where \(1<j<i<n\). When \(\beta>0\), the sequence change trend is upward, but when\(\ \beta<0\), then it has a downward trend. Since\(\beta\) is a non-normalized parameter, it can only show the size of the changing trend. It cannot judge the significance of the trend change for a time series. Therefore, the Mann-Kendall method needs to be used to test the significance of the trend (Kendall, 1948). Finally,\(\alpha<0.05\) and \(\alpha<0.1\) were considered very significant and significant, respectively, and the rest were not significant.
2.3.2 Correlation analysis
The relationships between variables include definite relationships and uncertain relationships. A statistical uncertainty analysis was used in this study, and the Pearson’s correlation coefficient revealed the relationship between soil wind erosion and its dominant factors. The Pearson’s correlation coefficient is a common linear correlation coefficient and is also known as the product-moment coefficient of correlation. Generally, r represents the degree of linear correlation between variables X and Y, and ranges from –1 to 1. There is a negative correlation when r < 0, whereas r> 0 means a positive correlation. The significance level was p < 0.1 and the formula is expressed as follows: