Long-term flood-hazard modeling for coastal areas using InSAR measurements and a hydrodynamic model: The case study of Lingang New City, Shanghai
journal contributionposted on 24.04.2019, 12:23 by Jie Yin, Qing Zhao, Dapeng YuDapeng Yu, Ning Lin, Julia Kubanek, Guanyu Ma, Min Liu, Antonio Pepe
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.
This work was supported by the National Key Research and Development Program of China (Grant no: 2017YFE0100700), the National Natural Science Foundation of China (Grant no: 41871164; 41801337; 51761135024), the Humanities and Social Science Project of Education Ministry of China (Grant no: 17YJAZH111), the Research Grants of Science and Technology Commission of Shanghai Municipality through Project 18ZR1410800, the UK Natural Environment Research Council under the Environmental Risks to Infrastructure Innovation Program (Grant no: NE/M008770/1; NE/N013050/1; NE/R009600/1), the Key Laboratory of Land Subsidence Monitoring and Prevention, Ministry of Land and Resources through Project KLLSMP201503, the Fund of the Director of the Key Laboratory of Geographic Information Science (Ministry of Education), East China Normal University (Grant no: KLGIS2017C03), and the National Science Foundation of the United States (EAR-1520683).
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering