Innovative triangular trend analysis

Güçlü Y. S., Sisman E., Dabanli I.

ARABIAN JOURNAL OF GEOSCIENCES, vol.13, no.1, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13 Issue: 1
  • Publication Date: 2020
  • Doi Number: 10.1007/s12517-019-5048-y
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), Geobase, INSPEC
  • Keywords: Time series, Trend analysis, Innovative trend analysis (ITA), Innovative triangular trend analysis (ITTA), MANN-KENDALL, PRECIPITATION, IDENTIFICATION, TEMPERATURE, REGRESSION, RAINFALL, FLOWS, TESTS
  • Yıldız Technical University Affiliated: No


In this study, based on the Sen innovative trend analysis (ITA) method, another approach has been developed as innovative triangular trend analysis (ITTA), which helps to identify partial trends within a given time series comparatively with each other. The basis of this methodology is to divide a given time series into a set of equal length sub-series and then to compare them pairwise in the form of a triangular array. In this manner, the trends within the whole series can be identified separately in detail. Consequently, it is possible to make much more realistic assessments depending on these trends. The application of the proposed method is carried out by considering the longest annual rainfall measurement records from 1966 to 2015, inclusive for stanbul, Rize, and Ankara provinces in Turkey. As a result, generally monotonically a negative trend in Ankara, no trend in Florya, and positive trend in Rize are determined by ITA methodology. On the other hand, instability of trends in time series is presented for these stations. Ankara has negative and no trend to the first 10 years and the last 20 years, respectively. Florya has successively positive and negative trends from the first to fifth part. As for Rize, according to ITTA, it has generally positive trends.