U.S. Geological Survey

Grand Canyon Monitoring

and Research Center

Fiscal Year 2019

Annual Project Report

to the

Glen Canyon Dam

Adaptive Management

Program
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Table of Contents

Table of Contents ................................................................................................................................................... i

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

LTEMP Resource Goals: Table 1......................................................................................................................2

Project A: Streamflow, Water Quality, and Sediment Transport and Budgeting in the 

Colorado River Ecosystem.................................................................................................................................8

Project B: Sandbar and Sediment Storage Monitoring and Research .......................................... 12

Project C: Riparian Vegetation Monitoring and Research................................................................. 21

Project D: Geomorphic Effects of Dam Operations and Vegetation Management for 

Archaeological Sites .......................................................................................................................................... 39

Project E: Nutrients and Temperature as Ecosystem Drivers: Understanding Patterns, 

Establishing Links and Developing Predictive Tools for an Uncertain Future .......................... 51

Project F: Aquatic Invertebrate Ecology .................................................................................................. 70

Project G: Humpback Chub Population Dynamics throughout the Colorado River 

Ecosystem ............................................................................................................................................................. 78

Project H: Salmonid Research and Monitoring ..................................................................................... 95

Project I: Warm-Water Native and Nonnative Fish Research and Monitoring.......................111

Project J: Socioeconomic Research in the Colorado River Ecosystem .......................................119

Project K: Geospatial Science and Technology ....................................................................................125

Project L. Remote Sensing Overflight in Support of Long-Term Monitoring and LTEMP..134

Project M: Administration ...........................................................................................................................135

Project N: Hydropower Monitoring and Research.............................................................................136

Appendix 1: Lake Powell Water Quality Monitoring.........................................................................141

Tables A and B...................................................................................................................................................151

Table A: Planned Uses of Final Deobligation from Previous 5-Year Agreement....................152

Table B: August 2019 Deobligation .........................................................................................................153
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Introduction

Following is the U.S. Geological Survey (USGS) Grand Canyon Monitoring and Research Center’s 

(GCMRC) Fiscal Year (FY) 2019 Annual Accomplishment Report. This report is prepared primarily 

for the Bureau of Reclamation to account for work conducted and products delivered in FY 

2019 by GCMRC and to inform the Technical Work Group of science conducted by GCMRC and 

its cooperators in support of the Glen Canyon Dam Adaptive Management Program. 

It includes a summary of accomplishments, modifications, results, and recommendations 

related to projects included in GCMRC’s FY 2018-2020 Triennial Work Plan for FY 20191. This 

work was done to support the 11 resource goals identified in the Glen Canyon Dam Long-Term 

Experimental and Management Plan (LTEMP) Environmental Impact Statement and Record of 

Decision (Table 1). The report also contains a summary of deobligation/reobligation funding 

amounts for specific projects that resulted from the transition to the new 5-year funding 

agreement with the Bureau of Reclamation in FY 2020 (Tables A & B).

1

This information is preliminary or provisional and is subject to revision. It is being provided to meet the need 

for timely best science. The information has not received final approval by the U.S. Geological Survey (USGS) 

and is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any 

damages resulting from the authorized or unauthorized use of the information.

The use of trade names is for informational purposes only and does not imply endorsement.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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LTEMP Resource Goals: Table 1

Archaeological and Cultural Resources

LTEMP Resource Goal Project Addressing this Goal

Maintain the integrity of potentially 

affected National Register of 

Historic Places (NRHP)-eligible or 

listed historic properties in place, 

where possible, with preservation 

methods employed on a sitespecific basis.

This LTEMP resource goal is being addressed by 

Project D through examining how flow and non-flow 

actions will ultimately affect the long-term 

preservation of cultural resources and other culturallyvalued and ecologically important landscape elements 

located within the Colorado River ecosystem (CRe).

Natural Processes

LTEMP Resource Goal Project Addressing this Goal

Restore, to the extent practicable, 

ecological patterns and processes 

within their range of natural 

variability, including the natural 

abundance, diversity, and genetic 

and ecological integrity of the plant 

and animal species native to those 

ecosystems.

This LTEMP resource goal is being addressed by 

Projects A, C, E, and F through: 1) monitoring of stage, 

discharge, water temperature, specific conductance, 

dissolved oxygen, turbidity, suspended-sediment 

concentration, and particle size at stream/river 

locations throughout the CRe, 2) monitoring changes 

in riparian vegetation using field-collected data and 

digital imagery, developing predictive models of 

vegetation composition as it relates to hydrological 

regime, and providing monitoring protocols and 

decision support tools for active vegetation 

management, 3) identifying processes that drive 

spatial and temporal variation in nutrients and 

temperature within the CRe and establishing 

quantitative and mechanistic links among these 

ecosystem drivers, primary production, and higher 

trophic levels, and 4) tracking the response of aquatic 

food base organisms to flow and non-flow actions.
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Humpback Chub

LTEMP Resource Goal Project Addressing this Goal

Meet humpback chub recovery 

goals, including maintaining a selfsustaining population, spawning 

habitat, and aggregations in the 

Colorado River and its tributaries 

below the Glen Canyon Dam.

This LTEMP resource goal is being addressed by 

Projects E, F, G, I, and J through: 1) identifying 

processes that drive spatial and temporal variation in 

nutrients and temperature within the CRe and 

establishing quantitative and mechanistic links among 

these ecosystem drivers, primary production, and 

higher trophic levels, 2) tracking the response of 

aquatic food base organisms to flow and non-flow 

actions, 3) monitoring of humpback chub populations, 

dynamics, and condition in aggregations in the 

mainstem Colorado River both upstream and 

downstream of the confluence with the Little 

Colorado River (LCR) and within the LCR, 4) 

monitoring the status and trends of native and 

nonnative fishes that occur in the CRe from Lees 

Ferry, AZ to Lake Mead, and 5) identifying preferences 

for, and values of, native fish like the humpback chub 

and evaluating how preferences and values are 

influenced by Glen Canyon Dam operations.

Tribal Resources

LTEMP Resource Goal Project Addressing this Goal

Maintain the diverse values and 

resources of traditionally associated 

Tribes along the Colorado River 

corridor through Glen, Marble, and 

Grand Canyons.

This LTEMP resource goal is being addressed by 

Project J through identifying Tribes’ preferences for, 

and values of, downstream resources and evaluating 

how these preferences and values are influenced by 

Glen Canyon Dam operations.
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Recreational Experience

LTEMP Resource Goal Project Addressing this Goal

Maintain and improve the quality of 

recreational experiences for the 

users of the CRe. Recreation 

includes, but is not limited to, 

flatwater and whitewater boating, 

river corridor camping, and angling 

in Glen Canyon.

This LTEMP resource goal is being addressed by 

Projects B, C, and H through: 1) tracking the effects of 

experimental actions such as High-Flow Experiments 

(HFEs) on sandbars, monitoring the cumulative effect 

of successive HFEs and intervening operations on 

sandbars and sand conservation, and investigating the 

interactions between dam operations and sand 

transport, and eddy sandbar dynamics, 2) monitoring 

changes in riparian vegetation using field-collected 

data and digital imagery, developing predictive models 

of vegetation composition as it relates to hydrological 

regime, and providing monitoring protocols and 

decision support tools for active vegetation 

management, and 3) monitoring the status and trends 

of both rainbow and brown trout upstream of Lees 

Ferry in Glen Canyon as well as increase understanding 

of key factors such as density and recruitment, prey 

availability, and nutrients that control the abundance 

and growth of the trout population.
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Other Native Fish

LTEMP Resource Goal Project Addressing this Goal

Maintain self-sustaining native fish 

species populations and their 

habitats in their natural ranges on 

the Colorado River and its 

tributaries.

This LTEMP resource goal is being addressed by 

Projects E, F, G, and I through: 1) identifying processes 

that drive spatial and temporal variation in nutrients 

and temperature within the CRe and establishing 

quantitative and mechanistic links among these 

ecosystem drivers, primary production, and higher 

trophic levels, 2) tracking the response of aquatic food 

base organisms to flow and non-flow actions, 3) 

monitoring of humpback chub populations, dynamics, 

and condition in aggregations in the mainstem 

Colorado River both upstream and downstream of the 

confluence with the LCR and within the LCR, and 4) 

monitoring the status and trends of native and 

nonnative fishes that occur in the Colorado River 

ecosystem from Lees Ferry to Lake Mead.

Sediment

LTEMP Resource Goal Project Addressing this Goal

Increase and retain fine sediment 

volume, area, and distribution in the 

Glen, Marble, and Grand Canyon 

reaches above the elevation of the 

average base flow for ecological, 

cultural, and recreational purposes.

This LTEMP resource goal is being addressed by 

Projects A and B through: 1) monitoring of stage, 

discharge, water temperature, specific conductance, 

dissolved oxygen, turbidity, suspended-sediment 

concentration, and particle size at stream/river 

locations in the Glen, Marble, and Grand Canyon 

reaches and 2) tracking the effects of experimental 

actions such as HFEs on sandbars, monitoring the 

cumulative effect of successive HFEs and intervening 

operations on sandbars and sand conservation, and 

investigating the interactions between dam operations 

and sand transport, and eddy sandbar dynamics.
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Hydropower and Energy

LTEMP Resource Goal Project Addressing this Goal

Maintain or increase Glen Canyon 

Dam electric energy generation, 

load following capability, and ramp 

rate capability, and minimize 

emissions and costs to the greatest 

extent practicable, consistent with 

improvement and long-term 

sustainability of downstream 

resources.

This LTEMP resource goal is being addressed by 

Project N through identifying, coordinating, and 

collaborating on monitoring and research 

opportunities associated with operational experiments 

at Glen Canyon Dam to meet hydropower and energy 

resource objectives.

Rainbow Trout Fishery

LTEMP Resource Goal Project Addressing this Goal

Achieve a healthy high-quality 

recreational rainbow trout fishery in 

Glen Canyon and reduce or 

eliminate downstream trout 

migration consistent with National 

Park Service fish management and 

Endangered Species Act

compliance.

This LTEMP resource goal is being addressed by Project 

H, E, F, and G through: 1) monitoring the status and 

trends of both rainbow and brown trout upstream of 

Lees Ferry in Glen Canyon as well as increase 

understanding of key factors such as density and 

recruitment, prey availability, and nutrients that 

control the abundance and growth of the trout 

population, 2) identifying processes that drive spatial 

and temporal variation in nutrients and temperature 

within the CRe and establishing quantitative and 

mechanistic links among these ecosystem drivers, 

primary production, and higher trophic levels, 3) 

tracking the response of aquatic food base organisms 

to flow and non-flow actions, and 4) monitoring of 

humpback chub populations, dynamics, and condition 

in aggregations in the mainstem Colorado River both 

upstream and downstream of the confluence with the 

LCR and within the LCR.
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Nonnative Invasive Species

LTEMP Resource Goal Project Addressing this Goal

Minimize or reduce the presence 

and expansion of aquatic nonnative 

invasive species.

This LTEMP resource goal is being addressed by 

Projects F, I, G, and J through: 1) tracking the response 

of aquatic food base organisms to flow and non-flow 

actions, 2) monitoring the status and trends of native 

and nonnative fishes that occur in the CRe from Lees 

Ferry to Lake Mead, 3) monitoring of humpback chub 

populations, dynamics, and condition in aggregations 

in the mainstem Colorado River both upstream and 

downstream of the confluence with the LCR and 

within the LCR, and 4) identifying preferences for, and 

values of, nonnative fish like the rainbow trout and 

evaluating how preferences and values are influenced 

by Glen Canyon Dam operations.

Riparian Vegetation

LTEMP Resource Goal Project Addressing this Goal

Maintain native vegetation and 

wildlife habitat, in various stages of 

maturity, such that they are diverse, 

healthy, productive, self-sustaining, 

and ecologically appropriate.

This LTEMP resource goal is being addressed by 

Project C through monitoring changes in riparian 

vegetation using field-collected data and digital 

imagery, developing predictive models of vegetation 

composition as it relates to hydrological regime, and 

providing monitoring protocols and decision support 

tools for active vegetation management.
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Project A: Streamflow, Water Quality, and Sediment Transport and

Budgeting in the Colorado River Ecosystem

Project Lead David Topping

Principal 

Investigator(s) (PI)

David Topping, USGS, GCMRC

Ronald Griffiths, USGS, GCMRC

David Dean, USGS, GCMRC

Email dtopping@usgs.gov

Telephone (928) 556-7396

SUMMARY

The Streamflow, Water Quality, and Sediment Transport and Budgeting in the Colorado River 

Ecosystem Project is focused on high-resolution monitoring of stage, discharge, water 

temperature, specific conductance, dissolved oxygen, turbidity, suspended-sediment 

concentration, and particle size at 8 mainstem and 16 tributary sites located throughout the 

Colorado River ecosystem (CRe). These data are collected to address the Glen Canyon Dam 

Adaptive Management Program (GCDAMP) Goal 7 and the Long-Term Experimental and 

Management Plan (LTEMP) Sediment Goal. The data collected by this project are used to inform 

managers on the physical status of the Colorado River in the CRe and how this physical status is 

affected by dam operations in near real time. Therefore, in addition to addressing the LTEMP 

sediment goal, the stage, discharge, and water-quality data collected by this project are used by 

other projects funded by the GCDAMP to address the LTEMP goals for archaeological and 

cultural resources, natural processes, humpback chub, other native fish, recreational experience, 

rainbow trout fishery, nonnative invasive species, and riparian vegetation. The high-resolution 

suspended-sediment data collected under this project are used to construct the mass-balance 

sediment budgets used by managers to trigger, design, and evaluate High-Flow Experiments 

(HFEs) under the High-Flow Protocol included in the 2016 LTEMP Record of Decision. Details of 

this ongoing project (including descriptions of the data-collection locations) are provided in the 

GCMRC fiscal year (FY) 2018–20 Triennial Work Plan (TWP).

Science Question Addressed

The Streamflow, Water Quality, and Sediment Transport and Budgeting in the CRe Project 

addresses the following fundamental science question on an ongoing basis: 

How do operations at Glen Canyon Dam affect flows, water quality, sediment 

transport, and sediment resources in the CRe?

During FY 2019, this question was addressed through these methods:
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1) All FY 2019 monitoring data required by this project, including those required to 

evaluate the November 2018 HFE, were collected. All continuous stage, discharge, 

water-quality, and acoustical suspended-sediment data have been uploaded to, and are 

available at, the U.S. Geological Survey's Grand Canyon Monitoring and Research Center 

(GCMRC) website (www.gcmrc.gov or https://www.usgs.gov/centers/sbsc/gcmrc/). 

Unlike in previous years where, by late November, we had completed the processing of 

95% of all suspended-sediment samples collected the previous fiscal year, processing of 

the suspended-sediment samples collected during FY 2019 data is only ~70% complete. 

This aspect of the project is still behind schedule as a result of the January 2019 

government shutdown and an unrelated several-month delay in hiring replacement

laboratory technicians by the USGS. 

2) Maintenance and continued updating of the database and website can be accessed at: 

https://www.gcmrc.gov/discharge_qw_sediment/ or 

https://cida.usgs.gov/gcmrc/discharge_qw_sediment/. All stage, discharge, waterquality (water temperature, specific conductance, turbidity, dissolved oxygen), 

suspended-sediment, and bed-sediment data collected at the active and inactive 

monitoring stations on the Colorado River and its tributaries are posted at this website. 

User-interactive tools at this website allow visualization and downloading of these data 

and the construction of sand budgets and duration curves.

3) Two peer-reviewed interpretive journal articles were published, three abstracts were

submitted, and oral presentations given at professional scientific meetings during FY 

2019. See products list below. In addition to these products, work progressed during 

2019 on several manuscripts under the FY 2018–20 Triennial Work Plan. One entitled 

"What grain size reveals about suspended-sand transport in the Colorado River in Grand 

Canyon," by David M. Rubin, Daniel Buscombe, Scott A. Wright, David J. Topping, Paul E. 

Grams, John C. Schmidt, Joseph E. Hazel, Jr., and Matthew Kaplinski has been through 

review at the Journal of Geophysical Research–Earth Surface, revised, and resubmitted. 

Two other manuscripts are nearing completion and will be submitted for peer review 

this winter. These include: "Peak-stage indicators of Colorado River floods in Grand 

Canyon National Park" by Thomas A. Sabol, Ronald E. Griffiths, David J. Topping, Erich R. 

Mueller, Robert B. Tusso, and Joseph E. Hazel, Jr. (to be submitted as a USGS Open-File 

Report), and "Effects of a dam and episodic tributary resupply on sand transport and 

storage in a supply-limited river," by David J. Topping, Ronald E. Griffiths, Paul E. Grams, 

David M. Rubin, and others (to be submitted to the Journal of Geophysical Research–

Earth Surface).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation Grain-size controls on sand storage in 

rivers

Dec

2018

Topping. D.J., Rubin, D.M., Griffiths, R.E., 

Dean, D.J., Schmidt, J.C., Grams, P.E., 

Mueller, E.R., 2018, Grain-size controls 

on sand storage in rivers—Abstract 

EP31C-2358: Washington, D.C., Dec. 10-

14, 2019, 2018 Fall Meeting, AGU.

Presentation

Geomorphic change and 

biogeomorphic feedbacks in a dryland 

river: The Little Colorado River, 

Arizona, USA

Sept 

2019

Dean, D.J., and Topping, D.J., 2019, 

Geomorphic change and biogeomorphic 

feedbacks in a dryland river—abstract: 

The Little Colorado River, Arizona, USA: 

Phoenix, Ariz., September 2019, 

Geological Society of America Abstracts 

with Programs, v. 51, no. 5, 

https://doi.org/10.1130/abs/2019AM339900.

Presentation

Geomorphic change, biogeomorphic 

feedbacks, and the downstream 

transformation of floodwaves in the 

Little Colorado River, Arizona, USA

Sept

2019

Dean, D.J., and Topping, D.J., 2019, 

Geomorphic change, biogeomorphic 

feedbacks, and the downstream 

transformation of floodwaves in the 

Little Colorado River, Arizona, USA: 

Flagstaff, Ariz.,September 9-12, 2019, 

15th Biennial Conference of Science & 

Management on the Colorado Plateau 

and Southwest Region, High Country 

Conference Center, Northern Arizona 

University. 

Journal 

article

How many measurements are 

required to construct an accurate 

sand budget in a large river? Insights 

from analyses of signal and noise

Jan 

2019

Grams, P.E., Buscombe, D., Topping, D.J., 

Kaplinski, M., and Hazel, J.E., Jr., 2019, 

How many measurements are required 

to construct an accurate sand budget in a 

large river? Insights from analyses of 

signal and noise: Earth Surface Processes 

and Landforms, v. 44, no. 1, p. 160-178, 

https://doi.org/10.1002/esp.4489.

Journal 

article

Geomorphic change and 

biogeomorphic feedbacks in a dryland 

river: The Little Colorado River, 

Arizona, USA

April

2019

Dean, D.J., and Topping, D.J., 2019, 

Geomorphic change and biogeomorphic 

feedbacks in a dryland river—The Little 

Colorado River, Arizona, USA: Geological 

Society of America Bulletin, v. 131, no. 

11-12, p. 1920- 1942, 

https://doi.org/10.1130/B35047.1.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Web

application

Stage, discharge, and water-quality 

data collected at 9 gaging stations by 

the USGS Utah and Arizona Water 

Science Centers under project are 

posted to the web every hour.

hourly

Online realtime database:

http://waterdata.usgs.gov/nwis

Web

application

Stage, discharge, sediment transport, 

water-quality, and sand-budget data 

are served through the USGS-GCMRC 

website. A web-based application has 

been maintained to provide 

stakeholders, scientists, and the 

public with the ability to perform 

interactive online data visualization 

and analysis, including the ondemand construction of sand budgets 

and duration curves. These 

capabilities are unique in the world.

updated 

every 

month

Online database and web-based 

applications:

http://www.gcmrc.gov/discharge_qw_se

diment/

and 

http://cida.usgs.gov/gcmrc/discharge_q

w_sediment/
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Project B: Sandbar and Sediment Storage Monitoring and Research

Project Lead Paul Grams

Principal 

Investigator(s) (PI)

Paul Grams, USGS, GCMRC

Keith Kohl, USGS, GCMRC

Robert Tusso, USGS, GCMRC

Robert Ross, USGS, GCMRC

Daniel Buscombe, NAU

Matt Kaplinski, NAU

Joe Hazel, NAU

Erich Mueller, SUU

Email pgrams@usgs.gov

Telephone (928) 556-7385

SUMMARY

The purposes of this project are to: a) track the effects of individual High-Flow Experiments

(HFEs) on sandbars, b) monitor the cumulative effect of successive HFEs and intervening 

operations on sandbars and sand conservation, and c) investigate the interactions between 

dam operations, sand transport, and eddy sandbar dynamics. Outcomes from this project will

be used to evaluate the effectiveness of the HFE protocol included in the 2016 Long-Term 

Experimental and Management Plan Record of Decision with respect to sandbar condition.

The list of products, below, is cumulative for the fiscal year (FY) 2018-2020 workplan and 

includes three recurring data products, eight products completed in FY 2019 and FY 2010 

products that were completed in FY 2018. In addition to those listed products, ten 

presentations were made involving project investigators at professional meetings.

Sandbar Monitoring Using Topographic Surveys and Remote Cameras (B.1.)

Sandbar Monitoring and Response to High-Flow Experiments 

Sandbar monitoring data were collected in October 2018, processed, and reported at the 

annual reporting meeting in March 2019. Images from the remote cameras were retrieved in 

October 2018, April 2019, and October 2019. As of the end of FY 2019, five HFEs have been

conducted, all under sand-enriched conditions, since the HFE Protocol was initiated in 2012. 

Those HFEs occurred in November of 2012, 2013, 2014, 2016, and 2018. In each case, sandbar 

building results were generally consistent with the results from previous HFEs. All HFEs resulted 

in substantial deposition at all sandbar types (see Mueller and others, 2018 for description of 

sandbar types). Deposition was followed by erosion of about half the new deposits within six

months, which is also consistent with the response to previous HFEs. Response immediately 

after the 2018 HFE based on digital camera images of sandbars from Lees Ferry to Diamond 
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Creek indicated that there was a substantial gain (deposition) for 27 sandbars (66% of sites), no 

substantial change for nine sandbars (22% of sites), and substantial loss (erosion) for five

sandbars (12% of sites) (Figure 1). The HFE deposits typically begin eroding immediately 

following each HFE and the bulk of the newly deposited sand persists for approximately 6 to 12 

months. Annual topographic surveys of sandbars were conducted between September 26 and 

October 12, 2018. Data from these surveys indicate that there has been some net increase in 

the size of reattachment sandbars since the beginning of the HFE protocol in 2012 (Figure 2). 

The size of other types (Mueller and others, 2018) of sandbars has fluctuated, with no 

significant net increase or decrease. Thus, despite erosion of much of the HFE-deposited sand, 

the deposits do persist longer at some sites. Deposition of sand during HFEs has caused 

temporary increases in campsite area; however, there has been a net long-term decline in 

campsite area caused by vegetation encroachment (Hadley and others, 2018). Although HFEs 

do not prevent vegetation encroachment, HFEs do provide increases in campsite area—even if 

those increases are temporary. Results from the October 2019 annual sandbar survey ,that 

show sandbar conditions 11 months after the most recent HFE in November 2018, will be 

presented at the Annual Reporting Meeting in January 2020.

Developments in Sandbar Data Processing and Public Database 

FY 2019 was the second year of implementing the new workflow and database for processing, 

analyzing, storing, and disseminating the sandbar monitoring data. The new workflow is 

standardized and allows automated processing of the entire data set and is implemented in a 

“workbench” that is based on open-source processing tools. The processing outputs of the 

workbench are stored in a MySQL database that powers the public-facing sandbar webpage 

where the data can be accessed and visualized by the public at (www.gcmrc.gov/sandbar or

https://www.usgs.gov/apps/sandbar). The database stores the results of over 1,700 individual 

topographic and bathymetric surveys that have been completed at the collection of 45 longterm monitoring sites.

Analysis of Remote Camera Images 

In FY 2019, additional progress was made on the effort to automate analysis of the remote 

camera images of sandbars. This has included the development of machine learning software 

for automated segmenting of the sandbars from the images (Buscombe and Ritchie, 2018) and 

identification of metrics for sandbar size that can be easily extracted from the remote camera 

images and correlated with the annual measurements of sandbar volume. In FY 2019, 

additional ground control points were collected at most long-term sandbar sites to finalize 

rectifications for all sites and compute reprojection errors. Rectification is the perspective 

transformation of the image into a planform image in a projected coordinate system, which 

enables sandbar areas to be estimated. The reprojection errors are horizontal errors in meters 

in Eastings and Northings and will be factored into final uncertainties of sandbar area 
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estimates. The software for automated segmenting of the sandbars has been refined and 

improved by correcting a model bias that caused segmentation errors to increase at sites 

further from the camera. Additionally, the frequency of sandbar mass failures, as revealed in 

the remote camera period of record for each site, has been documented. This analysis is part of 

an ongoing project into why some sandbars exhibit this behavior and others do not, with 

implications for both understanding and predicting sandbar dynamics as well as boater and 

camper safety.

Bathymetric and Topographic Mapping for Monitoring Long-Term Trends in Sediment Storage

(B.2.)

Data Collection 

In FY 2019, data were collected to map changes in riverbed sand storage in Lower Marble 

Canyon and eastern Grand Canyon. These data were collected on a 21-day river trip in April 

2019. This trip involved 151 multibeam sonar surveys and 126 terrestrial surveys. Over 2,600 

images were collected to characterize the composition and grain size of riverbed sediment. 

Data were also collected with frequency-modulating sonar to enable estimates of riverbed sand 

thickness. Processing of these data is underway by cooperators at Northern Arizona University.

Data Processing and Reporting

In FY 2019, progress was made on processing of data collected in the previous work plan. The 

topographic and bathymetric data collected in Glen Canyon (between Glen Canyon Dam and 

Lees Ferry) were integrated with photogrammetrically-derived elevations to produce a 

complete high-resolution digital elevation model for this segment. These data are currently 

available upon request and may be viewed online (grandcanyon.usgs.gov/portal/home). Data 

releases for Glen Canyon and previous channel mapping efforts from 2011 to 2016 are planned 

in FY 2020. 

Grams and others (2018b) reported on repeat mapping of the riverbed in Lower Marble Canyon 

and demonstrated that repeat mapping of at least 50% of the river segment was required to 

determine the sand budget with signal-to-noise ratio (SNR) > 1. This analysis was for the 2009 

to 2012 period, which did not include HFEs, but did include sustained high-flow volumes in 2011 

for reservoir equalization. These flows resulted in sand evacuation that was temporally 

concentrated (~100% of mass change occurred during 19% of the study period) and highly 

localized (70% of mass change occurred in 12% of the study segment). In FY 2019, analysis was 

completed for two additional repeat mapping data sets. These show sand evacuation in eastern 

Grand Canyon between 2011 and 2014 and sand accumulation in Upper Marble Canyon 

between 2013 and 2016. Together, these results demonstrate that sand accumulation can 

occur over periods that include substantial inputs from the Paria River and average or lower 

dam-release volumes (annual volumes were less than 9.2 million acre-feet every year between 
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2013 and 2016). Net erosion occurs when dam-release volumes are above average (the 2011 

annual volume was 12.7 million acre-feet). These findings will be presented at the Annual 

Reporting Meeting in January 2020.

Advances in Bedload Sediment Transport and Bed Sediment Classification

In FY 2019, several manuscripts have been prepared and submitted to journals on the topic of 

refining bedload sediment transport estimates in Grand Canyon. The three papers have 

examined different aspects of the problems of data processing, collection and modeling of 

bedload. Leary and Buscombe (2019) estimated the error associated with using a time-series of 

bed elevation changes at a point from a singlebeam sonar with a 4D dataset collected with a 

multibeam sonar, concluding that doing so introduces unacceptable error due to the ambiguity 

of migrating dune length and period. Ashley and others (2019) developed a Bayesian 

framework for estimating bedload transport at each long-term sediment monitoring gage. The 

new model, based on theory developed by Rubin and Topping (2001), continuously predicts 

bedload based on available suspended sediment, discharge and grain size information at gages 

only, with well-defined uncertainties. The application of the model might also be useful for 

identifying periods of relative sediment deficit and surplus in reach-scale sediment storage, 

which will be tested in future studies. Finally, Guala and others (2019) have developed a new 

model for predicting bedload flux based on dune geometry and shear stress. We are now 

presented with a viable opportunity to estimate bedload for any reach within Grand Canyon 

given bedform geometry estimates, depth and water surface slope measurements, all of which 

are derived products from channel mapping bathymetric and topographic data. In February 

2019 we collected another 4D multibeam bed elevation and ADCP dataset from the vicinity of 

the Diamond Creek gage. To date, we have collected seven datasets such as these for the 

purposes of better estimating bedload transport at different flows using dune tracking; five at 

the Diamond Creek gage, and one each at 30-mile and 166-mile gages. We plan to issue a USGS 

data release in FY 2020.

Up until FY 2019, all bed sediment classification used data collected using a Reson 7125 system, 

and in FY 2019 we also made progress toward a similar bed sediment classification for the data 

collected by the Norbit multibeam system. Laboratory measurements were collected using the 

Norbit that help us to acoustically constrain estimates of riverbed substrates and submerged 

aquatic vegetation. We are in the beginning stages of developing a new software that will 

incorporate this new information into the existing acoustic processing codes, and enable us to 

estimate and merge substrate maps from both the Reson and Norbit acoustic data. In FY 2019, 

our in-house sidescan sonar processing software (PyHum) has been updated to Python 3 and 

upgraded with new features. Additionally, we switched hydrographic data collection software; 

a major undertaking that will make backscatter data processing less cumbersome and more 

accurate.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[16]

Control Network and Survey Support (B.3.)

There was no logistics funding in FY 2019 for operations to advance survey control into new 

regions of the Colorado River through Grand Canyon. Survey control is adequate for mapping 

channel bathymetry in all segments of Grand Canyon, except for portions of the segment 

between Bright Angel Creek and National Canyon. One additional control trip is needed to 

prepare for mapping that segment in the FY 2021-23 work plan. However, logistics funding for 

that trip is not currently in the FY 2020 budget. 

In FY 2019, we mapped what had previously been two reaches and two river trips within the 

bounds of a single, 18-day river trip. Mapping efforts between Fence Fault at river mile 29 to 

Bright Angel Creek at river mile 88 were accomplished in April 2019 and entailed measurements 

from 121 control stations. These 121 stations were used to position 176 bathymetric shore 

station instruments and over 35,000 topographic points. Additionally, in October 2019, 68 

control stations were occupied with total stations for sandbar monitoring. The control network 

was also referenced for terrestrial lidar point clouds at ten sites where aeolian sand transport 

was modeled and at 15 sites where historical aerial imagery was orthorectified to determine 

area and volume of popular sandbars in 1983.

The river primary control network has been processed and adjusted through National Geodetic 

Survey bluebooking protocols and computations providing an independent check of the 

network which had been developed through proprietary software. The Pages and Adjust 

software used to compute the National Spatial Reference System are open-source and support 

improved transparency of computation methods. Positions referencing NAD83(2011) rim 

station control differ from those referencing active CORS and positioned in ITRF 2014 by < 4 cm 

in both horizontal and vertical components (at 95% confidence). The results verify that the 

control stations used for channel mapping have high-accuracy positions on a global datum.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[17]

Figure 1. Percent of 45 monitored sandbar sites with deposition (green squares) or erosion (red circles) based on visual 

estimates of change in sandbar size in remote-camera images from monitoring sites along the Colorado River in Grand Canyon 

National Park, Arizona, following the November 2016 HFE and Colorado River discharge at Lees Ferry, Arizona (blue line) in 

cubic feet per second from October 1, 2018 to November 1, 2019. Figure is from Grams and others (2018a).

Figure 2. Sandbar volume (m3) at long-term monitoring sites along the Colorado River in Grand Canyon National Park, Arizona

by sandbar type from 1990 through October 2018. Group 1a, 1b, and 1c are unvegetated, moderately vegetated and heavily 

vegetated reattachment bars, respectively (Mueller and others, 2018). Group 2 sites are separation bars in high-energy, wavedominated eddies. Group 3 sites are vegetated upper-pool sandbars. Group 4 sites are separation bars in low-energy eddies. 

Solid vertical lines are High-Flow Experiments of 36,000 ft3/s or greater and dashed lines are power-plant capacity releases. 

Modified from Mueller and others (2018).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[18]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Project B.2: Report 

on automated 

methods for 

substrate 

classification

March

2018

Buscombe, D., Grams, P.E., and Kaplinski, M.A., 2018, 

Probabilistic models of seafloor composition using 

multispectral acoustic backscatter: GeoHab 2018 

Conference, R2Sonic Multispectral Backscatter Challenge, 

Santa Barbara, Calif., May 8, 2018, 1-29 p., online 

download available at 

https://www.r2sonic.com/geohab2018/.

Presentation

Project B.1: Extended 

abstract on the 

effects of HFEs on 

sandbars

March

2019

Grams, P.E., 2019, Sandbar deposition caused by highflow experiments on the Colorado River downstream 

from Glen Canyon Dam—November 2012-November 

2018, in High-flow experiments assessment extended 

abstracts—Glen Canyon Dam Adaptive Management 

Program Annual Reporting Meeting Presentations, March 

12-13, 2019, Phoenix, Ariz.: U.S. Geological Survey, Grand 

Canyon Monitoring and Research Center, p. 12-22, 

https://www.usbr.gov/uc/progact/amp/amwg/2019-03-

06-amwg-meeting/20190301-HFE_Extended_AbstractsCombined_FINAL.pdf.

Presentation

Project B.1: Extended 

abstract on the 

effects of HFEs on 

sandbars

March 

2019

Topping, D.J., Grams, P.E., Griffiths, R.E., Hazel, J.E., 

Kaplinski, M.A., Dean, D.J., Voichick, N., Unema, J.A., and 

Sabol, T.A., 2019, Optimal timing of high-flow 

experiments for sandbar deposition, in High-flow 

experiments assessment extended abstracts—Glen 

Canyon Dam Adaptive Management Program Annual 

Reporting Meeting presentations, March 12-13, 2019, 

Phoenix, Ariz.: U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center, p. 3-9, 

https://www.usbr.gov/uc/progact/amp/amwg/2019-03-

06-amwg-meeting/20190301-HFE_Extended_AbstractsCombined_FINAL.pdf.

Journal article

Project B.1: Journal 

article on sandbar 

changes

Dec 

2017

Mueller, E.R., Grams, P.E., Hazel, J.E., Jr., and Schmidt, 

J.C., 2018, Variability in eddy sandbar dynamics during 

two decades of controlled flooding of the Colorado River 

in the Grand Canyon: Sedimentary Geology, v. 363, p. 

181-199, https://doi.org/10.1016/j.sedgeo.2017.11.007.

Journal article

Project B.2: Journal 

article on automated 

methods for 

substrate 

classification

Mar 

2018

Hamill, D., Buscombe, D., and Wheaton, J.M., 2018, 

Alluvial substrate mapping by automated texture 

segmentation of recreational-grade side scan sonar 

imagery: PLOS One, v. 13, no. 3, e0194373, p. 1-28, 

https://doi.org/10.1371/journal.pone.0194373.

Journal article

Project B.2: Journal 

article on automated 

methods for image 

classification

Jun 

2018

Buscombe, D., and Ritchie, A.C., 2018, Landscape 

classification with deep neural networks: Geosciences, v. 

8, no. 7, article 244, p. 1-23, 

https://doi.org/10.3390/geosciences8070244.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[19]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Journal article

Project B.2 Journal 

article on automated 

methods for 

substrate 

classification

Sept 

2018

Buscombe, D., and Grams, P.E., 2018, Probabilistic 

substrate classification with multispectral acoustic 

backscatter—A comparison of discriminative and 

generative models: Geosciences, v. 8, no. 11, article 395, 

https://doi.org/10.3390/geosciences8110395.

Journal article

Project B.1 Journal 

article on causes of 

campsite area 

change

Sept

2018

Hadley, D.R., Grams, P.E., and Kaplinski, M.A., 2018, 

Quantifying geomorphic and vegetation change at 

sandbar campsites in response to flow regulation and 

controlled floods, Grand Canyon National Park, Arizona: 

River Research and Applications, v. 34, no. 9, p. 1208-

1218, https://doi.org/10.1002/rra.3349.

Journal article

Project B.1 Journal 

article on sand-area 

change

Sept 

2018

Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., East, 

A.E., and Grams, P.E., 2018, Quantifying and forecasting 

changes in the areal extent of river valley sediment in 

response to altered hydrology and land cover: Progress in 

Physical Geography: Earth and Environment, v. 42, no. 6, 

p. 739-764, https://doi.org/10.1177/0309133318795846.

Journal article

Project B.2 Journal 

article on long-term 

monitoring of sand 

storage

Oct 

2018

Grams, P.E., Buscombe, D., Topping, D.J., Kaplinski, M.A., 

and Hazel, J.E., Jr., 2018, How many measurements are 

required to construct an accurate sand budget in a large 

river? Insights from analyses of signal and noise: Earth 

Surface Processes and Landforms, v. 44, no. 1, p. 160-

178, https://doi.org/10.1002/esp.4489.

