Climate Change Impact Report - Shire of Glenelg€¦ · Revision 0 - 17 May 2010 Table 3: Percentage changes in the intensity of 1-day rainfall events projected by various climate

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Appendix A

Climate Change Impact Report

Glenelg Shire Council

17 May 2010

Portland CoastalEngineering StudyClimate Change Investigation

AECOMPortland Coastal Engineering Study

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Portland Coastal Engineering StudyClimate Change Investigation

Prepared for


Prepared by

AECOM Australia Pty LtdLevel 9, 8 Exhibition Street, Melbourne VIC 3000, AustraliaT +61 3 9653 1234 F +61 3 9654 7117 www.aecom.comABN 20 093 846 925

17 May 2010

60148113 Climate Change Investigation

© AECOM Australia Pty Ltd 2010

The information contained in this document produced by AECOM Australia Pty Ltd is solely for the use of the Client identified on the cover sheetfor the purpose for which it has been prepared and AECOM Australia Pty Ltd undertakes no duty to or accepts any responsibility to any third partywho may rely upon this document.

All rights reserved. No section or element of this document may be removed from this document, reproduced, electronically stored or transmittedin any form without the written permission of AECOM Australia Pty Ltd.

http://www.aecom.com

AECOMPortland Coastal Engineering Study


Table of Contents1.0 Introduction 12.0 Sea level Rise 23.0 Extreme Rainfall 34.0 General Limitations 65.0 References 7

List of Tables

Table 1– SRES Scenarios 1Table 2: Adjusted projections of sea-level rise, based on the A1FI scenario (Hunter, 2009) 2Table 3: Percentage changes in the intensity of 1-day rainfall events projected by various climate models for a

1-in-100 year event, for 2055 and 2090 relative to 1980 in the south-western Victorian region (Rafter2010, pers. comm. 5 May) 4


1.0 IntroductionAverage temperatures in Australia are expected to rise this Century due to anthropogenic activities elevatingatmospheric concentrations of greenhouse gases. This change in temperature is expected to affect a range ofother climate variables.

The key climate variables that are likely to affect the risk of flooding between Portland and Narrawong includeincreases in rainfall intensity, changes in wave climate, sea-level rise and increases in the frequency and intensityof storm surge. Secondary effects of changes to climate variables, such as local erosion occurring as a result ofsea-level rise, could also have significantly change the inundation characteristics of coastal regions. It is beyondthe scope of this study to predict or model these secondary effects.

The extent of future inundation has been estimated based on projected increases in sea-level rise and extremerainfall intensity, and the implications of changing rainfall patterns on runoff. The impact of changes in sea-levelson storm surge intensity and frequency has been factored into AECOM’s modelling of future coastal floodingevents.

An overview of climate change emission scenarios and the potential changes in sea-level rise, extreme rainfalland runoff is also discussed in this report.

1.1 Emission Scenarios

Emission scenarios are estimates of the future quantity of greenhouse gases that may be released into theatmosphere. These are based on assumptions about future demographic changes, and the implementation andefficiency of energy policies. The scenarios are simply assumptions and represent a primary source ofuncertainties.

The Intergovernmental Panel on Climate Change (IPCC) developed scenarios in 1990, 1992 and 2000 andreleased a Special Report on Emission Scenarios (SRES). The SRES is used to provide input data for climatemodels. To reflect the latest rapid changes in societies since 2000, new emission scenarios are currently underdevelopment.

The IPCC emission scenarios are divided into four families: A1, A2, B1 and B2. A description of each scenario isprovided in Table 1

Table 1– SRES Scenarios

SRES Scenario Description of Scenario

A1FIRapid economic growth, a globalpopulation that peaks mid 21st

century and rapid introduction ofnew technologies

Intensive reliance on fossil fuel energyresources

A1TIntensive reliance on non-fossil fuel energyresources

A1B Balance across all energy sources

A2Very heterogeneous world with high population growth, slow economicdevelopment and slow technological change

B1Convergent world, same global population as A1 but with more rapid changes ineconomic structures toward a service and information economy

B2Intermediate population and economic growth, emphasis on development ofsolutions to economic, social and environmental sustainability

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2.0 Sea-level RiseSea-level rise has occurred at a global mean rate of 1.7mm per year for the past century, and more recently atrates estimated to be near 3.1 ± 0.7 mm per year (1993-2003) (Bindoff et al. 2007). Current sea-level rise isconsidered to be at least partly due to human-induced climate change. Increasing temperatures have contributedto sea-level rise due to the thermal expansion of water and addition of water to the oceans from the melting ofterrestrial ice sheets.

The IPCC Fourth Assessment Report (AR4) (2007) estimated a sea-level rise of 0.19-0.59 m by 2100 based onresults from 17 GCMs. More recent changes to ice sheet melting rates and dynamics are likely to increase sea-levels beyond current IPCC projections. Unlike the IPCC Third Assessment Report (TAR), the AR4 does notprovide time series of sea-level projections through the 21st century, but does provide maximum and minimumprojections for the decade 2090-2099 (here termed '2095') and for the potential dynamic response of theGreenland and Antarctic Ice Sheets. To estimate a time series of the maximum and minimum IPCC AR4projections, Hunter (2009)1 scaled the equivalent TAR projections (from Table II.5 of the IPCC TAR, pp. 824-825).

The resulting scaled maximum and minimum values are shown for 2030, 2070 and 2100 in Table 2 for the IPCC’shigher emissions growth scenario (‘A1FI’), and have been used as a basis for the Portland Coastal EngineeringStudy. The higher growth scenario assumes a continuation of strong economic growth based on continueddependence on fossil fuels. In this scenario, atmospheric carbon dioxide concentrations more than triple relativeto pre-industrial levels by 2100, with a global temperature increase of 4.0°C (2.4 to 6.4°C) likely.

Table 2: Adjusted projections of sea-level rise, based on the A1FI scenario (Hunter, 2009)

Climate Variable Baseline (1990) 2030 2070 2100

Sea-level rise 0 +0.05 to 0.15m 0.17 to 0.47m 0.27 to 0.82m

The Victorian Coastal Strategy recommends implementing a policy of planning for sea-level rise of not less than0.8 metres by 2100. This allowance is approximately consistent with Hunter’s (2009) upper limit of 81.9cm for theA1FI scenario by 2100, which has been used as a basis for the Portland Coastal Engineering Study. In order tobe consistent with the approach taken for selecting sea-level rise values for 2100, the upper limits of Hunter’s(2009) projections have also been adopted for other timeframes. This study has therefore used the following sea-level rise projections (note that increases have been applied to 2010 levels as a conservative estimate of sea-level rise):

2030 – increase of 0.15 m

2070 – increase of 0.47 m

2100 – increase of 0.82 m.

1Time series can be viewed at http://www.cmar.csiro.au/sealevel/sl_proj_21st.html

http://www.cmar.csiro.au/sealevel/sl_proj_21st.html


3.0 Extreme RainfallCatchment runoff for the flood modelling completed by AECOM uses the estimated 24 hour 1-in-100 yearAverage Recurrence Interval (ARI) as this was found to be the critical storm in a previous study of the Surry River(Water Technology, 2008), and is also consistent with the ARI used as a basis for flood modelling by GlenelgShire Council.

Changes in the 1 in 100 year ARI by 2100 have not been published for Victoria. CSIRO therefore undertook anextreme value analysis (EVA) of Global Climate Models (GCMs) in order to estimate potential changes in rainfallintensity caused by climate change. The EVA used 24 hour rainfall data over the south-western Victorian region,specifically showing the 100 year ARI for 2046-2095 (“2055”) and 2081-2100 (“2090”). Projections weredeveloped using the A2 emission scenario using 11 GCMs for 2055 and 12 GCMs for 2090.

Percentage changes in the intensity of 1-day rainfall events projected by various climate models for a 1-in-100year event are shown in Table 3. The mean and median of the grid points for each GCM falling within the region(N) are indicated, as are the climate model ensemble means and medians. The region was defined as longitude140.0 to 143.5 and latitude -39.0 to 37.5. The analysis masked any grid points that are less than 10% over land(Rafter 2010, pers. comm. 5 May).

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Table 3: Percentage changes in the intensity of 1-day rainfall events projected by various climate models for a 1-in-100 year event, for 2055 and 2090 relative to 1980 in the south-western Victorian region (Rafter2010, pers. comm. 5 May)

1-day (24hr) accumulation rainfall return levels

1-in-100 year event:

CNRMCM3

CSIROMk3.0

CSIROMk3.5

GFDLCM2.0

GFDLCM2.1

MIROC3.2

(medres)

MIUBECHO-G

MPIECHAM 5

MRICGCM2.3.2A

NCARCCSM3.0 (1)

NCARCCSM3.0 (3)

EnsembleAverage

EnsembleMedian

mean -15.6 6.5 -43.5 2.4 83.0 25.4 20.2 43.7 -3.9 5.1 36.0 14.5 6.5median -15.6 2.3 -42.3 -5.5 83.0 25.4 20.2 67.1 -3.9 -0.8 43.5 15.8 2.3N 2 3 3 4 2 2 1 3 2 6 6

CNRMCM3

CSIROMk3.0

CSIROMk3.5

GFDLCM2.0

GFDLCM2.1

MIROC3.2

(medres)

MIUBECHO-G

MPIECHAM 5

MRICGCM2.3.2A

NCARCCSM3.0 (1)

NCARCCSM3.0 (3)

UKMOHadCM3

mean 69.1 31.1 9.7 29.7 38.5 25.5 60.8 6.8 86.5 121.7 6.0 -2.7 44.1 31.1median 69.1 35.8 14.7 33.7 38.5 25.5 60.8 3.8 86.5 108.1 -1.3 -2.7 43.2 35.8N 2 3 3 4 2 2 1 3 2 6 6 2

2055 projections from various climate models

South West VIC(regional approach)

South West VIC(regional approach)

2090 projections from various climate models


The following were selected as inputs to flood modelling:

Climate model ensemble averages, as these provide higher values than the ensemble medians, andtherefore a conservative approach

An average of the median GCM values, which avoids the potential for distortion to be caused by high valuegrid points.

Using this approach, a 15.8% increase in 1-day (24hr) accumulation rainfall return levels is projected by 2055,with a 43.2% increase by 2090.

CSIRO (Rafter 2010, pers. comm. 5 May) has agreed that these are reasonable estimates of projected changesin 24-hour duration extreme rainfall for the Portland region subject to the following caveats:

1. The method used to derive the extreme rainfall projections involved the use of extreme value analysis (astatistical model) on the daily rainfall data from each GCM. The specific method used is the r-largest GEV;an r value of 2 was used, which means the top 2 values per year were inputs to the statistical model. Thestatistical fitting to the data allows us to determine what would be the return level (in this case, the amountof rain to fall) for a range of return periods. However, the longer the return period the larger the errorbounds on the estimated return levels become. As the two future climates examined were based on 20-year blocks of data, the error margins on the requested 1-in-100 year return levels become quite large, soit must be stressed that this could introduce a large amount of uncertainty to the projections. These futureclimate return levels were then compared with a “current climate” baseline, and expressed as a percentagechange from this baseline. This percentage comparison could amplify any differences between the 100-year return levels as the statistical fits obtained for the different climates could vary greatly.

2. The extreme rainfall data provided is derived from the output of GCMs. As these models are at a verycoarse resolution – typically they have grid spacing of 200km or more – they do not provide a greatamount of regional detail. It would be far more preferable to be able to provide data from a set of higherresolution extreme rainfall runs using a dynamically downscaled model, as these are better able torepresent more localised effects on extreme rainfall events. However, the GCM data is the best currentlyavailable to provide the required projections.

3. Using a regional approach to develop projections for extreme rainfall should provide a better indication ofhow the extremes will change over a larger area, which samples more data points (in most cases) andthus provides more data to consider, and an estimate of changes less subject to potential variabilitybetween neighbouring grid points. This should give a more robust estimate of changes. Taking the medianof the grid points in the region rather than the mean would further reduce the impact of an “outlier” gridpoint, although the small number of grid points falling within this region may reduce the effectiveness ofthis approach; e.g. if there are 1 or 2 grid points, the median gives the same result as the mean.

4. Whilst it would be preferable to perform runoff modelling for projections from each supplied GCM scenario,given the limitations of the study and the requirement of “one number” to inform the flooding/runoff modelthe willingness to use an ensemble average approach is understood. The use of the ensemble averagerather than the ensemble median gives a larger value (and hence a conservative approach), but moreimportantly is defensible on the grounds that ensemble averages are frequently used in climate analysisstudies and tend towards the true value much of the time, as seen in the projections of the IPCC models ofglobal average temperature.

(Adapted from Rafter 2010, pers. comm. 5 May)


4.0 General LimitationsThe following general limitations should be considered in the climate change projections provided for the PortlandCoastal Engineering Study:

It is recognised that there are inconsistencies in the choice of emission scenarios and climate models usedto obtain projections for the different climate variables. This is necessary in the absence of published databeing available for consistent emission scenarios and climate models for all climate variables andtimeframes

The climate change projections discussed in this document are based on current climate change science.This is a dynamic area of study, and it is recommended that the projections are reviewed on an ongoingbasis to incorporate relevant changes as the science evolves.


5.0 ReferencesBindoff, NL et al. (2007), "Observations: Oceanic Climate Change and Sea-level", Climate Change 2007: ThePhysical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change, Cambridge University Press.

Hunter, J.R. (2009), Estimating Sea-Level Extremes Under Conditions of Uncertain Sea-Level Rise. ClimaticChange, 2009.

IPCC (2007) Summary for Policymakers. Climate Change 2007: The Physical Science Basis. Contribution ofWorking Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. S.Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds) (ed.), CambridgeUniversity Press, Cambridge, United Kingdom and New York, NY, USA.

New South Wales (2009). Scientific basis of the 2009 sea-level rise benchmark: Draft Technical Note.

IPCC (2007) Summary for Policymakers. Climate Change 2007: The Physical Science Basis. Contribution ofWorking Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. S.Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds) (ed.), CambridgeUniversity Press, Cambridge, United Kingdom and New York, NY, USA.

Jones, R.N. and Durack, P.J (2005). Estimating the Impacts of Climate Change on Victoria’s Runoff using aHydrological Sensitivity Model CSIRO. Atmospheric Research, Melbourne, CSIRO Australia.

Rafter (2010), pers. comm. to Jolyon Orchard, 5 May..

Water Technology (2008). Surry River Estuary Flood Study, Study Report, Report Number J543/R03, WaterTechnology, July 2008.

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Appendix B

Coastal Erosion Report

Coastal Spaces - Inundation and Erosion - Coastal Engineering Study


8 July 2010

Portland Coastal Engineering Study Coastal Erosion

AECOMCoastal Spaces - Inundation and Erosion - Coastal Engineering Study Portland Coastal Engineering Study

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Portland Coastal Engineering Study Coastal Erosion

Prepared for


Prepared by

AECOM Australia Pty Ltd Level 9, 8 Exhibition Street, Melbourne VIC 3000, Australia T +61 3 9653 1234 F +61 3 9654 7117 www.aecom.com ABN 20 093 846 925

8 July 2010

60148113 Coastal Erosion Report

© AECOM Australia Pty Ltd 2010

The information contained in this document produced by AECOM Australia Pty Ltd is solely for the use of the Client identified on the cover sheet for the purpose for which it has been prepared and AECOM Australia Pty Ltd undertakes no duty to or accepts any responsibility to any third party who may rely upon this document.

All rights reserved. No section or element of this document may be removed from this document, reproduced, electronically stored or transmitted in any form without the written permission of AECOM Australia Pty Ltd.



Table of Contents 1.0 Introduction 1 2.0 Methodology 3 3.0 Extreme Event Analysis 4

3.1 Water Levels 5 3.1.1 Tides 5 3.1.2 Storm Surges 5 3.1.3 Storm Events (sea levels) 6

3.2 Waves 7 3.2.1 Storm Waves 7

4.0 Wave transformation Modelling 9 4.1 Bathymetry 9 4.2 Wave Measurements 9 4.3 Hindcast Waves 9 4.4 Winds 13 4.5 SWAN Model Set-up 14 4.6 SWAN Model Verification 17 4.7 Model Results 18

5.0 Erosion due to Cross-Shore Transport 22 5.1 Beach and Sediment Data 22 5.2 SBEACH Model 22

5.2.1 Design Storms 23 6.0 Recession due to Longshore Transport 28

6.1 Kamphuis, 1991 28 6.2 LITDRIFT (Danish Hydraulic Institute) 29 6.3 Results 31 6.4 Recession Rates from LST 32 6.5 Aerial Photography - Photogrammetry 33 6.6 Discussion 36

7.0 Recession due to Sea-level Rise 38 8.0 Coastal Hazard Lines 41 9.0 Glossary 44 10.0 References 46

Appendix A Appendix A - Grain size Analysis ........................................................................................................ A

Appendix B Appendix B - Beach Profiles ...............................................................................................................C

List of Tables

Table 1 Tidal Planes at Portland 5 Table 2 Top twenty events based on high sea-levels (combined tide and storm surge) 6 Table 3 Yearly maximum sea levels between 1991 and 2009. 6 Table 4 Extreme sea levels (combined tide and storm surge) 7 Table 5 Extreme offshore waves at Portland 8 Table 6 Joint distribution of significant wave height and wave direction (offshore Portland from

combined ECMWF and AUS WAM data) 12 Table 7 Joint distribution of significant wave height and peak wave period (offshore Portland from

combined ECMWF and AUS WAM data) 12 Table 8 Joint distribution of significant wave height and mean wave direction for swell waves

(offshore Portland from ECMWF) 13 Table 9 Joint distribution of wind speed and wind direction (offshore Portland from AUS WAM

data) 13



Table 10 Joint distribution of Significant wave height and mean wave direction for wind waves (offshore Portland from ECMWF) 14

Table 11 Summary of wave transformation modelling results 18 Table 12 Joint probability distribution of Hs and wave direction at Dutton Way (location 4) at 15 m

depth 20 Table 13 Extreme inshore waves at Portland 21 Table 14 Shoreline recession due 100 year ARI storm 24 Table 15 Input wave conditions to LITDRIFT 30 Table 16 LST potential rates along the Portland coast 31 Table 17 Closure depths and berm heights at the study locations 33 Table 18 Differences in shoreline position from aerial photographs 34 Table 19 Long-term shoreline recession (m per year) 36 Table 20 Predicted shoreline recession in 2100, 2070 and 2030 40 Table 21 Shoreline Recession due to Storm events, longshore transport and Bruun Rule 41 Table 22 Coastal Hazard Lines (m from existing coast line) 41

List of Figures

Figure 1 Study Area 1 Figure 2 Study Methodology 3 Figure 3 Probability of exceedance for measured and hindcast waves at Cape Sorell and Portland

(upper panel) and Cape de Couedic and Portland (lower panel). 10 Figure 4 Time series wave heights at Cape Sorrell (upper panel) and Cape de Couedic (lower

panel). 11 Figure 5 Model grid set-up showing the nested fine grid (50 m) within the coarse grid (200 m). 15 Figure 6 Bathymetry for the fine-grid model. 16 Figure 7 Probability of Exceedance of modelled and measured significant wave heights at Point

Danger 17 Figure 8 Study area showing locations where model results have been extracted. 18 Figure 9 Probability of Exceedance of modelled wave heights at Portland 19 Figure 10 Modelled wave vectors (length of vector represents the wave height and the direction

represents the wave direction (coming from) from the fine-grid model for an offshore condition of Hs =1 m, Tp=15 s and Dir = 157.5 deg. 20

Figure 11 Particle Size distribution for a sediment sample collected from Portland foreshore (3 m from the end of the rock wall). 23

Figure 12 Input time-series of wave heights, periods and water levels for 100 yr ARI storm to SBEACH model 24

Figure 13 Predicted change in beach profile, maximum Hs and maximum water elevation + set-up at location 2 caused by the 100 yr ARI storm 25

Figure 14 Predicted change in beach profile, maximum Hs and maximum water elevation + set-up at location 4 caused by the 100 yr ARI storm 26

Figure 15 Predicted changes in beach profile, maximum Hs and maximum water elevation + set-up at Section 7 caused by the 100 yr ARI storm 27

Figure 16 1972 Coastline 34 Figure 17 1977 Coastline 35 Figure 18 2003 Coastline 35 Figure 19 2009 Coastline 36 Figure 20 Schematic representation of the Bruun Rule. 38 Figure 21 Selected measured beach profiles and Equilibrium profile. 39 Figure 22 Overview of Coastal Erosion and Flooding Risk 42


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1.0 Introduction This report has been prepared to document the Coastal Engineering Investigations undertaken for the Portland Coastal Engineering Study. A location map of the Study Area is presented in Figure 1.

Figure 1 Study Area

Climate change impacts onto the Glenelg foreshore may result from increased rates of foreshore erosion and inundation resulting from sea level rise, increased storm surges and wave conditions. Any such increases will be superimposed upon a coastal process signature that already is causing significant foreshore erosion and inundation. To address climate change impacts, it is essential to develop an understanding of the existing coastal processes that are prevalent at the study site and to define and quantify their impacts.

Numerical modeling has been undertaken to develop an understanding of the coastal processes within the region. This, in conjunction with professional assessment and engineering judgment has lead to the definition and quantification of the pertinent coastal processes and hazards at the site, which is necessary for the successful development of appropriate management options.

The recommended methodology by The National Committee on Coastal and Ocean Engineering (NCCOE, 2004), for the assessment of coastal processes is the consideration of the following six key variables:

1) Mean Sea Level

2) Ocean Currents and Temperature

3) Wind Climate

4) Wave Climate

5) Rainfall/Runoff

6) Air temperature



NCCOE recommends the evaluation of the secondary variables of which local sea level, currents; winds, waves, beach response, foreshore stability, sediment transport, coastal flooding, and groundwater are most relevant to the current study. Following NCCOE’s recommendation, the following key coastal processes have been investigated for the study:

Evaluation of extreme water levels

Evaluation of regular and extreme wave conditions;

Cross shore erosion from extreme event storm conditions;

Longshore transport from prevailing wave conditions

Long term shoreline recession as a result of combined action of waves and currents;

Long term change in environmental exposure and the implications of climate change.

The following sections provide a description of each of the key coastal processes and the data required for their assessment. The methodology adopted for this study is similar to that used in major studies involving coastal assessment due to climate change in Australia (WRL, 2008; SMEC, 2006). The various tasks and models used along with the inputs and outputs are provided in Figure 1.



2.0 Methodology Figure 2 shows the methodology used for this investigation.

Figure 2 Study Methodology

Input Data

• Water levels • Extreme event

analysis• Bathymetric data• Profiles• Offshore wave data• SWAN modelling• Wave climate for

study area

Model

SBEACH

LITDRIFT

BRUUNS RULE

Output

Recession due to Cross Shore

Transport

Recession due to Longshore Transport

Recession due to sea-level rise

Coastal Hazard

Mapping



3.0 Extreme Event Analysis Extreme events analysis is required for the purpose of planning and engineering design. For the current study, it is necessary to ascertain the beach changes related to the specific occurrence of the storms. Extreme events based on both the sea-levels and the offshore and inshore waves have been assessed. Since the high sea-levels often occur at the same time as strong winds and high waves, significant coastal erosion can result from these events.

Extreme conditions are defined by:

Average recurrence interval (ARI) which is the average, or expected value of the periods between exceedances of a given value (for example wave height or water level) or;

Annual Exceedance Probability (AEP) which is defined as the probability that a given value total accumulated over a given duration will be exceeded in any one year.

The ARI (expressed in years) is related to AEP as follows:

The ARI is also referred to as the “return period” for example a 1 in 100 year ARI sea level is the sea level that is exceeded on average once every 100 years. It is important to note that this is a statistical average, and events exceeding the 1 in 100 year level may actually occur more frequently within any 100 year period. There is a 64% chance that the 1 in 100 year event will be exceeded in any consecutive 100 year period.

The commonly used variables for extreme event analysis for coastal planning are sea levels, waves and winds. For the purposes of this study, this analysis has been undertaken for planning and contingencies only and a more detailed analysis will be required for engineering design.

The following two methods have been used for the extreme value analyses.

Gumbel Analysis

The Gumbel distribution is given by:

ssH

eeP

Where:

P = Probability of any wave height (or period)

Hs = Significant wave height (or period)

β and are coefficients found by regression analysis of the data

To ensure that recurrence intervals are not biased by low energy events, only the largest storm events of a particular data set are analysed in the Gumbel method. A storm is defined using the ‘peak over threshold’ method whereby a storm is the time between when the wave height first exceeds some threshold to when it goes below the same threshold.



Weibull Distribution

The Weibull distribution is defined by:

Where:

= shape parameter, Β> 0 = scale parameter γ = location parameter.

The Weibull distribution is widely used for coastal applications in particular for estimating distributions of wind and waves.

3.1 Water Levels

It is important to have an accurate definition of water levels including tides, storm and wave set-up, which are the essential parameters for assessment of coastal processes. Since wave-driven sediment transport is depth-dependent, elevated water levels which are often associated with major storm events result in increased erosion of the normally sub-aerial beach while the seaward extent of cross-shore and longshore transport increases during storms accompanied by low water levels.

Recorded sea level data from the tidal gauge at Portland exists from 1982 as indicated by previous studies (McInnes et al, 2009). However data available for the current study from the National Tidal Centre (NTC), Bureau of Meteorology commences in July 1991 and ends in January 2010 (a total of 18.6 years). Storm surge analysis from previous studies was used in conjunction with the available data from NTC.

3.1.1 Tides

Tides at Portland are mixed with similar semi-diurnal and diurnal components. Along most of southern Australia, the shallow water on the continental shelf amplifies the semidiurnal tides. The diurnal tide propagates eastwards and the semidiurnal tide propagates shoreward from deep water in the Southern Ocean. Tidal planes obtained from the Australian National Tide Tables for Portland are given in Table 1 below:

Table 1 Tidal Planes at Portland

m AHD Highest astronomical tide, HAT 0.70 Mean high high water, MHHW 0.50 Mean low high water, MLHW 0.20 Mean sea level, MSL 0.00 Mean high low water, MHLW -0.20 Mean low low water, MLLW -0.40

3.1.2 Storm Surges

Storm surges occur during and after storm events where meteorological forcing of wind and atmospheric pressure leads to an increase in sea-level over a number of days. It is during such events that large-scale modifications occur to the coastline, including the cutting back of beach slopes and the erosion or undercutting of cliffs. The drop in atmospheric pressure and the winds and waves that often accompany large coastal storms can cause the ocean to rise above its normal level and if this occurs concurrently with high astronomical tides, flooding of low-lying coastal land and beach erosion may result.

The increase in sea-level means that less wave energy is lost due to friction and breaking and thus more energy reaches the coast and contributes to eroding beaches or cliffs. In addition, the higher sea-level means that areas that are not normally subject to wave activity are exposed to the full force of the approaching waves. This is especially important in areas where the beach is backed by dunes or soft cliff material. Since these areas are



rarely modified by wave action, they tend to be steeper than the beach found within the swash zone. The increased steepness means that the waves breaking on these sections of the beach will erode the dunes or cliffs located at the back of the beach.

3.1.3 Storm Events (sea levels)

The twenty highest sea-level events were extracted from the sea-level data provided by NTC, which spans over 18.6 years (July 1991 – January 2010). To ensure the selection of independent events, it was assumed that events separated by at least 5 days were independent of each other.

The sea-level including the storm surge for these events with the corresponding wind speeds and directions are shown in Table 2. This analysis showed that the increase in sea-level rise normally accompanies winds from the south-west to north-west with gusts greater than 10 m/s.

Table 2 Top twenty events based on high sea-levels (combined tide and storm surge)

Ranking Date Storm Sea-Level (m AHD)

Wind gust (m/s)

Wind direction (TN)

1 26/04/2009 3:00 1.09 19.7 238 2 26/05/1994 3:00 1.06 21.0 298 3 12/06/2002 4:00 1.04 22.3 297 4 03/05/2007 3:00 1.04 12.9 300 5 06/06/2003 6:00 1.04 19.1 273 6 24/06/1994 3:00 1.02 15.5 227 7 13/07/1995 4:00 1.01 11.3 307 8 19/06/2004 4:00 1.00 17.8 217 9 01/07/2008 2:00 0.99 14.6 264 10 03/07/1992 5:00 0.99 15.2 329 11 20/07/2000 5:00 0.94 12.7 333 12 19/05/2003 5:00 0.93 13.2 313 13 12/06/1998 4:00 0.93 15.5 252 14 19/05/2007 4:00 0.93 16.6 292 15 14/06/1999 3:00 0.92 15.9 206 16 04/07/2007 5:00 0.90 9.4 289 17 20/06/2005 2:00 0.90 10.3 248 18 22/06/2000 5:00 0.90 17.1 231 19 02/08/1996 4:00 0.89 17.7 307 20 25/05/2009 3:00 0.89 7.0 343

Yearly maximum for the same period was also computed and is presented in Table 3. Both are remarkably similar indicating the occurrence of a major storm event every year.

Table 3 Yearly maximum sea levels between 1991 and 2009.

Year Yearly Maximum Sea-Level (m AHD)

1991 0.88 1992 0.99 1993 0.84 1994 1.06 1995 1.01 1996 0.89 1997 0.84 1998 0.93 1999 0.92 2000 0.94 2001 0.87 2002 1.04



Year Yearly Maximum Sea-Level (m AHD)

2003 1.04 2004 1.00 2005 0.90 2006 0.89 2007 1.04 2008 0.99 2009 1.09

The extreme events were extrapolated to determine the various annual return periods using the Gumbel Method (Method of moments). The results are presented in Table 4. For comparison, results from previous studies are also provided.

Table 4 Extreme sea levels (combined tide and storm surge)

ARI (years) Sea-Level (m AHD) Current Study

Sea Level (m AHD) McInnes, 2009

Sea Level (m AHD) Tawn and Mitchell (1990)

10 1.05 0.83 50 1.13 1.02 100 1.17 1.07 1.18

It is seen that the results of this study match closely with those of Tawn and Mitchell, 1990 in McInnes (2009) as compared with McInnes (2009). Likely reasons are the similar length of records analysed and the use of combined sea-levels versus separated tide and surge components. The McInnes study analysed the tide and surge components separately and combined these using joint probability analysis. While using the total sea-level approach, it is possible that a high storm surge occurring during neap tides may be omitted which leads to higher estimates. The extreme sea levels from McInnes (2009) have been adopted in this study since it follows a more rigorous procedure.

3.2 Waves

The waves on the surface of the ocean result from the transfer of energy from the wind blowing over the ocean surface into the wave motion of the water. At any given location, the wave motion can be considered to be the resultant of the waves generated by the wind blowing at that time, the so-called wind-generated sea, and waves which have been generated by the wind elsewhere and have propagated into the area, known as swell.

There are very limited wave data available in the vicinity of the study area. Continuous time-series of at least ten years is required to compute extreme wave climate. In the absence of measured wave data, hind cast wave data have been obtained from the Bureau of Meteorology (BoM) operational wave model (AUSWAM). The data are on a 0.125 ° latitude and longitude grid (approximately 14 km x 11 km) and include wave parameters for sea and swell including height, period and direction as well as wind speed and direction. These data provide a continuous time series in Portland Bay close to the study area. Data from this model are available from January 2003 to the December 2008 at 12-hour intervals. Additional 5 years of data have been obtained from the global model operated by the European Centre for Medium Range Weather Forecasts (ECMWF). The data are on a 1° x 1° latitude and longitude grid and cover the time period from February 1998 to February 2003. The model data are first validated and calibrated so that long-term statistics are consistent with those from satellite data. Validation of the model data proves their high quality and calibration assures the statistics are as bias-free as possible.

Time-series of wave parameters from the two global models, ECWMF and AUSWAM were extracted at a location offshore of Portland in approximately 150 m depth. The maximum significant wave height for each year was identified and subject to extreme value analysis as described below.

3.2.1 Storm Waves

Extreme waves for offshore Portland were calculated using the both Gumbel and Weibull procedures described in the section above. The results are presented in Table 5.



Table 5 Extreme offshore waves at Portland

ARI (years) Hs (m), offshore Portland Gumbel Weibull 100 11.0 11.1 50 10.4 10.4 10 8.9 9.0

The above analysis is based on yearly maxima.



4.0 Wave transformation Modelling A representative inshore wave climate is required to assess the coastal processes in the study area. The wave climate has been developed using hindcast offshore wave data and transforming the offshore waves to inshore locations using wave transformation modelling. To allow for the variability of wave conditions over different time periods, a sufficiently long offshore wave data set (10 years) has been used to ensure that storm wave conditions in addition to “normal” wave conditions are included.

A reliable set of wave parameters that accurately describes the inshore wave conditions at Portland has been prepared for input into the wave and morphological models. Inshore wave conditions are rarely available; therefore, wave transformation modelling is employed to compute inshore wave parameters from a given set of offshore wave conditions. The other major input required for wave transformation modelling is detailed bathymetry over the model domain. The following sections describe the model inputs and results.

4.1 Bathymetry

The nearshore bathymetry data have been provided by the Department of Sustainability and Environment (DSE). The data consists of digital elevation model (DEM) with contours at 0.5 m intervals derived from high accuracy LiDAR survey between September 2007 and September 2009. The horizontal accuracy of the data set is +/- 35 cm and the vertical accuracy is +/- 10 cm. The data covers the area between Cape Nelson and Port Fairy and extends offshore to a depth contour of approximately 15 m. Additional offshore data has been obtained from the Australian hydrographic charts no. AUS 140 and AUS 349.

4.2 Wave Measurements

Available measurements of limited wave heights and periods closest to the site consist of the two non-directional Waverider buoys: one off Cape Sorrell on the west coast of Tasmania; and the second on the southern side of Kangaroo Island at Cape de Coeudic. The only known wave measurements in the Portland area are from two different wave recording devices south of Portland Harbour operated by the Portland Harbour Trust between 1973 and 1977. Only about one year of meaningful data were extracted from the measurements. The devices did not measure wave directions. Time-series of these wave data were not available for analyses during the present study. Statistics of the measured wave data from the instruments were available from previous studies and have been used to verify the inshore wave model.

4.3 Hindcast Waves

Hindcast data from the two global models, ECWMF (1998-2003) and AUSWAM (2003-2008) were extracted at a location offshore of Portland. The wave data from both the global wave models were compared with the wave measurements from Cape Sorrell (1998-2008) and Cape de Couedic, Kangaroo Island (2001-2008). Exceedance probabilities were computed for all the data sets and are presented in Figure 3. The hindcast data are in excellent agreement with the measurements. The plots also indicate that the waves offshore of Portland are remarkably similar to the waves at Cape Sorrell and Cape de Couedic.



Figure 3 Probability of exceedance for measured and hindcast waves at Cape Sorell and Portland (upper panel) and Cape de Couedic and Portland (lower panel).

Time-series of measured and hindcast wave heights at Cape de Couedic and Cape Sorrell match very well (Figure

4) showing that the hindcast data is of high quality and accurately represents the wave conditions in the study area.

0

1

10

0.0 0.1 1.0 10.0 100.0

Hs (m

)

Probability of Exceedance

Cape Sorrell & Portland

ECMWF Portland (5 yrs)

ECMWF Cape Sorrell (5 yrs)

AUS WAM Portland (5 yrs)

AUS WAM Cape Sorrell (5 yrs)

Measured (11 yrs)

0

1

10

0.0 0.1 1.0 10.0 100.0

Hs (m

)

Probability of Exceedance

Cape de Couedic & Portland

ECMWF Portland (5 yrs)

ECMWF Cape de Couedic (5 yrs)

AUS WAM Portland (5 yrs)

AUS WAM Cape de couedic (5 yrs)

Measured (11 yrs)



Figure 4 Time series wave heights at Cape Sorrell (upper panel) and Cape de Couedic (lower panel).



The wave data from offshore Portland from the two global models were combined and analysed for joint probability distribution of wave heights and wave directions and wave heights and wave periods. The joint distribution of wave height with wave direction (Table 6.) shows that the majority of waves approach from the south-west quadrant. This reflects both the direction of the prevailing wind and the much longer fetch available for the winds to generate waves. Generally, waves approach from the south-south-west to west-south-west (~85%) with lesser occurrences from the south-east (~5%) and the north-west (~10%). The maximum Hs during this time period was 8.9 m.

Table 6 Joint distribution of significant wave height and wave direction (offshore Portland from combined ECMWF and AUS WAM data)

Significant wave height, Hs (m) Direction 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 Total N 0.02 0.03 0.04 NNE 0.01 0 0 0.01 NE 0.01 0.01 0.02 ENE 0.01 0.01 E- 0.01 0.01 ESE 0.02 0.02 0.04 0.08 SE- 0.01 0.15 0.35 0.09 0.01 0.6 SSE 0.01 0.37 0.66 0.25 1.28 S 0.03 1.07 1.64 0.59 0.17 0.01 0.01 3.53 SSW- 0.03 3.44 6.05 2.53 0.52 0.11 0.04 0.02 0 12.74 SW 0.04 7.24 21.08 11.44 3.22 0.94 0.23 0.09 0 44.27 WSW 0.03 2.57 10.14 8.63 3.95 1.35 0.39 0.24 0.06 27.34 W 0.01 0.62 2.35 2.28 1.11 0.57 0.17 0.01 7.11 WNW 0.21 0.8 0.7 0.26 0.04 0.01 2.02 NW 0.06 0.2 0.31 0.15 0.73 NNW 0.05 0.05 0.06 0.03 0.20 Total 0.17 15.85 43.36 26.92 9.41 3.01 0.84 0.35 0.07

The distribution of peak wave period with Hs is shown in Table 7. Majority of the waves have a peak wave period between 11 and 15 s. The wave periods at Portland tend to be long with the maximum peak period occurrence of 22 s.

