An Investigation into Nearshore Wave and Sediment Dynamics at … · 2011. 5. 27. · processes in...
94
An Investigation into Nearshore Wave and Sediment Dynamics at Bandy Creek Boat Harbour, Esperance Colin Hedderwick
Transcript of An Investigation into Nearshore Wave and Sediment Dynamics at … · 2011. 5. 27. · processes in...
An Investigation into Nearshore Wave and Sediment Dynamics at Bandy Creek
Boat Harbour, Esperance
Colin Hedderwick
2
This thesis is presented as partial fulfilment of the degree
Bachelor of Engineering (Applied Ocean Science)
From the School of Environmental Systems Engineering,
Faculty of Engineering, Mathematics and Computing
November 2006
Cover Photo: Arial photograph of Bandy Creek Boat Harbour, Esperance
3
Contents Figures.....................................................................................................6
Tables......................................................................................................7
Abstract ...................................................................................................8
Acknowledgements ................................................................................ 10 1.0 Introduction................................................................................... 11
1.1 Motivation......................................................................................................... 11 1.2 Aim.................................................................................................................... 11 1.3 Objectives.......................................................................................................... 11 1.4 Previous Studies................................................................................................ 12
1.4.1 Prediction and Measurement of Wave energy and bottom shear stress for Esperance Bay (Johnson & Pattiaratchi 2004).......................................................... 13
1.5 Current Dredging Program................................................................................ 16 1.6 Coastal Design Criteria ..................................................................................... 17
1.6.1 Wave Data................................................................................................. 19 1.6.2 Current Estimates of Sediment Transport................................................. 19
2.0 Environmental Setting ................................................................... 21
2.1 Location ............................................................................................................ 21 2.2 Meteorological Conditions................................................................................ 21
2.2.1 High Pressure Systems.............................................................................. 22 2.2.2 Mid-latitude depressions........................................................................... 22 2.2.3 Sea breeze system ..................................................................................... 22 2.2.4 Extreme wind conditions .......................................................................... 23
2.3 Wave Climate.................................................................................................... 23 2.3.1 Wave Field Definitions ............................................................................. 23 2.3.2 Offshore wave climate .............................................................................. 24 2.3.3 Nearshore wave climate............................................................................ 26
2.4 Long Period Water level Fluctuations .............................................................. 32 2.4.1 Tides.......................................................................................................... 32 2.4.2 Storm surges.............................................................................................. 32 2.4.3 Seiches ...................................................................................................... 33
3.0 Morphodynamics relevant to Esperance.......................................... 34 3.1 Sediment Mobility ............................................................................................ 34
3.1.1 Forces acting on a sediment particle......................................................... 34 3.1.2 Selection of suitable wave theory ............................................................. 35 3.1.3 Maximum shear stress............................................................................... 37 3.1.4 Wave friction factor .................................................................................. 37 3.1.5 Peak orbital velocity.................................................................................. 38
4
3.1.6 Critical mobility parameter ....................................................................... 39 3.2 Modes of Sediment Transport........................................................................... 41
3.2.1 Threshold for suspension .......................................................................... 42 3.3 Prediction of sediment transport ....................................................................... 44
3.3.1 Longshore sediment transport................................................................... 45 4.0 Methods ........................................................................................ 49
4.1 Numerical Wave Modelling.............................................................................. 49 4.1.1 SWAN wave model details....................................................................... 49 4.1.2 Modelling design....................................................................................... 50 4.1.3 Input data................................................................................................... 50 4.1.4 Data extraction .......................................................................................... 52 4.1.5 Model validation ....................................................................................... 52
4.2 Estimating Sediment Transport Characteristics................................................ 53 4.2.1 Maximum Shear Stress ............................................................................. 54 4.2.2 Mobilised grain size.................................................................................. 54 4.2.3 Suspended grain size................................................................................. 55 4.2.4 Longshore transport .................................................................................. 55
5.0 Results .......................................................................................... 56 5.1 Operability Analysis ......................................................................................... 56 5.2 Numerical Wave Modelling.............................................................................. 58
5.2.1 Areas of interest ........................................................................................ 62 5.2.2 Significant Wave Heights ......................................................................... 63 5.2.3 Wave Periods ............................................................................................ 64 5.2.4 Wave Direction ......................................................................................... 64 5.2.5 Model Validation ...................................................................................... 65
5.3 Sediment Mobility ............................................................................................ 65 5.4 Sediment Suspension ........................................................................................ 66 5.5 Longshore sediment transport........................................................................... 66
6.0 Discussion..................................................................................... 68
6.1 Data Analysis .................................................................................................... 68 6.1.1 Implications for dredging operations ........................................................ 68 6.1.2 Implications for coastal management ....................................................... 69
6.2 Numerical Wave Modelling.............................................................................. 69 6.2.1 Model Validation ...................................................................................... 70 6.2.2 Drawbacks to numerical wave modelling................................................. 71
6.3 Sediment Transport........................................................................................... 72 6.3.1 General transport characteristics............................................................... 73 6.3.2 Longshore transport .................................................................................. 74 6.3.3 Limitations of sediment transport estimates ............................................. 75
7.0 Conclusions................................................................................... 76 8.0 Recommendations ......................................................................... 78
5
References ............................................................................................. 80 Appendix A ........................................................................................... 84 Appendix B............................................................................................ 88 Appendix C............................................................................................ 93
6
Figures Figure 1.1: Position of InterOcean S4 wave rider buoy (Johnson 2004)……..……. 14 Figure 1.2: Hindcast of significant wave height for 2002 (Johnson 2004)…………15 Figure 2.1: Location map of Esperance……………………………………………. 21 Figure 2.2: Offshore significant wave height, 2006………………………………...24 Figure 2.3: Distribution of offshore wave height and period 2006…………………25 Figure 2.4: Nearshore significant wave height, 2005……………………………….27 Figure 2.5: Combined distributions of wave height and period, 2005……………...29 Figure 2.6: Relative and cumulative distributions…………………………………. 30 Figure 2.7: Temporal distribution of storms, 2005……………………………….... 31 Figure 3.1: Ranges of suitability of various wave theories (Méhauté 1976)………. 36 Figure 3.2: Fluid particle displacement under waves (CERC 2003)………………. 38 Figure 3.3: Modified Shield’s diagram…………………………………………….. 40 Figure 3.4: Ranges of sediment motion (Yalin 1977)……………………………....44 Figure 4.1: SWAN Bathymetry and instrument locations……………………......... 53 Figure 5.1: Persistence of ‘calms’…………………………………………………..57 Figure 5.2: Persistence of ‘storms’………………………………………………… 58 Figure 5.3: SWAN output for storm conditions…………………………………….59 Figure 5.4: SWAN output for average winter conditions…….……………………. 60 Figure 5.5: SWAN output for average summer conditions………………………... 61 Figure 5.6: SWAN output for easterly conditions…………………………………. 62
7
Tables Table 1.1: Significant wave heights and periods (Johnson 2004)…………………. 15 Table 2.1: Nearshore wave statistics, 2005…………………………………………27 Table 5.1: Modelled wave heights…………………………………………………. 63 Table 5.2: Modelled wave periods…………………………………………………. 64 Table 5.3: Modelled wave directions………………………………………………. 64 Table 5.4: Expected and modelled wave heights…………………………………... 65 Table 5.5: Expected and modelled wave periods………………………………….. 65 Table 5.6: Critical mobility sediment diameters………………………………….... 66 Table 5.7: Volumetric rate of longshore sediment transport, Esperance…………... 67 Table 5.8: Volumetric rate of longshore sediment transport, BCBH…..………….. 67 Table 5.9: Volumetric rate of longshore sediment transport, Dredge disposal site... 67
8
Abstract
Bandy Creek Boat Harbour (BCBH) was constructed in 1983 five kilometres north east
of the Esperance townsite. Shortly after its construction, littoral drift sand began to
accumulate in the harbour entrance. The progressive accumulation of sediment has
required regular dredging to maintain navigation at the harbour entrance. The Department
of Planning and Infrastructure (DPI) estimates dredging costs are in the order of $1.0 M
to $1.5 M every two years; which is approximately 25% of the total annual budget
available to the DPI for all dredging campaigns throughout WA.
Esperance is unique in comparison to many other coastal areas of Western Australia.
Over the years a large number of coastal studies have been funded and conducted.
However, no overall study addressing coastal issues has ever been completed. This is
primarily due to the lack of sufficient directional wave data for the previous studies to
accurately estimate seasonal sediment movements. Potentially all the previous studies
could benefit from more detailed long-term wave hind casting and more complex
numerical modelling of the nearshore wave climate.
The DPI is interested in gaining a greater understanding of the coastal processes in
Esperance, so that the current dredging practice might be improved. This thesis aimed to
model and analyse wave data recently collected in the area and determine the nearshore
wave climate and sediment transport characteristics of the area.
The collected wave data was analysed for significant wave patterns. These commonly
observed wave patterns were then modelled using the numerical wave model SWAN
(Simulating WAves Nearshore). SWAN outputted nearshore wave data which could be
compared to previously measured wave data. This outputted wave data was then used to
characterise the nearshore wave and sediment climates.
9
The study found that the main sediment transport mechanisms in the vicinity of Bandy
Creek are wave action and wave induced currents. In the winter months these actions and
currents predominantly act from west to east; while in the summer months they tend to
act more east to west. As a result sediment transport directions and rates generally follow
this seasonal pattern with the majority of sediment moving east in winter and west in
summer. This finding matched previous attempts to characterise the nearshore wave and
sediment environment and also agreed with physical observations.
The outcomes of this study suggest that a number of parties in Esperance could benefit
from further analysis of the wave and sediment climate. The DPI is still collecting wave
data in the region. When this data becomes available it should be analysed and used to
produce detailed wave hind casts that could benefit future coastal design and
management in the area.
10
Acknowledgements
Firstly I would like to acknowledge Prof Chari Pattiaratchi for his help and advice over
the course of this project.
Secondly I would like to thank Stuart Barr from the DPI for proposing this thesis topic
and his help in directing the focus of my thesis. Thanks also to Cathy Clark, Tony
Lamberto and Steve Hearn from the DPI for their help in the making of this thesis.
A massive thankyou goes to Ben Hollings, who gave me probably the most valuable hour
of my thesis with his crash course in SWAN modelling.
Finally, I’d like to thank my friends, family, anyone who lives at Trinity and Fiona for
putting up with me when I’m tired, stressed and grumpy. Your continued support means
more to me then you’ll ever know.
11
1.0 Introduction 1.1 Motivation
Bandy Creek Boat Harbour (BCBH) was constructed in 1983 five kilometres north east
of the Esperance townsite. Shortly after construction, littoral drift sand began to
accumulate in the harbour entrance. The progressive accumulation of sediment has
required regular dredging to maintain navigation at the harbour entrance. Current
estimates of dredging costs are in the order of $1.0 M to $1.5 M every two years due to
difficulties with mobilisation, exposure conditions and seaweed.
The Department of Planning and Infrastructure (DPI) is responsible for the maintenance
of BCBH and is in charge of the current dredging program. Dredging records estimate
that between 30,000m3 and 50,000m3 of sediment can be trapped within the harbour each
year (Sinclair Knight Merz (SKM) 2005). The DPI has advised that 50,000m3 / year may
be the peak influx. The DPI is interested in gaining a greater understanding of the coastal
processes in Esperance, so the current dredging practice might be improved.
1.2 Aim
The aim of this project is to investigate wave action and sediment dynamics in the
Esperance region; paying particular attention Bandy Creek Boat Harbour region.
1.3 Objectives
At the beginning of the project the DPI identified a number of primary objectives that
they desired to have addressed:
· To model and analyse wave data recently collected in the area,
· Determine the near-shore wave climate and sediment transport characteristics of
the area.
12
1.4 Previous Studies
Esperance is unique in comparison to many other coastal areas of Western Australia.
Over the years a large number of studies have been funded and conducted. Initially the
state worked with the Shire of Esperance studying management problems on beaches
between Norseman Road and BCBH. More recently, the Port of Esperance has carried
out studies on the foreshore examining the behaviour renourishment works and proposing
management actions to meet their environmental development conditions (M P Rogers
and Associates 2005). The majority of studies are related to stabilising the Esperance
foreshore and explore:
· nourishment, resulting in the current problems with amenity,
· shoreline stabilisation, using coastal structures such as groynes,
· shoreline defence, using seawalls, or
· a combination of the above.
While all of the studies have recommendations and costs suitable for their brief they are
not easily comparable. The wide range of studies conducted in the area is presented in
Appendix A.
No overall study addressing coastal issues has ever been completed. This is primarily due
to the lack of sufficient directional wave data for the previous studies to accurately
estimate seasonal sediment movements. Potentially all the previous studies could benefit
from more detailed long-term wave hind casting and more complex numerical modelling
of the nearshore wave climate.
13
1.4.1 Prediction and Measurement of Wave energy and bottom shear
stress for Esperance Bay (Johnson & Pattiaratchi 2004)
This investigation aimed to examine the benthic habitats in the Recherche Archipelago
and link their distributions to bottom type and exposure to swells and currents. The
definition of the local wave climate was a primary requirement for the study. The project
used SWAN (Simulating WAves Nearshore), a state of the art wave propagation model,
to predict the wave climate in Esperance Bay. The model was forced using data from a
global hind cast model and was validated using directional wave data collected during the
study.
An InterOcean S4 was deployed, in a frame at 12m depth, in the north eastern part of
Esperance Bay (Figure 1.1). The horizontal water velocity and pressure was sampled at
2Hz. Data segments of 18-minute duration were recorded every two hours. Data was
collected over three periods during 2002-2003 and include both winter and summer
periods:
· 11th June – 21st July 2002
· 12th February - 19th March 2003
· 24th May – 7th June 2003
Spectral analysis was then carried out on each data segment to determine the significant
wave height, peak spectral period and peak spectral direction.
14
Figure 1.1: Deployment position of InterOcean S4 wave rider buoy (Johnson and Pattiaratchi 2004).
SWAN was then run to make daily predictions of significant wave height and peak
spectral direction. The model was run for typical wave conditions experienced within the
region (Figure 1.2, Table 1.1):
· Summer swell waves from the SSW (10-16s peak period)
· Locally generated easterly waves (4-9s peak period)
· Large winter swell from the SW (10-16s peak period)
To validate the numerical model, the predicted and measured wave conditions at the S4
deployment location were compared. In general there was a very good correlation
between the measured and predicted wave parameters. SWAN appeared to slightly
overestimate the maximum and root mean squared significant wave heights. Overall, the
good correspondence with the measurements gives a high level of confidence for the
model predictions.
15
Table 1.1: Predicted significant wave heights and significant wave periods from Johnson and Pattaratchi’s year long wave hindcast.
Hs (m) Tm (s) Season Mean s.d. Mean s.d.
Summer (Dec-Feb)
2.0 0.58 9.5 2.7
Autumn (Mar-May)
1.7 0.49 11.1 2.9
Winter (Jun-Aug)
2.6 0.76 12.4 2.4
Spring (Sep-Nov)
2.3 0.79 11.4 2.5
Annual 2.2 0.7 11.11 2.8
Jan Apr Jul Oct Jan0
1
2
3
4
5
6
Sig
nifi
can
t W
ave
Heig
ht (m
)
Time-series of significant wave height (Hs) for offshoreconditions for 2002.
Figure 1.2: Hindcast of significant wave height for 2002.
16
1.5 Current Dredging Program
The entrance of BCBH has been subject to siltation and has required ongoing dredging to
provide adequate depth for navigation since its completion in 1983. Details for the
current maintenance dredging program for the BCBH entrance are given in contract
documents presented to DPI annually (Dredging Environmental Management Plan
(DEMP) 2005). Dredging is conducted over the winter months from March to October in
order to maintain the navigability of the harbour.
The design depth of BCBH varies from 5.5m depth Chart Datum (CD) at the entrance,
4.2m depth CD in the channel further inside the harbour and 3.0m depth CD in the sand
traps. The volume of material to be dredged is dependant on a pre-dredge survey carried
out in March. However, estimates predict the required volume of sand will be around
70,000m3. Dredged material is pumped to the beach approximately 1,300m east of the
harbour entrance. The material is placed on the beach such that it is allowed to continue
its journey eastwards through natural processes.
The dredged material generally consists of fine to medium grained sand with a median
grain size, (D50 value) of approximately 0.2mm. Significant quantities of seagrass and
seaweed wrack material are often present above and within the material to be dredged.
The 2001-2003 maintenance reports suggest this sand and dredged material is appropriate
for beach nourishment (Jesz Flemming & Associates (JFA) 2003).
It has been suggested that the current dredging program in BCBH may actually increase
the volume of sediment deposited in the harbour mouth (SKM 2005). The exposure at the
mouth of the harbour also has a number of other implications on the dredging operations.
Wave activity at the entrance is often greater than on the harbours seaward side. This is
due to passing sand and wave activity that forms a bar across the mouth of the harbour.
The breakwaters also act to compress flow lines into the harbour mouth increasing wave
heights at the entrance.
17
Both of these effects lead to the shoaling of waves at the harbour entrance, such that
waves increase in height and break on the entrance bar. Dredging and navigation
consequently becomes hazardous at the harbour entrance.
Due to the exposed nature of the harbour and the ability of swell to penetrate the harbour,
sand and a significant volume of seaweed makes it way into the harbour, settling in thick
deposits in the more protected areas of the harbour (DAL Science & Engineering
(DALSE) 2003). Seagrass, seaweed and wrack have been responsible for disruption and
periods of extended downtime in dredging operations. Regular clearing of the cutter
heads from seaweed is a costly and time consuming expense.
In recent years the cost of dredging BCBH has escalated and its cost is predicted to
continue rising into the future. The most recent estimates suggest that the cost of
dredging will be in the order of $1M to $1.5M every two years (Jesz Flemming &
Associates (JFA) 2004). This is about 25% of the total annual budget available to the DPI
for all dredging campaigns throughout Western Australia.
1.6 Coastal Design Criteria
Coastal Engineering practice in the United States of America and throughout much of the
world has been built around the publications of the United States Army Corps of
Engineers (USACE) Coastal Engineering Research Centre (CERC). CERC’s Shore
Protection Manual (Coastal Engineering Research Centre (CERC) 1984) and more recent
Coastal Engineering Manual (Coastal Engineering Research Centre (CERC) 2003) are
technical documents which incorporate all the tools and procedures used to plan, design,
construct, and maintain coastal projects. For any successful use of these documents the
characterisation of the nearshore coastal processes in terms of waves, currents and
sediment movement is required.
18
Consequently, data on coastal processes is required for the functional and structural
design of coastal structures and as a basis for coastal management strategies. According
to CERC (2003) the basic data sets required for coastal design include the following:
· Historical Information – structures and history of coastal processes from records,
surveys, aerial photographs and anecdotal information.
· Meteorological – winds, meteorological patterns, storm details and extreme
values.
· Wave Climate – fundamental wave characteristics for the region, influence of
storms, sea breeze, seasonal changes, long term averages and extreme values.
· Other Oceanographic – tides, long waves, seiches, impact of storm surge and sea
level rise.
· Sediment movement – longshore and cross-shore sediment movement at
timescales ranging from hours to decades.
· Land and Bathymetric – sufficiently detailed bathymetry and shoreline surveys.
· Materials – details of available sediments.
Fleming, in (Abbot & Price 1994), also lists a number of variables that must be defined at
the outset of the application of beach control structures:
· Prevailing direction of longshore drift, its seasonal variation and the ratio of net to
gross transport.
· The extent of onshore-offshore sediment transport and its seasonal variation.
· The variability of the magnitude of littoral drift along the coastline and adjacent
coasts.
· The present rate of change of the shoreline along the study coast and what it
represents in terms of an annual volumetric loss or gain.
· Identification of all sources and sinks of beach material making up a sediment
budget.
· Any long term trends in the annual rate of change of any of the factors.
19
· The need to maintain a shoreline at a particular position or whether retreat is a
viable option.
· Additional factors which may affect the future trends such as sea level rise,
changes in sediment supply etc.
All of these criteria should be analysed or at least considered when preparing to design
costal structures or management strategies for any given area. Most of these data sets are
available for the Esperance region, bar the notable exception of any significant sets of
wave, sediment or other oceanographic data.
1.6.1 Wave Data
In many coastal environments, like BCBH, the limited range of directional wave data is
often a concern for coastal design. Wave data collection is expensive and most records
are consequently of short duration as a result. The Coastal Engineering Manual states that
at least three full years of wave data is required for a reasonably stable characterisation of
wave climate. The majority of coastal engineering projects will often rely on long term
wave hind casts from previously recorded wind and synoptic observation rather then long
term wave data. The analysis of extreme, interannular, seasonal and storm waves at a site
is required to fully characterise the wave climate for use in design.
1.6.2 Current Estimates of Sediment Transport
The existing estimates of sediment transport are based off a single year of wave hind
casts (M P Rogers and Associates 2005). This hind cast was made with limited wave data
periods used for calibration. Additionally, many of these sediment transport estimates
have not been calibrated against known depositions to confirm their accuracy. However,
most of these sediment transport rates have been made for the Bandy Creek area and
provide a characterisation of annual sediment movement in the area. In general the gross
annual transport rates to the east are 57,000m3, primarily due to swell during the winter
months. Gross annual transport to the west has been estimated as 32,000 m3, due to short
20
period seas that occur mainly in summer. There have been no real attempts to estimate
sediment transport at other locations, nor has there been any assessment of the gross
transport rates over short term events.
21
2.0 Environmental Setting
2.1 Location
The town of Esperance is situated on the southern coast of Western Australia, 720
kilometres south-east of Perth (Figure 2.1). Bandy Creek Boat Harbour is located five
kilometres north east of the main townsite.
Figure 2.1: Location map of Esperance.
The East side of the harbour consists of a commercial area, with commercial pens and a
land backed service wharf. On the West side of the harbour, an area has been set up for
the recreational boating community which includes pens and a boat ramp.
2.2 Meteorological Conditions
Esperance experiences hot dry summers and cool wet winters, characteristic of a
subtropical Mediterranean climate. The prevailing weather conditions of south-western
Australia are governed by an eastward moving subtropical high pressure belt dominated
22
by anticyclones (Gentilli 1971). During winter, this system is periodically disrupted by
storms originating from mid- latitude depressions, while in summer a strong sea breeze
system dominates the local environment. The sea breeze plays such an important role in
the local environment it is often coined by locals as the “Esperance Doctor” (Gentilli
1971).
2.2.1 High Pressure Systems
The normal breakdown of the high pressure belt into anticyclonic cells leads to the
prevailing circulation in south-west Australia to be anticlockwise (Gentilli 1972). In
winter this high pressure belt is located between the latitudes of 26°S and 34°S leading to
south-westerly, while in summer the belt moves south between the latitudes of 35°S and
45°S causing easterly winds.
2.2.2 Mid-latitude depressions
In summer months, the southerly location of the anticyclonic belt forces mid- latitude
depressions to far south to significantly impact the southern coastline of Australia.
However, during winter mid- latitude depressions can occur much further northward and
have the propensity to cause highly energetic storm conditions (Gentilli 1972). Average
wind speeds of these storms are between 15 – 29ms-1, and are accompanied by much
stronger gusts (Steedman 1982). The resulting wind directions from these storms range
from northwest to southwest, with the strongest winds generally coming from the
northwest (Silvester 1987).
2.2.3 Sea breeze system
The south west of Western Australia has one of the strongest sea breeze systems in the
world (Gentilli 1972). The Esperance Doctor is such a powerful system that on any hot
windless day the breeze can produce a significant temperature drop in Kalgoorlie 350
kilometres away. For this phenomena to occur the breeze must travel at approximately
23
40 kilometres per hour. However, this estimate is not an accurate as the sea breeze system
does not always penetrate this far inland (Clarke 1955). Clarke estimated the Esperance
Doctor averaged speeds of 10ms-1 with wind speeds often approaching that experienced
by storm conditions. The Esperance sea breeze is a southerly system, matching the
southerly facing coastline.
2.2.4 Extreme wind conditions
Extreme wind conditions play a crucial role in the mobilisation of sediment. Stronger
winds generate extreme waves and currents that have the potential to cause rapid
movement of sediments in the nearshore zone. The Bureau of Meteorology has been
collecting wind data in the area for a significant length of time which allows for a
definition of extreme wind characteristics. Typical storm average wind speed and
duration for the area range from 10-22ms-1 with a duration of 10-35 hours. These extreme
winds typically come from the West south-west as a result of passing mid latitude
depressions.
2.3 Wave Climate
2.3.1 Wave Field Definitions
Significant Wave Height (Hs)
This is defined as the average height of the highest 1/3 waves and is commonly used in
visual estimates of sea state. Individual waves may be up to twice the significant wave
height. In typical ocean wave spectra, this can be related to the total spectral energy
density by Hs = 4 M0 where M0 is the zeroth spectral moment (equivalent to the total
wave density).
24
Peak period (Tp)
The spectral peak period is the wave period with the greatest energy when summed over
all the directions. This is the same as the period corresponding to the highest point on the
(non-directional) frequency spectra.
Peak direction (Dp)
The spectral peak direction is the wave direction with the greatest energy when summed
over all the frequencies. It is important to note that this may not necessarily correspond to
the direction of the point of highest energy in the directional spectra. This is often
converted to the conventional swell specification of the direction of origin of the waves.
2.3.2 Offshore wave climate
The DPI placed a non-directional wave buoy at latitude 34°00’02” S, longitude
121°54’00” E from 13/06/06 onwards. The buoy was deployed in 52 metres water depth
south of Bandy Creek boat Harbour. The DPI has only received four months worth of
data from this buoy from June to September (Figure 2.2).
25
Jun Jul Aug Sep Oct0
1
2
3
4
5
6
Sig
nifi
can
t W
ave
He
igh
t (m
)
Time-series of significant wave height (Hs) for Offshore conditions Esperance, 2006
Figure 2.2: Plot of significant wave heights taken from offshore conditions in Esperance, 2006.
The mean significant wave height for all measurements was 1.2 m and the measured
maximum wave height was 5.7 m.
The peak periods were mainly in the range 12 s to 16 s, consistent with the dominance of the
wave energy by remotely generated swell (Figure 2.3). There were some shorter periods
corresponding to locally generated sea. The exceptionally long periods of over 18s coincided
with times of low significant wave heights. As the lower period wave components in the sea
state are attenuated more by bottom friction than the long period waves, it appears that the
longest period components of the wave field become dominant at the instrument location
during times of very low swell heights.
26
0 2 4 60
100
200
300
400
500
600
700
800
Significant Wave Height, hs (m)
Perc
enta
ge O
ccu
ren
ceN = 2520 a)
5 10 15 20 250
100
200
300
400
500
600
700
800
900
Spectral mean wave period, Tm (s)
Perc
enta
ge O
ccu
ren
ce
N = 2520 b)
Figure 2.3: Distribution of Significant Wave Height (a) and Spectral mean wave period (b) for Offshore conditions Esperance (July-October 2006).
The DPI’s offshore wave data was non directional, consequently other sources of data
were used to analyse wave direction. Johnson and Pattiaratchi’s 2002 study they found
winter wave directions within the bay were consistently from the WSW, with a mean of 240°.
During the summer they found there were periods with waves from the south that coincided
with lower wave heights and shorter periods. This was consistent with periods of easterly
winds during which the waves would be expected to propagate into the bay from the
southeast.
2.3.3 Nearshore wave climate
The DPI placed a non-directional wave recording instrument at latitude 33°50’26” S,
longitude 121°55’58” E from 17/02/05 to 28/01/06. The instrument was deployed in 12
metres water depth just south of Bandy Creek boat Harbour.
27
The instrument recorded significant wave height and wave period hourly. This data was
then broken down and analysed on a seasonal level (Figure 2.4, Table 2.1).
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
0.5
1
1.5
2
2.5
Sig
nifi
can
t W
ave
He
igh
t (m
)
Time-series of significant wave height (Hs) for Bandy Creek Boat Harbour 2005.
Figure 2.4: Total Significant wave height at Bandy Creek Boat Harbour, 2005.
Table 2.1: Nearshore wave statistics for Bandy Creek Boat Harbour, Esperance (February-December, 2005).
Hs (m) Tm (s) Season Mean s.d. Mean s.d.
Summer (Dec-Feb)
0.62
0.24
11.7
2.5
Autumn (Mar-May)
0.50 0.19 13.8 2.4
Winter (Jun-Aug)
0.64 0.28 13.9 2.3
Spring (Sep-Nov)
0.64 0.26 13.7 2.8
Annual 0.60 0.25 13.5 2.6
28
The joint distribution of wave height and period emphasises the difference between
summer and winter wave conditions (Figure 2.5). During the summer months
(November-April), most waves had a height/period combination of 0.4 to 0.6 m and 12.0
to 14.0 s (Figure 2.5a). Over the winter months (May-October), the modal height-period
combination was 0.5 to 0.65 m and 13.0 to 15.0 s (Figure 2.5b). Wave heights were
lower, and confined to a much narrower range, in summer than in winter (Figure 2.5a, b).
Hence, at Esperance there is a wave climatic shift from moderate, locally generated seas
in summer, to higher, distantly generated swell and locally generated storm waves in
winter. This pattern coincides with the seasonal wind pattern: during summer, local daily
sea breezes generate moderate seas; during winter, storms associated with the passage of
mid- latitude depressions generate larger seas and swell.
Spectral mean wave period, Tp (s)
Spect
ral w
ave
heig
ht, H
s (m
)
a)
3 6 9 12 15 18 21 24
.2
.4
.6
.8
1
1.2
1.4
1.6
1.8
2
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
29
b)
Spectral mean wave period, Tp (s)
Sig
nifi
cant
wave
he
igh
t, H
s (m
)
3 6 9 12 15 18 21 24
.2
.4
.6
.8
1
1.2
1.4
1.6
1.8
2
0.04
0.06
0.08
0.1
0.12
0.14
0.16
Figure 2.5: Combined distribution of significant wave height and spectral mean wave period off Bandy Creek Boat Harbour, with percentage occurrence contours: (a) summer (November-April) and (b) winter (May-October).
The relative frequency distribution of the wave height indicates a modal height of 0.4 m
and a range of heights from 0.2 t o 2.0 m (Figure 2.6). The cumulative frequency
distribution (or percentage exceedence diagram) of the wave height can be used to
determine the percentage of observations whereby the significant wave height is greater
than a certain value (Figure 2.6). The 10%, 50% and 90% exceedence Hs values are
1.25m, 0.65m and 0.35m, respectively. The relative frequency distribution of the spectral
mean wave period indicates a modal spectral mean wave period of 14s and a range of
periods from 4 to 22s (Figure 2.6). The percentage exceedence diagram for the wave
period indicates a 50% exceedence Tm of 16s (Figure 2.6).
30
Wave heights were lower during the summer period and also showed a longer time gap
between periods of high swell. The significant wave heights at the instrument location
will be smaller than offshore conditions as wave energy is dissipated with the bay.
0 0.5 1 1.5 2 2.5 30
1000
2000
3000
Perc
en
tage O
ccure
nce N=7314 a)
0 5 10 15 20 25 300
1000
2000
3000N=7314 b)
Perc
en
tage O
ccure
nce
0 0.5 1 1.5 2 2.5 30
20
40
60
80
100c)
Significant Wave Height, hs (m)
Perc
enta
ge
Exc
eed
ence
0 5 10 15 20 25 300
20
40
60
80
100d)
Spectral mean wave period, Tm (s)
Perc
enta
ge
Exc
eed
ence
Figure 2.6: (a) Relative and (c) cumulative frequency distribution of significant wave height. (b) Relative and (d) cumulative frequency distribution of spectral mean wave period, (February 2005-December 2005, nearshore Bandy Creek Boat Harbour).
Finally, an analysis of nearshore wave climate requires an understanding of extreme
storm events. A description of the storm wave climatology first requires an appropriate
definition of a storm event. In the present study, a storm was defined as an event where
the peak significant wave height exceeded 1.1 m (Figure 2.7). The initiation of the storm
was defined as the time when the hourly-averaged significant wave height exceeded 1.1
m; the end of the storm was defined as the time that the hourly averaged significant wave
height fell below 1.1 m (Figure 2.7). For each of the identified storms, the duration of the
storm and the peak and mean significant wave height were computed.
31
The extreme high wave conditions caused by storms over the coastal waters of Esperance
are of primary concern for designing offshore and coastal structures. 18 storms as defined
earlier, were observed over 2005 (Figure 2.7). The largest storm had a peak Hs of 2.02 m
with a duration of 36 hours, and occurred in August. The average peak Hs of the storms
was 1.6 m and the average mean Hs over the storm duration was 1.5 m. The average
storm duration was 12 hours; no clear relationship between storm intensity and duration
could be discerned from the data. The majority of the storms occurred during the winter
months (May-October). September was the stormiest month with seven storms occurring
in 2005.
FebJan Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
0.5
1
1.5
2
2.5
Peak H
s (
m)
a)
FebJan Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
0.5
1
1.5
2
2.5b)
Me
an
Hs (
m)
FebJan Mar Apr May Jun Jul Aug Sep Oct Nov Dec0
20
40
10
30
50c)
Sto
rm D
ura
tio
n (
h)
Figure 2.7: Temporal distribution of storms offshore from Perth: (a) storm peak Hs; (b) storm mean Hs; and (c) storm duration.
32
2.4 Long Period Water level Fluctuations
Long period water level fluctuations play an important role in coastal processes. Due to a
significant alteration of sea level height at the coast, waves and currents can begin to alter
regions that are normally untouched by coastal processes. In more sheltered
environments, such as estuaries and harbours, these water level fluctuations are often the
most important hydrodynamic forces that occur. At Bandy Creek Boat Harbour,
Esperance, long period water level fluctuations like tides, storm surges and seiches are
relevant.
2.4.1 Tides
There is an extended historical tidal record in Esperance. The DPI started measuring tidal
data at the Esperance port in 1991 and has collected a continuos record from 1994 to the
present day (Department of Planning and Infrastructure (DPI) 2006). Tides in Esperance
are diurnal in nature with one tidal cycle per day and are microtidal in range. Typical
daily tidal ranges for Esperance are around 0.4m (Sinclair Knight Merz (SKM) 2005).
This range is considered small in engineering terms and would not be anticipated to
generate tidal velocities capable of mobilising large volumes of sediment.
2.4.2 Storm surges
Storm surges are variations in water level due to meteorological effects. These surges are
not periodic in nature and can have a substantial effect on water level when there is a
rapid change in barometric pressure. Storm surges have a significant effect on beach
processes and morphology when surge levels exceed the local tidal range (Jackson &
Nordstrom 2002). Under extreme storm conditions surge levels in Esperance can exceed
one metre above any recorded tidal observation (Department of Transport (Transport)
1994).
33
The surge level due to a passing meteorological system is dependant on four features: the
change in pressure, the speed of the pressure system, the wind speed and the water depth
(Pattiaratchi 2006). While storm surges generally act to increase the water level at the
coast, the right set of meteorological conditions can cause a set down in water level.
When strong offshore winds prevail under high barometric pressure systems, low water
levels or negative surges can occur at the coast.
2.4.3 Seiches
Seiches are long period water level oscillations that occur in enclosed or semi enclosed
water basins. Seiches are started by external forcing conditions, such as passing weather
systems, initiating oscillations which continue for some time after the forcing condition
has ceased (Coastal Engineering Research Centre (CERC) 2003). There has been very
little research to examine wether any seiching occurs in the Esperance region. The
Recherche Archipelago has enclosed boundaries in the East-West direction and is semi
enclosed by the continental shelf in the North-South direction, so the potential for
seiching exists. However the amplitude of any seiche occurring in the area will most
likely be considerably smaller than tidal range, limiting the ability of any seiche to affect
sediment mobility.
34
3.0 Morphodynamics relevant to Esperance
3.1 Sediment Mobility
To correctly estimate or define sediment transport in a region it is important to
understand the concept of sediment mobility. Sediment mobility refers to the idea that
sediment will not move from the seafloor until some threshold flow condition is
exceeded. If the threshold condition is not exceeded then no sediment transport will take
place. To characterise sediment dynamics near Bandy Creek Boat Harbour sediment
mobility is an important concept.
The most commonly used critical mobility parameter is the Shield’s parameter, θcr. To
understand this parameter the forces acting on a sediment particle must first be
considered.
3.1.1 Forces acting on a sediment particle
The forces acting on a submerged sediment grain can be broken into four distinct
categories:
· Gravitational forces, relating to the weight and buoyancy of the particles.
· Lift forces, resulting from the Bernoulli Effect due to fluid flow over the particle.
· Drag forces, from fluid flow over the particle.
· Frictional forces, due to the reaction between the particle and other elements the
particle is in contact with.
Drag forces are often considered to be the most important factor in the mobilisation of
sediment grains and is consequently often referred to as the “mobilising force” (Coastal
Engineering Research Centre (CERC) 2003). However, drag force is not normally used in
sediment mobility calculations and is often expressed in terms of a shear stress (τ). Shear
35
stress can then be broken into two different components: τmax, the maximum shear stress
at the seabed and τcr, the critical shear stress, which is the shear stress required to
mobilise sediment (Coastal Engineering Research Centre (CERC) 2003). When surface
waves are deemed to be the primary cause of mobilised sediment, a suitable wave theory
must be selected before τcr can be calculated.
3.1.2 Selection of suitable wave theory
There are four primary wave theories that all have different mathematical definitions. To
select the most suitable wave theory basic wave parameters such as period, height and
water depth must be considered. The most basic wave theory is Airy wave theory (linear)
which considers waves that are basically sinusoidal in nature. Airy waves occur when
wave heights are small in comparison to water depth. As the water depth decreases, wave
heights increase and breaking or shoaling can occur. In these conditions higher order
wave theories such as Cnoidal or Stokes wave theories are more applicable.
In 1976 Le Méhauté presented the following graph to illustrate the approximate limits of
validity for the most commonly used wave theories (Méhauté 1976).
36
Figure 3.1: Ranges of suitability of various wave theories (Méhauté 1976).
This study attempts to determine the nearshore wave climate around BCBH.
Consequently, shallow water waves near their breaking limit will be considered in detail.
Le Méhauté’s ranges of suitability of various wave theories suggest that cnoidal theory
should be used for calculating peak orbital velocity under these conditions.
While cnoidal theory is considered to be the best mathematical approximation for shallow
water waves near the breaking limits there have been studies that show different wave
theories agree with actual measurements to a higher degree (Dean 1974). Work by the
Coastal Engineering Research Centre has attempted to demonstrate which wave theories
37
exhibit the highest degree of analytical validity. While the best mathematical
approximation for shallow water waves near the breaking limit is cnoidal wave theory,
predictions using linear (Airy) theory have a greater analytical validity (CEM 2003).
3.1.3 Maximum shear stress
τmax is the maximum shear stress at the seabed over one complete wave cycle. The
maximum shear stress is defined in the following equation:
2
maxmax2
1Ufwrt = (1)
Where r is the density of the fluid, wf is the wave friction factor and maxU is the peak
orbital velocity at the seabed. Thus to calculate τmax, wf and maxU must be found first.
3.1.4 Wave friction factor
The wave friction factor ( wf ) is used in the calculation of maximum shear stress to allow
for the friction generated by the fluid/seabed interaction. The closest approximation for
the wave friction factor is dependant on both wave parameters, and bed roughness, R
(Swart 1976):
wf = exp[-5.98+5.21(A0 / R)-0.19] for A0 / R > 1.57 (2)
= 0.3 for A0 / R > 1.57
max02
UT
A P
p= (3)
However, this approximation is only valid in the turbulent case and must be checked
accordingly.
38
For initial shear stress calculations, a spatially uniform bed roughness of 0.001 is generally
used. However, this is not realistic for all types of bottom substrate that are present in many
locations. In addition, the presence of biota such as sea grasses may significantly increase the
friction factor.
3.1.5 Peak orbital velocity
The peak orbital velocity ( maxU ) is the maximum instantaneous fluid velocity
experienced under a passing wave (Bailey 2005). Fluid particles move in circular or
elliptical orbits as waves pass. Under shallow or transitional waves fluid particles move
in an elliptical orbit whereas, with deep water waves fluid particles follow a circular orbit
(Coastal Engineering Research Centre (CERC) 2003) (Figure 3.2).
Figure 3.2 Fluid particle displacement under waves (Coastal Engineering Research Centre (CERC) 2003)
Under shallow or transitional water waves the fluid orbits become increasingly flatter
with depth. At the seabed there is no vertical movement of water and hence no vertical
39
component in the orbital velocity. Thus, calculations for the peak orbital velocity can be
made by evaluating the peak horizontal velocity.
In linear (Airy) wave theory, the peak orbital velocity at the seabed can be simplified to:
( )khT
HU
P
S
cosh
1max
p= (4)
Lk
p2= (5)
Where HS is the significant wave height, TP is the peak spectral period, k is the local wave
number, L is the wavelength and h is the water depth.
It is important to note that a real sea has a varying orbital velocity corresponding to the
variable periods and wave heights. The characteristic peak orbital bed velocity can be
calculated for a characteristic wave with significant wave height at the peak spectral
period. The largest wave encountered in a given sea state is usually twice the significant
wave height so an upper bound for the bottom orbital velocity could be estimated as
2Umax (Johnson & Pattiaratchi 2004).
3.1.6 Critical mobility parameter
After calculating the maximum shear stress at the seabed for a given set of wave
conditions the critical mobility parameter (τcr) can then be evaluated. From the critical
mobility parameter sediment mobility can be calculated from a modified Shield’s
diagram (Figure 3.3):
40
Figure 3.3: Modified Shield’s diagram.
To correctly use the modified Shield’s diagram a number of parameters must be used:
s = the specific gravity of the sediment particles that make up the seabed
D50 = the median grain diameter
v = the fluid viscosity (10-6 m2s-1 in seawater) and,
u*cr = the critical dimensionless friction velocity, given by:
2
1
* ÷÷ø
öççè
æ=
r
t crcru (6)
When a particular sediment has a known D50, specific gravity and is subjected to wave
actions with known characteristics, the modified Shield’s diagram can be used to predict
wether that sediment will be mobilised or not.
41
To use the diagram the dimensionless grain size parameter, D* is calculated so that the
corresponding value for the critical mobility parameter, θcr, can be determined. By
substituting equation (6) into the formula for θcr given in the Shield’s diagram and
rearranging for τcr yields the following equation:
( ) 501 gDscrcr rqt -= (7)
If the maximum wave induced shear stress τmax, is less than the critical shear stress τcr,
then the sediment is unlikely to become mobile. However, if the reverse is true and the
maximum wave induced shear stress is greater than the critical shear stress then the
sediment is likely to become mobile.
3.2 Modes of Sediment Transport
When sediments are mobilised from the seafloor they can be transported in two different
ways. When the threshold conditions are only just exceeded sediment transport occurs
through grains rolling, sliding or jumping (saltating) along the bed. This type of transport
is dominated by gravitational forces and is known as bedload transport.
When the threshold conditions are further exceeded by the flow intensity increasing,
grains make extended jumps where they only remain in contact with the seabed for a
fraction of a time. This type of transport is called suspended transport as the sediment
particles are suspended in the water column above the seafloor. Turbulent forces dictate
the amount of sediment transport in these conditions. The suspended transport is often
considered to be highly important as suspended grains are more easily influenced by
other factors such as longshore currents.
42
3.2.1 Threshold for suspension
The threshold required for suspension is based on a number of different parameters.
Firstly, the Bagnold criterion determines wether a particle will remain in suspension
when turbulent eddies have a vertical velocity greater than the settling velocity (8).
( )gds
wscr
1
2
-=q
(8)
Where ws is the settling velocity
( ) 2
18
1gDw ss rr
m-=
(9)
Where µ is the dynamic fluid viscosity (µ=ρυ), ρs is the sediment density, and D is the
sediment diameter.
The second criterion is the Rouse parameter, P. The Rouse parameter determines the ratio
between settling velocity and turbulence forces (10).
*u
wP s
k=
(10)
Where κ is the von Karman constant (0.408) and u* is the dimensionless friction velocity
given in (6).
From these parameters the criteria for suspension can be written as:
43
*u
wP s
k=
> 2.5; no suspension
1 < *u
wP s
k=
< 2.5; incipient suspension
*u
wP s
k=
< 1; full suspension
This can also be re-written and expressed in terms of shear stress:
2
max swrt < no suspension
2
max swrt > incipient suspension
2
max 25.6 swrt > full suspension
Incipient suspension is considered to be the lowest level of suspension, where particles
are being moved through small jumps or minor saltation. These criteria determine wether
a particle will undergo transport through bedload or suspension processes (Figure 3.4).
44
Figure 3.4: Ranges of sediment motion (Yalin 1977).
3.3 Prediction of sediment transport
Trying to accurately predict sediment transport is a notoriously difficult task. Hence,
basic beach morphodynamics should be understood before any estimates of sediment
transport can be made. Komar (1998) identified three general trends that effect sediment
movement on sandy beaches. Firstly, during storms sand is transported offshore. This
cross shore transport leads to narrow beaches and offshore bar formation to dissipate
wave energy. The reverse then occurs in calmer or swell dominated periods. Under these
conditions sediment is generally transported onshore creating wider beaches. Most
studies of beach morphodynamics tend to suggest that the net cross shore transport will
remain in equilibrium with no sediment lost or gained in the cross shore direction.
45
Longshore transport is due to prevailing wave directions and can lead to net gains and
losses in a beach’s sediment budget. Longshore transport is responsible for the littoral
drift sand that causes siltation in Bandy Creek Boat Harbour.
3.3.1 Longshore sediment transport
Littoral transport or longshore sediment transport is the transportation of sediments
parallel to the shore. Longshore transport occurs primarily within the surfzone where
wave action mobilises sediment particles. Longshore currents with velocities well below
the threshold required for particle mobilisation are then able to influence the direction of
sediment transport (Komar 1998). While longshore transport can be driven by a number
of different means, the longshore currents generated by waves breaking at an angle to the
shore can be considered the most significant factor for longshore sediment transport in
the Esperance region.
On virtually every piece of coastline, waves will arrive at the shore from different
directions. This effect can produce day to day and seasonal changes in the longshore
sediment transport direction.
