CN113899301A - Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation - Google Patents

Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation Download PDF

Info

Publication number
CN113899301A
CN113899301A CN202111084343.7A CN202111084343A CN113899301A CN 113899301 A CN113899301 A CN 113899301A CN 202111084343 A CN202111084343 A CN 202111084343A CN 113899301 A CN113899301 A CN 113899301A
Authority
CN
China
Prior art keywords
gnss
water reserve
deformation
inversion
reserve change
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111084343.7A
Other languages
Chinese (zh)
Other versions
CN113899301B (en
Inventor
钟波
李贤炮
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Wuhan University WHU
Original Assignee
Wuhan University WHU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Wuhan University WHU filed Critical Wuhan University WHU
Priority to CN202111084343.7A priority Critical patent/CN113899301B/en
Publication of CN113899301A publication Critical patent/CN113899301A/en
Application granted granted Critical
Publication of CN113899301B publication Critical patent/CN113899301B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B7/00—Measuring arrangements characterised by the use of electric or magnetic techniques
    • G01B7/16—Measuring arrangements characterised by the use of electric or magnetic techniques for measuring the deformation in a solid, e.g. by resistance strain gauge

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention provides a regional land water reserve change inversion method and system combining GNSS three-dimensional deformation, which comprises the steps of establishing the relation between the GNSS north, east and vertical deformation and regional land water reserve change according to the Green function theory of mass load; establishing an observation equation between regional land water reserve change and GNSS north, east and vertical deformation according to a mass load Green function theory, and obtaining a corresponding normal equation; and inverting regional land water reserve change according to least square joint adjustment, wherein a joint inversion model of GNSS vertical and horizontal deformation is formed according to a normal equation and by combining a prior information equation, then an observed value noise variance and a regularization parameter initial value are given, and the optimal weight ratio of various data is iteratively calculated by using a variance component estimation method to obtain the regional land water reserve change of optimal joint inversion. The method improves the accuracy and reliability of the inversion result of the regional land water reserve change.

