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近60a来中国洪涝灾情变化趋势持续性和周期性研究
引用本文:邱海军,曹明明,胡胜,王彦民,郝俊卿,刘闻.近60a来中国洪涝灾情变化趋势持续性和周期性研究[J].地球与环境,2014,42(1):17-24.
作者姓名:邱海军  曹明明  胡胜  王彦民  郝俊卿  刘闻
作者单位:1. 西北大学城市与环境学院, 西安 710127;2. 陕西理工学院化学与环境科学学院, 陕西汉中 723000;3. 西安财经学院商学院, 西安 710061
基金项目:西北大学科学研究基金(12NW32)、西北大学科研启动基金(PR12076)、国家自然科学基金(41270513)和陕西省社会科学界2012年度重大理论与现实问题研究项目(2012Z029)共同资助。
摘    要:本文利用Hurst指数和小波分析工具对洪涝灾情的1950~2010年的变化动态作了分析,揭示了灾情序列的趋势持续性、特征时间尺度、周期特征和突变点,同时还定性地预测了洪涝灾情的未来走势。研究结果发现:1)根据Hurst指数计算结果,受灾面积时间序列的Hurst指数为0.9338,具有很强的正持续性。未来有进一步增加的趋势。因灾死亡人口数时间序列的Hurst指数为0.4845,具有很弱的反持续性。而房屋倒塌间数时间序列的Hurst指数为0.6124,具有较弱的正持续性,未来有较弱的减少趋势。2)小波分析方法具有较好时空域特性,可以描述洪涝灾害灾情变化的多尺度特征,将隐含在灾情序列中随时间变化的周期震荡显现出来,并确定灾情序列中的突变点位置,为深入探索中国洪涝灾害的时空复杂性提供了全新的理论工具。3)中国洪涝灾害灾情都存在多时间尺度特征,不同的时间尺度表现为不同的循环交替,大尺度的周期变化嵌套着小尺度的周期变化。总体上表现为由小尺度的震荡剧烈,没有明显的规律到大尺度出现明显规律后继续增强或先升后降。4)60 a来,中国洪涝灾害受害面积总体上保持着增加的趋势。在9 a和25 a上分别存在着第1和第2主周期。中国洪涝灾害因灾死亡人口总体上保持着明显减少的趋势。在8 a和18 a上分别存在着第1和第2主周期。中国洪涝灾害倒塌房屋总数总体上保持着减少的趋势。在8 a、17 a和25 a上分别存在着第1、第2和第3主周期。

关 键 词:洪涝灾害  多时间尺度  小波分析  Hurst指数
收稿时间:2013/2/7 0:00:00
修稿时间:2013/6/20 0:00:00

Susceptibility and Periodicity of Flood Disasters Since the 1950 s in China
QIU Hai-jun,CAO Ming-ming,HU Sheng,WANG Yan-ming,HAO Jun-qing,LIU Wen.Susceptibility and Periodicity of Flood Disasters Since the 1950 s in China[J].Earth and Environment,2014,42(1):17-24.
Authors:QIU Hai-jun  CAO Ming-ming  HU Sheng  WANG Yan-ming  HAO Jun-qing  LIU Wen
Institution:1. College of Urban and Environment Science, Northwest University, Xi''an 710127, China;2. School of Chemistry and Environmental Science, Shaanxi University of Technology, Hanzhong 723001, China;3. School of Business, Xi''an Financial and Economic University, Xi''an 710061, China
Abstract:This paper analyzed the change of flood damage by using wavelet analysis and Hurst index from 1950 to 2010, revealing susceptibility, multiple time scales, cycle characteristics and mutation of time sequence of flood damage. The results showed that:1) according to the results, the Hurst index of the affected area is 0.9338, with a very positive sustainability and an increasing trend. Hurst index of population death is 0.4845, with a weak reverse sustainability and a weak increasing trend. Hurst index of the collapsed house is 0.6124, with a weak positive sustainability and a weak declining trend; 2) the wavelet analysis method has better multi-scale features that can describe the flood disasters in change, and identify mutations in the disaster sequence point position, not only to extract the different disaster sequence variations, also also to predict disaster indicators of change in the short term, and provide a new tool to complexity theory; 3) large-scale nesting cycle of the small-scale cycle. Overall small-scale performs shock severely, there is no obvious rule to large-scale significance or to enhance or increase first and then decrease; 4) the flood affected areas in China generally maintain an increasing trend. There exist the main 1 and 2 periods at the 9th and 25th years.The population death in general maintains a marked decline. There exist the main 1 and 2 periods at the 8th and 18th years. The collapsed houses on the whole maintain a decreasing trend. There exist the main 1, 2 and 3 periods at the 8th and 17th and 25th years, respectively.
Keywords:flood damage  multiple time scale  wavelet analysis  Hurst index
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