H ydrological frequency analysis relies on a serie s of assumptions, especially nonstationarity, homogeneity and independence. As hydrological events should be described through several dependent hydrological variables, e.g. peak, volume of flood; annual minimum monthly runoff, annual minimum 3 monthly runoff for low runoff process, multivariate hydrological frequency analysis methods have gained popularity during recent years. However, multivariate hydrological frequency analysis focused directly on fitting the frequency distribution without testing the assumption procedure. Neglecting the testing procedure may get the incorrect frequency distribution. This paper introduced multivariate MK testing, which was widely used in the field of water quality, to test both univariate and multivariate trends of annual peak and annual max 7 day volume, annual minimum morthly runoff and annual minimum 3 monthly runoff at the control stations of the upper reaches of the Yangtze River Basin. The results indicate that multivariate tests can detect the integrated trends of joint variables, whereas univariate tests can only detect the univariate trends. Therefor, it is recommended to jointly apply univariate and multivariate trend tests in order to get a precise result.