Final Presentation

1. Hydrologic Modeling of Development
Effects on an Untouched Coastal Watershed
Julianna Corbin, Hunter Morgan, Evan Patrohay, Ty Williams
Clemson University, Clemson, SC
December 3, 2020

2. Outline
● Introduction
○ Background
○ Rationale
○ Objectives
○ Approaches
● Literature Review
● Materials and Methods
● Results
● Recommendations
● Acknowledgements

3. Introduction

4. Background
● Above image shows the urban centers of the US
○ Southeastern Trend:
■ Higher densities
■ More urban centers
● Below image shows state of forests in the US
○ Almost everywhere in the southeast
contains forests that are regularly cut
○ With population growth trends, some of
this forest is never replanted
● EPA projects 2,029 mi² of forest in SC to be
cleared for urban use by 2050

5. Background
● Charleston Metro Area (CMA) population = 802,122 people
● The area is growing at:
○ ×3 the population growth rate of the USA
○ ×2 the population growth rate of South Carolina
● 30 new residents move in per day
○ Charleston (+13%)
○ North Charleston (+16%)
○ Mount Pleasant (+32%)
Percent growth from 2010-2019

6. Background
● The city is bounded by the Atlantic
Ocean to the east
● Constrained by the harbor
○ Ashley, Cooper, Wando Rivers
● Much of the land area is marshy and not
fitting for development
Means the city has to expand to the north & west!
Towards the Francis Marion Forest.
FMNF

7. Background
● Projected expansion of
development areas in the
Greater Charleston area
○ Towards Francis Marion
National Forest where
Santee Experimental
Forest is located

8. Background
● Mission of the Santee Experimental Forest:
○ Understand coastal plain forest hydrology
○ Silviculture and forest management
● Now, that Charleston, SC is encroaching into
the Francis Marion National Forest:
○ Wish to understand how will
imperviousness impacts forest hydrology
and ecosystem functions

9. Background
● Watershed of interest: WS80
○ 1st order watershed
○ ~ 400 acres
○ Drains into a tributary
of the Cooper River
○ Last logged in 1937
○ Most undisturbed
watershed in SEF since
that time

10. Background - Urbanization and Stormwater Flooding
● Natural land
○ Vegetation and soil intercept and soak up rainfall and slow runoff
○ Momentum of runoff is reduced and roots anchor the soil, reducing erosion
● Developed land
○ Rainfall hits impervious surfaces intensifies runoff
■ Rooftops, roads, parking lots, pavement
○ Natural water cycle is changed
○ Streets collect stormwater and channel it into waterways
○ Pollutants from urban surfaces are collected and transported into lakes, streams, and the ocean
■ Decreased water quality
○ Storm drains directly transport runoff and pollutants to bodies of water
○ Greater frequency and severity of flooding, channel erosion, and destruction of aquatic ecosystems

11. Background - Urbanization and Stormwater Flooding

12. Rationale
● Running urban hydrologic analyses is important for future land development
○ How does impervious surfaces affect hydrology here?
● WS80’s preservation makes it an excellent “control” for these hydrologic analyses
○ Assumed a typical Atlantic Coastal Plain Forested Watershed
○ Running peak flow / runoff modeling will give best approximation of a natural
watershed in this region
● Comparing results with current literature will expand datasets and increase
confidence in the mission of Santee Experimental Forest

13. Objectives
The objectives of this project are to:
1. Assess the pre-development hydrologic conditions of Watershed 80, located within the USDA
Forest Service’s Santee Experimental Forest northeast of Charleston, SC, using three different
stormwater hydrology models
(The Rational Method, NRCS TR-55 model, and USGS Regional Regression Equations).
1. Simulate runoff volume and peak flow rate with varying levels of urbanization, defined by 0%,
5%, 10%, and 15% imperviousness on Watershed 80 using the same models and compare the
values obtained to real-life data.
2. Design a culvert to transport the amount of peak discharge at the outlet of watershed 80
calculated from the model with the highest peak-flow at a 100-yr return period.

14. Approaches
Task 01: To obtain aerial, visual, soil, and elevation maps of Watershed 80
Task 02: To procure rainfall intensity data and stream flow data from the SEF website
Task 03: To delineate sub-basins and drainage area on GIS and Civil 3D
Task 04: To simulate peak flow and runoff values of the watershed using WinTR-55
Task 05: To perform the same calculations using the USGS Regression Equation
Task 06: To utilize the Rational Method for further calculations of peak flow and runoff values
Task 07: To repeat tasks 4-6 with three increasing iterations of imperviousness
Task 08: To design a culvert for a 100-year storm

16. Literature Review

17. The Southeast United States
● Approximately 55% of the Southeast US is forested
○ Timber production has increased dramatically
■ Doubled in the past few decades
■ Est. 4.9 million hectares of former forest
expected to be lost to development by
2020
○ Shift in maintenance has created a significant
nonpoint source pollution rise of sediments
● Some of this forest is not returning due to population
settlements

18. The Southern Coastal Plain
● Southern Coastal Plain
○ Barrier islands, coastal lagoons, marshes,
flat plains, swampy lowlands
○ Characterized by wet soils, low elevation,
little relief
● Location of WS80 and Charleston

19. The Southern Coastal Plain
Flat Plains Coastal Lagoons Barrier Islands
MarshesSwamps

20. Urban Stormwater Flow
● Urbanization presents significant danger to the
integrity of surrounding streams
○ Riparian buffers can be wiped out from
intense peak discharge values
○ Floodplain damage occurs during large
storm events
● Damaged buffers lead to increased exposure, UV
radiation and higher water temperatures
○ Threatens natural habitats

21. Urban Stormwater Flow
● Urban runoff contributes to polluted streams and
decreased water quality
○ Harmful to natural habitats
○ Trash and debris flows from streets into
the stream system
● This severely degrades the quality of the stream
and can lead to irreversible damage

22. Stormwater Flooding in Charleston
● Charleston flooded 1 out of 5 rain events in 2019
● Harbor flood gauges exceeded 7.0 feet 89 times
○ Flooding occurs at 7.0 ft

23. Stormwater Flooding in Charleston

24. Stormwater Management
● Municipal stormwater infrastructure can be used to
control flooding and convey runoff away from streets
○ Reduces pollution, erosion in local streams, and
sewer overflows
○ Includes gravity and force pipes, lateral line pipes,
catch basins, detention basins, manholes, valves,
pumps, and culverts
● Efforts are growing across the country as the need for
these systems and programs increase

25. Low Impact Design
● Low impact design (or green infrastructure) is used
to retain water within the landscape and reduce
downstream discharge
○ Includes bioretention, biofiltration,
infiltration basins, media filters, porous
pavements, green streets, and bioswales
● Integration stormwater management and low
impact design techniques
○ Used to improve retention and infiltration
○ Reduces peak discharge and flooding
○ Promotes the environmental restoration of
streams and waterbodies

26. WS8O
● Minimal disturbance within watershed
○ Latest human disturbance was in 1936 then the
US Forest Service acquired land
○ Only major disturbance since was a natural one
- Hurricane Hugo 1989
■ >80% of forest canopy was severely
damaged
■ Current forest stands within WS80 have
regenerated back to pre-hurricane levels
based on a study from Clemson in 2014
○ Lack of disturbance make WS80 an ideal study
subject for hydrologic studies of coastal forests
in SC

27. WS8O
● Characteristics:
○ Is 23% wetland
○ Slopes <1%
○ Soils: Primarily sandy loams, clay subsoils -- poorly drained
○ Vegetation: Loblolly pine, longleaf pine, cypress, sweet gum
● Weather characteristics:
○ Mean annual rainfall → 54 inches
○ Mean annual temperature → 64°F
● Monitored for:
○ Meteorological data, flow gauging, groundwater, water
quality
○ Contains a v-notch weir at outflow

28. Climate Change Risks
● Risk Management must take into account:
○ Biophysical factors influencing future stormflow
○ Socioeconomic factors influencing community adaptation to alterations in stormflow
● Projections:
○ 4-12°F increase in southeast US temperatures by 2100
○ More extreme hydrological events → frequent +10 yr storms
○ Population growth + urban land cover increase 101-192% by 2060

29. Materials &
Methods

30. Materials
● Santee Experimental Forest published datasets
○ GIS
○ Weather stations
● Mapping using ArcGIS software
● Mapping using AutoCAD Civil 3D
● Peak flow modeling using WinTR-55
● Low-impact design testing using L-THIA
● Data processing using Microsoft Excel
● Peak flow comparisons using NOAA published datasets
● Culvert design using HY-8 and Solidworks softwares

31. Soil Data for Watershed WS80
● NRCS resources used in collecting necessary soil
data
● Intended use is for proposal of development on
soils of different hydrologic soil groups for
comparison

32. Watershed Delineation
● Published data sets were utilized to input
layers into ArcGIS
● Data was also input into AutoCAD Civil
3D for delineation
● Drainage areas were collected based on
delineation
East Sub-Basin West Sub-Basin
Area [acres] Area [acres]
198 191

33. Modeling Parameters
Percent Imperviousness
0%
5%
10%
15%
Return Period Storms
2 year 5 year 10 year
25 year 50 year 100 year
200 year

34. Modeling Method #1 - Rational Method
● Developed by Thomas Mulvaney in 1851 and introduced in the US by Emil Kuichling in 1889
● Empirical formula used to estimate peak runoff discharge (Q) in small watersheds
● Function of drainage basin size, characteristics, and precipitation
Thomas Mulvaney Emil Kuichling

35. The Rational Method Equation:
Q= CiA
where
Q = peak flow rate [ft3/s]
C = runoff coefficient [dimensionless]
i = average rainfall intensity-duration [in/hr]
A = drainage area [acres]

36. Runoff Coefficient (C)
● Related to the abstractive and diffusive
elements found throughout drainage
basins
● Attributed to basin size, shape,
topography, soil, geology, and land use
● Range from 0 to 1
● Table of example C values from a
manual published by the SC
Department of Transportation

37. Rainfall intensity (i)
● Calculated by measuring
the amount of rainfall per
unit time in a specific
location
● The unit of time selected
for the Rational Method is
the same as the time of
concentration
● Rainfall intensity curve of
WS80 from NOAA
estimated i-values

38. Area (A)
● The purpose of the Rational Method is to estimate peak discharge
from smaller watersheds
○ Recommended that it be applied to watersheds with drainage areas up 200
acres
○ Valid up to 300 acres for low-lying tidewater areas
● WS80 exceeds the size limitations of the Rational Method
○ Area of about 389 acres

39. Assumptions and Limitations of the Rational Method
When applying the Rational Method it is assumed:
1. That precipitation is uniform over the entire basin
2. The precipitation does not vary with time or space
3. The duration of the storm is equal to the time of concentration
4. The designed storm of a specified frequency produces the design flood of the same frequency
5. That the basin area increases roughly in proportion to increases in length
6. The time of concentration is relatively short and independent of storm intensity
7. That the runoff coefficient does not vary with storm intensity or antecedent soil moisture
8. The runoff is dominated by overland flow
9. The basin storage effects are negligible

40. Modeling Method #2 - USGS Regression Equations
● In 2014, the USGS worked in collaboration with the SCDOT to gather data from 488
stream gauges across the east coast
● Done for 3 hydrologic regions (HRs):
○ HR1 - Piedmont
○ HR3 - Sand Hills
○ HR4 - Coastal Plain ← of interest for us
● Created specific regression equations based on:
○ Return period
○ Stream gauge peak flows
○ NOAA weather data

41. Modeling Method #2 - USGS Regression Equations
Peak Flow = 𝑓(Area, % Annual Exceedance (AEP), % Imperviousness)
The regression equations used are governed by the following parameters:

42. Modeling Method #2 - USGS Regression Equations
DRNAREA = drainage area [mi²]
IMPNLCD06 = % impervious area [-]
DEVNLCD06 = % developed land
I24H50Y = 24-hr, 50 yr maximum
precipitation [in]
Special note: Given the acceleration of climate change, the I24H50Y is variable
and will not always accurately represent the climate of the region.

43. Modeling Method #2 - USGS Regression Equations
Variance of Prediction Standard Error of Prediction
where
γ2
xi
U
x‘i
is the model error variance
variables for site i, augmented by 1 as the
first element
is the covariance matric for the regression
is the transpose of xi
where
Sp,ave
AVP
is the average standard error of
prediction, in percent
the average variance of prediction

44. Modeling Method #2 - USGS Regression Equations
Average Variance of Prediction
and
Standard Error of Prediction
*based on hydrologic region and return period.
● Used to give a general idea of an
estimated range of peak flow values
● Based on inherent uncertainty of the
regression equations

45. Limitations of the USGS Regression Equations:
1. Generally for use in areas with <10% impervious area (rural areas)
a. Study used limit of 15% imperviousness
2. Drainage area should be > 0.1 mi²
a. This watershed is 0.6 mi² in area
3. Not appropriate where significant man-made structures alter flow
a. V-notch weir at outlet, assumed non-significant
4. Do not apply where tidal effects are found
Modeling Method #2 - USGS Regression Equations

46. Modeling Method #3 - WinTR-55
● Single event small watershed
hydrology analysis program
● First launched in 1975
○ Several updates since
● Managed by the Natural Resources
Conservation Service (NRCS)

47. Modeling Method #3 - WinTR-55
● User inputs
○ Sub-basin drainage areas
○ Sub-basin Curve Numbers
○ Time of Concentration
○ Rainfall
● Computes outflow of watershed
● Can incorporate outflow through
culverts

48. WinTR-55 Limitations
● Sub-basin areas should be at least one acre
● No more than 25 square miles total
● Sheet flow must be less than 100 feet
● No more than ten sub-basins

49. Study of Low-Impact Design (LID)
● Long Term Hydrologic Impact Analysis (L-THIA)
○ Estimates changes in runoff from
past/proposed development
○ Based on climate data, soil type, & land use
● Enables study on how LID will reduce runoff based
on the % imperviousness of this study

50. Proposed Culvert Design
Design Limitations
● 30 ft wide
● 4.5 ft maximum diameter

51. HY-8 Advantages and Limitations
Advantages
● Simple user interface
● No hydraulic cross-section or survey
data required
● Relatively adaptive and easy to alter with
a change in design requirements
Limitations
● Only single stream crossings
● Not appropriate for bridges with piers
● Assumes the headwater section is a pool,
rather than a riffle

52. Results

53. Results - Rational Method
● Data for WS80 obtained
from SEF historical rainfall
and streamflow database
● Peak rainfall intensity
○ Tc = 3 hr
● Peak runoff (Q)
● Prior 2-day and 5-day
accumulated rainfall
Rainfall Event Peak rainfall intensity
(i) [in/(3-hr)]
Peak Runoff
(Q) [ft3/s]
2-day prior
total rainfall [in]
5-day prior total
rainfall [in]
Dec 14-15 2018 1.02 47 0.01 1.23
Feb 2-15 2016 1.52 27 0.00 0.01
Oct 6-19 2016
(Hurricane Matthew)
3.46 206 0.00 0.00
Jul 9-15 2017 2.85 8.5 0.20 0.30
Sep 10-23 2017
(Tropical Storm Irma)
2.65 60 0.03 0.24
Aug 29 - Sep 13 2019
(Hurricane Dorian)
2.13 50 1.10 1.06
Sep 29 - Oct 8 2015
(Hurricane Joaquin)
6.95 610 4.59 4.38

54. Results - Rational Method
● Linear regression of peak runoff (Q) vs rainfall intensity (i), total rainfall of 2-days and 5-days prior:
● Q vs i
● R2 = 0.88
● Q vs 2-day prior rainfall
● R2 = 0.83
● Q vs 5-day prior rainfall
● R2 = 0.76

55. Results - Rational Method
● Multivariate regression
○ Used to compare changes in each
combination to explain which variable
can determine the peak flow response
● Data from rainfall intensity biased by single
extreme value
○ Removing extreme point did not provide
significant information
● These events alone do not explain the variance
in peak flow
○ Parameters such as distributed soil moisture or
evapotranspiration could influence peak flow
Regression
P-value
Rainfall
intensity
2-day
rainfall
5-day
rainfall
Peak runoff vs rainfall
intensity and 2-day rainfall
0.006 0.92 -
Peak runoff vs rainfall
intensity and 5-day rainfall
0.005 - 0.76
Peak runoff vs rainfall
intensity, 2-day rainfall, and
5-day rainfall
0.031 0.17 0.16

56. Rainfall Event Q [ft3/s] i [in/3-hr] A [acres] C (= Q/iA)
Dec 14-15 2018 47 1.02
389
0.117
Feb 2-15 2016 27 1.52 0.046
Oct 6-19 2016 (Hurricane Matthew) 206 3.46 0.153
Jul 9-15 2017 8.5 2.85 0.008
Sep 10-23 2017 (Tropical Storm Irma) 60 2.65 0.058
Aug 29 - Sep 13 2019 (Hurricane
Dorian)
50 2.13 0.061
Sep 29 - Oct 8 2015 (Hurricane Joaquin) 610 6.95 0.225
Determination of C-value
● INPUTS: Q, i, A ● OUTPUT: C

57. Average C values
Average 0.096
Standard
Deviation
0.069
Avg C 0.096
Avg C + 10% 0.105
Avg C + 15% 0.119
Avg C + 25% 0.143

58. Pre Development Results
Return period [yr]
Rainfall
intensity(i)
[in/hr]
Area (A)
[acres]
Runoff coefficient (C) [-]
Cavg C+10% C+20% C+25%
2 0.88
389 0.096 0.105 0.115 0.119
5 1.21
10 1.49
25 1.95
50 2.39
100 2.91
● INPUTS: C, i, A

59. Pre Development Results
Return
period [yr]
Peak flow rate (Q) [ft3/s]
Qavg [ft3/s] Q+10%
[ft3/s]
Q+20%
[ft3/s]
Q+25%
[ft3/s]
2 32 36 39 41
5 45 49 54 56
10 55 61 66 69
25 72 79 87 91
50 89 98 107 111
100 108 119 130 135
● OUTPUT: Q

60. Post Development Results
The following equation was used to calculate the weighted average C-value for the simulated
development areas:
CW = (C1A1 + C2A2 + … + CnAn)/(A1 + A2 + … An)
where
CW = weighted runoff coefficient [-]
C = runoff coefficient [-]
A = drainage area [acres]

61. Post Development Results
● Rational Method Equation: Q = CiA
Return period
[yr]
i [in/hr] A0 [acres] A5% [acres] A10% [acres] A15% [acres] Cavg Cres Weighted
C5%
Weighted
C10%
Weighted
C15%
2 0.88
389 20 39 58 0.096 0.400 0.111 0.126 0.141
5 1.21
10 1.49
25 1.95
50 2.39
100 2.91
● INPUTS: C, i, and A

62. Post Development Results
● OUTPUT: Q
Return Period Q5% [ft3/s] Q10% [ft3/s] Q15% [ft3/s]
2 38 43 48
5 52 59 66
10 64 73 82.
25 84 95 107
50 103 117 132
100 125 142 160

63. Results - USGS Regression Equations
● INPUTS:
○ Area = 0.6 mi²
○ Imperviousness = 0%, 5%, 10%, 15%
○ 50-yr, 24-hr Intensity = 12.3 in
○ AEP = 50%, 20%, 10%, 4%, 2%, 1%, 0.5%
○ Changed to 2, 5, 10, 25, 50, 100, 200-yr return periods
● OUTPUTS:
○ Peak flow values (Q) [cfs]
○ For comparison with other models
Peak Flow = 𝑓(Area, % Annual Exceedance (AEP), % imperviousness)

64. Results - USGS Regression Equations
Figure 1: Pre-development peak flow Figure 2: Increase in flow by imperviousness

65. Results - USGS Regression Equations
Trends:
● Peak flow and imperviousness have a highly linear relationship
● Greatest difference in flow occurs for a 25-yr storm (Δ109 cfs from 0% - 15%)
○ Smaller differences in flow at either extreme

66. Results - USGS Regression Equations
● Increase in peak flow is more dramatic
for smaller return-period storms
○ Common storms will on average
cause more damage
● Flows from large return-period storms
are not affected as much
○ But their flow rates are more
unpredictable

67. USGS Regression Equations using NOAA values
● NOAA 24-hr 50-yr intensity = 8.85 in
○ WS80 value was higher because
Hurricanes Joaquin & Matthews
and tropical storms factored in
● Results shown:
○ Peak flows reduced in every case
○ Reduced by close to 50% at and
above 50-yr storms

68. WinTR-55 Inputs
Land Use Information
● Used a Curve Number of 67
for pre development and
undeveloped conditions (Epps
et al 2013)
● Used Curve Number of 98 for
simulated developed area
● Used sub basin delineation
areas from GIS and Civil3D
models
Rainfall Data
● Used depths for 2, 5, 10,
25, 50, 100, and 200 year
storms derived by
Amatya et al.
Time of Concentration
● Used a time of
concentration of 3 hours
derived by Amatya et al.
● Calculated a time of
concentration of 1.66
hours for simulated
development

69. Results - WinTR-55

70. Results - WinTR-55
0% Imperviousness
Pre Development

71. Results - WinTR-55
5% Imperviousness
Post Development

72. Results - WinTR-55
10% Imperviousness
Post Development

73. Results - WinTR-55
15% Imperviousness
Post Development

74. Comparison of Models
Figure 1: Comparison of Models at Pre-development Figure 2: Comparison of Models at 10% Imperviousness

75. Results - Low Impact Design
Using:
● Bioswales
● Downspout disconnections
● Green roofs
● Porous pavement
● Natural resource conservation
Models functions by calculating reduction in curve
number by LID and applying to runoff equations.

76. With 50% LID
● Avg. runoff volume reduced from
0.24 → 0.21 acre-ft
● Annual runoff depth reduced from
4.84 → 4.28 in
● Unweighted residential depth
reduced from 8.38 → 4.69 in

77. With 100% LID
● Avg. runoff volume reduced from
0.24 → 0.17 acre-ft (-20%)
● Annual runoff depth reduced from
4.84 → 3.59 in (-16%)
● Unweighted residential depth
reduced from 8.38 → 0.09 in (-98%)
Even on just 15% of the land,
LID practices are proven to
have a very considerable
impact on runoff.

78. Culvert Design: Rationale
● The existing box culvert at the outlet of WS80 will
not be able to withstand the peak flow of a 100-
year storm if the land is developed
● It is necessary to design a larger culvert to be able
to pass the water from a 100-year storm,
assuming 15% impervious ground cover
● The simulated results were considered when
determining the metrics for the proposed culvert

79. Risks of a Failing Culvert

80. Culvert Design
● HY-8 interface and design
specifications
● The inputs are:
○ Storm discharge data
○ Tailwater characteristics
○ Roadway dimensions
○ Culvert data
○ General site info
● Outputs:
○ 2-D model
○ Cross Rating Curve

81. Culvert Design
● HY-8 used an iterative process
to generate a 2-D model
representative of the proposed
culvert
● The model shows the culvert
and water passage looking from
a side view

82. Culvert Design
● Minimum discharge = 448 cfs
● Design discharge = 511 cfs
● Maximum discharge = 670 cfs
● The culvert is designed to pass all 3
scenarios and not overtop until a storm
peak flow reaches nearly 695 cfs

83. Culvert Cross-Rating Curve

84. 3-Dimensional Culvert Model
● Solidworks was used to produce a 3-dimensional
representation of the culvert that was designed
● The dimensions and characteristics produced
from HY-8 were used to generate this
Solidworks model

85. Culvert Design: Cost-Benefit Analysis
IN GENERAL:
● Benefits
○ Increased driving safety
○ Decreased traffic interruption
due to roadway flooding
● Costs
○ Materials
○ Excavation
○ Construction
○ Maintenance
DESIGN OBJECTIVES:
1. Safely provide public transportation
2. Remain stable and pass worst-case flooding scenario
3. Minimize maintenance problems
4. Reduce upstream flooding potential
5. Control scour and erosion above/below culvert

86. ● Shape
○ Circular
■ Most common, very efficient, support high loads
○ Elliptical/Arch
■ Use when height limited, allows for natural streambed
■ Expensive, scour of increased concern
○ Box → chosen
■ For the largest projects, can add width with more cells
■ Usually precast (quick construction but more delicate
installation)
Culvert Design: Cost-Benefit Analysis

87. ● Material
○ Corrugated Metal
■ Can be corroded if water is acidic
■ Infeasible for this size
○ Plastic (PVC)
■ Smooth, can increase flow velocities
■ Infeasible for this size
○ Concrete → chosen
■ Strong, long service life, relatively cheap
■ Weak to chipping over time
■ Cast in large amounts, fits channel geometry best
Culvert Design: Cost-Benefit Analysis

88. ● Service Life
○ Depends on importance of road
○ This road can be rebuilt in a relatively short time, a shorter service
life will be selected
● Risk Analysis
○ Minor stream crossings are “somewhat simplistic”
○ Total Expected Cost = Annual capital cost + Annual economic risk
○ When optimized → Least Total Expected Cost (LTEC)
● Organism Passage
○ Not necessary in this case
Culvert Design: Cost-Benefit Analysis

89. ● Estimated Dollar Cost of Installation (Cost scenarios of river crossings ~ USDA)
○ Most excavation money saved, hole already exists
○ Equipment → ~$10,000 total for backhoe, concrete pump, trucks
○ Labor → ~$30-40/hr (low end = general, high end = skilled/equipment operators)
○ Time → ~40-100 hrs (low end = general, high end = equipment operation)
■ Assume 1 person general labor, 2 persons skilled/equipment
■ ~$20,000 total
● Examples for Comparison (Minnesota Culvert Analysis)
○ Was a study of TOTAL COST of full culvert replacement, similar to this project
○ Culvert structure typically 50-70% of total costs
○ 28’ wide → $71,795
○ 30’ wide → $81,811
○ 36’ wide → $121,885
Culvert Design: Cost-Benefit Analysis

91. Acknowledgements

92. Acknowledgements
● Dr. Christophe Darnault, Clemson University
● Dr. Rui Xiao, Clemson University
● Dr. Devendra Amatya, USDA Forest Service
● Andy Harrison, USDA Forest Services
● Dr. Andrzej Wałȩga, University of Agriculture,
Krakow, Poland
Photo from our socially distant September
24 site visit to SEF. Pictured from L to R,
Andy Harrison, Dr. Amatya, Ty, Julianna,
Hunter, and Evan.

93. Thank You