Combined innovative trend analysis methods for seasonal trend testing

While holistic trend identification is essential, it does not consider the periodic, e.g., monthly, trend characteristics needed to identify seasonal trend behavior. Furthermore, identifying seasonal trends can help manage or regulate water resources systems and irrigation and agricultural operations. In this study, the innovative trend significance test (ITST), the revised ITST, and the Wilcoxon signed-rank test, which are non-parametric methods, are proposed as alternative seasonal trend tests by combining them with the innovative polygon trend analysis (IPTA), which provides visual and linguistic examinations of seasonal behaviors. Groundwater level data from the Chilgrove House (United Kingdom), flow data from the Danube River Basin (Romania), precipitation and temperature data from Türkiye were used to compare the proposed methods with the seasonal Mann-Kendall (SMK) method. For temperature and groundwater level data, all methods showed an increasing trend at different confidence intervals, but for other data, trends emerged according to the characteristics of the methods. So, some of the proposed methods are more rigid than the SMK in trend detection, while others are more sensitive. In addition to the advantage of its applications to seasonal trend behaviors, the proposed significance tests are combined with the IPTA method and comparable alternative methods to the SMK. So, seasons with a clear increase or decrease can be seen visually in the proposed combined methods contrary to the SMK method. Thus, both seasonal trend behaviors and inter-seasonal transitions can be examined graphically, and seasonal significance testing can be applied. According to the characteristics of these combined methods, they can be used not only for seasonal trend tests, just like the SMK method, but also for regional trend tests using stations data instead of seasons.