Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha
{"title":"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","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":"{\"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}","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}
Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)
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.
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.