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Glen Canyon Dam Technical Work Group 

Agenda Item Information 

June 24, 2014

Agenda Item 

Glen Canyon Dam Adaptive Management Program FY 2015-17 Budget and Work Plan 

Action Requested 

 Finalize 2015-17 Budget 

 Propose motion for AMWG 

Presenter 

Glen Knowles, Adaptive Management Group Chief, Bureau of Reclamation, Upper Colorado 

Region 

Jack Schmidt, Chief, Grand Canyon Monitoring and Research Center 

Scott VanderKooi, Deputy Chief, Grand Canyon Monitoring and Research Center 

Shane Capron, Technical Work Group Vice-Chair 

Previous Action Taken 

August 9, 2013 – Motion (Proposed by Kerry Christensen, seconded by Larry Stevens): AMWG 

recommends the FY2013-14 Biennial Budget and Work Plan for the Bureau of Reclamation and the 

Grand Canyon Monitoring and Research Center that includes the 2014 sequestration impacts, as 

reviewed by the TWG on June 26, 2013, and as revised by Reclamation and presented at the August 

2013 meeting to the Secretary of the Interior for approval. In the event that sequestration is not 

implemented in FY2014 budget, AMWG recommends the revised FY2013-14 Biennial Budget and 

Work Plan from the Bureau of Reclamation and Grand Canyon Monitoring and Research Center 

without the 2014 sequestration. Hearing no objection, the motion was passed by consensus. 

December 12, 2013 – Memorandum from Secretary Jewell - Report and Recommendations from 

the Glen Canyon Dam Adaptive Management Work Group Federal Advisory Committee Meetings 

held on February 20-21, 2013, May 8, 2013, and August 8-9, 2013 

http://www.usbr.gov/uc/rm/amp/amwg/mtgs/13aug08/Attach_14.pdf

Relevant Science 

Glen Canyon Dam Adaptive Management Program Biennial Budget and Work Plan—Fiscal Years 

2013–14 

http://www.usbr.gov/uc/rm/amp/amwg/mtgs/12aug29/Attach_08b.pdf

May 7, 2014 Memorandum from Assistant Secretary Anne Castle directing GCMRC and 

Reclamation to prepare a three-year budget and work plan for the GCDAM for FY 2015-17. 

http://www.usbr.gov/uc/rm/amp/amwg/mtgs/14may27/AC_Memo_TriennialBWP.pdf

June 6, 2014 Glen Canyon Dam Adaptive Management Program Triennial Budget and Work Plan 

Fiscal Years 2015-2017 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/14jun24/TWP_14jun06.pdf
GCDAMP FY15-16 BWP, continued 

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Background Information 

The Bureau of Reclamation and Grand Canyon Monitoring and Research Center with input from 

the TWG and BAHG has developed a draft FY 2015-17 Budget and Work Plan (BWP) for TWG 

review. 

Proposed Motion: TWG recommends the revised FY2015-17 Triennial Budget and Work Plan from the Bureau of 

Reclamation and Grand Canyon Monitoring and Research Center as reviewed by TWG on June 24 & 25, 2014 

and presented at the August 2014 AMWG meeting, to the Secretary of the Interior for approval. 
U.S. Department of the Interior

U.S. Geological Survey

Glen Canyon Dam 

Adaptive Management 

Program Triennial 

Budget

and Work Plan— 

Fiscal Years 2015–2017

Prepared by 

Bureau of Reclamation

Upper Colorado Regional Office

and

U.S. Geological Survey

Grand Canyon Monitoring and 

Research Center

Prepared in cooperation with the 

Glen Canyon Dam Adaptive 

Management Program 

Planning Document

Draft: June 6, 2014
Cover: View of Colorado River from Nankoweap Trail in Marble Canyon, Grand Canyon National Park, 

Scott VanderKooi, U.S. Geolgoical Survery.
Prepared in cooperation with the Glen Canyon Dam Adaptive Management 

Program

Glen Canyon Dam Adaptive Management 

Program Biennial Budget and Work Plan—

Fiscal Years 2015–2017

Prepared by

Bureau of Reclamation

Upper Colorado Regional Office

Salt Lake City, Utah

and

U.S. Geological Survey

Southwest Biological Science Center

Grand Canyon Monitoring and Research Center

Flagstaff, Arizona

Draft: June 6, 2014

U.S. Department of the Interior

U.S. Geological Survey
Contents 

Introduction............................................................................................................................................................................9

A.1. Adaptive Management Work Group Costs .................................................................................................................11

A.2. AMWG Member Travel Reimbursement.....................................................................................................................12

A.3. AMWG Reclamation Travel.........................................................................................................................................13

A.4. AMWG Facilitation Contract .......................................................................................................................................14

A.5. Public Outreach ............................................................................................................................................................15

A.6. AMWG Other ...............................................................................................................................................................16

B.1. TWG Costs....................................................................................................................................................................17

B.2. TWG Member Travel Reimbursement.........................................................................................................................18

B.3. TWG Reclamation Travel .............................................................................................................................................19

B.4. TWG Chair Reimbursement/Facilitation......................................................................................................................20

B.5. TWG Other....................................................................................................................................................................21

C.1. Administrative Support for NPS Permitting.................................................................................................................22

C.2. Contract Administration...............................................................................................................................................23

C.3. Science Advisor Contract.............................................................................................................................................24

C.4. Experimental Fund........................................................................................................................................................25

C.5. Native Fish Conservation Contingency Fund ...............................................................................................................26

D.1. Cultural Resources Program Administrative Costs.....................................................................................................27

D.2. Cultural Resources Work Plan .....................................................................................................................................28

D.3. Integrated Tribal Resources Monitoring .....................................................................................................................32

D.4. Tribal Participation in the GCDAMP ............................................................................................................................33

Chapter 2. U.S. Geological Survey, Southwest Biological Science Center, Grand Canyon Monitoring and 

Research Center Triennial Budget and Work Plan—Fiscal Years 2015–2017..................................................................36

Introduction......................................................................................................................................................................36

Purpose ............................................................................................................................................................................36

Overview of the FY15–17 GCMRC Monitoring and Research Program .........................................................................37

Overview of the FY 15–17 Projects.................................................................................................................................38

Reservoir water quality, sediment-transport/water-quality/stream-flow measurement, geomorphology of 

the active channel, and geomorphology of the Colorado River valley above the active channel .............................38

Projects in Aquatic and Fish Ecology...........................................................................................................................40

Projects in Riparian Ecology........................................................................................................................................42

Cultural Resources Monitoring and Research Project ................................................................................................43

Socioeconomic Project.................................................................................................................................................44

Independent Review and Science Oversight...............................................................................................................44

GCMRC Project Administration ...................................................................................................................................45

Relation between FY15–17 Triennial Work Plan and Administrative Guidance ...........................................................45

Desired Future Conditions ...........................................................................................................................................45

Science Planning to Implement the Environmental Assessment for a Protocol for High-Flow Experimental 

Releases.......................................................................................................................................................................49

Science Planning to Implement the Environmental Assessment for Non-Native Fish Control .................................49

Research and Monitoring Priorities Provided by Assistant Secretary Castle ............................................................50

General Core Monitoring Plan .....................................................................................................................................51

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Monitoring and Research Plan ....................................................................................................................................51

Allocation of the FY15–17 Budget ..................................................................................................................................51

References.......................................................................................................................................................................52

Project 2. Streamflow, Water Quality, and Sediment Transport in the Colorado River Ecosystem..................................54

A. Investigators................................................................................................................................................................54

B. Project Summary..........................................................................................................................................................54

C. Background ..................................................................................................................................................................54

C.1. Scientific Background...........................................................................................................................................54

C.2. Management Background ....................................................................................................................................56

C.3. Key Monitoring and Research Questions Addressed in this project...................................................................57

D. Proposed Work............................................................................................................................................................58

D.1. Project Elements...................................................................................................................................................58

D.2 Personnel and Collaborations...............................................................................................................................60

D.3 Deliverables...........................................................................................................................................................60

E. Productivity from Past Work (during FY 13–14) ..........................................................................................................61

E.1. Data Products........................................................................................................................................................61

E.2. Completed Publications........................................................................................................................................62

E.3. Publications in progress........................................................................................................................................62

E.4. Presentations at GCDAMP meetings ...................................................................................................................63

E.5. Presentations at professional meetings...............................................................................................................63

F. References ...................................................................................................................................................................63

G. Budget .........................................................................................................................................................................67

Project 3. Sandbars and Sediment Storage Dynamics: Long-term Monitoring and Research at the Site, Reach, 

and Ecosystem Scales. ........................................................................................................................................................68

A. Investigators................................................................................................................................................................68

B. Project Summary..........................................................................................................................................................68

C. Background ..................................................................................................................................................................70

C.1. Scientific Background...........................................................................................................................................71

C.2. Management Background ....................................................................................................................................78

C.3. Key Monitoring and Research Questions Addressed in this project...................................................................80

D. Proposed Work............................................................................................................................................................81

D.1. Project Elements...................................................................................................................................................83

D.2 Personnel and Collaborations.............................................................................................................................128

D.3 Deliverables.........................................................................................................................................................128

E. Productivity from Past Work (during FY 13–14) ........................................................................................................129

E.1. Data Products......................................................................................................................................................129

E.2. Completed Publications......................................................................................................................................129

E.3. Publications in progress......................................................................................................................................130

E.4. Presentations at GCDAMP meetings .................................................................................................................131

E.5. Presentations at professional meetings.............................................................................................................131

F. References .................................................................................................................................................................132

G. Budget .......................................................................................................................................................................140

Project 4. Connectivity along the fluvial-aeolian-hillslope continuum: quantifying the relative importance of 

river-related factors that influence upland geomorphology and archaeological site stability........................................142

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A. Investigators..............................................................................................................................................................142

B. Project Summary........................................................................................................................................................142

C. Background ................................................................................................................................................................142

C.1. Scientific Background.........................................................................................................................................142

C.2. Management Background ..................................................................................................................................147

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................151

D. Proposed Work..........................................................................................................................................................153

D.1. Project Elements.................................................................................................................................................153

D.2. Personnel and Collaborations............................................................................................................................162

D.3. Deliverables........................................................................................................................................................162

E. Productivity from Past Work (during FY 13–14) ........................................................................................................163

E.1. Data Products......................................................................................................................................................163

E.2. Completed Publications......................................................................................................................................163

E.3. Publications in progress......................................................................................................................................163

E.4. Presentations at GCDAMP meetings .................................................................................................................163

E.5. Presentations at professional meetings.............................................................................................................164

F. References .................................................................................................................................................................164

G. Budget .......................................................................................................................................................................169

Project 5. Foodbase Monitoring and Research.................................................................................................................171

A. Investigators..............................................................................................................................................................171

B. Project Summary........................................................................................................................................................171

C. Background ................................................................................................................................................................172

C.1. Scientific Background.........................................................................................................................................172

C.2. Management Background ..................................................................................................................................178

C.3. Key Monitoring and Research Questions Addressed ........................................................................................180

C.4. Hypotheses Explaining Aquatic Invertebrate Productivity and Diversity..........................................................180

D. Proposed Work..........................................................................................................................................................186

D.1. Project Elements.................................................................................................................................................186

D.2. Personnel and Collaborations............................................................................................................................195

D.3. Deliverables........................................................................................................................................................196

E. Productivity from Past Work (during FY 13–14) ........................................................................................................197

E.1. Data Products......................................................................................................................................................197

E.2. Completed Publications......................................................................................................................................197

E.3. Publications in progress......................................................................................................................................198

E.4. Presentations at GCDAMP meetings .................................................................................................................198

E.5. Presentations at professional meetings.............................................................................................................198

F. References .................................................................................................................................................................199

G. Budget .......................................................................................................................................................................204

Project 6. Mainstem Colorado River humpback chub aggregations and fish community dynamics...............................212

A. Investigators..............................................................................................................................................................212

B. Project Summary........................................................................................................................................................212

C. Background ................................................................................................................................................................215

C.1 Scientific Background..........................................................................................................................................215

C.2. Key Monitoring and Research Questions Addressed in this project.................................................................217

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C.3. Key management goals and objectives addressed in this project....................................................................218

D. Proposed Work..........................................................................................................................................................218

D.1. Project Elements.................................................................................................................................................218

D.2 Personnel and Collaborations.............................................................................................................................225

D.3 Deliverables.........................................................................................................................................................226

E. Productivity from Past Work......................................................................................................................................226

E.1. Data Products......................................................................................................................................................226

E.2. Publications in progress......................................................................................................................................226

E.3. Presentations at GCDAMP meetings .................................................................................................................227

E.4. Presentations at professional meetings.............................................................................................................227

F. References .................................................................................................................................................................228

G. Budget .......................................................................................................................................................................233

Project 7. Population Ecology of Humpback Chub in and around the Little Colorado River............................................236

A. Investigators..............................................................................................................................................................236

B. Project Summary........................................................................................................................................................236

C. Background ................................................................................................................................................................239

C.1. Scientific Background.........................................................................................................................................239

C.2. Management Background ..................................................................................................................................241

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................241

D. Proposed Work..........................................................................................................................................................243

D.1. Project Elements.................................................................................................................................................243

D.2 Personnel and Collaborations.............................................................................................................................250

D.3 Deliverables.........................................................................................................................................................250

E. Productivity from Past Work (during FY 13–14) ........................................................................................................251

E.1. Data Products......................................................................................................................................................251

E.2. Completed Publications......................................................................................................................................251

E.3. Publications in progress......................................................................................................................................251

E.4. Presentations at GCDAMP meetings .................................................................................................................251

E.5. Presentations at professional meetings.............................................................................................................252

F. References .................................................................................................................................................................252

G. Budget .......................................................................................................................................................................255

Project 8. Management Actions to Increase Abundance and Distribution of Native Fishes in Grand Canyon ..............258

A. Investigators..............................................................................................................................................................258

B. Project Summary........................................................................................................................................................258

C. Background ................................................................................................................................................................259

C.1. Management Background ..................................................................................................................................259

C.2 Key Monitoring and Research Questions Addressed in this Project..................................................................260

D. Proposed Work..........................................................................................................................................................261

D.1. Project Elements.................................................................................................................................................261

D.2 Personnel and Collaborations.............................................................................................................................265

D.3 Deliverables.........................................................................................................................................................265

E. Productivity from Past Work (during FY 13–14) ........................................................................................................265

E.1. Data Products......................................................................................................................................................265

E.2. Publications in progress......................................................................................................................................265

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E.3. Presentations at GCDAMP meetings .................................................................................................................266

E.4. Presentations at professional meetings.............................................................................................................266

F. References .................................................................................................................................................................266

G. Budget .......................................................................................................................................................................268

Project 9. Understanding the Factors Determining Recruitment, Population Size, Growth, and Movement of 

Rainbow Trout in Glen and Marble Canyons....................................................................................................................271

A. Investigators..............................................................................................................................................................271

B. Project Summary........................................................................................................................................................271

C. Background ................................................................................................................................................................274

C.1. Scientific Background.........................................................................................................................................278

C. 2. Key Monitoring and Research Questions Addressed in this Project................................................................281

D. Proposed Work- Monitoring and Research Projects................................................................................................282

D.1. Project Elements- Research ...............................................................................................................................282

D.2 Personnel and Collaborations.............................................................................................................................295

D.3 Deliverables.........................................................................................................................................................295

E. Productivity from Past Work (during FY 13–14) ........................................................................................................296

E.1. Completed Publications......................................................................................................................................296

E.2. Publications in progress......................................................................................................................................296

E.3. Presentations at GCDAMP meetings .................................................................................................................296

E.4. Presentations at professional meetings.............................................................................................................297

F. References .................................................................................................................................................................297

G. Budget .......................................................................................................................................................................304

Project 10. Where does the Glen Canyon Dam rainbow trout tailwater fishery end? - Integrating Fish and 

Channel Mapping Data below Glen Canyon Dam............................................................................................................307

A. Investigators..............................................................................................................................................................307

B. Project Summary........................................................................................................................................................307

C. Background ................................................................................................................................................................311

C.1. Scientific Background.........................................................................................................................................312

C.2. Management Background ..................................................................................................................................323

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................325

D. Proposed Work..........................................................................................................................................................327

D.1. Project Elements.................................................................................................................................................327

D.2 Personnel and Collaborations.............................................................................................................................342

D.3 Deliverables.........................................................................................................................................................342

E. Productivity from Past Work (during FY 13–14) ........................................................................................................342

E.1. Data Products......................................................................................................................................................342

E.2. Completed Publications......................................................................................................................................342

E.3. Publications in progress......................................................................................................................................342

E4. Presentations at GCDAMP meetings ..................................................................................................................343

E.5. Presentations at professional meetings.............................................................................................................343

F. References .................................................................................................................................................................343

G. Budget .......................................................................................................................................................................348

Project 11. Riparian Vegetation Monitoring and Analysis of Riparian Vegetation, Landform Change and 

Aquatic-Terrestrial linkages to Faunal Communities.......................................................................................................350

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A. Investigators..............................................................................................................................................................350

B. Project Summary........................................................................................................................................................350

C. Background ................................................................................................................................................................351

C.1. Scientific Background.........................................................................................................................................355

C.2. Management Background ..................................................................................................................................356

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................357

D. Proposed Work..........................................................................................................................................................358

D.1. Project Elements.................................................................................................................................................358

D.2. Personnel and Collaborations............................................................................................................................377

D.3. Deliverables........................................................................................................................................................377

E. Productivity from Past Work (during FY 13–14) ........................................................................................................377

E.1. Data Products......................................................................................................................................................377

E.2. Completed Publications......................................................................................................................................377

E.3. Publications in progress......................................................................................................................................378

E.4. Presentations at GCDAMP meetings .................................................................................................................378

E.5. Presentations at professional meetings.............................................................................................................378

F. References .................................................................................................................................................................378

G. Budget .......................................................................................................................................................................384

Project 12. Dam-Related Effects on the Distribution and Abundance of Selected Culturally-Important Plants in 

the Colorado River Ecosystem...........................................................................................................................................387

A. Investigators..............................................................................................................................................................387

B. Project Summary........................................................................................................................................................387

C. Background ................................................................................................................................................................388

C.1. Scientific Background.........................................................................................................................................388

C.2. Key Monitoring and Research Questions Addressed in this project.................................................................390

D. Proposed Work..........................................................................................................................................................390

D.1. Project Elements.................................................................................................................................................391

D.2 Personnel and Collaborations.............................................................................................................................393

D.3. Deliverables........................................................................................................................................................393

E. References.................................................................................................................................................................393

F. Budget ........................................................................................................................................................................396

Project 13. Socioeconomic Monitoring and Research......................................................................................................398

A. Investigators..............................................................................................................................................................398

B. Project Summary........................................................................................................................................................398

C. Background ................................................................................................................................................................399

C.1. Scientific Background.........................................................................................................................................401

C.2. Key Monitoring and Research Questions Addressed in this project.................................................................402

D. Proposed Work..........................................................................................................................................................403

D.1. Project Elements.................................................................................................................................................403

D.2 Personnel and Collaborations.............................................................................................................................408

D.3 Deliverables.........................................................................................................................................................409

E. References.................................................................................................................................................................409

F. Budget ........................................................................................................................................................................411

Project 14. Geographic Information Systems (GIS) Services and Support.......................................................................413

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A. Investigators..............................................................................................................................................................413

B. Project Summary.......................................................................................................................................................413

C. Background ................................................................................................................................................................414

C.1. Scientific Background.........................................................................................................................................414

C.2. Management Background ..................................................................................................................................416

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................416

D. Proposed Work..........................................................................................................................................................417

D.1. Project Elements.................................................................................................................................................417

D.2 Personnel and Collaborations.............................................................................................................................422

D.3 Deliverables.........................................................................................................................................................422

E. Productivity from Past Work (during FY 13/14).........................................................................................................422

E.1. Data Products......................................................................................................................................................422

E.2. Presentations at GCDAMP meetings .................................................................................................................423

E.5. Presentations at professional meetings.............................................................................................................424

F. Budget ........................................................................................................................................................................424

Table 1. A list of GIS planned support for FY15-17 Triennial Work Plan .....................................................................427

Project 15. Administration.................................................................................................................................................429

Budget............................................................................................................................................................................429

Appendices........................................................................................................................................................................431

Appendix 1 Project 1..........................................................................................................................................................432

Project 1. Lake Powell and Glen Canyon Dam Release Water-Quality Monitoring ........................................................432

A. Investigators..............................................................................................................................................................432

B. Project Summary........................................................................................................................................................432

C. Background ................................................................................................................................................................433

C.1. Scientific Background.........................................................................................................................................433

C.2. Management Background ..................................................................................................................................435

C.3. Key Monitoring and Research Questions Addressed in this project.................................................................435

D. Proposed Work..........................................................................................................................................................436

D.1. Project Elements.................................................................................................................................................436

D.2 Personnel and Collaborations.............................................................................................................................439

D.3 Deliverables.........................................................................................................................................................440

E. Productivity from Past Work.....................................................................................................................................440

E.1. Data Products......................................................................................................................................................440

E.2. Completed Publications......................................................................................................................................441

E.3. Publications in progress......................................................................................................................................441

E.4. Presentations at professional meetings.............................................................................................................441

F. References .................................................................................................................................................................442

G. Budget .......................................................................................................................................................................444

Appendix 2-A. Fiscal Year 2015 Budget............................................................................................................................445

Appendix 2-B. Fiscal Year 2015 Funding Source ..............................................................................................................454

Appendix 2-C. Fiscal Year 2016 Budget............................................................................................................................463

Appendix 2-D. Fiscal Year 2017 Budget............................................................................................................................472

Appendix 3. Logistics and Schedules of River Trips and Field Work...............................................................................481

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Chapter 1. Bureau of Reclamation, Glen Canyon Dam 

Adaptive Management Program, Triennial Budget and Work 

Plan—Fiscal Years 2015–17 

Introduction 

The Glen Canyon Dam Adaptive Management Program (GCDAMP) is a science-based process 

for continually improving management practices related to the operation of Glen Canyon Dam 

(GCD) by emphasizing learning through monitoring, research, and experimentation, in fulfillment 

of the consultation and research commitments of the Grand Canyon Protection Act (GCPA). The 

Bureau of Reclamation’s (BOR) Upper Colorado Region (BRUC) is responsible for administering 

funds for the GCDAMP and providing those funds for monitoring, research, and stakeholder 

involvement. The majority of program funding is derived from hydropower revenues; however, 

supplemental funding is provided by various Department of the Interior (DOI) agencies that receive 

appropriations. These agencies include BOR, the U.S. Geological Survey (USGS), the National 

Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), and the Bureau of Indian Affairs 

(BIA).

The budget and work plan for fiscal years (FY) 2015-17 was developed on the basis of previous 

budgets and work plans, the GCDAMP Biennial Budget and Work Process approved by the 

AMWG on May 6, 2010, the Streamlined GCMRC Biennial Work Planning Process, version April 

3, 2011, and the May 7, 2014 memorandum from Assistant Secretary and Secretary’s Designee 

Anne Castle on development of a tiennial GCDAMP Budget and Work Plan. Additional 

consideration was given to meeting the commitments outlined in the following compliance 

documents (1) the 2007 USFWS Biological Opinion for the Proposed Adoption of Colorado River 

Interim Guidelines for Lower Basin Shortages and Coordinated Operations for Lake Powell and 

Lake Mead (2007 Opinion); (2) the 2011 Reclamation Environmental Assessment (EA) and 2012 

Finding of No Significant Impact (FONSI) for Development and Implementation of a Protocol for 

High-Flow Experimental Releases from Glen Canyon Dam, Arizona, 2011 through 2020 (HFE 

Protocol); (3) the 2011 Reclamation EA and 2012 FONSI for Non-native Fish Control Downstream 

from Glen Canyon Dam (NNFC EA and FONSI); and the 2011 USFWS Final Biological Opinion 

on the Operation of Glen Canyon Dam including High Flow Experiments and Non-Native Fish 

Control (2011 Opinion). Additionally, this budget and work plan was developed in consideration of 

the Long-Term Experimental and Management Plan Environmental Impact Statement (LTEMP 

EIS).

The process used to arrive at the FY15-17 budget and work plan was adopted by the AMWG in 

2004 and revised in 2010 to a 2-year fixed budget process, and subsequently revised to a triennial 

budget process by the GCDAMP Secretary’s Designee on May 7, 2014. The Budget Ad Hoc Group 

(BAHG) of the Technical Work Group (TWG), with input from the Cultural Resources Ad Hoc 

Group (CRAHG), worked with the BRUC and GCMRC to develop a proposal for the TWG. The 

TWG then reviews the proposed budget and work plan and develops a recommendation to the 

AMWG.

The FY15-17 budget and work plan was also prepared in consideration of the projected 

hydrograph for Lake Powell release for water year (WY) 2015, which is based on forecasted 

inflows to Lake Powell and GCD releases determined by the 1996 Record of Decision on the 

9
operation of Glen Canyon Dam and the 2007 Record of Decision on Interim Guidelines for 

Coordinated Operation of Lake Mead and Lake Powell. It also observes commitments made in the 

2007 and 2011 U.S. Fish and Wildlife biological opinions. The projected hydrograph is based on 

best estimates available from BOR’s 24-month study released in May 2014, however, the forecast 

is subject to change as further data becomes available.

 

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A.1. Adaptive Management Work Group Costs 

This budget represents BOR staff costs to perform the daily activities required to support the 

Adaptive Management Work Group (AMWG), the GCDAMP Federal Advisory Committee Act

(FACA) committee. The work includes completing assignments resulting from AMWG meetings, 

consulting with stakeholders on a variety of GCDAMP issues relating to the operation of GCD, 

disseminating pertinent information to the AMWG, preparing and tracking budget expenses, and 

updating BOR’s Web page. BOR also responds to regular requests from the General Services 

Administration (GSA) to complete FACA reports and incorporate meeting and member 

information into the FACA database. BOR is now required to complete all stakeholder travel, 

activities that range from preparing travel authorizations to completing travel vouchers.

The primary goal is to perform all work associated with the AMWG in a timely and efficient 

manner, while using the funds available as prudently as possible. Secondary goals include 

increasing each stakeholder’s awareness of significant budget and legislative issues related to the 

GCDAMP, improving working relationships with the AMWG members/alternates, finding 

constructive ways to resolve differences, and addressing individual concerns in an open and 

accepting forum of discussion. 

BOR will work to ensure that personnel costs will not exceed what has been proposed in the 

budget unless Federal employee salaries are increased above the consumer price index (CPI). BOR

staff will provide budget information to the AMWG on a regular basis. Completed work products 

will be of high quality and promptly distributed to AMWG members/alternates and interested 

parties. Budget reports will be presented in a format conducive to AMWG needs.

Budget FY15 = $196,530 FY16 = $202,425 FY17 = $208,498

Reclamation Project - Personnel Costs—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries 134,443 136,846 141,030 141,337 145,578 149,944 154,443

Subtotal 134,443 136,846 141,030 141,337 145,578 149,944 154,443

DOI Overhead (35%) 44,367 47,923 49,361 49,468 50,952 52,481 54,055

Project total 178,810 184,846 190,391 190,805 196,530 202,425 208,498

Total outsourced (%)

 

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A.2. AMWG Member Travel Reimbursement 

This budget covers the costs to reimburse AMWG members or alternates to attend regularly 

scheduled AMWG meetings. 

Reimbursing AMWG members or alternates for travel expenses is done to encourage their 

attendance at all meetings. Many members live outside of Phoenix, Arizona, where meetings are 

often held. As a result, many members must incur travel costs. Having BOR provide 

reimbursement to AMWG members or alternates for air travel or mileage for the use of private 

vehicles, as well as other related travel costs such as hotel, per diem, and rental car increases 

opportunities for members to participate in a variety of AMWG assignments. Because BOR can 

purchase airline tickets at the Federal Government rate, there are additional cost savings to the 

program.

The GCDAMP benefits from having all AMWG members participating in regularly scheduled 

meetings. As a collective body, they address and resolve concerns associated with the operation of 

GCD and make recommendations to the Secretary of the Interior for continued science efforts 

performed below the GCD. 

Budget FY15 = $15,689 FY16 = $16, 159 FY17 = $16,644

Reclamation Project - AMWG Travel Reimbursement—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training 17,671 14,756 15,199 15,232 15,689 16,159 16,644

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 17,671 14,756 15,199 15,232 15,689 16,159 16,644

DOI Overhead (35%) — — — — — — —

Project total 17,671 14,756 15,199 15,232 15,689 16,159 16,644

Total outsourced (%) — — — —— — — —

12
A.3. AMWG Reclamation Travel 

This budget supports travel expenses BOR staff incur to attend AMWG and ad hoc group 

meetings. The primary goal is for BOR staff to be able to travel to meetings and participate in 

completing AMWG/TWG assignments. By doing so, the program benefits from greater interaction 

between BOR staff and GCDAMP members, and opportunities for BOR staff to obtain the latest 

results from monitoring and research being conducted by the GCDAMP.

BOR staff will be involved with AMWG/TWG members in completing work assignments and 

resolving issues that affect the GCDAMP. They will develop better working relationships with all 

involved and work toward consensus with AMWG members on a variety of issues. 

Budget FY15 = $16,097 FY16 = $16,580 FY17 = $17,077

Reclamation Project - Reclamation Travel—Funding History 

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training 14,344 15,140 15,595 15,628 16,097 16,580 17,077

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 14,344 15,140 15,595 15,628 16,097 16,580 17,077

DOI Overhead (35%) — — — — — — —

Project total 14,344 15,140 15,595 15,628 16,097 16,580 17,077

Total outsourced (%) — — — — — — —

 

13
A.4. AMWG Facilitation Contract 

This budget supports a facilitator who is under contract to BOR to provide facilitations services 

for AMWG meetings. This person may also assist AMWG ad hoc groups in completing 

assignments.

The facilitator’s primary responsibility is to keep the AMWG meetings organized and help the 

members reach consensus on important issues. The facilitator will create an atmosphere in which 

the members and other participants at AMWG meetings feel comfortable expressing their 

individual viewpoints.

Budget FY15 = $79,556 FY16 = $81,943 FY17 = $84,401

Reclamation Project - Facilitation Contract—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 27,274 40,531 41,747 0 79,556 81,943 84,401

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 27,274 40,531 41,747 0 79,556 81,943 84,401

DOI Overhead (35%) — — — — — — —

Project total 27,274 40,531 41,747 0 79,556 81,943 84,401

Total outsourced (%) — — — — — — —

14
A.5. Public Outreach 

This budget covers the expenses for BOR staff and the Public Outreach Ad Hoc Group 

(POAHG) to develop materials for the GCDAMP public outreach efforts.

BOR public affairs staff and the POAHG will work jointly in developing materials to inform 

and educate the public on the goals and administration of the GCDAMP. They will keep other 

GCDAMP members advised of progress and expenditures. 

Products will include fact sheets, Web site information, tribal outreach materials, video B-roll, 

special events, conference participation, and other pertinent means of advising the public and 

program members on the achievements of the GCDAMP. The POAHG will maintain accurate 

records of payments made against the contracts and will keep BOR staff informed of discrepancies 

or concerns. 

Since 2010, this line item has accumulated approximately $100,000 in carryover funding as a 

result of reduced activity. Part of the proposal for the FY 2015-17 triennial budget is to use $50,000 

of these funds each in FY 15 and FY 16 to implement the Glen Canyon Dam Administrative 

History Pilot Project. This project would help accomplish the goals of the Public Outreach Ad Hoc 

Group by providing a better understanding of the history of the GCDAMP, its work, and 

participants. The pilot project will undertake the following:

• Begin developing oral histories and interviews with AMP historical figures

• Create an annotated bibliography for program related literature

• Create a website and library database for information archival and retrieval

• Create a chronological program overview including participants

• Develop a new participant’s handbook for the AMP.

Budget FY15 = $63,054 FY16 = $64,945 FY17 = $66,893

Admin. History (carryover)

FY15 = $50,000 FY16 = $50,000 FY17 = $0

Reclamation Project - Public Outreach—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 2,000 2,000 2,000 2,000 2,000 2,000 2,000

Operations/supplies 2,500 2,500 2,500 2,500 2,500 2,500 2,500

Reclamation salaries 38,284 40,596 41,914 43,272 43,373 44,774 46,217

Subtotal 42,784 45,096 46,414 47,772 47,873 49,274 50,771

DOI Overhead (35%) 13,400 14,209 14,670 15,145 15,181 15,671 16,176

Project total 56,184 59,305 61,084 62,917 63,054 64,945 66,893

Total outsourced (%) — — — — — — —

 

15
A.6. AMWG Other 

This budget represents some of the other “miscellaneous” expenses incurred in operation of the 

AMWG, including the following expenses:

• Overnight mailings of AMWG meeting packets

• Copying of reports

• Purchasing meeting materials (cassette tapes, markers, paper, software upgrades for 

GCDAMP Web site posting, etc.)

• Purchasing equipment (audio recording/transcribing machines).

In addition to the expenses noted above, training courses are often required for staff to keep 

current on environmental issues, FACA changes, computer technology improvements, etc. The 

primary goal is to limit spending on “other” items as much as possible. By doing so, more money 

can be applied to science and research. Other expenses will be kept to a minimum in an effort to 

reduce the administrative portion of the GCDAMP budget. 

Budget FY15 = $9,047 FY16 = $9,318 FY17 = $9,598

Reclamation Project - Other—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 6,062 6,509 6,783 7,028 7,047 7,318 7,598

Operations/supplies 2,000 2,000 2,000 2,000 2,000 2,000 2,000

Reclamation salaries — — — — — — —

Subtotal 8,062 8,509 8,783 9,028 9,047 9,318 9,598

DOI Overhead (35%) — — — —

Project total 8,062 8,509 8,783 9,028 9,047 9,318 9,598

Total outsourced (%) — — — — — — —

 

16
B.1. TWG Costs 

This budget represents BOR staff costs to perform the daily activities required to support the 

TWG, a subgroup of the AMWG. The work includes completing assignments resulting from TWG 

meetings, consulting with stakeholders on a variety of GCDAMP issues relating to the operation of 

GCD, disseminating pertinent information to TWG members, preparing and tracking budget 

expenses, and updating the Web pages BOR maintains for the program. BOR also completes all 

stakeholder travel activities, which range from preparing travel authorizations to completing travel 

vouchers. 

Personnel costs will not exceed what has been proposed in the budget unless Federal employee 

salaries are increased above the CPI. BOR staff will provide budget information to the TWG on a 

regular basis. Completed work products will be promptly distributed to TWG members/alternates 

and interested parties. 

Budget FY15 = $97,863 FY16 = $100,799 FY17 = $103,823

Reclamation Project - Personnel Costs—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries 64,593 68,181 70,227 70,380 72,491 74,666 76,906

Subtotal 64,593 68,181 70,227 70,380 72,491 74,666 76,906

DOI Overhead (35%) 22,608 23,864 24,579 24,633 25,372 26,133 26,917

Project total 87,201 92,045 94,806 95,013 97,863 100,799 103,823

Total outsourced (%) — — — — — — —

17
B.2. TWG Member Travel Reimbursement 

This budget provides funds to reimburse TWG members or alternates for expenses incurred to 

attend regularly scheduled TWG meetings. 

Reimbursing TWG members or alternates for travel expenses is done to encourage their 

attendance at all meetings. By providing reimbursement to TWG members or alternates for air 

travel or mileage for the use of private vehicles, as well as other related travel costs such as hotel, 

per diem, and rental car increases opportunities for members to participate in a variety of TWG 

assignments. Because BOR can purchase airline tickets at the Federal Government rate, there are 

additional cost savings to the program.

The GCDAMP will benefit from having all the TWG members participate in regularly 

scheduled meetings. As a collective body, TWG members address and resolve concerns associated 

with the operation of GCD and make recommendations to the AMWG for continued research. 

Budget FY15 = $23,051 FY16 = $23,743 FY17 = $24,455

Reclamation Project - TWG Member Travel Reimbursement—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 24,232 21,861 22,331 22,380 23,051 23,743 24,455

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 24,232 21,861 22,331 22,380 23,051 23,743 24,455

DOI Overhead (35%) — — — — — — —

Project total 24,232 21,861 22,331 22,380 23,051 23,743 24,455

Total outsourced (%) — — — — — — —

18
B.3. TWG Reclamation Travel 

This budget covers travel expenses that BOR staff will incur to prepare for and attend TWG 

meetings and ad hoc group meetings resulting from AMWG/TWG assignments. The primary goal 

is for BOR staff to be able to travel to meetings and participate in completing AMWG/TWG 

assignments. BOR staff will continue to be involved in meeting with AMWG/TWG members to 

complete work assignments and resolve issues that affect the operation of GCD. They will develop 

better working relationships with all involved and work toward consensus on a variety of 

GCDAMP issues.

Budget FY15 = $15,903 FY16 = $16,381 FY17 = $16,872

Reclamation Project - Reclamation Travel—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training 17,864 14,958 15,407 15,440 15,903 16,381 16,872

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 17,864 14,958 15,407 15,440 15,903 16,381 16,872

DOI Overhead (35%) — — — — — — —

Project total 17,864 14,958 15,407 15,440 15,903 16,381 16,872

Total outsourced (%) — — — — — — —

19
B.4. TWG Chair Reimbursement/Facilitation 

This budget supports a person who is under contract to BOR to serve as the chairperson for the 

TWG. This person may also assist AMWG/TWG ad hoc groups in completing assignments. In the 

event that the TWG chair salary is covered through funding outside the GCDAMP, these funds can 

be used by BOR for administrative purposes or to cover professional facilitation of TWG issues.

The chairperson’s primary responsibility is to conduct regularly scheduled TWG meetings. The 

chairperson also participates in ad hoc group assignments and works closely with BOR and 

GCMRC staff in setting meeting agendas. The chairperson follows up on TWG and ad hoc group 

assignments and ensures that information is shared with the members and alternates in a timely 

manner.

The chairperson creates an atmosphere in which the members and other participants at TWG 

meetings feel comfortable expressing their individual viewpoints. The chairperson will bring the 

TWG members to consensus on sensitive issues with the ultimate goal of making recommendations 

to the AMWG that incorporate the best scientific information available to the GCDAMP. The 

chairperson will follow up on action items and make assignments as necessary to accomplish TWG 

objectives.

Part or all, of this budget may also be used to support a facilitator who is under contract to BOR

to provide facilitations services for TWG meetings. This person may also assist TWG ad hoc 

groups in completing assignments. The facilitator will help keep the TWG meetings organized and 

help the members reach consensus on important issues. The facilitator will create an atmosphere in 

which the members and other participants at TWG meetings feel comfortable expressing their 

individual viewpoints.

In 2013, a solicitor review of the legal authority to expend federal monies to fund the TWG 

Chair was initiated. Pending the results of this review this budget item may be modified or 

eliminated.

Budget FY15 = $32,050 FY16 = $33,012 FY17 = $34,002

Reclamation Project - TWG Chair Reimbursement—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training 24,913 30,145 31,049 31,117 32,050 33,012 34,002

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 24,913 30,145 31,049 31,980 32,050 33,012 34,002

DOI Overhead (35%) — — — — — — —

Project total 24,913 30,145 31,049 31,980 32,050 33,012 34,002

Total outsourced (%) — — — — — — —

20
B.5. TWG Other 

This budget represents some of the other “miscellaneous” expenses incurred in support of the 

TWG, including the following expenses:

• Overnight mailings of TWG meeting packets

• Copying of reports

• Purchasing meeting materials (cassette tapes, markers, paper, etc.)

• Purchasing equipment (audio recording/transcribing machines)

The primary goal is to limit spending on “other” items as much as possible. By doing so, more 

money can be spent on science and research. Other expenses will be kept to a minimum in an effort 

to keep within the GCDAMP budget. 

Budget FY15 = $2,585 FY16 = $2,662 FY17 = $2,742

Reclamation Project - Other—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 2,303 2,431 2,504 2,509 2,585 2,662 2,742

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 2,303 2,431 2,504 2,509 2,585 2,662 2,742

DOI Overhead (35%) — — — — — — —

Project total 2,303 2,431 2,504 2,509 2,585 2,662 2,742

Total outsourced (%) — — — — — — —

21
C.1. Administrative Support for NPS Permitting 

This budget item provides funding to support the Grand Canyon National Park permitting of 

research and monitoring projects conducted under the GCDAMP. Grand Canyon National Park 

employs a permitting specialist and staff who review all proposals for projects to be completed in 

the park. The program provides these funds under the auspices of the GCDAMP to offset the park’s 

administrative burden in providing permitting services. The primary goal is to ensure that projects 

conducted under the GCDAMP are reviewed and permitted by the NPS. Projects conducted under 

the GCDAMP will receive permits from the NPS in a timely manner.

Budget FY15 = $137,319 FY16 = $140,046 FY17 = $144,166

Reclamation Project - Administrative Support for NPS Permitting—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 120,240 121,882 126,242 125,811 129,586 133,743 137,478

DOI Overhead (35%) — — — — — — —

Project total 120,240 121,882 126,242 147,318

* 137,319 140,046 144,166

Total outsourced (%) — — — — — — —

* 2014 includes $17,297 cost reimbursement from FY-12 & 13.

22
C.2. Contract Administration 

This budget covers the expenses for BOR staff to prepare and monitor contracts associated with 

the GCDAMP. Specifically, these contracts are for AMWG facilitation, TWG chairperson 

reimbursement, Science Advisors, Tribal participation, Tribal resource monitoring, and 

programmatic agreement (PA) work.

BOR contract specialists will accurately apply funds spent on individual contracts to ensure 

costs do not exceed contract limits. They will keep other BOR staff informed as to those charges so 

accurate reporting can be made to both AMWG and TWG members. 

Contract specialists will ensure that individual contractors are fulfilling the requirements of 

their contracts. They will maintain accurate records of payments made against the contracts and 

will keep BOR staff informed of discrepancies or concerns. Work will be completed on time and 

within the limits of the contract. 

Budget FY15 = $45,362 FY16 = $46,723 FY17 = $48,124

Reclamation Project - Contract Administration—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries 29,491 31,604 32,552 32,623 33,601 34,610 35,647

Subtotal 29,491 31,604 32,552 32,623 33,601 34,610 35,647

DOI Overhead (35%) 10,479 11,061 11,393 11,418 11,761 12,113 12,477

Project total 40,420 42,665 43,945 44,041 45,362 46,723 48,124

Total outsourced (%) — — — — — — —

23
C.3. Science Advisor Contract 

This budget provides funding to support Science Advisors for technical reviews and advisory 

services to the GCDAMP. The program provides these funds under the auspices of the GCDAMP 

to obtain objective independent review of documents and work plans, and provide decision support 

to participating agencies and stakeholders.

Budget FY15 = $75,000 FY16 = $77,250 FY17 = $79,568

Science Advisor Contract Oversight — Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 75,000 77,250 79,568

DOI Overhead (35%) — — — — — — —

Project total — — — — 75,000 77,250 79,568

Total outsourced (%) — — — — — — —

24
C.4. Experimental Fund 

This budget item reserves funds for conducting experiments under the GCDAMP. The funds 

will be available to conduct experiments when conditions are appropriate. If the funds are not 

needed in a given year, they will be transferred to the Native Fish Conservation Contingency Fund.

Budget FY15 = $536,815 FY16 = $552,920 FY17 = $569,507

Reclamation Project - Experimental Carryover Funds—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 505,838 521,013 515,000 521,180 536,815 552,920 569,507

DOI Overhead (35%) — — — — — — —

Project total 505,838 521,013 515,000 521,180 536,815 552,920 569,507

Total outsourced (%) — — — — — — —

25
C.5. Native Fish Conservation Contingency Fund 

This budget item establishes a native fish conservation contingency fund. The goal of this 

budget item is to ensure that funds are available for nonnative fish control in the event this 

conservation action is needed for endangered humpback chub. This is a fund consisting of 

GCDAMP carryover funds from prior years and serves to ensure that funds are available for the 

control of nonnative fish should the need arise. This fund will implement nonnative fish control 

actions as defined in the 2007 and 2011 Opinions, and the NNFC EA and FONSI. Should excess 

funds become available beyond those needed for non-native fish control, these funds could be 

expended on other research, monitoring, and management actions that help conserve native fish.

This fund will be incrementally increased with future carryover dollars when available.

In FY 2015 $364,052 will be used to fund several important fisheries research and 

monitoring projects that will benefit native fish species. Funding these projects will still allow for 

sufficient funds to conduct nonnative fish control should the need arise over the course of the 

FY15-17 period. These projects are identified and described in the GCMRC FY 15-17 Budget and 

Work Plan, and include the following:

• 6.2 Aggregation recruitment $83,750

• 6.3 Monitoring mainstem aggregations with PIT tag antennas (pilot) $18,444

• 6.6 Direct Mainstem Augmentation of Humpback Chub $9,790

• 7.3 July Little Colorado River juvenile humpback chub marking to estimate production and 

outmigration $112,172

• 7.6 Potential for gravel substrate limitation for humpback chub reproduction in the 

LCR $11,600

• 7.7 Evaluate CO2 as a limiting factor early life history stages of humpback chub in the 

Little Colorado River $86,420

• 7.9 Development of a non-lethal tool to assess the physiological condition of humpback 

chub in the Colorado and Little Colorado Rivers $41,876

Budget FY15 = $824,079 FY16 = $1,360,894 FY2017 = $1,917,414

Reclamation Project – Native Fish Conservation Contingency Fund—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor

— — — —

Logistics field support — — — —

Project-related travel/training — — — —

Operations/supplies — — — —

Reclamation salaries — — — —

Subtotal 49,049 50,521 782,660 667,947 824,079 1,360,894 1,917,414

DOI Overhead (35%) — — — — — — —

Project total 49,049 50,521 782,660 667,947 824,079 1,360,894 1,917,414

Total outsourced (%) — — — — — — —

26
D.1. Cultural Resources Program Administrative Costs 

This budget funds the salary and travel expenses of BOR staff to administer the National 

Historic Preservation Act (NHPA) compliance for the GCDAMP. This includes the 1994 PA for 

Glen Canyon Dam Operations, the 2012 Memoranda of Agreement (MOA) documents for Nonnative Fish Control and the HFE Protocol, and general needs of tribal consultation for the 

GCDAMP. This also includes BOR staff administration costs associated with maintaining the 

grants for tribal participation in the GCDAMP and tribal contracts to implement tribal monitoring 

protocols.

Project Goals and Objectives

• Management of five tribal grants from both appropriated funds for participation in the 

GCDAMP and power revenues to provide implementation of tribal monitoring protocols.

• Management of the monitoring and data recovery of at-risk historic properties and other 

related projects associated with implementation of NHPA compliance agreements for the 

operation of Glen Canyon Dam.

• Attending TWG and AMWG meetings, Cultural Ad Hoc Group meetings, and conducting 

meetings required by the 1994 PA and 2012 MOAs.

Compliance with the National Historic Preservation Act, Section 106 is the primary outcome of 

this project, which also ensures accountability for the tribal grants and contracts and appropriate

use of both appropriated dollars and power revenues. 

Budget FY15 = $135,249 FY16 = $139,307 FY17 = $143,486

Reclamation Project - Cultural Resources Program Administrative Costs—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related travel/training 3,000 3,000 9,000 9,000 9,000 9,000 9,000

Operations/supplies — — — — — — —

Reclamation salaries 42,409 45,353 88,029 90,600 93,518 96,524 99,619

Subtotal 45,409 47,575 94,696 97,267 102,518 105,524 108,619

DOI Overhead (35%) 14,843 15,873 30,810 31,710 32,731 33,783 34,867

Project total 60,252 64,226 127,839 131,310 135,249 139,307 143,486

Total outsourced (%) — — — — — — —

27
D.2. Cultural Resources Work Plan

1. Glen Canyon National Recreation Area Monitoring and Mitigation 

In FY15, Glen Canyon NRA proposes to conduct data collection and monitoring of cultural 

resources at sites potentially affected by operations of the Glen Canyon Dam. Results from these 

efforts will inform the timing and scope of remedial action treatments proposed in out years for 

sites in Glen Canyon NRA. The FY15 scope of work includes two components: 1) implement the 

long-term monitoring program; and 2) conduct consultation with the five tribes to develop a plan of 

action to obtain tribal values. By so doing, Glen Canyon NRA gathers the data needed to assess 

effects on the sites, landscape and Traditional Cultural Property of Glen Canyon Reach. This work 

will help inform and be integrated into the long-term monitoring program proposed under 

Component 1 below.

Component 1: Implement the Long-term Monitoring Program for Terrestrial and Submerged 

Cultural Resources

Long-term monitoring of cultural resources in the Glen Canyon Reach is required under the 

Grand Canyon Protection Act. These activities were formally conducted annually from 1992 to 

1998 and again in 2003. Stipulations in the MOA for the Glen Canyon Dam High Flow Experiment 

Protocol identify the need for monitoring programs to determine potential adverse effects to 

previously unidentified sites and to include assurances that programs efficiently and effectively 

gather the data needed to assess effects on locations of cultural and religious importance to Tribes.

Glen Canyon NRA recognizes the limitations of its section 110 activities to fulfill the BOR’s 106 

obligations for the operations of Glen Canyon Dam. We therefore provide the following proposal 

for long-term monitoring activities to assist the BOR in meeting their compliance obligations.

Implementation of the proposed long-term monitoring program will be conducted by NPS 

through Glen Canyon NRA and coordinated with other NPS entities, the BOR, Grand Canyon 

Monitoring and Research Center (GCMRC), Tribes, and other stakeholders. Additional NPS 

entities involved will include Grand Canyon National Park, Submerged Resources Center (SRC), 

and Midwest Archeological Center. General monitoring methodologies will include periodic visual 

inspection, condition assessment, and evaluation via on-site monitoring and repeat photography.

The format of monitoring data will be finalized following review and coordination with partners 

and stakeholders. Sites selected for monitoring will be chosen through a review of existing data on 

archeological sites that are potentially affected by Glen Canyon Dam operations and include a 

control group of sites for comparison. Timing for monitoring of all resources will coincide with a 

schedule appropriate for evaluating the potential effects of dam operations with an emphasis on 

effects resulting from the HFE Protocol. Summary reports will be completed and submitted 

annually.

In addition to terrestrial monitoring, the NPS SRC will continue monitor the submerged 

Spencer Steamboat (AZ: C: 02:011, Feature 12) for baseline data collection in April of 2014.

Monitoring will continue if the report completed by NPS SRC recommends continued monitoring 

or mitigation. 

In FY16 and FY17, Glen Canyon NRA proposes to continue data collection and monitoring of 

cultural resources at sites potentially affected by operations of the Glen Canyon Dam. Results from 

these efforts will inform the timing and scope of remedial action treatments proposed in out years 

for sites in Glen Canyon NRA.

28
Component 2: Address Tribal Values

Glen Canyon NRA will conduct consultation with the five tribes to determine the protocol by 

which tribal values will be gathered and used to inform monitoring and potentially mitigation of 

locations of cultural and religious importance. This information should contribute to long-term 

monitoring and/or mitigation through potential non-intrusive and/or intrusive excavation.

Budget FY15 = $61,000 FY16 = $145,000 FY17 = $104,000 

2. Zuni Associative Values

When historic properties are valued for their association with important historical events and 

important people, mitigation is accomplished by documenting those associations. This project 

mitigates for losses of these values through the production of a DVD. Zuni religious leaders will be 

interviewed and asked to express their views and feelings about the importance of Grand Canyon, 

the Colorado River, the Little Colorado River, Ribbon Falls, and Zuni ancestral archaeological sites 

in Zuni culture, heritage, and the continuing sense of Zuni community. The DVD will be recorded 

on location within the Grand Canyon. Zuni heritage themes discussed in the DVD will be the 

emergence, the creation of medicine bundles, the migrations, and the continuing relational spiritual 

connection between the Pueblo of Zuni and the Grand Canyon. The final DVD is intended for use 

in the Zuni school systems, available for the Zuni general public through the Zuni libraries, and for 

use in educating GCDAMP stakeholders about the Zuni relationship to Grand Canyon.

Budget FY15 = $100,000 FY16 = $30,000 FY17 = $0

3. Support for GCMRC’s Project 4 

This project will examine deposition of aeolian sand from HFE-created sand bars on historic 

properties within the area of potential effect of future dam operations. The primary objectives of 

element 4.2. are to 1) draft and 2) implement a monitoring plan that meets requirements for 

monitoring effects of dam operations to cultural resources relative to the National Historic 

Preservation Act and Grand Canyon Protection Act. The plan will be designed to identify whether, 

and how much, HFE sand is transported by wind to a representative sample of archaeological sites, 

and to measure the effect that wind transported sand has on site surface condition and site stability 

(i.e., the degree to which this mitigates effects from precipitation induced gully erosion and other 

surface impacts). Year 1 of the project will focus on drafting, reviewing, revising, and pursuing 

approval for the monitoring plan. Years 2 and 3 of the project will focus on implementing the 

monitoring plan. The draft plan will make a recommendation of the sample of archaeological sites 

that should be monitored, but stakeholders (presumably including the BOR, NPS, SHPO, ACHP 

and tribes) will need to work very closely with GCMRC in year 1 of the project to come to 

agreement on the monitoring protocol and set of sites that is ultimately monitored. The monitoring 

plan will be designed in the context of the archaeological site classification developed and applied 

in 2013 and 2014 which provides useful, site-specific expectations of landscape response to dam 

operations and controlled floods. While recent monitoring efforts have focused on the use of lidar 

to measure topographic changes, in drafting the monitoring plan, GCMRC will also consider the 

use of other monitoring methods and tools.

29
Budget FY15 = $150,000 FY16 = $150,000 FY17 = $186,450 

4. TEK Ecological Restoration Project 

Based on the proposed completion of a Determination of Eligibility for Grand Canyon as a 

Hualapai TCP, this project will be a mitigation measure for vegetation that can be contributing 

elements to the TCP, such as the Gooddings Willow at Granite Park. The project will comprise 

planning (choosing collection areas and restoration sites), especially during the first year, site 

preparation (e.g., tamarisk removal if necessary), and some limited planting of certain species in 

select locations as pilot plots. Other aspects of the project are envisioned as longer term efforts, in 

particular propagating and nurturing Gooddings willow, cottonwood, and possibly other tree 

species, as well as research and monitoring for associated changes in ecological conditions.

Budget FY15 = $99,000 FY16 = $100,000 FY17 = $100,000

5. Tribal Synthesis 

This project will increase the understanding of the Native American perspective within the 

GCDAMP by utilizing Traditional Ecological Knowledge (TEK). The project will evaluate the 

management of other river systems and the involvement of Native Americans, increase tribal 

participation in the GCDAMP planning and management process and integrate tribal perspectives 

into the AMP science program.

Budget FY15 = $50,000 FY16 = $50,000 FY17 = $50,000

6. Annual Integrated River Trip: An Exchange of Values and World-Views 

The objective of this project is to provide an opportunity for tribal representatives and DOI 

federal employees in the GCDAMP to articulate their respective concerns and issues in a field 

situation. Each river trips will be agenda-driven and may also include restoration projects.

Budget FY15 = $30,000 FY16 = $30,000 FY17 = $30,000

7. Nonnative Fish Removal Consultation 

This project provides funding to support ongoing tribal consultation-related expenses associated 

with implementation of the Nonnative Fish Control EA, FONSI, and NHPA MOA. Should 

mechanical removal of non-native fish be necessary, this funding would be used to support tribal 

consultation and tribal participation in nonnative fish control efforts.

Budget FY15 = $10,000 FY16 = $10,000 FY17 = $10,000

30
8. Tribal Preparation of Paperwork for DOE of Grand Canyon to National Register 

This project provides funding to support and assist tribes to prepare the paperwork to prepare 

determinations of eligibility (DOE) of the Grand Canyon and contributing elements to the National 

Register of Historic Places as a Traditional Cultural Property. This would be done under criteria a 

and b.

Budget FY15 = $0 FY16 = $0 FY17 = $50,000

Summary budget table for cultural resources work plan. 

FY GLCA 

Treat/ 

Monitor

Zuni 

Assoc. 

Values

GCMRC 

Proj. 4

Tribal 

TEK 

Veg.

Tribal 

Synth.

Tribal 

River 

Trip

NN 

Removal 

Consult.

Tribal 

NRHP 

Nom.

Total

15 $61,000 $100,000 $150,000 $99,000 $50,000 $30,000 $10,000 $0 $500,000

16 $145,000 $30,000 $150,000 $100,000 $50,000 $30,000 $10,000 $0 $515,000

17 $104,000 $0 $236,450 $100,000 $50,000 $30,000 $10,000 $50,000 $530,450

 

31
D.3. Integrated Tribal Resources Monitoring 

This budget item provides funds to identify traditional cultural properties (TCPs) and 

implement Native American monitoring protocols that were developed in FY 2007 and 

recommended by the TWG as part of efforts to develop a core-monitoring program. 

In addition, the five GCDAMP Tribes (Hopi Tribe, Hualapai Tribe, Kaibab-Paiute Tribe, 

Pueblo of Zuni, and Navajo Nation) will work with BOR and the NPS to implement monitoring of 

historic properties in Glen and Grand Canyons. This will be accomplished by adding an additional 

3 days to the annual GCDAMP monitoring trips.

The primary goal of this activity is to evaluate the effects of dam operations and other actions 

under the authority of the Secretary of the Interior on resources of value to Native American Tribes.

A secondary goal is to conduct condition monitoring of historic properties to assist BOR in 

compliance with Section 106 of the National Historic Preservation Act.

Annual reports will be prepared detailing activities, findings, and monitoring data that result 

from implementing core-monitoring protocols for historic properties. Condition monitoring data 

will be provided to BOR to assist in prioritization of historic properties for treatment in subsequent 

years. In addition, monitoring data will be used to update NPS databases.

Budget FY15 = $162,227 FY16 = $167,094 FY17 = $172,107

Reclamation Project - Integrated Tribal Resources Monitoring—Funding History

Activity 2011 2012 2013 2014 2015 2016 2017

Outside Reclamation 

science/labor — — — — — — —

Logistics field support — — — — — — —

Project-related 

travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal (power 

revenues) 144,553 148,889 157,160 161,875 162,227 167,094 172,107

DOI Overhead (35%) — — — — — — —

Appropriated Funds 75,000 — — — — — —

Project total 219,553 148,889 157,160 161,875 162,227 167,094 172,107

Total outsourced (%) — — — — — — —

 

32
D.4. Tribal Participation in the GCDAMP 

This budget item provides funding through agency appropriations (not power revenues) for the 

participation in GCDAMP meetings, resource monitoring, and government-to-government 

consultation of the five GCDAMP Tribes (Hopi Tribe, Hualapai Tribe, Kaibab Paiute Tribe, Pueblo 

of Zuni, Navajo Nation) and five DOI agencies (U.S. Geological Survey, National Park Service, 

BOR, U.S. Fish and Wildlife Service, and Bureau of Indian Affairs), with BOR serving as lead 

agency. The purpose of the funding is to ensure tribal viewpoints are integrated into continuing 

GCDAMP dialogs, votes, and in the final recommendations made to the Secretary of the Interior.

The five DOI agencies provide appropriated funding to support this budget item.

Budget FY15 = $475,000 FY16 = $475,000 FY17 = $475,000

Reclamation Project E. Tribal Participation in the GCDAMP: Funding History

Activity 2008 2009 2010 2011 2012 2013 2014

Outside Reclamation 

science/labor

— — — — — — —

Logistics field support — — — — — — —

Project-related travel/training — — — — — — —

Operations/supplies — — — — — — —

Reclamation salaries — — — — — — —

Subtotal 475,000 475,000 475,000 475,000 475,000 475,000 475,000

DOI Overhead (35%)

Project total 475,000 475,000 475,000 475,000 475,000 475,000 475,000

Total outsourced (%) 100% 100% 100% 100% 100% 100% 100%

33
Glen Canyon Dam Adaptive Management Program

FY 2015-17 Preliminary Draft Budget for the Bureau of Reclamation Updated: 5/23/14

Description FY15 with

3.0% CPI

FY16 with

3.0% CPI

FY17 with

3.0% CPI

AMWG

Personnel Costs - Labor & Burden 196,530 202,425 208,498

AMWG Member Travel Reimbursement 15,689 16,159 16,644

AMWG Reclamation Travel Reimbursement 16,097 16,580 17,077

Facilitation Contract 79,556 81,943 84,401

POAHG Expenses - Labor, Burden, & Travel 63,054 64,945 66,893

Other 9,047 9,318 9,598

Subtotal 379,972 391,371 403,112

TWG

Personnel Costs - Labor 97,863 100,799 103,823

TWG Member Travel Reimbursement 23,051 23,743 24,455

Reclamation Travel 15,903 16,381 16,872

TWG Chair / Facilitation 32,050 33,012 34,002

Other 2,585 2,662 2,742

Subtotal 171,453 176,596 181,894

OTHER

Admin Support NPS Permitting 137,319 140,046 144,166

Contract Administration - Labor, Burden, Travel 45,362 46,723 48,124

Science Advisor Contract 75,000 77,250 79,568

Experimental Carryover Funds 536,815 552,920 569,507

Native Fish Conservation Contingency Fund 824.079 1,360,894 1,917,414

Subtotal 1,983,623 2,542,881 3,123,827

CULTURAL PROGRAM

Reclamation Administration and Travel 135,249 139,307 143,486

Cultural Resources Program Implementation 500,000 515,000 530,450

Integrated Tribal Resource Monitoring 162,227 167,094 172,107

Subtotal 797,476 821,401 846,043

34
Reclamation Power Revenue Costs Total 3,017477 3,617,201 4,189,828

Reclamation Power Revenue Costs w/o 

Carryover 2,143,398 2,206,307 2,272,414

Glen Canyon Dam Adaptive Management Program

FY 2015-17 Preliminary Draft Budget for the Bureau of Reclamation Updated: 5/23/12

Description FY15 FY16 FY 17

OTHER APPROPRIATED FUNDS

TRIBAL CONTRACTS (Appropriated Funds)

Hopi Tribe 95,000 95,000 95,000 95,000

Hualapai Tribe 95,000 95,000 95,000 95,000

Navajo Nation 95,000 95,000 95,000 95,000

Pueblo of Zuni 95,000 95,000 95,000 95,000

Kaibab Band of Paiute Indians 95,000 95,000 95,000 95,000

DOI Agency Appropriated Funds Total $475,000 $475,000 $475,000 $475,000

Total $475,000 $3,492,477 4,092,201 $4,664,828

Total w/o Carryover $2,618,398 $2,681,307 $2,747,414

35
Chapter 2. U.S. Geological Survey, Southwest Biological Science Center, 

Grand Canyon Monitoring and Research Center Triennial Budget and Work 

Plan—Fiscal Years 2015–2017 

Introduction 

The Glen Canyon Dam Adaptive Management Program (GCDAMP) is an advisory process 

wherein protection and management of Colorado River resources downstream from Glen 

Canyon Dam are considered in planning dam operations. The Grand Canyon Protection Act of 

1992 directs the Secretary of the Interior to establish and implement long-term monitoring 

programs to ensure that Glen Canyon Dam is operated “... in such a manner as to protect, 

mitigate adverse impacts to, and improve the values for which Grand Canyon National Park and 

Glen Canyon National Recreation Area were established....” The Final Environmental Impact 

Statement (EIS) for Operation of Glen Canyon Dam (U.S. Department of the Interior, 1995) 

recommended creation of a federal advisory committee to advise the Secretary on 

implementation of an adaptive management program for operations of the dam. The Record of 

Decision for the EIS that was signed in October 1996 created this federal advisory committee, 

and the charter of the Adaptive Management Work Group (AMWG) that implements the 

GCDAMP was signed in January 1997.

The GCDAMP budget is administered by the Bureau of Reclamation (Reclamation). One part 

of the GCDAMP budget supports Reclamation’s project administration and staff travel, provides 

reimbursements to AMWG members and members of other GCDAMP committees and 

subcommittees, provides meeting facilitation and public outreach, and supports compliance 

activities. Reclamation funding, with supplemental support from 4 other agencies of the 

Department of the Interior, supports Native American tribal participation in many aspects of the 

program. These aspects of the program are described in Chapter 1. 

Approximately 80 percent of the GCDAMP annual budget supports the monitoring and 

research work of the USGS Grand Canyon Monitoring and Research Center (GCMRC). The 

GCMRC is formally organized as a research station within the USGS Southwest Biological 

Science Center. The GCMRC is the primary science provider for the GCDAMP and undertakes 

monitoring and research activities about the status and trends of natural, cultural, and 

recreational resources of the Colorado River between Glen Canyon Dam and Lake Mead 

reservoir; this segment of the Colorado River is administratively termed the Colorado River 

ecosystem (CRe). GCMRC also conducts a program of monitoring water quality of Lake Powell 

reservoir, and the GCMRC undertakes other monitoring and research activities elsewhere in the 

Rio Grande and Colorado River watersheds funded from other sources.

Purpose 

This Triennial Work Plan (TWP) describes the monitoring and research activities that 

will be undertaken by GCMRC and its cooperators in fiscal years 2015, 2016, and 2017 (FY15–

17). These fiscal years occur between October 1, 2014, and September 30, 2017.

36
Overview of the FY15–17 GCMRC Monitoring and Research Program 

Each project described in this Work Plan is organized around large monitoring and research 

themes. The monitoring and research themes identified in the FY15–17 TWP are those common 

to: 

1. the 5 priority questions and the 12 program goals developed by the AMWG in 2004; 

2. the monitoring and research plan prepared by GCMRC, approved by AMWG in August 

2007 and amended and approved in April 2009 (U.S. Geological Survey, 2007a); 

3. the strategic science plan prepared by GCMRC in March 2007 and amended in April 

2009 (U. S. Geological Survey, 2007b);

4. the draft Core Monitoring Plan (U. S. Geological Survey, 2011); 

5. Assistant Secretary Castle’s March 31, 2011, memo establishing priorities in GCMRC 

science planning; 

6. the General Science Plan appended to the Environmental Assessment for the 

Development and Implementation of a Protocol for High-flow Experimental Releases 

from Glen Canyon Dam (Bureau of Reclamation, 2011a, appendix B);

7. the Research and Monitoring Plan for the Environmental Assessment for Non-Native 

Fish Control Downstream from Glen Canyon Dam (Bureau of Reclamation, 2011b, 

appendix B);

8. the 2011 report of the Desired Future Conditions Ad Hoc Group of the AMWG; and,

9. Assistant Secretary Castle’s May 7, 2014, memo establishing the triennial budget process 

and clarifying priorities in GCMRC science planning.

The monitoring and research themes described in the various GCDAMP documents and 

agreements written during the past decade concern (1) maintenance of the pre-dam physical 

template, especially regarding fine sediment; (2) recovery of the endangered humpback chub 

(Gila cypha) and maintenance of populations of other native fish; (3) maintenance of the food 

base on which the native fish community depends; (4) maintenance of the native riparian 

vegetation community; and, (5) maintenance of culturally important sites, including those that 

are of archaeological and historical significance. The various goals, questions, information 

needs, and desired future conditions developed by the various GCDAMP committees also 

recognize the importance of the nonnative rainbow trout (Oncorhynchus mykiss) fish population 

in Glen Canyon and the role played by nonnative riparian vegetation in providing habitat for 

some desired fauna. In addition to these resource considerations, delivery of water in accordance 

with the Law of the River and generation of renewable hydroelectricity are essential to the 

economic well-being of the Southwest. Thus, economic analysis of the various recommendations 

of the GCDAMP is another critical part of the GCDAMP.

The most recent guidance regarding Work Plan development was provided by Assistant 

Secretary Castle in May 2014. In that guidance, the Assistant Secretary reiterated that three main 

science priorities are: “science relevant to compliance with the Endangered Species Act, 

particularly relative to native fish and humpback chub; science informing our compliance with 

the Grand Canyon Protection Act, especially the sediment resource, and science on non-native 

fish control and the recreational trout fishery ... the need for this science continues.” 

Additionally, the Assistant Secretary recognized that other priority issues included 

“understanding ... how cultural and archaeological sites are linked to modern river processes and 

the role of Traditional Ecological Knowledge (TEK) in contributing to scientific understanding 

37
and river operations.” Thus, the Assistant Secretary stated that, “I think these four issues (the 

three described in my 2011 memo and the evolving issue related to cultural/archaeological 

resources as linked to modern river processes) are the primary areas where GCMRC should 

concentrate its scientific resources.”

The Assistant Secretary did not, however, preclude GCMRC from investigating other 

scientific topics in its monitoring and research work. She established, however, that such other 

investigations should focus on subjects, and resources, for which there is “widespread support 

and furthers the purposes of the Adaptive Management Program.” The Assistant Secretary also 

directed GCMRC to continue “long-term monitoring of core ecosystem components.” All 

activities must be conducted “within the relevant budget constraints.”

Overview of the FY 15–17 Projects 

In response to the monitoring and research themes described above, the FY15–17 work plan 

is organized into 15 major projects. Four of these projects are in the fields of reservoir water 

quality monitoring (Project 1), sediment-transport/water-quality/stream-flow measurement 

(Project 2), geomorphology of the active channel (Project 3), and geomorphology of the 

Colorado River valley above the active channel (Project 4). Six projects are in the fields of 

aquatic and fish ecology. These projects focus on the ecology of the food base (Project 5), 

monitoring and research related to main-stem native and nonnative fish populations (Project 6), 

humpback chub populations in the Little Colorado River (Project 7), management actions 

designed to benefit native fish (Project 8), rainbow trout in Glen and Marble Canyons (Project 

9), and physical habitat in Glen and Marble Canyons (Project 10). Projects 5 and 10 are new foci. 

Although food base studies were part of the GCMRC program in FY13–14, emerging results 

concerning the lack of species diversity, food-limited nature of the fishery, strong stakeholder 

interest, and strong interest among some sister agencies has inspired GCMRC to significantly 

expand its proposed body of work. Project 10 was developed in response to strong stakeholder 

interest in understanding the relationship between reservoir releases into Glen Canyon and 

associated changes in substrate and other attributes of physical habitat that provide advantage, 

and disadvantage, to rainbow trout populations in Glen and Marble Canyons. Two projects focus 

on vegetation. Project 11 is a broad monitoring and research project focused on riparian and 

upland vegetation as well as linkages between the aquatic ecosystem and terrestrial fauna and 

Project 12 is designed to specifically examine changes in the distribution of some riparian and 

upland plants that are of specific interest to tribes. Socioeconomic studies are proposed in Project 

13 – a new effort on the part of GCMRC. Geographic Information Systems, services, and support 

are described in Project 14 and administrative and support projects are described in Project 15.

Reservoir water quality, sediment-transport/water-quality/stream-flow measurement, 

geomorphology of the active channel, and geomorphology of the Colorado River valley 

above the active channel

Project 1 (called Project C in the FY13–14 BWP) is funded directly by Reclamation’s Water 

Quality Program and received no funds from the GCDAMP in FY13–14. In FY15, GCMRC 

proposes to fund a Science Review Panel to evaluate past studies of reservoir physical limnology 

and ecology that have focused on Lakes Powell or Mead. This Panel will be asked to make 

recommendations to the GCDAMP, Reclamation, and to other relevant agencies on how 

reservoir limnology and ecology ought to be monitored in the future and to make 

38
recommendations about how existing and new modeling tools could be used to predict future 

conditions in Lake Powell. Water quality, including temperature, is a strong determinant of 

ecological processes in the CRe. Because GCMRC and Reclamation continue to discuss changes 

in the approach and data analysis needs of Project 1, and because that project is funded on a 

calendar year cycle independent from the federal fiscal year cycle of the GCDAMP, only a 

preliminary description of Project 1 is included in the Appendix of this Draft Work Plan.

Project 2 (called Project B in the FY13–14 Work Plan) describes the monitoring program that 

measures the rate and quantity of the Colorado River’s stream flow, as well as the water inflow 

that occurs from tributaries. Additionally, Project 2 describes the measurement program of the 

fine sediment that enters the Colorado River from tributaries and measurement of the quality of 

the Colorado River’s water. This project began as fundamental research in the late 1990s and 

was recognized as a GCDAMP-approved core-monitoring project in 2007, designed to fully 

address the monitoring needs of GCDAMP Goal 7 and to partially address the monitoring needs 

of Goal 8. This project has changed little since that time; two gages have been established on 

Kanab Creek and Havasu Creek that are partly funded by other USGS programs. Otherwise, 

Project 1 is fundamentally a previously approved core-monitoring program with a relatively 

small amount of associated data analysis and interpretation. In FY 15–16 and as explained in the 

project proposal, the focus of this interpretative data analysis will be on the history of changing 

sediment delivery from the Paria and Little Colorado Rivers, because these two tributaries are 

the primary sources of fine sediment to the CRe.

Project 3 (called Project A in the FY13–14 Work Plan) concerns the geomorphology of fine 

sediment deposits in the active channel of the Colorado River. Fine sediment is sand (0.0625 – 2 

mm) and mud; in turn, mud is silt (0.0039-0.0625 mm) and clay (<0.0039 mm). These deposits 

are the substrate of the campsite resource, substrate in which the riparian ecosystem has 

developed, the architecture of native fish habitat including backwater nursery habitat for 

humpback chub, and is the substrate in and on which archaeological sites occur. The existence of 

Glen Canyon Dam and Lake Powell causes the deposition of all of the fine sediment supplied 

from the Upper Colorado River basin in the reservoir. Releases of reservoir water at the dam are 

free of sediment, and there is no significant fine sediment supply to Glen Canyon. The Paria 

River enters the Colorado River at Lees Ferry and delivers approximately 3.3 x 106 tons/yr of 

fine sediment (Topping and others, 2000), although the amount supplied from year to year varies 

greatly. The post-dam fine sediment supply to the upstream end of Marble Canyon has been 

decreased by 95%, in relation to the pre-dam fine sediment supply rate of 62.8 x 106 tons/yr that 

was supplied from the Upper Colorado River basin (Topping and others, 2000). Thus, the postdam Colorado River has excess mechanical energy available to transport fine sediment, and large 

amounts of fine sediment on the river bed and in eddies has been eroded and transported 

downstream towards Lake Mead.

The remaining fine sediment deposits that are of greatest interest to river managers are 

primarily composed of sand and occur in eddies. Eddies typically occur downstream from the 

rapids that make Marble and Grand Canyons a famous recreational whitewater river. Since the 

1970s, river scientists have struggled to understand the dynamics of the post-dam Colorado River 

and its adjustment to a greatly reduced fine sediment supply (Laursen and others, 1976, Howard 

and Dolan, 1981, Schmidt and Grams, 2011). It is inevitable that post-dam fine sediment 

deposits will be smaller and more sparsely distributed than pre-dam deposits, and significant 

river management questions concerning the Colorado River downstream from Glen Canyon Dam 

are:

39
What is the largest, sustainable amount of fine sediment that can occur along 

the banks of the Colorado River, especially as eddy sandbars? What flow 

regime, in relation to the natural supply of fine sediment from the Paria and 

Little Colorado Rivers, results in the most widespread distribution of fine 

sediment along the channel banks and in eddies?

Projects 2 and 3 are essential components to implementation of the Protocol for High-flow 

Experimental Releases, because the protocol calls for high flow releases from Glen Canyon Dam 

whenever a specified minimum amount of fine sediment delivered from the Paria River is 

exceeded. Project 2 and 3 are also responsive to the Assistant Secretary’s directions provided in 

her 2011 and 2014 memos. Project 2 is the measurement program needed to implement the High 

Flow Experiment Protocol. Project 3 supports the direct measurements of the volume of fine 

sediment, especially sand, that is stored on the bed of the Colorado River, in its eddies, or at 

higher elevation along the river’s banks; these measurements allow assessment of the 

effectiveness of the Protocol. A significant accomplishment of these programs in FY13–14 was 

the development of web-based interfaces to serve sediment transport and water quality data, 

calculate fine sediment mass balances, and to serve photographs of approximately 50 sandbars. 

The latter data allow stakeholders to evaluate the effects of controlled floods implemented under 

the High Flow Experiment Protocol.

Project 4 (called Project J in the FY13–14 Work Plan) is focused on monitoring and 

research concerning geomorphic and weather processes that affect cultural resources above the 

active channel of the Colorado River. This project is explicitly responsive to Assistant Secretary 

Castle’s guidance in her May 2014 memo and seeks to address longstanding issues associated 

with monitoring of landscape change near archaeological sites and other culturally significant 

properties. This project has been developed in close collaboration with Reclamation in hopes that 

the proposed monitoring and research is responsive to agency needs. The project has also been 

reviewed by tribal representatives. Reclamation is providing supplemental budget support to this 

project. 

Projects in Aquatic and Fish Ecology 

Projects 5, 6, 7, 8, 9, and 10 concern the fishes of the Colorado River and its tributaries, the 

food base on which those fish depend, and the habitats in which the food base and fishes occur. 

Project 5 is a new stand-alone effort designed to continue monitoring of the aquatic food base 

and to conduct research to resolve questions about the current condition of the aquatic 

invertebrate community in Glen Canyon. Many of the research and monitoring projects on native 

and nonnative fish in the mainstem Colorado River are included in Project 6. Project 7 is a 

research project intended to resolve critical uncertainties about humpback chub and their life 

history in the Little Colorado River and near its confluence with the mainstem Colorado River. 

Management actions focused on benefitting native and funded by the GCDAMP are included in 

Project 8 as is a proposed review of the fisheries program by an external protocol evaluation 

panel (PEP). Project 9 concerns the rainbow trout fishery of Glen Canyon as well as the factors 

influencing the distribution and movement of rainbow trout in Marble Canyon. Project 10 

focuses on improving understanding of the relationships between physical habitat in Glen 

Canyon and Marble Canyon and rainbow trout recruitment and distribution.

The goals in developing the aquatic ecology and fisheries portions of the FY15–17 TWP 

were to maintain long-term monitoring data sets of key aquatic resources in the CRe while also 

40
looking to minimize redundancy and increase efficiency and to continue addressing persistent 

scientific uncertainties that have plagued management of the aquatic ecosystem. Because 

nonnative rainbow and brown trout (Salmo trutta) compete and prey on native fish, including 

humpback chub, significant management questions focus on

What management strategies should to be employed to maintain a high quality rainbow trout 

fishery in Glen Canyon while protecting, and potentially recovering, the endangered 

humpback fish community in Marble and Grand Canyons?

New or expanded research projects are intended to provide information in areas where the 

greatest uncertainty remains. Most of the monitoring needs in the FY15–17 TWP were identified 

in the Environmental Assessment for Non-Native Fish Control Downstream from Glen Canyon 

Dam and its associated Biological Opinion. These documents also identified areas of uncertainty 

where more research was needed. These uncertainties, as well as others identified during 

interactions with stakeholders, informal meetings among scientists from cooperating agencies, 

and meetings organized as part of the development of the Glen Canyon Dam Long-Term 

Experimental and Management Plan (LTEMP) Environmental Impact Statement formed the 

foundation of the projects for new and expanded research presented in the TWP. Consideration 

was also given to past recommendations and guidance that were part of the development of

Strategic Science Questions, Research Information Needs, Core Monitoring Information Needs, 

and Desired Future Conditions. 

Monitoring of the aquatic food base and research of the biology and ecology of the aquatic 

invertebrates that comprise this important resource will continue or be expanded. Information to 

be collected in Glen, Marble, and Grand Canyons as part of Project 5 includes production of 

algae and invertebrates, organic matter biomass, drift of invertebrates and organic matter, and the 

abundance, distribution, and timing of emergence of flying insects. New research to understand 

the lack of aquatic invertebrate diversity in Glen Canyon will also be conducted including 

laboratory experimentation and field observation of how insect reproduction, egg survival, and 

emergence is influenced by various temperature and flow conditions. Supplemental funding 

external to the GCDAMP is also being sought to support a comparative study of the aquatic food 

base in other tailwaters. Understanding the aquatic food base and how dam operations and other 

factors influence its dynamics are essential to understanding the distribution, condition, and 

abundance of fish populations in the CRe.

The emphasis of research proposed in the remaining projects is on native fish, especially 

humpback chub, and nonnative fish that potentially threated the recovery of this endangered 

species. Although much has been learned about the distribution, habitat use, life history, 

population dynamics, and other aspects of the biology and ecology of this species, key 

uncertainties remain. Two areas of uncertainty believed to be among the most critical include the 

dynamics and ecology of the groups of humpback chub known as aggregations that live in 

discrete areas of the mainstem Colorado River (Project 6) and the variability in survival, growth, 

and emigration rates of early life history stages of humpback chub in the Little Colorado River. 

Additionally, little is known about the physical and biological drivers of this variation (Project 

7). Interactions between native and nonnative fish, particularly between humpback chub and 

trout, are still an area of concern given several remaining uncertainties. Continued laboratory 

experimentation and field study is needed to better understand the predation and competition 

41
effects of nonnative fish on native species and to determine to what extent these interactions are 

affected by environmental conditions (Project 7). 

Several management actions designed to increase survival of juvenile native fishes in the 

CRe will continue or begin during FY15–17. Mechanical removal of rainbow trout and brown 

trout in near the confluence of Bright Angel Creek will continue in cooperation with the National 

Park Service. Translocations of juvenile humpback chub from the Little Colorado River into 

uninhabited areas within this river will continue as will support of National Park Service 

translocation efforts into Havasu Creek and Shinumo Creek. New activities include an 

assessment of potentially harmful aquatic species within the Little Colorado River and genetic 

monitoring of humpback chub to confirm that ongoing management activities are not having 

negative effects. Finally, a review of the GCDAMP fisheries program will be conducted by an 

external review panel or PEP comprised of scientists with expertise relevant to ongoing research 

and monitoring activities. 

Maintaining the rainbow trout fishery in Glen Canyon has been a longstanding management 

priority. While our understanding of some of the drivers of this population has improved, a 

number of unknowns remain including a full understanding of the effects of flow related actions 

like HFEs and equalization. A combination of laboratory and field studies, modeling, and 

comparison to similar systems will help clarify the drivers of rainbow trout population status and 

trends, size composition, and downstream migration (Project 9), thus allowing for more effective 

management of this important fishery. 

Monitoring of key aquatic resources in the CRe remains a critical component of the FY15–17 

TWP. In fact, the majority of work proposed for this biennium is monitoring to be conducted by 

GCMRC and its cooperators. These projects generate data that can be used to provide a baseline 

for observing status and trends in resources of interest, to assess the effectiveness of various 

management actions, and to inform managers as to the need to conduct management actions or 

the attainment of identified goals. Surveys of humpback chub and other fishes are proposed to 

continue in the Little Colorado River (Project 7). This will include both physical captures of fish 

in the spring and fall and continuous electronic monitoring to detect individuals previously 

tagged with passive integrated transponders. Mainstem surveys of native and nonnative fish will 

also continue annually in the spring and fall as part of Project 6 and quarterly near the mouth of 

the Little Colorado River (Projects 7 and 9) to gather information on young humpback chub and 

trout. These surveys provide critical information on triggers for potential management actions to 

control nonnative fish abundance identified in the Biological Opinion for the HFE and nonnative 

fish control EAs. Needed information includes survival rates of young humpback chub, the 

relative abundance of sub-adult and adult humpback chub, and trout abundance near the LCR 

confluence. Additional monitoring activities include surveys of trout spawning, early life stages, 

and adult populations in Glen Canyon, trout abundance and emigration in Marble Canyon, and 

the distributions and relative abundance of all native and nonnative fishes in Glen, Marble, and 

Grand Canyons. These efforts will help keep scientists and managers informed on the status and 

trends of fish throughout the CRe and will provide a mechanism of surveillance and early 

detection of invasive fish species.

Projects in Riparian Ecology 

Project 11 (called Project I in the FY13–14 Work Plan) builds on the plant-response guild 

research and monitoring conducted in the FY 13–14 Work Plan to further stakeholder 

understanding of the role of riparian vegetation in ecosystem processes in a regulated river 

42
ecosystem. The project includes a continuation of the ground-based and landscape scale 

monitoring approaches initiated in FY13. The ground-based sampling downstream of Glen 

Canyon Dam is complimentary to riparian monitoring data that are collected within in other 

National Park Service units in the Upper Colorado River Basin by their Inventory and 

Monitoring Program. The landscape scale monitoring is moving from the total vegetation change 

analysis conducted in FY13–14 to the specific change analysis of vegetation classes and 

comparison of changes among river segments and different depositional environments (sandbars, 

debris fans, channel margins). Information gained in Project 11 monitoring supports efforts in 

Project 3 that endeavor to understand sediment dynamics over time and particularly with regard 

to sediment response and the Experimental High Flow Protocol. 

With the increasing recognition of the role that both vegetation and river regulation have on 

fluvial geomorphology, studies evaluating the additive effects of these change agents on 

shoreline and channel geomorphic landforms are increasingly relevant. Research elements in

Project 11 proposed to utilize the plant-response guilds to probabilistically evaluate and assess 

wildlife habitat, and integrate the response guilds with a 22-year topographic survey record for 

retrospective analyses of topographic change of 20 sandbars. A retrospective analysis of sandbar 

evolution contributes to an understanding of how landforms along the channel change in 

response to annual hydrology, controlled floods, and the presence of vegetation. In this regard, 

Project 11 is linked to the research priority for sediment identified by the Assistant Secretary 

Anne Castle on March 31, 2011. Increasing our knowledge about plant responses to changing 

hydrology can also support resource managers concerns about management of nonnative plants 

that may or may not benefit from changes in future flow regimes or how flow regimes might be 

integrated into decisions regarding plant removal and restoration. Project Element 11.5 is 

intended to begin to address these questions.

Collectively, the monitoring and research proposed in Project 11 supports the GCDAMP’s 

efforts to evaluate the High-Flow Experiment Protocol (Bureau of Reclamation, 2011a) and flow 

alternatives that will result from the on-going EIS for a Long-term Experimental Management 

Plan (LTEMP) for Glen Canyon Dam. The proposed research elements fundamentally aid in 

furthering our understanding of the role of riparian vegetation in ecosystem processes of a 

regulated river.

Cultural Resources Monitoring and Research Project 

The cultural resources program continues to be a significant focus of GCMRC activity in 

FY15–17. Project 4 explicitly focuses on providing scientific support for agency management 

responsibilities, especially regarding development of a new Programmatic Agreement and in 

relation to responsibilities associated with the High Flow Experiment Protocol. Reclamation is 

independently providing $150,000 to support this work. As of June 6, funds have not been 

identified to purchase a terrestrial laser scanner, as recommended by the investigators of this 

project; GCMRC is evaluating other options to purchase this equipment. This project involves a 

research component that follows on work completed by Amy Draut East and Joel Sankey in 

FY13–14. The other part of this project involves development of a formal archaeological site 

monitoring program that would be implemented in FY16. Project 12 is a small and novel project 

to evaluate historical changes in the distribution of plants significant to tribes, and some tribes 

are formally cooperating in this effort.

43
Socioeconomic Project 

Project 13 initiates socioeconomic monitoring and research at GCMRC. This project will 

identify recreation and tribal preferences for, and values of, downstream resources and evaluate 

how they are influenced by operations at Glen Canyon Dam. In addition, the project will 

integrate economic information with data from long-term and ongoing physical and biological 

monitoring and research studies led by GCMRC to develop a decision support system that will 

improve the ability of the GCDAMP to evaluate and prioritize management actions, monitoring 

and research. Specifically, the project involves three related socioeconomic monitoring and 

research studies that include: (a) evaluation of the impact of Glen Canyon Dam operations on 

regional economic expenditures and economic values associated with angling in Glen Canyon 

National Recreation Area downstream from Glen Canyon Dam, and whitewater floating in 

Grand Canyon National Park that begins at Lees Ferry; (b) assessment of the impact of Glen 

Canyon Dam operations on tribal preference for, and value of, downstream resources; and (c) 

development of decision methods, using economic metrics, to evaluate management actions and 

prioritize monitoring and research on resources downstream of Glen Canyon Dam. The 

recreation economics research builds on work in the late 1980s, under the Glen Canyon 

Environmental Studies program, which established a relationship between dam operations and 

recreational economic values related to angling and whitewater floating. Carryover funding from 

FY13 has been allocated to initiate the recreation economics research in FY14. The recreation 

economics research will continue in FY15–16. The decision methods and tribal research, original 

research at GCMRC, will be initiated in FY15 and FY16, respectively, and continue into FY17.

Geographic Information Systems (GIS), Services, and Support 

 

Project 14 concerns the implementation of GIS support both in terms of direct involvement in 

proposed science work (Projects 3, 4, 5, 6, 7, 9 and 10), and as a stand-alone effort that performs 

many functions within GCMRC and GCDAMP. These functions include the ability to serve as 

the focal point of geospatial knowledge and application, fulfill the role of geospatial data 

management, further develop GIS as a vehicle for data integration, and provide a gateway into 

GCMRC’s collection of geospatial data holdings.

Independent Review and Science Oversight 

In FY15, GCMRC proposes to convene three science oversight and review panels. One of 

these panels will focus on reservoir limnology and ecology, because the characteristics of Lake 

Powell will determine the long-term characteristics of the CRe. At the other end of the 

ecosystem, the limnology of Lake Mead is occasionally determined by inflows from controlled 

floods. Navigation across the emergent delta of Lake Mead is strongly affected by the storage 

contents of the reservoir. GCMRC is committed to working with Reclamation to identify a 

robust monitoring and research program that can aid in making future decisions about water 

management of these two large reservoirs.

Significant effort was expended in spring 2014 in developing the native fish and rainbow 

trout monitoring programs. These programs are implemented by a consortium of GCMRC, 

Arizona Game and Fish, US Fish and Wildlife Service, and cooperators. Although progress was 

made in developing an efficient and cost-effective program, much remains to be done to hone 

this program to meet the science needs of the GCDAMP while also expending money efficiently.

44
We believe that a panel of science experts on this topic could greatly assist the agencies in 

developing this program for the future.

In very early June, GCMRC was notified that riparian vegetation management was being 

proposed for the CRe. This work would be part of the LTEMP EIS program. Following 

conversation with sister agencies, GCMRC proposes to conduct a science panel to review 

methods of riparian vegetation management and monitoring in an effort to provide stakeholders 

and the National Park Service with a scientific basis to initiate this program.

GCMRC Project Administration 

Administration of the GCMRCs work is funded in two ways – as direct costs associated 

with the salaries and travel expenses of key leadership and administrative personnel and as 

indirect costs (called “burden” in the USGS) that support the USGS Southwest Biological 

Science Center (SBSC). Part of the indirect costs are assessed at a 16% burden rate in FY15 on 

all work conducted by GCMRC staff and partly by a direct $1 million allocation by the USGS to 

the SBSC. 

Relation between FY15–17 Triennial Work Plan and Administrative 

Guidance 

The FY15–17 TWP follows the structure of the FY13–14 BWP which simplified and 

consolidated GCMRC’s research and monitoring activities into larger projects focused on 

significant natural and socioeconomic resource questions and resource conditions. There are 

twelve projects (Project 1–Project 12) in the fields of physical and biological sciences. Two of 

those projects address issues of cultural resources and cultural landscape change. An additional 

project focused on socioeconomic monitoring and research (Project 13) is also included. Other 

funds support independent reviews, GIS services and support, and administration of the 

GCMRC.

In developing the TWP, GCMRC explicitly considered the recently adopted Desired Future 

Conditions report and the direction on science priorities provided by Assistant Secretary Castle 

in her memos of March 31, 2011 and May 7, 2014. Additionally, the TWP addresses 

commitments associated with GCMRC’s role in implementing two recent Environmental 

Assessments. Most importantly, the GCMRC TWP is consistent with the various GCDAMP 

science planning documents. Each BWP Project describes how work in FY15–17 addresses 

strategic science questions and information needs previously addressed by the GCDAMP.

Desired Future Conditions 

Desired Future Conditions (DFCs) for the Colorado River ecosystem were proposed by the 

Desired Future Conditions Ad Hoc Committee of the Adaptive Management Work Group 

(AMWG), and their report was presented to the AMWG in February 2012. By consensus, the 

AMWG commended to the Secretary of the Interior this report. On April 30, 2012, the Secretary 

of the Interior directed “the AMWG to utilize these DFCs to inform and guide the AMWG’s 

future considerations, including advice and recommendations ... concerning operations of Glen 

Canyon Dam and other related actions.” Thus, these desired future conditions are an essential 

foundation for decision-making in the Glen Canyon Dam Adaptive Management Program. The 

45
DFCs are divided into four categories: the Colorado River ecosystem (CRe), power, cultural 

resources, and recreation.

As described in a following section, Assistant Secretary Castle had provided guidance about 

science planning in a March 2011 memo that anticipated that these DFCs would be adopted. At 

that time, Assistant Secretary Castle directed GCMRC to focus most of its attention of those 

DFCs that concern sediment and fish. The Assistant Secretary reiterated that guidance in a May 

2014 memo while also noting that cultural resources are also priorities. The FY15–17 TWP 

follows the guidance provided in both these documents. Here, the relation of the TWP to all 

DFCs is discussed. 

Colorado River ecosystem 

The CRe DFCs “address the natural resource values for which Grand Canyon National Park 

and Glen Canyon National Recreation Area were established. As such, the CRe DFCs recognize 

that native and nonnative species are to be managed in accord with Federal regulations, policies, 

and guidelines. There are four attributes of the CRe specifically addressed by the DFCs: 

sediment-related resources, water quality, the aquatic domain, and the riparian domain. 

The FY15–17 TWP is organized to directly link with the organization of the CRe DFCs. 

Projects 1 and 2 address the issues raised by the Water Quality CRe DFC, that calls for 

measurement of dissolved oxygen, nutrient concentrations and cycling, turbidity, temperature, 

and hydro-physical conditions such as discharge and sediment transport. Project 1 focuses on 

measurement of water quality attributes of Lake Powell reservoir while Project 2 pertains to 

water quality, discharge, and sediment transport in the Colorado River and selected tributaries 

downstream of Glen Canyon Dam. 

Project 3 addresses monitoring and research topics related to the sediment-related resources 

of the CRe DFCs – primarily the characteristics of nearshore habitats for native fish, the 

substrate characteristics and landforms associated with marsh and riparian habitat for fish, and 

camping beaches. Project 4 addresses the linkage between fine-sediment deposits and cultural 

resource preservation.

The CRe DFC for the aquatic domain focuses on desired attributes of native species, rainbow 

trout, extirpated species, and non-fish biotic communities. Projects 6, 7, and 8 are focused on 

native fish species, especially the humpback chub, a federally-listed endangered species. 

Monitoring and research activities in Projects 6 and 7 address scientific issues associated with 

the desired recovery of humpback chub throughout its former range in the CRe. Project 7 is 

focused on scientific issues associated with the largest aggregation of humpback chub that occurs 

in and near the Little Colorado River. Project 8 entails management actions designed to benefit 

native fish.

Project 9 is focused on rainbow trout in Glen and Marble Canyons, and Project 9.6 is focused 

on the interactions between trout and native fish throughout the CRe. 

There are no proposed projects that focus on the re-establishment of extirpated fish species in 

the CRe, despite the stated DFC on this topic. There are also no proposed projects focused on 

nonnative non-fish species such as the Northern Leopard Frog, although Project 5 does include 

characterization of the invertebrate community that is a key part of the food base for native and 

nonnative fish.

Project 11 is focused on the CRe riparian domain. This project is primarily a vegetation 

monitoring project, because the distribution of vegetation communities, characterized as 

vegetation response guilds, and the distribution of fine-sediment substrates constitutes the 

46
various riparian habitats that are of interest in the DFCs. This project also includes an element to 

explore the linkages between the aquatic ecosystem and terrestrial fauna

The CRe DFCs explicitly propose four metrics by which achievement of the DFCs can be 

measured:

Percentage of critical habitat lost or gained

Condition of species variability

Carrying capacity thresholds

Population estimates

The FY15–17 TWP explicitly ensures that population estimates for humpback chub and 

rainbow trout are provided to the GCDAMP, and status and trend monitoring of other native and 

nonnative species are also determined. Additionally, the longitudinal distribution of humpback 

chub and trout are determined by studies of humpback chub aggregations and the distribution of 

rainbow trout throughout Marble Canyon. Other monitoring efforts provide estimates of the 

distribution of other native and nonnative fishes. Changes in critical habitat are provided for the 

area and abundance of backwater habitat (Project 3) and by mapping of riparian vegetation 

(Project 11).

Power 

The overarching DFC goal and objective for power is that “Glen Canyon Dam capacity 

and energy generation is maintained and increased, so as to produce the greatest practicable 

amount of power and energy, consistent with the other DFCs.” Thus, the DFC for power 

identifies the importance of hydropower to the greater Western Electricity Coordinating Council, 

but recognizes the impact power production at Glen Canyon Dam has on other downstream 

resources. Project 13 directly addresses this specific goal and objective by initiating the 

development of a decision support system to inform the GCDAMP in the organization and 

evaluation of management actions, monitoring, and research. The analytical methods, predictive 

models in the decision support system, will provide a platform to identify the least-cost approach 

(i.e., foregone hydropower) to meet other DFCs. The research in Project 13 is consistent with the 

goal and objective of the power DFC and with the Record of Decision’s goal of not maximizing 

benefits but determining an operation at Glen Canyon Dam that limits impact to hydropower 

while meeting recovery and long-term sustainability of downstream resources. 

Cultural Resources 

Cultural resources in the CRe include prehistoric archaeological sites, historic sites, and 

Traditional Cultural Properties (TCPs). The DFC for prehistoric archaeological sites and for 

historic sites is “to the extent feasible, maintain significance and integrity through preservation in 

place.” The focus of the DFCs for TCPs is that the attributes and integrity of TCPs is maintained. 

Thus, the DFC for cultural resources recognizes that many natural processes and attributes of the 

CRe affect cultural resources. These processes include those related to stream flow, sediment 

transport, geomorphology, and riparian vegetation. Cultural resources are also affected by 

recreation activity. The DFC specifically proposes that achievement of the goals for cultural 

resources be measured by:

Erosion or deposition rates of substrates in which cultural sites occur

47
Impacts at sites that affect eligibility to the National Register of Historic Places

The FY15–17 TWP is responsive to these DFCs and their proposed metrics. Project 11 

involves a system-wide monitoring of riparian vegetation. Project Element 4.1 continues a 

system-wide, comprehensive study of geomorphic processes and geomorphic attributes that 

affect prehistoric and historic sites. Such a project has never been previously undertaken as part 

of the GCDAMP-funded GCMRC program. The goal of this project is to establish the linkage 

between the area and abundance of river sand bars (Project 3) that are directly affected by dam 

operations and the redistribution of fine sediment upslope to areas that contain prehistoric and 

historic sites. Additionally, Project 4 evaluates the degree to which gullies in the CRe grow or 

are eliminated by changing geomorphic conditions in the river channel itself. This Project also 

explores detailed measurement protocols in Glen, Marble, and Grand Canyons that might be 

used to precisely measure topographic changes at the local scale. The challenge of Project 4 is to 

provide scientific guidance as to how large-scale and local-scale measurements and observations 

can be linked.

The cultural resource DFCs also propose metrics for assessing the condition of resources not 

eligible for the National Register of Historic Places. Because “only members of that culture can 

assess the status or health of the resources” important to each Native American Tribe, this 

monitoring activities are not part of the GCMRC program. Tribes are funded directly for their 

monitoring efforts, as described in Chapter 1.

Recreation 

There are four categories for recreation DFCs: 1) river recreation in Grand Canyon National 

Park; 2) river recreation in Glen Canyon National Recreation Area; 3) blue ribbon trout fishery 

in Glen Canyon National Recreation Area; and 4) river corridor stewardship. Each category 

identifies specific resource conditions as goals and objectives. The metrics used to evaluate these 

goals and objectives include the condition of recreational resources, socioeconomic value 

associated with the recreation, and overall recreation visitation/expenditures. The FY15–17 TWP 

will provide monitoring and research concerning the socioeconomic value of river recreation and 

angling below Glen Canyon Dam (Project 13). This research will also inform on the preference 

for resource quality and the regional economic effects of recreation based tourism in Glen 

Canyon National Recreation Area and Grand Canyon National Park. This information provides a 

subset of the metrics proposed to evaluate recreation DFCs. Project 13 also initiates the 

development of a decision support system to inform the GCDAMP in the organization and 

evaluation of management actions, monitoring, and research. This will allow GCDAMP to better 

evaluate the tradeoffs, how the recreation metrics in the DFCs are impacted, among other 

resource DFCs when managing the operation of Glen Canyon Dam.

The FY15–17 TWP will also provide monitoring data concerning other recreation DFCs and 

the metrics used to evaluate them. The distribution and size of campable beaches is an element of 

Project 3. Additionally, Project 7 will provide research and monitoring data concerning the 

interactions between trout and native fish and Project 9 will directly inform management of the 

Glen Canyon fishery. A creel survey (Project Element 6.8) will also provide data concerning 

angler success and experience in GCNRA.

48
Science Planning to Implement the Environmental Assessment for a Protocol for High-Flow Experimental 

Releases 

This Environmental Assessment (EA) was released by Reclamation on December 30, 2011, 

and this EA includes a General Science Plan that describes scientific activities needed to 

implement the High-Flow Experiment Protocol. 

This Science Plan describes eight tasks that would be undertaken by GCMRC. The primary 

work activity is Task 1: Monitoring within-channel and high-elevation sediment storage, and 

these same activities are described in more detail in Project 3 of this TWP. Task 2 of the Science 

Plan is described as Project 2 of this TWP. Task 3 concerns monitoring archaeological site 

conditions, and these activities are described in Project 4 of the TWP. The work described in 

Project 4 represents advancements in thinking about how to monitoring and understand changes 

at archaeological sites, and thus differs in detail from what is briefly described in the Science 

Plan. Task 4 concerns monitoring the aquatic food base and this work is described in Project 5. 

Riparian vegetation monitoring that is described in Task 5 of the Science Plan is described in a 

more comprehensive way in Project 11 of the FY15–17 TWP. Task 6 concerns monitoring of the 

Kanab ambersnail. GCMRC does not propose to conduct any monitoring of these populations in 

FY15–17 because new information needs were not identified and delisting of the Grand Canyon 

populations may occur. Task 7 of the Science Plan concerns water quality monitoring in Lake 

Powell and in Glen Canyon and these measurements will be undertaken as parts of Projects 1 and 

2 of the TWP. Task 8 concerns the evaluation of the effects on hydropower production, and this 

work will not be conducted as part of the GCMRC TWP.

Science Planning to Implement the Environmental Assessment for Non-Native Fish Control 

This Environmental Assessment (EA) and an associated Biological Opinion were released by 

Reclamation on December 30, 2011. The EA includes a General Science Plan that describes 

scientific activities needed to implement non-native fish control downstream from Glen Canyon 

Dam. The Biological Opinion also identifies research and monitoring activities needed for 

implementation of this EA.

The science plan in support of this EA identifies five objectives to be addressed by GCMRC. 

The first objective is to understand the relative roles of the Little Colorado River (LCR) and the 

mainstem Colorado River in juvenile humpback chub survival rates and recruitment into the 

adult humpback chub population which will be addressed by activities described in Projects 6 

and 7. To address objective two, determine the linkage between nonnative fish abundance and 

juvenile humpback chub abundance and survival rates in the LCR reach and elsewhere in Grand 

Canyon, we will undertake the tasks described in Projects 7 and 9. Determine the natal origins of 

rainbow trout found in Marble Canyon (river miles 8 to 56) and the LCR reach is the third 

objective and will be resolved by research and monitoring conducted as part of Project 9. 

Objective four is to assess the efficacy of nonnative fish removal in the Paria Riffle-Badger 

Rapid reach for rainbow trout and Upper Granite Gorge for brown trout. Fish removal in Paria 

Riffle-Badger Rapid reach will not occur due to the presence of whirling disease which disallows 

live fish removal, a condition agreed to for this task. Activities associated with brown trout 

removal are described in Projects 8. The final objective, assess the efficacy of flow 

manipulations to manage trout populations in the mainstem Colorado River from Lees Ferry to 

the LCR reach, will be monitored through tasks described for Projects 6 and 9. 

The Biological opinion mandates monitoring the status and trends of adult humpback chub in 

the LCR (see Project 7), in the mainstem Colorado River (see Projects 6 and 7), and at areas 

49
where humpback chub have been translocated (see Projects 6, 7, and 8). The Biological Opinion 

also defines triggers to determine when nonnative fish control will take place near the LCR. 

Triggers are related to the abundance of adult and juvenile humpback chub which are addressed 

in Projects 6 and 7, survival rates of juvenile humpback chub as determined in Projects E, F.3, 

and F.4.3, abundance of rainbow trout and brown trout as determined in Projects F.1, F.3, F.6, 

and G.2, and river temperature monitored as part of Project B.

Research and Monitoring Priorities Provided by Assistant Secretary Castle 

On March 31, 2011, Assistant Secretary Anne Castle provided direction to GCMRC 

regarding science planning; this direction was provided in the form of a memo to Kate Kitchell, 

Mark Sogge, and Ted Melis. Assistant Secretary Castle directed GCMRC to primarily focus on 

the DFCs that were, at the time, still in draft form. Within that context, the Assistant Secretary 

urged that GCMRC more narrowly focus its interest on a few of the DFCs, “because the DFCs 

are very comprehensive” and it was assumed that insufficient funds existed to focus on every 

DFC. The priorities provided in this memo are that GCMRC should “concentrate its resources” 

on

“... compliance with the Endangered Species Act, which means focus on the native fish 

and particularly the humpback chub”;

“... focus on sediment, which was an instigating factor for the Grand Canyon Protection 

Act and continues to be an issue with resources downstream of the dam. That 

includes being able to respond if the high flow protocol goes forward”; and,

“... science on both non-native fish control and the recreational trout fishery.”

Assistant Secretary Castle also observed that “while cultural resources remain a very high 

priority, it is not clear that there are significant science questions involving those resources, or 

the [Temperature Control Device],that require attention at this time.” Castle also indicated that 

core monitoring activities in other resource areas should continue. The overall objective of her 

guidance was “to enable GCMRC to better direct its limited resources and resist the Christmas 

tree approach to science planning.”

On May 7, 2014, Assistant Secretary Anne Castle provided additional direction concerning 

science planning in a memo to Jack Schmidt and Glen Knowles. The Assistant Secretary 

reiterated the guidance provided in the March 2011 for the three main science priorities. 

Additionally, the Assistant Secretary recognized that other priority issues included 

“understanding ... how cultural and archaeological sites are linked to modern river processes and 

the role of Traditional Ecological Knowledge (TEK) in contributing to scientific understanding 

and river operations.” Thus, the Assistant Secretary stated that, “I think these four issues (the 

three described in my 2011 memo and the evolving issue related to cultural/archaeological 

resources as linked to modern river processes) are the primary areas where GCMRC should 

concentrate its scientific resources.”

GCMRC’s FY15–17 TWP primarily focuses on the key priorities established by the 

Assistant Secretary, namely humpback chub (Projects 6 and 7), native and nonnative fish 

(Projects 6, 7, 8, and 9), recreational trout (Projects 6 and 9), and the interactions between trout 

and native fish (Project 9). Projects 2 and 3 monitor the flux and distribution of fine sediment, 

which is also a priority described in the memo. Project 3 is also fundamental to implementation 

50
of the High Flow Experiment Protocol, and Project 3 is fundamental to evaluating the 

effectiveness of the Protocol. Projects 4 and 12 address monitoring and research needs in cultural 

resources. Projects 11 and 13 address monitoring and research needs in vegetation and 

socioeconomics that are not explicitly described in the memo,but that have widespread 

stakeholder interest.

General Core Monitoring Plan 

A final draft plan was prepared by GCMRC on February 18, 2011, and was submitted to the 

TWG. This plan is organized around the eleven GCDAMP Program Goals that concern natural 

resources. Previous BWP documents of the GCMRC were also organized around these Program 

Goals. However, in the reorganization of the Work Plan represented in the FY13–14 document 

and carried forward in the FY15–17 TWP, the various goals associated with the aquatic domain 

(Goals 1, 2, 3, and 4) were reorganized into Projects 5, 6, 7, 8, 9. Program Goal 5 concerns the 

Kanab ambersnail, and there are no activities proposed in FY15–17 on this topic. Program Goal 

6 is the focus of Project 11 in the FY15–17 TWP. Goal 7 is the focus of Projects 1 and 2, and 

Goal 8 is the focus of Project 3. Goal 9 is, at least in part, the focus of Projects 3 (camping 

beaches), 6 (creel surveys), and 13 (economic values of recreational resources). Goal 10 is not 

explicitly evaluated in the TWP. Project 4 and 12 represent an expanded focus on Goal 11.

The monitoring methods described in the FY15–17 TWP represent a substantial scientific 

advancement in developing formalized protocols for regular measurement of key river resources. 

In the case of protocols for measuring sand bars (Project 3), sediment transport and water quality 

(Project 2), humpback chub and rainbow trout populations and status and trends of other fish 

species (Projects 6, 7, 8, 9), and monitoring vegetation communities, GCMRC has worked with 

sister agencies and collaborators to develop efficient protocols that take advantage of large 

bodies of historical data, address issues of how to extrapolate site scale measurements to the 

entire CRe, and how to estimate temporal trends in key resources.

The next step in the formalization of monitoring protocols will be to take the advancements 

described in the TWP and incorporate these into a revised General Core Monitoring Plan.

Monitoring and Research Plan 

The most recent plan was amended and approved in April 2009. This plan describes various 

Strategic Science Questions (SSQs). Subsequent planning documents have identified Core 

Monitoring Information Needs (CMINs) and Research Information Needs (RINs). Each of the 

GCMRC projects of the FY15–17 TWP describes the administrative and management context 

for each specific proposal and describes the relevant SSQs, CMINs, and RINs. Each project 

description also discusses the current status of knowledge on the various scientific topics and the 

role of work in FY15–17 in answering key questions of the GCDAMP.

Allocation of the FY15–17 Budget 

The total proposed budget of GCMRC in FY15 is $10,228,721 (see Appendix 2-A). Projects 

recommended for funding in FY15 by GCMRC total to $9,575,341 (see Appendix 2-B). Funding 

for this amount includes $8,749,810 from GCDAMP funds, an additional $804,181 from other 

Reclamation funding sources, including $364,052 for native fish projects from the native fish 

conservation contingency fund and $21,350 from the USGS Southwest Biological Science 

51
Center. Currently unfunded projects are fully described in the Work Plan and categorized as 

either High Priority or Moderate Priority in the budget table found in Appendix 2-B.

Of the almost $9.5 million budget recommended for funding, 40% is to be allocated to 

monitoring and research work in aquatic ecology and fisheries and 32% is to be allocated to the 

projects in geomorphology, stream flow monitoring, sediment transport, and water quality. 

Direct administrative costs are 14% of the budget. The combined work in riparian ecology, 

cultural resources, economics, and independent reviews is a small proportion of the proposed 

work. The budget for the GCMRC part of the FY15–17 TWP is described at the end of each 

project description, and is summarized in various appendices at the end of this document.

The proposed budgets for out years are $11,168,364 in FY16 (see Appendix 2-C) and 

$11,048,802 in FY17 (see Appendix 2-D). Projected GCDAMP funds available for these years 

are $9,025,273 in FY16 and $9,301,821 in FY17. Recommendations for project funding in FY16 

and FY17are not included in this draft of the TWP. Uncertainties related to LTEMP process, the 

need for stakeholder feedback, and other factors led to the decision to defer the development of 

project funding recommendations until July and August of 2014.

References 

Bureau of Reclamation, 2011a, Environmental assessment--development and implementation of 

a protocol for high-flow experimental releases from Glen Canyon Dam, Arizona, 2011 

through 2020: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado Region, 176 p. 

+ appendices, accessed on March 21, 2012, at 

http://www.usbr.gov/uc/envdocs/ea/gc/HFEProtocol/HFE-EA.pdf.

Bureau of Reclamation, 2011b, Environmental assessment--non-native fish control downstream 

from Glen Canyon Dam: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado

Region, 102 p. + appendices, accessed on March 21, 2012, at 

http://www.usbr.gov/uc/envdocs/ea/gc/nnfc/NNFC-EA.pdf.

Howard, A.D., and Dolan, R., 1981, Geomorphology of the Colorado River in Grand Canyon: 

Journal of Geology, v. 89, no. 3, doi: 10.1086/628592, p. 269-298, accessed on February 18, 

2010, at http://www.jstor.org/pss/30078299.

Laursen, E.M., Ince, S., and Pollack, J., 1976, On sediment transport through the Grand Canyon, 

in Federal Interagency Sedimentation Conference, 3d, Denver, Colo., March 22-25, 1976, 

Proceedings: p. 4-76 to 74-87.

Schmidt, J.C., and Grams, P.E., 2011, Understanding physical processes of the Colorado River, 

in Melis, T.S., ed., Effects of three high-flow experiments on the Colorado River ecosystem 

downstream from Glen Canyon Dam, Arizona: U.S. Geological Survey Circular 1366, 17-51 

p., accessed on June 28, 2011, at http://pubs.usgs.gov/circ/1366/.

Topping, D.J., Rubin, D.M., Nelson, J.M., and Kinzel, P.J., 2000, Colorado River sediment 

transport 2--systematic bed-elevation and grain-size effects of sand supply limitation: Water 

Resources Research, v. 36, no. 2, doi: 10.1029/1999WR900286, p. 543-570, accessed on 

November 9, 2010, at http://www.agu.org/journals/wr/v036/i002/1999WR900286/.

U.S. Department of the Interior, 1995, Operation of Glen Canyon Dam--final environmental 

impact statement, Colorado River storage project, Coconino County, Arizona: Salt Lake 

City, Utah, USA, Bureau of Reclamation, Upper Colorado Regional Office, 337 p., accessed 

on November 18, 2010, at http://www.usbr.gov/uc/library/envdocs/eis/gc/pdfs/Cov-con/covcon.pdf

52
U.S. Geological Survey, 2011, General core monitoring plan for the Glen Canyon Dam Adaptive 

Management Program: Flagstaff, Ariz., U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center, 134p.

U.S. Geological Survey, 2007a, Monitoring and research plain in support of the Glen Canyon 

Dam Adaptive Management Program: Flagstaff, Ariz., U.S. Geological Survey, Grand 

Canyon Monitoring and Research Center, 149 p.

U.S. Geological Survey, 2007b, Monitoring and research plan in support of the Glen Canyon 

Dam Adaptive Management Program: Flagstaff, Ariz., U.S. Geological Survey, Grand 

Canyon Monitoring and Research Center, 149 p.

 

53
Project 2. Streamflow, Water Quality, and Sediment 

Transport in the Colorado River Ecosystem 

A. Investigators 

David J. Topping, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center

Ronald E. Griffiths, Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

David J. Dean, Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

B. Project Summary 

This proposal is to fund the ongoing required core monitoring of stage, discharge, water 

quality (water temperature, specific conductance, turbidity, dissolved oxygen), suspended 

sediment, and bed sediment at gaging stations in the Colorado River Ecosystem (CRe) 

downstream from Glen Canyon Dam in Glen Canyon National Recreation Area and Grand 

Canyon National Park. The data collected by this project provide the fundamental stream-flow, 

sediment-transport, sediment-budget, water-temperature, and water-quality data that are required 

to evaluate the status of the Cre with respect to the Desired Future Conditions for the Cre 

approved by the Secretary of the Interior in April 2012. In addition, the data collected by this 

project are required to trigger and evaluate the High Flow Protocol approved by the Secretary of 

the Interior in May 2012 for the period through 2020, and are to be used to evaluate the success 

of the preferred alternative ultimately adopted by the Long-Term Experimental Plan (LTEMP) 

EIS. Finally, the data collected by this project are used in virtually all other physical, ecological, 

and socio-cultural resource investigations funded by the Glen Canyon Dam Adaptive 

Management Program. Thus, this project is the project that makes the basic measurements that 

directly link dam operations and reservoir releases to the physical, biological, and sociocultural 

resources of the CRe. This project also funds interpretation of these basic data, specifically 

examining how stream flow, water quality, and sediment transport affect resources of the CRe.

C. Background

C.1. Scientific Background 

The primary linkage between the release of Lake Powell reservoir water by Glen Canyon 

Dam operations and the response of the physical, biological, and cultural resources in the CRe is 

through the stage, discharge, water quality, and sediment transport of the Colorado River (U.S. 

Department of the Interior, 1995; National Research Council, 1996). Reservoir releases are the 

principal determinant of these attributes of the Colorado River in the CRe, because tributary 

inflows only affect the Colorado River’s characteristics during rare, large tributary floods.

Sediment on the bed and banks constitutes the physical template of the CRe (U.S. 

Department of the Interior, 1995; National Research Council, 1996). Suspended sediment is an 

important water quality parameter, because suspended sediment regulates the aggradation and 

54
erosion of eddy sandbars and channel-margin deposits that are important to many biological, 

cultural, and recreational resources (Rubin and others, 2002, Wright and others, 2005, 2008). 

Suspended sediment also controls turbidity, and therefore influences the aquatic and fish 

ecology of the river. The endemic fishes of the CRe evolved in a highly turbid river (Gloss and 

Coggins, 2005). Turbidity is predominantly determined by the concentration of suspended silt 

and clay (hereafter called mud) and, to a lesser degree, suspended sand. Prior to closure of Glen 

Canyon Dam, 60% of the fine sediment supply to the upstream end of the CRe was mud 

(Topping and others, 2000a). Closure of Glen Canyon Dam reduced the supply of sand and mud 

by about 95% at Lees Ferry, and the Paria River is now the major supplier of fine sediment to 

Marble Canyon (Topping and others, 2000). The post-dam Colorado River in Marble and Grand 

Canyons is much less turbid than ever occurred naturally (Voichick and Topping, 2014). 

Because the in-channel storage of sand and mud in the post-dam Colorado River is greatly 

reduced from pre-dam conditions, the Colorado River in the CRe is only now turbid during 

periods of tributary flooding. 

Systematic measurements of stream flow and the quality of water, including suspendedsediment concentration, in the CRe began with installation of the Lees Ferry gaging station in 

May 1921 (Topping and others, 2003; Howard, 1947). During much of the 20th century, daily 

measurements of suspended-sediment concentration and temperature, and episodic 

measurements of other water-quality parameters, were made by the USGS at multiple sites. This 

intensive period of measurements ended in the early 1970s (Topping and others, 2000a). 

Concern about the effects of operations of Glen Canyon Dam on the CRe resulted in a new 

emphasis on scientific measurements and modeling of water quality and sediment transport 

beginning in the early 1980s (National Research Council, 1996). The results of these studies 

have been published in numerous USGS reports and journal articles, and ultimately resulted in 

the current form of the proposed project. 

Recent research on the Colorado and on other rivers has shown that, to be meaningful, 

measurements of stage, discharge, water quality, and suspended sediment must be made at 

temporal resolutions higher than those over which these parameters vary. In the specific case of 

suspended sediment, substantial changes in suspended-sand concentration and suspended-mud 

concentration are determined by changes in the upstream supply of those sediments, changes that 

occur over timescales < 1 hour (Topping and others, 2000b; Wright and others, 2010a, 2010b). 

Furthermore, Rubin and Topping (2001a, 2001b, 2008) showed that, in the case of the damregulated Colorado River, suspended-sand transport is co-equally regulated by changes in 

discharge and changes in the grain-size of sand available for transport that in turn is determined 

by the upstream supply of sand. The former control is largely determined by changes in dam 

operations and the latter control is largely determined by changes in tributary sand supply. 

Topping and others (2005a, 2007a, 2010) showed that sand transport is much more sensitive to 

sand-supply-driven changes in the grain-size distribution of the bed sediment than changes in the 

amount of sand covering the bed. Topping and others (2005b, 2008) and Hazel and others (2006) 

built on the work of Rubin and Topping and concluded that eddy sandbars are the dominant 

environment containing sand and regulating sand transport in the Colorado River. These findings 

invalidated key aspects of the 1995 EIS (U.S. Department of the Interior, 1995) that assumed that 

suspended-sand transport was only regulated by changes in discharge (Rubin and others, 2002). 

Thus, this project is designed to provide measurements of stage, discharge, water quality, 

and suspended sediment at sufficiently high temporal resolutions (~15-minute) to allow accurate 

determination of suspended sediment loads, as well as other water quality parameters. To allow 

55
the construction of this comprehensive and cost-effective monitoring network, this project has 

conducted pioneering, cutting-edge research on using new, laser-diffraction and acoustic 

technologies to measure water quality and sediment transport (Melis and others, 2003; Topping 

and others, 2004, 2006a, 2007b; Wright and others, 2010c; Voichick and Topping, 2010, in 

press; Griffiths and others, 2012). The acoustic technologies and methods developed by this 

project to measure sediment transport in the Colorado River are now being used in monitoring 

networks to inform river managers in Big Bend National Park, Dinosaur National Monument, 

and Canyonlands National Park. 

C.2. Management Background 

This project funds the ongoing monitoring and research activities associated with the 

measurement of stream flow, sediment transport, and associated water quality attributes. This 

project began as fundamental research in the late 1990s and was recognized as a GCDAMPapproved core-monitoring project in 2007, designed to fully address the monitoring needs of 

GCDAMP Goal 7 (Establish water temperature, quality, and flow dynamics to achieve 

GCDAMP ecosystem goals) and partially address the monitoring needs of GCDAMP Goal 8 

(Maintain or attain levels of sediment storage within the main channel and along shorelines to 

achieve GCDAMP ecosystem goals). The primary objective of this project is to collect the basic 

monitoring data that directly link dam operations and reservoir releases to the physical template 

of the CRe. The stream-flow and sediment-transport data collected by this project are required to 

trigger and evaluate the High Flow Protocol (U.S. Department of the Interior, 2011) approved by 

the Secretary of the Interior in May 2012 for the period through 2020. In addition, the stage, 

stream-flow, sediment-transport, sediment-budget, water-temperature, dissolved-oxygen, 

specific-conductance, and turbidity data collected by this project are used to evaluate the status 

of the Cre with respect to the Desired Future Conditions for the Cre approved by the Secretary of 

the Interior in April 2012. These data are used directly to address DFCs 7 (Water Quality) and 8 

(Sediment), and are used indirectly to address DFCs 1 (Aquatic Foodbase), 2 (Native Fish), 4 

(Lees Ferry Trout Fishery), and 6 (Riparian Zone). Thus, data collected by this project 

constitutes core monitoring, administrative support for agency actions such as the High Flow 

Experiment protocol EA, 2012-2020 High Flow Protocol, and LTEMP EIS, and fundamental 

support for understanding ecosystem processes. Additionally, these data are used to monitor 

compliance with the 1996 Record of Decision, to support research about flow experiments, and 

are critical to development of numerical models concerning river processes.

In addition to supporting GCDAMP Goals 7 and 8, this project provides support for 

Goals 1 (Protect or improve the aquatic food base so that it will support viable populations of 

desired species at higher trophic levels), 2 (Maintain or attain a viable population of existing 

native fish, remove jeopardy for humpback chub and razorback sucker, and prevent adverse 

modification to their critical habitats), 4 (Maintain a wild reproducing population of rainbow 

trout above the Paria River to the extent practicable and consistent with the maintenance of 

viable populations of native fish), 6 (Protect or improve the biotic riparian and spring 

communities within the CRe, including threatened and endangered species and their critical 

habitat), 9 (Maintain or improve the quality of recreational experiences for users of the CRe 

56
within the framework of GCDAMP ecosystem goals), and 11 (Preserve, protect, manage, and 

treat cultural resources for the inspiration and benefit of past, present, and future generations). 

This project supports Goal 1 by providing information on flows, water temperature, 

turbidity, and dissolved oxygen that aids in food base studies, such as the assessment of primary 

productivity and allochthonous inputs. This project supports Goal 2 by providing watertemperature data for the assessment of fish growth rates, turbidity data that are used to adjust for 

catch efficiency in population models, flow and stage data that are important to understanding 

the effects of near-shore habitat changes caused by fluctuating flows, and data on sandbars and 

resulting backwater habitats that are helpful in understanding the importance of sandbars for 

native fish. This project supports Goal 4 through monitoring of discharge, water temperature, 

specific conductance, turbidity, and dissolved oxygen conditions in Glen Canyon. This project 

supports Goal 6 by monitoring the transport and fate of sand and mud, which provides the 

substrate for riparian vegetation and marsh communities. This project supports Goal 9 by 

collecting the monitoring data used in experimental and modeling research relating flow and 

sediment-transport dynamics to the size and abundance of sandbars used as campsites. This 

project supports Goal 11 by collecting the stage, flow, and sediment data used to assess effects of 

dam operations on cultural sites.

C.3. Key Monitoring and Research Questions Addressed in this project 

This project provides direct support to some of the priority questions identified by the 

GCDAMP Adaptive Management Work Group in August 2004. Monitoring of stage, discharge, 

sediment transport, water temperature, and other water quality parameters directly supports some 

priority questions and indirectly supports other questions by providing information on the 

general physical framework of the riverine environment.

This project also directly addresses the following Strategic Science Questions (SSQs), 

Core Monitoring Information Needs (CMINs), and Research Information Needs (RINs) 

previously identified by the GCDAMP. 

• SSQ 4-1. Is there a “Flow-Only” operation (that is, a strategy for dam releases, 

including managing tributary inputs with BHBFs, without sediment augmentation) 

that will restore and maintain sandbar habitats over decadal timescales?

• SSQ 5-1. How do dam release temperatures, flows (average and fluctuating 

component), meteorology, canyon orientation and geometry, and reach morphology 

interact to determine main-stem and near-shore water temperatures throughout the 

CRe?

• CMIN 7.4.2. Determine and track flow releases from Glen Canyon Dam, under all 

operating conditions, particularly related to flow duration, upramp, and downramp 

conditions.

• CMIN 7.1.2. Determine and track Little Colorado River discharge and temperature 

near the mouth.

57
• CMIN 7.1.1. Determine the water temperature dynamics in the main stem, tributaries 

backwaters, and near-shore areas throughout the CRe.

• CMIN 8.1.3. Track, as appropriate, the monthly sand and mud volumes and grainsize characteristics, by reach, as measured or estimated at the Paria and LCR, other 

major tributaries like Kanab and Havasu Creeks, and “lesser” tributaries?

• CMIN 8.1.2. What are the monthly sand and mud export volumes and grain-size 

characteristics, by reach, as measured or estimated at Lees Ferry, lower Marble Canyon, 

Grand Canyon, and Diamond Creek Stations?

• RIN 7.4.1. What is the desired range of seasonal and annual flow dynamics associated 

with power-plant operations, BHBFs, and habitat maintenance flows, or other flows that 

meet GCDAMP goals and objectives?

• RIN 7.3.1. Develop simulation models for Lake Powell and the Colorado River to predict 

water-quality conditions under various operating scenarios, supplant monitoring efforts, 

and elucidate understanding of the effects of dam operations, climate, and basin 

hydrology on Colorado River water quality.

• RIN 8.5.1. What elements of ROD operations (upramp, downramp, maximum and 

minimum flow, MLFF, high modified flow (HMF), and BHBF) are most/least critical to 

conserving new fine sediment inputs, and stabilizing sediment deposits above the 25,000 

ft3/s stage?

D. Proposed Work 

D.1. Project Elements 

(Recommended for funding FY15: $1,343,040)

Much of the proposed work in this project consists of continued high-resolution (typically 

15-minute) measurements of stage, discharge, water temperature, specific conductance, turbidity, 

dissolved oxygen, suspended-sediment concentration, and suspended-sediment grain-size 

distribution. In addition, episodic measurements of bed sediment will be made. These parameters 

are measured at USGS stream-flow gaging stations located on the Colorado River in Marble and 

Grand Canyons at river miles (RM) 0, 30, 61, 87, 166, and 225 (Griffiths and others, 2012). 

Selection of these gaging-station locations was largely based on the need to resolve longitudinal 

differences in sediment storage in key segments of the CRe, to bracket major tributaries, to 

support other GCDAMP-funded projects, and to reoccupy former USGS stream-flow gaging 

stations where stage, discharge, water quality, and sediment-transport data were previously 

collected. In addition, high-resolution stage, discharge, water temperature, suspended-sediment 

concentration, and suspended-sediment grain-size distribution are measured at sites in all of the 

major tributaries to the Colorado River and in a representative subset of the smaller, and 

formerly ungaged, tributaries (Griffiths and others, 2010, in press). All measurements of stage, 

discharge, water quality, and all physical measurements of suspended- and bed sediment are 

58
made using standard, approved USGS techniques. Errors in conventional suspended-sediment 

measurements are calculated using the methods of Topping and others (2011) and Sabol and 

Topping (2013). The laser diffraction and acoustic measurements of suspended sediment are 

made using techniques described in Melis and others (2003), Topping and others (2004, 2006a, 

2007b), and Wright and others (2010c).

The funding requested here only partially covers the costs of data collection at the USGS 

gaging stations, because operations of some of the gaging stations are supported by nonGCDAMP sources. Thus, their locations are partially dictated by non-GCDAMP goals. For 

example, gage height and discharge data collected at the gaging stations on the Colorado River at 

Lees Ferry, AZ (09380000), and above Diamond Creek near Peach Springs, AZ (09404200), are 

entirely funded from non-GCDAMP sources. In addition, gage height and discharge data 

collected at the gaging stations on the Paria River at Lees Ferry, AZ (09382000), the Little 

Colorado River near Cameron, AZ (09402000), and on the Colorado River near Grand Canyon, 

AZ (09402500), are heavily subsidized by non-GCDAMP sources. Finally, all of the personnel 

listed on this project receive parts of their salary from non-GCDAMP sources. Substantially 

reducing the requested budget for this project would result in an inability to accurately trigger 

and evaluate HFEs released under the 2012-2020 High Flow Protocol, decommissioning gaging 

stations at which data are collected to evaluate DFC metrics, and/or removing the website 

(described below) used to deliver data and trigger HFEs.

The most significant product from this project during FY 2013-14 has been the development 

of the website on which we serve project data and serve user-interactive sediment budgets: 

http://www.gcmrc.gov/discharge_qw_sediment/. The user-interactive sediment budgets found on 

this website are currently being used to design HFEs. During FY 2015-17, we propose to 

continue to serve project data and user-interactive sediment budgets through this website. In 

addition, work will continue to add additional data streams to this website and expand the userinteractive tools. Chief among the new tools to be developed are user-interactive duration curves. 

Duration curves are one of the most useful and powerful tools for conveying complicated 

hydrologic and water-quality datasets. We have successfully used duration curves to analyze 

changes in stage, discharge, and turbidity for various periods and reaches in the CRe (Topping 

and others, 2003; Voichick and Topping, 2014). Once the duration-curve tool is added to the 

website, the user will be able to plot the percentage of time any parameter served on our website 

is equaled or exceeded for any user-specified period.

All database and website work has been made possible through collaboration with the 

USGS Center for Integrated Data Analytics (CIDA). The CIDA is the leader within the USGS in 

database and web programming. Collaboration with the CIDA has resulted in a major leap 

forward in serving data in a user friendly and interactive way, something that has proven 

problematic for GCMRC to do on its own in previous funding cycles. The tools developed in 

collaboration with the CIDA are allowing anyone to plot the data, construct mass-balance 

sediment budgets, and plot changes in reach-averaged bed-sediment grain size for any time 

period in any reach of the CRe on demand. In addition, these tools allow different user-chosen 

methods for error propagation through these sediment budgets. Because sandbar response during 

controlled floods depends on both the amount and grain-size distribution of the sand stored in 

each river segment (Topping and others, 2006b, 2010), these tools have proven to be extremely 

useful in the planning of controlled floods under the HFE protocol EA (U.S. Department of the 

Interior, 2011) and will inform future monitoring efforts.

59
In addition to the collection and serving of the basic stream-flow, water-quality, and 

sediment-transport data, time is spent in this project interpreting the data and reporting on the 

results and interpretations in peer-reviewed articles in the areas of hydrology, water quality, and 

sediment transport. The interpretive papers published by this project are designed to address key 

questions relevant to river management, especially to management in the GCDAMP (see 

proposed publication list below). The data collected in this project form the basis of the 

collaborations listed in the next section. All of the projects funded in the areas of physical 

science, biology, and socioeconomics require the data collected by this project. During FY 2015-

17, multiple journal articles and top-tier USGS reports will be published on the following topics:

• Analysis of Paria River and Little Colorado River hydrology 1920s-present with 

implications for long-term sediment management in the CRe (lead author Topping)

• Geomorphology, hydraulic geometry, and sediment transport in the Paria River (lead 

author Topping)

• Analysis of a decade of measurements of sediment transport in the lesser tributaries: Do 

the lesser tributaries matter? (lead author Griffiths)

• Linkage between hydrology, sediment transport, and geomorphic change in the Little 

Colorado River, with implications for aquatic and riparian habitat in the lower Little 

Colorado River (lead author Dean)

In addition to these major publications, additional data reports and interpretive reports will be 

published by project personnel and USGS cooperators.

D.2 Personnel and Collaborations 

The USGS-GCMRC personnel on this project are: David Topping (Research Hydrologist 

and Project Chief), Ronald Griffiths (Hydrologist and Deputy Project Chief), David Dean 

(Hydrologist), Nick Voichick (Hydrologist and Water Quality Specialist), Tom Sabol 

(Hydrologist), Joel Unema (Hydrologic Technician, part-time), Taylor Roe (Hydrologic 

Technician, laboratory worker), and Jason Fobair (Hydrologic Technician, student laboratory 

worker).

The measurements of this project are essential to the success of Project 3 (Grams and others, 

Sandbars and Sediment Storage Dynamics). The measurement data and the mass balance 

sediment budgets computed in Project 2 and compared with the morphometric sediment budgets 

calculated in Project 3. The major external collaborations funded through this project are with 

three USGS cooperators: the Arizona Water Science Center, the Utah Water Science Center, and 

the Center for Integrated Data Analytics. Collaborations also exist between this project and every 

other funded physical-sciences and biology project at the Grand Canyon Monitoring and 

Research Center, mostly in a supporting role, and with researchers in academia. In previous 

years, academic collaborations have existed between this project and researchers at the 

University of Colorado, College of William and Mary, Arizona State University, Utah State 

University, and Northern Arizona University. 

D.3 Deliverables 

60
1. 15-minute stage, discharge, and water temperature data (updated every 1-4 hours in 

realtime) and other QW data from the 9 gaging stations maintained by the USGS Arizona 

and Utah Water Science Centers under this project are available at 

http://waterdata.usgs.gov/nwis and http://www.gcmrc.gov/discharge_qw_sediment/.

2. 15-minute stage, discharge, water temperature, specific-conductance, turbidity, dissolvedoxygen, and suspended-sediment-concentration and grain-size data from the stations 

maintained by GCMRC under this project are available at 

http://www.gcmrc.gov/discharge_qw_sediment/. These data are updated as frequently as 

every month, depending on data-collection location.

3. Mass-balance sand budgets for the CRe constructed using 15-minute sediment-transport 

data are served at http://www.gcmrc.gov/discharge_qw_sediment/ and updated on a 

monthly basis.

4. Advanced user-interactive data-analysis tools (including user-interactive duration curves) 

on the web at http://www.gcmrc.gov/discharge_qw_sediment/.

5. Annual water-data reports for stage, discharge, and water quality data collected by the 

Arizona and Utah Water Science Centers are published online.

6. At least four interpretive journal articles and top-tier USGS reports on project-relevant 

topics on the Colorado River and its tributaries in the CRe (see proposed publication list 

above).

7. At least three additional peer-reviewed data reports and interpretive reports identified 

during the course of this study.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

1. 15-minute stage, discharge, and water temperature data (updated every 1-4 hours in 

realtime) and other QW data from the 9 gaging stations maintained by the USGS Arizona 

and Utah Water Science Centers under this project are available at 

http://waterdata.usgs.gov/nwis and http://www.gcmrc.gov/discharge_qw_sediment/.

2. 15-minute stage, discharge, water temperature, specific-conductance, turbidity, dissolvedoxygen, and suspended-sediment-concentration and grain-size data from the stations 

maintained by GCMRC under this project are available at 

http://www.gcmrc.gov/discharge_qw_sediment/. These data are updated as frequently as 

every month, depending on data-collection location.

61
3. Mass-balance sand budgets for the CRe constructed using 15-minute sediment-transport 

data are served at http://www.gcmrc.gov/discharge_qw_sediment/ and updated on a 

monthly basis.

4. Annual water-data reports for stage, discharge, and water quality data collected by the 

Arizona and Utah Water Science Centers are published online at: 

http://wdr.water.usgs.gov/wy2012/pdfs/09380000.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09381800.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09382000.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09402000.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09402300.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09402500.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09403850.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09404115.2012.pdf

http://wdr.water.usgs.gov/wy2012/pdfs/09404200.2012.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09380000.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09381800.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09382000.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09402000.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09402300.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09402500.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09403850.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09404115.2013.pdf

http://wdr.water.usgs.gov/wy2013/pdfs/09404200.2013.pdf

E.2. Completed Publications 

Grams, P.E., Topping, D.J., Schmidt, J.C., Hazel, J.E., Jr., and Kaplinski, M., 2013, Linking 

morphodynamic response with sediment mass balance on the Colorado River in Marble 

Canyon: Issues of scale, geomorphic setting, and sampling design: Journal of Geophysical 

Research: Earth Surface, v. 118, 18p., doi:10.1002/jgrf.20050, 

http://onlinelibrary.wiley.com/doi/10.1002/jgrf.20050/pdf.

Sabol, T.A., and Topping, D.J., 2013, Evaluation of intake efficiencies and associated sedimentconcentration errors in US D-77 bag-type and US D-96-type depth-integrating suspendedsediment samplers: U.S. Geological Survey Scientific Investigations Report 2012–5208, 88 

p., http://dx.doi.org/10.3133/sir20125208, http://pubs.er.usgs.gov/publication/sir20125208

Sabol, T.A., and Springer, A.E., 2013, Transient simulation of groundwater levels within a 

sandbar of the Colorado River, Marble Canyon, Arizona, 2004: U.S. Geological Survey 

Open-File Report 2013-1277, 22 p., http://dx.doi.org/10.3133/ofr20131277

Voichick, N., and Topping, D.J., 2014, Extending the turbidity record: Making additional use of 

continuous data from turbidity, acoustic-Doppler, and laser diffraction instruments, and 

suspended-sediment samples in the Colorado River in Grand Canyon: U.S. Geological 

Survey Scientific Investigations Report 2014-5097, 31 p.

E.3. Publications in progress 

62
Griffiths, R.E., Topping D.J., Anderson R.S., Hancock, G.S., and Melis, T.S., in press, Design of 

a sediment-monitoring gaging network on ephemeral tributaries of the Colorado River in 

Glen, Marble, and Grand Canyons, Arizona: U.S. Geological Survey Open File Report.

Topping, D.J., and Wright, S.A., to be submitted for review during FY2014, Accurate long-term, 

high-resolution acoustic measurements of suspended-silt-and-clay concentration, suspendedsand concentration, and suspended-sand grain size in rivers: Journal of Geophysical 

Research. 

Topping, D.J., Wright, S.A., Griffiths, R.E., Dean, D.J., and Rubin, D.M., to be submitted for 

review during FY2014, Acoustic, laser-diffraction, and pump methods for measuring the 

concentration and grain-size distribution of suspended sediment in rivers at high temporal 

resolution over multi-year timescales: Theory, calibration, and error: either a U.S. Geological 

Survey Professional Paper or an American Geophysical Union Monograph.

E.4. Presentations at GCDAMP meetings 

Episodic updates made to TWG and AMWG on the state of sediment and QW in the CRE; more 

frequent updates on the trigger status provided leading up to the November 2012 and 2013 HFEs.

E.5. Presentations at professional meetings 

Grams, P.E., Schmidt, J.C., Topping, D.J., and Yackulic, C.B., 2012, Error and Uncertainty in 

High-resolution Quantitative Sediment Budgets: EOS, Transactions, American Geophysical 

Union.

Topping, D.J., Griffiths, R.E., Dean, D.J., Wright, S.A., Rubin, D.M., Garner, B.D., Sibley, 

D.M., and Reinke, T.A., 2013, Accurate sediment budgets in rivers require high-resolution 

discharge-independent measurements of suspended-sediment concentration: EOS, 

Transactions, American Geophysical Union.

Griffiths, R.E., and Topping, D.J, 2013, Measurements of sediments loads in small, ungaged, 

basins may be required to accurately close sediment budgets: An example from a monitoring 

network on the southern Colorado Plateau: EOS, Transactions, American Geophysical 

Union.

Grams, P.E., Buscombe, D., Hazel, J.E., Kaplinski, M.A., and Topping, D.J, 2013, 

Reconciliation of Flux-based and Morphologic-based Sediment Budgets: EOS, Transactions, 

American Geophysical Union.

Jain, S., Melis, T.S., Topping, D.J, Pulwarty, R.S., and Eischeid, J., 2013, Warm Season Storms, 

Floods, and Tributary Sand Inputs below Glen Canyon Dam: Investigating Salience to 

Adaptive Management in the Context of a 10-Year Long Controlled Flooding Experiment in 

Grand Canyon National Park, AZ, USA: EOS, Transactions, American Geophysical Union.

F. References 

Gloss, S.P., and Coggins, L.G., 2005, Fishes of Grand Canyon, in Gloss, S.P., Lovich, J.E., and 

Melis, T.S., eds., The state of the Colorado River ecosystem in Grand Canyon: U.S. 

Geological Survey Circular 1282, p. 33-68.

Griffiths, R.E., Topping, D.J., McDonald, R.R., and Sabol, T.A., 2010, The use of the multidimensional surface-water modeling system (MD_SWMS) in calculating discharge and 

sediment transport in remote ephemeral streams: Proceedings of the Joint Federal 

Interagency Conference on Sedimentation and Hydrologic Modeling, June 27- July 1, 2010, 

Riviera Hotel, Las Vegas, Nevada, 

http://acwi.gov/sos/pubs/2ndJFIC/Contents/P40_Griffiths_paper.pdf. 

63
Griffiths, R.E., Topping, D.J., Andrews, Timothy, Bennett, G.E., Sabol, T.A., and Melis, T.S., 

2012, Design and maintenance of a network for collecting high-resolution suspendedsediment data at remote locations on rivers, with examples from the Colorado River: U.S. 

Geological Survey Techniques and Methods, book 8, chapter C2, 44 p., 

http://pubs.usgs.gov/tm/tm8c2/.

Hazel, J., Jr., Topping, D.J., Schmidt, J.C., and Kaplinski, M., 2006, Influence of a dam on finesediment storage in a canyon river: Journal of Geophysical Research, v. 111, F01025, 16 p.

Howard, C.S., 1947, Suspended sediment in the Colorado River 1925-41: U.S. Geological 

Survey Water-Supply Paper 998, 165 p.

Melis, T.S., Topping, D.J., and Rubin D.M., 2003, Testing laser-based sensors for continuous in 

situ monitoring of suspended sediment in the Colorado River, Arizona, in Bogen, J., Fergus, 

T., and Walling, D.E., eds., Erosion and Sediment Transport Measurement in Rivers: 

Technological and Methodological Advances: Wallingford, Oxfordshire, United Kingdom, 

IAHS Press, IAHS Publication 283, p. 21-27.

National Research Council, 1996, River Resource Management in the Grand Canyon: 

Washington, D.C., National Academy Press, 226 p.

Rubin, D.M., and Topping, D.J., 2001a, Quantifying the relative importance of flow regulation 

and grain-size regulation of suspended-sediment transport (α), and tracking changes in bedsediment grain size (β): Water Resources Research, v. 37, p. 133-146. 

Rubin, D.M., and Topping, D.J., 2001b, What regulates suspended-sediment transport in a given 

setting? Grain size of bed sediment or flow: Proceedings of the 7th Inter-Agency 

Sedimentation Conference, v. 1, p. I-199 through I-205. 

Rubin, D.M., Tate, G.M., Topping, D.J., and Anima, R.A., 2001, Use of rotating side-scan sonar 

to measure bedload: Proceedings of the 7th Inter-Agency Sedimentation Conference, v. 1, 

p. III-139 through III-143.

Rubin, D.M., Topping, D.J., Schmidt, J.C., Hazel, J., Kaplinski, K., and Melis, T.S., 2002, 

Recent sediment studies refute Glen Canyon Dam hypothesis: EOS, Transactions, American 

Geophysical Union, v. 83, n. 25, p. 273, 277-278. 

Rubin, D.M., and Topping, D.J., 2008, Correction to “Quantifying the relative importance of 

flow regulation and grain-size regulation of suspended-sediment transport α, and tracking 

changes in bed-sediment grain size β”: Water Resources Research, v. 44, W09701, 5 p., doi: 

10.1029/2008WR006819.

Sabol, T.A., and Topping, D.J., 2013, Evaluation of intake efficiencies and associated sedimentconcentration errors in US D-77 bag-type and US D-96-type depth-integrating suspendedsediment samplers: U.S. Geological Survey Scientific Investigations Report 2012–5208, 88 

p., http://dx.doi.org/10.3133/sir20125208, http://pubs.er.usgs.gov/publication/sir20125208.

Topping, D.J., Rubin, D.M., and Vierra, Jr., L.E., 2000a, Colorado River sediment transport 1. 

Natural sediment supply limitation and the influence of Glen Canyon Dam: Water Resources 

Research, v. 36, p.515-542. 

Topping, D.J., Rubin, D.M., Nelson, J.M., Kinzel, III, P.J., and Corson, I.C., 2000b, Colorado 

River sediment transport 2. Systematic bed-elevation and grain-size effects of sand supply 

limitation: Water Resources Research, v. 36, p. 543-570.

Topping, D.J., J.C. Schmidt, and L.E. Vierra, Jr., 2003, Computation and Analysis of the 

Instantaneous-Discharge Record for the Colorado River at Lees Ferry, Arizona—May 8, 

1921, through September 30, 2000: U.S. Geological Survey Professional Paper 1677, 118 p.

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Topping, D.J., Melis, T.S., Rubin, D.M., and Wright, S.A., 2004, High-resolution monitoring of 

suspended-sediment concentration and grain size in the Colorado River in Grand Canyon 

using a laser-acoustic system, in Hu, C., and Tan, Y, eds., Proceedings of the Ninth 

International Symposium on River Sedimentation, October 18-21, 2004, Yichang, China: 

People’s Republic of China, Tsinghua University Press, p. 2507-2514.

Topping, D., Rubin, D., and Melis, T., 2005a, Coupled changes in sand grain size and sand 

transport driven by changes in the upstream supply of sand in the Colorado River, in

Flemming, B.W., Hartmann, D., and Delafontaine, M.T., eds., From Particle Size to 

Sediment Dynamics International Workshop, Hanse Institute for Advanced Study, 

Delmenhorst (Germany), April 15-18, 2004: Research Centre Terramare Reports, No. 13, p. 

153-158.

Topping, D.J., Rubin, D.M., and Schmidt, J.C., 2005b, Regulation of sand transport in the 

Colorado River by changes in the surface grain size of eddy sandbars over multi-year 

timescales: Sedimentology, v.52, p. 1133-1153.

Topping, D.J., Wright, S.A., Melis, T.S., and Rubin, D.M., 2006a, High-resolution monitoring of 

suspended-sediment concentration and grain size in the Colorado River using laserdiffraction instruments and a three-frequency acoustic system: CD-ROM Proceedings of the 

8th Federal Inter-Agency Sedimentation Conference, Reno, Nevada, April 2-6, 2006, ISBN 0-

9779007-1-1.

Topping, D.J., Rubin, D.M., Schmidt, J.C., Hazel, J.E., Jr., Melis, T.S., Wright, S.A., Kaplinski, 

M., Draut, A.E., and Breedlove, M.J., 2006b, Comparison of sediment-transport and barresponse results from the 1996 and 2004 controlled-flood experiments on the Colorado River 

in Grand Canyon: CD-ROM Proceedings of the 8th Federal Inter-Agency Sedimentation 

Conference, Reno, Nevada, April 2-6, 2006, ISBN 0-9779007-1-1.

Topping, D.J., Rubin, D.M., and Melis, T.S., 2007a, Coupled changes in sand grain size and sand 

transport driven by changes in the upstream supply of sand in the Colorado River: Relative 

importance of changes in bed-sand grain size and bed-sand area: Sedimentary Geology, 24 p., 

doi: 10.1016/j.sedgeo.2007.03.016.

Topping, D.J., Wright, S.A., Melis, T.S., and Rubin, D.M., 2007b, High-resolution 

measurements of suspended-sediment concentration and grain size in the Colorado River in 

Grand Canyon using a multi-frequency acoustic system: Proceedings of the Tenth 

International Symposium on River Sedimentation, August 1-4, 2007, Moscow, Russia, v. 3, 

p. 330-339.

Topping, D.J., Rubin, D.M., and Schmidt, J.C., 2008, Update on regulation of sand transport in 

the Colorado River by changes in the surface grain size of eddy sandbars over multiyear 

timescales: U.S. Geological Survey Scientific Investigations Report 2008–5042, 24 p.

Topping, D.J., Rubin, D.M., Grams, P.E., Griffiths, R.E., Sabol, T.A., Voichick, N., Tusso, R.B., 

Vanaman, K.M., and McDonald, R.R., 2010, Sediment transport during three controlledflood experiments on the Colorado River downstream from Glen Canyon Dam, with 

implications for eddy-sandbar deposition in Grand Canyon National Park: U.S. Geological 

Survey Open-File Report 2010-1128, 111 p. 

Topping, D.J., Rubin, D.M., Wright, S.A., and Melis, T.S., 2011, Field evaluation of the error 

arising from inadequate time averaging in the standard use of depth-integrating suspendedsediment samplers: U.S. Geological Survey Professional Paper 1774, 95 p., 

http://pubs.usgs.gov/pp/1774/.

65
U.S. Department of the Interior, 1995, Operation of Glen Canyon Dam Final Environmental 

Impact Statement, Bureau of Reclamation, Upper Colorado Region, Salt Lake City, 337 p. 

plus appendices. 

U.S. Department of the Interior, 2011, Environmental Assessment: Development and 

Implementation of a Protocol for High-Flow Experimental Releases from Glen Canyon Dam, 

Arizona, 2011 through 2020, Bureau of Reclamation, Upper Colorado Region, Salt Lake 

City, 496 p.

Voichick, N., and Topping, D.J., 2010, Comparison of turbidity to multi-frequency sideways 

looking acoustic-Doppler data and suspended-sediment data in the Colorado River in Grand 

Canyon: Proceedings of the Joint Federal Interagency Conference on Sedimentation and 

Hydrologic Modeling, June 27- July 1, 2010, Riviera Hotel, Las Vegas, Nevada, 

http://acwi.gov/sos/pubs/2ndJFIC/Contents/P34_Voichick_FISC_Paper.pdf.

Wright, S.A., Melis, T.S., Topping, D.J., and Rubin, D.M., 2005, Influence of Glen Canyon Dam 

operations on downstream sand resources of the Colorado River in Grand Canyon, in Gloss, 

S.P., Lovich, J.E., and Melis, T.S., eds., The state of the Colorado River ecosystem in Grand 

Canyon: U.S. Geological Survey Circular 1282, p. 17-31. 

Wright, S.A., Schmidt, J.C., Melis, T.S., Topping, D.J., and Rubin, D.M., 2008, Is there enough 

sand? Evaluating the fate of Grand Canyon sandbars: GSA Today, v. 18, no. 8, p. 4-10, doi: 

10.1130/GSATG12A.1

Wright, S.A., Topping, D.J., Rubin, D.M., and Melis, T.S., 2010a, An approach for modeling 

sediment budgets in supply-limited rivers: Water Resources Research, v. 46, W10538, 18 p., 

doi:10.1029/2009WR008600. 

Wright, S.A., Topping, D.J., Rubin, D.M., and Melis, T.S., 2010b, Modeling long-term sediment 

budgets in supply-limited rivers: Proceedings of the Joint Federal Interagency Conference 

on Sedimentation and Hydrologic Modeling, June 27- July 1, 2010, Riviera Hotel, Las 

Vegas, Nevada, 

http://acwi.gov/sos/pubs/2ndJFIC/Contents/3B_Wright_12_29_09_paper.pdf. 

Wright, S.A., Topping, D.J., and Williams, C.A., 2010c, Discriminating silt-and-clay from 

suspended-sand in rivers using sidelooking acoustic profilers: Proceedings of the Joint 

Federal Interagency Conference on Sedimentation and Hydrologic Modeling, June 27- July 

1, 2010, Riviera Hotel, Las Vegas, Nevada, 

http://acwi.gov/sos/pubs/2ndJFIC/Contents/2C_Wright_03_01_10_paper.pdf.

 

66
G. Budget 

 

Project 2 Project 2

Salaries $ 619,000.00 Salaries $ 659,000.00 

Traveling and Training $ 5,000.00 Traveling and Training $ 5,000.00 

Operating Expenses $ 50,000.00 Operating Expenses $ 52,000.00 

Logistics $ 70,000.00 Logistics $ 72,000.00 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - 

USGS Cooperators $ 480,000.00 USGS Cooperators $ 496,000.00 

USGS Burden $ 119,000.00 USGS Burden $ 173,000.00 

Total $ 1,343,000.00 Total $ 1,457,000.00 

FY 2015 Project 2 Gross Totals: $1,343,000

FY 2016

FY 2016 Project 2 Gross Totals: $1,457,000

FY 2015

Project 2

Salaries $ 671,000.00 

Traveling and Training $ 5,000.00 

Operating Expenses $ 53,000.00 

Logistics $ 74,000.00 

Cooperators (non-USGS) $ - 

USGS Cooperators $ 512,000.00 

USGS Burden $ 225,000.00 

Total $ 1,540,000.00 

FY 2017 Project 2 Gross Totals: $1,540,000

FY 2017 

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Project 3. Sandbars and Sediment Storage Dynamics: 

Long-term Monitoring and Research at the Site, Reach, 

and Ecosystem Scales. 

A. Investigators 

Paul Grams, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Daniel Buscombe, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Erich Mueller, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Joel Sankey, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Joseph Wheaton, Assistant Professor, Utah State University

Brandon McElroy, Assistant Professor, University of Wyoming

Mark Schmeeckle, Professor, Arizona State University

Joseph E. Hazel, Jr., Research Associate, Northern Arizona University

Matt Kaplinski, Research Associate, Northern Arizona University 

Keith Kohl, Surveyor, U.S. Geological Survey, Grand Canyon Monitoring and Research Center

Robert Tusso, Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

Robert Ross, Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

David Topping, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Ted Melis, Physical Scientist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

Mike Yard, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

David Rubin, Research Professor, University of California at Santa Cruz 

David Varyu, Hydraulic Engineer, Bureau of Reclamation, Technical Service Center

B. Project Summary 

This project consists of a set of integrated studies that (a) track the effects of individual HighFlow Experiments (HFEs, or “controlled floods”) on sandbars and within-channel sediment 

storage, (b) monitor the cumulative effect of successive HFEs and intervening operations, and (c) 

advance general understanding of sediment transport and eddy sandbar dynamics. While the first 

two efforts are focused on monitoring, the latter effort is focused on improving capacity to 

predict the effects of dam operations, because management of the Colorado River downstream 

from Glen Canyon Dam requires that managers balance the objective to achieve fine-sediment 

conservation with other management objectives. Such balancing of objectives requires 

comparing predicted outcomes of different dam operation scenarios, such as has been pursued in 

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the Long-Term Experimental and Management Plan (LTEMP) Environmental Impact Statement 

(EIS) process.