Longshore currents originate from the longshore component of radiation stress
(momentum flux), given by the following:
aar sincos8
2gHn
S xy = (11)
Analysing equation 11 it can be seen that the main factors affecting wave induced
longshore currents are: H, the wave height and α, the angle between the wave crest and
bottom contours. n, is the ratio of wave group speed and wave phase speed and is
considered to be approximately 1 in shallow water conditions.
46
If there are longshore currents in a nearshore wave environment then the potential for
longshore sediment transport exists. There are many ways to estimate longshore sediment
transport; however, different methods of estimating sediment transport can often yield
highly different results. Any estimate of longshore sediment transport must be treated
with a certain degree of caution until it can be confirmed through long term data
regarding sediment movement.
In a lecture on the “prediction of sediment transport on beaches” Professor Charitha
Pattiaratchi highlighted the following semi empirical formula for estimating longshore
sediment transport:
)cos()sin()(8.6 bbbS ECnQ aa= (12)
2
8
1gHE r=
ghC =
Where SQ is the volumetric transport rate in m3/day, E is the wave energy, C is the
shallow water wave velocity and ba is the breaking wave angle.
To apply equation 12 the breaking wave parameters must be calculated. Numerical
modelling is often not very accurate in the nearshore zone due to limitations on
bathymetry and the rapid change in wave parameters as waves shoal (Hollings 2006).
Consequently, waves need to be manually transformed as they approach the coast to
determine breaking characteristics.
Goda’s method (1970) and more recently Weggel’s (1972) are two of the most
commonly used techniques in coastal engineering to determine breaking wave
characteristics such as: breaking wave height and breaking wave depth. To use the
47
diagrams and formulas presented in Weggel’s (1972) method the local slope and offshore
wave characteristics must be known.
Weggel proposed that the breaker index γb is equal to:
2gT
Hab b
b -=g (13)
Where Hb is the breaking wave height, g is the effect of gravitational acceleration, T is
the wave period and the parameters a and b are semi empirical formulas for beach slope:
)1(8.43 tan19 b--= ea
and
( )btan5.191
56.1-+
=e
b
β is the slope of the beach, where the relationship tan β is the rise of the beach over its
length.
To calculate γb an estimate for Hb must be made. Komar and Gaughan (1973) derived a
semi-empirical relationship for the breaker height index from linear wave theory.
5
1
56.0
-
÷÷ø
öççè
æ=W
o
ob
L
H
Ho and Lo are the offshore wave height and offshore wave length respectively.
Where Hb can then be estimated as:
48
obb HH W= (14)
The last breaking wave parameter is the breaker depth, db. This can be calculated by
substituting the results from equations 13 and 14 into equation 15.
b
bb
Hd
g= (15)
These breaking wave characteristics can then be used in equation 12 to make estimate of
the volumetric transport rate in the longshore direction per day.
In Esperance the predominant offshore wave direction is from the southwest with sea-
breezes and storm winds coming from the south and southwest. Given the angle of the
shoreline, this leads to predominantly eastward sediment transport. During summer,
periods of lower swell and easterly winds lead to a reversal in the direction of longshore
sediment transport.
49
4.0 Methods
Numerical wave modelling using SWAN was performed to evaluate wave parameters at
different points around BCBH. These wave model outputs were then used to characterise
sediment transport at these sites.
4.1 Numerical Wave Modelling
Initial numerical simulations of the wave conditions across the Esperance Bay region
were carried out in 1987 by Riedel and Byrne. This model accurately predicted the
formation of a dense bar across the harbour entrance under swell conditions. Many of the
later reports have relied off the results of this report to estimate sediment movement in
the area. In 1994 Kirby and Dalrymple used the model REFDIF to model wave
parameters in the bay. However, the model was shown to have unacceptable levels of
noise related to wave propagation around the many islands in the Esperance Bay domain.
An alternative numerical model, SWAN, was used in Johnson and Pattiaratchi (2004) and
was found to perform far better in the complex geometry of the model domain.
4.1.1 SWAN wave model details
SWAN (Simulating WAves Nearshore) is a state of the art, third generation wave
propagation model. SWAN is the result of current knowledge regarding the generation,
propagation and transformation of wave fields in the nearshore. The model is available
under a public license, and is described fully in the user manual (Holthuijsen et al. 2004).
SWAN calculates the transformation of the directional wave spectrum over arbitrary
bathymetry, providing spatial and temporal maps of energy contained in the component
waves of different periods and directions.
50
It should be noted that SWAN does not simulate diffraction though this should have little
effect except in the immediate shadow zones of the islands. For monochromatic waves,
the lack of diffraction leads to unrealistic total shadows behind the islands; however,
because a directional spectrum is modelled in the SWAN simulations, a significant
amount of wave energy still enters the shadow region and the lack of diffraction should
be small except within one to two wavelengths of the island (Booij et al. 1992).
4.1.2 Modelling design
Ideally, modelling would be performed with the major aim of producing one year of
hourly wave data for the nearshore zone around Bandy Creek Boat Harbour. However,
lacking nearshore directional wave data it would be impossible to accurately validate the
model outputs. Consequently a series of ‘stationary’ model runs would be performed to
evaluate basic wave parameters experienced under important wind and offshore wave
conditions.
The model was run in stationary mode for a particular offshore wave field. Stationary
mode means that the conditions in the Bay are in equilibrium with the offshore
conditions, which is a good assumption for the scale of the model domain, as wave
energy propagates through the domain much faster than significant changes in the
offshore wave climate.
The wave spectrum at the outer (offshore) boundaries of the model domain at any
particular time were determined from known wave periods and significant wave heights.
4.1.3 Input data
To use SWAN, data had to be converted to a specific format that was readily useable by
the model. Input data was converted using a MATLAB based GUI (Graphical User
Interface) program written by Ben Hollings.
51
Wind
Hourly wind data from the Bureau of Meteorology (BOM) Esperance station was used.
The Esperance wind station is located several kilometres inland, while coastal wind data
would be more desirable readings from this station were considered to be the best
available data for the situation.
Raw wind data from the BOM is presented as a wind speed in kilometres per hour, and a
directional bearing. This data was converted into x and y components, and metres per
second to be utilised by SWAN.
Offshore Waves
There is very little real offshore wave data for Esperance and this data is limited to the
winter months of 2006. Consequently this data and the offshore wave hind cast data from
the year 2002 – obtained from Johnson and Pattiaratchi 2004, were analysed to produce a
series of different wave conditions. The wave parameters that could be extracted from the
hind cast and real wave data were significant wave height, peak spectral wave period and
peak spectral wave direction.
Nearshore Waves
The DPI recently collected a full year of non-directional wave data just outside Bandy
Creek Boat Harbour in 12 metres of water depth. While SWAN has been proven to work
better with offshore conditions, this nearshore data can be used to validate SWAN’s
output. As the nearshore data is non-directional, SWAN’s outputted significant wave
height and significant wave period are the only wave parameters that can be validated
with the DPI’s nearshore data.
Bathymetry
A coarse bathymetric grid was obtained off Professor Chari Pattiaratchi from previous
work he had done in the Recherche Archipelago. Depth soundings of the Esperance
coastline provided by the DPI were inputted into this bathymetric grid using GIS
(Geographic Information System) software (Appendix B). This bathymetric grid was then
52
simplified to a 100m resolution for use in the model. The domain of this bathymetric grid
was then defined in terms of easting, northing and depth, where the easting and northing
values are for the Australian Geographic Zone 51.
4.1.4 Data extraction
SWAN returns wave parameters for every cell on the bathymetric grid. Three areas of
interest around the bay were selected for analysis. These sites included points near the main
Esperance Port, Bandy Creek Boat Harbour, and the dredge disposal site east of Bandy
Creek. These points of interest where identified on a map of the area and were located using
the latitude and l ongitude grid on the map. These coordinates were then converted into
Northings and Eastings so that they could be located on the bathymetric grid output.
4.1.5 Model validation
The model was validated using nearshore wave data collected in 2005 by the DPI. The
model was calibrated using any available offshore wave data and the offshore wave
hindcast data from Johnson and Pattiaratchi 2004. The model was then run for a variety
of commonly observed wave events such that the offshore conditions at the point marked
in Figure 4.1 matched observed data. The significant wave conditions such as seasonal
averages and average storm events were then compared to analysed nearshore data to see
how accurate the model was at predicting wave climate in the area.
53
Figure 4.1: Bathymetric grid used for SWAN modelling. The upper red circle indicates the location of the nearshore wave buoy, while the lower red circle shows the location of the offshore wave buoy.
4.2 Estimating Sediment Transport Characteristics
The output data from SWAN was used to characterise sediment transport at different sites
around the bay. However, using a 100m bathymetric grid does not allow for an accurate
estimation of breaking wave parameters, such as breaking wave angle and breaking wave
height (Bailey 2005). Consequently, sediment transport will be characterised at the
closest possible point with 4m water depth rather than the breaker zone.
54
4.2.1 Maximum Shear Stress
Assuming linear wave theory is the most suitable wave theory, equations 1-4 were used
to calculate maximum shear stress. By using the wave parameters outputted by SWAN
for each site, maximum shear stress could be calculated for each set of wave conditions.
For initial shear stress calculations, a spatially uniform bed roughness of 0.001 was used.
While this is estimate is not realistic for all types of bottom substrate; when the seabed
substrate is not know this is considered to be a nominal value for the roughness factor
(Johnson & Pattiaratchi 2004). In cases when the seabed substrate is known the
roughness factor should be calculated; additionally the presence of biota such as sea
grasses may significantly increase the friction factor. However, in this study it was not
possible to calculate the roughness factor at each location due to a lack of information
available on bottom substrate types.
4.2.2 Mobilised grain size
Shield’s method was used to determine which grain size was most likely to become
mobile under wave conditions from SWAN output data. Use of Shield’s method and the
modified Shields diagram is outlined in section 3.1.6. There is a fundamental problem to
using this method, it requires both the dimensionless particle size (D*) and the critical
mobility parameter (θcr) to be known. Both of these parameters require the median grain
size (D50) to be already known. To overcome this, an iterative solution must be used.
Bailey (2005) designed an iterative MATLAB routine that solved for a final mobilised
grain size. The basic steps followed in the routine ‘mobgrain.m’ consisted of:
1. Making an arbitrary initial guess for D50 (500microns)
2. Using this D50 value to evaluate a value for D*
3. Using the equations from the modified Shield’s diagram to calculate a value of θcr
4. Rearranging the formula for θcr to find a new D50 value
5. Repeating steps 2-4 till an acceptable tolerance is reached.
55
This routine was modified and used to evaluate mobilised grain sizes in different areas
under different wave conditions (Appendix C). To calculate D* and θcr, specific gravity
(s) was approximated as 2.65, which is appropriate for sands comprised mainly of
calcium carbonate and quartz (Coastal Engineering Research Centre (CERC) 2003).
4.2.3 Suspended grain size
As outlined in section 3.2.1, the suspended grain size is the grain size most likely to
undergo suspended transport under set wave conditions. The grain sizes most likely to be
transported through suspension were calculated using the shear stress criteria for incipient
suspension. Sediment density was approximated as 2650kg/m3, a value considered by
CERC (2003) to be a good estimate for the density of any natural sediment comprised
mainly of calcium carbonate and quartz.
4.2.4 Longshore transport
Rough estimates of longshore transport were to be calculated for each location under the
four modelled conditions. This was done using the method outlined in section 3.3.1. To
use this semi empirical formula the breaking wave parameters are required. However, due
to SWAN’s accuracy in the surf zone wave parameters at a 4m depth were used as the
offshore wave parameters (Hollings 2006). The wave angle αb, was calculated using an
estimate of shoreline angle and wave orthogonals calculated from the SWAN’s wave
direction output. Finally, local slopes were required to calculate the breaking wave
parameters. To determine these slopes, depth soundings from the DPI were used
(Appendix B).
