In order to solve the problem that traditional correlation analysis method is difficult to reveal the correlation between non-linear and non-stationary hydrological sequences and external forcing factors in different time scales and different frequency domains, we proposed a new method which is the combination of EEMD and CWT to be applied to the multi-scale correlation analysis of the long term flow series of Ganjiang River and the sunspot series in the same period. The results showed that the IMF1 component of the EEMD decomposition of the Ganjiang River flow series from 1950 to 2015 has the maximum amplitude and the highest frequency, representing the main change factor in the original series, which is the embodiment of the nonlinear and nonstationary characteristics of the hydrological sequence. The results of the EEMD components of the sunspot series in the same period showed that from 1950 to 1970 the sunspot increased and then decreased from 1970 to 2015. CWT analysis showed that the correlation between the Ganjiang River flow and the sunspot series gradually shifted from the negative correlation to the 1/4 cycle lag and then to the positive correlation. From 1950 to 2000, the correlation coefficient of this two series was above 0.6, and the correlation coefficient was above 0.4 from 2001 to 2015. This study shows that the EEMD-CWT comprehensive analysis can effectively use the EEMD method to decompose the original signal to obtain the IMF components with stability. Based on this, the correlation between the two series in the time domain and the frequency domain can be obtained by the CWT method. This method can provide new ideas and technical means for exploring the multi-scale correlation between hydrological meteorological series and external forcing factors.