Beach Erosion Trend Measurement: A Comparison of

Journal of Coastal Research

SI 50

588 - 593

ICS2007 (Proceedings)

Australia

ISSN 0749.0208

Beach Erosion Trend Measurement: A Comparison of Trend Indicators D. J. Hanslow Coastal Unit NSW Department of Environment and Climate Change, Newcastle 2309, Australia. [email protected] ABSTRACT HANSLOW, D. J., 2007. Beach Erosion Trend Measurement: A Comparison of Trend Indicators, SI 50 (Proceedings of the 9th International Coastal Symposium), 588 – 593. Gold Coast, Australia, ISSN 0749.0208 The measurement of longer-term trends in coastal erosion is of particular importance for the management of the world’s coastlines. Methods commonly used for trend determination involve measurement of the shoreline or high water mark using aerial photography. For more dynamic coasts however, longer term trends in these features may be obscured by short-term fluctuations. In the present study, several different methods of quantifying beach recession and accretion are compared. In addition to the shoreline and the high water mark, these include the use of position indicators such as the vegetation line and the bluff or scarp location, as well as various volumetric measures. Comparison of the various methods is made with reference to MacMasters Beach, south-east Australia. The results show that the use of different indicators may result in significantly different trend estimates and that great caution needs to be exercised in the selection of appropriate indicators. For highly dynamic beaches, like MacMasters Beach, the less variable indicators like the scarp location and the dune volume may provide a better indication of underlying trends in beach erosion than the shoreline or high water mark. ADDITIONAL INDEX WORDS: Coastal erosion, Coastal management, Coastal hazards, Coastal risk, Accretion, Recession, Shoreline, High water mark

INTRODUCTION Many beaches around the world are subject to problems associated with beach erosion and recession. Causes may vary with location and can be related to the short term beach fluctuations or longer term trends associated with deficits in sediment budgets, rising sea levels and changes in wave climates. Responsible beach management requires accurate definition of both short term fluctuations and longer term trends for the assessment of risk to present development, and for the determination of acceptable set backs for future development or other forms of coastal management. Hazard assessment usually involves determination of the extent of short-term beach fluctuations (due to storms, rips, beach rotation etc), the extrapolation of past longer term trends in beach recession, as well making allowance for potential future changes to short and long term processes due to potential climate change. The current paper deals with methods used to estimate past rates of beach recession. Many papers have been published that deal with the measurement of beach recession (eg. Dolan et al., 1978; Hayden et al., 1979; Dolan and Hayden, 1983; Foster and Savage, 1989; NRC, 1990; Smith and Zarillo, 1990; Crowell et al., 1991; Dolan et al., 1991; Theiler and Danforth, 1994, Stive et al., 2004). See CROWELL 2006 for recent summary. Almost exclusively these papers have dealt with trend measurement using indicators such as the shoreline (commonly approximated by the high water line) as a reference feature. Unfortunately, the high water line can vary significantly from one day to the next both as a product of short

term beach erosion/accretion episodes and as a product of the daily tidal maximum, the wind and wave conditions, as well as the beach slope and grain size (e.g. DOLAN and HAYDEN, 1983; DOUGLAS et al., 1998). Along coasts where short-term variability of beach volume, wave climate, or beach slope is high (like east coast of Australia) and where the time base of available data is relatively short, the usefulness of this measure is severely limited. SMITH and ZARILLO (1990) highlighted the problem of short term variability in beach width. They showed that errors due to normal shoreline variability for a section of the Long Island coastline were as could be as large as the measured trend. Survey data from the east coast of Australia (THOM and HALL, 1991) show that for more energetic coastlines short term variability in beach width can be significantly greater than measured by SMITH and ZARILLO (1990). The aim of the present paper is to compare a number of different methods of quantifying beach recession and accretion. In addition to the shoreline and the high water mark these include the use of position indicators such as the vegetation line and the bluff or scarp location as well as various volumetric measures (Figure 1). Comparison of the various methods is made with reference to MacMasters Beach on the NSW Central coast.

TREND INDICATORS The Shoreline

Journal of Coastal Research, Special Issue 50, 2007

Beach Erosion Trend Measurement

Movement of the shoreline is the most commonly used indicator of coastal recession or accretion. NRC (1990) defines the shoreline in this context as the interface between the land and water. This interface is highly variable being subject to short term movement associated with the run-up of individual swell or wind waves, tidal oscillations, as well as with variations in wave climate, beach slope and grain size and as a product of beach erosion/accretion cycles.

High Water Line In practice the location of the shoreline is commonly approximated by the high water line because of its ease of identification in the field and on aerial photographs, and because of its use as a reference feature on early maps and charts (eg. DOLAN and HAYDEN, 1983; NRC, 1990; CROWELL et al, 1991). The high water line, unlike the shoreline, does not vary with the run-up of individual waves, but does however, still vary significantly from one day to the next both as a product of short term beach erosion/accretion episodes and as a product of variation in the daily tidal maximum, the wind and wave conditions, as well as the beach slope.

Vegetation Line Measurement of the seaward boundary of dune vegetation should ideally take into account the types of vegetation present (primary, secondary or tertiary species) with rates calculated on the basis of similar vegetation type. Factors other than coastal erosion which may effect vegetation cover include drought, fire, aeolian processes including blowout and transgressive dune formation, as well as animal grazing and human influence including over use and/or dune stabilisation. Trends in the movement of the vegetation line may therefore not always reflect coastal recession or accretion. In some cases a vegetation line may not be present at all.

Scarp or Bluff Location Several features can be used to approximate the scarp location

Figure 1. Examples of different types of position indicators.

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over time. These include the scarp top, the scarp base, or if profile information is available, the movement of the scarp face, usually approximated by movement at a particular contour or level.

Sub-Aerial Beach Volume With profile information available it is possible to calculate cross sectional area or the volume equivalent (m3/m) at each transect for each date of photography. Cross sectional area is measured above a selected level (usually mean sea level) and seawards of some landward boundary. The landward boundary is generally chosen to include all natural coastal process induced volume changes to the beach profile including any changes to the backbeach/foredune, but minimise any effects of man made change to the dune profile and errors in regions of dense vegetation.

Dune Volume On beaches with highly variable berm volumes it is possible to exclude the more variable portion of the beach profile by only examining changes to the dune volume. As with the sub-aerial beach volume calculation this requires profile data enabling calculation of cross sectional area or the volume equivalent (m3/m). However, here a base level for volume calculation is adopted at about the level of transition between the beach face and the dune. Analysis of dune volume provides a more complete picture of changes to the dune profile than that provided by measurement of a single contour or feature and allows for changes in dune height, which may affect the application of calculated rates. This approach may have advantages over other methods when dune heights have varied significantly over the period of analysis and/or are likely to be different in the region to which calculated rates are to be applied.

FIELD SITE AND METHODOLOGY MacMasters Beach MacMasters Beach is located in South Eastern Australia on the central coast of state of New South Wales. This beach faces southeast and is thus exposed to the predominant swell direction on the NSW coast. The beach is 1.5 km long and is backed by a relatively high dune, which in the central part of the beach reaches an elevation of about 16m above mean sea level (MSL). The dune encloses a small coastal lagoon, which while generally closed, has an entrance in the middle of the beach (Figure 2). The site is exposed to a highly variable wind wave climate superimposed on a variable but predominantly high energy south easterly swell. Modal deep water wave height on the NSW coast is approximately 1.5 m while storms with significant wave heights of up to 5.5 m and 9.2 m have return periods of approximately 1 year and 50 years respectively (WYLLIE et al., 1992). The tidal regime of the NSW coast is microtidal semidiurnal with a diurnal inequality. The tide range varies from approximately 2m at springs to less than 1m at neaps. Beach/nearshore sediments extend offshore from the beach to a depth of around 32 m where coarser inner shelf deposits are found The beach/nearshore sands are bound to the north and south by bedrock reefs which extend offshore of the enclosing headlands. The beach has a relatively high energy, intermediate beach type. Short term variability in beach width is high with volumetric fluctuations of up to 280 m3/m (above MSL) measured in association with 1974 storms (HANSLOW 1994).

Photogrammetry and Trend Measurement


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Hanslow

Figure 2. MacMasters Beach Profile locations. Profile and plan data for MacMasters Beach were obtained by undertaking analysis of vertical aerial photography. Ten photographs spanning the period between 1941 and 1993 were used to identify changes in shoreline, high water line, vegetation line, sub-aerial sand volumes and dune or scarp location. Photogrammetric analysis was undertaken using a Wild Aviolyt AC1 stereo analytical plotter operated by an experienced photogrammetrist. This type of instrument is similar to that commonly used for topographic mapping. It enables high resolution digital topographic data to be obtained from stereo pairs of aerial photograph diapositives. The AC1 measuring system is constructed strictly in accordance with the Abbe comparator principle and is equipped with linear encoders with a resolution of 1µm. The AC1 automatically takes into account corrections for systematic instrument errors, film shrinkage, lens distortion, earth curvature and refraction. Data output is in digital form and is down loaded to a CADD system for presentation. The set up of each photogrammetric model is undertaken in two stages involving inner orientation and outer orientation. Inner orientation is undertaken on corner fiducial crosses and a best fit computed with the camera calibration file. This procedure corrects for film shrinkage or expansion, and lens distortion. Outer orientation is then undertaken by measuring parallax points enabling a stereo model to be created. Up to 30 ground survey control points with known coordinates are then observed and the final photogrammetric model fitted using a bundle solution. The final model incorporates corrections for camera tips, tilts and rotations. Residuals for model fit to the available ground control are automatically calculated and presented in terms of easting, northing and elevation. The reader is referred to the American Society of Photogrammetry (1980) and Theiler and Danforth

(1994) for general details on photogrammetry. More specific detail of the methods used in this study are given in Hanslow et al. (1997). The photogrammetrists estimate of the observation errors at MacMasters beach are presented in Table 1. These are based on the residuals between ground control and the model fit as well as image quality, glare, scale etc. It should be noted that in areas of high vegetation cover, errors may be locally higher than that indicated in Table 1. In these areas generally the photogrammetrist will continue along the profile until the ground can be observed and a straight line is drawn between the observations. For each date of photography the location of the shoreline, high water line and vegetation line indicators at each profile location were measured directly and simply stored for later analysis. Dune or scarp location was approximated using contour analysis due to difficulties in accurately defining a scarp crest or toe for all dates of photography. The dune or scarp contour locations were calculated from the profile data using linear interpolation between adjacent observations. The contours or relative levels selected for analysis were located near the middle of the active dune or scarp face to minimise the effects of varying berm levels and dune slumping following storms etc. The contours selected were generally consistent between profiles but were varied between blocks to take account of changing dune and berm height. Analysis was undertake using relative level (RL) 5m (above MSL) for profiles 1-4, RL 6m (above MSL) for profiles 5-15 and 39-40, and RL 7m (above MSL) for profiles 16-38. Dune and sub-aerial beach volumes were calculated at each profile seawards of a baseline selected separately for each profile to minimise the effects of development related changes to the dune profile and the effects of vegetation cover which limit the accuracy of the landward portions of some profiles. Dune volumes were calculated above 4m AHD, which is just above the beach berm, while sub-aerial volumes were calculated above 0m AHD. AHD is Australian Height Datum, which approximates mean sea level (MSL). Longer term trends were calculated using linear regression. This method enables assessment of the validity of the calculated rates and is useful for the comparison of different measures. Testing of the overall significance of the calculated relationships was undertaken using an F test. This test involves calculating the ratio of the variance that is explained by the regression to the variance of what is not explained by the regression

RESULTS Rates of change of the shoreline, the high water mark, the vegetation line, the dune or scarp face, the sub aerial beach volume as well as the dune volume have been calculated at each profile location and are plotted in Figure 3. Also presented in this Figure are the standard errors of the rate of change estimates Table 1: Estimated photogrammetric model accuracy based on rms model fit and image quality. Photo Date

Horizontal Accuracy (m)

20-4-93 4-5-90 18-8-86 23-8-84 3-3-81 19-6-74 22-4-72 6-7-69 28-6-57 25-11-41

0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 1.3 1.6


Vertical Accuracy (m) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.6 0.7

Quality

Good Good Good Good Good Good Good Good Poor Poor


-2 5

10

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25

30

35

40

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1

0 Recession

Change in Veg. Line (m/year)

Vegetation Line 2

-1

-2 5

10

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25

30

35

40

Accretion

1

Recession

0

-1

-2 5

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1

-1

0 -2 -4 -6 -8 25

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35

40

30

35

40

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35

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0

-2 5

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2

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30

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Recession

4

Change in Dune Vol. (m3/m/year)

Accretion

6

Recession

Change in Subaerial Vol. (m3/m/year)

Subaerial Volume

15

25

Profile Number

8

10

20

2

Profile Number

5

15

Profile Number

Accretion

-1

High Water Mark 2

Recession

0

Change in Scarp Location (m/year)

Accretion

1

Recession

Change in Shoreline (m/year)

Shoreline 2

Change in High Water Mark (m/year)

(slope coefficients). The calculated trend measured for the shoreline is accretionary with an average rate of movement of 0.19 m/yr. However, standard errors in the estimated rates at each profile are very high, generally being significantly larger than the calculated trend. Significance testing indicates that the calculated trends have little statistical significance. The high water line trend varies along the beach with slight accretion in the south and slight recession in the middle/north (avg. rate = -0.04 m/yr). The calculated trends also display significant errors and have little statistical significance. The calculated vegetation movement trend is generally slightly recessional however some profiles display significant seawards movement (accretion) associated with vegetation recovery and blow out stabilisation. The standard errors of the estimated rates are lower than for the shoreline and high water line but are still significant, being of similar order to the calculated trends. In general, the calculated trends are not statistically significant at the 5% level. Trends in the scarp location were approximated by analysing movement of particular contours. The results indicate that the face of the dune or scarp has receded over most of the beach over the period of measurement. The average rate of recession for all profiles is -0.28 m/year. The rate of recession generally increases to the north reaching a maximum of -0.54 m/yr at profile 33. Standard errors of the estimated rates are, in general, reasonably small averaging less than 25% of the calculated trends. Significance testing shows that the rates calculated at most profiles are significant at the 1% level. Trends in the subaerial volume (volume above 0m AHD) also show a general recession over the length over the beach (with the exception of slight accretion at profiles 1-3). The volumetric loss averages -2.34 m3/m/year with rates generally increasing to the north. Standard errors average around 40% of the calculated rates, with significance testing indicating with a few exceptions that the calculated trends are statistically significant at the 5% level.

6 4 2 0 -2 -4 -6 -8 5

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Calculated trends in the dune volume also show recession along the beach with an average loss of -1.26 m3/m/year (above 4m AHD) over the length of the beach. The rate of recession is higher in the north with a maximum volumetric loss of -2.48 m3/m/year at profile 32. Standard errors average less than 25% of the calculated trends. Significance testing shows that the rates calculated at most profiles are statistically significant at the 1% level. Examples of regression plots for an individual profile are shown in Figure 4. In each of these graphs the calculated regression formulas and their associated R2 values are given. As seen in these plots there is significant scatter in the shoreline and high water mark data and to a lesser extent in the subaerial volume and vegetation line data. The least scatter is found in the scarp location and dune volume data, both of which display consistent recessional trends and high R2 values.

DISCUSSION The results from MacMasters Beach show that different indicators give different estimates of the trends in beach behaviour. Two questions need to be answered: firstly which indicators are reliable; and secondly which indicator or indicators provide the best measure of beach recession or accretion? The first question has to some extent already been answered in the examination of standard errors associated with each indicator and the statistical significance of each calculated regression slope coefficient. The results presented suggest that the scarp location and dune volume measures provide the most statistically reliable trend indicators. The subaerial volume also proved a reasonable indicator although somewhat less reliable. Vegetation line trends show little or no significance. It is likely that this is mainly a product of the absence of any trend in vegetation line movement over time rather than scatter in the individual observations. Trends in shoreline and high waterline movement have little or no statistical significance. This is not to say that no trends were present, but only that they were masked by variability in the data. There can be little confidence associated with the use of these indicators at MacMasters Beach with the available data. The problem with the more variable measures is that if one or two of the dates were varied slightly (e.g. one month earlier or later) then it is likely that a very different trend would be calculated. This problem is particularly significant for early dates of photography where observations are isolated and have a significant impact on the regression calculation (e.g. DOLAN et al., 1991). This problem becomes less significant when recession rates are high and the time period of observations is long. The answer to the question as to which of the indicators provides the best measure of beach accretion or recession depends on intended application of the calculated rates. For applications involving development on the dune crest or further landwards, the use of dune or scarp movement measures may actually be more appropriate than the shoreline. However, as indicated previously trends in the scarp movement and dune volume measures are more vulnerable to the occurrence of rare events than the other measures. This is because the longer time scales for dune recovery mean that single events, particularly near the end of the assessment period, may have a significant influence on trend determination. Care is needed therefore to assess whether the measured trend is likely to be representative of the longer term.

Figure 3. Rates of change of the shoreline, high water mark, vegetation line, scarp, subaerial volume, and the dune volume at each profile calculated using linear regression. Error bars plotted correspond to the standard errors of each slope estimate.


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High Water Mark

Shoreline 180

High Water Mark Location (m)

200 Slope = 0.209

Shoreline Location (m)

2

R = 0.026

180

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100 1950

1960

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80 1940

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R = 0.000

140

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R = 0.870

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Volume above 0m AHD (m /m)

Subaerial Volume 400

3

Slope = -2.152

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400

Slope =-3.369 R = 0.523

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R = 0.731

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2000

Slope = 0.005

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R = 0.058

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1940

Slope = 0.226

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Figure 4. An example of changes in the shoreline, high water mark, vegetation line, scarp location, subaerial volume and dune volume between 1941 and 1993 at profile 35. P-values for each regression are as follows: shoreline 0.6568, high water mark 0.5024, vegetation line 1.0, scarp location 0.0001, subaerial volume 0.0181 and dune volume 0.0018. In the current data set several erosion events are evident at different points along the beach. The most significant of these being the erosion prior to the 1974 photography which is evident at all profile locations. This event comprised a series of storms in May -June 1974. The larger of these storms was estimated on the basis of wave height to have a return period of between 20 to 70 years (LORD and KULMAR 2000). Considering other factors such as water levels the return period of this event could be significantly less suggesting a reasonable likelihood of a similar sized event over the next 50 years. In the 30 years since 1974 little dune recovery has occurred. This has in part been due to the occurrence of several smaller storm events, notably in 1978 and 1986. Dune recovery from the 1974 event is presumably dependent on the occurrence of a sustained period of calm weather which, on the basis of past storm history, is unlikely. The sub-aerial volume measure provides a more complete picture of changes in beach volume. However, the inclusion of the beach berm in the volume calculation significantly increases the effects of short term variability in the available data reducing the confidence in the calculated rates. Monitoring of the vegetation line can in theory be used as an indirect measure of changes beach topography. At MacMasters Beach however, trends in the vegetation line do not appear to have

reflected changes in the dune location. The fact that the measured rate of change in the vegetation line was significantly different from the rate of scarp movement shows that the vegetation line can move independently of changes in the beach topography. Differences between these two measures may in part be a result of changes in vegetation management practices and the improvement of vegetation cover in recent years. Therefore the vegetation line at MacMasters Beach must also be considered a poor indicator of beach recession although it is possible that use of this indicator may prove useful at other sites. Both the shoreline and the high water line as discussed earlier make very poor indicators of either recession or accretion at MacMasters Beach. The variable nature of these indicators restricts their usefulness to environments where the wave climate is less variable and the tide range is very low. The selective use of only accreted or eroded dates may potentially reduce the errors in trend determination although this technique requires subjective assessment as to the state of accretion or erosion at the time of the photography. On coasts with distinct seasonal patterns of accretion and erosion, selection of winter or summer data may potentially be quite useful in removing a portion of the short term variance. For coasts with variable, non-



seasonal wave climates, however, any assessment as to the degree of erosion or accretion is likely to be subject to some uncertainty.

CONCLUSION Comparison between the different trend indicators at MacMasters Beach show much caution should be used in the selection of potential indicators of long term coastal change. Comparison between several different trend indicators at MacMasters Beach demonstrate that the less variable indicators such as the scarp location or the dune volume provide more reliable measures of coastal recession than the shoreline or high water mark. The sub-aerial volume also proved a reasonable indicator although somewhat less reliable. The subaerial volume provides a more complete picture of changes in beach volume however the inclusion of the beach berm in the volume calculation significantly increases the effects of short term variability in the available data reducing the confidence in the calculated rates. Measured rates of change in the vegetation line at MacMasters Beach were significantly different from the rates of scarp movement indicating that the vegetation line can move independently of changes in the beach topography. The results obtained suggest that the vegetation line is quite a poor trend indicator at MacMasters Beach. The fact that different methodologies produce different results highlights some of the uncertainties involved with coastal hazard assessment. The results presented in this study illustrate the importance of considering the geomorphological variability of the trend indicator being used, as well as the various measurement errors involved with each observation. Determination of trend measurement error should be undertaken as a matter of course. Where possible, coastal planners should adopt robust risk management strategies, which allow for errors in trend measurement, short-term beach fluctuations, as well as other factors like climate change.

LITERATURE CITED AMERICAN SOCIETY OF PHOTOGRAMMETRY, 1980. Manual of Photogrammetry. Fourth Edition, American Society of Photogrammetry, Falls Church Va., 1056p. CROWELL, M., 2006. Historical Shoreline Mapping and Analysis: A Historical Overview. NOAA Shoreline Change Conference II: A Workshop on Managing Shoreline Change. Charlestown, SC. (http://www.csc.noaa.gov/shoreconf/2006_Conference_ Proceedings.htm). CROWELL, M., LEATHERMAN, S. P. and BUCKLEY, M. K., 1991. Historical Shoreline Change: Error Analysis and Mapping Accuracy. Journal of Coastal Research. 7(3), 839-852. CAMFIELD, F. E. & MORANG, A. 1996. Defining and interpreting shoreline change. Ocean & Coastal Management, 32, (3), 129-151. DOLAN R., HADEN, B. and HEYWOOD, J., 1978. A New Method for Determining Shoreline Erosion. Coastal Engineering, 2, 2139. DOLAN R. and HAYDEN, B., 1983. Patterns and Prediction of Shoreline Change. In CRC Hand Book of Coastal Processes and Erosion. P. D. Komar (Ed) Boca Raton, Fl, CRC Press, 123-149. DOLAN R., FENSTER, M. S. and HOLME, S. J., 1991. Temporal Analysis of Shoreline Recession and Accretion. Journal of Coastal Research, 7(3), 723-744. DOUGLAS , B. C., CROWELL, M. and LEATHERMAN, S. P., 1998. Considerations for Shoreline Prediction. Journal of Coastal Research, 14(3), 1025-1033.

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FOSTER, E. R. and SAVAGE, R. J., 1989. Methods of Historical Shoreline Analysis. Proceedings Coastal Zone 89, ASCE, 5, 4434-4448. HANSLOW D.J., (1994). Recession and Storm Bite Estimates for the Gosford Open Coast Beaches. Proc. 4th. NSW Coastal Management Conference, Terrigal. HANSLOW, D. J., CLOUT B., EVANS, P. and COATES, B., 1997. Monitoring Coastal Change Using Photogrammetry. Proceedings of the Institute of Australian geographers and New Zealand Geographical Society Second Joint Conference, Hobart, Australia, 1997, Department of Geography, The University of Waikato. Hayden, B., Dolan, R. and Felder, W., 1979. Spatial and Temporal Analyses of Shoreline Variations. Coastal Engineering, 2, 351-361. LORD, D. and KULMAR, M., 2000. The 1974 Storms Revisited: 25 Years Experience in Ocean Wave Measurement Along the South- East Australian Coast. Proceedings of the 27th International Conference on Coastal Engineering, Sydney Australia. pp559-572. NRC, 1990. Managing Coastal Erosion. US National Research Council, National Academy Press, Washington DC., 182p. SMITH, G. L. and ZARILLO, G. A., 1990. Calculating Long Term Shoreline Recession Rates using Aerial Photographic and Beach Profiling Techniques. Journal of Coastal Research, 6(1), 111-120. STIVE M.J.F., AARNINKOFF S.J.C., HAMM L., HANSON H., LARSON M., WIJNBERG K., NICHOLLS R.J. & CAPOBIANCO M., 2003. Variability of Shore and Shoreline Evolution. Coastal Engineering, 47, 211-235. THIELER, E. R. & DANFORTH, W. W. 1994. Historical Shoreline Mapping (I): Improving Techniques and Reducing Positioning Errors. Journal of Coastal Research, 10, (3), 549-563. THOM, B. G. and HALL, W., 1991. Behaviour of Beach Profiles During Accretion and Erosion Dominated Periods. Earth Surface Processes and Landforms, 16 113-127. WYLLIE, S. J., KULMAR, M. A. and DAVIDSON, P. J., 1992. Development of Design Offshore Wave and Ocean Level Conditions for the New South Wales Coastal Zone. Proceedings Coastline 92, NSW Coastal Management Conference, Kiama, NSW.

ACKNOWLEDGEMENTS The author wishes to thank to Bob Clout and Chris Gray for undertaking the photogrammetry and Peter Evans, Doug Lord and Bruce Thom for reviewing the draft paper. The views expressed in this paper are those of the author and not necessarily those of the NSW Department of Natural Resources.
