[1]周向阳,张荣,雷文娟.极端降水事件概率分布识别方法对比研究[J].自然灾害学报,2018,(05):158-168.[doi:10.13577/j.jnd.2018.0518]
 ZHOU Xiangyang,ZHANG Rong,LEI Wenjuan.Comparisons on probability distributions of extreme precipitation events identified by different methods[J].,2018,(05):158-168.[doi:10.13577/j.jnd.2018.0518]
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极端降水事件概率分布识别方法对比研究
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《自然灾害学报》[ISSN:/CN:23-1324/X]

卷:
期数:
2018年05期
页码:
158-168
栏目:
出版日期:
2018-10-28

文章信息/Info

Title:
Comparisons on probability distributions of extreme precipitation events identified by different methods
作者:
周向阳124 张荣1 雷文娟3
1. 贵州大学 资源与环境工程学院, 贵州 贵阳 550025;
2. 四川大学 水力学与山区河流开发保护国家重点实验室, 四川 成都 610065;
3. 四川大学 建筑与环境学院, 四川 成都 610065;
4. 贵州大学 贵州省公共大数据重点实验室, 贵州 贵阳 550025
Author(s):
ZHOU Xiangyang124 ZHANG Rong1 LEI Wenjuan3
1. College of Resource and Environmental Engineer, Guizhou University, Guiyang 550025, China;
2. State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu 610065, China;
3. College of Architecture & Environment, Sichuan University, Chengdu 610065, China;
4. Guizhou Provincial Key Laboratory of Pirblic Big Data, Guizhou University, Guiyang 550025, China
关键词:
极端降水概率分布假设检验方法对比降水序列
Keywords:
extreme precipitation eventsprobability distributionhypothesis testmethod comparisonprecipitation time series
分类号:
P467;X16
DOI:
10.13577/j.jnd.2018.0518
摘要:
识别极端降水的概率分布对于区域水旱灾害的预测防治具有重要意义。研究针对广泛采用的L-矩分析、KS检验和卡方检验3种方法,基于四川盆地24个气象站1951—2011年的日数据,对最大日降水量、连续最长无雨天数的概率分布分别进行了识别和误差分析。结果表明:KS检验结果的相对误差最小且大都小于0.05,并且与基于卡方检验的结果接近;基于L-矩分析识别结果的误差较大,尤其是连续最长无雨天数的平均误差在多个回归水平下超过10%;此外,具有相同概率分布的站点,基于KS和卡方检验结果的空间连续性更好。上述结果和一些研究优先推荐L-矩分析识别水文序列概率分布的结论不一致,原因是这些研究主要针对径流而非最极端的降水情况,且降水序列的空间异质性大。
Abstract:
Identifying the probability distribution of extreme precipitation events is crucial to regional floods and droughts prediction and prevention. In this study, three widely used methods (L-momentum analysis, KS test and Chi-Square test) are compared by test the probability distribution of maximum rainfall in a day, Max1d, and maximum consecutive drought days, Max CDD, on the basis of daily data from 1951-2011. The results reveal that the KS test exhibits the minimum relative error of less than 0.05 in most situations, Chi-square test shows close level. L-momentum analysis displays the largest error, especially in Max CDD which is more than 0.1 in several return periods. On the other hand, those stations showing the same probability distribution exhibit a better spatial continuity when the results are based on the KS test and Chi-square test. These results also reflect that KS test and Chi-square test are more appropriate than L-momentum analysis when identify the probability distribution of extreme precipitation events. However, this is different from the conclusions of some literatures, which recommend L-momentum analysis on testing the probability of hydrological time series. The main reason is that those studies are mostly based on runoff instead of extreme precipitation, and the precipitation time series also exhibits substantial spatial heterogeneity.

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备注/Memo

备注/Memo:
收稿日期:2017-10-31;改回日期:2018-04-15。
基金项目:贵州省水利科技经费项目(KT201707);国家自然科学基金项目(41701558);贵州省科技计划项目(黔科合LH字[2017]7290);贵州省国内生态学一流学科建设项目(GNYL[2017]007)
作者简介:周向阳(1982-),男,讲师,博士,主要从事陆面水文过程的不确定性与灾害问题研究.E-mail:zhouxy6@gzu.edu.cn
更新日期/Last Update: 1900-01-01