Yağış Zaman Serilerindeki Kısa Dönemli Eğilimlerin İzlenmesinde Çeşitli Yöntemlerin Karşılaştırılması

Year 2020, Volume: 25 Issue: 1, 153 - 168, 30.04.2020

Babak Vaheddoost

https://doi.org/10.17482/uumfd.656175

Cited By: 5

Abstract

Yağıştaki eğilimler, büyük ölçekli iklimsel olaylar veya döngüsel hareketler ile ilişkilidir. Kısa veri kayıtlarında bu davranışın incelenmesi sıkıntılı olabilmektedir. Bu çalışmada, Ocak 2005 - Ekim 2018 tarihleri arasında Bursa ilinde ölçülen aylık yağış zaman serileri kullanılmıştır. Bölgede en uzun zaman kaydına ve en az veri kaybına sahip istasyon verileri analizlerde kullanılmak üzere seçilmiştir. Bu amaca yönelik olarak, Osmangazi, Keleş, Uludağ, Gemlik, İznik, Karacabey ve Mustafakemalpaşa istasyonları seçilmiştir. Seçilen istasyonların yağış zaman serilerindeki kısa dönemli eğilimlerini tespit etmek için doğrusal eğilim (LT), hareketli ortalama (MA), Mann-Kendall (MK), dönüm noktaları (TP), Spearman sıralı korelasyon (SROC), yenilikçi Şen (IS), yenilikçi eğilim analizi (ITA), dağılım fonksiyonundaki değişiklikler (CD) ve standart yağış indis (SPI) yöntemleri kullanılmıştır. Uygulanan analizler neticesinde, önceki çalışmaların ortaya koymuş olduğu eğilimlerin tek başına LT, MK, SROC, IS, ITA ve MA yöntemleriyle tespit edilemediğini göstermektedir. Buna karşın, SPI-48, CD ve SPI yöntemleri ise eğilimleri tek başına belirgin bir şekilde tespit edebilmektedir. Aykırı değerlere sahip olan verilerde kısa dönemli eğilimleri tespit etmek zordur. Aykırı değerler barındıran verilerde kısa dönemli eğilimlerin değerlendirilmesinde CD, ITA ve IS yöntemlerinin birlikte kullanılması önerilmektedir.

Keywords

Bursa, kısa dönem eğilim, istatistiksel analiz, yağış

A COMPARISON OF SEVERAL METHODS IN TRACKING SHORT-TERM TRENDS ASSOCIATED WITH THE PRECIPITATION TIME SERIES

Abstract

Precipitation trends can be linked to large-scale climatic events or cyclic behaviors. However, exploring these patterns in short data records can be problematic. In this study, the monthly precipitation time series recorded across the Bursa district in Turkey were addressed between January 2005 to October 2018. Stations with the minimum data loss and the longest time records in the region were selected for the analysis. Therefore, Osmangazi, Keles, Uludag, Gemlik, Iznik, Karacabey, and Mustafakemalpasa stations were selected. Linear trend (LT), moving average (MA), Mann-Kendall (MK), turn points (TP), Spearman rank-order correlation (SROC), innovative Şen (IS), innovative trend analysis (ITA), changes in distribution (CD), and standardized precipitation index (SPI) methods were used to detect short-term trends in the precipitation time series. Results indicated that the trends, reported by the previous studies could not be reproduced at a monthly scale when using LT, MK, SROC, IS, ITA, and MA. However, the trends observed by the SPI-48 were also tracked down using CD, and SPI methods. It is concluded that the detection of the short-term trends is problematic whilst the outliers deviate results of the analysis. Hence, a combination of CD, ITA, and IS methods is a key in evaluation of the short-term trends within a data run.

Keywords

Precipitation, short term trend, statistical analysis, Bursa

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