Proceeding of the Joint International Symposium on Deformatuon Monitoring. 2-4 November, 2011. Hong Kong. China. Report. We applied six types of thresholding techniques in aim to impact of thresholding in denoising of time series, which were penalized threshold, Birge-Masssart Strategy, SureShrink threshold, universal threshold, minimax threshold and Stein's unbiased risk estimate. In order to compare the effect of them in denoising of noise components (white noise, flicker noise and random walk noise) we have constructed three kinds of stochastic models: the pure white noise model (I), the white plus random walk noise model (II) and the white plus flicker noise model (III). The numerical computations are performed through the analyzing 10 years (Jan 2001 to Jan 2011) of daily GPS solutions which are selected of 264 stations of SOPAC (Scripts orbit and permanent array center). According to results of computations, among the thresholding schemes in denoising of the pure white noise model (I): minimax threshold and Stein's unbiased risk estimate could reduced the distribution of low amplitude of white noise. However, minimax threshold and SureShrink threshold could reduced the distribution of high amplitude of white noise. Birge-Masssart Strategy and universal threshold could reduced both low and high amplitudes of white noise. In models II and III, all of threshold schemes could reduced both high and low amplitudes of white noise in same level. Whereas for power-law noise (flicker noise and random walk noise) penalized threshold and Stein's unbiased risk estimate led to reduction of low amplitudes and SureShrink threshold and minimax threshold led to reduction of colored noise with high amplitudes. Birge-Masssart Strategy and universal threshold could reduced both low and high amplitudes of colored noise.