Description

Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation
Technical Field
The invention relates to a method for inverting regional land water reserve change by utilizing space geodetic survey observation data, in particular to a regional land water reserve change inversion method and system combining GNSS three-dimensional deformation.
Background
The Terrestrial Water Storage (TWS) refers to all Water stored on the surface and underground, including surface Water, underground Water, glaciers, snow, soil Water, and the like, and is an important component of global Water circulation. Migration and redistribution to accurately determine land water reserves has a significant impact on natural environmental changes and human activities.According to the load green function theory, the earth crust is deformed due to the change of the surface water load. Therefore, the material migration and exchange process of the earth system can be deduced and monitored by observing the high-precision earth surface deformation field and the time-space change, and the higher the fineness of the obtained earth surface deformation field is, the more abundant the material migration information of the earth system is, so that the method has very important physical significance for the researches of geodetics, hydrology, glacier science, global environment change and the like[1-3]。
Since Argus et al (2014) first proposed inversion of regional surface quality changes using GNSS vertical deformation, surface quality changes of GNSS inversion are considered as beneficial additions to the results of GRACE/GFO inversion. Most of the scholars at present mainly use GRACE/GFO to invert the land water reserve change on the global and regional scales, but are limited by the satellite orbit height, the effective load and the influence of various error sources, and the inversion result still has a plurality of limitations. The change of the land water reserves can cause the deformation of the earth crust while causing the change of the external gravity field of the earth, and the deformation can be continuously observed by GNSS with millimeter-scale precision, so that land water reserves can be independently inverted by utilizing GNSS earth surface deformation data[1,5]. At present, thousands of global GNSS continuous stations with public data are available, and intensive GNSS continuous operation table networks (such as Chinese 'land network') are established in many countries to monitor regional earth surface deformation and geological structure movement[6-7]. In recent years, with the accumulation of GNSS observation data and the improvement of data processing methods, these high-precision and rich GNSS data provide important data support for studying regional land water reserve changes.
The existing research results focus on inverting regional land water reserve change by independently utilizing GNSS vertical deformation and carrying out comparative analysis on the regional land water reserve change, GRACE/GFO and hydrological model inversion results[8]. The study of Wahr et al (2013) found that combining GNSS horizontal and vertical deformations better determines the spatial distribution of mass loading. On the basis, the invention innovatively provides a combined GNSS three-dimensional deformation inversion method for regional land water storage capacity change so as to further improve regional land water storage capacity changeAnd (5) the reliability of the inversion result is normalized.
The relevant references are as follows:
[1]Blewitt G.,D.Lavallée,P.Clarke,K.Nurutdinov.Anew global mode of earth deformation:seasonal cycle detected.Science,2001,294(5550):2342-2345.
[2]Tapley,B.D.；Bettadpur,S.；Ries,J.C.；Thompson,P.F.；Watkins,M.M.GRACE Measurements of Mass Variability in the Earth System.Science 2004,305,503–505.
[3] the method comprises the steps of measuring the gravity of a satellite and the application thereof in monitoring the change of the geophysical environment, wherein the method comprises the steps of measuring the gravity of the satellite, and monitoring the change of the geophysical environment, wherein the step comprises the step of China science, 2012,42(6): 843-.
[4]Argus,D.F.；Fu,Y.；Landerer,F.Seasonal variation in total water storage in California inferred from GPS observations of vertical land motion.Geophys.Res.Lett.2014,41,1971–1980.
[5]Wu,X.Large-scale global surface mass variations inferred from GPS measurements of load-induced deformation[J].Geophysical Research Letters,2003,30(14):253-266.
[6] Li Qiang, Yongxinzhan, Yang Shao Min, etc. China mainland tectonic deformation high precision large density GPS monitoring-present velocity field [ J ] China science, geoscience, 2012,42(005):629-632.
[7] Jianweiping, development status, opportunity and challenge of satellite navigation positioning reference station network [ J ] survey and drawing bulletin, 2017(10): 181-.
[8]Zhong B,Li X,Chen J,et al.Surface Mass Variations from GPS and GRACE/GFO:A Case Study in Southwest China[J].Remote Sensing,2020,12(11):1835.
[9]Wahr,J.；Khan,S.A.；Van Dam,T.；Liu,L.；Van Angelen,J.H.；Broeke,M.R.V.D.；Meertens,C.The use of GPS horizontals for loading studies,with applications to northern California and southeast Greenland.J.Geophys.Res.Solid Earth 2013,118,1795–1806.
Disclosure of Invention
Aiming at the defects of the existing method for inverting the regional land water reserve change by independently utilizing GNSS vertical deformation, the invention provides a method and a system for inverting the regional land water reserve change by combining GNSS three-dimensional deformation.
The technical scheme adopted by the invention is an inversion method for inverting the land water reserve change of an area by combining GNSS three-dimensional deformation, which comprises the following steps,
step 1, establishing a relation between the northbound, eastern and vertical deformation of the GNSS and the water reserve change of the regional land according to the Green function theory of mass load;
step 2, establishing observation equations between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load, and then forming a joint inversion method equation set according to the GNSS vertical, north and east observation equations;
and 3, inverting regional land water reserve change according to the least square joint adjustment by using the result obtained in the step 2, wherein a GNSS three-dimensional deformation joint inversion model is formed according to a normal equation and by combining a prior constraint equation, then an observed value noise variance and a regularization parameter initial value are given, and the optimal weight ratio of various data is iteratively calculated by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
Further, in step 1, the relationship between the GNSS north, east and vertical deformations and the regional land water reserve change can be expressed as;
Figure BDA0003262664830000031
wherein n (theta), e (theta) and u (theta) are respectively the north, east and vertical deformation of the GNSS; Δ M is the hydrographic mass load, MRIs the earth mass; r is the mean radius of the earth; lnAnd hnThe load Love number; theta is the angular distance between the grid point and the GNSS survey station; p is a radical ofnIs Legendre polynomial; alpha is the included angle between the horizontal deformation and the north direction.
Further, the expression of the observation equation between the change of the regional land water reserves and the north, east and vertical deformation of the GNSS in the step 2 is as follows;
Figure BDA0003262664830000032
wherein, yN、yEAnd yUCorresponding to the observed values of the GNSS north, east and vertical deformation respectively, AN、AEAnd AUDesigning a matrix for a Green function corresponding to three-dimensional deformation, wherein x is a land water reserve change parameter to be estimated, and eN、eEAnd eURespectively corresponding to the residual vectors of the observation values of north, east and vertical deformation,
Figure BDA0003262664830000033
and
Figure BDA0003262664830000034
is the variance of the error of the observed value, IN、IEAnd IUIs the North, east and vertical deformation observations y of the sum GNSSN、yEAnd yUThe associated identity matrix.
Further, the specific expression of the joint inversion method equation set in step 2 is as follows,
Figure BDA0003262664830000035
wherein the content of the first and second substances,
Figure BDA0003262664830000041
Figure BDA0003262664830000042
is ANTranspose of (P)NIs a weight matrix corresponding to the north deformation observed value n (theta),
Figure BDA0003262664830000043
Figure BDA0003262664830000044
is AETranspose of (P)EIs an east deformation observed value e (theta)) The corresponding weight matrix is set to be the weight matrix,
Figure BDA0003262664830000045
Figure BDA0003262664830000046
is AUTranspose of (P)UIs a weight matrix corresponding to the vertical deformation observed value u (theta),
Figure BDA0003262664830000047
further, in step 3, the prior constraint equation is Lx ═ 0, and the inversion result is regularized and constrained by using a discrete laplace matrix L;
wherein L is Laplace matrix, specifically Laplace template
Figure BDA0003262664830000048
L2＝[1 -2 1]And
Figure BDA0003262664830000049
the method comprises the following steps that x is a land water reserve change parameter to be estimated, and 0 is a zero vector consistent with the length of an observed value;
further, in step 3, a GNSS three-dimensional deformation joint inversion model is formed according to a normal equation and by combining a prior constraint equation, that is, a joint inversion target function is formed: | | ANx-yN||2+||AEx-yE||2+||AUx-y||2+λ||Lx||2Min, where λ is the regularization parameter and L is the laplace matrix;
the joint inversion model of the regional land water reserve variation parameter estimation value to be solved can be expressed as:
Figure BDA00032626648300000410
wherein, PN、PEAnd PURespectively weighting arrays of GNSS north direction, east direction and vertical deformation observed values;
given three types of observation noise variance
Figure BDA00032626648300000411
And a regularization parameter alpha is an initial value, and an optimal regional land water reserve change result is solved through variance component estimation iteration weighting.
On the other hand, the invention also provides a regional land water reserve change inversion system combining GNSS three-dimensional deformation, which is used for realizing the regional land water reserve change inversion method combining GNSS three-dimensional deformation, and comprises the following modules,
the first module is used for establishing the relation between the northern, east and vertical deformation of the GNSS and the water reserve change of the regional land according to the Green function theory of mass load;
the second module is used for establishing observation equations between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load, and then forming a joint inversion method equation set according to the GNSS vertical, north and east observation equations;
and the third module is used for inverting regional land water reserve change according to the least square joint adjustment by using the result obtained by the second module, and comprises the steps of forming a GNSS three-dimensional deformation joint inversion model according to a normal equation and a priori constraint equation, then giving an observed value noise variance and a regularization parameter initial value, and iteratively calculating the optimal weight ratio of various data by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
The invention also provides computer equipment comprising a processor and a memory, wherein the memory is used for storing program instructions, and the processor is used for calling the stored instructions in the memory to execute the regional land water reserve change inversion method combining GNSS three-dimensional deformation.
The invention also provides a computer readable storage medium, which stores a computer program, and when the computer program is executed, the method for inversion of regional land water reserve variation combining GNSS three-dimensional deformation is realized.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the reliability of inversion of regional land water reserve change is improved.
The method is limited by factors such as sparse distribution, limited distribution range and the like of GNSS survey stations, and certain defects and shortcomings exist in the current method for inverting the land water reserve change in the region by independently utilizing GNSS vertical deformation data. The method for inverting the regional land water reserve change by combining the GNSS three-dimensional deformation data can fully utilize the GNSS three-dimensional deformation observation value to better constrain the spatial distribution of the land water reserve change, thereby improving the reliability of the inversion result.
2. The theoretical basis of the scheme is sufficient, and the stability and the effectiveness are realized.
By respectively comparing the GNSS north direction, east direction and vertical deformation observation value inversion results and the residual standard deviation of the GNSS three-dimensional deformation joint inversion result and the original signal, the joint inversion result and the original signal residual are smaller, and the reliability of the joint inversion result is reflected to be higher. The method makes full use of GNSS three-dimensional deformation observation data, so that the joint inversion method is effective for improving the reliability of regional land water reserve change.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention.
Detailed Description
The technical solution of the present invention is described in detail below with reference to the accompanying drawings and examples.
The method makes full use of the advantages and disadvantages of GNSS three-dimensional deformation inversion region land water reserve change, realizes advantage complementation, and inverts reliable region land water reserve change by combining GNSS three-dimensional deformation observation data. Therefore, the invention provides a method for inversing reliable regional land water reserve change by combining GNSS three-dimensional deformation data.
The following description will be given by taking the continental region of china as an experimental region, selecting the change of water storage in 9 months of 2005 calculated by GLDAS as an original signal, and combining with fig. 1, by closed numerical simulation, explaining the regional land water storage combining with GNSS three-dimensional deformation data provided by the embodiment of the present inventionAnd (3) a method of variable inversion. In the example, for ease of calculation, the study area was divided into uniform grids of 1 ° × 1 °, for a total of 3240 grids, including the ocean region. The number of the GNSS stations selected in the research area is 272, the water reserve change original signal and the GNSS station longitude and latitude calculated by the GLDAS hydrological model are utilized, and the GNSS station longitude and latitude are calculated according to the grid longitude and latitude of the research area
Figure BDA0003262664830000061
And
Figure BDA0003262664830000062
in m, a mathematical relationship between the GNSS north, east and vertical deformations and regional land water reserve changes can be established. Gaussian random white noise with noise standard deviations of 0.0001m, 0.0001m and 0.0005m is added to the GNSS north direction deformation, east direction deformation and vertical deformation respectively. The specific process steps are realized as follows:
step 1, according to the green function theory of mass load, the relationship between the GNSS north, east and vertical deformations and the regional land water reserve change can be expressed as:
Figure BDA0003262664830000063
wherein n (theta), e (theta) and u (theta) are respectively the north, east and vertical deformation of the GNSS; Δ M is the hydrographic mass load, MRIs the earth mass; r is the mean radius of the earth; lnAnd hnThe load Love number; theta is the angular distance between the grid point and the GNSS survey station; p is a radical ofnIs Legendre polynomial; alpha is the included angle between the horizontal deformation and the north direction.
Step 2, establishing an observation equation between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load; and forming a joint inversion method equation set according to the GNSS vertical and horizontal deformation (northing and easting) observation equations.
The observation equations of the GNSS north, east and vertical deformation are as follows:
Figure BDA0003262664830000064
wherein, yN、yEAnd yUCorresponding to the observed values of the GNSS north, east and vertical deformation respectively, AN、AEAnd AUDesigning a matrix for a Green function corresponding to three-dimensional deformation, wherein x is a land water reserve change parameter to be estimated, and eN、eEAnd eURespectively corresponding to the residual vectors of the observation values of north, east and vertical deformation,
Figure BDA0003262664830000071
and
Figure BDA0003262664830000072
is the variance of the error of the observed value, IN、IEAnd IUIs the North, east and vertical deformation observations y of the sum GNSSN、yEAnd yUThe associated identity matrix.
According to the observation equations of the GNSS north direction, east direction and vertical deformation, a normal equation set can be obtained:
Figure BDA0003262664830000073
wherein the content of the first and second substances,
Figure BDA0003262664830000074
Figure BDA0003262664830000075
is ANTranspose of (P)NIs a weight matrix corresponding to the north deformation observed value n (theta),
Figure BDA0003262664830000076
Figure BDA0003262664830000077
is AETranspose of (P)EIs a weight matrix corresponding to the east deformation observed value e (theta),
Figure BDA0003262664830000078
Figure BDA0003262664830000079
is AUTranspose of (P)UIs a weight matrix corresponding to the vertical deformation observed value u (theta),
Figure BDA00032626648300000710
in order to verify that the result of the joint inversion is better than the result of the individual inversion of the change of the terrestrial water reserves in the inversion region by using the GNSS north direction, the east direction and the vertical deformation alone, the inversion equation of the change of the terrestrial water reserves in the inversion region by using the GNSS north direction, the east direction or the vertical deformation alone can be obtained according to the single observation equation and the prior constraint equation:
