A method for joint inversion of terrestrial water storage changes and related devices

Abstract

This application relates to the field of water storage analysis technology, and provides a method and related equipment for jointly inverting changes in terrestrial water storage. The method includes: acquiring a hydrological model and surface deformation data of a target area, and constructing basis functions for the target area; performing spherical harmonic analysis on the hydrological model to convert it into spherical harmonic coefficients; establishing a first observation equation between the spherical harmonic coefficients and the basis function coefficients, and establishing a second observation equation between the surface deformation data and the basis function coefficients; solving for the basis function coefficients based on the first and second observation equations to obtain the final coefficient vector of the basis functions; and calculating the change in terrestrial water storage in the target area based on the final coefficient vector and the basis functions. The method of this application can simultaneously improve the spatiotemporal resolution and accuracy of jointly inverting changes in terrestrial water storage.

Description

Technical Field

[0001] This application relates to the field of water storage analysis technology, and in particular to a method and related equipment for joint inversion of changes in terrestrial water storage. Background Technology

[0002] Land water storage change is a comprehensive hydrological indicator encompassing multiple dimensions, including surface runoff, lake water bodies, glaciers / snow cover, soil water, and groundwater. It can be used to assess water resource distribution patterns. my country is rich in freshwater resources, but due to complex geography, topography, and climate types, water resources are unevenly distributed across regions, exacerbating droughts, floods, and extreme rainfall events triggered by climate change. Therefore, constructing high-precision, high spatiotemporal resolution land water storage change products can provide scientific basis and key data support for my country's water resource management, regional water cycle monitoring, and responses to extreme climate change.

[0003] Currently, the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite (GFO) provide an effective technical approach for monitoring changes in terrestrial water storage. However, limited by factors such as the orbital configuration, altitude, and background field model errors of the GRACE / GFO satellites, they can only invert changes in terrestrial water storage at large and medium scales globally. The migration and flow of terrestrial water storage leads to geometric deformation of the Earth's surface. This deformation can be continuously monitored with millimeter-level precision by Global Navigation Satellite Systems (GNSS), and the BeiDou Navigation Satellite System is one of the four major GNSS satellite navigation systems. Therefore, surface deformation monitored by BeiDou can be directly used to invert changes in terrestrial water storage. However, due to limitations imposed by varying levels of economic development and topographical conditions in different regions, not all areas have a densely distributed network of BeiDou reference stations for surface deformation monitoring. Therefore, the spatial resolution and accuracy of terrestrial water storage changes inverted using BeiDou surface deformation monitoring data are insufficient in areas with sparsely distributed stations. Current research attempts to address the insufficient spatial resolution and accuracy in sparse areas of BeiDou reference stations by jointly inverting terrestrial water storage changes using BeiDou surface deformation data and GRACE / GFO satellite gravity observations. However, the low spatiotemporal resolution (monthly temporal resolution and approximately 300–500 km spatial resolution) of GRACE / GFO data products results in a relatively low spatiotemporal resolution for the current BeiDou surface deformation and GRACE / GFO joint terrestrial water storage change data.

[0004] This shows that current methods for jointly inverting changes in terrestrial water storage cannot simultaneously address the issues of spatiotemporal resolution and accuracy. Summary of the Invention

[0005] This application provides a method and related equipment for jointly inverting changes in terrestrial water storage, which can solve the problem that the joint inversion of changes in terrestrial water storage cannot simultaneously take into account spatiotemporal resolution and accuracy.

[0006] In a first aspect, embodiments of this application provide a method for jointly inverting changes in terrestrial water storage, the method comprising: Obtain hydrological models and surface deformation data for the target area, and construct basis functions for the target area; the basis functions reflect the changes in terrestrial water storage at different spatial scales in the target area; Perform spherical harmonic analysis on the hydrological model to convert the hydrological model into spherical harmonic coefficients; Establish the first observation equation between the spherical harmonic coefficients and the basis function coefficients, and establish the second observation equation between the surface deformation data and the basis function coefficients; The basis function coefficients are solved by the first and second observation equations to obtain the final coefficient vector of the basis functions; The change in terrestrial water storage in the target area is calculated based on the final coefficient vector and basis functions.

[0007] Optionally, spherical harmonic analysis is performed on the hydrological model to convert it into spherical harmonic coefficients, including: Through the formula: ; Convert the hydrological model to spherical harmonic coefficients. ; in, Represents the longitude coordinates in the hydrological model. Represents the latitude coordinates in the hydrological model. express The terrestrial water storage value of the hydrological model. Represents the Earth's average radius. The dimensionless spherical harmonic coefficients represent the expansion of the hydrological model. For spherical harmonic basis functions, This represents the order of the expansion of the spherical harmonic basis functions. This indicates the degree of expansion of the spherical harmonic basis functions.

[0008] Optionally, the first observation equation is: ; in, Represents the basis function coefficients. This indicates the density of fresh water. This represents the Earth's average density. Represents the Love number for vertical deformation load. This represents the maximum order of the expansion of the basis functions. This represents the transformation coefficient matrix of the basis functions.

[0009] Optionally, the second observation equation is: ; in, Represents surface deformation data. This indicates the longitude coordinates of the BeiDou reference station. This indicates the latitude coordinates of the BeiDou reference station. Indicates the order of the basis function expansion. This represents the basis functions expanded at the BeiDou reference station.

[0010] Optionally, the basis function coefficients are solved according to the first and second observation equations to obtain the final coefficient vector of the basis functions, including: A rigorous model is obtained by jointly inverting the first and second observation equations. Solving the rigorous model yields the final coefficient vector of the basis functions.

[0011] Optional, rigorous model: ; in, This represents the vector of basis function coefficients obtained from the joint inversion. This represents the design matrix constructed based on the first observation equation. This represents the design matrix constructed based on the second observation equation. This indicates the transpose operation. This represents the weight matrix corresponding to the spherical harmonic coefficients. The weight matrix represents the data corresponding to surface deformation. Represents the vector of spherical harmonic coefficients. The observation vector represents the surface deformation data. This represents the error variance corresponding to the first observation equation. This represents the error variance corresponding to the second observation equation.

[0012] Optionally, the change in terrestrial water storage in the target area can be calculated based on the final coefficient vector and basis functions, including: Through the formula: ; Calculate the change in terrestrial water storage ; in, Denotes basis functions. This represents the final coefficient vector.

[0013] Secondly, embodiments of this application provide a device for jointly inverting changes in terrestrial water storage, comprising: The acquisition module is used to acquire hydrological models and surface deformation data of the target area, and construct basis functions for the target area; the basis functions reflect the changes in terrestrial water storage at different spatial scales in the target area; The spherical harmonic analysis module is used to perform spherical harmonic analysis on hydrological models and convert the hydrological models into spherical harmonic coefficients. A module is established to establish the first observation equation between the spherical harmonic coefficients and the basis function coefficients, and to establish the second observation equation between the surface deformation data and the basis function coefficients; The solution module is used to solve for the coefficients of the basis functions based on the first observation equation and the second observation equation, so as to obtain the final coefficient vector of the basis functions; The calculation module is used to calculate the change in terrestrial water storage in the target area based on the final coefficient vector and basis functions.

[0014] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned method for jointly inverting changes in terrestrial water storage.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned method for jointly inverting changes in terrestrial water storage.

[0016] The above-mentioned solution in this application has the following beneficial effects: In the embodiments of this application, a hydrological model and surface deformation data of the target area are acquired, and a basis function of the target area is constructed. Then, a spherical harmonic analysis is performed on the hydrological model to convert it into spherical harmonic coefficients. A first observation equation between the spherical harmonic coefficients and the basis function coefficients is established, and a second observation equation between the surface deformation data and the basis function coefficients is established. The basis function coefficients are then solved according to the first and second observation equations to obtain the final coefficient vector of the basis functions. Finally, the change in terrestrial water storage in the target area is calculated based on the final coefficient vector and the basis functions. Among them, joint inversion based on hydrological models and surface deformation data avoids the insufficient spatial resolution and accuracy of inversion in sparsely distributed areas due to the use of surface deformation data alone, effectively improving the inversion accuracy of land water storage changes in the target area. The introduction of hydrological models enables high spatiotemporal resolution simulation of land water storage changes. By solving the basis function coefficients through hydrological models and surface deformation data and conducting water storage change analysis, the advantages of hydrological models and surface deformation data in terms of spatiotemporal resolution, spectral sensitivity and accuracy are complementary, thereby simultaneously improving the accuracy and spatiotemporal resolution of joint inversion of land water storage changes.

[0017] Other beneficial effects of this application will be described in detail in the following detailed description section. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for jointly inverting changes in terrestrial water storage provided in an embodiment of this application; Figure 2 This is a schematic diagram of the boundary of a simulated research area provided in one embodiment of this application; Figure 3 A schematic diagram comparing the inversion results of different inversion models provided in an embodiment of this application; Figure 4 A schematic diagram of the structure of a device for jointly inverting changes in terrestrial water storage provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0020] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0021] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0022] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0023] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0024] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0025] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0026] To address the issue that existing joint inversion methods for terrestrial water storage changes cannot simultaneously achieve both spatiotemporal resolution and accuracy, this application provides a joint inversion method for terrestrial water storage change. This method acquires a hydrological model and surface deformation data for the target region, constructs basis functions for the target region, performs spherical harmonic analysis on the hydrological model to convert it into spherical harmonic coefficients, establishes a first observation equation between the spherical harmonic coefficients and the basis function coefficients, and establishes a second observation equation between the surface deformation data and the basis function coefficients. Then, the basis function coefficients are solved based on the first and second observation equations to obtain the final coefficient vector of the basis functions. Finally, the terrestrial water storage change value of the target region is calculated based on the final coefficient vector and the basis functions. Among them, joint inversion based on hydrological models and surface deformation data avoids the insufficient spatial resolution and accuracy of inversion in sparsely distributed areas due to the use of surface deformation data alone, effectively improving the inversion accuracy of land water storage changes in the target area. The introduction of hydrological models enables high spatiotemporal resolution simulation of land water storage changes. By solving the basis function coefficients through hydrological models and surface deformation data and conducting water storage change analysis, the advantages of hydrological models and surface deformation data in terms of spatiotemporal resolution, spectral sensitivity and accuracy are complementary, thereby simultaneously improving the accuracy and spatiotemporal resolution of joint inversion of land water storage changes.

[0027] The following is an exemplary description of the joint inversion method for changes in terrestrial water storage provided in this application.

[0028] like Figure 1 As shown, the joint inversion method for changes in terrestrial water storage provided in this application includes the following steps: Step 11: Obtain the hydrological model and surface deformation data of the target area, and construct the basis functions for the target area.

[0029] The aforementioned basis functions reflect the changes in terrestrial water storage at different spatial scales within the target area. The target area is the region requiring joint inversion of terrestrial water storage changes, such as a lake region. The aforementioned hydrological model is used to simulate the terrestrial water storage change process in the target area, including data such as the target area's topography, soil, land use static base map, and groundwater simulation results. The aforementioned surface deformation data is used to describe the topographic changes in the target area over a period of time (i.e., the time period for which joint inversion of terrestrial water storage changes is required), including relevant data such as Interferometric Synthetic Aperture Radar (InSAR).

[0030] In some embodiments of this application, hydrological models of the target area can be obtained using open-source tools such as SWAT or shared data centers, and surface deformation data can be obtained by accessing publicly available data websites of satellites such as BeiDou.

[0031] For example, the basis functions mentioned above can be Slepian basis functions. The expression is: ; in, This represents the maximum order of the expansion of the basis functions. This represents the matrix of basis function transformation coefficients. Represents spherical harmonic basis functions. The longitude coordinates of each point within the target area. The coordinates of each point within the target area are the latitude and longitude coordinates.

[0032] Step 12: Perform spherical harmonic analysis on the hydrological model to convert the hydrological model into spherical harmonic coefficients.

[0033] Specifically, through the formula: ; Convert the hydrological model to spherical harmonic coefficients. .

