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Linear Trend Detection In Serially Dependent Hydrometeorological Data Based On A Variance Correction Spearman Rho Method, Wenpeng Weng, Yuanfang Chen, Stefan Becker, Bo Liu

Publications and Research

Hydrometeorological data are commonly serially dependent and thereby deviate from the assumption of independence that underlies the Spearman rho trend test. The presence of autocorrelation will influence the significance of observed trends. Specifically, the positive autocorrelation inflates Type І errors, while it deflates the power of trend detection in some cases. To address this issue, we derive a theoretical formula and recommend an appropriate empirical formula to calculate the rho variance of dependent series. The proposed procedure of the variance correction for the Spearman rho method is capable of mitigating the effect of autocorrelation on both, Type І error and …