Journal article

Project B.2: Journal 

article on methods 

for measuring 

sediment grain size 

from images

Oct 

2019

Buscombe, D., 2019, SediNet—A configurable deep 

learning model for mixed qualitative and quantitative 

optical granulometry: Earth Surface Processes and 

Landforms, https://doi.org/10.1002/esp.4760.

Journal article

Project B.2: Journal 

article on methods 

for measuring sand 

bedload transport

Oct 

2019

Leary, K.C.P., and Buscombe, D., 2019, Estimating sand 

bedload in rivers by tracking dunes—A comparison of 

methods based on bed elevation time-series—preprint 

discussion paper: Earth Surface Dynamics, 

https://doi.org/10.5194/esurf-2019-38.

USGS

Scientific 

Investigations

Report

Project B.1 Report on 

causes of campsite 

area change

Dec 

2017

Hadley, D. R., Grams, P. E., Kaplinski, M. A., Hazel, J.E., J., 

& Parnell, R. A., 2018, Geomorphology and vegetation 

change at Colorado River campsites, Marble and Grand 

Canyons, Arizona: U.S. Geological Survey Scientific 

Investigations Report 2017–5096, 64 p., 

https://doi.org/10.3133/sir20175096.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[20]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

USGS

Open-File 

Report

Project B.1 Report on 

use of remote 

camera images for 

sandbar monitoring

Jan 

2018

Grams, P.E., Tusso, R.B., and Buscombe, D., 2018, 

Automated remote cameras for monitoring alluvial 

sandbars on the Colorado River in Grand Canyon, 

Arizona: U.S. Geological Survey Open-File Report 2018-

1019, 50 p., https://doi.org/10.3133/ofr20181019.

USGS 

Data

Project B.1: Data 

from long-term 

sandbar monitoring 

sites

Jan 

2019

To be presented at annual reporting meeting and 

www.gcmrc.gov/sandbar or

https://www.usgs.gov/apps/sandbar/

USGS 

Photos

Project B.1: Images 

from remote camera 

monitoring of 

sandbars

Jan 

2019

Website: www.gcmrc.gov/sandbar or

https://www.usgs.gov/apps/sandbar/

GCRG

Photos

Project B.1: Images 

from GCRG adopt-abeach program

Jan 

2019

Website: www.gcmrc.gov/sandbar or

https://www.usgs.gov/apps/sandbar/

USGS 

Data 

Project B.1: Data on 

causes of campsite 

area change

Sept 

2018

Hadley, D.R., Kaplinski, M.A., Hazel, J.E., Jr., Gushue, T.M., 

Ross, R.P., Grams, P.E., Parnell, R.A., and Fairley, H.C., 

2018, Geomorphology and campsite data, Colorado 

River, Marble and Grand Canyons, Arizona: U.S. 

Geological Survey data release, 

https://doi.org/10.5066/F7FJ2FQQ.

USGS 

Data 

Project B.1: Data on 

sand-area change

Oct 

2018

Kasprak, A., Sankey, J.B., Buscombe, D.D., Caster, J., East, 

A.E, Grams, P.E, 2018, River valley sediment connectivity 

data, Colorado River, Grand Canyon, Arizona: U.S. 

Geological Survey data release, 

https://doi.org/10.5066/P9SX3MGY.

USGS 

Data 

Project B.1: Data on 

sand-area change

Oct 

2018

Sankey, J.B., Chain, G.R., Solazzo, D., Durning, L.E., 

Bedford, A., Grams, P.E., and Ross, R.P., 2018, Sand 

classifications along the Colorado River in Grand Canyon 

derived from 2002, 2009, and 2013 high-resolution 

multispectral airborne imagery: U.S. Geological Survey 

data release, https://doi.org/10.5066/P99TN424.

USGS 

Data 

Project B.2: 

Computer code 

automated methods 

for substrate 

classification

Oct 

2018

Buscombe, D.D., Grams, P.E., and Kaplinski, M.A., 2018, 

Acoustic backscatter—Data & Python Code: U.S. 

Geological Survey data release, 

https://doi.org/10.5066/F7B56HM0.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[21]

Project C: Riparian Vegetation Monitoring and Research

Project Lead Joel Sankey

Principal 

Investigator(s) (PI)

Joel Sankey, USGS, GCMRC

Brad Butterfield, NAU

Emily Palmquist, USGS, GCMRC

Laura Durning, NAU

Email jsankey@usgs.gov

Telephone (928) 556-7289

SUMMARY 

Goals and Objectives FY 2019

Riparian vegetation is an important part of the Colorado River Ecosystem (CRe) in that it 

influences sediment deposition and retention, is key habitat for wildlife, can reduce camping 

area, adds beauty to the landscape, and creates shade and windbreaks. This project aims to 

monitor changes to riparian vegetation using field-collected data and digital imagery (C.1, C.2), 

develop predictive models of vegetation composition as it relates to hydrological regime (C.3), 

and provide monitoring protocols and decision support tools for active vegetation management 

(C.4).

Project Element C.1. Ground-Based Vegetation Monitoring

Regular monitoring of the native to nonnative plant species ratio, species richness, and overall 

location and types of vegetation that occur in the CRe is the best way to assess whether the 

resource goals for riparian vegetation are being met. There are more than 300 different riparian 

plant species in the CRe that range from annual species that are only a few centimeters tall to 

hundred-year-old trees over 20 m tall. Thus, riparian vegetation in the CRe is layered and 

complex and it is best practice to monitor on both annual and decadal-scale time scales to 

observe rapid changes such as shifts in wetland communities, as well as slower changes such as 

tree growth and mortality. An example of slower change is impacts of the herbivorous tamarisk 

beetle that are born out over many growing seasons. It is also important to sample at multiple 

spatial scales and geographic extents and to monitor locations along the entire length of the 

corridor since riparian vegetation communities change with distance downstream (Palmquist 

and others, 2018a). The different floristic communities located along the river may not respond 

similarly to dam operations. For example, conclusions based on data from Marble Canyon 

cannot be applied to western Grand Canyon (Palmquist and others, 2018a). 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[22]

In this project element of the FY 2018-20 workplan, we conduct annual ground-based 

vegetation monitoring to address the following objectives:

C.1.1. Annually sample and summarize the status (composition and cover) of native and 

nonnative vascular plant species within the riparian zone of the Colorado River from GCD 

and to 240 river miles downstream of Lees Ferry;

C.1.2. At 5-year intervals, assess change in vegetation composition and cover in the riparian 

zone, as related to geomorphic setting and dam operations, particularly flow regime;

C.1.3. Use available data to assess the required frequency for ground-based monitoring (i.e., 

power analysis);

C.1.4. Collect data in a manner that can be used by multiple stakeholders and is compatible 

with the basin-wide monitoring programs overseen by the NPS’s Northern Colorado 

Plateau Network Inventory and Monitoring program.

Riparian vegetation monitoring data was collected between August 5 and October 21, 2019 and 

included sites between river miles -15.5 and 240. Data were collected at a total of 103 

randomly selected sites and 42 long-term monitoring sites (NAU sandbar monitoring sites). 

These data are currently being entered and error checked. Data from the previous five years 

are being analyzed for patterns and trends (Figure 1). This analysis is currently being prepared 

as a status and trends report (Butterfield and others, in prep).

Figure 1. Percent foliar cover for six plant growth forms on annually surveyed sandbars by sample year. Median is indicated by 

the horizontal bar, the 25th and 75th percentiles are indicated by the box, whiskers extend to the most extreme data point that is 

not more than 1.5x the interquartile range, dots show outliers (Butterfield and others, in prep).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[23]

A comparison of riparian vegetation sampling methods was published in River Research and 

Applications (Palmquist and others, 2019). This method comparison assessed the strengths and 

weaknesses of the two main methods for sampling vegetation, ocular cover estimates and linepoint intercept. This comparison was conducted in Glen Canyon below Glen Canyon Dam 

specifically to determine how these methods perform in the complex, multilayered vegetation 

along the Colorado River. This comparison informed the sampling methods used in this 

program’s long-term monitoring protocol (Palmquist and others, 2018b). This document is 

available at https://doi.org/10.1002/rra.3440.

The database that was developed to manage all current monitoring data following the 

published monitoring protocol (Palmquist and others, 2018b) is fully functional and in 

operation. We are currently extending its abilities to serve data to multiple outlets.

We are working toward assessing the required frequency for ground-based monitoring by 

determining the best methods for data analysis given the vegetation data structure and 

monitoring goals. Recently developed Bayesian models developed for the National Park Service 

Inventory & Monitoring program (Irvine and others, 2019) are being explored for their utility 

and practicability.

We continue to collaborate with the National Park Service’s Northern Colorado Plateau 

Network Inventory and Monitoring – Big Rivers monitoring program. This collaboration allows 

us to maintain similar sampling methods and share ideas across the entire Colorado River Basin.

Project Element C.2. Imagery-based riparian vegetation monitoring at the landscape scale

In work completed prior to this FY 2018-20 workplan, landscape-scale remote sensing of 

riparian vegetation has been successfully used by GCMRC scientists to investigate several 

important contemporary environmental issues related to dam operations in the CRe. 

Specifically, we have: 1) quantified long-term changes in total riparian vegetation related to 

dam release patterns (discharge from the dam) and regional climate within specific reaches of 

the CRe (Sankey and others, 2015a), 2) classified and mapped the composition of riparian 

vegetation of the CRe (Durning and others, 2018; Sankey and others, 2015b; Ralston and 

others, 2008), and 3) mapped nonnative invasive tamarisk vegetation impacted by the 

introduced tamarisk beetle using 2009 and 2013 imagery from Glen Canyon Dam to Lake Mead 

and 2013 airborne lidar (Sankey and others, 2016; Bedford and others, 2017). In the first year 

(FY 2018) of the current workplan (FY 2018-20), we finalized several additional remote sensing 

derived datasets and publications on the riparian zone of the Colorado River in Grand Canyon 

(Bedford and others, 2018; Kasprak and others, 2018; Sankey and others, 2018). 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[24]

In this project element of the FY 2018-20 workplan, we are leveraging those datasets and 

successful applications of landscape-scale remote sensing of riparian vegetation to address the 

following research and monitoring objectives:

C.2.1. Analyze mapped species and associations to determine how the composition of woody 

riparian vegetation varies spatially throughout the entire river corridor and how species 

have changed through time as captured in digital imagery;

C.2.2. Quantify where, and to what degree, the combination of riparian vegetation 

encroachment and flow regime changes have altered bare sand area, and map turnover 

between riparian vegetation and bare sand due to erosion, deposition, establishment, 

and mortality;

C.2.3. Detect where tamarisk beetle herbivory events and tamarisk mortality have occurred 

since 2013.

Below we report on progress made during FY 2019 to address each of the research and 

monitoring objectives. With respect to objective C.2.1, in FY 2019 we finalized our map 

(Durning and others, 2018; see Figure 2 for an example) of riparian vegetation by species from 

Glen Canyon Dam to Lake Mead based on the 2013 overflight imagery (Durning and others, 

2016) and published this as a USGS data release (Durning and others, 2018). 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[25]

Figure 2. Example from the map of 2013 vegetation species classification by Durning and others (2018), with photos of 

dominant species. The map extends from Glen Canyon Dam to Lake Mead and is the highest resolution and most current map of 

riparian vegetation for the Colorado River ecosystem. The area displayed is river-right below Saddle Canyon (river kilometers 

from Lees Ferry, 77.6). Plant species codes are as follows: TAMRAM (Tamarix ramosissima x chinensis), ACAGRE (Senegalia 

greggii), PROGLA (Prosopis glandulosa), PLUSER (Pluchea sericea), PHRAUS (Phragmites australis), SALEXI (Salix exigua), 

BACC sp. (Baccharis sp.), BRILON (Brickellia longifolia), CAREX (Carex spp.), CELRET (Celtis laevigata), CEROCC (Cercis 

orbiculata), Sparse Veg (sparse areas of vegetation with limited or no training data), Shadow (vegetation in or created shadows), 

Sparse Grass (sparse areas of grass vegetation).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[26]

With respect to objective C.2.2, in 2018 we published our map of unvegetated, bare sand 

(Sankey and others, 2018) in the riparian zone from Glen Canyon Dam to Lake Mead also based 

on the 2013 overflight imagery (Durning and others, 2016). In FY 2019 we analyzed the Durning 

and others (2018) and Sankey and others (2018) datasets to address the questions posed by 

objectives C.2.1 and C.2.2. We have three different outlets or deliverables for the results of

these analyses. 

First, we delivered a talk at the Fall 2018 Meeting of the American Geophysical Union titled 

“Flow Alteration, River Valley Morphology, and the Influence of Glen Canyon Dam on Sediment 

Availability along the Colorado River in Grand Canyon” in December 2018 which covered the 

preliminary results of our work on C.2.2 on the interactions between riparian vegetation and 

bare sand for different geomorphic settings and hydrologic zones of the riparian area of the 

river. Second, during FY 2019 those preliminary results were further developed into a peerreviewed journal article that examines the historic dynamics and future trajectory of riparian 

vegetation and bare unvegetated sand along the Colorado River in Grand Canyon. We originally 

intended to publish this work as a short technical paper in the proceedings of the Federal 

Interagency Sedimentation and Hydrologic Modeling Conference convened in June, 2019. 

However, we instead decided to develop the study into a full research article that we will

submit to a peer-reviewed journal in FY 2020. Third, we have an additional manuscript in 

preparation which we plan to submit to a peer-reviewed journal in FY 2020 with a working title 

“A landscape scale evaluation of the Grand Canyon corridor’s riparian vegetation composition 

and encroachment using remotely sensed imagery”. 

The report details our work on objectives C.2.1 and C.2.2 using the Durning and others (2018) 

and Sankey and others (2018) datasets to answer these questions:

• What vegetation species occur and at what proportions within the different geomorphic 

units and hydrologic zones of the riparian area? (see Figure 3);

• What riparian species are most responsible for riparian vegetation encroachment onto 

bare sand? (see Figure 4);

• What riparian species are most commonly subjected to burial by river sand? (see Figure 

4).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[27]

Figure 3. Riparian species composition from Lees Ferry to Diamond Creek based on Durning and others (2018) analysis of the 

May 2013 aerial overflight imagery. The top panel shows composition by hydrologic flow zone. The bottom panel shows 

composition for aggregated geomorphic units. Preliminary results from a manuscript in preparation; please do not cite.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[28]

Figure 4. Species composition for three different modeled hydrologic zones on sandbars and other geomorphic surfaces where 

vegetation occurred in the 2002 overflight imagery, that was subsequently buried by Colorado River sand in the 2009 overflight 

imagery, and then riparian vegetation re-emerged and encroached as of the 2013 overflight imagery. The analysis was 

conducted from Lees Ferry to Diamond Creek using the data of Durning and others (2018). Preliminary results from a manuscript

in preparation; please do not cite. 

With respect to objective C.2.3, in 2017 and 2018 we published a map dataset (Bedford and 

others, 2017) and a manuscript (Bedford and others, 2018) describing tamarisk beetle impacts 

to tamarisk vegetation in the riparian zone of the river from Glen Canyon Dam to Lake Mead 

based on overflight remote sensing imagery acquired in 2009 and 2013. Those products were 

both final deliverables of the FY 2015-17 workplan. In FY 2018, we began using those datasets 

in conjunction with analysis of new, more recent satellite imagery acquired since 2013 to detect 

where tamarisk beetle herbivory events and tamarisk mortality have occurred. In FY 2019, we 

delivered two conference presentations on this work. The final deliverable associated with this 

work is planned for the last year of the FY 2018-20 workplan, and thus we will provide more 

information about this work as it progresses in future annual reports.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[29]

Figure 5. Deposition and erosion of sandbars as a function of hydrological regime (panels a-c), plant morphological guild (xaxis) and geomorphic position (symbols). 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[30]

Project Element C.3. Vegetation Responses to LTEMP Flow Scenarios

Predictive models of riparian vegetation change in response to Glen Canyon Dam Long-Term 

Experimental and Management Plan (LTEMP) Environmental Impact Statement (EIS) flow 

scenarios can inform stakeholders about the potential influences of daily flows and alternative 

flows outlined in the LTEMP Record of Decision (ROD; e.g., trout management flows, spring high

flow events, bug flows, equalization flows) on this resource of concern. This element will utilize 

existing vegetation data (from Elements C.1 and C.2) and flow data integrated with flowresponse vegetation guilds to examine the influence of flow scenarios on species distributions 

and potential community change. The modeling done for the LTEMP EIS identified likely 

outcomes for plant community states, but at a basic level of presence or absence and 

expansion or contraction. The new modeling approaches provide more detail, potentially about 

specific species of interest to stakeholders, and will result in a better understanding of how 

dam operations change vegetation. In FY 2018 we published initial models that identified 

interactive effects of climate and flow regime on vegetation composition (Butterfield and 

others, 2018). These models were further applied to projections of changes in bare sand area 

throughout the canyon (see Element C.2 above).

In FY 2019 we have developed two new lines of inquiry that will improve our predictive models 

based on: 

1. An understanding of vegetation feedbacks on sand deposition and erosion, and

2. Extending vegetation habitat prediction beyond the observed hydrological regime 

within the CRe and improve predictions of species sensitivity to hydrological and 

climatic variability. 

To this first objective, we have submitted a manuscript to River Research and Applications 

(Butterfield and others, in review) titled “Associations between riparian plant morphological 

guilds and fluvial sediment dynamics along the regulated Colorado River in Grand Canyon.” 

This work merges the long-term sandbar monitoring digital elevation models with the 2013 

vegetation classifications from the overflight to identify associations between plant effect guilds

and changes in elevation, providing estimates of net deposition or erosion over the period from 

2013-2018 that may be attributed to different plant groups. We found significant associations 

between vegetation and sandbar elevation change, and that these associations were very 

context-specific (Fig. 5). Specifically, there are strong interactions between hydrological regime, 

morphological guild, and geomorphic position, indicating that vegetation effects on sand 

dynamics are highly context-dependent but predictable. Low-statured rhizomatous and 

herbaceous species were highly effective at capturing sediment in the high velocity geomorphic 

settings, whereas tall herbs and large shrubs were more effective at capturing sediment in lowvelocity geomorphic settings. These results provide clear predictions about the role of 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[31]

vegetation in stabilizing sand, and which species/groups could be manipulated through direct 

vegetation management to achieve specific sand resource objectives. Furthermore, these 

feedbacks will be integrated into the next set of vegetation models to identify how successional 

processes (directional shifts from one type of vegetation to another over time) are likely to 

occur over time as plants continue to modify their local environment, and hence the 

hydrological conditions they experience.

The second objective of improving CRe vegetation predictions through use of a broader set of 

hydrological and climatic data is being achieved through integration of CRe and widespread 

data sources. The very narrow range of temporal variability in flow regime and climate for 

which we have detailed vegetation data in the CRe necessitates information on the same and 

similar species from other river systems. As a first step, we have developed a workflow for 

determining species hydrological and climatic niches using the National Hydrography Dataset 

Plus v.2 (NHDPlus). 

The novel workflow that we have developed in the R statistical and geospatial language extracts 

monthly average river flow and velocity data from NHDPlus associated with species occurrence 

records in the Southwest Environmental Information Network. This is a novel integration and 

use of these existing datasets, so as a first step to assess the utility and validity of this approach, 

we have conducted an initial study of willow species’ hydrological and climatic niches including 

two important CRe species, coyote willow (Salix exigua) and Gooding’s willow (Salix gooddingii) 

(Fig. 6). Willows were chosen for this initial analysis because they represent a very diverse 

genus that has been well-documented in terms of where they occur, and because many willows 

are riparian obligates. Our initial results indicate that this method is quite valid, based on a 

strong concordance between the estimates of species’ hydrological niches and knowledge of 

their ecology (Fig. 6). 

These results confirm expectations that riparian species should occur more closely to streams 

than by chance, supporting our use of this geospatial approach. The middle panel of Fig. 6 

demonstrates novel and important tradeoffs between willow species’ temperature and riparian 

obligation niches, further informed by evolutionary relationships (phylogeny on the right). 

These kinds of data will help us to understand linked hydrological and climatic sensitivities of 

riparian vegetation in the CRe, providing a wider range of predictive ability under alternative 

flow and climate scenarios. A manuscript is in preparation. The next iteration of this modeling 

approach will be to develop range-wide models of all the common CRe riparian plant species to 

understand where they lie within their broader realized hydrological and climate niches. These 

models will greatly improve our ability to predict species’ responses to on-going climate 

change, as well as to alternative flow scenarios, in ways that are impossible based on the 

narrow range of environmental variability in our empirical CRe datasets.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[32]

Figure 6. Preliminary results testing validity of workflow integrating west-wide hydrological, climate and species occurrence 

data to predict vegetation responses to hydrological and climate variability. The left panel shows the distribution of willow

occurrences with respect to distance from streams, compared to a random background sample. The middle panel shows 

relationships between temperature (MAT PIC) and hydrological niches (Distance from Stream PIC). The right panel shows the 

phylogenetic relationships among willow species.

To support these statistical models which infer species’ responses from correlations, we 

conducted a pilot experiment on physiological responses of arrowweed (Pluchea sericea) to 

flooding. The purpose of this experiment was to better understand the mechanisms of plant 

responses to dam operations under controlled conditions. Since field monitoring is limited by 

accessibility and the observed flow regime, we were interested in testing hypotheses in a 

greenhouse for a wider range of inundation depths and durations. We chose arrowweed for the 

pilot experiment, since it is a species of management interest. Cuttings collected from the along 

the Colorado River in Grand Canyon were flooded at different depths for 3 months over the 

summer of 2019. Data on growth, photosynthesis, rooting structure, and leaf traits were 

collected throughout and at the end of the study. These data are currently being processed. If 

this pilot study proves useful for understanding how plant species of interest respond to flow 

conditions, we will pursue options to continue these types of experiments with additional 

species and treatment conditions. 

All of the above results will be presented at the January 2020 Annual Reporting Meeting. 

Results will be presented in the context of decision-support tool development based on 

exogenous (flow regime, climate and vegetation management) and endogenous (e.g. biotic 

feedbacks on sand) processes known to affect vegetation condition. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[33]

Project Element C.4. Vegetation Management Decision Support

GCMRC partners with NPS and Native American Tribes on the LTEMP Riparian Vegetation 

Mitigation Project C.7 Experimental Vegetation Treatment. GCMRC’s roles and responsibilities 

in the project are: 

• Project partners and scientific support

• Provide input to NPS and Tribal partners on project design, site selection, methods for 

implementation and monitoring

• Provide scientific support via monitoring and/or research to evaluate vegetation 

management treatment outcomes, effectiveness, and success

• Provide objective advice on project efficiency and adaptive management

• Help manage project data while respecting Tribal data sensitivity 

• Attend and participate in meetings.

In FY 2019, GCMRC scientists, under the guidance of element C.4 and Project D, helped to 

design pilot experimental vegetation management treatments that were implemented by the 

National Park Service during a field campaign via river trip in April 2019. GCMRC’s efforts in 

experimental vegetation removal treatments on campsites, sandbars, and associated 

archaeological sites are described in detail in the Project D annual report in this document and 

are not discussed further here.

In cooperation with the NPS, GCMRC scientists have conducted an assessment of genetic 

structure and differentiation of cottonwood (Populus fremontii), Goodding’s willow (Salix 

gooddingii), coyote willow (Salix exigua), and honey mesquite (Prosopis glandulosa) in the 

Grand Canyon region (laboratory work funded by Grand Canyon National Park). The results of 

this work are anticipated to inform the development of genetically appropriate planting 

materials for the LTEMP experimental vegetation management treatments. These analyses 

indicate that cottonwoods are genetically different across the Grand Canyon region, genetic 

differences are related to geographic patterns, and populations within Grand Canyon are very 

different than those outside of Grand Canyon. The other three species are less genetically 

different across Grand Canyon, but Goodding’s willow exhibits some notable geographic 

differences. Coyote willow and honey mesquite, both common along the Colorado River, are 

characterized by extensive gene flow throughout the region. These results were presented at 

two regional conferences, the 2019 Riparian Restoration Conference hosted by River’s Edge 

West and the 15th Biennial Conference of Science & Management on the Colorado Plateau & 

Southwest Region. A manuscript is in preparation with a working title of, “Genetic structure and 

gene flow in woody riparian plants is mediated by geographic patterns.”
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[34]

REFERENCES

Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L.E., and Ralston, B.E., 2017, Remote sensing 

derived maps of tamarisk (2009) and beetle impacts (2013) along 412 km of the Colorado River 

in the Grand Canyon, Arizona: U.S. Geological Survey data release, 

https://doi.org/10.5066/F72B8X71.

Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L.E., and Ralston, B.E., 2018, Remote sensing of 

tamarisk beetle (Diorhabda carinulata) impacts along 412 km of the Colorado River in the 

Grand Canyon, Arizona, USA: Ecological Indicators, v. 89, p. 365-375, 

https://doi.org/10.1016/j.ecolind.2018.02.026.

Butterfield, B.J., Grams, P.E., Durning, L.E., Hazel, J.E., Jr., Palmquist, E.C., Ralston, B.E., and 

Sankey, J.B., in review, Associations between riparian plant morphological guilds and fluvial 

sediment dynamics along the regulated Colorado River in Grand Canyon: River Research and 

Applications.

Butterfield, B.J., Palmquist, E.C., and Ralston, B.E., 2018, Hydrological regime and climate 

interactively shape riparian vegetation composition along the Colorado River, Grand Canyon: 

Applied Vegetation Science, v. 21, no. 4, p. 572-583, https://doi.org/10.1111/avsc.12390.

Butterfield, B.J., Palmquist, E.C., and Ralston, B.E., in prep, Five-year status and trends of 

riparian vegetation in Glen and Grand Canyons downstream of Glen Canyon Dam: U.S. 

Geological Survey Open-File Report.

Durning, L.E., Sankey, J.B., Bedford, A., and Sankey, T.T., 2018, Riparian species vegetation 

classification data for the Colorado River within Grand Canyon derived from 2013 airborne 

imagery: U.S. Geological Survey data release, https://doi.org/10.5066/P9OUB1RS.

Durning, L.E., Sankey, J.B., Chain, G.R., and Sankey, J.B., 2017a, Water classification of the 

Colorado River corridor, Grand Canyon, Arizona, 2013—Data: U.S. Geological Survey data 

release, https://doi.org/10.5066/F7PZ5799.

Durning, L.E., Sankey, J.B., Chain, G.R., and Sankey, T.T., 2017b, Riparian vegetation 

classification of the Colorado River corridor, Grand Canyon, Arizona, 2013—Data: U.S. 

Geological Survey data release, https://doi.org/10.5066/F7K64GJF.

Durning, L.E., Sankey, J.B., Davis, P.A., and Sankey, T.T., 2016, Four-band image mosaic of the 

Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 

2013 airborne image acquisition: U.S. Geological Survey Data Series 1027, 

https://doi.org/10.3133/ds1027.

Irvine, K.M., Wright, W.J., Shanahan, E.K., and Rodhouse, T.J., 2019, Cohesive framework for 

modelling plant cover class data: Methods in Ecology and Evolution, v. 10, no. 10, p. 1749-1760, 

https://doi.org/10.1111/2041-210X.13262.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[35]

Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., East, A.E., and Grams, P.E., 2018, Quantifying 

and forecasting changes in the areal extent of river valley sediment in response to altered 

hydrology and land cover: Progress in Physical Geography: Earth and Environment, v. 42, no. 6, 

p. 739-764, https://doi.org/10.1177/0309133318795846.

Palmquist, E.C., Ralston, B.E., Merritt, D.M., and Shafroth, P.B., 2018a, Landscape-scale 

processes influence riparian plant composition along a regulated river: Journal of Arid 

Environments, v. 148, p. 54-64, https://doi.org/10.1016/j.jaridenv.2017.10.001.

Palmquist, E.C., Ralston, B.E., Sarr, D.A., and Johnson, T.C., 2018b, Monitoring riparianvegetation composition and cover along the Colorado River downstream of Glen Canyon Dam, 

Arizona: U.S. Geological Survey Techniques and Methods, book 2, chap. A14, 65 p., 

https://doi.org/10.3133/tm2A14.

Palmquist, E.C., Sterner, S.A., and Ralston, B.E., 2019, A comparison of riparian vegetation 

sampling methods along a large, regulated river: River Research and Applications, v. 35, no. 6, 

p. 759-767, https://doi.org/10.1002/rra.3440.

Ralston, B.E., Davis, P.A., Weber, R.M., and Rundall, J.M., 2008, A vegetation database for the 

Colorado River ecosystem from Glen Canyon Dam to the western boundary of Grand Canyon 

National Park, Arizona: U.S. Geological Survey Open-File Report 2008-1216, 37 p., 

https://pubs.usgs.gov/of/2008/1216/.

Sankey, J.B., Chain, G.R., Solazzo, D., Durning, L.E., Bedford, A., Grams, P.E., and Ross, R.P., 

2018, Sand classifications along the Colorado River in Grand Canyon derived from 2002, 2009, 

and 2013 high-resolution multispectral airborne imagery: U.S. Geological Survey data release, 

https://doi.org/10.5066/P99TN424.

Sankey, J.B., Ralston, B.E., Grams, P.E., Schmidt, J.C., and Cagney, L.E., 2015a, Riparian 

vegetation, Colorado River, and climate—Five decades of spatiotemporal dynamics in the 

Grand Canyon with river regulation: Journal of Geophysical Research—Biogeosciences, v. 120, 

no. 8, p. 1532-1547, https://doi.org/10.1002/2015JG002991.

Sankey, J.B., Ralston, B.E., Grams, P.E., Schmidt, J.C., and Cagney, L.E., 2015b, Riparian 

vegetation, Colorado River, and climate—Five decades of spatiotemporal dynamics in the 

Grand Canyon with river regulation—Data: U.S. Geological Survey data release, 

https://doi.org/10.5066/F7J67F0P.

Sankey, T.T., Sankey, J.B., Horne, R., and Bedford, A., 2016, Remote sensing of tamarisk 

biomass, insect herbivory, and defoliation—Novel methods in the Grand Canyon region, 

Arizona: Photogrammetric Engineering and Remote Sensing, v. 82, no. 8, p. 645-652, 

https://doi.org/10.14358/PERS.82.8.645.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[36]

U.S. Department of Interior, 2016, Record of Decision for the Glen Canyon Dam Long-Term 

Experimental and Management Plan final Environmental Impact Statement (LTEMP ROD): Salt 

Lake City, Utah, U.S. Department of the Interior, Bureau of Reclamation, Upper Colorado 

Region, National Park Service, Intermountain Region, 196 p., 

http://ltempeis.anl.gov/documents/docs/LTEMP_ROD.pdf.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Hydrological regime and 

climate interactively 

shape riparian vegetation 

composition along the 

Colorado River, Grand 

Canyon

July 

2018

Butterfield, B.J., Palmquist, E.C., and Ralston, B.E., 

2018, Hydrological regime and climate interactively 

shape riparian vegetation composition along the 

Colorado River, Grand Canyon—poster, at Natural 

Ecosystems as Benchmarks for Vegetation Science: 

Bozeman, Mont., July 22-27, 2018, International 

Association of Vegetation Scientists 61st Annual 

Symposium.

Presentation

Flow Alteration, River 

Valley Morphology, and 

the Influence of Glen 

Canyon Dam on Sediment 

Availability along the 

Colorado River in Grand 

Canyon

Dec 

2018

Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., 

Durning, L.E., East, A.E., and Grams, P., 2018, Flow 

alteration, river valley morphology, and the 

influence of Glen Canyon Dam on sediment 

availability along the Colorado River in Grand 

Canyon—presentation: Washington, D.C., Dec 10-

14, 2018, American Geophysical Union Fall 

Meeting.

Presentation

Genetic structure and 

gene flow in woody 

riparian plants: 

Implications for 

restoration in the Grand 

Canyon

Feb 

2019

Palmquist, E.C., Allan, G.A., Ogle, K., Whitham, T., 

Butterfield, B., Shafroth, P., 2019, Genetic 

structure and gene flow in woody riparian plants—

Implications for restoration in the Grand Canyon—

presentation: Phoenix, Ariz. Feb. 5-7, 2019, 

RiversEdge West Riparian Restoration Conference.

Presentation

Remote sensing of 

tamarisk and tamarisk 

beetle (Diorhaba 

carinulata) impacts along 

the Colorado River in 

Grand Canyon National 

Park and Glen Canyon 

National Recreation Area

Feb 

2019

Sankey, T.T., Bedford, A., Sankey, J.B., Ralston, B., 

and Durning, L., Remote sensing of tamarisk and 

tamarisk beetle (Diorhaba carinulata) impacts 

along the Colorado River in Grand Canyon National 

Park and Glen Canyon National Recreation Area—

presentation: Phoenix, Arizona, Feb. 5-7, 2019, 

RiversEdge West Riparian Restoration Conference.

Presentation Effects of HFEs on 

sandbar vegetation

March

2019

Butterfield, B.J., Sankey, J.B., Palmquist, E.C., 

Durning, L., 2019, Effects of HFEs on sandbar 

vegetation, Grand Canyon, Arizona—presentation: 

Phoenix, AZ., March 12, 2019, Annual Reporting 

Meeting to the Stakeholders of the Glen Canyon 

Dam Adaptive Management Program.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[37]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation Riparian vegetation 

monitoring and research

March 

2019

Butterfield, B.J., Sankey, J.B., Palmquist, E.C., 

Durning, L., 2019, Riparian vegetation monitoring 

and research, Grand Canyon, Arizona—

presentation: Phoenix, Ariz., March 12, 2019,

Annual Reporting Meeting to the Stakeholders of 

the Glen Canyon Dam Adaptive Management 

Program.

Presentation

Landscape scale riparian 

corridor analysis using 

2013 remotely sensed 

airborne data, Grand 

Canyon, Arizona

March 

2019

Durning, L., Sankey, J.B., 2019, Landscape scale 

riparian corridor analysis using 2013 remotely 

sensed airborne data, Grand Canyon, Arizona—

presentation: Phoenix, Ariz., March 12, 2019, 

Annual Reporting Meeting to the Stakeholders of 

the Glen Canyon Dam Adaptive Management 

Program.

Presentation

Remote sensing of 

tamarisk beetle 

(Diorhabda carinulata) 

impacts along 412 km of 

the Colorado River in the 

Grand Canyon, Arizona, 

USA

March 

2019

Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L., 

Ralston, B.E., 2019, Remote sensing of tamarisk 

beetle (Diorhabda carinulata) impacts along 

412 km of the Colorado River in the Grand Canyon, 

Arizona, USA—presentation: Phoenix, Ariz., March 

12, 2019, Annual Reporting Meeting to the 

Stakeholders of the Glen Canyon Dam Adaptive 

Management Program.

Presentation

Remote sensing of 

tamarisk beetle 

(Diorhabda carinulata) 

impacts along 412 km of 

the Colorado River in the 

Grand Canyon, Arizona, 

USA

Sept 

2019

Bedford, A., Sankey, T.T., Sankey, J.B., Durning, L., 

Ralston, B.E., 2019, Remote sensing of tamarisk 

beetle (Diorhabda carinulata) impacts along 

412 km of the Colorado River in the Grand Canyon, 

Arizona, USA—presentation: Flagstaff, Ariz., 

September 9-12, 2019, 15th Biennial Conference of 

Science & Management on the Colorado Plateau & 

Southwest Region. 

Presentation

Genetic structure and 

gene flow in woody 

riparian plants: A case 

study in the Grand 

Canyon

Sept 

2019

Palmquist, E.C., Allan, G.A., Ogle, K., Whitham, T., 

Butterfield, B., Shafroth, P., 2019, Genetic 

structure and gene flow in woody riparian plants—

A case study in the Grand Canyon—presentation: 

Flagstaff, Ariz., September 9-12, 2019, 15th 

Biennial Conference of Science & Management on 

the Colorado Plateau & Southwest Region.

Journal article

Landscape-scale 

processes influence 

riparian plant 

composition along a 

regulated river

Jan 

2018

Palmquist, E.C., Ralston, B.E., Merritt, D.M., and 

Shafroth, P.B., 2018, Landscape-scale processes 

influence riparian plant composition along a 

regulated river: Journal of Arid Environments, v. 

148, p. 54-64, 

https://doi.org/10.1016/j.jaridenv.2017.10.001.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[38]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Journal article

Hydrological regime and 

climate interactively 

shape riparian vegetation 

composition along the 

Colorado River, Grand 

Canyon

June

2018

Butterfield, B.J., Palmquist, E.C., and Ralston, B.E., 

2018, Hydrological regime and climate interactively 

shape riparian vegetation composition along the 

Colorado River, Grand Canyon: Applied Vegetation 

Science, v. 21, no. 4, p. 572-583, 

https://doi.org/10.1111/avsc.12390.

Journal article

A comparison of riparian 

vegetation sampling 

methods along a large, 

regulated river

May 

2019

Palmquist, E.C., Sterner, S.A., and Ralston, B.E., 

2019, A comparison of riparian vegetation 

sampling methods along a large, regulated river: 

River Research and Applications, v. 35, no. 6, p. 

759-767, https://doi.org/10.1002/rra.3440.

