Sediment Transport IV Mixed-Size Sediment Transport 1. Partial Transport: frequency & implications

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Sediment Transport IV Mixed-Size Sediment Transport. Partial Transport: frequency & implications using field and laboratory evidence 2. Armor layer persistence investigated using a surface-based transport model. 3. Effect of adding sand to a gravel-bed river leading to a two-fraction transport model

2 The Bed of Many Colors 8 Percent 6 4 2 0 0.25 0.5 2 4 8 6 32 64 GRAIN SIZE (mm)

. Bed Entrainment & Partial Transport

Partial Transport Some grains remain immobile over the course of a transport event Implications for benthic disturbance, bed dynamics & subsurface flushing but occurrence, prevalence undocumented

Measure partial transport in lab, using time series of bed photographs Proportion Active Grains 0.8 0.6 0.4 0.2 Proportion Active Grains 0.8 0.6 0.4 0.2 4.76 mm 6.73 mm 9.5 mm 3.5 mm 9.0 mm 26.9 mm 38. mm 53.8 mm Lognormal 0 τ o (Pa) 0 0. τ o / τ[50] i When Brian McArdell went blind (and a little nuts)

The domain of partial transport 2x 0 Proportion Active Grains 0.8 0.6 0.4 0.2 0 4 8 6 32 45 mm Bed Shear Stress τ 0 (Pa) 2x Grain Size (mm) % active 90% active D[50] ( τ 0) 3/2 Bed Shear Stress τ 0 (Pa)

Partial transport & the entrainment of benthic invertebrates (Steve Kenworthy).0 Proportion of Larvae Recovered in Seed Section(s) Series B 0.8 Proportion of larvae 0.6 0.4 0.2 0.0 2 4 6 8 2 τ ο Hydropsychidae Psephenidae Perlidae Ephemerellidae Atherix E

Field Observations of Partial Transport () Carnation Ck, BC 3000 magnetically tagged stones Judy Haschenburger, U. Auckland

2 yr flood 7 yr flood

Field Observations of Partial Transport (2) Harris Ck, BC Freq. % moved 989 >2 yr 60% 990 > 30 yr 88% 99 >2 yr 36%

Bed mobilization increases consistently with flow and grain size Substantial transport occurs over a partially mobile bed Partial transport persists from year to year complete disturbance not an annual event

2. Bed surface composition: Armoring & the problem of predicting transport rates

Stream-bed armoring is pervasive in gravel-bed steams Armor Ratio = D50 (surface) D50 (subsurface) Bed surface composition determines Streambed Armoring Frequency 50 45 40 35 30 25 20 5 5 0 0- -2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 Armor Ratio Mean: 2.80 Std. Deviation: 2.06 Median: 2.6 9- - -2 2-3 3-4 4-5 5-6 grains available for transport hydraulic roughness bed permeability living conditions for bugs & fish

The armor problem We can measure the bed surface size at low flow, but not at flows moving sediment, so We don t know what the bed surface looks like at the flows that create it Does the armor layer stay or go during floods?

With no field observations of armor change, we turn to the lab for guidance on armor persistence Doing this will sharpen our thinking about how rivers work at different scales of space and time Two ways to run flumes experiments: Feed Sediment Recirculate Sediment Q, Qs Q Qs Sediment Recirculate Sediment Feed Q, Qs Q

Sediment Feed Experiments As feed (transport) rate increases, bed surface becomes finer And approaches size of transport (and bed subsurface) D50 - Surface (mm) 0 Kuhnle Lisle et al. Seal et al. Dietrich et al. Wilcock & McArdell D50t / D50s.2 0.8 0.6 0.4 0.2 0.00 0.0 0. Dimensionless Transport Rate 0 0.00 0.0 0. Dimensionless Transport Rate

Sediment Recirculation Experiments As flow ( transport) increases, Transport grain size increases, while bed surface grain size remains relatively constant Approaching the size of the bed subsurface 0 0 J06 J4 J2 J27 BOMC D50 - Transport (mm) 0. 0 0.05 0. 0.5 water discharge (m^2/s) D50 - Surface (mm) 0 0 0.05 0. 0.5 water discharge (m^2/s) D50t / D50s 0.8 0.6 0.4 0.2 0 0.05 0. 0.5 water discharge (m^2/s)

In both cases, as transport rate increases, the transport coarsens relative to the bed surface D50t / D50s.2 0.8 0.6 0.4 FEED In the feed flume, this is accomplished via fining of the bed surface In the recirculating flume, this is accomplished via coarsening of the transport D50t / D50s 0.2 0 0.00 0.0 0. 0.8 0.6 0.4 0.2 Dimensionless Transport Rate RECIRCULATE 0 0 0.05 0. 0.5 water discharge (m^2/s)

So, does armor stay or go? Does it depends on how you think a river works? Depends on time & space scale of the problem Consider the essential flaws of the two flume types: Feed Transport has constant grain size Q, Qs Q Qs Internal Control External Control Recirculate Final equilibrium sensitive to initial conditions Q, Qs Q

To address the armor problem, we have to tackle the transport problem Transport rates depend on transport of grains available for transport on bed surface But nearly all transport data provide composition of the bed subsurface, not surface! This means that the resulting transport models must somehow implicitly account for surface sorting (armoring) NOT a good way to build a general model

Transport Modeling Basics - Given fully rough flow with boundary stress τ, sediment of mean size D m, with individual fractions of size D i and proportion f Transport rate q i. bi depends on q = fn ( f, D, D, τ, sed) bi i ri 2 ( τ, τ ( D m bi ri ), D i / D i where sed = other sediment properties. We search a transport model of form q f τ = = fn fn m i,sed) m where τ ri is a reference value of τ near the onset of sediment motion But, what size distribution should we use for f i? ans: surface

There are essentially no surface-based transport observations, so we made some Built five sediments, adding sand to gravel Sand: 0.5 2.0 mm Gravel: 2.0 64 mm Sand Content: 6%, 4%, 2%, 27%, 34% 9 or runs with each sediment, over a wide range of transport rates Depth & width held constant, primary variables are sand content & flow strength Every run: measure flow, transport rate & grain size, and bed surface grain size (point counts of photos of colored grains)

5 5 0 5 5 0 5 5 0 5 5 0 5 5 0 J06 J4 J2 J27 BOMC y y 0.2 0.4 0.7 2.0 4.0 8.0 6.0 32.0 64.0

Transport Modeling Basics - 2 To develop a general transport model, we nondimensionalize q F in the form of a similarity collapse where W * i = ( s F ) gq ( ) 3/ 2 τ / ρ F i surface proportion; g gravity; i ρ water density; s sed spec. gr. bi bi i = fn ( τ, τ ri * W i = fn ) 3 τ τ ri The Point: The transport function does not contain grain size!

How to make a transport model () Plot W* i vs τ; (2) Find τ ri at W* r ; (3) Plot W* i vs. τ/τ ri ; (4) Stand back, admire * W i * W r 0. 0.0 0.00 0.000 Sediment = J4 0.7.9.68 2.38 3.36 4.76 6.73 9.5 3.5 9.0 26.9 38. 53.8 tref tr fn 0 τ (Pa) * W r * W i 0. 0.0 0.00 0.000 Sediment = J4 0. τ/τ ri

All that remains is to explain τ ri 0 Sediment = J4 τ ri 0. 0 Grain Size Di (mm)

Surface-Based Transport Model All sizes, All runs, All sediments * W i 0. 0.0 0.00 0.000 0.0000 0. 0 τ /τ ri

Values of τ ri for all sizes and all sediments τ ri 0 J06 J2 BOMC Surface Dm J4 J27 S hie lds 0. 0. 0 D i Grain Size (mm)

Values of τ ri collapse nicely when divided by values at the mean size D sm τ ri τ rsm 0. 0.0 0. 0 D i D sm J06 J4 J2 J27 BOMC A 'hiding' function The resulting hiding function completes the surface-based transport model Wilcock, P.R. & Crowe, J.C., J. Hydr. Eng., 2003

Surface-based transport model can be used in both forward & inverse forms Forward: predict transport rate & grain size as function of τ and bed surface grain size Inverse: predict τ and bed surface grain size as function of transport rate & grain size Don t try this with a subsurface based model! The inverse model provides a useful tool for considering armor persistence because we do have good transport data from the field

Transport grain size increases with flow! isbtm not only predicts a persistent armor layer, it also predicts the surface grain size observed in the field! (a) Percent Finer (b) Median Grain Size (mm) 0 90 80 70 60 50 40 30 20 0 Oak Ck, OR Grain size of transport (measured) and bed surface (calculated) 0.00025 0.00025 0.003 0.003 0.0042 0.0042 0.0072 0.0072 0.033 0.033 0. 0. Surface 0 0. 0 00 Grain Size (mm) Transport Rate (kg/ms) Surface D50 Transport D50 0.000 0.00 0.0 0. Transport Rate (kg/ms) Solid symbols: predicted surface grain size

Again, transport grain size increases with flow! Again, isbtm predicts a persistent armor layer. This time it overpredicts the surface grain size observed in the field! Reason: dunes! (a) Percent Finer (b) Median Grain Size (mm) 0 90 80 70 60 50 40 30 20 0 0 Goodwin Ck MS Grain size of transport (measured) and bed surface (calculated) 0.002 0.002 0.0 0.0 0.056 0.056 0.85 0.85 0.706 0.706 SURF 0. 0 Grain Size (mm) Transport Rate (kg/ms) Surface D50 Transport D50 0. 0.00 0.0 0. Transport Rate (kg/ms) Solid symbols: predicted surface grain size

At reach and storm scales of space and time Armor layer grain size appears to be persistent a real advantage for predicting roughness & transport during floods: a low flow measurement of bed composition may suffice (unless dunes develop) Increasing transport grain size balances change in grain mobility to produce a constant bed surface A SBTM needed to model transients

3. How does increasing the supply of fines (sand) affect the gravel transport? Previous Experiments Jackson & Beschta (984) Ikeda & Iseya (988) Adding sand increases gavel mobility.

5 5 0 5 5 0 5 5 0 5 5 0 5 5 0 J06 J4 J2 J27 BOMC y y 0.2 0.4 0.7 2.0 4.0 8.0 6.0 32.0 64.0

Gravel transport rate [g / (m s)] 00 0 0. 0.0 0.00 0.000 J06 J4 J2 J27 BOMC 0.0000 0. 0 Bed Shear Stress (sidewall-corrected; Pa)

Sand content has a huge effect on gravel transport rates Model two fractions: How to generalize? Use a similarity collapse Use one scaling parameter, the reference shear stress τ r (a surrogate for the critical shear stress for incipient motion) Sand & Gravel W * = ( s ) gq ( / ρ ). 5 τ o τ /τ r bi

00 0 0. 0.0 0.00 0.000 0.0000 0. 0 Bed Shear Stress τ (Pa) 0. 0.0 0.00 W * r 0.000 0.0000 τ r 0. 0 Bed Shear Stress τ (Pa) 0. 0.0 0.00 0.000 0.0000 0. 0 τ /τ r J06 J4 J2 J27 BOMC Gravel transport rate qbi [g / (m s)] Dimensionless transport rate W* Dimensionless transport rate W*

Include field data to broaden model basis Oak Creek, Or (Milhous, Parker et al.) Goodwin Creek MS (Kuhnle) East Fork River WY (Emmett & Leopold) Jacoby Creek CA (Lisle)

W i * (a) Lab Data W i * (b) Field Data 0. 0. 0.0 0.0 0.00 0.00 0.000 0.000 0.0000 τ / τ ri 0. 0.0000 τ / τ ri 0. Both sand & gravel fractions plotted

Model collapse reasonably good; leaving a single similarity parameter to explain: the reference shear stress, τ r It provides a clean description and prediction of the effect of sand on gravel transport

Framework Supported Matrix Supported (a) * τ rg 0.05 0.04 0.03 Field Lab 0.02 0.0 0 0 0. 0.2 0.3 0.4 0.5 0.6 Sand Content of Bed τ * rg = ( s τ rg ) ρgd Wilcock, P.R. and Kenworthy, S.T., 2002, A two fraction model for the transport of sand/gravel mixtures, Water Resources Research, 38(). Wilcock, P.R., Kenworthy, S.T. and Crowe, J.C., 200. Experimental study of the transport of mixed sand and gravel, Water Resources Research Wilcock, P.R., 998. Two-fraction model of initial sediment motion in gravelbed rivers, Science 280:4-42

Test sand effect in a sediment feed flume Feed gravel (2-32 mm) at same rate in each run; Increase sand feed rate from much less to much more than gravel Results As sand feed increases, Bed gets sandier & Slope decreases: less stress is required to carry same gravel load and increased sand load 800 600 400 200 0 0.8 0.6 0.4 0.2 0 0.03 0.025 0.02 Gravel Feed Rate Sand Feed Rate 0 200 400 600 800 Feed Bed Surface 0 200 400 600 800 Bed Slope 0 200 400 600 800 Total Fe e d Rate (g/ms) Crowe, J.C. & P.R. Wilcock, in review, The Effect of Sand Supply on Transport Rates in a Gravel-Bed Channel, submitted to J. Hydraulic Engineering

The point? Adding sand can have a huge effect on gravel transport rates & there are lots of reasons why sand supply to a gravel-bed river might be increased fire, urbanization, reservoir flushing, dam removal & a two fraction approach captures this effect in a tractable framework

But there are more reasons to like a twofraction transport model! Robust! Mappable! Captures sand/gravel interaction! Little Granite CK, nr Bondurant WY

Some essential acknowledgements Alan (partial transport) Barta Brian (Mr. BOMC) McArdell Steve (buginflume) Kenworthy Joanna (million pts of color) Curran Brendan (isbtm) DeTemple

Summary Armor layers persist May be only partially active in a typical flood sand supply mobility of coarse grains Surface-based model available for predicting transient transport 2-fraction model available as a robust alternative