Combination of Wilcoxon test and scatter diagram for trend analysis of hydrological data


SAPLIOĞLU K., Güçlü Y. S.

JOURNAL OF HYDROLOGY, vol.612, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 612
  • Publication Date: 2022
  • Doi Number: 10.1016/j.jhydrol.2022.128132
  • Journal Name: JOURNAL OF HYDROLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, BIOSIS, CAB Abstracts, Communication Abstracts, Environment Index, INSPEC, Metadex, Pollution Abstracts, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Discharge, Mann-Kendall, Innovative Trend Analysis, Time series, Turkey, Wilcoxon Test, LONG-TERM PERSISTENCE, MANN-KENDALL, IDENTIFICATION, TEMPERATURE, COEFFICIENT
  • Süleyman Demirel University Affiliated: Yes

Abstract

In this study, time series data is divided into two equal parts, as in the basic principle of the Innovative Trend Analysis (ITA) method. However, unlike the ITA, the data are not ordered when comparing the halves to avoid any change in the time series. Wilcoxon Signed Rank Test is used to consider the differences between the two equal halves and to determine if there is any trend in time series. A graphical presentation is provided like ITA approach and is expressed as the Mann-Kendall (MK) test for trend detection at a given confidence interval (significance level). In the application phase, minimum, maximum and average discharge time series measured at Yakabasi, Sogutluhan, Aricilar, and Topluca stations along the northern line from west to east of Turkey are used. The trend conditions of the data are determined by the proposed method and compared with ITA and MK tests results. No trend is observed in 8 out of 12 cases for stations at the 95% confidence interval. While decreasing trends are detected in the maximum discharge of Yakabasi station, the minimum discharge of Ancilar station, and the average discharge of Yakabasi station, an increasing trend is detected in the average discharge records of Topluca station. Here, an easy-to-use model for decision-makers is proposed that presents numerical as well as graphical analyses of trend identification studies.