USGS 

Techniques 

and Methods

Report

Monitoring riparian 

vegetation composition 

and cover along the 

Colorado River 

downstream of Glen 

Canyon Dam

June 

2018

Palmquist, E.C., Ralston, B.E., Sarr, D.A., and 

Johnson, T.C., 2018, Monitoring riparianvegetation composition and cover along the 

Colorado River downstream of Glen Canyon Dam, 

Arizona: U.S. Geological Survey Techniques and 

Methods, book 2, chap. A14, 65 p., 

https://doi.org/10.3133/tm2A14.

USGS

Data

Riparian vegetation and 

environmental variables, 

Colorado River, 2014—

Data

Oct 

2017

Palmquist, E.C, 2017, Riparian vegetation and 

environmental variables, Colorado River, 2014—

Data: U.S. Geological Survey data release, 

https://doi.org/10.5066/F7V986X3.

USGS

Data

Climate, hydrology and 

riparian vegetation 

composition data, Grand 

Canyon, Arizona

July

2018

Palmquist, E.C., 2018, Climate, hydrology and 

riparian vegetation composition data, Grand 

Canyon, Arizona: U.S. Geological Survey data

release, https://doi.org/10.5066/F7DN4493.

USGS

Data

Riparian species 

vegetation classification 

data for the Colorado 

River within Grand 

Canyon derived from 

2013 airborne imagery: 

U.S. Geological Survey 

data release

Jan 

2019

Durning, L.E., Sankey, J.B., Bedford, A., and Sankey, 

T.T., 2018, Riparian species vegetation 

classification data for the Colorado River within 

Grand Canyon derived from 2013 airborne 

imagery: U.S. Geological Survey data release, 

https://doi.org/10.5066/P9OUB1RS.

 

 

 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[39]

Project D: Geomorphic Effects of Dam Operations and Vegetation 

Management for Archaeological Sites

Project Lead Joel Sankey

Principal 

Investigator(s) (PI)

Joel Sankey, USGS, GCMRC

Helen Fairley, USGS, GCMRC

Email jsankey@usgs.gov

Telephone (928) 556-7289

SUMMARY

Glen Canyon Dam (GCD) has reduced downstream sediment supply to the Colorado River by 

about 95% in the reach upstream of the Little Colorado River confluence and by about 85% 

downstream of the confluence (Topping and others, 2000). Operation of the dam for 

hydropower generation has additionally altered the flow regime of the river in Grand Canyon, 

largely eliminating pre-dam low flows (i.e., below 5,000 ft3/s) that historically exposed large 

areas of bare sand (U.S. Department of the Interior, 2016a; Kasprak and others, 2018). At the 

same time, the combination of elevated low flows coupled with the elimination of large, 

regularly-occurring spring floods in excess of 70,000 ft3/s has led to widespread riparian 

vegetation encroachment along the river, further reducing the extent of bare sand (U.S. 

Department of the Interior, 2016a; Sankey and others, 2015). Kasprak and others (2018) report 

that the areal coverage of bare sand has decreased by 45% since 1963 due to vegetation 

expansion and inundation by river flows. Kasprak and others (2018) forecast that the areal 

coverage of bare sand in the river corridor will decrease an additional 12% by 2036.

The changes in the flow regime, reductions in river sediment supply and bare sand, and the

proliferation of riparian vegetation have affected the condition and physical integrity of

archaeological sites and resulted in erosion of the upland landscape surface by reducing the

transfer (termed “connectivity”) of sediment from the active river channel (e.g., sandbars) to

terraces and other river sediment deposits in the adjoining landscape (U.S. Department of

Interior, 2016a; Draut, 2012; East and others, 2016; Kasprak and others, 2018; Sankey and 

others, 2018a,b). Many archaeological sites and other evidence of past human activity are now 

subject to accelerated degradation due to reductions in sediment connectivity under current 

dam operations and riparian vegetation expansion which are tied to regulated flow regimes 

(U.S. Department of the Interior, 2016a; East and others, 2016).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[40]

The GCD Long-Term Experimental and Management Plan Environmental Impact Statement 

(LTEMP EIS) predicts that conditions for achieving the goal of preservation for cultural 

resources, termed “preservation in place,” will be enhanced as a result of implementing the 

selected alternative (U.S. Department of Interior, 2016a). High-Flow Experiments (HFEs) are one 

component of the selected alternative that will be used to resupply sediment to sandbars in 

Marble and Grand Canyons, which in conjunction with targeted vegetation removal, is expected 

to resupply more sediment via wind transport to archaeological sites, depending on site-specific 

riparian vegetation and geomorphic conditions. However, HFEs have been shown to directly 

erode terraces that contain archaeological sites in Glen Canyon National Recreation Area 

(GLCA; East and others, 2016; U.S. Department of Interior, 2016a). HFEs have also been shown 

by Sankey and others (2018b) to rebuild or maintain sandbars that provide sand to resupply 

aeolian dunefields containing archaeological sites throughout Marble and Grand Canyons. 

Aeolian dunefields were resupplied with sand from HFE deposits in half of the flood-site 

instances monitored after the 2012, 2013, 2014, and 2016 HFEs (Sankey and others, 2018b). 

They also found evidence for cumulative effects of sediment resupply of dunefields when 

annual HFEs are conducted consistently in consecutive years (Sankey and others, 2018b).

This project quantifies the geomorphic effects of ongoing and experimental dam operations as

well as the geomorphic effects of riparian vegetation expansion and management, focusing on

effects of HFEs on the supply of sediment to cultural sites and terraces. The ongoing and 

experimental dam operations and vegetation management of interest are those that will be 

undertaken under the LTEMP Record of Decision (ROD; U.S. Department of the Interior, 2016b) 

through 2036. The data and analyses from this project will allow the GCDAMP to objectively 

evaluate whether and how these flow and non-flow actions directly affect cultural resources, 

vegetation, and sediment dynamics. It will also allow determination of how flow and non-flow 

actions will ultimately affect the long-term preservation of cultural resources and other

culturally-valued and ecologically important landscape elements located within the river 

corridor downstream of GCD.

There are two elements to this project:

D.1. Geomorphic Effects of Dam Operations and Vegetation Management

D.2. Cultural Resources Synthesis to Inform Historic Preservation Plan

Monitoring and other work completed in 2019 are described below for each project element.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[41]

Project Element D.1. Geomorphic Effects of Dam Operations and Vegetation Management

Summary of work completed in FY 2019

• Grand Canyon Monitoring and Research Center (GCMRC) Project D staff helped the 

National Park Service (NPS) design experimental vegetation removal treatments 

intended to increase the aeolian transport of Colorado River sediment, deposited by 

HFEs, to archaeological sites. The treatments focused on locations with coupled 

sandbars and archaeological sites that Grand Canyon NPS Archaeology staff monitor 

for visitor impacts and that GCMRC has specifically monitored for changes in 

geomorphic condition tied to dam-operations using lidar remote sensing and 

weather stations during the past decade. Grand Canyon staff implemented the 

proposed vegetation removal treatments at five sites during a field campaign via 

river trip conducted in April 2019. The work was carried out by NPS staff and tribal 

youth from the Ancestral Lands Conservation program. Dr. Sankey from GCMRC also 

participated in the trip to provide science support for the implementation of the 

vegetation removal treatments. GCMRC Project D staff subsequently conducted 

their annual field campaign via river trip (described in the next bullets below) 

immediately following the NPS trip in order to collect initial monitoring data for the 

vegetation removal treatments (Figure 1). Repeat monitoring in FY 2020 and later 

years will provide the data necessary to evaluate the outcome of the vegetation 

removal treatments (Figure 2).

• A field campaign to monitor changes in geomorphic condition tied to dam 

operations was conducted via river trip in May of 2019. Six archaeological sites were 

surveyed with lidar per the protocol described in the GCMRC plan for monitoring 

effects of geomorphic processes at archaeological sites in Grand and Glen Canyons. 

The monitoring plan was shared with stakeholders in 2016 during the 2015-17 

Triennial Work Plan (TWP), and again more recently with signatories of the 

Programmatic Agreement for Cultural Resources as part of the Historic Preservation 

Plan1. Five of the sites were those at which the NPS had conducted experimental 

vegetation removal treatments in April, 2019.

• Weather station data is important for interpreting monitoring data related to 

geomorphic effects of dam operations and vegetation management. Similar to past 

years, weather data were downloaded from six stations during field campaigns, one 

at Ferry Swale in Glen Canyon (river mile -11), one at Lees Ferry, and one at each of 

four Marble and Grand Canyon archaeological sites (e.g., Caster and others, 2014, 

 

1 The Programmatic Agreement for Cultural Resources is on file with the Bureau of Reclamation, Upper Colorado 

Region, Salt Lake City.
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2018; Sankey and others, 2018a,b). Stations collected measurements of rainfall, 

wind speed and direction, temperature, barometric pressure, and relative humidity 

at 4-minute timesteps. Several of the existing weather stations needed to be 

overhauled in 2019 to ensure data continuity. Weather station equipment was 

repaired and upgraded as necessary at existing stations, and a new weather station 

was installed at Soap Creek (river mile 10). Thus, a total of seven stations collected 

weather monitoring data during 2019 and those data will be retrieved during field 

campaigns in 2020.

• At three sites, stationary cameras took photographs up to four times per day to 

record information about the timing and nature of landscape change.

• All monitoring data acquired in 2019 were processed and archived at GCMRC. 

• A report summarizing archaeological site monitoring data acquired from 2010 

to2018 has been completed by project staff and is currently in external review with 

the NPS and USBR (U.S. Bureau of Reclamation). The report is titled “Terrestrial Lidar 

Monitoring of the Effects of Glen Canyon Dam Operations on the Geomorphic 

Condition of Archaeological Sites in Grand Canyon National Park 2010-2018.” It is 

anticipated that the report will be published in 2020 as a USGS Open-File Report 

once the review process is completed.

o The report summarizes baseline data collected at 23 archaeological sites. The 

report also summarizes the geomorphic changes that have been documented 

at five sites with two or more lidar monitoring episodes between 2010 and

2018.

o This report and the monitoring data contained therein will provide baseline 

data (see Figures 1 and 2 below) for evaluating the pilot experimental 

vegetation management treatments implemented by the National Park 

Service beginning in 2019 per the LTEMP EIS . The report contains baseline 

data acquired between 2010 and 2018 for four of the five pilot sites. 

o Some of these monitoring data also have been used by Sankey and others 

(2018b) to demonstrate how HFEs can rebuild or maintain sandbars that 

provide sand to aeolian dunefields containing archaeological sites 

throughout Marble and Grand Canyons. Aeolian dunefields were resupplied 

with sand from HFE deposits in half of the instances monitored after the 

2012, 2013, 2014, and 2016 HFEs (Sankey and others, 2018b). Sankey and 

others (2018b) found evidence for cumulative effects of sediment resupply of 

dunefields when annual HFEs were conducted consistently in consecutive 

years (Sankey and others, 2018b).
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Figure 1. Photos and lidar survey data showing the vegetation removed by NPS during the experimental vegetation 

management treatment near archaeological site AZ:C13:0321. The treatment at this and other sites is intended to increase 

sediment storage at the sites by enhancing aeolian transport of Colorado River HFE sand from sandbars to archaeological sites.

Vegetation removal at this location exposed an aeolian dune that is visible in the photos and lidar data. In the lidar data panels, 

the grey pixels are the sandy ground surface, and the colored pixels are vegetation. The vegetation pixel colors are scaled by 

plant canopy height, where cool colors are shorter plants and the warmer colors are taller plants.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Figure 2. Results from long-term monitoring of changes in sediment storage from lidar surveys at four of the five archaeological 

sites where experimental vegetation removal treatments were implemented in April 2019 by the NPS. Treatments are intended to 

increase sediment storage at the sites by enhancing aeolian transport of Colorado River HFE sand from sandbars to 

archaeological sites. Change detection from future monitoring in 2020 will provide the first set of post-vegetation management 

results with which to evaluate the effectiveness of vegetation removal treatments in comparison to the baseline data shown in 

this figure.

Project Element D.2. Cultural Resources Synthesis to Inform Historic Preservation Plan

In the 2018-2020 TWP, project element D.2 called for preparation of a report summarizing and 

evaluating past research and monitoring conducted under the 1994 Programmatic Agreement 

for Cultural Resources, followed by a more in-depth exploration of existing monitoring 

photographs collected by the Grand Canyon National Park (GRCA) cultural monitoring program 

since 1991. The purposes of the photographic archive evaluation were to determine whether 

the monitoring photographs were suitable for quantifying physical changes at archaeological 

sites over time and, if suitable, to analyze and quantify changes. This evaluation of GRCA’s 

cultural monitoring program photographic archives originally had been proposed by the Legacy 

Monitoring Data Review panel in 2007 (Kintigh and others, 2007).

The synthesis report was completed in September 2018 and has served its intended purpose of 

informing development of the Historic Preservation Plan (HPP), which was completed and 

adopted by signatories to the new (2017) Programmatic Agreement in November 2018. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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In June 2019, an evaluation of the GRCA photographic collection from the past ~20 years of 

cultural resource monitoring was initiated. After reviewing hundreds of photographs from a 

randomly-selected sample of archaeological sites, it became apparent that the monitoring 

photographs, while useful for documenting surficial changes at individual sites, were not well 

suited for systematically quantifying change. This conclusion was based on several observations 

and methodological considerations: 1) most of the photographs are low resolution “snap shots” 

taken with a 35mm analog camera under highly variable lighting conditions and are often of 

poor quality; 2) the amount of photographic coverage varies widely by site, with some sites 

having hundreds of photographs while others have only a few; generally, sites with the most 

coverage are those which receive high levels of visitation from river runners, which makes it 

challenging to segregate erosion and other damage caused by visitor use from impacts related 

to dam operations; 3) while many photographs depict the same features over multiple years, 

the photographic views of these features are taken from a wide variety of angles from year to 

year, making direct comparisons difficult; 4) changes in the monitoring protocols have resulted 

in uneven documentation of surface stability and change through time. With regard to factor 4 

specifically, after a decade of taking photographs during each monitoring visit regardless of 

whether or not changes in condition were observed, the GRCA archaeology staff changed their 

monitoring protocols in the late 1990s to only take photographs when a noticeable change was 

observed. What constituted a change worthy of photographing was not explicitly defined. 

Furthermore, because sites are monitored at varying and somewhat irregular intervals ranging 

between once every year to once every five years, it is not possible to determine when a 

change occurred or whether it occurred during a single moment in time or over a period of 

several years. All of these factors combined severely limits the utility of the existing monitoring 

photography collection for systematically analyzing or quantifying changes in site condition 

through time.

Since further analysis of the archaeological site monitoring photographs did not appear to be 

worthwhile, in FY 2019, project D.2 focused mainly on continuing to expand the photographic 

coverage of changes in riparian vegetation cover and open sand areas throughout the river 

corridor, with particular emphasis on documenting changes associated with specific Project D 

study sites (both lidar survey sites as well as vegetation removal sites). These photographs 

document changes in local environmental conditions related to the effects of regulated flows 

that have affected the current availability and redistribution of sediment in the river corridor. 

This work was accomplished through precisely matching existing historical images dating 

between 1889 through the early 1990s with replicate views of the same locations under current 

conditions (Figure 3). This work builds upon earlier photographic-matching efforts initiated in 

2015 during a previous phase of Project D (see Project 4 in the FY 2015-2017 TWP). During FY

2019, a total of 42 matched images were obtained during the May 2019 river trip, bringing the 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[46]

total number of matched historical images collected from the river corridor since 2015 to 

approximately 200. As in the past, the collection of the photo-matches was accomplished with 

the aid of two unpaid volunteers (Figure 4). We plan to continue this photo-matching effort for 

at least one more field season in FY 2020.

Figure 3. Photographic match of lidar study site near river mile 122. Top view taken by an unknown member of the Weeden 

campsite survey project in July, 1973 (Weeden and others, 1975). Bottom view by A. H. Fairley, May 2019. Note the large area 

of open sand in 1973 that is now largely overgrown by vegetation.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Figure 4. Volunteer photographer Alan Fairley (left) and USGS emeritus ecologist Michael Scott (right) match a 1923 

photograph taken by E.C. La Rue above Nankoweap Rapids. Photograph by Helen Fairley, May 2019. 

REFERENCES

Caster, J.J., Dealy, T.P., Andrews, T., Fairley, H., East, A., and Sankey, J.B., 2014, Meteorological 

data for selected sites along the Colorado River corridor, Arizona, 2011-13: U.S. Geological 

Survey Open-File Report 2014-1247, 56 p., https://doi.org/10.3133/ofr20141247.

Caster, J.J., Sankey, J.B., and Fairley, H., 2018, Meteorological data for selected sites along the 

Colorado River corridor, Arizona, 2014-2015: U.S. Geological Survey data release, 

https://doi.org/10.5066/F7DZ0771.

Draut, A.E., 2012, Effects of river regulation on aeolian landscapes, Colorado River, 

southwestern USA: Journal of Geophysical Research—Earth Surface, v. 117, no. F2, 

https://doi.org/10.1029/2011JF002329.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[48]

East, A.E., Collins, B.D., Sankey, J.B., Corbett, S.C., Fairley, H.C., and Caster, J.J., 2016, Conditions 

and processes affecting sand resources at archeological sites in the Colorado River corridor 

below Glen Canyon Dam, Arizona: U.S. Geological Survey Professional Paper 1825, 104 p., 

https://doi.org/10.3133/pp1825.

Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., East, A.E., and Grams, P.E., 2018, Quantifying 

and forecasting changes in the areal extent of river valley sediment in response to altered 

hydrology and land cover: Progress in Physical Geography: Earth and Environment, v. 42, no. 6, 

p. 739-764, https://doi.org/10.1177/0309133318795846.

Kintigh, K., Lipe, W., Altschul, J.H., and Urquhart, N.S., 2007, Legacy monitoring data review 

panel—unpublished report to the Grand Canyon Monitoring and Research Center: Legacy 

Monitoring Data Review Panel, 42 p. plus appendices, 

https://www.usbr.gov/uc/progact/amp/twg/2007-12-04-twg-meeting/Attach_10.pdf.

Sankey, J.B., Caster, J.J., Kasprak, A., and East, A.E., 2018a, The response of source-bordering 

aeolian dunefields to sediment-supply changes 2—Controlled floods of the Colorado River in 

Grand Canyon, Arizona, USA: Aeolian Research, v. 32, p. 154-169, 

https://doi.org/10.1016/j.aeolia.2018.02.004.

Sankey, J.B., Kasprak, A., Caster, J.J., East, A.E., and Fairley, H., 2018b, The response of sourcebordering aeolian dunefields to sediment-supply changes 1—Effects of wind variability and 

river-valley morphodynamics: Aeolian Research, v. 32, p. 228-245, 

https://doi.org/10.1016/j.aeolia.2018.02.005.

Sankey, J.B., Ralston, B.E., Grams, P.E., Schmidt, J.C., and Cagney, L.E., 2015, Riparian 

vegetation, Colorado River, and climate—Five decades of spatiotemporal dynamics in the 

Grand Canyon with river regulation: Journal of Geophysical Research—Biogeosciences, v. 120, 

no. 8, p. 1532-1547, https://doi.org/10.1002/2015JG002991.

Topping, D.J., Rubin, D.M., and Vierra, L.E., Jr., 2000, Colorado River sediment transport—1. 

Natural sediment supply limitation and the influence of the Glen Canyon Dam: Water Resources 

Research, v. 36, no. 2, p. 515-542, https://doi.org/10.1029/1999WR900285.

U.S. Department of Interior, 2016a, Glen Canyon Dam Long-term Experimental and 

Management Plan final Environmental Impact Statement (LTEMP FEIS): U.S. Department of the 

Interior, Bureau of Reclamation, Upper Colorado Region, National Park Service, Intermountain 

Region, online, http://ltempeis.anl.gov/documents/final-eis/.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[49]

U.S. Department of Interior, 2016b, Record of Decision for the Glen Canyon Dam Long-Term 

Experimental and Management Plan final Environmental Impact Statement (LTEMP ROD): Salt 

Lake City, Utah, U.S. Department of the Interior, Bureau of Reclamation, Upper Colorado 

Region, National Park Service, Intermountain Region, 196 p., 

http://ltempeis.anl.gov/documents/docs/LTEMP_ROD.pdf.

Weeden, H., Borden, F., Turner, B., Thompson, O.N., Strauss, C., and Johnson, R.R., 1975, Grand 

Canyon National park campsite inventory—unpublished Colorado River research report: 

National Park Service, submitted to Pennsylvania State University, contract no. CX 001-3-0061, 

72 p.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Process and progress in 

monitoring surficial changes 

to archaeological sites 

within Grand Canyon river 

corridor

March

2019

Caster, J, Sankey, J.B., Kasprak, A., Fairley, H., East, 

A., 2019, Process and progress in monitoring 

surficial changes to archaeological sites within 

Grand Canyon river corridor: Phoenix, Ariz., March 

12, 2019, Annual Reporting Meeting, Glen Canyon 

Dam Adaptive Management Program.

Presentation

The response of sourcebordering aeolian dunefields 

to the 2012-2016 High-Flow 

Experiments of the Colorado 

River in Grand Canyon

March

2019

Sankey, J.B., Caster, J, Kasprak, A., East, A., Fairley, 

H., 2019, The response of source-bordering 

aeolian dunefields to the 2012-2016 High-Flow 

Experiments of the Colorado River in Grand 

Canyon: Phoenix, Ariz., March 13, 2019, Annual 

Reporting Meeting, Glen Canyon Dam Adaptive 

Management Program—High-Flow Experiment 

Workshop.

Presentation

“Wind (and sand) in the 

willows”: Exploring the 

relationship between damregulated flows, sediment 

supply, vegetation 

encroachment, and 

archaeological site 

preservation in Glen and 

Grand Canyons, Arizona

March

2019

Fairley, H., Sankey, J., Caster, J., East, A., Kasprak, 

A., Collins, B., Corbett, S., 2019, “Wind (and sand) 

in the willows”—Exploring the relationship 

between dam-regulated flows, sediment supply, 

vegetation encroachment, and archaeological site 

preservation in Glen and Grand Canyons, 

Arizona—Oral presentation Marble Canyon, Ariz., 

March 29, 2019, Grand Canyon River Guides 

Training Seminar.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Understanding dam effects 

on downstream 

archaeological resources—

Lessons learned from three 

decades of research 

downstream from Glen 

Canyon Dam, Arizona

April

2019

Fairley, H.C., 2019, Understanding dam effects on 

downstream archaeological resources—Lessons 

learned from three decades of research 

downstream from Glen Canyon Dam, Arizona—

Oral presentation: Albuquerque, New Mex., April 

11, 2019, Society for American Archaeology 

Annual Meeting.

Presentation

Flow alteration, river valley 

morphology, and the 

influence of Glen Canyon 

Dam on sediment 

availability along the 

Colorado River in Grand 

Canyon

Dec

2019

Kasprak, A., Sankey, J.B., Buscombe, D., Durning, 

L., Caster, J., Grams, P., East, A., Butterfield, B., 

2019, Flow alteration, river valley morphology, 

and the influence of Glen Canyon Dam on 

sediment availability along the Colorado River in 

Grand Canyon: Washington, D.C., December 1-14, 

2018, AGU Meeting.

Presentation

Integrating lidar and SfM 

data from ground-based, 

unmanned (UAV) and 

manned aerial platforms to 

estimate sediment budgets 

for aeolian dunefields 

Dec

2019

Sankey, J.B., Kapsrak, A., Caster, J., Sankey, T., 

Andrews, T., Solazzo, D., 2018, Integrating lidar 

and SfM data from ground-based, unmanned 

(UAV) and manned aerial platforms to estimate 

sediment budgets for aeolian dunefields—

presentation: Washington, D.C., December 1-14, 

2018, AGU Meeting.

Journal 

article

The effects of topographic 

surveying technique and 

data resolution on the 

detection and interpretation 

of geomorphic change

FY 2019 

Kasprak, A., Bransky, N.D., Sankey, J.B., Caster, J., 

and Sankey, T.T., 2019, The effects of topographic 

surveying technique and data resolution on the 

detection and interpretation of geomorphic 

change: Geomorphology, v. 333, p. 1-15, 

https://doi.org/10.1016/j.geomorph.2019.02.020.

USGS

Fact 

Sheet

Managing sand along the 

Colorado River to protect 

cultural sites downstream of 

Glen Canyon Dam

FY 2019

Cook, T., East, A.E., Fairley, H., and Sankey, J.B., 

2019, Managing sand along the Colorado River to 

protect cultural sites downstream of Glen Canyon 

Dam: U.S. Geological Survey Fact Sheet 2019-

3054, 6 p., https://doi.org/10.3133/fs20193054.

USGS 

Data

River valley sediment 

connectivity data, Colorado 

River, Grand Canyon, 

Arizona: U.S. Geological 

Survey data release

FY 2019

Kasprak, A., Sankey, J.B., Buscombe, D.D., Caster, 

J., East, A.E, Grams, P.E, 2018, River valley 

sediment connectivity data, Colorado River, Grand 

Canyon, Arizona: U.S. Geological Survey data 

release, https://doi.org/10.5066/P9SX3MGY.
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Project E: Nutrients and Temperature as Ecosystem Drivers: 

Understanding Patterns, Establishing Links and Developing Predictive 

Tools for an Uncertain Future

SUMMARY

Overview

Temperature and nutrient dynamics can influence both community composition and metabolic 

rates across many different types of ecosystems (Allen and others, 2005; Brown and others, 

2004; Elser and others, 2003; Elser and others, 1996; Yvon-Durocher and others, 2012). Given 

the importance of nutrients and temperature as drivers of the aquatic ecosystem, it is 

important to understand their spatio-temporal patterns. The primary goals of this project are 

to: 1) identify processes that drive spatial and temporal variation in nutrients and temperature 

within the Colorado River Ecosystem (CRe), and 2) establish quantitative and mechanistic links 

among these ecosystem drivers, primary production, and higher trophic levels. Parallel work in 

Lake Powell that aims to identify the controls on nutrient concentrations in the Glen Canyon 

Dam outflow is ongoing with funding from the Bureau of Reclamation (see Appendix 1). 

During FY 2019, we improved the water temperature model currently used to make predictions 

in the CRe that will allow for a more accurate characterization of thermal conditions present 

now and in the future that will shape the distribution and abundance of native and nonnative 

fishes throughout Grand Canyon. We also used a combination of historical data and new 

sampling to characterize the potential role of both dam management and Colorado River 

tributaries in influencing spatio-temporal patterns in mainstem nutrient availability. While longterm nutrient monitoring at Lees Ferry (river mile (RM) 0) shows a strong correspondence 

between nutrient availability in the reservoir outflow and in the Lees Ferry reach (Vernieu, 

2009), the degree to which nutrient availability might change with outflow discharge and during 

an HFE is not well known. In addition, watershed disturbances such as wildfires have been 

linked to increased stream phosphorus (P) availability in other ecosystems (Emelko and others, 

2016), but the potential for tributary fires to affect the CRe is not known. Finally, while 

Project Lead Charles B. Yackulic

Principal 

Investigator(s) (PI)

Charles B. Yackulic, USGS, GCMRC

Bridget Deemer, USGS, GCMRC

Kimberly Dibble, USGS, GCMRC

Michael Yard, USGS, GCMRC

Theodore Kennedy, USGS, GCMRC

David Ward, USGS, GCMRC

Email cyackulic@usgs.gov

Telephone 928-556-7379
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baseflow P concentrations in many tributaries to the Grand Canyon are not high enough to 

significantly affect nutrient budgets, preliminary sampling in FY 2018 suggests that storm-based 

P inputs from the Paria River may contribute significantly to the CRe P budget. During FY 2019

we expanded our capacity to measure P during storms in the Paria River. We also used aquatic 

insect light trap samples collected before and after a major fire in the Shinumo watershed to 

look for an increased P concentration in the CRe food base (measuring the total phosphorus 

content of Diptera). Finally, we sampled for several P species during the fall 2018 HFE and 

during the summer 2019 bug flows to look at variation in P concentrations coming from the 

Glen Canyon Dam outflow. Key findings were that HFEs can elevate downstream soluble 

reactive phosphorus (SRP) concentrations, the most bioavailable form of P. In addition, we 

report significant increase in the total phosphorus (TP) content of adult midges across a 50-mile

reach of the Colorado river after the Galahad Fire in the Shinumo watershed, suggesting the 

capacity for a tributary fire to influence the P content of the CRe food base.

During FY 2019, we continued to make progress in developing and applying models of gross 

primary production (GPP) to understand river-wide patterns in GPP and link the base of the 

food web to drivers including light and nutrients. Initial analysis suggests that SRP exerts an 

important control on GPP all the way down to RM 60. In addition, adjusted weekend water 

releases due to bug flows had measurable effects on riverine GPP, but the direction and 

magnitude of this effect varied by site throughout the river. In FY 2018 the installation of 

artificial streams at the National Park Service water treatment facility in Lees Ferry failed due to 

an inability to control water temperature, challenging our ability to test hypotheses on how 

changes in water temperature and nutrient availability may affect primary production and 

aquatic biota in response to changes in Lake Powell elevation. However, we made significant 

progress in FY 2019 by conducting these experiments under a more controlled environment at 

the Rocky Mountain Research Laboratory in Flagstaff. From June-November 2019 we developed 

laboratory-based artificial streams using Colorado River water, substrate, algae, and New 

Zealand mud snails (Potamopyrgus antipodarum, hereafter “mud snails”) to determine the 

effect of 10°C, 15°C, and 20°C treatments on GPP and mud snail growth. Side experiments 

included investigating the effect of mud snail grazing on GPP under the three temperature 

treatments and investigating whether native fishes (humpback chub, roundtail chub, 

flannelmouth sucker) consume mud snails. In 2019 we continued the development of a semiautomated technique for classifying submersed aquatic vegetation from underwater imagery, 

providing a means for future monitoring of aquatic vegetation change in Glen Canyon. We also

established two permanent reaches with transects in Glen Canyon in June 2019 and took 

approximately 30,000 underwater images that will provide baseline information to assess

future aquatic vegetation change over time.
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While more progress was made in conceptually developing an ecosystem model in FY 2019 than 

in FY 2018, systematic underfunding across modeling projects (and in database entry) 

combined with several unplanned activities requested by stakeholders and managers, severely 

hampered progress in turning this conceptual model into a statistical model. Progress will 

continue to be slow so long as modeling projects remain underfunded and requests are made 

for work beyond that outlined in the approved workplan.

Project Element E.1. Temperature and Nutrients in the CRe – Patterns, Drivers, and Improved 

Predictions

Objectives:

E.1.1. Modify previous models for predicting CRe temperatures to reflect exponential (rather 

than linear) warming

E.1.2. Describe spatial and temporal patterns in riverine nutrient availability between Glen 

Canyon Dam and Diamond Creek (including an assessment of the relative importance of 

tributary nutrient inputs to river nutrient budgets), as well as potential processes driving 

these patterns.

Sub-element E.1.1.

Water temperature in the Colorado River in Grand Canyon is an important factor that 

influences the growth, reproduction, distribution, and abundance of native species including 

the endangered humpback chub. Predicting the response of humpback chub populations to 

Glen Canyon Dam management alternatives was a high priority in the Long-Term Experimental 

and Management Plan Environmental Impact Statement. Temperature predictions were 

generated using a linear warming model, but this model overestimates Colorado River 

temperatures by ~2°C in western Grand Canyon (Figure 1). To provide better predictions, we

modified the current linear model of water temperature (Walters and others, 2000; Wright and 

others, 2008) by changing the functional form to a saturating function and incorporating the 

effects of solar radiation (in addition to factors such as discharge, air temperature, and release 

temperature already present in previous model). The new model improved temperature 

predictions by decreasing residual error, with the largest prediction improvements in western 

Grand Canyon sites (Figure 1). We used this model to explore how changes in air temperature, 

discharge, and Lake Powell release temperatures may change water temperatures throughout 

the Grand Canyon.
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Figure 1. Comparison of residuals from the current model used for modeling water temperature in Grand Canyon (linear; 

Wright and others, 2009) relative to the new model we developed that includes an exponential decay in warming combined with 

the use of other data sources including solar radiation. The plot shows the residuals (predicted temperature (Tpredicted) minus 

observed temperature (Tobserved)) for the last two water temperature stations in Grand Canyon where linear model errors 

increase, Diamond Creek (RM 224) and Spencer Creek (RM 244).

Development of a refined water temperature model for Grand Canyon combined with a 

plethora of water temperature and discharge data already collected as part of the tailwater 

synthesis project from other reaches in the CRe (FY 2013-14 Work Plan, Project Element H.4; FY 

2015-17 Work Plan, Project Element 9.8) provided an opportunity to expand water 

temperature modeling to other river segments in the basin with minimal effort. The results 

have provided context in discussions of the current and potential future distribution of native, 

recovering fish populations, recreationally important coldwater trout species, and potential 

future invaders into Grand Canyon (e.g., smallmouth bass) from upstream and downstream 

sources (Figure 2). This could inform upcoming decisions about allocation of water supply 

among the basins’ existing reservoirs as runoff declines and air temperatures warm. 
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Figure 2. Heat map showing current water temperatures (6 – 26°C) in the CRe in Grand Canyon and in the upper and lower 

basin in July compared to the distribution and relative abundance of native, endemic fish populations (humpback chub, Colorado 

pikeminnow, roundtail chub), recreationally-important rainbow trout, and warmwater nonnatives (smallmouth bass, red shiner) 

that have hindered native fish recovery efforts in the upper basin. The Grand Canyon segment is currently much cooler than the 

upper basin river segments, which may be preventing the spread of undesirable warmwater nonnatives into Grand Canyon that 

could hinder recovery efforts for humpback chub.
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Sub-element E.1.2.

The purpose of this project is to characterize spatial and temporal patterns in Colorado River 

nutrient availability downstream of Glen Canyon Dam as well as to explore several processes 

that can influence the rate at which bioavailable nutrients are cycled and re-supplied to food 

webs. In FY 2019 we focused on the effects of two experimental flow regimes on phosphorus 

availability from the dam outflow, the role of storm-based inputs of phosphorus from the Paria 

River, and the potential for a wildfire to influence phosphorus pools in the CRe food web.

Because phosphorus concentrations in Lake Powell vary by depth, we hypothesized that the fall 

2018 HFE and experimental bug flows implemented during the spring and summer of FY 2018 

would affect downstream phosphorus concentrations. Sampling at the Lake Powell Wahweap 

station before, during, and after the High-Flow Experiment (HFE) in November 2018 revealed 

that SRP concentrations were approximately twice as high at the depth of the jet bypass tubes 

(4-7 ug/L) than at the depth of the penstocks (2-3 ug/L). A basic mixing model suggests that the 

discharge coming from the jet bypass tubes during the HFE should have elevated the outflow 

SRP concentration by about 1 ug/L (the detection limit of our analysis methods). Indeed, 

sampling at Lees Ferry before and during the HFE shows that SRP concentrations were higher

during the HFE compared to before the HFE (Figure 3). 

Figure 3. Soluble reactive phosphorus (SRP) concentrations (mg P L-1) at Lees Ferry prior to and during the 2018 HFE (n=4

for the “pre” time period and n=3 for the “during” time period). The red dashed line indicates the method detection limit for SRP. 

Individual data points are also shown.
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Bug flow sampling during FY 2018 was standardized for time of day and revealed no differences 

in total phosphorus or total dissolved phosphorus (TDP) in river water collected from the Glen 

Canyon reach (concentrations were always below the detection limit of 0.008 mg/L). No 

significant difference was found in SRP concentrations; however, concentrations were more 

variable during weekend water (undetectable to 0.004 mg/L) than during weekday water 

(0.001-0.002 mg/L). To follow up on the higher variation in SRP during weekend water, we 

conducted nutrient sampling four times per day across two weekend water days and three 

weekdays in August of 2019. During this August sampling campaign there were no significant 

differences in SRP, TDP, or TP concentrations and very low variation in SRP between weekend 

and weekday water. Still, there was generally high variation in TP concentrations across the 

entire sampling period, ranging from 0.006-0.018 mg/L (n=14). We also observed significantly 

higher nitrate concentration (by about 0.04 mg/L NO3-N) during weekdays than on the 

weekend (two-sided t-test, p=0.01). 