Table 7 Joint distribution of significant wave height and peak wave period (offshore Portland from combined ECMWF and AUS WAM data)

Significant wave height, Hs (m) Period, Tp (s)

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 Total

0.00+ 2.00+ 4.00+ 0.03 0.27 0.05 0.35 6.00+ 0.04 0.91 0.96 0.23 0.01 2.15 8.00+ 0.02 2.99 2.46 1.09 0.19 0.01 6.76 10.00+ 0.02 5.44 11.52 4.6 1.23 0.11 0.01 22.92 12.00+ 0.03 4.04 16.14 9.04 3.47 1.04 0.15 0.04 0.01 33.97 14.00+ 0.02 1.07 9.43 7.16 2.5 1.28 0.52 0.17 0.02 22.16 16.00+ 0.01 0.44 2.08 4.29 1.51 0.45 0.16 0.13 0.03 9.1 18.00+ 0.01 0.63 0.59 0.5 0.49 0.1 0.01 0.01 2.33 20.00+ 0.08 0.13 0.02 0.01 0.03 0.26 Total 0.17 15.85 43.36 26.92 9.41 3.01 0.84 0.35 0.07



The swell and sea (wind) component extracted from the global models were analysed separately. The joint occurrence of swell wave heights and directions is presented in Table 8. The distribution of swell waves is very similar to the total distribution of waves (combined swell and sea) as presented in Table 6 indicating the dominance of swell in this region.

Table 8 Joint distribution of significant wave height and mean wave direction for swell waves (offshore Portland from ECMWF)

Significant wave height, Hs (m) Direction 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 Total N NNE NE ENE E- ESE SE- 0.04 0.07 0.01 0.12 SSE 0.15 0.14 0.01 0.30 S 0.57 0.60 0.05 1.23 SSW- 2.97 4.41 1.05 0.25 0.01 8.69 SW 0.04 8.13 28.49 14.01 3.12 0.60 0.04 54.43 WSW 0.03 3.41 15.05 9.87 2.64 0.30 0.03 31.32 W 0.85 2.09 0.56 0.01 0.01 3.53 WNW 0.07 0.22 0.04 0.33 NW 0.03 0.03 NNW 0.01 0.01 Total 0.07 16.23 51.07 25.62 6.02 0.93 0.07

4.4 Winds

The study area is designated as a severe weather area, with storms occurring in all months of the year. Storms in the area result from the extra-tropical low pressure systems (associated with cold fronts) that move from west to east across the Great Australia Bight. In the more intense systems, wind speeds of 12-18 m/s are common and gusts of up to 40 m/s can occur. Table 9 shows the joint distribution of wind speed and direction from the AUSWAM model for the time period between 2003 and 2008.

Table 9 Joint distribution of wind speed and wind direction (offshore Portland from AUS WAM data)

Wind Speed (m/s) Direction 1.5 4.5 7.5 10.5 13.5 16.5 19.5 22.5 25.5 Total N 0.28 1.1 1.71 1.79 0.92 0.09 5.9 NNE 0.38 0.9 1.3 0.42 0.09 3.1 NE 0.40 1.1 0.6 0.23 2.3 ENE 0.45 1.3 0.8 0.23 2.8 E- 0.52 1.9 1.3 0.42 0.02 4.1 ESE 0.42 2.2 2.9 0.96 0.05 0.02 6.6 SE- 0.70 2.7 2.8 0.82 0.23 0.05 7.3 SSE 0.66 2.2 2.5 0.96 0.16 0.07 6.6 S 0.63 2.5 2.2 0.94 0.42 0.12 6.9 SSW- 0.59 2.1 2.6 1.2 0.35 0.12 7.0 SW 0.49 1.9 2.7 1.93 0.87 0.16 0.1 8.1 WSW 0.63 1.7 2.7 2.02 1.2 0.56 0.1 8.9 W 0.52 1.4 2.5 2.72 1.74 0.52 0.1 0.1 9.6 WNW 0.54 1.2 2.3 1.93 1.71 0.38 0.3 0 8.3 NW 0.47 0.7 2.0 1.74 0.89 0.28 0.1 0.1 6.2 NNW 0.52 0.9 1.5 2.23 1.13 0.21 6.5 Total 8.2 25.7 32.4 20.55 9.8 2.58 0.6 0.1



The maximum wind speed that occurred during this period was 23 m/s and the average is 7.7 m/s. As seen in the table, winds are possible from all directions, but westerly winds are most dominant.

The wind-generated waves tend to be shorter in period and height than compared to the swell waves because unlike swell waves, these do not generally travel over long distances. If the fetch (distance over which the wind blows) is large, then it can produce considerably bigger and longer waves.

The sea (wind) wave component was extracted from the ECMWF model and the distribution of wind waves from the ECMWF is shown in Table 10.

Table 10 Joint distribution of Significant wave height and mean wave direction for wind waves (offshore Portland from ECMWF)

Significant wave height, Hs (m) Direction 0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 Total N 3.24 1.35 0.27 4.87 NNE 2.86 0.59 0.01 3.46 NE 2.75 0.25 3.00 ENE 3.6 0.29 3.89 E- 4.09 1.09 0.19 0.01 5.39 ESE 4.86 1.3 0.18 6.34 SE- 4.72 0.99 0.12 0.01 5.84 SSE 4.6 0.94 0.14 5.68 S 3.93 1.26 0.22 0.11 5.51 SSW- 4.45 1.71 0.47 0.14 0.04 6.80 SW 5.05 1.72 0.79 0.29 0.10 0.04 0.03 8.02 WSW 4.99 2.85 1.46 0.73 0.33 0.22 0.10 0.04 10.71 W 4.54 2.74 1.97 1.05 0.53 0.12 0.03 10.99 WNW 3.91 2.23 1.33 0.36 0.11 7.94 NW 2.96 1.94 0.89 0.29 0.03 6.10 NNW 3.13 1.59 0.64 0.10 5.46 Total 63.68 22.84 8.69 3.08 1.09 0.42 0.15 0.04

4.5 SWAN Model Set-up

As waves propagate from deepwater to near-shore, they shoal and refract due to changes in the bathymetry. In an area where the water depth is greater than around one-half of the wave length (defined as deep water), waves propagate without being affected by the sea bed. When waves enter into a region of shallower water, the direction of propagation gradually shifts and the wave crest lines are bent into the pattern of the depth contours of the sea bed.

The SWAN model is a third-generation stand-alone (phase-averaged) wave model for the simulation of waves in waters of deep, intermediate and finite depth (Booij, 1999). It is also suitable for use as a wave hindcast model. The model is based on the wave action balance equation with sources and sinks.

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 non stationary 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

A nested grid system was set-up to transform the offshore waves to inshore depths in the study area. The inshore waves were then extracted at selected locations for input into sediment transport models. The model grid set-up consists of a large regional grid with a grid spacing of 200 m and a fine grid of 50 m spacing nested within



the coarse grid. Figure 5 shows the extent of areas covered by the model grids. The bathymetry for the fine grid is shown in Figure 6.

Figure 5 Model grid set-up showing the nested fine grid (50 m) within the coarse grid (200 m).



Figure 6 Bathymetry for the fine-grid model.

The joint probability distribution of offshore waves (Table 6) indicates that the range of wave directions is generally between south and north-west and the peak wave periods range between 5 and 18 s (Table 7).

Based on this information, the model runs were set-up for 8 different offshore directions (135, 157.5, 180, 202.5, 225, 247.5, 270, and 292.5 deg N) and 5 different peak wave periods (5, 10, 15, 20, 25 s) thus giving a total of 40 model simulations. A 1 m offshore wave height was adopted for each simulation. The model results extracted from each of the simulations consisted of wave coefficients, wave directions and wave periods at selected locations along the Portland coast. Time-series of wave parameters at each location was constructed using the 11 years continuous time-series of wave parameters from the ECMWF and AUS WAM global wave models and the wave period-direction matrix obtained from the modelling results by record-by-record interpolation.

Bathymetry (m AHD)



4.6 SWAN Model Verification

The SWAN model results were verified by comparison against the measured data at Point Danger. The significant wave heights at Point Danger were extracted from the fine-grid model and the probabilities of exceedances computed and compared with the statistics derived by Lawson & Treloar (1980) study from the wave measurements at Point Danger. Figure 7 shows that there is good agreement between the modelled and measured significant wave heights. Time series of wave data at Point Danger were not available for comparison.

Figure 7 Probability of Exceedance of modelled and measured significant wave heights at Point Danger

0.1

1

10

0.01 0.10 1.00 10.00 100.00

Hs (m

)

Probability of Exceedance (%)

Point Danger

SWAN Model

Measured



4.7 Model Results

The modelled wave parameters were extracted at ten locations along the Portland coast in depths of 5, 10 and 15 m. Figure 8 shows the location of the cross-sections where data were extracted. The 15 m depth contour is located approximately at the seaward end of the cross-sections.

Figure 8 Study area showing locations where model results have been extracted.

A summary of model results is presented in Table 11. The model results show that the wave heights are smaller at the western end of the study area and increase toward the east. The waves from the south reach the coast almost unimpeded. These would refract and shoal as they approach the Minerva reef which is located at approximately 500-800 m offshore of the Portland coast. The average wave directional flux varies from approximately 140 deg (south-east) at the western locations and turning southerly at the eastern locations. This increase of wave heights and the change in wave direction is indicative of an increasing rate of longshore drift toward the east.

Table 11 Summary of wave transformation modelling results

Location Median Hs

Hs exceeded 12 hr/yr

Average Direction

100 yr ARI Hs

(m) (m) (deg N) (m) 1 0.48 2.0 142.6 4.4 2 0.43 2.0 152.5 4.6 3 0.56 2.3 159.7 5.2 4 0.55 2.5 165.3 5.9 5 0.56 2.3 168.6 6.0 6 0.46 2.6 170.8 6.4 7 0.78 2.8 172.6 6.4 8 0.63 2.7 180.1 6.3 9 0.76 3.0 176.6 6.9 10 0.90 3.5 181.3 7.7



The probability of exceedances of significant wave height along the Portland coast at 15 m depth is shown in Figure 9. The wave heights at Portland are lower than those at Point Danger because Point Danger is more exposed to the larger waves from south-west and south-east while the locations along the study area are protected from the south-west waves.

Figure 9 Probability of Exceedance of modelled wave heights at Portland

Table 12 presents the distribution of joint occurrence of significant wave height and wave direction at location 4, Dutton Way, which is one of the critical locations of the study area. The predominant wave direction at this location is from the south-south-east with only small fraction of waves arriving from the south and other directions. The offshore waves applied at the model boundary include the swell and wind waves. The extremely small fraction of wind waves from the northern sector are not included. Typical model output for offshore wave direction of south-south-east is shown in Figure 10. The distributions of wave heights and directions were used to create an annual wave climate which was applied to longshore transport modelling (Section 6).

0

1

10

0.01 0.10 1.00 10.00 100.00

Hs (m

)

Probability of Exceedance (%)

Portland

loc 1

loc 2

loc 3

loc 4

loc 5

loc 6

loc 7

loc 8



Table 12 Joint probability distribution of Hs and wave direction at Dutton Way (location 4) at 15 m depth

Significant wave height, Hs (m) Direction 0.00+ 0.25+ 0.50+ 0.75+ 1.00+ 1.25+ 1.50+ 1.75+ 2.00+ 2.25+ 2.50+ 2.75+ Total N 0.04 0.04 NNE 0.01 0.01 NE 0.02 0.02 ENE 0.01 0.01 E- 0.01 0.01 ESE 0.03 0.03 SE- 0.01 0.02 0.05 0.04 0.13 0.05 0.01 0.07 0.39 SSE 2.47 33.59 33.09 13.59 5.23 2.42 1.29 0.52 0.43 0.22 0.22 0.01 92.97 S 1.79 3.12 0.47 0.01 5.39 SSW- SW WSW W WNW 0.2 0.20 NW 0.73 0.73 NNW 0.2 0.20 Total 5.51 36.71 33.57 13.62 5.29 2.46 1.42 0.57 0.44 0.29 0.22 0.01

Figure 10 Modelled wave vectors (length of vector represents the wave height and the direction represents the wave direction (coming from)

from the fine-grid model for an offshore condition of Hs =1 m, Tp=15 s and Dir = 157.5 deg.

Hs (m)



The yearly maximum significant wave heights were identified from the ten-year time-series of inshore wave parameters at each study location. Extremal analysis was then undertaken to determine the 100 year ARI extreme storm wave heights. These are provided in Table 13. The 100 year ARI storm wave heights were used to generate design storms for beach response modelling (Section 5).

Table 13 Extreme inshore waves at Portland

Location 100 yr ARI Hs (m) 1 4.36 2 4.57 3 5.24 4 5.87 5 6.04 6 6.39 7 6.42 8 6.34 9 6.93 10 7.69



5.0 Erosion due to Cross-Shore Transport Morphological response of the shoreline due to storm wave conditions occurs over relatively short periods (hours to days). This response primarily involves the erosion of the sub aerial beach face through offshore transport and deposition near the storm wave break point to form an offshore bar. It is referred to as the cross-shore or onshore-offshore transport.

The storm waves combined with the storm surge are largely responsible for the short-term erosion of the beach face. While the headlands of Cape Nelson and Point Danger provide a shelter to the study area from the severe south-west waves from the Southern Ocean, it is fully exposed to the south-east waves. The extreme wave and water level conditions as computed in the previous sections have been used as input into the beach response modelling. The model inputs, set-up and results are discussed below.