The effort to achieve fine-sediment conservation in the Colorado River ecosystem in Marble 

and Grand Canyons (CRe) is greatly constrained by the limited annual supply of fine sediments 

to the Colorado River from ephemeral tributaries. The challenge of rehabilitating sandbars when 

most of the fine-sediment once supplied to the CRe is now stored in Lake Powell reservoir has 

been described in many scientific articles and management documents. More than a decade of 

monitoring and research has demonstrated that eddy sandbars accumulate sand, as well as small 

amounts of clay and silt (hereafter referred to as mud), during short periods of relatively high 

flow, but these same sandbars typically erode during flows that occur in the months to years 

between the high flows requisite for sandbar building. Adoption of the HFE Protocol in 2012 

established a formal procedure whereby seasonal sand and mud (together referred to as fine 

sediment) inflows are measured, and high flows are released from Glen Canyon Dam with the 

purpose of redistributing that sand and mud from the channel bed to eddies. The long-term effect 

of the HFE Protocol depends on the relative “gain” to eddy sandbars that occurs during the short 

controlled floods and the intervening “loss” that occurs during other times. The Environmental 

Assessment for Development and Implementation of a Protocol for High-Flow Experimental 

Releases from Glen Canyon Dam (hereafter referred to as the HFE Protocol EA) asked, "Can 

sandbar building during HFEs exceed sandbar erosion during periods between HFEs, such that 

sandbar size can be increased and maintained over several years?" In other words, does the 

volume of sand aggraded into eddies and onto sandbars during controlled floods exceed the 

volume eroded from sandbars during intervening dam operations?

Thus, one of the most important objectives of this project is to monitor the changes in 

sandbars over many years, including a period that contains several controlled floods, in order to 

compile the information required to answer the fundamental question of the HFE Protocol EA. 

The monitoring program described here continues the program implemented in the FY13–14 

Biennial Work Plan and is based on annual measurements of sandbars, using conventional 

topographic surveys supplemented with daily measurements of sandbar change using ‘remote 

cameras’ that autonomously and repeatedly take photographs. Because these long-term 

monitoring sites represent only a small proportion of the total number of sandbars in Marble and 

Grand Canyons, this project also includes (1) the analysis of a much larger sample of sandbars, 

using airborne remote-sensing data of the entire CRe collected every 4 years, and (2) periodic 

measurements of nearly all sandbars within individual 50 to 130 km river segments.

Most of the fine-sediment involved in building sandbars is sand. Therefore, we focus on that 

component of the sediment load. HFEs build sandbars by redistributing sand from the lowelevation portion of the channel to sandbars in eddies and on the banks. The sand available for 

bar building is the sand that is in storage within the channel: the sum of the sand contributed by 

the most recent tributary inputs, all the sand that has accumulated during the decades since Glen 

Canyon Dam was completed, and any sand that remains from the pre-dam era. The goal of the 

protocol is to accomplish sandbar building by mobilizing only as much sand as is most recently 

contributed by the Paria River. Some of the mobilized sand is deposited in eddies where it 

maintains and builds eddy sandbars. Some of the sand is eventually transported downstream to 

Lake Mead reservoir. The most efficient floods for the purposes of sandbar building are those 

that maximize eddy sandbar aggradation yet minimize the amount of sand transported far 

downstream, thus minimizing losses to sand storage. Dam operations between HFEs also 

transport sand downstream, causing decreases in sand storage. If sand storage is maintained or 

69
increased, scientists expect the response to future HFEs to be similar to or better than that 

observed following recent HFEs. If, however, sand storage declines, scientists expect that future 

HFEs will result in the building of fewer and/or smaller sandbars. 

Thus, one of the critical pieces of information that will be needed to evaluate the outcome of 

the HFE protocol and the LTEMP will be the change in sand storage over the periods covered by 

the respective management actions. The total amount of sand in storage is not known, because 

measurements of fine-sediment thickness are very difficult to make, localized in nature and 

difficult to scale up. Changes in sand storage, however, can be determined by repeat 

measurements of the topography of the river bed and banks. This project, therefore, includes 

continued large-scale mapping of long river segments to track changes in sand storage. These 

data will allow more accurate comparisons of the seasonal amount of sand accumulation in 

relation to the total amount of sand stored in different segments of the CRe.

This project also includes three research and development components: (1) improving 

methods for making sandbar surveys rapidly and at low cost; (2) investigating bedload sand 

transport; and (3) developing of a new large-scale sandbar deposition/erosion model. These 

projects are, respectively, designed to improve monitoring methods, improve estimates of sand 

transport, and develop new tools for predicting how management actions including HFEs and 

daily dam operations affect resources. 

C. Background

The many sediment-related goals and objectives of the Glen Canyon Dam Adaptive 

Management Program (GCDAMP), summarized below in section C.2, may be distilled down to 

one overarching question: “what actions will create and maintain fine-sediment resources in the 

best condition possible within the constraints of a limited fine-sediment supply.” Answering this 

question requires making many linkages between sediment storage and ecosystem goals 

including: maintenance of sandbars used by recreationists, creation of sandbar-associated 

backwater habitats used by native fish, and maintenance of exposed bare sand surfaces that 

supply sand for redistribution to upland areas by wind. Research and monitoring supporting these 

objectives also provides knowledge about the relative proportions and spatial distributions of fine 

and coarse sediment on the bed of the river, because those characteristics control transport of 

suspended sediment and affect primary production and aquatic habitats. Because many of these 

objectives concern sandbars, the focus of this project is on the sand-size component of sediment. 

We use the term “sediment” to refer to alluvium of all sizes, “fine sediment” to refer to sand, silt, 

and clay (all sediment < 2 mm), and “sand” to refer to sand-sized sediment only (0.0625 – 2 

mm). This project addresses these objectives through monitoring components designed to track 

the trends in sandbars and fine-sediment storage, and research components designed to improve 

understanding of processes that affect fine-sediment-related resources.

Fine-sediment deficit and changes in flow regime brought about by completion of Glen 

Canyon Dam have resulted in a decline in the number and size of sandbars in Grand Canyon 

National Park (Schmidt and others, 2004; Wright and others, 2005). Sandbars are used as 

camping beaches, form aquatic habitat, and are a source of aeolian sand for the upland 

ecosystem. Schmidt and others (2004) estimated that there has been about a 25 percent decrease 

in the area of exposed sandbars in Marble Canyon and eastern Grand Canyon based on 

comparison of pre-dam and post-dam aerial photographs. Monitoring of sandbars between 1990 

and 2013 has shown that controlled floods cause widespread increases in the size of sandbars 

exposed above a given reference stage and that these bars decrease in size between controlled 

70
floods (Schmidt and others, 1999; Hazel and others, 1999; Topping and others, 2006; Hazel and 

others, 2010; Schmidt and Grams, 2011). These findings demonstrate that fine sediment supplied 

by tributaries can be redistributed by high flows from the bed of the river to higher elevations in 

eddies and along the channel margins. Although we currently have very limited knowledge of 

the absolute amount of fine sediment stored on the bed of the river, we do know that the 

difference between fine-sediment supply and fine-sediment export is positive in some time 

periods and negative in other time periods. Thus, it remains unknown whether the net long-term 

effect of dam operations, including controlled floods, will result in a stable fine-sediment budget 

or will progressively mine fine sediment from storage (Fig. 1). A quasi-stable sediment budget 

would indicate that controlled floods will continue to be an effective tool for building sandbars, 

while a downward trending sediment budget would indicate a decreasing capacity to rebuild 

sandbars using floods alone (Rubin and others, 2002; Wright and others, 2008; Schmidt and 

Grams, 2011).

Figure 1. Conceptual diagram illustrating the dependency of net sandbar size on potential variations in the amount of 

deposition that occurs during a High-Flow Experiment (HFE), the frequency of HFEs, and the rate of post-HFE erosion 

(figured adapted from Schmidt and Grams, 2011). The case shown in 1 shows a hypothetical amount of HFE deposition 

followed by an equal amount of erosion. Cases two and three result in net increases in sandbar size by increasing the amount 

of deposition during HFEs and increasing the frequency of HFEs, respectively. In case 4, the rate of erosion following HFEs 

is greater than the HFE deposit such that there are net decreases in sandbar size. 

C.1. Scientific Background 

Closure of Glen Canyon Dam has resulted in at least a 90 percent reduction in fine-sediment 

supply to the Colorado River in Marble and Grand Canyons (Topping and others, 2000) and a 

dam-controlled hydrograph that is dramatically different than the natural hydrograph (Topping 

and others, 2002). These changes caused deep scour and armoring of the river bed in the segment 

between the dam and Lees Ferry, 25-km downstream from the dam (Pemberton, 1976; Williams 

and Wolman, 1984; Grams and others, 2007). Scour was widespread in this segment because the 

71
river bed was dominated by sand when the dam was completed. Downstream from Lees Ferry, in 

Marble and Grand Canyons, inputs of large cobbles and boulders from tributaries change the 

nature of the river and the style of response to sediment deficit and flow regulation (Grams and 

others, 2007). The areas of the bed covered by coarse sediment (boulders) have been stable, 

whereas the areas of the bed covered by fine sediment have been subject to net sediment 

evacuation. One result of the fine-sediment evacuation has been a decrease in the size of eddy 

sandbars in Marble Canyon and the upstream part of Grand Canyon (Schmidt and others, 2004). 

In addition, the many studies conducted on sandbars since the 1970s have shown that (1) 

post-dam floods (unplanned spills and controlled high-flow experiments) cause widespread 

increases in sandbar size (Hazel and others, 2010; Schmidt and Grams, 2011); (2) regular dam 

operations (hydropeaking) result in sandbar erosion following floods (Grams and others, 2010; 

Schmidt and Grams, 2011); and (3) during any time interval, there is a large variability in the 

magnitude of sandbar response on aggregate (Hazel and others, 1999; Hazel and others, 2010). 

Two of the most important findings are that the supply of sand available to build sandbars is 

limited (Topping and others, 2000) and that floods that build some sandbars may do so at the 

expense of erosion of sand from other sandbars and eddies (Schmidt, 1999). 

Sandbar monitoring in the FY13–14 work plan included annual monitoring of long-term 

monitoring sites and evaluation of sandbars throughout the CRe from remote sensing. Results 

from the annual sandbar monitoring (Project Element 3.1.1) show that while sandbars at the 

long-term monitoring sites were relatively small before the November 2012 HFE, sandbars at 

these sites were relatively large in October 2013, 10 months following the 2012 HFE (Fig. 2). 

Analysis of images collected from remote cameras at the same long-term monitoring sites show 

that the November 2013 HFE also resulted in net sandbar deposition. These data indicate that 

HFEs have resulted in net increases in sandbar size in Grand Canyon (downstream from river 

mile 62) since the period of initial monitoring in the early 1990s. In Marble Canyon, HFEs cause 

relatively short-term increases in sandbar size, and sandbars remain similar in size or smaller 

than in the early 1990s.

Figure 2. Sandbar size from 1990 to October 2013 (preliminary data provided by Joseph E. Hazel, Jr.).

72
Evaluation of the remote sensing images (Ross and Grams, in preparation) provides a 

somewhat longer-term perspective (going back to 1984) on the effect of HFEs on sandbars in 

Marble Canyon (Project Element 3.1.2). These results show that the area of sandbars exposed 

above the 8,000 ft3/s stage in Marble Canyon was generally larger during the era of post-dam 

controlled floods (April 1996, May 2002, May 2005, and May 2009) compared with the postdam period before controlled floods (June 1990 and March 1996). Hazel and others (in 

preparation) are developing a more detailed comparison of sandbar sizes following recent HFEs 

to those following the 1983 and 1984 floods (see Project 3.1.4 for summary of these results).

Sandbars are a component of the total sediment budget for the Colorado River. The sediment 

budget, or sediment mass balance, is simply the accounting by mass (or volume) of all sediment 

entering and exiting a specified river segment. This budget may be expressed symbolically as, 

for a designated segment:

I − O = ∆S, (1)

which states that the sum of all sediment inputs, I, minus the sum of all outputs, O, is equal to the 

net change in the magnitude of sediment storage, ∆S. In the case that inputs exceed outputs, ∆S

is positive indicating sediment accumulation. To provide greater resolution and the opportunity 

to monitor different mechanisms and resources, the sand storage can be divided into sand stored 

in lower elevations, that are typically underwater, and sand stored in higher elevations that are 

only inundated occasionally,

∆S = ∆Slow + ∆Shigh. 

(2)

These storage components could be further subdivided based on other criteria such as whether 

the sediment is within eddies or the main channel.

We use “low” to refer to fine-sediment deposits below the stage associated with the 8,000 

ft3

/s discharge and “high” to refer to fine-sediment deposits above the 8,000 ft3/s stage. The lowelevation deposits are underwater except during the trough of some flow fluctuations, and consist 

of the lower parts of sandbars and patches of sand on the river bed. These low-elevation deposits 

are relevant to aquatic habitat and, in the case of sandbars in eddies, they underlie the highelevation sediment. The high-elevation fine-sediment deposits are alternately inundated and 

exposed, depending on the flow regime. These deposits are the high-elevation parts of sandbars

and are most relevant to camping beaches, riparian vegetation, and other upland resources. 

Low- and high-elevation sediment are coupled through processes of erosion and deposition 

by streamflow, erosion and deposition by wind, and mass failure of high-elevation deposits. This 

coupling means that changes in ∆S will affect both low- and high-elevation sediment. Therefore, 

predictions about the long-term fate of sandbars must be based on understanding and, by 

extension, the ability to predict, the long-term trend in ∆S. For these reasons, all sandbar research 

and monitoring is designed around this concept of the sediment budget.

Measurements of suspended sediment were initiated in 1999 to measure sediment inputs and 

outputs for each segment between measurement stations, i.e. the sediment budgeting reaches1

(Fig. 3). The measurements of inputs and outputs (I and O in equation 1) made in this ongoing 

program (see Project 2: Streamflow, Sediment Transport, and Water Quality) are used to 

1 In this proposal, we refer to observations and study areas that span a variety of spatial scales. We use “monitoring 

site” to refer to monitoring locations that are at the scale of individual sandbars, 100’s of meters in length. We use 

“short reach” to refer to study reaches that include many sites and are on the order of 2 to 5 km in length. We use 

“long reach” or “sediment budgeting reach” to refer to segments of the river that encompass the entire channel 

between fine-sediment monitoring gages; these reaches are 50 to 130 km in length. 

73

 
calculate ∆S. This tracks the accumulation and downstream dispersal of tributary inputs, 

providing the information that is needed to schedule HFEs to occur following the accumulation 

of sufficient inputs in the channel. These measurements only allow calculation of ∆S as a single 

value for long river segments and it is not possible to determine where within the sedimentbudget reach the sand storage significantly changed, and whether these sand storage changes 

were associated with changes in bed-sediment grain size, which is important for assessing the 

mobility of the sand and hence the propensity for it to transport to eddies and channel margins. 

Nor is it possible to determine ∆Slow and ∆Shigh individually. Measurements of the sediment 

deposits themselves are necessary to link changes in total storage with changes in sandbars. 

Between 2000 and 2004, changes in storage were evaluated in short (2- to 5 km long) reaches 

by repeatedly measuring submerged river bed elevations using sonar and exposed deposits using 

airborne LiDAR, aerial photogrammetry, and conventional topographic surveys. Eleven short 

reaches were selected, although repeat measurements were only made at seven of these reaches 

between river mile (RM) 0 and RM 87 (Fig. 3). The methods are described by Hazel and others 

(2008) and Kaplinski and others (2009; 2014). This monitoring program was a substantial 

advancement beyond earlier monitoring programs, because nearly all of the channel in each short 

reach was mapped, in contrast to previous efforts which made measurements at widely-spaced 

cross-sections or isolated sandbars.

Figure 3. Map showing the Colorado River between Glen Canyon Dam and Diamond Creek. The stations for suspended 

sediment transport monitoring (Project 2: Streamflow, Sediment Transport, and Water Quality) are shown by the red circles. 

The short reaches where sediment storage was mapped between 2000 and 2004 are shown by the green ovals. Based on 

analysis of these data, the current sediment storage monitoring plan calls for mapping 50 to 80 percent of the channel in the

segments between the sediment monitoring stations. In 2009 and 2012, most of the long sediment budgeting reach between 

RM 30 and RM 61 was mapped. In 2011 and 2014, most of the sediment budgeting reach between RM 61 and RM 87 was 

mapped. In 2013, most of the sediment budgeting reach between RM 0 and RM 30 was mapped.

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Results from this monitoring program demonstrated that 90 percent or more of the fine 

sediment in the modern river is stored in low-elevation locations (Hazel and others, 2006). Thus, 

the fine sediment that is generally of greatest management interest comprises only up to 10 

percent of the fine sediment in the system. This study also demonstrated that change in lowelevation sediment storage computed from repeat measurements of erosion and deposition in 

short (<5 km) reaches is not consistent with the change in storage computed from the difference 

in sediment transport over longer sediment budgeting reaches (Topping and others, 2006; Grams 

and others, 2011; Grams and others, 2013). In other words, extrapolating ∆S measured over short 

reaches to the longer reaches is not comparable with the computation of ∆S from equation (1). 

This discrepancy stems from extrapolation of measurements from the short reaches to longer 

reaches, rather than an inability to measure changes with sufficient precision. 

Extrapolation fails for at least two major reasons: (1) changes in storage are highly localized 

and (2) changes in storage are highly spatially variable. Schmidt and others (2004) showed that 

large changes in sediment storage are concentrated in eddies and in pools in the portions of 

channel adjacent to eddies. In addition, nearby eddy/channel storage locations in the same short 

reach do not necessarily behave consistently—scour in one eddy may be offset by an equal or 

larger magnitude of deposition in the next eddy. Finally, the magnitude of change in storage in 

these isolated pools can be large relative to the net change over a long reach. The net ∆S over a 

long reach is the sum of many component ∆S terms from individual pools, some positive, some 

negative, and nearly all of them large relative to the total sum. Thus, without better knowledge of 

the spatial distribution and size of these storage locations, and their variability in response to 

varying flows, it is not possible to extrapolate measurements from the short reaches to longer 

reaches (Grams and others, 2013). These findings have indicated that in order to determine 

whether sediment storage as a whole – at low and high elevations and in the channel and eddy 

storage environments – is increasing, decreasing, or stable, requires repeat measurements of sand 

storage throughout the long sediment budgeting reaches. The proposed fine-sediment monitoring 

includes measurements of channel and eddy sand storage at the scale of the long sediment 

budgeting reaches.

This long-reach monitoring program (also known as the “channel mapping” project) was 

initiated in 2009 with the mapping of lower Marble Canyon. This was followed with the 

mapping of eastern Grand Canyon in 2011, a repeat map of lower Marble Canyon in 2012, 

mapping upper Marble Canyon in 2013, and a repeat map of eastern Grand Canyon in 2014 (Fig. 

3.3). Each effort was comprised of mapping the river bed with multibeam and singlebeam sonar, 

mapping the exposed sand deposits with conventional survey equipment, and measurements of 

bed-sand grain size. Final products are high-resolution (1 m2 grid size) digital elevation models 

(DEMs) of the mapped segment. Preliminary results from the repeat mapping of lower Marble 

Canyon in 2012 depict changes in sediment storage throughout this 50 km river segment. During 

this period (2009 – 2012) the sediment budget calculated from measurements of suspended sand 

transport (Project 2) was significantly negative as a result of the high dam releases that occurred 

in 2011 (Fig. 4). The repeat measurements of the channel also show net erosion during this 

period. The magnitude of erosion measured by channel mapping is less than indicated by the 

measurements of sediment transport, but the agreement between the two methods is well within 

the respective ranges of uncertainty (Fig. 4). Because both methods have large uncertainty, the 

comparison shown in Figure 4 provides a valuable verification of both sets of measurements 

without which, scientists would have less confidence in the results of either method. For this 3-

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year time period, both methods have similar uncertainty. While the uncertainty associated with 

the budget computed from measurements of sand transport increases with the length of time over 

which the computations are made (Fig. 4), the uncertainty associated with the budget calculated 

from the repeat channel mapping would be approximately the same for any time period. Thus if 

one is interested in the net change in sediment storage for a ~20-year interval, the uncertainty 

associated with the budget computed from measurements of transport may span more than 4 

million metric tons (~8 years of Paria sand inputs), while the uncertainty associated with repeat 

topographic measurements will still be about 600,000 metric tons (~1 year of Paria River sand 

inputs). Over the period of long-term management actions, only the repeat measurements of the 

channel will therefore be able to attach significance to estimates of storage change (i.e. with an 

uncertainty that is less than the estimate of the magnitude of storage change).

Figure 4. Sand budget for May 1, 2009 to April 30, 2014 for lower Marble Canyon (upper plot) and discharge of the 

Colorado River at the downstream end of the segment for the same period (lower plot). The sand budget computed by the 

difference in sand transport at the upstream and downstream ends of the reach is shown by the solid line with the shaded 

region indicating the uncertainty. Each point on the line is the sand budget for the time period between the start date and the 

date indicated on the horizontal axis. The uncertainty associated with each measurement contributes to the total uncertainty 

and increases quasi-linearly with time. The morphologic sand budget for the same reach computed by the measurements of 

deposits in the channel in 2009 and 2012 is shown by the filled circle with error bars, shown at the time at which the repeat

measurements were made (May 2012).

The channel mapping data also include much more information about the changes in the 

magnitude of sediment storage (Fig. 5). These data show net erosion of sandbars (∆Shigh) in 

Lower Marble Canyon between May 2009 and May 2012. The low-elevation component of the 

budget (∆Slow) was comprised of net erosion in the channel and net deposition in eddies. These 

results confirm that in the conditions of sediment evacuation, the eddies remain efficient traps for 

fine sediment.

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Figure 5. Change in sediment storage between May 2009 and May 2012 for lower Marble Canyon computed by comparing 

the maps (DEMs) of the channel made in those two years. Each marker represents a surveyed pool. Note the different 

vertical scales. In this period with a net decrease in sediment storage (Fig. 4), the eddies exhibited a small net increase in 

storage while the bars and the channel both lost sediment. The largest changes occurred in the channel and were 

concentrated in relatively few pools.

The spatial variability of change in fine-sediment storage (Fig. 5), and the variability 

observed in the monitoring of individual sandbars, are related. Grams and others (2013) showed 

how the volume of sand at many of the individual long-term sandbar monitoring sites is 

correlated with river discharge during the preceding month. At some sites this correlation is 

negative, at others it is positive, and some sites show no significant relationship (see Fig. 11 in 

Project Element 3.3). This means that, for a given flow regime and sediment supply condition, 

there is a fundamental difference in sandbar response due to other factors that influence local 

flow hydraulics and sediment transport processes. This insight was only made possible, because 

we now have a long monitoring record at more than 30 individual sandbars that can be compared 

with flow record. 

In the FY13–14 work plan, we initiated work to investigate the variability of sandbar 

response in order to better understand the degree to which the changes observed at long-term 

77
sandbar monitoring sites are representative of changes throughout the CRe. In lower Marble 

Canyon, where we have the repeat channel mapping data (Fig. 5), we can compare sandbar 

changes measured at the long-term monitoring sites with changes measured at nearly all bars in 

the reach. This comparison indicates that the number of long-term monitoring sites is adequate in 

lower Marble Canyon, but possibly inadequate in other segments (see Fig. 6 in Project Element 

3.1.1). In addition to the repeat channel mapping data, repeat aerial photography in 2002, 2009, 

and 2013 will allow us to assess the system-wide representativeness of the long-term monitoring 

sites in terms of changes in sandbar size and area (Project Element 3.1.2). 

Better understanding of the physical controls on eddy dynamics will contribute to improved 

predictive capability through modeling. Documented and well-verified models have been 

produced to predict mainstem streamflow throughout Marble and Grand Canyons (Randle and 

Pemberton, 1987; Wiele and Smith, 1996; Wiele and Griffin, 1997; Magirl and others, 2008) and 

sediment flux at approximately 50 km increments between RM 0 and RM 87 (Wright and others, 

2010). These models can be used to predict sediment availability for planning reservoir releases 

(Wright and Grams, 2010) but do not easily facilitate prediction of sandbar response. Wiele and 

others (2007) coupled the canyon-scale models with detailed eddy models in order to provide 

better predictions of bar building and erosion. This approach assumed all eddies behaved 

similarly, with the magnitude of erosion and deposition scaled by eddy size. We now know that 

these assumptions are unfounded and that a predictive canyon-scale model for eddy response 

will have to incorporate the observed site-to-site variability in erosion and deposition. In the 

FY13–14 work plan, progress was made in identifying the sources of eddy sandbar variability 

(Grams and others, 2013) and towards developing a model that will be used, in the current work 

plan (see Project Element 3.3), to investigate the effects of channel geometry on flow and 

patterns of deposition and erosion in eddies (Alvarez and others, 2013; Alvarez and others, in 

preparation). This systematic investigation into the causes of eddy sandbar variability using a 

mechanistic model will facilitate development of an operational model for predicting sandbar 

response to flow and sediment supply (Project Element 3.3).

One uncertainty in estimates of sand flux (Project 2) and computation of sand budgets over 

long reaches that is not attributable to instrument error and which can be addressed through 

experimental design, is the contribution of bedload sand flux to the total transport. Present 

acoustic sediment monitoring captures the suspended sand flux but not the flux of sand which 

moves as bedload. Instead, bedload sand flux is estimated using a constant proportionality with 

suspended sand flux at each gaging station (Topping and others, 2010). The purpose of Project 

3.4 is to better incorporate bedload flux into total sand flux estimates, in order to reduce the 

uncertainty in estimates of total sand flux and, by extension, sand mass balance. This will be 

achieved by measuring bedload flux and developing parameterizations for bedload flux based on 

routinely measured quantities such as discharge and suspended sediment load.

C.2. Management Background 

This project is formulated around seven research questions (see section C.3, below) that have 

been developed from the goals, strategic science questions, information needs, and desired future 

conditions developed in cooperation with stakeholders of the GCDAMP. These many sedimentrelated goals and objectives may be distilled down to one overarching question: “what actions 

will create and maintain fine-sediment resources in the best condition possible within the 

constraints of a limited fine-sediment supply.”

Sediment-related goals were most recently articulated in the August 2011 statement of 

Desired Future Conditions developed by Adaptive Management Work Group. In this document, 

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the goals related to sediment resources are to “maintain adequate sand bars (including camping 

beaches) for recreation in Glen Canyon National Recreation Area and Grand Canyon National 

Park and enhance as needed once maintained” and “maintain nearshore habitats for native fish 

and enhance as needed once maintained.”

Further guidance on monitoring needs is provided by the HFE EA. The central sandbarrelated question identified in the HFE EA is, "Can sandbar building during HFEs exceed sandbar 

erosion during periods between HFEs, such that sandbar size can be increased and maintained 

over several years?" The science plan for the EA includes the following specific science 

questions related to sandbars and camping beaches: (1) Will multiple high flows conducted over 

a period of 10 years result in net increases in sandbar area and volume?; (2) With the available 

sand supply (i.e. tributary inputs), is the approach of using repeated floods to build sandbars 

sustainable?; and, (3) Will multiple high flows conducted over a period of 10 years result in net 

increases in campsite area along the Colorado River? This work plan includes monitoring to 

address each of these questions.

Previous statements of GCDAMP goals addressed in this project include the following:

• Goal 8: Maintain or attain levels of sediment storage within the main channel and along 

shorelines to achieve GCDAMP ecosystem goals.

• Goal 9: Maintain or improve the quality of recreational experiences for users of the 

Colorado River ecosystem within the framework of GCDAMP ecosystem goals. The 

monitoring provides information on the size and abundance of sandbars, which are 

resources that affect the recreational experiences of Colorado River users.

• Goal 11: Preserve, protect, manage, and treat cultural resources for the inspiration and 

benefit of past, present, and future generations. The project includes monitoring sandbars 

that provide a source of sediment, through aeolian transport, to high-elevation sand 

deposits that contain archaeological resources.

Because sediment monitoring addresses the physical framework of the ecosystem, which 

underlies many biological resource objectives, it also indirectly supports achievement of the 

following GCDAMP goals:

• Goal 1: Protect or improve the aquatic food base so that it will support viable populations 

of desired species at higher trophic levels. The proposed monitoring supports this goal by 

providing information on the size and distribution of channel substrate.

• Goal 2: Maintain or attain a viable population of existing native fish, remove jeopardy for 

humpback chub and razorback sucker, and prevent adverse modification to their critical 

habitats. The proposed sandbar and sediment storage monitoring supports this goal by 

providing information on sandbars which create backwaters, a habitat used by native fish.

• Goal 6: Protect or improve the biotic riparian and spring communities within the 

Colorado River ecosystem, including threatened and endangered species and their critical 

habitat. The sediment storage and sandbar monitoring tracks the status of the fine79
sediment deposits which provides the substrate for riparian vegetation and marsh 

communities.

The 2003 GCDAMP Strategic Plan identified Core Monitoring Information Needs (CMINs) 

related to sediment storage (goal 8). The CMINS that are addressed in Project 3 are listed below. 

For each, the prioritization ranking applied by the GCDAMP Science Planning Group (SPG) in 

2006 is also included. In addition, several Strategic Science Questions (SSQs) were identified by

scientists and managers during the knowledge assessment workshop conducted in the summer of 

2005 (Melis and others, 2006). 

• CMIN 8.1.1. Determine and track the biennial sandbar area and fine-sediment volume 

and grain-size changes within eddies below 5,000 cfs stage, by reach. (fourth-ranked goal 

8 CMIN). Addressed in project 3.2..

• CMIN 8.2.1. Track, as appropriate, the biennial or annual sandbar area, volume. and 

grain-size changes within and outside of eddies between 5,000 and 25,000 cfs stage, by 

reach. (second-ranked goal 8 CMIN). Addressed in projects 3.1.1, 3.1.2, and 3.2..

• CMIN 8.5.1. Track, as appropriate, the biennial sandbar area, volume, and grain-size 

changes above 25,000 cfs stage, by reach (fifth-ranked goal 8 CMIN). Addressed in 

projects 3.1.1, 3.1.2, and 3.2.

• CMIN 8.6.1. Track, as appropriate, changes in coarse sediment (> 2 mm) abundance and 

distribution (unranked goal 8 CMIN). Addressed in project 3.1.2 and 3.2.1.

• CMIN 9.3.1. Determine and track the size, quality, and distribution of camping beaches 

by reach and stage level in Glen and Grand Canyons (top-ranked goal 9 CMIN). 

Addressed in project 3.1.1.

• SSQ 4-1. Is there a “Flow Only” operation (that is, a strategy for dam releases, including 

managing tributary inputs with BHBFs, without sediment augmentation) that will rebuild 

and maintain sandbar habitats over decadal time scales? Addressed in all project 

components.

• SSQ RIN 5: What is the rate of change in eddy storage (erosion) during time intervals 

between BHBFs? Addressed in project 3.2.

C.3. Key Monitoring and Research Questions Addressed in this project 

The goals, science questions, and information needs listed above are often overlapping and 

have various degrees of specificity. We have, therefore, translated them into the following set of 

monitoring and research questions addressed in this Sandbar and Sediment Storage project:

1. What is the long-term net effect of dam operations, including high flows, on changes in 

high-elevation sandbar area and sand storage (i.e. the sand above the 8,000 ft3

/s stage)?

These changes are relevant to camping beaches, riparian vegetation, backwater habitat, 

and control the supply of bare sand that is redistributed by wind. Addressed in Project 

Elements 3.1.1 and 3.1.2.

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2. Do individual HFEs continue to build sandbars with the same effectiveness observed in 

response to previous HFEs (i.e. do floods of similar magnitude build a similar number of 

sandbars of similar size?)? Do individual sandbars respond significantly differently to 

different HFEs? How does sandbar size and shape prior to HFEs affect the bar-building 

response? Addressed in Project Elements 3.1.1 and 3.1.3.

3. What are the causes of variability in sandbar response to floods and intervening dam 

operations? Can we categorize this variability and incorporate this in a model for sandbar 

response? This builds on sandbar monitoring (Question 1) to support prediction of 

sandbar response. Addressed in Project Elements 3.1.1, 3.1.3, 3.1.4 and 3.3.

4. What is the long-term net effect of dam operations, including high flows, on changes in 

low-elevation sand storage (the sand below the 8,000 ft3/s stage) and bed-sediment grain 

size? These changes are relevant to backwaters and other aquatic habitat, the foundation 

of eddy sandbars, and the relative partitioning of transported sediment into eddies and 

downstream, which ultimately determines whether the use of experimental high flows is 

sustainable. Addressed in Project Element 3.2.

5. What is the relative abundance and spatial distribution of fine and coarse bed sediments 

and submerged aquatic vegetation, and how do these affect primary production, fish 

habitat, and modeled sediment fluxes? This builds on low elevation sand monitoring 

(Question 5) to support sediment transport and biological prediction. Addressed in 

Project Element 3.2.

6. Can we improve reach-scale estimates of sand flux and sediment mass balance by better 

quantifying the contribution of bedload transport? Can we use the geometry and 

sedimentology of bedforms as an indicator of 'bed state;' i.e. sand-enriched or sanddepleted bed conditions. Addressed in Project Element 3.4.

D. Proposed Work 

This project is divided into four monitoring and research elements and one additional support 

element. The first two project elements are monitoring projects, each with some research aspects 

that address monitoring needs. The latter two elements are research projects that contribute to 

improving the monitoring program and improving predictive capacity. Project Element 3.3 will 

continue the investigation of physical controls on variability in sandbar deposition with the goal 

of developing a new operational model for predicting sandbar response to flow and sediment 

conditions. The objective of Project Element 3.4 is to develop an improved estimate for the 

contribution of bedload transport to total sand flux. This will improve our ability to estimate sand 

mass balance and reduce the uncertainty in those estimates. The control network and survey 

project element advances our capacity for making repeatable geospatial measurements and 

supports all other Project 3 elements, as well as other GCMRC projects. 

The ultimate measure of whether or not fine sediment is conserved in and near the Colorado 

River is the increase or decrease in volume (and by extension, area) of fine-sediment deposits. 

Thus, monitoring elements involve repeat measurements of topography such that changes in the 

volume of sand deposits can be calculated. Because the management focus is on fine sediment, it 

is necessary to discriminate sand and finer sediment from gravel, cobbles, and boulders. In order 

to more effectively detect change in important resources, it is necessary to monitor change in 

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sand storage at both high and low elevations. This requires a mix of direct field measurement, 

remote sensing, and extrapolation throughout the 255 miles of the Colorado River between Glen 

Canyon Dam and RM 240, which is the upstream end of Lake Mead reservoir.

Data collection efforts must occur across a wide range of spatial and temporal scales (Table 

1) in order to detect change in a very large system in which significant change is often localized 

and episodic or short-lived. At a select set of long-term monitoring sites, sandbar monitoring is 

conducted at a daily (using remote cameras) and annual (by conventional survey) interval in 

order to track local response to individual events in the context of a long-term record. A larger 

collection of sandbars are also monitored using remote sensing, with a return interval of several 

years, in order to provide a synoptic view of the entire Colorado River.

Table 1. Summary of sandbar and sediment storage monitoring efforts.

Project 

Element

Spatial Focus Method Measurement 

Frequency

Information 

Needs Met

3.1† Selected highelevation sandbars 

(47 sites)

Conventional 

topographic surveys 

(volume and area)

Yearly Annual status 

check on 

sandbar and 

camping beach 

condition

3.1 Selected highelevation sandbars 

(42 sites)

Remotely deployed 

digital camera 

(approximate size)

Daily Status check on 

sandbar 

condition at ~6-

month intervals

3.1 High-elevation 

sandbars 

systemwide 

(>1000 sites)

Remote sensing 

(area)

Every 4+ years* Long-term trend 

of sandbar 

condition

3.2 Low-elevation 

fine-sediment 

storage in 30 to 

80-mile segments.

Combined 

bathymetric and 

topographic surveys 

(area and volume)

Every 3 to 10 

years, depending 

on reach.

Long-term trend 

in fine-sediment 

storage

* Remote sensing images of the entire CRe were collected in 2002, 2005, 2009, and 

2013.Frequency of future remote sensing missions is anticipated to be every 4 to 10 years.

†

Project Element 3.1.3 aims to develop methods to increase the spatial coverage at the same 

measurement frequency

Monitoring of fine-sediment deposits is also conducted at multiple scales using a variety of 

methods. Sediment inputs and outputs (the I and O terms in equation 1) are monitored at a daily 

scale in 30-mile or longer sediment budgeting reaches (Project 2: Streamflow, Water Quality, 

and Sediment Transport). In this project, we monitor changes in sediment storage directly (the 

∆S term in equation 1) at approximately 3- to 10-year time intervals and with very high 

precision. These monitoring strategies are complementary. The mass balance measurements of 

high temporal resolution can be used to track tributary inputs and to schedule high flows. Fine82
sediment storage monitoring provides a direct measurement of changes in storage for all storage 

environments over the entire monitoring period, whether a few years or several decades. 

D.1. Project Elements 

Project Element 3.1. Sandbar Monitoring 

Project Element 3.1.1. Monitoring sandbars using topographic surveys and remote cameras 

(Recommended for funding FY15: $370,258)

Paul Grams, Research Hydrologist, USGS, GCMRC 

Daniel Buscombe, Research Geologist, USGS, GCMRC

Joseph Hazel and Matt Kaplinski, Research Associates, Northern Arizona University

Keith Kohl, Surveyor, USGS, GCMRC

Robert Tusso, Hydrologist, USGS, GCMRC

Objectives

1. Continue measurements of sandbars at long-term monitoring sites during annual surveys, 

to track trends in sandbar area, volume, and other important metrics for understanding 

sandbar dynamics.

2. Track annual trends in total campsite area at long-term monitoring sites with data from 

annual surveys.

3. Continue to document sandbar condition on a daily timescale, by maintaining the 

network of autonomous remote-cameras.

4. Track monthly changes in sandbar areas at long-term monitoring sites by measuring areas 

using ortho-rectified images from the remote-camera network.

5. Complete the development of an interactive website to efficiently serve sandbar data and 

remote camera images with a user-friendly interface.

Hypotheses/Questions

1. What is the cumulative effect of HFEs and intervening dam operations on the size of 

sandbars in the CRe?

2. Do individual HFEs continue to build sandbars to a magnitude similar to that observed in 

response to previous HFEs?

3. Do individual sandbars respond differently to different HFEs? 

4. How does sandbar size and shape prior to HFEs affect the bar-building response?

Rationale/Justification

A subset of all sandbars and campsites located throughout the CRe will be monitored 

annually using conventional ground-based topographic surveys. These surveys will contribute to 

the long-term monitoring dataset commonly referred to as the “Northern Arizona University 

(NAU) sandbar time-series”. This is the longest, most accurate and complete dataset describing 

the state of sandbars. The monitoring program, initiated in 1990, includes surveys at 47 sites, 

which provides measurements of sandbar area and volume above the stage associated with a 

discharge of 8,000 ft3

/s. In addition, campsite area is measured at 37 of these sites. Methods for 

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these surveys are described by Hazel and others (2008; 2010; in preparation) and Kaplinski and 

others (2009; in review). These annual surveys are supplemented by photographs of 42 sites, 

several times per day, using autonomous remote digital-camera systems (Bogle and others, 

2012). These images make it possible to record the effects of changes in flow at a time scale that 

cannot be resolved by the annual topographic measurements. 

The sites monitored in this project were selected based on the lengthy historical record, rather 

than a random selection from among all sandbars in the CRe. One of the objectives of the FY13–

14 work plan was to evaluate the degree to which the sample of long-term monitoring sites 

represent changes at the population of sandbars, using data collected in the sediment storage 

monitoring project (Project Element 3.2). Preliminary results from this analysis indicate that 

mean change in sandbar thickness (volume normalized by area) between 2009 and 2012, based 

on the 18 long-term monitoring sites in lower Marble Canyon (-0.06 m ± 0.06 m standard error), 

is consistent with the mean change among a much larger sample of 84 sandbars mapped in 2009 

and 2012 by Project Element 3.2 (-0.06 m ± 0.04 m standard error) (Fig. 6). 

Figure 6. Bootstrap simulation of expected standard error (m) for estimates of sandbar thickness change as a function of 

sample size. Measurements of thickness change for 84 sandbars in lower Marble Canyon (data from Project 3.2) were 

sampled randomly using increasing sample size (1 to 84). For each sample size, 100 random selections of sites (numbering 

between 1 and 84) were made from among the 84 sites, and the standard error calculated and plotted. The standard error 

decreases quickly with increasing sample size up until n ~ 20. Standard error decreases more gradually thereafter. The 

sample site density in lower Marble Canyon (LMC) achieves a reasonable uncertainty for the number of sites. More sites 

would be required in east central Grand Canyon (ECGC), west central Grand Canyon (WCGC), upper Marble Canyon 

(UMC), and eastern Grand Canyon (EGC).

The variance of thickness change between 2009 and 2012 among all sandbars is 

approximately double the variance among the 18 monitoring sites, indicating that the monitoring 

sites may tend to have smaller-magnitude changes than the collection of all sandbars. This 

suggests that, for lower Marble Canyon at least, our long-term monitoring may adequately 

represent mean sandbar condition, but fails to capture the full extent of variability in sandbar 

condition. The analysis also indicates that a random sampling of fewer than the current number 

of monitoring sites would be unlikely to capture mean bar condition better than the current 

monitoring sites (Fig. 6). This presents a challenge to our monitoring design, because monitoring 

sites are more frequent in lower Marble Canyon (about 1 site every 1.8 miles) than any other 

84
reach (1 site every 4 to 9 miles). Matching the monitoring site density in other reaches would 

require adding about 7 sites in upper Marble Canyon, 6 sites in eastern Grand Canyon, and more 

than 50 sites in east- and west-central Grand Canyon (RM 87-225).

Adding long-term monitoring sites would require additional and/or longer monitoring trips 

and an increase in the monitoring budget. Instead, we propose to evaluate alternative methods for 

surveying the topography of sandbars that have the potential to allow rapid and inexpensive 

measurement of a large number of sites (see Project Element 3.1.3). In addition, we propose to 

develop a sandbar model (see Project Element 3.3) that would predict the volume of sand in bars 

by incorporating information from the sandbar surveys, sandbars measured by remote sensing 

(Project Element 3.1.2), during channel mapping (Project Element 3.2), and by rapid survey (if 

the method proves feasible) to estimate the status of the population of sandbars throughout 

Marble Canyon and eastern Grand Canyon. These efforts are focused on improving upon our 

annual estimate of sandbar size that is based on the topographic surveys conducted each fall. 

An additional objective of this project element is to improve upon the methods we use to 

estimate sandbar size following each HFE, or more frequently. Currently, remote digital cameras 

capture images of nearly all of the monitoring sites several times per day. These images have 

been made available on the GCMRC website following the 2012 and 2013 HFEs and have been 

used to make a rapid qualitative assessment of each sandbar response immediately after each 

HFE. It is also possible to use these images for more quantitative analyses; and we have made 

recent progress with the development of methods to measure sandbar area from these images, by 

ortho-rectifying each image using ground control points surveyed during monitoring trips. Orthorectification is the process of transforming an oblique image into an aerial photograph 

(rectification) which is geometrically corrected such that the photo has the same lack of 

distortion as a map (“ortho-”). We will continue to develop these methods with the goal of 

measuring sandbar response to each HFE and erosion rate following each HFE. Developing these 

methods involves: (1) measuring ground control points at all long-term monitoring sites that 

have cameras; (2) systematically evaluating the areal estimates from images using ground-based 

surveys carried out at the same time; and (3) because manual segmentation of sandbars is slow 

and subjective, developing unsupervised (fully automated) or partially supervised (minimal user 

input) methods to segment sandbars in ortho-rectified images. This will greatly improve upon 

our ability to compare the sandbar-building response to HFEs of different magnitude, duration, 

and sediment supply conditions.

One of the FY13–14 research projects involved the investigation of the relation between 

changes in campsite area and causal mechanisms. Preliminary results from this project indicate 

that while vegetation expansion can be a significant cause of campsite area change at some sites, 

sandbar erosion and deposition cause the majority of increases and decreases in campsite area 

since 1998 (Hadley and Grams, in preparation). This effort also included an assessment of 

uncertainty in the campsite monitoring methods that will be incorporated in future reports on 

campsite area.

In 2014, we initiated the development of a sandbar database with a web-browser based user 

interface. We also implemented a rudimentary web-browser based interface for viewing selected 

photographs of monitoring sites following the 2012 and 2013 high flows. We will continue the 

development of these tools to allow users to view and download all photographs for each of the 

monitoring sites, in addition to completing a web interface for downloading and interactively 

visualizing the sandbar data (initially, sandbar areas and volumes).

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Methods

Sandbar and campsite surveys will be conducted each fall using established methods (Hazel 

and others, 2010; Kaplinski and others, 2014). The methods for the proposed rapid surveys and 

modeling are described below under Project Elements 3.1.3 and 3.3, respectively. The novel 

methods that will be developed and used in this project element are those associated with the 

effort to quantify sandbar area and volume from the remote camera images. 

Essentially, the process of estimating sandbar area from oblique images consists of orthorectifying the images using surveyed ground control points, delineation of the sandbar on each 

orthoimage, and then simply calculating the area. The ortho-rectification is an automated process 

which creates a mapping between ground and image coordinates, and warps the image such that 

pixels are located in the correct positions for the final image to be planimetrically correct. 

Ground control points have been collected at a number of sites during FY13–14 in anticipation 

of applying this technique. The technique has been demonstrated using time-series of images 

from the 22-mile and 30-mile sandbars. The sandbars have been delineated manually and 

verified using ground-based surveys; this process has already added hundreds of sandbar-area 

estimates using images collected in the past 5 years (Buscombe and others, in prep.). Our goal is 

to make the process of sandbar delineation from images as automated as possible, because the 

process must be repeated many times at each of the monitoring sites. To this end, initial trials 

using a variety of image processing methods have been highly encouraging, so we are confident 

that accurate, automated delineation of sandbars from images is feasible. This technique has the 

potential to massively augment data on subaerial sandbar areas, at minimal extra cost and at a 

number of important sites, in the recent past and in the future.

We have recently demonstrated that sandbar volumes can also be estimated from digital 

elevation models (DEMs) constructed directly from ortho-rectified digital imagery from 

autonomous cameras (Buscombe and others, in preparation). If the elevations of water lines in 

images are known, contour maps of sandbars can be constructed as the flow varies. The process 

consists of obtaining the horizontal coordinates of waterlines from the rectified image, and 

assigning the vertical coordinate from the estimated water stage. As the stage varies, a DEM can 

be constructed from several contour lines. The process works best if stage varies significantly 

over short periods, such as upramp and downramp of controlled floods. Stage elevations are 

either measured using an instrumented record (such as a pressure transducer) or estimated using 

a stage-discharge relation (which exist for all long-term monitoring sites; Hazel and others, 

2006). The technique has been evaluated using imagery from 30-mile sandbar during the 2012 

and 3013 HFEs. The DEM constructed using imagery from the 2012 HFE was validated using 

data collected at that site immediately afterwards using conventional ground-based surveys. We 

propose to apply the technique to more sites to obtain volumetric estimates of bars after HFEs, as 

a very cost effective means with which to assess the effects of HFEs on sandbars. 

Outcomes and Products – FY15

• Presentation at annual reporting meeting on the status of sandbars and campsites based on 

monitoring from the previous year. 

• Web browser interface for viewing remote camera photographs.

• Web browser interface for viewing sandbar data.

• Journal article detailing and evaluating methods for measuring sandbar areas and 

volumes from remote camera images.

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Outcomes and Products – FY16

• Presentation at annual reporting meeting on the status of sandbars and campsites based on 

monitoring from the previous year. 

• Sandbar data and photographs updated on web interface.

• Report/journal article on sandbar response to HFEs or short-term sandbar variability 

based on measurements of sandbar size derived from remote camera images.

Outcomes and Products – FY17

• Presentation at annual reporting meeting on the status of sandbars and campsites based on 

monitoring from the previous year. 

• Sandbar data and photographs updated on web interface.

• Report/journal article on long-term trends at the sandbar monitoring sites.

Project Element 3.1.2. Monitoring sandbars and shorelines above 8,000 ft3/s by remote sensing 

(Recommended for funding FY15: $120,033)

Joel Sankey, Research Geologist, USGS/GCMRC

Rob Ross, Hydrologist, USGS/GCMRC

Tom Gushue, GIS Coordinator, USGS/GCMRC

Paul Grams, Research Hydrologist, USGS/GCMRC

Ted Melis, Physical Scientist, USGS/GCMRC

Objectives

The first objective of this work is to measure the area of exposed sand above the 

elevation of the 8,000 ft

3

/s stage (high-elevation sand) for more than 1300 large eddies 

(henceforth referred as “large eddy dataset”) along the Colorado River using imagery acquired 

from the remote sensing overflight in May 2013. The results from mapping sand area on the 

2013 images will be compared with sand area measured on the May 2002 and May 2009 

overflight images (Ross and others, in preparation). 

The second objective of this work is to evaluate changes in sandbar topography 

(elevation and volume) between 2002 and 2013 at the same set of more than 1300 eddies 

monitored for changes in sand area using digital surface models (DSMs) from automated 

photogrammetry that are acquired coincident with overflight imagery. 

The third objective will be to use results from the Objectives 1 and 2 to investigate the 

representativeness of the smaller set of ~47 long-term monitoring sites (Project Element 3.1.1) 

that are monitored with detailed topographic surveys. This will complement the analysis shown 

in Figure 6 that was based on one 30-mile river segment with an analysis using the exhaustive set 

of sandbars located within the large eddy dataset. It is anticipated that Objective 3 will be useful 

for other projects, and specifically will identify the extent to which the periodic remote sensing 

overflight measurements of sandbar area and topography for a large portion of the Colorado 

River can be used to inform the groupings of sandbars by morphology and flood response 

proposed in modeling work of Project Element 3.3.

In addition, this project will include the completion of a geomorphic base map for all of 

Grand Canyon. The geomorphic base map will be used by this and other projects that require 

87
information about the canyon-wide distribution and characteristics of eddies and sandbars or 

other types of geomorphic units, such as debris fans and gravel bars that provide important 

shoreline habitats for aquatic organisms and riparian vegetation.

Hypotheses/Questions

Mapping Sandbar Area

1. Are the changes in sandbar area observed between 2002, 2009 and 2013 at the smaller set 

of long-term monitoring sites representative of changes over that same period for 

sandbars within the more exhaustive set of large eddies throughout Marble and Grand 

Canyons?

2. Are there longitudinal (downstream) variations in sandbar response?

Measuring Topographic Variability in Sandbars

1. What is the accuracy and uncertainty of the aerial overflight-based measurements of 

sandbar topography when compared to measurements of topography derived from the 

more detailed long-term monitoring site surveys? 

2. Can the more spatially extensive set of sandbar measurements derived from the aerial 

overflight data be used to (a) better understand the ways in which the long-term 

monitoring sites are and are not representative of sandbars throughout the larger river 

corridor?, and(b) produce a larger data set of sandbar size and morphology useful for 

Project 3.3. In the latter case, the remotely-sensed data can be used to develop more 

robust groupings of sandbars by morphology (using metrics such as area, volume, slope, 

planform shape, and concavity) and as a validation data set for a generalized sandbar 

response model calibrated using the NAU sandbar time-series.

Geomorphic Base Map

1. What is the number, spatial distribution, and extent (area) in the CRe of: 

a. eddies that contain or may contain sandbars in the CRe;

b. channel-margin sand deposits not within eddies;

c. gravel bars; and

d. debris fans?

2. What proportion of the total number and area of the eddies identified in the geomorphic 

base map are represented in the dataset of long-term sandbar monitoring sites and in the 

large eddy dataset?, and how do these relative proportions vary spatially throughout the 

CRe?

Rationale/Justification

Mapping and measuring changes in sandbar area and topography 

Sandbars of the CRe below Glen Canyon Dam are found in association with eddies that are 

typically created and maintained by interaction of the main channel flow with bouldery debris 

fans. These landforms tend to be relatively stable over long periods. Debris fans constrict the 

river channel and form slower velocity eddies at hundreds of locations that act as “traps” for 

finer sediment transported downstream from source tributaries such as the Paria River (Schmidt 

88
and Rubin, 1995). Management of sandbars as recreational camping areas is currently ongoing 

through a long-term High Flow Experimental protocol that started in 2012 and is set to continue 

until at least 2020. Existing digital imagery and topographic data collected from remote sensing 

overflights in 2002, 2009, and 2013 allows an opportunity to inventory and document both largeand small-scale sandbar and shoreline changes within eddy areas during this time period, 

including those possibly associated with tributary floods and debris flows. Because only a subset 

of sandbars are surveyed using conventional methods (Project Elements 3.1.1 and 3.2), the 

purpose of these remote sensing data is to track the area of exposed sand above the elevation of 

the 8,000 ft3

/s stage (high-elevation sand) of 1300 large eddies along the Colorado River. The 

remote sensing images remain the only way to evaluate the condition of sandbars synoptically 

throughout all of Glen, Marble, and Grand Canyons. 

In the FY13–14 work plan, regions historically containing exposed sand above the elevation 

of the 8,000 ft3/s stage (high-elevation sand) were delineated for more than 1300 large eddies 

along the Colorado River in imagery acquired in 2002 and 2009. The classification of the areas 

of sand exposed in these large eddies in the 2002 and 2009 imagery will be completed in FY14. 

In this project, we will extend the record of canyon-wide sand area assessment above the 8,000 

ft3

/s stage to include analysis of overflight imagery acquired in 2013.

Imagery from 2002, 2005, and 2009 has also been incorporated in an analysis of sandbar area 

change within six reaches in which high-elevation sand was mapped from images taken in 1965, 

1973, 1984, 1990, March 1996, and April 1996 (Schmidt and others, 2004) (Fig. 7). These 

estimates of sandbar area were reasonably accurate with respect to independent ground truth 

estimates derived from more detailed topographic surveys; the area estimates under- or overpredicted survey-derived estimates by 3-15 percent among the reaches analyzed. The results 

show that the area of sandbars exposed above the 8,000 ft3/s stage in Marble Canyon was 

generally larger in images from the era of post-dam controlled floods (April 1996, May 2002, 

May 2005, and May 2009) than in images from the post-dam period before controlled floods 

(June 1990 and March 1996). From 2002 to 2009, sandbar areas, on average, were estimated to 

be lowest in 2002, greatest in 2005, and intermediate in 2009. Sandbar areas appeared to 

potentially vary as a function of time since a controlled flood (HFE), as the 2002 imagery were 

collected 6 years after an HFE, the 2005 imagery were collected 6 months after an HFE, and the 

2009 imagery were acquired 1 year after an HFE. Results of this work will be delivered and 

summarized in a manuscript prepared by the end FY14 (Ross and Grams, in prep.).

89
Figure 7. Area of sand in square meters per km in eddy deposition zones for all reaches with historical data from 1935 to 

2009. 

Recent analysis of digital topography from the 2002 and 2009 aerial overflights relative to 

ground truth of detailed topographic surveys demonstrates the feasibility and limitations of 

measuring topographic changes with data from overflights that is less accurate but provides a 

synoptic view of the river corridor compared to the surveys. Table 2 shows examples of the 

average error in estimates of sandbar elevations derived from overflight relative to survey data 

for cross-sections at 5 different sandbar monitoring sites. Changes measured between 2002 and 

2009 with the overflight data had a root mean square error (RMSE) of 0.49 m when compared to 

the ground truth data of changes measured from topographic surveys. These results provide 

conservative estimates of the uncertainty associated with topographic change detection 

conducted with the overflight data and the magnitude of change that might be reliably detected 

with the overflight data. On average, the correlations between elevations and changes in 

elevation measured with the overflight and survey data were moderate to strong. When compared 

with the magnitude of changes in elevation observed with the detailed topographic surveys (Fig. 

8) the average error estimates (Table 2) indicate that the overflight data will be most useful for 

detection of the more extreme changes characterized by the detailed topographic surveys. Similar 

uncertainty analyses and error budgets for sand volume, area, and other morphological 

characteristics of bars will need to be performed in the course of the work proposed for this 

project. Nonetheless, the potential for synoptic measurements of sandbar topography within the 

level of uncertainty in elevation indicated in Table 2 suggests that these remote sensing data have 

utility for better understanding the ways in which the long-term, sandbar survey monitoring sites 

are and are not representative of sandbars throughout the larger river corridor. Further, these data 

90
can be leveraged in Project Element 3.3. as both an additional data set to define sandbar 

groupings by morphology (using metrics such as area, volume, slope, planform shape, and 

concavity) and as a validation data set for a generalized sandbar response model. 

Table 2. Average error and correlation between elevation measurements from total station 

survey and DSMs acquired in 2002, 2009, and change detected with each method from 

2002 to 2009 at five sandbar study sites. 

Site Year RMSE (m) R2

44L 2002 0.20 0.87

2009 0.38 0.91

2002-2009 0.33 0.73

68R 2002 0.59 0.24

2009 0.90 0.73

2002-2009 0.67 0.03

93L 2002 0.53 0.70

2009 0.26 0.97

2002-2009 0.71 0.86

122L 2002 0.18 0.93

2009 0.39 0.92

2002-2009 0.43 0.74

194L 2002 0.22 0.99

2009 0.20 0.98

2002-2009 0.31 0.84

Average 2002 0.35 0.75

2009 0.43 0.90

2002-2009 0.49 0.64

Figure 8. Box plots showing distribution of changes in elevation determined from total station surveys in 2002 and 2009 at 

five sandbar monitoring sites.

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Geomorphic base map

A geomorphic base map is required to provide context for all system-wide studies in the 

CRe. The map is of immediate need for ongoing system-wide studies of sandbars and riparian 

vegetation. The map will consist of just a few simple map units such as: eddies; sand deposits 

within eddies; sand deposits along channel margins (not within eddies); debris fans; gravel bars; 

talus; and bedrock. This will enable any system-wide analyses to be segregated by geomorphic 

setting. While previous studies have completed detailed maps including these features for short 

segments (e.g. Hereford, 1996; Hereford and others, 2000; Schmidt and others, 2004) or 

conducted systemwide inventories of specific resources, such as eddies that contain backwaters 

(Grams and others, 2010), there does not exist a map that covers the entire CRe with a consistent 

set of map units and mapping criteria. 

Methods

Mapping sandbar area

The new work proposed in this project will extend analyses conducted on the 2002 and 2009 

imagery to include measurements of sand area in imagery acquired in the 2013 overflight. The 

canyon-wide remote sensing data used in this effort consists of four-band, orthorectified digital 

imagery (blue, green, red, and near-infrared bands) acquired in late May 2013. The remote

sensing effort will involve a landscape delineation of four units: water, vegetation, sand, and 

other bare (non-vegetated) terrestrial surfaces. This will be similar to the landscape databases in 

production for image data sets collected in 2002 and 2009. For each image set, the water surface 

and total vegetation are mapped using interactive image processing algorithms (Davis and others, 

2002; Ralston and others, 2008). This project will use water and total vegetation classifications 

produced for the 2013 imagery in riparian vegetation-related project work that is currently 

proposed for FY15. Following the water and vegetation classification, areas of sand will be 

classified. Therefore, the sand area classification and measurements proposed here will 

commence in FY16 and proceed into FY17. We will report on the results of the mapping and 

change analyses will be reported on in FY17.

Measuring topographic changes and evaluating representativeness of long-term survey dataset

Digital surface models (DSMs) were produced from airborne automated digital 

photogrammetry data acquired during the aerial overflights of 2002, 2009, and 2013 for the 450 

km length of Glen and Grand Canyon at steady Colorado River discharge of 227 m3/s (8,000 

ft3

/s) (Davis, 2012). The airborne automated digital photogrammetry DSM data acquired in 2002 

and 2009 have been evaluated during work recently completed in 2013 and 2014 by Phil Davis 

(personal communication). The DSM data have 1-m cell resolution with vertical ellipsoid heights 

reported to the nearest 10 cm (but only accurate to the nearest 30 cm – see following 

explanations and example of error assessment for the 2009 data), and are sectioned into U.S. 

Geological Survey map quadrangles. The data were not initially processed to remove effects of 

vegetation or other surface cover on topographic elevation values. However, work completed in 

2013 and 2014 developed a methodology to minimize these effects that was tested on the 2009 

dataset, in which pixels that contained vegetation canopies identified in classification of the 

coincidentally collected and co-registered multispectral imagery were replaced with elevations 

interpolated from surrounding bare ground surfaces.

Horizontal and vertical accuracy of the 2002 and 2009 DSM data were assessed by 

comparison with 125 ground control points distributed over the entire 450 km length of data 

collection (Davis, 2012; P. Davis, USGS, pers. comm., 2013). Errors for the 2009 dataset were 

normally distributed with an initial 38 cm vertical offset, but were adjusted resulting in a final 

92
dataset with relative vertical RMSE of 30 cm (59 cm at 95 percent confidence level with 1.96 

sigma) (P. Davis, USGS, pers. comm., 2013). The relative positional (horizontal) accuracy was 

determined to be 19 cm (47 cm at 95 percent confidence level with 2.45 bivariate sigma) (Davis, 

2012).

For this work, we will conduct change detection using the digital topography (DSM) data 

from 2002, 2009, and 2013 images. The change detection will be completed for sandbars in the 

same set of more than 1300 eddies monitored for changes in sand area. The datasets will be 

differenced and vertical and volume changes will be estimated for the areas of sand mapped in 

the large eddies that are the focus of Objectives 1 and 2. Changes that are detected in these areas 

will be evaluated relative to ground truth, as available, from the subset of sandbars that are 

topographically surveyed (e.g., Table 2).

The distribution of volumes and areas of sandbars for the 3 overflight dates as well as the 

distribution of changes between these dates will be compared to respective distributions of data 

derived from the smaller set of surveyed sandbars. The comparison of distributions will be 

instrumental in completing the third objective that aims to investigate the representativeness of 

the long-term NAU sandbar data set relative to the populations of sandbars that are located 

throughout larger segments of the river. For example, we may expect that the total number of 

eddy sandbars, as well as the area- or volume-based distribution of sandbars (e.g. Fig. 6), may 

vary among geomorphic reaches (e.g. Schmidt and Graf, 1990; Melis, 1997), among those 

reaches targeted for individual channel mapping efforts in element 3.2, and collectively within 

the greater river corridor between Glen Canyon Dam and Lake Mead Reservoir. Additionally, 

the representativeness of the long-term NAU sandbar data set is vital to the sandbar modeling 

component of this work plan (Project Element 3.3) For example, are sandbar groupings and eddy 

characteristics derived from the NAU sites appropriate for understanding eddy sandbar behavior 

in the 1300 eddies measured in this project? Does an empirical model of sandbar response 

calibrated from the NAU sandbar data represent a viable approach for modeling sandbars 

system-wide? Practically, these questions can only be answered on a scale as large as the Grand 

Canyon using data on sandbar characteristics and change derived from remote sensing, which 

provides us measures of the true (system-wide) sandbar population. 

As an additional component of this project, which requires relatively little additional data 

processing, we will investigate whether topographic changes at debris fans are detectable in 

comparison of the 2009 and 2013 DSMs. Several significant tributary streamfloods and debris 

flows have occurred since 2002. Three tributaries known to have produced debris flows since 

2009 include: Cathedral Wash, Red Canyon, and National Canyon, located at RM 2.8-R, RM 

76.7-L and RM 166.4-L, respectively. Because these tributaries are located in upper Marble 

Canyon, eastern and central Grand Canyon, and have drainage areas of 17.3, 10.5, and 407.1 km2

, they represent widely ranging catchment characteristics (lithologies, drainage aspect and 

median elevations) that are related to the potential for causing debris flows (Griffiths and others, 

2004). These events altered rating relations and affected rapids. Because of the potential 

significance of these events for changing channel morphology and thereby altering the hydraulics 

of rapids and adjacent eddies (Kieffer, 1985), it is important to monitor temporal changes in 

debris fan-channel interactions where recent debris flows are known to have occurred.

Geomorphic base map

The geomorphic base map will be constructed by identifying contacts between each of the 

map units and digitizing those lines on-screen in ArcGIS. The initial interpretation and mapping 

will be done in the office using recent (2009) aerial imagery as a base. The preliminary mapping 

93
will followed by field checking areas of uncertainty on the annual sandbar monitoring trip in Fall 

2015, requiring no additional logistic costs. Grams (unpublished data) has completed a 

preliminary base map for lower Marble Canyon (Fig. 9) for use in the channel mapping project 

(FY13–14 Project Element A.2). 

Figure 9. Example geomorphic base map for a segment of lower Marble Canyon showing channel segments (CH_*), eddies 

(ED), sandbars (RB, SB), and debris fans (DF).

Outcomes and Products – FY15

• Completed geomorphic base map.

• Report/journal article on geomorphic base map.

Outcomes and Products – FY16 and FY17

• Reports/journal articles on system wide variability and changes in sandbar area, sandbar 

elevation, and sandbar morphology from remote sensing, 2002–2013.

Project Element 3.1.3. Surveying with a camera: Rapid topographic surveys with digital images using 

structure-from-motion (SFM) photogrammetry 

(Recommended for funding FY15: $42,320)

Joseph Wheaton, Assistant Professor, Utah State University

Daniel Buscombe, Research Geologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Graduate Student

94
Objectives

The objective of this work is to develop, evaluate and implement (operationally, for 

monitoring purposes) a methodology which allows low-cost and rapid (in terms of data 

collection and processing) monitoring of sandbars with a camera, to support monitoring and 

geomorphic change detection. To this end, the use of a photogrammetric technique called 

‘structure-from-motion’ (SfM), which builds an accurate three-dimensional model of a scene 

from photographs taken from multiple viewpoints (James and Robson, 2012; Westoby and 

others, 2012; Fonstad and others, 2013), will be evaluated for the purposes of repeat mapping the 

topography of sandbars. This evaluation will include quantifying errors and uncertainties, as well 

as the logistical considerations for efficient field data collection. The intended outcome will be a 

set of sampling and data-processing protocols for the creation of a DEM of any sandbar from a 

set of photographs taken using any camera.

If the method is proven (i.e. the above objectives are completed), a further objective would 

be to develop 'citizen science' tools that would allow river guides or other members of the public 

to contribute to sandbar mapping efforts simply by taking a set of photographs following a 

prescribed protocol. The SfM technique would eventually be used to create DEMs of 100’s of 

sandbars to augment and evaluate the representativeness of the 45-50 long-term NAU sandbar 

time-series (see hypotheses/questions below).

Hypotheses/Questions

1. Can accurate digital elevation models (DEMs) be obtained rapidly, with quantification of 

errors and uncertainties, and with minimal logistical support, using a consumer-grade 

handheld digital camera? Assuming they can, what are the limitations of this technique 

relative to traditional total station surveys and what is the relative accuracy of SfMderived DEMs compared to total-station-derived DEMs.

2. Can a simple protocol for photographing any sandbar be drawn for a non-specialist, 

which would result in a set of images sufficient to create a DEM of that sandbar using 

SfM?

3. Using repeat SfM mapping at the same site(s), what set of metrics calculated from the 

DEMS (which can also be calculated from total-station-derived DEMs) encapsulate the 

essential changes to a sandbar over time? How can these metrics be combined to assess 

the state (health) and persistence (dynamism) of a given sandbar over time?

4. How does generalized sandbar morphology differ as a result of high flows with different 

hydrograph shapes (magnitudes, durations and asymmetries)? Specifically, downramp 

rate affect sandbar slope? Answering this question requires more frequent topographic 

data (i.e. multiple DEMs associated with different downramp rates) from sandbars at sites 

with a range of hydraulic and geological settings, hitherto unobtainable due to a 

technological shortfall that will be addressed with the SfM technique.

Rationale/Justification

This high-priority research will augment the data from, and inform sampling strategies for, 

long-term sandbar monitoring. The long-term time-series of sandbar areas and volumes at select 

sites throughout Grand Canyon is a vital resource for examining the long-term health of sandbars 

and the impacts of management strategies. Such time-series can be used to assess the 

95
effectiveness of individual management strategies such as controlled floods, develop data-driven 

models for sandbar behavior, and monitor campsite quality and area through time. 

The set of 47 sandbars measured annually by topographic survey is a small sample of the 

more than 1300 large eddies in the CRe, and is biased towards larger, more stable, sites. Recent 

efforts to evaluate the representativeness of sand volumes derived from these bars have indicated 

that the established long-term monitoring sites may adequately represent mean sandbar volume 

in lower Marble Canyon for some time intervals, although the variance is inadequately 

represented by the set of long-term monitoring sites. Because of this, and because more 

monitoring sites are located in lower Marble Canyon than other reaches, it is likely that the 

frequency of monitoring sites in lower Marble Canyon is a minimum. There remains a pressing 

need to develop a representative sandbar sampling design. Our analysis suggests that up to 60 

additional sites could be required to achieve the same frequency of monitoring sites in all reaches 

(see Project Element 3.1.1). Thus, the primary motivation for this project is to develop methods 

for measuring sandbars that would enable an increase in the number of bars monitored without a 

corresponding increase in field effort and expense. In practical terms, this means testing whether 

it is possible to survey any given exposed sandbar in something on the order of 20-30 minutes in 

the field, as opposed to 3 to 6 hours in the field per bar with traditional methods. 

Having a means by which to rapidly map any sandbar, at any time during daylight, using 

non-specialist equipment (a consumer-grade camera) would be an extremely useful tool with 

which to augment current sandbar mapping activities with minimal cost. The use of remote 

cameras to estimate sandbar areas (Project Element 3.1.1) is limited in scope to the specific sites 

at which these cameras are installed, and the specific time at which the photograph is taken 

(which needs to be programmed into the camera system in advance). The use of the remotecamera imagery to construct a sandbar volume (above a given stage) also requires large 

fluctuations in flow. The SfM technique, in contrast, could conceivably be used at any site to 

map sandbar volume of the aubaerial portion of the bar at that time. Monitoring certain sites with 

greater frequency would find several applications at the event-scale, such as monitoring bar 

slumping processes, erosion due to boat wake, or during experimental high flows. 

The method we propose to evaluate is photogrammetric technique commonly known as 

Structure-from-Motion (SfM). The SfM technique is a method for constructing a 3-dimensional 

surface (map) from a set of oblique photographs of the same area taken from different 

perspectives. The method is so-called because the 3D position (structure) of features present in 

multiple images can be recovered from acquiring imagery by moving the camera relative to the 

scene (motion) so that multiple perspectives are achieved. The process is also able to render the 

images onto the DEM to create a DSM (Digital Surface Model, which in this case is a DEM 

overlain with the image pixels in the correct 3D location) which could be invaluable for mapping 

useful attributes other than elevation that are not obtainable using conventional surveying 

techniques, such as vegetation (from image color), and even grain-size estimates of the sediment 

surfaces (from image texture, using techniques similar to Black and others, 2013). The 

algorithms for processing the images exist and are available in commercial software: the purpose 

of this project would be to implement those existing techniques using that software, evaluate the 

products (DEMs) with conventional survey techniques (Wheaton and others, 2010), and develop 

a work flow to facilitate implementation of the technique to monitoring sandbars in the CRe. 

Methods

96
The majority of the work will be carried out by a graduate student at Utah State University 

under the primary supervision of Joseph Wheaton, with co-advisement by Paul Grams and 

Daniel Buscombe of the USGS/GCMRC. The student will familiarize him/herself with powerful, 

and expansive (scriptable), commercial SfM software (e.g. Agisoft Photoscan) as well as opensource software implementations of SfM (e.g. VisualSfM); carry out a number of trials in 

controlled conditions in order to assess the accuracy and precision of digital surface models; and 

develop protocols for photo collection such as, but not limited to, (1) the number and angular 

spread of images; (2) the requirements for vantage and perspective; (3) the degree of overlap 

between images; (4) the minimum amount of ground control points required, and (5) the effects 

of light conditions and surface textures on the photogrammetric solution. Some of these issues 

have been discussed in a general sense by recent articles in the geomorphology literature (for 

example, James and Robson, 2012; Westoby and others, 2012; and Fonstad and others, 2013) but 

the specific requirements and sensitivities for landforms with the range of scales of sandbars 

would need to be addressed. 

The student will then systematically photograph sandbars in Grand Canyon during annual 

sandbar monitoring trips, during which time the same bars will be mapped using conventional 

total station surveys, which are highly accurate but low in spatial resolution (of the order 1 

measurement per several square meters). SfM provides point clouds at or near the spatial 

resolution of the photographs which, depending on factors such as the camera specifications, and

the range to the objects in the scene, is of the order tens to thousands of measurements per 

several square meters. Therefore, SfM-derived DEMs need to be down-sampled in order to 

compare with total-station-derived DEMs. To quantify the accuracy of SfM at its native 

resolution, a subset of bars will also be surveyed using ground-based LiDAR (up to millions of 

measurements per several square meters). These data will then be down-sampled to the average 

resolution of the SfM-derived DEMs. These data will be worked up into image-derived and 

conventional DEMs, and the accuracy of the SfM technique for sandbars will be assessed 

through extension of surface uncertainty estimation techniques in the GCD software. The 

precision of DEMs from the SfM technique will be assessed by comparing DEMs of the same 

sandbar(s) using different sets of photographs collected in the field.

One potential challenge associated with photogrammetric mapping of sandbars in Grand 

Canyon is the effect of strong sunlight and shadows, which may limit the success of SfM at pixel 

matching in areas of low contrast. This will be tackled directly by collecting images of the same 

bar from the same locations at several times during the same day. Another problem will be 

obtaining sufficient vantage to photograph from, so each bar will be photographed from a 

number of different relative elevations and viewpoints. The sensitivities of the technique to 

factors such as the number of images and angular spread of camera positions (the collective noun 

for these factors we term, the scene geometry) will be assessed by creating a DEM for each 

permutation of photographs of a scene in a collection, then organizing DEM errors (relative to a 

benchmark data set obtained by total station and/or LiDAR) by each factor in the scene 

geometry. Each set of images will be worked up and their accuracy assessed reference to 

benchmark data (e.g. total station and ground-based LiDAR surveys). To address the potential 

issue of insufficient image texture over the smoothest surfaces, the texture of these surfaces will 

be enhanced using a number of standard camera settings and image processing algorithms 

designed to enhance image contrast.

Outcomes and Products – FY15

97
• Presentation at annual reporting meeting on project progress.

Outcomes and Products – FY16

• Presentation at annual reporting meeting on project progress. 

• Report/journal article on application of the SfM method to measuring sandbar 

topography.

• SfM sampling protocol

Outcomes and Products – FY17

• Presentation at annual reporting meeting on project progress. 

• Report/journal article on sandbar topographic change measured by SfM.

• SfM extensions to GCD and existing SfM software, as well as stand-alone software 

required to facilitate efficient post-processing of imagery and change detection analysis. 

Project Element 3.1.4. Analysis of historical images at select monitoring sites 

(Recommended for funding FY15: $89,003)

Joseph E. Hazel, Jr., Research Associate, Northern Arizona University

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Robert Weber, Photogrammetrist, Pinnacle Mapping Technologies, Inc.

Objectives

1. Extend sandbar area and volume long-term monitoring measurements to include data 

points from 1984 for a select set of sites.

2. Interpret the sandbar area and volume measured from photogrammetrically-derived 

topography with regard to unplanned floods that occurred prior to October 1984, and in 

the context of measured sandbar response to HFEs since 1990.

3. Incorporate completed 1984 sandbar data into sandbar database and interactive website 

(Project Element 3.1.1).

Hypotheses/Questions

1. To what extent were sandbars larger in area and volume following the largest post-dam 

flood (the 1983 flood) than following recent HFEs? 

2. What can the 1984 post-HFE area and volume measurements for a select set of sites 

inform us about sandbar behavior? 

3. Can analysis of digital photogrammetry improve our understanding of sandbar change 

over time and improve analysis of the long-term monitoring record? 

Rationale/Justification

Our understanding of the long-term trends in sandbar size and abundance is limited by the 

lack of detailed measurements made before the era of environmental management in Grand 

Canyon that began in 1990. Our understanding of resource responses prior to the current sandbar 

monitoring efforts is based on limited observations of sandbars following the floods of 1983-86 

(Schmidt and Grams, 2011). However, those generalizations of sandbar behavior are based 

largely on imprecise photo comparisons and are not quantitatively tied to the current sandbar 

monitoring program. The purpose of this research activity is to extend the temporal monitoring 

record for the long-term sandbar monitoring sites (Project Element 3.1.1) by incorporating data 

98
from aerial photography taken before 1990. In FY13–14, we investigated the possibility of 

extending the long-term sandbar monitoring record (Project Element 3.1.1) by orthorectifying 

historical aerial images acquired in October 1984 for a selected set of sites. These images were 

then used to create a three-dimensional topographic surface using digital photogrammetry 

technologies and software. 

The feasibility of using digital photogrammetry to orthorectify photographs and generate 

digital elevation models (DEMs) of sandbars in Grand Canyon was initially examined by Blank 

(2000) and O’Brien and others (2000). At the time, the computer-based software and 

technologies did not result in photogrammetric surfaces sufficient for detecting significant 

change in sandbar elevation of less than 25 cm. Recent advances in photogrammetry computer 

software and high accuracy digital scans made from the original negatives collected during the 

aerial overflights have made digital terrain extraction economically feasible and with 

uncertainties more appropriate for change detection and comparison with historical sandbar 

surveys made during the 1990s and 2000s. This project element builds on the work of Blank 

(2000) and O’Brien and others (2000) and utilizes improved methods to derive topography for 

selected sandbar study sites in Glen, Marble, and Grand Canyons.

In FY13, digital terrain extraction and analysis of the results were made at 8 study sites. 

These results were presented at the Annual Reporting Meeting in January 2014. The DEMs 

generated from the 1984 images have a surface uncertainty of 25 cm or less. Thus, we can 

confidently use the DEMs to determine sandbar volume and area using similar methods for that 

of the NAU sandbar monitoring project. This has been accomplished at 7 of 8 study sites. Initial 

findings are that sandbar area and volume above the stage elevation of 8,000 ft3

/s was greater in 

1984 than that measured in 2013 at four of the 7 sites. One sandbar (the Saddle Canyon site at 

RM 47) was 70 percent greater in area and volume in 1984; the other sites were 10 to 50 percent 

greater in size. The remaining sites were smaller in 1984 than present. While the sample size is 

small, these results are encouraging for temporal extension of the sandbar monitoring time series 

to 1984, as well as other years of interest. These results only provide tentative support for the 

hypothesis that sandbars were larger in 1984 than present, as almost half of the bars analyzed 

were smaller compared to present. Analysis of additional monitoring sites is required to provide 

a more complete picture of sandbar size following the 1980’s floods for comparison with sandbar 

size following recent HFEs.

In order to determine the accuracy of the photogrammetrically-derived volumes, we are 

currently investigating a method that will allow us to better test the image-derived DEMs against 

actual ground surveys for four of the long-term monitoring sites previously processed in FY13. 

Because there have been not been independent topographic surveys made with conventional 

methods at the same time as the collection of aerial photography, it is important that the same 

methods developed in FY13–14 be applied to photographs taken within a week or two of a total 

station sandbar survey. This would allow determination of the elevation and volumetric error 

associated with the techniques utilized in the study. We have identified two possible photography 

datasets with which to make this comparison: May 1994 and September 1996. Both data sets 

meet the requirements needed to be usable for comparative purposes as they were collected at 

scales similar to the October 1984 film (1:4800 vs. 1:3000), and during similar dam releases (226 

m3

/s vs. fluctuating between 144 and 226 m3/s). We anticipate that most or part of this accuracy 

assessment work can be completed in FY14. 

In this Project Element, we propose to continue this work by processing an additional 4 sites 

each fiscal year. In order to successfully process the 1984 photography, we plan to obtain the 

99
necessary ground control points for each proposed site. These data will be collected as part of 

other field efforts described in this project (Project Elements 3.1.1 and 3.2), and potentially as 

part of other collaborative field work efforts. Thus, this project does not have any stand-alone 

logistics expenses.

By the end of FY17, we anticipate to have up to half of the long-term monitoring sites 

processed and analyzed for volumetric change using the October 1984 photographs. Continuing 

to extend the long-term sandbar monitoring time series back to the early 1980s will provide 

additional information needed to assess the condition of sandbars prior to ground survey data 

collection in Glen, Marble and Grand Canyons. The addition of derived topographic surfaces 

from the 1984 photographs, in conjunction with selected historical surveys will help better 

inform us on sandbar response to dam operations prior to the 1990s.

Outcomes and Products

• For each completed site:

o Spatial Data: Geodatabase feature class and shapefiles for ground control points 

and digital terrain model (point cloud), triangular irregular network (TIN) 3D 

surface derived from point cloud, 25-cm interpolated DEM, and a mosaicked, 

orthorectified image file of 1984 imagery. 

o Ancilliary data: Photogrammetry block file and triangulation reports, digital 

terrain model extraction report, vertical and horizontal accuracy assessments of 

final data sets, volumetric and cross-sectional comparison graphs, and summary 

reports containing all the above information for each site.

• Final Report/journal article in FY17 on historical sandbar condition for all sites 

processed.

Project Element 3.2. Bathymetric and Topographic Mapping for Monitoring Long-term Trends in Sediment 

Storage 

(Recommended for funding FY15: $459,964)

Paul Grams, Research Hydrologist, USGS, GCMRC 

Daniel Buscombe, Research Geologist, USGS, GCMRC

Matt Kaplinski and Joseph Hazel, Research Associates, Northern Arizona University

Bob Tusso, Hydrologist, USGS, GCMRC

Keith Kohl, Surveyor, USGS, GCMRC

Michael Yard, Fishery Biologist, USGS, GCMRC

Objectives

1. Complete the first (baseline) high-resolution bathymetric map of Glen Canyon (RM -15 

to RM 0) in 2015.

2. Complete a repeat bathymetric map the long reach from RM 0 to RM 30 in 2016, with a 

coverage matching that when the reach was first mapped in 2013.

3. Complete the first (baseline) high-resolution bathymetric map of the long reach from RM 

166 to RM 225 in 2017.

100
4. Implement a recently developed acoustic bed-sediment classification method using 

multibeam sonar data, by factoring in grain size in estimates for changes in sand storage, 

and in order to better constrain uncertainties in calculated sediment budgets.

5. Report on changes in sand storage in the reach between RM 60 and RM 87, mapped in 

2011 and repeat mapped in May 2014.

6. Report on changes in bed elevation in Glen Canyon, based on comparisons between 

cross-sections last surveyed in 2000 and data from mapping that is scheduled for 2015 

(Objective 1).

7. Continue development of methods for classification of bed sediments using multibeam 

sonar backscatter data. In particular, develop means by which it is still possible to classify 

bed sediments reliably in the presence of significant coverage of submerged vegetation, 

such as in Glen Canyon. 

8. Develop and implement methods to estimate sand thicknesses below the bed surface, 

non-intrusively (using acoustics) and which fit into existing channel mapping sampling 

protocols.

Hypotheses/Questions

1. Will HFEs and intervening dam operations result in a net increase in sandbar size at high 

elevation (above 8,000 ft3/s stage) and no net change in sand storage at low elevation 

(below 8,000 ft3/s stage)?

2. Where are locations of the major changes in sand storage? What is the relative proportion 

of storage change in the channel and eddies?

3. Has the bed of the river in riffles in Glen Canyon remained stable throughout the four 

HFEs that have occurred since 2000? 

4. Have pools in Glen Canyon continued to evacuate sediment since 2000?

5. Can we remotely sense the distribution of submerged aquatic vegetation using multibeam 

sonar backscatter and topography? If so, is it still possible to reliably distinguish between 

different sediment types (using the recently developed method of Buscombe and others, 

in review) in the presence of substantial vegetation? 

6. Is it possible to estimate submerged sand thicknesses using hydroacoustics, reliably and 

objectively, in order to better quantify absolute sand storage in the parts of the channel 

which are always submerged?

Rationale/Justification

In this section, we discuss the rationale for conducting channel mapping to monitor sediment 

storage in each of the 6 river segments between Glen Canyon Dam and Diamond Creek. Because 

this project is designed as long-term monitoring, it is necessary to discuss planned monitoring 

activities in a long-term context, provided below. In summary, we propose to map one channel 

segment in each of the 3 years of the FY15–17 work plan. These segments are Glen Canyon (RM 

-15 to 0) in 2015; upper Marble Canyon (RM 0 to 32) in 2016; and west-central Grand Canyon 

(RM 166 to 225) in 2017. The mapping of the segments in Marble Canyon and Grand Canyon 

will track long-term trends in sand storage with implications for maintaining and building

sandbars in those segments. A map of west-central Grand Canyon will provide the first baseline 

101
map of a segment downstream from RM 87. A repeat map of upper Marble Canyon will be used 

to evaluate changes in sediment storage in that reach between 2013 and 2016. The rationale for 

mapping Glen Canyon is somewhat different than the rationale for mapping the other segments 

and is discussed below.

Management objectives for fine sediment have focused on the condition of sandbars. Current 

management practice includes efforts to maintain and build sandbars using high flow releases 

that are timed to coincide with periods of fine-sediment supply from tributaries (HFE protocol 

EA). As described above in section C.1, the success of this approach is predicated on the 

maintenance of a sufficient supply of sand within the channel for rebuilding sandbars. The 

purpose of this sediment storage monitoring element of Project 3 is to track long-term trends in 

sand storage and thereby provide a robust measure of whether or not the supply of sand available 

for building sandbars is increasing, decreasing, or remaining stable over time-scales of years to 

decades. In other words, this project provides the direct measure of ∆S in equation (1) over the 

time scale of the HFE EA and the LTEMP EIS. Moreover, this project monitors those changes in 

sand storage by location, providing spatially explicit quantification of the changes in the channel 

and eddies (∆Slow in equation 2) and sandbars (∆Shigh in equation 2).

The greatest challenge in developing an appropriate monitoring program is the scale of the 

area of management interest, which is the entire CRe from Glen Canyon Dam to Lake Mead. As 

described above, previous efforts have demonstrated that measurements of sediment storage 

change made in short reaches cannot be extrapolated to determine sediment storage throughout 

the CRe. In spring 2012, we repeated the RM 30 to 61 long reach which was first mapped in 

spring 2009. A spatially explicit analysis of the differences in channel sediment storage once 

again demonstrated that the large local variability in bed response found almost everywhere 

necessitates sampling a large proportion of the river channel. 

The “long-reach” sampling design used in this project is based on analysis of previous 

channel bathymetry mapping efforts. Using the repeat maps made of short (< 5 km) reaches 

between 2000 and 2004, we investigated potential sampling strategies. This was accomplished 

by artificially subsampling the maps of topographic change that cover an entire 5 km short reach, 

using three different sampling strategies: (1) regularly spaced channel cross-sections; (2) 

randomly located channel cross-sections; and, (3) subsampling of major eddy storage locations. 

This analysis indicated that all of these sampling strategies result in error that is greater than 50 

percent of the actual change in storage, unless sampling intervals are sufficiently small such that 

the level of effort is equivalent to comprehensively mapping approximately 80 percent of the 

entire reach. Further, the analysis revealed that in order to estimate change in channel storage 

with an uncertainty of 50 percent of the observed value would require average cross-section 

spacing of 300 m or less, irrespective of whether the spacing is regular or locations are selected 

randomly. To achieve a similar level of accuracy by sampling eddy storage locations would 

require sampling more than 75 percent of those locations. Thus, to reduce the need for, and 

uncertainties associated with, extrapolation, the monitoring program consists of repeat mapping 

of most of the bed of the river for long segments. 

Although these comprehensive maps of the river bed provide the best measure of changes in 

sediment storage, mapping long river segments is a significant effort in terms of data collection 

and data processing. Within the scope of the current budget, it is possible to map and process 

approximately 30 river miles of channel per year. We have, therefore, developed a proposed 

schedule for mapping segments in rotation over the next 10 years that is based on the time 

frames of current and anticipated management actions. Because the segments in Marble Canyon 

102
and eastern Grand Canyon (Fig. 3.3) have the greatest risk of sediment deficit and because 

sandbar response has not been as strong in Marble Canyon as in downstream segments (Fig. 2), 

channel mapping efforts through 2014 have focused on these segments. The focus will continue 

to be on these segments for the next 7 years to provide monitoring needed to evaluate the HFE 

Protocol. By the conclusion of the first 10 years of the HFE protocol in 2021, each of these 

segments will have been mapped at least 3 times over the 10-year period. This will provide 

robust and spatially explicit quantification of the change in fine-sediment storage in each 

segment and a robust measure of the change in all sandbars in each segment. Each of these 

segments is approximately 30 river miles in length and it is possible to map most of the river 

bed, excluding rapids and riffles, resulting in maps of 80 to 90 percent of the deposits.

While an exclusive focus on the upstream 3 segments may be appropriate to address the 

monitoring needs of the HFE protocol, it does not fully address sediment-related AMP goals, 

which do not distinguish among river segments. There are very few measurements of the channel 

bed in the segments downstream from RM 87 and there are fewer long-term sandbar monitoring 

sites between RM 87 and RM 225 (Fig. 6). Without some direct measurements of changes in 

sediment storage and measurements at a larger set of sandbars than are monitored annually, it 

will be difficult to assess long-term trends in these segments. We, therefore, propose to collect 

baseline data within each of these segments within the next 5 years so that repeat maps may be 

made within the next 10 years. Because these segments are each 60 to 80 river miles in length, 

we anticipate mapping approximately 50 percent of each segment. Maps of these segments will 

be less comprehensive than the maps made for Marble Canyon and eastern Grand Canyon and 

there will be portions of these segments where changes in sediment storage will remain 

unknown. The maps will, nevertheless, provide a robust quantification of changes in sediment 

storage for the portions of the segments that are mapped providing much more information than 

provided by the sandbar monitoring alone.

The needs for long-term monitoring of sediment storage are different in the Glen Canyon 

segment than in the downstream segments. Because Glen Canyon is upstream from the Paria 

River, the sediment deficit in this segment is more severe than in the downstream segments 

(Topping and others, 2003). A series of high flows (pulse flows) released from the dam in 1965 

caused rapid degradation of the channel in most of the reach (Randle and Pemberton, 1976; 

Grams and others, 2007). Grams and others (2007) demonstrated that the pattern of degradation 

was different for riffles than in pools between riffles. The distinction between pools and riffles is 

important because degradation of riffles represents incision of the channel – lowering of the 

entire river bed. In riffles, the magnitude of degradation decreased with distance downstream to 

the point of zero degradation at the Paria Riffle near Lees Ferry. In addition, the rate of 

degradation decreased with time causing Grams and others (2007) to hypothesize that this 

process was complete by 2000, with the possible exception of locations within 1-km of the dam. 

In contrast to the riffles, pools more than 20 km downstream from the dam scoured as much 

or more than pools within 5 km of the dam. Pools continued to exhibit significant changes (scour 

in some locations, fill in others, with no systematic spatial pattern) in the most recent monitoring 

interval (1991-2000). Because bed lowering decreases the elevation reached by flows of a given 

discharge, near the dam the elevation reached by a discharge of 5000 ft3

/s decreased by more 

than 2 meters between 1956 and 2000 (Grams and others, 2007). Such changes affect many 

aspects of the aquatic and riparian ecosystems. Scour of sediment from pools, however, is not 

necessarily associated with channel incision, but instead represents changes in sediment storage. 

While the channel in Glen Canyon has experienced both incision and changes in storage, 

103
segments downstream from Lees Ferry have only experienced changes in storage (Grams and 

others, 2007). 

These changes were documented by repeat topographic/bathymetric surveys of more than 20 

monumented cross-sections that were originally established in 1956 for use in designing the dam 

and powerplant. A repeat survey was last made 14 years ago (Grams and others, 2007). The 

proposed mapping of the channel in 2015 will include a repeat survey of each of those channelcross sections. Given the legacy of data collection in Glen Canyon spanning several decades, a 

number of important scientific questions can be addressed using data from a single channel 

mapping campaign. These surveys will be used to evaluate two hypotheses. First, the 

measurements will be used to support (or refute) the hypothesis of Grams and others (2007) that 

the bed is stable in riffles. While it is believed that the channel is stable, continued scour is 

possible and would have important implications for aquatic habitat (see related biological 

projects, referenced below). Secondly, the measurements will be used to test the hypothesis of 

Grams and others (2007) that pools continue to evacuate sediment. These measurements will 

provide a valuable assessment of the stability of the channel bed and the status of sediment 

storage in pools early in the implementation of the HFE protocol. 

The mapping in Glen Canyon will also provide information required for several aquatic and 

fisheries related studies. A map of the Glen Canyon segment is enables mapping of the relative 

inundation frequency of trout spawning habitat (see Project 10); establishing flow-habitat 

relations necessary for studies of egg-laying and emergence behavior of aquatic insects (see 

Project 5); and parameterizing a model for primary production (see Project 9). 

In addition to collecting the data to address the questions described above, we also propose 

work on advancement of methods in two areas. First, we propose to expand our methods for 

mapping bed composition to include submerged vegetation. Given the importance that

submerged vegetation serves as habitat for fish and invertebrates (Riis and others, 2008) there is

a need to quantitatively examine the spatial distribution, diversity, and abundance of the

relatively diverse aquatic plant community found in Glen Canyon. We therefore need a reliable

method with which to non-intrusively document the distribution of submerged vegetation with a

large spatial coverage. Such a method needs to be able to: (1) remotely sense the water column 

and bed from a small boat; (2) distinguish vegetation from substrate; and (3) be spatially

referenced to enable repeat mapping for the purposes of monitoring. Currently there are no

standard methods with which to do this, however, we propose that the use of the multibeam 

sonar in the Glen Canyon channel mapping effort in 2015 is an ideal opportunity to overcome 

this technological shortfall, for the benefit of the long-term ecological goals of studies of primary 

production in Glen Canyon, and advancements in acoustic characterization of the composition of 

riverbeds in general for the purposes of habitat mapping as well as a number of physical goals.

The second advancement we propose involves measuring the thickness, in addition to the 

surface elevation, of sand on the river bed. This would involve testing low-broadband (known as 

‘seismic’) frequency sonars, which penetrate the bed to a much greater depth than the highfrequency sonars (singlebeam and multibeam echosounders) used to map the elevation of the bed 

surface. The aim is to develop a reliable means with which to estimate sand thicknesses below 

the bed surface, in order to better quantify the total volume of sand stored in a reach. In recent 

years, our continuing experience and expertise in the use of sonar mapping techniques has 

coincided with ongoing technological advances in sonar technology and the increasing use of 

sonars for estimating the thicknesses of submerged sediment deposits Frequency-modulated 

(FM, or CHIRP) sonars (Schock and others, 1989) provide higher resolution (a few cm compared 

104
with tens of cm) sub-bottom acoustic profiles with less signal-noise compared with traditional 

low-frequency sonars, have been used successfully to image subsurface stratigraphy within 

sedimentary deposits, typically up to 30m below the surface (e.g. Zeiler and others, 2000; 

Lafferty and others, 2006). Both the rate of attenuation of the echo strength with depth and the 

pattern of reflections revealed by concatenating subsequent profiles can be used to discriminate 

between sediment types. There are several established methods (e.g. LeBlanc and others, 1992; 

Kim and others, 2002; Schock, 2004; Rakotonarivo and others, 2011). Recent advances in bed 

surface sediment classification means that we can focus sampling efforts over known areas of 

sandy beds, making the problem of acoustic detection of sand thicknesses much more tractable. 

Information on sand thicknesses might also be a vital component in designing alternate sampling 

strategies for capturing the essential components of changes in sediment storage in a given reach. 

In other words, using sand thicknesses to estimate total sand volumes in a given reach might be 

critical in determining the return frequency to a given reach. It also provides much needed 

context for reported changes in sediment storage, by providing the means to begin to answer the 

question of what the proportion a reported sand storage change is of all sand stored in a given 

reach. 

Methods

It is not logistically feasible to map the entire river corridor in every segment. The goal of 

this work is, therefore, to map approximately 80 percent of each segment between Glen Canyon 

dam and RM 87 and approximately 50 percent of each segment between RM 87 and RM 225. 

Although it is not possible to identify all the important sediment storage locations prior to 

mapping, the effort is expected to include mapping of more than 90 percent of the large eddy 

storage locations upstream from RM 87 and at least 75 percent of those storage locations 

downstream from RM 87. We place greater emphasis on monitoring the three upstream reaches, 

because the most upstream reaches have greater sediment deficit and are, therefore, a greater risk 

for long term sand depletion. We further expect that, because these reaches have larger sediment 

deficit, storage changes are more likely to be spatially variable, requiring monitoring a greater 

proportion of each mass-balance reach. Each year, one of the five sediment budgeting reaches 

that are between 26 and 80 miles in length will be mapped such that each segment could be 

mapped twice in 10 years.

Table 3. Long sediment budgeting segments for long-term monitoring of sediment storage.

Segment River 

Miles

Completed 

surveys

Planned 

surveys

Short 

reaches*

Crosssections**Estimated 

proportion of 

reach 

mapping will 

cover

Repeat 

Interval

1 -15 to 

0

2000 (crosssections 

only)

2015 1 20 80 percent ~ 10 yr

2 0 to 

30

2013 2016, 

2021

2 41 80 percent 3 to 6 yr

3 30 to 

61

2009, 2012 2018, 

2023

3 17 80 percent 3 to 6 yr

4 61 to 2011, 2014 2020 2 39 80 percent 3 to 6 yr

105
87

5 87 to 

166

none 2019, 

2024

1 20 50 percent 5 to 10yr

6 166 to 

225

none 2017, 

2022

2 8 50 percent 5 to 10yr

* The number of short reaches 2 to 5 km in length that were mapped at least once between 2000 

and 2005 (Kaplinski and others, 2009).

** The number of cross-sections that were measured at least once between 1992 and 1999 (Flynn 

and Hornewer, 2003).

Because about 90 percent of the sand and finer sediment that is available for redistribution by 

dam operations is submerged (Hazel and others, 2006), the monitoring method must include 

measurements of the bed of the river in eddies and pools. Data collection will combine 

multibeam and singlebeam sonars, coupled with conventional topographic surveys for areas 

above the water surface. These methods have been described by Hazel and others (2008) and 

Kaplinski and others (2009; 2014) and were used extensively in monitoring the 2008 HFE (Hazel 

and others, 2010). Similar methods are used to monitor channel changes on other large rivers, 

including the Missouri River (Jacobson and others, 2009). The data will result in a high 

resolution digital elevation model of the mapped segments for each mapping effort. 

Upon completion of a repeat map of a segment, the maps (DEMs) will be compared to 

compute the net change in the volume of sediment within the segment. These computations will 

distinguish between fine and coarse sediment using recently developed acoustic sediment 

classification algorithms (Buscombe and others, in review), between sediment stored in the 

channel and eddies, and between sediment at high- and low-elevation. The methods of 

Buscombe and others (in review) uses multibeam sonar backscatter (echo strengths) to 

distinguish between homogeneous sand, mixed sand and gravel, and homogeneous gravel (Fig. 

10). These data are collected in conjunction with soundings used to compute bathymetries; 

therefore no additional data collection is required. The resulting maps of bed sediment substrates 

are as highly resolved as the bathymetric maps. Methods for bed-texture classification will 

continue to be developed in order for us to reliably distinguish between different substrate types 

(such as the relative proportions of sand and gravel in small areas), in order to make assessments 

of their relative mobility under a range of flows. 

One significant extension to the acoustic sediment classification methods of Buscombe and 

others (in review) is in being able to distinguish between sediment and submerged vegetation. 

We propose to use multibeam sonar backscatter data, collected as part of the Glen Canyon 

channel mapping effort in 2015, in conjunction with physical samples and underwater video 

surveys, to develop and test algorithms with which to reliably distinguish between sediments and 

vegetation. In so doing, we will have also developed a means by which to make a quantitative

assessment of the spatial distribution and areal cover (m2

) of submerged macrophytes,

bryophytes, and chlorophytes. Acoustics is, at least in theory, an ideal tool for mapping 

submerged aquatic vegetation because it is not limited by water clarity or deep water, and 

provides a much greater coverage, at higher resolution, in a fraction of the time compared with 

video surveys. 

106
Figure 10. Acoustic sediment classification 

at RM30, August 2013, using the methods 

of Buscombe and others (in review). The 

resolution of classification is 25 cm2

.

107
Ongoing analysis between sediment stored in the channel and eddies, and between sediment 

at high- and low-elevation, will incorporate more sophisticated estimates of uncertainty (e.g. 

Wheaton and others, 2010; Kaplinski and others, 2014) for which estimates of bed sediment 

grain size will also be a crucial component. In addition to making comparisons between years for 

which the entire segments are mapped, comparisons will also be made to earlier data were 

available (Grams and others, 2013). This will include comparisons to data collected in short 

reaches in 2000 to 2005, and data collected at monumented channel cross-sections (Table 3).

In 2016 and 2017 we will evaluate the use of sub-bottom, broadband low frequency 

(modulated in sweeps ranging from a few hundred Hz to a few kilohertz) acoustic CHIRP 

profilers to scope the feasibility of determining sand thicknesses below the bed. A number of 

different systems are available for rent. These sonars provide much greater resolution than 

previous generations of sub-bottom sonars, providing unparalleled detail on the sedimentary 

sequences down to several tens of meters. We propose to use these systems in areas of known 

sandy bed surfaces, and develop algorithms to detect sedimentary layers and acoustic 

attenuations with depth, towards an eventual goal of reliably estimating sand thicknesses.

Relation to Previous Work Plan

The approach in this work plan builds on the project from the FY13/14 work plan. The 

reaches proposed for mapping in 2013 and 2014 (Table 2) were completed successfully and 

those data are being processed according to schedule. The major reporting goal for the previous 

work plan was to report on changes in storage for the reach between RM 30 and RM 61. A 

preliminary report on this analysis was provided at the January 2014 reporting meeting and the 

final analysis and reporting is in preparation with submission for review expected by September 

2014. A major goal of the previous work plan was the development of automated methods for 

bed material classification (FY13–14 Project Element A.2.2). This was needed to determine the 

proportion of the river bed covered by sand and the proportion covered by other substrate, in 

addition to the utility to other projects for habitat characterization. That project will be 

successfully completed by the end of 2014 (Buscombe and others, in review) and is therefore not 

included in this work plan. The methods developed in that project will be used in this project and 

will continue to be refined and improved upon.

Outcomes and Products – FY15

• Presentation at annual reporting meeting. 

• Report and maps for RM 0 to 30 (mapped in 2013).

• Report and maps for eastern Grand Canyon (RM 61 to 87, mapped in 2011 and 2014).

• Report/journal article on geomorphic changes in eastern Grand Canyon, 2011 to 2014.

• Report/journal article on incorporating spatially explicit, high resolution, bed sediment 

maps in calculations of morphologic based changes in reach-scale sediment storage 

Outcomes and Products – FY16

• Presentation at annual reporting meeting.

• Report and maps for Glen Canyon (scheduled to be mapped in 2015). 

• Report/journal article on geomorphic changes in Glen Canyon, 2000 to 2015.

• Report/journal article on acoustic detection of submerged aquatic vegetation.

Outcomes and Products – FY17

108
• Presentation at annual reporting meeting. 

• Report and maps for upper Marble Canyon (scheduled to be repeat-mapped in 

2016).

• Report/journal article on geomorphic changes in upper Marble Canyon, 2013 to 

2016.

• Report/journal article on long-term trends at the sandbar monitoring sites.

• Report/journal article on the use low frequency sonars to estimate sand 

thicknesses below the surface.

Project Element 3.3. Characterizing, and Predictive Modeling, of Sandbar Response at Local and Reach Scales 

(Recommended for funding FY15: $100,787)

Erich Mueller, Research Hydrologist, USGS, GCMRC

Mark Schmeeckle, Professor, Arizona State University

Daniel Buscombe, Research Geologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

David Varyu, Hydraulic Engineer, Bureau of Reclamation 

Graduate Student

Objectives

1. Develop groupings of sandbars based on existing measurements of sandbar response and 

the geometry of fan-eddy complexes. Grouping sandbars that function similarly will 

allow us to use these groupings to model generalized eddy hydraulics and 

morphodynamics (two-way feedbacks between morphology and flow) as part of 

Objective 2 and document statistically the physical factors most important to different 

sandbar behaviors for the empirical parametric model in Objective 3.

2. Continue the development and testing of a 3-dimensional large-eddy simulation (LES) 

model for coupled streamflow, sediment transport, and sandbar morphodynamics in 

eddies. 

3. Develop a new parametric (driven by simple, measurable physical parameters) statistical 

model for sandbar response to high flows and intervening flows over decadal timescales 

which is based on the existing sandbar monitoring dataset. 

Hypotheses/Questions

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1. What are the typical sandbar morphologies associated with specific fan, channel, and 

eddy geometries? How do different fan-channel-eddy geometries influence the observed 

differences in sandbar behavior? Can we develop groupings of bars from a synthesis of 

existing data sets on sandbar form and dynamics?

2. Are differences in sandbar response driven by the topographic boundary conditions of a 

given reach, or more strongly linked to flow and sediment supply boundary conditions? 

To answer this question, can we use a topographically flexible form of the 3-dimensional 

LES model to assess the dominant controls between sites?

3. What has been the cumulative response of sandbar size (volume and area) to high flow 

experiments and intervening flows, and how can we parameterize this information 

statistically or semi-mechanistically to serve as the basis for a predictive model for 

average or aggregate sandbar responses to future flows? Can we predict the response of 

individual bars, or groupings of bars that behave similarly, using a comparable modeling 

approach? 

Rationale/Justification

Characterizing and predicting sandbar response to varying flow and sediment inputs over 

long reaches or at individual sites, based on mechanistic or empirical models, has long been a 

desired research and management goal. Continued advances in computational efficiency 

combined with long-term data on sandbar and channel morphology collected as part of the 

monitoring program, allows us to advance our understanding of eddy sandbar dynamics beyond 

what has previously been achieved. The long-term monitoring data includes more than two 

decades of sandbar measurements (Project Element 3.1.1), topographic measurements of the full 

river channel for long reaches (Project Element 3.2), measurements of sandbar grain size (Project 

Element 3.2), remote camera images (Project Element 3.1.1), remotely-sensed data of sandbar 

distributions throughout the CRe (Project Element 3.1.2), and over a decade of sediment flux 

monitoring (Project 2).The work proposed in this project element is motivated by several 

observations: (a) both immediate sandbar response to HFEs, and longer-term response to 

intervening dam operational flows, differ between eddies, sometimes over very short distances 

where discharge and sediment supply conditions are likely similar; (b) this difference in sandbar 

response must result from spatial differences in the coupled hydraulic and sediment transport 

processes that result in differing rates of erosion of, and/or deposition on, sandbars during 

different discharges and sediment supply conditions; and (c) understanding differences in 

sandbar responses may be made more tractable by generalizing responses into groupings of bars 

based on fan, channel, and eddy geometries. The latter of these provides a basis for 

understanding how much a change in river geometry influences sandbar depositional and 

erosional processes. In this proposal, we approach this problem spatially by comparing measured 

sandbar response to the characteristics of different fan-eddy complexes throughout the river 

corridor. 

Sandbars in Marble and Grand Canyon are formed primarily in zones of recirculating current 

(eddies) downstream from channel constrictions created by debris fans at the mouths of tributary 

drainages (Howard and Dolan, 1981; Schmidt, 1990; Schmidt and Graf; 1990; Melis, 1997). The 

interaction between stream flow and channel topography is the dominant control on flow 

hydraulics in rivers, and, in turn, the interaction of flow hydraulics with the bed sediment causes 

sediment transport and patterns of erosion and deposition. Thus, the location of, and 

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morphodynamic changes to, eddy sandbars is strongly dictated by interactions of the river’s flow 

with coarse-grained debris fan deposits. There is a wide range in eddy sandbar response to 

different dam operations and to floods (Schmidt and Graf, 1990; Beus and others, 1992; Hazel 

and others, 1999; Hazel and others, 2010; Schmidt and Grams, 2011). This variability may 

reflect sampling design, differences in reach-scale sand supply, or a difference in hydraulic 

characteristics between eddies. Recently, Grams and others (2013) showed that local variability 

in sediment storage in short (2.7 – 4.7 km long) reaches is at least as large as the variability 

between reaches in Marble Canyon. They conclude that, because sediment supply conditions are 

likely not changing appreciably over short reaches, local flow hydraulics are the dominant factor 

causing differences in response. For example, at some sites sand storage increases with 

discharge, and at others sand storage decreases with discharge (Fig. 11). There is no downstream 

trend favoring one type of site behavior, and sites very near each other may show the opposite 

correlation with discharge (Fig. 11). 

The work of Grams and others (2013) and the results shown in Figure 11 suggest that local 

differences in flow hydraulics must be a dominant factor influencing how site-scale fine 

sediment storage changes in response to changing discharge conditions, but does not link these 

differences among sites directly to feedbacks between fan-eddy geometry and channel 

hydraulics. Thus, the purpose of Objective 1 is to link the observed measurements of sandbar 

change to topographic, hydraulic, or geomorphic metrics of the larger fan-eddy complexes, 

which then can be used to develop groupings of eddy sandbars that are functionally similar. 

Previous researchers have described several metrics of fan, channel, and eddy characteristics 

(e.g. Schmidt, 1990; Schmidt and Graf, 1990; Melis, 1997; Hazel and others, 2010). For the 

channel, these include the constriction ratio, expansion ratio, recirculation zone length, 

constriction length or total length of the rapid, eddy size, stage change with discharge, 

divergence angle or jet angle (Fig. 12), water surface slope, and changes in depth between the 

constriction and expansion. Several other metrics describe the geometry of the fans impinging on 

the channel, including fan spacing, fan shape, and fan height (Schmidt and Graf, 1990; Melis and 

others, 1995; Melis, 1997). The size and occurrence of sandbars is also related to changes in 

canyon width caused by changes in river-level bedrock (Schmidt and Graf, 1990). These changes 

in canyon width often co-occur with changes in the characteristics and distribution of debris fans 

impinging the flow of the river (Melis, 1997), and provides a framework for aggregating 

individual site scale data (Schmidt and Grams, 2011). Preliminary results (P. Grams, unpublished 

data) show that there is no simple correlation between measured changes in sandbar volume and 

many of these parameters. Thus, more robust statistical methods or new metrics are needed to 

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define possible empirical relationships that can be linked to river processes. 

Figure 11. Left) Changes in observed total sand storage as a function of recent discharge for two of the long-term 

monitoring sites. Right) Downstream trends in the correlation coefficient, R, of the discharge-sediment storage relations. 

Positive (negative) values indicate increases (decreases) in sediment storage with discharge; closed (open) squares are 

locations where the regression is (is not) significant.

Metrics of fan, channel and eddy geometry or other hydrologic parameters that relate to 

changes in sandbar size provide proxies for changes in flow hydraulics and sediment transport 

processes in fan-eddy complexes. In Objective 2, we propose to link differences in topographic 

boundary conditions to sandbar response using a large eddy simulation (LES) model; LES is a 

mathematical technique that allows large-scale turbulence to be directly computed in numerical 

hydrodynamic models. Work currently in progress (FY13–14 Project Element A.3) includes 

development of a new 3-dimensional LES model for flow and sediment transport in eddies of the 

Colorado River. The hydraulic (streamflow) component of the model has been validated 

(Alvarez and others, 2013; Alvarez and others, in prep.). More recently, components that allow 

for computation of sediment transport and bed morphodynamics have been added to the model. 

The LES approach has revealed the importance of using both a three-dimensional and timedependent model in lateral separation eddies. The model shows that the difference in direction of 

surface and near-bed flow vectors and low-frequency variation of the strength of the eddy 

recirculation current are key features necessary to model the import and export of sediment from 

sandbars. Work is in progress to use the validated flow model in a topographically-flexible form 

to evaluate the effect of differences in channel geometry on temporal and spatial patterns of 

sandbar deposition and erosion. From our empirical analysis relating sandbar form and change to 

fan-channel-eddy geometry (Objective 1), we intend to develop groupings of sites that can be 

modeled using the flexible form of the LES model. The LES modeling will therefore elucidate 

the flow hydraulics and sediment transport processes important to different sandbar behaviors.

The last goal of this project is to develop a more generalized predictive model for average or 

aggregate sandbar responses to future flows (Objective 3). This is a challenging goal for a river 

corridor as long and varied as the Grand Canyon, thus progress is incremental, but would be of 

great use for resource management. Previous efforts to model individual or aggregate sandbar 

response have had mixed success. Models for streamflow and sediment transport for individual 

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eddies have been used to successfully evaluate the rate of sandbar deposition during high flows 

(Wiele and others, 1999) or following tributary inputs (Wiele and others, 1996). More recently, 

Wiele and others (2007) constructed a reach-averaged model for streamflow, sediment transport, 

and sandbar response. This model used 1-dimensional flow and sediment transport relations to 

predict downstream changes in sediment mass balance to drive sandbar erosion and deposition. 

The processes of sandbar erosion and deposition were based on empirical relations with flow and 

eddy properties derived from 2-dimensional model outputs from a subset of eddies. The model 

results generally agreed with measurements of sand flux and suspended sediment grain size, but 

consistently under-predicted the magnitudes of sandbar response, evaluated against that 

measured at the long-term monitoring sites. An advantage of the approach used in the Wiele and 

others (2007) model is that it is physically-based. A disadvantage is that it does not provide a 

means to predict the response of individual bars or groupings of bars that may be of interest to 

managers. Another modeling approach was developed for the analyses of the LTEMP EIS 

alternatives that is highly empirical and is parameterized with the observed sandbar volume data. 

This approach matches the overall trend in the sandbar volume data series, but suffers from a 

parameterization whose physical meaning is unclear, and seeks to model all sandbars as a single 

representative sandbar for all of Marble Canyon.

While the approaches above address the problem from different perspectives, neither 

approach allows for a prediction of the behavior of individual bars, nor groupings of similar bars, 

to different flow and sediment supply scenarios. This simplification has been made because (1) 

we lacked the information necessary to address variability among the many different sandbars 

and, (2) we lacked a reasonable means to extend modeling efforts to the many sandbars for 

which no monitoring information was available. For example, Wiele and others (2007) used data 

through 2004 in their model, and the availability of many new data sets in the subsequent decade 

will allow us to develop a more data-driven model of sandbar response for either individual bars, 

or groupings of similar bars. These data sets include suspended sediment monitoring 

(http://www.gcmrc.gov/discharge_qw_sediment/), the Wright and others (2010) shifting rating 

curve model of sand transport, bathymetric surveys of the channel bed (Kaplinski and others, 

2014), surveys of sandbar volumes (Hazel and others, 2008), an extensive time series of remote 

camera images of sandbar change (http://www.gcmrc.gov/gis/sandbartour2013/index.html), and 

remotely sensed data from the entire CRe (Project Element 3.1.2). Furthermore, results from our 

empirical analysis of sandbar groupings and from the three-dimension LES modeling will allow 

for a more robust characterization of the functional form of process-response relationships 

important to sandbar deposition and erosion. For example, can we use the long-term sandbar 

surveys to develop robust relationships between sandbar volume and area, which could be used 

to extend modeling efforts to sandbars that have only be characterized with aerial photos? Can 

we improve functional relations between discharge or eddy characteristics and magnitudes of 

sandbar erosion and deposition, building on the work of Wiele and others (1999, 2007)?

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While a collection of sites have been monitored for almost 25 years, these represent only a 

very limited subset of all sandbars which may not be representative of the dynamics of all bars 

(hence Project Elements 3.1.2 and 3.1.3). Thus, if a parametric (data-driven) model is based on 

the data from, but is designed to apply to more than these few sites, it must include some 

provision for extrapolating to a larger number of sandbars without being overly sensitive to the 

specifics of any given bar. What limits an ad hoc approach to this scaling is the diversity in 

sandbar responses to the same flow and sediment conditions, owing to complex relationships 

between sandbar morphology and streamflow, suspended sediment concentration, bed sediment 

grain size, fixed channel geometry, and existing sandbar morphology. Objective 2 allows us to 

address these different factors mechanistically using the LES model, while Objectives 1 and 3 

will allow us to develop more sophisticated approaches using our growing body of information 

to build a more generalized statistical or semi-mechanistic model of sandbar response to high 

flows and intervening flows over event- to decadal-timescales, building on the work of previous 

scientists. Objective 3 will include collaboration with Bureau of Reclamation (BOR) engineers 

who developed the empirical model for the LTEMP EIS. 

Methods

Objective 1: 

In the first phase of our analysis, we will identify groupings of sandbars based on 

morphological properties and temporal response to different flow regimes using the long-term 

sandbar data set. As a first step, we will group those sandbars that exhibit similar discharge to 

sandbar volume relationships (Fig. 11); for example, those sites that show positive, neutral, or 

negative relationships would form the initial groupings. We will also use a statistical clustering 

(dimensionality reduction) approach on sandbar metrics such as volume, area, thickness, slope, 

planform shape metrics, concavity, and grain size, and/or the persistence and time-derivatives of 

these quantities to determine whether these metrics allow for additional groupings (or clusters) of 

bars. Once we have established different bar groupings, we will use a statistical analysis of 

variance (ANOVA) technique to determine which hydrologic or geomorphic metrics separate the 

groups. Many of these metrics (listed above) have already been determined for many of the faneddy complexes that are part of the long-term sandbar data set (e.g. Schmidt and Graf, 1990; 

Hazel and others, 2010), and we will formalize a database with these metrics for each sandbar 

site. This will include defining these metrics where they do not exist, and developing new 

metrics for each site. Previous researchers had only limited data on the topographic form of the 

submerged portion of the channel bed, which must be an important control on flow hydraulics in 

the eddy recirculation zone, and is a primary input into the LES model of Objective 2. Thus, new 

metrics will include those developed from detailed measurements of the full river channel 

topography over long reaches collected over the last decade and continuing in Project Element 

3.2. For example, we can define the dimensions of the main channel scour zone (labeled “pool” 

in Fig. 3.12a) adjacent to recirculation eddies relative to the average bed elevation in the flow 

expansion. Once we have a complete database of sandbar and fan-channel-eddy metrics, we can 

analyze the data set systematically for statistically significant relationships. 

For sites where the full reach channel mapping has been repeated, such as Lower Marble 

Canyon, we can assess whether the groupings developed from the long-term NAU sandbar 

monitoring sites are appropriate for aggregating sandbar behavior in longer reaches. In addition, 

Project Element 3.1.2. will provide a comprehensive “large eddy dataset” of sand area and 

volume in 2002, 2009, and 2013 for 1300 eddies throughout the river corridor using remote 

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sensing; a base map of geomorphic deposit types, including debris fans, eddies, and sandbars, 

will also be created. These data will initially be used to assess the representativeness of the NAU 

sandbar sites, in terms of sandbar area and volume or changes in these quantities, for different 

geomorphic reaches throughout the river corridor. Depending on the outcome of the sandbar 

grouping analysis at the NAU sites, these data may also be used to extrapolate or validate these 

groupings for long reaches based on fan, channel, or eddy characteristics and corresponding 

sandbar characteristics. 

The outcome of this objective will feed into the next objective, which is to investigate the 

generalized flow hydraulics and sediment transport processes associated with the different 

groupings of eddy sandbar types. We will relate differences in measured channel geometry 

between sites to the identified sandbar groupings. We will then incorporate several generic 

channel geometries into the LES model that are representative of the major sandbar groupings. 

This will allow us to link the topographic boundary conditions (as determined by channel 

geometry) to processes of erosion and deposition in eddies, and compare these results to the 

observed changes in sandbar size and shape. Together, the results from Objectives 1 and 2 will 

provide insight into the important physical processes and their functional forms for incorporation 

into Objective 3.

Objective 2: 

The goal of this effort is a physically-based numerical model capable of predicting sandbar 

size (area and volume) and morphology (shape) given routinely measured or modeled 

streamflow characteristics, suspended sediment supply, and sandbar configuration. Because of 

the temporal and/or spatial resolution of the required inputs and high computational demands of 

this model, it is not expected to be a suitable operational model for all sandbars in Grand 

Canyon. Rather, it will be a tool to help understand the interactions amongst the suite of driving 

variables and processes of sandbar response at selected sites, and will allow ranking of these 

variables and processes by their relative importance. In order to generalize the model to 

characteristic sites, we will use the data compilation and analysis in Objective 1. This 

information will then be used to refine a more generalized empirical or statistical model for 

sandbar response applicable to all sandbars in Grand Canyon (Objective 3).

Large eddy simulation (LES) is a computationally intensive modeling technique in which 

turbulence larger than the scale of the grid is directly calculated by the fluid equations of motion. 

Current parallel algorithms employed on supercomputers are now able to perform simulations of 

turbulence and suspended sediment transport on grid-spacing of a meter or less when applied to 

Grand Canyon fan-eddy complexes. The LES model developed for Grand Canyon eddies 

simultaneously solves for the turbulent flow field and the suspended sediment concentration field 

by solving the three-dimensional, time-dependent sediment concentration continuity equation. 

The flow and suspended sediment has very recently been coupled with a morphodynamic model 

based on the rate of erosion or deposition predicted by the model. The morphodynamic model 

also utilizes a bed mixing depth model to evolve the grain sizes available for transport from the 

bed. 

Figure 12a below shows general topographic features of a lateral separation eddy. Figure 12b 

below shows a subset of possible geometric parameters that may be found to be important in the 

groupings determined by Objective 1. A generic grid will be formed and the geometric 

parameters of each bar group from Objective 1 will be used to form a synthetic grid that 

corresponds to each bar group. The LES flow and suspended sediment model will be conducted 

on each bar group synthetic grid. We will focus attention on the key flow features for import and 

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export of sediment from the lateral eddy zone to test our Hypothesis/Question 2 that different 

sandbar responses to similar sediment and water discharges are the result of specific topographic 

boundary conditions.

Figure 12. a) General topography of an eddy and b) geometric parameters influencing flow hydraulics.

Objective 3: 

We will use existing field and remotely sensed data sets, which include coupled (concurrent 

and co-located) observations of sandbar response and hydrology, to develop a data-driven model 

of sandbar response to HFEs and other flow regimes. This model will predict the generalized 

response of a given sandbar (sandbar volume and/or area) and/or groups of similar bars 

(Objective 1) given inputs of routinely measured or modeled flow and sediment parameters, and 

measured or modeled (depending on availability at a given model time step) sandbar parameters. 

The model will be empirical (as opposed to the mechanistic model of Objective 2), and 

calibrated and validated with existing long-term sandbar monitoring data. The applicability of 

the model beyond the monitoring data on which it is built will be evaluated using data from the 

channel mapping projects (Project Element 3.2.), the remote sensing of sandbars (Project 

Element 3.1.2.), the remote camera element of the sandbar monitoring program (Project Element 

3.1.1), and the rapid survey project (3.1.3).

Our modeling approach is to begin simply, and incorporate complexity as results from 

Objectives 1 and 2 allow us to refine our understanding of the key physical processes. First, we 

will use an empirical statistical approach to model sandbar response for individual bars and for 

groupings of bars (Objective 1). This work will proceed concurrently with Objective 1 in 

collaboration with the BOR, who developed a generalized empirical model for the average 

behavior of all sandbars in Marble Canyon for the LTEMP EIS. Our initial approach will use a 

simple parametric model of individual or grouped sandbar response. Examples include a multiple 

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regression approach, a mixed-effects model, or a model based on statistical unsupervised 

learning methods that is trained on the existing data set. The latter approach finds parameters 

based on statistical principles such as minimizing variance, but which have defensible physical 

meaning. Using results from Objectives 1 and 2, we will attempt to develop a more sophisticated 

statistical model that is based on calibrated physical parameters derived from physical principles

and understanding and empirically-derived response rates. This approach could include reapplication of the Wiele and others (2007) approach using the new data sets collected in the last 

decade if practicable in light of results from the preceding approaches. For example, we can 

develop empirical relations between (1) eddy properties and rates of sandbar erosion or 

deposition for different discharge conditions (e.g. Wiele and others, 2007), (2) between sandbar 

volume or mass balance (erosion or deposition) and flow/sediment transport parameters (e.g. Fig. 

11), or (3) between sandbar mass balance and the morphological characteristics of those bars in 

deficit, and those in surplus, over specific periods. 

For Objectives 1 and 3, we intend to focus initially on Lower Marble Canyon, where there is 

a higher density of long-term monitoring sandbar sites, repeat bathymetric surveys from channel 

mapping campaigns in 2009 and 2012, and a complete geomorphic base map of channel 

characteristics and geomorphic units (P.E. Grams, unpublished data). We will then test the 

applicability of applying the data-driven empirical model to other reaches in Marble and Grand 

Canyons. Field surveys in reaches outside of Lower Marble Canyon, combined with Canyonwide remote sensing data, will allow us to document the longitudinal occurrence of different 

eddy sandbar types, and provide a validation data set to test applicability of the model. We also 

expect that the spatially rich remotely-sensed data will be important for providing insight into 

improving the approach described here for longer reaches or in other segments of the CRe. 

Outcomes and Products – FY15

• Presentation at annual reporting meeting on statistically-derived groupings of 

sandbars (Objective 1) and potential approaches for coupling with LES and 

statistical modeling (Objectives 2 and 3) 

• Development of the sandbar groupings and database of fan-channel-eddy metrics

• Development and implementation of “flexible” version of LES model compared 

with measured sandbar response in different sandbar groupings (Objectives 1 and 

2)

Outcomes and Products – FY16

• Presentation at annual reporting meeting on results of linking topographically-flexible 

LES model (Objective 2) with the generalized sandbar groupings (Objective 1)

• Develop a simple statistical, parametric model of sandbar response to HFEs and 

intervening flows

• Report/journal article on generalized sandbar groupings from morphological 

characteristics of the channel and bars and/or results from the “flexible” LES model 

Outcomes and Products – FY17

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• Presentation at annual reporting meeting integrating the statistical and LES modeling 

approaches to understand spatial and temporal variations in sandbar dynamics

• Continue refining the parametric model, with the potential for developing a semimechanistic model incorporating results from Objectives 1 and 2

• Report/journal article on statistical sandbar model to predict sandbar response using the 

monitoring data set 

• Report/journal article on coupled flow and morphodynamic LES model of Grand Canyon 

sandbars

Project Element 3.4. Connecting total sand transport, bed morphodynamics, and sand budgets in Grand 

Canyon 

(Recommended for funding FY15: $36,050)

Brandon McElroy, Assistant Professor, University of Wyoming

Daniel Buscombe, Research Geologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

David Rubin, Professor, University of California at Santa Cruz

David Topping, Research Hydrologist, USGS, GCMRC

Graduate Student

Objectives

1. Carry out repeat high-resolution bathymetric and flow-field surveys over sand bedform 

fields in select reaches, over a range of discharges, including a controlled flood (Wright

and Kaplinski, 2011) and flows associated with routine dam operations.

2. Use this data to estimate bedload and bed sand fluxes associated with the deformation 

and migration of bedforms by applying, and modifying where necessary, existing 

numerical techniques and theory.

3. Determine a bedload 'rating curve' which relates sand flux as bedload with routinely 

measured flow and sediment quantities (discharge, or suspended sand flux, or both).

4. Use the rating curve in conjunction with a discharge model to estimate a total bedmaterial sand mass balance for Marble Canyon and eastern Grand Canyon (stations at 

RM 30, RM 61, and RM 87), combining estimates of sand bedload flux with sand 

suspended flux to enable estimation of total sand transport, system-wide and nearly 

continuous in time.

5. Develop a conceptual 'bed state indicator' model relating bedforms in a given reach 

classified by their morphology and sedimentology to the surplus or otherwise of sand in 

the bed, and therefore the propensity of the bed in that reach to contribute sand for 

sandbar building during controlled floods. 

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6. Examine the two-way feedbacks between evolving bedform fields and spatial 

distributions of flow and sediment concentrations, in order to better understand the 

potential time-varying importance of bedload sand flux. This is necessary to estimate the 

representativeness of suspended sediment measurements for bed sand flux estimates at 

discrete locations.

Questions / Hypotheses

1. What is the contribution of bedload to time-integrated sand flux in the Colorado River in 

Grand Canyon? How does this vary with discharge, suspended sand load, hydraulic 

geometry, and bed sediment grain size? We hypothesize that the fraction of sand moving 

as bedload varies inversely with discharge above the suspension threshold (e.g. Maddock, 

1976), positively with bend radius and channel width, and positively with grain size.

2. Does bedload flux scale with suspended sand flux? We hypothesize that (1) bedload sand 

flux varies non-linearly with suspended sand flux because the presence of bedforms 

enhances local sediment suspension by adding form drag to total bed shear stress 

(Einstein, 1950); and (2) the importance of incorrectly estimating bedload sand flux 

increases at low discharges and transport stages.

3. Can reach-scale estimates of sand flux and sediment mass balance improve with direct 

quantification of the contribution of bedload transport, using routinely measured 

quantities at gaging sites (discharge, suspended sediment concentration and grain size) 

for inclusion in operational sand flux models? We hypothesize that more robust 

parameterization of bedload flux will enable partial if not complete accounting for 

discrepancies between morphologic and suspended sediment based estimates of sand 

mass balance.

4. Can geometric and sedimentologic characters of bedforms be used as a 'bed state' 

indicator? What bedforms (if any) indicate sediment-starved beds, and what (if any) 

represent significant stores of sand which could be re-mobilized during controlled floods 

to build sandbars? We hypothesize that certain bedforms shapes and grain sizes are 

indicative of thin veneers of sand, and others indicate thick sand bed deposits. The use of 

bedform classification (geometric characteristics and sedimentology) is common in field 

and experimental settings to indicate the presence or otherwise of a starved sand bed. For 

example, the existence of 'sand stripes' indicate relatively starved bed conditions (Grams 

and Wilcock, 2007), as do dunes with coarse underlying sediment exposed in the troughs. 

High amplitude dunes with more regular geometries indicate areas with a surplus of sandsized sediment. 

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5. Do evolving bedform fields alter hydraulic conditions and suspended sediment 

concentrations? We hypothesize that, for a given flow field and upstream suspended 

sediment supply, an evolving bedform field alters the spatial distribution of total bed 

shear stress sufficiently, through form drag, to alter the concentration and spatial 

distribution of suspended sand. This is manifest as non-equilibrium responses in the 

distribution of sand flux between bedload suspended load, calculated using Einstein’s 

(1950) shear stress partitioning method with skin frictions estimated from known grain 

sizes.

Rationale/Justification

By measuring and parameterizing bedload sand flux (the rate of flow of the mass of sediment 

per unit area), this project will contribute to the sediment monitoring program as an important 

component of both flux-based and morphologic-based estimates of sand mass balance in Grand 

Canyon (Grams and others, 2013). This project has the potential to substantially improve 

estimates of mobile sand volumes that are available for sandbar construction during controlled 

floods.

The method with the highest potential for spatially explicit estimates of bedload sand flux 

over large areas (100s to 1000s of square meters) is through the time-evolution of bed 

topography in entire pools (up to 1 km in length) captured at a time scale of hours to days From 

the pioneering work of Bagnold (1941) and Simons and others (1965), fluxes of bed sediment 

have been directly tied to the migration of idealized triangular mobile bedforms. These early 

techniques have been modified to suit application in large rivers (e.g. Mississippi River, 

Nittrouer and others, 2008; Missouri River, Gaueman and Jacobson, 2007, and Abraham and 

others, 2010) where bedforms are not idealized shapes, and where bedforms deform as they 

migrate. McElroy and Morhig (2009) proposed an extension to these methods that captures all 

bed-sediment flux through analyzing the evolution of sand bedforms. This relatively new method 

has not yet been systematically tested on numerous river systems, but there is clear support for it 

with existing data (McElroy and Abraham, 2010). The sediment monitoring and channel 

mapping programs combine to provide a unique opportunity to carry out a robust test of the 

method, by coupling spatially explicit measurements of bedform evolution with detailed 

measurements of suspended bed sand fluxes. We propose to capitalize on the following recent 

advances to connect suspended sand fluxes to bedload sand fluxes and, in combination, the sand 

budget in Grand Canyon.

First, it is now possible to measure bathymetry using multibeam sonar with extremely high 

resolution (cm), high accuracy (cm), and high precision (cm). Second, recent advances have been 

made in estimating bed-sediment surface grain-size using multibeam sonar acoustic backscatter. 

Third, it is now possible to measure and record the acoustic scattering signature of sediments 

suspended in the water while mapping bathymetry (Hughes-Clarke, 2006), opening up the 

possibility of quantifying spatial heterogeneity in suspended sediment concentrations (Jones, 

2003; Simmons and others, 2010). We are therefore close to being able to measure bathymetry, 

bed sediment grain size and suspended sediment concentration simultaneously with the same 

instrument, and with no additional field time. These advances will be applied to estimating 

bedload and bed load sand flux using repeat surveys over bedform fields.

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Figure 13a. Schematic of how the relative proportions of bed material load (total load minus wash load) change with 

increasing flow strength. Two scenarios are presented: (a) represents the current assumption that bedload is a constant 

proportion of bed material load; and (b) depicts the new hypothesis to be tested in this study that the proportion of bed 

material load moving as bedload is a function of flow strength. 

We know that not all sand in the Colorado River moves through Grand Canyon in 

suspension; some near-bed transport occurs below the detection of acoustic suspended sediment 

samplers. Current acoustic sediment monitoring (Project 2) captures the suspended sand flux but 

not the flux of sand which moves as bedload. Instead, bedload sand flux is estimated as the same 

constant proportion of suspended sand flux at each gage station (Topping and others, 2010). The 

percentage used (typically 5 percent; Fig. 13a) is an estimate based on limited field observations. 

This practice is based on a study by Rubin and others (2001) who used measurements of bedform 

wavelength made by rotating side-scan sonar in eddies, estimates of bedform height, and point 

measurements of suspended sediment concentration to estimate that bedload was approximately 

5 percent and 0.3 percent of total sand flux at the 61-mile and Grand Canyon gages, respectively. 

This represents two point measurements over a 20 m circular section of channel bottom over 10-

20 hours during a discharge of about 20,000 ft3/s. 

Based on those data, there are substantial uncertainties surrounding the present use of a 

constant proportion of suspended sand flux as an estimate for bedload flux. For example, what 

are the spatial variabilities of bedload flux? How do the controls and rates of bedload differ 

between the main channel (not measured by Rubin and others, 2001) and eddies, which are 

fundamentally different flow regimes? Is bedload flux always in phase with discharge and/or 

suspended flux, or is there some time-lag or hysteresis effect in place due to the deformation 

and/or migration of bedforms? What are the feedbacks between evolving bedform fields, and 

fields of flow velocity and suspended sediment concentrations? What is the effect of bed 

sediment grain size distribution on bedform movement and therefore bedload flux? Bedload sand 

flux is not likely to be larger than ~10 percent of the suspended sand flux. However, variations 

between ~1 percent and ~10 percent of the suspended flux are possible, both temporally and 

between gages. These variations could affect computed sand budgets. For example, if bedload 

sand flux is ~1 percent at one station and ~10 percent at another station, this adds ~10 percent 

possible bias to the sand budget for the intervening river segment if bedload fluxes are 

erroneously assumed to be equal at both stations. Using the sediment budget tool on the GCMRC 

website (Lower Marble Canyon, May 2009 to May 2012) this could mean the difference of a 

budget that is -800,000 metric tons with uncertainty range of -1,100,000 to -490,000 metric tons 

to a budget that is -800,000 metric tons with uncertainty range of -1,700,000 to +100,000 metric 

tons. The 10 percent potential bias in the bedload flux adds substantially to the uncertainty in the 

estimated sand budget. Thus, until we have a better understanding of these processes, the 

application of a universal linear relationship between suspended and bedload sand fluxes (Fig. 

13a) will continue to add potentially substantial uncertainties to total sand fluxes in Grand 

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Canyon. We hypothesize that the proportion of total sand load moving as bedload varies with 

flow strength (discharge; Fig. 13b).

One of the goals that we propose is to significantly expand the dataset on which the 

conclusions of Rubin and others (2001) are based. Primarily this includes: (1) measuring 

bedform geometry (wavelengths and heights) more accurately (using multibeam sonar rather 

than sidescan sonar), over a larger area, and in both the main channel and eddies; (2) observing 

the evolution of that geometry over a greater range of flow conditions and at sites which are 

specifically tied into the existing suspended sediment monitoring program; (3) measuring the 

surface grain size of sand comprising the bedforms; and (4) using recent theoretical 

understanding and computational advances in estimating bedload flux from high-resolution 

bathymetries (McElroy and Mohrig, 2009). 

We will integrate our field measurements with ongoing work to maximize the utility of the 

project. Primary connections will be made with two other projects, namely (1) suspended 

sediment monitoring, and (2) acoustic bed sediment classification. Underwater video has 

revealed the existence of gravel troughs between sand bedforms, as well as small dunes in mixed 

sand-gravel substrates. In addition, there is anecdotal evidence dunes composed entirely of 

gravel exist on the bed of the Colorado River in Grand Canyon. Using MBES acoustic 

backscatter, Buscombe and others (in review) have developed methods which will allow us to 

distinguish bedforms between different substrate types (homogeneous sand, mixed sand and 

gravel, and homogeneous gravel). 

Methods

This study will be achieved primarily using repeat multibeam sonar (MBES) and ADCP 

surveys. The MBES will provide bathymetric maps, as well as maps of surface bed sediment 

type at the same resolution, and full water column backscatter measurements for visualizing the 

3D suspended sediment field. The ADCP will provide measurements of flow velocity fields. 

Repeat mapping of the riverbed using MBES has been shown to be able to capture the migration 

and deformation of sand dunes over short time scales (hours to days) during a controlled flood 

(Wright and Kaplinski, 2011; also Fig. 14). The MBES system currently in use allows better 

resolution of the bed morphology, therefore a smaller threshold of change detection. We 

anticipate that capturing the same degree of mobility under regular flows from normal dam 

operations would take several days to a week. 

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Figure 14. Evolution of the bed at Eminance during the 2008 HFE (data from Wright and Kaplinski, 2011) showing 

significant bed deformation and migration of bedforms over the timescale of hours to days.

In year 1, we propose to conduct this work in the water and sediment gaging pool at RM 61, 

above the confluence with the Little Colorado River and within Natal Origins Reach 4. In order 

to maximize the efficiency of the fieldwork, and minimize costs, this in conjunction with a Natal 

Origins field trip. This site has been mapped using multibeam-sonar-derived bathymetry in May 

2009, May 2012, August 2013, and May 2014. A well-developed bedform field is present (Fig. 

15). We propose to map the same bedform fields repeatedly as many times as possible over a 

week, in conjunction with ADCP measurements along multiple transects, which have been 

shown to adequately characterize the near-bed velocity flow field responsible for mobilizing and 

transporting sediment as bedload under varying discharges. This intensive repeat mapping and 

sampling of an entire ~1 mile reach, near an existing long-term gauging site, and over multiple 

days with a range of flows, is the best strategy for compiling enough data to answer the suite of 

scientific questions posed above. Bedload fluxes will be estimated by applying to the MBESderived data a suite of existing techniques, principally the migration of bedforms based on the 

Exner equation (Simons and others, 1965); cross-correlation of bedform crest locations (Engel 

and Lau, 1980; Duffy and Hughes-Clarke, 2005) and time-varying vertical exchanges with the 

suspended load (McElroy and Mohrig, 2009).

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Figure 15. Bathymetry (measured in May 2014) of the sediment gaging pool at RM61. Repeat surveys of this area (in May 

2009, May 2012, and August 2013) have revealed an active and consistently well developed dune field.

Bed sediment grain size will be estimated using the techniques of Buscombe and others (in 

review) using the MBES acoustic backscatter data (Fig. 10). The goal of connecting to this work 

is to allow for bed load fluxes to be determined as a function of bed sediment type. For example, 

distinguishing between sand and gravel dunes is important so migrating gravel dunes do not 

contribute to the sand mass balance. The relative proportions of mobile sand and lag coarse 

deposits in an entire dune field would be estimated by extrapolating from the areal proportion of 

those two sediment fractions at the surface, as measured using acoustic techniques. It will also 

provide insight into bed condition as a function of bed sediment transport. In addition, highresolution observations of bed sediment type are required to meet Objective 5 (bed state indicator 

model). Similarly we will connect to ongoing efforts to monitor suspended sand loads (e.g. 

Topping and others, 2010). The major goal of this connection is to elucidate the extent to which 

sand is exchanged between bedload and suspended load volumes within and between individual 

flow events, within and between individual reaches, and at scales from individual bedforms to 

those relevant for calculating bed sand load.

We also propose to collect full water-column imaging from MBES at discrete locations 

above dunes in conjunction with both physical samples of suspended sediment and the 15-minute 

acoustic suspended sediment time-series at the gauging station at RM 61. This creates the 

possibility of calibrating MBES acoustic backscatter for suspended sediment concentration, 

making possible the mapping, in 3D, of the time-integrated field (spatially static) of suspended 

sediment, using the methods detailed in Jones (2003) and Simmons and others, (2010). Such 

information is a requirement of Objective 6 and enables us to answer questions related to the 

interaction of an evolving bedform field with a spatially non-uniform flow and sediment field, 

and the representativeness of suspended sediment measurements at discrete locations.

One of the outcomes of this project will be a test of the hypotheses laid out above. In doing 

so, we will generate a bedload sediment rating curve for the Colorado River in Grand Canyon 

based on routinely measured quantities (discharge and suspended sediment). This will lead to an 

informed methodology to account for bedload in sediment management operations and possibly 

to better understanding of the interaction between sandbars and bed load during low discharges.

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We anticipate at least two major scientific products and at least one major management 

product. In addition yearly reports and presentations at national-scale conferences will be 

produced. One scientific manuscript will deal exclusively with bed load fluxes through the Grand 

Canyon and its physical controlling factors. The second will focus on the relations between bed 

load and suspended load, and it will include a treatment of Grand Canyon sediment budgets 

including bedload. Finally, we will produce a document that makes recommendations for if and 

how to further incorporate bedload with sediment monitoring in the canyon.

Outcomes and Products – FY15

• Presentation on project progress at annual reporting meeting. 

Outcomes and Products – FY16

• Presentation at annual reporting meeting. 

• Journal article on measurements of bedform migration and physical controls on 

bedload sediment transport.

Outcomes and Products – FY17

• Presentation at annual reporting meeting. 

• Journal article on relation between bedload and suspended sediment load in the Colorado 

River.

• Report/Journal article on procedures for measuring and estimating bedload.

Project Element 3.5. Control Network and Survey Support 

(Recommended for funding FY15: $109,003)

Keith Kohl, Surveyor, USGS, GCMRC

Objectives

Ensure that all data collected in scientific investigations are correctly and consistently 

referenced to the National Spatial Reference System (NSRS) for reliable use in Geographical 

Information Systems (GIS). 

Rationale/Justification

The overarching goal of this project element is to develop a sound process for establishing, 

maintaining, and verifying survey control in support of long-term monitoring within the CRE. 

Toward this end, GCMRC requires a control network and survey procedures that will yield 

reliable and consistent results now, while allowing for advances in theory and technology in the 

future. Importantly, the procedures must withstand changes in personnel that will inevitably 

occur over the life of the CRE monitoring programs.

An accurate geodetic control network is required to support nearly every aspect of this 

project as well as most other GCMRC monitoring projects. The purpose of the control network is 

to ensure that spatial data acquired on all projects are collected with accurate and repeatable 

spatial reference. The control network is essential to enable comparison among data sets 

collected by different methods and ensure that spatially referenced observations are repeatable 

and that all data are documented and archived appropriately. Projects that are directly dependent 

on the control network include this project, all other projects that use systemwide airborne 

remote sensing, archeological site monitoring, and vegetation monitoring. The remote sensing 

work is particularly dependent on accurate control operations, without which image data could 

not be compared accurately with ground-based measurements. 

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The control network is the set of monumented and documented reference points 

(benchmarks) that exist along the river corridor and on the rim together with the collection of 

observations that determine the relative and absolute positions of those points. Those points 

serve as the basis for referencing all ground- and air-based monitoring observations. Currently, 

the control network includes more than 7,000 GPS observations and more than 2,000 optical 

observations that determine the precise location of more than 1,300 benchmarks in the river 

corridor and on the canyon rim. This project includes work in three broad categories: (1) building 

the control network, (2) direct support of research and monitoring activities, and (3) storage and 

archival of the control database.

Combining conventional measurements (which reference gravity) with GPS measurements 

(which reference a geocentric ellipsoid) requires the reduction of field measurements to the 

ellipse. Variations of mass density will affect local gravity, deflection of the vertical, zenith 

angle measurements, and height determination. High-resolution geoid models set out to define 

these relationships. Identifying these interactions within the CRE is critical since diverse methods 

are used to determine positions, including remote sensing, conventional ground-based optical 

methods, Global Positioning System (GPS), and bathymetric surveys. 

Combining the results of these various methods to derive a consistent set of coordinates 

requires a detailed knowledge of how these coordinates are derived, as well as the accuracy of 

the derivation. Coordinates, datum descriptions, and accuracy results are provided in a format 

compatible with Federal Geographic Data Committee (FGDC) delivery standards.

Proposed Work: Control Network

Primary tasks of building the control network include making GPS observations at new and 

existing benchmarks, and linking conventional traverses between the GPS monuments to 

determine positions and ellipsoid heights. Most segments of the river corridor now have a 

sufficient number of control points to support monitoring activities. 

Determining accurate elevations requires addressing the difference that exists between 

ellipsoid heights, which are determined by GPS observations, and orthometric elevations (i.e. 

NAVD88), which can be determined only by gravity measurements or precise leveling. The 

deviation between ellipsoid height and orthometric height is modeled in a hybrid geoid model 

(Geoid12a) which combines GPS observations, gravity and optical leveling. The deviation can 

be as large as 10 cm over a distance of 1 km and affects our ability to determine river slope and 

develop longitudinal profiles. This, in turn, affects the accuracy of streamflow models. The 

challenge of determining accurate elevations in rugged topography is a major focus of the 

National Geodetic Survey (NGS). We have been encouraging the NGS to conduct a campaign of 

gravity measurements for the region; however, due to the remote location, low population, and 

difficult access, the geoid model in Marble and Grand Canyons is improving much slower than 

in high–use, populated areas. 

We have made progress with these challenges by incorporating existing leveling 

measurements into the control network. In FY13–14 this involved the publication in the NGS 

database of 1046 newly adjusted NAVD 88 benchmarks throughout Grand Canyon 

www.ngs.noaa.gov/cgi-bin/ds_proj.prl, Survey Project ID: L27947). In FY15, these data will be 

analyzed to compare GPS observations with historical leveling observations to better define the 

relation between GPS heights and orthometric heights and enable more accurate measurements 

of elevation.

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Additional leveling information is available in Glen Canyon, including a published level line 

with NAVD88 orthometric heights determined from differential leveling done in 1923 and 

adjusted by the NGS in 1992. In FY16, we will perform an analysis of the leveling data and 

evaluate height differences between previous and current control networks in Glen Canyon. The 

data provides an excellent opportunity to test the performance of both the hybrid geoid 

(Geoid12a) and the gravimetric geoid (USGG2012) in a steep canyon environment. Information 

gleaned from this study will be used to estimate elevation accuracies throughout the CRE.

A longitudinal profile study of the Colorado River through Glen, Marble, and Grand 

Canyons is scheduled for FY17. The study will use all available data to define the Colorado 

River water surface with accurate geodetic positions and elevations. Conventional traverse 

measurements will be used to evaluate geoid performance.

Proposed Work: Support of Research and Monitoring Projects

The two major projects that require survey support in 2015–2017 are the sandbar (3.1.) and 

sediment storage (3.2.) project elements and Project 4. The sandbar and sediment storage project 

elements described here rely on the accurate positions of hundreds of monuments to link 

measurements and confirm proper equipment setup and calibration. The topographic and 

bathymetric surfaces share the same datum and are referenced to the same monuments and 

coordinates as the remotely sensed data. The control network also supports remote sensing by 

determining the positions of well-defined points from independent sources of higher accuracy.

This allows scientists and managers means to assess positional accuracy of data, maps, and 

products.

The scope of this survey support project element is to assist other GCMRC projects with 

survey knowledge, control infrastructure and equipment as need arises. The expertise of the 

survey staff is used in many data collection efforts including collecting, processing, and 

delivering reference base station data for overflight missions and supporting Streamflow, Water 

Quality, and Sediment Transport project (Project 2), and the Vegetation Monitoring project 

(Project 11). GNSS basestations are published (bluebooked) within the National Geodetic Survey 

Integrated Database (NGSIDB) (National Geodetic Survey, 2012). The budget for personnel 

time required for the collection of field data and processing for specific projects is incorporated 

in each individual project element.

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Storage, Archival, and Documentation of the Control Network Database

The control network data are stored in a Microsoft Access database that is linked with the 

GCMRC GIS database. The survey staff works with GIS staff to maintain and update the 

database as needed. 

D.2 Personnel and Collaborations 

The project lead is Paul Grams. Daniel Buscombe is a post-doctoral fellow and Research 

Geologist with specialization in bed-texture characterization using underwater imaging and 

acoustics. Erich Mueller is a post-doctoral fellow and Research Hydrologist with specialization 

in geomorphology and sediment transport. Joel Sankey is a Research Geologist and remote 

sensing expert. Keith Kohl is the control network specialist and surveyor. Support is provided by 

Rob Ross and Bob Tusso who are term hydrologists. Graduate students will work on the Rapid 

Survey project (3.1.3.), modeling project (3.3), and bedload project (3.4). Ted Melis is a Physical 

Scientist with expertise in hillslope and debris flow process and linkages between physical 

science and ecology. David Varyu is a hydraulic engineer at the BOR Technical Service Center 

with expertise in hydraulic and sediment transport modeling. The GCMRC staff have 

management responsibility for the entire project and share responsibility for data collection, 

analysis, and reporting. Joseph E. Hazel, Jr, and Matt Kaplinski of Northern Arizona University 

are long-term collaborators on sandbar and sediment storage monitoring. Joe Wheaton is an 

Assistant Professor at Utah State University and an expert in collecting, processing, and 

analyzing digital elevation models. Brandon McElroy is an Assistant Professor at the University 

of Wyoming and an expert in bed form migration and bedload transport in sand-bedded rivers.

D.3 Deliverables 

See “Outcomes and Products” listed by project element, above.

 

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E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

Website showing repeat photographs showing effects of Fall 2012 HFE: 

http://www.gcmrc.gov/gis/sandbartour2012/index.html?

Website showing repeat photographs showing effects of Fall 2013 HFE: 

http://www.gcmrc.gov/gis/sandbartour2013/index.html?

Sandbar Monitoring Data: Sandbar topographic surveys and campsite surveys conducted Fall 

2012 and 2013. Reported at Annual Reporting Meetings and provided to Reclamation for 

inclusion in LTEMP analysis. Website to serve data is in development.

Sediment Storage Data (Channel Mapping): Data collected in 2013 for topographic/bathymetric 

map of RM 0 to 30: processing is nearly complete. 

E.2. Completed Publications 

Alvarez L.V, Schmeeckle M.W. 2013. “Erosion of River Sandbars by Diurnal Stage Fluctuations 

in the Colorado River in Marble and Grand canyons: Full-Scale Laboratory Experiments”. 

River Research and Applications., 29: 839-854. doi:10.1002/rra.2576.

Buscombe, D., 2013, Transferable Wavelet Method for Grain Size-Distribution from Images of 

Sediment Surfaces and Thin Sections, and Other Natural Granular Patterns. Sedimentology, 

60: 1709–1732.

Davis, P.A., 2013, Natural-color and color-infrared image mosaics of the Colorado River 

corridor in Arizona derived from the May 2009 airborne image collection, U.S. Geological 

Survey Data Series 780.

Draut, A.E. and Rubin, D.R., 2013, Assessing grain-size correspondence between flow and 

deposits of controlled floods in the Colorado River, USA: Journal of Sedimentary Research 

83 (11), 962-973.

Grams P. E., 2013, A sand budget for Marble Canyon, Arizona--implications for long-term 

monitoring of sand storage change, U.S. Geological Survey Fact Sheet 2013–3074, 4 p., 

http://pubs.usgs.gov/fs/2013/3074/.

Grams P. E., D. J. Topping, J. C. Schmidt, J. E. Hazel Jr., and M. Kaplinski (2013), Linking 

morphodynamic response with sediment mass balance on the Colorado River in Marble 

Canyon: Issues of scale, geomorphic setting, and sampling design, J. Geophys. Res. Earth 

Surf., 118, 361–381, doi:10.1002/jgrf.20050. 

http://onlinelibrary.wiley.com/doi/10.1002/jgrf.20050/full

Grams, P. E., and P. R. Wilcock (2013), Transport of fine sediment over a coarse, immobile river 

bed, Journal of Geophysical Research: Earth Surface 

http://onlinelibrary.wiley.com/doi/10.1002/2013JF002925/abstract.

Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., Davis, P.A., 2014, Monitoring fine-sediment volume 

in the Colorado River ecosystem, Arizona—Construction and analysis of digital elevation 

models: U.S. Geological Survey Open-File Report 2014–1052, 29 p., 

http://dx.doi.org/10.3133/ofr20141052.

Kennedy, T. A., C. B. Yackulic, W. F. Cross, P. E. Grams, M. D. Yard, and A. J. Copp (2014), 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river, Freshwater Biology, 59(3), 557-572.

129
Mueller, E.R., Grams, P.E., Schmidt, J.C., Alexander, J.S., Hazel Jr., J.E., and Kaplinski, M., 

accepted with revisions, The influence of controlled floods on fine sediment storage in debris 

fan affected canyons of the Colorado River basin. Geomorphology.

Ross, R., and Grams, P.E., 2013, Nearshore thermal gradients of the Colorado River near the 

Little Colorado River confluence, Grand Canyon National Park, Arizona, 2010: U.S. 

Geological Survey Open-File Report 2013–1013, 65 p. (Available at 

http://pubs.usgs.gov/of/2013/1013/.)

Ross, R.P., and Vernieu, W.S., 2013, Nearshore Temperature Findings for the Colorado River in 

Grand Canyon, Arizona—Possible Implications for Native Fish: U.S. Geological Survey Fact 

Sheet 2013-3104, 4 p., http://dx.doi.org/10.3133/fs20133104.

E.3. Publications in progress 

Alvarez L.V, Schmeeckle M.W., Grams P., in prep., The Mechanics of Turbulent Flow in 

Lateral Separation Zones: Field Scale Detached Eddy Simulation Model, Water Resources 

Research.

Buscombe, D., Grams, P.E., Kaplinski, M.A., in review, Characterizing riverbed sediment using 

high-frequency acoustics 1: Spectral properties of scattering. Intended for Journal of 

Geophysical Research - Earth Surface.

Buscombe, D., Grams, P.E., Kaplinski, M.A., in review, Characterizing riverbed sediment using 

high-frequency acoustics 2: Scattering properties of Colorado River bed sediment in Marble 

and Grand Canyons. Intended for Journal of Geophysical Research - Earth Surface.

Buscombe, D., Rubin, D.M., Lacy, J.R., Storlazzi, C., Hatcher, G., Chezar, H., Wyland, R., and 

Sherwood, C., accepted for publication, Autonomous bed-sediment imaging-systems for 

revealing temporal variability of grain size. Limnology and Oceanography: Methods.

Buscombe, D., and others, in prep., Mapping sandbar topography in Marble Canyon, AZ, using 

time-lapse imagery during controlled floods, Earth Surface Processes and Landforms.

Davis, P.A., Kohl, K.A., and Gushue, T.M., in prep., Evaluation of Airborne ADS40 

Photogrammetric Digital Surface Models for Monitoring the Colorado River Corridor below 

Glen Canyon Dam, Arizona.

Grams, P.E. and others, in prep., A comprehensive sand budget for the Colorado River in Marble 

Canyon, Arizona: 2009-2012, Earth Surface Processes and Landforms.

Gushue, T., and others, in preparation, Photogrammetric methods for processing 1984 historical 

images.

Hadley, D.R. and Grams, P.E., in prep., Geomorphology and vegetation change at sandbar 

campsites along the Colorado River, Marble and Grand Canyons, AZ: River Research and 

Applications.

Hadley, D.R., Grams, P.E., and Parnell, R., in prep., Geomorphology and vegetation change at 

sandbar campsites along the Colorado River, Marble and Grand Canyons, AZ: U.S. 

Geological Survey Open-file Report.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R., Grams, P., Ross, R., Hamill, D., and Kohl, K., in 

prep., Sandbar Monitoring at Selected Sites in Colorado River in Marble and Grand 

Canyons, Arizona, 1990-2013: U.S. Geological Survey Scientific Investigations Report.

Hazel, J.E., and others, in preparation, Extending sandbar monitoring back in time using 

photogrammetry, digital terrain extraction and orthorectification of historical aerial imagery, 

Grand Canyon.

130
Kaplinski, M., Hazel, J.E., Jr., Parnell, R., Hadley, D., and Grams, P.E., in review, Colorado 

River Campsite Monitoring, 1998 – 2012, Grand Canyon National Park, Arizona: US. 

Geological Survey Open-file Report.

Kaplinski and others, in prep., Monitoring fine-sediment volume in the Colorado River 

ecosystem, Arizona: Topographic and bathymetric maps of the Colorado River.

Ross, R.P. and Grams, P.E., Changes in Sandbar Area from Remote Sensing: 2002-2009, in 

prep., U.S. Geological Survey Open-file Report.

Rubin, Topping, Grams, Tusso, Schmidt, Buscombe, Melis, & Wright, in prep., What sediment 

grain size reveals about suspended-sediment transport in the Colorado River in Grand 

Canyon.

Sankey, J.B., Ralston, B.E., Grams, P.E., Schmidt, J.C., Cagney, L.E., in review, Colorado River, 

vegetation, and climate: five decades of spatio-temporal dynamics in the Grand Canyon with 

river regulation. 

Tusso, R., and others, in prep., Bed-sediment grain size in selected monitoring reaches of the 

Colorado River in Grand Canyon: 2009-2012, U.S. Geological Survey Open-file Report.

E.4. Presentations at GCDAMP meetings 

Buscombe, D. and others, Where is the sand? Using multibeam sonar to map sediment type in 

Marble Canyon: poster presentation at January 2014 Annual Reporting Meeting.

Grams, P.E. and others, Sand in Marble, Glen, and Grand Canyons: status and trends, oral 

presentation at January 2014 Annual Reporting Meeting.

Grams, P.E. and others, Sandbar Monitoring for November 2012 Controlled Flood: oral 

presentation at January 2013 Annual Reporting Meeting.

Gushue, T. and others, Extending sandbar monitoring back in time using photogrammetry, 

digital terrain extraction and orthorectification of historical aerial imagery, Grand Canyon, 

AZ: poster presentation at January 2014 Annual Reporting Meeting.

Hadley, D.R. and others, Geomorphologic and vegetation analysis at Colorado River campsites, 

Marble and Grand Canyons, AZ: poster presentation at January 2014 Annual Reporting 

Meeting.

Kaplinski, M. and others, Constructing a Morphologic Sediment Budget, With Uncertainties, for 

a 50-km Segment of the Colorado River in Grand Canyon: poster presentation at January 

2014 Annual Reporting Meeting.

Mueller, E.R. and others, The effect of controlled floods on decadal-scale changes in channel 

morphology and fine sediment storage in debris fan-affected river canyons: poster 

presentation at January 2014 Annual Reporting Meeting.

Ross, R.P. and Grams, P.E., Using remote sensing to determine sandbar area from 1935-2009 

within select reaches, Marble and Grand Canyons, AZ: poster presentation at January 2014 

Annual Reporting Meeting.

Tusso, R. and Mueller, E.R., Effects of High Flow Events on sandbars along the Colorado River, 

Grand Canyon: poster presentation at January 2014 Annual Reporting Meeting.

E.5. Presentations at professional meetings 

Alvarez L.V, Schmeeckle M.W. 2013. "Numerical Model of Turbulence, Sediment Transport, 

and Sediment Cover in a Large Cayon-Bound River". Presentation Type: Oral Presentation. 

Abstract ID: 1813508.. Final Paper Number: EP24B-07. American Geophysical Union, 2013 

Fall Meeting, San Francisco, CA.

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Alvarez L.V, Schmeeckle M.W. 2013. Numerical Model of Turbulence and Sediment Transport 

in Lateral Recirculation Zones Along the Colorado River in Grand Canyon. Presentation 

Type: Poster. 2013 CSDMS (Community Surface Dynamics Modeling System), Boulder, 

CO.

Alvarez L.V, Schmeeckle M.W. 2012. “Laboratory and numerical modeling of sandbar bank 

erosion, application to diurnal stage variations in Grand Canyon”. Presentation Type: Oral 

Presentation. American Association of Geographers, 2012 Meeting, New York city, NY.

Buscombe, D., Grams, P.E., Kaplinski, M.A. 2013 Acoustic Scattering by an Heterogeneous 

River Bed: Relationship to Bathymetry and Implications for Sediment Classification using 

Multibeam Echosounder Data. American Geophysical Union Fall Meeting, San Francisco, 

Dec 2013

Grams. P.E., Buscombe, D., Hazel, J.E., Kaplinski, M.A., and Topping, D.J. (2013) 

Reconciliation of Flux-based and Morphologic-based Sediment Budgets. American 

Geophysical Union Fall Meeting, San Francisco, Dec 2013.

Kaplinski, M.A., Hazel, J.E., Grams. P.E., Buscombe, D., Hadley, D., and Kohl. K. (2013) 

Constructing a morphologic sediment budget, with uncertainties, for a 50-km segment of the 

Colorado River in Grand Canyon. American Geophysical Union Fall Meeting, San 

Francisco, Dec 2013.

Mueller, E.R., Grams, P.E., and Schmidt, J.C. (2013) The effect of controlled floods on decadalscale changes in channel morphology and fine sediment storage in a debris-fan affected river 

canyon. Abstract EP33C-0923 presented at 2013 Fall Meeting, AGU, San Francisco, CA, 9-

13 Dec.

Rubin, Topping, Grams, Tusso, Schmidt, Buscombe, Melis, & Wright, 2014, What sediment 

grain size reveals about suspended-sediment transport in the Colorado River in Grand 

Canyon: International Conference on the Status and Future of the World‘s Large Rivers, in 

press.

F. References 

Abraham D., Kuhnle, R., and Odgaard, A. J., 2011, Validation of bed load transport 

measurements with time sequenced bathymetric data: ASCE Journal of Hydraulic 

Engineering, v. 137, p. 723-728.

Bagnold, R.A., 1941, The physics of blown sand and desert dunes (1973, 4th ed.): London, 

Methuen, 265 p.

Beus, S.S., David, J.N., Lojko, F.B., and Stevens, L.E., 1992 Colorado River investigations XI, 

report submitted to Grand Canyon National Park: Northern Arizona University and National 

Park Service, available from U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center, Flagstaff, AZ., 175 p.

Beus, S.S., Avery, C.C., Stevens, L., Cluer, B., Kaplinski, M., Anderson, P., Bennett, J., Brod, 

C., Hazel, J., Gonzales, M., Hayes, H., Protiva, F., and Courson, J., 1992, The influence of 

variable discharge regimes on Colorado River sand bars below Glen Canyon Dam (chap. 6), 

in Beus, S.S., and Avery, C.C., Principal investigators, 1992, The influence of variable 

discharge regimes on Colorado River sand bars below Glen Canyon Dam—final report: 

Bureau of Reclamation, Glen Canyon Environmental Studies, National Park Service, 

cooperative agreement no. CA 8006-8-0002 with Northern Arizona University, 62 p.

Blondel, P., and Gomez Sichi, O., 2009, Textural analyses of multibeam sonar imagery from 

Stanton Banks, Northern Ireland continental shelf: Applied Acoustics, v. 70, p. 1288-1297.

132
Black, M., Carbonneau, P., Church, M., and Warburton, J., 2013, Mapping sub-pixel fluvial 

grain sizes with hyperspatial imagery: Sedimentology, v. 61, p. 691-711.

Blank, B.L., 2000, Application of digital photogrammetry to monitoring sand bar change in 

Marble Canyon, AZ: Utah State University, Honors Thesis.

Bogle, R., Velasco, M., and Vogel, J., 2012, An automated digital imaging system for 

environmental monitoring applications: U.S. Geological Survey Open-File Report 2012-

1271, 18 p.

Brown, C.J., and Blondel, P., 2009, Developments in the application of multibeam sonar 

backscatter for seafloor habitat mapping: Applied Acoustics, v. 70, p. 1242-1247.

Brown, C.J., Smith, S.J., Lawton, P., and Anderson, J.T., 2011, Benthic habitat mapping--a 

review of progress towards improved understanding of the spatial ecology of the seafloor 

using acoustic techniques: Estuarine, Coastal and Shelf Science, v. 92, p. 502-520.

Buscombe, D., and Rubin, D.M., 2012, Advances in the simulation and automated measurement 

of well-sorted granular material, part 2--Direct measures of particle properties: Journal of 

Geophysical Research, v. 117, F02002.

Buscombe, D., Rubin, D.M., and Warrick, J.A., 2010, Universal approximation of grain size 

from images of non-cohesive sediment: Journal of Geophysical Research --Earth Surface 

115, F02015.

Cooley, M.E., Aldridge, B.N., and Euler, R.C., 1977, Effects of the catastrophic flood in 

December 1966, North rim area, eastern Grand Canyon, Arizona: U.S. Geological Survey 

Professional Paper 980, p. 43.

Davis, P.A, Staid, M.I, Plescia, J.B., and Johnson, J.R., 2002, Evaluation of airborne image data 

for mapping riparian vegetation within the Grand Canyon: U.S. Geological Survey Open-File 

Report 02-470, 65 p.

Davis, P.A., 2012, Airborne digital-image data for monitoring the Colorado River corridor below 

Glen Canyon Dam, Arizona, 2009 – Image-mosaic production and comparison with 2002 

and 2005 image mosaics: U.S. Geological Survey Open-File Report 2012-1139, 82 p.

Dolan, R., Howard, A., and Gallenson, A., 1974, Man's impact on the Colorado River in the 

Grand Canyon: American Scientist, v. 62, p. 393-401.

Duffy, G.P., and Hughes-Clarke, J.E., 2005, Application of spatial cross correlation to detection 

of migration of submarine sand dunes: Journal of Geophysical Research, v.110, F04S12.

Einstein, H.A., 1950, The bedload function for sediment transportation in open channels: 

Technical Bulletin 1026, U.S. Department of Agriculture, Soil Conservation Service, 

Washington, D.C.

Engel, P., and Lau, Y.L., 1980, Computation of bedload using bathymetric data: Journal of the 

Hydraulics Division, v. 106, 369-380.

Flynn, M.E., and Hornewer, N.J., 2003, Variations in sand storage measured at monumented 

cross sections in the Colorado River between Glen Canyon Dam and Lava Falls Rapid, 

Northern Arizona, 1992-99: U.S. Geological Survey Water-Resources Investigations Report 

03-4104, 39 p.

Fonseca, L., Brown, C., Calder, B., Mayer, L., and Rzhanov, Y., 2009, Angular range analysis of 

acoustic themes from Stanton Banks, Ireland--a link between visual interpretation and 

multibeam echosounder angular signatures: Applied Acoustics, v. 70, p. 1298-1304.

Fonstad, M.A., Dietrich, J.T., Courville, B.C., Jensen, J.L. and Carbonneau, P.E., 2013, 

Topographic structure from motion--a new development in photogrammetric measurement: 

Earth Surface Processes and Landforms, v. 38, p.421-430.

133
Gaueman, D., and Jacobson, R., 2007. Field assessment of alternative bed-load transport 

estimators: Journal of Hydraulic Engineering, v. 133, p. 1319-1328.

Grams, P.E., Hazel, J.E., Schmidt, J.C., Kaplinski, M., Wright, S.A., Topping, D.J., and Melis, 

T.S., 2010, Geomorphic response of sandbars to the March 2008 high-flow experiment on 

the Colorado River downstream from Glen Canyon Dam, in Hydrology and sedimentation 

for a changing future; existing and emerging issues (Joint Federal Interagency Conference 

2010--Federal Interagency Hydrologic Modeling, 4th, and Federal Interagency 

Sedimentation, 9th), Las Vegas, Nev., June 27- July 1, 2010, Proceedings: Proceedings of the 

Federal Interagency Sedimentation Conferences, U.S. Subcommittee on Sedimentation, CDROM. 

Grams, P.E., and Wilcock, P.R., 2007, Equilibrium entrainment of fine sediment over a coarse 

immobile bed: Water Resources Research, v. 43, p. W10420, 

http://www.agu.org/pubs/crossref/2007/2006WR005129.shtml.

Grams P.E., 2013, A sand budget for Marble Canyon, Arizona--implications for long-term 

monitoring of sand storage change, U.S. Geological Survey Fact Sheet 2013–3074, 4 p., 

http://pubs.usgs.gov/fs/2013/3074/.

Griffiths, P.G., Webb, R.H., and Melis, T.S., 2004, Frequency and initiation of debris flows in 

Grand Canyon, Arizona: Journal of Geophysical Research, v.109, F04002.

Hazel, J.E., Jr., Grams, P.E., Schmidt, J.C., and Kaplinski, M., 2010, Sandbar response in Marble 

and Grand Canyons, Arizona, following the 2008 high-flow experiment on the Colorado 

River: U.S. Geological Survey Scientific Investigations Report 2010-5015, 52 p., 

http://pubs.usgs.gov/sir/2010/5015/.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R.A., Kohl, K., and Schmidt, J.C., 2008, Monitoring finegrained sediment in the Colorado River ecosystem, Arizona--control network and 

conventional survey techniques: U.S. Geological Survey Open-File Report 2008-1276, 15 p., 

http://pubs.usgs.gov/of/2008/1276/.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R., Kohl, K., and Topping, D.J., 2006, Stage-discharge 

relations for the Colorado River in Glen, Marble, and Grand Canyons, Arizona, 1990-2005: 

U.S. Geological Survey Open-File Report 2006-1243, 7 p., 

http://pubs.usgs.gov/of/2006/1243/pdf/of06-1243_508.pdf.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R., Manone, M., and Dale, A., 1999, Topographic and 

bathymetric changes at thirty-three long-term study sites, in Webb, R.H., Schmidt, J.C., 

Marzolf, G.R., and Valdez, R.A., eds., The 1996 controlled flood in Grand Canyon: 

Washington, D.C., American Geophysical Union, Geophysical Monograph 110, p. 161-184.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R., Grams, P., Ross, R., Hamill, D., and Kohl, K., in 

preparation, Sandbar monitoring at selected sites in Colorado River in Marble and Grand 

Canyons, Arizona, 1990-2013: U.S. Geological Survey Scientific Investigations Report.

Hereford, R., 1996, Map showing surficial geology and geomorphology of the Palisades Creek 

area, Grand Canyon National Park, Arizona: U.S. Geological Survey Miscellaneous 

Investigations Map I-2499, scale 1:2,000, 26 p.

Hereford, R., Burke, K.J., and Thompson, K.S., 2000, Map showing Quaternary geology and 

geomorphology of the Granite Park area, Grand Canyon National Park, Arizona: U.S. 

Geological Survey Miscellaneous Investigations Map I-2662, scale 1:2,000.

Howard, A.D., 1975, Establishment of benchmark study sites along the Colorado River in Grand 

Canyon National Park for monitoring of beach erosion caused by natural forces and human 

impact, p. 14.

134
Howard, A., and Dolan, R., 1981, Geomorphology of the Colorado River in the Grand Canyon: 

Journal of Geology, v. 89, no. 3, p. 269-298.

Jacobson, R.B., Johnson, H.E., III, and Dietsch, B.J., 2009, Hydrodynamic simulations of 

physical aquatic habitat availability for pallid sturgeon in the lower Missouri River, at 

Yankton, South Dakota, Kenslers Bend, Nebraska, Little Sioux, Iowa, and Miami, Missouri, 

2006-07: U.S. Geological Survey Scientific Investigations Report 2009-5058, 67 p.

Jackson, R., Winebrenner, D.P., and Ishimaru, A., 1986, Application of the composite roughness 

model to high-frequency bottom backscattering: Journal of the Acoustic Society of America, 

v. 79, p. 1410-1422.

James, M.R., and Robson, S., 2012, Straightforward reconstruction of 3D surfaces and 

topography with a camera--accuracy and geoscience application: Journal of Geophysical 

Research, v. 117, F03017.

Jones, C.D., 2003, Water-column measurements of hydrothermal vent flow and particulate 

concentration using multibeam sonar: Journal of the Acoustical Society of America, v. 114, 

p. 2300-2301.

Kaplinski, M., Hazel, J.E., Jr., and Parnell, R., 2010, Colorado River campsite monitoring, 1998-

2006, Grand Canyon National Park, Arizona, in Melis, T.S., Hamill, J.F., Bennett, G.E., 

Coggins, L.G., Jr., Grams, P.E., Kennedy, T.A., Kubly, D.M., and Ralston, B.E., eds., 

Proceedings of the Colorado River Basin Science and Resource Management Symposium, 

November 18-20, 2008, Scottsdale, Arizona: U.S. Geological Survey Scientific 

Investigations Report 2010-5135, 275-284 p., http://pubs.usgs.gov/sir/2010/5135/.

Kaplinski, M., Hazel, J.E., Jr., Parnell, R., Breedlove, M.J., Kohl, K., and Gonzales, M.F., 2009, 

Monitoring fine-sediment volume in the Colorado River ecosystem, Arizona--bathymetric 

survey techniques: U.S. Geological Survey Open-File Report 2009-1207, 33 p., 

http://pubs.usgs.gov/of/2009/1207/of2009-1207.pdf.

Kaplinski, M., Hazel, J.E., Jr., Grams, P.E., and Davis, P.A., 2014, Monitoring fine-sediment 

volume in the Colorado River ecosystem, Arizona--construction and analysis of digital

elevation models: U.S. Geological Survey Open-File Report 2014–1052, 29 p., 

http://dx.doi.org/10.3133/ofr20141052.

Kieffer, S.W., 1985, The 1983 hydraulic jump in Crystal Rapid--implications for river-running 

and geomorphic evolution in the Grand Canyon: The Journal of Geology, v. 93, no. 4, p. 385-

406.

Kim, H-J., Chang, J-K., Jou, H-T., Park, G-T., Suk., B-C., and Kim., K.Y., 2002, Seabed 

classification from acoustic profiling data using the similarity index: Journal of the 

Acoustical Society of America, v. 111, p. 794-799.

Kruse, F.A., Lefkoff, A.B., Boardman, J.B., Heidebrecht, K.B., Shapiro, A.T., Barloom, P.J., and 

Goetz, A.F.H., 1993, The spectral image processing System (SIPS)-- Interactive visualization 

and analysis of imaging spectrometer data: Remote Sensing of Environment, v. 44, p. 145-

163.

Lafferty, B., Quinn, R., and Breen, C., 2006, A side-scan sonar and high-resolution chirp subbottom profile study of the natural and anthropogenic sedimentary record of Lower Lough 

Erne, northwestern Ireland: Journal of Archaeological Science, v. 33, p. 756-766.

Lamarche, G., Lurton, X., Verdier, A.L., and Augustin, J.M., 2011, Quantitative characterisation 

of seafloor substrate and bedforms using advanced processing of multibeam backscatter--

application to Cook Strait New Zealand: Continental Shelf Research, v. 31, p. S93–S109.

135
LeBlanc, L.R., Mayer, L., Rufino, M., Schock, S.G., and King, J., 1992, Marine sediment 

classification using the chirp sonar: Journal of the Acoustical Society of America, v. 91, p. 

107-115.

Logan, B., Nelson, J., McDonald, R., and Wright, S., 2010, Mechanics and modeling of flow 

sediment transport and morphologic change in riverine lateral separation zones, in Hydrology 

and sedimentation for a changing future; existing and emerging issues (Joint Federal 

Interagency Conference 2010--Federal Interagency Hydrologic Modeling, 4th, and Federal 

Interagency Sedimentation, 9th), Las Vegas, Nev., June 27- July 1, Proceedings.

Maddock, T., 1976, Equations for resistance to flow and sediment transport in alluvial channels: 

Water Resources Research, v. 12, p. 11-21.

Magirl, C.F.N., Webb, R., and Griffiths, P., 2008, Modeling water-surface elevations and virtual 

shorelines for the Colorado River in Grand Canyon, Arizona: U.S.Geological Survey 

Scientific Investigations Report 2008-5075, 32 p.

McElroy B., and Abraham, D., 2011, Quantifying bed load and bed material load from repeat 

bathymetric surveys: Report to FISP Technical Committee on work completed.

McElroy, B., and Mohrig, D. 2009, Nature of deformation of sandy bed forms: Journal of 

Geophysical Research, v. 114, no. F00A04.

Melis, T.S., Webb, R.H., Griffiths, P.G., and Wise, T.W., 1995, Magnitude and frequency data 

for historic debris flows in Grand Canyon National Park and vicinity, Arizona: U.S. 

Geological Survey Water Resources Investigations Report 94-4214, 285 p.

Melis, T.S., 1997, Geomorphology of debris flows and alluvial fans in Grand Canyon National 

Park and their influence on the Colorado River below Glen Canyon Dam, Arizona: 

University of Arizona, Tucson, Ph.D. dissertation, 490 p.

Nittrouer, J., Allison, M., Mohrig, D., and Campanella, R., 2008. Bedform transport rates for the 

lowermost Mississippi River: Journal of Geophysical Research, v. 113, no. F03004.

O’Brien, L.E., Coleman, A., Blank, B.L., Grams, P.E., and Schmidt, J.C., 2000, Testing the 

application of digital photogrammetry to monitor topographic changes in sandbars in the 

Colorado River ecosystem--final report: U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center, cooperative agreement 1425-98-FC-40-22640, 59 p.

Rakotonarivo, S., Legris, M., Desmare, R., Sessarego, J-P., Bourillet, J-F., 2011, Forward 

modeling of marine sediment characterization using chirp sonars: Geophysics, v. 76, p. T91-

T99.

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.

Randle, T.J., and Pemberton, E.L., 1987, Results and analysis of STARS modeling efforts of the 

Colorado River in Grand Canyon: Washington, D.C., U.S. Department of the Interior, 

Bureau of Reclamation, NTIS report no. PB88-183421/AS. 

Rubin, D.M., Chezar, H., Harney, J.N., Topping, D.J., Melis, T.S., and Sherwood, C.R., 2007, 

Underwater microscope for measuring spatial and temporal changes in bed-sediment grain 

size: Sedimentary Geology, v. 202, no. 3, p. 402-408, 

http://dx.doi.org/10.1016/j.sedgeo.2007.03.020.

Rubin, D.M., Tate, G.B., Topping, D.J., and Anima, R.A., 2001, Use of rotating side-scan sonar 

to measure bedload, in Seventh Federal Interagency Sedimentation Conference, Reno, Nev., 

March 25-29, 2001, Proceedings: Subcommittee on Sedimentation, v. 1, p. III-139 to III-143.

136
Rubin, D.M., Topping, D.J., Schmidt, J.C., Hazel, J., Kaplinski, M., and Melis, T.S., 2002, 

Recent sediment studies refute Glen Canyon Dam hypothesis: Eos Transactions, American 

Geophysical Union, v. 83, no. 25, p. 273, p. 277-278.

Rubin, D.M., and Topping, D.J., 2001, Quantifying the relative importance of flow regulation 

and grain size regulation of suspended sediment transport alpha and tracking changes in grain 

size of bed sediment beta: Water Resources Research, v. 37, no. 1, p. 133-146.

Schmidt, J.C., 1999, Summary and synthesis of geomorphic studies conducted during the 1996 

controlled flood in Grand Canyon, in Webb, R.H., Schmidt, J.C., Marzolf, G.R., and Valdez, 

R.A., eds., The controlled flood in Grand Canyon: Washington, D.C., American Geophysical 

Union, Geophysical Monograph Series, v. 110, p. 329–341.

Schmidt, J.C., and Rubin, D.M., 1995, Regulated streamflow, fine-grained deposits, and 

effective discharge in canyons with abundant debris fans, in Costa, J.E., Miller, A.J., Potter, 

K.W., and Wilcock, P.R., eds., Natural and Anthropogenic Influences in Fluvial 

Geomorphology, Geophysical Monograph Series, vol. 89: Washington, D.C., AGU, p. 177-

195.

Schmidt, J.C., 1990, Recirculating flow and sedimentation in the Colorado River in Grand 

Canyon, Arizona: The Journal of Geology, v. 98, no. 5, p. 709-724.

Schmidt, J.C., and Graf, J.B., 1990, Aggradation and degradation of alluvial sand deposits, 1965 

to 1986, Colorado River, Grand Canyon National Park, Arizona: U.S. Geological Survey 

Professional Paper 1493, 74 p.

Schmidt, J.C., Grams, P.E., and Leschin, M.F., 1999, Variation and magnitude of deposition and 

erosion in three long-term (8-12 km) reaches as determined by photographic analyses, in

Webb, R.H., Schmidt, J.C., Marzolf, G.R., and Valdez, R.A., eds., The controlled flood in 

Grand Canyon: Washington, D.C., American Geophysical Union, Geophysical Monograph 

Series, v. 110, p. 185–204.

Schmidt, J.C., Topping, D.J., Grams, P.E., and Hazel, J.E., Jr., 2004, System-wide changes in the 

distribution of fine sediment in the Colorado River corridor between Glen Canyon Dam and 

Bright Angel Creek, Arizona--final report: Logan, Utah, submitted to U.S. Geological 

Survey, Grand Canyon Monitoring and Research Center, cooperative agreement no. 1425-

98-FC-40-22640, 107 p., 

http://www.gcmrc.gov/library/reports/Physical/Fine_Sed/Schmidt2004.pdf.

Schmidt, J.C., and Grams, P.E., 2011, The high flows – physical science results, in Melis, T.S. 

(ed.), Effects of three high-flow experiments on the Colorado River ecosystem downstream 

from Glen Canyon Dam, Arizona: U.S. Geological Survey Circular 1366, p. 53-92.

Schock, S.G., 2004, A method for estimating the physical and acoustic properties of the sea bed 

using chirp sonar data: IEEE Journal of Oceanic Engineering, v. 29, p.1200-1217.

Schock, S.G., LeBlanc, L.R., and Mayer, L.A., 1989, Chirp subbottom profiler for quantitative 

sediment analysis: Geophysics, v. 54, p. 445-450, 

http://library.seg.org/doi/pdf/10.1190/1.1442670.

Simmons, S.M., Parsons, D.R., Best, J.L., Orfeo, O., Lane, S.N., Kostaschuk, R., Hardy, R.J., 

West, G., Malzone, C., Marcus, J., and Pocwiardowski, P., 2010, Monitoring suspended 

sediment dynamics using MBES: Journal of Hydraulic Engineering, v. 136, no. 1, p. 45-49.

Simons, D.B, Richardson, E.V., Nordin, C.F, Jr., 1965, Bedload equation for ripples and dunes: 

U.S. Geological Survey Professional Paper 462-H, http://pubs.usgs.gov/pp/0462h/report.pdf.

Topping, D.J., Rubin, D.M., Grams, P.E., Griffiths, R.E., Sabol, T.A., Voichick, N., Tusso, R.B., 

Vanaman, K.M., and McDonald, R.R., 2010, Sediment transport during three controlled137
flood experiments on the Colorado River downstream from Glen Canyon Dam, with 

implications for eddy-sandbar deposition in Grand Canyon National Park: U.S. Geological 

Survey Open-File Report 2010-1128, 111 p., http://pubs.usgs.gov/of/2010/1128/.

Topping, D.J., Wright, S.A., Rubin, D.M., and Melis, T.S., 2007, Draft report to the technical 

work group of the Glen Canyon Dam Adaptive Management Program--recommended 

protocols for core monitoring of sediment within the Colorado River Ecosystem below Glen 

Canyon Dam, part IV--developing a scientifically based long-term monitoring plan for the 

GCDAMP: U.S. Geological Survey, Grand Canyon Monitoring and Research Center, 

Flagstaff, Ariz., 34 p.

Topping, D.J., Rubin, D.M., Schmidt, J.C., Hazel, J.E., Jr., Melis, T.S., Wright, S.A., Kaplinski, 

M., Draut, A.E., and Breedlove, M.J., 2006, Comparison of sediment-transport and barresponse results from the 1996 and 2004 controlled-flood experiments on the Colorado River 

in Grand Canyon, in Federal Interagency Sedimentation Conference, 8th, Reno, Nev., April 

2-6, 2006, Proceedings: p. 171-179 (CD-ROM).

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 Glen Canyon Dam: Water Resources 

Research, v. 36, p. 515−542.

U.S. Geological Survey, 2006, Strategic science plan to support the Glen Canyon Dam Adaptive 

Management Program, fiscal years 2007–11: Grand Canyon Monitoring and Research Center 

in cooperation with the Glen Canyon Dam Adaptive Management Program, 11 p., 

www.usbr.gov/uc/rm/amp/amwg/mtgs/06dec05/Attach_07b.pdf.

Webb, R.H., Griffiths, P.G., Melis, T.S., and Hartley, D.R., 2000, Sediment delivery by ungaged 

tributaries of the Colorado River in Grand Canyon: U.S. Geological Survey Water-Resources 

Investigations Report 00–4055, 67 p., 

http://www.gcmrc.gov/library/reports/physical/coarse_sed_webb/wrir2000_00-4055s.pdf.

Westoby, M.J., J. Brasington, N.F. Glasser, M.J. Hambrey, J.M. Reynolds, ‘Structure-frommotion’ photogrammetry--a low-cost, effective tool for geoscience applications: 

Geomorphology, v. 179, p. 300-314, http://dx.doi.org/10.1016/j.geomorph.2012.08.021.

Wiele, S.M., Wilcock, P.R., and Grams, P.E., 2007, Reach-averaged sediment routing model of a 

canyon river: Water Resources Research, v. 43, no. W02425, p. 1-16, 

http://www.agu.org/journals/wr/wr0702/2005WR004824/.

Wiele, S.M., and Griffin, E.R., 1998, Modifications to a one-dimensional model of unsteady 

flow in the Colorado River through Grand Canyon, Arizona: U.S. Geological Survey WaterResources Investigations Report 97-4046, 17 p.

Wiele, S.M., and Smith, J.D., 1996, A reach-averaged model of diurnal discharge wave 

propagation down the Colorado River through the Grand Canyon: Water Resources 

Research, v. 32, no. 5, p. 1375-1386.

Wiele, S.M., Graf, J.B., and Smith, J.D., 1996, Sand deposition in the Colorado River in the 

Grand Canyon from flooding of the Little Colorado River: Water Resources Research, v. 32, 

p. 3579-3596. 

Wiele, S.M., Andrews, E.D., and Griffin, E.R., 1999, The effect of sand concentration on 

depositional rate, magnitude, and location in the Colorado River below the Little Colorado 

River, in Webb, R.H., Schmidt, J.C., Marzolf, G.R., and Valdez, R.A., eds., The controlled 

flood in Grand Canyon: Washington, D.C., American Geophysical Union, Geophysical 

Monograph Series, v. 110, p. 131-145.

138
Wright, S.A., and Grams, P.E., 2010, Evaluation of water year 2011 Glen Canyon Dam flow 

release scenarios on downstream sand storage along the Colorado River in Arizona: U.S. 

Geological Survey Open-File Report 2010-1133, 19 p., http://pubs.usgs.gov/of/2010/1133/.

Wright, S.A., and Kaplinski, M., 2011, Flow structures and sandbar dynamics in a canyon river 

during a controlled flood, Colorado River, Arizona: Journal of Geophysical Research, v. 116, 

no. F01019, p. 15, http://www.agu.org/pubs/crossref/2011/2009JF001442.shtml.

Wright, S.A., Topping, D.J., Rubin, D.M., and Melis, T.S., 2010a, An approach for modeling 

sediment budgets in supply-limited rivers: Water Resources Research, v. 46, no. W10538, p. 

1-18, http://www.agu.org/pubs/crossref/2010/2009WR008600.shtml.

Wright, S.A., Topping, D.J., Rubin, D.M., and Melis, T.S., 2010, Modeling long-term sediment 

budgets in supply-limited rivers, in Hydrology and sedimentation for a changing future; 

existing and emerging issues (Joint Federal Interagency Conference 2010--Federal 

Interagency Hydrologic Modeling, 4th, and Federal Interagency Sedimentation, 9th), Las 

Vegas, Nev., June 27- July 1, Proceedings.

Wright, S.A., Schmidt, J.C., Melis, T.S., Topping, D.J., and Rubin, D.M., 2008, Is there enough 

sand? Evaluating the fate of Grand Canyon sandbars: Geological Society of America Today, 

v. 18, no. 8, p. 4-10, http://www.geosociety.org/gsatoday/archive/18/8/pdf/i1052-5173-18-8-

4.pdf.

Wright, S.A., Melis, T.S., Topping, D.J., and Rubin, D.M., 2005, Influence of Glen Canyon Dam 

operations on downstream sand resources of the Colorado River in Grand Canyon, in Gloss, 

S.P., Lovich, J.E., and Melis, T.S., eds., The state of the Colorado River ecosystem in Grand 

Canyon: U.S. Geological Survey Circular 1282, p. 17−31.

Zeiler, M., Schulz-Ohlberg, J., and Figge, K., 2000, Mobile sand deposits and shoreface 

dynamics in the inner German Bight (North Sea): Marine Geology, v. 170, 363-380.

 

139
G. Budget 

Project Element 3.1.1 Project Element 3.1.2 Project Element 3.1.3

Salaries $ 106,670 Salaries $ 103,477 Salaries $ 18,724 

Traveling and Training $ 2,000 Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ 4,000 Operating Expenses $ - Operating Expenses $ - 

Logistics $ 26,568 Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 156,060 Cooperators (non-USGS) $ - 

p (

USGS) $ 20,000 

USGS Cooperators $ 48,000 USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 26,960 USGS Burden $ 16,556 USGS Burden $ 3,596 

Total $ 370,259 Total $ 120,033 Total $ 42,320 

Project Element 3.1.4 Project Element 3.2 Project Element 3.3

Salaries $ 15,979 Salaries $ 163,741 Salaries $ 64,687 

Traveling and Training $ - Traveling and Training $ 2,000 Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ 27,000 Operating Expenses $ - 

Logistics $ - Logistics $ 29,679 Logistics $ - 

Cooperators (non-USGS) $ 68,415 Cooperators (non-USGS) $ 196,075 

p (

USGS) $ 25,000 

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 4,609 USGS Burden $ 41,469 USGS Burden $ 11,100 

Total $ 89,003 Total $ 459,965 Total $ 100,787 

Project Element 3.4 Project Element 3.5

Salaries $ - Salaries $ 77,068 

Traveling and Training $ - Traveling and Training $ 1,900 

Operating Expenses $ - Operating Expenses $ 15,000 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 35,000 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 1,050 USGS Burden $ 15,035 

Total $ 36,050 Total $ 109,003 

$ 1,327,420

FY 2015

FY 2015 Project 3 Gross Total:

Project Element 3.1.1 Project Element 3.1.2 Project Element 3.1.3

Salaries $ 109,061 Salaries $ 107,235 Salaries $ 19,099 

Traveling and Training $ 2,000 Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ 4,000 Operating Expenses $ - Operating Expenses $ - 

Logistics $ 27,828 Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 156,060 Cooperators (non-USGS) $ - 

Coope ato s ( o

USGS) $ 20,000 

USGS Cooperators $ 20,000 USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 36,117 USGS Burden $ 23,592 USGS Burden $ 4,802 

Total $ 355,066 Total $ 130,827 Total $ 43,901 

Project Element 3.1.4 Project Element 3.2 Project Element 3.3

Salaries $ 16,299 Salaries $ 167,016 Salaries $ 67,515 

Traveling and Training $ - Traveling and Training $ 2,000 Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ 27,000 Operating Expenses $ - 

Logistics $ - Logistics $ 64,474 Logistics $ - 

Cooperators (non-USGS) $ 68,415 Cooperators (non-USGS) $ 196,075 

p (

USGS) $ 25,000 

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 5,638 USGS Burden $ 63,190 USGS Burden $ 15,603 

Total $ 90,352 Total $ 519,755 Total $ 108,118 

Project Element 3.4 Project Element 3.5

Salaries $ - Salaries $ 79,360 

Traveling and Training $ - Traveling and Training $ 1,900 

Operating Expenses $ - Operating Expenses $ 15,000 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 35,000 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 1,050 USGS Burden $ 21,177 

Total $ 36,050 Total $ 117,437 

$ 1,401,506

FY 2016

FY 2016 Project 3 Gross Total:

140
Project Element 3.1.1 Project Element 3.1.2 Project Element 3.1.3

Salaries $ 114,218 Salaries $ 110,281 Salaries $ 20,048 

Traveling and Training $ 2,000 Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ 4,000 Operating Expenses $ - Operating Expenses $ - 

Logistics $ 29,088 Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 156,060 Cooperators (non-USGS) $ - 

Coope ato s ( o

USGS) $ 20,000 

USGS Cooperators $ 20,000 USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 46,488 USGS Burden $ 30,879 USGS Burden $ 6,214 

Total $ 371,855 Total $ 141,160 Total $ 46,262 

Project Element 3.1.4 Project Element 3.2 Project Element 3.3

Salaries $ 16,852 Salaries $ 174,705 Salaries $ 70,978 

Traveling and Training $ - Traveling and Training $ 2,000 Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ 27,000 Operating Expenses $ - 

Logistics $ - Logistics $ 66,664 Logistics $ - 

Cooperators (non-USGS) $ 68,415 Cooperators (non-USGS) $ 196,075 

Coope ato s ( o

USGS) $ 25,000 

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 6,771 USGS Burden $ 81,585 USGS Burden $ 20,624 

Total $ 92,038 Total $ 548,029 Total $ 116,602 

Project Element 3.4 Project Element 3.5

Salaries $ - Salaries $ 80,947 

Traveling and Training $ - Traveling and Training $ 1,900 

Operating Expenses $ - Operating Expenses $ 15,000 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 35,000 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 1,050 USGS Burden $ 27,397 

Total $ 36,050 Total $ 125,244 

$ 1,477,240

FY 2016

FY 2016 Project 3 Gross Total:

141
Project 4. Connectivity along the fluvial-aeolian-hillslope 

continuum: quantifying the relative importance of riverrelated factors that influence upland geomorphology and 

archaeological site stability 

A. Investigators 

Joel Sankey, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Amy East (formerly Amy Draut), Research Geologist, U.S. Geological Survey, Pacific Coastal 

and Marine Science Center

Helen Fairley, Research Specialist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Joshua Caster, Geographer, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

B. Project Summary 

The connectivity, or potential for movement of sand by wind, between active channel 

sandbars and higher elevation sand landscapes has important implications for the effects of dam 

operations on archaeological sites and other cultural and natural resources within the Colorado 

River ecosystem (CRe). In particular, quantifying the relative importance and interactions of 

wind, rain, river-related factors, and riparian zone characteristics that might affect connectivity 

can provide insight into the influence of dam operations on the condition of archaeological sites. 

This proposal is composed of two integrated elements. The elements are: 1) a landscape scale 

analysis of the connectivity between fluvial processes and patterns in the active channel of the 

Colorado River (generally below the 45,000 ft3

/s stage) and geomorphic processes and patterns 

at higher elevations (above the 45,000 ft3

/s stage); and 2) implementation of a long-term 

monitoring component to evaluate if and how much the interactions between fluvial, aeolian, and 

hillslope processes affect the condition of cultural resource sites in the Colorado River corridor. 

The second element is intended to address Department of Interior agency requirements for 

monitoring effects of dam operations on cultural resources in compliance with the Grand Canyon 

Protection Act and in accordance with the terms of a negotiated programmatic agreement under 

the National Historic Preservation Act. 

C. Background

C.1. Scientific Background 

The environmental processes and factors that contribute to the current condition of cultural 

resources in the CRe are complex. Because the vast majority of archaeological sites in the CRe 

are situated well above the elevation reached by 25,000 ft3

/s river flows (Sondossi and Fairley, in 

revision), effects of dam operations on cultural sites are mainly indirect and manifest themselves 

through diffuse effects to the larger terrestrial ecosystem (Fairley and others, 1994; Fairley and 

Sondossi, 2010). The 1995 Environmental Impact Statement on the Operations of Glen Canyon 

Dam (USDI 1995) identified 336 sites in Grand, Marble, and Glen Canyons that were considered 

142
to be directly or indirectly affected by dam operations. These archaeological sites are situated in 

or on Holocene fine-sediment fluvial deposits derived from the Colorado River that were formed 

either before or after completion of Glen Canyon Dam (GCD). 

Interest in the potential of dam operations to affect erosion rates at cultural resource sites in 

the CRe dates back to the early 1980s, when NPS archaeologists observed an increase in the 

amount and severity of gullying at archaeological sites (Hereford and others, 1991; Fairley, 

2003). This topic was also identified by the Hopi Tribe as an important issue to understand, 

because these processes influenced the Hopi’s perspective on whether mitigation of potential 

dam effects to archaeological sites would, or would not, be appropriate to undertake (L. 

Kuwanwisiwma, personal communication, 1990, to H. Fairley). In 1989, a decision by the 

Department of Interior to undertake research on the downstream effects of Glen Canyon Dam 

resulted in the initiation of several studies focused on mapping the geomorphic context of 

archaeological resources and the geomorphic processes acting on those resources (Hereford and 

others, 1991, 1993, 1996; Lucchitta, 1991). This initial phase of research led to the publication of 

several detailed surficial geology maps that emphasized the distribution of Holocene deposits in 

areas of high cultural resource density, plus several reports documenting changes in the post-dam 

environment (Hereford and others, 1993, 1996; Hereford, Burke and Thompson, 1998, 2000a, 

2000b; Lucchitta, 1991).

Subsequent work during multiple decades (e.g., Draut and others, 2005, 2010; Draut and 

Rubin, 2008; Collins and others, 2008, 2009, 2012; Draut 2012) has collectively indicated that a 

post-dam reduction in fine sediment supply (Topping and others, 2003) contributed to a 

reduction in active channel sandbars that are available for transport to high elevation sand

deposits where archaeological sites are often located (Draut, 2012). This same phenomenon 

appears to have also reduced the resilience of the upland landscape to weather-induced erosional 

impacts, as illustrated for example, by the fact that locations with less high elevation sand have 

greater prevalence of gullies from rainfall-runoff erosion (Sankey and Draut, in press). Draut 

(2012) and Draut and Rubin (2008) proposed that the upland sand deposits in the river corridor 

can be broadly grouped into those with modern sand supply by wind from river sandbars 

(modern-fluvial-sourced sand deposits, hereafter referred to as MFS) and those that have not 

received sand in post-dam time, but received their most recent major sediment replenishment 

from deposits associated with the 1921 flood of 170,000 ft3

/s (relict-fluvial-sourced deposits, 

hereafter referred to as RFS; Draut, 2012). Available evidence indicates that sediment supply 

limitation and lack of large floods, in conjunction with increased biological soil crust cover, has 

further reduced mobility of high-elevation sand deposits, with multiple interacting effects to 

surface erosion processes in and adjacent to archaeological sites and associated Holocene 

deposits (Draut, 2012). Work conducted in 2013 and 2014 (Project J of the FY 13/14 Biennial 

Work Plan) described the extent to which aeolian sand provides a protective cover to the ground 

surface of archaeological sites, and even infills – with potential to mitigate – eroding gullies 

within and adjacent to archaeological sites (Sankey and Draut, in press; Collins and others, in 

review). Very recent work has also qualitatively described the role, in many locations, of riparian 

vegetation that produces a barrier to the onshore and upslope transport by wind of MFS aeolian 

sand (Draut East, 2014), thus segregating the general category of MFS landscapes into additional 

categories reflecting the varying degrees to which sites receive modern sand resupply based on 

whether vegetation impedes aeolian transport of sand from a fluvial sandbar to an archaeological 

site. 

143
Recent work has quantified the long-term trend of the lowering and encroachment of riparian 

vegetation into the former active channel in response to decreased flood magnitude and duration 

(Sankey and others, in preparation). During the same post-dam timeframe, periods of increases 

and decreases in xeric (upland, desert) vegetation have occurred at higher stage-elevations in 

response to regional climate and episodes of drought (Sankey and others, in preparation). While 

environmental factors, including fluvial sources of aeolian sand and riparian vegetation, have 

been identified previously (Draut, 2012; Collins and others, in review) as important controls on 

connectivity along the fluvial-aeolian-hillslope continuum, the relative prevalence and 

importance of many of these controls have not been explicitly tested over large geographic extent 

or multi-temporal scales. We define connectivity (Merriam, 1984) as the “degree to which a 

landscape facilitates or impedes movement among resource patches” (Taylor and others, 1993), 

and focus specifically on the potential for movement of sand by wind between active channel 

sandbars to higher elevation sand landscapes. Potentially important controls on connectivity 

include: upwind sand bars that are resupplied by controlled floods (administratively referred to 

as High Flow Experiments or HFEs); alternative sediment sources including tributary 

channels/mouths, bare sediment surfaces on terrace risers, campsites and other high user impact 

areas; vegetation (either barriers positioned between fluvial sand bars and upland areas or cover 

of formerly open sand [source] areas); and, topographic barriers such as rock outcrops and debris 

fans. 

In addition to the recent work conducted at landscape scales that has identified some of the 

important controls on connectivity along the fluvial-aeolian-hillslope continuum, site-specific 

monitoring has identified that many archaeological sites are dominated by erosion processes that 

include discrete runoff erosion events that can lower the ground surface several centimeters over 

areas as large as tens to hundreds of square meters (Collins and others, 2012; Collins and others, 

in review). In addition to aeolian influx of fluvial sediment, potentially important controls on site 

erosion also include proposed mitigation treatments such as the installation of check dams that 

might control expansion and propagation of gullies. Possible vegetation treatments that remove 

or reduce dense vegetation barriers also might be employed to promote aeolian transport of 

fluvially sourced sand to higher elevations. Defoliation of tamarisk caused by the recent spread 

of the tamarisk beetle (Diorhabda carinulata) is also a contemporary environmental factor that 

might increase the potential for aeolian sand transport through vegetation barriers, and may have 

effects similar to vegetation removal treatments. 

Most recent small spatial scale monitoring work in Grand Canyon has been conducted with 

terrestrial (ground-based) lidar remote sensing. Collins and Kayen (2006) first demonstrated 

lidar’s potential utility for documenting topographic and vegetation change in the CRe. A phased 

program of research and development was initiated between 2006 and 2010 towards 

implementation of a long-term core-monitoring program (Fairley and others, 2007). The first 

phase of this project (Phase I) began in spring 2006 and initially focused on completing a 

comprehensive assessment of the geomorphic and archaeological attributes of 232 river corridor 

sites (O’Brien and Pederson, 2009a) to characterize the range of variability in these 

archaeological sites and to aid in the selection of an appropriate sample for a future pilot 

monitoring program (Vance and Smiley, 2011). Phase I involved testing a variety of survey 

techniques, including terrestrial lidar, as potential tools for measuring change in resource 

condition (Collins and others, 2008).

The applicability and utility of monitoring archaeological sites using terrestrial lidar was 

subsequently demonstrated at 13 sites in Grand Canyon (e.g., Collins and others, 2008, 2009, 

144
2012). Collins and others, (2008) showed that terrestrial lidar technology could be used to collect 

data as accurate as or better than previously evaluated total station topographic surveys, while 

minimizing impacts to the sites being monitored; total station techniques had been previously 

evaluated as a potential monitoring approach (Leap and others, 2000). Several criticisms of the 

total station method that led to the investigation of lidar as an alternative tool included the fact 

that total station surveys often resulted in significant impacts (e.g., trampling) to sites, and the 

resolution and measurement error in repeated surveys was potentially greater than the amount of 

change targeted for detection. The work of Collins and others, (2008) documented that entire site 

areas could be monitored with lidar with minimal impact. Initially, Collins and others (2009) 

documented surface-elevation changes greater than 8 cm at 6 of 9 sites monitored between 

September 2006 and September 2007. Since these initial field studies, advances in lidar 

technology have resulted in laser scanning devices with greater accuracy and new software with 

improved potential to measure small-scale (centimeter-level) topographic change (Collins and 

others, 2012). Incorporating these advances, Collins and others (2012) collected multiple 

comparable lidar data sets at 11 sites during a 5-year period. This effort demonstrated that (1) 

land surface change of ~ 5 cm could be reliably and accurately detected over large areas, and (2) 

it is possible to link observed changes to specific geomorphic processes.

Work completed in 2013 and 2014 incorporated additional lidar surveys into a synthesis of 

more than 5 years of surface-elevation data and change detection at archaeological sites in Grand 

Canyon and sought to link measured landscape changes to meteorological conditions (Collins 

and others, January 28, 2014 GCMRC Annual Reporting Meeting, and Collins and others, in 

review). Key findings of this work were that erosion dominates the landscape response at most 

sites, in large part because high intensity, runoff producing storms that sometimes induce erosion 

and gullying are relatively common within Grand Canyon. Precipitation records from the past 

century indicate that storms comparable to those that induce significant overland flow occur 

during years of average and wet conditions. Erosion-inducing storms occur at individual sites 

with frequencies that range from approximately once per year to once per decade, and results 

suggest that such storms occur at a majority of sites at least once every 2-3 years. The synthesis 

also identified the influx of aeolian sand – and specifically the infilling of individual gullies by 

aeolian sand – as a key landscape process that can mitigate erosion and the formation and 

propagation of gullies.

In conjunction with the work in 2013 and 2014 that was conducted at landscape scales 

(Sankey and Draut, in press) and site-specific scales (Collins and others, in review) and that 

quantified the importance of aeolian influx to gullied archaeological sites, additional novel work 

developed a system for classifying archaeological sites based on the degree to which the sites 

could potentially receive windblown sand from recent controlled floods (East, 2014). The 

classification of additional archaeological sites is currently ongoing and is anticipated to be 

completed in 2014 for sites within Grand Canyon National Park. All river-corridor 

archaeological sites will be classified based on an evaluation of geographic position relative to 

visible recent flood-sediment deposits, measured or inferred local prevailing wind directions, and 

identification of any potential barriers to aeolian sand transport between flood deposits and 

archaeological sites. The classification system identifies whether a site’s geomorphic context 

includes river-derived sediment—either fluvial, aeolian, or both. The system also identifies 

whether barriers exist that could limit the aeolian transport of upwind fluvial sediment by wind 

to archaeological site(s). There are 5 types of sites included in the classification:

145
Type 1: Sites with an adjacent, upwind fluvial sediment deposit formed by a recent high 

flow, and no evident barriers that would hinder aeolian sand transport from the flood 

deposit toward the archaeological site. 

Type 2: Sites with an upwind sediment deposit formed by a recent flood, but with a 

barrier separating the flood deposit from the archaeological site. These barriers were 

interpreted to potentially limit aeolian sand transport from the fluvial deposit toward the 

archaeological site. Such barriers may not entirely eliminate sand movement from fluvial 

deposit to archaeological site, but are interpreted as likely to inhibit aeolian sand 

transport.

2a: Vegetation barrier present (may be riparian or higher-elevation, non-riparian 

upland vegetation).

2b: Topographic barrier present (most often a tributary channel, but in several 

cases a steep bedrock cliff). 

2c: Both vegetation and topographic barriers present.

Type 3: Sites at which a recent flood did not deposit sediment upwind of site, even 

though flood water had been present at an upwind location relative to the archaeological 

site (where an upwind shoreline exists for a recent controlled flood).

Type 4: Sites at which there is no upwind shoreline that could allow deposition from a 

recent controlled flood, but whose geomorphic context does involve river-derived sand 

deposited by pre-dam floods. 

Type 5: Sites in the river corridor whose geomorphic context is not dependent on 

Colorado River-derived sand, such as those situated on bedrock or talus.

For the purposes of this proposal, we have considered the recent synthesis of 5 years of 

monitoring surface-elevation changes at archaeological sites in Grand Canyon (Collins and 

others, in review) in the context of the site classification system (Figure 1). We note that this 

evaluation presently includes only a limited sample size, and that increasing the number of sites 

available for such evaluations is one of the goals of the work we propose herein. Some of the 

largest surface elevation changes attributed to rainfall events – and including erosion and 

deposition by aeolian and overland flow transport – occurred at sites classified as type 1. , 

Upwind fluvial sediment deposits formed by recent controlled flood(s) occur at these type 1 

sites, and there were no barriers to hinder aeolian sand transport from the flood deposit toward 

the archaeological sites. However, fewer than half of these type 1 sites (two of the five type 1 

sites; Figure 1) exhibited measureable aeolian deposition during the period of analysis (e.g., note 

the large standard error of the mean bar for aeolian deposition at type 1 sites). Moreover, a 

majority of the sites for which detailed data are available (8 of the 13 total sites), encompassing a 

variety of classes, had measurable aeolian erosion (deflation). Thus, interpretation of the sitespecific surface elevation changes in the context of the archaeological site classification suggests 

that most sites of all classes are likely not transport limited with respect to aeolian processes (i.e., 

wind energy is often sufficient for transport). However, apparently even the most favorably 

positioned sites (e.g., type 1) with respect to fluvial sources of aeolian sand can still be lacking in 

either sediment source and/or possibly the right temporal and spatial interaction of wind energy 

146
and sediment availability to cause net long-term deposition and improve the chance of 

archaeological-site preservation in place.

Clearly, the classification system developed in 2013 and 2014, and the actual classification of 

archaeological sites, creates an important framework that should be further evaluated as a guide 

for future monitoring and research efforts. In particular, the classification provides scientists and 

managers with hypotheses that can be tested concerning the expected future landscape response 

of individual archaeological sites relative to dam operations and high flow events. The 

classification also promotes hypothesis testing concerning the future landscape response of 

individual sites to the potentially interacting effects of dam operation and high flow events with 

contemporary and possible future mitigation efforts such as erosion control check dams and 

riparian vegetation reduction treatments. 

Figure 1. Volumetric surface change (by type and process) at archaeological sites, measured with lidar, and summarized by 

archaeological site class. Individual site change data are from Collins and others, (in review) and are summarized by classes. 

Changes were determined at 1-3 year intervals for 13 sites between 2006 and 2010. Error bars show the standard error of the 

mean for n sites. 

C.2. Management Background 

Project 4 has been designed to be responsive to the stated goals of the GCDAMP, the 

monitoring requirements of the Grand Canyon Protection Act, the recommendations of the 2000 

PEP (Doelle, 2000) and the 2007 Legacy Monitoring Data review panel (Kintigh and others, 

2007). Project 4 has also been designed to be responsive to the needs of DOI agencies related to 

compliance with Section 106 and Section 110 of the National Historic Preservation Act for 

assessing effects of dam operations and effectiveness of experimental management actions such 

as HFEs, as well as the effectiveness of other non-flow management actions that may be initiated 

in the future to achieve the management goals for in situ preservation of archaeological sites.

When BOR decided to modify operations at Glen Canyon Dam in the early 1980s in order to 

increase peaking power generation, they initiated a series of environmental discussions and 

studies that led to development of an EIS and Record of Decision under the National 

0

5

10

15

20

25

30

35

40

45

50

Type 1

(n = 5)

 Type 2a and 2b

(n = 4)

 Type 3 and 4

(n = 4)

Volume Change (m3)

Archaeological Site Classification

Runoff Erosion

Aeolian Erosion

Runoff Deposition

Aeolian Deposition

147
Environmental Policy Act (USDOI 1995, 1996) and a programmatic agreement (PA) under the 

National Historic Preservation Act, all three of which included provisions to continue monitoring 

and researching effects of dam operations on archaeological sites and other cultural resources. 

Prior to these events, Grand Canyon National Park (GCNP) archeologists had been monitoring 

cultural sites in the river corridor since the late 1970s, using a monitoring approach that was 

designed to document the presence or absence of visitor use impacts and other types of threats 

and disturbances (Kintigh and others, 2007). These threats and disturbances included qualitative 

observations about erosion that potentially compromised the integrity of cultural sites. 

The NPS monitoring approach, which was subsequently incorporated as the interim approach 

for monitoring dam effects under the PA, relies on assigning sites by categorical monitoring 

criteria that are supplemented with repeat photographs of impacted areas. Maps are drawn to 

show locations of specific impacts. Monitoring is performed to meet the Park’s compliance 

obligations under Section 110 of the National Historic Preservation Act (NHPA) and to 

demonstrate progress towards achieving federally-mandated goals for historic preservation under 

the Government Performance and Results Act. The NPS monitoring program also identified sites 

that may require excavation or other forms of “treatment” to preserve their cultural, historic, and 

scientific values. This same approach is currently used by GCNP archaeologists to monitor 

impacts associated with implementing the Colorado River Management Plan and to monitor sites 

on the canyon rims (E. Brennan, personal communication to the workshop participants at August 

2011 Knowledge Assessment Workshop).

In 2000, a cultural resources Protocol Evaluation Panel (PEP) recommended redesigning the 

PA monitoring program to focus more specifically on monitoring the effects of dam operations 

and evaluating the efficacy of erosion control efforts (Doelle, 2000). Although effects of dam 

operations were not specifically defined by the PEP, it is clear from the context of discussion in 

the PEP report that effects of dam operations were thought to be those changes in the physical 

condition of archaeological resulting from the direct inundation of sites and increases in rates of 

erosion resulting from sediment supply limitations due to the presence and operation of Glen 

Canyon Dam. Although the PEP criticized the “overly narrow focus, adoption, and reliance on 

the ’base-level’ hypothesis developed by Hereford and others”, geomorphologists on the panel 

recognized that “dam operations must contribute to the spatial and temporal variability in rates of 

erosion of deposits along the river corridor” to some unknown degree. They also noted that the 

aeolian hypothesis, as proposed by Thompson and Potochnik (2000), “had not been adequately 

tested” and that “broader research on the topic would be useful.” Thus, the PEP felt that it was 

important to structure the future monitoring program to distinguish and track the effects of dam 

operations separately from other non-dam-related impacts that can also affect cultural site 

condition, such as social trailing and artifact loss due to visitation. Specifically, the PEP 

recommended that the monitoring activities of the NPS and GCMRC should be integrated and 

refocused to: (1) evaluate the effectiveness of long-term management strategies (including 

treatments designed to control/minimize dam-related erosion) and (2) evaluate effects of 

different flow regimes on archaeological sites and other cultural resources such as Traditional 

Cultural Properties (TCPs). The PEP noted that “monitoring should be designed and organized to 

serve as the basis for periodic quantitative evaluations of the effect of dam operations, 

effectiveness of erosion control methods, and development of treatment plans”. These 

recommendations were later echoed and further refined by the members of the legacy monitoring 

review committee (Kintigh and others, 2007), who emphasized the need for “unpacking the 

concept of site condition” to distinguish dam-related effects from other sources of impacts to 

148
cultural sites and for developing an explicit model to describe our understanding of how dam 

operations affect site condition, and then design a monitoring protocol that could explicitly test 

and evaluate the model.

Throughout the history of the GCDAMP, there has been ongoing discussion and considerable 

debate about the need for monitoring programs in general and what purpose(s) monitoring is 

supposed to serve. In general terms, monitoring can serve a broad variety of purposes (Hellawell, 

1991):

• To assess the effectiveness of policy or legislation;

• To comply with regulatory requirements (performance or audit function); and,

• To detect incipient change (“early warning system”).

Noon (2003) proposed an additional reason: to “assess the value and temporal (or spatial) 

trend of those indicators that characterize the state of an ecological system”. In the GCDAMP 

generally, and in the cultural program arena specifically, all of these reasons have been cited as 

driving the need for monitoring (GCDAMP, 2003). Additionally, there is concern with meeting 

legal mandates, such as those identified in the Grand Canyon Protection Act (GCPA), which 

calls for “long term monitoring programs and activities that will ensure that Glen Canyon Dam is 

operated in a manner consistent with that of Section 1802.” Section 1802 requires that the dam 

be operated in such a manner as to “protect, mitigate adverse impacts to, and improve the values 

for which Grand Canyon National Park and Glen Canyon National Recreation Area were 

established including, but not limited to natural and cultural resources and visitor use.” In 

addition, there are legal obligations embedded within the National Historic Preservation Act 

(NHPA) that require federal agencies to consider effects of their actions on cultural resources 

(NHPA, Section 106) and also for the responsible land manager to identify, evaluate, and protect 

historic properties under their care (NHPA, Section 110). While monitoring is not specifically 

required for compliance with NHPA, monitoring is routinely implemented as a component of 

Section 106 compliance programs to assess effects of management actions or to evaluate the 

effectiveness of mitigation measures.

In the 2003 Strategic Plan (GCDAMP, 2003), GCDAMP stakeholders distinguished two 

monitoring categories: “Core Monitoring” and “Effects Monitoring”. The GCDAMP developed 

the following definition of core monitoring:

Core monitoring consists of consistent, long-term, repeated measurements using set 

protocols and is designed to establish status and trends in meeting specific management 

objectives. Core monitoring is implemented on a fixed schedule regardless of variable 

factors or circumstances (e.g., water year, experimental flows, temperature control, 

stocking strategy, non-native control, etc.) affecting target species.

Effects monitoring, on the other hand, was defined as:

... the collection of data associated with an experiment performed under the Record of 

Decision, an unanticipated event, or other management action. Changes in resource 

conditions measured by effects monitoring generally will be short-term responses. The 

purpose of effects monitoring is to supplement the fixed schedule and variables collected 

under core monitoring. This will both increase the understanding of the resource status 

149
and trends and provide a research opportunity to discover the effect of the experiment or 

management action.

The project described here will implement monitoring protocols to address both “core 

monitoring information needs” (CMINs) and “effects information needs” (EINs) for cultural 

sites in Glen and Grand Canyons. The highest priority CMIN for historic properties, as revised 

by the Cultural Resource Ad Hoc Group (CRAHG) and adopted by the Science Planning Group

(SPG) of the GCDAMP in the fall of 2005, is:

CMIN 11.1.1 (SPG revised). Determine the condition and integrity of prehistoric and 

historic sites in the CRe through tracking rates of erosion, visitor impacts, and other 

relevant variables. Determine the condition and integrity of TCPs in the CRe.

In 2007, an expert panel reviewed the previous PA monitoring protocols and existing NPS 

monitoring data and developed recommendations for potentially incorporating these “legacy” 

monitoring data into future monitoring programs for the GCDAMP (Kintigh and others, 2007). 

Among several recommendations, the panel recommended that the monitoring program be 

redesigned to “unpack” the concept of site condition and separate out the factors affecting site 

condition that are potentially dam-related from those that are not (Wood and Johnson, 1978; 

Wildesen, 1982; Jones, 2007). The panel suggested that data from historical photographs might 

be productively mined in the future to evaluate changes that have already occurred to the sites 

through time. In addition, the reviewers suggested exploring the use of lidar technology as a tool 

for measuring and tracking ongoing surface changes at archaeological sites that are potentially 

linked to dam operations. At the same time, the panel recommended developing a model 

reflecting current understanding of how dam operations affect archaeological site condition, and 

to use the monitoring program to evaluate whether model predictions conform to monitoring 

results. The current proposal incorporates all of these recommendations.

This project is designed to address two primary Strategic Science Questions (SSQs) 

identified in the 2007 Monitoring and Research Plan (GCMRC, 2007):

• SSQ 2-1. Do dam-controlled flows affect (increase or decrease) rates of erosion and 

vegetation growth at archaeological sites and TCP sites in the CRE, and if so, how?

• SSQ 2-4. How effective are various treatments (e.g., experimental flows, check dams, 

vegetation management, etc.) in slowing rates of erosion at archaeological sites over the 

long term?

A high-quality monitoring program is also essential for determining whether management 

actions designed to stabilize or improve site conditions are working as intended. Therefore, this 

project also directly addresses EIN 11.1 (formerly CMIN 11.1.2 of the GCDAMP Strategic Plan, 

subsequently re-designated by CRAHG/SPG as EIN 11.1):

• EIN 11.1. Determine the efficacy of treatments for mitigation of adverse effects to 

historic properties.

Additionally, this project addresses a general GCDAMP research information need

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(formerly identified as CMIN 11.1.4 in the 2001 GCDAMP Strategic Plan):

How effective is monitoring, what are the appropriate strategies to capture change

at an archaeological site – qualitative, quantitative?

More recently, AMP stakeholders have worked with DOI management agency personnel to 

craft descriptions of desired future conditions (DFCs) for resources in the CRe, which are 

intended to provide general targets for resource conditions to guide future monitoring and 

management projects, and the Department of Interior has accepted these DFCs as official 

program guidance (Salazar, 2012). The DFCs for archaeological sites identify preservation in 

place as the desired goal for archaeological sites and identify rates of erosion or deposition as 

one metric for assessing whether desired future conditions are being achieved. The DFCs do not 

specify what rates of erosion or deposition are necessary to meet (or not meet) the desired 

condition, however, and this is an area of inquiry that the current proposal would help to resolve. 

Other metrics for assessing cultural resource condition include the presence of other impacts that 

affect National Register eligibility of sites (such as evidence of artifact collecting and deliberate 

vandalism). These latter impacts are not necessarily dam-related, however, and therefore would 

not be a focus of the future monitoring program being proposed by GCMRC. However, by 

combining the data that will be collected through the currently proposed project, along with other 

data that is being routinely collected by NPS to meet their Section 110 obligations and Section 

106 obligations for other management purposes such the 2005 Colorado River Management 

Plan, plus monitoring data that is currently being collected by tribal stakeholders, it is possible to 

achieve multiple related objectives for monitoring cultural resource condition in the CRe.

The process of developing a new Long Term Experimental and Management Plan (LTEMP) 

to guide future operations of Glen Canyon Dam has highlighted the need for additional 

monitoring data that can help us better understand how dam-controlled flows affect cultural 

resource condition. Completion of the LTEMP may also introduce additional needs for 

monitoring in the future. While those additional monitoring needs are currently unknown, the 

monitoring plan that is proposed for development as part of Project Element 4.2 will be 

designed, at a minimum, to track the effects to cultural resources of whatever preferred 

alternative flow regime is ultimately selected.

C.3. Key Monitoring and Research Questions Addressed in this project 

In element 4.1., the primary question that we will ask is: (1) How do the contemporary location 

and size of active and inactive aeolian sand deposits vary spatially throughout the river corridor 

as a function of, and in proximity to, controls that we have identified or hypothesized to be 

important? We hypothesize that important controls include:

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• Upwind sand bars subject to scour and fill during HFEs

• Other sediment sources including deposits in tributary mouths, bare sediment surfaces on 

terrace treads and risers, campsites, and other high user impact areas

• Vegetation (either thick vegetation barriers that occur between fluvial sand bars and 

upland areas or cover of formerly open sand [source] areas)

• Topographic barriers including rock outcrops, debris fans, and tributary channels, and 

terrace risers

The second question that we will ask is how have location and size of active and inactive 

upland sand units varied temporally in the contemporary period of restricted power plant 

operation with controlled floods? This work will consider temporal changes relative to the 

hypothesized important controls presented above and employ interpretation of digital imagery 

acquired by overflights since 2002. We propose to test the following hypotheses: 

• The distribution of aeolian sand has varied as a function of vegetation changes, and 

episodes of decreased potential for aeolian activity are evident in response to vegetation 

expansion at low elevations and increased potential for aeolian activity are evident in 

response to vegetation decreases (“drought pruning”) at high elevations

A third question we will consider is how has the presence of active and inactive aeolian sand 

varied within archaeological sites over longer-term pre- to post-dam time periods? Building on 

earlier work (Draut and Rubin, 2008) that found limited utility of the analog aerial photograph 

record for identifying trends in aeolian sand cover but recommended using oblique historical 

photographs for this purpose, this work will consider temporal changes in historical oblique 

photos and will test the following hypotheses:

• Cultural sites currently situated in inactive aeolian areas (areas that no longer receive 

aeolian sand inputs from upwind source areas) have more biologic crust cover and/or 

more vegetation cover today than in the past, and

• Cultural sites currently situated in inactive aeolian areas have more and/or larger gullies 

than in the past. 

The fourth question that we will ask is: How are the processes and controls that govern 

aeolian-fluvial-hillslope connectivity impacted by the different effects that river regulation has 

on rivers? Answering this last question will involve a comparison of findings related to questions 

1-3 asked in Grand Canyon with observations in Desolation and Gray Canyons of the Green 

River; we will specifically investigate whether, in the Desolation-Gray Canyon system with 

greater fluvial sediment supply and larger annual spring floods, there exists a greater proportion 

of active aeolian sand in upland sediment deposits than occurs in Grand Canyon. We are seeking 

non-GCDAMP funding for this last sub-element.

In element 4.2., we propose to draft and implement a monitoring plan that is designed to 

identify whether, and how much, HFE sand is transported by wind to a representative sample of 

archaeological sites, and then to measure the effect that wind transported sand has on site surface 

condition and site stability (i.e., the degree to which these processes mitigate effects from 

precipitation-induced gully erosion and other surface impacts). Review, approval, and 

implementation of the monitoring plan will require that BOR, NPS, and the tribes work very 

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closely with GCMRC to come to agreement about the full scope and specific objectives of the 

monitoring program. In addition to satisfying BOR’s Section 106 compliance responsibilities and 

to meeting legal requirements of GCPA for monitoring how changes in dam operations affect 

resource condition, the proposed monitoring program will be designed to test the following 

hypotheses:

• Cultural sites where adjacent, upwind fluvial sediment deposits form by high flow events, 

and that have unimpeded aeolian sand transport from the flood deposit toward the 

archaeological site (i.e., type 1), show less erosional surface change than sites of the other 

classification types (types 2-4) where either lack of sediment sources, presence of 

transport barriers, or both are potentially limiting factors, and where other factors 

(weather conditions, drainage catchment size) are approximately equivalent.

• Cultural sites where transport barriers are present, but fluvial source of aeolian sand is 

also present (i.e., type 2), show less erosional surface change than sites with no current 

fluvial source of aeolian sand (type 3 or 4).

Since approximately 30 sites within the Grand Canyon portion of the river corridor have 

received erosion control treatments (check dams) in the past (Leap and others, 2000), we also 

plan to further explore the efficacy of check dam treatments as a mitigation measure by 

evaluating potential differences in erosion condition between treated and untreated sites. While 

acknowledging that we might be limited logistically in our ability to sample a large number of 

sites with check dam treatments and untreated control sites, if sample sizes allow, we would 

propose to test the following two hypotheses:

• Cultural sites with check dams show less evidence of gully erosion than sites without 

check dams, regardless of whether or not they are situated downwind of open sand areas 

(e.g., among all archaeological site classes), and

• Cultural sites with check dams that are situated downwind of open sand source areas (i.e., 

type 1 and type 2 sites) show less evidence of gully erosion than sites with check dams 

that are not situated downwind of open sand source areas (i.e., type 3 and 4 sites).

D. Proposed Work 

D.1. Project Elements 

Project Element 4.1. Quantifying connectivity along the fluvial-aeolian-hillslope continuum at landscape 

scales 

(Recommended for funding FY15: $212,725)

Joel Sankey, Research Geologist, USGS, GCMRC

Amy Draut East, Research Geologist, USGS, PCMSC

Helen Fairley, Research Specialist, USGS, GCMRC

Joshua Caster, Geographer, USGS, GCMRC

The primary objective of Project Element 4.1 is to explain how connectivity along the 

fluvial-aeolian-hillslope continuum varies spatially throughout the river corridor and to 

determine if this connectivity has changed during the recent decades of restricted power plant 

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operation and the occurrence of controlled floods. As noted previously, we define connectivity 

(Merriam, 1984) as the “degree to which a landscape facilitates or impedes movement among 

resource patches” (Taylor and others, 1993). This project element includes three sub-elements 

that examine connectivity by focusing on the potential for movement of sand by wind from 

active channel sandbars to higher elevation sand landscapes. In the context of landscape 

connectivity, vegetation and topography have the potential to decrease the distance that sand can 

be transported, by decreasing the length of the connected pathway between source (e.g. sandbar) 

and sink (MFS sandscape) (Okin and others, 2009). The project elements are designed to 

examine the nature of connectivity between sand in the active channel of the Colorado River and 

higher elevation sand patches and to examine the factors that control these redistribution 

processes at different spatial and temporal scales. The first project sub-element, examines 

landscape-scale spatial variability using a combination of remote sensing and GIS analyses of 

existing digital imagery and topography data to test hypotheses developed during the FY 13–14 

work-cycle about what environmental factors related to river operations control the location and 

size of aeolian sand deposits and whether or not these deposits contribute to the stability of 

archaeological sites. The second project sub-element will extend the first analysis farther back in 

time by conducting visual interpretation of historical oblique photos to assess whether 

hypothesized changes due to dam operations are supported by photographic evidence. The third 

project sub-element will investigate how the processes and controls that govern connectivity are 

impacted by the effects of river regulation on sediment supply. This last sub-element will 

contrast observations of aeolian sand distribution in Grand Canyon with other, analogous river 

systems, specifically Desolation and Gray Canyons of the Green River. The sub-elements are 

each described in further detail below.

In the first sub-element, we will conduct landscape-scale, remote sensing and GIS analyses 

of existing digital imagery and topography as well as geospatial databases developed and 

previously reported on for work conducted in the FY 13–14 work plan (Sankey and Draut, in 

press; Draut East,2014). We will spatially analyze the relative importance of the hypothesized 

controls independently for each date of “corridor-wide” digital imagery and topography that we 

have (e.g., 2002, 2009, and 2013). Methodological steps will be to first expand the aeolian sand 

map completed for the FY 13–14 work plan to include the greater river corridor using image 

classification techniques and the existing maps as training data to identify river-derived upland 

sand (above 45,000 ft3

/s) that is active or inactive with respect to aeolian transport. In defining 

areas that are ‘active’ with respect to aeolian sediment transport, we assume that sand deposits 

are active where there is open sand area lacking vegetation, biologic soil crust, or matter other 

than sand; these are places where sediment forms wind-rippled surfaces and, locally, dune 

slipfaces at the angle of repose, thus meeting the criteria for ‘active aeolian sand’ defined by 

Lancaster (1994). We will next quantify relationships of the spatial proximity of aeolian sand 

units and their areal dimensions to the location and dimensions of adjacent and upwind fluvial 

sand (sandbar) deposits. We will similarly quantify relationships of aeolian sand units to 

alternative sediment sources that are adjacent and upwind, including exposed terrace scarps, 

tributary mouths, and open campsite areas. Work completed in the FY 13–14 work plan 

described the role, in many locations, of riparian vegetation that produces a barrier to the inland 

and upslope transport of fluvially-sourced aeolian sand (Draut East,2014). Previous work also 

quantified the long-term trends of: (1) riparian vegetation that has consistently increased at lower 

elevations and encroached towards increasingly lower elevations in response to decreased flood 

magnitude and duration; (2) xeric (upland) vegetation that has exhibited increases and decreases 

154
at higher elevations in response to regional climate and specifically episodes of drought (Sankey 

and others, in preparation). Therefore, an important step will also be to examine how the 

presence, dimensions, and long-term stability of vegetation located between aeolian sand 

deposits and active channel sandbars, or formerly open sand areas, are related to the distribution 

and size of contemporary mapped aeolian sand deposits. Finally, we will quantify temporal 

changes in area and dimensions of aeolian sand units and attempt to explain changes as a 

function of variability in fluvial sand sources, alternative fine-sediment sources, and transport 

barriers. We will conduct the change analysis for the decadal time period between 2002 and 2013 

for which high resolution digital imagery are available. We propose to statistically test the 

independent and interacting effects of the hypothesized explanatory variables for the response of 

aeolian sand unit area and change. Statistical tests may employ mixed model analysis with 

hypothetical effects (predictor variables) that could include, for example: distance and direction 

to fluvial sand; area of fluvial sand; distance, direction to, and area of vegetation barrier; stageelevation of aeolian sand; relief or elevation difference between aeolian and fluvial sand; 

distance and direction to alternative sediment sources or topographic barriers such as camp sites 

or tributary channels, respectively; inferred or measured wind direction (including predominant, 

in addition to secondary or less common, wind directions where such information are available); 

as well as additional and potentially random effects such as geomorphic reach or distance from 

Glen Canyon Dam. The work in the first sub-element will be led by Joel Sankey with 

collaboration from Amy Draut East and Joshua Caster.

In the second sub-element, we will extend the analysis back farther in time, to ascertain the 

degree to which environmental conditions at or near cultural sites have changed during the past > 

50 years by comparing conditions in areas that appear to have functioned differently as aeolian 

landscapes in the past compared to current conditions. This work will be completed using 

qualitative visual comparisons of historical oblique imagery and current surface conditions. 

Although the exact number of images that will be analyzed is currently unknown, we anticipate 

that several hundred historical images (>600) will be examined, of which perhaps 150-200 will 

contain information directly relevant to this analysis. Methods will include visual evaluations of 

area and cover of bare sand, soil crust, and vegetation. Images capturing cultural sites and 

aeolian sand source areas by photographers such as Stanton (1890), Birdseye (1923), Schwartz 

(1965), Euler (1960s), Shoemaker (1969), and Webb and others, (1990, 2010) will be the focus 

of the analysis. Historical photographs and recent imagery will be carefully examined and 

qualitatively assessed in terms of whether the imagery shows more or less biologic crust cover, 

vegetation cover, surface inflation or deflation, and other evidence of erosion or surface stability 

within specific areas designated as cultural sites and also within the areas that appear to have 

served as aeolian source areas to cultural sites (Figure 2). Changes in vegetation composition, 

density, biocrust cover, and evidence of surface deposition or erosion will be assigned to ranked 

categories reflecting “no apparent change”, “minimal change”, and “significant change”. We also 

propose to experimentally apply some automated techniques to digitized imagery to further 

quantify the changes in the amount of lateral vegetation cover evident in the photos. The current 

state of cultural sites and aeolian sand areas will be similarly assessed based on recent site photos 

as well as recent site descriptions (e.g., from site investigation work completed in 2013 and 

2014). An important outcome of this analysis will be an estimate of the proportion of previously 

classified cultural sites for which the potential influence of aeolian sand inputs has changed with 

time, as reflected in changes in aeolian-sand-dependent environmental characteristics such as 

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vegetation and biologic crusts. The work in the second sub-element will be led by Helen Fairley 

with collaboration from Joel Sankey, Amy East, and Joshua Caster.

Figure 2. (Top) Stanton photograph of the Fossil area, looking downstream, February, 1890, Center photo: 1990. Bottom photo: 

May, 2014. In all three photos, the biologic composition (small arrowweed shrubs, bunch grasses, and lack of biocrust) is 

indicative of an active aeolian landscape, but note that the density and also pedestaling of some plants appears to have increased

through time. Note also that there appears to be a greater exposure of rocks and deepening of swales in the sand dune surface in 

156
2014 relative to the earlier photos. The arrow in the 2014 photo points towards a gully that formed in 2007 and is the focus of 

monitoring with repeat lidar surveys by Collins and others, (2012).

In the third sub-element, we will investigate how the processes and controls that govern 

connectivity are impacted by the different effects of river regulation on sediment supply. This

work will contrast observations in Grand Canyon with those in Desolation and Gray Canyons of 

the Green River, Utah. There, previous mapping has shown that numerous large aeolian deposits 

exist (Elliott, 2002) that are likely sourced from fluvial sandbars. In that system with greater 

fluvial sand supply and a flow regime that more closely resembles natural flows, we aim to map 

active and inactive sand deposits and to map the distribution of gullies. We will evaluate whether 

there is widespread evidence of gully annealing. This will also complement comparative work 

done in the Colorado River corridor through Cataract Canyon (Draut, 2012), but using a canyon 

where aeolian dunes are a more common feature of upland river-corridor morphology. The work 

in the third sub-element will be led by Amy Draut East, conducted by an M.S. student at Utah 

State University supervised by J.C. Schmidt, with collaboration from Joel Sankey.

Project Element 4.2. Monitoring of cultural sites in Grand and Glen Canyons 

(Recommended for funding FY15: $123,624)

Joel Sankey, Research Geologist, USGS, GCMRC

Helen Fairley, Research Specialist, USGS, GCMRC

Amy East, Research Geologist, USGS, PCMSC

Joshua Caster, Geographer, USGS, GCMRC

The primary objectives of Project Element 4.2. are to 1) draft and 2) implement a monitoring 

plan that meets requirements for monitoring effects of dam operations to cultural resources 

relative to the requirements of the Grand Canyon Protection Act and the terms of a new 

Programmatic Agreement currently being developed to achieve BOR’s Section 106 compliance 

under the National Historic Preservation Act for the Long Term Experimental and Management 

Plan (LTEMP). At a minimum, the monitoring plan will be designed to identify whether, and 

how much, HFE sand is transported by wind to a representative sample of archaeological sites 

and to measure the effect of the wind-transported sand on site surface condition and site stability 

(i.e., the degree to which this mitigates effects from gully erosion and other surface impacts). 

Year 1 of the project will focus on drafting, reviewing, revising, and pursuing approval for the 

monitoring plan. Years 2 and 3 of the project will focus on implementing the monitoring plan. 

The draft plan will make a recommendation of the sample of archaeological sites that should be 

monitored, but stakeholders (presumably including the BOR, NPS, and tribes) will need to work 

very closely with GCMRC in year 1 of the project to come to agreement about the full scope and 

specific objectives of the monitoring program. 

The BOR has explicitly recommended that the draft monitoring plan consider the following 

22 points (M. Barger, email communication, May 19 2014, to J. Sankey) and GCMRC will 

evaluate these recommendations in the course of drafting the plan as well as any additional 

recommendations provided by other stakeholders: 

1. Focus on sites that would benefit from HFE sand (types 1 and 2a, maybe 2b and 2c);

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2. For those sites identified in #1, describe a method to determine which sites could receive

enough sand to make a difference e.g. the HFE sand bar is large enough, the vegetation 

barrier is not too dense or the topographic barrier is not too large;

3. Define how much sand is needed to benefit a site that is eroding (this may be part of the 

methodology);

4. Include criteria to determine where to focus the monitoring effort on such sites (gullies?); 

5. Include the number of sites and schedule/interval of monitoring events that would be 

statistically significant; 

6. State criteria to be used in the evaluation of effectiveness that the HFE sand is making a 

difference for site erosion/stability;

7. Include a form used for any monitoring;

8. Define qualifications of the monitors;

9. State criteria to determine if covering the site with HFE sand would be an adverse effect 

by changing the site’s setting; 

10. State criteria to determine any other negative (adverse) effects from HFE sand on or 

across sites;

11. Include strategies to re-evaluate sites to see if their type has changed; include strategies 

for removing sites from monitoring if HFE sand is either 1) not reaching the site or 2) not 

effective for stabilizing erosion; 

12. Precisely define all monitoring attributes that will be used (e.g. how will you use lidar?); 

13. For monitoring not using lidar, include what will be measured;

14. Since geomorphic conditions can vary from time to time based on sand availability and 

weather conditions, state how temporal variations of this type will be incorporated into 

the assessment of effectiveness; 

15. State the criteria by which plant cover will be evaluated in relation to sand transport to 

and across the site (this could include how evaluate cryptogamic crust); 

16. How you will determine if the archaeological assemblage is in situ or has been lowered to 

an erosional surface (mixing of components); and 

17. Define the criteria for active vs. inactive sand;

18. Where weather station is used, describe what data is collected and how it will be 

analyzed;

19. Where remote cameras will be used, describe what data is collected and how it will be 

analyzed;

20. Describe how new sites (discoveries) will be addressed and assigned a type;

21. Include a method to report findings to the PA signatories; and

22. The GCMRC’s geoarchaeologist should be instrumental in developing this plan.

While most of the points raised by BOR are appropriate for GCMRC to consider in 

developing the monitoring plan, some (e.g., #9 and #10) might involve value judgments that will 

need to be resolved by the management agencies and other signatories to the new PA.

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We propose to design the monitoring plan in the context of the archaeological site 

classification developed and applied in 2013 and 2014 (East, 2014) which provides useful, sitespecific expectations of landscape response to dam operations and controlled floods. While 

recent monitoring efforts have focused on the use of lidar to measure topographic changes, in 

drafting the monitoring plan we will also consider the use of other monitoring methods and tools. 

In particular, we will consider protocols and tools that might be used by NPS and/or tribes on 

river trips that aren’t led by GCMRC personnel. This might include, for example, keeping track 

of presence of sandbars upwind of archaeological sites with repeat oblique photography, tracking 

changes in the lateral cover and porosity of vegetation barriers with repeat oblique photography, 

measuring area of active aeolian sand at sites and between HFE deposits and archaeological 

sites, measuring the cover and stature and spacing of vegetation at sites or between HFE deposits 

and sites, and documenting wind directions near fluvial sandbars from sand shadows, ripples, 

and dune slip faces. 

In drafting the monitoring plan, we will consider the recent synthesis of 5 years of 

monitoring surface-elevation changes from lidar at archaeological sites in Grand Canyon 

(Collins and others, in review) in the context of the site classification system (Figure 1). Figure 1 

shows the mean response with time of runoff and aeolian surface change for different classes of 

archaeological sites measured with lidar during site investigations between 2006 and 2010. The 

large uncertainties (shown by bars that are the standard error of the mean for n sites in Figure 1) 

demonstrate the inherent limitations associated with the small sample sizes of the present 

monitoring program (# of sites per class). Therefore, while the existing lidar monitoring data 

provide useful information about landscape response to dam operations and controlled floods, 

additional data (i.e., additional sites but also additional repeat visits of previously measured sites) 

are required to tighten the uncertainty about the mean responses and identify any observed 

differences that are statistically significant.

Summary of existing lidar monitoring data indicate that type 1 and 2 sites – which have 

upwind sources of flood-supplied sand but differ in terms of the existence of transport barriers –

exhibit some of the largest surface elevation changes attributed to aeolian processes (Figure 1); 

an expected result based on the site class definitions. However, fewer than half of these type 1 (2 

of 5 sites) and type 2 (2 of 4 sites) sites exhibited measureable aeolian deposition during the time 

period of analysis. Moreover, a majority of all sites (8 of 13 total sites), encompassing a variety 

of classes, had measurable aeolian erosion. Therefore, our current interpretation of the sitespecific surface elevation changes in the context of the archaeological site classification suggests 

that most sites of all classes are likely not transport limited with respect to aeolian processes (i.e., 

wind energy is often sufficient for transport), however, even the most favorably positioned sites 

(type 1 and type 2) with respect to fluvial sources of aeolian sand can still be lacking in either 

sediment source and/or possibly the right temporal and spatial interaction of wind and sediment 

availability to cause net long-term deposition and improve the chance of archaeological-site 

preservation in place. The site-specific surface-elevation lidar monitoring employed for these 

analyses was conducted with repeat site measurements on the order of once every 1-3 years 

(Collins and others, in review); field campaigns were strategically designed such that every site 

under consideration wasn’t necessarily measured in a single campaign or year, but a longer term 

record of change was still amassed for a maximum number of sites (Table 1). In the context of 

the archaeological site classification system, change detection results by volume, mechanism and 

type (runoff erosion, aeolian erosion, runoff deposition, aeolian deposition) will have been 

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derived by the end of 2014 for various intervals between 2006 and 2014 at five type 1 sites, four 

type 2 sites, five type 3 sites, and three type 4 sites (Table 1).

Table 1. Summary of measurement intervals for lidar change detection by archaeological site

Lidar Change Intervals

Site 

Jurisdiction

Class 5/2006-

5/2007

5/2007-

9/2007

9/2007-

4/2010

9/2007-

9/2010

4/2010-

9/2010

11/2012-

11/2013

5/2013-

5/2014

1 GRCA 1 x x

2 GRCA 1 x x

3 GRCA 1 x x

4 GRCA 1 x x x x

5 GRCA 1 x x x x

6 GRCA 2a x x x

7 GRCA 2a x x

8 GRCA 2b x x x

9 GRCA 2b x x

10 GLCA 3 x

11 GLCA 3 x

12 GLCA 3 x

13 GLCA 3 x

14 GRCA 3 x x

15 GRCA 4 x x x

16 GRCA 4 x x x x

17 GRCA 4 x x x x

In drafting the monitoring plan, we will consider whether the continuation of detailed 

characterization of topographic changes with lidar, such as conducted by Collins and others (in 

review) is necessary for monitoring whether and how much HFE sand is transported by wind to 

archaeological sites, and to measure the effect that wind transported sand has on site surface 

condition and site stability. We might, for example, propose to incorporate additional sites to the 

set measured by Collins and others, (in review) and in surveys completed in 2013 and 2014, such 

that we maintain a meaningful number of sites (i.e., n = 4 clearly presents limitations for 

evaluating the central tendency and uncertainty among classes of sites; even a slightly larger 

sample size might be extremely useful for identifying the variety of landscape process trends) of 

each of the classification types 1, 2 (a+b), 3 and 4. With the combination of the existing and new 

terrestrial lidar survey time series data in addition to other measurements that may be made as 

part of the new monitoring protocol, we will be positioned to answer the following questions:

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1. Do sites where adjacent, upwind fluvial sediment deposits form by high flow events, and 

unimpeded aeolian sand transport from the flood deposit toward the archaeological site 

(i.e., type 1), show different types of surface change and less erosion by gullies and 

overland flow than sites of the other classification types where either lack of sediment 

source, presence of transport barriers, or both are potentially limiting factors?

2. Do sites where transport barriers are present, but fluvial source of aeolian sand is also 

present (i.e., type 2), show different types of surface change and less erosion by gullies 

and overland flow than sites without a fluvial source of aeolian sand (type 3 or 4)? 

Check dams have been installed at several sites by the NPS and, depending on the 

recommendations of stakeholders, could also be considered in addition to aeolian sand influx as 

a possible interacting control on erosion and surface elevation changes within archaeological 

sites. Sites of any classification type where check-dam-type erosion control treatments have been 

applied might be expected to benefit from interacting effects of dam operations and high flow 

events with the erosion control treatments. It might not be logistically feasible to monitor the 

large number of sites from each class that might be required to test for significant effects and 

interactions of site class and check dam treatments. However, in drafting the monitoring plan, we 

will consider the potential of using the combination of the existing and new terrestrial lidar 

survey time series data to ask, “Do sites of any classification type that have check dams exhibit 

surface elevation changes and types of change that appear to be anomalous relative to those 

without check dams?”

Vegetation barriers are perceived as the most temporally transient obstacle to aeolian influx 

for sites that have a modern fluvial source of aeolian sand. Defoliation of tamarisk owing to the 

recent spread of the tamarisk beetle is one of the only contemporary environmental factors that 

might increase the potential for aeolian sand transport through vegetation barriers. Potential 

future vegetation reduction treatments might also be useful for promoting aeolian sand transport 

from fluvial sources to upslope cultural sites. In drafting the monitoring plan, we will consider 

the potential for using existing airborne lidar data (from previous high density airborne lidar 

acquired in 2013–2014 in GLCA; Collins and others, in press) in addition to existing or new 

terrestrial lidar site surveys as appropriate, to evaluate effects of changes in porosity, stature, and 

spacing of vegetation barriers, such as might occur with tamarisk defoliation or potential 

treatments that would reduce or remove the barrier of vegetation within units of active aeolian 

sand and between fluvial sources of sand and higher elevation cultural sites. We could for 

example, examine natural gradients of vegetation cover and porosity, as well as manipulate the 

lidar datasets to represent different levels of cover and porosity – e.g., that could be characteristic 

of different intensities of vegetation treatments or defoliation – and use an aeolian transport 

model to estimate potential sediment fluxes for the different vegetation treatment scenarios. The 

methodology for this work has been previously tested and published by Sankey and others, 

(2013) for different levels of mesquite encroachment in a Sonoran desert vegetation community 

and the transport model is presented in Okin (2008) and validated in Li and others, (2013).

Ground based lidar has proven to be a useful and efficient tool for tracking fine-scale 

changes of upland environments associated with cultural sites in Glen, Marble and Grand 

Canyons, and the technology also holds promise for future interdisciplinary physical science and 

aquatic ecology work at GCMRC focused on mapping terrestrial settings and near-shore 

environments. Although in past years GCMRC has relied on personnel and equipment from other 

161
USGS centers to perform lidar surveys, for future monitoring that uses lidar, we intend to rely on 

“in-house” terrestrial lidar capacity at GCMRC. This would require the purchase of a lidar 

scanner and hiring of a survey/scanner technician prior to implementing the monitoring plan. 

River trips in year 2 and year 3 would likely be conducted to collect lidar topography using 

protocols developed and tested in the FY13–14 and prior GCMRC work plans. Pending NPS 

approval, the currently deployed automated weather stations and stationary cameras (installed in 

FY13) would continue to collect data on local weather conditions at 24.5 mile, 70 mile, 126 mile, 

and 223 mile (all type 1 sites in the recent classification) to refine our current understanding of 

how local weather events contribute to the erosion and/or deposition measured at this sample of 

type 1 sites; these data are useful for attributing site-specific surface elevation changes to 

meteorological events. The weather stations that are currently deployed in GRCA are permitted 

to collect data through April 30, 2015, and we will discuss with the NPS extension of the permit 

through the duration of this project (December, 2017). 

D.2. Personnel and Collaborations 

This project builds upon several past research efforts, including very recent work completed 

in 2013 and 2014 by Sankey and Draut (in press), Collins and others, (in review, in press), Draut 

East (2014). It builds upon the previous work of Draut and Rubin (2006, 2008), Draut and others, 

(2005, 2009a, 2009b, 2010a, 2010b), Draut (2011, 2012), Pederson and others, (2003, 2006) 

O’Brien and Pederson (2009a, 2009b), Damp and others, (2007), Fairley and others, (2007; 

Fairley and Sondossi 2010) and Collins and others, (2008, 2009, 2012). Specifically, it directly 

builds upon the Phase I work of the Cultural Monitoring Research and Development Project by 

applying the knowledge gained through that effort (Collins and others, 2008, 2009, 2012, in 

press); Draut and others, 2009a, 2009b, 2010a, 2010b; O’Brien and Pederson 2009a, 2009b) to 

track and quantify dam-related topographic changes (i.e., amounts and rates of erosion and 

deposition from fluvial sand sources) occurring at cultural sites throughout the CRe. 

This study complements Grand Canyon National Park’s CRMP monitoring program. 

Monitoring protocols for assessing impacts of human visitation at archaeological sites have been 

developed independently by GRCA staff to serve the monitoring needs of the Park Service for 

evaluating effects of visitation at cultural sites, and tribal monitoring programs also collect 

qualitative data related to visitor use impacts. These data will be drawn upon in the analysis of 

the results of this project specifically to determine whether measured surface changes correlate 

with NPS’s documentation of visitor use levels, as reflected in monitored visitor use impacts. 

The quantitative approaches for monitoring change in archaeological site condition developed 

through the previous cultural monitoring R&D effort and proposed for implementation now as 

part of this project will supplement and enhance the qualitative, observational monitoring 

protocols and data developed by NPS for CRMP compliance and by the tribes who monitor 

resource conditions in Grand Canyon through the adaptive management program.

D.3. Deliverables 

For element 4.1, at least one journal article or professional USGS report will be prepared in 

FY17 for each sub-element. These publications are expected to address several of the themes of 

the proposed work, including: 

• connectivity along the fluvial-aeolian-hillslope continuum in Grand Canyon;

• implications of river regulation, and variability in downstream responses of rivers to 

dams, for connectivity along the fluvial-aeolian-hillslope continuum;

162
• documenting changes in the size and location of aeolian sand dominated landscapes, as 

determined from the analysis of historical oblique photographs;

• evaluating potential effectiveness of management treatments for promoting aeolian 

redistribution of fluvially-sourced sand along the fluvial-aeolian-hillslope continuum, and 

mitigating erosion of cultural sites in Grand Canyon

For element 4.1, if funding is secured for the third sub-element that will contrast observations 

of aeolian sand distribution in Grand Canyon with other, analogous river systems, a thesis and 

journal publication will be produced from this work.

For element 4.2, the monitoring plan will be drafted in FY15, and a monitoring report will be 

completed in FY17 that reports on the monitoring that is implemented in FY16 and FY17.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

E.2. Completed Publications 

Hereford, R., Bennett, G.E., and Fairley, H.C., 2014, Precipitation variability of the Grand 

Canyon region, 1893 through 2009, and its implications for studying effects of gullying of 

Holocene terraces and associated archeological sites in Grand Canyon, Arizona: U.S. 

Geological Survey Open-File Report 2014–1006, 23 p., 

http://dx.doi.org/10.3133/ofr20141006.

Sankey, JB, Draut, AE, in press. Gully annealing by aeolian sediment: Field and remote-sensing 

investigation of aeolian-hillslope-fluvial interactions, Colorado River corridor, Arizona, 

USA. Geomorphology , doi:10.1016/j.geomorph.2014.05.028

Collins, BD, Corbett, SC, Sankey, JB, Fairley, HC, in press. High resolution topography and 

geomorphology of select archaeological sites in Glen Canyon National Recreation Area, AZ. 

US Geological Survey, Scientific Investigations Report 2014-XXXX

Dealy, T., East, A.E., and Fairley, H.C., in press. Weather and aeolian sand-transport data from 

the Colorado River corridor, Grand Canyon, Arizona: U.S. Geological Survey Open-File 

Report 2014-XXXX, in press.

E.3. Publications in progress 

Collins, B.D., Bedford, D., Corbett, S.C., Cronkite-Ratcliff, C, and Fairley, H.C., in review. 

Meteorologic and anthropogenic effects on archeological site change in Grand Canyon, 

Arizona: fluvial-aeolian interactions within a dam-controlled river corridor. (Submitted to 

Journal of Geophysical Research: Earth Surface)

Caster, J, Dealy, T, Andrews, T, Fairley, H, Draut, A, Collins, B, Sankey, J, Bedford, D. 

Meteorological data for select sites along the Colorado River Corridor, Arizona, 2011-2013, 

US Geological Survey, Data Series Report 2014-XXXX, in preparation.

E.4. Presentations at GCDAMP meetings 

Sankey, JB, Draut, AE, Fairley H, Collins B, Bedford, D, 2014, Gully annealing by aeolian 

sediment: Field and remote-sensing investigation in Glen, Marble, and Grand Canyons. 

Annual Reporting Meeting to the Stakeholders of the Glen Canyon Dam Adaptive 

Management Program, Jan. 29, 2014, Phoenix, AZ

163
Collins, B, Corbett, S, Bedford, D, Fairley, H, Sankey, J, 2014. Quantifying archaeological site 

erosion in Glen Canyon National Recreation Area and Grand Canyon National Park to assist 

sand resource management and operations of Glen Canyon Dam. Annual Reporting Meeting 

to the Stakeholders of the Glen Canyon Dam Adaptive Management Program, Jan. 29, 2014, 

Phoenix, AZ

Collins, B, Corbett, S, Bedford, D, Fairley, H, Sankey, J, 2014. Quantifying archaeological site 

erosion in Glen Canyon National Recreation Area and Grand Canyon National Park to assist 

sand resource management and operations of Glen Canyon Dam. Annual Reporting Meeting 

to the Stakeholders of the Glen Canyon Dam Adaptive Management Program, Jan. 29, 2014, 

Phoenix, AZ (poster)

Collins, B, Corbett, S, Sankey, J, Fairley, H, 2014. High resolution topography and 

geomorphology of select archaeological sites in Glen Canyon National Recreation Area, 

Arizona. Annual Reporting Meeting to the Stakeholders of the Glen Canyon Dam Adaptive 

Management Program, Jan. 29, 2014, Phoenix, AZ (poster)

Sankey, JB, Draut, AE, Fairley H, Collins B, Bedford, D, 2014, Gully annealing by aeolian 

sediment: Field and remote-sensing investigation in Glen, Marble, and Grand Canyons. 

Annual Reporting Meeting to the Stakeholders of the Glen Canyon Dam Adaptive 

Management Program, Jan. 29, 2014, Phoenix, AZ (poster)

Fairley, H, Draut, AE, Sankey, JB, Collins, B, Bedford, D, Corbett, S, 2014. Landscape-scale 

management implications of cultural resource studies. Annual Reporting Meeting to the 

Stakeholders of the Glen Canyon Dam Adaptive Management Program, Jan. 29, 2014, 

Phoenix, AZ.

E.5. Presentations at professional meetings 

Fairley, H., Collins, B., Draut, A., Corbett, S. and Bedford, D., 2014. Evaluating the Effects of 

Glen Canyon Dam on Downstream Archaeological Sites in Glen and Grand Canyons, 

Arizona. 78th annual meeting of the Society for American Archaeology, April 24, Austin, 

TX.

Sankey, JB, Draut, A, 2013, Reconciling historical and contemporary evidence of aeolian-based, 

gully annealing processes in Glen, Marble, and Grand Canyon, USA. American Geophysical 

Union Fall Meeting, Dec 9-13, San Francisco, CA.

F. References 

Collins, B.D., Bedford, D., Corbett, S.C., Cronkite-Ratcliff, C, and Fairley, H.C., in review. 

Meteorologic and anthropogenic effects on archeological site change in Grand Canyon, 

Arizona: fluvial-aeolian interactions within a dam-controlled river corridor. (Submitted to 

Journal of Geophysical Research: Earth Surface)

Collins, BD, Corbett, SC, Sankey, JB, Fairley, HC, in press. High resolution topography and 

geomorphology of select archaeological sites in Glen Canyon National Recreation Area, AZ. 

US Geological Survey, Scientific Investigations Report 2014-XXXX

Collins, B.D., Brown, K.B., and Fairley, H., 2008. Evaluation of Terrestrial LIDAR for 

Monitoring Geomorphic Change at Archaeological Sites in Grand Canyon National Park, 

Arizona: U.S. Geological Survey, Open File Report 2008-1384, 60 p. 

[http://pubs.usgs.gov/of/2008/1384/]. 

164
Collins, B.D. and Kayen, R., 2006. Applicability of Terrestrial LIDAR Scanning for Scientific 

Studies in Grand Canyon National Park, Arizona, U.S. Geological Survey, Open File Report 

2006-1198, 27p, Menlo Park, California, [http://pubs.usgs.gov/of/2006/1198/]. 

Collins, B.D., Minasian, D., and Kayen, R., 2009. Topographic Change Detection at Select 

Archaeological Sites in Grand Canyon National Park, Arizona, 2006-2007: U.S. Geological 

Survey, Scientific Investigations Report 2009-5116, 97p. 

[http://pubs.usgs.gov/sir/2009/5116/]. 

Collins, B.D., Corbett, S., Fairley, H., Minasian, D., Dealy, T.P., and Kayen, R., 2012. 

Topographic Change Detection at Select Archeological Sites in Grand Canyon National Park, 

Arizona, 2007-2010: U.S. Geological Survey, Scientific Investigations Report 2012-XXXX, 

150pg; (http://pubs.usgs.gov/sir/2012/XXXX/).

Damp, J., Pederson, J., and O’Brien, G., 2007, Geoarchaeological Investigations and 

Archaeological Treatment Plan for 151 Sites in the Grand Canyon, Arizona. Unpublished 

report prepared for Bureau of Reclamation, Upper Colorado River Region, Salt Lake City. 

502p.

Doelle, W. H., editor, 2000. Final Report: Cultural Resource Program Assessment. Ms. on file, 

Grand Canyon Monitoring and Research Center, Flagstaff, Ariz.

Draut, A.E., 2011, Vegetation and substrate properties of aeolian dune fields in the Colorado 

River corridor, Grand Canyon, Arizona: U.S. Geological Survey Open-File Report 2011-

1195., 16 p. and 28 tables, at http://pubs.usgs.gov/of/2011/1195/.

Draut, A., 2012, Effects of river regulation on aeolian landscapes, Colorado River, southwestern 

USA: Journal of Geophysical Research – Earth Surface, v. 117, F2, 

doi:10.1029/2011JF002329.

Draut East, A.E., 2014, Summary of Methods Analyzing Potential Aeolian HFE Sediment 

Supply to Individual Archaeological Sites: U.S. Geological Survey Administrative Report, 

11 p.

Draut, A.E., Andrews, T., Fairley, H.C., and Brown, C.R., 2009a, 2007 Weather and aeolian 

sand-transport data from the Colorado River corridor, Grand Canyon, Arizona: U.S. 

Geological Survey Open-File Report 2009-1098, 110 p. [http://pubs.usgs.gov/of/2009/1098/]. 

Draut, A.E., Hazel, J.E., Jr., Fairley, H.C., and Brown, C.R., 2010, Aeolian reworking of 

sandbars from the March 2008 Glen Canyon Dam high-flow experiment in Grand Canyon, in 

Melis, T.S., Hamill, J.F., Bennett, G.E., Coggins, L.G., Jr., Grams, P.E., Kennedy, T.A., 

Kubly, D.M., and Ralston, B.E., eds., Proceedings of the Colorado River Basin Science and 

Resource Management Symposium, November 18-20, 2008, Scottsdale, Arizona: U.S. 

Geological Survey Scientific Investigations Report 2010-5135, 325-331 p., accessed on July 

15, 2010, at http://pubs.usgs.gov/sir/2010/5135/. 

Draut, A.E., and Rubin, D.M., 2005, Measurements of wind, aeolian sand transport, and 

precipitation in the Colorado River corridor, Grand Canyon, Arizona—November 2003 to 

December 2004: U.S. Geological Survey Open-File Report 2005-1309.

Draut, A.E., and Rubin, D.M., 2006, Measurements of wind, aeolian sand transport, and 

precipitation in the Colorado River corridor, Grand Canyon, Arizona—January 2005 to 

January 2006: U.S. Geological Survey Open-File Report 2006-1188, 88 p. [URL 

http://pubs.usgs.gov/of/2006/1188/].

Draut, Amy E., and Rubin, David M. 2008, The role of eolian sediment in the preservation of 

archeologic sites along the Colorado River corridor in Grand Canyon National Park, Arizona: 

U.S. Geological Survey Professional Paper 1756, 71 p. [http://pubs.usgs.gov/pp/1756].

165
Draut, A.E., Rubin, D.M., Dierker, J.L., Fairley, H.C., Griffiths, R.E., Hazel, J.E., Jr., Hunter, 

R.E., Kohl, K., Leap, L.M., Nials, F.L., Topping, D.J., and Yeatts, M., 2005, Sedimentology 

and stratigraphy of the Palisades, Lower Comanche, and Arroyo Grande areas of the 

Colorado River corridor, Grand Canyon, Arizona: U.S. Geological Survey Scientific 

Investigations Report 2005-5072, 68 p. 

Draut, A. E., Rubin, D. M., Dierker, J. L., Fairley, H. C., Griffiths, R. E., Hazel, J. E. Jr., Hunter, 

R. E., Kohl, K., Leap, L. M., Nials, F. L., Topping, D. J., and Yeatts, M., 2008, Application 

of sedimentary-structure interpretation to geoarchaeology in the Colorado River corridor, 

Grand Canyon, Arizona, USA: Geomorphology, v. 101, n. 3, p. 497-509, doi: 

10.1016/j.geomorph.2007.04.032.

Draut, A.E., Sondossi, H.A., Hazel, J.E., Jr., Andrews, T., Fairley, H.C., Brown, C.R., and 

Vanaman, K.M., 2009b, 2008 Weather and aeolian sand-transport data from the Colorado 

River corridor, Grand Canyon, Arizona: U.S. Geological Survey Open-File Report 2009-

1190, 98 p., accessed on August 23, 2010, at http://pubs.usgs.gov/of/2009/1190/. 

Draut, A.E., Sondossi, H.A., Dealy, T.P., Hazel, J.E., Jr., Fairley, H.C., and Brown, C.R., 2010, 

2009 weather and aeolian sand-transport data from the Colorado River corridor, Grand 

Canyon, Arizona: U.S. Geological Survey Open-File Report 2010-1166, 98 p. 

http://pubs.usgs.gov/of/2010/1166/. 

Fairley, H.C., 2003, Changing river: time, culture, and the transformation of landscape in Grand 

Canyon: a regional research design for the study of cultural resources along the Colorado 

River in lower Glen Canyon and Grand Canyon, National Park, Arizona: Tucson, Ariz., 

Statistical Research, Inc., SRI Press, Technical Series 79.

Fairley, H.C., Bungart, P.W., Coder, C.M., Huffman, J., Samples, T.L., and Balsom, J.R., 1994, 

The Grand Canyon river corridor survey project: archaeological survey along the Colorado 

River between Glen Canyon Dam and Separation Rapid: Flagstaff, Ariz., Bureau of 

Reclamation Glen Canyon Environmental Studies Program, cooperative agreement no. 9AA40-07920.

Fairley, H.C., Collins, B, and Draut, A., 2009, FY07-FY11 Archaeological Site Monitoring 

Research and Development Project. NPS Research and Collecting Permit Proposal. 99pp.

Fairley, H.C., and Sondossi, H., 2010, Applying an ecosystem framework to evaluate 

archaeological site condition along the Colorado River in Grand Canyon National Park, 

Arizona, in Melis, T.S., Hamill, J.F., Bennett, G.E., Coggins, L.G., Jr., Grams, P.E., 

Kennedy, T.A., Kubly, D.M., and Ralston, B.E., eds., Proceedings of the Colorado River 

Basin Science and Resource Management Symposium, November 18-20, 2008, Scottsdale, 

Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5135, 333-341 p., 

accessed on July 15, 2010, at http://pubs.usgs.gov/sir/2010/5135/. 

Hereford, R., Burke, K.J., and Thompson, K.S. 1998. Quaternary Geology and Geomorphology 

of the Nankoweap Rapids Area, Marble Canyon, Arizona. U. S. Gological Survey Geological 

Investigations Series Map I-2608. 

Hereford, R., Burke, K.J., and Thompson, K.S. 2000a, Map Showing Quaternary Geology and 

Geomorphology of the Lees Ferry Area, Marble Canyon, Arizona. U. S. Gological Survey 

Miscellaneous Investigations Series Map I-2663, scale 1:2000, with discussion. 

Hereford, R., Burke, K.J., and Thompson, K.S. 2000b, Map Showing Quaternary Geology and 

Geomorphology of the Granite Park Area, Grand Canyon, Arizona. U. S. Gological Survey 

Miscellaneous Investigations Series Map I-2662, scale 1:2000. 

166
Hereford, R., Fairley, H.C., Thompson, K.S., and Balsom, J.R., 1993, Surficial geology, 

geomorphology and erosion of archeologic sites along the Colorado River, eastern Grand 

Canyon, Grand Canyon National Park, Arizona. Grand Canyon National Park in cooperation 

with the Bureau of Reclamation, Glen Canyon Environmental Studies, Flagstaff, Ariz.: U.S. 

Geological Survey Open-File Report 93-517.

Hereford, R., Thompson, K.S., Burke, K.J., and Fairley, H.C., 1996, Tributary debris fans and 

Late Holocene alluvial chronology of the Colorado River, eastern Grand Canyon, AZ: GSA 

Bulletin, v. 108, no. 1, p. 3–19.

Jones, K., 2007, Caring for archaeological sites: practical guidelines for protecting and managing 

archaeological sites in New Zealand. Department of Conversation, Wellington, New Zealand.

Kintigh, K., lipe, W., Altschul, J., and Urquhart, N.S., 2007, Legacy monitoring data review 

panel report to the grand canyon monitoring and research center. Unpublished report 

prepared for the Grand Canyon Monitoring and Research Center, November 29, 2007.

http://www.usbr.gov/uc/rm/amp/twg/mtgs/07dec04/Attach_10.pdf

Lancaster, N., 1994. Controls on aeolian activity: some new perspectives from the Kelso Dunes, Mojave 

Desert, California. Journal of Arid Environments, v. 27(2), p. 113–125.

Leap. L.M., Kunde, J.L., Hubbard, D.C., Andrews, N., Downum, C.E., Miler, A., and Balsom, 

J.R., 2000, Grand Canyon Monitoring Project 1992-1999: Synthesis and Annual Monitoring 

Report FY99. Grand Canyon National Park River Corridor Monitoring Project Report No. 

66, submitted to Bureau of Reclamation, Upper Colorado River Region Office, Salt Lake 

City, UT. 

Li, J., G. S. Okin, J. E. Herrick, J. Belnap, M. E. Miller, K. Vest, and A. E. Draut (2013), 

Evaluation of a new model of aeolian transport in the presence of vegetation, J. Geophys. 

Res., 118, doi:10.1002/jgrf.20040.

Lucchitta, I., 1991, Quaternary geology, geomorphology, and erosional processes, eastern Grand 

Canyon, Arizona. U.S. Geological Survey administrative report: Submitted to Bureau of 

Reclamation, Upper Colorado Region, Salt Lake City, Utah.

Merriam, G. 1984. Connectivity: A fundamental ecological characteristic of landscape pattern. -

In: Brandt, J. and Agger, P. (eds), Proceedings First international seminar on methodology in 

landscape ecological research and planning. Theme I. International Association for 

Landscape Ecology. Roskilde Univ., Roskilde, pp. 5-15.

Noon, B. R., 2003, Conceptual Issues in Monitoring Ecological Resources. Chapter 2 in Busch,

D.E. and Trexler, J.C., editors, Monitoring Ecosystems: Interdisciplinary Approaches for 

Evaluating Ecoregional Initiatives: Washington, D.C., Island Press, p. 27-71.

O’Brien, G. and Pederson, J., 2009a, Geomorphic Attributes of 232 Cultural Sites Along The 

Colorado River In Grand Canyon National Park, Arizona. Final report dated July 20, 2009. 

Submitted by Department of Geology, Utah State University, Logan, to U.S. Geological 

Survey, Grand Canyon Monitoring and Research Center, Flagstaff. 

O’Brien, G. and Pederson, J., 2009b, Gully Erosion Processes and Parameters at Six Cultural 

Sites Along the Colorado River in Grand Canyon National Park, Arizona. Final draft report 

dated July 20, 2009, submitted by Department of Geology, Utah State University, Logan, to 

U.S. Geological Survey, Grand Canyon Monitoring and Research Center, Flagstaff.

Okin, G. S., 2008. A new model of wind erosion in the presence of vegetation. J. Geophys. Res. 

113, F02S10.

Okin, G. S., Parsons, A. J., Wainwright, J., Herrick, J. E., Bestelmeyer, B. T., Peters, D. C., and 

Fredrickson, E. L., 2009. Do changes in connectivity explain desertification?. BioScience, 

59(3), 237-244.

167
Pederson, J.L., Petersen, P.A., MacFarlane, W.W., Gonzales, M.F., and Kohl, K., 2003, 

Mitigation, monitoring, and geomorphology related to gully erosion of cultural sites in Grand 

Canyon. Final report in fulfillment of CA-01-WRAG-0074: On file, Grand Canyon 

Monitoring and Research Center, Flagstaff, Ariz.

Pederson, J.L., Petersen, P. A., and Dierker, J.L., 2006, Gullying and erosion control at 

archaeological sites in Grand Canyon, Arizona: Earth Surface Processes and Landforms, v. 

31, p. 507-525, doi: 10.1002/esp.1286

Sankey, JB, Law, D, Breshears, DD, Munson, SM, Webb, RH, 2013. Employing LiDAR to 

detail vegetation canopy architecture for prediction of aeolian transport. Geophysical 

Research Letters 40, 1-5, doi: 10.1002/grl.50356

Sankey, JB, Draut, AE, in press. Gully annealing by aeolian sediment: Field and remote-sensing 

investigation of aeolian-hillslope-fluvial interactions, Colorado River corridor, Arizona, 

USA. Geomorphology

Sankey, JB, Ralston, BE, Grams, PE, Schmidt, JC, Cagney, LE, in preparation. Colorado River, 

vegetation, and climate: five decades of spatio-temporal dynamics in the Grand Canyon with 

river regulation

Sondossi, H.A. and Fairley, H.C., in revision, An Analysis of Potential for Glen Canyon Dam 

Releases to Inundate 242 Cultural Sites in Grand Canyon National Park, Arizona: U.S. 

Geological Survey Open-File Report 2012-XXXX 

Taylor, P. D., Fahrig, L., Henein, K., and Merriam, G., 1993. Connectivity is a vital element of 

landscape structure. Oikos, 571-573. 

Thompson, K.S., Potochnik, A.R., Ryel, R., O’Brien, G., Neal, L.A., 2000, Development of a 

geomorphic model to predict erosion of pre-dam Colorado River terraces containing 

archaeological resources: SWCA, Environmental Consultants, Inc., submitted to Grand 

Canyon Monitoring and Research Center, Flagstaff, Ariz.Wildesen, L.E., 1982, The study of 

impacts on archaeological sites. In Schiffer, M.E., editor, Advances in Archaeological 

Method and Theory 5. New York: Academic Press, 51-59 p.

Topping, D.J., J.C. Schmidt, and L.E. Vierra, Jr., 2003, Computation and Analysis of the 

Instantaneous-Discharge Record for the Colorado River at Lees Ferry, Arizona—May 8, 

1921, through September 30, 2000: U.S. Geological Survey Professional Paper 1677, 118 p.

Vance, M.M., and Smiley, F.E., 2011. Landforms, Inundation and Archaeological Sites: Data 

Exploration and Sample Selection for a Grand Canyon Monitoring and Research Center Pilot 

Monitoring Project in the Colorado River Corridor. Northern Arizona University 

Archaeological Report No. 1337, Flagstaff, Ariz. 26 p., with database.

Webb, R.H., Belnap, J., Scott, M.L., Esque, T.C., 2011. Long-term change in perennial 

vegetation along the Colorado River in Grand Canyon National Park (1889-2010). Park 

Science 28, 73-77.

Wildesen, L.E., 1982, The study of impacts on archaeological sites. in Schiffer, M.E., editor, 

Advances in Archaeological Method and Theory 5. New York: Academic Press, 51-59 p.

Wood, W.R. and Johnson, D.L., 1978. A survey of disturbance processes in archaeological site 

formation. In Schiffer, M.E., editor, Advances in Archaeological Method and Theory 1. New 

York: Academic Press, 315-381 p.

U.S. Department of the Interior, 1995, Operation of Glen Canyon Dam Final Environmental 

Impact Statement, Bureau of Reclamation, Upper Colorado Region, Salt Lake City, 337 p. 

plus appendices. 

 

168
G. Budget 

Project Element 4.1. 

Quantifying connectivity 

along the fluvial-aeolianhillslope continuum at 

landscape scales 

Project Element 4.2. 

Monitoring of cultural sites in 

Grand and Glen Canyons

Salaries $ 107,198.00 Salaries $ 90,578.00

Traveling and Training $ 9,000.00 Traveling and Training $ -

Operating Expenses $ 2,500.00 Operating Expenses $ 157,500.00

Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators $ 75,035.00 USGS Cooperators $ 9,854.00

USGS Burden $ 18,992.00 USGS Burden $ 39,692.00

Total $ 212,725.00 Total $ 297,624.00

Project Element 4.1. 

Quantifying connectivity 

along the fluvial-aeolianhillslope continuum at 

landscape scales 

Project Element 4.2. 

Monitoring of cultural sites in 

Grand and Glen Canyons

Salaries $ 99,224.00 Salaries $ 185,834.00

Traveling and Training $ 10,000.00 Traveling and Training $ 4,000.00

Operating Expenses $ 5,000.00 Operating Expenses $ 58,000.00

Logistics Logistics $ 30,000.00

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators $ 77,124.00 USGS Cooperators $ 10,152.00

USGS Burden $ 25,129.00 USGS Burden $ 61,123.00

Total $ 216,477.00 Total $ 349,109.00

FY 2015

FY 2015 Project 4 Gross Totals: $510,349.00

FY 2016

FY 2016 Project 4 Gross Totals: $565,586.00

169
Project Element 4.1. 

Quantifying connectivity 

along the fluvial-aeolianhillslope continuum at 

landscape scales 

Project Element 4.2. 

Monitoring of cultural sites in 

Grand and Glen Canyons

Salaries $ 119,826.00 Salaries $ 197,358.00

Traveling and Training $ 10,000.00 Traveling and Training $ 4,000.00

Operating Expenses $ 8,000.00 Operating Expenses $ 26,000.00

Logistics Logistics $ 30,000.00

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators $ 77,124.00 USGS Cooperators $ 10,152.00

USGS Burden $ 38,591.00 USGS Burden $ 72,060.00

Total $ 253,541.00 Total $ 339,570.00 

FY 2017 Project 4 Gross Totals: $593,111.00

FY 2017 

170
Project 5. Foodbase Monitoring and Research 

A. Investigators 

Theodore Kennedy, Research Aquatic Ecologist, U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center

Jeffrey Muehlbauer, Research Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Charles Yackulic, Research Statistician, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Scott Miller, Director, BLM/Utah State University National Aquatic Monitoring Center

David Lytle, Associate Professor, Oregon State University

Scott Wright, Research Hydrologist, U.S. Geological Survey, California Water Science Center

Michael Yard, Fisheries Biologist, U.S. Geological Survey, GCMRC

B. Project Summary 

The productivity of the aquatic foodbase, particularly invertebrates, fuels production and 

growth of fishes in the Colorado River. However, recent studies by Kennedy and collaborators 

have shown that the productivity of this foodbase is low. Further, the foodbase in Grand Canyon 

is dominated by only two groups of invertebrates: midges and blackflies, both of which are 

small-bodied, relatively low-quality prey. Larger, more nutritious aquatic insects such as 

mayflies, stoneflies, and caddisflies (hereafter, EPT), are virtually absent throughout Glen, 

Marble, and Grand Canyons. These conditions of low invertebrate productivity and the absence 

of high quality invertebrate prey have resulted in a fishery throughout Glen, Marble, and Grand 

Canyons that is food-limited, negatively affecting the abundance of native fishes such as 

humpback chub (Gila cypha), as well as the growth of recreationally-important non-native 

rainbow trout (Oncorhynchus mykiss). If the factors and stressors affecting this low foodbase 

productivity and diversity can be isolated, adaptive management experimentation intended to 

ameliorate these stressors, and benefit the productivity and diversity of the aquatic foodbase, 

could be considered.

In this proposal, we describe a multi-faceted approach to better understanding the conditions 

effecting the low productivity and diversity of the foodbase in the Colorado River, as well as an 

experiment to potentially improve these conditions. We focus principally on two methods: 

sampling emergent aquatic insect adults on land, and sampling aquatic invertebrate larvae in the 

drift. Sampling emergent insects allows for the observation of large-scale patterns in insect 

dynamics through time and over large spatial scales, such as throughout the entire Colorado 

River in Grand Canyon. In contrast, sampling invertebrate drift allows us to understand the finescale factors affecting invertebrate populations, particularly during a phase (drifting in the water 

column) in which these invertebrates are most available to fish. To a lesser extent, we also 

describe the continuation of a monitoring effort to estimate algae production in the Colorado 

River, which represents the base of the entire aquatic food web and the food resources available 

to these invertebrate populations.

Many of the studies we propose here are logical continuations of projects initiated in FY 13–

14, such as an expansion of the citizen science monitoring of emergent insects and the 

development of a more mechanistic understanding of the factors controlling invertebrate drift. In 

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addition, we intend to synthesize published datasets to explore the factors affecting invertebrate 

productivity, diversity, and EPT abundance throughout tailwaters in the Intermountain West. We 

will couple this synthesis with natural history observations and lab studies of invertebrates in the 

Colorado River and adjacent ecosystems. The goal of those studies is to better understand how 

the specific insects present in the Colorado River and its tributaries in Glen, Marble, and Grand 

Canyons respond to environmental conditions such as altered temperature regimes and daily 

hydropeaking. We also propose to carry out insect emergence and drift studies in other Colorado 

River Basin tailwaters and in Cataract Canyon to better characterize aquatic foodbase conditions 

in reference ecosystems, and to determine whether the foodbase downstream of Glen Canyon is 

unique, or broadly similar to other river segments in the region. Finally, based on logic described 

below, we identify recruitment limitation of insects as a primary stressor limiting both 

invertebrate production and the colonization of EPT in the Colorado River in Glen, Marble, and 

Grand Canyons. Accordingly, we outline a flow experiment to be carried out during FY15–17 

involving weekend summer steady flows that may mitigate this recruitment limitation. If 

successful, this experiment would improve the short- and long-term productivity and diversity of 

the aquatic foodbase and, ultimately, the condition of fish populations and the stability of food 

webs in the Colorado River.

C. Background 

C.1. Scientific Background 

Productivity and Diversity of the Aquatic Foodbase

The primary focus of foodbase research at GCMRC over the past two decades has been on 

the broad-scale characterization of the aquatic foodbase in Glen, Marble, and Grand Canyons. 

The recent culmination of this research has been illuminating, particularly because of the strong 

links that were identified between flow management, the invertebrate prey base, and fish 

populations. Specifically, food web architecture and energy flow were quantified and it was 

shown that the growth and abundance of rainbow trout in Glen Canyon and native fishes in 

Grand Canyon are limited by the absence/scarcity of high quality invertebrate prey (Cross and 

others, 2013; Kennedy and others, 2013b). The foodbase is dominated by two aquatic insect taxa, 

midges and blackflies, and production of these taxa is low (Cross and others, 2013; Kennedy and 

others, 2013b). In fact, annual invertebrate production across four reaches of the Colorado River 

in Grand Canyon falls in the bottom 10th percentile of invertebrate production values for streams 

and rivers worldwide (Huryn and Wallace, 2000). This result is surprising because midges and 

blackflies can be among the most productive invertebrate taxa in streams and rivers. For 

example, four of the eight highest invertebrate production values ever measured for streams and 

rivers (production levels 100-1000 times higher than in Grand Canyon) were in streams where 

midges and blackflies were the dominant taxa in the assemblage (Huryn and Wallace, 2000).

Further, the tailwater synthesis GCMRC initiated in FY2013 revealed that it is actually a 

unique condition for a tailwater to support only two insect taxa; the invertebrate assemblage in 

the Glen Canyon tailwater supports fewer aquatic insects than any of the 58 other tailwaters in 

Dibble’s tailwater synthesis database (Kennedy and others, 2014a; Dibble, USGS, unpublished 

data). This is significant, because low insect diversity likely contributes to food limitation of 

fishes in the River, as larger-bodied, higher-quality invertebrates in the mayfly, stonefly, and 

caddisfly groups (“EPT,” from their collective Order names: Ephemeroptera, Plecoptera, and 

Trichoptera, respectively) are conspicuously absent (Cross and others, 2013; Kennedy and 

others, 2013b). Whereas midges and blackflies are known to be some of the most stress-tolerant 

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groups of aquatic invertebrates, EPT taxa are actually used as bio-indicators of stream quality 

nationwide and internationally (Lenat, 1993). EPT taxa are useful bio-indicators on a global 

scale because: 1) EPT are universally present in streams and rivers, but they are sensitive to 

human perturbation and 2) they are universally important to fish populations. An important 

benefit of the EPT metric is that simply measuring EPT abundance or richness, and then relating 

it to other streams/rivers in the region, provides an integrated measure of food web structure and 

stream health (Lenat and Penrose, 1996; Barbour and others, 1999). The condition of zero EPT 

taxa in Glen Canyon, and only one EPT taxon (the micro-caddisfly, Hydroptilidae) at very low 

densities in Marble and Grand Canyons, would result in the Colorado River ecosystem being 

classified as “unhealthy,” regardless of the specific reference condition used for comparison 

(Carlisle and others, 2013). Although some may argue whether invertebrates have value or 

importance in their own right, in practical terms, low aquatic insect diversity and simple food 

web architecture result in fish populations and food webs that are inherently unstable (Cross and 

others, 2013).

It is commonly accepted in aquatic ecology that flow and temperature alterations associated 

with river regulation can lead to invertebrate assemblages that are “unhealthy” (Bunn and 

Arthington, 2002). Specifically, regulation often leads to invertebrate assemblages that are 

dominated by non-insects such as worms, snails, and amphipod crustaceans like Gammarus spp., 

while insect groups such as EPT taxa tend to decline in abundance (Vinson, 2001; Robinson, 

2012). However, the extremely low EPT condition found in the Colorado River downstream of 

Glen Canyon Dam is unusual even relative to other regulated rivers in the region (Fig. 1). In 

contrast to the Glen Canyon Dam tailwater where no EPT are found, EPT taxa represent 24–35% 

of the invertebrate assemblage in five other large tailwaters in the Colorado River Basin.

One possible explanation for the low diversity of the aquatic foodbase in Glen, Marble, and 

Grand Canyons may be that the invertebrate assemblage has never been diverse, even before 

construction of Glen Canyon Dam. The physical template of the pre-dam Colorado River did 

have a dramatic disturbance regime with many distinctive characteristics that may have made life 

in the River difficult for aquatic invertebrates (Resh and others, 1988), including large snowmelt 

floods, extremely high suspended sediment concentrations, and low water clarity. However, the 

Green and Colorado Rivers located near or within Cataract Canyon, approximately 100 river 

miles upstream of Glen Canyon Dam, maintain similar characteristics to the pre-dam river, and 

the invertebrate assemblage of these reaches includes 16 genera of mayflies (Order 

Ephemeroptera), 7 genera of stoneflies (Order Plecoptera), and 7 genera of caddisflies (Order 

Trichoptera; Haden and others, 2003; Fig. 1). Tributaries in Grand Canyon also support a diverse 

invertebrate assemblage that includes many species of EPT (Oberlin and others, 1999; Whiting 

and others, 2014). It thus seems probable that EPT were extirpated from the mainstem Colorado 

River at some point in the past half century, and that some stressors exist that prevent these 

groups from recolonizing the river.

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Using midges and blackflies as surrogates for all aquatic insects, including EPT, it may be 

possible to identify specific, principal stressors affecting the aquatic foodbase in Glen, Marble, 

and Grand Canyons. For example, over the past two years river guides working in Marble and 

Grand Canyons have been serving as “citizen scientists” by setting out light traps at night and 

collecting the winged, terrestrial adult forms of aquatic insect larvae. These data show striking 

spatial and temporal patterns in midge and blackfly emergence that likely reflect similar 

variation in larval aquatic invertebrate densities within the River (Statzner and Resh, 1993). They 

can also be used as indicators of environmental stress, as the timing of emergence can be 

affected by environmental cues (Lytle, 2002). Analysis of the citizen science data in Grand 

Canyon is ongoing; however, preliminary data suggest that emergent insect dynamics may be 

affected by changes in the hydropeaking regime, the daily timing of high water at a given 

location, and monthly step changes in flow (Fig. 2). 

Figure 1. EPT% richness for six regulated rivers, including the Glen Canyon Dam tailwater (1–6), three Grand 

Canyon tributaries (7–9), and the Colorado River in Cataract Canyon. EPT% richness is the number of genera 

of Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies) relative to the total 

number of invertebrate genera in the assemblage. EPT values for regulated rivers (1–6) are derived from 

benthic invertebrate samples collected within 25 km downstream of their respective dam. Regulated rivers 

data are courtesy of Kim Dibble, USGS, and Grand Canyon tributary data are courtesy of Brian Healy, NPS. 

Cataract Canyon data are from Haden and others (2003). 

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If the specific stressors that prevent EPT from becoming re-established can be better 

identified, then the Glen Canyon Dam Adaptive Management Program could consider evaluating 

alternative policies that mitigate these stressors (see section C.4, below, for a proposed flow 

experiment). Re-establishment of EPT will improve the overall health of the River, and it will 

likely also increase the overall productivity of the foodbase. This is because, as bio-indicators, 

EPT are sentinels of environmental perturbation, meaning a decrease in the abundance, density, 

or richness of these taxa is generally mirrored by declines in other aquatic invertebrate groups. 

Midges and blackflies, as insects, have similar life histories to EPT taxa, but are less sensitive to 

environmental perturbation. The same stressors that are sufficient to prevent mayflies, stoneflies, 

and caddisflies from recolonizing the Colorado River may also be negatively affecting midge 

and blackfly populations, albeit to a lesser extent, thereby directly causing their low overall 

production. Therefore, even in the absence of successful re-colonization by EPT taxa, mitigation 

of the stressors that might be limiting aquatic insects in general could still have the beneficial 

effect of increasing the production of midges and blackflies present in the aquatic foodbase. 

Thus, adaptive management experimentation intended to improve the aquatic foodbase in Glen, 

Marble, and Grand Canyons should consider not only on ways to improve the productivity of 

existing groups, but also to improve the overall invertebrate diversity of the invertebrate 

assemblage as a whole.

Invertebrate Drift in Tailwaters

Over the past several years, GCMRC foodbase research has also been focused on measuring 

invertebrate drift, particularly in Glen Canyon. Invertebrate drift is a ubiquitous phenomenon in 

freshwaters, in which aquatic insects and other macroinvertebrates leave the channel bed and 

become entrained or caught in the water column. Unlike the broad-scale, system-wide patterns in 

the foodbase described above, measurement of invertebrate drift can allow the study of 

Figure 2. Midge catch rates and Colorado River discharge in summer 2013. Note midge emergence peaks at 

the end of the month, followed by steep declines coincident with stepped changes in flow.

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invertebrate population dynamics at spatial scales that are directly relevant to fish populations. 

Quantifying invertebrate drift concentrations (#∙m-3), and the spatial and temporal variation in 

drift at this level of resolution is critical from a fisheries perspective, because these drifting 

invertebrates represent a key food resource for many fish species. Relevant to the Colorado 

River, the endangered humpback chub (Gila cypha) and recreationally-important non-native 

rainbow trout (Oncorhynchus mykiss) are both classified as “drift-feeding fishes,” meaning that 

they rely on invertebrate drift as the key component of their foodbase. 

In addition, drifting represents a key life stage for many aquatic invertebrates. Drift can be a 

behavioral response to avoid predation or to move away from unfavorable habitat. It can also be 

unintentional or “catastrophic” in nature, such as during floods when high water velocities shear 

invertebrates off the channel bed. Finally, for aquatic insects specifically, drift necessarily occurs 

during the transitional time between when insect larvae leave the channel bed and when they 

emerge out of the water as winged adults. Thus, measuring invertebrate drift concentrations 

provides data about the stability of aquatic invertebrate populations and the conditions 

underlying the entire aquatic food web.

Foodbase research has documented that aquatic invertebrate drift in Glen Canyon is 

controlled by a suite of factors, including benthic invertebrate density (Kennedy and others, 

2014b) and physical variables such as discharge (Kennedy and others, 2014b), bed shear stress 

(the force of the water acting on bed sediment and biota), and distance from the dam 

(Muehlbauer and others, 2013; Fig. 3). These results have improved our general understanding of 

the conditions under which drift occurs; however, the specific mechanisms by which many of 

these variables actually affect invertebrate drift remain unclear. For instance, “catastrophic” drift 

(Anderson and Lehmkuhl, 1968) occurs when invertebrates are physically removed from the 

channel bed and a high proportion of the available invertebrates become entrained in the drift. If 

the conditions for initiating catastrophic drift persist for prolonged periods of time, benthic 

populations can be depleted, reducing the food base available to support fish over long time 

scales (i.e., months to years). Logically, such catastrophic drift may be initiated when one of 

three conditions is met (Gibbins and others, 2007a; b):

1. Shear stress is sufficient to entrain sand and “sand blast” invertebrates off the bed.

2. Shear stress is sufficient to physically remove invertebrates off the bed.

3. Very high shear stress mobilizes the cobble substrates on which invertebrates live.

Some data are available for small streams (<10 ft3

/s) in linking the initiation of catastrophic 

drift to specific shear stress and sediment grain size conditions (e.g., Gibbins and others, 2007a; 

b). However, the applicability of drift studies on small streams to larger systems such as the 

Colorado River (>10,000ft3/s) is tenuous, and few large river drift data are available (Kennedy 

and others, 2014b). Bed sediment conditions also vary substantially throughout the Colorado 

River (gravels in Glen Canyon, sand deposits in Marble Canyon, etc.). Thus, the frequency with 

which one or more of these three catastrophic drift conditions occurs likely varies widely 

throughout Glen, Marble, and Grand Canyons. In order to quantify and predict the response of 

invertebrate drift to flow conditions within specific habitats throughout the Colorado River, 

studies that couple high resolution measurements of shear stress, sediment grain size, and 

invertebrate drift are needed.

These results will provide important information for characterizing the spatial and temporal 

dynamics of the aquatic invertebrate community in the Colorado River and, by extension, the 

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food base available to drift-feeding rainbow trout and humpback chub populations. For example, 

research conducted in Glen Canyon demonstrates that Glen Canyon Dam acts as a 

“discontinuity” (Ward and Stanford, 1983; Stanford and Ward, 2001). Essentially, the dam 

creates conditions akin to a headwater stream, in that there is no upstream source of 

macroinvertebrate colonists. This is in contrast to most large river reaches, including the 

Colorado River in Marble and Grand Canyons, where invertebrate drift from upstream provides a 

principal source of colonists. Populations in the Glen Canyon tailwater are therefore maintained 

entirely by individuals flying, crawling, or swimming against the current from downstream 

(Müller, 1982). As a result, species accumulation in Glen Canyon increases with distance 

downstream of the dam, as more invertebrates are able to colonize and maintain persistent 

populations. This affects invertebrate drift concentrations, benthic populations, and the food base 

available to fish, such that the number of invertebrates entering the drift varies as a function of 

distance from the dam, and very low drift concentrations are found in the first ~ 4 miles of the 

tailwater (Muehlbauer and others, 2013; Fig. 3).

The low diversity of the invertebrate foodbase in Glen Canyon may also have tangible effects 

on drift characteristics in this tailwater. For instance, tailwaters with high diversity may 

experience less pronounced seasonal and spatial variation in drift availability, as a more diverse 

invertebrate assemblage will contain species that drift and emerge at different times of year, and 

from a greater diversity of habitats. This may benefit fish populations by providing a more 

Figure 3. Colorado River bed shear stress at 8000 ft3/s discharge in May 2013, relative to midge and blackfly 

drift concentrations at 26 drift sampling sites between Glen Canyon Dam and Lees Ferry. Invertebrate drift is 

highly variable in space and is directly related to shear stress conditions. Drift also increases exponentially 

with increased distance downstream of Glen Canyon Dam.

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consistently-available food base (McKinney and Speas, 2001). Thus, better characterizing 

invertebrate drift not only in Glen Canyon, but also in tailwaters throughout the Intermountain 

West, will better inform how fish in Glen, Marble, and Grand Canyons may be affected by the 

low diversity and productivity of the aquatic foodbase present in the Colorado River.

Monitoring algae production in Glen, Marble, and Grand Canyon

Algae represent the base of the food web in Glen, Marble, and Grand Canyons, feeding the 

invertebrates that, in turn, become food for fish (Cross and others, 2011; Donner, 2011; Cross 

and others, 2013; Wellard Kelly and others, 2013; Seegert and others, in press). In cooperation 

with University of Wyoming and Montana State University, GCMRC has developed an approach 

for continuously measuring rates of algal production in the River at reach-scales using detailed 

dissolved oxygen budgeting (Hall and others, 2010; Hall and others, 2012; Hall and others, In 

review). In collaboration with GCMRC’s water quality monitoring program (Project 2), we have 

been continuously measuring dissolved oxygen concentrations at six sites (RM 0, 30, 61, 87, 

166, and 225) since 2008–2010 (Fig. 4). Continued monitoring of algae production at these sites 

in FY15–17 will identify the effects that ongoing adaptive experimentation have on a key 

resource that is at the base of Colorado River food webs. Further, continuous estimates of algae 

production from Glen, Marble, and Grand Canyons will help inform insect emergence and 

invertebrate drift data that is also described in this Project. 

C.2. Management Background 

An important part of maintaining native and desired non-native fish populations is ensuring 

there is an adequate food supply to support them. This need has been translated into policy as 

part of the strategic plan of the Glen Canyon Dam Adaptive Management Program:

Goal 1: Protect or improve the aquatic foodbase so that it will support viable populations of 

desired species at high trophic levels. 

The research and monitoring described in this Project is motivated by Goal 1, and informed 

by Protocol Evaluation Panels (PEP) conducted in 2001 and 2012. The PEP conducted in 2001 

Figure 4. A nearly continuous record of algae production for the Glen Canyon tailwater, from 15 March 2008 

to 10 August 2011. Although dissolved oxygen monitoring commenced after the March 2008 HFE, these data 

still provide insight into the effect of that HFE on algae production in the reach. For example, 2008 is the only 

year in the record that lacks a strong spring peak in algae production, likely because the HFE scoured 

benthic substrates and reduced the biomass of algal primary producers. Breaks in the record are due to 

equipment failure. Rob Payn, Montana State University, unpublished data.

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recommended that:

“The food base program needs to be critically reviewed because the current level of 

understanding about the linkages between lower trophic levels and food availability 

of native fishes is not adequate to interpret food base data in relation to [Goal 1].” 

(Anders and others, 2001).

In other words, the 2001 PEP recommended that GCMRC ‘unpack’ the GCDAMP’s Goal 1 

for foodbase by first demonstrating whether populations of desired species at higher trophic 

levels would even benefit from protection or improvement of the aquatic foodbase. Although it 

might seem like a purely academic exercise to demonstrate that animals populations are limited 

by their food, in fact, factors other than food can often limit animal populations. For example, 

because cold water temperatures during spring and summer prevent native fishes from spawning 

in the River, the supply of recruits to adult mainstem populations is limited by the capacity of 

tributaries to produce young fish. Thus, one might expect the food requirements of native fish 

populations in Grand Canyon to be far lower than the foodbase is capable of supporting, because 

native fish populations might be limited by the availability of suitable spawning and rearing 

habitat. In fact, the food web studies that were motivated by the recommendations of the 2001 

PEP demonstrated that fish populations throughout Glen, Marble, and Grand Canyons were 

consuming virtually all of the available midge and blackfly biomass produced annually (Cross

and others, 2013; Kennedy and others, 2013b). Simply put, these recent food web studies 

demonstrated that fish populations in the River were limited by the foodbase. Further, the simple 

architecture of the Glen Canyon tailwater food web makes it inherently unstable and susceptible 

to large changes following disturbances, including High Flow Experiments (HFE) (Cross and 

others, 2013). Thus, food web studies described in Cross and others (2013) demonstrated that 

fish populations will likely benefit from improvement of the aquatic food base. 

Project 5.1 seeks to identify the specific stressors that are limiting the diversity and 

productivity of the foodbase so that managers will have a scientific basis for considering how 

they might go about improving the foodbase. Additionally, Project 5.1 describes a flow 

experiment that might actually improve the foodbase, and could be considered for 

implementation in FY15–17. 

The scope of the research described in Project 5 is also informed by the recommendations of 

the 2012 PEP. Specifically, that panel recommended that GCMRC:

“Expand monitoring and research beyond the Colorado River mainstem within Glen and 

Grand Canyons; information from key tributaries and mainstem locations above Lake Powell 

is critical to understanding the aquatic food webs of the Colorado River and what potential 

exists for successful alterations to the system.”(Carlisle and others, 2012).

Invertebrate drift provides a principal food source for drift-feeding fishes such as humpback 

chub and rainbow trout, so characterizing this component of the aquatic foodbase is critical to 

understanding the state of fish populations in the Colorado River in Glen, Marble, and Grand 

Canyons. The proposed monitoring and research outlined in Project 5.2 is dedicated to 

understanding the conditions, habitats, and times under which invertebrate drift occurs. As such, 

it is directly related to Goal 1. 

Finally, the data collection and methods employed by the GCMRC Foodbase Group 

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represent the state-of-the-art in terms of aquatic monitoring and research, as described in section 

E, below. This monitoring and research therefore reflects another of the 12 goals of the Adaptive 

Management Program:

Goal 12: Maintain a high quality monitoring, research, and adaptive management program.

C.3. Key Monitoring and Research Questions Addressed 

Stated simply, the overarching question we propose to answer through the work described in 

this project is “why is the diversity and productivity of the aquatic foodbase in Glen, Marble, and 

Grand Canyons so low?” Each of the questions enumerated below represents a component of this 

question. The numbers in italics at the end of each question represent the project sub-elements 

associated with answering each question.

1. Do water level stage changes due to hydropeaking lead to aquatic invertebrate recruitment 

limitation, preventing recolonization of the Colorado River by EPT? 5.1.1, 5.1.2, 5.1.5

2. Is recruitment limitation a primary cause of low midge and blackfly production in the 

Colorado River? 5.1.1, 5.1.2, 5.1.5, 5.1.6

3. What factors generally control EPT distributions in rivers, and are conditions different in the 

Colorado River in Glen, Marble, and Grand Canyons compared to other systems in the Upper 

and Lower Basin? 5.1.3, 5.1.4, 5.1.7, 5.1.8

4. Do processes and physical characteristics of drift habitat (flow dependent distributions of bed 

shear stress and distribution of substrate type) vary among reaches, and does this explain 

differences in observed concentrations of invertebrate drift? 5.2.3, 5.2.4

5. How does invertebrate drift in Glen, Marble, and Grand Canyons vary spatially and 

seasonally, and with respect to emergent insect densities, dam management, and fish 

population dynamics? 5.2.1, 5.2.2, 5.2.3

6. Is the rate at which species accumulate and drift concentrations increase with distance from 

the dam consistent across tailwaters, or is this rate unusually low downstream of Glen 

Canyon Dam? 5.2.1, 5.2.5

7. Are the spatial patterns and functional relationships between physical controls and 

invertebrate drift downstream of Glen Canyon Dam unique, or more broadly applicable to 

other tailwaters in the Colorado River Basin? 5.2.3, 5.2.4, 5.2.5

8. Does higher invertebrate diversity in a tailwater result in less variable seasonal and spatial 

patterns of drift? 5.2.1, 5.2.5

9. How does algae production vary seasonally, with HFEs and other flow changes, and 

longitudinally throughout Glen, Marble, and Grand Canyons? 5.3.1, 5.3.2, 5.3.3

C.4. Hypotheses Explaining Aquatic Invertebrate Productivity and Diversity 

We present five hypotheses that could explain why aquatic insect diversity is low 

downstream of Glen Canyon Dam. We also note whether any of these diversity hypotheses can 

also explain why production of midges and blackflies is low. Numerous other hypotheses can 

explain just the low production, but not the low diversity, of the Colorado River, such as nutrient 

dynamics, high turbidity/low algae, or armoring of the bed; however, these types of productionrelated hypotheses are not included here because they were a major focus of earlier foodbase 

research (Cross and others, 2013; Kennedy and others, 2013b). After each hypothesis is 

presented, we outline management implications if the hypothesis is true.

Hypothesis 1 (H1). Cold water temperatures of the Colorado River prevent EPT taxa from 

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completing their lifecycle.

Rationale: H1 specifically attributes the absence of EPT taxa to cold water temperatures. 

Summer water temperatures of the post-dam Colorado River are colder than the tributary streams 

in Grand Canyon that support populations of EPT taxa (Voichick and Wright, 2007). Larval 

stages of EPT taxa from tributaries may be able to survive and grow in the mainstem in spite of 

cold water temperatures, as evidenced by the persistence of EPT in the tributaries even though 

winter temperatures in these tributaries are similar to the mainstem. However, consistently cold 

temperatures throughout spring and summer may prevent EPT taxa from completing their life 

cycle in the mainstem, particularly due to the sensitivity of key life stage transitions, such as the 

transition from egg to larva, that occur at these times (Elliott, 1978). Although H1 may explain 

why EPT taxa are absent, this hypothesis cannot by itself explain why production of midges and 

blackflies is low, because many cold water streams and rivers have high invertebrate production 

(Huryn and Wallace, 2000). 

Management Implications: Under H1, installation of a selective withdrawal structure on 

Glen Canyon Dam would be required to increase river temperature and allow populations of EPT 

taxa to complete their life cycle and establish naturally recruiting populations in the Colorado 

River. Alternatively, EPT taxa may colonize the Colorado River in future years if climate change 

results in consistently lower elevations in Lake Powell and warmer releases from Glen Canyon 

Dam. Warmer water temperatures would also be expected to increase the production of midges 

and blackflies (Huryn and Wallace, 2000).

Hypothesis 2 (H2). Unnatural water temperature regimes are out of phase with the seasonal 

timing of key EPT life stage changes.

Rationale: H2 ascribes the absence of EPT taxa to the unnatural seasonal timing of 

temperature regimes rather than to cold temperatures per se (Olden and Naiman, 2010). For 

example, in the Glen Canyon tailwater, maximum water temperatures typically occur in October 

or November (http://www.gcmrc.gov/discharge_qw_sediment/station/GCDAMP/09380000), 

whereas in tributaries maximum water temperatures occur in June–July when air temperatures 

are highest (Voichick and Wright, 2007). If annual maximum temperatures or specific 

temperature thresholds (e.g., day of year when 55 °F is reached) are the primary cues that trigger 

insect emergence and other key life stage changes, then the unnatural timing of water 

temperature regimes may be causing critical delays in the life cycle of EPT taxa. For example, 

unnatural water temperature regimes might be causing EPT taxa to emerge from the Colorado 

River during winter months when air temperatures are freezing. However, H2 cannot explain 

why midge and blackfly production is low, because citizen science emergence monitoring 

indicates midge and blackfly emergence occurs throughout the spring and summer, and peaks in 

late June around the summer solstice (Kennedy and others, unpublished data). That is, midge and 

blackfly emergence appears related to day length, and the unnatural seasonal timing of Colorado 

River water temperature regimes does not appear to be causing abnormal delays in emergence of 

these insects. 

Management Implications: The management implications of H2 are similar to H1. 

However, the specifications on a selective withdrawal device, such as the number of units 

outfitted, may differ if the management objective is re-creating the pre-dam maximum and 

minimum temperatures (H1) vs. more natural seasonal timing of temperature maxima and 

minima (H2).

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Hypothesis 3 (H3). Dispersal limitation prevents EPT taxa native to the Colorado River from 

colonizing Glen, Marble, and Grand Canyons.

Rationale: H3 posits that native EPT taxa are capable of inhabiting the Colorado River in 

Glen, Marble, and Grand Canyons, but they have not re-colonized because suitable source 

populations are distant. For example, Cataract Canyon is >100 river miles from Glen Canyon and 

is separated from it by a large dam and reservoir. However, there are several assumptions 

implicit in H3. First, there is an assumption that load-following flows (i.e., unconstrained 

hydropeaking) or some other historical bottleneck extirpated EPT taxa from segments 

downstream of Glen Canyon Dam. Second, there is the assumption that this bottleneck is no 

longer present, most likely due to flow changes implemented by the 1996 Record of Decision. 

H3 also assumes that EPT species currently present in Grand Canyon tributaries differ from 

species historically present in the Colorado River mainstem. That is, H3 assumes that EPT taxa 

in tributaries are incapable of serving as source populations for mainstem re-colonization. H3 is 

the first hypothesis presented that attributes the absence of EPT to flow management, specifically 

to flow management policies that have not been in place for more than two decades. However, 

H3 cannot explain why EPT taxa present in tributaries have not colonized the mainstem river, 

especially at downstream locations where water temperature regimes are somewhat naturalized. 

Further, H3 cannot explain why production of midges and blackflies within the mainstem is low. 

Management implications: Reintroductions of invertebrates from upper basin segments and 

tailwaters is a logical next step in the adaptive management process under H3. Note that a 

similar dispersal limitation hypothesis provides the basis for ongoing humpback chub 

translocations in Grand Canyon tributaries (Holton, 2008; Spurgeon, 2012; Trammel and others, 

2012). That is, humpback chub translocations are occurring (Shinumo Creek, Havasu Creek, 

Upstream of Chute Falls in the Little Colorado River), and are planned (Bright Angel Creek), 

because it is assumed that dispersal limitation is preventing humpback chub from inhabiting 

these locations. Likewise, a dispersal limitation hypothesis motivates recent translocations of 

razorback sucker (Xyrauchen texanus) into western Grand Canyon.

Hypothesis 4 (H4). Hydropeaking causes catastrophic drift and high mortality of EPT larvae, 

thereby preventing populations from becoming established.

Rationale: Invertebrate drift is a fundamental aspect of the overall life history of aquatic 

insects because drift allows for rapid re-colonization of benthic substrates by larvae following 

egg-laying by emergent adults. Invertebrate drift is often triggered by changes in discharge, and 

the daily changes in discharge associated with hydropeaking may cause exceptionally high rates 

of drift for EPT taxa that have catastrophic consequences for their populations. H4 is informed 

by recent research in Glen Canyon that demonstrated the strong effect that hydropeaking can 

have on invertebrate drift concentrations (Kennedy and others, 2014b). Specifically, during 

summer hydropeaking, Kennedy and others (2014b) found that more than 1% of midge and 

blackfly larvae for the entire 16 mile tailwater were being exported past Lees Ferry each day. H4

posits that over invertebrate life spans (months to years), catastrophic drift (Anderson and 

Lehmkuhl, 1968) associated with hydropeaking is a critical source of mortality. Note that H4 can 

also reasonably explain why production of midges and blackflies is low, because Kennedy and 

others (2014) demonstrated high rates of drift for these taxa in Glen Canyon. However, H4

implicitly assumes that EPT taxa on whole are susceptible to catastrophic drift to a much greater 

extent than midges and blackflies, such that EPT have become extirpated but midges and 

blackflies have not. H4 is the first hypothesis presented that attributes the absence/rarity of EPT 

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to existing flow management policies. 

Management Implications: H4 suggests that a new flow action, constraining the daily range 

of hydropeaking to reduce catastrophic invertebrate drift, be considered. These constraints would 

likely need to occur for substantial portions of the year under H4, because aquatic insects are 

susceptible to catastrophic drift throughout their larval lifespan. 

Hypothesis 5 (H5). EPT taxa are recruitment limited, because hydropeaking causes high egg 

mortality.

Rationale: Hydropeaking from Glen Canyon Dam creates a large varial (intermittently 

wetted) zone along shorelines. Because the Colorado River in Glen, Marble, and Grand Canyon 

is canyon bound and the tributaries that join the river all have comparatively low discharge, the 

size of the varial zone does not appreciably decrease with distance downstream. For example, 

daily stage change during summer hydropeaking is around 2 feet at both the Lees Ferry gage and 

the Diamond Creek gage 225 miles downstream. Thus, although water temperature regimes 

become more naturalized with distance downstream, the effect that hydropeaking has on the 

stability of shoreline habitat does not attenuate with distance from the dam. 

H5 attributes the absence of EPT and the poor health of the invertebrate assemblage to the 

width of the varial zone, similar to earlier investigations (Blinn and others, 1995), but H5 goes a 

step further and focuses on the effect that unstable shorelines have on a specific life stage of 

aquatic insects—eggs. H5 implicitly assumes that egg-laying by EPT taxa occurs principally 

along shorelines, because if egg-laying by EPT taxa was occurring in the main channel then egg 

survival would be unaffected by daily changes in stage. This assumption of egg-laying along 

shorelines seems reasonable given the life history of aquatic insects, and EPT taxa in particular. 

Aquatic insects concentrate along shorelines immediately after emergence, and mating swarms 

of aquatic insects are associated with vegetation and other physical structures along shorelines 

(Gratton and Vander Zanden, 2009; Muehlbauer and others, 2014). Females likely choose to 

oviposit (lay eggs) in the first ideal habitat they encounter as they travel back to the water from 

land, so it makes intuitive sense that most egg laying would also occur in the varial zone near 

shorelines. Further, the specialized egg-laying behaviors of some EPT taxa necessitate this 

critical life history step occur along shorelines. For example, mated females of the ubiquitous 

mayfly genus Baetis land on an emergent rock in fast water, then crawl a couple of inches under 

the water’s surface and affix a cluster of eggs to the rock (Encalada and Peckarsky, 2012). In 

fact, Encalada and Peckarsky (2012) were able to double the number of Baetis larvae present in 

50 m stream reaches simply by doubling the number of rocks available for Baetis egg-laying, and 

to reduce by half the number of Baetis larvae present in stream reaches by eliminating the 

emergent rocks that adults require for egg-laying. This example highlights the critical role that 

recruitment plays in determining aquatic insect population dynamics. 

H5 posits that EPT taxa downstream of Glen Canyon Dam are recruitment limited, because 

hydropeaking negatively affects habitat quality along the shorelines where egg-laying is assumed 

to occur. Note that H5 also assumes that the eggs laid by EPT taxa in the varial zone, and which 

are subjected to daily drying, will experience high mortality prior to larval development. This 

assumption of high mortality also seems reasonable given typical summertime air temperatures 

in Grand Canyon that can exceed >110 °F, with ground temperatures >130 °F. H5 can also 

explain why midge and blackfly production is low, because these taxa will also be susceptible to 

high egg mortality and recruitment limitation if egg laying occurs principally along shorelines. 

Management implications: Both H5 and H4 posit that hydropeaking is responsible for the 

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absence/rarity of EPT taxa and the low production of midges and blackflies. However, mitigating 

the effects of hydropeaking under H5 is fundamentally different than mitigating the effects of 

hydropeaking under H4. Specifically, H5 implies that shorelines only need to be stable for 

sufficient time to overcome the negative effects that recruitment limitation is having on the 

diversity and productivity of the aquatic food base.

Support for Hypothesis 5 (H5)

As a first step toward framing the problem of low aquatic invertebrate diversity and 

productivity in the Colorado River, we have focused on the role that individual stressors may be 

playing in driving observed patterns of insect diversity and productivity. Although there are 

likely significant interactions among stressors such as temperature and flow (Olden and Naiman, 

2010), isolating the predominant, most-impactful stressor will represent a major step towards 

understanding how to go about improving the aquatic foodbase. Likely each stressor represents 

an environmental filter that limits invertebrate populations to some extent (Poff, 1997), with the 

cumulative effect of all these stressors resulting in the low diversity and productivity conditions 

in the Colorado River. Removing all these stressors is infeasible; however, identifying and 

ameliorating the stressor that has the greatest filtering effect on invertebrate populations may be 

sufficient to impart large and beneficial change to the aquatic invertebrate diversity and 

productivity of the Colorado River ecosystem.

Managers also have limited ability or willingness to actively mitigate some of the stressors 

we identified. For example, the high-cost (>$150M) and risks (invasion by warm-water 

nonnatives) associated with installation and use of a selective withdrawal structure on Glen 

Canyon Dam mean active temperature mitigation is unlikely (H1 and H2). Mitigating and testing 

the dispersal limitation hypothesis (H3) could be accomplished through translocations of insects 

from other river segments, but, in our opinion, this hypothesis requires too many unreasonable 

assumptions, none of which are actually testable, to warrant serious consideration. In contrast, 

mitigating the negative effects of hydropeaking under both H4 and H5 is logistically possible. 

However, the diversity assumption implicit in H4 is that EPT are much more susceptible to 

catastrophic drift than midges and blackflies. Project 5.2 describes research and monitoring that 

will address uncertainties relative to H4. However, while it may be a lesser filter affecting 

species distributions within small scales or certain reaches of the river (Poff, 1997), it seems 

unreasonable to expect that catastrophic drift is the predominant stressor limiting EPT 

colonization throughout Glen, Marble, and Grand Canyons.

There are two assumptions that are implicit in H5: that substantial egg-laying by adult insects 

occurs near shorelines, and that mortality of eggs subjected to drying is high. Because aquatic 

insects have a biological imperative to return to the water as quickly as possible to lay their eggs 

and are generally not well adapted to life outside of water, both of these assumptions seem 

reasonable. Further, both assumptions can be tested with field and laboratory studies. 

Given management realities as well as the assumptions embedded in many of the five 

hypotheses, we focus on testing H5 in Project 5.1 and with the flow experiment we propose, 

because emergence and egg-laying of aquatic insects are very poorly studied processes, 

particularly in the context of river regulation and hydropeaking. Most importantly, mitigating 

potentially negative effects of recruitment limitation, assuming H5 is true, has the highest 

probability of leading to a large and positive increase in insect diversity and productivity, even as 

other stressors persist.

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Proposed Flow Experiment

There are numerous flow experiments that could be developed to experimentally test the 

validity of H5. However, a central tenet of adaptive management is to focus on testing 

alternative policies, as opposed to simply testing hypotheses (Walters, 1986), and many potential 

flow experiments are impractical from a policy standpoint. For example, year-round stable flows 

would represent a definitive test of H5, but such an experiment would likely lead to a large 

cohort of juvenile rainbow trout (Korman and others, 2012), with potentially negative 

consequences for humpback chub populations. Thus, year-round stable flows do not represent a 

good test of a policy option that might eventually be considered for long-term implementation, 

because negative or undesirable effects on other resources such as rainbow trout and hydropower 

production may outweigh the benefits that year-round stable flows might have on insect diversity 

and productivity. Although stable summer flows have occurred in 2000 and 2011, foodbase 

monitoring techniques were not well developed in 2000, and only rudimentary monitoring was in

place in 2011 due to budget cuts in the foodbase program. Thus, it is not possible to draw 

inferences about H5 using invertebrate monitoring data from these years. 

Alternatively, the validity of H5 could be evaluated with a shorter duration block of steady 

flows. For example, the time of year with the highest rates of emergence and egg-laying could be 

identified (mid-June–mid-July), and then stable flows that encompass this entire emergence 

period could be implemented. However, emergence timing varies widely among EPT taxa, and a 

month-long block of stable flows might positively affect egg survival for some species, but other 

species that emerge and lay eggs during other times of year would not be affected by this 

experiment. Additionally, short-lived species such as midges and Baetis mayflies have multiple 

generations per year, so this experimental design might positively affect egg survival for one 

generation of these short-lived species, but population dynamics would likely be determined by 

the fate of other generations that are emerging at other times of year. Thus, this type of shortduration experiment does not represent a good test of a policy option that might eventually be 

considered for implementation, because it is unlikely that a month-long block of steady flows 

will significantly increase invertebrate diversity or productivity. 

We propose a novel experimental design for testing the validity of H5 that involves stable 

flows every weekend from May through August (34 days total). The discharge on weekends 

would be the minimum discharge for that month, which will ensure that the insect eggs laid 

during weekends will never be subjected to drying due to lower water levels at any point prior to 

larval development. No change in monthly volumes, ramping rates, or the daily range in 

discharge during weekdays would be required as part of this experiment. To offset the smaller 

water releases that would occur during weekends within a given month, larger releases would 

need to occur during the weekdays within a given month. Ideally, and pending environmental 

compliance discussions and approval, this flow experiment could be initiated in 2015. Results 

from 2015 would be available in early 2016 and should be sufficient to provide baseline support 

or opposition for any continuation of the flow experiment in summer 2016 and future years.

The timing of the proposed experiment is informed by citizen science light trapping results 

demonstrating that midges, and to a lesser extent blackflies and micro-caddisflies (Order 

Trichoptera, Family Hydroptilidae), are emerging from the mainstem throughout the summer 

period from May to August (Kennedy unpublished data). This experiment will provide an ideal 

egg-laying environment of stable water levels along shorelines, at regularly-timed intervals 

throughout the emergence and egg-laying season. Thus, if the mechanisms and assumptions 

underlying H5 are true, this flow experiment should elicit both short-term (month-to-month) and 

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long-term, (year-to-year) population-level responses from aquatic insects, as more eggs hatch 

into larvae, leading to more adults, which lay the eggs that set the stage for more successful 

cohorts of future generations.

D. Proposed Work 

Sixteen proposed project sub-elements are described in this proposal. For ease, these subelements are partitioned into three broader project elements: 1) tasks principally related to 

studying the factors limiting diversity and production of the invertebrate foodbase, 2) tasks 

principally related to characterizing the factors controlling invertebrate drift, and 3) tasks related 

to monitoring algae production in the Colorado River. 

Some of the project sub-elements described here involve fieldwork in the Upper and Lower 

Colorado River Basin, outside of Glen, Marble, and Grand Canyons (Project Elements 5.1.7, 

5.1.8, and 5.2.5). We recognize that these sub-elements therefore may not be eligible for funding 

by GCDAMP. Consequently, supplemental funding for these projects has been requested from 

sources external to the GCDAMP. These project sub-elements are noted by the text “Potentially 

not eligible for funding by GCDAMP, may require external funding sources.” We have chosen to 

incorporate these project sub-elements into this GCDAMP proposal because, regardless of their 

ultimate source of funding, they represent a critical component of the overall body of work we 

propose to carry out in FY15–17, and will be crucial in providing insight into the remaining 

project elements we propose for GCDAMP funding.

D.1. Project Elements 

Project Element 5.1. Is aquatic insect diversity and production recruitment limited? 

Here, we present research and monitoring focused on evaluating the validity of H5, described 

in section C.4 above. This work includes field experiments and modeling that will directly 

address the assumptions that are implicit in this hypothesis. The strength of our inferences will 

be significantly increased if these studies are accompanied by the proposed flow experiment; 

however, these studies will provide insights into the validity of H5, regardless of whether the 

flow experiment is also implemented. Because EPT taxa are virtually absent from the Colorado 

River in Glen, Marble, and Grand Canyons, we also propose field studies of insect emergence 

and egg-laying in other segments of the Colorado River that support these taxa.

Project Element 5.1.1. Insect emergence in Grand Canyon via citizen science 

(Recommended for funding FY15: $117,920)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

David Lytle, Associate Professor, Oregon State University

The citizen science sampling of insect emergence initiated by Kennedy in 2012 has yielded 

an unprecedented dataset of spatial and temporal patterns in aquatic insect emergence throughout 

225 miles of Grand Canyon. These data are also beginning to shed light on how flow 

management affects the critical adult life stage of aquatic insects. This project has also become a 

powerful outreach tool for communicating Grand Canyon science, and the important role that 

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adaptive management plays, to dozens of river guides and thousands of passengers annually. In 

many ways, this dataset has been the basis for the research and questions described in this 

proposal, and we propose to continue this citizen science monitoring in FY15–17. In addition, if 

flow management changes aimed at increasing insect productivity and diversity in the Colorado 

River are initiated, data from this monitoring program will be essential in tracking any changes 

to aquatic insect populations.

Project Element 5.1.2. Quantifying the effects of hydropeaking on oviposition and egg mortality 

(Recommended for funding FY15: $97,236)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

The main focus of this project element is addressing the two assumptions that are implicit in 

H5. Specifically, this project will quantify 1) the proportion of egg-laying by aquatic insects that 

occurs in the varial zone relative to permanently inundated habitats, and 2) rates of mortality for 

eggs that are subjected to daily drying. Observational and field studies of egg-laying will be 

conducted at sites where the varial zone is wide vs. narrow, and sites where daily flow minima 

occur during daytime hours vs. nighttime hours. Field studies on egg mortality will be 

complemented by more controlled laboratory studies on egg mortality (see Project Element 5.1. 

6).

Project Element 5.1.3. Synthesis of stressors and controls on EPT distributions 

(Recommended for funding FY15: $29,672)

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Scott Miller, Director, National Aquatic Monitoring Center, Bureau of Land Management

All the hypotheses described above are predicated on an understanding of the stressors and 

controls that affect the ability of insects to colonize, reproduce, and persist in aquatic 

ecosystems. The hypotheses we presented are based on sound science for aquatic insects in 

general; however, in moving toward potential mitigation strategies that will promote colonization 

or increased production of target species, a better understanding of species-specific traits and 

stressors will be required (Table 1).

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Table 1. Life History Information for Select Aquatic Insect Taxa. Information on midges and blackflies is specific 

to the sub-families (midges) or species (blackflies) that are present and widely distributed in the Colorado River. 

Life history information for representative genera from Ephemeroptera, Plecoptera, and Trichoptera are also 

presented, even though these taxa are not present in the Colorado River in Grand Canyon. This type of speciesspecific information will inform the development of field studies and provide insights into invertebrate population 

responses to the flow experiment we have proposed. Data from Merritt and others (2008).

Life Trait

Midges

(Chironominae,

Orthocladiinae)

Blackflies

(Simulium vittatum 

complex)

Ephemeroptera

(mayflies)

Baetis

Plecoptera

(stoneflies)

Hydroperla

Trichoptera

(caddisflies)

Hydropsyche

Feeding mode CollectorGatherer Filter feeder Collectorgatherer

Leaf shredder, 

then predator Filter feeder

Generations per year Multiple One or multiple Multiple One One

Egg-laying location Water surface Below water line 

on vegetation

Shallow riffles, 

under stones Head of riffles Submerged object

Pre-egg laying 1-2 days Variable, requires 

blood meal 1 day 2-5 days A few days

Fecundity 

(eggs per female) 1000-2000 300-600, clumps from many females ~1000 150-300 per egg mass

300-500

Egg incubation Days to weeks Days to weeks Weeks Weeksmonths Days-weeks

Notes Eggs masses 

often float

Overwinters as 

diapausing egg

Hatching period 

highly variable

Synchronous 

hatching

Project Element 5.1.4. Synthesis of the aquatic foodbase in western US tailwaters 

(Recommended for funding FY15: $29,672)

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Scott Miller, Director, National Aquatic Monitoring Center, Bureau of Land Management

This project element will follow an approach similar to the tailwater synthesis project being 

led by Kim Dibble (see Project 9). That synthesis of trout population dynamics has yielded 

important insight into how dam management affects trout populations, and has been useful in 

putting the rainbow trout fishery in Glen Canyon and the operations of the Glen Canyon Dam in 

context. We will conduct a similar synthesis of aquatic food base conditions in western 

tailwaters. Some data are already available as a result of Dibble’s work, and much of these data 

were provided by Scott Miller; however, the food base synthesis will naturally have a somewhat 

different focus from that project. Thus, successful completion of this project will require 

additional data collection from published journal articles, government reports, and databases, as 

well as further interaction and data gathering from state, federal, and academic researchers across 

these western tailwaters.

Project Element 5.1.5. Natural history of oviposition for species present in Grand Canyon 

(Recommended for funding FY15: $25,878)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Eric Kortenhoeven, Ecologist, USGS, GCMRC

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Anya Metcalfe, Ecologist, USGS, GCMRC

To understand how environmental stressors affect the populations of aquatic insects present 

in Grand Canyon, a better understanding of their life history is required. For instance, additional, 

observational information on the oviposition (egg-laying) behavior of black flies and midges in 

the Colorado River in Grand Canyon will help support or discredit the hypotheses listed above, 

and will inform the extent to which alterations to flow management may increase production of 

the aquatic food base.

Project Element 5.1.6. Laboratory studies on insect oviposition and egg mortality associated with changing 

water levels 

(Unfunded, High Priority FY15: $37,038)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Adam Copp, Ecologist, USGS, GCMRC

Many of the hypotheses listed above are based on mortality at key insect life stages, 

particularly the effect of desiccation on egg-mortality (H5). Lab or experimental mesocosm 

studies are highly amenable to isolating such effects and providing conclusive data on the impact 

of individual stressors, such as the desiccation time and temperature at which 50% (a clinical 

threshold for mortality) of midge or blackfly eggs become non-viable.

Project Element 5.1.7. Comparative emergence studies in Upper Basin using citizen science light trapping 

(Submitted for non-AMP funding FY15: $58,762)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC 

Scott Miller, Director, BLM/Utah State University National Aquatic Monitoring Center

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC 

Citizen science emergence monitoring in Grand Canyon (Project Element 5.1.1) will provide 

information on insect population response to Glen Canyon Dam operations; however, it is 

difficult to put the temporal and spatial patterns present in these data into context without 

comparable data from other regulated and unregulated rivers that have different characteristic 

flow regimes. Thus, we propose to carry out similar studies in Upper Basin tailwaters including 

Flaming Gorge Dam, Fontenelle Dam, and Navajo Dam. We will also collaborate with citizen 

scientists to quantify insect emergence in segments that are unregulated, such as the Green River 

in Desolation-Gray Canyon, the Colorado River in Westwater and Black Rocks, and Cataract 

Canyon. These data will elucidate the degree to which unique operations of Glen Canyon Dam 

affect insect behaviors and life stages, and the degree to which certain behaviors and population 

dynamics are consistent across segments of the Colorado River Basin. Note that the three years 

of citizen science emergence monitoring that we have acquired from Grand Canyon (2012–2014) 

will provide an experimental ‘control’ in the event the flow experiment we propose is 

implemented. Citizen science monitoring in the San Juan River was already initiated in April 

2014 in collaboration with Grand Canyon Youth, and will occur through FY14 and, ideally, into 

future years as well. As with the Grand Canyon citizen science monitoring, we expect this 

collaboration to also provide a large outreach benefit to the GCDAMP.

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Project Element 5.1.8. Natural history of oviposition for EPT via studies in the Upper Basin 

(Submitted for non-AMP funding FY15: $25,372)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC 

Scott Miller, Director, BLM/Utah State University National Aquatic Monitoring Center

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC 

As described in Project Element 5.1.5, understanding the life history behaviors of aquatic 

insects will provide useful information for predicting insect population responses to flow 

management. For midge and blackfly species, these studies can be done in Grand Canyon. 

However, for target EPT taxa that are not currently present in Grand Canyon, their life histories 

must be studied in river systems where they are extant. The closest segments where these species 

are present is the Upper Colorado River Basin, specifically tailwaters such as those downstream 

of Flaming Gorge, Fontenelle, and Navajo Dams, and the unregulated Cataract Canyon reach 

that serves as a proxy for conditions in the pre-dam river. Thus, we propose natural history 

studies similar to those in Project Element 5.1.5., to be carried out in these Upper Basin segments 

with a focus on EPT taxa.

Project Element 5.2. Patterns and controls of aquatic invertebrate drift in Colorado River tailwaters 

The work described here focuses on studies that predominantly use drift as a method for 

assessing the condition of the aquatic foodbase. Such measurements represent a more direct 

metric for quantifying food availability for humpback chub and rainbow trout, both of which are 

“drift-feeding fish.” The purpose of many of the tasks proposed in these sub-elements is to 

mechanistically describe the factors influencing drift, particularly on small scales that are known 

hotspots of fisheries interest such as Glen Canyon and at the confluence of the Little Colorado 

River. Measuring drift is also a well-established method in stream and river ecology, which 

allows results of these studies to be more easily compared to other river ecosystems. As with the 

studies proposed in Project Element 5.1, some of the project sub-elements proposed here will 

also take place in other tailwaters in the Upper and Lower Colorado River Basin, for the sake of 

comparing conditions in Glen Canyon to representatively similar sites in the region.

Project Element 5.2.1. Continue characterizing and monitoring drift and insect emergence in Glen Canyon 

(Recommended for funding FY15: $52,092)

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Monthly invertebrate drift measurements have been taken longitudinally at six stations 

throughout Glen Canyon (RM -11, -8, -4.9, -3.5, -2.1, 0.2) and laterally at a cross section at Lees 

Ferry (RM 0) since January 2013. Monthly monitoring of emergent insects using sticky and light 

trap sampling was also initiated throughout Glen Canyon in January 2014. This monitoring is 

carried out using published methods developed by our lab group (Kennedy and others, 2013a; 

Kennedy and others, 2014b; Smith and others, 2014). These monitoring efforts will be used to 

describe spatial and temporal patterns of drift throughout Glen Canyon and will be compared to 

similar data we will collect from other tailwaters as outlined in Project Elements 5.2.2 and 5.2.5, 

below. In addition, the emergent insect monitoring in Glen Canyon will be linked to the citizen 

science emergent insect study initiated in 2012 (Kennedy and others, 2013a) to provide an 

unprecedented longitudinal dataset of emergence, from Glen Canyon Dam at RM -16, to 

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Diamond Creek 225 miles downstream. Extending insect emergence monitoring into Glen 

Canyon will allow us to better identify the role that flow management plays in driving insect 

population dynamics, because Glen Canyon is unaffected by sediment turbidity. Emergent insect 

monitoring will also be coupled with the drift data to describe the proportional relationship 

between concentrations of drifting invertebrates (i.e., food for fishes) and emergent insects 

(Statzner and others, 1986; Statzner and Resh, 1993) in the Colorado River. Emergent insects are 

more easily sampled than drift, and better quantifying the nature of this relationship in Glen 

Canyon and at the Natal Origins sites in Marble and Grand Canyons (as outlined in Project 

Element 5.2.2, below) will allow the citizen science emergent insect database to be used as a 

proxy for drift concentrations throughout the Colorado River.

Project Element 5.2.2. Continue Natal Origins drift monitoring in Glen, Marble, and Grand Canyons 

(Recommended for funding FY15: $87,365) 

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Invertebrate drift has been monitored as part of the ongoing fish Natal Origins (NO) project 

since 2012. Drift samples are taken at all NO sites (RM -3.5, 18.9, 39.5, 60.15, 63.7) and during 

the run-out of NO trips at RM 63.7, 71.2, 88, 138.6, 166, and 225. Drift data from NO sites will 

eventually be linked to fish diet, abundance and distribution data collected concurrently with NO 

quarterly sampling (see Project 9 in work plan). NO drift data will also be used to parameterize 

rainbow trout bioenergetics models for Glen, Marble, and Grand Canyons (Project 9). High 

resolution drift monitoring will also be used to build a coarse-scale map of drift patterns 

throughout the Colorado River, as outlined in Project Elements 5.2.3 and 5.2.4, below.

In FY13–14, 20 drift samples were taken quarterly at each NO site (100 total samples per 

trip, or 500 per year). In this work plan, sampling effort per site visit will be reduced by ~50% 

(10 samples per site) to reduce laboratory sample processing burdens. Power analysis indicates 

this reduction will only marginally affect our ability to draw inferences from the data. Intensive 

diet sampling was also conducted at each NO site during FY12–14, resulting in 100 samples for 

rainbow trout gut content analysis per trip, or 400 per year. This diet analysis sampling will be 

discontinued in this work plan, because the three years of intensive diet sampling are sufficient to 

describe the relationship between drift concentrations, water clarity, and rainbow trout feeding 

habits. During the last two years of the NO project (FY15–16), we will predict rainbow trout 

feeding habits based on drift concentrations and water clarity, rather than continuing with timeintensive fish gut content analysis.

Project Element 5.2.3. Link drift at Natal Origins project transects to channel bed shear stress 

(Recommended for funding FY15: $20,619) 

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Scott Wright, Research Hydrologist, USGS, California Water Science Center

Bed shear stress conditions will be quantified at all drift sites sampled during NO trips (11 

total sites). This work can be done over the course of one NO trip using an acoustic Doppler 

current profiler (ADCP) with standardized methods developed previously in Glen Canyon 

(Muehlbauer and others, 2013). These hydrodynamic data will also be useful in fish 

bioenergetics modeling at the NO sites, and in understanding spatial variability in habitat 

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conditions affecting both invertebrate and fish distributions. Further, these data will be used to 

characterize the functional relationship between physical environmental controls and invertebrate 

drift at a coarse scale throughout Glen, Marble, and Grand Canyons, as outlined in Project 

Element 5.2.5, below.

Project Element 5.2.4. Link invertebrate drift patterns to substrate conditions in Glen, Marble, and Grand 

Canyons 

(Recommended for funding FY15: $20,735) 

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Scott Wright, Research Hydrologist, USGS, California Water Science Center

This task will integrate spatially and temporally-extensive data on aquatic macroinvertebrate 

drift, bed shear stress, and sediment grain size distributions. Much of the data collection required 

has already been completed or is ongoing. The critical work remaining for this task is to 

systematically link available point data on drift and bed shear stress to channel bed grain size 

estimates at these same locations. Such data can be used to predict the shear stress conditions 

under which incipient motion of bed sediment will occur for a given substrate habitat patch 

(Shields, 1936; Parker and Klingeman, 1982; Wilcock, 1996). By comparing variation in 

macroinvertebrate drift concentrations across habitat patches where sands and gravels are 

alternately stable or mobilized for given flow conditions, it is possible to determine the effects on 

drift of “sand blasting,” vs. shear stress alone, vs. habitat loss via rock rolling.

We will carry out high resolution, habitat-specific, linked drift-shear stress-grain size data 

collection at five fishing ‘hot-spots’ in Glen Canyon (e.g., “4-mile bar” at RM -4.1). These study 

locations were originally suggested by fishers (Gerald Meyers, personal communication) and 

were corroborated as drift ‘hot-spots’ using drift monitoring data (see figure, above). On multiple 

dates and flow conditions over two years, we will collect data using standardized drift methods 

(Kennedy and others, 2014b), ADCP velocimetry for shear stress, and photographic methods for 

bed surface sediment. Using existing Glen Canyon-wide drift and bed shear stress data, along 

with bed sediment data that will be collected as part of Project 3, these resulting habitat-specific 

relationships between invertebrate drift concentrations, shear stress, and sediment entrainment 

can then be scaled up to predict invertebrate drift responses at habitat patches throughout Glen 

Canyon. To extend these predictions down river, especially into habitat near the LCR of interest 

for humpback chub management, we will use data from ADCP measurements for shear stress at 

the NO drift sites, as outlined above in Project Element 5.2.2. Combined with drift and with 

existing channel mapping data for the LCR inflow reach from Project 3, these data will allow 

drift predictions to be scaled up at a coarse scale throughout Grand Canyon, especially in reaches 

of particular interest for fisheries management.

For the study reach in Lower Marble Canyon—and possibly the reaches outlined above for 

Glen Canyon—invertebrate drift and bed condition will be investigated at a process level. In this 

reach, drift sampling in short downstream intervals will be conducted concurrently with repeat 

bed surveys and full water column multibeam echosounder data collection (described in Project 

3). These repeat bed surveys will enable identification of areas of the bed where active sand 

transport may limit benthic invertebrate colonization and areas where colonization may occur but 

is subject to disturbance. The full water column data may be used to detect invertebrate drift in 

the water column directly.

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Project Element 5.2.5. Comparative longitudinal drift studies in Upper and Lower Colorado River Basin 

tailwaters 

(Submitted for non-AMP funding FY15: $142,641)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Jeffrey Muehlbauer, Research Ecologist, USGS, GCMRC

Scott Miller, Director, BLM/Utah State University National Aquatic Monitoring Center

Here, we propose research on invertebrate drift in Glen, Marble, and Grand Canyons, and in 

other tailwaters of the Colorado River Basin: downstream of Fontenelle, Flaming Gorge, Navajo, 

Hoover, Davis, and Parker Dams. We will quantify the extent to which the low invertebrate 

diversity/productivity condition in Glen Canyon is unusual and how invertebrate diversity affects 

drift dynamics, especially in terms of temporal and spatial variation. We will also quantify how 

drift concentrations vary among tailwaters that are situated in canyons with different 

geomorphology than Glen Canyon, and have different flow management policies, such as 

hydropeaking in Flaming Gorge and Hoover, but not in Fontenelle and Navajo. Finally, we will 

characterize longitudinal drift and shear stress dynamics downstream of these Upper and Lower 

Basin dams and conduct seasonal at-a-station drift measurements to characterize the diversity 

and density of invertebrates entering the drift through time.

Sampling will occur over the course of one or two trips (single sampling), including sites 

extending approximately every mile from the dam to ~15 miles downstream. In addition, 

seasonal changes in the drift will be monitored at select stations within these tailwaters, likely 

proximate to discharge gages. Such seasonal monitoring in the Fontenelle and Flaming Gorge 

tailwaters would ideally be carried out through a collaborative agreement with other agencies, or 

by personnel led by Scott Miller and the BLM Bug Lab at Utah State University.

Our group has developed optimized methods for monitoring drift in Glen Canyon (as 

outlined in the Background and in Project Element 5.1). However, we expect these methods to 

require some adjustment in the Upper Basin tailwaters, particularly in river reaches that are 

narrower and shallower than those present in Glen Canyon. Ideally, appropriate drift sampling 

methodologies would be modified for these sites in consultation and collaboration with Scott 

Miller, who has experience sampling drift in some of these tailwaters (Miller and Judson, 2014).

One outcome of characterizing drift in other tailwaters will be to better understand the 

response of the food base that is available to endangered fish species, as relevant to proposed 

peak flow studies for endangered fish habitat in the Upper Basin (LaGory and others, 2014). 

Longitudinal and seasonal drift data in these tailwaters will also be useful in comparison to 

emergent insect data to better link emergent insect dynamics to invertebrate drift concentrations, 

as discussed in Project Element 1, above. Emergent insect citizen science monitoring in these 

tailwaters is currently proposed by Kennedy and others, and was initiated on the San Juan River 

downstream of Navajo Dam in April 2014 in collaboration with Grand Canyon Youth.

Finally, these drift data will be useful in putting observed drift, habitat, and invertebrate 

diversity patterns in the Glen Canyon Dam tailwater in context. For example, increased 

understanding of drift in other tailwaters should elucidate the degree to which observed patterns 

and biological processes downstream of Glen Canyon Dam, such as food limitation of fish 

populations, zero/low EPT diversity, and rates of downstream colonization are potentially 

atypical. These studies may also help identify approaches for increasing invertebrate drift 

availability, which would benefit native and desired non-native fish populations in the GlenMarble-Grand Canyon reach of the Colorado River.

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Project Element 5.3. Monitoring algae production in Glen, Marble, and Grand Canyons 

The monitoring described in this project element will synthesize algae production data for 

Glen Canyon, maintain dissolved oxygen monitoring at select locations in Glen, Marble, and 

Grand Canyon, and develop simpler, automated approaches for estimating algae production. 

Project Element 5.3.1. Controls of algal production in Glen, Marble, and Grand Canyon 

(Recommended for funding FY15: $25,970)

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

Michael Yard, Fisheries Biologist, USGS, GCMRC

Robert Payn, Assistant Professor, Montana State University

Robert Hall Jr., Professor, University of Wyoming

Daily estimates of algal production in Glen Canyon have been computed from 2008–present 

(Fig. 4). In FY15, we will synthesize these data and develop a manuscript describing the controls 

of algal production in Glen Canyon. In FY16 and FY17 we will estimate algae production in 

Marble and Grand Canyon using data from 2011–2015. A manuscript describing controls of 

algae production in these locations is currently in review (Hall and others, In review), but the 

period of record for that manuscript only spans 2008–2011 for one location (Diamond Creek) 

and quarterly estimates for other locations. Notably, the period of record does not include any 

HFEs.

Project Element 5.3.2. Continuous monitoring of dissolved oxygen concentrations in Glen, Marble, and Grand 

Canyons 

(Recommended for funding FY15: $15,260)

Adam Copp, Ecologist, USGS, GCMRC

Nicholas Voichick, Hydrologist, USGS, GCMRC

In FY15–17 we will maintain our network of continuous dissolved oxygen monitoring 

stations at six locations in Glen, Marble, and Grand Canyons (RM 0, 30, 61, 87, 166, and 225).

Project Element 5.3.3. Develop automated tools for converting dissolved oxygen data to algal production 

(Recommended for funding FY15: $0)

Charles Yackulic, Research Statistician, USGS, GCMRC

Edward Stets, Ecologist, USGS, National Research Program

Robert Hall Jr., Professor, University of Wyoming

Stets is the lead, and Hall and Yackulic are collaborators, on a recently submitted USGS 

Powell Center for Analysis and Synthesis proposal, the purpose of which is to develop 

automated tools for converting dissolved oxygen data into algal production estimates. If the 

proposal is successful, one outcome of the synthesis will be automated tools developed 

specifically for sites in Glen, Marble, and Grand Canyons where we have been continuously 

monitoring dissolved oxygen since 2008–2010.

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D.2. Personnel and Collaborations 

Aquatic invertebrate monitoring and research efforts at GCMRC provide important insight 

into the condition of the Colorado River ecosystem, particularly with respect the foodbase 

available to fish. However, these studies require the collection of a large number of samples that 

can demand substantial time to process, necessitating a large staff. Within the GCMRC Aquatic 

Ecology group, research projects are conceived, designed, and analyzed by principal investigator 

Theodore Kennedy. Postdoctoral fellow Jeffrey Muehlbauer also acts as a principal investigator 

in conceiving and carrying out research projects and analysis, and brings integrated invertebrate 

ecology, geomorphology, and hydrology expertise to the group. Adam Copp manages sample 

inventories and databases, maintains the invertebrate drift and water quality monitoring projects, 

and oversees the day-to-day operations of the lab. Joshua Smith serves as field crew leader, 

particularly for ongoing research and monitoring projects in Glen Canyon and the Little 

Colorado River. Eric Kortenhoeven and Anya Metcalfe are responsible for processing light trap 

samples; they also provide outreach and interface with the citizen scientist river guides who 

collect these samples. Moriah Evans, Thomas Quigley, and ~3 additional full time, part time, or 

student technicians are primarily responsible for the lab processing of drift samples. All 

personnel also take part in field work in support of these projects.

Our group is also taking innovative steps to optimize workflow and minimize processing 

times. For instance, we have developed a barcoding system to track the status of >6000 samples 

that are in various stages, from sample collection, to storage, to active processing, to analyzed 

sample archiving (Copp and others, In review). Since barcoding was initiated in 2012, we have 

collected an average of 900 drift samples per year, which will be reduced to ~650 samples 

annually in FY 15–17 with reduced sampling effort for the Natal Origins project. Earlier 

inefficiencies created a large backlog of samples that we are still processing, but at current rates 

of 4 hours of processing time per sample we expect our FY15–17 drift processing capacity to be 

approximately equal to sample collection efforts.

We have also processed ~2000 light trap samples since 2012, at a rate of roughly one sample 

every 45 minutes. Finally, we have deployed ~2000 sticky traps since 2013 (Smith and others, 

2014). Most of the sticky trap samples have not yet been processed because the automated image 

processing protocol for their analysis is still in active development; however, early tests indicate 

that processing time should ultimately be only 2 minutes per sample.

This project will utilize and integrate data from, provide data for, and require collaborations 

with other projects described in this work plan. Specifically, data collection in Projects 2 and 3 

related to discharge, temperature, suspended sediment concentrations, channel width, and 

shoreline inundation will be requisite for successful completion of most of the sub-tasks in 

Project Elements 5.1, 5.2, and 5.3 outlined in this project. Completion of these tasks will take 

place with input from geomorphologists Paul Grams and Daniel Buscombe and hydrologist 

Nicholas Voichick associated with those projects, in addition to Scott Wright from the USGS 

California Water Science Center. Algae production modeling described in Project Element 5.3 

will also occur in collaboration with faculty at Montana State University and the University of 

Wyoming, as well as USGS scientists affiliated with the National Research Program.

Many sub-tasks within this project will specifically address fisheries questions outlined 

throughout this work plan. For instance, Project Elements 5.2.2 and 5.2.3 build upon rainbow 

trout and humpback chub foodbase data needs described by Michael Yard, Josh Korman, and 

others as part of the Natal Origins project described in Project 9. These data will be used to 

195
quantify the availability of invertebrate prey resources at key fish monitoring locations in Glen 

and Marble Canyons, including at the confluence of the Little Colorado River. Citizen science 

emergence monitoring data will also inform new proposed studies on terrestrial-aquatic linkages 

(see Project Element 11.4).

Several of the sub-tasks in Project Elements 5.1 and 5.2 describe a nascent collaboration 

between GCMRC scientists and the BLM/Utah State University National Aquatic Monitoring 

Center. The results and output from this collaboration will be invaluable toward the goal of 

putting the state of the aquatic foodbase in Glen, Marble, and Grand Canyons in the larger 

context of the Colorado River Basin throughout the Intermountain West.

Finally, David Lytle/Oregon State University is the author of seminal publications on aquatic 

insect dispersal, aquatic insect response and adaptations to disturbances including floods, and 

population genetics of insects in arid landscapes (Lytle, 1999, 2001, 2002; McMullen and Lytle, 

2012). Collaboration with Lytle on Project Element 5.1 will allow us to put proposed data 

collections into the broader context of disturbance regimes and aquatic insect life-history 

evolution.

D.3. Deliverables 

This project will yield new scientific insights that are directly relevant to management of 

invertebrate assemblages and food webs in the River. Our investigations will largely focus on 

evaluating the validity of one hypothesis (H5) that explains the low diversity and productivity of 

the aquatic foodbase. The flow experiment we propose represents a test of policy option that 

might ultimately ameliorate the effects that hydropeaking may be having on invertebrate 

diversity and productivity. Implementation of the proposed flow experiment will also greatly 

increase the power of the inferences we can draw relative to the validity of H5. If the studies 

proposed for FY15-2017 yield data that does not ultimately support this hypothesis (i.e., 

hydropeaking does NOT appear to be the principal stressor limiting the diversity and 

productivity of invertebrate assemblages), then investigations in 2018 and beyond could focus on 

evaluating alternative hypotheses, including the dispersal limitation hypothesis (H3) through 

direct translocations of native Colorado River invertebrates. Additionally, the syntheses and field 

studies we propose in other regulated and unregulated segments of the Basin will yield a list of 

“candidate” aquatic insect species that are native to the Colorado River that Glen Canyon 

National Recreational Area and/or Grand Canyon National Park could consider for translocation.

In general, most of the 16 project elements should result in one or more peer-reviewed 

journal articles and presentations at scientific meetings; the remaining smaller project elements 

will provide critical supporting information to larger project elements. These larger project 

elements describe cutting-edge work in the fields of limnology as well as ecology in general, and 

the outcome of several of these project elements should be the publication of papers in some of 

the highest-tier scientific journals.

The studies described in Project Elements 5.1 and 5.2 on emergent and drifting insect 

dynamics are representative examples of the current trend in ecology toward “big data,” or the 

analysis of very large datasets, as well as the syntheses of data on a large scale from multiple, 

disparate sources. This work will enable us to characterize aquatic insect and invertebrate 

dynamics in the Colorado River Basin in unprecedented detail, with the benefit that we will be 

able to discern patterns and controls on invertebrate populations that were previously impossible 

to describe. The publication of these data and analyses, beginning in FY15 and continuing in 

future fiscal years as studies are completed, thus represent a major step forward in our power to 

predict and describe aquatic foodbase patterns in time and space.

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Finally, algae production monitoring described in Project Element 5.3 is unprecedented for a 

large river, and at least two peer-reviewed articles describing controls on algae production in 

Glen, Marble, and Grand Canyon will be produced during FY15–17.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

Aquatic ecology webpage. Provides photos and publications that describes major areas of 

research. (http://www.gcmrc.gov/research_areas/food_base/food_base_default.aspx)

Citizen Science in Grand Canyon. 7 minute video that describes the ecology of the Colorado 

River in Grand Canyon, and how citizen science insect monitoring is leading to a deeper 

understanding of this unique ecosystem. (http://www.youtube.com/watch?v=2TxLWlrw7y4)

E.2. Completed Publications 

Cross, W.F., Baxter, C.V., Rosi-Marshall, E.J., Hall, R.O., Kennedy, T.A., Donner, K.C., 

Wellard Kelly, H.A., Seegert, S.E.Z., Behn, K.E., and Yard, M.D., 2013, Food-web 

dynamics in a large river discontinuum: Ecological Monographs, v. 83, no. 3, p. 311–337.

Kennedy, T.A., 2013, Identification and evaluation of scientific uncertainties related to fish and 

aquatic resources in the Colorado River, Grand Canyon—summary and interpretation of an 

expert-elicitation questionnaire: US Geological Survey Scientific Investigations Report 

2013–5027.

Kennedy, T.A., Cross, W.F., Hall, R.O., Baxter, C.V., and Rosi-Marshall, E.J., 2013, Native and 

nonnative fish populations of the Colorado River are food-limited—evidence from new food 

web analyses: US Geological Survey Fact Sheet 2013–3039, 8 p.

Kennedy, T., Kortenhoeven, E., and Fritzinger, C., 2013, Guides + science = citizen science: 

Boatman's Quarterly Review, v. 26, no. 1, p. 20–21.

Kennedy, T.A., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M.D., and Copp, A.J., 2014, 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river: Freshwater Biology, v. 59, no. 3, p. 557–572.

Muehlbauer, J.D., Collins, S.F., Doyle, M.W., 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.

Riggsbee, J.A., Doyle, M.W., Julian, J.P., Manners, R., Muehlbauer, J.D., Sholtes, J.S., and 

Small, M.J., 2013, Influence of aquatic and semi-aquatic organisms on channel forms and 

processes, in Wohl, E., ed., Fluvial Geomorphology: San Diego, California, USA, Academic 

Press, p. 189–202.

Smith, J.T., Kennedy, T.A., and Muehlbauer, J.D., 2014, Building a better sticky trap: 

description of an easy-to-use trap and pole mount for quantifying the abundance of adult 

aquatic insects: Freshwater Science, v. 33, no. 3.

Wang, H., Li, H., Zhang, Z., Muehlbauer, J.D., He, Q., Xu, X., Yue, C., and Jiang, D., 2014, 

Linking stoichiometric homeostasis of microorganisms with soil phosphorus dynamics in 

wetlands subjected to microcosm warming: PLoS ONE, v. 9, no. 1, p. e85575.

Wellard Kelly, H.A., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O., Cross, W.F., and Baxter, 

C.V., 2013, Macroinvertebrate diets reflect tributary inputs and turbidity-driven changes in 

food availability in the Colorado River downstream of Glen Canyon Dam: Freshwater 

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Science, v. 32, no. 2, p. 397–410.

Zahn Seegert, S., Rosi-Marshall, E., Baxter, C., Kennedy, T., Hall, R., and Cross, W., In press, 

High diet overlap between native small-bodied and non-native Fathead Minnow in the 

Colorado River, Grand Canyon: Transactions of the American Fisheries Society.

E.3. Publications in progress 

Clay, P.A., Muehlbauer, J.D., and Doyle, M.W., In review, Effect of tributary and braided 

confluences on aquatic macroinvertebrate communities and geomorphology in an alpine river 

watershed: Submitted to Freshwater Science.

Copp, A.J., Kennedy, T.A., and Muehlbauer, J.D. In review, Barcodes are a useful tool for 

labeling and tracking ecological samples: Submitted to Bulletin of the Ecological Society of 

America.

Hall, R.O., Yackulic, C.B., Kennedy, T.A., Yard, M.D., Rosi-Marshall, E.J., Voichick, N., Behn, 

K.E., In review, Turbidity, light, and hydropeaking control gross primary production in the 

Colorado River, Grand Canyon: Submitted to Limnology and Oceanography.

Muehlbauer, J.D., and Doyle, M.W. (In Prep) Flooding decouples a major aquatic-terrestrial 

subsidy: insights from the combination of multiple ecological theories: For Journal of Animal 

Ecology.

Muehlbauer, J.D., Clay, P.A., Doyle, M.W., and Tockner, K. (In Prep) Geophysical controls on 

the spatial dynamics of river-to-land subsidies, based on global field analysis: For Ecological 

Monographs.

E.4. Presentations at GCDAMP meetings 

Kennedy, T.A., 2013, Foodbase update, Glen Canyon Dam Adaptive Management Program 

Technical Work Group Annual Reporting Meeting, Phoenix, Arizona, USA.

Kennedy, T.A., and Hall, R.O., 2013, Foodweb analysis shows that food availability for fish 

downstream of Glen Canyon Dam is severely limited, Webex Briefing to the Assistant 

Secretary for Water and Science.

Kennedy, T.A., Hall, R.O., and Cross, W.F., 2013, Foodweb analysis shows that food 

availability for fish downstream of Glen Canyon Dam is severely limited, Webex Briefing to 

the Technical Work Group.

Kennedy, T., Muehlbauer, J., and Yackulic, C. 2014, Foodweb update, Glen Canyon Dam 

Adaptive Management Program Annual Reporting Meeting, Phoenix, Arizona, USA.

E.5. Presentations at professional meetings 

Copp, A.J., Kennedy, T.A., and Muehlbauer, J.D., 2013, Learning from retailers: barcoding is a 

useful tool for labeling and tracking samples in field and lab settings, 12th Biennial 

Conference of Science and Management on the Colorado Plateau: Flagstaff, Arizona, USA.

Copp, A.J., Kennedy, T.A., and Muehlbauer, J.D., 2014, Don't get clogged up: using net 

filtration efficiency to inform deployment length in drift studies, Joint Aquatic Sciences 

Meeting: Portland, Oregon, USA.

Kennedy, T., Yackulic, C., Cross, W., Grams, P., Yard, M., and Copp, A. 2013, The relationship 

between invertebrate drift and two primary controls—discharge and benthic density—in a 

large regulated river, Ecological Society of America Meeting: Minneapolis, Minnesota, USA.

Kennedy, T.A., Yackulic, C.B., Muehlbauer, J.D., Kortenhoeven, E., and Copp, A.J., 2013, High 

resolution sampling of insect emergence by citizen scientists leads to fundamental insights 

198
about the life history of aquatic insects in the Colorado River, Grand Canyon, 12th Biennial 

Conference of Science and Management on the Colorado Plateau: Flagstaff, Arizona, USA.

Kennedy, T.A., Muehlbauer, J.D., and Yackulic, C.B., 2014, Flow management alters rates of 

insect emergence from the Colorado River in Grand Canyon, Joint Aquatic Sciences 

Meeting: Portland, Oregon, USA.

Muehlbauer, J.D., Kennedy, T.A., and Yackulic, C.B., 2013, Shear stress drives local variation in 

invertebrate drift in a large river, American Geophysical Union Fall Meeting: San Francisco, 

Califonia, USA.

Muehlbauer, J.D., Kennedy, T.A., Smith, J.T., Sankey, J.B., and Kortenhoeven, E.W., 2014, 

Advances in emergent insect sampling: new sticky trap designs and automated sample 

processing, Joint Aquatic Sciences Meeting: Portland, Oregon, USA.

Smith, J.T., Kennedy, T.A., and Muehlbauer, J.D., 2013, Building a better bug trap, 12th 

Biennial Conference of Science and Management on the Colorado Plateau: Flagstaff, 

Arizona, USA.

Smith, J.T., Muehlbauer, J.D., and Kennedy, T.A., 2014, Determining the effects of insect 

pheromone release on sticky trap catch rates, Joint Aquatic Sciences Meeting: Portland, 

Oregon, USA.

F. References 

Anders, P., Bradford, M.c., Higgins, P., Nislow, K.H., Rabeni, C.F., and Tate, C., 2001, Grand 

Canyon Monitoring and Research Center protocols evaluation program—final report of the 

aquatic protocol evaluation program panel: U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center, 43 p.

Anderson, N.H., and Lehmkuhl, D.M., 1968, Catastrophic drift of insects in a woodland stream: 

Ecology, v. 49, no. 2, p. 198–206.

Barbour, M.T., Gerritsen, J., Snyder, B.D., and Stribling, J.B., 1999, Rapid bioassessment 

protocols for use in streams and wadeable rivers: US Environmental Protection Agency 

Report EPA 841-B-99-002, 339 p.

Blinn, D.W., Shannon, J.P., Stevens, L.E., and Carder, J.P., 1995, Consequences of fluctuating 

discharge for lotic communities: Journal of the North American Benthological Society, v. 14, 

no. 2, p. 233–248.

Bunn, S.E., and Arthington, A.H., 2002, Basic principles and ecological consequences of altered 

flow regimes for aquatic biodiversity: Environmental Management, v. 30, no. 4, p. 492–507.

Carlisle, D.M., Meador, M.R., Short, T.M., Tate, C.M., Gurtz, M.E., Bryant, W.L., Falcone, J.A., 

and Woodside, M.D., 2013, Ecological health in the Nation’s streams, 1993–2005: US 

Geological Survey Circular 1391, 120 p.

Copp, A.J., Kennedy, T.A., and Muehlbauer, J.D., In review, Barcodes are a useful tool for 

labeling and tracking ecological samples: Submitted to Bulletin of the Ecological Society of 

America.

Cross, W.F., Baxter, C.V., Donner, K.C., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O., 

Wellard Kelly, H.A., and Rogers, R.S., 2011, Ecosystem ecology meets adaptive 

management: food web response to a controlled flood on the Colorado River, Glen Canyon: 

Ecological Applications, v. 21, no. 6, p. 2016–2033.

Cross, W.F., Baxter, C.V., Rosi-Marshall, E.J., Hall, R.O., Kennedy, T.A., Donner, K.C., 

Wellard Kelly, H.A., Seegert, S.E.Z., Behn, K.E., and Yard, M.D., 2013, Food-web 

dynamics in a large river discontinuum: Ecological Monographs, v. 83, no. 3, p. 311–337.

199
Donner, K.C., 2011, Trophic basis of production of fishes in the Colorado River, Grand 

Canyon—an assessment of potential competition for food: Pocatello, Idaho, USA, Idaho 

State University, M.S. Thesis.

Elliott, J.M., 1978, Effect of temperature on the hatching time of eggs of Ephemerella ignita 

(Poda) (Ephemeroptera:Ephemerellidae): Freshwater Biology, v. 8, no. 1, p. 51–58.

Encalada, A.C., and Peckarsky, B.L., 2012, Large-scale manipulation of mayfly recruitment 

affects population size: Oecologia, v. 168, no. 4, p. 967–976.

Gibbins, C., Vericat, D., and Batalla, R.J., 2007a, When is stream invertebrate drift catastrophic? 

The role of hydraulics and sediment transport in initiating drift during flood events: 

Freshwater Biology, v. 52, no. 12, p. 2369–2384.

Gibbins, C., Vericat, D., Batalla, R.J., and Gomez, C.M., 2007b, Shaking and moving: low rates 

of sediment transport trigger mass drift of stream invertebrates: Canadian Journal of Fisheries 

and Aquatic Sciences, v. 64, no. 1, p. 1–5.

Gratton, C., and Vander Zanden, M.J., 2009, Flux of aquatic insect productivity to land: 

comparison of lentic and lotic ecosystems: Ecology, v. 90, no. 10, p. 2689–2699.

Haden, G.A., Shannon, J.P., Wilson, K.P., and Blinn, W., 2003, Benthic community structure of 

the Green and Colorado Rivers through Canyonlands National Park, Utah, USA: The 

Southwestern Naturalist, v. 48, no. 1, p. 23–35.

Hall, R.O., Kennedy, T.A., and Rosi-Marshall, E.J., 2012, Air–water oxygen exchange in a large 

whitewater river: Limnology & Oceanography: Fluids & Environments, v. 2, p. 1–11.

Hall, R.O., Kennedy, T.A., Rosi-Marshall, E.J., Cross, W.F., Wellard, H.A., and Baxter, C.F., 

2010, Aquatic production and carbon flow in the Colorado River, in Melis, T.S., Hamill, J.F., 

Bennet, G.E., Coggins, L.G., Grams, P.E., Kennedy, T.A., Kubly, D.M., and Ralston, B.E., 

eds., Proceedings of the Colorado River Basin Science and Resource Management 

Symposium, November 18–20, 2008, Scottsdale, Arizona: US Geological Survey Scientific 

Investigations Report 2010–5135, p. 105-112.

Hall, R.O., Yackulic, C.B., Kennedy, T.A., Yard, M.D., Rosi-Marshall, E.J., Voichick, N., and 

Behn, K.E., In review, Turbidity, light, and hydropeaking control gross primary production 

in the Colorado River, Grand Canyon: Submitted to Limnology and Oceanography.

Holton, B., 2008, Translocation of humpback chub above Chute Falls in the Little Colorado 

River, July 17-22, 2008—trip report: U.S. Fish and Wildlife Service, 13 p.

Huryn, A.D., and Wallace, J.B., 2000, Life history and production of stream insects: Annual 

Review of Entomology, v. 45, p. 83–110.

Kennedy, T., Kortenhoeven, E., and Fritzinger, C., 2013a, Guides + science = citizen science: 

Boatman's Quarterly Review, v. 26, no. 1, p. 20–21.

Kennedy, T., Muehlbauer, J., and Yackulic, C., 2014a, Foodweb update, Glen Canyon Dam 

Adaptive Management Program Annual Reporting Meeting: Phoenix, Arizona, USA.

Kennedy, T.A., Cross, W.F., Hall, R.O., Baxter, C.V., and Rosi-Marshall, E.J., 2013b, Native 

and nonnative fish populations of the Colorado River are food-limited—evidence from new 

food web analyses: US Geological Survey Fact Sheet 2013–3039, 8 p.

Kennedy, T.A., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M.D., and Copp, A.J., 2014b, 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river: Freshwater Biology, v. 59, no. 3, p. 557–572.

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 

200
assessment model: Canadian Journal of Fisheries and Aquatic Sciences, v. 69, no. 11, p. 

1827–1849.

LaGory, K., Chart, T., Mohrman, J., Pitlick, J., Williams, C., Minear, J.T., Schmidt, J.C., 

Topping, D., Grams, P., Greimann, B., Pitts, T., and Luecke, D.F., 2014, Study plan to 

identify peak flow requirements for sediment transport and habitat maintenance in the Upper 

Colorado River Basin (Preliminary draft): Upper Colorado River Endangered Fish Recovery 

Program, 21 p.

Lenat, D.R., 1993, A Biotic Index for the Southeastern United States: Derivation and List of 

Tolerance Values, with Criteria for Assigning Water-Quality Ratings: Journal of the North 

American Benthological Society, v. 12, no. 3, p. 279-290.

Lenat, D.R., and Penrose, D.L., 1996, History of the EPT taxa richness metric: Bulletin of the 

North American Benthological Society, v. 13, no. 2, p. 305-307.

Lytle, D., 1999, Use of rainfall cues by Abedus herberti (Hemiptera: Belostomatidae): a 

mechanism for avoiding flash floods: Journal of Insect Behavior, v. 12, no. 1, p. 1-12.

Lytle, D., 2001, Disturbance regimes and life history evolution: American Naturalist, v. 157, p. 

525-536.

Lytle, D., 2002, Flash floods and aquatic insect life-history evolution: evaluation of multiple 

models: Ecology, v. 83, no. 2, p. 370-385.

McKinney, T., and Speas, D., 2001, Observations of size-related asymmetries in diet and energy 

intake of rainbow trout in a regulated river: Environmental Biology of Fishes, v. 61, no. 4, p. 

435–444.

McMullen, L.E., and Lytle, D.A., 2012, Quantifying invertebrate resistance to floods: a globalscale meta-analysis: Ecological Applications, v. 22, no. 8, p. 2164-2175.

Merritt, R.W., Cummins, K.W., and Berg, M.B., eds., 2008, An introduction to the aquatic 

insects of North America (4th ed.): Dubuque, Iowa, USA, Kendall Hunt, 1214 p.

Miller, S.W., and Judson, S., 2014, Responses of macroinvertebrate drift, benthic assemblages 

and trout foraging to hydropeaking: Canadian Journal of Fisheries and Aquatic Sciences.

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.

Muehlbauer, J.D., Kennedy, T.A., and Yackulic, C.B., 2013, Shear stress drives local variation in 

invertebrate drift in a large river, American Geophysical Union Fall Meeting: San Francisco, 

Califonia, USA.

Müller, K., 1982, The colonization cycle of freshwater insects: Oecologia, v. 52, no. 2, p. 202–

207.

Oberlin, G.E., Shannon, J.P., and Blinn, D.W., 1999, Watershed influence on the 

macroinvertebrate fauna of ten major tributaries of the Colorado River through Grand 

Canyon, Arizona: The Southwestern Naturalist, p. 17–30.

Olden, J.D., and Naiman, R.J., 2010, Incorporating thermal regimes into environmental flows 

assessments: modifying dam operations to restore freshwater ecosystem integrity: Freshwater 

Biology, v. 55, no. 1, p. 86–107.

Parker, G., and Klingeman, P.C., 1982, On why gravel bed streams are paved: Water Resources 

Research, v. 18, no. 5, p. 1409–1423.

Poff, N.L., 1997, Landscape Filters and Species Traits: Towards Mechanistic Understanding and 

Prediction in Stream Ecology: Journal of the North American Benthological Society, v. 16, 

no. 2, New Concepts in Stream Ecology: Proceedings of a Symposium, p. 391-409.

201
Resh, V.H., Brown, A.V., Covich, A.P., Gurtz, M.E., Li, H.W., Minshall, G.W., Reice, S.R., 

Sheldon, A.L., Wallace, J.B., and Wissmar, R.C., 1988, The role of disturbance in stream 

ecology: Journal of the North American Benthological Society, v. 7, no. 4, Community 

Structure and Function in Temperate and Tropical Streams: Proceedings of a Symposium, p. 

433–455.

Robinson, C.T., 2012, Long-term changes in community assembly, resistance, and resilience 

following experimental floods: Ecological Applications, v. 22, no. 7, p. 1949–1961.

Seegert, S.E.Z., Rosi-Marshall, E.J., Baxter, C.V., Kennedy, T.A., Hall, R.O., and Cross, W.F., 

In press, High diet overlap between native small-bodied and non-native Fathead Minnow in 

the Colorado River, Grand Canyon: Transactions of the American Fisheries Society.

Shields, A., 1936, Anwendung der aehnlichkeitsmechanik und der turbulenzforschung auf die 

geschiebebewegung, Mitteilung der preußischen Versuchsanstalt für Wasserbau und 

Schiffbau: Berlin, Germany.

Smith, J.T., Kennedy, T.A., and Muehlbauer, J.D., 2014, Building a better sticky trap: 

description of an easy-to-use trap and pole mount for quantifying the abundance of adult 

aquatic insects: Freshwater Science, v. 33, no. 3.

Spurgeon, J.J., 2012, Translocation of humpback chub (Gila cypha) and food-web dynamics in 

Grand Canyon National Park tributary streams: Columbia, Missouri, USA, University of 

Missouri-Columbia, M.S. Thesis, 84 p.

Stanford, J.A., and Ward, J.V., 2001, Revisiting the serial discontinuity concept: Regulated 

Rivers: Research & Management, v. 17, no. 4-5, p. 303–310.

Statzner, B., Elouard, J.M., and Dejoux, C., 1986, Field experiments on the relationship between 

drift and benthic densities of aquatic insects in tropical streams (Ivory Coast). II. 

Cheumatopsyche falcifera (Trichoptera: Hydropsychidae): Journal of Animal Ecology, v. 55, 

no. 1, p. 93–110.

Statzner, B., and Resh, V., 1993, Multiple-site and-year analyses of stream insect emergence: a 

test of ecological theory: Oecologia, v. 96, no. 1, p. 65–79.

Trammel, M., Healy, B., Omana Smith, E., and Sponholtz, P.J., 2012, Humpback chub 

translocation to Havasu Creek, Grand Canyon National Park—implementation and 

monitoring plan: National Park Service, Grand Canyon Park Natural Resource Report 

NPS/GRCA/NRR—2012/586, 26 p.

Vinson, M.R., 2001, Long-term dynamics of an invertebrate assemblage downstream from a 

large dam: Ecological Applications, v. 11, no. 3, p. 711–730.

Voichick, N., and Wright, S.A., 2007, Water-temperature data for the Colorado River and 

tributaries between Glen Canyon Dam and Spencer Canyon, northern Arizona, 1988-2005 

U.S. Geological Survey Data Survey Series 251, 24 p.

Walters, C.J., 1986, Adaptive management of renewable resources: Caldwell, New Jersey, USA, 

The Blackburn Press, 374 p.

Ward, J.V., and Stanford, J.A., 1983, The serial discontinuity concept of lotic ecosystems, in

Fontaine, T.D., and Bartell, S.M., eds., Dynamics of Lotic Ecosystems: Ann Arbor, 

Michigan, USA, Ann Arbor Science Publications, p. 29–42.

Wellard Kelly, H.A., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O., Cross, W.F., and Baxter, 

C.V., 2013, Macroinvertebrate diets reflect tributary inputs and turbidity-driven changes in 

food availability in the Colorado River downstream of Glen Canyon Dam: Freshwater 

Science, v. 32, no. 2, p. 397-410.

Whiting, D.P., Paukert, C.P., Healy, B.D., and Spurgeon, J.J., 2014, Macroinvertebrate prey 

202
availability and food web dynamics of nonnative trout in a Colorado River tributary, Grand 

Canyon: Freshwater Science, v. 33, no. 3.

Wilcock, P.R., 1996, Estimating local bed shear stress from velocity observations: Water 

Resources Research, v. 32, no. 11, p. 3361–3366.

203
G. Budget 

Project Element 5.1.1 Insect 

emergence via citizen science 

Project Element 5.1.2. 

Hydropeaking effects on egg 

mortality

Salaries $75,688 Salaries $37,844

Traveling and Training $350 Traveling and Training $700

Operating Expenses $9,000 Operating Expenses $3,000

Logistics $3,807 Logistics $26,648

GIS/RS/Electronics support $4,820 GIS/RS/Electronics support $9,639

Cooperators (non-USGS) $9,000 Cooperators (non-USGS) $6,750

USGS cooperators $0 USGS cooperators $0

USGS Burden $15,217 USGS Burden $12,626

Total $117,881 Total $97,207

Project Element 5.1.3. Synthesis 

of controls on EPT distributions

Project Element 5.1.4. 

Synthesis of the foodbase in 

tailwaters

Salaries $25,229 Salaries $25,229

Traveling and Training $350 Traveling and Training $350

Operating Expenses $0 Operating Expenses $0

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $4,093 USGS Burden $4,093

Total $29,672 Total $29,672

Project Element 5.1.5. 

Oviposition for species in 

Grand Canyon

Project Element 5.1.6. 

Laboratory studies on egg 

mortality 

Salaries $12,615 Salaries $25,229

Traveling and Training $700 Traveling and Training $700

Operating Expenses $3,000 Operating Expenses $6,000

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $6,750 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $2,783 USGS Burden $5,109

Total $25,848 Total $37,038

Project Element 5.1.7. Upper 

Basin emergence via citizen 

science

Project Element 5.1.8. Natural 

history of EPT in the Upper 

Basin

Salaries $37,844 Salaries $12,615

Traveling and Training $1,400 Traveling and Training $2,450

Operating Expenses $6,000 Operating Expenses $3,000

Logistics $3,807 Logistics $3,807

GIS/RS/Electronics support $1,607 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $8,105 USGS Burden $3,499

Total $58,762 Total $25,371

FY 2015 Project Grand Total: $421,452

FY 2015

204
Project Element 5.1.1. Insect 

emergence via citizen science 

Project Element 5.1.2. 

Hydropeaking effects on egg 

mortality

Salaries $78,223 Salaries $39,111

Traveling and Training $361 Traveling and Training $721

Operating Expenses $9,270 Operating Expenses $3,090

Logistics $3,921 Logistics $27,448

GIS/RS/Electronics support $5,070 GIS/RS/Electronics support $10,140

Cooperators (non-USGS) $1,854 Cooperators (non-USGS) $6,953

USGS cooperators $0 USGS cooperators $0

USGS Burden $21,353 USGS Burden $17,891

Total $120,052 Total $105,354

Project Element 5.1.3. Synthesis 

of controls on EPT distributions

Project Element 5.1.4. 

Synthesis of the foodbase in 

tailwaters

Salaries $26,074 Salaries $26,074

Traveling and Training $361 Traveling and Training $361

Operating Expenses $0 Operating Expenses $0

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $5,816 USGS Burden $5,816

Total $32,250 Total $32,250

Project Element 5.1.5. 

Oviposition for species in 

Grand Canyon

Project Element 5.1.6. 

Laboratory studies on egg 

mortality 

Salaries $13,037 Salaries $26,074

Traveling and Training $721 Traveling and Training $721

Operating Expenses $3,090 Operating Expenses $6,180

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $6,953 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $3,885 USGS Burden $7,255

Total $27,686 Total $40,230

Project Element 5.1.7. Upper 

Basin emergence via citizen 

science

Project Element 5.1.8. Natural 

history of EPT in the Upper 

Basin

Salaries $39,111 Salaries $13,037

Traveling and Training $1,442 Traveling and Training $2,524

Operating Expenses $6,180 Operating Expenses $3,090

Logistics $3,921 Logistics $3,921

GIS/RS/Electronics support $1,690 GIS/RS/Electronics support $0

Cooperators (non-USGS) $464 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $11,528 USGS Burden $4,966

Total $64,336 Total $27,538

FY 2016 Project Grand Total: $449,696

FY 2016

205
Project Element 5.1.1. Insect 

emergence via citizen science 

Project Element 5.1.2. 

Hydropeaking effects on egg 

mortality

Salaries $88,319 Salaries $44,160

Traveling and Training $371 Traveling and Training $743

Operating Expenses $9,548 Operating Expenses $3,183

Logistics $4,039 Logistics $28,271

GIS/RS/Electronics support $5,172 GIS/RS/Electronics support $10,343

Cooperators (non-USGS) $1,432 Cooperators (non-USGS) $7,161

USGS cooperators $0 USGS cooperators $0

USGS Burden $30,122 USGS Burden $24,459

Total $139,004 Total $118,320

Project Element 5.1.3. Synthesis of 

controls on EPT distributions

Project Element 5.1.4. 

Synthesis of the foodbase in 

tailwaters

Salaries $29,440 Salaries $29,440

Traveling and Training $371 Traveling and Training $371

Operating Expenses $0 Operating Expenses $0

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $8,347 USGS Burden $8,347

Total $38,158 Total $38,158

Project Element 5.1.5. Oviposition 

for species in Grand Canyon

Project Element 5.1.6. 

Laboratory studies on egg 

mortality 

Salaries $14,720 Salaries $29,440

Traveling and Training $743 Traveling and Training $743

Operating Expenses $3,183 Operating Expenses $6,365

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $7,161 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $5,404 USGS Burden $10,233

Total $31,211 Total $46,781

Project Element 5.1.7. Upper Basin 

emergence via citizen science

Project Element 5.1.8. Natural 

history of EPT in the Upper 

Basin

Salaries $44,160 Salaries $14,720

Traveling and Training $1,485 Traveling and Training $2,599

Operating Expenses $6,365 Operating Expenses $3,183

Logistics $4,039 Logistics $4,039

GIS/RS/Electronics support $1,724 GIS/RS/Electronics support $0

Cooperators (non-USGS) $955 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $16,201 USGS Burden $6,871

Total $74,929 Total $31,412

FY 2017 Project Grand Total: $517,973

FY 2017

206
5.2.1. Continue characterizing and 

monitoring drift and insect 

emergence in Glen Canyon

5.2.2. Continue Natal Origins 

drift monitoring in Glen, Marble, 

and Grand Canyon

Salaries $36,407 Salaries $72,815

Traveling and Training $7,000 Traveling and Training $1,000

Operating Expenses $1,500 Operating Expenses $1,500

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $7,185 USGS Burden $12,050

Total $52,093 Total $87,365

5.2.3. Link drift at Natal Origins 

project transects to channel bed 

shear stress

5.2.4. Link invertebrate drift 

patterns to substrate conditions 

in Glen, Marble, and Grand 

Canyon

Salaries $9,102 Salaries $9,102

Traveling and Training $300 Traveling and Training $400

Operating Expenses $250 Operating Expenses $250

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $9,423 USGS cooperators $9,423

USGS Burden $2,144 USGS Burden $2,160

Total $21,219 Total $21,335

5.2.5. Comparative longitudinal 

drift studies in Upper and Lower 

Colorado River Basin tailwaters

Salaries $54,611

Traveling and Training $5,300

Operating Expenses $1,500

Logistics $20,000

GIS/RS/Electronics support $0

Cooperators (non-USGS) $46,800

USGS cooperators $0

USGS Burden $13,026

Total $141,237

FY 2015 Project Gross Total:

$323,249

Project Element 5.2, FY 2015

207
208
5.2.1. Continue characterizing and 

monitoring drift and insect emergence 

in Glen Canyon

5.2.2. Continue Natal Origins 

drift monitoring in Glen, Marble, 

and Grand Canyon

Salaries $60,395 Salaries $120,790

Traveling and Training $7,426 Traveling and Training $1,061

Operating Expenses $1,591 Operating Expenses $1,591

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $19,435 USGS Burden $34,564

Total $88,848 Total $158,006

5.2.3. Link drift at Natal Origins 

project transects to channel bed shear 

stress

5.2.4. Link invertebrate drift 

patterns to substrate conditions 

in Glen, Marble, and Grand 

Canyon

Salaries $15,099 Salaries $15,099

Traveling and Training $318 Traveling and Training $424

Operating Expenses $265 Operating Expenses $265

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $9,997 USGS cooperators $9,997

USGS Burden $5,028 USGS Burden $5,057

Total $30,707 Total $30,842

5.2.5. Comparative longitudinal drift 

studies in Upper and Lower Colorado 

River Basin tailwaters

Salaries $90,592

Traveling and Training $5,623

Operating Expenses $1,591

Logistics $21,218

GIS/RS/Electronics support $0

Cooperators (non-USGS) $49,650

USGS cooperators $0

USGS Burden $33,327

Total $202,001

FY 2017 Project Gross Total:

$510,404

Project Element 5.2, FY 2017

209
Project Element 5.3.1. Synthesis of 

algae production in Glen, Marble, 

and Grand Canyon

Project Element 5.3.2. 

Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon

Salaries $10,401 Salaries $10,155

Traveling and Training $0 Traveling and Training $1,000

Operating Expenses $0 Operating Expenses $2,000

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $13,500 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $2,010 USGS Burden $2,105

Total $25,912 Total $15,260

Project Element 5.3.3. Developing 

automated tools for estimating 

algae production FY 2015 Project Grand Total:

Salaries in kind $41,171

Traveling and Training in kind

Operating Expenses $0

Logistics $0

GIS/RS/Electronics support $0

Cooperators (non-USGS) $0

USGS cooperators $0

USGS Burden $0

Total $0

Project Element 5.3, FY 2015

Project Element 5.3.1. Synthesis of 

algae production in Glen, Marble, 

and Grand Canyon

Project Element 5.3.2. 

Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon

Salaries $10,505 Salaries $10,693

Traveling and Training $0 Traveling and Training $1,030

Operating Expenses $0 Operating Expenses $2,060

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $13,905 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $2,668 USGS Burden $3,032

Total $27,078 Total $16,815

Project Element 5.3.3. Developing 

automated tools for estimating 

algae production FY 2016 Project Gross Total:

Salaries in kind $43,893

Traveling and Training in kind

Operating Expenses $0

Logistics $0

GIS/RS/Electronics support $0

Cooperators (non-USGS) $0

USGS cooperators $0

USGS Burden $0

Total $0

FY 2016

210
Project Element 5.3.1. Synthesis of 

algae production in Glen, Marble, and 

Grand Canyon

Project Element 5.3.2. 

Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon

Salaries $10,610 Salaries $11,249

Traveling and Training $0 Traveling and Training $1,061

Operating Expenses $0 Operating Expenses $2,122

Logistics $0 Logistics $0

GIS/RS/Electronics support $0 GIS/RS/Electronics support $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0

USGS cooperators $0 USGS cooperators $0

USGS Burden $2,971 USGS Burden $4,041

Total $13,581 Total $18,473

Project Element 5.3.3. Developing 

automated tools for estimating algae 

production FY 2017 Project Gross Total:

Salaries in kind $32,054

Traveling and Training in kind

Operating Expenses $0

Logistics $0

GIS/RS/Electronics support $0

Cooperators (non-USGS) $0

USGS cooperators $0

USGS Burden $0

Total $0

FY 2017

211
Project 6. Mainstem Colorado River humpback chub 

aggregations and fish community dynamics 

A. Investigators 

William Persons, Fishery Biologist, USGS, Grand Canyon Monitoring and Research Center

Michael Dodrill, Fishery Biologist, USGS, Grand Canyon Monitoring and Research Center

David Ward, Fishery Biologist, USGS, Grand Canyon Monitoring and Research Center

Luke Avery, Fishery Biologist, USGS, Grand Canyon Monitoring and Research Center

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

David Van Haverbeke, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation 

Office

David Rogowski, Fishery Biologist, Arizona Game and Fish Department, Research Branch

Karin Limburg, Professor, State University of New York

B. Project Summary 

Native and nonnative fish populations in Glen and Grand Canyons are key resources of 

concern influencing decisions on both the operation of Glen Canyon Dam and non-flow actions. 

To inform these decisions, it is imperative that accurate and timely information on the status of 

fish populations, particularly the endangered humpback chub (Gila cypha), be available to 

managers. A suite of adaptive experimental management actions are either underway or being 

contemplated to better understand the mechanisms controlling the population dynamics of fish in 

the Colorado River in Glen and Grand Canyons and to identify policies that are consistent with 

the attainment of management goals. Much effort has been and continues to be focused on 

humpback chub and rainbow trout (Oncorhynchus mykiss) both in the reach of the Colorado 

River from Glen Canyon Dam to the Little Colorado River (LCR) confluence and in the LCR 

itself (see Projects 7 and 9). While this work is important and meets critical information needs, it 

is also important to have robust monitoring of mainstem fish populations downstream of the 

LCR confluence. Status and trend information is needed to further understand mechanisms 

controlling native and nonnative fish population dynamics, determine the effects of dam 

operations and other management actions, and identify evolving threats presented by expansion 

in range or numbers of nonnative predators. This type of information is also potentially useful in 

assessing changes to the Federal Endangered Species Act listing status of humpback chub in 

Grand Canyon.

Sampling mainstem humpback chub aggregations has been conducted periodically over the 

last two decades. Fish were sampled by hoop and trammel nets at aggregations first described by 

Valdez and Ryel (1995). Most captures of humpback chub in the mainstem Colorado River have 

been downstream of the LCR (Persons and Van Haverbeke, in prep.). Continuing to sample for 

humpback chub in the mainstem river outside of the LCR and the LCR confluence area is 

important for monitoring the status of the Grand Canyon population of this endangered species 

and determining the effects of management actions like dam operations and translocations.

During the last few years the first 75 miles of the Colorado River downstream of Glen 

Canyon Dam has been sampled extensively for fish by several projects including the following 

projects in the USGS Grand Canyon Monitoring and Research Center’s (GCMRC) FY11–12 and 

212
FY13-14 work plans: 

• E.2 Juvenile Chub Monitoring Project near the LCR confluence

Near Shore Ecology Project, BIO 2.R15.11 in FY11–12, and 

Project Element F.3 in FY13–14,

• H.2 Rainbow Trout Movement Project, a.k.a. the Rainbow Trout Natal Origins 

Project

Project Element BIO 2.E18 in FY11–12, and 

Project Element F.6 in FY13–14,

• D.4 System Wide Electrofishing Project 

Project Element BIO 2.M4 in FY11–12, and 

Project Element F.1 in FY13–14

• H.1 Lees Ferry Trout Monitoring Project

Project Element BIO 4.M2 in FY11–12, and 

Project Element F.2 in FY13–14

• D.7 Rainbow Trout Early Life Stage Survey Project, RTELSS

Project Element BIO 4.M2 in FY11–12, and 

Project Element F.2.2 in FY13–14

The remaining portion of the Colorado River downstream of Glen Canyon Dam (between 

approximately the LCR and Lake Mead) has been sampled using standardized methods since 

2000 as described in Project 6.4, the System Wide Electrofishing Project and since 2010 as 

described in Project 6.1, the Mainstem Humpback Chub Aggregation Monitoring Project. In 

order to improve efficiencies and to reduce duplication of effort, GCMRC and cooperating 

agencies conducting fisheries monitoring and research propose to coordinate and/or combine 

several project elements in GCRMC’s FY15-17 work plan. These include the Juvenile Chub 

Monitoring project and System Wide Electrofishing effort (see Project Elements 7.2 and 6.4) as 

well as the Rainbow Trout Natal Origins study and Lees Ferry Trout Monitoring (see Project 

Elements 9.1 and 9.2). In general, this will mean a reduction of electrofishing effort in the first 

70 miles of the Colorado River downstream of Glen Canyon Dam and a focus on obtaining 

abundance estimates rather than catch per unit effort (CPUE) indices through the updated Lees 

Ferry Rainbow Trout Monitoring project (see Project Elements 9.1 and 9.2). Systematic 

sampling of the mainstem Colorado River downstream of the Juvenile Chub Monitoring (see 

Project Element 7.2) reference site (River Mile (RM) 63-64.5) will continue under Project 

Elements 6.1, 6.2, and 6.4 (see Section 4) and will continue to collect and analyze species 

composition and CPUE data. 

Project 6 is comprised of eight Project Elements and includes monitoring and research 

projects in the mainstem Colorado River, with particular emphasis on humpback chub 

aggregations. Over the last several years humpback chub in the LCR aggregation have increased 

in abundance (Coggins and Walters, 2009; Van Haverbeke and others, 2013; Yackulic and 

others, 2014). Humpback chub at many other aggregations have also increased in abundance, and 

some aggregations appear to have increased their distribution (Persons and Van Haverbeke, in 

prep.). Recruitment to aggregations may come from local reproduction (e.g. 30 Mile 

aggregation; Andersen and others, 2010; Middle Granite Gorge Aggregation; Douglas and 

Douglas, 2007), the LCR aggregation, and translocations to Shinumo and Havasu Creeks. 

Annual monitoring of the status and trends of the mainstem humpback chub aggregations has 

213
been identified as a conservation measure in a recent Biological Opinion (U.S. Fish and Wildlife 

Service, 2011) and will continue to be monitored in Project Element 6.1, although effort will be 

reduced to a single trip per year down from two trips annually in the FY13–14 work plan. We 

will also continue to sample in conjunction with the National Park Service (NPS) near Shinumo 

Creek and Havasu Creek to assess contribution of translocated humpback chub to mainstem 

aggregations. 

Understanding recruitment at aggregations continues to be an area of uncertainty. Humpback 

chub otolith microchemistry (Hayden and others, 2012; Limburg and others, 2013) was proposed 

as a method to determine sources of humpback chub recruitment in the FY13–14 Work Plan.

However, due to Tribal concerns about directed take of humpback chub we were unable to 

collect the otoliths necessary for these analyses. During FY15–16 we plan to further evaluate the 

use of otolith microchemistry to identify surrogate fish hatched in Shinumo Creek, Havasu 

Creek, 30-Mile springs or other locations in Project Element 6.2. We will work with NPS staff to 

collect water samples and otoliths from brown trout (Salmo trutta), rainbow trout, and other 

fishes sacrificed as part of their trout removal activities. We will also make use of any humpback 

chub incidentally killed during other sampling efforts. Further, we will place additional emphasis 

on catching and marking juvenile humpback chub to assist in determining sources of recruitment 

to aggregations. During FY15–16 we propose to evaluate slow shocking and seining as methods 

to capture and mark more juvenile humpback chub with passive integrated transponder (PIT) 

tags in order to assess juvenile humpback chub survival and recruitment to aggregations. This 

will also provide a possible method to assess dispersal of juvenile humpback chub marked in the 

LCR with visible implant elastomer (VIE) and PIT tags (see Project Element 7.3).

Project Element 6.3 will continue efforts that began in the FY13–14 work plan to locate 

additional aggregations by standardized sampling and by the use of remotely deployed PIT-tag 

antennas. GCMRC has had success in deploying relatively portable PIT-tag antennas in the LCR 

and proposes to work with NPS and U.S. Fish and Wildlife Service (USFWS) personnel to 

develop antenna systems that can be deployed at mainstem aggregations and other locations to 

detect PIT-tagged fish. If successful, these systems will provide an opportunity for collaborative 

citizen science with commercial and scientific river trips whereby river guides could deploy 

antennas overnight at camp sites in an attempt to detect PIT-tagged fish in areas not sampled 

during mainstem fish monitoring trips. 

The System Wide Electrofishing Project (Project Element 6.4) will continue to collect longterm monitoring data following the methods described in Makinster and others, (2010) and will 

evaluate the efficacy of a mark-recapture approach downstream of the LCR confluence. To 

eliminate duplicative efforts, we propose that sampling be conducted in areas not sampled by the 

Rainbow Trout Natal Origins and the Juvenile Chub Monitoring projects (Project Elements 7.2

and 9.2). We will also increase sampling effort downstream of Diamond Creek to monitor for 

native and non-native fishes. Continued concerns over upstream movement of non-native 

warmwater predatory species such as striped bass (Morone saxatilis), largemouth bass 

(Micropterus salmoides), channel catfish (Ictalurus punctatus) and walleye (Sander vitreus) 

from Lake Mead highlight the need to continue to monitor the river for non-native fishes. 

Electrofishing is effective at capturing bass species, sunfishes (Centrarchidae), and walleye, so 

this sampling should detect upstream movements of these species. Channel catfish on the other 

hand, are not effectively captured by electrofishing, so monitoring of catfish distribution by 

standardized angling (Persons and others, 2013) will continue during electrofishing trips.

Standardized electrofishing sampling is also effective at capturing native sucker species 

including flannelmouth sucker (Catostomus latipinnis), bluehead sucker (Catostomus 

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discobolus), and razorback sucker (Xyrauchen texanus). Recent captures of razorback sucker 

downstream of Diamond Creek by this project have been widely publicized and ongoing 

monitoring will help document if this once extirpated species continues its apparent recolonization of Grand Canyon.

Nonnative brown trout are effective fish predators known to preferentially prey on native 

Colorado River fishes including humpback chub (Yard and others, 2011). Determining the 

source or sources of this species in Grand Canyon will help scientists and managers better target 

efforts aimed at controlling this threat to native fish populations (see Project Element 8.1). 

Project Element 6.5 will conduct research on the use of brown trout pigment patterns to identify 

natal origins of brown trout; data and images will be collected during the System Wide 

Electrofishing Project and other projects that encounter brown trout.

One risk to the Grand Canyon humpback chub population is that it includes only one selfsustaining spawning population, the LCR aggregation. The USFWS has identified the 

establishment of a second self-sustaining spawning population of humpback chub as an 

important step towards recovery of this endangered species (U.S. Fish and Wildlife Service 

1995). Project Element 6.6 will develop plans and conduct necessary compliance activities to 

experimentally translocate humpback chub from the LCR to a mainstem aggregation in 2016 or 

later.

The Rainbow Trout Early Life Stage Survey (Project Element 6.7 - RTELLS) seasonally 

monitors rainbow trout egg deposition and population early life history dynamics, particularly

age-0 survival in Glen Canyon. This project in particular, provides managers with an initial 

indication of the annual cohort strength of rainbow trout recruiting into the population. Findings 

from this also have relevance to the Natal Origin research project (see Project Element 9.2). 

The Lees Ferry Creel Survey (Project Element 6.8) monitors the health of the rainbow trout 

fishery and provides information on the influence of Glen Canyon Dam operations, other 

management actions, and natural disturbances on recreational fishing. Information on the levels 

of direct harvest as well as angler use and satisfaction of the important recreational fishery is also 

provided. 

C. Background 

C.1 Scientific Background 

Currently, the only known reproducing and self-sustaining population of humpback chub 

within Grand Canyon is in the LCR and in the mainstem Colorado River near its confluence with 

the LCR (Valdez and Ryel, 1995; Gloss and Coggins, 2005; Coggins and others, 2006). Because 

these fish appear to rely exclusively on the LCR for reproduction, they are at increased risk of 

catastrophic loss (U.S. Fish and Wildlife Service, 2008; Bureau of Reclamation, 2011).

Eight other aggregations of humpback chub were described in the mainstem Colorado River 

(Valdez and Ryel, 1995), and closed population model abundance estimates were generated for 

six of those aggregations An aggregation was defined as “a consistent and disjunct group of fish 

with no significant exchange of individuals with other aggregations, as indicated by recapture of 

PIT-tagged juveniles and adults and movement of radio-tagged adults” (Valdez and Ryel, 1995). 

Recent data collected at aggregations and throughout the Colorado River, suggest that there is 

substantial movement among some of the originally identified aggregations, and they may not all 

meet the original definition of an aggregation. 

The LCR aggregation of humpback chub has been studied extensively, (Van Haverbeke and 

others, 2013; Yackulic and others, 2014) and models have been developed to estimate abundance 

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of chub in the LCR and near the confluence of the Colorado River (Coggins and Walters, 2009; 

Yackulic and others, 2014). Results from these efforts demonstrate that humpback chub 

abundance in the LCR aggregation has increased over the last several years (Coggins and 

Walters, 2009; Van Haverbeke and others, 2013; Yackulic and others, 2014). An understanding 

of the status and trends of humpback chub outside of the LCR population is needed for managers 

to assess the effects of Glen Canyon Dam operations on mainstem populations of humpback 

chub. Recent findings suggest that humpback chub relative abundance has increased at most 

locations since the 1990’s and some aggregations appear to have increased their distribution 

(Persons and Van Haverbeke, in prep.). Recruitment to aggregations may come from local 

reproduction (e.g., 30 Mile aggregation; Andersen and others, 2010; Middle Granite Gorge 

Aggregation; Douglas and Douglas, 2007), the LCR aggregation, and translocations to Shinumo 

and Havasu Creeks. Recent evidence indicates that female humpback chub are capable of 

producing eggs at most aggregations (M. Brizendine, GCMRC Annual Reporting Meeting 2014 

poster). In addition, catches of humpback chub that were translocated to Shinumo and Havasu 

Creeks are common in catches near the confluences of these two tributaries (Persons and Van 

Haverbeke, in prep). 

Valdez and Ryel (1997) were able to generate closed abundance estimates of humpback chub 

at several aggregations by sampling up to 7 times per year. The amount of sampling required to 

generate similar abundance estimates raises serious concerns about over-handling these rare fish. 

From a conservation standpoint, it may be more hazardous to extensively sample this endangered 

species in order to generate abundance estimates than it is to monitor trends over time using 

CPUE indices.

Attempts were made to estimate humpback chub abundance at known aggregations during 

2012 and 2013 using pooled capture probability estimates derived from closed mark-recapture 

population estimates. This approach and these estimates were deemed not valid during peer 

review. In addition, attempts to generate two-pass mark-recapture population estimates at the 

Shinumo Creek aggregation during 2012 by combining NPS sampling and USFWS/GCMRC 

sampling were unsuccessful because capture probabilities appeared to change dramatically 

between the first capture event and subsequent attempts to recapture fish within a few days. 

Results suggest fish were evidently very trap-shy after their initial capture.

We propose to continue use of CPUE indices to evaluate trends in relative abundance of 

humpback chub at known aggregations as well as at locations not associated with aggregations 

(Persons and Van Haverbeke, in prep.). Although CPUE indices have a high degree of 

uncertainty, trends in these indices over 4–5 year time periods are likely reflective of relative 

abundance of humpback chub in the mainstem Colorado River. Use of CPUE indices to evaluate 

changes in abundance over annual time periods is not proposed due to the high variability in 

capture probabilities (the probability of capturing an individual fish) among trips. 

Long-term fish monitoring in the mainstem Colorado River has been an essential element of 

GCDAMP supported fisheries work. Data from this program provides managers and 

stakeholders with accurate and timely information on the status and trends of fish populations in 

Grand Canyon in support of their efforts manage Glen Canyon Dam operations and other nonflow actions in a manner beneficial to the aquatic ecosystem. The annual System Wide 

Electrofishing (SWEF) of native and nonnative fish in the mainstem Colorado River has been 

ongoing since 2000 (Makinster and others, 2010). These efforts rely upon boat-operated 

electrofishing to provide information on native and nonnative fishes between Lees Ferry and 

Lake Mead. Information generated includes population status and trends and species 

distributions as well as surveillance for undesirable or potentially harmful nonnative species.

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C.2. Key Monitoring and Research Questions Addressed in this project 

This project directly addresses the following Strategic Science Questions (SSQs), Core 

Monitoring Information Needs (CMINs), and Research Information Needs (RINs) previously 

identified by the Glen Canyon Dam Adaptive Management Program (GCDAMP).

Primary SSQ addressed:

• SSQ 1-1. To what extent are adult populations of native fish controlled by production of 

young fish from tributaries, spawning and incubation in the mainstem, survival of youngof-year and juvenile stages in the mainstem, or by changes in growth and maturation in 

the adult population as influenced by mainstem conditions?

• SSQ 1-2. Does a decrease in the abundance of rainbow trout and other cold- and warm 

water nonnatives in Marble and eastern Grand Canyons result in an improvement in the 

recruitment rate of juvenile humpback chub to the adult population?

• SSQ 1-8. How can native and nonnative fishes best be monitored while minimizing 

impacts from capture and handling or sampling?

The GCDAMP Science Advisors articulated the following summary science questions addressed 

by this project:

• SA 1. What are the most limiting factors to successful humpback chub adult recruitment 

in the mainstem: spawning success, predation on young of year and juveniles, habitat 

(water, temperature), pathogens, adult maturation, food availability, competition?

• SA 2. What are the most probably positive and negative impacts of warming the 

Colorado River on humpback chub adults and juveniles?

Information Needs Addressed

• CMIN 2.1.2. Determine and track recruitment of all life stages, abundance, and 

distribution of humpback chub in the Colorado River.

• CMIN 2.4.1. Determine and track the abundance and distribution of nonnative predatory 

fish species in the Colorado River.

• CMIN 2.6.1. Determine and track the abundance and distribution of flannelmouth 

sucker, bluehead sucker, and speckled dace populations in the Colorado River ecosystem.

• RIN 2.2.8. What combination of dam release patterns and nonnative fish control 

facilitates successful spawning and recruitment of humpback chub in the Colorado River 

ecosystem?

• RIN 2.4.2. Determine if suppression of nonnative predators and competitors increases 

native fish populations. 

• RIN 2.4.3. To what degree, which species, and where in the system are exotic fish a 

detriment to the existence of native fish through predation or competition?

• RIN 2.4.4. What are the target population levels, body size, and age structure for 

nonnative fish in the Colorado River ecosystem that limit their levels to those 

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commensurate with the viability of native fish populations?

• RIN 4.2.2. What is the most effective method to detect emigration of rainbow trout from 

the Lees Ferry reach?

• EIN 2.1.1. How does the abundance and distribution of all size classes of HBC in the 

LCR and mainstem change in response to an experiment performed under the Record of 

Decision, unanticipated event, or other management action?

• EIN 2.1.2. How does the year class strength of HBC (51–150 mm) in the LCR and 

mainstem change in response to an experiment performed under the Record of Decision, 

unanticipated event, or other management action?

• EIN 2.4.1. How does the abundance and distribution of nonnative predatory fish species 

and their impacts on native fish species in the Colorado River ecosystem change in 

response to an experiment performed under the Record of Decision, unanticipated event, 

or other management action?

• EIN 2.6.1 How does the abundance, distribution, recruitment and mortality of 

flannelmouth sucker, bluehead sucker and speckled dace populations in the Colorado 

River ecosystem change in response to an experiment performed under the Record of 

Decision, unanticipated event, or other management action?

• CMIN 4.1.2. Determine annual proportional stock density of rainbow trout in the 

Lees Ferry reach.

C.3. Key management goals and objectives addressed in this project 

• Goal 2: Maintain or attain a viable population of existing native fish, remove 

jeopardy for humpback chub and razorback sucker, and prevent adverse modification 

to their critical habitats.

In August 2004, the GCDAMP Adaptive Management Work Group reviewed these goals and 

identified priority questions. This project addresses the top priority question:

• Priority 1: Why are humpback chub not thriving, and what can we do about it? How 

many humpback chub are there and how are they doing? 

D. Proposed Work 

D.1. Project Elements 

Project elements include sampling humpback chub aggregations, investigating recruitment at 

aggregations, investigating the use of PIT-tag antennas at aggregations, system wide monitoring 

of native and non-native fishes outside of Glen and Marble Canyons, investigating brown trout 

origins through examining their pigment patterns, investigating the translocation of humpback 

chub to the mainstem Colorado River, and investigating the use of portable PIT tag antennas to 

detect tagged humpback chub and other fishes

 

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Project Element 6.1. Monitoring humpback chub aggregation relative abundance and distribution 

(Recommended for funding FY15: $218,768)

William Persons, Fishery Biologist, USGS/GCMRC

D.R. Van Haverbeke, Fishery Biologist, U.S. Fish and Wildlife Service

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

This Project Element will concentrate on monitoring status and trends of humpback chub 

aggregations not associated with the LCR. This Project Element will build on work conducted in 

2013 and 2014. Persons and Van Haverbeke (in prep) have been able to detect long term changes 

in relative abundances by pooling data into 5-year blocks, but were unable to provide defensible 

annual abundance estimates from the aggregations (Persons and Van Haverbeke, GCMRC 

Annual Reporting Meeting, 2014). Sampling will be reduced from two trips to one trip, but will 

include sampling by seine and nearshore electrofishing which has been effective capturing 

juvenile humpback chub near the LCR confluence (J. Korman, pers. comm.). While sampling 

trips will concentrate on known aggregations and translocation sites, several days of effort will 

also be devoted to sampling areas associated with springs and faults thought likely to harbor 

humpback chub. 

The project will produce annual progress reports and one peer reviewed publication at project 

completion.

Project Element 6.2. Humpback chub aggregation recruitment studies 

(Recommended for funding FY15: $83,750)

Michael Dodrill, USGS/GCMRC

Karin Limburg, State University of New York

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

Recent apparent increases in relative abundance of humpback chub at mainstem aggregations 

(Persons and Van Haverbeke, in prep.) suggest that local recruitment may be occurring at some 

sites. While it is known that the LCR serves as a source of humpback chub into the mainstem 

Colorado River and that some of these fish move downstream and survive, there may be other 

areas with local reproduction that act as sources of recruitment (Andersen and others, 2010). 

Although we will not deliberately sacrifice humpback chub to collect otoliths for microchemistry 

analysis, we will work with NPS to collect surrogate species from tributaries of interest and 

analyze samples for unique chemical signatures that might be associated with particular 

tributaries. We will continue to work with all projects to collect and preserve any humpback 

chub incidentally killed during sampling. 

This Project Element will also attempt to collect juvenile humpback chub in backwaters and 

other nearshore areas by seining and electrofishing. Fish will be examined closely for VIE tags 

(see Project Element 7.3) and PIT tags to evaluate possible sources of recruitment. The project 

will also acquire and explore the use of a thermal imaging infrared camera to help identify 

sampling locations at warm springs in the mainstem. 

The project will produce annual progress reports and one peer reviewed publication at project 

completion.

 

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Project Element 6.3. Monitoring mainstem humpback chub aggregations using PIT-tag antenna technology 

(Recommended for funding FY15: $18,444)

Kirk Young, Fishery Biologist, U.S. Fish and Wildlife Service

D.R. Van Haverbeke, Fishery Biologist, U.S. Fish and Wildlife Service

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

David Ward, Fishery Biologist, USGS/GCMRC

William Persons, Fishery Biologist, USGS/GCMRC

The objective of this project is to investigate use of remotely deployed, portable PIT-tag 

antennas to monitor mainstem aggregations of humpback chub, especially at mainstem 

translocation sites. Two long standing goals of biologists monitoring humpback chub in Grand 

Canyon are to develop indices to monitor the abundance or relative abundance of humpback 

chub, and to reduce handling of fish. This project will evaluate use of stationary, temporary PITtag antennas to detect humpback chub and other PIT-tagged fish in the mainstem Colorado 

River. Deployment of antennas at known aggregations may also help answer questions about 

residencies of humpback chub within and among aggregations, potential gene flow among the 

aggregations, and movement. It is believed that given strategic placement of antennas at sites 

such as near Shinumo Creek, we may be able to increase the detection rates of tagged fish, and 

possibly decrease the amount of trammel netting or hoop netting. In addition, remote antennas 

could be deployed near future translocation sites in the mainstem. If proven feasible, similar 

technology might also be used in a Citizen Science approach working with commercial and 

science river guides to deploy PIT-tag antennas at overnight campsites.

Investigators and involved agencies will coordinate selection of appropriate locations, obtain 

environmental clearances, coordinate with tribes and install up to three experimental remote 

solar powered PIT-tag antennas at known aggregations. Site location, materials, and temporary 

installation strategies will be deployed so as to minimize visual impact and Grand Canyon visitor 

detection. Possible sites include near aggregations at 30-Mile, the Shinumo Creek Inflow, 

Middle Granite Gorge, the Havasu Creek Inflow, or near RM 214. Sites for antennas would be 

located at aggregations that have historically yielded a high number of chub. The ability to keep 

antennae equipment safe and out of view of the public would also be a factor in site selection. 

Antennas will be downloaded and serviced from existing GCMRC river trips and data will be 

evaluated for incorporation into the GCRMC fish database. The project will produce annual 

progress reports and recommendations for use of the methods and data as part of long-term 

monitoring efforts.

Project Element 6.4. System Wide Electrofishing 

(Recommended for funding FY15: $283,722)

David Rogowski, Fishery Biologist, Arizona Game and Fish Department

William Persons, Fishery Biologist, USGS/GCMRC

The primary objective of this project element is to continue providing data on the 

longitudinal distribution and status of the fish community in the mainstem Colorado River from 

Lees Ferry to Lake Mead, with an emphasis on reaches downstream of Lava-Chuar rapid (RM 

66.0). This project uses CPUE indices to track relative status and trends of the most common 

native and nonnative fish species in the mainstem. The current monitoring program was designed 

to be able to detect population level changes in target species over a five-year time scale. 

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Localized questions or questions on a time scale shorter than five years require additional, 

separate effort beyond that outlined for long-term monitoring (Rogers and others, 2008). Given 

this, we propose to incorporate mark-recapture sampling events to estimate fish abundance and 

vital rates at specific sites (e.g., confluence of Bright Angel Creek, reaches downstream of 

Diamond Creek) to evaluate the ability of this approach to address questions of interest to 

scientists and managers.

Sampling for the SWEF project in FY2013-14 consisted of two annual spring 

electrofishing trips from Lees Ferry to Diamond Creek and one fall trip from Diamond Creek to 

Lake Mead. For the FY15-17 workplan, we propose to increase sampling effort by extending one 

spring trip to include sampling from Diamond Creek to Lake Mead. This will extend the 

temporal and geographic scope of available information on nonnative and native fish in this 

reach of the Colorado River. In order to avoid duplication of effort with the Natal Origins 

research project (Project Element 9.2), we propose to coordinate sample site selection such that 

these projects avoid sampling in the same reaches. Stratified random sampling will occur in 

Marble Canyon, but at a reduced effort and may occur in directed areas of interest not sampled 

by the Natal Origins research project (e.g., near the confluence of Nankoweap Creek). To avoid 

oversampling and duplication of effort, sampling will not occur in the Juvenile Chub Monitoring 

(see Project Element 7.2) reference site (RM 63-64.5). Normal random stratified sampling will 

occur from Lava-Chuar rapid (RM 66.0) to Lake Mead and will provide information on species 

composition and relative abundance. 

Difficulties arise in fish monitoring programs as a result of the rarity of many species, life 

history characteristics that contribute to patchy distributions and variable densities in time and 

space, low and variable capture probabilities, and the inability to use consistent sampling gear 

among all occupied habitats. With the exception of mark-recapture based abundance estimators, 

most fish monitoring efforts produce relative indices of abundance (e.g., catch rates, 

presence/absence) for monitoring the status and trend of a fish community. Yet, in order for 

catch rates (i.e., CPUE) to be effective as a short term monitoring metric, capture probabilities 

(probability of an animal being caught) need to be known rather than just assumed to be constant 

across sites or sampling periods. When capture probabilities vary due to factors like trout 

densities, fish size or turbidity levels (Korman and others, 2009; Korman and others, unpublished 

data; Speas and others, 2004), catch rate indices can become an inaccurate proxy for fish 

abundance. Factors like these are a common phenomenon in Grand Canyon that leads to 

estimation biases in fish abundance. For example, catch rates are likely to underestimate actual 

abundance at high trout densities (i.e., Glen Canyon) and overestimate actual abundance under 

low trout densities (i.e., below the LCR). Therefore, reliance on this type of metric solely 

becomes problematic, particularly when management decisions require a high degree of 

accuracy. This can only be resolved if capture probabilities are estimated using mark-recapture 

procedures, hence our interest in implementing this approach at selected sites to address specific 

questions. 

For FY15-17, we propose a hybrid approach be evaluated for this project; one that maintains 

continuity with past SWEF sampling, but also evaluates the applicability of using a markrecapture program (where increased accuracy and precision are needed), particularly in the 

downstream reaches. One downstream sampling trip and part of the second will use the standard 

SWEF sampling (single-pass) protocol with a stratified random sampling design used in site 

selection (400-500 sites per year) (similar to Makinster and others, 2010). The second 

downstream sampling trip will also incorporate one or more focused mark-recapture efforts using 

similar sampling protocols developed for the Natal Origin research project (Korman and others, 

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2012) at specific areas of interest (e.g., confluence of Bright Angel Creek, reaches downstream 

of Diamond Creek). This may require lengthening the duration of the second trip by several days 

to implement both sampling protocols. Data from initial efforts will be used in conjunction with 

other mark-recapture and CPUE data to develop a set of estimation procedures for conducting 

simulations to evaluate and redesign the GCDAMP’s long-term fishery monitoring programs 

inclusive of the System Wide Electrofishing program. The redesigned program will be evaluated 

by an independent protocol evaluation panel (see Project Element 8.3). Sampling efforts as part 

of the System Wide Electrofishing program will continue sampling the downstream sections 

including below Diamond Creek. Three trips will be conducted annually during late April-May, 

late May-June, and October (Diamond Creek to Pearce Ferry) to increase the probability that 

maximum water clarity conditions are present for electrofishing, particularly in the downstream 

reaches.

This project will produce trip and annual reports with recommendations for long-term 

monitoring.

Project Element 6.5. Brown trout natal origins through body pigmentation patterns in the Colorado River 

(Unfunded, Moderate Priority FY15: $16,146)

David Rogowski, Fishery Biologist, Arizona Game and Fish Department, Research Branch

Michael Collyer, Assistant Professor, Western Kentucky University

William Persons, Fishery Biologist, USGS/GCMRC

Non-native brown trout have been introduced into the Colorado River and tributaries and are 

maintaining a naturally reproducing population. Brown trout are highly piscivorous and 

negatively affect the imperiled native fishes of the Colorado River drainage (Yard and others, 

2011). Much effort has been invested in control and removal of brown trout and other nonnatives (Coggins and others, 2011; Yard and others, 2011). It is thought that the bulk of 

reproduction and recruitment occurs in the tributaries (e.g., Bright Angel Creek). However, it is 

not known whether Bright Angel Creek is the main source of brown trout into the system, if 

there are other major recruitment areas (mainstem or tributaries), or even if there is a large 

panmictic population or a number of smaller populations. For salmonids there appears to be a 

heritable basis for coloration as well as a phenotypic response based on environment. It is 

thought that background color is based on environment (Westley and others, 2013), while 

spotting characteristics have a heritable basis (Blanc and others, 1982; 1994; Skaala and Jørstad, 

1988; Skaala and others, 1992). It has been shown that one can discriminate between native and 

hatchery brown trout as well as hybrids based on the number and shape of parr marks (Blanc and 

others, 1982; Mezzera and others, 1997). One can also discriminate different strains of brown 

trout based on coloration and spotting patterns (Aparico and others, 2005). Thus it might be 

possible to determine if brown trout within the Colorado River system are one panmictic 

population or comprised of various metapopulations based on differing phenotypic 

characteristics.

We propose to quantify the colorations and spotting patterns of brown trout at various 

locations within the Colorado River and tributaries between Glen Canyon Dam and Lake Mead. 

Digital images of fish will be taken with a Munsell color chart and a scale. The shape, color, size, 

number, and location of spots (and parr marks for juvenile fish) will be quantified using a digital 

imaging program (e.g., ImageJ, tpsDIG2).

This project will produce annual progress reports and one peer reviewed publication at 

project completion.

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Project Element 6.6. Mainstem translocation of humpback chub 

(Recommended for funding FY15: $9,790)

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

D. Van Haverbeke, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

David Ward, USGS, GCMRC

William Persons, Fishery Biologist, USGS, GCMRC

A long standing goal of managers has been establishing a second spawning population of 

humpback chub in Grand Canyon. The USFWS issued a Biological Opinion (U.S. Fish and 

Wildlife Service, 1995) concerning the preferred Modified Low Fluctuating Flow alternative on 

the Operation of Glen Canyon Dam EIS (U.S. Department of the Interior, 1995), whereby one 

element of the reasonable and prudent alternative (RPA) was to “Make every effort to establish a 

second spawning aggregation of humpback chub downstream of Glen Canyon Dam.” To address 

this RPA, Valdez and others, (2000) produced a research and implementation plan for 

establishing a second spawning population of humpback chub in Grand Canyon. The conclusions 

in Valdez and others, (2000) were: 1) the highest chance for success of establishing a viable 

mainstem spawning population for humpback chub would be in the mainstem itself, and 2) 

experimental translocations into side tributaries should be conducted. The second 

recommendation of Valdez and others (2000) has been implemented with promising success at 

Shinumo and Havasu Creeks. This project would attempt to more directly address the first 

recommendation of Valdez and others, (2000).

Humpback chub have been successfully translocated into Shinumo and Havasu Creeks, and 

emigrants from these tributaries have augmented their respective mainstem aggregations 

(Persons and Van Haverbeke, in prep). These translocations are thought to have been successful 

in augmenting mainstem aggregations in part because the tributaries provide suitable rearing 

habitat for juveniles before some emigrate into the mainstem. Many translocated humpback chub 

that have emigrated from Shinumo and Havasu Creeks and were subsequently captured in the 

mainstem have been sub adults (<200 mm), suggesting that direct augmentation of small 

humpback chub into the mainstem may be feasible. This approach could be an avenue to 

augment aggregations or other groups of humpback chub not located near tributaries.

Approximately 250 juvenile (<100 mm) or larval humpback chub will be collected annually 

from the LCR as part of Project Element 7.1. Fish will be transported out of the LCR by 

helicopter and then transported to Southwestern Native Aquatic Resources and Recovery Center 

(SNARRC) along with humpback chub designated for Shinumo and Havasu Creeks. Once at 

SNARRC, fish will undergo quarantine procedures and will be reared for a year until reaching 

~150 mm TL. Fish will be PIT tagged, and transported back to Grand Canyon. They will then be 

transported either by boat or by helicopter to a release site. The eventual release site will be 

decided upon by management agencies, with input from cooperators. One possible location 

would be within, or adjacent to, the Pumpkin Spring aggregation. This area may be favorable for 

humpback chub rearing due to the presence of springs, several large eddy complexes, at least one 

large backwater, a large cove, several gravel producing debris fan inflows, and relatively warm 

water. 

Fish will be tempered and soft released in large eddy complexes, backwaters or slow current 

areas. Release of fish would likely occur in September or possibly earlier if it is possible to grow 

chub to a sufficient size at SNAARC. Annual monitoring would occur during mainstem 

aggregation trips. Additional monitoring could be possible if release occurs near the Pumpkin 

223
Spring aggregation, and upriver access was granted from Diamond Creek. The project will 

produce annual progress reports and one peer reviewed publication at project completion.

Project Element 6.7 Rainbow Trout Early Life Stage Survey 

(Recommended for funding FY15: $77,024)

Luke Avery, Fishery Biologist, USGS, GCMRC

G. Dave Foster, Logistic Support, USGS, GCMRC

The objective of the RTELSS study is to monitor the response of the age-0 population of 

rainbow trout in Lees Ferry to variations in Glen Canyon Dam operations and to naturally 

occurring disturbances to the CRe in Glen Canyon. 

Understanding of the effects of various physical and biological conditions on the age-0 

rainbow trout population will enable better management practices to attain desired rainbow trout 

abundance and population structure. Monitoring of the age-0 population also provides early 

indication of potential changes to the juvenile and adult rainbow trout population, providing the 

potential for early response to undesirable conditions. This monitoring will answer the following 

questions: 1) how do changes in the conditions (e.g., bed texture, flow, aquatic vegetation, and 

sediment supply) of the Colorado River in Glen Canyon effect the age-0 population of rainbow 

trout? 2) How can dam operations be experimentally evaluated to determine whether or not they 

might be used to manage the rainbow trout population via influences on the young-of-the-year 

population?

The RTELSS program was initiated in January 2003 to monitor the effects of the 

nonnative fish suppression flows (NFSF) that occurred during January through March from 

2003–2005 (Korman and others, 2005). Since then it has provided information on the response of 

the age-0 rainbow trout population to higher flow dam releases that have occurred in March 

through June 2008, and falls of 2011, 2012, and 2013, as well as the response to the equalization 

flows that occurred in spring through fall 2011. An understanding of the response of the age-0 

rainbow trout population to these flow events has provided a more mechanistic understanding of 

correlated changes that have occurred in the adult rainbow trout population and downstream 

emigration events that have been associated with some of those changes (Korman and others, 

2012, Makinster and others, 2011, Melis and others, 2012). Maintaining the RTELSS as a 

monitoring program ensures sufficient data will be available to detect a response of the age-0 

rainbow trout population to changes in the CRe within Glen Canyon, whether those changes in 

the system be by scientific design or not. Understanding of the response of age-0 rainbow trout 

to various conditions and events may enable management to better maintain the balance between 

a blue ribbon rainbow trout fishery and the welfare of the endangered native humpback chub.

The RTELSS program monitors egg deposition in winter and early spring and proceeds 

with monitoring of population dynamics through summer, fall, and early winter. Monitoring of 

egg deposition consists of 9-10 redd surveys conducted from December through May. Data 

collected provides information on the timing and magnitude of the spawn that provides the 

foundation for the year’s cohort of fish. Larval and juvenile fish sampling (backpack and boat 

electrofishing) trips occur once a month in June-September and November. Data collected 

provides information on hatch success and early survival, as well as survival through the year. 

Otoliths extracted from specimens collected across trips provide information on growth and 

hatch distribution. Survey, sampling, and data analysis details can be found in in Korman and 

others (2009), and Korman and others (2011).

224
Project Element 6.8. Lees Ferry Creel Survey 

(Unfunded, High Priority FY15: $0)

David Rogowski, Fishery Biologist, AGFD

William Persons, Fishery Biologist, USGS, GCMRC

The objective of this project element is to evaluate how changes in the conditions of the 

Colorado River in Glen Canyon affect angler effort, catch and harvest on an annual basis

The blue ribbon rainbow trout fishery of Lees Ferry has been identified as a key resource of 

the Colorado River in Glen Canyon under the purview of the Glen Canyon Dam Adaptive 

Management Program (GCDAMP) and so must be maintained. The Lees Ferry trout fishery is 

located in the tailwater portion of the Colorado River ecosystem from Glen Canyon Dam to the 

Paria River. The status and trends of the fishery are regulated by biotic and abiotic mechanisms 

that may in turn be affected by the operations of Glen Canyon Dam. 

Creel surveys are an effective tool to monitor a variety of metrics such as: the impact of 

recreational fishing on the fishery (harvest rates), angler use (indirect measure of economic 

impact), and angler satisfaction (Malvestuto 1996). Creel surveys are also an effective way to 

maintain an active presence with the fishing public, provide needed outreach, as well as feedback 

and observations about the fishery from the public. Anglers are often the first to notice changes 

in fish health or invasive species. Angler creel surveys will be conducted to estimate angler 

effort, catch and harvest. Monitoring basic angler statistics including angler usage (anglers/year), 

catch-per-unit-effort, and harvest rates provide information necessary to assess the status of these 

resources and inform the Adaptive Management Program.

D.2 Personnel and Collaborations 

The overall lead for Project 6 is William Persons a fishery biologist with U.S. Geological 

Survey, Grand Canyon Monitoring and Research Center (GCMRC). Kirk Young and David Van 

Haverbeke are fishery biologists with the U.S. Fish and Wildlife Service with extensive 

humpback chub experience and will lead the humpback chub aggregation project (6.1). Brian 

Healy is a fishery biologist with Grand Canyon National Park with expertise in humpback chub 

translocations and humpback chub aggregations at Shinumo and Havasu Creeks. Mr. Healy will 

assist with humpback chub aggregation studies (6.1 and 6.2), the PIT tag antenna project (6.3) 

and mainstem translocation of humpback chub (6.6). Dr. Karin Limburg is a professor at State 

University of New York who specializes in otolith microchemistry and will be the lead for the 

humpback chub recruitment project (6.2). Michael Dodrill is a fishery biologist with GCMRC 

with extensive experience sampling for young-of-the-year humpback chub and will assist with 

the humpback chub recruitment project (6.2). David Ward is a fishery biologist with GCMRC 

that maintains and operates the GCMRC experimental laboratory facility at Northern Arizona 

University. He will provide expertise in sampling young-of-the-year humpback chub (6.2) the 

PIT tag antenna project (6.3) and the translocation of humpback chub (6.6). Dr. David Rogowski 

is a fisheries biologist with Arizona Game and Fish Department with expertise in aquatic ecology 

and conservation biology of fish, and will lead the System Wide Electrofishing project (6.4), the 

brown trout natal origins project (6.5) and the Lees Ferry Creel Survey project (6.8). Dr. Michael 

Collyer is an Assistant Professor at Western Kentucky University with expertise in development 

of quantitative methods for analyzing phenotypic change and will provide technical support for 

the brown trout natal origins project. Luke Avery is a GCMRC fishery biologist with GCMRC 

and is the lead for the RTELSS (6.7). Dave Foster is a GCMRC River Operations Mechanic and 

225
Lees Ferry fishing guide and will assist with the RTELSS project. Thomas Gushue is a GCMRC 

GIS specialist, expert in collecting, processing and analyzing spatial data in Grand Canyon.

D.3 Deliverables 

Project elements will produce annual progress reports and peer reviewed publications at project 

completions.

E. Productivity from Past Work 

During FY13 the following products were delivered to GCMRC prior to April 1, 2014.

E.1. Data Products 

Data, trip reports and annual reports:

Trip ID Project

GC20130404 System Wide Electrofishing and catfish angling, Lees Ferry to Diamond Creek

GC20130525 System Wide Electrofishing and catfish angling, Lees Ferry to Diamond Creek

GC20131028 System Wide Electrofishing and catfish angling, Diamond Creek to Lake Mead

Rogowski, D.L. and P.N. Wolters. Colorado River Fish Monitoring in Grand 

Canyon, Arizona – 2013 Annual Report.

GC20130720 Mainstem netting, July aggregation monitoring

GC20130907 Draft manuscript in preparation: Persons, W.R. and D.R. Van Haverbeke.

Colorado River Fish Monitoring in Grand Canyon, Arizona: 2002—2013 

Humpback Chub Aggregations. 

RTELSS RTELLS survey results. 

Draft manuscript submitted. Avery, L.A. and others, 2014, Effects of 

increased discharge and temperature on age-0 rainbow trout dynamics in 

Lees Ferry, AZ

 

Linder, C.M., R.A. Cole, T.L. Hoffnagle, B. Persons, and A. Choudhury. 2012. Parasites of 

fishes in the Colorado River and selected tributaries in Grand Canyon, Arizona. Journal of 

Parasitology 98(1) pp 117-127.

Makinster, A.S., Persons, W.R., and Avery, L.A., 2011, Status and trends of the rainbow trout 

population in the Lees Ferry Reach of the Colorado River downstream from Glen Canyon 

Dam, Arizona, 1991–2009: U.S. Geological Survey Scientific Investigations Report 2011-

5015, 17 p., http://pubs.usgs.gov/sir/2011/5015/.

Makinster, A.S., Persons, W.R., Avery, L.A., and Bunch, A.J., 2010, Colorado River fish 

monitoring in Grand Canyon, Arizona--2000 to 2009 summary: U.S. Geological Survey 

Open-File Report 2010-1246, 26 p., http://pubs.usgs.gov/of/2010/1246/.

E.2. Publications in progress 

Persons, W.R. and D.R. Van Haverbeke. 2014. Colorado River Fish Monitoring in Grand 

Canyon, Arizona: 2002—2013 Humpback Chub Aggregations. 

226
Avery, L.A. 2014. Effects of increased discharge and temperature on age-0 rainbow trout 

dynamics in Lees Ferry, AZ.

Bunch, A.J., W.R. Persons, and W.T. Stewart. 2014. Integrating stationary PIT antennas into 

evaluations of fish sampling gear. In review.

Pearson, K.N., W.L. Kendall, D.L. Winkelman, and W.R. Persons. 2014. Evidence for skipped 

spawning in the endangered humpback chub (Gila cypha) with implications for demographic 

parameter estimates. In review.

E.3. Presentations at GCDAMP meetings 

Healy, B., E.Omana Smith, C. Nelson, M. Trammel, M. McKinstry, B. Albrecht, and R. 

Kegerries. Native Fish Population Trends – Grand Canyon Tributaries and Razorback 

Sucker: Status and Habitat Use. January 28, 2014 , Glen Canyon Dam Adaptive Management 

Program Annual Reporting Meeting, Phoenix, AZ.

Persons, W.R., D.R. Van Haverbeke and B. Healy. Colorado River fish monitoring in Grand 

Canyon, Arizona: 1990-2013 humpback chub, Gila cypha, aggregations. January 28, 2014 

Glen Canyon Dam Adaptive Management Program Annual Reporting Meeting, Phoenix, AZ.

Rogowski, D. and B. Healy. Other native fishes: population status and trends in the Colorado 

River and tributaries. January 28, 2014, Glen Canyon Dam Adaptive Management Program 

Annual Reporting Meeting, Phoenix, AZ.

Rogowski, D. Colorado River trout population monitoring: spawning and rearing surveys, 

seasonal and annual electrofishing surveys, and creel survey. January 28, 2014, Glen Canyon 

Dam Adaptive Management Program Annual Reporting Meeting, Phoenix, AZ.

Young, K. and B. Healy. Humpback chub in the Little Colorado River and other tributaries: 

monitoring of juveniles, sub-adults, and adults and translocations. January 28, 2014, Glen 

Canyon Dam Adaptive Management Program Annual Reporting Meeting, Phoenix, AZ.

E.4. Presentations at professional meetings 

Persons, W.R., D.R. Van Haverbeke and B. Healy. Colorado River fish monitoring in Grand 

Canyon, Arizona: 1990-2012 humpback chub, Gila cypha, aggregations. Desert Fishes 

Council Annual Meeting, November 20-24, 2013, Flagstaff, AZ.

Rogowski, David. Does variation in sampling effort during a long term monitoring project 

matter? Desert Fishes Council Annual Meeting, November 20-24, 2013, Flagstaff, AZ.

Brizendine, M.E., D.L. Ward and S.A. Bonar. Use of ultrasonic imaging and Ovaprim® to 

evaluate egg maturation of humpback chub, Gila cypha. Desert Fishes Council Annual 

Meeting, November 20-24, 2013, Flagstaff, AZ.

Omana Smith, E., B. Healy, C. Nelson and M. Trammell. Endangered humpback chub 

translocations to Colorado River tributaries in Grand Canyon National Park. Desert Fishes 

Council Annual Meeting, November 20-24, 2013, Flagstaff, AZ.

Healy, B., C. Nelson, E. Omana Smith, and M. Trammell. Non-native fish control in Colorado 

River tributaries in Grand Canyon National Park . Desert Fishes Council Annual Meeting, 

November 20-24, 2013, Flagstaff, AZ.

Van Haverbeke, D.R., M.J. Pillow, D.M. Stone and K.L. Young. Monitoring of humpback chub, 

bluehead sucker, and flannelmouth sucker in the Little Colorado River, Grand Canyon, 

Arizona. Desert Fishes Council Annual Meeting, November 20-24, 2013, Flagstaff, AZ.

227
F. References 

Andersen, M.E., Ackerman, M.W., Hilwig, K.D., Fuller, A.E., and Alley, P.D., 2010, Evidence 

of young humpback chub overwintering in the mainstem Colorado River, Marble Canyon, 

Arizona, USA: The Open Fish Science Journal, v. 3, , p. 42-50, at 

http://www.bentham.org/open/tofishsj/articles/V003/42TOFISHSJ.pdf.

Aparicio, E., García-Bertho, E., Araguas, R.M., Martínez, P., and García-Marín, J.L., 2005, 

Body pigmentation pattern to assess introgression by hatchery stocks in native Salmo trutta

from Mediterranean streams: Journal of Fish Biology, v. 67, p. 931-949. 

Blanc, J.M., Poisson, H. and Vibert, R., 1982, Variabilité génétique de la punctuation noire sur la 

truitelle fario (Salmo trutta L.): Annales de Génétique et de Sélection Animale, v. 14, p. 225-

236. 

Blanc, J.M., Chevassus, B. and Krieg, F., 1994, Inheritance of the number of red spots on the 

skin of brown trout: Aquatic Living Resources, v. 7, p. 133-136.

Bureau of Reclamation, 2011, Environmental assessment--non-native fish control downstream 

from Glen Canyon Dam: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado 

Region, 102 p. plus appendices, http://www.usbr.gov/uc/envdocs/ea/gc/nnfc/NNFC-EA.pdf.

Coggins, L.G., Jr., Pine, W.E., III, Walters, C.J., Van Haverbeke, D.R., Ward, D., and Johnstone, 

H.C., 2006, Abundance trends and status of the Little Colorado River population of 

humpback chub: North American Journal of Fisheries Management, v. 26, no. 1, p. 233-245, 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/06may24/Attach_06f.pdf.

Coggins, L.G., Jr., and Walters, C.J., 2009, Abundance trends and status of the Little Colorado 

River population of humpback chub--an update considering data from 1989-2008: U.S. 

Geological Survey Open-File Report 2009-1075, 18 p., http://pubs.usgs.gov/of/2009/1075/.

Coggins, L.G., Yard, M.D., and Pine, W.E., 2011, Nonnative fish control in the Colorado River 

in Grand Canyon, Arizona--an effective program or serendipitous timing?: Transactions of 

the American Fisheries Society, v. 140, no. 2, p. 456-470, 

http://dx.doi.org/10.1080/00028487.2011.572009.

Douglas, M.R., and Douglas, M.E., 2007, Genetic structure of humpback chub Gila cypha and 

roundtail chub G. robusta in the Colorado River ecosystem--final report: Fort Collins, 

Department of Fish, Wildlife and Conservation Biology, Colorado State University, 99 p., 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/07jun25/Attach_04.pdf.

Gloss, S.P., and Coggins, L.G., 2005, Fishes of the Grand Canyon, in Gloss, S.P., Lovich, J.E., 

and Melis, T.S., eds., The state of the Colorado River ecosystem in Grand Canyon--a report 

of the Grand Canyon Monitoring and Research Center 1991-2004: U.S. Geological Survey 

Circular 1282, p. 33-56, http://pubs.usgs.gov/circ/1282/.

Hayden, T.A., Limburg, K.E., and Pine, W.E., III, 2012, Using otolith chemistry tags and growth 

patterns to distinguish movements and provenance of native fish in the Grand Canyon: River 

Research and Applications, v. (online), 

http://onlinelibrary.wiley.com/doi/10.1002/rra.2627/abstract.

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, http://www.tandfonline.com/doi/abs/10.1577/T08-025.1.

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. 

228
1827-1849, http://dx.doi.org/10.1139/F2012-097.

Limburg, K.E., Hayden, T.A., Pine, W.E., III, Yard, M.D., Kozdon, R., and Valley, J.W., 2013, 

Of travertine and time--otolith chemistry and microstructure detect provenance and 

demography of endangered humpback chub in Grand Canyon, USA: PLoS ONE, v. 8, no. 12, 

online (e84235), http://dx.doi.org/10.1371/journal.pone.0084235.

Makinster, A.S., Persons, W.R., Avery, L.A., and Bunch, A.J., 2010, Colorado River fish 

monitoring in Grand Canyon, Arizona--2000 to 2009 summary: U.S. Geological Survey 

Open-File Report 2010-1246, 26 p., http://pubs.usgs.gov/of/2010/1246/.

Malvestuto, S. P., 1996, “Sampling the recreational creel”, in Murphy, B.R. and Willis, D.W., 

eds., Fisheries techniques (2d): Bethesda, Maryland: American Fisheries Society, p. 591–

623.

Melis, T.S., Korman, J., and Kennedy, T.A., 2012, Abiotic and biotic responses of the Colorado 

River to controlled floods at Glen Canyon Dam, Arizona, USA: River Research and 

Applications, v. 28, no. 6, p. 764-776, http://dx.doi.org/10.1002/rra.1503.

Mezzera, M., Largiadèr, C.R., and Scholl, A. 1997, Discrimination of native and introduced 

brown trout in the River Doubs (Rhône drainage) by number and shape of parr marks: 

Journal of Fish Biology, v. 50, p. 672-677. 

Persons, W.R., Ward, D.L., and Avery, L.A., 2013, Standardized methods for Grand Canyon 

fisheries research 2012: U.S. Geological Survey, Techniques and Methods, book 2, chapter 

A12, 19 p., http://pubs.usgs.gov/tm/tm2a12/.

Rogers, S., Ward, D., Clark, B., and Makinster, A., 2008, History and development of long-term 

fish monitoring with electrofishing in Grand Canyon, 2000–2007: Phoenix, Arizona Game 

and Fish Department, 70 p.

Skaala, Ø., and Jørstad, K.E., 1988, Inheritance of the fine-spotted pigmentation pattern of 

brown trout: Polskie Archiwum Hydrobiologii, v. 35, p. 295-304. 

Skaala, Ø., Jørstad, K.E., and Børgstrom, R., 1992, Fine-spotted brown trout--genetic aspects 

and the need for conservation: Journal of Fish Biology, v. 39 (suppl. A), p. 123-130. 

Speas, D.W., Walters, C.J., Ward, D.L., and Rogers, R.S., 2004, Effects of intraspecific density 

and environmental variables on electrofishing catchability of brown and rainbow trout in the 

Colorado River, Arizona: North American Journal of Fisheries Management, v. 24, no. 2, p. 

586-596, http://dx.doi.org/10.1577/M02-193.1.

U.S. Department of the Interior, 1995, Operation of Glen Canyon Dam--final environmental 

impact statement, Colorado River storage project, Arizona: Salt Lake City, Utah, Bureau of 

Reclamation, Upper Colorado Regional Office, 337 p., 

http://www.usbr.gov/uc/library/envdocs/eis/gc/pdfs/Cov-con/cov-con.pdf.

U.S. Fish and Wildlife Service, 1995, Final biological opinion for the operation of Glen Canyon 

(2-21-93-F-167), submitted to Bureau of Reclamation, Upper Colorado Region, 

http://www.fws.gov/southwest/es/arizona/Documents/Biol_Opin/93167_GlenCanyonOperati

ons.pdf.

U.S. Fish and Wildlife Service, 2008, Final biological opinion for the operation of Glen Canyon 

Dam: Phoenix, Ariz., submitted to Bureau of Reclamation, Upper Colorado Region, 

AESO/SE 22410-1993-F-167R1, 88 p., http://www.usbr.gov/uc/envdocs/bo/FinalGCDBO2-

26-08.pdf.

U.S. Fish and Wildlife Service, 2011, Final biological opinion on the operation of Glen Canyon 

Dam including high flow experiments and non-native fish control: Phoenix, Ariz., submitted 

to Bureau of Reclamation, Salt Lake City, Utah, AESO/SE 22410-2011-F-0100, 22410-

2011-F-0112, 150 p., 

229
http://www.fws.gov/southwest/es/arizona/Documents/Biol_Opin/110112_HFE_NNR.pdf.

Valdez, R.A., and Ryel, R.J., 1995, Life history and ecology of the humpback chub (Gila cypha) 

in the Colorado River, Grand Canyon, Arizona--final report: Logan, Utah, BIO/WEST, Inc., 

submitted to Bureau of Reclamation, contract no. 0-CS-40-09110, technical report no. TR250-08, 328 p.

Valdez, R.A., Carothers, S.W., Douglas, M.E., Douglas, M., Ryel, R.J., Bestgen, K.R., and 

Wegner, D.L., 2000, Research and implementation plan for establishing a second population 

of humpback chub in Grand Canyon--final report: Flagstaff, Ariz., U.S. Department of the 

Interior, Grand Canyon Monitoring and Research Center, 56 p.

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, 

http://dx.doi.org/10.3996/082012-JFWM-071.

Westley, P.A.H., Stanley, R., Fleming, I.A., 2013, Experimental tests for heritable morphological 

color plasticity in non-native brown trout (Salmo trutta) populations: PLoS ONE, v. 8, no. 

11, e80401.

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, 

http://dx.doi.org/10.1002/ece3.990.

Yard, M.D., Coggins, L.G., Baxter, C.V., Bennett, G.E., and Korman, J., 2011, Trout piscivory 

in the Colorado River, Grand Canyon--effects of turbidity, temperature, and fish prey 

availability: Transactions of the American Fisheries Society, v. 140, no. 2, p. 471-486, 

http://dx.doi.org/10.1080/00028487.2011.572011.

230
Table 1. Administrative History of Project 6.

Project

FY11-12 FY13-14 FY15-17

Mainstem Fish Studies

6.1. Humpback chub 

aggregation 

monitoring.

FY11: BIO 2.M4.11 $283,090

FY12: BIO 2.M4.12 $539,107

FY13: D.1 $203,900

FY14: D.1 $210,000

FY15: $218,768

FY16: $249,888

FY17: $252,6332

6.2 Humpback chub 

aggregation 

recruitment.

FY13: D.2 $167,400

FY14: D.2 $155,300

FY15: $83,750

FY16: $53,680

FY17: $50,048

6.3 Detecting 

aggregations with PIT 

tag antennas (new 

project)

FY15: $18,444

FY16: $13,500

FY17: $ 9,216

6.4 System Wide 

Electrofishing (SWEF)

FY11: BIO 2.M4.11 $283,090

FY12: BIO 2.M4.12 $539,107

FY13: F.1 $220,500

FY14: F.1 $227,200

FY15: $283,722

FY16: $295,900

FY17: $298,522

6.5 Brown trout origins 

through body 

pigmentation patterns. 

(new project)

FY15: $16,146

6.6 Humpback chub 

translocation to 

mainstem locations. 

(new project)

FY15: $ 9,790

FY16: $10,152

FY17: $10,782

6.7 Rainbow trout early 

life stage survey 

(RTELSS)

FY11 BIO4.M2.11

No line item for this project

FY13-14: F2.2

No line item for this 

project

FY15: $77,024

FY16: $69,296

FY17: $74,112

6.8 Lees Ferry Creel 

Survey

FY11 BIO4.M2.11

No line item for this project

FY13-14: F2.3

No line item for this 

project

FY15:

FY16: $25,750

FY17: $25,750

Related Projects

7.2 Juvenile Chub 

Monitoring near LCR 

confluence (NSE and 

NSE BIO 2.R15.11 $697,039

NSE BIO 2.R15.12 $423,475

FY13: F.3 $474,600

FY14: F.3 $488,800

FY15: $492,700

FY16: $510,900

FY17: $182,600

231
JCM). Integrated with 

6.4

9.2 Rainbow trout 

movement (Natal 

Origins). Integrated 

with 6.4

BIO 2.E.18.11 $432,518

BIO 2.E.18.12 $453.029

FY13: F.6 $281,800

FY14: F.6 $290,300

FY15: $440,500

FY16: $484,900

FY16: $371,900

 

232
G. Budget 

Project Element 6.1. 

Monitoring humpback chub 

aggregation relative 

abundance and distribution

Project Element 6.2. 

Humpback chub aggregation 

recruitment studies

Project Element 6.3. 

Monitoring mainstem 

humpback chub 

aggregations using PITtag antenna 

technology

Salaries $ 56,000.00 Salaries $ 34,800.00 Salaries $ 8,100.00

Traveling and Training $ 1,000.00 Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 6,100.00 Operating Expenses $ 6,400.00 Operating Expenses $ 7,800.00

Logistics $ 36,700.00 Logistics $ 8,800.00 Logistics $ -

Cooperators (non-USGS) $ 100,000.00 Cooperators (non-USGS) $ 25,000.00 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 18,968.00 USGS Burden $ 8,750.00 USGS Burden $ 2,544.00

Total $ 218,768.00 Total $ 83,750.00 Total $ 18,444.00

Project Element 6.4. System 

Wide Electrofishing

Project Element 6.5. Brown 

trout natal origins through 

body pigmentation patterns 

in the Colorado River

Project Element 6.6. 

Mainstem 

translocation of 

humpback chub

Salaries $ 31,900.00 Salaries $ - Salaries $ 4,000.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 8,100.00 Operating Expenses $ 600.00 Operating Expenses $ -

Logistics $ 49,200.00 Logistics $ - Logistics $ -

Cooperators (non-USGS) $ 175,000.00 Cooperators (non-USGS) $ 15,000.00 

Cooperators (nonUSGS) $ 5,000.00

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 19,522.00 USGS Burden $ 546.00 USGS Burden $ 790.00

Total $ 283,722.00 Total $ 16,146.00 Total $ 9,790.00

Project Element 6.7 Rainbow 

Trout Early Life Stage Survey

Project Element 6.8. Lees 

Ferry Creel Survey

Salaries $ 56,200.00 Salaries $ -

Traveling and Training $ 3,900.00 Traveling and Training $ -

Operating Expenses $ 700.00 Operating Expenses $ -

Logistics $ 5,600.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 10,624.00 USGS Burden $ -

Total $ 77,024.00 Total $ -

FY 2015

FY 2015 Project 6 Gross Totals: $707,644.00

233
Project Element 6.1. 

Monitoring humpback chub 

aggregation relative 

abundance and distribution

Project Element 6.2. 

Humpback chub aggregation 

recruitment studies

Project Element 6.3. 

Monitoring mainstem 

humpback chub 

aggregations using PITtag antenna 

technology

Salaries $ 68,700.00 Salaries $ 31,000.00 Salaries $ 8,400.00

Traveling and Training $ 1,200.00 Traveling and Training $ 500.00 Traveling and Training $ -

Operating Expenses $ 6,200.00 Operating Expenses $ 3,500.00 Operating Expenses $ 2,700.00

Logistics $ 44,300.00 Logistics $ 9,000.00 Logistics $ -

Cooperators (non-USGS) $ 100,000.00 Cooperators (non-USGS) $ - 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 29,488.00 USGS Burden $ 9,680.00 USGS Burden $ 2,442.00

Total $ 249,888.00 Total $ 53,680.00 Total $ 13,542.00

Project Element 6.4. System 

Wide Electrofishing

Project Element 6.5. Brown 

trout natal origins through 

body pigmentation patterns 

in the Colorado River

Project Element 6.6. 

Mainstem 

translocation of 

humpback chub

Salaries $ 22,600.00 Salaries $ - Salaries $ 4,100.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 8,100.00 Operating Expenses $ - Operating Expenses $ -

Logistics $ 59,700.00 Logistics $ - Logistics $ -

Cooperators (non-USGS) $ 175,000.00 Cooperators (non-USGS) $ 15,000.00 

Cooperators (nonUSGS) $ 5,000.00

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 25,138.00 USGS Burden $ 450.00 USGS Burden $ 1,052.00

Total $ 290,538.00 Total $ 15,450.00 Total $ 10,152.00

Project Element 6.7 Rainbow 

Trout Early Life Stage Survey

Project Element 6.8. Lees 

Ferry Creel Survey

Salaries $ 47,100.00 Salaries $ -

Traveling and Training $ 4,000.00 Traveling and Training $ -

Operating Expenses $ 700.00 Operating Expenses $ -

Logistics $ 5,000.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 25,000.00

USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 12,496.00 USGS Burden $ 750.00

Total $ 69,296.00 Total $ 25,750.00

FY 2016

FY 2016 Project 6 Gross Totals: $728,296.00

234
Project Element 6.1. 

Monitoring humpback chub 

aggregation relative 

abundance and distribution

Project Element 6.2. 

Humpback chub aggregation 

recruitment studies

Project Element 6.3. 

Monitoring mainstem 

humpback chub 

aggregations using PITtag antenna 

technology

Salaries $ 65,300.00 Salaries $ 26,000.00 Salaries $ 4,400.00

Traveling and Training $ 1,200.00 Traveling and Training $ 500.00 Traveling and Training $ -

Operating Expenses $ 6,200.00 Operating Expenses $ 3,500.00 Operating Expenses $ 2,800.00

Logistics $ 44,200.00 Logistics $ 9,100.00 Logistics $ -

Cooperators (non-USGS) $ 100,000.00 Cooperators (non-USGS) $ - 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 35,732.00 USGS Burden $ 10,948.00 USGS Burden $ 2,016.00

Total $ 252,632.00 Total $ 50,048.00 Total $ 9,216.00

Project Element 6.4. System 

Wide Electrofishing

Project Element 6.5. Brown 

trout natal origins through 

body pigmentation patterns 

in the Colorado River

Project Element 6.6. 

Mainstem 

translocation of 

humpback chub

Salaries $ 24,300.00 Salaries $ - Salaries $ 4,400.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 8,100.00 Operating Expenses $ - Operating Expenses $ -

Logistics $ 60,000.00 Logistics $ - Logistics $ -

Cooperators (non-USGS) $ 175,000.00 Cooperators (non-USGS) $ - 

Cooperators (nonUSGS) $ 5,000.00

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 31,122.00 USGS Burden $ - USGS Burden $ 1,382.00

Total $ 298,522.00 Total $ - Total $ 10,782.00

Project Element 6.7 Rainbow 

Trout Early Life Stage Survey

Project Element 6.8. Lees 

Ferry Creel Survey

Salaries $ 48,200.00 Salaries $ -

Traveling and Training $ 4,000.00 Traveling and Training $ -

Operating Expenses $ 700.00 Operating Expenses $ -

Logistics $ 5,000.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 25,000.00

USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 16,212.00 USGS Burden $ 750.00

Total $ 74,112.00 Total $ 25,750.00

FY 2017 Project 6 Gross Totals: $721,062.00

FY 2017 

235
Project 7. Population Ecology of Humpback Chub in and 

around the Little Colorado River 

A. Investigators 

Charles B. Yackulic, Research Statistician, U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center

Bill Persons, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Kirk Young, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and Wildlife 

Conservation Office

Kimberly Dibble, Research Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Michael Yard, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Maria Dzul, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

David Rogowski, Fisheries Biologist, Arizona Game and Fish Department

Randy VanHaverbeke, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and 

Wildlife Conservation Office 

Dennis Stone, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and Wildlife 

Conservation Office

David Ward, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Jeff Muehlbauer, Aquatic Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Josh Korman, President, Ecometric Research Inc.

Ted Kennedy, Aquatic Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

B. Project Summary 

During 2013–14 we developed models that integrate data collected in the Little Colorado 

River (LCR) with data collected by the juvenile chub monitoring (JCM) project to provide a 

holistic picture of humpback chub (Gila cypha) population dynamics (Yackulic and others,

2014). This manuscript suggests that chub movement between the LCR and Colorado River prior 

to adulthood is relatively rare, with the exception of young-of-the-year outmigration and that 

growth and survival rates are very different in these two environments. This journal article also 

identified the need for studies of trap avoidance among older humpback chub in the LCR, a need 

that can potentially be addressed by increased use of remote technologies for detecting 

humpback chub. We then used a modified version of these models to explain interannual 

variability in mainstem growth and survival in terms of monthly temperature and estimated 

rainbow trout (Oncorhynchus mykiss) abundances in order to support the development of the 

Glen Canyon Dam Long-Term Experimental and Management Plan (LTEMP) Environmental 

Impact Statement and address the key uncertainty surrounding the relative importance of 

rainbow trout and temperature in humpback chub population dynamics (Yackulic and others, in 

236
prep.). While parameter estimates in these models are based on field data collected in the LCR 

and JCM, this modelling was aided conceptually by lab experiments exploring impacts of trout 

and temperature on chub growth and survival (Ward and others, in prep). 

Simulating future dynamics under alternative management strategies as part of the LTEMP 

process highlighted the importance of uncertainty associated with several key population 

processes, especially the production and outmigration of young-of-the-year humpback chub from 

the LCR. To address this uncertainty, already identified in the Grand Canyon Monitoring and 

Research Center’s workplan for Fiscal Years (FY) 2013–14, we initiated juvenile humpback 

chub marking with visible implant elastomer (VIE) tags in the LCR during early July, a period 

when humpback chub are just becoming large enough to have a reasonable chance of surviving 

in the mainstem. Although LTEMP obligations have delayed a formal analysis of these data, 

preliminary work suggests that this effort will allow us to estimate juvenile humpback chub 

abundance and outmigration with acceptable precision. We also analyzed data collected by the 

U.S. Fish and Wildlife Service (USFWS) from 2001–2013 to characterize spatio-temporal 

variation in survival, growth and movement of sub-adult humpback chub in the LCR (Dzul and 

others, in review). This work suggests both that winter growth is strongly and negatively 

correlated with the extent of winter/spring flooding and that habitat quality for sub-adult 

humpback chub is better in upper reaches of the LCR. This follows work by Vanhaverbeke and 

others (2013) indicating that when winter/spring flooding was minimal, juvenile production was 

poor. Other activities during FY13–14 included pilot work to determine the best ways to 

characterize spatio-temporal variation in the food base in FY13, with plans to rigorously sample 

the LCR food base in calendar year 2014.

In FY15–17, we will: (a) continue to monitor humpback chub in the LCR and Colorado 

River reference site (river mile (RM) 63.0-64.5) and to mark young-of-year humpback chub 

throughout the lower 13.6 km of the LCR in July, (b) develop field and analytical techniques to 

better use remote technologies for detecting passive integrated transponder (PIT) tags to address 

questions of trap avoidance and to potentially minimize future handling of chub, (c) develop new 

non-lethal tools for measuring the health and condition of humpback chub in the field, (d) 

undertake targeted, cost-effective research to understand mechanisms underlying observed 

population processes, including the roles of high CO2 at base flow, gravel limitation, parasites, 

and the aquatic food base, and (e) continue to develop models that integrate findings from the 

above projects. The proximate goals of these activities is to better understand the relative roles of 

LCR hydrology, water quality, intraspecific and interspecific interactions, and mainstem 

conditions in humpback chub juvenile life history and adult recruitment, as well as to better 

estimate the current adult abundance. The ultimate goal of these activities is to continue to 

develop tools that allow us to better predict the impacts of dam operations and other management 

activities on humpback chub populations as well as appropriately account for uncertainty in these 

predictions. Specific questions of interest include:

1. To what extent does young-of-the-year humpback chub production and outmigration 

from the LCR vary between years and how is this variation driven by LCR hydrology and 

intraspecific interactions (i.e., cannibalism and competition)?

2. What are the drivers of interannual and spatial variation in survival and growth of 

juvenile and sub-adult humpback chub? In particular, what are the roles of LCR and 

mainstem conditions in the overall trajectory of the population?

237
3. Are there factors, such as heterogeneity in skip-spawning rates, heterogeneity in adult 

humpback chub capture probabilities in the JCM, or trap avoidance in the LCR that bias 

estimates of the adult population size and population processes?

Juvenile humpback chub are the most sensitive life stage to mainstem conditions and an 

understanding of their life history is the key to predicting the influence of dam operations on this 

species. Prior to the Near Shore Ecology (NSE) project (2009–2011) and the more recent JCM 

project (2012–current), our understanding of humpback chub early life history was limited to 

back-calculations of cohort strength (number of fish surviving to adulthood from a given hatch 

year) derived from abundance estimates of humpback chub greater than 200 mm and believed to 

be four years old (Coggins and others, 2006; Coggins and Walters, 2009). However, given the 

disparity in growth rates between humpback chub living in the LCR and Colorado River 

(Yackulic and others, 2014) this approach was almost certainly misleading as humpback chub 

could be anywhere from 4–10 years old when they reach 200 mm depending on where they had 

spent most of their time (LCR or mainstem Colorado River) and what environmental conditions 

had been like in those locations. 

Since 2009, we have developed the field techniques (including a fixed reference site in the 

Colorado River) and analytical methods that allow us to understand humpback chub early life 

history in the detail required to begin to tease apart the effects of variation in population 

processes caused by mainstem temperature, trout abundance, and conditions in the LCR. For 

example, in support of the LTEMP process we were able to fit relationships between monthly 

temperature and estimated rainbow trout abundance and juvenile humpback chub survival and 

growth using only data from 2009–2013 that accurately predicted trends in adult humpback chub 

numbers from 1989–2009. While there is still room for improvement in these models, this 

represents a dramatic step in our ability to predict the consequences of management options. 

While conditions in the LCR are not directly affected by dam operations, they nonetheless play a 

vital role in determining the degree to which temperature and rainbow trout numbers in the 

Colorado River must be managed. For example, if juvenile humpback chub production and 

export are high, this may suggest less need for rainbow trout management and/or lower flows to 

increase water temperatures in the mainstem. Alternatively, a better understanding of the factors 

leading to increased humpback chub production could provide decision makers opportunities to 

strategically implement management actions in years when they would have the largest effect. 

For example, the 2000 Low Steady Summer Flow experiment may have been ineffective simply 

because it followed two years of potentially minimal production of juvenile chub. Improved 

information about the drivers of humpback chub population dynamics could have helped 

managers and scientists plan this experiment such that it occurred when conditions were more 

likely to result in a detectable response. Likewise, management actions such as mechanical 

removal of nonnative fishes will be much more effective if they occur in years of high humpback 

chub production. If variation in production is primarily driven by exogenous factors (e.g., extent 

of flooding) as opposed to endogeneous factors (e.g., competition between cohorts) this also has 

implications for long-term population dynamics.

With respect to adult humpback chub, key uncertainties revolve around our understanding of 

capture probability and movement. In particular, heterogeneity in capture probability in the LCR 

caused by some adult humpback chub (especially potential residents) avoiding hoop nets could 

lead to underestimates of abundance. At the same time, the potential for temporary emigration in 

the JCM reach is a cause for concern and could lead to overestimates of abundance. Lastly, a 

better understanding of skip-spawning in adult humpback chub is essential because many adults 

238
are only vulnerable to capture during spring sampling in the LCR and thus inferences about their 

survival and abundance depends on assumptions about the skip-spawning process. Answering 

the above uncertainties is dependent both on new data streams from remote tag readers and 

intellectual investment into developing the appropriate models to incorporate this information 

and test hypotheses. 

C. Background

C.1. Scientific Background 

Standardized sampling in the LCR over the last decade has revealed substantial year to year 

variation in relative abundances of juvenile humpback chub in the fall (VanHaverbeke and 

others, 2013). In particular, juvenile catch in 2002 and 2006 was markedly lower than other years 

and occurred in the same years as relatively low winter/spring discharge in the LCR over the 

same span, suggesting an important and unresolved link between LCR hydrology and humpback 

chub population dynamics. On the other hand, there appears to be substantial variation in fall 

juvenile relative abundances in others years (e.g., 2009 and 2013 were relatively low) that 

appears to be unrelated to winter/spring discharge.

There are at least four hypotheses to explain this linkage, each of which has different 

implications for the significance of the observation—low juvenile fall abundance in the LCR—to 

humpback chub population dynamics and adult recruitment. These hypotheses also have 

different implications for the relative roles of conditions in the mainstem Colorado versus the 

LCR in determining adult humpback chub population dynamics and adult recruitment. Low 

juvenile abundance in the fall could be a leading indicator of a failed hatch year caused by: 

(Hypothesis-(H1) poor egg survival in the LCR associated with gravel limitation (H1a) or high 

CO2 levels (H1b), (H2) poor juvenile survival in the LCR the preceding summer associated with 

low prey production, (H3) low juvenile survival in the LCR the preceding summer due to 

predation by conspecifics, or (H4) unrelated to juvenile survival and instead a result of 

outmigration from the LCR due to displacement from monsoon floods or relatively favorable 

rearing conditions in the mainstem Colorado River.

Under Hypothesis 1 (H1) Survival of humpback chub eggs in the LCR is limited in years 

when snowmelt flooding is negligible or small because of poor spawning substrate conditions or 

high CO2 conditions that limit egg and larval survival. The rationale for this spawning limitation 

hypothesis is that the LCR is a high CO2, travertine system, and marl deposition in the lower 

LCR is extremely rapid (Robinson and others, 1996). Without moderate/large snowmelt floods 

that deliver lower CO2 water and clean gravels, substrates in the downstream part of the LCR 

during the spawning season will likely be cemented together with marl and will lack the 

interstitial spaces and/or water quality necessary for egg survival. Under this hypothesis, we 

would expect lowered numbers of juveniles in both the LCR and in the mainstem near the LCR 

confluence during years without large LCR snowmelt floods. Further, if this hypothesis is true, it 

suggests that the continued success of the LCR population may be predicated on climatic 

conditions in the LCR basin and are best in years of moderate/large snowmelt floods. H1b may 

also explain the lower frequency of juvenile chub in upper portions of the LCR, where CO2 

concentrations are greater.

Under Hypothesis 2 (H2) Large snowmelt floods in the LCR stimulate production of the prey 

base through improvements in both the quantity and quality of food resources consumed by 

humpback chub, which leads to high juvenile humpback chub survival and low outmigration. 

(H2) is somewhat related to H1 in that it also posits a link between LCR hydrology and juvenile 

239
abundance in the fall, but the mechanism underlying H2 is different. In years with small 

snowmelt floods, the foodbase in the LCR is unproductive (see Fisher and others, 1982; Cross 

and others, 2011), which in turn leads to low survival and/or high out-migration of juvenile 

humpback chub. Under this hypothesis, the population of juvenile humpback chub (both 

yearlings and young-of-year) in the mainstem could remain the same, or even increase, if 

juveniles choose to outmigrate in response to low food densities in the LCR in years without 

substantial snowmelt flooding. If this hypothesis is true, and there is earlier and higher 

outmigration in response to negligible/small snowmelt floods in the LCR, it suggests that 

mainstem conditions may be especially important as a greater proportion of the juvenile 

population will be rearing in the mainstem.

Hypothesis 3 (H3) focuses on the role of intraspecific interactions, especially predation and 

cannibalism by yearlings on young-of-the-year, and can take two non-mutually exclusive forms. 

The first variety of this hypothesis (H3a) posits that in years without large LCR snowmelt 

floods, more yearlings remain in the system and there are higher levels of cannibalism and 

competition than in years with large LCR snowmelt floods. The second version (H3b) posits 

that, independent of the reason for decreases in fall abundances in 2002 and 2006, the lack of 

yearlings in the LCR in the following spawning season (2003 and 2007) led to especially large 

cohorts of young-of-year in those hatch years because of reduced cannibalism and competition. 

It is also possible that snowmelt floods are not an important factor affecting humpback chub 

dynamics and, instead, the intensity of summer/fall monsoon floods is the primary driver of fall 

abundances of juvenile humpback chub; that is, low LCR fall abundances are not a leading 

indicator of a failed hatch year. In both 2002 and 2006, LCR discharge during the snowmelt 

season was negligible, but there were relatively large monsoon floods in the fall. This 

observation leads to Hypothesis 4 (H4), which argues that outmigration rates of juvenile 

humpback chub from the LCR are directly linked to the intensity of monsoon flooding in the 

summer and fall. Under this hypothesis, we would expect increased migration from the LCR to 

the mainstem during years of large monsoon flooding in the LCR, and we would expect most 

migration to occur during the monsoon season—from July to September. VIE marking as part of 

both USFWS and NSE sampling between 2009 and 2011 has provided hints of movement 

between the LCR and the mainstem over these time scales; however, interpretation of these data 

has been hampered by the relatively low number of juveniles marked between the spawning 

season and before fall monsoons. Specifically, the last scheduled spring marking event in the 

LCR occurs in May, and young-of -year humpback chub are rarely large enough to mark with 

VIE tags (>40 mm total length). The next scheduled marking occurs in September, and monsoon 

floods that displace young-of- year may have already occurred. 

Survival rates for juvenile fish are highly correlated with individual growth rates; a juvenile 

population that grows rapidly will generally experience higher survival relative to a population 

of juveniles that is growing slowly (Walters and Martell, 2004). Understanding the causes of 

variation in juvenile humpback chub growth rates among habitats will therefore aid interpretation 

of any estimates of juvenile survival among habitats. One hypothesis to explain the observed 

variation in humpback chub growth rates among locations and times is that growth rates are 

mainly driven by concomitant changes in water temperature (H5). This hypothesis has clear 

implications for dam operations. Another hypothesis (H6) states that humpback chub growth 

among locations and times is mainly driven by differences in the quantity and quality of prey 

available to juvenile humpback chub. This hypothesis also has implications for dam operations, 

but the types of operational changes that might be evaluated to mitigate low prey production in 

the mainstem are very different from the types of operations that might be evaluated to mitigate 

240
water temperature effects related to (H5). Lastly, interspecific and intraspecific competition for 

food resources is the main driver of humpback chub growth rates among locations and times 

(H7). These hypotheses (H5-H7) are obviously not mutually exclusive. H6 and H7, in particular, 

are linked because food limitation (H6) is a necessary condition for resource competition (H7). 

We believe the distinction is important, however, because LCR hydrology may have strong 

effects on resource availability (H6) independent of fish abundance (H7). Thus, there may be 

some years when one factor ultimately limits or constrains humpback chub growth, and other 

years when a different factor limits growth. 

It is improbable that a two-year study could fully resolve all of these hypotheses, in part 

because our ability to distinguish among certain hypotheses is dependent on LCR hydrology. 

However, irrespective of LCR hydrology, the activities we will conduct in FY15–17 will allow 

us to evaluate the strength of evidence for at least some of the above hypotheses and address key 

uncertainties surrounding the population dynamics of humpback chub. This new research will be 

integrated with ongoing USFWS monitoring in the LCR and JCM sampling in the mainstem, 

which will help minimize handling of juvenile humpback chub. Integration of this new research 

effort into ongoing monitoring will also build upon these long-term efforts in a way that allows 

us to ask new questions. 

C.2. Management Background 

This project directly addresses the following Strategic Science Questions (SSQs), Core 

Monitoring Information Needs (CMINs), and Research Information Needs (RINs) previously 

identified by the Glen Canyon Dam Adaptive Management Program (GCDAMP). 

• Goal 2: Maintain or attain a viable population of existing native fish, remove jeopardy 

for humpback chub and razorback sucker, and prevent adverse modification to their 

critical habitats.

• Goal 4: Maintain a naturally reproducing population of rainbow trout above the Paria 

River, to the extent practicable and consistent with the maintenance of viable populations 

of native fish.

In August 2004, the GCDAMP Adaptive Management Work Group reviewed these goals 

and identified priority questions. This project addresses the top priority question:

• Priority 1: Why are humpback chub not thriving, and what can we do about it? How 

many humpback chub are there and how are they doing? 

In March 2011, the Secretary’s Designee, Assistant Secretary for Water and Science, 

identified that the first priority was compliance with the Endangered Species Act, followed by 

sediment, with the third priority being science on both non-native control and the recreational 

trout fishery. These monitoring projects contribute to improved understanding of humpback 

chub, rainbow trout, and their interactions.

C.3. Key Monitoring and Research Questions Addressed in this project 

Primary SSQ addressed:

241
• SSQ 1-1. To what extent are adult populations of native fish controlled by production 

of young fish from tributaries, spawning and incubation in the mainstem, survival of 

young-of-year and juvenile stages in the mainstem, or by changes in growth and 

maturation in the adult population as influenced by mainstem conditions?

• SSQ 1-2. Does a decrease in the abundance of rainbow trout and other cold- and 

warm water nonnatives in Marble and eastern Grand Canyons result in an 

improvement in the recruitment rate of juvenile humpback chub to the adult 

population?

Additional SSQs addressed:

• SSQ 1-8. How can native and nonnative fishes best be monitored while minimizing 

impacts from capture and handling or sampling?

• SSQ 5-4. What is the relative importance of increased water temperature, shoreline 

stability, and food availability on the survival and growth of YoY and juvenile native 

fish?

• SSQ 5-6. Do the potential benefits of improved rearing habitat (warmer, more stable, 

more backwater and vegetated shorelines, more food) outweigh negative impacts due 

to increases in nonnative fish abundance?

The GCDAMP Science Advisors articulated the following summary science questions addressed 

by this project:

• SA 1. What are the most limiting factors to successful humpback chub adult 

recruitment in the mainstem: spawning success, predation on young of year and 

juveniles, habitat (water, temperature), pathogens, adult maturation, food 

availability, competition?

• SA 2. What are the most probably positive and negative impacts of warming the 

Colorado River on humpback chub adults and juveniles?

Information Needs Addressed

• CMIN 2.1.2. Determine and track recruitment of all life stages, abundance, and 

distribution of humpback chub in the LCR.

• RIN 2.2.2. Determine if a population dynamics model can effectively predict 

response of native fish under different flow regimes and environmental conditions.

• RIN 2.2.8. What combination of dam release patterns and nonnative fish control 

facilitates successful spawning and recruitment of humpback chub in the Colorado 

River ecosystem?

• RIN 2.4.2. Determine if suppression of nonnative predators and competitors 

increases native fish populations.

• RIN 2.4.3. To what degree, which species, and where in the system are exotic fish a 

detriment to the existence of native fish through predation or competition?

• RIN 4.2.5 To what extent is there overlap in the Colorado River ecosystem below 

the Paria River of RBT habitat and native fish habitat?

• EIN 2.1.1 How does the abundance and distribution of all size classes of humpback 

chub in the LCR and mainstem change in response to an experiment performed 

under the Record of Decision, unanticipated event, or other management action?

242
• EIN 2.1.2 How does the year class strength of humpback chub (51–150 mm) in the 

LCR and mainstem change in response to an experiment performed under the 

Record of Decision, unanticipated event, or other management action?

• EIN 2.4.1 How does the abundance and distribution of nonnative predatory fish 

species and their impacts on native fish species in the Colorado River ecosystem 

change in response to an experiment performed under the Record of Decision, 

unanticipated event, or other management action?

D. Proposed Work 

D.1. Project Elements 

Project Element 7.1. Annual spring/fall humpback chub abundance estimates in the lower 13.6 km of the 

Little Colorado River 

(Recommended for funding FY15: $531,320)

William Persons, Fishery Biologist, USGS, GCMRC

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office David 

R. Van Haverbeke, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

David Rogowski, Fisheries Biologist, Arizona Game and Fish Department

The most efficient way to sample adult humpback chub that spawn in the LCR is during 

the spring as capture probabilities in the LCR for adults are much higher than in the mainstem. 

Fall sampling provides us with yearly estimates of the abundance of young-of-the-year that have 

not left the LCR and is the closest we have to a long-term dataset of juvenile humpback chub 

production. Data collected during these trips are all used to estimate spring and fall closed 

population abundance for various size classes of humpback chub (> 150 mm and > 200 mm total 

length (TL)), and during some years provides abundance estimates of other native fishes 

(Coggins and others, 2006; Van Haverbeke, 2010). The project also marks juvenile humpback 

chub (< 100 mm TL) with VIE tags in the fall in conjunction with JCM project (Project Element 

7.2) and the July LCR marking project (Project Element 7.3) to improve our understanding of 

juvenile humpback chub production and outmigration. This is an ongoing project since 2000 and 

the monitoring was identified as a necessary component in the 2011 Environmental Assessment 

for Non-Native Fish Control Downstream from Glen Canyon Dam and associated Biological 

Opinion (Bureau of Reclamation, 2011). The specific objectives for 2015–17 (similar to 

objectives for previous years) are:

1. Determine length stratified Chapman modified Peterson closed population estimates 

of humpback chub (e.g., >100 mm, ≥150 mm, ≥200 mm) in the lower 13.57 km of the 

LCR during the spring and fall.

2. Generate a population estimate of age 0 humpback chub (40-99 mm) during fall.

3. Collect data on PIT tagged fish in support of humpback chub population modelling 

(Project Element E.10).

4. Collect additional data on fishes in the LCR such as size, species, sexual condition 

and characteristics, and external parasites (i.e., Lernaea cyprinacea).

Modifications to this project include use of experienced biologists and expansion of 

remote sensing efforts throughout the LCR (see Project Element 7.4). Specifically, we will 

replace three volunteer positions with paid staff. This will result in increased salary costs for 

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fiscal years 2015–2017, but reduced travel expenses that had been used for volunteer travel. 

Working with partners, we propose amalgamation of Arizona Game and Fish Department’s 

(AGFD) lower 1200 meter monitoring efforts into LCR mark-recapture effort (Spring and Fall). 

This approach avoids the need to increase overall LCR long term monitoring costs due in part to 

savings associated with fewer helicopter flights and facilitates deployment of portable remote 

PIT tag readers to assess humpback chub demographics across the three sample reaches 

constituting the occupied 13 km of the LCR. We also propose to involve Navajo Nation or other 

Tribal members in sampling activities and have included funding to support a temporary field 

position (four 10-day trips). Methods will follow those used from 2000-2014 (described in Van 

Haverbeke and others, 2013). Arizona Game and Fish Department will provide experienced 

biologists to assist with hoop net efforts, and be responsible for small PIT tag antennas deployed 

near each camp.

Project Element 7.2. Juvenile Chub Monitoring in the mainstem near the Little Colorado River Confluence 

(Recommended for funding FY15: $497,878)

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research, Inc.

Maria Dzul, Fishery Biologist, USGS, GCMRC

Charles B. Yackulic, Research Statistician, USGS, GCMRC

This project provides the data to estimate survival, growth and abundance of juvenile 

humpback chub for a reference reach (RM 63-64.5) in the mainstem Colorado River just 

downstream of the LCR confluence. It also provides additional passes to estimate rainbow trout 

and brown trout abundance in this same reach (the reference reach is sampled using rainbow 

trout specific methods as part of the Natal Origins project; Project Element 9.2). Data from this 

project, in addition to temperature collected near the LCR confluence through Project 2, will be 

used in Project Element 7.10 to refine our understanding of the effects of temperature and trout 

on humpback chub survival and growth. Recent progress in our understanding of trout and 

mainstem temperature effects on humpback chub population dynamics are solely dependent on 

data collected through this project and its precursor, the NSE project. Recaptures of VIE marked 

humpback chub in the reference reach, especially humpback chub marked through the July LCR 

sampling (Project Element 7.3), are crucial to understanding annual survival and movement out 

of the LCR into the Colorado River. Obtaining rainbow and brown trout abundance estimates 

between RM 63-64.5 were identified as necessary activities in the 2011 Environmental 

Assessment for Non-Native Fish Control Downstream from Glen Canyon Dam and associated 

Biological Opinion (Bureau of Reclamation, 2011). The metrics are included in the suite of 

triggers identifying when to implement mechanical removal of nonnative fish to protect 

humpback chub. Continued annual assessments of juvenile humpback chub survival rates and 

abundance in the mainstem using methods developed in the NSE Study will provide key metrics 

by which management actions such as rainbow trout removal will be evaluated. 

As with the Natal Origin Research project (Project Element 9.2), the Juvenile Chub 

Monitoring project is scheduled to be completed by the end of FY2016. This leaves a significant 

data gap in outlying years for information on juvenile humpback chub as required by the 

Biological Opinion for Glen Canyon Dam operations including high flow experiments and 

nonnative fish control (USFWS 2011). To avoid this gap, a transition of the Juvenile Chub 

Monitoring project from a research focus to a monitoring effort needs to occur while maintaining 

a robust multi-gear, multi-pass mark-recapture effort necessary to generate reliable survival 

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estimates of these young fish. We propose that GCMRC and its cooperators collaboratively 

develop a plan for this transition and include it among the topics to be reviewed by the fisheries 

program protocol evaluation panel (PEP; see Project Element 8.3). The new monitoring project 

will begin in FY2017 following review and implementation, as appropriate, of the PEP’s 

recommendations by GCMRC.

Project Element 7.3. July Little Colorado River juvenile humpback chub marking to estimate production and 

outmigration 

(Recommended for funding FY15: $112,172)

Maria Dzul, Fishery Biologist, USGS, GCMRC

Charles B. Yackulic, Research Statistician, USGS, GCMRC

Luke Avery, Fishery Biologist, USGS, GCMRC

David Ward, Fishery Biologist, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

The objective of this project element is to determine how rates of juvenile humpback chub 

outmigration vary between years and the degree to which outmigration rates are driven by 

juvenile densities or the strength of flooding associated with summer monsoons. This project 

also seeks to estimate the abundance of young-of-the-year humpback chub in the LCR prior to 

the most significant period of outmigration (July-September). As mentioned above, juvenile 

production and rates of juvenile outmigration are two of the largest uncertainties in population 

models of humpback chub that spawn in the LCR and thus uncertainty in these population 

processes hampers efforts to determine how much management is required to maintain healthy 

adult populations. Uncertainty in juvenile production and outmigration was one of the largest 

uncertainties in predicting humpback chub responses to alternatives during the LTEMP process. 

Previous research suggests that rates of outmigration are relatively high (Yackulic and others, 

2014). It should be noted, however, that these estimates were based on marks put out only in the 

lowest portion of the LCR and were concentrated in years that likely had high levels of export 

(2011 & 2012), thus may have biased estimates high. Preliminary estimates suggest that 

outmigration by the 2013 cohort was lower and that the size of this cohort may have be relatively 

small. Lastly, if rates of recovery of juvenile humpback chub marked during July sampling are 

substantially lower at non-LCR aggregations (Project D) as opposed to in the JCM reach (Project 

Element E.2) this could be taken as evidence of local reproduction at aggregations. 

Sampling during July relies on three gear types, seining, dip nets and hoop nets to capture 

juvenile humpback chub at each of the three sample reaches and humpback chub between 40-100 

mm are given VIE batch marks (humpback chub over 100 mm are scanned for PIT tags 

according to the standard protocol, however, the focus of our efforts is on juveniles, that is 

humpback chub under 100 mm in total length).

Project Element 7.4 Remote PIT tag array monitoring 

(Recommended for funding FY15: $53,638)

William Persons, Fishery Biologist, USGS, GCMRC

The objectives of this project are to provide data to test hypotheses about trap avoidance and 

humpback chub movement and to potentially provide a future alternative to decrease handling of 

adult humpback chub. This has been an ongoing effort since 2009, with lapses and equipment 

245
failures during parts of 2010 and 2011. The project has installed two PIT tag antenna arrays in 

the LCR approximately 2 km upstream from the confluence with the mainstem Colorado River. 

The antenna arrays read and record PIT tag codes from marked fish along with a date/time stamp 

as they pass near antennas anchored to the river bottom. These data can be used within 

population models as well as to provide information on timing of movement and survival of PIT 

tagged native fishes. Antenna detection efficiency has varied greatly and was estimated to be 6 –

42%. Work completed during FY2012-13 by a Colorado State University graduate student is 

expected to result in a thesis during 2014. Preliminary findings suggests that skip-spawning by 

adult humpback chub is Markovian (i.e., individuals that spawned in the previous year are less 

likely to spawn than individuals that did not spawn). During FY2015-17 we plan to maintain the 

existing antenna arrays and to deploy three portable antennas approximately 9 km upstream from 

the LCR mouth to attempt to better assess movement and avoidance of hoop nets.

Project Element 7.5. Food web monitoring in the Little Colorado River 

(Recommended for funding FY15: $141,520)

Jeff Muehlbauer, Aquatic Ecologist, USGS, GCMRC

Ted Kennedy, Aquatic Ecologist, USGS, GCMRC

Charles B. Yackulic, Research Statistician, USGS, GCMRC

The objectives of this project are to characterize invertebrate drift, benthic densities and 

emergence throughout the perennial (lower 21 km) reach of the LCR over various seasons and to 

test whether emergence techniques are an appropriate technique for long-term monitoring in this 

and other tributaries. We suspect that the amount of invertebrates available for consumption by 

fish, and humpback chub in particular, varies longitudinally because of work suggesting higher 

humpback chub growth above Chute Falls (Stone and others, in prep) as well as higher growth 

and abundance of subadult humpback chub in Coyote and Salt camps relative to Boulders camp 

(Dzul and other, in review; Vanhaverbeke and others, 2013). Preliminary data collected in July 

2013 suggests that emergence below the Chute Falls (no sampling occurred above Chute Falls) 

increases at stations located further from the confluence. A better understanding of the food base 

in areas that support high densities of humpback chub growing quickly may aid in determining 

the carrying capacity within the LCR as well as in tributaries considered for translocation efforts.

This project is a continuation of a project begun in FY 2013-14. Logistical constraints and 

weather-related issues ultimately precluded the total completion of this project within that 

timeframe, and we therefore propose to continue the project into FY 2015 and possibly the first 

months of FY 2016 in order to provide better quality results. Sampling will occur quarterly 

(December, April, June, and September), and monthly in the period of highest humpback chub 

growth (April to September), with additional opportunistic samples occurring once per year as 

soon as possible after the first annual summer monsoon flood. Sampling will involve the 

deployment of sticky traps (Smith and others, 2014) in consistent locations and habitat 

conditions throughout the perennial 21 km reach of the LCR, from Blue Spring to the confluence 

with the Colorado River. Light traps (Kennedy and others, 2013) are also set out at camps in the 

evenings. At the three main camps (Salt, Coyote, Boulders) and at major aquatic habitat changes 

(Blue Spring, Chute Falls, confluence), benthic samples are also taken using standard D-nets, 

emergence traps are deployed over the water, infall traps for organic matter and terrestrial insects 

are deployed at the water’s edge, and aquatic habitat is quantified based on visual estimates of 

percent cover of algae and using pebble counts (Wolman, 1954). Finally, temperature, 

246
conductivity, and dissolved oxygen are measured using data loggers deployed above and below 

the Chute Falls/Atomizer complex and near Salt and Coyote camps.

Project Element 7.6. Potential for gravel substrate limitation for humpback chub reproduction in the LCR 

(Recommended for funding FY15: $11,600)

Maria Dzul, Fishery Biologist, USGS, GCMRC

Jeff Muehlbauer, Aquatic Ecologist, USGS, GCMRC

David Ward, Fishery Biologist, USGS, GCMRC

Charles B. Yackulic, Research Statistician, USGS, GCMRC

The objectives of this project element are to characterize year-to-year variation in gravel 

availability in the LCR and determine whether lack of gravels limits juvenile humpback chub 

production in certain years. VanHaverbeke and others (2013) showed that juvenile humpback 

chub production in the LCR has been lower during the period 2001–2012 during years without 

significant winter/spring flooding. Earlier work suggested that increases in discharge in the LCR 

exposes fresh gravel deposits that are ideal for development of humpback chub eggs (Kaeding 

and Zimmerman 1983) and that humpback chub spawning activity is associated with clean 

gravel deposits (Gorman and Stone 1999). Accordingly, scarcity of gravel substrates may play a 

significant role in humpback chub population processes, however, there is little direct evidence 

to determine whether the cause of low recruitment is due to scarcity of fresh gravel deposits. 

Evaluating how low spring discharge affects humpback chub recruitment is especially important 

because climate projections predict decreased precipitation throughout the southwestern USA 

(Seager and others 2007), and thus years with low snowmelt may become increasingly common 

in northern Arizona. This project will involve annual substrate mapping and monitoring using 

bed surface random-walk pebble counts (Wolman 1954) in a reference reach of the LCR 

conducted every year in conjunction with spring LCR monitoring (Project Element 7.1). In 

addition, we will conduct gravel tray experiments to determine the sediment characteristics that 

are required for humpback chub egg deposition and survival. 

Project Element 7.7. Evaluate CO2 as a limiting factor early life history stages of humpback chub in the Little 

Colorado River 

(Recommended for funding FY15: $86,420)

David Ward, Fishery Biologist, USGS, GCMRC

Dennis Stone, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

The objective of this project is to evaluate the extent to which high levels of dissolved CO2 in 

the LCR at base flow impacts early life history stages of humpback chub. High levels of 

dissolved CO2 in water are known to negatively affect fish populations and have been 

hypothesized to constrain humpback chub to the lower 14.2 km of the LCR in Grand Canyon 

(Mattes 1993, Robinson and others 1996, Kaeding and Zimmerman 1983). Elevated CO2 levels 

decrease the ability of a fish’s hemoglobin to transport oxygen and can compromise respiration 

in fishes. The safe or accepted levels of CO2in water depend upon fish species (Basu 1959). In 

general, levels above 60 ppm are avoided by fish and can be detrimental to fish health (Alabaster 

and others 1957, Reviewed in Heinen and others 1996) with early life history stages of fish being 

most sensitive (Baumann and others 2012). At base flow CO2 levels near the confluence of the 

LCR are often above 100 ppm and increase upstream (Robinson and others 1996, Dennis Stone 

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FWS, personal communication). Such high levels of CO2 have the potential to structure the fish 

community within the LCR, but little is known about CO2 tolerances of humpback chub or other 

native Colorado River fishes. Measures of upper lethal CO2 tolerances will be made in the 

laboratory for all fish species commonly found within the LCR and for invasive nonnative fishes 

that could become established within the LCR. Both adult and juvenile life stages will be 

evaluated. Captive reared humpback chub from the Southwestern Native Aquatic Research and 

Recovery Center in Dexter New Mexico will be utilized for these studies. All other species will 

be captured from the LCR in Grand Canyon.

Project Element 7.8. Evaluate effects of Asian tapeworm infestation on juvenile humpback chub 

(Recommended for funding FY15: $16,820)

David Ward, Fishery Biologist, USGS, GCMRC

The objective of this project is to monitor the extent of Asian fish tapeworm 

(Bothriocephalus acheilognathi) infestation in juvenile humpback chub annually in the LCR and 

assess potential impacts to humpback chub populations. Asian fish tapeworm has been identified 

as one of six potential threats to the continued persistence of endangered humpback chub 

(USFWS 2002). It is potentially fatal to multiple age classes of fish (Schäpperclaus 1986), and 

has caused high mortality when infecting new host species (Hoffman and Schubert 1984). Asian 

fish tapeworm was first documented in the LCR in Grand Canyon in 1990 (Minckley 1996) and 

is hypothesized to be a cause of long-term declines in condition of adult humpback chub from 

the LCR (Meretsky and others 2000). The life cycle of Asian fish tapeworm is highly 

temperature dependent (Granth and Esch 1983) and management options aimed at increasing 

mainstem Colorado River water temperatures may permit Asian tapeworm to increase in number 

and range with detrimental effects to humpback chub. Monitoring is needed since no baseline 

information for tapeworm infestation in humpback chub is available. USFWS captures juvenile 

humpback chub from the LCR each summer prior to monsoon flooding for translocation into 

Grand Canyon tributary streams such as Shinumo Creek and Havasu Creek. These fish are held 

at the U.S. Fish and Wildlife Service Southwest Native Aquatic Research and Recover Center 

(SNARRC) in Dexter, New Mexico prior to being PIT tagged and translocated. They are treated 

with Praziquantel to remove Asian Tapeworm as part of this process but no efforts have been 

made to quantify tapeworm loads in these fish. We propose to non-lethally quantify tapeworm 

loads (Ward 2007) on an annual basis from humpback chub collected for translocation. Our 

objectives are to establish a baseline of tapeworm infestation levels in LCR humpback chub and 

to determine whether year-to-year variation in the prevalence of tapeworm infestation is linked 

to annual variation in growth, survival or abundance of juvenile humpback chub.

Project Element 7.9. Development of a Non-Lethal Tool to Assess the Physiological Condition of Humpback 

Chub in the Colorado and Little Colorado Rivers 

(Recommended for funding FY15: $41,876)

Kimberly Dibble, Research Biologist, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

David Ward, Fishery Biologist, USGS, GCMRC

This research focuses on laboratory work to test the feasibility of a more sensitive technique 

to assess the condition of native fish, which could then be used in the field as a non-lethal tool to 

248
monitor the health and condition of fish residing in mainstem aggregations and in the LCR. Past 

research studies using length-weight relationships and recapture data have observed differences 

in fish condition and growth between fish residing in the mainstem vs. the LCR. Findings have 

shown periodic and seasonal declines in adult humpback chub condition, where fish recovered 

more rapidly in the Colorado River than those remaining in the LCR (Meretsky and others 2000). 

Similar patterns have also been observed for juvenile humpback chub growth rates (Finch and 

others 2013; Hayes and others, unpublished data), findings that are of concern because of 

implications to humpback chub survival. However, these length/weight relationships may not 

provide an accurate assessment of the true physiological condition of fish because relationships 

change through ontogeny and seasonally (Bolger and Connolly 1989, Cone 1989, Simpkins and 

others 2003, Froese 2006), and weights may be overinflated due to ova (eggs), parasites, 

hydrated tissues (water gain following lipid loss), and/or instrument error, especially for small 

fish. Further, high summer growth of humpback chub in the LCR followed by low growth in 

early fall suggests that the energy allocation strategy of these fish shifts toward fat storage in 

preparation for winter rather than somatic growth (length or weight gain). Investment into lipid 

storage would increase the condition of humpback chub, but this is not reflected in growth 

analyses. Therefore, humpback chub monitoring of growth and condition would be improved 

through the development of a tool in the laboratory to assess the condition of native fish, which 

would eventually be incorporated into field monitoring efforts. 

Bioelectrical Impedance Analysis (BIA) is a tool that has been successfully developed for 

cyprinids and other fish species (e.g., common carp (Cyprinus carpio), brook trout (Salvelinus 

fontinalis), cobia (Rachycentron canadum), steelhead (Oncorhynchus mykiss)) in both freshwater 

and marine ecosystems (Cox and Hartman 2005, Duncan and others 2007, Hanson and others 

2010, Klefoth and others 2013); however, this technique has not been refined for native cyprinids 

such as humpback chub, roundtail chub (Gila robusta), or sucker species of interest in the 

Colorado River basin. BIA measures body condition and is based on the technology used by 

humans to estimate percentages of body fat and water when they step on an at-home digital 

scale. A low-level, safe, electrical current is passed through the human body (or fish body), and 

the level of “impedance” is measured. Fat offers more resistance to electrical current than water, 

so a human (or fish) that has a higher fat content will score higher on the impedance scale. For 

fish, a higher impedance reading correlates to better condition and indicates the fish is more 

likely to survive periods of low food availability, disease outbreaks, successfully reproduce the 

following spring, and cope with environmental perturbations. 

The temperature of the water in which a fish resides can significantly influence BIA 

readings (Klefoth and others 2013), so we will develop a suite of experimental treatments in the 

laboratory where temperature and food rations can be controlled. Throughout each experiment, 

repeated measures of impedance in hatchery-raised humpback chub and/or surrogate species 

(e.g., roundtail chub, bonytail (Gila elegans)) of varying lengths will be quantified using a 

Quantum IV Body Composition Analyzer. Relationships between impedance readings and 

proximate body composition (percent lipid, protein, carbohydrate, water, ash) of sacrificed fish 

from laboratory experiments will allow us to calibrate the models for use in subsequent field 

monitoring (we need this calibration to verify the BIA analyzer is accurately characterizing the 

condition of native fish species). Since we need to develop these relationships for multiple

species of varying lengths, this project will occur in several phases over 3 years to allow 

hatchery fish to grow to the size of comparable fish in the field. 

Project Element 7.10. Humpback chub population modelling 

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(Recommended for funding FY15: $97,556)

Charles B. Yackulic, Research Statistician, USGS, GCMRC

Maria Dzul, Fishery Biologist, USGS, GCMRC

The ultimate objective of this project is to provide better tools to understand the current state of 

the humpback chub resource (i.e., adult population size) and to predict its future state in response 

to management decisions. In some instances, better prediction will come mainly through the 

incorporation of more data (e.g., additional JCM data will help determine whether trout and 

temperature relationships developed for the LTEMP model hold), whereas other instances 

require substantial intellectual investment into building appropriate statistical models (e.g., 

efforts to incorporate data collected through remote sensors (Project Element 7.4) with data 

collected through mark-recapture techniques (Project Elements 7.1-3)). One area of emphasis in 

FY15–17 will be on better estimation of juvenile humpback chub production and outmigration, 

as well as on potential mechanisms that may explain year to year variation in these population 

processes. Another area of emphasis will be on further clarifying relationships between 

temperature, trout abundances and juvenile humpback chub population biology in the mainstem. 

Specific attention will be placed on publishing statistical models used to link temperature and 

rainbow trout analyses to humpback chub growth and survival for the LTEMP process as well as 

exploring the implications of these results for triggering management actions like mechanical 

removal of nonnative fishes. We can also envision modifying these models to jointly model 

rainbow trout abundance and humpback chub survival to provide more accurate estimates of 

uncertainty. A third area of emphasis will be on testing hypotheses about adult humpback chub 

capture probability and movement. 

D.2 Personnel and Collaborations 

The overall project lead for Research Project 7.0 is Dr. Charles Yackulic, a research 

statistician with U.S. Geological Survey, Grand Canyon Monitoring and Research Center 

(GCMRC), who specializes in population dynamics and modeling. Kirk Young, Randy 

VanHaverbeke, and Dennis Stone are fishery biologists with the U.S. Fish and Wildlife Service, 

Arizona Fish and Wildlife Conservation Office that collect and analyze fishery data from annual 

spring and fall mark-recapture studies conducted in the LCR. Bill Persons, a fishery biologist at 

GCMRC is responsible for database management, analysis, and remote PIT tag array monitoring 

in the LCR. Dr. Kim Dibble is a post-doctoral fellow and research biologist at GCMRC with 

expertise in fish physiology and metadata analysis. Maria Dzul is a fishery biologist (GCMRC) 

that specializes in data collection, modeling and data analysis of HBC production and movement.

David Ward is a fishery biologist (GCMRC) that maintains and operates the experimental 

laboratory facility at Northern Arizona University. He has expertise in experimental physiology 

with an emphasis on non-native and native fish interactions. Dr. Jeff Muehlbauer is a postdoctoral fellow and research biologist at GCMRC with expertise in ecology and life history of 

aquatic macro-invertebrates. Dr. David Rogowski is a fishery biologist with Arizona Game and 

Fish Department and is the principal investigator that collects, provides, and analyzes data as part 

of the SWEF project (6.4). Dr. Josh Korman with Ecometric Research Inc. and Dr. Michael Yard 

with (GCMRC) are co-investigators on the Natal Origin Project (9.2) that provide the necessary 

field data from the Colorado River mainstem for the JCM project. 

D.3 Deliverables 

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The work described here should lead to multiple peer-reviewed publications (i.e., at least 4), as 

well as annual reports and presentations to the GCDAMP. This project will also provide 

estimates of quantities relevant to biological opinions at regular intervals.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

By the end of FY13–14, FWS LCR system-wide sampling will have occurred four times in each 

year, JCM sampling will have occurred four times in each year, and July LCR juvenile marking 

will have occurred once per year. All data from these trips has or will be entered into the 

GCMRC fish database.

E.2. Completed Publications 

Van Haverbeke, D. R., D. M. Stone, L. G. Coggins, and M. J. Pillow. 2013. Long-Term 

Monitoring of an Endangered Desert Fish and Factors Influencing Population Dynamics. 

Journal of Fish and Wildlife Management 4:163-177.

Yackulic, C. B., M. D. Yard, J. Korman, and D. R. Van Haverbeke. 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 4:1006-1018.

E.3. Publications in progress 

Dodrill, M., C. B. Yackulic, B. Gerig, W. E. Pine, III, J. Korman, C. Finch in review. Do 

Management Actions to Restore Rare Habitat Benefit Native Fish Conservation? Distribution 

of Juvenile Native Fish among Shoreline Habitats of the Colorado River. River Research and 

Applications

Dzul, M., C. B. Yackulic, D. M. Stone, D. R. Van Haverbeke in review. Survival, growth, and 

movement of age 1-2 humpback chub, Gila cypha, in the Little Colorado River, Arizona. 

River Research and Applications

Ward, D.L. and others. In review. A laboratory evaluation of tagging related mortality and tag 

loss in juvenile humpback chub, Gila cypha. North American Journal of Fisheries 

Management.

Ward, D.L. and R. Morton-Starner. In prep. Effects of water temperature and fish size on 

predation vulnerability of humpback chub to rainbow and brown trout.

Yackulic, C. B. and others. In prep. Vital rate estimation sheds light on the relative importance 

of altered habitat and introduced rainbow trout in the decline and recovery of an endangered 

fish, humpback chub.

E.4. Presentations at GCDAMP meetings 

Dzul and others (2014) Variation in vital rates of age 1 humpback chub Gila cypha in the Little 

Colorado River. Glen Canyon Dam Adaptive Management Program Annual Reporting 

Meeting, Phoenix, AZ. POSTER – TWG and AMWG meetings.

Morton-Starner, R. and D.L. Ward (2014). An experimental evaluation of competition between 

rainbow trout and humpback chub. Glen Canyon Dam Adaptive Management Program 

Annual Reporting Meeting, Phoenix, AZ. POSTER.

Yackulic C.B. and others (2013) Recent advances in population modeling, preliminary estimates, 

and their relevance to BO triggers. Glen Canyon Dam Adaptive Management Program 

Annual Reporting Meeting, Phoenix, AZ. PRESENTATION – TWG.

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Yackulic C.B. and others (2014) Results from Colorado River Study Site and ongoing population 

modeling. Glen Canyon Dam Adaptive Management Program Annual Reporting Meeting, 

Phoenix, AZ. PRESENTATION – TWG.

Yackulic C.B. and others (2014) LTEMP modelling results for humpback chub and trout. 

LTEMP stakeholders workshop, Phoenix, AZ. PRESENTATION – LTEMP.

Yackulic C.B. and others (2014) LTEMP modelling results for humpback chub and trout and 

follow up. LTEMP Consensus discussions, Phoenix, AZ. PRESENTATION – LTEMP.

Ward, D.L. and R. Morton-Starner (2014). Effects of water temperature and fish size on 

predation vulnerability of humpback chub to rainbow and brown trout. Glen Canyon Dam 

Adaptive Management Program Annual Reporting Meeting, Phoenix, AZ. POSTER – TWG 

and AMWG meetings.

E.5. Presentations at professional meetings 

Dzul M. and others (2013) Assessing variation through space and time in the vital rates of 

humpback chub in the Little Colorado River. Desert Fishes Council – Flagstaff, AZ.

Dzul M. and others (2014) Spatial and temporal variation in vital rates of an endangered fish in a 

desert stream. Ecological Society of Ameria – Sacramento, CA.

Morton-Starner, R. and D.L. Ward (2014). An experimental evaluation of competition between 

rainbow trout and humpback chub. Desert Fishes Council – Flagstaff, AZ.

Yackulic C.B. and others (2012) Movement and growth in humpback chub: Using multistate 

models for inference from a mixed batch and individual tag dataset. Ecological Society of 

America – Portland, OR.

Yackulic C.B. and others (2013) Variation in vital rates in a doubly partially migratory system: 

Humpback chub in the lower Colorado River. Euring Analytical conference – Athens, GA.

Yackulic C.B. and others (2013) Disentangling residency and migration in a partial migratory 

system where detection is much less than one. Ecological Society of America – Minneapolis, 

MN.

Yackulic C.B. and others (2013) A quantitative life history of humpback chub that spawn in the 

Little Colorado River: variation in movement, growth and survival. Desert Fishes Council –

Flagstaff, AZ.

Ward, D.L. and R. Morton-Starner. Effects of water temperature and turbidity on predation 

vulnerability of juvenile humpback chub to rainbow trout and brown trout. Desert Fishes 

Council – Flagstaff, AZ.

F. References 

Alabaster, J.S., Herbert, D.W.H., and He-mens, J., 1957, The survival of rainbow trout (Salmo 

gairdneri Richardson) and perch (Perca fluviatilis L.) at various concentrations of dissolved 

oxygen and carbon dioxide: Annals of Applied Biology, v. 45, p. 177-188.

Baumann , H., Talmage,S.C., and Gobler, C.J., 2012, Reduced early life growth and survival in a 

fish in direct response to increased carbon dioxide: Nature Climate Change, v. 2, p. 38-41.

Basu, S.P., 1959, Active respiration of fish in relation to ambient concentrations of oxygen and 

carbon dioxide: Journal of the Fisheries Research Board of Canada, v. 16, no. 2, p. 175-212.

Coggins, L.G., Jr., Pine, W.E., III, Walters, C.J., and Martell, S.J.D., 2006, Age-structured markrecapture analysis--a virtual population-analysis-based model for analyzing age-structured 

capture-recapture data: North American Journal of Fisheries Management, v. 26, no. 1, 

http://www.tandfonline.com/doi/abs/10.1577/M05-133.1.

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Coggins, L.G., Jr., and Walters, C.J., 2009, Abundance trends and status of the Little Colorado 

River population of humpback chub--an update considering data from 1989-2008: U.S. 

Geological Survey Open-File Report 2009-1075, 18 p., http://pubs.usgs.gov/of/2009/1075/.

Cross, W.F., Baxter, C.V., Donner, K.C., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O., Jr., 

Wellard-Kelly, H.A., and Rogers, R.S., 2011, Ecosystem ecology meets adaptive 

management--food web response to a controlled flood on the Colorado River, Glen Canyon: 

Ecological Applications, v. 21, no. 6, p. 2016-2033, 

http://www.esajournals.org/doi/abs/10.1890/10-1719.1. 

Fisher, S.G., Gray, L.J., Grimm, N.B., and Busch, D.E., 1982, Temporal succession in a desert 

stream ecosystem following flash flooding: Ecological Monographs, v. 52, no. 1, p. 93-110, 

http://www.jstor.org/stable/pdfplus/2937346.pdf.

Granath, W.O., Jr., and Esch, G.W., 1983, Seasonal dynamics of Bothriocephalus acheilognathi

in ambient and thermally altered areas of a North Carolina cooling reservoir: Proceedings of 

the Helminthological Society Washington, v. 50, no. 2, p. 205-218, 

http://bionames.org/bionames-archive/issn/0018-0130/50/205.pdf.

Heinen, J.M., Hankins, J.A., Weber, A.L., and Watten, B.J., 1969, A semiclosed recirculatingwater system for high- density culture of rainbow trout: The Progressive Fish-Culturist, v. 58, 

p. 11-22.

Hoffman, G.L., and Schubert, G., 1984, Some parasites of exotic fishes, in Courtenay, W.R.J., 

and Stauffer, J.R.J., eds., Distribution, biology, and management of exotic fishes: Baltimore, 

Md., Johns Hopkins University Press, p. 233-261.

Kaeding, L.R., and Zimmerman, M.A., 1983, Life history and ecology of the humpback chub in 

the Little Colorado and Colorado Rivers of the Grand Canyon: Transactions of the American 

Fisheries Society, v. 112, no. 5, p. 577-594, http://dx.doi.org/10.1577/1548-

8659(1983)112<577:LHAEOT>2.0.CO;2.

Mattes, W.P., 1993, An evaluation of habitat conditions and species composition above, in and 

below the Atomizer Falls complex of the Little Colorado River: Tucson, University of 

Arizona, M.S. thesis, 105 p.

Meretsky, V.J., Valdez, R.A., Douglas, M.E., Brouder, M.J., Gorman, O.T., and Marsh, P.C., 

2000, Spatiotemporal variation in length-weight relationships of endangered humpback chub-

-implications for conservation and management: Transactions of the American Fisheries 

Society, v. 129, no. 2, p. 419-428, http://dx.doi.org/10.1577/1548-

8659(2000)129<0419:SVILWR>2.0.CO;2.

Minckley, C.O., 1996, Observations on the biology of the humpback chub in the Colorado River 

Basin, 1980-1990: Flagstaff, Northern Arizona University, Ph.D. dissertation, 218 p.

Robinson, A.T., Kubly, D.M., Clarkson, R.W., and Creef, E.D., 1996, Factors limiting the 

distribution of native fishes in the Little Colorado River, Grand Canyon, Arizona: The 

Southwestern Naturalist, v. 41, no. 4, p. 378-387, http://www.jstor.org/stable/30055194.

Schäperclaus, W., 1986, Fish diseases, Vol. 2: Berlin, Akademie-Verlag.

253
U.S. Fish and Wildlife Service, 2002, Humpback chub (Gila cypha) recovery goals--amendment 

and supplement to the humpback chub recovery plan: Denver, Colo., U.S. Fish and Wildlife 

Service, Mountain-Prairie Region 6.

U.S. Fish and Wildlife Service, 2011, Final biological opinion on the operation of Glen Canyon 

Dam including high flow experiments and non-native fish control: Phoenix, Ariz., submitted 

to Bureau of Reclamation, Salt Lake City, Utah, 150 p.

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, 

http://dx.doi.org/10.3996/082012-JFWM-071.

Walters, C.J., and Martell, S.J.D., 2004, Fisheries ecology and management: Princeton, N.J., 

Princeton University Press.

Ward, D.L., 2007, Removal and quantification of Asian tapeworm from bonytail chub using 

Praziquantel: North American Journal of Aquaculture, v.69, p. 207-210.

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, p. 1006-1018.

 

254
G. Budget 

Project Element 7.1. Annual 

spring/fall humpback chub 

abundance estimates in the 

lower 13.6 km of the Little 

Colorado River

Project Element 7.2. Juvenile 

Chub Monitoring in the 

mainstem near the Little 

Colorado River Confluence

Project Element 7.3. July 

Little Colorado River 

juvenile humpback chub 

marking to estimate 

production and 

outmigration

Salaries $ 23,200.00 Salaries $ 93,600.00 Salaries $ 62,500.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ 4,000.00

Operating Expenses $ 15,500.00 Operating Expenses $ 8,900.00 Operating Expenses $ 5,400.00

Logistics $ 90,800.00 Logistics $ 135,800.00 Logistics $ 24,800.00

Cooperators (non-USGS) $ 370,000.00 Cooperators (non-USGS) $ 215,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 31,820.00 USGS Burden $ 44,578.00 USGS Burden $ 15,472.00

Total $ 531,320.00 Total $ 497,878.00 Total $ 112,172.00

Project Element 7.4 Remote PIT 

tag array monitoring

Project Element 7.5. Food web 

monitoring in the Little Colorado 

River

Project Element 7.6. 

Potential for gravel 

substrate limitation for 

humpback chub 

reproduction in the LCR

Salaries $ 34,700.00 Salaries $ 114,800.00 Salaries $ 5,400.00

Traveling and Training $ - Traveling and Training $ 2,000.00 Traveling and Training $ 500.00

Operating Expenses $ 3,500.00 Operating Expenses $ 1,000.00 Operating Expenses $ 1,000.00

Logistics $ 3,600.00 Logistics $ 4,200.00 Logistics $ 3,100.00

Cooperators (non-USGS) $ 5,000.00 Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 6,838.00 USGS Burden $ 19,520.00 USGS Burden $ 1,600.00

Total $ 53,638.00 Total $ 141,520.00 Total $ 11,600.00

Project Element 7.7. Evaluate 

CO2 as a limiting factor early 

life history stages of humpback 

chub in the Little Colorado River

Project Element 7.8. Evaluate 

effects of Asian tapeworm 

infestation on juvenile 

humpback chub 

Project Element 7.9. 

Development of a NonLethal Tool to Assess the 

Physiological Condition 

of Humpback Chub in the 

Colorado and Little 

Colorado Rivers

Salaries $ 53,500.00 Salaries $ 11,000.00 Salaries $ 27,900.00

Traveling and Training $ 3,000.00 Traveling and Training $ 2,000.00 Traveling and Training $ 1,500.00

Operating Expenses $ 18,000.00 Operating Expenses $ 1,500.00 Operating Expenses $ 6,700.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 11,920.00 USGS Burden $ 2,320.00 USGS Burden $ 5,776.00

Total $ 86,420.00 Total $ 16,820.00 Total $ 41,876.00

Project Element 7.10. Humpback 

chub population modelling

Salaries $ 82,000.00

Traveling and Training $ 2,000.00

Operating Expenses $ 100.00

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 13,456.00

Total $ 97,556.00

FY 2015

FY 2015 Project 7 Gross Totals: $1,590,800.00

255
Project Element 7.1. Annual 

spring/fall humpback chub 

abundance estimates in the 

lower 13.6 km of the Little 

Colorado River

Project Element 7.2. Juvenile 

Chub Monitoring in the 

mainstem near the Little 

Colorado River Confluence

Project Element 7.3. July 

Little Colorado River 

juvenile humpback chub 

marking to estimate 

production and 

outmigration

Salaries $ 26,900.00 Salaries $ 96,700.00 Salaries $ 56,200.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ 4,000.00

Operating Expenses $ 8,300.00 Operating Expenses $ 9,000.00 Operating Expenses $ 5,300.00

Logistics $ 98,100.00 Logistics $ 135,800.00 Logistics $ 26,800.00

Cooperators (non-USGS) $ 370,000.00 Cooperators (non-USGS) $ 215,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 40,426.00 USGS Burden $ 59,580.00 USGS Burden $ 20,306.00

Total $ 543,726.00 Total $ 516,080.00 Total $ 112,606.00

Project Element 7.4 Remote PIT 

tag array monitoring

Project Element 7.5. Food web 

monitoring in the Little Colorado 

River

Project Element 7.6. 

Potential for gravel 

substrate limitation for 

humpback chub 

reproduction in the LCR

Salaries $ 79,900.00 Salaries $ 70,000.00 Salaries $ 5,600.00

Traveling and Training $ - Traveling and Training $ 2,000.00 Travel and Training $ 300.00

Operating Expenses $ 3,500.00 Operating Expenses $ - Operating Expenses $ 1,000.00

Logistics $ 3,900.00 Logistics $ - Logistics $ 3,300.00

Cooperators (non-USGS) $ 5,000.00 Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 19,356.00 USGS Burden $ 15,840.00 USGS Burden $ 2,244.00

Total $ 111,656.00 Total $ 87,840.00 Total $ 12,444.00

Project Element 7.7. Evaluate 

CO2 as a limiting factor early 

life history stages of humpback 

chub in the Little Colorado River

Project Element 7.8. Evaluate 

effects of Asian tapeworm 

infestation on juvenile 

humpback chub 

Project Element 7.9. 

Development of a NonLethal Tool to Assess the 

Physiological Condition 

of Humpback Chub in the 

Colorado and Little 

Colorado Rivers

Salaries $ 59,500.00 Salaries $ 11,300.00 Salaries $ 71,600.00

Traveling and Training $ 3,000.00 Traveling and Training $ 2,000.00 Traveling and Training $ -

Operating Expenses $ 18,000.00 Operating Expenses $ 500.00 Operating Expenses $ 6,700.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 17,710.00 USGS Burden $ 3,036.00 USGS Burden $ 17,226.00

Total $ 98,210.00 Total $ 16,836.00 Total $ 95,526.00

Project Element 7.10. Humpback 

chub population modelling

Salaries $ 121,000.00

Traveling and Training $ 2,000.00

Operating Expenses $ 100.00

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 27,082.00

Total $ 150,182.00

FY 2016

FY 2016 Project 7 Gross Totals: $1,745,106.00

256
Project Element 7.1. Annual 

spring/fall humpback chub 

abundance estimates in the 

lower 13.6 km of the Little 

Colorado River

Project Element 7.2. Juvenile 

Chub Monitoring in the 

mainstem near the Little 

Colorado River Confluence

Project Element 7.3. July 

Little Colorado River 

juvenile humpback chub 

marking to estimate 

production and 

outmigration

Salaries $ 22,400.00 Salaries $ 67,100.00 Salaries $ 63,600.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ 4,000.00

Operating Expenses $ 8,400.00 Operating Expenses $ 9,000.00 Operating Expenses $ 5,300.00

Logistics $ 105,300.00 Logistics $ 26,300.00 Logistics $ 28,800.00

Cooperators (non-USGS) $ 370,000.00 Cooperators (non-USGS) $ 50,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 49,208.00 USGS Burden $ 30,172.00 USGS Burden $ 28,476.00

Total $ 555,308.00 Total $ 182,572.00 Total $ 130,176.00

Project Element 7.4 Remote PIT 

tag array monitoring

Project Element 7.5. Food web 

monitoring in the Little Colorado 

River

Project Element 7.6. 

Potential for gravel 

substrate limitation for 

humpback chub 

reproduction in the LCR

Salaries $ 99,000.00 Salaries $ - Salaries $ 5,900.00

Traveling and Training $ - Traveling and Training $ 2,000.00 Traveling and Training $ 300.00

Operating Expenses $ 3,500.00 Operating Expenses $ - Operating Expenses $ 1,000.00

Logistics $ 4,200.00 Logistics $ - Logistics $ 3,600.00

Cooperators (non-USGS) $ 5,000.00 Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 30,026.00 USGS Burden $ 560.00 USGS Burden $ 3,024.00

Total $ 141,726.00 Total $ 2,560.00 Total $ 13,824.00

Project Element 7.7. Evaluate 

CO2 as a limiting factor early 

life history stages of humpback 

chub in the Little Colorado River

Project Element 7.8. Evaluate 

effects of Asian tapeworm 

infestation on juvenile 

humpback chub 

Project Element 7.9. 

Development of a NonLethal Tool to Assess the 

Physiological Condition 

of Humpback Chub in the 

Colorado and Little 

Colorado Rivers

Salaries $ 71,400.00 Salaries $ 11,900.00 Salaries $ 74,400.00

Traveling and Training $ 3,000.00 Traveling and Training $ 2,000.00 Traveling and Training $ -

Operating Expenses $ 18,000.00 Operating Expenses $ 500.00 Operating Expenses $ 6,700.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 25,872.00 USGS Burden $ 4,032.00 USGS Burden $ 22,708.00

Total $ 118,272.00 Total $ 18,432.00 Total $ 103,808.00

Project Element 7.10. Humpback 

chub population modelling

Salaries $ 157,500.00

Traveling and Training $ 2,000.00

Operating Expenses $ 100.00

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 44,688.00

Total $ 204,288.00

FY 2017 Project 7 Gross Totals: $1,470,966.00

FY 2017 

257
Project 8. Management Actions to Increase Abundance 

and Distribution of Native Fishes in Grand Canyon 

A. Investigators 

David Ward, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

William Persons, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Scott VanderKooi, Supervisory Biologist, U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center 

Kirk Young, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and Wildlife 

Conservation Office

Dennis Stone, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and Wildlife 

Conservation Office

David R. VanHaverbeke, Fishery Biologist, U.S. Fish and Wildlife Service, Arizona Fish and 

Wildlife Conservation Office

Brian Healy, Fishery Biologist, National Park Service, Grand Canyon National Park

Clay Nelson, Fishery Biologist, National Park Service, Grand Canyon National Park

Emily Omana, Fishery Biologist, National Park Sservice, Grand Canyon National Park

David Rogowski, Fisheries Biologist, Arizona Game and Fish Department

B. Project Summary 

This project encompasses two ongoing management actions and two new projects, all 

designed to increase survival of juvenile native fishes in Grand Canyon. In addition, we propose 

to convene a protocol evaluation panel comprised of external experts to conduct a review of the 

fisheries research, monitoring, and management actions conducted in support of the Glen 

Canyon Dam Adaptive Management Program (GCDAMP). In FY15–17 we will continue 

ongoing mechanical removal of rainbow trout (Oncorhynchus mykiss) and brown trout (Salmo 

trutta) using electrofishing near the confluence of Bright Angel creek, to reduce predation on 

juvenile native fish. We will also continue to translocate juvenile humpback chub (Gila cypha) 

annually from the Little Colorado River (LCR) into areas within the LCR and continue to 

support translocation efforts into Havasu Creek and Shinumo Creek, to increase survival and 

distribution of humpback chub. In FY16 or FY17 we will participate in a review by external 

experts of these activities and other fisheries projects (see Projects 6, 7, and 9). The review of 

Project 8 activities will emphasize evaluation of the effectiveness of these management actions 

and the panelists will be asked to make recommendations as to whether the continuation of these 

efforts is warranted in future years. This project also includes two new project elements that will 

inform future potential management actions: 1). An assessment of invasive aquatic species 

within the LCR drainage, to evaluate potential risks to humpback chub populations and 2.) 

Genetic monitoring of humpback chub to confirm that ongoing management activities do not 

have detrimental effects on the genetics of the Grand Canyon population of this endangered 

species. 

258
C. Background 

Fish populations are typically limited by survival and recruitment of juvenile fish (Myers 

1995). Endangered humpback chub in Grand Canyon are also believed to be limited by survival 

and recruitment of juvenile fish (Coggins and Walters, 2009; Hayden and others, 2012; Limburg 

and others, 2013). Management actions for humpback chub have focused on trying to reduce 

predation mortality of juvenile fish by either mechanically removing predatory trout from the 

mainstem Colorado River, or by translocating juvenile humpback chub from the lower LCR into 

other areas to improve growth and subsequent survival. Predation mortality in fish is highly size 

dependent with smaller fish being much more vulnerable to predation than larger individuals 

(Bailey and Houde, 1989). Increases in growth rate generally leads to higher survival and less 

predation mortality (Tonn and Paszkowski, 1992). These general patterns are also true for 

humpback chub in Grand Canyon (Ward and Morton-Starner, in prep). Translocation of juvenile 

humpback chub from the LCR into other areas with lower fish densities and higher food 

abundance is one way to increase growth rates and potentially increase subsequent survival. 

Management activities to benefit native fishes that were funded in the USGS Grand Canyon 

Monitoring and Research Center’s FY13–14 workplan included a collaborative effort with the 

National Park Service (NPS) to mechanically remove Brown trout from the Colorado River 

mainstem near the confluence of Bright Angel Creek and a U.S. Fish and Wildlife Service led 

project to translocate juvenile humpback chub from the LCR into areas above the 

Chute/Atomizer Falls complex, within the LCR. Support was also provided for NPS efforts to 

collect juvenile humpback chub from the LCR for translocation into Shinumo and Havasu 

Creeks. 

C.1. Management Background 

Humpback chub have declined in both abundance and distribution likely because of 

interactions with nonnative species and the alteration of flow and temperature regimes caused by 

construction and operation of Glen Canyon Dam (Minckley and Marsh, 2009). Introduced 

rainbow trout and brown trout are known to prey upon juvenile native fish, including humpback 

chub, in Grand Canyon (Yard and others, 2011). Predation by these nonnative species may 

adversely affect native fishes at a population level. To reduce potential predation on humpback 

chub, electrofishing was used to mechanically remove nonnative fish from the Colorado River 

near the confluence with the LCR, from 2003–2006, and again in 2009 (Coggins and others, 

2011). Humpback chub abundance increased following removal efforts, but system-wide 

decreases in rainbow trout and drought induced increases in water temperature occurred during 

the same period making it difficult to determine which factors were responsible for increased 

native fish abundance (Coggins and others, 2011). 

Brown trout are of particular concern for native fishes in Grand Canyon because of their 

highly piscivorous nature (Yard and others, 2011, Ward and Morton-Starner, in prep). The 

highest densities of brown trout in Grand Canyon occur in or near Bright Angel Creek 

(Makinster and others, 2010). Large numbers of brown trout in this area may be limiting native 

fish abundance, including humpback chub, locally as well as downstream. This idea is based on 

the hypothesis that most of the humpback chub inhabiting western Grand Canyon are produced 

within the LCR and disperse downstream. If the bottleneck to dispersal and recruitment of 

humpback chub or other native fish species in western Grand Canyon is occurring near the 

confluence of Bright Angel Creek because of brown trout predation, then removing brown trout 

from this area could increase the number of native fish that inhabit downstream reaches. 

259
Removal of brown trout in the mainstem Colorado River near the confluence of Bright Angel 

Creek occurred in 2013, and is scheduled to occur again in November 2014. The 2013 high Flow 

Experiment caused mechanical removal efforts at Bright Angel Creek to be reduced from 10 

depletions to 5 depletions, and high turbidity throughout much of the removal effort reduced 

capture efficiency significantly such that only 1,851 fish were removed (Nelson and others, 

2014). The effectiveness of this management action cannot be adequately evaluated without at 

least one more year of removal effort. Mainstem mechanical removal of nonnative fish near the 

confluence of the LCR is a prescriptive management action that is only implemented when a set 

of criteria outlined in the 2011 Biological Opinion for Operation of Glen Canyon Dam (U.S. Fish 

and Wildlife Service, 2011) are met, but mainstem mechanical removal near the confluence of 

Bright Angel Creek is being evaluated as an experimental management action as described in the 

Park Service Comprehensive Fisheries Management Plan (NPS, 2013).

Efforts to translocate humpback chub upstream of Chute Falls in the LCR and to monitor 

their status have been ongoing annually since 2003. Approximately 2,363 juvenile (70-130 mm 

total length; TL) humpback chub have been translocated upstream of Chute Falls through 2013.

In 2003, the action was identified as a voluntary conservation action to offset potential impacts 

on humpback chub from proposed experimental releases from Glen Canyon Dam and mainstem 

mechanical removal of nonnative fish. Since 2012, translocation and monitoring efforts of 

humpback chub in this upper portion of the LCR corridor have been incorporated as a 

conservation measure in the recent Final Biological Opinion on the Operation of Glen Canyon 

Dam (U.S. Fish and Wildlife Service, 2011).

C.2 Key Monitoring and Research Questions Addressed in this Project 

This project addresses two Adaptive Management Work Group (AMWG) priority Questions 

1: Why are humpback chub not thriving? and 2: What are the most limiting factors to successful 

humpback chub adult recruitment in the mainstem Colorado River?

This project directly addresses the following Strategic Science Questions (SSQs), Core 

Monitoring Information Needs (CMINs), Science advisory summary questions (SA), and 

Research Information Needs (RINs) previously identified by the GCDAMP in the 2007 Grand 

Canyon Monitoring and Research Plan:

Primary SSQ addressed:

• SSQB2. What are the most effective strategies and control methods to limit nonnative 

fish predation on, and competition with native fishes? 

Primary Core Monitoring Information Needs addressed:

• CMIN SA 1. Which of the following are the most limiting factors to successful HBC 

adult recruitment in the mainstem: spawning success, predation on YoY and juveniles, 

habitat (water, temperature), pathogens, adult maturation, food availability, or 

competition?

Research Information Needs addressed:

• RIN 2.4. To what degree, which species, and where in the system are exotic fish a 

detriment to the existence of native fish through predation or competition?

This project will answer the following key questions about impacts of nonnative fish on 

native fish within Grand Canyon:

260
1. What is the efficacy and feasibility of using electrofishing to control brown trout 

populations through a coordinated mainstem and tributary removal effort in and around 

Bright Angel Creek.

2. Does brown trout removal have a measurable positive effect on native fish abundance 

and distribution in the mainstem near Bright Angel Creek or within Bright Angel Creek?

3. Can translocation of Juvenile Humpback chub from the Little Colorado River into 

uninhabited locations increase survival and recruitment of juvenile chub?

D. Proposed Work 

D.1. Project Elements 

Project Element 8.1. Efficacy and Ecological Impacts of Brown Trout Removal at Bright Angel Creek 

(Recommended for funding FY15: $96,396)

David Ward, Fishery Biologist, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

Scott VanderKooi, Supervisory Biologist, USGS, GCMRC

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

Emily Omana, Fishery Biologist, NPS, Grand Canyon National Park

Clay Nelson, Fishery Biologist, NPS, Grand Canyon National Park

The objective of this project is to evaluate the feasibility and efficacy of brown trout removal 

in and around Bright Angel Creek using electrofishing, and to assess the response of native fish 

to brown trout removal. A multi-year, brown trout removal treatment using mechanical removal 

began in 2013 and will be applied to the mainstem Colorado River complimenting ongoing NPS 

efforts in Bright Angel Creek. The objective is to significantly reduce brown trout abundance by 

75–80%. Removal in the Colorado River mainstem will occur in a 8.45 km (5.25 mile) reach of 

Upper Granite Gorge (river miles 85 to 90) using electrofishing depletion methods similar to 

those used from 2003 to 2006 at the confluence of the LCR (Coggins and others, 2011). 

Electrofishing removals on the mainstem Colorado River will occur during the fall-winter season 

and will compliment ongoing NPS operation of a weir and multi-pass depletions by backpack 

electrofisher within Bright Angel Creek from October to March. Efforts in the mainstem will 

consist of 5 to 10-pass depletions with a single pass occurring over the entire study area in two 

nights (amount of effort based on calculated capture probabilities with a goal of 75% reduction 

in brown trout numbers). It has been estimated that each trip will consist of 10-20 nights of 

sampling. All electrofishing will be conducted at night using two 16’ sport boats outfitted for 

electrofishing with a Coffelt® or equivalent CPS unit with one netter per boat. Large numbers of

brown trout (> 2,000 fish) are likely to be removed. These fish will be put beneficial use as 

described in NPS’s Comprehensive Fish Management Plan (NPS, 2013) and its associated 

Section 106 consultation with Native American tribes. To determine efficacy and ecological 

consequences of brown trout removal, densities and conditions of native fishes will be monitored 

by NPS in Bright Angel Creek and by GCRMC in areas near its confluence. Continued native 

fish monitoring (see Project Element 6.4), both within the removal area and in other areas 

downstream, are needed to assess if increased dispersal of native fish is occurring as a result of 

removal efforts. This project was initiated in 2013–2014 (Nelson and others, 2014) and we 

261
propose that this experimental management action be continued in FY15 with possible extension 

through FY17.

Project Element 8.2. Translocation and monitoring of Humpback chub above Chute Falls in the Little Colorado 

River 

(Recommended for funding FY15: $88,690)

Dennis Stone, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

D. R. VanHaverbeke, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

William Persons, Fishery Biologist, USGS, GCMRC

The objective of this project is to increase the survival of up to 1,000 juvenile humpback 

chub annually by translocating them from the lower Little Colorado River (LCR) into areas 

above the Chute /Atomizer Falls complex in the LCR or into Shinumo Creek or Havasu Creeks. 

These locations all have low densities of large-bodied fish and high food abundance (Robinson 

and others 1996; Spurgeon, 2012), which would presumably lead to increased growth rates and 

higher likelihood of survival. In the December 2002 and November 2004 Biological Opinions on 

the proposed experimental releases from Glen Canyon Dam and removal of nonnative fish 

within the Colorado River, a conservation action was identified to relocate approximately 300 

humpback chub (50-100 mm TL) in 2003 and 2004, and another 600 fish in 2005 from near the 

LCR confluence to an upstream LCR reach above Chute Falls that was previously unoccupied by 

this species. Additional translocations ensued following the recommendations of other Biological 

Opinions. Translocation and monitoring efforts of humpback chub in this upper portion of the 

LCR corridor have since been incorporated as a conservation measure in the recent Final 

Biological Opinion on the Operation of Glen Canyon Dam Including High Flow Experiments 

and Non-Native Fish Control (U.S. Fish and Wildlife Service, 2011). Through 2013, 2,363 

juvenile (50–130 mm TL) humpback chub have been translocated upstream of Chute Falls 

(Stone and others, in prep). From 2003 to 2013, 777 unique humpback chub (i.e., counted only 

once) have been captured above Chute Falls, of which 369 were adults (≥ 200 mm). 

Additionally, 1,540 unique humpback chub (893 were ≥ 200 mm) were captured directly 

downriver in the small 0.5 km Atomizer reach. The rapid growth rates of humpback chub in 

these two reaches may have resulted in many individuals losing their elastomer tags before they 

were recaptured, making it difficult to distinguish the provenance of many of these fish (i.e., 

translocated, progeny, or upriver migrants); however, all humpback chub translocated since 2008 

have been PIT-tagged before being released. From 2006 to 2009, two-pass mark recapture 

population estimates of humpback chub were conducted annually in the Atomizer reach and 

above Chute Falls, after which capture probabilities have been used to estimate the populations. 

Monitoring will continue to occur during the spring, prior to monsoon flooding to evaluate the 

retention and growth rates of translocated humpback chub.

Project Element 8.3.Glen Canyon Dam Adaptive Management Program Fisheries Research, Monitoring, and 

Management Actions Protocol Evaluation Panel 

(Recommended for funding FY15: $0)

Scott VanderKooi, Supervisory Biologist, USGS, GCMRC

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

262
Brian Healy, Fishery Biologist, NPS, Grand Canyon National Park

David Rogowski, Fisheries Biologist, Arizona Game and Fish Department

An external review panel comprised of scientists with relevant expertise will be convened in 

either FY16 or FY17 to ensure that the quality and relevance of fisheries science being 

conducted by GCMRC and its cooperators is held to the highest of standards. This panel will 

conduct a review of all aspects of the GCRMC fisheries program described in Projects 6, 7, 8, 

and 9 of the FY15–17 workplanThey will make recommendations regarding the scope and 

direction of the program as well as provide an evaluation and recommendations for future work 

with respect to the level of effort, study design, and relevance of individual research activities. 

Project Element 8.4. Little Colorado River Invasive Aquatic Species Surveillance 

(Recommended for funding FY15: $0)

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

Dennis Stone, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office

David Ward, Fishery Biologist, USGS, GCMRC

Bill Persons, Fishery Biologist, USGS, GCMRC

David Rogowski, Fisheries Biologist, AGFD

The objective of this project is to identify surveillance sites within the LCR basin upstream 

of Grand Canyon that can provide early detection and response for emerging deleterious invasive 

aquatic species within the LCR drainage. If invasive species deleterious to humpback chub are 

detected, we will develop and implement a rapid response plan. In Arizona, dozens of aquatic 

invasive species have been introduced (fish, mollusks, crustaceans), have expanded distributional 

ranges, and pose a growing threat to native aquatic species. The first line of defense for reducing 

the impact from invasive species is preventing their introduction and establishment. Multiple 

management agencies, notably state wildlife agencies, maintain active invasive species 

prevention programs. Even the best prevention efforts cannot stop all invasive species, and thus, 

early detection, rapid assessment and Rapid Response actions represent a critical second defense.

In Grand Canyon, the LCR is the largest tributary and primary spawning ground for 

humpback chub, however, the species is limited to the lower 15 km of the system (Douglas and 

Marsh, 1996; Gorman and Stone, 1999). The LCR encompasses a basin of about 8,100 m2 in 

eastern Arizona and western New Mexico, with its perennial headwaters arising near Mt. Baldy, 

Arizona. Estimates of surface water supply and contemporary cultural depletions by the Arizona 

Department of Water Resources (1989; 1990; 1994) feed approximately 95 reservoirs and 3,700 

stock tanks. Reservoirs and stock tanks are potential sources of invasive species and many drain 

into the LCR or its tributaries. Large quantities of human derived debris in the LCR in Grand 

Canyon illustrate the connectivity of the river in Grand Canyon to upper portions of the 

watershed. Biological connectivity also exists based on the capture of red shiner (Cyprinella 

lutrensis), common carp (Cyprinus carpio), fathead minnow (Pimephales promelas), black 

bullhead (Ameiurus melas), and plains killifish (Fundulus zebrinus) at Grand Falls, all thought to 

have originated hundreds of kilometers upstream (Stone and others, 2007). Conservation success 

of humpback chub in the LCR and Grand Canyon is vulnerable to incursion by invasive aquatic 

species from upstream.

A Reasonable and Prudent Alternative in the 1995 EIS was to protect humpback chub in the 

LCR by development of a LCR Management Plan (USBR, 1995). A final draft of the plan was 

completed in 2008 (Valdez and Thomas, 2009). This study will augment that plan by providing 

263
specific information and data concerning sources of non-native fish within the LCR basin. 

Surveillance sites will be assessed based on their likelihood to concentrate/harbor species, 

watershed/sub-watershed reference location, accessibility, ability to be sampled. From 6–12 sites 

will be sampled annually in May-June using passive (entanglement nets, hoop nets) and active 

(seines, electrofishers) gears as appropriate.

Project Element 8.5. Genetic monitoring of Humpback chub in Grand Canyon 

(Recommended for funding FY15: $0)

Kirk Young, Fishery Biologist, USFWS, Arizona Fish and Wildlife Conservation Office Bill 

Persons, Fishery Biologist, USGS, GCMRC

Wade Wilson, Geneticist, USFWS, Southwest Native Aquatic Resources Research and Recovery 

Center

The objectives of this project are to monitor genetic changes in the Grand Canyon population 

of humpback chub that may result because of ongoing management activities such as 

translocations. Humpback chub management actions in the lower basin of the Colorado River 

include annual population monitoring, translocations to Shinumo Creek, Havasu Creek, and the 

Chute Falls area of the LCR. In 2008, a refuge population was started at the USFWS Southwest 

Native Aquatic Resources Research and Recovery Center. As a result of these ongoing 

management actions, a small set of fin clip samples (about 30 per reach in the LCR) were taken 

to establish baseline genetic data in the LCR. An initial assessment of the LCR samples indicated 

no biologically meaningful differences between Boulders, Coyote and Salt reaches, but sample 

sizes were low. An initial and provisional assessment of Chute Falls reach showed a significantly 

higher Fst value (increased homozygosity compared to other LCR reaches) which would suggest 

genetic variation between these groups. The source of this difference, however, is uncertain. It is 

possible that the difference was due to sample error (sample size 40), or it may have indicated 

breeding by a small number of adults above Chute Falls being reflected in increased 

homozygosity of the offspring (F1) generation. In any case, funding for analyzing the LCR tissue 

samples has never been procured, and further investigation into such anomalies would appear 

warranted. Although baseline genetics data for humpback chub in the LCR and other mainstem 

aggregations has been collected, the authors of these studies stated unequivocally that sample 

sizes were low and results should be interpreted cautiously (Douglas and Douglas, 2007; 2010; 

Connie-Keeler Foster and Wade Wilson, pers. com.). 

Douglas and Douglas (2007) addressed the genetics of mainstem Colorado River humpback 

chub aggregations in Grand Canyon, and many of the results from their report were published in 

Douglas and Douglas (2010). Based on a sample size of 234 fish collected from nine areas in 

Marble and Grand Canyons, Douglas and Douglas (2010) indicated that humpback chub 

downstream from the LCR were clearly connected by gene flow, and proposed downstream drift 

of larvae and juveniles as the scenario, with the LCR population being the primary source. 

However, contribution from occasional local reproduction by mainstem aggregations could not 

be excluded. Based on excess homozygosity, Douglas and Douglas (2010) specifically stated 

local reproduction may be occasionally occurring at Middle Granite Gorge. To date, this is the 

only baseline genetics data that researchers have concerning mainstem aggregations of 

humpback chub in Grand Canyon. The sample sizes obtained by Douglas and Douglas (2007; 

2010) were generally very small, ranging from 4-26 fish from all aggregations except the LCR (n 

= 77) and Middle Granite Gorge (n = 80). This led Douglas and Douglas (2010) to suggest 

264
cautionary interpretation of some of their results, and underscores the need for additional 

baseline data.

Fin clips from approximately 300 humpback chub will be collected annually for DNA 

extraction and microsatellite genotyping. Samples will be collected throughout the LCR as well 

as from translocated fish and from fish in each of the established mainstem aggregations. It is 

expected that establishing baseline data will take 2–3 years after which only periodic sampling 

(once every 3–5 years) would be required. 

D.2 Personnel and Collaborations 

The overall lead for Project 8 is David Ward, a fishery biologist with U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center (GCMRC) with expertise in native non-native 

fish interactions. Dr. Michael Yard is a fishery biologist with GCMRC with extensive experience 

in non-native fish removal projects and Brian Healy, Clay Nelson, and Emily Omana are fishery 

biologists with Grand Canyon National Park who will provide assistance and expertise in the 

Brown Trout Removal project (8.1) and the Chute Falls Translocation Project (8.2). Kirk Young, 

Dennis Stone, and David R. VanHaverbeke are fishery biologists with the U.S. Fish and Wildlife 

Service and will provide data, analysis and reporting on the Chute Falls Translocation project 

(8.2). Kirk Young has extensive fisheries management experience and will lead the Little 

Colorado River Invasive Aquatic Species Surveillance project (8.4). Scott Vanderkoii is the 

Deputy Chief and a fishery biologist with GCMRC and will lead the Protocol Evaluation Panel 

review (Project 8.3). Dr. Wade Wilson is a geneticist with the U.S.Fish andWildlife Service 

Southwest Native Aquatic Resources Research and Recovery Center and will expertise on the 

genetic monitoring of humpback chub (8.5). Dr. David Rogowski is a fisheries biologist with 

Arizona Game and Fish Department with expertise in aquatic ecology and conservation biology 

of fish, and will lead the System Wide Electrofishing project (6.4), the brown trout natal origins 

project (6.5) and the Lees Ferry Creel Survey project (6.8) and will provide management 

experience to the project elements in Project 8.

D.3 Deliverables 

Project elements will produce annual progress reports submitted to GCMRC and peer 

reviewed publications at project completions.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

Healy, B., C. Nelson, E. O. Smith, and A. Martin. Bright Angel Creek Trout Control Project. 

National park Service Trip Report. February 2013. 

Nelson C., D. Ward, B. Healy, and E. O. Smith. Bright Angel Creek inflow trout reduction pilot 

study. Trip report submitted to GCMRC. February 2014.

Stone D. Summer 2013 monitoring and translocation of humpback chub (Gila cypha) above 

Lower Atomizer falls in the Little Colorado River, Arizona. Trip Report submitted to 

GCMRC. July 2013.

E.2. Publications in progress 

Stone D., D. Van Haverbeke, M. Pillow, J. Walters, M. Cantrell, and K. Young. Translocation of 

Endangered Humpback Chub above Chute Falls in the Little Colorado River, Arizona. In 

prep . North American Journal of Fisheries Management. 

265
Ward, D.L. and others. In review. A laboratory evaluation of tagging related mortality and tag 

loss in juvenile humpback chub, Gila cypha. In Review. North American Journal of Fisheries 

Management.

Ward, D.L. and R. Morton-Starner. In prep. Effects of water temperature and fish size on 

predation vulnerability of humpback chub to rainbow and brown trout.

E.3. Presentations at GCDAMP meetings 

Morton-Starner, R. and D.L. Ward. 2014. An experimental evaluation of competition between 

rainbow trout and humpback chub. Glen Canyon Dam Adaptive Management Program 

Annual Reporting Meeting, Phoenix, AZ. POSTER.

Ward, D.L. and R. Morton-Starner. 2014. Effects of water temperature and fish size on predation 

vulnerability of humpback chub to rainbow and brown trout. Glen Canyon Dam Adaptive 

Management Program Annual Reporting Meeting, Phoenix, AZ. POSTER – TWG and 

AMWG meetings.

E.4. Presentations at professional meetings 

Morton-Starner, R. and D. L. Ward 2014. An experimental evaluation of competition between 

rainbow trout and humpback chub. Desert Fishes Council – Flagstaff, AZ.

Stone D. M. Translocation of Humpback Chub above Chute Falls in the Little Colorado River, 

Arizona. The 47th Joint Annual Meeting of the Arizona/New Mexico Chapter of the 

American Fisheries Society, Hon-Dah Resort and Casino, Pinetop, Arizona. February 2014.

Ward, D. L. and R. Morton-Starner. Effects of water temperature and turbidity on predation 

vulnerability of juvenile humpback chub to rainbow trout and brown trout. Desert Fishes 

Council – Flagstaff, AZ.

F. References 

Arizona Department of Water Resources, 1989, Hydrology of the Little Colorado River system--

special report to the settlement committee, in The general adjudication of the Little Colorado 

River system and source: Phoenix, Arizona Department of Water Resources.

Arizona Department of Water Resources, 1990, Hydrographic survey report for the Silver Creek 

watershed, vol. I--general assessment, filed with the court November 30, 1990.

Arizona Department of Water Resources, 1994, Little Colorado River settlement committee 

group “A”--in-basin negotiating committee assessment of Chevelon Creek, Clear Creek, and 

Jacks Canyon watersheds. 

Bailey, K.M., and Houde, E.D., 1989, Predation on early developmental stages of marine fishes 

and the recruitment problem: Advances in Marine Biology v. 25, p. 1–83.

Coggins, L.G., Jr., and Walters, C.J., 2009, Abundance trends and status of the Little Colorado 

River population of humpback chub--an update considering data from 1989-2008: U.S. 

Geological Survey Open-File Report 2009-1075, 18 p., http://pubs.usgs.gov/of/2009/1075/.

Coggins, L.G., Yard, M.D., and Pine, W.E., 2011, Nonnative fish control in the Colorado River 

in Grand Canyon, Arizona--an effective program or serendipitous timing?: Transactions of 

the American Fisheries Society, v. 140, no. 2, p. 456-470, 

http://dx.doi.org/10.1080/00028487.2011.572009.

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, http://www.jstor.org/stable/1446938.

266
Douglas, M.R., and Douglas, M.E., 2007, Genetic structure of humpback chub Gila cypha and 

roundtail chub G. robusta in the Colorado River ecosystem--final report: Fort Collins, 

Department of Fish, Wildlife and Conservation Biology, Colorado State University, 99 p., 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/07jun25/Attach_04.pdf.

Douglas, M.R., and Douglas, M.E., 2010, Molecular approaches to stream fish ecology, in Gido, 

K.B., and Jackson, D.A., eds., Community ecology of stream fishes--concepts, approaches, 

and techniques, Ottawa, Ontario, Canada, August 19-20, 2008, Proceedings of the American 

Fisheries Society Symposium 73: v. 73, p. 157–195.

Gorman, O.T., and Stone, D.M., 1999, Ecology of spawning humpback chub, Gila cypha, in the 

Little Colorado River near Grand Canyon, Arizona: Environmental Biology of Fishes, v. 55, 

no. 1-2, p. 115-33, http://www.springerlink.com/content/vq675171n84786p7/.

Hayden, T.A., Limburg, K.E., and Pine, W.E., III, 2012, Using otolith chemistry tags and growth 

patterns to distinguish movements and provenance of native fish in the Grand Canyon: River 

Research and Applications, v. (online), 

http://onlinelibrary.wiley.com/doi/10.1002/rra.2627/abstract.

Makinster, A.S., Persons, W.R., Avery, L.A., and Bunch, A.J., 2010, Colorado River fish 

monitoring in Grand Canyon, Arizona--2000 to 2009 summary: U.S. Geological Survey 

Open-File Report 2010-1246, 26 p., http://pubs.usgs.gov/of/2010/1246/.

Minckley, W.L., and Marsh, P.C., 2009, Inland fishes of the greater Southwest--chronicle of a 

vanishing biota: Tucson, University of Arizona Press.

Myers, R., 1995, Recruitment of marine fish—the relative roles of density-dependent and 

density-independent mortality in the egg, larval, and juvenile stages: Marine Ecology 

Progress Series, v. 128, p. 305-310.

Nelson, C., Ward, D., Healy, B., and Smith, E.O., 2014, Bright Angel Creek inflow trout 

reduction pilot study-- trip report: Flagstaff, Ariz., National Park Service, prepared for the 

Upper Colorado Region, Bureau of Reclamation, interagency agreement no. R12PG40034.

National Park Service, 2013, Comprehensive fisheries management plan--Grand Canyon 

National Park and Glen Canyon National Recreation area: U.S. Department of the Interior, 

National Park Service.

Paine, R.T., 1976, Size-limited predation--an observational and experimental approach with the 

Mytilus-Pisaster interaction: Ecology, v. 57, p. 858-873.

Robinson, A.T., Kubly, D.M., Clarkson, R.W., and Creef, E.D., 1996, Factors limiting the 

distribution of native fishes in the Little Colorado River, Grand Canyon, Arizona: The 

Southwestern Naturalist, v. 41, no. 4, p. 378-387, http://www.jstor.org/stable/30055194.

Spurgeon, J.J., 2012, Translocation of humpback chub (Gila cypha) and food-web dynamics in 

Grand Canyon National Park tributary streams: Columbia, University of Missouri-Columbia, 

M.S. thesis, 84 p.

Stone, D.M., Van Haverbeke, D.R., Ward, D.L., and Hunt, T.A., 2007, Dispersal of nonnative 

fishes and parasites in the intermittent Little Colorado River, Arizona: The Southwestern 

Naturalist, v. 52, no. 1, p. 130-137, http://dx.doi.org/10.1894/0038-

4909(2007)52[130:DONFAP]2.0.CO;2.

Tonn, W.M., and Paszkowski C.A., 1992, Piscivory and recruitment--mechanism structuring 

prey populations in small lakes: Ecology, v. 73, p. 951–958.

U.S. Department of the Interior, 1995, Operation of Glen Canyon Dam--final environmental 

impact statement, Colorado River storage project, Arizona: Salt Lake City, Utah, Bureau of 

Reclamation, Upper Colorado Regional Office, 337 p., 

http://www.usbr.gov/uc/library/envdocs/eis/gc/pdfs/Cov-con/cov-con.pdf.

267
U.S. Fish and Wildlife Service, 2011, Final biological opinion on the operation of Glen Canyon 

Dam including high flow experiments and non-native fish control: Phoenix, Ariz., submitted 

to Bureau of Reclamation, Salt Lake City, Utah, AESO/SE 22410-2011-F-0100, 22410-

2011-F-0112, 150 p., 

http://www.fws.gov/southwest/es/arizona/Documents/Biol_Opin/110112_HFE_NNR.pdf.

Yard, M.D., Coggins, L.G., Baxter, C.V., Bennett, G.E., and Korman, J., 2011, Trout piscivory 

in the Colorado River, Grand Canyon--effects of turbidity, temperature, and fish prey 

availability: Transactions of the American Fisheries Society, v. 140, no. 2, p. 471-486, 

http://www.tandfonline.com/doi/abs/10.1080/00028487.2011.572011.

G. Budget 

Project Element 8.1. Efficacy 

and Ecological Impacts of 

Brown Trout Removal at 

Bright Angel Creek

Project Element 8.2. 

Translocation and monitoring 

of Humpback chub above 

Chute Falls in the Little 

Colorado River

Project Element 

8.3.Glen Canyon Dam 

Adaptive 

Management Program 

Fisheries Research, 

Monitoring, and 

Management Actions 

Protocol Evaluation 

Panel

Salaries $ 49,900.00 Salaries $ 4,000.00 Salaries $ -

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 2,800.00 Operating Expenses $ 4,700.00 Operating Expenses $ -

Logistics $ 30,400.00 Logistics $ 7,200.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 68,200.00 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 13,296.00 USGS Burden $ 4,590.00 USGS Burden $ -

Total $ 96,396.00 Total $ 88,690.00 Total $ -

Project Element 8.4. Little 

Colorado River Invasive 

Aquatic Species Surveillance

Project Element 8.5. Genetic 

monitoring of Humpback 

chub in Grand Canyon

Salaries $ - Salaries $ - 

Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ - 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ - USGS Burden $ - 

Total $ - Total $ - 

FY 2015

FY 2015 Project 8 Gross Totals: $185,086.00

268
Project Element 8.1. Efficacy 

and Ecological Impacts of 

Brown Trout Removal at 

Bright Angel Creek

Project Element 8.2. 

Translocation and monitoring 

of Humpback chub above 

Chute Falls in the Little 

Colorado River

Project Element 

8.3.Glen Canyon Dam 

Adaptive 

Management Program 

Fisheries Research, 

Monitoring, and 

Management Actions 

Protocol Evaluation 

Panel

Salaries $ 57,300.00 Salaries $ 4,100.00 Salaries $ -

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 2,800.00 Operating Expenses $ 2,300.00 Operating Expenses $ -

Logistics $ 37,500.00 Logistics $ 7,800.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 68,200.00 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 21,472.00 USGS Burden $ 5,170.00 USGS Burden $ -

Total $ 119,072.00 Total $ 87,570.00 Total $ -

Project Element 8.4. Little 

Colorado River Invasive 

Aquatic Species Surveillance

Project Element 8.5. Genetic 

monitoring of Humpback 

chub in Grand Canyon

Salaries $ - Salaries $ - 

Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ - 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ - USGS Burden $ - 

Total $ - Total $ - 

FY 2016

FY 2016 Project 8 Gross Totals: $206,642.00

269
Project Element 8.1. Efficacy 

and Ecological Impacts of 

Brown Trout Removal at 

Bright Angel Creek

Project Element 8.2. 

Translocation and monitoring 

of Humpback chub above 

Chute Falls in the Little 

Colorado River

Project Element 

8.3.Glen Canyon Dam 

Adaptive 

Management Program 

Fisheries Research, 

Monitoring, and 

Management Actions 

Protocol Evaluation 

Panel

Salaries $ 52,600.00 Salaries $ 4,400.00 Salaries $ -

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 2,800.00 Operating Expenses $ 2,300.00 Operating Expenses $ -

Logistics $ 37,700.00 Logistics $ 7,200.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 68,200.00 

Cooperators (nonUSGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 26,068.00 USGS Burden $ 5,938.00 USGS Burden $ -

Total $ 119,168.00 Total $ 88,038.00 Total $ -

Project Element 8.4. Little 

Colorado River Invasive 

Aquatic Species Surveillance

Project Element 8.5. Genetic 

monitoring of Humpback 

chub in Grand Canyon

Salaries $ 4,400.00 Salaries $ 4,400.00 

Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ 1,200.00 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ 45,000.00 Cooperators (non-USGS) $ 25,000.00 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 2,582.00 USGS Burden $ 2,318.00 

Total $ 51,982.00 Total $ 32,918.00 

FY 2017 Project 8 Gross Totals: $292,106.00

FY 2017 

270
Project 9. Understanding the Factors Determining 

Recruitment, Population Size, Growth, and Movement of 

Rainbow Trout in Glen and Marble Canyons 

A. Investigators 

Michael Yard, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Kim Dibble, Research Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Josh Korman, President, Ecometric Research Inc. 

Charles Yackulic, Research Statistician, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Theodore Melis, Physical Scientist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

David Rogowski, Fishery Biologist, Arizona Game and Fish Department

Theodore Kennedy, Research Aquatic Ecologist, U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center

David Ward, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Michael Dodrill, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

William Persons, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Daniel Buscombe, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Paul Grams, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Thomas Gushue, Computer Specialist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

B. Project Summary 

Over the past few decades, electrofishing and creel monitoring data collected by Arizona 

Game and Fish Department (AGFD) in Glen Canyon and Lees Ferry has shown that the rainbow 

trout (Oncorhynchus mykiss) fishery is characterized by three undesirable properties, including: 

(1) instability in population size that has led to decadal cycles of high and low fish abundance; 

(2) increased potential for negative interactions between rainbow trout and native fishes, 

especially the endangered humpback chub (Gila cypha), primarily due to rainbow trout 

population expansion downstream (Yard and others, 2011); and (3) an absence of the large 

rainbow trout that are highly valued by the angling community (Schmidt and others, 1998). 

Accordingly, much of the recent biological research conducted in Glen and Marble Canyons has 

focused on understanding factors that influence the size and health of the rainbow trout fishery 

(Korman and Campana, 2009; Anderson and others, 2012; Cross and others, 2013), as well as 

determining how Glen Canyon Dam operations and other factors may influence interactions 

271
between non-native trout and native species downriver (Yard and others, 2011; Korman and 

others, 2012; Melis and others, 2012). 

These undesirable properties have also been a key concern to decision makers involved 

with the development of the Glen Canyon Dam Long-Term Experimental and Management Plan 

(LTEMP) Environmental Impact Statement. Fisheries modelling conducted to support the 

LTEMP process has identified a number of factors that lead to uncertainty in our ability to 

predict rainbow trout responses to flow management. Uncertainties identified prior to modelling 

as “critical” included the degree to which the seasonal timing of high flow experiments (HFEs) 

versus other factors contributes to variation in the strength of the trout recruitment response, and 

the degree to which experimental trout management flows (TMFs), if implemented, could limit 

rainbow trout recruitment in Glen Canyon (as well as other chub related uncertainties – see 

Project 7). The modelling also included other uncertainties, including the uncertainty in 

recruitment-flow relationships, rates of rainbow trout outmigration from Glen Canyon, and the 

degree to which larger rainbow trout populations in Lees Ferry limit trout growth. Modelling 

revealed that these other uncertainties had a large impact on variation in predictions, a similar 

effect to the “critical” uncertainties, and generally larger uncertainty in hydrologic traces over the 

next 20 years. Resolving uncertainty in the “critical” uncertainties as well as the recruitmentflow relationships will require the continuation of sampling focused on juvenile rainbow trout 

recruitment (i.e., RTELLS) alongside a well-designed plan for testing different flow management 

strategies (assuming that refining these uncertainties is necessary for management). Uncertainties 

in our ability to predict outmigration rates and growth, on the other hand, requires a combination 

of mark-recapture techniques which provide more precise estimates of movement and survival 

parameters, and process levels studies to better understand how movement and growth might 

respond to future conditions.

The Natal Origins Project (see Project Element H.2 in the GCMRC FY13–14 workplan) was 

designed to address the need for mark-recapture studies to better understand rainbow trout 

population dynamics, especially movement. Previous modelling work using just catch data found 

it difficult to parse out whether local reproduction in Marble Canyon contributed meaningfully to 

populations or whether population dynamics were driven primarily by outmigration from the 

Lees Ferry reach (Korman and others, 2012). Preliminary results from the Natal Origins study 

suggest that movement is lower than expected, however, it is unclear whether movement rates 

may vary over time either as fish age or in response to changing environmental conditions. 

Furthermore, it is unclear how well these drift-feeding fish can maintain locally self-sufficient 

populations in Marble Canyon where environmental factors (i.e., reduced underwater light due to 

intermittent periods of high turbidity) may influence their ability to effectively forage (Kennedy, 

unpublished data). Another unknown is why local reproduction does not occur in Marble Canyon 

more than it does in Glen Canyon (Korman and others, 2012; also see Project 10). 

Physiologically, fish that exhibit reduced foraging capacity because of low light conditions 

and/or prey size and availability will often not be able to successfully spawn since gamete 

development is energetically costly (Hutchings, 1994; Hutchings and others, 1999). For the 

FY2015-17 workplan, we developed a suite of research and monitoring projects that will 

elucidate some of the mechanisms behind changes in trout abundance, survival, movement, 

reproduction, and growth in Glen and Marble Canyons. These research efforts will provide 

information that can be used to better understand the potential for negative interactions between 

non-native trout and native species like humpback chub, and perhaps identify experimental 

treatment options for mitigating high rainbow trout abundance downstream of Lees Ferry. 

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Since the early 1990’s the Arizona Game and Fish Department (AGFD) has monitored the 

Lees Ferry rainbow trout fishery via electrofishing in multiple seasons, providing data that has 

fostered the development of research projects to investigate causal mechanisms behind changes 

in population and trout size over time. These data have been used to develop catch per unit effort 

(CPUE) indices as a surrogate for population size, but other research and monitoring programs 

have commenced that estimate population size via more robust mark-recapture methods. To 

reduce redundancy between programs and optimize the utility of data generated (e.g., markrecapture population estimates in lieu of CPUE), a transition is needed from current research and 

monitoring efforts to a longer-term monitoring program that maintains a robust multi-pass markrecapture effort necessary to generate reliable estimates of vital rates for rainbow trout in Glen 

and Marble Canyons. We propose to develop and implement a plan for this transition during 

FY2015-17. Monitoring of juvenile trout will also continue under the Rainbow Trout Early Life 

Stage Survey (RTELSS) project (Project Element 6.7), while creel data from the Lees Ferry 

fishery will continue to be collected by AGFD (Project Element 6.8). Collectively, these 

monitoring data are essential to the management of the Lees Ferry trout fishery because they 

provide an indication of the influence of Glen Canyon Dam operations and other naturally 

occurring disturbances in the Colorado River ecosystem (CRe) on the health of the rainbow trout 

fishery. 

In addition to monitoring adult and juvenile rainbow trout populations, a suite of new 

research activities will improve our understanding of the mechanisms that drive rainbow trout 

population dynamics as they relate to dam operations and flow management actions. 

Specifically, these research projects will target questions related to characteristics of the physical 

habitat (e.g., channel-bed texture, water temperature, turbidity, water depth, and flow) and food 

base that may limit trout growth, size, and reproduction including: (a) a quantification of the

energy (lipid) reserves of drift-feeding trout in Glen and Marble Canyons to examine potential 

drivers of trout growth, movement, survival, and reproduction under varying light intensities preand post-monsoon; (b) a morphometric analysis of feeding structures in drift feeding fish to 

assess whether feeding efficiency is constrained by the size of invertebrate prey in the CRe; (c) a 

meta-analysis of data on the effects of light intensity, prey size, predator size, and turbidity on 

visual reactive distances of drift feeding fish, which will be used to develop an encounter rate 

model that predicts how light intensity and prey size affects trout foraging success and growth in 

Glen and Marble Canyons; (d) a laboratory study to assess the feasibility of using dam 

operations following fine sediment inputs (sub-sand sized) into Marble Canyon so as to assess 

whether or not managing turbidity is feasible as a trout management tool during minimumvolume dam release years; (e) development of bioenergetics models to quantify the effects of 

turbidity and food availability on trout growth in Marble Canyon; (f) an assessment of the 

mechanisms that limit trout growth in other tailwaters using data collected during the tailwater 

synthesis project; (g) development of population dynamic models that assess growth, 

reproduction and movement of rainbow trout between Glen and Marble Canyons; and (h) an 

evaluation of the effects of fall High Flow Experiments (HFE) on the growth, survival, 

movement, and condition of young-of-the-year rainbow trout via comparison of data from HFE 

and non-HFE sampling years. Collectively, results from these monitoring and research projects 

will be used to identify key drivers behind changes in rainbow trout population size, movement, 

survival, reproduction, size, and condition that will be used to better manage the trout fishery 

while protecting endangered fish populations in the CRe.

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C. Background 

Rainbow trout data collected in both Lees Ferry and Marble Canyon over the last few 

decades has been synthesized recently to provide a more holistic picture of rainbow trout 

population dynamics that points to uncertainties in our understanding and ultimately in our 

ability to predict the effects of management options. Korman and others, (2012) quantified the 

connections between certain flow characteristics and rainbow trout recruitment and attempted to 

estimate movement from Lees Ferry and Marble Canyon. This exercise illustrated that the sort of 

data collected over the preceding decades (mainly CPUE), while useful, was not capable of 

answering important questions about the origins of rainbow trout in Marble Canyon. More recent 

modelling to support the LTEMP process has reiterated this uncertainty, while also suggesting 

that our understanding of relationships between flows and rainbow trout recruitment require 

more precision to manage both rainbow trout and humpback chub. In short, if conditions 

favorable to high abundance of trout were desired, then operations that included steady summer 

flows with frequent equalization and HFE events would be implemented and rainbow trout 

monitoring efforts could be minimal. Similarly, if conditions favorable to humpback chub were 

favored, sufficient evidence exists to suggest that the opposite conditions (as few HFEs and 

equalizations as possible and unsteady summer flows) would be recommended. Under this 

scenario, again little rainbow trout monitoring would be required. However, to manage for 

intermediate conditions requires continued research and monitoring of rainbow trout recruitment, 

movement, growth and abundance.

During FY13–14, studies of rainbow trout were partitioned in such a way that research into 

the abundance and movement of rainbow trout below Lees Ferry was separated from research 

into the growth and abundance of these fish in Glen Canyon. For FY15–17, we have integrated 

much of this work into Project 9. Findings from these research activities in 2013–14, though 

preliminary (GCMRC Annual Reporting Meeting, January 2014; 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/14jan30/), suggest that the rainbow trout population in 

Glen and Marble Canyons is characterized by instability in population size, uneven spatial 

distribution, seasonally and spatially variable growth rates, and higher than expected survival 

upstream of the LCR. Furthermore, there is growing evidence linking rainbow trout abundance 

to declines in juvenile humpback chub survival near the LCR confluence (obtained through 

mark-recapture efforts begun during NSE and continued as part of the Natal Origins and Juvenile 

Chub Monitoring projects; Yackulic, unpublished data). To date, only limited downstream 

movement of tagged rainbow trout has been detected, however, many rainbow trout near the 

LCR are likely immigrants from Glen Canyon. Thus, despite the extremely high densities of 

rainbow trout in upper Marble Canyon, only a small proportion has moved downstream. 

Although small relative to upstream abundance, these numbers of rainbow trout appear to have 

been sufficient to significantly reduce juvenile humpback chub survival near the LCR 

confluence. At the same time, these results are based on only a few years’ data and movement 

appears to be lower than measured during the mechanical removal period from 2003–06 (the 

only other period when mark-recapture techniques were used and thus allows for inferences to be 

made about movement). This suggests that movement likely varies through time and that the 

number of rainbow trout in lower Marble Canyon may correspond directly to increases or 

decreases in emigration rates or recruitment rates in Glen Canyon or Marble Canyon 

The ability to predict movement of rainbow trout might improve if a better understanding 

were developed as to why they were moving more in the early 2000s than they are now.

Turbidity, changes in the prey base and the increasing energetic needs of older rainbow trout 

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have all been suggested as potential factors that could explain these differences. Previous and 

ongoing bioenergetic modelling (McKinney and Speas 2001; Dodrill, unpublished data), as well 

as a lipid pilot study, and measurement of weight losses and gains suggest that the limited quality 

and quantity of drift in Glen Canyon and Marble Canyon may limit growth to a few months of 

the year. As rainbow trout grow, they appear to spend many months of the year only meeting 

maintenance energy requirements, but not growing. This could be due to a number of causes 

including seasonal increases in turbidity that negatively affect rainbow trout foraging ability, 

limited food resources, intense competition due to high fish densities, or other factors. The low 

rates of downstream movement by rainbow trout in recent years may be related to relatively low 

turbidity levels and most fish being small, thus more likely to find adequate food. In the future, 

movement may increase to levels seen during the mechanical removal study as fish grow and 

require more food, if turbidity increases, or if other conditions that influence fish movement rates 

change. We believe this warrants the continuation of more directed studies along this research 

line, with greater emphasis on measuring the short-term physiological effects of dam operations 

on trout populations and modeling the interacting mechanisms that potentially control trout 

growth, population size, distribution, and recruitment in Glen and Marble Canyons. 

Rainbow trout were initially introduced to Grand Canyon (circa, 1920–30’s) through 

stocking in small tributaries, which then resumed once flow regulation commenced with 

completion of Glen Canyon Dam in 1964 (refer to unpublished stocking reports: Stricklin 1950; 

AGFD records). During the “stocking era,” the rainbow trout fishery was sustained by annual 

stocking at Lees Ferry (1964–1997) with minimal recruitment from natural reproduction 

(Maddux and others, 1987; McKinney and others, 2001). Rainbow trout were widely distributed 

throughout the Colorado River in advance of the most fish surveys (Carothers and others, 1981; 

Maddux and others, 1987) and occurred in areas used by native fish (Kaeding and Zimmerman, 

1983; Valdez and Ryle, 1995). The extent of interactions between native and non-native fish 

during this period is not well understood, and is often presumed to have been limited in 

comparison to more recent years (Valdez and Ryel, 1995; Marsh and Douglas, 1997). 

Since 1991, the fishery has been increasingly sustained by natural recruitment and stocking 

was completely phased out by 1998 (McKinney and others, 2001). While limited recruitment 

was occurring prior to 1991 (Maddux and others, 1987), this transition to a “recruitment era” is 

often attributed to implementation of modified low fluctuating flows (MLFF; USDOI, 1996; 

Walters and others, 2000). Demography of rainbow trout during the recruitment era is closely 

linked not only to implementation of MLFFs, higher-flow periods, such as High Flow 

Experiments (HFE; USDOI, 2011a) and equalization flows (Interim Guidelines; USDOI, 2007). 

Spring-timed high flow experiments in 1996, 2000, and 2008, while higher and steadier dam 

operations (response to spring runoff forecasts in the upper Colorado River basin) during the 

middle of the water year, either to mitigate the probability of spills from the dam or equalize 

water storage between Lakes Powell and Mead flows in winter to spring seasons, as in 1997, 

2008 and 2011, led to recruitment of large numbers of juvenile rainbow trout in subsequent years 

(Korman and others, 2012; Korman and others, unpublished data). Research surrounding these 

flow events suggests that this recruitment, driven by increased juvenile survival and growth, was 

mainly attributable to increased food availability in the drift. In turn, this was linked to higher 

production of key drifting species of insects upon which rainbow trout rely heavily (blackflies 

and midges; Cross and others, 2013; Kennedy and others, 2013). Although increased local 

reproduction led to a self-sustaining population, the “recruitment era” for the rainbow trout 

fishery has been characterized by undesirable properties such as fluctuations in population size, a 

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decline in trout size (Schmidt and others, 1998), and an increased potential for negative 

interactions with humpback chub (Yard and others, 2011).

On one hand, there is a renowned and highly valued sport fishery of rainbow trout whose 

population is self-sustaining. On the other hand, there is an endangered fish population separated 

from the trout fishery by distance, although not entirely insular from the other, and whose status 

appears negatively related to the population dynamics of rainbow trout found upstream (Yard 

and others, 2011; Yackulic, and others, in prep.). The intersection between these two important 

but, interacting fish populations appears strongly linked to causal mechanisms that control 

growth and population density, particularly for trout. Nonetheless, the degree to which dam 

operations and associated factors (i.e., population cycles) interact to affect rainbow trout 

movement and growth is considered one of the largest uncertainties associated with the Glen 

Canyon Adaptive Management Program (GCDAMP; McKinney and others, 2001; McKinney 

and Speas, 2001; Cross and others, 2011). This is the central motivation driving the proposed 

research and monitoring projects in FY15–17. 

This uncertainty was highlighted during modelling for the recent LTEMP process. While 

there is a good understanding of the direction of flow impacts on trout recruitment (Korman and 

others, 2012) and an improving understanding of the magnitude of the effect of rainbow trout on 

juvenile humpback chub survival (Yackulic and others, in prep.), management options that could 

meaningfully decouple trout and sand resources from humpback chub are not being considered. 

Presumably, this is due to the costs of resolving these issues in terms of other resources. 

Whereas, the density of the stocked rainbow trout fishery present 20-30 years ago was relatively 

easy to manage by changing stocking strategies, changes in in flow management have led to a 

rainbow fishery that is more difficult to manage. More recently, HFEs and equalization flows 

appear to have led to increased rainbow trout recruitment. While some management options 

being considered (e.g., TMFs) could counteract increased recruitment linked to an increasing 

frequency of HFEs if applied selectively, trout abundance or recruitment are likely to continue to 

be instable. In other words, the problem of a naturally reproducing, and thus difficult to manage, 

rainbow trout fishery is unlikely to disappear given future dam operations being considered in 

proposed alternatives for the LTEMP EIS. Each alternative being considered would require 

maintaining a rainbow trout fishery and conserving sand resources while working to recover 

humpback chub, and the science to support this detailed tradeoff analysis is necessarily intense.

Recognizing this uncertainty has led to a plethora of hypotheses regarding the causal 

source(s) regulating rainbow trout density, recruitment, and growth. Cause and effect 

relationships are more easily determined when a single factor is chronically apparent and 

measureable; all the same, the difficulty in discerning causal mechanisms often arises because: 

(1) an effect is acutely strong but short lived; (2) a mechanism is no longer present but the 

antecedent effect remains; and (3) multiple causal factors may be involved. Since growth is an 

integrated measure across time, the use and application of different metrics that exemplify 

growth over different time scales (long-term vs. short-term) are helpful in discriminating 

between effects from different environmental factors. Monitoring programs are important for 

documenting population characteristics (e.g., abundance, size distribution, and occurrence; 

Project Element F in the GCMRC FY13–14 Workplan), but are not a very effective approach in 

time or cost for determining causation, particularly when used as the sole method. How then do 

we better understand what factor(s) might be regulating trout growth?

Although rainbow trout are one of the most abundant fish species in the CRe, trout densities 

and growth rates decline substantially with distance downstream from Glen Canyon Dam 

(Makinster and others, 2011; Korman and others, unpublished data). Spatial and temporal 

276
variation in the invertebrate prey base and how it is consumed by fish may play an important role 

in determining individual fish growth, and subsequently, fish survival, movement and 

reproduction throughout the CRe. Non-native rainbow trout and brown trout (Salmo trutta) are 

likely to compete with (and prey on) native fish (Donner, 2011), including humpback chub (Yard 

and others, 2011), because the foraging mode used by all three fish species relies predominately 

on drifting invertebrates (Cross and others, 2013). Larger invertebrates are often more vulnerable 

and therefore preferentially selected by fish predators over small prey because ease of detection 

and retention while foraging, particularly since prey size is also correlated with energy content 

(Breck and Gitter, 1983; McKinney and others, 2001). Although food is often one of the most 

commonly limiting resources in aquatic ecosystems, visual sight feeders like rainbow and brown 

trout may have encounter rates that are periodically reduced; in essence the number of 

invertebrates a fish encounters daily, thereby affecting growth rates. Consequently, 

understanding these biotic interactions is of significant concern to the management of the CRe 

(Yackulic and others, 2014).

Owing to a recent and extensive tagging effort associated with the Natal Origins of Rainbow 

Trout research project (see Project Element F.4 in the GCMRC FY13–14 workplan) we are now 

able to estimate size-based seasonal growth rates for rainbow trout using across-trip recapture 

data, as well as model length-at-age growth trajectories for trout in downstream reaches (i.e., 

from Glen Canyon to the Little Colorado River (LCR) confluence) using a von Bertalanffy 

growth curve. Other data are being collected in conjunction with the Natal Origins project, 

including integrated drift samples, trout diet (rainbow and brown trout), trout lipid mass, and gill 

branchial arches, as well as physical data (turbidity and temperature). In particular, lipid analysis 

will provide a sensitive indicator of the physiological condition of trout since fat stores in fish 

become depleted during prolonged starvation events (Adams, 1999; Parrish, 1999). This 

analytical tool will be very effective in evaluating the effects of food availability and fish density 

and size on the energy storage capacity of trout residing in different reaches of the Colorado 

River, which will elucidate potential mechanisms behind between-reach differences in 

reproductive capacity (Adams, 1999; Cleary and others, 2012). Preliminary findings from the 

above research projects indicate seasonal differences in trout growth that are likely due to a 

combination of factors, including drifting prey availability (food resource limitations; Kennedy, 

unpublished data), trout densities (intra-specific competition; Korman and others, unpublished 

data), turbidity events (prey detection), and energy storage (feeding efficiencies; Dibble, 

unpublished data). The metrics from these and future data collections will be extremely useful 

for comparing empirical findings to the outcomes from predictive models (encounter rate and 

bioenergetics models). 

Data collected in FY13–14 has provided significant insights on rainbow trout population 

dynamics in the CRe as well as in other regulated rivers across the West. Management concerns 

for the trout fishery in the CRe downriver of Glen Canyon Dam are similar to those in other 

systems, including a decline in trout size and catch, potential interactions with endangered 

species, whirling disease, seasonal low flow conditions, diminished food base, parasites, and 

other natural and anthropogenic factors that influence trout growth and survival. Analysis of 

tailwater data has revealed that a decline in the size of rainbow and brown trout in other 

tailwaters is primarily correlated with dam operations (hydropeaking and seasonal and annual 

flow volume) and high densities of small and medium-sized rainbow and brown trout. Additional 

analyses planned in FY15–16 (see Project Element 9.8) will elucidate some of the mechanisms 

behind changes in trout size and growth in other tailwaters, which will not only inform the 

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management of Glen Canyon Dam but will inform the management of a broader number of 

tailwater systems in the Western U.S.

To resolve uncertainties associated with factors that regulate trout growth in Glen and Marble 

Canyons and in other tailwater systems, we propose complementing long-term rainbow trout 

monitoring with a suite of new research activities. 

C.1. Scientific Background 

As specified in the FY13–14 Work Plan, many of the same hypotheses thought to explain the 

mechanisms of rainbow trout growth still pertain to this project. For brevity we have reduced 

some of the original text, but have included some additional research hypotheses that support the 

proposed project elements.

Hypothesis 1 (H1) The strain of rainbow trout present in Glen Canyon is incapable of growing 

to large sizes (i.e., >20 inches). This hypothesis attributes diminished rainbow trout growth to 

changes in the genetic strains historically stocked at Lees Ferry, and does not consider 

physiological conditions for trout growth as affected by dam operations (see GCMRC FY13–14 

Workplan, Project Element H.1). 

Hypothesis 2 (H2) The current prey base, composed chiefly of midges and black flies, can 

support the growth of smaller rainbow trout, but does not provide enough energy to allow for 

growth in large rainbow trout. H2 argues that there have been shifts in the foodbase that now 

leave it incapable of supporting larger rainbow trout. While dam operations can shift the 

foodbase to favor the recruitment and growth of small rainbow trout (Cross and others, 2011), 

growth and survival of large rainbow trout appears largely unaffected by Glen Canyon dam 

operations. Possible causes of this shift in the foodbase include declining nutrient inputs from 

Lake Powell as the reservoir has aged (Stockner and others, 2000; see GCMRC FY15–17 

Workplan, Project Element 5.3. [nutrient budget]), introduction of invasive species (i.e., New 

Zealand mudsnail (Potamopyrgus antipodarum); Cross and others, 2010), and changes in 

channel-bed texture as the Glen Canyon reach was winnowed of finer sediment initially in 

summer 1965 and then during other periods of higher dam releases over time (Grams and others, 

2007). Changes in invertebrate composition could lead to changes in both the seasonal 

availability of drifting invertebrates (there is currently ~100-fold variation in drift rates among 

seasons; Kennedy, unpublished data) and in the prevalence of high quality drift (i.e., large prey 

items such as Gammarus), both of which might strongly constrain growth of large rainbow trout 

while still allowing small rainbow trout to thrive. Support for this hypothesis comes from 

McKinney and Speas (2001), who observed size-related asymmetries in rainbow trout diet and 

energy intake that suggests larger sized trout are food-limited more often than smaller fish. 

Although the total amount of prey available to support rainbow trout populations may have 

increased during this time period (Angradi and Kubly, 1993; Blinn and others, 1995; Benenati 

and others, 1998), juvenile trout appear to be the primary beneficiaries of any such change 

(McKinney and Speas, 2001). More recent research on the Glen Canyon food web (Cross and 

others, 2011) supports these observations. 

A corollary to H2 is that some combination of rainbow trout dispersal patterns, food 

availability, and declining prey detectability explains the declining abundances of rainbow trout 

at distances further downstream from Lees Ferry (Carothers and Brown, 1991; Makinster and 

others, 2011). Turbidity increases downriver (Voichick), and since rainbow trout are visual 

feeders, it is more challenging for them to see food. However, the importance of this effect 

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relative to declining food availability and dispersal rates is unknown (Barrett and others, 1992; 

Stuart-Smith and others, 2004).

Defined below, are a set of secondary hypotheses where we explore some of the mechanisms 

underlying H2; these hypotheses are not mutually exclusive. Under 

Hypothesis 2.1 (H2.1), Feeding morphology differs among rainbow trout, brown trout, and 

humpback chub which leads to resource partitioning among drift feeding fish. We expect that 

morphological differences in the branchial-arch/gill-raker feeding structure exists among the 

three drift feeding species, which leads to a preferential consumption of different prey sizes. If 

true, differences in feeding efficiencies due to feeding morphology rather than behavior may 

explain the differential consumption of prey observed between trout species (Yard, unpublished 

data). The anatomical similarities and differences found in feeding morphology among these 

three fish species may partially explain why rainbow trout and humpback chub have a high diet 

overlap and a potential for competitive interactions (Donner, 2011), whereas brown trout diet 

consists primarily of large prey items, with a strong preferential use of Gammarus and juvenile 

fish (Yard and others, 2011). 

Under Hypothesis 2.2 (H2.2), Feeding morphology changes with fish size and leads to feeding 

inefficiencies. This hypothesis presupposes that feeding efficiencies change as a fish grows 

which should lead to a selection of specific prey based on size, a trend that favors consumption 

of larger invertebrates (chironomids → simuliids → gammarids) as a fish grows (MacNeill and 

Brandt, 1990). Because anatomical features often change in size and shape disproportionately as 

a fish increases in length (increase in gill-raker spacing as a consequence of growth), it is likely 

that these morphological differences should reduce the retention efficiencies for smaller prey 

items with increasing fish length. Therefore, we would expect to observe increases in the mean 

prey size as a fish becomes larger, along with a commensurate decrease in the variation of the 

prey size distributions found in the diet. Under environmental conditions where prey availability

is not limited, we should expect that the diet of small fish will be more similar to the invertebrate 

size distributions in the drift, whereas the diet for large fish should contain a higher proportion of 

larger invertebrates than the actual size distributions available in the drift (high electivity 

indices). In contrast, under environmental conditions when prey availability is limited, we should 

expect reduced feeding efficiencies for larger sized fish, such that the quantity of food items 

found in the diet, scaled according to fish size, will be less in larger fish than in smaller fish. 

Thus, limited prey diversity (H.2.0) favoring small sized dipterans impose growth restrictions on 

larger sized trout due to feeding inefficiencies.

Nevertheless, it is also possible that feeding efficiencies of trout are not limited by feeding 

morphology, but by other mechanisms such as visual prey detection. Under 

Hypothesis 2.3 (H2.3); Feeding efficiencies of trout are limited by visual acuity, presupposes 

that varying underwater light intensities (Hansen and others, 2013) mediated by turbidity and 

prey size (Barrett and others, 1992) affect reactive distances of visual sight feeders, particularly 

in rainbow trout. This is one of the most abundant fish species in the CRe; even so, it has been 

observed that trout densities and growth rates decline with increasing turbidity levels as found 

downstream (Korman, unpublished data). Under increased turbidity conditions we expect that 

the quantity of dietary items found in small and large fish will be reduced regardless of prey 

availability in the drift (Hansen and others, 2013). 

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Hypothesis 3 (H3) The growth of large rainbow trout is limited by exploitative competition for 

limited prey items. The diet composition of large and small rainbow trout overlap (i.e., their 

production is primarily supported by midges, black flies, and Gammarus; McKinney and Speas, 

2001; Cross and others, 2011); however, smaller rainbow trout may be able to subsist on smaller 

prey items, and this may in turn affect food availability for larger rainbow trout. Many of the 

smaller prey items (small Gammarus and 1st instar larvae of midges and black flies) consumed 

by small rainbow trout represent early life stages of species that large fish would be better able to 

exploit if these prey items continued to mature. Since recruitment of smaller rainbow trout is tied 

to dam operations, H3 posits an indirect and time lagged linkage to dam operations. While H2

and H1 predict no changes in large rainbow trout growth if small rainbow trout numbers are 

suppressed, H3 predicts an increase in the growth of large rainbow trout if small rainbow trout 

are suppressed. H3 can also be extended to argue that while HFEs augment juvenile recruitment, 

the dynamics in the following years may be chiefly driven by intraspecific interactions between 

younger and older age-classes of trout, as opposed to physical factors (Schlosser 1985; Walters 

and Post, 1993).

Hypotheses 4 (H4) Operational constraints that occurred in 1990 limit the growth of large 

rainbow trout. H4 directly links the lack of large rainbow trout to changes in dam operations. H4

posits that the load-following dam operations that occurred during the stocking era created 

habitat that was more beneficial to large rainbow trout by favoring a fast-growing and highquality early successional algal assemblage, creating daily surges in invertebrate drift (Perry and 

Perry, 1986). This also favored larger invertebrate prey items, all of which sustained the growth 

of larger rainbow trout (Barrett and others, 1992; Graf, 1995; Stuart-Smith and others, 2004). 

Growth studies on young-of-year rainbow trout have demonstrated that daily flow variation has 

significant effects on growth for early life stages (Korman and Campana, 2009). However, we 

lack a similar understanding of how daily variation in discharge affects growth of larger rainbow 

trout.

Hypotheses 5 (H5) Depressed growth rates leads to rainbow trout movement. Predator-prey 

dynamics may occur under conditions where invertebrate prey are initially plentiful (e.g., springfloods or equalization flows stimulate invertebrate production); conditions favoring increased 

growth and physiological condition may lead to successful trout reproduction and recruitment 

(Korman and others, 2011). Subsequently, high trout densities the following year may exceed the 

carrying capacity of the food resources and outstrip the food supply (H2). Under this scenario, 

H5 predicts that fish are more likely to move when metabolic requirements are not met, due to 

either an increase in foraging time when invertebrate prey are less available (H2, resource 

limitations), or when there are strong competitive interactions occurring within or between 

different sized cohorts (H3, intraspecific competition). If movement is governed by predatorprey dynamics, downstream dispersal may occur episodically due to resource depletion (H2) or 

gradually over time depending on the relationship between trout densities and resource 

availability (H3).

The motivation for these proposed research projects is to better understand how growth 

affects rainbow trout dynamics so as to improve the recreational fishing experience for rainbow 

trout at Lees Ferry, while at the same time protecting and maintaining native fish populations 

downstream in Marble and Grand Canyons. Being able to distinguish among these multiple 

hypotheses will help inform the types of experiments the GCDAMP might evaluate during the 

Long-Term Experimental and Management Plan (LTEMP) Environmental Impact Statement 

280
(EIS) to meet goals for native and non-native fishes. If the research outlined below supports 

either H1 or H2.0-2.3, then experimental changes in dam operations alone are unlikely to 

provide the conditions necessary to support the large rainbow trout that are sought by anglers. If 

we find support for H1, then this would suggest that the GCDAMP might pursue experimental 

stocking of alternative strains of rainbow trout, which are capable of growing to large size, into 

Glen Canyon. If the proposed research primarily supports H2.0-2.3, then the GCDAMP could 

consider experimentally introducing invertebrate species from other Colorado River Basin 

tailwaters (i.e., San Juan, Flaming Gorge, etc.), particularly larger taxa, and/or consider habitat 

modification (e.g., flows, large woody debris additions, or a temperature control device). If the 

proposed research primarily supports H3 or H4, then the GCDAMP might consider alterations in 

dam operations. In recent years, dam operations designed to achieve goals for sediment and 

native fish (i.e., HFEs and Low Steady Summer Flows) or meet equalization requirements (i.e., 

2008 and 2011-12), have created pulses of rainbow trout recruitment (Korman and others, 2012). 

As a consequence, recreational catch rates in Glen Canyon have increased following these 

operations, yet the large rainbow trout that are sought by many anglers are absent. Further, these 

pulses of recruitment and subsequent downstream dispersal (H5) have led to costly and 

controversial rainbow trout removal efforts designed to reduce the threat that they pose to 

endangered humpback chub (Coggins and others, 2011). One specific management option 

available to the GCDAMP is moving towards dam operations that will suppress juvenile 

recruitment. Suppressing juvenile rainbow trout recruitment might improve growth of larger 

rainbow trout either by lowering the degree of competition with smaller size classes (H3) or by 

creating more ideal habitat conditions (H4). 

C. 2. Key Monitoring and Research Questions Addressed in this Project 

This project directly addresses the following Strategic Science Questions (SSQs), Core 

Monitoring Information Needs (CMINs), and Research Information Needs (RINs) previously 

identified by the GCDAMP. In addition, Project Elements 9.9 and 9.10 in the current workplan 

comply with directives from the Secretary of the Interior to ensure effective and coordinated 

implementation of Environmental Assessments associated with the High Flow Experimental 

releases and with Non-Native Fish Control downriver of Glen Canyon Dam.

Primary SSQ addressed:

• SSQ 1-5. What are the important pathways, and the rate of flux among them, that link 

lower trophic levels with fish and how will they link to dam operations?

• SSQ 1-6. Are trends in the abundance of fish populations, or indicators from fish such as 

growth, condition, and body composition (e.g., lipids), correlated with patterns in 

invertebrate flux?

• SSQ 3-5. How is invertebrate flux affected by water quality (for example, temperature, 

nutrient concentrations, turbidity) and dam operations?

• SSQ 3-6. What GCD operations (ramping rates, daily flow range, etc.) maximize trout 

fishing opportunities and catchability?

• SSQ 5-2. Is invertebrate flux affected by water quality (e.g., temperature, nutrient 

concentrations, turbidity) and dam operations?

• SSQ 5-6. Do the potential benefits of improved rearing habitat (warmer, more stable, 

more backwater and vegetated shorelines, more food) outweigh negative impacts due to 

increases in non-native fish abundance?

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Primary Core Monitoring Information Needs addressed:

• CMIN 1.5.1. Determine and track the composition and biomass of drift in the Colorado 

River in conjunction with measurements of flow, nutrients, water temperature, and light 

regime.

Research Information Needs addressed:

• RIN 1.1. What are the fundamental trophic interactions in the aquatic ecosystem?

• SIN 7.2.2. Which water quality variables influence food base and fisheries in the CRE?

• IN 6.3. How is the abundance of vertebrate consumers affected by seasonal shifts in food 

base abundance in the CRE?

• RIN 1.4.3. How do top-down effects (grazing and predation) affect the abundance and 

composition of benthic invertebrates?

D. Proposed Work- Monitoring and Research Projects 

D.1. Project Elements- Research 

Project Element 9.1. Rainbow Trout Population Dynamics – Ongoing Modelling and Future Monitoring 

(Recommended for funding FY15: $37,120)

Charles Yackulic, Research Statistician, USGS, GCMRC

Josh Korman, President, Ecometric Research, Inc.

William Persons, Fishery Biologist, USGS, GCMRC

David Rogowski, Fishery Biologist, AGFD 

Michael Yard, Fishery Biologist, USGS, GCMRC 

Scott VanderKooi, Supervisory Biologist, USGS, GCMRC 

Luke Avery, Fishery Biologist, USGS, GCMRC

The Lees Ferry rainbow trout fishery is one of the most intensively studied tailwaters in the 

western United States (Dibble pers. comm.). Standard monitoring in most tailwaters consists of 

CPUE indices based on a single sampling trip (typically in the fall), whereas monitoring in Glen 

Canyon has traditionally consisted of three seasonal trips to collect CPUE data. Given the 

sensitivity of the fishery to dam operations and the interests of stakeholders, extra effort is 

perhaps warranted, however, much of the concern regarding rainbow trout revolves around fish 

not residing in the tailwater. Therefore, any monitoring design should consider questions 

regarding rainbow trout both in Glen and Marble Canyons. Downstream of Glen Canyon, 

monitoring has traditionally consisted of CPUE based indices based on 1-2 trips per year as part 

of the SWEF project (project element 6.4). Recent modelling efforts (Korman and others, 2011 

and 2012; Yackulic, unpublished data) suggest that these data were not sufficient to address

competing hypotheses concerning the origin of rainbow trout in Marble Canyon. Intuitively, this 

makes sense since the only indication of provenance in catch data comes from few tag recaptures 

of adult fish (Maddux and others, 1987) and differences in size structure at different locations 

(Korman and others, 2012), and these differences can be explained via multiple processes (e.g., 

different combinations of spatial variation in timing of spawning, growth, survival and 

movement). This suggests the need for mark-recapture studies, which allow for estimation of key 

process variables (survival, growth, movement, etc.) and was the motivation for the Natal 

Origins project. The increased information in mark-capture data over catch data is illustrated by 

the dramatic increases in our understanding of the roles of temperature and trout in the dynamics 

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of juvenile humpback chub through NSE and then JCM sampling (see Project Element 7.2) 

combined with recent modelling for LTEMP process. For example, these data allowed us to 

determine that recent decreases in juvenile humpback chub survival in a mainstem reference 

reach (RM 63-64.5) in response to increasing rainbow trout numbers were somewhat offset by 

years of high juvenile production and outmigration from the LCR such that juvenile chub 

numbers initially increased even as survival decreased (Yackulic and others, 2014 annual 

reporting). The Natal Origins project has helped answer questions about how different process 

variables (survival, growth and movement) vary throughout Glen and Marble Canyons. It is 

likely, however, that rates of these variables fluctuate through time, warranting continuation of 

this research in some form at least for the duration of the HFE protocol (through 2020).

In light of the above, the goals of this project are two-fold. Firstly, to analyze ongoing Natal 

Origins research activities to better understand rainbow trout population dynamics in Glen and 

Marble Canyons and secondly, to use information gained to develop recommendations for future 

monitoring and research. An initial assessment informed by modelling for the LTEMP process 

and guidance from DOI leadership and stakeholders, suggests that some version of the Natal 

Origins project will be needed in the near future so long as the GCDAMP seeks to maintain 

naturally reproducing populations of rainbow trout and a healthy humpback chub population in 

the same river. While primarily focused on rainbow trout downstream of Lees Ferry, the Natal 

Origins project also includes sampling in Glen Canyon, particularly in the fall when large 

numbers of fish are marked with PIT tags. Ongoing analyses suggest that data from this effort 

can be analyzed to provide estimates of the actual abundance of rainbow trout in Glen Canyon 

with no additional sampling (Dzul, unpublished data). If correct, catch indices as well as actual 

estimates of the state variable of interest (i.e., abundance) will be able to be calculated from data 

collected during the marking efforts described above. While minor differences in sampling 

protocols exist between this work and those used to collect the long-term data set, a comparison 

is needed to determine if a mark-recapture approach can be used in lieu of the CPUE monitoring 

that has been in place since 2000. We propose that additional data be collected in 2015 and that 

all overlapping data be evaluated to determine the suitability of a Natal Origins-type approach to 

meet long-term status and trend information needs. 

As with the Juvenile Chub Monitoring project (Project Element 7.2), the Natal Origin 

Research project (Project Element 9.2) is scheduled to be completed by the end of FY2016. This 

leaves a significant data gap in outlying years for information on rainbow trout abundance, 

distribution, and movement in Glen and Marble Canyons in response to dam operations and 

other management actions outlined in environmental assessments for HFEs and nonnative fish 

control (USDOI, 2011a and 2011b) and other management documents. To avoid this gap, a 

transition of the Natal Origin Research project from a research focus to a monitoring effort needs 

to occur. We propose that GCMRC and its cooperators collaboratively develop a plan for this 

transition and include it among the topics to be reviewed by the fisheries program protocol 

evaluation panel (PEP; see Project Element 8.3). The new monitoring project will begin in FY17 

following review and implementation, as appropriate, of the PEP’s recommendations by 

GCMRC. 

Project Element 9.2. Detection of Rainbow Trout Movement from the Upper Reaches of the Colorado River 

below Glen Canyon Dam/Natal Origins 

(Recommended for funding FY15: $440,512)

Josh Korman, Ecometric Research, Inc.

Michael Yard, Fishery Biologist, USGS, GCMRC 

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Charles Yackulic, Research Statistician, USGS, GCMRC 

The central objectives of this research project are to (1) determine the natal origins of 

rainbow trout in the Marble Canyon/LCR confluence area via a large-scale mark and recovery 

effort, (2) to evaluate the linkage between trout populations in the Lees Ferry reach and Marble 

Canyon, (3) assess the efficacy of the proposed alternative of a trout removal effort between the 

Paria River to Badger Rapid (PBR), (4) develop analytical methods for monitoring abundance, 

survival, recruitment and capture probability of rainbow trout in the CRe. And lastly (5) studying 

the response of juvenile native fish to changes in trout density near the LCR area resulting from 

removal and experimental flow treatments will be used to support the data and analytical 

requirements as per the Biological Opinion for Glen Canyon Dam operations including high flow 

experiments and nonnative fish control (USFWS 2011) (see project element 7.2 [Juvenile chub 

monitoring]).

This project as originally described in the FY11–2012 Work Plan (BIO 2.E18.11, 12), has 

been modified and expanded (see FY13–14 Work Plan) with fieldwork continuing through the 

end of FY16. The scheduled completion for this project is 1st quarter of FY17. This study is a 

research project to determine if Glen Canyon is the natal source of trout emigrating into the 

downstream reaches of Marble and Grand Canyons (Korman and others, 2011). Information 

from this project will help resolve some of the uncertainties about prescribing nonnative fish 

control activities such as fish suppression flows (e.g., LTEMP possible alternatives), or in 

locations that are geographically distant to the area of concern (Little Colorado River confluence 

area). This project is based on existing information (Coggins, 2008; Korman and others, 2012) 

that concludes that rainbow trout reared in the Lees Ferry reach of the Colorado River (Glen 

Canyon Dam to Lees Ferry) move downstream under some conditions. During FY13–k14, the 

Natal Origin Research project used a quarterly sampling design (January, April, June-July, and 

September); however, owing to budgetary constraints the number of research trips may be 

reduced to three trips in 2015 and 2016. This reduction in field work will reduce other associated 

project costs (see Project Elements: 5.2.2, 9.1, 9.3, 9.4, 9.7, 9.9, and 9.10).

The analytical methods being developed to assess trout movement use a robust-design (RD, 2 

km section) where captured fish are spatially referenced at a 250 m resolution in all sampling 

reaches (Lees Ferry [R1], House Rock [R2], Buckfarm [R3], Above LCR [R4], and Below LCR 

[R5]) initially on pass 1, and when recaptured on pass 2 or on other sampling trips. Therefore, 

emigration losses can be determined based on observations of movement distances of fish 

released in the RD section and subsequently recaptured at the same or different locations within 

or across trips. To further supplement this movement information, 2 km sections upstream and 

downstream of the RD section in reaches R1-3 are sampled. This spatial layout allows us to 

detect within-reach movements of up to 4 km, but the opportunity to detect shorter movements is 

greater than for larger ones. Fitting parametric distributions to such data facilitates comparison of 

movement patterns among reaches and trip intervals, and can also be used to derive a robust 

estimate of emigration losses for an open population modeling approach like the Jolly Seber (JS) 

model. Although, the current sampling design allows for estimations of trout movement 

distances occurring within and across sampling reaches located between Glen Canyon and the 

LCR; the spatially fixed sampling approach (5-reaches) limits estimations of intermediate 

movement occurring among tagged trout found between reaches that are not currently sampled. 

To acquire additional trout movement data for between reach movements of tagged animals, 

AGFD is planning on conducting mark recapture studies between the five sampling reaches in 

Marble and Eastern Grand Canyons during FY15–16 (see Project Element 6.4). 

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The JS model is used to estimate reach-specific abundance, survival and recruitment based 

on data from the RD mark-recapture sampling design. The apparent survival of marked fish in 

RD sections based on the decline in recaptures of each marked cohort (a group of fish released in 

a reach on a given trip) through time. That decline depends on mortality rate as well as loss of 

fish due to emigration from RD sections. Estimates of movement are required to convert the 

apparent survival normally estimated by a JS model (which includes losses from mortality and 

movement) into an actual survival rate, by comparing models where survival rate can vary 

among trips vs. models where survival is assumed to be constant. Using different modeling 

approaches allows for estimating abundance at the start of each trip, survival and recruitment 

between trips, and capture probability for each trip and pass. Parameters of the different models 

are estimated by minimizing the negative value of the total log likelihood and using the nonlinear 

search procedure in the AD model-builder (ADMB) software (Fournier and others, 2011). 

Abundance of unmarked fish at the start of the 1st pass on trips 2 and later depends on 

abundance at the end of the last pass on the previous trip, and survival and recruitment between 

trips. Combinations of models (Mt-So, Mtb-So, Mt-S*, Mtb-S*) are being evaluated using 

Akaike’s Information Criteria (AIC, Burnham and Anderson 2002). Model selection, particularly 

the use of Mb model (behavioral response to capture) types are required because of detection 

differences for within trip vs across trip. This is likely due to spatial heterogeneity that leads to 

overestimating capture probabilities and results in an underestimation of trout abundance. These 

habitat linked differences in fish vulnerability to capture might arise due to fish moving to lower 

velocity or more protected/shallow habitats, and are to be addressed by some additional habitat 

assessment (see Project Element 10.1).

Preliminary results from this research study (GCMRC Annual Reporting Meeting, January 

2013 & 2014); indicate relatively modest movement of trout between trips with a high proportion 

of recaptures found in their original release sections, or in adjacent sections, and the vast 

majority of the recaptures occurring within a 2 km of the original release locations. To date, 

movement rates into a reach (immigration) rather than out of a reach (emigration) have been 

considerably less (1/2 the rate observed in 2003) than those reported for previous studies 

(Coggins 2008; and Coggins and others, 2011) near the LCR. This suggests that the current low 

immigration rate for trout may be indicative of relatively good conditions for growth in Marble 

Canyon which could reduce downstream dispersal (see Project Elements 9.3-5, & 9.9), and that 

movement is more episodic rather than incrementally constant. This is the underlying rationale 

for such an extended research project (2012–2016). Trout growth is key to interpreting the 

observed differences in length frequencies and provides the insight on the underlying 

mechanisms for trout movement. Trout growth is very limited between Sep-Jan and likely most 

of Jan-Apr period and may be linked to low food availability (hypothesis H2) or low feeding 

efficiency (H2.1-3). The differential trout growth as observed among the five RD sections 

provides insight on understanding what fraction of the Marble Canyon fish immigrate into the 

LCR inflow reach. 

This research project also provides the logistical framework to support the fieldwork 

necessary for a number of other study projects, these include several project elements in Project 

9 “Understanding the Factors Limiting the Recruitment, Population Size, Growth, and 

Movement of Rainbow Trout in Glen and Marble Canyons”, Project Element 7.2., “Mainstem 

monitoring of native and nonnative fishes near the LCR confluence -Juvenile Chub Monitoring” 

(as per USDOIa 2011), and Project Element L.2. “Linking invertebrate drift with fish feeding 

habits.” Owing to the extensive tagging effort in this study, other research studies are possible 

which allow for greater collaboration between these research studies. Currently the NO project 

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provides the logistical framework for data collection and some of the analysis as part of the JCM 

project (see Project Element 7.2) and other research elements proposed addressing the 

underlying mechanisms for trout growth and possible movement (see Project Elements: 5.2.2, 

9.2, 9.3, 9.4, 9.7, 9.9, and 9.10). 

Products expected from this project are a series of peer-reviewed publications.

Project Element 9.3. Exploring the Mechanisms behind Trout Growth, Reproduction, and Movement in Glen 

and Marble Canyon using Lipid (fat) Reserves as an Indicator of Physiological Condition 

(Recommended for funding FY15: $102,660)

Kimberly Dibble, Research Biologist, USGS, GCMRC

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research Inc.

Ted Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC 

The objective of this research is to determine whether the ability of adult rainbow trout to 

acquire and store energy from the prey base is a potential mechanism behind spatial and 

temporal differences in growth, reproduction, and movement of rainbow trout in Glen and 

Marble Canyons.

As described in GCMRC’s FY13–14 Work Plan (see Project Elements H.2 & L.2.2), 

rainbow trout size, distribution, diet, and prey base data have been collected for the past two 

years to examine potential drivers of trout growth, movement, and population size in Glen and 

Marble Canyons. Continuations of these projects have been requested as part of the FY15–17 

Work Plan (see Project Element 9.2), so we propose to add an additional component to this 

project to quantify lipid (fat) reserves in a subsample of the fish that are already sacrificed to 

collect data on trout diet. This provides an opportunity to leverage an existing project to gain 

exciting scientific information in a cost-effective way. Briefly, five sampling reaches 

downstream from Glen Canyon Dam will be sampled on two separate nights during four seasons 

over one year. Fish tissue (muscle, liver, hindgut) will be excised, preserved in liquid nitrogen, 

and brought back to GCMRC for biochemical analysis. In the laboratory, total lipid will be 

extracted gravimetrically (Bligh and Dyer, 1959; Phillips and others, 1997) and then separated 

into lipid classes (e.g., non-polar “storage” lipids and polar “structural” lipids) using highperformance thin layer chromatography (Churchward and others, 2008; Zhou and others, 2012). 

These data will then be used to: 1) examine temporal and spatial differences in the physiological 

condition of trout in Glen and Marble Canyons; 2) improve rainbow trout growth models 

currently in development by Korman and Yard; and 3) understand the mechanisms behind the 

maximum size and growth potential of rainbow trout in Lees Ferry. 

Lipid mass data will be examined in combination with growth (mark-recapture data from the 

whole population; Project Element 9.1), diet (from the same individuals), and drift availability 

(see GCMRC’s FY13–14 Workplan, Project Element F.7.1, FY15–17 Workplan, Project 

Element 5.2.2) to assess how energy availability and storage plays a role in rainbow trout 

growth, reproduction, and movement across all study reaches during multiple seasons. These 

data will be especially important in elucidating the mechanisms behind reproduction in Marble 

Canyon. If adult rainbow trout are critically depleted in lipid mass throughout the growing 

season (e.g., due to high turbidity in summer) such that energy stores are depleted in fall and 

spring, there is a high likelihood that fish in Marble Canyon may choose to forgo spawning or 

reabsorb eggs and gametes to survive (Adams 1999, Hutchings and others, 1994, 1999), which 

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may explain the apparent reduction in local reproduction in lower Marble Canyon by the LCR 

(Korman and others, 2012).

These data will also be used to improve modeling efforts that assess rainbow trout population 

dynamics in Glen and Marble Canyons. Korman and Yard have analyzed preliminary data from 

the Natal Origins project to assess spatial and temporal differences in rainbow trout growth 

(length and weight; GCMRC Annual Reporting Meeting, January 2014; 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/14jan30/). However, unexplained patterns in weight 

loss in the late summer (when the fish should be gaining weight in preparation for winter) 

indicate the fish may have switched to a fat storage strategy (Adams, 1999), which as described 

above, would be under-represented in the growth analysis. Models will be improved by 

incorporating data on spatial and temporal fluctuations in tissue energy density, which is a more 

reliable indicator of weight gain.

In addition to helping answer mechanistic questions related to rainbow trout growth, these data 

will also improve our understanding of factors that constrain the maximum size of trout in Lees 

Ferry. One of the main hypotheses in the FY15–17 Work Plan (H.2) was that the size of and 

species available in the prey base (primarily midges and black flies) support the growth of small 

rainbow trout but limit the growth of large adult trout. This hypothesis is supported by research 

conducted by McKinney and Speas (2001) that found that adult rainbow trout are more often 

food-limited than smaller trout. Rainbow trout, like other temperate fishes, invest in somatic 

growth (length) prior to investing in visceral (fat) stores, so lipid mass vs. length should show an 

allometric relationship (Post and Parkinson, 2001; Simpkins and others, 2003). However, 

preliminary data indicate the opposite, with small fish having larger fat reserves per gram of 

body tissue than large adult fish (Dibble, unpublished data). Therefore, additional lipid data will 

be very useful in evaluating the hypothesis that rainbow trout fail to reach trophy status due to a 

diminished prey base.

Project Element 9.4. Comparative study on the feeding morphology of drift feeding fish 

(Unfunded, Moderate Priority FY15: $86,420)

Michael Yard, Fishery Biologist, USGS, GCMRC

Joel Sankey, Research Physical Scientist, USGS, GCMRC

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

Josh Korman, President, Ecometric Research Inc.

The objective to this project element is to determine if prey retention efficiencies associated 

with the feeding morphology of rainbow trout, brown trout, and humpback chub are potentially 

constrained by the size of invertebrate prey available in the CRe. 

Prey size has a strong effect on foraging success because prey items are not always retained once 

consumed. In a functional sense, once prey items are captured in the mouth cavity of a fish, 

water passes through the gill-rakers like a sieve, and prey are retained and ingested. Therefore, 

branchial arch/gill-raker morphology may control feeding efficiencies (i.e., the number of prey 

consumed divided by the number of prey captured) such that larger prey items are more often 

retained than smaller prey. Feeding efficiencies change because morphological structures 

become larger with increasing fish length (Breck and Gitter, 1983; MacNeill and Brandt, 1990), 

which cause larger fish to selectively retain only larger prey items (Budy and others, 2005). 

Therefore, size-related changes in feeding morphology are likely to vary within the same species 

due to plasticity of morphological traits (Keeley and others, 2007); essentially structural 

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relationships may vary between different environments even though it is the same species. 

Similarly, these same morphological structures are highly likely to vary among different species, 

which may be partially responsible for resource partitioning. Lack of prey diversity and minimal 

prey size in the CRe (Cross and others, 2013) has likely influenced competitive and piscivorous 

interactions between native and non-native fishes. Findings from these analyses will be used to 

test hypotheses H2.1, H2.2, and H3 (potential for intra- and interspecific competition)

In this study, we propose to (1) measure gill-raker number, length, and spacing for three drift 

feeding species: rainbow trout, brown trout, and humpback chub; (2) develop and compare 

branchial arch and gill-raker morphology within and among fishes; (3) determine if mean prey 

size distributions found in fish diet correlate with morphometrics (i.e., method of quantifying a 

structure through measurements of size, shape, and quantity); (4) and determine if diet electivity 

for prey size distributions are proportionally greater in the fish diet than what is found available 

in the drift Exploring these other types of quantitative methods may further reduce the amount of 

analytical time and cost associated with conducting these types of morphometric measurements.

Invertebrate drift and diet samples for rainbow and brown trout have been and are continuing 

to be collected as part of the Foodbase Monitoring project (see GCMRC’s FY13–14 Workplan, 

Project Element F.7.1). Since humpback chub are an endangered species, source material used 

for morphometric analysis will be acquired from incidental mortalities (GCMRC monitoring 

program, 2000-Present), archival collections, and from breeding stock mortalities at Dexter 

National Fish Hatchery. For each fish species, we will evaluate a large size distribution (~50 to 

400+ mm fork length) and develop relationships between fish size and morphological 

characteristics. The minimum fish size has yet to be determined because of developmental 

differences in feeding structures. For comparative purposes, morphological data will be paired 

with detailed diet analysis (prey size and prey densities), using a subset of fish samples 

containing both branchial arches and stomach contents. For the fish length relationships we will 

select and measure three fish per size class, with samples grouped at 5 mm increments. Because 

of limited availability, comparisons made between chub diet and feeding morphology are 

unlikely. This project will produce two manuscripts, each suitable for publication. Expected 

timeline for project completion is 2017.

Project Element 9.5. Meta-analysis, and the development of reactive distance relationships for encounter rate 

models 

(Recommended for funding FY15: $20,000; Unfunded High Priority FY15: $18,512)

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research Inc.

Charles Yackulic, Research Statistician, USGS, GCMRC

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

The objective of this project element contains two parts: (1) determine the effects of varying 

light intensity and prey size on fish reactive distances; and (2) develop an encounter rate model 

for drift feeding fish that accounts for varying reactive distances and prey availability within the 

range of channel depths and light levels encountered in Glen and Marble Canyons.

Underwater light intensities are likely to interact with different prey sizes because larger 

rather than smaller items are perceived at greater distances. Reactive distance relationships have 

been developed for a number of fish species (e.g., Howick and Obrien, 1983; Vinyard and 

O’Brien, 1976; Ware, 1973); however, inconsistencies exist in the literature. This is partly due to 

the scope and range of variables experimentally tested, particularly with the use of turbidity as a 

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predictive proxy for light (e.g., Barrett and others, 1992; Sweka and Hartman, 2003). 

Considering that underwater light intensities change over the day and with increasing depth, 

most turbidity-based relationships are limited in application to small, clear, and shallow (depth < 

0.5 m) streams. There are however a number of existing models that have been developed 

specifically for the CRe that account for variation in light reaching the water surface due to 

canyon topography (Yard and others, 2005) as well as predictive relationships between the 

underwater light attenuation and suspended sediment (Yard, 2003). 

We will conduct an extensive meta-analysis on all known published data on reactive 

distances (i.e., distance a prey item can be visually detected) of visual sight-feeding fish. We will 

evaluate literature and quantitatively summarize regression slopes obtained from independent 

studies, either published as relationships or through extraction of data from graphs and tables 

(Tummers, 2006). Through this meta-analysis we are going to refine the predictive capabilities 

of these reactive distance relationships so that they can be broadly applied to more realistic 

environmental conditions. We will evaluate specific variables that affect predator reactive 

distances, including light intensity, turbidity, prey size, and predator size. Findings from this data 

synthesis will inform the process used in selecting or developing the most appropriate 

relationships to use in developing an encounter rate model (i.e., quantifying the daily number of 

drifting invertebrates encountered by a visual sight feeding fish; Gerritsen and Strickler, 1977; 

Harvey and Nakamoto, 2013). From this analysis, the type of encounter rate model selected will 

be a critical element for developing an accurate bioenergetic model capable of linking driftavailability and metabolic demands thought to limit overall fish growth in a seasonally turbid 

river (see project 9.7).

Data sets from both long-term monitoring and research studies will be used for developing an 

encounter rate model for rainbow trout. These data requirements include seasonal variation in 

invertebrate drift (Project Element 5.2.2), and other physical data such as instantaneous light 

intensities (Yard and others, 2005), channel characteristics, flow discharge, and suspended 

sediment concentrations (http://www.gcmrc.gov/discharge_qw_sediment/). Encounter rates will 

be determined for five specific study reaches (NO reach designation) located between Glen 

Canyon and the LCR confluence area. We will model the potential influence that reduced light 

levels have on the frequency of trout daily encounter rates (mediated through differences in 

channel depths, turbidity levels, and invertebrate drift). Findings from these analyses will be used 

to test hypothesis H2.3, as well as compare responses to other independent data on trout diet (see 

Project Element 5.2.2.), monthly growth rates (see Project Element 9.2), and physiological 

condition (see Project Element 9.3). Results from this will determine whether or not reduced 

encounter rates exert a population-level effect on rainbow trout throughout Glen and Marble 

Canyons. This project will produce two manuscripts, each suitable for publication. Expected 

timeline for project completion is 2017.

Project Element 9.6. Evaluation of Turbidity (in terms of TSS) as a potential Glen Canyon Dam operations 

management tool to constrain rainbow trout populations and reduce predation/competition on juvenile 

humpback chub 

(Recommended for funding FY15: $37,120)

David Ward, Fishery Biologist, USGS, GCMRC

The objective to this project element is to determine what level and duration of turbidity 

would be necessary to negatively effect, or prevent persistence of, rainbow trout in the areas near 

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mid-to-lower Marble Canyons and below the Little Colorado River confluence in eastern Grand 

Canyon. This project also aims to determine whether turbidity levels in the Colorado River could 

be manipulated during years of minimum annual release coincident with Paria and Little 

Colorado River fine-sediment inputs, so as to limit downstream rainbow trout outmigration from 

their natal origin habitat areas above the Paria River.

Predation on juvenile humpback chub by rainbow trout is considered a significant threat to 

humpback chub populations in Grand Canyon (Marsh and Douglas, 1997; Coggins and others, 

2011; Yard and others, 2011; Runge and others, 2011). Relatively low levels of turbidity <100 

Formazin Nephelometric Units (FNU) have been found to effectively reduce vulnerability of 

juvenile humpback chub to predation by rainbow trout (Ward, 2014 AMWG poster session, 

unpublished data), and extended periods of turbidity have been shown to negatively impact and 

exclude salmonids in other systems (Harvey and Railsback, 2011, reviewed in Newcombe and 

MacDonald, 1991). Increasing turbidity can also have positive effects on small species and 

juvenile fish but a negative effect on larger piscivorous fishes (Utne-Palm, 2002). Understanding 

how the magnitude and duration of turbidity in the Colorado River impacts various life stages of 

rainbow trout will allow researchers to better evaluate turbidity as a potential management tool 

of juvenile humpback chub in Marble and eastern Grand Canyons.

This project is intended to evaluate the feasibility of using dam operations in response to 

naturally input fine sediment-induced turbidity as a management tool to disadvantage trout 

populations in the mainstem Colorado River near the confluence with the Little Colorado River. 

This project includes laboratory studies to evaluate turbidity effects on trout, as well as modeling 

of turbidity (silt/clay) routing from the Paria River to areas downstream of the Little Colorado 

River down to river mile 87 (Grand Canyon stream gage near Phantom Ranch). In the laboratory, 

we will evaluate the effects of multiple turbidity concentrations (50–200 FNU) and extended 

high turbidity durations (1–5 months) to identify turbidity thresholds that negatively impact 

rainbow trout and reduce survival. LISST-100 instrumentation will be used in combination with 

YSI turbidity probes to compare level of FNUs to total suspended sediment concentration and 

grain size distributions in controlled tank experiments (Voichick and Topping, written commun., 

USGS, 2014). We propose to develop a model (Anderson and Wright, 2007) to include routing 

of sediment finer than sand; particle sizes which are known to significantly elevate turbidity at 

relatively low concentrations. This will enable researchers to route and predict the downstream 

fate of silt and clay (persistence of suspended finer sediments) that cause turbidity from the Paria 

River downstream into Marble and Grand Canyon, as well as between the LCR and Grand 

Canyon gage, so as to estimate the possibilities for routing silt and clay concentrations needed to 

produce target turbidities (determined from laboratory studies to disadvantage trout) upstream 

and below at the LCR confluence. This information will allow for science based, data driven 

discussions of possible annual-to-multiyear scenarios for seasonal dam operations under 

minimum annual release volumes from Lake Powell that may allow levels of turbidity associated 

with natural tributary sediment inputs to be used as a fish management tool. 

Originally an idea from the 1995 EIS, MLFF was purposefully intended to allow 

accumulation of sand inputs within reaches below the Paria and Little Colorado Rivers prior to 

sandbar building controlled floods, but higher monthly release volumes associated with 

hydropeaking operations in winter and summer seasons have been shown to accumulate sand 

inputs under minimum volume release years when tributary sediment loads are above average 

and occur in consecutive years, such as Topping and others, (2010) report for sediment years 

2006–07, preceding the 2008 HFE. To date, evaluation of turbidity has been limited to field 

measurements in Marble Canyon during 2013–14; a period of above average Paria River 

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sediment loading, the lowest annual release volume since 1964, but also a period of fall HFE 

operations. Flow and finer-sediment modeling would allow evaluation of the potential for 

season-to-season management of fines for elevating turbidity, but without having to forego fall 

HFEs after tributary sand enrichment as a large-scale experiment.

Understanding how turbidity impacts rainbow trout is critical in evaluating flow and exotic 

fish control management options aimed at preservation of native fishes in Grand Canyon. Runge 

and others, (2011) in assessing 19 options for mitigating the negative influence of rainbow trout 

on humpback chub identified sediment augmentation from sources in Lake Powell to Lees Ferry 

as likely the most effective treatment for reducing trout predation on chub juveniles, and 

numerous studies (Reviewed in Newcombe and MacDonald, 1991) demonstrate that relatively 

low sediment concentrations can adversely impact rainbow trout populations. Questions 

regarding effects of turbidity on fish are difficult to answer in a field setting because of 

confounding factors and the often extended time periods needed to evaluate turbidity effects, but

these types of interactions can often effectively be evaluated in laboratory settings (Hairston, 

1989). Previous discussions about sediment augmentation below Glen Canyon Dam were aimed 

at restoring both sand and finer sediment to the river to benefit native fish, as well as sandbars, 

which was cost prohibitive, but small scale silt and clay augmentation that only increase turbidity 

slightly may be just as effective at reducing predation mortality of native fish and was identified 

by Randle and others, (2007) as much less costly than sand augmentation. We currently have a 

very good 1-D sand routing model (Wright and others, 2010), but unfortunately sand has very 

little influence on turbidity (Voichick and Topping, written commun., USGS, 2014). Hence, 

additional modeling development is needed to route the finer sediments that cause turbidity. 

Seasonally focused flow management efforts to increase turbidity within the Colorado River may 

be a much more cost effective and acceptable solution than downstream mechanical trout 

removal (Coggins and others, 2011) as a means to reduce predation and competition on juvenile 

humpback chub, particularly during periods when dam releases are naturally warmer at the LCR; 

a condition known in 2011 to be associated with reduced juvenile chub annual survival (possibly, 

linked to increase trout metabolism; see Keiffer and others, 1994). This project will allow an 

assessment of turbidity as a trout management tool, from both a lab experimental perspective and 

in the context of field data and flow and suspended sediment modeling simulations tied to dam 

operations and tributary fine sediment inputs.

Project Element 9.7. Application of a bioenergetics model in a seasonally turbid river 

(Recommended for funding FY15: $33,234; Unfunded High Priority FY15: $33,324)

Michael Dodrill, Fishery Biologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research, Inc.

The objective to this project element is to adapt process-oriented ecological models (such as 

drift-foraging bioenergetics or net energy intake methods) to quantify the effects of physical 

conditions (i.e., flow, turbidity, and depth) and food availability on rainbow trout growth and 

distribution. 

Understanding the linkages between food availability and growth of drift feeding fish in large 

regulated rivers presents significant challenges to scientists and managers. Process-oriented 

ecological models show promise for describing ecological dynamics in rivers across levels of 

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biological organization (Anderson and others, 2006). Linked foraging-bioenergetics or Net 

Energy Intake (NEI) models explicitly consider physical habitat (depth, velocity) and ecological 

processes (drift-availability) to describe the foraging process and how food availability translates 

into fish growth. These methods have been used to assess the effects of invertebrate drift size 

structure on the lifetime growth of drift-feeding fish (Hayes and others, 2000), assess habitat, and 

provide an alternative to traditional approaches (i.e., PHABSIM) for predicting the response of 

fish changes in physical conditions, such as altered flow regimes (Rosenfeld and Ptolemy, 2012) 

or turbidity levels (Harvey and Railsback, 2009). 

Building on preliminary methods developed for Lees Ferry (Dodrill, unpublished data), 

coupled drift-foraging bioenergetics have identified linkages between drift-availability and 

metabolic demands thought to limit overall fish growth. Benthic invertebrates are the ultimate 

source of drift consumed by rainbow trout and contribute to the spatial patterns of drifting 

invertebrates. Understanding factors that influence the spatial and temporal dynamics of

invertebrate drift and physical factors (such as turbidity or flow conditions) that influence the 

detection of food items (Project Element 9.5) will help to correlate patterns of rainbow trout 

growth and abundance (Project Element 9.2) to underlying mechanisms. We propose integrating 

data sourced from existing and proposed projects to develop and parameterize process-oriented 

models. This includes information on invertebrate drift rates (Project Element 5.2.2), channel 

characteristics (Project Element 10.1), turbidity, and temperatures for river segments extending 

from Lees Ferry to the LCR. 

Project Element 9.8. Mechanisms that Limit Rainbow and Brown Trout Growth in other Western Tailwater 

Systems 

(Recommended for funding FY15: $72,384)

Kimberly Dibble, Research Biologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC 

Ted Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Phaedra Budy, Research Aquatic Ecologist, USGS, Utah Coop. Fish and Wildlife Research Unit

Michael Dodrill, Fishery Biologist, USGS, GCMRC

The objective of this research is to continue to develop a broader understanding of the links 

between dam operations and salmonid population dynamics by synthesizing data from tailwaters 

across the Western United States.

Under Project H.2 of GCMRC’s FY13-14 Workplan, the principal investigator amassed 

fishery, discharge, reservoir, food base, and other data from 56 dams throughout the West. We 

are in the process of analyzing this dataset and continued funding will maximize the degree to 

which the GCDAMP can learn from other tailwater ecosystems. The analysis presented at 

GCMRC’s Annual Reporting Meeting (January 2014) was an appropriate first step at 

synthesizing these data and addressed one of the four main hypotheses (H4) related to changes in 

trout size over time relative to dam operations. This analysis focused on the influence of 

hydropeaking, seasonal flow, specific discharge, and other metrics on trout size, recruitment, and 

catch-per-unit-effort downriver of dams with multiple purposes (e.g., hydropower, irrigation, and 

storage). This analysis allowed us to understand broad correlations between dam operations and 

aspects of trout populations across many dams and we are in the process of preparing a 

manuscript based on these results, which will be submitted for publication in FY14. 

We propose to complement this broad assessment with in-depth analyses of tailwaters that 

contain a rich time-series of information. This new set of analyses will be focused on assessing 

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the mechanisms behind salmonid growth as they relate to dam operations (e.g., prey availability, 

temperature, nutrients) using a subset of high-quality fishery data from the Colorado River Basin 

that spans 20+ years. For example, does discharge volume and/or hydropeaking directly 

influence trout size, or does discharge indirectly influence trout size through another variable 

(e.g., prey availability or nutrient inputs from the reservoir). Since all the data for this analysis 

are already collected, we expect to begin our work within FY14, with the expectation that it will 

spill over into FY15. We will prepare one manuscript for publication associated with the new 

analysis in FY15. 

In addition to the mechanistic model developed in FY15, we propose to apply bioenergetics 

models developed for rainbow trout in Glen and Marble Canyon to other data-rich tailwaters in 

the Colorado River Basin (CRB) to further elucidate mechanisms responsible for differential 

performance on trout fisheries. By applying the same modelling format to different tailwaters, it 

should ease our ability to interpret differences between Glen Canyon and other tailwater systems. 

