Modelling shoreline evolution to enhance flood risk assessment
Modelling shoreline evolution to enhance flood risk assessment
复制标题
模拟海岸线演变以加强洪水风险评估
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
M. Panzeri
中科院分区：
文献类型：
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作者：
S. Stripling;M. Panzeri
传统的洪水风险评估认为海岸防御是静态的功能，只是用指定的海拔和坡度表示的前滨。然而，海滩的海拔会随着时间的推移而迅速变化，可能会季节性波动，并且经常在较长的时间内失去或增加体积。它们的动态性质最终影响到海岸侵蚀和洪水的风险。在区域洪水风险评估中，海滩为各种后滨特征（如海堤、软质悬崖和沙丘）提供保护，代表这些防御前沿的海滩动态的能力非常重要。在区域范围内，还必须考虑在漫长的海岸线上可能遇到的各种后滨环境，以及它们各自的过程如何影响洪水风险，特别是如果它们是可侵蚀的。目前正在制定一个综合框架，将沿海过程的动态联系数字模型和统计分析方法结合起来，通过考虑沿海演变和前滨地貌动力学，加强区域洪水风险评估。该框架完全由商业上可获得的地理信息系统软件运行，管理模型操作和数字输出;因此，模型系统内也有标准的地理信息系统分析和数据库能力。本文概述了模块化框架的基础，并演示了如何加强洪水风险评估。
Traditional flood-risk assessment considers coastal defences to be static features with foreshores represented simply with an assigned elevation and slope. However, beach elevations can vary rapidly over time, perhaps fluctuating seasonally, and often losing or gaining volume over a longer time period. Their dynamic nature ultimately influences the risk of coastal erosion and flooding. In a regional flood-risk assessment, in which beaches offer protection to a variety of backshore features such as seawalls, soft cliffs, and dunes, the ability to represent the beach dynamics fronting these defences is important. At regional scale, it is also necessary to consider the various backshore environments that may be encountered over a long stretch of coastline, and how their individual processes affect flood risk, particularly if they are erodible. An integrated framework of dynamically linked numerical models of coastal processes and statistical analysis methods is being developed to enhance regional flood-risk assessment via consideration of coastal evolution and foreshore morphodynamics. The framework is run entirely from within commercially available geographical information system software where model operation and numerical output is managed; standard geographical information system analysis and database capabilities are therefore also available within the modelling system. This paper outlines the basis of the modular framework, and demonstrates how flood-risk assessment is enhanced.