Nonstationarity and clustering of flood characteristics and relations with the climate indices in the Poyang Lake basin,China |
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| Authors: | Jianyu Liu Vijay P Singh Xihui Gu Peijun Shi |
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| Institution: | 1. Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou, China;2. Department of Biological and Agricultural Engineering and Zachry Department of Civil Engineering, Texas A&3. M University, College Station, Texas, USA;4. Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing, China;5. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China;6. Faculty of Geographical Science, Academy of Disaster Reduction and Emergency Management, Beijing Normal University, Beijing, China |
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| Abstract: | The magnitude, occurrence rate and occurrence timing of floods in the Poyang Lake basin were analysed. The flood series were acquired by annual and seasonal maximum flow (AMF) sampling and peaks-over-threshold (POT) sampling. Nonstationarity and uncertainty were analysed 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. EDITOR A. Castellarin ASSOCIATE EDITOR T. Kjeldsen |
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| Keywords: | flooding behaviour nonstationarity clustering effect kernel density estimation climate indices |
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