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Determination of the High Water Mark and Its Location Along a Coastline

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Determination of the High Water Mark and Its Location Along a Coastline Faculty of Science and Engineering Department of Spatial Sciences Determination of the High Water Mark and its Location Along a Coastline Xin Liu This thesis is presented for the degree of Doctor of Philosophy of Curtin University April 2013 Declaration To the best of my knowledge and belief this thesis contains no material previously published by any other person except where due acknowledgement has been made. This thesis contains no material which has been accepted for the award of any other degree or diploma in any university. Signature…………………………………………………………….. Date………………………………………………………………….. i ABSTRACT The High Water Mark (HWM) is an important cadastral boundary that separates land and water. It is also used as a baseline to facilitate coastal hazard management, from which land and infrastructure development is offset to ensure the protection of property from storm surge and sea level rise. However, the location of the HWM is difficult to define accurately due to the ambulatory nature of water and coastal morphology variations. Contemporary research has failed to develop an accurate method for HWM determination because continual changes in tidal levels, together with unimpeded wave runup and the erosion and accretion of shorelines, make it difficult to determine a unique position of the HWM. While traditional surveying techniques are accurate, they selectively record data at a given point in time, and surveying is expensive, not readily repeatable and may not take into account all relevant variables such as erosion and accretion. In this research, a consistent and robust methodology is developed for the determination of the HWM over space and time. The methodology includes two main parts: determination of the HWM by integrating both water and land information, and assessment of HWM indicators in one evaluation system. It takes into account dynamic coastal processes, and the effect of swash or tide probability on the HWM. The methodology is validated using two coastal case study sites in Western Australia. These sites were selected to test the robustness of the methodology in two distinctly different coastal environments. At the first stage, this research develops a new model to determine the position of the HWM based on the spatial continuity of swash probability (SCSP) or spatial continuity of tidal probability (SCTP) for a range of HWM indicators. The indicators include tidal datum-based HWMs, such as mean high water spring or mean higher high water, and a number of shoreline indicators, such as the dune toe and vegetation line. HWM indicators are extracted using object-oriented image analysis or Light Detection and Ranging (LiDAR) Digital Elevation Modelling, combined with tidal datum information. Field verified survey data are used to determine the swash heights and shoreline features, and provide confidence levels against which the swash height empirical model and feature extraction methods are validated. Calculations of inundation probability for HWM indicators are based solely on tide ii data for property management purposes; while swash heights are included for coastal hazard planning. The results show that the accuracy of swash height calculations is compromised due to gaps that exist in wave data records. As a consequence, two methods are utilised to interpolate for gaps in the wave data records: the wavelet refined cubic spline method and the fractal method. The suitability of these data interpolation methods for bridging the wave record data gaps is examined. The interpolation results are compared to the traditional simple cubic spline interpolation method, which shows different interpolation methods should be applied according to the duration of the gap in the wave record data. At the second stage of this research, all the HWM indicators, including the two new HWM indicators, SCSP and SCTP, are evaluated based on three criteria: precision, stability and inundation risk. These indicators are integrated into a Multi-Criteria Decision Making model to assist in the selection and decision process to define the most ideal HWM position. Research results show that the position of the dune toe is the most suitable indicator of the HWM for coastal hazards planning, and SCTP is the most ideal HWM for coastal property management purposes. The results from this research have the potential for significant socio-economic benefits in terms of reducing coastal land ownership conflicts and in preventing potential damage to properties from poorly located land developments. This is because the methodology uses a data-driven model of the environment, which allows the HWM to be re-calculated consistently over time and with consideration for historical and present day coastal conditions. iii ACKNOWLEDGEMENTS For the duration of this study, I have been fortunate to receive support, encouragement and advice from a number of people, to whom I wish to express sincere gratitude. Firstly and foremost my supervisor, Dr Jianhong (Cecilia) Xia who has provided constant support, encouragement and has challenged and discussed my research throughout the study program. I also appreciate my supervisors Professor Graeme Wright and Dr Lesley Arnold for their time and contribution in strengthening the methodology development in this study, and in editing and improving this thesis. My three supervisors’ critical thinking on details was very helpful in submitting a sound thesis. I would also like to acknowledge Ric Mahoney and Murray Dolling who acted as consultants to the research and provided advice on any issues based on their vast experience. Without their assistance, I would not have taken up the challenge and dipped into the unknown ‘high water’. A research project is hardly feasible without the necessary funding and there are a number of institutions I want to thank for their support. I would not have come to Australia without the Curtin International Postgraduate Research Scholarships offered by Curtin University and Landgate. I am also indebted to the Cooperative Research Centre for Spatial Information, activities of which are funded by the Commonwealth of Australia Cooperative Research Centres Programme. Thanks to all the staff members and postgraduate students in the Department of Spatial Sciences, Curtin University, for providing help and encouragement in times of need. Particularly I would like to thank Professor Bert Veenendaal, Associate Professor Michael Kuhn, Dr Tom Schut, Dr Robert Corner, and Dr Mick Filmer for their encouragement and assistance, including many hours discussing this research. Thank you to Caroline Rockliff, Pam Kapica, and Meredith Mulcahy for their assistance with my study life, especially to Lori Patterson, for her assistance with formatting, editing and associated issues. Special thanks also go to Val Macduff, Dr Sten Claessens, Saud Aboshiqah, Ting Lin, Xiaoying Wu, Chunmei Chen, Qian Sun, Robert Odolinski, Amir Khodabandeh, Dr Christian Hirt and many others for their friendship that did not stop at the lab iv door. The often very welcome distractions such as the rogaining and soccer training and barbecues will never be forgotten. Thanks are also extended to John Fenner, Russell Teede, Aaron Thorn, Doug Hardman, Allan Campbell, Rodney Hoath, Tia Byrd and other staff from Landgate, Department of Transport and Department of Planning for their assistance in providing the necessary data required for this research and advice and help on the questionnaire and methodology design. I would also like to acknowledge the Department of Water, Tremarfon Pty Ltd. and the many nameless participants who provided the data which provided the basis for this research. Their efforts are very much appreciated. My sincere thanks also go to Associate professor Jennifer Whittal at University of Cape Town, for the insights she has provided. Finally, I would like to thank all my family, especially to my parents, for their encouragement, love and support throughout this study. v RELATED PUBLICATIONS Refereed Conference Papers: Liu, X., J. Xia, G. Wright, L. Arnold, and R. Mahoney. 2011. Identification of onshore features for delineation of the land water interface and their spatial- temporal variation using high resolution imagery. Proceedings of 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 24-29 July 2011, Vancouver: IEEE. Liu, X., J. Xia, G. Wright, R. Mahoney, and L. Arnold. 2011. High water mark determination based on the wave runup height distribution and spatial continuity. Proceedings of Coasts and Ports 2011: Diverse and Developing: Proceedings of the 20th Australasian Coastal and Ocean Engineering Conference and the 13th Australasian Port and Harbour Conference, 28-30 September 2011, Perth: Engineers Australia. Journal papers: Liu, X., J. Xia, M. Kuhn, G. Wright, and L. Arnold. 2013. Assessment of Spatial and Temporal Variations of High Water Mark Indicators. Ocean & Coastal Management. In press. Liu, X. et al.. 2013. Comparison of Wave Height Interpolation with Wavelet Refined Cubic Spline and Fractal Methods. Submitted to Ocean Engineering. Liu, X., J. Xia, C. Blenkinsopp, L. Arnold, and G. Wright. 2012. High Water Mark Determination Based on the Principle of Spatial Continuity of the Swash Probability. Journal of Coastal Research. In press, doi: 10.2112/jcoastres-d- 12-00061.1. vi TABLE OF CONTENTS ABSTRACT .................................................................................................................. i ACKNOWLEDGEMENTS .......................................................................................
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