INNOVATIVE TREND ANALYSIS METHODOLOGY IN LOGARITHMIC AXIS

Year 2020, , 573 - 585, 03.09.2020

Sadık Alashan

https://doi.org/10.36306/konjes.668212

Cited By: 5

Abstract

Future uncertainties of climate change cause people to worry, and therefore, in order to
reduce the associated risks, scientific research methodologies are improved continuously. For instance,
temperature raises as a result of carbon content increase cause variations in hydro-meteorological data
including evaporation, drought, precipitation, runoff, and flood. Along these lines, the most commonly
used trend analysis methods are linear regression analysis, Mann-Kendall, sequential Mann-Kendall,
Spearman’s Rho, and recently a new method referred to as innovative trend analysis (ITA), which does
not require initial assumptions, normality, and independence in a data structure. The ITA method
presents a great visual ability for trend identification in graphical forms in addition to qualitative and
quantitative interpretations. In the original form of the ITA approach, scatter points are presented in the
arithmetic scale, where changes of scatter points in small values may not be clearly distinguishable like
big values for wide data ranges. In this study, the ITA method is used on arithmetic and logarithmic
scales to calculate such differences in two sub-series. The suggested logarithmic scale methodology is
referred to as proportional Şen innovative trend analysis (ITA_P). This method is used to determine
percent trends for the annual, autumn, winter, spring and summer season rains in England. ITA_P is
successful in determining trends in minimum values compared to the classical ITA.

Keywords

Innovative trend analysis, hydro-meteorological data, proportional innovative trend analysis, climate change

Logaritmik Ölçekte Yenilikçi Yönelim Çözümleme Yöntemi

Abstract

Gelecekle ilgili belirsizlikler insanoğlunu endişelendirmekte ve olası riskleri azaltmak için bilimsel
araştırma yöntemleri sürekli geliştirilmektedir. Örneğin karbon salınımının artışıyla birlikte artan
sıcaklıklar buharlaşma, yağış gibi iklim olaylarının değişimini artırarak akışlar üzerinde kuraklık ve
taşkınlara neden olabilmektedir. Bu olaylar üzerindeki eğilimi belirlemek üzere Mann-Kendall, sıralı
Mann-Kendall, Spearman rho ve son zamanlarda ortaya atılan Şen’in yenilikçi yönelim çözümleme
(Şen_ITA) yöntemleri literatürde sıklıkla kullanılmaktadır. Bu yöntemlerden Şen_ITA yöntemi
normallik ve bağımsız seri gibi başlangıç kabulleri gerektirmemektedir. Ayrıca niteliksel ve nicel
yorumlamaları yanında grafiksel olarak görsel kabiliyeti yüksek bir yöntemdir. Şen_ITA yöntemi esasen
aritmetik ölçekte kullanılır ve bu durum değişim katsayısı yüksek bir seri üzerinde minimum değerler
üzerindeki eğilimin maksimum değerlerin yanında gözden kaçabilmesine neden olabilmektedir. Bu
çalışmada, Şen_ITA yöntemi aritmetik ve logaritmik ölçekte kıyaslanmıştır. Önerilen yaklaşım, oransal
Şen yenilikçi yönelim çözümleme yöntemi olarak adlandırılmıştır (ITA_P). Bu yaklaşım İngiltere’nin
mevsimsel ve yıllık yağışları üzerindeki oransal eğilimleri belirlemek için kullanılmıştır. ITA_P
yaklaşımının klasik Şen_ITA yöntemine göre bir seri üzerinde minimum değerlerdeki eğilimleri
belirlemede daha başarılı olduğu belirlenmiştir.

Keywords

Yenilikçi yönelim çözümlemesi, hidro-meteorolojik veri, oransal yenilikçi yönelim çözümlemesi, iklim değişikliği

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