U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the U.S. Army Corps of Engineers

An Evaluation of Fish Behavior Upstream of the Water 

Temperature Control Tower at Cougar Dam, Oregon, 

Using Acoustic Cameras, 2013

Open-File Report 2015–1124

U.S. Department of the Interior

U.S. Geological Survey

An Evaluation of Fish Behavior Upstream of the Water 

Temperature Control Tower at Cougar Dam, Oregon, 

Using Acoustic Cameras, 2013 

By Noah S. Adams, Collin D. Smith, John M. Plumb, Gabriel S. Hansen, and John W. Beeman 

Prepared in cooperation with the U.S. Army Corps of Engineers

Open-File Report 2015–1124
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director

U.S. Geological Survey, Reston, Virginia: 2015

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Suggested citation:

Adams, N.S., Smith, C.D., Plumb, J.M., Hansen, G.S., and Beeman, J.W., 2015, An evaluation of fish behavior 

upstream of the water temperature control tower at Cougar Dam, Oregon, using acoustic cameras, 2013: U.S. 

Geological Survey Open-File Report 2015-1124, 62 p., http://dx.doi.org/10.3133/ofr20151124. 

ISSN 2331-1258 (online)
iii

Acknowledgments

This study was completed with assistance from many people and organizations. U.S Army 

Corps of Engineers and Reservoir Control staff at Cougar Dam were instrumental in coordinating our 

activities to install equipment at the dams, as were David Griffith and Fenton Khan at the Portland 

District office. Our administrative and science colleagues at the Columbia River Research Laboratory, 

particularly Scott Brewer, Theresa Liedtke, Gary Rutz, Matt Sholtis, Tyson Hatton, Amy Hansen, and 

Nick Swyers contributed greatly to this study. The report was improved with review comments from 

Michael Horn and Lisa Gee. This study was funded by the U.S. Army Corps of Engineers under 

contract W66QKZ30864777. 
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Contents

Acknowledgments.......................................................................................................................................................iii

Abstract ...................................................................................................................................................................... 1

Introduction................................................................................................................................................................. 1

Methods...................................................................................................................................................................... 5

Dam Operations and Environmental Conditions ..................................................................................................... 5

Acoustic Camera Surveillance Systems.................................................................................................................. 5

Data Collection........................................................................................................................................................ 6

Data Processing and Analysis................................................................................................................................. 7

Data Analysis ...................................................................................................................................................... 9

Evaluating Direction and Travel Speed of Fish Toward Water Temperature Control Tower................................ 9

Evaluating Numerical Response of Fish Movement Toward Water Temperature Control Tower...................... 10

Evaluating Fish Track Density Upstream of Water Temperature Control Tower ............................................... 11

Results...................................................................................................................................................................... 11

Data Processing.................................................................................................................................................... 11

Environmental Conditions and Dam Operations ................................................................................................... 12

Fish Movements.................................................................................................................................................... 15

Spring................................................................................................................................................................ 15

Fish Directions............................................................................................................................................... 15

Fish Depth ..................................................................................................................................................... 21

Fish Speed and Duration of Observation....................................................................................................... 23

Quantifying Movement Toward the Water Temperature Control Tower......................................................... 26

Timing of Detection........................................................................................................................................ 30

Fall .................................................................................................................................................................... 32

Fish Directions............................................................................................................................................... 32

Fish Depth ..................................................................................................................................................... 38

Fish Speed and Duration of Observation....................................................................................................... 40

Quantifying Movement Toward Water Temperature Control Tower............................................................... 44

Timing of Detection........................................................................................................................................ 47

Fish Track Density ................................................................................................................................................ 49

Discussion ................................................................................................................................................................ 49

References Cited...................................................................................................................................................... 51

Appendix A. Sample Dates Selected for Analysis of DIDSON and ARIS Acoustic Camera Data Collected 

at the Cougar Reservoir Water Temperature Control (WTC) Tower, Oregon, 2013 ................................................. 53

Appendix B. Rose Plots and Circular Histograms of Mean Travel Directions of Fish Collected by Acoustic 

Cameras by Depth and Photoperiod at Cougar Reservoir and Dam, Oregon .......................................................... 55

Appendix C. Density Plots of Fish Target Locations from DIDSON and ARIS Acoustic Camera Data 

Collected during the Fish Behavior Evaluations at Cougar Reservoir and Dam, Oregon, 2013 ............................... 59
vi 

Figures

Figure 1. Photograph showing water temperature control (WTC) tower in the forebay of 

Cougar Reservoir, Oregon......................................................................................................................................... 2

Figure 2. Cross section of water temperature control (WTC) tower showing water elevation at full 

conservation and minimum flood control pool and intake elevations of the regulating outlet (RO) and

powerhouse penstock, Cougar Reservoir, Oregon .................................................................................................... 3

Figure 3. Orthoimage showing water temperature control (WTC) tower, and the floating acoustic camera 

platforms at Cougar Dam, Oregon............................................................................................................................. 6

Figure 4. Schematic showing spring and fall coverage areas of the DIDSON®, ARIS®, and BlueView® 

acoustic cameras near the water temperature control (WTC) tower at Cougar Reservoir, Oregon, 2013 ................. 7

Figure 5. Data flow of semiautomated Echoview® processing structure used to process acoustic camera 

targets at the water temperature control (WTC) tower at Cougar Reservoir, Oregon, 2013 ...................................... 8

Figure 6. Plots showing mean daily project discharge and head over the weir gates (top) and forebay 

elevation and temperature (bottom) at Cougar Reservoir. Oregon, May 1–November 14, 2013 ............................. 12

Figure 7. Plot showing daily dam operating conditions for discharge through the regulating outlet and 

turbines at Cougar Reservoir and Dam, Oregon, May 1–November 14, 2013......................................................... 13

Figure 8. Rose plots and circular histograms of mean directions (degrees) of 30–60 and 60–90 

millimeter (mm) fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod 

(day, night, or combined) at Cougar Reservoir and Dam, Oregon, spring 2013 ...................................................... 16

Figure 9. Rose plots and circular histograms of mean directions (degrees) of 90–250 and >300 

millimeter (mm) fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod 

(day, night, or combined) at Cougar Reservoir and Dam, Oregon, spring 2013 ...................................................... 17

Figure 10. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the 

beam of the DIDSON® acoustic camera upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, spring 2013 ............................................................................................................... 19

Figure 11. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the 

beam of the ARIS® acoustic camera upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, spring 2013 ............................................................................................................... 20

Figure 12. Graph showing hourly mean depth of fish (in meters [m]), by size category (in millimeters [mm]), 

in the area covered by DIDSON® and ARIS® acoustic cameras, which were upstream of the water temperature 

control (WTC) tower at Cougar Reservoir and Dam, Oregon, spring 2013.............................................................. 21

Figure 13. Box and whisker plots of the depth of fish (in meters [m]) observed under different camera 

angles using DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, spring 2013 .......... 22

Figure 14. Graphs showing distributions of fish travel speeds (in meters per second [m/s]) and the amount 

of time fish spent within the acoustic beams (in seconds [s]) of the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 24

Figure 15. Plots for multiple regression model estimates of mean travel speed of fish (in meters per 

second [m/s]), by size category (in millimeters [mm]), within the beams of the DIDSON® and ARIS® acoustic 

cameras upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, 

spring 2013.............................................................................................................................................................. 26

Figure 16. Scatter plots showing number (n) of fish moving toward the water temperature control (WTC) 

tower (per 3-second interval) and total number of fish observed in the acoustic beam (per 3-second interval) 

of the DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, spring 2013 ..................... 28

Figure 17. Effects plots for the reduced Poisson rate regression modeling the numbers of fish traveling 

toward the water temperature control (WTC) tower while in the beam of the DIDSON® acoustic camera at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 29
vii 

Figure 18. Effects plots for the reduced Poisson rate regression model of numbers of fish traveling 

toward the water temperature control (WTC) tower while in the beam of the ARIS® acoustic camera at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 30

Figure 19. Graph showing hour of detection of fish, by size category (in millimeters [mm]), using the 

DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 31

Figure 20. Graph showing hour of detection of fish, by size category (in millimeters [mm]), that were observed 

traveling toward the water temperature control (WTC) tower using the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 31

Figure 21. Rose plots and circular histograms of mean directions (degrees) of 30–60 and 60–90 

millimeter (mm) fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod 

(day, night, or combined) upstream of the water temperature control (WTC) tower at Cougar Dam, 

Oregon, fall 2013 ..................................................................................................................................................... 33

Figure 22. Rose plots and circular histograms of mean directions (degrees) of 90-250 and >300 

millimeter (mm) fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod 

(day, night, or combined) upstream of the water temperature control (WTC) tower at Cougar Dam, 

Oregon, fall 2013 ..................................................................................................................................................... 34

Figure 23. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the 

beam of the DIDSON® acoustic camera upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, fall 2013 .................................................................................................................... 36

Figure 24. Effects plots for the full circular-linear model of mean directions fish (in degrees) within the 

beam of the ARIS® acoustic camera upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, fall 2013 .................................................................................................................... 37

Figure 25. Graph showing hourly mean depth of fish (in meters [m]), by size category 

(in millimeters [mm]), in the area covered by DIDSON® and ARIS® acoustic cameras, which 

were upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, fall 2013 ..................................................................................................................................................... 38

Figure 26. Box and whisker plots of the depth of fish (in meters [m]) observed under different camera angles 

using DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013........................... 40

Figure 27. Graphs showing distributions of fish travel speeds (in meters per second [m/s]) and the 

amount of time fish spent within the acoustic beams of the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, fall 2013...................................................................................................................... 41

Figure 28. Plots for the multiple regression model estimates of mean travel speed of fish (in 

meters per second [m/s]), by size category (in millimeters [mm]), within the beams of the DIDSON® and 

ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar Reservoir and 

Dam, Oregon, fall 2013............................................................................................................................................ 43

Figure 29. Scatter plots showing number (n) of fish moving toward the water temperature control (WTC) 

tower (per 3-second interval) and total number of fish observed in the acoustic beam (per 3-second interval) 

of the DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013........................... 45

Figure 30. Effects plots for the reduced Poisson rate regression modeling the numbers of fish traveling 

toward the water temperature control (WTC) tower while in the beam of the DIDSON® acoustic camera at 

Cougar Reservoir and Dam, Oregon, fall 2013........................................................................................................ 46

Figure 31. Effects plots for the reduced Poisson rate regression model of the numbers of fish traveling 

toward the water temperature control (WTC) tower while in the beam of the ARIS® acoustic camera at 

Cougar Reservoir and Dam, Oregon, fall 2013........................................................................................................ 47
viii

Figure 32. Graph showing hour of detection of fish, by size category (in millimeters [mm]), using the 

DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, fall 2013 .................................................................................................................... 48

Figure 33. Graph showing hour of detection of fish, by size category (in millimeters [mm]), that were 

observed moving toward the water temperature control (WTC) tower using the DIDSON® and ARIS® 

acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013 ....................................................................... 48

Tables

Table 1. Mean hourly summary statistics of dam operations and environmental conditions at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 13

Table 2. Mean hourly summary statistics of dam operations and environmental conditions at 

Cougar Reservoir and Dam, Oregon, fall 2013........................................................................................................ 14

Table 3. Mean directions (radians) and concentration parameters by fish-size category and 

acoustic-camera type (DIDSON® or ARIS®) at Cougar Reservoir and Dam, Oregon, spring 2013.......................... 15

Table 4. Results for circular-linear models of mean directions (radians) of fish in the acoustic beams of the 

DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, spring 2013 ............................................................................................................... 18

Table 5. Sample size, and mean, standard deviation, minimum, and maximum depths of each fish-size 

category observed with the DIDSON® and ARIS® acoustic cameras upstream of the water temperature 

control (WTC) tower at Cougar Reservoir and Dam, spring 2013............................................................................ 22

Table 6. Summary statistics for the travel speeds and duration of fish observed with the DIDSON® and 

ARIS® acoustic cameras at the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, spring 2013................................................................................................................................................ 23

Table 7. Results for multiple regression models of mean travel speeds ( m s/ ) of fish while in the 

acoustic beams of the DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) 

tower at Cougar Reservoir and Dam, Oregon, spring 2013..................................................................................... 25

Table 8. Results for Poisson rate regression models of fish moving toward the water temperature 

control (WTC) tower while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, Oregon, spring 2013................................................................................................... 27

Table 9. Results for reduced Poisson rate regression models of fish moving toward the water temperature 

control (WTC) tower while in the acoustic beam of the DIDSON® and ARIS® cameras at Cougar Reservoir 

and Dam, Oregon, spring 2013................................................................................................................................ 28

Table 10. Mean directions (radians) and concentration parameters by fish-size category and 

acoustic-camera type (DIDSON® or ARIS®) at Cougar Reservoir and Dam, Oregon, fall 2013............................... 32

Table 11. Results for circular-linear models of mean directions (radians) of fish in the acoustic beams 

of the DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower 

at Cougar Reservoir and Dam, Oregon, fall 2013.................................................................................................... 35

Table 12. Sample size, and mean, standard deviation, minimum, and maximum depths of each fish-size 

category observed with the DIDSON® and ARIS® acoustic cameras upstream of the water temperature 

control (WTC) tower at Cougar Reservoir, Oregon, fall 2013 .................................................................................. 39

Table 13. Summary statistics for the travel speeds and duration that fish were observed by the

DIDSON and ARIS acoustic cameras at the water temperature control (WTC) tower at Cougar Reservoir

and Dam, Oregon, fall 2013..................................................................................................................................... 41
ix

Table 14. Results for multiple regression models of mean travel speeds (square root of meter per 

second [ m s/ ]) of fish while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras 

upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, fall 2013 ........... 42

Table 15. Results for reduced Poisson rate regression models of fish traveling toward the water temperature 

control (WTC) tower while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras at Cougar 

Reservoir and Dam, Oregon, fall 2013 .................................................................................................................... 44

Table 16. Results for reduced Poisson rate regression models with removal of nonsignificant predictors of fish 

traveling toward the water temperature control (WTC) tower while in the acoustic beams of the DIDSON® and ARIS 

acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013 ....................................................................... 46

Conversion Factors

Inch/Pound to International System of Units

Multiply By To obtain

foot (ft) 0.3048 meter (m)

cubic foot per second (ft3/s) 0.02832 cubic meter per second (m3/s)

International System of Units to Inch/Pound

Multiply By To obtain

millimeter (mm) 0.03937 inch (in.)

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

meter per second (m/s) 3.281 foot per second (ft/s)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as °F = (1.8 × °C) + 32.

Datums 

Vertical coordinate information is referenced to the National Geodetic Vertical Datum of 1929 (NGVD 29). 

Horizontal coordinate information is referenced to the World Geodetic System of 1984 (WGS 84).

Elevation, as used in this report, refers to distance above the vertical datum.

Abbreviations

AIC Akaike Information Criterion

CSV comma-separated value

GLMs Generalized Linear Models

PFFC Portable Floating Fish Collector

RO regulating outlet

R2 coefficient of determination

USACE U.S. Army Corps of Engineers

UWR Upper Willamette River

WTC Water Temperature Control Tower
x 

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1 

An Evaluation of Fish Behavior Upstream of the Water 

Temperature Control Tower at Cougar Dam, Oregon, Using 

Acoustic Cameras, 2013

By Noah S. Adams, Collin D. Smith, John M. Plumb, Gabriel S. Hansen, and John W. Beeman

Abstract

This report describes the initial year of a 2-year study to determine the feasibility of using 

acoustic cameras to monitor fish movements to help inform decisions about fish passage at Cougar Dam 

near Springfield, Oregon. Specifically, we used acoustic cameras to measure fish presence, travel speed, 

and direction adjacent to the water temperature control tower in the forebay of Cougar Dam during the 

spring (May, June, and July) and fall (September, October, and November) of 2013. Cougar Dam is a 

high-head flood-control dam, and the water temperature control tower enables depth-specific water 

withdrawals to facilitate adjustment of water temperatures released downstream of the dam. The 

acoustic cameras were positioned at the upstream entrance of the tower to monitor free-ranging 

subyearling and yearling-size juvenile Chinook salmon (Oncorhynchus tshawytscha). Because of the 

large size discrepancy, we could distinguish juvenile Chinook salmon from their predators, which 

enabled us to measure predators and prey in areas adjacent to the entrance of the tower. We used linear 

models to quantify and assess operational and environmental factors—such as time of day, discharge, 

and water temperature—that may influence juvenile Chinook salmon movements within the beam of the 

acoustic cameras. Although extensive milling behavior of fish near the structure may have masked 

directed movement of fish and added unpredictability to fish movement models, the acoustic-camera 

technology enabled us to ascertain the general behavior of discrete size classes of fish. Fish travel speed, 

direction of travel, and counts of fish moving toward the water temperature control tower primarily were 

influenced by the amount of water being discharged through the dam. 

Introduction

The U.S. Army Corps of Engineers (USACE) operates the Willamette Project (Project) in 

western Oregon, including 13 dams, about 68 km of revetments, and several fish hatcheries. The 

primary purpose of the Project is flood control, but it also is operated to provide hydroelectricity, 

irrigation water, navigation, instream flows for wildlife, and recreation. The dams, including Cougar 

Dam, are all on tributaries of the Willamette River. The National Oceanic and Atmospheric 

Administration determined in a recent Biological Opinion that the Project jeopardizes the sustainability 

of anadromous fish stocks in the Willamette River Basin (National Oceanic and Atmospheric 

Administration, 2008). 
2 

Cougar Dam is a 158 m-high rock-fill dam on the South Fork of the McKenzie River, about 63 

km east of Springfield, Oregon. The dam, completed in 1964, is owned and operated by the USACE, 

Portland District. The powerhouse has a hydraulic capacity of 1,050 ft3/s and uses two Francis turbine 

units capable of generating a total of 25 megawatts. The dam also has a spillway with two Tainter gates, 

and a water temperature control (WTC) tower that was installed in 2005 (fig. 1). Water passes the dam 

through the WTC tower either into a flow regulating outlet (RO) or through the powerhouse penstock, 

both of which are supplied through a common wet well. The reservoir is used primarily for flood 

control, power generation, and irrigation. The forebay elevation normally is maintained at high levels 

during summer months and low levels during winter months. The maximum conservation-pool 

elevation of 1,690 ft typically is reached in May, and the minimum flood-control pool elevation of 1,532 

ft usually is reached in December.

Juvenile salmon that migrate downstream are required to pass through the WTC tower. Prior to 

installation of the WTC tower, water passing through the dam was drawn from deep within the reservoir 

and often was too cold for attraction and spawning of salmon downstream. The WTC tower allows the 

use of water from various depths in the forebay to provide water temperatures suitable for salmon. All 

water passing through the dam enters the WTC tower and passes to the tailrace either through the RO at 

a centerline elevation of 1,485.0 ft, or through the powerhouse penstock intake at a centerline elevation 

of 1,424.8 ft. At water elevations of 1,571.0 ft or greater, water passes over or between weir gates into 

the wet well of the temperature control tower and then through the RO or the penstock (fig. 2). At 

elevations lower than 1,571.0 ft, water can pass into the wet well through either the RO bypass gate 

(centerline elevation 1,488.5 ft) or the penstock bypass gate (centerline elevation 1,429.0 ft). A fish 

ladder and trapping facility are used to collect adult salmon in the tailrace for transportation upstream 

and provide a means of upstream passage for adult salmon. There currently is no passage route designed 

for downstream passage of juvenile salmon. 

Figure 1. Photograph showing water temperature control (WTC) tower in the forebay of Cougar Reservoir, 

Oregon. Photograph by John Beeman, U.S. Geological Survey, 2010. 
3 

Figure 2. Cross section of water temperature control (WTC) tower showing water elevation at full conservation and 

minimum flood control pool and intake elevations of the regulating outlet (RO) and powerhouse penstock, Cougar 

Reservoir, Oregon. Schematic from U.S. Army Corps of Engineers.

The 2008 Willamette Biological Opinion requires improvements to operations or structures to 

reduce impacts on Upper Willamette River (UWR) Chinook salmon (Oncorhynchus tshawytscha) and 

UWR steelhead (Oncorhynchus mykiss) (National Oceanic and Atmospheric Administration, 2008). The 

Opinion includes a requirement to install fish passage facilities to provide safe downstream passage for 

juvenile salmonids at Cougar Dam by 2014, a goal that has yet to be reached but may be achieved 
4 

through operational or structural alternatives. Information about the presence and behavior of juvenile 

salmonids and predator activity near the upstream face of the WTC tower during various dam operating 

conditions can be used to inform decisions about downstream passage alternatives. 

Several important factors affecting dam passage rates at Cougar Dam have been identified. A 

study of juvenile Chinook salmon implanted with acoustic transmitters and released near the head of the 

reservoir showed that dam passage was positively related to the night diel period and increased dam 

discharge and negatively related to high reservoir elevation (Beeman and others, 2013). Volitional dam 

passage rates at night were about 9 times greater than during the day. As such, the greatest dam passage 

rates occurred at night during high discharge and low pool elevation. Data from radio-tagged fish 

released near the water surface at the WTC tower and from volitionally migrating fish released in the 

reservoir corroborate the preponderance of passage through the WTC tower at night (Beeman and 

others, 2012, 2014). 

To meet the requirement of the Biological Opinion, the USACE installed a Portable Floating 

Fish Collector (PFFC) near the WTC tower in early 2014 to test surface-passage technology as a means 

to collect juvenile salmonids at Cougar Dam. The objective of this study was to use acoustic cameras to 

summarize the presence and behavior of untagged fish at Cougar Reservoir and Dam to inform 

decisions about the arrival timing, movements, and predator activity near the upstream face of the WTC 

tower, prior to the operation of the PFFC. A similar evaluation of fish movements upstream of the WTC 

tower was done in 2010 (Khan and others, 2012), but just one low-resolution acoustic camera was used, 

and a small fraction of the data collected was analyzed to quantify fish behavior just upstream of the 

WTC tower. Therefore, our study attempts to overcome these shortcomings by using multiple highresolution acoustic cameras and an automated proofing process that will allow for the inclusion of more 

data in the analysis. These improvements should enable a better characterization of the response of 

juvenile salmon in relation to biological and environmental factors such as day and night, fish size, 

water temperature, river flow, and the presence of other predatory fish, such as Bull Trout (Salvelinus 

confluentus). 

This study used acoustic cameras to collect behavioral data on juvenile salmonids and their 

predators at the Cougar Reservoir and Dam WTC tower during spring through fall of 2013. Acoustic 

cameras are capable of recording near-video quality sonar images in a wide variety of habitats and 

environmental conditions (Tiffan and others, 2005; Doehring and others, 2011; Able and others, 2014 ). 

An advantage of using acoustic cameras for behavioral observations of aquatic species is that the images 

are constructed from data collected from target ensonification, and not from methods requiring visual 

observation. Therefore, data collection can occur in turbid conditions (Liedtke and others, 2013) without 

altering fish behavior, or can be used at night to investigate diurnal effects, which are an important 

behavioral factor for migrating salmonids (Dunbar, 2008; Pavlov and others, 2009). Data collected with 

the acoustic camera provides information on fish size (target strength), entrance depth, movement 

direction, and fish travel speed. The date, time, water temperature, and river flow also were recorded 

concurrently with the acoustic camera to enable us to assess the response of fish to environmental 

conditions upstream of the WTC tower. A Generalized Linear Models (GLMs) framework was then 

used to assess the response of fish to biological and environmental covariates. Using GLMs for the 

different responses (for example, directions or counts) allowed different error structures of the data to be 

accounted for while enabling the assessment of multiple effects on the different responses by fish 

upstream of the tower. 
5 

Methods

Dam Operations and Environmental Conditions

Powerhouse discharge, discharge through the regulating outlet (RO), forebay elevation, head 

over the temperature control tower weir gates, and water temperature data were summarized to 

document the environmental conditions of juvenile Chinook salmon during the 2013 study periods. 

Hourly powerhouse discharge, RO discharge, and forebay elevation data were obtained from the 

USACE Web site http://www.nwd-wc.usace.army.mil/perl/dataquery.pl?k=id:CGR. Weir elevation and 

RO gate opening data were provided by the USACE. Hourly temperature data were obtained from the 

USACE Web site http://www.nwd-wc.usace.army.mil/ftppub/water_quality/tempstrings/. Diel periods 

were assigned using U.S. Naval civil twilight data for Springfield, Oregon, which was obtained at 

http://www.usno.navy.mil/USNO/astronomical-applications. Data were summarized using hourly 

observations, but mean daily values were plotted to increase clarity in the plots. Water-elevation data 

and fish depths are presented in feet and discharge is presented as cubic feet per second because this is 

the preferred local convention. Head differential was calculated by subtracting the water-surface 

elevation inside the tower from the water-surface elevation outside the tower. Water-elevation data were 

provided by the USACE. 

Acoustic Camera Surveillance Systems

In this study, we used three acoustic cameras with different resolution and field-of-view 

capabilities to collect data on fish movements. A BlueView® P900 (0.9 MHz, 130° beam and 100-m 

range) was used to monitor fish behavior upstream of the WTC tower. The higher resolution DIDSON®

300 (1.8 MHz, 29° beam, 15-m range) and ARIS® 3000 (3.0 MHz, 30° beam, 5-m range) acoustic 

cameras were mounted on the sides of the WTC tower to monitor fish behavior at the entrance of the 

structure. We selected these different acoustic-camera technologies to balance the likelihood of 

observing the greatest number of fish targets, while still capturing sufficient behavioral data from small 

fish targets. The minimum size of fish targets that generally can be observed varies by camera type, with 

the ARIS and DIDSON acoustic cameras capable of detecting fish targets greater than 30 and 40 mm, 

respectively, whereas the BlueView acoustic camera was limited to detecting targets larger than about 

250 mm. Positively determining the species of each individual target, especially with small fish, is not 

possible with acoustic camera technology. 

The acoustic cameras were deployed from two 14-ft floating platforms positioned on the 

southeastern and southwestern corners of the WTC tower (fig. 3). The platforms were guided by 

stainless steel cables that were vertically tensioned on the exterior of the parapet walls, which allowed 

the vertical movement of the platforms with fluctuations in pool elevation, but restricted lateral 

movement. Spring-tensioned spoolers were installed on each platform to provide automatic tensioning 

of lines for the guidance and support of data and electrical cables from the top of the WTC tower to the 

deck of each platform. 
6 

Figure 3. Orthoimage showing water temperature control (WTC) tower, and the floating acoustic camera platforms 

at Cougar Dam, Oregon. Photograph by U.S. Geological Survey, High Resolution State Orthoimagery for Oregon, 

2013, 0.5-meter resolution. 

All acoustic cameras were attached to poles mounted on each platform, and lowered to a depth 

of 2 m below the surface of the water. The BlueView was mounted on the east platform, and was 

pointed directly away from the tower (fig. 4). During the spring season, the DIDSON was mounted on 

the west platform, and aimed horizontally (west to east) across the west and center WTC tower intakes. 

Because of anticipated underwater obstructions that would be present when the elevation of the pool 

was low, the DIDSON was moved prior to the fall season to the east platform and positioned 

horizontally (east to west) across the east and center WTC tower intakes. The ARIS was deployed from 

the east platform and aimed (east to west) across the east WTC tower intake for both the spring and fall 

seasons. All three acoustic cameras were deployed on rotators to provide precise aiming of the cameras. 

To capture vertical distribution data near the upstream face of the WTC tower, the rotators were 

automated to randomly tilt the DIDSON and ARIS acoustic cameras every 36 min, at three angles 

through the water column (0o, 25o, and 50o from horizontal angle).

Data Collection

Data were collected continuously at the WTC tower starting on May 1 and ending on July 11, 

2013, for the spring season, and again between September 26 and November 14, 2013, for the fall 

season. We collected about 6,300 h of data over the 120 d that the acoustic cameras were recording. 

Data collection was interrupted only when equipment malfunctioned or when the cameras were 

removed for servicing and calibration between the spring and fall seasons. All data collected were stored 

to hard drives for archival and subsequent processing. 
7 

Figure 4. Schematic showing spring and fall coverage areas of the DIDSON®, ARIS®, and BlueView® acoustic 

cameras near the water temperature control (WTC) tower at Cougar Reservoir, Oregon, 2013. 

Data Processing and Analysis

Traditionally, acoustic camera data are processed by having a person review each file in real 

time, record the number of fish, and, if desired, characterize swimming behavior. This is very time 

consuming and often limits the amount of data that can be included in the analysis. Alternatively, signal 

processing software can be used to automate data processing, thereby allowing a greater proportion of 

data to be processed. Other researches have used this method when the fish of interest are relatively 

large (that is, greater than 300 mm fork length), but few have successfully implemented it when fish are 

smaller than 150 mm fork length. A main objective for the 2013 evaluation was to develop automated 

data processing procedures that would allow more of the information collected on small fish to be 

included in the analysis. To do this, we used Echoview® software (version 5.4, Myriax Pty. Ltd., 

Hobart, Tasmania, Australia) to process the data. The Echoview platform allows the operator to use 

successive filters to manipulate data in order to enhance the acoustic signal and remove static objects 

and noise from acoustic returns (Kang, 2011). Non-stationary acoustic returns are then identified as 

targets within individual camera frames and converted to two-dimensional position and time data, which 

can then be applied to target tracking. The conceptual layout of the virtual variable interface for the 

processing of acoustic camera data is shown in figure 5. Each object in the layout represents operational 

steps applied to the original data, which allows each individual step to be optimized to maximize 

efficiency and improve consistency (Boswell and others, 2008). 

Initially, geospatial and positional data for each acoustic camera were associated with the 

geographic location of the platform to enable each target to be geospatially referenced (fig. 5, step 1). 

Next, acoustic camera data files were loaded into Echoview and converted to volume back-scattering 

strength (Sv) from raw signal magnitudes (fig. 5, step 2). To remove stationary objects (WTC tower) 

from the data, targets were deemed immobile by calculating the mean results of the four previous pings, 

which also had targets that did not move. These targets were then removed from the dataset (fig. 5 step 

3). Next, static noise was removed by implementing a sample statistic subtract operator (fig. 5 step 4). 
8 

This process implements a synthetic ping into the background signal, then subsequently subtracts the 

synthetic ping from each actual ping. This process leads to an increase in the signal-to-noise ratio by the 

removal of pings returned from inanimate objects and background noise. Following subtraction of 

background noise, the image was enhanced by applying a convolution (3×3 median) algorithm filter 

(fig. 5, step 5). This filter used the median value of a data point and the eight direct neighboring cells to 

remove interference and smooth the image without significantly affecting the shape of the target.

The next step was to use the multibeam target detection operator to generate multibeam targets 

from the multibeam data (fig. 5, step 6). These three-dimensional targets were created from groups of 

adjoining data points (clusters), which were then reduced to point data that include the geometric values 

of each fish target. The target conversion process was used next (fig. 5, step 7) to transform multibeam 

targets into single-point targets. Because of the multiple acoustic cameras operating near each other, 

much crosstalk noise in the form of vertical banding was not removed from the data by the filters in 

Echoview. To further reduce the volume of these non-fish targets in the data files, the filtered data were 

imported into SAS (version 9.3 of the SAS System for Windows, Copyright© 2002–2010, SAS Institute 

Inc., Cary, North Carolina), and vertical banding was removed by comparing consecutive pings at a 

given range and eliminating the stationary noise (fig. 5, step 8). 

Following the operational steps of filtering noise and smoothing the data, all single targets with 

all associated target properties were exported as comma-separated values (CSVs; fig. 5, step 9). These 

CSV files were then reimported into Echoview for further tracking and analysis (fig. 5, step 10). The 

purpose of fish tracking is to obtain counts and movements of individual fish, along with their 

associated behavioral and morphometric data (Simmonds and MacLennan, 2005). 

Figure 5. Data flow of semiautomated Echoview® processing structure used to process acoustic camera targets at 

the water temperature control (WTC) tower at Cougar Reservoir, Oregon, 2013. 
9 

Data Analysis

Summary statistics of fish targets derived from Echoview (for example, mean length, direction, 

speed, angle, and orientation) were imported into SAS for subsequent proofing and to combine datasets 

with dam operations and environmental conditions. Data were proofed to eliminate non-valid records or 

records that did not provide measurable morphometric or behavioral data. To consider a fish track as 

valid, we required that each fish track consisted of at least five pings and had a minimum duration of 

detection of 1 s. The acoustic-camera technology cannot distinguish fish that have entered and exited the 

field of view multiple times; therefore, the detection duration for each individual fish track within a 

camera beam was determined by the time a fish was first detected by the camera, to the time that the 

fish exited the camera view. Datasets for each acoustic-camera type and spring and fall seasons were 

then exported as CSV files for statistical modeling. 

Evaluating Direction and Travel Speed of Fish Toward Water Temperature Control Tower

The direction of a given fish j, dj, within the acoustic beam may be assumed to follow a von 

Mises distribution with a mean direction μ and concentration parameter κ. To summarize these data, we 

use circular statistics to calculate means and measures of variability (Mardia and Jupp, 2000) and use a 

circular-linear model as described by Pewsey and others (2013), which was implemented in R software 

(R Core Team, 2014). By proposing a set of candidate model subsets from a global model, we assess 

how combinations of covariates affect fish direction just upstream of the WTC tower. For example, the 

mean direction of the fish, μ, in the acoustic beam (in radians) for the dj may be expressed as

1 size 2 diel 3 4 =+ ⋅ + ⋅ + ⋅+ ⋅ + ( ) j j d d gF P Q T μg g g g e (1)

where μ, κ, and the γ coefficients for each predictor will be estimated using maximum likelihood. The 

variable Fsize is the maximum target strength of the fish in the array providing a rough measure of fish 

size, Pdiel is a two-level class factor that resolves to 1 if the fish entered the acoustic beam during night 

or 0 if during the day. Water flow (Q) and water temperature (T) are factors that may affect fish passage 

and behavior upstream of dams, so we included total discharge and the water temperature during the 

hour the fish enter the acoustic beam as continuous covariates in the model. These predictors and their 

coefficients are linked to the response using the following link function as 1

gu u ( ) 2 tan ( ) − = , where tan1

 is also known as the arc tangent. 

Using a similar set of predictors, we also model factors affecting the mean travel speed of fish,

j v , toward the WTC tower as 

 = + ⋅ + ⋅ + ⋅+ ⋅+ ⋅ + 0 1 size 2 diel 3 4 5 j j v v ββ β β β β e F P Q T DD (2)

where the βs are coefficients to be estimated. We assume the errors, j v ε , are normally distributed about 

the model for the j v . We square-root transformed the response to fulfill the assumption of normally 

distributed errors. Preliminary attempts to account for different error distributions using link functions 

were relatively unsuccessful compared to the more simple square-root transformation. We used standard 

diagnostics for linear models to assess goodness of fit. For example, we calculated variance inflation 

factors to assess collinearity among the predictors, as well as use diagnostic plots to determine outliers 

and assess homogeneity among the residuals. 
10 

Evaluating Numerical Response of Fish Movement Toward Water Temperature Control Tower

Another approach to modeling fish responses in the acoustic beam is to model the number of 

fish that exit the area ensonified by the acoustic beam toward the WTC tower given the total number of 

fish in the acoustic beam. When compiling these counts on a per unit of time basis, we can evaluate how 

factors might influence the number of fish moving toward the tower by using a Poisson rate regression 

(Faraway, 2006) to test hypotheses about the numerical response of fish to environmental covariates. On 

preliminary inspection of the data, the median observation time for a fish in the acoustic camera was 

about 3 s, which influenced the application of the Poisson rate regression to the counts of fish per unit 

time within the acoustic beams. First, to minimize the counting of a single fish as a multiple within a 

single observation in the analysis, we defined the time interval as 3 s, which roughly equaled the median 

residence time of fish in the beam (see section, “Results”). A consequence of using such a short time 

interval was a preponderance of zeros in the dataset. When using the DIDSON acoustic camera, 96 

percent (234,902 of 244,800) of all 3-s observations were zeros in the spring, and 94 percent (67,332 of 

72,000) of all 3-s observations were zeros in the fall. Therefore, we conditioned all the following 

Poisson rate regressions on there being at least one fish present in the acoustic beam. 

The Poisson rate regressions, constructed from the logarithm of the number of fish that exit the 

acoustic beam toward the WTC tower (per unit time t) given the total number of fish that entered the 

acoustic beam, can be modeled as a function of covariates: 

WTC,

0 1 1, ,

beam,

log , ,     =+ + +

 

 t

e t n nt

t

N

x x

N

δδ δ (3)

where t is the given time period (most likely in minutes), x1,t, ..., xn,t are the values of n covariates for 

time period t, δ 1 , ..., n δ are the corresponding slope coefficients, and 0 δ is the intercept. To fit this 

model to the data, we can express this equation as

( ) ( ) WTC, beam, 0 1 1, , log log e t e t N N xx = ++ + + t , ,  n nt δδ δ (4)

and then use a generalized linear model with a Poisson family, a log link function, and an offset for 

loge(Nbeam,t) (that is, slope coefficient fixed to 1). This formulation assumes that the count of fish exiting 

toward the WTC tower (NWTC,t) is Poisson distributed. This assumption can be verified by estimating a 

dispersion parameter φ, (that is, (X2

/df)0.5; Agresti, 1996), which if greater than 1, may be used to adjust 

model selection statistics and standard errors of the coefficients. We also can test model fit by 

conducting a bootstrapped goodness-of-fit test (Efron and Tibshirani, 1993; Faraway, 2006). By 

including the numbers of predators in the acoustic beam as a covariate to the model, we should be able 

to assess how numbers of predators upstream of the WTC tower may affect the numbers of fish exiting 

the acoustic beam toward the WTC tower.

We used Akaike Information Criterion (AIC) to help determine the relative importance and 

strength of a given response (Burnham and Anderson, 2002). We compared relative differences in AIC 

values amongst the set of single-predictor models that are subsets of their respective full models 

(equations 1 and 2). For model selection, however, we took a more cursory and simple approach by 

simply deleting the non-significant predictors from the full models. 
11 

Evaluating Fish Track Density Upstream of Water Temperature Control Tower

The collected point samples for each individual fish track were used to create three-dimensional 

density plots of unique fish track locations for the volume sampled (Tecplot 360TM, Bellevue, 

Washington). The spatial resolution within the view of each acoustic camera was about 1 cm, and no 

interpolation of point data was performed. The magnitude of the point count is defined as the count of 

unique observations of each individual fish location within each cell. Datasets for each camera type and 

both spring and fall seasons were used for plotting location data for each size category of fish by diel 

period. 

Results

Data Processing

We divided the acoustic camera operation and data collection into spring and fall study periods. 

