Long-term flood-hazard modeling for coastal areas using InSAR measurements and a hydrodynamic model: The case study of Lingang New City, Shanghai

Long-term flood-hazard modeling for coastal areas using InSAR measurements and a hydrodynamic model: The case study of Lingang New City, Shanghai
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使用 InSAR 测量和水动力模型对沿海地区进行长期洪水灾害建模:以上海临港新城为例

DOI:
10.1016/j.jhydrol.2019.02.015
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发表时间:
2019-04
影响因子:
6.4
通讯作者:
Pepe Antonio
Pepe Antonio
中科院分区:
地球科学1区
文献类型:
--
作者:
Yin Jie;Zhao Qing;Yu Dapeng;Lin Ning;Kubanek Julia;Ma Guanyu;Liu Min;Pepe Antonio

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本文研究了上海临港新城的长期沿海洪水风险,考虑了100年和1000年的沿海洪水重现期、局部海平面上升预测和长期地面沉降预测。利用2012年获得的Tandem-X卫星数据生成高分辨率地形图,使用多传感器干涉合成孔径雷达位移时间序列获得2007至2017年间的地面形变率。然后,这两个数据集被用来预测本世纪30年代和20世纪50年代的地面形变率。采用二维洪水淹没模型(FroudMap-Inertial)对两种情况下的沿海洪水淹没进行了预报。结果表明,随着时间的推移,海平面上升和地面下沉可能会对沿海洪水造成轻微但非线性的影响。洪水风险将主要由未来洪水平原人口和财产的暴露和脆弱性决定。虽然洪水风险估计显示出一些不确定性,特别是对长期预测,但这里提出的方法可以适用于其他沿海地区,这些地区的海平面上升和地面沉降正在气候变化和城市化的背景下演变。
In this paper, we study long-term coastal flood risk of Lingang New City, Shanghai, considering 100- and 1000-year coastal flood return periods, local seal-level rise projections, and long-term ground subsidence projections. TanDEM-X satellite data acquired in 2012 were used to generate a high-resolution topography map, and multi-sensor InSAR displacement time-series were used to obtain ground deformation rates between 2007 and 2017. Both data sets were then used to project ground deformation rates for the 2030s and 2050s. A 2-D flood inundation model (FloodMap-Inertial) was employed to predict coastal flood inundation for both scenarios. The results suggest that the sea-level rise, along with land subsidence, could result in minor but non-linear impacts on coastal inundation over time. The flood risk will primarily be determined by future exposure and vulnerability of population and property in the floodplain. Although the flood risk estimates show some uncertainties, particularly for long-term predictions, the methodology presented here could be applied to other coastal areas where sea level rise and land subsidence are evolving in the context of climate change and urbanization.
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