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Qinghai Region Terrestrial Water Storage Variation Analysis Based On GRACE Data

Posted on:2017-02-08Degree:MasterType:Thesis
Country:ChinaCandidate:Z D WangFull Text:PDF
GTID:2180330485475128Subject:Geodesy and Survey Engineering
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The earth mass distribution is not stable all the time, the seasonal and inter-annual changes of the earth surface water’s regional distribution have a great influence on the climate change and the human life. As the main content of the space geodesy, the research of the earth gravity field can improve the human’s cognition on earth. The launch of the GRACE satellite in 2002 makes the global long space scale time-varying gravity field information’s measurement all-weather, with a high precision and efficiency, providing a new method to monitoring the earth quality change.In this thesis, the data of GRACE RL05 are used to estimate the earth mass variations from 2002 to 2012, analyze the Qinghai region with the Global hydrological models, precipitation and the satellite altimetry data. Using principal component analysis to breakdown, sieve, rebuild the calculating results. The specific content and results of this thesis are summarized as follows(1) Give a brief description of the development of the satellite gravimetry in space geodesy and the CHAMP, GRACE, GOCE gravity satellite; make a summary about the overseas and domestic research status of the earth mass detection using the gravity satellite data. Introduce the data product of GRACE satellite and elaborate the theories and methods to calculate the earth mass variations by GRACE temporal gravity field model data, especially analyze the Gaussian filtering, fan-filtering and decorrelation filtering in the post-processing method to remove the correlated errors in GRACE data and the effect in eliminating strips.(2) The second part of this thesis use principal component analysis to breakdown the earth mass variation results calculated with the GRACE data of 84 months from 2004 to 2010, getting the spatial mode showing the distribution of the global terrestrial water storage variation and the time mode showing the inter-annual trend of the global terrestrial water storage variation, rebuilding with some high contribution degree spatial and time modes can both keep the principal component of the original signal and eliminate strips.(3) The last part of this thesis analyzes the global water reserves variations on seasonal and inter-annual trends using GRACE data during 2002 to 2012, calculating the global surface water storage variation with the Global hydrological models to compare and verify with GRACE results. Reach a conclusion that the terrestrial and surface water storage of Qinghai region both has an obvious seasonal trend which has a good consistency with the precipitation data, showing that the terrestrial and surface water storage show maximum in summer than winter because there’s more rainfall in summer in Qinghai region. On the other hand he terrestrial water storage of Qinghai region during 2002 to 2012 show an obvious inter-annual characteristics with an average increasing rate of 4.3±0.4mm/year of equal water height from 2002 to 2012 and the western plateau region showing a faster increasing rate. The increasing rate of the Qinghai Lake basin terrestrial water storage variation is 3.8±0.4mm/year of equal water height, mainly made up with the surface water storage variation 2.2±0.3mm/year of equal water height and the Qinghai Lake water storage variation of equal water height 0.9±0.1 mm/year from 2002 to 2012, at the same time the increasing rate of the Qinghai Lake basin terrestrial water storage variation is 6.4±0.4mm/year of equal water height, which mainly made up with the permafrost, underground water, surface water storage and lake storage variation.The results of the satellite altimetry data show that a number of lakes’storage is increasing during 2002 to 2012, which reaches unanimity with the terrestrial water storage variation trend calculated by GRACE data.
Keywords/Search Tags:GRACE, terrestrial water storage, space filtering, principal component analysis
PDF Full Text Request
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