56
5.0 Results
5.1 Operability Analysis
Planning by the offshore industry requires a knowledge of the persistence of various sea
states, in particular calms and storms (Lemm et al. 1999). However this is also true for
any nearshore project such as dredging at harbour entrances. Wave height persistence
curves were calculated for the one year period from February 2005 to December 2005 to
provide information on weather windows (Figure 5.1) a n d downtime (Figure 5.2).
Weather windows quantify periods during which low wave conditions are maintained
(i.e. non-exceedence) (Lemm et al. 1999). For instance, figure 5.1 shows that the
significant wave height remained below 0.6 m for longer than 24 h on approximately 100
occasions per year. Downtime quantifies periods over which high waves persist (i.e.
exceedence). For example, Figure 5.2 shows that on two occasions per year, significant
wave heights remained above 1.4 m for more than 24 hours.
57
Figure 5.1: Persistence of ‘calms’ (weather windows) (February 2005 – December 2005, Nearshore Bandy Creek Boat Harbour).
58
Figure 5.2: Persistence of ‘storms’ (downtimes) (February 2005 – December 2005, Nearshore Bandy Creek Boat Harbour).
5.2 Numerical Wave Modelling
Outputs from stationary SWAN runs have been used to evaluate significant wave patterns
within the Recherche Archipelago. The following figure (Figure 5.3) shows predicted
wave heights and directions for the area under typical winter storm conditions:
59
Figure 5.3: Significant wave height (m) and direction under average winter storm conditions (Offshore Boundaries: Hs = 4.5m, Tp = 10s and Direction = 225°, wind speed = 16m/s at 225°).
The islands directly south of the main townsite play an important role in sheltering the
western half of the bay under these conditions. Without these islands producing a wave
‘shadow’ the western half of the bay would potentially be subjected to much higher wave
heights.
Under average winter conditions the significant wave height is drastically reduced
(Figure 5.4). The islands south of the townsite once again play an important role in
protecting the western side of the bay. However, the Bandy Creek dredging disposal site
falls on the border of the islands ‘shadow’ zone and is consequently subjected to greater
wave heights than Bandy Creek Boat Harbour.
60
Figure 5.4: Significant wave height (m) and direction under average winter conditions (Offshore Boundaries: Hs = 2.2m, Tp = 14s and Direction = 240°, wind speed = 8m/s at 240°).
A stationary run was also conducted for typical summer swell dominated conditions
(Figure 5.5).
61
Figure 5.5: Significant wave height (m) and direction under average summer conditions (Offshore Boundaries: Hs = 2.0m, Tp = 9s and Direction = 200°, wind speed = 6m/s at 180°).
The southerly nature of summer conditions meant that only the Esperance townsite
received any degree of protection from the islands wave shadow. Bandy Creek Boat
Harbour and the dredge disposal site were subjected to much more direct wave action
than the winter scenarios.
Finally, a stationary run of reduced swell and easterly conditions was conducted to
determine the effect of easterly winds in the summer (Figure 5.6). This simulation
represented a significant change in wave direction for the bay. The eastern side was
offered greater protection from incoming waves while Esperance and the Bandy Creek
area were subject to proportionally higher waves.
62
Figure 5.6: Significant wave height (m) and direction under average easterly conditions (Offshore Boundaries: Hs = 2.0m, Tp = 9s and Direction = 160°, wind speed = 8m/s at 90°).
5.2.1 Areas of interest
Three primary areas of interest were identified as important for understanding nearshore
wave and sediment processes in the area. These areas had their coordinates marked in
Eastings and Northings and were extracted from the closest SWAN output. The areas of
interest are as follows:
1. North of the Esperance townsite, out of the shelter of the harbour breakwaters
near the caravan park. Coordinates (Grid 51):
Easting: 399400.00
Northing: 625250.00
63
2. 100m west of Bandy Creek Boat Harbour. Coordinates (Grid 51):
Easting: 402500.00
Northing: 625510.00
3. The Bandy Creek dredge disposal site 800m east of Bandy Creek Boat Harbour.
Coordinates (Grid 51):
Easting: 404000.00
Northing: 625500.00
5.2.2 Significant Wave Heights
The following table has been constructed from the data extracted from the four stationary
SWAN runs for each location of interest (Table 5.1):
Table 5.1: Modelled wave heights under different prevailing conditions.
Significant Wave Heights (m) Winter Storms Winter Average Summer Easterly Esperance townsite 1.0 0.4 0.4 0.7 Bandy Creek Boat Harbour
2.0 0.6 0.6 0.6
Bandy Creek dredge disposal site
2.2 0.75 0.75 0.6
Under any westerly conditions the islands south of Esperance create a shadow the helps
to protect these sites from incoming wave energy. The further eastwards around the bay
the higher the significant wave heights become. This is reflected by higher significant
wave heights at the dredge disposal sight under winter and summer conditions. However,
under easterly conditions the islands south of Esperance do not create a wave ‘shadow’ to
protect the western side of the bay. Consequently, the Esperance townsite receive higher
significant wave heights due to its orientation under easterly conditions.
64
5.2.3 Wave Periods
Wave period was also extracted from each of the model runs for each site (Table 5.2).
Table 5.2: Modelled wave periods under different prevailing conditions.
Wave Periods (s) Winter Storms Winter Average Summer Easterly Esperance townsite 10.0 12.0 9.0 3.0 Bandy Creek Boat Harbour
10.0 8.0 7.5 5.0
Bandy Creek dredge disposal site
10.0 8.0 7.5 4.5
Extracted wave periods were consistent with seasonal wave climate trends. The winter
simulations had proportionally longer periods than the summer simulations.
5.2.4 Wave Direction
Finally, wave directions were also extracted from the model runs for each of the target
sites (Table 5.3).
Table 5.3: Modelled wave directions under different prevailing conditions.
Wave Direction (degrees) Winter Storms Winter Average Summer Easterly Esperance townsite 170 165 155 130 Bandy Creek Boat Harbour
185 180 180 140
Bandy Creek dredge disposal site
190 190 185 140
Wave direction at Bandy Creek Boat Harbour and the dredge disposal site were limited to
small bands under the majority of conditions. The direction at the Esperance townsite had
a slightly greater range of direction due to waves refracting differently around the
headland under the different wave conditions.
65
5.2.5 Model Validation
To validate the numerical modelling the DPI’s non-directional 2005 nearshore wave data
was analysed to determine the nearshore wave climate under each of the simulated
offshore conditions. The instrument’s position (Easting: 4012558.397, Northing:
6255010.527, Grid 51) was extrapolated to the nearest point on the model grid and the
data was then extracted from this point. This enables a comparison of expected and
modelled significant wave heights and wave periods (Tables 5.4-5.5).
Table 5.4: Expected and modelled wave heights for each of the different prevailing conditions.
Expected significant wave heights (m)
Modelled significant wave heights (m)
Winter Storms 2.0 2.0 Winter Average 0.65 0.60 Summer 0.6 0.6 Easterly 0.4 0.6 Table 5.5: Expected and modelled wave periods for each of the different prevailing conditions.
Expected wave period (s) Modelled wave period (s) Winter Storms 11.0 10.0 Winter Average 14.0 8.0 Summer 12.0 7.5 Easterly 7.0 5.0
5.3 Sediment Mobility
Using the method outlined in section 4.2.2 the critical diameter for mobilising sediment
was calculated for each of the locations of interest under each modelled wave condition
(Table 5.6).
66
Table 5.6: Critical mobility sediment diameter for each location under the four modelled conditions (diameters expressed in m x 10-3).
Modelled condition Winter
Storms Winter
Average Summer Average
Easterly Conditions
Esperance Townsite 1.00 0.24 0.35 1.83 Bandy Creek Boat Harbour 2.53 0.69 0.75 1.16 Bandy Creek Dredge Disposal site 2.87 0.93 1.00 1.26
Notably, the storm condition is capable of mobilising sediment with a greater diameter.
When each area was exposed to greater incoming wave activity, the potential for larger
grain sizes to be mobilised increased.
5.4 Sediment Suspension
Applying calculations for sediment suspension revealed that under the simulated
conditions sediment would primarily be transported through bedload transport. In most
cases sediment needed to have a diameter of less than 100microns to undergo full
suspension within the water column. Dredging records show that the median grain size
for the Bandy Creek region is 200microns. Analysing sediment of this size using the
method outlined in section 3.2 reveals that sediment transport near Bandy Creek will
most likely occur through incipient suspension.
5.5 Longshore sediment transport
The volume of sediment transport per day through longshore transport was calculated
using Equation 12. Firstly, the angle αb was calculated at each location under each model
condition. The following tables estimate the volume of sediment transported per day
under the modelled conditions, where a negative value of Qs indicates westerly transport
rather than easterly (Tables 5.7-5.9):
67
Table 5.7: Volumetric rate of sediment transport for each modelled condition near the Esperance townsite.
Storm Conditions
Winter Average Summer Average
Easterly Conditions
Qs (m3/day) 456 214 21 41
Table 5.8: Volumetric rate of sediment transport for each modelled condition on the westward side of Bandy Creek Boat Harbour. Storm
Conditions Winter Average Summer
Average Easterly
Conditions Qs (m
3/day) 624 208 44 -259 Table 5.9: Volumetric rate of sediment transport for each modelled condition near the Bandy Creek dredge disposal site.
Storm Conditions
Winter Average Summer Average
Easterly Conditions
Qs (m3/day) 587 223 54 -305
68
6.0 Discussion
6.1 Data Analysis
Historically the level of detail of data required for coastal design in Esperance has been
debated. The amount of data collected and the required length of a historical hind cast has
been weighed against the cost of data collection and the computational costs of
generating hind casts. Consequently, there are no complete records of wave data in the
area.
The DPI has recently placed wave recorder instruments in the area to ascertain more
wave data. However, the data they have collected so far has a seasonal bias to the winter
months. To complement this data, the wave recording instruments should be redeployed
in the summer months to enable a more detailed analysis of wave climate. These data sets
could then be integrated to generate detailed wave hind casts for the area.
6.1.1 Implications for dredging operations
The current practice for the management of the Bandy Creek Boat Harbour entrance is
outlined in section 1.5. This dredging program is conducted by the DPI and is carried out
independently of any other Esperance foreshore actions such as beach nourishment. Most
of the dredging is done in order to remove material that forms a bar across the entrance
channel reducing harbour navigability. Dredging is limited by existing equipment to
within the harbour due to the wave climate at the entrance. The entrance channel is often
over dredged to extend dredging periods.
By analysing the persistence of calms or weather windows dredging operators may be
able to gain better estimates on the duration that they can remain in the harbour entrance
for any given time. The frequency of storm events over the dredging period may also be
useful for estimating downtime in any given dredging campaign.
69
6.1.2 Implications for coastal management
There is a lack of sufficient directional wave data for previous studies to accurately
estimate seasonal sediment movements and allow preliminary engineering design of
coastal structures and groyne compartments commensurate with best practice. This could
be addressed with more detailed long term wave hind casting and more complex
numerical modelling of the nearshore climate.
Such studies allow for sufficient detailing of the littoral sediment movements in both a
seasonal and individual storm timeframes for more accurate prediction of the
performance and outcomes of the proposed beach stabilisation structures.
Additionally, coastal design and management often requires the knowledge of extreme
high wave conditions, caused by storms. An analysis of extreme waves requires a
sufficiently long data record to provide reliable long term estimates. 10 years worth of
data is considered to be the bare minimum required to characterise extreme conditions.
Currently the only wave data for the area is limited to old recordings from 1980-83 and
the more recent data set from the DPI in 2005-06. The sporadic nature of these data
recordings m ean that many extreme wave events and conditions may not have been
recorded. This is particularly evident when the history of the area is considered. There
have been instances when strong easterly conditions have caused large amounts of
erosion around the Esperance foreshore. This type of event is considered to be a one in
ten year event and as such its wave characteristics have not been recorded by any real
wave data.