We have high-quality fishery, growth, foodbase, temperature, discharge, and reservoir data from 

Flaming Gorge Dam, which is the system that is most comparable to Glen Canyon Dam in the 

CRB. However, it differs from Glen Canyon because it has a selective withdrawal device that 

allows modification of the thermal regime (a phenomenon that may occur naturally below Glen 

Canyon resulting from climate change), it differs in invertebrate composition, and its trout 

population is composed of >50% brown trout. Brown trout are highly efficient predators (Yard 

and others, 2011), and their population expansion has been of concern in the Colorado River

downriver of Glen Canyon Dam. Therefore, we propose to develop a bioenergetics model for the 

Flaming Gorge tailwater that is similar to the model currently being developed for Glen Canyon, 

which will examine how prey size, water velocity, temperature, and rainbow and brown trout 

density (competition) influence the growth potential of rainbow trout. In addition, we may also 

construct a bioenergetics model for the tailwater below Navajo Dam. The Navajo tailwater lacks 

thermal modification and differs from Glen Canyon and Flaming Gorge in its flow regime (no 

hydropeaking), invertebrate assemblage, and brown trout density (~39%). Comparison of Glen 

Canyon to other tailwaters from a bioenergetics perspective will yield important insights that will 

be useful in the management of Glen Canyon Dam operations. We will prepare one manuscript 

in FY16 associated with these bioenergetics models.

Project Element 9.9. Effects of High Experimental Flows on Rainbow Trout Population Dynamics 

(Recommended for funding FY15: $72,616)

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research, Inc.

Charles Yackulic, Research Statistician, USGS, GCMRC

Ted Melis, Physical Scientist, USGS, GCMRC

Dan Buscombe, Research Geologist, USGS, GCMRC

Thomas Gushue, Computer Specialist, USGS, GCMRC

The objective to this project element is to determine the effects of fall HFEs and other 

potential management actions, such as the Fall Steady Flow treatments of 2011–12, on rainbow 

trout populations in Glen Canyon. The purpose of the contingency plan as originally proposed 

(GCMRC FY13–14 Workplan, Project Element H.3) was to determine the effect of a single fall 

HFE on age-0 trout densities. Although spring floods were known to have a large effect on early 

life stages of age-0 trout (Korman and Campana, 2009), there was considerable uncertainty about 

the effect that fall floods had on the survival of age-0 trout due to seasonal differences in growth 

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(Melis and others, 2012). Typically, age-0 fish have a higher mortality rate than adults, yet rates 

begin to stabilize through late-summer into fall (Korman and others, 2011). The experiment was 

originally designed to estimate age-0 trout density and survival during pre- and post-flood 

periods, and then compare estimates between years with and without experimental floods. 

Currently we have successfully estimated changes in the apparent survival across two successive 

HFEs, flow events that had different magnitudes and durations, but due to hydrology we have 

been unable to acquire data during a year without an experimental flow. 

The sampling design uses two mark-recapture trips that are conducted annually during earlyand late-fall and samples the entire 25 km reach between Glen Canyon Dam and Lees Ferry. On 

average a total of ~5,000 fish are tagged with passive integrated transponders (PIT tags) per trip 

to determine site-specific capture probabilities for estimating age-0 fish abundance. A second 

trip is repeated in late-fall, to estimate across-trip survival and growth using recapture 

information from the previous trip. Although age-0 trout densities were estimated to be very high 

at the inception of the research study (fall 2011) successive marking efforts conducted in 2012 

and 2013 have each required an additional 10-day sampling trip per year to tag sufficient 

numbers of trout (~10,000 age-0 trout quota) for the Natal Origin Project (see Project Element 

9.2). For this reason we propose a continuation of funding for fall marking trips through FY16, 

when at that time the Natal Origins research project will transition to monitoring led by AGFD. 

Funding for this project will support additional fieldwork and tagging efforts necessary for 

meeting the Natal Origin research objectives, as well as providing a means to further evaluate 

multiple fall-HFEs over a range of different age-0 fish densities. Also, efforts were started in fall 

2013 to assess change in Glen Canyon channel-bed texture (Natal Origins Reach 1) in response 

to August 2013 fine-sediment inputs to that reach from Waterholes Canyon (the reach being 

imaged with side-scan sonar in October and December 2013 to bracket the November 2013 HFE, 

as well as in April 2014 to assess evolving shorelines and bed textures relative to ongoing trout 

monitoring and research.

Project Element 9.10. Examining the Effects of High Flow Experiments on the Physiological Condition of Age-0 

and Adult Rainbow Trout in Glen Canyon 

(Recommended for funding FY15: $54,404)

Kimberly Dibble, Research Biologist, USGS, GCMRC

Luke Avery, Fishery Biologist, USGS, GCMRC

Michael Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, President, Ecometric Research, Inc.

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

The objective of this research is to quantify the effect of lower and steadier fall flows (~5,000 

ft3/s) followed by an HFE on the physiological condition and growth of age-0 and adult rainbow 

trout in Glen Canyon.

In fall 2012 and 2013, the Federation of Fly Fishers raised concerns regarding the potential 

effects of lower and steadier fall flows followed by an HFE on the foodbase for rainbow trout in 

Glen Canyon. Although previous research indicates that steadier flows can increase the growth 

rate of age-0 rainbow trout (Korman and Campana, 2009), and spring-timed HFEs can increase 

their survival and growth (Korman and others, 2011), it is unclear how lower and steadier fall 

flows (5,000-8,000 ft3/s) followed by a potentially energetically costly HFE may influence the 

growth and physiological condition of rainbow trout during a season where prey are typically 

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limited. It is also unclear how quickly the trout population recovers following such an event, and 

whether the response for age-0 and adult fish differs. Therefore, this research will assess rainbow 

trout condition by using total lipid mass and lipid classes (e.g., storage fats, triacylglycerols) as 

sensitive biochemical indicators of physiological condition. In addition, otoliths of age-0 

rainbow trout will be collected in post-flood fish to examine their daily growth rate in the weeks 

prior to and following an HFE to assess response and recovery time. These data will be 

compared to food base data collected prior to, during, and after the HFE. In addition, data will be 

collected in fall during a non-HFE year to compare rainbow trout condition and growth in a 

normal year to those influenced by an HFE. 

Field sampling to collect fish will largely be incorporated into existing research and 

monitoring trips (Project Elements 6.7 [RTELSS], 9.2 [Natal Origins], and 9.9 [HFE/Fall 

Marking]), but additional electrofishing trips may be necessary. Total lipid will be extracted 

gravimetrically from whole-body age-0 fish and from adult tissue samples (Bligh and Dyer, 

1959; Phillips and others, 1997), and total lipid will be separated into lipid classes using highperformance thin layer chromatography (Churchward and others, 2008; Zhou and others, 2012). 

Otoliths will be extracted from age-0 rainbow trout (Secor and others, 1991) collected during an 

HFE year and prepared for growth rate analysis using the distance between daily increments preand post-flood (Gilliers and others, 2004; Amara and others, 2009). In addition, age-0 otoliths 

will be checked for a “check” (a dark line indicating daily growth rings are placed very close 

together) to determine whether growth is interrupted in response to environmental conditions 

prior to and during the HFE. Growth rate measurements will be compared to those from fish 

captured during a non-HFE year to account for normal seasonal fluctuations in growth that occur 

regardless of the occurrence of a controlled flood.

D.2 Personnel and Collaborations 

The overall project lead for Research Project 9.0 is Dr. Michael Yard a fishery biologist with 

U.S. Geological Survey, Grand Canyon Monitoring and Research Center (GCMRC). Dr. Josh 

Korman a fishery biologist with Ecometric Research Inc., and is the principal investigator for the 

Natal Origin Project (9.2) specializing in analytical models and database development, 

population dynamics, and modelling capabilities. Dr. Kim Dibble is a post-doctoral fellow and 

research biologist at GCMRC with expertise in fish physiology and metadata analysis. Dr. 

Charles Yackulic is a research statistician specializing in population dynamics with an emphasis 

in modeling linkages and vital rates between trout populations. Dr. Theodore Melis is a physical 

scientist and will be instrumental in assessing changes in channel-bed texture and relationships 

among fish communities. Daniel Buscombe is a post-doctoral fellow and Research Geologist 

with specialization in image processing and bed-texture characterization. Thomas Gushue is a 

GIS specialist, expert in collecting, processing, and analyzing digital elevation models.

D.3 Deliverables 

Journal articles will be prepared in FY15–17 covering several of the following components 

of this project:

• Factors leading to differential growth in rainbow trout (Oncorhynchus mykiss) in the 

Colorado River, Grand Canyon. 

• Experimental flood effects on age-0 rainbow trout in the Colorado River, Grand Canyon.

• Analytical methods using a modified open robust design: estimation of rainbow trout 

abundance in a large spatially complex river. 

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• Using a hierarchical Bayesian model: estimating age-0 rainbow trout abundance in the 

Lees Ferry sport fishery.

• Estimating rainbow trout (Oncorhynchus mykiss) emigration using capture-recapture data 

with open robust design models

E. Productivity from Past Work (during FY 13–14) 

E.1. Completed Publications 

Kennedy, T.A., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M.D., and Copp, A.J., 2013, 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river, Freshwater Biology, v. 59, p. 557-572.

Ward, D.L., Morton-Starner, R., and Hedwall S.J., 2013, An evaluation of liquid ammonia 

(ammonium hydroxide) as a candidate piscicide, North American Journal of Fisheries 

Management, v. 33, p. 400-405. 

Yackulic, C.B., Yard, M.D., Korman, J., and Van Haverbeke, D.R., 2014, A quatitative life 

history of endangered humpback chub that spawn in the Little Colorado River: variation in 

movement, growth, and survival: Ecology and Evolution, doi: 10.1002/ece3.990.

E.2. Publications in progress 

Dibble, K.L., Yackulic, C.B., Kennedy, T., and Budy, P., Factors that limit salmonid size in 

tailwater fisheries across the western United States. 

Ward, D.L., and R. Morton-Starner. In prep. Effects of turbidity on predation vulnerability of 

humpback chub to rainbow trout and brown trout.

Yard, M.D., Coggins, L.G., Kennedy, T., and Yackulic, C.B., Effects of turbidity on foraging 

ecology of nonnative rainbow trout and brown trout

E.3. Presentations at GCDAMP meetings 

Dibble, K.L., Yackulic, C.B., Kennedy, T., and Budy P., 2014, Context and comparison: status 

of tailwater fisheries in the Western United States: Annual Reporting Meeting to the 

Adaptive Management Program for Glen Canyon Dam. Phoenix, AZ, 1/28/2014.

Korman, J., and Yard, M., 2014, Rainbow trout movement, growth, population dynamics and 

modeling in Glen and Marble Canyons: Annual Reporting Meeting, Adaptive Management 

Program for Glen Canyon Dam, Phoenix, AZ, 1/28/2014. 

Melis, T.S., Gushue, T., Kennedy, T.A., Muehlbauer, J.D., Yard, M.D., Grams, P.E., Sankey, 

J.B., Kohl, K., Andrews, T., Hazel, J.E., Jr., and Korman, J., 2014, Low flows in Glen 

Canyon, preliminary geomorphic analysis of the potential effects on fish and foodbase: 

Annual Reporting Meeting to the Adaptive Management Program for Glen Canyon Dam. 

Phoenix, AZ, 1/28/2014.

Rogowski, D., 2014, Colorado River trout population monitoring: spawning and rearing surveys, 

seasonal and annual electrofishing surveys, and creel survey: Adaptive Management Program 

for Glen Canyon Dam, Phoenix, AZ, 1/28/2014. 

Ward, D.L. and R. Morton-Starner (2014). Effects of turbidity on predation vulnerability of 

humpback chub to rainbow trout and brown trout: Glen Canyon Dam Adaptive Management 

Program Annual Reporting Meeting, Phoenix, AZ. POSTER – TWG and AMWG meetings.

Yackulic, C., Yard, M.D., Korman, J., Van Haverbeke, D.R., and Coggins, L., 2014, Results 

from Colorado River study site and ongoing population modeling: Annual Reporting 

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Meeting , Adaptive Management Program for Glen Canyon Dam, Phoenix, AZ, 1/28/2014. 

E.4. Presentations at professional meetings 

Avery, L., Korman, J, and Copp, A., 2013, Flow related responses of the age-0 population of 

rainbow trout in Lees Ferry, Desert Fishes Council, Flagstaff, AZ. 11/20/13.

Dibble, K.L., Yackulic, C.B., Kennedy, T., and Budy, P., 2013, What factors drive salmonid 

growth in tailwater ecosystems? A synthesis of data on salmonid population dynamics and 

dam operations across the Western United States, Annual Colorado River Fish Cooperator’s 

Meeting, Flagstaff, AZ, 12/19/2013.

Dibble, K.L., Yackulic, C.B., Kennedy, T., Budy, P., and Korman J., 2013, What can we learn 

from other tailwaters? A synthesis of data on salmonid population dynamics and dam 

operations across the Western United States, 12th Biennial Conference of Science and 

Management on the Colorado Plateau, Flagstaff, AZ, 9/18/13.

Dibble, K.L., 2013, Telling tall tales? Teasing out the mechanisms behind changes in trout size 

over time in western tailwaters, Watershed Sciences Department, Utah State University, 

Logan, UT. 5/8/13. 

Dodrill, M., Pine, B., Gerig, B., and Finch, C., 2013, Steady as she flows: assessing the response 

of native fish to a steady flow experiment from Glen Canyon Dam, Desert Fishes Council, 

Flagstaff, AZ. 11/20/13.

Rogowski, D., 2013, Does variation in sampling effort during a long term monitoring project 

matter (Lees Ferry, Colorado River)?, Desert Fishes Council – Flagstaff, AZ. AZ. 11/20/13.

Morton-Starner, R., and Ward, D.L., 2014, An experimental evaluation of competition between 

rainbow trout and humpback chub. Desert Fishes Council – Flagstaff, AZ. 

Ward, D.L., and Morton-Starner, R., 2014, What environmental factors reduce predation 

vulnerability for native fish? Colorado River Area Biologists Meeting, Laughlin, NV.

Ward, D.L., and Morton-Starner, R., 2014, Effects of water temperature and turbidity on 

predation vulnerability of juvenile humpback chub to rainbow trout and brown trout. Desert 

Fishes Council – Flagstaff, AZ. AZ. 11/20/13.

Wolters, P., 2013, Common carp ages, back calculations and growth rates at a large backwater 

above Lees Ferry in Glen Canyon, Colorado River, Desert Fishes Council – Flagstaff, AZ. 

AZ. 11/20/13.

Yackulic, C., Yard, M., Korman, J., and Vanhaverbeke, D.R., 2013, A quantitative life history of 

humpback chub that spawn in the Little Colorado River: variation in movement, growth and 

survival, Desert Fishes Council, Flagstaff, AZ. 11/20/13.

Yard, M., Korman, J., Kennedy, T., Yackulic, C., VanderKooi, S., 2013, Turbidity effects on 

spatial dynamics of rainbow trout abundance and growth, Grand Canyon, AZ, 

F. References 

Adams, S.M., 1999, Ecological role of lipids in the health and success of fish populations, in 

Arts, M.T., and Wainman, B.C., eds., Lipids in freshwater ecosystems: New York, Springer, 

p. 132-160.

Amara, R., Selleslagh, J., Billon, G., and Minier, C., 2009, Growth and condition of 0-group 

European flounder, Platichthys flesus as indicator of estuarine habitat quality: Hydrobiologia, 

v. 627, p. 87-98.

Anderson, C.R, Wright, S.A., 2007, Development and application of a water temperature model 

for the Colorado River ecosystem below Glen Canyon Dam, Arizona: Hydrological Science 

297
and Technology, v. 23, no.1–4, Annual Meeting and International Conference, Reno, Nev., 

April 22-25, 2007, Proceedings: American Institute of Hydrology, p. 13–26.

Anderson, K.E., Paul, A.J., McCauley, E., Jackson, L.J., Post, J.R., Nisbet, R.M., 2006, Instream 

flow needs in streams and rivers--the importance of understanding ecological dynamics: 

Frontiers in Ecology and the Environment, v. 4, no. 6, p. 309 – 318.

Anderson, M.C., Bunch, A.J., and Osterhoudt, R.J., 2012, Status of the Lees Ferry rainbow trout 

fishery: Flagstaff, Arizona Game and Fish Department.

Angradi, T.R., and Kubly, D.M., 1993, Effects of atmospheric exposure on chlorophyll a, 

biomass and productivity of the epilithon of a tailwater river: Regulated Rivers--Research 

and Management, v. 8, no. 4, p. 345-358, http://www3.interscience.wiley.com/cgibin/fulltext/113394869/PDFSTART.

Barrett, J.C., Grossman, G.D., and Rosenfeld, J., 1992, Turbidity-induced changes in reactive 

distance of rainbow trout: Transactions of the American Fisheries Society, v. 121, no. 4, p. 

437-443, http://www.tandfonline.com/doi/abs/10.1577/1548-

8659%281992%29121%3C0437%3ATICIRD%3E2.3.CO%3B2.

Benenati, P.L., Shannon, J.P., and Blinn, D.W., 1998, Desiccation and recolonization of 

phytobenthos in regulated desert river--Colorado River at Lees Ferry, Arizona, USA: 

Regulated Rivers--Research and Management, v. 14, p. 519-532, 

http://www.rmrs.nau.edu/awa/ripthreatbib/Benenati_etal_1998.pdf.

Bligh, E.G., and Dyer, W.J., 1959, A rapid method of total lipid extraction and purification: 

Canadian Journal of Biochemistry and Physiology, v. 37, p. 911-917.

Blinn, D.W., Shannon, J.P., Stevens, L.E., and Carder, J.P., 1995, Consequences of fluctuating 

discharge for lotic communities: Journal of the North American Benthological Society, v. 14, 

no. 2, p. 233-248, http://www.jstor.org/stable/pdfplus/1467776.pdf.

Breck, J.E. and Gitter, M.J., 1983, Effect of fish sizes on the reactive distance of bluegill 

(Lepomis macrochirus) sunfish: Canadian Journal of Fisheries Aquatic Science, v. 40, p. 

162–167.

Budy, P., Haddix, T., and Schneidervin, R., 2005, Zooplankton size selection relative to gill 

raker spacing in rainbow trout: Transactions of the American Fisheries Society, v. 134, p. 

1228-1235. 

Burnham, K.P., and Anderson, D.R., 2002, Model selection and multimodel inference: a 

practical information-theoretic approach: New York, Springer.

Carothers, S.W., and Brown, B.T., 1991, The Colorado River through Grand Canyon--natural 

history and human change: Tucson, University of Arizona Press, 235 p.

Churchward, M., Brandman, D., Rogasevskaia, T., and Coorssen, J., 2008, Copper (II) sulfate 

charring for high sensitivity on-plate fluorescent detection of lipids and sterols--quantitative 

analyses of the composition of functional secretory vesicles: Journal of Chemical Biology, v. 

1, p. 79-87.

Cleary, J.S., Bradford, M.J., and Janz, D.M., 2012, Seasonal and spatial variation in lipid and 

triacylglycerol levels in juvenile chinook salmon (Oncorhynchus tshawytscha) from the 

Bridge River, British Columbia: Limnologica--Ecology and Management of Inland Waters, 

v. 42, p. 144-150. 

Coggins, L.G., Jr., 2008, Active adaptive management for native fish conservation in the Grand 

Canyon--implementation and evaluation: Gainseville, University of Florida, Ph.D. 

dissertation, 173 p.

Coggins, L.G., Yard, M.D., and Pine, W.E., 2011, Nonnative fish control in the Colorado River 

in Grand Canyon, Arizona--an effective program or serendipitous timing?: Transactions of 

298
the American Fisheries Society, v. 140, no. 2, p. 456-470, 

http://www.tandfonline.com/doi/abs/10.1080/00028487.2011.572009.

Cross, W.F., Rosi-Marshall, E.J., Behn, K.E., Kennedy, T.A., Hall, R.O., Fuller, A.E., and 

Baxter, C.V., 2010, Invasion and production of New Zealand mud snails in the Colorado 

River, Glen Canyon: Biological Invasions, v. 12, no. 9, p. 3033-3043, 

http://www.springerlink.com/content/bv834031865h2077/.

Cross, W.F., Baxter, C.V., Donner, K.C., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O., Jr., 

Wellard-Kelly, H.A., and Rogers, R.S., 2011, Ecosystem ecology meets adaptive 

management--food web response to a controlled flood on the Colorado River, Glen Canyon: 

Ecological Applications, v. 21, no. 6, p. 2016-2033, 

http://www.esajournals.org/doi/abs/10.1890/10-1719.1.

Cross, W.F., Baxter, C.V., Rosi-Marshall, E.J., Hall, R.O.J., Kennedy, T.A., Donner, K.C., 

Wellard-Kelly, H.A., Seegert, S.E.Z., Behn, K.E., and Yard, M.D., 2013, Foodweb dynamics 

in a large river discontinuum: Ecological Monographs, v. 8, no. 3, p. 311-337.

Donner, K.C., 2011, Trophic basis of production of fishes in the Colorado River, Grand Canyo--

an assessment of potential competition for food: Pocatello, Idaho State University, M.S. 

thesis.

Eggers, D.M., 1977, The nature of prey selection by planktivorous fish: Ecology, v. 58, p. 46-59.

Gerritsen, J., and Strickler, J.R., 1977, Encounter probabilities and community structure in 

zooplankton--a mathematical model: Journal of the Fisheries Research Board Canada, v. 34, 

p.73-82.

Gilliers, C., Amara, R., and Bergeron, J.-P., 2004, Comparison of growth and condition indices 

of juvenile flatfish in different coastal nursery grounds: Environmental Biology of Fishes, v. 

71, p. 189-198.

Graf, J.B., 1995, Measured and predicted velocity and longitudinal dispersion at steady and 

unsteady flow, Colorado River, Glen Canyon Dam to Lake Mead: U.S. Geological Survey 

Water Resources Bulletin, v. 31, no. 2, p. 265−281.

Grams, P.E., Schmidt, J.C., and Topping, D.J., 2007, The rate and pattern of bed incision and 

bank adjustment on the Colorado River in Glen Canyon downstream from Glen Canyon 

Dam, 1956-2000: Geological Society of America Bulletin, v. 119, no. 5-6 p. 556-575, 

http://gsabulletin.gsapubs.org/content/119/5-6/556.abstract.

Hairston, N.G., Sr., 1989, Hard choices in ecological experimentation: Herpetologica, v. 45, no. 

1, p. 119-122.

Hansen, A.G., Beauchamp, D.A., and Schoen, E.R., 2013, Visual prey detection responses of 

piscivorous trout and salmon--effects of light, turbidity, and prey size: Transactions of the 

American Fisheries Society, v. 142, p. 854-867.

Harvey, B.C., and Nakamoto, R.J., 2013, Seasonal and among-stream variation in predator 

encounter rates for fish prey: Transactions of the American Fisheries Society, v. 142, p. 621–

627.

Harvey, B.C., Railsback, S.F., 2009, Exploring the persistence of stream-dwelling trout 

populations under alternative real-world turbidity regimes with an individual-based model: 

Transactions of the American Fisheries Society, v. 138, p. 348 – 360.

Hayes, J.W., Stark, J.D., Shearer, K.A., 2000, Development and test of a whole-lifetime foraging 

and bioenergetics growth model for drift-feeding brown trout: Transactions of the American 

Fisheries Society, v. 129, p. 315 – 332.

Howick, G.L., and O’Brien, W.J., 1983, Piscivorous feeding behavior of largemouth bass--an 

experimental analysis: Transactions of the American Fisheries Society, v. 112, p. 508-516.

299
Hutchings, J.A., 1994, Age- and size-specific costs of reproduction within populations of brook 

trout, Salvelinus fontinalis: Oikos, v. 70, p. 12-20.

Hutchings, J.A., Pickle, A., McGregor-Shaw, C.R., and Poirier, L., 1999, Influence of sex, body 

size, and reproduction on overwinter lipid depletion in brook trout: Journal of Fish Biology, 

v. 55, p. 1020-1028.

Kaeding, L.R., Zimmerman, M.A., 1983, Life history and ecology of the humpback chub in the 

Little Colorado and Colorado rivers of the Grand Canyon: Transactions of the American 

Fisheries Society, v. 112, p. 557-594.

Keeley, E.R., Parkinson, E.A., and Taylor, E.B., 2007, The origins of ecotypic variation of 

rainbow trout--a test of environmental vs. genetically based differences in morphology: 

Journal of Evolutionary Biology, v. 20, p. 725-736.

Kennedy, T.A., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M.D., and Copp, A.J., 2013, 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river: Freshwater Biology, v. 59, p. 557-572. 

Kieffer, J.D., Currie, S., and Tufts, B.L., 1994, Effects of environmental temperature on the 

metabolic and acid–base responses of rainbow trout to exhaustive exercise: Journal of 

Experimental Biology, v. 194, p. 299–31. 

Kondolf, G.M., Cook, S.S., Maddux, H.R., and Persons, W.R., 1989, Spawning gravels of 

rainbow trout in the Grand Canyon, Arizona: Journal of the Arizona–Nevada Academy of 

Science, v. 23, p. 19–28.

Korman, J., Kaplinski, M., Hazel, J.E.J., and Melis, T.S., 2005, Effects of the experimental 

fluctuating flows from Glen Canyon Dam in 2003 and 2004 on the early life history stages of 

rainbow trout in the Colorado River--final report: Ecometric Research, Inc., Northern 

Arizona University, and U.S. Geological Survey, submitted to U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center, cooperative agreement no. 04-WRAG-0006 

and modification no. 002, 171 p.

Korman, J., Yard, M., Walters, C.J., and Coggins, L.G., 2009a, 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, http://www.tandfonline.com/doi/abs/10.1577/T08-025.1.

Korman, J., and Campana, S.E., 2009b, Effects of hydropeaking on nearshore habitat use and 

growth of age-0 rainbow trout in a large regulated river: Transactions of the American 

Fisheries Society, v. 138, no. 1, p. 76-87, http://www.tandfonline.com/doi/abs/10.1577/T08-

026.1.

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, http://www.tandfonline.com/doi/abs/10.1080/00028487.2011.572015.

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, p. 1827-1849.

MacNeill, D.B., and Brandt, S.B., 1990, Ontogenetic shifts in gill-raker morphology and 

predicted prey capture efficiency of the alewife, Alosa pseudoharengus: Copeia, v. 1990, p. 

164-171.

Maddux, H.R., Kubly, D.M., deVos, J.C., Jr., Persons, W.R., Staedicke, R., and Wright, R.L., 

1987, Effects of varied flow regimes on aquatic resources of Glen and Grand Canyons--final 

300
report: Phoenix, Arizona Game and Fish Department, submitted to Bureau of Reclamation, 

Glen Canyon Environmental Studies, contract no. 4-AG-40-01810, 291 p.

Makinster, A.S., Persons, W.R., and Avery, L.A., 2011, Status and trends of the rainbow trout 

population in the Lees Ferry reach of the Colorado River downstream from Glen Canyon 

Dam, Arizona, 1991–2009: U.S. Geological Survey Scientific Investigations Report 2011–

5015, 17 p.

Malvestuto, S.P., 1996, Sampling the recreation creel, in B.R. Murphy and D.W. Willis, eds., 

Fisheries Techniques (2d): Bethesda, Md., American Fisheries Society, p. 591-623.

Marsh, P.C., and Douglas, M.E., 1997, Predation by introduced fishes on endangered humpback 

chub and other native species in the Little Colorado River, Arizona: Transactions of the 

American Fisheries Society, v. 126, p. 343-346.

McKinney, T., and Speas, D.W., 2001, Observations of size-related asymmetries in diet and 

energy intake of rainbow trout in a regulated river: Environmental Biology of Fishes, v. 61, 

no. 4, p. 435-444, http://www.springerlink.com/content/u177356554v07546/.

McKinney, T., Speas, D.W., Rogers, R.S., and Persons, W.R., 2001, Rainbow trout in a 

regulated river below Glen Canyon Dam, Arizona, following increased minimum flows and 

reduced discharge variability: North American Journal of Fisheries Management, v. 21, p. 

216-222.

Melis, T.S., Korman, J., and Kennedy, T.A., 2012, Abiotic and biotic responses of the Colorado 

River to controlled floods at Glen Canyon Dam, Arizona, USA: River Research and 

Applications, v. 28, p. 764-776.

Newcombe, C.P., and MacDonald, D.D., 1991, Effects of suspended sediment on aquatic 

ecosystems: North American Journal of Fisheries Management, v. 11, p. 72–82.

Parrish, C.C., 1999, Determination of total lipid, lipid classes, and fatty acids in aquatic samples, 

in Arts, M.T., and Wainman, B.C., eds., Lipids in freshwater ecosystems: New York, 

Springer-Verlag, p. 4-20.

Perry, S.A., and Perry, W.B., 1986, Effects of experimental flow regulation on invertebrate drift 

and stranding in the Flathead and Kootenai Rivers, Montana, USA: Hydrobiologia, v. 134, 

no. 2, p. 171-182. http://www.springerlink.com/content/wu08t083k8r41554/.

Phillips, K.M., Tarrago-Trani, M.T., Grove, T.M., Grun, I., Lugogo, R., Harris, R.F., and 

Stewart, K.K., 1997, Simplified gravimetric determination of total fat in food composites 

after chloroform-methanol extraction: Journal of the American Oil Chemists Society, v. 74, 

p. 137-142.

Post, J.R., and Parkinson, E.A., 2001, Energy allocation strategy in young fish--allometry and 

survival: Ecology, v. 82, p. 1040-1051.

Rosenfeld, J.S., Ptolemy, R., 2012, Modelling available habitat versus available energy flux--do 

PHABSIM applications that neglect prey abundance underestimate optimal flows for juvenile 

salmonids?: Canadian Journal of Fisheries and Aquatic Sciences, v. 69, p. 1920 – 1934.

Runge, M.C., Bean, E., Smith, D.R., and Kokos, S., 2011. Non-native fish control below Glen 

Canyon Da--report from a structured decision-making project: U.S. Geological Survey OpenFile Report 2011–1012, 74 p., http://pubs.usgs.gov/of/2011/1012/. 

Schmidt, J.C., Webb, R.H., Valdez, R.A., Marzolf, G.R., and Stevens, L.E., 1998, Science and 

values in river restoration in the Grand Canyon: Bioscience, v. 48, p. 735-747.

Secor, D.H., Dean, J.M., and Laban, E.H., 1991, Manual for otolith removal and preparation for 

microstructural examination: Belle W. Baruch Institute for Marine Biology and Coastal 

Research.

301
Simpkins, D.G., Hubert, W.A., Del Rio, C.M., and Rule, D.C., 2003, Physiological responses of 

juvenile rainbow trout to fasting and swimming activity--effects on body composition and 

condition indices: Transactions of the American Fisheries Society, v. 132, p. 576-589. 

Speas, D.W., Walters, C.J., Ward, D.L., and Rogers, R.S., 2004, Effects of intraspecific density 

and environmental variables on the electrofishing catchability of brown and rainbow trout in 

the Colorado River: North American Journal of Fisheries Management, v. 24, p. 586-596.

Stockner, J.G., Rydin, E., and Hyenstrand, P., 2000, Cultural oligotrophication--causes and 

consequences for fisheries resources: Fisheries, v. 25, p. 7-14.

Stuart-Smith, R.D., Richardson, A.M.M., and White, R.W.G., 2004, Increasing turbidity 

significantly alters the diet of brown trout--a multi-year longitudinal study: Journal of Fish 

Biology, v. 65, p. 376-388.

Sweka, J.A., and Hartman, K.J., 2003, Reduction of reactive distance and foraging success in 

smallmouth bass, Micropterus dolomieu, exposed to elevated turbidity levels: Environmental 

Biology of Fishes, v. 67, p. 341–347.

Topping, D.J., Schmidt, J.C., and Vierra, L.E., Jr., 2003, Computation and analysis of the 

instantaneous-discharge record for the Colorado River at Lees Ferry, Arizona–May 8, 1921, 

through September 30, 2000: U.S. Geological Survey Professional Paper 1677, 118 p. 

Topping, D.J., Rubin, D.M., Grams, P.E., Griffiths, R.E., Sabol, T.A., Voichick, N., Tusso, R.B., 

Vanaman, K.M., and McDonald, R.R., 2010, Sediment transport during three controlledflood experiments on the Colorado River downstream from Glen Canyon Dam, with 

implications for eddy-sandbar deposition in Grand Canyon National Park: U.S. Geological 

Survey Open-File Report 2010–1128, 111 p.

Tummers, B., 2006, DataThief III--version 1.6, available from http://datathief.org.

Bureau of Reclamation, 1996, Record of decision on the operation of Glen Canyon Dam--final 

environmental impact statement: Salt Lake City, Utah, Glen Canyon Dam Adaptive 

Management Program, UC-326 ENV-6.00, 15 p., 

http://www.usbr.gov/uc/rm/amp/pdfs/sp_appndxG_ROD.pdf.

U.S. Department of the Interior, 2007, Record of decision, Colorado River interim guidelines for 

lower basin shortages and the coordinated operations for Lake Powell and Lake Mead: 

Washington, D.C., Office of the Secretary of the Interior, 59 p., 

http://www.usbr.gov/lc/region/programs/strategies/RecordofDecision.pdf.

Bureau of Reclamation, 2011, Environmental assessment--development and implementation of a 

protocol for high-flow experimental releases from Glen Canyon Dam, Arizona, 2011 through 

2020: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado Region, 176 p. + 

appendices, http://www.usbr.gov/uc/envdocs/ea/gc/HFEProtocol/HFE-EA.pdf.

Utne-Palm, A.C., 2002, Visual feeding of fish in a turbid environment--physical and behavioural 

aspects: Marine and Freshwater Behaviour and Physiology, v. 35, p. 111–128.

Valdez, R.A., and Ryel, R.J., 1995, Life history and ecology of the humpback chub (Gila cypha) 

in the Colorado River, Grand Canyon, Arizona--final report: Logan, Utah, BIO/WEST, Inc.,

submitted to Bureau of Reclamation, contract no. 0-CS-40-09110, technical report no. TR250-08, 328 p.

Van Haverbeke, D.R., Stone, D.M., Coggins, L.G., 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, p. 163–177.

Vinyard, G.L. and O’Brien, W.J., 1976, Effects of light and turbidity on the reactive distance of 

bluegill (Lepomis macrochirus): Journal of the Fisheries Research Board of Canada, v. 33, p. 

2845-2849. 

302
Voichick, N., and Wright, S.A., 2007, Water-temperature data for the Colorado River and 

tributaries between Glen Canyon Dam and Spencer Canyon, northern Arizona, 1988-2005: 

U.S. Geological Survey Data Survey Series 251, 24 p., http://pubs.usgs.gov/ds/2007/251/.

Vogel, J.L., and Beauchamp, D.A., 1999, Effects of light, prey size, and turbidity on reaction 

distances of lake trout (Salvelinus namaycush) to salmonid prey: Canadian Journal of 

Fisheries and Aquatic Sciences, v. 56, p. 1293-1297.

Walters, C.J., 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, p. 

1-38.

Ware, D.M., 1973, Risk of epibenthic prey to predation by rainbow trout (Salmo gairdneri): 

Journal of the Fisheries Research Board of Canada, v. 30, p. 787-797.

Wright, S.A. and Grams, P.E., 2010, Evaluation of water year 2011 Glen Canyon Dam flow 

release scenarios on downstream sand storage along the Colorado River in Arizona: U.S. 

Geological Survey Open-File Report 2010-1133, 18 p.

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, 

http://onlinelibrary.wiley.com/doi/10.1002/ece3.990/abstract.

Yard, M.D., 2003, Light availability and aquatic primary production, Colorado River, Glen and 

Grand Canyons, AZ: Flagstaff, Northern Arizona University, Ph.D. dissertation, 205 p.

Yard, M.D., Bennett, G.E., Mietz, S.N., Coggins Jr., L.G., Stevens, L.E., Hueftle, S., and Blinn, 

D.W., 2005, Influence of topographic complexity on solar insolation estimates for the 

Colorado River, Grand Canyon, AZ: Ecological Modelling, v. 183, p. 157–172.

Yard, M.D., Coggins, L.G., Baxter, C.V., Bennett, G.E., and Korman, J., 2011, Trout piscivory 

in the Colorado River, Grand Canyon--effects of turbidity, temperature, and fish prey 

availability: Transactions of the American Fisheries Society, v. 140, no. 2, p. 471-486, 

http://www.tandfonline.com/doi/abs/10.1080/00028487.2011.572011.

Zhou, A.L., Hintze, K.J., Jimenez-Flores, R., and Ward, R.E., 2012, Dietary fat composition 

influences tissue lipid profile and gene expression in Fischer-344 rats: Lipids, v. 47, p. 1119-

1130.

 

303
G. Budget 

Project Element 9.1. Rainbow 

Trout Population Dynamics – 

Ongoing Modelling and Future 

Monitoring

Project Element 9.2. Detection of 

Rainbow Trout Movement from 

the Upper Reaches of the 

Colorado River below Glen 

Canyon Dam/Natal Origins 

Project Element 9.3. 

Exploring the 

Mechanisms behind 

Trout Growth, 

Reproduction, and 

Movement in Glen and 

Marble Canyon using 

Lipid (fat) Reserves as an 

Indicator of 

Physiological Condition 

Salaries $ 32,000.00 Salaries $ 95,700.00 Salaries $ 48,500.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ - Operating Expenses $ 50,100.00 Operating Expenses $ 40,000.00

Logistics $ - Logistics $ 127,400.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 120,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 5,120.00 USGS Burden $ 47,312.00 USGS Burden $ 14,160.00

Total $ 37,120.00 Total $ 440,512.00 Total $ 102,660.00

Project Element 9.4. Comparative 

study on the feeding morphology 

of drift feeding fish

Project Element 9.5. Metaanalysis, and the development of 

reactive distance relationships 

for encounter rate models 

Project Element 9.6. 

Evaluation of Turbidity 

(in terms of TSS) as a 

potential Glen Canyon 

Dam operations 

management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition 

on juvenile humpback 

chub 

Salaries $ 72,100.00 Salaries $ 29,200.00 Salaries $ 27,500.00

Traveling and Training $ - Traveling and Training $ 2,500.00 Traveling and Training $ 2,000.00

Operating Expenses $ 2,400.00 Operating Expenses $ 1,500.00 Operating Expenses $ 2,500.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 11,920.00 USGS Burden $ 5,312.00 USGS Burden $ 5,120.00

Total $ 86,420.00 Total $ 38,512.00 Total $ 37,120.00

Project Element 9.7. Application 

of a bioenergetics model in a 

seasonally turbid river 

Project Element 9.8. Mechanisms 

that Limit Rainbow and Brown 

Trout Growth in other Western 

Tailwater Systems 

Project Element 9.9. 

Effects of High 

Experimental Flows on 

Rainbow Trout 

Population Dynamics 

Salaries $ 53,800.00 Salaries $ 58,400.00 Salaries $ 12,500.00

Traveling and Training $ 2,000.00 Traveling and Training $ 2,500.00 Traveling and Training $ -

Operating Expenses $ 1,500.00 Operating Expenses $ 1,500.00 Operating Expenses $ 28,000.00

Logistics $ - Logistics $ - Logistics $ 22,100.00

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 9,168.00 USGS Burden $ 9,984.00 USGS Burden $ 10,016.00

Total $ 66,468.00 Total $ 72,384.00 Total $ 72,616.00

Project Element 9.10. Examining 

the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

Salaries $ 44,400.00

Traveling and Training $ -

Operating Expenses $ 2,500.00

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 7,504.00

Total $ 54,404.00

FY 2015

FY 2015 Project 9 Gross Totals: $1,008,216.00

304
Project Element 9.1. Rainbow 

Trout Population Dynamics – 

Ongoing Modelling and Future 

Monitoring

Project Element 9.2. Detection of 

Rainbow Trout Movement from 

the Upper Reaches of the 

Colorado River below Glen 

Canyon Dam/Natal Origins 

Project Element 9.3. 

Exploring the 

Mechanisms behind 

Trout Growth, 

Reproduction, and 

Movement in Glen and 

Marble Canyon using 

Lipid (fat) Reserves as an 

Indicator of 

Physiological Condition 

Salaries $ 60,000.00 Salaries $ 100,500.00 Salaries $ -

Traveling and Training $ 2,500.00 Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ - Operating Expenses $ 50,100.00 Operating Expenses $ -

Logistics $ - Logistics $ 145,500.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 120,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 13,750.00 USGS Burden $ 68,742.00 USGS Burden $ -

Total $ 76,250.00 Total $ 484,842.00 Total $ -

Project Element 9.4. Comparative 

study on the feeding morphology 

of drift feeding fish

Project Element 9.5. Metaanalysis, and the development of 

reactive distance relationships 

for encounter rate models 

Project Element 9.6. 

Evaluation of Turbidity 

(in terms of TSS) as a 

potential Glen Canyon 

Dam operations 

management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition 

on juvenile humpback 

chub 

Salaries $ 80,000.00 Salaries $ 29,800.00 Salaries $ 21,400.00

Traveling and Training $ 2,500.00 Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 2,400.00 Operating Expenses $ 1,500.00 Operating Expenses $ 2,500.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 18,678.00 USGS Burden $ 6,886.00 USGS Burden $ 5,258.00

Total $ 103,578.00 Total $ 38,186.00 Total $ 29,158.00

Project Element 9.7. Application 

of a bioenergetics model in a 

seasonally turbid river 

Project Element 9.8. Mechanisms 

that Limit Rainbow and Brown 

Trout Growth in other Western 

Tailwater Systems 

Project Element 9.9. 

Effects of High 

Experimental Flows on 

Rainbow Trout 

Population Dynamics 

Salaries $ 56,100.00 Salaries $ 65,600.00 Salaries $ 12,900.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 1,500.00 Operating Expenses $ 1,500.00 Operating Expenses $ 28,000.00

Logistics $ - Logistics $ - Logistics $ 10,000.00

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 12,672.00 USGS Burden $ 14,762.00 USGS Burden $ 11,198.00

Total $ 70,272.00 Total $ 81,862.00 Total $ 62,098.00

Project Element 9.10. Examining 

the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

Salaries $ 55,000.00

Traveling and Training $ 2,500.00

Operating Expenses $ -

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 12,650.00

Total $ 70,150.00

FY 2016

FY 2016 Project 9 Gross Totals: $1,016,396.00

305
Project Element 9.1. Rainbow 

Trout Population Dynamics – 

Ongoing Modelling and Future 

Monitoring

Project Element 9.2. Detection of 

Rainbow Trout Movement from 

the Upper Reaches of the 

Colorado River below Glen 

Canyon Dam/Natal Origins 

Project Element 9.3. 

Exploring the 

Mechanisms behind 

Trout Growth, 

Reproduction, and 

Movement in Glen and 

Marble Canyon using 

Lipid (fat) Reserves as an 

Indicator of 

Physiological Condition 

Salaries $ 60,400.00 Salaries $ 98,600.00 Salaries $ -

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ - Operating Expenses $ 50,100.00 Operating Expenses $ -

Logistics $ - Logistics $ 101,600.00 Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 50,000.00 Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 16,912.00 USGS Burden $ 71,584.00 USGS Burden $ -

Total $ 77,312.00 Total $ 371,884.00 Total $ -

Project Element 9.4. Comparative 

study on the feeding morphology 

of drift feeding fish

Project Element 9.5. Metaanalysis, and the development of 

reactive distance relationships 

for encounter rate models 

Project Element 9.6. 

Evaluation of Turbidity 

(in terms of TSS) as a 

potential Glen Canyon 

Dam operations 

management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition 

on juvenile humpback 

chub 

Salaries $ 70,000.00 Salaries $ - Salaries $ 20,900.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 2,400.00 Operating Expenses $ - Operating Expenses $ 2,500.00

Logistics $ - Logistics $ - Logistics $ -

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 20,272.00 USGS Burden $ - USGS Burden $ 6,552.00

Total $ 92,672.00 Total $ - Total $ 29,952.00

Project Element 9.7. Application 

of a bioenergetics model in a 

seasonally turbid river 

Project Element 9.8. Mechanisms 

that Limit Rainbow and Brown 

Trout Growth in other Western 

Tailwater Systems 

Project Element 9.9. 

Effects of High 

Experimental Flows on 

Rainbow Trout 

Population Dynamics 

Salaries $ 50,800.00 Salaries $ - Salaries $ 27,200.00

Traveling and Training $ - Traveling and Training $ - Traveling and Training $ -

Operating Expenses $ 1,500.00 Operating Expenses $ - Operating Expenses $ 28,000.00

Logistics $ - Logistics $ - Logistics $ 22,100.00

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - Cooperators (non-USGS) $ -

USGS Cooperators $ - USGS Cooperators $ - USGS Cooperators $ -

USGS Burden $ 14,644.00 USGS Burden $ - USGS Burden $ 21,644.00

Total $ 66,944.00 Total $ - Total $ 98,944.00

Project Element 9.10. Examining 

the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

Salaries $ 4,000.00

Traveling and Training $ -

Operating Expenses $ -

Logistics $ -

Cooperators (non-USGS) $ -

USGS Cooperators $ -

USGS Burden $ 1,120.00

Total $ 5,120.00

FY 2017 Project 9 Gross Totals: $742,828.00

FY 2017 

306
Project 10. Where does the Glen Canyon Dam rainbow 

trout tailwater fishery end? - Integrating Fish and Channel 

Mapping Data below Glen Canyon Dam 

A. Investigators 

Ted Melis, Physical Scientist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

Daniel Buscombe, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Michael Yard, Fishery Biologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Josh Korman, Ecometric Research,

Paul Grams, Research Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Tom Gushue, GIS Coordinator, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Geographer, U.S. Geological Survey, Grand Canyon Monitoring and Research Center

Student, U.S. Geological Survey, Grand Canyon Monitoring and Research Center

B. Project Summary 

Glen Canyon Dam’s rainbow trout tailwater fishery (hereafter, GCD tailwater) begins in the 

project’s tailrace, but where does it end? The serial discontinuity concept for impounded rivers 

was first described by Ward and Stanford (1983), whereby recovery of river ecosystems 

impaired by dams is predicted to increase with distance below dams; often influenced by 

locations of downstream tributaries that to some degree add back resources lost to upstream 

reservoirs. The Colorado River ecosystem (CRe) is composed of several river segments 

extending from the forebay of GCD to the western boundary of GCNP, and has been studied 

extensively for the past five decades (Gloss and others, 2005; Schmidt and Grams, 2011a). 

However, it remains unclear how long-term trends in the river’s channel morphology in response 

to dam operations, will combine with climate-change induced trends in downstream quality-ofwater (QW) to influence the exotic rainbow trout tailwater fishery and native fish in the CRe. 

Stream forecasting under current climate change for the southwestern US and Colorado River 

suggests dryer conditions are already occurring under global warming (see chaps. 8 & 20 of the 

2014 National Climate Assessment: http://nca2014.globalchange.gov/report). 

Reduced water storage in Lake Powell since 2001, has already resulted in warmer GCD 

releases; a trend that has significantly influenced the discontinuity distance and recovery relative 

to the river’s altered thermal regime in Grand Canyon over the last 14 years. Whether exotic or 

native fish species in GCNP will benefit more from these somewhat warmer, but still unnaturally 

cold releases under both drier and warmer conditions below GCD remains highly uncertain. 

Located 15 miles below GCD, the confluence with the Paria River is typically referred to as the 

downstream terminus of the “Lees Ferry” recreational trout fishery, and is also the approximate 

boundary between Glen Canyon National Recreation Area and Grand Canyon National Park 

(GCNRA and GCNP, respectively). However, rainbow trout are also found below the Paria and 

307
Little Colorado Rivers, more than 75 miles downstream of the dam (Makinster and others, 2010). 

Recent modeling studies suggest that sand-sized sediment can be a significant limiting factor in 

the spawning success of trout in gravel-bed settings, and may be more important than finer 

sediments in limiting flow and reducing levels of dissolved oxygen needed by incubating trout 

eggs within redds (Pattison and others, 2012; Sear and others, 2012). The highly sporadic and 

intermittent nature of flooding and sediment production from the Paria River results in periods 

when the Colorado River’s bed and water quality may or may not be greatly affected by finesediment deliveries from this important tributary. Paria River flow volumes are relative small 

and typically have little influence on the now-altered temperature regime of the Colorado River 

below Glen Canyon. Therefore, the effective “discontinuity distance” below GCD may be highly 

variable through time relative to the Paria River’s location below GCD.

Ellis and Jones (2013) conclude that at least two recovery gradients exist in regulated rivers, 

with the thermal recovery gradient typically being the longest. To improve understanding about 

discontinuity distance(s) associated with the GCD tailwater, this interdisciplinary research 

project proposes to integrate new and existing channel mapping methods with ongoing fisheries 

analyses using a variety of information about the geometry of channel margins, bed-sediment 

characteristics (softer (sand and finer) and harder (gravel or bedrock) substrates), and QW data 

(including, flow, water temperature and turbidity or total suspended sediment). This project’s 

aim is to evaluate the potential effects of physical processes (water temperature and sediment 

input frequency) on native and nonnative fish dynamics. The basic questions being asked are: 1) 

How do seasonal fine-sediment inputs, high flow events and discharge temperatures affect 

downstream spawning for rainbow trout, and rearing habitat for trout and humpback chub? and, 

2) Do fall-timed pulse flows extend the rainbow trout fishery downstream to the Little Colorado 

River? Sources of information needed to address these questions are shown in figure 1.

308
Figure 1. Sources of existing and new information from ongoing GCMRC monitoring that are already available and needed 

to answer new ecologically important questions about GCD operation and co-management of native and nonnative fish in 

GCNRA and GCNP. The CRe’s thermal recovery gradient has moved upstream since 2002, in response to reduced Lake 

Powell Storage, while point sources of sediment influencing turbidity remained fixed.

This information has management implications, particularly below GCNRA where rainbow 

trout are of concern relative to native fish conservation in GCNP. Understanding the 

relationships between trout life history, and abiotic and biotic processes affected by specific dam 

operations and climate change will provide greater insight about strategies for co-managing 

native and nonnative fisheries between Lakes Powell and Mead. Project findings may also be 

transferable to other river basin settings, and inform management of other Colorado River basin 

tailwaters where similar challenges in co-management of native and nonnative sport fisheries 

exist (see Trammel, 2010; Clarkson and Marsh, 2010).

As shown in figure 1, this project intends to build on the numerous recent achievements of 

several FY2013-14 projects, including near real time monitoring of flow, QW and suspendedsediment transport (Topping and others, Project 2), annual channel mapping of sandbars (Grams 

and others, Project 3), quarterly monitoring of natal origins (NO) of rainbow trout and humpback 

chub juvenile survival (Korman and Yard, Project 9), and ongoing monitoring of the CRe’s food 

base (Kennedy and others, Project 5). Proposed interdisciplinary analyses of fish and channelmap data also critically depend upon the capabilities of the GCMRC’s GIS Services and Support 

project, as well as GCMRC’s abundant existing remote sensing data (Gushue and others).

We propose to use both new and existing channel mapping data (Table 1) to advance an 

integrated physical and biological outcome that is only possible owing to ongoing sandbar 

channel mapping, and NO field studies during 2015-16. 

Table 1. Existing and Proposed channel-bed bathymetry and bed-sediment imagery data needed 

for integrated analyses with biological data from Natal Origins of Rainbow Trout & Juvenile 

Humpback Chub Survival study reaches

Water Year (WY) / 

Month(s) data 

collected/ Annual 

Release Volume 

(maf)/ Types of dam 

operations

NO Reach 

#1

(rms -6 to 

-2)

NO Reach 

#2 (rms 16 

to 20)

NO Reach #3

(rms 37 to 41)

NO Reach #4a 

(rms 60 to 61)

NO Reach 

#4b (rms 

62 to 64)

WY2016/ annual 

volume & operations 

are not projected yet

HSS (SEP 

& APR)

MBB/AB 

(MAY) + 

HSS (SEP 

& APR)

HSS (SEP & 

APR)

*

MBB/AB & 

HSS (APR, 

*

JUL & SEP)

HSS (APR & 

SEP)

WY2015/ projected

~9.0 maf/ Modified 

Low Fluctuating Flows 

(MLFF)

MBB/AB 

(NOV or 

AUG)

HSS (APR 

& SEP)

HSS (APR & 

SEP))

*

MBB/AB & 

HSS (APR, 

*

JUL & SEP)

HSS (APR & 

SEP)

WY2014/ 7.48 maf/ 

MLFF & fall HFE

HSS (APR) HSS (SEP) HSS (SEP) HSS (APR), 

MBB/AB 

(MAY)

HSS (APR), 

MBB/AB 

(MAY)

WY2013/ 8.23 maf/ 

MLFF & fall HFE

HSS (OCT 

& DEC)

HSS (MAY) n.d. MBB/AB

(AUG)

n.d.

309
WY2012/ 9.47 maf/ 

MLFF & fall steady 

flow test (OCT 2011)

n.d. n.d. MBB/AB/HSS MBB/AB/HSS n.d.

KEY – n.d., No data, HSS, Humminbird sidescan sonar imagery; MBB/AB, Multi-beam bathymetry/acoustic 

backscattering imagery; TSS, Towed sidescan imagery (Klein® system, digital, duel frequency, UWV, 

Underwater video, AHGI, 2003, Airborne, high-gain digital imagery). *

, Collection of these data contingent 

upon funding of Project Element 3.4 (McElroy and others).

These coordinated research efforts involving members of multiple existing projects will 

culminate in new interdisciplinary geospatial analyses in 2017, centered around a workshop, and 

will be built upon the following three project elements with the following 7 objectives:

Element #1 (2015) – has one objective

1. Complete Humminbird® Sidescan Sonar Mapping Methods - in 2015, for determining 

changes in the areal extents of sand and gravel bed surface sediment types using lowcost, easy-to-use sidescan technology, where benthic organisms and spawning trout are 

monitored in Glen and Marble Canyon study segments,

Element #2 (2015-16) – has five objectives

1. Use of Glen Canyon Map to Support Aquatic Modeling Research - Project 3 element 3.2, 

channel topographic and bed-sediment type map for Glen Canyon, data collected in 2015 

(see Grams and others), will be used with flow model (Project 5 ) to support primary 

production model, and assessment of channel margins and shorelines in task 3, below,

2. Document Geometry of Glen Canyon Channel Margins and Grain Size – in 2015-16, the 

proportion of low-angle channel margins (less than 11 degree slopes, after Korman and 

others, 2005) known to be used by juvenile trout in Glen Canyon,

3. Document Geometry of Marble and eastern Grand Canyon Channel Margins – using 

existing channel data from previously mapped segments of Marble and Eastern Grand 

Canyon within NO study sites, we will estimate the proportion of low-angle channel 

margins (less than 11 degrees) for comparison with results from task #3 above,

4. Determining the Time-Varied Proportion of Sand and Gravel in Deeper Channel –

through use of new and existing channel-map data, we will estimate the time-varied 

spatial distributions (2012-16) of sand and gravel areas on the Colorado River bed 

surface that may support rainbow trout spawning in NO study sites 1 - 4b,

5. Determining Time-Varied Proportion of Channel Margin Types in NO Study Sites – to 

assess possible influences on fish catch rates in NO study reaches #1 - 4b between 2012-

16, associated with changing shoreline and near-shore sand deposits (low elevation eddy 

and lower channel sandbars) that may result from tributary sand inputs combined with 

high flow dam operations.

Element #3 (2017) – has one objective

1. Synthetic Analysis of Rainbow Trout Catch and Physical Data – Integrating, in 2017, five 

years of physical (segment-scale channel geometry, changes in areal bed surface sand 

coverage, and variations in flow patterns, total suspended sediment flux and water 

temperature) and biological (the aquatic foodbase, in terms of invertebrate drift) and 

rainbow trout responses; analyses developed through an integration workshop approach.

Downstream of GCD, QW, suspended-sediment transport and sandbars (Project 2 and 3) are 

already monitored by the GCMRC in support of several GCDAMP information needs. However, 

recent data and advances in understanding about how specific dam operations can affect aquatic 

310
resources, such as benthic invertebrates and rainbow trout that are linked to the river bed and 

channel margins (Kennedy and others, 2013a; 2013b; Cross and others, 2012; Korman and 

others, 2011;12) suggest that there is a greater need to evaluate changes in QW and physical 

characteristics of the river channel through collaborative analyses between physical and aquatic 

scientists. The integrated goal of this proposed interdisciplinary effort is to increase 

understanding about how specific dam operations under drier hydrology from global warming 

may directly or indirectly influence fish distribution, abundance tied to early life history 

responses to changes in QW, use of changing channel margins (more or less sandbars) and bedsediment type up and downstream of the Paria River confluence.

C. Background 

Despite its 1996 reoperation (USDOI, 1995; 1996), GCD releases can still vary quite widely 

over hourly-to-decadal time scales. Relative to pre-regulation, average daily flow is now much 

higher, but much less steady, while annual peaks are only a fraction of previous floods that 

occurred in Grand Canyon prior to dam closure (Topping and others, 2003). Hourly patterns of 

GCD water release, termed Modified Low Fluctuating Flows (MLFF) vary with monthly and 

annual water release volumes that are governed by upper Colorado River basin hydrology, water 

transfer agreements, and hydropower electrical energy demands. As a result, these factors can all 

directly influence inundation of channel margins used by aquatic organisms, as well as flow 

velocities and shear stresses along the river bed below the dam. Downstream variation in channel 

geometry within and between Glen, Marble and eastern Grand Canyon river segments means that 

abiotic and biotic resources can be affected differently by changes in hourly, daily, seasonal or 

annual patterns of releases (see figure 3 of Alvarez and Schmeeckle, 2012). In addition, 

suspended-sediment transport, spatial segregation of fine and coarse sediments of the river bed 

that affects channel geomorphology, and QW below the dam, including water temperature and 

turbidity, all vary longitudinally throughout GCNRA and GCNP. Spatial gradients in these 

quantities are known to change through time in response tributary sediment inputs, water storage 

in Lake Powell, and dam operations (Gloss and others, 2005). Perhaps the largest influence of 

GCD operations on downstream aquatic organisms has been that of thermal “pollution” –

meaning the diminished range in seasonal water temperature (Olden and Naiman, 2010) that 

resulted from filling of Lake Powell by 1980.

During the last two years, GCDAMP stakeholders have expressed interest in better 

understanding whether or not dam releases below 8,000 ft3

/s might negatively influence the 

foodbase and recreational rainbow trout fishery in Glen Canyon. In support of foodbase research 

tied to this question, both Projects 3 and 10 will provide aquatic foodbase researchers with 

channel geometry, channel-bed sediment type, and bed grain-size at Four-Mile Bar and other 

low-angle shoreline areas within Glen Canyon; information required to evaluate early life-stage 

survival of invertebrates and low-flow influences on the foodbase (see projects 5.1 and 5.2). 

Shallow nearshore channel margin areas as well as deeper parts of the channel with coarsegrained sediments (gravel) are known to be important substrates that support primary production 

and aquatic food for tailwater fish, as well as areas required for rainbow trout spawning and 

juvenile trout rearing. Better quantification and understanding about how varying dam releases 

alter channel-bed sediment types (sand and gravel), and inundate channel margins used by 

juvenile rainbow trout throughout Glen Canyon requires more detailed channel map data than 

currently exists in the GCD tailwater if understanding about trout dynamics is to be improved.

Implementation of a decade-long High Flow Experiment (HFE) Protocol in 2012, now 

potentially allows HFEs to occur 1 to 2 times annually following Paria River floods that supply 

311
sufficient new sand to the CRe below Glen Canyon. The potential increasing frequency of these 

high-flow operations, in combination with other higher releases to manage water storage in 

Lakes Powell and Mead, provides a unique chance for scientists and managers to conduct 

integrated studies of the influence of dam operations on both sediment, fish and the foodbase 

during 2015-17 research and monitoring. Nearly all of the data required for ecological 

assessments are already being collected from various monitoring projects, and this project aims 

at integrating these diverse data through collaborative analyses. Information from integrated 

studies on how specific dam operations influence the river’s bed-sediment type, inundation of 

channel margins used by fish, and other aquatic organisms is needed by members of the 

GCDAMP, but will also inform resource managers working to complete an ongoing 

environmental impact statement required to implement a 20-year Long Term Experimental 

Management Plan (LTEMP) for operating Glen Canyon Dam (see: http://ltempeis.anl.gov/).

C.1. Scientific Background 

The GCD tailwater is commonly referred to as “The Lees Ferry reach” and contains a 

popular and highly valued recreational rainbow trout fishery within the remaining ~15-mile long 

segment of Glen Canyon, extending from the dam to the confluence of the Paria and Colorado 

Rivers (Korman and others, 2010). Glen Canyon is generally considered to be the source of most 

rainbow trout found in GCNP, and where most of the CRe’s limited aquatic food is produced 

(mainly composed of drifting benthic invertebrates; Kennedy and others, 2013a). Owing to the 

facts that Lake Powell traps about 94% of the river’s upstream fine sediment supply, and Paria 

River flows are of limited duration and highly variable, winnowing of fine sediments on the bed 

of the river below Glen Canyon occurs nearly continuously under most dam operations. Because 

sand and finer particles are efficiently transported downstream by higher MLFF releases (greater 

than about 9,000 ft3/s; Topping and others, 2000) in the main channel between Paria River 

sediment deliveries, long periods may occur when the tailwater, and its discontinuity distance 

created by the dam may extend below the Paria River confluence. Sediment researchers have 

extensively studied the influence of dam operations on sediment transport, and bed winnowing as 

these physical processes relate to fine sediment resources in GCNP (Grams and others, 2013; 

Schmidt and Grams, 2011a; 2011b; Wright and others, 2010; Grams and others, 2007; Grams 

and Wilcock, 2007; Rubin and others, 2002; Topping and others, 2000;). However, the process 

of bed winnowing with respect to fine sediment below the dam has not been fully evaluated as an 

integrated part of aquatic resource monitoring and research projects, particularly those focused 

on rainbow trout and the foodbase.

Glen Canyon

Although the CRe is impounded by a single large dam, Kennedy and others have described 

the GCD tailwater as being highly impaired on the basis of the river’s low diversity of aquatic 

invertebrates, and complete lack of three key indicator invertebrate taxa (written commun., US 

Geological Survey, 2013). At full pool, the dam impounds about 4 years of upper Colorado River 

basin runoff in Lake Powell; resulting in release temperatures more like those found in alpine 

river settings. The impounded river below the reservoir consists of several different “rivers” or 

segments, each with their own unique characteristics; the first being the remaining segment of 

Glen Canyon not inundated by Lake Powell. Glen Canyon is a meandering segment of the 

Colorado River incised into Navajo Sandstone with only a few ephemeral tributaries which 

rarely flow and contribute very little sand to the channel below the dam. An exception to this 

occurred in August 2013, when two large floods in Waterholes Canyon, a tributary about 3 miles 

312
upstream of Lees Ferry, added volumes of gravel and fine sediment to lower Glen Canyon at 

about the mid-point of NO study reach 1. Although details about these floods are not yet 

available, the sediment inputs appear to have altered the river’s channel-bed and channel margin 

sediment type immediately below this ephemeral tributary (preliminary observations, Yard, 

Korman and Melis, 2013). In winter 2013-14, NO researchers later reported declines in quarterly 

rainbow trout catch, perhaps in response to increased sand coverage of the gravel bed and 

channel margins (preliminary data, Korman and Yard, US Geological Survey, 2014). The 

Waterholes Canyon flooding was an important motivating influence for this project, as well as 

other questions recently raised by recreational anglers about possible influences of lower-flow 

dam operations on the trout fishery during 2014 (the WY 2014 7.48 maf minimum release 

volume has been the lowest since 1964). Recent evaluation of existing Glen Canyon channel data 

associated with low-angle channel margins accessed by juvenile trout (figure 2-upper panels; 

preliminary data, Melis and Grams, US Geological Survey, 2014), indicates that dam releases 

result in very different types of shoreline changes as flow increases between the dam and Lees 

Ferry. Use of low-angle near shore channel margins by juvenile trout is therefore likely to be 

quite variable throughout Glen Canyon under diurnal fluctuating releases associated with 

hydropeaking operations. Trout researchers have suggested that knowing more about how dam 

releases inundate low-angle channel margins used by trout would advance understanding about 

how various stable or fluctuating flows influence early life survival of rainbow trout. Figure 2 

(lower) shows the variability in deep versus shallow areas of Glen Canyon, and most low-angle 

channel margins are located near the shallower channel sections, such as Four Mile Bar (RM3.9). Additional details on Glen Canyon channel change history since closure of GCD can be 

found in the Project 3, element 3.2 (Grams and others, above).

14

14.5

15

15.5

16

16.5

17

17.5

18

200 400 600 800 1000 1200

FOUR-MILE BAR (river miles -4.2 to -3.2) 

Low-Angle Habitat Area Changes with Increasing 

Glen Canyon Dam Releases [X-Section R-4]

y = 8.2299 * x^(0.10344) R= 0.95438 

CUMULATIVE WETTED CHANNEL AREA (ha)

DISCHARGE (m3/s)

HISTORIC VERTICAL SCOUR OF R-14

[1965-2000] ~ 0.60 METERS

5.5

6

6.5

7

7.5

8

8.5

200 400 600 800 1000 1200

PUMPHOUSE BAR (river miles -14.5 to -14.0) 

Low-Angle Habitat Area Changes with Increasing 

Glen Canyon Dam Releases [X-Section R-18]

y = 3.3956 * x^(0.12725) R= 0.83532 

CUMULATIVE WETTED CHANNEL AREA (ha)

DISCHARGE (m3/s)

25,000 CFS

8,000 CFS

6,000 CFS

5,000 CFS

7,000 CFS

HISTORIC VERTICAL SCOUR OF R-18 

[1965-2000] ~ 2.25 METERS

313
Figure 2. Top panels - two examples of hypsometric profiles, or channel-margin inundation curves derived from 2 

dimensional cross sections located adjacent to low-angle gravel bars in Glen Canyon; (upper left) Four-Mile, and (upper 

right) Fourteen-Mile Bars, (located 4 and 14 miles upstream from Lees Ferry). Though not derived from modelled flows, or 

even thought to be fully representative of river stage and inundation across the entirety of either of these bars, the examples 

demonstrate the range of variability in gravel bar area river shorelines at low-angle channel margins between the dam and 

Lees Ferry for dam releases ranging from the lowest to the highest flows that typically occur under MLFF operations 

(preliminary data, Melis, Gushue and Grams, U.S. Geological Survey, 2014). Lower panel – longitudinal depth profile of the 

bed of the CRe (measured at a flow of 8,000 ft3

/s) between Glen Canyon Dam and Lees Ferry in late May 2009, (with large 

vertical exaggeration) showing the high variability in flow depth in the post-regulated era (preliminary data, Melis, Andrews 

and Kennedy, U.S. Geological Survey, 2009).

As Lake Powell filled during the 1970s, Glen Canyon was further transformed from the 

setting of a desert river to one with near-perfect conditions for establishment of the highly prized 

GCNRA rainbow trout sport fishery. Between 1986 and 2002, dam releases were cold owing to 

hypolimnetic reservoir releases from Lake Powell through the GCD hydropower plant, with little 

annually variation. The river in Glen Canyon in that era was about 3-8oC colder than optimal 

temperatures needed by rainbow trout for spawning, egg incubation and growth (Valdez and 

Speas, 2007). By 1980 GCD and Lake Powell had even created a “thermal” discontinuity in the 

Colorado River with respect to introduced trout. A similar issue was recognized on the Green 

River below Flaming Gorge Dam, but alteration of the thermal regime there was mitigated 

through construction and operation of a selective withdrawal structure to warm dam releases to 

manage the tailwater sport fishery (see figure 6 of Olden and Naiman, 2010).

0

20

40

60

80

14 12 10 8 6 4 2 0

LONGITUDINAL PROFILE OF 

GLEN CANYON TAILWATER - MAY 2009

WATER DEPTH IN FEET AT 8,000 FT3/S

DISTANCE ABOVE LEES FERRY IN MILES

Glen 

Canyon 

Dam

Lees Ferry

X-Section

Locations

APPROXIMATE 8,000 CFS WATER SURFACE

314
Glen Canyon Dam Operations and Rainbow 

In keeping with the river continuum and serial discontinuity concepts, GCD releases from 

Lake Powell are virtually devoid of fine sediment most of the time, resulting in turbidity levels 

more typically found in a headwater mountain stream than in a desert river (Ward and Stanford, 

1983). Hence, the channel bed remained armored from the 1965 releases, and Kondolf and others 

(1989) report that grain-size distributions of gravel in Glen Canyon were “adequate” for trout 

spawning when sampled in the mid-1980s. However, daily ranges in GCD releases associated 

with hydropeaking operations between 1965 and 1991, limited natural rainbow trout 

reproduction in Glen Canyon (Maddux and others, 1987), and the fishery required annual 

stocking to be maintained as a recreational resource until the 1990s. Despite channel scouring 

following dam closure in 1963, many areas of the river in Glen Canyon remain relatively 

shallow, particularly at lower MLFF dam releases of 8,000 ft3/s or below (figure 2-lower panel). 

Trout spawning areas in Glen Canyon are often located along channel margins, particularly along 

point bars, such as the Four Mile Bar, but redds are also observed in the deeper parts of the river 

channel (Korman and others, 2005). Experimental fluctuating flows between 5,000 and 20,000 

ft3/s in January through March 2003-5, were intended to desiccate eggs in redds down to 5,000 

ft3

/s and hence limit trout survival. However such flows were found not to be sufficiently low 

enough to reduce the Glen Canyon trout population owing to compensatory survival of fry that 

emerged from deeper redds in the channel (Korman and others, 2011; Korman and Melis, 2011). 

Following reoperation of the dam in 1996, MLFF releases supported natural reproduction of 

rainbow trout and allowed for the fishery to become self-sustaining (Walters and others, 2000). 

Recent channel surveys (preliminary data, Grams and others, US Geological Survey, 2014) and 

1998 resurvey of Marble Canyon cross sections, plus suspended-sediment transport monitoring 

in channel segments downstream of Glen Canyon (preliminary channel data from the late 1990s, 

and WY 2011 data, Topping and others, US Geological Survey) suggest that similar channel-bed 

adjustments may have continued downstream of Glen Canyon since dam closure in 1963. What 

might be the implications of channel-bed sediment winnowing in Marble Canyon (coarsening of 

bed grain size and reduction of bed coverage by fine sediment) if bed sediments evolve there in 

ways similar to those observed in 1965 above Lees Ferry? 

Our first hypothesis follows after this question: “Dam operations that support trout”

Hypothesis - 1: Operations of Glen Canyon Dam result in progressive winnowing of the 

channel-bed to the extent that coarsened bed sediments of the main channel, combined with 

ongoing tributary inputs of gravel, and QW conditions, increasingly support life history 

requirements of nonnative rainbow trout within and below Glen Canyon. 

We suggest that river managers consider the possibility that such combined influences of 

GCD operations may, at least in part, explain 2013-14 presence of abundant age-0 fish caught in 

lower Marble and eastern Grand Canyons (figure 3). To date, Korman and Yard report that 

preliminary NO catch data from reach #2 (RM16 to RM20) of upper Marble Canyon through 

April 2014, have not yet included juvenile trout, but do contain abundant adult rainbow trout. 

One possibility for explaining this might be the upstream influence of Paria River sand inputs 

during 2012-13 on sand coverage of the deeper channel bed upstream of mid-Marble Canyon, 

among several other possible reasons.

315
Figure 3. Length-frequency data collected by NO project from river miles 62-64. Left – July 2012 catch includes mostly 

adults. Right – July 2013 catch includes abundant juveniles (preliminary data, Korman and Yard, US Geological Survey, 

2013).

Following the March 2008 high-flow experiment (HFE), Korman and others (2011) report 

that rainbow trout survival and recruitment in Glen Canyon was above average in 2008-9. This 

enhanced fish production is thought to have, in part, been the result of flood disturbance of the 

channel bed in Glen Canyon; a process that resulted in reduced production of benthic 

invertebrates overall, but with elevated production of a couple of benthic taxa that were 

important dietary items for juvenile trout fry after their emergence from gravel redds (Cross and 

others, 2012). Korman and others (2012) also report that other experimental and management 

flow operations from GCD since 2008, that have been associated with enhanced rainbow trout 

production on the basis of monitoring data and modelling simulations (figure 4).

High-flow dam releases since GCD was experimentally re-operated to MLFF rules in 1996, 

such as the March 2008 HFE, indicate that such flows are large enough to “cleanse” the channel 

bed below the dam of finer sediment and other debris that clog interstitial pore spaces used by 

trout and benthic invertebrates (Cross and others, 2012; see table 1 of Melis and others, 2012; 

Korman and others, 2011).

5000

10000

15000

20000

25000

30000

35000

10/1/1996 1/1/1997 4/1/1997 7/1/1997 10/1/1997 1/1/1998

Discharge of the Colorado River below 

Glen Canyon Dam, 

measured at Lees Ferry, AZ 

(USGS streamgage #09380000)

DISCHARGE (cubic feet per second)

WATER YEAR 1997

A.

Low Flow for 

Aerial Imagery

Overflight

Higher Steady

Flows Released

in response to 

Above Average

Runoff Forecast

1st Test of Habitat-Maintenance

Flow in November (Fall HFE)

5000

10000

15000

20000

25000

30000

35000

10/1/1999 1/1/2000 4/1/2000 7/1/2000 10/1/2000 1/1/2001

Discharge of the Colorado River below 

Glen Canyon Dam, 

measured at Lees Ferry, AZ 

(USGS streamgage #09380000)

DISCHARGE (cubic feet per second)

WATER YEAR 2000

B.

Low Summer Steady Flows

June through September

Higher Steady

Flows Released

as part of Low Summer Steady 

Flow Experiment 

(intended to pond

LCR confluence and simulate

spring flooding prior to 

summer lows)

2nd and 3rdTests of Habitat-Maintenance

Flow released as part of Low Summer Steady Flow

Experiment

316
Figure 4. Flow hydrographs for Colorado River measured at Lees Ferry, AZ (USGS streamgage #09380000) – these show 

Glen Canyon Dam releases in water years during which Korman and others (2012) modeled above-average rainbow trout 

survival/recruitment: (a) 1997, (b) 2000, (c) 2008, (d) 2011. Each of these hydrographs contains annual release volumes 

greater than the minimum required water transfer from the Upper to Lower Colorado River Basin, and have similarities in 

that each year had periods from winter through summer and fall in which river flows were higher and steadier than would 

otherwise have likely occurred during minimum-volume release years after 1996 (8.23 million acre feet), without reservoir 

equalization or experimental flows (2001-02, and 2006-07). Since the Glen Canyon Dam EIS was completed in 1995, 

experimental flows of one type or another have occurred in: 1996-97, 2000, 2003-05 and 2008-13. Water Years 1998-99, 

were the only years of MLFF operations associated with larger than minimum annual release volumes, but no experimental 

flow treatments other than MLFF.

The four annual hydrographs shown in figure 4, each have common elements of higher flows 

in late winter through spring, as well as a component of increased daily flow stability during 

seasons in which trout early life-stage survival are known to respond positively, at least within 

Glen Canyon (Korman and others, 2005; 2011; 2012). In 2011, the largest estimated trout 

recruitment year to date, dam operations were managed most of the year to achieve required 

“equalization” water transfer from Lakes Powell to Mead, but experimental steady flows in 

September-October 2011, were also released at about 16,000 ft3/s. The Water Year 2011 

hydrograph was characterized by relatively high and stable flows relative to most MLFF releases 

that had occurred from about 2001, up to that time. Korman and others (2012) conclude that high 

flows in spring, and steady flows after trout fry emerge from redds, appear to support elevated 

juvenile trout survival in Glen Canyon. Perhaps similar dam releases might also benefit rainbow 

trout in Marble and eastern Grand Canyons. However, to date early life-stage survival studies 

including redds inventory surveys, such as those conducted by Korman and others in 2003-6, 

(Korman and others, 2005), have only been conducted within Glen Canyon. 

A key uncertainty recently identified by aquatic biologists about HFEs is whether fall-timed 

high releases would also disturb the channel bed in ways that increase rainbow trout populations 

in Glen Canyon, or result in more abundant trout in GCNP (Kennedy and Ralston, 2011)?

Our second hypothesis follows after this question: “High-flow frequency and timing”

Hypothesis - 2: Increasing frequency of higher and warmer releases from Glen Canyon Dam 

increases rainbow trout production in the GCD tailwater regardless of seasonal timing, but this 

response is also spatially controlled by the abundance and distribution of fish in Glen, Marble 

5000

10000

15000

20000

25000

30000

35000

40000

45000

10/1/2007 1/1/2008 4/1/2008 7/1/2008 10/1/2008 1/1/2009

Discharge of the Colorado River below 

Glen Canyon Dam, 

measured at Lees Ferry, AZ 

(USGS streamgage #09380000)

DISCHARGE (cubic feet per second)

WATER YEAR 2008

C.

Higher Monthly

Volume MLFF

Released

in response to 

Above Average

Runoff Forecast

First Time

Equalization 

Operations 

Released under

2007 Interim Guidelines

Record-of-Decision

Spring Test of High Flow

Experiment in March

First Year of 

5-Year Long

Test of Fall Steady

Flow Experiment

5000

10000

15000

20000

25000

30000

10/1/2010 1/1/2011 4/1/2011 7/1/2011 10/1/2011 1/1/2012

Discharge of the Colorado River below 

Glen Canyon Dam, 

measured at Lees Ferry, AZ 

(USGS streamgage #09380000)

DISCHARGE (cubic feet per second)

WATER YEAR 2011

D.

High & Steady

Flows Released

in response to 

Above Average

Runoff Forecast for

Upper Colorado 

River Basin

4th-Year Test of 

Fall Steady Flow

Experiment - Flows

Were Steady at about

16,000 cfs for Sept - Oct.

2nd Equalization Operations under

2007 Interim Guidelines Record-of-Decision

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and eastern Grand Canyons, as well as the timing, frequency and magnitude of Paria River 

floods.

During recent periods from 2003-13, when Lake Powell storage has been reduced, available 

QW data from lower Marble Canyon suggest that the thermal discontinuity distance below GCD, 

at least with respect to rainbow trout life history requirements, may have retreated upstream of 

the Little Colorado River into Marble Canyon. Bioenergetic needs and muscle recover times of 

rainbow trout have been shown by Kieffer and others (1994) to be sensitive to increased 

temperatures. In addition, Robinson and Uehlinger (2008) also report that increased frequency of 

artificial flood disturbance over several years of experimental releases in the River Spol, led to 

gradual shifts in the benthos that were associated with improvements in a brown trout fishery 

below a hydroelectric dam. Owing to relatively more frequent high releases from GCD since 

2008, warmer temperatures in lower Marble Canyon combined with periods of low turbidity, and 

relatively shallow river depths in spring seasons of 2012-13, we therefore propose to integrate 

QW data with channel-bed sediment and fish catch data in evaluating the above hypotheses.

Marble and Eastern Grand Canyons

Below Glen Canyon, the Colorado River through Marble Canyon descends through harder 

Paleozoic lithologies that contribute very coarse sediments to the main channel from small, 

ephemeral tributaries during infrequent hill slope failures that result in debris flows. These 

bouldery debris flow deposits create a series of pools and drops where rapids are formed below 

tributary channel constrictions. The Marble Canyon segment is most clearly distinguished from 

Glen Canyon by relative absence of frequent point bars, but appearance of numerous debris faneddy complexes. These landforms are river reworked lag deposits accumulated from repeated 

debris flows over time (Melis and others, 1995), that locally constrict the river’s channel and 

create recirculating flow zones that are effective traps for sand and finer sediment transported in 

suspension (Schmidt and Rubin, 1995). 

Owing to Glen Canyon Dam and Lake Powell, only about 6% of the CRe’s former sand 

supply is still delivered to the upstream boundary of GCNP in Marble Canyon by the Paria River 

just below Lees Ferry (Topping and others, 2000). This is the primary sand supply available to 

rebuild and maintain sandbars in the eastern third of park when high flows are released that can 

move sand from the river bed and redeposit it along the channel margins (Schmidt and Grams, 

2011b). Currently, an experimental 10-year protocol of HFE releases from the dam is ongoing 

through 2020, in which each experimental release occurs following tributary sand inputs from 

the Paria River. Because Paria River floods that enrich the CRe with sand and finer sediment are 

relatively infrequent, but releases from the dam are nearly always devoid of fine sediments, 

winnowing of channel-bed sand in Marble Canyon occurs most of the time. During experimental 

high flows intended to rebuild sandbars within eddies, bed winnowing is in-fact a required 

process, whereby new sand in the lower areas of the river channel are suspended and carried into 

near shore areas along channel margins and re-deposited at higher elevations.

The upper Tapeats Sandstone gorge of GCNP is bisected 61 miles below Lees Ferry by the 

Little Colorado River (LCR) at its confluence with the Colorado River. Eastern Grand Canyon 

begins at this point. The LCR is the natal origin source area for the largest population of 

endangered humpback chub, is a second major source of sand to the main channel, and is also 

one of three potential source areas for exotic fish introductions to the Colorado River in Grand 

Canyon. The LCR is also a second significant downstream source of silt/clay loads to the main 

channel below the dam. Turbidity values measured 26 miles downstream of the LCR confluence 

are typically elevated above levels resulting from Paria River fines input to Marble Canyon. On 

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the basis of both water temperature and downstream turbidity, one might reasonably conclude 

that the LCR is the downstream boundary of the GCD discontinuity distance with respect to 

nonnative trout and the CRe’s foodbase, but not perhaps relative to native fish in terms of either 

turbidity or temperature.

Recent Lower Marble Canyon Sediment Monitoring Data

Besides site-to-site variation in how a given flow from the dam might inundate specific 

channel-margin areas used by rainbow trout, it’s also important to recognize that above-average 

dam operations in 2011, were also very effective at exporting a large volume of the highly 

limited sand supply in Marble Canyon downstream, as reported by Topping (U.S. Geological 

Survey, written commun., January 2012, as the annual volume released from the dam was about 

50% greater (12.5 maf than prior minimum annual releases of 8.23 maf). The estimated sand 

budget for the lower 30 miles of Marble Canyon between May 2009 and 2012, suggests a sand 

deficit within measurement uncertainties; one that appears to have mostly resulted from 2011 

operations (figure 5-left). 

One possible influence of sand export from Marble Canyon might be that sediment on the 

river bed becomes coarser grained as finer particles (sand and finer) are winnowed (Rubin and 

others, 2002). Topping and others (2003) report that re-operation of GCD in the 1990s actually 

reduced the percentage of time that sand inputs from the Paria River can accumulate on the river 

bed (figure 5-right) as a result of reduction in the lower flows that commonly occurred from 

1965 until late 1991. Ongoing annual inputs of sediment coarser than sand from smaller 

ephemeral tributaries in Marble Canyon (Webb and others, 2000), also means that gravel 

supplied to the bed of the Colorado River below Lees Ferry could also be potentially augmenting 

trout spawning areas of the deeper bed as sand is exported downstream under most dam releases. 

Preliminary results from channel mapping (Project 3, Grams and others, US Geological Survey, 

2014) conducted over a three year period from 2009 to 2012 in lower Marble Canyon also 

support the downward trending sand budget over the same period (figure 5-left). The repeat 

channel surveys also reveal that the majority of sand lost from the 30-mile long river segment 

was evacuated from the deeper parts of the channel bed outside of eddies where most sandbars 

are found. An example of bed map imagery is shown in figure 15 of Project element 3.4 (above).

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Figure 5. Left - cumulative sand budget for Lower Marble Canyon (river miles 30-61) from May 2009 to June 2012, and 

discharge at the Colorado River above the Little Colorado River near Desert View, AZ. Although the budget over this 3-

year period is still technically indeterminate within the uncertainty bounds, it more clearly suggests sand mass export from 

Lower Marble Canyon (GCMRC preliminary sand budget, 2014; www.gcmrc.gov), and the downward trend in sand storage 

supports topographic channel-bed monitoring of the segment from May 2009 to May 2012, that indicates about 0.47(+/-

0.15) Tg of sand were eroded from the main channel of Lower Marble Canyon in the period between the mapping surveys 

(Grams and others, preliminary data, USGS 2014). Right - Flow-duration curves for the Colorado River at Lees Ferry from 

each of the four post-dam decades and the entire pre-dam period. The gray shaded region shows the pre-dam discharge 

range under which sand accumulated in the reach between the Lees Ferry and Grand Canyon gaging stations, in Marble and 

upper Grand Canyons. The percentages of time when these discharges were exceeded during each period are indicated in 

italics (from Topping and others, 2003). This trend suggests that MLFF has probably been effective at keeping the channel 

bed in lower Marble Canyon highly winnowed with respect to sand and finer sediments, and implementation of the 2012-20 

HFE protocol, allowing annual clear water floods annually in the fall might also be providing areas of gravel exposure and 

lower water turbidity during the December through June periods; seasons when rainbow trout are typically known to spawn 

below Glen Canyon Dam.

Recent Lower Marble Canyon Water Quality Data

Korman and others (2012) report that high and steady releases from the dam throughout 

much of Water Year 2011, and the earlier spring 2008 HFE both resulted in above average 

rainbow trout survival and recruitment in Glen Canyon. Fish monitoring data in Marble and 

eastern Grand Canyons after 2010, indicate that rainbow trout abundance increased below Lees 

Ferry, but most trout were assumed to have derived from Glen Canyon source area. As already 

mentioned, recent trout catch data from the NO project in July 2013, suggest that rainbow trout 

reproduction has been occurring in either lower Marble or eastern Grand Canyons (figure 3). The 

most recent spring 2014, preliminary catch data also suggest possible spawning further upstream 

in mid-Marble Canyon as well. (preliminary data, Korman and Yard, US Geological Survey, 

2014). One possible explanation for these observations is the presence of more trout in below 

Lees Ferry since 2011, but other information might also be considered to explain downstream 

abundance of juvenile trout.

Recent (2006-13) QW data collected from the Colorado River 61 miles downstream of Glen 

Canyon, provide insight about the July 2013 juvenile rainbow trout catch data collected by NO 

researchers in their most downstream study site (NO reach 4b) just below the confluence of the 

Little Colorado River (figure 3). The median water temperature of the Colorado River in lower 

Marble Canyon during the December through May period (months when rainbow trout are 

observed to spawn in Glen Canyon) of Water Year (WY) 2013, was only slightly above the 

optimal temperature of 10oC for rainbow trout spawning and egg incubation (figure 5-left; 

Valdez and Speas, 2007). Bioenergetic and food availability must also be considered relative to 

temperature influences and trout metabolism (Elliott, 1984; Kieffer and others, 1994), and 

Kennedy and others (2013a) report aquatic food to be a limiting factor for fish in the CRe. 

As part of a risk assessment study of thermal conditions and fish below GCD, Valdez and 

Speas (2007) estimated “assessment scores” for native and nonnative species found in GCNRA 

and GCNP, under two simulated thermal regimes for operation of GCD; with and without a 

selective withdrawal structure (SWS) added to the project’s hydropower plant intakes. The 

purpose of the previously proposed SWS, is to mitigate thermal pollution from GCD, and 

manage for warmer water temperature releases downstream; the aim being to increase juvenile 

native fish survival, including humpback chub. Scores estimated for rainbow trout under the 

SWS simulations in both Glen and Marble Canyon suggest that this nonnative species is likely to 

benefit most from the relatively small increases in downstream water temperatures when a 2-unit 

SWS operation, with brown trout scoring second highest (preliminary data, R. Valdez and D. 

Speas, 2007, Bureau of Reclamation). Although an SWS is no longer being proposed for 

operation at the GCD, reduced storage in Lake Powell since about 2001, has resulted in 

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downstream water temperatures that trend very close to those estimated from the SWS 2-unit 

simulations. In the late 1970s, Flaming Gorge Dam on the Green River was retrofitted with an 

SWS, and has been operated successfully, but mostly to increase downstream water temperatures 

to benefit nonnative sport fish, including rainbow trout (see figure 6 of Olden and Naiman, 

2010).

Following sustained high releases from Glen Canyon Dam in WY 2011, and the November 

2012 HFE, the median value of main channel turbidity in lower Marble Canyon from December 

2012 through May 2013,was very low (figure 5-right). On the basis of what is known about the 

life-history requirements of rainbow trout (Valdez and Speas, 2007; Korman and others, 2011), 

water quality in lower Marble Canyon was similar during winter through spring 2012-13, to 

conditions found upstream in Glen Canyon. However, many other factors might limit or promote 

trout spawning, egg survival and recruitment in lower Marble Canyon. Korman and Melis (2011) 

have suggested that careful and consistent monitoring of rainbow trout and factors associated 

with their survival and recruitment, including HFEs, is required to inform managers about GCD 

operating strategies aimed at co-management of native and nonnative fish below the dam.

Figure 6. Left - recent values of median annual and (DEC through JUN) water temperatures of the Colorado River 

measured at river mile 61 in Lower Marble Canyon for water years 2006-13. December through June periods have tended to 

be colder than the annual median water temperature and contrast the most during Water Year 2011, when 12.5 million acre 

feet of water were released from Glen Canyon Dam to equalize water storage between Lakes Powell and Mead. During the 

following Water Year 2012, by contrast, water temperatures were relatively warmer upstream of the Little Colorado River 

(NO study reach 4a) and about 2o Celsius warmer than in 2011, during months when rainbow trout are known to spawn 

upstream in Glen Canyon. Both colder median annual and winter-through-spring water temperatures occurred in Water Year 

2013, prior to preliminary juvenile rainbow trout catch data (July 2013) suggesting localized trout production in lower 

Marble Canyon. It is not presently clear how water temperatures, turbidity levels or channel-bed sediment types might 

influence aquatic food production and potential for rainbow trout spawning and recruitment below Glen Canyon, but 

monitoring has shown increased abundance of trout near the Little Colorado River since about 2011 (W. Pine, written 

commun. Univ. of Florida, 2012, and Korman and Yard, preliminary data, Ecometric Research and USGS, 2014). Right -

recent levels of median turbidity (DEC through JUN) measured at river mile 61 in lower Marble Canyon for water years 

2006-13. The winter through spring seasons shown follow the warm-season (JUL – OCT) when tributary fine-sediment 

inputs typically enter Marble Canyon from the Paria River and other lesser drainages upstream of the Little Colorado River. 

Rainbow trout studies in Glen Canyon suggest that fall through winter and into spring is the main period for spawning in the 

15-mile long tailwater below Glen Canyon Dam. It is not clear if and to what degree both lower turbidity and channel-bed 

sediment types (presence of gravel suitable for redds) during 2012-13 in Lower Marble Canyon might have contributed to 

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July 2013 to April 2014, preliminary juvenile catch data suggesting localized trout production in NO study reaches 3 and 4a, 

located between 37 and 61 mile and just upstream of the Little Colorado River confluence with the main Colorado River.

Drift samples are also collected as an ongoing part of rainbow trout research within all NO 

study sites during seasonal fish monitoring to evaluate trout diets. At present, those data are not 

yet available, but increasing water depth has been identified by Yard (2003) as an attenuating 

factor in solar insolation reaching the river bed under low turbidity, and may therefore also limit 

primary production. It is possible that higher rainbow trout abundance in lower Marble Canyon 

observed after 2011, combined with more optimal water temperatures for spawning and egg 

incubation in winter, plus low turbidity and warming in late spring and summer may have 

promoted aquatic food availability and trout growth in spring 2013. Such influences may 

partially explain large numbers of juvenile trout captured recently by NO researchers below Lees 

Ferry. But what about conditions of the channel bed with respect to suitable spawning gravels? 

Channel-bed sediment data that might shed light on this question have been collected by Project 

3 (channel and sandbar mapping) scientists in May of 2009 and 12, as part of sand storage 

monitoring throughout lower Marble Canyon, but have not yet been evaluated relative to trout 

monitoring data collected by NO researchers. Similarly, the river segment just below the LCR 

confluence (NO study site 4b) was also mapped by sediment researchers in May 2011 and 14, as 

part of eastern Grand Canyon sandbar monitoring (Project 3, Grams and others). We propose that 

an integrated evaluation of these valuable physical data sets with fish data is needed to address 

new and emerging ecological questions (figure 1). We believe that this research must now be 

undertaken to further inform managers about how dam operations may be influencing aquatic 

resources through downstream changes in physical characteristics of the GCD tailwater.

“STAGE” SET FOR A THIRD HYPOTHESIS

Korman and others (2012) also report that high and steady flows in spring through summer, 

may also provide trout fry that emerge from gravel redds access to expanded near-shore areas 

that are hypothesized to enhance juvenile survival. One of these areas, Four Mile Bar in Glen 

Canyon, was observed by fisheries scientists (Korman and Avery, 2011) to be shallow, warm 

and vegetated with extremely abundant numbers of juvenile rainbow trout in summer 2011 when 

dam releases were steady at about 25,000 ft3

/s. This is one hypothesis for why the 2011 rainbow 

trout cohort likely exceeded the 2008 HFE response. Owing to geomorphic variations in the Glen 

Canyon channel width, and non-uniform 1965 vertical channel scouring that transformed Glen 

Canyon gravel bars, we estimate that any given dam release will inundate the low-angle channel 

margins differently, and these are areas known to be used by juvenile trout in the Lees Ferry 

tailwater (Korman and others, 2011; figure 2-upper panels). How different are distributions of 

low-angle and steeper channel margins in Glen, Marble and eastern Grand Canyon NO study 

areas, and which of the low-angle channel-margin areas used by rainbow trout throughout these 

river segments are most sensitive to river inundation or dewatering in response to hourly varied 

GCD operations?

Our third hypothesis follows after this question: “Flow variations and shoreline changes”

Hypothesis - 3: Geomorphic differences of the Colorado River’s channel geometry within NO 

study sites 1 & 4b, combined with behavior of flow and stage, result in varied channel margins, 

and these differences influence fish access to near shore areas in ways that limit the influence of 

how hourly changes in flow affect trout below GCD relative to their distribution, abundance, 

growth and survival of age-0 rainbow trout.

As such, experimental dam operations that have been recently discussed by GCDAMP 

stakeholders and LTEMP cooperators for managing rainbow trout abundance below the dam in 

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Glen and Marble Canyons, may have limited downstream effectiveness on early life-stage 

survival of rainbow trout.

Without proposed 2015 mapping by Project 3 (see description for element 3.2), 

developing more detailed hyposometric profiles (relationship showing area of channel margins 

covered by water over a range of river stages and dam releases using flow modeling methods) is 

only possible for Glen Canyon from Lees Ferry upstream to about Six-Mile Bar, where shoreline 

and channel bathymetry were previously obtained in 2004 and 2009. Upstream of Six-Mile Bar, 

full channel bathymetry has not been collected. In most of Glen Canyon only widely spaced 

cross sections exist (Grams and others, 2007), but most of them are not ideally located close to 

juvenile trout nursery channel-margin areas to be fully informative to NO or foodbase 

researchers (Projects 9 and 5). Further, without development of a flow model in Glen Canyon in 

2015 (see project 5, Kennedy, Wright and Muehlbauer), shorelines can only be crudely estimated 

in low-angle channel margin areas using a few of the widely spaced, cross sections and 

associated rating curves. A two-dimensional flow model exists for NO reach 4b, and we propose 

to use it for estimating shorelines along channel margins below the LCR confluence (RM62-

RM64) where rainbow trout and juvenile humpback chub are intensively monitored) in this 

project. A meaningful comparison of shoreline sensitivity to dam operations between fish 

sampling sites in lower Glen Canyon (NO reach 1) and NO reach 4b, requires that flow modeling 

be possible upstream of Lees Ferry as well (see Project 5 elements). 

Depending upon which of the several hypotheses regarding rainbow trout growth are supported 

by ongoing research (see hypotheses associated with Project 9), recruitment of juvenile trout tied 

to use of low-angle channel margins in late spring and summer seasons (Korman and others, 

2011) might be experimentally managed throughout the GCD tailwater using flow treatments 

patterned over specific stage ranges and changing flow rates. Hence, design of future flow 

experiments to manage the trout population in Lees Ferry, might be informed using low-angle 

channel margin and shoreline maps in NO reaches 1 (lower Glen Canyon) and 4b (RM62-RM64 

of eastern Grand Canyon), as well as information resulting from combined analyses of fish catch 

data and shoreline mapping. This new project, in combination with Projects 3, 5 and 9, intends to 

collect additional data about physical channel characteristics (Table 1) that will allow more 

detailed assessments and understanding about how specific experimental and management dam 

releases influence life history strategies of rainbow trout in Glen, Marble and eastern Grand 

Canyons.

C.2. Management Background 

At least eleven resources are described within four Desired Future Conditions (DFC) 

associated with adaptive management of Glen Canyon Dam. Three of them include: protection of 

native fish, particularly the humpback chub; maintaining a quality recreational rainbow trout 

fishery immediately below the dam in GCNRA, while also simultaneously controlling nonnative 

fish in GCNP, particularly trout; and conservation of fine sediment (rebuilding and maintenance 

of sandbars also valued as camping beaches). All three of these valued resources are described in 

two of the DFCs “Colorado River ecosystem” and “Recreation”, but understanding by scientists 

and managers about how each of these resources is tied to dam operations can vary from well 

documented to highly uncertain (Gloss and others, 2005; Kennedy and Ralston, 2011). 

Responses of sandbars, fish and their prey items, to dam releases also vary widely in time and 

space over 400 km of the CRe. The other two DFCs include hydropower, and cultural resources.

An ecosystem approach to long-term monitoring was identified as a priority by the GCMRC 

at the time it was established in 1996. During past reviews of the GCMRC and the GCDAMP, 

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integrating physical, biological monitoring efforts with focused interdisciplinary analyses of 

diverse, but interrelated data was identified as a critically needed strategy for improved 

understanding about how Glen Canyon Dam operations influence downstream resources: 

“As pointed out in previous National Research Council reviews (1987, 1996a), an 

ecosystem approach seeks an understanding of interrelationships among important physical, 

chemical, biological, and social processes.” (Wescoat and others, 1999).

Further, the 1999 review panel suggested that “Short term research projects must be closely 

linked with the monitoring program.” and that “Physical, biological, cultural, and socioeconomic 

measures should be co-located in space and time wherever and whenever practical.” In their 

review of the biological program at that time, the panel’s final report states that “Linkages 

between and among biological and various other resource categories remain poorly articulated. It 

is therefore critical that the Biological Resources Program be closely integrated within itself and 

that, at a minimum, the Biological Resources and Physical Resources programs be tightly 

interwoven; it is not yet apparent that either condition is satisfied.” (Wescoat and others, 1999). 

Since then, many advances have been made in areas of the GCMRC’s physical and biological 

monitoring programs. However, less progress has occurred in the area of interdisciplinary 

research using now abundant monitoring data for focused science integration to address 

management uncertainties; particularly, those relating sediment to the CRe’s nonnative and 

native fisheries, and the river’s foodbase.

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Conceptual ecosystem modeling was also identified in the GCMRC’s initial 5-year strategic 

science plan as a critical activity to help identify gaps in monitoring, linkages between resources 

and dam operations, as well as alternative “policy” experiments that might also be considered for 

adaptive management of the dam. Two phases of such modeling between 1998 and about 2011, 

focused mostly on the CRe’s aquatic resources, but understanding about how certain dam 

operations influence fine sediment, exotic rainbow trout and elements of the river’s food web has 

been greatly advanced through flow experimentation, such as high flow experiments (HFE) 

mainly intended to rebuild sandbars using the highly limited remaining sand inputs below the 

dam.

Although conceptual ecosystem modeling is not currently an element of the science program 

to support the GCDAMP, the legacy of past modeling efforts strongly suggests that aquatic 

ecosystem linkages with physical characteristics of the river channel that support fish and 

foodbase resources of GCNRA and GCNP, are particularly important areas to focus integrated 

research on. This may be particularly true now that ongoing sediment, flow, quality-of-water 

(QW), and aquatic monitoring projects are well established.

Perhaps one of the largest uncertainties facing GCDAMP resource managers, may be dam 

operating options to achieve sustainable co-management of both valued nonnative recreational 

and endemic native fisheries below Glen Canyon Dam in GCNRA and GCNP. Uncertainties 

about trout in GCNP and their interactions with humpback chub are at the center of this goal 

(Yard and others, 2011; Korman and others, 2011; Korman and Melis, 2011). Because nonnative 

species are not desired within GCNP, but rainbow trout are highly valued as a recreational 

resource within GCNRA, the challenge of co-managing these two fisheries has a strong 

longitudinal and geographical context relative to Glen Canyon Dam and its operation. Recent 

monitoring and research has shed light on direct and indirect influences of dam operations and 

these two important fisheries, as well as the aquatic foodbase of the CRe. Integrated studies of 

specific dam operations, such as high and steady flows, and their influence on multiple resources 

linked to both fisheries will help identify possible future options for fisheries co-management.

C.3. Key Monitoring and Research Questions Addressed in this project 

This interdisciplinary project will use QW data collected by Project 2 (Topping and others), 

and foster collaboration between physical and aquatic Projects 3, and 9, through the coordinated 

involvement of scientists that are already conducting research and monitoring in support of the 

GCDAMP and planning of a 20-year long experimental management plan being completed as 

part of the LTEMP EIS (see Grams and others; Korman, Yard and Kennedy, FY2013-14 BWP). 

These combined projects directly address the following Strategic Science Questions (SSQs), and 

Core Monitoring Information Needs (CMINs) previously identified by the GCDAMP, but 

through coordination provided by this project and the valuable products derived from Projects 3 

and 9, we will ensure a more direct linkage between existing channel sandbar mapping data and 

NO rainbow trout studies in an attempt to address the following questions and information needs 

relative to the three hypotheses identified above. 

Primary SSQs addressed:

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• SSQ 1-3. Do rainbow trout immigrate from Glen to Marble and eastern Grand Canyons, 

and, if so, during what life stages? To what extent do Glen Canyon immigrants support 

the population in Marble and eastern Grand Canyon?

• SSQ 5-6. Do the potential benefits of improved rearing habitat (warmer, more stable,

more backwater and vegetated channel margins, more food) outweigh negative impacts 

due to increases in nonnative fish abundance?

Answering any of the above questions requires integrated analyses of fisheries and foodbase 

information with data from Project 3 (see Grams and others, FY2013-14 BWP), a project that 

has also identified information needs focused on sediment conditions monitored in the main 

channel of the Colorado River, including: 

• CMIN 8.6.1. Track, as appropriate, changes in coarse sediment (> 2 mm) abundance and 

distribution.

• CMIN 8.1.1. Determine and track the biennial sandbar area and fine-sediment volume 

and grain-size changes within eddies below 5,000 cfs stage, by reach. 

Although not specifically identified as an information need by the GCDAMP, Project 3 also 

provides critical information about bathymetry and “sand area and fine-sediment volume and 

grain-size changes” throughout long segments of the main channel below 5,000 ft3/s stage 

outside of eddies in upper and lower Marble Canyon, as well as eastern Grand Canyon; areas 

containing intensive rainbow trout and native fish monitoring segments. The GCDAMP’s DFC 

“Colorado River ecosystem” encompasses what was originally identified as the main sediment 

resource objective: “Goal 8: Maintain or attain levels of sediment storage within the main 

channel and along channel margins to achieve Adaptive Management ecosystem goals.” 

Generally, it is assumed that the sediment goal focuses on rebuilding and maintenance of 

higher-elevation sandbars along channel margins which can only be achieved by periodic high 

dam releases that re-suspend available sand from deeper parts of the main channel and lower 

eddies and redeposit it as sandbars. However, to date, there has not previously been any 

identification by managers about whether sand deposits covering the river bed have any role in 

the management of other non-sediment resources also described in the CRe desired future 

condition, such as nonnative trout, native fish or the foodbase. Despite guidance from managers 

about the role of fine sediment in the Colorado River channel outside of eddies, there has been 

prior recognition of the linkages between fine and coarse sediments in the channel and other CRe 

aquatic resources, as mentioned within the FY2013/14 biennial work plan (formerly Project A, 

now Project 3, Grams and others): 

“Because sediment monitoring addresses the physical framework of the ecosystem, 

which underlies many biological resource objectives, Project A also indirectly supports 

achievement of:

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• Goal 1: Protect or improve the aquatic food base so that it will support viable populations 

of desired species at higher trophic levels. The proposed monitoring supports this goal by 

providing information on the size and distribution of channel substrate.

• Goal 2: Maintain or attain a viable population of existing native fish, remove jeopardy

for humpback chub and razorback sucker, and prevent adverse modification to their

critical habitats. The proposed sandbar and sediment storage monitoring supports this

goal by providing information on sandbars which create backwaters, a habitat used by

native fish.”

Another overarching question identified by Grams and others (FY2013/14 BWP) during the 

last two years is: “What is the long-term net effect of dam operations, including high flows, on 

changes in low-elevation sand storage and bed sediment texture (the sand below the 8,000 ft3

/s 

stage)?” The answer to this question, perhaps as much as any other, is the one that we intend to 

integrate into 2017 NO analyses tied to NO fish catch and diet data.

The strategy for ongoing channel mapping was initiated prior to the start of NO monitoring 

efforts in the FY2013/14 biennial work plan and before recent fish sampling suggesting trout 

reproduction in Marble Canyon. Therefore, there has been only limited opportunity for planning 

of integration between fish and sediment monitoring efforts before now. In light of new 

emerging information from juvenile trout catch data below Glen Canyon, coordinating additional 

bed imagery and topographic data collection is now critically needed in 2015-16 within NO 

study sites in Glen, Marble and eastern Grand Canyons. This effort will support multi-year 

integrated evaluation (2012-16) of fisheries and channel-bed sediment data (Table 1). Following, 

are summary descriptions of the tasks and methods associated with the seven project tasks within 

two elements proposed for 2015-17.

D. Proposed Work 

D.1. Project Elements 

(Recommended for funding FY15: $95,000; Unfunded Moderate Priority FY15: $54,094)

As listed above, there are seven objectives of this integrated tailwater fisheries project to be 

achieved in three elements. One particularly critical objective likely has the most immediate 

management implications for co-management of native and nonnative fisheries below the dam. 

This is the assessment of the low-angle channel-margin areas inundated by most MLFF dam 

releases typically ranging from 5,000 up to ~25,000 ft3/s. These are operations that have 

occurred since rainbow trout studies started in 2003, and have a direct influence on the nearshore 

areas that become available to trout fry after they emerge from redds (Korman and others, 2011). 

We believe that observations in summer 2011 by NO researchers of juvenile trout extensively 

using shallow inundated channel margins within Glen Canyon under high and steady dam 

operations, and the resulting survival of record numbers of fry that year (Korman and Yard, 

preliminary 2011 juvenile trout population estimate ranging from 0.8 to 1.2 million fish, 2012), 

warrant evaluation of the range of dam releases that create rearing areas for trout. As such, we 

anticipate the use for this type of information in planning future experimental flows that may be 

proposed to manage rainbow trout abundance below the dam. This information may be of 

particular interest to managers involved in the ongoing LTEMP EIS, and planning of a 20-year 

experimental management plan for Glen Canyon Dam operations.

 

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Project Element 10.1. Refine Humminbird Sidescan Sonar and Other Channel Mapping Methods to Support 

Fish and Foodbase Research 

Dan Buscombe, Research Geologist, USGS, GCMRC

Graduate Student, USGS, GCMRC

Ted Melis, Physical Scientist, USGS, GCMRC

Tom Gushue, GIS Coordinator, USGS, GCMRC

GS-9 Geographer, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Cooperator: Josh Korman, Fishery Biologist, Ecometric Research

Here, we intend to complete and document the methodology for determining changes in sand 

and gravel of channel-bed areas where trout are monitored by NO researcher in Glen, Marble and 

eastern Grand Canyons. This work is anticipated to be completed in FY2015, with methods 

being used through 2016 for ongoing post-processing of sidescan sonar channel-bed imagery. 

Results will support data collection and analyses needed to address three hypotheses associated 

with Project element 10.3.

Objectives: 

• Define protocols for the best use of sidescan sonar to quantify spatial area of sand and 

gravel bed sediments of the Colorado River channel, as such the proposal includes 

provision for a graduate student, whose tasks will include:

• Developing completely or partially supervised bed sediment classification algorithms 

using existing sidescan data, collected in recent years, at high resolution with continuous 

coverage, based on calibrated echo strengths and texture (spatial pattern) of echoes,

• Validating these methods using concurrent video observations and sediment 

classifications based on multibeam backscatter (where available),

• Developing the computational advances necessary for correcting a boat-mounted 

sidescan transducer for attitude instabilities (heave, roll, pitch and yaw), and evaluating 

the effects on sidescan image quality, using data collected in UMC in 2013 and EGC in 

2014,

• Evaluate the sensitivities in corrected geo-referenced sidescan amplitudes to 

uncertainties in attenuation due to sediment or gradients in sediment concentration, 

transducer location and boat heading,

• Developing the computational means by which sidescan can be corrected for bed slope 

effects when bed bathymetry is available, in which case it would be possible to correct 

for grazing angle effects on the sidescan echoes. The grazing angle is the angle made 

between the incoming acoustic beam and the local normal to the surface and affects the 

extent to which acoustic wave energy is reflected specularly and scattered diffusely. As 

such it represents a significant source of uncertainty in the image of the bed taken from 

multiple viewpoints (transducer locations and look angles). If the slopes are known 

along and across the beam, from existing bathymetries, a beam footprint can be 

accurately calculated and the backscatter value from each sidescan pixel modified by 

integrating over the area, 

• Systematically characterize bed sediments in data collected in 2000 using a Klein towedsidescan system, from RM0 to RM225 (preliminary data, Anima and others, 2007, US 

Geological Survey, Marine Geology Team, Pacific Science Center, Santa Cruz, CA).

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Rationale/Justification

Topographic mapping and the collection of photographic imagery of the Colorado River’s 

deeper channel bed below GCD have become an ongoing monitoring protocol to track changes 

in the spatially segregated distribution of sand area and sand volume with in the main channel 

and eddies of the Colorado River. This information supports sediment information needs of the 

GCDAMP, and is an integral part of monitoring in support of the 2012-20 HFE protocol. Dam 

operations are known to influence sand and gravel area coverage of the bed, and areas of coarser 

bed sediment are known to be used by benthic invertebrates and trout below the dam. As such, 

there is need to better document and evaluate changes over time in bed sediment type in response 

to tributary sediment inputs and MLFF dam operations, including high flow releases, particularly 

in key areas where fish and fish diet data are intensively monitored (NO, Project 9). Integrated 

analyses of bed mapping information with NO catch and diet data will then help identify how 

dam operations may influence and perhaps be used to manage not only sandbars, but also certain 

aquatic resources, such as trout and the foodbase.

The sediment make-up of the bed surface, which is exceptionally diverse in character, with 

the full spectrum of fine sand to boulders arranged in complicated spatial patterns, is constantly 

evolving and almost impossible to predict to any meaningful degree. That is, beyond generalized 

(and broad scale) observations of sand accumulating in eddies adjacent to sand-winnowed main 

channels, our prediction skill for a particular substrate or substrate mixture to be present in a 

particular location is poor. Bed sediment type is a boundary condition for which no predictive 

model exists. We therefore rely on observations of the bed which consists of: 1) the technology 

to image the riverbed surface with sufficient resolution that different substrates are 

distinguishable; 2) the accuracy and precision in positional measurements which make it possible 

to detect changes in individual locations through time; and 3) methods with which to accurately 

and efficiently (ideally unsupervised or partially supervised) estimate substrate type. 

Conventional sampling of submerged sediment deposits (e.g. grabs, cores, and dredges) is costly 

and labor-intensive. Video and photographic sampling is more cost-effective and does not 

require time-consuming laboratory analyses, which allows sampling at greater frequency and 

coverage (Rubin and others, 2007; Buscombe and others, 2014a). However, the use of highfrequency acoustic backscatter from swath-mapping systems to characterize sediment and 

classify by grain size (Anderson and others, 2008; Brown and Blondel, 2009; Brown and others, 

2011) has the potential to provide near complete coverage, which photographic sampling could 

not practically achieve, at least within the same time and with the same positional accuracy. 

Completely capturing the variability bed sediment grain size with conventional physical or 

photographic sampling would be prohibitively costly and time-consuming. 

Methods

We have recently developed a technique (Buscombe and others 2014b; 2014c) which 

automatically classifies sediments into 3 broad categories: 1) sand; 2) gravel (and sand-gravel 

mixtures); and 3) rocks (boulders and bedrock), based on the statistics of backscatter over these 

different sediments. Using this technique we're producing maps of substrates at unprecedented 

coverage and detail (figure 7). The method uses the spectral properties of the fluctuating 

component of backscatter over small spatial scales in combination with a machine-learning 

classification approach (decision tree). The method has been designed to be general in 

application with a solid physical basis. So far, 30 miles of river bed (lower Marble Canyon, 

LMC) have been classified at a resolution of 0.25 m2

, through a completely automated and 

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unsupervised classification algorithm, using data collected in May 2012. The results have been 

validated using thousands of underwater video observations. The approach to sediment 

classification was able to classify patches of homogeneous sands, gravels (and sand-gravel 

mixtures), and cobbles/boulders with 95, 88, and 91% accuracy, respectively. The technique is 

currently being applied to other reaches mapped by Project 3 (LMC in 2009, eastern Grand 

Canyon (EGC) in 2011, and upper Marble Canyon, (UMC) in 2013). This work, which will be 

completed in 2014, will provide a full channel substrate map from RM0 to RM87, and a repeat 

substrate map for RM30 to RM61. Ongoing and future method development work (within 

Project Element 3.2) includes extending this technique so it is able to differentiate between sands 

and gravels of different sizes, as well as experimenting with the use of multibeam (MBES) 

backscatter to map submerged vegetation in Glen Canyon in 2015. With an operational method 

already developed for acoustic substrate classification, and several years of experience with 

collecting MBES data from the Colorado River in GCNP, we anticipate a rapid turn-around in 

data-processing which, for the first time, makes repeat mapping of substrates a realistic 

operational goal. To maximize efficiency, and minimize data collection costs, this data will be 

collected as part of Project Elements 3.2 and 3.4: namely, “Bathymetric and Topographic 

Mapping”, which proposes to map the reach RM-15 to RM0 in 2015 (including Natal Origins 

(NO) reach 1), RM87 to RM165 in 2016, and RM0 to RM30 in 2017 (including NO reach 2); 

and “Connecting bed material transport, bed morphodynamics, and sand budgets in Grand 

Canyon”, which is proposed to annually map in NO reach 4a upstream of the confluence of the 

Little Colorado and Colorado Rivers. 

Sidescan Sonar

The dynamics of the system are such that at a given location, sand coverage, and the spatial 

distribution of sand coverage, can vary significantly in time. Given the spatial heterogeneity of 

the Colorado riverbed, substrate estimates based on only a handful of observations at discrete 

locations are difficult to reliably extrapolate to reach-scale areal coverage of various substrate 

types. Physical sampling is also costly, laborious, and intrusive to organisms that call the 

riverbed home or use the bed to spawn. However, the use of acoustics for substrate mapping is 

non-intrusive and offers unparalleled spatial coverage and resolution. 

The need to develop methodologies to map subaqueous riverbed sediment types is especially 

great when the water is too swift or deep to wade, too shallow for multibeam sonar, too turbid or 

deep to sense the bed from aerial imaging platforms, and/or when minimal logistics are required. 

The deployment of multibeam sonar requires a significant logistical overhead. Conventional 

underwater photographic imaging systems are limited by light attenuation, turbidity, and small 

spatial footprint of images when close enough to the bed to provide high resolution. A lowprofile, pole- or transom-mounted sidescan sonar has the potential to meet this technical 

shortfall. Sidescan sonars image large swaths of the bed from a vessel, typically with decimeter 

to meter resolution depending on the range to the bed. The sonar sends out a high-frequency 

(several hundreds of kHz) acoustic pulse either side of the receiver and records the amplitude of 

the returning echo. With each pulse, a small strip of the bed is mapped, providing near 

continuous coverage as the boat moves slowly downstream. Coupled with a GPS or other type of 

vessel tracking, it can provide a continuous image of the bed, the texture of which can be used to 

infer the channel-bed sediment type. In addition to morphological form roughness, the strength 

of the returned echo is a function of the composition of the bed sediments. The basic premise is 

that, given the same roughness, a harder surface with greater acoustic impedance, such as rocks 

and cobbles, will return more energy than a softer bed such as sand. Inexpensive commercial 

sidescan systems are available which are designed to be mounted to small vessels and easy to 

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use. They are also lightweight and have low demands for power, so could potentially be applied 

in any navigable river or stream, by as little as 1 person. Many modern sidescan transducers are 

very low profile and require minimal draft which means they are especially suitable for imaging 

in very shallow water. Kaeser and Litts (2010) reported that the sidescan sonar on the 

Humminbird® commercial fishfinder was sufficient quality for shallow water bed sediment 

mapping in shallow rocky streams. They were able to produce bed texture maps by merging and 

superimposing imagery onto a base map in a GIS, and manually identifying regions of similar 

bed texture on these maps (Kaeser and others, 2012). Since 2009, a Humminbird® sidescan 

sonar unit has been used opportunistically to image certain sections of the riverbed. We have 

tested this inexpensive sidescan sonar system in Marble and Glen Canyons in 2013 and 2014, 

establishing that the sonar is able to provide detailed images of the bed in water depths less than 

a meter (whereas MBES systems are limited to relatively deep water: >2m). The sonar provides 

an instant picture of the texture of the bed (figure 8) and can be used to map hundreds to 

thousands of square meters of riverbed in minutes (figure 9). Over the past year, we have 

improved upon the processing procedures of Kaeser and others (2012) by developing means by 

which to, in an automated sense:

1. Convert raw recorded sidescan amplitudes into units of acoustic power (dBW; decibel 

Watts). This potentially enables the derivation of acoustic/physical properties such as 

acoustic attenuation, bed roughness and hardness.

2. Correct the sidescan amplitudes for directivity attenuation, which depends on the 

geometry of the transducers and the beam shape of the acoustic wave, and acoustic 

attenuation by water and sediment, based on measured depth and estimates of the 

concentration and grain size of sediment in suspension.

3. Correct (partially) the sidescan amplitudes for angular effects imposed by the relative 

angle between the acoustic beam and the surface insonified by the beam (the acoustic 

footprint).

4. Apply geometric (slant-range) corrections to the data and estimate the orientation of scan 

lines, so it is possible to estimate the location of each sidescan pixel with greater 

accuracy, and which enables sidescan amplitudes to be processed as a geo-referenced 

point cloud.

Small, portable and lightweight sidescan sonars are easily deployable instruments for bed 

sediment reconnaissance surveys and the instantaneous qualitative assessment of large swaths of 

bed habitats. As such it is a technology which is, uniquely amongst its competitors, capable of 

providing rapid assessment of substrates over large areas of the bed, with minimal logistic 

overhead. In this proposal, we aim to build upon the recent advances listed above in a number of 

ways, all contributing to the aim of developing and utilizing robust and automated methods to 

relate sidescan image texture to different channel-bed sediment types, with an aim of producing 

maps of bed-sediments which are comparable in quality, resolution and reproducibility as those 

created using MBES backscatter. We aim to develop unsupervised (fully automated) or partially 

supervised (minimal user input) methods to classify bed sediments by grain-size using the echo 

strengths and/or the texture (spatial pattern) of echoes. If substrate classifications are carried out 

manually, this is not only time-consuming and labor-intensive (therefore expensive) but, in 

addition, the results are not necessarily reproducible (the same classifications obtained by 

different people, or by the same person at different times) unless a set of rigid protocols are in 

place. Such protocols would be difficult to achieve for sonar data across multiple instruments. 

The solution is to develop automated (unsupervised) or at least partially supervised (minimal 

user input) methods to classify large amounts of bed imagery in a consistent manner.

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In summary, the aim of this work is to produce near-continuous (spatially explicit) maps of 

channel-bed sediment types, broadly categorized into sand, gravel, cobble and rock, at high 

spatial resolution (centimeters to meters). These techniques will be applied existing data sets 

(Table 1) previously collected in each of the NO reaches during 2012-14, as well as data which 

will be collected during 2015-2016, in support of the collaborative 5-year integrated analysis of 

fish and physical data described in Project Element 10.3. 

Figure 7. Map of riverbed sediments near Phantom Ranch in eastern Grand Canyon. Yellows are sandy bed, blues are 

gravels and mixed sand/gravels, and reds are rocky areas. This map has been created using a newly developed technique 

which relates the statistics of multibeam echoes to different types of riverbed sediments (preliminary data, Buscombe and 

others, U.S. Geological Survey, 2014).

Figure 8. Example of “Humminbird®” sidescan imagery of the riverbed near -9 mile bar in Glen Canyon showing a patchy 

riverbed with fine to coarse gravels and clumps of submerged vegetation (shadow areas). Ongoing work is trying to relate 

each observed texture to a substrate type using underwater video for reference (preliminary data, Buscombe and Melis, US 

Geological Survey, 2013).

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Figure 9. Example of “Humminbird®” sidescan imagery of the riverbed immediately downstream of Glen Canyon Dam 

showing a uniform coarse gravel bed. Units are decibel Watts, assuming a root-mean-square transducer output of 1000 

Watts. It is standard convention to express this value 1m from the transducer. The inset panels show the trace from the low 

frequency sonar, and the depth sounding from under the boat (preliminary data, Buscombe and Melis, US Geological 

Survey, 2013).

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Project Element 10.2 Collecting New Channel-Bed Humminbird® Sidescan Sonar and Digital Channel Margin 

Imagery, and Analyzing Channel-Margin Geometry, and Shoreline Responses to Flow Variation using Channel 

Map Data to Support Natal Origins of Rainbow Trout and Juvenile Humpback Chub Research 

Ted Melis, Physical Scientist, USGS, GCMRC

Tom Gushue, GIS Coordinator, USGS, GCMRC

GS-9 Geographer, USGS, GCMRC

Dan Buscombe, Research Geologist, USGS, GCMRC

Graduate Student, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Cooperator: Josh Korman, Fishery Biologist, Ecometric Research

Objectives: 

• Collect new Humminbird® sidescan sonar imagery of the channel-bed and evaluate 

similar existing data to determine spatially segregated proportions of bed-sediment type 

within NO reaches 1 through 4 (see Table 1),

• Semi-annually in 2015-16, collect new Brinno® time-lapse digital imagery of shorelines 

during April and September intensive fish sampling trips in NO reaches 1 through 4.

• Evaluate changes in distributions of sand deposits along NO sampled shorelines between 

2012 and 2017, using 2013 aerial imagery, existing Brinno® imagery collected in 2014, 

and new imagery collected through 2016,

• Spatially analyze shoreline geometry (proportion of slope angles less than 11 degrees 

used by juvenile trout) and gravel grain size distributions of low-angle channel margins 

throughout Glen Canyon; then evaluate hypsometric characteristics of shorelines relative 

to changes in dam releases from 5,000 to ~25,000 ft3/s using new Glen Canyon flow 

model (contingent upon funding for Wright and others, Project 5), in NO reach 1, 

• Spatially analyze geometry (proportion of slope angles less than 11 degrees used by 

juvenile trout) of low-angle channel margins throughout NO reaches 2 – 4b of Marble 

and eastern Grand Canyons; then evaluate hypsometric characteristics of shorelines 

relative to changes in dam releases from 5,000 to ~25,000 ft3/s using existing flow model

(preliminary model, Logan, US Geological Survey, 2012) in NO reach 4b in eastern 

Grand Canyon,

• Summarize median seasonal and annual statistics for water temperature and total 

suspended-sediment, and turbidity measurements made in the Colorado River from 

available QW data collected in 2011-16, at monitoring sites between the dam and RM87.

Hypotheses/Questions: 

1. Hypothesis - Operations of Glen Canyon Dam result in progressive winnowing of the 

channel-bed to the extent that coarsened bed sediments of the main channel, combined 

with ongoing tributary inputs of gravel, and QW conditions, increasingly support life 

history requirements of nonnative rainbow trout within and below Glen Canyon. 

Questions: 1) Are grain-size distributions of low-angle gravel bars throughout Glen 

Canyon similar between the dam and Lees Ferry? 2) Do proportions of sand and gravel 

areas of the deeper channel bed channel in NO reaches 1 through 4 vary annually (within 

detection limits) between 2012 and 2016, and if so, then by how much? 3) Do 

proportions of sandbar mantled shorelines in NO reaches 1 through 4 vary annually 

between 2012 and 2016, and if so by how much? 4) Is there a multi-year trend in the 

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relative proportions of channel-bed sand and gravel area within NO reaches 1 through 4, 

and if so, then do variations correspond with release of high flows from GCD, and annual 

fine-sediment supplied to the Colorado River from the Paria and Little Colorado Rivers?

2. Hypothesis - Geomorphic differences of the Colorado River’s channel geometry within 

NO study sites 1 & 4b, combined with behavior of flow and stage, result in varied 

channel margins, and these differences influence fish access to near shore areas in ways 

that limit the influence of how hourly changes in flow affect trout below GCD relative to 

their distribution, abundance, growth and survival of age-0 rainbow trout. Questions: 1) 

Is the abundance and distribution of low-angle (less than 11 degree channel-margin 

slopes), consistent throughout NO reaches 1 - 4b? 2) Are shorelines associated with lowangle (less than 11 degree slope) channel margins most sensitive to changes in dam 

operations on the basis of modelled shorelines over a range of 5,000 to 25,000 ft3

/s within 

NO reach 1 (lower Glen Canyon) or 4b (eastern Grand Canyon below the LCR)?

Rationale/Justification

Gravel spawning areas for rainbow trout in Glen and Marble Canyons have been previously 

described (Korman and others 2005; Kondolf and others, 1989, Maddux and others, 1987). Trout 

spawning continues to be monitored in Glen Canyon annually as continuation of the rainbow 

trout early life-stage survival (RTELSS) studies initiated in 2003 to study effects of experimental 

fluctuations on trout egg survival (see element 9.2). However, much less is known about whether 

spawning gravel area grain sizes used by trout in Glen Canyon have changed at sites such as 

Four Mile Bar over time, or whether new trout spawning areas have evolved downstream in 

Marble Canyon since initial studies were done by Kondolf and others (1989) in the 1980s. 

Previously collected bathymetric and digital imagery of Marble Canyon have been obtained 

through a variety of methods associated with earlier mapping and monitoring projects and are 

available in FY 2015 for use in development of quantitative methods for estimating areas below 

Glen Canyon with suitable rainbow trout spawning substrates. This research is needed now, as 

preliminary 2013-14 data from the NO project suggest local production of rainbow trout below 

Glen Canyon (fig. 3) has occurred since the project started in fall 2011 (Korman and others, 

Ecometric Research and USGS, preliminary data). Sand budgeting and channel bathymetry data 

collected from 2009 to 2012 from lower Marble Canyon (Grams and others, USGS, 2014, 

preliminary data) also suggest that dam operations since 2009, such as the 2011 extended high 

releases, have created a sand deficit in this segment such that channel-bed conditions below river 

mile 30 may be highly winnowed of finer sediment. The winnowed bed of the channel, 

combined with changing water quality, may have made Marble Canyon more suitable recently 

for rainbow trout spawning and rearing of juveniles; in effect, extending the favorable conditions 

for trout found in Glen Canyon to areas downstream of Lees Ferry.

Topping and others (2003) report that dam operations under MLFF during the 1990s resulted 

in flows exceeding those required to accumulate sand on the river bed between Lees Ferry and 

Phantom Ranch – by about a factor of two compared to the pre-regulated era (figure 6-right). 

This fact also further supports the idea that MLFF dam operations since 1996 have likely 

winnowed bed conditions in parts of lower Marble Canyon where rainbow trout from natal origin 

areas upstream might find suitable channel-bed spawning areas after moving downstream from 

Glen Canyon. Because typical MLFF dam operations were shown to limit accumulation of multiyear tributary sand inputs on the bed of Marble Canyon after 1996, a protocol was implemented 

in 2012 to experimentally determine if more frequent HFEs could rebuild and maintain sandbars 

following Paria River tributary floods. More frequent HFEs that deposit sand deposits from the 

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deeper channel to channel margins within eddies may, however, also create conditions of bed 

winnowing in deeper parts of the channel in lower Marble Canyon; scoured areas that perhaps 

expose areas of the bed with coarser grain sizes (see fig. 15 of Project Element 3.4, above); areas 

perhaps suitable for spawning by rainbow trout.

Methods

Below Glen Canyon, submerged areas of Marble and eastern Grand Canyon have been 

previously mapped at high resolution (Grams, Buscombe and others, preliminary data, USGS, 

2014) multi-beam sonar, but discharge and inundation characteristics of nearshore habitats used 

by juvenile trout have not been previously evaluated downstream of Lees Ferry. The location of 

the USGS gage at 61-Mile (gage 09383100), also provides an opportunity to document channel 

margin habitat inundation upstream of the Little Colorado River confluence, while existing 

channel bathymetry data downstream of the Little Colorado River to about river mile 64, and an 

existing 2-dimensional flow model (B. Logan, preliminary model, USGS, 2012) now make 

evaluation of nearshore habitat in these reaches also possible in 2015-17.

In 2015, using existing 2004 channel bathymetry data, 2009 digital surface model data, and 

available 2-dimensional cross-sections to estimate flows, we will estimate hypsometric curves 

associated with shorelines that vary with dam releases along channel margins where rainbow 

trout and native fish sampling by NO researchers is ongoing between 2012-16. Products will 

include maps showing channel margins inundated by flows of 5,000, 8,000, 15,000, and 25,000 

ft3

/s, and this channel geometry information will also support data needs of food base researchers 

(see Project Elements 5.2.2 and 5.2.4). As shown in Table 1, Project 3 researchers will collect 

new channel map data in Glen Canyon during 2015 (see Project Element 3.2, above), to provide 

a full-channel topographic and channel-bed sediment map for Glen Canyon, in part, to support 

more integrated evaluations of channel characteristics and fish data collected as part of the NO 

project (Project 9). These new data will be used in 2016 to develop a Glen Canyon flow model 

that can then be used to improve modelled shorelines in NO reach 1, and extend similar 

hypsometric channel margin analyses upstream to other low-angle channel margin areas used by 

juvenile trout. We will also use the new 2015 channel data to conduct Arc® map based 

evaluations of the abundance and distribution of low-angle channel margin areas throughout 

Glen Canyon, with particular emphasis within NO reach 1 and the Four Mile Bar, as this 

segment contains a point bar that is frequently used by sport anglers, and on that is also annually 

monitored for redds as part of rainbow trout early life-stage survival (RTELSS) effort (see 

Project Element 9.2).

As described above, in an attempt to better use channel-bed imagery data to support fish and 

foodbase research, Buscombe and others, will develop completely or partially supervised 

channel-bed sediment classification algorithms using existing sidescan data and validate these 

methods using concurrent video observations and multibeam backscatter. They will also pursue 

computational advances necessary for correcting a boat-mounted sidescan transducer for attitude 

instabilities (heave, roll, pitch and yaw) and evaluate the effects on sidescan image quality, using 

data collected from Marble Canyon in 2013 and eastern Grand Canyon in 2014. 

Using the computational means developed in 2015 from Project Element 10.1 (above), by 

which sidescan data can be corrected for bed slope effects, when bed bathymetry is available, we 

will also systematically characterize channel bed sediments in sidescan sonar imagery collected 

in September 2000 (Anima and others 2007). Data from this era prior to intensive rainbow trout 

sampling and research will provide a historical context for bed-change mapping results using 

data from 2011-16, particularly in Glen Canyon where RTELSS monitoring has been ongoing 

336
for more than a decade. Within detection limits of data and methods used for image analysis and 

mapping, we will identify spatial and temporal trends in sand and gravel area of the channel bed 

from existing channel-bed topographic or imagery data collected within four NO study reaches 

(and to the extent possible, adjacent segments upstream) between 2012 and 2016. This is the 

main interpretive physical resource element intended to link areas of the channel associated with 

1) drifting and emergent insects (Projects 5.1 and 5.2), and 2) rainbow trout spawning and early 

life history (Project 9) to changing physical conditions of the Colorado River channel (Project 

3), in the context of other quality-of-water environmental attributes (turbidity and water 

temperature) within Glen and Marble Canyons (Project 2) already being evaluated within the 

2015-17 budget and workplan.

Glen Canyon Low-Angle Channel Margins & Grain Size

In addition, we will document surficial grain size distributions of gravel bars associated with 

these fish monitoring shorelines using digital images collected at approximately the 8,000 ft3

/s 

shoreline elevation at each sample site. Size distributions will be determined using the algorithm 

of Buscombe (2013; example shown in figure 10 here) and these data will be evaluated to 

identify longitudinal trends in grain size along channel margins used by trout between GCD and 

Lees Ferry. Riebe and others (2014) report that trout length may be associated with gravel 

particle size in channel settings where fish build redds. Following after this finding, we will 

measure surficial grain size in channel margin areas of Glen Canyon where redds are typically 

observed and compare them with trout catch data from NO fall marking trips in Glen Canyon to 

evaluate whether either trout abundance and/or length are related to gravel size distributions.

We will also determine shoreline and dam release relationships along low-angle channel 

margins within NO study reach 1 with emphasis on Four Mile Bar; an area used by juvenile trout 

in Glen Canyon (Korman and others, 2011). This work is intended to more accurately identify 

areas of Four Mile Bar that are most sensitive to changes in dam releases; information that can 

be used to inform hydrograph design(s) of experimental trout management dam releases that 

might be implemented under LTEMP as strategy to regulate early life history stages (age-0) of 

rainbow trout, and later using existing 2000-era cross sections (local 2-D rating curves) and 2015 

channel bathymetry data for entire Glen Canyon segment in 2016. Using underwater video 

imaging systems, we will also determine aquatic vegetation characteristics of selected areas of 

the river bed at 500-m spacing between Eight Mile Bar and Lees Ferry above and below 8,000 

cfs to support ongoing development of a potential primary production model (Yard and others).

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Figure 10. Example of coarse-grained size distribution derived from digital still image taken from the surface of a point bar 

located along the river right shoreline about 9 miles upstream of Lees Ferry in Glen Canyon (preliminary data, Buscombe 

and Melis, US Geological Survey, 2013), using the algorithm of Buscombe (2013).

Use of Marble and Eastern Grand Canyon Map Data to Assess Channel Margins

We will produce information similar to what derives from task 3 above, but for existing 

mapped segments of Marble and eastern Grand Canyon - physical channel geometry data needed 

for addressing NO issues regarding spatial heterogeneity effects on capture probabilities within 

and among NO study reaches 2 - 4b (see project element 9.2). This will be undertaken using 

ARC® Map slope analysis tools to evaluate May 2012-13-14 topographic channel data collected 

by Grams and others for sandbar monitoring. Additional multibeam data may also be collected as 

part of Project 3 in 2015-17 in NO reaches 4a and 4b as part of bedload sediment transport 

studies proposed by Grams and others. An existing flow model (preliminary model, B. Logan, 

US Geological Survey, 2012) will also be used to identify shoreline and flow relationships 

within NO reach 4b below the confluence of the LCR and the Colorado River. 

This information will then be used to compare the sensitivity of channel margins to flow 

changes below the LCR, where trout and juvenile chub are monitored, to similar changes in dam 

operations upstream within NO reach 1 (Four Mile Bar) and possibly at other upstream lowangle channel margin settings. Differences in shorelines in response to varied dam releases 

between lower Glen and eastern Grand Canyons will inform fish scientists and dam managers 

about the potential for designing and testing experimental trout management flows in these river 

segments relative to use of low-angle channel margins by juvenile trout. 

Estimating Relative Proportion of Sand and Gravel in Deeper Channel 

Using the methods developed and documented in 2015 by task #1, we will determined 

the time-varied spatial distributions of gravel and sand area exposed along channel margins and 

the deeper channel bed of the Colorado River that are known to be used by rainbow trout in Glen 

Canyon. In Marble and eastern Grand Canyon river segments, we will conduct similar 

assessments in deeper areas of the channel bed to identify areas that may represent potential 

spawning gravel used by trout below the Paria and Little Colorado River confluences. The 

evaluation will be done using pre-existing and new Humminbird and multibeam data specifically 

within or upstream of NO reaches 1 - 4b in 2016; Buscombe, Melis, Gushue, and others.

338
Estimating Relative Proportion of Sand Mantled Shorelines in NO Study Sites

Evaluating possible influences on fish catch rates in NO study reaches 1 - 4b between 2012-

16, associated with changing shoreline and near-shore sandbar deposits (low elevation eddy and 

lower channel sandbars) that may result from tributary sand inputs combined with high flow dam 

operations. To identify channel-margin changes in NO sample sites, we will examine shorelines 

imaged within NO study sites in 2009 and 2013 (digital overflights flown at 8,000 ft3/s), and 

compare sediment and vegetation conditions of those shorelines, with Brinno® time-lapse digital 

camera imagery collected at the study sites on NO fish sampling trips during spring 2014, and 

September and April 2015-16. The imagery will also be evaluated in the context of the 

geomorphic base map being developed by Project 3 (Grams and others) in Glen, Marble and 

eastern Grand Canyons. Changes in sandbar distribution along channel margins between 2013 

and 2016 will be evaluated relative to fish catch data from the NO project to determine whether 

or not sediment characteristics of shorelines influence use of channel margins by rainbow trout 

and native fish. Using Brinno® time-lapse digital cameras, we will image and evaluate channel 

margins in September and April during times when NO rainbow trout catch data are collected 

and when shorelines are imaged at relatively lower flows associated with “shoulder season” or 

reduced monthly dam release volumes that tend to expose larger channel margin areas. 

In this task, we believe we have two unique opportunities to assess possible influences of 

sandbar deposition along shorelines on fish catch. First, within NO site 1, up and downstream of 

Waterholes Canyon. Summer 2013 flooding from this ephemeral tributary appears to have 

altered the lower portion of this most upstream NO study reach; perhaps to an extent that has 

altered trout distribution in Glen Canyon. Trends in trout catch data from 2011 through 2016 

collected above and below Waterholes Canyon will be evaluated relative to the timing of 

Waterholes Canyon flooding and high flows from the dam to determine whether or not the 2013 

sediment inputs altered fish abundance and distribution in reach 1. Downstream, in Marble and 

eastern Grand Canyons, we will also evaluate changes in sandbar abundance along channel 

margins in NO study sites 1 through 4, to determine possible influences of Paria River sand 

inputs and HFEs that may occur in 2014-16, and compare them with fish catch data; Melis, 

Buscombe, Grams and others, in collaboration with Yard and Korman.

Project Element 10.3. Integrated Time Series Analysis of Physical Channel Mapping, Quality-of Water, and 

Natal Origins of Rainbow Trout and Juvenile Humpback Chub Catch and Diet Data 

Ted Melis, Physical Scientist, USGS, GCMRC

Mike Yard, Fishery Biologist, USGS, GCMRC

Josh Korman, Fishery Biologist, Ecometric Research

Dan Buscombe, Research Geologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Tom Gushue, GIS Coordinator, USGS, GCMRC

GS-9 Geographer, USGS, GCMRC

Other aquatic biologists, and invited synthesis workshop expert participants, USGS and 

GCDAMP stakeholders

339
Objectives

1. Identify spatial and temporal correlations between adult and age-0 rainbow trout 

abundance, growth rates, and channel-bed and channel-margin sediment type (sand and 

coarser grain sizes) within NO reaches 1 through 4b,

2. Compare multi-year trends in NO fish catch data, with seasonal to annual variation in 

median water temperature and total suspended sediment data (turbidity), the frequency, 

magnitude and seasonal timing of high-flow dam releases, relative to frequency and 

magnitude of Paria and Little Colorado River fine-sediment inputs to the Colorado River 

between 2011 through 2016,

3. Identify spatial and temporal correlations between age-0 rainbow trout abundance and 

growth rates and the distribution of low-angle (11 degrees slope or less) channel margins 

throughout Glen Canyon, and within NO study reaches 1 through 4b,

4. In collaboration with Project 3, 5 and 9 researchers, evaluate trends in foodbase and 

rainbow trout diet relative to 2011-16 changes in fish catch and channel-bed sediment 

type in NO reaches 1 through 4.

Hypotheses/Questions 

1. Hypothesis - Operations of Glen Canyon Dam result in progressive winnowing of the 

channel-bed to the extent that coarsened bed sediments of the main channel, combined 

with ongoing tributary inputs of gravel, and QW conditions, increasingly support life 

history requirements of nonnative rainbow trout within and below Glen Canyon. 

Question: Do trends in mapped areas of sand and gravel along channel margins and 

within the deeper channel bed in NO reaches 1 through 4b, change between 2011 and 

2017, and if so, then is there any correlation between bed sediment type, adult or age-0 

rainbow trout abundance and growth-rate, or juvenile humpback chub survival data?

2. Hypothesis - Increasing frequency of higher and warmer releases from Glen Canyon Dam 

increases rainbow trout production in the GCD tailwater regardless of seasonal timing, 

but this response is also spatially controlled by the abundance and distribution of fish in 

Glen, Marble and eastern Grand Canyons, as well as the timing, frequency and magnitude 

of Paria River floods. Question: How has the discontinuity distance below GCD changed 

through time relative to the CRe’s thermal and turbidity regimes relative to NO project 

catch data for adult and age-0 rainbow trout abundance and distribution?

Rationale/Justification

Ongoing monitoring of aquatic resources of the CRe, including fish, foodbase, quality-ofwater and sediment, have now been underway to support information and research needs of the 

GCDAMP since the late 1990s through GCMRC’s science program. Over time, new finding 

about how each of these individual resources is tied to operation of GCD has grown. Earlier, 

learning about how dam releases influence fine and coarse sediment in GCNP was advanced 

rapidly by monitoring of the spring 1996 Beach/Habitat Building Flow experiment, as well as 

sediment-transport and channel monitoring of sandbar thereafter (Schmidt and Grams, 2011b; 

Topping and others, 2000). Understanding about how dam operations influence rainbow trout 

and the foodbase in Glen Canyon were advanced initially following integration of singleresource monitoring during and after the March 2008 HFE (Korman and others, 2011; Cross and 

others, 2012). Knowledge about food web dynamics, dam operations and fish in the CRe was 

also advanced by research that focused on trophic linkages below the dam over the last decade 

(Cross and others, 2013; Kennedy and others, 2013). On the basis of these recent advances 

340
intended to better inform managers about options for operating GCD to achieve downstream 

resource goals tied to Desired Future Conditions in GCNRA and GCNP, new research to 

synthesize physical and aquatic data over a multiple year period is now needed. The outcome of 

the project 9 synthesis is intended to provide greater understanding about how specific GCD 

operations influence the channel bed and margins of the CRe, and in turn how changes in those 

physical resources may influence fish and the foodbase over distances that might vary 

downstream of the dam through time. In undertaking this synthesis, we propose to address the 

question about where the GCD tailwater ends below the dam.

Methods

Synthesis Workshop 2017 - The project’s seventh element is the main objective of the 

project, which is to achieve a synthesis of physical and aquatic monitoring data and research 

findings from the NO fisheries and physical channel mapping and QW projects. The aim here is 

to better understand whether and how specific dam operations may be influencing the 

downstream length of the GCD tailwater fisheries, particularly in terms of rainbow trout and 

humpback chub dynamics and interactions, as well as trout diet related to the CRe foodbase. This 

will be a collaboration between aquatic biologist and sediment scientists; one that is initiated 

through a 2-3 day integrated workshop with participants from Projects 3, 5 and 9, as well as 

other invited experts. The timing of this activity is proposed for some time during the first half 

2017, and following the proposed Project 9 Protocol Evaluation Panel (PEP) 2016 review 

meeting to allow input from the PEP to also be considered by workshop participants. Workshop 

participants will present findings from individual research and monitoring projects to promote 

sharing of information among synthesis team members. The first step in synthesizing the 

available physical and biological data will be to overlay time series for rainbow trout catch data, 

with channel map information related to bed-sediment type within each of the NO study reaches 

using available data from 2012-16. The objective of the workshop is to refine approaches for 

further analyses and toward completion of an interpretive report on integrated research findings 

from the NO project’s 5-year intensive fish monitoring of trout origins, movements, diet and 

juvenile humpback chub survival in the Colorado River below the Little Colorado River.

Strategies for further analyzing available time series data to identify spatial and temporal 

patterns in rainbow trout catch and diet, relative to measured variations in channel characteristics 

and QW of the CRe downstream of the dam in the GCD tailwater, will be reviewed and 

discussed among team members to develop approaches for further analyzing spatial and temporal 

patterns of fish catch trends within the GCD tailwater. Strategies for integration physical and 

aquatic data sets into fisheries and productivity models developed by Projects 2, 3, 5 and 9 will 

also be identified. In the 2017 workshop, the 2012-16 fish and physical resource information will 

also be evaluated and discussed in context of earlier ecosystem modeling exercises that were 

formerly undertaken by GCMRC and cooperators in the late 1990s and mid-2000s. In the spirit 

of these early conceptual modeling efforts, GCDAMP stakeholders will participate in the final 

day of the project’s synthesis workshop.

While many other factors likely influence the distribution and abundance of rainbow trout 

below the dam, our synthesis of physical and fish data will provide new perspectives about the 

possible role of dam operations as a factor influencing these aquatic resources throughout Glen 

and Marble Canyons (abiotic/biotic synthesis of dam operations within the upper 1/3 of the 

CRe), and will also inform managers about possible value or need for continuing similar 

integration of physical and biological strategies in future long term monitoring of the CRe.

341
D.2 Personnel and Collaborations 

The majority of researchers is located at the US Geological Survey’s Southwest Biological 

Science Center, GCMRC, but is largely dependent upon ongoing collaboration with cooperator J. 

Korman of Ecometric Research (Vancouver, BC).

D.3 Deliverables 

Project element 10.1) - Manuscript on research and development of new methods for using 

Humminbird sidescan sonar instruments for imaging channel-bed sediment type and sediment 

changes in channel margin settings to support aquatic resource monitoring, Buscombe and others 

(proposed for 2015), Project element 10.2 - Topographic and channel-bed sediment type maps of 

Glen Canyon, Grams, Buscombe and others(proposed for 2016), Project elements 10.3 and 10.4 

– Manuscript on spatial channel-geometry (channel margin slope and grain-size analyses) 

variations along the Colorado River within Glen, Marble and eastern Grand Canyons, with focus 

on modelled flow in channel margin areas (NO reaches 1 & 4b, contingent upon flow model 

development being funded for Glen Canyon) relative to documented use of channel margins by 

rainbow trout and benthic invertebrates, Melis, Gushue, Yard, Korman and others (proposed for 

2016), Project elements 10.5 and 10.6 – Manuscript on the time series of spatially segregated 

distribution of sand and gravel areas of the Colorado River channel margins and bed within NO 

study sites 1-4b between 2011 and 2016, Grams, Buscombe, Melis, Gushue and others (proposed 

for 2017). Presentations at conferences and annual reports to GCDAMP stakeholders. Project 

element 10.7 – Interdisciplinary spatial analysis of 5-years of abiotic and biotic data. Manuscript 

on multi-year rainbow trout catch and diet data relative to mapped changes in channel-bed 

sediment type (sand and coarser grained bed sediment) in Glen, Marble and eastern Grand

Canyons study sites associated with Natal Origins of Rainbow Trout project. Presentations at 

conferences and annual reports to GCDAMP stakeholders.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

None to date, owing to new project status, but the proposed interdisciplinary research builds 

upon numerous physical and biological data products from other ongoing projects preceding this 

integration (see Projects 2, 3, 5, 9).

E.2. Completed Publications 

None to date, owing to new project status, but the proposed interdisciplinary research builds 

upon various publications from other ongoing projects preceding this effort (see Projects 2, 3, 5, 

9).

E.3. Publications in progress 

Buscombe and others, currently have three manuscripts submitted and in review on 

development of methods for imaging channel-bed substrates on the basis of 2013-14 Colorado 

River research conducted under Project 3 (Grams and others) that supports the Element 10.4.1:

Buscombe, D., Rubin, D.M., Lacy, J.R., Storlazzi, C., Hatcher, G., Chezar, H., Wyland, R., 

and Sherwood, C., 2014a (accepted for publication), Autonomous bed-sediment imagingsystems for revealing temporal variability of grain size: Limnology and Oceanography: Methods; 

Buscombe, D., Grams, P.E., Kaplinski, M.A., 2014b (in review), Characterizing riverbed 

342
sediments using high-frequency acoustics 1: Spectral properties of scattering: Journal of 

Geophysical Research - Earth Surface; and Buscombe, D., Grams, P.E., Kaplinski, M.A., 2014c 

(in review), Characterizing riverbed sediments using high-frequency acoustics 2: Scattering 

signatures of Colorado River bed sediments in Marble and Grand Canyons: Journal of 

Geophysical Research - Earth Surface.

E4. Presentations at GCDAMP meetings 

PowerPoint Presentation: GCDAMP Annual Reporting Meeting, Phoenix, AZ, January 29, 

2014, “Low flows in Glen Canyon: preliminary geomorphic analysis of the potential effects on 

fish and food base”, by T.S. Melisa, T. Gushuea, T.A. Kennedya, J.D. Muehlbauera, M.D. Yarda, 

P.E. Gramsa, J.B. Sankeya, K. Kohla, T. Andrewsa, J.E. Hazel Jr.b and J. Kormanc

a U.S. Geological Survey, Grand Canyon Monitoring and Research Center, Southwest 

Biological Science Center, 2255 N. Gemini Dr., Flagstaff, AZ 86001 Contact: tmelis@usgs.gov

b Northern Arizona University, c

Ecometric Research, 3650 W. 22nd Ave., Vancouver, B.C. 

V6S1J3

Poster Sessions: “PRELIMINARY LOW-FLOWS STUDY IN THE LEES FERRY 

TAILWATER BELOW GLEN CANYON DAM” January TWG, and February AMWG 

meetings, Phoenix, AZ, by T.S. Melisa

, T. Gushuea, T.A. Kennedya, J.D. Muehlbauera, M.D. 

Yarda

, P.E. Gramsa, J.B. Sankeya, K. Kohla, T. Andrewsa, J.E. Hazel Jr.b and J. Kormanc

a U.S. Geological Survey, Grand Canyon Monitoring and Research Center, Southwest 

Biological Science Center, 2255 N. Gemini Dr., Flagstaff, AZ 86001 Contact: tmelis@usgs.gov

b Northern Arizona University, c

Ecometric Research, 3650 W. 22nd Ave., Vancouver, B.C. 

V6S1J3.

E.5. Presentations at professional meetings 

None to date, owing to new project status, but the proposed interdisciplinary research builds 

upon various presentations from other ongoing projects preceding this effort (see Projects 2, 3, 5, 

9).

F. References 

Alvarez, L.V., and Schmeeckle, M.W., 2012, Erosion of river sandbars by diurnal stage 

fluctuations in the Colorado River in the Marble and Grand Canyons: Full-scale laboratory 

experiments: River Research and Application, DOI: 10.1002/rra.

Anima, R., Wong, F.L., Hogg, D., Galanis, P., 2007, Sidescan Sonar Imaging of the Colorado 

River, Grand Canyon: U.S. Geological Survey Open-file Report 2007-1216.

Anderson, J.T., Holliday, D.V., Kloser, R., Reid, D.G., Simard, Y., 2008, Acoustic seabed 

classification: current practice and future directions: ICES Journal of Marine Science 65, 

1004–1011.

Brown, C.J., Blondel, P., 2009, Developments in the application of multibeam sonar backscatter 

for seafloor habitat mapping: Applied Acoustics, 70, 1242–1247.

Brown, C.J., Smith, S.J., Lawton, P., Anderson, J.T., 2011, Benthic habitat mapping: A review of 

progress towards improved understanding of the spatial ecology of the seafloor using 

acoustic techniques: Estuarine, Coastal and Shelf Science, 92, 502–520.

Buscombe, D., 2013, Transferable Wavelet Method for Grain Size-Distribution from Images of 

Sediment Surfaces and Thin Sections, and Other Natural Granular Patterns: Sedimentology, 

60: 1709–1732.

343
Buscombe, D., Rubin, D.M., Lacy, J.R., Storlazzi, C., Hatcher, G., Chezar, H., Wyland, R., and 

Sherwood, C., 2014a (accepted for publication), Autonomous bed-sediment imaging-systems 

for revealing temporal variability of grain size: Limnology and Oceanography: Methods.

Buscombe, D., Grams, P.E., Kaplinski, M.A., 2014b (in review), Characterizing riverbed 

sediments using high-frequency acoustics 1: Spectral properties of scattering: Journal of 

Geophysical Research - Earth Surface.

Buscombe, D., Grams, P.E., Kaplinski, M.A., 2014c (in review), Characterizing riverbed 

sediments using high-frequency acoustics 2: Scattering signatures of Colorado River bed 

sediments in Marble and Grand Canyons: Journal of Geophysical Research - Earth Surface.

Clarkson, R.W., and Marsh, P.C., 2010, Effectiveness of the Barrier-and-Renovate Approach to 

Recovery of Warmwater Native Fishes in the Gila River Basin: p. 209-218, in Melis, T.S., 

Hamill, J.F., Bennett, G.E., Coggins, L.G., Jr., Grams, P.E., Kennedy, T.A., Kubly, D.M., 

and Ralston, B.E., eds., 2010, Proceedings of the Colorado River Basin Science and 

Resource Management Symposium, November 18–20, 2008, Scottsdale, Arizona: U.S. 

Geological Survey Scientific Investigations Report 2010–5135, 372 p.

Cross, W.F., Baxter, C.V., Donnor, K.C., Rosi-Marshall, E.J., Kennedy, T.A., Hall, R.O. Jr.,

Wellard Kelly, H.A., and Rogers, R.S., 2012, Ecosystem ecology meets adaptive 

management: food web response to a controlled flood on the Colorado River, Glen Canyon: 

Ecological Applications, 21(6), 2011, pp. 2016–2033.

Davis, P.A., and Melis, T.S., 2010, Mapping Full-Channel Geometry in Grand Canyon by Using 

Airborne Bathymetric Lidar: The Lees Ferry Test Case: pp. 363-372 in Melis, T.S., Hamill, 

J.F., Bennett, G.E., Coggins, L.G., Jr., Grams, P.E., Kennedy, T.A., Kubly, D.M., and 

Ralston, B.E., eds., 2010, Proceedings of the Colorado River Basin Science and Resource 

Management Symposium, November 18–20, 2008, Scottsdale, Arizona: U.S. Geological 

Survey Scientific Investigations Report 2010–5135, 372 p.

Dietrich, W.E., Smith, J.D., 1984, Bed load transport in a river meander: Water Resources 

Research, 20, 1355–1380.

Ellis, L.E., and Jones, N.E., 2013, Longitudinal trends in regulated rivers: a review and synthesis 

within the context of the serial discontinuity concept: Environmental Reviews, 21: 136–148 

(2013) dx.doi.org/10. DOI: 10.1139er-2012-0064.

Gloss, S.P., Lovich, J.E., and Melis, T.S., eds., 2005, The state of the Colorado River ecosystem 

in Grand Canyon: U.S. Geological Survey Circular 1282, 220 p.

Grams, P.E., Topping, D.J., Schmidt, J.C., Hazel, J.E., Kaplinski, M., 2013, Linking 

morphodynamic response with sediment mass balance on the Colorado River in Marble 

Canyon: Issues of scale, geomorphic setting, and sampling design: Journal of Geophysical 

Research - Earth Surface, 118, 361–381.

Grams, P.E., and Wilcock, P.R., 2007, Equilibrium entrainment of fine sediment over a coarse 

immobile bed: Water Resources Research, 43, W10420, doi:10.1029/2006WR005129.

Grams, P.E., Schmidt, J.C., and Topping, D.J., 2007, The rate and pattern of bed incision and 

bank adjustment on the Colorado River in Glen Canyon downstream from Glen Canyon 

Dam, 1956–2000: Geological Society of America Bulletin 119(5–6):556–575. [online] URL: 

doi:10.1130/B25969.1.

Kaeser, A.J., and Litts, T.L., 2010, A novel technique for mapping habitat in navigable streams 

using low-cost side scan sonar: Fisheries, 35 (4), 163–174.

Kaeser, A.J., Litts, T.L., and Tracy, T.W., 2012, Using low-cost sidescan sonar for benthic 

mapping throughout the Lower Flint River, Georgia, USA: River Research and Applications, 

29, 634 – 644.

344
Kennedy, T.A., Yackulic, C.B., Cross, W.F., Grams, P.E., Yard, M.D., and Copp, A.J., 2013, 

The relation between invertebrate drift and two primary controls, discharge and benthic 

densities, in a large regulated river: Freshwater Biology, doi:10.1111/fwb.12285, p. 1-16.

Kennedy, T.A., Cross, W.F. , Hall, R.O. Jr., Baxter, C.V. , and Rosi-Marshall, E.J., 2013, Native 

and nonnative fish populations of the Colorado River are food limited--evidence from new 

food web analyses: U.S. Geological Survey Fact Sheet 2013-3039, 4 p. [online] URL: 

http://pubs.usgs.gov/fs/2013/3039/. 

Kennedy, T.A., and Ralston, B.E., 2011, Biological Responses to High-Flow Experiments at 

Glen Canyon Dam: in Melis, T. S., ed., 2011, Effects of three high-flow experiments on the 

Colorado River ecosystem downstream from Glen Canyon Dam, Arizona: U.S. Geological 

Survey Circular 1366, 147 p. 

Kieffer, J.D., Currie, S., and Tufts, B.L., 1994, Effects of environmental temperature on the 

metabolic and acid-base responses of rainbow trout to exhaustive exercise: Journal of 

Experimental Biology,194, 299–317.

Kondolf, G.M., Cook, S.S. , Maddux, H.R., and Persons, W.R., 1989, Spawning gravels of 

rainbow trout in Glen and Grand Canyons, Arizona: Journal of the Arizona-Nevada Academy 

of Science, 23:19-28.

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 in 

the Colorado River in Grand Canyon using an Integrated Assessment Model: Canadian 

Journal of Fisheries and Aquatic Science. 69:1-23.

Korman, J., and Melis, T.S., 2011, The Effects of Glen Canyon Dam Operations on Early Life 

Stages of Rainbow Trout in the Colorado River: U.S. Geological Survey Fact Sheet 2011-

3002, 4 p.

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 140(2):487–505. 

[online] URL: http://dx.doi.org/10.1080/00028487.2011.572015/.

Korman, J., Kaplinski, M., and Melis, T.S., 2010, Effects of high-flow experiments from Glen 

Canyon Dam on abundance, growth, and survival rates of early life stages of rainbow trout in 

the Lees Ferry reach of the Colorado River: U.S. Geological Survey Open-File Report 2010–

1034. 31 p. [online] URL: http://pubs.usgs.gov/of/2010/1034/.

Korman, J., Kaplinski, M., Hazel, J.E. III, and Melis, T.S., 2005, Effects of the experimental 

fluctuating flows from Glen Canyon Dam in 2003 and 2004 on early life history stages of 

rainbow trout in the Colorado River: Final RTELSS report to the GCMRC, 171 p. [online] 

URL: http://www.gcmrc.gov/.

Maddux, H.R., Kubly, D.M., deVos, J.C., Jr., Persons, W.R., Staedicke, R., and Wright, R.L., 

1987, Effects of varied flow regimes on aquatic resources of Glen and Grand Canyons—

Final report: Phoenix, Arizona Game and Fish Department, submitted to Bureau of 

Reclamation, Glen Canyon Environmental Studies, contract no. 4-AG-40-01810, 291 p. 

[Available from National Technical Information Service, Springfield, Va. as NTIS Report 

PB88-183439/AS.]

Makinster, A.S., Persons, W.R., Avery, L.A., and Bunch, A.J., 2010, Colorado River fish 

monitoring in Grand Canyon, Arizona: 2000 to 2009 summary: U.S. Geological Survey 

Open-File Report 2010–1246.

345
Melis, T.S., Korman, J., and Kennedy, T.A., 2012, Abiotic & biotic responses of the Colorado 

River to controlled floods at Glen Canyon Dam, Arizona, USA: River Research and 

Applications 28:764–776.

Melis, T.S., Webb, R.H., Griffiths, P.G., and Wise, T.J., 1995, Magnitude and frequency data for 

historic debris flows in Grand Canyon National Park and vicinity, Arizona: U.S. Geological 

Survey Water Resources Research Investigation Report 94-4214, 297 p. [online] URL:

http://pubs.er.usgs.gov/publication/wri944214.

Olden, J.D., and Naiman, R.J., 2010, Incorporating thermal regimes into environmental flows 

assessments: modifying dam operations to restore freshwater ecosystem integrity. 

Freshwater Biology 55: 86–107.

Pattison, I., Sear, D.A., Carling, P., Collins, A.L., Jones, J.I., and Naden, P.S., 2012, Assessing 

the effect of fine sediment upon salmonid egg incubation using a modelling approach: SIDOUK. BHS Eleventh National Symposium, Hydrology for a changing world, Dundee 2012. 

ISBN: 1903741181© British Hydrological Society. doi: 10.7558/bhs.2012.ns43.

Riebe, C.S., Sklar, L.S., Overstreet, B.T., and Wooster, J.K., 2014, Optimal reproduction in 

salmon spawning substrates linked to grain size and fish length, Water Resources Research, 

50, doi:10.1002/2013WR014231.

Rubin, D.M., Topping, D.J., Schmidt, J.C., Hazel, J.E., Kaplinski, M.A., and Melis, T.S., 2002, 

Recent sediment studies refute Glen Canyon Dam hypothesis: Eos, Transactions, American 

Geophysical Union, 83(25):273, 277-278.

Rubin, D.M., Chezar, H., Harney, J.N., Topping, D.J., Melis, T.S., Sherwood, C.R., 2007, 

Underwater microscope for measuring spatial and temporal changes in bed-sediment grain 

size: Sedimentary Geology, 202, 402–408.

Schmidt, J.C., and Rubin, D.M., 1995, Regulated streamflow, fine-grained deposits, and 

effective discharge in canyons with abundant debris fans: in Costa, J.E., Miller, A.J., Potter, 

K.W., and Wilcock, P.R., eds., Natural and anthropogenic influences in fluvial 

geomorphology: American Geophysical Union, Geophysical Monograph Series, v. 89, p. 

177–195.

Schmidt, J.C., and Grams, P.E., 2011a, Understanding Physical Processes of the Colorado River: 

Pages 17-52, in T.S. Melis, editor, 2011, Effects of three high-flow experiments on the 

Colorado River ecosystem downstream from Glen Canyon Dam, Arizona, [online] URL: 

http://pubs.usgs.gov/circ/1366/.

Schmidt, J.C., and Grams, P.E., 2011b, The high flows – physical science results: Pages 53-92, 

in T.S. Melis, editor. 2011, Effects of three high-flow experiments on the Colorado River 

ecosystem downstream from Glen Canyon Dam, Arizona: U.S. Geological Survey Circular 

1366, [online] URL: http://pubs.usgs.gov/circ/1366/.

Sear, D.A., Pattison, I., Collins, A.L., Newson, M.D., Jones, J.I., Naden P.S., and Carling, P.A.,

2012, Factors controlling the temporal variability in dissolved oxygen regime of salmon 

spawning gravels: Hydrological Processes, 2012, DOI: 10.1002/hyp.9565.

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, doi: 10.1029/1999WR900285.

Topping, D.J., Schmidt, J.C., and Vierra, L.E., Jr., 2003, Computation and analysis of the 

instantaneous-discharge for the Colorado River at Lees Ferry, Arizona: May 8, 1921, through 

September 30, 2000: U.S. Geological Survey Professional Paper; 1677, 118 p.

Trammel, M. 2010, Fish Management in National Park Units Along the Colorado River: p. 235-

244, in Melis, T.S., Hamill, J.F., Bennett, G.E., Coggins, L.G., Jr., Grams, P.E., Kennedy, 

346
T.A., Kubly, D.M., and Ralston, B.E., eds., 2010, Proceedings of the Colorado River Basin 

Science and Resource Management Symposium, November 18–20, 2008, Scottsdale, 

Arizona: U.S. Geological Survey Scientific Investigations Report 2010–5135, 372 p.

U.S. Department of the Interior, Bureau of Reclamation, 1995, Operation of Glen Canyon Dam 

Colorado River Storage Project, Arizona, Final Environmental Impact Statement: 337 pages 

+ appendices. [online] URL: http://www.usbr.gov/uc/envdocs/eis/gc/pdfs/Cov-con/covcon.pdf.

U.S. Department of the Interior, Bureau of Reclamation, 1996, Record of Decision, Operation of 

Glen Canyon Dam Final Environmental Impact Statement: Office of the Secretary of the 

Interior. [online] URL: http://www.usbr.gov/uc/rm/amp/pdfs/sp_appndxG_ROD.pdf.

U.S. Global Change Research Program, 2014, National Climate Assessment: Washington, DC, 

[online] URL: http://nca2014.globalchange.gov/report.

Valdez, R.A., and Speas, D.W., 2007, A RISK ASSESSMENT MODEL To Evaluate Risks and 

Benefits to Aquatic Resources From A Selective Withdrawal Structure On Glen Canyon 

Dam, draft report, Bureau of Reclamation, Salt Lake City, UT, 55 p.

Walters, C.J., Korman, J., Stevens, L.E., and Gold, B., 2000, Ecosystem modeling for evaluation 

of adaptive management policies in the Grand Canyon: Conservation Ecology, 4(2):1. 

[online] URL: http://www.consecol.org/vol4/iss2/art1/. 

Ward, J.V., and Stanford, J.A., 1983, The serial discontinuity concept of lotic ecosystems: In 

Dynamics of Lotic Ecosystems, Fontaine TD, Bartell SM (eds), Ann Arbor Scientific 

Publishers: Ann Arbor, MI; 29–42.

Webb, R.H., Griffiths, P.G., Melis, T.S., and Hartley, D.R., 2000, Sediment delivery by ungaged 

tributaries of the Colorado River in Grand Canyon: U.S. Geological Survey Water-Resources 

Investigations Report 00–4055, 67 p. [online] URL: 

http://wwwpaztcn.wr.usgs.gov/webb_pdf/wrir00-4055.pdf.

Wescoat, J.L., Jr., Cameron, T.A., Fish, S.K., Ford, D., Gloss, S.P., Kratz, T.K., Minckley, W.L., 

and Wilcock, P.R., 1999, Downstream: adaptive management of Glen Canyon Dam and the 

Colorado River Ecosystem: National Academy Press, Washington, DC, 230 p.

Wright, S.A., Topping, D.J., Rubin, D.M., and Melis, T.S., 2010, An approach for modeling 

sediment budgets in supply‐limited rivers: Water Resources Research, 46: 1-18. W10538, 

doi:10.1029/2009WR008600. [Online] URL: 

http://www.agu.org/journals/wr/wr1010/2009WR008600/2009WR008600.pdf.

Yard, M.D., 2003, Light availability and aquatic primary production: Colorado River, Glen and 

Grand Canyons, AZ: Ph.D. dissertation, Northern Arizona University, Flagstaff, 205 p.

Yard, M.D., Coggins, L.G., Jr., Baxter, C.V., Bennett, G.E., and Korman, J., 2011, Trout 

piscivory in the Colorado River, Grand Canyon: Transactions of the American Fisheries 

Society, 140(2):471– 486.

347
G. Budget 

Project Element 10.1. Refine 

Humminbird Sidescan Sonar 

and Other Channel Mapping 

Methods to Support Fish and 

Foodbase Research

Project Element 10.2 

Collecting New Channel-Bed 

Humminbird® Sidescan Sonar 

and Digital Channel Margin 

Imagery, and Analyzing 

Channel-Margin Geometry, 

and Shoreline Responses to 

Flow Variation using Channel 

Map Data to Support Natal 

Origins of Rainbow Trout and 

Juvenile Humpback Chub 

Research

Salaries $ 63,529.00 Salaries $ 60,000.00 

Traveling and Training $ 2,500.00 Traveling and Training $ 2,500.00 

Operating Expenses $ - Operating Expenses $ - 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 10,565.00 USGS Burden $ 10,000.00 

Total $ 76,594.00 Total $ 72,500.00 

FY 2015

FY 2015 Project 10 Gross Totals: $149,094

348
NOTE: Salary support for Buscombe, Yard, Korman and Grams, derived from Projects 3 & 9 budgets.

Project Element 10.2 

Collecting New Channel-Bed 

Humminbird® Sidescan Sonar 

and Digital Channel Margin 

Imagery, and Analyzing 

Channel-Margin Geometry, 

and Shoreline Responses to 

Flow Variation using Channel 

Map Data to Support Natal 

Origins of Rainbow Trout and 

Juvenile Humpback Chub 

Research

Project Element 10.3. 

Integrated Time Series 

Analysis of Physical Channel 

Mapping, Quality-of Water, 

and Natal Origins of Rainbow 

Trout and Juvenile Humpback 

Chub Catch and Diet Data

Salaries $ 129,774.00 Salaries 96,790

Traveling and Training $ 5,000.00 Traveling and Training 7,000

Operating Expenses $ - Operating Expenses 0

Logistics $ - Logistics 0

Cooperators (non-USGS) $ - Cooperators (non-USGS) 0

USGS Cooperators $ - USGS Cooperators 0

USGS Burden $ 29,650.00 USGS Burden 29,061

Total $ 164,424.00 Total $132,851

FY 2016 Project 10 Gross Totals: $164,424 FY 2017 Project 10 Gross Totals: $132,851

FY 2016 FY 2017 

349
Project 11. Riparian Vegetation Monitoring and Analysis 

of Riparian Vegetation, Landform Change and AquaticTerrestrial linkages to Faunal Communities 

A. Investigators 

Barbara E. Ralston, Supervisory Biologist, U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center

Daniel Sarr, Research Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Joel B. Sankey, Research Geologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Charles B. Yackulic, Research Statistician, U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center

Theodore A. Kennedy, Research Aquatic Ecologist, U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center 

Jeff Muehlbauer, Aquatic Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

David M. Merritt, Research Ecologist, U.S. Forest Service

Patrick Shafroth, Research Ecologist, U.S. Geological Survey, Fort Collins

Joseph E. Hazel, Research Associate, Northern Arizona University

Emily Palmquist, Ecologist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

Laura Cagney, Research Specialist, Northern Arizona University

Todd Chaudhry, Restoration Ecologist, NPS, Grand Canyon National Park, 

Dustin W. Perkins, Program Manager, NPS, Northern Colorado Plateau Inventory and 

Monitoring Program

John Spence, Resource Manager, National Park Service, Glen Canyon National Recreation Area

B. Project Summary 

Riparian vegetation affects physical processes and biological interactions along the channel 

downstream of Glen Canyon Dam. The presence and expansion of riparian vegetation promotes 

bank stability, diminishes the magnitude of scour and fill during floods, and has a role in wildlife 

habitat and recreational values. This project utilizes annual field measurements and digital 

imagery for integrated monitoring of changes in vegetation assessed within a hydro-geomorphic 

context. Research elements of this project utilize the monitoring data to explore the utility of 

plant response-guilds to probabilistically evaluate and assess wildlife habitat, and integrate the 

response guilds with a 22-year topographic survey record for retrospective analyses of 

topographic change of 20 sandbars. This project builds upon accomplishments associated with 

the FY13/14 workplan, provides information that support stakeholder needs as identified by 

guiding documents developed by the Adaptive Management Program, and furthers our 

understanding of the role of riparian vegetation in ecosystem processes in a regulated river 

ecosystem. 

350
The objectives and elements of this monitoring and research project are: 

1. Measurement and analysis of plant cover and species presence to assess change as related 

to the geomorphic setting, elevation above the channel, and flow regime (Project Element 

11.1) 

2. Mapping changes in woody vegetation at the landscape scale through image processing, 

classification, and analysis (Project Element 11.2) 

3. Utilizing vegetation response-guilds for integrated research of sandbars and riparian 

vegetation (Project Element 11.3) 

4. Use multiple sampling approaches and historic data sets to quantify the strength of 

aquatic-terrestrial linkages and the relative importance of vegetation change and aquatic 

production in driving the population dynamics of a subset of the terrestrial fauna (Project 

Element 11.4).

5. A review and assessment of nonnative plant control and native plant restoration efforts 

along regulated segments of the Colorado and Rio Grande Rivers (Project Element 11.5). 

Each of these objectives and the associated project elements inform stakeholders about the 

status of vegetation and support analysis of vegetation’s role in the ecological, physical, 

sociocultural responses to dam operations. 

C. Background 

The abundance, structure, and location of riparian plant species reflect differential responses 

to substrate properties, channel geomorphology (e.g., width, depth, bed and bank material, slope, 

floodplain functionality), and flow regime (Auble and Scott 1998; Mahoney and Rood 1998; 

Auble and others, 2005; Naiman and others, 2005). Species that respond similarly to these 

geomorphic and hydrologic processes can be categorized into response-guilds (Grime, 1979; 

Lavorel and Garnie, 2002; Merritt and others, 2010). Alteration of the flow regimes due to 

regulation by dams changes the disturbance regime and hydroperiod across channel margins and 

leads to changes in the plants that dominate the landscape: river regulation contributed to the 

dominance of tamarisk (Tamarix sp.) and Russian olive (Elaeagnus angustifolia) along the 

majority of the streams and rivers in the southwestern United States (Stromberg and others, 

2007; Birken and Cooper, 2006; Merritt and Poff 2010). River regulation is thus a selective force 

on riparian communities and shifts the dominant species and associated response-guilds found 

along channel boundary.

The nine response-guilds identified from the 2012-2013 field collections (fig. 1, Table 1) are 

a unifying component of each element of the riparian vegetation project (Project 11) in FY15–

17. Annual, ground-based vegetation monitoring is used to refine guilds and identify changes in 

the frequency of guilds encountered at fixed and random sampling sites. These data are 

compatible with Upper Basin river monitoring efforts conducted by the National Park Service’s 

Northern Colorado Inventory and Monitoring. Response-guilds encountered along a river 

channel can imply the responses of vegetation to changes in flow regimes (for example, reduced 

annual water volumes, or increased frequency of floods would be associated with shifts in 

distribution and occurrence of different guilds). Monitoring vegetation within a hydrogeomorphic framework permits the identification of response guilds along a river channel, as 

well as changes in frequency of guild presence that may be associated with changes in the river’s 

flow regime. 

351
Monitoring that includes landscape-scale change detection enables an assessment of the 

extent of observed ground-based changes across the landscape and answers questions such as: Is 

a trend of more plants adapted to xeric conditions along one river segment similar to what is 

observed elsewhere? Is a trend of vegetation-type or amount specific to sandbars or channel 

margins or common to all or most features along a river channel? Annual ground-based 

monitoring provides primary data that enables local and landscape-scale assessment of changes 

in the riparian plant community relative to changes in annual hydrology.

With the increasing recognition of the role that both vegetation and river regulation have on 

fluvial geomorphology, studies evaluating the additive effects of these change agents on 

shoreline and channel geomorphic landforms are increasingly relevant to resource managers 

interested in preserving or re-establishing channel dynamics and in native plant restoration 

efforts (Stromberg, 2001). Just as plants respond to river regulation, the location and distribution 

of riparian plants along a channel affects alluvial landform evolution (Corenblit and others,, 

2008; Osterkamp and Hupp, 2010; Manners and others, 2014). In Grand Canyon, the effect of 

riparian plants on the physical template of the Colorado River corridor is little studied, yet the 

interaction between vegetation and sediment has implications for campsite availability and 

accessibility (Hadley, 2014, Kaplinski and others, 2005, 2014), wildlife habitat (Durst and 

others, 2008; Sogge and others, 2003), and aquatic shoreline habitats. 

352
Figure 1. Dendrogram of preliminary Plant-response 

guilds for the Colorado River in Grand Canyon.

Table 1. Description of Plant Response-guild and 

associated species within guilds.

Guild Guild Description Species

A Xeroriparian 

shrubs, 

disturbance 

intolerance

Lycium pallida,

Artemisia 

ludoviciana, 

Baccharis 

sarothroides

B Drought tolerant 

well dispersed, 

ruderal 

herbs/grasses

Melilotus spp., 

Oenothera pallida, 

Bromus rubens, 

Sporobolus 

cryptandrus

C Mesic, well 

dispersed, 

herbs/grasses

Taraxicum 

officianale, Conyza 

canadensis

D Wetland, clonal 

grasses

Agrostis 

stolonifera, 

Phragmites 

australis

E Wetland,

low growing, 

short-lived, forbs

Equisetum 

arvense, Veronica 

americana

F Wetland, shallow 

rooted, forb, 

nonclonal

Apocynum 

canabinum, 

Boehmeria 

cylindrica

G Wetland, 

perennial grasses, 

forbs

Juncus spp.

Muhlenbergia 

asperifolia, Typha 

latifolia

H Tall-deep rooted, 

disturbance 

tolerant riparian 

phraeatophytes

Tamarix spp.,

Salix exigua, 

Pluchea sericea

I Woody, 

xeroriparian, 

disturbance 

adapted

Prosopis 

glandulosa, Celtis 

reticulate,

Acacia greggii 

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The plant response-guild information developed during FY13–14, provides a means to 

aggregate multiple species into a single variable (guild) to study vegetation’s effect on sediment 

dynamics. For example, each response-guild, composed of a suite of species, could be assigned a 

single roughness value when considering the process of sediment transport and deposition, or a 

single critical shear stress value assigned to a response-guild to evaluate plant removal and 

erosion during high flows in Grand Canyon. A research element for FY15–17 proposes to 

conduct a retrospective analysis of sandbar evolution since 1991 when significant flow regime 

changes occurred. A retrospective analysis of sandbar evolution contributes to an understanding 

of how landforms along the channel change in response to annual hydrology, controlled floods, 

and the presence of vegetation. 

Riparian vegetation comprises critical habitat for terrestrial fauna along the Colorado River 

corridor (Carothers and Brown, 1991; Kearsley and others, 2006; Ralston, 2005), yet the 

relationship between riparian guilds and these animal species remains unstudied. While dam 

operations modify the frequency of vegetation guilds likely leading to changes in the abundance 

and distribution of animal species that rely on these habitats, most studies of terrestrial 

consumers were done many years ago over a relatively short period of time. During these shorter 

time scales, the primary linkage between flow regime and terrestrial animals may be through 

variation in space and time in the amount of emerging aquatic insects that are available as prey to 

terrestrial consumers. Therefore, we will study a suite of terrestrial consumers to better 

understand short-term variation attributable to changes in the strength of insect emergence from 

the Colorado River and, where long-term data are available, use methods that allow us to make 

inferences about long-term changes potentially linked to vegetation change. To the extent 

possible, we will also use historic data to better understand which animal species are linked to 

specific vegetation-flow response guilds 

Lastly, native and nonnative woody riparian vegetation expansion is linked to Glen Canyon 

Dam operations (Turner and Karpiskac, 1980; Mortenson and others, 2011), but removal of 

woody vegetation through dam operations may have limited success. To achieve desired future 

conditions for riparian vegetation, experimental vegetation removal and plantings of native 

vegetation that incorporate future flow operations may be required. For example, experimental 

plant removal and subsequent habitat restoration efforts may focus on tamarisk since tamarisk 

beetle defoliation has occurred along segments of the Colorado River since 2009 (see Project 

Element 11.2). Incorporating a review of previous riparian restoration projects within the 

Colorado River Basin (Colorado River in Canyonlands, the Yampa River in Lodore Canyon, and 

the Rio Grande River in Big Bend National Park) can identify approaches that may be most 

successful in identifying expected outcomes, and in estimating costs for project initiation and 

subsequent monitoring and maintenance. Project Element 11.5 proposes a science panel review 

to examine successes and challenges in non-native vegetation control in the Colorado River and 

Rio Grande watersheds (the area that is the jurisdiction of the US and LC regions of reclamation) 

and to seek recommendations from that group as to how to plan a scientifically-based riparian 

management control program.

Collectively, the monitoring and research elements proposed in the riparian vegetation 

project supports the Adaptive Management Program’s efforts to evaluate the High-Flow 

Experiment Protocol (Bureau of Reclamation, 2011) and flow alternatives that will result from 

the on-going EIS for a Long-term Experimental Management Plan (LTEMP) for Glen Canyon 

Dam. The proposed research elements fundamentally aid in furthering our understanding of the 

role of riparian vegetation in ecosystem processes of a regulated river.

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C.1. Scientific Background 

A riparian plant community integrates the history of hydrologic events that vary in 

magnitude of disturbance and depth of innundation (Naiman and others, 2005). General 

conclusions from decades of plant studies along the Colorado River downstream from Glen

Canyon Dam and in other rivers in the southwest are that: 

• tamarisk colonization events occur following large-scale disturbance that create bare 

substrate for colonization, or changes in the flow regime of regulated rivers where 

alluvial deposits become exposed (Stevens and Waring, 1986; Birkin and Cooper, 2006; 

Mortenson and others, 2012); 

• the reduction in magnitude and frequency of floods in Grand Canyon promoted the 

development of marsh communities (Stevens and others, 1995);

• woody riparian vegetation, in general, has expanded under Record of Decision (RoD) 

operations also as a result of reduced flood magnitude and disturbance (Sankey and 

others, unpublished).

• increases in base flow in the mid-2000’s resulted in increased woody vegetation 

expansion below the stage of 25,000 ft3

/s discharge even with increasing flood frequency 

(Sankey and others, unpublished). 

Landscape scale research and small scale data collection since the 1980s document the 

immediate and long-term response of vegetation to changes in seasonal hydrographs and 

minimum baseflows associated with dam operations.

Current knowledge gained from geophysical studies affords opportunities for linkages 

between geomorphology and plant ecology to assess the interactive response of sediment and 

vegetation on landform processes and terrestrial habitat quality. Key insights from the physical 

science program for the Colorado River in Grand Canyon that are fundamental to integrated 

research include the following:

• Sediment grain-sized eddy bars and channel margin deposits has coarsened since Glen 

Canyon Dam was completed; wind-transported deposits are also coarser as a result (Draut 

and others, 2008; Schmidt and others, 2004; Topping and others, 2000a, b).

• Sandbar response to high-flows include deposition occurring principally within debris fan 

eddy-complexes, with the greatest amount of deposition occurring near zones of flow 

separation and reattachment (Hazel and others, 1999; Schmidt and others, 2001); 

Sediment storage along the channel is greatest within these eddy complexes (Hazel and 

others, 2006b). 

Coarser sediment deposits along the river’s channel and upslope have implications for water 

accessibility and nutrient availability to the roots of plants. Coarser sediments and reduced 

nutrient availability favor drought tolerant plant species and plant species that are adapted to 

nutrient poor environments. Controlled floods that result in sediment reworking and deposition 

affects vegetation by initially partially burying woody vegetation and scouring herbaceous 

vegetation (Kearsley and Ayers, 1999). Vegetation that is adapted to burial or disturbance (for 

example, Salix exigua, Pluchea sericea; table 1) may fair better under increased frequencies of 

controlled floods. Sediment deposition that results in sandbars with increasing elevation affect 

relationships plants roots have to the water table. Plants that are more drought tolerant and have 

355
deeper root systems may be favored under this scenario (for example, Prosopis sp., Tamarix sp.; 

table 1). 

The vegetated landscape that results from changes in sediment characteristics and landform 

evolution affects associated terrestrial fauna. Sogge and others, (1998) identified that complex 

structural habitat, present along the river channel from 1990-1994 increase bird diversity. A 

long-term trend towards increased woody vegetation of similar architecture and height may 

result in either reduced bird diversity, or the attraction of a different assemblage of birds than 

those currently observed along the channel. Similarly, the terrestrial arthropod assemblage that 

forms a food base for both terrestrial and aquatic species may change as substrates become drier, 

or vegetation shifts from a mix of perennial herbaceous and woody vegetation towards a 

predominantly woody vegetated landscape (McCluny and Sabo, 2012; Paetzold and others, 

2008). Whereas vegetation may act a primary filter to determine which species are present in a 

given area, the abundance and distribution of particular terrestrial animal species may also be 

affected by the amount of local insect emergence (Project 5).

The physical components that are studied downstream of Glen Canyon Dam (Projects 2, 3) 

constitute the abiotic inputs that constrain landform processes and the biotic responses. 

Understanding the riparian landscape response to Glen Canyon Dam operations requires 

collective analysis of data from physical and biological disciplines. The challenge for the FY15–

17 Project 11 workplan is higher-level research that links physical and biological responses and 

associated feedbacks. The proposed research elements fundamentally aid in furthering our 

understanding of the role of riparian vegetation in ecosystem processes and the potential effect of 

riparian vegetation on habitat quality within a regulated river.

C.2. Management Background 

Vegetation is recognized as in important element of the Colorado River and is highlighted 

with a specific management goal [Goal 6: Protect or improve the biotic riparian and spring 

communities, including threatened and endangered species and their critical habitat] of the 

GCDAMP. Vegetation provides wildlife habitat (cover, forage, nesting), is the basis of terrestrial 

food webs, influences channel and bar dynamics, provides recreational opportunities and 

aesthetic value, and performs many of the important functions and services valued by humans. 

Most recently, the response of vegetation to future flow regimes associated with the LTEMP EIS 

has been a focus for stakeholders. The vegetation component of the EIS process considers how 

groups of riparian plants may respond to changes in flows and how particular flow regimes may 

benefit native or nonnative species (for example, tamarisk), increase biodiversity, and affect the 

Desire Future Conditions developed by stakeholders. The State and Transition Modeling effort 

by Ralston and others (2014) provided stakeholders with a tool that can assist in evaluating how 

plants respond to changes in the flow regime. For example, the state and transition models 

suggest that relying of flows to remove woody vegetation is likely to have limited success, unless 

the flow regime includes large extended controlled floods like those that occurred in the mid1980s. These collaborative efforts between the GCMRC, the LTEMP EIS team and the agency 

leads involved in assessing alternative flow regimes provides opportunities to be forward 

thinking about the need for mitigation efforts related to vegetation management, as a means to 

support goals for vegetation associated with desired future conditions for the Colorado River 

downstream of Glen Canyon Dam. The state and transition model provides a first step in being 

aware of potential vegetation management needs, strategic planning for vegetation management 

that is linked to monitoring and research outcomes can be a follow-up step. 

356
Monitoring approaches have aimed to collect data in a manner that informs stakeholders of 

the current status of riparian vegetation as well as other elements of the riparian ecosystem 

(Kearsley and others, 2006; Ralston and others, 2008). The response of riparian vegetation to 

dam operations can positively or negatively affect the quality of other resources within the 

riparian zone. For example, available campable area can decline as vegetation cover increases 

(Kearsley and others, 1994), though more recent analysis suggests that since 2002 vegetation 

encroachment in campsite areas appears to be less important when evaluating changes in 

campsite conditions (Hadley, 2014). Additionally, though not well documented in Grand 

Canyon, increasing vegetation on sandbars likely affects sediment transport dynamics and 

aeolian processes thus playing a role in sediment conservation (Trimble 2004, Kean and Smith, 

2004; Dean and others, 2011; Draut and Rubin, 2008). Thus, the status of riparian vegetation and 

its relationship to other resources is a primary information need for the stakeholders to evaluate 

how dam operations are affecting downstream resources. 

This project consists of monitoring and associated research activities relating to the 

measurement of riparian vegetation attributes in response to dam operations to inform multiple 

stakeholder needs. Project 11 incorporates information gained from previous monitoring efforts 

(Stevens and Ayers 1995; Kearsley and Ayers 1995; Kearsley and others, 2006) and 

recommendations from protocol review panels (Urquhart and others, 2000; Cooper and others, 

2008). The primary objectives of this project are to measure variables of plant response (cover, 

species presence, and abundance) as related to the geomorphic setting, elevation, and flow

regime. These variables inform stakeholders about the status of vegetation and support analysis 

of vegetation’s role in the physical and sociocultural responses to dam operations. The proposed 

methods in the Plant-response Guild element also support research related to evaluation of 

alternative flow regimes, including implementation of the High-Flow Experiment Protocol (U.S. 

Department of the Interior, 2011) and other flow regimes that may result from the LTEMP EIS. 

The sampling is hydrologically and geomorphically based, and its annual sampling schedule in 

September and October generally brackets proposed high flow releases, and sampling at the end 

of each growing season provides an assessment of riparian vegetation for each year. Thus, data 

collected by this project contribute to core monitoring, agency actions such as the High-Flow 

Experiment Protocol or other dam operations, and fundamental support for understanding 

riparian plant responses within a regulated river.

C.3. Key Monitoring and Research Questions Addressed in this project 

This project addresses the following Strategic Science Questions (SSQs), Core Monitoring 

Information Needs (CMINs), and Research Information Needs (RINs) and Desire Future 

Conditions (DFC’s) previously identified by the GCDAMP.

Primary SSQs addressed are:

• SSQ 2-1. Do dam-controlled flows affect (increase or decrease) rates of erosion and 

vegetation growth at archaeological sites and TCP sites, and if so, how?

• SSQ 5-7. How do warmer releases affect viability and productivity of native/nonnative 

vegetation?

The primary information needs addressed by these projects are CMINs 6.1.1., 6.2.1, 6.5.1, and 

6.6.1, which are summarized as the following:

357
• Determine and track the abundance, composition, distribution, and area of terrestrial 

native and nonnative vegetation species in the CRe

• Determine parameters and metrics to be measured, and the information needs that address 

each element

• Determine how the abundance, composition, and distribution of the Old High Water 

Zone, New High Water Zone, and sand beach community have changed since dam 

closure (1963), high flows (1984), interim flows (1991), and the implementation of ROD 

operations (RIN 6.2.1, 6.3.1, 6.4.1, 6.5.1, 6.5.2, 6.5.3)

In addition to supporting GCDAMP Goal 6, this project also supports Goals 8, 9, and 11. 

• Goal 8: Maintain or attain levels of sediment storage within the main channel and along 

shorelines to achieve GCDAMP ecosystem goals.

This project supports Goal 8 by collecting vegetation response data associated with sandbars and 

other geomorphic features that physical scientists can use to further understand mechanisms 

affecting sediment storage and transport.

• Goal 9: Maintain or improve the quality of recreational experiences for users of the CRe 

within the framework of GCDAMP ecosystem goals.

This project supports Goal 9 by collecting vegetation response data that may inform researchers 

about how vegetation cover and abundance affects recreational experiences. This has 

implications for both direct vegetation management as well as altering flow regimes to achieve 

specific management goals.

• Goal 11: Preserve, protect, manage, and treat cultural resources for the inspiration and 

benefit of past, present, and future generations.

This project supports Goal 11 by collecting vegetation cover data and an overall species list that may be 

used to inform other researchers about how the quantity of vegetation affects sediment transport and 

cultural site preservation, or how the loss or gain of plant species affect interpretations of ecosystem 

status.

All element of this project also support information related to the Desire Future Conditions 

(Department of Interior, 2012) associated with: Sediment-related Resources, the Riparian 

Domain and the Linkages component - Ecosystem Structure. The research

D. Proposed Work 

D.1. Project Elements 

Project Element 11.1. Ground-based Vegetation Monitoring 

(Recommended for funding FY15: $176,513)

Barbara Ralston, Supervisory Biologist, USGS, GCMRC

Daniel Sarr, Research Ecologist, USGS, GCMRC

Emily Palmquist, Ecologist, USGS, GCMRC

Todd Chaudhry, Restoration Ecologist, NPS, Grand Canyon National Park, 

Dustin W. Perkins, Program Manager, NPS, Northern Colorado Plateau Inventory and 

Monitoring Program 

Work Category: Required monitoring

Objectives 

358
• To annually collect vegetation data (presence, cover) within a geomorphic and hydrologic 

framework downstream of Glen Canyon Dam.

• To use the traits of the plants found to identify plant response-guilds 

• Data and results are collected and described in a manner that can be utilized by multiple 

stakeholders for monitoring approaches used by Tribal stakeholders, and for use in basinwide riparian vegetation monitoring programs overseen by the National Park Service’s 

Northern Colorado Plateau Network Inventory and Monitoring Program 

Hypotheses/Questions

1. Tracking response guild frequency as determined through annual data collection is an 

effective way to monitor directional responses of the riparian community and the river 

channel to dam operations.

Rationale/Justification

River regulation in the semi-arid West creates conditions that support both nonnative and 

native riparian plant species (Stromberg, 1998; Rood and others, 2009). The altered flow regime 

associated with river regulation can promote successful colonization of nonnative species, 

particularly tamarisk (Tamarix spp.) or other colonizing species, on newly exposed bare 

substrates (Sher and others, 2000; Birken and Cooper, 2006; Mortenson and others, 2012). In the 

southwest, the riparian plant community is one in which nonnative tamarisk or Russian olive 

dominates the landscape (Friedman and others, 2005). Consistent monitoring at the local and 

landscape scale, and research that strives to understand the interplay among river regulation, 

riparian vegetation response and the feedback between riparian vegetation development and 

sediment deposition in regulated rivers is critical. Ground-based monitoring provides an 

assessment of annual changes in species occurrences that feeds into the frequency occurrence of 

response-guilds.

Methods

The study area consists of four river segments whose limits are defined by the influence of 

tributaries and by floristic communities (Glen Canyon, Marble Canyon, eastern Grand Canyon, 

western Grand Canyon; fig. 2). The confluences of the Paria and Little Colorado Rivers and 

Kanab Creek with the Colorado River are points that divide the four segments. These river 

segment designations also overlap with suspended sediment sampling stations and work focused 

on sediment budgets that bracket Marble Canyon and eastern Grand Canyon (see Project 2). 

Further, assessing response guilds within short river reaches can help stakeholders identify areas 

that may be more or less responsive to dam operations. Species lists obtained from plot sampling 

(described below) within these river segments can inform park management of areas where 

undesirable species occur in greater abundance and allow a more focused approach to controlling 

these species. 

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Figure 2. Four landscape-scale segment used for stratification (Glen Canyon, Marble Canyon, 

Eastern Grand Canyon, and Western Grand Canyon). The confluences of the Paria, and the 

Little Colorado Rivers, and Kanab Creek with the Colorado River separates the four 

segments.

Ground-based sampling

Sampling is intended to be complementary with the Big River Protocol of the NPS Northern 

Colorado Plateau Network (Scott and others, 2011), which includes fixed sites and randomly 

sampled plots that are matched to geomorphic features (e.g., reattachment bar, separation bar, 

debris fan, channel margins). Sampling downstream from Glen Canyon Dam will follow a 

similar approach. Fixed sites will be coincident with sandbar monitoring sites (Hazel and others, 

2010, see Project Element 3.1) and channel mapping segments (USGS, 2011), see Project 

Element 3.2. Random sites will be stratified and equal numbers of geomorphic features will be 

sampled within river segments. Response guild identification was initiated in 2012 in 

collaboration with D. Merritt using species lists and data collected from 2001-2005 (Kearsley 

and others, 2006) and Stevens and others, (1995) from 1991-1993 and data collected in 2012. 

These guilds continue to being refined as monitoring data are added to the database.

Fixed site sampling 

Sampling sites are coincident with sandbar and channel monitoring sites. Among the 

potential sites that can be sampled (50 sandbars and the river channel data from RM 30 to 87), 

sandbar sites that are most and least responsive to controlled floods, as measured by changes in 

sand volume and area (Hazel and others, 2010; Schmidt and Grams, 2011). Because the 50 sites 

in Project 3 are surveyed and sandbar area and volume calculated, the relationship between 

vegetation plot locations, associated plant response guild (derived from plot samples) and stage 

can be determined. Monitoring vegetation response guilds at sandbars that are measured for 

responses to HFEs and other dam operations can help address physical resource questions about 

causes of variability in sandbar response. Specifically, this co-located data collection effort can 

360
support the monitoring and research questions presented in Project 3 with respect to the role of 

vegetation and the type of vegetation present on a sandbar affecting sandbar response to 

controlled floods. 

Plots at fixed sites will consist of 1-m

2 quadrats that are stratified across geomorphic features 

within a debris fan-eddy complex (sensu Schmidt and Rubin, 1995). The number of quadrats 

sampled will be proportional to the area of each feature. For example, a reattachment bar may be 

half the size of a separation bar and would have 50% fewer plots sampled. Plots will be 

randomly placed within each geomorphic feature. Because the sandbar sites are surveyed 

annually (Project 3), the topographic information can be used to determine river flow necessary 

to inundate plots. The complementary data reduces the time necessary to locate permanent plots 

and obviates the need to monument plots. The vegetation monitoring determines annual changes 

in response guilds to dam operations and informs managers about how these changes may affect 

geomorphic features. Data collected will include cover and species presence. Plot data will also 

provide species richness and diversity and distinguish between native and nonnative species 

(table 2). 

Random site sampling 

The objective of random site sampling is to augment the fixed site sampling. Plot sampling 

here is limited to the area affected by annual dam operations including HFEs. Sampling includes 

an equal number of sandbars, debris fans, and channel margins within each river segment. Onemeter square quadrats are used and data collected will be on species presence and total 

vegetative cover. Selection of random sites occurs prior to the sampling trip to ensure the sites 

are logistically feasible. Quadrats will be located along transects that are perpendicular to the 

channel. Because the locations will be determined prior to launch of the trip, the height above 

river level in relation to the 45,000 ft3

/s stage can be determined using established stage elevation 

relationships and flow routing models (Griffin and Wiele, 1996; Hazel and others, 2006). Having 

the known river discharge for a particular day and time of day can assist in determining distance 

upslope to reach the 45,000 ft3

/s stage. Successive plots along the transect line will be sampled. 

These results will be compared with the fixed sampling site results for an assessment of the river 

segment and total river corridor.

Analysis

Data are collected annually at the end of the growing season (September/October) to capture 

vegetation response to changes in the annual flow regime. These sampling approaches will also 

capture non-flow related interactions (e.g., tamarisk leaf beetle) that affect changes in 

community composition. Data analyses result in descriptive metrics outlined in Table 2 and are 

also used to support response guilds identification. For many of the common species, the 

physiological traits that are related to hydrology (disturbance tolerance, inundation capacity, 

drought tolerance), reproductive mode (seed only, vegetative), growth form, life span and 

salinity tolerance are determined for species encountered, primarily from the PLANTS database 

(www.usda.gov). These traits are used in a classification procedure to statistically determine the 

plant-response guilds (fig. 1). The number of species within each guild and the number of guilds 

may change as more trait information is quantified and added. 

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Table 2. Data collected for all plots and interpretation

Objective Data Inference Goal

Raw Summarized Trend Statistic(s) for 

status

Estimate temporal 

change in riparian and 

wetland plant 

communities

Herbaceous 

spp

Y* x̅% cover/sp; 

p plots/sp

spp richness Y x̅richness

Total 

herbaceous

Y x̅% cover

PI Y x̅index value

Woody spp Y* x̅% cover/sp; 

p plots/sp; x̅

no./m2

Total woody Y x̅% cover; 

p plots; x̅

no./m2

Exotic spp Y* x̅% cover/sp; 

p plots/sp

spp richness Y x̅richness

Total exotics Y x̅% cover; p

plots

Litter Y x̅% cover

Bare ground Y x̅% cover

Timeline

Work and reporting schedule.

FY 15 FY 16 FY 17

Field work September, October August, October August, October

Meeting w/NPS, 

Tribes

February February February

Draft Report May May May

Final Annual Report December December December

Outcomes and Products

• Annual species list provide at annual reporting meeting

• Annual monitoring report describing changes in cover and species occurrence along the 

river corridor. Description of changes in indicator species and changes in frequency of 

vegetation response-guilds. – As an annual report this may be folded into a USGS data 

series report where data are accessible to the public and each year’s data are added to the 

report.

• 1Peer-review journal articles on response-guilds as a monitoring tool for rivers in the 

southwestern United States. One identifying guilds within Grand Canyon and among 

other rivers of the Colorado River Basin. 

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Project Element 11.2. Periodic landscape scale vegetation mapping and analysis using Remotely Sensed Data 

(Recommended for funding FY15: $154,874)

Joel Sankey, Research Geologist, USGS, GCMRC

Laura Cagney, Research Specialist, Northern Arizona University

Barbara Ralston, Supervisory Biologist, USGS, GCMRC

Daniel Sarr, Research Ecologist, USGS, GCMRC 

Work Category: Required monitoring

Objectives

1. To produce an accurate classification of vegetation from the imagery acquired with the 

remote sensing overflight in 2013. 

2. To quantify stability and changes in vegetation composition from the classifications of 

vegetation completed for imagery acquired in 2002 to 2013. 

3. To cross-walk the composition of vegetation in the image-based classes from 2013 and 

2002 with composition of response guilds identified in Element 11.1.

4. To detect and map tamarisk leaf beetle effects for remotely sensed vegetation canopies 

from overflight imagery from 2009 to 2013.

Hypotheses/Questions 

1. What was the composition of riparian vegetation in 2013, and how did it vary spatially 

throughout the CRe? 

The ability to address the first question of this objective is contingent upon successful, 

accurate classification of vegetation based on the 2013 imagery that is as good as or better than 

the classification based on 2002 imagery. The classification will be derived from the high 

resolution (20-cm pixel size) multispectral remote sensing imagery from the May, 2013 

overflight for the entire river corridor of the CRe. This will produce a new and up-to-date 

assessment of the presence, absence, and composition of vegetation in the CRe. (This work will 

be completed by Laura Cagney).

2. How has the vegetation composition in the CRe changed within the approximately 1-

decade period from 2002 to 2013? 

The assessment of change and stability in vegetation composition will span a decade of rivermanagement characterized by reduced powerplant operations and 3 controlled floods, as well as 

the appearance of the tamarisk leaf-beetle (Diorhabda carinulata) in portions of the CRe. 

Importantly, the 2013 classification can also be added to the long term assessment of riparian 

vegetation encroachment for select reaches (Waring, 1995) of total vegetation from 1965 to 2013 

that was successfully completed using data through 2009 in the FY-14–15 workplan. We 

anticipate that changes from 2002 to 2013 will reflect a suite of environmental conditions 

identified by previous work at GCMRC; including recent work completed during the FY 13–14 

workplan. Based on previous work, we hypothesize that (i) temporal stability and changes in 

vegetation classes (composition) will vary by river stage zone, and (ii) compositional changes by 

363
river stage zone will be indicative of effects of regional drought at higher elevations, and river 

hydrology (e.g., flow duration) at lower elevations. Moreover, we know from work completed 

during the FY13–14 workplan that the long-term, post-dam trajectory of increased vegetation 

expansion into increasingly lower elevation zones occurred during the 2002 to 2009 time period 

at elevations well below the maximum of recent controlled floods. Therefore, we will ask 

whether increases and decreases in vegetation at these lower elevations (i.e., inundated during 

operations that include controlled floods between 2002 and 2013) vary by vegetation class 

composition. In particular, we will focus on identifying the range of (and most common) classes 

of vegetation that bare ground (e.g., sand) transitioned to from 2002 to 2013. Finally, we know 

that the tamarisk leaf beetle appeared in portions of the CRe during the time period of our 

vegetation composition change analysis and therefore we will ask whether the spatial variability 

in changes in the abundance of the class containing tamarisk exists and if so, whether it 

correlates to understanding of where the tamarisk leaf-beetle existed pre-2013? (This work will 

be completed by Laura Cagney in collaboration with Joel Sankey).

3. Can the composition of vegetation in the image-based classes from 2013 and 2002 be 

cross-walked with the composition of response guilds identified in Element 11.1 in a 

manner that produces a useful and accurate, landscape-scale assessment of spatial 

variability in response guilds? 

To the extent possible, we will expand on the third question to quantify how the relative 

abundance and spatial variability in the detectable response guild(s) have and have not changed 

during the approximately 1-decade time period. Our ability to detect these changes, if present, 

largely depends on whether the composition of response guilds can be effectively cross-walked. 

(This work will be completed by Joel Sankey in collaboration with Barbara Ralston and Daniel 

Sarr). 

4. Can beetle-impacted stands of tamarisk be detected and successfully mapped by 

independent and combined analysis of 2009 and 2013 imagery in select reaches where 

the leaf beetle are known to have appeared since approximately 2009. Additionally, can 

variability and changes in remotely sensed characteristics of the tamarisk canopies (e.g., 

greenness, cover, leaf area) be detected and attributed quantitatively to the presence of 

the leaf beetle?

This fourth question will focus on specific reaches where the beetle appeared since 2009, 

including (1) Kanab Creek in Grand Canyon, (2) within Glen Canyon, as well as (3) a control 

reach not yet impacted by the leaf beetle. (Completed by NAU M.S. student Ashton Bedford 

with Joel Sankey and Barbara Ralston serving as thesis committee members).

Rationale/Justification

The relative abundance and composition of vegetated and non-vegetated surfaces are factors 

that contribute to the evaluation by stakeholders of goals for physical resources, recreation, 

cultural resources, and riparian communities. In addition to producing a basemap of vegetation 

composition and providing additional data for detection and analysis of stability and change, 

mapping vegetation at the landscape scale can inform stakeholders of the status of several 

364
resources in the CRe that include: effects of riparian vegetation for campsite quality (Kearsley 

and other, 1994; Hadley, unpublished); and effects of riparian vegetation for wildlife habitat 

(Kearsley and others, 2006; Sogge and others, 2003); effects of riparian vegetation on transport 

of sand along the fluvial-aeolian-hillslope continuum, which is important to archaeological site 

preservation (Draut and Rubin, 2008). The development and application of a remote sensing 

image-based methodology that is accurate and provides a synoptic assessment of the CRe has 

been identified as integral to supplementing and corroborating ground-based monitoring data. 

The primary deliverable product is a vegetation classification dataset that can be used in 

multiple disciplines working in the CRe, with additional deliverables focused on salient 

interpretations of variability and change in vegetation composition summarized in written 

report(s) and journal manuscript(s). The dataset will extend from the 8,000 ft3/s to 250,000 ft3/s 

shoreline, starting at River Mile -15 and ending at approximately River Mile 280. The products 

are designed to fulfill stakeholders’ request to, “Determine and track the abundance, 

composition, distribution, and area of terrestrial native and nonnative vegetation species in the 

CRe.” as defined by Core Monitoring Information Needs (CMIN) 6.1.1., 6.6.1., 6.2.1, 6.5.1.

Methods - Preparation of 2013 imagery mosaic and shoreline masks

Before vegetation analysis can begin, the 2013 imagery must be mosaicked from flight lines 

received from the contractor, and broken down into standardized GCMRC Quarter-Quarter-Quad 

boundaries. This process includes the required reflectance value or digital number histogram 

matching. Another critical step before vegetation analysis can begin is to produce a shoreline, 

which also creates the ability to remove known open water pixels from further analysis. 

Depending on the sediment load of the 2013 imagery, this process can be executed using a 

Green/Red band ratio extraction or a principal component analysis approach. The Green/Red 

band ratio extraction compares the values of the green band to the red band. These two 

reflectance values are uniquely different when trying to isolate open terrestrial water and will 

result in a dataset that represents the May 2013 shoreline at a steady 8,000 ft3/s water discharge.

Methods - Total vegetation map

We will produce a total vegetation database and a vegetation class database with at least 6 

vegetation classes for the entire river corridor up to the top of the Old High-Water Zone (at the 

250,000 ft3/s flow stage) using image processing of remotely sensed data. Normalized Difference 

Vegetation Index (NDVI) is a commonly used method to segregate total vegetation in 

multispectral data. A more robust and accurate method is the Spectral Angle Mapper (SAM), 

which was used in mapping with the 2009 imagery and is proposed for use with the 2013 dataset. 

The SAM technique provides the vector angle between the wavelength-band values of an image 

pixel determined to be vegetation. For any pixel, the smaller the vector angle, the more likely the 

image pixel is to contain vegetation. Both sunlit and shadowed vegetation spectra will be used in 

the SAM analysis in order to map all vegetation, even within shadows. If image band data are 

consistent throughout the corridor, then the range of SAM values for vegetation should also be 

consistent, or at least vary systematically throughout the canyon, allowing the vegetation to be 

mapped quickly. The range of SAM values for vegetation will be determined interactively using 

the image result from the SAM output and the corresponding color-infrared image. To determine 

corridor consistence and variability, SAM ranges will be determined every 8 km of the corridor; 

if the derived SAM ranges are consistent or vary systematically, then the observed SAM range 

relation will be used to map the total vegetation throughout the canyon. The results for each of 

the 126 image tiles that cover the river corridor will be examined for accuracy and the SAM 

365
range adjusted when necessary. If the initial SAM ranges at 8 km increments are random, then 

the SAM range for every image tile will be independently determined and applied interactively 

to provide an accurate total vegetation database. 

Methods - Vegetation classification

Once total vegetation is segregated in the 2013 image data set (anticipated by or before 

summer 2016), a most-likely vegetation species will be assigned to each image pixel based on 

reflectance angle. Even though final mapping will probably occur at the response guild or 

association level (categories of classification within the National Vegetation Classification 

Standard (FGDC, 2008)), the spectral band quality of the 2013 imagery are very different in 

terms of dynamic range, consistency, and accuracy and, therefore, the level of the final 

vegetation map for this database will not be known until the species classification is completed. 

Species classification will be accomplished using the following information, in order of 

preference: (1) ground observations that were collected in August and September 2013; (2) 

ground-truth site observations that occurred during other image acquisitions, where it is 

determined by visual examination of the periodic images that certain vegetation is the same in 

the image data being analyzed; and (3) our previously collected ground-reflectance database for 

the common vegetation species within the canyon. Image classification will proceed in 8-km 

increments progressing downstream in the river corridor from Glen Canyon Dam, because 

vegetation composition and the spectral properties of species gradually change downstream. 

Image classification will be based mostly on the image-band signatures and canopy texture of 

representative vegetation species (Davis and others, 2002). Species classification using the 2013 

image data will use a supervised classifier, such as Maximum Likelihood, SAM, or Neural 

Network. We will experiment with various classifiers to determine the classifier that is most 

robust and produces the highest accuracies for most vegetation species. We will use the same 

canopy texture measures that were employed for the 2002 vegetation mapping, although the areal 

dimensions of the spatial tools may change due to the higher spatial resolutions of the 2013 

image data compared to that of the 2002 image data, the most recent vegetation map from 

GCMRC.

Undoubtedly, there will be ambiguities in the final species classifications, because the 

spectral and textural characteristics of some species overlap. We will try to reduce the ambiguity 

using knowledge of dominant species within particular ecotones related to river stages, although 

care will be exercised within the riparian zone not to exclude xeric species. When the species 

classification process reaches the point of diminishing returns, a statistical accuracy assessment 

will be performed on the 2013 results, and a determination will be made as to the aggregation 

levels for their final vegetation databases. We will also incorporate approaches used in Grand 

Canyon National Park’s vegetation-mapping project to develop compatible layers and classes of 

vegetation.

Methods – Objective 2

Total vegetation from 2013 will be used to extend the long-term change analysis conducted 

for the FY13–14 BWP using the GIS and statistical methods previously developed and 

described. Change and stability in vegetation classes from 2002 to 2013 will be summarized by 

stage-elevation zone, and by units of debris fan, channel margin, and eddy areas as represented in 

the canyon-wide geomorphic base map (see Project Element 3.1.2). Relationships of temporal 

variability in vegetation composition by elevation zone and by geomorphic unit will be examined 

relative to variability in flow duration by elevation zone and the expected response to regional 

366
drought from 2002 to 2013. Changes to the abundance and spatial distribution of the class 

containing tamarisk will be examined longitudinally throughout the corridor and tested for 

significant differences between reaches where leaf beetles have been and have not been 

documented.

Methods – Objective 3

The composition of the mapped vegetation classes and response guilds will be compared to 

determine whether any of the response guilds or aggregates of functionally similar guilds can be 

accurately represented by individual or aggregate vegetation classes. If some classes or 

aggregates are successfully identified as potential proxies for response guilds, spatial and 

temporal variability from 2002 to 2013 will be examined using the change detection and 

summary methods described for the secondary objective. 

Methods – Objective 4

Supervised classification methods will be used to map foliated tamarisk within the study 

reaches using 2009 and 2013 imagery. The classifications will potentially incorporate the 4 

multispectral bands from the imagery in addition to NDVI, EVI and leaf area index (LAI). The 

classification will be developed from training pixels in the study reaches that represent foliated 

tamarisk stands. Change analysis of the area mapped as foliated tamarisk in 2009 and 2013 will 

be conducted. Change analysis will also consider relative changes in the indices (NDVI, EVI, 

LAI) for locations where foliated tamarisk was mapped as present in one image date and absent 

in the other, as well as present or absent in both dates. Ground-based point observations of 

known beetle populations (personal communication, Levi Jameson and Charles van Riper, April 

2014, to Ashton Bedford) will be used identify the relationship between changes in presence and 

remotely sensed canopy characteristics of tamarisk stands and beetle populations.

Outcomes and Products

The primary deliverable is the vegetation classification dataset that will extend from the 8,000 

ft3

/s to 250,000 ft3/s shoreline starting at River Mile 15 and end at approximately River Mile 280, 

and that can be used in multiple disciplines working in the CRe. Additional deliverables will be 

USGS professional reports or journal manuscripts that focus on salient interpretations of 

variability and change in vegetation composition, and at least one publication will be produced 

per objective by FY17. 

Project Element 11.3 Influence of sediment and vegetation feedbacks on the evolution of sandbars in Grand 

Canyon since 1991 (FY15-17) 

(Recommended for funding FY15: $100,425)

Daniel Sarr, Research Ecologist, USGS, GCMRC

Paul Grams, Research Hydrologist, USGS, GCMRC

Barbara Ralston, Supervisory Biologist, USGS, GCMRC

Pat Shafroth, Research Ecologist, USGS, Fort Collins

Emily Palmquist, Ecologist, USGS, GCMRC

Joseph E. Hazel, Research Associate, NAU

David M. Merritt, Research Ecologist, U.S. Forest Service

Work Category: High priority research

367
Objectives

To understand the interplay between hydrology, vegetation and sediment dynamics among 20 

sandbars for a 23-year period (1991 to 2013) by using long-term sandbar monitoring data, 

instantaneous discharge record, sediment transport information, intermittent vegetation sampling 

data, riparian plant response guilds, and aerial and oblique repeat photography.

Hypotheses/Questions 

1. How does establishment of vegetation nearer the channel (below stage at power plant 

capacity (31,000 ft3/s) influence sediment deposition on sandbars (net deposition and 

scour) associated with experimental high flows?

2. Does expansion of woody riparian vegetation below stage elevations of power plant 

capacity (31,000 ft3/s) and associated sediment response decrease shoreline complexity 

and negatively affect native fish rearing habitat (backwaters) and riparian habitat 

(compositional and structural complexity)?

3. In a regulated, debris fan-eddy river system does expanded floodplain development on 

reattachment bars result in smaller eddy circulation zones and with reduced temporary 

storage capacity, or do river currents fundamentally change and affect sediment storage 

and transport capacity?

Rationale/Justification

In Grand Canyon, the effect of riparian plants on the physical template of the Colorado River 

corridor is little studied, yet the interaction between vegetation and sediment has implications for 

campsite availability and accessibility, wildlife habitat, and aquatic and shoreline habitats. The 

shoreward expansion of vegetation along the channel is believe to be caused by reduced 

frequency and magnitude of floods, a result of Glen Canyon Dam operations (Turner and 

Karpiscak, 1980; Sankey and others, unpublished). This results in less frequent disturbance of 

sand deposits and longer intervals between floods, facilitating vegetation establishment. Since 

2002, the greatest increase in woody vegetated area is associated with stage elevations less than 

31,000 ft3/s. 

The Experimental High Flow Protocol (Bureau of Reclamation, 2011) will increase the 

frequency of short-duration flood disturbance to the Colorado River with the goal of causing 

cumulative increase in the size of sandbars. How vegetation responds to the increased frequency 

of these short flood pulses, and how vegetation response creates a feedback that affects 

subsequent patterns of sediment deposition is unknown, but could significantly affect the longterm geomorphic response to the high flow protocol. Increased frequency of short-duration 

floods greater than 31,000 ft3/s may limit the expansion of woody vegetation and reverse the 

observed trend of channel narrowing. Conversely, the presence of vegetation may also accelerate 

the rate of sediment deposition on sandbars. The presence of vegetation along channel margins 

increases resistance, reduces water velocities and erosive power, increases bank cohesion, and 

thus affects sediment mobilization, transport, and deposition. This is reflected by the pattern of 

vegetation on sandbars, which is often distributed in clumped or linear arrangements, with the 

densest vegetation associated with the annual flood stage (on the Colorado River in Grand 

Canyon this has been approximately 566 m3

/s since 2000). 

Instead of sediment depositing somewhat uniformly across a sandbar, sediment is predicted 

to accumulate where vegetation reduces water velocity at and around the vegetation associated 

368
with the annual flood stage. This will result in an increase of sandbar elevation near the channel 

(i.e., vegetated levees), but reduced deposition beyond the vegetation boundary. Repeated floods 

of similar or smaller magnitude may have a ratcheting effect where deposition on sandbars 

results in steeper sandbar fronts and channel narrowing. At the same time, vegetation on the 

sandbar may continue to expand and cover the bar’s surface, creating a vegetated floodplain and 

loss or reduction in the size of the eddy boundary. The repeated response may thus limit the 

effectiveness of these pulse flows, and change the channel shape and width. Currently, work is 

under way to test hypotheses about how sandbars stabilized by vegetation affect patterns of 

streamflow and sand deposition in eddies (FY 13–14 Project A.3) using numerical flow models. 

The modeling work, which is expected to provide results in late 2014, will provide more specific 

predictions about how established vegetation will affect depositional patterns. Thus, this 

proposed retrospective analysis of sandbars will complement the work initiated in FY13-14. In 

this project we will exploit the more than 20-years of sandbar monitoring data (1992-2013), 

instantaneous discharge records, intermittent vegetation sampling data, repeat photographs, and 

plant response-guild occurrence probabilities to describe topographic sandbar response, changes 

in eddy boundaries and vegetation expansion among sandbars since 1992. The frequency of 

short-duration high flows, a management action intended to promote sediment conservation, is 

likely to increase in the coming years. Understanding how vegetation responds to this 

management regime and its effect on sediment deposition and transport provides stakeholders 

with critical information that they can use to help meet their goals. 

Methods

This element has two parts A: retrospective analysis of vegetation change among sandbars in 

response to flow regimes (FY15-16). B: linking vegetation change and geomorphology, a proof 

of concept (FY17). 

Approach for Part A: The retrospective analysis uses multiple data sources (Table 3). 

Topographic surfaces from 1991 to 2013 of selected sandbars will be used to compute the 

elevation changes between each survey for transects across sandbars and following controlled 

floods. Using plant-response guilds (based on traits associated with water acquisition and fluvial 

disturbance, but also grouped based on traits that influence hydraulics) and exceedance 

probabilities associated with the instantaneous discharge record for each year, we will make 

occurrence probability maps for plant guilds across the sandbar surfaces for each year. The daily 

repeat photography collected since 1991 (table 3) will be used to verify guild representation. 

Repeat aerial imagery will be used to estimate canopy cover. The intermittent vegetation 

sampling data will also be used to determine guild occurrence relative to predicted guilds and 

support estimated cover values for guilds. This approach will give a time-series of vegetation 

succession based on annual hydrology that is also coupled with observed sandbar morphologic 

change. We propose to do this analysis for 20 sandbars distributed throughout the canyon.

Approach for Part B: The linkage between vegetation change and geomorphology will be 

strengthened with numerical flow modeling. The purpose of the modeling that was initiated in 

the FY13–14 work plan (Element A.3) and is proposed to continue in FY15-17 in Project 3.3 

examines processes by which vegetation-stabilized bar areas affect flow and deposition (see 

preliminary findings (Alvarez and others 2013, and Project 3.3 description). The modeling 

proposed in Element A.3 study will be used to establish relations between the vegetation 

response-guilds and flow parameters such as velocity and shear stress for high flows. Models 

will be developed using roughness values for vegetation obtained in the literature (Manners and 

others, 2014; Griffith and others, 2014) and applied to the guilds. For example, roughness for 

369
tamarisk or willow that co-occur in a guild (Table 1) may be applied for all plants associated in 

the guild. The age of guilds will be determined from the vegetation succession time-series 

process described above. Age of guilds provides a proxy for the stem diameters of vegetation 

within a guild. This information and canopy cover estimates that can be used to estimate stem 

stiffness that influence hydraulics and sediment transport in the water column (Griffith and 

others, 2014; Kean and Smith, 2004). Available velocity profiles and suspended sediment data 

will also be used in this modeling effort (McDonald and Nelson, 1996; Wright and Kaplinski, 

2011). Subsequent year change in sandbar topography can be used to verify expected versus 

observed sediment response. This approach is proposed as a proof of concept for a subset (2-4) 

of the 20 sandbars described in the retrospective analysis for vegetation change beginning in 

FY17. The subset will be distributed upstream and downstream of the Little Colorado River to 

account for tributary effects on sediment inputs related to sandbar response. 

Table 3. Summary of topographic, sediment transport, imagery and vegetation sample data 

available for sandbars

Data type Dates collected Reference

Instantaneous (15 minute 

interval) discharge at Lees Ferry

1921 to present Topping and others, 2003

Sediment transport data 1996, 2000, 2004, 

2008, 2012, 2013

Webb and others, 1999; Schmidt and 

others, 2007; Grams and others, 

2013

High-precision Topographic 

surveys (±0.05m ground point 

precision) 

Annually since 1991 Hazel and others, 2008, Kaplinski 

and others, 2014; 

Stage-discharge relations 1990-2005 Hazel and others, 2007

Oblique Imagery Intermittently since 

1991

USGS, unpublished data

Aerial imagery (orthorectified) 2002, 2009, 2013 Davis, 2013, 2012

Vegetation sample plots 1995, 2001-2005, 

2012-2013

Kearsley and Ayers, 1995; Kearsley 

and others, 2006; USGS unpublished 

data, 2012-13.

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Timeline:

Work and reporting schedule.

FY 15 FY 16 FY 17

1st quarter Part A: Data 

Consolidation, 

Parameter 

Identification,

Initial methodology 

outlined

Application of 

methodology to 

successive bars

Part B: Initiate Proof 

of concept,

Consolidation, 

Parameter 

Identification,

Initial methodology 

outlined

2nd quarter Preliminary analysis 

for 4 sandbars

Results Initial analysis of first 

sandbar

3rd quarter Status Report Draft 

Report/manuscript

Results

4th quarter Methods Report and 

initial results

Manuscript 

submission

Draft 

report/manuscript

Outcomes and Products

• Analysis of 20 bars for vegetation response to changing flow regimes. 

• Report of 20 sandbars retrospective analyses FY16

• American Geophysical Union presentation FY16

• Manuscripts FY16 – Methods for using response guilds to understand multi-year 

vegetation response to river regulation: Vegetation assembly rules along a regulated river.

• Draft manuscript FY17 - Twenty-year reconstructive geomorphic history and vegetatitive

evolution for 2 sandbars in Grand Canyon. 

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Project Element 11.4 Linking dam operations to changes in riparian biodiversity – the potential significance of 

vegetation change and insect emergence 

(Recommended for funding FY15: $44,631)

Charles B. Yackulic, Research Statistician, USGS, GCMRC

John Spence, Resource Manager, National Park Service, Glen Canyon National Recreation Area

Jeff Muehlbauer, Aquatic Ecologist, USGS, GCMRC

Charles Drost, Research Wildlife Biologist, USGS, SBSC 

Barbara Ralston, Supervisory Ecologist, USGS, GCMRC 

Theodore Kennedy, Research Aquatic Ecologist, USGS, GCMRC

Daniel A. Sarr, Research Ecologist, USGS, GCMRC 

Emily Palmquist, Ecologist, USGS, GCMRC

Work Category: High priority research

Objectives

1. Build a strong conceptual basis for understanding and analyzing linkages between flow 

management and riparian biodiversity in the Colorado River ecosystem

2. Determine the degree to which populations of terrestrial animals respond to spatial and 

temporal variation in aquatic insect emergence along the Colorado River, with an initial 

focus on the Glen and upper Marble Canyons.

3. Identify whether long-term changes in vegetation have influenced populations of 

terrestrial consumers, particularly birds and terrestrial insects inGlen Canyon. 

4. To the extent possible, determine the links between terrestrial fauna and vegetation-flow 

response guilds.

Hypotheses/Questions

1. Can we identify and compare quantitative linkages between ongoing vegetation and 

aquatic and geomorphic monitoring and targeted riparian wildlife assemblages in the 

Colorado River ecosystem?

2. Can we detect long and/or short-term trends in avian populations by combining historical 

and newly collected data in an occupancy modeling framework? Are short-term trends 

for insectivores linked to changes in annual aquatic production?

3. To what degree does swallow and bat activity track spatial and temporal patterns in insect 

emergence from the Colorado River? Can their activity serve as a continuous noninvasive 

index of insect emergence?

4. How have terrestrial arthropod communities responded to relatively recent changes in 

dam operations, including increased frequency of HFEs (which may remove litter within 

the inundated area); how have communities changed in response to increasing impacts of 

tamarisk beetle?

5. How are aquatic-terrestrial subsidies structured spatially and do spiders distribute 

themselves to take advantage of these subsidies? What proportion of spider consumption 

is based on terrestrial versus aquatic sources?

Rationale/Justification

Riparian environments comprise critical habitat for terrestrial fauna along the Colorado River 

corridor (Carothers and Brown, 1991; Kearsley and others, 2006; Ralston, 2005), yet the 

372
mechanisms that link flow management with riparian biodiversity are poorly understood. A 

focused effort to expand our knowledge of the pathways linking flow with biodiversity, and their 

relative strength, is a valuable step forward in our efforts to understand and conserve the 

Colorado River ecosystem.

Terrestrial fauna of the Colorado River may be affected by flow management from Glen 

Canyon Dam via two fundamentally different pathways: 1) changes in the availability of 

emergent insect prey from the Colorado River and 2) the density and composition of the riparian 

vegetation that provides habitat for many of these animals. Although the structure of riparian 

food webs and animal populations has been conceptually sketched (e.g. Suttkus and others, 1976, 

Spence 2004, Yard and others, 2004, Kearsley and others, 2006), trends in the structure of these 

food webs, and riparian food web response to changes in aquatic food webs, are poorly known. 

Moreover, we do not yet know the relative strengths of trophic-driven effects of emergent insects 

in comparison to the effects of vegetation structure and composition. We will employ the method 

of multiple working hypotheses to (Chamberlin 1965) to explore the relative strength of the two 

causal pathways.

Emergent insects—The emergence of adult insects from aquatic ecosystems (i.e., streams, rivers, 

lakes) represents a key source of energy and nutrients that supports terrestrial food webs and 

consumers including birds, bats, lizards, toads, frogs, and spiders (Nakano and Murakami 2001, 

Sabo and Power 2002, Baxter and others, 2005). The availability of adult life stages of aquatic 

insects as prey can be critical to supporting the stability and biodiversity of riparian food webs 

(Nakano and Murakami 2001, Sabo and Power 2002, Baxter and others, 2005). The aquatic 

invertebrate assemblage of the Colorado River in Glen, Marble, and Grand Canyons contains 

only two common groups: midges and blackflies (Diptera: Chironomidae and Simuliidae), with 

midges being particularly abundant (Cross and others, 2013). Research has demonstrated that 

inter-annual differences in flow management (e.g., spring HFE’s, occasional large volume 

releases associated with equalization) can drive increases in the production of midges and 

blackflies (Cross and others, 2013, Kennedy unpublished data). It is well established that 

rainbow trout (Oncorhyncus mykiss) populations, which are studied and monitored closely, have 

responded strongly to these inter-annual changes in aquatic insect productivity (Cross and others, 

2011; Korman and others, 2011; Korman and others, 2012). Previous work in Grand Canyon has 

demonstrated that emergent insects, particularly midges, are a key prey item for several bird 

species (Yard and others, 2004). Thus, occasional pulses of aquatic insects associated with 

infrequent flow events may also lead to increases in the populations of terrestrial animals that 

also prey on emerging insects (i.e., bats, some bird species, spiders), but this has never been 

evaluated. 

In addition to tracking temporal variation in emergent insects, terrestrial animals may also be 

tracking spatial variation in emergent insect availability. Within river reaches, terrestrial fauna 

that rely on aquatic subsidies are expected to be more common at sites near to aquatic production 

hotspots (e.g., riffles), whereas other factors may affect the amount of insect emergence across 

reaches. Specifically, citizen science monitoring indicates emergent insect availability is greatest 

in parts of Lower Marble Canyon (RM 30-50) and the Muav Gorge (RM 140-160), and lowest in 

Furnace Flat and Upper Granite Gorge (RM 60-90) and Glen Canyon (RM -15 to 0) (Kennedy 

and others, unpublished data). 

Riparian vegetation— Habitat availability likely acts a primary filter determining which 

terrestrial fauna are found locally. As vegetation communities of the Colorado River riparian 

zones expand and contract in response to changes in flow management and other perturbations 

373
(e.g., Tamarix beetle invasion), the density and composition of terrestrial animals will likely 

respond in kind. Changes in animal populations that are mediated by riparian vegetation will 

occur over long time scales (i.e., many years to decades), while changes in animal populations 

that are mediated by emergent insect prey will occur over shorter time scales (i.e., seasonally to 

annually). Understanding the relative importance of these factors, as well as association between 

terrestrial fauna and vegetation-flow response guilds will help create a better understanding of 

how terrestrial fauna will respond to future dam operations.

Choices of study organisms are driven by many factors. Bats and certain bird species (e.g., 

swallows) can be monitored relatively cheaply using either remote technology or citizen 

scientists, and rely heavily on aquatic insects emerging from the river (are thus are most likely to 

respond to spatio-temporal variation in the amount of emergence). Birds and terrestrial 

arthropods have been well studied in the past, particularly in Glen and Upper Marble Canyons, 

providing reference conditions to quantify long-term population changes. Within these two 

groups, we hypothesize that certain species (e.g., yellow warblers and spiders) may be more 

closely linked to the aquatic ecosystem than other species.

Methods

This project is intended to be implemented in two phases, starting with analysis, synthesis, 

and conceptual model development in FY 2015 , and followed by targeted research projects that 

will test the aquatic and terrestrial pathways in FY 2016 and 2017. This project element will 

summarize and synthesize current understanding of linkages between flow and riparian 

biodiversity, and utilize information and insights gained from past work. Specifically, it 

emphasizes the vegetation response-guild work and insect emergence monitoring conducted in 

FY13–14. It will also include some analysis of historic data, particularly breeding bird data 

collected in the 1990s in Glen Canyon and studies of terrestrial arthropod communities ~5 years 

ago. This project will also involve field work to collect new data. Broad tasks for this project 

follow.

1. Task 1 (FY 2015): Develop a concept paper summarizing and articulating hypothesized 

linkages between flow variables and riparian biodiversity in Grand Canyon. Specifically, 

the paper will evaluate existing data and information about aquatic and terrestrial 

pathways. This paper will also articulate a riparian research agenda for testing such 

hypothesized linkages in an adaptive management context, which will guide subsequent 

fields studies.

2. Task 2 (FY 2015): Hold a scoping workshop with project principals and other scientists 

to decide upon the appropriate consumer taxa and field sampling locations for target 

studies.

3. Task 3 (FY 2016-17): Work with a graduate student to prepare field study in Glen 

Canyon todevelop and test methods for quantifying the abundance and distribution of 

targeted riparian consumers (swallow,bat species, and test whether feeding 

concentrations are closely linked to patterns of emergence, as we hypothesize. Possible 

approaches include cost-effective remote automated cameras positioned to capture hourly 

pictures of swallows and fixed acoustic recorders for quantifying bat activity and species 

composition. Additionally, we will also develop standardized techniques for 

quantification of swallow abundance and bat activity that can be used throughout Grand 

Canyon by citizen scientists.

4. Task 4 (FY 2016-17: Develop project toinvestigate changes in the abundance and 

374
distribution of breeding bird populations in Glen Canyon using sampling methods and 

fixed locations previously surveyed by John Spence (National Park Service) in the 1990s, 

and reanalyze both the historic and new data using occupancy methodswith respect to 

changes in riparian vegetation structure and guild composition using FY 2013-14 

monitoring data, and if feasible, with respect to FY 2013-14 patterns of aquatic insect 

emergence.

Outcomes and Products

• Deliverable 1: Manuscript describing hypothesized linkages between flow management 

and riparian biodiversity in the Colorado River ecosystem. Draft FY15

• Deliverable 2: Workshop report summarizing existing datasets, highest priority consumer 

taxa to sample, and specific sampling recommendations. FY15

• Deliverable 3: Manuscript describing the relationship between aquatic emergence and 

consumer abundance in a temporal and spatial context. FY17 

• Deliverable 4: Manuscript linking bird occurrence and changes in riparian vegetation 

structure and composition for a 20-year time period at Glen Canyon National Recreation 

Area. FY17

• Deliverable 5: Annual list of taxa recorded during the duration of the field projects FY16, 

FY17

Project Element 11.5. Science Review Panel of Successes and Challenges in Non-native Vegetation Control in 

the Colorado River and Rio Grande Watersheds 

(Recommended for funding FY15: $33,577)

Daniel Sarr, Research Ecologist, USGS, GCMRC

Barbara Ralston, Supervisory Biologist, USGS, GCMRC

Work Category: Research

Objectives 

To convene a science expert review panel composed of natural resource managers and 

riverine research scientists to examine successes and challenges in non-native vegetation control 

in the Colorado River and Rio Grande watersheds, and to seek recommendations from that group 

as to how to plan a scientifically-based riparian management control program applicable to the 

Colorado River ecosystem in Glen, Marble and Grand Canyons.

Rationale/Justification

Native and nonnative woody riparian vegetation expansion is linked to Glen Canyon Dam 

operations (Turner and Karpiscak, 1980; Mortenson and others, 2011), but removal of woody 

vegetation through repeated flooding in association with the Experimental High Flow Protocol 

may have limited success. To achieve desired future conditions for riparian vegetation as 

outlined by stakeholder of the GCDAMP (Castle memo, 2012), removal of nonnative species 

and planting of native vegetation with approaches that incorporate future flow regimes may be 

required. For example, experimental plant removal and plant actions may focus on tamarisk 

since tamarisk beetle defoliation has occurred along segments of the Colorado River since 2009 

(see Project Element 11.2).

375
Revegetation efforts are often costly and many times the success is unquantifiable. One 

reason for a lack of quantifiable success is that the project objectives are too vague (Shafroth and 

others, 2008). Specific measureable objectives help to define the approach for prioritizing sites 

and the methodology for vegetation removal regardless of the nonnative or native status of the 

target species. Additionally, incorporating a review of previous riparian restoration projects 

within the Southwest (Green River in Canyonlands, the Yampa River in Dinosaur National Park, 

and the Rio Grande River in Big Bend National Park) can identify approaches that may be most 

successful in identifying expected outcomes, and in estimating costs for project initiation and 

subsequent monitoring and maintenance. Element 11.1.5 proposes a science panel review to 

examine successes and challenges in non-native vegetation control in the Colorado River and 

Rio Grande watersheds and to seek recommendations from that group as to how to plan a 

scientifically-based riparian management control program applicable to the Colorado River 

ecosystem in Glen, Marble and Grand Canyons.

Methods

In FY15, convene a review panel –2-day workshop. Panel participants will include:

• Representatives from National Park Units (GRCA, GCNRA, CANY, DINO, BIBE), the 

BLM with hands-on experience in nonnative plant control in riparian habitats on 

regulated rivers

• Riparian ecologists and geomorphologists involved in nonnative species control and 

environmental flows research.

Use case studies from park units, BLM, or tribal land units to describe results (positive/negative) 

and recommendations for future planning related to riparian management. 

GCMRC organizers will work with presenters prior to the review panel to develop a summary 

document that can be used to plan science-based management and monitoring for nonnative 

control for the Colorado River ecosystem.

Questions that will drive the discussion and case study narratives

1. What were nonnative control objectives and what were the methods used for control 

(poison, mechanical removal, etc)? 

2. Which effort resulted in greater or less desirable outcomes? (Was there subsequent 

extensive weed control that was required and greater manpower needed than anticipated 

for success). 

3. What were the criteria used for each site (logistics only? extent of tamarisk cover?) and 

were there other considerations that should be included in future site selection?

4. How did hydrologic and geomorphic controls influence or inform site location or 

approaches for nonnative removal or revegetation?

5. How was success assessed? What monitoring occurred prior to and following 

removal/restoration actions?

376
6. What should all resource managers consider prior to and following initiation of riparian 

management control efforts?

One outcome of this panel would be the decision to proceed with development of a multiagency planning program (in FY16) wherein BoR, GCNP, and GCMRC would work together to 

develop a science-based program to plan where vegetation control along the Colorado River 

ought to occur, the methods to be used in removal, and the methods to be used in monitoring 

success/or challenges.

Timeline:Work and reporting schedule.

FY 15 FY 16 FY 17

1st quarter Identify Review Panel 

participants, specific 

questions for each 

case study and format 

for case study 

document

TBD – Potentially 

Planning program for 

experimental 

vegetation control

2nd quarter Convene Review 

Panel (February)

Status Report

3rd quarter Draft Case Study 

Report

4th quarter Final Document

Outcomes and Products

• A journal article that summarizes Case Studies of Nonnative Riparian Vegetation Control 

within the Colorado and Rio Grande Watersheds. 

D.2. Personnel and Collaborations 

Personnel from GCMRC include riparian ecologists, aquatic ecologists and wildlife 

ecologists. Collaborators include individuals from the National Park Service, other USGS 

Science Centers, the U.S. Forest Service, Northern Arizona University, and masters students 

affiliated with Arizona State University and Northern Arizona University. 

D.3. Deliverables 

See “Outcomes and Products” listed by project element, above.

E. Productivity from Past Work (during FY 13–14) 

E.1. Data Products 

Field data sheets entered from 2012 and 2013.

Traits database initiated and being populated

Guilds identified – Draft manuscript completed Fall 2014, to be submitted Jan 2015

E.2. Completed Publications 

377
Ralston, B.E., Starfield, A.M., Black, R.S., and Van Lonkhuyzen, R.A., 2014, State-andtransition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona: 

U.S. Geological Survey Open-File Report 2014-1095, 26 

p., http://dx.doi.org/10.3133/ofr20141095.

E.3. Publications in progress 

Sankey, J.B., Ralston, B.E., Grams, P.E., Schmidt, J.C. and Cagney, L.E. Colorado River, 

vegetation, and climate: five decades of spatio-temporal dynamics in the Grand Canyon with 

regulation – to be submitted this summer.

Vegetation monitoring report 2012-2013 in development –Draft to be completed Summer 2014 –

Ralston is lead author.

Riparian vegetation response-guilds downstream of Glen Canyon Dam: a tool for monitoring and 

evaluating flow needs for vegetation. – Preliminary guilds identified, draft manuscript 

completed by December 2014. Sarr is lead author.

E.4. Presentations at GCDAMP meetings 

Sankey, J.B., and Ralston, B.E. Changes in riparian vegetation in the Colorado River Corridor, 

1965-present. Glen Canyon Dam Adaptive Management Working Group Meeting August 

2013.

E.5. Presentations at professional meetings 

Sankey, J.B., and Ralston, B.E., Colorado River, Vegetation, and Climate: Five Decades of 

Spatio-Temporal Dynamics in the Grand Canyon in Response to River Regulation. Colorado 

Plateau Biennial Conference, Flagstaff, AZ, September 2013.

Ralston, B.E., and Sankey, J.B., EP43C-0860. Colorado River, Vegetation, and Climate: Five 

Decades of Spatio-Temporal Dynamics in the Grand Canyon in Response to River 

Regulation. American Geophysical Union, Fall Meeting, San Francisco, CA, December 

2013.

F. References 

Auble, G., and Scott, M., 1998, Fluvial disturbance patches and cottonwood recruitment along 

the upper Missouri River, Montana: Wetlands, v. 18, no. 4, doi: 10.1007/bf03161671, p. 

546-556, http://dx.doi.org/10.1007/BF03161671.

Auble, G., Scott, M., and Friedman, J., 2005, Use of individualistic streamflow-vegetation 

relations along the Fremont River, Utah, USA to assess impacts of flow alteration on 

wetland and riparian areas: Wetlands, v. 25, no. 1, doi: 10.1672/0277-

5212(2005)025[0143:uoisra]2.0.co;2, p. 143-154.

Baxter, C. V., K. D. Fausch, and W. C. Saunders. 2005. Tangled webs--reciprocal flows of 

invertebrate prey link streams and riparian zones. Freshwater Biology 50:201–220.

Birkin, A.S., and Cooper, D.J., 2006, Processes of Tamarix invasion and floodplain development 

along the Lower Green River, Utah: Ecological Applications, v. 16, no. 3, p. 1103-1120, 

accessed on March 8, 2011, at http://dx.doi.org/10.1890/1051-

0761(2006)016[1103:POTIAF]2.0.CO;2.

Brown, B. T., and M.W. Trosset. 1989. “Nesting-Habitat Relationships of Riparian Birds along 

the Colorado River in Grand Canyon, Arizona.” The Southwestern Naturalist 34 (2): 260. 

doi:10.2307/3671736.

378
Bureau of Reclamation, 2011, Environmental assessment--development and implementation of a 

protocol for high-flow experimental releases from Glen Canyon Dam, Arizona, 2011 

through 2020: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado Region, 176 p. 

+ appendices, http://www.usbr.gov/uc/envdocs/ea/gc/HFEProtocol/HFE-EA.pdf.

Carothers, S.W., and Brown, B.T., 1991, The Colorado River through Grand Canyon--natural 

history and human change: Tucson, University of Arizona Press, 235 p.

Cooper, D.J., Battaglia, L., Batzer, D., Chong, G.K., Hudak, A., and Young, M., 2008, Review 

of terrestrial monitoring protocols for the Grand Canyon--report of the Protocol Evaluation 

Panel (PEP): submitted to U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center, 31 p.

Corenblit, D., Gurnell, A.M., Steiger, J. and Tabacchi, E., 2008, Reciprocal adjustments between 

landorms and living organisms: Extended geomorphic evolutionary insights: Catena. 

73:261-273. 

Cross, W. F., C. V. Baxter, K. C. Donner, E. J. Rosi-Marshall, T. A. Kennedy, R. O. Hall, Jr., H. A. 

Wellard-Kelly, and R. S. Rogers. 2011. Ecosystem ecology meets adaptive management--food web 

response to a controlled flood on the Colorado River, Glen Canyon. Ecological Applications 

21:2016-2033.

Cross, W. F., C. V. Baxter, E. J. Rosi-Marshall, R. O. Hall, Jr., T. A. Kennedy, K. C. Donner, H. A. 

Wellard Kelly, S. E. Z. Seegert, K. Behn, and M. D. Yard. 2013. Foodweb dynamics in a large river 

discontinuum. Ecological Monographs 83:311-337.

Davis, P.A., Staid, M.I., Plescia, J.B. Johnson, J.R., 2002, Evaluation of airborne image data for 

mapping riparian vegetation within the Grand Canyon, U.S. Geological Survey Open-File 

Report: 2002-470, 65p.

Dean, D.J., Scott, M.L., Shafroth, P.B., and Schmidt, J.C., 2011, Stratigraphic, sedimentologic, 

and dendrogeomorphic analyses of rapid floodplain formation along the Rio Grande in Big 

Bend National Park, Texas: Geological Society of America Bulletin, v. 123, no. 9-10, doi: 

Doi 10.1130/B30379.1, p. 1908-1925, <Go to ISI>://000293286100015.

Draut, A.E., and Rubin, D.M., 2008, The role of aeolian sediment in the preservation of 

archaeological sites, Colorado River corridor, Grand Canyon, Arizona, in van Riper, C., III, 

and Sogge, M.K., eds., The Colorado Plateau III--integrating research and resource 

management for more effective conservation: Tucson, University of Arizona Press, ISBN: 

0816527385, p. 331-350.

Durst, S.L., Theimer, T.C., Paxton, E.H., and Sogge, M.K., 2008, Age, Habitat, and Yearly 

Variation in the Diet of a Generalist Insectivore, the Southwestern Willow Flycatcher: 

Condor, v. 110, no. 3, doi: DOI 10.1525/cond.2008.8493, p. 514-525, <Go to 

ISI>://000260732000012.

Griffin, E.R., and Wiele, S.M., 1996, Calculated hydrographs for unsteady research flows at 

selected sites along the Colorado River downstream from Glen Canyon Dam, Arizona, 1990 

and 1991: U.S. Geological Survey Water Resources Investigations Report 95-4266, 30 p., 

http://pubs.usgs.gov/wri/1995/4266/report.pdf.

Grime, J.P., 1979, Plant Strategies and Vegetation Processes: John Wiley & Sons, Chichester. 

Hazel, J.E., Jr., Grams, P.E., Schmidt, J.C., and Kaplinski, M., 2010, Sandbar response in Marble 

and Grand Canyons, Arizona, following the 2008 high-flow experiment on the Colorado 

River: U.S. Geological Survey Scientific Investigations Report 2010-5015, 52 p., accessed on 

July 27, 2010, at http://pubs.usgs.gov/sir/2010/5015/.

Hazel, J.E., Jr., Kaplinski, M., Parnell, R., Kohl, K., and Topping, D.J., 2006, Stage-discharge 

relations for the Colorado River in Glen, Marble, and Grand Canyons, Arizona,1990-2005: 

379
U.S. Geological Survey Open-File Report 2006-1243, 7 p., accessed on January 11, 2010, at 

http://pubs.usgs.gov/of/2006/1243/pdf/of06-1243_508.pdf.

Hazel JE, Jr., Kaplinski M, Parnell R, Manone M, Dale A. 1999. Topographic and bathymetric 

changes at thirty-three long-term study sites. In The controlled flood in Grand Canyon, 

Webb RH, Schmidt JC, Marzolf GR, Valdez RA (eds). American Geophysical Union, 

Geophysical Monograph Series, v. 110, Washington, D.C.; 161-183.

Kaplinski, M., Behan, J., Hazel, J.E., Parnell, R.A., and Fairley, H.C., 2005, Recreational values 

and campsites in the Colorado River ecosystem, in Gloss, S.P., Lovich, J.E., and Melis, 

T.S., eds., The state of the Colorado River ecosystem in Grand Canyon--a report of the 

Grand Canyon Monitoring and Research Center 1991-2004: U.S. Geological Survey 

Circular 1282, 193-205 p., http://pubs.usgs.gov/circ/1282/.

Kaplinski, M.A., Hazel, J.E., Grams, P.E., and Davis, P.A., 2014, Monitoring fine-sediment 

volume in the Colorado River ecosystem, Arizona--Construction and analysis of digital 

elevation models: U.S. Geological Survey Open-File Report 2014–1052, 29 p., 

http://dx.doi.org/10.3133/ofr20141052.

Kean, JW, and Smith, JD, 2004. Flow and boundary shear stress in channels with woody bank 

vegetation. In Riparian vegetation and fluvial geomorphology, Bennett SJ, Simon A (eds). 

American Geophysical Union, Water Science and Application, v. 8, Washington, D.C.; 237-

252.

Kearsley, L.H., Schmidt, J.C., and Warren, K.D., 1994, Effects of Glen Canyon Dam on 

Colorado River sand deposits used as campsites in Grand Canyon National Park, USA: 

Regulated Rivers--Research and Management, v. 9, no. 3, p. 137-149, accessed on 

December 30, 2009, at http://www3.interscience.wiley.com/cgibin/fulltext/113512382/PDFSTART.

Kearsley, M.J.C., Cobb, N.S., Yard, H.K., Lightfoot, D.C., Brantley, S.L., Carpenter, G.C., and 

Frey, J.K., 2006, Inventory and monitoring of terrestrial riparian resources in the Colorado 

River corridor of Grand Canyon--an integrative approach--final report: Flagstaff, Northern 

Arizona University, submitted to U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center, cooperative agreement no. 01-WRAG-0044 (NAU) and 01-WARG-0034 

(HYC), 262 p.

Korman, J., M. Kaplinski, and T. S. Melis. 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 140:487-505.

Korman, J., S. J. D. Martell, C. J. Walters, A. S. Makinster, L. G. Coggins, M. D. Yard, and W. 

R. Persons. 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 69:1827-1849.

Lavorel S., Garnier E., 2002, Predicting changes in community composition and ecosystem 

functioning from plant traits: revisiting the Holy Grail: Functional Ecology, v. 16, p. 545-

556. DOI: 10.1046/j.1365-2435.2002.00664.x.

Mahoney J, Rood S. 1998. Streamflow requirements for cottonwood seedling recruitment—An 

integrative model. Wetlands 18, 634-645. DOI: 10.1007/bf03161678.

Manners, R.B., Schmidt, J.C., and Scott, M.L., 2014, Mechanisms of vegetation-induced channel 

narrowing of an unregulated canyon river: Results from a natural field-scale experiment. 

Geomorphology. 211:100-115.

380
Mccluney, K.E., and Sabo, J.L., 2012, River drying lowers the diversity and alters the 

composition of an assemblage of desert riparian arthropods: Freshwater Biology, v. 57, no. 

1, doi: DOI 10.1111/j.1365-2427.2011.02698.x, p. 91-103,

Merritt, D.M., Scott, M.L., Poff, N.L., Auble, G.T., and Lytle, D.A., 2010, Theory, methods and 

tools for determining environmental flows for riparian vegetation--riparian vegetation-flow 

response guilds: Freshwater Biology, v. 55, no. 1, doi: 10.1111/j.1365-2427.2009.02206.x, 

p. 206-225, accessed on October 18, 2010, at 

http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2427.2009.02206.x/full.

Merritt, D. M., and N. L. Poff. 2010. Shifting dominance of riparian Populus and Tamarix along 

gradients of flow alteration in western North American rivers. Ecological Applications 

20:135-152.

Mortenson, S., Weisberg, P., and Stevens, L., 2012, The influence of floods and precipitation on 

Tamarix establishment in Grand Canyon, Arizona: consequences for flow regime 

restoration: Biological Invasions, v. 14, no. 5, doi: 10.1007/s10530-011-0139-z, p. 1061-

1076, http://dx.doi.org/10.1007/s10530-011-0139-z.

Nakano, S. and M. Murakami. 2001. Reciprocal subsidies: dynamic interdependence between 

terrestrial and aquatic food webs. Proceedings of the National Academy of Sciences 

98:166–170.

Naiman, R.J., Decamps, H., and McClain, M.E., 2005, Riparia--ecology, conservation, and 

management of streamside communities: Oxford, Elsevier Academic Press, 430 p.

Osterkamp, W.R., Hupp, C.R., 2010, Fluvial processes and vegetation – Glimpses of the past, the 

present and perhaps the future, Geomorphology. 116: 274-285.

Ralston, B.E. 2005. Chapter 6 Riparian Vegetation and Associated Wildlife. In State of the 

Colorado River Ecosystem in Grand Canyon, edited by Steven P. Gloss, Jeffrey Lovich, and 

Theodore Melis, 103–22.

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., accessed on January 12, 2010, at http://pubs.usgs.gov/of/2008/1216/.

Ralston, B.E., Starfield, A.M., Black, R.S., and Van Lonkhuyzen, R.A., 2014, State-andtransition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona: 

U.S. Geological Survey Open-File Report 2014-1095, 26 

p., http://dx.doi.org/10.3133/ofr20141095.

Rood, S.B., Braatne, J.H., and Goater, L.A., 2009, Responses of obligate versus facultative 

riparian shrubs following river damming: River Research and Applications, v. 26, no. 2, doi: 

10.1002/rra.1246, p. 102-117, accessed on June 6, 2011, at 

http://onlinelibrary.wiley.com/doi/10.1002/rra.1246/abstract.

Sabo, J. L. and M. E. Power. 2002. River-watershed exchange: effects of riverine subsidies on riparian 

lizards and their terrestrial prey. Ecology 83:1860–1869.

Scott, M.L., Perkins, D, Wheaton, J.M., 2011, Big River Protocol Development – A Prototype 

Warranty Project: Final Report submitted to USGS Park Inventory and Monitoring Program. 

68 p.

Shafroth, P.B., Beauchamp, V.B., Briggs, M.K., Lair, K., Scott, M.L., and Sher, A.A., 2008, 

Planning riparian restoration in the context of Tamarix control in western North America: 

Restoration Ecology, v. 16, no. 1, doi: DOI 10.1111/j.1526-100X.2008.00360.x, p. 97-112.

Sher, A.A., Marshall, D.L., and Gilbert, S.A., 2000, Competition between native Populus 

deltoides and invasive Tamarix ramosissima and the implications for reestablishing flooding 

381
disturbance: Society of Conservation Biology, v. 14, no. 6, p. 1744-1754, accessed on 

January 12, 2010, at http://www.jstor.org/stable/2641526.

Sogge, M.K., Sferra, S.J., McCarthey, T.D., Williams, S.O., and Kus, B.E., 2003, Distribution 

and characteristics of southwestern willow flycatcher breeding sites and territories: 1993-

2001: Studies in Avian Biology, v. 26, p. 5-11 

Spence, J. R. 2004. The riparian and aquatic bird communities along the Colorado River from 

Glen Canyon Dam to Lake Mead, 1996-2000. Final Report to Grand Canyon Monitoring 

and Research Center.

Stevens, L.E., and Waring, G.L., 1986, Effects of post-dam flooding on riparian substrates, 

vegetation, and invertebrate populations in the Colorado River corridor in Grand Canyon, 

Arizona: Flagstaff, Ariz., Bureau of Reclamation, Glen Canyon Environmental Studies, 

contract no. IA4-AA-40-01930, GCES 19/87, 175 p. [Available from National Technical 

Information Service, Springfield, Va. as NTIS Report PB88-183488.]

Stevens, L.E., Schmidt, J.C., Ayers, T.J., and Brown, B.T., 1995, Flow regulation, 

geomorphology, and Colorado River marsh development in the Grand Canyon, Arizona: 

Ecological Applications, v. 5, no. 4, p. 1025-1039, accessed on December 10, 2009, at 

http://www.jstor.org/stable/pdfplus/2269352.pdf.

Stevens, L. E., J. P. Shannon, and D. W. Blinn. 1997. Colorado River benthic ecology in Grand 

Canyon, Arizona, USA--dam, tributary, and geomorphological influences. Regulated Rivers-

-Research and Management 13:129-149.

Stromberg, J., 1998, Dynamics of Fremont cottonwood (Populus fremontii) and salt cedar 

(Tamarix chinensis) populations along the San Pedro River, Arizona: Journal of Arid 

Environments, v. 40, no. 2, p. 133-155, accessed on August 23, 2011, at 

http://dx.doi.org/10.1006/jare.1998.0438.

Stromberg, J.C., 2001, Restoration of riparian vegetation in the south-western United States: 

importance of flow regimes and fluvial dynamism: Journal of Arid Environments, v. 49, no. 

1, doi: http://dx.doi.org/10.1006/jare.2001.0833, p. 17-34

Stromberg, J. C., S. J. Lite, R. Marler, C. Paradzick, P. B. Shafroth, D. Shorrock, J. M. White, 

and M. S. White. 2007. Altered stream-flow regimes and invasive plant species: the Tamarix 

case. Global Ecology and Biogeography 16:381-393.Trimble, SW, 2004. Effects of riparian 

vegetation on stream channel stability and sediment budgets. In Riparian vegetation and 

fluvial geomorphology, Bennett SJ, Simon A (eds). American Geophysical Union, Water 

Science and Application, v. 8, Washington, D.C.; 153-170. 

Suttkus, R. D., G. H. Clemmer, C. Jones, and C. R. Shoop. 1976. Survey of fishes, mammals and 

herpetofauna of the Colorado River in Grand Canyon. Colorado River Research Program 

Final Report, Technical Report no. 5.

Turner, R.M., and Karpiscak, M.M., 1980, Recent vegetation changes along the Colorado River 

between Glen Canyon Dam and Lake Mead, Arizona: U.S. Geological Survey Professional 

Paper 1132, 125 p.

Urquhart, N.S., Auble, G.T., Blake, J.G., Bolger, D.T., Gerrodette, T., Leibowitz, S.G., 

Lightfoot, D.C., and Taylor, A.H., 2000, Report of a peer review panel on terrestrial aspects 

of the biological resources program of the Grand Canyon Monitoring and Research Center: 

submitted to U.S. Geological Survey, Grand Canyon Monitoring and Research Center, 50 p.

U.S. Department of the Interior, 1996, Record of decision, operation of Glen Canyon Dam--final 

environmental impact statement: Washington, D.C., Office of the Secretary of the Interior, 

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Bureau of Reclamation, 15 p., accessed on October 13, 2010, at 

http://www.usbr.gov/uc/rm/amp/pdfs/sp_appndxG_ROD.pdf.

Waring, G. L., 1995, Current and historical riparian vegetation trends in Grand Canyon, using 

multitemporal remote sensing analyses of GIS sites: Final report, submitted to Bureau of 

Reclamation, Glen Canyon Environmental Studies, and National Park Service Rep., 20 pp, 

Northern Arizona University, Flagstaff.

Wright, S.A., and Kaplinski, M., 2011, Flow structures and sandbar dynamics in a canyon river 

during a controlled flood, Colorado River, Arizona: Journal of Geophysical Research, v. 

116, no. F01019, 15 p., http://www.agu.org/pubs/crossref/2011/2009JF001442.shtml.

Yard, H.K., van Riper Charles III, Brown, B.T., and Kearsley, M.J., 2004, Diets of insectivorous 

birds along the Colorado River in Grand Canyon, Arizona: Condor, v. 106, no. 1, p. 106-

115, accessed on December 28, 2009, at http://www.jstor.org/stable/pdfplus/1370520.pdf.

 

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G. Budget 

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385
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Project 12. Dam-Related Effects on the Distribution and 

Abundance of Selected Culturally-Important Plants in the 

Colorado River Ecosystem 

A. Investigators 

Helen Fairley, Social Scientist, U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

Peter Bungart, Senior Archaeologist, Department of Cultural Resources, Hualapai Tribe

Tony Joe, Supervisory Anthropologist, Historic Preservation Department, Navajo Nation

Michael Yeatts, Archaeologist, Hopi Tribe

B. Project Summary 

This proposal aims to document changes to the cultural landscape of the Colorado River 

corridor as reflected in changes to the historical distribution and comparative abundance of a 

subset of plants that are known to have been culturally important to multiple Native American 

tribes, and specifically the tribes currently involved in the Glen Canyon Dan Adaptive 

Management Program (GCDAMP). This project will involve systematically analyzing historical 

plant data and historical photographs from the river corridor in an office setting as well as in the 

field, to qualitatively and quantitatively assess changes to species of particular cultural 

importance to tribes during the past 20 years, as well as over longer time intervals. This study 

would serve as one basis for assessing dam effects to the cultural landscape of the Colorado 

River corridor below Glen Canyon Dam. 

This study will be accomplished through compiling and synthesizing existing data on 

selected plant species that have been collaboratively identified by the GCDAMP tribes and 

through comparing historical photographs of locations exhibiting the specific targeted species 

with more recent photographs of those same locations. The study will also incorporate direct 

observations of many of those same locations, to compare past and current vegetation conditions, 

and assess whether, from tribal perspectives, the cultural landscape has changed in a positive or 

negative manner. 

This project will serve the interests of the tribes involved in the GCDAMP, as well as the 

interests of all GCDAMP stakeholders, in several important respects. Specifically, this project 

will: 1) utilize traditional ecological knowledge to inform DOI managers and GCDAMP 

stakeholders about dam-related changes affecting culturally-valued vegetation species and the 

larger river corridor cultural landscape; 2) integrate Native American values and traditional 

ecological knowledge in a collaborative GCMRC-sponsored science effort to assess dam effects 

to culturally-valued plant components of Colorado River cultural landscape; and 3) utilize a 

combination of traditional ecological knowledge and western scientific information to further 

enhance connections between tribal youth and elders in the context of tribal monitoring 

programs. In addition, this project will address a long-standing interest of multiple GCDAMP 

stakeholders who have expressed interest in seeing a variety of approaches, including more 

holistic and qualitative methods, used for assessing how Glen Canyon Dam is affecting the 

riparian landscape and the diverse cultural values of the Colorado River corridor. Furthermore, it 

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is aligned with the new Department of Interior Secretarial directive to use a landscape approach 

for assessing and mitigating effects of energy-related projects on federal lands (DOI 2013, 

Secretarial Order No.330).

C. Background

C.1. Scientific Background 

It is well documented that the distribution, density, and diversity of riparian vegetation is 

directly and indirectly affected by dam regulation of rivers (Williams and Wohlman, 1984), and 

the Colorado River below Glen Canyon Dam is no exception (Stevens and Ayers, 1993; Turner 

and Karpisak 1980; Webb 1996; Webb, Leake, and Turner, 2007). Dam-related changes can 

include shifts in plant densities and in dominant plant communities tied to the frequency and 

elevation of seasonal inundation, wetting-drying cycles tied to diurnal fluctuations, periodicity 

and magnitude of flooding, and other types of dam-controlled disturbances. In lower Glen and 

Grand Canyons, as a result of hydrologic changes due to the presence and operation of Glen 

Canyon Dam, riparian vegetation has moved downslope and become much denser than it was in 

the pre-dam era, while the old high water zone vegetation has died back and in some cases, 

become senescent (Anderson and Ruffner, 1988; Carothers and Brown, 1991). These changes 

have resulted in a river corridor landscape that appears significantly different from the one that 

existed just prior to the construction of Glen Canyon. 

The biological changes resulting from Glen Canyon Dam’s alteration of river hydrology 

(Topping and others, 2003) have not only affected individual species and habitats; they have also 

affected culturally-valued attributes of the landscape. Landscapes are, by definition, culturally 

and socially constructed concepts (Greider and Garkovich, 1994; Evans and others, 2001). For 

example, the Colorado River corridor in Grand Canyon is often viewed as an example of wild, 

untrammeled nature by EuroAmericans visitors to Grand Canyon National Park, while this same 

landscape is viewed by some Native American tribes as an extensively occupied, previously 

cultivated, and heavily utilized area that was formerly more like a familiar “back yard” than a 

“wilderness”. These differences reflect the significant differences in histories, traditons, and 

world views, although both groups cherish this landscape, albeit for different reasons and from 

very different respective points of view.

All of the tribes involved in the GCDAMP possess considerable knowledge of the terrestrial 

riparian and upland landscapes of the Colorado Plateau and the specific plants and animals that 

dwell within in its river-dependent ecosystems from generations of using these resources for 

daily sustenance, medicines, and ceremonial purposes. For example, ancestors and relatives of 

the Hualapai and Southern Paiute gathered plants for food, medicine and ceremonies and hunted 

sheep and other fauna in the western portions of Grand Canyon well into the first decades of the 

20th century, while Navajo people used Glen and Marble Canyon for grazing and watering 

livestock and collecting medicinal plants through most of the last century (Stoffle and others, 

1994; Stoffle and others, 1997; Roberts and others, 1995). These traditional activities require an 

intimate knowledge of the seasonality and distribution of plants based on centuries of prior 

experience living within this environment. Thus, in contrast to most scientists and stakeholders 

involved in the GCDAMP, the Native American tribes view the river corridor landscape as a 

cultural resource, and many of its associated plants are likewise viewed as cultural resources, in 

addition to being valued as habitat for other animal species.

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In contrast to the time depth of tribal traditional knowledge, studies of the plants in the Grand 

Canyon river corridor by western scientists date back to the late 1930s, when Elzada Clover, a 

professor of botany from the University of Michigan, and her assistant Lois Jotter, conducted the 

first botanical inventory of the river corridor of Grand Canyon (Clover and Jotter, 1944). In the 

late 1950s, additional inventories and studies were undertaken by scientist affiliated with the 

University of Utah in anticipation of the inundation of the Glen Canyon reservoir (Woodbury 

and others, 1958, 1959a, 1959b). Starting in the 1970s and continuing through the 1980s, more 

detailed studies of specific plant distributions and their response to Glen Canyon Dam operations 

were undertaken by National Park Service scientists and other scientists who worked for the 

Bureau of Reclamation’s Glen Canyon Environmental Studies program (e.g., Anderson and 

Ruffner, 1988; Carothers and others, 1976; Carothers and Brown, 1991; Kearsley and others, 

2006; Ralston, 2005; Ralston and others, 2008; Stevens, 1989; Stevens and others, 1995; Stevens 

and Waring, 1986). In addition, several USGS-sponsored studies have used replication of 

historical photographs to document changes to both the riparian and high desert vegetation 

through time (e.g., Turner and Karpisak, 1980; Webb, 1996, Webb and others, 2007). Other 

studies have focused on evidence from the dendrochronological record to interpret dam-related 

changes in the distribution and abundance of specific riparian species, such as Goodding willow 

and netleaf hackberry (Mast and Waring, 1997; Salzer and others, 1996), while still other studies 

have mapped the distribution of specific species (e.g., Anderson and Ruffner, 1986; Stevens, 

2011). 

Recently, GCMRC initiated a new study to evaluate effects of Glen Canyon Dam operations 

on the downstream riparian ecosystem. This study focuses on monitoring plant guild responses 

(see Project 11, this volume). While plant guild-response monitoring is not specifically focused 

on tracking changes to individual species, some species-specific data is being collected through 

Project 11 that potentially could contribute to assessing changes in the distribution and density of 

culturally-valued plants (B. Ralston, personal comm. to H. Fairley, 2014.) 

Other recent work by Amy Draut (2011, 2012) has demonstrated that dam operations can 

affect vegetation growing well-above the zone of active inundation. These effects occur in part 

because dam operations influence the distribution of sand bars and other exposed sand areas 

which serve as sources for wind-blown sand. The distribution of wind-blown sand at higher 

elevations within the river corridor, and whether it is regularly resupplied or not, influences the 

texture of surface substrates, water retention capacity of the substrate, distribution of biological 

soil crusts, and the types, density and distribution of associated plant species. Some of the plants 

commonly associated with active aeolian landscapes, such as Sporobolus sp. and Oryzopsis 

hymenoides, are known to have been highly valued as food sources by many Southwestern tribes. 

The extent of active and inactive aeolian sand areas has been partially mapped by Draut and 

others for large segments of the river corridor as part of Project J in the FY13–14 work plan, and 

will be more completely mapped in FY15–17 as part of Project 4 (this volume), but the extent to 

which these landscape-scale changes have affected plant species of cultural importance to Native 

American tribes is currently unknown.

This project intends to build on botanical studies previously undertaken and accomplished by 

GCES and GCMRC as well as recent work initiated by the Hualapai Tribe as part of their pilot 

TEK study (Hualapai Tribe, 2013). Ultimately, the larger goal of this project is to place speciesspecific observations of a select group of culturally-valued plants in a larger landscape context 

and allow the tribes to evaluate those documented landscape changes from their own unique 

cultural perspectives as part of their ongoing tribal monitoring programs.

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C.2. Key Monitoring and Research Questions Addressed in this project 

Strategic Science Question:

• SSQ 2-1. Do dam-controlled flows affect (increase or decrease) rates of erosion and 

vegetation growth at archaeological sites and TCP sites in the CRE, and if so, how?

AMP Strategic Plan Questions

• CMIN 11.2.1 Are the traditionally important resources and locations for each tribe and 

other groups being affected [by dam operations]?

• RIN 11.2.1 What are the traditionally important resources and locations for each tribe and 

other groups?

• RIN 11.24 What changes are occurring in cultural resources sites, and what are the causes 

of those changes?

• RIN 12.9.1 How well does current tribal participation in the AMP research and long-term 

monitoring programs meet tribal needs and desires?

Research questions specific to this project: 

• To what extent have the abundance and distribution of key plant species of traditional 

importance to tribes been altered in the past 20 years and over longer time frames due to 

dam operations?

• To what extent have changes in the availability of active eolian areas affected the 

distribution and abundance of specific grass species that are of traditional importance to 

tribes?

• Where (specifically) did culturally-valued species grow in the past compared to where 

they grow today?

• How do tribal members view the changes in plant communities and individual species of 

traditional importance – positively, negatively, or neutrally? 

• How has the cultural landscape of the Colorado River corridor been affected by damrelated changes to the distribution and abundance of culturally-valued species?

D. Proposed Work 

This project encompasses two elements with inter-related objectives. Element 12.1 involves 

the systematic analysis of historic data and imagery to assess changes in the density and 

distribution of culturally-values plants. The primary objectives of this first element are fourfold: 

1) to identify the historical and modern locations and contexts of specific traditionally-valued 

plant species that can be reliably identified in historical plant inventories and from historical 

photographs and that are known to be of cultural importance to multiple tribes, 2) to assess the 

distribution and comparative abundance these plants in past decades throughout the river corridor 

landscape as compared with current conditions; 3) to identify a subset of historical photographs 

located in proximity to cultural sites that are routinely monitored by the Tribes, so that they can 

be incorporated into future tribal monitoring efforts, and 4) to characterize the geomorphic 

conditions that promoted the growth and survival of the targeted species, to serve as a guide for 

restoration efforts that may be implemented by the tribes and the National Park Service under 

separate projects in the future. A workshop and the analysis of historical imagery will occur in 

first year (FY15) of this two-year project.

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Project Element 12.2 will solicit tribal feedback concerning current vegetation conditions vs. 

historical conditions through the use of historical photographs. Photographs identified in element 

1 that were taken in proximity to cultural sites that are currently being monitored by the 

GCDAMP tribes, will provide a basis for compiling tribal views about dam-related changes that 

have occurred or that are currently occurring to the cultural landscape in the river corridor. The 

work associated with element 2, plus the production of publications, will occur in FY16. The 

specific methods to be applied in each project element are described in greater detail below.

D.1. Project Elements 

Project Element 12.1. Tribal workshop and analysis of cultural landscape change 

(Recommended for funding FY15: $45,000; Unfunded Moderate Priority FY15: $7,161)

At the outset of this project, GCMRC will host a one-day workshop involving tribal 

members, GCMRC program staff, and riparian ecologists from USGS, NPS, and possibly other 

local institutions. The purpose of this workshop will be to review and compare lists of plant 

species developed by tribes during previous ethnobotanical research and use these lists to 

identify a subset of plants that are of common interest to all the tribes, whose life history is 

intimately linked to Colorado River hydrology, and that have good potential to be readily 

recognized in historical photographs. The final list of species that will become the focus of 

subsequent analysis efforts will be determined through consensus of the tribes involved in this 

project. This list is anticipated to include 6-8 species. 

After the list of target species has been identified, GCMRC staff will compile and synthesize 

existing literature related to these specific plants and also undertake a systematic analysis of 

historical photograph collections that may capture images of these plants in their predam setting 

along the Colorado River. Specific collections that will be analyzed include the photographs 

from the Stanton expedition (1890) and matches of these photographs created by Webb and 

colleagues in 1990–1991 and 2010–2011 (Webb, 1996; Webb and others, 2011), photographs 

from the 1971–1972 Powell expedition and the 1923 Birdseye Expedition (some which have 

been previously matched by Stephens and Shoemaker, 1987 and Barrs and Buchanan, 1994), 

photo matches documenting vegetation changes by Turner and Karpisak (1980), plus 

photographs taken by H. Butchart, R. Euler, and D. Schwartz in the early to mid-1960s and by 

Weeden and others (1975) in the mid-1970s. This analysis will be carried out in conjunction with 

similar analyses being undertaken for other purposes as part of Project 4 and will involve 

collaboration with staff of the Hualapai Tribe who have initiated similar historical photographic 

analyses as part of a pilot TEK project in FY13–15. 

An effort will be made to identify photographs from a variety of temporal contexts 

distributed throughout the length of the river corridor over a variety of geomorphic settings 

immediately adjacent to the historically-active river channel. The intent is to provide a 

reasonably representative picture of the river corridor landscape immediately adjacent to the 

historically-active channel and its component plant species from the late 19th century onward. 

We estimate that out of approximately 800 historical photographs that will be initially sorted, 

perhaps 250-300 historical photographs will contain sufficiently detailed images of vegetation to 

allow species identification; these images will provide the basis for the historical photo analysis 

component of this project and will serve as the “sampling frame” for characterizing changes in 

plant distributions throughout the river corridor. 

Using analytical methods previously developed by Webb (1996) for comparing the 1890 

Stanton photos and 1990 replicates, GCMRC staff will systematically analyze and qualitatively 

391
assess changes to the specific plants of traditional cultural importance to tribes. The analysis will 

identify whether the same plants are present in the same areas today, and whether their 

abundance appears to have increased or decreased using a simple ranked scale (e.g., no apparent 

increase/decrease, slight increase or decrease (less than 25% difference in individuals or cover --

the exact metric will depend on the plant species being evaluated), moderate increase or decrease 

(25–50% difference) or significant change (>50% difference). We will also use the photographs 

to qualitatively characterize the context in which the plants of interest occur, noting any apparent 

physical changes to local context associated with observed plant changes (e.g., differences in 

characteristics of fluvial deposits, biological soil crust cover, aeolian sand cover, associated 

vegetation, etc.) Specific protocols will be established for recording these observations to ensure 

consistency, comparability and reliability of resulting data. The photo analysis data will be 

compiled and evaluated in conjunction with previously published plant studies and any relevant 

quantitative data being collected by ongoing GCMRC projects (Projects 3, 4 and 11) to provide 

additional time-depth perspective about landscape changes at specific locations throughout the 

river corridor.

The minimize field time and reduce costs, the analyst will rely on existing matches of 

photographs that have been made through previous replication efforts as much as possible. 

GCMRC staff will assess the reliability of observations made only from photographs by field 

checking a sample of the photographs and comparing them with actual conditions observed in 

the field. This work will be accomplished in conjunction with river trips planned for other 

projects, such Projects 3, 4 and 11, tribal monitoring trips, or Grand Canyon Youth trips.

While conducting these analyses for Project Element 12.1, any photographs taken at or near 

locations currently monitored by the Tribes will be flagged for later incorporation into future 

tribal monitoring programs as part of Project Element 12.2.

Project Element 12.2. Tribal evaluations of cultural landscape changes 

(Unfunded Moderate Priority FY15: $0)

In addition to evaluating changes in the distribution and abundance of specific culturallyvalued plants, as described above for Project Element 12.1, this project includes a second 

element that focuses on evaluating the documented changes from each participating tribe’s 

unique cultural perspective. As noted above, while sorting through and analyzing the historical 

photograph collections, GCMRC staff will identify photographs taken at or in close proximity to 

areas monitored by the participating tribes. Tribes that have elected to participate in this element 

of the project will use the historical photographs to solicit feedback from tribal members about 

whether they view the documented changes in a positive or negative light, and why. These 

observations may be incorporated into ongoing tribal monitoring projects, some of which are 

already exploring the utility of historical photographs for this purpose (e.g., Hualapai Tribe’s 

TEK pilot project). 

After selecting a subset of the photographs that capture views of the landscape surrounding 

locations of particular importance to each tribe, tribal members will relocate each photo view 

during their annual monitoring trips and compare the historical photo view to current conditions. 

Following an established protocol (to be developed in collaboration with GCMRC), tribal 

members will analyze changes in plant species by comparing the selected historic photographs 

with current conditions. (Tribes may also duplicate these views as part of their ongoing 

monitoring efforts.) Tribal staff will use the information obtained from the field photo 

comparisons to elicit tribal members’ input about their perceptions of the observed changes, i.e., 

392
whether a change is perceived as positive, negative, or neutral. The underlying basis for each 

perspective/assessment will be elicited through semi-structured interviews and will be 

documented, either through recording the interview with a tape recorder or video camera or by 

completing a structured interview form. This information is expected to complement and 

enhance other information already being collected during annual tribal monitoring trips. The 

results of the semi-structured interviews will be incorporated into a final report for this project, 

and may also be incorporated into annual tribal monitoring reports, as each tribe deems 

appropriate.

D.2 Personnel and Collaborations 

This project will be led by Helen Fairley, GCMRC Social Scientist, in collaboration with 

multiple tribal cooperators. Peter Bungart will lead the Hualapai Tribe’s participation in this 

project. Bungart is also co-lead of the Hualapai Tribe’s ongoing TEK project, and the experience 

and insights that he has gained from that earlier work, and his knowledge of managing culturallysensitive databases, will be essential for ensuring the quality of results for both elements of 

Project 12. Tony Joe is a Supervisory Anthropologist with the Navajo Nation and will help 

organize and contribute information relevant to the Navajos’ perspective on culturally-valued 

plants and landscapes. Tony will lead the Navajo Nation’s participation in elements 1 and 2 of 

Project 12. Michael Yeatts is an archaeologist with the Hopi Tribe. Yeatts will organize Hopi’s 

participation in Project 12, which will initially focus on element 1. The Hopi’s participation in 

element 2 will depend, in part, on the results obtained from the first year of work and further 

consideration of how the proposed element 2 monitoring component may impact the Hopi 

Tribe’s current monitoring program. Fairley will have management responsibility for the project, 

but data collection, analysis, and reporting will be done in collaboration with Bungart and Joe 

and with cooperation from Yeatts. 

D.3. Deliverables 

A USGS report will be prepared at the end of the project documenting the changes that have 

been compiled and observed through the review and synthesis of existing studies and the 

intensive photo analysis. This report will also include a summary of the observations made by 

tribal members, to the extent that tribes are willing to share their observations.

A journal article will be collaboratively prepared at the conclusion of the project 

documenting the work accomplished and its strengths or weaknesses as a model for 

incorporating tribal perspectives in science programs that can be potentially applied to other 

adaptive management programs in the future. 

E. References 

Anderson, L.S., and Ruffner, G.A., 1988, Effects of the post-Glen Canyon Dam flow regime on 

the old high water line plant community along the Colorado River in Grand Canyon--

executive summeries of technical reports: Bureau of Reclamation, Glen Canyon 

Environmental Studies. [Available from National Technical Information Service, Springfield, 

Va. as NTIS Report PB-183505/AS]

Baars, D.L. and Buchanan, R.C., 1994, The Canyon Revisited: A Rephotography of the Grand 

Canyon 1923/1991: Salt Lake City: University of Utah Press, 168 p.

Carothers, S.W., Aitchison, S.W., Karpiscak, M.M., Rufner, G.A., Sharber, N.J., Shoemaker, 

P.L., Stevens, L.E., Theroux, M.E., and Tomko, D.S., 1976, An ecological survey of the 

393
riparian zone of the Colorado River and its tributaries between Lees Ferry and the Grand 

Wash Cliffs--final report: Flagstaff, Museum of Northern Arizona, Department of Biology, 

submitted to U.S. Department of the Interior, National Park Service, Grand Canyon National 

Park, Colorado River Research Series, contribution no. 38, contract no. CX821500007, 

Colorado River Research technical report no.10, 251 p.

Carothers, S.W., and Brown, B.T., 1991, The Colorado River through Grand Canyon--natural 

history and human change: Tucson, University of Arizona Press, 235 p.

Clover, E.U., and Jotter, L., 1944, Floristic studies in the canyon of the Colorado and tributaries: 

American Midland Naturalist, v. 32, no. 3, p. 591-

642., http://www.jstor.org/stable/pdfplus/2421241.pdf.

Evan, M.J., Roberts A. and Nelson, P., 2001, Ethnographic Landscapes. CRM Vol. 24, no.5, p. 

53-56.

Draut, A.E., 2011, Vegetation and substrate properties of aeolian dune fields in the Colorado 

River corridor, Grand Canyon, Arizona: U.S. Geological Survey Open-File Report 2011–

1195, 16 p., available at http://pubs.usgs.gov/of/2011/1195/.

Draut, A.E., 2012. Effects of river regulation on aeolian landscapes, Colorado River, 

southwestern USA. Journal of Geophysical Research: Earth Surface, 117(F2). 

Greider, T. and Garkovich, L., 1994, Landscape: The social construct of nature and the 

environment. Rural Sociology, Vol. 59, no. 1, p. 1-24.

Hualapai Tribe, 2013, Proposal for TEK Pilot Project. Ms. submitted to Bureau of Reclamation, 

Upper Colorado River Region, Glen Canyon Dam Adaptive Management Program.

Kearsley, M.J.C., Cobb, N.S., Yard, H., Lightfoot, D., Brantley, S., Carpenter, G., and Frey, J., 

eds., Inventory and monitoring of terrestrial riparian resources in the Colorado River corridor 

of the Grand Canyon--an integrative approach--final report: Flagstaff, Northern Arizona 

University, submitted to U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center, cooperative agreement no. 01 WRAG 0044 (NAU) and 01 WRAG 0034 (HYC), 177-

85 p.

Kearsley, M.J.C., and Ayers, T.J., 1996, The effects of interim flows from Glen Canyon Dam on 

riparian vegetation in the Colorado River corridor, Grand Canyon National Park, Arizona--

final report: Flagstaff, Northern Arizona University, submitted to Grand Canyon National 

Park, Grand Canyon Science Center, cooperative agreement no. 8041-8-0002, 702 

p., http://www.riversimulator.org/Resources/GCMRC/Terrestrial/Kearsley1996b.pdf.

Mast, J.N. and Waring, G., 1997, Dendrochronological Analysis of Goodding Willows in Grand 

Canyon National Park. In Van Riper, C. and Deshler, E., eds., Proceedings of the Third 

Biennial Conference of Research on the Colorado Plateau. Transactions and Proceedings 

Series NPS/NRNAU?NRTP-97/12: Flagstaff: National Park Service, p. 115-127.

Ralston, B., 2005, Riparian Vegetation and Associated Wildlife. Chapter 6 in Gloss, S.P., 

Lovich, J.E., and Melis, T.S., eds., 2005, The State of the Colorado River Ecosystem in 

Grand Canyon: A Report of the Grand Canyon Monitoring and Research Center, 1991-2004. 

U.S. Geological Circular No. 1282, p. 103-122.

Roberts, A., Begay, R.M., and Kelley, K.B., 1995 Bits’iis Nineeze (The River of Neverending 

Life), Navajo History and Cultural Resources of the Grand Canyon and the Colorado River.

Submitted by the Navajo Nation Historic Preservation Department to the Glen Canyon 

Environmental Studies Office, USDI Bureau of Reclamation, Flagstaff, Arizona.

Salzer, M.W., McCord, V.A.S., Stevens, L.E. and Webb, R.H., 1996, The dendrochronological 

analysis of netleaf hackberry (Celtis reticulate Torr.) in Grand Canyon: Assessing the impact 

394
of regulate river flow on tree growth, in Dean. J.S., Meko, D.M., and Swetham, T.S., eds., 

1996, Tree Rings, Environment, and Humanity: Tucson: Radiocarbon, p. 273-281. 

Stephens, H. G. and Shoemaker, E. M., 1987, In the Footsteps of John Wesley Powell: An 

Album of Comparative Photographs from the Green and Colorado Rivers, 1871-1872: 

Boulder, Ccolorado: Johnson Books.

Stevens, L.E., 1989, Mechanisms of Riparian Plant Community Organization and Succession in 

Grand Canyon, Arizona. Ph.D. Dissertation, Northern Arizona University, Flagstaff.

Stevens, L.E., 2011, Goodding’s Willow in Grand Canyon: Requiem or Revival? Boatman’s 

Quarterly Review, vol. 24, no3, p. 6-9. 

Stevens, L.E. and T.J. Ayers, 1993,The impacts of Glen Canyon Dam on riparian vegetation and 

soil stability in the Colorado River corridor, Grand Canyon, Arizona. National Park Service 

Cooperative Parks Study Unit 1992 Final Report, Flagstaff. 

Stevens, L.E., Schmidt, J.C., Ayers, T.J., and Brown, B.T., 1995, Flow regulation, 

geomorphology, and Colorado River marsh development in the Grand Canyon, Arizona: 

Ecological Applications, v. 5, no. 4, doi: 10.2307/2269352, p. 1025-

1039, http://dx.doi.org/10.2307/2269352.

Stevens, L.E., and Waring, G. 1986, Effects of Post-Dam Flooding on Riparian Substrates, 

Vegetation and Invertebrate Populations in the Colorado River Corridor in Grand Canyon, 

Arizona. Final Report, Terrestrial Biology of the Glen Canyon Environmental Studies. Glen 

Canyon Environmental Studies Report No. A2, April 15, 1986. 

Stoffle, R.W., Halmo, D.B., and Austin, D.E., 1997 Cultural Landscapes and Traditional 

Cultural Properties: A Southern Paiute View of the Grand Canyon and the Colorado River. 

American Indian Quarterly 21:219–249.

Stoffle, R.W., Halmo, D.B., Evans, M.J., and Austin, D.E., 1994 Piapaxa ‘Uipi (Big River 

Canyon): Southern Paiute Ethnographic Resource Inventory and Assessment for Colorado 

River Corridor, Glen Canyon National Recreation Area, Utah and Arizona, and Grand 

Canyon National Park, Arizona. Submitted to the Glen Canyon Environmental Studies 

Office, USDI Bureau of Reclamation, Flagstaff.

Topping, D.J., Schmidt, J.C., and Vierra, L.E., Jr., 2003, Computation and Analysis of the 

Instantaneous-discharge Record for the Colorado River at Lees Ferry, Arizona – May 8, 1921 

through September 30, 2000. U.S. Geological Survey Professional Paper1677, 118 p. 

Turner, R. M. and Karpisak, M.M., 1980, Recent Vegetation Changes Along the Colorado River 

Between Glen Canyon Dam and Lake Mead, Arizona. U.S. Geological Survey Professional 

Paper 1132, 125 p.

Webb, R. H., 1996, Grand Canyon, a Century of Change: Rephotography of the 1889-1890 

Stanton Expedition. Tucson: University of Arizona Press, 290 p. 

Webb, R.H., Belnap, J., Scott, M.L., and Esque, T.C., 2011, Long-term change in perennial 

vegetation along the Colorado River in Grand Canyon National Park (1889-2010). Park 

Science vol. 28, no. 2, p. 83-87.

Webb, R.H., Leake, S.A., and Turner, R.M., 2007, The Ribbon of Green: Change in Riparian 

Vegetation in the Southwestern United States: Tucson: The University of Arizona Press, 463 

p.

Weeden, H., Borden, F. Turner, B., Thompson, D., Strauss, C. and Johnson, R., 1975, Grand 

Canyon National Park Campsite Inventory. Report prepared for National Park Service 

Contract No. CX 001-3-0061. University Park: Pennsylvania State University.

Williams, G.P and Wohlman, M.G., 1984, Downstream Effects of Dams on Alluvial Rivers. U.S. 

Geological Survey Professional Paper1286, 83 p. 

395
Woodbury, A.M., and multiple additional authors, 1958, Preliminary Report on Biological 

Resources of Glen Canyon Reservoir: Salt Lake City: University of Utah Anthropological 

Papers, Vol. 31

Woodbury, A.M., and multiple additional authors, 1959a, Ecological Studies of the Flora and 

Fauna of Glen Canyon: Salt Lake City: University of Utah Anthropological Papers, Vol. 40.

Woodbury, A.M., Durrant, S.D., and Flowers, S., 1959b, A Survey of Vegetation in the Glen 

Canyon Reservoir Basin: Salt Lake City: University of Utah Anthropological Papers, Vol.36.

F. Budget 

Project Element 12.1. Tribal 

workshop and analysis of 

cultural landscape change

Project Element 12.2. Tribal 

evaluations of cultural 

landscape changes

Salaries $ 19,647.00 Salaries $ - 

Traveling and Training $ 5,000.00 Traveling and Training $ - 

Operating Expenses $ 2,000.00 Operating Expenses $ - 

Logistics $ 5,000.00 Logistics $ - 

Cooperators (non-USGS) $ 15,000.00 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 5,514.00 USGS Burden $ - 

Total $ 52,161.00 Total $ - 

Project Element 12.1. Tribal 

workshop and analysis of 

cultural landscape change

Project Element 12.2. Tribal 

evaluations of cultural 

landscape changes

Salaries $ 19,962.00 Salaries $ - 

Traveling and Training $ 2,500.00 Traveling and Training $ - 

Operating Expenses $ 5,000.00 Operating Expenses $ - 

Logistics $ 5,000.00 Logistics $ - 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ 45,000.00 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 7,252.00 USGS Burden $ 1,350.00 

Total $ 39,714.00 Total $ 46,350.00 

FY 2015

FY 2015 Project 12 Gross Totals: $52,161.00

FY 2016

FY 2016 Project 12 Gross Totals: $86,064.00

396
Project Element 12.1. Tribal 

workshop and analysis of 

cultural landscape change

Project Element 12.2. Tribal 

evaluations of cultural 

landscape changes

Salaries $ - Salaries $ - 

Traveling and Training $ - Traveling and Training $ - 

Operating Expenses $ - Operating Expenses $ - 

Logistics $ - Logistics $ - 

Cooperators (non-USGS) $ - Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ - USGS Burden $ - 

Total $ - Total $ - 

FY 2017 Project 12 Gross Totals: $0

FY 2017 

397
Project 13. Socioeconomic Monitoring and Research 

A. Investigators 

Lucas Bair, Economist, U.S. Geological Survey, Grand Canyon Monitoring and Research Center

Charles Yackulic, Research Statistician, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

John Duffield, Research Professor, Department of Mathematical Sciences, University of 

Montana

Chris Neher, Researcher, Department of Mathematical Sciences, University of Montana

David Patterson, Professor, Department of Mathematical Sciences, University of Montana

Michael Springborn, Assistant Professor, University of California at Davis

Craig Bond, Economist, Pardee RAND Graduate School

B. Project Summary 

During the past three decades, socioeconomic monitoring and research in the Glen Canyon 

Environmental Studies and Glen Canyon Dam Adaptive Management Program (GCDAMP) have 

been limited (Hamilton and others, 2010). Previous research has indicated that the economic 

value of recreation and other downstream resources are impacted by Glen Canyon Dam (GCD) 

operations; however, because these studies were conducted 20 to 30 years ago, the findings are 

out-of-date, as dam operations and resource conditions have changed since that time (Bishop and 

others, 1987; Welsh and others, 1995; U.S. Department of Interior, 1996; USGS, 2005). 

This project is designed to identify recreation and tribal preferences for, and values of, 

downstream resources and evaluate how preference and value are influenced by GCD operations. 

In addition, the research will integrate 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) to develop a decision support system that will 

improve the ability of the GCDAMP to evaluate and prioritize management actions, monitoring 

and research (Hamilton and others, 2010). 

This project involves three related socioeconomic monitoring and research studies. These 

studies include: (a) evaluation of the impact of GCD operations on regional economic 

expenditures and economic values associated with angling in the Glen Canyon National 

Recreation Area (GCNRA) downstream from GCD, and whitewater floating in Grand Canyon 

National Park (GCNP) that begins at Lees Ferry (Project Element 13.1); (b) assessment of the 

impact of GCD operations on tribal preference for and value of downstream resources (Project 

Element 13.2); and (c) development of decision methods, using economic metrics, to evaluate 

management actions and prioritize monitoring and research on resources downstream of GCD 

(Project Element 13.3).

This project will be coordinated with related economic research efforts implemented by the 

National Park Service (NPS) and U.S. Bureau of Reclamation (Reclamation) in conjunction with 

the Glen Canyon Dam Long-Term Experimental and Management Plan Environmental Impact 

Statement (LTEMP EIS). The NPS is conducting research to provide current economic values of 

ecosystem resources downstream of GCD. In addition, Argonne National Laboratory, contracted 

through Reclamation, has made significant advancements in the power system analysis modeling 

for the LTEMP EIS that provide information on the economic value of hydropower production at 

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GCD under different management alternatives. These coordinated efforts to determine individual 

preferences for and economic values of downstream resources, and the development of decision 

methods to improve decision making abilities of GCDAMP are necessary to evaluate and 

prioritize management, monitoring, and research decisions.

C. Background 

Recreation

The Grand Canyon Protection Act (GCPA) of 1992 states that, “long-term monitoring of 

Glen Canyon Dam shall include any necessary research and studies to determine the effect of the 

Secretary's actions under section 1804(c) on the...recreational...resources of Grand Canyon 

National Park and Glen Canyon National Recreation Area” (GCPA, sec. 1805(b)). Bishop and 

others (1987) were the first to establish a relationship between dam operations and recreational 

preferences and economic values related to angling in GCNRA and whitewater floating in 

GCNP. Nearly 30 years have passed since this comprehensive study of regional recreational 

expenditures and preferences for and economic values of releases at GCD. The characteristics of 

recreational resources have changed significantly since this research was conducted. Specifically, 

alteration of diurnal flow patterns and greater whitewater floating opportunities resulting from 

The Operation of Glen Canyon Dam, Record of Decision (ROD) (U.S. Department of Interior, 

1996), and the Colorado River Management Plan (NPS, 2006), respectively, have changed the 

whitewater floating experience. The angling experience has also changed in Glen Canyon since 

the Bishop and others (1987) study as a result of fluctuations in catch rates and fish condition 

and modifications to angling regulations (Loomis and others, 2005). 

Additional research was conducted in GCNP to assess whitewater floater trip preferences; 

although the research did not identify specific economic values of flows for whitewater floating 

trips (Stewart and others, 2000). Furthermore, the economic information related to recreation 

will not be updated through empirical research for the LTEMP EIS (Harpman, 2013). Because it 

is important to understand the potential effects of dam operations on the recreational experiences 

in GCNRA and GCNP, there is a need to update and extend the original Bishop and others 

(1987) study. Undoubtedly, this research will contribute to a primary GCDAMP goal, which is to 

“maintain or improve the quality of recreational experiences for users of the Colorado River 

ecosystem, within the framework of the GCDAMP ecosystem goals” (USGS, 2006). 

Native American Tribes

The operation of GCD also has direct and indirect effects on downstream resources of 

cultural value and traditional use in GCNRA and GCNP. The GCPA of 1992 states that, 

“...monitoring programs and activities conducted under subsection (a) shall be established and 

implemented in consultation with...Indian tribes...” (GCPA, sec. 1805(c)). The GCDAMP has 

also recognized a need to maintain effective consultation with tribes to appropriately incorporate 

tribal values into the GCDAMP. 

“Because culture defines the roles that resources play in that culture, only 

members of that culture can assess the status or health of the resources. Therefore, 

measures for resource status or health and appropriate management will need to 

be determined individually by the federal agencies in consultation with the 

traditionally associated peoples (AMWG, 2012a).”

399
Research concerning tribal preferences for and values of downstream resources, and 

assessment of the influence of dam operations on these resources, is lacking (Hamilton and 

others, 2010). This research, in partnership with the tribes, is critical for furthering the 

understanding of tribal socioeconomic impacts associated with resource management decisions 

within the GCDAMP. 

Decision Theory

It is the “absence of decision making mechanisms” in adaptive management (AM) programs 

that make systematic prioritization of investment in monitoring, research, and management 

alternatives difficult (Scarlet, 2013). Decision making mechanisms, including the economic 

assessment of investment in monitoring and research, are important components of AM 

programs (Doremus, 2010). Recent studies have highlighted the shortcomings of traditional costbenefit methods when facing the state-dependency and inherent uncertainty in AM programs 

(Loomis and other, 2009, Bond 2010). Given these shortcomings, optimal control or stochastic 

dynamic optimization methods have been proposed to evaluate the economics of management 

actions and monitoring and research efforts (Bond, 2010; Bond and Loomis, 2009; EpanchinNiell and Hasting, 2010; Springborn and Sanchirico, 2013). These methods use mathematical 

techniques to identify optimal management actions, including monitoring and research, given an 

objective (e.g., minimize economic costs) and a set of physical, biological and/or institutional 

constraints (e.g., humpback cub recovery goals).

Previous research has developed a decision support system for the Colorado River ecosystem 

(CRE) in GCNRA and GCNP downstream from GCD. Walters and others (2000) developed a 

decision support system to screen the effect of various management options on downstream 

resources. While some predictions of resource responses to various management scenarios were

accurate, responses to management scenarios of other resources (e.g., sediment storage, native 

fish) were very uncertain, due to limited empirical data (Walters and others, 2000). More recent 

analysis in the LTEMP EIS used structured decision analysis to identify alternative future 

management scenarios, but this process is not comparable to an economically based decision 

support system (Reclamation, 2014). This project element would take the next step in the 

development of a decision support system to inform the GCDAMP in the organization and 

evaluation of management actions, monitoring, and research.

It is pertinent that monitoring and research in the physical science (see FY15–17 Workplan, 

Projects 1, 2, 3, and 11), biological science (see FY15–17 Workplan, Projects 6, 7, 8, 9, and 10), 

cultural (see FY15–17 Workplan, Project 4 and 12), and socioeconomic (see FY15–17 

Workplan, Project Elements 13.1 and 13.2) programs be integrated into an analytical framework 

that can inform the GCDAMP in evaluation of future monitoring and research. Developing a 

decision support system based on analytical methods, such as predictive, integrated dynamic 

models, is essential when answering questions such as, “how do we quantify and integrate the 

full range of socio-economic concerns into dam re-regulation, in addition to hydropower 

concerns (GCDAMP, 2004)?” Therefore, there is a critical need to develop a decision support 

system within the GCDAMP to assist in the organization, evaluation and prioritization of 

investment in monitoring and research and improve the economic efficiency of long-run 

management decisions under uncertainty.

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C.1. Scientific Background 

The following hypotheses and research questions support the proposed project elements. 

Given that project elements are a synthesis of monitoring and research, there are components that 

are not hypothesis driven. 

Recreation

Hypothesis 1 (H1) The operation of GCD influences the economic value of angling in GCNRA, 

between GCD and Lees Ferry. 

Hypothesis 2 (H2) The operation of Glen Canyon Dam influences the economic value of 

whitewater floating in GCNP. Demand for recreation is determined by (a) socioeconomic 

characteristics (e.g., income, education, age, etc.), (b) quality, (c) substitutes, (d) travel time, (e) 

crowding, and (f) tastes and preferences (Loomis and Walsh, 1997). Operation of GCD directly 

impacts the quality of angling in GCNRA and whitewater floating in GCNP (Bishop and others, 

1987). For example, different flows affect the ability to operate watercraft during angling and 

whitewater floating activities and influence trip attributes such as catch rate for anglers and 

length of time spent on the river for whitewater floaters. Similar to findings by Bishop and others 

(1987), H1 and H2 posit that both anglers’ and whitewater floaters’ economic values increase 

with increased flows, until an inflection point is reached, at which time economic value 

decreases with increased flow. Figure 1 is an example of the relationship between an individual 

whitewater floater’s surplus economic value per trip and average flows.

Figure 2: Theoretical Flow Value Curve for an Individual Whitewater Floater (Bishop and others, 1987)

While the primary objective of this research is to evaluate the relationship between operation 

of GCD and economic values of recreational angling and whitewater floating, this project 

element will also provide information about; (a) regional expenditures, (b) trip attributes of 

importance, and (c) direct recreational use values (see section D.1). This information is important 

when conducting impact, and other policy related analysis. 

Native American Tribes

Hypothesis 3 (H3) Tribal preferences for and values of downstream resources differ among 

downstream resource attributes. To test this hypothesis, the relative ranking, marginal rate of 

substitution, and parameter estimates of preference relationships among resource attributes (e.g., 

0

200

400

600

800

1,000

5,000 10,000 20,000 30,000 40,000 50,000

Individual's 

Surplus Value 

Per Trip ($)

Average Flow Level (CFS)

401
hydropower, native fish) will be generated and assessed. H3 posits that there will be significant 

variation in the preferences for and values of downstream resources by resource attribute. 

Because tribes may have specific culturally determined “decision processes” and approaches to 

resource valuation that may limit aggregation of individual preferences, the choice of elicitation 

methods, and comparison of preferences among tribes (Adamowicz and others, 1998), additional 

hypotheses to be tested in Project Element 13.2 will be generated following tribal consultation. 

An additional hypothesis that may be addressed in this project element is: 

• Tribal preferences for and values of downstream resources differ among tribes. 

This research will enhance understanding of tribal preferences for and values of downstream 

resources, and perspectives associated with tradeoffs that occur when evaluating management 

actions and prioritizing monitoring and research decisions within the GCDAMP. 

Decision Theory

This project element will improve the GCDAMP’s ability to organize scientific information 

and evaluate and prioritize, monitoring, research and management alternatives specific to the 

operation of GCD. For example, in the Non-native Fish Control Downstream from Glen Canyon 

Dam Environmental Assessment (NNFC) (Reclamation, 2011), it is informally hypothesized that 

in mitigation of the effects of rainbow trout (Oncorhynchus mykiss) on humpback chub (Gila 

cypha) (Reclamation 2011), flow actions may be more cost-effective in the long-run relative to 

the proposed non-native removal efforts in the Paria-Badger Creek Rapid and Little Colorado 

River reaches (Reclamation, 2011). This is the type of question this project element will address.

One of the twelve goals of the GCDAMP is to “maintain a high-quality monitoring, research, 

and adaptive management program” (USGS, 2006). In order to accomplish this goal, it is 

important to prioritize management actions, including monitoring and research. In fact, several 

of the eleven other goals of the GCDAMP specify desired resource states and stress actions to 

achieve these states where “practicable”, “feasible”, or “within the framework” of other resource 

goals (e.g., ecosystem goals). This direction calls for a balanced approach to managing resources 

downstream of GCD. Identifying economic values of downstream resources and establishing a 

decision support system will assist in the evaluation of actions the GCDAMP recommends and 

implements through GCMRC to answer research questions specific to its goals.

C.2. Key Monitoring and Research Questions Addressed in this project 

This project is organized around hypotheses and research questions (see section C.1) that are 

based on Strategic Science Questions (SSQs), Core Monitoring Information Needs (CMINs), and 

Research Information Needs (RINs) previously identified by the GCDAMP. The project also 

supports the evaluation and prioritization of Desired Future Conditions as identified by the 

AMWG (2012a.)

Primary SSQ addressed:

• SSQ 2-6. How can tribal values/data/analyses be appropriately incorporated into a 

science driven adaptive management process in order to evaluate the effects of flow 

operations and management actions on TCPs?

• SSQ 2-7. Are dam controlled flows affecting TCPs and other tribally-valued resources in 

the CRE, and, if so, in what respects are they being affected, and are those effects 

considered positive or negative by the tribes who value these resources?

402
• SSQ 3-7. How do dam controlled flows affect visitors’ recreational experiences, and what 

is/are the optimal flows for maintaining a high quality recreational experience in the 

CRE? 

• SSQ 3-8. What are the drivers for recreational experiences in the CRE, and how 

important are flows relative to other drivers in shaping recreational experience outcomes?

Primary Core Monitoring Information Needs addressed:

• CMIN 11.2.1 (SPG revised). Determine the condition of traditionally important resources 

and locations using tribal perspectives and values.

Research Information Needs addressed:

• RIN 12.1.1 What is the economic value of the recreational use of the CRE downstream 

from GCD?

• RIN 12.3.2 What are the differences between western science and tribal processes for 

design of studies and for gathering, analyzing, and interpreting data used in the adaptive 

management program? How well do research designs and work plans incorporate tribal 

perspectives and values into the standard western science paradigm? Is it more beneficial 

to keep the perspective separated?

The development of the proposed project has occurred through communication with and 

cooperation from the GCDAMP Socioeconomics Ad Hoc Group (SEAHG). The SEAHG has 

repeatedly identified the proposed project elements as critical information needs (AMWG 

2012b). The proposed project elements are also based on coordinated activities with the NPS and 

Reclamation in conjunction with the LTEMP EIS. The proposed project elements will 

compliment current economic analysis associated with the LTEMP EIS.

D. Proposed Work 

D.1. Project Elements 

Project Element 13.1. Economic Values of Recreational Resources along the Colorado River – Grand Canyon 

Whitewater Floater and Glen Canyon Angler Values – 

(Recommended for funding FY15: $69,801)

Lucas Bair, Economist, USGS, GCMRC

John Duffield, Research Professor, Department of Mathematical Sciences, University of 

Montana

Chris Neher, Researcher, Department of Mathematical Sciences, University of Montana

David Patterson, Professor, Department of Mathematical Sciences, University of Montana

The objective of this project element is to determine preferences, regional expenditures, and 

economic values of anglers in GCNRA2 and whitewater floaters in GCNP3

, as affected by 

operation of GCD, to provide the GCDAMP and federal decision-makers with current recreation 

2 For purposes of this project element, anglers in GCNRA include walk-in anglers from Lees Ferry to Badger Creek 

Rapid.

3 This project does not include whitewater floaters that begin their trip at Diamond Creek.

403

 
resources information for decision making. This project element has been initiated with FY13–

14 funds from Project K, Economist and Support ($241,305). The funding request for FY15–16 

is for continued involvement of the GCMRC economist, Lucas Bair. 

To accomplish the project objective, a series of economic surveys will be conducted to obtain 

current information on recreationists’ preferences, expenditures, and economic values associated 

with angler and whitewater floater trips. Specifically, surveys of anglers in GCNRA and 

whitewater floaters in GCNP will include questions addressing:

• Regional expenditures associated with trip activities such as the cost of transportation, 

lodging, guide services, and various other local purchases.

• Trip attributes of importance such as crowding, fish catch characteristics, overall trip 

enjoyment, and other trip qualities.

• Direct recreational use values (i.e., net economic benefits) to the recreationist, as 

measured by willingness to pay over and above trip costs.

• Variation in direct recreational use values related to a range of flow levels presented in 

the surveys.

As was the case with the original Bishop and others (1987) study, the proposed project will 

use a mail survey contact method with a follow-up protocol for non-responders. The respondents 

will be sent a mail survey packet, followed by a postcard reminder, and, later, by a second survey 

packet for non-responders. Non-respondents to the second survey packet will be contacted to 

complete non-response questions. 

A random sample from the most recent year’s whitewater floaters will be obtained with the 

assistance of GCNP and outfitters. GCNP maintains a comprehensive mailing list of all members 

of private whitewater floater parties. Additionally, commercial outfitters maintain mailing lists of 

the commercial clients. The survey will include: 1) private party floaters, 2) commercial motor 

powered floaters, and 3) commercial oar powered floaters. The target sample size will be 2,850 

whitewater floaters divided equally between private and commercial trip participants. The 

commercial sample will be further divided equally between oar and motor-powered trips. 

Anglers in Glen Canyon, using Lees Ferry downstream to Badger Creek Rapid as access 

points, will be contacted during high use periods, spring (April-May) and fall (OctoberNovember), to participate in the surveys. No a priori attempt will be made to stratify the 

sampling based on guided or non-guided status. However, preferences, expenditures, and 

economic values of guided and non-guided anglers will be compared within the data analysis. 

Anglers contacted at Lees Ferry will be asked questions regarding demographics and attributes 

of their trip. In addition, anglers will be asked to provide contact information. The target sample 

size is 750 anglers.

Statistical models appropriate for the experimental design and elicitation format of the 

surveys will be developed to evaluate the relationship between preferences, economic value and 

trip attributes (e.g., flow levels). The models will provide information on the relative preferences 

and economic value for trip attributes and the marginal rates of substitution between trip 

attributes. This information is necessary for the GCDAMP to make informed decisions about the 

economic tradeoffs that occur, with regard to recreation, when evaluating future management 

actions (see FY15–17 Workplan, Project Element 13.3).

404
Project Element 13.2. Tribal Perspectives for and Values of Resources Downstream of Glen Canyon Dam – 

(Unfunded, High Priority FY15: $0) 

Lucas Bair, Economist, USGS, GCMRC

John Duffield, Research Professor, Department of Mathematical Sciences, University of 

Montana

Chris Neher, Researcher, Department of Mathematical Sciences, University of Montana

David Patterson, Professor, Department of Mathematical Sciences, University of Montana

The objective of this project element is to identify tribal preferences and values associated 

with management of resources downstream of GCD in order to inform decision making 

processes in the GCDAMP. Emphasis will be placed on resources of tribal significance that are 

directly or indirectly affected by dam operations, experiments, and ongoing management. The 

assessment of tribal preferences and values will be achieved through focus group meetings with

individual tribes, where choice experiment methods will be conducted to explicitly evaluate 

resource attributes tradeoffs that occur from management of GCD. The project will be initiated 

in FY16, subsequent to, and coordinated with, ongoing GCMRC economics studies.4

The individual project elements will consist of four major tasks:

1. Cooperate with GCDAMP Tribal representatives and Tribal members to review previous 

studies and tribal programs relating to tribal preferences for and values of resources 

downstream of GCD and obtain necessary permits to conduct research on tribal land. 

2. Conduct initial meetings with individual tribes to obtain permission and gauge interest in 

participation, identify focus group participants, and develop and pretest focus group 

survey content to ensure culturally appropriate methodology. 

3. Conduct focus group meetings with individual Tribal members to explore preferences for 

and values of downstream resources. The meetings will use choice experiment methods 

(Breffle and Rowe, 2002; Harpman, 2008), which are commonly applied in marketing 

and resource economics studies, to identify these preferences and values. 

4. Analyze survey results and prepare manuscript for publication. 

For the choice experiment methods, resource attributes of tribal importance (e.g., 

hydropower, humpback chub) and their potential variation with different future management 

actions will be defined and will shape the experimental design. The experimental design will be 

based on the number of possible scenarios to choose from, where respondents may be asked to 

evaluate all possible scenarios or just a subset of randomly chosen scenarios if the number of 

choices are unwieldy. Based on input during tribal consultation, future attribute levels will be 

either ranked, rated, or evaluated in a choice-based format (two alternative future scenarios 

compared and one is selected). It is important to note that comparisons among resource attributes 

can contain explicit cost information (e.g., forgone hydropower revenue) when comparing future 

resource attributes, or may just compare resource attributes alone. Statistical models appropriate 

for the experimental design and elicitation format will be developed to evaluate the relationship 

between preferences, or values, and resource attributes. The models will provide information on 

4 Focus groups are considered “qualitative” research and require less time-intensive review by the Office of 

Management and Budget.

405

 
the relative preferences and values for resource attributes and the rates of substitution 

between resource attribute tradeoffs.5 Information gained through this research is necessary for 

evaluation of management decisions and development of applied decision methods that 

accommodate tribal preferences for and values of downstream resources (see FY15–17 

Workplan, Project Element 13.3).

Project Element 13.3. Applied Decision Methods for the Glen Canyon Adaptive Management Program – 

(Recommended for Funding FY15: $106,803) 

Lucas Bair, Economist, USGS, GCMRC

Charles Yackulic, Research Statistician, USGS, GCMRC

Michael Springborn, Assistant Professor, University of California at Davis

Craig Bond, Economist, Pardee RAND Graduate School

The objective of this project element is to improve the GCDAMP’s ability to consider, 

organize and prioritize monitoring, research, and long-term management alternatives related to 

the operation of GCD. A decision support system comprised of analytical models, that 

incorporate economic parameters, will provide prompt assessment capabilities in science and 

management program planning.

To accomplish this, existing published approaches to resource management under uncertainty 

will be evaluated. Specific attention will be paid to methods that improve decision making 

processes when evaluating resource tradeoffs related to monitoring, research, and management 

decisions. Evaluation efforts will focus on decision frameworks and analytical tools that best 

apply to the GCDAMP when considering the need for collaboration, complex 

biophysical/socioeconomic interactions, and constraints on GCDAMP resources. 

There are multiple analytical approaches used in decision frameworks that address resource 

management under uncertainty. These include maximizing expected utility, applying the 

precautionary principle and other robust decision making processes such as dynamic stochastic 

programming, optimal control, or simulation methods (Lempert and Collins, 2007). The various 

approaches differ in the types of scientific information utilized and the way in which decision 

process outcomes are framed and communicated (Lempert and Collins, 2007).

There are also various types of decision support system frameworks that are important to 

consider when interdisciplinary teams of scientists and stakeholder groups that hold divergent 

views, or core values, are involved in the decision process. It is as important to address the 

decision process, or context, as it is to develop the scientific foundation, or content, of the 

analytical methods (Norton, 2005; Clifford and Sagoff, 2009).

This project element will develop and implement a decision support system specific to the 

GCDAMP in a series of model development tasks. Analytical model development of 

downstream resources will be prioritized for resources that:

1. Contain significant economic value and/or that garner a significant portion of the 

GCMRC annual budget;

2. Are impacted by operational decisions at GCD; and

5 Model results will not quantify the economic value of the resource attribute. However, if price based attributes 

(e.g. hydropower costs) are assessed in the surveys, economic values can be ascertained. 

406

 
3. Have sufficient predictive modeling frameworks developed to assess future resource 

states. 

The initial focus of this project element will be the development of a bioeconomic model to 

identify the economically preferred management strategy for established nonnative fish, in 

relation to humpback chub survival.6 This is a question explicitly identified in the NNFC 

(Reclamation, 2011). This task follows the model prioritization structure, (1) ecosystem values 

(including humpback chub) exhibit significant economic value (Welsh and other, 1995); (2) dam 

operation impacts non-native fish populations (see FY15-17 Workplan, Project 9), and (3) recent 

advancements in predictive models of rainbow trout and humpback chub survival have led to 

opportunities to evaluate humpback chub population management from an economic perspective 

(Yackulic and others, 2014). This task will evaluate economic outcomes, as part of the Yackulic 

and others (2014) model, to minimize the cost of rainbow trout removal over time, under 

different future scenarios. While the exact methodological approach will be determined through 

model development, the likely approaches include optimization (stochastic dynamic 

programming or optimal control) and/or simulation based approaches (Epanchin-Niell and

Hasting, 2010). Incorporating future scenarios allows for modeling humpback chub recovery 

goals in various conditions while identifying strategies that are both cost-effective and robust to 

uncertain future conditions (e.g., climate). This analytical model, and accompanying 

documentation, will be completed in FY15.

This proposed bioeconomic model utilizes cost-effectiveness analysis. Like cost-benefit 

analysis, cost-effectiveness analysis is a standard economic practice. However, cost-effectiveness 

fundamentally asks a different question than cost-benefit analysis. Cost-benefit analysis assigns 

an overall net benefit (or net cost) to a future management action. Cost-effectiveness analysis inturn identifies the least cost alternative, when faced with competing or complimentary 

management actions, to reach a defined objective. In this case, the objective is humpback cub 

recovery, as defined by the U.S. Fish and Wildlife Service (U.S. Fish and Wildlife Service, 

2002). Implementing cost-effectiveness analysis is consistent with the ROD’s goal, not to 

maximize benefits but to determine an operation at GCD that limits impact to hydropower while 

meeting recovery and long-term sustainability of downstream resources (Reclamation, 1996). 

There are several other implications when using cost-effectiveness analysis that are important 

to recognize. For example, it must be determined that the defined goal is worth achieving. This is 

demonstrated by either verifying the economic benefit of the objective outweighs the costs 

associated with achieving the objective or the objective is mandated through a public process. In 

the case of the humpback chub recovery goals, both the economic value of recovery exceeds the 

cost of proposed recovery actions and recovery goals are mandated through public process 

(Welsh and others, 1995; U.S. Fish and Wildlife Service, 2002). Conducting cost-effectiveness 

analysis also implies that the defined goal will be reached across all possible alternative future 

scenarios. Again, this is a reasonable assumption based on the recovery mandate (U.S. Fish and 

Wildlife Service, 2002). This implication is important because it essentially removes the 

onerous, or in some cases contentious, identification of economic value of downstream 

resources. The focus is shifted from establishing the benefit of the objective to identifying the 

most cost-effective way to meet the objective (Sagoff, 2009). This is an important distinction 

when stakeholders may fundamentally reject attempts to economically value aspect of ecosystem 

6 Management strategies would consider constraints with respect to tribal concerns and other factors (e.g., whirling 

disease). 

407

 
resources. Cost-effectiveness analysis isn’t appropriate in every context. However, it lends itself 

to the GCDAMP’s task of evaluating and prioritizing management actions, monitoring and 

research where incremental decisions must be made, under uncertainty, understanding that many 

overarching objectives are set through public processes. 

While the initial task is focused on research to identify the most cost-effective management 

actions with respect to non-native fish management policies, as identified in the NNFC 

(Reclamation, 2011), the modeling effort will be expanded in FY16–17 to include other 

downstream resources that impact rainbow trout and humpback chub populations, better 

facilitating decision making in the GCDAMP. Specifically, in FY16–17, subsequent tasks in 

model development will include:

1. Identify the importance of parameter uncertainty on the sensitivity of cost-effective 

outcomes in the bioeconomic model. Evaluating parameter uncertainty will aid in the 

identification of the value and prioritization of monitoring and research (i.e., how 

scientific discovery and monitoring, and reducing model parameter uncertainty, decreases 

expected management costs) and demonstration of how modeling can prioritize future 

monitoring and research. This advancement in the analytical model, and accompanying 

documentation, will be completed in FY16–17.

2. Incorporate additional management variables and associated costs, such as trout 

management flows at GCD, to improve humpback chub survival, again identifying the 

most cost-effective management alternatives under different future scenarios. This 

advancement in the analytical model, and accompanying documentation, will be 

completed in FY16–17.

The decision support system will be developed over FY15–17 in cooperation with 

stakeholders, according to stakeholder’s expressed needs and the advancement of scientific 

knowledge at GCMRC. For example, updating the economic value of whitewater floating in 

GCNP will provide insight into modeling the tradeoffs between flow regimes and recreational 

experiences (see FY15–17 Workplan, Project Element 13.1). This deliberate process of building 

a decision support system through the development of individual analytical, predictive models 

will enable analysts to identify monitoring and scientific information needs and screen policy 

options as the GCDAMP advances its goals. This process is essential in enabling the GCDAMP 

to better organize and evaluate the scientific monitoring and research that is provided by 

GCMRC. 

D.2 Personnel and Collaborations 

The project lead is Lucas Bair. Collaborators for Project Elements 13.1 and 13.2. include 

John Duffield and Chris Neher, economists at the University of Montana, and David Patterson, a 

statistician at the University of Montana. These collaborators will assist with the development 

and implementation and analysis of recreational and tribal surveys. Collaborators for Project 

Element 13.3. will include Charles Yackulic and other biology and physical-sciences program 

staff at the GCMRC, mostly in supporting roles, Michael Springborn, an economist specializing 

in adaptive management, at the University of California at Davis, and Craig Bond, an economist 

specializing in adaptive management, at the RAND Corporation. These collaborators will assist

with development of applied decision methods.

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D.3 Deliverables 

Products from this project, led by Lucas Bair, will include annual reports to the GCDAMP, 

presentations at TWG and AMWG meetings when appropriate, presentations at scientific 

meetings, and peer-reviewed scientific journal articles. 

• In FY16–17, one or two manuscripts will be prepared from the results of Project Element 

13.1 for submission to peer-reviewed scientific journals. 

• In FY17, one manuscript will be prepared from the results of Project Element 13.2 for 

submission to a peer-reviewed scientific journal.

• In FY15–17, two or three manuscripts will be prepared from the results of Project 

Element 13.3 for submission to peer-reviewed scientific journals.

E. References 

Adamowicz , W., Beckley, T., Hatton Macdonald, D., Just, L., Luckert, M., Murray, E., and 

Phillips, W., 1998, In search of forest resource values of indigenous peoples--are nonmarket 

valuation techniques applicable?: Society & Natural Resources--An International Journal, v.

11, no. 1, doi: 10.1080/08941929809381061, p. 51-66.

Bishop, R.C., Boyle, K.J., Welsh, M.P., Baumgartner, R.M., and Rathbun, P.R., 1987, Glen 

Canyon Dam releases and downstream recreation--an analysis of user preferences and 

economic values: Madison, Wisc., Huberlein-Baumgartner Research Service, submitted to 

Bureau of Reclamation, Upper Colorado Region, Glen Canyon Environmental Studies report 

no. GCES/27/87, 188 p. [Available from National Technical Information Service, 

Springfield, Va. as NTIS report PB88-182546/AS.]

Bond, C.A., and Loomis, J.B., 2009, Using numerical dynamic programming to compare passive 

and active learning in the adaptive management of nutrients in shallow lakes: Canadian 

Journal of Agricultural Economics, v. 57, p. 555-573.

Bond, C.A., 2010, On the potential use of adaptive control methods for improving adaptive 

natural resource management: Optimal Control Applications and Methods, v. 31, p. 55-56.

Breffle, W.S., and Rowe, R.D., 2002, Comparing choice question formats for evaluating natural 

resource tradeoffs: Land Economics, v. 78, no. 2, p. 298-314.

Clifford, R.S., and Sagoff, M., 2009, On the collaboration of economists and ecologists, in 

Clifford, R.S., and Sagoff, M., eds., Evolution of water resource planning and decision 

making: Northampton, Mass., Edward Elgar Publishing, Inc.

Doremus, H., 2010, Adaptive management as an information problem: NCL Review, v. 89, p. 

1455.

Epanchin-Niell, R.S., and Hastings, A., 2010, Controlling established invaders--integrating 

economics and spread dynamics to determine optimal management: Ecology Letters, v. 13, p. 

528-541.

Glen Canyon Dam Adaptive Management Program (GCDAMP), 2004, Priority setting 

workshop--questions from stakeholders to help design GCMRC budget and workplan: 

Updated August 8, 2004, 

http://www.usbr.gov/uc/rm/amp/amwg/mtgs/04aug09/Attach_13a.pdf.

Glen Canyon Dam Adaptive Management Work Group (AMWG), 2012a, Desired future 

conditions for the Colorado River ecosystem in relation to Glen Canyon Dam: DFC Ad Hoc 

Committee Review 23 January 2012 as Approved by AMWG on February 23, 2012.

409
Glen Canyon Dam Adaptive Management Work Group (AMWG), 2012b, Recommended 

information needs and program elements for a proposed AMP socioeconomics program as 

approved by AMWG on February 23, 2012: AMWG.

Harpman, D.A., 2008, Introduction to conjoint analysis for valuing ecosystem amenities: U.S. 

Bureau of Reclamation, Technical Service Center, technical memorandum number EC 2008-

03.

Hamilton, J.R., Hanemann, W.M., Loomis, J.B., and Peters, L., 2010, Final report of the 

GCMRC socioeconomic research review panel: Flagstaff, Ariz., U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center, report of a workshop held December 2 & 3, 

2009, Phoenix, Ariz., http://www.usbr.gov/uc/rm/amp/twg/mtgs/10mar15/Attach_03b.pdf.

Lempert, R.J., and Collins, M.T., 2007, Managing the risk of uncertain threshold responses--

comparison of robust, optimum, and precautionary approaches: Risk Analysis, v. 27, no. 4, 

doi: 10.1111/j.1539-6924.2007.00940.x, p. 1009–1026.

Loomis, J.B., Bond, C.A., and Harpman, D.A., 2009, The potential of agent-based modelling for 

performing economic analysis of adaptive natural resource management: Journal of Natural 

Resource Policy Research, v. 1, no. 1, p. 35-48.

Loomis, J.B., Douglas, A.J., and Harpman, D.A., 2005, Recreation use values and nonuse values 

at Glen and Grand Canyon--chapter 9, in Gloss, S.P., Lovich, J.E., and Melis, T.S., eds., The 

state of the Colorado River ecosystem in Grand Canyon----a report of the Grand Canyon 

Monitoring and Research Center 1991-2004: U.S. Geological Survey Circular 1282, 153-164 

p., http://pubs.usgs.gov/circ/1282/.

Loomis, J.B., and Walsh, R., 1997, Recreation economic decisions--comparing benefits and 

costs (2d ed.): State College, Pa., Venture Publishing, 637 p.

National Park Service, 2006, Colorado River management plan: Grand Canyon, Ariz., 

Department of the Interior, Grand Canyon National Park, Office of Planning and 

Compliance.

Norton, B.G., 2005, Sustainability--a philosophy of adaptice ecosystem management: Chicago, 

Ill., University of Chicago Press.

Sagoff, M., 2009, Collaborative adaptive management--challenges and opportunities: Ecology 

and Society, v. 18, no. 3, p. 26.

Scarlet, L., 2013, Collaborative adaptive management--challenges and opportunities: Ecology 

and Society, v. 18, no. 3, p. 26.

Springborn, M., and Sanchirico, J.N., 2013, A density projection approach for non-trivial 

information dynamics--adaptive management of stochastic natural resources: Journal of 

Environmental Economics and Management, v. 66, no. 3, p. 609-624, 

http://dx.doi.org/10.1016/j.jeem.2013.07.003.

Stewart, W.p., Larkin, K., Orland, B., Anderson, D., Manning, R., Cole, D., Taylor, J., and 

Tomar, N., 2000, Preferences of recreation user groups of the Colorado River in Grand 

Canyon--final report: Flagstaff, Ariz., submitted to U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center, cooperative agreement no. 98-FG-40-0190, 232 p., 

http://www.gcmrc.gov/library/reports/cultural/Recreation/Stewart2000.pdf.

Bureau of Reclamation, 2011, Environmental assessment--non-native fish control downstream 

from Glen Canyon Dam: Salt Lake City, Utah, Bureau of Reclamation, Upper Colorado 

Region, 102 p. + appendices, http://www.usbr.gov/uc/envdocs/ea/gc/nnfc/NNFC-EA.pdf.

410
Bureau of Reclamation, 2014, Glen Canyon LTEMP environmental impact statement (EIS) 

update--presentation to AMWG, February 20, 2014: Bureau of Reclamation and National 

Park Service, http://www.usbr.gov/uc/rm/amp/amwg/mtgs/14feb19/Attach_11b.pdf.

Bureau of Reclamation, 1996, Record of decision on the operation of Glen Canyon Dam--final 

environmental impact statement: Salt Lake City, Utah, Glen Canyon Dam Adaptive 

Management Program,, UC-326 ENV-6.00, 15 p., accessed on July 22, 2011, at 

http://www.usbr.gov/uc/rm/amp/pdfs/sp_appndxG_ROD.pdf.

U.S. Fish and Wildlife Service, 2002, Humpback chub (Gila cypha) recovery goals--amendment 

and supplement to the humpback chub recovery plan: Denver, Colo., U.S. Fish and Wildlife 

Service, Mountain Prairie Region, 71 p., http://www.fws.gov/mountainprairie/crrip/doc/rg/Humpbackchub.pdf.

U.S. Geological Survey, 2006, Strategic science plan to support the Glen Canyon Dam adaptive 

management program--Fiscal years 2007-11: U.S. Geological Survey, Grand Canyon 

Monitoring and Research Center, in cooperation with the Glen Canyon Dam Adaptive 

Management Program (GCDAMP), 11 p., 

http://www.usbr.gov/uc/rm/amp/amwg/mtgs/06dec05/Attach_07b.pdf.

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, p. 

1-38, http://www.consecol.org/vol4/iss2/art1/.

Welsh, M.P., Bishop, R.C., Phillips, M.L., and Baumgartner, R.M., 1995, Glen Canyon Dam 

Colorado River storage project, Arizona--non-use values final study summary report: 

Madison, Wisc., Hagler Bailly Consulting, Inc., National Technical Information Service no. 

PB98-106636, 37 p.

Yackulic, C.B., Coggins, L., and Korman, J., 2014, An overview of rainbow trout-humpback 

chub model developed for the LTEMP environmental impact statement (EIS): Flagstaff, 

Ariz., U.S. Geological Survey, Grand Canyon Monitoring and Research Center.

F. Budget 

Project Element 13.1 

Economic Values of 

Recreational Resources 

along the Colorado River – 

Grand Canyon Whitewater 

Floater and Glen Canyon 

Lees Ferry Angler Values 

Project Element 13.2 Tribal 

Perspectives for and Values 

of Resources Downstream of 

Glen Canyon Dam 

Project Element 13.3 

Applied Decision Methods 

for the Glen Canyon 

Adaptive Management 

Program 

Salaries $54,673 Salaries $0 Salaries $64,093

Traveling and Training $5,000 Traveling and Training $0 Traveling and Training $7,500

Operating Expenses $500 Operating Expenses $0 Operating Expenses $500

Logistics $0 Logistics $0 Logistics $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $0 Cooperators (non-USGS) $22,500

USGS Cooperators $0 USGS Cooperators $0 USGS Cooperators $0

USGS Burden $9,628 USGS Burden $0 USGS Burden $12,210

Total $69,801 Total $0 Total $106,803

FY 2015

FY 2015 Project 13 Gross Totals: $176,605

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Project Element 13.1 

Economic Values of 

Recreational Resources 

along the Colorado River – 

Grand Canyon Whitewater 

Floater and Glen Canyon 

Lees Ferry Angler Values 13.1

Project Element 13.2 Tribal 

Perspectives for and Values 

of Resources Downstream of 

Glen Canyon Dam 

Project Element 13.3 

Applied Decision Methods 

for the Glen Canyon 

Adaptive Management 

Program 

Salaries $57,516 Salaries $0 Salaries $67,426

Traveling and Training $2,500 Traveling and Training $2,500 Traveling and Training $7,500

Operating Expenses $250 Operating Expenses $10,250 Operating Expenses $500

Logistics $0 Logistics $0 Logistics $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $117,500 Cooperators (non-USGS) $54,000

USGS Cooperators $0 USGS Cooperators $0 USGS Cooperators $0

USGS Burden $13,259 USGS Burden $6,330 USGS Burden $18,214

Total $73,525 Total $136,580 Total $147,640

FY 2016

FY 2016 Project 13 Gross Totals: $357,746

Project Element 13.1 

Economic Values of 

Recreational Resources 

along the Colorado River – 

Grand Canyon Whitewater 

Floater and Glen Canyon 

Lees Ferry Angler Values 

Project Element 13.2 Tribal 

Perspectives for and Values 

of Resources Downstream of 

Glen Canyon Dam 

Project Element 13.3 

Applied Decision Methods 

for the Glen Canyon 

Adaptive Management 

Program 

Salaries $0 Salaries $0 Salaries $127,441

Traveling and Training $0 Traveling and Training $5,000 Traveling and Training $7,500

Operating Expenses $0 Operating Expenses $500 Operating Expenses $500

Logistics $0 Logistics $0 Logistics $0

Cooperators (non-USGS) $0 Cooperators (non-USGS) $117,500 Cooperators (non-USGS) $54,000

USGS Cooperators $0 USGS Cooperators $0 USGS Cooperators $0

USGS Burden $0 USGS Burden $5,065 USGS Burden $39,543

Total $0 Total $128,065 Total $228,984

FY 2017 Project 13 Gross Totals: $357,049

FY 2017 

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Project 14. Geographic Information Systems (GIS) 

Services and Support 

A. Investigators 

Thomas M. Gushue, GIS Coordinator, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

Timothy Andrews, IT Specialist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

TBD, Geographer (GS-09), U.S. Geological Survey, Grand Canyon Monitoring and Research 

Center

B. Project Summary 

Geographic Information Systems (GIS) continues to play a critical role in nearly all of 

GCMRC’s science efforts and is prevalent in many of the projects proposed in the FY2015-17 

Triennial Work Plan. It is used across disciplines and is itself a powerful tool for integrating 

geospatial data collected by many different projects. The GIS Services and Support project is the 

epicenter of GCMRC’s geospatial knowledge and support for a broad range of activities. It 

supports acquisition of remote sensing overflight data and river-based data collection efforts, 

provides geospatial expertise across all resources of interest, maintains and preserves all 

geospatial data holdings, and produces a wide range of cartographic, geographic and analytical 

output in support of GCMRC’s science projects. Linkages to other projects in this work plan are 

addressed in the Geospatial Data Analysis element of this project (14.1.1.) and more specifically 

outlined in Table 1 at the end of this project description. This project provides a high-level of 

support to other GCMRC projects in the form geospatial data processing and analysis, geospatial 

data management, and the development of web-based services and applications that provide 

access to GCMRC’s geospatial data holdings.

As we move into a new planning cycle, an opportunity exists to promote a vision of how a 

GIS project will successfully function within GCMRC and meet the current and future needs of 

scientists, managers and the public alike. Most work performed within this project falls within 

one of three main tenets: Geospatial Data Analysis, Geospatial Data Management, and Access to 

Geospatial Data Holdings. These concepts are not new, and have been a part of GCMRC work in 

various forms over the last 15 years or more. This project description affords us a chance to more 

clearly define each of these elements and how they relate to individual projects as well as 

GCMRC’s overall mission.

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 Figure 1. One example of many Grand Canyon location maps designed and produced by GIS staff in support of GCDAMP 

activities.

C. Background

C.1. Scientific Background 

Research and monitoring efforts at GCMRC have led to the collection of a wealth of 

geospatial information over the last twenty years. Many of GCMRC’s geospatial data holdings 

have large spatial extents (from Lake Powell to Lake Mead), fine resolutions (20-cm pixels for 

imagery, 0.01 meter spatial tolerances), and large file sizes with tens of thousands to millions of 

records per file. This presents a challenge to map a considerably large area at very fine scales, as 

does the sinuosity of the Colorado River and the extreme elevation changes found in Grand 

Canyon. Challenges also arise in handling, analyzing, storing and serving these unique data sets.

The GIS staff at GCMRC has met these challenges by continuing to provide a stable and 

consistent platform for conducting geospatial processing, analysis and output for over a decade.

The last ten years have seen many advances in the geospatial industry, with some of the more 

noticeable changes coming in the role that GIS and geospatial data now play in our daily lives.

Similarly, the role of GIS within GCMRC has changed during this same time period. The most 

recent versions of GIS software have become easier to use with more standardized workflows for 

creating, maintaining, processing and analyzing geospatial data. This has allowed science staff to 

begin using GIS tools on their own, thus broadening the Center’s base knowledge in GIS. It has 

also increased the amount and level of support requested of GIS professional staff within 

GCMRC.

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Over the last decade, the use of GIS within GCMRC has evolved into a fully functioning, 

mature, enterprise-level system. All geospatial information collected and produced by GCMRC 

can be overlaid, analyzed and integrated. More recently, the GIS staff has made a concerted 

effort to stay at the forefront of technological advances in providing access to geospatial 

information online. Final versions of geospatial data are available internally through both filebased and server-based platforms, and externally through custom-built web mapping applications 

on GCMRC’s website, as well as other online avenues (see Project Elements 14.3.1 and 14.3.2).

Anyone can now access many of GCMRC’s most important geospatial data sets online including 

canyon-wide, aerial imagery (Fig. 2) and elevation data of the CRe between Lakes Powell and 

Mead, locations of river campsites used by recreationalists, long-term sandbar monitoring DEM 

surfaces, site photographs of campsites and sandbars, and sandbar deposition photographs before 

and after recent high flow events. These data serve as a tremendous resource to managers, 

stakeholders, and members of the general public interested in Grand Canyon and its resources.

The advances made by GCMRC in online mapping applications have already proven useful 

in supporting management activities such as the development of the Glen Canyon Dam LongTerm Experimental and Management Plan (LTEMP) Environmental Impact Statement. In 

addition, they provide opportunities for scientific collaborations not previously possible. 

Figure 2. Aerial imagery collected in May 2009 showing the top of Hance Rapid. Digital imagery collected in years 2002, 

2005, and 2009, along with many other geospatial data sets, can be viewed online at http://www.gcmrc.gov/

 

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C.2. Management Background 

As the science provider for the Glen Canyon Adaptive Management Program (GCDAMP), 

GCMRC is responsible for providing complete and spatially accurate geospatial data in support 

of funded GCDAMP projects. Historically, this responsibility was outlined in the Adaptive 

Management Work Group’s (AMWG) original list of program goals (Goal 12: Maintain a high 

quality monitoring, research and adaptive management program), and upheld by GCMRC’s GIS 

and Survey staff, both formerly a part of a now nonexistent Information Technology (IT) 

program. The elements of GIS and Survey (Project 3.5) still remain and have continued to 

provide the expertise required to maintain federal guidelines and standards for data quality and 

accuracy as well as fully support the needs of GCMRC scientists and managers.

The ability to maintain consistent and accurate geospatial information, perform necessary 

analyses on geospatial data, and integrate information across projects has been essential to other 

GCMRC projects directly supporting many of the other GCDAMP goals. Successive refinements 

of GCDAMP goals, objectives, and questions (Core Monitoring Information Needs, Research 

Information Needs, Strategic Science Questions, Desired Future Conditions, and the HFE EA) 

all still rely on GCMRC’s ability to maintain, process and serve highly accurate geospatial 

information, and in some cases, have prompted the need for new or additional data to be 

collected and processed.

Beginning in 1999, GCMRC’s GIS staff undertook the development of a canyon-wide, 

spatially consistent Geographic Information Systems platform. The centerpiece of this platform 

was the GCMRC centerline and river mileage reference system that was completed in 2002. This 

data set cross-referenced the most commonly used river mile systems in existence at the time, 

and has since become the backbone of all georeferenced information collected or developed 

along the Colorado River corridor. Nearly all scientific research, published literature, 

management decisions, and even commercially available river guide books now use this system 

for referencing locations along the river. The GCMRC centerline and river mileage reference 

system, as well as all other geospatial data collected or derived within the Colorado River 

corridor, are dependent on the survey control network (Project Element 3.5). These two 

components (GIS and Survey) remain closely tied and together have produced a spatially 

accurate and logically consistent georeference system used by all GCMRC projects. This 

geospatial system is comprised of data sets, databases, workflows, processing techniques and 

metadata documentation that is adaptable to new advances in technology, and yet continues to be 

a stable platform for conducting long-term scientific studies of the Colorado River. Even as 

management needs change and become further refined, it is anticipated that the role of GIS as 

both a scientific and management support tool will continue to become increasingly important.

C.3. Key Monitoring and Research Questions Addressed in this project 

For relationships between the GIS Services and Support project and key monitoring and 

research questions, please refer to project linkages briefly described below in Geospatial Data 

Analysis (14.1.1.) and more specifically listed in Table 1 of this project description.

 

416
D. Proposed Work 

D.1. Project Elements 

Project Element 14.1. Geospatial Data Analysis 

(Recommended for funding FY15: $223,562)

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Timothy Andrews, IT Specialist, USGS, GCMRC

TBD, Geographer (GS-09), USG, GCMRC

To measure the amount of GIS support provided to all projects in the FY2015-17 Work plan, 

we estimated the number of pay periods required of GIS professional staff to assist with 

geospatial related tasks for each project element. The level of involvement was determined in 

consultation with principal investigators and other researchers for each project with specific 

geospatial processing, analytical tasks and associated writing assignments described within the 

appropriate project element. In some cases, senior GIS staff members are assigned as coinvestigators to specific projects or project elements that require high-level geospatial application 

and analytical support (see Project Elements 3.1.2, 3.1.4, 9.9, and 10.1). Proposed research 

efforts defined in the work plan that will require a significant amount of high-level GIS support 

include elements of projects 3, 4, 5, 6, 7, 9 and 10. For project elements requiring geospatial 

support that is lower-level in nature (Projects 8 and 11), the work to be performed is considered 

to be fairly simple, commonly performed tasks requiring less than one day of one person’s time.

A listing of GIS support planned for all pertinent project elements is provided in Table 1 at the 

end of this project description. 

417
 Figure 3. Two examples of map products designed and produced by GIS staff in support of a) GCDAMP management 

actions, a map series illustrating anticipated inundation areas related to the November 2012 HFE (left), and b) GCMRC 

science efforts, a map book series created specifically for the system-wide electrofishing project (right), Project element 6.4 

in FY2015-17 work plan.

Project Element 14.2.1. Geospatial Data Management 

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Timothy Andrews, IT Specialist, USGS, GCMRC

TBD, Geographer (GS-09), USG, GCMRC

Geospatial data and how these data are handled has changed considerably in the last ten 

years. Improvements in remote sensing technologies have resulted in much larger, more accurate 

geospatial data sets that require advanced storage and retrieval systems. As a solution, the GIS 

industry has moved away from the traditional desktop environment (localized software and data ) 

to an enterprise environment consisting of server and client roles where the ability to share large 

amounts of geospatial data and associated analytical tools is increasingly more important.

Previously, individuals processing and maintaining their own individual data sets (i.e. Arc/Info 

coverages, shapefiles) was the norm; now organizations build GIS services and applications for 

GIS users to consume in many different ways. The move towards an enterprise GIS system at 

GCMRC began over a decade ago, however, this effort has gained momentum over the last five 

years. In 2011, a stand-alone Oracle database was designed and built specifically for storing and 

serving large amounts of geospatial data. Prior to this time, all tabular and spatial were stored on 

the same Oracle database server which caused many data storage and access issues. Since 2012, 

we have been populating an Oracle Spatial Database with a range of geospatial data sets that are 

used locally by GCMRC for mapping and analysis purposes and consumed by the public through 

our web mapping services online.

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Geospatial data management incorporates the organization and documentation of both filebased and server-based geospatial data. This needs to be a collaborative effort with GIS staff 

providing the lead through consultation on the best practices for organizing, storing, using, 

processing and documenting geospatial data, and GCMRC project staff adhering to protocols and 

best practices. Each project is unique, and how the geospatial data are organized is the 

responsibility of the principal investigator or another member of the project assigned as the data 

steward. This mostly speaks to file-based data (data stored in directories and folders). Serverbased geospatial data are final versions of data sets stored within an Oracle Spatial Database.

These are enterprise-level data sets that range from canyon-wide data collection missions 

(overflight imagery, digital surface models) to long-term monitoring efforts (site-based and 

reach-based topographic surveys) to more localized reference layers (Glen Canyon Fish 

Sampling Units). The GCMRC Oracle Spatial Database now contains over 3.5 terabytes of 

geospatial data, with more being added every year. 

By leveraging the power of an Oracle database, very large data sets, such as 20-cm pixel 

resolution, 4-band (Red, Green, Blue, and Near-Infrared wavelengths) digital imagery for 300 

miles of river, can be stored and served efficiently allowing for improved access to geospatial 

data by multiple users through many different avenues. While maintaining an Oracle database 

does come with some additional responsibility for GIS staff, the benefits by far outweigh the 

costs in terms of staff time. While the ease of access and improved performance alone would 

warrant using an enterprise system, the power of server-based data storage and retrieval is truly 

realized when considering how much utility is gained through this system. Data stored just once 

in an Oracle database can be accessed simultaneously on a local desktop computer, through 

GCMRC’s web mapping applications, on a mobile device application, and through services to a 

remote computer. The effort devoted to building and improving upon this aspect of our data 

management capability will benefit most, if not all, projects and GCMRC as a whole.

Project Element 14.2.2. GIS Process and Data Set Documentation 

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Timothy Andrews, IT Specialist, USGS, GCMRC

TBD, Geographer (GS-09), USG, GCMRC

Senior GIS staff members will also be in charge of writing USGS Open-File Reports and 

possibly other published works that document geospatial data sets, GIS processes and other GISrelated applications developed for GCMRC. These published reports would follow the USGS 

peer and policy review process and provide the necessary, citable building blocks for other, more 

scientifically rigorous manuscripts developed by other projects. Currently, a need exists for 

researchers to be able to cite some of our most basic data sets, such as the GCMRC river mile 

system, within their own manuscripts.

Outcomes and Products – FY15

• The GCMRC Centerline and River Mileage Reference System. A published data series 

report on the methods and processes used to develop this system and the associated cross 

reference work with other known mile systems used for the Colorado River between 

Lake Powell and Lake Mead.

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Outcomes and Products – FY16

• The GCMRC Colorado River Map Book. A data series/map series publication of 

GCMRC’s most commonly used river map book developed by GIS staff as a field 

reference for scientific work conducted on the Colorado River in Grand Canyon. The 

map book to be published will contain many of GCMRC’s geospatial data sets including 

most recent available overflight imagery (May 2013), GCMRC’s river mile system, 

monitored and National Park System river campsites, river rapids, place names, and 

tributaries of the Colorado River. Peer and policy reviews will be required prior to 

making this mapping product more widely available.

Outcomes and Products – FY17

• The GCMRC Colorado River Fish Sampling Cross Reference System. A data series 

report on the methods used to develop a fish sampling system currently used by all 

mainstem sampling efforts, and how the cross reference relationships were built to join 

previously collected fish monitoring data associated with mainstem sampling.

Project Element 14.3.1. Access to Geospatial Data Holdings – The Geospatial Portal 

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Timothy Andrews, IT Specialist, USGS, GCMRC

TBD, Geographer (GS-09), USG, GCMRC

Along with the strides made in developing an enterprise-level GIS at GCMRC, new GIS 

services leveraging the Oracle Spatial Database have been deployed both internally for desktop 

GIS users and through GCMRC’s public-facing website to provided better access to more 

geospatial data holdings than ever before (Fig. 4). How geospatial data are stored and served is 

intimately tied to how users will access these data sets. Perhaps the most powerful aspect of 

using GIS services for disseminating data is the flexibility in how data can be packaged (a single 

service for an individual data set, multiple services containing many data sets within one map, 

time-enabled services, 3D services, etc.) and how these services can be consumed (desktop 

mapping applications, web page maps, website applications, mobile device applications, etc.).

Geographic Information Systems services are the new currency for sharing geospatial data, and 

providing a single website for accessing these services is the next logical step for improving 

access to GCMRC’s geospatial data holdings.

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Figure 4. GCMRC’s interactive campsite and sandbar site map with integrated photo viewer. Users can query campsite and 

sandbar site data sets, view related attributes, and launch available photo collections that offer thousands of on-site and 

remote camera photographs.

In 2014, a beta version Geospatial Portal is being designed and built that will streamline 

access to many of GCMRC’s most frequently used and requested geospatial data sets.

Ultimately, the Geospatial Portal will provide access to all of GCMRC’s finished geospatial 

products. The Geospatial Portal builds on the existing Oracle-ESRI system architecture currently 

used by GCMRC for creating and sharing GIS Services, and so many of the components needed 

for the Geospatial Portal are already in place. The portal will provide access to maps, data sets, 

metadata, applications and other associated data through an organized, searchable interface.

Services accessible through the portal will range from a basic map of where GCMRC projects 

conduct their field work to an application with interactive tools for analyzing sandbar changes 

over time to a map service that allows researchers to create and print their own field maps.

Ultimately, GCMRC project leads and outside cooperators will be able to share data through 

this system, pushing the Geospatial Portal beyond just a content delivery system into a truly 

collaborative tool. While it is anticipated that a development version of the Geospatial Portal will 

be available in FY15, it is likely that populating the portal with content will be an ongoing 

activity. Benchmarks for what is made available through the Geospatial Portal will be addressed 

as project-specific geospatial data sets are finalized.

 

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Project Element 14.3.2. Access to Geospatial Data Holdings – ESRI’s ArcGIS Online 

Thomas M. Gushue, GIS Coordinator, USGS, GCMRC

Timothy Andrews, IT Specialist, USGS, GCMRC

TBD, Geographer (GS-09), USG, GCMRC

In FY13-14, GCMRC’s GIS staff began using ESRI’s online portal service for disseminating 

data to a much wider audience than ever before. This service, ArcGIS Online, has quickly 

become one of the most used geospatial content delivery systems available on the web. There are 

currently several GCMRC applications and data sets available through this online system (see 

Data Products section). In FY15-17, we plan to expand on the data made available to the public 

through this service. 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.

D.2 Personnel and Collaborations 

The personnel required for this project includes two full-time senior (GS-12) GIS 

professionals and one full-time junior-level (GS-09) GIS professional. Geospatial data 

processing and analysis tasks performed specifically for other project elements are described and 

budgeted within those project descriptions (see Table 1 below for a listing of those project 

elements). Additionally, one half-time junior-level (GS-09) GIS professional will be assigned to 

GIS Services and Support project elements (14.2.2. and 14.3.2.). 

D.3 Deliverables 

See “Outcomes and Products” in Project Element 14.2.2.

E. Productivity from Past Work (during FY 13/14) 

E.1. Data Products 

List of existing Products (from FY13-14)

Web Mapping Applications and Services available on GCMRC’s website 

Maps and Data Portal: http://www.gcmrc.gov/dasa/ (Fig. 5)

• GCMRC Interactive Campsite and Sandbar Map with Photo Viewer: 

http://www.gcmrc.gov/gis/silvermap1.aspx (requires Microsoft Silverlight)

• GCMRC Campsite Atlas Viewer: http://www.gcmrc.gov/gis/silveratlas1.aspx (requires 

Microsoft Silverlight)

• Grand Canyon River Campsites Tour: http://www.gcmrc.gov/gis/camptour/index.html 

(multiplatform, works on Windows, Mac, iOS, Android operating systems)

• Photo Viewer application: http://www.gcmrc.gov/gis/silverimage1.aspx (view thousands 

of sandbar and campsite photos, requires Microsoft Silverlight)

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• Dual Photo Viewer application: http://www.gcmrc.gov/gis/silverdualpivot.aspx 

(view thousands of sandbar and campsite photos side-by-side for comparison, 

requires Microsoft Silverlight)

Figure 5. Sample image from GCMRC’s website showing the Maps and Data Portal page.

Availability of GCMRC data and services on ESRI’s http://www.arcgis.com/home/

• Digital imagery of the Colorado River corridor between Glen Canyon Dam and Lake 

Mead (2002, 2005, and 2009)

• 10-meter Digital Elevation Model (DEM) of the Grand Canyon basin

• Fine-grained Integrated Sediment Team (FIST) reach-based full channel topography 

(2000 – 2005)

• Sandbar deposition map tour web application following the HFEs of 2012 and 2013

• Campsite atlas map tour web application

• Grand Canyon base layers web mapping application

E.2. Presentations at GCDAMP meetings 

Development of a new web mapping and photo viewer application for the Grand Canyon 

Monitoring and Research Center, Poster presentation at GCDAMP Technical Work Group 

meeting, Phoenix, AZ, January 28, 2014.

Extending sandbar monitoring back in time using photogrammetry, digital terrain extraction, and 

orthorectification of historical aerial imagery, Grand Canyon, Arizona, Poster presentation at 

GCDAMP Technical Work Group meeting, Phoenix, AZ, January 28, 2014.

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Low flows in Glen Canyon: preliminary geomorphic analysis of the potential effects on fish and 

food base, Presentation by T.S. Melis and others, at GCDAMP Technical Work Group meeting, 

Phoenix, AZ, January 28, 2014.

Preliminary low-flows study in the Lees Ferry tailwater below Glen Canyon Dam, Poster 

presentation at GCDAMP Technical Work Group meeting, Phoenix, AZ, January 28, 2014.

E.5. Presentations at professional meetings 

Development of a new web mapping and photo viewer application for the Grand Canyon Monitoring and 

Research Center, Poster presentation at ESRI UC Conference, July 2013, San Diego, CA.

F. Budget 

Project Element 14.1.1. 

Geospatial Data Analysis

Project Element 14.2.1. 

Geospatial Data Management

Project Element 

14.2.2. GIS Process and 

Data Set 

Documentation

Salaries na Salaries $35,226 Salaries $69,955

Traveling and Training Traveling and Training Traveling and Training

Operating Expenses $14,108 Operating Expenses $500 Operating Expenses $2,000

Logistics Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

Cooperators (nonUSGS)

USGS Cooperators USGS Cooperators USGS Cooperators

USGS Burden $2,257 USGS Burden $5,716 USGS Burden $11,512

Total $16,365 Total $41,442 Total $83,467

Project Element 14.3.1. 

Access to Geospatial Data 

Holdings – The Geospatial 

Portal

Project Element 14.3.2. 

Access to Geospatial Data 

Holdings – ESRI’s ArcGIS 

Online

Salaries $61,982 Salaries $4,155

Traveling and Training $4,000 Traveling and Training

Operating Expenses $800 Operating Expenses

Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators USGS Cooperators

USGS Burden $10,685 USGS Burden $665

Total $77,467 Total $4,820

FY 2015

FY 2015 Project 14 Gross Totals: $223,561

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Project Element 14.1.1. 

Geospatial Data Analysis

Project Element 14.2.1. 

Geospatial Data Management

Project Element 

14.2.2. GIS Process and 

Data Set 

Documentation

Salaries Salaries $37,968 Salaries $70,265

Traveling and Training Traveling and Training $2,000 Traveling and Training

Operating Expenses $10,690 Operating Expenses $500 Operating Expenses $4,000

Logistics Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

Cooperators (nonUSGS)

USGS Cooperators USGS Cooperators USGS Cooperators

USGS Burden $2,352 USGS Burden $8,903 USGS Burden $16,339

Total $13,042 Total $49,371 Total $90,604

Project Element 14.3.1. 

Access to Geospatial Data 

Holdings – The Geospatial 

Portal

Project Element 14.3.2. 

Access to Geospatial Data 

Holdings – ESRI’s ArcGIS 

Online

Salaries $64,673 Salaries $0

Traveling and Training $4,000 Traveling and Training

Operating Expenses $800 Operating Expenses

Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators USGS Cooperators

USGS Burden $15,284 USGS Burden

Total $84,757 Total $0

FY 2016

FY 2016 Project 14 Gross Totals: $237,774

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Project Element 14.1.1. 

Geospatial Data Analysis

Project Element 14.2.1. 

Geospatial Data Management

Project Element 

14.2.2. GIS Process and 

Data Set 

Documentation

Salaries Salaries $35,876 Salaries $68,818

Traveling and Training Traveling and Training Traveling and Training

Operating Expenses $10,690 Operating Expenses $500 Operating Expenses $4,000

Logistics Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

Cooperators (nonUSGS)

USGS Cooperators USGS Cooperators USGS Cooperators

USGS Burden $2,993 USGS Burden $10,186 USGS Burden $20,389

Total $13,683 Total $46,562 Total $93,207

Project Element 14.3.1. 

Access to Geospatial Data 

Holdings – The Geospatial 

Portal

Project Element 14.3.2. 

Access to Geospatial Data 

Holdings – ESRI’s ArcGIS 

Online

Salaries $74,613 Salaries $0

Traveling and Training $4,000 Traveling and Training $0

Operating Expenses $800 Operating Expenses $0

Logistics Logistics

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators USGS Cooperators

USGS Burden $22,235 USGS Burden $0

Total $101,648 Total $0

FY 2017 Project 14 Gross Totals: $255,100

FY 2017 

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Table 1. A list of GIS planned support for FY15-17 Triennial Work Plan Number of Pay 

Periods

Project Title Name Project 

Number

GIS Staff Project Element Title FY15 FY16 FY17

Sandbars and Sediment 

Storage Dynamics

3.1.2 Tom Gushue, GS-12 Monitoring sandbars and shorelines above 

8,000 ft3/s by remote sensing

2 1 1

Sandbars and Sediment 

Storage Dynamics

3.1.2 Geographer, GS-09 Monitoring sandbars and shorelines above 

8,000 ft3/s by remote sensing

2 3 3

Sandbars and Sediment 

Storage Dynamics

3.1.4 Tom Gushue, GS-12 Analysis of historical images at select 

monitoring sites

4 4 4

Sandbars and Sediment 

Storage Dynamics

3.1 Tim Andrews, GS-12 Sandbar Monitoring 1 1 1

Connectivity along the 

fluvial-aeolian-hillslope 

continuum

4.2 Tim Andrews, GS-12 Monitoring of cultural sites in Grand and 

Marble Canyons

4 4 4

Foobase Monitoring and 

Research

5.1.1

5.2

Geographer, GS-09 Insect emergence in Grand Canyon via 

citizen science; Patterns and controls of 

aquatic drift

2 2 2

Foobase Monitoring and 

Research

5.2 Tim Andrews, GS-12 Patterns and controls of aquatic drift 4 4 4

Mainstem Colorado 

River humpback chub 

aggregations

6.1 Tom Gushue, GS-12 Monitoring humpback chub aggregation 

relative abundance and distribution

2 2 1

Mainstem Colorado 

River Humpback Chub 

Aggregations

6.1

6.2

6.7

Geographer, GS-09 Mainstem Colorado River humpback chub 

aggregations and fish community dynamics 

(four elements supported)

1 2 2

Mainstem Colorado 

River Fish Community 

Dynamics

6.4 Geographer, GS-09 System-wide Electrofishing 1 2 3

Population Ecology of 

Humpback Chub in LCR

7.1 Geographer, GS-09 Annual spring/fall humpback chub 

abundance estimates in the lower 13.6 km 

of the LCR

1 2 3

Population Ecology of 

Humpback Chub in LCR

7.2

7.3

7.5

Geographer, GS-09 Juvenile Chub Monitoring in the mainstem 

near LCR; July LCR juvenile humpback chub 

marking; Food web monitoring in the Little 

Colorado River.

2 2 2

Population Ecology of 

Humpback Chub in LCR

7.3 Tim Andrews, GS-12 GIS software development for field mapping 

and data entry applications

2 2 2

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Population Ecology of 

Humpback Chub in LCR

7.4 Tim Andrews, GS-12 Remote PIT tag array monitoring 3 3 3

Rainbow Trout in Glen 

and Marble Canyons

9.1

9.2

Tom Gushue, GS-12 Lees Ferry Rainbow Trout Monitoring; 

Detection of Rainbow Trout Movement

2 2 1

Rainbow Trout in Glen 

and Marble Canyons

9.9 Tom Gushue, GS-12 Effects of High Flow Experiments on 

Rainbow Trout Population Dynamics

2 2 2

Rainbow Trout in Glen 

and Marble Canyons

9.1 9.9 Geographer, GS-09 Lees Ferry Rainbow Trout: Monitoring, 

Analysis, and Study Design; Effects of High 

Flow Experiments on Rainbow Trout 

Population Dynamics

1 1 1

Mapping Flow 

Inundation of Shoreline 

Areas and Bed Textures

10.1 Tom Gushue, GS-12 Refine Hummingbird Sidescan Sonar and 

other Channel Mapping Methods to Support 

Fish and Foodbase Research

3 4 4

Mapping Flow 

Inundation of Shoreline 

Areas and Bed Textures

10.1 Geographer, GS-09 Refine Hummingbird Sidescan Sonar and 

other Channel Mapping Methods to Support 

Fish and Foodbase Research

2 2 2

Riparian Vegetation 

Monitoring and Analysis

11.1 Geographer, GS-09 Project Element 11.1. Ground-based 

Vegetation Monitoring

1 0 0

GIS Services and 

Support

14.2.1 Tom Gushue, GS-12 Geospatial Data Management 4 5 5

GIS Services and 

Support

14.2.1 Geographer, GS-09 Geospatial Data Management 7 5 4

GIS Services and 

Support

14.2.2 Tom Gushue, GS-12 GIS Process and Data Set Documentation 5 4 4

GIS Services and 

Support

14.2.2 Geographer, GS-09 GIS Process and Data Set Documentation 6 5 4

GIS Services and 

Support

14.2.2 Tim Andrews, GS-12 GIS Process and Data Set Documentation 6 5 5

GIS Services and 

Support

14.2.2 SBSC Geographer, 

GS-09

GIS Process and Data Set Documentation 5 5 5

GIS Services and 

Support

14.3.1 

14.3.2

Tom Gushue, GS-12 Access to Geospatial Data Holdings 4 4 6

GIS Services and 

Support

14.3.1 

14.3.2

Tim Andrews, GS-12 Access to Geospatial Data Holdings 6 5 5

GIS Services and 

Support

14.3.1 

14.3.2

SBSC Geographer, 

GS-09

Access to Geospatial Data Holdings 8 8 8

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Project 15. Administration 

The USGS Administration budget covers salaries for the communications coordinator, the 

librarian, and the budget analyst for GCMRC, in addition to monetary awards for all GCMRC 

personnel. The vehicle section covers GSA vehicle costs including monthly lease fee, mileage 

costs, and any costs for accidents and damage. DOI vehicles are also included in this section of 

the budget to pay for vehicle gas, maintenance, and replacements costs. Leadership personnel 

covers salary for the GCMRC Chief and Deputy Chief, half the salary for two program 

managers, and some of the travel and training costs for these personnel. AMWG/TWG travel 

covers the cost of GCMRC personnel to travel to the AMWG and TWG meetings. SBSC 

Information Technology (IT) overhead covers GCMRCs IT equipment costs. Logistics base 

costs covers salaries and travel/training. These base costs also include a $35,000 contribution to 

the equipment and vehicles working capital fund. 

Budget 

Project Element 15.1. GCMRC 

Admin and Support

Project Element 15.2. GCMRC 

Logisitical Support

Salaries $ 550,376.00 Salaries $ 259,345.00 

Traveling and Training $ 30,000.00 Traveling and Training $ 5,000.00 

Operating Expenses $ 227,000.00 Operating Expenses $ - 

Logistics $ 20,000.00 Logistics $ - 

Cooperators (non-USGS) $ 79,000.00 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 134,750.00 USGS Burden $ 42,295.00 

Total $ 1,041,126.00 Total $ 306,640.00 

FY 2015

FY 2015 Project 15 Gross Totals: $1,347,766.00

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Project Element 15.1. GCMRC 

Admin and Support

Project Element 15.2. GCMRC 

Logisitical Support

Salaries $ 563,196.00 Salaries $ 264,515.00 

Traveling and Training $ 32,000.00 Traveling and Training $ 5,500.00 

Operating Expenses $ 226,500.00 Operating Expenses $ - 

Logistics $ 20,000.00 Logistics $ - 

Cooperators (non-USGS) $ 81,500.00 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 187,618.00 USGS Burden $ 59,403.00 

Total $ 1,110,814.00 Total $ 329,418.00 

Project Element 15.1. GCMRC 

Admin and Support

Project Element 15.2. GCMRC 

Logisitical Support

Salaries $ 578,094.00 Salaries $ 269,794.00 

Traveling and Training $ 34,000.00 Traveling and Training $ 6,000.00 

Operating Expenses $ 246,000.00 Operating Expenses $ - 

Logistics $ 20,000.00 Logistics $ - 

Cooperators (non-USGS) $ 84,000.00 Cooperators (non-USGS) $ - 

USGS Cooperators $ - USGS Cooperators $ - 

USGS Burden $ 248,398.00 USGS Burden $ 77,222.00 

Total $ 1,210,492.00 Total $ 353,016.00 

FY 2017 Project 15 Gross Totals: $1,563,496.00

FY 2016

FY 2016 Project 15 Gross Totals: $1,440,232.00

FY 2017 

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Appendices 

Appendix 1 references Project 1, which is funded through a different account.

Appendix 2-A summarizes the categories for the FY15 budget. A budget summary for each 

project element is described. The category for “non-USGS cooperators” includes universities, 

consulting firms, sister agencies of the federal government, and agencies of state government. 

The category for “USGS cooperators” includes various science centers of the USGS located in 

Arizona, California, and Wisconsin. Investigators and their affiliations are described in each 

project description.

Appendix 2-B summarizes the source of funding for each project element for the FY15 budget. 

Project elements for which no funding source has presently been identified are listed.

Appendix 2-C summarizes the categories for the FY16 budget. A budget summary for each 

project element is described. The category for “non-USGS cooperators” includes universities, 

consulting firms, sister agencies of the federal government, and agencies of state government. 

The category for “USGS cooperators” includes various science centers of the USGS located in 

Arizona, California, and Wisconsin. Investigators and their affiliations are described in each 

project description.

Appendix 2-D summarizes the categories for the FY17 budget. A budget summary for each 

project element is described. The category for “non-USGS cooperators” includes universities, 

consulting firms, sister agencies of the federal government, and agencies of state government. 

The category for “USGS cooperators” includes various science centers of the USGS located in 

Arizona, California, and Wisconsin. Investigators and their affiliations are described in each 

project description.

Appendix 3 lists logistics and schedules for all river trips and field work

 

431
Appendix 1 Project 1 

Project 1. Lake Powell and Glen Canyon Dam Release 

Water-Quality Monitoring 

A. Investigators 

William S. Vernieu, Hydrologist, U.S. Geological Survey, Grand Canyon Monitoring and 

Research Center

B. Project Summary This project conducts water-quality monitoring on Lake Powell and the Glen Canyon Dam 

tailwaters. The water-quality monitoring program consists of monthly surveys of the reservoir 

forebay and tailwater, as well as quarterly surveys of the entire reservoir, including the Colorado, 

San Juan, and Escalante arms. Water temperature, specific conductance, dissolved oxygen, pH, 

redox potential, turbidity, and chlorophyll concentration are measured throughout the water 

column at up to 30 sites (fig. 1) on the reservoir, with samples for major ionic constituents, 

nutrients, dissolved organic carbon, chlorophyll, phytoplankton, and zooplankton being collected 

at selected sites. The project also includes continuous monitoring of Glen Canyon Dam releases 

for water temperature, specific conductance, dissolved oxygen, pH, turbidity, and chlorophyll 

concentration and monthly sampling for major ionic constituents, nutrients, dissolved organic 

carbon, chlorophyll, phytoplankton, and zooplankton below the dam and at Lees Ferry.

The data collected by the project describe the current water quality of Glen Canyon Dam 

releases to the downstream ecosystem, as well as describe the current water-quality conditions 

and hydrologic processes in Lake Powell, which can be used to predict the quality of future 

releases from the dam. 

It is proposed that the existing water-quality monitoring program will continue through the 

FY15–17 period at its current level. The Seabird CTD instrument will continue to be used as the 

primary profiling device for reservoir stations. Minor changes may be made to the existing 

program in terms of number of stations sampled and the amount and type of samples collected. 

Recent data collected from the monitoring program will continue to be published and an 

interpretive synthesis of existing data will be developed for publication during the FY15–17 

period. 

Physical and chemical information from this program was published as Data Series Report 

DS-471 (Vernieu, 2013). An updated revision to this report is currently in development. 

Biological data is contained in a separate data series report, currently in review. All information 

from this program is currently stored in the Microsoft Access water-quality database (WQDB).

It is also proposed that a system for online data access and dissemination will be developed 

during this time. This will involve migration of the current WQDB database into an Oracle 

database to enhance online data availability. A web site will also be developed that will allow 

access to currently available data and the interactive display of various graphic products 

depicting summarized data collected by the program. Some aspects of data management and the 

development of visualization tools will be made in collaboration with the Wisconsin Science 

Center and Center for Integrated Data Analytics.

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Figure 3. Lake Powell water-quality monitoring locations.

The USGS Grand Canyon Monitoring and Research Center (GCMRC) will work 

collaboratively with the Bureau of Reclamation (BOR) in efforts to enhance simulation modeling 

of Lake Powell Reservoir water quality and limnology. Modeling will utilize the CE-QUAL-W2 

model, a 2D water quality and hydrodynamic model, currently maintained by BOR. This model 

is used to project Glen Canyon Dam release temperatures, and will be enhanced to answer 

various research questions relating to the fate of inflow currents, effects of reservoir drawdowns, 

and dissolved oxygen dynamics in the reservoir. 

C. Background

C.1. Scientific Background 

Lake Powell is formed by impoundment of the Colorado River by Glen Canyon Dam, which 

was completed in 1963 and receives the combined inflows of the Colorado, Green, San Juan, 

Escalante, and Dirty Devil rivers. The reservoir is stratified vertically according to density into 

different layers with varying water-quality characteristics. This stratification is the primary 

determinant of the quality of water released from Glen Canyon Dam and also affects physical, 

chemical, and biological characteristics of other portions of the reservoir. 

Two main mixing processes take place in Lake Powell. Convective mixing is the cooling of 

surface waters in winter months, which increase in density and mix with deeper waters in the 

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upper layers of the reservoir. This results in a well-mixed surface layer, or epilimnion, that 

extends to the penstock withdrawal zone in early winter and begins to influence Glen Canyon 

Dam releases, resulting in the warmest water released from the dam. Advective mixing results 

from the horizontal flow of water through the reservoir. Seasonal differences in the density of 

inflow currents determine the depth at which this water moves through the reservoir and its 

interaction with existing reservoir waters. The largest volume of water enters the reservoir from 

spring snowmelt runoff and represents the water with the least density entering the reservoir. 

This runoff plume travels through the reservoir near the surface and influences the most 

biologically active layers of the reservoir. In contrast, winter inflows represent water of the 

greatest density entering the reservoir and plunge to deeper depths as they enter the reservoir. 

When densities are sufficient to cause a bottom underflow throughout the length of the reservoir, 

this fresher water displaces older water in the deepest portions of the reservoir upward. When 

winter inflows are of insufficient density to travel as a bottom underflow, they flow into 

intermediate layers of the reservoir and leave the deepest portions of the reservoir stagnant, 

which can lead to a loss of dissolved oxygen. The conditions that result in a bottom underflow, 

as opposed to an interflow, are currently poorly understood.

Throughout the history of Lake Powell, there have been several extended drought periods 

that have been characterized by lower inflow volumes to the reservoir, compared to reservoir 

release volumes, resulting in a reduction in reservoir storage and a drawdown of surface 

elevations. Through most of the past decade, the Colorado River basin has experienced drought 

conditions, which resulted in the drawdown of the reservoir to a minimum of 3,555 ft in 2005. 

This resulted in the warmer surface layers being closer to the penstock withdrawal elevation and 

release temperatures increased to a maximum of 16°C in October 2005, more than 6°C above 

normal for that period. Release temperatures have been above normal from 2003 through 2013 as 

the reservoir remained at elevations below 3,640 ft, with the exception of 2011 in which the 

reservoir reached an elevation of 3,660 ft. In the spring of 2014, Lake Powell reached a surface 

elevation of 3,575 ft, its second lowest elevation since the reservoir first filled in 1980. Increased 

temperatures and possible reductions in dissolved oxygen concentrations in Glen Canyon Dam 

releases are expected in the fall of 2014.

Lake Powell receives an average of approximately 30,000 acre feet of sediment per year 

(Ferrari, 1986), most of which forms deltaic sediment deposits in the inflow areas of the 

reservoir. As reservoir elevations fluctuate, these deposits are resuspended and moved further 

downstream into the reservoir. Because of oxygen demand from decaying organic matter in the 

delta sediments, inflows traveling through the exposed delta become depleted in oxygen 

concentrations. With low reservoir elevations, these hypoxic waters can influence dam releases, 

which can cause adverse conditions in the aquatic ecosystem below Glen Canyon Dam.

Reservoir drawdown may also cause the release of nutrients from deltaic deposits and may 

act to enhance the biological characteristics of the reservoir. If further reductions to reservoir 

inflows occur in the future in response to a changing climate, these reservoir drawdown 

scenarios may become more common. An increased understanding of the relative effects of 

various factors such as reservoir elevation, inflow volume, age and oxygen demand of delta 

sediments on Glen Canyon Dam releases would be beneficial predicting and mitigating adverse 

effects to the downstream ecosystem.

As delta deposits are resuspended, they are also redeposited as they enter the reservoir, 

resulting in the overall movement of the sediment deltas farther downstream under drawdown 

conditions. Although the 2014 low reservoir elevation of 3,575 ft was approximately 20ft higher 

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than its 2005 low elevation of 3,555 ft, sediment deltas extended 2.5, 1.4, and 0.5 km farther 

downstream on the Colorado, San Juan, and Escalante arms of the reservoir, respectively, than 

they did in 2005. In some areas of the reservoir, major landslide deposits in the main channel of 

the reservoir can act as underwater dams that block sediment from moving further downstream.

C.2. Management Background 

BOR initiated a water-quality monitoring program on Lake Powell starting in 1964, which 

has continued to the present, to gather information to describe water-quality conditions and to 

observe changes in water quality as the reservoir filled and matured. Four distinct phases of 

monitoring activity have been identified, based on sampling frequency, spatial resolution of 

measurements, and changes in instrumentation.

Studies related to Lake Powell were conducted in the 1970s by educational consortiums and 

Federal and State agencies on topics that include sedimentation, circulation patterns, traceelement chemistry, remote sensing, and public-health issues (Potter and Drake, 1989). Various 

agencies and institutions have conducted additional research and monitoring during Lake 

Powell’s recent history (Hart and Sherman, 1996; Marzolf, 1998; Hart, and others, 2005).

Since 1996, the Lake Powell water-quality monitoring program has been conducted by 

GCMRC. While coordinating with investigators and information needs of the Glen Canyon Dam 

Adaptive Management Program (GCDAMP), funding for the Lake Powell monitoring program 

is provided solely by BOR, through Colorado River Storage Project power revenues. A five-year 

memorandum of agreement for Lake Powell monitoring was initiated between BOR and 

GCMRC for the period from January 1, 2014 to December 31, 2018.

C.3. Key Monitoring and Research Questions Addressed in this project 

Reservoir simulation modeling has the potential address several research questions related to 

reservoir hydrodynamics and the water quality in Lake Powell and Glen Canyon Dam releases. It 

is now being used to predict temperatures of Glen Canyon Dam releases for the Long-Term 

Experimental and Management Plan (LTEMP) Environmental Impact Statement currently in 

development. However, additional development of the model is possible to provide better 

predictive capabilities earlier in time with improved inflow and meteorological monitoring. The 

CE-QUAL-W2 model has the capabilities to model dissolved oxygen concentrations, as well as 

other parameters such as nutrients and plankton, but the model has not been calibrated to do so. 

Improvement of inflow and meteorological monitoring and calibrations of the model for 

dissolved oxygen, nutrients, and plankton will improve the model’s effectiveness.

One of the most important processes to maintaining dissolved oxygen concentrations in the 

deepest portions of the reservoir is the travel of high density water currents through the reservoir 

during the winter. Normally, winter inflows are of sufficient density and volume to travel along 

the bottom of the reservoir and reach the dam in the early spring. This displaces pre-existing 

water in the hypolimnion upward for entrainment in dam releases and freshens the water in the 

deepest portion of the reservoir. However, in some years, the inflows are not of sufficient density 

to flow along the entire bottom of the reservoir and may travel through the reservoir in 

intermediate layers, leaving deeper portions of the reservoir stagnant and hypoxic. The 

conditions that dictate the fate of this inflow current are poorly understood at present. Simulation 

modeling of various winter inflow scenarios may be beneficial in identifying what factors are 

most important in determining the fate of these inflow currents.

Reproducing populations of quagga mussels (Dreissena rostriformis bugensis) have now 

been identified in Lake Powell. Subsequent monitoring of plankton populations will provide an 

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excellent opportunity to determine the effects of this invasion on the biological resources of Lake 

Powell by comparison to the existing pre-invasion dataset of plankton abundance and community 

structure. A compilation of biological data through 2009 is slated for publication in 2014. In 

addition, a contract is now in place for the analysis of a large backlog of plankton samples 

collected through 2014. These analyses are expected to be completed by early 2015. Data from 

these analyses will be incorporated into the WQDB database and published as part of an annual 

comprehensive data report, which will combine the biological data with existing chemical and 

physical data. This information will also be available through interactive online queries once the 

Lake Powell portion of the GCMRC website is developed.

As the reservoir ages, the major tributaries of the Colorado, San Juan, and Escalante rivers 

continue to add sediment and reduce capacity of the reservoir with most sedimentation occurring 

in the inflow areas of the tributary arms as delta deposits. Reservoir drawdown processes 

remobilize these deposits, moving them further downstream in the reservoir basins. Large 

landslide deposits are present in the major tributary arms of the reservoir and can act to prevent 

further downstream movement of sediment. They can also cause localized water-quality 

problems in some areas of the reservoir. Two large landslide deposits in the Escalante arm of the 

reservoir are now, acting as underwater weirs, and limit hypolimnetic circulation, above these 

areas. This phenomenon results in low dissolved oxygen concentrations and presents an 

opportunity for simulation modeling to replicate these conditions and identify factors that 

promote or mitigate the development of these conditions.

D. Proposed Work D.1. Project Elements 

Monitoring

It is proposed the Lake Powell monitoring program continue in its present structure, consisting of 

monthly surveys of the reservoir forebay and tailwater, as well as quarterly surveys of the entire 

reservoir, including the Colorado, San Juan, and Escalante arms. Depth profiles of water 

temperature, specific conductance, dissolved oxygen, pH, oxidation-reduction potential, 

turbidity, and chlorophyll concentration are measured throughout the water column at up to 30 

sites (fig. 1) on the reservoir, with samples for major ionic constituents, nutrients, dissolved 

organic carbon, chlorophyll, phytoplankton, and zooplankton being collected at selected sites. 

Continuous monitoring of Glen Canyon Dam releases for water temperature, specific 

conductance, dissolved oxygen, pH, turbidity, and chlorophyll concentration and monthly 

sampling for major ionic constituents, nutrients, dissolved organic carbon, chlorophyll, 

phytoplankton, and zooplankton below the dam and at Lees Ferry, will also be maintained.

 

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Data Access and Availability 

The development of a website with online data access capabilities is a necessary component 

of the Lake Powell monitoring program. Data are already stored effectively in a Microsoft 

Access database, have been published as a USGS Data Series Report, and are available for 

download in database and csv format. However, the ability to query selected data, view graphical 

analyses of these queries, and server other products through an interactive web-based interface is 

currently lacking. It is proposed that a system with these capabilities be developed and 

implemented early in the proposal period.

This project would first entail migration of the existing database to an Oracle-based database 

so that it would be for use by GCRMC staff to provide functionality equal to, or better than the 

existing database system. Since the existing database is already normalized and fully functional 

migration is expected to be fairly straightforward and can be accomplished in-house with 

collaboration provided by the USGS Center for Integrated Data Analytics (CIDA). Migration 

would consist of the following steps:

1. transferring the contents of each table in the database

2. migrating existing queries, data-entry forms, and reports

3. establishing procedures for incorporation of new data by manual or automated methods

4. developing interfaces to various analytical software tools such as SAS, Surfer, Arc Map, 

and Microsoft Office products

5. testing and quality assurance verification

To facilitate online access by stakeholders, managers, and other interested users, a website 

will also be developed that would serve as a primary point of access for information relating to 

the Lake Powell water-quality monitoring program. This site would allow interactive access to 

the database in the form of a map-based query system that would serve data from the various 

components of the monitoring program based on selected locations and time ranges. From these 

queries, users would be able to retrieve tabular data, statistical summaries of these data, and 

graphical depictions of depth profiles and the results of chemical and biological sample analyses 

at various time scales ranging from recent data to the entire historical record. 

Data products would include summary graphs and tables showing Lake Powell reservoir 

elevations and 24-month projections, Glen Canyon Dam release water quality, selected reservoir 

depth profiles, and isopleth figures displaying temperature, conductivity, dissolved oxygen or 

other parameters for the entire reservoir at a single point in time or as a time series for a given 

station. 

At its full development, data from other sources would be available on the website, 

including:

1. reservoir elevation and storage information for other upper and lower Colorado River 

Basin reservoirs provided by BOR

2. streamflow and water-quality information for inflows from tributaries to Lake Powell

from the USGS NWIS system

3. other Lake Powell data collected outside the existing GCMRC monitoring program

4. water-quality information collected on other reservoirs such as Lake Mead, Flaming 

Gorge, Navajo, and other reservoirs provided by BOR, Southern Nevada Water 

Authority, and other agencies or academic institutions.

437
5. links to other data sources and relevant publications.

The web interface to the data would be accomplished by a combination of in-house work and 

assistance from the USGS Center for Integrated Data Analytics project will be accomplished inhouse, with assistance from CIDA. CIDA has developed similar applications for the GCMRC 

Sandbar and Sediment Storage (Project A) and 

Streamflow, Water Quality, and Sediment programs. Currently there is a sub-allocation of 

funding to the Wisconsin Science Center for the work of Dale Robertson of approximately 

$30,000 per year. This funding could be used for initial development of the web interface, 

depending on the actual distribution of work between CIDA and GCMRC.

Modeling

Simulation modeling of Lake Powell water quality and hydrodynamic patterns is currently 

being conducted by BOR's Upper Colorado Regional Office using the Army Corps of Engineers 

CE-QUAL-W2 model. The CE-QUAL-W2 model is a two-dimensional (longitudinal and 

vertical), laterally averaged, finite-difference water-quality and hydrodynamic model for rivers, 

estuaries, lakes, reservoirs and river basin systems. It was originally known as LARM (Laterally 

Averaged Reservoir Model), developed by Edinger and Buchak (1975). In its early stages, The 

LARM model was applied to Lakes Powell and Mead, (Edinger and Buchak, 1982; Edinger and 

others, 1984). Current model release enhancements have been developed under research 

contracts between the Army Corps of Engineers and Portland State University under supervision 

of Dr. Scott Wells (2000). Williams (2007) applied the CE-QUAL-W2 model to Lake Powell 

and developed an initial dissolved oxygen calibration for the model.

GCMRC provides data and collaboration with the development of the model for calibration 

and verification. The model has been calibrated and verified to simulate historical patterns of 

temperature and salinity in Glen Canyon Dam releases. Dissolved oxygen is also being 

simulated; however, some additional effort is needed for final calibration and verification. This 

model can be used to synthesize data for periods in which regular monitoring was not conducted 

and to simulate the effects of various hypothetical operational, hydrological, and climatological 

scenarios on historical patterns. It is also used to provide predictions of future temperature and 

dissolved oxygen patterns in Glen Canyon Dam releases. One major shortcoming of the model's 

predictive capabilities is the lack of adequate input data for inflow water quality and 

meteorological conditions in the upstream portion of the reservoir. The error in predictive 

capability decreases substantially with the input of data from reservoir monitoring in the early 

summer.

Opportunities exist for further understanding of reservoir processes by model development 

and enhancement. The use of this model, calibrated for temperature, nutrients, and biological 

components, to reconstruct historical conditions, project future hydrological and climatic 

scenarios, and simulate the response of the system to hypothetical reservoir operations could help 

to answer a variety of research questions and gain further understanding of the various 

hydrodynamic, chemical, biological, and mixing processes in the reservoir.

GCMRC will work on a collaborative basis with BOR to calibrate the model for dissolved 

oxygen, nutrient dynamics, and biological responses under a collaborative system in which 

current capabilities of the CE-QUAL-W2 model are maintained, while the research-related 

capabilities of the model, such as the forecasting of low dissolved oxygen concentrations in Glen 

Canyon Dam releases under reservoir drawdown and identifying factors that affect the fate of 

438
inflow currents. It is proposed the model be maintained for its current purposes by BOR, with 

further development by GCMRC, a post-doctoral fellow, or an outside contractor, such as Ed 

Buchak, who has performed previous work for BOR.

Biological Data Analysis

As data from a backlog of plankton samples become available within the next year, a 

complete history of Lake Powell plankton data, including the initial stages of a quagga mussel 

invasion, will become available for analysis. When complete, it is proposed that the biological 

data be incorporated in regular reporting with physical-chemical data. An analysis of these data 

would include identifying trends in biomass and community structure of zooplankton and 

phytoplankton populations and identifying potential factors that affect these populations.

Sediment Delta Monitoring

Since 1998, longitudinal sonar depth measurements of the sediment deltas in Lake Powell 

tributaries have been recorded on thermal chart paper, in conjunction with quarterly reservoir 

water-quality surveys. Digitization of these charts yields a longitudinal profile of the elevation of 

the sediment delta with respect to distance along the original river channel. Collectively, these 

profiles provide a history of Lake Powell sediment deposition during this period, over a range of 

reservoir elevations and inflow volumes. Information from this record demonstrates sediment 

transport and deposition processes as affected by inflow currents, underwater landslides, and 

other channel obstructions and can help to explain unusual water-quality conditions observed in 

portions of the reservoir.

Digitization of these profiles was initiated in 2012, with the aid of a temporary student intern. 

Progress has stalled since the departure of that intern and lack of additional staffing. With the 

addition of a technician to the GCMRC staff, it is proposed that remaining profiles be digitized, 

compiled, and published as a complete historical record. 

D.2 Personnel and Collaborations 

Funding for the Lake Powell water-quality monitoring program is provided directly by BOR; 

no GCDAMP funds are used for this project. In addition to direct funding, BOR also provides 

field support staff for quarterly reservoir surveys, chemical sample analysis through its Lower 

Colorado Regional Laboratory, plankton sample analysis through contract, and maintains the 

Seabird SBE19plusV2 CTD profiling instrument. The National Park Service provides a 0.5 FTE 

field technician, also funded by BOR. GCMRC participates in the Lake Powell Cooperators 

Group, a group of federal, state, and academic researchers, tribal representatives, 

concessionaires, recreational organizations, and members of the general public with interests in 

scientific activities conduction on Lake Powell. The National Park Service hosts annual meetings 

of the Lake Powell Cooperators Group to present and discuss current monitoring activities and 

findings, and coordinate future activities.

Dale Robertson, of the USGS Wisconsin Science Center, has been collaborating with the 

Lake Powell program to assist with data interpretation and modeling and to develop an 

interpretive synthesis of the published data. This synthesis will describe the physical, chemical, 

and biological characteristics of Lake Powell and Glen Canyon Dam releases compared to 

climatological factors and various aspects of dam operations. Available meteorological, 

hydrological, and limnological data will be used to improve, document, and verify the existing 

CE-QUAL-W2 model for Lake Powell, in collaboration with BOR scientists. The model will 

439
then be used to better understand the changes that have occurred in Lake Powell, predict future 

changes in response to climate change, and verify interpretive hypotheses.

We propose to collaborate with the USGS Center for Integrated Data Analytics to assist with 

migration of the current database to an Oracle platform, to develop tools for data retrieval, 

summary, and analysis, and to develop a web-based interface to allow access to data and display 

of graphical products. In addition, GCMRC will become more closely involved with the USGS 

Community for Data Integration to share and integrate reservoir data management techniques 

with other reservoir monitoring programs.

GCMRC also plans to continue to work closely with Richard A. Wildman, currently serving 

as professor at Quest University Canada and previously a postdoctoral fellow and Harvard 

University Center for the Environment. GCMRC has provided field assistance, water quality 

data, and reviews for publications related to phosphorus release and sediment transport related to 

reservoir drawdown (Wildman and others, 2011; Wildman and Hering, 2011.)

Other potential collaborations include work with Kevin Speer, Professor of Physical 

Oceanography at Florida State University. He has proposed using Lake Powell as a testing site 

for the deployment of unmanned underwater profiling systems. BOR works closely with 

Brigham Young University on studies of some Utah reservoirs. GCMRC supported a study in 

August 2013 in which students used various locations in the Colorado River inflow area of Lake 

Powell for the deployment and refinement of sediment oxygen demand sensors.

D.3 Deliverables 

During FY15–17, an interpretive data synthesis report will be published to build on the 

monitoring data and provide insights into how climatological, meteorological, and hydrodynamic 

processes, as well as the operation of Glen Canyon Dam, affect inflow routing and stratification 

in the reservoir and the water quality of releases from Glen Canyon Dam. Each year, the DS-471 

report, “Historical Physical and Chemical Data for Water in Lake Powell and from Glen Canyon 

Dam Releases, Utah-Arizona, 1964–2012”, will be revised with final data from the previous 

year. After initial publication of the biological data report, these reports will be combined and 

revised annually. The existing WQDB database will be migrated to the Oracle platform, online 

access tools and automated statistical and graphical products will be developed, and a website 

will be developed to provide current conditions and historical data to the public in the form of 

graphical or statistical summaries. Other reports will be developed in future years describing 

water-quality changes in response to climatological factors, model development and verification, 

and application of modeling results to downstream resources.

E. Productivity from Past Work E.1. Data Products 

Products from the Lake Powell monitoring program include published reports, listed in the 

following section, the WQDB database, which is now available through online download, 

presentations at scientific meetings, presentations to the general public, and presentations or 

supporting data to the AMWG and TWG. Preliminary data from monitoring surveys are 

provided to BOR within one month of collection.

 

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E.2. Completed Publications 

Vernieu, W.S., 2013, Historical physical and chemical data for water in Lake Powell and from 

Glen Canyon Dam releases, Utah-Arizona, 1964–2012 (ver. 2.0, October 2013): U.S. 

Geological Survey Data Series 471, 23 p., http://pubs.usgs.gov/ds/471/.

Vernieu, W.S., and Anderson, C.R., 2013, Water temperatures in select nearshore environments 

of the Colorado River in Grand Canyon, Arizona, during the Low Steady Summer Flow 

experiment of 2000: U.S. Geological Survey Open-File Report 2013–1066, 44 p., 

http://pubs.er.usgs.gov/publication/ofr20131066.

Ross, R.P., and Vernieu, W.S., 2013, Nearshore temperature findings for the Colorado River in 

Grand Canyon, Arizona--Possible implications for native fish: U.S. Geological Survey Fact 

Sheet 2013-3104, 4 p., http://dx.doi.org/10.3133/fs20133104.

E.3. Publications in progress 

Vernieu, W.S., 2014, Biological data for water in Lake Powell and from Glen Canyon Dam 

releases, Utah-Arizona, 1991-2008: U.S. Geological Survey Data Series xxx (in review).

Vernieu, W.S., 2013, Historical physical and chemical data for water in Lake Powell and from 

Glen Canyon Dam releases, Utah-Arizona, 1964–2013 (ver. 3.0): U.S. Geological Survey 

Data Series 471, 23 p., http://pubs.usgs.gov/ds/471/. (revision for 2013).

E.4. Presentations at professional meetings 

11/7/2012 Presentation at North American Lake Management Society 32nd International 

Symposium titled “Data Management for Long-Term Water-Quality Monitoring in Lake 

Powell, Utah-Arizona, 1964–2011”.

11/8/2012 Presentation at North American Lake Management Society 32nd International 

Symposium titled “Historic Deltaic Sedimentation Patterns in Lake Powell, Utah-Arizona, 

1998-2011”.

3/11-13/2013 River Management Society Workshop – presentation cancelled because of 

sequester.

7/10/2013 Presentation at Museum of Northern Arizona’s Science Café lecture series on Lake 

Powell and Glen Canyon Dam Release Water-Quality Monitoring Program.

9/18/2013 Organized and led special symposium at 12th Biennial Conference of Science and 

Management on the Colorado Plateau at Northern Arizona University titled “Lake Powell 

after 50 Years – Patterns, Processes, and Predictions”. This session consisted of seven 

presentations relating to water-quality monitoring, simulation modeling, hydrodynamic 

processes, quagga mussel status, the Lake Powell sport fishery, contaminant monitoring, and 

sedimentation patterns.

9/19/2013 Presentation at Arizona Hydrological Society annual symposium in Tucson, AZ titled 

“Historic Deltaic Sedimentation Patterns in Lake Powell, Utah-Arizona, 1998-2011”.

9/20/2013 Interview with Eric Betz, Arizona Daily Sun reporter, for 9/20/2013 article on turbid 

releases from Glen Canyon Dam in late September (http://azdailysun.com/floods-turnpowell-discharge-murky/article_cfd87d70-2285-11e3-9c56-001a4bcf887a.html).

9/30/2013 Presentations to three middle and high school classes titled “Lake Powell and Glen 

Canyon Dam – Storing Water in Times of Drought” as part of Flagstaff Festival of Science 

in-school program.

 

441
F. References computational basis: Cincinnati, Ohio, prepared for U.S. Army Corps of Engineers, Ohio River 

Division, contract no. DACW27-74-C-0200.

Edinger, J.E., and Buchak, E.M., 1982, Development, verification and use of methods to model 

chemical and thermal processes for Lakes Mead and Powell, phase I--model evaluation and 

data analysis: Denver, Colo., prepared J.E. Edinger Associates, Inc. for U.S. Department of 

Interior, Bureau of Reclamation, 44 p.

Edinger, J.E., Buchak, E.M., and Merritt, D.M., 1984, Longitudinal-vertical hydrodynamics and 

transport with chemical equilibria for Lake Powell and Lake Mead, in French, R.H., ed., 

Salinity in watercourses and reservoirs--International Symposium on State-of-the-Art Control 

of Salinity, Salt Lake City, Utah, July 13-15, 1983, Proceedings: Butterworth Publishers, p. 

213-222.

Ferrari, R.L., 1988, 1986 Lake Powell survey: Denver, Colo., Bureau of Reclamation, report no. 

REC-ERC-88-6, 67 p. [Available from National Technical Information Service, Springfield, 

Va. as NTIS Report PB89-178818.]

Hart, R.J., and Sherman, K.M., 1996, Physical and chemical characteristics of Lake Powell at the 

forebay and outflow of Glen Canyon Dam, northeastern Arizona, 1990-91: U.S. Geological 

Survey Water-Resources Investigations Report 96-4016, 78 p., 

http://pubs.er.usgs.gov/publication/wri964016.

Hart, R.J., Taylor, H.E., Antweiler, R.C., Fisk, G.G., Anderson, G.M., Roth, D.A., Flynn, M.E., 

Peart, D.B., Truini, M., and Barber, L.B., 2005, Physical and chemical characteristics of 

Knowles, Forgotten, and Moqui Canyons, and effects of recreational use on water quality, 

Lake Powell, Arizona and Utah: U.S. Geological Survey Scientific Investigations Report 

2004-5120, 116 p., http://pubs.usgs.gov/sir/2004/5120/pdf/sir2004-5120.pdf.

Hueftle, S.J., and Vernieu, W.S., 1998, Assessment of impacts of Glen Canyon Dam operations 

on water quality resources in Lake Powell and the Colorado River in Grand Canyon--

unpublished draft report: Flagstaff, Ariz., U.S. Geological Survey, Grand Canyon Monitoring 

and Research Center, 77 p.

Jones, J., Kennedy, R.H., Nestler, J., Robertson, D., Ruane, R.J., and Schladow, S.G., 2001, 

Final report of the Protocol Evaluation Panel (PEP) for the Grand Canyon Monitoring and 

Research Center Integrated Water Quality Program (IWQP): Flagstaff, Ariz., 39 p. plus 

appendices. (Available at 

http://www.usbr.gov/uc/rm/amp/twg/mtgs/09mar16/Attach_11.pdf.)

Majeski, A.L., 2009, Fluvial systems tied together through a common base level--the 

geomorphic response of the Dirty Devil River, North Wash Creek, and the Colorado River to 

the rapid base level drop of Lake Powell: Logan, Utah State University, Ph.D. dissertation, 

191 p.

Marzolf, G.R., Hart, R.J., and Stephens, D.W., 1998, Depth profiles of temperature, specific 

conductance, and oxygen concentrations in Lake Powell, Arizona-Utah, 1992-1995: U.S. 

Geological Survey Open-File Report 97-835, 124 p.

Potter, L.D., and Drake, C.L., 1989, Lake Powell-Virgin flow by dynamo, University of New 

Mexico Press, 311 p.

Pratson, L., Hughes-Clarke, J., Anderson, M., Gerber, T., Twichell, D., Ferrari, R., Nittrouer, C., 

Beaudoin, J., Granet, J., and Crockett, J., 2008, Timing and patterns of basin infilling as 

documented in Lake Powell during a drought: Geology, v. 36, no. 11, doi: 10.1130/

G24733A.1, p. 843-846.

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Vernieu, W.S., 2013, Physical and chemical data for water in Lake Powell and from Glen 

Canyon Dam releases, Utah-Arizona, 1964-2012 (ver. 2.0, October 2013): U.S. Geological 

Survey Data Series 471, 23 p., http://pubs.usgs.gov/ds/471/.

Wells, S.A., 2000, Hydrodynamic and water quality river basin modeling using CE-QUAL-W2 

in Ibarra-Berastegic, G., Brebbia, C., and Zannetti, P., eds., Development and Application of 

Computer Techniques to Environmental Studies: WIT Press, Boston, 195-204.

Wildman, R.A., Pratson, L.F., DeLeon, M., and Hering, J.G., 2011, Physical, chemical, and 

mineralogical characteristics of a reservoir sediment delta (Lake Powell, USA) and 

implications for water quality during low water level: Journal of Environmental Quality, v. 

40, no. 2, p. 575-586.

Wildman, R.A., Jr., and Hering, J.G., 2011, Potential for release of sediment phosphorus to Lake 

Powell (Utah and Arizona) due to sediment resuspension during low water level: Lake and 

Reservoir Management, v. 27, no. 4, p. 365-375.

Williams, N.T., 2007, Modeling dissolved oxygen in Lake Powell using CE-QUAL-W2: Provo, 

Brigham Young University, M.S. thesis, 120 p.

Wurtsbaugh, W., Lay, C., Carlise, D., Huxol, C., Schaugaard, C., Clements, B., Beauchamp, D., 

1992, A trophic gradient analysis of Lake Powell during spring runoff 1992, Report to the 

Glen Canyon National Recreation Area: Watershed Sciences Faculty Publications, paper 517, 

Utah State University, 217 p.

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G. Budget 

Project 1 Project 1

Salaries $183,534 Salaries $187,205

Traveling and Training $8,700 Traveling and Training $8,961

Operating Expenses $40,340 Operating Expenses $41,550

Logistics Logistics

GIS/RS/Electronics support 

(includes burden)

GIS/RS/Electronics support 

(includes burden)

Cooperators (non-USGS) Cooperators (non-USGS)

USGS Cooperators $17,538 USGS Cooperators $18,064

USGS Burden $40,018 USGS Burden $56,271

Total $290,130 Total $312,051

Project 1

Salaries $190,949

Traveling and Training $9,230

Operating Expenses $42,796

Logistics

GIS/RS/Electronics support 

(includes burden)

Cooperators (non-USGS)

USGS Cooperators $18,606

USGS Burden $73,243

Total $334,824

FY 2017 Project 1 Gross Totals: $334,824

FY 2015

FY 2015 Project 1 Gross Totals: $290,130

FY 2016

FY 2016 Project 1 Gross Totals: $312,051

FY 2017 

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Appendix 2-A. Fiscal Year 2015 Budget 

(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

Burden Rate 16.000%

M 1

Lake Powell and Glen 

Canyon Dam Release WaterQuality Monitoring

$183,534 $8,700 $40,340 $0 $0 $20,343 $37,212 $290,129

1.2

Reservoir limnology and ecology 

monitoring and research science 

review palen

$20,000 $600 $20,600

1 Total $183,534 $8,700 $40,340 $0 $20,000 $20,343 $37,812 $310,729

M/R 2

Stream Flow, Water Quality, 

and Sediment Transport in 

the Colorado River 

Ecosystem

$619,000 $5,000 $50,000 $70,000 $0 $480,000 $119,040 $1,343,040 

3

Sandbars and Sediment 

Storage Dynamics

M 3.1.1

Monitoring sandbars using 

topographic surveys and remote 

cameras

$106,670 $2,000 $4,000 $26,568 $156,060 $48,000 $26,960 $370,258 

M 3.1.2

Monitoring sand bars and 

shorelines above 8000 ft3

/s by 

remote sensing

$103,477 $16,556 $120,033 

R 3.1.3

Surveying with a camera: rapid 

topographic surveys with digital 

images using structure-frommotion (SFM) photogrammetry

$18,724 $20,000 $3,596 $42,320 

M/R 3.1.4 Analysis of historical images at 

selected monitoring sites $15,979 $68,415 $4,609 $89,003 

M/R 3.2 Sediment storage monitoring $163,741 $2,000 $27,000 $29,679 $196,075 $41,469 $459,964 

R 3.3

Characterizing, and predictive 

modeling, of sand bar response at 

local and reach scales

$64,687 $25,000 $11,100 $100,787 

R 3.4

Connecting bed material 

transport, bed morphodynamics, 

and sand budgets in Grand Canyon

$35,000 $1,050 $36,050 

M 3.5 Control network and survey 

support $77,068 $1,900 $15,000 $15,035 $109,003 

3 Total $550,346 $5,900 $46,000 $56,247 $500,550 $48,000 $120,375 $1,327,418 

FY15

445
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

4

Connectivity along the 

Fluvial-Aeolian-Hillslope 

Continuum: Quantifying the 

Relative Importance of 

River-Related Factors that 

Influence Upland 

Geomorphology and 

Archaeological Site Stability

R 4.1

Quantifying connectivity along the 

fluvial-aeolian-hillslope continuum 

at landscape scales

$107,198 $9,000 $2,500 $75,035 $18,992 $212,725 

M 4.2 Monitoring of cultural sites in 

Grand and Glen Canyons $90,578 $157,500 $9,854 $39,692 $297,624 

4 Total $197,776 $9,000 $160,000 $0 $0 $84,889 $58,684 $510,349 

FY15

446
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

5 Food Base Monitoring and 

Research

5.1 Are aquatic insect diversity and 

production recruitment limited?

M 5.1.1 Insect emergence in Grand Canyon 

via citizen science $80,507 $350 $9,000 $3,807 $9,000 $15,256 $117,920

R 5.1.2

Quantifying the effects of 

hydropeaking on oviposition and 

egg mortality

$47,483 $700 $3,000 $26,648 $6,750 $12,655 $97,236

R 5.1.3 Synthesis of stressors and controls 

on EPT distributions $25,229 $350 $4,093 $29,672

R 5.1.4 Synthesis of the aquatic foodbase 

in western US tailwaters $25,229 $350 $4,093 $29,672

R 5.1.5 Natural history of oviposition for 

species present in Grand Canyon $12,615 $700 $3,000 $6,750 $2,813 $25,878

R 5.1.6

Laboratory studies on insect 

oviposition and egg mortality 

associated with changing water 

levels

$25,229 $700 $6,000 $5,109 $37,038

R 5.1.7

Comparative emergence studies in 

Upper Basin using citizen science 

light trapping

$39,450 $1,400 $6,000 $3,807 $8,105 $58,762

R 5.1.8 Natural history of oviposition for 

EPT via studies in the Upper Basin $12,615 $2,450 $3,000 $3,807 $3,500 $25,372

5.2

Patterns and controls of aquatic 

invertebrate drift in Colorado 

River tailwaters

M 5.2.1

Continue characterizing and 

monitoring drift and insect 

emergence in Glen Canyon

$36,407 $7,000 $1,500 $7,185 $52,092 

M 5.2.2

Continue natal origins drift 

monitoring in Glen, Marble, and 

Grand Canyons

$72,815 $1,000 $1,500 $12,050 $87,365 

R 5.2.3

Link drift at natal origins Project 

transects to channel bed shear 

stress

$9,102 $300 $250 $9,423 $1,544 $20,619 

R 5.2.4

Link invertebrate drift patterns to 

substrate conditions in Glen, 

Marble, and Grand Canyons

$9,102 $400 $250 $9,423 $1,560 $20,735 

R 5.2.5

Comparative longitudinal drift 

studies in Upper and Lower 

Colorado River Basin tailwaters

$54,611 $5,300 $1,500 $20,000 $46,800 $14,430 $142,641 

5.3 Primary Production Monitoring in 

Glen Marble and Grand Canyons

M 5.3.1 Synthesis and publication of Glen 

Canyon algae production $10,401 $13,500 $2,069 $25,970 

M 5.3.2 Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon $10,155 $1,000 $2,000 $2,105 $15,260 

R 5.3.3 Developing automated tools for 

estimating algae production $0 $0 

5 Total $470,950 $22,000 $37,000 $58,069 $82,800 $18,846 $96,567 $786,232

FY15

447
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

6

Mainstem Colorado River 

Humpback Chub 

Aggregations and Fish 

Commuity Dynamics

M 6.1

Mainstem Colorado River 

Humpback Chub aggregation 

monitoring

$56,000 $1,000 $6,100 $36,700 $100,000 $0 $18,968 $218,768 

R 6.2 Aggregation recruitment $34,800 $0 $6,400 $8,800 $25,000 $0 $8,750 $83,750 

R 6.3

Monitoring mainstem 

aggregations with PIT tag antennas 

(pilot)

$8,100 $0 $7,800 $0 $0 $0 $2,544 $18,444 

M 6.4 System Wide Electrofishing $31,900 $0 $8,100 $49,200 $175,000 $0 $19,522 $283,722 

R 6.5

Brown trout natal origins through 

body pigmentation patterns in the 

Colorado River

$0 $0 $600 $0 $15,000 $0 $546 $16,146 

R 6.6 Direct Mainstem Augmentation of 

Humpback Chub $4,000 $5,000 $790 $9,790 

M 6.7 Rainbow Trout Early Life Stage 

Survey $56,200 $3,900 $700 $5,600 $0 $0 $10,624 $77,024 

M 6.8 Lees Ferry Creel Survey $0 $0 $0 $0 $0 $0 $0 $0 

6 Total $191,000 $4,900 $29,700 $100,300 $320,000 $0 $61,744 $707,644 

FY15

448
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

7

Population Ecology of 

Humpback Chub in and 

around the Little Colorado 

River

M 7.1

Annual spring/fall humpback chub 

abundance estimates in the lower 

13.6 km of the Little Colorado 

River

$23,200 $0 $15,500 $90,800 $370,000 $0 $31,820 $531,320 

M 7.2

Juvenile chub monitoring in the 

mainstem near the Little Colorado 

River confluence

$93,600 $0 $8,900 $135,800 $215,000 $0 $44,578 $497,878 

R 7.3

July Little Colorado River juvenile 

humpback chub marking to 

estimate production and 

outmigration

$62,500 $4,000 $5,400 $24,800 $0 $0 $15,472 $112,172

M 7.4 Remote PIT tag array monitoring in 

the LCR $34,700 $3,500 $3,600 $5,000 $0 $6,838 $53,638 

R 7.5 Food web monitoring in the Little 

Colorado River $114,800 $2,000 $1,000 $4,200 $0 $0 $19,520 $141,520

R 7.6

Potential for gravel substrate 

limitation for humpback chub 

reproduction in the LCR

$5,400 $500 $1,000 $3,100 $0 $0 $1,600 $11,600 

R 7.7

Evaluate CO2 as a limiting factor 

early life history stages of 

humpback chub in the Little 

Colorado River

$53,500 $3,000 $18,000 $0 $0 $0 $11,920 $86,420 

M 7.8

Evaluate effects of Asian 

tapeworm infestation on Juvenile 

humpback chub

$11,000 $2,000 $1,500 $0 $0 $0 $2,320 $16,820 

R 7.9

Development of a non-lethal tool 

to assess the physiological 

condition of humpback chub in the 

Colorado and Little Colorado 

Rivers

$27,900 $1,500 $6,700 $0 $0 $0 $5,776 $41,876 

R 7.10 Humpback chub population 

modelling $82,000 $2,000 $100 $0 $0 $0 $13,456 $97,556

7 Total $508,600 $15,000 $61,600 $262,300 $590,000 $0 $153,300 $1,590,800

FY15

449
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

8

Management Actions to 

Increase Abundance and 

Distribution of Native Fishes 

in Grand Canyon

R 8.1 Efficacy and ecological impacts of 

BNT removal $49,900 $0 $2,800 $30,400 $0 $0 $13,296 $96,396 

M 8.2 Translocation and monitoring 

above Chute Falls $4,000 $0 $4,700 $7,200 $68,200 $0 $4,590 $88,690 

M 8.3

Fisheries Protocol Evaluation 

Panel (FY16 or FY17) $0 $0 $0 $0 $0 $0 $0 $0 

M 8.4 Invasive Species Surveillance and 

Response $0 $0 $0 $0 $0 $0 $0 $0 

R 8.5 Genetic Monitoring of Lower Basin 

Humpback Chub $0 $0 $0 $0 $0 $0 $0 $0

8 Total $53,900 $0 $7,500 $37,600 $68,200 $0 $17,886 $185,086

FY15

 

450
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

9

Understanding Factors 

Determining Recruitment, 

Population Size, Growth, 

and Movement of Rainbow 

Trout in Glen and Marble 

Canyons

R/M 9.1 Lees Ferry RBT; monitoring, 

analysis, and study design $32,000 $0 $0 $0 $0 $0 $5,120 $37,120 

R 9.2

Detection of RBT movement from 

upper Colorado River below GCD 

(NO)

$95,700 $0 $50,100 $127,400 $120,000 $0 $47,312 $440,512 

R 9.3

Exploring the mechanisms behind 

trout growth, reproduction, and 

movement in Glen and Marble 

Canyons using lipid (fat) reserves 

as an indicator of physiological 

condition

$48,500 $0 $40,000 $0 $0 $0 $14,160 $102,660 

R 9.4 Comparative study on the feeding 

morphology of drift feeding fish $72,100 $0 $2,400 $0 $0 $0 $11,920 $86,420 

R 9.5

Meta-analysis and the 

development of reactive distance 

relationships for encounter rate 

models 

$29,200 $2,500 $1,500 $0 $0 $0 $5,312 $38,512 

R 9.6

Lab studies to evaluate turbidity as 

a potential Glen Canyon Damoperations management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition on 

juvenile humpback chub

$27,500 $2,000 $2,500 $0 $0 $0 $5,120 $37,120 

R 9.7 Application of a bioenergetics 

model in a seasonally turbid river $53,800 $2,000 $1,500 $0 $0 $0 $9,168 $66,468 

R 9.8

Mechanisms that limit RBT and 

BNT growth in other western 

tailwater systems

$58,400 $2,500 $1,500 $0 $0 $0 $9,984 $72,384 

R 9.9

Contingency Planning for High 

Experimental Flows and 

Subsequent Rainbow Trout 

Population Management 

$12,500 $0 $28,000 $22,100 $0 $0 $10,016 $72,616 

R 9.10

Examining the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

$44,400 $0 $2,500 $0 $0 $0 $7,504 $54,404 

9 Total $474,100 $9,000 $130,000 $149,500 $120,000 $0 $125,616 $1,008,216 

FY15

 

451
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

R 10

Mapping and Assessment of 

Aquatic Habitats below Glen 

Canyon Dam 

$123,529 $5,000 $0 $0 $0 $0 $20,565 $149,094 

11

Riparian Vegetation Studies: 

Ground-based and 

Landscape-scale Riparian 

Vegetation Monitoring and 

Plant Response-Guild 

Research associated with 

Sandbar Evolution and 

Wildlife Habitat Analysis 

M 11.1 Ground-based vegetation 

monitoring $84,110 $1,500 $1,000 $48,908 $18,750 $22,245 $176,513

M 11.2

Periodic landscape scale 

vegetation mapping and analysis 

using remotely sensed data

$41,555 $2,000 $1,500 $0 $99,622 $10,197 $154,874

R 11.3

Influence of sediment and 

vegetation feedbacks on the 

evolution of sandbars in Grand 

Canyon since 1991

$71,011 $2,000 $1,000 $0 $7,627 $6,716 $12,071 $100,425

R 11.4 Linking dam operations to changes 

in terrestrial fauna $16,216 $2,500 $2,000 $20,000 $3,915 $44,631

M/R 11.5

Science Review Panel of Successes 

and Challenges in Non-native 

Vegetation Control in the 

Colorado River and Rio Grande 

Watersheds

$28,946 $0 $4,631 $33,577 

11 Total $241,838 $8,000 $5,500 $48,908 $145,999 $6,716 $53,059 $510,020 

R 12

Dam-Related Effects on the 

Distribution and Abundance 

of Selected CulturallyImportant Plants in the 

Colorado River Ecosystem 

R 12.1 Tribal workshop and analysis of 

cultural landscape change $19,647 $5,000 $2,000 $5,000 $15,000 $5,514 $52,161 

R 12.2

Tribal evaluations of cultural 

landscape changes $0 $0 

12 Total $19,647 $5,000 $2,000 $5,000 $15,000 $0 $5,514 $52,161 

FY15

 

452
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

13 Socio-economic Monitoring 

and Research

M/R 13.1

Economic Values of Recreational 

Resources Along the Colorado 

River – Grand Canyon Whitewater 

Floater and Lees Ferry Angler 

Values

$54,673 $5,000 $500 $0 $0 $0 $9,628 $69,801 

R 13.2

Tribal Values and Perspectives of 

Resources Downstream of Glen 

Canyon Dam

$0 $0 $0 $0 $0 $0 $0 $0 

R 13.3

Applied Decision Methods for the 

Glen Canyon Adaptive 

Management Plan

$64,093 $7,500 $500 $0 $22,500 $0 $12,210 $106,803 

13 Total $118,766 $12,500 $1,000 $0 $22,500 $0 $21,838 $176,604 

14

Geographic Information 

Systems, Services, and 

Support

$171,318 $4,000 $17,408 $0 $0 $0 $30,836 $223,562 

15 Administration and Support

15.1 GCMRC Admin and Support $550,376 $30,000 $227,000 $20,000 $79,000 $134,750 $1,041,126

15.2 GCMRC logistical support $259,345 $5,000 $42,295 $306,640

15 Total $809,721 $35,000 $227,000 $20,000 $79,000 $0 $177,045 $1,347,766

Total Lake Powell $183,534 $8,700 $40,340 $0 $0 $20,343 $37,212 $290,129

Total AMP $4,550,491 $140,300 $774,708 $807,924 $1,964,049 $638,451 $1,062,669 $9,938,592

Grand Total $4,734,025 $149,000 $815,048 $807,924 $1,964,049 $658,794 $1,099,881 $10,228,721

Independent Review

Fisheries Protocol Evaluation 

Panel (see Project 8.3)

Reservoir Limnology/ecology 

and linkage PEP (see Project 

1.2)

Vegetation Management PEP 

(see Project 11.5)

FY15

 

453
Appendix 2-B. Fiscal Year 2015 Funding Source 

(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

M 1

Lake Powell and Glen 

Canyon Dam Release WaterQuality Monitoring

$290,129 $290,129 $290,129

1.2

Reservoir limnology and ecology 

monitoring and research science 

review palen

$20,600 $20,600 $20,600

1 Total $310,729 $20,600 $290,129 $0 $310,729 $0 $0

M/R 2

Stream Flow, Water Quality, 

and Sediment Transport in 

the Colorado River 

Ecosystem

$1,343,040 $1,343,040 $1,343,040

3

Sandbars and Sediment 

Storage Dynamics

M 3.1.1

Monitoring sandbars using 

topographic surveys and remote 

cameras

$370,258 $370,258 $370,258

M 3.1.2

Monitoring sand bars and 

shorelines above 8000 ft3

/s by 

remote sensing

$120,033 $120,033 $120,033

R 3.1.3

Surveying with a camera: rapid 

topographic surveys with digital 

images using structure-frommotion (SFM) photogrammetry

$42,320 $42,320 $42,320

M/R 3.1.4 Analysis of historical images at 

selected monitoring sites $89,003 $89,003 $89,003

M/R 3.2 Sediment storage monitoring $459,964 $459,964 $459,964

R 3.3

Characterizing, and predictive 

modeling, of sand bar response at 

local and reach scales

$100,787 $100,787 $100,787

R 3.4

Connecting bed material 

transport, bed morphodynamics, 

and sand budgets in Grand Canyon

$36,050 $36,050 $36,050

M 3.5 Control network and survey 

support $109,003 $109,003 $109,003

3 Total $1,327,418 $1,327,418 $0 $0 $1,327,418 $0 $0

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

454
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

4

Connectivity along the 

Fluvial-Aeolian-Hillslope 

Continuum: Quantifying the 

Relative Importance of 

River-Related Factors that 

Influence Upland 

Geomorphology and 

Archaeological Site Stability

R 4.1

Quantifying connectivity along the 

fluvial-aeolian-hillslope continuum 

at landscape scales

$212,725 $137,725 $75,000 $212,725

M 4.2 Monitoring of cultural sites in 

Grand and Glen Canyons $297,624 $48,624 $75,000 $123,624 $174,000

4 Total $510,349 $186,349 $150,000 $0 $336,349 $0 $174,000

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

455
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

5 Food Base Monitoring and 

Research

5.1 Are aquatic insect diversity and 

production recruitment limited?

M 5.1.1 Insect emergence in Grand Canyon 

via citizen science $117,920 $117,920 $117,920

R 5.1.2

Quantifying the effects of 

hydropeaking on oviposition and 

egg mortality

$97,236 $97,236 $97,236

R 5.1.3 Synthesis of stressors and controls 

on EPT distributions $29,672 $29,672 $29,672

R 5.1.4 Synthesis of the aquatic foodbase 

in western US tailwaters $29,672 $29,672 $29,672

R 5.1.5 Natural history of oviposition for 

species present in Grand Canyon $25,878 $25,878 $25,878

R 5.1.6

Laboratory studies on insect 

oviposition and egg mortality 

associated with changing water 

levels

$37,038 $0 $37,038

R 5.1.7

Comparative emergence studies in 

Upper Basin using citizen science 

light trapping

$58,762 $0 $58,762

R 5.1.8 Natural history of oviposition for 

EPT via studies in the Upper Basin $25,372 $0 $25,372

5.2

Patterns and controls of aquatic 

invertebrate drift in Colorado 

River tailwaters

M 5.2.1

Continue characterizing and 

monitoring drift and insect 

emergence in Glen Canyon

$52,092 $52,092 $52,092

M 5.2.2

Continue natal origins drift 

monitoring in Glen, Marble, and 

Grand Canyons

$87,365 $87,365 $87,365

R 5.2.3

Link drift at natal origins Project 

transects to channel bed shear 

stress

$20,619 $20,619 $20,619

R 5.2.4

Link invertebrate drift patterns to 

substrate conditions in Glen, 

Marble, and Grand Canyons

$20,735 $20,735 $20,735

R 5.2.5

Comparative longitudinal drift 

studies in Upper and Lower 

Colorado River Basin tailwaters

$142,641 $0 $142,641

5.3 Primary Production Monitoring in 

Glen Marble and Grand Canyons

M 5.3.1 Synthesis and publication of Glen 

Canyon algae production $25,970 $25,970 $25,970

M 5.3.2 Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon $15,260 $15,260 $15,260

R 5.3.3 Developing automated tools for 

estimating algae production $0 $0 $0

5 Total $786,232 $522,419 $0 $0 $522,419 $263,813 $0

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

*Project Elements 5.1.7., 5.1.8., and 5.2.5 submitted for non-AMP funding.

*

*

*

456
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

6

Mainstem Colorado River 

Humpback Chub 

Aggregations and Fish 

Commuity Dynamics

M 6.1

Mainstem Colorado River 

Humpback Chub aggregation 

monitoring

$218,768 $218,768 $218,768

R 6.2 Aggregation recruitment $83,750 $83,750 $83,750

R 6.3

Monitoring mainstem 

aggregations with PIT tag antennas 

(pilot)

$18,444 $18,444 $18,444

M 6.4 System Wide Electrofishing $283,722 $283,722 $283,722

R 6.5

Brown trout natal origins through 

body pigmentation patterns in the 

Colorado River

$16,146 $0 $16,146

R 6.6 Direct Mainstem Augmentation of 

Humpback Chub $9,790 $9,790 $9,790

M 6.7 Rainbow Trout Early Life Stage 

Survey $77,024 $77,024 $77,024

M 6.8 Lees Ferry Creel Survey $0 $0 $0

6 Total $707,644 $579,514 $111,984 $0 $691,498 $0 $16,146

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

457
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

7

Population Ecology of 

Humpback Chub in and 

around the Little Colorado 

River

M 7.1

Annual spring/fall humpback chub 

abundance estimates in the lower 

13.6 km of the Little Colorado 

River

$531,320 $531,320 $531,320

M 7.2

Juvenile chub monitoring in the 

mainstem near the Little Colorado 

River confluence

$497,878 $497,878 $497,878

R 7.3

July Little Colorado River juvenile 

humpback chub marking to 

estimate production and 

outmigration

$112,172 $112,172 $112,172

M 7.4 Remote PIT tag array monitoring in 

the LCR $53,638 $53,638 $53,638

R 7.5 Food web monitoring in the Little 

Colorado River $141,520 $141,520 $141,520

R 7.6

Potential for gravel substrate 

limitation for humpback chub 

reproduction in the LCR

$11,600 $11,600 $11,600

R 7.7

Evaluate CO2 as a limiting factor 

early life history stages of 

humpback chub in the Little 

Colorado River

$86,420 $86,420 $86,420

M 7.8

Evaluate effects of Asian 

tapeworm infestation on Juvenile 

humpback chub

$16,820 $16,820 $16,820

R 7.9

Development of a non-lethal tool 

to assess the physiological 

condition of humpback chub in the 

Colorado and Little Colorado 

Rivers

$41,876 $41,876 $41,876

R 7.10 Humpback chub population 

modelling $97,556 $97,556 $97,556

7 Total $1,590,800 $1,338,732 $252,068 $0 $1,590,800 $0 $0

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

458
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

8

Management Actions to 

Increase Abundance and 

Distribution of Native Fishes 

in Grand Canyon

R 8.1 Efficacy and ecological impacts of 

BNT removal $96,396 $96,396 $96,396

M 8.2 Translocation and monitoring 

above Chute Falls $88,690 $88,690 $88,690

M 8.3

Fisheries Protocol Evaluation 

Panel (FY16 or FY17) $0 $0

M 8.4 Invasive Species Surveillance and 

Response $0 $0

R 8.5 Genetic Monitoring of Lower Basin 

Humpback Chub $0 $0

8 Total $185,086 $185,086 $0 $0 $185,086 $0 $0

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

459
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

9

Understanding Factors 

Determining Recruitment, 

Population Size, Growth, 

and Movement of Rainbow 

Trout in Glen and Marble 

Canyons

R/M 9.1 Lees Ferry RBT; monitoring, 

analysis, and study design $37,120 $37,120 $37,120

R 9.2

Detection of RBT movement from 

upper Colorado River below GCD 

(NO)

$440,512 $440,512 $440,512

R 9.3

Exploring the mechanisms behind 

trout growth, reproduction, and 

movement in Glen and Marble 

Canyons using lipid (fat) reserves 

as an indicator of physiological 

condition

$102,660 $102,660 $102,660

R 9.4 Comparative study on the feeding 

morphology of drift feeding fish $86,420 $0 $86,420 

R 9.5

Meta-analysis and the 

development of reactive distance 

relationships for encounter rate 

models 

$38,512 $20,000 $20,000 $18,512 

R 9.6

Lab studies to evaluate turbidity as 

a potential Glen Canyon Damoperations management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition on 

juvenile humpback chub

$37,120 $37,120 $37,120

R 9.7 Application of a bioenergetics 

model in a seasonally turbid river $66,468 $33,234 $33,234 $33,234 

R 9.8

Mechanisms that limit RBT and 

BNT growth in other western 

tailwater systems

$72,384 $72,384 $72,384

R 9.9

Contingency Planning for High 

Experimental Flows and 

Subsequent Rainbow Trout 

Population Management 

$72,616 $72,616 $72,616

R 9.10

Examining the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

$54,404 $54,404 $54,404

9 Total $1,008,216 $870,050 $0 $0 $870,050 $51,746 $86,420

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

460
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

R 10

Mapping and Assessment of 

Aquatic Habitats below Glen 

Canyon Dam 

$149,094 $95,000 $95,000 $54,094

11

Riparian Vegetation Studies: 

Ground-based and 

Landscape-scale Riparian 

Vegetation Monitoring and 

Plant Response-Guild 

Research associated with 

Sandbar Evolution and 

Wildlife Habitat Analysis 

M 11.1 Ground-based vegetation 

monitoring $176,513 $170,413 $6,100 $176,513

M 11.2

Periodic landscape scale 

vegetation mapping and analysis 

using remotely sensed data

$154,874 $148,774 $6,100 $154,874

R 11.3

Influence of sediment and 

vegetation feedbacks on the 

evolution of sandbars in Grand 

Canyon since 1991

$100,425 $94,325 $6,100 $100,425

R 11.4 Linking dam operations to changes 

in terrestrial fauna $44,631 $44,631 $44,631

M/R 11.5

Science Review Panel of Successes 

and Challenges in Non-native 

Vegetation Control in the 

Colorado River and Rio Grande 

Watersheds

$33,577 $30,527 $3,050 $33,577

11 Total $510,020 $488,670 $0 $21,350 $510,020 $0 $0

R 12

Dam-Related Effects on the 

Distribution and Abundance 

of Selected CulturallyImportant Plants in the 

Colorado River Ecosystem 

R 12.1 Tribal workshop and analysis of 

cultural landscape change $52,161 $45,000 $45,000 $7,161

R 12.2

Tribal evaluations of cultural 

landscape changes $0 $0 $0

12 Total $52,161 $45,000 $0 $0 $45,000 $0 $7,161

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

461
(M)Monitoring

(R)Research

Project Identifier

Project Description Total GCDAMP

Other BoR 

Sources

Internal 

USGS/SBS

C funding

Total High Priority Moderate Priority

13 Socio-economic Monitoring 

and Research

M/R 13.1

Economic Values of Recreational 

Resources Along the Colorado 

River – Grand Canyon Whitewater 

Floater and Lees Ferry Angler 

Values

$69,801 $69,801 $69,801

R 13.2

Tribal Values and Perspectives of 

Resources Downstream of Glen 

Canyon Dam

$0 $0 $0

R 13.3

Applied Decision Methods for the 

Glen Canyon Adaptive 

Management Plan

$106,803 $106,803 $106,803

13 Total $176,604 $176,604 $0 $0 $176,604 $0 $0

14

Geographic Information 

Systems, Services, and 

Support

$223,562 $223,562 $223,562

15 Administration and Support

15.1 GCMRC Admin and Support $1,041,126 $1,041,126 $1,041,126

15.2 GCMRC logistical support $306,640 $306,640 $306,640

15 Total $1,347,766 $1,347,766 $0 $0 $1,347,766 $0 $0

Total Lake Powell $290,129 $290,129 $0 $310,729 $0 $0

Total AMP $9,938,592 $8,749,810 $514,052 $21,350 $9,264,612 $315,559 $337,821

Grand Total $10,228,721 $8,749,810 $804,181 $21,350 $9,575,341 $315,559 $337,821

Independent Review

Fisheries Protocol Evaluation 

Panel (see Project 8.3)

Reservoir Limnology/ecology 

and linkage PEP (see Project 

1.2)

Vegetation Management PEP 

(see Project 11.5)

FY15 FY15 Recommended for Funding FY15 Unfunded/Recommended

462
Appendix 2-C. Fiscal Year 2016 Budget 

(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

Burden Rate 22.000%

M 1

Lake Powell and Glen 

Canyon Dam Release 

Water-Quality Monitoring

$187,205 $8,961 $41,550 $0 $0 $22,037 $52,298 $312,051

1.2

Reservoir limnology and ecology 

monitoring and research science 

review palen

$0 $0

1 Total $187,205 $8,961 $41,550 $0 $0 $22,037 $52,298 $312,051

M/R 2

Stream Flow, Water 

Quality, and Sediment 

Transport in the Colorado 

River Ecosystem

$659,000 $5,000 $52,000 $72,000 $496,000 $173,360 $1,457,360 

3

Sandbars and Sediment 

Storage Dynamics

M 3.1.1

Monitoring sandbars using 

topographic surveys and remote 

cameras

$109,061 $2,000 $4,000 $27,828 $156,060 $20,000 $36,117 $355,066 

M 3.1.2

Monitoring sand bars and 

shorelines above 8000 ft3

/s by 

remote sensing

$107,235 $23,592 $130,827 

R 3.1.3

Surveying with a camera: rapid 

topographic surveys with digital 

images using structure-frommotion (SFM) photogrammetry

$19,099 $20,000 $4,802 $43,901 

M/R 3.1.4 Analysis of historical images at 

selected monitoring sites $16,299 $68,415 $5,638 $90,352 

M/R 3.2 Sediment storage monitoring $167,016 $2,000 $27,000 $64,474 $196,075 $63,190 $519,755 

R 3.3

Characterizing, and predictive 

modeling, of sand bar response 

at local and reach scales

$67,515 $25,000 $15,603 $108,118 

R 3.4

Connecting bed material 

transport, bed morphodynamics, 

and sand budgets in Grand 

Canyon

$35,000 $1,050 $36,050 

M 3.5 Control network and survey 

support $79,360 $1,900 $15,000 $21,177 $117,437 

3 Total $565,585 $5,900 $46,000 $92,302 $500,550 $20,000 $171,169 $1,401,506 

FY16

463
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

4

Connectivity along the 

Fluvial-Aeolian-Hillslope 

Continuum: Quantifying 

the Relative Importance of 

River-Related Factors that 

Influence Upland 

Geomorphology and 

Archaeological Site 

Stability

R 4.1

Quantifying connectivity along 

the fluvial-aeolian-hillslope 

continuum at landscape scales

$99,224 $10,000 $5,000 $77,124 $25,129 $216,477 

M 4.2 Monitoring of cultural sites in 

Grand and Glen Canyons $185,834 $4,000 $58,000 $30,000 $10,152 $61,123 $349,109 

4 Total $285,058 $14,000 $63,000 $30,000 $0 $87,276 $86,252 $565,586 

FY16

464
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

5 Food Base Monitoring and 

Research

5.1 Are aquatic insect diversity and 

production recruitment limited?

M 5.1.1 Insect emergence in Grand 

Canyon via citizen science $83,293 $361 $9,270 $3,921 $1,854 $21,362 $120,061

R 5.1.2

Quantifying the effects of 

hydropeaking on oviposition and 

egg mortality

$49,252 $721 $3,090 $27,448 $6,953 $17,921 $105,385

R 5.1.3 Synthesis of stressors and 

controls on EPT distributions $26,074 $361 $5,816 $32,251

R 5.1.4

Synthesis of the aquatic 

foodbase in western US 

tailwaters

$26,074 $361 $5,816 $32,251

R 5.1.5 Natural history of oviposition for 

species present in Grand Canyon $13,037 $721 $3,090 $6,953 $3,915 $27,716

R 5.1.6

Laboratory studies on insect 

oviposition and egg mortality 

associated with changing water 

levels

$26,074 $721 $6,180 $7,255 $40,230

R 5.1.7

Comparative emergence studies 

in Upper Basin using citizen 

science light trapping

$40,802 $1,442 $6,180 $3,921 $464 $11,530 $64,339

R 5.1.8 Natural history of oviposition for 

EPT via studies in the Upper Basin $13,037 $2,524 $3,090 $3,921 $4,966 $27,538

5.2

Patterns and controls of aquatic 

invertebrate drift in Colorado 

River tailwaters

M 5.2.1

Continue characterizing and 

monitoring drift and insect 

emergence in Glen Canyon

$46,401 $7,210 $1,545 $12,134 $67,290 

M 5.2.2

Continue natal origins drift 

monitoring in Glen, Marble, and 

Grand Canyons

$92,803 $1,030 $1,545 $20,983 $116,361 

R 5.2.3

Link drift at natal origins Project 

transects to channel bed shear 

stress

$11,600 $309 $258 $9,706 $2,677 $24,550 

R 5.2.4

Link invertebrate drift patterns 

to substrate conditions in Glen, 

Marble, and Grand Canyons

$11,600 $412 $258 $9,706 $2,699 $24,675 

R 5.2.5

Comparative longitudinal drift 

studies in Upper and Lower 

Colorado River Basin tailwaters

$69,602 $5,459 $1,545 $20,600 $48,204 $22,831 $168,241 

5.3

Primary Production Monitoring 

in Glen Marble and Grand 

Canyons

M 5.3.1 Synthesis and publication of Glen 

Canyon algae production $10,505 $13,905 $2,728 $27,138 

M 5.3.2 Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon $10,693 $1,030 $2,060 $3,032 $16,815 

R 5.3.3 Developing automated tools for 

estimating algae production $0 $0 

5 Total $530,847 $22,662 $38,111 $59,811 $78,333 $19,412 $145,665 $894,841

FY16

465
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

6

Mainstem Colorado River 

Humpback Chub 

Aggregations and Fish 

Commuity Dynamics

M 6.1

Mainstem Colorado River 

Humpback Chub aggregation 

monitoring

$68,700 $1,200 $6,200 $44,300 $100,000 $29,488 $249,888 

R 6.2 Aggregation recruitment $31,000 $500 $3,500 $9,000 $9,680 $53,680 

R 6.3

Monitoring mainstem 

aggregations with PIT tag 

antennas (pilot)

$8,400 $2,700 $2,442 $13,542 

M 6.4 System Wide Electrofishing $22,600 $8,100 $59,700 $175,000 $25,138 $290,538 

R 6.5

Brown trout natal origins through 

body pigmentation patterns in 

the Colorado River

$15,000 $450 $15,450 

R 6.6 Direct Mainstem Augmentation 

of Humpback Chub $4,100 $5,000 $1,052 $10,152 

M 6.7 Rainbow Trout Early Life Stage 

Survey $47,100 $4,000 $700 $5,000 $12,496 $69,296 

M 6.8 Lees Ferry Creel Survey $25,000 $750 $25,750 

6 Total $181,900 $5,700 $21,200 $118,000 $320,000 $0 $81,496 $728,296 

FY16

466
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

7

Population Ecology of 

Humpback Chub in and 

around the Little Colorado 

River

M 7.1

Annual spring/fall humpback 

chub abundance estimates in the 

lower 13.6 km of the Little 

Colorado River

$26,900 $8,300 $98,100 $370,000 $40,426 $543,726 

M 7.2

Juvenile chub monitoring in the 

mainstem near the Little 

Colorado River confluence

$96,700 $9,000 $135,800 $215,000 $59,580 $516,080 

R 7.3

July Little Colorado River 

juvenile humpback chub marking 

to estimate production and 

outmigration

$56,200 $4,000 $5,300 $26,800 $20,306 $112,606

M 7.4 Remote PIT tag array monitoring 

in the LCR $79,900 $3,500 $3,900 $5,000 $19,356 $111,656 

R 7.5 Food web monitoring in the 

Little Colorado River $70,000 $2,000 $15,840 $87,840

R 7.6

Potential for gravel substrate 

limitation for humpback chub 

reproduction in the LCR

$5,600 $300 $1,000 $3,300 $2,244 $12,444 

R 7.7

Evaluate CO2 as a limiting factor 

early life history stages of 

humpback chub in the Little 

Colorado River

$59,500 $3,000 $18,000 $17,710 $98,210 

M 7.8

Evaluate effects of Asian 

tapeworm infestation on 

Juvenile humpback chub

$11,300 $2,000 $500 $3,036 $16,836 

R 7.9

Development of a non-lethal 

tool to assess the physiological 

condition of humpback chub in 

the Colorado and Little Colorado 

Rivers

$71,600 $6,700 $17,226 $95,526 

R 7.10 Humpback chub population 

modelling $121,000 $2,000 $100 $27,082 $150,182

7 Total $598,700 $13,300 $52,400 $267,900 $590,000 $0 $222,806 $1,745,106

FY16

467
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

8

Management Actions to 

Increase Abundance and 

Distribution of Native 

Fishes in Grand Canyon

R 8.1 Efficacy and ecological impacts of 

BNT removal $57,300 $2,800 $37,500 $21,472 $119,072 

M 8.2 Translocation and monitoring 

above Chute Falls $4,100 $2,300 $7,800 $68,200 $5,170 $87,570 

M 8.3

Fisheries Protocol Evaluation 

Panel (FY16 or FY17) $0 $0 

M 8.4 Invasive Species Surveillance and 

Response $0 $0 

R 8.5 Genetic Monitoring of Lower 

Basin Humpback Chub $0 $0

8 Total $61,400 $0 $5,100 $45,300 $68,200 $0 $26,642 $206,642

FY16

468
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

9

Understanding Factors 

Determining Recruitment, 

Population Size, Growth, 

and Movement of 

Rainbow Trout in Glen and 

Marble Canyons

R/M 9.1 Lees Ferry RBT; monitoring, 

analysis, and study design $60,000 $2,500 $13,750 $76,250 

R 9.2

Detection of RBT movement 

from upper Colorado River below 

GCD (NO)

$100,500 $50,100 $145,500 $120,000 $68,742 $484,842 

R 9.3

Exploring the mechanisms 

behind trout growth, 

reproduction, and movement in 

Glen and Marble Canyons using 

lipid (fat) reserves as an indicator 

of physiological condition

$0 $0 

R 9.4

Comparative study on the 

feeding morphology of drift 

feeding fish 

$80,000 $2,500 $2,400 $18,678 $103,578 

R 9.5

Meta-analysis and the 

development of reactive 

distance relationships for 

encounter rate models 

$29,800 $1,500 $6,886 $38,186 

R 9.6

Lab studies to evaluate turbidity 

as a potential Glen Canyon Damoperations management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition on 

juvenile humpback chub

$21,400 $2,500 $5,258 $29,158 

R 9.7 Application of a bioenergetics 

model in a seasonally turbid river $56,100 $1,500 $12,672 $70,272 

R 9.8

Mechanisms that limit RBT and 

BNT growth in other western 

tailwater systems

$65,600 $1,500 $14,762 $81,862 

R 9.9

Contingency Planning for High 

Experimental Flows and 

Subsequent Rainbow Trout 

Population Management 

$12,900 $28,000 $10,000 $11,198 $62,098 

R 9.10

Examining the Effects of High 

Flow Experiments on the 

Physiological Condition of Age-0 

and Adult Rainbow Trout in Glen 

Canyon 

$55,000 $2,500 $12,650 $70,150 

9 Total $481,300 $7,500 $87,500 $155,500 $120,000 $0 $164,596 $1,016,396 

FY16

469
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

R 10

Mapping and Assessment 

of Aquatic Habitats below 

Glen Canyon Dam 

$129,774 $5,000 $29,650 $164,424 

11

Riparian Vegetation 

Studies: Ground-based 

and Landscape-scale 

Riparian Vegetation 

Monitoring and Plant 

Response-Guild Research 

associated with Sandbar 

Evolution and Wildlife 

Habitat Analysis 

M 11.1 Ground-based vegetation 

monitoring $88,705 $1,000 $1,000 $50,438 $19,106 $31,625 $191,874

M 11.2

Periodic landscape scale 

vegetation mapping and analysis 

using remotely sensed data

$44,912 $2,000 $2,000 $65,850 $12,736 $127,498

R 11.3

Influence of sediment and 

vegetation feedbacks on the 

evolution of sandbars in Grand 

Canyon since 1991

$63,461 $2,500 $2,500 $7,704 $6,783 $15,293 $98,241

R 11.4 Linking dam operations to 

changes in terrestrial fauna $47,180 $8,000 $2,000 $15,000 $46,766 $17,283 $136,229

M/R 11.5

Science Review Panel of 

Successes and Challenges in Nonnative Vegetation Control in the 

Colorado River and Rio Grande 

Watersheds

$0 $0 

11 Total $244,258 $13,500 $7,500 $65,438 $139,426 $6,783 $76,937 $553,842 

R 12

Dam-Related Effects on 

the Distribution and 

Abundance of Selected 

Culturally-Important 

Plants in the Colorado 

River Ecosystem 

R 12.1 Tribal workshop and analysis of 

cultural landscape change $19,962 $2,500 $5,500 $5,000 $7,252 $40,214 

R 12.2

Tribal evaluations of cultural 

landscape changes $45,000 $1,350 $46,350 

12 Total $19,962 $2,500 $5,500 $5,000 $45,000 $0 $8,602 $86,564 

FY16

470
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

13

Socio-economic 

Monitoring and Research

M/R 13.1

Economic Values of Recreational 

Resources Along the Colorado 

River – Grand Canyon 

Whitewater Floater and Lees 

Ferry Angler Values

$57,516 $2,500 $250 $13,259 $73,525 

R 13.2

Tribal Values and Perspectives of 

Resources Downstream of Glen 

Canyon Dam

$2,500 $10,250 $117,500 $6,330 $136,580 

R 13.3

Applied Decision Methods for 

the Glen Canyon Adaptive 

Management Plan

$67,426 $7,500 $500 $54,000 $18,214 $147,640 

13 Total $124,942 $12,500 $11,000 $0 $171,500 $0 $37,803 $357,745 

14

Geographic Information 

Systems, Services, and 

Support

$172,906 $6,000 $15,990 $42,877 $237,773 

15

Administration and 

Support

15.1 GCMRC Admin and Support $563,196 $32,000 $226,500 $20,000 $81,500 $187,618 $1,110,814

15.2 GCMRC logistical support $264,515 $5,500 $59,403 $329,418

15 Total $827,711 $37,500 $226,500 $20,000 $81,500 $0 $247,021 $1,440,232

Total Lake Powell $187,205 $8,961 $41,550 $0 $0 $22,037 $52,298 $312,051

Total AMP $4,883,343 $151,062 $631,801 $931,251 $2,114,509 $629,471 $1,514,876 $10,856,313

Grand Total $5,070,548 $160,023 $673,351 $931,251 $2,114,509 $651,508 $1,567,174 $11,168,364

Independent Review

Fisheries Protocol 

Evaluation Panel (see 

Project 8.3)

Reservoir 

Limnology/ecology and 

linkage PEP (see Project 1.2)

Vegetation Management 

PEP (see Project 11.5)

FY16

471
Appendix 2-D. Fiscal Year 2017 Budget 

(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

Burden Rate 28.000%

M 1

Lake Powell and Glen 

Canyon Dam Release WaterQuality Monitoring$190,949 $9,230 $42,797 $23,814 $68,033 $334,823

1.2

Reservoir limnology and ecology 

monitoring and research science 

review palen

$0 $0

1 Total $190,949 $9,230 $42,797 $0 $0 $23,814 $68,033 $334,823

M/R 2

Stream Flow, Water Quality, 

and Sediment Transport in 

the Colorado River 

Ecosystem

$671,000 $5,000 $53,000 $74,000 $512,000 $224,840 $1,539,840 

3

Sandbars and Sediment 

Storage Dynamics

M 3.1.1

Monitoring sandbars using 

topographic surveys and remote 

cameras

$114,218 $2,000 $4,000 $29,088 $156,060 $20,000 $46,487 $371,853 

M 3.1.2

Monitoring sand bars and 

shorelines above 8000 ft3

/s by 

remote sensing

$110,281 $30,879 $141,160 

R 3.1.3

Surveying with a camera: rapid 

topographic surveys with digital 

images using structure-frommotion (SFM) photogrammetry

$20,048 $20,000 $6,213 $46,261 

M/R 3.1.4 Analysis of historical images at 

selected monitoring sites $16,852 $68,415 $6,771 $92,038 

M/R 3.2 Sediment storage monitoring $174,705 $2,000 $27,000 $66,664 $196,075 $81,586 $548,030 

R 3.3

Characterizing, and predictive 

modeling, of sand bar response at 

local and reach scales

$70,978 $25,000 $20,624 $116,602 

R 3.4

Connecting bed material 

transport, bed morphodynamics, 

and sand budgets in Grand Canyon

$35,000 $1,050 $36,050 

M 3.5 Control network and survey 

support $80,947 $1,900 $15,000 $27,397 $125,244 

3 Total $588,029 $5,900 $46,000 $95,752 $500,550 $20,000 $221,007 $1,477,238 

FY17

472
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

4

Connectivity along the 

Fluvial-Aeolian-Hillslope 

Continuum: Quantifying the 

Relative Importance of 

River-Related Factors that 

Influence Upland 

Geomorphology and 

Archaeological Site Stability

R 4.1

Quantifying connectivity along the 

fluvial-aeolian-hillslope continuum 

at landscape scales

$119,826 $10,000 $8,000 $77,124 $38,591 $253,541 

M 4.2 Monitoring of cultural sites in 

Grand and Glen Canyons $197,358 $4,000 $26,000 $30,000 $10,152 $72,060 $339,570 

4 Total $317,184 $14,000 $34,000 $30,000 $0 $87,276 $110,651 $593,111 

FY17

473
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

5 Food Base Monitoring and 

Research

5.1 Are aquatic insect diversity and 

production recruitment limited?

M 5.1.1 Insect emergence in Grand Canyon 

via citizen science $93,491 $371 $9,548 $4,039 $1,432 $30,129 $139,010

R 5.1.2

Quantifying the effects of 

hydropeaking on oviposition and 

egg mortality

$54,503 $743 $3,183 $28,271 $7,161 $24,491 $118,352

R 5.1.3 Synthesis of stressors and controls 

on EPT distributions $29,440 $371 $8,347 $38,158

R 5.1.4 Synthesis of the aquatic foodbase 

in western US tailwaters $29,440 $371 $8,347 $38,158

R 5.1.5 Natural history of oviposition for 

species present in Grand Canyon $14,720 $743 $3,183 $7,161 $7,226 $33,033

R 5.1.6

Laboratory studies on insect 

oviposition and egg mortality 

associated with changing water 

levels

$29,440 $743 $6,365 $10,233 $46,781

R 5.1.7

Comparative emergence studies in 

Upper Basin using citizen science 

light trapping

$45,884 $1,485 $6,365 $4,039 $955 $16,205 $74,933

R 5.1.8 Natural history of oviposition for 

EPT via studies in the Upper Basin $14,720 $2,599 $3,183 $4,039 $6,871 $31,412

5.2

Patterns and controls of aquatic 

invertebrate drift in Colorado 

River tailwaters

M 5.2.1

Continue characterizing and 

monitoring drift and insect 

emergence in Glen Canyon

$60,395 $7,426 $1,591 $19,435 $88,847 

M 5.2.2

Continue natal origins drift 

monitoring in Glen, Marble, and 

Grand Canyons

$120,790 $1,061 $1,591 $34,564 $158,006 

R 5.2.3

Link drift at natal origins Project 

transects to channel bed shear 

stress

$15,099 $318 $265 $9,997 $4,391 $30,070 

R 5.2.4

Link invertebrate drift patterns to 

substrate conditions in Glen, 

Marble, and Grand Canyons

$15,099 $424 $265 $9,997 $4,421 $30,206 

R 5.2.5

Comparative longitudinal drift 

studies in Upper and Lower 

Colorado River Basin tailwaters

$90,592 $5,623 $1,591 $21,218 $49,650 $34,816 $203,490 

5.3 Primary Production Monitoring in 

Glen Marble and Grand Canyons

M 5.3.1 Synthesis and publication of Glen 

Canyon algae production $10,610 $2,971 $13,581 

M 5.3.2 Monitoring dissolved oxygen in 

Glen, Marble, and Grand Canyon $11,249 $1,061 $2,122 $4,041 $18,473 

R 5.3.3 Developing automated tools for 

estimating algae production $0 $0 

5 Total $635,472 $23,339 $39,252 $68,767 $59,198 $19,994 $216,488 $1,062,510

FY17

474
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

6

Mainstem Colorado River 

Humpback Chub 

Aggregations and Fish 

Commuity Dynamics

M 6.1

Mainstem Colorado River 

Humpback Chub aggregation 

monitoring

$65,300 $1,200 $6,200 $44,200 $100,000 $35,732 $252,632 

R 6.2 Aggregation recruitment $26,000 $500 $3,500 $9,100 $10,948 $50,048 

R 6.3

Monitoring mainstem 

aggregations with PIT tag antennas 

(pilot)

$4,400 $2,800 $2,016 $9,216 

M 6.4 System Wide Electrofishing $24,300 $8,100 $60,000 $175,000 $31,122 $298,522 

R 6.5

Brown trout natal origins through 

body pigmentation patterns in the 

Colorado River

$0 $0 

R 6.6 Direct Mainstem Augmentation of 

Humpback Chub $4,400 $5,000 $1,382 $10,782 

M 6.7 Rainbow Trout Early Life Stage 

Survey $48,200 $4,000 $700 $5,000 $16,212 $74,112 

M 6.8 Lees Ferry Creel Survey $25,000 $750 $25,750 

6 Total $172,600 $5,700 $21,300 $118,300 $305,000 $0 $98,162 $721,062 

FY17

475
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

7

Population Ecology of 

Humpback Chub in and 

around the Little Colorado 

River

M 7.1

Annual spring/fall humpback chub 

abundance estimates in the lower 

13.6 km of the Little Colorado 

River

$22,400 $8,400 $105,300 $370,000 $49,208 $555,308 

M 7.2

Juvenile chub monitoring in the 

mainstem near the Little Colorado 

River confluence

$67,100 $9,000 $26,300 $50,000 $30,172 $182,572 

R 7.3

July Little Colorado River juvenile 

humpback chub marking to 

estimate production and 

outmigration

$63,600 $4,000 $5,300 $28,800 $28,476 $130,176

M 7.4 Remote PIT tag array monitoring in 

the LCR $99,000 $3,500 $4,200 $5,000 $30,026 $141,726 

R 7.5 Food web monitoring in the Little 

Colorado River $2,000 $560 $2,560

R 7.6

Potential for gravel substrate 

limitation for humpback chub 

reproduction in the LCR

$5,900 $300 $1,000 $3,600 $3,024 $13,824 

R 7.7

Evaluate CO2 as a limiting factor 

early life history stages of 

humpback chub in the Little 

Colorado River

$71,400 $3,000 $18,000 $25,872 $118,272 

M 7.8

Evaluate effects of Asian 

tapeworm infestation on Juvenile 

humpback chub

$11,900 $2,000 $500 $4,032 $18,432 

R 7.9

Development of a non-lethal tool 

to assess the physiological 

condition of humpback chub in the 

Colorado and Little Colorado 

Rivers

$74,400 $6,700 $22,708 $103,808 

R 7.10 Humpback chub population 

modelling $157,500 $2,000 $100 $44,688 $204,288

7 Total $573,200 $13,300 $52,500 $168,200 $425,000 $0 $238,766 $1,470,966

FY17

476
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

8

Management Actions to 

Increase Abundance and 

Distribution of Native Fishes 

in Grand Canyon

R 8.1 Efficacy and ecological impacts of 

BNT removal $52,600 $2,800 $37,700 $26,068 $119,168 

M 8.2 Translocation and monitoring 

above Chute Falls $4,400 $2,300 $7,200 $68,200 $5,938 $88,038 

M 8.3

Fisheries Protocol Evaluation 

Panel (FY16 or FY17) $0 $0 

M 8.4 Invasive Species Surveillance and 

Response $4,400 $45,000 $2,582 $51,982 

R 8.5 Genetic Monitoring of Lower Basin 

Humpback Chub $4,400 $1,200 $25,000 $2,318 $32,918

8 Total $65,800 $0 $6,300 $44,900 $138,200 $0 $36,906 $292,106

FY17

477
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

9

Understanding Factors 

Determining Recruitment, 

Population Size, Growth, 

and Movement of Rainbow 

Trout in Glen and Marble 

Canyons

R/M 9.1 Lees Ferry RBT; monitoring, 

analysis, and study design $60,400 $16,912 $77,312 

R 9.2

Detection of RBT movement from 

upper Colorado River below GCD 

(NO)

$98,600 $50,100 $101,600 $50,000 $71,584 $371,884 

R 9.3

Exploring the mechanisms behind 

trout growth, reproduction, and 

movement in Glen and Marble 

Canyons using lipid (fat) reserves 

as an indicator of physiological 

condition

$0 $0 

R 9.4 Comparative study on the feeding 

morphology of drift feeding fish $70,000 $2,400 $20,272 $92,672 

R 9.5

Meta-analysis and the 

development of reactive distance 

relationships for encounter rate 

models 

$0 $0 

R 9.6

Lab studies to evaluate turbidity 

as a potential Glen Canyon Damoperations management tool to 

constrain rainbow trout 

populations and reduce 

predation/competition on 

juvenile humpback chub

$20,900 $2,500 $6,552 $29,952 

R 9.7 Application of a bioenergetics 

model in a seasonally turbid river $50,800 $1,500 $14,644 $66,944 

R 9.8

Mechanisms that limit RBT and 

BNT growth in other western 

tailwater systems

$0 $0 

R 9.9

Contingency Planning for High 

Experimental Flows and 

Subsequent Rainbow Trout 

Population Management 

$27,200 $28,000 $22,100 $21,644 $98,944 

R 9.10

Examining the Effects of High Flow 

Experiments on the Physiological 

Condition of Age-0 and Adult 

Rainbow Trout in Glen Canyon 

$4,000 $1,120 $5,120 

9 Total $331,900 $0 $84,500 $123,700 $50,000 $0 $152,728 $742,828 

FY17

478
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

R 10

Mapping and Assessment 

of Aquatic Habitats below 

Glen Canyon Dam 

$96,790 $7,000 $29,061 $132,851 

11

Riparian Vegetation 

Studies: Ground-based and 

Landscape-scale Riparian 

Vegetation Monitoring and 

Plant Response-Guild 

Research associated with 

Sandbar Evolution and 

Wildlife Habitat Analysis 

M 11.1 Ground-based vegetation 

monitoring $96,442 $1,200 $1,000 $51,968 $19,469 $42,755 $212,834

M 11.2

Periodic landscape scale 

vegetation mapping and analysis 

using remotely sensed data

$46,682 $1,500 $2,000 $67,101 $16,064 $133,347

R 11.3

Influence of sediment and 

vegetation feedbacks on the 

evolution of sandbars in Grand 

Canyon since 1991

$61,046 $2,550 $2,500 $7,781 $6,851 $18,740 $99,468

R 11.4 Linking dam operations to changes 

in terrestrial fauna $43,454 $4,000 $2,500 $8,000 $35,000 $17,277 $110,231

M/R 11.5

Science Review Panel of Successes 

and Challenges in Non-native 

Vegetation Control in the 

Colorado River and Rio Grande 

Watersheds

$0 $0 

11 Total $247,624 $9,250 $8,000 $59,968 $129,351 $6,851 $94,836 $555,880 

R 12

Dam-Related Effects on the 

Distribution and Abundance 

of Selected CulturallyImportant Plants in the 

Colorado River Ecosystem 

R 12.1 Tribal workshop and analysis of 

cultural landscape change $0 $0 

R 12.2

Tribal evaluations of cultural 

landscape changes $0 $0 

12 Total $0 $0 $0 $0 $0 $0 $0 $0 

FY17

479
(M)Monitoring

(R)Research

Project Identifier

Project Description Salaries Travel &

Training

Operating

Expenses Logistics

Cooperators

(non-USGS)

USGS

Cooperators

USGS/SBSC 

Burden Total

13 Socio-economic Monitoring 

and Research

M/R 13.1

Economic Values of Recreational 

Resources Along the Colorado 

River – Grand Canyon Whitewater 

Floater and Lees Ferry Angler 

Values

$0 $0 

R 13.2

Tribal Values and Perspectives of 

Resources Downstream of Glen 

Canyon Dam

$5,000 $500 $117,500 $5,065 $128,065 

R 13.3

Applied Decision Methods for the 

Glen Canyon Adaptive 

Management Plan

$127,441 $7,500 $500 $5,400 $38,085 $178,926 

13 Total $127,441 $12,500 $1,000 $0 $122,900 $0 $43,150 $306,991 

14

Geographic Information 

Systems, Services, and 

Support

$179,307 $4,000 $15,990 $55,803 $255,100 

15 Administration and Support

15.1 GCMRC Admin and Support $578,094 $34,000 $246,000 $20,000 $84,000 $248,386 $1,210,480

15.2 GCMRC logistical support $269,794 $6,000 $77,222 $353,016

15 Total $847,888 $40,000 $246,000 $20,000 $84,000 $0 $325,608 $1,563,496

Total Lake Powell $190,949 $9,230 $42,797 $0 $0 $23,814 $68,033 $334,823

Total AMP $4,854,235 $139,989 $607,842 $803,587 $1,814,199 $646,121 $1,848,006 $10,713,979

Grand Total $5,045,184 $149,219 $650,639 $803,587 $1,814,199 $669,935 $1,916,039 $11,048,802

Independent Review

Fisheries Protocol Evaluation 

Panel (see Project 8.3)

Reservoir Limnology/ecology 

and linkage PEP (see Project 

1.2)

Vegetation Management PEP 

(see Project 11.5)

FY17

480
Appendix 3. Logistics and Schedules of River Trips and Field Work 

PROJECT TITLE PROJECT 

CODE

GENERAL LOGISTICS 

DESCRIPTION

LOGISTICS 

TYPE (RT=river 

trip, LP=Lake 

Powell, 

HS=Helicopter 

Support, 

LF=Glen 

Canyon Reach annual # 

trips trip months boats #people #days

1 Lake Powell and Glen Canyon Dam 

Release Water Quality Monitoring

LPQM food packs provided for quarterly 

Lake Powell monitorng trips, 4-6 

people, 7 days, includes limited 

boat/motor maintence support

LP

4

2 Stream flow, water quality, and 

sediment transport

FGS two river trips anually, to monitor 

sediment transport at monitoring 

stations; 30 mi., 60 mi., Phantom, 

National and Diamond Creek

RT

2

February, late 

August

2 support, 1-

16' technical

3 Sandbars and Sediment Storage 

Dynamics

3.1 Sandbar and camping beach monitoring FCS one river trip anually to survey 

established longterm set of 

monitoring sites. Non motorized 

trip consisting of 6-18' row boats 

occurs in October

RT

1 October 6 row 12 18

3.2 Sediment storage monitoring SSM one river trip anually, motor 

supported trip occurs April/May 

to map channel in rotating 

reaches of river. In 2015, mapping 

will occur in Glen Canyon reach 

which will require less equipment 

and personnel. The project plans 

to survey RM 0-RM30 in 2016 and 

RM 166-RM225 in 2017.

RT

1 May

2 support, 2-

22' technical 

(multi-beam 

and "eyeball"), 1-16' 

technical 

(single beam), 

1-16' 

technical 20 19

4 Connectivity along the fluvial-aeolian 

hillslope continuum

4.1 Monitoring the status of cultural 

resources in Glen Canyon

LF

1 Nov/Dec cofelt 2 4

4.2 . Monitoring strategies for the status of 

cultural resources in Grand Canyon

one river trip to monitor 

designated sites and maintain 

weather stations, additional 

logistics for weater station 

maintenace will be covered on 

existing scheduled trips (GCY, 

FCS, NO/JCM). In 2015 monitoring 

will only occur in Glen Canyon 

reach. 2016 and 2017

RT

1 May

1-support, 1-

22' 10 13

481
 

PROJECT TITLE PROJECT 

CODE

GENERAL LOGISTICS 

DESCRIPTION

LOGISTICS 

TYPE (RT=river 

trip, LP=Lake 

Powell, 

HS=Helicopter 

Support, 

LF=Glen 

Canyon Reach annual # 

trips trip months boats #people #days

5 Foodbase Monitoring and Research

5.1 AQFB Emergence Trip AQFB one river trip annually, citizen 

science

RT

1 June

1-support, 1-

22', 1-sport 

boat 5 15

5.2 AQFB Invertebrate Drift: Dam to Badger 

Rapids

AQFB-LF monthly trips, Copp or Smith will 

operate boat (no boatman 

needed).

LF (to Badger)

12 Monthly

coffelt or jet 

boat 3 2

AQFB Invertebrate Drift: upper/lower 

basin

AQFB-U/LB one trip annually to upper and 

lower basin (separate trips)

Logistics are 

similar to LF, 

except not in 

LF 2

June-August? 

TBA

1-sport boat, 

or coffelt 3 8

AQFB Invertebrate Drift: mainstem AQFB-NO work is conducted on NO/JCM 

trips

RT

6 Mainstem humpback chub 

aggregations and fish community 

dynamics

6.1 Monitoring Humpback Chub 

aggregation relative Abundance and 

Distribution

MSF-AG one river trips anually, to support 

monitoring focused on identified 

HBC aggregations

RT

1

July, 

September

2-support, 2-

16' technical 10 18

6.2 Humpback Chub aggregation 

recruitment studies

work is conducted on project 6.1 

logistics with addition of one 

sport boat for 

electroshocking/seining

1-16' 

technical 

boat

6.3 Mainstem. PIT tag antenna monitoring maintence of remote PIT tag array 

as needed

HS (will tag on 

to existing 

trips) 2

6.4 System wide electrofishing MSF-NN two river trips anually, to 

electrofish sample entire river 

corridor, 

RT

2 April, May

2-support, 2-

16' technical 10 14

6.5 Brown Trout natal origins no stand alone logistics-work will 

be conducted on existing logistics

6.6 Mainstem Translocation no stand alone logistics-work will 

be conducted on existing logistics

6.7 Rainbow trout early life stage studies Redd/RTELSS 8 winter/spring one day trips to 

survey Glen Canyon reach for RBT 

redds, and 4 sampling trips 

utilizing electrofishing and 

backpack shocking to monitor RBT 

early life stage

LF

8 Redd, 4 

RTLESS

Redd: Dec, 

Jan, Feb, 

March, April 

RTELSS: July, 

Aug, Sept, 

Nov

Cofelt, 2-16' 

technical 2

Redd: 

one day 

trips, 

RTELSS: 

2-16' 

technic

al

6.8 LF Creel Survey work conducted by AZGFD-no 

logistics

482
 

PROJECT TITLE PROJECT 

CODE

GENERAL LOGISTICS 

DESCRIPTION

LOGISTICS 

TYPE (RT=river 

trip, LP=Lake 

Powell, 

HS=Helicopter 

Support, 

LF=Glen 

Canyon Reach annual # 

trips trip months boats #people #days

7 Population Ecology of Humpback Chub 

in and around the Little Colorado River

7.1 Annual spring and fall humpback chub 

abundance estimates in the 

downstream 13.6km of the Little 

Colorado River

LCR-HBC helicopter support for 3 LCR 

camps, April/May and 

September/October, 9 people, 11 

days per trip

HS

4

April, May, 

September, 

October 9 11

7.2 Juvenile Chub Monitoring in the 

mainstem near the Little Colorado River 

Confluence

JCM Logistics are combined with 

project 9.2 ( days 7-16 of river 

trip) to sample for HBC near LCR 

confluence.

RT

4

May, July, 

September, 

January* 

(January trip 

may be 

eliminated)

2-support, 1-

22' 

Processing 

boat 3-16' 

technical 18 18

7.3 LCR JCM helicopter support for 3 LCR 

camps to monitor LCR HBC 

populations

HS

1 June/July 12 12

7.4 LCR PIT tag antenna monitoring maintence of remote PIT tag array 

as needed

HS

1 2 4

7.5 LCR foodweb work is conducted in conjunction 

with project 7.1 trips

HS

8 Management Actions to Increase 

Abundancee and Distribution of Native 

Fishes in Grand Canyon

8.1 Efficacy and ecological impacts of 

brown trout removal at Bright Angel 

Creek

new project to colaborate with 

NPS to remove Brown trout in 

Bright Angel Creek confluence. 

Logistics could be coupled with 

F.3/F.6 project run-out.

RT

2

May, 

September

1-support, 2-

16' technical 8 18

8.2 F.4.3. Translocation and monitoring 

above Chute Falls

3 helicopter supported trips for 

HBC mark/recap and 

translocation/capture

HS

3

April/May, 

July

8.3 PEP may be one river trip for PEP in 

2016

RT

1 ? 2-support 18 12

483
 

PROJECT TITLE PROJECT 

CODE

GENERAL LOGISTICS 

DESCRIPTION

LOGISTICS 

TYPE (RT=river 

trip, LP=Lake 

Powell, 

HS=Helicopter 

Support, 

LF=Glen 

Canyon Reach annual # 

trips trip months boats #people #days

9 Understanding the Factors Limiting the 

Recruitment, Population Size, Growth, 

and Movement of Rainbow Trout in 

Glen and Marble Canyons

9.1 Glen Canyon Rainbow trout; 

monitoring, analysis and study design

LFT 3 Glen Canyon trips to monitor 

RBT population, includes 

additional day on July trip for nonnative fish detection

LF

3

April, July, 

October

2-16' 

technical 4

4days, 

July trip 

5 days

9.2 Detection of rainbow trout movement 

from Glen Canyon to Marble Canyon

NO Logistics are combined with 

project 7.2 (first six days of river 

trip) to electrofish sample for 

tagged RBT between Glen Canyon 

Dam and LCR confluence.

RT

4

May, July, 

September, 

January* 

(January trip 

may be 

eliminated)

2-support, 1-

22' 

Processing 

boat 3-16' 

technical 18 18

9.3 Detection of rainbow trout movement 

from Glen Canyon to Marble CanyonLees Ferry marking

NO-mark november Glen Canyon marking 

trip

Glen Canyon

1 November

1-support, 1-

22' 

processing 

boat, 2-16' 

technical, 

cofelt 10 9

9.9 Contingency planning for High Flow 

Experiments and subsequent rainbow 

trout population managment

1 additional RBT marking trip in 

Glen Canyon post HFE (in years 

when fall HFE occurs)

Glen Canyon

1 Dec

1-support, 1-

22' 

processing 

boat, 2-16' 

technical, 

cofelt 10 9

10 Mapping Flow Innundation of Shorline 

Areas and Bed Textures in Glen and 

Marble Canyons

This project hast no stand-alone 

logistics but does propose a field 

element to be accomplished on 

APR & SEP 2015-16 NO/JCM trips 

(collecting additional channel-bed 

sediment and channel margin 

imagery, See Table 1 of revised 

description). Other new field data 

used in this integrated project will 

derive from Project 3 channel 

mapping in Glen (2015) and 

upper/lower Marble Canyons 

(2015-16, see Grams and others 

elements 3.2 & 3.4).

RT

11 Riparian Vegetation Monitoring and 

Analysis of Riparian Vegetation, 

Landform Change and AquaticTerrestrial linkages to Faunal 

Communities

 Integrated vegetation monitoring one river trip to monitor riparian 

vegetation, plus addition of one 

boat to project 3.1

RT

1 September 4 row 14 16

12 Dam-Related Effects on the 

Distribution and Abundance of 

Selected Culturally-Important Plants in 

the Colorado River Ecosystem

add one boat to project 3.1? RT October 1 row 2 16

13 Socio-Economic Monitoring and 

Research

LF to Badger creel survey no additional logistics, surveys 

completed by foot trail access

484