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Velocity Reduction Factors in Near Boundary Flow and the
Effect on Fish Passage Through Culverts
Keelan Michael Jensen
A project report submitted to the faculty of Brigham Young University
in partial fulfillment of the requirements for the degree of
Master of Science
Rollin H. Hotchkiss, Chair E. James Nelson
A. Woodruff Miller
Department of Civil and Environmental Engineering
Brigham Young University
April 2014
Copyright © 2014 Keelan Michael Jensen
All Rights Reserved
ABSTRACT
Velocity Reduction Factors in Near Boundary Flow and the Effect on Fish Passage
Keelan Michael Jensen
Department of Civil and Environmental Engineering, BYU Master of Science
Fish passage assessment of culverts is often done by comparing hydraulic characteristics
of the culvert flow (such as velocity or depth) to fish swimming capabilities. A survey revealed that twenty states have fish passage guidelines. One of the most common applications is to compare the average velocity in the culvert barrel to the prolonged swimming speed of the fish species of interest. However, this method is often overly conservative, because it does not account for areas of low velocity in a culvert that fish can utilize when velocities are excessive. The program FishXing has the ability to account for these areas of reduced velocity by using velocity reduction factors, but the feature is rarely used due to a lack of knowledge on the topic. This study developed an equation that can determine velocity reduction factors for a culvert based on the relative roughness of the culvert and the depth at which the fish swims. This equation was shown to provide reasonable and conservative estimates for velocity reduction factors in non-embedded culverts. The effect of velocity reduction factors on predicted passage rates was also investigated. The use of velocity reduction factors in fish passage assessment was found to increase passage rates by an average of 3.5%, which was found to be statistically significant. The use of velocity reduction factors also caused seven of the thirty one culverts tested to be reclassified as partial barriers rather than complete barriers. Keywords: Fish Passage, culverts, FishXing, Reduced Velocity Zones
ACKNOWLEDGMENTS
I would like to thank Dr. Rollin H. Hotchkiss for his mentorship, guidance, and constant
patience with me throughout this process. I would also like to thank Mr. Ross Taylor for supplying
real field data for us to work with, and I would like to thank Luke Kevan and Trey McGhin for
their assistance on the project.
TABLE OF CONTENTS
LIST OF TABLES ................................................................................................................. vii
LIST OF FIGURES ................................................................................................................. ix
1 Introduction ....................................................................................................................... 1
Objectives ................................................................................................................... 1
Document Organization .............................................................................................. 2
Literature Review ....................................................................................................... 2
2 Methods .............................................................................................................................. 9
Objectives ................................................................................................................... 9
Data Collection ........................................................................................................... 9
Procedures ................................................................................................................. 10
3 Results & Discussion ....................................................................................................... 15
Velocity Reduction Factor for Native Utah Fish ...................................................... 15
General Equation for Calculating Velocity Reduction Factors ................................ 16
Equation Testing ....................................................................................................... 19
Field Testing of Velocity Reduction Factors through FishXing ............................... 23
Survey of Current Culvert Fish Passage Situation .................................................... 24
4 Conclusions & Recommendations ................................................................................. 27
Recommendations ..................................................................................................... 28
REFERENCES ........................................................................................................................ 29
Appendix A. Table of Velocity Reduction Factors .......................................................... 35
Appendix B. Summary of State Regulations Regarding Fish Passage .......................... 38
B.1 Alaska (Alaska Department of Fish and Game and Alaska Department of Transportation and Public Facilities, 2001) .............................................................. 38
B.2 Arizona (Arizona Game and Fish Department, 2006) .............................................. 38
v
B.3 California (Love et al., 2010) .................................................................................... 39
B.4 Connecticut (Connecticut Department of Environmental Protection, 2008) ............ 39
B.5 Georgia (Georgia Department of Transportation, 2008) .......................................... 40
B.6 Idaho (Idaho Department of Lands, 2009) ................................................................ 40
B.7 Maine (Maine Department of Transportation, 2007) ................................................ 40
B.8 Maryland (Maryland Department of the Environment, 2000) .................................. 40
B.9 Massachusetts (Massachusetts Department of Transportation, 2010) ...................... 41
B.10 Minnesota (Minnesota Department of Natural Resources, 2011) ............................ 41
B.11 Montana (AASHTO, 1996) ...................................................................................... 41
B.12 New Hampshire (New Hampshire Department of Environmental Services, 2009) . 41
B.13 New York (New York Department of Environmental Conservation, 2013) ............ 42
B.14 Ohio (Tumeo and Pavlick, 2011) .............................................................................. 42
B.15 Oregon (Oregon Department of Fish and Wildlife, 2006) ........................................ 42
B.16 Pennsylvania (Pennsylvania Department of Transportation, 2009) ......................... 42
B.17 Vermont (Bates and Kirn, 2009) ............................................................................... 43
B.18 Virginia (Fitch, 1995) ............................................................................................... 43
B.19 Washington (Barnard et al., 2013) ............................................................................ 43
B.20 Wisconsin (Wisconsin Department of Natural Resources, 2007) ............................ 44
vi
LIST OF TABLES
Table 2-1: Fish Classifications used to Test the Velocity Reduction Factors ......................12
Table 2-2: Information on Culverts used to Test the Velocity Reduction Factors ...............12
Table 3-1: Data from Flume Tests ........................................................................................15
Table 3-2: A Comparison of Velocity Reduction Factors from Several Studies ..................16
Table 3-3: Summary of Roughness Heights for Various Materials ......................................17
Table 3-4: Summary of Tests for Effectiveness of Velocity Reduction Factors. .................24
Table A-1: Calculated Velocity Reduction Factors based on Relative Depth and Relative Roughness ..................................................................................................................36
vii
LIST OF FIGURES
Figure 3-1: Effect of Relative Roughness on the Velocity Profile .......................................18
Figure 3-2: Measured vs. Predicted VRFs for the Arch Culvert ..........................................20
Figure 3-3: Measured vs. Predicted VRFs for the Unrestricted Stream ...............................20
Figure 3-4: Measured vs. Predicted VRFs for the Box Culvert ............................................21
Figure 3-5: Measured vs. Predicted VRFs for the Corrugated Pipe Culvert ........................21
Figure 3-6: Measured vs. Predicted Average VRFs for each Culvert Investigated ..............22
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1 INTRODUCTION
Fish passage assessment of culverts is often done by comparing culvert hydraulic
characteristics (such as velocity or depth) to fish swimming capabilities. One of the most common
applications of this is to compare the average velocity in the culvert barrel to the prolonged
swimming speed of the fish species of interest. However, this method is often overly conservative,
because it does not account for areas of low velocity in a culvert that fish can utilize. The program
FishXing has the ability to account for these areas of reduced velocity by using velocity reduction
factors, but the feature is rarely used due to a lack of understanding on the topic. Accounting for
areas of low velocity can be useful when assessing a culvert for fish passage, because it can help
determine culverts that are only partial barriers compared to culverts that are complete barriers.
This study investigated a way to determine velocity reduction factors for any culvert, and
demonstrates the usefulness of these reduction factors in fish passage assessment.
Objectives
The primary objectives of this research were to develop culvert velocity reduction factors
for small native Utah fish, and to develop a general equation that can be used to calculate velocity
reduction factors in any culvert based on flow and fish data. Secondary objectives were to
determine if velocity reduction factors could have a significant impact on fish passage assessment,
1
which would allow their use in prioritizing for culvert retrofit. Finally, a survey of current fish
passage design standards was conducted to determine the importance being placed on fish passage.
Document Organization
First, a literature review of background information and current standards and practices is
presented. Afterwards, a description of the data collection and research methods used is presented.
This is followed by a presentation and discussion of results. Finally, conclusions are presented and
recommendations are made. Appendices with additional information are also included.
Literature Review
Fish passage through culverts has become a focus of culvert design in recent years. When
hydraulic efficiency is the only design concern, the result is often a structure that is narrower than
the surrounding stream channel. The narrowing of the channel can result in increased velocities
within the culvert and greater scour potential around the culvert. These changes can make the
culvert a barrier to fish swimming upstream, which can result in fragmentation of habitat and fish
population (Trombulak and Frissell, 2000). To mitigate these problems, standards for fish passage
assessment and design are becoming more commonplace. Many fish passage/habitat evaluation
techniques use mean velocity to determine flow requirements (Stone and Hotchkiss, 2006), often
comparing flow velocities and depths to swimming requirements for fish. Methods of fish passage
design at culverts can be separated into three categories: geomorphic simulation, hydraulic
simulation, and hydraulic design (Hotchkiss and Frei, 2007). Both geomorphic and hydraulic
simulation strive to match the culvert flow characteristics to those of the stream. The hydraulic
design method, on the other hand, matches the flow depth and velocity in the culvert barrel to the
2
swimming requirements of a specific fish species. This method is generally used in retrofits, or
when the other two methods are not deemed appropriate.
FishXing is a free program created by the US Forest Service to assist in the evaluation of
culverts for fish passage (USDA Forest Service, 2006). It uses a hydraulic design method for
assessing culverts in which it models organism capabilities against culvert hydraulics. It compares
the flow, velocities, and leap requirements with the swimming abilities of the species of interest,
then determines the limiting fish passage factors and flows. Fish performance data for a number
of species are available as part of a built-in database, and the program can base passage on fish
swimming speeds, time to exhaustion, minimum required depth, or outlet jump requirements. For
example, the program compares the fish’s swim speed and the speed of the water where the fish is
swimming, known as the occupied velocity. A culvert can be impassable to fish due to excessive
flow velocity in the culvert or due to exhaustion of the fish.
FishXing includes an option to use velocity reduction factors in calculating fish passage.
This option was included to help make FishXing a more accurate fish passage predictor. Velocity
reduction factors are used to account for fish swimming against water flowing slower than the
calculated average cross sectional velocity. The velocity reduction factor is defined as the ratio of
the occupied velocity to the average velocity in the culvert. The values for velocity reduction
factors vary between 0 and 1, and are usually only used for small fish (USDA Forest Service,
2006). When used, the calculated average velocity is multiplied by the reduction factor, and the
result is then compared to the fish swimming abilities. The culvert is divided into three longitudinal
areas: the inlet, the barrel, and the outlet sections, each of which can each be assigned a different
reduction factor due to the different flow dynamics in each section. Velocity reduction factors can
3
vary substantially based on the culvert shape and roughness, and on the fish size (USDA Forest
Service, 2006).
The idea of using occupied velocity was introduced to realistically address fish passage in
corrugated culverts (Morsell et al., 1981). The occupied velocity describes the velocity in the
portion of the culvert where fish have been observed to swim. Subsequent studies found that in
culverts with corrugations, the occupied velocity was considerably less than the mean (Behlke et
al., 1988), and they recommended that the occupied velocity be used in culvert design instead of
average velocity. To aid in this, several studies were conducted to determine appropriate reduction
factors based on culvert corrugation and culvert dimensions (Behlke et al., 1988; Behlke et al.,
1991; Kane et al., 1989). These studies found velocity reduction factors ranging from 0.2-0.4 for
deep corrugations to 0.8-0.9 for accelerating flow. Each study recommended that reduction factors
be used on a case by case basis according to engineering judgment. Powers (1997) conducted a
study to determine if small fish would make use of the reduced velocity near the boundary to pass
culverts. He found that smaller fish made use of the near-boundary more frequently than larger
fish, and that they tended to move to the boundary of the culvert when the flow velocity increased.
He determined through measurements that the occupied velocity ranged from 20-80% of the
average velocity.
The reduced velocity zones present a problem with using average velocity as the predictor
of fish passage: mean velocity may predict a fish passage barrier when fish can actually pass. One
study has found that though FishXing predicted a complete barrier, a field assessment found that
fish could pass the culvert (Blank, 2008). Another study found that small fish could pass the
culvert, even when average velocity was double the fish swimming velocity (Thurman and Horner-
Devine, 2007). Similar results have been seen in other studies (Behlke et al., 1988; Monk, 2012).
4
The average velocity does not account for the reduced velocity areas, which fish can use
to successfully pass a culvert. In an attempt to account for low velocity areas, Vasconcelos
developed a post-processing tool for HEC-RAS to assess fish passage at culverts (Vasconcelos et
al., 2011), which accounts for 2-D flow distribution and predicted significantly (33%) higher
passage rates than 1-D models. Similarly, Blank developed a 3-D model which more accurately
predicted fish passage (when compared to field data) than a 1-D model (Blank, 2008).
Several critiques and suggestions have been made to change or improve assessment
methods. One study found that current hydraulic design criteria may be too conservative, offering
no additional benefit while forcing unnecessary complexity (Lang et al., 2004). The same study
suggests using assessment criteria that are less conservative than design criteria. This suggestion
was echoed by Alberta Transportation when they concluded that “assessment of fish passage based
on a comparison of mean velocities between the culvert and channel appears to be a reasonable
approach. If, however, theoretical fish swimming performance curves are to be used, the
comparison should be based on a fraction of the mean velocity due to the provision of large areas
with velocities much lower than the section-averaged mean velocity” (Alberta Transportation,
2010). In addition, using the weakest swimming species as the culvert design target may create
depth barriers for larger fish (Mozes, 2008), and in this case a stream simulation approach may not
be the most effective culvert design method.
The vertical velocity distribution through a column of water can be described using the
log-law, or universal law of the wall, for rough boundaries (Kironoto and Graf, 1994). The log-
law specifically describes the region of near boundary flow, and can be reasonably applied to flow
depths up to y/D=0.5 (Petrie et al., 2010; C. Song and Yang, 1979), where y is measured positive
upward from the boundary and D is the flow depth. The log-law was originally developed for
5
velocity distributions in pipe flow. However, it has been shown to predict the velocity profile well
in open channel flow with rough boundaries (Stone and Hotchkiss, 2006; Wang et al., 2012).
Flow through culverts that are partially full is similar to stream flow (House et al., 2005).
Studies have found that Manning’s equation for open channel flow works reasonably well in
corrugated (Toews and Clark, 2012) and embedded (White, 1996) culverts. Other studies have
shown that velocity profiles in culverts can be well predicted by the log-law for large portions of
the flow depth (Ead et al., 2000; Magura, 2007; Richmond et al., 2007). This indicates that flow
in partially full culverts is similar enough to open channel flow that the same equations can be
reasonably used.
Like open channel flow, flow in culverts is diverse (Blank, 2008). Substantial distribution
of velocity has been found in all culverts (Alberta Transportation, 2010). While natural channels
and embedded culverts do provide more low flow area, there is still significant low flow area in
corrugated and smooth pipes. Roughness is a significant factor in velocity distribution variance.
Increased roughness in a culvert can increase low velocity area (Kehler, 2009).
Due to boundary roughness and its effect on velocity distributions, areas of reduced
velocity can often be found throughout the length of a culvert. One study found that velocities in
the reduced velocity zone of a culvert were as low as 36% of the centerline velocities (Richmond
et al., 2007). Studies have found that reduced velocity zone can also show reduced turbulence
(Morrison et al., 2009; Richmond et al., 2007).
Several recent studies have measured flow patterns in culverts in an effort to quantify the
areas of reduced velocity. Some of these studies have attempted to use existing equations to
quantify low velocity zones (Barber and Downs, 1996), while others have attempted to create new
equations (Ead et al., 2000). White developed an empirical equation to find the ratio of the velocity
6
at a depth to the average velocity based on the relative depth at which the velocity was measured
(1996). The empirical constants varied with the culvert location, but the equations generally under
predicted the amount of low flow. Another model was created to predict the amount of area below
a certain velocity based on stream characteristics (House et al., 2005). The computed percentages
were again less than the measured percentages because they did not account for low velocity areas
near the edges of the channel. Other attempts have used radial equations to find areas of low flow
(Clark and Kehler, 2011), which also under predicted areas of low flow compared to measured
data. However, they did find that 30-45% of the total area is below the mean velocity, which
matched results from Magura (2007).
Many studies have observed fish behavior as they attempt to navigate culvert flow in an
effort to quantify their swimming abilities and behavior. Pearson et al. found that fish use low
velocity pathways to accomplish passage (2006). They found that the actual pathways varied with
roughness and flow, but fish were able to find and use the low velocity pathways under several
different conditions. Studies investigating reduced velocity zones have found that fish find and
take advantage of the observed reduced velocity zones (Richmond et al., 2007). It has been
generally observed that small fish generally tend to swim near the culvert walls to take advantage
of the reduced velocity (Behlke et al., 1991; Gardner, 2006; Kane et al., 1989; Morsell et al., 1981).
While a variety of fish seek out low velocity zones, not all fish are equally capable of using
them. Esplin (2011) found that benthic dace were able to use the near boundary more efficiently
than mid-column chub, though both fish used the near boundary for swimming and holding.
Benthic swimmers are designed to swim near the boundary, and expend energy more efficiently
in the boundary region compared to other fish.
7
One concern about accounting for reduced velocity zones in culverts is the effect that
turbulence may have on fish passage. Turbulence is a concern in the near boundary because
turbulence values tend to be higher near the boundary (Kironoto and Graf, 1994). Additionally,
increased roughness leads to increased turbulence values (Haws, 2008; Wang et al., 2012).
Turbulence reaches a peak near the bed before decreasing with depth and becoming more uniform
(Clark and Kehler, 2011; Monk, 2012). Peak turbulence tends to be located at 10-20% of the flow
depth (Haws, 2008; Strom and Papanicolaou, 2007). When measured in culverts, turbulence values
were similar to those recorded in gravel and cobble bed rivers, but turbulence didn’t decrease with
depth as much as it would in a channel (Morrison et al., 2009)
Several studies have investigated turbulence effects on fish swimming ability and behavior.
One study found that at the same velocities, passage increased in smooth culverts compared to
rough culverts, attributed to the increased turbulence in rough culverts (Powers, 1997). Another
study found that increased turbulence resulted in increased swimming costs for juvenile Atlantic
salmon (Enders et al., 2005). However, different studies have found that turbulence had no
noticeable effect on swimming velocities for smaller fish (Nikora et al., 2003), or that no
relationship between turbulence and fish passage exists (Morrison et al., 2009).
8
2 METHODS
Objectives
The primary objectives of this study were to develop velocity reduction factors for native
Utah fish, and to create a general equation for calculating velocity reduction factors for a culvert.
Secondary objectives of this study were to test the equation against actual field data to demonstrate
its applicability and to investigate if velocity reduction factors can have a significant impact on
fish passage. Finally, this study demonstrates that there is wide spread applicability for velocity
reduction factors, especially in culvert retrofit or rehabilitation.
Data Collection
Velocity data used to calculate specific velocity reduction factors for native Utah fish were
gathered at the in a flume at Brigham Young University (Esplin, 2011). Longnose dace and
leatherside chub were the native fish used in this experiment. The fish were placed in a Plexiglas
flume, and their swimming locations and behaviors were observed with flow velocities near their
prolonged swim speeds. Water velocity was measured with a SonTek 16-MHz Micro Acoustic
Doppler Velocimeter (ADV). Once the fish movements were observed, extra velocity
measurements were taken in the occupied zone to determine the occupied velocity. While several
tests were performed, only the data from the bare flume tests were used to calculate velocity
reduction factors. This test was chosen because the consistency of fish swimming locations
9
allowed for accurate velocity measurements in the occupied zone. For a more detailed explanation
of the flume testing procedure and results, see Esplin (2011).
Additional flow data were taken on Salina Creek in Central Utah and were used to verify
the velocity reduction factor equation developed. Flow measurements were taken at three different
sites: an open bottom arch culvert, a box culvert with no sediment present, and a section of stream
without a culvert. Flow was measured two cm above the bed using a Pygmy Meter. This depth
was chosen because it corresponds to the swimming depth for benthic fish. In addition, a pebble
count was used to find the particle size distribution in the arch culvert and stream section. For a
more detailed description of the field data collection, see Monk (2012).
Procedures
Using the data gathered in the flume, velocity reduction factors were developed for the
chub and dace. The swimming paths chosen by the fish were observed, and the velocity was
measured in these occupied areas. The occupied velocity, or velocity in the region where the fish
swam, was divided by the average velocity in the flume to find the velocity reduction factors for
native Utah fish.
A general equation was then developed to predict the velocity reduction factors for any
culvert. The equation is based on the Log-law (Prandtl’s Law) of velocity distribution. The idea
was to create an equation that could be used to predict the velocity reduction factor based on the
relative roughness and the depth in the culvert. An Excel program was created to make calculation
of reduction factors easier.
The equation was then tested using two different sets of velocity data measured in different
types of culverts. The first set of data was collected as described above (Monk, 2012), and
consisted of flow measured in a box culvert with no sediment and an open-bottom arch culvert.
10
Data collected in a stream section were also used for comparison to the open bottom culvert data.
The other set of data was from a study performed on fish passage through a corrugated culvert in
on Fish Creek in Alaska (Kane et al., 1989). The flow measurements were taken in a 60 ft. long,
9.6 ft. diameter culvert. The culvert was constructed of corrugated steel with 6 inches between
corrugations with a height of 1.375 inches (6x1.375). Measurements were taken at several depths
and at several locations along the centerline of the culvert where the inlet effects had dissipated
and flow was fully developed.
Measured velocity reduction factors were calculated from the field data by dividing the
measured velocity by the cross-sectional average velocity of the culvert. In addition, because
FishXing only allows a single velocity reduction factor to be used for the culvert barrel, a single
velocity reduction factor was calculated for each culvert for each measured depth. A velocity
reduction factor was then predicted using the developed equation, the relative depth at which the
field measurement was taken, and the roughness characteristic of the culvert. Predictions greater
than the measured value were considered conservative and would indicate that the equation is
acceptable for use.
Once a method to calculate velocity reduction factors was created, their application and
usefulness were tested. FishXing files used to model several culverts in northern California were
obtained from Ross Taylor (Taylor, 2014). Table 2-2 lists the culverts tested. These culverts had
previously been investigated for fish passage for three different fish classes: adult, resident trout,
and juvenile. An explanation of these classes is shown in Table 2-1. Velocity reduction factors for
each culvert were calculated using the equation developed. The fish body height was used as the
swimming depth, and the smallest flow depth in the culvert calculated by FishXing was used as
11
the flow depth. The body heights used were 15 cm for the adult class, 10 cm for resident trout, and
2 cm for juveniles.
Table 2-1: Fish Classifications used to Test the Velocity Reduction Factors
Fish Type Description
Adult This groups represented adult anadromous salmonids that may use these streams to spawn.
Resident Trout This group represented resident trout and juveniles salmonids age 2+
Juveniles This group represented juvenile salmonids age 1+, and also represents small native fish
Table 2-2: Information on Culverts used to Test the Velocity Reduction Factors
Study Location Creek/Culvert Name Description Jackson State Forest Bear Gulch, 48 ft. long, 10 ft. diameter corrugated pipe;
5”x1” corrugations Jackson State Forest Bunker Gulch #1 55 ft. long, 7.5’x6.5’ oval corrugated pipe;
3”x1” corrugations Jackson State Forest Bunker Gulch #2 53 ft. long, 7 ft. diameter corrugated pipe;
3”x1” spiral corrugations Jackson State Forest Blue Gum Creek 91 ft. long, 6 ft. diameter corrugated pipe;
3”x1” spiral corrugations Jackson State Forest Railroad Gulch 81 ft. long, 8’x6.5’ oval corrugated pipe;
3”x1” corrugations Jackson State Forest
North Fork Berry Gulch
60 ft. long, 8 ft. diameter corrugated pipe; 2-2/3”x1/2” spiral corrugations
Jackson State Forest Chamberlain Creek 79 ft. long, 8.4’x12.8’ corrugated pipe arch;
6”x2” corrugations Skunk Train Railway Noyo River 140 ft. long, 9 ft. diameter corrugated pipe;
3”x1” spiral corrugations Skunk Train Railway Redwood Creek 84 ft. long, 9 ft. diameter corrugated pipe;
6”x1” corrugations Skunk Train Railway Duffy Gulch 40 ft. long, 8’x8’concrete box culvert
Skunk Train Railway Park Creek 65 ft. long, 4 ft. diameter corrugated pipe;
3”x1” spiral corrugations
12
Fish passage rates through the culverts with velocity reduction factors (as calculated by the
developed equation) and without reduction factors were compared. Overall passage rates were
compared, as were changes in the range of flows that presented a velocity barrier. The velocity
barrier was specifically investigated because other types of barriers may exist which should not be
effected by the velocity reduction factors. The significance in the passage rate change was tested
using a paired t-test.
Lastly, in an effort to establish the usefulness of velocity reduction factors, a survey was
conducted of the current state of culvert fish passage awareness. This survey included a web search
of state Departments of Transportation and Departments of Natural Resources for any fish passage
design guidelines or requirements for culvert installation. A small investigation of was also done
to find the number of known culverts that may present barriers to fish passage and be in need of
retrofit or replacement.
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3 RESULTS & DISCUSSION
Velocity Reduction Factor for Native Utah Fish
Using the data gathered in the flume tests, velocity reduction factors were developed for
leatherside chub and longnose dace. The data gathered are shown in Table 3-1. The average
calculated velocity reduction factors are 0.62 and 0.49 for chub and dace, respectively. These fall
within the range of those found by other researchers, as shown in Table 3-2. This indicates that the
reduction factors are reasonable for small native fish, and these reduction factors can be used for
native Utah fish in bare culverts that are not corrugated.
Table 3-1: Data from Flume Tests
Run # Q (cfs) Vavg (m/s) Vocc (m/s) Dace 1 0.20 0.83 0.43 Dace 2 0.20 0.87 0.43 Dace 3 0.20 0.88 0.43 Dace 4 0.20 0.91 0.43 Chub 1 0.14 0.74 0.47 Chub 2 0.14 0.75 0.47 Chub 3 0.14 0.76 0.47 Chub 4 0.15 0.76 0.47
15
Table 3-2: A Comparison of Velocity Reduction Factors from Several Studies
Velocity Reduction Factor Source 0.49-0.62 This Study 0.4-0.8 Behlke et al. (1991) 0.2-0.8 Powers (1997)
0.625-0.7 Morsell et al. (1981) 0.3-0.7 Lang et al. (2004)
General Equation for Calculating Velocity Reduction Factors
A general equation was developed to predict velocity reduction factors that could be used
in any culvert. The equation predicts the reduction factors based on the depth where the fish swims
and the relative roughness of the culvert. It relies upon the fact that velocity changes with depth to
account for regions of low velocity near the bed which fish can utilize. The equation is based on
the log-law for rough boundaries, which predicts the velocity profile based on depth and other
variables. For a completely rough flow regime, the log-law can be expressed as (Schlichting, 1979)
𝑢𝑢𝑢𝑢∗
= 1𝜅𝜅
ln � yks� + 𝐵𝐵𝐵𝐵 (3-1)
where u(y) is the velocity at depth y from the bed; 𝑢𝑢∗ is the shear velocity; κ is the von Karman
universal constant, here taken as 0.4 (Bray and Davar, 1987; T. Song and Graf, 1996); Br is a
numerical constant of integration, approximately 8.5 for rough boundaries (Bray and Davar, 1987;
Ead et al., 2000; Nezu and Nakagawa, 1993; T. Song and Graf, 1996); and ks is the roughness
height. By integrating the log-law over depth, an equation for predicting average velocity can be
obtained
𝑈𝑈𝑢𝑢∗
= 1𝜅𝜅
ln �𝐷𝐷𝑘𝑘𝑠𝑠� + �𝐵𝐵𝐵𝐵 − 1
𝜅𝜅� (3-2)
where U is the mean velocity, and D is the flow depth.
16
Because the velocity reduction factor is defined as the ratio of the occupied velocity to the
average velocity, Equation 3-1 and Equation 3-2 were combined to create an equation that predicts
velocity reduction factors.
𝑢𝑢𝑈𝑈
= 𝑎𝑎 �ln �𝑦𝑦𝐷𝐷� + 1� + 1 (3-3)
where u/U is the velocity reduction factor, and 𝑎𝑎 is a variable, dependent on roughness and defined
as
𝑎𝑎 = �𝜅𝜅𝐵𝐵𝐵𝐵 − 1 − ln �𝑘𝑘𝑠𝑠𝐷𝐷��
−1 (3-4)
and which simplifies to
𝑎𝑎 = �2.40 − ln �𝑘𝑘𝑠𝑠𝐷𝐷��
−1 (3-5)
when κ and Br are taken as 0.4 and 8.5 respectively, as described above. The actual value used for
ks varies with the type of bed being used. In this study, the following standards were used to define
ks: d50 for embedded culverts (Stone and Hotchkiss, 2006); corrugation height for corrugated
culverts (Ead et al., 2000); and a table of ks values for concrete and other smooth culverts (Simons
and Senturk, 1992). Other options for ks values are 95% of corrugation height (Clark and Kehler,
2011) or to calculate it based on d50 and other parameters (Simoes, 2010). Table 3-3 provides a
summary of how to obtain roughness heights. Using Equation 3-5, a table of velocity reduction
factors was created and is included in Appendix A.
Table 3-3: Summary of Roughness Heights for Various Materials
Material Type Roughness height (ks) Corrugated Metal Use corrugation height
Concrete (or other smooth material)
Table of experimental values, such as Simons and Senturk (1992)
Embedded Use the characteristic sediment size, d50 or d84
17
The derived equation was used to investigate how the shape of the velocity profile changes
with roughness. Figure 3-1 shows that as the roughness increases, the velocity increases more
gradually with depth, resulting in lower velocities near the bed. Similar results were found by
Alberta Transportation (2010). Figure 3-1 also shows that the mean velocity occurs at a relative
depth (y/D) of 0.37, no matter the roughness height. This matches the results of other studies that
found that the mean velocity occurred at a relative depth of 0.35 (Strom and Papanicolaou, 2007),
and also reflects the standard of measuring average velocity at 40% of the total depth above the
bed when using point current meters (Turnipseed and Sauer, 2010).
Figure 3-1: Effect of Relative Roughness on the Velocity Profile
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4
Rela
tive
Dept
h (y
/D)
Velocity Ratio (u/U)
ks/D= 0.0005
ks/D= 0.0056
ks/D= 0.0278
ks/D= 0.1075
18
Equation Testing
Equation 3-3 was tested using velocity data collected from several different locations and
types of culverts. As explained in Section 2.3, the test locations include a box culvert with no
sediment present, an open-bottom arch culvert, and a corrugated steel culvert with no sediment. A
section of stream with no culvert was also tested for comparison.
Graphs of measured vs. predicted velocity reduction factors (VRF) for the arch culvert, the
stream section, the box culvert, and the corrugated pipe are shown in Figure 3-2, Figure 3-3, Figure
3-4, and Figure 3-5, respectively. The results for the bottomless arch culvert and the natural stream
reach are very similar. The equation was only conservative in its predictions for 25% of values
(5/20) for the bottomless culvert and for 27% of values (6/22) in the natural stream reach. The
equation was also tested in a box culvert with no sediment on the same river as the arch culvert
and was much more successful in this case, providing a conservative yet reasonable estimate of
velocity reduction factors in 65% of the cases (12/18). In these three cases, the occupied velocity
was measured two centimeters above the bed. Because all measurements were taken at the same
depth and the total depth in the culvert remained fairly constant, the predicted velocity reduction
factors were all close to the same value. However, local velocity variations resulted in a wide range
of measured velocities. This resulted in a vertical distribution of values in the graphs. The final
test used data collected from a corrugated steel pipe culvert, as described in Section 2.3. Rather
than at cross sections, the data was collected along the centerline of the culvert at varying depths.
As a result of using different depths rather than a constant depth, a wider range of velocity
reduction factors was predicted and measured. Again, the equation was generally successful,
providing a conservative estimate in 70% of the cases (28/40).
19
Figure 3-2: Measured vs. Predicted VRFs for the Arch Culvert
Figure 3-3: Measured vs. Predicted VRFs for the Unrestricted Stream
0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2
Mea
sure
d VR
F
Predicted VRF
0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2
Mea
sure
d VR
F
Predicted VRF
20
Figure 3-4: Measured vs. Predicted VRFs for the Box Culvert
Figure 3-5: Measured vs. Predicted VRFs for the Corrugated Pipe Culvert
0.4
0.5
0.6
0.7
0.8
0.9
1
0.4 0.5 0.6 0.7 0.8 0.9 1
Mea
sure
d VR
F
Predicted VRF
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 0.2 0.4 0.6 0.8 1 1.2 1.4
Mea
sure
d VR
F
Predicted VRF
21
Because FishXing only allows one velocity reduction factor to be used for the main culvert
barrel, an average velocity reduction factor was calculated for each culvert at the depths measured.
Figure 3-6 shows the measured vs. predicted velocity reduction factor for each test, and also
includes the values calculated from the flume. The stream section and arch culvert had similar
results, and both showed less velocity reduction than was predicted. The box culvert and
corrugated pipe showed greater velocity reduction than predicted, indicating that the equation is
conservative. Additionally, the values determined from the flume both showed greater velocity
reduction than predicted. This was expected because the fish made use of the flume corners, which
had reduced velocity due to both the bed and wall effects. The effects of corners is not anticipated
by equation, which contributes to it being conservative.
Figure 3-6: Measured vs. Predicted Average VRFs for each Culvert Investigated
0
0.2
0.4
0.6
0.8
1
1.2
0 0.2 0.4 0.6 0.8 1 1.2
Mea
sure
d VR
F
Predicted VRF
Arch Culvert
Stream Section
Box Culvert
Flume Study
Corrugated Pipe
22
Overall, the equation reasonably predicts velocity reduction factors for flow through most
culverts. It is generally conservative in predicting the velocity reduction factors in concrete (box)
and corrugated metal (pipe) culverts with no sediment. These are the culverts of the most interest,
since they will probably be the most in need of replacement or retrofit. The equation can also be
considered conservative because it does not account for areas of reduced velocity that occur in the
corners box and other culverts. Because the equation provides conservative velocity reduction
factors, using them in FishXing allows for a more accurate assessment of fish passage status while
maintaining a factor of safety in the fish passage estimate.
The equation is not as accurate for bottomless culverts, and tends to predict greater velocity
reduction than actually occurs. However, many bottomless culverts are specifically designed for
fish passage, or to simulate the flow in the adjacent stream sections. Figure 3-2 and Figure 3-3
show that the relationship between the boundary velocity and the mean velocity in bottomless
culverts is similar to the relationship in a natural stream reach. This supports the idea that
bottomless culverts reasonably simulate the flow patterns of a natural stream reach. This means if
the fish can swim in the regular stream section then they should also be able to navigate the
bottomless culvert. Engineering judgment should be used in any case where velocity reduction
factors might be used. If there are unique circumstances (such as adverse slope, backwater,
hydraulic jump, etc.) the equation will not predict accurate velocity reduction.
Field Testing of Velocity Reduction Factors through FishXing
To establish the usefulness of velocity reduction factors in fish passage assessment, passage
rates at several actual culverts were compared with and without the use of velocity reduction
factors. The locations used and the fish types investigated are discussed in Section 2.3. The overall
23
passage rates were compared, as were the range of flows with passable velocity. Overall,
percentage of passable flows increased by 3.5%, while the percentage of flow with passable
velocities increased by 6%. Both of these values were found to be statistically significant using a
paired t-test (p<0.05). These results, along with the bounds for the 95% Confidence Interval (CI)
and p-values, are summarized in Table 3-4.
Table 3-4: Summary of Tests for Effectiveness of Velocity Reduction Factors.
Overall Percent Passage Percent Passable Velocity Mean Increase 3.54 6.02
p-value 0.024 0.0046 Upper CI Limit 6.58 10.03 Lower CI Limit 0.50 2.01
In addition to being statistically significant, the results were also practically significant.
While the average increase in passable flows was not very large, some scenarios saw passage
increases of up to 50%. In seven of the thirty one tests, use of velocity reduction factors caused a
previously impassable culvert to become passable for some flows. In one test, the velocity barrier
for adult salmonids completely disappeared. However, not all culverts will be fish passable.
Velocity reduction factors can help identify those culverts in most urgent need of retrofit by
identifying culverts that may be passable to fish under some conditions.
Survey of Current Culvert Fish Passage Situation
A survey of the current fish passage situation throughout the country was conducted to
determine where these results could be applied. While the number of culverts that are currently
fish passage barriers is not precisely known, there have been some inventories performed which
indicate how wide spread the problem is. For example, there are approximately 10,000 culverts on
24
government land alone in Washington and Oregon, of which more than half are barriers, and there
are up to 28,500 such crossings in Massachusetts (Hotchkiss and Frei, 2007).
A number of states have recently implemented fish passage design guidelines and
assessment criteria for culverts. Twenty states currently have design guidelines for fish passage
through culverts, and thirteen of these states allow hydraulic design as an option for new or retrofit
culverts. The majority of these states are in the west and in the northeast, where sport fish such as
salmon and trout are of interest. These guidelines are generally the result of coordination between
state natural resource and transportation departments. Appendix B contains a summary of these
design requirements by state. While no specific state assessment criteria were found, culvert
assessment criteria generally use variables such as flow depth and velocity to assess whether a
culvert is passable to a specific species of fish (Kilgore et al., 2010). Assessment criteria are
generally not as conservative as design criteria. Some states use a visual assessment as a
preliminary assessment before any computations are done (Beavers et al., 2008).
25
4 CONCLUSIONS & RECOMMENDATIONS
An equation to predict velocity reductions factors, for use in the program FishXing, was
developed in this study. The predicted values from the equation were similar to measured values
in non-embedded concrete box and corrugated metal pipe culverts. The equation generally under
predicted the amount of velocity reduction that occurred, which indicates that the equation can be
used while still allowing for conservative assessment and design. The equation tended to over
predict the amount of velocity reduction in embedded culverts, but still provided a reasonably close
estimation. This indicates that engineering judgment should be used in specific scenarios if the
equation is applied to embedded culverts.
It was also determined that velocity reduction factors can have a significant impact on fish
passage assessment. The use of velocity reduction factors in fish passage assessment creates a
more realistic and accurate assessment of fish passage by accounting for areas of low velocity that
fish can use to successfully navigate a culvert. Because of this, velocity reduction factors should
be used in culvert assessment for fish passage.
It is important to use velocity reduction factors due to the large number of culverts that
may be barriers to fish passage. A large number of states are beginning to focus on fish passage
and culvert replacement, and using velocity reduction factors can help determine which culverts
most urgently need to be replaced. Accounting for low velocity areas can help determine which
culverts are only partial barriers, and therefore do not need to be replaced as soon. This will allow
27
for more efficient use of funds, and faster ecological recovery through removal of the culverts that
are complete barriers. Velocity reduction factors can also be used in hydraulic design methods
when appropriate. However, their use is not intended to replace stream or hydraulic simulation
design methods, which are required in many states and preferred for new installations.
Recommendations
Velocity reduction factors should be used in assessment of fish passage through non-
embedded culverts. The equation provided can be used for corrugated pipe and concrete box
culverts that are flowing less than half full. It is recommended to use the fish size as the swimming
depth, and the smallest measured depth in the culvert as the flow depth. Values such as roughness
and Br should be chosen based on a sound understanding of the culvert under investigation, and
guidelines for choosing these values are given in this report.
Because of the small number of culvert shapes and materials investigated in this study,
further work is required to test the predicted velocity reduction factors for a wider variety of culvert
shapes and materials. In addition, field studies should be performed to further test passage rates
predicted using velocity reduction factors.
28
REFERENCES
AASHTO. (1996). American Association of State Highway and Transportation Officials Drainage Manual Chapter 9: Culverts.
Alaska Department of Fish and Game, and Alaska Department of Transportation and Public
Facilities. (2001). Memorandum of Agreement Between Alaska Department of Fish and Game and Alaska Department of Transportation and Public Facilities for the Design, Permitting, and Construction of Culverts for Fish Passage.
Alberta Transportation. (2010). Velocity Distributions Impacts on Fish Passage at Culverts. Arizona Game and Fish Department, Habitat Branch. (2006). Guidelines for Culvert
Construction to Accommodate Fish & Wildlife Movement and Passage. Barber, Michael E., and Downs, Randall Craig. (1996). Investigation of Culvert Hydraulics
Related to Juvenile Fish Passage (pp. 54). Pullman, WA: Washington State Department of Transportation.
Barnard, R. J., Johnson, J., Brooks, P., Bates, K. M., Heiner, B., Klavas, J. P., . . . Powers, P. D.
(2013). Water Crossing Design Guidelines. Olympia, WA. Bates, Kozmo Ken, and Kirn, Rich. (2009). Guidelines of the Design of Stream/Road Crossings
for Passage of Aquatic Organisms in Vermont. Beavers, Aaron E., Hotchkiss, Rollin H., and Belk, Mark C. (2008). Fish Passage at UDOT
Culverts: Prioritization and Assessment (pp. 251). Salt Lake City, UT: Utah Department of Transportation.
Behlke, Charles E., Kane, Douglas L., McLean, Robert F., Reynolds, James B., and Travis,
Michael D. (1988). Spawning Migration of Arctic Grayling Through Poplar Grove Creek Culvert, Glennallen. Alaska, 1986 (pp. 178): Alaska Department of Transportation and Public Facilities, Division of Planning and Programming.
Behlke, Charles E., Kane, Douglas L., McLean, Robert F., and Travis, Michael D. (1991).
Fundamentals of Culvert Design for Passage of Weak-Swimming Fish: Alaska Department of Transportation and Public Facilities.
Blank, Matthew David. (2008). Advanced Studies of Fish Passage Through Culverts: 1-D and 3-
D Hydraulic Modeling of Velocity, Fish Energy Expenditure, and a New Barrier Assessment Method. (PhD), Montana State University, Bozeman, MT.
29
Bray, Dale I, and Davar, Kersi S. (1987). Resistance to flow in gravel-bed rivers. Canadian
Journal of Civil Engineering, 14(1), 77-86. Cahoon, Joel E., McMahon, Thomas, Solcz, Andy, Blank, Matt, and Stein, Otto. (2007). Fish
Passage in Montana Culverts: Phase II - Passage Goals (pp. 61). Helena, MT: Montana Department of Transportation.
