The Effects of High-flow Experiments (HFEs) on 

Sandbar Dynamics

GCDAMP Annual Reporting Meeting

March 13, 2019

Paul Grams

U.S. Geological Survey

Grand Canyon Monitoring and Research Center

photo : Michael Collier
Project Reporting Slides

• 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: $1,050,430

• Cooperators: Northern Arizona University, University of Wyoming, 

Utah State University

• Products
Project B: Sandbar and Sediment Storage Monitoring 

and Research

• Data Products

• 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

• Glen Canyon topographic/bathymetric map

• grandcanyon.usgs.gov/portal/home

• Other USGS data releases

• Campsite report data: doi.org/10.5066/F7FJ2FQQ

• Sand-area data: doi.org/10.5066/P9SX3MGY

• Bed classification processing: doi.org/10.5066/F7B56HM0

• Publications

• 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.

• 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

• 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.
Publications (continued)

• 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.
Map of bed and banks between Glen Canyon Dam and 

Lees Ferry

grandcanyon.usgs.gov/portal In review for Sciencebase
Sandbar database and web application

• In development since 2014

– Started as a javascript app supported by oracle 

database

– Now mainly in python and supported by a sql

database (free and open source)

• Includes a desktop “workbench” for 

loading, processing and viewing data

• Web application for public access to data

• Series of python scripts for generating 

summary plots

• Next step is to incorporate those in workbench 

and web application

Desktop sandbar 

workbench

Sandbar web 

application

www.gcmrc.gov/sandbar OR www.usgs.gov/apps/sandbar
Fifty-six years of dam operations and twentythree years of high-flow experimentation:

High Flows and Sandbar Response

photo : Michael Collier
Overview

• Background on pre-floods, post-dam floods, and highflow experiments

• Observations of sandbar response to HFEs from 2012-

2018

• Cumulative sandbar response for the 2012-2018 period

• Sandbar model results, comparing HFE protocol to 

period without high flows

• Sand budgets from 2012-2018

• Will HFEs continue to be effective tools?

• What are the HFEs not doing?

• Summary and next steps
Change in flow regime and disruption of sand supply have 

caused changes to river morphology and sandbars

Grand Canyon

~ 16% of pre-dam sand supply

Little Colorado River

Marble Canyon

~ 6% of pre-dam 

sand supply

Glen Canyon Dam

Paria River

Colorado River at Lees Ferry, AZ

85 to 95% reduction in supply coupled with ~20% 

reduction in mean annual flow  sediment deficit

Topping et al. (2000)

https://waterdata.usgs.gov
Sandbar erosion near Tapeats Creek

1952

2003

photo by S. Tharnstrom

photo by K. Frost

Change in flow regime and disruption of sand supply have 

caused changes to river morphology and decrease in the size 

of sandbars and campsites

2010

1890

photo by R. Stanton

photo by R. Webb

Sandbar erosion and vegetation expansion near 

Palisades

Schmidt and Graf (1990), Kearsley and others (1994)
Pre-dam floods and high-flow experiments

www.gcmrc.gov/discharge_qw_sediment

• HFEs are small and infrequent compared to pre-dam snowmelt floods.

• Dam releases between HFEs do not resemble pre-dam winter flows.
Post-dam Floods and High-flows: Floods scour the bed

Grams and others (2007)

1965 “Channel-cleaning” flows

• Scoured an average of 2.6 m from bed in Glen Canyon, 

eliminating most sand from riverbed in this reach.

• Likely caused in sandbar deposition in Marble and 

Grand Canyons, but that was undocumented. 

Floods in a system with no 

sand resupply cause 

irreversible bed scour
Post-dam Floods and High-flows: Floods build sandbars

1983-86 “high water” spills

• Caused sandbar deposition, followed by erosion

• Scoured vegetation that had colonized since 1963

• Effects observed, but not well documented (Glen 

Canyon Environmental Studies Phase I was just 

initiated)

1980’s floods provided 

demonstration of sandbar 

building; amount of bed scour 

unknown

Schmidt and Graf (1990)
Post-dam Floods and High-flows: Sand supply is limited

1996 experimental flood

• Planned with hypothesis that sand accumulated on bed 

since floods of 1980s

• Caused bar building, but net loss of sand from eddies.