[0034] in, Represents the longitude coordinates in the hydrological model. Represents the latitude coordinates in the hydrological model. express The terrestrial water storage value of the hydrological model. Represents the Earth's average radius. The dimensionless spherical harmonic coefficients represent the expansion of the hydrological model. For spherical harmonic basis functions, This represents the order of the expansion of the spherical harmonic basis functions. This indicates the degree of expansion of the spherical harmonic basis functions.

[0035] Step 13: Establish the first observation equation between the spherical harmonic coefficients and the basis function coefficients, and establish the second observation equation between the surface deformation data and the basis function coefficients.

[0036] The first observation equation described above is used to describe the functional transformation relationship between spherical harmonic coefficients and basis function coefficients, and the second observation equation described above is used to describe the functional transformation relationship between surface deformation data and basis function coefficients.

[0037] Specifically, the first observation equation is: ; in, Represents the basis function coefficients. This indicates the density of fresh water. This represents the Earth's average density. Represents the Love number for vertical deformation load. This represents the maximum order of the expansion of the basis functions. This represents the transformation coefficient matrix of the basis functions.

[0038] For example, the linear model of the first observation equation is: , Represents the vector of spherical harmonic coefficients. The number of spherical harmonic coefficients. According to the first observation equation The constructed design matrix Let be the vector of basis function coefficients corresponding to the change in terrestrial water storage to be estimated. The number of basis function coefficients. The residual vector is the estimated value of the spherical harmonic coefficient vector. This represents the error variance corresponding to the first observation equation. It is an identity matrix.

[0039] The second observation equation is: ; in, Represents surface deformation data. This indicates the longitude coordinates of the BeiDou reference station. This indicates the latitude coordinates of the BeiDou reference station. This represents the order of the Slepian basis function expansion. This represents the basis functions expanded at the BeiDou reference station.

[0040] For example, the linear model of the second observation equation is: , The observation vector represents the surface deformation data. This indicates the number of BeiDou surface deformation observations. For the second observation equation The constructed design matrix Let be the vector of basis function coefficients corresponding to the change in terrestrial water storage to be estimated. The number of basis function coefficients. This represents the error variance corresponding to the second observation equation. This represents the residual vector of BeiDou surface deformation observations. It is an identity matrix related to the number of BeiDou reference stations.

[0041] Step 14: Solve for the basis function coefficients according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions.

[0042] The final coefficient vector mentioned above includes all the solved basis function coefficients.

[0043] In some embodiments of this application, the step of solving the basis function coefficients according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions includes: The first step is to perform a joint inversion of the first and second observation equations to obtain a rigorous model.

[0044] Specifically, the rigorous model is as follows: ; in, This represents the vector of basis function coefficients obtained from the joint inversion (including all basis function coefficients). This represents the design matrix constructed based on the first observation equation. This represents the design matrix constructed based on the second observation equation. This indicates the transpose operation. This represents the weight matrix corresponding to the spherical harmonic coefficients. The weight matrix represents the data corresponding to surface deformation. Represents the vector of spherical harmonic coefficients. The observation vector represents the surface deformation data. This represents the error variance corresponding to the first observation equation. This represents the error variance corresponding to the second observation equation.

[0045] The second step is to solve the rigorous model to obtain the final coefficient vector of the basis functions.

[0046] Specifically, the hydrological model and topographic deformation data are input into the above-mentioned rigorous model for calculation, and the calculated basis function coefficient vector is used as the final coefficient vector.

[0047] Step 15: Calculate the change in terrestrial water storage in the target area based on the final coefficient vector and basis functions.

[0048] The above-mentioned changes in terrestrial water storage are used to describe the changes in terrestrial water storage in the target area over a period of time.

[0049] Specifically, through the formula: ; Calculate the change in terrestrial water storage .

[0050] in, Denotes basis functions. This represents the final coefficient vector.

