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首页> 外文期刊>Journal of the American Water Resources Association >A Rapid Response Survey to Characterize the Impacts of the 2017 High Water Event on Lake Ontario
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A Rapid Response Survey to Characterize the Impacts of the 2017 High Water Event on Lake Ontario

机译：快速响应调查，以表征2017年高水位事件对安大略湖的影响

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摘要

In the spring and summer of 2017, communities along the Lake Ontario shoreline suffered from the worst flood event on record. In late May, daily water levels reached their highest point in over 100 years, and flooding continued throughout much of the summer as lake levels slowly declined, with inundation and erosion significantly impacting shoreline homes and businesses. In this work, we present results from a rapid response online survey of property owners along the New York Lake Ontario shoreline to quantify the perceived flood impacts of the 2017 extended high water event. The survey focused on the degree and spatial distribution of inundation and erosion; the duration and drivers of inundation; the associated damages to different property features, with an emphasis on shoreline protection; and the degree of disruption to business and other activities and services. Photographic documentation of inundation extent and property damage also was provided by survey respondents. We demonstrate the potential utility of this dataset by characterizing key features of inundation and erosion impacts across the shoreline, and by using classification and regression trees to explore the predictability of inundation and erosion based on property characteristics. This work is part of a larger effort to develop models of inundation and erosion that can support flood impact assessments across the shoreline and help communities better prepare for future extended high water events.
机译：在2017年春季和夏季，安大略湖沿岸的社区遭受了有记录以来最严重的洪灾。 5月下旬，每日水位达到100多年来的最高点，并且由于湖水位缓慢下降，整个夏季的大部分时间洪水泛滥，洪水和侵蚀严重影响了海岸线的房屋和企业。在这项工作中，我们展示了对安大略湖纽约湖沿岸的业主进行的快速在线调查的结果，以量化2017年高水位事件对洪水的感知影响。调查的重点是淹没和侵蚀的程度和空间分布；淹没的持续时间和驱动因素；对不同财产特征的相关损害，重点是海岸线保护；以及对业务及其他活动和服务的破坏程度。调查受访者还提供了淹没程度和财产损失的照相文件。通过表征整个海岸线的淹没和侵蚀影响的关键特征，并通过使用分类和回归树根据属性特征探索淹没和侵蚀的可预测性，我们证明了该数据集的潜在效用。这项工作是开发淹没和侵蚀模型的更大努力的一部分，该模型可以支持整个海岸线的洪水影响评估，并帮助社区更好地为将来的高水位事件做准备。

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