The Influence of the El Niño Southern Oscillation on the Entrance Regime of Icolls

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2014

The influence of the El Niño Southern Oscillation on the entrance regime of ICOLLs

Sarah Perry University of Wollongong Follow this and additional works at: https://ro.uow.edu.au/thsci

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Recommended Citation Perry, Sarah, The influence of the El Niño Southern Oscillation on the entrance regime of ICOLLs, Bachelor of Environmental Science (Honours), School of Earth & Environmental Sciences, University of Wollongong, 2014. https://ro.uow.edu.au/thsci/86

Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] The influence of the El Niño Southern Oscillation on the entrance regime of ICOLLs

Abstract Intermittently closed and open lakes and lagoons (ICOLLs) are coastal environments that are prominent features of the NSW coastline. On the south coast ICOLLs are often extensively developed environments, resulting in ICOLL processes being of significance not only ecologically but also for the surrounding community. Consequently ICOLLs are the focus of extensive management, including artificial entrance openings. The natural entrance regime of ICOLLs represents a balance between rainfall, stream-flow and wave processes, which are themselves driven by dominant climatological processes including the El Niño Southern Oscillation. Changes in the entrance regime of ICOLLs due to artificial management and increases in the prevalence and severity of rainfall and storm events due to changes in climate are therefore likely to influence ICOLL processes. With a focus on the entrance processes of a number of ICOLLs on the NSW South Coast, this study explores correlation between the El Niño Southern Oscillation (ENSO), and the entrance regime.

The ICOLLs included in this study are located in the Shoalhaven City Council, Eurobodalla Shire Council and Bega Valley Shire Council local government areas. The entrance regime of these ICOLLs comprises both natural and artificial openings over the study period from 1992 – 2013. Long-term in-situ data representing the wave climate, ICOLL water level and catchment rainfall was analysed with respect to the Southern Oscillation Index (SOI) to determine if the entrance condition of the ICOLLs is correlated to the El Niño Southern Oscillation through the application of comparative and statistical methodologies. The results of the analysis show that there is no correlation between the ICOLL entrance condition and the El Niño Southern Oscillation for the study ICOLLs. Although the wave climate and catchment rainfall are correlated to the El Niño Southern Oscillation at some sites, there is no correlation between the wave climate, catchment rainfall and the ICOLL entrance condition. The results indicate that overall the El Niño Southern Oscillation is not a direct influence on the entrance regime of these ICOLLs on the NSW south coast.

Degree Type Thesis

Degree Name Bachelor of Environmental Science (Honours)

Department School of Earth & Environmental Sciences

Advisor(s) Colin Woodroffe

Keywords ICOLL, coastal lake, ENSO, entrance regime

This thesis is available at Research Online: https://ro.uow.edu.au/thsci/86

Faculty of Science Medicine and Health

School of Earth and Environmental Sciences

The influence of the El Niño Southern Oscillation on the entrance regime of ICOLLs

Sarah Perry

This thesis is presented as part of the requirements for the award of the Degree of Bachelors of Environmental Science Advanced (Honours) of the University of Wollongong

October 2014

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The information in this thesis is entirely the result of investigations conducted by the author, unless otherwise acknowledged, and has not been submitted in part or otherwise for any other degree or qualification.

Sarah Perry

Cover Photo: Burrill Lake entrance open to the ocean 24 September 2014

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Abstract

Intermittently closed and open lakes and lagoons (ICOLLs) are coastal environments that are prominent features of the NSW coastline. On the south coast ICOLLs are often extensively developed environments, resulting in ICOLL processes being of significance not only ecologically but also for the surrounding community. Consequently ICOLLs are the focus of extensive management, including artificial entrance openings. The natural entrance regime of ICOLLs represents a balance between rainfall, stream-flow and wave processes, which are themselves driven by dominant climatological processes including the El Niño Southern Oscillation. Changes in the entrance regime of ICOLLs due to artificial management and increases in the prevalence and severity of rainfall and storm events due to changes in climate are therefore likely to influence ICOLL processes. With a focus on the entrance processes of a number of ICOLLs on the NSW South Coast, this study explores correlation between the El Niño Southern Oscillation (ENSO), and the entrance regime.

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Acknowledgements

Thank you firstly to my supervisors Colin Woodroffe and Errol McLean, who provided guidance, feedback and assistance throughout the completion of this project. I appreciate the time and attention that you both gave me.

Thank you also to my supervisors from the Office of Environment and Heritage Ray Laine and John Murtagh, for your valuable insights and assistance throughout the year. Additional thanks to Ray for your time in accompanying me on field trips to Newcastle and the ICOLLs for the project. I would also like to thank the Office of Environment and Heritage and the Manly Hydraulics Laboratory for supplying data for use in this project.

Thank you to Kerrylee Rogers for your assistance with the statistical analysis, your time and problem solving were very much appreciated. Thank you also to Marijka Batterham from the Statistical Consulting Service for your initial advice on the statistical design of the project.

Finally, a big thank you to my family and friends for their support and encouragement!

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Table of Contents

Abstract ...... 3

Acknowledgements ...... 4

Table of Contents ...... 5

List of Figures ...... 6

List of Tables ...... 7

Chapter One: Introduction ...... 9 1.1 Study Context ...... 9 1.2 Aim and Objectives ...... 12 1.3 Thesis Outline ...... 12

Chapter 2: Literature Review ...... 13 2.1 ICOLLs ...... 13 2.1.1 ICOLL Processes ...... 16 2.1.2 ICOLL Management ...... 19 2.2 Coastal and Catchment Processes ...... 21 2.3 El Niño Southern Oscillation ...... 25

Chapter 3: Regional Setting ...... 31 3.1 Site Selection ...... 31 3.2 Geology, Climate and Wave-climate of the NSW South Coast ...... 32 3.3 Characteristics of study ICOLLs ...... 34

Chapter 4: Methods and Results ...... 38 4.1 Datasets...... 38 4.1.1 Representing ENSO: the Southern Oscillation Index ...... 40 4.1.2 Representing coastal processes: wave statistics and water levels...... 41 4.2 The El Niño Southern Oscillation and Interdecadal Pacific Oscillation ...... 43 4.3 ICOLL Entrance Condition...... 44 4.3.1 Entrance Openings: Natural or Artificial? ...... 51 4.4 Rainfall, Wave Climate and Storms ...... 52 4.4.1 Rainfall ...... 52 4.4.2 Wave Climate ...... 55

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4.4.3 Storms ...... 57 4.5 Statistical Analysis ...... 60 4.6 Summary of Results ...... 64

Chapter 5: Discussion ...... 66

Chapter 6: Recommendations and Conclusion ...... 73

References ...... 75

Appendix One ...... 84

Appendix Two ...... 86

List of Figures

Figure 1: Panoramic photograph of the Lake Durras entrance (25 September 2014)………..9 Figure 2: Schematic of a south coast ICOLL………………………………………………..10 Figure 3: Estuary morphologies in New South Wales (adapted from Roy et al. 2001)…….13 Figure 4: Evolutionary progression of a barrier estuary (based on Roy 1984 adapted from Hopley 2013)…………………………………………………………………………16 Figure 5: Fish kill at Lake Wollumboola due to low water levels (Stephenson 2011)..…….18 Figure 6: Artificial entrance openings: training walls at Lake Illawarra Entrance (left) (MAP 2009); Excavation of entrance channel at Burrill Lake (right) (Massie date unknown)……………………………………………………………………………..19 Figure 7: Schematic of entrance closure through longshore drift (mechanism 1) and onshore sediment transport processes (mechanism 2) (Ranasinghe and Pattiaratchi 2003)…..22 Figure 8: Number of storms occurring on the NSW coast based on 60 year analysis (1920 – 1980) (Anon 1985 in Short and Trenaman 1992)……………………………………23 Figure 9: The three phases of the El Niño Southern Oscillation (BOM 2012)……………...26 Figure 10: Illustration of the major climatic drivers influencing rainfall variability across Australia (Risbey et al. 2009)………………………………………………………..27 Figure 11: Seasonal correlation between rainfall and the El Niño Southern Oscillation across Australia (Risbey et al. 2009)………………………………………………………..28 Figure 12: Schematic illustration of the response of ICOLL, including entrance condition, inlet sediment and water level, to rainfall events (Woodroffe 2007)………………...29 Figure 13: Satellite image of ICOLL locations (left) (Google Earth); Geology of the NSW south coast (right) (Geoscience Australia 2012)……………………………………..32

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Figure 14: Satellite imagery of each ICOLL (Google Earth)……………………………….34 Figure 15: Underfloor flooding of waterfront property at Burrill Lake (left) (Spurway et al. 2008); Waterfront tourist accommodation at risk of high water levels at Lake Wallaga (right) (25 September 2014)………………………………………………………….37 Figure 16: Comparison between two indices of the El Niño Southern Oscillation (NOAA 2005)………………………………………………………………………………….41 Figure 17: MHL water level gauges at Lake Tabourie (left) and Lake Wallaga (right)…….42 Figure 18: Monthly SOI (blue), with 5 month moving average (black) and IPO phases (red) (January 1991 – December 2013)……………………………………………………43 Figure 19: Water level profile (m) for each ICOLL………………………………………...45 Figure 20: Indicators of entrance condition inferred from water level curve, illustrated on extract of Durras Lake water level (m) from January 2011 – December 2012………46

Figure 21: Entrance constriction illustrated by the M2 profile (m) (black) for Burrill Lake, Lake Tabourie and Lake Durras……………………………………………………...48 Figure 22: Entrance condition of ICOLLs and respective phase of the El Niño Southern Oscillation……………………………………………………………………………50 Figure 23: Proportion of natural and artificial openings for all ICOLLs……………………51 Figure 24: Long-term monthly mean rainfall for ICOLL catchments………………………52 Figure 25: Mean monthly rainfall (mm) for each ICOLL catchment over the study period..54 Figure 26: MHL Batemans Bay Waverider Buoy (G) location in respect to study ICOLLs (Google Earth)………………………………………………………………………..55 Figure 27: Mean monthly wave power recorded at Batemans Bay (1992-2013)…………...56 Figure 28: Mean monthly maximum wave height recorded at Batemans Bay (1992-2013)..56 Figure 29: Peak wave height for storm events from Batemans Bay (1991 – 2011)………...57 Figure 30: Yearly mean rainfall (Lake Tabourie) v yearly mean SOI regression plot with linear fit (P = 0.0026)………………………………………………………………...62

List of Tables

Table 1: Geological Classification of ICOLLs (Roy et al. 2001)…………………………...33 Table 2: ICOLL Characteristics……………………………………………………………..36 Table 3: Description of Datasets…………………………………………………………….39 Table 4: Bureau of Meteorology defined El Niño Southern Oscillation phases and corresponding phase of the Interdecadal Pacific Oscillation………………………...44

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Table 5: Large rainfall events and corresponding ICOLL opening events………………….53 Table 6: Mean seasonal wave direction for Batemans Bay (1992 – 2013)………………….56 Table 7: Storms and ICOLL opening events………………………………………………...58 Table 8: Storms and ICOLL closure events…………………………………………………59 Table 9: Regression analysis for all test variables against the SOI………………………….61 Table 10: Regression analysis for the controlling variables against ICOLL water level……62 Table 11: Regression analysis for the controlling variables against ICOLL entrance condition……………………………………………………………………………...63 Table 12: ANOVA testing controlling variables against the ICOLL water level…………...63 Table 13: ANOVA testing controlling variables against the ICOLL entrance condition…...63 Table 14: Historic record of Burrill Lake entrance condition from Burrill Lake EMP (Spurway et al. 2008)………………………………………………………………...68

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Chapter One: Introduction

1.1 Study Context

Estuaries are distinct coastal environments that provide considerable environmental, recreational and commercial amenity. Estuaries and estuarine sub-groups including coastal lakes and lagoons are transition environments, ranging from freshwater river systems upstream to the saline ocean downstream. As the junction between fluvial and marine systems the physical, chemical and biological processes in estuaries are complex, dynamic and highly variable (Haines 2008; Carvalho and Fidélis 2013). This variability gives rise to ecological communities that are equally diverse, with environments ranging from terrestrial riparian communities to mangroves and saline marshes (Roy et al. 2001). Estuaries are host to a variety of aquatic and terrestrial species and provide primary breeding grounds for many of these species, including fish and migratory birds.

The visual and recreational appeal of coastal lakes and lagoons in addition to their provision of commercial opportunity has led to significant development around these environments in Australia, such that no other country has a concentration of urban affluence on a coastal zone equivalent to that of the southeast coast of Australia (Roy et al. 2001). Development around estuaries is so prevalent in New South Wales (NSW) that Nadgee Lake, with its waterway and catchment entirely enclosed in a National Park, is the only site that remains completely in its natural state (Haines 2008). At all other estuaries in NSW the presence of human activity, especially when this activity is incompatible with natural processes, places pressure on the estuary and its ability to function naturally (Carvalho and Fidélis 2013). The Healthy Rivers Commission (HRC) independent inquiry into coastal lakes (2002) states that healthier lakes can be achieved through adequate management, stating that management should prioritise the protection of natural values, including holistically managing the coastal lake and its catchment.

Figure 1: Panoramic photograph of the Lake Durras entrance (25 September 2014).

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An Intermittently Closed and Open Lake or Lagoon (ICOLL) is a specific type of barrier estuary that periodically rather than permanently connects to the ocean at the entrance (Figure 2). There are a large number of ICOLLs in Australia, the majority of which are situated on the southeast coastline of New South Wales (Haines et al. 2006). ICOLLs are also found internationally, with examples occurring in South Africa, New Zealand and Brazil (Haines 2008). The temporal nature of the ICOLLs connection with the ocean is referred to as the entrance regime and is a function of the relative influence of opposing wave and fluvial processes. These processes themselves are influenced by regional and large-scale climatic conditions, including the El Niño Southern Oscillation (ENSO).

Figure 2: Schematic of a south coast ICOLL. Morphology of features including the entrance channel, presence of tidal deposits, size and depth of the central lake are dependent on the characteristics of the particular embayment.

Due to importance of estuarine environments for human activities and the proximity of development to the water bodies themselves, the entrance regimes of a large proportion of ICOLLs are artificially managed to maintain certain conditions in the estuary, for example to enable tidal exchange and to mitigate floods. Entrance management occurs on a spectrum, ranging from the less permanent mechanical excavation of entrance channels to the construction of training walls engineered to permanently maintain open conditions (as is apparent at Lake Illawarra, for example). Permanently changing the entrance condition of an

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ICOLL fundamentally alters the natural processes and as a result can alter the ecosystems that are present. Disparities between commercial requirements, community beliefs regarding water quality and ‘natural processes’, and science-based ecological principles often lead to conflicting views regarding entrance management. There have been numerous recorded cases where community members take management into their own hands by illegally opening ICOLL entrances.

Estuaries, as an important coastal environment, have been the focus of numerous studies. These studies, focused on estuaries both in NSW and elsewhere in the world, cover a large range of estuarine processes including geomorphology (see for example Roy et al. 2001; Haines et al. 2005) ecology (Jones and West 2005; Dye and Barros 2005; Scanes et al. 2011), and specific entrance process studies (Ranasinghe and Pattiaratchi 2003; Baldock et al. 2008; Morris and Turner 2008). A number of these studies have highlighted the possible influence that the climate has on ICOLL processes, including predictions for how these processes will change with future climate change (see for example Haines and Thom 2004).

The El Niño Southern Oscillation, specifically its influence in the Australasian region, has also been the focus of a large number of studies. The relationship between the El Niño Southern Oscillation and the variability of rainfall (referred to as an ENSO teleconnection) has been well established (see for example Allan 1988; Power et al. 1999; Verdon and Wyatt 2004; Cai et al. 2011), so too has that of other relevant teleconnections including storms (You and Lord 2008) and the wave climate (Phinn and Hastings 1992; Goodwin 2005). There have been few studies however that focus on linking changes in specific coastal phenomena to the phase of the El Niño Southern Oscillation. One example is that of Ranasinghe et al. (2004), who focuses on the changes in wave direction and subsequent beach rotation, identifying a correlation between the direction of rotation and the phase of ENSO. The purpose of this project is to further associate physical coastal processes to the phase of the El Niño Southern Oscillation.

This study will examine the relationship between the processes that give rise to the entrance regime of ICOLLs and the broad-scale climate phenomenon the El Niño Southern Oscillation to determine if there is correlation between the entrance condition and the phase of ENSO. The project will build upon previous studies that detail physical ICOLL and estuary processes and connect this information to research that examines how the El Niño Southern Oscillation

11 S Perry (2014) affects rainfall, storm and wave processes to identifying if there are any temporal patterns in the entrance regime that occur with respect to the broad climatic conditions. Ranasinghe and Pattiaratchi (2003) state that understanding the dominant processes that cause the seasonal closure of ICOLL is a prerequisite to the development of sustainable management solutions.

1.2 Aim and Objectives

The aim of this study is to determine if the entrance regimes of ICOLLs on the south coast are correlated to the phase of the El Niño Southern Oscillation. This aim will be achieved through the fulfilment of the following objectives: 1. Establish if there is a relationship between the coastal and catchment processes, the phase of ENSO and the entrance condition, through visual analysis of time-series data that is representative of these parameters. 2. Determine if any apparent relationship between the entrance condition and the El Niño Southern Oscillation is significant, through statistically examining (1) correlation between the phase of ENSO and the coastal and catchment processes, and (2) correlation between the coastal and catchment processes and the entrance condition. It has been hypothesised that the increased rainfall and storms associated with the La Niña phase of the El Niño Southern Oscillation will lead to more open entrance conditions observed at ICOLLs, while the reduced rainfall and drought conditions more prevalent during the El Niño phase will give rise to more closed entrance conditions.

1.3 Thesis Outline

Previous studies of ICOLL processes, coastal and catchment processes, the El Niño Southern Oscillation and the legislative context regarding ICOLL management are reviewed in Chapter 2. The regional context of the NSW south coast and specific ICOLL characteristics are described in Chapter 3, with the methods used in the study and the results obtained presented in a combined format in Chapter 4. A detailed discussion of the implications of the results including the limitations associated with the study is given in Chapter 5, followed by the subsequent recommendations and conclusion in Chapter 6. Data specific to but not included in the body of the thesis is presented in the Appendices.

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Chapter 2: Literature Review

2.1 ICOLLs

An Intermittently Closed and Open Lake or Lagoon (ICOLL) as introduced by Professor Bruce Thom in 1998, is a specific sub-group of wave-dominated barrier estuaries. ICOLLs are connected to the ocean only periodically, often for short periods of time, unlike estuaries that are permanently open. ICOLLs are also referred to as saline coastal lakes (Roy 1984), intermittent estuaries (Roy et al. 2001) and seasonally open tidal inlets (Ranasinghe and Pattaratchi 2003). In geological terms, an estuary can be defined as: the seaward portion of a drowned valley, receiving sediment from both fluvial and marine sources, containing facies influenced by tide, wave and fluvial processes; the estuary extends from landward limit of tidal facies at its head and to the seaward limit of coastal facies at its mouth (Dalrymple et al. 1992). Another definition put forth by the NSW Government in the Estuary Management Manual (1992, p.31) incorporates the intermittent characteristic of ICOLLs, stating an estuary is “any semi-enclosed body of water having an open or intermittently open connection with the ocean, in which water levels vary in a predictable, periodic way in response to the ocean tide at the entrance”.

Figure 3: Estuary morphologies in New South Wales (adapted from Roy et al. 2001). The influence of tides and waves in shaping estuary morphology decreases as the respective influence of rivers increases from a – d. Plate c is representative of a typical ICOLL in closed entrance condition.

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ICOLLs represent one of many estuary morphologies evident on the NSW coast (Figure 3). The morphology of an estuary is a function of geological inheritance, boundary conditions including sea level, and the relative influence of wave, tide and fluvial (river) action (Roy 1984; Roy et al. 2001). In the Roy et al. (2001) classification model, estuaries are grouped with respect to these parameters, ranging from tide dominated embayments and drowned river valleys (Figure 3, a), to river dominated estuaries (Figure 3, d). The NSW coast is wave- dominated and so it is the wave-dominated estuaries (Figure 3, b and c) that are the most prevalent. Under the same wave regime, the nature of the embayment and the sediment supply determines the estuary-mouth dynamic that will form (Roy et al. 2001). The bedrock valleys along the New South Wales coast have evolved over millions of years, during this time cycles of excavation and infilling have occurred as a result of changes in sea level due to the respective glacial and interglacial periods (Roy et al. 2001). Sediment supply is limited to local sources, as the NSW south coast is highly compartmentalised due to the headlands that extend either side of embayed bedrock compartments into deep water on the coastal shelf (Roy and Stephens 1980). The availability of sediment enables barriers to form.

A barrier is an elongate shore parallel sand body consisting of beach dunes, tidal deltas, berms and spits composed of marine sand (Boyd et al. 1992), which protects the environment behind it from the majority of wave energy (Dalrymple et al. 1992; Baldock et al. 2008). The barrier also creates a restricted entrance through which the exchange of water between the ocean and the estuary occurs, and in the case of ICOLLs, this entrance is periodically closed due to the accumulation of sediment in the entrance berm (Figure 3, c) (Haines 2006). Entrance berms are formed through the process of sediment overwash, in which marine sand that is entrained by waves is deposited during wave run-up, accumulating on the beach face and berm crest (Hanslow et al. 2000; Weir et al. 2006; Baldock et al. 2008). Deposition will continue to occur until the berm height is equal to the maximum height of wave run-up, which is dependent on incident wave conditions and the slope of the beach face (Hanslow et al. 2000). Tides alter the rate of growth and determine whether accretion occurs vertically or horizontally (Weir et al. 2006). These berm building processes act to close the entrance of the ICOLL.

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The temporal nature of entrance closures is referred to as the entrance regime. ICOLL entrance regimes are either mostly open or mostly closed; it is rare than an ICOLL will have an entrance regime that is bimodal where the entrance is open for half of the time and closed for the other half (Haines 2006). ICOLLs that are more river-dominated (occurring when the catchment is greater than 100 km2 in size) and or have entrances that are protected from waves by a headland will be predominantly open, while those with smaller catchments and or exposed entrances will be predominantly closed (Haines 2006). The latter condition is apparent for approximately 70% of ICOLLs on the New South Wales south coast, due to the proximity of the Great Dividing Range catchments in this region are small in size (Haines 2008, p.6). The entrance regime of an ICOLL is dependent on the relative balance between catchment (fluvial) and coastal (waves and tides) processes (Haines and Thom 2007). Coastal processes largely act to close off the entrance through the development and maintenance of the berm. Catchment processes conversely act to open the ICOLL. When the water level within the ICOLL exceeds the height of the entrance berm a breakout occurs in which water overtopping the berm erodes sediment and scours a channel (Haines 2008). Breakouts occur following large rainfall events where catchment inflow is large and occur with a positive feedback dynamic; ongoing scour progressively enlarges the entrance channel allowing more water to discharge from the estuary, which then further enlarges the channel. This will occur until the water level within the lagoon equilibrates with the ocean and tides (Haines 2008).

Over time estuaries shallow and decrease in water area due to the progressive infill of sediment at the floodtide delta, fluvial delta and in central basin (Roy 1984). The extent of infill represents the estuaries stage in an evolutionary progression described by Roy (1984) (Figure 4). Holocene sedimentation was initiated following the post-glacial sea level rise approximately 8000 years ago, since then the rate of infill is dependent on site specific topography, sediment supply and relative level of fluvial or marine influence (Roy et al. 2001). Human driven changes such as the clearing of land in the catchment for development or agriculture can increase the rate of sediment supply and increase the rate of estuary infill (Haines 2008). In addition to increasing the rate of infill, increasing the sediment supply especially when the sediment is rich in organic matter and nutrients, can also give rise to water quality issues within the ICOLL, further discussed below.

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Figure 4: Evolutionary progression of a barrier estuary (based on Roy 1984 adapted from Hopley 2013).

2.1.1 ICOLL Processes

ICOLLs are complex coastal environments; evidence of this is the large array of processes that determine the physical, chemical and biological characteristics of ICOLLs. The ICOLLs morphology, coastal and fluvial characteristics give rise to a number of morphometric parameters including the tidal prism, catchment input (in terms of total runoff, direct rainfall, sediment and pollutant load) and the entrance regime, which in turn influence the hydrodynamic and ecological processes within the ICOLL (Haines et al. 2006). Morphometric parameters are highly variable by nature, leading to fluctuating and highly dynamic conditions within the estuary. It is due to the variable nature of ICOLLs that they are recognised as the most sensitive estuary out of the estuary types in NSW (Haines et al. 2006).

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The intermittent entrance conditions and the tendency for long periods of closure result in ICOLLs having the largest abiotic variability of all estuary types. This subsequently has a constraining effect on biota (Roy et al. 2001). The ecological communities within ICOLLs must be capable of tolerating fluctuations in salinity, nutrients and depth of water. Shallow barrier estuaries are in general well mixed however the total salinity varies due to the relative input of fresh and saline water (Roy et al. 2001). Evaporation from the water surface can reduce the water depth to low levels during prolonged closed periods where little to no catchment input occurs (during drought periods, for example). In extreme conditions this evaporation of large amounts of water can lead to hypersalinity (Haines et al. 2005). Species diversity tends to be low, with euryhaline species occurring in relatively high abundance (Haines et al. 2006). Scanes et al. (2011) conducted a thorough aquatic survey of Nadgee Lake on the far south coast of NSW to establish baseline data that is deemed to be representative of the most natural state. The biota identified at Nadgee Lake included: phytoplankton, zooplankton, 13 species of fish including Australian salmon, sea mullet, bream and garfish, and species of infauna including polychaetes, crustaceans, and molluscs.

Aquatic and riparian vegetation is also limited by the abiotic parameters and is restricted to communities that can withstand periodic inundation of saline or brackish water, variable water level and quality (Haines 2006). Communities that are present include mangroves, salt marshes, seagrasses and freshwater wetlands (Haines 2006; Roy et al. 2001). However, the distribution of these species is varied at each ICOLL dependent on local conditions; mangroves are rarely found in ICOLLs that are mostly closed, while seagrasses are limited at ICOLLs that experience rapid changes in water level (Haines 2008). Additionally, an important process in ICOLLs, as in all estuaries, is the cycling of nutrients as part of primary production. Nutrients in sediment or in runoff are sequestered in the bottom sediment or cycled in the water column by bacterial decomposition (Scanes et al. 2007). The release of nutrients from bottom sediment enables phytoplankton and algae to grow on the water surface, providing food for macrophyte species such as fish and prawns (Roy et al. 2001). The maintenance of natural ICOLL processes is essential for the ecosystems to function.

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Figure 5: Fish kill at Lake Wollumboola due to low water levels (Stephenson 2011).

ICOLLs are at risk of degradation due to the increasing anthropogenic activity on and around them reducing their capacity to function naturally. The commercial, recreational and scenic amenity offered by ICOLLs has made them attractive to human settlement (Thom 2004) and has resulted in significant residential, commercial and agricultural development in ICOLL catchments and around the lake margins at many sites (Haines 2006). The increased human activity poses a series of risks for the sustainability of ICOLL ecosystems. These impacts include: increased sediment load from land clearing in catchment (Haines 2006; Borrell 2013), algal blooms and eutrophication from excessive nutrient input (Haines 2006), introduction of pollutants including trace metals, organochlorines and acidic groundwater from acid sulphate soils (associated with draining of alluvial plains during development) (Roy et al. 2001).

Further impacts relate specifically to the disruption of the ICOLLs entrance regime through the artificial opening of entrances, either periodically through mechanical excavation or permanently through the construction of training walls engineered to maintain an open entrance (as is apparent at Lake Illawarra) (Figure 6). There are a number of motivating factors that lead to the artificial management of ICOLL entrances; foremost is the risk of flooding for low-lying development on the margin of ICOLLs when the entrance is closed and water levels behind the barrier increase (Stephens and Murtagh 2012). Other motivations for opening entrances include alleviating water quality issues and in attempt to enhance marine fish and prawn recruitment (Stephens and Murtagh 2012). Natural, but often unpleasant, odours and the tendency for lake water to be turbid can lead to public pressure to

18 S Perry (2014) open or maintain a permanently open entrance (Haines 2006). Additional pressure to open entrances can arise from community beliefs surrounding the ‘best practice’ for the ICOLL and or the belief that it will improve surfing conditions (Stephens and Murtagh 2012). In the extreme, community members illegally initiate entrance openings to uphold their ideals about entrance management. Repeatedly opening entrances artificially has a degrading effect on ICOLLs in the long term. This includes altering the structure of ecological communities as the extent of seagrasses, saltmarshes and riparian wetlands is reduced, removing habitat for biota (Jones and West 2005; Haines 2006), and changing the behaviour of the entrance itself as lower water levels have less potential to scour out the entrance channel and as a result entrances rapidly close (Haines 2006). Short term impacts such as mass kills have been observed at ICOLLs following entrance breakouts (Figure 5) (Stephenson 2011). To mitigate impacts, preserve ecosystem integrity and balance conflicting community and land-use perspectives ICOLLs are systematically managed.

Figure 6: Artificial entrance openings: training walls at Lake Illawarra Entrance (left) (MAP 2009); Excavation of entrance channel at Burrill Lake (right) (Massie date unknown).

2.1.2 ICOLL Management

The diverse land-use and development that occurs around ICOLLs, in addition to their value as ecosystems, has led to a series of legislated management policies at all levels of government. ICOLLs are one of the most complex management systems on the coast due to the number of factors that have to be taken into consideration (HRC 2002; Thom 2004; Haines 2008). Specifically, these issues include entrance management, nutrient and sediment load from catchment land use, present ecosystems and their resilience to impacts, and economic and social interests (Thom 2004). Government legislation in Australia has shifted

19 S Perry (2014) in the recent decades to promote ecologically sustainable development (ESD) (Thom 2004). The foundations of ESD are: the conservation of biological diversity and ecological integrity, inter-generational equity, improved valuation, pricing and incentive mechanisms and the application of the precautionary principle. Government policy advocates that these principles are to be used to guide decision-making in all areas that affect the NSW coast (BVSC and ESC 2000).

At the state government level there are a number of policies and instruments that govern the management and use of ICOLLs, examples of these policies include (NSW) Coastal Policy 1997, (NSW) Threatened Species and Conservation Act 1995 and the Fisheries and Management Act 1994. Development around ICOLLs is restricted based on land zoning in Local Environment Plans (LEPs) and State Environmental Planning Policies (SEPPs) (Haines 2006). Specific to the management of ICOLLs is the (NSW) Estuary Management Policy, which is contained in the (NSW) Coastal Policy 1997 legislation. The objectives of the Policy are:  The protection of estuarine habitats and ecosystems in the long-term, including the maintenance of the hydraulic regime of each estuary  The preparation and implementation of a balanced long-term management plan for the sustainable use of each estuary and its catchment, defining strategies for: o Conservation of aquatic and other wildlife habitats o Conservation of aesthetic values of estuaries and wetlands o Prevention of further estuary degradation o Repair of damage to the estuarine environment o Sustainable use of estuarine resources, including commercial uses and recreational uses as appropriate (BVSC and ESC 2000)

Estuary Management Plans (EMPs) are the practical way in which the goals of the Estuary Management Policy are enforced. Local governments form Estuary Management Committees that design and implement EMPs based on the requirements of each estuary and the concerns of the local community. The requirements of each estuary, such as threatened species, breeding grounds, anthropogenic impacts and or water quality concerns are identified in Estuary Process Studies or Review of Environmental Factors reports. As water quality is a major concern for a number of estuaries, EMPs include water quality objectives (WQOs) and

20 S Perry (2014) river flow objectives (RFOs) in compliance with the Australian Water Quality Guidelines for Fresh and Marine Water (Australian and New Zealand Environment Conservation Council, 1992) and subsequent guidelines set by the NSW Environment Protection Agency (EPA). The final EMP consists of management strategies and a schedule of activities (such as remediation tasks) to be undertaken in order to achieve the objectives (BVSC and ESC 2000; Haines 2008). Haines (2008, p.24) asserts that a formal EMP does not ensure that an ICOLL is managed effectively, nor that the goals of the EMP are given due consideration when development applications are assessed by authorities. Furthermore, the adequate formulation and implementation of EMPs are dependent on funding and resource constraints (Haines 2008).

The guidelines for entrance management including the thresholds for initiating an artificial entrance opening are detailed in the relevant ICOLLs EMP. Where artificial openings are undertaken for the purposes of flood mitigation a maximum water level is given in meters Australian Height Datum (AHD). This trigger value represents the maximum height that the water level within the ICOLL can reach before encroaching on low-lying development, infrastructure or services (including sewage and septic systems) and is specific to each ICOLL and its surrounding environment. Approximately 50% of all ICOLLs in NSW are artificially managed for flood mitigation purposes (Haines 2008, p.6). The management of ICOLL entrances, indeed ICOLLs in general, should be conducted with as much consideration as possible to natural processes to promote and maintain the natural entrance regime and associated flow-on ecological and physical conditions.

2.2 Coastal and Catchment Processes

The coastline of NSW is wave-dominated; the coast is subject to physical processes that are dominated by wave energy rather than those that are dominated by tide energy, for example (Davis and Hayes 1984). Waves are a principal source of energy for erosion and deposition, and are responsible the movement of sediment along coasts. Waves striking the coastline obliquely result in the longshore transport of sand, which acts to form barriers across coastal inlets and embayments (Haines 2006). Ranasinghe and Pattiaratchi (2003) hypothesise that the formation of barriers occurs by two mechanisms (Figure 7). The first mechanism is that of longshore sediment transport mentioned by Haines (2006), in which waves entrain sediment and transport it along the beach in the direction of the wave current (drift-aligned).

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At an estuary entrance, a shoal forms up-drift resulting in the formation of a spit across the entrance. The size and rate of growth of the spit is dependent on the intensity of the longshore drift, eventually the spit will prograde and close off the entrance when the out-flowing current from the estuary is not strong enough to erode and maintain the channel. In the second mechanism, hypothesised by Ranasinghe and Pattiaratchi (2003), longshore transport rates of sediment are small, instead onshore sediment transport occurs due to swell waves breaking parallel to the shore (swash-aligned). Sand that has been previously eroded from the beach during storms and stored offshore is transported back onto the beach, choking the entrance and forming an entrance berm. This second mechanism is more likely to occur on beaches where near-normal wave incidence is apparent. The mechanisms for berm formation illustrate the importance of the incident directions of waves that make up the wave-climate.

Figure 7: Schematic of entrance closure through longshore drift (mechanism 1) and onshore sediment transport processes (mechanism 2) (Ranasinghe and Pattiaratchi 2003).

The wave climate of NSW is energetic and highly variable, consisting of a moderate east coast swell that is amplified by storm wave generation originating in the Coral and Tasman Seas (Short and Trenaman 1992). Short and Trenaman (1992) undertook a comprehensive analysis of the wave climate of Sydney NSW, identifying a number of seasonal trends apparent over the twenty-year study period. The east coast swell is predominant, with 42% of waves arriving from an easterly direction annually, with peak incidence in March and June.

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Northeast swells occur during summer; 17% of annual waves are from the northeast while waves from the southeast occur during winter, peaking in August. The energy associated with waves also changes seasonally, with wave-power varying in accordance to changes in incident direction: wave power increases from January to June, before decreasing to the annual minimum in December. These temporal changes in wave climate vary in accordance with the meteorological systems that are responsible for generating waves of certain directions. A subtropical anticyclone high-pressure system has a dominant influence on the climate of Sydney; this system varies in latitude seasonally and its position is associated with the presence of mid-latitude cyclones in the Tasman Sea, which in turn influences deepwater wave power (Goodwin 2005). Other meteorological systems of relevance are tropical and east coast cyclones (Short and Trenaman 1992). Each system generates distinctly different wave conditions, as identified by Phinn and Hastings (1992). Tropical cyclones occur in summer, originating in the Coral Sea before tracking south along the Queensland (QLD) and NSW coasts. High energy waves associated with tropical cyclones originate from the north and northeast, accounting for the peak in wave power early in the calendar year. Strong winds, rainfall and large waves from the Tasman Sea are associated with east coast cyclones (east coast low pressure systems). These systems are most prevalent during April to September and contribute to the high degree of variability, producing waves from a southeast origin (Short and Trenaman 1992). The relative influence of each A: Anticyclones SS: Southern Lows synoptic system in determining the CL: Continental Lows wave climate illustrates that the IT: Inland Lows coastal ocean off NSW and southeast EL: East Coast Lows TC: Tropical Cyclones Australia in general is dominated by storm activity (Figure 8) (Short and Trenaman 1992; Roy et al. 2001). Storms have three main effects on ICOLL entrance condition: (1) storms with rainfall increase catchment input into ICOLLs and can lead to entrance openings; (2) large and high energy

Figure 8: Number of storms occurring on the storm waves can erode sediment from NSW coast based on 60 year analysis (1920 – entrances and beaches; and (3) large 1980) (Anon 1985 in Short and Trenaman 1992).

23 S Perry (2014) storm surges can inundate entrances with sediment and associated debris. Rainfall is associated with a number of storm systems including east coast cyclones (Short and Trenaman 1992), and when sufficiently strong, the opening effect of rainfall can overcome the closing effect of storm waves and lead to natural entrance breakouts (Ranasinghe and Pattiaratchi 2003). Where the ICOLL entrance is already open, erosion by swell and storm waves contributes to the scouring of the entrance channel, acting to prolong the duration of time the ICOLL is open (Ranasinghe and Pattiaratchi 2003). Large, high power storm waves can breach entrances in the form of surges during which these large waves deposit sediment and other associated storm wrack, which chokes the entrance (Roy et al. 2001).

The morphology of ICOLL entrances (as with all beach landforms) is influenced by the dominant storm and wave climate, as unconsolidated sediment along the coast constantly readjusts respective to wave direction and power (Harley et al. 2010). As discussed above, the exposure to waves of certain incidences will influence the mechanism of barrier formation (Ranasinghe and Pattiaratchi 2003). The location of the ICOLL entrance with respect to the embayment will influence the degree to which certain wave directions affect the entrance. Sediment in beaches undergoes the phenomenon of rotation due to changes in the direction of waves (Ranasinghe et al. 2004).

Rotation occurs where sediment that has been eroded from one end of the compartment is deposited at the other end, resulting in net accretion and widening at that end. Changes in wave incidence reverse the direction of sediment transport, eroding from the previously accreting end of the compartment and depositing the sediment on the previously eroded end (Ranasinghe et al. 2004). Both mechanisms of sediment transport contribute to rotation, with two-thirds the result of onshore sediment transport and the remaining third attributed to longshore sediment transport (Harley et al. 2011). How much waves of a certain incident direction affect the entrance conditions of the ICOLL depends on the direction that the beach faces and the location of the entrance along the beach. ICOLLs that are on the accreting end of the coastal compartment will be inundated with sediment and as the beach widens (Haines and Thom 2007). Conversely, at the eroding end there is reduced potential for sediment ingress and deposition in the entrance, increasing the potential for more open entrance conditions (Haines and Thom 2007). Rotation processes have been linked to broad climate systems including the El Niño Southern Oscillation (Ranasinghe et al. 2004; Short et al. 2000; Haines and Thom 2007). This is largely attributed to the inter-annual variation in the

24 S Perry (2014) wave climate, which is also linked to phase changes in the El Niño Southern Oscillation (Phinn and Hastings 1992; Harley et al. 2011) (discussed further below).

2.3 El Niño Southern Oscillation

The El Niño Southern Oscillation (ENSO) is a broad-scale atmospheric circulation phenomenon that occurs across the Pacific Ocean. Atmospheric circulation occurs on a global scale, with a number of regional patterns that drive ocean currents, local winds, monsoons and rainfall together influencing regional climate (Allan 1988; BOM 2014). The El Niño Southern Oscillation consists of the temporal changes in the direction and intensity of the Walker Circulation, which is modulated by changes in sea surface temperature (SST) (Allan 1988). Initial research into the El Niño Southern Oscillation described a ‘see-saw’ effect in atmospheric pressure, apparent between the eastern and western regions of the Pacific Ocean, with an oscillation occurring every 2 – 7 years (Bjerknes 1969 in Allan 1988). The oscillation effect is dependent on coupled interactions between the atmosphere and the ocean, with each variable being strongly influenced by the boundary conditions imposed by the other (Neelin et al. 1988). The El Niño Southern Oscillation is responsible for driving many interrelated atmospheric and oceanic parameters including precipitation, pressure and temperature (Allan 1988). Termed ‘teleconnections’ by Bjerknes in 1969 there are apparent correlations between the phase of the El Niño Southern Oscillation and regional weather patterns including rainfall and storm activity (Diaz et al. 2001; You and Lord 2008). These factors influence other environmental processes such as wave climate and subsequent patterns of erosion and deposition (as discussed above).

There are three phases to the El Niño Southern Oscillation: the El Niño phase, the La Niña phase and the neutral phase. In the neutral phase, the typical conditions of the Walker Circulation are apparent, in which warm ocean temperatures cause warm air to rise in the western Pacific (eastern Australia) and circulate east across the Pacific Ocean before descending over the cooler ocean in the east (Figure 9). In the Walker Circulation, the trade winds bring warm moist air that rises above northern Australia and Indonesia creating the dominant low-pressure systems associated with rainfall (BOM 2014). In the La Niña phase the Walker Circulation and trade winds are intensified. The ocean thermocline is higher in the eastern Pacific Ocean resulting the upwelling of cool, deep ocean waters that confine warm water to the western Pacific Ocean. These warm waters in addition to the strengthened trade

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Figure 9: The three phases of the El Niño Southern Oscillation (BOM 2012).

26 S Perry (2014) winds result in higher than average rainfall across northern Australia and monsoon conditions in Indonesia (BOM 2012). In the El Niño phase the reverse is apparent: the Walker Circulation and trade winds are weakened or reversed depending on the intensity of the El Niño event, causing the thermocline to deepen in the central and eastern Pacific. Cooler ocean temperatures that result in the western Pacific Ocean combined with the absence of the moisture-laden trade winds result in below average rainfall and drought conditions over Australia (Figure 9) (BOM 2012).

Figure 10: Illustration of the major climatic drivers influencing rainfall variability across Australia (Risbey et al. 2009).

The variability in rainfall across Australia and the association with the El Niño Southern Oscillation has been widely studied (see for example Power et al. 1999; Risbey et al. 2009; Cai et al. 2010). The strength of ENSOs influence on rainfall variability is varied across different seasons and regions of Australia (Risbey et al. 2009). ENSO is also not the only climate variable that is important in determining rainfall patterns in Australia: Risbey et al. (2009) studied the respective level of influence of ENSO, the Southern Annular Mode (SAM), atmospheric blocking, and the Indian Ocean Dipole (IOD) in contributing to rainfall variability (Figure 10). In addition to ENSO, the SAM and atmospheric blocking contribute to rainfall variability on the southeast coast of Australia; however these drivers are all interdependent, with correlations between each of the drivers apparent. The influence of

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ENSO on rainfall variability in the southeast of Australia is strongest during the winter and spring months, however for the coast of NSW specifically there is no correlation apparent during the winter months, indicating the importance of other climate drivers in influencing rainfall patterns at that time (Figure 11) (Risbey et al. 2009).

Figure 11: Seasonal correlation between rainfall and the El Niño Southern Oscillation across Australia. Correlations are significant at the 95% level, from data spanning 1889 – 2006 (Risbey et al. 2009).

Seasonally, the variability of rainfall and other climate variables is linked to the El Niño Southern Oscillation, broadly however the phase and associated strength of ENSO is influenced by longer-term climate regimes that vary on decadal scales, including the Interdecadal Pacific Oscillation (IPO). The IPO is a similar phenomenon to ENSO however it is principally the result of changes in sea surface temperate confined to the equatorial belt and extra-tropical North Pacific Ocean. When the IPO is in the positive phase SST anomalies over the North Pacific Ocean are negative, as are anomalies in the South Pacific, while SST in the equatorial Pacific are positive (Salinger et al. 2001). In the negative phase the reverse relationship is apparent. The IPO and ENSO operate on different time scales, however the similarities between the two climate systems suggest that the IPO has a modulating effect on

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ENSO and ENSO teleconnections (Salinger et al. 2001; Cai et al. 2010). In a study focusing on southeast QLD, Cai et al. (2010) show that the decline in summer rainfall since 1980 is consistent with the shift in the IPO phase, reinforcing the notion that the ENSO-rainfall relationship is sensitive to the interdecadal condition. Furthermore, correlations between the IPO and ENSO suggest that the positive phase of the IPO is associated with enhanced and more frequent El Niño events (Salinger et al. 2001).

Figure 12: Schematic illustration of the response of ICOLL, including entrance condition, inlet sediment and water level, to rainfall events (Woodroffe 2007).

Rainfall variability represents only aspect of how the El Niño Southern Oscillation affects ICOLL processes. Changes in the wave climate and subsequent sediment transport regimes including beach rotation and barrier formation has been shown to be largely influenced by storm activity (as discussed above). Correlation between storms and the El Niño Southern Oscillation has been identified, in terms of both frequency and severity (see Phinn and Hastings 1992; Short et al. 2000; You and Lord 2008). Phinn and Hastings (1992) studied the frequency of tropical cyclone activity based on the foundation work by Nicholls (1979, 1984, 1985) who identified correlations between tropical cyclone and activity and ENSO, concluding that tropical cyclones are more active during La Niña. Phinn and Hastings hypothesise that the increased prevalence of tropical cyclones, including their tendency to

29 S Perry (2014) track further south, will result in prolonged conditions of high-energy cyclone generated waves from the arriving from northeast to the south coast. These high-energy conditions increase the potential for erosion. Their conclusion is supported by other studies: for example, Ranasinghe et al. (2004) state that the frequency of storms in La Niña compared to El Niño is approximately double. In addition, You and Lord (2008) reach the same conclusion, further stating that La Niña storms are more severe. The altered wave climate accounts for oscillating periods of erosion and accretion on beaches, affecting the sediment transport regimes that are present. During La Niña phases the prevalence of waves of northeast direction cause erosion of the northern end of beaches, transporting entrained sediment to the southern end. In El Niño phases, where the incident direction of waves is mostly from the south and southeast due to east coast cyclones and low-pressure systems, the opposite effect is apparent, with the southern end of a compartment eroding while the northern end accretes (Ranasinghe et al. 2004; Short et al. 2000). ICOLLs with entrances positioned at the northern entrance of beaches will be more likely to experience erosion of the entrance berm and barrier during La Niña phase, while ICOLLs with entrances at the southern end of beaches will have increased sediment influx (Figure 12). The reverse trend will be apparent during El Niño phases.

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Chapter 3: Regional Setting

3.1 Site Selection

ICOLLs on the south coast of New South Wales that are of interest to the NSW Office of Environment and Heritage were selected to be included in this study. The distribution of ICOLLs in NSW is especially concentrated on the south coast between Wollongong and Victoria (Haines 2008). Out of the large number of ICOLLs in NSW 6 sites were selected to be included in this study. These 6 ICOLLs fulfil the following requirements:  The entrance condition of the ICOLL has exhibited both open and closed conditions throughout the study period. Sites may exhibit mostly closed or mostly open tendencies (as it is rare that an ICOLL will be bimodal, as previously discussed).  The entrance condition may have been altered by artificial openings, however the entrance must not be permanently opened by engineering structures such as training walls as effectively the estuary is no longer exhibiting the fundamental entrance characteristics of an ICOLL.  The ICOLL entrances have different orientations, positions on the beach and / or protection by headlands. This will allow for analysis into the affect that these variables have in determining the ICOLLs response to coastal processes including major storms and associated large waves of different incident directions.  The Manly Hydraulics Laboratory captures data for the ICOLL. Water level data provided by MHL from the ICOLL stations is the basis of determining entrance condition and is therefore a necessary requirement.  A Bureau of Meteorology rainfall station is within close proximity to the ICOLL.

Lake Wollumboola, Swan Lake, Burrill Lake, Lake Tabourie, Durras Lake and Wallaga Lake were the 6 sites selected for inclusion in this study. Two additional ICOLLs, Meroo Lake and Lake Nadgee, were proposed for inclusion as reference ICOLLs as their entrances largely exhibit only natural conditions, however the absence of water level data at these sites excludes them from this study.

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3.2 Geology, Climate and Wave-climate of the NSW South Coast

The ICOLLs included in this study (hereafter referred to as the ICOLLs) are spread along the south coast of NSW. The northernmost ICOLL Lake Wollumboola (Figure 13, site A) is situated just north of Jervis Bay, approximately 185 km south of Sydney NSW, while the southernmost ICOLL Lake Wallaga is situated just north of Bermagui on the far south coast 470 km south of Sydney (Figure 13, site F). Geologically, this area of NSW consists of the southernmost portion of the Sydney Basin unit and the igneous units of the Lachlan Orogen to the south (Figure 13) (Geoscience Australia 2012).

Jervis Bay Ps

Mzg

Os Dd

EOw

Batemans Bay

Geological Units: Dg Ps – Permian Sedimentary Mzg – Mesozoic Felsic Legend: Os – Ordovician (a) Wollumboola Intermediate (b) Swan Dd – Devonian Mafic (c) Burrill EOw – Palaeozoic mixed (d) Tabourie origin Sedimentary (e) Durras Dg – Devonian Felsic (f) Wallaga Kg – Cretaceous Felsic Bermagui Kg

Figure 13: Satellite image of ICOLL locations (left) (Google Earth); Geology of the NSW south coast (right) (Geoscience Australia 2012).

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The geologically-based classification by Roy et al. (2001) of each ICOLL is listed in Table 1. The ICOLLs fall into two categories: intermittently closed saline coastal lagoons or wave- dominated barrier estuaries. The sites exhibit different levels of sediment infill and therefore different evolutionary maturity; Lake Tabourie is the most evolutionary mature out of the ICOLLs, grouped in the semi-mature phase (see Figure 4).

Table 1: Geological Classification of ICOLLs (Roy et al. 2001) ICOLL Group Type Evolution Lake Wollumboola IV: intermittently closed Saline coastal lagoon Intermediate Swan Lake IV: intermittently closed Saline coastal lagoon Youthful Burrill Lake III: wave dominated Barrier estuary Youthful Lake Tabourie IV: intermittently closed Saline coastal lagoon Semi-mature Durras Lake IV: intermittently closed Saline coastal lagoon Intermediate Wallaga Lake III: wave dominated Barrier estuary Intermediate

In broad terms, the climate of the NSW south coast is classified as warm-temperate ranging to cool-temperate nearer to the Victorian border (Roy et al. 2001). The average annual rainfall (based on the 30-yr period from 1976 – 2005) for the NSW south coast is approximately 1000 mm, decreasing to approximately 800 mm on the far south coast (BOM 2011). Trends in rainfall specific to the catchment of the individual ICOLLs are identified in the analysis (see Chapter Four).

The NSW south coast is wave dominated with a predominant east – southeast swell. The wave climate for the south coast is much the same as that of Sydney, and therefore the attributes of the wave climate identified for Sydney in the literature including storm frequency, incident direction of waves and the influence of the El Niño Southern Oscillation will have a similar effect on the south coast (see Chapter Two) (Short and Trenaman 1992; Phinn and Hastings 1992; You and Lord 2008). The influence of the wave climate on the ICOLLs is dependent on the exposure of the entrance and the location with respect to the coastal embayment (discussed below).

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3.3 Characteristics of study ICOLLs

(a) Lake Wollumboola (b) Swan Lake

(e) Lake Durras (f) Wallaga Lake

Figure 14: Satellite imagery of each ICOLL. Each ICOLL exhibits a different size, shape and entrance channel morphology. Additionally, the position of the entrance within the embayment and orientation of the embayment is varied across the sites (Google Earth).

The ICOLLs all exhibit a range of entrance morphologies, including orientation, channel length and width and the location of the entrance with respect to the embayment (Figure 14). Lake Wollumboola is unique among the study ICOLLs for two reasons. First, the entrance is relatively wide with the main lake separated from the ocean only by the sand barrier and

34 S Perry (2014) berm. The other ICOLLs exhibit narrow, often long, entrance channels that separate the main lakes from the respective barriers. Second, Lake Wollumboola is the only ICOLL with a coastline that is orientated north south, with the beach (and therefore entrance) facing directly east. The embayments in which Swan Lake and Durras Lake are located are angled towards the southeast, while the remaining ICOLLs are oriented east-southeast. The orientation of the embayment affects the extent that the entrance (and beach as a whole) will be impacted by waves from certain directions (Haines et al. 2006). Furthermore, the position of the entrance along the beach with respect to headlands also shelters the entrances from waves of certain directions. The entrance at Lake Durras is very protected from waves from the north by the large headland, while the entrance at Lake Wollumboola receives minimal protection from the smaller headland (Figure 14, e and a). Lake Durras and Lake Wollumboola are the only two entrances located at the northern end of the embayments; the remaining ICOLLs are positioned towards the southern end of their respective beaches, receiving minimal protection from the smaller headlands. The entrance at Lake Tabourie is however protected from waves of easterly incidence by a rocky island and adjoining tombolo, situated directly east of the entrance (Figure 14, d). Similarly, offshore and near-shore rocky reefs shelter the entrance at Swan Lake (Figure 14, b) (Spurway et al. 2004).

In addition to the entrance and embayment characteristics, each ICOLL also has a distinct set of physical characteristics including waterway area and depth and the size of the catchment, which are listed in Table 2. The morphological characteristics of each site give rise to the hydrological, chemical and ecological properties of the ICOLL (Haines et al. 2006), which are all outlined in the respective Estuary Management Plans that are prepared for each ICOLL (as discussed above). The EMPs for the study ICOLLs identify a number of endangered ecological communities (EECs) that are present at some or all of the ICOLLs including Bangalay Sand Forest, Coastal Saltmarsh, Swamp Oak Forest, and Swamp Sclerophyll Forest. In addition to EECs, some of the ICOLLs are breeding grounds for a number of vulnerable and endangered sea- and shorebird species including the Little Tern, Pied Oystercatcher and Hooded Plover. At Swan Lake endangered amphibian species, specifically the Green and Golden Bellfrogs have also been sighted (Spurway et al. 2004). Other ecological communities present at the ICOLLs include varied species of fish (both commercial and not commercially valuable), prawns, oysters and seagrasses. Invasive species including the algae Caulerpa taxifolia have also been identified at some of the ICOLLs, notably Burrill Lake (Spurway et al. 2008). The ICOLL ecosystems are at risk from

35 S Perry (2014) anthropogenic activities; Spurway et al. (2008) state in the Burrill Lake EMP that pollution and other impacts from increased urban activity on the estuary fringe pose a greater risk to the EECs than altered hydrological regime from changing entrance condition.

Table 2: ICOLL Characteristics ICOLL Location Catchment Estuary Average Maximum Area Area Depth water level* (km2) (km2) (m) (m AHD) Wollumboola 34°57’06” S 34.1 6.3 0.8 2.5 150°45’43” E Swan 35°11’18” S 26.4 4.7 2.4 2.5 150°33’36” E Burrill 35°23’01” S 60.7 4.4 4.3 1.25 150°26’43” E Tabourie 35°26’33” S 46.1 1.5 0.8 1.17 150°24’23” E Durras 35°38’28” S 58.4 3.8 1.4 2.4 150°18’01” E Wallaga 36°21’57” S 263.8 9.3 3.7 1.25 150°04’33” E NB: Table adapted from OEH (2012, a – f); *Maximum water level at which the entrance is opened artificially to mitigate flood hazard to low-lying assets.

The extent to which anthropogenic activity impacts the ICOLLs is dependent on the concentration of urban and agricultural development within the ICOLLs catchment. Visible in Figure 14, the level and nature of development around the fringe of the ICOLL and the entrance is different at each site. The catchment of Durras Lake is the least developed, as the majority of the catchment is enclosed in the Durras Lake National Park, development is limited to tourist accommodation located on the northern side of the entrance channel (Figure 14, d). Areas of the catchments for Lake Wollumboola, Swan Lake, Lake Tabourie and Wallaga Lake are also enclosed in National Parks, with an additional portion of the Wallaga Lake in use as State Forest. Burrill Lake shows the highest concentration of urban development around the ICOLL, specifically around the entrance channel and floodplain (Figure 14, c). Low-lying development is at risk of inundation when water levels within the lake increase under closed entrance conditions; to prevent damage from occurring the critical height before inundation is ascertained through specific flood studies and analysis of previous flood events (Figure 15). If the water level of the ICOLL reaches the critical height, Council or another relevant local authority will conduct artificial entrance openings to lower the water level. Lake Wollumboola, Swan Lake, Burrill Lake and Lake Tabourie are all managed by

36 S Perry (2014) the Shoalhaven City Council, Lake Durras by the Eurobodalla Shire Council, who also jointly manages Lake Wallaga with the Bega Valley Shire Council. The trigger water level for each of the study ICOLLs is given in Table 2. The tendency for the water level to reach this level dictates how frequently the entrance is opened artificially for flood mitigation purposes, for example, Lake Tabourie frequently reaches the trigger water level and is regularly opened to ensure that low-lying development (specifically the septic tanks of residential properties located on the entrance channel margin) is not inundated. The frequency of artificial entrance openings at the study ICOLLs is analysed in this report (see below).

Figure 15: Underfloor flooding of waterfront property at Burrill Lake (left) (Spurway et al. 2008); Waterfront tourist accommodation at risk of high water levels at Lake Wallaga (right) (25 September 2014).

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Chapter 4: Methods and Results

Two approaches were used to determine if there is correlation between the ICOLL entrance regime and the El Niño Southern Oscillation. First, data analysis utilising graphing techniques was undertaken to identify the relationship between the ICOLL entrance condition and ENSO. This was achieved by examining the relationship between the ICOLL and the controlling coastal and catchment variables, and in turn the relationship between those variables and ENSO. Second, based on these findings, a number of statistical tests were run to determine if the correlations between the ICOLL entrance regime, the forcing variables and ENSO are significant. The methodology applied and the results are presented in this chapter in a combined format.

4.1 Datasets

Time-series datasets that are representative of ICOLL entrance condition, catchment and coastal processes and the El Niño Southern Oscillation were used for this analysis. A summary of these datasets is provided in Table 3 followed by a description of the data capture methods for ENSO and the coastal parameters. The data was acquired for the purposes of this project from multiple government sources including the NSW Office of Environment and Heritage, the Manly Hydraulics Laboratory (MHL) and the Australian Bureau of Meteorology. The temporal coverage of each dataset is different: the record for ENSO is accessible from 1876, whereas the in-situ water level recorders for the ICOLLs are much more recent installations, therefore the availability of water level data became the limiting factor on the time period analysed for each ICOLL. The water level record for Lake Wollumboola, Burrill Lake, Lake Tabourie and Wallaga Lake span approximately 20 years from the early 1990’s, however as the stations for Swan Lake and Lake Durras were only installed in 2000 the records at these sites are considerably shorter. These records, as well as those for rainfall, are incomplete and any absent data was left as an empty cell rather than a zero value during pre-processing. Pre-processing of the data in Microsoft Excel entailed adjusting the data for these absent entries to preserve the time-series as well as the creation of monthly, yearly and long-term means for parameters including water level, maximum wave height and rainfall.

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Table 3: Description of Datasets Dataset (units) Purpose Coverage Source Southern Representative of El 1876 – present Australian Bureau Oscillation Index Niño Southern of Meteorology Oscillation Interdecadal Pacific Phases of the IPO 1922 – 2010 Power et al.(1999) Oscillation Dai (2013) Water Level (m) Entrance condition Lake Wollumboola: 1991 Manly Hydraulics – 2013 Laboratory Swan Lake: 2000 – 2013 Burrill Lake: 1991 – 2013 Lake Tabourie: 1992 – 2013 Lake Durras: 2000 – 2013 Wallaga Lake: 1993 – 2007 M2 Tidal Entrance condition Burrill Lake: 1991 – 2013 Manly Hydraulics Constituent (m) Lake Tabourie: 1992 – Laboratory 2013 Lake Durras: 2000 – 2013 Rainfall (mm) Surrogate for Lake Wollumboola: 1991 Australian Bureau catchment flows – 2013 of Meteorology Swan Lake: 2000 – 2013 Burrill Lake: 1991 – 2013 Lake Tabourie: 1992 – 2013 Lake Durras: 2000 – 2013 Wallaga Lake: 1993 – 2007 Wave Data Coastal processes 1986 – present Manly Hydraulics Hsig (m) Laboratory Hmax (m) Direction (degrees) TP1 (seconds) Tsig (seconds) Power (kW/m) Aerial Photography Entrance condition Lake Wollumboola: 1949 NSW Office of – 2011 Environment and Swan Lake: 1949 – 2011 Heritage Burrill Lake: 1944 – 2011 Lake Tabourie: 1944 – 2011 Lake Durras: 1949 – 2011 Wallaga Lake: 1944 – 2011 NB: Data for Wallaga Lake is incomplete – due to time constraints the complete data series could not be accessed and included in the analysis – for this reason Wallaga Lake analysis is limited to the 14 year period.

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4.1.1 Representing ENSO: the Southern Oscillation Index

The Southern Oscillation Index (SOI) provides an indication of the development and intensity of El Niño and La Niña phases of the El Niño Southern Oscillation. The SOI is derived from the difference in atmospheric pressure observations recorded at Darwin in the Northern Territory of Australia and Tahiti in the South Pacific. The index is positive when surface pressure is low over Australasia and high over the southeastern Pacific (La Niña) and negative when the reverse relationship is apparent (El Niño) (Allan 1988). The Bureau of Meteorology (from whom the data was sourced) calculates the SOI using the formula established by Troup (1965) as follows:

(푷풅풊풇풇−푷풅풊풇풇풂풗) 푺푶푰 = ퟏퟎ Equation 1. 푺푫 (푷풅풊풇풇)

Where: Pdiff = mean monthly pressure Tahiti – the mean monthly pressure Darwin Pdiffav = long term mean Pdiff for the month, and SD (Pdiff) = long term standard deviation of Pdiff for the month (BOM 2012)

SOI values calculated in this way are referred to as Troup SOI data to distinguish from other indices. The Bureau of Meteorology measure and derive the SOI daily, however these values fluctuate significantly due to changes in atmospheric pressure in response to short-term weather patterns. To illustrate long-term climate variability, the SOI is presented as a monthly mean value that is plotted with a 5-month moving average trendline. Sustained positive SOI values greater than 7 are indicative of a La Niña phase while sustained negative values less than -7 indicate an El Niño phase (BOM 2014). Interim periods where the monthly SOI values fluctuate or are only mildly positive or negative are representative of a neutral phase in the Walker Circulation.

The SOI is not the only index used to measure the El Niño Southern Oscillation. Other indices are most often ocean-based measurements that record sea surface temperature (SST) anomalies as a means to measure the oscillation. Niño-3, Niño-3.4 and Niño-4 as well as the ENSO Modoki index (EMI) are such indices (Risbey et al. 2009). These indicators are usually well correlated however as the indices utilise different variables to reflect the El Niño Southern Oscillation some variation in the record is apparent (Figure 16) (Risbey et al. 2009). The Troup SOI was selected as the index used to illustrate the El Niño Southern Oscillation

40 S Perry (2014) for the purposes of this project because a long-term record of the mean monthly SOI from 1876 – present is freely available from the Australian Bureau of Meteorology website. Additionally, a number of authors in the literature support the use of the Troup SOI; Risbey et al. (2009) purport that Troup SOI offers the most consistent record going back in time. Furthermore, because the SOI is based on large-scale surface pressure variation, the index is more related to rainfall processes and has the highest correlation (out of the various indices) with Australian rainfall (Risbey et al. 2009).

Figure 16: Comparison between two indices of the El Niño Southern Oscillation. La Niña phases are represented in blue, El Niño phases in red; overall the comparison between the two indices of ENSO for this period show good correlation (NOAA 2005).

4.1.2 Representing coastal processes: wave statistics and water levels

Wave statistics and observational records provide datasets for the representation and analysis of the wave climate. Such records were previously ascertained through ship logs and manned lighthouses, however Waverider buoys and satellite modelling techniques have enabled comprehensive datasets that describe the wave climate to be produced (Short and Trenaman 1992; Hemer et al. 2007). Although there are numerous datasets sourced from satellite techniques, data from Waverider buoys is deemed to be the most comprehensive and accurate and was chosen for use in this project (Short and Trenaman 1992; Hemer et al. 2007).

The Manly Hydraulics Laboratory (MHL) provided wave data collected in-situ from a Directional Waverider buoy stationed at Batemans Bay for use in this project. The Waverider buoys operated by MHL record data in 34-minute bursts, which are transmitted to shore via a

41 S Perry (2014) telemetry network for processing using zero-crossing and spectral analysis (MHL 2011). Directional Waverider buoys also record wave direction in-situ using on-board accelerometers and compass systems to ascertain the orthogonal direction of arriving waves (MHL 2011). Direction has been recorded in this way at Batemans Bay since 2001 when the Waverider buoy was upgraded; prior to this the deepwater wave direction included in the record was estimated (MHL 2012).

Figure 17: MHL water level gauges at Lake Tabourie (left) and Lake Wallaga (right).

In addition to data on the wave climate, MHL has collected water level and tide data through permanent and semi-permanent gauges at numerous locations on the New South Wales coast (Modra and Hesse 2011). These gauges form a network that enables analysis of tidal and climatic influences on water level (as with this study) (Modra and Hesse 2011). MHL uses five types of data capture systems (radar sensor, electromagnetic wave staff (EWS), vented pressure systems, solid state floatwell, and submersed water level recorders) situated across four types of locations (open ocean bays, offshore ocean, island sites and river entrance sites) to construct the water level records (Figure 17) (MHL 2013; Modra and Hesse 2011). Data is recorded continuously or in bursts and sent via telemetry to shore for processing into 1- minute or 15-minute time series (MHL 2013).

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4.2 The El Niño Southern Oscillation and Interdecadal Pacific Oscillation

The phases of the El Niño Southern Oscillation were first established to enable differentiation between ICOLL entrance conditions with respect to the ENSO phase. The Australian Bureau of Meteorology states that sustained negative values of the SOI less than -8 are indicative of an El Niño phase, while sustained positive values of the SOI greater than 8 are indicative of a La Niña phase (as above) (BOM 2014). The monthly mean SOI dataset was converted to a running 5-month moving mean and using conditional formatting the periods that fit the BOM criteria were extracted to be classified as El Niño or La Niña respectively. Periods that did not fit either criterion were classified as the neutral phase of the oscillation. The resulting time periods are tabulated in Table 4. As the severity of any particular El Niño or La Niña phase is not solely dependent on the strength of the SOI (instead it is due to the cumulative effect of climatic variables, as previously discussed) historic records from BOM were used to further categorise each phase as ‘weak’, ‘moderate’ or ‘strong’. A line graph of the SOI was produced in Excel, illustrating the phases of ENSO, to use in the later stage of the analysis (Figure 18). The Interdecadal Pacific Oscillation was included as an additional dataset to the SOI (Table 4) as it is known to have a modulating effect on the El Niño Southern Oscillation across Australia. The phases of the IPO were ascertained from analyses published by Power et al. (1999) and Dai (2013). One change in IPO phase coincides with the study period (Figure 18).

40 Positive IPO 30

SOI 0

-10

-20

-30 Negative IPO

-40

1/01/2005 1/01/1992 1/01/1993 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2006 1/01/2007 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013 1/01/1991 Figure 18: Monthly SOI (blue), with 5 month moving average (black) and IPO phases (red) (January 1991 – December 2013). Positive SOI values indicate La Niña phases while negative values indicate El Niño phases.

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Table 4: Bureau of Meteorology defined El Niño Southern Oscillation phases and corresponding phase of the Interdecadal Pacific Oscillation El Niño La Niña IPO Weak Moderate Strong Weak Moderate Strong Phase 1991 – 1992 Positive 1993 – 1994 1978 – 1998 1994 – 1995 1997 – 1998 1998 – 2001 2002 – 2003 Negative 2006 – 2007 2007 – 2008 2000 – 2010 2009 – 2010 2008 – 2009 2010 – 2012

Over the time period analysed there has been a total of 7 El Niño phases and 4 La Niña phases recorded by the Bureau of Meteorology (Table 4). The 5-month mean trendline in Figure 18 however indicates the presence of an additional El Niño phase between 2004 – 2005 as well two additional La Niña phases between 1996 – 1997 and 2006 – 2007. These periods may not be recognised as phases by BOM for a number of reasons including inconsistencies with the SOI signal or the interaction of other climate variables that are not included in this analysis. As the BOM guidelines regarding the SOI are used to determine the ENSO phases these additional phases will be included in the analysis.

4.3 ICOLL Entrance Condition

Water level data was used as the main surrogate for entrance condition. Although there are some records kept by the NSW Office of Environment and Heritage, MHL and Local Councils regarding the timing and nature of ICOLL openings they are incomplete and could not be used as the sole indication of entrance condition for each ICOLL. The water level is continuously recorded by in-situ stations run by MHL (NSW Public Works 2014) and was supplied for this study as a daily mean dataset for each site. Although the water level is not a direct measurement for the entrance condition it can be used to extrapolate the state of the entrance by analysing the data in graph form. A line graph of the water level for each site was produced in Excel (Figure 19). The scale of the x-axis was set to be the same as that used in the plot of the SOI (Figure 18) to allow for comparative analysis.

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3.5 Wollumboola

2.5

1.5 (m) 0.5 -0.5

3 Swan

(m) 1

1.5 Burrill

0.5 (m) 0 -0.5

1.5 Tabourie

0.5 (m) 0 -0.5

Durras

1.5

(m)

-0.5

1.6 1.4 Wallaga 1.2 1 0.8

(m) 0.6 0.4 0.2 0

-0.2

1/01/1992 1/01/1993 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2007 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013

Figure 19: Water level profile (m) for each ICOLL.

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The following parameters (illustrated in Figure 20) were used to infer the entrance condition from the water level line graph:  A stable (or relatively stable) line is indicative of a closed entrance (Figure 20, red arrow). The water level will show an increasing trend over a longer period of time while the entrance is closed. This occurs as rainfall and runoff are stored and accumulate in the ICOLL.  A highly variable line illustrates short-term changes in water level due to wave and tidal activity (Figure 20, blue arrow). The entrance is therefore open, allowing tidal exchange to occur. Although there is variation, the water level is likely to be low, as water does not accumulate behind the barrier when the entrance is open to the ocean.  An abrupt increase, or spike, in the water level (while closed) occurs in response to a large volume of input over a short span of time (Figure 20, purple or green arrow). For example a storm event releasing a significant volume of rainfall over a few hours.  Where a rapid decline in water level occurs immediately after a spike this is indicative of a change in the entrance condition as stored water is released from the ICOLL. This suggests that the entrance has opened.  The transition from an open condition to closed condition is illustrated by a gradual lessening in the variation in the curve and an overall increase in the water level.

Minimal variability = closed entrance

High variability = open entrance 2 Artificial Opening (2011) 1.8 1.6 Natural Opening (2012)

1.4 1.2 1 0.8

Water Level (m) 0.6 0.4 0.2 0

Figure 20: Indicators of entrance condition inferred from water level curve, illustrated on extract of Durras Lake water level (m) from January 2011 – December 2012.

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In addition to water level, M2 data can be used to illustrate the entrance condition of an

ICOLL. The M2 (principal lunar semi-diurnal constituent) is one of 4 constituents used in the harmonic analysis of ocean tides (Modra and Hesse 2011; MHL 2012). The derivation of tides and specifically the M2 through harmonic analysis is beyond the scope of this project, however when calculated using short-term (14-30 day periods) analysis the M2 value for the estuary mouth can be used to illustrate the tidal exchange through the estuary (ICOLL) entrance, thereby indicating the condition of the entrance at the time. The calculation to derive the M2 values becomes skewed towards 0 when there is no tidal signature for long periods of time, for example where the entrance to the ICOLL is closed. MHL omits M2 calculations from annual reports where the site in question is non-tidal for more than 50% of the year in order to maintain data integrity (MHL 2012). For this reason M2 data for the study ICOLLs was only accessible for the ICOLLs that spent the majority of time open (on average more than 180 days per year) (MHL 2012).

The M2 data used in this project was provided by MHL in processed form. Similar to the water level, line graphs from Excel were used to display the data in a similar way to enable comparisons. An M2 value of 0m is indicative of a closed entrance, with no tidal exchange occurring. A value close to 0m suggests that the entrance is heavily constricted, infilled with sand, allowing only minimal tidal exchange to occur. Respectively high M2 values indicate that tidal exchange is occurring through the entrance, illustrating that there is minimal entrance constriction apparent and therefore suggesting open entrance conditions. Figure 21 illustrates the results of the M2 analysis. The water level profiles are displayed alongside the

M2 profiles to illustrate the correlation between the two proxies of entrance condition.

Entrance constriction over time is most evident at Lake Durras and Burrill Lake (Figure 21).

The profile of the M2 changes gradually over time, indicating the progressive infill of sediment in the entrance berm. Similarly, from 2001 to 2004 the M2 profile of Burrill Lake indicates that the entrance channel was infilling during this time before closing for the first time within the data series (since 1991). The entrance condition at Lake Tabourie changes more abruptly, with entrance openings and closures occurring frequently. These changes in the M2 profile correspond to similar changes in the water level profile (Figure 19) indicating when the changes in the entrance condition of the ICOLLs occurred. As the M2 is available for only half of the sites, the M2 was used as a supplementary dataset but not included further in the analysis.

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0.3 M2 Burrill

0.2

(m) 0.1

1.5 Water level Burrill

0.5 (m) 0 -0.5

0.3 M2 Tabourie

0.2

(m) 0.1

1.5 Water level Tabourie

0.5 (m) 0 -0.5

0.3 M2 Durras

0.2

(m) 0.1

2 Water level Durras

1.5

1 (m) 0.5

1/01/2009 1/01/1993 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2007 1/01/2008 1/01/2010 1/01/2011 1/01/2012 1/01/2013 1/01/1992 Figure 21: Entrance constriction illustrated by the M2 profile (m) (black) for Burrill Lake, Lake Tabourie and Lake Durras. Water level profiles (m) (blue) correspond well to the M2 profiles: when the water level is highly variable the M2 is high indicating open conditions.

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A record of entrance condition for the whole study period was determined from the water level and M2 profiles (see Appendix One for the full record). The record details: the date of opening, maximum water level, period of time that the entrance was open, and the date of closure. Using the timing of entrance openings and closures, the ICOLL was classified into a binary condition, either ‘open’ or ‘closed’. For use in the statistical analysis this binary was assigned values; ‘open’ as 2 and ‘closed’ as 1. An additional line graph was produced in Excel for each ICOLL illustrating the entrance condition as either ‘open’ or ‘closed’. The SOI was included as an additional series to overall illustrate the relative time period that each ICOLL was open and or closed during each phase of the El Niño Southern Oscillation (Figure 22).

This figure illustrates a number of patterns regarding the relationship of ICOLL entrances to the El Niño Southern Oscillation. First, all of the ICOLLs were closed for a relative long period of time during the dry conditions associated with the 2009 – 2010 El Niño (Figure 22). This also occurred (with the exception of Burrill Lake) during the strong El Niño period from 2006 – 2007 (Table 4), however the ICOLLs that exhibit mostly closed entrance conditions, in particular Lake Wollumboola and Swan Lake, had already been closed for a number of years. As all of the ICOLLs did not exhibit a closed entrance condition during earlier El Niño years (for example 1993 – 1994 or 1997 – 1998) the closed condition could illustrate the influence of the Interdecadal Pacific Oscillation. In the negative phase of the IPO (apparent for the 2006 – 2007 El Niño), El Niño impacts across Australia are strengthened (Power et al. 1999; Salinger et al. 2001). Second, a number of entrance openings occur when the SOI is transitioning from one phase to another. For example, Lake Wollumboola opened in 1994 and 1998 during the transition out of the respective El Niño phases. The same is also evident for Lake Tabourie however due to the number of openings for that ICOLL there is no clear pattern.

Although there are some similarities, overall the six ICOLLs exhibit distinctly different entrance regimes across the same period of time. As the El Niño Southern Oscillation is constant across all sites the difference between these ICOLLs and the response to ENSO must therefore be the result of other variables that are unique to each ICOLL. Although this is a logical conclusion it is important to distinguish that the relationship between the El Niño Southern Oscillation and ICOLL entrance condition is not causal.

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SOI +

Wollumboola O

Swan O

Burrill O

Tabourie O

Durras O

Wallaga O

1/01/1992 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2007 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013 1/01/1993

Figure 22: Entrance condition of ICOLLs and respective phase of the El Niño Southern Oscillation. + = La Niña, - = El Niño, O = open entrance, C = closed entrance.

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4.3.1 Entrance Openings: Natural or Artificial?

The ICOLLs in this study are all managed, and as part of that management artificial opening of the entrance by the relevant authority is routinely carried out. Therefore, not all of the opening events in the entrance record occurred naturally. The records held by the NSW Office of Environment and Heritage, MHL and respective local government provided evidence for the nature of opening events and where possible this information was used to classify the nature of the opening. As these records are incomplete the water level plot was used to infer the nature of openings when the record was not available. The water level plot was analysed for Lake Durras, as there was a record for both a natural and artificial opening (Appendix One). As illustrated in Figure 20, a difference in the water level curve was identified for the natural opening and the artificial opening. When the ICOLL opened naturally the response is abrupt, the spike in water level is immediately followed by a rapid decline in water level. In comparison, the peak in water level is followed by a decline in water level that is not as steep, indicating that it occurred more slowly over a longer period of time. This was applied to other water level curves to determine the nature of opening, as the result is based on observation with no supporting evidence these classifications were italicised to be distinguishable in the record (see Appendix One). Figure 23 illustrates the number of entrance openings and the proportion of those openings that are natural or artificial for each ICOLL.

25 Artificial

20 Natural

0 Wollumboola Swan Burrill Tabourie Durras Wallaga

Figure 23: Proportion of natural and artificial openings for all ICOLLs.

Although the nature of entrance openings was identified, neither were adjusted or treated differently in the analysis. The effect of this will be discussed further in the discussion chapter. Proportionally, artificial openings were more common at all sites with the exception of Lake Durras (which had an equal number of natural and artificial openings).

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4.4 Rainfall, Wave Climate and Storms

Coastal and catchment variables were included to expand the analysis from the broad-scale El Niño Southern Oscillation to a smaller-scale site-specific analysis. The relative influence that these variables (specifically rainfall, wave climate and storms) will have in determining the ICOLL entrance condition is different for each site. The data for each of the parameters was analysed and then compared against the water level to identify trends in entrance condition, broadly linking to the phase of the El Niño Southern Oscillation. The relationship between the wave climate, rainfall and storms to the phase of the El Niño Southern Oscillation is further explored in greater detail using statistical analysis, which will be discussed later in this chapter.

4.4.1 Rainfall

Rainfall data was acquired from the Bureau of Meteorology as a daily and monthly record to be used as a surrogate for catchment processes. Rainfall is only a surrogate value as the true catchment processes include stream-flow and runoff in addition to direct rainfall (Haines 2008). The monthly long-term average rainfall for each station was also acquired from the Bureau of Meteorology. The long-term mean data was graphed as a combined line graph in Excel (Figure 24) and used to infer annual and seasonal trends in the catchment rainfall. Evident in Figure 24, the long-term mean rainfall exhibits a distinctly seasonal trend. February and March receive the highest rainfall, with the lowest rainfall occurring in July and August. These seasonal rainfall trends are consistent with those experienced across most of Australia (BOM 2014). Wallaga Lake, the southernmost ICOLL in this study, receives (on average) the lowest annual rainfall of the study sites.

140

120 Wollumboola Swan 100 Burrill

80 Tabourie Durras 60 Wallaga

40 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Figure 24: Long-term monthly mean rainfall for ICOLL catchments.

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The monthly mean rainfall for each ICOLL was graphed as a bar graph with time consistent on the x-axis to enable comparisons between data series (Figure 25). The recorded monthly rainfall was compared against the equivalent month in the long-term mean series to enable periods in which the recorded rainfall is above or below average to be identified. These periods indicate the potential effect of the ENSO and or the IPO.

Trends in rainfall at each catchment are similar, as evident in Figure 25. This is likely to be due to the close proximity of each of the ICOLLs to one another and therefore exposure to the same weather systems. To undertake initial comparison, the rainfall (Figure 25) and water level (Figure 19) graphs were printed at a large scale and analysed. From this comparative analysis it is evident that when the ICOLL is closed periods of high rainfall correspond to peaks in water level. When the event is large enough the input of rainfall leads to a change in entrance condition. Approximately one third (36%) of entrance opening events (across all sites) occurred following a large influx of rainfall (Table 5). Although the opening events are not being analysed separately based on their nature (natural or artificial) it is important to note that all except one (Lake Tabourie in 2013) of the natural opening events occurred due to a large influx of rainfall.

Table 5: Large rainfall events and corresponding ICOLL opening events ICOLL Date Open ENSO Phase Rainfall (mm) Natural / (E, L, N) Artificial Lake 13/04/1994 E 250 Artificial Wollumboola 18/08/1998 L 176.6 Natural* 23/03/2011 L 168.4 Natural* 27/06/2013 N 187 Artificial Swan Lake 24/06/2013 N 106 Natural Lake Tabourie 13/041994 E 96 Artificial 1/09/1996 N 243 Artificial 8/10/1997 E 113 Artificial 22/10/2004 N 142 Artificial 12/10/2012 L 170 Natural* Lake Durras 6/02/2002 N 149.2 Natural 12/10/2012 N 215 Natural 26/06/2013 N 110.8 Natural Wallaga Lake 28/09/2000 L 103.6 Artificial 11/07/2005 N 108.4 Artificial 12/02/2007 E 94.4 Artificial NB: The rainfall that occurred on the day of opening and 2 days prior to opening were totalled. A large event was anything greater than 90mm in the 3-day period. Openings with an asterisk were inferred from the data and do not have a supporting record.

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600 Wollumboola

400

(mm) 200

400 Swan

300

200 (mm) 100 0

600 Burrill

400

(mm) 200

600 Tabourie

400

(mm) 200

400 Durras

300

200 (mm) 100 0

500 Wallaga 400 300

(mm) 200 100

1/01/1991 1/01/1992 1/01/1993 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2007 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013

Figure 25: Mean monthly rainfall (mm) for each ICOLL catchment over the study period.

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4.4.2 Wave Climate

Wave date was provided by the Manly Hydraulics Laboratory to ascertain the wave climate specific to the south coast and the ICOLLs. Data from the Batemans Bay buoy was used as the buoy is in a central location to the ICOLLs (Figure 26). The wave parameters obtained from MHL used in the analysis are the maximum wave height (Hmax), wave power and wave direction. The raw data was processed in Excel to obtain daily and monthly mean values. A line graph for both the daily and monthly series of wave height and wave power against time was produced. At large scale, the daily average plot was used to identify peaks in wave conditions and compare against the already ascertained rainfall and water level graphs to identify cross correlations. Periods where increased wave activity was sustained are evident as peaks in the monthly average (Figure’s 27 and 28) such as the month of June 2007, represented by the largest peak in both graphs.

Legend: (a) Wollumboola (b) Swan (c) Burrill (d) Tabourie (e) Durras (f) Wallaga (g) Batemans Bay Waverider buoy

Figure 26: MHL Batemans Bay Waverider Buoy (G) location in respect to study ICOLLs (Google Earth).

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40000 35000 30000 25000 20000

(kW/m) 15000 10000 5000

1/01/1993 1/01/1994 1/01/1995 1/01/1996 1/01/1997 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2002 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2007 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013 1/01/1992 Figure 27: Mean monthly wave power recorded at Batemans Bay (1992-2013).

4.5 4 3.5 3 2.5

(m) 2 1.5 1 0.5

1/01/1992 1/01/1997 1/01/2002 1/01/2007 1/01/1994 1/01/1995 1/01/1996 1/01/1998 1/01/1999 1/01/2000 1/01/2001 1/01/2003 1/01/2004 1/01/2005 1/01/2006 1/01/2008 1/01/2009 1/01/2010 1/01/2011 1/01/2012 1/01/2013 1/01/1993 Figure 28: Mean monthly maximum wave height recorded at Batemans Bay (1992-2013).

The mean wave direction for each season was calculated from the Batemans Bay data (Table 6). The results show that waves originate from a more easterly direction during summer, indicative of the tropical cyclone component, while for the rest of the year they are consistently from the southeast. This is similar to the seasonal trends identified by Short and Trenaman (1992) for Sydney, however overall the direction is more southerly.

Table 6: Mean seasonal wave direction for Batemans Bay (1992 – 2013). Season Direction (Degrees) Direction (Cardinal) Summer: DJF 117.87 ESE Autumn: MAM 126.11 SE Winter: JJA 130.89 SE Spring: SON 126.33 SE NB: Directional data missing from record for years 1997 – 2000

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The effect that the wave climate has on ICOLL entrances is more difficult to determine using the visual comparison method than that of rainfall (in which peaks correspond directly to increased water level or opening events). Some of the water level variability, particularly for mostly open entrances such as Burrill Lake corresponds with peaks in the wave climate, however as both records are highly variable the association is not particularly clear. The comparison however illustrates that rather than opening the ICOLL the effect of waves is largely to close the ICOLL. A number of peaks in the wave power record correspond to the closure of entrances, which occurs in a relatively short span of time for the study sites, with most ICOLLs open for less than 12 months (see Appendix One). For example, in 1995, Lake Tabourie was open for less than 1 month and a peak in the wave power corresponds to the closure that occurred on the 20th of June (1995) (see Figure 27). When peaks are apparent in both wave power and the maximum wave height this is indicative of a storm event. This is especially the case when a corresponding peak in rainfall is also observed, providing an initial point of reference for identifying the effect of storm events.

4.4.3 Storms

The Manly Hydraulics Laboratory publishes a storm record that is based on the analysis of wave data for each of their Waverider buoys (MHL, 2012). The record details the duration of each event, the peak and mean wave height and wave power, and the incident direction. For Batemans Bay this record is available from 1986 – 2011. The storm data of relevance to this study (from 1992 – 2011) was extracted and a storm record for the study was created (Appendix Two). These periods were plotted in Excel as a column graph (Figure 29).

14 12 10

(m) 6 4 2

8/06/2007 5/01/1991 8/06/1991 6/09/1995 7/04/1997 8/10/2006 7/02/2008 5/05/2011

23/09/2011 20/10/1992 13/06/1993 13/04/1994 18/10/1994 14/07/1996 24/03/1998 17/08/1998 21/04/1999 29/12/1999 14/07/2000 11/04/2001 19/10/2001 11/02/2002 25/12/2002 30/07/2003 14/05/2004 29/12/2004 13/09/2005 16/08/2008 18/02/2009 14/02/2010 15/10/2010 10/02/1992 Figure 29: Peak wave height for storm events from Batemans Bay (1991 – 2011).

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A number of ICOLL openings correspond to storm events. While there is rainfall associated with the majority of these storms, the opening events that correspond with storms are not always those that correspond with peak rainfall (Table 5). The storms and entrance openings are detailed in Table 7; the total volume of rainfall is also included to illustrate the storms that occurred with and without rainfall.

Table 7: Storms and ICOLL opening events ICOLL Storm Start Storm ENSO Peak Peak Direction Rainfall Date Finish Date Phase Hmax Power (mm) (E, L, N) (m) (kW/m) Lake 13/04/1994 14/04/1994 E 6.0 43.9 SSE 250* Wollumboola 08/08/1998 09/09/1998 L 7.7 125.4 SSE 176.6* 21/03/2011 23/03/2011 L 7.2 66.5 ESE 168.4* Swan Lake 14/04/2002 14/04/2002 E 4.9 36.9 SSE 30 14/06/2007 16/06/2007 E 7.9 70.9 ESE 0 18/08/2011 20/08/2011 L 6.7 71.3 ESE 11.6 Burrill Lake 23/06/2005 24/06/2005 N 9.8 145.8 SSE 57.8 Lake Tabourie 13/04/1994 14/04/1994 E 6.0 43.9 SSE 96* 31/08/1996 02/09/1996 N 12.4 300.4 E 243* 04/03/1997 05/03/1997 E 5.5 54.9 SE 56 22/08/2001 23/08/2001 L 6.3 65.7 S 0 19/07/2011 24/07/2011 L 10.7 191.3 ESE 58 Lake Wallaga 28/09/1995 28/09/1995 E 4.8 34.9 SE 1.6 10/07/2005 11/07/2005 N 9.1 169.9 ESE 108.4* 12/02/2007 12/02/2007 E 5.5 43.4 ESE 94.4* NB: Rainfall with an asterisk indicates a peak rainfall event

Additionally, the number of entrance closures that coincide with storm events was ascertained through comparison of the ICOLL entrance condition and storm records. Approximately one third (33%) of the entrance closures occurred on or within three days of a storm event (Table 8). This suggests that the increased wave action associated with the storms drives sediment into the entrance, and without significant outflow from the ICOLL to combat this process the entrance becomes choked with sediment and closed off to the ocean.

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Table 8: Storms and ICOLL closure events ICOLL Storm Start Storm Finish Closure Date ENSO Phase Direction Date Date (E, L, N) Lake 12/02/2007 12/02/2007 12/02/2007 E ESE Wollumboola Swan Lake 27/06/2007 29/06/2007 29/06/2007 E SSE 12/09/2007 12/09/2007 12/09/2011 L SSE Burrill Lake 6/09/2008 07/09/2008 6/09/2008 L E Lake Tabourie 9/08/1994 10/08/1994 12/08/1994 E S 17/06/1995 19/06/1995 19/06/1995 E S 10/11/1999 12/11/1999 13/11/1999 L SSE 31/12/2004 31/12/2004 31/12/2004 N SE 20/10/2006 21/10/2006 20/10/2006 E S 18/08/2011 20/08/2011 23/08/2011 L SSE Lake Durras 07/09/2003 08/09/2003 10/09/2003 N SSE 09/04/2006 10/04/2006 10/04/2006 N SE 16/08/2008 17/08/2008 18/08/2008 L SSE Lake Wallaga 08/10/2002 09/10/2002 8/10/2002 E SSE

The direction of storm events further influences the effect that the storm waves will have on the ICOLL entrance. Ranasinghe et al. (2004) state that on a north-south aligned coast, waves arriving from the north or northeast contribute to erosion in the northern end of the beach, transporting eroded sediment to the southern end of the embayment. Conversely, waves arriving from the south or southeast erode sediment from the southern end, transporting sediment to the northern end of the beach. Lake Wollumboola is the only ICOLL out of the study sites that is aligned north-south, and as the entrance is located on the northern end of the coast according to the theory waves from the north would erode sediment from the entrance, while waves from the south would deposit sediment around the entrance (Haines and Thom 2007). However, entrance openings at Lake Wollumboola have been shown to coincide with storms from the southeast (Table 7) although these storms are also associated with significant rainfall events, which can outweigh the influence of storm waves and give rise to entrance openings (Ranasinghe and Pattiaratchi 2003). The remaining ICOLLs are oriented towards the southeast and are therefore more exposed to storm waves arriving from that direction (SCC 2012). These storms, both with and without associated rainfall, contribute to both entrance openings and entrance closures for the study ICOLLs. As entrance closures occur only naturally (entrances are not artificially closed as part of ICOLL management) the direction of storm waves associated to closure events was further analysed, with results listed in Table 8. Storms arriving from the southeast contributed to entrance closures at all of the ICOLLs, with the exception of Burrill Lake, which is protected on the southern side by a

59 S Perry (2014) headland (Figure 14). The closure at Burrill Lake occurred in 2008 following a storm with waves arriving from an easterly direction, to which the entrance is exposed. The entrance closure associated with a storm that occurred at Lake Wollumboola is consistent with the theory, with the storm arriving from an east-southeast direction, contributing to sediment transport into the entrance. The relationship between wave direction and the El Niño Southern Oscillation has also been previously established (see for example Phinn and Hastings 1992). The storm record for Batemans Bay (Appendix Two) shows that the majority of storms arrive from the east or southeast, with very few incidences of storms from the northeast (indicative of tropical cyclone systems). Tables 7 and 8 also show that all of the storm systems that result in changed entrance conditions are of east or southeast origin, irrespective of the El Niño Southern Oscillation condition. Due to limited time, no further analysis into the effects of ENSO on direction were conducted.

4.5 Statistical Analysis

Exploring the data through visual inspection identified a number of relationships between the ICOLL entrance condition, coastal and catchment processes and the El Niño Southern Oscillation. Statistical modelling was undertaken to determine if these relationships are significant. Each of the parameters (rainfall, wave height, ICOLL entrance condition and the SOI) was treated as a separate variable in the statistical analysis, which consisted of two types of tests. First, correlations between the variables were identified in bivariate regression analyses. This type of regression describes the dependence of one variable on another. As both the wave climate and the catchment input give rise to the entrance condition a second test, an analysis of variance (ANOVA), was run. An ANOVA describes the dependence between multiple interacting variables. To indicate whether the tests were significant (if there is dependence between the variables) the p-values of each test are provided. If the p-value of a test is less than the stated significance level (for example p < 0.05) then that test is statistically significant.

To run the analyses the data was classified and imported into the statistical analysis program JMP. Although the initial analysis was based on the raw and averaged data (either daily, monthly or yearly), to perform the statistical analysis the data was classified into specific El Niño or La Niña years. The empirical method used by Chiew et al. (1998) was adapted to identify and classify the El Niño years. In this method an El Niño year is defined when the

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12-month (April to March) mean SOI is below -5. The same parameter was used to classify La Niña years, when the 12-month (April to March) mean SOI is greater than 5, however this was not defined by Chiew et al. (1998, p.140). The 12-month (April to March) mean SOI was calculated in Excel. Conditional formatting was used to identify the years that fit the condition. These years were then classified as being El Niño or La Niña years. As the SOI parameter in the statistical analysis was a 12-month average the same formatting was applied to the other variables to maintain consistency. Coastal and catchment processes were each represented by one variable: for coastal processes only maximum wave height was used in the analysis and as the only surrogate for catchment processes, the rainfall was used. ICOLLs were represented by two variables that were tested separately. A 12-month mean for the water level as well as a 12-month mean for the binary entrance condition, ‘open’ or ‘closed’, was identified. For the entrance condition this mean was based on the numerical values that were assigned. A year that had a mean entrance condition closer to 2 was more open, while a year that had a mean entrance condition closer to 1 was more closed. The correlation between rainfall, wave height and SOI were run for each of the entrance condition variables to test if there was any difference between the water level indicators (that is more variable) or the observed condition of the entrance. Table 9 provides the results of the tests.

Table 9: Regression analysis for all test variables against the SOI Test Wollumboola Swan Burrill Tabourie Durras Wallaga Entrance DF 20 12 20 19 11 11 Condition P-value 0.6661 0.8152 0.4142 0.3708 0.9658 0.6445 Water DF 20 12 20 19 11 12 level P-value 0.4449 0.7863 0.2154 0.0348 0.1453 0.3602 Rainfall DF 20 12 20 19 10 12 P-value 0.0367 0.2298 0.0132 0.0026 0.1967 0.3029 Wave DF 20 12 20 19 11 12 height P-value 0.0414 0.2098 0.0414 0.0354 0.0994 0.3216 NB: Significance values P < 0.05 are shown in bold and P < 0.10 in italics

The results indicate that there is a significant correlation between the ICOLL water level and the SOI for Lake Tabourie (P = 0.0348). At all other ICOLLs the relationship between the entrance and the El Niño Southern Oscillation is not significant. Correlation is apparent between the El Niño Southern Oscillation and the coastal and catchment variables: rainfall and wave height are correlated to the SOI for Lake Wollumboola (P = 0.0367, P = 0.0414), Burrill Lake (P = 0.0132, P = 0.0414) and Lake Tabourie (P = 0.0026, P = 0.0354 respectively). The wave height is also significantly correlated to the SOI for Lake Durras (P =

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0.0994). As the wave height data for each ICOLL is the same series (sourced only from the Batemans Bay buoy) the difference in correlation at each ICOLL is relative to the time period analysed, for example, as both Lake Wollumboola and Burrill Lake cover the same 20 year period the correlation between the SOI and the wave height is the same (P = 0.0414). Correlation at Lake Durras suggests that for that 11 year period there is a greater relationship between the wave height and SOI than the 12 year periods for Swan Lake and Lake Wallaga. The correlations between wave height, rainfall and the SOI are positive: as the SOI increases so too do the volume of rainfall and the height of waves. The regression plot for the rainfall and SOI test for Lake Tabourie illustrates this (Figure 30).

