quest4d workshop sediment dynamics and increasing anthropogenic pressure: ways forward? flanders...

Quest4D WorkshopSediment Dynamics and Increasing Anthropogenic Pressure: Ways

Forward?Flanders Hydraulics Research, May 14th, 2009

Management Unit of the North Sea Mathematical ModelsMUMM | BMM | UGMM

http://www.mumm.ac.be/

Sediment Transport ModellingBelgian part of the North Sea

Dries Van den Eynde, Michael Fettweis, Fritz Francken, Vera Van LanckerManagement Unit of the North Sea Mathematical Models

Jaak Monbaliu, Erik ToormanKatholieke Universiteit Leuven

Job Janssens, Joris Vanlede, Toon Verwaest Flanders Hydraulics Research





Overview Two sediment transport models

– Transport of material in suspension MU-STM– Transport of sand MU-SEDIM

New developments– Bottom model– Flocculation model

Conclusions





Sediment transport model mu-STM Semi-Lagrangian model – based on Second Moment

Method Bottom stress under influence of currents and waves Erosion and sedimentation Consolidation model with different layers in the bottom Boundary conditions

Applications– Dispersion of dumped material – optimisation of dredging

works– Sediment balance for the Belgian Continental Shelf

Turbidity maximum is a natural phenomenon not caused by the dumping Most of the material that enters the BCS from the Dover Strait,

disappears to the North





Sediment transport model MU-SEDIM Bottom stress as function of currents and waves: Bijker formula Bottom roughness

– Skin-friction, roughness by bottom load, roughness by bottom ripples

Shields-criterium for start of sediment transport Different formulae for local total load

– Ackers-White (1973) with adaptations of Swart (1976, 1977) many different formulae available, results vary of orders of

magnitude Continuity for bottom: erosion and sedimentation

Applications– Modelling of volumetric changes of Kwintebank, assess effects of

sand extraction– Modelling sediment transport at wind mill farms





Q4D Sediment transport model

MU-STM MU-SEDIM

Multi-classesFlocculation

model

Bed modelGeological information

Armouring Sand/mud layers





Fall velocity of flocs

p : density of primary particles grain size analysis, OM, CaCO3 of SPM sample (2580 kg/m³)

w : density of water CT measurements

Df : floc size LISST measurements

Dp: primary particle size grain size analysis of SPM sample (1.8 µm - 7.2 µm)

: molecular viscosity

g : gravitation constant

f : density of flocs

nf : fractal dimension

, : parameters of sphericity of flocs

Re : floc Reynolds number

2

18

1f

wffv gDw

Stokes law

Flocs with fractal structure (Winterwerp, 1998)

687.0

1

3

Re15.0118

nffnf

pwp

fv

DgDw





Flocculation models (settling velocity) Kwintebank: 2-11 March 2004





Bioflocculation model Maggi

dt

dV

dt

dV

dt

dV BM

2

3

2/3

43

111

1 fnfpf

bnff

anfp

nffM D

DD

Gk

D

Gck

D

Dnf

dt

dV

Calculates floc formation and breakup under influence of turbulence, SPM, primary particle size, fractal dimension, organic fraction, biomass growth

GDB

Bf

f

BB

dt

dV

dt

dD

dD

dV

dV

dV

dt

dV





Result 1D





Towards 2D model Definition of the parameters over the BCP

– Organic content– Other parameters





Result 2D





Geology - Tertiary and Quarternary clay

Compact cohesive sediments in first m

Fettweis et al. 2007. Mud origin, characterisation and human activities (MOCHA). Belgian Science Policy.





2.6 2.8 3 3.2 3.4

51.1

51.2

51.3

51.4

51.5

51.6

Fresh m ud =1300 kg/m ³

Soft/m edium cons. m ud =1500-1800 kg/m ³





Biological activity and sediment erosion/stabilization

Ensis directus (American jackknife clam) at Koksijde after a storm

Invasive species

Lives in great numbers and high densities in sandy substratum.

Can be released due to extreme events (storm)

Empty shells in high densities can form “reef” structures.

Spatial extent of Ensis beds will be available by autumn ’09: Belgian Science Policy project ‘Ensis’ (2009-2011)

Photo F. Kerkhof





Critical erosion shear stress measurements Very soft consolidated mud (navigation channel)

•Critical shear stress measurement: 0.5-4Pa (top), 4-9 Pa (rest)•Bulk density: 1.3-1.6 g/cm³(carried out by Westrich & Jancke, Stuttgart Univ.)

Fluid mud on top, sandy with shell fragments; very soft mud with intercalation of sand layers





Bed model: parent bed – active bed

In order to incorporate erosion of old sediments the bed is split in active & parent partActive layer: consist of different sub-layers to allow consolidation of mud, pore filling of sand by mud and segregation between sand/mud layers

Cohesive sediments (fine, mixed)•Active bed layers: ce < 4 Pa, sedimentation/erosion processes, corresponds to recent sediments•Parent bed layer: ce > 4 Pa, only erosion processes, corresponds to old sediments (Holocene, tertiary clays near surface)

Sandy sedimentsactive & passive layers





Bed model - variables

Erosion characteristics: ce at surface ce averaged over the depth interval• Density averaged over the depth interval• Mass over the depth interval• Critical erosion rate averaged over the depth interval

Maps are constructed based on geological constraints and erosion flume experiments

2.6 2.8 3 3.2 3.4

51.1

51.2

51.3

51.4

51.5

51.6

Vers afgezet slib <1.0 N /m ²

W einig/m iddelm . gecons. s lib 1.4 N /m ²< <2.0 N /m ²

cr

cr

Recent mud ce <4PaCompact mud ce > 4Pa





Bed model - variables

Sediment characteristics:• 8 grain size classes from gravel to clay• Clay is defined as fraction <8 µm is based on the difference

between sortable silts and aggregated particles (Chang et al., 2007)• Cohesive – non cohesive behaviour is based on Van Ledden et al.

(2004) adapted according to clay definition

Maps are constructed based on sedimentological data





Bed model - ternary diagram

Most sediments fall into

I : non cohesive sand dominated

II : cohesive mixed sediments

III : non-cohesive mixed sediments

IV : cohesive clay dominated

Van Ledden et al. (2004)

Silt content [0.008<%<0.063mm]

0

10

20

30

40

50

60

70

80

90

100

Clay content [%<0.008mm]

0

10

20

30

40

50

60

70

80

90

100

Sand content

0102030405060708090100

IV

VI

VIII

II

I

40%

50%





Bed model cohesive/non cohesive

2.3 2.4 2.5 2.6 2.7 2.8 2.9 3 3.1 3.2 3.3 3.4 3.5 3.6

51.1

51.2

51.3

51.4

51.5

51.6

51.7

51.8

I - Sand dominated non-cohesive sediments

II - Sand dominated cohesive sediments

IV - Clay dominated cohesive sediments





Conclusions Flocculation model gives good predictions of the floc

size Dependent on geographical distribution of parameters

like fractal dimension, …

Bed model: active and parent bed Geological, sedimentological and erosion behaviour are

included Biological data: more data will become available

Further work: model simulations– Armouring– Different layers of sand / mud

quest4d workshop sediment dynamics and increasing anthropogenic pressure: ways forward? flanders...

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