The Galahad fire occurred in the Shinumo watershed in May of 2014 and was followed by a 

large storm in August of 2014. Given the potential for fire to mobilize P and increase its rate of 

delivery to waterways (Emelko and others, 2016), we hypothesized that emergent aquatic 

insects collected near the mouth of Shinumo would have a higher P signature after the fire than 

before the fire. We also hypothesized that this effect would mostly be seen along the Colorado 

River downstream of Shinumo (whereas the upstream reach could be considered a control in a 

before and after control impact (BACI) analysis). Using historic light trap samples collected 

along the Colorado River (as described in Kennedy and others, 2016), we selected samples 

collected within 25 river miles up or downstream of Shinumo from June-September in 2013, 

2014, and 2015 (n~150). From these samples, we selected those that contained specimens of 

the order Diptera (n=54), and at least 4 individual Diptera were handpicked from the sample 

under a microscope for chemical analysis. Diptera were selected given their capability of 

reflecting a sizeable stream signature following emergence (Muehlbauer and others, 2014) and 

given their general abundance in Colorado River light trap samples. A small subset of the 

samples with the highest abundance of Diptera were run at the Colorado Plateau Stable Isotope 

Laboratory of Northern Arizona for analysis of d15N, %N, d13C, and %C (n=10). The remainder 

of the samples were weighed on a scale with an accuracy of 1 ug and shipped to the High Sierra 

Water Lab for total phosphorus analysis using a standard sulfuric acid digestion followed by 

spectrophotometric analysis and subsequent conversion to mg P per mg Diptera (n=44). There 

were no significant differences in %N, %C, d15N, or d13C across treatment groups, although 

C:N was generally lower post fire.
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We found significantly higher TP content of Diptera collected after the Galahad Fire and storm 

than from those collected before (two-sided t-test p<0.05), with emergent Diptera containing 

an average of 20% more P after the fire than before (Figure 4). Still, there was no effect of reach 

location (by two-way ANOVA), such that samples collected upstream after the fire were 

similarly elevated in P as those collected downstream. Over the same time, SRP outflow from 

Glen Canyon Dam was declining such that dam outflow chemistry is unlikely to be driving the 

patterns we observed. Collectively these results suggest that a large fire may have elevated the 

P content of Diptera in the CRe, but the role of other confounding factors such as changing 

water temperatures and P inputs from the Paria or Little Colorado Rivers need to be ruled out 

for a more conclusive interpretation.

Figure 4. Total phosphorus content of Diptera specimens collected in light traps along the Colorado River before and after a 

major fire and subsequent storm in the Shinumo watershed. Samples collected within 25 river miles upstream of Shinumo were 

considered “control” whereas those collected within 25 river miles downstream were considered “experiment.” There was 

significantly more phosphorus in Diptera after the fire than before (two-way t-test, p<0.05), but there was no reach effect.

While Glen Canyon Dam outflow dominates the water budget in the Colorado River, sampling 

conducted in FY 2018 suggests that the role of some larger tributaries may be important, at 

least during certain times of year in certain parts of the river, to the phosphorus 

budget. Storms, in particular, are often key times for phosphorus transport in river systems. The 

Paria River had the highest total phosphorus concentrations of any tributary tested during both 

FY 2017 sampling and a previous Arizona Department of Environmental Quality tributary 
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sampling effort (0.48 mg/L total P; Lawson, 2007). This combined with the relatively high 

discharges typical of the Paria River relative to other tributaries makes it a prime candidate for 

significant storm-driven phosphorus inputs to the Colorado River. Preliminary sampling during 

an August 2018 storm suggested that August storms alone could be responsible for 50% of the 

August total phosphorus loading and 8% of the annual loading. During FY 2019 a permit was 

obtained from NPS and a refrigerated ISCO automated water sampler was installed at the gage 

site where two other ISCOs are currently operated for sediment budgeting exercises. This ISCO 

is programmed for automated storm sample collection. A lack of monsoonal floods during FY 

2019 precluded our ability to quantify storm-based phosphorus inputs from the Paria River, but 

we are well positioned to look at this question in FY 2020 as long as there are monsoonal (or 

winter) storms.

In addition, a critical question is, how bioavailable is this total phosphorus coming from the 

Paria River (since very little of it is dissolved). While SRP is considered the most bioavailable 

form of phosphorus, bacteria and plants can also access other phosphorus fractions with 

varying levels of difficulty. Thus, it is important to characterize the quality (e.g., bioavailability) 

of phosphorus entering the river and not just its total concentration. In FY 2019 we ordered 

equipment and made plans to conduct a series of bioassays to better discern the role of pH and 

temperature on phosphorus cycling at the sediment water interface. These bioassays will assess 

total protein and alkaline phosphatase (methods we developed in FY 2018) together with major 

water column phosphorus forms. The last-minute loss of a student intern resulted in the 

project’s postponement until FY 2020.

Project Element E.2. Linking Temperature and Nutrients to Metabolism and Higher Trophic 

Levels

Objectives:

E.2.1. Determine drivers of ecosystem metabolism (including primary production and 

respiration) throughout the CRe

E.2.2. Document aquatic vegetation composition at fixed sites in Glen Canyon and develop a 

monitoring scheme to track future changes

E.2.3. Use artificial stream experiments to study how multiple trophic levels may respond to 

elevated temperatures

E.2.4. Develop ecosystem models linking temperature and nutrients to higher trophic levels.
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Sub-element E.2.1.

The purpose of this project is to link information about patterns in riverine nutrients and 

temperature to the base of the food web, primary production. Primary production in rivers can 

be estimated from diel patterns of dissolved oxygen. Long-term dissolved oxygen data are 

available at six sites throughout the Grand Canyon and can be analyzed to yield time-series of 

primary production. In FY 2018 we compared seasonal patterns of GPP at these long-term sites 

and found a lack of synchrony between sites. To follow up on these findings, a network of 10 

additional oxygen sensors (PME MiniDOTs equipped with wipers) were deployed throughout 

the river from April-September 2018 and 2019. Preliminary analysis of 2018 data show a similar 

lack of seasonal synchrony. For example, significant declines in GPP were noted from summer 

to fall 2018 at some sites, but not others (Figure 5). In addition, our analyses have uncovered 

measurable differences in GPP from weekday to weekend water during bug flows, but with a 

response that differs depending on the location within the canyon. Finally, analysis of long-term

data show declines in GPP following high flow events relative to years with no high flows 

(Figure 6). We plan to follow up on this finding with analysis of the 2019 dataset. In addition, 

we plan to use a combination of MiniDOT and long-term data to examine how GPP responds to 

other types of flow regulation such as HFEs, summer steady flows, and month-to-month 

changes in flow.

 

Figure 5. 2018 seasonal modeled GPP rates across at 11 sites with dissolved oxygen data in the Colorado River. GPP is in 

units of g O2 m-2 d

-1 and sites are ordered from the upstream-most site on the left to the downstream-most site on the right. Note 

that summertime GPP is much higher than fall gap at some sites (e.g. RMs 75, 124,189,208), but does not differ significantly 

seasonally at other sites (e.g. RM 269). “Summer” represents data collected between April 23 and May 10, 2018 (n=18 all sites) 

and “fall” represents August 30 through September 19, 2018 (n=21 all sites), where each data point is a single day GPP 

estimate.
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Understanding the environmental drivers of primary production at sites where there is bottomup control of primary production on the food web can provide important management-relevant 

information. In FY 2018 we employed a similar semi-mechanistic model at Diamond Creek (Hall 

and others, 2015) to examine the environmental controls on primary production at river mile

60. In addition to the drivers considered at Diamond Creek, we added SRP concentrations being 

exported from Glen Canyon Dam. We found that SRP is nearly as strong a lever on primary 

production as is the seasonal variation in light. Future work will employ this semi-mechanistic 

modeling approach at other sites along the river to better discern whole-ecosystem drivers.

Figure 6. Modeled gross primary production (GPP) rates in the Colorado River at river mile 60 before “Pre,” during “HFE,” and 

after “Post” High-Flow Experiment (HFE) in 2013 (upper left), 2014 (upper right), and 2016 (lower right), as well as during a non 

HFE year where the approximate timing of fall HFEs was approximated (lower left). Each time period depicts approximately a 

week’s worth of data with each point being a daily estimate of GPP. During years with HFEs, GPP declined significantly after the 

HFE. This stands in contrast to the non-HFE year where GPP did not decline markedly with time. 

Sub-element E.2.2. 

The purpose of this project is to develop a semi-automated aquatic vegetation classification 

system using underwater imagery combined with the use of machine learning and deep 

convolutional neural networks to detect annual to decadal scale changes in vegetation cover 

and species composition in the Colorado River downstream from Glen Canyon Dam. This 

project will facilitate detection of change to the base of the food web as varying ecosystem 

drivers (nutrients, temperature) change in response to a decline in Lake Powell water levels 

from ongoing and anticipated future drought and warming air temperatures that further 

decrease flow into rivers and reservoirs in the southwest region. 
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In FY 2018 we completed the first step of this project by developing a program to classify 

vegetation species composition and cover using a series of underwater images collected in 

August 2016. We assessed the ability of two independent biologists to correctly classify plant 

species within a series of mid- to high-quality underwater images. The two sets of images show 

a relatively high level of agreement on vegetation type, with precision scores ~0.7-0.8. Image 

classes from this process were used to train a model to classify the type and cover of other 

vegetation species within each image (Figure 7). 

Figure 7. a) Underwater image taken in Lees Ferry (i.e., the input file); b) Manual on-screen image annotations that classify 

vegetation types at the pixel level (i.e., unary potentials); c) Confidence assigned to each unary potential by the manual 

annotator in “b”; and d) Predictions of vegetation cover classes using conditional random fields (CRF), a classification and 

graphical modeling technique.

In FY 2019 we developed a cloud computer workspace to simplify image processing; however, 

the PIs struggled to get the code to work within the cloud workspace. An alternative workflow

was developed that will use of image polygon annotations in JSON format in the ‘Make Sense’ 

webtool (https://www.makesense.ai/) to create image labels and continue to develop a library 

of images; model refinement will continue in FY 2020. This model will ultimately be used to 

automatically classify thousands of underwater images from annual sampling events and 

develop a monitoring program to detect change in the CRe over time.

In addition to model development, we selected two permanent reaches of the Colorado River 

in Glen Canyon that will be used as baseline reaches to detect future aquatic vegetation 

change. From June 10-13, 2019 we took approximately 30,000 images of aquatic vegetation, 
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split between the upper reach (~-13 RM) and lower reach (~-4 RM). The upper reach was split 

into two sections, while the lower reach was split into three sections based on river hydrology 

and geomorphology. Within each section a piece of equipment adapted from the 

geomorphology field called the “flying eyeball” (Chezar and Rubin, 2004) captured images along 

transects running parallel to river flow spaced ~25 meters apart. Analysis of those images is 

ongoing – it is anticipated we will have a fully functioning tool in FY 2020 based on underwater 

images taken in FY 2016, FY 2019, and an upcoming trip in FY 2020.

Sub-element E.2.3. 

In FY 2018 we set up 12 replicate fiberglass raceways near the NPS Water Treatment Plant and 

Maintenance Shop in Lees Ferry for the purpose of using artificial stream experiments to study 

how aquatic vegetation, invertebrates, and fish may respond to elevated temperatures coming 

from potential future lower Lake Powell levels. While each recirculating tank was fed by water

coming directly from the Colorado River through underground pipes ~200 meters away, the 

temperatures in our raceways varied significantly more than the mainstem Colorado River 

(Δ3°C) due to underground heating combined with aboveground solar radiation and high 

summer air temperatures. Even with the most drastic temperature reduction strategies, water 

temperatures fluctuated by 10 °C daily in May and 7 °C daily in October (Figure 8). As such, the 

research setup at the NPS facility could not produce results directly applicable to the 

management of the Colorado River ecosystem as originally envisioned in the FY 2018-20 

Triennial Work Plan (TWP). Due to a lack of alternate options for artificial stream placement in 

Lees Ferry we decided the only low-cost option was to move the tanks back to Flagstaff and 

answer research questions in a controlled laboratory setting at the U.S. Forest Service, Rocky 

Mountain Research Station.
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Figure 8. Temperature loggers were placed in tanks having a variety of temperature control mechanisms. These two plots 

represent the most extreme measures to control temperatures in the tanks, including placing a chiller in each recirculating tank 

with a foam insulation pad covering 3⁄4 of the tank. Temperatures ranged from 10-20 °C in May (with increasing temperatures 

reflecting increasing air temperatures as the week progressed) and from 12-19 °C in October. The power grid shorted due to the 

chillers on 10/26/2018, allowing tank temperatures to increase over the next day until staff drove to Lees Ferry to remove the 

loggers.

In FY 2019 we developed a study design to answer research questions posed in the FY 2018-20 

TWP, using all aspects of the CRe to simulate river conditions to the extent possible in a 

laboratory setting. For this study we posed the following questions: 1) how does GPP change in 

response to cold, cool, and warm temperature treatments over time? 2) what diatom and softbodied algal taxa dominate under the three thermal conditions; 3) how might the population 

dynamics of grazers (i.e., New Zealand mud snails) respond to temperature treatments as 

measured by changes in growth, survival, and reproduction? 4) what effect do grazers have on 

GPP under various warming scenarios? and, 5) to what extent do native, endangered fishes 

(humpback chub, flannelmouth sucker, roundtail chub) consume mud snails? In June 2019 we 

collected cobble, algae, mud snails, and water from the Colorado River to inoculate 12 replicate 

raceways at the Rocky Mountain Research Station in Flagstaff. These raceways were located in 

an air temperature-controlled greenhouse to reduce variability in water temperatures. Each 

150-gallon raceway was filled to approximately 100 gallons and a recirculating pump simulated 

flow within each tank; filters were removed to keep nutrient concentrations consistent. 

Colorado River water was replaced in a half-tank water change every 2-3 weeks to maintain 

nutrient levels. Heaters and chillers set to 10, 15, and 20°C worked in tandem to create desired 

thermal conditions (Figure 9).
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Figure 9. Boxplot of water temperatures in the four replicates for each temperature treatment (10, 15, and 20°C) in the artificial 

stream experiment. Water temperatures are logged every 1-hr; these data are from July 7 to November 7, 2019.

Artificial streams grew from June 21 to November 4, 2019 (Figure E.2.3c). To start the growing 

process, each tank was inoculated with 1 liter of algal slurry containing the dominant algal taxa 

in Lees Ferry (e.g., Cladophora, Ulothrix, etc.). Approximately 10 dry cobbles were placed in 

each of three baskets (~500 μm mesh size) per tank. One basket contained cobble only and 

acted as a control; the other two baskets were seeded with 40 mud snails in two size classes 

(small ~0.5-1.18 μm, large >1.18 μm). Nine 5.1 x 5.1 cm ceramic tiles were placed in each 

raceway to track changes in GPP over a 4-5-month period and to examine diatom and softbodied algal communities at the conclusion of the experiment. One tile was preserved in 3% 

Lugol’s Solution on November 5, 2019 for analysis of diatom and soft-bodied algal communities. 

At the conclusion of the experiment (November 5-12) we conducted a whole-tank GPP 

experiment using the cobble from each basket to examine the effect of temperature 

treatments and grazing on GPP. A separate light experiment was conducted on November 12, 

2019 to determine whether light levels varied by area of the greenhouse. Due to the recent end 

of this experiment, preliminary GPP, light, and mud snail data are not available—results will be 

forthcoming in FY 2020 to determine future research directions (Figure 10).

10 15 20

10 12 14 16 18 20 22

Temperature Treatment

July-November Water Temperature
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1) Experimental set-up in laboratory 2) Whole-tank GPP experiment

3) Mud snails in baskets 4) Algae growing on cobble after five months

Figure 10. Artificial stream experiment at the Rocky Mountain Research Station in Flagstaff. 1) Experimental setup with 

recirculating tank, baskets of cobble with mud snails (control, small, large snails), and gross primary production (GPP) tiles; 2) 

Whole-tank GPP experiment with cobble from each basket, incubated for 18+ hours in water bath, with continuous reading O2

mini-dot sensor; 3) Cobble with mud snails; and 4) Algal growth after five months in artificial stream (June-November 2019).
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Sub-element E.2.4. 

The purpose of this project is to link information about patterns in riverine nutrients, 

temperature, and primary production to higher trophic levels. During early FY 2019, the lead PI 

(Charles Yackulic) participated in a National Science Foundation-funded workshop and helped 

develop a conceptual basis for dynamic ecosystem models that use high frequency 

measurements of GPP. The paper developed from this workshop is currently in review in the 

journal Limnology and Oceanography Letters. This work was entirely funded outside of the 

GCDAMP. We are currently working to turn this conceptual model into a statistical model that 

links gross primary productivity, invertebrate drift and fish population data that are routinely 

monitored at a few fixed sites in the river. Progress has been slower than desired primarily 

because of the overall underfunding of modeling and data management in the current 

workplan, which has required reducing staff and taking on additional outside projects to 

maintain staff that were only partially funded.

REFERENCES

Allen, A.P., Gillooly, J.F., and Brown, J.H., 2005, Linking the global carbon cycle to individual 

metabolism: Functional Ecology, v. 19, no. 2, p. 202-213, https://doi.org/10.1111/j.1365-

2435.2005.00952.x.

Brown, J.H., Gillooly, J.F., Allen, A.P., Savage, V.M., and West, G.B., 2004, Toward a metabolic 

theory of ecology: Ecology, v. 85, no. 7, p. 1771-1789, https://doi.org/10.1890/03-9000.

Chezar, H., and Rubin, D., 2004, Underwater microscope system—U.S. Patent no. US 6,680,795 

B2: Washington, D.C., Secretary of the Interior, 9 p., https://prd-wret.s3-us-west2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/Chezar_2004.pdf.

Elser, J.J., Acharya, K., Kyle, M., Cotner, J.B., Makino, W., Markow, T.A., Watts, T., Hobbie, S.E., 

Fagan, W.F., Schade, J., Hood, J., and Sterner, R.W., 2003, Growth rate-stoichiometry couplings 

in diverse biota: Ecology Letters, v. 6, no. 10, p. 936-943, https://doi.org/10.1046/j.1461-

0248.2003.00518.x.

Elser, J.J., Dobberfuhl, D.R., MacKay, N.A., and Schampel, J.H., 1996, Organism size, life history, 

and N:P stoichiometry: BioScience, v. 46, no. 9, p. 674-684, 

http://www.jstor.org/stable/1312897.

Emelko, M.B., Stone, M., Silins, U., Allin, D., Collins, A.L., Williams, C.H.S., Martens, A.M., and 

Bladon, K.D., 2016, Sediment-phosphorus dynamics can shift aquatic ecology and cause 

downstream legacy effects after wildfire in large river systems: Global Change Biology, v. 22, no. 

3, p. 1168-1184, https://doi.org/10.1111/gcb.13073.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Hall, R.O., Jr., Yackulic, C.B., Kennedy, T.A., Yard, M.D., Rosi-Marshall, E.J., Voichick, N., and 

Behn, K., 2015, Turbidity, light, temperature, and hydropeaking control primary productivity in 

the Colorado River, Grand Canyon: Limnology and Oceanography, v. 60, no. 2, p. 512-526, 

https://doi.org/10.1002/lno.10031.

Kennedy, T.A., Muehlbauer, J.D., Yackulic, C.B., Lytle, D.A., Miller, S.W., Dibble, K.L., 

Kortenhoeven, E.W., Metcalfe, A.N., and Baxter, C.V., 2016, Flow management for hydropower 

extirpates aquatic insects, undermining river food webs: BioScience, v. 66, no. 7, p. 561-575, 

https://doi.org/10.1093/biosci/biw059.

Lawson, L., ed., 2007, A water quality investigation of seventeen Grand Canyon tributaries—July 

2004-May 2005: Phoenix, Arizona Department of Environmental Quality, Division of Water, 

Surface Water Section, publication no. OFR-07-04, 88 p., 

http://www.azdeq.gov/environ/water/assessment/download/gcreport.pdf.

Muehlbauer, J.D., Collins, S.F., Doyle, M.W., and Tockner, K., 2014, How wide is a stream? 

Spatial extent of the potential “stream signature” in terrestrial food webs using meta‐analysis: 

Ecology, v. 95, no. 1, p. 44-55, https://doi.org/10.1890/12-1628.1.

Vernieu, W.S., 2009, Historical physical and chemical data for water in Lake Powell and from 

Glen Canyon Dam releases, Utah-Arizona, 1964-2013 (ver. 3.0, February 2015): U.S. Geological 

Survey Data Series 471, 23 p., https://doi.org/10.3133/ds471.

Walters, C., Korman, J., Stevens, L.E., and Gold, B., 2000, Ecosystem modeling for evaluation of 

adaptive management policies in the Grand Canyon: Conservation Ecology, v. 4, no. 2, article 1, 

http://www.consecol.org/vol4/iss2/art1/.

Wright, S.A., Anderson, C.R., and Voichick, N., 2008, A simplified water temperature model for 

the Colorado River below Glen Canyon Dam: River Research and Applications, v. 25, no. 6, p. 

675-686, https://doi.org/10.1002/rra.1179.

Yvon-Durocher, G., Caffrey, J.M., Cescatti, A., Dossena, M., Giorgio, P.d., Gasol, J.M., Montoya, 

J.M., Pumpanen, J., Staehr, P.A., Trimmer, M., Woodward, G., and Allen, A.P., 2012, Reconciling 

the temperature dependence of respiration across timescales and ecosystem types: Nature, v. 

487, no. 7408, p. 472-476, https://doi.org/10.1038/nature11205.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Presentation

Catchment and 

management 

characteristics are key 

in determining 

reservoir response to 

climate change

March 

2019

Deemer, B.R., Hayes, N.M., Strock, K.E., 

Corman, J.R., Razavi, N.R., Dibble, K.L., and 

Yackulic, C.B., 2019, Catchment and 

management characteristics are key in 

determining reservoir response to climate 

change—Invited talk: San Juan, Puerto Rico, 

Feb 24-March 1, 2019, Association for the 

Sciences of Limnology and Oceanography.

Presentation

Water storage 

decisions in response 

to drought in the 

Colorado River Basin 

will drive aquatic 

ecosystem dynamics

Oct 

2019

Dibble, K.L., Yackulic, C.B., Schmidt, J.S., 

Kennedy, T.A., and Bestgen, K.R., 2019, 

Water storage decisions in response to 

drought in the Colorado River Basin will 

drive aquatic ecosystem dynamics—Invited 

talk: Reno, Nev., Sept 29-Oct 3, 2019, 149th

American Fisheries Society Annual Meeting 

and Joint Conference with the Wildlife 

Society.

Journal 

article

Water storage policy 

will determine future 

persistence, and 

biogeography of, 

imperiled river fishes in 

a changing climate

To be 

submitted 

Dec 2019

Dibble, K.L., Yackulic, C.B., Schmidt, J.C., 

Kennedy, T.A., and Bestgen, K.R., in prep, 

Water storage policy will determine future 

persistence, and biogeography of, imperiled 

river fishes in a changing climate: Frontiers 

in Ecology and the Environment.

Journal 

article

Dam management 

effects on gross 

primary production in a 

large regulated river

To be 

submitted 

Sept 2020

Deemer, B.R., Yackulic, C.B., Hall, R.O., 

Kennedy, T.A., J. Muehlbauer, J.D., Yard, 

M.D., in prep, Dam management effects on 

gross primary production in a large 

regulated river. 
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Project F: Aquatic Invertebrate Ecology

SUMMARY

Overview

The principal goal of our work this year was to track invertebrate population response to the 

second year of the Bug Flow experiment that was tested from May-August 2019. We designed 

the Bug Flows hydrograph in collaboration with Western Area Power Administration (WAPA) 

and Bureau of Reclamation staff. We monitored ecosystem response to the Bug Flow 

experiment by launching Grand Canyon river trips in April, May, and September, through 

continuation of long-term citizen science monitoring in Grand Canyon, continuation of monthly 

drift and insect emergence monitoring in Glen Canyon, and intensive invertebrate and fish 

sampling in Glen Canyon in June and August. Additionally, we continued food base data 

collections in reaches where humpback chub populations appear to be growing (see Project G) 

and we collected data to understand the food web effects of trout removal and humpback chub 

reintroduction in Bright Angel Creek. 

Accomplishments

In FY 2019 our group worked with the Bureau of Reclamation and WAPA to design and 

implement the hydrograph for the Bug Flows experiment. This included deciding the 

appropriate flow level for weekend steady flows for each month of the experiment and routing 

these flows throughout Grand Canyon to predict how they would affect stage change at various 

locations of management interest, such as Lees Ferry and the confluence of the Little Colorado 

River.

To quantify the effects of Bug Flows, we launched three Grand Canyon river trips (April, May, 

and September). The objectives of the April and September trips were to quantify invertebrate 

drift concentrations approximately every four miles throughout Glen, Marble, and Grand 

Canyons and to identify whether Bug Flows increased the baseline abundance of drifting 

midges and other taxa compared to similar, pre- and during-Bug Flow drift data that was 

collected in 2017 and 2018. The purpose of the May river trip was to study food base response 

to the onset of the Bug Flow experiment. For the first weekend of Bug Flows in May, we 

Project Lead Theodore Kennedy

Principal 

Investigator(s) (PI)

Theodore Kennedy, USGS, GCMRC

Jeff Muehlbauer, USGS, GCMRC

Morgan Ford, USGS, GCMRC

Anya Metcalfe, USGS, GCMRC

Charles Yackulic, USGS, GCMRC

Email tkennedy@usgs.gov

Telephone (928) 556-7374
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collected drift, sticky traps, light traps, and surveyed for insect eggs in the vicinity of the Little 

Colorado River confluence (~ river mile (RM) 61). For the second weekend of Bug Flows in May, 

we carried out this same sampling in the vicinity of Fall Canyon (~RM 211) where humpback 

chub populations have been increasing. Sample processing for all three FY 2019 river trips is 

ongoing. 

Citizen science light trapping of adult aquatic insects has been ongoing since 2012, and this 

dataset is critical to evaluating food base response to the Bug Flow experiment. These data 

indicate aquatic insects responded strongly and positively during the first year of Bug Flow 

testing in 2018. For example, the abundance of caddisflies increased by around 400% in 2018, 

concurrent with Bug Flow testing, compared to pre-Bug Flow years (2012-2017; Figure 1). 

Citizen science data also indicate the abundance of midges was significantly higher Canyonwide during weekend Bug Flow releases compared to weekdays with load-following flows 

(Figure 2). 

Citizen science sampling yielded 1,100 light trap samples in 2019. Although we do not 

anticipate completing sample processing until March 2020, most citizen science samples will be 

processed by January 2020 and these results will be included in our Annual Reporting Meeting 

presentation. Citizen scientists also collected acoustic bat activity data paired with over 400 of 

these light trap samples. These paired insect-bat data will be used to identify whether there is a 

correlation between aquatic insect abundance and bat activity levels throughout the Colorado 

River corridor in Grand Canyon.

Figure 1. There was a significant increase in the number of adult caddisflies captured in citizen science light traps during the 

first year of Bug Flows in 2018 compared to 2012-2017 light trap samples. Bars represent standard error and numbers represent 

mean light trap catch rates. Caddisflies are in the Order Trichoptera, which is part of the sensitive “EPT” indicator group. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Figure 2. During Bug Flows in 2018, more adult non-biting midges (Chironomidae) emerged during low and steady Bug Flow 

weekend water conditions than during normal, fluctuating weekday water conditions. Bars represent standard error and numbers 

represent mean light trap catch rates throughout Grand Canyon. Inset photo shows hundreds of yellow “egg ropes” laid by 

midges at the air-water interface on a rock in Glen Canyon in August 2019. Each egg rope contains hundreds of midge eggs. 

Photo by David Herasimtschuk, Freshwaters Illustrated/USGS.

Our group continued long-term monitoring of the aquatic food base in the Lees Ferry sport 

fishery with monthly drift, sticky trap, and light trap sampling from Glen Canyon Dam (RM -15) 

to Badger Rapid (RM 8). Sample processing for all Lees Ferry data collections is current and upto-date (i.e., there is no backlog). As part of our monthly sampling in Lees Ferry, we also recalibrated and serviced dissolved oxygen monitoring instruments, which provide data used in 

modeling algae production in the Colorado River (see Project E). Collectively, these data 

collection efforts will allow us to assess invertebrate population response to Bug Flows and 

track the status and trends of the aquatic food base across a variety of sampling methods and 

on robust spatial and temporal scales.

In response to concerns raised by WAPA, we conducted intensive sampling in Glen Canyon to 

determine the short-term response of invertebrate drift, insect emergence, rainbow trout 

feeding habits, and angling success to the Bug Flows experiment. Sampling occurred from June 
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14-17 and August 23-26, Friday-Monday in both cases. Each sampling event included two days 

with load-following flows and two weekend days with low steady discharges for Bug Flows. On 

each day, invertebrate drift samples were collected at five sites (RM -15, -12.9, -8, -3.5, and 0) 

and starting at two different times of day (6 am, 3 pm; sampling took around 2 hours to 

complete). On weekdays during load-following, the two sample times correspond to low and 

high (on-peak) discharge while during weekend Bug Flows the two sample times correspond to 

identical, low discharges. Rainbow trout diet samples were collected daily using non-lethal 

gastric lavage from trout collected by guided angling. Volunteer anglers helped capture rainbow 

trout used in this diet study. Invertebrate and fish diet sample processing from this experiment 

is ongoing. However, results from the angling success portion of the study have been analyzed 

and demonstrate that the average angler caught more fish during low steady Bug Flows 

compared to load-following flows (Figure 3). This finding is consistent with numerous fishing 

blogs from Lees Ferry guide services describing how low steady Bug Flow releases improves 

angling success. 

Figure 3. Modeled number of fish captured by anglers during weekday load-following flows compared to low steady Bug Flow 

weekends. In our study involving 31 anglers, we caught 368 fish over 8 days (4 weekdays and 4 weekend days). On average, 

5.1 fish were caught per angler on the weekdays compared to 6.8 fish caught per angler on weekend days (+/- standard error of 

0.62 and 1.02, respectively). 
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In response to manager concerns, our group continued studies of the food base in Bright Angel 

Creek associated with trout mechanical removal efforts and reintroduction of humpback chub 

in 2019. Our sampling approach is based on the design used by Whiting and others (2014) that 

was used to sample aquatic invertebrates in Bright Angel Creek prior to trout removal. We 

sampled aquatic invertebrates in Bright Angel Creek three times in FY 2019 (November 2018 

and June and September 2019; a planned January trip was canceled due to the government 

shutdown). In total, we collected 36 benthic, 27 drift, and 36 sticky trap samples of aquatic 

insects in the 3200-m reach upstream from the mouth of Bright Angel Creek. We have been 

conducting these sampling trips since 2016, and now have a dataset that spans multiple years 

of trout removal in addition to humpback chub reintroduction. This work will allow us to 

explore how the food web has responded to these management actions and what invertebrate 

food may be available for the translocated humpback chub.

Next Steps

Our results suggest that Bug Flows had a strong, positive impact on the aquatic food base in 

Glen, Marble, and Grand Canyons. Our data also demonstrate that weekend low steady Bug 

Flow releases improve angler catch rates in the rainbow trout sport fishery compared to 

weekday load-following flows. 

In FY 2020, we will continue our long-term monitoring of drift and sticky trap collections in the 

Glen Canyon reach, our citizen science light trap sample collection throughout Glen, Marble, 

and Grand Canyons, our drift-focused river trips in spring and fall, and our drift sampling on 

juvenile chub monitoring and rainbow trout monitoring trips (see projects G and H). 

Collectively, these data collections provide important insight into the long-term status and 

trends of the aquatic food base in the Colorado River ecosystem, particularly as it pertains to 

food resources for rainbow trout and humpback chub. These data collection efforts also allow 

us to track food base response to Bug Flow experimentation on robust spatial and temporal 

scales. Finally, contingent on funding and testing the Bug Flow experiment again in 2020, we 

will also repeat the intensive weekday-weekend study in Glen Canyon to more fully 

characterize how Bug Flows affect aquatic resources and angling success on a daily scale. 

REFERENCES

Whiting, D.P., Paukert, C.P., Healy, B.D., and Spurgeon, J.J., 2014, Macroinvertebrate prey 

availability and food web dynamics of nonnative trout in a Colorado River tributary, Grand 

Canyon: Freshwater Science, v. 33, no. 3, p. 872-884, https://doi.org/10.1086/676915.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Series, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Bug Flows 

implementation and 

resource response

March 

2019

Kennedy, T.A. and Muehlbauer, J.D., 2019, Bug Flows 

implementation and resource response—presentation:

Phoenix, Ariz., March 12, 2019, TWG Annual Reporting 

Meeting. 

Presentation

Big flood, small flood, 

spring flood, fall 

flood: HFE timing 

affects food base 

response

March 

2019

Kennedy, T.A. and Muehlbauer, J.D., 2019, Big flood, 

small flood, spring flood, fall flood—HFE timing affects 

food base response—presentation: Phoenix, Ariz., March 

13, 2019, TWG HFE workshop meeting.

Presentation

Bug Flows 

implementation and 

resource response

April 

2019

Kennedy, T.A., 2019, Bug Flows implementation and 

resource response—presentation: Marble Canyon, Ariz., 

April 15, 2019, Meeting with fishing guides.

Presentation

Bug Flows evaluation 

and recommendation 

for 2019 

April 

2019

Smith, E.O., Kennedy, T.A., and Vanderkooi, S.P., 2019, 

Bug Flows evaluation and recommendation for 2019—

presentation: Flagstaff, Ariz., April 22, 2019, LTEMP 

Planning and Implementation Team Webinar.

Presentation Bug Flows update

May 

2019

Kennedy, T.A., Muehlbauer, J.D., and Dodrill, M.J., 2019, 

Bug Flows update—presentation: Flagstaff, Ariz., May 1, 

2019, TWG Webinar.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Series, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

When flow food 

webs get fishy: Some 

challenges and 

opportunities

May 

2019

Baxter, C.V., Bellmore, J., Cross, W.F., Hall, R.O., 

Kennedy, T.A., Marcarelli, A., Paris, J., Rosi, E.J., 2019, 

When flow food webs get fishy—Some challenges and 

opportunities—presentation: Salt Lake City, Utah, May 

20, 2019, Society for Freshwater Science Annual 

Meeting.

Presentation

Genetic diversity of a 

vagile aquatic insect 

varies with river 

network structure

May 

2019

Metcalfe, A.N., Kennedy, T.A., Marks, J.C., Muehlbauer, 

J.D., 2019, Genetic diversity of a vagile aquatic insect 

varies with river network structure—presentation: Salt 

Lake City, Utah, May 20, 2019, Society for Freshwater 

Science Annual Meeting.

Presentation

Food web controls 

on mercury flux and 

fate in the Colorado 

River, Grand Canyon

May 

2019

Walters, D., Rosi, E.J., Cross, W.F., Kennedy, T.A., Baxter, 

C.V., and Hall, R.O., 2019, Food web controls on mercury 

flux and fate in the Colorado River, Grand Canyon—

presentation: Salt Lake City, Utah, May 20, 2019, Society 

for Freshwater Science Annual Meeting.

Presentation

Hydropower and 

aquatic-terrestrial 

linkages in the 

Colorado River

May 

2019

Lupoli, C.A., Kennedy, T.A., Sabo, J.L., and Yackulic, C.B., 

2019, Hydropower and aquatic-terrestrial linkages in the 

Colorado River—presentation: Salt Lake City, Utah, May 

21, 2019, Society for Freshwater Science Annual 

Meeting.

Presentation

Bug Flows: LTEMP 

planning process and 

preliminary 

observations

May 

2019

Smith, E.O. and Kennedy, T.A., 2019, Bug Flows—LTEMP 

planning process and preliminary observations—

presentation: Flagstaff, Ariz., May 22, 2019, AMWG 

Webinar.
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PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Series, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Colorado River 

ecosystem response 

to the 2018 Bug Flow 

experiment from 

Glen Canyon Dam

May 

2019

Muehlbauer, J.D. and Kennedy, T.A., 2019, Colorado 

River ecosystem response to the 2018 Bug Flow 

experiment from Glen Canyon Dam—presentation: Salt 

Lake City, Utah, May 23, 2019, Society for Freshwater 

Science Annual Meeting.

Presentation

Preliminary 

observations from 

the Bug Flows 

Experiment

June 

2019

Kennedy, T.A. and Muehlbauer, J.D., 2019, Preliminary 

observations from the Bug Flows Experiment—

presentation: Phoenix, Ariz., June 11, 2019, TWG 

Meeting.

Presentation

Colorado River 

Ecosystem response 

to the 2018 Bug Flow 

Experiment from 

Glen Canyon Dam

September 

2019

Kennedy, T.A., Muehlbauer, J.D., and Rogowski, D.L., 

2019, Colorado River ecosystem response to the 2018 

Bug Flow Experiment from Glen Canyon Dam—

presentation: Flagstaff, Ariz., September 11, 2019, 15th

Biennial Conference of Research on the Colorado 

Plateau.

Presentation

Gene flow among 

net-spinning 

caddisfly populations 

in the Colorado River 

Basin 

September 

2019

Metcalfe, A.N., Kennedy, T.A., Marks, J.C., and 

Muehlbauer, J.D., 2019, Gene flow among net-spinning 

caddisfly populations in the Colorado River Basin—

presentation: Flagstaff, Ariz., September 11, 2019, 15th

Biennial Conference of Research on the Colorado 

Plateau.
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Project G: Humpback Chub Population Dynamics throughout the 

Colorado River Ecosystem

Project Lead Charles B. Yackulic

Principal 

Investigator(s) (PI)

Charles B. Yackulic, USGS, GCMRC

Maria Dzul, USGS, GCMRC

Michael Yard, USGS, GCMRC

Kirk Young, USFWS

Randy Van Haverbeke, USFWS

David Ward, USGS, GCMRC

Laura Tennant, USGS, GCMRC

Email cyackulic@usgs.gov

Telephone (928) 556-7379

SUMMARY

In 2019, humpback chub (HBC) research included sampling trips to the lower Little Colorado 

River (LCR), in the neighboring reaches of the Colorado River (near the LCR confluence), and in 

the Colorado River near Fall Canyon (in western Grand Canyon). The above-mentioned 

sampling efforts visited the same reaches across trips, and thus mark-recapture efforts were 

relatively intensive. To complement the more spatially-intensive sampling efforts, 2019 

sampling also included more widespread sampling of the Colorado River via HBC aggregations

and backwater seining trips. These sampling trips visited many sites along the Colorado River 

and sampling efforts were more diffuse along a larger spatial area. All monitoring efforts 

generally followed the same fish sampling protocol as described in Persons and others (2015).

Monitoring of the LCR in 2019 included U.S. Fish and Wildlife Service (USFWS)-led sampling in 

the lower 13.6 km of the LCR (two fall trips and two spring trips), which yielded abundance 

estimates from closed models. Furthermore, the USFWS also visited a more upstream site 

(located 13.6-17.7 river kilometers upstream of the Colorado River confluence) in May to 

conduct HBC monitoring and in October to translocate HBC juveniles from the lower LCR into 

upstream reaches. One additional trip to the lower 13.6 km of the LCR was conducted by USGS 

in June-July 2019, where the goal was to sample the age-0 cohort that was produced in the 

spring of 2019. Colorado River monitoring by the USGS in 2019 included May, July, and October 

sampling trips near the LCR confluence in the juvenile chub monitoring reach (located 62.8-65.9 

river miles (RM) downstream of Lees Ferry - hereafter referred to as JCM-east). Similarly, May, 

July, and October 2019 trips also visited a site in western Grand Canyon (RM 210.5-214.0) 

referred to as the Fall Canyon reach or JCM-west.
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Data from LCR monitoring and from JCM-east will be used to obtain estimates of vital rates 

(survival, growth) and adult HBC abundances from multistate models. Additionally, we are 

working on modeling methods to help us explore how to best integrate data from passive 

integrated transponder (PIT) tag antennas into humpback chub population models. Initial 

results of this effort suggest that PIT tag antennas are a powerful tool that can augment 

detections of larger adult fish (which tend to have low capture probabilities in hoop nets and 

with electrofishing). We are also developing models that explicitly incorporate information 

about alternative life histories and demographic groups (e.g., males versus females, small 

versus large adults), where survival and movement rates differ among these groups.

Project Element G.1. Humpback Chub Population Modeling

Progress on HBC population modeling includes initial development of a mark-recapture model 

of spawning dynamics in the LCR aggregation, construction of a model assessing the 

effectiveness of HBC translocations upstream of Chute Falls, and a recent manuscript 

submission that describes a new approach to model building that includes a modeling example 

from the LCR HBC aggregation.

The spawning dynamics model is being developed by USGS-GCMRC staff and researchers from 

Colorado State University. This model is designed to assess variability in survival, growth, and 

movement rates for different demographic groups (i.e., small females, large females, small 

males, large males) and alternate life history states (i.e., annual spawners, skipped spawners, 

residents). One important aspect of this model is that it explicitly incorporates antenna 

detections and physical capture data (e.g., hoopnet and electrofishing captures) into a markrecapture model structure. Antenna data include both data from the LCR multiplexer array 

(MUX) that is located near the LCR-Colorado River confluence, as well as submersible antennas 

placed in the JCM-east reach. Initial results suggest that antennas detect trap-shy individuals 

that have not been captured in many years. For example, inclusion of LCR MUX data show that 

many adult HBC that swim into the LCR are not captured by USFWS as part of their spring 

sampling. This can be seen in the results of previous studies, which over-estimated skipped 

spawning probabilities (or the probability an adult in the Colorado River (CR) does not move 

into the LCR to spawn in spring) either because the models did not include antenna data 

(Yackulic and others, 2014) or because the models included antenna data that were of poor 

quality (Pearson and others, 2015). Comparison of models fit with and without antenna data 

also show that models without antenna data also tend to underestimate survival of large adult 

spawners (Figure 1). 
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Figure 1. Comparison of two models fit with and without antenna data. Data were fit from 2009-2017 and include different 

biological states which include spawner (moves between Colorado and Little Colorado Rivers in spring), skipped spawner (in 

Colorado River year-round), and resident (in Little Colorado River year-round). The top panel shows the mean annual survival 

probability for the spawners for four demographic groups: small females (200-249mm TL), small males (200-249mm TL), large 

females (250+mm TL), and large males (250+mm TL). The lower panel shows the mean probability that a annual spawner 

becomes a skipped spawner according to demographic group. Graphs indicate that models fit without antenna data may overestimate the probability of annual spawners becoming skipped spawners and underestimate survival of large adult spawners.

Additionally, USGS and USFWS are collaborating to construct a model that estimates the 

effectiveness of USFWS translocations above Chute Falls. Results suggest that the 

translocations produce a modest increase in the size of the LCR adult HBC population. 

Specifically, the continuous effort of translocating 300 juvenile HBC each year upstream of 

Chute Falls would be expected to result in an extra 350-400 adult HBC under equilibrium 

conditions, compared to no translocations. Importantly, these extra adult HBC should decrease 

the likelihood that other management actions, like trout removal, are required and we are 

working to estimate the size of this impact using a decision model.

0.5

0.6

0.7

0.8

0.9

1.0 Annual survival

small females large females small males large males

0.0

0.2

0.4

0.6

0.8

1.0

Prob spawner becomes skipped spawner

small females large females small males large males

with antennas

without antennas Prob S to SS
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Figure 2. Abundance of adult humpback chub (HBC; >199mm TL) that spawn in the Little Colorado River. This figure is from a 

manuscript that was recently submitted to the journal Ecological Applications.

Lastly, the latest HBC population numbers are included in a manuscript (Figure 2; Yackulic and 

others, in review) that is currently in review in the journal Ecological Applications. This 

manuscript describes an approach to population modeling that allows researchers to build 

faster and more complex mark-recapture models, and we are currently using the approach 

described in this paper to obtain better population models for HBC.

Project Element G.2. Annual Spring/Fall Humpback Chub Abundance Estimates in the Lower 

13.6 km of the LCR

In 2019, USFWS and volunteers conducted four monitoring trips to monitor HBC in the LCR. 

These trips occurred in April, May, September, and October. The goal of these trips was to 

monitor the population status and trend of HBC in the LCR during spring and fall. During spring 

2019, it was estimated that there were 11,210 (Standard Error [SE] = 1,300) humpback chub 

≥150 mm total length (TL), of which 8,987 (SE = 1,048) were ≥200 mm TL in the LCR (Figure 3A). 

These numbers represent the highest spring abundance of humpback chub in the LCR recorded 

to date.
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A.

B.

Figure 3. Chapman Petersen abundance estimates (±95% CI) of humpback chub ≥150 mm total length (TL) and ≥200 mm TL 

in the Little Colorado River (0-13.57 river km) during (A) spring (2001-2018) and (B) fall seasons (2000-2018). Note: closed 

spring and fall abundance estimates of humpback chub >150 mm TL in the Little Colorado River during 1991 and 1992 are from 

Douglas and Marsh (1996). 
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Fall 2019 abundance estimates are forthcoming. However, in fall 2018, it was estimated that 

there were 4,694 (SE=116) HBC ≥150 mm TL in the LCR. Of these fish, an estimated 2,779 (SE = 

84) were ≥200 mm TL (Figure 3B). We add the caveat that the fall 2018 estimate was calculated 

by applying historical capture probability data to the September 2018 catch data, and that 

because of high variance in daily turbidity values during the September 2018 trip, this estimate 

may be conservative. 

Project Element G.3. Juvenile Humpback Chub Monitoring near the LCR Confluence

In 2019, there were three juvenile HBC monitoring trips (occurring in May, July, and October) in 

the JCM-east site. Two methods (slow-shock electrofishing and hoop nets) were used to 

capture fish, and eight submersible antennas were also deployed during these trips. All HBC > 

79 mm TL were marked with PIT tags, and all HBC between 40-79 mm TL were marked using 

visual implant elastomer (VIE). One change that occurred during the July and October trips was 

that total length was only measured for recaptured fish.

Humpback chub were the most frequently caught species in JCM-east catch (1369), followed by 

flannelmouth sucker (1306), fathead minnow (784), rainbow trout (748), bluehead sucker (541), 

speckled dace (113), plains killifish (42), yellow bullhead (38), carp (26), brown trout (9), red 

shiner (9), channel catfish (8), and green sunfish (3). In total, all JCM-east trips captured 1038

HBC > 79mm TL and marked 275 HBC between (40-79 mm TL) with VIE. Catch of HBC >79mm TL 

was 143 in May, 246 in July, and 649 in October. In addition, the number of humpback chub 

given a VIE mark (between 40-79mm TL) was 35 in April, 51 in July, and 189 in October.

Table 1 compares PIT antenna data to the other two more conventional sampling types 

(electrofishing and hoop netting). Specifically, in the JCM-east reach, the PIT antennas detected 

more fish than what were captured using electrofishing and hoopnetting (1728 compared to 

1147). Importantly, only 8.7% of fish in the JCM-east reach that were detected on antennas 

were also captured using hoop nets or electrofishing, showing there was low overlap in antenna 

detections and physical recaptures. 
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Table 1. Comparison of passive integrated transponder antennas (or fish scanners = FS) and physical 

capture methods (EF= electrofishing, HP= hoop net) for JCM-east and JCM-west reaches during 2019 

sampling.

Figure 4. Estimated abundance of age-0 humpback chub (i.e., < 99 mm total length (TL)) during mid-summer sampling trips to 

the lower 13.6 km of Little Colorado River.
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Pre-Monsoon Juvenile Chub Sampling in the LCR

In 2019, monitoring occurred from June 27 to July 8. As in previous years, three teams 

completed two passes of the LCR using hoop nets, seines, and dip nets. The main focus of the 

trip was to mark and recapture juvenile HBC to obtain an estimate of population size and 

outmigration. Accordingly, all HBC > 39 mm TL and < 80 mm TL were given VIE marks that were 

specific to the trip, gear type (hoop net versus dipnet/seine), and size category (40-59 mm TL or 

60-79 mm TL). For other fish, the trips followed the fish handling protocol described in Persons 

and others, 2015, except that native fish > 99 mm TL that were captured during the afternoon

hoop net hauls were not processed (i.e., they were released immediately without scanning for a 

tag or obtaining measurements). This change occurred at the direction of USFWS. During this 

trip, 3022 humpback chub (40-79 mm TL) were marked with VIE. Population estimates of age-0 

HBC were higher for 2019 than for the three previous years (2016-2018; Figure 4A). 

Importantly, compared to previous years (2013-2018), the size of age-0 fish was much smaller 

(Figure 4B), indicating either later hatch dates or poorer growth conditions in 2019.

Project Element G.4. Remote PIT Tag Array Monitoring in the LCR

Remote Technologies

The LCR MUX is located about 1.7 kilometers upstream of the LCR confluence with the Colorado 

River. The MUX is comprised of two arrays (in situ chains of PIT tag antennas that stretch across 

the river), an upstream and a downstream array, that continuously detect PIT-tagged fish. The 

main advantage of this array is that it provides a non-obtrusive method for evaluating 

movements of fishes between the Colorado River and LCR. In FY 2019, the battery bank 

powering the downstream array was depleted and not replaced due to the limited functionality 

of the downstream MUX. The upstream array only had 1-2 antennas working during FY 2019. 

The current MUX shows very little functionality and there are currently plans to replace the 

entire MUX with a newer model in 2020. The new MUX has been funded by the Bureau of 

Reclamation, and Biomark was awarded the contract to build the antennas and help with the 

installation.

In addition to the MUX, a network of 4-8 single, shore-based antennas were deployed in the 

LCR in 2017 to help supplement MUX detections. The network antenna design was operational 

in 2019 and the design consisted of seven antennas – four were placed near 1.3-1.4 river 

kilometers (rkm) upstream of the LCR confluence with the Colorado River (hereafter the 

Amazon Island cluster) and three were placed upstream of the waterfall at Boulders camp (rkm 

2.0-2.2, hereafter the A-Rock cluster). These antennas are much smaller than the MUX and did 

not span the entire river width. Rather, they are 123 cm x 61 cm in dimension and are placed 

parallel to the shoreline. We hope this new design will better help us assess directionality of 

fish movements, since there is a large waterfall between the two antennas clusters which we 
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hope will act as an obstacle that deters fish from continuously swimming over both antenna 

clusters over short time intervals. 

During the 2019 spring migration window (Feb 15 – Jun 15), the antenna network detected 

5027 unique PIT tags, 3767 of which were HBC. Of these 3767 tags, 383 were detected on both 

the Amazon Island and A-Rock clusters. Furthermore, of the 383 fish detected on both antenna 

clusters, 380 were detected on the downstream cluster (Amazon Island) before the upstream 

cluster (A-Rock), suggesting the antennas were detecting upstream movement. The median 

time between antenna cluster detections was 76 hours, indicating fish took a little over three 

days to swim upstream from Amazon Island to above the waterfall at Boulders camp. 

Project Element G.5. Monitoring Humpback Chub Aggregation Relative Abundance and 

Distribution

During fall 2019, two river trips were conducted the USFWS to monitor HBC in the mainstem 

Colorado River in Marble and Grand Canyons. The first trip (aggregation trip) occurred from 

September 7-23. A second trip (Diamond down trip) occurred from September 30 to October 8. 

One objective of the aggregation trips is to continue a long-term relative abundance (catch per 

unit effort, or CPUE) index of HBC in the known historical aggregation sites. In addition, fish 

were sampled within three discrete river reaches as part of mark-recapture studies; these being 

the JCM-west (Fall Canyon) site near Pumpkin Spring, downstream of Diamond Creek near 

Bridge City, and near 250 mile. The second Diamond down trip functioned as a recapture event 

for the Bridge City reach and the reach near 250 mile. These trips employed baited hoop nets 

and submersible antennas as sampling gear. 

Since 2006, there have been increases in HBC CPUE at most aggregations, as well as at some 

non-aggregation sites. There has also been a dramatic increase in HBC catch in western Grand 

Canyon since 2014 (Van Haverbeke and others, 2017). Because of this, and because of an 

increasing interest in understanding absolute abundances of HBC in the mainstem Colorado 

River, mark-recapture studies were incorporated into this work in 2017. To this end, USFWS has 

worked collaboratively with the JCM project (Project G.6) to conduct mark-recapture 

experiments in the JCM-east and JCM-west reaches. In addition, USFWS conducted markrecapture studies below Diamond Creek near Bridge City and near 250 mile in 2018 and 2019. 

In fall of 2018 for example, an estimate of 1,165 humpback chub ≥ 100 mm was generated for a 

two-mile reach of the Colorado River near Bridge City (river mile 236-238), of which 582 were 

adults ≥ 200 mm. An estimate of 619 flannelmouth sucker ≥ 150 mm was also generated for 

this same reach. 

In fall of 2019, USFWS conducted monitoring in the following historic aggregations: 30-mile, LCR 

Inflow, Bright Angel, Stephen Aisle, Middle Granite Gorge, Havasu Inflow, and Pumpkin Spring. 

We conducted mark-recapture experiments at JCM west, Bridge City, and near 250 mile. 
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Results are forthcoming. In the near future, USFWS plans to compare estimates from JCM-west 

derived from open models to the estimates reported here for closed models.

Project Element G.6. Juvenile Humpback Chub Monitoring – West

Sampling occurred near Fall Canyon and consisted of three passes of hoop net captures and 

night-time electrofishing. Methods for JCM-west were similar to those described for JCM-east 

(see Project Element G.3). Species composition of catch in JCM-west was comprised mostly of 

native species, with the highest catch occurring for flannelmouth sucker (15952), speckled dace 

(14350), bluehead sucker (1664), humpback chub (1621), and unidentified suckers (1). 

Nonnative catch was comprised of fathead minnow (434), rainbow trout (181), red shiner (10), 

brown trout (9), carp (9), green sunfish (2), and striped bass (1). Note that native species were 

more predominant in catch of the JCM-west site compared to JCM-east, the latter of which had 

very high catch of fathead minnows and rainbow trout. In the JCM-west reach, catch of HBC

>79 mm TL was 302 in May, 880 in July, and 379 in October. In addition, the number of HBC

issued VIE marks between 40-79 mm TL was 19 in May, 31 in July, and 51 in October.

Submersible PIT antennas provided an alternate gear type that was used to supplement 

electrofishing and hoop netting efforts (Table 1). Sampling efforts from hoop net captures show 

that all size classes of HBC were present in both JCM-east and JCM-west (Figure 5).

Figure 5. Length-probability histograms for humpback chub captured in hoop nets for three different sampling occasions (May, 

July, October 2019) at two different sites in the Colorado River (JCM-east, JCM-west).
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[88]

Project Element G.7. Chute Falls Translocations

The goals of this project, conducted by the USFWS, are to:

1) Annually translocate at least 300 juvenile HBC from lower portions of the LCR to 

upstream of rkm 14.2 (i.e., upstream of Chute Falls). 

2) Annually monitor the abundance of HBC upstream of rkm 13.6 in the LCR. This includes 

monitoring in a small reach of river known as the Atomizer reach (rkm 13.6–14.1) and 

the reach of river known as the Chute Falls reach (rkm 14.1–17.7).

This project is identified as a Conservation Measure in the 2016 Biological Opinion. These 

monitoring activities also coincide with collaborative efforts with NPS to collect juvenile or 

larval HBC for transport to the Southwest Native Aquatic Research and Recovery Center 

(SNARRC), destined to support a genetic refuge population at SNARRC, or for grow out and 

release into Shinumo, Havasu, or Bright Angel Creeks. The project also fulfills a conservation 

measure to translocate HBC to upstream of rkm 13.6 in the LCR, intended to increase growth 

rates and survivorship, expand the range, and ultimately augment the LCR HBC population in 

Grand Canyon. In addition, this project provides managers with an annual index of abundance 

and trend of HBC residing above rkm 13.6. 

Translocations

One effort to translocate HBC to the LCR upstream of Chute Falls was conducted in FY 2019. No 

translocations were conducted in Havasu, Shinumo or Bright Angel Creeks during FY 2019. 

Chute Falls:

Efforts to translocate HBC upstream of Chute Falls in the LCR have been ongoing since 2003. To 

date, approximately 3,470 juvenile (~80-130 mm TL) HBC have been translocated upstream of 

Chute Falls. Of these, 49 were released above Chute Falls (at rkm 16.2) on October 26, 2018. It 

is thought that no spring runoff in the LCR during spring 2018 resulted in very poor production 

of age 0 HBC. That, combined with LCR flooding during the October 2018 collection effort, 

resulted in an unusually low number of HBC being translocated upstream of Chute Falls. On 

October 25, 2019, another 307 juvenile humpback chub were released upstream of Chute Falls. 

Monitoring

U.S. Fish and Wildlife Service and volunteers conduct an annual monitoring trip upstream of 

rkm 13.6 in the LCR. The purpose of this effort is primarily to monitor the abundance of HBC 

that are translocated upstream of Chute Falls but also serves to monitor the abundance of HBC 

in a small section of river between rkm 13.6 and 14.1, known as the “Atomizer Reach.” This 

effort typically occurs in May or June, when river conditions are not flooding, and it is safe to 

conduct work activities in this stretch of river. From 2006–2009, two pass mark-recapture 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[89]

population estimates of HBC were conducted upstream of rkm 13.6 in the Atomizer and Chute 

Falls reaches of the LCR. During these trips, capture probability data was obtained. From 2010–

2019, this set of capture probability data were used to annually estimate the abundance of HBC 

upstream of rkm 13.6 in the Chute Falls and Atomizer reaches. During a trip in May 2019, we 

estimated there were 349 HBC ≥ 100 mm TL (SE = 44) in the Chute Falls reach. Of these, it was 

estimated that 263 (SE = 33) were adults ≥200 mm TL (Figure 6). In the Atomizer reach, it was 

estimated that there were 587 HBC ≥100 mm TL (SE = 26). Of these, it was estimated that 416 

(SE = 20) were adults ≥200 mm TL. Results have also indicated unusually rapid growth of 

translocated fish, and high apparent survival.

Figure 6. Numbers of juvenile humpback chub that have been translocated to the Chute Falls reach since 2003 (black bars); 

and abundances of adult humpback chub ≥ 200 mm in the Chute Falls reach (river km 14.1-17.7) estimated with Chapman 

Petersen method (dark grey bars), and Monte Carlo simulation (light grey bars).

Project Element G.8. Havasupai Translocation Feasibility

This project element is not funded until FY 2020.

Project Element G.9. Backwater Seining

The primary objective of this project element is to develop a long-term assessment of juvenile 

native and nonnative fishes in the Colorado River from Lees Ferry to Diamond Creek, including 

relative abundance metrics, species composition, size distribution, and the spatial distribution 

of backwater habitats. Seining represents a useful monitoring tool for assessment of both 

juvenile native (particularly age-0) and nonnative fish due to the high capture probability of the 

sampling gear and ability to easily sample across large spatial extents. Understanding the 

relationship between backwater catch rates and local population size in collaboration with 

Project Element G.6 could be particularly insightful. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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One backwater seining trip was conducted in 2019 (September 14-27). During this sampling 

trip, 4478 fish were captured. Native fishes captured included 351 HBC (17-366 mm TL), 2487 

flannelmouth sucker, 1326 speckled dace, and 124 bluehead sucker. Nonnative fishes were also 

captured including 74 fathead minnow, 17 plains killifish, and 5 rainbow trout. 

REFERENCES

Douglas, M.E., and Marsh, P.C., 1996, Population estimates/population movements of Gila 

cypha, an endangered cyprinid fish in the Grand Canyon region of Arizona: Copeia, v. 1996, no. 

1, p. 15-28, https://doi.org/10.2307/1446938.

Pearson, K.N., Kendall, W.L., Winkelman, D.L., and Persons, W.R., 2015, Evidence for skipped 

spawning in a potamodromous cyprinid, humpback chub (Gila cypha), with implications for 

demographic parameter estimates: Fisheries Research, v. 170, p. 50-59, 

https://doi.org/10.1016/j.fishres.2015.05.015.

Persons, W.R., Ward, D.L., and Avery, L.A., 2015, Standardized methods for Grand Canyon 

fisheries research 2015: U.S. Geological Survey, Techniques and Methods, book 2, chapter A12, 

19 p., http://pubs.er.usgs.gov/publication/tm2A12.

Van Haverbeke, D.R., Stone, D.M., Dodrill, M.J., Young, K.L., and Pillow, M.J., 2017, Population 

expansion of humpback chub in western Grand Canyon and hypothesized mechanisms: The 

Southwestern Naturalist, v. 62, no. 4, p. 285-292, https://doi.org/10.1894/0038-4909-62.4.285.

Yackulic, C.B., Dodrill, M.J., Dzul, M.C., Sanderlin, J., and Reid, J., in review, A need for speed in 

Bayesian population models—A practical guide to marginalizing and recovering discrete latent 

states: Ecological Applications.

Yackulic, C.B., Yard, M.D., Korman, J., and Van Haverbeke, D.R., 2014, A quantitative life history 

of endangered humpback chub that spawn in the Little Colorado River—Variation in movement, 

growth, and survival: Ecology and Evolution, v. 4, no. 7, p. 1006-1018, 

https://doi.org/10.1002/ece3.990.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[91]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Presentation

Integrated 

assessment of 

ecosystem 

management and 

hydropower 

generation in 

endangered 

species recovery

May 2019

Bair, L., Reimer, M., Donovan, P., Springborn, 

M., Bain, D., and Yackulic, C., 2019, Integrated 

assessment of ecosystem management and 

hydropower generation in endangered species 

recovery—presentation: Halifax, Nova Scotia, 

May 22-24, 2019, North American Association 

of Fisheries Economists Forum.

Presentation

Environmental 

drivers of 

humpback chub 

population 

dynamics in the 

Colorado River and 

Little Colorado 

River.

Sept 

2019

Dzul, M.C., Yackulic, C.B., Van Haverbeke, D.R., 

Kendall, W., and Winkelman, D., 2019, 

Environmental drivers of humpback chub 

population dynamics in the Colorado River and 

Little Colorado River—presentation: Flagstaff, 

Ariz. September 9-12, 2019, 15th Biennial 

Conference of Science and Management on the 

Colorado River Plateau and Southwest Region.

Presentation

Combining markrecapture and PIT 

antenna detection 

data to assess 

ecological drivers 

of spawning in an 

endangered desert 

fish

Oct 

2019

Dzul, M.C., Kendall, W., Winkelman, D., and 

Yackulic, C.B., 2019, Combining mark-recapture 

and PIT antenna detection data to assess 

ecological drivers of spawning in an endangered 

desert fish—presentation: Reno, Nev., Sept 29-

Oct 3, 2019, Joint Annual Conference of the 

American Fisheries Society and The Wildlife 

Society

Presentation

Using population 

models of 

interacting species 

to support 

decision makers: 

Taking the extra 

steps

Oct 

2019

Yackulic, C.B., 2019, Using population models of 

interacting species to support decision 

makers—Taking the extra steps —presentation: 

Reno, Nev., Sept 29-Oct 3, 2019, Joint Annual 

Conference of the American Fisheries Society 

and The Wildlife Society.

Presentation

A need for speed 

in Bayesian 

population 

models: A practical 

guide to 

marginalizing 

discrete latent 

states

Oct 

2019

Yackulic, C.B., Dodrill, M., Dzul, M., Sanderlin, 

J.S., and Reid, J.A. 2019, A need for speed in 

Bayesian population models—A practical guide 

to marginalizing discrete latent states—

presentation: Reno, Nev., Sept 29-Oct 3, 2019,

Joint Annual Conference of the American 

Fisheries Society and The Wildlife Society.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[92]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Journal 

article

The trophic 

ecology of a desert 

river fish 

assemblage: 

Influence of 

season and 

hydrologic 

variability

2019

Behn, K.E., and Baxter, C.E., 2019, The trophic 

ecology of a desert river fish assemblage—

Influence of season and hydrologic variability: 

Ecosphere, v. 10, no. 1, e02583, 

https://doi.org/10.1002/ecs2.2583.

Journal 

article

Safety in numbers: 

applying chanceconstrained 

dynamic 

programming to 

population 

viability analysis 

and adaptive 

management

FY 

2019

Donovan,P., Bair, L.S., Yackulic, C.B., and 

Springborn, M.R., 2019, Safety in numbers—

Applying chance-constrained dynamic 

programming to population viability analysis 

and adaptive management: Land Economics, v. 

95, no. 3, p. 435-453, 

https://doi.org/10.3368/le.95.3.435.

Journal 

article

Maintaining the 

long-term viability 

of the humpback 

chub in the Grand 

Canyon

FY

2019

Donovan, P., and Springborn, M.R., 2019, 

Maintaining the long-term viability of the 

humpback chub in the Grand Canyon: ARE 

Update, University of California, Giannini 

Foundation of Agricultural Economics, v. 22, no. 

5, p. 5-8, 

https://giannini.ucop.edu/publications/areupdate/issues/2019/22/5/maintaining-thelong-term-viability-of-the-humpbac/.

Journal 

article

An evaluation of 

sedatives for use 

in transport of 

juvenile 

endangered fishes 

in plastic bags

FY 

2020

Tennant, L.A., Vaage, B.M., and Ward, D.L., in 

press, An evaluation of sedatives for use in 

transport of juvenile endangered fishes in 

plastic bags: Journal of Fish and Wildlife 

Management, online, 

https://www.fwspubs.org/doi/abs/10.3996/03

2019-JFWM-016.

Journal 

article

Effects of 

disparate water 

temperatures and 

food bases on 

growth rates of 

humpback chub 

within the Little 

Colorado River, 

Arizona

FY 

2020

Stone, D.M., Pillow, M.J., Young, K.L., Van 

Haverbeke, D.R., and Walters, J.D., in review, 

Effects of disparate water temperatures and 

food bases on growth rates of humpback chub 

within the Little Colorado River, Arizona: North 

American Journal of Fisheries Management. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[93]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Journal 

article

What’s in the 

hump of the 

humpback chub

FY 

2020

Ward, D.L., and Ward, M.B., in press, What’s in 

the hump of the humpback chub?: Western 

North American Naturalist. 

Journal 

article

A need for speed 

in Bayesian 

population 

models: A practical 

guide to 

marginalizing and 

recovering 

discrete latent 

states

FY 

2020

Yackulic, C.B., Dodrill, M.J., Dzul, M.C., 

Sanderlin, J., and Reid, J., in review, A need for 

speed in Bayesian population models—A

practical guide to marginalizing and recovering 

discrete latent states: Ecological Applications.

Report

Spring 2019 

monitoring of 

humpback chub 

(Gila cypha) and 

other fishes above 

Lower Atomizer 

Falls in the Little 

Colorado River, 

Arizona

Aug 

2019

Stone, D.M., 2019, Spring 2019 monitoring of 

humpback chub (Gila cypha) and other fishes 

above Lower Atomizer Falls in the Little 

Colorado River, Arizona—trip report April 16-26 

and May 14-24, 2019: Flagstaff, Ariz., U.S. Fish 

and Wildlife Service, submitted to U.S. 

Geological Survey, Grand Canyon Monitoring 

and Research Center, Interagency acquisition 

no. G17PG00059, document no. USFWSAZFWCO-FL-19-04, 11 p.

Report

Mark-recapture 

and fish 

monitoring 

activities in the 

Little Colorado 

River in Grand 

Canyon from 2000 

to 2018

Jan 

2019

Van Haverbeke, D.R., Young, K.L., Stone, D.M., 

and Pillow, M.J., 2019, Mark-recapture and fish 

monitoring activities in the Little Colorado River 

in Grand Canyon from 2000 to 2019: Flagstaff, 

Ariz., U.S. Fish and Wildlife Service, submitted 

to U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center, document no. 

USFWS-AZFWCO-FL-19-02, 46 p.

Report

Fall 2019 

monitoring and 

translocation of 

humpback chub 

(Gila cypha) in the 

lower 13.57 km of 

the Little Colorado 

River, Arizona—

trip report for Sept 

17-27 and Oct 15-

25, 2019

Dec 

2019

Pillow, M.J., 2019, Fall 2019 monitoring and 

translocation of humpback chub (Gila cypha) in 

the lower 13.57 km of the Little Colorado River, 

Arizona—trip report for Sept 17-27 and Oct 15-

25, 2019: Flagstaff, Ariz., U.S. Fish and Wildlife 

Service, prepared for U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[94]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Report

Mark-recapture 

and fish 

monitoring 

activities in the 

Little Colorado 

River in Grand 

Canyon from 2000 

to 2019

Jan 

2020

Van Haverbeke, D.R., Young, K.L., Stone, D.M., 

and Pillow, M.J., 2020, in prep, Mark-recapture 

and fish monitoring activities in the Little 

Colorado River in Grand Canyon from 2000 to 

2019: Flagstaff, Ariz., U.S. Fish and Wildlife 

Service, submitted to U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center.

Report

Monitoring 

humpback chub in 

the Colorado 

River, Grand 

Canyon during fall 

2019

May 

2020

Van Haverbeke, D.R., Pillow, M.J., and Young, 

K.L., 2020, in prep, Monitoring humpback chub 

in the Colorado River, Grand Canyon during fall 

2019: Flagstaff Arizona Fish and Wildlife 

Conservation Office, submitted to U.S. 

Geological Survey, Grand Canyon Monitoring 

and Research Center.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[95]

Project H: Salmonid Research and Monitoring

SUMMARY

Protection of the endangered humpback chub (HBC) near the Little Colorado River remains as 

one of the highest priorities of the Glen Canyon Adaptive Management Program (GCDAMP), but 

a concurrent priority of the GCDAMP is to maintain a high-quality rainbow trout sport fishery 

upstream of Lees Ferry in Glen Canyon. As such, rainbow trout were an important component 

in the development of the Long-Term Experimental and Management Plan Environmental 

Impact Statement (LTEMP EIS) (U.S. Department of Interior, 2016a) and thus were a major 

consideration when developing Glen Canyon Dam (GCD) operations and experimental flows 

included in the selected alternative and LTEMP Record of Decision (ROD) (U.S. Department of 

Interior, 2016b). Experimental flows proposed in the LTEMP were designed to limit rainbow 

trout recruitment and dispersal out of Lees Ferry with a goal of maintaining the balance 

between the sport fishery and the downstream HBC population. However, ecosystems are 

dynamic and there has been a large increase in brown trout recruitment upstream of Lees Ferry 

over the past few years. Given this new development, it is unclear whether the expansion of 

brown trout will disrupt the balance between rainbow trout and endangered native fishes 

downstream, and further, to what degree flow manipulations can be used to manage both 

species concurrently.

This project is composed of four integrated elements: the first three (H.1 - H.3) are research 

elements, and the last (H.4) is a monitoring element.

Project Lead Mike Yard

Principal 

Investigator(s) (PI)

Mike Yard, USGS, GCMRC

Kim Dibble, USGS, GCMRC

Josh Korman, Ecometric Research

Charles Yackulic, USGS, GCMRC

Ted Melis, USGS, GCMRC

David Rogowski, AZGFD

Ted Kennedy, USGS, GCMRC

David Ward, USGS, GCMRC

Mike Dodrill, USGS, GCMRC

Dan Buscombe, USGS, GCMRC

Paul Grams, USGS, GCMRC

Tom Gushue, USGS, GCMRC

Email myard@usgs.gov

Telephone (928) 556-7377
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[96]

Project Element H.1. Experimental Flow Assessment of Trout Recruitment

Project H.1, as described in FY 2018-20 Triennial Work Plan (TWP), is a new research project 

called Trout Recruitment and Growth Dynamics (TRGD). The data collection and analyses are 

intended to determine the effects of LTEMP ROD flows on the recruitment of young-of-year 

(YOY) rainbow and brown trout in Glen Canyon, the growth rate of juveniles and adults, and 

dispersal of YOY trout from Glen Canyon. The other goal that is central to this study is to 

increase our understanding of the key factors (trout density and recruitment, prey availability, 

nutrients, etc.) that control the abundance and growth of the Glen Canyon trout population. 

This improved understanding could lead to the identification of policies other than flow 

manipulation that could benefit the Lees Ferry fishery and limit the downstream dispersal of 

rainbow trout to the Little Colorado River, as well as controlling brown trout should this species 

become more established in Glen Canyon. 

Study Objectives:

The objectives of project H.1 are to evaluate: 

1. The effects of higher and potentially more stable flows in spring and summer during 

equalization events on trout recruitment, growth, and dispersal. 

2. The effect of fall High-Flow Experiments (HFEs) on recruitment of trout in Glen Canyon, 

measured either through direct effects on juvenile survival or through reduced egg 

deposition in later years driven by reduced growth of trout (which reduces fecundity 

and rates of sexual maturation).

3. The effect of spring HFEs on trout recruitment, growth, and dispersal.

4. The effect of Trout Management Flows (TMFs) on rainbow and brown trout recruitment 

and dispersal. 

In 2018, a new sampling scheme was implemented in Glen Canyon where juvenile and adult 

trout (rainbow trout and brown trout) are sampled in two sub-reaches four times a year, and in 

a single sub-reach (-4 river mile - sub-reach 1C) five times a year. For purposes of study 

replication, three sub-reaches were established and assigned a 3-km length. Each sub-reach 

contains a combination of low-angle (spawning bars) and high-angle (talus slopes) shorelines; 

and in sum, these three sub-reaches represent 36% of the total shoreline length of Glen 

Canyon. The primary objective of this project is to assess the effectiveness of GCDAMP policy 

actions that influence rainbow trout abundance, survival, recruitment, and movement. This 

type of information has management implications, particularly downstream of Glen Canyon 

Dam where rainbow trout dynamics are central to understanding how to manage a functional 

sport fishery at Lees Ferry and its downstream relationship to native fish conservation in Grand 

Canyon. Secondly, owing to management concerns regarding brown trout establishment and 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[97]

population expansion in Glen Canyon, some efforts are being made to understand brown trout 

population dynamics. In addition to rainbow trout, all fishery data are used for informing the 

model development used for estimating population dynamics in brown trout. Per National Park 

Service (NPS) guidance, brown trout have been removed from the lowest sub-reach (-4 river 

mile - sub-reach 1C) and monitored in the upper two less populous sub-reaches. As of 2019, the 

brown trout removal effort was discontinued in lowest sub-reach 1C. Currently, brown trout are 

PIT tagged and released unharmed to monitor movement, growth, and to determine variation 

in capture probabilities, toward improving our understanding of other factors (flows, nutrients 

temperature, trout density, and size structure) that could be influencing these species in Glen 

Canyon. 

General Overview

In 2019, a total of 46,981 fish (44,113 rainbow trout; 2,584 brown trout; 273 flannel-mouth 

suckers; 7 green sunfish; 2 common carp, and 2 striped bass) were captured by electrofishing 

across five seasonal sampling trips conducted in Glen Canyon. Overall, brown trout catch rates 

(number of fish caught per km shoreline) pooled across all three study sub-reaches has 

continued to increase (Figure 1). The highest proportion of the catch for brown trout continues 

to be found in the lowest sub-reach 1C (BNT 2019 catch proportions: 1A – 34%; 1B – 11%; and 

1C – 55%). In 2019, brown trout catch rates showed a seasonal increase over the year likely due 

to changes in the catchability of small fish by electrofishing. Factors that are likely controlling 

the catchability remain uncertain (Korman and Yard, 2017a); however, fish size, fish density, 

spawning behavior, and elevated water temperatures, particularly in the fall season are likely 

factors responsible for the increase in brown trout catchability. 

