Article(id=1314918423004545510, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1740758400000, receivedDateStr=2025-03-01, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1791430582046, onlineDateStr=2026-10-08, pubDate=1763568000000, pubDateStr=2025-11-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1791430582046, onlineIssueDateStr=2026-10-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1791430582046, creator=13701087609, updateTime=1791430582046, updator=13701087609, issue=Issue{id=1314918356222829028, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='11', pageStart='5921', pageEnd='6512', issueExtLink='null', onlineDate='null', pubDate='1763568000000', pubDateStr='2025-11-20', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1791430566125, creator='13701087609', updateTime=1791431596967, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1314922679942078535, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1314922679942078536, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1314918356222829028, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=6262, endPage=6274, ext={EN=ArticleExt(id=1314918423210066407, articleId=1314918423004545510, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Dynamic evolution of vegetation in major watersheds in China and suitability assessment of its mutation method, columnId=1234106388083954308, journalTitle=China Environmental Science, columnName=Environmental Ecology, runingTitle=null, highlight=null, articleAbstract=
Based on the long-series normalized vegetation index (NDVI) and climate, topographic and human activity factor data, this study studied the dynamic change characteristics and temporal stability of vegetation NDVI in China's first-class watersheds from 2000~2022 by using Theil-Sen Media trend analysis+Mann-Kendall test, geographic detector and temporal stability, and identified the representative sub-watersheds of nine first-class watersheds in China. The findings indicated that: in terms of time, the NDVI values of vegetation in the nine major river basins of China showed a significant upward trend. Among them, the Yellow River Basin had the highest growth rate of 0.0052a-1, followed by the Songliao River Basin with a growth rate of 0.0032a-1, while the Huaihe River Basin had the lowest growth rate, at only 0.0010a-1. Spatially, the NDVI of vegetation exhibited a declining trend from the southeast to the northwest, and the vegetation change was mainly improved, accounting for 52.02%, and the flow between different levels of vegetation cover was mainly to the higher grades. The representative sub-basins of vegetation stability in the major river basins of China are as follows: Southwest River Basins (No. 35 Lancang River Basin), Inland River Basins (No. 15 Tarim River Basin), Yangtze River Basin (No. 8 Han River Basin), Southeast River Basins (No. 24 Min River Basin), Huai River Basin (No. 16 Yi River Basin), Hai River Basin (No. 32 Daqing River Basin), Songliao River Basin (No. 21 Songhua River Basin), Pearl River Basin (No. 12 Xijiang River Basin), and Yellow River Basin (No. 7 Fen River Basin). Based on the mutation methods of different river basins, it was concluded that the ordered clustering method and the sliding T-test were more suitable for the detection of vegetation change mutations in most of the river basins, among which the Pettt test was suitable for the southeast river basins, the Haihe River, inland rivers, Songliao River and Yangtze River basins, the Huaihe River and Southwest river basins were suitable for the ordered clustering method and the sliding T-test method, and the Yellow River basin was suitable for the sliding T-test.
, authors=Hao-cheng KE
1, *, Chun-hui YUAN
1, Mao-lin WANG
1, Xiao-yan MA
1, Fei WANG
1, Chen YANG
1, Zhan-bin LI
2, Peng LI
2, authorsList=Hao-cheng KE, Chun-hui YUAN, Mao-lin WANG, Xiao-yan MA, Fei WANG, Chen YANG, Zhan-bin LI, Peng LI, authorCompany=null, correspAuthors=Hao-cheng KE, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1314918423495279080, articleId=1314918423004545510, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=中国主要流域植被动态演变及其突变方法适宜性评估, columnId=1234106388268503686, journalTitle=中国环境科学, columnName=环境生态, runingTitle=null, highlight=null, articleAbstract=
基于长序列归一化植被指数(NDVI)数据,运用Theil-Sen Media趋势分析+Mann-Kendall检验、时间稳定性、有序聚类法、滑动T检验多种突变方法,研究了2000~2022年中国主要流域植被NDVI的动态变化特征和时间稳定性,并识别中国主要流域的代表性子流域.研究结果表明:时间上,中国主要流域植被NDVI值均呈显著上升趋势,其中,黄河流域增长速率最高,为0.0052a-1,松辽河流域次之,为0.0032a-1,淮河流域最小,增长速率仅为0.0010a-1.空间上,植被NDVI呈现出由东南到西北递减的趋势特征,植被变化以改善为主,占比为52.02%,且各等级植被覆盖间的流动以流向更高等级为主.中国主要流域植被稳定性的代表性子流域分别为:西南诸河流域(35# 澜沧江流域)、内陆河流域(15# 塔里木河流域)、长江流域(8# 汉江流域)、东南诸河流域(24# 闽江流域)、淮河流域(16# 沂河流域)、海河流域(32# 大清河流域)、松辽河流域(21# 松花江流域)、珠江流域(12# 西江流域)、黄河流域(7# 汾河流域).综合不同流域突变方法,得出有序聚类法和滑动T检验法更适用于大部分流域植被变化突变检测,其中东南诸河流域Pettitt检验法适宜,海河、内陆河、珠江、长江流域适宜有序聚类法,松辽河、淮河、西南诸河流域适宜有序聚类法和滑动T检验法,黄河流域适宜滑动T检验法.
, authors=柯浩成
1, *, 袁春慧
1, 王茂林
1, 马晓燕
1, 王飞
1, 杨陈
1, 李占斌
2, 李鹏
2, authorsList=柯浩成, 袁春慧, 王茂林, 马晓燕, 王飞, 杨陈, 李占斌, 李鹏, authorCompany=null, correspAuthors=柯浩成, authorNote=
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1, *, address=
1.College of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou 730050, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1314918424015372787, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1314918423004545510, authorId=1314918423851794928, language=CN, stringName=柯浩成, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=
1, *, address=
1.兰州理工大学能源与动力工程学院,甘肃 兰州 730050, bio={"content":"
柯浩成(1986-),男,甘肃武威人,副教授,博士,主要从事寒旱区水资源的高效利用研究.发表论文20余篇.kehc@lut.edu.cn.
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柯浩成(1986-),男,甘肃武威人,副教授,博士,主要从事寒旱区水资源的高效利用研究.发表论文20余篇.kehc@lut.edu.cn.
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