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G R A N G E R E S O U R C E S

A L B A N Y P O R T A U T H O R I T Y

Port Development

Oceanographic Studies

and Dredging Program Simulation Studies

July 2007

G L O B A L E N V I R O N M E N T A L M O D E L L I N G S Y S T E M S P T Y L T D Australian Oceanographers & Ocean Modelling Software Developers ABN 28 061 965 339

GEMS – Global Environmental Modelling Systems Report 376/06

Albany Dredging Program Simulations

GEMS Contact Details

Melbourne Office PO Box 149

Warrandyte VIC 3113

Telephone: +61 (0)3 9712 0016

Fax: +61 (0)3 9712 0016

Dr Graeme D Hubbert Mobile: +61 (0)418 36 63 36

Email: [email protected]

Steve Oliver Mobile: +61 (0)408 81 8702


Perth Office PO Box 1432

Subiaco WA 6094

Telephone: +61 (0)8 6364 0880

Matt Eliot Mobile: +61 (0)408 414 225


Website: www.gems-aus.com

Disclaimer

This report and the work undertaken for its preparation, is presented for the use of the

client. Global Environmental Modelling Systems (GEMS) warrants that the study was

carried out in accordance with accepted practice and available data, but that no other

warranty is made as to the accuracy of the data or results contained in the report. This

GEMS report may not contain sufficient or appropriate information to meet the purpose of

other potential users. GEMS, therefore, does not accept any responsibility for the use of

the information in the report by other parties.



CONTENTS

GEMS Contact Details...........................................................................................................2 1. Introduction...................................................................................................................9 2. Scope of Work............................................................................................................10

2.1 Field Work .........................................................................................................10 2.2 Model Setup ......................................................................................................10 2.3 Verification of MesoLAPS winds, GCOM3D and SWAN in King George Sound

and Princess Royal Harbour ......................................................................................10 2.4 Simulations for a Representative Dredging Period ...........................................11

3. GEMS Background Information..................................................................................12 4. Climate and Meteorology ...........................................................................................13 5 Oceanography............................................................................................................16

5.1 Circulation .........................................................................................................16 5.2 Waves ...............................................................................................................17

5.2.1 Extreme Wave Analysis ...........................................................................17 5.2.2 Waves Employed in the Current Study ................................................18

6. Field Work ..................................................................................................................19 6.1 ADCP Deployments ..........................................................................................19 6.2 Drifting Buoy Deployments................................................................................20

7. Meteorological Forcing ...............................................................................................24 7.1 Method ..............................................................................................................24

7.1.1 Data Sources.......................................................................................24 7.2 Analysis and Verification ...................................................................................25

7.2.1 MesoLAPS Validation..........................................................................25 7.2.2 Analysis of Wind Records ....................................................................25

8. Ocean Circulation Simulation .....................................................................................32 8.1 Method ..............................................................................................................32

8.1.1 Bathymetry ...........................................................................................32 8.1.2 Tides.....................................................................................................32

8.2 Verification ........................................................................................................32 9 Wave Simulation ........................................................................................................44

9.1 Method ..............................................................................................................44 9.1.1 The Wave Model ..................................................................................44

9.2 Verification ........................................................................................................44 9.2.1 Observational Data...............................................................................44 9.2.2 Results ................................................................................................45

10. Dredge Modelling .......................................................................................................53 10.1 Method..........................................................................................................53



10.2 Verification....................................................................................................53 11. Oceanographic Issues................................................................................................54

11.1 The Effects of Changes to the Entrance to Princess Royal Harbour............54 11.1.1 Hydrodynamic Studies .......................................................................54 11.1.2 Numerical “Dye” Tracing Studies .......................................................56 11.1.3 Conclusions from the Hydrodynamic and Numerical “Dye” Tracing

Studies ............................................................................................................57 11.2 Waves along the Channel ............................................................................67 11.3 Spoil Ground Location ..................................................................................67

12. Dredging Simulations .................................................................................................70 12.1 Dredge Assumptions ....................................................................................70 12.2 Particle Size Distributions and Settling Velocities ........................................71 12.2 Dredging Simulation .....................................................................................77

12.2.1 Total Suspended Solids ......................................................................77 12.2.2 Sedimentation ....................................................................................79

13. References .................................................................................................................91 Appendix A: Qualitative and Limited Quantitative Comparisons of DREDGE3D

Predictions with Data during the Geraldton Port Redevelopment Dredging Program .........92 A.1 Method.........................................................................................................92 A.2 Comparison of Predictions with TSS Measurements ..................................93 A.3 Comparison of Model Predictions with Satellite & Aerial Photos..................93 A.4 Outcomes ....................................................................................................94

Appendix B: Model Descriptions.....................................................................................100 B.1 GCOM3D....................................................................................................100

B.1.1 History and Physics...........................................................................100 B.1.2 General Description...........................................................................101 B.1.3 Horizontal and Vertical Structure.......................................................101 B.1.4 Numerical Procedures.......................................................................101 B.1.5 Boundary Conditions .........................................................................102 B.1.6 Tidal Data Assimilation......................................................................103 B.1.7 Model Applications ............................................................................103

B.2 SWAN.........................................................................................................104 B.3 DREDGE3D................................................................................................106

B.3.1 Model Features .................................................................................106 B.3.2 Establishment of the Dredge Log ......................................................107 B.3.3 DREDGE3D Methodology.................................................................107 B.3.4 Analysis of Results ............................................................................108



Table of Figures Figure 1: Princess Royal Harbour, Oyster Harbour and King George Sound ......................9 Figure 4.1: Typical synoptic evolution during March..........................................................14 Figure 4.2: Typical synoptic evolution during June............................................................15 Figure 6.1: ADCP Mooring configuration ...........................................................................19 Figure 6.2: Location of observation stations used for fixed point verification of winds

(MET), waves (WR) and currents (ADCP and CM). ........................................20 Figure 6.3: Wireless GPS Davis drifter prior to deployment in King George Sound..........22 Figure 6.4: Wireless GPS Davis drifter in King George Sound..........................................22 Figure 6.5: The 10 wireless GPS Davis drifter tracks. .......................................................23 Figure 7.1: Time series of wind direcions during validation period. ...................................27 Figure 7.2: Time series of wind speed during validation period.........................................28 Figure 7.3(a): Monthly wind roses based on Albany airport data..........................................29 Figure 7.3(b): Monthly wind roses based on Mesolaps airport data. ....................................29 Figure 7.4(a): Energetic wind frequency analysis. .................................................................30 Figure 7.4(b): Light wind frequency analysis..........................................................................30 Figure 7.5: Polar wind diagrams based on MesoLAPS for the period March-June for all

years (left) and 2005 (right). ............................................................................31 Figure 8.1: Region over which 3D ocean currents were simulated with GCOM3D. ..........34 Figure 8.2: Example of the ebb tide in KGS and PRH predicted by GCOM3D. ................35 Figure 8.3: Example of the flood tide in KGS and PRH predicted by GCOM3D................35 Figure 8.4: Comparison of near-surface current speeds measured at ADCP4 from

January 21 to February 12, 2006 (blue) with GCOM3D predictions (red). ......36 Figure 8.5: Comparison of near-surface current directions measured at ADCP4 from

January 21 to February 12, 2006 (blue) with GCOM3D predictions (red). ......36 Figure 8.6: Comparison of near-surface current speeds measured at ADCP5 from

February 12 to March 12 (blue) with GCOM3D predictions (red)....................37 Figure 8.7: Comparison of near-surface current directions measured at ADCP5 from

February 12 to March 12, 2006 (blue) with GCOM3D predictions (red)..........37 Figure 8.8: Comparison of near-bed current speeds measured at ADCP4 from January

21 to February 12, 2006 (blue) with GCOM3D predictions (red).....................38 Figure 8.9: Comparison of near-bed current directions measured at ADCP4 from

January 21 to February 12, 2006 (blue) with GCOM3D predictions (red). ......38 Figure 8.10: Comparison of near-surface current speeds measured at ADCP5 from

February 12 to March 12 (blue) with GCOM3D predictions (red)....................39 Figure 8.11: Comparison of near-surface current directions measured at ADCP5 from

February 12 to March 12, 2006 (blue) with GCOM3D predictions (red)..........39



Figure 8.12: Comparison of near-surface (blue) and near-bottom (red) current speeds

measured at ADCP6 from March 12 to April 29, 2006. ...................................40 Figure 8.13: Comparison of near-surface (blue) and near-bottom (red) current directions

measured at ADCP6 from March 12 to April 29, 2006. ...................................40 Figure 8.14: Comparison of near-surface (blue) and near-bottom (red) current speeds


measured at ADCP5 from March 12 to April 29, 2006. ...................................41 Figure 8.16: Comparison of near-surface (blue) and near-bottom (red) current speeds


measured at ADCP4 from March 12 to April 29, 2006. ...................................42 Figure 8.18: Comparison of the first 5 GPS drifter tracks with the tracks predicted from

GCOM3D near-surface currents (marked with M)...........................................43 Figure 8.19: Comparison of the second 5 GPS drifter tracks with the tracks predicted from

GCOM3D near-surface currents (marked with M)...........................................43 Figure 9.1: Wave model grid regions.................................................................................47 Figure 9.2: Location of MetOcean winter moorings ...........................................................48 Figure 9.3(a): Modelled wave heights at three locations AWAC-1(red), WRB (green) and

ADCP-3 (blue). ................................................................................................49 Figure 9.3(b): Modelled wave directions at WRB...................................................................49 Figure 9.4: Wave height attenuation through KGS. ...........................................................50 Figure 9.5(a): SWAN model (green) versus observed (red) wave heights at WRB. ..............51 Figure 9.5(b): SWAN model (green) versus observed (red) wave heights at AWAC-1. ........51 Figure 9.6: Typical spatial variability of wave induced bottom velocities. ..........................52 Figure 9.7: Time series of wave induced bottom velocities at AWAC-1 (red), WRB

(green) and ADCP-3 (blue)..............................................................................52 Figure 11.1: Plan view of the proposed channel dredging and reclamation in the wharf

and harbour entrance area. .............................................................................58 Figure 11.2: Cross section view of the proposed channel dredging and reclamation in the

wharf and harbour entrance area. ..................................................................59 Figure 11.3: Representation of Princess Royal Harbour Entrance before dredging

showing the model monitoring points inside and outside PRH and in the

entrance (X).....................................................................................................60 Figure 11.4: Representation of Princess Royal Harbour Entrance after dredging...............60 Figure 11.5: The high resolution model study region showing the monitoring points in the

channel and in side and outside PRH. ............................................................61 Figure 11.6: Wind speed in KGS during the 15 days modelled. ............................................62



Figure 11.7: Wind directions (to) in KGS during the 15 days modelled, showing a variation

from westerlies to north easterlies and back to westerlies. .............................62 Figure 11.8: Sea levels in Princess Royal Harbour before and after dredging....................63 Figure 11.9: Sea levels in the Harbour Entrance before and after dredging. ......................63 Figure 11.10: Sea levels in the shipping channel before and after dredging.........................63 Figure 11.11: Current speeds in Princess Royal Harbour before and after dredging...........64 Figure 11.12: Current speeds in the Harbour Entrance before and after dredging. ..............64 Figure 11.13: Current speeds in the shipping channel before and after dredging.................64 Figure 11.14: Current directions in Princess Royal Harbour before and after dredging. .......65 Figure 11.15: Current directions in the Harbour Entrance before and after dredging............65 Figure 11.16: Current directions in the shipping channel before and after dredging. ............65 Figure 11.17: Numerical “dye” trace 5 days after release from site labelled PRH1 forced by

currents through the channel before dredging is started. ................................66 Figure 11.18: Numerical “dye” trace 5 days after release from site labelled PRH1 forced by

currents through the channel after dredging is completed. .............................66 Figure 11.19: Location of the two spoil ground options. ........................................................68 Figure 11.20: Comparison of current speeds near the surface (blue) and near the bottom

(red) at the outer spoil ground option in September 2005. ..............................69 Figure 11.21: Comparison of current speeds near the bottom (blue) with the wind speed

(red) at the outer spoil ground option in September 2005. ..............................69 Figure 12.1: Sample TSS plot during dredging of the channel by the TSHD showing the

effects of anti-clockwise circulation in KGS during southeasterly winds. ........82 Figure 12.2: Sample TSS plot during dredging of the channel by the TSHD showing the

effects of clockwise circulation in KGS during northeasterly winds. ................82 Figure 12.3: Sample TSS plot during dredging of the channel by the TSHD showing the

effects of circulation in KGS during westerly winds. ........................................83 Figure 12.4: Location of the five stations where time series data were captured during

the analysis of the turbidity results. .................................................................84 Figure 12.5: TSS time series at five locations during dredging starting in March................84 Figure 12.6: TSS time series at five locations during dredging starting in July. ..................85 Figure 12.7: TSS time series at five locations during dredging starting in November. ........85 Figure 12.8: Sea grass mortality zones derived for dredging starting in March...................86 Figure 12.9: Sea grass mortality zones derived for dredging starting in July. .....................87 Figure 12.10: Sea grass mortality zones for dredging starting in November.........................87 Figure 12.11: Sediment accumulation (above 100gm/m2) at the end of the dredging

program which started in March. .....................................................................88 Figure 12.12: Sediment accumulation (above 100gm/m2) 12 months after the start of

dredging in March...........................................................................................88



Figure 12.13: Sediment accumulation (above 100gm/m2) at the end of the dredging

program which started in July..........................................................................89 Figure 12.14: Sediment accumulation (above 100gm/m2) 12 months after the start of

dredging in July. .............................................................................................89 Figure 12.15: Sediment accumulation (above 100gm/m2) at the end of the dredging

program which started in November................................................................90 Figure 12.16: Sediment accumulation (above 100gm/m2) 12 months after the start of

dredging in November. ...................................................................................90 Figure A.1: Model region showing TSS sites chosen for output in Champion Bay. ...........94 Figure A.2: Sample surface currents from GCOM3D during southerly winds....................95 Figure A.3: Sample surface currents from GCOM3D during north-easterly winds. ...........95 Figure A.4: Satellite photo of the turbid plume on October 30, 2002 .................................97 Figure A.5: Model prediction for the turbid plume on October 30, 2002 ............................97 Figure A.6: Aerial photo of the turbid plume on November 26, 2002 .................................98 Figure A.7: Model prediction for the turbid plume on November 26, 2002.........................98 Figure A.8: Aerial photo of the turbid plume on December 18, 2002 .................................99 Figure A.9: Model prediction on December 18, 2002.........................................................99

Table of Tables

Table 1: Estimate of significant wave heights Offshore and in Princess Royal Harbour....17 Table 2: GEMS ADCP and Drifting Buoy Deployment Locations and MetOcean Wave

and Meteorological stations.............................................................................21 Table 3: SWAN set-up specifications.................................................................................46 Table 4: Extract from the dredge log used to carry out the dredge modelling. ..................72 Table 5: Basic particle size distributions used in the dredge simulations ..........................75 Table 6: Analysed particle settling velocities compared with the values used in the

dredge modelling. ............................................................................................76 Table 7: The Sea grass Impact Zone Criteria Supplied by SKM........................................81 Table A.1: Comparison of Predicted (P1-8) and measured TSS values (TL1-21). ..........96



1. Introduction

Global Environmental Modelling Systems (GEMS) was contracted to carry out simulations

of the dredging impacts for the development of Albany Port for the Grange Resources

Southdown Magnatite Project. At the time this study was carried out dredging for the port

expansion in Princess Royal Harbour (PRH) and the deepening and extension of the

shipping channel in King George Sound (KGS) was expected to commence sometime in

March 2007 and continue for 4 to 5 months. The study region is shown in Figure 1.

The work has been undertaken using three sophisticated numerical computer models:

The GEMS 3D Coastal Ocean Model (GCOM3D) to simulate the complex three-

dimensional ocean currents in PRH and KGS; and

The GEMS 3D Dredge Simulation Model (DREDGE3D) to determine the fate of particles

released into the water column during the dredging operations; and

The SWAN wave model to simulate the waves in KGS and PRH during the dredging

operations for calculations of sediment re-suspension.

In addition a field program was undertaken to augment existing data and provide an

extensive database for verification of the wind, wave and ocean models.

Figure 1: Princess Royal Harbour, Oyster Harbour and King George Sound



2. Scope of Work

The Scope of Work for this study has been undertaken as follows:

2.1 Field Work

Deploy wireless GPS ocean surface drifters (Davis drifters) in PRH and KGS to map

surface current movements.

Deploy an Acoustic Doppler Current Profiler (ADCP) at three locations in KGS to measure

currents through the water column.

2.2 Model Setup

Incorporate detailed bathymetry data for PRH and KGS and establish bathymetric grids

covering PRH and KGS for the hydrodynamic, wave and dredge simulation modelling.

Extract data from the high resolution (12km) Bureau of Meteorology forecast model

(Mesoscale Limited Area Prediction System – MesoLAPS).

Analyse the MesoLAPS data for the region to choose a representative dredging period

starting in March.

Setup tidal forcing for the region from the GEMS Australian region tidal database (originally

developed for AMSA Search and Rescue in Canberra).

2.3 Verification of MesoLAPS winds, GCOM3D and SWAN in King George Sound and Princess Royal Harbour

Compare MesoLAPS wind data with observations from the anemometer installed by

MetOcean on a KGS channel pile from July 2005 to April 2006.

Run GCOM3D, driven by tides and MesoLAPS winds, for selected periods and compare

with ocean currents (ADCP and drifter data) and tides measured by MetOcean in winter

2005 and by GEMS in summer 2006.



Run the SWAN wave model, driven by MesoLAPS winds, and compare wave predictions

with observations from a wave rider buoy installed in KGS from July 2005 to April 2006.

2.4 Simulations for a Representative Dredging Period

• Establish the best estimate of the dredge simulation parameters including:

• Particle distribution curve

• Dredge(s) to be used and proposed hours of operation

• Dredge cutting rate(s)

• All potential sources of turbidity together with rate and duration

• Proposed spoil ground(s)

• Particle size distributions (PSD) encountered along the dredging path

• Establish the expected maintenance schedules and associated down times.

• Develop a detailed dredge log (sample in Table 4) to drive the dredge simulation

program

• Establish the required outcomes of dredge simulations (e.g. TSS levels and

durations, bottom sedimentation thickness, impact zone criteria)

• Run GCOM3D for the representative dredging period driven by winds and tides.

• Run the SWAN wave model for the representative dredging period driven by winds.

• Run DREDGE3D for the full representative dredging period driven by the simulated

dredge log, currents from GCOM3D and orbital velocities from SWAN.

• Analyse output from the simulation to provide data for initial impact assessment

studies.

• Derive impact zones, based on model output and exposure criteria, defining regions

of full mortality, partial mortality and exposure without mortality.



3. GEMS Background Information GEMS has expertise in the development and application of high-resolution computer

models to realistically predict atmospheric and oceanographic conditions for use in riverine,

coastal and oceanic settings. The GEMS team is made up of qualified and experienced

physical oceanographers, meteorologists, numerical modellers and environmental

scientists.

GEMS is a leading developer of numerical models in Australia. It has developed a system

of validated environmental models that provide solutions to a variety of environmental,

engineering and operational problems. Services provided include:

• Oil Spill Prediction and Risk Modelling under fully representative climatic and

oceanographic conditions;

• Real-time, on-call Oil Spill Modelling

• Dredge sediment fate modelling

• Production Formation Water and Pipeline Hydro-test discharge modelling and

related risk analysis;

• Wave/Current design criteria modelling for pipelines and off-shore and on-shore

facilities;

• Comprehensive tropical cyclone modelling, including winds, waves, currents and

storm surge;

• Provision of accurate tidal prediction based on extensive 2D and 3D

hydrodynamic ocean modelling.

Through it links with Australia’s premier research institution, the Commonwealth Scientific

and Industrial Research Organization (CSIRO), GEMS now includes satellite derived ocean

elevation and large-scale ocean current data into its modelling suite. This state-of-the-art

approach allows more accurate representation of ocean currents to be included in all ocean

discharge applications. The methodology was applied successfully as part of a

comprehensive Environmental Impact Assessment for the Woodside Enfield Project (and

more recently for the BHP Stybarrow and Pyrenees studies) near the Ningaloo Marine

Park.



4. Climate and Meteorology

The planned operation is to occur during a period (March-June) in which there is marked

change in the predominating synoptic pattern.

At the beginning of the period, in March, the mean position of the sub-tropical ridge is near

its most southern extent in the annual cycle. This ridge of high-pressure routinely directs

easterly quarter winds over the southwest corner of the continent. The pressure gradient

during this period generally shifts more northeasterly on the eastern flank of transitory

eastward propagating heat troughs and then shifts southwards after the passage of the

trough. Usually, a rapidly reforming high will then cause a burst of stronger south-easterlies

following trough passage.

By April, the cooling continent causes the sub-tropical ridge to migrate northwards and the

southwest corner becomes increasingly affected by mid-latitude westerly flow into the

winter months. This increasingly subjects the region to passing frontal and low-pressure

systems; high pressure may still develop over ocean latitudes but tends to be much more

transitory in nature.

Figures 4.1 and Figures 4.2 show examples of the typical evolution of the synoptic pattern

for March and June respectively.



Figure 4.1: Typical synoptic evolution during March.



Figure 4.2: Typical synoptic evolution during June



5 Oceanography

5.1 Circulation The Albany Port is situated in PRH, a marine embayment of surface area 28.7 km2, the

predominant depth being about two metres, with a narrow opening to KGS.

The dominant influence on the circulation in the waters of KGS and PRH is the local wind.

Tides are relatively weak at Albany and vary from diurnal to semi-diurnal throughout the

year with a spring tidal range of approximately 1.1 metres. Water levels are also influenced

by the weather systems, with wind driven setup resulting from sustained winds in KGS

readily transmitted into PRH. The water-level ranges within and outside the harbour are

virtually identical (EPA, 1990).

Modelling of wind driven circulation of water in Princess Royal Harbour (Mills and Brady,

1985) showed that west to north-west winds in Winter generate predominantly anti-

clockwise circulation whereas east to south-east winds in Summer generate predominantly

clockwise circulation. Investigations into water circulation and flushing characteristics of the

Harbour (Mills and D’ Adamo, 1993) also found that up to 30 million m3 of water may enter

or leave the Harbour within 8 hrs of rising tides and 16 hrs of falling tides. The water

movement passing through the entrance channel of the Harbour mouth was found to

accelerate to current speeds of up to 0.5m/sec.

The above findings have been supported by the observations and modelling carried out

during this study and further findings have emerged regarding the circulation in King

George Sound, namely:

• During summer, winds from the south to south-east sector generate a

predominantly anti-clockwise circulation in KGS;

• During summer, winds from the east to north-east sector generate a predominantly

clockwise circulation in KGS;

• During summer, when winds are from the south-east to north-east sector, the

surface flow in the centre of KGS is generally towards the west but the bottom flow

is generally in the opposite direction;

• During winter sustained strong westerly winds generate what appears to be a shelf

wave along the continental shelf outside KGS resulting in current speeds over 1

knot at depths of 40 metres. The amplitude of the bottom current in these situations

correlates well with the wind speed and the phase of the bottom current variations

often leads the phase of the wind.



5.2 Waves

The broad high latitude westerly flow over Southern and Indian Oceans produces a highly

energetic wave climate at the southwest corner of the continent. However, the

southeasterly to easterly aspect of KGS provides a significant level of protection to these

waves.

While there can be sustained easterly wind flow (see Section 7) in the region, more

particularly in the warmer months, these winds are generally not spatially extensive so that

the resulting waves are less energetic, and at higher frequency.

Occasionally, however, the synoptic pattern may be favourable for the development of

higher energy southeast waves. Typically, these events occur with the development of a

high-pressure system at higher latitudes; such a system may be accompanied by a slow-

moving depression, cut-off from the prevailing westerly flow in the region of the Great

Australian Bight. Strong pressure gradients ‘squeezed’ between such coupled systems

are ideal for generating large southeast waves that propagate towards the study region.

5.2.1 Extreme Wave Analysis

An assessment of the offshore wave climate at Albany was undertaken for Berth No’s 5 and

6 Development, by Lawson and Treloar in 1999. The resulting estimates of significant

wave heights for severe storms offshore and at the entrance to Princess Royal Harbour are

as shown in Table 1.

Table 1: Estimate of significant wave heights Offshore and in Princess Royal Harbour

Recurrence Interval Significant Wave Height (m)

Offshore Entrance to Princess Royal

Harbour

100 years ARI 10.5 m 1.7 m

50 years ARI 9.8 m 1.5 m



5.2.2 Waves Employed in the Current Study

The primary aim of wave modelling undertaken for the study was to quantify spatial and

time varying wave-induced (bottom) orbital velocities for incorporation into the re-

suspension module of the sediment model.

Although detailed observational wave data have been collected from the study region (see

below), these data are limited because they location specific and because they represent a

small window relative to the overall wave climate.

In order to represent the wave climate for the planned period of operation of the dredger, a

comprehensive wave model (SWAN) has been established. Wave validation studies have

been carried out to assess the accuracy of this model against data collected during the

wave monitoring period. These are discussed in detail in Section 5.2 along with the details

of the model setup and outcomes of the modelling program.



6. Field Work

In order to produce reliable predictions of the fate of turbid plumes during the dredging it is

critical to have accurate predictions of the ocean currents and tides in PRH and KGS. A

field program measuring winds, waves and currents was undertaken from July to October

2005 by MetOcean. The results of this program were very useful but did not provide

sufficient information to determine the circulation in KGS and given that the dredging

program would start around March 2007 it was decided to pursue further current

measurements in the summer and autumn of 2006.

These field measurements involved:

• The deployment of an Acoustic Doppler Current Profiler (ADCP) at three sites in

KGS by GEMS for approximately 1 month at each location,

• The deployment of five wireless tracked GPS drifting buoys (Davis drifters) for 5

days in PRH and KGS.

6.1 ADCP Deployments

The locations of the fixed point data used for verification in this study are defined in Table 2

and marked in Figure 6.2. The GEMS ADCP mooring components are shown

schematically in the mooring design in Figure 6.1.

Figure 6.1: ADCP Mooring configuration

Buoy

Large small

Current

40m

10m



The ADCP deployed by GEMS was from RDI Instruments in the USA and was calibrated

and supplied by their agent in Australia (Underwater Video Systems).

The workboat, diving and logistics support for the mooring deployments, was provided by

the Albany Port Authority.

6.2 Drifting Buoy Deployments GEMS developed the wireless tracked GPS drifting buoys (known as Davis drifters)

specifically for lagrangian drifter experiments to help map ocean surface currents (see

figures 6.3 and 6.4). A wireless receiver on the deck of the boat, or mounted on a shore

station, can then receive the location of each of the drifters from the onboard GPS. The

Davis drifters are subject to very low windage due to their design (particularly the

underwater “sail”).

The release points for the wireless GPS Davis drifters are defined in Table 1 and the tracks

are shown in Figure 6.5.

Figure 6.2: Location of observation stations used for fixed point verification of winds

(MET), waves (WR) and currents (ADCP and CM).



Table 2: GEMS ADCP and Drifting Buoy Deployment Locations and MetOcean Wave and Meteorological stations

Instrument Deployment Latitude

Deployment Longitude

Deployment Time (UTC+8.0)

Retrieval Time (UTC+8.0)

Wave Buoy -35.055560 118.009500 20050403 20060412

Met Station -35.035833 117.930550 20050726 20060412

ADCP 4 -35.080000 118.000000 20060121 0900 20060212 0800

ADCP 5 -35.025517 117.942050 20060212 1100 20060312 1500

ADCP 6 -35.049850 117.982230 20060312 1600 20060429 0900

Drifter 1 -35.036855 117.882287 20060122 1735 20060123 0940

Drifter 2 -35.030653 117.947958 20060122 1130 20060123 1805

Drifter 3 -35.038082 117.961147 20060122 1125 20060123 1800

Drifter 4 -35.045942 117.886460 20060122 1745 20060123 1815

Drifter 5 -35.051268 117.978190 20060122 1115 20060123 1750

Drifter 6 -35.028040 117.931895 20060124 1140 20060124 0700

Drifter 7 -35.045802 117.950423 20060124 1155 20060125 1400

Drifter 8 -35.049082 117.983902 20060124 1215 20060125 1420

Drifter 9 -35.069248 117.962037 20060124 1250 20060125 1430

Drifter 10 -35.080390 117.986772 20060124 1235 20060125 1510



Figure 6.3: Wireless GPS Davis drifter prior to deployment in King George Sound.

Figure 6.4: Wireless GPS Davis drifter in King George Sound.



Figure 6.5: The 10 wireless GPS Davis drifter tracks.



7. Meteorological Forcing

Accurate modelling of the currents in any region, and throughout King George Sound in

particular, can only be achieved with a suitable representative wind data set.

In this section, the wind data set employed for the modelling is described, together with an

analysis that demonstrates the suitability of employing winds from the year 2005 to initialize

both the 3D ocean model and wave model.

The focus of this analysis is on the expected dredging period – from March to June

inclusive.

7.1 Method

7.1.1 Data Sources

Albany Airport The Bureau of Meteorology holds data for its site at Albany Airport. Half hourly reports from

the Automatic Weather Station (AWS) at this site date back to 1993. Since this site is some

10km inland, it is well recognized that winds from this location are unlikely to represent the

wind regime over King George Sound. This is particularly the case in view of the strong

influence of local topography in the region; differences in terrestrial and marine wind

behaviour also result from diurnal variability. However, the length of the data-set may be

used as an aid to analysis of inter-annual trends in the broader wind climate of the region.

MesoLAPS The Bureau of Meteorology also routinely operates a suite of Numerical Weather Prediction

(NWP) models at a range of spatial and temporal resolutions. These models are nested in

space so that the model system captures a range of atmospheric scales ranging from

global through regional (continental) to the local, or mesoscale.

The Bureau has operated its mesoscale model at a spatial resolution of about 10km for a

period of more than five years. Wind data from the analysis cycle of this model are routinely

archived and, for the current study, have been extracted for the period January 2000 to

May 2006. Validation of the accuracy of the data, specific to the current study area, is

discussed in the next section of this report; however, GEMS has determined from previous

studies that the model data provides good representation of coastal wind regimes.

It is acknowledged that, at the available resolution, the MesoLAPS wind data cannot

capture very localized topographic effects; however, such small impacts have been found

to have little impact on current flows within King George Sound which are controlled by

wind flow over the ocean at scales of tens of kilometers.



7.2 Analysis and Verification

7.2.1 MesoLAPS Validation

An Automatic Weather Station (AWS) installed on Beacon 4 at the entrance to King George

Sound (see Figure 9.2) commenced gathering data in July 2005. Data included in the wind

analysis included the period from commencement in 2005 through to mid April 2006.

Figures 7.1 and 7.2 respectively show plots of wind direction and wind speed from the AWS

(10 minute mean) overlaid with MesoLAPS output for the commensurate period. The first

plot in each shows the full period of analysis and the second two plots show higher

temporal resolution, randomly selected periods.

At times the peak wind speeds from MesoLAPS are slightly weaker than those measured

by the AWS but in general the strong correlation between the observed and modelled winds

demonstrates that mesoLAPs winds provide excellent representation of the maritime wind

regime in the Albany region.

When interpreting Figures 7.1 and 7.2 it should be noted that:

a) The raw data was not filtered and therefore wind gusts make it “noisier” than the

model data.

b) If the peak winds are in fact slightly weaker then the impact on dredge plume

modelling will be conservative as the currents will be slightly weaker and dispersion of

plumes will be reduced.

c) The use of the MesoLAPS winds has provided a big step forward in the accuracy of

offshore winds from the relatively recent necessity to use single station data to drive ocean

models. Verification of MesoLAPS winds across a large number of projects has shown a

much improved representation of offshore winds than was originally possible.

7.2.2 Analysis of Wind Records

Speed-Direction Frequency Analysis

Polar wind diagrams were constructed on a monthly basis (for the proposed operations

period) for both MesoLAPS [Figure 7.3(a)] and airport [Figure 7.3(b)] data sets

The two sets of diagrams show general similarity in relation to the distribution of wind

direction with a shift from easterly to westerly predominance during the period of interest.

As expected, the offshore (mesoblast) diagrams show more energetic (ie. stronger winds)



relative to the airport diagrams. The lighter winds at the airport reflect greater topographic

and frictional shielding as well as much more marked diurnal variation. However, the

general similarity provides increased confidence that the mesoblast data set is of sufficient

duration to captures the general inter-annual variation of the wind climate operating over

the region.

The polar diagrams also clearly demonstrate the shift from predominant easterly quadrant

to westerly quadrant winds over the course of the proposed modelling period.

Light and Energetic Conditions An analysis was also undertaken to specifically investigate the variability of wind strength

for both light and energetic conditions, specified as below 2.5 m/s and above 7.5 m/s

respectively. This analysis was carried out for both the airport and MesoLAPS winds, with

the results for MesoLAPS reported here.

The results for the energetic analysis are shown in the Figure 7.4(a) and for the light winds,

in Figure 7.4(b). In each case the frequency of the specified condition is provided on a

monthly basis. An expected general negative correlation between the light and energetic

conditions is evident in the diagrams. This analysis provides an excellent basis for

selecting either typical or biased years.

Selection of a Period of Representative Winds As well as demonstrating the accuracy of the wind data set used for initialising the

oceanographic models, a primary aim of the wind analysis was to select a period that

provides representation of the winds that may be expected to occur during the operations

period.

Since no one year will exactly represent other years, the selected year should be biased

towards those conditions that would tend to increase general turbidity levels. After analysis

of the data, the year 2005 was chosen because of a tendency towards more easterly winds

which would be expected to produce higher turbidity levels in PRH and KGS.

To demonstrate this Figure 7.5, which contains polar diagrams for the March-June period

over all years (2000-2005) and for Year 2005 only, shows that 2005 has a typical

directional distribution, but with a slight easterly bias.



Figure 7.1: Time series of wind direcions during validation period.

0

60

120

180

240

300

360

17/07/2005 5/09/2005 25/10/2005 14/12/2005 2/02/2006 24/03/2006

Dire

ctio

n (d

eg)

AWS MesoLAPS

0

60

120

180

240

300

360

25/10/2005 4/11/2005 14/11/2005 24/11/2005 4/12/2005 14/12/2005 24/12/2005 3/01/2006 13/01/2006 23/01/2006 2/02/2006

Dire

ctio

n (d

eg)

AWS MesoLAPS

0

60

120

180

240

300

360

14/12/2005 19/12/2005 24/12/2005 29/12/2005 3/01/2006 8/01/2006 13/01/2006 18/01/2006 23/01/2006 28/01/2006 2/02/2006

Dire

ctio

n (d

eg)

AWS MesoLAPS



Figure 7.2: Time series of wind speed during validation period.

0

5

10

15

20

25/10/2005 4/11/2005 14/11/2005 24/11/2005 4/12/2005 14/12/2005 24/12/2005 3/01/2006 13/01/2006 23/01/2006 2/02/2006

Spe

ed (m

/s)

AWS MesoLAPS

0

5

10

15

20

14/12/2005 19/12/2005 24/12/2005 29/12/2005 3/01/2006 8/01/2006 13/01/2006 18/01/2006 23/01/2006 28/01/2006 2/02/2006

Spee

d (m

/s)

AWS MesoLAPS

0

5

10

15

20

14/12/2005 19/12/2005 24/12/2005 29/12/2005 3/01/2006 8/01/2006 13/01/2006 18/01/2006 23/01/2006 28/01/2006 2/02/2006

Spee

d (m

/s)

AWS MesoLAPS

0

5

10

15

20

17/07/2005 5/09/2005 25/10/2005 14/12/2005 2/02/2006 24/03/2006

Spe

ed (m

/s)

AWS MesoLAPS



Figure 7.3(a): Monthly wind roses based on Albany airport data.

Figure 7.3(b): Monthly wind roses based on Mesolaps airport data.



Figure 7.4(a): Energetic wind frequency analysis.

Figure 7.4(b): Light wind frequency analysis.