Declining sand concentration 

and increasing sand grain size 

during 1996 flood revealed 

limited sand supply

Schmidt (1999); Topping and others (2000)
Post-dam Floods and High-flows: higher flows build larger 

sandbars

2000 powerplant capacity high flows

Powerplant capacity flows do 

build sandbars, but lower 

flood stage = lower flood 

deposit thickness

Hazel and others (2006)
Post-dam Floods and High-flows: Response linked to sand 

supply

Greater proportion 

of sites with net 

eddy erosion in 

1996

The 2004 and 2008 HFEs 

demonstrated sandbar 

building under conditions 

of greater sand 

enrichment  less erosion 

of sand from storage in 

eddies and channel

1996

2008

Greater proportion 

of sites with net 

eddy deposition in 

2008

Hazel and others (2010); Schmidt and Grams (2011)
Post-dam Floods and High-flows: Floods create backwaters

Building of sandbars during high flows greatly increases the 

area of backwater habitat across a range of flows for a short 

time, but greatest habitat at low flows (below ~ 12,000 cfs)

1 to 6 weeks 

post-HFE

Pre-HFE and 6 

months post-HFE

Grams and others (2010)
Post-dam Floods and High-flows: 

Summary of findings up to start of 2012 HFE Protocol

• Sediment depleted floods scour the bed.

• Sediment-depleted floods can build highelevation sandbars at expense of erosion from 

the channel and low-elevation parts of eddies.

• Floods during sediment-enriched conditions 

build bars without “mining” background sand 

storage.

• High flows should be timed to best take 

advantage of recent tributary sand inputs.

 These findings are basis of the key components of HFE Protocol:

• Tracking sand inputs from Paria River over the summer-fall 

storm season.

• Scheduling HFEs to follow the series of inputs when sand 

storage in Upper Marble Canyon is greatest.

• Scaling the size (magnitude and duration) of HFE to 

“match” the amount of sand accumulation.

Schmidt and Grams (2011); Wright and Kennedy (2011)
HFE-related Science and 

Management Questions:

• With frequent HFEs, will 

sandbars increase in size 

and abundance?

• Will frequent HFEs cause 

sand supply in channel to 

decrease and exacerbate 

sediment deficit?

Pre-dam: 

• Annual floods

• Abundant sand 

supply

• Large sandbars

Post-dam I: 

• Daily small floods

• Limited sand supply

• Eroding sandbars

• Unplanned floods (spills)

Post-dam II:

• Restricted hydropower 

operations

• High Flow Experiments 

(HFEs) 

• triggered by sand 

supply from Paria River

Pre-dam Post-dam I

Pre-HFE Post-HFE

https://waterdata.usgs.gov
The HFE Protocol: 

• Track sand inputs from Paria River 

and model sand budget during 

designated accounting periods

• July 1 – Dec. 1

• Dec. 1 – Jun. 30

• Find the magnitude and duration 

of HFE that “fits” the amount of 

sand available

• Schedule HFE

Wright and Kennedy (2011)
What are the high-flow 

experiments (HFEs) doing?

Debris Fan

HFEs transfer sand from channel and lowelevation parts of eddies to sandbars 

along channel margins

Eroded sandbar before HFE

HFE inundates sandbar

Sandbar following HFE

https://waterdata.usgs.gov
November 2016 High-flow Experiment Sandbar Deposition-1

11/07/2016 11/13/2016

HFE Deposition 

HFE Deposition 

River Mile (RM) 122R

11/07/2016 11/13/2016

River Mile (RM) 119 R
November 2016 High-flow Experiment Sandbar Deposition-2

River Mile (RM) 23L

HFE Deposition filling gullies

11/06/2016

11/13/2016
November 2016 High-flow Experiment Sandbar Deposition-3

River Mile (RM) 23L

HFE Deposition filling gullies

11/03/2018

11/19/2018
What are the HFEs doing?

Most sandbars erode to near preHFE size within 6 to 12 months.

11/17/2014

5/7/2015

9/23/2015

Grams et al. (2018)T
November 2016 High-flow Experiment Sandbar Deposition

River Mile (RM) 23L

Post-2016 HFE

Post-2018 HFE

HFE Protocol period

www.gcmrc.gov/sandbar or www.usgs.gov/apps/sandbar/
Fall 2018 HFE

Results of 2018 HFE on par with previous HFEs

11/1/2018

11/10/2018

www.gcmrc.gov/sandbar Preliminary results, subject to review, do not cite
Rebuilding of sandbars and 

campsites affected by 

tributary floods

• Flash flood and debris flow at 220-

mile in 2018 eroded and wiped out 

middle camp (a long-term monitoring 

site)

• Also eroded gully through upper 

camp

• Both partially rebuilt by 2018 HFE

Middle camp

upper camp

11/3/2018

11/13/2018

RM 220 R
Sandbar size measured in annual fall surveys-1

Total sandbar volume for each bar type

• Very slight upward trends in most bar types 

and in both Marble and Grand Canyon

• Trend is significant (greater than 

measurement uncertainty)

2008 HFE

reattachment bars

Undifferentiated, upper 

pool, and separation bars

Preliminary results, subject to review, do not cite
Sandbar size measured in annual fall surveys-2

• Very slight upward trends in most bar types and in both 

Marble and Grand Canyon

• Large site-to-site variability (large standard error)

Wide, vegetated bars

Narrow to medium 

reattachment bars

Undifferentiated and 

separation bars

Preliminary results, subject to review, do not cite
Cumulative increases in sand 

volume at some sites

Post-HFE 2018

pre-HFE 2012

2012 HFE

Fall 2012 to Fall 2018 increase

Preliminary results, subject to review, do not cite

RM 9 L
Summary of sandbar response to HFEs

• Consistently rebuilding sandbars

• Sandbars consistently erode following HFEs

• But, sandbars are consistently larger than in periods without 

the HFEs

• Erosion continues in years without HFEs

https://waterdata.usgs.gov

Grams et al. (2018)

Preliminary data – do not cite

Preliminary results, subject to review, do not cite
Sandbar morphodynamic model: based on physical processes, 

calibrated to long-term sandbar monitoring data-1

Model applied above the 8000 cfs stage

30-mile bar

λ: Eddy Exchange Coefficient

Cs: Sand Concentration

D: Sand Grain Size

Sd: Sand Deposition Rate

(function of settling velocity, ws)

e: Erosion Rate 

(has the form of exponential decay)

L: Bar Dimensions

A: Submerged (s) and total (tot) area

h: Thickness of submerged (s) and 

exposed (e) bar

model

domain

Preliminary data and results, subject to review, do not cite
Sandbar morphodynamic model: based on physical processes, 

calibrated to long-term sandbar monitoring data-2

Key model equations 

(after Andrews and Vincent, 2007)

Suspended sand flux into eddy:

qqss,iiii = λλVVeeCCss

SSdd = wwssCCee

Deposition rate in eddy:

λλVVeeCCss=λλVVeeCCoo + wwssCCeeAAee

Mass balance in eddy:

Using a linear approximation for the 

concentration of sand in the eddy 

SSdd = wwssCCee = λλheewwssCCss

λλhee + wwss

2

Rearrange:

Mass/time

Mass/area

Total flux in = flux out + deposition

Uses variables routinely measured 

at gaging stations (discharge, 

stage, sand concentration, and 

grain size)

Erosion estimated as a simple 

exponential decay with bar volume:

dd

dddd = −kk

VVdd = SSddAAee Volume/time

where k is rate

parameter (1/s)

Bar “half-life” approximately 2 

years

Preliminary data and results, subject to review, do not cite
Sandbar morphodynamic model: based on physical processes, 

calibrated to long-term sandbar monitoring data-3

In this permutation, the modeled bars 

represent the scaled average of nine

dynamic bars (Mueller et al., 2018).

Deposition depends on the rate (λ) at 

which suspended sand enters the 

eddy using a physically-based 

approach based on particle settling 

velocity (Andrews and Vincent, 2007). 

Deposition does not explicitly depend 

on discharge, but rather the average 

submerged depth of the bar.

The eddy exchange coefficient (λ) and 

erosion rate (e) are optimized to fit 

the measured bar volume. An 

empirical relation relates bar volume 

and area.

Key model inputs are discharge, sand 

concentration, and sand grain size

Time-series plots of discharge, stage, sand concentration and 

grain size for the period modeled at the 30-mile gage

www.gcmrc.gov/discharge_qw_sediment
Best-fit model for nine dynamic bars:

normalized by their maximum measured volume Modeled vs. Measured

The model reproduces peak volumes during floods and minima between floods. 

Sustained intermediate flows such as the 2011 equalization are more difficult to predict. 

Error bars are the standard error in the normalized measured volume. 2011 was not included in the optimization.

Preliminary data and results, subject to review, do not cite
Calibrated using only 5 measurements:

Validated with more than a decade of measurements Modeled vs. Measured

The model is relatively insensitive to the calibration data if they occur over a 

representative range of conditions. This suggests that physical processes are 

reasonably well-represented in the model equations.

Preliminary data and results, subject to review, do not cite
Post-hoc Controlled Flood Scenario Modeling

Model simulations reducing the number of HFEs

Fewer HFEs = reduced sandbar size

Proportion of time sandbars 

are larger during HFE protocol.

Over the period of 

the protocol, 

sandbars are at least 

70% of maximum 

observed size for 80% 

of the time. 

Without protocol, sandbars are 

that large only 20% of the 

time.

Preliminary data and results, subject to review, do not cite
Will HFEs continue to be effective-1?

• Since 2012, the average July-Nov sand inputs have been about 970,000 

metric tons, which is about the same as historical average values

• Paria River continues to be a reliable, but unpredictable, source of sand

• Future success depends on continued sand inputs from Paria and Little 

Colorado rivers

www.gcmrc.gov/discharge_qw_sediment
Will HFEs continue to be effective-2?

Sand Budget in Grand Canyon: 2012-2018

• Alternating segments of significant sand accumulation and 

erosion

• Overall accumulation (but not significant)

 No evidence for overall net evacuation or accumulation 

Glen Canyon Dam

Marble Canyon

+ 2.6 ± 3.1 million metric 

tons sand accumulation

Eastern Grand Canyon

- 1.7 ± 1.3 million metric 

tons sand erosion

Western Grand Canyon

+ 1.3 ± 2.9 million metric tons sand 

accumulation

Overall (Lees Ferry 

to Diamond Creek)

+ 2.2 ± 7.3 million 

metric tons

Little Colorado River

Paria River

www.gcmrc.gov/discharge_qw_sediment
Will HFEs continue to be effective-3?

• Periods of sustained high dam 

releases (e.g. 2011 equalization 

flows) result in net sand evacuation.

• Frequency of equalization years will 

affect long-term sand budget and 

likelihood of continued success of 

high flows.

• Repeat maps of river channel show 

changes in sand storage with wellconstrained uncertainty that does 

not increase over time.

– Requires measurements 

comprising ~60% of a study 

reach or more to see past 

variability

Grams and others (2019)
What are the HFEs not doing?

• Not depositing sandbars substantially 

larger than observed in past HFEs?

• Not depositing sandbars at substantially 

more locations than observed in past 

HFEs.

• Response likely constrained by HFEs 

that are all within narrow range of 

magnitude and duration.

• Response may also be constrained by 

hydrograph shape.

• Not removing vegetation or causing 

channel width to increase

RM 194 L

11/20/2016

4/20/1996
Summary

• Each HFE since 2012 has resulted in 

sandbar deposition

• Increases in sandbar size occur at 50% or 

more of monitoring sites.

• Although bars erode, they are larger than 

they would be without HFEs

– Some bar types are at least 70% of 

maximum size 80% of the time, compared 

to achieving that size only 20% of the time 

before HFE protocol

• HFEs do not scour or remove 

vegetation.

• There is evidence for cumulative increases 

in bar size at some sites.

• Sand budget is indeterminate (no definitive 

evidence for increase or decrease)

– Indicates that it is possible to build sandbars 

with HFEs while maintaining sand supply 

during periods of ~average inputs and 

~average release volumes (no equalization)

RM 9 L

Post-HFE 2018

pre-HFE 2012
Next steps

• LTEMP calls for evaluation of HFE program 

after 10 years of implementation (Oct. 2027)

– In addition to sandbar monitoring results, we 

will have full evaluation of impact on sand 

storage in the channel and low-elevation parts 

of eddies.

• Results indicate future HFEs implemented 

following the protocol should continue to be 

equally successful

• Expect some progressive increases in some 

sandbars

– Likely will reach upper limit constrained by 

magnitude of HFE releases.

• May experiment with hydrograph shape to 

affect sandbar shape (e.g. slope of bar front).

• Address vegetation...

RM 194 L

11/20/2016

4/20/1996
HFE Design Experiments-1

• Extended duration HFEs

– Up to 8-10 days (compared to 4 days as currently implemented)

– Only if there is “enough” sand

– If enough sand, could build larger and more numerous bars

– LTEMP simulations estimated conditions might occur 5 times in 20 

years, LTEMP ROD allows 4 implementations

Makes sense to test when 

conditions occur.

• Monitoring needed for comparison with 

other HFEs

• Monitoring sand concentration

• Sandbar monitoring at all sites with 

complete surveys

• Daily surveys at selected sites to measure 

changes in deposition rates during HFE

1996 HFE was 8 days, but was not designed to 

match recent sand inputs

0

10,000

20,000

30,000

40,000

50,000

-10 -5 0 5 10 15 20

1996

2004

2008

2012

DISCHARGE, IN CUBIC FEET PER SECOND

TIME, IN DAYS RELATIVE TO DEPARTURE FROM NORMAL DAM OPERATIONS

Data from: https://www.gcmrc.gov/discharge_qw_sediment
HFE Design Experiments-2

• Proactive HFEs

– Spring HFE released regardless of sand trigger 

in advance of summer equalization flows

– Goal is to create some high-elevation sand 

deposits in advance of erosion that will occur 

during sustained high releases.

– LTEMP simulations estimated conditions 

might occur twice in 20 years

Makes sense to test when 

conditions occur.

• Monitoring needed for comparison with other HFEs

• Monitoring sand concentration

• Sandbar monitoring at all sites with complete surveys

• Compare deposition with other HFEs

• Measure summer erosion (what is the size of bars following 

equalization compared to before the proactive HFE?)

Conditions in 2011 “inspired” idea 

for proactive Spring HFE – large 

sand inputs during previous fall 

followed by equalization flows

2011 

equalization 

flows

Data from: https://www.gcmrc.gov/discharge_qw_sediment
HFE Design Experiments-3

• Changes to hydrograph shape (lower 

downramp rate)

– Deposition at range of 

elevations, instead of focused at 

elevation of peak stage

– Expected to produce sandbars 

that have lower slope on bar 

face

– Tested in 2012

• Limited monitoring 

indicated some bars did 

have lower slopes

• Bars still eroded, but lack 

enough measurements to 

compare erosion rates.

Since all releases above powerplant capacity count towards the HFE duration, lower 

downramp comes at expense duration of peak sand concentrations. Best experiment might 

be to follow a “regular” 96-hour HFE with slow downramp as part of extended duration HFE 

test.

• Monitoring needed for comparison with other HFEs

• Sandbar monitoring at all sites with complete surveys

• Compare deposition with other HFEs

0

10,000

20,000

30,000

40,000

50,000

-10 -5 0 5 10 15 20

1996

2004

2008

2012

DISCHARGE, IN CUBIC FEET PER SECOND

TIME, IN DAYS RELATIVE TO DEPARTURE FROM NORMAL DAM OPERATIONS

Data from: https://www.gcmrc.gov/discharge_qw_sediment
HFE Design Experiments-4

Surveys before and after 2012 HFE at 3 large reattachment bars

• Bar volume largest in 1996 (highest discharge and longest duration), area 

above 8,000 cfs stage largest in 2012 (gradual downramp)

• Slope from bar crest to 8,000 cfs level less steep than other floods

Preliminary results, subject to review, do not cite

>8,000 cfs

>25,000 cfs

1996 post-HFE

>8,000 cfs

>25,000 cfs

2008 post-HFE

>8,000 cfs

>25,000 cfs

2012 post-HFE

>8,000 cfs

>25,000 cfs

2004 post-HFE
HFE Design Experiments-5

• Low-magnitude HFE (HFE at or near powerplant capacity of 31,500 cfs)

– Not identified as “experiment” in LTEMP.

– Allowed by HFE protocol

– But they have not yet occurred

Is there interest in comparison with larger HFEs 

if a low-magnitude HFE does occur?

• Monitoring needed for comparison with other HFEs

• Sandbar monitoring at all sites with complete surveys

• Compare deposition with other HFEs
Acknowledgements

Erich Mueller, Daniel Buscombe, 

Thomas Gushue, Daniel Hamill, 

James Hensleigh, Joseph Hazel, 

Matt Kaplinski, Robert Ross, Keith 

Kohl, David Rubin, Joel Sankey, 

Jack Schmidt, David Topping, 

Robert Tusso, Scott Wright, ... 

Rod Parnell, Bryan Cooperrider, 

Karen Koestner, Emily Thompson, 

Daniel Hadley, Katie Chapman, 

Ryan Semptua...