H T WIEK AREA (B S )....V2 and a roughness length of 0.006m at station V3. 69 Figure 4.17:...

SOES 6030 Advanced Independent Oceanography Research Project

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ALICE LEFEBVRE 2004-2005

UNIVERSITY OF SOUTHAMPTON SCHOOL OF OCEAN AND EARTH SCIENCES

UNIVERSITÉ BORDEAUX 1

UFR DES SCIENCES DE LA TERRE ET DE LA MER

Hydrodynamic impact and sediment mobility at gravel dredge pits: a case study of the Tromper Wiek area (Baltic Sea).

Alice Lefebvre University of Southampton School of Ocean and Earth Science

i

Contents List of Figures iii List of Tables iv List of Plates v List of Annexes v 1. Introduction 1

1.1. General introduction 1 1.2. Marine aggregates extraction 1 1.2. Studied area 8 1.3. Objectives 12

2. Theoretical background 13 2.1. Sediment mobility 13

2.1.1. Introduction 13 2.1.2. Currents 14 a) Generalities 14 b) Current-induced bed shear-stress 15 2.1.3. Waves 16 a) Generalities 16 b) Wave-induced bed shear-stress 18 2.1.4. Combined waves and currents 20 2.1.5. Threshold of motion 21

2.2. Suspended sediment concentration 23 2.3. Grain size analysis 26

3. Materiel and Methods 28

3.1. Instrumentation 28 3.1.1. Electro-Magnetic Current Meter 28 3.1.2. Pressure sensor 29 3.1.3. Optical Backscatter Sensor 29 3.1.4. Wavelog 30

3.2 Field experiment 31 3.2.1. Deployment 31 3.2.2. Sediment samples and meteorological conditions 33

3.3. Calibration 33 3.4. Grain size analysis 35

3.4.1. Sieving and weighing 35 3.4.2. Settling tower 36 3.4.3 Coulter Counter 37 3.4.4. Total Particle Size Distribution 38

3.5. High frequency data processing 38 3.5.1. Pressure 38 3.5.2 U and V components of the flow 39 3.5.3. Turbidity 40



ii

4. Results 42 4.1. Sediment characteristics 42

4.1.1. Video 42 4.1.2. Seabed sediment 43 4.1.3. Bottles sediment 46

4.2. General conditions during the experiment 48 4.2.1. Meteorological conditions and waves 48 4.2.2. Water level variations 51 4.2.3. Currents 53 a) Comparison of methods 53 b) Currents description and analysis 54 4.2.4. Suspended sediment concentration 56

4.3. Comparison of data at the three stations 57 4.3.1. Currents 57 4.3.2. Waves 58 a) Wave height and period 58

b) Directional wave spectra 59 c) High frequency surface elevation 60 4.3.3. Suspended sediment concentration 62

4.4. Sediment mobility 64 4.4.1. Current-only bed shear stress 65 4.4.2. Wave orbital velocity 65

a) Amplitude of the wave orbital velocity under the crest and under the trough 67 b) Comparison of theoretical and measured wave orbital velocity 68 c) Differences between the stations 68

4.4.3. Wave-only bed shear-stress 69 4.4.4. Total bed shear-stress 70 4.4.5. Fraction of sediment on motion 72

4.5. Suspended sediment concentration 74 5. Interpretation 77

5.1. Hydrodynamics effects 77 5.2. Effects on sedimentation 78

6. Conclusions 82 Bibliography 84 Annexes 89



iii

List of Figures Figure 1.1: The two most commonly used methods for marine aggregates extraction.

A. Anchor hopper dredging, B. Trailor suction dredging. 3 Figure 1.2: Possible biological impacts of marine aggregate extraction. 5 Figure 1.3: Chain of possible effects caused by changing the bathymetry. 6 Figure 1.4: Reduction of current and wave velocity by increasing the water depth

in dredged area. 7 Figure 1.5: Zone of study. 9 Figure 1.6: Generalized sediment distribution map for the whole of Tromper

Wiek Bay and sites of marine aggregate extraction. 10 Figure 1.7: Side Scan Sonar from Tromper Wiek Bay. 11 Figure 2.1: The velocity profile for steady current flow over a bed showing

current shear (length of arrow proportional to velocity) in the boundary layer. 13 Figure 2.2: Types of surface waves, showing the relationship between

wave frequency and period, the nature of the forces that cause them, and the relative amounts of energy in each type of wave. 17

Figure 2.3: Airy waves showing the particle orbits at various depths below the surface. (a) In deep water, the particle or orbits are circular and their radius decays exponentially with depth. (b) With a depth of L/2, the orbits, including those of the surface particles have become elliptical. 18

Figure 2.4: Schematic diagram of non linear interaction of current-only (τc) and wave-only (τw) bed shear-stresses. 20

Figure 2.5: Threshold of motion of sediments beneath waves and/ or currents. 22 Figure 2.6: Wentworth grain-size classification together with the range

of various analysis techniques. 26 Figure 2.7: Ternary diagram for mixtures of clay, sand and gravel. 27 Figure 3.1: Schema of the ABLs. 28 Figure 3.2: Site of deployment of the three ABLs. The bathymetry is

given in meters, coordinates in UTM system. 31 Figure 3.3: General arrangement of settling tower. 34 Figure 3.4: Calibration curve 36 Figure 3.5: a. Separation of wave and current components from the total

high frequency files by applying a filter. b. Wave components which let determine wave significant and maximal orbital velocity under crest and trough and wave direction. c. Current components which let determine mean current speed and direction for each burst. 40

Figure 4.1: Frequency histogram and cumulative frequency curve

representing the grain size distribution at each sampling station. The median diameter of the sediments found in the bottles is also shown. 45

Figure 4.2: Frequency histogram and cumulative frequency curve representing the grain size distribution of the sediment found in the bottles at each sampling station. 47

Figure 4.3: Pressure and wind at Cape Arkona (the direction indicates where the wind comes from); wave height, direction (where it propogates towards) and period (Tz), current (where it goes) and depth at the station V1 during the experiment (HL = High water Level; LL = Low water Level). 49

Figure 4.4: Comparison of current speed and direction given in tidestat files and calculated from puvt files; example for station V1. 54

Figure 4.5: Schematic representation of the currents at station V1 and wind



iv

at Cape Arkona before, at the beginning, at the end and after the storm. The size of the arrows gives an indication of the speed of wind and currents. 55

Figure 4.6: Currents at the three stations during the experiment. 57 Figure 4.7: Wave height and period for the three stations during the experiment. 58 Figure 4.8: Frequency, direction and spectral power density estimated using

EMEP method. 59 Figure 4.9: Surface elevation during the burst 73 (20/10, storm conditions)

showing the waves for the three stations. 61 Figure 4.10: Suspended sediment concentration (SSC) during the experiment

for the three stations. 62 Figure 4.11: Current-induced bed-shear stress (τc) and threshold bed

shear-stress (τcr); example for the station V1 for a roughness length z0 of 0.0003m (sand/gravel) and 0.006m (rippled sand). 64

Figure 4.12: Significant and maximum orbital velocity under crest and trough at station V1. 65

Figure 4.13: Difference of amplitude of wave orbital velocity under the crest and under the trough at station V1. 66

Figure 4.14: Significant measured and calculated orbital velocity during the experiment at station V1. 67

Figure 4.15: Significant wave orbital velocity for the three stations during the experiment. 68

Figure 4.16: Wave bed shear-stress (τw) calculated for a roughness length (z0) of 0.0003m (sand/gravel) and 0.006m (rippled sand) at stations V1 and V2 and a roughness length of 0.006m at station V3. 69

Figure 4.17: Wave-induced bed shear stress, (τw), maximum bed shear-stress for combined flow (τmax) and threshold bed shear stress (τcr) during the experiment; example for the station V1. 70

Figure 4.18: Relative importance of the wave-induced bed shear-stress on the maximum bed shear-stress during the experiment for the three stations. 71

Figure 4.19: Wave bed shear-stress and threshold of motion for different quartile at the three stations during the experiment. 73

Figure 4.20: Suspended sediment concentration (SSC) calculated at the height (z) of each OBS for the three stations. 75

Figure 5.1: Measured SSC at the three stations during the experiment, time

of sediment movement calculated from the bed shear-stress and time of sediment suspension at the height of the sensor from the calculated SSC. 79

Figure 5.2: Schematic representation of the sequence of events during the storm. 80 List of Tables Table 3.1: Presentation of puvt files. 30 Table 3.2: Presentation of Tidestat (a) and Wavestat files (b). 30 Table 4.1: Percentage in weight of the different fractions for each sample. 43 Table 4.2: Summary of statistical parameters (phi units) of the particle size

distribution of the seabed sediments for the three stations and their description according to McManus (1988). 44

Table 4.3: Summary of statistical parameters (phi units) of the particle size distribution of the sediments found in the bottles for the three stations and their description according to McManus (1988); the relative weight of sediment found at each station compared with the total amount of sediment found in all three bottles is also indicated. 46



v

List of Plates Plate 3.1: An ABL ready for deployment from the side of the vessel. 36 Plate 4.1: Pictures from the video showing the seabed. 42 List of Annexes Annexe 1: Model to illustrate the formation of relict sand and gravel,

example offshore south-eastern Britain 89 Annexe 2: Statistical measures of grain size parameters and descriptive

terms applied to parameter values. 90 Annexe 3: Sketch showing the Faraday effect, which forms

the basis of the electromagnetic current meter. 90 Annexe 4: Sketch showing the principle of capacitive pressure sensors

which use a thin diaphragm, quartz or silicon, as one plate of a capacitor. 91 Annexe 5: Constant pressure contours beneath a 100m wave. Water wave is 100m. 91 Annexe 6: A selection of information from the Beaufort Wind scale. 92 Annexe 7: Nomogram of deepwater significant wave prediction curves of

wind speed, fetch length and wind duration. 93 Annexe 8: Density and kinematic viscosity of water in function of temperature

and salinity. 94



Notations A orbital amplitude of wave motion (m) b Rouse number or suspension parameter Ca reference concentration at the height za (m) C(z) concentration at height z CD drag coefficient C0 concentration at the seabed d50 median grain diameter (m)

*D dimensionless grain size diameter

wf wave friction factor g acceleration due to gravity (ms-2) h water depth (m) H wave height (m) k wave number (=2π/L) Ks eddy diffusivity of sediment. l decay length scale L wavelength (m) U depth-averaged current velocity (ms-1) Uws significant wave orbital velocity (ms-1) Uwmax maximum wave orbital velocity (ms-1) U(z) velocity at depth z (ms-1) s ratio of sediment and water densities (= ρs / ρ) T period (s)

sw settling velocity (ms-1) z height of the sensor (m) za reference height near the seabed, at which reference concentration Ca is

calculated (m) z0 roughness length (m)

r∆ ripple height (m) θcr threshold Shields parameter θr modified Shields parameter. θw skin friction Shield parameter κ Von Karman constant = 0.40 λr wavelength of ripples (m) ν kinematic viscosity of water (m2s-1) ρ water density (kgm-3) ρs sediment density (kgm-3) τc current-only bed shear stress (Nm-2) τm mean shear-stress under combined waves and currents (Nm-2) τmax maximum bed shear-stress under combined waves and currents (Nm-2) τw wave-only bed shear stress (Nm-2) ø angle between current direction and direction of wave travel Φ grain diameter in phi units ψ mobility number



ACKNOWLEDGEMENTS

I would like to express my gratitude to Pr Michael B. Collins for giving me the

possibility to work on this project and for his continual support throughout the

study. I would like to extend my appreciation to Dr Erwan Garel for his constant

guidance with the data analysis and helpful comments and suggestions during the

writing of the report. I also would like to thank Pr Patrice Castaing, from my

University of Bordeaux 1, for his encouragement and support throughout the year.

Special thanks are extended to Clara for the long time she spent correcting my

English, and to Susannah for encouraging me to come to England.

Chapter 1: Introduction


1

CHAPTER 1: INTRODUCTION

1.1. General introduction

An ever increasing number of natural resources are being used to satisfy our day-to-

day needs. Terrestrial settings have traditionally been exploited to a greater extent

than the oceans due to relatively easier access. As a consequence of progress in

exploration and exploitation techniques, the ocean floor has become an important

source of materials, like for example, gas, oil and aggregates. However, the effects

of the exploitation of the marine seabed are not clearly defined. Depending on the

type of material extracted, the site location and the prevailing physical conditions;

exploitation effects may be insignificant or may disturb the marine ecosystem to

varying extents and lead to coastal erosion. The exploitation of the ocean floor is

increasing and there is a real need to quantify the effects that it causes. This study

will investigate the physical effects of marine aggregate extraction upon waves,

currents and suspended sediment concentrations in the Tromper Wiek Bay, located

in the western Baltic Sea.

