Sandbars and Sediment Storage in Marble and 

Grand Canyons: Response to Recent High-flow 

Experiments and Long-term Trends 

GCMRC Project 3 

Paul Grams1 , Daniel Buscombe1, Tom Gushue1, Dan Hamill, Joseph 

Hazel2, Matt Kaplinski2, Keith Kohl1, Erich Mueller1, Robert Ross1 , 

Robert Tusso1 

1U.S. Geological Survey, Grand Canyon Monitoring and Research Center 

2Northern Arizona University 

photo : Michael Collier 
 

Project 3 

3.1 Sandbar Monitoring and Research 

3.1.1 Annual Sandbar Monitoring (this talk) 

3.1.2 Sandbar Monitoring by Remote Sensing (Sankey talk) 

3.1.3 Use of Structure-from-motion Photogrammetry (poster) 

3.1.4 Analysis of Historical Photographs (not covered) 

3.2 Long-term Sediment Storage Monitoring and Research (this talk and poster) 

3.3 Sandbar Modeling (this talk) 

3.4 Bedload Sand Transport (poster) 

3.5 Control Network and Survey Support (not covered) 

photo : Michael Collier 

Outline 
 

 

 

Sediment budget affected by disruption of sand 

supply and change in flow regime
 

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) 
-

 

 

Pre dam: 

• Annual floods 

• Abundant sand 

supply 

• Large sandbars 

Post-dam I: 

• Daily small floods 

• Limited sand supply 

• Eroding sandbars 

• Unplanned floods (spills) 

Pre-dam Post-dam I 

1952 2003 

Ratio of observed sandbar area to maximum 

potential sandbar area (reach-average) 

1935 

1965-1996 1996-2009

1935 

1965-1996 1996-2009

1935 

1965-1996 1996-2009

1935 

1965-1996 1996-

1935 

2009 

1965-1996 1996-2009 

RM: 

29-35 

RM: 

0-8 

RM: 

42-49 

RM: 

50-56 

RM: 

60-72 

About 25% reduction in 

sandbar area in Marble 

Canyon (Schmidt et al., 2004; 

Ross and Grams, 2015) 
-

-

Pre dam: 

• Annual floods 

• Abundant sand 

supply 

• Large sandbars 

Post-dam I: 

• Daily small floods 

• Limited sand supply 

• Eroding sandbars 

• Unplanned floods (spills) 

Pre-dam Post-dam I 

Overarching Questions: 

• With frequent floods, will 

sandbars increase in size 

and abundance? 

• What will happen to sand 

storage with frequent 

floods? 

Post dam II: 

• Restricted hydropower 

operations 

• controlled floods triggered 

by sand supply 

Pre-HFE Post-HFE 
 

Eddy-deposited sandbars in Grand Canyon 

–	 Campsites 

–	 Habitat 

–	 Source of sand for upland areas 

–	 At least about 1400 eddies that may contain large 

sandbars between Lees Ferry and Diamond Creek 

(based on inspection of air photos} 

– 569 sandbars that may form backwater habitat 

based on inventories done in 2008 

Debris Fan 

Eroded sandbar before flood 

Sandbar deposited by 

controlled flood 
3.1.1 Sandbar 

Monitoring
 

•	 What is effect of 

individual HFEs? 

•	 What is cumulative 

effect of HFEs and dam 

operations? 

•	 Topographic Surveys 

•	 Photographs 

from automated 

remote cameras. 
Major Components of Sandbar and Sediment Storage Monitoring
 

• Sandbar monitoring 

•	 Annual topographic surveys at 47 sites 

•	 Daily photographs (42 sites) 

•	 High-elevation sand only (above 8,000 ft3/s 

stage) 

•	 Long-term record back to 1990 

•	 Denser network of sites in Marble Canyon than 

Grand Canyon 
Annual Sandbar 

Monitoring
 

Period of HFE Protocol 

• Blue arrows/lines show each 

HFE 

• Surveys are ~11 months after 

most recent HFE 

preliminary data, do not cite 
Annual Sandbar 

Monitoring
 

• Largest increase is during 

2012 HFE 

Period of HFE Protocol 

• Blue arrows/lines show each 

HFE 

• Surveys are ~11 months after 

most recent HFE 

preliminary data, do not cite
 
Annual Sandbar 

Monitoring
 

Period of HFE Protocol 

• Blue arrows/lines show each 

HFE 

• Surveys are ~11 months after 

most recent HFE 

• Largest increase is during 

2012 HFE 

• Bars largest in October 2014 

preliminary data, do not cite 
Annual Sandbar 

Monitoring
 

preliminary data, do not cite 

Period of HFE Protocol 

• Blue arrows/lines show each 

HFE 

• Surveys are ~11 months after 

most recent HFE 

• Largest increase is during 

2012 HFE 

• Bars largest in October 2014 

• “Balancing” flows peaking at 

20,000 cfs likely caused more 

erosion than previous years. 

• Consistently larger than 

“average” for period without 

regular HFE’s 
November 2016 High-flow Experiment Sandbar Deposition
 

River Mile (RM) 119 R 

11/07/2016 11/13/2016 

HFE Deposition 

HFE Deposition 

River Mile (RM) 122R 

11/07/2016 11/13/2016 
November 2016 High-flow Experiment Sandbar Deposition
 

HFE Deposition 

River Mile (RM) 213L 

11/07/2016 11/15/2016 

•	 Post 2016 HFE images available from 14 out 45 monitoring 

sites. 

–	 Net deposition at 9 sites 

–	 Erosion at 2 sites 

–	 No net change at 3 sites 

•	 Images from remaining sites will be collected in February 

preliminary data, do not cite
 
 

 

Sandbar Research, Data 

Processing, and Online Access
 

•	 25 years of data to 

manage 

–	 Web tool for data 

storage and viewing
 

–	 Scripted data 

processing tools 

–	 New database for 

centralized storage 

and data management 

Photos at www.gcmrc.gov 

Sandbar data at www.gcmrc.gov/sandbar/
 
 

•

•

•

View is looking upstream 

Black dots are 0.1 mi intervals 

Project 3.2: In-channel Sand Supply: 

Research and Long-term monitoring 

Periodic repeat mapping to 

measure trends in sand 

storage 

– Will dam operations 

(including HFEs) cause 

increase, decrease, or stable 

sand supply? 

– If changes occur, where do 

they occur? 

What is “total” supply of 

sand in channel? 

What are the relative 

proportions of “recent” 

sand from the Paria River 

and “old” sand in HFEdeposited sandbars? 

(see Katie Chapman’s poster) 
 

-

 

Results: closed sand budget for Lower Marble Canyon: 

May 2009 to May 2012
 

•	 Both budgets have large 

uncertainty
 

•	 Good agreement between 

methods
 

• Sand loss during equalization flows 

–	 Over short (3-year) period have similar 

uncertainty to flux measurements)
 

–	 Over long (10-20 year) period have 

much less uncertainty than flux 

measurements
 

Cumulative flux based sand budget 

Morphologic budget 

May 2009 May 2012 

May 2009 May 2012 

Grams et al. (2015) 
Area shown on 

previous slide

 

topographic change

(meters)

< -2 m

-1.9 - -1

-0.9 - -0.5

-0.4 - -0.3

-0.2 - -0.1

0

0.1

0.2 - 0.3

0.4 - 0.5

0.6 - 1

1.1 - 2

> 2 m

Small changes at most 

locations, but large 

changes at some locations
 

Grams et al. (2015) 
 

 

Better Estimates of “!bsolute” sand 

storage 

• Based on: 

– Measured topography/bathymetry 

– Bed composition 

– Dune heights in channel 

– Assumptions for sand thickness* 

 5 to 13 million m3 (7 to 21 million metric 

tons) sand in eddies and channel in Lower 

Marble Canyon. 

1 million metric tons is about the amount of 

sand delivered by the Paria in a good input 

season (like 2016). 

* Will refine these assumptions using measurements of sand thickness made in 2016
 

Preliminary results, do not cite
 

 

 

Eastern Grand Canyon: 2011-2014 

Tapeats 

Gorge Furnace Flats Granite Gorge 

•	 Most of the net sand evacuation for the first 3 years of this period was from pools in 

the upper Granite Gorge. 

•	 Most of the erosion is not from sandbars on the channel margins, but from the deep 

parts of eddies and the center of the channel. Preliminary results, do not cite 
 

Project 3.2: In-channel Sand Supply: Research 

and Long-term monitoring 

• Validation and context for flux-based sand mass 

balance (project 2) 

– Measurements are independent of the acoustical 

measurements of concentration 

– Measurements reveal locations of change in sand storage 

– Only method to allow estimates of the absolute sand storage 

• Advances on methods for bed classification using a 

range of acoustic methods (high-end to inexpensive) – 

See Dan Hamill poster 

• Provides data used for a range of applications: 

– Bed composition for aquatics and fish habitat 

– Channel bathymetry/topography for new and improved flow 

models 

• Better estimates of sand transport as bedload – See 

Tom Ashley poster 

• May lead to refining expectations for sand supply and 

sandbar response in different segments of the canyon 
 - 

 

Mean changes in normalized bar 

volume at same sites 

• Error bars are standard error 

• Larger uncertainty, owing to 

variability among sites 

3.3 Sandbar Modeling 

•	 What is relation between channel 

shape and sandbar characteristics? 

•	 What is relative importance of site 

characteristics, streamflow, and 

sediment supply in determining 

sandbar response to HFEs? 

We know what the monitoring 

sites are doing, less confident 

extrapolating to “all sandbars” 

Preliminary results, do not cite 

Sum of changes in sand volume at all long 

term monitoring sites (“N!U sites”) 

• Error bars are measurement uncertainty 

• Small, because measurements are 

accurate and precise 
-

Grouping sites of similar behavior and 

>40 monitoring sites 

statistical classification 

(PCA + k means) 

structure 

Observations of similar 

behavior among sites with 

similar vegetation cover 

Low 

veg 

Med. 

Veg. 

High 

Veg. 

•	 Abundance of perennial vegetation is 

one of the characteristics that 

distinguishes site behavior 

•	 Vegetation and channel shape have 

stronger influence on bar response 

than distance downstream 

 Progress towards a process-based 

model for sandbar response 

Preliminary results, do not cite Mueller et al. (in review)
 
What is the effect of changing the hydrograph 

of the high flow?
 

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
 

 

Post-HFE Sandbar Shape
 

>8,000 cfs 

>25,000 cfs 

>8,000 cfs 

>25,000 cfs 

>8,000 cfs 

>25,000 cfs 

>8,000 cfs 

>25,000 cfs 

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 data subject to revision – do not cite. 

1996 post-HFE 2012 post-HFE 2004 post-HFE 2008 post-HFE 
Physical model for Grand Canyon sandbars: July 2016 Pilot Study
 

Colorado River in Grand Canyon
 St. Anthony Falls Hydraulic Lab, 

University of Minnesota 

Objectives for pilot project:	 Ultimate objective: 

•	 Can we make a physically realistic • Develop predictive relations for bar 

recirculation zone (eddy)? shape based on channel 

•	 Describe flow and morphology for characteristics, streamflow, and 

comparison with numerical model and sediment conditions 

validation. 
With a few 

modifications
 

~ 1:50 geometric scaling of channel 

Froude scaling of flow 

v1 v2

=

gd1 gd2

16.5 m 

2.74 m 
Experimental Runs and
 

Measurements
 

Run Flow 

(l/s) 

Froude 

Number 

Duration 

(hr) 

Measurements 

1a 90 ~0.6 24 Bed topography, PIV 

1b 90 ~0.3 26 Bed topography, PIV, ADV 

Bed regraded to flat 

2 165 ~0.5 17 Bed topography 

Bed regraded to flat, moved constriction 

3 165 ~0.5 4 Bed topography 
 

Run 1 – ~90 l/s 

• No deposition in constriction 

• Rapid initial development of 

scour hole 

• Slow lengthening of scour 

hole 

• Slow downstream migration 

of mid-channel dune 

• Deposition of bar in 

recirculation zone upstream 

from reattachment point 

Run1: initial bed 

end of 1a (Fr = 0.6) 

end of 1b (Fr = 0.3) 

Preliminary results, do not cite 
 

Recirculating flow 

characteristics in 

lab, model, and field
 

Images for PIV (playing ~ 0.4 x actual speed) 

Field-scale LES PIV in flume 

Mean velocities in flume about 

1/10 field scale, but different 

distribution tail (PIV vs model?).
 

Detached eddy simulation model at flume scale Preliminary results, do not cite 
 

Rate and Pattern of Morphological Development
 

Using downstream dune as index: 

morphological development is 

function of time, discharge, and
 

constriction shape/position
 

Preliminary results, do not cite