Unlike the previous year, the removal efforts directed at brown trout within the lowest subreach 1C near -4 river mile has been discontinued. As previously reported, these removal 

efforts at this sub-reach or other sub-reaches upstream were considered ineffective at reducing 

brown trout densities; however, with the deemphasis of removal it enables the TRGD program 

to sample more effectively and provide resource managers and the GCDAMP with better 

informed inferences on the status and trends of this problematic species. In particular, the 

continued tagging effort has resulted in an increase in the proportion of brown trout with PITtags as well as secondary recaptures that are required to estimate abundance and vital rates 

such as growth, survival and movement. 

Presently, we can report on the relative condition factor for both trout species in Glen Canyon. 

The recent increase in the spring-summer condition factor strongly suggests that growing 

conditions are good for rainbow trout (large fish ≥ 275 mm Fork Length (FL)) and are higher 

now than in past years, particularly when contrasted with the years between 2012 and 2014 

(Figure 2). Notably though, the 2016 spring-summer condition factor for large rainbow trout 

attained the highest condition to date and has since trended downward over the last three 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[98]

years. One possible explanation for this trend could have been the initial reduction in trout 

densities following the collapse of the Glen Canyon rainbow trout population in 2014 that 

resulted in reduced intra-specific competition and by extension a relative increase in the 

availability of invertebrate prey. Now that the decline in rainbow trout population abundance 

has stabilized these fish have grown and are recruiting into the population. With the increase in 

size and overall biomass the demand for invertebrates may be increasing relative to prey 

availability. Nevertheless, the current condition factor for rainbow trout remains above the 

relative average since 2012. 

Figure 1. Brown trout seasonal catch rates (number of fish caught per km of shoreline) are based on electrofishing in Reach 1C, 

Glen Canyon, AZ. Size classes are assigned by fork length, small (≤ 200 mm), medium (201 – 400 mm), and large (> 400 mm). 

Brown trout catch rates are based on data from the 1st pass of a multiple-pass mark-recapture study.

In contrast, the relative condition factor for brown trout, particularly large sized fish remains 

much higher than observed for similarly sized rainbow trout. There are three major points that 

need to be emphasized: 1) brown trout densities have increased over time (Figure 1) and these 

increases appear to be independent of the factors that led to the collapse of the rainbow trout 

population (Korman and others, 2017), 2) no corresponding change in relative condition factor 

was observed between brown trout and rainbow trout, essentially the factors regulating trout 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[99]

condition are not the same, and 3) large brown trout condition remains consistently higher 

than rainbow trout, even during the time period that invertebrate prey production likely 

declined. The sharp difference in condition factor observed between these two trout species 

suggest food resources are being partitioned by the larger sized fish. It is likely that brown trout 

are subsisting more on fish (rainbow trout) rather invertebrate prey items.

Figure 2. Rainbow trout and brown trout relative condition factor using all electrofishing data collected in Glen Canyon, between 

April 2012 and September 2019. Points represent the relative condition factor of trout (size range, 300 mm fork length) in Glen 

Canyon between 2012 and 2018. Condition points show the median value, error bars show 80% credible interval. Seasonal 

sampling trips are symbolized by color: Green = spring (April), yellow = summer (July), red = late-summer (September), brown = 

fall (October), blue = winter (December and January). The solid colored points represent rainbow trout and open points represent 

brown trout. 

As proposed in the FY2018-20 TWP, considerable modifications were needed to be made to 

update the existing Glen Canyon trout population model (Korman and others, 2017). The 

modeling changes have been accomplished and we are able to report on some of the 

population dynamics of the rainbow trout population for the three sub-reaches. We are still 

unable to report on brown trout abundance until we acquire additional recapture information. 

Results suggest that there is spatial variability in the distribution of rainbow trout abundance 

(stratified by size-class), abundances among the three sub-reaches are: upstream (1A, Figure 3), 

middle (1B, Figure 4), and downstream (1C, Figure 5) sections of the study area.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[100]

Figure 3. Bar graph, primary y-axis shows rainbow trout abundance estimates (stratified by 5 size-classes) in the upper most 

sub-reach 1A in Glen Canyon, AZ. Size classes are assigned by fork length, 75-124 mm, 125-174 mm, 175-224 mm, 225-274 

mm, and > 275 mm. The secondary line graph represents the percentage of marked to unmarked fish in the local population in 

sub-reach 1A. 

Figure 4. Bar graph, primary y-axis shows rainbow trout abundance estimates (stratified by 5 size-classes) in the middle subreach 1B in Glen Canyon, AZ. Size classes are assigned by fork length, 75-124 mm, 125-174 mm, 175-224 mm, 225-274 mm, 

and > 275 mm. The secondary line graph represents the percentage of marked to unmarked fish in the local population in subreach 1B.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Figure 5. Bar graph, primary y-axis shows rainbow trout abundance estimates (stratified by 5 size-classes) in the lowest subreach 1C in Glen Canyon, AZ. Size classes are assigned by fork length, 75-124 mm, 125-174 mm, 175-224 mm, 225-274 mm, 

and > 275 mm. The secondary line graph represents the percentage of marked to unmarked fish in the local population in subreach 1C.

H.1.1. Weekend Stable Flows (Bug Flows) in Spring and Summer 

The analytical approach we intend to use will require some additional years of data collected 

with and without flow treatments to determine how trout (rainbow trout and brown trout) 

dynamics in Lees Ferry respond to weekend stable flows designed to improve aquatic insect egg 

survival (Bug Flows) during spring and summer. Late-spring and summer trout growth will be 

used as the primary parameter to make comparisons and contrasts as the trout population 

responds to the flow effects between years. At the earliest, we will begin to report on trout 

growth in response to Bug Flows after the 2019 data set is collected. 

H.1.2. Fall High-Flow Experiments

To date, five fall HFEs have been conducted between 2012 and 2019 (Figure 6). If there is a flow 

effect related to HFEs, we hypothesize that the likely mechanism acts directly on the benthic 

invertebrate community and secondarily on trout by reducing the invertebrate prey available 

following the flow disturbance. Contrasts made between flow events (with and without HFEs) is 

a necessary requirement to determine flow effect; unfortunately, there are only three years 

over this time-period without HFEs (2015, 2017, and 2019). Poor fall-winter growth was 

observed in three consecutive HFE years (2012-2014) across all catchable sized fish. These three 

consecutive HFE years were accompanied also with declining trout growth that was associated 

with the ultimate collapse in the rainbow trout population (late-2014). This trout population 

collapse could be independent of HFE effect. Note that there was a progressive annual drop in 

soluble reactive phosphorus (SRP; B. Deemer pers. comm.) over the first three consecutive HFEs 
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that is strongly correlated with trout decline that may explain trout population declines. The 

effect of HFEs versus SRP on reduced trout abundance, recruitment and growth cannot 

currently be determined. 

Poor growth in September-October 2012 occurred before the first fall HFE was implemented, 

suggesting that other factors (low SRP or high trout density, refer to Figure 2) might be 

depressing growth over the fall-winter period (similar conditions were repeated in 2013 and 

2014). In fall of 2014, the occurrence of high trout growth before HFE and low growth 

immediately after HFE in the winter of 2015 does suggest a potential HFE effect in that year. 

However, the current population biomass has continued to decline irrespective of flow events. 

Since the trout population collapse, we compared seasonal growth differences based on weight 

change between pre- and post-flood periods and between years with and without HFEs and 

reported that there might have been an HFE effect on monthly growth rates of rainbow trout (≥ 

200 mm FL). The two years with HFEs (2016 and 2018) show only slight reductions in fall growth 

for rainbow trout within the HFE interval. In contrast, 2017 showed no reduction in growth, 

particularly for the fall and winter seasons. We have yet to complete the data collection effort 

for 2019 or analyze the growth interval for the other accompanying year without an HFE.

Figure 6. Bar-graph, primary y-axis, is the estimated mean monthly growth rate (g/month, positive or negative) of rainbow trout 

(300 mm FL) in Glen Canyon between April, 2012 and February, 2019. Monthly growth rates are each estimated across the 

seasonal interval between sampling trips. Each growth interval has been assigned a color: Spring = yellow; Summer = red, Fall = 

brown, and Winter = blue. 
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H.1.3. Spring High-Flow Experiments

No spring High-Flow Experimental treatment has been implemented to date.

H.1.4. Trout Management Flows

Trout Management Flows are intended to reduce the probability of large recruitment events of 

young rainbow trout in Glen Canyon. High levels of recruitment can contribute to poor growth 

and population collapse which has negative effects on the trout fishery in Glen Canyon (e.g., 

2005-06, 2014-15) (Korman and others, 2017). Also, high levels of recruitment in Glen Canyon 

can increase the number of trout dispersing into Marble Canyon and lead to higher trout 

abundance at the Little Colorado River with potential negative effects on HBC (e.g., 2007-09, 

2011-14) (Korman and others, 2016; Yard and others, 2016). The basic premise of the TMFs is 

that newly emerged trout (age-0) are small and fragile and are limited to very shallow and low 

velocity areas near the immediate shoreline. Because of the microhabitat requirements, newly 

emerged fish are likely to move into habitat inundated by elevated and stable flows (Korman 

and others, 2011). Under years of high recruitment and once habitat is occupied, if elevated 

stable flows (flow equalization periods) were to be rapidly reduced age-0 fish would likely be 

stranded in low-angle habitats. Unfortunately, there are a number of uncertainties that remain 

about the design of the TMFs. These include questions regarding: peak and withdrawal flow 

discharge levels, down-ramp rate, flow treatment frequency, quantity of available low-angle 

habitat, period of flow stability required for colonization, fish-size dependent response, efficacy 

of action due to compensation, hydropower costs, and others. 

The optimization approach that is being used to design and evaluate future TMFs are: 

1. Stranding studies literature review, to be completed in FY 2020;

2. Determine the relationships between shoreline slope and discharge and other physical 

spatial attributes (discussed in June/July 2019 presentation);

3. Conduct GIS and hypsometric analysis to quantify the area of inundation, substrate 

types, vegetative cover, and velocity, to be completed in FY 2020;

4. A TRGD study to assess annual recruitment of YOY (< 75 mm FL), to be completed in FY 

2020; and

5. The development of contingency plans for sampling, should a TMF be implemented in 

the outlying years of this workplan. These plans include: additional mark-recapture 

studies, pre- and post-flood response to age-0 trout, and TRGD study to assess annual 

recruitment of YOY (inter- and intra-annual comparisons with and without a TMF). Final 

analysis and deliverables are to follow completion of the FY 2018-20 TWP study period. 

That methodology is discussed in Korman and others, 2009.
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Project Element H.2. Rainbow and Brown Trout Recruitment and Outmigration Model

The primary focus of this research was development of the brown trout model for the brown 

trout workshop report (Runge and others, 2018). The model uses both mark-recapture and 

catch per unit effort (CPUE) data to estimate brown trout recruitment, growth and survival. This 

model served as the basis for comparing evidence for various hypothesized drivers of recent 

increases in brown trout. We then coupled this model with previously developed models of 

rainbow trout and HBC population dynamics to simulate the potential impacts of different 

management scenarios. In FY 2019, we explored the role that priors played in model output. 

(Priors is a term commonly used in Baysean statistics, where a prior is defined as the probability 

distribution of an uncertain quantity/parameter before empirical data is accounted for in the 

model). Estimates of abundance and vital rates were sensitive to priors because mark-recapture 

data remains sparse. While mark-recapture data are now becoming available, the limited 

investment in this item and the diminished capacity for data management and analysis has 

slowed additional progress. 

Project Element H.3. Using Early Life History and Physiological Growth Data from Otoliths to 

Inform Management of Rainbow Trout and Brown Trout populations in Glen Canyon

The objective of this project is to use life history and growth information contained within 

rainbow and brown trout otoliths to inform the management of trout populations in Glen 

Canyon. Projects in this sub-element include: 1) collecting a limited number of age-0 rainbow 

trout to obtain early life history data to continue to inform existing rainbow trout recruitment 

models; 2) collecting age-0 brown trout to determine hatch and emergence dates to inform the 

timing of future experimental floods; and 3) collecting age-0 brown trout after experimental 

floods (e.g., TMFs, HFEs) to determine their immediate growth response to flow perturbations 

relative to brown trout survival. 

Building on sample collections from FY 2018, we continued to obtain age-0 brown trout 

samples in FY 2019 in collaboration with sampling conducted on quarterly TRGD trips with an 

end goal of estimating hatch and emergence dates via back-calculation for brown trout in the 

Glen Canyon reach. To date approximately 35 age-0 samples have been collected across six 

trips. In FY 2020 we will attempt to increase our sample size during spring to summer sampling 

trips, after which all samples will be processed, and models developed that estimate life history 

parameters for this species. Due to insufficient sediment inputs HFEs were not implemented in 

fall 2017 (FY 2018) nor fall 2019 (FY 2020). 

Project Element H.4. Rainbow Trout Monitoring in Glen Canyon

The cold tailwater downstream of Glen Canyon Dam is an important rainbow trout recreational 

fishery. The goal of monitoring in Glen Canyon is to monitor the status and trends of rainbow 

trout abundance and distribution in the Colorado River reach between Glen Canyon Dam and 
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Lees Ferry, and to monitor angler use of the Lees Ferry fishery. Arizona Game and Fish 

Department (AZGFD) used three approaches to monitor the Lees Ferry fishery: 1) boat 

electrofishing, 2) angler surveys (creel) including the use of a game camera, and 3) a pilot 

citizen science program with angling guides to measure fish caught by their clients.

Boat electrofishing is utilized to obtain a representative sample of the fish community within 

this reach. The general objectives are to monitor the trout fishery and gather long-term trend 

data on relative abundance using CPUE methods, population structure (size composition), 

distribution, growth rate, relative condition and overall recruitment to reproductive size. These 

data are useful in monitoring overall trends in the trout population but may not allow 

assessments of short-term responses to specific dam operations. In addition, we conducted one 

night of nonnative sampling trip within this reach to detect warm water nonnative species 

during summer and autumn sampling trips (Project Element I.2). 

To monitor the status of the Lees Ferry fishery and estimate angler use, AZGFD conducted 

angler surveys to obtain a representative sample of the recreational angling community at Lees 

Ferry. AZGFD uses a stratified random sampling approach to select a subset of days for 

interviews of both boat and shoreline anglers. Information obtained includes, but is not limited 

to, catch rates, gear type, species composition, harvest, and satisfaction with angling 

experience. Since June 2015, a game camera has been installed at Lees Ferry to record images 

of the boat launch area and provide a better estimate of boat anglers for the days and hours 

when a technician is not present.

The pilot citizen science program is an attempt to quantify the exact size of the fish captured by 

anglers. This is a metric that was included in the Lees Ferry fisheries management plan but 

cannot be determined from angler surveys.

Summary of Progress

AZGFD completed three monitoring trips in 2019, sampling 120 sites and capturing 3,098 fish 

(excluding the nonnative sampling). Rare nonnatives captured during our normal monitoring 

were one bluegill sunfish, two common carp, and 219 brown trout. We conducted angler 

interviews on 60 days (as of the end of October), and have data from 32 unique trips from the 

citizen science project. The monitoring activities funded include: one spring electrofishing trip 

(March 11-13, 2019, 40 sample sites), one summer electrofishing trip (July 8-11, 2019, 40 

sample sites, plus an additional 11 sites for nonnatives), one autumn electrofishing trip 

(September 23-26, 2019, 40 sample sites, plus an additional 10 sites for nonnatives), angler 

surveys—six days each month (four weekend days, and two weekdays), and the citizen science 

project (two-four guides participating, resulting in 32 days of data).
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[106]

H.4.1. Electrofishing

Rainbow trout continue to dominate the fish community within the Lees Ferry reach, 

comprising 92.1% of the catch (standard electrofishing), with brown trout comprising 7.07% of 

the catch. However, for autumn only data, rainbow trout were 88.3% of the catch and brown 

trout comprised 9.8%. This is a dramatic increase in relative abundance of brown trout 

compared to all previous years (Figure 7). Rainbow trout have maintained a self-sustaining 

population since the mid-1990s. Relative abundance, as measured by electrofishing CPUE, has 

fluctuated greatly since AZGFD began standardized sampling in 1991 (Figure 8). Rainbow trout 

CPUE was the highest ever recorded in 2011–2012 but declined from 2012 to 2016. Rainbow 

trout CPUE in 2019 was lower than that observed in 2018 (2.65 vs. 4.15 fish/minute), with most 

of the fish captured attributable to YOY rainbow trout (< 152 mm TL). Rainbow trout YOY in the 

fall catch was 49% (compared to 60% in 2018), with a CPUE of 1.36 fish/hour (lower than 2018 

at 2.41 fish/minute). After two consecutive years of relatively high CPUE of YOY, a lower CPUE is 

a positive indicator for this rainbow trout population, as too many YOY fish can lead to too 

much fish biomass in the system for the available food base.

Figure 7. Average catch per unit effort (fish/minute) of brown trout captured during Arizona Game and Fish Department’s 

monitoring at Lees Ferry by year.
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The percent of large rainbow trout in the system has declined as has the median size of 

reproductively active fish. This suggests there were more rainbow trout in the system (based on 

higher CPUE) than the system was able to maintain during 2011-2014, from a limited food base. 

Relative fish condition for rainbow trout reached a record low (~ 0.8) in fall of 2014 and has 

been increasing since then. Condition of rainbow trout in 2019 has been good with the average 

condition above 0.90 for all size classes across all sampling trips. During our summer monitoring 

it was greater than 1.0 for two of the three size classes (152-305 mm total length (TL) and 306-

405 mm TL). It was 0.99 for the largest size class (> 405 mm TL).

Figure 8. Average catch per unit effort (fish/minute) of rainbow trout at Lees Ferry from Arizona Game and Fish Department’s 

standardized monitoring (electrofishing) by size class and year.
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[108]

H.4.2. Angler Surveys (Creel)

For angling surveys, we use a calendar year for summarizing data on angler use, CPUE, and 

other metrics. At the time of this report (December 2019) we were still collecting angling data 

and results based on data from January through October (60 creel days, 930 boat anglers, 221 

walk-in anglers). Boat angler CPUE and 95% confidence intervals for rainbow trout from January 

through October was 0.88 fish/hr [0.83, 0.94], while for walk-in anglers it was 0.60 fish/hr [0.39, 

0.81]. CPUE in 2019 was essentially the same as last year, and is lower than the AZGFD’s goal 

for the fishery of 1.0 fish/hr. We also saw an increase in angler reported captures of brown 

trout. Up to the end of October 2019, AZGFD recorded 87 brown trout captured during angler 

surveys, while in 2018 anglers only captured 47. 

As AZGFD is still collecting angler use data, data from 2018 is presented (Figure 9). We 

estimated a yearly relative angler use of 7,347 anglers in 2018 of which 4,705 (95% CI [4,037, 

5,373]) were boat anglers and 2,642 (95% CI [2,213, 3,072]) were walk-in anglers. Angler use 

was similar to that in 2017 for boat anglers (4,593 95% CI [4,029, 5,158]), and walk-in anglers 

(2,432 (95% CI [2,065, 2,800]). 

Figure 9. Estimated yearly relative angler use at Lees Ferry from AZGFD angler survey data.
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[109]

H.4.3. Citizen Science Program

In 2019, three guides participated in the citizen science program, and we received length 

measurements for 689 rainbow trout captured by 55 anglers over 28 unique fishing trips. 

Preliminary results show that we are not meeting AZGFD’s goals for size structure of fish 

captured by anglers in the Lees Ferry fishery – only 21% of anglers caught at least one 14-inch

rainbow trout per hour, and only four rainbow trout over 20 inches were recorded. The average 

size of fish measured was 13 inches ± 2.7” (mean ± SD), and the largest fish measured was 20

inches.

REFERENCES

Korman, J., Kaplinski, M., and Melis, T.S., 2011, Effects of fluctuating flows and a controlled 

flood on incubation success and early survival rates and growth of age-0 rainbow trout in a 

large regulated river: Transactions of the American Fisheries Society, v. 140, no. 2, p. 487-505, 

https://doi.org/10.1080/00028487.2011.572015.

Korman, J., Yard, M., Walters, C.J., and Coggins, L.G., 2009, Effects of fish size, habitat, flow, and 

density on capture probabilities of age-0 rainbow trout estimated from electrofishing at 

discrete sites in a large river: Transactions of the American Fisheries Society, v. 138, no. 1, p. 58-

75, https://doi.org/10.1577/T08-025.1.

Korman, J., and Yard, M.D., 2017, Effects of environmental covariates and density on the 

catchability of fish populations and interpretation of catch per unit effort trends: Fisheries 

Research, v. 189, p. 18-34, https://doi.org/10.1016/j.fishres.2017.01.005.

Korman, J., Yard, M.D., and Kennedy, T.A., 2017, Trends in rainbow trout recruitment, 

abundance, survival, and growth during a boom-and-bust cycle in a tailwater fishery: 

Transactions of the American Fisheries Society, v. 146, no. 5, p. 1043-1057, 

https://doi.org/10.1080/00028487.2017.1317663.

Korman, J., Yard, M.D., and Yackulic, C.B., 2016, Factors controlling the abundance of rainbow 

trout in the Colorado River in Grand Canyon in a reach utilized by endangered humpback chub: 

Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 1, p. 105-124, 

https://doi.org/10.1139/cjfas-2015-0101.

Runge, M.C., Yackulic, C.B., Bair, L.S., Kennedy, T.A., Valdez, R.A., Ellsworth, C., Kershner, J.L., 

Rogers, R.S., Trammell, M., and Young, K.L., 2018, Brown trout in the Lees Ferry reach of the 

Colorado River—Evaluation of causal hypotheses and potential interventions: U.S. Geological 

Survey Open-File Report 2018-1069, 83 p., https://doi.org/10.3133/ofr20181069.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[110]

U.S. Department of Interior, 2016a, Glen Canyon Dam Long-term Experimental and 

Management Plan final Environmental Impact Statement (LTEMP FEIS): U.S. Department of the 

Interior, Bureau of Reclamation, Upper Colorado Region, National Park Service, Intermountain 

Region, online, http://ltempeis.anl.gov/documents/final-eis/.

U.S. Department of Interior, 2016b, Record of Decision for the Glen Canyon Dam Long-Term 

Experimental and Management Plan final Environmental Impact Statement (LTEMP ROD): Salt 

Lake City, Utah, U.S. Department of the Interior, Bureau of Reclamation, Upper Colorado 

Region, National Park Service, Intermountain Region, 196 p., 

http://ltempeis.anl.gov/documents/docs/LTEMP_ROD.pdf.

Yard, M.D., Korman, J., Walters, C.J., and Kennedy, T.A., 2016, Seasonal and spatial patterns of 

growth of rainbow trout in the Colorado River in Grand Canyon, Arizona: Canadian Journal of 

Fisheries and Aquatic Sciences, v. 73, no. 1, p. 125-139, https://doi.org/10.1139/cjfas-2015-

0102.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Trout management 

flows—A review of 

data, research results,

and information needs

June

2019

Korman, J., and Yard, M., 2019 Trout management 

flows—A review of data, research results, and 

information needs: Phoenix, Ariz., June 11-12, 2019, 

TWG GCDAMP, Arizona Department of Water 

Resources.

Presentation

Colorado River 

ecosystem responses 

to the 2018 Bug Flow 

experiment from Glen 

Canyon Dam

Sept

2019

Kennedy, T.A., Muehlbauer, J.D., and Rogowski, D.L., 

2019, Colorado River ecosystem responses to the 2018 

Bug Flow experiment from Glen Canyon Dam: Flagstaff, 

Ariz., Sept 9-12, 2019, 15th Biennial Conference of 

Science Management on the Colorado Plateau and 

Southwest Region.

Report

Status of the Lees 

Ferry rainbow trout 

fishery—2018 annual 

report

FY 2019

Boyer, J.K., and Rogowski, D.L., 2019, Status of the Lees 

Ferry rainbow trout fishery—2018 annual report: 

Phoenix, Arizona Game and Fish Department, 40 p., 

https://www.researchgate.net/publication/333634720

_STATUS_OF_THE_LEES_FERRY_RAINBOW_TROUT_FIS

HERY_2018_ANNUAL_REPORT.
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Project I: Warm-Water Native and Nonnative Fish Research and 

Monitoring

Project Lead David Ward

Principal 

Investigator(s) (PI)

David Ward, USGS, GCMRC

David Rogowski, AZGFD

Kirk Young, USFWS

Kim Dibble, GCMRC

Charles Yackulic, GCMRC

Email dlward@usgs.gov

Telephone (928) 556-7280

SUMMARY

Project I.1. System-wide Native Fish and Invasive Aquatic Species Monitoring

Goals and Objectives

The primary goal of the system wide monitoring program is to monitor the status and trends of 

native and nonnative fishes in the Colorado River from Lees Ferry, AZ to Lake Mead. Arizona 

Game and Fish Department (AZGFD) randomly samples selected reaches and sites throughout 

the Colorado River in Grand Canyon using boat electrofishing, baited hoop nets, and angling to 

obtain a representative sample of the fish assemblage. Species composition and relative 

abundance using catch per unit effort (CPUE) methods can be used to interpret trends in 

abundance and distribution of native and nonnative fish throughout the Grand Canyon.

Summary of Progress

AZGFD completed three mainstem sampling trips in 2019. On two spring trips (April 3-15, May 

18-30) 4,331 fish were captured at 435 electrofishing sites, 2,471 fish in 216 hoop net sets, and 

12 fish angling on 25 nights. During the fall sampling trip (Oct 24-28) from Diamond Creek to 

Pearce Ferry Rapid, 1,256 fish were captured at 72 electrofishing sites, and 1,482 fish in 61 

hoop net sets, and eight fish angling on four nights. 

Most fish captured were flannelmouth sucker (Table 1; 55% of electrofishing catch, 71% of 

hoop net catch). AZGFD captured 652 humpback chub in baited hoop nets set from Lees Ferry 

to Pearce Ferry Rapid. Since monitoring began in 2000, relative abundance of most nonnative 

species has decreased, and relative abundance of native species has increased (Figure 1, 

Rogowski and others 2018). 
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Table 1. 2019 Catch summaries for AZGFD mainstem monitoring.

Native Species Nonnative Species

Flannelmouth sucker 5,879 Rainbow trout 1,691

Speckled dace 959 Fathead minnow 48

Humpback chub 652 Brown trout 35

Bluehead sucker 259 Common carp 13

Unidentified sucker 1 Red shiner 10

Striped bass 3

Native Hybrids Channel catfish 1

Bluehead/flannelmouth 6 Green sunfish 1

Flannelmouth/razorback 3 Yellow bullhead 1

Total 7,759 Total 1,803

Figure 1. Electrofishing catch per unit effort (CPUE; fish/hour) of nonnative (panels A-C) and native (panels D-F) fishes in the 

Colorado River in Grand Canyon, 2000-2019.
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Asian Fish Tapeworm Monitoring

Asian fish tapeworm monitoring was conducted in conjunction with U.S. Fish and Wildlife 

Service spring fish monitoring efforts in the Little Colorado River. Forty-one humpback chub 

(77-302 mm total length (TL)) were held in a collapsible tank on the river bank at Boulders 

Camp (river kilometer 1.8) and treated with Praziquantel at 6 mg/l for 48-hrs before being 

released (Ward 2007). Twenty-six tapeworm were detected in 13 individual fish (range 1-11 

tapeworms per fish; Figure 2). Relatively low incidence of infestation and the magnitude of 

infestation per fish from 2015-2019 appears lower than in assessments conducted from 2005-

2007. 2D Graph 1

Year

2004 2006 2008 2010 2012 2014 2016 2018 2020

% of humpback chub infested

0

20

40

60

80

100

Figure 2. Percentage of hump Col 2 back chub sampled from 2005-2019 from the Little Colorado River at Boulders Camp that were 

infested with at least one Asian fish tapeworm.

Project I.2. Improve Early Detection of Warm-Water Invasive Fish

Invasive Aquatic Species Monitoring in Lees Ferry

To improve early detection of rare, nonnative species in Glen Canyon (Project Element I.2) 

AZGFD conducts rare-nonnative monitoring twice a year (summer and autumn). 

Goals and Objectives

The primary goal of the rare nonnative monitoring is to provide early detection of rare 

nonnative fish species in Glen Canyon. We target areas where rare nonnatives have been 

caught before and warmer areas such as spring inflows and sloughs/backwaters. Data collected 
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from our standard monitoring (Project Element H.4) and rare nonnative targeting efforts 

provide some information on long-term status and trends of rare nonnatives, including brown 

trout, found in this reach of the Colorado River. 

Summary of Progress

During AZGFD’s rare nonnative sampling, 61 rare nonnative fish were captured including: 30

common carp, 10 brown trout, 7 green sunfish, 3 walleye, and 1 smallmouth bass. Rare 

nonnative fish captured during AZGFD’s standardized sampling (Project Element H.4) in Lees 

Ferry consisted of 219 brown trout, 2 common carp and 1 bluegill sunfish. 

eDNA Sampling

Water samples to evaluate the use of environmental DNA (eDNA) technology were not 

collected in 2019 because funding was not approved in the Work Plan for FY 2019. This new 

technology may allow scientists to detect both the presence and relative abundance of aquatic 

invasive species moving upstream out of Lake Mead into western Grand Canyon. In FY 2019 we 

purchased 4 GeopumpTM II eDNA sampling pumps with GCDAMP funds in preparation for a MayJune 2020 sampling trip. Grand Canyon Monitoring and Research Center (GCMRC) successfully 

obtained additional non-AMP funding through the FY 2020-2021 USGS-USFWS Science Support 

Partnership (SSP) Program to fund costs associated with this project that were not granted in 

the Work Plan, including the cost of a Principal Investigator and technician salaries. GCMRC also 

obtained additional non-AMP funding from the Bureau of Reclamation (Reclamation) Phoenix 

Area Office to fund the cost of the river trip. Reclamation also provided funds directly to the US 

Forest Service, Rocky Mountain Research Station to fund the cost of sample preparation and 

eDNA analysis for this project. In total, an additional $158,270 was obtained to be used along 

with the $7,438 in GCDAMP funds budgeted in the FY 2018-20 TWP to complete this project. 

Water samples for eDNA analysis will be collected in FY 2020 to detect the presence and 

distribution of four species of interest; a potential fifth species will be assessed if funding 

allows. Due to logistical constraints associated with joining an existing AZGFD fish monitoring 

trip, we obtained the additional funding to pay for a separate river trip that is longer in length 

which will allow us to move at our own pace without delaying AZGFD sampling.

Project I.3. Assess the Risks Warm-water Nonnative Fish Pose to Native Fish

Goals and Objectives

The goal of this project is to evaluate impacts of invasive nonnative warm-water fish on 

humpback chub in both laboratory and field settings. Our objective is to quantify the relative 

risks that each warm-water predator poses to native fish. The risk of predation on humpback 

chub by existing predators such as channel catfish and green sunfish is significant, but impacts 

have not been quantified. The potential impact of smallmouth bass, which are not yet 

established in the CRe but may become established, has also not been quantified. Our goal is to 
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evaluate the relative predation vulnerability of humpback chub to these predatory warm-water 

species using methods similar to those employed for past trials with rainbow and brown trout

(Ward and Morton-Starner, 2015). Standardized methods allow comparison of relative 

predation risks. These data will allow managers to understand which warm-water invasive 

fishes are the most detrimental to humpback chub populations so that management efforts can 

be focused on those species that are the most problematic.

Summary of Progress

In 2019, field efforts focused on marking channel catfish within the Little Colorado River (LCR). 

We completed four angling trips within the lower 13 km of the LCR (May - June). Eighty-two 

channel catfish were caught and tagged with Passive Integrated Transponder (PIT) tags with 

109 hours of angling effort (0.75 fish/hour). Channel catfish were widely distributed throughout 

the lower 13 km of the LCR and typically aggregated in deeper pools with large boulders. 

Although rarely caught with other sampling methods, channel catfish were very susceptible to 

angling with earthworms. Only two previously tagged fish were recaptured, so no population 

estimate can be calculated at this time, but the relatively high numbers of fish caught does 

indicate potential impacts to native fish may be larger than expected. The population is 

dominated by large adults with the average size being 408 mm TL (Range = 261-630 mm TL;

Figure 3). Marking sufficient fish for population estimation may be challenging and require 

additional angling effort.

Channel Catfish in the Little Colorado River 2019

Total Length (mm)

100 200 300 400 500 600

Frequency

0

2

4

6

8

10

Figure 3. Length frequency histogram for 82 channel catfish angled from the Little Colorado River in 2019.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[116]

In FY 2019, laboratory evaluations of predation risk focused on assessing the potential impacts 

of channel catfish and green sunfish on juvenile humpback chub. Both channel catfish and 

green sunfish are currently found in the LCR and in the mainstem Colorado River downstream 

of Glen Canyon Dam. Although their populations numbers are low, they are known to be 

detrimental to native fish populations in other areas of the Colorado River Basin. In general, 

green sunfish have been found to be behaviorally more predacious than other predators we 

have previously tested in laboratory trials and appear to be only limited by gape as far as their 

ability to capture and consume juvenile humpback chub, as indicated by the steepness of the 

survival curves (Figure 4).

Figure 4. Predicted age-0 humpback chub survival as green sunfish size increases (A), and chub size increases (B). Predicted 

probability of survival calculated using JMP Prediction Profiler, with a single variable altered in each panel. Results are based on 

replicated 24-hr laboratory trials. Grey lines represent 95% confidence intervals.

REFERENCES

Rogowski, D.L., Osterhoudt, R.J., Mohn, H.E., and Boyer, J.K., 2018, Humpback chub (Gila cypha) 

range expansion in the western Grand Canyon: Western North American Naturalist, v. 78, no. 1, 

article 4, https://scholarsarchive.byu.edu/wnan/vol78/iss1/4.

Ward, D.L., 2007, Removal and quantification of Asian tapeworm from bonytail chub using 

Praziquantel: North American Journal of Aquaculture, v. 69, no. 3, p. 207-210, 

https://doi.org/10.1577/A06-054.1.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[117]

Ward, D.L., and Morton-Starner, R., 2015, Effects of water temperature and fish size on 

predation vulnerability of juvenile humpback chub to rainbow trout and brown trout: 

Transactions of the American Fisheries Society, v. 144, no. 6, p. 1184-1191, 

https://doi.org/10.1080/00028487.2015.1077160.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Presentation

Effects of high flow 

events on warmwater native and 

nonnative fishes

April 

2019

Ward, D.L., 2019, Effects of high flow events 

on warm-water native and nonnative fishes—

presentation: Phoenix, Ariz., April, 2019, Glen 

Canyon Dam Adaptive Management Program 

Annual Reporting Meeting.

Presentation

Development of 

new ammoniabased piscicides for 

control of invasive 

aquatic species

Oct 

2019

Ward, D.L., 2019, Development of new 

ammonia-based piscicides for control of 

invasive aquatic species—Poster 

presentation: Montreal, QC Canada, Oct 27-

31, 2019, 21st International Conference on 

Aquatic Invasive Species, 

https://www.icais.org/pdf/abstracts_2019.pd

f.

Presentation

Interactions 

between native 

and nonnative 

fishes in Arizona

Nov 

2019

Ward, D.L., 2019, Interactions between native 

and nonnative fishes in Arizona—

presentation: Flagstaff, Northern Arizona 

University, Forestry Department, Ecological 

Restoration 382. 

Presentation

Science of 

biological threats: 

Aquatic Invasive 

Species and 

Disease

Nov 

2019

Ward, D.L., 2019, Science of biological 

threats—Aquatic Invasive Species and 

Disease—presentation: Flagstaff, Ariz., Nov, 

2019, Southwest Biological Science Center, 

Ecosystems Management Area executive 

leadership science strategy meeting. 

Journal article

What 

environmental 

conditions reduce 

predation 

vulnerability for 

juvenile Colorado 

River native fishes? 

June 

2019

Ward, D.L., and Vaage, B.M., 2019, What 

environmental conditions reduce predation 

vulnerability for juvenile Colorado River 

native fishes?: Journal of Fish and Wildlife 

Management, v. 10, no. 1, p. 196-205, 

https://doi.org/10.3996/042018-JFWM-031.

Journal article

Native fish 

recovery in a highly 

regulated river

Nov 2019

submitted

Boyer, J., and Rogowski, D.R., in review,

Native fish recovery in a highly regulated 

river: submitted to Transactions of the 

American Fisheries Society.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[118]

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Journal article

Effects of body size 

on vulnerability of 

young of year 

roundtail chub to 

predation by 

smallmouth bass 

April 

2020

Tennant, L.A., and Ward, D.L., in prep, Effects 

of body size on vulnerability of young of year 

roundtail chub to predation by smallmouth 

bass.

