lancelin coastal vulnerability study · aim of this project, is to develop a wave model to help...

LANCELIN COASTAL VULNERABILITY

STUDY Supervisor: Charitha Pattiaratchi

Benjamin Robinson

October 2011

1

Cover Photo: Panoramic view of Lancelin bay taken on the 15th October 2011

2

31 Florence St

West Perth

WA 6005

November 3, 2011

Head of School,

School of Civil & Resource Engineering

The University of Western Australia,

NEDLANDS,

WA 6009

Dear Sir,

I have the pleasure of submitting this thesis entitled LANCELIN COASTAL VULNERABILITY

STUDY as partial fulfilment for the combined degree Bachelor of Commerce (Investment &

Corporate Finance) / Bachelor of Engineering (Civil) with Honours.

Yours Sincerely,

Ben Robinson.

4

I Abstract

Throughout history humans have inhabited the coastlines of many continents due to the life

giving properties of coastal environments. Not many other places around the world give a

better example of this than Australia, with more than 80% of the population existing within

100km of the coast (DFAT 2008). As people are attracted to the coast they become

vulnerable to any coastline movement and in fact for as long as historically possible people

have taken note of coastal change. The earliest observed effects of coastal change can be

seen in the oral traditions of the indigenous Australian population known as the dreamtime.

Where stories depicting rising sea levels causing the loss of vital communication routes and

food sources have been passed on from generation to generation. Further indications of

disruption due to coastal change can be seen throughout different stages in history however

accurate documentation and the study of coastal change is a relatively new area considering

that some coastal processes can take decades to develop.

The dynamic environment that makes up the coast continually adjusts to the effects of

weather, tides, seasons and climate change. Climate change, although heavily debated is

becoming increasingly difficult to ignore. Extreme weather conditions and rising sea levels

are being realised and with an ever expanding population our effect on the environment will

only increase. The question is not so much whether the coast is eroding, but how we can

live with it and properly accommodate its changing shoreline conditions.

This particular study has focused on the region of Lancelin for its unique protective reef

system that creates the sheltered waters inside the bay of Lancelin. Fears exist that as mean

sea level increases globally due to climate change, the protection to the bay by the reef will

diminish to a point where the conditions are not suitable for current purposes.

The results from this study have confirmed that these fears will in fact become a reality

within the next 100 years. Even given conservative predictions for climate change resulting

in a rise of 50cm, significant wave heights inside the bay are expected to increase by 62.5%.

Even more alarming if sea levels rise to higher expectations of 100cm over the next 100

years, wave heights inside the bay may increase by as much as 140.6%.

6

II Acknowledgements

I would like to thank my supervisor Dr Chari Pattiaratchi from the school of environmental

engineering at the University of Western Australia for his support and guidance.

I would also like to acknowledge Dr Sarath Wijeratne for his time spent with me developing

my model and analysing the results.

Finally I would like to acknowledge the department of transport for the survey data they

provided that was essential for developing the bathymetry used in my model.

7

Contents

I Abstract .............................................................................................................................. 4

II Acknowledgements ............................................................................................................ 6

III List of Figures ..................................................................................................................... 9

IV List of Tables .................................................................................................................... 11

1. Introduction ..................................................................................................................... 12

1.1 Rationale ................................................................................................................... 12

1.2 Aim ............................................................................................................................ 12

1.3 Objectives .................................................................................................................. 12

2. Literature Review ............................................................................................................. 13

2.1 Geography ................................................................................................................. 13

2.2 Geology ..................................................................................................................... 14

2.3 Meteorology .............................................................................................................. 15

2.4 Wave Climate ............................................................................................................ 16

2.4.1 Short Period Water Level Fluctuations .............................................................. 16

2.4.2 Long Period Water Level Fluctuations .............................................................. 19

2.5 Climate Change ......................................................................................................... 19

2.6 Mike 21 ...................................................................................................................... 21

3. Research Methodology .................................................................................................... 22

3.1 Bathymetry ................................................................................................................ 22

3.2 Wind Forcing Data ..................................................................................................... 23

3.3 Wave Forcing Data .................................................................................................... 25

3.4 Model Duration ......................................................................................................... 26

3.5 Analysis ...................................................................................................................... 27

4. Results and Discussion ..................................................................................................... 28

4.1 Current conditions..................................................................................................... 28

8

4.2 Minimum Sea level Rise ............................................................................................ 30

4.3 Maximum Sea level Rise ............................................................................................ 32

4.4 Discussion .................................................................................................................. 34

5. Conclusions ...................................................................................................................... 38

6. Recommendations ........................................................................................................... 40

7. REFERENCES ..................................................................................................................... 42

8. Appendices ....................................................................................................................... 44

8.1 Matlab Scripts ........................................................................................................... 44

9

III List of Figures

Figure 2.1 – Lancelin Satellite photos (Google 2011)

Figure 2.2– Dune Formation Process

Figure 2.3 – Summer Wave Climate (December – February) (Lemm et al., 1999)

Figure 2.4 – Winter Wave Climate (June – August) (Lemm et al., 1999)

Figure 2.5 – Summer Sea Climate (December – February) (Lemm et al., 1999)

Figure 2.6 – Winter Sea Climate (June – August) (Lemm et al., 1999)

Figure 2.7 - Recommended allowance for sea level rise in coastal planning for W.A.

