ANALYSIS OF THE PRECIPITATION INTENSITY VALUES OF VARIOUS DURATIONS IN TRABZON PROVINCE OF TURKEY BY SEN'S INNOVATIVE TREND METHOD


TERZİOĞLU Z. Ö., KANKAL M., YÜKSEK Ö., Nemli M. O., Akcay F.

SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, cilt.37, sa.1, ss.241-250, 2019 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 1
  • Basım Tarihi: 2019
  • Dergi Adı: SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Academic Search Premier, Directory of Open Access Journals
  • Sayfa Sayıları: ss.241-250
  • Anahtar Kelimeler: Eastern Black Sea Basin, Mann-Kendall test, Sen's innovative trend method, trend analyses
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

Hydrological and meteorological studies indicate that hydrological processes and water resources are significantly affected by the climate change, particularly with increasing greenhouse gases and temperature. In this study, the trend analyses of the biggest precipitation intensity values in Trabzon, the most populous province of the Eastern Black Sea Basin in Turkey, have been carried out by using Mann-Kendall and Sen's Innovative Trend methods. In line with this purpose; the precipitation intensity data of standard time series from 5 minutes to 24 hours for two meteorological stations in Trabzon (Trabzon and Akcaabat) were used. Before carrying out trend analyses, the Run (Swed Eisenhart) Homogeneity Test was applied to all data and non-homogeneous data were not analysed. Before applying the Mann-Kendall Method, the internal dependency of the data was examined. When the analysis results are reviewed; in Trabzon Meteorology Station an increasing trend for intensities of all-time series has been detected, whereas in the Akcaabat Meteorology Station, a general result of the trend could not be obtained as most the data related to different time series were not homogeneous data.