20181598_ICE Report_20131125

HAVELOCK BYPASS
CRAVENCOUNTY, NORTH CAROLINA
TIP PROJECT NO. R-1015
INDIRECT AND CUMULATIVE IMPACT
WATER QUALITY STUDY REPORT
PREPARED FOR:
North Carolina Departmentof Transportation
Division of Highways
Project Development and Environmental Analysis Unit
September 2013

Prepared by:
Stantec Consulting Services Inc.
801 Jones Franklin Road, Suite 300
Raleigh, NC 27606

Havelock Bypass
ICI Water Quality Study
Table of Contents

Executive Summary..........................................................................................................v

1Introduction................................................................................................1-2

1.1Transportation Project Overview................................................................1-2

1.2ICI Modeling Study Background.................................................................1-2

2Water Resources.......................................................................................2-1

2.1Surface Water Resources in the Study Area..............................................2-1

2.2Impaired Waters.........................................................................................2-1

2.3Trends in Water Quality..............................................................................2-4

2.4Neuse River Basin Water Quality Initiatives...............................................2-5

2.4.1Neuse River NSW Management Strategy..................................................2-5

2.4.2Neuse River Estuary TMDL........................................................................2-6

3Development Considerations.....................................................................3-1

3.1Population and Market for Development....................................................3-1

3.2Land Availability.........................................................................................3-4

3.3Land Use Policies......................................................................................3-4

3.4Infrastructure..............................................................................................3-5

3.5Stormwater Management...........................................................................3-6

3.5.1Neuse River NSW Management Strategy..................................................3-6

3.5.2NC Session Law 2006-246 and NPDES Phase II.......................................3-7

3.5.3NC Session Law 2008-211 20 Coastal Counties Stormwater Law.............3-7

4Watershed Modeling Approach..................................................................4-1

4.1Objectives and Model Selection.................................................................4-1

4.2The GWLF-E Model...................................................................................4-1

4.2.1Hydrology...................................................................................................4-2

4.2.2Erosion and Sedimentation........................................................................4-3

4.2.3Nutrient Loading.........................................................................................4-3

4.2.4Fecal Coliform Loading..............................................................................4-3

4.2.5Input Data Requirements...........................................................................4-4

4.2.6Enhancements to the GWLF-E Model........................................................4-4

5GWLF-E Model Development.....................................................................5-1

5.1Delineation of Subbasins............................................................................5-1

5.2Land Use Scenarios...................................................................................5-1

5.2.1Existing Land Use......................................................................................5-2

5.2.2Future No-Build and Build Scenarios..........................................................5-5

5.2.3Scenario Comparisons...............................................................................5-6

5.2.4Model Imperviousness...............................................................................5-6

5.3Surface Water Hydrology...........................................................................5-8

5.3.1Precipitation...............................................................................................5-9

5.3.2Evapotranspiration Cover Coefficients.......................................................5-10

5.3.3Antecedent Soil Moisture Conditions..........................................................5-10

5.3.4Runoff Curve Numbers...............................................................................5-10

5.4Groundwater Hydrology.............................................................................5-10

5.4.1Recession Coefficient................................................................................5-10

5.4.2Seepage Coefficient...................................................................................5-11

5.4.3Unsaturated AvailableSoil Water Capacity................................................5-11

5.5Erosion and Sediment Transport................................................................5-12

5.5.1Soil Erodibility (K) Factor............................................................................5-12

5.5.2Slope-Length (LS) Factor...........................................................................5-12
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5.5.3Cover (C) and Management Practice (P) Factors.......................................5-12

5.5.4Sediment Delivery Ratio.............................................................................5-12

5.5.5Sedimentation from Urban Land Uses........................................................5-13

5.5.6Erosion from Streams.................................................................................5-14

5.6Nutrient Loading.........................................................................................5-14

5.6.1Nutrients in Soils........................................................................................5-14

5.6.2Dissolved Groundwater Nutrients...............................................................5-15

5.6.3Rural and Urban Land Use Loads..............................................................5-15

5.6.4Septic System Loading...............................................................................5-17

5.6.5Point Sources.............................................................................................5-18

5.6.6Animals......................................................................................................5-19

5.7Pathogen Loading......................................................................................5-19

5.7.1Urban Land Use Loads..............................................................................5-19

5.7.2Septic System Loading...............................................................................5-19

5.7.3Point Sources.............................................................................................5-20

5.7.4Animals......................................................................................................5-20

5.8Consideration of Existing Environmental Regulations................................5-20

5.8.1Neuse River Nutrient Sensitive Waters Management Rules.......................5-20

5.8.2Coastal Stormwater Management Rules....................................................5-21

5.9Model Implementation................................................................................5-22

6GWLF-E Model Results and Discussion.....................................................6-1

6.1Calibration..................................................................................................6-1

6.2Pollutant Loading Results...........................................................................6-3

6.3Nitrogen Loading tothe Neuse River Estuary.............................................6-11

6.4Verification of Model Results......................................................................6-11

7Stream Erosion Risk Analysis....................................................................7-1

7.1Technical Approach...................................................................................7-1

7.2Results.......................................................................................................7-2

8Conclusions...............................................................................................8-1

9References.................................................................................................9-1
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Tables

Table 2.2.1 Impaired Water Bodies in the Havelock ICI Study Area..................................2-2

Table 2.3.1 303(d) Listings of Water Bodies in the ICI Study Area, 2008 –2012...............2-5

Table 3.1.1 Population and Household Data, 2010 –2030................................................3-3

Table 3.2.1 Protected Land, ICI Study Area......................................................................3-4

Table 5.2.1 Land Use Categories and Density..................................................................5-1

Table 5.2.2 Existing Land Use/Land Cover Conversion Table...........................................5-3

Table 5.2.3 Estimates of Imperviousness from the Literature............................................5-7

Table 5.2.4 Land Use Categories and Estimated Imperviousness.....................................5-8

Table 5.3.1 Surface Water Hydrology Input Parameters....................................................5-9

Table 5.4.1 Groundwater Input Parameters.......................................................................5-11

Table 5.5.1 Rural Sediment Transport Input Parameters...................................................5-13

Table 5.5.2 Cover (C) and Management Practice (P) Factors...........................................5-13

Table 5.5.3 Sediment Mass Build-Up Rates......................................................................5-14

Table 5.6.1 Solid Phase and Groundwater Nutrient Loading Input Parameters.................5-15

Table 5.6.2 Nutrient Runoff Concentrations by Rural Land Use Category.........................5-16

Table 5.6.3 Nutrient Mass Build-up Rates by Urban Land Use Category...........................5-17

Table 5.6.4 Septic System Input Parameters....................................................................5-18

Table 5.8.1 Selected BMP Removal Efficiencies...............................................................5-21

Table 6.2.1 Mean Annual Pollutant Loads for All Subbasins..............................................6-7

Table 6.2.2 Mean Annual Pollutant Load Rates for All Subbasins.....................................6-9
Table 6.3.1 Project Study Area Nitrogen Loading as a Percentage of TMDL Nitrogen

Loading to the Neuse River Estuary...........................................................................6-11

Table 6.4.1 Comparison of Model Loading Rates to the Literature....................................6-13

Table 7.1.1 Selected Curve Numbers................................................................................7-2

Table 7.2.1 Storm Flow Volumes (cubic meters) for the One-Year, 24-Hour Storm...........7-3
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Figures& Exhibits

Exhibit 1.1.1 ICI Project Study Area and Vicinity Map........................................................1-4

Figure 2.2.1 Segments of the Neuse Estuary (NCDWQ 2009)..........................................2-3

Figure 3.1.1 City of Havelock Population Forecasts (Havelock, 2012)...............................3-2

Exhibit 3.2.1 Protected Lands............................................................................................3-9

Figure 4.2.1Schematic of GWLF-E Model Processes (taken from Dai et al., 2000).......4-2

Exhibit 5.1.1 Model Subbasins..........................................................................................5-23

Exhibit 5.2.1 Existing Land Use.........................................................................................5-25

Exhibit 5.2.2 Future Land Use No-Build Scenario..............................................................5-27

Exhibit 5.2.3 Future Land Use Build Scenario...................................................................5-29

Figure 6.1.1Mean Monthly Water Balance for Subbasin 3 (No-Build Scenario).............6-2

Figure 6.2.1Mean Annual Total Nitrogen Loads............................................................6-5

Figure 6.2.2Mean Annual Total Phosphorus Loads.......................................................6-5

Figure 6.2.3Mean Annual Sediment Loads...................................................................6-6

Figure 6.2.4Mean Annual Fecal Coliform Loads............................................................6-6

Exhibit 6.2.1 Increase in Nutrient Pollutant Loading Rates................................................6-15

Exhibit 6.2.2 Increase in Sediment and Fecal Coliform Pollutant Loading Rates...............6-17
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EXECUTIVE SUMMARY
The NCDOT proposes to construct a four-lane, median-divided roadway on new location
in thevicinity of the City of Havelock in Craven County, North Carolina. The project will
improve thecorridor capacity and incrementally step toward the Strategic Highway
Corridors Vision adopted bythe NC Board of Transportation in 2004. The length of the
project is 10.35miles. The project locationis shown in Exhibit 1.1.1. This transportation
improvement project is identified in the State Transportation Improvement Program
(STIP) as Project No. R-1015, with right-of-wayacquisitionanticipated to begin in FY
2014and constructionanticipated to begin in FY 2016(NCDOT, 2013).
An Indirect and Cumulative Effects (ICE)Analysis was completed in 2008 and was
updated in 2011to provide an assessment of the potential long-term, induced impacts of
the proposed project (HNTB, 2008 and NCDOT, 2011).This new study is a water quality
modeling analysis that has been conductedtoquantify the project’s potential indirect and
cumulative impacts (ICIs)on water resources. The focus of the analysis is on the
potential increases in stormwater runoff and non-pointsource loads of nitrogen,
phosphorus, sediment, and fecal coliformresulting from afuture development scenario
associated with the bypass.
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 non-pointsource pollutants. An additional
parameter, runoff from the one-year, 24-hour storm event, was evaluated using the SCS
Curve Number Method (SCS, 1986) to assess the potential risk of downstream channel
erosion.
Predictions from the modeling analyses indicatethat the potential for increase in
pollutant loads and stormflow over the entire watershed is low. This is due to a number
of factors including the use of stormwater controls to mitigate the effects of new
development and the low population growth and anticipated housing needs in the study
area.The bypasswill likely induce some development within the study area and
therefore some associated increases in pollutant loads to impaired waterbodies;
however, the increases suggested by the modeling analysis show very little increase
over the No-Buildscenario.
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1INTRODUCTION
1.1Transportation Project Overview
The North Carolina Department of Transportation (NCDOT) StateTransportation
Improvement Program (STIP) includes transportation improvements for the US 70
corridor in Craven County, North Carolina. This project is referred to as the Havelock
Bypass (STIP Project No. R-1015) and is proposed as a four-lane, divided roadway on
new location in the vicinity of the City of Havelock. The approximate length of the project
is 10.35miles on new location (Alternative 3). Exhibit 1.1.1 showsthe vicinity of the
proposed project.
The project begins approximately 3.5 miles northwest of the City of Havelock, with a
flyover interchangeat existing US 70. There is a proposed grade-separated interchange
at Lake Road. The project would end with another flyover interchangeat existing US 70,
south of the southern corporate limits of Havelock.
1.2ICI Modeling Study Background
An Indirect and Cumulative Effects(ICE) Assessment was developed to provide
comprehensive information on the potential long-term, induced impacts of the proposed
project (HNTB, 2008).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).
The ICE addressed three new location bypass alternatives. All three alternatives were
found to induce the same amount of growth potential andland use change given their
similar geographic location, equal level of access control, and same number of
interchanges. The study investigated two build scenarios. The Case 1 Build scenario
assumed a growth rate increase of 10% as a result of the bypass. The Case 2 Build
scenarioassumed a growth rate increase of 15%. Both growth rates were developed
based onresults from three previous studies that are most commonly cited for
estimating growth occurring as a result of transportation projects. The assumed rates of
10% and 15% were then presented toa focus group consisting of major property owners
such as Weyerhauser and the U.S. Forest Service, and local business and government
officials with market knowledge of growth and development trends within Craven County,
Carteret County, Havelock, Newport, and Cherry Point Marine Corps Air Station
(MCAS).The focus group concurred with the two assumed land use change
percentages.The study found that the increase in projected development in both Case 1
and Case 2 was relatively small in comparison to the No-Buildscenario.In general, the
ICE found that the potential for land use change associated with thebypass was ‘low’ to
‘moderate.’
In addition, the ICE included a hydrologic analysis model that compared peak discharge
rates and runoff volumes for the existing condition, No-Build scenario, Case 1 Build
scenario, and Case 2 Build scenario. The HEC-HMS model showed less than one
percent increase in peak discharge and runoff volumes between the No-Build and Build
scenarios. This difference was considered negligible. The hydrological analysis did not
include an analysis of impacts to water quality.
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An update to the ICE was completed by NCDOT in 2011, taking into account more
recent data and plans, and employing updated analysis processes utilizing NCDOT’s
ICE screening tool. The overall findings of the update varied slightly from the original
ICE, predicting that the potential for land use change associated with the bypass was
instead ‘moderate’ to ‘moderately-high.’No new modeling efforts (hydrologic or water
quality) were included in the 2011update.
The NCDOT contracted with Stantec to conduct watershed modeling to quantify the
project’s indirect and cumulative impacts (ICIs) on water resources. The focus of the
analysis is potential increases in stormwater runoff and non-pointsource loads of
nitrogen, phosphorous, sediment, and fecal coliform resulting from a future development
scenario associated with the roadway.For this study the future development scenario
that had been established in the previous two studies, was updated to reflect new
census data and information from the local jurisdictions(Sections 3.1, 3.2, and 5.2).
The study area for the ICI focused onan area in the Neuse River Basin, draining to the
Neuse River Estuary, in addition to crossing into the White Oak River Basin and draining
to the Newport River. This study area was based on the previously defined ICE study
area, and refinedand expandedto include the extent of14-digit hydrologic units (HUCs)
for watershed modeling purposes.TheICI study area was delineated into sixty-five
222
subbasinscovering 142 mi(367 km). Subbasins ranged in size from 1.0to 4.9 mi(2.6
2
to 12.7 km).The model study area contains portions of the following jurisdictions:
Havelock, Newport, Craven County, and Carteret County.
The Generalized Watershed Loading Function (Haith and Shoemaker, 1987; Haith et al.,
1992) model was selectedfor the purposesof simulating non-pointsource loads of
nitrogen, phosphorous,and sediment. 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 channel erosionresulting from increased storm volumes.
A particular focus in the analysis was the potential increase in predicted pollutant loads
to Slocum Creek, Sassafras Branch, Cherry Branch, and segments of the Neuse River
Estuary which have been designated as impaired bythe NC Department of Environment
and Natural Resources (NCDENR). These impairments are discussed in detail in
Section 2.2.
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Exhibit1.1.1 ICI Project Study Area and Vicinity Map
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2WATER RESOURCES
2.1Surface Water Resources in the Study Area
The ICI study area is located primarily within the Neuse River Basin8-digit HUC
03020204with the southern portion of the study area encompassingpart of the White
Oak River Basin 8-digit HUC 03020106. These areas include NCDWQ Subbasins 03-04-
10 and 03-05-03.Streams within the White Oak portion of the study area include
Ramhorn Branch, Little Run, Shoe Branch, Cypress Drain, and Deep Creek, which are
tributaries of the Newport River. All waters in the White Oak portion of the study area are
classified by NCDWQ as Class C waters. There are more than 50 named streams in the
Neuse portion of the study area. The main systems include East Prongof Slocum Creek,
Southwest Prong of Slocum Creek,Bice Creek, Otter Creek, Tucker Creek, Slocum
Creek, Hancock Creek, Gum Branch, Cherry Branch, King Creek, and Sassafras
Branch. These systems drain directly to the Neuse RiverEstuary. Theuse classifications
for waters within this portion of the study area include C Sw NSW, SA HQW NSW, SB
Sw NSW, and SC Sw NSW.
Class C waters are best suited for aquatic life survival and propagation, fishing, wildlife,
secondary recreation, and agriculture.Class SA waters are designated for use as
shellfishing waters. Class SB are salt waters best suited for primary recreational use,
while Class SC waters are salt waters best suited for aquatic life survival and
propagation, as well as secondary recreation. Streams in the Neuse portion of the study
area 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(Section2.4.1 and 3.5.1).
Swamp waters are designated as such due to their low velocities and other natural
characteristics that are different from adjacent streams.Streams designated as Class
SA waters are also classified as HQW –high quality waters. These waters have
protection rules which regulate activities such as development which may impact surface
water quality (NCDWQ,2013). There are no Outstanding Resource Waters (ORW),
Water Supply Watersheds (WSW), or Wild and Scenic Rivers within the ICI study area.
2.2Impaired Waters
NCDWQ maintains and updates a 303(d) list of impaired and threatened waters on a
biannual basis, as required by the Clean Water Act Section 303(d) and 40 CFR 130.7.
The most recent list was finalized in 2012(NCDWQ,2012).Sevenwaterbody segments
within the ICI study area have been listed on the 2012 303(d) list as Category 4 or 5
(impaired). These include Slocum Creek, Cherry Branch, Sassafras Branch, and four
segments of the Neuse River Estuary. A summary of these listings is presented in Table
2.2.1.Stressorsin the watershed include chlorophyll a, copper, high pH, and loss of
shellfish harvesting use. It should be noted that all waters in North Carolina are also
listed as impaired for mercury due to statewide fish consumption advisories for several
fish species.Refer to Figure2.2.1for the location of the impaired water body segments.
The segments of the Neuse Estuary (Middle, Bend, and Lower) refer to model segments
created for the development of a Total Maximum Daily Load (TMDL)model for the
estuary. This TMDL is discussed further in Section 2.4.2.
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Table 2.2.1ImpairedWater Bodies in the Havelock ICI Study Area
STREAM RIVER
1
NAMEDESCRIPTIONBASINSTRESSORCATEGORY
Slocum
CreekFrom source to Neuse RiverNeuseChlorophyll a5
Impaired for loss of
Cherry From source to Neuse River shellfish harvesting
Branch(1.20249724388123 S Miles)Neuseuse5
Impaired for loss of
Sassafras From source to Neuse River shellfish harvesting
Branch(1.11560964584351 S Miles)Neuseuse5
From a line across Neuse River from
Johnson Point to McCotter Point to a
Neuse
line across Neuse River from 1.2 miles
River NeuseCopper, High pH5
upstream of Slocum Creek to 0.5 miles
Estuary
upstream of Beard Creek (Middle
3
model segment)
From a line across Neuse River from
1.2 miles upstream of Slocum Creek to
Neuse
0.5 miles upstream of Beard Creek to a Chlorophyll a, High
2
River Neuse4t
line across Neuse River from Wilkinson pH
Estuary
Point to Cherry Point (Bend model
3
)
segment
From a line across Neuse River from
Neuse
Wilkinson Point to Cherry Point to a line
River NeuseCopper5
across the river From Adams Creek to
Estuary
Wiggins Point (part of Lower model
3
)
segment
Impaired for loss of
Neuse Prohibited area at Cherry Branch
Neuseshellfish harvesting 5
River Minnesott Ferry Landing south side of
use
Estuary river
1All watersin NC arealsolisted as impaired for Mercury due to statewide fish consumption advisories
for several fish species
2Category 4t indicates that a TMDL has been approved. A TMDL for total nitrogen was finalized in 2001
(NCDWQ,2001)
3The segments of the Neuse Estuary (Middle, Bend, and Lower) refer to model segments created for
the development of the total nitrogen TMDL model for the estuary
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Figure2.2.1Segmentsofthe Neuse Estuary (NCDWQ 2009)
Slocum Creek is located adjacent to the MCASCherry Point and flows into the Bend
segment of the Neuse Estuary. One ambient monitoring station is maintained on this
water body by NCDWQ. According to the latest Basinwide Water Quality Plan for the
Neuse River (NCDWQ, 2009), none of the parameters sampled at this site exhibited
violations of water quality standards; however, very high nutrient levels were detected,
indicating anthropogenic sources of both nitrogen and phosphorus. Slocum Creek drains
the most developed portions of the ICI study area, including MCAS Cherry Point and the
City of Havelock, with forest and some agricultural use in its headwaters.
Cherry Branch andSassafras Branch are small tributariesthatdrainto the Lower
segment of the NeuseEstuary in the northeastern portion of the ICI study area. Cherry
Branch’s watershed is primarily comprised of low and medium density residential
development, as well as smaller areas of wetland and forest.Sassafras Branch’s
watershed is a mix of low-density residential, agricultural, forested, and wetland land
uses. There are no NCDWQ ambient monitoring sites or biological sites located on
either Cherry Branch or SassafrasBranch.
The ICI study area drains to four segments of the Neuse Estuary. According to the 2009
Basinwide Water QualityPlan,there are 23 water quality monitoring stations located in
thesefour segments of the Neuse Estuary, which arelisted as impaired on the 2012
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303(d) list. Parameters sampled at these sites showed violations of water quality
standards for chlorophyll a, pH, and copper in addition to shellfish harvesting use
impairments. Refer to Table 2.3.1for a description of the existing impairments in each of
the four segments. Currently, only the Bend segment of the estuary is listed as impaired
for chlorophyll a.
2.3Trends in Water Quality
The latest Basinwide Water Quality Plan (NCDWQ,2009) and 303(d) listsfrom 2008 to
2012 were reviewed to assess water quality trends in the ICI study area. Table 2.3.1lists
the 303(d) listings of streams in the ICI study area from 2008 to the present. The 2009
Basinwide Water Quality Plan for the Neuse River assessed trends in water quality
between the 2006 and2008 303(d) lists. According to the Plan,the most significant
trend in water quality during this assessment period was that the chlorophyll a
impairment in the estuary had shifted downstream, closer to the Pamlico Sound.
According to the 2008 303(d) listings, this impairmentwas presentfrom the mid-Upper
estuary segment through the Bend segment. In 2008,there was also a new impairment
for pH from the Middle through the Bend segments of the estuary. As can be seen in
Table 2.3.1, chlorophyll aviolationshave declined, with the Middle and Lower segments,
as well as the area at Cherry Branch on the Neuse Estuary being delisted for chlorophyll
ain 2012. However, Slocum Creek was listed for chlorophyll ain 2010 and continues to
be listed as impaired in 2012. Cherry Branch and Sassafras Branch were listed as
impaired for loss of shellfish harvesting use from 2008 through 2012.
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Table 2.3.1 303(d) Listings of Water Bodies in the ICI Study Area, 2008 –2012
STREAM
NAMEDESCRIPTION201220102008
Slocum
CreekFrom source to Neuse RiverChlorophyll aChlorophyll a
Impaired for loss Impaired for loss Impaired for loss
Cherry From source to Neuse River of shellfish of shellfish of shellfish
Branch(1.20249724388123 S Miles)harvesting useharvesting useharvesting use
Impaired for loss Impaired for loss Impaired for loss
Sassafras From source to Neuse River of shellfish of shellfish of shellfish
Branch(1.11560964584351 S Miles)harvesting useharvesting useharvesting use
From a line across Neuse River
from Johnson Point to McCotter
Neuse
Point to a line across Neuse
River
River from 1.2 miles upstream
Estuary
of Slocum Creek to 0.5 miles
(Middle)
Chlorophyll a,Chlorophyll a,
upstream of Beard Creek
(Middle model segment)Copper, High pHCopper, High pHCopper, High pH
From a line across Neuse River
from 1.2 miles upstream of
Neuse
Slocum Creek to 0.5 miles
River
upstream of Beard Creek to a
Estuary
line across Neuse River from
(Bend)
Chlorophyll a,Chlorophyll a,Chlorophyll a,
Wilkinson Point to Cherry Point
(Bend model segment)High pHHigh pHHigh pH
From a line across Neuse River
Neuse from Wilkinson Point to Cherry
River Point to a line across the river
Estuary From Adams Creek to Wiggins
Chlorophyll a,Chlorophyll a,
(Lower)Point(part of Lower model
segment)CopperCopperCopper
Chlorophyll a,Chlorophyll a,
Neuse
Prohibited area at Cherry Impaired for loss Impaired for loss Impaired for loss
River
Branch Minnesott Ferry of shellfish of shellfish of shellfish
Estuary
Landing south side of riverharvesting useharvesting useharvesting use
2.4Neuse River Basin Water Quality Initiatives
Water quality in the Neuse River estuary has been a concern for overa century.
Nitrogen loading hadbeen 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 beendeclining. Elevated nutrient levels 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 aon North Carolina’s 303(d) list
in theearly to mid-1990’s.
2.4.1Neuse 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
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be a probable cause. Anumber of fish kills were also attributed to a dinoflagellate known
as Pfiesteria piscicida;thought to thrive in poor water quality situations (NCDWQ,
2002a). In 1997, the North Carolina Environmental Management Commission (EMC)
adopted a mandatory plan, the Neuse River Nutrient Sensitive Waters (NSW)
Management Strategy, to control both point and non-pointsources of pollution in the
Neuse River basin (NCDWQ, 2002b). With the exception of the riparian buffer rules,
these rules became effective in 1998. Thebuffer 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 tothe Neuse River Estuary by 30% from
1991-1995 baseline levels.
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). NCDWQ is responsible for administeringand enforcing
these rules.
2.4.2Neuse 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. 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 NCDWQ 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.A declining trend in nitrogen is attributed to the
implementation of the 1997 Neuse River NSW Management Strategy outlined above
(Harned, 2003).
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3DEVELOPMENT CONSIDERATIONS
The ICE analysis (HNTB,2008) included a focus group that helped apply constraint
values to a series of development constraints in the ICE study area. The values were
compiled using a GIS tool that resultedin a future development suitability map. In order
to determine potential development type, quantity, and location for the current study,
these constraints along with additional information were analyzed, updated when
necessaryto reflect new data,and applied to the larger ICI study area. The information
is divided into five sections discussed below: population and market demand, land
availability, land use policies, stormwater policies, and infrastructure thatmay affect
future development and pollutant loads.
3.1Population and Market for Development
Population based on the 2010 Census as well as projected population through 2030 was
calculated for the ICI study area. The 2010 Census data was not available when the ICE
and the ICE update werereleased. In addition, the current ICI study area is slightly
larger than the ICE study area and therefore includes additional population.
Existing population was calculated using census tractdata. The ICI study area
completely contains fivecensus tracts, and portions of an additional five tracts. For those
tracts only partially within the study area, population was determined using the number
of houses, calculated inGISand existing land use layers (Section 5.2.1), and the
average number of people per household in each of the two counties.
The Havelock Comprehensive Plan, published in 2009, contained an estimate of the
2010 population as well as projections through 2030. The 2010 estimate was based on
growth through 2005 and greatly exceeds the population that wascounted during the
2010 census. The 2030 projectionwasbased on a growth rate of 30.9% of the 2010
population. The City reevaluated its population projectionsin a 2011-2012 fiscal year
planning report(Havelock, 2012). The reevaluation cited additional studies,
demonstrating thatgrowth rates are much lower than had been anticipated. The report
included a graph of the different growth rates,including the 2030Comprehensive Plan
rate and annual rates of 0.3% and 1.5% (communities with healthy economies).Refer to
Figure 3.1.1.The growth rates includedin the Comprehensive Plan were significantly
higher than rates for “communities with healthy economies.”
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Figure3.1.1City of Havelock Population Forecasts (Havelock,2012)
The Office of StateBudget and Management publishes population projections by county
for North Carolina(NCOSBM,2013). The population growth ratepublished for Craven
County is an approximate annual rate of 0.83%,which falls between the suggested rates
cited by the City in the 2011/2012 report. Therefore, the state projection numbers were
chosen to determine the projected population of the ICI study area. According to the
Office of State Budget and Management, the percent increase expected in Craven and
Carteret Counties between 2010and 2030 is 16.7% (0.83% annually) and 29.3% (1.5%
annually), respectively.These rates were applied to theICI study area 2010Census
population to determine the projected No-Buildpopulation in 2030(Table 3.1.1).
The projections,along with average household size for each county,were then used to
determine the number of houses necessary to accommodate the growth in populationfor
the No-Buildscenario.This methodology was selected as a conservative method to
capture growth in the area based on population instead of using building permits which
reflect the volatility of the housing market. The ICE used building permits from 2000 to
2005 and other information to quantify future households. This method resulted in a high
growth rateas there was a building boom in the early 2000s. The rate drastically
declined in the latter half of the decade. The City of Havelock had an annual average of
96 building permits per year between 2000 and 2010. However, a City report notes that
the 7-yearaverage (2000-2006) was 123 permits per year while the 4-year average
(2007-2010) was only 21 permits per year (Havelock,2012).Similar decreases in
permits have occurred in Craven and Carteret Counties, although not as drastic as that
seen in Havelock. When looking over an extended time period of 20 years, basing
housing needs on increase in population reduces housing projection errors induced by
the effects of the volatilityof the housing market.
To determine the number of additional houses necessaryfor the Build scenario, a
percent increase was applied to the growth rate determined for the No-Buildscenario.
The ICE study (HNTB,2008) investigatedtwo growth scenarios: a10% and 15%
increase in the No-Buildgrowth rate. As discussed in Section 1.2, these rate increases
were developed based on three previous studies, as well as significant input from a
focus group consisting of local planners and developers. The higher growth rate
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increase of 15% was selected for thisICI study as it is the more conservative choice in
terms of determining impacts to water quality.
Additionally,future population attributed to MCAS Cherry Point was determined from
other documents and studies, as increases in military personnel would not be reflected
in population projections from the state. Similar to the other portions of the study area,
military populationprojections are based on past population estimates and growth rates.
According to the USMC F-35B East Coast Basing Final Environmental Impact Statement
and Record of Decision(Department of the Navy 2010), an alternative for the new
aircraft has been recordedthat will result in eight new squadrons at MCAS Cherry Point.
According to the document, this will result in a net gain of 1,194 personnel and 2,323
dependents. Assuming one household per military personnel, there would be an
increase of 1,194 households. Additionally, MCAS Cherry Point will not be expanding
housing on the base; therefore allof these additional households wouldbe housed off
base. Roughly half of the anticipated households (568)were added to the No-Buildand
Build scenarios to account for this population. This number was applied to both
scenarios as the increase in personnel is not dependent on the construction of the
bypass. A percentage of the total was used,as many military personnel live in New Bern
or in Carteret County and commute to the base. This trendis likely to continue.Applying
50% of military households to the ICI study area is a conservative estimate, as
population projectionsactually show significantlymore growth in other portions of
Craven County,as well as in Carteret County.
Table 3.1.1Population and Household Data, 2010 –2030
PPH 1 2010 2010 2030 No-2030 No-No-Build2030 2030 Build
PopHHBuildBuildChange Build Build Change
PopHHHHPopHHHH
Craven
County
(Total)2.45103,50540,229120,83747,373--
Carteret
County
(Total)2.2766,46928,87085,90637,433--
ICI Study
Area –
Craven2.4528,0299,31032,72211,2261,91633,42711,5132,203
ICI Study
Area –
Carteret2.272,9981,3213,8751,7073864,0061,765444
2
BRAC---3,5175685683,517568568
ICI Study
Area
Total
2,8703,215
31,58010,63140,11414,12740,95014,472
1–PPH = person per household
2–BRAC = estimated growth due to increase in military personnel and dependents
In order to determine No-Buildand Build non-residential future land use needs of the ICI
study area, an analysis of job growth was conducted based on a similar analysis in the
Havelock Land Use Plan (Havelock, 2009). First, pertinent data used in the Havelock
Land Use Plan including labor force statistics, number of housing units, unemployment,
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and jobs per household was updated using the 2010 Census data. The number of
additional jobs anticipated in the No-Buildand Build scenarios was calculated using
number of households for each scenario and the average jobs per household rate for the
two counties. The analysis included abreakdown of jobs by sector,a calculation of the
square footage needed per job,and the ratio of building size to property size.
3.2Land Availability
Areas available for development were calculated as ‘moderate’using the indirect land
use effects screening tool in the ICE Update (NCDOT,2011). However, the study area
contains a number of protected lands that surround a large portion of the proposed
roadwayleaving a limited amount of land available for development (Exhibit 3.2.1). The
land available for development is mainly located north and south of Havelock’s city
limits. In addition, there are scattered areas throughout the City of Havelock and
between the proposed bypass and the existing US Highway 70. Protected land includes
a portion of the Croatan National Forest (USFS), the Marine Corps Air Station Cherry
Point, and the Croatan Wetland Mitigation Bank (NCDOT). South of Long Lake and the
Croatan Mitigation Bank, there are three privately held areas: Camp Bryan, Camp
Brinson, and the Longstraw Wildlife Club. Although there are no conservation
easements or deeds for these areas, they are included in the conservation category in
the Craven County Future Land Use Plan (HCP 2009) and are considered not available
for development for this study.Protected lands and their acreage are presented in Table
3.2.1.
Table 3.2.1Protected Land, ICI Study Area
Protected LandsOwnerArea (acres)% of Watershed
Croatan National ForestUSFS37,86341.7%
Marine Corps Air Station Cherry PointDept. Navy11,59312.8%
Croatan Wetland Mitigation BankNCDOT4,1984.6%
Camp BryanPrivate8,1429.0%
Camp BrinsonPrivate1,0441.2%
LongstrawPrivate8220.9%
Total63,66270.1%
An additional 4,502 acres (5%) in the study area are water. Also, existing development
encompasses 10,408 acres (11.5%), leaving approximately 14,561 acres (16%) of the
watershed available for development. The area for development includes scattered
parcels available for infill in many of the existing neighborhoods,as well as large tracts
of landlocated along Lake Road and between the existing and proposed US 70Bypass.
There are also large tracts of land available south of the bypass near the county
boundaryand inthe Townof Newport. While the percent of the study area available for
development is low, itstill exceeds the calculated demand (Section 3.1).
3.3Land Use Policies
All of the jurisdictions within the ICI study area have a CAMA Land Use Plan (Craven
County 2009, Havelock 2009, Carteret County 2005, and Newport 2006). These plans
contain information on infrastructure, stormwater, land availability, and land suitability.
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Each plan includes a future land use map based on gathered information and land
suitability maps. Once approved, changes to the future land use mapsrequire approval
by the local jurisdiction as well as the Coastal Resources Commission.
In Havelock and Newport, zoning and ordinances provide additional support to the future
land use maps. While there may be some discrepancies and the land use map is usually
more general, the two shouldcoincide. The largest discrepancy between the Havelock
land use and zoning maps is the area surrounding the southern terminus of the
proposed bypass. In this area, the future land use map shows national forest whilethe
zoning map shows Highway Commercial. This was addressed in the ICE update which
stated that if a private developer was able to acquire USFS land, any proposed
development would likely be denied “due to its inconsistency with the Future Land Use
Map within the 2030 Comprehensive Plan.”Additionally, the ICE update stated thatif an
amendment was sought, approval would be needed from the City’s planning board,
commissioners and finally the Coastal Resources Commission (NCDOT, 2011).
Furthermore, discussions with the USFS for this ICI study indicate that land swaps in this
area are not common,as every acre of land in the vicinity of the proposed bypass is
dedicated to Red-cockaded Woodpecker recovery. In general,the USFS follows its land
management plan which includes a strategy for land adjustment (personal
communication Ms. RachellePowell, wildlife biologist, Croatan National Forest,
12/2012). According to this strategy there are a limited number of small parcels in the
Havelock area that USFS categorize as areas of “potential exchange” (USFS 2002).
None of these small parcels is located at the southern terminus of the proposed bypass
and therefore any exchange in this area is unlikely.
According to the Craven County Land Use Plan, the County was considering zoning for
the US 70 corridor between New Bern and Havelock. It is mentioned twice in the plan:a)
in the Citizens Participation Plan (part of the land use planning process),andb) as a
solution to preventing additional stormwater runoff/drainage problems in the corridor.
However, nothing has been adopted to date.
In Havelock’s Land Use Plan, the City states that a small area plan may be developed
for the proposed interchange at Lake Road in order to achieve a sustainable
development pattern. TheCity would like to see certain restrictions in place before
interchanges are constructed. Havelock has expanded their future land use map to
encompass the bypass and all of the interchanges, however current zoning does not
include the northern interchangeor the western side of the Lake Road interchange.
3.4Infrastructure
Public water service is generally available throughout the study area and is provided by
the various local jurisdictions.According to the Craven County CAMA Land Use Plan
(2009), the county “aggressively pursues the policy that central water service should be
provided to all areas of the County as funds become available.”The county will need to
andplans onexpandingthe capacity of the water supply system as needed in the
coming years. The City of Havelock provides water service within the city limits and to
portions of the extraterritorial jurisdiction (ETJ).According to Havelock’s CAMA Land
Use Plan (2009), the city will consider “costs and benefits for extending service into the
extra-territorial jurisdiction on a project-by-project basis.”
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The Town of Newport provides water service within the town limits and to some portions
of the ETJ. Newport will extend water services beyond its ETJ if the developer funds the
expansion and the land will be annexed. This includes expanding water lines through
conservation areas to serve new development. Carteret County currently has 15 facilities
that provide water to certain areas of the county. The County plans to provide water
service to areas classified on the future land use map as developed, limited transition,
and rural with services. The portion of the study area within Carteret County and outside
of the Newport ETJ is shown as rural (without services) and protected. Therefore it is
unlikely these areas will have water service in the future unless provided by the Town of
Newport.
Access to sewer service is currently limited to areas within the Havelock and Newport
city limits in addition to MCAS Cherry Point. The City of Havelock operates a wastewater
treatment plant with a capacity of 2.25 million gallons per day (MGD). MCAS Cherry
Pointis servedby a 3.5MGD capacity WWTP. Additionally, a package treatment plant
serves the Carolina Pines neighborhood located approximately 1.5 miles northof the
Havelockcity limits.Sewered areas within the study area servicedby the City of
Newport are servedby a WWTP which discharges outside of the ICI study area.
Portions of the northwest corner of the ICI study area are provided sewer service by the
City of New Bern thatis also servedby a WWTP thatdischarges outside of the study
area.
According to the Havelock 2030 Comprehensive Plan, the city was investigating means
to temporarily expand WWTP capacity by linking into the New Bern sewer system until
the planned expansion of the Havelock WWTP was completed. However, such planning
has since ceased as an immediate need for increased capacity has dissipated since the
recent economic downturn. Additionally, there are currently noplans to expand sewer
service outside of the Havelock city limits (personal communication, Mr. Bill Ebron,
Havelock Public Services Director).
Newport allows for the expansion of its sewer lines to portions of the ETJ as long as the
developer funds the cost of the extension. The town also plans to continue to develop its
wastewatertreatment system while exploring other means of treatment including the use
of on-site treatment in order to promote growth(Newport, 2006).
3.5Stormwater Management
3.5.1Neuse River NSW Management Strategy
The Neuse stormwater rules require the development of stormwater management plans
for fifteen local governments within the basin, including the City of Havelock. 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
rules require that each new development must meet a nitrogen export performance
standard with a provision for mitigation offset payments. The Neuse NSW stormwater
management program imposes a 4.0 kg/ha/yr (3.6 pounds per acre per year orlb/ac/yr)
nitrogen loading limit on new development. Nitrogen loadsfrom new developments that
exceed this performance standard may be offset by payment of a fee to the Wetlands
Restoration Fund provided, however, no new residential development can exceed6.7
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kg/ha/yr (6.0 lb/ac/yr) and no new nonresidential development can exceed 11.2 kg/ha/yr
(10.0 lb/ac/yr).
The rule also requires preservation of fifty-foot riparian buffers on perennial and
intermittent streams. Further, all new development must control water runoff so that
there is no net increase in the peak discharge from the predevelopment conditions for
the 1-year, 24-hour storm.
3.5.2NC Session Law 2006-246 and NPDES Phase II
Session Law 2006-246 was approved by the NC Legislature and signed into law in late
summer of 2006. The act provides for the implementation of the federal Phase II
stormwater program and additional stormwater management provisions.
Under the Phase II stormwater program,any new development that cumulatively
disturbs one acre or more of land located within the Phase II jurisdictionmust comply
with the standards set forth in Section 9 of Session Law 2006-246. Under Section 9,
programs are deemed compliant where the Neuse River NSW Management Strategy is
being implemented. For the study area, this includes the portions of MCAS Cherry Point
thatfall outside of the City of Havelock city limits.
3.5.3NC Session Law 2008-211 20 Coastal Counties Stormwater Law
Session Law 2008-211 was approved by the NC Legislature and signed into law in 2008.
The act provides for specific stormwater rules in the 20 coastal counties of the state.
Under this law, any development activity that requires a major permit or a Sediment &
Erosion Control Plan must comply with the standards set forth in Section 2.(b) of
Session Law 2008-211. These standards specify limits on impervious surface area, the
use of stormwater best management practices (BMPs), and the protection of vegetated
riparian buffers. For the study area, these rules apply to Craven County, outside of
Havelock, in addition to Carteret County and the Town of Newport. Additionally, rules
specific to areas within 1 mile of shellfish waters apply to a small section of the northeast
portion of the study area encompassing Cherry Branch, King Creek,and Sassafras
Branch. Impervious cover thresholds for triggering the stormwater rules are lower in
these shellfish areas.
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Exhibit 3.2.1 Protected Lands
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4WATERSHED MODELING APPROACH
4.1Objectives and Model Selection
The objective of this modeling analysis is to quantify the changes in long-termpollutant
loads resulting from potential land use changes induced within the project study area by
construction of the HavelockBypass. Two land use scenarios, the No-Build(no
construction of the Bypass) and Build (construction of the Bypass) Scenarios, were
developed for this study. The analysis will quantify changes in pollutant loads in the Build
scenariorelative to the No-Buildscenario.
The parameters of interest in this study are sediment, total nitrogen (TN), total
phosphorus (TP), fecal coliform bacteria (FC), 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, sediment, and fecal coliform
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 change in runoff volume between the No-BuildandBuild scenarios.
The Generalized Watershed Loading Function (GWLF) is a continuoussimulation 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
(USEPA, 2001a). 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 streamflow data wasnot 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; Stantec, 2005;Stantec, 2006) and was used for the watershed
modeling component of the Jordan Reservoir Nutrient TMDL (NCDWQ, 2005).
The MapShed 1.1.1version of GWLF was selected for this modeling analysis, called
GWLF-Enhanced (GWLF-E).MapShed is an updated user interface for the creation of
input data to the GWLF-E watershed model, developed by a team of researchers at
Pennsylvania State University. The updates consist of a GIS user interface and the
addition of software utilities to edit input and manage and display GWLF-Eresults.
GWLF-E model updates also incorporate RUNQUAL derived routines (Evans and
Corradini, 2012).Refer to Section 4.2.6for further information on theseRUNQUAL
routines.
4.2TheGWLF-EModel
This section provides an overview of the mathematical basis used in GWLF-E. The
discussion is a summary, largely drawn from the GWLFVersion 2.0 User Manual (Haith
et al., 1992)and MapShed Version 1.0 Users Guide (Evans and Corradini, 2012).Figure
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4.2.1is a schematic illustration of the structure of the GWLF-Emodel from Dai et al.
(2000).
GWLF-Eprovides the ability to simulaterunoff, sediment, nutrient (TN and TP) and
pathogen loading from a watershed given variable-size source areas (i.e., agricultural,
forested and developed landoverlaying varied soil mapunits). It alsohas algorithms for
calculating septic system loads, and allows for the inclusion of point source data.
The model uses a daily time stepfor 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 assumedto 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.
Figure 4.2.1Schematicof GWLF-EModel Processes (taken from Dai , 2000)
et al.
4.2.1Hydrology
GWLF-Eestimates 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
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snowmelt less runoff and evapotranspiration. The product of a cover factor dependent
on land use/cover type and potential evapotranspiration yieldsdaily 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.
4.2.2Erosion andSedimentation
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 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, isthen applied to estimate the sediment yield for each
source area.
Sediment loadsfrom urban land uses are simulated in Mapshed using exponential
accumulation and wash-off functions. Accumulation factors vary for the impervious
versus pervious fractions of land use types. Sediment accumulation factors used in this
study were derived from Haith et al.(1992) andKuo et al.(1988).Note that GWLF-Eand
the current study donot predict short term sedimentation from construction sites.
4.2.3Nutrient Loading
Surface nutrient losses are determined by applying dissolved nitrogen (N) and
phosphorus (P) coefficients to surface runoff from each rural 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; similar to sediment, the model
uses exponential accumulation and washoff functionsfor 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.
4.2.4Fecal Coliform Loading
In MapShed, there are routines that can be used to estimate pathogen loads originating
from various sources including, farm animals, wastewater treatment plants, urban
landscapes, septic systems, and wildlife loadings. By default, the pathogen simulated in
MapShed is assumed to be fecal coliform. Pathogen loads from farm animals follow
similar routines as those used for nutrients in manured areas. For wastewater treatment
plants, an assumed standard discharge concentration is applied to estimates of total
volume of effluent discharged by all point sources to derive total organisms released on
a monthly basis. Pathogen load estimates for urbanized areas are derived using event
mean concentrations (EMCs) and surface runoff from urban land uses.Loads from
septic systems are calculated using information on septic system populations and typical
per capita pathogen production rates. Wildlife pathogen loads are calculated based on
wildlife fecal coliform production rates, assumed wildlife densities per acre of natural
area, surface runoff, and fecal coliform die-off rate.
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4.2.5Input Data Requirements
For execution, the model requires inputs for transport, nutrient, and weather-related
data. The transport datadefines 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 data
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 dataconsists ofdaily minimum and maximumtemperature
and total precipitation values for each year simulated.
4.2.6Enhancements to the GWLF-EModel
In MapShed, the GWLF-Emodel has been revised to include a number of routines and
functions not found in the original model. This includes a streambank erosion routine
estimated using lateral erosion rates based on stream length in subbasins. New routines
have also been incorporated for more direct simulation of loads from farm animals and a
new pathogen load estimation routine. Additionally, new functions based on the
RUNQUAL model developed by Haith (1993) have beenincorporated. In contrast to the
original GWLF model, in the RUNQUAL functions, flows and loads are calculated from
both the pervious and impervious fractions associated witheach landuse/cover category
used. The pervious and impervious fractions of each landuse type are modeled
separately, and runoff and contaminant loads from the various surfaces are calculated
daily and aggregated to monthly outputs. Contaminated runoff may also be routed
through various urban BMPs in order to simulate reductions that may occur prior to
being discharged at the watershed outlet.
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5GWLF-EMODEL DEVELOPMENT
The following sections provide a discussion of the data sources, parameter inputs, and
assumptions utilized in this watershed modeling analysis.
5.1Delineation of Subbasins
22
The ICI study area was delineated into sixty-fivesubbasinscovering 142 mi(367 km).
A 10-meter (~30-foot) digital elevation model (DEM)(USGS, 2012)was used to develop
a preliminary delineation with the ArcHydro Tools 2.0, a hydrology modeling extension
developed for ArcGIS (ESRI, 2011). Fourteen-digit hydrologic unit code (HUC)
boundaries were ‘burned in’ to the subbasindelineation boundaries. Field
reconnaissance was conducted to identify man-made alterations to flow paths and
directions of drainage,refining the delineation. Final subbasin boundaries are presented
in Exhibit 5.1.1.
It should be noted that the original ArcHydro subbasin delineation resulted in 67
subbasins. The GWLF-E model produces less accurate results for subbasins less than 1
22
miin size. Two subbasins in the original delineation less than 1miwere therefore
aggregated into adjacent subbasins for model efficiency, resulting in 65 subbasins total.
The original subbasin numbers/labels were maintained;as such, theseaggregated
subbasin numbers/labels do not appear in tables and figures (Subbasins 57 and 60).
22
Final subbasins ranged in size from 1.0to 4.9 mi(2.6to 12.7 km).Further aggregation
of subbasins was not conducted in order to be able to evaluate model results on a more
detailed spatial scale.
5.2Land Use Scenarios
No-Buildand Build land use scenarios were developed using the categories presented in
Table 5.2.1.The scenarios were based on zoning,comprehensive plans, special
studies, and personal communication with various cityand county planners.
Table 5.2.1Land Use Categories and Density
Land Use NameGWLF CategoryDensity
Low Density ResidentialLow-Density Residential1-5 acres per d.u.
Residential -Medium DensityMedium-Density Residential0.1 -1 acres per d.u.
Residential -Multi-familyHigh-Density Residential<0.1 acres per d.u.
Office/Institutional/Light IndustrialMedium-Density MixedN/A
Commercial/Heavy IndustrialHigh-Density MixedN/A
Paved Road with Right of WayLow-Density MixedN/A
Golf CourseTurf/GolfN/A
Row CropCroplandN/A
PasturePasture/HayN/A
Disturbed/Non-vegetatedDisturbedN/A
Vacant/GrassOpenN/A
ForestForestN/A
WetlandsWetlandN/A
WaterWaterN/A
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5.2.1Existing Land Use
The watershed exhibits a wide range of existing land uses. The Croatan National Forest
and associated wilderness areas make up a large part of the southern and western
portions of the watershed. The majority of the Croatan National Forest is comprised of
forested wetlands. The City of Havelock and the MCAS Cherry Point make up the urban
development in the central portion of the watershed. Additional urban development
exists around Newport on the southern edge of the watershed and sporadically along US
Highway 70. Some residential subdivisions exist along the Neuse River. The remainder
of the watershed is primarily made up of forested land with limited agriculture including
row crops and a few horse farms.
Existing land uses within the watershed were classifiedbefore producing the No-Build
and Build land use scenarios. Existing developmentwas distinguished from future
development in the Build and No-Buildland use scenarios as their modeled loading
rates are different due to environmental regulations now in place that govern new
development in the study area(discussed further in Section 5.8). All land use datasets
(existing, Build and No-Build) were created asGIS data layers. Each GIS layer was
created as described below and in Section 5.2.2.
The existing land use was developed (Exhibit 5.2.1)based on a compilation of parcel
dataprovided by CravenandCarteretCounties, 2012 National Agriculture Imagery
Program (NAIP) aerial photography, and wetlands data from NC Division of Coastal
Management (NCDCM).Craven County parcel data included the City of Havelock while
Carteret County parcel data included the Town of Newport. In conjunction with aerial
photography, land use descriptions included within each County’s parcel datawere
assigned to each of the model categories (Table 5.2.1). Existing land uses for areas
within the MCAS Cherry Point were determined using 2012 aerial photography.
Craven and CarteretCounty parcel data was obtained from the each respective county
in 2012. The existing land use description within the parcel data included 72 different
land use codes for Craven County and 20 different codes in Carteret County. Each code
was categorized into one of 14 model categories. For more details refer to Table 5.2.1.
Parcels in both counties that fell into one of the many residential land use codes were
automatically classified as residential and broken into three density categories based on
parcel size. Low-Density Residential included residential parcels from 1 to 5 acres,
Medium-Density Residential were residential parcels from 0.1 to 0.99 acres while High-
Density Residential included residential parcels less than 0.1 acre and any multifamily
classifications. Residential parcels larger than five acres were evaluated using the 2012
aerial to determine and subsequently assign dominant land cover.
Non-residential developed areas were assigned to either Medium-Density Mixed Urban
or High-Density Mixed Urban based on land use classifications. Medium-Density
included office, institutional and light industrial areas while the High-Density category
included commercial and heavy industrial land use classifications. The Low-Density
Mixed Urban category was reserved for roads and their associated right of ways. The
runway at MCAS Cherry Point was also classified within the Low-Density category since
it was assumed it would have similar water quality inputs as the local roadways.
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Large forested tracts (Croatan National Forest, associated wilderness areas, and others)
were classified using the 2012 aerial. Areas designated as one of the various agricultural
classifications were evaluated using the aerial and assigned either Pasture, Cropland or
Open depending on the obvious presence or absence of livestock or row cropping.
Sports fields and golf courses were assigned to the Turf category as determined by the
aerial. Any areas that appeared as significant ground disturbance or classified as mining
(Craven County) were assigned to the Disturbed land use category.
The Neuse and White Oak NCDCM wetlands GIS layers were clipped to the watershed
and merged to create one wetlands file. It was determined that the wetland types
Drained, Human Impact, Non-Wetland and Managed Pine, when overlaid on the existing
land use, would not have an effect on the modeled loading rates;therefore,those
categories were deleted from the wetland file. The resulting file was then unioned with
the existing land use data. Where wetlands overlaid Forest and Open areas,those areas
were converted to a Wetland land use class. Where wetland overlaid Cropland,
Disturbed, all Mixed Urban, all Residential, Pasture, Turf and Water existing land use
was kept (not converted towetlands).
Table 5.2.2 Existing Land Use/Land Cover Conversion Table
CategoryCravenCarteretMCAS Cherry Point
WaterDetermined from 2012 aerialDetermined from 2012 aerialDetermined from 2012 aerial
Hay/PastureIncludes various parcels Includes variousparcels n/a
designated as 'Ag' or 'Vacant' designated as 'Agriculture'
and has obvious animal usage or 'Vacant' and has obvious
(as determined by 2012 aerial)animal usage (as
determined by 2012 aerial)
CroplandIncludes various parcels Includes various parcels Obvious row cropping (as
designated as 'Ag' or 'Vacant' designated as 'Agriculture,’determined by 2012 aerial)
and has obvious row cropping 'Horticultural' or 'Vacant'
(as determined by 2012 aerial)land and has obvious row
cropping (as determined by
2012 aerial)
ForestAreas currently forested, Areas currently forested, Digitized from 2012 aerial
appear to be regenerating appear to be regenerating
forests and other small forest forests and other small
stands (as determined by forest stands (as determined
2012 aerial). Railroad ROW by 2012 aerial). Railroad
was either called Forest or ROW and 'Common Area'
Open depending on dominant was either called Forest or
land cover.Open depending on
dominant land cover.
Disturbed'Industrial Mining (Rock/Sand)' Areas that appear as Areas that appear as significant
and other small areas that significant ground ground disturbance on 2012
appear as significant ground disturbance on 2012 aerialaerial
disturbance on 2012 aerial
TurfSports fields and golf courses Sports fields and golf Sports fields and golf courses
as determined using 2012 courses as determined as determined using 2012
aerialusing 2012 aerialaerial
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CategoryCravenCarteretMCAS Cherry Point
Open LandAreas of grass or minimal Areas of grass or minimal Areas of grass or minimal
development. Includes many development. Includes many development. Includes wide
'Vacant' parcels, wide utility 'Vacant' parcels, 'Cemetery,’utility easements, grassy areas
easements and other wide utility easements and around runways and other
undeveloped areas. Railroad other undeveloped areas. undeveloped areas. Railroad
ROW was either called Forest Railroad ROW and ROW was either called Forest
or Open depending on 'Common Area' was either or Open depending on
dominant land cover.called Forest or Open dominant land cover.
depending on dominant land
cover.
Low-Density 'Residential-One Family 'Residential',
ResidentialUnit', 'Res -Personal Prop 'Manufachomeperm,'1 acre. Estimated using 2012
MfgHome,’'Res-MFG Home 'Manufachomeperson' if aerial.
1 acre. If over 5
acre. If over 5 acres parcel acres parcel was assigned
was assigned predominant predominant land cover as
land cover as determined by determined by 2012 aerial.
2012 aerial.
Medium-'Residential -One Family 'Residential', Residential areas on parcels
Density Unit,’ 'Res -Personal Prop 'Manufachomeperm,’0.1-0.99 acres. Estimated using
ResidentialMfg Home,’'Res-MFG Home 'Manufachomeperson' if 2012 aerial.
as Real Prop' if parcel 0.1-parcel 0.1-0.99 acre
0.99 acre
High-Density 'Residential -One Family 'Residential,’ Residential areas on parcels
ResidentialUnit,’ 'Res -Personal Prop 'Manufachomeperm,’<0.1 acres and multifamily
Mfg Home,’'Res-MFG Home 'Manufachomeperson' ifareas
as Real Prop' if parcel < 0.1 parcel < 0.1 acre, (apartments/condominiums/tow
acre,’ 'Residential -Two 'Apartment,’'Condo,’'Mobile n houses). Estimated using
Family Unit,''Residential -Home Park,’Multi-Family 2-2012 aerial.
Three Family Unit,’'Comm-4'
Multifamily Apt > 3 Units,’
'Comm-Mobile Home Parks >
4 UNT,’'Comm-Condominium
Development'
Low-Density Roads and associated Right of Roads and associated Right MCAS Runway, roads and
Mixed UrbanWays from parcel data.of Ways from parcel data.associated Right of Ways as
determined using 2012 aerial.
Medium-Office/Institutional/Light Office/Institutional/Light Developed areas within MCAS
Density Industrial -includes churches, Industrial -includes that were neither residential nor
Mixed Urbanschools, utilities as well as churches, schools and high enough imperviousness to
'Comm-Bank,’'Comm-General 'Commercial' areas that qualify for High Density Mixed
Office Building,’'Comm-were not high enough Urban.
Private Owned Child Care,’imperviousness to qualify for
'Comm-Professional/Medical High Density Mixed Urban
Offc,’'Comm-Veterinarian
Clinic/Kennl'
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CategoryCravenCarteretMCAS Cherry Point
High-Density Commercial/Heavy Industrial -'Commercial' areas with high Development with high
Mixed Urbanincludes 'Comm-Automotive,’imperviousness (>70%)imperviousness (>70%);
'Comm-Commercial w/Res includes majority of MCAS
Use,’'Comm-Convience development near runways.
Store,’'Comm-Food Serv,’
'Comm-General Commercial
Use,’'Comm-Hotel,’'Comm-
LargeResional Stores,’
'Comm-Neighborhood Strip
Shops,’'Comm-Retail Shops,’
'Comm-Storage Units,’
'Comm-Storage/Distribution,’
'Comm-Dealer-Not Auto,’
'Comm-Diner,’'Comm-Park
Lot (Parking),’'Comm-Retail-
Lg Food Store,’'Comm-
Shopes Resional Centers,’
'Commercial,’'Rec-
Commerical Motion Picture,’
'Rec-Health Spa,’'Industrial'
WetlandNCDCM Wetlands layer. Removed Wetland Types 'Drained,’'Human Impact,’'Non-
Wetland,’and 'Managed Pine.' Wetland file unioned with Existing Land Use file. Where
wetland overlaid Cropland, Disturbed, all Mixed Urban, all Residential, Pasture, Turf and
Water existing landuse was kept (not converted to wetland). Where wetland overlaid Forest
and Open, those areas converted to Wetland Land Use Class.
5.2.2Future No-Buildand Build Scenarios
Existing land uses were identified separately in the land use scenarios GISlayer as their
modeled loading rates are different from new development due to regulations governing
new development in the study area (discussed in Section 3.5). All existing land areas
that had been classified as developed were put in their same categories in the future
scenarios. It was assumed that existing stream buffers as well as marsh and open water
wetlands as depicted on the existing land use map would remain. Protected lands were
assigned the same land use category for both scenarios (Section 3.2and Exhibit 3.2.1).
New development was added to the No-Buildscenario based on the number of future
households (one residential unit = one household). Residential units were generally
placed in proportion to the predicted population of the census tracts. In some areas,
including MCAS Cherry Point, development could not be placed in the appropriate
census tract as there was no land available for development. In those cases,
development was placed in the nearest neighboringcensus tract. Zoning and future land
use maps were used to determine whereto place development within eachcensus tract.
Residential land use was not placed in areas zoned or planned for other uses. In
addition, the zoning classifications or future land use category descriptions were used to
determine parcel sizeof new development,except for in-fill areaswhich were already
parceled out. For in-fill areas, i.e. vacant lots in existing neighborhoods, the current
parcel size was used even if the size of the lot was smaller than permitted by the zone.
Commercial development was allocated to the existing commercial centers in the
watershed. Some emphasis was placed on multi-family housing for the housing needs of
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MCAS CherryPoint as military personnel arelikely to favor this over single-family
housing (personal communication Mr. Skip Conklin, Facilities Director, MCAS Cherry
Point). Many parcels did not change land use between the existing and the No-Build
scenario as the quantity of land for development exceeded the quantity needed to
accommodate the projectednumber of newhouseholds. As noted in Sections 3.1 and
3.2, this methodology for establishing the baseline No-Build scenario differs from the ICE
methodology. Itresults in less land use development in the future No-Build conditionand
subsequently the Build scenario as well.
Before adding development to the Build scenario, the proposed Bypass(including right-
of-way and interchanges)were merged into the GIS land use datalayer. Then,the new
development(15% increase as established in the ICE)was allocated in a similar fashion
to the No-Buildscenario;however,more emphasis was puton placing development in
accordance with the impact areas identified in the ICE (HNTB, 2008) rather than
following census tract data. Non-residential land use needs (see Section3.1), were
assigned to appropriately zoned areas around the interchanges andalong existing US
70 to reflect the growth that the City predicts will occur there (Havelock, 2009). The
southern terminus was left undeveloped for reasons described in Section 3.3.
5.2.3Scenario Comparisons
Graphical depictions of the Build and No-Buildscenarios are presented in Exhibits 5.2.2
and 5.2.3.Approximately 95% of the increase in new development between the two
scenarios was found in 10 subbasins (1, 16, 17, 32, 36, 37, 39, 45, 47, 48, and 54). All
or a majority of the increase is a direct resultof the planned bypass roadway and right-
of-way in Subbasins 16, 17, 32, 36, 39, 45, 47, and 48. In addition to the roadway,
Subbasins 17 and 39 saw increases in high-density mixed development and Subbasins
36 and 54 had an increase in medium-density residential. The majority of the increase in
Subbasin 1 consisted of medium-density residential and some low-density residential.
Medium-density residential accounted for almost all of the development in Subbasin 37.
The remaining increases consisted mainly of medium-density residential and a small
amount of low-density residential development.
5.2.4Model 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. Site-specific impervious factors were not readily available for the study area.
Therefore, literature-based estimates were adapted to the watershed.
Table 5.2.3shows land use imperviousness values from three literature sources: Soil
Conservation Service(SCS 1986), Hunt and Lucas (2003), and Cappiella and Brown
(2001). Impervious estimates from Hunt and Lucas (2003) and Cappiella and Brown
(2001) are close in value, whereas estimates from SCS (1986) are high in comparison,
particularly for small residential lots.
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Table 5.2.3Estimates of Imperviousness from the Literature
Land Use CategoryPercent Impervious
Hunt and Lucas Cappiella and
Reference
SCS (1986)
(2003)Brown (2001)
Tar-Pamlico River Chesapeake Bay,
LocationNational Estimate
Basin, NCVa/Md
-0.48-0.42-0.5707
Regression Equationy=0.148xy=14.669xy=17.895x
2
R0.980.980.98
Residential 1/8 acre lot383365
Residential 1/4 acre lot302838
Residential 1/2 acre lot222125
Residential 1acre lot141420
Residential 2 acre lot11*1112
MultiFamily/Townhome41-4465
Institutional34
Light Industrial53
Industrial72
Commercial7285
* Calculated with regression equation.
The imperviousness values selected for this study are presented in Table 5.2.4.The
MapShed version of GWLF-Eonly allows for three categories of residential development
at pre-defined impervious values. Therefore, the Hunt and Lucas (2003) equation was
used to derive the size of residential lots at those percent impervious values. The Hunt
and Lucas equation wasselected given that it was derived using North Carolina data.
Values for non-residential land uses are taken from Cappiella and Brown (2001)given
that it covers several non-residential land use types and is based on regional data.
Additionally, the assumed imperviousness for roads with right of way is 61%,based on
semi-rural highways studied in Wu et al. (1998).
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Table 5.2.4Land Use Categories and Estimated Imperviousness
LAND USE NAMEGWLF-ECATEGORYPERCENT IMPERVIOUS
Low Density Residential
Low-Density Residential15%
(1-5 acre per d.u.)
Residential -Medium Density
Medium-Density Residential52%
(0.1 -1 acres per d.u.)
Residential -Multi-family
High-Density Residential87%
(<0.1 acres per d.u.)
Office/Institutional/Light
Medium-Density Mixed53%
Industrial
Commercial/Heavy IndustrialHigh-Density Mixed72%
Paved Road with Right of WayLow-Density Mixed61%
Golf CourseTurf/Golf0%
Row CropCropland0%
PasturePasture/Hay0%
Disturbed/Non-vegetatedDisturbed0%
Vacant/GrassOpen0%
ForestForest0%
WetlandsWetland0%
WaterWaterN/A
5.3Surface Water Hydrology
Table 5.3.1 provides a summary of several of the surface water inputs and assumptions
utilized in the GWLF-Emodeling analysis. The individual parameters are discussed
below.
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Table 5.3.1Surface Water Hydrology Input Parameters
COMMENTS/
INPUT BASELINE
DESCRIPTIONUNITLITERATURE REFERENCE
PARAMETERVALUE
RANGE
PrecipitationDaily rainfallinAnnual Min Elevenyears of Data from
=31.4data (January MCAS Cherry
Max = 72.7
2002 –December PointAWOS
Mean = 2012) used for Station KNKT,
52.2simulation and Moorehead City
assumed to be COOP 315830,
uniform for the & New Bern
study areaCOOP 316108,
State Climate
Office of NC
Haith et al.
Evapo-Cover coefficient noneValues Model defaults
transpiration for estimating ETrange from based on (1992),
(ET) Cover1.0 for literature valuesHammon (1961)
forest to 0.3
for cropland
Antecedent Moisture for up to cm0Unknown 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 noneComputed Site dependant SCS (1986)
Numbersconverting mass by Mapshed based on soil type
rainfall to mass based on and land use.
runoff.GIS layers.
5.3.1Precipitation
Daily temperature and rainfall records for the study area were obtained from the North
Carolina State Climate Officefor AWOS Station KNKT, located within the watershed on
MCAS Cherry Pointand COOP Station 315830, located approximately 8 miles southeast
of the watershed model boundary in Morehead City. Data for an eleven-year period was
assembled(2002-2012).A significant portion of precipitation data was noted to be
missing from 2003-2006at Station KNKT. For this period, precipitation data from COOP
Station 316108 were used to supplement missing data. Station 316108 is located
approximately15miles from the center of the study area, in New Bern.Minor missing
values in the time series were filled in using the averages of the surrounding daily
values.
The mean rainfall over the ten-year simulation period is within 9%percent of the 30-year
normal for the annual average (57.1 in) at MCAS Cherry Point,indicating that the model
simulation period represents average hydrologic conditions for the area. Rainfall was
assumed uniform throughout the study area.
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5.3.2Evapotranspiration Cover Coefficients
The portion of rainfall returned to the atmosphere through evapotranspiration (ET) is
determined by temperature and the density of vegetative cover, which varies by land use
and by season (growing and dormant).Within Mapshed, potential evapotranspiration
(PET) is computed using the method recommended by Hammon (1961). In this method,
PET is a function of daylight hours per day, the saturated water vapor pressure, and the
mean daily temperature. ET coefficients are assigned by landuse/cover type with typical
values ranging from 1.0 for wooded areas during the growing season, to 0.3 for row
crops during the dormant season. Monthly values aredetermined by watershed on an
area-weighted basis.
5.3.3Antecedent 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 (Haithet
al., 1992).
5.3.4Runoff Curve Numbers
The fraction of precipitation that becomes surface water runoff in GWLF-Eis calculated
on the basis of the SCS Curve Number Method as presented in the TR-55 Manual (SCS,
1986). Curve numbers are derived based onland covertypeand soil hydrologic group.
Soil hydrologic groups for the soils present within the study area were determined using
the Natural Resource Conservation Service (NRCS) detailed soil survey geographic
(SSURGO) database. MapShed internally calculates curve number based on hydrologic
group and land cover. For urban land categories, curve numbers are derived for both
pervious and impervious areas. Refer to Section 5.2.4for the determination of percent
imperviousness for the various landuse/cover types.
5.4Groundwater Hydrology
Table 5.4.1 providesa summary of several of the groundwater inputs and assumptions
utilized in the GWLF-Emodeling analysis. The individual parameters are discussed
below.
5.4.1Recession Coefficient
The rate at which groundwater is discharged to streams is a function of the recession
coefficient. In theory, provided that flow data isavailable, this factor can be determined
through analysis of the hydrograph. However, no flow data wasavailable within the
study area. GWLF modelingstudies by Lee et al. (1999) in 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
2
relationship between recession coefficient (R) and drainage area (DA in km
):
-1
R = 0.0450 + 1.13 * (0.306 + DA)
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This equation was used to calculate individual recession coefficients for each ofthe
GWLF-Esubbasins simulated. Results ranged in value from 0.05to 0.43.
5.4.2Seepage Coefficient
GWLF-Esimulates three subsurface zones: a shallow unsaturated zone, a shallow
saturated zone (aquifer), and a deep aquifer zone. The deep seepage coefficient is the
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 adjusted during model calibration to produce a
3% loss to deep groundwater over the entire study area. The result was a seepage
coefficient of 0.01.
Table 5.4.1Groundwater Input Parameters
COMMENTS/
INPUT BASELINE
DESCRIPTIONUNITLITERATURE REFERENCE
PARAMETERVALUE
RANGE
–1 Leeet al.
Baseflow Groundwater day Min = 0.05Drainage area-
Recession seepage rateMax = 0.43dependent and (1999)
Coefficient (r)Mean = calculated
0.21according to
Leeet al.(1999)
Haith et al.
Seepage(s)Deep seepage n/a0.01Site dependent;
coefficientGoal to (1992);
Evans et al.
generate 3%
deep seepage (2000)
over the
simulation
period
Unsaturated Interstitial storagecmMin = 0Determined Haith et al.
Soil Water Max = 52.5from Craven (1992)
Storage Mean = and Carteret
Capacity20.3County Soil
Survey Data
5.4.3Unsaturated Available Soil Water Capacity
Water stored in the soil may evaporate, be transpired by plants, or percolate down to
groundwater below the rooting zone. The amount of water that can be stored in the soil
in the region where it is still available for evapotranspiration is the available soil water
capacity (AWC), which varies according to soil type and rooting depth. Volumetric AWC
values (cm/cm) were extracted from the Craven and Carteret Counties Soil Survey
Geographic (SSURGO) Database.Using the AWC values reported for the entire soil
profile (maximum depth of 150cm reported), the AWC values ranged from 0 to 52.5cm
in the ICI study area.
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5.5Erosion and Sediment Transport
Sediment erosion in the GWLF-Emodel is simulated through application of the USLE,
which uses four input factors (K, LS, C and P). Table 5.5.1 providesa summary of
several of the erosion and sediment transport inputs and assumptions utilizedin the
GWLF-Emodeling analysis. The individual parameters are discussed below.
5.5.1Soil Erodibility (K) Factor
Soil erodibility or (K) factor, is a measure of a given soil’s propensity to erode due to
rainfall. K factors in this analysiswere obtained from the SSURGO Databasefor Craven
and Carteret County. Within MapShed, an area-weighted K factor value is calculated for
each land use/land cover (LULC)type (i.e., source area) in a subbasin.
5.5.2Slope-Length(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 are generated automatically in MapShed for elevation data with grid cell
resolution of 50 meters or less. The functions within MapShed are based on functions
contained within the ArcView Terrain Analysis Extension, including the technical
algorithms described by Moore and Wilson (1992).A 10-meter resolution DEM grid for
the study area was used forcalculation of LS factors in this modeling analysis.
5.5.3Cover (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). These
mechanisms arerepresented by cover and management factors in the USLE. Cover and
management factors for non-agricultural land uses in this study are based on factors
developed for the Jordan Lake Watershed TMDL Watershed Model Development
(TetraTech, 2003). The factors were further refined based on input from district
conservationists atthe Craven County Natural Resource Conservation Service (personal
communication, Mr. Andrew Metts). Theresulting factors are summarized in Table 5.5.2.
Note thatC and P factors are not required for the urban land uses, which are modeled in
GWLF-Evia a build-up/washoff formulation rather than the USLE.
5.5.4Sediment Delivery Ratio
In GWLF-E, 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). GWLF-Ecalculates the sediment delivery ratio on the
basis of the drainage area of the subbasinbeing simulatedaccording to empirically-
derived equations (Vanoni, 1975).
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Table 5.5.1 RuralSediment Transport Input Parameters
COMMENTS/
INPUT BASELINE
DESCRIPTIONUNITLITERATURE REFERENCE
PARAMETERVALUE
RANGE
RainfallKinetic energy MJ-0.16 (cool Rainfall erosivity Haith et al.
Erosivity (R)of rainfallMm/haseason)may vary (1992) for
0.28 (warm seasonally and is Wilmington,
season –Apr estimated by NC
thru Oct)geographic
region
Soil Erodibility Soilerosion NoneArea-weighted Derived from County level
Factor (K)potentialVaries by LULC soils GIS data soils data for
type(function of soil the study area
texture and
composition)
Length-Slope Sediment NoneVaries by Derived from Moore and
Factor (LS)transport SubbasinDEM as function Wilson (1992)
potential based of slope and
on topographyoverland runoff
Sediment Portion of NoneVaries by Empirically
Vanoni (1975)
Delivery Ratio Eroded Material Subbasinestimated as a
(SDR)that is function of
transported to subbasin.
receiving waters
Table 5.5.2 Cover (C) and Management Practice (P) Factors
LAND USE NAMECP
Hay/Pasture0.0031.000
Cropland0.2000.800
Forest0.0021.000
Wetland0.0011.000
Disturbed0.0801.000
Turf/Golf0.0031.000
Open0.0000.000
Bare Rock0.0000.000
Sandy Areas0.0000.000
5.5.5Sedimentation from Urban Land Uses
For urban land uses, the GWLF-Emodel calculates particle loads as a function of
sediment accumulation and wash-off. In the model application, sediment accumulation
rates by urban land use ranged from 0.8 to 6.2kilograms per hectare per day
(kg/ha/day)on the pervious and impervious fractions (Table 5.5.5).These rates were
based on suspended solids accumulation rates from Kuoet al.(1988) as cited in Haith et
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al. (1992). The sediment accumulation rate for roadwayswas assumed to be the same
as medium-density mixed development, given their similarimperviousness.
Table 5.5.3 Sediment Mass Build-Up Rates
SEDIMENT MASS BUILD-UP RATES
TSS (kg/ha/day)
URBAN LAND USES% Impervious
ImperviousPervious
Low-density Residential15
2.51.3
Medium-density Residential52
6.21.1
High-density Residential/Multi-
87
family5.01.5
Roadway61
6.20.8
Medium-density Mixed53
6.20.8
High-density Mixed72
2.80.8
5.5.6Erosion from Streams
As mentioned in Section 4.2.6, GWLF-E includes several revisions to the GWLF model,
including a routine which estimates streambank erosion for inclusion in total sediment
loads. This routine is basedon an approach often used in the field of geomorphology in
which monthly streambank erosion is estimated by first calculating an average
watershed-specific lateral erosion rate (LER). The LER is based on empirically-derived
constants and monthly stream flow. The total sediment load generated from stream bank
erosion is then calculated by multiplying the LER by the total length of streams in the
watershed, the average streambank height, and average soil bulk density. GWLF-E
assumes an average bank height of1.5 meters (Evans and Corradini 2012).
Stream bank height in coastal watersheds can be highly variable, depending on factors
such as soils, land use, and local topography. Using an average default bank height of
1.5 meters does not allow for accounting for this variability across a watershed. For this
reason, the streambank erosion routine was not incorporated into this model study.
5.6NutrientLoading
Nutrient loads in stream flow are comprised of both dissolved and solid phases.
Dissolved nutrients are associated with overland runoff, point sources, and subsurface
discharges to streams. Solid-phase nutrients are also associated with point sources, in
addition to soil erosion and wash-off of material from urban areas.Table 5.6.1 providesa
summary of several of the nutrient inputs and assumptions utilized in the GWLF-E
modeling analysis. The individual parameters are discussed below.
5.6.1Nutrients in Soils
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 to1,400
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).
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5.6.2Dissolved Groundwater Nutrients
The GWLF-Emodel 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) ina 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.
Table 5.6.1SolidPhase and Groundwater Nutrient Loading Input Parameters
COMMENTS/
INPUT BASELINE
DESCRIPTIONUNITLITERATURE REFERENCE
PARAMETERVALUE
REVIEW
Solid Phase Nutrient Loading
Haith et al.
Nutrient Total Nitrogen mg/kg1,400Varies
concentration Concentrationregionally and (1992)
in sediment by site; 500-900 Mills et al.
from rural based on (1985)
sourcesliterature;
multiplied by a
mid-range
enrichment ratio
of 2.0
Haith et al.
Total mg/kg352Varies
Phosphorous regionally and (1992)
Mills et al.
Concentrationby site; less
than or equal to (1985)
400; multiplied
P2O5
conversion
factor and
enrichment ratio
(2.0)
Dissolved Nutrient in Groundwater
Nutrient Total Nitrogen mg/L0.42Median value Spruill et al.
concentration Concentrationfor the inner (1998)
coastal plain
Total mg/L0.04Median value Spruill et al.
Phosphorous for the inner (1998)
Concentrationcoastal plain
5.6.3Rural and Urban LandUse Loads
In GWLF-E, 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-Emodel uses build-up/washoff
relationships to predict nutrient and sediment loads for urban (developed) land uses, and
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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
vary between the pervious and impervious fractions of the LULC type.
Nutrient runoff concentrations from rural and agricultural usesare presented in Table
5.6.2.The runoff concentrations were derived from various GWLF modeling studies
performed in North Carolinaincludingstudies on the Jordan Lake Watershed (Tetra
Tech2003), Upper Rocky River (Tetra Tech 2005), Greenville Southwest Bypass ICI
(Stantec 2007), and Monroe Connector ICE(PBS&J 2010).Several of these studies are
within the Neuse River Basin.Nutrient runoff concentrations from golf courses have
been shown to vary based on fertilizer application rate and soil conditions. However,
nutrient runoff concentrations are similar to urban and agricultural losses (Soldat and
Petrovic, 2008). Lacking data specific to North Carolina, nutrient runoff concentrations
from golf courses were assumed to be similar to agriculture concentrations within the ICI
study area.
Nutrient and sediment accumulation rates (kg/ha/yr) for urban land uses are presented
in Table 5.6.3. These rates are the model defaults in GWLF-E, derived from Kuo et al.
(1988), a study which investigated the nutrient accumulation rates for both the
impervious and pervious fractions of urban land uses. Accumulation rates for the
roadway land use category were assumed to be similar to medium-density mixed urban
land use, given the similarity in percent imperviousness.
Table 5.6.2Nutrient Runoff Concentrations byRural Land UseCategory
RUNOFF CONCENTRATIONS
DISSOLVED P
RURAL LAND USESDISSOLVED N (mg/L)
(mg/L)
Hay/Pasture2.7700.250
Cropland2.7700.250
Forest0.1900.006
Wetlands0.1900.006
Disturbed0.1900.006
Turf/Golf2.7700.250
Open0.1900.006
Bare Rock0.0000.000
Sandy Areas0.0000.000
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Table 5.6.3Nutrient Mass Build-up Rates by Urban Land Use Category
MASS BUILD-UP RATES
N(kg/ha/day)P(kg/ha/day)
RURAL LAND Percent
Dissolved Dissolved
USESImpervious
ImperviousPerviousImperviousPervious
FractionFraction
Low-density
150.0950.0150.280.00950.00190.37
Residential
Medium-density
520.1000.0150.280.01150.00390.37
Residential
High-density
Residential/Multi870.1050.0150.280.01200.00780.37
-family
Roadway610.0950.0150.330.00950.00210.40
Medium-density
530.1050.0150.330.01050.00210.40
Mixed
High-density
720.1100.0150.330.01150.00210.40
Mixed
5.6.4Septic System Loading
The septic system component of the model simulates dissolved nutrient loads to stream
flow from a variety of system types. These types include normal, short-circuited, ponded,
and direct discharge systems. In normal systems,nitrogen entering surface water is
assumed to be a factor of plant uptake or its ability to infiltrate groundwater and
subsequent discharge to streams. Phosphorus is assumed to be completely absorbed
by soils in this scenario. In ‘short-circuit’ systems, the septic tanks are assumed to be in
close-proximity to streams, and therefore phosphorus absorption by soil is assumed to
be negligible. ‘Ponded’ systems describe septic tanks with hydraulic failure, resulting in
the surfacing of tank effluent which enters surface water via overland flow. ‘Direct
discharge’ systems are illegal systems which discharge tank effluent directly to surface
water.
Inputs required by the model are presented in Table 5.6.4and include the number of
people on septic systems by subbasin, the per capita effluent load, and the rate of plant
uptake. The population of septic was estimatedusing GIS analysis to determine the
number of residential parcelsand housing unitsoutside of Havelock and Newport sewer
service areas, andCensusdata for theaverage number of persons per housing unit.
Subbasins that did not have a change in land use between No-Buildand Build scenarios
were assigned the same population on septic.
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Table 5.6.4Septic System Input Parameters
INPUT PARAMETERUNITVALUECOMMENTSREFERENCE
Population Using PersonsRanges from Based on GIS US Census
Septic0 to 1,825per analysis of residential Bureau(2010)
subbasinparcels, sewer service
area, and census-
based average
persons per housing
unit
Nitrogen Septic TankGrams/day12.33Based on Neuse River Buetow (2002)
Effluentbasin data
Phosphorus Septic Grams/day1.75Based on Neuse River Buetow (2002)
Tank Effluentbasin data
Nitrogen Plant Grams/day1.6Growing season Model default
UptakeRate
Phosphorus Plant Grams/day0.4Growing seasonModel default
Uptake Rate
Failure ratePercent11.4Based on NC NCDEH (2000)
statewide homeowner
survey
County-specific statisticaldata on septic system malfunction in North Carolina is limited.
However, astate-wide survey on septic system failure was performed by the North
Carolina Office of State Budget and Management in 1981. In this citizen survey, 11.4%
reported septic system malfunction or failure in the preceding year (NCDEH, 2000).
For nutrients,septic tank failure rates within GWLF-E are modeled by adjusting the
population which uses each of the four types of septic systems described previously.
Non-failing septic systems are modeled as ‘normal.’Given that failure rates reported in
the citizen survey was based on homeowner observation, the most accurate
representation of this failure in the GWLF-E model is the ‘ponded’ system. It was
assumed that no illegal ‘direct discharge’ systems are present in the watershed.
5.6.5Point Sources
As discussed inSection 3.4,there are currently three wastewater treatment plants within
the model study area: Havelock WWTP, Cherry Point WWTP, and Carolina Pines
WWTP. Additionally, there is one water treatment plant (WTP) which discharges within
the study area: BrownBoulevard WTP. Discharge monitoring reports (DMRs) for all four
facilities were obtained from NC Division of Water Quality Central Files Office.
Average daily values for flow, TN, TP, total suspended sediment (TSS), and FC
concentration (where available) were used to derive an averageyearly load for nitrogen,
phosphorus, TSS, and FC bacteria for each of these facilities under existingconditions.
Projected loads from the WWTP’s for both the No-BuildandBuild future land use
scenarios were estimated using the number of new households in each scenario, and an
estimated average requirement of 212 gallons/day per household (Urban Resource
Group, 2009). Additional flow was attributed to each WWTP according to the number of
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new households within the service area of each facility. As mentioned in Section 3.1, no
new residential development is projected for the MCAS Cherry Point. As a result, loads
from the Cherry Point WWTP are projected to remain the same as existing conditions.
For the Brown Boulevard WTP, projected increases in discharge were estimated based
on the projected increase in population within the Craven County portion of the study
area.
The discharge locations for these point sources is included in Exhibit 5.1.1.
5.6.6Animals
As described in Section 4.2.3 nutrient loads from animals are modeled via the simulation
of run-off from manured and pasture/grazing areas. GWLF-E allows for users to directly
simulate loads from farm animals by entering the number of farm animals in the
watershed. During field reconnaissance of the model study area, no concentrated animal
feeding operations (CAFOs) or livestock operations were observed. However, several
horse stables were observed. The location of these stables was recorded and added to
the model(Exhibit 5.1.1). A density of 25 horses per stable was assumed. Model
defaults regardingnutrient production per animal and manure application rates were
used.Model defaults for estimated loading rates per were drawn from many literature
sources (Miller etal. 1982, ASAE 1993, SCS 1992). The model assumes that horses are
grazing animals, and therefore the pathway for runoff is via pasture/grazing areas.
5.7PathogenLoading
Within GWLF-E there are a number of routines that can be used to estimate pathogen
loads originating from: urban land uses, septic systems, wastewater treatment plants,
farm animals, and ‘natural areas’ (i.e. wildlife loadings). In some instances, these
routines vary from the nutrient routines. By default, the pathogen simulated in GWLF-E
is assumed to be fecal coliform.It should be noted that for all pathogen loads, the model
assumes that 50% of pathogens will die shortly after they have been transported to
nearby surface waters (Easton et al. 2005, LaWare and Rifai 2006, and NCDENR 2004).
5.7.1Urban Land Use Loads
Load estimates from urban areas are made using the concept of ‘event mean
concentrations’ (EMC), or the mean concentration of a pollutant in runoff. Unlike the
nutrient routines, which utilize accumulation rates for the impervious and pervious
fractions of varied urban land use types, the pathogen routine uses a single EMC value
3
for all urban land use types. The model default of 9.60 x 10cfu/100mL was selected as
this is based on several urban studies (USEPA 2001b).
Pathogen loads associated with rural land uses are incorporated into the farm animal
and wildlife routines discussed in Section 5.6.6.
5.7.2Septic System Loading
Similar to nutrient loading from septic systems, fecal coliform load estimates from septic
systems require inputs such as the number of people on septic systems by subbasinand
the per capita effluent load.However, the fecal coliform routines vary from the nutrient
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routines in that they assume that only failing septic systems contribute to loading. This
assumption is borne from studies that suggest low survival rates for pathogens in
properly operating septic systems (USEPA 2001b). As mentioned in Section 5.6.4, a
9
failure rate of 11.4% was selected. The per capita loading rateof 2 x 10
counts/person/day was selected, based on USEPA guidance (USEPA 2001b).
5.7.3Point Sources
For pathogen loads delivered from wastewater treatment plants, the model assumes a
single effluent pathogen concentration for all plants in the model study area, and
calculates pathogen loads based on total volume of effluent discharged by each plant.
DMRswere reviewed for all WWTPs and WTPs in the study area as described in
Section 5.6.5. Fecal coliform was only monitored for at the City of Havelock WWTP. An
average concentration of 10 cfu/100mL was observed in effluent from the Havelock
WWTP, as such a value of 10 cfu/100mL was assumed for the effluent from all point
sources within the model study area.
5.7.4Animals
The pathogen loading routines from farm animals is the same as the routines described
for nutrients in Section 5.6.6. In addition, the model also incorporates pathogen loads
from ‘natural areas,’ i.e. wildlife loads.Wildlife pathogen load estimates are assumed to
be equivalent to those loads generated by a population density of 25 deer per acre of
‘natural area’ within the watershed, such as forest and wetland, using deer as a
8
surrogate for all wildlife inputs. A default loading rate for deer of 5 x 10organisms per
animal per day was selected based on USEPA guidance (USEPA 2001b). A die-off rate
of 90% organisms produced in natural areas before reaching surface water was
assumed (Evans and Corradini 2012).
5.8Consideration of Existing Environmental Regulations
5.8.1Neuse 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 lb/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 North Carolina Ecosystem Enhancement Programprovided,
however, that no new residential development can exceed 6.7 kg/ha/yr (6.0 lb/ac/yr) and
no new nonresidential development can exceed 11.2 kg/ha/yr (10.0 lb/ac/yr).
The effect of the NSW rules were implemented in the model by applying stormwater
Best Management Practice (BMP) pollutant removal efficiency rates to new developed
land in the No-BuildandBuild scenarios compared to existing land use. BMP pollutant
removal efficiencies for nitrogen, phosphorus, and sediment were derived from the
efficiencies listed for stormwater wetlands in the North Carolina BMP Manual (NCDWQ
2007). The removal efficiency for fecal coliform was derived from literature values
(Davies and Bavor, 2000; Mallin, 2002). SelectedBMP removal efficiencies are
presented in Table 5.8.1.
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Projected loading rates of each land use category of new development were derived
from loading rates listed in the City of Havelock Stormwater Management Ordinance
(Havelock 2013). An area-weighted average loading rate for new development for each
subbasin was calculated. Next, BMP pollutant removal efficiencies were applied to
determine the number of BMPs that would be required to meetthe NSW nitrogen
loading limits for new development. In many subbasins, a minimum of two or three
BMPs in series would be required to meet the loading limits. In practice, it is more likely
that one BMP would be utilized, with excess loads compensated through the in-lieu fee
program. As a conservative estimate, the effect of only one BMP was simulated in the
model at the BMP Removal efficiencies outlined in Table 5.8.1. It should also be noted
that while payment to the in-lieu fee program would result in nitrogen removal projects
being implemented, the location of these projects cannot be predicted. As a conservative
estimate, it was assumed that these projects would occur outside of the model study
area.
Table 5.8.1Selected BMP Removal Efficiencies
PollutantRemoval Efficiency
Total Nitrogen40%
Total Phosphorus40%
Total Suspended Sediment85%
Fecal Coliform56%
North Carolina BMP Manual (NCDWQ 2007)
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 many traditional 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. This is a conservative assumption since control of peak flows may
be expected to provide additional control of runoff. However, note that control of peak
flows is required regardless of the development scenario. Therefore, the change in the
peak of the hydrograph or difference between the two scenarios should be insignificant
since nearly all of the new development would require control.
In both land use scenarios, a fifty-foot buffer on all streams identified in the National
Hydrography Dataset-based stream coveragewas classified as forest.
5.8.2Coastal Stormwater Management Rules
The Coastal Stormwater Management Rules imposes impervious cover (IC) limits on
non-residential development that adds more than 10,000 square feet of built-upon-area
or requires a Sediment and Erosion Control (S&EC) Plan, or residential development
that requires a S&EC Plan. For the low-density development option which falls below the
IC threshold, the rules require that stormwater be conveyed through vegetated
conveyances and that 50-foot vegetated buffers be maintained for all new development,
and 30-footbuffers for redevelopment. For the high-density development with IC above
the threshold, stormwater BMPs must be installed to treat runoff from new development.
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In areas within 575 feet of Outstanding Resource Waters (including shellfish waters) in
the coastal counties, the IC threshold is 12%. For all other areas in the coastal counties,
the threshold is 24%.
Similar to above, the effects of the Coastal SW Management Rules were incorporated
into the model by applying stormwater Best Management Practice (BMP) pollutant
removal efficiency rates to new developed areas covered by the rules (Carteret County
and Craven County outside of Havelock). It should be noted that for portions of the
model study area covered by the Coastal SW Rules but not near shellfish waters, low-
density residential development was not included in the calculation of new development
acreage on which to apply BMPs, as the impervious cover for this land use category
(15%) is lower than the threshold outlined in the rules (24%). For portions of the model
study area near shellfish areas (Subbasins 61 and 7),low-density residential
development was included in the new development calculation as it is above the 12% IC
threshold. The BMP pollutant removal efficiencies outlined in Table 5.8.1were applied.
5.9Model Implementation
Based on the series of inputs discussed in the following section, a series GIS files and
model inputs were developed to execute individual model runs simulating the Build and
No-Buildscenarios in each of the GWLF-Esubbasins presented in Figure 5.1.1. All
model runs relied on the same weather file that contains precipitation and air
temperature data for climate years 2002 through 2012. The climate year for GWLF-Eis
defined as January 1 –December 31.
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Exhibit5.1.1 Model Subbasins
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Exhibit5.2.1 Existing Land Use
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Exhibit5.2.2 Future Land Use No-BuildScenario
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Exhibit5.2.3 Future Land Use Build Scenario
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6GWLF-EMODEL RESULTS AND DISCUSSION
6.1Calibration
Several resources were reviewedfor stream flow data within the project study area, including
USGS, NCDWR (formerly NCDWQ), the Croatan Mitigation Bank, and the U.S. Forest Service.
There is no stream flowdata within the study area for model calibration. To calibrate the model,
model parameters were adjusted such that average hydrologic model results over the model
period were in agreement with literature values for hydrologic parameters specific to eastern
North Carolina.
Components of the hydrologic cycle illustrated in Figure 4.2.1include precipitation,
evapotranspiration, runoff, and deep groundwater seepage. In eastern North Carolina, rainfall
typically ranges from 112 to 152 cm (44-60 in). A study by Evans et al. found that
evapotranspiration (ET), runoff (i.e., surface and subsurface flow to streams)and deep
groundwater seepageto aquifers 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). Inother words, the water balance
breakdown would be comprised of 65 to 71% evapotranspiration, 26 to 32% runoff, and about
3% deep groundwater seepage.
In addition, 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).Wilder et al. (1978)cited 68% of the water balance as ET for
northeastern NC. The predicted hydrologic components of the model are compared to these
literature values.
Model parameters which affect the ratio of ET, runoff, and deep groundwater seepage in the
hydrologic cycle include: ET cover, antecedent soil moisture conditions, curve number, available
groundwater recession coefficient, unsaturated available soil water capacity (AWC), and
groundwater seepage coefficient. Refer to Section 5.3 and 5.4 for a detailed description of each
of these parameters. ET cover is based on literature values for different landuse types and was
not adjusted during model calibration. Antecedent soil moisture conditions is unknown, but has
little effect over the duration of the model period given that it is a function of rainfall only five
days prior to the first day of the model period; therefore it was not adjusted during model
calibration. Curve numbers were also not adjusted. While themodel is driven by the SCS
method and curve numbers, it isrelatively insensitive to small changes in curve number.
Significant adjustments to curve numbers would not be a realistic representation of on-the-
ground landuse and soils conditions, and curve numbers were not adjusted during model
calibration.
AWC is an intrinsic characteristic property based on soil type and cannot be used for calibration.
However, one adjustment was made during model calibration. The GWLF-E manual calls for the
use of the AWCvalue for the entire soil profile, which it defines as the soil profile to a depth of
100 cm. SSURGO data for Carteret and Craven County includes AWC values for a soil profile
depth of 150 cm. Model runs showed that using the 150 cm AWC slightly improved ET values in
the model results over the 100 cm AWC values calculated from soil reports; therefore, 150 cm
AWC values were used in the final model runs.
The groundwater seepage coefficient was the primary parameter adjusted during the hydrology
calibrationof the model. The seepage coefficient was adjusted during multiple runs such that
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the predicted hydrologic components of the model were within the ranges of theliterature values
discussed above.Model results were compared at both the watershed and subbasin level.
Since the literature values are based on hydrology in an undisturbed watershed, Subbasin 3
was chosen for comparison.In the No-Build scenario thissubbasinisprimarily forested and
wetlandwith some crop and open land. .A final groundwater seepage coefficient of 0.01 was
found to produce ET, runoff, and deep groundwater seepage within range of literature values.
Runoff from Subbasin 3comprised 28% of the water balance of the simulation period for the No-
Buildscenario, which is within the range of both the Evans et al.and Chesheir et al.literature
values. Evapotranspiration comprised 70% of the water balance, which is within range of the
Evans et al.values, and similar to the Wilder et al.estimate. Similarly, deep seepage accounted
for 2% of the water balance for Subbasin 3, falling within the range of Evans et al.values.The
hydrologic balance for the entire model study area was 64% ET, 33% runoff, and 3% deep
groundwater seepage; all within range of literature values.
The seasonal change in hydrologic conditions in Subbasin 3 is shown in Figure 6.1.1.As
expected, evapotranspiration decreases in winter due to lower temperatures and dormant
vegetation resulting in a higher proportion of runoff.
25
Precipitation
Evapotranspiration
Subsurface Runoff
20
Surface Runoff
Total Runoff
15
cm
10
5
0
JanFebMarAprMayJunJulAugSepOctNovDec
Figure 6.1.1Mean Monthly Water Balance for Subbasin 3 (No-BuildScenario)
In the absence of stream flow data within the study area, 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 outside of the watershed with similar
drainage area characteristics.
The nearest USGS gage of a watershed of similar land use and size is the gage on Chicod
Creek at State Road 1760, station number 02084160. The Chicod Creek gage, located
2
approximately 45 miles northof the study area has a reported drainage area of 117 kmand an
average daily dischargeof 49 cubic feet per second or 1.4 cubic meters per second (m³/s), over
the 11-year model period.
In order to provide a standardized comparison, the stream flows from the GWLF subbasins
were converted into annual m³/ha yields. The 11-year average annual yields from the 65
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subbasins (No-Build scenario) ranged from 3,653 to 14,322 m³/ha/yr, resulting in percent errors
of 0.3 to 278% and an overall average of 23%, when compared to the average annual yield from
the Chicod Creek gaging station over the same 11-year period (3,790 m³/ha/yr). Percent errors
in annual mean values were calculated by the following formula: \[(simulated -observed) /
observed\] x 100% (Zarriello, 1998). However, the watershed for Chicod Creek watershed is
rural which has implications for its water balance: less streamflow is expected due to greater
evapotranspiration (more vegetation) and less runoff (less impervious surface). When
comparing some of the least developed subbasins (3, 26, and 44) in the study area to the
Chicod Creek gage, the percent errors average 3% suggesting the modeladequatelysimulates
the long-termwater balance and stream response.
If this were a comparison of simulated values and actual observed values measured within the
watershed, an average error of 10% in annual predictions would represent a “Good” calibration
according to Donigian’s (2002) generalcalibration targets for watershed modeling. The
comparison indicates that the predicted stream flows from the GWLF modeling results are
reasonable.
6.2Pollutant LoadingResults
For each land use scenario, GWLF model output time series were generated reflecting an11-
yearmean of annual total nitrogen (TN), total phosphorus (TP), sediment, and fecal coliform
(FC) loads. The mean annual pollutant loads for each subbasin, the model study area as a
whole, as well as the breakdown of pollutant loads between the White Oak and Neuse River
Basin portions of the study areaare presented in Table 6.2.1. Pollutant load rates are presented
in Table 6.2.2. Additionally, mean annual pollutant loads for the model study area and the White
Oak and Neuse River Basin portions of the study area are presented in Figures 6.2.1 through
6.2.4.Exhibits 6.2.1 and 6.2.2depict the increase in mean annual pollutant loading rates by
parameter for each subbasin.
The Build scenario resulted in changes in TN and TP loads ranging from 0% to 16.6% and 0%
and 30.1%, respectively. The increase in mean annual nutrient loads over the entire model
study area was 1.6% (TN) and 1.76% (TP). The largest increases in mean nutrient loads occur
in undeveloped subbasins through which the proposed bypass occurs, including Subbasin 39,
45, and 47. The very low nutrient loads in these undeveloped subbasins in the No-Build
scenario strongly influences the higher percent increase in the Build scenario loads. Notable
increases in mean annual nutrient loads also occurred in Subbasin 1. This increase is a result of
and is proportional to the increase in septic systems associated with new residential
development in the Build scenario.
The Build scenario resulted in increases in TN and TP loading rates ranging from 0.01to 0.5
kg/ha/yrand 0.01 to 0.03 kg/ha/yr,respectively.Of these, Subbasins 1, 39, 45, and 55 saw the
highest increase in loading ratefor nitrogen while Subbasins 1, 37, 39, and 45 were the highest
for phosphorous. Subbasin 1 is located north of the bypass, Subbasin 39 contains the Lake
Road proposed interchange and Subbasins 45 and 55 are at the southern end of the bypass.
Subbasin 37 covers much of downtown Havelock. Approximately 57%of the predicted growth
between the No-Buildand Build scenarios occurred in Subbasins 1, 37, 39, 45, and 55.
While loading rate increases were predicted in the Build scenario subbasins where growth
occurred, it is important to note that two of the highest loading rates for TN and TP in the
watershed occur in Subbasins 11 and 28 where no additional growth over the No-Buildscenario
6-3

Havelock Bypass
ICI Water Quality Study
occurs. Subbasin 28 is already highly developed and Subbasin 11 contains the discharge for
the Havelock wastewater treatment plant.
The average increase in sediment loads across all subbasins was2.6% when comparing the
Build and No-Buildscenarios. Significant increases were estimated in Subbasin 18, 32, 39, 45,
47, and 48. Similar to nutrient loads, the magnitude of these increases is affected by the
undeveloped condition of the watersheds and associated low sediment loads in the No-Build
scenario. In the Build scenario, the direct impacts of the Bypass footprint replaces forested and
wetland land uses, resulting in higher sediment loads. For example, Subbasin 18, 47, and 48
are undeveloped watersheds comprised completely of either forest or wetland in the No-Build
scenariowith very low sediment loading rates of 1.26 to 2.35 kg/ha/yr. In the Build scenario, the
only development in these Subbasins is the proposed Bypass, resulting in estimated sediment
loading rates of 1.64 to 8.68 kg/ha/yr. While this is a significant increase in loads by percentage,
load rates remain low and are comparable to other undeveloped or low density developed
subbasins in the model study area. Subbasins 32, 39, and 45 are primarily forest and wetland,
with limited residential development in the No-Buildscenario. The increase in sediment loads in
Subbasin 45 is related to the footprint of the proposed Bypass, whereas in Subbasins 32 and 39
loads are associated with both the footprint of the proposed Bypass, in addition to new
development associated with one of the three proposed interchanges in the Build scenario.
These subbasins contribute a relatively low load of sediment compared to the loading rates in
found in Subbasins 1, 16, 17, 27, 37, 38, and 55 where rates are over 100 kg/ha/yr in each.
These subbasins have a large amount of developed land in both scenarios. Increases to loading
rates were minor as a result of the additional development in the Build scenario.
Model results demonstrated an increase in fecal coliform loads between the No-BuildandBuild
scenarios in eleven subbasins with the most significant percent increases occurring in 1, 37, 45,
54, and 55. In all but one instance, the increase in fecal coliform loads is associated with and is
proportional to the increase in the number of septic systems associated with new residential
development in the Build scenario. However, in Subbasin45 there are no septic systems in
either the No-Buildor Build scenarios. In this case, the increase in fecal coliform loads is directly
related to the functionality of the model in its estimation of loads from wildlife sources. The
model applies wildlifedensities to ‘natural areas’ to develop wildlife fecal coliform loads;
however, only forested lands are modeled as natural areas in GWLF –wetland is not included.
Subbasin 45 is primarily wetland in the No-Buildscenario, yielding very low baseline fecal
coliform loadings. In the Build scenario, the proposed Bypass occurs almost completely in
wetland areas generating a significant increase in fecal coliform loads within the model.
Therefore, the model result is likely an over estimation of the percent increase in fecal coliform
loads in Subbasin 45. Additionally, minor decreases in fecal coliform loads were estimated in
Subbasins 18, 47, and 48. These decreases occur in subbasins where the Bypass replaces
forested lands and its associated wildlife loads, and no other new development occurs in the
Build scenario.
In summary, non-pointsource loading is increased slightly in the Build scenario relative to the
No-Buildscenario, though the increases are reducedby the stormwater regulations governing
the jurisdictions. The greatest percent increase in pollutant loads is estimated to occur in
undeveloped watersheds with low baseline loads, and in subbasins where direct impacts from
the proposed Bypass or development along the proposed interchanges is expected to occur.
6-4

Havelock Bypass
ICI Water Quality Study
100,000
No Build
90,000
Build
80,000
70,000
kilograms
60,000
50,000
95,10796,657
40,000
78,36879,693
30,000
20,000
10,000
16,73916,964
0
TotalWhite OakNeuse
\\
Figure 6.2.1Mean Annual Total NitrogenLoads
10,000
9,000
No Build
8,000
Build
7,000
kilograms
6,000
5,000
7,5887,722
4,000
6,4136,531
3,000
2,000
1,000
1,191
1,175
0
TotalWhite OakNeuse
\\
Figure 6.2.2Mean Annual Total Phosphorus Loads
6-5

Havelock Bypass
ICI Water Quality Study
14,000
No Build
12,000
Build
10,000
kilograms x 100
8,000
13,11413,458
6,000
9,97510,302
4,000
2,000
3,1393,156
0
TotalWhite OakNeuse
Figure 6.2.3Mean Annual Sediment Loads
5E+14
3,156
4.5E+14
No Build
4E+14
Build
3.5E+14
FC (counts)
4.75E14
3E+14
4.55E14
2.5E+14
3.22E14
2E+14
3.07E14
1.5E+14
1.53E14
1E+14
1.48E14
5E+13
0
TotalWhite OakNeuse
Figure 6.2.4Mean Annual Fecal Coliform Loads
6-6

Havelock Bypass
ICI Water Quality Study
Table 6.2.1Mean Annual Pollutant Loads for All Subbasins
Total Nitrogen (kg/yr)Total Phosphorus (kg/yr)Total Sediment (kgx100/yr)Fecal Coliform (counts/yr)
Change % Change Change % Change Change % Change Change % Change
No-Over No-Over No-Over Over No-Over No-Over No-Over No-Over No-
SubbasinBuildBuildBuildBuildNo-BuildBuildNo-BuildBuildNo-BuildBuildBuildBuildNo-BuildBuildBuildBuild
16720.87348.3627.59.34%724.7763.438.85.35%1248.71295.046.33.71%4.45E+135.73E+131.28E+1328.76%
2987.9987.90.10.00%80.380.30.00.00%76.376.30.00.00%5.71E+125.71E+120.00E+000.00%
31343.91343.90.00.00%101.1101.10.00.00%160.5160.50.00.00%4.89E+114.89E+110.00E+000.00%
42173.32192.319.00.87%158.1158.70.50.33%259.5259.50.00.01%1.71E+131.75E+134.00E+112.34%
51240.11240.10.00.00%121.7121.70.00.00%280.2280.20.00.00%5.04E+115.04E+110.00E+000.00%
6869.0869.00.00.00%78.578.50.00.00%60.660.60.00.00%3.64E+113.64E+110.00E+000.00%
73190.43190.40.00.00%211.5211.50.00.00%239.8239.80.00.00%4.23E+134.23E+130.00E+000.00%
8237.0237.00.00.00%9.09.00.00.00%7.67.60.00.00%9.43E+099.43E+090.00E+000.00%
9323.0323.00.00.00%14.114.10.00.00%3.53.50.00.00%8.90E+108.90E+100.00E+000.00%
10627.8627.80.00.00%60.160.10.00.00%108.2108.20.00.00%2.34E+112.34E+110.00E+000.00%
119142.79173.831.10.34%1096.21100.14.00.36%238.0238.00.00.00%3.66E+113.66E+110.00E+000.00%
121953.11975.222.11.13%166.8172.05.23.10%229.4231.11.70.76%2.06E+132.06E+130.00E+000.00%
13712.2712.20.00.00%26.326.30.00.00%5.25.20.00.00%9.70E+109.70E+100.00E+000.00%
141683.01683.00.00.00%171.3171.30.00.00%376.0376.00.00.00%1.46E+121.46E+120.00E+000.00%
151449.91449.90.00.00%144.2144.20.00.00%462.4462.40.00.00%1.07E+121.07E+120.00E+000.00%
161801.41815.814.40.80%184.3185.81.60.85%680.4693.713.31.95%3.05E+123.10E+125.00E+101.64%
171751.91806.554.63.11%156.5163.36.84.34%842.6875.332.73.88%8.14E+128.22E+128.00E+100.98%
18728.5733.34.90.67%34.535.10.61.65%11.214.53.329.35%2.44E+112.43E+11-1.00E+09-0.41%
19788.4788.40.00.00%75.375.30.00.00%164.5164.50.00.00%5.71E+115.71E+110.00E+000.00%
20502.6502.60.00.00%17.017.00.00.00%1.11.10.00.00%3.88E+103.88E+100.00E+000.00%
21515.9515.90.00.00%17.217.20.00.00%5.45.40.00.00%1.52E+081.52E+080.00E+000.00%
22204.8204.80.00.00%6.56.50.00.00%0.10.10.00.00%0.00E+000.00E+000.00E+000.00%
23263.1263.10.00.00%8.58.50.00.00%0.00.00.00.00%0.00E+000.00E+000.00E+000.00%
24535.5535.50.00.00%49.149.10.00.00%100.4100.40.00.00%1.96E+111.96E+110.00E+000.00%
25665.2665.20.00.00%57.257.20.00.00%24.624.60.00.00%3.00E+113.00E+110.00E+000.00%
26628.2628.20.00.00%21.921.90.00.00%2.02.00.00.00%1.67E+101.67E+100.00E+000.00%
272495.82499.73.90.16%228.8229.20.40.19%564.4565.91.50.27%2.17E+132.17E+130.00E+000.00%
289013.29013.20.00.00%414.5414.50.00.00%287.0287.00.00.00%2.91E+122.91E+120.00E+000.00%
29718.3718.30.00.00%61.861.80.00.00%48.648.60.00.00%3.02E+113.02E+110.00E+000.00%
30465.1465.10.00.00%21.621.60.00.00%0.60.60.00.00%1.23E+101.23E+100.00E+000.00%
312320.32320.30.00.00%186.8186.80.00.00%348.7348.70.00.00%1.07E+131.07E+130.00E+000.00%
321066.31093.327.12.54%66.969.93.04.52%58.376.017.630.19%2.16E+132.16E+130.00E+000.00%
332941.52946.44.90.17%242.4242.40.00.00%651.1651.10.00.00%5.56E+125.56E+120.00E+000.00%
34748.5748.50.00.00%64.264.20.00.00%241.1241.10.00.00%2.22E+122.22E+120.00E+000.00%
35738.1738.10.00.00%41.041.00.00.00%55.755.70.00.00%1.75E+121.75E+120.00E+000.00%
363417.33485.968.62.01%252.8259.36.52.58%382.6406.423.86.22%4.89E+134.99E+131.00E+122.04%
371891.61954.362.83.32%200.6209.18.54.24%547.3577.830.55.58%2.87E+123.08E+122.10E+117.32%
381478.01478.00.00.00%149.1149.10.00.00%425.3425.30.00.00%3.34E+123.34E+120.00E+000.00%
391295.61399.0103.47.98%89.4101.512.113.52%83.2152.669.383.29%1.22E+131.22E+130.00E+000.00%
40622.3622.30.00.00%39.739.70.00.00%39.239.20.00.00%6.22E+126.22E+120.00E+000.00%
41489.1489.10.00.00%28.628.60.00.00%6.56.50.00.00%6.96E+106.96E+100.00E+000.00%
42682.4682.40.00.00%48.048.00.00.00%30.830.80.00.00%5.31E+115.31E+110.00E+000.00%
6-7

Havelock Bypass
ICI Water Quality Study
Total Nitrogen (kg/yr)Total Phosphorus (kg/yr)Total Sediment (kgx100/yr)Fecal Coliform (counts/yr)
Change % Change Change % Change Change % Change Change % Change
No-Over No-Over No-Over Over No-Over No-Over No-Over No-Over No-
SubbasinBuildBuildBuildBuildNo-BuildBuildNo-BuildBuildNo-BuildBuildBuildBuildNo-BuildBuildBuildBuild
43638.9638.90.00.00%48.948.90.00.00%9.09.00.00.00%5.61E+115.61E+110.00E+000.00%
44257.5257.50.00.00%14.714.70.00.00%11.911.90.00.00%6.80E+106.80E+100.00E+000.00%
45532.5621.188.516.63%37.849.211.430.05%71.0124.953.875.83%8.55E+101.40E+115.45E+1063.74%
46170.4170.40.00.00%10.610.60.00.00%0.20.20.00.00%1.32E+101.32E+100.00E+000.00%
47316.5345.028.59.00%20.223.53.316.48%5.125.420.3397.93%1.35E+111.30E+11-5.00E+09-3.70%
48854.6870.415.81.85%44.446.21.84.08%21.933.411.552.22%2.31E+112.27E+11-4.00E+09-1.73%
491304.61304.60.00.00%99.599.50.00.00%465.4465.40.00.00%3.61E+123.61E+120.00E+000.00%
502166.42166.40.00.00%165.4165.40.00.00%529.1529.10.00.00%9.50E+129.50E+120.00E+000.00%
51636.5636.50.00.00%36.436.40.00.00%6.46.40.00.00%2.87E+112.87E+110.00E+000.00%
52527.4527.40.00.00%39.239.20.00.00%2.32.30.00.00%2.87E+112.87E+110.00E+000.00%
531504.71509.54.80.32%115.1115.80.70.62%398.8399.20.40.10%7.43E+127.51E+128.00E+101.08%
545317.85455.7137.92.59%380.2386.86.61.74%889.2898.29.01.01%7.17E+137.48E+133.10E+124.32%
552061.82143.581.63.96%130.4135.14.73.57%340.0347.87.82.29%2.95E+133.12E+131.70E+125.76%
562614.92614.90.00.00%188.9188.90.00.0%506.8506.80.00.00%2.54E+132.54E+130.00E+000.00%
58412.5412.50.00.00%13.013.00.00.00%0.00.00.00.00%1.76E+091.76E+090.00E+000.00%
59192.6192.60.00.00%7.37.30.00.00%0.70.70.00.00%4.50E+104.50E+100.00E+000.00%
611536.31536.30.00.00%109.8109.80.00.00%227.0227.00.00.00%1.71E+131.71E+130.00E+000.00%
621140.81145.64.80.42%116.4116.80.40.36%205.1205.20.00.01%4.98E+115.09E+111.10E+102.21%
63183.7183.70.00.00%6.06.00.00.00%0.00.00.00.00%0.00E+000.00E+000.00E+000.00%
64187.9187.90.00.00%8.88.80.00.00%0.00.00.00.00%0.00E+000.00E+000.00E+000.00%
65537.6537.60.00.00%36.636.60.00.00%48.548.50.00.00%3.53E+093.53E+090.00E+000.00%
66267.1267.10.00.00%11.111.10.00.00%2.82.80.00.00%3.44E+103.44E+100.00E+000.00%
67322.2322.20.00.00%19.919.90.00.00%13.713.70.00.00%2.38E+102.38E+100.00E+000.00%
TOTAL95107.696657.01549.41.63%7588.27721.7133.61.76%13113.513457.6344.12.62%4.55E+144.67E+141.20E+132.64%
White Oak16739.216963.5224.31.34%1175.41190.615.21.29%3138.93156.017.10.55%1.478E+141.53E+144.88E+123.30%
Neuse78368.479693.51325.11.69%6412.86531.2118.41.85%9974.610301.6326.93.28%3.072E+143.14E+147.12E+122.32%
6-8