5.1 Beach and Sediment Data

Beach Profiles at the ten study locations (Figure 8) have been extracted from the DEM based on 2008 and 2009 surveys. Sediment size was determined from grain-size distribution of sediment samples collected from the Portland beach during the site inspection and sent to the laboratory for analysis. Samples were collected from two different locations: 1) from the end of the rock wall approximately 3 m from the wall; and 2) from the sand dune near the Surrey River entrance. Complete report of grain-size analysis is provided in Appendix A. Both samples have a median size of 0.2 mm.

Similar median grain size of 0.2 mm has been reported by Foster (1991) along the Portland coast. The grain-size distribution undertaken by Water Technology (2008) provides a median grain-size of 0.21 mm at the Surrey River mouth.

The ten beach profiles are shown in Appendix B.

5.2 SBEACH Model

SBEACH was employed to predict the beach response and erosion as a result of extreme storm events. SBEACH, an acronym for Storm induced Beach Change was developed at the US Army Engineer Waterways Experiment Station, Coastal and Hydraulics Laboratory (Larson et al, 1990) to calculate beach and dune erosion under storm water levels and wave action. SBEACH is an empirical based program that calculates the net cross-shore sand transport rate in four zones from the dune or beach face, through the surf zone and into the offshore past the deepest break-point bar produced by short period incident waves. The wave model is relatively sophisticated and computes shoaling, refraction, breaking, breaking wave re-formation, wave and wind induced set-up and set-down and run-up.

The SBEACH model was set-up using the profile data from the 2009 DEM. The model input consisted of ten different beach profile shapes extracted at a resolution of 0.5 m for the topographic data and 1 m for the bathymetric data. A median grain size of 0.2 m was adopted for all beach profiles. Figure 11 shows the grain-size distribution near the end of the rock wall. Time-series of water levels, wave height, period and direction and wind speed and direction were input to determine their impact on the current beach profiles.



Figure 11 Particle Size distribution for a sediment sample collected from Portland foreshore (3 m from the end of the rock wall).

5.2.1 Design Storms

Three different design storm events were prepared for input into the SBEACH model. These storms were selected on the basis of their severity. The first one is an actual storm which had an offshore significant wave height with a return period equivalent to 10 years but the 10 year ARI waves persisted continuously for 4 days, coinciding with a spring tide. The remaining two storms are based on 100 year ARI significant wave height combined with 100 year ARI sea level. The three storms are listed below.

1) An actual south-west storm that occurred in November 1994 (Wave, wind and water level data were available and used as input).

2) A 100-year ARI storm using 100 year ARI Hs and 100 year ARI water levels with a duration of 96 hours. The wave height was assumed to increase linearly from 0.5 m to a maximum of 6 m at 48 hours and then gradually reduce back to 0.5 m at 96 hours. A 100 year storm surge was added to a spring tide, the maximum water level was made to coincide with the maximum wave height.

3) Two back to back 100-year ARI storms.

The south-west storm of November 1994 had an offshore wave height of 8.7 m but as the waves refract, diffract and bend around the Portland headland, the wave height is reduced to less than 3 m at the inshore locations along the coast. Lawson and Treloar (1995) reported similar magnitude of modelled waves near the Portland breakwaters as a result of the 1994 storm. Whilst, the offshore 8 m waves persisted for almost four days and were coincident with the spring tide, the storm erosion caused by the south-west waves was significantly smaller than the 100 year ARI storm which had a maximum inshore wave height of approximately 6 m (Figure 12). The third storm has a very low probability of occurrence, therefore it was not considered for further analysis. The recession caused by the 100 year ARI storm was used in the computation of coastal hazard lines.



Figure 12 Input time-series of wave heights, periods and water levels for 100 yr ARI storm to SBEACH model

The predicted shoreline recession and the resulting maximum surface elevation plus wave set-up caused by the 100 year ARI storm at different locations are summarized in Table 14 .

Table 14 Shoreline recession due 100 year ARI storm

Location Storm recession ( m) at 2m AHD

Maximum water elevation + setup (m)

1 22 2.54

2 15 2.46

3 7 2.35

4 10 2.81

5 13 2.43

6 7 2.38

7 22 2.82

s8 13 2.54

9 4 2.43

10 3 2.45 The model simulations have been undertaken with the assumption that the sea-wall does not exist and that it will be severely damaged and over-topped. At present, locations 1-6 are backed by the sea wall. This is a realistic assumption given that currently over-topping has been observed by local residents. The sea-level rise has not been considered in the simulations because it is a gradual process while the erosion due to storms is a short-term event and there is likelihood that the beach will build back to its original shape when calm conditions prevail.

‐0.6

‐0.4

‐0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0

2

4

6

8

10

12

14

16

18

0 20 40 60 80

Water Level (m AHD)

Hs(m)/Tp(s)

Hours after start of Storm

100 year ARI StormHs(m)

Tp (s)

Spring tide + storm surge



The changes in beach profile, occurrence of maximum wave height and the maximum surface elevation plus wave set-up are shown in Figure 13, Figure 14 and Figure 15 at locations 2, 4 and 7.

Figure 13 Predicted change in beach profile, maximum Hs and maximum water elevation + set-up at location 2 caused by the 100 yr ARI storm

The dune recession at 2m AHD is reported as it is more severe than the beach recession at mean sea level and is a realistic indicator of the erosion caused by the severe storms. The changes in beach profile indicate the areas of erosion or deposition. For example, in Figure 13, the entire beach face above mean sea level has been eroded by the storm. The eroded material is then transported offshore and deposited in an offshore bar, approximately 50 – 170 m offshore. This material is then removed over time by the littoral drift transport processes. The subaqueous beach profiles lowers and the nearshore slope steepens up. This makes the dune more vulnerable and during subsequent storms further dune erosion occurs.



Figure 14 Predicted change in beach profile, maximum Hs and maximum water elevation + set-up at location 4 caused by the 100 yr ARI storm

Figure 14 shows that there is 10 m of recession predicted at location 4. The recession above 2m AHD is greater than this, with much of the sand from above the water-line ending up in an off-shore bar approximately 50 – 120m offshore.

The offshore bar at location 4 is significantly larger than at the other locations because of the steeper profile which drops to -3.5 m AHD within a distance of 50 m (slope of 1:14). In comparison, the beach at the other locations has slopes of 1:30 to 1:50 below -1m AHD.

The model results (Table 14) show that the maximum recession of 22 m occurs at locations 1 and 7. The berm height at location 7 is 2.7 m AHD and is overtopped when the maximum surface elevation and set-up increase to 2.8m AHD which is above the height of the berm (Figure 15).

The maximum wave height refers to the maximum wave height over the length of the simulation. As the waves run up the beach slope, they break and the wave height rapidly decreases in height. The water level or surface elevation shown in the plots is the maximum water-level over the length of the storm. This includes the wave set-up. It is generally around 2.5 m AHD at all locations except at location 7 where it reaches 2.8 m AHD.



Figure 15 Predicted changes in beach profile, maximum Hs and maximum water elevation + set-up at Section 7 caused by the 100 yr ARI storm



6.0 Recession due to Longshore Transport The long-term recession at the Portland foreshore has been evaluated by assessing longshore transport rates along the coast in conjunction with the recession rates estimated by historical aerial photographs.

Longshore transport (LST) is the movement of sand approximately parallel to the shore. It occurs when the waves arrive at an oblique angle to shoreline. Variations in the magnitude and direction of longshore transport lead to areas of erosion and accretion as well as changes in beach alignment. Where the LST rate decreases in the direction of longshore transport, accretion will occur. Conversely, where the LST rate increases in the direction of longshore transport, erosion will occur. LST may be a result of natural causes (headlands, sediment influx from rivers, wave, current and wind patterns) or because of man-made structures (breakwaters, jetties, groynes, marinas). On the open beaches of the study area, the LST is predominantly driven by swell.

Longshore computations are usually applied to beach systems assuming that infinite amounts of sand are available for sediment transport. However, real beaches will often not have infinite sources of sand. This is especially valid for the study area where it is believed that erosion has been caused by the lack of sand to maintain the beaches. Most of the sections of the beach along the Portland foreshore have sand available only near low tide. At high tide, the waves run up to the cliff. At some sections, the beach is completely starved of sand and the waves and the water level run up the edge of the cliffs.

In these circumstances computation methods usually calculate the potential to move sand on the basis that sand is there to be moved. Using this assumption as a basis, the sediment transport potential at 10 different sections along the Portland beach was computed using 1) Kamphuis (1991); and 2) LITDRIFT (DHI, 2009). The two methodologies are discussed below:

6.1 Kamphuis, 1991

Kamphuis (1991) developed an empirical formula that calculates the LST as a function of incident waves, beach slope, shore normal, and sediment grain size,

where:

S = longshore sediment transport (m3/s) = density of sea water (kg/m3) s = density of the sand (kg/m3) p = porosity of the sediment Hb = significant wave height at breaking point (m) T = peak period of the spectrum (sec) D50 = median sand grain size (m) b = wave angle at breaking to the seabed contours = beach slope, and L0 = deep water wave length (m)

The Kamphuis formulation is a simple calculation based on field studies. It only takes into account wave breaking but neglects bed friction, refraction and shoaling. LST has been computed at the ten locations within the study area (Figure 8). An annual wave climate (based on SWAN wave modeling results) and varying beach slopes were used to calculate the total annual longshore transport at each section of the beach.

Sp

H

T

H

L

H

Ds

b b

o

bb

13 10

12

3 3 1 25

0 75

50

0 25

0 6.

( )tan ( ) sin

.

.

.

.x

(1)



6.2 LITDRIFT (Danish Hydraulic Institute)

The methodology used by the software developed by Danish Hydraulic Institute (DHI, 2009) to compute LST is much more comprehensive than Kamphuis (1991) as it considers non-uniform friction, full beach profile, shoaling, breaking, refraction, wave setup caused by radiation stress, wind and residual current. The sediment transport module, LITDRIFT is a one-dimensional model that computes the cross-shore distribution of the long shore current, wave height and set-up for a particular coastal profile by solving the long and shore momentum balance equations. Waves can be specified as regular/irregular, unidirectional/directional. LST is computed at each specified point in the profile and interpolated and integrated across the profile. Wave input can consist of a single wave condition, time-series of wave conditions or an annual wave climate where the duration of wave incidence is given as a fraction of a year.

For the present study, the percentage occurrence of various wave heights from the wave modeling was used to calculate the duration of that particular wave height. The wave modeling shows that the 90-95% of the waves arrive from the south-south east. Hence a single averaged wave direction for each location was used as input to the model. The shore-normal, average wave direction and percentage occurrence of various wave heights at different locations are presented in Table 15. For example at Location 4, the probability of occurrence of 1 m wave height is 1.87%. The waves at location 4 are assumed to always arrive from 161 deg N. The wave period was assumed to vary between 12 and 15 s. A grid size of 5 m was used to define the coastal profile. Care was taken such that the slope of the beach face was accurately defined and was not smoothed over the 5 m grid. All computations were undertaken at mean sea level. The shore-normal i.e. the angle (relative to north) perpendicular to the shoreline was determined by measuring the angle using the shoreline extracted from the DEM.



Table 15 Input wave conditions to LITDRIFT

Loc 1 Loc 2 Loc 3 Loc 4 Loc 5 Loc 6 Loc 7 Loc 8 Loc 9 Loc 10 Shore-normal (deg N) 135 144 145 152 148 150 150 148 148 148 Avg wave direction (deg N) 140 152 160 161 164 171 166 169 165 171 Hs (m) Percentage occurrence 0.1 1.486 1.617 1.363 1.494 1.442 1.477 1.486 1.398 1.494 1.433 0.2 2.989 7.437 1.171 4.570 1.879 2.508 2.735 1.398 2.561 1.861 0.3 12.995 24.836 6.729 17.487 7.454 9.193 8.468 4.833 7.419 4.719 0.4 21.454 26.872 15.171 22.616 14.044 15.547 12.392 8.888 12.374 8.110 0.5 20.965 17.801 18.125 19.165 16.333 16.919 13.388 11.754 14.778 10.102 0.6 15.704 9.246 16.980 12.645 15.136 14.402 12.846 12.339 13.694 10.775 0.7 9.884 4.509 13.187 7.516 12.523 11.361 11.282 11.859 12.401 10.749 0.8 5.348 2.534 9.123 4.090 9.316 7.944 9.071 10.801 8.748 9.569 0.9 3.164 1.547 5.776 2.875 6.205 5.095 6.694 8.687 6.913 8.389 1.0 2.071 0.874 3.434 1.870 4.090 3.548 5.007 6.851 4.474 6.930 1.1 1.215 0.638 2.482 1.223 2.954 2.543 3.452 4.841 3.225 5.497 1.2 0.839 0.472 1.765 0.970 2.176 1.879 2.788 3.697 2.604 4.221 1.3 0.437 0.288 1.232 0.717 1.669 1.599 2.141 2.674 2.089 3.417 1.4 0.419 0.323 0.830 0.542 1.267 1.005 1.888 2.054 1.617 2.639 1.5 0.253 0.262 0.629 0.446 0.926 1.014 1.486 1.757 1.188 2.071 1.6 0.288 0.227 0.559 0.446 0.673 0.647 0.918 1.337 0.848 1.590 1.7 0.140 0.149 0.245 0.218 0.559 0.594 0.839 0.970 0.673 1.564 1.8 0.166 0.096 0.218 0.184 0.306 0.559 0.629 0.900 0.787 1.293 1.9 0.035 0.105 0.262 0.210 0.253 0.463 0.690 0.647 0.481 0.935 2.0 0.044 0.026 0.245 0.227 0.218 0.367 0.419 0.498 0.350 0.743 2.1 0.044 0.044 0.105 0.131 0.166 0.262 0.367 0.402 0.297 0.664 2.2 0.017 0.044 0.114 0.087 0.149 0.184 0.218 0.323 0.227 0.507 2.3 0.017 0.026 0.096 0.096 0.114 0.166 0.210 0.218 0.218 0.516 2.4 0.017 0.000 0.044 0.070 0.044 0.157 0.166 0.218 0.079 0.332 2.5 0.017 0.061 0.035 0.079 0.149 0.070 0.105 0.105 0.323 2.6 0.017 0.044 0.009 0.096 0.096 0.166 0.114 0.201 2.7 0.017 0.000 0.009 0.105 0.070 0.096 0.087 0.157 2.8 0.009 0.017 0.079 0.052 0.096 0.061 0.140 2.9 0.052 0.052 0.070 0.026 0.096 3.0 0.035 0.017 0.070 0.035 0.096 3.1 0.035 0.026 0.026 0.026 0.061 3.2 0.000 0.026 0.009 0.061 3.3 0.009 0.009 0.052 3.6 0.009 0.052 3.7 0.009 0.044 4.8 0.009 0.009 0.035 5.0 0.009 6.0 0.009 0.017 6.1 0.009 0.009 6.3 0.009 0.017



6.3 Results

The two methods used to compute LST produce very similar results as shown in Table 16. Both indicate that the sediment transport at Portland is from the west to the east and the LST potential increases gradually from the west to the east. Larger rates of LST occur due to the refraction of approaching waves which arrive at the eastern locations at an angle less oblique to the offshore contours than at the western locations. Larger angles of wave breaking at the offshore contours will produce large rates of LST than the smaller angles.

Table 16 LST potential rates along the Portland coast

Location LITDRIFT m3/year

Kamphuis m3/year

1 42,000 44,000 2 27,000 22,000 3 97,000 74,000 4 61,000 46,000 5 122,000 143,000 6 136,000 112,000 7 159,000 277,000 8 352,000 321,000 9 208,000 303,000 10 372,000 363,000 Average 156,200 172,000

Longshore transport computations by CES (2002) using the Kamphuis formulation indicate that the transport capacity is more or less the same (about 50,000 m3 per year) at all locations along the Portland foreshore except for Nun’s Beach which does not have any sediment transport capacity and Anderson’s point (start of Dutton Way) which has a transport capacity of 100,000 m3 per year. These estimates are significantly lower than the estimates from the current study. It is not known whether the CES computations were based on measured profiles or low resolution data extracted from hydrographic charts. Summary of wave statistics at various Portland foreshore locations were not available from the CES study, therefore, it is not possible to interpret the differences in LST between the CES and the current study.

The current study uses measured beach profiles and a realistic wave climate from a verified SWAN wave model. LITDRIFT is considered to be a reliable and useful tool for coastal study applications and has been used worldwide for the computations of LST. To gain confidence in the model results, the LST results from the present study have been compared with recent hydrographic surveys at the Port of Portland. In addition, the rates of shoreline recession derived from the computed LST have been compared with those estimated from aerial photographs thus providing confidence in the reliability of these results.

A study of the volume of breakwater siltation at Portland Harbour (Marine Laboratory, 1987) estimated that the breakwaters had trapped approximately 1.5 million cubic meters of sand at an average rate of 48,500 m3 per year since their construction (Foster, 1991). Analysis of the recent bathymetric surveys (March 2005 to May 2007) by the Port of Melbourne Corporation show that a total volume of 147,000 m3 of sand has accreted around the main breakwater and within the harbour over a period of two years. There is significant erosion behind the breakwater which is likely to be caused by the waves breaking over the accumulated sand. The accretion estimated from this survey is not indicative of the total volume of sand blocked by the breakwater due to the fact that the survey area was limited to 400 m from the breakwater. There is ample evidence (from aerial photos, anecdotal evidence, Google earth etc) that sand accumulation extends to almost 1 km from the main breakwater. In order to estimate the volume of sand blocked, it was deemed realistic to assume that the volume of sand accumulated would be at least twice as that estimated in a small area covered by the survey. This would lead to a total accumulated volume of about 146,000 m3 per year. This means that the breakwater has trapped a volume of sand on the order of 150,000 m3 which would have been otherwise available to be transported to the Portland beaches. This is in close agreement with the average value of 156,000 m3 of LST potential estimated by LITDRIFT.



6.4 Recession Rates from LST

The recession rates from the longshore transport were computed on the basis of the conservation equation of sediment in a control volume or shoreline reach, and a bulk longshore sand transport equation (CEM, 2006). It is assumed that the beach profile shape moves in the cross-shore direction between two limits defined by the offshore closure depth and the berm height which is upper end of the active profile. This implies that sediment transport is uniformly distributed over the active portion of the profile. The incremental volume of sediment in a reach is simply:

(B +d)ΔxΔy (2)

where:

B = berm height d = closure depth Δx = the reach of shoreline segment, Δy = the cross-shore displacement of the profile

The berm heights for each location were determined from the measured beach profiles and the closure depth was computed using Hallermeier (1981, 1983) procedure. The closure depth is the depth at the seaward extent of measurable cross-shore movement of beach sand.

Hallermeier defines a simple zonation of an onshore-offshore beach profile consisting of a littoral zone, shoal zone or buffer zone, and offshore zone where surface wave effects on the bed are negligible. According to Hallermeier, the seaward depth of the active beach profile lies within the shoal zone.

Based on an analytical approach, supported by laboratory data and some field data, the two water depths bounding the shoal zone, defined by ds and do are given by:

22

5.0 1

110

1

9.2

gTS

H

S

Hds

(3)

where: ds= water depth bounding the littoral and shoal zones H = significant wave height exceeded 12 hours per year T = associated wave period S = specific gravity of the sediment, and G = acceleration due to gravity; and

5.0

501018.0

DS

gTHd medmedo

(4)

Where

do = the depth at the boundary of the offshore zone D50 = is the median grain size H and T are the median significant wave height and period parameters

The inner littoral zone was considered as the active zone for the study area because of the presence of Minerva reef in shallow waters off the Portland foreshore. The reef is found in depths of 4-6 m at a distance of 400-800 m from the shoreline. The rocky outcrops of the reef retard any sediment movement over it. Therefore Equation (3) was used to compute the closure depth at various locations. Equation (2) was then applied to obtain the recession rates at each location of the study area. Table 17shows the closure depth and the berm heights used for the computation of LST.



Table 17 Closure depths and berm heights at the study locations

Location Closure depth (m) Berm height

(m) 1 4.4 3.2 2 4.4 3.5 3 5.0 4.5 4 5.5 5.0 5 5.1 3.0 6 5.7 3.5 7 6.0 2.7 8 6.0 3.5 9 6.5 4.0 10 7.5 4.0

The recession was then calculated using an average rate of potential sediment transport across the entire study area (Δx = 10 km). Similarly an average berm height and an average closure depth were then used to compute the average rate of recession (Δy).

An average rate of recession of 1.8 m per year is estimated using LST from both LITDRIFT and Kamphuis.

6.5 Aerial Photography - Photogrammetry

Historical changes in the position of shoreline indicate where the coast is receding and where it is accreting. Analysis of aerial photographs using photogrammetry where the shoreline is identified by means of cliff lines, water line or vegetation line provides a good indication of shoreline movements over the past several years.

Photogrammetry is a technique for mapping ground terrain from vertical aerial photography. It allows the surface elevation of the subaerial beach (the portion of the beach above the water line) to be measured along transect lines on the beach. The technique has been used for many years to produce topographic maps and is a useful tool for analysing changes to subaerial beach profiles over time, particularly as historical aerial photography often spans many decades. The technique cannot be used, however, to analyse changes to the beach profile below the water line and is thus limited to analysing only part of the total littoral system.

For the current study, aerial photographs of 1972, 1977, 2003 and 2009 were geo-referenced into the GIS and analysed. The shoreline was identified as the vegetation line for all photographs except 2009 where LIDAR data was available. In this case, the +2m AHD contour was taken as representative of the shoreline. The shoreline positions at different years from a “baseline” year were determined and are presented in Table 18. The extracted shoreline near cross-section 5 from the various aerial photographs is shown in Figure 16 to Figure 19.



Table 18 Differences in shoreline position from aerial photographs

Rate of recession m per year

Location 1972 1977 2003 2009 2009-2003 2009-1977 2009-1972

1 baseline 6 1.00

2 baseline 7 1.17

3 baseline 14 2.33

4 baseline 25 4.17

5 baseline 0 5 25 3.33 0.78 0.68

6 baseline 10 21 34 2.17 0.75 0.92

7 baseline 40 53 2.17 1.66

8 baseline -9 4 2.17 0.125

9 baseline 23 -21 -7.33 -0.66

10 baseline N/A -66

Note: Baseline is the initial year from which the shoreline distance at subsequent years has been measured

The average rates of recession between 1972 and 2009 were computed and are presented in Table 18. The shoreline was observed to recede at all locations except 9 and 10 which are located near the river mouth. This could be due to the periodic opening and closing of the entrance which may cause a buildup of sand at the mouth.

Figure 16 1972 Coastline








6.6 Discussion

The recession rates estimated by aerial photography are presented in

Table 19.

Table 19 Long-term shoreline recession (m per year)

Location Recession

rate m/yr

1 1.0 2 1.2 3 2.3 4 4.2 5 1.6 6 1.3 7 1.9 8 1.1 Average 1.82

It is interesting to observe that the rate of recession calculated from the aerial photos and the longshore drift is almost the same. While the estimates of longshore drift are subject to some uncertainty (arising from assumptions of sand availability, uniform grain size, directional spread of waves, bed friction etc), the recession rate calculated from the aerial photos provides a reliable indication of the extent of historical shoreline movement. It is acknowledged that seasonal fluctuations are not considered, but with the availability of photographs dating back to almost 40 years, it is believed that most of the fluctuations would have been smoothed out.



The historical recession shows that the largest shoreline movements occur between locations 3 and 7 (between Rosslyn Street and Schnapper Point). Moore Drive and Kiernan Ave (located near locations 3, 4 and 5) were completely lost when the shoreline receded more than 50 m between 1977 and 2009. Foster (1991) reports that the shoreline at Henty Bay suffered severe erosion and receded 120 m over a 40-year period between 1950 and 1991. This is equivalent to a recession rate of 3 m per year. Recession rates of 2 m per year at Henty Bay were estimated in a recent study by Nyugen et al (2008) who used photogrammetry and statistical techniques to compute the rate of change of shoreline movement. The shoreline data used in this study comprised of aerial photographs from 1966, 1967, 1972, 1976, 1977, 1981, 1986 and 1992 and covered a 2-km segment of Portland cost from the east end of the basalt rock cover to Monaghan’s place in Henty Bay Estate. The shoreline recession between 1986 and 1992 was determined to be 11m and 15 m respectively at the two transect locations close to Monaghan’s place.

The rates of LST and the shoreline recession as a result of long-term coastal processes computed for this study are in good agreement with those estimated from previous studies, aerial photography and measured volumes of sediment trapped by the breakwater at Portland harbour.

A recent study by CES (2007) indicates that the western end of Portland coast (locations 1-4) have accreted between 2004 and 2007 while the eastern end has suffered erosion. However this is likely to be temporary accretion due to the sand-by passing that CES reports as 240,000 m3 of sand from behind the breakwaters of the Port to Andersons Point in 1994/95 and a further 222,000 m3 between 1997 and 2007. The analysis by CES consisted of computing vertical differences in bed-levels from measured beach profiles at 50 m from the back of beach or sea wall. The beach profiles were surveyed once or twice a year between 2004 and 2007. The study did not report any horizontal accretion or recession. It is probable that the computed “vertical” changes in bed-level at the specified location in the beach profile were not representative of the “horizontal recession” of the shoreline. The current beach profiles measured in 2009 show that the slope of the sea wall is approximately 1V:2H and the bed-level at about 50 m from the back of the sea wall is about -1 m AHD or below MLLW at the western locations. The rates of recession at bed-levels at low water can differ significantly to those at mean sea level or high water. Since the CES report does not present any plots of the differences in bed levels of the entire bed profiles, it is not possible to ascertain at what levels the reported accretion is taking place and whether similar rates of accretion were observed at other sections of the beach profile.



