Multi-lass Sediment Dynamics and Export in the Fraser River Estuary Philip Orton, David Jay, Tom hisholm Department of Environmental and Biomolecular Systems Oregon Health & Science University Funded by the National Science Foundation Special thanks to Rocky Geyer and Dan Macdonald Ray McQuin and Nikki Hix of the R/V Barnes Influential in research: Gail Kineke and Annika Fain
1-D Inverse Modeling of SPM: Paper submitted to Marine Geology Three-step inverse analysis calibration procedure Bulk calibrations for one or more backscatter sensors SPM decomposition: using a 1-D model, partition total concentration into discrete settling velocity (Ws)-classes Bias correction: corrects sie-dependence of sensor response Sensitivity and properties of inversion tested using synthetic data and Monte arlo methods Near-bed results compare favorably with laser in situ particle sie data (LISST-100) Paper relied on a diffusion-settling model limited!
Presentation Timeline Dynamics of Fraser SPM export ADS: 1-D model with advection Preliminary results for two export regimes You are here SPM decomposition using DS model FADS: 1-D model with advection & flocculation Enlightenment?
Dynamics of Fraser SPM export
Fraser Estuary Bed Sediments sand fine sand clay/silt Sampling during freshet, 1999-2000 Salt wedge estuary Wide range of particle sies in suspension Ebb salt washout transects (x,y,,t) Salt wedge erosion transects (x,,t)
Washout Dynamics at Fraser Mouth freshwater
Ws(d/d) (d/d)[ks(d/d)] u(d/dx) (d/dt) Discrepancy ( ) + + = + + k k s F K Ws w x u t,, Temporal Advective terms Particle settling Vertical diffusion Aggregation Mass continuity of suspended sediment
Ebb-Tide Salt Wedge Erosion 08:25 hrs 08:00 hrs
Upper Layer Dilution (entrainment) Horiontal advection Vertical advection Discrepancy (Agg.?) g g Lower Layer Settling Diffusion Discrepancy (Agg.?)
SPM Decomposition Using Diffusion-Settling (DS) Model
Simplest Model: Diffusion & Settling (DS) = s a a K d Ws ) ( exp ) (,, ( ) + + = + + k k s F K Ws w x u t,, Temporal Advective terms Particle settling Vertical diffusion Aggregation : oncentration in = 1 n Ws-classes Ws : Particle settling velocity K s, : Eddy diffusivity parameteriation (using observations of velocity to estimate turbulence) a, : Reference concentration scales profiles
SPM Decomposition Procedure hoose a reasonable set of Ws-classes Basis function slopes depend on Ws a,1 a,2 a,3 Simulations with artificial data and noise show that # Wsclasses depends upon: (a) vertical number of measurements, (b) noise level in data, and (c) proximity of data to the bed
ADS: 1-D Model with Advection
Advection-Diffusion-Settling (ADS) Integrate from to surface (η) with Leibni s Rule B..: no SPM or water flux across free surface Pseudo-2D model with iterative procedure Start with D-S model estimate for (x,) Invert to find (new) estimates of (x,) Iterate to convergence, bringing (x,) into line with ADS dynamics () = function of a,, Ws, observations, (x,) K s, + x ( Ws ) w + A( ) = 0 where A( ) = η u' d
FADS: 1-D Model with Advection & Flocculation
FADS Vertical Profile Model for Ws-class #2 η 2 2 K s, 2 + ( Ws2 w) + A2( ) + F( ) = 0 where F( ) = N1 d Agg. term is N 12, where N is an agg. rate constant Aggregation is a one-way transfer from 1 to 2 Estimate N in surface layer using a two-layer salt / sediment conservation model 1 horiontal dynamics: aggregation, advection and dilution orrect for dilution via an entrainment velocity (W e ) into the upper layer from SAL insitu 1 is salinity-dependent in vertical
Preliminary Results for Two Export Regimes
Ebb Washout Transect Substantial difference between DS and ADS results ADS results are sensible along-channel gradient in 2 Results are sensitive to spatial averaging of d/dx To obtain convergence, needed to assume 1 was constant DS model ADS model 2 2
Ebb Salt Wedge Erosion Transect Mean entrainment velocity of 7 x 10-4 m s -1 is reasonable compared with MacDonald dissertation result for mouth lift-off one (20 x 10-4 ) Aggregation dynamic term, as modeled, averaged 2 x 10-3 mg L -1 s -1 in surface layer. Ws(d 2 /dz) is O(0.01) DS model 1 : Ws=0.01 mm s FADS model -1 2 2 observed 3 : Ws=10 mm s -1 washload modeled 2 : Ws=2 mm s -1 4 : Ws=50 mm s -1 washload 3 3 4 oncentration (mg L -1 ) 4 oncentration (mg L -1 )
Ebb Salt Wedge Erosion Transect 1 (washload) 2 (aggregates) 3 (fine sand) 4 (bed sand) shear velocity
onclusions Fraser sediment export is dominated by two regimes: (a) washouts, and (b) ebb-tide salt erosion periods These SPM regimes are dynamically relatively simple, and vertical profiles can be modeled using pseudo 2-D approaches Through inverse modeling, we can decompose our observations of SPM into multiple classes Our method has potential to provide routine estimates of in situ Ws-spectra at high spatial resolution difficult to measure directly