0

5

10

15

20

25

30

35

40

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Ene

rget

ic (%

>7.5

m/s

)MarchAprilMayJune

0

10

20

30

40

50

60

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Ligh

t Fre

quen

cy (%

< 2

.5 m

/s) March

AprilMayJune



Figure 7.5: Polar wind diagrams based on MesoLAPS for the period March-June for all

years (left) and 2005 (right).



8. Ocean Circulation Simulation

8.1 Method

8.1.1 Bathymetry

The bathymetric data sets held by GEMS were updated with bathymetry provided by JFA.

The GEMS database has been developed from a range of sources including data from

Geoscience Australia (formerly AUSLIG) and oil company surveys.

8.1.2 Tides

Tidal forcing was based on data from the GEMS Australian region gridded tidal data base,

which has been developed with extensive modelling programmes (primarily for AMSA

Search and Rescue in Canberra).

8.2 Verification

The ocean circulation data measurement program designed by GEMS was specifically

focussed on understanding the circulation in KGS and in PRH. Accordingly vertical profiles

of currents were obtained in southern, northern and central KGS to provide information on

clockwise and anticlockwise flows (north and south moorings) under different wind regimes

and on return flows at depth. These data were augmented by the mapping of the surface

circulation with GPS drifters.

To verify GCOM3D, and to provide 3D currents for the dredge plume modelling, a

bathymetric grid covering the region in Figure 8.1 was set up at 50 metre resolution. The

vertical levels were at 2, 4,7, 10, 14, 20, 30, 40 metres etc.

Tidal data for the model boundaries was extracted from the GEMS database and

MesoLAPS winds from the Bureau of Meteorology were used to force the model.

GCOM3D was run for the period of summer/autumn field measurements (Jan 21, 2006 to

April 28, 2006) producing half-hourly currents at between 5 and 15 levels in the water

column (depending on the depth).



Figure 8.2 shows an example of the ebb tide in KGS during and Figure 8.3 shows an

example of the flood tide in KGS during relatively weak winds. Figures 8.4 to 8.11 show the

agreement obtained between GCOM3D predictions of current speed and direction and the

observed near-surface and near-bed current data from the ADCP deployments in southern

and northern KGS respectively.

Figures 8.12 to 8.17 show a comparison of the near-surface and near-bottom current

speeds and direction measured at the three ADCP locations. These figures show that the

currents near the bottom are significantly weaker than at the surface and that, whilst the

currents north of the shipping channel are generally in the same direction throughout the

water column (Figures 8.14 and 8.15), the currents in the southern half of KGS generally

show a weak return flow at the bottom when the surface currents are being driven into KGS

by strong winds. The comparison shown in Figures 8.4 to 8.11 shows that GCOM3D

captures these features reasonably well.

Figures 8.18 and 8.19 show the comparison of drift tracks predicted from GCOM3D

currents with the measured drift tracks in KGS and PRH. Apart from the very good

agreement between model predictions and observations the major finding was that the

tracks in Figure 8.18, which were released during a predominantly south to southeasterly

wind regime, show a generally anticlockwise circulation in KGS. The tracks in Figure 8.19

however, which were released during a predominantly east to northeasterly wind regime,

show a generally clockwise circulation in KGS.

The fact that GCOM3D captures this mechanism was very encouraging for the dredge

plume predictions.

The important issue with ocean modelling is that the model used can be shown to represent

the basic oceanographic features reliably and with an acceptable level of accuracy. The

agreement between model predictions and observations in this study appears to satisfy

these requirements very well.

In Figure 8.4 the peak current speeds predicted by GCOM3D are slightly below measured

peak speeds but of course the slightly slower current speeds would reduce plume

dispersion and tend to make results conservative. This difference may be related to the

slightly weaker winds noted earlier.



The drifter data has illustrated the response of the surface circulation in KGS to varying

wind directions during summer and the ADCP data has shown the existence of a bottom

return flow, albeit rather weak, during surface flows into KGS.

GCOM3D has been shown to represent these features with a high level of accuracy.

Figure 8.1: Region over which 3D ocean currents were simulated with GCOM3D.



Figure 8.2: Example of the ebb tide in KGS and PRH predicted by GCOM3D.

Figure 8.3: Example of the flood tide in KGS and PRH predicted by GCOM3D.



Figure 8.4: Comparison of near-surface current speeds measured at ADCP4 from

January 21 to February 12, 2006 (blue) with GCOM3D predictions (red).

Figure 8.5: Comparison of near-surface current directions measured at ADCP4 from

January 21 to February 12, 2006 (blue) with GCOM3D predictions (red).



Figure 8.6: Comparison of near-surface current speeds measured at ADCP5 from

February 12 to March 12 (blue) with GCOM3D predictions (red).

Figure 8.7: Comparison of near-surface current directions measured at ADCP5 from

February 12 to March 12, 2006 (blue) with GCOM3D predictions (red).



Figure 8.8: Comparison of near-bed current speeds measured at ADCP4 from January 21

to February 12, 2006 (blue) with GCOM3D predictions (red).

Figure 8.9: Comparison of near-bed current directions measured at ADCP4 from January

21 to February 12, 2006 (blue) with GCOM3D predictions (red).



Figure 8.10: Comparison of near-bed current speeds measured at ADCP5 from February

12 to March 12 (blue) with GCOM3D predictions (red).

Figure 8.11: Comparison of near-bed current directions measured at ADCP5 from

February 12 to March 12, 2006 (blue) with GCOM3D predictions (red).




measured at ADCP6 from March 12 to April 29, 2006.

Figure 8.13: Comparison of near-surface (blue) and near-bottom (red) current directions




Figure 8.18: Comparison of the first 5 GPS drifter tracks with the tracks predicted from

GCOM3D near-surface currents (marked with M).

Figure 8.19: Comparison of the second 5 GPS drifter tracks with the tracks predicted from

GCOM3D near-surface currents (marked with M).



9 Wave Simulation

9.1 Method

9.1.1 The Wave Model

The SWAN model (see Appendix B.2) has been established in order to estimate the spatial

and temporal variation of wave induced bottom currents over the course of the period of

modelling.

Wave Grids and Winds In order to capture broad scale wave generation processes affecting the region, a grid was

established over the southern ocean a resolution of approximately one degree. Inner grids

were then established at 10km and 200m resolution, in order to model the more detailed

near-shore processes. The grid domains are shown in Figure 9.1. Bathymetry of the inner

grid reflects that shown in Figure 1.1.

The model was initialized with archived winds from the Bureau of Meteorology’s numerical

weather prediction analysis fields. For the broad scale wave modelling, the LAPS fields

(resolution approximately 40km) were employed.

SWAN Setup SWAN allows for a range of parameter settings, some of which may be tuned to the

particular application. The settings used to obtain the best verification results in the study

are set out in Table 3. Of these, the verification results were most sensitive to the

directional resolution and the friction scheme employed for the high resolution, inner grid.

9.2 Verification

9.2.1 Observational Data

The most complete set of observational data was available from the winter 2005 measurements form the

MetOcean deployments which included two AWACs and the wave rider buoy (see Figure 9.2). Since

the primary focus of the modelling was on the wave climate and impacts on sediment re-suspension in

King George Sound, the wave validation focused particularly on the AWAC-1 and wave rider buoy

(WRB) sites. Furthermore, modelling the propagation of waves into PRH was not attempted due to the

complexity of the problem with the narrow entrance channel.



9.2.2 Results

General Wave Climate - Height and Direction The period of validation coincides with the wave data acquisition period from July to

September 2005; this period included several energetic wave episodes and also coincides

with one of the dredging simulation periods.

Figure 9.3(a) shows time series of the modelled significant wave heights and directions at

output locations corresponding to the positions of AWAC-1, ADCP-3 and WRB. Figure

9.3(b) shows modelled directions for the concurrent period at WRB. Although there are no

observational wave data at ADCP-3, it is key location with respect to disposal site re-

suspension; the location is also a good indication of the open ocean wave conditions.

Figure 9.4, which was constructed for a (randomly selected) energetic episode, clearly

shows how wave energy is typically attenuated within KGS due to depth and directional

shielding effects.

As previously discussed, the most significant inshore wave episodes are expected to

correspond with southeasterly (from) wave directions. The results of the modelling program

confirm this assumption.

Validation The model generated wave heights were compared with the observed heights from the

wave rider buoy (WRB) and AWAC-1 sites – see Figure 9.5. In general, the agreement

between the model wave heights and observations are very good. The more energetic

events, such as those observed in early July and late August, are well represented.

Wave height increases inside King George Sound are highly dependent on the wave

direction. Since model directional resolution was set at 20 degrees, small directional error

in the model can result in more or less energy being allowed into the model representation

of the Sound. The significant event in early September is picked up by the model, but wave

heights inside the harbour are a little under-estimated.

In general, the results of the validation show that the energetic and spatial variations of the

waves across King George Sound are suitably captured and can be used to quantify wave

generated re-suspension.

Bottom (Orbital) Velocities The model produces time varying output of the bottom orbital velocity maxima at each

output time step. The spatial variation of bottom velocities is shown for a sample output

time step during a high wave period in late August (Figure 9.6). The bottom maxima are a



function of the wave height, wave period and the depth – the larger waves in shallower

water will result in higher orbital velocities (and therefore greater contribution to re-

suspension of sediments). The example shows that highest orbital velocities are generally

occurring in the shallower regions.

Figure 9.7 shows a time series of orbital velocities over the July-August period for the three

observation sites. Although these cannot be directly validated, the fact that model is well-

validated for wave height suggests that the variability of bottom velocities should also be

well represented.

Figure 9.7 shows how wave height and depth variation impacts wave induced bottom

velocities. Generally the larger waves are at the southern most site (ADCP-3), compared

to the inshore, but in certain circumstances where the directions and periods are suitable,

the inshore wave heights are comparable and the shallower depths result in higher bottom

velocities.

Table 3: SWAN set-up specifications.

Model Grid Ocean Regional Local

Minimum Latitude -72.0 -38.0 -35.2

Maximum Latitude -25.0 -33.0 -35.0

Minimum Longitude 70.0 114.0 117.8

Maximum Longitude 178.0 121.0 -35.0

Grid Resolution (deg) 1.0 0.1 0.002

Directional resolution 20 20 20

Frequency Range (Bins) 0.04 – 1 (20) 0.04 - 1(20) 0.04 - 1(20)

Friction Scheme None Collins Collins



Figure 9.1: Wave model grid regions



Figure 9.2: Location of MetOcean winter moorings

.



Figure 9.3(a): Modelled wave heights at three locations AWAC-1(red), WRB (green)

and ADCP-3 (blue).

Figure 9.3(b): Modelled wave directions at WRB.

0.0

60.0

120.0

180.0

240.0

300.0

360.0

1-Jul 7-Jul 13-Jul 19-Jul 25-Jul 31-Jul 6-Aug 12-Aug 18-Aug 24-Aug 30-Aug 5-Sep 11-Sep 17-Sep 23-Sep 29-Sep

Wav

e D

irect

ion

(deg

)



Figure 9.4: Wave height attenuation through KGS.



Figure 9.5(a): SWAN model (green) versus observed (red) wave heights at WRB.

Figure 9.5(b): SWAN model (green) versus observed (red) wave heights at AWAC-1.

0.0

1.0

2.0

3.0

4.0


Hs

(m)

0.0

1.0

2.0

3.0

4.0


Hs

(m)



Figure 9.6: Typical spatial variability of wave induced bottom velocities.

Figure 9.7: Time series of wave induced bottom velocities at AWAC-1 (red), WRB (green)

and ADCP-3 (blue).

0.0

0.2

0.4

0.6

0.8

2-Aug 8-Aug 14-Aug 20-Aug 26-Aug 1-Sep 7-Sep 13-Sep 19-Sep 25-Sep 1-Oct

Um

ax (m

/s)



10. Dredge Modelling

10.1 Method Once the physical oceanography has been simulated it is possible to study the movement

of discharges into the water column (e.g. sediments, chemicals etc.) or components of the

water body itself (flushing rates of harbours, bays etc.).

The GEMS 3D Dredge Simulation Model (DREDGE3D) is used for simulating the specific

fate of particles discharged during a dredging program. This model inputs the physical

environmental data from GCOM3D, together with wave data from SWAN and

meteorological data, to simulate the movement and deposition, of suspended particles in

the water body across the study area.

DREDGE3D is a lagrangian particle model and therefore is independent of grids and grid

resolutions. More details on the processes and methodology simulated in DREDGE3D is

given in Appendix B.3.

DREDGE3D was used with great success in the Geraldton Port Redevelopment Project

where it was compared with in-situ data, aerial photographs and satellite images.

In the past 3 years since the dredging of Geraldton Port, DREDGE3D has been used in

Mermaid Sound for both the Dampier Port Authority and the Hammersley Iron port

expansion projects, Chevron Gorgon dredging at Barrow Island, two projects in

Queensland, several developments in the United Arab Emirates and in New Caledonia for

the INCO nickel processing plant and port development.

10.2 Verification

The best verification of DREDGE3D available so far was carried out during the Geraldton

Port dredging program. The results are described in Appendix A.

Whilst the Geraldton comparisons provide some important feedback about the accuracy of

DREDGE3D the data was very limited. It is very important to obtain detailed data on TSS

throughout the dredging program to enable much more detailed verification and testing of

the processes simulated in DREDGE3D. It is hoped that these data will be obtained during

this project for comparison with model predictions.



11. Oceanographic Issues

There have been a number of possible oceanographic impacts of the dredging raised which

need to be considered. In particular, there are two potential issues, which can be

commented on from the modelling work carried out in this study.

11.1 The Effects of Changes to the Entrance to Princess Royal Harbour A significant question for this study therefore is whether the changes to the port

(reclamation and channel deepening) near the entrance to PRH will affect the exchange of

waters between PRH and KGS. The answer is almost certainly yes as the cross-sectional

area of the entrance to PRH is calculated to change from approximately 4,300 m3 to

approximately 5,700 m3 (see Figures 11.1 and 11.2).

11.1.1 Hydrodynamic Studies

The exchange process between PRH and KGS through the existing entrance channel has

been studied previously by Mills and D’Adamo (1993) with a 2 dimensional hydrodynamic

modelling study on a 100 metre grid. In this study the authors conclude that the dominant

mechanisms governing water exchange between PRH and KGS are the wind driven

circulation and asymmetric momentum-driven tidal jets. The modelling work was actually

undertaken in the 1980’s and, as such, was very much state-of-the-science at the time.

The speed of computers twenty years ago limited the resolution at which studies like this

could be carried out and so the 100 metre grid spacing and using a 2D model instead of a

3D model would have been necessary due to the limitations of computational speed. The

limitation of the grid spacing is that the entrance to Princess Royal harbour is less than 200

metres wide at its narrowest point and so there would have been only one water point in the

grid representation of the channel.

Separate studies by CSIRO (McInnes and Hubbert, 1999) have shown that at least five grid

points are required across a channel to represent the flow with any degree of accuracy, and

that seven grid points are preferable. This latter work was carried out during a

hydrodynamic modelling study of the Nerang River at the Gold Coast in Queensland.



The increase in computational speed, and advances in hydrodynamic modelling

techniques, now allow much higher resolution studies to be undertaken in three

dimensions.

In this study, the effects of increasing the cross-sectional area of the entrance to PRH have

been investigated with a high resolution 3D hydrodynamic model setup to cover PRH, the

entrance channel and the western part of KGS. The model grid resolution was 20 metres

to satisfy the need for at least seven grid points across the entrance channel. The

bathymetry before the dredging is shown in Figure 11.3 and the bathymetry after

completion of dredging is shown in Figure 11.4.

The high resolution model was run over the region shown in Figure 11.5 for 15 days from

July 1 to July 15, 2005 (a full spring - neap tidal cycle) on each of the bathymetric grids

(before and after dredging) to detect any changes in sea levels or currents. The horizontal

resolution was 20 metres and the vertical levels were set at 2, 4,7, 10, 14, 20, 30, 40, etc.

The wind speed and direction derived from the BoM MesoLAPS model for the 15 days are

shown in Figures 11.6 and 11.7 where it can be seen that both easterly and westerly winds

and a range of wind speeds were sampled.

To quantify any changes three monitoring stations were established inside PRH, in the

entrance and outside PRH as shown in Figure 11.5.

The sea levels for the pre- and post-dredging cases, for the spring-neap tidal cycle (15

days), are compared in Figures 11.8, 11.9 and 11.10. These Figures show no changes in

sea level due to the dredging; a result which is not surprising since the tidal water levels in

both PRH and KGS are presently almost exactly the same.

Figures 11.11 – 11.13 compare the current speeds at the three monitoring stations before

and after the dredging for the same 15 day period.

Figure 11.11 shows no change in the current speeds inside PRH whilst Figure 11.12

shows a small decrease in the current speeds through the entrance. This result is

consistent with the fact that the dredging is increasing the cross-sectional area of the

entrance to PRH and so the currents must reduce in speed slightly to maintain a similar flux

to the conditions before dredging.



Figure 11.13 shows only very small differences in the flow outside PRH, probably due to

the deeper channel.

Figures 11.14 – 11.16 compare the current directions at the three monitoring stations

before and after the dredging for the same 15 day period and show only minor variations in

current directions.

11.1.2 Numerical “Dye” Tracing Studies

A further investigation of the impacts of changes to the entrance channel to PRH was

undertaken through a numerical “dye” tracing study. The 15 days of 3D currents simulated

for the pre- and post-dredging cases were used to drive a model “dye” study where the

numerical equivalent of a neutrally buoyant dye was released throughout the water column

at a strategic location inside PRH channel entrance (see Figure 11.17). The advection and

dispersion of the numerical “dye” was simulated with the GEMS 3D Plume dispersion

model (PLUME3D).

Sample plots of the “dye” trace for the pre- and post-dredging cases after 5 days are shown

in Figures 11.17 and 11.18. In these plots existence of dye at any level in the water column

is shown.

These figures show a minimal difference between the two cases with the dye spreading

slightly more in the post-dredging case, further supporting the belief that the water

exchange between PRH and KGS will be slightly greater after dredging.

After the 15 day simulation, 77% of the dye had left PRH in the post-dredging case

compared with 72% in the pre-dredging case.



11.1.3 Conclusions from the Hydrodynamic and Numerical “Dye” Tracing Studies

The major conclusions to be drawn from these studies and our understanding of the

oceanography of PRH and KGS are:

• the mass flux through the entrance to PRH due to tidal forces does not change

significantly since the tidal levels are the same in KGS as in PRH;

• the numerical “dye” tracing studies suggest a slightly increased exchange of waters

between PRH and KGS, which will slightly improve flushing but have no impact on

sea levels;

• the exchange of waters between PRH and KGS is not just a two-dimensional

process (i.e. water is not always exchanged as an integrated mass), particularly for

flow produced by winds and not tides;

• Particularly during sustained easterly wind events (northeast to southeast) the

surface waters may flow into PRH but there will be a balancing bottom flow out of

PRH, in the same manner as has been described for KGS during these wind

events.

Figure 11.1: Plan view of the proposed channel dredging and reclamation in the wharf and harbour entrance area.



Figure 11.2: Cross section view of the proposed channel dredging and reclamation in the wharf and harbour entrance area.



Figure 11.3: Representation of Princess Royal Harbour Entrance before dredging showing

the model monitoring points inside and outside PRH and in the entrance (X).

Figure 11.4: Representation of Princess Royal Harbour Entrance after dredging.



Figure 11.5: The high resolution model study region showing the monitoring points in the

channel and in side and outside PRH.



Figure 11.6: Wind speed in KGS during the 15 days modelled.

Figure 11.7: Wind directions (to) in KGS during the 15 days modelled, showing a variation

from westerlies to north easterlies and back to westerlies.



Figure 11.8: Sea levels in Princess Royal Harbour before and after dredging.

Figure 11.9: Sea levels in the Harbour Entrance before and after dredging.

Figure 11.10: Sea levels in the shipping channel before and after dredging.



Figure 11.11: Current speeds in Princess Royal Harbour before and after dredging.

Figure 11.12: Current speeds in the Harbour Entrance before and after dredging.

Figure 11.13: Current speeds in the shipping channel before and after dredging.



Figure 11.14: Current directions in Princess Royal Harbour before and after dredging.

Figure 11.15: Current directions in the Harbour Entrance before and after dredging.

Figure 11.16: Current directions in the shipping channel before and after dredging.



Figure 11.17: Numerical “dye” trace 5 days after release from site labelled PRH1 forced by

currents through the channel before dredging is started.

Figure 11.18: Numerical “dye” trace 5 days after release from site labelled PRH1 forced by

currents through the channel after dredging is completed.



11.2 Waves along the Channel The second issue which can be commented on is the question as to whether the deepening

of the channel in KGS will allow larger waves to penetrate to places such as Middleton

Beach and therefore change the ambient coastal processes.

To test this a wave modelling exercise was carried out with a very high resolution setup of

the SWAN wave model on the pre- and post-construction channel depths. Analysis of the

results of the two wave model runs showed no effect of the channel deepening in KGS and,

in particular, the wave heights off Middleton Beach were unchanged.

11.3 Spoil Ground Location

Originally two spoil ground locations were considered (Figure 11.19) and during the field

program undertaken by MetOcean from July to October 2005 current measurements were

taken at each site to investigate spoil ground stability.

The results at the outer spoil ground were rather surprising as illustrated in Figure 11.20

which shows near bottom current speeds with a similar magnitude to the near surface current

speeds. Moreover the near bottom current speeds reached maxima of approximately 1.5

knots (0.75 m/s). Current speeds of this magnitude at a depth of 36 metres are very unusual

and initially it was thought that the data must be in error. After meeting with MetOcean, who

reanalysed the particular ADCP, it was concluded that these current speeds were real. This

conclusion was further supported by anecdotal evidence from fishermen and divers in Albany

who also reported strong bottom currents in that region.

After plotting the wind speed against the near bottom current speed (Figure 11.21) it became

clear that the cause of the strong bottom currents must be shelf waves generated by the

strong westerly wind conditions during the winter months.

These results indicated that the outer spoil ground location would not be stable and so this

option was not considered any further.



Figure 11.19: Location of the two spoil ground options.



Figure 11.20: Comparison of current speeds near the surface (blue) and near the bottom

(red) at the outer spoil ground option in September 2005.

Figure 11.21: Comparison of current speeds near the bottom (blue) with the wind speed

(red) at the outer spoil ground option in September 2005.



12. Dredging Simulations

The dredge modelling was carried out in two steps. Firstly the 3-dimensional ocean

circulation of the KGS, PRH and Oyster harbour was predicted for 5 months using GCOM3D.

Then the total dredge program was simulated using DREDGE3D, which simulates the

behaviour of the dredge(s) based on an estimated dredge log.

Modelling relied on the best available meteorology and bathymetric information and included

assumptions and details from other recent dredging programs in WA. Where there was

uncertainty in model parameters, conservative values were chosen such that the model

would tend to overestimate the impact.

The dredge modelling was carried out for just over 4 months starting at three distinct times of

the year:

• Starting on March 1, 2005 (dominated by easterly winds);

• Starting on July 1, 2005 (dominated by westerly winds);

• Starting on November 1, 2005 (mixed season with both easterly and westerly winds).

The dredge modelling predicted the hourly distribution of Total Suspended Solids (TSS) and

seabed coverage to be developed over the total dredge program (approximately 120 days).

The hourly output was analysed to derive periods of continuous exposure to turbidity and/or

sedimentation above defined thresholds.

The result of this analysis is summarised in maps of exposure zones showing regions

affected by turbidity or sedimentation that result in high impact, moderate impact or a visible

plume or a very small level of sedimentation.

12.1 Dredge Assumptions The detailed specifications of the dredges and their expected program can be found

elsewhere (JFA, 2006). GEMS worked closely with the dredge management team (JFA) to

define the estimated dredge log, an extract of which is shown in Table 4.



12.2 Particle Size Distributions and Settling Velocities An important point to note is that all measured settling velocities that we are aware of are

significantly different to theoretical values and so the use of theoretical values as a

benchmark is not valid. Laboratory measurements in Australia are usually performed by the

CSIRO Marine Labs in Perth.

Particle size distributions for this study were defined at every time step from borehole data

taken along the dredging path which was subsequently analysed by the CSIRO Marine Labs.

The particle settling velocities for each particle size in the distribution were also derived by

CSIRO.

The basic particle size distributions for the two main material types (sand and rock flour/clay)

are defined in Table 5. The settling velocities derived by CSIRO for each of these particle

sizes are given in Table 6.

Due to the availability of core data every 100 metres the actual distribution used at each time

step was defined by combining the distributions in Table 5 according to analysed constituent

fractions (i.e fraction of sand plus fraction of clay/rock flour).



Table 4: Extract from the dredge log used to carry out the dredge modelling. Time

(hours) Dredge

Cut_Rate

(m3/sec)

Duration

(hours) Easting Northing Sand % Clay % Flour %

Dump

Flag Oflow UKC

Ship

Speed

2603.00 THSD 1.389 0.05 582916.0 6122045.0 100 0 0 0 N 6.0 4.6

2603.05 THSD 1.389 0.05 583135.3 6122114.3 100 0 0 0 N 6.1 4.6

2603.08 CSD 0.000 0.08 583216.0 6122045.0 78.5 21.5 0 0 N 0.0 20.4

2603.10 THSD 1.389 0.05 583354.6 6122183.6 100 0 0 0 N 6.3 4.6

2603.15 THSD 1.389 0.05 583573.9 6122252.9 100 0 0 0 N 6.4 4.6

2603.17 CSD 0.204 1.00 583216.0 6122045.0 78.5 21.5 0 2 N 0.0 0.9

2603.20 THSD 1.389 0.05 583793.2 6122322.2 100 0 0 0 N 6.5 4.6

2603.25 THSD 1.389 0.05 584012.5 6122391.5 100 0 0 0 N 6.7 4.6

2603.30 THSD 1.389 0.05 584231.8 6122460.8 100 0 0 0 N 6.8 4.6

2603.35 THSD 1.389 0.05 584451.1 6122530.1 100 0 0 0 N 6.9 4.6

2603.40 THSD 1.389 0.05 584670.4 6122599.4 100 0 0 0 N 7.0 4.6

2603.45 THSD 1.389 0.05 584889.7 6122668.7 100 0 0 0 N 7.2 4.6

2603.50 THSD 1.389 0.05 585109.0 6122738.0 100 0 0 0 Y 7.3 4.6

2603.55 THSD 1.389 0.05 585330.8 6122789.6 100 0 0 0 Y 6.8 4.6

2603.60 THSD 1.389 0.05 585552.6 6122841.2 100 0 0 0 Y 6.3 4.6

2603.65 THSD 1.389 0.05 585774.4 6122892.8 100 0 0 0 Y 5.8 4.6

2603.70 THSD 1.389 0.05 585996.2 6122944.4 100 0 0 0 Y 5.3 4.6

2603.75 THSD 1.389 0.05 586218.0 6122996.0 100 0 0 0 Y 4.8 4.6

2603.80 THSD 1.389 0.05 586439.8 6123047.6 100 0 0 0 Y 4.2 4.6



2603.85 THSD 1.389 0.05 586661.6 6123099.2 100 0 0 0 Y 3.7 4.6

2603.90 THSD 1.389 0.05 586883.4 6123150.8 100 0 0 0 Y 3.2 4.6

2603.95 THSD 1.389 0.05 587105.2 6123202.4 100 0 0 0 Y 2.7 4.6

2604.00 THSD 1.389 0.05 587327.0 6123254.0 100 0 0 0 Y 2.2 4.6

2604.05 THSD 1.389 0.05 587504.1 6123112.4 100 0 0 0 Y 2.9 4.6

2604.10 THSD 1.389 0.05 587681.2 6122970.8 100 0 0 0 Y 3.5 4.6

2604.15 THSD 1.389 0.05 587858.3 6122829.2 100 0 0 0 Y 4.2 4.6

2604.17 CSD 0.000 0.33 583222.0 6122045.0 78.5 21.5 0 0 N 0.0 20.4

2604.20 THSD 1.389 0.05 588035.4 6122687.6 100 0 0 0 Y 4.8 4.6

2604.25 THSD 1.389 0.05 588212.5 6122546.0 100 0 0 0 Y 5.5 4.6

2604.30 THSD 1.389 0.05 588389.6 6122404.4 100 0 0 0 Y 6.2 4.6

2604.35 THSD 1.389 0.05 588566.7 6122262.8 100 0 0 0 Y 6.8 4.6

2604.40 THSD 1.389 0.05 588743.8 6122121.2 100 0 0 0 Y 7.5 4.6

2604.45 THSD 1.389 0.05 588920.9 6121979.6 100 0 0 0 Y 8.1 4.6

2604.50 CSD 0.204 1.00 583222.0 6122045.0 78.5 21.5 0 2 N 0.0 4.6

2604.50 THSD 1.389 0.05 589098.0 6121838.0 100 0 0 0 Y 8.8 4.6

2604.55 THSD 1.389 0.05 589262.6 6121677.4 100 0 0 0 Y 8.9 6.2

2604.60 THSD 1.389 0.05 589427.2 6121516.8 100 0 0 0 Y 9.0 7.8

2604.65 THSD 1.389 0.05 589591.8 6121356.2 100 0 0 0 Y 9.2 9.3

2604.70 THSD 1.389 0.05 589756.4 6121195.6 100 0 0 0 Y 9.3 10.9

2604.75 THSD 1.389 0.05 589921.0 6121035.0 100 0 0 0 Y 9.4 12.5



2604.80 THSD 1.389 0.05 590085.6 6120874.4 100 0 0 0 Y 9.5 14.1

2604.85 THSD 1.389 0.05 590250.2 6120713.8 100 0 0 0 Y 9.6 15.7

2604.90 THSD 1.389 0.05 590414.8 6120553.2 100 0 0 0 Y 9.8 17.2

2604.95 THSD 1.389 0.05 590579.4 6120392.6 100 0 0 0 Y 9.9 18.8

2605.00 THSD 0.000 0.25 590744.0 6120232.0 100 0 0 0 N 10.0 20.4

2605.25 THSD 0.000 0.25 593655.0 6117370.0 100 0 0 1 N 10.0 0.9

2605.50 CSD 0.000 0.08 583228.0 6122045.0 78.5 21.5 0 0 N 0.0 4.6

2605.50 THSD 0.000 0.05 590959.0 6120022.0 100 0 0 0 N 7.0 20.4

2605.55 THSD 0.000 0.05 590154.7 6120224.3 100 0 0 0 N 6.9 18.8

2605.58 CSD 0.204 1.00 583228.0 6122045.0 78.5 21.5 0 2 N 0.0 4.6

2605.60 THSD 0.000 0.05 589350.4 6120426.6 100 0 0 0 N 6.8 17.2

2605.65 THSD 0.000 0.05 588546.1 6120628.9 100 0 0 0 N 6.7 15.7

2605.70 THSD 0.000 0.05 587741.8 6120831.2 100 0 0 0 N 6.6 14.1

2605.75 THSD 0.000 0.05 586937.5 6121033.5 100 0 0 0 N 6.5 12.5

2605.80 THSD 0.000 0.05 586133.2 6121235.8 100 0 0 0 N 6.4 10.9

2605.85 THSD 0.000 0.05 585328.9 6121438.1 100 0 0 0 N 6.3 9.3

2605.90 THSD 0.000 0.05 584524.6 6121640.4 100 0 0 0 N 6.2 7.8

2605.95 THSD 0.000 0.05 583720.3 6121842.7 100 0 0 0 N 6.1 6.2



Table 5: Basic particle size distributions used in the dredge simulations

Sand Rock Flour/Clay Diameter Percentage Percentage

1589 6.0 6.0 893 6.0 6.0 502 6.0 6.0 399 27.0 27.0 252 33.0 33.0 159 8.0 8.0 126 4.0 4.0 100 1.5 0.1 89 2.0 0.1 79 1.0 0.1 71 1.0 0.1 63 1.0 0.1 50 1.0 0.1 40 0.5 0.6 32 0.5 0.5 25 0.4 0.5 16 0.3 0.5 13 0.1 0.5 10 0.1 0.5 8.0 0.1 0.5 6.3 0.1 0.5 5.0 0.1 0.5 4.0 0.1 0.5 2.8 0.1 0.5 2.0 0.1 0.6 1.4 - 0.6 1.0 - 0.6 0.8 - 0.5 0.6 - 0.4 0.5 - 0.3 0.4 - 0.2 0.3 - 0.1



Table 6: Analysed particle settling velocities compared with the values used in the dredge modelling.

Diameter (micron) %

CSIRO Settling Rate

(mm/s)

2000.00 31.0 5152

1589.00 9.0

893.40 8.0

502.40 7.0 322

399.10 7.0 206

251.80 6.0 80.5

200.00 5.0 51.5

158.90 4.0 29.0

126.20 3.0

100.00 2.0 12.88

89.34 2.0

79.62 2.0 8.24

63.25 2.0 4.64

50.24 2.0 3.22

39.91 2.0 2.06

31.70 1.0 1.16

25.18 1.0 0.805

20.00 0.5 0.515

15.89 0.5 0.290

10.02 0.5 0.129

7.96 0.5 0.0824

5.02 0.5 0.0322

3.99 0.5 0.0206

2.83 0.5 0.0116

2.00 0.5 0.0052

1.00 0.5 0.0013

0.80 0.5 0.0008

0.63 0.5 0.0005

0.40 0.5 0.0002



12.2 Dredging Simulation

DREDGE3D was used to simulate the behaviour of particles released into the water column

by the dredges, driven by 3D ocean currents from GCOM3D, waves from SWAN, the

estimated dredge log and particle size distributions at every time step.

As explained earlier, three possible dredging periods were simulated to sample the full range

of meteorology at Albany. Turbidity and sedimentation data were stored hourly for each 1 m

layer of the water column of the gridded study area.

These results were then analysed according to exposure criteria provided by marine

biologists (SKM) to determine impact zones. These impact zones are then interpreted by the

marine biologists (SKM) to determine the extent of the impacts on the marine habitat.

12.2.1 Total Suspended Solids

Sample plots showing predicted TSS plumes during varying meteorological conditions are

shown in Figures 12.1 to 12.3. These plots provide an insight to the variations that are likely

to occur as a result of changes to dredge location, tidal phase and wind strength and

direction during the dredging program.

When interpreting the results in Figures 12.1 and 12.3 the following issues should be noted:

The plots show turbidity levels due to dredging alone, and the colour codes were chosen to

distinguish the different concentration ranges. The latter should not be taken as any

indication of water coloration or clarity.

The turbidity levels were derived at each model grid point by scanning the water column from

surface to bottom for the grid cell with the highest turbidity rather than averaging over the

water column. The results therefore show the highest turbidity levels found across the grid.

In all three dredging simulations the modelling predicts a build up of deposited sediments in

the immediate vicinity of the dredging area and spoil disposal site from the settlement of the

larger sediments (>75 µm). Finer sediment fractions remain suspended for longer periods

and lead to increased turbidity, which varies significantly in space and time.



These variations are due to the ocean circulation in KGS driven predominantly by, at times,

strong marine winds.

To provide an understanding of the variations in TSS throughout the dredging, time series of

TSS at five locations (see Figure 12.4) are shown in Figures 12.5 to 12.7 for the dredging

periods starting in March, July and November respectively.

The impact criteria provided by SKM are given in Table 7. These criteria define the levels of

average turbidity in the water column, averaged over the duration of the dredging, which

were used to analyse the hourly model output to produce exposure zones showing regions

affected by turbidity that result in high impact, moderate impact or influence (but no impact).

The results for each of the three dredging periods are shown in Figures 12.8 to 12.10).

Closer examination of the results shows that:

• The main area experiencing turbidity impacts is around the dredged channel and at

the spoil ground;

• During the “easterly wind” dredging program, and to a lesser extent during the “mixed

season” dredging program (presumably also due to easterly winds), there are also

turbidity impacts in an area north of the mussel farms and south of the channel due to

southerly and/or anticlockwise flow in KGS.

• During the “westerly wind” dredging program the dominant region showing turbidity

impacts is an area along the northern shoreline of KGS resulting from clockwise

circulation within KG. This region also experiences turbidity impacts, but to a lesser

degree, during the other two dredging “seasons”.

• Partial impacts occur on a wider area and extend into the channel in PRH

• The zone of influence covers a larger region than the zones of impact but is only an

indication of where turbid plumes MAY be seen at some time during the dredging but,

by definition, do NOT cause any impacts on seagrasses



12.2.2 Sedimentation

There was a requirement to investigate the sedimentation on completion of the dredging

program and the subsequent stability of the spoil ground. It needs to be noted however that

spoil ground stability is one of the less accurate processes modelled due to a limited ability to

accurately simulate resuspension processes.

Resuspension is driven by ocean currents near the sea bed and by orbital velocities

generated near the sea bed by wave action. The main reasons for our limited ability to

produce reliable predictions are:

• Orbital velocities are predicted by the SWAN wave model but unfortunately there is

no data to verify these predictions.

• The distribution of particles available for resuspension is difficult to define. For

example all the fine material is not available for immediate resuspension at the spoil

ground because it may be buried under heavier material.

With these caveats in mind the sediment distribution on completion of dredging programs

starting in March, July and November is shown in Figures 12.11, 12.13 and 12.15

respectively.

In each of the three cases the dredge plume model was allowed to run for a complete 12

months (approx. 8 months after dredging ceased) and the sediment distribution at the spoil

ground is shown in Figures 12.12, 12.14 and 12.16.

The results show a degree of smoothing out of the spoil ground but do not identify any

significant levels of migration to any other location within KGS, including the dredged

channel. Several factors need to be considered when interpreting this outcome:

• The spoil ground, after completion of disposal, is over 30 metres deep and therefore

too deep for wave action to produce significant resuspension

• The data and the model results show that the bottom currents at the disposal site are

quite weak and therefore there is no consistent mechanism for resuspension of the

material.

• For material to accumulate back in the channel it would need to be resuspended and

somehow drift to the channel which is over 15 metres shallower.



Table 7: The Sea grass Impact Zone Criteria Supplied by SKM

Depth

(metres)

Zone 1

High Impact

(mg/litre)

Zone 2

Moderate Impact

(mg/litre)

Zone 3

No Impact

(mg/litre)

<1 98 32 1

2 48 16 1

3 31 11 1

4 23 8 1

5 18 6 1

6 15 5 1

7 12 5 1

8 11 4 1

9 9 4 1

10 8 3 1

11 7 3 1

12 6 3 1

13 6 2 1

14 5 2 1

15 5 2 1

16 4 2 1

17 4 2 1

>17 4 2 1

Note:

1) Exposure was restricted to daylight hours

2) The criteria are depth dependent because, for a given turbidity, sea grass are much

more affected at depth than in shallow waters (such as PRH).



Figure 12.1: Sample TSS plot during dredging of the channel by the TSHD showing the

effects of anti-clockwise circulation in KGS during southeasterly winds.


effects of clockwise circulation in KGS during northeasterly winds.




effects of circulation in KGS during westerly winds.



Figure 12.4: Location of the five stations where time series data were captured during

the analysis of the turbidity results.

Figure 12.5: TSS time series at five locations during dredging starting in March.



Figure 12.6: TSS time series at five locations during dredging starting in July.

Figure 12.7: TSS time series at five locations during dredging starting in November.



Figure 12.8: Sea grass mortality zones derived for dredging starting in March.

Note: Level 1 (red) = high impact,

Level 2 (magenta) = moderate impact,

Level 3 (yellow) = no impact but occasional visible plume when TSS above 1mg/litre.



Figure 12.9: Sea grass mortality zones derived for dredging starting in July.

Figure 12.10: Sea grass mortality zones for dredging starting in November.

Note: Level 1 (red) = high impact,

Level 2 (magenta) = moderate impact,

Level 3 (yellow) = no impact but occasional visible plume when TSS above 1mg/litre.




program which started in March.

Figure 12.12: Sediment accumulation (above 100gm/m2) 12 months after the start of

dredging in March.




program which started in July.


dredging in July.




program which started in November.


dredging in November.



13. References

Mills, D. and D’Adamo, N. (1993). Water circulation and flushing characteristics of

Princess Royal Harbour. Technical Series No. 51, Environmental Protection

Authority, Perth, Western Australia, March, 1993.



Appendix A: Qualitative and Limited Quantitative

Comparisons of DREDGE3D Predictions with Data during the

Geraldton Port Redevelopment Dredging Program A.1 Method

To establish predictions for the verification of the GEMS sediment plume model, a hindcast

of the actual dredging program was carried out using the real-time wind, wave and dredge

location/performance data. The hindcast was carried out from the commencement of

dredging in October, 2002 until December 31, 2002 to generate fine particle loads in

Champion Bay for comparison with TSS data collected in late November and December

2002 by the GPA.

The detailed tasks required to achieve these aims were as follows:

• Setup the model domain and bathymetry

• Process wind, wave and dredge log data from the commencement of dredging to

December 31, 2002

• Hindcast ocean currents with the GCOM3D driven by tides and winds from Geraldton

Port for the period October 2002 to December 31 2002

• Hindcast turbid plume behaviour with DREDGE3D, driven by currents from GCOM3D

and the historical dredge log, for the period October 2002 to December 31 2002

• Compare model predictions with satellite and aerial photos at four specific times in

the prediction period.

• Analyse hindcast data to compare predicted TSS values with measured data in

November and December 2002.

Figure A.1 shows the model region and the sites chosen for sampling TSS levels in

Champion Bay. Figures A.2 and Figure A.3 show sample surface currents from GCOM3D

during the three month simulation under the influence of southerly and northeasterly winds

respectively.



A.2 Comparison of Predictions with TSS Measurements

The results of DREDGE3D predictions for TSS are compared with observations taken by the

GPA on 7 days in late November and December in Table A.1. The observed values shown

in Table 1 are an average of all measurements taken in Champion Bay on the particular day.

Since TSS measurements can vary significantly with small spatial or temporal changes it was

considered to be more valid to compare regional averages rather than try and compare site-

specific predictions and measurements.

Table 4 indicates that on December 5 the model exhibits a generally higher suspended

sediment load in Champion Bay than recorded. On the other 6 days, however, the

agreement is much closer. Given the potential errors in the input data (winds, dredge

performance, particle distribution) the overall agreement must be considered to be very

good.

A.3 Comparison of Model Predictions with Satellite & Aerial Photos

Comparison of model predictions with aerial or satellite photos can be misleading as it is

impossible to determine what TSS values are contributing to the turbid plume in the images.

Nevertheless a qualitative comparison can be made and such things as the basic path of the

plume, denser areas etc. can be compared.

The GPA provided satellite images for November 26 and December 17, 2002 and aerial

photos for October 30, December 5 and December 18, 2002. Comparisons are shown for

these dates in the following figures:

Figures A.4 and A.5 compare the satellite image with model predictions on October 30, 2002.

Figures A.6 and A.7 compare an aerial photo with model predictions on November 26, 2002.

Figures A.8, A.9 and A.10 compare aerial and satellite photos with model predictions on

December 18, 2002

On the other three days of comparison with satellite and aerial photos the turbid plume is

predominantly moving northward and the predictions show similar paths and density patterns

to the photos.



A.4 Outcomes The qualitative comparisons with satellite and aerial photographs show similar features and

density patterns although, as expected, agreement is by no means exact.

These qualitative results and the good agreement between predicted and measured TSS

values on six out of the seven days suggests that DREDGE3D is simulating the turbid plume

behaviour in Champion Bay reasonably well.

Figure A.1: Model region showing TSS sites chosen for output in Champion Bay.



Figure A.2: Sample surface currents from GCOM3D during southerly winds.

Figure A.3: Sample surface currents from GCOM3D during north-easterly winds.



Table A.1: Comparison of Predicted (P1-8) and measured TSS values (TL1-21).

Site TSS (mg/l) Nov-28 Nov-29 Dec-05 Dec-06 Dec-10 Dec-24 Dec-27 Average

P1 5.4 7.3 9.7 6.1 4.9 3.4 1.3

P2 5.2 3.0 8.8 2.6 3.9 3.5 1.1

P3 4.9 2.5 6.0 4.6 2.0 3.5 1.0

P4 4.2 2.2 5.6 3.5 3.0 1.8 0.4

P5 4.2 5.4 8.7 6.3 4.5 3.3 5.4

P6 3.6 2.3 8.7 3.4 2.9 2.7 5.0

P7 2.9 1.6 5.6 4.2 1.7 2.5 5.4

P8 2.7 1.0 5.5 3.3 1.9 1.0 2.3

Average 4.1 3.2 7.3 4.3 3.1 2.7 2.7 3.9

TL1 5.8 1.2 2.6 1.7 4.7 1.2 2.9

TL2 3.9 2.2 4.0 2.7 4.3 1.3 2.1

TL3 3.4 3.3 2.9 3.0 1.8 0.9 2.4

TL4 3.8 14.2 3.6 4.2 4.2 2.0 4.8

TL5 3.1 1.9 6.0 2.7 2.6 1.6 1.9

TL6 2.4 2.8 5.2 5.9 3.4 2.2 3.2

TL7 9.3 2.7 4.5 2.0 2.5 1.4 3.1

TL8 11.9 2.6 5.1 2.8 2.9 1.1 3.7

TL9 6.7 2.2 5.0 3.3 1.8 5.1 5.6

TL10 4.7 - 3.6 3.6 2.6 1.4 1.5

TL11 - 2.9 3.1 4.4 2.7 1.6 2.1

TL12 - 2.0 3.0 4.7 4.3 2.0 2.2

TL13 3.4 2.7 5.4 5.3 2.8 1.2 1.6

TL14 - 3.7 2.4 4.8 4.2 2.2 2.0

TL15 - 2.7 2.6 4.5 4.0 4.1 1.8

TL16 5.0 2.6 3.1 4.4 4.2 1.8 3.9

TL17 - 2.7 2.8 4.4 3.4 1.3 2.9

TL18 - 4.2 3.4 3.5 5.2 3.8 3.6

TL19 - 3.6 2.9 4.1 3.3 2.8 2.3

TL20 - 5.6 2.7 5.1 5.9 3.1 3.4

TL21 4.2 4.6 7.2 4.6 3.7 6.1 3.5

Average 5.2 3.5 3.9 3.9 3.5 2.3 2.9 3.6



Figure A.4: Satellite photo of the turbid

plume on October 30, 2002

Figure A.5: Model prediction for the

turbid plume on October

30, 2002



Figure A.6: Aerial photo of the turbid plume on November 26, 2002

Figure A.7: Model prediction for the turbid plume on November 26, 2002.



Figure A.8: Aerial photo of the turbid plume on December 18, 2002

Figure A.9: Model prediction on

December 18, 2002.

Figure A.10: Satellite photo on

December 17, 2002.

GEMS – Global Environmental Modelling Systems Pty. Ltd. Report 376/06


Appendix B: Model Descriptions

B.1 GCOM3D

For studies of hydrodynamic circulation and sea level variation under ambient and extreme

weather conditions, GEMS has developed the GEMS 3-D Coastal Ocean Model (GCOM3D).

GCOM3D is an advanced, fully three-dimensional, ocean-circulation model that determines

horizontal and vertical hydrodynamic circulation due to wind stress, atmospheric pressure

gradients, astronomical tides, quadratic bottom friction and ocean thermal structure. The

system will run on Windows/NT or UNIX platforms. GCOM3D is fully functional anywhere in

the world using tidal constituent and bathymetric data derived from global, regional and local

databases.

GCOM3D has never been fully published. Some details appear in publications (Hubbert

1991, 1993, 1999). Further information is given below:

B.1.1 History and Physics

The history of development of GCOM3D began in 1982, initially stimulated by the 3D model

development by Lendertsee (1973) who applied a “z” co-ordinate 3D barotropic model to a

number of coastal engineering tasks in the 1970’s.

The publication of what was the predecessor to the Princeton Ocean Model in 1983 by

Blumberg and Mellor (1983) raised the standard of 3D ocean modelling by incorporating the

vertical mixing schemes then used in atmospheric modelling into an ocean model for the

first time.

GCOM3D was the first “z” coordinate ocean model to incorporate the Mellor-Yamada (1982)

vertical mixing scheme and was first used for consulting purposes in 1984 for the Geelong

ocean outfall study near Barwon Heads in Victoria.

GCOM3D is a fully baroclinic ocean model but is most often run in barotropic

(hydrodynamic) mode due to either the lack of data on ocean thermal structure or the

dominance of winds and tides as the major forcing factors.



B.1.2 General Description

GCOM3D is a fully three-dimensional, ocean-circulation model that determines horizontal

and vertical circulation due to wind stress, atmospheric pressure gradients, astronomical

tides, quadratic bottom friction and ocean thermal structure.

The system will run on Windows or UNIX platforms

GCOM3D is formulated as a relocatable model which can be applied anywhere in the world

using tidal constituent and bathymetric data derived from global and local databases.

The three-dimensional structure of the model domain, tidal conditions at the open

boundaries, thermodynamics and wind forcing are defined for each model application by

extraction of data stored in gridded databases covering a wider geographical area of

interest.

The model scale is freely adjustable, and nesting to any number of levels is supported in

order to suit the oceanographic complexity of a study area.

As the model is fully three-dimensional, output can include current data at any or all levels in

the water column.

B.1.3 Horizontal and Vertical Structure

The model operates on a regular grid (in the x and y directions) and uses a z-coordinate

vertical-layering scheme. That is, the depth structure is modelled using a varying number of

layers, depending on the depth of water, and each layer has a constant thickness over the

horizontal plane.

This scheme decouples surface wind stress and seabed friction and avoids the bias of

current predictions for a particular layer caused by averaging of currents over varying

depths, as used in sigma co-ordinate and “depth-averaged” model schemes.

In the upper water column levels are typically a few metres apart, increasing to several

hundred metres in deep waters.

B.1.4 Numerical Procedures

The basic equations are solved using a split-explicit finite-difference scheme on an

Arakawa-C grid (Messinger and Arakawa, 1976) as described in Hubbert et al. (1990). The

continuity equation and the gravity wave and Coriolis terms in the momentum equations are

solved on the shortest time step, (the adjustment step) using the forward-backward method.



The non-linear advective terms are solved on an intermediate advective time step using the

two-time-level method of Miller and Pearce (1974). Finally, on the longest time step, the so-

called physics step, the surface wind stress, bottom friction stress and atmospheric pressure

terms are solved using a backward-implicit method. This approach is extremely efficient in

oceanographic models with free surfaces because of the large disparity between advective

speeds and gravity-wave phase speeds in deep water.

The numerical scheme used for the advective step is the two-time-level method of Miller and

Pearce (1974). This scheme alternates the Euler and Euler-backward (Matsuno) schemes

at odd and even advective time-steps and has the major advantage of an amplification

factor of almost exactly unity for the Courant numbers that are found in ocean models

(Hubbert et al. (1991).

The adjustment and advective integration cycle is carried out N times to produce an interim

solution which is completed with the inclusion of the physics terms using a numerical

technique similar to that described for the adjustment step.

B.1.5 Boundary Conditions

Boundary conditions can be applied in a range of ways depending on the type of process

being modelled.

Meteorological forcing is applied via the wind stress and surface pressure gradient at all

submerged model grid-points in the computational domain.

Tidal and meteorological forcing at lateral boundaries is achieved by specifying the

incremental displacement of the water surface due to changes in tidal height and

atmospheric pressure. These boundary conditions are applied using a ‘one-way nesting’

technique to the appropriate model variable with a logarithmic decreasing intensity from the

boundary to some specified number of model grid-points (typically 10-15) into the domain.

At coastal boundaries and along river banks, the wetting and drying of grid cells is

accomplished via the inundation algorithm described published in Hubbert and McInnes

(1999).

On outflow, a radiation boundary condition, as described in Miller and Thorpe (1981) is

applied to the velocity field to prevent the build up of numerical energy, while on inflow

boundaries, a zero-gradient condition is applied.



B.1.6 Tidal Data Assimilation

In order to improve the simulation of tidal forced dynamics the model includes the facility to

“nudge” the solution with tidal height predictions at locations within the model domain.

The nudging method is based on deriving a new solution at grid points near each tidal

station from a weighted combination of the model solution and the station sea level

prediction.

B.1.7 Model Applications

GCOM3D has undergone exhaustive evaluation and verification in the 15 years it has

served the coastal engineering industry in Australia and has a proven record of accurately

predicting the wind and tidal driven ocean currents around the Australian continental shelf

(and in many other parts of the world).

The Australian National Search and Rescue system is based on ocean currents from

GCOM3D, which has been running in real-time at the Australian Maritime Safety Authority in

Canberra for the past 4 years. It is the first real-time ocean prediction model in Australia.

The U.S. Navy also purchased GCOM3D for its coastal ocean forecasting system.

GCOM3D has also been used in a wide range of ocean environmental studies including

prediction of the fate of oil spills, sediments, hydrotest chemicals, drill cuttings, produced

formation water and cooling waters as well as in other coastal ocean modelling studies such

as storm surges and search and rescue.



B.2 SWAN To obtain realistic estimates of random, short-crested wind-generated waves in such

conditions for a given bottom topography, wind field, water level and current field, the

numerical wave model SWAN can be used.

The SWAN model was developed at Delft University of Technology, Delft (the Netherlands).

It is specified as the new standard for nearshore wave modelling and coastal protection

studies. The SWAN model has been released into the public domain.

SWAN simulates the following physical phenomena:

• Wave propagation in time and space, shoaling, refraction due to current and depth,

frequency shifting due to currents and nonstationary depth.

• Wave generation by wind.

• Nonlinear wave-wave interactions (both quadruplets and triads).

• Whitecapping, bottom friction, and depth-induced breaking.

• Blocking of waves by current

•

The SWAN model is a non-stationary third-generation wave model (see e.g. Holthuijsen et

al., 1993; Ris, 1997) and is the successor of the stationary second-generation HISWA model

(Holthuijsen et al., 1989).

The non-stationary SWAN model is based on the discrete spectral action balance equation

and is fully spectral (over the total range of wave frequencies and over the entire 360°). This

latter implies that short-crested random wave fields propagating simultaneously from widely

different directions can be accommodated. The wave propagation is based on linear wave

theory (including the effect of currents). The processes of wind generation, dissipation and

nonlinear wave-wave interactions are represented explicitly with state-of-the-art third-

generation formulations. (It is noted that for reasons of economy, more simple first- and

second-generation formulations are also optionally available.) The SWAN model can also be

applied as a stationary model (stationary mode). This is considered acceptable for most

coastal applications because the travel time of the waves from the seaward boundary to the

coast is relatively small compared to the time scale of variations in incoming wave field, the

wind or the tide.

To avoid excessive computing time and to achieve a robust model in practical applications,

fully implicit propagation schemes (in time and space) have been implemented. The SWAN

computations can be made on a regular and a curvilinear grid in a Cartesian co-ordinate

system. Nested runs can be made with the regular grid option.



SWAN provides many output quantities including two-dimensional spectra, significant wave

height and mean wave period, average wave direction and directional spreading, root-mean-

square of the orbital near-bottom motion and wave-induced force (based on the radiation-

stress gradient).

The SWAN model has successfully been validated and verified in several laboratory and

(complex) field cases (see e.g. Ris, 1997).



B.3 DREDGE3D The dredge modelling is carried out in two steps. Firstly the 3-dimensional ocean circulation

of the region is predicted for the full dredge program using GCOM3D. Then the total dredge

program is simulated using DREDGE3D, which simulates the behaviour of the dredge(s)

based on an estimated dredge log (at time steps of 10-15 minutes).

B.3.1 Model Features

• DREDGE3D is used for simulating the specific fate of particles discharged during a

dredging program.

• The model is a Lagrangian particle model and does not run on a grid and

consequently is independent of grid resolution.

• The model inputs the ocean currents (and temperature, salinity if important) from

GCOM3D, together with wave data from SWAN and meteorological data from

MesoLAPS, to simulate the movement and deposition of suspended particles in the

water body resulting from a dredging activity defined by an estimated dredge log.

• DREDGE3D release particles into the water column, as determined by the dredge

log, representing the range of particle sizes (say 50) and volume of each particle size

fraction. Thereafter the particle transport is simulated and the x,y,z coordinates of

each particle written out to a file each hour of the dredging program.

• All sources of particles introduced to the water column can be simulated including

releases from the CSD cutter head; the TSHD drag head; barge and hopper

overflow; spoil ground dumping; reclamation bund overflow; TSHD propellor wash

etc.

• Particles move through the water as a function of the assigned settling velocity, the

ambient current speeds and a random walk dispersion algorithm

• Particles which settle to the ocean bed can be resuspended if the shear stress

resulting from the ambient bottom currents and orbital velocities generated by waves

exceed defined threshholds which vary as a function of particle size and density.

• Modelling predicts the hourly distribution of Total Suspended Solids (TSS) and

seabed coverage to be developed over the total dredge program. The hourly output

is analysed to derive periods of continuous exposure to turbidity and/or

sedimentation above defined thresholds.



B.3.2 Establishment of the Dredge Log

The type of information required to set up the simulated dredge log for Trailer Suction

Hopper (THSD) and Cutter Suction Dredges (CSD) includes:

• Total volume of material to be dredged

• Region to be dredged

• Expected start time(s)

• Expected duration of dredging

• Particle size distributions and settling rates for all types of material to be dredged

• Number and type of dredges

• Draft (full and empty) of dredge(s)

• Average hours per week of operation

• Maintenance schedule (repairs, refuelling etc.)

• Time of operation before overflow (of THSD or CSD barges)

• Duration of overflow

• Depth of overflow

• Overflow rate m3/sec

• Whether under keel clearance is controlled or not (THSD only)

• Particle size distributions for all types of material to be dredged

• No dredging periods (such as coral spawning)

• Cutting rate

• Hopper capacity (m3) for overflow and no overflow conditions in terms of dry solids

• Speed of dredge(s) while dredging, travelling to, and returning from, the dump site

• Number, location and capacity of disposal sites.

B.3.3 DREDGE3D Methodology

The basic steps undertaken by DREDGE3D (for a TSHD) are:

• Read from the dredge log the next location

• Determine dredging action (dredging, overflowing or not, sailing to spoil ground,

dumping or returning from spoil ground)

• If dredging

• read the cutting rate

• Calculate the volume to be dredged in the time step between now and the next

location



• Add this volume to the total volume count

• Compare dredged volume with total volume to be dredged to determine when to

cease dredging

• Distribute the mass to the model particles to be released at this time step according

to the particle size analysis curve for that location

• Keep a count of the total mass distributed

• Determine the fate of each model particle (overflowed, retained in hopper)

• Add overflow mass to total overflow mass

• Add hopper mass to total hopper mass

• If dumping at spoil ground

• Release all particles in the hopper at the designated spoil ground

• Add dumped mass to total spoil ground mass

• Check if spoil ground mass has exceeded spoil ground capacity.

• All model particles released are tracked for the full duration of the dredging program

(whether it be 2 months or 2 years) and the XYZ coordinates are written out to a

binary output file every hour (eventually several million particles).

• At each output time step the total mass assigned to each model particle released so

far is added up and compared with the total mass dredged. If they are not the same,

the model stops and an error is flagged.

• Note that for a TSHD another source of turbidity is the wash from the propellers,

particularly when the under keel clearance (UKC) reduces as the hopper fills. This

process is simulated using empirical algorithms developed during the recent Dampier

Port dredging program from measurements of turbidity in the vicinity of the TSHD

propellers.

B.3.4 Analysis of Results

The turbidity levels are derived at each model grid point by scanning the water column from

surface to bottom for the grid cell with the highest turbidity rather than averaging over the

water column. The results therefore show the highest turbidity levels found across the grid.

Although a large amount of detail is included in the dredge simulations the results are still

based on a wide range of assumptions and the proper use of the output should be to

provide an indication of potential impacts from the dredging program.



The simulation of several dredging periods experiencing differences in the Meteorology,

together with the detailed dredge log method, provides a rich source of information from

which potential impacts can be derived. In the actual dredging program however, regions

that show potential impacts may not occur due to variations in meteorology and/or dredge

behaviour.

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