1.2. Marine aggregate extraction

Aggregates are sand, gravel or crushed solid rock and are used in the construction

industry for purposes such as concrete, mortar and asphalt manufacture. For

example, to build one house requires 50 or 60 tonnes of aggregates and each mile of



2

motorway uses 200,000 tonnes (BMAPA, 1995). Aggregates are also used in beach

replenishment schemes and for fill-in coastal reclamation projects.

Aggregate demand in Europe has traditionally been met by land-based quarries and

pits, but in recent years offshore sources have made an increasingly important

contribution (Harrisson, 2003). The reasons for this are an increased awareness of

the environmental and social conflicts of terrestrial mineral extraction, increasing

legal restrictions for the exploitation of terrestrial resources, progress in extraction

techniques which facilitate the exploitation of marine sand as well as the advantages

of marine sediments with respect to quality, availability and ease of transport and

delivery (HELCOM, 1999). For instance, in 1992, the total production of marine

aggregates in the UK was 20.6 million tonnes (Meakins et al., 1999), which

represents around 18% of the UK�s total aggregate consumption (Selsby, 1992).

Sand and gravel deposits can be either relict or modern (Dyer and Huntley, 1999).

Relict deposits were formed during periods of post-glacial sea level rise. During

glacial times, the sea level was lower than at present and sand and gravel were

deposited by rivers that poured out onto the dry shelf. In the warmer interglacial

stages that followed, these deposits were re-worked during rising and high sea level

(BMAPA, 1995, Annexe 1). Modern deposits, on the other hand, have been deposited

and are controlled by modern hydrodynamic and sedimentological regimes. Sand

deposits can be either relict or modern, whereas gravel deposits can be only relict,

therefore constitute a non-renewable resource (Dyer and Huntley, 1999).

The extraction of aggregates from the seafloor is carried out by dredging. There are

two main types of dredging techniques: anchor dredging and trailer dredging



3

(Figure 1.1). Their use is dependent on the type of deposit located (HELCOM,

1999). Anchor dredging involves a ship anchoring over a deep deposit with its pipe

drawing up the sand and gravel; trailer dredging requires the ship to drag its pipe

along the seabed sucking up material from more evenly distributed deposits. A large

dredger can load 5,000 tonnes of sand and gravel in around 3 hours (BMAPA,

1995).

For both techniques, the aggregates and water are piped aboard into the ship�s

hopper. As the hopper fills up the aggregates displace the water, which overflows

back into the sea, carrying with it fine suspended material which forms a turbidity

plume in the wake of the ship (Nakata et al., 1989). On some dredgers, screening of

the aggregates is carried out in order to maintain a specific sand to pebble ratio,

excess sand is returned to the seabed, which also generates a plume (Hitchcock and

Drucker, 1996).

The production of aggregates is essential to economic growth and the improvement

of living standards. The demand is constantly increasing; aggregates are now a

Figure 1.1: The two most commonly used methods for marine aggregates extraction. A.Anchor hopper dredging, B. Trailor suction dredging (from HELCOM, 1999)



4

strategic resource. However, marine aggregate extraction can have important

impacts on the environment and marine life.

The effects of marine aggregate extraction which have previously been studied

include (EUMARSAND, 2004):

• changes in seabed elevation which may alter inner shelf flows, enhance the

wave energy reaching the coast and therefore increase coastal erosion and

retreat,

• harmful effects on fauna, flora and water quality in the area of mining

including the destruction of benthic habitats and species, such as fish and

shelfish populations, the formation of turbid plumes of fine-grained sediment

during extraction which may affect the benthic ecology in a large area around

the extraction site and the creation of large depressions on the seabed

(depending upon extraction method) where anoxic conditions may develop,

• disturbance of cultural heritage sites e.g. shipwrecks of archaeological

interest.

• conflicts of interests between marine aggregates industry and other sea-bed

users such as fisheries, shipping, the oil industry and offshore wind farms.

The biological short term as well as the long term effects of marine aggregates

extraction upon the benthic community have been well studied in the English

Channel (Boyd and Rees, 2003, Boyd et al., 2003, 2004, Desprez 2000), in the

North Sea (Kenny and Rees, 1994, 1996), in the Baltic Sea (ICES/ACME, 1997,

Graca et al., 2004), and on the US coasts (Oliver, 1973, Drucker, 1995, Diaz et al.,



5

2004). These studies gave variable results with no definite indications of the extent

and duration of the long term impacts.

The possible effects of marine aggregate extraction upon the benthic fauna are

summarised in Figure 1.2.

The principal physical effect of marine aggregate extraction is to change the

bathymetry of the seabed, which will in turn influence hydrographical conditions

and sediment transport (IADC, 1997, Figure 1.3). The effects on the physical

environment caused by alteration of the bathymetry depend on the existing

bathymetry, the shape and location of the dredged area relative to the wave and

current direction, the hydrographic conditions (tide, waves, currents) low or high

energy and the sedimentary regime (silt, sand, rock), sediment transport and

sedimentation rates.

Increased concentration of

suspended material

Reduced light penetration

Settling of larvae

influenced

Reduced growth of bottom vegetation

Covering of fauna/ mussels

Excavation of habitats for flora/

fauna

Figure 1.2: Possible biological impacts of marine aggregate extraction (from IADC, 1997)



6

Marine aggregate extraction may have a number of physical impacts:

- deepening the natural pathways of the water allows the energy to be

transported with less friction from the bottom, and then reduces the

current or wave impact in the dredged area compared with outside the

pit (Graca et al., 2004, Kleinhans et al., 2004, Figure 1.4),

- the reduced current or wave action at the seabed can increase

sedimentation inside the dredged area (Kenny and Rees, 1996, Desprez,

2000); this may produce a lack of sediment available to the coast and

lead to coastal erosion.

- the reduced friction at the seabed can also enhance wave or tidal energy

(Maa et al., 2004) and then increase coastal erosion.

Figure 1.3: Chain of possible effects caused by changing the bathymetry (from IADC, 1997).



7

The time scales of recovery of the pits are not clearly defined (Boers, 2004); it has

been found that this depends profoundly on the position of the extraction site

relative to the seaward limit of the shoreface. Locating extraction sites well beyond

this limit implies a slow regeneration due to the fact that the threshold of re-

mobilisation of the ambient sediment is surpassed only during extreme events.

Meanwhile, extraction on the shoreface means that pits can recover quite fast but

negative impacts on the coastal sediment budget cannot be ignored (Diesing et al.,

2004). In certain sites, the presence of weathered dredged tracks or pits can be

detected 10 years after the extraction (Boyd et al., 2004). In other sites the time

scales of regeneration are assessed to be in the order of decades (Diesing et al.,

2004).

Figure 1.4: Reduction of current and wave velocity by increasing the water depth in dredgedarea (from IADC, 1997).



8

1.3. Studied area

The Baltic Sea is an almost enclosed sea with very restricted access to the North

Sea through the Kattegat. As a consequence the tides are rather small, a few cm at

the most in most places. (Kantha et al., 2005). Furthermore they have a mixed

nature, with diurnal or semi-diurnal components dominant depending on exact

location. The drainage basin of the Baltic Sea is located entirely within a humid

climate setting. This results in a freshwater surplus, with river discharges as the

main contributor (Klein, 2003).

In the Western Baltic Sea, the Pomeranian Bight is a typical coastal basin,

extending from Cape Arkona (Rügen Island) in the west to Poland in the east

(Figure 1.5); it is bordered to the north by a 20m depth contour and encompasses a

200km long coastline (Schwarzer et al., 2003). Pomeranian Bight is characterised

by the largest freshwater discharge into the Western Baltic and therefore the salinity

is low, around 8 (Lass et al., 2001). The dynamical regime of Pomeranian Bight is

governed by a locally wind-driven Ekman current and a compensating bottom

current, as well as by coastal jets (Lass et al., 2001).

The Tromper Wiek is a semi-enclosed bay on the northern coast of Rügen Island.

The circulation in the Tromper Wiek Bay is highly variable. Currents are primarily

influenced by wind as well as water level variations due to wind surges and seiches

(Klein, 2003).

Three periods with different prevailing wind directions occur annually: dominant

easterly winds from February to May, westerly winds from June to September and

westerly to southwesterly winds from October to January (Schwarzer et al., 2003).



9

Tromper Wiek's inner coastline is exposed only to wave approach from Northeast to

East and the fetch, limited by Bornholm Island and Sweden in the North, has a

maximum of approximately 90km (Schwarzer et al., 2003). Therefore, Easterly

winds produce high wave energy input transferred into high sediment movement

whereas westerly winds result in low energy input and low sediment movement

(Schwarzer and Diesing, 2001).

Figure 1.5: Zone of study.

Germany Poland

Sweden

Rügen

Tromper Wiek

Bornholm

35 km

North Sea

Baltic Sea

N

Cape Arkona

Pomeranian Bight



10

Tromper Wiek Bay has been a site of sand and gravel extraction for many years

(Figure 1.6).

The seafloor of the sand extraction site is characterised by marine fine sands in

water depths of between 14 and 21m (Albrechts, 1997). Sand has been extracted

twice (151 000 m3 in 1989 and 104 000m3 in 2000) by trailer suction dredging in a

water depth of around 11m causing relatively shallow (< 1m) furrows of several

hundreds of metres in length and less than 10m in width (Diesing et al., 2004).

The gravel extraction site in Tromper Wiek is situated in water depths of between 9

and 14m. There, the seafloor is covered by sandy gravel forming prominent NE-

SW-trending ridges, which are interpreted as being the remains of a drowned beach

ridge system dating back to the Pleistocene (Schwarzer et al., 2000).

Site of gravel extraction

Site of sand extraction

Figure 1.6: Generalized sediment distribution map for the whole of Tromper Wiek Bay (from Albrechts, 1997) and sites of marine aggregate extraction (after Diesing et al., 2004)



11

The gravel deposits are extracted by anchor hopper dredging, which results in the

formation of extraction pits 5 to 50m in diameter and up to 7m in depth (Figure

1.7.).

After extraction, the material is screened on board, i.e. sediments with grain sizes

<2mm are sorted out and spilt back into the sea. The spilt material settles down to

the area of extraction, creating recognisable sediment distribution patterns on the

seafloor (Diesing et al., 2004). Between 1988 and 2000, approximately 460,000 m3

of sediment were extracted of which half the volume was spilled back into the sea.

From repeated sidescan sonar surveys, Diesing et al. (2004) found that the pits do

not re-fill completely, but remain stable for at least several years. However, the

pattern of spilt sands shows rapid changes. Spilt sands are re-mobilised, especially

during late winter and early spring when easterly winds produce high waves within

Tromper Wiek Bay. The re-mobilised sands partly re-fill the pits as could be proved

by cores obtained from the seafloor inside the pits. Diesing et al. (2004) estimated

the appropriate time scales for regeneration to be in the order of years, at least.

Figure 1.7: Side Scan Sonar from Tromper Wiek bay (Ramso, 2004, unpublished).



12

1.4. Objectives

This research will investigate the physical impact of an isolated gravel-pit in the

North-Western part of the Tromper Wiek Bay. The study will be based on the

analysis of waves, currents, water level and suspended sediment concentration high

frequency measurements inside and outside the crater during a 4days experiment.

The main objectives of this study are:

- to identify any hydrodynamic effects of the presence of the pit i.e. morphological

influence on currents and wave propagation; and

- to evaluate whether the crater can act as a trap for fine sediments.

Chapter 2: Theoretical Background


13

CHAPTER 2: THEORETICAL BACKGROUND

2.1. Sediment mobility

2.1.1. Introduction

The flow of a current or waves in the sea is usually accompanied by the formation

of a turbulent boundary layer adjacent to the seabed. This is a region of frictionally

retarded flow which is characterised by a spatial and temporal randomness of the

velocity field and through which the horizontal mean flow adjusts from zero at the

bed to its maximum value away from the bed in the free-stream (Heathershaw,

1988, Figure 2.1). Throughout this layer turbulent energy levels and shear stresses

also change, decreasing from maximum values near the bed, to zero at the outer

edge of the boundary layer. The bed shear-stress is defined as the frictional force

exerted on a unit area of the seabed by the current flowing over it.

