Natural Hazards

, Volume 61, Issue 2, pp 425–439 | Cite as

Spatial and temporal changes in flooding and the affecting factors in China

  • Chengjing Nie
  • Hairong Li
  • Linsheng Yang
  • Shaohong Wu
  • Yi Liu
  • Yongfeng Liao
Original Paper


Spatial and temporal changes in flood events in China are becoming increasingly important due to the rapid climate warming that is occurring. This study was conducted to consider changes in flood events and the factors affecting such changes. To accomplish this, China was divided into natural and social-economic flood regions: north China, northwest China, northeast China, southwest China, central China, east China, south China, and Taiwan, Hong Kong and Macau. Spatial and temporal changes in flood patterns were rebuilt during 1980–2009, and Fast Fourier Transform Filtering was then employed to stimulate the changes in floods during this period. The factors affecting flooding were then analyzed quantitatively. The results showed that, based on the time series for China as a whole, flooding was more serious during 1990–1999 than 1980–1989 and 2000–2009. However, in different regions, the trends in flooding differed greatly. Based on spatial changes, the areas hardest hit by floods were northeast China in the 1980s, northeast China, central China and east China in the 1990s, and central China after 2000. In China, the main flood-affecting factors were meteorological, ecological, population, water conservation facilities, and policy factors. However, the main affecting factors differed by region. Overall, the complex spatial and temporal features of flood variations and various affecting factors demand proper national and regional governmental action in the face of the changing flood patterns in China. The results of the present study provide valuable information to flood policymakers and flood disaster researchers.


Flood disaster Spatial and temporal change Affecting factors China 



We are grateful to the Knowledge Innovation Program of the Chinese Academy of Sciences (KZCX2-YW-Q03-01) and the National Key Technology R&D Program (2008BAK50B05) for providing funding. We thank the Climate Data Center of the National Meteorological Center of the China Meteorological Administration and Data Sharing Infrastructure of Earth System Science for providing data. We also thank Naomi Brodkey for her help in editing the paper. We would like to specially thank to the anonymous reviewers for valuable comments and suggestions, which considerably improved the quality of the paper.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Chengjing Nie
    • 1
  • Hairong Li
    • 1
  • Linsheng Yang
    • 1
  • Shaohong Wu
    • 1
  • Yi Liu
    • 1
  • Yongfeng Liao
    • 2
  1. 1.Institute of Geographic Sciences and Natural Resources ResearchCASBeijingChina
  2. 2.National Disaster Reduction Center of ChinaBeijingChina

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