[0051] It is worth mentioning that the joint inversion based on hydrological models and surface deformation data avoids the insufficient spatial resolution and accuracy of inversion in sparsely distributed areas due to the use of surface deformation data alone. This effectively improves the inversion accuracy of changes in terrestrial water storage in the target area. The introduction of hydrological models enables high spatiotemporal resolution simulation of changes in terrestrial water storage. By solving the basis function coefficients and analyzing water storage changes through hydrological models and surface deformation data, the advantages of hydrological models and surface deformation data in terms of spatiotemporal resolution, spectral sensitivity, and accuracy are complementary, thereby simultaneously improving the accuracy and spatiotemporal resolution of the joint inversion of changes in terrestrial water storage.

[0052] The method of this application will be illustrated below with a specific example.

[0053] The Earth system model (AOHIS, Atmosphere, Ocean, Hydrology, Ice and Solid Earth) and the time-varying spherical harmonic coefficient products (DEAL+AOerr, DEAL plus Atmosphere Ocean error) for a certain region from January 2004 to December 2006 were used for experimental analysis. Closed-loop simulation experiments were conducted to illustrate the method provided in this embodiment of the invention. In this embodiment, for ease of calculation, the study area was divided into a 1°×1° geographic grid, 1096 BeiDou reference stations were selected, and the maximum order of the basis function expansion was 60.

[0054] The simulated map of the area is as follows Figure 2 As shown, the black line represents the region boundary, the dots represent the simulated locations of BeiDou reference stations, the horizontal axis is longitude, and the vertical axis is latitude.

[0055] To verify the technical effect of this application, the change in land water storage can be calculated based on the joint inversion model mentioned above, and compared with the results of inversion using the hydrological model and BeiDou surface deformation alone. The standard deviation and correlation coefficient between the inversion results and the real signal are used as the criteria for evaluating the reliability of the inversion results.

[0056] The inversion results of real signals and different inversion models (BeiDou surface deformation inversion, hydrological model inversion, and joint inversion) are compared to, for example... Figure 3 As shown, the horizontal axis of each subplot represents geographical longitude, and the vertical axis represents geographical latitude. The plot content is the change in terrestrial water storage, with the unit being millimeters (mm).

[0057] The results of BeiDou surface deformation inversion are as follows: Figure 3 As shown in (b), the unit is millimeters (mm), the horizontal axis is geographical longitude, and the vertical axis is geographical latitude. This is compared with the actual signal (…). Figure 3 The standard deviation between (a) and (b) is 67.76 mm, and the correlation coefficient is 0.77.

[0058] The results of the hydrological model inversion alone are as follows: Figure 3 As shown in (c), the unit is millimeters (mm), the horizontal axis is geographical longitude, and the vertical axis is geographical latitude. This is compared to the actual signal (…). Figure 3 The standard deviation between (a) and (b) is 68.67 mm, and the correlation coefficient is 0.75.

[0059] The joint inversion results are as follows Figure 3 As shown in (d), the unit is millimeters (mm), the horizontal axis is geographical longitude, and the vertical axis is geographical latitude. This is compared to the actual signal ( Figure 3 The standard deviation between (a) and (b) is 59.12 mm, and the correlation coefficient is 0.83.

[0060] It can be seen that the standard deviation and correlation coefficient between the BeiDou surface deformation inversion results and the original signal are 67.76 mm and 0.77, respectively. The standard deviation and correlation coefficient between the hydrological model inversion results and the original signal are 68.67 mm and 0.75, respectively. The standard deviation and correlation coefficient between the land water storage change obtained by combining the hydrological model and BeiDou surface deformation inversion according to the method of this application and the original signal are 59.12 mm and 0.83, respectively. These are significantly better than the standard deviation and correlation coefficient of the two types of data obtained by inversion alone, indicating that the accuracy and reliability of the combined inversion results are better.

[0061] The following is an exemplary description of the joint inversion device for changes in terrestrial water storage provided in this application.

