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

Jie Yin, Qing Zhao, Dapeng Yu, Ning Lin, Julia Kubanek, Guanyu Ma, Min Liu, Antonio Pepe

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)593-604
Number of pages12
JournalJournal of Hydrology
Volume571
DOIs
StatePublished - Apr 2019

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

Keywords

  • Coastal flooding
  • FloodMap
  • InSAR
  • Land subsidence
  • Sea level rise

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