Figure 2.8 – Mike 21 Schematic

Figure 3.1 – Bathymetry and mesh grid of entire model domain

Figure 3.2 – Bathymetry and mesh grid of Lancelin bay and reef system.

Figure 3.3 – Model Surface wind and sea level pressure (Source; NOAA – NCEP)

Figure 3.4 – Summer Wind Climate

Figure 3.5 – Winter Wind Climate

Figure 3.6 – Model open boundary wave data (source; NOAA – WWII)

Figure 3.7 – Summer Wave Climate

Figure 3.8 – Winter Wave Climate

Figure 3.9 – Model Wave Vector Field.

Figure 3.10 – Data extraction points and lines.

Figure 4.1 – Significant Wave Height Inside and Outside reef system (0cm Shift).

Figure 4.2 – Significant Wave Heights along reference lines 1 and 2 (0cm Shift).

10

Figure 4.3 – Mean Significant Wave Heights along reference lines 1 and 2 (0cm Shift).







Figure 4.10 – Significant Wave Height comparison inside the reef system.

Figure 4.11 – Significant Wave Height comparison outside the reef system.

Figure 4.12 – Significant Wave Height Line comparison inside the reef system.

Figure 4.13 – Significant Wave Height Line comparison outside the reef system.

11

IV List of Tables

Table 2.1 – South Western Australia Weather Systems (Hollings, 2004; Stul, 2005).

Table 2.2 – Published extreme wave height estimates for Rottnest Island (Fangjun et al.

2010).

Table 3.1 – Data extraction point and line location

Table 4.1 – Percentage increase of wave heights inside the reef system.

Table 4.2 – Percentage increase of wave heights outside the reef system

Table 4.3 – Wave reduction comparison.

12

1. Introduction

1.1 Rationale

Studies conducted on the significance of reef structures surrounding the shoreline in close

proximity to inhabited land are useful for future coastal planning and management. Lancelin

is a perfect example of a region that is not well understood and that could be potentially

devastated by worsening ocean conditions. The bay of Lancelin although protected now by a

significant reef system and set of islands is susceptible to a rise in sea level due to climate

change.

Lancelin relies heavily on this protected bay for its existence and although difficult to

produce, the need for a model that can predict wave heights within the reef system is

essential. A significant increase in wave height within the bay would potentially interfere

with commercial fishing operations and the lure for tourists to the town.

1.2 Aim

The Department of Transport has information on dunes, reefs and shoreline movement. The

aim of this project, is to develop a wave model to help further understand the wave climate,

but also consider how sensitive the climate would be to an increase in mean sea level and

ultimately how the coast will behave over the next 100 years.

1.3 Objectives

The main objective of this project is to accurately develop a wave model of the Lancelin

area. In order to complete this, certain forcing data will need to be realised before the

model can function. These inputs include:

1 Bathymetry

2 wave Climate

3 Wind Climate

4 Sea Level Approximation

13

2. Literature Review

2.1 Geography

Lancelin is a small fishing and tourist town, with a population of 666 people (Census 2006)

and located in the Shire of Gingin, 110km north of Perth Western Australia. Below are three

satellite photos showing the Lancelin coastline, surrounding area and the location within

Australia.

Figure 2.1 – Lancelin Satellite photos (Google 2011)

14

2.2 Geology

A sound understanding of the geology and geomorphology of Lancelin is essential for any

coastal planning and management decisions (Gozzard 2009). The geological setting of any

location controls the shoreline response to energy inputs, sediment properties as well as the

availability of these sediments (Wright & Thom 1977). The shoreline at Lancelin is composed

of Holocene sands deposited onto Limestone dunes formed during the middle and late

Pleistocene eras. This limestone is known as Tamala limestone and consists of calcarenite

wind-blown shell fragments and quarts sands. Coastal change in these environments is even

more difficult to predict than usual because the wave dominated, high energy coastal areas

undergo rapid erosion and accretion in response to storm events.

Lancelin Island and the protecting reef system that surrounds Lancelin bay is comprised of

this Tamala limestone. The material stretches from Shark Bay in Western Australia as far

south as Albany in combination with other geological formations. The Holocene sands that

dominate Lancelin are prevalent all along the western coast of Australia also. Hence they

are readily available and account for the majority of all sediments in shoreline processes as

well as forming the recognizable parabolic sand dunes that surround the town of Lancelin.

Figure 2.2– Dune Formation Process

15

2.3 Meteorology

The weather systems that affect Lancelin are very similar to the weather systems that affect

Perth as described in detail in Gentilli (1971). High pressure belts breakdown into

anticyclonic cells moving eastward over the coastline every 3-10 days (Gentilli, 1972). This

anticyclonic band migrates from around 38⁰S in summer to 30⁰S in winter (Gentilli 1972).

Due to the latitude of Lancelin at approximately 31⁰S, these cells produce predictable

offshore winds in summer with increasingly unpredictable winds in winter as onshore winds

dominate the climate.

Winter conditions are also affected by periodic storm events associated with mid latitude

depressions. These depressions interrupt the prevailing weather with initially northerly

winds, freshening and shifting to north westerlies, then rapidly swinging to westerlies and

finally south westerlies as the system crosses the coast (Lemm et al. 1999). These conditions

may continue for up to 36 hours with wind speeds ranging from 15 – 29 ms-1 and frequent

strong gusts (Steedman, 1982).

In summer these mid latitude depressions exist too far south to affect the wind climate

however the sea breeze system that is prevalent in the south west region of Australia has a

very noticeable effect on the wind climate. As the land mass is heated from the summer

sun, the hot air rises sucking in the cooler air from the ocean, creating the regular

occurrence of the sea breeze predicted between noon and 3:00pm most days. This south-

west Australian sea breeze is considered one of the strongest in the world with winds

reaching up to a maximum of 20 ms-1 and a mean velocity of 8 ms-1 at the coastline

(Pattiaratchi et al., 1997; Masselink & Pattiaratchi, 2000). This system differs to the usual

sea breeze system in that the wind does not strike the coastline perpendicularly due to

orientation of the land mass with the ocean. Because of this the wind blows predominantly

from the south to southwest direction (Hollings 2004). When these winds are at their

strongest towards the end of summer the waves that are generated from these winds may

exceed that of the prevailing swell (Hegge et al. 1996).

16

The final weather system to affect the coastline are tropical cyclones. Although these

systems only occur once every 10 years, (Gentilli 1971) due to their intense energy their

affect can be substantial. The best example of this was when tropical cyclone Alby caused

extensive erosion to Perth beaches in 1978 (Lemm, 1996).

Weather

System

Occurrence Frequency Wind

Direction

Avg Wind Speed

and Duration

Extreme 30 min

Avg Wind Speed

Anticyclone

January -

December

Every 3 -

10 days

All 0 – 5 m/s

Steady

5 – 10 m/s

Mid Latitude

Depressions

May -

October

Avg 3 – 8

year

N→ NW

→W→SW

15 – 25 m/s

10 – 55 hours

20 – 25 m/s

Squalls

December -

April

Every 13

days

All 15 – 20 m/s

2 – 4 hours

25 m/s

Sea Breeze

October –

March

> 15 days

a month

180⁰ -

200⁰

10 – 15 m/s

4 – 8 hours

20 m/s

Tropical

Cyclones

October -

March

1 every 10

years

Cyclone

Location

15 – 25 m/s

5 – 15 hours

25 – 30 m/s

Table 2.1 – South Western Australia Weather Systems (Hollings, 2004; Stul, 2005).

2.4 Wave Climate

The offshore wave conditions at Lancelin are similar to the offshore wave conditions along

the entire south west coast of Western Australia. This is due to the generation of deep

water waves by large scale weather systems over the Indian and Southern Oceans resulting

in little spatial variation in the deep water wave climate (Lemm et al, 1999). This wave

climate exists both 200km north and south of Perth encompassing the area of study for this

paper and is characterized by extreme seasonality.

2.4.1 Short Period Water Level Fluctuations

Over summer (December – February) the mean significant wave height is 1.8m with a period

of 7.6s compared to a mean significant wave height of 2.8m with a period of 9.7s in winter

17

(June – August) (Masselink & Pattiaratchi, 2001). These swells are generated by the typical

weather systems highlighted in the meteorology section and as the location of these high

pressure belts migrate seasonally so does the swell approach direction. In summer when the

anticyclonic bands exist approximately around the line of latitude 38⁰S, the swell generated

approach primarily from the south, south west compared to winter where these bands

migrate north to approximately the line of latitude 31⁰S generating swells approaching the

coast from a west, south west direction (Lemm et al., 1999). The wave roses shown below in

figure 2.3 and 2.4 clearly show the offshore wave climate for the region. They were created

by Lemm (1996) as a compilation of 18 years of sea and swell observations approaching

Fremantle from the period 1950 – 1967.

Figure 2.3 – Summer Wave Climate Figure 2.4 – Winter Wave Climate

December – February June – August

The seas for the region are a direct product of the wind climate that generates them. In

summer the wind climate is characterized by consistent southern winds generating seas

approaching from a southerly direction. In winter the seas generated by the wind climate

increase with increasing wind conditions as well as becoming less consistent and swinging to

a westerly direction. Sea roses for the Perth region can be seen below in figures 2.5 and 2.6

for both summer and winter, and again created by Lemm (1996).

18

Figure 2.5 – Summer Sea Climate Figure 2.6 – Winter Sea Climate

December – February June – August

An analysis of the wave climate requires a good understanding of the extreme offshore

wave conditions. From a coastal engineering point of view extreme wave conditions would

generate the dominant design requirements for any infrastructure design. A paper by

Fangjun et al. (2010) brings together a variety of research into the area to try and give a

better view of the extreme wave heights for offshore Perth and can be seen in table 2.2.

Table 2.2 – Published extreme wave height estimates for Rottnest Island (Li et al. 2010).

19

2.4.2 Long Period Water Level Fluctuations

Long period water level fluctuations affecting Lancelin can be accredited to two major

factors, tidal and storm surges. Lancelin can be defined as having diurnal micro-tidal

conditions with the maximum tidal range being 0.76m (Department of Transport, 2011).

This range can be greatly increased by the combination of surge events and high energy

wave conditions. Storm surge is defined as an offshore rise in water level attributed to the

combined effect of wind induced shear stress and a low pressure weather system acting on

the water surface. The timing of surges is an important factor, if they combine with the

timing of maximum tidal range at the peak of a spring high tide the effect on the shoreline

can be substantial. Any change to the beaches caused by this effect may remain for a long

period of time as water levels are unable to recreate peak conditions to allow reworking.

Due to seasonal variations in ambient barometric pressure and prevailing wind direction,

caused by the seasonal migration of the subtropical high pressure belt, water levels are

higher in winter than in summer by an average of about 0.25 m (Masselink & Pattiaratchi,

2001).

2.5 Climate Change

Climate Change refers to a change in the state of the climate that can be identified (e.g.

using statistical tests) by changes in the mean and/or the variability of its properties, and

that persists for an extended period, typically decades or longer (IPCC 2007). Climate change

affects a number of key environmental variables that include (Bicknell 2010):

Mean sea level;

Ocean currents and temperature;

Wind and wave climates;

Rainfall / Runoff; and

Air temperature

From these, the most dominant factor affecting our model will be the increase in mean sea

level, however it is important to understand that any predictions of future sea level rises

20

due to climate change will also create errors in our predicted model forcing data, as these

variables above are affected.

There is much debate surrounding the area of climate change and predictions in global sea

levels. The most widely accepted paper on the subject is the 2007 Climate Change Report

developed by the Intergovernmental Panel on Climate Change. This paper gives a detailed

breakdown of the causes of climate change and delivers a prediction that sea levels will rise

in the next century by 50 – 100cm (Bindoff at al. 2007).

Further work by the Commonwealth Scientific and Industrial Research Organisation (CSIRO)

has been done continuing on from the IPCC report to determine local variations around the

Australian coastline. This work has been implemented by the WA Planning Commission to

develop the Statement of Planning Policy No. 2.6: State Coastal Planning Policy (Bicknell

2010). The recommended allowance for sea level rise in coastal planning for W.A. over the

next century from this policy can be seen in figure 2.7 below.

Figure 2.7 - Recommended allowance for sea level rise in coastal planning for W.A.

There are views that this rise of between 50 – 100cm may be an underestimate. The report,

A Semi-Empirical Approach to Projecting Future Sea-Level Rise by Stefan Rahmstorf (2007) is

an example of this. It predicts sea level rises to be between 50 – 140cm due to the poorly

understood dynamics of glaciers and ice sheets (Rahmstorf 2007). This paper is only being

21

used as an example of varying views on the topic but for the purpose of this project I have

accepted the IPCC 2007 findings of predicted sea levels increasing between 50cm and

100cm which agrees with State Coastal Planning Policy.

2.6 Mike 21

In order to accurately model the flow field for Lancelin a program developed by the Danish

Hydraulic Institute called MIKE 21 has been employed. MIKE 21 is a computer program that

simulates flows, waves, sediments and ecology in rivers, lakes, and coastal areas. This

software has been used extensively throughout the world to not only model existing

scenarios but further undertake design data assessment for coastal and offshore structures,

to optimise port layouts and to develop and test coastal protection measures. Figure 2.8

below shows a schematic breakdown of how the model works. It is important to note that

this software uses an iterative process where continuity and momentum equations are

continually solved for each time step and the inputs are changed respectively after every

time step.

Figure 2.8 – Mike 21 Schematic

22

3. Research Methodology

3.1 Bathymetry

The bathymetry used for this model, shown in Figure 3.1 and Figure 3.2 below, is a

combination of survey data obtained from the Department of Transport and data taken

from Geoscience Australia. A coarse mesh size of approximately 1.5km has been used in

deep open water and then refined to a fine grid size of approximately 20m close to the

shoreline and surrounding reef structures. The survey data has been obtained inside the

reef system comprising of approximately 3km. ideally a bathymetry consisting of 100%

survey data would have been desirable but unfortunately no such data exists.

Figure 3.1 – Bathymetry and mesh grid of entire model domain

23

Figure 3.2 – Bathymetry and mesh grid of Lancelin bay and reef system.

3.2 Wind Forcing Data

To generate the surge component of sea levels, the model has been forced with

atmospheric pressures and wind taken from the US National Centre for Environmental

Predictions (NCEP). This data can be seen in the figures below from the 1st January 2009

through to the 1st January 2010 every 6 hours. The wind is broken down into vector

velocities and the surface pressure system is measured in milibars. The data is extracted

from a larger weather history of the entire country and refined to a square grid between the

lines of latitude 30 to 32 degrees south and lines Longitude 114.5 and 115.5 East.

24

Figure 3.3 – Model Surface wind and sea level pressure (Source; NOAA – NCEP)

From this data I have also plotted the wind velocity and direction for both summer and

winter seasons. The summer period in figure 3.4 captures the months of January and

February where the winter period in figure 3.5 captures the months of June and July.

Figure 3.4 – Summer Wind Climate Figure 3.5 – Winter Wind Climate

25

3.3 Wave Forcing Data

Wave data for the area has been retrieved from NOAA Wave watch III. This data is shown

below in figure 3.6 and is again from the 1st January 2009 to the 1st January 2010 every 3

hours. The data contains three variables significant wave height, mean wave period as well

as mean wave direction and again plotted the wave height and direction for both summer

and winter seasons in figures 3.7and 3.8 respectively.

Figure 3.6 – Model open boundary wave data (source; NOAA – WWII)

Figure 3.7 – Summer Wave Climate Figure 3.8 – Winter Wave Climate

26

3.4 Model Duration

Ideally multiple runs of the model would be best to generate a series of data with varying

inputs for the increase in mean sea level. In order to achieve this, a significant amount of

time would be required, outside of the allowances of this study. To give some idea of the

complexities of the software it takes approximately 7 days to run the model built for

Lancelin for one year not including sediment transport. For this study findings should be

clear from running the model for the three scenarios. Firstly on current conditions with no

change in mean sea level. Then followed by adjusting for the change in sea level due to

climate change by running two models, once with the minimum predicted increase in mean

sea level of 50cm, and lastly once with the maximum predicted increase in mean sea level of

100cm. Figure 3.9 below show the complex wave vector field calculated for every step of

the model. For the entire year it required 8750 iterations for it to be solved.

Figure 3.9 – Model Wave Vector Field.

27

3.5 Analysis

In order to analyse the model outputs two points were selected, one inside the reef system

and one outside at similar sea depths to show the difference in significant wave heights at

these points. As well as this two parallel lines stretching out 20km from the shoreline were

chosen to extract the data from the model to also show how the wave climate behaved

approaching the reef system in comparison to approaching the shoreline directly. These

points and lines can be seen in figure 3.10 below.

Figure 3.10 – Data extraction points and lines.

Point Depth (m) Latitude Longitude

A -5.58461 115.3223 -31.0089

B -5.50549 115.2920 -30.9684

Line Distance (km) Latitude Longitude

1 20.032 115.3266955 - 115.1437938 (-31.00812827) – (-31.09969702)

2 20.018 115.2966852 - 115.1137305 (-30.95195418) – (-31.04278986)

Table 3.1 – Data extraction point and line location

Point B

Point A

Line 1

Line 2

28

4. Results and Discussion

4.1 Current conditions

To simulate current conditions we simply ran the model for the year 2009. Figure 4.1 shows

the difference in significant wave heights between point A inside the reef system and point

B outside the reef system. Figure 4.2 and Figure 4.3 shows the wave climate along lines 1

and 2 as they approach the shoreline.



B

A

Line1 Line 2

29


Line1 Line 2

30

4.2 Minimum Sea level Rise

To simulate the conditions for a minimum rise in sea level over the next 100 years the model

datum was shifted positively 50cm. Figure 4.4 shows the difference in significant wave

heights between point A inside the reef system and point B outside the reef system. Figure

4.5 and Figure 4.6 shows the wave climate along lines 1 and 2 as they approach the

shoreline.



Line1 Line 2

B

A

31


Line1 Line 2

32

4.3 Maximum Sea level Rise

To simulate the conditions for a maximum rise in sea level over the next 100 years the

model datum was shifted positively 100cm. Figure 4.7 shows the difference in significant

wave heights between point Figure 4.8 and Figure 4.9 shows the wave climate along lines 1

and 2 as they approach the shoreline.



Line1 Line 2

B

A

33


Line1 Line 2

34

4.4 Discussion

The best way to demonstrate how the wave climate will be affected by a predicted rise in

sea level is to compare the three outputs given for 0cm, 50cm and 100cm together as

shown below.

Figure 4.10 – Significant Wave Height comparison inside the reef system.

Figure 4.11 – Significant Wave Height comparison outside the reef system.

(cm)

100

50

0

(cm)

100

50

0

35

Figure 4.12 – Significant Wave Height Line comparison inside the reef system.

Figure 4.13 – Significant Wave Height Line comparison outside the reef system.

(cm)

100

50

0

(cm)

100

50

0

36

Table 4.1 – Percentage increase of wave heights inside the reef system.

Sea Level rise (cm) Mean Wave Height (m) Percentage Increase

0 0.1843 0

50 0.2994 62.5 %

100 0.4435 140.6 %

Table 4.2 – Percentage increase of wave heights outside the reef system

Sea Level rise (cm) Mean Wave Height (m) Percentage Increase

0 2.1727 0

50 2.2715 4.54 %

100 2.3546 8.37 %

Figure 4.10 and Table 4.1 clearly show how the region inside the bay will behave to an

increase in mean sea level. An increase of 50cm reflects 62.5% increase in significant wave

height at point A and a 140.6% increase caused by a predicted sea level rise of 100cm. This

data needs to be compared to our control Point B not protected by the reef system which

can be seen in Figure 4.4.5 and table 4.4.7.

These figures show a considerably lesser effect on significant wave height due to an increase

in mean sea level at Point B. For a 50 cm rise the waves only increase by 4.54% compared to

62.5% at Point A. This is shown again for an increase of 100cm producing an increase of only

8.37% compared to 140.6% at Point A.

This significant difference of wave heights at the two points A and B gives a good indication

of the role that the reef system is playing in protection of the bay.

37

This comparison can also be shown by table 4.3 which shows the effective reduction due to

the reef at point A compared to a similar point B not affected by the reef system.

Datum Shift 0cm 50cm 100cm

Mean Wave Height

Inside (m)

0.1843 0.2994 0.4435

Mean Wave Height

Outside (m)

2.1727 2.2715 2.3546

Reduction due to

Reef (%)

91.5191 86.8184 81.1654

Table 4.3 – Wave reduction comparison.

Currently the reef effectively reduces the wave heights by 91.5%, then after a 50cm increase

in sea level this drops to 86.81% and to 81.16% given a rise of 100cm. If the mean sea level

is expected to keep rising into the future the reduction of wave heights due to the reef

system will only decrease further. It is unsure at what point the worsening wave conditions

inside the bay will become problematic however this model gives a good indication of how

quickly the conditions will worsen.

38

5. Conclusions

The aim of this study was to develop a wave model to help further understand the wave

climate, but also consider how sensitive the climate would be to an increase in mean sea

level and ultimately how the coast will behave over the next 100 years.

In terms of constructing the model, the best possible model was built given the available

data. Ideally 100% in situ observations would be used to build the bathymetry and force the

model however in the absence of this data appropriate sources have been used for the

framework as discussed in the research methodology. Any errors that can be accredited to

the use of such data can be considered irrelevant for the purpose of this study was never to

accurately predict wave heights or sensitive sediment transport but rather to show how the

wave climate will behave relative to a predicted rise in mean sea level. The predictions for

rises in mean sea level due to climate change will always be passionately debated. The

model has been constructed in a way to keep this as a variable that can be easily changed to

reflect differing views. For these reasons the data that has been used to drive the model can

be deemed accurate and the model itself can be accepted as a good model.

At the commencement of this study I expected to see a small effect on the bay of Lancelin

as a result of a rising sea level. I did not however expect to see the kind of figures that were

produced by the model. An increase over the next 100 years in significant wave height

inside the bay of 62.5% for a minimum predicted sea level increase and an increase of

140.6% for a maximum predicted sea level increase should be alarming for anyone with in

an interest in the bay.

An increase like this will affect all aspects of marine activity in the harbour. The number of

days acceptable to launch boats from the shore will drop. The attraction for tourists

swimming, diving, boating and fishing will slowly drop as conditions inside the bay worsen.

The fishing industry that exists in Lancelin may need to look for more acceptable locations

to harbour their boats in fear of lost revenue from problems occurring with regard to an

increase in wave heights within the bay. Even the town jetty may have to be redesigned to

accommodate for the changing conditions.

39

To put these figures into perspective one only needs to look at the guidelines for the design

of boat launching facilities in Western Australia. The criteria for a ‘good’ wave climate in

small craft harbours state that the significant wave height should stay below 0.3m in height

(AS3692, 2001). Currently the bay meets this basic requirement but given even just the

minimum predicted rise in sea level pushes this bay out of the guidelines for any boat

launching facilities.

The results that have come from this study highlight the potential effects that can come

from climate change. Hopefully this study will help breakdown people’s views that climate

change will not affect them in their lifetime as this model has proven that over the next 100

years the protected waters that make the bay of Lancelin a major attraction, will only

worsen.

40

6. Recommendations

Given the results of this paper it is strongly recommend that further research into the wave

climate inside the bay of Lancelin be conducted. Specifically research into more accurate

wave height predictions and sediment transport is required, however finding a way to

validate the model with in situ observations before proceeding with any physical

recommendations is advised.

This model from the outset has been constructed in such a way that it can be revisited and

modified to give any desired outputs. If this model is to be used in the future It is

recommended to upgrade the bathymetry with more accurate survey data. This model

relies heavily on the bathymetry for all of its calculations and any errors associated with the

model can be greatly reduced by a more accurate bathymetry.

For any infrastructure planning inside the bay, the findings of this study should be consulted

before commencement of any construction. It is also recommended considering the findings

of this study with regard to the serviceability of any current infrastructure in particular the

main service jetty for the town.

42

7. REFERENCES

Australian Standards AS3692 – 2001, Guidelines for the Design of Marinas, Council of

Standards Australia 2001.

Bicknell, C. 2010. ‘Sea Level Change in Western Australia – Application to Coastal

Planning.’ Department of Transport Coastal Infrastructure, Coastal Engineering Group.

Bindoff, N.L., J. Willebrand, V. Artale, A, Cazenave, J. Gregory, S. Gulev, K. Hanawa, C. Le

Quéré, S. Levitus, Y. Nojiri, C.K. Shum, L.D. Talley and A. Unnikrishnan, 2007:

Observations: Oceanic Climate Change and Sea Level. In: Climate Change 2007: The

Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of

the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen,

M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)].

Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.Gentilli,

J. 1971, Climates of Australia and New Zealand. (World Survey of Climatology, Volume 13),

Elsevier, Amsterdam.

Department of Transport, Western Australia., www.transport.wa.gov.au, 2011.

DFAT - Australian Department of Foreign Affairs and Trade, www.dfat.gov.au, 2008.

Gentilli, J. 1972, Australian Climate Patterns, Nelson’s Australasian Paperbacks.

Gozzard, B. ‘WACoast – A knowledge Base for Coastal Managers’, October 2009.

Hegge, B., Eliot, I. & Hsu, J. 1996, ’Sheltered sand beaches of south-western Australia’,

Journal of Coastal Research, vol. 12, no. 3, pp. 748-760.

Hegge, B. J. 1994, Low - energy sandy beaches of south-western Australia: Two –

dimensional morphology, sediment dynamics, PhD Thesis, The University of Western

Australia.

Hollings, B. 2004, Sediment Dynamics of Warnbro Sound, Western Australia, Honours

Thesis, University of Western Australia.

IPCC 2007, Intergovernmental Panel on Climate Change, Fifth Assesment Report,

www.ipcc.ch.

http://www.transport.wa.gov.au/

http://www.dfat.gov.au,/

43

Lemm, A. J. 1996, Offshore Wave Climate: Perth, Western Australia, Honours Thesis,

University of Western Australia.

Lemm, A. J., Hegge, B. J. & Masselink, G. 1999, ’Offshore wave climate, Perth (Western

Australia), 1994-96’, Marine and Freshwater Research, vol. 50, pp. 95-102.

Li, F. Bicknell, C. & Lowry, R.. 2010. Extreme wave analysis for offshore Perth, 1994-2010.

Department of Transport, Western Australia

Masselink, G. & Pattiaratchi, C. B. 2000, ’Characteristics of the sea breeze system in Perth,

Western Australia, and its effect on the nearshore wave climate’, Journal of Coastal Research.

National Centers for Environmental Prediction (NCEP). www.ncep.noaa.gov/, 2011.

NOAA - National Oceanic and Atmospheric Administration., www.noaa.gov/. 2011.

Pattiaratchi, C. B. et al., 2011. ‘Coastal Assesment Study at Yanchep Lagoon

Redevelopment.’

Pattiaratchi, C. B., Hegge, B., Gould, J. & Eliot, I. 1997, ’Impact of sea-breeze activity on

nearshore and foreshore processes in south-western Australia’, Continental Shelf Research,

vol. 17, no. 13, pp. 1539-1560.

Rahmstorf, S. (2007). "A Semi-Empirical Approach to Projecting Future Sea-Level Rise".

Science315 (5810): 368–70. doi:10.1126/science.1135456. PMID 17170254.

Steedman, R. K. 1982, Record of storms, Port of Fremantle 1962-1980, R112, Steedman and

Associates, Perth.

Stul, T. 2005, Physical Characteristics of Perth Beaches, Western Australia, Honours Thesis,

University of Western Australia

Wright, L.D. & Thom, B. G., 1977. Coastal Depositional Landforms: a morphodynamic

approach. Progress in Physical Geography, 1, 412-59.

http://www.ncep.noaa.gov/

http://www.noaa.gov/

44

8. Appendices

8.1 Matlab Scripts

Wind Data

load wind_ 2009.txt dt=datenum(2009,01,01,00,00,00):datenum(0000,00,00,06,00,00):datenum(2011,0

1,25,18,00,00); dt2=[]; for mm=1:12; dt2=[dt2 datenum(2009,mm,01,00,00,00)]; end dt3=[dt2 datenum(2010,01,01,00,00,00)] subplot(311) plot(dt,wind_ 2009(:,1)) datetick('x','mmm')

title('Wind U','FontName','Calibri', 'Fontsize',14) ylabel('ms^-^1','FontName','Calibri', 'Fontsize',14) axis([dt3(1) dt3(length(dt3)) 0 20]) set(gca,'Box','off','TickDir', 'out','TickLength',[.02 .02])

% set(gca,'Box','off','TickDir', 'out','TickLength',[.02

.02],'XMinorTick','off','YMinorTick','off','XColor',[0.0 0.0

0.0],'YColor',[0.0 0.0 0.0],'YTick', 2:2:20,'LineWidth',.5);

subplot(312) plot(dt,wind_ 2009(:,2)) datetick('x','mmm') title('Wind V','FontName','Calibri', 'Fontsize',14) ylabel('ms^-^1','FontName','Calibri', 'Fontsize',14) axis([dt3(1) dt3(length(dt3)) 0 20]) set(gca,'Box','off','TickDir', 'out','TickLength',[.02 .02]) subplot(313) plot(dt,wind_ 2009(:,3)) datetick('x','mmm') title('MSL Pressure','FontName','Calibri', 'Fontsize',14) ylabel('mb','FontName','Calibri', 'Fontsize',14) axis([dt3(1) dt3(length(dt3)) 1000 1040]) set(gca,'Box','off','TickDir', 'out','TickLength',[.02 .02])

Wind Rose

path(path,'E:\Thesis\model_lancelin\wind') load wind_pnt.txt u=wind_pnt(:,2); v=wind_pnt(:,1); [s,d] = spddir(u,v);

figure(1) Db=d(1:240); Vb=s(1:240);

45

wind_rose(Db,Vb,'ci',[1 2 7],'dtype','meteo')

figure(2) Db=d(600:840); Vb=s(600:840);

wind_rose(Db-180,Vb,'ci',[1 2 7],'dtype','meteo')

Wave Data

load lancelin_wave _ 2009.txt dt=datenum(2009,01,01,00,00,00):datenum(0000,00,00,03,00,00):datenum(2010,0

1,02,09,00,00); dt2=datenum(2009,01,01,00,00,00):datenum(0000,01,00,00,00,00):datenum(2010,

01,02,09,00,00);

subplot(311) plot(dt,lancelin_wave _ 2009(:,2)) datetick('x','dd/mm') title('Sig. Wave Height','FontName','Calibri', 'Fontsize',14) ylabel('m','FontName','Calibri', 'Fontsize',14) axis([dt(1) dt(length(dt)) 0 10])

set(gca,'Box','off','TickDir', 'out','TickLength',[.02

.02],'XMinorTick','off','YMinorTick','off','XColor',[0.0 0.0

0.0],'YColor',[0.0 0.0 0.0],'YTick', 1:2:9,'LineWidth',.5);

subplot(312) plot(dt,lancelin_wave _ 2009(:,3)) datetick('x','dd/mm') title('Mean Wave Period','FontName','Calibri', 'Fontsize',14) ylabel('Sec','FontName','Calibri', 'Fontsize',14) axis([dt(1) dt(length(dt)) 0 20]) set(gca,'Box','off','TickDir', 'out','TickLength',[.02 .02]) subplot(313) plot(dt,lancelin_wave _ 2009(:,4)) datetick('x','dd/mm') title('Mean Wave Direction','FontName','Calibri', 'Fontsize',14) ylabel('^o','FontName','Calibri', 'Fontsize',14) axis([dt(1) dt(length(dt)) 0 360]) set(gca,'Box','off','TickDir', 'out','TickLength',[.02 .02])

Wave Rose

path(path,'C:\wind_rose\model_wave') load model_bus _sig _dir.txt

Db=model_bus _sig _dir(:,2); Vb=model_bus _sig _dir(:,1);

figure wind_rose(Db-180,Vb,'ci',[1 2 7],'dtype','meteo')

46

Point Plots

path(path,'E:\tst') dt=datenum(2009,01,01,08,00,00):datenum(0000,00,00,01,00,00):datenum(2009,1

2,29,00,00,00); data=xlsread('zero_50_100_5m_in_out_reef.xls'); plot(dt,data(:,1),'b',dt,data(:,7),'g',dt,data(:,13),'k') datetick('x','mmm') ylabel('Sig. wave height (m) ') xlabel('2009')

Line Plots

path(path,'F:\tst') data_0_1=xlsread('line_1_0cm.xls'); data1a=data_0_1(1:10:length(data_0_1),:); data_0_2=xlsread('line_2_0cm.xls'); data2a=data_0_2(1:10:length(data_0_2),:); x1=((1:1:200)*100)/1000; x2=((1:1:199)*100)/1000;

hold q1=plot(x2,data2a','g') q2=plot(x1,data1a','b') axis([0 10 0 10])

ylabel('Sig. wave height (m) ') xlabel('Distance out from shoreline (km)')

Mean Wave Heights and percentage reduction due to reef system

path(path,'E:\tst') dt=datenum(2009,01,01,08,00,00):datenum(0000,00,00,01,00,00):datenum(2009,1

2,29,00,00,00); data=xlsread('zero_50_100_5m_in_out_reef.xls'); x = mean(data(:,1)); y = mean(data(:,2)); p=(1-x/y)*100;

Mean Wave Heights along extraction lines

path(path,'F:\tst') dt=datenum(2009,01,01,08,00,00):datenum(0000,00,00,01,00,00):datenum(2009,1

2,29,00,00,00); line_1_50cm=xlsread('line_1_50cm.xls'); line_2_50cm=xlsread('line_2_50cm.xls'); hold

ln1=mean(line_1_50cm); ln2=mean(line_2_50cm);

plot(ln1,'b')

47

plot(ln2,'g')

ylabel('Sig. wave height (m) ') xlabel('Distance out from shoreline (x10^2^m)')

Mean Wave Heights along extraction lines Comparison

path(path,'F:\tst') dt=datenum(2009,01,01,08,00,00):datenum(0000,00,00,01,00,00):datenum(2009,1

2,29,00,00,00); line_1_0cm=xlsread('line_1_0cm.xls'); line_1_50cm=xlsread('line_1_50cm.xls'); line_1_100cm=xlsread('line_1_100cm.xls'); hold

ln1=mean(line_1_0cm); ln2=mean(line_1_50cm); ln3=mean(line_1_100cm);

plot(ln1,'b') plot(ln2,'g') plot(ln3,'k')

axis([0 100 0 3.5])

ylabel('Sig. wave height (m) ') xlabel('Distance out from shoreline (x10^2^m)')

lancelin coastal vulnerability study · aim of this project, is to develop a wave model to help...

Documents