Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)

IF 2.7 4区 环境科学与生态学 Q2 WATER RESOURCES
Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha
{"title":"Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)","authors":"Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha","doi":"10.2166/wcc.2024.462","DOIUrl":null,"url":null,"abstract":"\n Climate change (CC) significantly influences agricultural water productivity, necessitating increased irrigation. Therefore, the present study was undertaken to assess the trend and change-point analyses of weather variables such as temperature (T), rainfall (R), and reference evapotranspiration (ET0) using 31-year long-term data for semi-arid climate. The analysis was carried out employing Mann–Kendall (MK), Modified Mann–Kendall (MMK), Innovative Trend Analysis (ITA), and Innovative Polygon Trend Analysis (IPTA) methods. Homogeneity tests, including Pettitt's test, Standard Normal Homogeneity Test (SNHT) , Buishand range test, and Von Neumann Ratio Test (VNRT), were employed to detect change points (CPs) in the time series data. The results indicated that, for maximum temperature, MK and MMK revealed a positive trend for September and July, respectively, while minimum temperatures indicated increasing trends in August and September. Rainfall exhibited an increasing trend during the Zaid season (April–May). ET0 exhibited a negative trend in January. ITA and IPTA displayed a mixture of positive and negative trends across months and seasons. The change-point analysis revealed that for Tmax, the CP occurred in 1998 for time-series data for the month of April. Likewise, for Tmin, the change points for April and August time series were found in 1997.","PeriodicalId":49150,"journal":{"name":"Journal of Water and Climate Change","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water and Climate Change","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.2166/wcc.2024.462","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 0

Abstract

Climate change (CC) significantly influences agricultural water productivity, necessitating increased irrigation. Therefore, the present study was undertaken to assess the trend and change-point analyses of weather variables such as temperature (T), rainfall (R), and reference evapotranspiration (ET0) using 31-year long-term data for semi-arid climate. The analysis was carried out employing Mann–Kendall (MK), Modified Mann–Kendall (MMK), Innovative Trend Analysis (ITA), and Innovative Polygon Trend Analysis (IPTA) methods. Homogeneity tests, including Pettitt's test, Standard Normal Homogeneity Test (SNHT) , Buishand range test, and Von Neumann Ratio Test (VNRT), were employed to detect change points (CPs) in the time series data. The results indicated that, for maximum temperature, MK and MMK revealed a positive trend for September and July, respectively, while minimum temperatures indicated increasing trends in August and September. Rainfall exhibited an increasing trend during the Zaid season (April–May). ET0 exhibited a negative trend in January. ITA and IPTA displayed a mixture of positive and negative trends across months and seasons. The change-point analysis revealed that for Tmax, the CP occurred in 1998 for time-series data for the month of April. Likewise, for Tmin, the change points for April and August time series were found in 1997.
利用曼-肯德尔族检验和创新趋势评估技术对新布帕尼亚指挥部(印度)的气象变量进行趋势和变化点分析
气候变化(CC)极大地影响了农业用水生产率,因此必须增加灌溉。因此,本研究利用半干旱气候的 31 年长期数据,对气温(T)、降雨量(R)和参考蒸散量(ET0)等天气变量的趋势和变化点分析进行了评估。分析采用了曼-肯德尔(MK)、修正曼-肯德尔(MMK)、创新趋势分析(ITA)和创新多边形趋势分析(IPTA)方法。为检测时间序列数据中的变化点(CPs),采用了同质性检验,包括佩蒂特检验、标准正态同质性检验(SNHT)、布瓦山德范围检验和冯-诺依曼比率检验(VNRT)。结果表明,就最高气温而言,MK 和 MMK 分别在 9 月和 7 月显示出正趋势,而最低气温在 8 月和 9 月显示出上升趋势。降雨量在扎伊德季节(4 月至 5 月)呈上升趋势。ET0 在 1 月份呈负趋势。ITA和IPTA在不同月份和季节呈现正负混合趋势。变化点分析表明,就 Tmax 而言,4 月份时间序列数据的 CP 出现在 1998 年。同样,就 Tmin 而言,4 月和 8 月时间序列的变化点出现在 1997 年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.80
自引率
10.70%
发文量
168
审稿时长
>12 weeks
期刊介绍: Journal of Water and Climate Change publishes refereed research and practitioner papers on all aspects of water science, technology, management and innovation in response to climate change, with emphasis on reduction of energy usage.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信