The spring study period was from May 1 to July 11, 2013, and the fall study period was from September 

26 to November 14, 2013. The cameras were removed for servicing and calibration between the spring 

and fall seasons, a time when smolt abundance at the WTC tower has been low (Khan and others, 2012). 

All acoustic cameras were removed on November 15, 2013, when the forebay elevation became 

insufficient for data collection in front of the WTC tower intakes. 

We were successful in using the Echoview software platform to automate the processing of the 

data collected with the acoustic cameras. These methods allow substantially more of the data to be 

processed in a relatively short time than has previously been possible using standard manual methods. 

However, the nature of the data collected in 2013 prevented us from realizing the maximum benefit of 

the automated process. First, there was a large amount of debris in the water immediately upstream of 

the WTC tower, which made it difficult to identify fish as they swam among the debris field. Second, 

wind and wave action caused the platforms that the cameras were mounted on to move. This gave the 

appearance that otherwise stationary objects were moving, which further complicated identifying fish 

targets in the beam. The level of debris in the water, combined with the moving platforms, made it 

difficult to fully implement the automated data processing methods we developed. As a result, it was not 

feasible to process all data, so we subsampled dates throughout the study period (appendix A). The 

duration of each subsampled date was from midnight to midnight. On each date, we randomly 

subsampled 15-min blocks of every hour for each 24-h period. For the DIDSON data, we subsampled 

and processed 34 days of the data collected in the spring and 10 days in the fall. For the ARIS data, we

subsampled and processed 30 days during the spring and 20 days during the fall. 

The high volume of debris and the moving platforms not only affected our ability to process the 

data, but it also hindered our ability to take full advantage of the automated tracking feature in the 

Echoview software. Once again, in future studies this feature would be implemented to increase the 

volume of data that could be used in the analysis. However, this was not the case in 2013, so instead we 

manually tracked all data (fig. 5 step 10) to ensure that fish targets were accurately determined and that 

targets from woody debris and noise were excluded from analysis. 

Finally, initial subsampling and inspection of the images collected with the BlueView acoustic

camera revealed that the 0.9 mHz camera was not capable of detecting either individual smolt-sized fish 

or schooling fish in this size range of interest. The limitation of this technology did not allow us to 

address the proposed research questions for this study, so no further processing or analysis was 

performed on the data collected with the BlueView acoustic camera. 
12 

Environmental Conditions and Dam Operations 

Dam operations and environmental conditions varied during the spring (fig. 6). The hourly total 

project discharge (mean 707.6 ft3/s, range 400.0–1,220.0 ft3/s) through the dam primarily was through 

the turbines and not the regulating outlet (fig. 7). Mean hourly discharge was 63.4 ft3/s (range 0.0–

1,050.0 ft3

/s) through the regulating outlet, and 644.2 ft3/s (range 60.0–1,000.0 ft3/s) through the 

powerhouse (table 1). The seasonal change in forebay elevation (mean 1,661.4 ft NGVD 29, range 

1,652.1–1,670.0 ft NGVD 29) and head elevation over the upper weir gates (mean 4.4 ft, range 1.1–10.2 

ft) also varied throughout the season (table 1), but this change was related to total discharge, which was 

positively related to the amount of head (r=0.73, p<0.0001, Pearson’s) such that when the total 

discharge was high, so was the head. The temperature of the top 13–19 ft of the reservoir increased 

through the spring season, with the mean hourly temperature of 13.0 °C (range 8.2–18.1 °C) (table 1). 

We did not find any marked differences in dam operations or water temperatures between day and night 

operations, although discharge through the regulating outlet was slightly higher at night, and turbine 

discharge was slightly higher during the day. 

Figure 6. Plots showing mean daily project discharge and head over the weir gates (top) and forebay elevation 

and temperature (bottom) at Cougar Reservoir. Oregon, May 1–November 14, 2013. Water temperature is the 

average of the upper 13–19 feet of the water column near the water temperature control (WTC) tower. 
13 

Figure 7. Plot showing daily dam operating conditions for discharge through the regulating outlet and turbines at 

Cougar Reservoir and Dam, Oregon, May 1–November 14, 2013. 

Table 1. Mean hourly summary statistics of dam operations and environmental conditions at Cougar Reservoir and 

Dam, Oregon, spring 2013. 

[SD, standard deviation; ft3/s, cubic foot per second; NGVD 29, National Geodetic Vertical Datum of 1929]

Dam operation Period Mean Median Range SD

Total project discharge (ft3/s) Overall 707.6 910.0 400.0–1,220.0 258.6

Day 711.2 910.0 400.0–1,220.0 258.4

Night 701.5 910.0 400.0–1,120.0 258.9

Powerhouse (ft3/s) Overall 644.2 460.0 60.0–1,000.0 283.8

Day 652.0 460.0 60.0–1,000.0 285.9

Night 631.1 460.0 60.0–1,000.0 280.1

Regulating outlet (ft3/s) Overall 63.4 0.0 0.0–1,050.0 228.5

Day 59.3 0.0 0.0–1,050.0 226.7

Night 70.4 0.0 0.0–1,050.0 231.6

Forebay elevation (feet, NGVD 29) Overall 1,661.4 1,662.4 1,652.1–1,670.0 5.1

Day 1,661.4 1,662.4 1,652.1–1,670.1 5.1

Night 1,661.4 1,662.3 1,652.1–1,670.0 5.1

Head over the weir gates (feet) Overall 4.4 4.9 1.1–10.2 2.0

Day 4.4 4.9 1.1–10.2 2.1

Night 4.4 4.9 1.1–9.2 2.0

Water temperature (degrees Celsius) Overall 13.0 12.8 8.2–18.1 1.8

Day 12.7 12.5 8.2–18.0 1.7

Night 13.4 13.3 8.2–18.1 1.9
14 

During the fall, dam discharge generally was greater than during the spring, and reservoir 

elevation and water temperature decreased throughout most of the period. Total project discharge 

peaked in November (2,590.0 ft3/s) and remained greater than 2,400 ft3/s until the end of the study 

period (fig. 6, table 2). The turbine(s) operated throughout the fall, except for 28 h during November 6– 

8, 2013 (fig. 7). Mean hourly turbine discharge was 750.7 ft3/s (range 0.0–1,345.0 ft3/s), and mean 

hourly regulating outlet discharge was 204.7 ft3/s (range 0.0–1,570.0 ft3/s) (table 2). Forebay elevation 

decreased from 1,607.5 to a low of 1,543.5 ft NGVD 29 in mid-November (table 2). The weir gates in 

the temperature control tower were out of the water after November 18, 2013, at 11:00 a.m. Water

temperature in the top 13–19 ft of the water column near the WTC tower decreased from 14.6 to 6.9 °C 

(table 2). Dam operations during day and night periods generally were similar.

Table 2. Mean hourly summary statistics of dam operations and environmental conditions at Cougar Reservoir and 

Dam, Oregon, fall 2013. 

[SD, standard deviation; ft3/s is cubic foot per second; NGVD 29, National Geodetic Vertical Datum of 1929] 

Dam operation Period Mean Median Range SD

Total project discharge (ft3s/) Overall 955.4 550.0 350.0–2,590.0 642.5

Day 912.7 550.0 360.0–2,530.0 607.8

Night 989.5 560.0 350.0–2,590.0 667.4

Powerhouse (ft3/s) Overall 750.7 550.0 0.0–1,345.0 360.4

Day 738.6 550.0 0.0–1,345.0 364.5

Night 760.4 550.0 0.0–1,270.0 357.2

Regulating outlet (ft3/s) Overall 204.7 0.0 0.0–1,570.0 458.0

Day 174.2 0.0 0.0–1,380.0 410.1

Night 229.1 0.0 0.0–1,570.0 491.9

Forebay elevation (feet, NGVD 29) Overall 1,586.5 1,585.1 1,543.5–1,607.5 16.2

Day 1,587.3 1,586.8 1,545.2–1,607.5 15.8

Night 1,586.0 1,583.7 1,543.5–1,607.5 16.4

Head over the weir arrays (feet) Overall 28.8 30.2 12.0–46.0 13.3

Day 29.0 31.2 12.0–46.0 13.2

Night 28.6 30.0 12.0–46.0 13.3

Water temperature (degrees Celsius) Overall 10.1 9.8 6.9–14.6 1.9

Day 10.2 9.9 6.9–14.6 1.9

Night 10.0 9.4 7.0–14.5 1.9
15 

Fish Movements

Spring

Fish Directions

Mean directions within each of the four fish-size categories indicated size-specific differences in 

fish directions near the WTC tower at Cougar Dam. In particular, the small fish (30–60 mm) had a mean 

direction that was opposite the direction of the larger fish (60–90 and 90–250 mm), and predators (>300 

mm; table 3). Rose plots and circular histograms of the mean directions support this conclusion (figs. 8 

and 9).

The directions of fish in the acoustic beams also were dependent on photoperiod and the location 

of the camera just upstream of the WTC tower (figs. 8 and 9). The mean direction of small fish (30–60 

mm) observed by the DIDSON acoustic camera was toward the east of the WTC tower (during day and 

night), but these fish moved toward the WTC tower when in the area covered by the ARIS acoustic 

camera during the day, and toward the northeast during the night. Movements of medium fish (60–90 

mm) near the DIDSON acoustic camera were to the west of the WTC tower during the day, and toward 

the WTC tower during the night. Medium fish also were moving toward the WTC tower near the ARIS 

acoustic camera regardless of photoperiod. The large fish (90–250 mm) were highly variable in their 

movements with mean direction of fish toward the west side of the WTC tower during the day 

(regardless of the acoustic camera location), whereas at night, fish observed by both acoustic cameras 

moved away from the WTC tower. Predator-sized fish (>300 mm) were most consistent in their 

movement directions with the mean direction of movement toward the west side of the WTC tower 

when in the area covered by the DIDSON acoustic camera, and toward the northwest when observed 

with the ARIS acoustic camera. Additional rose plots and circular histograms of fish travel directions by 

depth and photoperiod are shown in appendix B. 

Table 3. Mean directions (radians) and concentration parameters by fish-size category and acoustic-camera type 

(DIDSON® or ARIS®) at Cougar Reservoir and Dam, Oregon, spring 2013. 

[n, sample size; μ, mean direction of the fish, κ, concentration parameter; SE, standard error; mm, millimeter; >, greater than] 

Fish-size category (type) n μ (SE) κ (SE)

DIDSON

30–60 mm (small fish) 336 0.641 (0.161) 0.486 (0.081)

60–90 mm (medium fish) 712 -2.490 (0.161) 0.331 (0.054)

90–250 mm (large fish) 3,464 -2.390 (0.069) 0.351 (0.025)

>300 mm (predators) 1,095 -2.390 (0.067) 0.649 (0.046)

ARIS

30–60 mm (small fish) 507 -0.145 (0.157) 0.405 (0.065)

60–90 mm (medium fish) 570 -0.320 (0.136) 0.443 (0.061)

90–250 mm (large fish) 1,008 -2.183 (0.729) 0.061 (0.045)

>300 mm (predators) 50 -1.007 (0.469) 0.436 (0.207)
16 

Figure 8. Rose plots and circular histograms of mean directions (degrees) of 30–60 and 60–90 millimeter (mm) 

fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod (day, night, or combined) at 

Cougar Reservoir and Dam, Oregon, spring 2013. 
17 

Figure 9. Rose plots and circular histograms of mean directions (degrees) of 90–250 and >300 millimeter (mm) 

fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod (day, night, or combined) at 

Cougar Reservoir and Dam, Oregon, spring 2013. 
18 

Overall, our full model of the fish directions within the DIDSON acoustic beam provided little 

ability to predict fish directions near the WTC tower. As a consequence of having 4,512 observations, 

statistical (although not necessarily biological) significance was virtually ensured for all factors included 

in the full model (table 4, fig. 10). Based on the differences in AIC values for single-predictor candidate 

model subsets, diel period had the most influence (AIC=-211.83) on fish directions, followed by fish 

size (AIC=-198.39), and then discharge (AIC=-195.99) and temperature (AIC=-189.99). Although our 

modeling of fish directions provided little standing for predicting fish responses near the WTC tower, 

our findings support the premise that diel period, fish size, and dam operations help to determine fish

direction upstream of the WTC tower.

The full model of fish directions within the ARIS acoustic beam also had little predictive ability. 

Similar to our findings with fish directions with the DIDSON acoustic camera, we had a total of 2,085 

observations, and so we were able to determine statistical significance for all modeled effects on fish 

directions in the area covered by the ARIS acoustic camera (table 4, fig. 11). Based on the differences in 

AIC values for the single-predictor models, fish size had the most influence (AIC=-49.05) on fish 

directions, followed by temperature (AIC=-45.50), and then discharge (AIC=-42.09) and diel period 

(AIC=-41.99). This again suggests that environmental conditions and dam operations have a modest 

influence on fish directions upstream of the WTC tower at Cougar Reservoir.

Table 4. Results for circular-linear models of mean directions (radians) of fish in the acoustic beams of the 

DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, spring 2013. 

[AIC values denote estimates for each single-predictor model. The factor in brackets is factor level being measured against 

the reference category. SE, standard error; AIC, Akaike Information Criterion; μ, mean direction of the fish; κ, concentration 

parameter; n, ]sample size; NA, not applicable

Model effect Estimate SE t-value p-value AIC

DIDSON (log-likelihood = 145.40, n=4,512)

μ 1.202 0.058 NA NA NA

κ 0.365 0.022 NA NA NA

Diel period[LIGHT] 3.629 0.646 5.620 <0.0001 -211.83

Discharge 3.842 1.135 3.385 0.0004 -195.99

Temperature 0.174 0.051 3.413 0.0003 -189.99

Fish size 0.263 0.127 2.069 0.0193 -198.39

ARIS (log-likelihood = 37.02, n=2,085)

μ 3.773 0.116 NA NA NA

κ 0.269 0.031 NA NA NA

Diel period[LIGHT] 2.817 0.596 4.725 <0.0001 -41.99

Discharge 1.466 0.341 4.296 <0.0001 -42.09

Temperature 0.168 0.046 3.624 0.0001 -45.50

Fish size -1.008 0.285 3.543 0.0002 -49.05
19 

Figure 10. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the beam of 

the DIDSON® acoustic camera upstream of the water temperature control (WTC) tower at Cougar Reservoir and 

Dam, Oregon, spring 2013. 
20 

Figure 11. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the beam of 

the ARIS® acoustic camera upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, spring 2013. 
21 

Fish Depth

The mean hourly depth of fish during the spring differed among camera type and fish-size 

categories (fig. 12). In general, smaller fish targets were observed nearer to the surface than larger fish

targets. As fish size increased, the hourly mean depth of the fish also increased. During daylight, fish 

tended to remain closer to the surface than during night. Irrespective of daytime; however, the larger 

predator-sized fish (>300 mm) generally were about 1–2 m deeper than the smaller sized fish. 

For fish observed with the DIDSON acoustic camera, mean depth of fish increased with larger 

fish (table 5). An exception to this was the 90–250 mm size class, where mean depths were 8 mm 

shallower than the 60–90 mm size class, recognizing that this small difference was unlikely to be 

biologically significant. For fish observed with the ARIS acoustic camera, mean depth of fish increased 

with each successive fish-size class. Predators were at depths greater than the smaller fish, irrespective 

of the different acoustic cameras and locations. Additionally, for fish observed with both acoustic 

cameras, mean depth of fish during spring (3.4 m) increased with increasing camera angle (fig. 13). 

Figure 12. Graph showing hourly mean depth of fish (in meters [m]), by size category (in millimeters [mm]), in the 

area covered by DIDSON® and ARIS® acoustic cameras, which were upstream of the water temperature control

(WTC) tower at Cougar Reservoir and Dam, Oregon, spring 2013. 
22 

Table 5. Sample size, and mean, standard deviation, minimum, and maximum depths of each fish-size category 

observed with the DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower

at Cougar Reservoir and Dam, spring 2013.

[n, sample size; SD, standard deviation; mm, millimeter; >, greater than] 

Depth (meters)

Fish-size category (type) n Mean SD Minimum Maximum

DIDSON

30–60 mm (small fish) 408 3.05 0.96 2 6.87

60–90 mm (medium fish) 809 3.34 1.18 2 8.39

90–250 mm (large fish) 3,866 3.26 1.49 2 9.39

>300 mm (predators) 1,154 3.88 1.71 2 9.41

ARIS

30–60 mm (small fish) 518 2.37 0.68 2 6.17

60–90 mm (medium fish) 525 2.65 0.93 2 6.76

90–250 mm (large fish) 882 2.83 0.94 2 5.95

>300 mm (predators) 43 2.94 0.77 2 4.22

Figure 13. Box and whisker plots of the depth of fish (in meters [m]) observed under different camera angles using 

DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, spring 2013. The upper and lower 

boundaries of the box represent the 25th and 75th quartiles, the line inside the box is the mean, the whiskers 

represent the 5- and 95-percent confidence intervals, and outliers are shown by solid points.
23 

Fish Speed and Duration of Observation

Irrespective of fish size and the acoustic camera used to collect the data, fish traveled at similar 

speeds (table 6, fig. 14). For example, the mean travel speed of fish passing through the DIDSON 

acoustic beam was 0.101 m/s (interquartile range = 0.080 m/s), and the mean travel speed of fish 

passing through the ARIS acoustic beam was 0.062 m/s (interquartile range = 0.055 m/s). The duration 

of time that fish were observed in the acoustic beam also varied by camera type. Fish were observed in 

the DIDSON acoustic beam for a median of 2.630 s (mean 9.795 s; IQR = 3.510 s), but in the ARIS 

acoustic beam for a median of 3.498 s (mean = 17.634 s; IQR = 6.988 s). Thus, in comparison to the 

DIDSON acoustic camera, the distribution of travel times was more skewed toward longer travel times 

and slower swimming fish in the area covered by the ARIS acoustic camera. 

Table 6. Summary statistics for the travel speeds and duration of fish observed with the DIDSON® and ARIS®

acoustic cameras at the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, spring 

2013.

[n, sample size; SD, standard deviation; IQR, interquartile range]

Camera n Mean SD IQR Minimum 2.5

percent

50

percent

97.5

percent

Maximum

Travel speed (meter per second) 

DIDSON 4,512 0.101 0.063 0.080 0.001 0.014 0.088 0.250 0.456

ARIS 2,085 0.062 0.053 0.055 0.001 0.005 0.048 0.194 0.500

Time in acoustic beam (second)

DIDSON 4,512 9.795 49.330 3.510 0.500 0.660 2.630 53.340 900.000

ARIS 2,085 17.634 62.733 6.988 0.526 0.771 3.498 145.986 875.873
24 

Figure 14. Graphs showing distributions of fish travel speeds (in meters per second [m/s]) and the amount of time 

fish spent within the acoustic beams (in seconds [s]) of the DIDSON® and ARIS® acoustic cameras at Cougar 

Reservoir and Dam, Oregon, spring 2013. 

Application of linear models to estimate the travel speeds of fish in the acoustic beams indicated 

a poor ability to predict fish movements. All models had residuals that were evenly distributed over the 

predicted range, but they only explained less than 5 percent of the variation. Regardless of this poor 

model fit, however, modeling indicated camera- and location-specific differences in travel speeds near 

the WTC tower (table 7). In particular, modeling confirmed that travel speeds were faster in the area of 

the DIDSON acoustic camera, and that the response to discharge was more acute compared to travel 

speeds measured in the area of the ARIS acoustic camera. This finding was especially apparent for the 

larger fish (table 7, fig. 15). Based on the AIC values for the single-predictor models, the most 

important predictors of the travel speeds of fish in the area of the DIDSON acoustic camera in spring 

were, in descending importance, (1) fish size (AIC = -8,310, (2) discharge (AIC = -8,295, (3) diel period 

(AIC = -8,149), and (4) temperature (AIC = -8,127). In the area of the ARIS acoustic camera, the order 

of single-predictor importance to fish travel speed was ranked slightly different with (1) size (AIC = -

3,921, (2) diel period (AIC = -3,892), (3) discharge (AIC = -3,868), and (4) temperature (AIC = -3,859). 
25 

Table 7. Results for multiple regression models of mean travel speeds ( m s/ ) of fish while in the acoustic 

beams of the DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at 

Cougar Reservoir and Dam, Oregon, spring 2013. 

[SE, standard error; AIC, Akaike Information Criterion; R2, coefficient of determination; n, sample size; mm, millimeter; <, 

less than] 

Model effect Estimate SE t-value p-value Single-predictor AIC

DIDSON (R2 = 0.062, n=4,512, AIC=-8362)

Intercept 0.223 0.016 13.870 <0.0001 (intercept only) -8,149

Diel period (day) -0.0001 0.004 -0.025 0.9798 -8,149

Fish size (60–90 mm) 0.024 0.006 3.771 0.0002 -8,310

Fish size (90–250 mm) 0.053 0.006 9.575 <0.0001 -8,310

Discharge 0.018 0.002 10.191 <0.0001 -8,295

Temperature 0.003 0.001 2.588 0.0097 -8,127

ARIS (R2 = 0.044, n=2,085, AIC=-3952)

Intercept 0.168 0.028 6.086 <0.0001 (intercept only) -3,870

Diel period (day) -0.026 0.005 -4.961 <0.0001 -3,892

Fish size (60–90 mm) 0.011 0.006 1.836 0.0665 -3,921

Fish size (90–250 mm) 0.044 0.006 7.786 <0.0001 -3,921

Discharge -0.005 0.002 -2.300 0.0216 -3,868

Temperature 0.005 0.002 2.322 0.0203 -3,859
26 

Figure 15. Plots for multiple regression model estimates of mean travel speed of fish (in meters per second [m/s]), 

by size category (in millimeters [mm]), within the beams of the DIDSON® and ARIS® acoustic cameras upstream of 

the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, spring 2013. 

Quantifying Movement Toward the Water Temperature Control Tower

Use of Poisson rate regressions to quantify the numbers of fish moving toward the WTC tower 

given the total number of fish in the acoustic beam (per 3-s interval) provided some insight into how 

factors may influence fish movement toward the WTC tower. However, it should be cautioned that the 

global model has some structural problems. For example, the Q-Q plots were jagged and suggested 

departure from the theoretical quantiles at the upper tail of the distribution. Additionally, calculation of 

Nagelkerke’s (1991) coefficient of determination (R2

) indicated that less than 5 percent of the deviance 

was explained, regardless of the camera type used to collect the data, corroborating poor model 

predictive ability (table 8). The most important factor determining the number of fish moving toward the 

tower was the total number of fish in the acoustic beam per unit time (Nbeam,t; table 8, fig. 16). Using the 

log of Nbeam,t as the rate variable for the number of fish moving toward the tower yielded a slope = 

0.9866 (SE=0.0392) for the DIDSON acoustic camera, and a slope=1.054 (SE=0.0621) for the ARIS 
27 

acoustic camera, supporting the assumption of 1:1 relation between the total number of fish in the 

acoustic beam and those moving toward the WTC tower; therefore, we offset this parameter from the 

Poisson rate regression models (table 9). 

Perhaps the most significant finding from this analysis was the effect of predators on fish 

moving toward the WTC tower at the different locations. For example, in the area covered by the 

DIDSON acoustic camera, the number of predators was important to the model, but in the area covered 

by the ARIS acoustic camera, the number of predators had little influence on the numbers of fish 

moving toward the WTC tower (table 8). In the area covered by the DIDSON acoustic camera, there 

also was evidence for an interaction between predators and photoperiod, and predators and discharge, 

supporting the conclusion that predation risk, time of day, and discharge interact to influence the 

number of fish moving toward the WTC tower (fig. 17); however, the importance of predators and their 

effect on fish movements seems to be site-specific. 

Table 8. Results for Poisson rate regression models of fish moving toward the water temperature control (WTC) 

tower while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, 

Oregon, spring 2013. 

[SE, standard error; <, less than; R2, coefficient of determination; n, sample size] 

Model effect Estimate SE z-value p-value

DIDSON (Nagelkerke’s R2 = 0.011, n = 9,371)

Intercept -2.0021 0.2547 -7.859 0.000

log(Nbeam t) 0.9866 0.0392 25.160 <0.00001

Predators -0.2952 0.1572 -1.878 0.060

Discharge -0.0002 0.0001 -2.025 0.043

Temperature 0.0100 0.0154 0.652 0.514

Photoperiod[LIGHT] -0.1267 0.0471 -2.689 0.007

Photoperiod[LIGHT]*Predators 0.3362 0.1416 2.375 0.018

Discharge*Predators 0.0002 0.0001 1.929 0.054

ARIS (Nagelkerke’s R2 = 0.050, n = 8,140)

Intercept -3.232 0.3270 -9.883 <0.00001

log(Nbeam t) 1.054 0.0621 16.967 <0.00001

Predators 0.424 0.8916 0.476 0.634

Discharge -0.001 0.0001 -7.284 <0.00001

Temperature 0.092 0.0215 4.281 <0.00001

Photoperiod[LIGHT] 0.611 0.0621 9.831 <0.00001

Photoperiod[LIGHT]*Predators 0.435 0.8267 0.526 0.599

Discharge*Predators -0.001 0.0008 -1.487 0.137
28 

Table 9. Results for reduced Poisson rate regression models of fish moving toward the water temperature control 

(WTC) tower while in the acoustic beam of the DIDSON® and ARIS® cameras at Cougar Reservoir and Dam, 

Oregon, spring 2013. 