Figure BDA00032626648300000711
wherein σ2And for the noise variance, lambda is a regularization parameter, A is a design matrix, y represents an observed value, and min represents the minimum (specifically, it can be understood that when a residual two-norm of the observed value, the model and the constraint matrix is the minimum, the optimal regional water reserve change parameter x to be estimated can be obtained).
Change of water reserve to be requested
Figure BDA00032626648300000712
Can be expressed as:
Figure BDA00032626648300000713
where P is a weighted array of observations given the variance σ of the noise2And an initial value of the regularization parameter lambda, the regional land water reserve change can be iteratively calculated through variance component estimation.
In the embodiment, the observation equation of the GNSS northbound deformation is as follows:
Figure BDA00032626648300000714
the observation equation of the GNSS east deformation is as follows:
Figure BDA00032626648300000715
the observation equation of the GNSS vertical deformation is as follows:
Figure BDA0003262664830000081
the prior constraint equation is Lx ═ 0. Respectively simulating observation data by utilizing GNSS (global navigation satellite system) three-dimensional deformation containing errors, and inverting the model according to single type of data
Figure BDA0003262664830000082
Regional land water reserve changes can be iteratively calculated using variance component estimates. Inversion results of the GNSS north direction, east direction and vertical deformation and residual images of the inversion results of the GNSS north direction, east direction and vertical deformation and original signals can be obtained respectively. The GNSS vertical deformation is more sensitive to the change of the hydrological load signal, but the observation precision is lower. The GNSS north and east deformation observation precision is high, but the sensitivity to the hydrological mass load change is low. Therefore, the GNSS three-dimensional deformation data can be comprehensively utilized to realize advantage complementation, and further the optimal regional land water reserve change can be inverted. In addition, in the simulation research area (continental region of China), the standard deviations of the GNSS north, east and vertical deformation independent inversion results and the original signal residuals are 24.93mm, 30.32mm and 26.11mm respectively.
And 3, inverting regional land water reserve change according to the least square joint adjustment by using the result obtained in the step 2, wherein a GNSS three-dimensional deformation joint inversion model is formed according to a normal equation and by combining a prior constraint equation, then an observed value noise variance and a regularization parameter initial value are given, and the optimal weight ratio of various data is iteratively calculated by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
Because the GNSS three-dimensional deformation data has different sensibility to hydrological mass load change and different observation precision, the optimal fusion of the two types of observation values needs to be realized by fully considering the optimal fusion mode and criterion thereof, and the optimal weight ratio of the two types of data is determined by variance component estimation.
The land water reserve change of a joint GNSS three-dimensional deformation inversion region belongs to a discrete ill-conditioned problem, an appropriate regularization method is required to be utilized to carry out constraint solution on a ill-conditioned equation set, and the commonly used methods including Tikhonov regularization, Truncated Singular Value Decomposition (TSVD), ridge estimation and the like are limited by how to quickly and effectively obtain optimal regularization parameters.
The invention further provides that joint inversion needs to determine a joint inversion model and an optimal weight ratio, and the method also comprises the following substeps:
3.1 forming a GNSS three-dimensional deformation joint inversion model according to a normal equation and by combining a prior information equation, namely forming a joint inversion target function: | | ANx-yN||2+||AEx-yE||2+||AUx-y||2+λ||Lx||2Min, where λ is the regularization parameter.
The joint inversion model of the regional land water reserve variation parameter estimation value to be solved can be expressed as:
Figure BDA0003262664830000083
3.2 setting an observation value noise variance and a regularization parameter initial value, determining an optimal weight ratio by iterative computation by using a variance component estimation method, and optimally combining and inverting regional land water storage change.
Given a
Figure BDA0003262664830000091
And a regularization parameter lambda is an initial value, and an optimal regional land water reserve change result can be estimated through variance component estimation iteration weighting.
In this embodiment, the reliability of the joint inversion result can be evaluated by performing statistical analysis on the Global Navigation Satellite System (GNSS) northbound direction, eastern direction and vertical deformation and the residual standard deviation of the joint three-dimensional deformation inversion result and the original signal.
In the embodiment, the three-dimensional deformation simulation data of the GNSS with the error is combined to invert the land water reserve change of the Chinese continental region.
The method specifically comprises the following substeps:
3.1 obtaining a joint inversion model according to the observation equation and the prior constraint equation of the GNSS east, north and vertical deformation in the step 2:
Figure BDA0003262664830000092
because the change of land water reserves in the region is inverted by utilizing the GNSS three-dimensional deformation, the inversion result is regularized and constrained by utilizing a discrete Laplace matrix L, and the constraint equation is as follows:
Lx＝0，
wherein L is Laplace matrix, specifically Laplace template
Figure BDA0003262664830000093
L2＝[1 -2 1]And
Figure BDA0003262664830000094
