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

viii

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

ix

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.

13

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

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33

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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

37

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

38

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.

39

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.

40

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

B.20 Wisconsin (Wisconsin Department of Natural Resources, 2007)

Bottomless plate arch and pipe arch culverts are the preferred type of culvert installation.

Closed bottom culverts can also be used as long as they don’t create velocity or depth barriers.

44