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研究进展-Nonstationarity and clustering of flood characteristics and relations with the climate indices in the Poyang Lake basin, China
发布时间: 2017-08-06  

Jianyu Liu, Qiang Zhang, Vijay P. Singh, Xihui Gu, Peijun Shi

 

[Jianyu Liu, Xihui Gu]. Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China.

[Qiang Zhang, Peijun Shi]. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China.

[Qiang Zhang, Peijun Shi]. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China.

[Qiang Zhang, Peijun Shi]. Faculty of Geographical Science, Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing 100875, China.

[Vijay P. Singh]. Department of Biological and Agricultural Engineering and Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA.

 

ABSTRACTThe magnitude, occurrence rate and occurrence timing of floods in the Poyang Lake basin were analyzed. The flood series were acquired by annual and seasonal maximum flow (AMF) sampling and peaks-over-threshold (POT) sampling. Nonstationarity and uncertainty were analyzed using kernel density estimation and the bootstrap resampling methods. Using the relationships between flood indices and climate indices, i.e. El Niño/Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian Ocean Dipole (IOD) and Pacific Decadal Oscillation (PDO), the potential causes of flooding were investigated. The results indicate that (1) the magnitudes of annual and seasonal AMF- and POT-based sampled floods generally exhibit an increasing tendency; (2) the highest occurrence rates of floods identified were during the 1990s, when the flood-affected crop area, flood-damaged crop area and crop failure area reached the highest levels; and (3) ENSO and IOD are the major climate indices that significantly correlate with the magnitude and frequency of floods of the following year.

 

Published in Hydrological Sciences Journal, 2017, https://doi.org/10.1080/02626667.2017.1349909.

 


 
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