[The model effect in brackets is the factor level being measured against the reference category. SE, standard error; n, sample 

size; <, less than] 

Model effect Estimate SE z-value p-value

DIDSON (n=9,371) 

Intercept -1.8110 0.0589 -30.7390 <0.00001

Predators -0.2838 0.1496 -1.8980 0.058

Discharge -0.0003 0.0001 -3.9900 0.0001

Photoperiod[LIGHT] -0.1412 0.0452 -3.1220 0.002

Photoperiod[LIGHT]*Predators 0.3150 0.1322 2.3820 0.017

Discharge*Predators 0.0002 0.0001 2.1290 0.033

ARIS (n=8,140) 

Intercept -3.2410 0.3260 -9.936 <0.00001

Discharge -0.0007 0.0001 -7.433 <0.00001

Temperature 0.0957 0.0214 4.482 <0.00001

Photoperiod[LIGHT] 0.6190 0.0617 10.039 <0.00001

Figure 16. Scatter plots showing number (n) of fish moving toward the water temperature control (WTC) tower (per 

3-second interval) and total number of fish observed in the acoustic beam (per 3-second interval) of the DIDSON®

and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, spring 2013. Solid fitted lines represent the 

average trend using a loess smoothing function, dotted lines represent average trend using a linear model, and the 

dashed lines represent 1:1 lines of equality.
29 

Figure 17. Effects plots for the reduced Poisson rate regression modeling the numbers of fish traveling toward the 

water temperature control (WTC) tower while in the beam of the DIDSON® acoustic camera at Cougar Reservoir 

and Dam, Oregon, spring 2013.
30 

Figure 18. Effects plots for the reduced Poisson rate regression model of numbers of fish traveling toward the 

water temperature control (WTC) tower while in the beam of the ARIS® acoustic camera at Cougar Reservoir and 

Dam, Oregon, spring 2013.

Timing of Detection

The timing of fish observations over the 24-h diel cycle may be considered an indicator of 

animal movement. The percentage of juvenile fish detections peaked at about 6:00 a.m., and then 

generally declined throughout the day until about 5:00 p.m., when fish detections began to increase 

again (fig. 19). These two periods of greater fish detection coincided with the crepuscular period during 

the spring. Percentage of detections of predator size fish (>300 mm) was similar to percentage of 

detections of the smaller fish, except that the peak number of observations occurred later in the day (at 

about 11:00 a.m.). The timing of detection for fish that were traveling directly toward the WTC tower 

peaked about 1 h earlier (between 5:00and 10:00 a.m.; fig. 20) than detections for all fish, but trends for 

both groups were otherwise similar. Detections of fish of all size categories, and regardless of the 

direction of movement, were low during the night. 
31 

Figure 19. Graph showing hour of detection of fish, by size category (in millimeters [mm]), using the DIDSON® and 

ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, spring 2013. 

Figure 20. Graph showing hour of detection of fish, by size category (in millimeters [mm]), that were observed 

traveling toward the water temperature control (WTC) tower using the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, Oregon, spring 2013. 
32 

Fall

Fish Directions

Mean directions of fish in the acoustic beams indicated size- or species-specific differences 

depending on the location and the type of acoustic camera (table 10). Using the DIDSON acoustic 

camera, the two smallest size categories of fish (30–60 and 60–90 mm) had mean directions of 

movement that were opposite the mean directions of the large fish (90–250 mm) and predators (>300 

mm). Movements were similar for the 30–60 mm and predator categories using the ARIS acoustic 

camera, and were more similar for the medium and large fish (figs. 21 and 22).

The directions of fish in the acoustic beams also were dependent on photoperiod (figs. 21 and 

22). The mean direction of small fish (30–60 mm) in the DIDSON acoustic beam was toward the WTC 

tower during the day, but to the northeast of the WTC tower during the night. Alternatively, in the area 

covered by the ARIS acoustic camera, fish tended to be directed to the east of the WTC tower during the 

day, but away from the WTC tower during the night. Medium fish (60–90 mm) within the DIDSON

acoustic beam were directed toward the WTC tower during the day, and to the west of the tower during 

the night. Fish were directed to the east of the WTC tower when in the beam of the ARIS acoustic 

camera both day and night. The mean directions of the large fish-size category (90–250 mm) seemed

unrelated to the photoperiod, with fish movement directed away from the WTC tower when in the 

DIDSON acoustic beam, and to the east of the WTC tower when in the ARIS acoustic beam. The 

movement of predator-sized fish (>300 mm) was directed away from the WTC tower during day and 

night when within the DIDSON acoustic beam, and when in the ARIS acoustic beam, the predators

moved away from the tower during the day but to the east of the tower during the night. Additional 

rose plots and circular histograms of fish travel directions by depth and photoperiod are shown in 

appendix B. 

Table 10. Mean directions (radians) and concentration parameters by fish-size category and acoustic-camera type 

(DIDSON® or ARIS®) at Cougar Reservoir and Dam, Oregon, fall 2013. 

[n, sample size; μ, mean direction of the fish, κ, concentration parameter; SE, standard error; mm, millimeter; >, greater than] 

Fish-size category (type) n μ (SE) κ (SE)

DIDSON

30–60 mm (small fish) 44 -0.294 (0.794) 0.273 (0.216)

60–90 mm (medium fish) 128 -0.350 (0.710) 0.177 (0.126)

90–250 mm (large fish) 1,760 -3.429 (0.179) 0.189 (0.034)

>300 mm (predators) 514 -2.891 (0.216) 0.290 (0.063)

ARIS

30–60 mm (small fish) 86 -3.978 (0.373) 0.415 (0.157)

60–90 mm (medium fish) 180 1.483 (0.199) 0.541 (0.111)

90–250 mm (large fish) 582 0.856 (0.133) 0.447 (0.061)

>300 mm (predators) 106 -4.072 (1.502) 0.092 (0.138)
33 

Figure 21. Rose plots and circular histograms of mean directions (degrees) of 30–60 and 60–90 millimeter (mm) 

fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod (day, night, or combined)

upstream of the water temperature control (WTC) tower at Cougar Dam, Oregon, fall 2013. 
34 

Figure 22. Rose plots and circular histograms of mean directions (degrees) of 90-250 and >300 millimeter (mm) 

fish-size categories by acoustic-camera type (DIDSON® or ARIS®) and photoperiod (day, night, or combined)

upstream of the water temperature control (WTC) tower at Cougar Dam, Oregon, fall 2013. 
35 

Models of fish directions in the acoustic beam of the DIDSON acoustic camera had little 

predictive ability. However, with 1,932 observations, we were able to determine which variables 

provided statistical (although not biological) significance to the model (table 11, fig. 23). Based on the 

differences in AIC values for the single-predictor models, discharge had the most influence (AIC=-

45.42) on fish directions, followed by diel period (AIC=-26.04), temperature (AIC=-24.94), and fish 

size (AIC=-22.22). These findings support the premise that fish movement upstream of the WTC tower 

was influenced by the diel period and the size of the fish, and that additional variation in fish directions 

may arise from differences in dam operations and water temperatures.

There were 848 observations of fish direction in the area covered by the ARIS acoustic camera, 

so statistical significance should be easily obtained. Nevertheless, diel period was the only nonsignificant (p = 0.0604) contributor to the model (table 11, fig. 24). Based on the differences in AIC 

values for single-predictor models, fish size had the most influence (AIC=-83.75) on fish directions, but 

diel period (AIC=-71.54), temperature (AIC=-71.41), and discharge (AIC=-69.49) were equivocal. 

Table 11. Results for circular-linear models of mean directions (radians) of fish in the acoustic beams of the 

DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar 

Reservoir and Dam, Oregon, fall 2013. 

[AIC values denote estimates for each single-predictor model. SE, standard error; AIC, Akaike Information Criterion μ, 

mean direction of the fish, κ, concentration parameter; n, sample size] 

Model effect Estimate SE t-value p-value AIC

DIDSON (n=1,932)

μ 1.474 0.106 -- --

κ 0.307 0.033 -- --

Diel period 0.594 0.183 3.244 0.0006 -26.04

Discharge 0.399 0.121 3.298 0.0005 -45.42

Temperature -0.645 0.106 6.057 <0.0001 -24.94

Fish size 2.004 0.315 6.367 <0.0001 -22.22

ARIS (n=848)

μ 0.822 0.101

κ 0.490 0.051

Diel period 0.175 0.113 1.552 0.0604 -71.54

Discharge 0.127 0.060 2.138 0.0136 -69.49

Temperature 0.126 0.027 4.679 <0.0001 -71.41

Fish size -0.447 0.095 4.714 <0.0001 -83.75
36 

Figure 23. Effects plots for the full circular-linear model of mean directions of fish (in degrees) within the beam of 

the DIDSON® acoustic camera upstream of the water temperature control (WTC) tower at Cougar Reservoir and 

Dam, Oregon, fall 2013 
37 

Figure 24. Effects plots for the full circular-linear model of mean directions fish (in degrees) within the beam of the 

ARIS® acoustic camera upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, fall 2013. 
38 

Fish Depth

The mean hourly depth of fish in the area covered by the DIDSON and ARIS acoustic cameras

was more variable among the size groups during the fall (fig. 25) than during the spring (fig. 12). Small 

fish (30–60 mm) had the greatest amount of variability among hourly mean depths, and there was no 

clear response to changes in photoperiod. The 60–90 mm fish-size category generally was observed 

nearer to the surface during both photoperiods than the other fish-size categories. Fish in the 90–250 

mm size category showed little change in mean depth with time of day. Fish in the predator size 

category (>300 mm) generally were observed at greater depths than the smaller fish throughout the day, 

with the greatest mean depth occurring during the night. 

Figure 25. Graph showing hourly mean depth of fish (in meters [m]), by size category (in millimeters [mm]), in the 

area covered by DIDSON® and ARIS® acoustic cameras, which were upstream of the water temperature control

(WTC) tower at Cougar Reservoir and Dam, Oregon, fall 2013. 
39 

The mean depths by fish-size category during the fall varied by location and acoustic-camera 

type (table 12). For the fish observed in the area covered by the DIDSON acoustic camera, the mean 

depths increased with the size category of the fish. The predator size fish (>300 mm) that were 

observed with the DIDSON acoustic camera were observed at mean depths of about 1 m deeper than the 

smaller size categories. Conversely, the mean depth of fish in the area covered by the ARIS acoustic 

camera generally decreased with increasing fish-size category. Fish were shallowest in the area covered 

by the ARIS acoustic camera. Differences in observations between camera types may be attributed to 

the location of the camera and the limited range of the ARIS acoustic camera. Predators also tended to 

occupy the region nearer the center of the WTC tower, thus remaining out of the range of the ARIS 

acoustic camera. Additionally, the mean depth of fish observed with both acoustic cameras during the 

fall season (3.0 m) increased as the camera angle increased from horizontal, but were similar between 

25 and 50 degrees (fig. 26).

Table 12. Sample size, and mean, standard deviation, minimum, and maximum depths of each fish-size category

observed with the DIDSON® and ARIS® acoustic cameras upstream of the water temperature control (WTC) tower

at Cougar Reservoir, Oregon, fall 2013.

[n, sample size; SD, standard deviation; mm, millimeter; >, greater than] 

Depth (meters)

Fish-size class (type) n Mean SD Minimum Maximum

DIDSON

30–60 mm (small fish) 58 2.56 1.08 2 5.92

60–90 mm (medium fish) 165 2.82 1.35 2 6.11

90–250 mm (large fish) 1,961 2.86 1.34 2 8.75

>300 mm (predators) 531 3.73 1.52 2 6.39

ARIS

30–60 mm (small fish) 126 2.80 1.09 2 6.27

60–90 mm (medium fish) 206 2.85 1.12 2 5.97

90–250 mm (large fish) 650 2.53 0.91 2 6.26

>300 mm (predators) 109 2.32 0.52 2 4.46
40 

Figure 26. Box and whisker plots of the depth of fish (in meters [m]) observed under different camera angles using 

DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013. The upper and lower 

boundaries of the box represent the 25th and 75th quartiles, the line inside the box is the mean, the whiskers 

represent the 5- and 95-percent confidence intervals, and outliers are shown by solid points.

Fish Speed and Duration of Observation

Juvenile salmon-sized fish traveled at speeds that generally were less than 1 m/s in the areas 

covered by both the DIDSON and ARIS acoustic cameras (table 13, fig. 27). The mean swim speed of 

fish in the DIDSON acoustic beam was 0.078 m/s (interquartile range = 0.063 m/s), and the mean travel

speed of fish in the ARIS acoustic beam was 0.098 m/s (interquartile range = 0.082 m/s). The duration 

of time that fish were observed in the acoustic beams also was similarly short in the areas covered by 

the two acoustic cameras. Fish in the area covered by the DIDSON acoustic camera spent, on average, 

8.783 s (interquartile range = 3.960 s) in the acoustic beam, whereas fish in the area covered by the 

ARIS acoustic camera spent 7.865 s (interquartile range = 5.890 s) in the acoustic beam. 
41 

Table 13. Summary statistics for the travel speeds and duration that fish were observed by the DIDSON and ARIS 

acoustic cameras at the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, fall 2013. 

