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Journals / Gaziosmanpaşa Üniversitesi Ziraat Fakültesi Dergisi / 2019 / Cilt: 36 - Sayı: 3

Detecting Change-point in Seasonal Reference Evapotranspiration (ETo) datasets

Kadri YUREKLI
Pages
206–210
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

None of the others showed significant variability in statistic sense.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The aim of the current study in the Central Anatolia Region was on assessing the reference evapotranspiration (ETo) behavior as proxies in exposing the presence of climate variability.
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Key Findings & Data:Historical climatic data spanning forty-three years (1970-2012) from the Turkish State Meteorological Service was used to calculate ETo data for five meteorological stations.
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Conclusion & Impact:None of the others showed significant variability in statistic sense.
🔬Design:Research Article
📍Scope:2012 Verileri
⚙️Variables:Central Anatolia Region · Reference Evapotranspiration · CUSUM approach

Abstract

The aim of the current study in the Central Anatolia Region was on assessing the reference evapotranspiration (ETo) behavior as proxies in exposing the presence of climate variability. Historical climatic data spanning forty-three years (1970-2012) from the Turkish State Meteorological Service was used to calculate ETo data for five meteorological stations. The change–point in ETo dataset was revealed by the distribution-free CUSUM (Cumulative Sum) statistic technique. The two stations, named Ankara and Konya, had a statistically significant shift. None of the others showed significant variability in statistic sense.

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Cite This Article

YUREKLI, K. (2019). Detecting Change-point in Seasonal Reference Evapotranspiration (ETo) datasets. Gaziosmanpaşa Üniversitesi Ziraat Fakültesi Dergisi, Cilt: 36 - Sayı: 3, 206–210. https://ajindex.com/articles/158052

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