MATLAB Programs for Hydrological Trend and Change-Point Analysis - Spearman, Kendall, and Pettitt Methods

In the field of hydrological trend and change-point analysis, utilizing MATLAB implementations of the Spearman, Kendall, and Pettitt methods enables researchers to derive significant insights about hydrological phenomena. The Spearman method calculates rank correlation coefficients to detect monotonic trends, while Kendall's tau method provides a non-parametric test for trend significance. The Pettitt test algorithm efficiently identifies abrupt change points in hydrological time series by examining differences in cumulative distributions. These MATLAB programs typically involve data preprocessing, statistical computation functions, and visualization components to display trend patterns and change-point locations. The conclusions obtained not only enhance our understanding of fundamental hydrological concepts and patterns but also support more accurate predictions of future hydrological changes. Furthermore, these methods facilitate deeper investigations into critical water resource management issues. By employing these MATLAB implementations, researchers can obtain comprehensive and precise hydrological data analysis, thereby supporting better decision-making in future water resource planning and management initiatives. The code typically includes functions for data validation, statistical testing with significance levels, and graphical output generation for result interpretation.