[n, sample size; SD, standard deviation; IQR, interquartile range] 

Camera n Mean SD IQR Minimum 2.5 

percent 

50 

percent 

97.5 

percent 

Maximum 

Travel speed (meter per second) 

DIDSON 1,932 0.078 0.067 0.063 0.001 0.013 0.069 0.190 0.327 

ARIS 848 0.098 0.070 0.082 0.001 0.015 0.082 0.277 0.453 

Time in acoustic beam (second) 

DIDSON 1,932 8.783 35.153 3.960 0.770 0.990 3.240 44.372 832.780 

ARIS 848 7.865 18.731 5.890 0.532 0.770 3.344 33.568 284.312 

Figure 27. Graphs showing distributions of fish travel speeds (in meters per second [m/s]) and the amount of time 

fish spent within the acoustic beams of the DIDSON® and ARIS® acoustic cameras at Cougar Reservoir and Dam, 

fall 2013. 

 
42 

Application of linear models to estimate the travel speeds of fish indicated a limited ability to 

predict the travel speeds of fish. All models had residuals that were evenly distributed over the predicted 

range, but they only explained less than 5 percent of the variation. Regardless of this poor model fit, 

however, modeling indicated camera- and location-specific differences in travel speeds near the WTC 

tower (table 14). In particular, modeling confirmed that travel speeds were faster in the area of the ARIS 

acoustic camera, and that the response to both temperature and discharge was more acute compared to 

travel speeds measured in the area of the DIDSON acoustic camera. This finding was especially 

apparent for the larger fish (table 14, fig. 28). Based on the AIC values for the single-predictor models, 

the order of importance for the predictors of travel speeds of fish in the area of the DIDSON acoustic 

camera in the fall was identical to the order of importance in the spring. These predictors, in descending 

order of importance, were (1) fish size (AIC = -4,148), (2) discharge (AIC = -4,120), (3) diel period 

(AIC = -4,110) and then (4) temperature (AIC = -4,107). In the area of the ARIS acoustic camera, the 

order of single-predictor importance to fish travel speed was ranked slightly different with (1) diel 

period (AIC = -1,476), (2) discharge (AIC = -1,455), (3) fish size (AIC = -1,439) and (4) temperature 

(AIC = -1,406). 

Table 14. Results for multiple regression models of mean travel speeds (square root of meter per

second [ m s/ ]) of fish while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras upstream of 

the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, fall 2013. 

[SE, standard error; AIC, Akaike Information Criterion; R2, coefficient of determination; n, sample size; mm, millimeter; <, 

less than]

Model effect Estimate SE t-value p-value Single-predictor AIC

DIDSON (R2 = 0.046, n=1,932, AIC=-4,187) 

Intercept 0.354 0.033 10.617 <0.0001 (intercept only) -4,106

Diel period (day) -0.012 0.004 -3.073 0.0022 -4,110

Fish size (60–90 mm) 0.033 0.014 2.303 0.0214 -4,148

Fish size (90–250 mm) 0.065 0.013 5.244 <0.0001 -4,148

Discharge -0.012 0.002 -5.867 <0.0001 -4,120

Temperature -0.017 0.004 -4.672 <0.0001 -4,107

ARIS (R2 = 0.164, n=848, AIC=-1,547) 

Intercept 0.134 0.027 4.891 <0.0001 (intercept only) -1,404

Diel period (day) 0.051 0.007 7.507 <0.0001 -1,476

Fish size (60–90 mm) 0.013 0.013 0.998 0.319 -1,439

Fish size (90–250 mm) 0.045 0.011 3.936 <0.0001 -1,439

Discharge 0.028 0.004 7.342 <0.0001 -1,455

Temperature 0.010 0.003 3.916 <0.0001 -1,406
43 

Figure 28. Plots for the multiple regression model estimates of mean travel speed of fish (in meters per second 

[m/s]), by size category (in millimeters [mm]), within the beams of the DIDSON® and ARIS® acoustic cameras 

upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, Oregon, fall 2013. 
44 

Quantifying Movement Toward Water Temperature Control Tower 

Fall results differed slightly from spring results when we used Poisson rate regressions to 

quantify the numbers of fish moving toward the WTC tower given the total number of fish in the 

acoustic beam (per 3-s interval). However, it should be cautioned that the global model had structural 

problems similar to those found in the analysis of the spring data. The Q-Q plots were jagged and 

suggested departure from the theoretical quantiles at the upper tail of the distribution. Additionally, 

calculation of Nagelkerke’s (1991) coefficient of determination (R2

) indicated that less than 5 percent of 

the deviance was explained (after accounting for the rate variable) regardless of the camera, indicating 

poor model predictive ability (table 15). The rate variables used in the models were the most significant 

determinant of the numbers of fish moving toward the tower, so we assume that this rate was equal to 1 

and was offset from the model. No indication of overdispersion was discovered in the global models, 

irrespective of whether the data were obtained from the DIDSON (φ=0.97) or the ARIS (φ=1.03) 

acoustic cameras (fig. 29). 

Table 15. Results for reduced Poisson rate regression models of fish traveling toward the water temperature 

control (WTC) tower while in the acoustic beams of the DIDSON® and ARIS® acoustic cameras at Cougar 

Reservoir and Dam, Oregon, fall 2013.

[The model effect in brackets is the factor level being measured against the reference category. SE, standard error; <, less 

than; R2

, coefficient of determination; n, sample size]

Model effect Estimate SE z-value p-value

DIDSON (Nagelkerke’s R2 = 0.022, n=4,668)

Intercept -2.1700 0.4962 -4.3730 <0.0001

Log(Nbeam t) 1.3880 0.0551 25.2040 <0.0001

Photoperiod[LIGHT] -0.1117 0.0618 -1.8060 0.0709

Predator count 0.2124 0.1075 1.9760 0.0482

Discharge 0.0002 0.0000 5.0680 <0.0001

Temperature -0.0550 0.0548 -1.0020 0.3164

Photoperiod[LIGHT]:Predator count 0.1288 0.0739 1.7430 0.0813

DISCHARGE: Predator count -0.0002 0.0001 -2.4820 0.0130

ARIS (Nagelkerke’s R2 = 0.018, n=1,995)

Intercept -2.1610 0.4968 -4.3500 <0.0001

Log(Nbeam t) 1.2900 0.1149 11.2260 <0.0001

Photoperiod[LIGHT] -0.4274 0.1097 -3.8950 0.0001

Predator count 1.5660 0.8246 1.9000 0.0575

Discharge 0.0000 0.0001 0.5020 0.6155

Temperature -0.0327 0.0434 -0.7520 0.4519

Photoperiod[LIGHT]:Predator count 1.5920 0.6844 2.3260 0.0200

DISCHARGE: Predator count -0.0017 0.0010 -1.7300 0.0837
45 

Figure 29. Scatter plots showing number (n) of fish moving toward the water temperature control (WTC) tower (per 

3-second interval) and total number of fish observed in the acoustic beam (per 3-second interval) of the DIDSON®

and ARIS® acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013. Solid lines represent the average 

trend using a loess smoothing function, dotted lines represent average trend using a linear model, and dashed lines 

represent 1:1 line of equality.

Perhaps, the most significant finding from this analysis was the effect of predators on fish 

moving toward the WTC tower at the different locations and cameras. For example, in the area covered 

by the DIDSON acoustic camera, the number of predators was important to the model, but in the area 

covered by the ARIS acoustic camera, the number of predators had little influence on the numbers of 

fish moving toward the WTC tower. In the area covered by the DIDSON acoustic camera, there also 

was evidence for an interaction between predators and discharge (fig. 30), supporting the conclusion 

that predation risk, time of day, discharge, and location upstream of the WTC tower can interact with 

and influence the number of fish moving toward the WTC tower. In the area covered by the ARIS 

acoustic camera, stepwise removal of the non-significant predictors supported the conclusion that 

photoperiod was the only significant contributor to the numbers of fish moving toward the WTC tower 

(table 16, fig. 31).
46 

Table 16. Results for reduced Poisson rate regression models with removal of nonsignificant predictors of fish 

traveling toward the water temperature control (WTC) tower while in the acoustic beams of the DIDSON® and ARIS 

acoustic cameras at Cougar Reservoir and Dam, Oregon, fall 2013. 

[The model effect in brackets is the factor level being measured against the reference category. SE, standard error; n, sample 

size] 

Model effect Estimate SE z-value p-value

DIDSON (n=4,668)

Intercept -2.4190 0.0693 -34.9080 <0.0001

Predator count 0.3788 0.0886 4.2730 <0.0001

Discharge 0.0003 0.0000 6.4110 <0.0001

DISCHARGE: Predator count -0.0002 0.0001 -2.5140 0.0120

ARIS (n=1,995)

Intercept -2.20649 0.07474 -29.521 <0.0001

Photoperiod[LIGHT] -0.38051 0.10726 -3.548 0.0004

Figure 30. Effects plots for the reduced Poisson rate regression modeling the numbers of fish traveling toward the 

water temperature control (WTC) tower while in the beam of the DIDSON® acoustic camera at Cougar Reservoir 

and Dam, Oregon, fall 2013.
47 

Figure 31. Effects plots for the reduced Poisson rate regression model of the numbers of fish traveling toward the 

water temperature control (WTC) tower while in the beam of the ARIS® acoustic camera at Cougar Reservoir and 

Dam, Oregon, fall 2013.

Timing of Detection

The timing of fish present in the acoustic beams varied among fish sizes and time of day (fig. 

32). As observed during the spring, data from the fall also showed an increase in the detections of fish 

from all size groups during the crepuscular periods. Additionally, there was an increase in the number of 

all fish sizes near midday that was not observed during the spring. Compared to spring, the percentage 

of detections of predator-sized fish (>300 mm) in fall more closely followed peak detections of the 

smaller fish, with peak observations occurring at about 8:00 a.m. and 3:00 p.m. Detections of fish that 

were traveling directly toward the WTC tower peaked between 10:00 a.m. and 3:00 p.m. (fig. 33). As 

was the case in the spring, detections of all fish-size classes in the fall generally were low during the 

night. 
48 

Figure 32. Graph showing hour of detection of fish, by size category (in millimeters [mm]), using the DIDSON® and 

ARIS® acoustic cameras upstream of the water temperature control (WTC) tower at Cougar Reservoir and Dam, 

Oregon, fall 2013.

Figure 33. Graph showing hour of detection of fish, by size category (in millimeters [mm]), that were observed 

moving toward the water temperature control (WTC) tower using the DIDSON® and ARIS® acoustic cameras at 

Cougar Reservoir and Dam, Oregon, fall 2013. 
49 

Fish Track Density

The spatial distribution of fish tracks near the WTC tower varied by fish size, but was similar 

between season and photoperiod (appendix C). The fish densities in the view of the DIDSON and ARIS 

acoustic cameras during the spring are represented by 9,026 individual tracks. The spatial densities of 

fish that were less than 90 mm in length were more concentrated upstream of the WTC tower during 

spring and fall. Alternatively, spatial densities of the 90–250 mm fish were more uniformly distributed 

across the face of the WTC tower. The spatial densities of predators (>300 mm) were more concentrated 

toward the center of the WTC tower compared to the other fish-size classes. During the fall, predator 

locations were more uniformly distributed across the view of both the DIDSON and ARIS acoustic 

cameras.

Discussion

Although there was a previous study (Kahn and others,. 2012) that used acoustic cameras to 

evaluate fish behavior at Cougar Dam, the study we conducted in 2013 was unique in numerous ways. 

Our study was one of the first to implement the latest technology in acoustic cameras (ARIS) to monitor 

the movement of relatively small fish (30–60 mm). This study also was the only one we are aware of 

that attempted to use existing software (Echoview) to automate processing and tracking of the data 

collected on fish smaller than 250 mm in fork length. Automation enables more of the data to be 

processed in a timely manner so a larger proportion of the data can be used in the analysis. Finally, 

acoustic camera data historically have provided mostly qualitative data that summarize trends in fish 

movement. In this study we implemented a number of analytical methods designed to provide a 

quantitative assessment of fish movement and how it is influenced by environmental factors such as 

photoperiod, discharge, water temperature, and proximity to predators. Although there were some 

challenges, our study was largely successful. 

Not surprisingly, we determined that discharge at the dam had an important influence on the 

direction, travel speed, and numbers of fish moving toward the WTC tower. Discharge seemed to effect

a complete reversal in the directional movement of juvenile salmon in the spring, such that at both high 

and low discharges fish were directed similarly, but at the more common mid-range discharges (400–

1,000 ft3

/s), the mean directions of the juvenile salmon were undergoing change. Interestingly, a similar 

linkage between fish direction and discharge was not observed during the fall study, suggesting that 

migratory disposition (that is, level of smoltification) of the fish may affect the influence of discharge 

on fish movement. We also noted an increase in mean travel speed as discharge at the dam increased. 

However, there also was an increase in travel speeds with an increase in temperature. Given that higher 

temperatures increase the rate of smoltification and migratory status (Marine and Cech, 2004), these 

findings support the hypothesis that higher water temperatures may lead to faster travel speeds upstream 

of the WTC tower. Of the responses evaluated in this report, the modeling results for travel speeds were 

the most consistent between the spring and fall studies. In contrast, our modeling of fish directions and 

the numbers of fish moving toward the WTC tower were much more varied in their conclusions. A lack 

of uniform direction upstream of the WTC tower is supported by the results from fish tagged with 

acoustic transmitters that also showed extensive milling behavior in this area (Beeman and others, 

2014). 
50 

Interactions between behavioral and physical processes can alter the diel activity patterns of fish, 

and, in turn, their movement toward the WTC tower. Others have evaluated the diel activities of 

juvenile Chinook salmon at dams. Beeman and Maule (2006) showed that juvenile Chinook salmon in 

the Columbia River occupied shallower water during the night when the risk of predation was 

presumably lower than during daytime. Predation likely is lower during the night because prey fish, 

such as juvenile salmon, are not readily noticed by aerial and piscivorous predators when near the 

surface (Olla and Davis, 1990; Sundström and others, 2003). Thus, factors such as predation risk can 

greatly alter the diel activity patterns of juvenile Chinook salmon, and we show that movement toward 

the WTC tower was influenced by time of day and the number of predators in the acoustic beam. By 

applying a Poisson rate regression to the counts of fish per unit time that moved toward the WTC tower, 

given the number of fish in the acoustic beam, we were able to verify that the numbers of fish moving 

toward the WTC tower were influenced by the number of predators, the time of day, and the discharge 

at the dam. Interestingly, the influence of the number of predators on the numbers of fish moving 

toward the WTC tower differed between spring and fall, suggesting that migratory status of the juvenile 

salmon and predation risk may interact to affect fish movement toward the WTC tower. It should be 

noted, however, that our Poisson rate regressions had some structural problems, which we think mostly 

were owing to an “unaccounted-for” or perhaps an “improperly specified” effect in the model. 

Nonetheless, the exploratory nature of the analysis during the first year of this study will help inform the 

analyses for the 2014 study at Cougar Dam when the USACE plans to test the passage effectiveness of a 

Portable Floating Fish Collector.

Acoustic camera data can yield previously unattainable information on fish behavior, but this 

technology is limited in the ability to definitively determine the species of fish that is in the acoustic 

beam. In the case of Cougar Reservoir, it is reasonable to assume that most fish that were less than 300 

mm long were juvenile salmon, and that those fish greater than 300 mm long likely were either bull 

trout or rainbow trout (Oncorhynchus mykiss). However, dace (Rhinichthys sp.) were observed in the 

near-dam area, so it is possible that our smallest size class (30–60 mm) may not exclusively represent 

juvenile salmon. Given that this uncertainty may exist, fish size was considered an important factor in 

determining fish direction and travel speeds upstream of the WTC tower. On average, we noted that the 

larger the size of the fish, the faster the travel speed. Larger fish (in this case, what we believe were 

predators) not only tended to move faster, but generally were deeper in the water column and their 

direction of movement tended to be offset to the direction of the smaller fish. 

Although there were many challenges when collecting, processing, and analyzing the relatively 

larger volume of data (20 terabytes) that can be obtained using acoustic-camera technology, that 

technology was an informative tool for evaluating fish movements. Nonetheless, there was a relatively 

large degree of unpredictability when modeling fish movements at such fine space and time scales. For 

example, differences in observations may be attributed to camera type and location, sampling angle, and 

range of the acoustic beam. The area ensonified by the beam was fairly limited relative to the overall 

size of the near-dam area, and varied among the different cameras with the ARIS acoustic camera being 

the most limited. For example, predators are believed to occupy the region near the center of the WTC 

tower, yet they might be underrepresented in the sample because of the limited range of the acoustic 

beam resulting in undersampling the area in the center of the tower, and especially so with the ARIS 

acoustic camera. Similarly, statements about changes in fish depth across changing environmental 

conditions were difficult to make because the camera angle was changed on a random basis to 

investigate potential differences in the size of fish that occurred at various depths in the water column. 
51 

As a result of the changing angle and the relatively limited range of the acoustic beam, the area sampled 

at each depth was very limited, and making inferences about how environmental variables influence the 

presence or absence of fish at a particular depth was not feasible; therefore, we did not formally model 

fish depth as a response in this analysis. Despite such limitations, there was clear support for biological 

and environmental effects on fish directions and travel speeds within the acoustic beams upstream of the 

WTC tower. Two of the main objectives of the 2013 study were to determine if this technology could be 

used to aid in the evaluation of fish passage alternatives in the future and to establish the data processing 

and analytical procedures in advance to facilitate the timely analysis and reporting of the results. The 

results of the 2013 study meet these objectives and, as a result this technology, the 2013 study is well 

suited for evaluating the efficacy of fish passage alternatives such as the Portable Floating Fish 

Collector.

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53 

Appendix A. Sample Dates Selected for Analysis of DIDSON and ARIS Acoustic 

Camera Data Collected at the Cougar Reservoir Water Temperature Control 

(WTC) Tower, Oregon, 2013

 [ft3/s, cubic foot per second; NGVD 29, National Geodetic Vertical Datum of 1929] 

Date Season Acoustic cameras 

Project

discharge 

(ft3/s) 

Forebay 

elevation

(feet above 

NGVD 29)

Temperature

(degrees 

Celsius) 

05-03-2013 Spring DIDSON, ARIS 952.9 1,662.7 9.9

05-05-2013 Spring DIDSON, ARIS 957.1 1,662.7 11.2

05-07-2013 Spring DIDSON, ARIS 955.8 1,662.9 12.0

05-09-2013 Spring DIDSON 952.1 1,663.0 12.9

05-11-2013 Spring DIDSON, ARIS 951.7 1,663.1 12.9

05-13-2013 Spring DIDSON, ARIS 1,003.2 1,662.9 12.4

05-15-2013 Spring DIDSON, ARIS 979.6 1,662.1 12.0

05-17-2013 Spring DIDSON, ARIS 1,047.5 1,660.9 12.5

05-19-2013 Spring DIDSON, ARIS 957.9 1,659.7 11.9

05-21-2013 Spring DIDSON, ARIS 945.4 1,658.5 12.4

05-23-2013 Spring DIDSON, ARIS 931.7 1,657.6 11.5

05-25-2013 Spring DIDSON, ARIS 459.6 1,658.2 11.9

05-27-2013 Spring DIDSON, ARIS 455.8 1,659.6 11.7

05-29-2013 Spring DIDSON, ARIS 446.7 1,662.7 12.1

05-31-2013 Spring DIDSON, ARIS 450.4 1,665.9 11.3

06-02-2013 Spring DIDSON, ARIS 451.2 1,667.8 11.1

06-04-2013 Spring DIDSON, ARIS 442.9 1,668.9 12.1

06-06-2013 Spring DIDSON, ARIS 442.5 1,669.5 13.8

06-08-2013 Spring DIDSON, ARIS 449.6 1,669.9 14.4

06-10-2013 Spring DIDSON, ARIS 928.2 1,670.0 14.5

06-12-2013 Spring DIDSON, ARIS 928.8 1,668.9 12.4

06-14-2013 Spring DIDSON, ARIS 937.1 1,667.3 12.2

06-16-2013 Spring DIDSON, ARIS 942.9 1,665.5 12.6

06-18-2013 Spring DIDSON, ARIS 903.8 1,663.7 14.1

06-20-2013 Spring DIDSON, ARIS 924.6 1,661.8 12.6

06-22-2013 Spring DIDSON, ARIS 927.2 1,659.7 12.9

06-24-2013 Spring DIDSON, ARIS 939.2 1,657.6 13.2

06-26-2013 Spring DIDSON, ARIS 740.4 1,656.0 11.7

06-28-2013 Spring DIDSON, ARIS 415.0 1,655.7 12.7

06-30-2013 Spring DIDSON 414.8 1,655.4 13.7
54 

Date Season Acoustic cameras 

Project

discharge 

(ft3/s) 

Forebay 

elevation

(feet above 

NGVD 29)

Temperature

(degrees 

Celsius) 

07-02-2013 Spring DIDSON, ARIS 412.1 1,655.0 14.1

07-04-2013 Spring DIDSON, ARIS 418.0 1,654.5 14.7

07-06-2013 Spring DIDSON 419.6 1,653.9 16.0

07-08-2013 Spring DIDSON 418.5 1,653.3 16.5

09-27-2013 Fall ARIS 529.6 1,599.4 14.1

09-29-2013 Fall ARIS 540.4 1,600.0 13.5

10-01-2013 Fall ARIS 540.8 1,605.5 12.7

10-03-2013 Fall ARIS 547.1 1,607.3 12.0

10-05-2013 Fall ARIS 544.6 1,607.5 12.1

10-07-2013 Fall ARIS 545.4 1,607.1 12.1

10-09-2013 Fall ARIS 810.8 1,606.6 11.2

10-11-2013 Fall ARIS 1,094.2 1,603.8 11.4

10-13-2013 Fall ARIS 1,102.1 1,600.6 8.1

10-15-2013 Fall ARIS 1,155.0 1,597.0 10.7

10-23-2013 Fall ARIS 980.0 1,581.2 9.6

10-24-2013 Fall DIDSON, ARIS 990.0 1,579.4 9.3

10-25-2013 Fall DIDSON, ARIS 722.5 1,577.8 8.9

10-27-2013 Fall ARIS 457.1 1,576.6 9.1

10-29-2013 Fall ARIS 492.9 1,575.5 8.2

10-30-2013 Fall DIDSON, ARIS 476.5 1,574.9 8.4

10-31-2013 Fall DIDSON, ARIS 469.2 1,574.3 8.4

11-02-2013 Fall ARIS 370.4 1,573.6 8.7

11-03-2013 Fall DIDSON 426.3 1,573.7 8.7

11-04-2013 Fall DIDSON 416.3 1,573.5 8.5

11-07-2013 Fall DIDSON 1,033.3 1,574.6 8.0

11-08-2013 Fall DIDSON 1,635.4 1,574.8 7.9

11-09-2013 Fall ARIS 2,496.3 1,572.1 8.3

11-11-2013 Fall DIDSON, ARIS 2,445.4 1,562.9 8.3

11-12-2013 Fall DIDSON 2,478.8 1,557.7 8.3
55 

Appendix B. Rose Plots and Circular Histograms of Mean Travel Directions of 

Fish Collected by Acoustic Cameras by Depth and Photoperiod at Cougar 

Reservoir and Dam, Oregon 

Figure B1. Rose plots and circular histograms of mean travel directions of fish (in degrees) collected by the 

DIDSON® acoustic camera by depth and photoperiod (day or night) at Cougar Reservoir and Dam, Oregon, spring 

2013.
56 

Figure B2. Rose plots and circular histograms of mean travel directions of fish (in degrees) collected by the ARIS®

acoustic camera by depth and photoperiod (day or night) at Cougar Reservoir and Dam, Oregon, spring 2013. 
57 

Figure B3. Rose plots and circular histograms of mean travel directions of fish (in degrees) collected by the 

DIDSON acoustic camera by depth and photoperiod (day or night) at Cougar Reservoir and Dam, Oregon, fall

2013.
58 

Figure B4. Rose plots and circular histograms of mean travel directions of fish (in degrees) collected by the 

ARIS® acoustic camera by depth and photoperiod (day or night) at Cougar Reservoir and Dam, Oregon, fall 2013.
59 

Appendix C. Density Plots of Fish Target Locations from DIDSON and ARIS 

Acoustic Camera Data Collected during the Fish Behavior Evaluations at Cougar 

Reservoir and Dam, Oregon, 2013

Figure C1. Top-down perspective density plots of fish target locations (fish size 30–60 millimeters [mm]) by 

photoperiod (day, night, or combined) from DIDSON® and ARIS® acoustic-camera data collected during the fish 

behavior evaluations at Cougar Reservoir and Dam, Oregon, 2013. 
60 

Figure C2. Top-down perspective density plots of fish target locations (fish size 60–90 millimeters [mm]) by 

photoperiod (day, night, or combined) from DIDSON® and ARIS® acoustic-camera data collected during the fish 

behavior evaluations at Cougar Reservoir and Dam, Oregon, 2013.
61 

Figure C3. Top-down perspective density plots of fish target locations (fish size 90–250 millimeters [mm]) by 

photoperiod (day, night, or combined) from DIDSON® and ARIS® acoustic-camera data collected during the fish 

behavior evaluations at Cougar Reservoir and Dam, Oregon, 2013.
62 

Figure C4. Top-down perspective density plots of fish target locations (fish size >300 millimeters [mm]) by 

photoperiod (day, night, or combined) from DIDSON® and ARIS® acoustic camera data collected during the fish 

behavior evaluations at Cougar Reservoir and Dam, Oregon, 2013.
Publishing support provided by the U.S. Geological Survey

Science Publishing Network, Tacoma Publishing Service Center

For more information concerning the research in this report, contact the

 Director, Western Fisheries Research Center

U.S. Geological Survey

6505 NE 65th Street

Seattle, Washington 98115 

http://wfrc.usgs.gov/
Adams and others—Fish Behavior Upstream of the Water Temperature Control Tower at Cougar Dam, Oregon, 2013—Open-File Report 2015–1124

ISSN 2331-1258 (online)

http://dx.doi.org/10.3133/ofr20151124