Scrutinizing variability in full and partial rainfall time series by different approaches

Kadri Yurekli ()
Additional contact information
Kadri Yurekli: Gaziosmanpasa University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 105, issue 3, No 9, 2523-2542

Abstract: Abstract 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.

Keywords: Kizilirmak basin; Rainfall; Trend analysis; ITA test (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-020-04410-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:105:y:2021:i:3:d:10.1007_s11069-020-04410-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-020-04410-0

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().