Havelock Bypass
ICI Water Quality Study
Table 6.2.2MeanAnnual Pollutant Load Rates for All Subbasins
Total Nitrogen (kg/ha/yr)Total Phosphorus (kg/ha/yr)Total Sediment (kg/ha/yr)Fecal Coliform (counts/ha/yr)
Change Change Change Change
Area No-Over Over Over No-Over No-
Subbasin(hectares)BuildBuildNo-BuildNo-BuildBuildNo-BuildNo-BuildBuildBuildNo-BuildBuildBuild
11252.95.365.870.500.5780.6090.0399.67103.363.693.55E+104.57E+101.02E+10
2379.62.602.600.000.2110.2110.0020.1020.100.001.50E+101.50E+100.00E+00
3939.91.431.430.000.1080.1080.0017.0717.070.005.20E+085.20E+080.00E+00
4764.22.842.870.020.2070.2080.0033.9533.960.002.24E+102.29E+105.23E+08
5545.62.272.270.000.2230.2230.0051.3551.350.009.24E+089.24E+080.00E+00
6564.31.541.540.000.1390.1390.0010.7310.730.006.45E+086.45E+080.00E+00
7779.84.094.090.000.2710.2710.0030.7430.740.005.42E+105.42E+100.00E+00
8302.20.780.780.000.0300.0300.002.522.520.003.12E+073.12E+070.00E+00
9408.90.790.790.000.0340.0340.000.850.850.002.18E+082.18E+080.00E+00
10368.31.701.700.000.1630.1630.0029.3729.370.006.35E+086.35E+080.00E+00
11424.621.5321.610.072.5822.5910.0156.0556.050.008.62E+088.62E+080.00E+00
12400.54.884.930.060.4160.4290.0157.2757.710.435.14E+105.14E+100.00E+00
13963.20.740.740.000.0270.0270.000.540.540.001.01E+081.01E+080.00E+00
14714.52.362.360.000.2400.2400.0052.6252.620.002.04E+092.04E+090.00E+00
15586.52.472.470.000.2460.2460.0078.8478.840.001.82E+091.82E+090.00E+00
16602.82.993.010.020.3060.3080.00112.87115.072.215.06E+095.14E+098.29E+07
17656.62.672.750.080.2380.2490.01128.34133.314.981.24E+101.25E+101.22E+08
18889.80.820.820.010.0390.0390.001.261.640.372.74E+082.73E+08-1.12E+06
19339.62.322.320.000.2220.2220.0048.4448.440.001.68E+091.68E+090.00E+00
20682.00.740.740.000.0250.0250.000.160.160.005.69E+075.69E+070.00E+00
21688.30.750.750.000.0250.0250.000.780.780.002.21E+052.21E+050.00E+00
22278.90.730.730.000.0230.0230.000.050.050.000.00E+000.00E+000.00E+00
23355.00.740.740.000.0240.0240.000.000.000.000.00E+000.00E+000.00E+00
24340.31.571.570.000.1440.1440.0029.5029.500.005.76E+085.76E+080.00E+00
25381.11.751.750.000.1500.1500.006.466.460.007.87E+087.87E+080.00E+00
26819.40.770.770.000.0270.0270.000.240.240.002.04E+072.04E+070.00E+00
27484.25.155.160.010.4730.4730.00116.57116.880.314.48E+104.48E+100.00E+00
28288.731.2231.220.001.4361.4360.0099.4299.420.001.01E+101.01E+100.00E+00
29404.41.781.780.000.1530.1530.0012.0312.030.007.47E+087.47E+080.00E+00
30955.10.490.490.000.0230.0230.000.070.070.001.29E+071.29E+070.00E+00
311105.42.102.100.000.1690.1690.0031.5431.540.009.68E+099.68E+090.00E+00
32423.02.522.580.060.1580.1650.0113.7917.964.165.11E+105.11E+100.00E+00
331268.92.322.320.000.1910.1910.0051.3151.310.004.38E+094.38E+090.00E+00
34394.41.901.900.000.1630.1630.0061.1361.130.005.63E+095.63E+090.00E+00
35715.21.031.030.000.0570.0570.007.797.790.002.45E+092.45E+090.00E+00
36514.56.646.780.130.4910.5040.0174.3678.984.639.50E+109.70E+101.94E+09
37531.53.563.680.120.3770.3930.02102.97108.715.755.40E+095.79E+093.95E+08
38380.93.883.880.000.3920.3920.00111.66111.660.008.77E+098.77E+090.00E+00
39519.82.492.690.200.1720.1950.0216.0129.3513.342.35E+102.35E+100.00E+00
40260.12.392.390.000.1530.1530.0015.0815.080.002.39E+102.39E+100.00E+00
41533.20.920.920.000.0540.0540.001.221.220.001.31E+081.31E+080.00E+00
42559.31.221.220.000.0860.0860.005.505.500.009.49E+089.49E+080.00E+00
43431.91.481.480.000.1130.1130.002.072.070.001.30E+091.30E+090.00E+00
6-9

Havelock Bypass
ICI Water Quality Study
Total Nitrogen (kg/ha/yr)Total Phosphorus (kg/ha/yr)Total Sediment (kg/ha/yr)Fecal Coliform (counts/ha/yr)
Change Change Change Change
Area No-Over Over Over No-Over No-
Subbasin(hectares)BuildBuildNo-BuildNo-BuildBuildNo-BuildNo-BuildBuildBuildNo-BuildBuildBuild
44267.70.960.960.000.0550.0550.004.434.430.002.54E+082.54E+080.00E+00
45467.61.141.330.190.0810.1050.0215.1926.7011.521.83E+082.99E+081.17E+08
46466.70.370.370.000.0230.0230.000.050.050.002.83E+072.83E+070.00E+00
47292.61.081.180.100.0690.0800.011.748.686.944.61E+084.44E+08-1.71E+07
48934.80.910.930.020.0470.0490.002.353.571.232.47E+082.43E+08-4.28E+06
49837.11.561.560.000.1190.1190.0055.6055.600.004.31E+094.31E+090.00E+00
501149.61.881.880.000.1440.1440.0046.0346.030.008.26E+098.26E+090.00E+00
51684.10.930.930.000.0530.0530.000.940.940.004.20E+084.20E+080.00E+00
52398.71.321.320.000.0980.0980.000.570.570.007.20E+087.20E+080.00E+00
53719.72.092.100.010.1600.1610.0055.4155.470.051.03E+101.04E+101.11E+08
54960.95.535.680.140.3960.4030.0192.5493.470.937.46E+107.78E+103.23E+09
55325.56.336.590.250.4010.4150.01104.46106.862.409.06E+109.59E+105.22E+09
56624.64.194.190.000.3020.3020.0081.1481.140.004.07E+104.07E+100.00E+00
58562.20.730.730.000.0230.0230.000.000.000.003.13E+063.13E+060.00E+00
59262.60.730.730.000.0280.0280.000.280.280.001.71E+081.71E+080.00E+00
61316.84.854.850.000.3470.3470.0071.6571.650.005.40E+105.40E+100.00E+00
62507.92.252.260.010.2290.2300.0040.3940.390.019.81E+081.00E+092.17E+07
63313.50.590.590.000.0190.0190.000.010.010.000.00E+000.00E+000.00E+00
64491.50.380.380.000.0180.0180.000.000.000.000.00E+000.00E+000.00E+00
65354.31.521.520.000.1030.1030.0013.6913.690.009.96E+069.96E+060.00E+00
66325.80.820.820.000.0340.0340.000.870.870.001.06E+081.06E+080.00E+00
67264.41.221.220.000.0750.0750.005.195.190.009.00E+079.00E+070.00E+00
TOTAL36727.82.592.630.040.2070.2100.0035.7036.640.941.24E+101.27E+103.27E+08
White Oak6525.02.572.600.030.1800.1820.0048.148.40.262.26E+102.34E+107.48E+08
Neuse30202.82.592.640.040.2120.2160.0033.034.11.081.02E+101.04E+102.36E+08
Minimum0.370.370.000.020.020.000.000.000.000.00E+000.00E+00-1.71E+07
Maximum31.2231.220.502.582.590.03128.34133.3113.349.50E+109.70E+101.02E+10
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6.3Nitrogen Loading to the Neuse River Estuary
Given the concerns about water quality and nutrient loads in the Neuse River estuary, it
is important to examine how the predicted increase in nitrogen loads in the GWLF-E
model compares to the cumulative nutrient loading to the Neuse River estuary. A TMDL
for total nitrogen has been approved by the EPA for the Neuse River estuary. The TMDL
for nitrogen is 8,388 kilograms per day \[kg/d\] (NCDENR, 2001). The GWLF-E model
results for total nitrogen over the 11-year model period were converted to units of
kilograms per day in order to compare the TMDL to predicted increases in estuary inputs
in the No Build and Build scenarios. This comparison is presented in Table 6.3.1.
Table 6.3.1 Project Study Area Nitrogen Loading as a Percentage of TMDL
Nitrogen Loading to the Neuse River Estuary
Average Annual Average Daily
% of TMDL to
LoadLoad
Scenario
Estuary
(kg/yr)(kg/day)
No Build95,107.6 260.63.11%
Build96,657.0 264.83.16%
Predicted total nitrogen loads for the project study area in the No Build scenario are
calculated to be 3.11% of the allowable load to the estuary. The Build scenario results in
an increase of 0.04 percentage points of the allowable load to the estuary. This increase
in loads as a percentage of the TMDL is negligible. However, any increase in loads over
existing conditions may have an effect on water quality in the estuary.
6.4Verification of Model Results
No stream flowdata within the study area wasavailable 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 differencebetween 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 studies.
Table6.4.1 presents predicted pollutant loads from the current GWLF analysis as well
as those fromfourGWLF modeling studies in North Carolina and additional literature
values. The subbasinranges of reported values from the modeling studies were
standardized to areal load rates for purposes of comparison.
Threeof the fourGWLF 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 this study.
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When evaluating thereported load values in Table 6.4.1,consideration should be given
to the differences in study area characteristics. For example, the studydescribed in
CH2M HILL (2003) wasperformed on a rural watershedand hence reflectsthe impact of
significant areas of agricultural land. The Morgan Creek study by Tetra Tech (2004)
encompassed the Town of Chapel Hill. The Stantec (2006) study was located on the
inner Coastal Plain in a smaller, urbanizing watershed.
Nutrient and sediment pollutant load ranges for literature values, in addition to the results
of this study are presented in Table 6.4.1. Evaluation of the load values demonstrate that
the maximum values for sediment and phosphorus are within the range of literature
values. The maximum load rate for total nitrogen is slightly higher than reported values;
however, this maximum occurred in Subbasin 31, which is entirely comprised of high
density urban land uses associated with the MCAS Cherry Pointair station and runway.
Minimum pollutant loading rates for the model study area are below the reported
literature values for TN, TP, and sediment. This is not unexpected given that these low
pollutant load rates occur in subbasins predominated by wetland land use types which
yield very low pollutant loads, particularly when compared to the rural, urban, and mixed
land use types of the literature watersheds. Elevated sediment loading in CH2M Hill
(2003) is derived mostly from row crop agricultural land uses.
Literature values for fecal coliform load modeling in GWLF are not common. One study
was conducted on the Monroe Connector using a GWLF and RUNQUAL hybrid model
(PBS&J,2010). Fecal coliform load rates in this study varied from 2.69e8 to 7.31e9
counts/ha/yr. Land use within the Monroe study area consisted of rural and urban uses.
Additionally, literature values for fecal coliform studies conducted in North Carolina using
other modeling software were investigated. The TMDL developed for Crowders Creek
(NCDENR2004), located in the Outer Coastal Plain of North and South Carolina, was
modeled using WARMF. The model results reported fecal coliform loading rates by land
use type, ranging from 0 to 1.21e11 counts/ha/yr for wetlands and high intensity
development, respectively. Evaluation of the fecal coliform loading rates within the
Havelock model study area demonstrated that the minimum and maximum values are
within the range of literature values. Loading rates ranged from 0 to 9.5e10
counts/ha/year. The lowest loads occurred in subbasins predominated by wetland and
the highest loads occurred in subbasins with predominantly urban development or a
large number of septic systems.
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Table 6.4.1Comparison of Model Loading Rates to the Literature
Watershed
Total N Total P Sediment
StudyLocation
(kg/ha/yr)(kg/ha/yr)(kg/ha/yr)
Land Use
MinMaxMinMaxMinMax
Outer Coastal
Current urban and
Plain
0.431.20.022.60128
Study*undeveloped
NC
Inner Coastal
Stantec
Plain
urban3.39.80.71.942127
(2006)*
NC
Inner Coastal
CH2M HILL
Plain
rural2.580.71.929361
(2003)*
NC
Piedmont NC
Tetra Tech
mixed1.826.90.32.8----
Jordan Lake
(2003)*
Watershed
Piedmont NC
Tetra Tech
mixed3.716.10.31.9----
Morgan Creek
(2004)*
Watershed
Compilation of
Literature
Variousvarious0.72803.8----
Export
Coefficients **
* GWLF Modeling 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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Exhibit6.2.1 Increase in Nutrient Pollutant Loading Rates
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Exhibit6.2.2 Increase in Sediment and Fecal Coliform Pollutant Loading Rates
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7STREAM 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 scenario relative to that of the No-Buildscenario. 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.
7.1Technical 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:
S= (1000 / CN)–10
UU
Where:CN= Runoff Curve Number for Land Use Type U
U
The portion of runoff contributed by each land use type within a given watershed is
calculated by:
2
Q= (P -0.2 * S)/ (P + 0.8 * S)
UUU
Where:Q= Flow Volume contributed by Land Use Type U
U
P = rainfall
The total flow volume is then estimated with the equation:
Q=(A* Q)
TOTALUUU
Where:Q= Total Flow Volume contributed by all Land Uses within the watershed
TOTAL
evaluated
A= Area of Land Use Type U
U
The runoff curve numbers utilized in this analysis are presented in Table 7.1.1and were
derived from the TR-55 manual (SCS, 1986). 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 two years. The
rainfall volume for the one-year, 24-hour storm is approximately 9 cm or 3.5 inches
(USDC, 1961).
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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.
Table 7.1.1Selected Curve Numbers
SOIL HYDROLOGIC GROUP
LAND USEABCD
Low-Density Residential46657782
Medium-Density Residential61758387
High-Density Residential77859092
Medium-Density Mixed77859092
High-Density Mixed81889193
Road83899293
Turf/Golf39617480
Cropland67788589
Pasture/Hay49697984
Disturbed77868194
Open39617480
Forest30557077
Wetland36607379
Water98989898
7.2Results
The above equations and assumptions were executed on the Build and No-Buildland
use scenarios presented in Section 5.2.Theresults comparing the two scenarios for the
65 GWLF subbasins are presented in Table 7.2.1.
The analysis suggests that development of the Build scenario would have no impact on
storm event flowvolumes for theone-year, 24-hour storm in 46of the 65 subbasins.
Minimal impact (i.e. less than 1% increase in runoff) will occur in 9subbasins, and some
impact willoccur in the remaining 10subbasins,with the greatest increase in Subbasin
39.
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Table 7.2.1Storm Flow Volumes (cubic meters) for the One-Year, 24-Hour Storm
%
% Change Change
Over No-Over No-
SubbasinNo-BuildBuildBuildSubbasinNo-BuildBuildBuild
1381,921388,5301.73%34101,899101,8990.00%
249,75049,7500.00%35224,637224,6370.00%
3322,075322,0750.00%36189,984193,7461.98%
4279,912280,0590.05%37221,698225,9301.91%
5136,105136,1050.00%38209,497209,4970.00%
6126,169126,1690.00%39144,176163,05113.09%
7182,984182,9840.00%4076,57776,5770.00%
892,55992,5590.00%41156,998156,9980.00%
9128,071128,0710.00%42164,357164,3570.00%
1087,25987,2590.00%43132,985132,9850.00%
11134,182134,1820.00%4472,84672,8460.00%
12134,546134,7420.15%45149,983161,8347.90%
13285,746285,7460.00%46314,591314,5910.00%
14267,059267,0590.00%4794,44098,3534.14%
15218,712218,7120.00%48279,496282,6431.13%
16240,150242,6781.05%49272,780272,7790.00%
17223,869235,4825.19%50385,045385,0500.00%
18283,609284,2490.23%51226,822226,8220.00%
19124,873124,8730.00%52140,328140,3280.00%
20205,602205,6020.00%53239,067239,1410.03%
21207,517207,5170.00%54319,105320,2930.37%
2283,57883,5780.00%55121,304121,8950.49%
23106,356106,3560.00%56219,550219,5500.00%
24107,655107,6550.00%58168,372168,3720.00%
2575,87875,8780.00%5981,85881,8580.00%
26244,195244,1950.00%6064,04364,5970.87%
27208,695208,8750.09%6193,04793,0470.00%
28142,000142,0000.00%62149,314149,4350.08%
2979,50979,5090.00%63128,730128,7300.00%
30530,577530,5770.00%65116,883116,8830.00%
31306,161306,1610.00%66101,116101,1160.00%
32136,797141,1983.22%6790,41390,4130.00%
33476,868476,8680.00%Total12,300,87112,374,9450.61%
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8CONCLUSIONS
Predictions from the modeling analyses indicatethat the increase in pollutant loads and
stormflow over the entire watershed is low.
This is due to a number of factors including the use of stormwater controls to mitigate
the effects of new development and the low population growth and anticipated housing
needs in the study area. Previous studies of this area had indicated over 1% growthin
population a year and had then predicted residential development to meet or exceed that
need. More recent data supports the assumption of moderate population growth and an
increase in housing to match those needs. This results in a small increase from existing
land use to the No-Buildscenario. Adding an additional 15% for the Build scenario does
not greatly impact the overall developed land acreage. The result is a small impact to
pollutant loading in the watershed.
However, direct impacts from the proposed road yield high increases in pollutant loads in
undeveloped basins with low baseline loads. This can be even further mitigated with
additional stormwater controls on drainage from the proposed road. Unsewered areas
where growth could occur in the Build scenario have an impact attributed to septic
systems. However, additional zoning and the extension of sewer service to these areas
could mitigate the projected impact.
The analysis shows that the Bypass will not increase fecal coliform pollutant loadsin the
CherryBranch or Sassafras Branchsubbasins, waters impaired for loss of shellfish
harvesting use.
Nutrients are a concern throughout the Neuse portion of the study area due to the
impairment for chlorophyll a.Nutrient loading rates exceed theNeuse NSW stormwater
program limit of 4 kg/ha/yr in eightof the subbasins that drain to the Neuse River.
However,this is the case for the Build and No-Buildscenarios and the increase in mean
annual loads over the No-Buildscenariofor the Neuse portionof the study areais less
than 2% for TN and TP. The increased loads are related to the induced residential
growth and associated septic systems.
Finally, the increase to sediment loading rates is less than 1 kg/ha/yr. The highest
increases occur along the Bypass although loads still remain low in comparison to other
undeveloped or low-density developed subbasins.
While development in the area will result in increases in pollutant loads to impaired
waterbodies, the increases suggested by the modeling analysis show comparitivelylittle
increase over the No-Buildscenario.
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