Figure 30: Yearly mean rainfall (Lake Tabourie) v yearly mean SOI regression plot with linear fit (P = 0.0026).

As the wave climate and rainfall have been shown to largely influence the ICOLL entrance condition, if there is a significant relationship between the ICOLL entrance condition and the forcing variables then by extension, where the rainfall and wave parameters are correlated to the SOI, so too is the ICOLL entrance condition. This was tested through additional bivariate regression analyses for the wave height and rainfall against water level and entrance condition. The results of the analyses are provided in Tables 10 and 11 respectively.

Table 10: Regression analysis for the controlling variables against ICOLL water level Test Wollumboola Swan Burrill Tabourie Durras Wallaga Rainfall DF 20 12 20 19 11 12 P-value 0.4732 0.491 0.1834 0.149 0.5772 0.4951 Wave DF 20 12 20 19 11 12 height P-value 0.092 0.9635 0.5064 0.7641 0.4859 0.5846 NB: Significance values P < 0.05 are shown in bold and P < 0.10 in italics

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Table 11: Regression analysis for the controlling variables against ICOLL entrance condition Test Wollumboola Swan Burrill Tabourie Durras Wallaga Rainfall DF 20 12 20 19 11 11 P-value 0.0542 0.9505 0.8331 0.6112 0.6047 0.2222 Wave DF 20 12 20 19 11 11 height P-value 0.1845 0.4598 0.6590 0.8955 0.7353 0.0651 NB: Significance values P < 0.05 are shown in bold and P < 0.10 in italics

The wave height is significantly correlated to the water level only at Lake Wollumboola (P = 0.092). Rainfall was not found to be significant in explaining the water level at any ICOLL. Rainfall was significant for Lake Wollumboola however when tested against the entrance condition (P = 0.542). The wave height was significant for Lake Wallaga when tested against the entrance condition (P = 0.0651) whereas the wave height was not significantly correlated to the SOI for Lake Wallaga.

To further test for association an ANOVA was run. Separate ANOVAs were run for the entrance condition and the water level to determine the relative influence that the wave climate and catchment have in influencing the entrance regime. Rainfall and wave height were tested as individual variables and as a cross (rainfall x wave height) to test for any significance in the association, which was not achieved through the bivariate regression models. The results of each test are given in Tables 12 and 13.

Table 12: ANOVA testing controlling variables against the ICOLL water level Wollumboola Swan Burrill Tabourie Durras Wallaga Variables DF 20 12 20 19 10 12 Model P-value 0.2094 0.7866 0.6116 0.1686 0.9173 0.9095 Rf P-value 0.9954 0.4298 0.3101 0.1939 0.6861 0.8599

Hmax P-value 0.1522 0.9301 0.8011 0.2978 0.6509 0.7444 Rf x Hmax P-value 0.1944 0.4651 0.7647 0.1214 0.8914 0.8290 NB: Significance values P < 0.05 are shown in bold and P < 0.10 in italics

Table 13: ANOVA testing controlling variables against the ICOLL entrance condition Wollumboola Swan Burrill Tabourie Durras Wallaga Variables DF 20 12 20 19 10 12 Model P-value 0.1624 0.2087 0.8619 0.8666 0.9041 0.3147 Rf P-value 0.1590 0.4443 0.9054 0.4380 0.7428 0.8144

Hmax P-value 0.4300 0.5464 0.6353 0.6350 0.8667 0.2549 Rf x Hmax P-value 0.3620 0.0594 0.4698 0.6777 0.6604 0.6953 NB: Significance values P < 0.05 are shown in bold and P < 0.10 in italics

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The results illustrate that the combination of rainfall and wave height (rainfall x wave height) is significant in determining the entrance condition for Swan Lake (P < 0.10). The models are not significant at any other site indicating that rainfall, wave height, or the combination of the two do not have a significant effect in determining the water level of the ICOLL, nor whether the entrance is open or closed.

As storms consist of both increased wave action and rainfall (in some cases), a specific storm analysis was not included in the statistical tests due to the added complexity of separating and classifying the storm variables. Instead only the separate tests of wave action and rainfall were run. In order to identify if there is a relationship between storms and the El Niño Southern Oscillation, the frequency of storm events for each phase (from 1992 – 2011) was calculated using the MHL storm record. The ratio of storm events that occur during a La Niña phase compared to the El Niño phase is 1:1.7 and therefore a storm is more likely to occur during a La Niña year, as has been previously identified (You and Lord 2008). This further suggests why the wave height and rainfall is positively correlated to the El Niño Southern Oscillation; storms and associated increases in wave height and rainfall are more apparent with a more positive SOI.

4.6 Summary of Results

 The ICOLLs have very different and highly variable entrance regimes for the study period. Trends within, and between, the different sites and their entrance condition for the recurring phases of the El Niño Southern Oscillation are inconsistent over the period studied, with only one example in which the similar entrance conditions could be possibly related to the ENSO phase (see below).  Closed entrance conditions coinciding with the El Niño in 2006-2007 and 2009-2010 were evident at all of the study ICOLLs (to varied extents) illustrating the possible influence of the El Niño Southern Oscillation by way of drought. Furthermore, this could also be indicative of the modulating influence of the Interdecadal Pacific Oscillation on the El Niño Southern Oscillation, as the IPO was in negative phase during this time where it was positive for previous El Niño events where the corresponding closures were not observed.  Rainfall, when occurring in large volumes over a short period of time, can lead to entrance openings, explaining all but one of the natural entrance openings for the

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study period. Rainfall is significantly correlated to the El Niño Southern Oscillation for half of the ICOLL catchments, illustrating by extension the influence of ENSO on the entrance condition. Although there was no statistical correlation, the natural entrance openings that occurred due to rainfall coincided with either a La Niña or neutral phase in the El Niño Southern Oscillation, but not with an El Niño.  Waves, including storm events, are associated to both entrance openings and entrance closures. Storms on the south coast for the study period were found to be approximately twice as frequent in the La Niña phase than the El Niño phase; the positive correlation between the SOI and wave height supports this. The orientation of the ICOLL to the storm event influences the exposure, with all of the storms of significance to the ICOLLs originating from the east or southeast.  Although there are apparent relationships between the phase of the El Niño Southern Oscillation and the entrance regime, through the relationship between the coastal and catchment variables, the results of the statistical analysis showed that any apparent correlation to the ICOLLs is not significant. The combined ANOVA models showed that overall there is no significant correlation between the ICOLL entrance condition and the El Niño Southern Oscillation.

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Chapter 5: Discussion

It was hypothesised that the reduced rainfall associated with an El Niño phase would result in more closed entrance conditions observed at ICOLLs on the south coast, while during La Niña the increased rainfall and prevalence of storms would lead to more open entrance conditions. The results of the analysis show that this relationship is apparent under very few circumstances, with no recurring trends, and overall is statistically insignificant. This suggests that the entrance condition of the different ICOLLs is dependent on site-specific parameters rather than regional climate drivers such as the broad scale El Niño Southern Oscillation. These site-specific parameters include the ICOLLs morphology as well as the hydraulic properties of the lake and the entrance channel (SCC 2004; Haines et al. 2006). These factors result in the individual behaviour of each ICOLL in response to a rainfall or storm event, and give to rise to the overall highly variable entrance regimes.

The analysis, aimed at identifying relationships between the forcing catchment and coastal variables, showed that opening events do correspond to heavy rainfall increasing catchment input and inundation via storm waves. Entrance closures were also shown to be influenced by increased wave activity following storm events. That the ICOLLs respond to these variables in this way is consistent with previous findings (see for example Ranasinghe and Pattaratchi 2003; Haines 2006; Weir et al. 2006). The catchment and coastal variables were also shown to be influenced by the El Niño Southern Oscillation through significant correlation with the SOI (for some of the study sites). This result is also consistent with previous studies that identified correlations between ENSO and teleconnections (see for example Allan 1988; Phinn and Hastings 1992; Cai et al. 2011). By extension, this suggests that the ICOLL entrance regime is correlated to the El Niño Southern Oscillation; however the statistical tests that were performed to quantify this link did not show significant results. This indicates that the coastal and catchment variables do not exert a significant control on determining the ICOLLs entrance regime. As there have been no previous studies performed to quantify this relationship there is no solid ground to state whether this result is consistent, or if limitations with the methodology or data have masked any apparent correlation. There are a number of limitations associated to the methodology and data that may have influenced the study outcomes.

The relatively short time period that was analysed in this study presents one limitation. The length of the study period is especially important considering the aim of the project was to

66 S Perry (2014) identify correlation of coastal system behaviour with response to broad scale climatic features. Analyses in the literature concerning ENSO teleconnections are based on significantly longer time periods in which more ENSO phases have occurred in order to identify the presence of long-term patterns. For example, Verdon and Wyatt (2004) identified trends in rainfall and stream flow in Victoria in relation to ENSO using records that span 75 years from 1924 – 1998, similarly, Cai and Cowan (2008) constructed monthly and seasonal rainfall anomalies over the 57 year period 1950 – 2006 to illustrate the modulating effect of ENSO.

The longest records for the study span only 2 decades, with the record for two of the ICOLLs (Swan Lake and Lake Durras) even shorter, covering just over 1 decade. Incidentally, where correlation between the wave height and rainfall with the SOI was statistically significant the period of time was longer (Lake Wollumboola, Burrill Lake and Lake Tabourie gave significant results each test having degrees of freedom 20, 20 and 19 respectively). Correlation between the variables for the other sites may be improved if the time period for the analyses were longer, enabling the identification of long-term trends while reducing the effect of short-term discrepancies that may be inconsistent in the long-term. Water level data for each of the sites limited the period of time that the ICOLL entrance regime could be studied as the water level profiles formed the basis for reconstructing a record of the entrance regime. This data is limited due to the relatively recent implementation of monitoring devices in estuaries by the Manly Hydraulics Laboratory.

In order to overcome this limitation a different source of information on past entrance condition needs to be identified. For example, a historic log of the entrance condition of Burrill Lake is included in the Burrill Lake EMP (Spurway et al. 2008) (Table 14), a similar record is also available in the Swan Lake EMP (SCC 2004). If additional sources were available detailing similar historic occurrences for other sites then this information could be used to piece together a longer entrance record. A dataset, such as the binary entrance condition data produced for the statistical analysis, could then be constructed based on this data. However, without supplementary observational data or appropriate references, this type of record would introduce issues of accuracy. Power et al. (1999) utilise linear statistical schemes to hindcast rainfall data for Australia for the period 1900 – 1997; although not practical for use in this project, this example illustrates other methodologies that have been developed to overcome limitations with data availability. Remotely sensed data has also been used with success in a number of studies to determine estuarine parameters including water quality (by measuring the concentrations of algal blooms), coastline movement, migration of

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Table 14: Historic record of Burrill Lake entrance condition from Burrill Lake EMP (Spurway et al. 2008)

Closure Date Comments on closure and Source of Data Authority of Data reopening 1902 Manual opening McAndrew (1993) Note in Milton and Ulladulla Times 26/07/1902 1908 Lake apparently closed for long McAndrew (1993) Historical photograph period 1914 Entrance being opened by horse McAndrew (1993) Historical photograph and scoop January 1914 1930 Unknown. Reputedly remained Smith (1987) p.100 N Hooper, personal opened for 40 years communication 1942 Major flood. Entrance manually McAndrew (1993) p.79 Recollection of Stan opened. Prior to opening, Rattey inundation extended as far as the community hall 1944-1986 No closure observed in aerial SCC, Public Works, DLWC aerial photos photos, though entrance heavily Patterson Britton and shoaled Partners (1992) 1957 or 58 Closed for approximately 1 week. Peter Williams Personal communication Manually opened by residents across sand dune 1965-1970 South Coast inlets reported to be Bentley (1976) quoted often closed in this period in Smith (1987) 1968 Entrance being opened by McAndrew (1993) Photograph manpower and shovels 1970 Closed sporadically for most of Smith (1987) identifies Unnamed local resident 1970. Inlet naturally opened and this closure as the most closed 3 times before staying recent closure prior to open 1987 1971 Spit breached by big swells J Downey, personal communication 1974-1977 Breaching of entrance spit by DLWC aerial photos 1974 storms Mar-1987 Closed for 4 months before Smith (1987). Patterson Smith, personal apparent natural opening Brittion (1992) suggest observation lake was manually opened 31 Jan 2005 Closed for 5 months following SCC MHL Water Level coastal storm. Manual opening by Records SCC on 25 June 2005 at 1.15m AHD 5 Aug 2006 Lake was open for 3 months, Community observation closure following accretion of beach berm after heavy NE to E swells and lack of ebb channel conveyance 28 Mar 2007 Manual opening by SCC at 0.99m SCC MHL Water Level AHD Records May / Jun Gradual closure followed by SCC SCC survey 2007 manual opening on 17 June at 1.38m AHD after heavy rainfall

68 S Perry (2014) shoals and location of deepwater channels (see for example Brando and Dekker 2003; Chen et al. 2005). These spatial techniques could be extended to tracing the entrance berm and shoals to determine changes over time in order to reconstruct a record of entrance condition. For this to be appropriate the resolution and temporal reoccurrence of the spatial data capture needs to be adequate to accurately capture changes in ICOLL entrances.

An additional limitation within the datasets is the use of rainfall data as a surrogate for catchment processes. Rainfall does not fully account for the complete inflow; instead catchment inflow is the accumulation of direct rainfall, volumetric runoff and groundwater inflows (Haines 2006). Using a measure of volumetric runoff takes into account the effect of different land covers within the catchment and the variability in rainfall losses (through infiltration and evapotranspiration) that results (Haines 2006; Spurway et al. 2008). Furthermore, the gauges that were used to represent the inflow for each ICOLL were some distance from the ICOLL itself and may not be fully representative of the rainfall within the catchment. Spurway et al. (2008) identify this issue for Burrill Lake, stating that the trends in Ulladulla rainfall (the BOM gauge nearest to the lake) and the water level response at Burrill Lake have marked variation as the rainfall at Ulladulla is not always representative of the rainfall in the whole Burrill catchment. The rainfall data itself also has reliability issues as large portions of the data were not quality controlled, this and other instrumental concerns have been highlighted in the literature (see Carvalho and Woodroffe unpublished). The implications of these factors for the analysis is that the correlation between the rainfall and ICOLL datasets may not be adequate in representing the effect that catchment inflow has in influencing the entrance condition.

The variability of rainfall (and other teleconnections) associated with the El Niño Southern Oscillation is influenced by more than just modulation with the IPO. Previous studies have shown that the effect of ENSO on rainfall is dependent on geographic region, season, and other climatological parameters including the Southern Annular Mode and atmospheric blocking (Risbey et al. 2009; Verdon-Kidd and Kiem 2009; Carvalho and Woodroffe unpublished). Furthermore, variations within the ENSO itself including ENSO-Modoki anomalies (in which two rather than one Walker circulation cells are apparent in the upper atmosphere, which occurred during the 2002-2003 El Niño) can affect the variability of rainfall (Ashok et al. 2007 in Cai et al. 2010). The outcomes of this study are therefore

69 S Perry (2014) influenced by simplification. Although necessary for the limited time frame in which the study was conducted, the scope of the analysis was restricted by only comparing the influence of the El Niño Southern Oscillation and to a small extent modulation by the Interdecadal Pacific Oscillation. The combined influence that the other climatic parameters would have had on rainfall during the study period may have had an effect in reducing correlation to ENSO.

The effect that the El Niño Southern Oscillation has on influencing teleconnections is not always immediately apparent; there can be a lag between when increased or decreased rainfall (for example) associated with the El Niño Southern Oscillation phase is observed (Allan 1988). McBride and Nicholls (1983) evaluated the relationship between seasonal rainfall and the SOI using both simultaneous and lagged correlation methods, finding that rainfall is lagged dependent on area and season. Various lag times have been adopted in numerous studies since, for example, in their study into beach rotation Ranasinghe et al. (2004) found that a lag time of up to 1.5 years was apparent before changes in the southern end of beaches were observed. This was varied, as changes to the northern end of the study beaches were lagged only 3 months. As previous studies show, the influence of the El Niño Southern Oscillation on rainfall and physical processes can be both simultaneous and lagged. The analysis in this project, both through the initial identification of relationships and through statistical methods, did not incorporate any lags when analysing the correlations. Adapting the study method to include lagged analysis would provide greater detail to the results, identifying seasonal and time-dependent relationships in the rainfall, wave climate, and overall ICOLL entrance response. Lagged correlations can be identified using statistical techniques associated to time-series analysis, which, due to the complexity of the data processing and analysis involved, were not suited to the timeframe of this project.

The influence that storms have on changing entrance condition of the ICOLLs provides one possible reason as to why there was not a significant correlation between the entrance regime and the El Niño Southern Oscillation. ENSO is a continuous climatic phenomenon; even though the occurrence and length of El Niño and La Niña phases are highly variable, the atmospheric pressure and oceanic temperature gradients are continually influencing regional weather patterns to some extent (Allan 1988; BOM 2012). The typical dry-weather entrance condition of the ICOLL represents the consistent balance between stream-flow, catchment outflow and the wave conditions (Roy et al. 2001); however changes in the entrance

70 S Perry (2014) condition are influenced by rainfall and storm events that are periodic in nature. Although storm events (in terms of frequency and severity) have been shown to correlate to the phase of the El Niño Southern Oscillation (You and Lord 2008) they can occur year round at any time, dependent on local weather conditions. Analysis of the MHL storm record illustrated that there was an increased frequency of storm events in La Niña years when compared to El Niño years, however out of the total number of storms that resulted in entrance openings, more occurred during El Niño years than La Niña years. Although rainfall overall may be reflective of the trends associated with the El Niño Southern Oscillation (as the correlation between rainfall and the SOI indicates) the correlation between the rainfall and the ICOLL entrance may be reduced due to the presence periodic storm events.

A fundamental issue in the reliability of the methodology and results is that the ICOLLs included in the study are all subject to artificial entrance openings. This is because the entrance openings were not separated or classified in the statistical analyses to differentiate the nature of the opening event, i.e. whether it was natural or artificial. The reason for this was twofold; first, because the entrances are opened when water levels are high to mitigate flood and this would usually indicate that a natural entrance opening would transpire relatively soon if the intervention did not occur (following one more episode of rainfall for example), and second, because of the high proportion of artificial entrance openings for the ICOLLs in the time period, adjusting the data to account for these artificial entrance openings adds a level of complexity to the analysis that there was not adequate time to address. Treating the entrance openings the same lowers the threshold values for opening events. For example, because it is artificially opened, the volume of rainfall that occurred in the lead up to the opening is not as large as would be required to open the entrance naturally. This is especially apparent when the artificial opening was conducted illegally by members of the community as the threshold values for water level put in effect by EMPs would not have been met, potentially creating an anomalous set of conditions associated to opening in the dataset.

