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DOI10.1007/s11069-020-04410-0
Scrutinizing variability in full and partial rainfall time series by different approaches
Yurekli K.
发表日期2021
ISSN0921030X
起始页码2523
结束页码2542
卷号105期号:3
英文摘要The main goal of this study was established on the effect of splitting full data in disclosing time-related internal variability in a given time series, as well as classical trend analysis procedure. For this purpose, Mann–Kendall (MK), Spearman's Rho (SR), linear regression (LR), and innovative trend analysis (ITA) approaches were applied to the full part and the split data of the seasonal and annual rainfall data provided from the Kizilirmak Basin in Turkey. In the study, it was determined that the ITA method was more effective than other methods in terms of finding out the statistically significant trend in a significant portion of the rainfall data (approximately 87%), whereas this rate varied between 7 and 13% in other methods. Similar results have been experienced when the full data were divided into three groups. Among the trend analysis approaches applied to the split data groups formed for the analysis of the internal variability that occurs during the observation periods in the rainfall time series, the ITA method was quite effective in detecting the mentioned change in the time series. The ITA procedure revealed that there was a statistically significant decrease in rainfall amounts in the seasons with the highest rainfall of the region. This result could not be presented sufficiently when the data were divided into two groups. The remaining three methods failed to produce a remarkable result in determining the internal variability experienced in the data. In this sense, the consideration of full data in the analysis produces information about the average trend, it is insufficient to reveal the hidden information in the data. © 2020, Springer Nature B.V.
关键词ITA testKizilirmak basinRainfallTrend analysis
英文关键词detection method; innovation; rainfall; seasonal variation; time series; trend analysis; Kizilirmak River; Turkey; Meleagris gallopavo
语种英语
来源期刊Natural Hazards
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/206698
作者单位Department of Biosystem Engineering, Agriculture Faculty, Gaziosmanpasa University, Tokat, Turkey
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Yurekli K.. Scrutinizing variability in full and partial rainfall time series by different approaches[J],2021,105(3).
APA Yurekli K..(2021).Scrutinizing variability in full and partial rainfall time series by different approaches.Natural Hazards,105(3).
MLA Yurekli K.."Scrutinizing variability in full and partial rainfall time series by different approaches".Natural Hazards 105.3(2021).
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