Clark, Shawn P., and Kehler, Nicholas. (2011). Turbulent Flow Characteristics in Circular
Corrugated Culverts at Mild Slopes. Journal of Hydraulic Research, 49(5), 676-684. Connecticut Department of Environmental Protection. (2008). Stream Crossing Guidelines. Ead, S. A., Rajaratnam, N., Katopodis, C., and Ade, F. (2000). Turbulent Open-Channel Flow in
Circular Corrugated Culverts. Journal of Hydraulic Engineering, 126(10), 750-757. Enders, Eva C., Boisclair, Daniel, and Roy, Andre G. (2005). A Model of Total Swimming Costs
in Turbulent Flow for Juvenile Atlantic Salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences, 62(5), 1079-1089.
Esplin, Lindsay D. (2011). Culvert Roughness Elements for Native Utah Fish Passage: Phase I.
(Master of Science), Brigham Young University, Provo, UT. Fitch, G. Michael. (1995). Nonanadromous Fish Passage in Highway Culverts (pp. 18).
Richmond, VA: Virginia Department of Transportation. Gardner, Angela. (2006). Fish Passage Through Road Culverts. (Master of Science), North
Carolina State University, Raleigh. Georgia Department of Transportation. (2008). Manual on Drainage Design for Highways.
Atlanta. Haws, Benjamin B. (2008). Ability of ADV Measurements to Detect Turbulence Differences
between Angular and Rounded Gravel Beds of Intermediate-Roughness Scale. (Master of Science), Brigham Young University, Provo, UT.
Hotchkiss, Rollin H., and Frei, Christopher M. (2007). Design for Fish Passage at Roadway-
Stream Crossings: Synthesis Report: Office of Infrastructure Research and Development, Federal Highway Administration.
House, Matthew R., Pyles, Marvin R., and White, Dale. (2005). Velocity Distributions in
Streambed Simulation Culverts Used for Fish Passage. Journal of the American Water Resources Association, 41(1), 209-217.
Idaho Department of Lands. (2009). Fish Passage Guidelines when Installing Stream Crossings.
30
Kane, Douglas L., Behlke, Charles E., Basketfield, Daniel L., Gieck, Robert E., McLean, Robert F., and Travis, Michael D. (1989). Hydrology, Hydraulics, and Fish Passage Performance of Arctic Grayling (Thymallus Arcticus) at Fish Creek, Denali Highway near Cantwell Alaska: Alaska Department of Transportation and Public Facilities.
Kehler, Nicholas Jon. (2009). Hydraulic Characteristics of Fully Developed Flow in Circular
Culverts. (Master of Science), University of Manitoba, Winnepeg. Kilgore, Roger T., Bergendahl, Bart S., and Hotchkiss, Rollin H. (2010). Culvert Design for
Aquatic Organism Passage Hydraulic Engineering Circular Number 26 (pp. 234). Kironoto, B. A., and Graf, Walter H. (1994). Turbulence Characteristics in Rough Uniform
Open-Channel Flow. Procedings of the ICE-Water Maritime and Energy, 106(4), 333-344.
Lang, Margaret, Love, Michael, and Trush, William. (2004). Improving Stream Crossings for
Fish Passage: National Marine Fisheries Service Love, Michael, Bates, Kozmo, Lang, Margaret, Shea, Rachel, and Llanos, Antonio. (2010).
California Salmonid Stream Habitat Restoration Manual. Magura, Chris R. (2007). Hydraulic Characteristics of Embedded Circular Culverts. (Master of
Science), University of Manitoba, Winnipeg. Maine Department of Transportation. (2007). Fish Passage Design Guide. Maryland Department of the Environment. (2000). Maryland's Waterway Construction
Guidelines. Massachusetts Department of Transportation. (2010). Design of Bridges and Culverts for
Wildlife Passage at Freshwater Streams. Minnesota Department of Natural Resources. (2011). Best Practices Manual: Best Practices for
Meeting DNR General Public Waters Work Permit GP 2004-0001. Monk, Suzanne Kim. (2012). Culvert Roughness Elements for Native Utah Fish Passage: Phase
II. (Master of Science), Brigham Young University, Provo, UT. Morrison, Ryan R., Hotchkiss, Rollin H., Stone, Mark, Thurman, David, and Horner-Devine,
Alex R. (2009). Turbulence Characteristics of Flow in a Spiral Corrugated Culvert Fitted with Baffles and Implications for Fish Passage. Ecological Engineering, 35(3), 381-392.
Morsell, J., Houghton, J., Bell, M., and Costello, R. (1981). Fish Protection Strategies for the
Design and Construction of the Alaska Segment of the Alaska Natural Gas Transportation System: Northwest Alaskan Pipeline Company.
31
Mozes, Kathryn Michelle. (2008). Hydraulic Stream-Simulation Design Option for Culvert Construction in Eastern Washington to Meet Fish Passage Criteria: How Big is Big Enough? (Master of Civil Engineering-Water Resources), Washington State University, Pullman, WA.
New Hampshire Department of Environmental Services. (2009). New Hampshire Stream
Crossing Guidelines. University of New Hampshire. New York Department of Environmental Conservation. (2013). Stream Crossings - Protecting
and Restoring Stream Continuity. Nezu, Iehisa, and Nakagawa, Hiroji. (1993). Turbulence in Open-Channel Flows. Rotterdam: A.
A. Balkema. Nikora, V. I., Aberle, J., Biggs, B. J. F., Jowett, I. G., and Sykes, J. R. E. (2003). Effects of Fish
Size, Time-to-Fatigue and Turbulence on Swimming Performance: a Case Study of Galaxias Maculatus. Journal of Fish Biology, 63(6), 1365-1382.
Oregon Department of Fish and Wildlife. (2006). Oregon Administrative Rules: Division 412
Fish Passage. Pearson, W. H., Southard, S. L., May, C. W., Skalski, J. R., Townsend, R. L., Horner-Devine, A.
R., . . . Deng, D. (2006). Reseach on the Upstream Passage of Juvenile Salmon through Culverts: Retrofit Baffles (pp. 60): Battelle Memorial Institute.
Pennsylvania Department of Transportation. (2009). Design Manual Part 2. (13M). Petrie, J., Diplas, P., Nam, S., and Gutierrez, M. S. (2010). Local Boundary Shear Stress
Estimates from Velocity Profiles Measured with and ADCP. Paper presented at the River Flow 2010, Braunschweig, Germany.
Powers, Patrick D. (1997). Culvert Hydraulics Related to Upstream Juvenile Salmon Passage (L.
a. R. S. Program, Trans.): Washington State Department of Transportation. Richmond, Marshall C., Deng, Zhiqun, Guensch, Gregory R., Tritico, Hans, and Pearson, Walter
H. (2007). Mean Flow and Turbulence Characteristics of a Full-Scale Spiral Corrugated Culvert with Implications for Fish Passage. Ecological Engineering, 30(4), 333-340.
Schlichting, Hermann. (1979). Boundary-Layer Theory (7 ed.). New York: McGraw-Hill Book
Compay. Simoes, Francisco J.M. (2010). Flow Resestance in Open Channels with Fixed and Movable
Bed. Paper presented at the 2nd Joint Federal Interagency Conference, Las Vegas. Simons, Daryl B., and Senturk, Fuat. (1992). Sediment Transport Technology: Water and
Sediment Dynamics. Littleton, CO: Water Resources Publications.
32
Song, Charles, and Yang, Chih Ted. (1979). Velocity Profiles and Minimum Stream Power.
Journal of the Hydraulics Division, 105(8), 981-998. Song, T, and Graf, W. H. (1996). Velocity and Turbulence Distributions in Unsteady Opan-
Channel Flows. Journal of Hydraulic Engineering, 122(3), 141-154. Stone, Mark C., and Hotchkiss, Rollin H. (2006). Evaluating Velocity Measurement Techniques
in Shallow Streams. Journal of Hydraulic Research, 45(6), 752-762. Strom, Kyle B., and Papanicolaou, Athanasios N. (2007). ADV Measurements around a Cluster
Microform in a Shallow Mountain Stream. Journal of Hydraulic Engineering, 133(12), 1379-1389.
Taylor, Ross (2014). [Personal Communication]. Thurman, David R., and Horner-Devine, Alex R. (2007). Hydrodynamic Regimes and Structure
in Sloped Weir Baffled Culverts and their Influence on Juvenile Salmon Passage (pp. 50). Seattle: Washington State Transportation Center.
Toews, Jonathan Scott, and Clark, Shawn Paul. (2012). Relative Depth Effects on Corrugated
Culvert Roughness. Journal of Water Resource and Protection, 4(10), 838-841. Trombulak, Stephen C., and Frissell, Christopher A. (2000). Review of Ecological Effects of
Roads on Terrestrial and Aquatic Communities. Conservation Biology, 14(1), 18-30. Tumeo, Mark A., and Pavlick, Joe. (2011). A Study of Bankfull Culvert Design Effectiveness
(pp. 58). Columbus, OH: Ohio Department of Transportation. Turnipseed, D.P., and Sauer, V.B. (2010). Discharge Measurements at Gaging Stations: U.S.
Geological Survey Techniques and Methods book 3, chap. A8, 87p. USDA Forest Service. (2006). FishXing Version 3: User Manual and Reference. San Dimas,
CA: USDA Forest Service. Vasconcelos, Jose G., Tritico, Hans M., and Hatcher, Thomas M. (2011). A post-processing tool
for HEC-RAS for the assessment of fish passage conditions in highway culverts. Paper presented at the World Environmental and Water Resources Congress, Palm Springs California.
Wang, X. Y., Yang, Q. Y., Lu, W. Z., and Wang, X. K. (2012). Experimental Study of Near-
Wall Turbulent Characteristics in an Open-Channel with Gravel Bed Using an Acoustic Doppler Velocimeter. Experiments in Fluids, 52(1), 85-94.
White, Dale. (1996). Hydraulic Performance of Countersunk Culverts in Oregon. (Master of
Science), Oregon State University, Corvallis, OR.
33
Wisconsin Department of Natural Resources. (2007). Managing Woodlands for Wisconsin's
Coastal Trout Streams. Madison, WI.
34
APPENDIX A. TABLE OF VELOCITY REDUCTION FACTORS
This section includes a table of velocity reduction factors as calculated by Equation 3-3,
based on the relative depth (y/D) and the relative roughness (ks/D).
35
Table A-1: Calculated Velocity Reduction Factors based on Relative Depth and Relative Roughness
y/D ks/D 0.01 0.02 0.05 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2 0.21 0.22
0.0001 0.69 0.75 0.83 0.89 0.90 0.90 0.91 0.92 0.92 0.93 0.93 0.94 0.94 0.95 0.95 0.96 0.0005 0.64 0.71 0.80 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.92 0.93 0.93 0.94 0.94 0.95 0.001 0.61 0.69 0.79 0.86 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.92 0.93 0.93 0.94 0.94 0.002 0.58 0.66 0.77 0.85 0.86 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.92 0.93 0.93 0.94 0.003 0.56 0.65 0.76 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.91 0.92 0.93 0.93 0.94 0.004 0.54 0.63 0.75 0.84 0.85 0.86 0.87 0.88 0.89 0.89 0.90 0.91 0.92 0.92 0.93 0.94 0.005 0.53 0.62 0.74 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.91 0.92 0.93 0.93 0.006 0.52 0.61 0.73 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.93 0.93 0.007 0.51 0.60 0.73 0.82 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.92 0.93 0.008 0.50 0.60 0.72 0.82 0.83 0.85 0.86 0.87 0.88 0.88 0.89 0.90 0.91 0.92 0.92 0.93 0.009 0.49 0.59 0.72 0.82 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.91 0.92 0.93 0.01 0.49 0.58 0.72 0.81 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.91 0.92 0.93 0.02 0.43 0.54 0.68 0.79 0.81 0.82 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.90 0.91 0.92 0.03 0.39 0.51 0.66 0.78 0.80 0.81 0.82 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.91 0.04 0.36 0.48 0.64 0.77 0.79 0.80 0.81 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.91 0.05 0.33 0.46 0.63 0.76 0.78 0.79 0.81 0.82 0.83 0.85 0.86 0.87 0.88 0.89 0.90 0.90 0.06 0.31 0.44 0.62 0.75 0.77 0.79 0.80 0.81 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.07 0.29 0.42 0.61 0.74 0.76 0.78 0.79 0.81 0.82 0.84 0.85 0.86 0.87 0.88 0.89 0.90 0.08 0.27 0.41 0.59 0.74 0.75 0.77 0.79 0.80 0.82 0.83 0.84 0.85 0.87 0.88 0.89 0.90 0.09 0.25 0.39 0.58 0.73 0.75 0.77 0.78 0.80 0.81 0.83 0.84 0.85 0.86 0.87 0.88 0.89 0.1 0.23 0.38 0.58 0.72 0.74 0.76 0.78 0.79 0.81 0.82 0.84 0.85 0.86 0.87 0.88 0.89
0.11 0.22 0.37 0.57 0.72 0.74 0.76 0.77 0.79 0.81 0.82 0.83 0.84 0.86 0.87 0.88 0.89 0.12 0.20 0.36 0.56 0.71 0.73 0.75 0.77 0.79 0.80 0.82 0.83 0.84 0.85 0.87 0.88 0.89 0.13 0.19 0.34 0.55 0.71 0.73 0.75 0.77 0.78 0.80 0.81 0.83 0.84 0.85 0.86 0.87 0.88 0.14 0.17 0.33 0.54 0.70 0.72 0.74 0.76 0.78 0.79 0.81 0.82 0.84 0.85 0.86 0.87 0.88 0.15 0.16 0.32 0.54 0.70 0.72 0.74 0.76 0.78 0.79 0.81 0.82 0.83 0.85 0.86 0.87 0.88 0.16 0.15 0.31 0.53 0.69 0.71 0.74 0.75 0.77 0.79 0.80 0.82 0.83 0.84 0.86 0.87 0.88 0.17 0.14 0.30 0.52 0.69 0.71 0.73 0.75 0.77 0.78 0.80 0.81 0.83 0.84 0.85 0.87 0.88 0.18 0.12 0.29 0.51 0.68 0.71 0.73 0.75 0.77 0.78 0.80 0.81 0.83 0.84 0.85 0.86 0.88 0.19 0.11 0.28 0.51 0.68 0.70 0.72 0.74 0.76 0.78 0.79 0.81 0.82 0.84 0.85 0.86 0.87 0.2 0.10 0.27 0.50 0.68 0.70 0.72 0.74 0.76 0.78 0.79 0.81 0.82 0.84 0.85 0.86 0.87
36
Table A-1 Continued
y/D ks/D 0.23 0.24 0.25 0.3 0.27 0.28 0.29 0.3 0.31 0.32 0.33 0.34 0.35 0.36 0.37
0.0001 0.96 0.96 0.97 0.97 0.97 0.98 0.98 0.98 0.99 0.99 0.99 0.99 1.00 1.00 1.00 0.0005 0.95 0.96 0.96 0.97 0.97 0.97 0.98 0.98 0.98 0.99 0.99 0.99 1.00 1.00 1.00 0.001 0.95 0.95 0.96 0.96 0.97 0.97 0.97 0.98 0.98 0.99 0.99 0.99 0.99 1.00 1.00 0.002 0.95 0.95 0.96 0.96 0.96 0.97 0.97 0.98 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.003 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.004 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.97 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.005 0.94 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.006 0.94 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.007 0.94 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.99 0.99 0.99 1.00 1.00 0.008 0.94 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.98 0.99 0.99 1.00 1.00 0.009 0.93 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.98 0.99 0.99 1.00 1.00 0.01 0.93 0.94 0.94 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.98 0.99 0.99 1.00 1.00 0.02 0.93 0.93 0.94 0.95 0.95 0.96 0.96 0.97 0.97 0.98 0.98 0.99 0.99 1.00 1.00 0.03 0.92 0.93 0.93 0.94 0.95 0.95 0.96 0.97 0.97 0.98 0.98 0.99 0.99 1.00 1.00 0.04 0.92 0.92 0.93 0.94 0.94 0.95 0.96 0.96 0.97 0.98 0.98 0.99 0.99 1.00 1.00 0.05 0.91 0.92 0.93 0.94 0.94 0.95 0.96 0.96 0.97 0.97 0.98 0.99 0.99 1.00 1.00 0.06 0.91 0.92 0.93 0.93 0.94 0.95 0.95 0.96 0.97 0.97 0.98 0.98 0.99 1.00 1.00 0.07 0.91 0.92 0.92 0.93 0.94 0.95 0.95 0.96 0.97 0.97 0.98 0.98 0.99 1.00 1.00 0.08 0.90 0.91 0.92 0.93 0.94 0.94 0.95 0.96 0.97 0.97 0.98 0.98 0.99 1.00 1.00 0.09 0.90 0.91 0.92 0.93 0.94 0.94 0.95 0.96 0.96 0.97 0.98 0.98 0.99 1.00 1.00 0.1 0.90 0.91 0.92 0.93 0.93 0.94 0.95 0.96 0.96 0.97 0.98 0.98 0.99 1.00 1.00
0.11 0.90 0.91 0.92 0.92 0.93 0.94 0.95 0.96 0.96 0.97 0.98 0.98 0.99 1.00 1.00 0.12 0.90 0.91 0.91 0.92 0.93 0.94 0.95 0.95 0.96 0.97 0.98 0.98 0.99 1.00 1.00 0.13 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.95 0.96 0.97 0.98 0.98 0.99 1.00 1.00 0.14 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.95 0.96 0.97 0.98 0.98 0.99 1.00 1.00 0.15 0.89 0.90 0.91 0.92 0.93 0.94 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00 0.16 0.89 0.90 0.91 0.92 0.93 0.94 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00 0.17 0.89 0.90 0.91 0.92 0.93 0.93 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00 0.18 0.89 0.90 0.91 0.92 0.92 0.93 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00 0.19 0.88 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00 0.2 0.88 0.89 0.90 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.97 0.98 0.99 0.99 1.00
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APPENDIX B. SUMMARY OF STATE REGULATIONS REGARDING FISH
PASSAGE
The following is a state by state summary of current fish passage design guidelines for
culverts. If available, assessment criteria were also included in this list.
B.1 Alaska (Alaska Department of Fish and Game and Alaska Department of
Transportation and Public Facilities, 2001)
A list of approved design methods is given. In order of preference, these design methods
are stream simulation design, FISHPass program design, and hydraulic engineering design. Stream
Simulation Design attempts to replicate natural stream flow through the culvert by spanning the
entire bankfull channel and by replicating the bed slope and gradation. FISHPass, like FishXing,
compares water velocity and depth to the swimming capabilities of specific fish species to ensure
that the culvert will not be a barrier. Hydraulic engineering design uses an allowable flow depth
and velocity to ensure the culvert is fish passable. For corrugated culverts, the design requirements
suggest using velocity reduction factors of 0.4-0.8, depending on the flow conditions in the culver.
B.2 Arizona (Arizona Game and Fish Department, 2006)
The guidelines do not give a standard design method, such as stream or hydraulic
simulation, but rather provide a list of requirements for culverts to provide fish passage. The
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guidelines most resemble hydraulic simulation, and include requirements such as the culvert must
be embedded, the culvert must maintain natural substrate, the culvert must span the stream and
allow for flood plains on either side, and the culvert flow and depth should match the natural stream
conditions.
B.3 California (Love et al., 2010)
The first design choice for new or replacement culverts is the stream simulation design
method. However, hydraulic design is allowed in situations where ecological connectivity is not a
project objective. Its applications are in retrofits of existing culverts, grade control structures, and
new or replacement culverts where the physical setting precludes the use of other design options
(such as stream simulation). Water velocity and depth are the primary considerations in this design.
The guidelines also recommend minimizing the turbulence in the culvert by using an energy
dissipation factor to evaluate the turbulence.
B.4 Connecticut (Connecticut Department of Environmental Protection, 2008)
Due to the number of small streams and small fish species native to Connecticut, the
guidelines are specifically set to allow passage of all species. The first choice for stream crossings
is a bridge or bottomless arch culvert. However, in certain situations, hydraulic simulation style
culverts are allowed. The culverts must be embedded, and must match their slope and substrate
material to the natural stream, and ensuring that the culvert is slightly wider than bankfull flow.
Hydraulic design is not given as a design alternative, but baffles are allowed for retrofits in some
cases.
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B.5 Georgia (Georgia Department of Transportation, 2008)
The design guidelines for the USACE regional permit are used in culvert fish passage
design. The guidelines allow for bottomless culverts, and in conditions where the culvert is not
bottomless, the requirements most closely resemble the hydraulic simulation method.
B.6 Idaho (Idaho Department of Lands, 2009)
Fish passage is required by state law in Idaho, and specific guidelines are set forth in state
law to ensure this. The requirements are similar to hydraulic design, setting required flow depth
and velocity, and regulating both inlet and outlet drops. These requirements are based on trout
swimming ability, and are chiefly concerned with sport fish such as salmon and steelhead.
B.7 Maine (Maine Department of Transportation, 2007)
Two basic design approaches are used in Maine. For new and replacement culverts, the
preferred approach is similar to hydraulic simulation. In this method, the culvert dimensions and
gradient are set to match the natural stream’s bankfull hydraulic geometry. For culvert
rehabilitation, the ideas is to maintain a minimum flow depth and not exceed the maximum velocity
for a species of interest, which is essentially the hydraulic design method.
B.8 Maryland (Maryland Department of the Environment, 2000)
The method recommended is similar to the hydraulic simulation technique. The culverts
should match the slope of the stream, should span the bankfull width of the stream, and should be
embedded to allow for natural deposition to occur. However, when other methods have been
examined and deemed not appropriate, baffles or corrugated pipes can be used to create low flow
zones to aid in fish passage.
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B.9 Massachusetts (Massachusetts Department of Transportation, 2010)
A variety of culvert design options are presented, mostly of the stream simulation variety.
The preferred methods include using bridges or wide span culverts that would not constrict stream
flow. However, some hydraulic design methods are permitted when other options are not viable.
These are primarily allowed for replacement and retrofit culverts.
B.10 Minnesota (Minnesota Department of Natural Resources, 2011)
Regulations require that water crossings shall provide for fish movement unless the stream
has negligible fisheries. Several culvert design methods are mentioned, including hydraulic design,
stream simulation, and conventional design. No preferred method is given, though guidelines for
several methods are laid out. The DNR will approve any of the given methods on a case by case
basis if fish passage requirements are met.
B.11 Montana (AASHTO, 1996)
Montana follows the AASHTO model drainage manual for its culvert designs. The manual
mentions that fish passage is required, but doesn’t give guidelines or specifications on how that is
to be carried out. However, a separate report on fish passage performed for the DOT includes
hydraulic design as one of the recommended culvert design options (Cahoon et al., 2007).
B.12 New Hampshire (New Hampshire Department of Environmental Services, 2009)
Regulations require that culverts and bridges cannot obstruct aquatic organism movements,
and that any unavoidable impacts should be minimized. Stream simulation and hydraulic
simulation are both presented as options for new and replacement culverts. Retrofits are mentioned
as a temporary solution, but should not be considered as long term solutions.
41
B.13 New York (New York Department of Environmental Conservation, 2013)
Bridges are listed as the preferred choice for stream crossings, but culverts can be used if
a bridge is not reasonable. Culverts should be embedded, should have the same slope as the stream,
and should be wider than the stream bed. The flow depth and velocity should match those in the
natural stream near the crossing, and the substrate used should be natural and match the stream
substrate. These guidelines are similar to the hydraulic simulation and stream simulation methods.
No mention is made of hydraulic design or culvert retrofit requirements.
B.14 Ohio (Tumeo and Pavlick, 2011)
In compliance of the nationwide Clean Water Act, the EPA requires that all new culvert
installations be bankfull culverts. The culverts should span the bankfull width of the stream, should
be embedded, and should mimic the characteristics of the natural stream bed.
B.15 Oregon (Oregon Department of Fish and Wildlife, 2006)
Stream simulation is the primary option listed for new culvert installations. No other
approved methods are given. Any alternate installation options must be approved by the
Department of Fish and Wildlife on a case by case basis.
B.16 Pennsylvania (Pennsylvania Department of Transportation, 2009)
Culverts should be designed so that flow depth and velocity do not impede fish passage.
Baffles are recommended for steep slopes, and culvert embedment is recommended for mild
slopes. The recommendations are similar to hydraulic design methods, and include designing for
the specific species that are present in the stream of interest.
42
B.17 Vermont (Bates and Kirn, 2009)
Stream simulation is the recommended method for new and replacement culverts. However
a variation known as the low-slope design method can also be used in certain conditions. The
hydraulic design method is allowed for retrofit culverts, and for new and replacement culverts
where stream simulation is not feasible. In addition to flow velocity and flow depth requirements,
the hydraulic design guidelines also include turbulence criteria. This is especially applicable in
roughened channel culverts, which are a subset of hydraulic design culverts.
B.18 Virginia (Fitch, 1995)
The study recommends a design approach that is similar to both hydraulic design and
hydraulic simulation. The culvert should be embedded and should match the stream slope, but a
maximum flow velocity is also introduced. Increased roughness is recommended to ensure that the
velocity requirement is met on steeper slopes.
B.19 Washington (Barnard et al., 2013)
Bridges are the preferred crossing method when possible, but culverts may also be used.
The preferred culvert design methods for fish passage are stream simulation culverts and no-slope
culverts (which should only be used on small, low gradient streams). The hydraulic design method
is allowed in limited scenarios, including retrofits and locations that require exceptionally long or
steep culverts. The given state standards are based on the swimming abilities of a 6 inch trout, but
other fish species can be used when the information is available. There are design velocity, depth,
and turbulence criteria for hydraulic design. The roughened channel method is also discussed.
43