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Assessment of spatial and temporal variations of high water mark indicators

机译：评估高水位指标的时空变化

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摘要

The high water mark (HWM) is commonly used as a boundary for coastal management and planning. Due to the dynamic nature of the coastal environment, the determination of HWM can be difficult and may vary based on the indicators unique to the location. Using remote-sensing image analysis techniques, this study evaluates the spatial and temporal variation of HWM based on several indicators. These include vegetation lines, frontal dune toe, mean high water spring (MHWS)/mean higher high water (MHHW), and high water lines (HWL). Other linear boundaries defined by agencies for various applications are also used as indicators. For improved coastal property management, this study also uses an enhanced Spatial Continuity of the Swash Probability (SCSP) model as a HWM indicator by excluding the runup parameter regarding the Spatial Continuity of Tide Probability (SCTP). In order to better account for sudden shape changes, the extended instead of the simple Hausdorff distance has been used to measure the seasonal variation of HWM position. Monte Carlo simulation of DEM data and Fractal Dimension (FD) techniques were used to examine spatial uncertainties due to both the precision of input data and the processing techniques used. Two case study areas in Western Australia with varying coastal conditions have been selected to evaluate the approach. These are Coogee Beach in South Fremantle and Cooke Point in Port Hedland. Results for both study areas indicate that spatial variations of HWM due to seasonal changes are about one order of magnitude larger than variations due to uncertainties in the input data. This behaviour, while present at both study areas, is more significant at Coogee Beach having a sandy beach with high wave energy.
机译：高水位线（HWM）通常用作沿海管理和规划的边界。由于沿海环境的动态性质，HWM的确定可能很困难，并且可能会根据该位置的唯一指标而有所不同。这项研究使用遥感图像分析技术，基于几个指标评估了HWM的时空变化。这些包括植被线，前沙丘脚趾，平均高水位弹簧（MHWS）/平均高水位（MHHW）和高水位线（HWL）。代理商为各种应用定义的其他线性边界也用作指标。为了改善沿海物业管理，本研究还通过将有关潮汐概率空间连续性（SCTP）的启动参数排除在外，将增强的冲刷概率空间连续性（SCSP）模型用作HWM指标。为了更好地说明形状的突然变化，已使用扩展距离而不是简单的Hausdorff距离来测量HWM位置的季节性变化。由于输入数据的精度和所使用的处理技术的原因，DEM数据的蒙特卡罗模拟和分形维数（FD）技术用于检查空间不确定性。已选择了西澳大利亚州两个沿海条件不同的案例研究区域来评估该方法。这些是南弗里曼特尔的库吉海滩和黑德兰港的库克角。两个研究区域的结果均表明，由于季节性变化而导致的HWM的空间变化要比由于输入数据的不确定性而导致的变化大一个数量级。尽管在两个研究区域都存在这种行为，但在具有高波能沙滩的库吉海滩上，这种行为更为明显。

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  • 来源
    《Ocean & coastal management》 |2013年第ptaa期|77-89|共13页
  • 作者

    Xin Liu; Jianhong (Cecilia) Xia; Michael Kuhn; Graeme Wright; Lesley Arnold;

  • 作者单位

    Department of Spatial Sciences, Curtin University, Bentley, WA 6845, Australia;

    Department of Spatial Sciences, Curtin University, Bentley, WA 6845, Australia;

    Department of Spatial Sciences, Curtin University, Bentley, WA 6845, Australia;

    Research and Development, Curtin University, Bentley, WA 6845, Australia;

    Ceospatial Frameworks, Perth, WA 6000, Australia;

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