The Activity Model And Crustal Deformation Analysis Of Sichuan-yunnan Block

Sichuan-yunnan, the hot spot for the study of modern crustal movement in China, itsunique motion characteristic is basically just the Indian plate subducting Eurasian plate. Theintense subduction squeezing not only lead to the shorted and uplift of Tibetan region, butalso lead to it’s material inside of the curst east to overflow. When flowing to Sichuan-yunnanregion, it blocked by the stable south China block, making the area clockwise rotation.The rapid development of modern Space Geodesy technology, has opened a new way toaccess the observation data in an unprecedented high resolution in modern crustal movementresearch. In this paper, we used the data mainly the GPS data in Sichuan-yunnan area whichare the part of Crustal Movement Observing Network in China, and the lever data in westernSichuan region. Comprehensive analysed the horizontal and vertical motion characteristic inSichuan-yunnan region, adopted different quantitative models to simulate the trenddeformation, and established the quantitative models to the regional crustal movement instudy area. Accordingly, we described the characteristics of regional deformation moreaccurate.The concrete research achievement and content includes:1. Using the GPS data, we established the model of Euler vector and Least squaresconfiguration in horizontal crustal deformation analysis. Confirming the meaning of modelparameter, the concrete steps of establishment, and the matters need attention in build-upprocess more clearly. Considering the Euler model can only provide the average deformationinformation in large time scales, we further used Least squares configuration model to takethe long-term movement of the plates and the local movement of a small scale intoconsideration at the same time, completed the collocation of horizontal deformation in studyarea.2. When in a process of least-squares configuration, the vector of signal is easy to beaffected by the priori error of covariance function. Thus we adopted Helmet variancecomponent estimation, adjusted the signal vector and the observation vector by constructingan adaptive factor, building the improved model of least squares estimate based on adaptive fitting. Preliminary we solved the problems of shortages and uneven distribution inobservation data in deformation analysis.3. Combining the research of Quasi-Accurate Detection of gross errors (QUAD), wegave the gross error test steps that observation in1dimension and unequal weight. And thenwe completed the rejection of gross error in western Sichuan region level observation data.4. Scrupling the effect of gross error in the process of fitting, separately we built themulti-surface function method and the partition fitting method based on detection of grosserror, and completed the vertical deformation trend fitting in study area. Meanwhile, thestatistics showed that partition fitting method is more suitable than the fitting method of thesingle, especially in a complicated vertical deformation area.