Increasing current

velocity U

Incr

easi

ng h

eigh

t abo

ve th

e be

d z.

boundary layer

Figure 2.1 The velocity profile for steady current flow over a bed showing current shear (length of arrow proportional to velocity) in the boundary layer (after Open University, 2000).



14

The total bed shear-stress (τ0) acting on the bed is made up of contributions from

(Soulsby, 1997):

• the skin friction τ0s produced by (and acting upon) the sediment grains

• the form drag τ0f produced by the pressure field associated with the flow

over ripples and/or larger features on the bed

• a sediment-transport contribution τ0t caused by momentum transfer to

mobilise the grains.

Only the skin friction contribution acts directly on the sediment grains, and it is

therefore this contribution which is used to calculate the threshold of motion, the

bedload transport, and the reference concentration or pick up rate for grains in

suspension. On the other hand, it is the total bed shear-stress that corresponds to the

overall resistance of the flow and determines the turbulence intensities which

influence the diffusion of suspended sediment to higher levels in the water column

(Soulsby, 1997).

For simplicity the subscript 's' is omitted from the skin friction bed shear-stress and

only the others contributions will have the subscript.

2.1.2. Currents

a) Generalities

Currents in the sea may be caused by tidal motions, wind-stress, atmospheric

pressure gradients, wave-induced forces, river out-flow, large-scale quasi-steady

water surface slopes and horizontal density gradients associated with oceanic

circulation (Soulsby, 1997). In the nearshore region, wave-induced (longshore)



15

currents are dominant, whereas further offshore a combination of tidal and

meteorological forcing (including storm surges) dominates.

Strom surges are changes in water level generated by atmospheric forcing;

specifically by the drag of the wind on the surface and by variations in the surface

atmospheric pressure associated with storms (Flather, 2001). They last for periods

ranging from a few hours to 2 or 3 days and have large spatial scales compared with

the water depth. They can raise or lower the water level in extreme cases by several

metres. Both pressure and wind effects are present in all storm surges, but their

relative importance varies with location. Wind forcing is most important in shallow

waters whereas pressure (diminution of atmospheric pressure produces an increase

in depth) dominates in the deep ocean.

Associated storm surge currents, superimposed on tidal and wave-generated flows

can contribute to extremes in current and bed stress.

b) Current-induced bed shear-stress

The depth-averaged current velocity U (ms-1) can be calculated from a single

measurement in the water column using the empirical formula of Soulsby (1990):

)(32.0 71

zUz

hU

= for 0 < z < 0.5h (1)

where h is water depth and U(z) is the velocity at the depth z.

The current skin friction bed shear-stress τc is related to the depth-averaged current

speed U through the drag coefficient CD by the quadratic friction law



16

2UCDc ρτ = (2)

where ρ is the density of water and CD is the drag coefficient which can be

calculated using the log profile expression:

2

0ln1

+=

hz

CDκ (3)

where κ is the Von Karman constant (0.40) and z0 is roughness length, which, in the

absence of simultaneous measurements at different levels during the experiment,

can be estimated from the mean values of z0 for different bottom type given by

Soulsby (1997).

2.1.3. Waves

a) Generalities

Waves play a major role in stirring up sediments from the seabed, as well as giving

rise to steady current motions such as longshore currents, undertow, and mass-

transport velocities, which transport the sediments. Waves are classified according

to their period (Figure 2.2). Tides belong to the long period wave band; they play an

indirect role in sediment movement by creating tidal current. Lower periods waves,

called surface waves, may be generated either as a locally-generated sea (wave-sea)

due to the effect of local winds blowing over the sea for a certain distance (the

fetch), and time (duration), or as swell, which results from distant storms and

usually has a longer period and less spread in period and direction than a locally-

generated sea (Soulsby, 1997).



17

For small disturbances of the sea surface, the waves, according to the wave linear

theory, can be represented by a freely propagating, long-crested, sinusoidal wave

train (Tucker and Pitt, 2001). The orbits are closed (i.e. waves do not produce a net

displacement), circular in deep water and elliptical in shallow water (Figure 2.3).

From the wave linear theory, the amplitude of the wave orbital velocity can be

derived from the wave height (H), the period (T), the wave length (L) and the water

depth (h) by using the relation:

)sinh(khTHU w

π= (4)

where k is the wave number (=2π/L)

This applies to waves whose steepness (height/wavelength) is very small, in which

case the magnitude of Uw is the same under the trough and the crest (Soulsby,

1997). The orbital velocity beneath the wave crest is in the same direction as the

wave is travelling, and under the wave trough it is in the opposite direction. Then an

Figure 2.2: Types of surface waves, showing the relationship between wave frequency andperiod, the nature of the forces that cause them, and the relative amounts of energy ineach type of wave (from Knauss, 1997).



18

asymmetry of velocities beneath the wave and the trough is a source of net transport

in the direction of greater orbital velocity (Soulsby, 1997). In practise the waves of

most interest for sediment transport will have a larger steepness, i.e. the amplitude

of orbital velocity will be different under the crest and the trough. A variety of non-

linear wave theories are available to deal with steep waves (Stokes 2nd-5th order

solutions, cnoidal theories, stream-function theory, see Tucker and Pitt, 2001).

b) Wave-induced bed shear-stress

Frictional effects near the bed produce an oscillatory boundary layer within which

the wave orbital velocity amplitudes increase rapidly with height from zero at the

bed to a value Uw at the top of the boundary layer. In the absence of a current the

turbulence is confined within the boundary layer, which for waves is only a few

millimetres or centimetres thick in contrast to the boundary layer of a steady current

Figure 2.3: Airy waves showing the particle orbits at various depths below the surface. (a) In deep water, the particle or orbits are circular and their radius decays exponentially with depth. (b) With a depth of L/2, the orbits, including those of the surface particles have become elliptical (from Tucker and Pitt, 2001).



19

in which it can be metres or tens of metres thick. This has the effect of producing a

much larger velocity shear in the wave boundary layer, which in turn causes the bed

shear-stress produced by a wave with orbital velocity Uw to be much larger than that

produced by a steady current with an equal depth-averaged speed U (Soulsby,

1997).

The amplitude τw of the wave's oscillatory bed shear-stress is usually obtained from

the bottom orbital velocity Uw of the waves via the wave friction factor wf , using

the quadratic friction law for waves

2

21

www Ufρτ = (5)

Several equations have been proposed to calculate the wave friction factor. It is

dependant on whether the flow is laminar, smooth turbulent or rough turbulent.

Grant and Madsen (1979) proposed the following expressions valid under waves

only or combined waves and currents:

1057.0=wf for 3

0

10<zA (6a)

0316.0=wf for 4

0

3 1010 <<zA (6b)

0135.0=wf for 5

0

4 1010 <<zA (6c)

00690.0=wf for 5

0

10>zA (6d)

where A is the orbital amplitude of wave motion at the bed

π2TU

A w= (7)



20

2.1.4. Combined waves and currents

In most parts of coastal and shelf seas, both waves and currents play an important

role in sediment dynamics. The interaction of the two may affect wave

characteristics (by modification of the phase speed and wavelength of waves by the

current), current velocity (by generation of currents by the waves) and bed shear-

stress (Van Rijn, 1993).

Because of the non-linear interaction of the wave and current boundary layers, the

bed shear-stresses beneath combined flows are enhanced beyond the values which

would result from a simple linear addition of the wave-only and current-only

stresses (Soulsby, 1997, Figure 2.4).

Several models have been proposed to calculate the mean and maximum bed shear-

stress during a wave cycle (Grant and Madsen, 1979, Fredsøe, 1984, Huynh-Tanh

and Temperville, 1991, Davies et al., 1988). Using a data-based method Soulsby

(1995) deduced the simple equations

τc

τw

τmax

τm

(a) (b)

(c)

ø

Figure 2.4: Schematic diagram of non linear interaction of current-only (τc) and wave-only (τw) bed shear-stresses (from Soulsby et al., 1993).



21

+

+=2.3

2.11wc

wcm ττ

τττ (9)

[ ] 2/122max )sin()cos( φτφτττ wwm ++= (10)

where τm and τmax are the mean and maximum bed shear-stress during a wave cycle,

τc is the current-only bed shear-stress, τw is the wave-only bed shear-stress and ø is

the angle between current direction and direction of wave travel.

τmax is used to determine the threshold of motion and entrainment rate of sediments,

and τm to determine sediment diffusion (Soulsby, 1997).

2.1.5. Threshold bed shear-stress

During very slow flows over a sand bed the sand remains immobile. If the flow is

slowly increased, a velocity is reached at which a few grains begin to move. This is

called the threshold of motion or incipient motion (Soulsby, 1997); a similar

process occurs beneath waves. Shields (1936) investigated the threshold of motion

in terms of the ratio of the force exerted by the bed shear-stress acting to move a

grain on the bed, to the submerged weight of the grain counteracting this. The

threshold Shields parameter θcr is defined as

dg s

crcr )( ρρ

τθ−

= (11)

where τcr is the threshold bed shear-stress, ρs is the sediment density, ρ is the water

density, d is the grain diameter and g is the acceleration due to gravity.



22

It can be plotted against the dimensionless grain size diameter *D (Figure 2.5)

given by

dsgD3/1

2*)1(

−=

ν (12)

where ν is the kinematic viscosity of water and s is the ratio of density (= ρs / ρ).

Soulsby and Whitehouse (1997) proposed an equation to calculate the threshold

Shields parameter θcr from the dimensionless grain size *D

(13)

The threshold bed shear-stress can next be calculated using equation (11).

Figure 2.5: Threshold of motion of sediments beneath waves and/ or currents (fromSoulsby, 1997).

))020.0exp(1(055.02.11

30.0*

*

DDcr −−+

+=θ



23

2.2. Suspended sediment concentration

For current speeds or wave conditions significantly above the threshold of motion,

sand is entrained off the bed and into suspension, where it is carried at the same

speed as the current. For grains to remain in suspension, their settling velocity must

be smaller than the upward turbulent component of velocity. The settling velocity

sw of sand grains is determined by their diameter and density, and the viscosity of

the water. Soulsby (1997) proposed the following formula:

[ ]36.10)049.136.10( 2/13*

2 −+= Dd

wsν (12)

where ν is the kinematic viscosity of water, *D is the dimensionless grain size

diameter and d is the grain diameter.

In a sand suspension the settling of the grains towards the bed is counterbalanced by

diffusion of sand upwards due to the turbulent water motions near the bed. The

equation governing this balance is

dzdCKCw ss −= (13)

where C is the volume concentration of sediment at height z and Ks is the eddy

diffusivity of sediment.

If the eddy diffusivity is assumed to increase linearly with height above the bed, the

corresponding concentration profile is the power-law profile:

b

aa z

zCzC−

=)( (14)



24

where C(z) is the concentration at the height z above the bed, Ca is the reference

concentration at the height za and b is the Rouse number or suspension parameter

which is defined as

κ*uw

b s= (15)

where κ is the Von Karman constant and *u is the total friction velocity

( 2/10 )/( ρτ= ).

If the eddy diffusivity is assumed to vary parabolically with height, the Rouse

profile is obtained:

b

a

aa zh

zhzzCzC

−

−−

=)( (16)

where h is the water depth.

If the eddy diffusivity is assumed to be constant with height, which is the case

under waves for a rippled bed, the concentration profile is given by

lzeCzC /0)( −= (17)

where C0 is the concentration at the seabed and l is the decay length scale.

Various expressions have been given for l and C0, of which one of the most widely

used is that of Nielsen (1992) for rippled bed:

rs

w

wU

l ∆= 075.0 for 18<s

w

wU

(18a)

rl ∆= 4.1 for 18≥s

w

wU

(18b)



25

30 005.0 rC θ= (19)

where r∆ is the ripple height and rθ is the modified Shields parameter which is

given by

250 )/1()( rrs

wr dg λπρρ

τθ∆−−

= (20)

The ripple height r∆ can be calculated using the expression proposed by Nielsen

(1992) valid for 156<ψ and 831.0<wθ (if these values are exceeded the model

predicts the wash out of ripples):

Ar )022.0275.0( 5.0ψ−=∆ (21)

where A is the orbital amplitude of wave motion at the bed (equation 7) and ψ is

the mobility number defined as

50

2

)1( dsgU w

−=ψ (22)

where Uw is the wave orbital velocity, g is the acceleration due to gravity, s is the

ratio of sediment and water densities and d50 is the median grain diameter.



26

2.3. Grain size analysis

Sediment grains are classified according to their diameter into mud (which

comprises clays and silts), sands and gravel (which comprises granules, pebbles,

cobbles and boulders). Grains size can be expressed either in millimetres or phi

units, which are related by the expression:

d = 2 �Φ (23)

where d is the grain diameter in millimetre and Φ the grain diameter in phi units.

The most commonly used classification is the Wentworth scale (Soulsby, 1997,

Figure 2.6).

Different techniques are available to analyse the sediment samples depending on the

sample grain size (Figure 2.6).

Figure 2.6: Wentworth grain-size classification together with the range of variousanalysis techniques (from Heathershaw, 1988).



27

The proportions of the different fractions allow one to classify the sediment samples

on a ternary diagram (Figure 2.7)

The grain-size distribution is usually presented as a cumulative curve showing the

percentage by mass of grains smaller than d, versus d. Statistics are used to

characterise grain-size distributions (Annexe 2). The most commonly used

parameters are the median diameter d50 which is the diameter for which half of the

grain is finer, the sorting which is a measure of the spread about the average, the

skewness which indicates the preferential spread and the kurtosis which evaluates

the peakedness of the distribution (McManus, 1988).

Figure 2.7: Ternary diagram for mixtures of clay, sand and gravel (from Dyer, 1986).



28

CHAPTER 3: MATERIEL AND METHODS

3.1. Instrumentation

The data were collected using three Autonomous Benthic Landers (ABLs, Figure

3.1), each of them held up on a frame and equipped with an electromagnetic current

meter (EMCM), a pressure sensor and an Optical Backscatter Sensor (OBS). The

ABLs operated autonomously taking measurements at regular intervals called bursts.

3.1.2. Electro-Magnetic Current Meter

A current meter permits the monitoring of the instantaneous (mean and fluctuating

parts) of the water motion in two directions (Voulgaris, 1992), therefore it estimates

the speed and direction of water moving relative to the instrument. In

electromagnetic current meters an alternating current (ac) or switched direct current

Figure 3.1: Schema of the ABLs.

Material and Methods


29

(dc) magnetic field is imposed on the surrounding seawater using a coil buried in

the sensing head, and measurements of the potential gradients arising from the

Faraday effect are made using orthogonally mounted pairs of electrodes (Shercliff,

1962, Annexe 3). Unlike mechanical current meters, electromagnetic instruments

have no zero velocity thresholds (Collar and Griffiths, 2001) and are thus utilisable

for very slow flows.

3.1.2. Pressure sensor

The principle of the pressure sensor is that the pressure at a fixed point under a

wave system fluctuates in phase with waves (Tucker and Pitt, 2001). The pressure

sensor incorporated on the Valeport is based on the principle that changes in water

pressure cause changes in frequency of a resonant circuit using a silicon crystal

(Williams, 2005, Annexe 4).

3.1.3. Optical Backscatter Sensor

The OBS manufactured by D&A Instruments, was developed at the University of

Washington for monitoring suspended sediment concentrations (SSC) in the surf

zone (Downing et al., 1981) and has proved an excellent tool for suspended

sediment studies due to his high frequency response, relative insensitivity to

bubbles, approximate linear response to concentration and small size causing

minimal disruption to transporting flow (Kineke and Sternberg, 1992). There are

many advantages to using an OBS for measuring SSC rather than water sampling

methods, such as continuous monitoring, real time display and simultaneous

measurements with flow meters and water properties sensors.



30

The OBS is a miniature nephelometer that measures scattering of infrared radiation

by suspended particles. Scattering is highly influenced by both the number of

particles and particle size (Kineke and Sternberg, 1992, Xu, 1997). Hence, most

optical sensors cannot be used successfully in highly turbid waters and are

extremely susceptible to the effects of particle size (Baker and Lavel, 1984).

3.1.4. Wavelog

The high frequency data were downloaded by a software package called Wavelog

and regrouped in puvt (pressure, U, V and turbidity) files (Table 3.1), which for

each burst give the date and time, the pressure (dBar), the U and V components of

the flow (ms-1) and the turbidity (V).

Just after their recording, the high frequency data were processed by Wavelog.

After correcting the pressure attenuation with depth and detrending the pressure

a.

b.

Table 3.2: Presentation of Tidestat (a) and Wavestat files (b).

Table 3.1: Presentation of puvt files.



31

burst data, Wavelog applies a spectral analysis to give the tide slope, mean depth

and statistics wave parameters, i.e. significant wave height (Hs), significant and

zero-crossing period (Tz and Tp), total energy and spectral data for each burst.

All the results are given in statistics files called tidestat and wavestat (Table 3.2).

3.2 Field experiment

3.2.1. Deployment

Hydrodynamics measurements were collected during the cruise of the Research

Vessel "ALKOR" (16 to 25/10/2004) as part of the research training network

EUMARSAND.

N

Figure 3.2: Site of deployment of the three ABLs. The bathymetry is given in meters,coordinates in UTM system.



32

Three ABLs were deployed in the north-western part of the Tromper Wiek Bay in

the gravel dredging zone (Figure 3.2), one in the middle of an isolated 3m-deep

crater (station V3) and the two others on its edge (stations V1 and V2), at a water

depth of ~12m, between the 19th and 23rd of October 2004.

Bursts were taken every 30min lasting 8min 32sec at a frequency of 4Hz throughout

the study period, allowing the recording of 184 bursts at each station. The ABLs

were logged at the same moment therefore the bursts are taken at the same time at

the three stations.

This location allowed us to have two references stations (stations V1 and V2) and

one inside the area of gravel-extraction (station V3)which allows the

characterisation of the hydrodynamic conditions and turbidity inside and outside the

pit

Trigger

OBS

EMCM head

Weights

Pressure sensor

Bottle

Frame

Plate 3.1: An ABL ready for deployment from the side of the vessel.



33

The sensor height was 0.5m for stations V1 and V3 and 0.6m for station V2, the

OBS is situated 5cm lower (Plate 3.1). Three divers controlled the tilting and GPS

positioning of the three ABLs.

Wind data and atmospheric pressure were recorded throughout the experiment at

Cape Arkona (Figure 1.5). The data constitute 10min values recorded every 60min.

3.2.2. Sediment samples

Surface sediment samples were collected by divers at each mooring location.

Moreover, bottles were left on the frames that support the instruments during the

three days of the experiment allowing them to collect the sediments in suspension.

The bottles were situated approximately at the same height as the OBS (Plate 3.1).

A video was also recorded during the ABLs' recoveries which give the possibility

of visualising the sea floor and analysing the features present.

3.3. Calibration

The OBS measures the turbidity (in Volts), that has to be converted to Suspended

Sediment Concentration (gl-1) with a calibration curve. The particle size strongly

influences the scattering therefore the measurement of turbidity. As a result,

sediment from the field had to be used to calibrate the OBS (Sternberg et al, 1991,

Downing and Beach, 1981). Different techniques are proposed for the calibration,

such as the use of the Laser In-Situ Scattering and Transmissometer deployed



34

simultaneously to the OBS to measure the size distribution of the suspended

sediments (Agrawal and Pottsmith, 1994), the use of bottom sediment in a

calibration tank (Green and Boon, 1993), or calculation of the in situ calibration

coefficient by modelling grain-size distribution of suspended sediments (Xu, 1997).

In this study, we have chosen to do the calibration using a bucket filled with water

and field sediments as recommended by the manufacturers (D&A Instruments,

1988). Grain-size distribution of the suspended sediment may be different to that of

the bottom sediment, and the use of sediment found in the water column or bottom

sediment will change the results of the calibration (Kineke et al., 1989, Sternberg et

al., 1991). That is why we preferred the utilisation of sediments found in the bottles,

i.e. sediment in suspension at the height of the sensor during the experiment, to

those taken at the seabed.

Sediments were put in a bucket and OBS measurements were taken at the same

time as water samples, the latter were next filtered (2µm filters, dry weight

established prior to calibration). Filtered samples were then dried and weighed and,

hence, the suspended sediment concentration calculated for each sample.

Figure 3.3: OBS calibration curve.

y = 110.36x2 + 16.275xR2 = 0.8239

0

10

20

30

40

50

60

70

80

90

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9turbidity (V)

SSC

(mg/

l)



35

A calibration curve was drawn using the results (Figure3.3). Voulgaris (1992) found

that a polynomial curve gives a better correlation that a linear form when the

calibration is done with the bucket method and storm experiment conditions; in the

present study, we found the same results: a polynomial curve gives a better

correlation coefficient (0.82) than a linear form (0.73).

3.4. Grain size analysis

3.4.1. Sieving and weighing

To analyse the sediments taken at the experiment site, we began by sieving them in

order to separate them according to their grain diameter Ø into mud (Ø<63µm),

sand (63µm< Ø <2mm) and gravel (Ø > 2mm) fractions.

The mud fraction was put in a measuring cylinder and filled up to 1L with water.

After stirring the water and the mud for 2min and waiting 20sec, a sample of 20ml

was taken at 20cm height and put in a Petri dish previously weighed when dry. The

sand and gravel were put into boxes.

All the samples were then dried during one night in the oven at 60°C and weighed.

The gravel fraction was dry sieved by mechanical shaking for 15min with a series

of standard test sieves with successively smaller mesh sizes decresing by 0.25 phi

each time, from �1 phi (2mm) to �4 phi (16mm).

The sediment collected into the bottles was dried and weighed.



36

3.4.2. Settling tower

To determine the mass frequency distribution of sand particle size, we used a

settling tower. The principle of this is that the force of resistance of a spherical

particle moving throw a fluid depends on the diameter and relative velocity of the

particle, and on the density and viscosity of the fluid. The assumption is made that

particles settle out individually, this is true for sand-size particles (Syvitsky et al.,

1991).

The settling tower (Figure 3.4) consists of a 2m long perspex tube with an external

diameter of 20cm. The tube was filled with fresh water at a temperature of 16°C

maintained throughout experiments. It is essential to maintain a constant

Figure 3.4: General arrangement of settling tower (from Rigler et al., 1981).



37

temperature since the settling velocity depends on the density of water, which is a

function of its temperature. A perspex pan (15cm in diameter) is used for sample

collection, the assumption is made that statistically equivalent proportions of all

size ranges within the sample are capable of passing between the pan and tube wall

during a set of readings (Rigler et al., 1981). The pan is suspended from a Sartorius

electromagnetic balance. The start of the recording sequence is set by an external

trigger, operated by the sediment release mechanism as the sample just comes into

contact with the water surface. The balance logs the weight every 6 Hz, this then

provided a raw file containing the parameters, which are weight (cumulative weight

of the sediment), distance (length of the column) and time.

Conversion of settling velocities to grain size was carried out using a Matlab

program written by Urs Neumeier (2003).

3.4.3 Coulter Counter

The mud fraction as well as the sediment found in the bottles were analysed using a

Coulter Counter LS 130 Laser Diffraction Size Analyser, measuring grain size

distribution from 0.4 to 1000µm. The principle of the Coulter Counter is that

particles of a given size diffract light through a given angle (Wen and Duzgoren-

Aydin, 2002). The angle increases with decreased particle diameter size. A parallel

beam of monochromatic light passes through a suspension contained in a sample

cell, the diffracted light is focused onto a detector. The detector measures the

distribution of scattered light in term of density. A lens focuses on the undiffracted

light to a point at the centre and leaves only the surrounding patterns, which do not



38

vary with particle movement. A computer controls every function of the instrument

and gives the PSD.

3.4.4. Total Particle Size Distribution (PSD)

The results of the Coulter Counter, the Settling Tower and the dry sieving were

amalgamated with respect to the relative weight of each fraction in order to have the

complete PSD. Statistic parameters were used to describe the PSD (Annexe 2).

3.5. PUVT files treatment

The high frequency data (puvt files) were processed using Matlab.

3.5.1. Pressure

The pressure measured by the pressure sensor is the sum of the atmospheric

pressure and the pressure of the water column over the sensor. Thus we first

subtracted the atmospheric pressure measured at Cape Arkona from the raw

pressure high frequency measurements.

The pressure disturbance created by waves decays with depth according to the wave

amplitude (and length) to water depth ratio and is a strong function of the wave

period (Pajala, 2002, Annexe 5). The pressure measurements then have to be

corrected to the pressure attenuation with depth in order not to underestimate the

smaller waves. This was done using a Matlab function written by Urs Neumier

(2005) and based on principles described by Tucker and Pitt (2001).



39

The data are then detrended, i.e. corrected for the tide using a Matlab routine, and

the mean pressure and the sensor height are added in order to obtain the total depth

in metres.

3.5.2 U and V components of the flow

The U and V components of the flow were corrected for the sensor heading

(direction of sensor relative to North) to give north and east components.

The 2 dimensional components of the flow represent the high frequency variations

of a water particle, this includes the displacement induced by waves and that

induced by currents.

The Fourrier analysis is a method which allows one to distinguish one frequency

from another in measurement data. This analysis can take a time series of

observations and transform it into its fundamental periods (Young, 1999). Using

such a method, the U and V components of the flow can be approximated by the

linear superposition of sinusoidal forms. Each component is characterised by its

frequency and energy.

By applying a filter on the spectral density of the U and V components of each burst,

we separate wave and current components. The applied filter separates frequencies

smaller than 0.083Hz (i.e. periods greater than 12sec), considered as current

components, from frequencies greater than 0.083Hz, considered as wave

components (Figure 3.5.a).



40

For each burst, the current speed is computed as the average of the current

components and the current direction is calculated from the angle of the line joining

the origin, i.e. sensor position, to the average value of current speed, and the

ordinate axis, i.e. north direction (Figure 3.5.c).

The wave components were analysed by adapting the Matlab function

Zero_crossing written by Urs Neumier (2005). The wave direction was calculated

by applying a linear regression to the data. A rotation was applied on the data so

that the x-axis was in the direction of wave travel. The zero crossing was calculated

and allowed us to compute the wave orbital velocities under the crest and the trough

as the maximum and minimum values between a downward crossing. Then, the

maximum and significant wave orbital velocities under the crest and the trough

were calculated for each burst. The significant wave orbital velocity was taken as

the mean of the 1/3 biggest orbital velocities.

3.5.3. Turbidity

The high frequency turbidity data were controlled and anomalous values (abrupt

and short increase to very high values) attributed to presence of fishes, algae or

sampling errors were removed. The turbidity was next converted in to suspended

sediment concentration using the calibration curve (Figure 3.3).



41

Figure 3.5: a. Separation of wave and current components from the total high frequencyfiles by applying a filter. b. Wave components which let determine wave significant andmaximal orbital velocity under crest and trough and wave direction. c. Currentcomponents which let determine mean current speed and direction for each burst.

03:10 03:15

-0.07

-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

north

velo

city

(m

/s)

total signal

wave-component

current-component

a.

-0.07 -0.06 -0.05 -0.04 -0.03 -0.02 -0.01 0-0.06

-0.05

-0.04

-0.03

-0.02

-0.01

0

east (ms-1)

nort

h (m

s-1)

c.

mean current speed

N

Current direction

-0.05 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05-0.03

-0.02

-0.01

0

0.01

0.02

0.03

east (ms-1)

nort

h (m

s-1)

b.

Uw crest Uw trough

N

wave direction



42

CHAPTER 4: RESULTS

4.1. Sediment characteristic

4.1.1. Video

On the video, one can see the patchy nature of the gravel deposits. Gravel

sometimes covers the entire seabed (Plate 4.1c.), or is in patches surrounded by

sand (Plate 4.1a. and d.) as described by Albrechts (1997). We also see that the size

of the gravel can be quite significant (Plate 4.1b.).

We observed that the seabed is sandy with some gravel patches at stations V1 and

V2 (Plate 4.1a. and b.), and devoid of gravel at station V3, inside the pit. The video

also indicates that the sand portions of the seabed are rippled.

Plate 4.1: Pictures from the video showing the seabed.

a. b.

c. d.

Cobble

Sand

Gravel

Sand

Gravel covered

with mussels

Chapter 4: Results


43

4.1.2. Seabed sediment

The total particle size distribution (PSD) of the sediment taken from the seabed is

presented in Figure 4.1, its characterising parameters are summarised in Tables 4.1

and 4.2.

In all the samples, the mud fraction represents less than 1% of the total weight

(Table 4.1).

The sample of station V1 contains gravelly sand sediments, essentially composed of

sand with approximately 6% gravel in which we note the presence of some small

mussel shells. The median grain diameter is 0.5mm, at the limit between the coarse

and medium sand; the distribution is unimodal with a dominant mode of 1.3 phi

(0.4mm), it is moderately sorted positively skewed, i.e. the preferential spread is

towards coarser grain (Figure 4.2) and leptokurtic.

The sample from station V2 is a sandy gravel, mainly composed of gravel; this is

principally due to the presence of a cobble (7cm long, 4cm large). We have seen the

patchy nature of the gravel deposits and we found that this boulder represents more

than 50% of the weight of the sample. Taking this cobble into account when

calculating the particle size distribution would have greatly under-represented the

sand fraction (which covers a large fraction of the seabed surface). It was therefore

Table 4.1: Percentage in weight of the different fractions for each sample.



44

decided to remove it from the PSD, thus the percentage of the different fractions has

been re-calculated without it (V2�). This does not change the classification of 'sandy

gravel' found at station V2 (Table 3.1). The sample is thereafter composed of about

70% sand and 30% gravel. We note that an important part of the gravel fraction is

composed of mussel shells of all sizes, which represent around 5% of the total

weight of the sample. The median grain diameter is 0.5mm, as for station V1. The

distribution is bimodal in the sand fraction with a dominant mode of 1.6phi

(0.34mm) and a secondary mode, coarser than the dominant one, of 0.8phi

(0.57mm); it is moderately sorted, very positively skewed and platykurtic.

Contrary to the other samples, the sample of station V3, which was situated in the

dredged zone, does not contain gravel and is composed of more than 99% sand. The

median diameter of 0.34mm, classified as medium sand, is the finest of the three

stations. The distribution is bimodal, with a dominant mode of 1.7phi (0.31mm) and

a secondary mode of 1.1phi (0.48mm); it is mesokurtic and as opposed to the other

samples, this one is well-sorted and symmetrical.

Table 4.2: Summary of statistical parameters (phi units) of the particle size distribution of the seabed sediments for the three stations and their description according to McManus (1988).

Chapter 4: Results


45

Figure 4.1: Frequency histogram and cumulative frequency curve representing the grain sizedistribution at each sampling station. The median diameter of the sediments found in the bottles (d50 bottle) is also shown.

-4-3-2-101234560%

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46

4.1.3. Bottles sediment

Figure 4.2 presents the PSD of the sediment collected in the bottle left on the frame

supporting the instruments and Table 4.3 summarises the statistical parameters.

The sediment of bottle V3 represents more than 50% of the total weight of

sediments collecting in the bottles of the three stations during the experiment (Table

3.3, relative weight). This means that substantially more sediment was in

suspension at station V3 than at the two other stations.

The median diameter indicates that it is the finer fraction of the PSD (Figure 4.1)

which is put in suspension at the height of the sensor, as expected (Soulsby, 1997).

It was found that the sample from station V1 has the largest median diameter, at

28phi (102.9µm), which is classified as very fine sand. The sediment from station

V2 has the smallest median grain diameter, at 4.17phi (55.6µm), this size is

classified as coarse silt. This dissimilarity can be explained by the fact that the

sample from station V2 has a lower dominant mode than does the station V1 sample

(Figure 4.1) therefore the suspended sediment is composed of finer particles at

station V2 and coarser ones at station V1.

However, we found that the median diameter of sediment particles from the station

Table 4.3: Summary of statistical parameters (phi units) of the particle size distribution of thesediments found in the bottles for the three stations and their description according toMcManus (1988); the relative weight of sediment found at each station compared with the totalamount of sediment found in all three bottles is also indicated.

Chapter 4: Results


47

V3 bottle, which has a value of 3.86phi (68.9µm, very fine sand) is in between

those of the bottles of stations V1 and V2, whereas the median diameter of the total

PSD of seabed sediments is the finest of the three samples at station V3.

For all stations, the samples were found to be poorly sorted, symmetrical and

leptokurtic.

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Figure 4.2: Frequency histogram and cumulative frequency curve representing the grain size distribution of the sediment found in the bottles at each sampling station.



48

4.2. General conditions during the experiment

4.2.1. Meteorological conditions and waves.

Meteorological conditions and wave height, direction and period variations

throughout the 4-day experiment can be divided into five time periods (�phases�

hereafter) ranging from calm conditions to the beginning, development and end of a

storm.

During Phase 1, from the beginning of the experiment on the 19th of October at

13:00, until the 20th of October at 6:00am, the wind speed is low (2-7ms-1), the

wave height is small (~10cm), the wave period is quite variable with a relatively

low average of 4sec. The pressure is high which indicates fine weather conditions

(Buckley et al., 2004).

On the 20th of October from 6:00am to 14:00, during Phase 2, the wind blows from

the SSE, resulting in a fetch of approximately 5km in the Tromper Wiek Bay and

70km in the Pomeranian Bight. The wind speed increases, but not enough to cause

an increase in wave height. The pressure begins to decrease during Phase 2.

During Phase 3, on the 20th of October at 14:00, the beginning of the storm is

apparent. From 14:00 to 23:00, the wind continues to blow from the SSE with a

maximum speed of 15ms-1, which is classified as a moderate breeze on the Beaufort

wind scale (Annexe 5). The wave height increases, reaching a maximum value of

1.3m at the end of Phase 3 and the wave period increases at the same time as the

wave height.

Chapter 4: Results


49

Figure 4.3: Pressure and wind at Cape Arkona (the direction indicates where the wind comesfrom); wave height, direction (where it propogates towards) and period (Tz), current (where itgoes) and depth at the station V1 during the experiment (HL = High water Level; LL = Lowwater Level).

20/10 21/10 22/10 23/10

11.6

11.8

12

dept

h (m

)

20/10 21/10 22/10 23/10-0.5

0

0.5

spee

d (x

0.1

ms-1

)

20/10 21/10 22/10 23/10

1000

1005

1010

pres

sure

(dB

ar)

20/10 21/10 22/10 23/100

5

10

15

20

spee

d (m

s-1)

20/10 21/10 22/10 23/100

90

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270

360

dire

ctio

n (d

egre

e)

20/10 21/10 22/10 23/100

0.4

0.8

1.2

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Hs

(m)

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dire

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n (d

egre

e)

20/10 21/10 22/10 23/102

4

6

Tz

(s)

20/10 21/10 22/10 23/100

5

10

SS

C (

mgl

-1)

1 2 3 4 5

Storm

N

HL

LL LL

LL LL LL

HLHL



50

After 23:00 (Phase 4), the wind direction progressively changes from a SSE to a

SW source, i.e. wind blowing from the land. The fetch is greatly reduced (about

2.5km, Figure 1.5) and the wave height progressively decreases until the end of the

storm on the 21st of October at 16:00.

Due to the semi-enclosed nature of the bay, the wave height in Tromper Wiek Bay

is strongly influenced by the wind direction (Klein, 2003). Only if the wind comes

from the east can the wave height increase. A diminution in wave height is

effectively observed since the wind blows from the west. The pressure reaches its

minimum value of 995 dBar during Phase 4, which indicates cloudy or rainy

weather (Buckley et al., 2004).

Next, during Phase 5, the pressure is high, i.e. the weather improves, and the wave

conditions are calm, despite the wind being classified as a fresh breeze on the

Beaufort wind scale, due to the limited fetch.

The wave direction always falls between 250 and 280° during non-storm conditions

and equals 285° throughout the entire storm period (Figure 4.3).

The low wave period (4-5sec) observed during the whole experiment indicates that

the waves are locally-generated (periods of wind-waves = 1-10sec) and do not

constitute swell, which have a much longer period (10s or more, Melville, 2001).

The predicted wave height and period for a wind blowing at 10ms-1 on a fetch on

the whole Pomeranian Bight (70km) in deep water is of 1.3m of 5.5sec respectively

(Annexe 6). However, if a scenario with only the fetch on the Tromper Wiek Bay

Chapter 4: Results


51

taken into account (5km), a wave height of 0.35m and a period of 2.3s are

predicted. This is, nevertheless, an approximation since the water depth in the

Pomeranian Bight is shallower than 20m and the wind speed varies with time.

However, it does show that the waves recorded during the experiment were

certainly initiated in the Pomeranian Bight and travel to the Tromper Wiek Bay so

cannot be generated in the Tromper Wiek Bay. The wave direction data lends

support to this hypothesis since the waves are coming from the ESE, i.e. from the

Pomeranian Bight.

4.2.2. Water level variations

Water level oscillations with amplitude of about 15cm were observed (Figure 4.3).

These oscillations can be due to tides. The diurnal component of the tide is

dominant in the Tromper Wiek Bay but the semi-diurnal component is not

negligible (M2 + K2 / (S1 + K1) = 0.75, Kantha et al., 2005). However, the period

of these variations is variable (17h, 20h and 15h between two successive low water

levels, Figure 4.3). It is likely that the tides, which are of mixed nature, are

deformed by the local bathymetry and are subjected to water level variations caused

by the wind. Therefore the observed oscillation does not have the same period as

would have produced the tide alone. On the other hand, no variations occur during

the storm but we observe a decrease in the water level during the whole storm

period. This may be due to a storm surge, with wind blowing from the East pushing

the water out of the Tromper Wiek Bay and the whole Pomeranian Bight, thereby

inducing a diminution of the water level. This can have masked the tidal

oscillations.



52

However, as we know that the water level variations in the Tromper Wiek Bay are

largely influenced by wind surges and seiches (Klein, 2003) we can also envisage

that these oscillations are not due to tides but to a seiche. A seiche is a slow

oscillation of the water about one or several axes (nodes) which can happen in lakes

or basins (Knauss, 1997). There are a variety of ways in which a seiche may be

excited in a natural body of water; one of the most common is the passage of a

storm in which the wind pushes the water level up at the downward end of the

basin. When the wind dies down and the wind stress is removed, the water runs

downslope and the lake surface begin to oscillate. The period T of the oscillation in

a bay is:

ghnlT 4= (19)

where l is the length of the basin, g is the acceleration due to the gravity, h is the

water depth and n (= 1, 3, 5�) is the number of the node.

However, it proves difficult to estimate the length of the basin and the number of

the node. We have seen that during the storm a surge may have been produce by the

wind blowing from the land. The induced decrease of the water level can next

initiate or be super-imposed on the previous oscillations. A basin length of 100km

(from the coast of the Pomerianian Bight to Sweden), a water depth of 70m and

assuming one node is present lead to a seiche period of 4h. Therefore, if the

oscillations recorded are produced by a seiche, it must have been initiated on a

bigger scale than that of the basin from the Pomeranian Bight to Sweden.

Chapter 4: Results


53

We also observed smaller oscillations with a period of 1h and maximum amplitude

5cm. The 1h period recorded may well not be the �real� period of the phenomenon

but is the smallest oscillation period that can be recorded because bursts are taken

every 30min. These oscillations may be due to a seiche in the Tromper Wiek Bay.

The length of the bay from the coast to the depth 20m is about 5.5km, the mean

depth in the bay is estimated to be 13m. Assuming that there is only one node, we

find a period of 32min, which is half the observed period of 1h. Therefore, it does

not seem plausible that these oscillations were caused by a seiche on the scale of

Tromper Wiek Bay.

It is highly possible that the water level variations recorded during the experiment

are in fact a combination of all of these factors, tidal variations, storm surges and

seiches, all oscillations being influenced by the local topography.

4.2.3. Currents

a) Comparison of methods.

We begin by comparing the results given by Wavelog in the statistical files with the

results of the analysis of the high frequency files (Figure 4.4). The results are very

similar with a correlation coefficient of 0.95 for current direction and 0.81 for

current speed for station V1 (approximately the same is found for the other

stations). The slight difference is due to the fact that Wavelog does not separate the

wave and current components to calculate the current characteristics.



54

Consequently, because the data calculated from the high frequency files are filtered

from the wave component, they better estimate the current characteristics and will

be used for the rest of the study.

b) Currents description and analysis

Before the storm, currents at station V1 at the height of the sensor (0.5m of the

seabed, ~11.5m depth) are very weak (~0.02ms-1), towards the South when the

water level increases and towards the North when it decreases (Figure 4.3).

Therefore these currents are certainly linked to the water level variations, be they of

tidal or other origin. At the beginning of the storm, the currents are slightly stronger

20/10 21/10 22/10 23/100

0.02

0.04

0.06

0.08

0.1

flow

(m

s-1)

from tidestat files

from puvt files

20/10 21/10 22/10 23/100

90

180

270

360

dire

ctio

n (d

egre

e)

from tidestat files

from puvt files

20/10 21/10 22/10 23/100

90

180

270

360

dire

ctio

n (d

egre

e)

from tidestat files

from puvt files

Figure 4.4: Comparison of current speed and direction given in tidestat files and calculatedfrom puvt files; example for station V1.

Chapter 4: Results


55

(~0.05ms-1) and flow towards the NE. At this time, the wind blows from the SSE

which certainly induces a circulation of water inside the bay, pushing the water to

the N. The currents are recorded at the northwestern part the bay and indicate that at

this point the currents flow offshore (Figure 4.5).

During the storm the currents progressively turn and at the end of the storm flow

towards the NW. At this time, the wind is blowing from the SW, pushing the water

out of the bay, the circulation inside the bay induces the currents recorded at the

ABLs position and depth to flows towards the North.

After the storm, the currents flow towards the SSW whilst the wind is still blowing

from the SW. Therefore, these currents are almost certainly compensating bottom

2.5 km

NCape Arkona

2.5 km

NCape Arkona

2.5 km

NCape Arkona

2.5 km

NCape Arkona

Wind

Currents

Before the storm Beginning of the storm

End of the storm After the storm

Figure 4.5: Schematic representation of the currents at station V1 and wind at Cape Arkonabefore, at the beginning, at the end and after the storm. The size of the arrows gives anindication of the speed of wind and currents.



56

currents, frequently observed in the Pomeranian Bight (Lass et al., 2001), which

compensate for the water that the wind pushes away.

4.2.4. Suspended Sediment Concentration

The suspended sediment concentration measured at the height of the sensor shows a

relatively constant value of 0.4mgl-1 during non-storm conditions (Figure 4.3). This

represents the background value which is the concentration during non-event

periods.

The SSC at station V1 begins to increase at 18:00, 4 hours after the beginning of the

storm when the wave height is 0.65m. SSC then increases significantly at 21:00

(wave height 0.85m); it reaches a maximum value of 8.2mgl-1 on the 21st at 3:00am

(wave height 1m). It decreases quite rapidly to a value of 1mgl-1 at 8:30am (wave

height 0.45m) and then decreases very slowly to the background value by 21:30, 5

hours and thirty minutes after the end of the storm.

Chapter 4: Results


57

4.3. Comparison of data at the stations

4.3.1. Currents

Currents at station V2 exhibit similar variations to what was seen at station V1

(Figure 4.6) although they are slightly stronger (~20%) at station V2. Therefore

conclusions made for station V1 are also applicable to station V2.

Currents at station V3 are found to be quite different. Their direction is nearly

always northward to northwestward. Their speed is always slower (~50%) than at

stations V1 and V2. Before and after the storm, current speed for station V1 is very

low (around 0.01 ms-1) with very small variations and during the storm, it only

20/10 21/10 22/10 23/10-0.4

-0.2

0

0.2

0.4

0.6

0.8

spee

d (x

0.1

ms-1

)

V1

20/10 21/10 22/10 23/10-0.4

-0.2

0

0.2

0.4

0.6

0.8

spee

d (x

0.1

ms-1

) V2

20/10 21/10 22/10 23/10-0.4

-0.2

0

0.2

0.4

0.6

0.8

spee

d (x

0.1

ms-1

) V3

Storm

N

Figure 4.6: Currents at the three stations during the experiment.



58

reaches a value of 0.03ms-1.

Therefore we observed that the currents speed is reduced inside the gravel-dredged

pit compared with outside, as expected since the water depth is greater.

4.3.2. Waves

a) Wave height and period

The variations of wave height and period are very similar for the three stations

(Figure 4.7). However, we found that the wave height is approximately 10% larger

and the period 4% higher at station V3 than at stations V1 and V2.

This finding has no physical explanation since the wave theory predicts a decrease

of wave height with increasing water depth. This could be due to an offset of the

records caused by slightly different calibrations of the three instruments.

20/10 21/10 22/10 23/100

0.2

0.4

0.6

0.8

1

1.2

Hs

(m)

V1

V2V3

20/10 21/10 22/10 23/102

4

6

Tz

(s)

Figure 4.7: Wave height (Hs) and period (Tz) at the three stations during the experiment.

Chapter 4: Results


59

b) Directional wave spectra

The estimation of directional wave spectra was calculated using 'Diwasp', a toolbox

of Matlab functions. Directional wave spectra, calculated and plotted for bursts

recorded before and during the storm at stations V1 and V3 (V2 is very similar to

V1), show differences in the wave energy in storm and non-storm conditions.

In non storm conditions (Figure 4.7a. and b., example of burst 30 at stations V1 and

Figure 4.8: Frequency, direction and spectral power density estimated using EMEPmethod. a. station V1 burst 30; b. station V3 burst 30 (calm conditions); c. station V1 burst 75; d. station V3 burst 75 (storm conditions).

Figure 4.9: Wave height and period for the three stations during the experiment. a. b.

c. d.

V1 V3 Non-storm Non-storm

Storm Storm



60

V3), we observe that the energy is quite low (with the range of 10-3m2sdeg-1) and

distributed over a large band of directions and periods with an energy peak at

180°N and a period of 5sec.

During the storm (Figure 4.8c. and d., example of burst 75 at stations V1 and V3)

the maximum wave energy is much higher (~100 times higher) and concentrated

upon a narrower band of direction and period (~150-200°) than in non-storm

conditions (~120-270°), even though the peak direction and period are still almost

identical (180°-5sec).

These plots also show energy differences between the reference station V1 and the

station inside the dredged-pit, V3. In non-storm conditions, the maximum wave

energy at station V3 is higher (~50%) and is distributed over a larger range of

direction. It is observed during the entire storm period that the maximum wave

energy at station V3 is higher than at station V1 but is distributed over a much

narrower range of period and direction (e.g. during burst 75, at station V1 the

period, direction and peak energy are respectively 3.5-6.6sec, 150-200° and

0.4m2s/deg and at station V3 are 4.2-6.6sec, 170-190° and 1.4 m2s/deg).

c) High frequency surface elevation

The surface elevation variations of each burst allow one to actually see the waves as

they pass over the sensor (Figure 4.9). Each single wave is clearly identifiable as

well as the waves groups. We can see the progressions of the waves and wave

groups over the three sensors; the waves travel from east to west and are first

Chapter 4: Results


61

recorded at station V2, next at station V1 and finally at station V3. However, it is

important to remember that the stations are not exactly aligned in the direction of

wave propagation (Figure 3.3). Therefore slight variations between the stations are

likely due to lateral variations of the waves.

22:40 22:4510.5

11

11.5

12

12.5

13

dept

h (m

)

V2

22:40 22:4513.5

14

14.5

15

15.5

16

dept

h (m

)

V3

22:40 22:4510.5

11

11.5

12

12.5

13

dept

h (m

)

V1

Figure 4.9: Surface elevation during Burst 73 (20/10, storm conditions) showing the wavesfor the three stations.



62

4.3.3. Suspended Sediment Concentrations

The suspended sediment concentrations measured during the experiment at the

three stations is shown in Figure 4.10. We observe that the background value is the

same for the three stations (~0.4mgl-1).

The SSC at station V2 is found to be very similar to that at station V1. On the

contrary, SSC at station V3 is very dissimilar to those at the other two stations.

During the storm, SSC at station V3 is almost always greater than SSC at stations

V1 and V2. SSC at station V3 then begins to significantly increase at 19:30, i.e. an

hour and a half before the SSC at stations V1 and V2 begin, in turn, to considerably

increase. Subsequently, the SSC at station V3 is observed to be consistently higher

than the SSC at stations V1 and V2 for the entire storm period.

The maximum SSC value at station V3 is 20.3mgl-1, measured on the 21st October

at 1:00, at which time SSC at stations V1 and V2 is equal to 3mgl-1 and 2.8mgl-1

20/10 21/10 22/10 23/100

2

4

6

8

10

12

14

16

18

20

SS

C (

mgl

-1)

V1

V2

V3

Storm

Figure 4.10: Suspended sediment concentration (SSC) during the experiment for the threestations.

Chapter 4: Results


63

respectively. At the end of the storm, when SSC at stations V1 and V2 decrease

rapidly to a value of 1mgl-1, we note that the SSC at station V3 reaches the same

value simultaneously (at 8:30am) and from then on has the same value as do the

other two stations.

Therefore, it was observed that SSC at station V3, as compared to SSC at stations

V1 and V2:

- has the same background value,

- begins to increase before,

- is higher during the entire storm period and

- decreases simultaneously.



64

4.4. Sediment mobility

4.4.1. Current only bed shear-stress

The skin friction bed shear-stress due to the current only (equation (2)) was

calculated using the results from the high frequency data and compared with the

threshold of movement (equation (11)). The temperature during the experiment was

5°C and the typical salinity in the Pommerian Bight for the month of October is 8

(Lass et al., 2001); therefore the water density ρ was taken as 1008kgm-3 and the

kinematic viscosity of water ν as 1.5x10-6m2s-1 (Annexe 6).

Soulsby (1983) proposes values of bed roughness length equal to 0.006m for

rippled sand and to 0.0003m for seabed composed of a sand and gravel mixture. We

have seen that the sediment sampled from station V3 was mainly composed of sand

and the video has shown that the bed is rippled; therefore the roughness length is

taken as 0.006m. Sediment samples from stations V1 and V2 are composed of sand

and gravel, so a value of 0.0003m can be used. However we have seen that large

portions of the seabed around stations V1 and V2 are composed of rippled sand,

thus a roughness length equal to 0.006m was also tested for these stations.

20/10 21/10 22/10 23/100

0.05

0.1

0.15

0.2

0.25

0.3

τ (N

m-2

)

τ c (z

0 rippled sand)

τ c (z

0 sand/gravel)

τ critic

Storm

Figure 4.10: Current-induced bed shear-stress (τc) and threshold bed shear-stress (τcr); example for the station V1 for a roughness length z0 of 0.0003m (sand/gravel) and 0.006m (rippled sand).

Chapter 4: Results


65

The results show that the current induces a very weak bed shear-stress which is

incapable of putting the sediment into movement at any of the stations as well as for

all of the bed roughness lengths used (Figure 4.11, example at station V1, results

similar are found at the two others stations).

4.4.2. Wave orbital velocity

a) Amplitude of the wave orbital velocity under the crest and under the trough

The significant and maximum wave orbital velocity under the crest (Uwcrest) and

the trough (Uwtrough) calculated from the high frequency data at station V1 are

shown in Figure 4.12. The results are similar at the two others stations. It is

observed that the amplitudes of orbital velocity under the crest and the trough are

very similar; the difference between them is found to be very low (Figure 4.13).

20/10 21/10 22/10 23/100

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

ms-1

Uwsig crest

Uwsig troughUwmax crest

Uwmax trough

Storm

Figure 4.11: Significant and maximum amplitude of orbital velocity under crest and troughat station V1.



66

The amplitude difference almost equals zero during non-storm conditions. It

increases during the storm and varies from -20 to 20% of Uwcrest for the maximum

orbital velocity and from -6 to 6% for the significant orbital velocity. The variations

at the three stations have almost the same amplitude but different signs. The

average of the difference of orbital velocity under the crest and the trough over the

whole experiment is between -1 and 1% of Uwcrest for all the stations.

Thus we found that the waves are highly symmetrical. Indeed, the steepness

(height/wavelength) is very small throughout the experiment (~0.01).

As a result, the crest orbital velocity alone will be used for the remainder of the

study since the difference between the crest and trough orbital velocities is not

significant. Results derived from the trough orbital velocity were calculated in order

to verify this assumption and were found to be the same as those calculated using

the crest orbital velocity.

20/10 21/10 22/10 23/10

0

0.05

0.1

ms-1

significant

maximum

Storm

Figure 4.12: Difference of amplitude of wave orbital velocity under the crest and underthe trough at station V1.

Chapter 4: Results


67

b) Comparison of theoretical and measured wave orbital velocity

Using the significant wave height given in the statistical files, we calculated the

theoretical significant wave orbital velocity from the linear wave theory (equation

(4)) and compared it to the significant orbital velocity calculated from the high

frequency data (Figure 4.14).

The calculated orbital velocities underestimate by half the measured wave orbital

velocities for the low values, i.e. in non-storm conditions (Uw ≈ 0.025ms-1).

However, they accurately predict the measured Uw for the larger values (for Uw >

0.15 ms-1 the calculated orbital velocity is between 0 and 10% higher than the

measured one). It should be noted that the measured orbital velocities show fewer

variations from one measurement to another than the calculated orbital velocities.

The variations of the latter are found to be essentially due to variations in the wave

height (which are large) and are not attributable to fluctuations of the wave period,

which was found to be relatively constant throughout the storm.

20/10 21/10 22/10 23/100

0.05

0.1

0.15

0.2

0.25

orbi

tal v

eloc

ity (

ms-1

)

Uwsig-crest

Uwsig calculated

Storm

Figure 4.13: Significant measured and calculated amplitudes of orbital velocity during the experiment at station V1.



68

However, these results show that the difference between measured and calculated

amplitudes of orbital velocity is very small; hence the wave linear theory is

applicable to the waves recorded during this experiment.

c) Differences between the stations

The significant and maximum wave orbital velocities for the three stations are

presented in Figure 4.15.

Wave orbital velocities variations are the same at the three stations; however the

orbital velocity amplitude is smaller at station V3 than at stations V1 and V2,

especially during the storm (~0.05ms-1 smaller). This is effectively what is

predicted by the wave linear theory since the water depth is greater at station V3,

inside the crater, than at the reference stations V1 and V2.

20/10 21/10 22/10 23/100

0.05

0.1

0.15

0.2

0.25

Uw

(ms-1

)

V1

V2

V3

Storm

Figure 4.14: Significant wave orbital velocity for the three stations during the experiment.

Chapter 4: Results


69

4.4.3. Wave-only bed shear-stress

The skin friction bed shear-stress for the waves (equation (5)) was calculated using

the crest orbital velocity calculated from the high frequency data and compared

with the threshold of movement (Figure 4.16).

Figure 4.15: Wave bed shear-stress (τw) calculated for a roughness length (z0) of 0.0003m (sand/gravel) and 0.006m (rippled sand) at stations V1 and V2 and a roughness length of0.006m at station V3.

20/10 21/10 22/10 23/100

0.5

1

1.5

2

2.5

3

3.5

τ (N

m-2

)

τ w

τ critic

20/10 21/10 22/10 23/100

1

2

3

τ (N

m-2

)

τ w (z0 rippled sand)

τ w (z0 sand/gravel)

τ critic

20/10 21/10 22/10 23/100

1

2

3

τ (N

m-2

)

τ w (z0 rippled sand)

τ w (z0 sand/gravel)

τ critic

V1

V2

V3

Storm

Threshold exceeded



70

We notice that a roughness length of 0.0003m or 0.006m used to calculate the wave

bed shear-stress at stations V1 and V2 does not alter the result due to the fact that

the wave friction factor, fw, does not change. Indeed in this model the wave friction

factor value is more sensitive to the wave orbital velocity value than to the

roughness length.

We can see that the wave bed shear-stress calculated for station V3 is nearly half

the value of those of stations V1 and V2. This is because the wave orbital velocity

is smaller at station V3. As a consequence the critic bed shear-stress is reached at a

different moment at stations V1 and V2, and V3 (Figure 4.16.

The threshold of movement is exceeded from 17:30 on the 20th to 14:30 on the 21st

at stations V1 and V2 and from 18:00 on the 20th to 13:00 on the 21st for station V3,

i.e. the sediment will be put into motion half an hour later and will stop moving an

hour and a half earlier at station V3 than at stations V1 and V2.

4.4.4. Total bed shear-stress

The maximum bed shear-stress under combined waves and currents (equation 10) is

found to be almost equal to the wave-induced bed shear-stress (Figure 4.17). The

20/10 21/10 22/10 23/100

0.5

1

1.5

2

2.5

3

3.5

τ (N

m-2

)

τ w

τ max

τ m

τ critic

Storm

Threshold exceeded

Figure 4.16: Wave-induced bed shear stress, (τw), maximum bed shear stress for combinedflow (τmax) and threshold bed shear stress (τcr) during the experiment at station V1.

Chapter 4: Results


71

relative importance of the wave bed shear-stress on the maximum wave shear-stress

(τw /τmax) was found to equal 100% for the three stations during almost the entire

period during which the threshold was exceeded (Figure 4.18). The current

component of the bed shear-stress is found to be important only when the threshold

is not exceeded. We note that the relative strength of the wave bed shear-stress is

sometimes higher than 100%; this is due to the different directions of the waves and

the current which may act to reduce the wave-induced bed shear-stress.

The mean bed shear-stress during a wave cycle almost always equals zero (Figure

4.17), i.e. the current does not diffuse the sediment upwards.

20/10 21/10 22/10 23/100

20

40

60

80

100

τ w

/ τ

max

%

20/10 21/10 22/10 23/100

50

100

τ w

/ τ

max

%

20/10 21/10 22/10 23/100

50

100

τ w

/ τ

max

%

V1

V2

V3

Storm

Threshold exceeded

Figure 4.17: Relative importance of the wave-induced bed shear-stress on the maximumbed shear-stress during the experiment for the three stations.



72

Waves can effectively put the sediment into motion during the storm; however we

have seen that they are very symmetrical and so will induce a relatively small

amount of sediment transport. This is why the currents, even if they are too low in

magnitude to induce sediment movement or diffuse the sediment upwards

themselves, can play a transporting role once the sediment has been put into

suspension by the waves.

4.4.5. Fraction of sediment in motion

In order to evaluate which fraction of seabed sediment is put into motion during the

storm, we calculated the threshold of movement for the different fractions present in

each seabed sample and compared them with the wave bed shear-stress (Figure

4.19).

At station V1 all the sediment is put into motion but the coarser fraction is in

motion only when the bed shear-stress is maximal.

At station V2, not all of the sediment is put into motion. Sediment coarser than

~4mm (d84) will not move even at the maximum bed shear-stress, i.e. in the gravel

fraction, only the granules (2mm< Ø < 4mm) will move.

We see that all the sediments are put in motion almost simultaneously at station V3

because the seabed sample is entirely composed of sand.

These results indicate that the entire sand fraction is put into motion at all three

stations during the storm, the granule fraction moves when the bed shear-stress is

strong enough (τw > ~1.5 Nm-2) and sediment coarser than this does not move under

any circumstances during the experimental period. However, it is important to

Chapter 4: Results


73

remember that this indicates which sediment fractions are put into motion but does

not indicate whether the mode of transport is as bedload or in suspension. Indeed,

only the finest part of the sediment in motion can be transported in suspension, the

coarser fraction will move as bedload.

20/10 21/10 22/10 23/100

1

2

3

4

bed

shea

r st

ress

(N

m-2

)

τw

d5 = 0.28224mmd16 = 0.34869mmd25 = 0.38689mm

d50 = 0.5mm

d75 = 0.80107mmd84 = 1mmd95 = 2.4623mm

20/10 21/10 22/10 23/100

2

4

6

8

10

bed

shea

r st

ress

(N

m-2

)

τw

d5 = 0.23326mmd16 = 0.29525mm

d25 = 0.32988mm

d50 = 0.5mm

d75 = 2.4623mmd84 = 4.5948mm

d95 = 9.8492mm

20/10 21/10 22/10 23/100

0.5

1

1.5

2

2.5

bed

shea

r st

ress

(N

m-2

)

τw

d5 = 0.19278mmd16 = 0.24571mm

d25 = 0.26794mm

d50 = 0.34151mm

d75 = 0.41466mmd84 = 0.46329mm

d95 = 0.54525mm

V1

V2

V3

Figure 4.18: Wave bed shear-stress and threshold of motion for different quartile at the three stations during the experiment.



74

4.5. Suspended sediment concentration

We have demonstrated that sediment movement is entirely due to wave action and

that the current does not diffuse the sediment upwards, therefore the suspended

sediment concentration was calculated using equation (17) valid under waves for a

rippled bed (Soulsby, 1997).

The median grain diameter of the seabed sample was used to calculate the mobility

number and the different Shield parameters. This is due to the fact that bed shear-

stress, ripples length and height, as well as mobility number are functions of the

total sediment distribution at the seabed. On the other hand, the median grain

diameter of the sediment found in the bottles was used to calculate the settling

velocity (equation (13)) because it allowed us to know the size of sediment which is

in suspension at this height. Sediment in the bottles was found to be a mixture of

mud and sand; the median grain diameter is classified as very fine sand at stations

V1 and V3 and coarse silt at station V2. We decided to use equation (13), valid for

sand grain sizes for the three samples since the median grain diameter is just at the

boundary between sand and mud and certainly exhibited non-cohesive sediment

behaviour rather than cohesive sediment behaviour.

For all stations, the calculated SSC does not predict the background value and thus

is found to be zero in non storm conditions.

During the storm the calculated SSC at station V1 is 0 to 4 times higher than the

measured SSC. It is found to predict the increase and decrease in SSC at the same

Chapter 4: Results


75

time as the observed increase (20th of October at 21:00) and decrease (21st of

October at 8:30am, Figure 4.20).

The calculated suspended sediment concentration at station V2 at a height of 0.55m

is 0-0.5 times lower than the measured concentration during the storm. The increase

in SSC is calculated to occur half an hour after what is observed and the decrease

half an hour before.

Figure 4.19: Suspended sediment concentration (SSC) calculated at the height (z) of eachOBS for the three stations.

20/10 21/10 22/10 23/100

5

10

15

20

SS

C (

mgl

-1)

z = 0.45 m

SSC calculated

SSC measured

20/10 21/10 22/10 23/100

2

4

6

8

SS

C (

mgl

-1)

z = 0.55 m

SSC calculated

SSC measured

20/10 21/10 22/10 23/100

5

10

15S

SC

(m

gl-1

)

z = 0.45 m

SSC calculated

SSC measured

V3

V2

V1



76

At station V3 it was found that the calculated SSC underestimates greatly the

measured SSC (4 times lower). It predicts an increase in SSC at 21:30 the 20th of

October, 2 hours later than the observed increase (19:30) and a decrease at 8:00am

on the 21st of October half an hour earlier than the observed decrease (8:30am).

The differences found between the calculated and measured SSC at stations V1 and

V2 may be due, amongst other reasons, to inaccurate estimation of parameters, non-

constant eddy diffusivity or error in the calibration of instruments.

Almost all of the formulas that we used are empirical formulas deduced from

measurements in a particular environment and can lead to inaccurate estimations

when used for other set of conditions.

We observe that each peak in the calculated SSC occurs slightly earlier than what is

measured. This could indicate the influence of currents, which even if there are very

small, can cause slight variations in the eddy viscosity.

On the other hand, the calibration curve of the OBS could be inaccurate and lead to

errors in the estimation of the SSC.

However, it is observed that the calculated SSC at the reference stations V1 and V2

predicts the increase and decrease of the measured SSC at almost the right moment

and both have the same order of magnitude. On the contrary, at station V3 the

calculated SSC is much lower, the increase is predicted to happen 2 hours after and

the decrease half an hour earlier than what is observed.

Chapter 5: Interpretation


77

CHAPTER 5: INTERPRETATION

5.1. Hydrodynamic effects

The results show that throughout the entire experiment the currents are slower at

station V3, inside the pit, than at the reference stations V1 and V2 and have

different directions. This difference is induced by the greater water depth in the

gravel-pit, which leads, as described by Klein (2003) in the Tromper Wiek Bay, to a

decoupling of the flow inside the crater from the flow above. The current direction

inside the pit, always towards the NW, may be caused by a morphological effect.

Furthermore a significant reduction of the orbital velocity is observed inside the pit

compared with outside the pit. This agrees very well with the wave linear theory

which predicts a diminution of orbital velocity when increasing the water depth.

Therefore it has been found, as expected by theories and previous research (Graca

et al., 2004, Kleinhans et al., 2004), that both wave and current components of the

flow are reduced in the pit and above compare with in the area surrounding the pit,

due to the increase in water depth.



78

5.2. Effects on sedimentation

The pit seabed has been found to be entirely composed of sand whereas seabed at

the reference stations is composed of both sand and gravel. This indicates that the

gravel extraction induces a change in the seabed nature since the gravel is extracted

whereas the sand is spilt back into the sea and partially refills the pit in the same

area, as described by Diesing et al. (2004). Thereafter the sediments inside the

crater are finer and better sorted than outside.

Results found from the SSC and sediment mobility are summarised in Figure 5.1.

It has been calculated that the threshold of movement is reached half an hour later

in the pit than outside and sediment movement stops an hour and a half earlier

although the sediments are finer, which implies a smaller threshold of movement.

Thereafter the bed shear-stress is smaller inside the crater.

Contrary at what was expected from these results it has been observed that the SSC

at the height of the sensor increases significantly an hour and a half earlier inside

the pit than at the reference stations. Furthermore, the SSC inside the crater is found

to be significantly larger than the SSC outside the pit.

The calculated SSC at the height of each sensor also indicates differences between

the reference stations, V1 and V2, and the station inside the gravel-dredged pit, V3.

It predicts well the increase of SSC at stations V1 and V2 but at station V3 the

increase is observed 2 hours before that which is predicted. Additionally the

calculated SSC underestimates the measured SSC.



79

The results indicate that a large part of the sediment is advected from outside the

crater rather that being of local origin. We can put forward the succession of events.

At 17:30 on the 20th the threshold of motion is reached outside the crater and the

bed shear-stress increases rapidly. The sediment begins to move principally as

bedload and the finer fraction is carried in suspension. The SSC at stations V1 and

V2 increases very slightly. Inside the pit the bed shear-stress is exceeded half an

hour later and is lower, here the sediments are transported essentially as bedload. At

19:30, the SSC at the height of the sensor inside the pit began to increase whereas

Figure 5.1: Measured SSC at the three stations during the experiment, time ofsediment movement calculated from the bed shear-stress and time of sediment suspension at the height of the sensor from the calculated SSC.

20/10 21/10 22/10 23/100

5

10

15

20

SS

C (

mgl

-1)

20/10 21/10 22/10 23/100

5

10

15

20

SS

C (

mgl

-1)

20/10 21/10 22/10 23/100

5

10

15

20

SS

C (

mgl

-1)

Predicted sediment movement

V3

V2

V1

Predicted sediment suspension at the

sensor height

Observed increase in SSC



80

this is not predicted and does not occur outside the pit. This can be explained by the

lower waves and current speeds above the pit compared with around it which

induces the sediment put into motion and transported outside the pit to fall into the

pit. A vertical component of the current, enhanced by the depth of the pit, may also

contribute to the increase in SSC inside the pit by pushing the sediment into it. At

21:00 the wave action is strong enough to put the sediment into suspension at the

height of the sensor outside and inside the pit, the SSC therefore increases

significantly. For the entire period during which the sediment is in suspension at the

height of the sensor, the SSC inside the pit is significantly higher that outside and

made up of local and advective sediment. At 8:30 on the 21st, the bed shear-stress is

no longer high enough to maintain the sediment in suspension and therefore, the

SSC decreases significantly inside and outside the pit. It will take 12 and a half

more hours for all of the sediments to fall to the seabed and the SSC to equal the

background value.

Figure 5.2: Schematic representation of the sequence of events during the storm.

The blue arrows indicate the strength of the current, the ellipse represent the action of waves. In the non-dredged zone gravels are present in patchy deposit and the sediment size is bigger than inside the pit.



81

Therefore, this proves that due to the less significant wave and current action inside

and above the pit than outside and also due to a vertical component of the current,

the pit acts as a trap to the sediment which was put into motion outside the pit

(Figure 5.2).

Although this experiment demonstrates that the pit acts as a trap for fine sediment,

it has also proven, as described by Diesing et al. (2004), that at this water depth the

sediment is put into motion only when the wave height is relatively high (at least

0.45m), which is true on this coastline only during storm events when the wind

blows from the East. Therefore, the time scale of regeneration may be quite long.

However we also demonstrated that the pit acts as a trap for sediment. In the

Tromper Wiek Bay an important quantity of aggregates has been dredged and in the

northern part, a site of gravel extraction, the seabed is covered by a significant

number of pits. The pits, by trapping the sediment, remove it from its natural

pathway, and may alter the sedimentary budget of the beach. This can result in a

lack of sediment arriving at the coast and hence cause coastal erosion.



82

CHAPTER 6: CONCLUSIONS

This study allowed the description of waves, currents and suspended sediment

concentration in the Tromper Wiek Bay under storm and non-storm conditions. It

was observed that:

- the currents were permanently very low (~0.003ms-1),

- the wave height under non-storm condition was very small (~10cm) as was the

wave period (~4sec) and its increase was strongly dependent on wind direction;

only wind from the east produced an increase in wave height (up to 1.3m), which

was observed at the same time as an increase in wave period (up to 5s),

- the waves recorded in the Tromper Wiek Bay during the storm were locally

generated (generation in the Pomeranian Bay),

- the waves were very symmetrical, i.e. orbital velocities under the crest almost

equalled orbital velocities under the trough, and are well described by the wave

linear theory,

- the sediments were put in motion by waves since the wave height was high

enough (~0.5m), the currents were not found to be sufficiently strong to induce

sediment movement.

Furthermore, the results of this study allowed us to characterise some effects of the

isolated 3m-deep gravel-dredged pit studied:

- the currents were found to be decoupled inside the pit, i.e. current speed was

reduced inside and above the dredged zone and current direction was changed

compared with that of currents around the pit,



83

- the wave orbital velocities inside the pit were observed to be smaller than around,

as predicted by the wave linear theory, since the water depth increased,

- inside the pit, the seabed sediment size (sand) was found to be much smaller than

outside (mixture of sand and gravel), this was first induced by pit re-filling with

spilled back sediment during the dredging and then amplified by the fact that the pit

acted as a trap for sediment when put in movement by wave action. The pit refilled

with transported fine sediment due to the decrease in waves and currents speed

above and inside the pit.

Although we have proved that the pit is a trap for fine sediments, and will certainly

change the sediment budget towards the coast, we cannot quantify the influence that

it will have on coastal erosion. Therefore further studies could concentrate on the

quantification of sediment trapping and the influence on coastal erosion. This can

be done, for example, by modelling the waves, currents and sediment transport as

done on US coasts by Maa et al. (2004).

Furthermore, it would also be interesting to better evaluate the time scale of

regeneration of the dredged-area. This could be done by a survey of the gravel-pit

over a long time scale (several years at least) using, for example, a repeated Side

Scan Sonar.

Furthermore this research was done on a site of low energy where the threshold of

movement is reached only during storms. Other studies on the effect of pits in

smaller water depth or in high currents environment would increase the knowledge

of marine aggregate extraction impacts.



84

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Chapter 5: Annexes


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ANNEXES



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Annexe 1: Model to illustrate the formation of relict sand and gravel, example offshore south-eastern Britain (from BMAPA, 1995).

Chapter 5: Annexes


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Annexe 2: Statistical measures of grain size parameters and descriptive terms applied to parameter values (McManus, 1988).

Annexe 3: Sketch showing the Faraday effect, which forms the basis of the electromagnetic current meter. The effect results in a potential difference E= B V L induced between two electrodes (X and XX) with a separation L when a conductor (seawater) moves at a resolved velocity V perpendicular to the line X - XX and perpendicular to a magnetic field with a flux density of B induced by coil C (from Collar and Griffiths, 2001).



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Annexe 4: Sketch showing the principle of capacitive pressure sensors which use a thin diaphragm, quartz or silicon, as one plate of a capacitor. The diaphragm is exposed to the process pressure on one side and to a reference pressure on the other. Changes in pressure cause it to deflect and change the capacitance. The change may or may not be linear with pressure and is typically a few percent of the total capacitance. The capacitance can be monitored by using it to control the frequency of an oscillator or to vary the coupling of an AC signal. It is good practice to keep the signal-conditioning electronics close to the sensor in order to mitigate the adverse effects of stray capacitance. Circuit 6 is a schematic example (from Annexe 5: Constant pressure contours beneath a 100m wave. Water wave is 100m (from Pajala, 2002).

Chapter 5: Annexes


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Annexe 6: A selection of information from the Beaufort Wind scale (from Open University, 2000).



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Annexe 7: Nomogram of deepwater significant wave prediction curves of wind speed, fetch length and wind duration (from CERC, 1984).

Fetch length (km)

Win

d-st

ress

Fac

tor ,

UA, (

ms-1

)

Chapter 5: Annexes


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Annexe 8: Density and kinematic viscosity of water in function of temperature and salinity (from Soulsby, 1997).

H T WIEK AREA (B S )....V2 and a roughness length of 0.006m at station V3. 69 Figure 4.17:...

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