7.0 Recession due to Sea-level Rise Any sea level rise has the potential to cause recession of unconsolidated shorelines if the beach profile is in equilibrium with the prevailing wave climate. Bruun (1962, 1983) investigated the long term erosion along Florida’s beaches, which was assumed to be caused by a long term sea level rise. Bruun hypothesised that the beach assumed a profile that was in equilibrium with the incoming wave energy. Accordingly, with a rise in sea level the profile would adjust, without changing its shape, by an upward translation of sea level rise (S) and shoreline retreat (R), as shown in Figure 20.

Figure 20 Schematic representation of the Bruun Rule.

The Bruun Rule equation is given by:

LBh

SR

c /

(5)

where:

R = shoreline recession due to sea level rise; S = sea level rise (m) h = closure depth B = berm height; and L = length of the active zone.

The closure depth has been defined in the previous section and the length of the active zone is the distance offshore along the profile in which sand movement still occurs.

The Bruun Rule is simplistic in that it predicts that the recession (R) is equal to the sea-level rise divided by the slope of the active nearshore bed profile. Due to its simplicity and lack of easy-to-use alternatives, coastal scientists and engineers have been using Bruun Rule for almost five decades. The effective application of Bruun Rule is possible if the assumptions underlying the Bruun Rule are managed and justified. The assumptions of Bruun are:

1) The beach profile is in an equilibrium state

2) All sand transport occurs perpendicular to the coastline (cross-shore transport)

3) Uniform slope and sediment size along the profile

4) Only unconsolidated material is present



For the purposes of the current study, the beach profiles along the Portland foreshore were compared with the equilibrium profile (Figure 21). The equilibrium profile was developed in accordance with Bruun (1954) who proposed a simple power law to describe the equilibrium profile, being the relationship between water depth, h, and offshore distance, x, measured at the mean sea level thus:

3

2

Axh

Where

A = a dimensional shape factor, mainly dependent on the grain size

x = the offshore distance (m)

h = the water depth (m)

Figure 21 Selected measured beach profiles and Equilibrium profile.

It was found that the 2009 beach profiles were similar to the equilibrium profile in depths of less than 4 or 5 which is about the same as the computed depth of closure of the beach profiles. The length of the active zone is within 200 to 300 m from the shoreline. The Minerva reef lies at a distance greater than 500 m from the coast and is thus not included in the profile which is subject to Bruun Rule. In this study, Bruun Rule is used to estimate only the cross-shore transport; therefore assumption (2) is satisfied. The long term longshore transport has been estimated separately using sediment transport models and verified by aerial photography. The longshore computations are based on measured beach profiles and a median grain-size from grain size analysis. While the sediment size is assumed to be uniform along the profile, the sediment is graded into a number of fractions, the calculation of which is based on a log-normal grain curve characterized by the median grain diameter.

The depth of closure and the berm height used as input into Bruun Rule is given in Table 17. The length of the active profile varies from 150 m to 400 m at the different locations. The application of Bruun Rule implies that there is no sea wall. This is a realistic assumption given that the sea wall continues to suffer damage due to scour and erosion. In the absence of maintenance or repairs, it is highly likely that the sea wall will be further damaged, disintegrated and overtopped by the high sea-level rise.

‐6

‐5

‐4

‐3

‐2

‐1

0

1

2

3

4

5

6

0 50 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800

Bed level (m AHD)

Distance offshore (m)

sec1

sec2

sec4

sec8

Equilibrium



The sea-level rise has been adopted as 0.82 m by 2100, 0.47m by 2070 and 0.146m by 2030. Details of sea-level rise and climate change scenarios are discussed in a separate section of this report. The results of the application of Bruun Rule for the next 20, 60, and 90 years are presented in Table 20.

Table 20 Predicted shoreline recession in 2100, 2070 and 2030

Location

Recession (m) Bruun Rule Projected year

2100 2070 2030

1 27 16 5

2 19 11 3

3 20 12 4

4 12 7 2

5 20 12 4

6 22 12 4

7 23 13 4

8 23 13 4

9 31 18 6

10 24 14 4

The shoreline is predicted to recede by up to 31 m in 2100. The recession by 2070 is expected to be between 7 and 18 m and the shoreline is predicted to recede by up to 6 m by 2030. The Bruun Rule factor which is expressed as L/(hc+B) ranges from 15 to 38. Brunn factors of 24 to 70 have been determined by previous studies in Narrawong and Port Fairy. This is indicative of the wide range of variation in the application of Bruun Rule.

Water Technology (2009) used Bruun Rule to compute a shoreline recession of 19-56 m by the year 2100 near the Surrey River mouth. These estimates were based on a 0.8 m sea-level rise by the year 2100, and assumed values of depth of closure of 2.0 m and active length of profile (100 and 300 m).

A panel and advisory committee report on the planning scheme of east beach at Port Fairy provides estimates of shoreline recession due to Bruun Rule between 28-34 m based on a sea-level rise of 0.8 m.



8.0 Coastal Hazard Lines The coastal hazard lines or zones define the area enclosed by the zone that is subject to coastal erosion and recession. Any land, infrastructure or assets situated within the coastal hazard zone are under threat of damage and/or complete loss.

The coastal hazard lines have been calculated for the purpose of planning purposes only. These should be considered as allowances for setbacks for erosion and recession and comprise of the following components:

A. Recession due to cross-shore transport (SBEACH)

B. Recession due to longshore transport (LITDRIFT)

C. Recession due to sea level rise (Bruun Rule)

Allowance for recession due to cross-shore transport (storm erosion) was determined from SBEACH modeling (it is the same for 2100, 2070, and 2030); allowance for recession due to longshore transport (long term erosion) was calculated by evaluating long shore transport rates using LITDRIFT and photogrammetry; and recession due to sea level rise was assessed using the Bruun Rule. A summary of coastal recession by the three components is given in Table 21.

Table 21 Shoreline Recession due to Storm events, longshore transport and Bruun Rule

Location A

(m) B

(m) C

(m) Projected year

2100, 2070, 2030

2100 2070 2030 2100 2070 2030

1 22 162 108 36 27 16 5

2 15 162 108 36 19 11 3

3 7 162 108 36 20 12 4

4 10 162 108 36 12 7 2

5 13 162 108 36 20 12 4

6 7 162 108 36 22 12 4

7 22 162 108 36 23 13 4

8 13 162 108 36 23 13 4

9 4 162 108 36 31 18 6

10 3 162 108 36 24 14 4

The coastal hazard lines are thus computed as: A+B+C and are presented in Table 22 and Figure 22.

Table 22 Coastal Hazard Lines (m from existing coast line)

Location Distance (m) from the existing shoreline Projected year

2100 2070 2030

1 211 146 63 2 196 134 54 3 189 127 47 4 183 124 48 5 195 133 53 6 191 127 47 7 207 143 62 8 197 134 53 9 197 130 46 10 189 125 43

PRINCES HIG

HWAY

HEN

TY H

IGHW

AY

PORTLAND (3KM)Û

WESTLAKES ROAD

WINDHAM STREET

WIL

SO

NS

RO

AD

BO

YE

RS

RO

AD

THE ESPLANADEVAUGHAN STREET

DUTTO

N WAY

CARAVAN PARK ROAD

OCEAN VIEW DRIVE

RIVETTS ROAD

KEILLERS ROAD

COATESRO

AD

CALEDONIAN HILL ROAD

ROBERTSONS ROAD

CA

LED

ON

IAN

RO

AD

CROWES ROAD

KEILLERS BEACH

ROAD

BE

RR

YS

RO

AD

NASHS ROAD

GORAE ROAD

EVANS ROAD

PENNYS ROAD

LEVETTS ROAD

HA

WK

INS

LAN

E

MAT

HESO

N

STREET

GR

EAT

SO

UT

H W

ES

TW

AL

K

PRIN

CES

HIG

HW

AY

SURRYRIVER

BOLWARRA

NARRAWONG

ALLESTREE

S T U D Y AR E A E

X T E N T

0 500 1,000 1,500250

metres

´

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PROJECT ID

LAST MODIFIEDCREATED BY

60148113LFLF 17 MAY 2010

LEGEND

Study Area ExtentCadastreProperties Impacted by Hazard Areas

HAZARD LINES2009 Baseline2030 Coastal Erosion Risk2070 Coastal Erosion Risk2100 Coastal Erosion Risk2030, 2070 & 2100 Flooding

HAZARD AREAS2030 Coastal Erosion2030 Coastal Erosion & Flooding2030 Flooding2070 Coastal Erosion2070 Coastal Erosion & Flooding2100 Coastal Erosion2100 Coastal Erosion & Flooding

HYDROGRAPHYMajor WatercourseMinor WatercourseMinor Channel/DrainLakeWetland/SwampSubject to Innundation

DATUM GDA 1994, PROJECTION MGA ZONE 54

Overview of Coastal Erosion and Flooding Risks

Data sources:Base Data: (c) DSE 2009, GHCMA(data source)

Map Document: (P:\60148113\4_Tech_work_area\4.7_GIS\06_Maps\M035)

22Figure

Client: Glenelg Shire Council

PORTLAND COASTAL ENGINEERINGSTUDY - COASTAL EROSION

V I C T O R I AV I C T O R I A

N S WN S W

MELBOURNESTUDY AREA

PORTLAND!( !( WARRNAMBOOL

!(GEELONG

!(

HAMILTON

SA

SA



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9.0 Glossary Accretion The accumulation of (beach) sediment, deposited by natural fluid flow processes.

ACES A computer program, developed by the US Army Corps of Engineers, that is used to determine extreme waves, wave run-up, wave transformation, littoral processes and coastal structural design.

Astronomical tide

The tidal levels and character which would result from gravitational effects, e.g. of the Earth, Sun and Moon, without any atmospheric influences.

Bar An offshore ridge or mound of sand, gravel, or other unconsolidated material which is submerged (at least at high tide), especially at the mouth of a river or estuary, or lying parallel to, and a short distance from, the beach.

Bathymetry The measurement of depths of water in oceans, seas and lakes; also the information derived from such measurements.

Beach profile A cross-section taken perpendicular to a given beach contour; the profile may include the face of a dune or sea wall; extend over the backshore, across the foreshore, and seaward underwater into the nearshore zone.

Berm A nearly horizontal plateau on the beach face or backshore.

Breaker zone The zone within which waves approaching the coastline commence breaking, typically in water depths of around 2 m to 3 m in fair weather and around 5 m to 10 m during storms

Breaking depth The still-water depth at the point where the wave breaks.

Coastal processes

Collective term covering the action of natural forces on the shoreline, and the nearshore seabed.

Datum Any position or element in relation to which others are determined, as datum point, datum line, datum plane.

Deep water In regard to waves, where depth is greater than one-half the wave length. Deep-water conditions are said to exist when the surf waves are not affected by conditions on the bottom, typically in water depths of around 60 m to 100 m.

Dunes Accumulations of wind-blown sand on the backshore, usually in the form of small hills or ridges, stabilised by vegetation or control structures.

Dynamic equilibrium

Short term morphological changes that do not affect the morphology over a long period.

Elevation The distance of a point above a specified surface of constant potential; the distance is measured along the direction of gravity between the point and the surface.

Erosion On a beach, the carrying away of beach material by wave action, tidal currents or by deflation.

Geomorphology That branch of physical geography that deals with the form of the Earth, the general configuration of its surface, the distribution of the land, water, etc.

High water (HW) Maximum height reached by a rising tide. The height may be solely due to the periodic tidal forces or it may have superimposed upon it the effects of prevailing meteorological conditions. It is also called the high tide.

Inshore (1) The region where waves are transformed by interaction with the sea bed.

(2) In beach terminology, the zone of variable width extending from the low water line through the breaker zone.

Littoral (1) Of, or pertaining to, a shore, especially a seashore.

(2) Living on, or occurring on, the shore.

Littoral drift The material moved parallel to the shoreline in the nearshore zone by waves and currents.

Littoral transport

The movement of littoral drift in the littoral zone by waves and currents. Includes movement both parallel (long shore drift) and perpendicular (cross-shore transport) to the shore.

Longshore Parallel and close to the coastline.

Longshore drift Movement of sediments approximately parallel to the coastline.

Low water (LW) The minimum height reached by each falling tide, also called low tide.

Mean high water (MHW)

The average elevation of all high waters recorded at a particular point or station over a considerable period of time, usually 19 years. All high water heights are included in the average where the type of tide is either semidiurnal or mixed. Only the higher high water heights are included in the average where the type of tide is diurnal.



Mean high water springs (MHWS)

The average height of the high water occurring at the time of spring tides.

Mean low water (MLW)

The average height of the low waters over a 19-year period. For shorter periods of observation, corrections are applied to eliminate known variations and reduce the result to the equivalent of a mean 19-year value.

Mean low water springs (MLWS)

The average height of the low waters occurring at the time of the spring tides.

Mean sea level The average height of the surface of the sea for all stages of the tide over a 19-year period, usually determined from hourly height readings.

Morphology The form of a river/estuary/lake/seabed and its change with time.

Nearshore In beach terminology, an indefinite zone extending seaward from the shoreline well beyond the breaker zone.

Refraction The process by which the direction of a wave moving in shallow water at an angle to the bottom contours is changed. The part of the wave moving shoreward in shallower water travels more slowly than that portion in deeper water, causing the wave to turn or bend to become parallel to the contours.

Rip current A strong current flowing seaward from the shore. It is the return of water piled up against the shore as a result of incoming waves. A rip current consists of three parts: the feeder current flowing parallel to the shore inside the breakers; the neck, where the feeder currents converge and flow through the breakers in a narrow band or "rip"; and the head, where the current widens and slackens outside the breaker line.

Runup The rush of water up a structure or beach on the breaking of a wave. The amount of run-up is the vertical height above still water level that the rush of water reaches. It includes wave setup.

SBEACH A computer program, developed by the US Army Corps of Engineers, that is used to determine, among other things, wave transformation across the surf zone, beach and dune erosion and levels of wave runup on natural beaches.

Setup Wave setup is the elevation of the nearshore still water level resulting from breaking waves and may be perceived as the conversion of the wave’s kinetic energy to potential energy.

Shoal (1) (noun) A detached area of any material except rock or coral. The depths over it are a danger to surface navigation.

(2) (verb) To become shallow gradually.

Shoreface The narrow zone seaward from the low tide shoreline permanently covered by water, over which the beach sands and GRAVELS actively oscillate with changing wave conditions.

Shoreline The intersection of a specified plane of water with the shore.

Significant wave height

Average height of the highest one-third of the waves for a stated interval of time.

Spring tide A tide that occurs at or near the time of new or full moon, and which rises highest and falls lowest from the mean sea level (MSL).

Storm surge A rise or piling-up of water against shore, produced by strong winds blowing onshore. A storm surge is most severe when it occurs in conjunction with a high tide.

Sub-aerial beach

That part of the beach which is uncovered by water (e.g. at low tide sometimes referred to as drying beach).

Surf zone The nearshore zone along which the waves become breakers as they approach the shore.

Swell Waves that have traveled a long distance from their generating area and have been sorted out by travel into long waves of the same approximate period.

Tide The periodic rising and falling of the water that results from gravitational attraction of the moon and sun acting upon the rotating earth. Although the accompanying horizontal movement of the water resulting from the same cause is also sometimes called the tide, it is preferable to designate the latter as tidal current, reserving the name tide for the vertical movement.



10.0 References Booij, N., Ris, R.C, and Holthuijsen, L.H (1999). A third-generation wave model for coastal regions, Part I, Model description and validation, Journal of Geophysical Research, 104, C4, 7469-7666.

Bruun, P.M. (1954). Coast erosion and the development of beach profiles, Technical Memorandum 44, US Army Beach Erosion Board, June 1954.

Bruun, P.M (1962). Sea Level Rise as a cause of beach erosion, Proceedings ASCE Journal of the Waterways and Harbours Division, Volume 88, WW1, pp 117-130, American Society of Civil Engineers.

Bruun, P.M. (1983). Review of conditions for uses of the Bruun Rule of erosion, Journal of Coastal Engineering,7, No. 1, 77-89.

CEM (2006). Coastal Engineering Manual, US Army Corps of Engineers, Waterways Experiment Station, Coastal Engineering Center, Vicksburg, MS.

Coastal Engineering Solutions (CES) 2007. Port of Portland Advice Regarding Sand Disposal North of Anderson Point. Unpublished report prepared by CES for Port of Portland, November 2007.

Coastal Engineering Solutions (CES) 2002. Assessment and Management of Coastal Processes within Portland Bay: Coastal Processes Modelling. Unpublished report prepared by CES, 2002.

DHI (2009). Modelling software developed by Danish Hydraulic Institute (DHI), Denmark.

Foster, D.N (1991). Henty Bay Erosion by DN Foster, report no UT 91-11, Unisearch limited Tasmania, Nov 1991

Hallermeier, R. J. (1981). A profile zonation for seasonal sand beaches from wave climate, Coastal Engineering, 4, 253-277.

Hallermeier, R. J. (1983). Sand Transport limits in coastal structure design, Proceedings Coastal Structures ’83, ASCE, 703-716.

McInnes, K.L., Macadam, I., Hubbert, G.D., and O’Grady, J.G. (2009): A Modelling Approach for Estimating the Frequency of Sea Level Extremes and the Impact of Climate Change in Southeast Australia. Natural Hazards DOI 10.1007/s11069-009-9383-2.

Kamphuis, J. W. (1991). Alongshore sediment transport rate, Journal of Waterways, Port, Coastal and Ocean Engineering, ASCE, 117(6), 624-641.

Larson, M., Karus, N.C and Byrnes, M.R (1990). SBEACH:Numerical model for simulating storm-induced beach change, report 2: Numerical formulation and model tests, Technical report CERC-89-9, US Army Corps of Engineers, Waterways Experiment Station, Coastal Engineering Center, Vicksburg, MS.

Lawson and Treloar Pty Ltd (1995). Waves off Portland Harbour, unpublished report prepared by Lawson and Treloar for Maunsell Pty Ltd, report NoJ5036/R1590, August 2005.

Lawson and Treloar Pty Ltd, (1980). Portland Victoria – Wave Statistics, unpublished report prepared by Lawson and Treloar for Portland Harbour Trust Commissioners..

NCCOE, National Committee on Coastal and Ocean Engineering, Engineers Australia (2004). Guidelines for Responding to the Effects of Climate Change in Coastal and Ocean Engineering. The Institution of Engineers Australia

Nguyen, T, Peterson, J, Gordon-Brown, L., and Wheeler, P (2008). Coastal Changes Predictive Modelling: A Fuzzy Set Approach, World Academy of Science, Engineering and Technology, 48, ISSN 2070-3724.

Panel and Advisory Committee Report (2009). Moyne Planning Scheme Permit Application PL04/232, Residential Subdivision East Beach, Port Fairy. Unpublished report prepared by the panel for the Minister for Planning and Environment. June 2009.

Shore Protection Manual. (1984). 4th ed., 2 Vol, U.S. Army Engineer Waterways Experiment Station, U.S. Government Printing Office, Washington, DC.

SMEC (2006). Coastal Zone Management Study and Plan, Callala Beach, Coastal Hazard Study, report prepared by Snowy Mountains Engineering Corporation (SMEC) for Shoalhaven City Council, Document No. 3001209-002, May 2006.



Water Technology (2009) Coastal Vulnerability and Flood Risk Assessment – Lot 18 The Esplanade, Narrawong, Report No. J1270_R02v01, unpublished report prepared for Alpeggio Veduta Pty Ltd, September 2009.

Water Technology (2008): Surrey River Estuary Flood Study, Report No. J543/R03, unpublished report prepared by Water Technology for Glenelg Hopkins CMA, July 2008.

WRL (2008). Coastal Processes, Coastal Hazards, Climate Change and Adaptive Responses for Preparation of a Coastal Management Strategy for Clarence City, Tasmania, unpublished report prepared by Water Research Laboratory (WRL), University of New South Wales School of Civil and Environmental Engineering, technical report 2008/04, October 2008.

AECOMCoastal Spaces - Inundation and Erosion - Coastal Engineering StudyPortland Coastal Engineering Study

C:\Documents and Settings\peterss2\My Documents\SharePoint Drafts\Coastal Erosion Study v2.docxRevision 1 - 17 May 2010 A

Appendix A

Appendix A - Grain sizeAnalysis

Ground Science Pty Ltd Factory 11, 8 - 20 Brock Street Thomastown, VIC 3074

Ph (03) 9464 4617 Fax (03) 9464 4618

Particle Size Distribution & Atterberg Limits Test Report

Client: AECOM Job No. GS2002/1

Project: PORTLAND ENGINEERING STUDY Test Date: 15-Feb-10

Location: PORTLAND Report No. AA

Lab Reference No. #1 Sample Identification: SS1 (sand dune near Surry)

Laboratory Specimen Classification: SAND, fine-coarse, light grey-brown

Particle Size Distribution AS1289 3.6.1 Consistency Limits and Moisture Content

Sieve Size % Passing Specification Test Method Result

150 mm 100 Liquid Limit % AS1289 3.1.2 ND

75 mm 100 Plastic Limit % AS1289 3.2.1 ND

53mm 100 Plasticity Index % AS1289 3.3.1 ND

37.5 mm 100 Linear Shrinkage % AS1289 3.4.1 ND

26.5 mm 100 Moisture Content % AS1289 2.1.1 0.3

19.0 mm 100 Sample History: Oven Dried

13.2 mm 100 Preparation Method: Dry sieved

9.5 mm 100 Crumbling / Curling of linear shrinkage:

6.7 mm 100 Linear shrinkage mould length: 250 mm

4.75 mm 100 ND = not determined NO = not obtainable NP = non plastic

2.36 mm 100 Moisture / Dry Density Relationship AS 1289 5.2.1

1.18 mm 100 Maximum Dry Density: t/m3

600 um 100 Optimum Moisture Content: %

425 um 98

300 um 89 Notes

150 um 11 sampled by client tested, as received

75 um 1

Laboratory Accredtation No. 15055 Date:19/02/2010This document is issued in accordance with NATA's accreditation requirements. 19/02/2010

Accredited for compliance with ISO/IEC 17025.

The results of the tests, calibrations and/or measurements included Ernst Gmehling

in this document are traceable to Australian/national standards. Approved Signatory

Particle Size Distribution

0

10

20

30

40

50

60

70

80

90

100

0.001 0.01 0.1 1 10 100Particle Size (mm)

Perc

ent P

assin

g

75 150 300 425 600 1.18 2.36 4.75 9.5 13.2 19 26.5 37.5 53

A.S.

Sieves

mclay silt gravelsand

Form: GS005/R

version 3 Sept 05

Ground Science Pty Ltd Factory 11, 8 - 20 Brock Street Thomastown, VIC 3074

Ph (03) 9464 4617 Fax (03) 9464 4618

Particle Size Distribution & Atterberg Limits Test Report

Client: AECOM Job No. GS2005/1

Project: PORTLAND ENGINEERING STUDY Test Date: 15-Feb-10

Location: PORTLAND Report No. AB

Lab Reference No. # 2 Sample Identification: SS2 end of rock wall, 3m from wall

Laboratory Specimen Classification: SAND, fine-coarse, grey-brown

Particle Size Distribution AS1289 3.6.1 Consistency Limits and Moisture Content

Sieve Size % Passing Specification Test Method Result

150 mm 100 Liquid Limit % AS1289 3.1.2 ND

75 mm 100 Plastic Limit % AS1289 3.2.1 ND

53mm 100 Plasticity Index % AS1289 3.3.1 ND

37.5 mm 100 Linear Shrinkage % AS1289 3.4.1 ND

26.5 mm 100 Moisture Content % AS1289 2.1.1 49.1

19.0 mm 100 Sample History: Oven Dried

13.2 mm 100 Preparation Method: Dry sieved

9.5 mm 100 Crumbling / Curling of linear shrinkage:

6.7 mm 100 Linear shrinkage mould length: 250 mm

4.75 mm 100 ND = not determined NO = not obtainable NP = non plastic

2.36 mm 100 Moisture / Dry Density Relationship AS 1289 5.2.1

1.18 mm 100 Maximum Dry Density: t/m3

600 um 100 Optimum Moisture Content: %

425 um 100

300 um 98 Notes

150 um 48 sampled by client tested, as received

75 um 8

Laboratory Accredtation No. 15055 Date:19/02/2010This document is issued in accordance with NATA's accreditation requirements. 19/02/2010

Accredited for compliance with ISO/IEC 17025.

The results of the tests, calibrations and/or measurements included Ernst Gmehling

in this document are traceable to Australian/national standards. Approved Signatory

Particle Size Distribution

0

10

20

30

40

50

60

70

80

90

100

0.001 0.01 0.1 1 10 100Particle Size (mm)

Perc

ent P

assin

g

75 150 300 425 600 1.18 2.36 4.75 9.5 13.2 19 26.5 37.5 53

A.S.

Sieves

mclay silt gravelsand

Form: GS005/R

version 3 Sept 05

AECOMCoastal Spaces - Inundation and Erosion - Coastal Engineering StudyPortland Coastal Engineering Study

C:\Documents and Settings\peterss2\My Documents\SharePoint Drafts\Coastal Erosion Study v2.docxRevision 1 - 17 May 2010 B

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