Report

Colorado River Fish 

Monitoring in 

Grand Canyon, 

Arizona – 2018 

Annual Report

March 

2019

Rogowski, D.L., and Boyer, J.K., 2018, 

Colorado River fish monitoring in Grand 

Canyon, Arizona—2018 annual report: 

Phoenix, Ariz., Arizona Game and Fish 

Department, submitted to U.S. Geological 

Survey, Grand Canyon Monitoring and 

Research Center, 45 p., 

https://www.researchgate.net/publication/3

33634628_Colorado_River_Fish_Monitoring_i

n_the_Grand_Canyon_Arizona2018_Annual_Report.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[119]

Project J: Socioeconomic Research in the Colorado River Ecosystem

SUMMARY

The overall objective of Project J is to identify preferences for, and values of, downstream 

resources and evaluate how preferences and values are influenced by Glen Canyon Dam (GCD) 

operations. In addition, Project J is integrating economic information with data from long-term 

and ongoing physical and biological monitoring and research studies led by the Grand Canyon 

Monitoring and Research Center (GCMRC). This integration will lead to the development of 

tools for scenario analysis that improve the ability of the Glen Canyon Dam Adaptive 

Management Program (GCDAMP) to evaluate and prioritize management actions, monitoring, 

and research.

This project addresses the tribal, humpback chub, hydropower and energy, and rainbow trout 

fishery Long-Term Experimental and Management Plan (LTEMP) Environmental Impact 

Statement resource goals by addressing the LTEMP Record Of Decision objective to respect the 

“interests and perspectives of American Indian Tribes” and “determine the appropriate 

experimental framework that allows for a range of programs and actions, including ongoing and 

necessary research, monitoring, studies, and management actions in keeping with the adaptive 

management process.” These studies also attempt to “maintain or increase Glen Canyon Dam 

electric energy generation, load following capability, and ramp rate capability, and minimize 

emissions and costs to the greatest extent practicable, consistent with improvement and longterm stability of downstream resources.”

Project Element J.1. Tribal Perspectives for, and Values of, Resources Downstream of Glen 

Canyon Dam: Tribal Member Population Survey

Conducting socioeconomic studies of Tribal preferences for, and values of, resources 

downstream of Glen Canyon Dam is an important research element of the GCDAMP. Tribal 

socioeconomic studies allow insight into the preferences of Tribal stakeholders concerning 

resources management downstream of Glen Canyon Dam, the underlying reasons for the 

preferences, and the relative tradeoffs Tribal members are willing to make in the maintenance 

and improvement of downstream resources. This information is important to inform the 

prioritization of funding for monitoring and research in an adaptive management program. 

Project Lead Lucas Bair

Funded Principal 

Investigator(s) (PI)

Lucas Bair, USGS, GCMRC

Chris Neher, University of Montana

John Duffield, University of Montana

Michael Springborn, UC Davis

Charles Yackulic, USGS, GCMRC

Email lbair@usgs.gov

Telephone (928) 556-7362
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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The first phase of the tribal survey project was initiated in early 2017. Initial tasks involved 

researching the current state of economic information pertaining to the five tribes involved in 

the GCDAMP, as well as the broader issues of conducting natural resource survey research 

within a tribal setting. The second task, initiated in 2017 and carried into 2018, involved 

modifying the Glen Canyon Dam passive use survey instrument used in a 2016 national 

valuation study for use in a tribal setting. The development of a modified survey specific to each 

tribe was informed by formal meetings with representatives of the Hualapai Tribe, Hopi Tribe, 

Pueblo of Zuni, and the Navajo Nation and focus group meetings with the Hopi Tribe’s and 

Pueblo of Zuni’s cultural resource advisory groups. These meetings proved critical in the 

development of the tribal surveys in general, identifying critical flaws in design and 

implementation methods. 

Following initial research, in 2019 we implemented surveys on the Navajo Nation and with the 

Hualapai Tribe. A number of contact methods were considered for collecting survey data from 

Navajo Nation Tribal members. The challenges associated with implementing mail and phone 

surveys on the reservation led us towards employing a structured set of representative inperson group surveys at selected, geographically representative Chapters across the 

reservation. The Chapters are local government entities that historically represent local family 

or clan relations and were formally established to regulating grazing activities on the Navajo 

Nation. Presently, Chapters address grazing but also infrastructure, housing and social issues. 

Surveys on the Navajo Nation were facilitated through our participation in official Chapter 

meetings and subsequent use of Chapter facilities. Engagement with Chapters entailed several 

trips to the Chapter to request use of the facility and approval of the Chapter government for 

administering the group surveys. The group surveys were advertised in Chapter meetings, and 

participants were paid a $40 stipend for their participation in the approximately two-hour 

group survey. In total, between November 2018 and May 2019, group surveys were held at 12 

Chapters and 289 individual tribal member surveys were collected though the process. 

The Hualapai Tribal surveys were conducted September 23-25, 2019. Prior to survey 

implementation, pretesting of the survey occurred with Hualapai Department of Natural 

Resources staff and members of the Cultural Advisory Committee in November 2019. The 

Hualapai Tribal surveys were conducted in the community of Peach Springs at the Hualapai 

Cultural Center, Education and Training Center, and Elderly Center. As with the Navajo Nation, 

the challenges associated with implementing mail and phone surveys with the Hualapai Tribe 

led us towards employing a structured set of representative in-person surveys. Hualapai 

Cultural Center staff facilitated the implementation of the surveys. The in-person group surveys 

were advertised in news media, and participants were paid a $40 stipend for their participation 

in the approximately two-hour group survey. In total, 108 individual Hualapai Tribal member 

surveys were collected though the group survey process.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[121]

Both the Navajo Nation and Hualapai Tribal survey was divided into five sections. The survey 

began with initial questions on the importance of downstream attributes to the Tribal member. 

This set of questions was followed by a block of questions on the member’s level of approval of 

the use of specific river flow management tools for protection or improvement of downstream 

resources. The second survey section was a one-page question on the willingness to pay for the 

implementation of the respondent’s approved river flow management tools to protect 

downstream resources. A third large block of questions presented a set of nine discrete choice 

comparisons of two different sets of resource outcomes from river flow management and 

asked participants to choose which of each set they would prefer. Following the discrete choice 

questions, participants were asked two sets of Likert-scaled questions concerning their level of 

agreement or disagreement with a set of statements about Colorado River resources and their 

use. The second to last survey section asked a set of standard demographic questions followed 

by a set of open-ended questions allowing for additional comments by the participant. The final 

survey section asked respondents to report on general values associated with the Grand 

Canyon and the Colorado River (two separate questions). The final question asked respondents 

to share stories, experiences or other important information about the Grand Canyon and 

Colorado River. Results from the Navajo Nation and Hualapai Tribal surveys will be presented at 

the Annual Reporting meeting in January 2020, following approval from the Navajo Nation 

Human Research Review Board and the Hualapai Cultural Center staff. 

In 2020 continued engagement with tribal representatives, researchers, and tribal members 

through presentation to the Navajo Nation Human Research and Review Board, Navajo Nation 

Chapters that participated in the survey, Hualapai Cultural Advisory Team, and Hualapai 

Cultural Center staff will occur. Population level surveys with the Hopi Tribe and the Pueblo of 

Zuni are uncertain in 2020. The Southern Paiute Consortium have indicated that they will not 

participate in the survey. Continued engagement with the Hopi Tribe, learning from survey 

implementation with the Navajo Nation and the Hualapai Tribe, and continued investigation 

into existing documentation and ethnographic material will potentially position researchers for 

population level surveys with the Hopi Tribe in 2020. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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Project Element J.2. Juvenile Chub Monitoring Near the LCR Confluence

In 2019, Donovan and others (2019) published an updated bioeconomic model to estimate the 

most cost-effective approach to managing rainbow trout removal at the confluence of the LCR 

and the Colorado River to meet long-term adult humpback chub survival goals. The Donovan 

and others (2019) paper refined previous work by Bair and others (2018), using novel dynamic 

programming methods to identify removal actions that cost-effectively met long-term adult 

humpback chub abundance goals. The updated model does not impose a predetermined 

structure on the shape of the policy function and removals are based on the abundance of 

rainbow trout in the juvenile humpback chub monitoring reach and the abundance of adult 

humpback chub in the Little Colorado River aggregation. This new framework also allowed for 

initial investigation into the value of information with respect to reducing uncertainty in the 

relationship between humpback chub survival and rainbow trout abundance. Results of the 

model are similar to the Bair and others (2018) simulation but are more effective and efficient 

at meeting humpback chub abundance goals because triggers are informed jointly by rainbow 

trout and humpback chub abundance (Figure 1). 

Figure 1. (Adapted from Donovan and Springborn, 2019.) The policy function indicating how many mechanical removals of 

rainbow trout are cost-effective in a year given the current populations of rainbow trout (horizontal axis) and humpback chub 

(vertical axis) in the management reach. The light green line spanning the figure from left to right delineates where the probability 

of remaining above the adult humpback chub abundance goal is not certain over a 20-year time horizon. The blue curve shows 

the likely rainbow trout and humpback chub abundance (50%) after 20 years under the optimal policy.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[123]

The assessment of the value of additional information related to the presence of adult rainbow 

trout in the juvenile humpback chub monitoring reach and the survival of juvenile humpback 

chub proved to be substantial. The estimated reduction in cost from improved information, 

reducing the total number of removals over a 20-year period, was $600,000. This estimated 

value of information does not consider other benefits of reducing removals over the period.

Lucas Bair and collaborators are expanding on the rainbow trout and humpback chub dynamic 

programming model to assess the effectiveness of trout management flows and the value of 

information with respect to reducing uncertainty in the relationship between trout 

management flows and mortality of juvenile rainbow trout. The Donovan and others (2019) 

model will also allow research into the impact of nonstationary climate impacts (e.g., changes 

in flood frequency) on humpback chub recruitment in the Little Colorado River and how that 

may inform effective and efficient management and research. This work is based on the 

Donovan and others (2019) model but also will rely on important research in biogeomorphic 

changes in the Little Colorado River (Dean and Topping, 2019) and humpback chub recruitment 

(Van Haverbeke and others, 2013). The modeling framework will also allow us to model the 

effectiveness of management alternatives across future scenarios. For example, ongoing 

research includes the refinement of the bioeconomic model to assess the effect of U.S. Fish and 

Wildlife Service Chute Falls translocations on the number of expected trout removals to achieve 

a population viability goal for adult humpback chub. Extending the dynamic programing model 

described by Donovan and others (2019) in these ways could allow researchers to investigate 

the effectiveness and efficiency of flow management actions for other nonnative species, such 

as brown trout, in the Lees Ferry reach of the Colorado River. 

REFERENCES

Bair, L.S., Yackulic, C.B., Springborn, M.R., Reimer, M.N., Bond, C.A., and Coggins, L.G., 2018, 

Identifying cost-effective invasive species control to enhance endangered species populations 

in the Grand Canyon, USA: Biological Conservation, v. 220, p. 12-20, 

https://doi.org/10.1016/j.biocon.2018.01.032.

Dean, D.J., and Topping, D.J., 2019, Geomorphic change and biogeomorphic feedbacks in a 

dryland river—The Little Colorado River, Arizona, USA: GSA Bulletin, v. 131, no. 11-12, p. 1920-

1942, https://doi.org/10.1130/B35047.1.

Donovan, P., Bair, L.S., Yackulic, C.B., and Springborn, M.R., 2019, Safety in numbers—Costeffective endangered species management for viable populations: Land Economics, v. 95, no. 3, 

p. 435-453, https://doi.org/10.3368/le.95.3.435.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[124]

Donovan, P., and Springborn, M.R., 2019, Maintaining the long-term viability of the humpback 

chub in the Grand Canyon: ARE Update, University of California, Giannini Foundation of 

Agricultural Economics, v. 22, no. 5, p. 5-8, https://giannini.ucop.edu/publications/areupdate/issues/2019/22/5/maintaining-the-long-term-viability-of-the-humpbac/.

Van Haverbeke, D.R., Stone, D.M., Coggins, L.G., and Pillow, M.J., 2013, Long-term monitoring 

of an endangered desert fish and factors influencing population dynamics: Journal of Fish and 

Wildlife Management, v. 4, no. 1, p. 163-177, https://doi.org/10.3996/082012-JFWM-071.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Socioeconomic 

considerations of 

environmental flows: 

Using bioeconomic 

modeling to identify 

cost-effective 

approaches for 

managing invasive 

species in the Grand 

Canyon, USA

May

2019

Bair, L., Reimer, M., Donovan, P., Springborn, M., Bain, 

D. and Yackulic, C., 2019, Integrated assessment of 

ecosystem management and hydropower generation in 

endangered species recovery: Halifax, Nova Scotia, May 

22-24, 2019, North American Association of Fisheries 

Economists Forum.

Presentation

Tribal preferences for 

Colorado River water 

management and the 

Glen Canyon Dam

Sept

2019

Huber, C., Bair, L.S., Arviso-Ciocco, M., Neher, C.J., and 

Duffield, J.W., 2019, Tribal preferences for Colorado 

River water management and the Glen Canyon Dam—

presentation: Flagstaff, Ariz., September 9-12, 2019, 

15th Biennial Conference of Science & Management on 

the Colorado Plateau & Southwest Region.

Journal 

article

Testing the limits of 

temporal stability: 

Willingness to pay 

values among Grand 

Canyon whitewater 

boaters across 

decades

FY 2019

Donovan, P., Bair, L.S., Yackulic, C.B., and Springborn, 

M.R., 2019, Safety in numbers—Cost-effective 

endangered species management for viable 

populations: Land Economics, v. 95, no. 3, p. 435-453, 

https://doi.org/10.3368/le.95.3.435.

Journal 

article

Maintaining the longterm viability of 

humpback chub in the 

Grand Canyon

FY 2019

Donovan, P., and Springborn, M.R., 2019, Maintaining 

the long-term viability of humpback chub in the Grand 

Canyon: ARE Update, University of California Giannini 

Foundation of Agricultural Economics, v. 22, no. 5, p. 5-

8, https://giannini.ucop.edu/publications/areupdate/issues/2019/22/5/maintaining-the-long-termviability-of-the-humpbac/.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[125]

Project K: Geospatial Science and Technology

SUMMARY

The Geospatial Science and Technology project provides support to Grand Canyon Monitoring 

and Research Center (GCMRC) science projects in the realms of Geographic Information 

Systems (GIS), database development and operation, programming and source control for code, 

web application development, and other online data resources. Continued efforts in pioneering 

the Amazon Webs Services (AWS) cloud environment for the Center, expanding on a new 

Internet of Things (IoT) sensor-to-cloud initiative, and furthering relational database and frontend application development highlight the work being produced from this project. Most work 

performed within Project falls within one of three main categories—Geospatial Data Analysis, 

Geospatial Data Management, and Access to Geospatial Data Holdings—although many work 

elements will have aspects that can be discussed in all three of these categories.

K.1. Geospatial Data Analysis: Support to Science Projects

General Support to all Projects

The Geospatial Science and Technology project continued to support research and monitoring 

projects from the FY 2018-20 Triennial Work Plan by providing geospatial expertise to most 

projects on field mapping methods, development of customized maps, sample site unit 

definition and selection, GIS layer development, and GIS tool development and support. Often 

this work involved the oversight and supervision of science project staff with all GIS-related 

work including spatial analysis in support of projects, training for staff and cooperators in GIS 

data entry and database management concepts, data processing techniques, production of 

printed maps and online map products, error troubleshooting, and other basic GIS methods and 

techniques. GIS Administration tasks related to science support included the testing and 

migration of systems to newer versions of the most commonly used GIS/Remote Sensing 

software, maintaining licensing information, and/or working with Information Technology (IT)

staff to ensure all licenses, software, extensions, add-ons, and custom applications work 

properly.

Project Lead Tom Gushue

Principal 

Investigator(s) (PI)

Thomas Gushue, USGS, GCMRC

Timothy Andrews, USGS, GCMRC

James Hensleigh, USGS, GCMRC

Email tgushue@usgs.gov

Telephone (928) 556-7370
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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The level of support now being provided by this project for GCMRC extends into the application 

of relational databases, adopting and leveraging source control platforms for managing 

programming code and software/application development, migration of project data away 

from flat files and into enterprise database systems, and providing the avenue for eventual 

inclusion into the USGS’ Cloud Hosting Solutions (CHS) environment within Amazon Web 

Services (AWS) cloud platform, or other suitable endpoints. There is a shift in this support to 

now focus more on promoting GCMRC’s abilities to move project data from the field to 

databases to the cloud where appropriate, in efficient, modern workflows that maintain some 

consistent elements and yet can be adapted to each project’s unique properties.

Project-Specific Support

List of Projects Support:

1. Project B: Sandbar and Sediment Storage

a. Staff in the Geospatial Project led the way in instituting a new sandbar database and 

data processing workflow and were responsible for the migration of both the 

database and sandbar webpage application that now serves these data to the public. 

It’s important to add that this all exists in the Center’s new AWS CHS environment 

for the USGS which has been established and is maintained by the Geospatial Project 

(Project K).

b. Redesigned and maintained C# application Survey Accounting CRUD to create, 

update, delete, display, summarize, catalog and output data from Global Positioning 

Systems (GPS) and terrestrial surveys not associated with the geodetic control 

network. This data comes from a variety of sources and geographic scope and 

provides support for data outside of the Project B.

2. Project C: Riparian Vegetation Monitoring

The Geospatial project provided updates and training to vegetation monitoring staff on the 

proper use of the vegetation monitoring database and application interface. The main goal 

was to assist with data management, analysis, and reporting of vegetation survey data 

acquired in the field. Prior to this, the data for this project were manually entered into 

spreadsheets from field data sheets – a workflow that is known to produce many errors, 

some of which are costly and require time to fix. By continuing to support the database 

entry workflow that has error-flagging and handling routines built-in, we have been able to 

greatly improve the process. Additionally, the new vegetation monitoring database will 

improve the ability to perform analysis across multiple years of data (which were previously 

aggregated in different spreadsheet files) and more efficiently create reports and webbased analytics on this resource in the future. 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[127]

3. Project H: Salmonid Research

a. Continuation of basic geospatial support in the form of river map products and 

GPS unit preparation in support of field work, basic analysis, and map production 

for publication and presentation purposes. The GIS project also supports some 

advance geospatial analysis of Digital Elevation Model (DEM) data to determine 

slope characteristics of the Glen Canyon Reach.

4. Project I: Warm-Water Native and Nonnative Fish Research and Monitoring

a. Continuation of basic geospatial support in the form of river map products and 

GPS unit preparation in support of field work, basic analysis and map production 

for publication and presentation purposes.

K.2. Geospatial Data Management, Processing, and Documentation

Geospatial data management tasks included making updates to server hardware and software, 

updating existing applications to comply with new security measures, and testing and 

troubleshooting connectivity to internal systems – such as existing relational databases (Oracle, 

SQL Server) – as well as external clients that range from desktop applications (ArcGIS ArcMap, 

QGIS) to web-based endpoints (REST services, online applications, ArcGIS Online content). Work 

performed within this project also includes many IT-centric tasks that were originally not a part 

of the GIS project in past work plans. This included working with other USGS IT entities to 

resolve web-based issues and improve performance in delivering GCMRC geospatial content 

online. 

Expansion of Cloud Environment Usage for Science Project Support

One example of the expanded role in data management is the effort to advance GCMRC into 

the AWS cloud environment. This work involved coordination at a high-level with GIS and IT 

staff at the USGS Southwest Biological Science Center (SBSC), USGS CHS team members across 

the country, USGS project leads from other science centers, and contractual partners from the 

private sector. There were several goals outlined for this past year, with the most notable as 

follows:

1. Further develop the GCMRC’s capacity for working in and building applications for the 

Amazon cloud environment, 

2. Acquiring licenses for and begin working with new data visualization software (Tableau 

Desktop and Server) that will allow Center staff to connect to a variety of data sources 

(static files, spreadsheets, relational databases, online services, etc.) and develop 

custom and advanced data visualizations of their project’s information, and 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[128]

3. Help lead at least one project into using AWS for their data storage and data serving 

needs. 

In FY 2019, we were able to achieve all three of these goals. Some specifics that were achieved 

related to these goals include the development and implementation of a repeatable continuous 

integration/continuous development (CI/CD) pipeline to deploy applications to AWS, and the 

development of a public Simple Storage Service (S3) bucket that can be used to serve photos 

and replace out-of-service web servers previously being used for same purpose.

Expanding Use of Source Control

Project K has continued to the lead GCMRC in developing and managing geoprocessing scripts, 

web applications and other work involving programming through online source control and 

versioning platforms, such as USGS GitLab, USGS CHS GitLab, and USGS BitBucket spaces. This 

effort has led to greater efficiency in code development, geoprocessing task performance, and 

faster development of new web applications than previously possible. By spearheading this 

shift to source control for GCMRC, the Geospatial team can better serve as technical advisors 

for GCMRC scientists and technical staff and allow for greater collaboration with cooperators 

and other external entities.

K.3. Access to Geospatial Data and Online Data Resources

Project K continued to perform all the administration, installation, system upgrades, and 

content expansion made available through the online GIS Portal (Grand Canyon Map Portal, 

https://grandcanyon.usgs.gov/portal/home/index.html) and increased the use of this content 

delivery system to a wider audience outside GCMRC. This work also involved configuring, 

testing and publishing new geospatial data sets to the Grand Canyon Map Portal that directly 

support new science project information and findings. 

1. Migration of GCMRC Website to USGS WRET-Compliant Pages

In December 2018, it became apparent that a need existed to migrate the GCMRC 

website away from a locally-hosted server and into the USGS Web RE-engineering 

Team’s (WRET) cloud-based Drupal environment web hosting platform. This has been a 

long-standing goal for the USGS, however, it was accelerated due to the USGS Director’s 

new initiative to have all USGS websites migrated by the end of April 2019. Despite this 

traditionally being a function handled either by the SBSC IT staff or by the SBSC 

Outreach Coordinator, it was obvious that neither of these entities would be able to 

complete this task. So the Geospatial project took the lead and migrated content away 

from the old website (https://www.gcmrc.gov) and into the new USGS-approved web 

content management system, to which the old website now redirects 

(https://www.usgs.gov/centers/sbsc/gcmrc/). This work included understanding the 
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[129]

back-end architecture upon which the content management system was built on, 

designing the web pages, linkages, related content, etc. to be hosted on the new 

website, and coordinating and communicating with the WRET team on how best to get 

their platform to work for our Center’s unique situation. The new USGS web platform 

did not have an easy way to define GCMRC as its own entity within the Southwest 

Biological Science Center, since it is essentially a Center that needs its own home page 

within another cost accounting Center in the USGS. This work also included identifying 

and documenting the web redirect links that would be applied through the USGS’ 

National Web Server System (NatWeb) in order for GCMRC’s legacy website and web 

pages to be properly ported to the new content in the cloud. Additionally, this project 

directed and performed the work to apply the WRET-approved web content to the 

GCMRC’s existing online web applications. All of this work led to a seamless transition 

for GCMRC’s online presence into the larger content management system of the USGS 

(Figure 1). The new URL for GCMRC’s Home Page is located here: 

https://www.usgs.gov/centers/sbsc/gcmrc.

Figure 1. A screenshot of GCMRC’s new website and home page. There are several ways to get to this web page, and the 

original GCMRC URL (https://www.gcmrc.gov) now re-directs to this new location.
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2. System Migrations to New OS

A major effort in this area was to handle a national system security directive within the 

Department of the Interior to migrate all systems to newer operating systems. While 

this is rather simple for desktops and laptops, it is more involved for servers that handle 

live access to our geospatial content. In FY 2019, this project was able to rebuild the 

internal GIS Portal to a new, more advanced system. Work remains on restoring (or 

redesigning) all content services that existed prior to the migration. The movement of 

some content was determined to be unnecessary as the data were not current.

3. New or Improved Web Applications hosted in ArcGIS Online

Work this year also included leading the effort to improve upon existing web-based 

services and applications through both the Grand Canyon Map Portal and stand-alone, 

web-based applications. Additionally, this project has led the efforts to create new, 

advanced geospatial data exploration tools and applications that are now available as 

online content. Below is a partial list of just a few new applications now available on 

ArcGIS Online:

• Predicted Shorelines for High Flows on the Colorado River Application

• Sandbar deposition following the 2018 High-Flow Experiment

• Campsite Atlas Web Application

4. Grand Canyon Map Portal: https://grandcanyon.usgs.gov/portal/home/index.html

Work this year also included improving upon existing web-based services and 

applications through both the Grand Canyon Map Portal and stand-alone, web-based 

applications. The following is a descriptive list with URLs of new online mapping and 

data exploration applications now available through GCMRC’s website.

5. UPDATED HFE web page: https://www.usgs.gov/centers/sbsc/science/high-flowexperiments-colorado-river

We developed a new web page that brings together online maps, data-serving web 

applications and relevant publications related to past HFE events that is now available 

through the new GCMRC website. Some of this work was initiated at the end of FY 2018 

in preparation for the HFE in November 2018; however, back-end work continued into 

the first quarter of FY 2019. 
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6. UPDATED Geospatial Services page: 

https://grandcanyon.usgs.gov/gisapps/restservices/index_wret.html

We continue to provide access to GCMRC’s geospatial data sets through a web services 

directory page that organizes Representational State Transfer (REST) service endpoints 

by data set and resource type. Web services and applications built on the REST 

architectural style have standardized methods for interacting with the data content and 

are optimized to work best on the Web. These services can be used in desktop 

applications by downloading a link (*.lyr) file of any service. They can also be accessed in 

web applications developed by users outside the GCMRC, or added into other programs,

such Google Earth, as a layer on the map. The Geospatial Services page has been updated 

in FY 2019 to contain Environmental Systems Research Institute (ESRI) ArcGIS 10.7.1 

services. This process involves updating both ArcGIS Server and Portal applications on an 

external-facing webserver to make available the most current functionality provided by 

these platforms at the time. Additionally, updating map services to the latest version 

allows for better desktop-client compatibility for users. 

These services take advantage of new functionality that is available to geospatial data at 

this version, while still being backwards-compatible with 10.x versions of ESRI ArcGIS 

desktop software. Additionally, many of the geospatial services are being offered as Web 

Map Services (WMS) as defined by the Open-source Geospatial Consortium (OGC), which 

means that many of GCMRC’s geospatial data sets can be accessed by anyone through 

open-source software and custom-built applications. This fact increases both the 

importance of GCMRC’s Enterprise GIS platform, and the visibility of our work to a much 

wider audience.

7. Access to Geospatial Data Holdings – ESRI’s ArcGIS Online:

http://usgs.maps.arcgis.com/home/search.html?q=GCMRC&t=content

The benefit of using ArcGIS online in addition to hosting our own geospatial portal is that 

a particular service only needs to be created once by GIS staff, but can then be posted on 

both GCMRC’s website and through ESRI’s ArcGIS Online to reach a wider audience.

8. IoT Sensor-to-Cloud Data Transmission

We have expanded the Center’s use of the USGS’ CHS environment and provided 

unparalleled opportunities for GCMRC science staff. Despite having to deal with an 

unprecedented government shutdown and an extended period of downtime on the 

sensor-to-cloud work that is part of a larger USGS-wide initiative, we were able to still 

advance the GCMRC’s use of new technologies, including expanding our plans for 

instituting IoT technology in multiple study sites. This work has made our Center poised 
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for a renewed interest in IoT technologies and is one of four new pilot projects for the 

USGS Director’s Earth Mapping, Analysis, and Processing (EarthMAP) initiative. Currently, 

we are able to send data via encrypted text messages using the MQ or “machine-tomachine” Telemetry Transport (MQTT) protocol from a base access point located at Lees 

Ferry to a cloud brokering service in our CHS-AWS account. The data are sent via cellular 

transmission from a weather station located adjacent to our base access point at Lees 

Ferry, and we plan to begin connecting other devices including water quality sensors 

located in the Lees Ferry vicinity in FY 2020. By leveraging the power of cloud computing, 

we are able to see data parameters values in near real-time in the form of data packets 

sent to the cloud broker (Figure 2) and we can build custom data dashboards to track 

changes in data parameters over time (Figure 3).

Figure 2. A screenshot of weather station data streaming to AWS IoT cloud environment for the GCMRC’s Lees Ferry 

Internet of Things (IoT) pilot project on November 19, 2019. Data are recorded every 4 minutes and sent via MQ or 

“machine-to-machine” Telemetry Transport (MQTT) protocol every 15 minutes.
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Figure 3. A screenshot of the dashboard functionality available through a third-party data brokering entity called Thinglogix. In 

FY 2019, the USGS was able to put in place a long-term contract for the Bureau of Reclamation to have exclusive rights for 

using this service for sensor-to-cloud data transmissions.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Reports, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Web 

application

Grand Canyon 

sandbar monitoring

FY 2019

(updated)

Online database and web application:

https://www.usgs.gov/apps/sandbar/

New 

website

Grand Canyon 

Monitoring and 

Research Center website

April 

2019

New GCRMC website:

https://www.usgs.gov/centers/sbsc/gcm

rc
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Project L. Remote Sensing Overflight in Support of Long-Term

Monitoring and LTEMP

Project Lead Joel Sankey

Principal 

Investigator(s) (PI)

Email jsankey@usgs.gov Joel Sankey, USGS, GCMRC

Telephone (928) 556-7289

SUMMARY 

The remote sensing overflight described in Project L has been postponed and will occur no later 

than calendar year 2021 so that funding can be applied to other projects with greater priority. 

A portion of the funds for the overflight (at least $75,000) will be set aside in each year of the 

FY 2018-20 Triennial Work Plan (TWP) and applied to the overflight in the FY 2021-23 TWP.

Reclamation has requested that the geographic extent of the next overflight as a well as the 

scope of remote sensing work be expanded, particularly in western Grand Canyon and eastern

Lake Mead to address conservation measures for razorback sucker as well as other species and 

resources. This increase in the extent of data acquisition and scope of remote sensing work will 

further increase the total cost of the next overflight and associated analyses. 

The remote sensing projects at Grand Canyon Monitoring and Research Center (GCMRC) were 

subject to substantial technical staffing reductions in FY 2018-20 due to the budget 

prioritization described above. Given this and the requested expansion of the geographic extent 

of the overflight, GCMRC will request additional funding in the FY 2021-23 in order to

successfully complete the next overflight and process and serve the imagery in a timely 

manner.
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Project M: Administration

SUMMARY

During the Fiscal Year 2019, the budget for this project included the salaries for the librarian, 

and 80% of a budget analyst. This budget also includes leadership personnel salaries, travel and 

training for the Chief and Deputy Chief, and part of the salary and travel of one program 

manager. The vehicle section covers the costs associated with Interior-owned and GSA-leased 

vehicles that Grand Canyon Monitoring and Research Center (GCMRC) uses for travel and field 

work. Costs include fuel, maintenance, and repairs for Interior-owned vehicles and monthly 

lease fees, mileage costs, and any costs for accidents and damages for GSA-leased vehicles. 

This project also includes the costs of Information Technology (IT) equipment for GCMRC. 

Salaries, travel, and training for logistics staff are also included in this project’s budget.

In addition, funding from Project M helped support the Partners in Science program with Grand 

Canyon Youth, a nonprofit organization that provides youth (ages 10-19) with educational 

experiences along the rivers and canyons of the southwest, including the Grand Canyon. 

GCMRC scientists participated in the two Partners in Science river trips conducted in FY 2019

during which they educated youth participants in Colorado River science and directed them in 

data collection efforts in support of the FY 2018-2020 Triennial Work Plan. Data were collected 

in support of understanding geomorphic processes of sandbars (Projects B and D), riparian 

vegetation (Project C), aquatic invertebrate ecology (Project F), the biology and ecology of 

native and nonnative fishes including humpback chub (Projects G and I), and rainbow trout 

(Projects H).

Project Lead Scott VanderKooi, Chief

Principal 

Investigator(s) (PI) Email svanderkooi@usgs.gov Scott VanderKooi

Telephone 928-556-7376
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Project N: Hydropower Monitoring and Research

SUMMARY

The overall objective of Project N is to identify, coordinate, and collaborate on monitoring and 

research opportunities associated with operational experiments at Glen Canyon Dam (GCD) to 

meet hydropower and energy resource objectives, as stated in the Long-Term Experimental and 

Management Plan (LTEMP) Record of Decision. Operational experiments include those

proposed in the LTEMP Environmental Impact Statement (EIS; e.g., High-Flow Experiments, 

macroinvertebrate production flows, trout management flows) or experiments that improve 

hydropower and energy resources (e.g., change in ramp rates, change in daily flow range, 

fluctuating flow factors, monthly volume patterns), while consistent with long-term 

sustainability of other downstream resources. The operation of GCD to meet hydropower and 

energy resource objectives, as the integration of renewables and a greater recognition of the 

social cost associated with power system emissions occurs, is an important consideration when 

attempting to maintain and improve resources downstream of GCD. 

Project N: 14.1. Hydropower Monitoring and Research

Evaluating tradeoffs between hydropower generation at GCD and downstream resources is a 

constant challenge in the Glen Canyon Dam Adaptive Management Program. However, there

are limited inquiries into the role of existing hydropower facilities, such as GCD, in minimizing 

total social and environmental costs. Structural changes in the electricity sector are presenting 

opportunities for hydropower to play an important role in renewable integration and electricity 

sector emissions mitigation, reducing total social costs of energy generation. Thus, hydropower 

can reduce social costs within the electricity sector, and consideration of this potentially 

restructures costs associated with flow experiments to restore and maintain resources 

downstream of GCD.

In 2019, Lucas Bair collaborated with researchers at Northern Arizona University (NAU) to 

identify the impact of proxy flow experiments on generation and emissions costs in the 

coordinated electricity grid in the western United States, Canada and Mexico. The ongoing 

collaboration utilizes existing research in power system modeling at NAU (Bain and Aker, 2017). 

Project Lead Lucas Bair

Funded Principal 

Investigator(s) (PI)

Lucas Bair, USGS, GCMRC

Dominique Bain, NAU 

Email lbair@usgs.gov

Telephone 928-556-7362
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This collaboration provides foundational research to meet the objective of Project N, to 

estimate and attempt to minimize impacts of proposed experiments in the LTEMP EIS on 

hydropower as part of the experimental design. To minimize impacts to hydropower and 

energy resources, cost production modeling is used to estimate the change in total economic 

value of hydropower generated at GCD under various future scenarios. The total value of 

hydropower generated at GCD includes cost associated with energy generation, greenhouse gas 

emissions, human health, and other regional impacts. These impacts are dependent on the 

price of fuel (e.g., natural gas) and the integration of additional generation, including renewable 

energy, into the electricity sector. Scenarios incorporating these factors were used to assess 

total economic costs associated with a proxy experimental flow at GCD. 

We demonstrated the change in production and emissions costs in the Western Interconnect 

by reoperation of GCD. This example illustrates the importance of incorporating external social 

costs in environmental decision making and consideration of the technical characteristics of 

future power system expansion when managing resources downstream of GCD. Based on 

power system modeling in the LTEMP (U.S. Dept. of Interior, 2016), our hypothesis is that 

consideration of total costs (energy generation and emissions) when evaluating alternative 

flows at GCD will significantly change the results of the economic outcomes of experimental 

flows. Implementing a proxy experimental flow, or changing from economic dispatch to flat 

flows, allowed us to compare changes in total power system costs under various fuel price and 

renewable integration scenarios. Economic dispatch at GCD minimizes production costs of 

power system generation in the Western Interconnect, constrained by operating rules at GCD 

(U.S. Dept. of Interior, 2016). Flat flows represent a constant release of water at GCD consistent 

with monthly release volume requirements.

We used PLEXOS, a production cost model, to estimate variable costs of generation in the 

Western Electricity Coordinating Council’s Transmission Expansion Planning and Policy 

Committee 2024 baseline (TEPPC, 2014) under economic dispatch and flat flows at GCD. 

External costs by county associated with CO2, SO2, and NOX power system emissions were 

estimated following the PLEXOS optimization runs using output from the AP3 Model (Sergi and 

others, 2019). This allowed us to compare total economic costs under differing operating 

guidelines and future energy scenarios (Table 1). Note, this is a short run economic analysis and 

we assumed, confirmed by modeling results, that power capacity requirements were met 

across future scenarios.

Results indicate that social costs of emissions are significant enough in different future 

scenarios to offset some changes in production costs under a proxy environmental flow. 

However, the difference between the social cost of emissions and production costs is 

dependent on the scenario. Changes in fuel costs (e.g., natural gas) and the integration of 

different levels of solar generation result in very different economic outcomes (Table 1). While 
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the proxy experimental flow is not a flow experiment defined in the LTEMP EIS, it is 

representative of the type of potential changes in total economics costs that may be observed 

under experimental flows at GCD. Further investigation into the seasonal differences in 

production and emissions costs under different renewable integration scenarios is warranted.

Table 1. Change in Western Interconnect production and emissions costs with flat flows at Glen Canyon 

Dam ($2018 dollars in millions).

The baseline production cost is based on the Western Electricity Coordinating Council’s Transmission 

Expansion Planning and Policy Committee 2024 baseline (TEPPC, 2014). Solar scenarios add an 

additional 700 MW of generation to Arizona. Business as usually, low, and high natural gas prices are $4, 

$2 and $6 per MMBtu, respectively. Emissions damages are estimated using output from the AP3 Model 

(Sergi and others, 2019; https://public.tepper.cmu.edu/nmuller/APModel.aspx).

Structural changes in the electricity sector are altering the role of hydropower and how costs 

associated with experimental flows accrue. Total economic costs of our proxy experimental flow 

are significantly different when compared to various levels of renewable capacity expansion and 

fuel costs. Including emissions costs in the analysis significantly modifies total economic costs. 

