Project B: Effects of dam releases on in-channel 

sediment storage and sandbar dynamics

Paul Grams

U.S. Geological Survey

Grand Canyon Monitoring and Research Center

GCDAMP Annual Reporting Meeting

Phoenix, Arizona

January 13, 2020

U.S. Department of the Interior

U.S. Geological Survey
Project B: Sandbar and Sediment Storage Monitoring and 

Research 

• Project Elements

• B.1 Sandbar Monitoring

• B.2 Bathymetric and topographic mapping for monitoring long-term trends in 

sediment storage

• B.3 Control Network and Survey Support 

• Project Objectives

• track the effects of individual High Flow Experiments (HFEs) on sandbars

• monitor the cumulative effect of successive HFEs and intervening operations on 

sandbars and sand conservation

• investigate the interactions between dam operations, sand transport, and eddy 

sandbar dynamics

• GCDAMP FY2019 Funding: $1,100,000

• Cooperators: Northern Arizona University
Project B: Sandbar and Sediment Storage Monitoring and 

Research, cont.

• Data Products FY19

• Sandbar monitoring photographs

• www.gcmrc.gov/sandbar OR www.usgs.gov/apps/sandbar

• Sandbar monitoring data

• www.gcmrc.gov/sandbar OR www.usgs.gov/apps/sandbar

• Data collection FY19

• April: Bathymetric and topographic mapping of Lower Marble 

Canyon and Eastern Grand Canyon (River Mile 29 to 87)

• Data are currently being edited and processed

• Expect to report results that will show 10-year trends in sandbars and sand 

storage for these reaches by next January

• October: Sandbar and campsite surveys

• Data are ~50% processed

• Results in next (Hazel and Kaplinski) presentation

• Remaining sites will be processed and data on website by end of February
Project B: Publications (2018-2019)

• Buscombe, D., 2019, SediNet—A configurable deep learning model for mixed 

qualitative and quantitative optical granulometry: Earth Surface Processes and 

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

• Grams, P.E., 2019, Sandbar deposition caused by high-flow experiments on the 

Colorado River downstream from Glen Canyon Dam--November 2012-November 

2018, in High-flow experiments assessment extended abstracts--Glen Canyon Dam 

Adaptive Management Program Annual Reporting Meeting Presentations, March 

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

Research Center, p. 12-22, https://www.usbr.gov/uc/progact/amp/amwg/2019-03-

06-amwg-meeting/20190301-HFE_Extended_Abstracts-Combined_FINAL.pdf.

• Leary, K.C.P., and Buscombe, D., 2019, Estimating sand bedload in rivers by 

tracking dunes--A comparison of methods based on bed elevation time-series--

preprint discussion paper: Earth Surface Dynamics, https://doi.org/10.5194/esurf2019-38.

• Topping, D.J., Grams, P.E., Griffiths, R.E., Hazel, J.E., Kaplinski, M.A., Dean, D.J., 

Voichick, N., Unema, J.A., and Sabol, T.A., 2019, Optimal timing of high-flow 

experiments for sandbar deposition, in High-flow experiments assessment extended 

abstracts--Glen Canyon Dam Adaptive Management Program Annual Reporting 

Meeting presentations, March 12-13, 2019, Phoenix, Ariz.: U.S. Geological Survey, 

Grand Canyon Monitoring and Research Center, p. 3-9, 

https://www.usbr.gov/uc/progact/amp/amwg/2019-03-06-amwg-meeting/20190301-

HFE_Extended_Abstracts-Combined_FINAL.pdf.

• Grams, P.E., Buscombe, D., Topping, D.J., Kaplinski, M.A., and Hazel, J.E., Jr., 

2019, How many measurements are required to construct an accurate sand budget 

in a large river? Insights from analyses of signal and noise: Earth Surface 

Processes and Landforms, online, https://doi.org/10.1002/esp.4489

• Buscombe, D., and Ritchie, A.C., 2018, Landscape classification with deep neural 

networks: Geosciences, v. 8, no. 7, article 244, 

https://doi.org/10.3390/geosciences8070244

• Buscombe, D., and Grams, P.E., 2018, Probabilistic substrate classification with 

multispectral acoustic backscatter--A comparison of discriminative and generative 

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

https://doi.org/10.3390/geosciences8110395

• Buscombe, D., Grams, P.E., & Kaplinski, M., 2018, Probabilistic models of 

seafloor composition using multispectral acoustic backscatter: GeoHab

2018 International Symposium, R2Sonic Multispectral Backscatter 

competition entry. Download using online form at: 

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

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

cameras for monitoring alluvial sandbars on the Colorado River in Grand 

Canyon, Arizona: U.S. Geological Survey Open-File Report 2018-1019, 50 

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

• Hamill, D., Buscombe, D., and Wheaton, J.M., 2018, Alluvial substrate 

mapping by automated texture segmentation of recreational-grade side 

scan sonar imagery: PLOS One, v. 13, no. 3 (e0194373), p. 1-28, 

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

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

geomorphic and vegetation change at sandbar campsites in response to 

flow regulation and controlled floods, Grand Canyon National Park, 

Arizona: River Research and Applications, online, 

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

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

A., 2018, Geomorphology and vegetation change at Colorado River 

campsites, Marble and Grand Canyons, Arizona: U.S. Geological Survey 

Scientific Investigations Report 2017–5096, 64 p., 

https://doi.org/10.3133/sir20175096

• Kasprak, A., Sankey, J.B., Buscombe, D., Caster, J., East, A.E., and 

Grams, P.E., 2018, Quantifying and forecasting changes in the areal extent 

of river valley sediment in response to altered hydrology and land cover: 

Progress in Physical Geography: Earth and Environment, online, 

https://doi.org/10.1177/0309133318795846.

• Mueller, E.R., Grams, P.E., Hazel, J.E., Jr., and Schmidt, J.C., 2018, 

Variability in eddy sandbar dynamics during two decades of controlled 

flooding of the Colorado River in the Grand Canyon: Sedimentary Geology, 

v. 363, p. 181-199, https://doi.org/10.1016/j.sedgeo.2017.11.007.
Project B Presentations at Annual Reporting Meeting

• Talks:

– In-channel sand storage (this talk)

– Sandbar changes (Joe Hazel, next talk)

– Relation between riparian vegetation and sandbar deposition (Brad Butterfield, 

tomorrow AM)

• Posters:

– Estimates of sand thickness and total sand storage for west-central Grand Canyon 

(Daniel Buscombe and Matt Kaplinski)

– Tracing the origin of sandbar deposits in the Grand Canyon of the Colorado River 

using XRF signatures and Bayesian mixing models (Katie Chapman)
Project B: Key findings with respect to LTEMP Goals and 

Knowledge Assessment

• LTEMP goal: 

– “Increase and retain fine sediment volume, area, and 

distribution in the Glen, Marble, and Grand Canyon reaches 

above the elevation of the average base flow for ecological, 

cultural, and recreational purposes.”

• Assessment: 

– Although specific targets are not defined, each HFE has 

resulted in deposition and the general objective of retaining 

and/or increasing sand volume above the 8000 cfs stage has 

been achieved in the HFE Protocol period (2012-2019). 

• Prognosis: 

– Deposition at sandbars is likely stage-limited (bars not likely 

to get larger without larger HFEs)

– Since 2011, dam releases have been relatively low and sand 

inputs from Paria River generally high. Changes in either of 

these conditions could cause trend to reverse.

OR

Status: unknown, because targets not 

defined; or good, because sand volume and 

area are not currently decreasing

Trend: unchanging because HFEs result in 

deposition, but bars are not progressively 

expanding

Confidence: high, because the monitoring is 

robust.
Project B: AMP goals addressed and information provided

• LTEMP goal: 

– “Increase and retain fine sediment volume, area, and distribution in the Glen, Marble, and Grand 

Canyon reaches above the elevation of the average base flow for ecological, cultural, and 

recreational purposes.”

• Question from HFE Protocol: 

– “Can sandbar building during HFEs exceed sandbar erosion during periods between HFEs, such 

that sandbar size can be increased and maintained over several years?”

• Project B address these questions by two related monitoring efforts:

– Annual sandbar and campsite monitoring (sandbar surveys and daily photographs)

• Critical information provided: Annual assessment of the effects of HFEs and other dam operations on selected 

sandbars and campsites.

– Periodic channel mapping (Combined topographic and bathymetric mapping)

• Critical information provided: Periodic assessment of long-term trends at large sample of sandbars and trends in 

sand storage on the river bed. 
Why measure sand storage by 

mapping the riverbed?

• Sandbar replenishment controlled by:

– Flow (need high flows to build large bars)

– Sand supply (if supply in the channel is low, a 

net loss from eddy sandbars is risked)

• Sand supply is controlled by:

– Dam releases (annual volume and release 

pattern)

– Inputs from tributaries

• The sand that builds sandbars is stored on the 

bed of the river and understanding the sand 

supply is critical to understanding and 

predicting sandbar response
Three decades of Sand Budgets in Grand Canyon have been incorrect or 

ambiguous because of inadequate measurements or because of measurement 

uncertainty

1990’s

Stable rating curves  sand accumulation 

(Glen Canyon Dam Environmental Impact Statement, 1990)

2000’s

Analysis of historical 

data  no 

accumulation

(Topping et al., 2000)

2010’s

Continuous measurements of flux  accumulation 

and evacuation with large uncertainty

https://www.gcmrc.gov/discharge_qw_sediment/reaches/GCDAMP
How we measure sand storage on the bed

• Repeat topographic and 

bathymetric measurements

– Multibeam sonar

– Singlebeam sonar

– Total station

• Referenced to geodetic control 

network

• Use backscatter to classify 

sand/gravel/rock

• High spatial resolution

• Uncertainty accumulates 

spatially – not over time

May 2016 May 2013 Difference

Blue = deposition

Red = erosion

- =
Uncertainty in measurements of sand storage

Error is less when computing changes 

in mean elevation over large areas 

And is less than 0.03 m when averaging 

over areas more than 500 m2

• Measurement uncertainty

– Caused by instrument and/or 

position errors

– Estimated by analysis of stable rock 

and gravel

• Sampling uncertainty

– Caused by gaps in data coverage and large spatial variability of 

erosion and deposition

– Estimated by bootstrap analysis for over the area we mapped

Must map at least 50 to 60% of 

the reach to detect direction of 

change (SNR > 1). 

Random sampling from among 

mapped segments shows the 

decrease in uncertainty as a 

function of sample size

Grams et al. (2019)
Channel mapping results: Lower Marble Canyon, 2009-2012

50-km reach (50-100 km downstream from Paria River)

Lower Marble Canyon, 2009-2012

• No controlled floods

• Includes 2011 equalization flows

• Flux budget: -700,000 ± 317,000 Mg

• Morphological budget: - 466,700 ± 303,300 Mg

Must map at least 50 to 60% of the reach to 

detect direction of change (SNR > 1). 

Grams et al. (2019)
Channel mapping results: Eastern Grand Canyon, 2011-2014

40-km reach (100-140 km downstream from Paria River)

Eastern Grand Canyon, 2011-2014

• Includes 2 controlled floods

• Includes 2011 equalization flows

• Flux budget: -690,000 ± 580,000 Mg

• Morphological budget: -297,300 ± 231,800 Mg

SNR never > 1; must map everything!

• Average inputs coupled with high flow volumes 

 moderate erosional signal that can be 

detected only by mapping a majority of the 

reach

Preliminary data, do not cite
Channel mapping results: Upper Marble Canyon, 2013-2016

50-km reach (0-50 km downstream from Paria River)

Upper Marble Canyon, 2013-2016

• Includes 2 controlled floods

• No summer high-volume flows

• Flux budget is +1,635,000 ± 894,000 Mg

• Morphological budget: 2,340,600 ± 324,000 Mg

SNR > 1 with just a small fraction of reach mapped

Mapping 50% of the reach gives SNR = 5

• Successive large inputs from upstream 

tributary  large depositional signal that is 

easy to detect

Preliminary data, do not cite
Upper Marble Canyon, 2013-2016

• Includes 2 controlled floods

• No summer high-volume flows

• Flux budget is +1,635,000 ± 894,000 Mg

• Morphological budget: 2,340,600 ± 324,000 Mg

• Successive large inputs from upstream 

tributary  large depositional signal that is 

easy to detect

50-km reach (0-50 km downstream from Paria River)

Nearly all (>99%) of the accumulated 

sand is on the riverbed

Preliminary data, do not cite

Channel mapping results: Upper Marble Canyon, 2013-2016, cont.
How will the channel mapping data be used to evaluate the 

effects of dam operations?

Mining 

sand from 

storage to 

build 

sandbars

Mining 

sand and 

losing 

sandbars

Accumulating 

sand and 

building 

sandbars

Accumulating 

sand, but not 

building 

sandbars.

loss gain

“Channel and eddies below 8,000 cfs”

loss gain

“Sandbars above 8,000 cfs”

• Declining storage for 2009 to 2012 (yellow and red)

• Bars increase in period with HFE (yellow)

• Increasing storage for 2013 to 2016 (green)

Preliminary data, do not cite • Bars maintain volume
How will the channel mapping data be used to 

evaluate the effects of dam operations?

Mining 

sand from 

storage to 

build 

sandbars

Mining 

sand and 

losing 

sandbars

Accumulating 

sand and 

building 

sandbars

Accumulating 

sand, but not 

building 

sandbars.

“Channel and eddies below 8,000 cfs”

loss gain

“Sandbars above 8,000 cfs”

loss gain

• HFEs

• Use sand from storage in channel to build bars

• Long-term

• Goal is to maintain storage and build sandbars

HFEs

Periods with 

equalization

Normal 

releases and 

HFEs

Preliminary data, do not cite
Conclusions: Long-term sand budget in Grand Canyon

• After 30+ years, we now have reliable 

measurements of the sand mass balance with 

well-constrained uncertainty.

– Morphologic and flux budgets agree

– We will be able to detect long-term changes

– Must map at least 50% of each segment to detect 

change when signal is weak (more is better)

• Periods with high summer release volumes cause 

evacuation

• Periods with normal summer release volumes and 

strong tributary inputs result in accumulation

• Use of controlled floods for rebuilding sandbars 

may be sustainable

– But, depends on the relative frequency of high water 

volume years vs. tributary supply
Channel mapping data applications

• Flow modeling

– New 2d flow model for Glen Canyon

– Now have capacity to develop similar 

model for Lees Ferry to Phantom 

Ranch

• Habitat characterization

– Substrate type (sand, gravel, 

vegetation, etc.)

– Flow depth 

– Streamflow velocity (with flow model)

• Physical habitat based sampling 

design now possible

Hidden Slough at 20,000 ft3/s

Hidden Slough at 40,000 ft3/s

Preliminary data, do not cite Flow model by Scott Wright, USGS California WSC
Future Channel Mapping to monitor sandbars and sand storage for LTEMP

• Annual sampling of entire canyon would be useful, 

but would double the project budget (to ~ $2 

million)

 Rotation mapping with goal to provide assessments 

at major milestones

• Milestone 1: 10 years into HFE Protocol

– Reporting in 2021 (end of current work plan)

– Repeat maps of Marble Canyon and Eastern GC at 3- to 7-yr 

intervals

– Will include results from mapping completed in 2019

• Milestone 2: 10 years into LTEMP

– Reporting in 2026

– Repeat maps of Marble Canyon and Eastern GC at 5 to 7-yr 

intervals

– Will include results from sampling conducted in 2021-25

• Milestone 3: 20 years into LTEMP

– Reporting in 2036

– Repeat maps of all segments at 7 to 10-yr intervals

– Will include results from sampling conducted in 2027-35

Segment Completed Maps

Glen Canyon 2014

Upper Marble Canyon 2013, 2016

Lower Marble Canyon 2009, 2012, 2019

Segment Completed Maps

Eastern Grand Canyon 2011, 2014, 2019

East Central Grand Canyon *

West Central Grand Canyon 2017

Western Grand Canyon *

* Segment not yet 

mapped. Proposed for 

next workplan.

Paria River

Little 

Colorado River

Upper MC (2)

Lower MC (3)

Eastern GC (3)

West Central GC (1)

East Central GC (0)

Glen Canyon (1)

Western GC (0)
Acknowledgements

Project B staff:

Daniel Buscombe, Matt Kaplinski, Joseph Hazel, Keith 

Kohl, Robert Tusso, James Hensleigh, and Thomas 

Gushue

Field assistants and collaborators over many years:

David Topping, Erich Mueller, Robert 

Ross, Daniel Hamill, David Rubin, 

Joel Sankey, Jack Schmidt, Scott 

Wright, Rod Parnell, Bryan 

Cooperrider, Karen Koestner, Emily 

Thompson, Daniel Hadley, Katie 

Chapman, Ryan Semptua...