the method comprises the following steps that x is a land water reserve change parameter to be estimated, and 0 is a zero vector consistent with the length of an observed value;
and 3.2, taking the noise standard deviation of the simulated GNSS three-dimensional deformation as an initial variance value, giving a regularization parameter, and estimating an optimal regional land water storage change result by iterative weighting through variance components. The GNSS three-dimensional deformation joint inversion result is obtained, and because the GNSS vertical deformation is more sensitive to the change of the hydrological load signal, the observation precision is lower; the GNSS north and east deformation observation precision is high, but the sensitivity to the hydrological mass load change is low; compared with the method for inverting the land water reserve change by singly utilizing the north direction, east direction or vertical deformation of the GNSS, the joint inversion can comprehensively utilize the three-dimensional deformation information to carry out better constraint on the land water reserve change spatial distribution, and further obtain a more reliable regional land water reserve change inversion result. Residual graphs of inversion and original signals by utilizing the GNSS north direction, east direction or vertical deformation can be obtained, wherein standard deviations of the inversion results and the original signals are 24.93mm, 30.32mm and 26.11 mm. A residual map of the joint inversion result and the original signal can be obtained, wherein the standard deviation of the residual of the inversion result and the original signal is 18.52 mm. According to the result, the STD of the joint inversion result and the original signal residual is far smaller than that of the inversion result and the real signal residual by independently utilizing the one-dimensional deformation data, the joint inversion result can fully utilize the GNSS deformation observation data, and then the inversion can obtain a more reliable regional water reserve change inversion result.
In order to verify the technical effect of the method, regional land water reserve change can be solved according to the joint inversion model in the step 3, the regional land water reserve change is compared with inversion results which independently utilize the northward direction, the eastern direction and the vertical deformation of the GNSS, and the standard deviation of the inversion results and the real signal residual is used as the judgment of the reliability of the inversion results.
In the embodiment, the standard deviations of the regional land water reserve change and the original signal residual error which are independently inverted by utilizing the northing direction, the easting direction and the vertical deformation of the GNSS are respectively 24.93mm, 30.32mm and 26.11mm, the standard deviation of the regional land water reserve change and the original signal residual error which are jointly inverted by the GNSS is 18.52mm and is obviously smaller than the residual error standard deviation of the independent inversion results of the two types of data, and the accuracy and the reliability of the joint inversion result are better.
In summary, the invention provides a method for inverting regional land water reserve change by combining GNSS three-dimensional deformation. The method is mainly characterized in that respective advantages of the change of the terrestrial water reserves of the GNSS in the north direction, the east direction and the vertical deformation in the inversion region are comprehensively utilized, advantage complementation is effectively achieved, and the accuracy and the reliability of the regional terrestrial water reserve change estimation result can be improved through joint inversion. Finally, a numerical simulation test is carried out in the mainland area of China by a joint inversion method, and the correctness and the effectiveness of the method are verified.
In specific implementation, a person skilled in the art can implement the automatic operation process by using a computer software technology, and a system device for implementing the method, such as a computer-readable storage medium storing a corresponding computer program according to the technical solution of the present invention and a computer device including a corresponding computer program for operating the computer program, should also be within the scope of the present invention.
In some possible embodiments, a combined GNSS three-dimensional deformation inversion region land-water reservoir change inversion system is provided, which includes the following modules,
the first module is used for establishing the relation between the northern, east and vertical deformation of the GNSS and the water reserve change of the regional land according to the Green function theory of mass load;
the second module is used for establishing observation equations between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load, and then forming a joint inversion method equation set according to the GNSS vertical, north and east observation equations;
and the third module is used for inverting regional land water reserve change according to the least square joint adjustment by using the result obtained by the second module, and comprises the steps of forming a GNSS three-dimensional deformation joint inversion model according to a normal equation and a priori constraint equation, then giving an observed value noise variance and a regularization parameter initial value, and iteratively calculating the optimal weight ratio of various data by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
In some possible embodiments, there is provided a computer apparatus comprising a processor and a memory, the memory storing a computer program which, when executed by the processor, implements a joint three-dimensional deformation inversion region land-water reservoir change inversion method as described above.
In some possible embodiments, a computer readable storage medium is provided, having stored thereon a computer program that, when executed by a processor, implements a joint three-dimensional deformation inversion region land-water reservoir change inversion method as described above.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.

Claims (9)

1. A regional land water reserve change inversion method combined with GNSS three-dimensional deformation is characterized in that: comprises the following steps of (a) carrying out,
step 1, establishing a relation between the northbound, eastern and vertical deformation of the GNSS and the water reserve change of the regional land according to the Green function theory of mass load;
step 2, establishing observation equations between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load, and then forming a joint inversion method equation set according to the observation equations of the GNSS north, east and vertical deformation;
and 3, inverting regional land water reserve change according to the least square joint adjustment by using the result obtained in the step 2, wherein a GNSS three-dimensional deformation joint inversion model is formed according to a normal equation and by combining a prior constraint equation, then an observed value noise variance and a regularization parameter initial value are given, and the optimal weight ratio of various data is iteratively calculated by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
2. The method for inversion of regional land-water reserve change in joint GNSS three-dimensional deformation according to claim 1, wherein: in the step 1, the relation between the GNSS north direction, east direction and vertical deformation and the regional land water reserve change can be expressed as follows;
Figure FDA0003262664820000011
wherein n (theta), e (theta) and u (theta) are respectively the north, east and vertical deformation of the GNSS; Δ M is the hydrographic mass load, MRIs the earth mass; r is the mean radius of the earth; lnAnd hnThe load Love number; theta is grid point and GNSS surveyAngular separation between stations; p is a radical ofnIs Legendre polynomial; alpha is the included angle between the horizontal deformation and the north direction.
3. The method for inversion of regional land-water reserve change in joint GNSS three-dimensional deformation according to claim 1, wherein: the expression of the observation equation between the regional land water reserve change and the GNSS north, east and vertical deformation in the step 2 is as follows;
Figure FDA0003262664820000021
wherein, yN、yEAnd yUCorresponding to the observed values of the GNSS north, east and vertical deformation respectively, AN、AEAnd AUDesigning a matrix for a Green function corresponding to three-dimensional deformation, wherein x is a land water reserve change parameter to be estimated, and eN、eEAnd eURespectively corresponding to the residual vectors of the observation values of north, east and vertical deformation,
Figure FDA0003262664820000022
and
Figure FDA0003262664820000023
is the variance of the error of the observed value, IN、IEAnd IUIs the North, east and vertical deformation observations y of the sum GNSSN、yEAnd yUThe associated identity matrix.
4. The regional land-water reserve change inversion method combining GNSS three-dimensional deformation according to claim 3, characterized in that: the specific expression of the joint inversion method equation set in the step 2 is as follows,
Figure FDA0003262664820000024
wherein the content of the first and second substances,
Figure FDA0003262664820000025
Figure FDA0003262664820000026
is ANTranspose of (P)NIs a weight matrix corresponding to the north deformation observed value n (theta),
Figure FDA0003262664820000027
Figure FDA0003262664820000028
is AETranspose of (P)EIs a weight matrix corresponding to the east deformation observed value e (theta),
Figure FDA0003262664820000029
Figure FDA00032626648200000210
is AUTranspose of (P)UIs a weight matrix corresponding to the vertical deformation observed value u (theta),
Figure FDA00032626648200000211
5. the method for inversion of regional land-water reserve change in joint GNSS three-dimensional deformation according to claim 1, wherein: in step 3, the prior constraint equation is Lx is 0, and a discrete Laplace matrix L is used for carrying out regularization constraint on the inversion result;
wherein L is Laplace matrix, specifically Laplace template
Figure FDA00032626648200000212
L2＝[1 2 1]And
Figure FDA00032626648200000213
composition, x is land water reserve change parameter to be estimated, 0 is consistent with observation value lengthA zero vector.
6. The method of claim 4, wherein the inversion method of regional land-water reserve change by combining GNSS three-dimensional deformation is as follows: in step 3, a GNSS three-dimensional deformation joint inversion model is formed according to a normal equation and by combining a prior constraint equation, namely a joint inversion target function is formed: | | ANx-yN||2+||AEx-yE||2+||AUx-y||2+λ||Lx||2Min, where λ is the regularization parameter and L is the laplace matrix;
the joint inversion model of the regional land water reserve variation parameter estimation value to be solved can be expressed as:
Figure FDA0003262664820000031
wherein, PN、PEAnd PURespectively weighting arrays of GNSS north direction, east direction and vertical deformation observed values;
given three types of observation noise variance
Figure FDA0003262664820000032
And a regularization parameter alpha is an initial value, and an optimal regional land water reserve change result is solved through variance component estimation iteration weighting.
7. Regional land water reserves change inversion system of joint GNSS three-dimensional deformation, its characterized in that: comprises the following modules which are used for realizing the functions of the system,
the first module is used for establishing the relation between the northern, east and vertical deformation of the GNSS and the water reserve change of the regional land according to the Green function theory of mass load;
the second module is used for establishing observation equations between regional land water reserve change and GNSS north, east and vertical deformation according to a Green function theory of mass load, and then forming a joint inversion method equation set according to the GNSS north, east and vertical deformation observation equations;
and the third module is used for inverting regional land water reserve change according to the least square joint adjustment by using the result obtained by the second module, and comprises the steps of forming a GNSS three-dimensional deformation joint inversion model according to a normal equation and a priori constraint equation, then giving an observed value noise variance and a regularization parameter initial value, and iteratively calculating the optimal weight ratio of various data by using a variance component estimation method to obtain the regional land water reserve change of joint inversion.
8. A computer device comprising a processor and a memory, the memory storing a computer program, characterized in that: the processor, when executing the computer program, realizes the steps of the method of any of claims 1-6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: the computer program, when executed by a processor, implementing the steps of any of the methods of claims 1-6.
CN202111084343.7A 2021-09-15 2021-09-15 Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation Active CN113899301B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111084343.7A CN113899301B (en) 2021-09-15 2021-09-15 Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111084343.7A CN113899301B (en) 2021-09-15 2021-09-15 Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation

Publications (2)

Publication Number Publication Date
CN113899301A true CN113899301A (en) 2022-01-07
CN113899301B CN113899301B (en) 2022-07-15

Family

ID=79028736

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111084343.7A Active CN113899301B (en) 2021-09-15 2021-09-15 Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation

Country Status (1)

Country Link
CN (1) CN113899301B (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106529164A (en) * 2016-11-03 2017-03-22 清华大学 Method and system for acquiring ground water storage variation value by combining GRACE satellite
CN111241473A (en) * 2019-12-27 2020-06-05 中国空间技术研究院 Method for improving regional underground water reserve estimation precision
CN111912333A (en) * 2020-08-13 2020-11-10 北京讯腾智慧科技股份有限公司 Linear deformation monitoring method based on Beidou GNSS and triaxial tilt sensor
US20210011149A1 (en) * 2019-05-21 2021-01-14 Central South University InSAR and GNSS weighting method for three-dimensional surface deformation estimation
AU2020103449A4 (en) * 2020-11-16 2021-01-28 China University Of Mining And Technology Method for monitoring the water level of reservoir by using GNSS triple-frequency phase combination data
CN112989589A (en) * 2021-03-05 2021-06-18 武汉大学 Local earth surface quality change inversion method and system combining GRACE and GNSS

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106529164A (en) * 2016-11-03 2017-03-22 清华大学 Method and system for acquiring ground water storage variation value by combining GRACE satellite
US20210011149A1 (en) * 2019-05-21 2021-01-14 Central South University InSAR and GNSS weighting method for three-dimensional surface deformation estimation
CN111241473A (en) * 2019-12-27 2020-06-05 中国空间技术研究院 Method for improving regional underground water reserve estimation precision
CN111912333A (en) * 2020-08-13 2020-11-10 北京讯腾智慧科技股份有限公司 Linear deformation monitoring method based on Beidou GNSS and triaxial tilt sensor
AU2020103449A4 (en) * 2020-11-16 2021-01-28 China University Of Mining And Technology Method for monitoring the water level of reservoir by using GNSS triple-frequency phase combination data
CN112989589A (en) * 2021-03-05 2021-06-18 武汉大学 Local earth surface quality change inversion method and system combining GRACE and GNSS

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
薛康等: "附加GPS时序约束的GRACE陆地水储量反演", 《地球物理学进展》 *

Also Published As

Publication number Publication date
CN113899301B (en) 2022-07-15

Similar Documents

Publication Publication Date Title
Chen Satellite gravimetry and mass transport in the earth system
CN110045432B (en) Gravity field forward modeling method and three-dimensional inversion method under spherical coordinate system based on 3D-GLQ
El-Ashmawy Investigation of the accuracy of google earth elevation data
CN100520298C (en) Method for fine correcting satellite remote sensing image geometry based on topographic line
Yao et al. An improved iterative algorithm for 3-D ionospheric tomography reconstruction
Ziggah et al. Coordinate transformation between global and local data based on artificial neural network with k-fold cross-validation in Ghana
CN112989589B (en) Local earth surface quality change inversion method and system combining GRACE and GNSS
Carouge et al. What can we learn from European continuous atmospheric CO 2 measurements to quantify regional fluxes–Part 2: Sensitivity of flux accuracy to inverse setup
CN114417646B (en) High-dimensional heterogeneous precipitation data fusion method and system
CN104007479A (en) Ionized layer chromatography technology and ionized layer delay correction method based on multi-scale subdivision
CN115238550A (en) Self-adaptive unstructured grid landslide rainfall geoelectric field numerical simulation calculation method
Liang et al. Vertical surface displacement of mainland China from GPS using the multisurface function method
Ali On the selection of an interpolation method for creating a terrain model (TM) from LIDAR data
CN113899301B (en) Regional land water reserve change inversion method and system combining GNSS three-dimensional deformation
ZHONG et al. Inversion of regional terrestrial water storage changes using GPS vertical displacements based on TSVD-Tikhonov regularization method
CN115755103B (en) Robust self-adaptive GNSS water vapor chromatography method
CN116609859A (en) Weather disaster high-resolution regional mode forecasting system and method
Volodin et al. Reproduction of World Ocean circulation by the CORE-II scenario with the models INMOM and INMIO
CN113268869B (en) Method and system for monitoring change of earth surface quality
Yang et al. On study of the Earth topography correction for the GRACE surface mass estimation
CN117272182B (en) Daily air temperature prediction method, device, medium and equipment
CN114969628A (en) Method, system and equipment for inverting regional land water reserve change by using GPS (global positioning system)
Kumar et al. Comparison of Digital Surface Modelling Techniques for Sloping Hill Terrain Using GPS Data
Yuan et al. Preliminary research on imaging the ionosphere using CIT and China permanent GPS tracking station data
Manjunatha et al. High Resolution Digital Elevation Model for Chamundi Hill of Mysuru city, Karnataka, India using Geospatial Technology

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant