Logaritmik Ölçekte Yenilikçi Yönelim Çözümleme Yöntemi
Selcuk University Journal of Engineering Science and Technology
Future uncertainties of climate change cause people to worry, and therefore, in order to reduce the associated risks, scientific research methodologies are improved continuously. For instance, temperature raises as a result of carbon content increase cause variations in hydro-meteorological data including evaporation, drought, precipitation, runoff, and flood. Along these lines, the most commonly used trend analysis methods are linear regression analysis, Mann-Kendall, sequential Mann-Kendall,
... tial Mann-Kendall, Spearman's Rho, and recently a new method referred to as innovative trend analysis (ITA), which does not require initial assumptions, normality, and independence in a data structure. The ITA method presents a great visual ability for trend identification in graphical forms in addition to qualitative and quantitative interpretations. In the original form of the ITA approach, scatter points are presented in the arithmetic scale, where changes of scatter points in small values may not be clearly distinguishable like big values for wide data ranges. In this study, the ITA method is used on arithmetic and logarithmic scales to calculate such differences in two sub-series. The suggested logarithmic scale methodology is referred to as proportional Şen innovative trend analysis (ITA_P). This method is used to determine percent trends for the annual, autumn, winter, spring and summer season rains in England. ITA_P is successful in determining trends in minimum values compared to the classical ITA.