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Natural Hazards

, Volume 92, Issue 2, pp 1011–1038 | Cite as

Human damage assessments of coastal flooding for Hong Kong and the Pearl River Delta due to climate change-related sea level rise in the twenty-first century

  • Qiwei YuEmail author
  • Alexis K. H. Lau
  • Kang T. Tsang
  • Jimmy C. H. Fung
Original Paper

Abstract

The adverse impact of climate change-associated extreme weather events is becoming more significant globally, particularly the flood impact on coastal and low-lying areas such as the Pearl River Delta (PRD). This study applied the framework to obtain order-of-magnitude estimations of human damages from future flood disasters caused by sea level rise for Hong Kong and the PRD region in southern China by 2050 and 2100. The assessment framework employs statistical analysis to combine global historical flood damage data with national development indicators and local sea level characteristics to assess the potential damages. Following the terminology of the Intergovernmental Panel on Climate Change Special Report on Extreme Events, the three determinants of disaster risk (climate extreme, exposure and vulnerability) are quantified in our framework. It is found that without adaptation, sea level rise will significantly increase the flood risk in this region. For instance, in the PRD region, with a 75-cm sea level rise by 2100, the deaths and displacements from a 100-year flood are estimated to be around 200 and 1.5 million, respectively. Our results provide motivation for regional authorities to adopt a long-term adaptation plan to reduce exposure and vulnerability to flooding, thus managing the risks in this region. Furthermore, with appropriate datasets available, our framework allows the assessment of the effects of flooding in other areas and/or the quantitative evaluation of potential losses from other climate-related hazards such as heat waves.

Keywords

Climate change Flood risk Damage assessment Statistical data analysis Order-of-magnitude estimation 

Notes

Acknowledgements

Funding was provided by Hong Kong University of Science and Technology (Grant No. FSGRF12IPO03) and United International College, Beijing Normal University-Hong Kong Baptist University (Grant No. R201313).

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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Atmospheric Research Center, HKUST Fok Ying Tung Graduate SchoolNansha IT ParkNansha, GuangzhouChina
  2. 2.Division of EnvironmentThe Hong Kong University of Science and TechnologyKowloonChina
  3. 3.Department of Statistics, United International CollegeBeijing Normal University-Hong Kong Baptist UniversityZhuhaiChina

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