped parameter model using a water balance approach.
3.2.1 Hydrology
GWLF estimates surface runoff using the Soil Conservation Service (SCS) Curve
Number (CN) approach with daily weather (temperature and precipitation) inputs. Daily
water balances are calculated for unsaturated and shallow saturated zones. Infiltration to
the unsaturated and shallow saturated zones equals the excess, if any, of rainfall and
snowmelt less runoff and evapotranspiration. The product of a cover factor dependent
on land uselcover type and potential evapotranspiration gives daily evapotranspiration.
The latter is estimated as a function of daylight hours, saturated water vapor pressure
and daily temperature. Percolation occurs when unsaturated zone water exceeds field
capacity. Streamflow consists of runoff and discharge from groundwater.
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3.2.2 Erosion and Sedimentation
Precipitation EvapotranspQation
Erosion
(USLE)
Land Surface - SCS Curve
Number Sunulation
Unsaturated Zone
Shallow Saturated Zone
Deep Seepage
Loss
Runoff
Septic System Loads
Particulate
Nutrients
Dissolved Nutr6ents
Groundwater
Loading to
Stream
Figure 3.2.1 Schematic of GWLF Model Processes
Erosion and sediment yield from rural land uses are estimated using monthly erosion
calculations based on the Universal Soil Loss Equation (USLE) algorithm (with monthly
rainfall-runoff coefficients) and monthly composite of soil erodibility (K), topographic
factor (LS), crop management (C), and conservation practice (P) values for each source
area. A sediment delivery ratio, which is based on watershed size, and a transport
capacity, which is based on average daily runoff, are then applied to estimate the
sediment yield for each source area.
Sediment load from urban land uses are not included in the current BasinSim
application. For the present study, sediment from urban sources was modeled using the
same accumulation and washoff functions from the model substituting sediment
accumulation rates for particulate nutrient accumulation in the nutrient data file. A similar
approach was used by Schneiderman et al. (2002) in an update to the original
application of GWLF on the Cannonsville watershed by Haith and Shoemaker (1987).
Note that GWLF and the current study does not predict short term sedimentation from
construction sites.
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3.2.3 Nutrient Loading
Surface nutrient losses are determined by applying dissolved nitrogen (N) and
phosphorus (P) coefficients to surface runoff from each agricultural source area. Point
source discharges can also contribute to dissolved losses and are specified in terms of
kilograms per month. Manured areas, as well as septic systems, can also be considered.
Urban nutrient inputs are all assumed to be solid-phase; the model uses exponential
accumulation and washoff function for these loadings. Sub-surface losses are calculated
using dissolved N and P coefficients for shallow groundwater contributions to stream
nutrient loads. The sub-surface sub-model considers only a single, lumped parameter
contributing area.
3.2.4 Input Data Requirements
For execution, the model requires three separate input files containing transport,
nutrient, and weather-related data. The transport file defines the necessary parameters
for each source area to be considered (e.g., area size, curve number) as well as global
parameters (e.g., initial storage, sediment delivery ratio) that apply to all source areas.
The nutrient file specifies the various loading parameters for the different source areas
identified (e.g., number of septic systems, urban source area accumulation rates,
manure concentrations). The weather file contains daily average temperature and total
precipitation values for each year simulated.
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ICI Water Quality Study
4 GWLF MODEL DEVELOPMENT
The following sections provide a discussion of the data sources, parameter inputs, and
assumptions utilized in this watershed modeling analysis. Input files (nutrient and
transport) for all subwatersheds and scenarios tested are presented in Appendix A.
4.1 Delineation of subwatersheds
The study area was delineated into 7 subwatersheds ranging from 1.63 to 12.07 kmZ
(0.63 to 4.66 mil) using a hydrology modeling extension developed for ArcGIS (ESRI,
2005). A 6-meter (20-foot) digital elevation model (DEM), a raster grid of regularly
spaced elevation values derived from recent Light Detecting and Ranging (LIDAR) data
and obtained from NCDOT (2005b), was used to develop drainage areas. Field
reconnaissance to verify flow paths and directions of drainage aided in refining the
delineation. The size of each subwatershed in square miles is shown in Figure 4.1.1.
4.2 Land Use Scenarios
No-Build, Build, and Build Enhanced land use scenarios (Figures 4.2.1, 4.2.2 and 4.2.3)
were developed using the categories presented in Table 4.2.1. As mentioned previously,
two land use scenarios were presented in the 2005 ICI Assessment (NCDOT, 2005a).
These previously developed scenarios were modified, as the GWLF model area is larger
than the ICI study area. Within the ICI project study area, the No-Build and Build
Scenario remain the same as shown in the 2005 ICI Assessment with some exceptions.
In the Build Scenario the industrial area in the northern part of the area was expanded
south to US 70, the commercial areas associated with access points were relocated to
the west of the proposed roadway, and the residential density was increased. These
changes reflect new information provided by the City of New Bern Planning Department
(Avery, personal communication, 2005).
4.2.1 Existing Land Use
The previous scenarios from the 2005 ICI Assessment did not include existing land
uses. Existing and future land uses were identified separately in the land use scenarios
as their modeled loading rates are different due to regulations governing new
development in the study area (discussed Section 4.7). Existing land uses were
identified in each land use scenario using information from the 2005 ICI Assessment
(NCDOT, 2005a), county parcel data, and aerial imagery (Figure 4.2.4). Two
assumptions were made when determining existing land use. For existing residential
development, it was assumed that the density of development would not change even if
it were zoned or appeared on the future land use plan with a higher or lower density.
Existing homes will not likely be demolished to make room for higher density homes, as
land is readily available. On the other hand, it was assumed if the existing land use is
residential and the future land use plan or zoning allows for a separate land use such as
commercial or industrial, the assumed future land use was used for the land use
scenarios. It is more likely homes will be removed along major roadways to make space
for commercial and industrial uses.
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ICI Water Quality Study
ay
' 'Yi9h /
RAVEN CO ,~
l~'_ "~~/
/ ~~
ij Caswell eranc ~~
-+ 2.3 mir ~j
.~~ ,:
,. ~~
~ r p;
.i Deep ra ch ~~,~(~ IN
~'
-I J.~m' ' ~ ` -S ost Hi
~, r `--
I)
:~J` ~ ~- ,VI,
~. 1~ 1 Wilson
it~~e h~ r~-~.. ~~I a.7 i
t.J.`2,~
//ff~~``'''' \ ~ ~to Wilson'Cr(ael
)' R3.6 ml' Hay~artl ~feek~~;~'~
~ (N.6 mi~ -
~ =.
. ~ f^
~ .~ \ tit ~,
~~ t \ ~ -:
Y f_.
CO
ICI Project Area IM I: Model Subwetersheds
~
` _ ~ Proposed NC 43 Connector (All F) ~ New Bem
~\ i Streams ~~
i_ i New Bern ETJ
Water Bodies
River Bend
^~ Roads
Trent Wootls
~~ Railroads r-

. Weather Stations r _ _ _~ Couny Bountlary
~~~
J '~~
rent Hirrr ..~ KE
t >~
//~ 316108
Figure 4.1.1. Model Subwatersheds
ICI Water Quality Study - NC 43 Connector
TIP No. R-44fi3, Craven County, NC
°~ `~.
\ North Carolina
~,~ Department of Transportation
`.:~~
0 1 2 Miles
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4.2.2 No Build and Build Scenarios
The previous scenarios were developed based on three intersection/interchanges
located at NC 43/55, US 70, and US 17. The new scenarios take into consideration four
additional access points. Land uses at each access point were determined using the NC
43 Connector Proposed Development Plan (New Bern, 2005) and information from the
City of New Bern planning department (Avery, personal communication, 2005). The first
point is located at Bosch Blvd. where existing commercial and industrial land uses are
found. The second point is at the intersection of the proposed Elizabeth Avenue
Extension north of US 70. Light industrial or office/institutional is predicted at this access
point. The third point is south of US 70 where commercial land use is predicted. The
fourth access point is north of US 17 at the north end of an existing development.
Additional residential units are expected in this area.
Outside of the original ICI study area, City of New Bern zoning and Craven County
parcel data were used to determine the land use for the No-Build and Build Scenarios.
Minimum lot size for residential zones was used to determine the GWLF residential
category (Table 4.2.1). The Heavy Industrial zone was placed in the CommerciallHeavy
Industrial category along with commercial districts C-3 and C-4 (Commercial District and
Neighborhood District). The C-5 zone (office and institutional) as well as the Light
Industrial zone were placed in the Office/Light Industrial category.
Parcel data were used where zoning data were unavailable or nonexistent. The parcel
data contain a current land use attribute that was used for all developed parcels. Vacant
parcels were assigned the land use most suitable to the parcel according to the parcel
attribute data, aerial photography and land cover. Residential densities were determined
using 2003 aerial photography and adjacent zoning information.
The two quarry sites located north of US 70 were assigned land use categories of water
and urban green space. One site has been reclaimed and the site further to the west
remains active but was assumed to be reclaimed in the future land use scenarios.
Cemeteries and golf courses were assigned to the urban green space category. All
wetlands that have been field delineated during prior studies were added to the No-Build
and Build Scenarios. Not all wetlands throughout the study area have been delineated.
The Elizabeth Avenue Extension was added to the Build Scenario. Neuse buffers (50
feet on each side) were added to all perennial and intermittent streams in the
subwatersheds. These areas were categorized as urban green space.
4.2.3 Build-Enhanced Scenario
The Build-Enhanced scenario was developed using the Build Scenario as a base and
adding data from the NC 43 Connector Proposed Development Plan produced by the
City of New Bern (New Bern, 2005). One major change between the Build and Build-
Enhanced scenarios was to change the residential areas south of US 70 to cluster
developments. Cluster development is designed to protect environmentally sensitive
areas by maximizing undisturbed open space and by creating small lots. In addition a
one hundred foot buffer was added around all delineated wetlands, a five hundred foot
conservation area in the southwestern section of the study area was created, and afifty-
foot buffer was added to the drainage canal in the Greenbriar community located in the
southeastern section of the study area. The drainage canal does not appear as a blue .
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NC 43 Connector
ICI Water Quality Study
line stream on the USGS 1:24,000 quad or in the Soil Survey of Craven County
therefore it is most likely anon-jurisdictional channel.
4.2.4 Scenario Comparisons
Commercial, industrial, institutional, and office land use increases by almost. 400
hectares (7%) in the Build and Build-Enhanced scenarios compared to the No Build
Scenario. This development is expected to occur north of US 70 on both sides of the
proposed connector. The amount of land dedicated to Residential -Very High Density
and Residential -High Density does not change significantly between the three land use
scenarios except that 80% of the High Density area and 16% of the Very High Density
area in the Build Enhanced scenario will consist of cluster development. The roadway
will impact approximately two acres of wetlands. The Build-Enhanced scenario aims to
protect wetlands in the area by planning a 30-meter (100-foot) buffer around all existing
delineated wetlands. These buffers as well as a habitat conservation area increase the
urban green space in the Enhanced Build Scenario of the study area by 155 hectares
compared with the No Build Scenario. The three land use scenarios for each
subwatershed can be found in Appendix 9.2.
Table 4.2.1 Land Use Categories and Estimated Imperviousness
~~ ~ ~ LAND USE NAME• ` ~ ~~
- .-.#
...6 -... Y. i ~ •GWLF CODE~~

..a r-''`RERCENT~IMP.ERVIO S

:: .Y .`.:...
Residential -Very Low Density
(2+ acres per dwelling unit) RVL 8
Residential -Low Density
(1.5-2 acres per d.u.) RLL 14
Residential -Medium Low Density
(1-1.5 acres per d.u.) RML 1 S
Residential-Medium High Density
(0.5-1 acres per d.u.) RMH 23
Residential -High Density
(0.25-0.5 acres per d.u.) RHH 29
Residential-MultifamilyNeryHigh Density
(0.25 acres per d.u.) RVH 50
Office/Institutional/Light Industrial OFF 70
Commercial/Heavy Industrial COM 85
Paved Road with Right of Way" ROAD 85
Urban Green Space/Golf Course UGR 0
Row Crop ROW 0
Forest FOR 0
Wetlands WET 0
Water WAT N/A
' Existing and clustered development codes are tagged with "e" and "c", respectively, in the
model with no change in percent impervious.
'* Assumed imperviousness equal to commercial land use.
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NC 43 Connector
ICI Water Quality Study
e B

Watershed Boundary ~ Golf Course
ICI Project Area ~ Green Space
/~/ Roads -Quarry
~~ Railroads -Commercial/Heavy Industrial
~ . _ _; County Boundary - Q~ce/Institutional/Light Industrial
'~_. Streams ~ Residential Very High Density
® Water Bodies -Residential High Density
- Wetland -Residential Medium High Density
_ Forest -Residential Medium Low Density
Row Crop -Residential Low Density
- Residential Very Low Density
Figure 4.2.1 No Build
Land Use Scenario
ICI Water Quality Study - NC 43 Connector
TIP No. Rd463, Craven County, NC
•::
~,r ~~I North Carolina
~s~i Department of Transportation
0 0 5 1 Miles
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NC 43 Connector
ICI Water Quality Study
v

1
~0
e w -
( *~ tE, P . , °~
- • ~~4
~R. ~~
~ti
Watershed Boundary ~ Golf Course
ICI Project Area r ,Green Space
• Access Points -Quarry
/~/ Roads _ CommerdallHeavy Industrial
f\/' Railroads ~ Office/Institutional/Light Industrial
,County Boundary
r _ _ _
~ Residential Very High Density
~ Streams ~ Residential High Density
Water Bodies
- Residential Medium High Density
Wetland
- Residential Medium Low Density
- Forest
- Residential Low Density
Row Crop
- Residential Very Low Density
~,
Trem /titer

Figure 4.2.2 Build
Land Use Scenario
ICI Water Quality Study - NC 43 Connector
TIP No. R-4463, Craven County, NC
~~ ~\ North Carolina
;\~/l Department of Transportation
0 0.5 Miles
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NC 43 Connector
ICI Water Quality Study

IC Wes/hrghWay7p

o~

Trenr fthrr
Watershed Boundary ~ ~' Green Space
ICI Project Area puany
• Access Points Commerdal/Heavy Industrial
/~/ Roads ~ Office/Institutional/Light Industrial
/~/` Railroads ~ Residential Very High Density
~ _ _ _ ~ County Boundary Clustered Residential Very High Density
~\_~ Streams ~ Residential High Density
Water Bodies DOO Clustered Residential High Density
® Wetland Residential Medium High Density
_ Forest Residential Medium Low Density
Row Crop Residential Low Density
0 Golf Course Residential Very Low Density
Figure 4.2.3 Build Enhanced
Land Use Scenario
ICI Water Quality Study - NC 43 Connector
TIP No. R-4463, Craven Count', NC
ra:a.,;~
(, 1SJ North Carolina
f~y~% Department of Transportation
"zs.,.r%j
0 0.5 Miles
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ICI Water Quality Study
4.2.5 Modellmperviousness
The intensity of imperviousness increases as development density increases, which
directly affects the velocity and volume of runoff, as well as the quantity of pollutant
export. The land use categories and associated impervious intensities utilized in this
modeling analysis represent interpolations of the imperviousness levels given by lot size
in the SCS TR-55 Manual (SCS, 1986) and are identical to the categories utilized in the
Jordan Lake watershed model except for roads which were not explicitly included in the
Jordan model (Tetra Tech, 2004). The Jordan Lake categories were utilized because
they represent a strong resolution of categories with which to capture all the existing and
future land uses present in the NC-43 connector study area. The categories and their
associated impervious percentages are presented in Table 4.2.1.
4.3 Surface Water Hydrology
Table 4.3.1 provides a summary of several of the surface water inputs and assumptions
utilized in the GWLF modeling analysis. The individual parameters are discussed below.
Table 4.3.1 Surface Water Hydrology Input Parameters
INPUT BASELIN COMMENTS/
DESCRIPTION ®
UNIT E LITERATURE REFERENCE
PARAMETER VALUE RANGE
Precipitation Daily rainfall cm Annual Min Seven years of Data from
= 100.1 data (1998-2005) Craven County
Max = 184.4 used for Airport (KEWN)
Mean = simulation and and COOP
133.2 assumed to be Station 316108,
uniform for the State Climate
study area Office of NC
Evapo- Cover coefficient none Values Rural land uses: Haith et al.
transpiration for estimating ET range from Default values (1992)
(ET) Cover 1.0 for derived based on
forest to land use.
0.15 far high Urban land uses:
intensity ane minus
urban impervious
category fraction
(COM)
Antecedent Moisture for up to cm 0 Unknown and Haith et al.
Soil Moisture five days prior to therefore (1992)
Conditions initial step. assumed in
accordance with
manual to be zero
Runoff Curve Parameter for none Ranges Site dependant SCS (1986)
Numbers converting mass from 63 to based on soil type
rainfall to mass 98 in the and land use.
runoff. current
study.
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4.3.1 Precipitation
Daily rainfall records from two stations, located one kilometer apart and 4.8 kilometers
from the study area were obtained from the North Carolina State Climate Office: Craven
County Airport (KEWN) and COOP Station 316108 (Figure 4.1.1). Data for aten-year
period was not available, therefore aseven-year time series was assembled. Data from
station KEWN for the period 4/1/98 - 3/31/99 was appended to data from station 316108
for the period 4/1/99 - 3/31/05. Missing values in the time series from station 316108
were filled in using either values from KEWN or the average for that month.
The mean rainfall over the seven-year period is within 4 percent of the long-term
average (139 cm) at station 316108 indicating that the model simulation period
represents average hydrologic conditions for the area. Rainfall was assumed uniform
throughout the study area.
4.3.2 Evapotranspiration Cover Coefficients
The portion of rainfall returned to the atmosphere through evapotranspiration (ET) is
determined by temperature and the density of vegetative cover, which varies by land use
and by season (growing and dormant). For rural land uses, evapotranspiration cover
coefficients were determined from seasonal values provided in the GWLF manual (Haith
et al., 1992). For urban land uses, the coefficients were set equal to one minus the
impervious fraction. Monthly values were determined by watershed on an area-weighted
basis.
4.3.3 Antecedent Soil Moisture Conditions
Antecedent soil moisture conditions are a function of rainfall levels up to five days prior
to the day on which modeling begins. Antecedent soil moisture conditions were unknown
and were assumed to be zero as per guidance provided in the GWLF manual (Haith et
al., 1992).
4.3.4 Runoff Curve Numbers
The fraction of precipitation that becomes surface water runoff in GWLF is calculated on
the basis of the SCS Curve Number Method as presented in the TR-55 Manual (SCS,
1986). Curve numbers are derived based on impervious cover and sail hydrologic group.
Soil hydrologic groups for the soils present within the study area were determined using
a the Natural Resource Conservation Service (NRCS) detailed soil survey geographic
(SSURGO) database. Each spatial association between a given soil group and a land
use category was deemed a hydrologic response unit (HRU) and each HRU was
assigned a curve number according to the values presented in Table 4.3.2. For each
land use within a watershed, an area-weighted curve number is assigned based on the
HRUs.
The curve numbers in Table 4.3.2 are interpolations of curve numbers given in SCS
(1986). Forest, wetland, and urban green space curve numbers are based on
Good/Fair, Poor, and Fair hydrologic conditions, respectively.
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Table 4.3.2 Curve Numbers for Land Use and Soil Hydrologic Groups
LAND USE LU GROUP GROUP GROUP GROUP COMBINED ~~
NAME CODE A B G D GROUP B 8 D,
Residential -
Very Low RVL 44 64 76 82 73
Density
Residential - RLL 47 66 77 83 75
Low Density
Residential -
Medium Law RML 50 67 78 84 76
Density
Residential -
Medium High RMH 53 69 80 84 77
Density
Residential - RHH 57 72 81 86 79 '
High Density
Clustered
Residential - RHHc 56 71 78 82 76
High Density
Residential -
Very High RVH 68 79 86 89 84
Density
Clustered
Residential - RVHc 67 77 82 85 80
Very High
Density
Office/Light OFF 80 87 91 93 90
Industrial
Commercial/He COM 89 92 94 95 94
avy Industrial
Paved Road
with Right of ROAD 83 89 92 93 91
Way
Urban UGR 49 69 79 84 77
Greenspace
Row Crop ROW 67 78 85 89 84
Forest FOR 33 57 71 78 68
Wetlands WET 45 66 77 83 75
Water WAT 98 98 98 98 98
4.3.5 Curve Numbers for Cluster Development
The development of curve numbers for clustered land uses found in the Build-Enhanced
scenario is discussed below. Cul-de-sacs, large lots, and minimal open space are typical
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features of conventional curvilinear development. Urban cluster developments are
designed to protect environmentally sensitive areas by increasing open space and
decreasing lot size. Conversion of open space to lawn usually results in less permeable
soils due the effect of grading and site development. Natural infiltration characteristics
are lost. Brander et al. (2004) conducted a comparative study of different development
types and found that even without additional BMPs and with approximately the same
amount of impervious surfaces, cluster development resulted in approximately 10 to
23% less runoff from long-term rainfall compared to conventional development. The
decrease for the one-year, 24-hour storm ranged from 23 to 37%. The decrease was a
function of hydrologic soil group, with groups C and D demonstrating the greatest
decreases. These findings are consistent with other studies showing decreases in runoff
due to clustering of approximately 25% (NOAA, 2006; Caraco et a1.,1998).
The impact of cluster development was incorporated into the model by decreasing curve
numbers for the clustered land uses (RHHc and RVHc). For example, decreasing the
curve number for a one third-acre lot on a D soil from 86 to 82 results in a decrease in
runoff of 23% fora 1.5-inch (3.8-cm) rainfall. Reductions by hydrologic soil group were
applied to curve numbers for clustered development that resulted in a 20 to 25%
decrease in runoff from C and D soils and decrease of approximately 15% for A and B
soils fora 3.8-cm rainfall. Although large storm events generate greater amounts of
runoff and transport large pollutant loads, most storm events are small. The selection of
the 3.8-cm rainfall represents a compromise between large and small events. Note that
the cluster development measure is simulated as an addition to existing caps on
nitrogen loading.
4.4 Groundwater Hydrology
Table 4.4.1 provides a summary of several of the groundwater inputs and assumptions
utilized in the GWLF modeling analysis. The individual parameters are discussed below.
4.4.1 Recession Coefficient
The rate at which groundwater is discharged to streams is a function of the recession
coefficient. In theory, provided that flow data are available, this factor can be determined
through analysis of the hydrograph. However, no flow data were available within the
study area. GWLF modeling studies by Lee et al. (1999) coastal Maryland have shown
that the GWLF model results are sensitive to the recession coefficient and that the
coefficient is strongly correlated with drainage area. Through model calibrations and
regression analyses on numerous watersheds Lee et al. (1999) developed the following
relationship between recession coefficient (R) and drainage area (DA in km2):
R = 0.0450 + 1.13 ' (0.306 + DA)-'
This equation was used to calculate individual recession coefficients for each of the
GWLF subwatersheds simulated. Results ranged in value from 0.14 to 0.63.
4.4.2 Seepage Coefficient
GWLF simulates three subsurface zones: a shallow unsaturated zone, a shallow
saturated zone (aquifer), and a deep aquifer zone. The deep seepage coefficient is the
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portion of groundwater in the shallow aquifer that seeps down to the deep aquifer and
does not return as surface flow, thereby removing it from the water balance of the
watershed. In eastern North Carolina, 2.5 to 5 cm per year typically infiltrates through to
deep groundwater aquifers, representing about 2 to 3% of the water balance (Evans et
al., 2000). The seepage coefficient was set to a value (0.005) that produced a 2% loss to
deep groundwater.
Table 4.4.1 Groundwater Input Parameters
__.w~
INPUT ~s- " 'r ~_ra. w. ar. F"~
M
DESCRIPTION xae~nq.

UNIT , ~ -: s~. _
BASELINE
' COMMENTS/

R
U
R
E
LITE m r ,a .
~~
R~
EFyERE
PARAMETER; ,9V
A
LUE ~
NG
„
~
,f_31 ,~
,
~
Baseflow Groundwater day -' Min = 0.14 Drainage area- Lee et al.
Recession seepage rate Max = 0.63 dependant and (1999)
Coefficient (r) Mean = calculated
0.24 according to
Lee et al. (1999)
Seepage (s) Deep seepage day -' 0.005: Site dependant; Haith eta/.
coefficient Goal to (1992);
2°!;+ generate 2% Evans et al.
deep seepage (2000)
over the
simulation
period
Unsaturated Interstitial storage cm Min = 12.9 Determined Haith et al.
Soil Water Max = 19.0 from SSURGO (1992)
Storage Mean = soils data
Capacity 16.2
Initial Initial amount of cm 10 GWLF Manual Haith et al.
Unsaturated water stored in default (1992)
Storage (IUS) unsaturated zone
Initial Saturated Initial amount of cm 0 GWLF Manual Haith et al.
Storage (ISS) water stored in default (1992)
saturated zone
4.4.3 Available Soil Water Capacity
Water stored in the soil may evaporate, be transpired by plants, or percolate down to
groundwater below the rooting zone. The amount of water that can be stored in the soil
in the region where it is still available for evapotranspiration is the available soil water
capacity (AWC), which varies according to soil type and rooting depth. Volumetric AWC
values (cm/cm) were extracted from the Soil Survey Geographic (SSURGO) Database
for the study area and area-weighted. Assuming a 100 cm rooting depth and the
volumetric AWC, the AWC values ranged from 12.9 to 19 cm (Haith et al., 1992).
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4.4.4 Initial Saturated and Unsaturated Storage
When the initial amounts of water stored in the saturated shallow aquifer and the
unsaturated zone are unknown, the GWLF manual advises using default values of zero
and 10 cm, respectively (Haith et al., 1992). It should be noted that these parameters
have only a minimal impact on modeling results; they only affect the water balance for
the first three months of simulation (Lee et al., 1999).
4.5 Erosion and Sediment Transport
Table 4.5.1 provides a summary of several of the erosion and sediment transport inputs
and assumptions utilized in the GWLF modeling analysis. The individual parameters are
discussed below.
Sediment erosion in the GWLF model is simulated through application of the USLE,
which uses four input factors (K, LS, C and P). The first of these four is soil erodibility or
(K) factor, which is a measure of a given soil's propensity to erode when struck by water.
4.5.1 Soil Erodibility (K) Factor
K factors in this analysis were obtained from the SSURGO database. For the four soil
groups distributed within the study area, area-weighted K factors ranged from 0.15 to
0.32.
4.5.2 Length-Slope (LS) Factor
Erosion potential varies with slope as much as with soil characteristics, so the second
element in the USLE equation is the length-slope (LS) factor, which is the average
length (L) that runoff travels from the highest point of any flow path within a watershed to
the point at which it reaches concentrated flow multiplied by the slope (S), which
represents the effect of slope steepness on erodibility for each soil type. LS factors for
this modeling analysis were generated by GIS spatial analysis using the USLE Sediment
Tool included in the US Environmental Protection Agency (USEPA) Watershed
Characterization System (Tetra Tech, 2000). Area-weighted values ranged from 0.13 to
1.4, with the high values associated with the quarries.
4.5.3 Cover (C) and Management Practice (P) Factors
The mechanism by which soil is eroded from a land area and the amount of soil eroded
depends on soil treatment resulting from a combination of land uses (e.g., forestry
versus row-cropped agriculture) and the specific manner in which land uses are
managed (e.g., no-till agriculture versus non-contoured row cropping), which are
represented by cover and management factors in the USLE. Cover and management
factors for non-agricultural land uses in this study are from Haith et al. (1992). Factors
for row crop agricultural were estimated from the North Carolina Revised USLE Manual
(USDA, 1995). The resulting factors are summarized in Table 4.5.2. C and P factors are
not required for the urban land uses, which are modeled in GWLF via abuildup-washoff
formulation rather than the USLE.
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Table 4.5.1 Rural Sediment Transport Input Parameters

'INPUT

BASELINE
4_COMMENTS//' ~....
s~
°

PARAMETER
DESCRIPTION
UNIT

VALUE ~~'~~
LITERATURE
d RANGE ~
REFERENCE
Rainfall Kinetic energy MJ- 0416 (cool Rainfall erosivity Haith et al.
Erosivity (R) of rainfall Mm/ha season) may vary (1992) for
0.28 (warm seasonally and is Wilmington,
season-Apr estimated by NC
thru Oct) geographic
region
Soil Erodibility Soil erosion None Area-weighted Derived from SSURGO
Factor (K) potential soils GIS data soils data for
Min = 0.15 (function of soil the study area
Max = 0.32 texture and
composition)
Length-Slope Sediment None Varies by Derived from USEPA
Factor (LS) transport Subwatershed DEM as function Watershed
potential based of slope and Characterizati
on topography overland runoff on System
(Tetra Tech,
2000)
Sediment Portion of None Varies by Empirically BasinSim
Delivery Ratio Eroded Material Subwatershed estimated as a Utility
(SDR) that is function of (Dai et al.,
transported to Subwatershed. 2000)
receiving waters
Table 4.5.2 Cover (C) and Management Practice (P) Factors
LAND USE NAME
Residential -Very Low Density C
0.0100 P
1.000
Barren Land 0.5000 1.000
Wetlands 0.0020 1.000
Forest 0.0020 1.000
Row Crop 0.0940 0.600
Urban Grass 0.0065 1.000
4.5.4 Sediment Delivery Ratio
In GWLF, the sediment delivery ratio accounts for trapping of sediments and sediment-
bound pollutants that occurs between the edge of the field (origin) and the watershed
outlet (delivery point). The BasinSim version of GWLF utilized in this analysis includes a
software utility that calculates the sediment delivery ratio on the basis of the drainage
area of the Subwatershed being simulated. Sediment delivery ratios for this study ranged
from 0.212 to 0.318.
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4.5.5 Sedimentation from Urban Land Uses
For urban land uses, the GWLF model calculates particle loads associated with
particulate nutrients without calculating sediment load. For the present study, sediment
from urban sources was modeled using the same accumulation and washoff functions
from the model substituting sediment accumulation rates for particulate nutrient
accumulation rates. A similar approach was used by Schneiderman et al. (2002) in an
update to the original application of GWLF on the Cannonsville watershed by Haith and
Shoemaker (1987).
In the model application, sediment accumulation rates by land use ranged from 1.8 to
3.7 kilograms per hectare per day (kg/ha/day). These rates were based on suspended
solids accumulation rates from Kuo et al. (1988) as cited in Haith et al. (1982). Rates for
residential land uses ranged from 1.8 to 3.7 kg/ha/day, with values increasing with
imperviousness. Rates for nonresidential land uses including commercial and
institutional categories were 2.2 to 2.5 kg/ha/day.
The accumulation rate (1.8 kg/ha/day) for roads was determined by iteratively running
the Wilson Creek No Build Scenario, adjusting the rates until the model predicted an
export rate of 185 kg/ha/yr. The target export is based on the average of the North
Carolina value from FHWA (1990) and regional event mean concentration values in
USEPA (2001).
4.6 Nutrient Loading
Table 4.6.1 provides a summary of several of the nutrient inputs and assumptions
utilized in the GWLF modeling analysis. The individual parameters are discussed below.
4.6.1 Solid Phase Nutrients
Sediment bound nutrient loads to streams are driven by the soil nutrient concentrations
within the watershed. In the absence of study area specific information, the soil
concentration of total nitrogen and total phosphorus in this analysis was set at 1400
mg/kg and 352 mg/kg, respectively, based on guidance from the GWLF Manual (Haith et
al., 1992) and regional observations provided by Mills et al. (1985).
4.6.2 Dissolved Groundwater Nutrients
The GWLF model applies average groundwater nitrogen and phosphorus concentrations
to flow from the saturated zone to the stream channel. Based on the nutrient
concentration values reported by Spruill et al. (1998) in a study of water quality in the
Albemarle-Pamlico Drainage Basin, groundwater nutrient concentrations in this modeling
analysis were set at 0.42 mg/L for TN and 0.04 mg/L for TP.
4.6.3 Runoff Concentrations and Build-up Rates
In GWLF, nutrient loads from different land uses are based on the volumes of flow and
the associated flow pathways (overland or seepage), the amounts of soil eroded, and
concentrations that express the amount of nutrient load per unit volume of water flow or
sediment erosion from each land use. The GWLF model uses buildup/washoff
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relationships to predict nutrient loads for urban (developed) and runoff concentrations to
predict nutrient loads from rural and agricultural land uses. These processes vary based
on the interactions between soil types and land uses, and are defined by a range of
parameter values (Table 4.6.2). Except for roadways and urban greenspace, runoff
concentrations and build up/wash off rates are based on those used in the Jordan Lake
Watershed Model (Tetra Tech, 2003).
Table 4.6.1 Nutrient Loading Input Parameters
INPUT
PARAM=ETER' ~ .'""''
DESCRIPTION
~. ~ ~~-
UNIT ~ BASELINE

;VALUE- ..~~.MENTS/
LITE~R,A,,,~TURE . _ .
REFERENCE
~z
~~""` «,~ ~~
REVIEW ..,,.
„
~ q. w, „
. rex, ~ 3. F ,~n,''
- ~Soo°h '~'L~ ...n Rh.:~.#~'sl xa`..'~ .... Ty^ C'.t°SF '~'~:..
d P:ha9e Nutrient CoaBing
Nutrient Total Nitrogen mg/kg 1400 Varies Haith et al.
concentration Concentration regionally and (1992)
in sediment by site; 500-900 Mills et al.
from rural based on (1985)
sources literature;
multiplied by a
mid range
enrichment ratio
of 2.0
Total mg/kg 352 Varies Haithetal.
Phosphorous regionally and (1992)
Concentration by site; ;less Mills et al.
than or equal to (1985)
400; multiplied
P2O5
conversion
factor and
enrichment ratio
(2.0)
Disso lved Nut~len tin Groundw ater ,.

Nutrient Total Nitrogen mg/L 0.42 Median value Spruill et al.
concentration Concentration for the inner (1998)
coastal plain
Total mg/L 0.04 Median value Spruill et al.
Phosphorous for the inner (1998)
Concentration coastal plain
Nutient runoff concentrations and build-up rates are from Tetra Tech (2003). The rates
were re-evaluated for use in this study and were found to be within the range of the
GWLF nutrient inputs used in recent studies focused on coastal plain watersheds except
for nitrogen build-up (CH2M Hill, 2003; Lee et al., 1999; Dodd and Tippett, 1994).
Nitrogen build-up rates used in the Jordan Lake study and the present study are higher
(about double) than default model values and the coastal plain studies cited above.
Buildup rates in the Jordan Lake study were derived based on event mean concentration
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values from Line et al. (2002), CH2M HILL (2000), Greensboro (2003), and U.S. EPA
(1983). Those rates were found to be in general agreement with export coefficients
reported in the literature (CDM, 1989; Hartigan et al., 1983; USEPA, 1983; Beaulac and
Reckhow, 1982; Frink, 1991). The Jordan Lake values are probably more appropriate
given that their origin is primarily in North Carolina research.
Table 4.6.2 Nutrient Runoff and Buildup Rates for Existing Land Uses
RUNOFF CONCENTRATIONS...,
_
RURAL LAND USES ~ ,-
DISSOLVED N (mg/L)
m /L
Pasture 2.770 0.250
Row Crop 2.770 0.250
Forest 0.190 0.006
Wetlands 0.190 0.006
Barren 0.190 0.006
Urban Greenspace 0.200 0.0065
Residential -Very Low Density 0.230 0.007
' ~ "~ ~' MASSi BUIL`-DUP,RATES " '~"
URBAN LAND USES ~ '
~ N BUIL''DUP (kg/ha/day) °P BUILDUP (kglha/day)
Residential -Low Density 0.214 0.040
Residential -Medium Low Density 0.242 0.040
Residential -Medium High Density 0.242 0.040
Residential -High Density 0.219 0.037
Residential -Very High Density 01 0.033
Office/Light Industrial 0.158 0.025
Commercial/Heavy Industrial 0.191 0.029
Roadways 0.052 0.006
Rates for roadways were assigned values using the iterative method described in
section 4.5.5: determination of accumulation rates necessary to produce TN and TP
export rates of 5.5 and 0.7 kg/ha/yr (FHWA, 1990; USEPA, 2001). Urban greenspace
land uses were assigned values between very low density residential and forest land
uses.
An important assumption of the analysis was that the study area would be served by the
existing wastewater treatment plant of the City of New Bern (Avery, personal
communication, 2005). As a result, no inputs for septic tanks were included in the GWLF
modeling analysis. Also, there are no permitted point sources of pollutant load located
within the study area.
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4.7 Consideration of Existing Environmental Regulations
4.7.1 Neuse River Nutrient Sensitive Waters Management Rules
The Neuse NSW stormwater management program imposes a 4.0 kg/ha/yr (3.6 pounds
per acre per year or Ib/aclyr) nitrogen loading limit on new development. Nitrogen load
from new developments that exceeds this performance standard may be offset by
payment of a fee to the Wetlands Restoration Fund provided, however, that no new
residential development can exceed 6.7 kg/ha/yr (6.0 Ib/ac/yr) and no new nonresidential
development can exceed 11.2 kg/ha/yr (10.0 Ib/ac/yr).
Since most existing development within the study area occurred before 1998, all existing
development was assigned loading rates shown in Table 4.6.2. Rates for future
residential and nonresidential development were determined using the iterative process
described in section 4.5.5 targeting TN export rates of 6.5 and 4.4 kg/ha/yr for
nonresidential and residential land uses, respectively. These export rates are based on
an approximation of the amount of time that land developers in New Bern choose to use
the payment offset provision in the regulations. Meadows (2006) suggests that use of
the offset provision occurs 15 and 50% of the time for residential and commercial
development, respectively. Weighted export rates were determined accordingly.
Reductions in nitrogen loading will be accompanied by reductions in TP and TSS
(NCDWQ, 2004 and 2005). A concomitant reduction of 30% in both constituents is
assumed and implemented in the model simulations.
An additional feature of the Neuse rules requires no net increase in peak flow leaving a
newly developed site compared to predevelopment conditions for the one-year, 24-hour
storm. This feature was not explicitly incorporated into the model simulation for two
reasons. Since most BMPs convert little runoff to infiltration, mitigating peak flows will
have little impact on long-term runoff rates or volumes. In addition, BMPs for water
quality provide some control of peak flow, so some of this required control is considered
implicitly.
In all three land use scenarios, afifty-foot buffer on all perennial and intermittentstreams
identified on the USGS-based stream coverage was classified as urban greenspace.
4.7.2 Coastal stormwater Management Program
Control of volume from the first inch of rainfall is not explicitly considered in the analysis
for the reason cited above for the peak flow requirements under the Neuse rules. The
TSS removal requirement has been incorporated into the model as follows: a reduction
factor is applied to sediment or TSS loading rates for the land uses with assumed
imperviousness greater than 30%: COM, OFF, RVH. The factor (0.184) was calculated
based on two primary assumptions: approximately 80% of storms are one inch (2.5 cm)
or less (NCDWQ, 2005b) and approximately 80% of TSS load from a storm is
transported in the first inch of rainfall. The factor is applied in lieu of the reduction
described in section 4.7.1.
The latter assumption is based on a modification of the "first-flush" phenomenon. "First
flush" is the runoff that occurs at the beginning of a rainstorm. The concept suggests that
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most contaminants that have accumulated on impervious surface are transported in the
"first flush" or runoff from the first one half inch of rainfall. An often-cited number is 90%
of the load is delivered in the "first flush" (Hager, 2001). Chang (1990) investigated the
concept further finding that TSS capture in the first half inch was 43 to 81 % for levels of
impervious of 30% or greater (Schueler and Holland, 2000). Therefore, it was assumed
for the purposes of the model simulation that 80% of TSS load from a storm is
transported in runoff from the first inch of rainfall.
4.8 Modellmplementation
Based on the series of inputs discussed in the following section, a series of transport
and nutrient model input files were developed to execute individual model runs
simulating the Build, No-Build, and Build-Enhanced scenarios in each of the GWLF
subwatersheds presented in Figure 4.1.1. All model runs relied on the same weather file
that contains precipitation and air temperature data for climate years 1998 - 2005. The
climate year for GWLF is defined as April 1 -March 31. Model input files are presented
in Appendix A.
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5 GWLF MODEL RESULTS AND DISCUSSION
5.1 Hydrology
Components of the hydrologic cycle illustrated in Figure 3.2.1 include precipitation,
evapotranspiration, runoff, and deep groundwater seepage. In eastern North Carolina,
rainfall typically ranges from 112 to 152 cm (44-60 in). Evapotranspiration (ET), runoff
(surface and subsurface) and deep groundwater outflow range from 81 to 102 cm (32-40
in), 30 to 51 cm (12-20 in), and 3 to 5 cm (1-2 in), respectively (Evans etal., 2000).
A comprehensive study of hydrology of forested lands in eastern North Carolina found
that annual outflow or runoff from forested sites ranged from 17 to 45% of rainfall
(Chescheir et al., 2003). Runoff from the most undeveloped subwatershed in the model
simulations, Rocky Run, comprised 39% of the water balance over the simulation period
for the No-Build Scenario. ET comprised 59% of the water balance, lower than the
typical range of 67 to 73% cited by Evans et al. (2000). The lower percentage of ET is
likely due to the greater amount of development compared to the typical mass balance
described in Evans et al. (2000). Urbanization is accompanied by a decrease in
vegetation available to produce evapotranspiration as well as a greater proportion of
surface runoff (versus subsurface runoff in shallow groundwater). For the study area as
a whole, ET and runoff were 46 and 53% of total rainfall for the No Build Scenario.
The seasonal change in hydrologic conditions in the Rocky Run subwatershed is shown
in Figure 5.1.1. As expected, evapotranspiration decreases in winter due to lower
temperatures and dormant vegetation resulting in a higher proportion of runoff.
5.2 Pollutant Loading
For each land use scenario, GWLF model output time series were generated reflecting 7
years of annual total nitrogen (TN), total phosphorus (TP) and sediment loads. Annual
loads were aggregated into 7-year pollutant loads for each parameter and each
subwatershed and the results are presented by pollutant in Tables 5.1.1 through 5.1.3.
The Build Scenario resulted in increases in TN and TP for all subwatersheds ranging
from less than 1% to about 16%. Sediment loads increased in four of seven
subwatersheds. The average sediment load across all subwatersheds decreased 1.5%
when comparing the Build and No-Build Scenario. This overall decrease results from
existing regulations governing sediment loss from new development.
The Build-Enhanced scenario resulted in pollutant decreases in all subwatersheds
except one. Caswell Branch saw no change in any constituent in the Build Enhanced
scenario because no additional measures are planned. The greatest reductions (13 to
23%) due to the Build-Enhanced scenario were found in UT to Wilson Creek due to
additional management measures covering nearly half of the subwatershed. An
additional decrease over the Build Scenario of almost 7% of sediment loading is
predicted for the Build-Enhanced scenario. This results from a decrease in surface runoff
due to the implementation of open space preservation and cluster development.
subwatershed decreases in surface runoff ranged from 1 to 13%.
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20
18
16
14
12
E 10
8
6
4
2
0
-~ Predpitation (cm)
t Evapotranspiration (cm)
Subsurface RunoR (cm)
~-Surtace Runoff (cm)
~TOtal Runoff (crn)
Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar
Figure 5.1.1 Mean Monthly Water Balance for the Rocky Run Subwatershed (No Build
Scenario)
Nutrient and sediment export by subwatershed is presented in Figures 5.2.1 through
5.2.3. Patterns are similar for all three constituents. Rocky Run had the lowest export of
all constituents due to its relatively undevelopecJ nature: 58% of the land use in the No
Build Scenario is forest or open space. The Neuse River and Wilson Creek catchments
exhibited the highest loading rates. While these are the largest by area, they also have
the most existing development, which is simulated at higher loading rates in the model.
In sum, nonpoint source loading is increased in the Build Scenario, though the increase
is mitigated to some extent by the existing regulations governing the jurisdiction.
Additional measures proposed by the City of New Bern simulated in the Build-Enhanced
scenario were effective in providing further mitigation of the impacts of new
development. Based on model predictions and the assumptions therein, the Build-
Enhanced scenario resulted in decreases in pollutant loading to near or below No-Build
levels over the entire study area (Figure 5.2.4).
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Table 5.1.1 Seven-Year Total Nitrogen Loads (tonnes) for All Subwatersheds
,..r _

~

Caswell Branch

No Build

21

Build

24 °h Change

Over No
Build
15.5% ..
Enhanced

guild
24 % Change

Over No
guild
15.5%
Deep Branch 34 36 7.5% 35 4.6%
Hayward Creek 7 7 9.2% 7 3.7%
Neuse River 73 76 4.2% 76 3.3%
Rocky Run 24 25 3.9% 24 0.4%
UT to Wilson Creek 34 35 3.0% 31 -10.3%
Wilson Creek 92 93 1.5% 91 -0.8%
Total 285 297 4.5% 288 1.1%
Table 5.1.2 Seven-Year Total Phosphorus Loads (tonnes) for All Subwatersheds

aswell Branch

No Build

6

Build

7 Cha' n' g

Over No
Build
13.6%
Enhanced

Build
7 ~"/o Cha' nge~

Over No
Build
13.6%
Deep Branch 7 8 8.4% 8 2.6%
Hayward Creek 2 2 9.3% 2 0.0%
Neuse River 16 17 2.3% 16 0.6%
Rocky Run 5 5 3.1% 5 -5.4%
UT to Wilson Creek 8 8 1.0% 6 -21.7%
Wilson Creek 17 17 0.3% 16 -5.1%
Total r80~ r-84~ 3.7% 59 -2.8%
Table 5.1.3 Seven-Year Total Sediment Loads (tonnes) for All Subwatersheds

aswell Branch
No Build

300
Build

218 °~ Change
Over No
Build
-27.4% Enhanced

guild
218 °~ Change
Over No
guild
-27.4%
Deep Branch 374 374 -0.1% 344 -8.1%
Hayward Creek 74 81 9.3% 71 -4.9%
Neuse River 966 910 -5.8% 903 -6.5%
ROCky RUn 305 344 12.6% 314 2.7%
UT to Wilson Creek 466 488 4.6% 382 -18.1%
Wilson Creek 1192 1210 1.5% 1147 -3.7%
Total 03.578 X3625 -1.5% ~3378~ -8.2%
5-3

NC 43 Connector
ICI Water Quality Study
12
10
8
_T
(0 6
t
OI
Y
'~ 4
2
0
Figure 5.2.1 Mean Annual Total Nitrogen Loading Rates
3.5
3.0
2.5
i. 2.0
m
L
r 1.5
1.0
0.5
0.0
Figure 5.2.2 Mean Annual Total Phosphorus Loading Rates
5-4
Caswell Deep Hayward Neuse Rocky UT to Wilson
Wilson
Caswell Deep Hayward Neuse Rocky UT to Wilson
Wilson

NC 43 Connector
ICI Water Quality Study
250
200
150
^ No Build
^ Build
^ Enhanced Build
T
t0
L
Ol
100
0
50
Caswell Deep Hayward Neuse Rocky UT to Wilson
Wilson
Figure 5.2.3 Mean Annual Sediment Loading Rates
500
450
400
350
~, 300
a~
c 250
0
~ 200
150
100
50
0
^ No Build
^ Build
^ Enhanced Build
": a
~'..
ti
-; <';..1
09 _,~
TN TP Sediment X 10
Figure 5.2.4 Total Nitrogen (TN), Total Phosphorus (TP), and Sediment Loading Over
the Seven-Year Model Simulation Period
5-5

NC 43 Connector
ICI Water Quality Study
5.3 Verification of Model Results
No stream flow or water quality data within the study area were available for model
calibration. Though the current model application can only provide a coarse
approximation of pollutant loads for the study area, it still remains highly useful for
purposes of comparing relative degrees of change between different watershed
management strategies or land use regimes. Further, the uncertainty in the difference
between the model results of two alternatives is typically much smaller than the
uncertainty in the absolute results (Reichart and Borsuk, 2002).
Nonetheless, it is appropriate to determine if, at a minimum, the results are reasonable
and within physically defensible ranges. One approach for judging the validity of results
is by comparison of predicted pollutant load outputs to those reported in other t studies.
5.3.1 Pollutant Loading Comparison
Table 5.2.1 presents predicted pollutant loads from the current GWLF analysis as well
as those from the four GWLF modeling studies in North Carolina and additional literature
values. The subwatershed ranges of reported values from the modeling studies were
standardized to aerial load rates for purposes of comparison.
Three of the four GWLF modeling analyses received some limited calibration. The
exception is CH2M HILL (2003), which lacked local flow and constituent data to formally
calibrate the model as in the present study.
When evaluating the reported load values in Table 5.2.1 consideration should be given
to the differences in study area characteristics. For example, the studies described in
CH2M HILL (2003) and RTI (1995) were performed on a rural watersheds and hence
reflect the impact of significant areas of agricultural land. The Morgan Creek study by
Tetra Tech (2004) encompassed the Town of Chapel Hill.
Evaluation of the load values presented in Table 5.2.1 reveals that the maximum values
of TN and sediment loads from the current GWLF analysis are lower than most of the
other studies except for TN in the rural watersheds. This largely stems from the
representation of nutrient loading restrictions in the Neuse River Basin as well as the
Coastal Stormwater Rules' treatment requirement for TSS. Elevated sediment loading in
CH2M Hill (2003) and RTI (1995) is derived mostly from row crop agricultural land uses.
Phosphorus values from the current study are within the range of most of the citations.
5.3.2 Streamflow Comparison
Another effective means by which to judge the validity of results from a modeling
analysis of this nature is to compare the predicted stream flow to that from a nearby
USGS stream gage with similar drainage area characteristics.
The nearest USGS gage with a reasonably small drainage area is the gage on West
Prong Brice Creek below SR 1101 near Riverdale, station number 0209257120. The
Brice Creek gage, located approximately 16 km south of the study area has a reported
drainage area of 29 km2 and an average daily flow of 19 cubic feet per second or 0.54
cubic meters per second (m'/s), based on data from four years (1987-1990). This time
5-6

NC 43 Connector
ICI Water Quality Study
period coincidentally represents average hydrologic conditions based on state-wide
annual precipitation data.
In order to provide a standardized comparison, the flows from the seven GWLF
subwatersheds were converted into annual m'/ha yields. The 10-year average annual
yields from the seven subwatersheds (No Build Scenario) ranged from 5,224 to 7,997
m'/ha/yr, resulting in percent errors of -11 to 37% and an overall average of 20%, when
compared to the average annual yield form the Brice Creek gaging station (5,855
m'/ha/yr). Percent errors in annual meari values were calculated by the following
formula: [(simulated -observed) / observed] x 100% (Zarriello, 1998).
If this were a comparison of simulated values and actual observed values measured
within the watershed, an average percent error of 20% in annual predictions would
represent a "Fair' calibration according to Donigian's (2000) general calibration targets
for watershed modeling. The comparison indicates that the predicted stream flows from
the GWLF modeling results are reasonable.
Table 5.2.1 Comparison of Model Loading Rates to the Literature
L Stud Location watershed Tot al N K Tot al P Sed~l menTt~
y Land Use (kg/~ `
ly~ (kg/h atyr) (kglfr atyr)
s" MIn Max Mln Max Mln Max:
Current Inner Coastal Plain urban 3
3 9
8 0
7 1
9 42 127
Study' NC . . . .
CH2M HILL Inner Coastal Plain rural 2.5 8
0 7
0 1
9 29 361
(2003)' NC . . .
Tetra Tech Piedmont NC
(2003)' Jordan Lake mixed 1.8 26.9 0.3 2.8 -- --
Watershed
Tetra Tech Piedmont NC
(2004)' Morgan Creek mixed 3.7 16.1 0.3 1.9 -- --
Watershed
Coastal Plain and
RTI (1995)' Piedmont NC rural 1.6 2.7 0.1 0.3 25 355
Tar-Pamlico River
Basin
Compilation
of Literature
Export Various various 0.7 28.0 0.01 3.8 -- --
Coefficients "
'GWLF Modeling Study
'" A compilation of literature export coefficients for nutrients was presented in both Line et al.
(2002) and Tetra Tech (2003).
5-7

NC 43 Connector
ICI Water Quality Study .
STREAM EROSION RISK ANALYSIS
The proportion of impervious surface increases as the intensity of development
increases, which also increases the volume and velocity of stormwater runoff. The
resulting increase in frequency and magnitude of high flow events in receiving streams
has the propensity to increase hydraulic shear stress, in turn raising the risk level for
stream erosion and sedimentation, potentially leading to degradation of aquatic habitat.
In order to examine the potential for increased risk levels for these phenomena, a simple
analysis was used to predict the degree of change in storm flow volume associated with
the Build and Build-Enhanced Scenarios relative to that of the No Build Scenario. The
analysis was performed through application of the SCS Curve Number Method as
presented in Urban Hydrology for Small Watersheds (SCS, 1986). The technical
approach to the analysis and the results are described below.
6.1 Technical Approach
The Curve Number Method represents awell-established means to estimate runoff
volume from a given rainfall event. The method involves three equations, the first of
which is used to determine the potential maximum retention after runoff begins (S) for
each land use type through:
Su = (1000 /CNu) - 10
Where: CNu =Runoff Curve Number for Land Use Type U
The portion of runoff contributed by each land use type within a given watershed is
calculated by:
Qu=(P-0.2`Su)2/(P+0.2`Su)
Where: Qu =Flow Volume contributed by Land Use Type U
P =rainfall
The total flow volume is then estimated with the equation:
Qrorar = ~u (Au { Qu)
Where: Q7orn~ =Total Flow Volume contributed by all Land Uses within the watershed
evaluated
P =rainfall
Au =Area of Land Use Type U
The runoff curve numbers utilized in this analysis are identical to those used in the
GWLF modeling analysis and are presented in Table 4.3.2. The storm event selected
for the analysis was the one-year, 24-hour storm in order to approximate the amount of
rainfall that would result in bankfull flow conditions in the receiving streams. The greatest
potential for channel erosion occurs for storms with a recurrence interval of one to town
years. The rainfall volume for the one-year, 24-hour storm is approximately 9 cm or 3.5
inches (USDC, 1961).
6-1

NC 43 Connector
ICI Water Quality Study
Note that runoff volume is calculated for each land use and then summed rather than
producing a single area-averaged curve number from which to calculate runoff. This
approach avoids underestimation of runoff derived from the fact that runoff is not a linear
function with respect to curve number.
The analysis incorporated the requirements from the coastal stormwater program, which
calls for control of a one inch (3 cm) rainfall for high density development. In addition, the
Neuse rules require no net increase in peak flow leaving a newly developed site
compared to predevelopment conditions for the one-year, 24-hour storm. Therefore, the
peak flow from both the Build and Build-Enhanced Scenarios are required to be equal or
less than the No Build peak flow. Since this analysis looks at runoff volume rather than
peak flow rate, this requirement is not explicitly incorporated into the analysis.
5.2 Results
The above equations and assumptions were executed on the Build, No-Build, and Build-
Enhanced land use scenarios presented in Section 4.2 and the results comparing the
three scenarios for the seven GWLF subwatersheds are presented in Table 6.2.1.
The analysis suggests that development of the Build Scenario would have a slight
impact on storm event flows volumes for the one-year, 24-hour storm. However, the
Build-Enhanced scenario mitigates most of the increases by subwatershed and actually
reduces the total storm flow volume to below No Build levels. While the peak flow rate
control was not included in the analysis, it can be expected to provide additional
protection in both Build Scenarios.
Table 6.2.1 Storm Flow Volumes (cubic meters) for the One-Year, 24-Hour Storm
(1 acre-foot equals 1233.5 m')
""
subwatershed

.,.
.w
No Build
~Bulid % Chan a
Over No
Build ^"% `_
gU1ld
Enhanced % Chan e
Over No
gulldEl ,
x a
Caswell Branch 344,932 339,901 -1.5% 339,901 -1.5%
Deep Branch 325,748 325,570 -0.1% 317,861 -2.4%
Hayward Creek 61,275 64,734 5.6% 62,235 1.6%
Neuse River 621,392 624,045 0.4% 623,794 0.4%
Rocky Run 334,377 343,489 2.7% 331,781 -0.8%
UT to Wilson Creek 272,224 279,997 2.9% 267,166 -1.9%
Wilson Creek 579,476 581,716 0.4% 561,384 -3.1%
Total 2,539,423 2,559,451 0.8% 2,504,121 -1.4%
6-2

NC 43 Connector
ICI Water Quality Study
7 CONCLUSIONS
The project referred to as the NC 43 Connector (TIP Project No. R-4463) is proposed as
a four-lane, median-divided, partial control of access facility on new location in City of
New Bern. An ICI Assessment was developed in January 2005 to provide
comprehensive information on the potential long-term, induced impacts of the proposed
project (NCDOT, 2005b).
In response to NC Division of Water Quality (NCDWQ) comments on the ICI
Assessment and in preparation for an Individual Section 401 Water Quality Certification,
a water quality modeling analysis was conducted to quantify the project's ICIs on water
resources. The focus of the analysis is on the potential increases in stormwater runoff
and nonpoint source loads of nitrogen, phosphorous and sediment resulting from various
future development scenarios associated with the roadway.
Predictions from the modeling analyses suggest that while storm event runoff volume
and nonpoint source pollutant loading would increase in the Build Scenario relative to
the No Build Scenario, the increase is mitigated to some extent by the existing
regulations governing the jurisdiction including the Neuse Rules. Additional measures
proposed by the City of New Bern simulated in the Build-Enhanced Scenario were
effective in providing further mitigation resulting in overall decreases in storm flow
volume and pollutant loading to near or below No-Build levels over the entire study area.
These results are particularly important for TN considering the impairment status of the
Neuse Estuary and its existing TMDL. The analysis suggests that implementation of the
City of New Bern proposed conservation measures would be protective of downstream
water quality and consistent with the TMDL.
7-1

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8
Avery, M. 2005. New Bern Department of Planning. Personal communication. December
2005.
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Donigian, A.S., Jr. 2002. Watershed model calibration and validation: The HSPF
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9 APPENDIX
9.1 GWLF Model Inputs
9.1.1 Nutrient and Sediment Files
Nutrient.dat
1400 352 0.42 0.04
0 1 2
0.19 0.006
1.94 0.175
0.2 0.0065
0.23 0.007
0.2 0.0065
0 0
0.19 0.006
0.055 0.0203
0.191 0.029
0.055 0.0203
0.158 0.025
0.063 0.026
0.219 0.037
0.063 0.026
0.061 0.026
0.214 0.037
0.0619 0.028
0.242 0.04
0.061 0.028
0.0515 0.0064
0.0532 0.0231
0.201 0.033
0.0532 0.0231
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 0
0 0 0 0
0 0 0 0
9-1

NC 43 Connector
ICI Water Quality Study
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
0 0 0 0
0 0 0 0
12 2.5 1.6 0.4
UrbanSediment.dat
0 0 0 0
0 1 2
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0.46
0 2.5
0 0.4
0 2.2
0 1.81
0 2.58
0 1.81
0 1.27
0 1.81
0 1.59
0 2.27
0 1.41
0 1.75
0 0.67
0 3.65
0 0.67
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
0 0
9-2

NC 43 Connector
ICI Water Quality Study
UrbanSediment.dat
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 0 0 0
0 0 0 0
0 0 0 0
0 0 0 0
0 0 0 0
0 0 0 0
12 2.5 1.6 0.4
9.1.2 Transport Files
Caswell NoBld Trans.dat
7 16
0.22 0.005 10 0 0 0.245 19
0
0
0
0
0
Apr 0.736 12.8 1 0.28
May 0.736 13.7 1 0.28
Jun 0.736 14.2 1 0.28
Jul 0.736 14 1 0.28
Aug 0.736 13.2 1 0.28
Sep 0.736 12.2 1 0.28
Oct 0.736 11.2 1 0.28
Nov 0.734 10.2 0 0.16
Dec 0.734 9.8 0 0.16
Jan 0.734 10 0 0.16
Feb 0.734 10.8 0 0.16
Mar 0.734 11.8 0 0.16
FOR 35.45 75 0.00006
ROW 1.7 87 0.00079
RVL 0 88 0
RVLe 0 88 0
UGR 115.44 82 0.0002
WAT 116.04 98 0
WET 0 98 0
9-3

NC 43 Connector
ICI Water Quality Study
COM 57.73 95 0
COMB 8.11 95 0
OFF 0.26 93 0
OFFe 0.02 93 0
RHH 137.63 86 0
RHHe 0 86 0
RHHC 0 86 0
RLL 10.29 81 0
RLLe 7.8 81 0
RMH 1.35 84 0
RMHe 1.55 84 0
RML 0 84 0
ROAD 11.82 93 0
RVH 97.69 88 0
RVHe 4.76 83 0
RVHc 0 88 0
9-4

NC 43 Connector
ICI Water Quality Study
Dee NoBld Trans.dat
7 16
0.18 0.005 10 0 0 0.233 17
0
0
0
0
0
Apr 0.699 12.8 1 0.28
May 0.699 13.7 1 0.28
Jun 0.699 14.2 1 0.28
Jul 0.699 14 1 0.28
Aug 0.699 13.2 1 0.28
Sep 0.699 12.2 1 0.28
Oct 0.699 11.2 1 0.28
Nov 0.699 10.2 0 0.16
Dec 0.699 9.8 0 0.16
Jan 0.699 10 0 0.16
Feb 0.699 10.8 0 0.16
Mar 0.699 11.8 0 0.16
FOR 262.98 73 0.00002
ROW 0.4 85 0.00122
RVL 54.4 73 0.00008
RVLe 0.12 73 0.00008
UGR 8.92. 80 0.00018
WAT 3.42 98 0
WET 6.67 83 0
COM 21.24 94 0
COMB 46.24 94 0
OFF 118.31 90 0
OFFe 3.33 90 0
RHH 65.61 82 0
RHHe 0 84 0
RHHc 0 86 0
RLL 0.07 83 0
RLLe 1.33 83 0
RMH 148.19 80 0
RMHe 0 83 0
RML 0 84 0
ROAD 41.83 91 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0
9-5

NC 43 Connector
ICI Water Quality Study
Ha and NoBld Trans.dat
7 16
0.63 0.005 10 0 0 0.318 12.9
0
0
0
0
0
Apr 0.708 12.8 1 0.28
May 0.708 13.7 1 0.28
Jun 0.708 14.2 1 0.28
Jul 0.708 14 1 0.28
Aug 0.708 13.2 1 0.28
Sep 0.708 12.2 1 0.28
Oct 0.708 11.2 1 0.28
Nov 0.708 10.2 0 0.16
Dec 0.708 9.8 0 0.16
Jan 0.708 10 0 0.16
Feb 0.708 10.8 0 0.16
Mar 0.708 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 17.37 75 0.0004
RVLe 0.26 64 0.0004
UGR 4.98 77 0.0002
WAT 0 98 0
WET 25.87 78 0
COM 5.79 92 0
COMB 6.2 92 0
OFF 14.47 90 0
OFFe 0.01 87 0
RHH 26.88 79 0
RHHe 1.34 57 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 42.61 75 0
RMHe 10.26 69 0
RML 0 84 0
ROAD 6.12 89 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0
9-6

NC 43 Connector
ICI Water Quality Study
Neuse NoBld Trans.dat
7 16
0.14 0.005 10 0 0 0.215 17.4
0
0
0
0
0
Apr 0.566 12.8 1 0.28
May 0.566 13.7 1 0.28
Jun 0.566 14.2 1 0.28
Jul 0.566 14 1 0.28
Aug 0.566 13.2 1 0.28
Sep 0.566 12.2 1 0.28
Oct 0.566 11.2 1 0.28
Nov 0.566 10.2 0 0.16
Dec 0.566 9.8 0 0.16
Jan 0.566 10 0 0.16
Feb 0.566 10.8 0 0.16
Mar 0.566 11.8 0 0.16
FOR 0 75 0.00018
ROW 0 87 0.00258
RVL 0 88 0
RVLe 0 88 0
UGR 23.59 67 0.0002
WAT 178.56 98 0
WET 6.32 83 0
COM 143.97 94 0
COMB 81.42 94 0
OFF 22.59 92 0
OFFe 46.31 91 0
RHH 304.72 84 0
RHHe 99.05 80 0
RHHc 0 86 0
RLL 0.04 83 0
RLLe 0.03 83 0
RMH 3.72 83 0
RMHe 1.77 84 0
RML 0 84 0
ROAD 61.92 92 0
RVH 133.31 87 0
RVHe 39.08 83 0
RVHc 0 88 0
9-7

NC 43 Connector
ICI Water Quality Study
Rock NoBld Trans.dat
7 16
0.16 0.005 10 0 0 0.224 17.3
0
0
0
0
0
Apr 0.892 12.8 1 0.28
May 0.892 13.7 1 0.28
Jun 0.892 14.2 1 0.28
Jul 0.892 14 1 0.28
Aug 0.892 13.2 1 0.28
Sep 0.892 12.2 1 0.28
Oct 0.892 11.2 1 0.28
Nov 0.869 10.2 0 0.16
Dec 0.869 9.8 0 0.16
Jan 0.869 10 0 0.16
Feb 0.869 10.8 0 0.16
Mar 0.869 11.8 0 0.16
FOR 512.31 75 0.00003
ROW 30.64 87 0.00139
RVL 0 88 0
RVLe 0 88 0
UGR 29.08 79 0.0002
WAT 0 98 0
WET 0.3 83 0
COM 1.94 92 0
COMB 4.45 92 0
OFF 6.47 88 0
OFFe 5.57 88 0
RHH 11.66 86 0
RHHe 0 86 0
RHHc 0 86 0
RLL 0 81 0
RLLe 0 81 0
RMH 227.61 78 0
RMHe 58.72 66 0
RML 29.64 74 0
ROAD 14.69 88 0
RVH 0 88 0
RVHe 0 88 0
RVHc 0 88 0
9-8

NC 43 Connector
ICI Water Quality Study
UT NoBld Trans.dat
7 16
0.21 0.005 10 0 0 0.241 14.6
0
0
0
0
0
Apr 0.641 12.8 1 0.28
May 0.641 13.7 1 0.28
Jun 0.641 14.2 1 0.28
Jul 0.641 14 1 0.28
Aug 0.641 13.2 1 0.28
Sep 0.641 12.2 1 0.28
Oct 0.641 11.2 1 0.28
Nov 0.641 10.2 0 0.16
Dec 0.641 9.8 0 0.16
Jan 0.641 10 0 0.16
Feb 0.641 10.8 0 0.16
Mar 0.641 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 20.85 66 0.00017
WAT 18.08 98 0
WET 42.02 80 0
COM 37.45 93 0
COMB 25.77 93 0
OFF 1.68 92 0
OFFe 0.19 82 0
RHH 238.86 81 0
RHHe 106.11 62 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 68.57 83 0
RMHe 1.1 77 0
RML 0 84 0
ROAD 43.58 88 0
RVH 45.41 85 0
RVHe 19.02 82 0
RVHc 0 88 0
9-9

NC 43 Connector
ICI Water Quality Study
Wilson NoBld Trans.dat
7 16
0.14 0.005 10 0 0 0.212 15.7
0
0
0
0
0
Apr 0.566 12.8 1 0.28
May 0.566 13.7 1 0.28
Jun 0.566 14.2 1 0.28
Jul 0.566 14 1 0.28
Aug 0.566 13.2 1 0.28
Sep 0.566 12.2 1 0.28
Oct 0.566 11.2 1 0.28
Nov 0.566 10.2 0 0.16
Dec 0.566 9.8 0 0.16
Jan 0.566 10 0 0.16
Feb 0.566 10.8 0 0.16
Mar 0.566 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 136.14 79 0.00015
WAT 0.07 98 0
WET 8.35 78 0
COM 54.03 92 0
COMB 149.38 93 0
OFF 4.38 90 0
OFFe 73.5 91 0
RHH 281.65 83 0
RHHe 252.47 73 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 96.83 83 0'
RMHe 0 83 0
RML 0 84 0
ROAD 125.13 90 0
RVH 14.46 86 0
RVHe 11.69 80 0
RVHc 0 88 0
9-10

NC 43 Connector
ICI Water Quality Study
Caswell Bld Trans.dat
7 16
0.22 0.005 10 0 0 0.245 19
0
0
0
0
0
Apr 0.609 12.8 1 0.28
May 0.609 13.7 1 0.28
Jun 0.609 14.2 1 0.28
Jul 0.609 14 1 0.28
Aug 0.609 13.2 1 0.28
Sep 0.609 12.2 1 0.28
Oct 0.609 11.2 1 0.28
Nov 0.607 10.2 0 0.16
Dec 0.607 9.8 0 0.16
Jan 0.607 10 0 0.16
Feb 0.607 10.8 0 0.16
Mar 0.607 11.8 0 0.16
FOR 35.45 75 0.00006
ROW 1.7 87 0.00079
RVL 0 88 0
RVLe 0 88 0
UGR 115.44 82 0.0002
WAT 116.04 98 0
WET 0 98 0
COM 195.27 95 0
COMB 8.11 95 0
OFF 0.35 93 0
OFFe 0.02 93 0
RHH 0 86 0
RHHe 0 86 0
RHHc 0 86 0
RLL 10.29 81 0
RLLe 7.8 81 0
RMH 1.35 84 0
RMHe 1.55 84 0
RML 0 84 0
ROAD 11.82 93 0
RVH 97.69 88 0
RVHe 4.76 83 0
RVHC 0 88 0
9-11

NC 43 Connector
ICI Water Quality Study
Deep Bld Trans.dat
7 16
0.18 0.005 10 0 0 0.233 17
0
0
0
0
0
Apr 0.639 12.8 1 0.28
May 0.639 13.7 1 0.28
Jun 0.639 14.2 1 0.28
Jul 0.639 14 1 0.28
Aug 0.639 13.2 1 0.28
Sep 0.639 12.2 1 0.28
Oct 0.639 11.2 1 0.28
Nov 0.639 10.2 0 0.16
Dec 0.639 9.8 0 0.16
Jan 0.639 10 0 0.16
Feb 0.639 10.8 0 0.16
Mar 0.639 11.8 0 0.16
FOR 262.98 73 0.00002
ROW 0.4 85 0.00122
RVL 54.4 73 0.00008
RVLe 0.12 73 0.00008
UGR 8.92 80 0.00018
WAT 3.42 98 0
WET 6.67 83 0
COM 88.91 94 0
COMB 46.24 94 0
OFF 118.31 90 0
OFFe 3.33 90 0
RHH 143.79 82 0
RHHe 0 84 0
RHHc 0 86 0
RLL 0.07 83 0
RLLe 1.33 83 0
RMH 2.34 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 41.83 91 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0
9-12

NC 43 Connector
ICI Water Quality Study
Hayward Bld Trans.dat
7 16
0.63 0.005 10 0 0 0.318 12.9
0
0
0
0
0
Apr 0.654 12.8 1 0.28
May 0.654 13.7 1 0.28
Jun 0.654 14.2 1 0.28
Jul 0.654 14 1 0.28
Aug 0.654 13.2 1 0.28
Sep 0.654 12.2. 1 0.28
Oct 0.654 11.2 1 0.28
Nov 0.654 10.2 0 0.16
Dec 0.654 9.8 0 0.16
Jan 0.654 10 0 0.16
Feb 0.654 10.8 0 0.16
Mar 0.654 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 17.37 75 0.0004
RVLe 0.26 64 0.0004
UGR 4.98 77 0.0002
WAT 0 98 0
WET 25.87 78 0
COM 15.53 92 0
COMB 7.54 91 0
OFF 14.47 90 0
OFFe 0.01 87 0
RHH 57.2 79 0
RHHe 0 78 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 2.55 80 0
RMHe 10.26 69 0
RML 0 84 0
ROAD 6.12 89 0
RVH 0 87 0
RVHe 0 87 0
RVHC 0 88 0
9-13

NC 43 Connector
ICI Water Quality Study
Neuse Bld Trans.dat
7 16
0.14 0.005 10 0 0 0.215 17.4
0
0
0
0
0
Apr 0.504 12.8 1 0.28
May 0.504 13.7 1 0.28
Jun 0.504 14.2 1 0.28
Jul 0.504 14 1 0.28
Aug 0.504 13.2 1 0.28
Sep 0.504 12.2 1 0.28
Oct 0.504 11.2 1 0.28
Nov 0.504 10.2 0 0.16
Dec 0.504 9.8 0 0.16
Jan 0.504 10 0 0.16
Feb 0.504 10.8 0 0.16
Mar 0.504 11.8 0 0.16
FOR 0 75 0.00018
ROW 0 87 0.00258
RVL 0 88 0
RVLe 0 88 0
UGR 27.31 69 0.0002
WAT 178.56 98 0
WET 5.38 83 0
COM 150 95 0
COMB 81.12 94 0
OFF 145.73 92 0
OFFe 46.01 91 0
RHH 141.6 84 0
RHHe 99.05 80 0
RHHc 0 86 0
RLL 0.04 83 0
RLLe 0.03 83 0
RMH 3.72 83 0
RMHe 1.77 84 0
RML 0 84 0
ROAD 97.79 92 0
RVH 129.19 87 0
RVHe 39.08 83 0
RVHC 0 88 0
9-14

NC 43 Connector
ICI Water Quality Study
Rocky Bld Trans.dat
7 16
0.16 0.005 10 0 0 0.224 17.3
0
0
0
0
0
Apr 0.877 12.8 1 0.28
May 0.877 13.7 1 0.28
Jun 0.877 14.2 1 0.28
Jul 0.877 14 1 0.28
Aug 0.877 13.2 1 0.28
Sep 0.877 12.2 1 0.28
Oct 0.877 11.2 1 0.28
Nov 0.854 10.2 0 0.16
Dec 0.854 9.8 0 0.16
Jan 0.854 10 0 0.16
Feb 0.854 10.6 0 0.16
Mar 0.854 11.8 0 0.16
FOR 512.31 75 0.00003
ROW 30.64 87 0.00139
RVL 0 88 0
RVLe 0 88 0
UGR 29.08 79 0.0002
WAT 0 98 0
WET 0.3 83 0
COM 1.94 92 0
COMB 4.45 92 0
OFF 6.47 88 0
OFFe 5.57 88 0
RHH 226.26 81 0
RHHe 0 86 0
RHHc 0 86 0
RLL 0 81 0
RLLe 0 81 0
RMH 13.01 72 0
RMHe 58.72 66 0
RML 29.64 74 0
ROAD 14.69 88 0
RVH 0 88 0
RVHe 0 88 0
RVHc 0 88 0
9-15

NC 43 Connector
ICI Water Quality Study
UT Bld Trans.dat
7 16
0.21 0.005 10 0 0 0.241 14.6
0
0
0
0
0
Apr 0.614 12.8 1 0.28
May 0.614 13.7 1 0.28
Jun 0.614 14.2 1 0.28
Jul 0.614 14 1 0.28
Aug 0.614 13.2 1 0.28
Sep 0.614 12.2 1 0.28
Oct 0.614 11.2 1 . 0.28
Nov 0.614 10.2 0 0.16
Dec 0.614 9.8 0 0.16
Jan 0.614 10 0 0.16
Feb 0.614 10.8 0 0.16
Mar 0.614 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 20.85 66 0.00017
WAT 18.08 98 0
WET 41.04 80 0
COM 47.07 94 0
COMB 25.77 93 0
OFF 1.68 92 0
OFFe 0.19 82 0
RHH 284.66 82 0
RHHe 106.1 62 0
RHHC 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 0.17 80 0
RMHe 1.1 77 0
RML 0 84 0
ROAD 57.54 89 0
RVH 45.41 85 0
RVHe 19.02 82 0
RVHc 0 88 0
9-16

NC 43 Connector
ICI Water Quality Study
Wilson Bld Trans.dat
7 16
0.14 0.005 10 0 0 0.212 15.7 '
0
0
0
0
0
Apr 0.541 12.8 1 0.28
May 0.541 13.7 1 0.28
Jun 0.541 14.2 1 0.28
Jul 0.541 14 1 0.28
Aug 0.541 13.2 1 0.28
Sep 0.541 12.2 1 0.28
Oct 0.541 11.2 1 0.28
Nov 0.541 10.2 0 0.16
Dec 0.541 9.8 0 0.16
Jan 0.541 10 0 0.16
Feb 0.541 10.8 0 0.16
Mar 0.541 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 139.89 80 0.00017
WAT 0.07 98 0
WET 8.35 78 0
COM 88.61 93 0
COMB 149.38 93 0
OFF 4.38 90 0
OFFe 73.5 91 0
RHH 328 83 0
RHHe 252.47 73 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 0 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 137.28 91 0
RVH 14.46 86 0
RVHe 11.69 80 0
RVHc 0 88 0
9-17

NC 43 Connector
ICI Water Quality Study
Caswell Enh Trans.dat
7 16
0.22 0.005 10 0 0 0.245 19
0
0
0
0
0
Apr 0.609 12.8 1 0.28
May 0.609 13.7 1 0.28
Jun 0.609 14.2 1 0.28
Jul 0.609 14 1 0.28
Aug 0.609 13.2 1 0.28
Sep 0.609 12.2 1 0.28
Oct 0.609 11.2 1 0.28
Nov 0.607 10.2 0 0.16
Dec 0.607 9.8 0 0.16
Jan 0.607 10 0 0.16
Feb 0.607 10.8 0 0.16
Mar 0.607 11.8 0 0.16
FOR 35.45 75 0.00006
ROW 1.7 87 0.00079
RVL 0 88 0
RVLe 0 88 0
UGR 115.44 82 0.0002
WAT 116.04 98 0
WET 0 98 0
COM 195.27 95 0
COMB 8.11 95 0
OFF 0.35 93 0
OFFe 0.02 93 0
RHH 0 86 0
RHHe 0 86 0
RHHc 0 86 0
RLL 10.29 81 0
RLLe 7.8 81 0
RMH 1.35 84 0
RMHe 1.55 84 0
RML 0 84 0
ROAD 11.82 93 0
RVH 97.69 88 0
RVHe 4.76 83 0
RVHc 0 88 0
9-18

NC 43 Connector
ICI Water Quality Study
Deep Enh Trans.dat
7 16
0.18 0.005 10 0 0 0.233 17
0
0
0
0
0
Apr 0.645 12.8 1 0.28
May 0.645 13.7 1 0.28
Jun 0.645 14.2 1 0.28
Jul 0.645 14 1 0.28
Aug 0.645 13.2 1 0.28
Sep 0.645 12.2 1 0.28
Oct 0.645 11.2 1 0.28
Nov 0.644 10.2 0 0.16
Dec 0.644 9.8 0 0.16
Jan 0.644 10 0 0.16
Feb 0.644 10.8 0 0.16
Mar 0.644 11.8 0 0.16
FOR 261.86 73 0.00002
ROW 0.4 85 0.00122
RVL 54.4 73 0.00008
RVLe 0.12 73 0.00008
UGR 25.06 83 0.00014
WAT 3.42 98 0
WET 6.67 83 0
COM 88.91 94 0
COMB 46.24 94 0
OFF 118.31 90 0
OFFe 3.33 90 0
RHH 0 82 0
RHHe 0 84 0
RHHC 131.1 79 0
RLL 0.07 83 0
RLLe 1.33 83 0
RMH 0 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 41.83 91 0
RVH 0 87 0
RVHe 0 87 0
RVHC 0 88 0
9-19

NC 43 Connector
ICI Water Quality Study
Hayward Enh Trans.dat
7 16
0.63 0.005 10 0 0 0.318 12.9
0
0
0
0
0
Apr 0.668 12.8 1 0.28
May 0.668 13.7 1 0.28
Jun 0.668 14.2 1 0.28
Jul 0.668 14 1 0.28
Aug 0.668 13.2 1 0.28
Sep 0.668 12.2 1 0.28
Oct 0.668 11.2 1 0.28
Nov 0.668 10.2 0 0.16
Dec 0.668 9.8 0 0.16
Jan 0.668 10 0 0.16
Feb 0.668 10.8 0 0.16
Mar 0.668 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 17.37 75 0.0004
RVLe 0.26 64 0.0004
UGR 12.45 79 0.0001
WAT 0 98 0
WET 25.87 78 0
COM 15.53 92 0
COMB 7.54 91 0
OFF 14.47 90 0
OFFe 0.01 90 0
RHH 0 78 0
RHHe 0 78 0
RHHc 49.73 76 0
RLL 0 83 0
RLLe 0 83 0
RMH 2.55 80 0
RMHe 10.26 69 0
RML 0 84 0
ROAD 6.12 89 0
RVH 0 87 0
RVHe 0 87 0
RVHC 0 88 0
9-20

NC 43 Connector
ICI Water Quality Study
Neuse Enh Trans.dat
7 16
0.14 0.005 10 0 0 0.215 17.4
0
0
0
0
0
Apr 0.504 12.8 1 0.28
May 0.504 13.7 1 0.28
Jun 0.504 14.2 1 0.28
Jul 0,504 14 1 0.28
Aug 0.504 13.2 1 0.28
Sep 0.504 12.2 ' 1 0.28
Oct 0.504 11.2 1 0.28
Nov 0.504 10.2 0 0.16
Dec 0.504 9.8 0 0.16
Jan 0.504 10 0 0.16
Feb 0.504 10.8 0 0.16
Mar 0.504 11.8 0 0.16
FOR 0 75 0.00018
ROW 0 87 0.00258
RVL 0 88 0
RVLe 0 88 0
UGR 42.97 74 0.0002
WAT 178.56 98 0
WET 5.38 83 0
COM 143.47 95 0
COMB 80.74 94 0
OFF 137.95 92 0
OFFe 46.01 91 0
RHH 140.96 84 0
RHHe 99.05 80 0
RHHc 0 86 0
RLL 0.04 83 0
RLLe 0.03 83 0
RMH 3.72 83 0
RMHe 1.77 84 0
RML 0 84 0
ROAD 97.79 92 0
RVH 128.87 87 0
RVHe 39.08 83 0
RVHc 0 88 0
9-21

NC 43 Connector
ICI Water Quality Study
Rock Enh Trans.dat
7 16
0.16 0.005 10 0 0 0.224 17.3
0
0
0
0
0
Apr 0.878 12.8 1 0.28
May 0.878 13.7 1 0.28
Jun 0.878 14.2 1 0.28
Jul 0.878 14 1 0.28
Aug 0.878 13.2 1 0.28
Sep 0.878 12.2 1 0.28
Oct 0.878 11.2 1 0.28
Nov 0.855 10.2 0 0.16
Dec 0.855 9.8 0 0.16
Jan 0.855 10 0 0.16
Feb 0.855 10.8 0 0.16
Mar 0.855 11.8 0 0.16
FOR 512.31 75 0.00003
ROW 30.64 87 0.00139
RVL 0 88 0
RVLe 0 88 0
UGR 33.09 80 0.00018
WAT 0 98 0
WET 0.3 83 0
COM 1.94 92 0
COMB 4.45 92 0
OFF 6.47 88 0
OFFe 5.57 88 0
RHH 0 76 0
RHHe 0 76 0
RHHC 222.25 78 0
RLL 0 81 0
RLLe 0 81 0
RMH 13.01 72 0
RMHe 58.72 66 0
RML 29.64 74 0
ROAD 14.69 88 0
RVH 0 88 0
RVHe 0 88 0
RVHc 0 88 0
9-22

NC 43 Connector
ICI Water Quality Study
UT Enh Trans.dat
7 16
0.21 0.005 10 0 0 0.241 14.6
0
0
0
0
0
Apr 0.663 12.8 1 0.28
May 0.663 13.7 1 0.28
Jun 0.663 14.2 1 0.28
Jul 0.663 14 1 0.28
Aug 0.663 13.2 1 0.28
Sep 0.663 12.2 1 0.28
Oct 0.663 11.2 1 0.28
Nov 0.663 10.2 0 0.16
Dec 0.663 9.8 0 0.16
Jan 0.663 10 0 0.16
Feb 0.663 10.8 0 0.16
Mar 0.663 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 107.73 79 0.00008
WAT 18.08 98 0
WET 41.04 80 0
COM 34.82 93 0
COMB 25.77 93 0
OFF 1.68 92 0
OFFe 0.19 82 0
RHH 33.49 64 0
RHHe 106.1 62 0
RHHc 180.32 80 0
RLL 0 83 0
RLLe 0 83 0
RMH 0.15 80 0
RMHe 0.87 77 0
RML 0 84 0
ROAD 57.54 89 0
RVH 11.97 82 0
RVHe 17.04 82 0
RVHc 31.88 82 0
9-23

NC 43 Connector
ICI Water Quality Study
Wilson Enh Trans.dat
7 16
0.14 0.005 10 0 0 0.212 15.7
0
0
0
0
0
Apr 0.546 12.8 1 0.28
May 0.546 13.7 1 0.28
Jun 0.546 14.2 1 0.28
Jul 0.546 14 1 0.28
Aug 0.546 13.2 1 0.28
Sep 0.546 12.2 1 0.28
Oct 0.546 11.2 1 0.28
Nov 0.546 10.2 0 0.16
Dec 0.546 9.8 0 0.16
Jan 0.546 10 0 0.16
Feb 0.546 10.8 0 0.16
Mar 0.546 11.8 0 0.16
FOR 0 73 0.00002
ROW 0 85 0.00122
RVL 0 75 0.0004
RVLe 0 75 0.0004
UGR 157.51 80 0.00016
WAT 0.07 98 0
WET 8.35 78 0
COM 87.31 93 0
COMB 149.38 93 0
OFF 4.38 90 0
OFFe 73.5 91 0
RHH 27.3 77 0
RHHe 248.96 73 0
RHHc 288.57 80 0
RLL 0 83 0
RLLe 0 83 0
RMH 0 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 137.28 91 0
RVH 0.25 84 0
RVHe 11.69 80 0
RVHc 13.53 82 0
9-24

NC 43 Connector
ICI Water Quality Study
9.2 Land Use Scenarios
9-25

NC 43 Connector
ICI Water Quality Study
9-26

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ICI Water Quality Study
9.3 Runoff Volume Analysis
9-29

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NC 43 CONNECTOR UPDATED ICI ANALYSIS
Latest table provided by Colin:
Nc q3 Co n d ,-
Crawr- Ca.
2ooao9ju
2010 Analysis
Stantec 2006 Results
Neuse, SW, No Offsets
No Build Build
Neuse, SW, Max. Offset
No Build Build
Tiered Offset Only
No Build Build Build Enhanced
TN total load (Mg)
TP total load (Mg)
Sed total load (Mg)
403.3 410.9
85.7 87
5,266.6 5,084.1
439.3
85.7
5,266.6
450.6
87.1
5,084.1
285 297 288
61 63 59
3,680.0 3,620.0 3,380.0
Adjusted for simulation period (7 or 11 years)
TN total load (kg/ha/yr)
TP total load (kg/ha/yr)
Sed total Ioad (kg/ha/yr)
36.7
7.8
478.8
37.4
7.9
462.2
39.9
7.8
478.8
41.0
7.9
462.2
40.7
8.7
525.7
42.4
9.0
517.1
41.1
8.4
482.9
Are the new scenarios as effective as the Enhanced Build scenario?
Compare the new annual loadings to the Build Enhanced annual Loading rates to determine the
percent loading difference:
(kg/ha/yr)
No Offsets Allowed (best case)
Tiered Offests (closer to reality)
BE
N,SW,NO
%Change
BE
N,SW,TO
I %Change
TN
TP
Sed
41.1
8.4
482.9
37.4
7.9
462.2
( -9,89%
41.1
8.4
482.9
41
7.9
462.2
I -0.24%
-6.33%
1 _ -6.33%
r =�
1 -4.48%
r -4.48%
IT DEPENDS. If one considers the best case scenario, which does not include tiered offsets, then yes,
better reductions are expected. However, there is a precedence and history of being able to purchase
offset credits in the project area, and this will likely continue. As such, the ability to purchase offset
credits in the project area will likely continue. If so, and these are taken into consideration, then the
Build Enhanced scenario provides the greater protection. It should also be noted that the newer analysis
includes updated population information as well as updated data inputs. This makes it more difficult to
perform a straight analysis of the data. Therefore, consider the following in which the three no -build
scenarios are compared to their respective build scenarios:
(kg/ha/yr)
Stantec
No -Build
2006 Build
Stantec 2006 Build
No Build Build Enh.I%
Enhanced
2010 Neuse,
No -Build
SW, & No Offsets
2010 Neuse, SW, &
No -Build Build
Tiered Offsets
Build I%Change
Change
Build I%Change
I % Change
TN
TP
Sed
40.70
8.70
525.70
42.40 I 4.01%
40.70 41.10
8.70 8.40
525.70 482.90
0.97%
36.70
7.80
478.80
37.40
1.87%
39.90
7.80
478.80
41.00
7.90
462.20
2.68%
9.00 3.33%
-3.57%
7.90
1.27%
1.27%
517.101 -1.66%
I -8.86%
462.201
-3.59%
I
-3.59%
1

Total Nitrogen Loading
In the analysis above, all scenarios increase TN inputs; but the Build Enhanced scenario has the
least overall increase in inputs at 0.97%. The greatest TN increases are seen under the 2006 Build
scenario (4.01%), which isn't surprising, considering it includes only offset payments while the
other scenarios include other BMPs which would be expected to reduce overall loading.
Total PhosphorousLoadine
As with TN, the 2006 Build Scenario would contribute the largest anticipated increase in loading at
3.33%; overall, the greatest decrease would be seen under the Build Enhanced scenario, at a 3.57%
reduction. It should be noted that both of the 2010 analyses indicate that TP loads will increase
under both scenarios.
Sediment Loading
The same results are seen with sediment as with TN and TP. The 2006 Build scenario reflects the
least reduction in loading while the Build-Enhanced scenario shows the greatest reduction in
loading, with more than twice the reduction seen in either of the 2010 analyses.
Based on the last analysis above (and to some extend the prior analysis), it appears that neither of the
2010 scenarios will provide the same level of protection as the Build Enhanced scenario.
While seemingly not as effective as the Build Scenario, are the 2010 analyses sufficient enough to be
protective of surface waters?
It is assumed that the DWQ approved the 2006 analysis and determined it sufficient enough to
protect surface waters. While the overall reductions in TN, TP, and sediment are not as significant
percentage-wise over the No Build scenarios, the actual loading rates are less. For example, the TN
loading rate for the Build Enhanced scenario is 41.10 Mg/year; for the 2010 scenarios, the actual
anticipated loading rate is 37.40 Mg/yr and 41.00 Mg/yr. The same situation is also true with TP
(8.40 Mg/yr vs. 7.90 Mg/year) and with sediment (482.9 Mg/yr vs. 462.2 Mg/yr). Based on the 2010
analyses, the overall loading will be less over time, assuming that the Neuse Rules, the stormwater
rules, and nutrient offsets are administered appropriately and the rules are not relaxed in the
future. Even if maximum nutrient offsets are allowed, the overall loading rates are less than with
the Build Enhanced scenario.
A supplemental document provided to DOT by Baker Engineering and subsequently provided to the
DWQ indicates that the population data has been updated for the 2010 analysis. The document
states "...updated population forecasts from the NC Office of State Budget and Management
(September 2010) indicate that population in Craven County will be greater than those generated
in 2005 forecasts. The 2005-generated forecast of 2030 population in Craven County was 105,070.
The most recently available population forecast, however, shows a 2030 population of 116,835 in
Craven County. Therefore, the forecasted 2030 population of the study area is expected to be
higher than the 2005-generated forecast, resulting in more developed residential land use."

i
The statement indicates that between 2005 and 2010 the anticipated increase in population in
Craven County increased by 10.1 percent. This makes it extremely difficult to draw a comparison
between the 2006 analysis and the 2010 analysis. However, based on the new projections, it should
be assumed that the No Build numbers for the 2006 analysis should be higher than what has been
presented in the analysis results. How much so is unknown though. However, this may create
loading percentages that are less dramatic as those presented in the tables, and may, although
unknown, create percent reductions that are more in line with those of the 2010 analysis.
Another concern we had was about the built and non-built roads being/not being included in the
model. DOT has indicated that the recently completed section of the road was NOT included in the
No Build analysis as being completed. While not including it creates a scenario more equivalent to
the 2006 analysis, the road is already built and will not be removed, so not including does not
reflect reality. It was suggested by DOT that awork-around for including the road in the analysis is
to include the numbers from the Build scenario in the Neuse and from the No Build numbers in the
Wilson Creek and UT to Wilson Creek. Using this methodology, other Build/No Build scenarios can
be derived also. Based on DOT's suggestion, some scenarios may look like:
Existing Road is Built, But Not the southern section
Subwatershed Size (ha) TN (Mg) TP (Mg) sect (Mg)
Neuse (Build)
Wilson Cr. (NO Build)
UT to Wilson (NO Build) 1,152
1,205
669 126.4
135.9
50.5 23.5
24.9
11.4 1,187.8
1,635.2
480.9
Total: 3,029 312.8 59.8 3,303.9
Loading (kg/ha/yr): 9.39 1.79 99.16
None of the Road is Built
Subwatershed Size (ha) 7N (Mg) TP (Mg) sect (Mg)
Neuse (No Build)
Wilson Cr. (NO Build)
UT to Wilson (NO Build) 1,152
1,208
669 123.2
135.9
50.5 23.4
24.9
11.4 1,139.8
1,635.2
480.9
Total: 3,029 309.6 59.7 3,255.9
Loading (kg/ha/yr): 9.29 1.79 97.72
Both Sections of Road Are Built
sutrvvatershed Size (ha) TN (Mg) TP (Mg) Sed (Mg)
Neuse (Build)
Wilson Cr. (Build)
UT to Wilson (Build) 1,152
1,208
669 126.4
137.9
52.0 23.5
25.1
11.7 1,187.8
1,629.2
455.4
Tota I: 3,029 316.3 60.3 3,272.4
Loading (kg/ha/yr): 9.49 1.81 98.21
It should be kept in mind that this is not a true comparison, as there are certain assumptions that
have not been included, such as distribution of housing and commercials space (based on DOT
response to this question). The uncompleted road is not built in the No Build scenario, but is
included as built in the Build scenario. As shown above, the numbers can be teased to show what
loadings may be like if none of the road was constructed, as in the last comparison in the table.

This is a rather simplistic and nontechnical way of looking at the differences. To get a true measure
of the loadings, the model would need to be properly set up and run with all the appropriate
assumptions. The differences in the total loading numbers shown above are probably not overly
significant; in most cases differences amount to a few tenths of a kilogram (one-tenth kilogram is
0.22 pounds).
The Phase II TMDL for the Neuse River Estuary, which includes the New Bern and study area, calls
fora 30 percent reduction in from the 1991-1995 baseline total nitrogen loading. This reduction
is for point and non-point source, but not for natural sources. The information available on the
TMDL website does not include specific allocations, so it is unknown at this time specifically what
reductions should be expected from non-point sources due to development.
Just as a side item, all the tables and discussions provided by DOT discuss loading as either mg/ha
or kg/ha/yr. Based on mg/ha/yr and watershed area, actual or total loading would look like what is
presented on the table below. It is interesting to note that the reductions in nitrogen between the
Build and No Build scenarios are the same whether or not offsets are allowed. However, the
amount of loading is higher (around 10 percent or so) when offsets are allowed. The project area is
5,515 hectares, which is 13,628 acres or 21.29 square miles.
2030Analysiswith Neuse Rules, Stormwater, & N~ Offset Payments
Project area TN TN TN ~ TP TP ~ TP Sediment Sediment Sediment
Scenario (hectares) (kg/ha/yr) (kg/yr) , Qb/yr) ~ (kg/ha/yr) (kg/yr) ~ (Ib/yr) ~ (kg/ha/yr) (kg/yr) ~ (Ib/yr)
No Build 5,515 6.60 36,399.00 80,245.96 f 1.40 7,721.00 ,17,021.87 86.8 478,702.00 X1,055,356.00
Build 5,515 6.80 37,502.00 1 82,677.66 1.40 7,721.00 ;17,021.87 83.80 462,157.00 11,018,880.57
Difference Build/No BUild 0.20 1,103.00 I 2,431.70 j 0.00 0.00 i 0.00 -3.00 -16,545.00 I -36,475.44
2030Analysiswith Neuse Rules, Stormwater, & Tiered Offset Payments
Project Area TN TN i TN TP TP ~ TP Sediment Sedimem Sedimem
Scenario
(hectares)
(kg/ha/yr (kg/yr)
k /ha/yr
; (Ib/yr) (g (kg/yr) i (Ib/yr) (kg/ha/yr) (kg/yr) Qb/yr)
No Build 5,515 7.20 39,708.00 ( 87,541.05) 1.40 7,721.00 ,17,021.87; 86.80 478,702.00 1,055,356.00
Build 5,515 7.40 40,811.00 ) 89,972.75 1.40 7,721.00 :17,021.87. 83.80 462,157.00 (1,018,880.57
Difference Build/No Build 0.20 1,103.00 I 2,431.70 I 0.00 0.00 0.00 -3.00 -16,545.00 I -36,475.44

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Build Scenario
Similar to the No Build Scenario update, but with one exception, planned land use, zoning and the
expectations for growth and development patterns have not changed substantially since 2005. Thus, the
overall pattern of development in the Stantec Land Use model is reasonably accurate. The one major
exception is the recently proposed Craven 30 North development requested by Weyerhaeuser. The
proposed development would include retail, office, industrial and residential development mostly in the
northeast quadrant of the proposed US 70/NC 43 interchange. The current development plan, shown in
Figure 3, is still conceptual but the illustrative plan was provided by Weyerhaeuser to provide a basis for
updating the Build Scenario.
The illustrative plan was converted into the same land use categorized shown in Table I and the new
planned uses replaced the previously forecast uses from the Stantec land use forecast. This resulted in
approximately I50 fewer acres of Commercial and Office/Institutional/ Light Industrial uses and about
120 more acres of residential development. Also, about 40 acres of residential land use was increased in
density based on the Craven 30 North proposal. Overall, changes made to the Build Scenario to account
for the Craven 30 North proposal resulted in increases in the forecasted residential development and
decreases in the forecast non-residential development. ~
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Figure 3: Craven 30 North Conceptual Development Plan

In addition to updating the Build Scenario to include the Craven 30 North development, residential
density had to be increased to account for the increased population forecast outlined in the No Build
section. This update was accomplished by applying the No Build to Build percent increase in population
calculated in Table 2 from Stantec's forecast and applying the same growth factors to the new No Build
forecast in Table 3. The resulting Build Scenario population forecast is shown in Table 5.
Table 5: New Build Population Forecast
Population Percent Change
New Build Projections
2000 2010 2020 2030 2000-2010 2010-2020 2020-2030
Craven County 91,523 101,052 113,142 127,002 10.4% 12.0% 12.3%
New Bern 23,111 33,697 53,513 82,216 45.8% 58.8% 53.6%
Study Area 4,659 5,695 10,064 16,149 22.2% 76.7% 60.5%
Converting these population forecasts to household forecasts was accomplished by the same method
outlined for Table 4. The resulting household forecast, shown in Table 6, indicates that an additional 899
households, an 11.2% increase, will be required to accommodate the additional population.
Table 6: New Build Scenario Household Forecast

Household Type
% Persons Per
Household Stantec
2030 Build Baker 2030
Build
Difference
Difference
Single Person 32.4% 1.00 4,705 5,232 527 11.2%
Family 63.5% 2.98 3,095 3,441 346 . 11.2%
Other 4.1% 2.59 230 256 26 11.2%
Total 100.0% 8,030 8,929 899 11.2%
About one-third of the acreage required to meet this increase in households is accounted for in additional
acres and increased densities of residential development in the Craven 30 North plan. The remainder was
added to the Build Scenario by increasing residential densities along the eastern side of NC 43 south of
US 70. The resulting Build Land Use Scenario is shown in Figure 4.

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