The change in emissions costs is primarily due to a change in the quantity of coal fired generation 

(Figure 1) and subsequent change in sulfur dioxide (Figure 2) and other emissions. 

In FY 2020, GCMRC will continue to coordinate with external partners, including Western Area 

Power and the Department of Energy National Renewable Energy Laboratory, to investigate the 

implication of renewable energy integration and emissions costs for management of GCD and 

the maintenance and improvement of downstream resources. This research is also being 

coordinated with the evaluation of hydropower costs associated with trout management flows 

and other experiential flows analyzed as part of Project J.2.
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Figure 1. Change in annual generation of coal and natural gas fired generation (GwH) when comparing economic dispatch to 

flat flows at Glen Canyon Dam under the Western Electricity Coordinating Council’s Transmission Expansion Planning and 

Policy Committee 2024 baseline scenario (TEPPC, 2014).

Figure 2. Change in annual sulfur dioxide emissions (tons) by United States county when comparing economic dispatch to flat 

flows at Glen Canyon Dam under the Western Electricity Coordinating Council’s Transmission Expansion Planning and Policy 

Committee 2024 baseline scenario (TEPPC, 2014).
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REFERENCES

Bain, D.M., and Acker, T.L., 2018, Hydropower impacts on electrical system production costs in 

the southwest United States: Energies, v. 11, no. 2, article 368, p. 1-21, 

https://doi.org/10.3390/en11020368.

Sergi, B., Azevedo, I.L., Davis, S.J., and Muller, N.Z., in review, Transboundary health damages of 

air pollution in the U.S.: Nature Sustainability.

Transmission Expansion Planning and Policy Committee (TEPPC), 2014, 2014 study program by 

Transmission Expansion Planning and Policy Committee: Salt Lake City, Utah, Western 

Electricity Coordinating Council, 26 p., 

https://www.wecc.org/Reliability/TEPPC_2014_StudyProgram.docx.

U.S. Department of Interior, 2016, Record of Decision for the Glen Canyon Dam Long-Term 

Experimental and Management Plan final Environmental Impact Statement (LTEMP ROD): Salt 

Lake City, Utah, U.S. Department of the Interior, Bureau of Reclamation, Upper Colorado 

Region, National Park Service, Intermountain Region, 196 p., 

http://ltempeis.anl.gov/documents/docs/LTEMP_ROD.pdf.

PRODUCTS

(Product order: Presentations, Journal articles, Reports, USGS Series, USGS Data, Web applications)

Type Title Date 

Delivered Citation, URL, or Notes

Presentation

Integrated assessment of 

ecosystem management and 

hydropower generation in 

endangered species 

recovery

May 

2019

Bair, L., Reimer, M., Donovan, P., Springborn, M., 

Bain, D., and Yackulic, C., 2019, Integrated 

assessment of ecosystem management and 

hydropower generation in endangered species 

recovery: Halifax, Nova Scotia, May 22-24, 2019, 

North American Association of Fisheries Economists 

Forum.

Presentation

Identifying the value of 

hydropower in the electricity 

sector and implications for 

environmental management 

of rivers

Sept 

2019

Bair, L. and Bain, D., 2019, Identifying the value of 

hydropower in the electricity sector and implications 

for environmental management of rivers—

presentation: Flagstaff, AZ, September 9-12, 2019, 

15th Biennial Conference of Science and 

Management on the Colorado Plateau and 

Southwest Region.

 
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Appendix 1: Lake Powell Water Quality Monitoring

Program Manager (PM) Bridget Deemer

Principal 

Investigator(s) (PI)

Bridget Deemer, USGS, GCMRC

Nick Voichick, USGS, GCMRC

Email bdeemer@usgs.gov

Telephone 360-606-4353

SUMMARY

In Fiscal Year (FY) 2019, the U.S. Geological Survey’s (USGS) Grand Canyon Monitoring and 

Research Center (GCMRC) collected physical, biological, and chemical data and samples from 

Lake Powell, Glen Canyon Dam (GCD), and Lees Ferry. GCMRC also did some archiving of 

collected data in an existing Microsoft Access database; however, effort was mainly focused on 

the development of a new structured query language (SQL) based database platform that will 

house existing data and provide a more streamlined data entry process for newly generated 

data. A new interagency agreement was signed in FY 2018, which has supported GCMRC 

involvement in the Lake Powell Water Quality Monitoring program over the past two years with 

the potential for funding for three more years. In addition to fulfilling basic monitoring 

activities, GCMRC contributed to focused sampling before, during, and after the 2018 High-Flow 

Experiment (HFE) to monitor effects on water column stratification and outflow chemistry. 

Collaboration with Dickinson College has also resulted in initial analysis of the long-term 

plankton data set at the Wahweap station, and collaboration with the Environmental 

Protection Agency has supported greenhouse gas emission measurements from Lake Powell. 

Finally, historical data analysis conducted in FY 2018 and 2019 shows that Lake Powell has been 

functioning as a long-term calcite sink, resulting in salinity retention comparable to that 

achieved by efforts implemented as part of the Colorado River Basin Salinity Control Act. 

Project Summary

GCMRC has conducted a long-term water-quality monitoring program of Lake Powell and GCD 

releases in collaboration with the Bureau of Reclamation (Reclamation) and National Park 

Service (NPS). This project has been funded entirely by Reclamation from water and power 

revenues and receives no monetary support from the GCDAMP. In addition to direct funding of 

the program, Reclamation also provides support for laboratory analyses. The Lake Powell 

monitoring program was designed to determine status and trends of the water quality of Lake 

Powell and GCD releases, determine the effect of climate patterns, hydrology, and dam 

operations on reservoir hydrodynamics and the water quality of GCD releases, and provide 

predictions of future conditions.
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Monitoring Activities

Water-quality monitoring was conducted by Reclamation from 1964 to 1996. Since 1997, the 

GCMRC and Reclamation have continued water quality monitoring with assistance from NPS 

under a cooperative agreement funded via the Water Quality group in the Upper Colorado 

Regional Office of Reclamation. Sampling protocols and sampling sites are summarized in USGS 

data series reports 471 and 959 (Vernieu, 2015a; Vernieu, 2015b). For most years since 1997, 

the sampling program has consisted of monthly sampling in the forebay area immediately 

upstream of GCD, in the GCD draft tubes, and in the GCD tailwater (at Lees Ferry), quarterly 

surveys of the entire reservoir, and continuous monitoring of GCD releases via two water 

quality sondes, one connected to an active penstock and one directly below the dam. Quarterly 

reservoir surveys have typically been conducted within a six-day time period. Monitoring during 

these surveys has consisted of field observations of weather conditions, Secchi depth 

measurements, and vertical depth profiles of temperature, specific conductance, dissolved 

oxygen, pH, turbidity, and chlorophyll concentrations at up to 35 locations on the reservoir, and 

sampling for major ions, dissolved organic carbon, and nutrients at a subset of these locations. 

In addition, biological samples for chlorophyll, phytoplankton, and zooplankton have been 

collected near the surface at selected stations. 

In FY 2019, Reclamation conducted four complete reservoir-wide surveys with involvement 

from GCMRC (Table 1). In addition, GCMRC conducted six complete forebay surveys and four 

partial surveys to supplement the quarterly surveys (Table 1). January 2019 was the only month 

in FY 2019 with no measurements taken owing to annual repair of the Seabird CTD system. 

GCMRC also maintained two sonde instruments monitoring GCD releases and conducted 

several methods tests to compare historic and current filtration techniques for inlet water.

Results from laboratory analyses of samples are usually received within two months of 

collection. While some data were entered into a Microsoft Access database, focus was placed 

mostly in the development of a SQL-based database that will streamline data import and 

export. Reclamation also uses a subset of the water quality data to run the CE-QUAL-W2 model 

(a 2D water quality and hydrodynamic model) and to create cross-section time series 

visualizations of reservoir temperatures, dissolved oxygen, pH, and total dissolved solids.

In March of 2018 a thermistor string with 17 Hobo temperature loggers and 2 Hobo 

conductivity loggers was deployed off the buoy line near GCD. Temperature loggers are 

deployed at 1m, 5m, 10m, 15m, 20m, 25m, 30m, 35m, 40m, 50m, 55m, 60m, 70m, 80m, 90m, 

100m, and 120m with conductivity loggers at 45m and 110m. The thermistor string was 

checked twice in FY 2019, once during the October 2018 sampling and once during the June 

2019 sampling. Units are set to log at least every half hour, providing data describing lake 

stratification at the sub-daily time scale. A similar thermistor string was placed in the same 
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location in August of 2011. Data from this deployment are available through mid-December of 

2014 at which time the thermistor string was lost.

Table 1. Beginning dates and sampling activity for the Lake Powell water-quality monitoring for FY 2019.

Date Sampling Activity

10/10/18 Forebay, draft tubes, Lees Ferry, and thermistor string

11/2/18 Forebay and Lees Ferry

11/6/18 Forebay and Lees Ferry

11/19/18 Forebay

12/12/18 Quarterly survey

02/07/19 Forebay, draft tubes, and Lees Ferry

03/19/19 Quarterly survey

04/17/19 Forebay, draft tubes, and Lees Ferry

05/16/19 Forebay, draft tubes, and Lees Ferry

06/04/19 Quarterly survey and thermistor string

07/01/19 Forebay, draft tubes, and Lees Ferry

08/01/19 Draft tubes and Lees Ferry

08/22/19 Forebay, draft tubes, and Lees Ferry

09/09/19 Quarterly survey

Analysis Activities

Historical nutrient data from the Lake Powell Water Quality Monitoring program are being 

used together with data from the four major gaged tributary sites to Lake Powell (USGS 

stream gages at Colorado River near Cisco, UT, 09180500; Green River at Green River, UT, 

09315000; San Rafael River near Green River, UT, 09328500; and San Juan River near Bluff, 

UT, 09379500) and the gaged outflow site at Lees Ferry (USGS stream gage 09380000) to 

improve our understanding of the controls on phosphorus transport in the reservoir and 

links between phosphorus and food web dynamics in the Glen Canyon reach of the Colorado 

River. The goal of this analysis is to better understand the controls on phosphorus 

concentrations in releases from GCD with the eventual goal of modeling/predicting these 

concentrations. 
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Work is also ongoing to ensure that nutrient collection and analysis protocols are yielding 

the highest quality data possible, especially with regards to phosphorus species. Total 

dissolved phosphorus was added to the list of nutrient analyses in October of 2017. An 

inter-lab comparison of total phosphorus and soluble reactive phosphorus concentrations 

was conducted in March of 2018. Currently, all nutrient and major ion analyses are done by 

Reclamation’s Lower Colorado Region Water and Soil Laboratory in Boulder City, Nevada. 

This lab was compared to the High Sierra Water Lab in Tahoe City, CA (High Sierra)—a lab 

that specializes in low detection phosphorus analysis. Dissolved phosphorus concentrations 

reported by High Sierra were, on average, 65% of the values reported by the USBR lab. 

Similarly, water column total phosphorus concentrations reported by High Sierra were, on 

average, 52% of the values reported by BOR. Samples were well above reported detection 

limits (at least 3x higher) in all cases. In contrast, High Sierra reported higher total 

phosphorus concentrations in reservoir inflow waters (where total suspended solids are 

high), averaging 2.1 times the concentrations reported by the Reclamation lab. The 

Reclamation lab has been very willing to re-run sample sets when the coefficient of variation 

on replicate samples is poor, and to troubleshoot anomalous readings. That said, any future 

work that focuses specifically on phosphorus cycling may benefit from consulting a lab like 

High Sierra that specializes in phosphorus measurements. Currently, funding to send 

duplicate samples for phosphorus measurements is beyond the program budget (full suite 

of phosphorus analytes would total $75 per sample at a lab like High Sierra).

Water column stratification and outflow chemistry were monitored before, during, and after 

the fall 2018 HFE to better understand the extent to which this experimental flow regime 

affects water quality and limnology. Water quality profiles using the Seabird and water samples 

were collected at the Wahweap station and water samples were collected at Lees Ferry before, 

during, and after the HFE. A transect of water quality profiles using the Seabird was also 

collected up-lake from Wahweap during the HFE. We saw very little change in water column 

stratification during the HFE, but outflow chemistry was affected by the additional spill from 

the bypass tubes (which draw water from a lower depth). Some HFE related changes in outflow 

water quality have been explained elsewhere (Hueftle and Stevens, 2001), but the sampling 

conducted this year detected higher soluble reactive phosphorus at Lees Ferry during the HFE 

(see Figure E.1.2a earlier in this report), an effect that could not be deciphered when detection 

limits for this analyte were lower.
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Finally, historical major ion data from Lees Ferry (USGS stream gage 09380000), and the three 

major gaged tributary sites to Lake Powell (USGS stream gages 09180500, 09315000, and 

09379500) was used together with data from this monitoring program to examine patterns in 

salinity transport within the basin. Results show that Lake Powell acts as a sink for total 

dissolved solids, mainly via calcite precipitation. In addition, the reservoir functions to 

moderate downstream salt concentrations (Figure 1). These findings are contained in a 

manuscript currently under consideration for publication at the journal Limnology and 

Oceanography.

Figure 1. Measured total dissolved solids (TDS) concentrations at Lees Ferry (dark blue, n=223) versus discharge-weighted 

modeled salinity concentrations from the Colorado River and San Juan River inflow sites (light orange, n=71). TDS is calculated 

as the sum of the major ions Ca2+, Mg2+, Na+, K+, CO32-, HCO3-, Cl-, and SO42-. The size of each point is scaled to the 

discharge in cubic meters per second. The largest inflows for water supply generally occur in the months of May and June due to 

spring snowmelt. The dashed horizontal line represents the TDS limit at Hoover Dam (723 mg L-1).

Current Conditions

Hydrology

Lake Powell received 12.8 million acre feet (maf; 120% of the 1981-2010 average) of 

unregulated inflow in Water Year (WY) 2019. In comparison, inflow observed in WY 2018 was 

4.6 maf (43% of average). The peak reservoir elevation in WY 2019 was 3621.68 feet on August 

1, 2019 compared to an October peak of 3628.4 feet in WY 2018. At the end of WY 2019, Lake 

Powell’s surface elevation was 3615 feet (85 feet from full pool) with a storage of 13.3 maf, or 

55% of full capacity. This is up from the end of WY 2018 when surface elevation was 3592.3 ft 

and storage was 11 maf.
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Releases for WY 2019 totaled 9.0 maf (the same as for WY 2017 and WY 2018) with operations 

under the Upper-Elevation Balancing Tier. Operations for WY 2020 will also fall under the Upper 

Elevation Balancing Tier, with a total projected annual release volume of 8.23 maf and potential 

for an April 2019 adjustment to equalization or balancing releases.

Glen Canyon Dam Release Temperature

Glen Canyon Dam releases temperatures had reached a maximum of 16.1°C by mid-October of 

2019, which is a few degrees higher than the peak of 13°C in October of 2018. These high 

temperatures are consistent with a recent trend wherein peak temperatures in GCD releases 

have exceeded 15°C in 3 of the 6 previous years.

Lake Powell Limnology

In FY 2019, an interflow plume of low dissolved oxygen (DO) water moved through Lake Powell 

and contributed to historically low concentrations of DO in the GCD tailwaters (minimum DO of 

4.0 mg/L in October of 2019, compared to 4.4 mg/L in October 2014 and 3.5 mg/L in 2005). The 

2005 low dissolved oxygen event coincided with much lower recruitment and growth in the 

Glen Canyon rainbow trout fishery (Korman and others, 2012), so the low dissolved oxygen 

observed in Glen Canyon is of concern. The National Park Service continues to track and 

monitor the quagga mussel population throughout Lake Powell, mainly by estimating veliger 

densities in zooplankton tows. 

Research Collaboration Activities

Collaboration with Dickinson College has supported an analysis of the historical phytoplankton 

and zooplankton data described in Vernieu, 2015a. Initial findings show that phytoplankton 

biomass in the surface waters at Wahweap has increased significantly from 1993 to 2014 in all 

months but January (Figure 2). In contrast, zooplankton biomass shows only small generaspecific increases in February (rotifers) and June (Cladocerans) over the same time period. Of 

potential management interest is the increasing biovolume and temporal occurrence of 

Cyanobacteria, a phenomenon which may uncouple trophic interactions as well as negatively 

impacting lake recreation. These increases are not accompanied by significant trends in water 

chemistry. Based on a longer-term record of surface water temperatures starting in the mid1960s, however, Wahweap surface waters are experiencing significant warming trends in 

winter, spring, and early summer (0.26, 0.59, and 0.24 °C per decade respectively via Sen slope 

analysis). Spring warming was nearly double the global average lake surface warming rate of 

0.34 °C per decade reported by O’Reilly and others (2015). We plan to follow up on these 

findings by working with a group of Dickinson students to write up findings into a manuscript 

for submission at a peer reviewed scientific journal in FY 2020.
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Figure 2. Monthly sen slopes (μm3 L

-1 yr-1

) for phytoplankton biomass in the surface waters at the Wahweap station, Lake 

Powell between 1993 and 2014. We report significant increases in surface water phytoplankton biomass across all months 

accept January. 

Collaboration with the Environmental Protection Agency supported floating chamber-based 

measurements of carbon dioxide and methane emissions in July of 2017 as part of a 

quarterly survey. Efforts are underway to compare the results of this single-time point 

survey to several global scale models that represent our current best estimate of the 

potential magnitude of greenhouse gas emissions from Lake Powell. This work is of interest 

given the recent inclusion of reservoirs in the IPCC flooded lands methodology (Lovelock and 

others, 2019) combined with both the large surface area of Lake Powell and the general lack 

of data from arid region reservoirs. Our single day survey suggests that the per Megawatthour (MWh) emission factor for Lake Powell is somewhere around 32 kg CO2-eq MWh-1 at 

full pool (the majority of which is from CH4). This emission factor is somewhat higher than 

that predicted by two global scale models of reservoir greenhouse gas production (18-28 kg 

CO2-eq MWh-1, Prairie and others, 2017; Del Sontro and others, 2018), but is significantly 

lower than a third global model whose results suggested that the potential emissions from 

Lake Powell could be comparable to the per MWh emissions of natural gas and oil (173-662 

kg CO2-eq MWh-1, Scherer and Pfister, 2016). The emission factor is also dependent on 

reservoir elevation and the amount of energy that is being generated at any given time. We 

are working towards a manuscript for the Journal of Environmental Science and Policy that 

describes this effort. 
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Program Support

A five-year agreement for continued support of the Lake Powell water-quality monitoring 

program was developed with Reclamation in FY 2018 (R18PG00108 - Water Quality Monitoring 

of Lake Powell). The agreement provides funding for GCMRC involvement in the Lake Powell 

Water Quality Monitoring program over the next year with the potential for funding for up to 

five years (January 1, 2018 - December 31, 2023). It should be noted that this agreement is 

separate from the agreement which provides funding under the Glen Canyon Adaptive 

Management Program. Projected budgets provide funding for a postdoctoral research ecologist 

3⁄4 time, a research hydrologist 1⁄4 time, and a technician 1⁄4 time. The agreement also projects 

support for 12 pay periods of IT specialist/geographer time for improvements to the Lake 

Powell water quality database and to develop a method of serving the data.

REFERENCES

Bureau of Reclamation, 2011, Glen Canyon Dam penstock withdrawal characteristics, 2007-

2008: Denver, Colo., U.S. Department of the Interior, Bureau of Reclamation, Middle River 

Division-Glen Canyon Unit Colorado River Storage Project, Hydraulic laboratory report HL-2011-

02, 49 p., https://www.usbr.gov/tsc/techreferences/hydraulics_lab/pubs/HL/HL-2011-02.pdf.

DelSontro, T., Beaulieu, J.J., and Downing, J.A., 2018, Greenhouse gas emissions from lakes and 

impoundments—Upscaling in the face of global change: Limnology and Oceanography Letters, 

v. 3, no. 3, p. 64-75, https://doi.org/10.1002/lol2.10073.

Hueftle, S.J., and Stevens, L.E., 2001, Experimental flood effects on the limnology of Lake Powell 

Reservoir, southwestern USA: Ecological Applications, v. 11, no. 3, p. 644-656, 

https://doi.org/10.2307/3061107.

Korman, J., Martell, S.J.D., Walters, C.J., Makinster, A.S., Coggins, L.G., Yard, M.D., and Persons, 

W.R., 2012, Estimating recruitment dynamics and movement of rainbow trout (Oncorhynchus 

mykiss) in the Colorado River in Grand Canyon using an integrated assessment model: Canadian 

Journal of Fisheries and Aquatic Sciences, v. 69, no. 11, p. 1827-1849, 

https://doi.org/10.1139/F2012-097.

Lovelock, C.E., Evans, C., Barros, N., Prairie, Y., Alm, J., Bastviken, D., Beaulieu, J.J., Garneau, M., 

Harby, A., Harrison, J., Pare, D., Raadal, H.L., Sherman, B., Zhang, C., Ogle, S.M., Grinham, A., 

Deemer, B., dos Santos, M.A., Kosten, S., Peacock, M., Zhe Li, Z., and Stepanenko, V., 2019, 

Wetlands, in Gómez, D., and Irving, W., eds., 2019 Refinement to the 2006 IPCC guidelines for 

national greenhouse Gas inventories: IPCC, chap. 7, v. 4, 7.1-7.54 p., https://www.ipccnggip.iges.or.jp/public/2019rf/index.html.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

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O'Reilly, C.M., Sharma, S., Gray, D.K., Hampton, S.E., Read, J.S., Rowley, R.J., Schneider, P., 

Lenters, J.D., McIntyre, P.B., Kraemer, B.M., Weyhenmeyer, G.A., Straile, D., Dong, B., Adrian, 

R., Allan, M.G., Anneville, O., Arvola, L., Austin, J., Bailey, J.L., Baron, J.S., Brookes, J.D., de Eyto, 

E., Dokulil, M.T., Hamilton, D.P., Havens, K., Hetherington, A.L., Higgins, S.N., Hook, S., 

Izmest'eva, L.R., Joehnk, K.D., Kangur, K., Kasprzak, P., Kumagai, M., Kuusisto, E., Leshkevich, G., 

Livingstone, D.M., MacIntyre, S., May, L., Melack, J.M., Mueller-Navarra, D.C., Naumenko, M., 

Noges, P., Noges, T., North, R.P., Plisnier, P.-D., Rigosi, A., Rimmer, A., Rogora, M., Rudstam, 

L.G., Rusak, J.A., Salmaso, N., Samal, N., Schindler, D.E., Schladow, S.G., Schmid, M., Schmidt, 

S.R., Silow, E., Soylu, M.E., Teubner, K., Verburg, P., Voutilainen, A., Watkinson, A., Williamson, 

C.E., and Zhang, G., 2015, Rapid and highly variable warming of lake surface waters around the 

globe: Geophysical Research Letters, v. 42, no. 24, p. 10773-10781, 

https://doi.org/10.1002/2015GL066235.

Prairie, Y.T., Mercier-Blais, S., and Nahas, R., 2017, The GHG reservoir tool (G-res) technical 

documentation—UNESCO/IHA research project on the GHG status of freshwater reservoirs—

Version 1.12: Joint publication of the UNESCO Chair in Global Environmental Change and the 

International Hydropower Association, 76 p., 

https://www.hydropower.org/sites/default/files/publications-docs/gres_technical_document_v1.12.pdf.

Scherer, L., and Pfister, S., 2016, Hydropower's biogenic carbon footprint: PLOS One, v. 11, no. 

9, e0161947, p. 1-11, https://doi.org/10.1371/journal.pone.0161947.

Vernieu, W.S., 2009, Historical physical and chemical data for water in Lake Powell and from 

Glen Canyon Dam releases, Utah-Arizona, 1964-2013 (ver. 3.0, February 2015): U.S. Geological 

Survey Data Series 471, 23 p., https://doi.org/10.3133/ds471.

Vernieu, W.S., 2015, Biological data for water in Lake Powell and from Glen Canyon Dam 

releases, Utah and Arizona, 1990-2009: U.S. Geological Survey Data Series 959, 12 p., 

https://doi.org/10.3133/ds959.
Grand Canyon Monitoring and Research Center, FY 2019 Annual Project Report to the Glen Canyon Dam Adaptive Management Program

[150]

PRODUCTS

(Product order: Presentation, Journal article, Report, USGS Report, USGS Data, Web application)

Type Title Date 

Delivered

Date 

Expected Citation, URL, or Notes

Presentation

Lake Powell 

significantly reduces 

the concentration, 

seasonal variation, 

and downstream 

transport of major 

cations and anions 

in the Colorado 

River

June 

2018

Deemer, B.R., Stets, E., and Yackulic, C.B., 

2018, Lake Powell significantly reduces the 

concentration, seasonal variation, and 

downstream transport of major cations and 

anions in the Colorado River—presentation: 

Victoria, B.C., June 12, 2018, Talk at the 

Association for the Sciences of Limnology 

and Oceanography Meeting.

Presentation

Shifting 

phytoplankton and 

zooplankton 

phenology in recent 

decades in Lake 

Powell reservoir, 

southwestern USA

Aug

2019

Marinelli, M.B., Strock, K.E.D., and Deemer, 

B.R., 2019, Shifting phytoplankton and 

zooplankton phenology in recent decades in 

Lake Powell reservoir, southwestern USA—

poster: Louisville KY, August 13, 2019, 

Ecological Society of America Meeting. 

Presentation

Lake Powell—A 

critical 

biogeochemical 

regulator of 

downstream 

ecosystems

Dec

2018

Deemer, B.R., and Yackulic, C.B., 2018, Lake 

Powell—A critical biogeochemical regulator 

of downstream ecosystems—poster: 

December 5, 2018, Rottnest Island, 

Australia, Poster at the Global Lakes 

Ecological Observatory Network Meeting. 

Journal 

article

Calcite precipitation 

in Lake Powell 

reduces alkalinity 

and total salt 

loading to the Lower 

Colorado River Basin

Dec 

2019

Deemer, B.R., E. Stets, and C.B. Yackulic, in 

revision, Calcite precipitation in Lake Powell 

reduces alkalinity and total salt loading to 

the Lower Colorado River Basin: Limnology 

and Oceanography.

Journal 

article

Are greenhouse gas 

emissions from Lake 

Powell significant in 

a policy decision 

making context? 

Results from existing 

models and an 

exploratory dataset

June 

2020

Are greenhouse gas emissions from Lake 

Powell significant in a policy decision making 

context? Results from existing models and 

an exploratory dataset: To be submitted to 

Environmental Science and Policy journal.

USGS 

Data

Calcium, magnesium 

and total dissolved 

solids data as well as 

modeled salinity and 

mass balance 

estimates for Lake 

Powell, 1952-2017

Dec 

2019

Deemer, B.R., 2019, Calcium, magnesium 

and total dissolved solids data as well as 

modeled salinity and mass balance 

estimates for Lake Powell, 1952-2017: U.S. 

Geological Survey data release, doi: 

10.5066/P9A9P44R, (Note: When this data 

goes online, it will be available at 

https://doi.org/10.5066/P9A9P44R.).
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Tables A and B

Tables A and B present funding by project carried forward from FY 2019 to FY 2020 with short 

narratives outlining the purpose for which the funds will be used in FY 2020. This information 

was provided to Reclamation in support of two requests from GCMRC to deobligate funding 

from the 5-year interagency agreement between the two agencies that expired on September 

30, 2019 and reobligate these funds to a new 5-year interagency agreement which was 

established in August 2019. The majority of these funds are to support the work of GCMRC’s 

cooperators including the U.S. Fish and Wildlife Service, Arizona Game and Fish Department, 

and Northern Arizona University as outlined in the Triennial Workplan FY 2018–2020. Funding 

from GCMRC for agreements with cooperators does not typically align with the federal fiscal 

year due to the timing of Congressional budget approvals and the time it takes for Reclamation 

to receive funds and then, in turn, transfer those funds to GCMRC. The end of the last 5-year 

agreement and establishing a new one created the need for the deobligations and reobligations 

described above since funds transferred to cooperators earlier in FY 2019 could only be used 

for costs incurred through September 30, 2019.
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Table A: Planned Uses of Final Deobligation from Previous 5-Year Agreement

Agency/ 

Cooperator/Contractor Project/Activity Amount

NAU

Project C / Planned carryover to fund a NAU cooperator researching riparian vegetation dynamics in Grand Canyonto provide decision support to NPS efforts to experimentally manage 

native and nonnative plants. Funding of agreement postponed to FY20 due to delays in receiving USGS and DOI approvals for the cooperative agreement. $89,000

NAU

Project C / Planned carryover to fund a NAU cooperator to analyze remote sensed data of riparian vegetation to provide decision support to NPS efforts to experimentally manage native 

and nonnative plants in Grand Canyon. Funding of agreement postponed to FY20 due to delays in receiving USGS and DOI approvals for the cooperative agreement. $81,773

USGS-GCMRC

Project C / Planned carryover to fund a term plant ecologist position not originally included in the FY20 workplan due to a lack of funds. The ecologist will analyze riparian vegetation data 

in support of to NPS efforts to experimentally manage native and nonnative plants in Grand Canyon. $75,100

USGS-GCMRC Project D / Planned carryover to support completion of the effects of dam operations on geomorphic featues and associated archeological sites in Grand Canyon. $19,469

USGS-GCMRC

Project E / This project is a new effort that began in the FY18-20 Triennial Workplan to describe the roles of temperature and nutrients as drivers of ecosystem processes in the Colorado 

River downstream of Glen Canyon Dam and in Grand Canyon. This will help resource managers understand what factors control the aquatic food base and, in turn, fish populations of 

concern including the endangered humpback chub and rainbow trout, an important sport fish. Sample processing, data entry, and analysis of data collected in FY19 are behind schedule 

due to a vacant technician position and delays by the USGS Regional Human Resources Office in advertising and hiring that position. This work will now need to be completed in FY20 along 

with work already planned for FY20. Due to this additional workload, GCMRC proposes to hire an additional technician such that all tasks outlined in the FY18-20 Triennial Workplan are 

completed by the end of FY20.

$47,342

USGS-GCMRC Project F / Planned carryover to support processing of aquatic insect samples collected during the 2019 Bug Flows to detemine the effect of this experiment. $13,995

USGS-GCMRC

Project G / GCMRC is responsible for generating annual population estimates of endangered humpback chub in order for Reclamation to remain in compliance with the 2016 Biological 

Opinion. Funding for this project supports those efforts. Processing and analysis of humpback chub data collected in FY19 is behind schedule due the retirement of a staff member and 

delays by the USGS Regional Human Resources Office in advertising and refilling the position. This work will now need to be completed in FY20 along with work already planned for FY20. 

Due to this additional workload, GCMRC proposes to hire an additional post doc position supported in part by carryover from this project (support will also come from Project H) to help 

complete all tasks outlined in the FY18-20 Triennial Workplan by the end of FY20. 

$101,749

USGS-GCMRC

Project H / GCMRC is responsible for generating information on rainbow trout and brown trout distribution, abundance, production, and other metrics of concern for Colorado River 

populations of these species downstream of Glen Canyon Dam and in Grand Canyon. Results are provided to Reclamation and the Glen Canyon Dam Adaptive Management Program in 

support of implementation of the Long-Term Experimental and Management Plan and its Record of Decision. Funding for this project supports those efforts. Processing and analysis of 

rainbow trout and brown trout collected in FY19 is behind schedule due the retirement of a staff member and delays by the USGS Regional Human Resources Office in advertising and 

refilling the position. This work will now need to be completed in FY20 along with work already planned for FY20. Due to this additional workload, GCMRC proposes to hire an additional 

post doc position supported in part by carryover from this project (support will also come from Project G) to help complete all tasks outlined in the FY18-20 Triennial Workplan by the end 

of FY20.

$82,843

USGS-GCMRC Project I / Funds will be used to support continued laboratory studies of predation by nonnative warm water fishes on native fishes. $4,887

ASU

Project J / Funding for ASU cooperator to help evaluate planned NPS incentivised harvest program to control Brown Trout in Glen Canyon. Funding of agreement postponed to FY20 due to 

delays in receiving USGS and DOI approvals for the cooperative agreement. $38,000

USGS-GCMRC Project J / Funds will be used to support continued socioeconomics studies of tribal perspectives and values of resources in Grand Canyon. $8,946

USGS-GCMRC

Project K / Planned carryover to fund a position that wasn't fully supported in the FY20 workplan due to a lack of funds. This position will help to provide geospatial support for other 

GCMRC projects and to serve geospatial information and products over the internet to DOI, Reclamation, GCDAMP, stakeholders and the public. $34,342

USGS-GCMRC Project L / Planned carryover of funds budgeted in FY18 and FY 19 in support of the remote sensing overflight of Grand Canyon planned for FY21. $150,000

USGS-GCMRC

Project M / Carryover of funds will be used for the following IT expenses that were planned for FY19, but delayed into FY20: six Life Cycle Replacement Laptops with docking stations, mice, 

and keyboards ($1,800 each) = $10,800 and one Xen VM server = $9,000. $19,752

USGS-GCMRC

Logistics / Funds will be used to support GCMRC field operations and to replace damaged equipment as needed. Carryover amount is due to delays in hiring a vacancy created due to a 

retirement.

$34,398

Ceiba

Logistics / Funds will be used to fully fund the remainder of the first year (through July 2020) of the five-year agreement with Ceiba Adventures to provide professional boat operators and 

technicians in support of GCMRC field operations. Full funding could not be obligated to this contract due to guidance from Reclamation to not allow spending on obligated funds from IA 

#R19PG00070 beyond Sept. 30, 2019. 

$245,433

Total $1,047,029

Planned Uses of Final Deobligation from Previous 5-Year Agreement
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Table B: August 2019 Deobligation

Cooperator/ Contractor Project/activity Amount

NAU

Project B / Long Term Sediment Monitoring in Grand Canyon. Funds were used to supoort continued long-term monitoring of sandbars in Grand Canyon by NAU in FY2020. Specifically, this 

project involves monitoring and research to measure erosion and deposition of sediment in Grand Canyon. This information is used by the Department of the Interior to inform decisions 

regarding the operations of Glen Canyon Dam in order to manage sediment resources downstream of the dam. NAU collaborators participate with USGS collaborators in data collection, 

have lead responsibility for data processing, and work with USGS collaborators on data analysis and reporting. The NAU team has the specialized knowledge and background from many 

previous years of working on the Colorado River to perform the specific data collection and analyses required for this work. One river trip headed by NAU and which occurred in early 

FY2020 was supported from this amount.

$448,206

USFWS

Project G / GCMRC is responsible for generating annual population estimates of endangered humpback chub for Reclamation to remain in compliance with the 2016 Biological Opinion. 

Funding for US Fish & Wildlife Service supports these efforts. USFWS collects data on the distribution, relative abundance, and condition of humpback chub. Funds were used to support 

USFWS field data collection operations as well as data analysis and reporting related to the humpback chub aggregations in the mainstem Colorado River. 

$67,590

USFWS

Project G / GCMRC is responsible for generating annual population estimates of endangered humpback chub for Reclamation to remain in compliance with the 2016 Biological Opinion. 

Funding for US Fish & Wildlife Service supports these efforts. USFWS collects data on the distribution, relative abundance, and condition of humpback chub. Funds were used to support 

field data collection operations as well as data analysis and reporting related to the humpback chub the Little Colorado River including translocation efforts.

$262,017

AZGFD

Project H / GCMRC is responsible for generating information on rainbow trout and brown trout distribution, abundance, production, and other metrics of concern for Colorado River 

populations of these species between Glen Canyon Dam and Lees Ferry. Results are provided to Reclamation and the Glen Canyon Dam Adaptive Management Program in support of 

implementation of the Long-Term Experimental and Management Plan and its Record of Decision. Funding for Arizona Game & Fish Department (AZGFD) supports these efforts. AZGFD 

collects data on the distribution, catch rates, and condition of rainbow trout and brown trout in the mainstem Colorado River upstream of Lees Ferry. Funds were used to support field data 

collection operations as well as data analysis and reporting. 

$77,080

AZGFD

Project H / GCMRC is responsible for generating information on native and nonnative fish distribution, abundance, production, and other metrics of concern for Colorado River populations 

in Grand Canyon. Results are provided to Reclamation and the Glen Canyon Dam Adaptive Management Program in support of implementation of the Long-Term Experimental and 

Management Plan and its Record of Decision. Funding for Arizona Game & Fish Department (AZGFD) supports these efforts. AZGFD collects data on the distribution and catch rates of 

native and nonnative fishes in the mainstem Colorado River downstream of Lees Ferry. Funds were used to support field data collection operations as well as data analysis and reporting.

$188,509

Mango Logistics / Funds will be used to provide additional needed drivers and warehouse help through a contract with Mango Tree Enterprises in support of GCMRC field operations. $56,000

CEIBA

Logistics / Funds will be used to initially fund the five-year agreement with Ceiba Adventures to provide professional boat operators and technicians in support of GCMRC field operations. 

The contract with CEIBA required a minimum obligation of $400,000. An initial amount of $256,200 of funding needed to be deobligated from FY19 obligations and immediately reobligated 

in FY20 in order to meet the required minimum obligation of $400,000 and continue to conduct river operations.

$256,200

Total $1,355,602

2,402,631.00

August 2019 Deobligation