This effects the statistical models as the wave height (Hmax) and rainfall values associated to changes in entrance condition for artificial openings are not representative of the true values associated with natural changes in entrance condition. Furthermore, in testing the opening event against the SOI the artificial event may have occurred sooner than a natural event would have, altering the association of opening events with ENSO phases. That all of the natural openings for the study period occurred during a La Niña or neutral phase further supports this notion that artificial openings alters the associations within the datasets. Two

71 S Perry (2014) additional ICOLLs were proposed for inclusion in the study (Lake Nadgee and Meroo Lake) as these sites are not artificially managed; however, as previously stated the lack of data for these ICOLLs made them unsuitable for inclusion in this study using the methods that have been applied. If these, or other unmanaged sites were able to be included in the study (for example, utilising satellite imagery to map entrance condition or observational records on entrance condition where available) then the natural threshold values could be identified, providing a more accurate account of the relationship between entrance regime and the El Niño Southern Oscillation.

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Chapter 6: Recommendations and Conclusion

The following recommendations are provided as suggestions to overcome the limitations discussed above and to further improve upon the study design. It is recommended that future studies aim to:  Increase the time-period over which the correlations are identified. This increases the reliability of trends identified in the analysis if they are identified in the long-term. If possible, additional sources detailing the historic entrance condition (such as those of the historic condition of Burrill Lake) not only increases the study period but additionally removes the reliance on short-term water level data. Where possible, the acquisition of spatial data and subsequent analytical techniques would also be of benefit to the study design. Spatial data analysis would also enable the inclusion of ICOLLs that are in a natural or more natural state (such as Lake Nadgee) as the site selection is not limited to locations where MHL data capture is present (although there are additional limitations with spatial data such as capture frequency and resolution, as discussed above). If proven to be appropriate, spatial data could both broaden the sites included in the study as well expand the time-period over which the analysis is conducted.  Improve on the statistical design of the analysis, as this would increase the power of the analysis and may improve correlations identified between parameters. The inclusion of lagged correlations and more sophisticated time series data processing and analysis to identify trends in long-term seasonal and annual response would also be of benefit to the overall analysis.  Adjust the design so that the nature of the entrance opening (whether it is a natural, artificial or illegal event) is classified and accounted for in the statistical tests. This would identify threshold values specific to natural entrance openings and further identify their correlation to the SOI and therefore the El Niño Southern Oscillation.

This study has illustrated the complexity of the interrelationship between the catchment and coastal variables and their influence on ICOLL entrance regimes. The results of this study show that there was overall poor correlation between the ICOLL entrance condition and the El Niño Southern Oscillation, suggesting that even though the wave climate and rainfall are teleconnections of ENSO, entrance openings will occur periodically, irrespective of the phase of the El Niño Southern Oscillation. In regards to the management of ICOLLs this presents a

73 S Perry (2014) number of issues to be addressed. For example, the periodic nature of storm and large rainfall events means that artificial management of ICOLLs to mitigate flood risks to property is likely to occur during both El Niño and La Niña phases. When the trigger height is reached in otherwise dry conditions (such as during a strong El Niño), artificially opening the entrance to mitigate elevated water levels could lead to prolonged periods of time where the water level is low. In dry conditions, evaporative losses can be greater than catchment input posing a number of risks to the ICOLL including hypersalinity and an insufficient depth of water to support aquatic communities (Haines 2006). These issues need to be managed appropriately.

The entrance management of ICOLLs has been regarded as one of the most complex management tasks (Thom 2004) especially considering that ICOLLs are also recognised as one of the most vulnerable coastal environments (Haines and Thom 2007). The Healthy Rivers Commission (2002) stated that sustainable management of coastal lake environments requires the lake and the surrounding catchment to be managed holistically, a sentiment that has been echoed in numerous other studies (see for example Thom 2004; Haines 2006). Management plans must therefore be strategic, reflecting the natural variability and enabling or where possible emulating natural entrance processes to reduce the risk of further degradation (HRC 2002).

In light of future climate change and the predictions that the modulating influence of the El Niño Southern Oscillation on rainfall and storms across Australasia is set to increase, such as the increased prevalence of drought and extreme weather, the influence that the El Niño Southern Oscillation has on the ICOLLs (through the forcing variables) may well also increase. However, other elements associated with climate change such as sea level rise and the subsequent alteration of coastal processes may well mask these increased effects, as well as contributing further considerations for ongoing ICOLL management (Hanslow et al. 2000; Stephens and Murtagh 2012).

ICOLLs, in all their complexity, remain an area for future study. There is large potential to build on this study design, including adapting it to other ICOLLs of interest, as illustrated by the recommendations. Increasing the understanding of how coastal environments respond to changes in site-specific and regional drivers improves the capacity for managers to design and implement sustainable management plans.

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Appendix One

ICOLL Entrance Regime Record (1991 – 2013)

ICOLL Date Open Max ENSO Natural/ Period Open Date ENSO Period (Max) Height (m) Artificial Closed Closed Wollumboola 13/04/1994 2.197 El Nino Artificial 3 months 9/07/1994 El Nino 4 years, 4 months Wollumboola 8/08/1998 2.595 La Nina Natural* 6 months 20/02/1999 La Nina 7 years, 5 months Wollumboola 28/07/2006 2.458 El Nino Artificial* 7 months 12/02/2007 El Nino 4 years, 1 month Wollumboola 23/03/2011 2.208 La Nina Natural* 5 months 12/08/2011 La Nina 1 year, 10 months Wollumboola 27/06/2013 2.464 Neutral Artificial 3 months 2/09/2013 Neutral (Illegal) Swan 14/04/2002 2.023 El Nino Artificial 1 month 7/05/2002 El Nino 5 years, 1 month Swan 16/06/2007 2.131 El Nino Artificial* <1 month 29/06/2007 El Nino 4 years, 1 month Swan 18/08/2011 1.869 La Nina Artificial* 1 month 12/09/2011 La Nina 1 year, 9 months Swan 24/06/2013 2.084 Neutral Natural 3 months 18/09/2013 Neutral

Burrill 9/11/1991 13 years, 6 31/05/2005 Neutral 1 month months Burrill 24/06/2005 1.122 Neutral Artifical 1 year, 2 4/08/2006 El Nino 7 months months Burrill 27/03/2007 0.986 Neutral Artifical 1 year, 6 6/09/2008 La Nina 2 years, 3 months months Burrill 2/12/2010 1.028 La Nina Artifical

Tabourie 4/12/1992 0.91 El Nino Artificial 4 months 20/03/1993 El Nino 1 year, 1 month Tabourie 13/04/1994 1.077 El Nino Artificial 4 months 12/08/1994 El Nino 10 months

Tabourie 16/06/1995 1.037 El Nino Artificial <1 month 19/06/1995 El Nino 3 months

Tabourie 1/09/1996 1.289 Neautral Artificial 2 months 24/11/1996 Neutral 4 months

Tabourie 5/03/1997 1.097 El Nino Artificial 2 months 2/05/1997 El Nino 1 month

Tabourie 27/06/1997 1.105 El Nino Artificial 1 month 16/07/1997 El Nino 3 months

Tabourie 8/10/1997 1.079 El Nino Artificial 4 months 11/02/1998 El Nino 4 months

Tabourie 16/06/1998 0.87 La Nina Artificial 8 months 23/02/1999 La Nina 5 months

Tabourie 6/07/1999 0.729 La Nina Artificial 4 months 13/11/1999 La Nina 1 year

Tabourie 13/11/2000 1.041 La Nina Artificial 4 months 10/03/2001 La Nina 5 months

Tabourie 23/08/2001 0.727 La Nina Artificial* 1 year, 6 15/02/2003 El Nino 1 year, 8 months months Tabourie 22/10/2004 1.077 Neutral Artificial 2 months 31/12/2004 Neutral 7 months

Tabourie 8/07/2005 1.154 Neutral Artificial <1 month 25/07/2005 Neutral 1 year

Tabourie 21/07/2006 1.12 El Nino Artificial* 3 months 20/10/2006 El Nino 1 year, 4 months Tabourie 11/02/2008 1.046 La Nina Artificial* <1 month 24/02/2008 La Nina 2 years, 10 months Tabourie 2/12/2010 1.137 La Nina Artificial* <1 month 15/12/2010 La Nina 7 months

Tabourie 20/07/2011 1.124 La Nina Artificial* 1 month 23/08/2011 La Nina 5 months

Tabourie 1/03/2012 0.877 La Nina Artificial* 1 month 23/04/2012 La Nina 2 months

Tabourie 15/06/2012 1.197 La Nina Artificial 1 month 24/07/2012 La Nina 9 months

Tabourie 12/10/2012 1.029 La Nina Natural* 1 month 8/11/2012 La Nina 5 months

Tabourie 29/04/2013 1.161 Neutral Natural

Durras 6/02/2002 1.593 Neutral Natural 1 year, 7 10/09/2003 Neutral 1 year, 10 months months

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Durras 5/07/2005 1.719 Neutral Artificial 9 months 10/04/2006 Neutral 10 months (Illegal) Durras 24/06/2007 1.7 La Nina Artificial 1 year, 2 18/08/2008 La Nina 2 years, 10 months months Durras 20/06/2011 1.78 La Nina Artificial 1 year, 1 month 20/07/2012 Neutral 3 months

Durras 12/10/2012 1.343 Neutral Natural 8 months 3/06/2013 Neutral < 1 month

Durras 26/06/2013 1.577 Neutral Natural

Wallaga 28/09/1995 0.932 El Nino Artificial* 4 years, 3 9/12/1999 La Nina 9 months months Wallaga 28/09/2000 1.074 La Nina Artificial 3 months 18/12/2000 La Nina 8 months

Wallaga 18/08/2001 1.249 La Nina Artificial 4 months 21/01/2002 Neutral 1 month

Wallaga 24/02/2002 1.268 El Nino Artificial 8 months 8/10/2002 El Nino 6 months

Wallaga 16/04/2003 1.274 El Nino Artificial 4 months 27/08/2003 El Nino 3 years, 6 months Wallaga 12/02/2007 1.445 El Nino Artificial

NB: Entrance record constructed from water level profiles (m), M2 profiles (m) and historic entrance opening logs held by the NSW Office of Environment and Heritage. An asterisk (*) indicates that the nature of the opening event was inferred from the profiles with no supporting record.

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Appendix Two

Storm Record for Batemans Bay 1991 – 2011 (Adapted from MHL, 2012)

Start Date Finish Date Peak Hsig Mean Hsig Peak Hmax Peak Power Mean Power Degrees Direction 5-Jan-91 6-Jan-91 3.3 3.1 5.9 43.6 40.1 180 S 16-Jan-91 16-Jan-91 3.2 3.2 5.8 38.5 35.5 135 SE 16-Feb-91 20-Feb-91 5.1 3.9 9.5 192 99.5 135 SE *01-MAR-1991 2-Mar-91 3.8 3.3 6.5 72.6 55.2 180 S 10-Mar-91 12-Mar-91 3.6 3.2 6.8 50.1 40.9 135 SE 23-Mar-91 25-Mar-91 4.1 3.6 7.1 95.4 70.9 180 S 21-Apr-91 21-Apr-91 3 3 5.8 36.7 36.7 157 SSE 22-Apr-91 23-Apr-91 3.3 3.2 5.8 63.5 56.5 180 S 26-Apr-91 27-Apr-91 4.6 3.6 8.2 95 58.5 157 SSE 8-Jun-91 12-Jun-91 3.9 3.4 7.1 65.3 50.3 90 E 10-Jul-91 12-Jul-91 4.6 3.8 8.8 125.2 80.5 67 ENE 16-Jul-91 18-Jul-91 4.2 3.5 7.3 110.4 71.7 135 SE 22-Jul-91 23-Jul-91 4.1 3.3 7.9 142.8 73.9 157 SSE 16-Oct-91 16-Oct-91 3.4 3.4 5.6 49.4 49.3 180 S 27-Oct-91 27-Oct-91 3.6 3.3 6.6 61.3 52.4 157 SSE 20-Nov-91 20-Nov-91 3.1 3.1 6 39.1 37.8 45 NE 13-Dec-91 14-Dec-91 3.5 3.3 6.8 54.3 49.1 67 ENE 28-Jan-92 28-Jan-92 3.8 3.3 6.9 62.4 46.9 180 S *10-FEB-1992 11-Feb-92 4.5 3.8 7.9 97.7 72.6 135 SE 14-Feb-92 14-Feb-92 3.2 3.1 5.6 48.4 43.4 157 SSE 22-May-92 23-May-92 3.4 3.1 5.9 58.1 50.3 135 SE 26-Jun-92 28-Jun-92 3.7 3.3 7.1 64.7 52.1 90 E 10-Jul-92 10-Jul-92 3.3 3.2 6.5 66.6 58.7 135 SE 20-Jul-92 21-Jul-92 3.3 3.1 5.6 48.5 38.2 112 ESE 24-Aug-92 25-Aug-92 3.9 3.2 6.8 61.5 45 135 SE 17-Sep-92 17-Sep-92 3.1 3.1 5.5 38.9 38.9 157 SSE 25-Sep-92 26-Sep-92 4.7 3.8 8.8 106.4 72.8 112 ESE 20-Oct-92 22-Oct-92 4.5 3.5 8.7 101.6 62.6 180 S 5-Nov-92 5-Nov-92 3 3 5.9 34.9 34.9 135 SE 12-Nov-92 14-Nov-92 3.9 3.4 6.8 85.7 59 157 SSE 30-Nov-92 30-Nov-92 3 3 5.3 39.1 38.5 157 SSE 1-Dec-92 2-Nov-92 3.3 3.1 5.7 59.8 54.2 112 ESE *05-DEC-1992 5-Dec-92 4.1 3.7 7.1 71.3 56.5 45 NE 25-Jan-93 25-Jan-93 3.9 3.5 7.3 68.1 52.5 180 S 30-Mar-93 30-Mar-93 3 3 4.8 47.4 47.1 157 SSE 15-May-93 15-May-93 3.1 3.1 5.1 49.8 49.8 180 S *13-JUN-1993 15-Jun-93 4.7 3.6 8.9 168.1 99.6 180 S 4-Aug-93 4-Aug-93 3.3 3.2 6.3 44.6 40.7 135 SE 3-Sep-93 4-Sep-93 3.6 3.4 6.2 82.7 69.8 180 S 4-Oct-93 4-Oct-93 3.3 3.1 5.9 41.6 38.6 157 SSE

86 S Perry (2014)

9-Nov-93 9-Nov-93 3.5 3.3 6.3 53.7 47.5 180 S 2-Dec-93 2-Dec-93 3 3 5.3 41 41 180 S 21-Jan-94 21-Jan-94 3.3 3.2 5.4 46 43.3 90 E 28-Feb-94 28-Feb-94 3.1 3.1 5.5 39.2 36.8 157 SSE 11-Mar-94 14-Mar-94 4.2 3.4 7.4 96.6 68.5 180 S *13-APR-1994 14-Apr-94 3.3 3.1 6 43.9 38.7 157 SSE *09-JUN-1994 11-Jun-94 4.3 3.5 6.8 110.1 63.7 157 SSE 27-Jun-94 27-Jun-94 3.2 3.1 6 45.1 42.1 180 S 22-Jul-94 23-Jul-94 3 3 4.8 52.2 51.8 180 S 9-Aug-94 10-Aug-94 4.9 3.9 7.6 162.4 104.1 180 S 13-Aug-94 13-Aug-94 3.1 3.1 5.3 42.2 42.2 180 S 6-Sep-94 6-Sep-94 4 3.6 7 69.9 57.8 180 S 21-Sep-94 21-Sep-94 3.2 3.1 5.7 50.8 48.9 157 SSE 11-Oct-94 11-Oct-94 3 3 5.5 37.8 37.4 180 S 18-Oct-94 18-Oct-94 3.5 3.3 6.8 54.8 47.2 180 S 20-Oct-94 21-Oct-94 4 3.5 7.4 66 52.4 135 SE 4-May-95 4-May-95 3.1 3.1 5.5 37.2 37.2 135 SE 18-May-95 19-May-95 4.3 3.6 7.9 104.2 64.1 135 SE *12-JUN-1995 13-Jun-95 4 3.7 6.6 101.7 83 180 S 17-Jun-95 19-Jun-95 3.9 3.4 7.2 79.7 59.2 180 S 21-Jun-95 22-Jun-95 4.3 3.5 8 99.2 64.4 157 SSE 20-Jul-95 21-Jul-95 3.3 3.2 6 76.5 74.3 180 S 8-Aug-95 9-Aug-95 3.7 3.2 6.6 74.6 54.8 180 S 6-Sep-95 6-Sep-95 3.3 3.1 5.8 53 47.5 180 S 24-Sep-95 27-Sep-95 5.2 4 9.8 152.6 84.6 112 ESE 28-Sep-95 28-Sep-95 3 3 4.8 34.9 34.9 135 SE 20-Oct-95 20-Oct-95 3.2 3.2 6.2 39 38.3 135 SE 23-Oct-95 24-Oct-95 3.4 3.2 6.3 50.1 44.7 112 ESE 30-Oct-95 30-Oct-95 3.2 3.1 5.5 38.4 37.1 157 SSE 21-Dec-95 22-Dec-95 3.7 3.4 7.6 72.2 58.1 180 S 12-Feb-96 12-Feb-96 3.5 3.2 6.3 54.6 47.2 157 SSE 12-Apr-96 13-Apr-96 3.9 3.3 7.9 64.3 48.2 135 SE 14-Jul-96 15-Jul-96 3.3 3.2 6 58.8 52.1 180 S 19-Aug-96 20-Aug-96 3.8 3.3 6.7 64.6 47.8 180 S 31-Aug-96 2-Sep-96 7.2 4.9 12.4 300.4 143.4 90 E 19-Oct-96 19-Oct-96 3 3 5.5 34.4 34.4 180 S 4-Nov-96 6-Nov-96 3.3 3.1 6.3 46.1 39.3 157 SSE *08-JAN-1997 8-Jan-97 3.8 3.4 6.1 72.8 58.3 135 SE 4-Mar-97 5-Mar-97 3.2 3.2 5.5 54.9 52.9 135 SE 9-Mar-97 9-Mar-97 3.3 3.2 5.1 46.4 41.6 112 ESE 13-Mar-97 13-Mar-97 3.2 3.2 5.6 43.6 43.6 112 ESE *07-APR-1997 7-Apr-97 4 3.7 6.9 96.9 83 180 S 18-Apr-97 18-Apr-97 3.4 3.2 5.7 47.1 42 180 S 17-Jun-97 17-Jun-97 3.2 3.1 6.1 51 47.6 135 SE 28-Jun-97 28-Jun-97 3.1 3 5.1 49.1 47.5 90 E

87 S Perry (2014)

30-Jun-97 30-Jun-97 3.1 3 5.5 53.8 52.8 135 SE *06-SEP-1997 6-Sep-97 3.4 3.2 6 53.2 47 135 SE 17-Sep-97 17-Sep-97 3.3 3.2 5.8 60.6 56.1 157 SSE 22-Sep-97 25-Sep-97 3.6 3.2 6.8 60.3 44.6 157 SSE *06-MAR-1998 10-Mar-98 3.3 3.1 5.7 57 47.3 180 S 24-Mar-98 24-Mar-98 4.3 3.9 8.6 90.7 71.3 157 SSE *05-MAY-1998 6-May-98 3.8 3.4 6.9 79.7 56.9 180 S *18-MAY-1998 19-May-98 3.6 3.1 6.2 76.5 55 90 E 22-May-98 22-May-98 3 3 5.3 54.8 54.8 180 S 25-May-98 25-May-98 3 3 5.2 36.4 36.4 157 SSE *08-JUN-1998 8-Jun-98 3.5 3.3 6 56.2 50.6 157 SSE *23-JUN-1998 23-Jun-98 3.6 3.3 5.8 74.4 62.6 180 S 26-Jun-98 26-Jun-98 3.1 3.1 5.1 55.7 54 180 S *08-AUG-1998 9-Aug-98 4.5 4.1 7.7 125.4 88.5 157 SSE 17-Aug-98 17-Aug-98 3.3 3.1 6.4 47.8 42.8 90 E *31-OCT-1998 1-Nov-98 4.2 3.6 7 80.3 59.6 135 SE 18-Nov-98 18-Nov-98 3 3 5.2 38.2 38.2 112 ESE 30-Nov-98 1-Dec-98 3.3 3.1 6.1 56.4 51.6 135 SE 13-Jan-99 14-Jan-99 3.6 3.3 6.1 53.6 46.7 180 S *26-FEB-1999 26-Feb-99 3.4 3.2 5.8 67.3 57.6 157 SSE 22-Mar-99 22-Mar-99 3.2 3.2 5.7 44.4 42.4 180 S 28-Mar-99 28-Mar-99 3.2 3.2 4.9 38.1 38.1 180 S 6-Apr-99 7-Apr-99 3.5 3.3 7.3 51.7 44.3 157 SSE *21-APR-1999 23-Apr-99 4.8 3.7 8.5 145.5 82.4 90 E *28-APR-1999 30-Apr-99 4.9 3.8 8.2 145.4 77.2 135 SE 24-May-99 25-May-99 4 3.4 6.8 117.1 84 67 ENE 11-Jun-99 13-Jun-99 4.3 3.6 7.8 122.5 81.2 180 S 13-Jul-99 16-Jul-99 4.5 3.6 7.6 122.3 68.4 112 ESE 10-Sep-99 13-Sep-99 3.9 3.3 7.3 94.3 62.1 135 SE *24-OCT-1999 25-Oct-99 6.6 4.6 11.8 238.8 120 112 ESE 10-Nov-99 12-Nov-99 4.5 3.7 8.1 152.5 89.8 157 SSE 11-Dec-99 11-Dec-99 3 3 4.7 35.6 35.6 180 S *29-DEC-1999 1-Jan-00 4.3 3.5 7.6 98.7 65 180 S 5-Jan-00 7-Jan-00 4.8 3.9 8.4 140.8 85.4 180 S 13-Feb-00 13-Feb-00 3.4 3.2 5.9 52.8 43.9 180 S 7-Mar-00 7-Mar-00 3.1 3.1 5.2 43.8 42.9 135 SE *23-MAR-2000 23-Mar-00 3.7 3.4 6 # # 180 S 5-Apr-00 6-Apr-00 3.8 3.5 6.7 61.4 53.5 180 S *06-MAY-2000 6-May-00 3.7 3.5 6.8 # # 180 S *01-JUN-2000 3-Jun-00 3.9 3.4 7 # # 180 S *29-JUN-2000 1-Jul-00 5.3 4 9.2 # # 180 S 14-Jul-00 14-Jul-00 3.2 3.1 5.9 56.1 54.2 157 SSE *17-JUL-2000 19-Jul-00 3.4 3.2 6.3 71 57.7 135 SE *26-SEP-2000 27-Sep-00 4.4 3.6 7 # # 112 ESE 1-Dec-00 1-Dec-00 3 3 5.3 34.5 34.5 180 S

88 S Perry (2014)

29-Dec-00 30-Dec-00 3.1 3.1 5.3 51.4 49.9 157 SSE 8-Jan-01 8-Jan-01 3 3 5.8 40.6 40.6 157 SSE 15-Jan-01 16-Jan-01 4.7 4.1 7.7 104.9 81.7 180 S 12-Mar-01 12-Mar-01 3.2 3.2 5.1 48.9 48.9 157 SSE 31-Mar-01 31-Mar-01 3.1 3.1 5.7 79.3 78.8 146 SE *11-APR-2001 13-Apr-01 4.3 3.5 6.8 109.7 65.5 146 SE 16-Jun-01 16-Jun-01 3.3 3.2 6.1 59.9 55.8 162 SSE *08-JUL-2001 10-Jul-01 3.7 3.2 7 76.2 56.6 118 ESE *27-JUL-2001 30-Jul-01 5.4 4.2 9.5 176.6 95.4 146 SE 22-Aug-01 23-Aug-01 3.4 3.2 6.3 65.7 54.1 169 S 29-Aug-01 29-Aug-01 3.7 3.3 6.5 60.5 49.1 136 SE 26-Sep-01 26-Sep-01 3.2 3.1 5 44.7 41.1 174 S 8-Oct-01 9-Oct-01 4.6 4.1 8.1 114.5 93 167 SSE 14-Oct-01 14-Oct-01 3 3 6.1 39.3 39.3 167 SSE 19-Oct-01 19-Oct-01 3.1 3.1 6.1 40.8 40.8 187 S 13-Nov-01 14-Nov-01 3.6 3.3 6.1 67.4 53.9 171 S 18-Nov-01 19-Nov-01 4.8 3.9 7.9 120.6 74.6 173 S 20-Nov-01 22-Nov-01 4.8 3.9 8.3 132.6 81.6 125 SE 4-Dec-01 6-Dec-01 3.6 3.2 6.2 71.5 54.9 139 SE 9-Jan-02 9-Jan-02 3.1 3 5.3 46.2 44.1 145 SE 3-Feb-02 3-Feb-02 3 3 4.6 38.3 38.3 153 SSE 5-Feb-02 5-Feb-02 3.1 3.1 5.1 40.3 38.7 131 SE 9-Feb-02 9-Feb-02 3.5 3.2 6.5 53.7 43.9 174 S 11-Feb-02 11-Feb-02 3.2 3.2 5.4 52.8 50.5 157 SSE 14-Apr-02 14-Apr-02 3 3 4.9 36.9 36.9 148 SSE 21-Apr-02 22-Apr-02 4.3 3.7 7.1 94.1 66.9 162 SSE 28-May-02 29-May-02 3.8 3.3 6.8 124 83.6 148 SSE 17-Jun-02 19-Jun-02 4.7 3.8 8.8 136.3 85.6 138 SE 28-Jun-02 30-Jun-02 4.5 3.9 8 133.5 94.4 152 SSE *14-AUG-2002 16-Aug-02 4.6 3.7 8.6 # # 149 SSE 8-Oct-02 9-Oct-02 3.1 3.1 4.8 46.1 44 163 SSE 1-Dec-02 1-Dec-02 3.3 3.2 5.8 41.2 38.6 169 S 25-Dec-02 25-Dec-02 3.3 3.2 5.8 53.4 47.7 176 S 8-Jan-03 9-Jan-03 4 3.5 6.7 80.4 57 170 S 9-Jan-03 9-Jan-03 3.3 3.2 5.8 50.8 46.8 159 SSE 5-Mar-03 5-Mar-03 3.1 3.1 5.3 56.3 54 136 SE 3-Apr-03 3-Apr-03 3.3 3.2 5.9 49.7 46.3 171 S 18-Apr-03 19-Apr-03 3.5 3.2 5.9 72 58.3 132 SE 17-May-03 18-May-03 3.7 3.3 6.5 77.4 63 91 E 27-Jun-03 27-Jun-03 4.4 3.6 6.6 150.6 98.4 80 E 30-Jun-03 1-Jul-03 3.6 3.3 6.9 92.4 70.5 149 SSE 30-Jul-03 1-Aug-03 4.1 3.4 7 116.6 69.6 157 SSE 3-Sep-03 4-Sep-03 3.9 3.5 6.9 95.4 77.1 169 S 7-Sep-03 8-Sep-03 3.2 3.1 5.9 53.2 47.9 167 SSE 16-Nov-03 16-Nov-03 3.3 3.1 5.8 46.9 43 163 SSE

89 S Perry (2014)

5-Dec-03 5-Dec-03 3.6 3.4 6.3 58.8 51.2 163 SSE 16-Feb-04 16-Feb-04 3.6 3.5 6.5 60.6 54.9 160 SSE 29-Feb-04 29-Feb-04 3.5 3.3 6.2 54.3 48.1 163 SSE 10-Mar-04 10-Mar-04 3.4 3.3 6 53.3 50.8 163 SSE 12-May-04 12-May-04 3.4 3.1 6.5 57.2 49.4 155 SSE 14-May-04 15-May-04 3.8 3.4 6.6 85.5 69.2 146 SE 29-May-04 29-May-04 3 3 5.2 54.8 54.8 149 SSE *17-JUL-2004 19-Jul-04 4.7 3.7 8 136.7 75.1 153 SSE 15-Aug-04 15-Aug-04 3.9 3.4 6.8 72.1 55.9 173 S 21-Oct-04 21-Oct-04 3.7 3.4 6.9 68.5 58.7 69 ENE 28-Oct-04 29-Oct-04 3.9 3.4 7 104.2 72.4 142 SE 22-Nov-04 23-Nov-04 3.4 3.3 6.3 50.3 47 171 S 7-Dec-04 8-Dec-04 3.2 3.1 5.4 50.1 44.6 72 ENE 27-Dec-04 28-Dec-04 3.7 3.4 6 57.9 50.4 169 S 29-Dec-04 29-Dec-04 3.3 3.2 5.7 62.4 56.9 164 SSE 31-Dec-04 31-Dec-04 3.2 3.1 5 64.7 60 131 SE 12-Feb-05 13-Feb-05 3.6 3.3 6.7 54.1 47.5 176 S 17-May-05 19-May-05 3.2 3.1 5.4 49.9 49.3 148 SSE 25-May-05 25-May-05 3.1 3.1 5.5 40.3 39.3 164 SSE 23-Jun-05 24-Jun-05 5.4 4 9.8 145.8 83.5 164 SSE 30-Jun-05 1-Jul-05 4.7 3.7 8.8 104.7 66.7 59 ENE *10-JUL-2005 11-Jul-05 5.2 4.3 9.1 169.9 112.8 121 ESE 31-Aug-05 31-Aug-05 3.3 3.2 5.7 51.7 47.9 67 ENE 13-Sep-05 13-Sep-05 3.3 3.2 5.7 64.5 58.9 160 SSE 15-Nov-05 16-Nov-05 4.9 3.8 8.3 127.1 73.8 177 S 27-Nov-05 29-Nov-05 6.6 4 11.2 287.5 99.6 153 SSE 6-Feb-06 7-Feb-06 4.2 3.7 8.4 86.3 64.5 166 SSE 28-Mar-06 28-Mar-06 3.1 3.1 5.3 67.7 64.9 94 E *03-APR-2006 3-Apr-06 3.8 3.5 6.3 0.2 0.1 157 SSE 9-Apr-06 10-Apr-06 3.2 3.1 5.8 74.5 68.6 142 SE 16-Apr-06 17-Apr-06 4.5 3.7 7.7 154.9 97.2 148 SSE 7-Sep-06 10-Sep-06 4.3 3.4 7.8 78.8 50.3 163 SSE 8-Oct-06 8-Oct-06 4 3.4 6.6 64.4 46.8 169 S 20-Oct-06 21-Oct-06 4.1 3.6 7 68.7 53.8 185 S 26-Oct-06 26-Oct-06 3.2 3.2 5.8 42.4 42.1 166 SSE 28-Oct-06 28-Oct-06 3.5 3.4 6.1 61.9 55.4 166 SSE 5-Nov-06 6-Nov-06 3.4 3.2 7 53.4 45.7 180 S 27-Jan-07 27-Jan-07 3.6 3.3 6.8 55.2 47.9 162 SSE *12-FEB-2007 12-Feb-07 3.1 3.1 5.5 43.4 43.4 111 ESE 12-Mar-07 12-Mar-07 3.2 3.2 5.3 54.3 54.3 159 SSE 24-Mar-07 24-Mar-07 3.6 3.4 6.9 47.7 43.9 170 S 8-Jun-07 11-Jun-07 4.8 4 10.3 133.6 89.7 128 SE 14-Jun-07 16-Jun-07 3.8 3.4 7.9 70.9 53.9 113 ESE 19-Jun-07 20-Jun-07 5.7 4.1 10.7 192.1 96 148 SSE 21-Jun-07 21-Jun-07 3.6 3.2 6.4 72.9 57.2 163 SSE

90 S Perry (2014)

27-Jun-07 29-Jun-07 5.4 3.8 9.5 187.3 90 149 SSE 6-Jul-07 6-Jul-07 3.2 3.1 6.2 63.4 60.2 161 SSE 9-Jul-07 10-Jul-07 4 3.5 7.7 78.2 59.7 151 SSE 12-Jul-07 12-Jul-07 3.4 3.2 6.6 94.2 75.8 110 ESE 4-Nov-07 6-Nov-07 4.6 4 8.5 112.1 80 158 SSE 7-Feb-08 8-Feb-08 3.6 3.3 6.1 61.7 52.7 183 S 13-Feb-08 13-Feb-08 3.1 3.1 4.8 40.5 40.1 179 S 28-Feb-08 28-Feb-08 3.1 3.1 5.2 40.4 40.4 187 S *29-FEB-2008 1-Mar-08 3.5 3.3 6.7 64.3 54.3 161 SSE 21-Mar-08 21-Mar-08 3.5 3.4 6.3 51.2 46.2 176 S 5-Jun-08 5-Jun-08 3 3 6.6 47.3 45.7 89 E *14-JUN-2008 16-Jun-08 3.4 3.2 7.9 63.1 55.5 159 SSE 22-Jul-08 22-Jul-08 3 3 5.5 66.5 64.4 163 SSE *28-JUL-2008 29-Jul-08 3.9 3.4 7.2 81.1 61.8 151 SSE *16-AUG-2008 17-Aug-08 3.7 3.3 7.3 84.2 66.9 151 SSE *22-AUG-2008 23-Aug-08 3.5 3.2 6 58.2 46.9 152 SSE 6-Sep-08 7-Sep-08 3.6 3.3 6.4 79.5 62.6 82 E *08-SEP-2008 10-Sep-08 3.7 3.2 7.7 62.7 56.2 175 S 4-Nov-08 4-Nov-08 3.1 3.1 6.3 51.1 51.1 172 S 24-Nov-08 24-Nov-08 3.4 3.2 7.8 59 52.9 165 SSE 14-Dec-08 15-Dec-08 3.8 3.4 7.5 84.2 65.1 172 S 24-Jan-09 24-Jan-09 3 3 5.3 38.9 38.9 161 SSE 10-Feb-09 11-Feb-09 3.8 3.3 6.9 61.6 48.2 180 S 18-Feb-09 18-Feb-09 3.3 3.1 5.5 52 47.7 103 ESE 1-Apr-09 1-Apr-09 3.3 3.1 6.2 61.5 52.2 90 E 19-Apr-09 20-Apr-09 3.4 3.2 7.2 61.2 53.9 109 ESE 25-Apr-09 25-Apr-09 3.2 3.1 5.4 78.7 74.5 78 ENE 23-May-09 23-May-09 3.2 3.1 5.7 54.2 50.9 80 E 10-Jun-09 11-Jun-09 3.4 3.2 6.2 66.5 56.7 165 SSE 7-Oct-09 9-Oct-09 4.4 3.7 8.8 110.1 72 165 SSE 17-Dec-09 18-Dec-09 3.1 3.1 5.7 39.9 39.6 185 S 6-Feb-10 6-Feb-10 3.2 3.1 6.2 43.1 43.1 189 S 14-Feb-10 16-Feb-10 4.3 3.6 8 92.8 64.1 158 SSE 14-May-10 15-May-10 3.9 3.4 6.9 111.5 81.4 130 SE 26-May-10 27-May-10 4.3 3.5 7.8 79.9 54.8 123 ESE 30-May-10 31-May-10 5.5 3.7 8.9 168.1 74.2 118 ESE 6-Jun-10 6-Jun-10 3.4 3.2 5.9 51.8 46.8 190 S 2-Aug-10 3-Aug-10 4.1 3.6 8 93.7 63.6 166 SSE 13-Aug-10 13-Aug-10 3.4 3.4 6.1 68.6 68.4 163 SSE 4-Sep-10 4-Sep-10 3.1 3.1 5.3 44.4 43.8 61 ENE 21-Sep-10 21-Sep-10 3.2 3.2 5.5 44.1 43.7 166 SSE 15-Oct-10 10-Oct-10 3.5 3.3 6.2 63 55 65 ENE 1-Nov-10 2-Nov-10 3.1 3.1 6.3 42.5 40 166 SSE 29-Nov-10 29-Nov-10 3.1 3.1 6.4 41.6 40.5 183 S 27-Dec-10 27-Dec-10 3.7 3.4 6.4 60.6 49 183 S

91 S Perry (2014)

21-Feb-11 22-Feb-11 3.6 3.3 6.8 68.8 57.5 179 S 1-Mar-11 1-Mar-11 3.7 3.5 6.2 64.7 53.9 178 S 21-Mar-11 23-Mar-11 3.6 3.2 7.2 66.5 54.2 102 ESE 15-Apr-11 16-Apr-11 3.3 3.1 6.3 52.9 47.7 152 SSE 3-May-11 3-May-11 3.1 3.1 5.4 56.1 54.4 106 ESE 5-May-11 5-May-11 3 3 6 49.2 49.2 159 SSE 24-May-11 25-May-11 3.7 3.3 6.9 63.3 50.4 168 SSE 31-May-11 31-May-11 3.1 3.1 5.1 47.1 46.6 90 E 9-Jun-11 11-Jun-11 3.9 3.3 7.3 81.7 57.9 151 SSE 16-Jun-11 17-Jun-11 3.4 3.2 6.4 76.7 64.2 103 ESE 19-Jul-11 24-Jul-11 5.6 4 10.7 191.3 96.8 121 ESE 18-Aug-11 20-Aug-11 3.7 3.3 6.7 71.3 53.9 117 ESE 10-Sep-11 10-Sep-11 3.1 3.1 5.9 54.2 50.7 166 SSE 12-Sep-11 12-Sep-11 3.1 3.1 6.4 58.4 58.4 151 SSE 23-Sep-11 23-Sep-11 3.4 3.2 6.5 50.5 46.4 168 SSE 2-Oct-11 2-Oct-11 3.2 3.1 6.5 45.6 43.2 168 SSE 25-Oct-11 25-Oct-11 3 3 4.8 41.6 41.6 152 SSE 23-Nov-11 23-Nov-11 3 3 5.1 36.9 36.9 170 S 30-Nov-11 1-Dec-11 3.1 3.1 5.5 37.1 36.2 162 SSE 4-Dec-11 4-Dec-11 3.3 3.2 6.9 43.2 40.9 176 S

NB: Direction prior to February 2001 was estimated using the deep-water values. Since February 2001 the Waverider buoy was updated to a Directional Waverider Buoy where direction is recorded in situ (MHL, 2012). MHL Record spans 1986 – 2011. MHL record was used for period 1991 – 2011.