Article(id=1222963539686449519, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1222963536863678929, articleNumber=null, orderNo=null, doi=10.20040/j.cnki.1000-7709.2023.20221327, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1656345600000, receivedDateStr=2022-06-28, revisedDate=1659283200000, revisedDateStr=2022-08-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1769506829424, onlineDateStr=2026-01-27, pubDate=1682352000000, pubDateStr=2023-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769506829424, onlineIssueDateStr=2026-01-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769506829424, creator=13701087609, updateTime=1769506829424, updator=13701087609, issue=Issue{id=1222963536863678929, tenantId=1146029695717560320, journalId=1205116964453384197, year='2023', volume='41', issue='4', pageStart='1', pageEnd='220', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769506828752, creator=13701087609, updateTime=1769508076664, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1222968771057279321, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1222963536863678929, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1222968771057279322, tenantId=1146029695717560320, journalId=1205116964453384197, issueId=1222963536863678929, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=9, endPage=12, ext={EN=ArticleExt(id=1222963539917136251, articleId=1222963539686449519, tenantId=1146029695717560320, journalId=1205116964453384197, language=EN, title=Analysis of Nonstationary Standardized Precipitation Index in Yunnan Province Based on GAMLSS Model, columnId=1222925279849341011, journalTitle=Water Resources and Power, columnName=HYDROLOGY, WATER RESOURCES AND ENVIRONMENT, runingTitle=null, highlight=null, articleAbstract=

Drought index is crucial to the study of drought. With the influence of climate change and human activities, the frequency distribution of hydrological time series changes with time, so the nonstationary of drought index needs to be considered. The standardized precipitation index (S_SPI) considers that the precipitation obeys the Gamma distribution, the corresponding distribution function parameters are usually stationary and invariable. The actual distribution function parameters have a certain correlation with the time series. Therefore, based on the GAMLSS model, the nonstationary Gamma distribution model of precipitation series was constructed with time series as covariate. The nonstationary standardized precipitation index N_NSPI was calculated. Taking Yunnan Province as an example, the monthly N_NSPI and S_SPI during 1960 to 2019 were calculated respectively. Comparing the two indices, it is found that the overall trend of drought recognition results of the two indices is similar. However, in 1960~1985, the number and grade of droughts identified by N_NSPI were stronger than those identified by S_SPI, and the two were similar in 1986~2005. In 2006~2019, the number and grade of droughts identified by S_SPI gradually exceeded those identified by S_SPI. Further analysis shows that the N_NSPI with considering the time-varying distribution function parameters can more accurately reflect the actual drought situation.

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干旱指数对干旱的研究至关重要。随着气候变化和人类活动的影响，水文序列的频率分布随时间变化，因此需考虑干旱指数的非一致性。标准化降水指数S_SPI认为降水服从Gamma分布，对应的分布函数参数通常稳定不变，而实际的分布函数参数与时间序列具有一定相关性，因此利用GAMLSS模型以时间序列为协变量构建了降水序列的非一致性Gamma分布模型，在此基础上计算出非一致性标准化降水指数N_NSPI。以云南省为例，分别计算了1960~2019年的逐月N_NSPI、S_SPI，将两者进行对比分析，发现两者对干旱的识别结果总体趋势相近，但在1960~1985年N_NSPI识别的干旱数量和等级强于S_SPI，1986~2005年两者相近，而在2006~2019年，S_SPI识别的干旱数量和等级逐渐超过N_NSPI，进一步分析表明，考虑了分布函数参数随时间变化的N_NSPI能更精确反映实际干旱情况。

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陈灏（1994-），男，硕士、工程师，研究方向为水资源规划与管理，E-mail：chenhaoqy@whu.edu.cn

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陈灏（1994-），男，硕士、工程师，研究方向为水资源规划与管理，E-mail：chenhaoqy@whu.edu.cn

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