20070932 Ver 1_Reports_20060227

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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
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FEBRUARY 2006
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FEB 2 7 2006
DENR - WATER QUALITY
WETLANDS AND STOR.MWAI ER BRANCH

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Prepared by.

Stantm
Stantec Consulting Services Inc
801 Jones Franklin Road, Suite 300
Raleigh, NC 27606
February 2006

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Table of Contents
Introduction 1-1
1 1 Transportation Project Overview 1-1
1 2 ICI Modeling Study Description 1-2
Existing Water Quality Conditions 2-1
21 Neuse River Basin Water Quality Initiatives 2-1
21 1 Neuse River NSW Management Strategy 2-1
21 2 Neuse River Estuary TMDL 2-1
21 3 Water Quality Improvement 2-2
22 Notable Features and Development Considerations 2-2
221 Water Resources 2-2
222 Wetlands 2-3
223 Groundwater Resources 2-3
224 Soils 2-4
225 Protected Species 2-4
226 Fishery Resources 2-4
227 Natural Areas 2-5
228 Infrastructure 2-5
229 Other Development Considerations 2-5
23 Stormwater Management 2-5
Watershed Modeling Approach 3-1
31 Objectives and Model Selection 3-1
32 The GWLF Model 3-2
321 Hydrology 3-2
322 Erosion and Sedimentation 3-3
323 Nutrient Loading 3-4
324 Input Data Requirements 3-4
GWLF Model Development 4-1
41 Delineation of Subwatersheds 4-1
42 Land Use Scenarios 4-1
421 Existing Land Use 4-1
422 No Build and Build Scenarios 4-3
423 Build-Enhanced Scenario 4-3
424 Scenario Comparisons 4-4
425 Model Imperviousness 4-9
43 Surface Water Hydrology 4-9
431 Precipitation 4-10
432 Evapotranspiration Cover Coefficients 4-10
433 Antecedent Soil Moisture Conditions 4-10
434 Runoff Curve Numbers 4-10
435 Curve Numbers for Cluster Development 4-11
44 Groundwater Hydrology 4-12
441 Recession Coefficient 4-12
442 Seepage Coefficient 4-12
443 Available Soil Water Capacity 4-13
444 Initial Saturated and Unsaturated Storage 4-14
45 Erosion and Sediment Transport 4-14
451 Soil Erodibility (K) Factor 4-14
452 Length-Slope (LS) Factor 4-14
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453 Cover (C) and Management Practice (P) Factors 4-14
454 Sediment Delivery Ratio 4-15
455 Sedimentation from Urban Land Uses 4-16
46 Nutrient Loading 4-16
461 Solid Phase Nutrients 4-16
462 Dissolved Groundwater Nutrients 4-16
463 Runoff Concentrations and Build-up Rates 4-16
47 Consideration of Existing Environmental Regulations 4-19
471 Neuse River Nutrient Sensitive Waters Management Rules 4-19
472 Coastal Stormwater Management Program 4-19
48 Model Implementation 4-20
GWLF Model Results and Discussion 5-1
51 Hydrology 5-1
52 Pollutant Loading 5-1
53 Verification of Model Results 5-6
531 Pollutant Loading Comparison 5-6
532 Streamflow Comparison 5-6
Stream Erosion Risk Analysis 6-1
61 Technical Approach 6-1
62 Results 6-2
Conclusions 7-1
References 8-1
Appendix 9-1
91 GWLF Model Inputs 9-1
91 1 Nutrient and Sediment Files 9-1
912 Transport Files 9-3
92 Land Use Scenarios 9-25
93 Runoff Volume Analysis 9-29
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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 Storm 6-2

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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 Seven-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 dust
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
(NCDWQ) 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 ICls 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

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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 from 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
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TN TIP Sediment x 10
Total Nitrogen (TN), Total Phosphorus (TP), and Sediment Loading in Metric Tonnes
Over the Seven-Year Model Simulation Period
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1 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 dust
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 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)

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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 fob 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
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ICI Water Quality Study
NC 43 Connector s

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Figure 1.1.1 Project Vicinity

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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 defined 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)
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Streams New Bem Major Roads Model Subwatersheds
Water Bodies
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Impaired Waters
ICI Project Area Railroads ?i Biologically Impaired
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Boundary Chlorophyll a
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Proposed NC 43 Connector (Alt F)
Trent Woods Low Dissolved Oxygen
Figure 1.2.1. Project Study Area
ICI Water Quality Study - NC 43 Connector

d TIP No. R-4463, Craven County, NC
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North Carolina
Department of Transportation
Craven Co unty
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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 Pfiestena piscic?da, 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 12 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 13 Water Quality Improvement
A declining trend in nitrogen is attributed to the implementation of the 1997 Neuse River
NSW Management Strategy outlined above (Harned, 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, fishing, 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
protect area are classified as SA waters, which are protected for shellfishing Portions of ,
the Trent River and Neuse River in the protect area are on the State's 303(d) list of
impaired waterbodies (NCDWQ 2004a)
2 2 2 Wetlands '
A majority of the protect 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 rock 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 a state-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 Sods
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

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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 virgirnca), bald eagle (Hahaeetus /eucocepha/us), leatherback sea turtle
(Dermochelys conacea), West Indian manatee (Tnchechus manatus), red-cockaded
woodpecker (Picoldes borealis), and American alligator (Alligator mississippiens?s)
(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 for Craven County There is
suitable habitat for several FSCs The project study area may also host a population of
black bear (Ursus amencanus)
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 saxatdis), 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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(Micropogonias undulatus), and menhaden (Brevoortia 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)

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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
mayor permit within twenty coastal counties including Craven The program also applies
to development draining to Outstanding Resource Waters (ORW) or High Quality Waters
(HQW)
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 (91-meter)
minimum setback from perennial waters and shorelines is also required
1 2-6
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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 (NCDWQ, 2005a)
' The BasinSim 1 0 version of GWLF was selected for this modeling analysis BasmSim
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 (Dal 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 Dal 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 use/cover 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
I Precipitation Evapotranspiration
Septic System Loads
Erosion
Land Surface - SCS Curve
Number Simulation
Unsaturated Zone
Shallow Saturated Zone
Deep Seepage
Loss
(USLE)
Particulate
ZVEW
Nutrients
?. Runoff
Dissolved Nutrients Loading to
Stream
Groundwater
(Shallow)
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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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 km2
(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 mayor roadways to make space
for commercial and industrial uses
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ICI Project Area Model Subwatersheds Figure 4 1 1 Model Subwatersheds
Proposed NC 43 Connector (Alt F) New Bern ICI Water Quality Study - NC 43 Connector
?i Streams New Bern ETJ TIP No R-4463 Craven County NC
Water Bodies River Bend
North Carolina
'dM
Roads Trent Woods .
Department of Transportation
/ Railroads
- Weather Stations County Boundary 0 1 2 Miles