6.2 Numerical Wave Modelling
The model was run in stationary model for four prevailing conditions observed in the
area. From these runs some general observations about wave climate could be made for
the area. Firstly, significant wave heights in the bay are much higher during storm
70
conditions due to large offshore waves and strong south westerly winds driving waves
into the bay. These storm conditions can have a great impact on sediment transport in the
area as higher waves have a greater propensity for mobilising sediment. Wave heights
modelled within the bay under storm conditions where nearly more than three times the
height of the waves normally observed within the bay under winter conditions.
To analyse the effect of seasonality on the Esperance wave climate summer and easterly
conditions were also modelled. Summer conditions represented a significant change from
the prevailing winter conditions whereby the observed wave heights were lower and the
wave periods where smaller, indicating the presence of locally generated waves. Under
easterly conditions areas of the bay that were normally sheltered by islands were exposed
to incoming wave activity. This was particularly evident at the Esperance townsite where
easterly conditions forced waves directly onto a normally sheltered beach. Easterly
conditions were also significant as it represented a shift in the direction of longshore
transport with waves arriving at beaches from a different quadrant forcing longshore
sediment transport west rather than east.
6.2.1 Model Validation
SWAN was validated by comparing average or commonly seen offshore scenarios to
their measured nearshore counterparts. The data taken to validate the model is presented
in section 5.3.
Overall, the model appeared to be highly accurate in predicting significant wave height at
the nearshore location. The only offshore condition in which the expected wave height
was not almost identical to its modelled counterpart was the Easterly condition. Of all the
modelled offshore scenarios, this condition had the least measured offshore wave data.
Thus, the underlying boundary conditions for this run may not actually be accurate
enough for the testing of this condition. Stationary runs using SWAN appear to have a
high validity for predicting significant wave height in the nearshore zone.
71
When comparing the expected and modelled wave periods for each stationary run, it
became apparent that the modelled periods were consistently shorter than the measured
nearshore wave periods. Esperance is a unique part of the West Australian coast due to its
offshore wave climate containing a lot of longer period waves in comparison to other
areas, such as Perth. The comparison of the expected and outputted periods of the waves
suggests that the numerical methods governing SWAN may need to be adjusted to
accurately model these longer period waves as they propagate into the Recherche
Archipelago.
Wave period is an important parameter for estimating conditions such as Umax and fw.
Consequently, any calculations performed using this modelled data must be treated with a
degree of caution due to the data’s shorter than anticipated wave period.
Unfortunately over the period of this study there was no nearshore directional wave data
available. It was impossible to validate the directional outputs of SWAN to any degree of
certainty.
6.2.2 Drawbacks to numerical wave modelling
Numerical wave modelling is a powerful tool for applications in coastal engineering
projects. The results of numerical modelling can often be highly influential on the design,
construction and maintenance of maritime projects. However, the results of numerical
wave modelling should never be taken as a gospel truth as there will always be
limitations to the accuracy of the modelled data.
Essentially, numerical modelling endeavours to describe natural processes with a series
of ordered mathematics. Nature often has a certain degree of inherent randomness that
will not be reflected in the modelled wave data. This uncertainty can significantly
decrease the accuracy of any modelled data. Thus a degree of caution must be employed
when considering the data from any numerical modelling project.
72
SWAN has some immediately identifiable weaknesses in the accuracy of its predictions.
Firstly, SWAN does not simulate the effect of diffraction or reflection of waves as they
pass through the chain of islands surrounding Esperance. In Johnson and Pattiaratchi
(2004), they suggested that this was not a significant problem except in the condition of
trying to extract wave data within two wavelengths behind an island. In the nearshore
environment, features such as the Esperance breakwater may have a significant effect on
wave climate as diffraction may occur.
The inputs for SWAN also reflect a highly mathematic approach to simulating wave
climate. The wind field is assumed to be uniform over the modelled area and the inputted
offshore wave parameters are assumed to be spatially uniform over the model boundary.
While offshore conditions have been observed not to change rapidly, satisfying the
equilibrium nature of the model, spatial irregularities in the wind field and offshore wave
climate are part of nature.
In this study SWAN was applied to an interpolated 100m resolution bathymetric grid for
the Esperance area. When we consider shallow water waves, for the purpose of
estimating sediment transport, relatively small bathymetric features can have a significant
effect on wave parameters. A 100m grid is not able to encompass all the underwater
features, such as reefs, that may affect the wave parameters at any given location. All of
these drawbacks decrease the degree that modelled data can be relied upon.
While it is important to remain critical of the limitations and drawbacks of using numerical
models to estimate wave climate, they are still a proven tool for coastal design purposes. Real
time wave data tended to agree with the models predictions suggesting that the results from
the model are still highly relevant.
6.3 Sediment Transport
The Coastal Engineering Manual states that sediment transport rates must be determined
over the longest possible time period (2003). Sediment transport calculations can then be
73
calibrated using historical shoreline positions and wave conditions from the same period.
The lack of extended wave data at Esperance limits the reliability of any sediment
transport calculations in the area.
6.3.1 General transport characteristics
The minimum wave activity required to mobilise sediment is an important part of
defining sediment transport ant any location. The critical grain size required for sediment
mobility at each of the locations, under each model condition, shows some common
trends. From dredging records it is apparent that the median grain size dredged out of
Bandy Creek Boat Harbour has a median diameter of 200 microns. If we look at this
value in Table 5.6 it is apparent that all the modelled conditions are capable of mobilising
this grain size at Bandy Creek Boat Harbour and the dredge disposal site.
This differs at the Esperance townsite location, where sediment of diameter 200 microns
will be mobilised under storm and easterly conditions but remains close to the
mobilisation threshold for summer and winter conditions. Given any error in the
modelled wave data, sediment with a D50 value of 200 microns may or may not fall over
the mobilisation threshold. This observation highlights the important role storms play in
the mobilisation of sediment. Storm conditions are capable of mobilising larger grain
sizes which then allows for other factors such as longshore currents to then move the
sediment away.
An analysis of the threshold for suspension suggests that none of the modelled wave
conditions are capable of fully suspending sediment within the water column. However,
this does not rule out the potential for incipient or bed load transport to occur within the
area.
74
6.3.2 Longshore transport
Confirming the accuracy of any longshore sediment transport estimate is a difficult task
when there is a lack of historical wave data and sediment records. The only records to
check this study’s estimates are the estimates developed from Reidel and Byrne’s 1987
wave hind cast and the dredging records at Bandy Creek Boat Harbour. The estimates
derived from the four stationary model runs is limited to predicting volumetric transport
rates over one day under one condition. To a make an estimate of gross and net annual
transport in the area a year long wave hind cast is needed.
Despite the lack of a year long wave hind cast the daily longshore results from this study
are not insignificant. When the results are expanded to make a rough estimate of annual
sediment movements, the results fall within one order of magnitude of current estimates.
This suggests that the model is producing reasonably reliable wave data for sediment
estimates. It also encourages the running of a full year wave hind cast to analyse annual
sediment movements.
One notable difference between the predicted rates of volumetric transport and generally
observed transport conditions is the effect of average summer conditions. The model
predicted that under summer conditions there would be smaller amounts of transport than
in winter conditions. Also the direction the model predicted sediment would travel was
west to east, contradicting general observations of sediment movement in the area.
Under clearly defined easterly conditions the model predicted that sand would move from
east to west, yet the average summer condition simulation suggests that there would still
be sediment transport to the east even in summer periods. While this result cannot be
proven in this study it is an area that should be further investigated in any additional work
in the area.
75
6.3.3 Limitations of sediment transport estimates
Estimates of sediment transport should always be treated with a large degree of caution.
As many engineering studies have observed the volume of predicted sediment transport
can vary greatly depending on what method of estimation is used. In this study sediment
transport characteristics have been calculated using numerically modelled wave data for
each site. As such any limitations that increase the uncertainty of the accuracy of the
wave data also apply to any estimate of sediment transport characteristics.
The lack of sufficient directional wave data impedes the ability to make accurate
estimates of longshore transport. To estimate longshore transport the breaking wave
angle, αb, needs to be known. For this study it was very difficult to calculate this
parameter. For each calculation αb was estimated either using a known slope and Snell’s
law, modelled directional data or visual observations from aerial photographs. Relying on
such sources adds another area of uncertainty to estimating longshore sediment transport
characteristics in the area.
76
7.0 Conclusions
A detailed understanding of the coastal processes is necessary for any coastal design or
management. This is particularly true for Bandy Creek Boat Harbour. Problems with the
erosion of the Esperance foreshore and the siltation of the Bandy Creek harbour has led
to a number of studies being undertaken in the area with regards to these problems.
All of these studies have expressed the need for more wave data so that coastal design
and management can be undertaken according to ‘best practice’ scenarios. The DPI has
recently been collecting wave data in the Esperance region, which should be analysed in
a fashion similar to this study and used to produce detail wave hind casts. Further
numerical modelling should be performed on new wave data to further investigate
nearshore wave and sediment dynamics.
The main sediment transport mechanisms in the vicinity of Bandy Creek are wave action
and wave induced currents. In the winter months these predominantly act from west to
east, while in the summer months they tend to act more east to west. As a result sediment
transport directions and rates generally follow this seasonal pattern with the majority of
sediment moving east in winter and west in summer.
Numerical wave modelling using SWAN showed good correlation to real wave data in
predicting significant wave height. However, SWAN tended to predict shorter wave
periods than observed the wave data suggested; while no data was available to validate
directional wave output from the model. The results from a series of stationary runs
suggest that the model does predict wave climate within the bay with a satisfactory
degree of accuracy and should be used to produce a full year wave hind cast.
Nearshore data was then extracted from the model outputs to make estimates for
sediment transport characteristics within the area. The modelled data suggested that
sediment in areas like Bandy Creek Boat Harbour and the dredge disposal site would be
mobilised under all conditions, while more sheltered areas like the Esperance townsite
77
will be more likely to have sediment mobilised under storm or strong easterly conditions.
Additionally, the study found that sediment was more liable to undergo transportation
through bedload or incipient transportation rather than being fully suspended in the water
column.
Longshore transport estimates were evaluated for each modelled condition at three
different places. These estimates were calculated as volume per day and were deemed to
be in the correct range to match current estimates and observations of sediment
movement in the area. No estimates of gross and net annual sediment movement could be
attained from this investigation. The creation of a full year wave hind cast would be
instrumental in calculating these annual figures.
78
8.0 Recommendations
The DPI has just finished collecting directional nearshore wave data for the winter
months of 2006. The wave recording instrument was positioned in the same location as
the non-directional wave recording instrument that measured nearshore wave data for
2005. Ideally this data should be analysed to gain a greater understanding about the
direction of waves as they break onshore.
This data and the 2006 offshore wave data would be an ideal source to calibrate a
numerical model to accurately predict wave climate within the Esperance area. It is
recommended that at least a detailed full year wave hind cast is performed on the area
using a higher resolution bathymetry. Ultimately 10 years of wave hind casts should be
performed to increase each hind cast’s accuracy and characterise Esperance’s extreme
wave climate. These hind casts could then be used to give a much better description of
sediment transport characteristics in the area.
Wave transformation modelling should be used on any wave hind cast to generate wave
parameters for several locations in the nearshore zone. This data would allow for a more
accurate estimate of sediment transport characteristics as well provide design wave data
at a number of locations.
Further studies should also be conducted concerning headland control in the Esperance
area. It is apparent that erosion near the Esperance town site is a significant problem that
requires regular beach nourishment. If this area is stabilised it may act to reduce the
volume of sediment available for longshore transport. By stabilising this area the volume
of sand that could be potentially transported by littoral drift into Bandy Creek Boat
Harbour from the west may be reduced.
From previous studies it is apparent that the responsibility for coastal management in
Esperance is divided into a number of different groups. It is recommended that these
groups meet and form an integrated plan for the entire coastal area from the main Port to
79
Wylie Head. A combined management approach would ensure that future studies provide
complete and integrated information on the coastal issues in the area.
80
References
Abbot, M. & Price, W. 1994, Coastal, Estuarial and Harbour Engineers' Reference
Book, Edited reference published by E&FN Spon, London, December 1996.
Bailey, J. 2005, Effects of Sediment Dynamics on the Navigability of the Murchison
River Ocean Entrance, Western Australia, Undergraduate, University of Western
Australia.
Booij, N., Holthuijsen, L. H. & de Lange, P. H. M. 1992, 'The penetration of short crested
waves through a gap', Proc. 23rd Int. Conf. Coastal Eng, no. Venice 4-9 Oct.,
1992, New York, 1993, 1044-1052.
Clarke, R. H. 1955, 'Some observations and comments on the seabreeze', Australian
Meteorological Magazine, vol. 11, pp. 47-68.
Coastal Engineering Research Centre (CERC) 1984, Shore Protection, Manual prepared
for the USACE and published by the US Government Printing Office,
Washington D.C., Second Printing 1990.
Coastal Engineering Research Centre (CERC) 2003, Coastal Engineering Manual,
Publication EM 1110-2-1100, online Manual prepared for USACE and released,
2003.
DAL Science & Engineering (DALSE) 2003, Headland Control Concepts for Beach
Stabilisation of Esperance Bay, Report prepared by DALSE with J Hsu & R
Silvester for the Shire of Esperance, September 1996.
81
Dean, R. G. 1974, Evaluation and Development of Water Wave Theories for Engineering
Applications, Coastal Engineering Research Centre, U.S. Army Engineer
Waterways Experiment Station Special Report No. 1.
Department of Planning and Infrastructure (DPI), Historical Tide Data [Online],
Available: http://www.dpi.wa.gov.au/imarine/coastaldata/1897.asp.
Department of Transport (Transport) 1994, Esperance Beach Stabilisation Report on
Coastal Erosion and Shore Protection Works Beach Investigations - Report on
Coastal Erosion and Possible Shore Protection Works, CIES Report DMH P
19/93, May 1994.
Dredging Environmental Management Plan (DEMP) 2005, Bandy Creek Boat Harbour -
Maintenance dredging 2005-2009, March 2005.
Gentilli, J. 1971, 'Climates of Australia and New Zealand', World Survey of Climatology,
vol. 13.
Gentilli, J. 1972, Australian Climate Patterns, Nelson's Australasian Paperbacks.
Goda, Y. 1970, "A synthesis of breaker indices", Trans. JSCE, Vol. 2, pp. 227-230.
Hollings, B. 2006, Validity of SWAN determining breaking wave parameters.
Holthuijsen, L. H., Booij, N., Ris, R. C., Haagsma, I. J. G., Kieftenburg, A. T. M. M.,
Kriezi, E. E., Ziijlema, M. & van der Westhuysen, A. J. 2004, 'SWAN Cycle III
version 40.31 User Manual. Available: http://fluidmechanics.tudelft.nl/swan'.
Jackson, N. L. & Nordstrom, K. F. 2002, 'Low Energy Sandy Beaches in Marine and
Estuarine Environments: A Review', Journal of Geomorphology, vol. 48, pp.
147-162.
82
Jesz Flemming & Associates (JFA) 2003, Bandy Creek Boat Harbour. Maintenance
dredging works 2003-2004, Contract close out report.
Jesz Flemming & Associates (JFA) 2004, Bandy Creek Boat Harbour - Esperance,
Ongoing Management of Entrance Channel, Business Case Summary, August
2004.
Johnson, D. & Pattiaratchi, C. 2004, Prediction and Measurement of Wave Energy and
Bottom Shear Stress for Esperance Bay, Centre for Water Research.
Komar, P. D. 1998, Beach Processes and Sedimentation, Upper Saddle River, N.J.,
Prentice Hall.
Komar, P. D. & Gaughan, M. K. 1973, 'Airy Wave Theory and Breaker Height
Prediction', Proceedings of the 13th Coastal Engineering Conference, American
Society of Civil Engineers, pp. 405-418.
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.
M P Rogers and Associates 2005, Esperance Townsite Foreshore Masterplan - Extension
to Bandy Creek.
Méhauté, B. L. 1976, Introduction to Hydrodynamics and Water Waves, Springer -
Verlag, New York.
Pattiaratchi, C. 2006, Oceanographic Engineering Lecture.
Silvester, R. 1987, Review of findings, Evaluation of the Westport Environmental Review
and Management Program, Environmental Protection Authority.
83
Sinclair Knight Merz (SKM) 2005, Bandy Creek Boat Harbour, Esperance - Sand
Bypassing System Investigation, Report prepared for DPI, January 2005.
Steedman, R. K. 1982, Record of storms, Port of Fremantle 1962-1980, Steedman and
Associates, Perth.
Swart, D. H. 1976, Coastal Sediment Transport: computation of longshore transport,
Report No. R968, Waterloopkundig Laboratorium, Delft Hydraulics Laboratory,
112 pp.
Weggel, J. R. 1972, 'Maximum Breaker Height', Journal of Waterways, Harbours and
Coastal Engineering Division, Vol 98, No. WW4, pp 529-548.
Yalin, M. S. 1977, Mechanics of sediment transport, Pergamon Press.
84
Appendix A List of previous studies in the Esperance region:
85
Andrew, W. 2000, Esperance Littoral Drift Management, Transport file memorandum
reporting on review of littoral drift management at Esperance by W Andrew,
Coastal Consultant Nov 2000.
Boreham, P. 1991, Sand Bypassing at Bandy Creek Boat Harbour Esperance, Using an
Offshore Breakwater, Paper for 10th Australasian Conference on Coastal &
Ocean Engineering, December 1991.
DAL Science & Engineering (DALSE) 2003, Headland Control Concepts for Beach
Stabilisation of Esperance Bay, Report prepared by DALSE with J Hsu & R
Silvester for the Shire of Esperance, September 1996.
Department of Marine & Harbours (DMH) 1987, Esperance Small Fishing Boat Harbour
- Breakwater Extensions Investigation, DMH report by M Crawford, DMH 3/88,
December 1987.
Department of Marine & Harbours (DMH) 1988, Bandy Creek Boat Harbour - Entrance
Management Investigation Summary, DMH Report - DMH 3/88, August 1988.
Department of Transport (Transport) 1994, Esperance Beach Stabilisation Report on
Coastal Erosion and Shore Protection Works Beach Investigations - Report on
Coastal Erosion and Possible Shore Protection Works, CIES Report DMH P
19/93, May 1994.
Department of Transport (Transport) 2000, Esperance Bandy Creek Boat Harbour
Entrance Management - Brainstorming Session, Unpublished Departmental file
memorandum reporting on workshop of entrance management, November 2000.
Department of Transport (Transport) 2001, Bandy Creek Boat Harbour - Evaluation of
Entrance Management Options, Unpublished Departmental file memorandum
reporting on workshop of entrance management, March 2001.
86
Gutteridge Haskins & Davey (GHD) 1999, Esperance Foreshore Coastal Protection
Works - Coastal Management Options, Report prepared for the Shire of
Esperance, May 1999.
Gutteridge Haskins & Davey (GHD) 2000, Esperance Foreshore Coastal Protection
Works - Report on Sand Backpassing System for Foreshore Nourishment, Report
Prepared for the Shire of Esperance, April 2000.
Gutteridge Haskins & Davey (GHD) 2005, Esperance Townsite Foreshore Masterplan,
Report on master planning for the town prepared for the Shire of Esperance,
March 2004.
Hsu, J. R. C. 1995, A review on Esperance Beach Stabilisation, Centre for Water
Research.
Hsu, J. R. C. 1996, Headland Control for Esperance Beach Stabilisation, Centre for
Water Research.
Johnson, D. & Pattiaratchi, C. 2004, Prediction and Measurement of Wave Energy and
Bottom Shear Stress for Esperance Bay, Centre for Water Research.
M J Paul & Associates (MJPA) 2000, Foreshore Enhancement Study for Esperance
Town Beach between James Street Groyne and the Old Timber Jetty, Report
prepared for the Esperance Port Authority, March 2000.
M J Paul & Associates (MJPA) 2001, Consolidated Coastal Processes Management and
Monitoring Plan - Esperance Beach Management ACTION PLAN, Report
prepared for the Esperance Port Authority, June 2001.
87
M J Paul & Associates (MJPA) 2003, Esperance Beach Management - Proposed New
Groynes to Further Protect the Beach South of the Old Timber Jetty, Fax report to
the Esperance Port Authority, November 2003.
M J Paul & Associates (MJPA) 2004, Esperance Beach Management Action Plan - from
Port to Bandy Creek Boat Harbour July 2000 to April 2004, Draft report on beach
profile analysis to the Esperance Port Authority, May 2004.
Oceanica Consulting (Oceanica) 2004, Determination of Setback Line for Physical
Processes: Esperance Bay (Flinders to Wylie Head), Report prepared for the
Shire of Esperance, November 2004.
Port & Harbour Consultants (Worley) 2001, Bandy Creek Boat Harbour Siltation
Investigation, Worley memorandum to Ben Maloney (Transport) reporting on
brief review of data on sedimentation at BCBH, May 2001.
Public Works Department (PWD) 1978, Esperance Beach Investigations - Report on
Coastal Erosion and Possible Shore Protection Works, PWD Report CIS 78/2,
October 1978.
Riedel & Byrne 1987, Bandy Creek Boat Harbour - Breakwater Extensions, Reporting on
wave climate for basin modelling and sediment transport for 1 year hindcast
waves included as Appendix C Hindcast Wave Climate and Sediment Transport
Potential in DMH 3/88, December 1987.
Sinclair Knight Merz (SKM) 2001, Department of Transport Bandy Creek Boat Harbour
- Report on Entrance Management Issues, Report prepared for the Department of
Transport, June 2001.
Sinclair Knight Merz (SKM) 2005, Bandy Creek Boat Harbour, Esperance - Sand
Bypassing System Investigation, Report prepared for DPI, January 2005.
88
Appendix B Depth soundings used to update and refine 100m grid bathymetry and estimate beach slopes:
89
90
91
92
93
Appendix C Modified ‘mobgrain.m’ script (Available in Bailey 2005):
94
load tmax.dat; sze = length(tmax); % Establish intial conditions Dx = ones(sze,1); d50 = 0.001*ones(sze,1); d502 = ones(sze,1); thetcrA = ones(sze,1); diff = 1; tm = tmax; % Perform Itteration 20 times. for jj = 1:20 % Calculate D50 for each tmax. for ii = 1:sze; Dx(ii,1) = d50(ii,1)*((1.585*9.81)/1e-12)^(1/3); % Select appropriate equation from modified Shields diagram if Dx(ii,1) <= 4; thetcr(ii,1) = 0.24*Dx(ii,1).^(-1); end if 4 < Dx(ii,1) <= 10; thetcr(ii,1) = 0.14*Dx(ii,1).^(-0.64); end if 10 < Dx(ii,1) <= 20; thetcr(ii,1) = 0.04*Dx(ii,1).^(-0.10); end if 20 < Dx(ii,1) <= 150; thetcr(ii,1) = 0.013*Dx(ii,1).^(0.29); end if 150 < Dx(ii,1); thetcr(ii,1) = 0.055; end % Re-arrange equations and variables to continue itterating d502(ii,1) = tm(ii,1)/(thetcr(ii,1)*1025*9.81*1.65); d50(ii,1) = d502(ii,1); end end