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4 2 2 No Build and Build Scenanos
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 Commercial/Heavy
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 Scenano
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 mayor 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 a fifty-
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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line stream on the USGS 1 24,000 quad or in the Soil Survey of Craven County
therefore it is most likely a non-jurisdictional channel
4 2 4 Scenano Compansons
Commercial, industrial, institutional, and office land use increases by almost 400
hectares (7%) in the Budd 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 Budd-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* GWLF CODE PERCENT IMPERVIOUS
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 18
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 - Multifamily/Very High 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
4-4
NC 43 Connector
ICI Water Quality Study
V
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14,
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- Highwa

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71,
Trent River
Watershed Boundary Golf Course
ICI Project Area Green Space
. / Roads - Quarry Figure 4.2.1 No Build
Railroads - Commercial/Heavy Industrial Land Use Scenario
County Boundary ICI Water Quality Study NC 43 Connector
y ry Office/Institutional/Light Industrial Y-
' Streams Residential Very High Density TIP No. R-4463, Craven County, NC
Water Bodies Residential High Density North Carolina
- Wetland Residential Medium High Density ' Department of Transportation
- Forest - Residential Medium Low Density o o.s 1 Miles
Row Crop - Residential Low Density
- Residential Very Low Density
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Watershed Boundary Golf Course
ICI Project Area Green Space
• Access Points _ Quarry Figure 4.2.2 Build
Roads CommerciaVHeavy Industrial Land Use Scenario
Railroads Office/Institutional/Light Industrial ICI Water Quality Study - NC 43 Connector
' County Boundary Residential Very High Density TIP No. R-4463, Craven County, NC
Streams Residential High Density ? North Carolina
Water Bodies
Residential Medium High Density
Department of Transportation
s
`
- Wetland
Residential Medium Low Density
0.5 Miles
0
_ Forest
- Residential Low Density
Row Crop
_ Residential Very Low Density
NC 43 Connector
ICI Water Quality Study
2
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west y'964
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ICI Project Area Quarry
• Access Points Commercial/Heavy Industrial Figure 4.2.3 Build Enhanced
Roads - Office/Institutional/Light Industrial Land Use Scenario
j Railroads Residential Very High Density ICI Water Quality Study - NC 43 Connector
'. County Boundary Clustered Residential Very High Density TIP No. R-4463, Craven County, NC
Streams Residential High Density
Water Bodies North Carolina
Clustered Residential High Density R Department of Transportation
® Wetland Residential Medium High Density
_ Forest Residential Medium Low Density 0 0.5 Miles
Row Crop Residential Low Density
Golf Course Residential Very Low Density
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4.2.5 Model Imperviousness
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
u
INPUT BASELINE COMMENTS/
PARAMETER DESCRIPTION UNIT VALUE LITERATURE REFERENCE
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 for high Urban land uses:
intensity one 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 a ten-year
' period was not available, therefore a seven-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
t 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 soil 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
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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 C D GROUP B& D
Residential -
Very Low RVL 44 64 76 82 73
Density
Residential - RLL 47 66 77 83 75
Low Density
Residential -
Medium Low 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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ICI Water Quality Study
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 al, 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% for a 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 for a 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
INPUT BASELINE COMMENTS/
PARAMETER DESCRIPTION UNIT VALUE LITERATURE REFERENCE
RANGE
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 et al
coefficient Goal to (1992),
generate 2% Evans et al
deep seepage (2000)
overthe
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 162
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 Sod Water Capacity

E

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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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 Erodibdity (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 a buildup-washoff
formulation rather than the USLE

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Table 4.5 1 Rural Sediment Transport Input Parameters
INPUT BASELINE COMMENTS/
PARAMETER DESCRIPTION UNIT VALUE LITERATURE REFERENCE
RANGE
Rainfall Kinetic energy MJ- 0 16 (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 sods GIS data sods 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 C P
Residential - Very Low Density 00100 1 000
Barren Land 05000 1 000
Wetlands 00020 1 000
Forest 00020 1 000
Row Crop 00940 0 600
Urban Grass 00065 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 0212 to 0318
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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 BASELINE COMMENTS/
PARAMETER DESCRIPTION UNIT VALUE LITERATURE REFERENCE
REVIEW
Solid Phase Nutrient Loading
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
of20
Total mg/kg 352 Varies Haith et al
Phosphorous regionally and (1992)
Concentration by site, ,less Mills et al
than or equal to (1985)
400, multiplied
P2O5
conversion
factor and
enrichment ratio
(20)
Dissolved Nutrient in Groundwater
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) DISSOLVED P
(mg/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 0200 00065
Residential - Very Low Density 0 230 0 007
MASS BUILDUP RATES
URBAN LAND USES N BUILDUP (kg/ha/day) P BUILDUP (kg/ha/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 0201 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/ac/yr) 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, a fifty-foot buffer on all perennial and intermittent streams
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 Model Implementation
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 et al, 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
10
8
6
4
2
0
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 undeveloped 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).
Precipitation (cm)
Evapotranspiration (cm)
e- Subsurface Runoff (cm)
Surface Runoff (cm)
e Total Runoff (cm)
,A\ A
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Table 5.1.1 Seven-Year Total Nitrogen Loads (tonnes) for All Subwatersheds

No Build

_
Budd % Change
Over No
Budd
Enhanced
Budd % Change
Over No
Build
Caswell Branch 21 24 155% 24 155%
Deep Branch 34 36 75% 35 46%
Hayward Creek 7 7 92% 7 37%
Neuse River 73 76 42% 76 33%
Rocky Run 24 25 39% 24 04%
UT to Wilson Creek 34 35 30% 31 -103%
Wilson Creek 92 93 15% 91 -08%
Total 285 297 45% 288 11%
Table 5.1.2 Seven-Year Total Phosphorus Loads (tonnes) for All Subwatersheds

No Budd

_
Build % Change
Over No
Budd
Enhanced
Budd % Change
Over No
Budd
Caswell Branch 6 7 136% 7 136%
Deep Branch 7 8 84% 8 26%
Hayward Creek 2 2 93% 2 00%
Neuse River 16 17 23% 16 06%
Rocky Run 5 5 31% 5 -54%
UT to Wilson Creek 8 8 10% 6 -217%
Wilson Creek 17 17 03% 16 -51%
Total 80 84 37% 59 -28%
Table 5.1 3 Seven-Year Total Sediment Loads (tonnes) for All Subwatersheds

No Budd

_
Build % Change
Over No
Budd
Enhanced
Budd % Change
Over No
Build
Caswell Branch 300 218 -274% 218 -274%
Deep Branch 374 374 -01% 344 -81%
Hayward Creek 74 81 93% 71 -49%
Neuse River 966 910 -58% 903 -65%
Rocky Run 305 344 126% 314 27%
UT to Wilson Creek 466 488 46% 382 -18 1 %
Wilson Creek 1192 1210 15% 1147 -37%
Total 3678 3625 -15% 3378 -82%
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12
10
8
cu 6
rn
4
2
0
Figure 5.2.1 Mean Annual Total Nitrogen Loading Rates
3.5
3.0
2.5
>`. 2.0
CU
Y' 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
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250
¦ No Build
200 ¦ Build
¦ Enhanced Build
150
a
_Ile 100
50
0 4-AMENEEnt ,
Caswell
Figure 5.2.3 Mean Annual Sediment Loading Rates
500
450
400
350
CD 300
a)
c 250
0
~ 200
150
100
50
0
Wilson
Figure 5.2.4 Total Nitrogen (TN), Total Phosphorus (TP), and Sediment Loading Over
the Seven-Year Model Simulation Period
5-5
Deep Hayward Neuse Rocky UT to
Wilson
TN TP Sediment X 10

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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

0

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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 kmz and an average daily flow of 19 cubic feet per second or 0 54
cubic meters per second (m3/s), based on data from four years (1987-1990) This time
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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 m3/ha yields The 10-year average annual
yields from the seven subwatersheds (No Build Scenario) ranged from 5,224 to 7,997
m3/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
m3/ha/yr) Percent errors in annual mean values were calculated by the following
formula [(simulated - observed) / observed] x 100% (Zarnello, 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
Study Location Watershed Total N Total P Sediment
Land Use (kg/ha/yr) (kg/ha/yr) (kg/ha/yr)
Min Max Min Max Min Max
Current Inner Coastal Plain urban 33 98 07 19 42 127
Study NC
CH2M HILL Inner Coastal Plain
(2003)" NC rural 25 80 07 19 29 361
Tetra Tech Piedmont NC
(2003)- Jordan Lake mixed 18 269 03 28 -- --
Watershed
Tetra Tech Piedmont NC
(2004)- Morgan Creek mixed 37 161 03 19 -- --
Watershed
Coastal Plain and
RTI (1995)- Piedmont NC rural 16 2 7 0 1 0 3 25 355
Tar-Pamlico River
Basin
Compilation
of Literature

Export Various various 07 280 0 01 38
--
--
Coefficients --
- wvLF moaeiing Study
-- A compilation of literature export coefficients for nutrients was presented in both Line et al
(2002) and Tetra Tech (2003)

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6 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 a well-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 CND =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-02 *SU)2/(P+02 *Su)
Where Qu = Flow Volume contributed by Land Use Type U
P = rainfall
The total flow volume is then estimated with the equation
QTOTAL = FU (AU * QU)
Where QTOTAL = 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
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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
6.2 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 I
(1 acre-foot equals 1233 5 m3)

Subwatershed
No Build
Build % Change
Over No
Build Budd-
Enhanced % Change
Over No
Build
Caswell Branch 344,932 339,901 -1 5% 339,901 -1 5%
Deep Branch 325,748 325,570 -01% 317,861 -24%
Hayward Creek 61,275 64,734 56% 62,235 16%
Neuse River 621,392 624,045 04% 623,794 04%
Rocky Run 334,377 343,489 27% 331,781 -08%
UT to Wilson Creek 272,224 279,997 29% 267,166 -1 9%
Wilson Creek 579,476 581,716 04% 561,384 -31%
Total 2,539,423 2,559,451 08% 2,504,121 -14%

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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
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8 REFERENCES
Avery, M 2005 New Bern Department of Planning Personal communication December '
2005
Beaulac, M N and K H Reckhow 1982 An examination of land use and nutrient export
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Little River Reservoir Watersheds Report to the County of Durham, NC
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and Conservation Services Austin, TX
Chescheir, G M, M E Lebo, D M Amatya, J Hughes, J W Gilliam, R W Skaggs, and '
R B Hermann 2003 Hydrology and Water Quality of Forested Lands in Eastern
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CH2M HILL 2000 Urban Stormwater Pollutant Assessment Prepared for the North '
Carolina Department of Environment and Natural Resources, Division of Water
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CH2M HILL 2003 Pasquotank Basin Water Quality Model - GWLF Prepared for '
Decision Support Professionals (DSPRO) under contract with the NC DEHNR-
Ecosystem Enhancement Program by CH2M HILL September 2003
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Package, User's Guide Virginia Institute of Marine Science, College of William &
Mary, Gloucester Point, VA '
Dodd, R C and J P Tippett 1994 Nutrient Modeling and Management in the Tar-
Pamlico River Basin Prepared for N C Division of Environmental Management '
Research Triangle Institute, Research Triangle Park, NC

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' ICI Water Quality Study
Donigian, A S, Jr 2002 Watershed model calibration and validation The HSPF
' experience Water Environment Federation National TMDL Science and Policy
Conference Phoenix, Arizona November 13-16, 2002
I ESRI 2005 Hydrologic Modeling Tool ArcObjects Online ESRI Developer Network
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' Evans, R 0, J P Lilly, R W Skaggs, and J W Gilliam 2000 Rural Land Use, Water
Movement, and Coastal Water Quality NC Cooperative Extension Publication
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' Federal Highway Administration 1990 Pollutant Loadings and Impacts from Highway
Stormwater Runoff Volume III Analytical Investigation and Research Report
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Quality, 20 717-724
' Giese, G L, Eimers, J L, and Coble, R W, 1997, Simulation of ground-water flow in the
Coastal Plain aquifer system of North Carolina, in Regional Aquifer-System
' Analysis-Northern Atlantic Coastal Plain U S Geological Survey Professional
Paper
' Greensboro 2003 Storm Event Monitoring Summary Report, 1995-1999 City of
Greensboro, North Carolina
' Haith, D A, R Mandel, and R S Wu 1992 GWLF, Generalized Watershed Loading
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' Haith, D A and L L Shoemaker 1987 Generalized watershed loading functions for
stream flow nutrients Water Resources Bulletin, 23(3) 471-478
Harned, D A 2003 Water Quality Trends in the Neuse River Basin, North Carolina
1974-2003 Transactions of the American Geophysical Union 2003, Eos, Fall
Meeting Supplement, Abstract H41 F-1048, vol 84, no 46, p F703
' Hartigan, J P , T F Quasebarth, and E Southerland 1983 Calibration of NPS model
loading factors Journal of Environmental Engineering, 109(6) 1259-1272
' HDR Engineering, Inc of the Carolinas 2001 City of New Bern, North Carolina -
Stormwater Management Manual April 10, 2001
' Kuo, C Y, K A Cave, and G V Loganathan 1988 Planning of urban best management
practices Water Resources Bulletin 24(1) 125-132
' Lee, K, T R Fisher, Jordan, T E, Correll, D L, and Weller, D E 1999 Modeling the
hydrochemistry of the Choptank River basin using GWLF and Arc/Info 1 Model
validation and application Blogeochemistry, 49 143-173
1
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LeGrand, Harry E 1960 Geology and Groundwater Resources of the Wilmington-New
Bern Area NC Department of Water Resources Division of Groundwater '
Raleigh, NC
Line, D E, N M White, D L Osmond, G D Jennings, and C B Motonnier 2002 '
Pollutant export from various land uses in the Upper Neuse River Basin Water
Environment Research 74(1) 100-108
Lunetta, R S , R G Greene, and J G Lyon 2005 Modeling the Distribution of Diffuse '
Nitrogen Sources and Sinks in the Neuse River Basin of North Carolina, USA
Journal of the American Water Resources Association (JAWRA) 41(5) 1129- ,
1147
Meadows, D 2006 New Bern Public Works Personal communication January 2006
Mills, W B, D B Porcella, M J Ungs, S A Ghenni, K V Summers, L Mok, G L Rupp, ,
G L Bowie, and D A Haith 1985 Water Quality Assessment A Screening
Procedure for Toxic and Conventional Pollutants in Surface and Ground Water '
EPA/600/6-85/002 Environmental Research Laboratory, U S Environmental
Protection Agency, Athens, GA
Neitsch, S L, Arnold, J G Kiniry, J R, and J R Williams 2001 Soil and Water '
Assessment Tool Theoretical Documentation United States Department of
Agriculture - Agricultural Research Service - Grassland, Soil And Water '
Research Laboratory
New Bern, City of 2005 NC 43 Connector Proposed Development Plan ,
National Oceanic and Atmospheric Administration (NOAH) 2006 Alternatives for
Coastal Development http //www csc noaa gov/alternatives Accessed
1/11/2006
'
North Carolina Department of Transportation (NCDOT) 2001 Guidance for Assessing
Indirect and Cumulative Impacts of Transportation Projects in North Carolina '
Prepared by the Louis Berger Group, Inc Cary, NC
North Carolina Department of Transportation (NCDOT) 2005a NC 43 Connector From I
NC 55 to US 17 State Environmental Assessment
North Carolina Department of Transportation (NCDOT) 2005b NC 43 Connector '
Indirect and Cumulative Impact Assessment Prepared by Stantec Consulting
North Carolina Department of Transportation (NCDOT) 2005c Draft Second Bridge to
Oak Island Water Quality Study Report Prepared by Stantec Consulting '
North Carolina Department of Transportation (NCDOT) 2005b Contour and elevation
data generated from Light Detection And Ranging (LIDAR) data obtained from '
the North Carolina Flood Mapping Program
http //www ncdot org/planning/tpb/gis/DataDist/GISContourMags html
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' ICI Water Quality Study
North Carolina Division of Coastal Management (NCDCM) 1999 Wetland Types,
' Division of Coastal Management, Coastal NC GIS data June 1999
North Carolina Division of Marine Fisheries (NCDMF) 2003 Fishery Resources in the
NC 43 Connector Project Vicinity Personal communication with Mike Marshall
' on February 28, 2003 NC Department of Environment and Natural Resources
North Carolina Division of Water Quality (NCDWQ) 1999 Neuse River Basin Model
' Stormwater Program for Nitrogen Control Prepared by NC DEHNR-Division of
Water Quality Raleigh, NC August 1999
' North Carolina Division of Water Quality (NCDWQ) 2000 Fact Sheet Estuarine Fish
Kills in North Carolina Raleigh, NC August 2000
' North Carolina Division of Water Quality (NCDWQ) 2001 Phase II of the Total
Maximum Daily Load for Total Nitrogen to the Neuse River Estuary, North
Carolina NC Department of Environment and Natural Resources, Division of
' Water Quality, Raleigh, NC December 2001
North Carolina Division of Water Quality (NCDWQ) 2002a Nonpomt Source
Management Program Neuse Nutrient Strategy (Effective February 10, 2002,
' accessed January 31, 2006)
http Hh2o enr state nc us/nps/Neuse NSW Rules htm
' North Carolina Division of Water Quality (NCDWQ) 2002b Neuse River Basinwide
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' Division of Water Quality, Water Quality Section, Raleigh, NC July 2002
North Carolina Division of Water Quality (NCDWQ) 2004a North Carolina Water Quality
Assessment and Impaired Waters List 2004 Integrated 305(b) and 303(d)
' Report NC Department of Environment and Natural Resources, Division of
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' North Carolina Division of Water Quality (NCDWQ) 2004b Neuse River Nutrient
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' North Carolina Division of Water Quality (NCDWQ) 2004c Annual Report of Fish Kill
Events, 2004 NC Department of Environment and Natural Resources, Division
' of Water Quality, Environmental Sciences Section, Raleigh, NC December 2004
North Carolina Division of Water Quality (NCDWQ) 2005a B Everett Jordan Reservoir
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' Draft April 2005 NC Department of Environment and Natural Resources,
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' North Carolina Division of Water Quality (NCDWQ) 2005b Updated Draft Manual of
Stormwater Best Management Practices NC Department of Environment and
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North Carolina Division of Water Quality (NCDWQ) 2005c Best Usage Classifications
for North Carolina Waterbodies, Craven County - Updated September 30, 2005
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1/30/2006)
http //h2o enr state nc us/su/Neuse NSW Management Strategy htm
Randall, M 2005 NC Division of Water Quality, Planning Section Electronic
communication December 22, 2005
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Schueler, T R and H K Holland 2000 First Flush of Stormwater Pollutants in Texas
The Practice of Watershed Protection Watershed Protection Techniques
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Drainage Basin, North Carolina and Virginia, 1992-95 USGS Circular 1157
Stow, C E, M E Borsuk, D W Stanley 2001 Long-term Changes in Watershed Nutrient
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' ICI Water Quality Study
Swaney, D P , D Sherman, and R W Howarth 1996 Modeling water, sediment and
' organic carbon discharges in the Hudson-Mohawk Basin Coupling to terrestrial
sources Estuaries, 4 833-847
Tetra Tech 2000 Watershed Characterization System, Version 1 1 Prepared for U S
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' Tetra Tech 2003 B Everett Jordan lake TMDL Watershed Model Development
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November 2003
' Tetra Tech 2004 Morgan Creek Local Watershed Plan - Detailed Assessment Report
Prepared by Tetra Tech, Inc for NC DENR-Ecosystem Enhancement Program
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'
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'
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' Service Raleigh, North Carolina
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' United States Technical Paper No 40 Weather Bureau Washington, D C
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Nationwide Urban Runoff Program, Volume 1 Water Planning Division, USEPA,
' Washington, DC
United States Environmental Protection Agency (USEPA) 2001 PLOAD version 3 0, An
' ArcView GIS Tool to Calculate Nonpoint Sources of Pollution in Watershed and
Stormwater Projects U S Environmental Protection Agency, Washington, D C
I United States Environmental Protection Agency (USEPA) 2004 Superfund Home
Page http //www epa gov/superfund/index htm
' United States Environmental Protection Agency (USEPA) 2005 Section 319 Nonpomt
Source Program Success Story, North Carolina Basin-wide Cleanup Effort
Reduces Instream Nitrogen USEPA Office of Water, Washington, D C
' United States Fish & Wildlife Service (USFWS) 1994 National Wetland Inventory
(NWI) United States Department of the Interior, Washington, D C
http //www nwi fws gov/index html
' United States Fish & Wildlife Service (USFWS) 2006 Endangered Species, Threatened
Species, and Federal Species of Concern - Craven County United States
' Department of the Interior, Washington, D C (accessed January 9, 2006)
http Hnc-es fws gov/es/cntylist/craven html

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Wischmeier, W H and D D Smith 1978 Predicting Rainfall Erosion Losses A Guide to
Conservation Planning Agricultural Handbook 537 U S Department of I
Agriculture, Washington, DC
Zarnello, P J 1998 Comparison of nine uncalibrated runoff models to observed flows in
two small urban watersheds, in Proceedings of the First Federal Interagency
Hydrologic Modeling Conference, April 19-23, 1998, Las Vegas, NV
Subcommittee on Hydrology of the Interagency Advisory Committee on Water ,
Data, p 7-163 to 7-170

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9 APPENDIX
9.1 GWLF Model Inputs
1 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
02 00065
0 23 0 007
02 00065
0 0
0 19 0 006
0 055 00203
0 191 0 029
0 055 00203
0 158 0 025
0 063 0 026
0 219 0 037
0 063 0 026
0 061 0 026
0 214 0 037
00619 0 028
0 242 0 04
0 061 0 028
00515 00064
00532 00231
0201 0 033
00532 00231
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
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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 25 16 04
UrbanSed iment 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 25
0 04
0 22
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

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UrbanSed iment 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
12 25 16 04
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1 9 12 Transport Fdes

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Caswell NoBld Trans dat
7 16
0 22 0 005 10 0 0 0 245 19
0

0
0
0
Apr 0 736 128 1 0 28
May 0 736 137 1 0 28
Jun 0 736 142 1 0 28
Jul 0 736 14 1 0 28
Aug 0 736 132 1 0 28
Sep 0 736 122 1 0 28
Oct 0 736 112 1 0 28
Nov 0 734 102 0 0 16
Dec 0 734 98 0 0 16
Jan 0 734 10 0 0 16
Feb 0 734 108 0 0 16
Mar 0 734 11 8 0 0 16
FOR 3545 75 000006
ROW 1 7 87 000079
RVL 0 88 0
RVLe 0 88 0
UGR 115 44 82 00002
WAT 116 04 98 0
WET 0 98 0
1 9-3
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COM 57 73 95 0
COMe 811 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 78 81 0
RMH 135 84 0
RMHe 155 84 0
RML 0 84 0
ROAD 1182 93 0
RVH 9769 88 0
RVHe 4 76 83
--- 0
RVHc 0 i8
J o
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Dee NoB ld Trans dat
7 16
018 0 005 10 0 0 0 233 17

0
0
0
0
Apr 0 699 128 1 0 28
May 0 699 137 1 0 28
Jun 0 699 142 1 0 28
Jul 0 699 14 1 0 28
Aug 0 699 132 1 0 28
Sep 0 699 122 1 0 28
Oct 0 699 11 2 1 0 28
Nov 0 699 102 0 0 16
Dec 0 699 98 0 0 16
Jan 0 699 10 0 0 16
Feb 0 699 108 0 0 16
Mar 0 699 11 8 0 0 16
FOR 262 98 73 000002
ROW 04 85 000122
RVL 544 73 1 000008
RVLe 0 12 73 000008
UGR 8 92 80 000018
WAT 3 42 98 0
WET 6 67 83 0
COM 2124 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
RILL 0 07 83 0
RLLe 133 83 0
RMH 14819 80 0
RMHe 0 83 0
RML 0 84 0
ROAD 4183 91 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0
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Hayward NoBld Trans dat
7 16
063 0005 10 0 0 0318 129

0
0
0
0
Apr 0 708 128 1 0 28
May 0 708 137 1 0 28
Jun 0 708 142 1 0 28
Jul 0 708 14 1 0 28
Aug 0 708 132 1 0 28
Sep 0 708 122 1 0 28
Oct 0 708 112 1 0 28
Nov 0 708 102 0 0 16
Dec 0 708 98 0 0 16
Jan 0 708 10 0 0 16
Feb 0 708 108 0 0 16
Mar 0 708 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 17 37 75 1 00004
RVLe 0 26 64 00004
UGR 4 98 77 00002
WAT 0 98 0
WET 25 87 78 0
COM 5 79 92 0
COMe 62 92 0
OFF 14 47 90 0
OFFe 0 01 87 0
RHH 26 88 79 0
RHHe 134 57 0
RHHc 0 86 0
RILL 0 83 0
RLLe 0 83 0
RMH 42 61 75 0
RMHe 10 26 69 0
RML 0 84 0
ROAD 612 89 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0
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Neuse NoBld Trans dat
7 16
014 0005 10 0 0 0215 174

0
0
0
0
Apr 0 566 128 1 0 28
May 0 566 137 1 0 28
Jun 0 566 142 1 0 28
Jul 0 566 14 1 0 28
Aug 0 566 132 1 0 28
Sep 0 566 122 1 0 28
Oct 0 566 112 1 0 28
Nov 0 566 102 0 0 16
Dec 0 566 98 0 0 16
Jan 1 0 566 10 0 0 16
Feb 0 566 108 0 0 16
Mar 0 566 11 8 0 0 16
FOR 0 75 000018
ROW 0 87 000258
RVL 0 88 0
RVLe 0 88 0
UGR 23 59 67 00002
WAT 178 56 98 0
WET 6 32 83 0
COM 143 97 94 0
COMB 8142 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
RILL 0 04 83 0
RLLe 0 03 83 0
RMH 3 72 83 0
RMHe 177 84 0
RML 0 84 0
ROAD 6192 92 0
RVH 133 31 87 0
RVHe 39 08 83 0
RVHc 0 88 0
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Rock No Bld Trans dat
7 16
0 16 0 005 10 0 0 0 224 173

0
0
0
0
Apr 0 892 128 1 0 28
May 0 892 137 1 0 28
Jun 0 892 142 1 0 28
Jul 0 892 14 1 0 28
Aug 0 892 132 1 0 28
Sep 0 892 122 1 0 28
Oct 0 892 11 2 1 0 28
Nov 0 869 102 0 0 16
Dec 0 869 98 0 0 16
Jan 0 869 10 0 0 16
Feb 1 0 869 108 0 0 16
Mar 0 869 11 8 0 0 16
FOR 512 31 75 000003
ROW 30 64 87 000139
RVL 0 88 0
RVLe 0 88 0
UGR 29 08 79 00002
WAT 0 98 0
WET 03 83 0
COM 194 92 0
COMe 4 45 92 0
OFF 6 47 88 0
OFFe 5 57 88 0
RHH 1166 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

1

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UT NoBld Trans dat
7 16
021 0005 10 0 0 0241 146
0
0
0
0
0
Apr 0 641 128 1 0 28
May 0 641 137 1 0 28
Jun 0641 142 1 028
Jul 0 641 14 1 0 28
Aug 0 641 132 1 0 28
Sep 0 641 122 1 0 28
Oct 0 641 112 1 0 28
Nov 0 641 102 0 0 16
Dec 0 641 98 0 0 16
Jan 0 641 10 0 0 16
Feb 10 641 108 0 0 16
Mar 0 641 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 0 75 00004
RVLe 0 75 00004
UGR 2085 66 000017
WAT 18 08 98 0
WET 42 02 80 0
COM 3745 93 0
COMe 25 77 93 0
OFF 168 92 0
OFFe 019 82 0
RHH 238 86 81 0
RHHe 10611 62 0
RHHc 0 86 0
RLL 0 83 0
RLLe 0 83 0
RMH 68 57 83 0
RMHe 11 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
014 0005 10 0 0 0212 157

0
0
0
0
Apr 0 566 128 1 0 28
May 0 566 137 1 0 28
Jun 0 566 142 1 0 28
Jul 0 566 14 1 0 28
Aug 0 566 132 1 0 28
Sep 0 566 122 1 0 28
Oct 0 566 11 2 1 0 28
Nov 0 566 102 0 0 16
Dec 0 566 98 0 0 16
Jan 0 566 10 0 0 16
Feb 0 566 108 0 0 16
Mar 0 566 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 1 000122
RVL 0 75 00004
RVLe 0 75 00004
UGR 136 14 79 000015
WAT 0 07 98 0
WET 8 35 78 0
COM 54 03 92 0
COMe 149 38 93 0
OFF 4 38 90 0
OFFe 735 91 0
RHH 28165 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 12513 90 0
RVH 14 46 86 0
RVHe 1169 80 0
RVHc 0 88 0

1

1

9-10

u

t

1

NC 43 Connector
ICI Water Quality Study
Caswell B ld Trans dat
7 16
0 22 0 005 10 0 0 0 245 19

0
0
0
0
Apr 0 609 128 1 0 28
May 0 609 137 1 0 28
Jun 0 609 142 1 0 28
Jul 0 609 14 1 0 28
Aug 0 609 132 1 10 28
Sep 0 609 122 1 0 28
Oct 0 609 112 1 0 28
Nov 0 607 102 0 0 16
Dec 0 607 98 0 0 16
Jan 0 607 10 0 0 16
Feb 1 0 607 108 0 0 16
Mar 0 607 11 8 0 0 16
FOR 3545 75 000006
ROW 1 7 87 000079
RVL 0 88 0
RVLe 0 88 0
UGR 115 44 82 1 00002
WAT 116 04 98 0
WET 0 98 0
COM 195 27 95 0
COMB 811 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 78 81 0
RMH 135 84 0
RMHe 155 84 0
RML 0 84 0
ROAD 1182 93 0
RVH 9769 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
Apr 0 639 128 1 0 28
May 0 639 137 1 0 28
Jun 0 639 142 1 0 28
Jul 0 639 14 1 0 28
Aug 0 639 132 1 0 28
Sep 0 639 122 1 0 28
Oct 0 639 112 1 0 28
Nov 0 639 102 0 0 16
Dec 0 639 98 0 0 16
Jan 0 639 10 0 0 16
Feb 0 639 108 0 0 16
Mar 0 639 11 8 0 0 16
FOR 262 98 73 000002
ROW 04 85 000122
RVL 544 73 000008
RVLe 0 12 73 000008
UGR 8 92 80 000018
WAT 3 42 98 0
WET 6 67 83 0
COM 88 91 94 0
COMe 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 133 83 0
RMH 2 34 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 4183 91 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0

F -1
L

11

1
1

5
9-12

n
J

1
fl

1

NC 43 Connector
ICI Water Quality Study
Hayward B ld Trans da t
7 16
0 63 0 005 10 0 0 0 318 129
0
0
0
0
0
Apr 0 654 128 1 0 28
May 0 654 137 1 0 28
Jun 0 654 142 1 0 28
Jul 0 654 14 1 0 28
Aug 0 654 132 1 0 28
Sep 0 654 122 1 0 28
Oct 0 654 112 1 0 28
Nov 0 654 102 0 0 16
Dec 0 654 98 0 0 16
Jan 0 654 10 0 0 16
Feb 1 0 654 108 0 0 16
Mar 0 654 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 17 37 75 00004
RVLe 1 026 64 00004
UGR 4 98 77 00002
WAT 0 98 0
WET 25 87 78 0
COM 15 53 92 0
COMe 7 54 91 0
OFF 14 47 90 0
OFFe 0 01 87 0
RHH 572 79 0
RHHe 0 78 0
RHHc 0 86 0
RLL 0 83 0
RI-Le 0 83 0
RMH 2 55 80 0
RMHe 10 26 69 0
RML 0 84 0
ROAD 612 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
014 0005 10 0 0 0215 174

0
0
0
0
Apr 0 504 128 1 0 28
May 0 504 137 1 0 28
Jun 0 504 142 1 0 28
Jul 0 504 14 1 0 28
Aug 0 504 132 1 0 28
Sep 0 504 122 1 0 28
Oct 0 504 112 1 0 28
Nov 0 504 102 0 0 16
Dec 0 504 98 0 0 16
Jan 0 504 10 0 0 16
Feb 0 504 108 0 0 16
Mar 0 504 11 8 0 0 16
FOR 0 75 000018
ROW 0 87 000258
RVL 0 88 0
RVLe 0 88 0
UGR 27 31 69 00002
WAT 178 56 98 0
WET 5 38 83 0
COM 150 95 0
COMe 8112 94 0
OFF 145 73 92 0
OFFe 46 01 91 0
RHH 1416 84 0
RHHe 99 05 80 0
RHHc 0 86 0
RILL 0 04 83 0
RLLe 0 03 83 0
RMH 3 72 83 0
RMHe 177 84 0
RML 0 84 0
ROAD 97 79 92 0
RVH 12919 87 0
RVHe 39 08 83 0
RVHc 0 88 0

1

it

E

9-14

r -,

1
1

t
NC 43 Connector
ICI Water Quality Study
Rocky Bld Trans dat
7 16
0 16 0 005 10 0 0 0 224 173
0
0
0
0
0
Apr 0 877 128 1 0 28
May 0 877 137 1 0 28
Jun 0 877 142 1 0 28
Jul 0 877 14 1 0 28
Aug 0 877 132 1 0 28
Sep 0 877 122 1 0 28
Oct 0 877 112 1 0 28
Nov 0 854 102 0 0 16
Dec 0 854 98 0 0 16
Jan 0 854 10 0 0 16
Feb 1 0 854 108 0 1 0 16
Mar 0 854 11 8 0 0 16
FOR 512 31 75 000003
ROW 30 64 87 000139
RVL 0 88 0
RVLe 0 88 0
UGR 29 08 79 1 00002
WAT 0 98 0
WET 03 83 0
COM 194 92 0
COMe 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 2964 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
021 0005 10 0 0 0241 146
0
0
0
0
0
Apr 0 614 128 1 0 28
May 0 614 137 1 0 28
Jun 0614 142 1 028
Jul 0 614 14 1 0 28
Aug 0 614 132 1 0 28
Sep 0 614 122 1 0 28
Oct 0 614 112 1 0 28
Nov 0614 102 0 016
Dec 0 614 98 0 0 16
Jan 0 614 10 0 0 16
Feb 0 614 108 0 0 16
Mar 0 614 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 1 000122
RVL 0 75 00004
RVLe 0 75 00004
UGR 2085 66 000017
WAT 18 08 98 0
WET 4104 80 0
COM 47 07 94 0
COMe 25 77 93 0
OFF 168 92 0
OFFe 019 82 0
RHH 284 66 82 0
RHHe 1061 62 0
RHHc 0 86 0
RILL 0 83 0
RLLe 0 83 0
RMH 017 80 0
RMHe 11 77 0
RML 0 84 0
ROAD 57 54 89 0
RVH 45 41 85 0
RVHe 1902 82 0
RVHc 0 88 0
9-16

L

1

r-,
I??J

LI
1
?I

NC 43 Connector
ICI Water Quality Study
Wilson Bid Trans da t
7 16
014 0005 10 0 0 0212 157
0
0
0
0
0
Apr 0 541 128 1 0 28
May 0 541 137 1 0 28
Jun 0541 142 1 028
Jul 0 541 14 1 0 28
Aug 0 541 132 1 0 28
Sep 0 541 122 1 0 28
Oct 0 541 112 1 0 28
Nov 0 541 102 0 0 16
Dec 0 541 98 0 0 16
Jan 0 541 10 0 0 16
Feb 0 541 108 0 0 16
Mar 0 541 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 0 75 00004
RVLe 0 75 1 00004
UGR 139 89 80 000017
WAT 1 007 98 0
WET 8 35 78 0
COM 88 61 93 0
COMe 149 38 93 0
OFF 4 38 90 0
OFFe 735 91 0
RHH 328 83 0
RHHe 252 47 73 0
RHHc 0 86 0
RILL 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 1169 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 0 609 128 1 0 28
May 0 609 137 1 0 28
Jun 0 609 142 1 0 28
Jul 0 609 14 1 0 28
Aug 0 609 132 1 0 28
Sep 0 609 122 1 0 28
Oct 0 609 112 1 0 28
Nov 0 607 102 0 0 16
Dec 0 607 98 0 0 16
Jan 0 607 10 0 0 16
Feb 0 607 108 0 0 16
Mar 0 607 11 8 0 0 16
FOR 35 45 75 000006
ROW 1 7 87 000079
RVL 0 88 0
RVLe 0 88 0
UGR 115 44 82 00002
WAT 116 04 98 0
WET 0 98 0
COM 195 27 95 0
COMe 811 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 78 81 0
RMH 135 84 0
RMHe 155 84 0
RML 0 84 0
ROAD 1182 93 0
RVH 9769 88 0
RVHe 4 76 83 0
RVHc 0 88 0
9-18

1

n

r^
L

I!?

1
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 0 645 128 1 0 28
May 0 645 137 1 0 28
Jun 0645 142 1 028
Jul 0 645 14 1 0 28
Aug 0 645 132 1 0 28
Sep 0 645 122 1 0 28
Oct 0 645 112 1 0 28
Nov 0 644 102 0 0 16
Dec 0 644 98 0 0 16
Jan 0 644 10 0 0 16
Feb 0 644 108 0 0 16
Mar 0 644 11 8 0 0 16
FOR 261 86 73 000002
ROW 1 04 85 000122
RVL 544 73 000008
RVLe 0 12 73 000008
UGR 25 06 83 000014
WAT 3 42 98 0
WET 6 67 83 0
COM 88 91 94 0
COMe 46 24 94 0
OFF 118 31 90 0
OFFe 3 33 90 0
RHH 0 82 0
RHHe 0 84 0
RHHc 1311 79 0
RLL 0 07 83 0
RLLe 133 83 0
RMH 0 83 0
RMHe 0 83 0
RML 0 84 0
ROAD 4183 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
063 0005 10 0 0 0318 129
0
0
0
0
0
Apr 0 668 128 1 0 28
May 0 668 137 1 0 28
Jun 0 668 142 1 0 28
Jul 0 668 14 1 0 28
Aug 0 668 132 1 0 28
Sep 0 668 122 1 0 28
Oct 0 668 112 1 0 28
Nov 0 668 102 0 0 16
Dec 0 668 98 0 0 16
Jan 0 668 10 0 0 16
Feb 0 668 108 0 0 16
Mar 0 668 11 8 0 0 16
FOR 0 73 1 000002
ROW 0 85 000122
RVL 17 37 75 00004
RVLe 1 026 64 00004
UGR 12 45 79 00001
WAT 0 98 0
WET 25 87 78 0
COM 15 53 92 0
COMe 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
RILL 0 83 0
RLLe 0 83 0
RMH 2 55 80 0
RMHe 10 26 69 0
RML 0 84 0
ROAD 612 89 0
RVH 0 87 0
RVHe 0 87 0
RVHc 0 88 0

E
n
H

1

9-20
iJ
7-
L

L

NC 43 Connector
ICI Water Quality Study
Neuse Enh Trans dat
7 16
014 0005 10 0 0 0215 174
0
0
0
0
0
Apr 0 504 128 1 0 28
May 0 504 137 1 0 28
Jun 0 504 142 1 0 28
Jul 0 504 14 1 0 28
Aug 0 504 132 1 0 28
Sep 0 504 122 1 0 28
Oct 0 504 112 1 0 28
Nov 0 504 102 0 0 16
Dec 0 504 98 0 0 16
Jan 0 504 10 0 0 16
Feb 0 504 108 0 0 16
Mar 0 504 11 8 0 0 16
FOR 0 75 1 000018
ROW 0 87 000258
RVL 0 88 0
RVLe 0 88 0
UGR 42 97 74 00002
WAT 178 56 98 0
WET 5 38 83 0
COM 143 47 95 0
COMe 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 1 004 83 0
RLLe 0 03 83 0
RMH 3 72 83 0
RMHe 177 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 En h Trans dat
7 16
0 16 0 005 10 0 0 0 224 173

0
0
0
0
Apr 0 878 128 1 0 28
May 0 878 137 1 0 28
Jun 0 878 142 1 0 28
Jul 0 878 14 1 0 28
Aug 0 878 132 1 0 28
Sep 0 878 122 1 0 28
Oct 0 878 112 1 0 28
Nov 0 855 102 0 0 16
Dec 0 855 98 0 0 16
Jan 0 855 10 0 1 0 16
Feb 0 855 108 0 0 16
Mar 0 855 11 8 0 0 16
FOR 512 31 75 000003
ROW 30 64 87 1 000139
RVL 0 88 0
RVLe 0 88 0
UGR 33 09 80 000018
WAT 0 98 0
WET 03 83 0
COM 194 92 0
COMe 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 2964 74 0
ROAD 14 69 88 0
RVH 0 88 0
RVHe 0 88 0
RVHc 0 88 0

7

1

9-22

1

1
1

NC 43 Connector
ICI Water Quality Study
UT Enh Trans dat
7 16
021 0005 10 0 0 0241 146
0
0
0
0
0
Apr 0 663 128 1 0 28
May 0 663 137 1 0 28
Jun 0 663 142 1 0 28
Jul 0 663 14 1 0 28
Aug 0 663 132 1 0 28
Sep 0 663 122 1 0 28
Oct 0 663 112 1 0 28
Nov 0 663 102 0 0 16
Dec 0 663 98 0 0 16
Jan 0 663 10 0 0 16
Feb 1 0 663 108 0 0 16
Mar 0 663 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 0 75 1 00004
RVLe 0 75 00004
UGR 107 73 79 000008
WAT 18 08 98 0
WET 4104 80 0
COM 34 82 93 0
COMe 25 77 93 0
OFF 168 92 0
OFFe 019 82 0
RHH 3349 64 0
RHHe 1061 62 0
RHHc 180 32 80 0
RLL 0 83 0
RLLe 0 83 0
RMH 015 80 0
RMHe 0 87 77 0
RML 0 84 0
ROAD 57 54 89 0
RVH 1197 82 0
RVHe 17 04 82 0
RVHc 3188 82 0
9-23
NC 43 Connector
ICI Water Quality Study '
Wilson Enh Trans dat
7 16
014 0005 10 0 0 0212 157
0
0
0
0
0
Apr 0 546 128 1 0 28
May 0 546 137 1 0 28
Jun 0546 142 1 028
Jul 0 546 14 1 0 28
Aug 0 546 132 1 0 28
Sep 0 546 122 1 0 28
Oct 0 546 112 1 0 28
Nov 0 546 102 0 0 16
Dec 0 546 98 0 0 16
Jan 0 546 10 0 0 16
Feb 0 546 108 0 0 16
Mar 0 546 11 8 0 0 16
FOR 0 73 000002
ROW 0 85 000122
RVL 0 75 00004
RVLe 0 75 00004
UGR 157 51 80 1000016
WAT 0 07 98 0
WET 8 35 78 0
COM 87 31 93 0
COMe 149 38 93 0
OFF 4 38 90 0
OFFe 735 91 0
RHH 273 77 0
RHHe 248 96 73 0
RHHc 288 57 80 0
RILL 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 1169 80 0
RVHc 13 53 82 0
9-24
11

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NC 43 Connector
ICI Water Quality Study
9-25

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