[0062] like Figure 4 As shown, this application embodiment provides a joint inversion device for land water storage change, the joint inversion device 400 for land water storage change includes: The acquisition module 401 is used to acquire the hydrological model and surface deformation data of the target area, and construct the basis functions of the target area; the basis functions reflect the changes in terrestrial water storage at different spatial scales in the target area; The spherical harmonic analysis module 402 is used to perform spherical harmonic analysis on the hydrological model and convert the hydrological model into spherical harmonic coefficients. Module 403 is established to establish the first observation equation between the spherical harmonic coefficients and the basis function coefficients, and to establish the second observation equation between the surface deformation data and the basis function coefficients. The solver module 404 is used to solve the basis function coefficients according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions; The calculation module 405 is used to calculate the change in terrestrial water storage in the target area based on the final coefficient vector and basis functions.

[0063] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0064] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0065] like Figure 5 As shown, an embodiment of this application provides a terminal device, wherein the terminal device D10 of this embodiment includes: at least one processor D100 ( Figure 5The diagram shows only one processor, a memory D101, and a computer program D102 stored in the memory D101 and executable on the at least one processor D100, wherein the processor D100 executes the computer program D102 to implement the steps in any of the above method embodiments.

[0066] Specifically, when the processor D100 executes the computer program D102, it acquires the hydrological model and surface deformation data of the target area, constructs the basis functions of the target area, performs spherical harmonic analysis on the hydrological model to convert the hydrological model into spherical harmonic coefficients, establishes a first observation equation between the spherical harmonic coefficients and the basis function coefficients, and establishes a second observation equation between the surface deformation data and the basis function coefficients. Then, it solves the basis function coefficients according to the first and second observation equations to obtain the final coefficient vector of the basis functions. Finally, it calculates the change value of terrestrial water storage in the target area based on the final coefficient vector and the basis functions. Among them, joint inversion based on hydrological models and surface deformation data avoids the insufficient spatial resolution and accuracy of inversion in sparsely distributed areas due to the use of surface deformation data alone, effectively improving the inversion accuracy of land water storage changes in the target area. The introduction of hydrological models enables high spatiotemporal resolution simulation of land water storage changes. By solving the basis function coefficients through hydrological models and surface deformation data and conducting water storage change analysis, the advantages of hydrological models and surface deformation data in terms of spatiotemporal resolution, spectral sensitivity and accuracy are complementary, thereby simultaneously improving the accuracy and spatiotemporal resolution of joint inversion of land water storage changes.

[0067] The processor D100 can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0068] In some embodiments, the memory D101 may be an internal storage unit of the terminal device D10, such as a hard disk or memory of the terminal device D10. In other embodiments, the memory D101 may be an external storage device of the terminal device D10, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the terminal device D10. Furthermore, the memory D101 may include both internal and external storage units of the terminal device D10. The memory D101 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory D101 can also be used to temporarily store data that has been output or will be output.

[0069] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0070] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0071] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to the joint inversion of terrestrial water storage change method apparatus / terminal equipment, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0072] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0073] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0074] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention.

Claims

1. A method for jointly inverting changes in terrestrial water storage, characterized in that, include: Obtain the hydrological model and surface deformation data of the target area, and construct the basis functions for the target area; The basis functions reflect the changes in terrestrial water storage at different spatial scales in the target region; Perform spherical harmonic analysis on the hydrological model to convert the hydrological model into spherical harmonic coefficients; A first observation equation is established between the spherical harmonic coefficients and the basis function coefficients, and a second observation equation is established between the surface deformation data and the basis function coefficients; The basis function coefficients are solved according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions; The change in terrestrial water storage in the target area is calculated based on the final coefficient vector and the basis function.

2. The method for jointly inverting changes in terrestrial water storage according to claim 1, characterized in that, The step of performing spherical harmonic analysis on the hydrological model, converting the hydrological model into spherical harmonic coefficients, includes: Through the formula: Convert the hydrological model to spherical harmonic coefficients. ; in, This represents the longitude coordinates in the hydrological model. This represents the latitude coordinates in the hydrological model. express The terrestrial water storage value of the hydrological model. Represents the Earth's average radius. The dimensionless spherical harmonic coefficients represent the expansion of the hydrological model. For spherical harmonic basis functions, This represents the order of the expansion of the spherical harmonic basis functions. This indicates the degree of expansion of the spherical harmonic basis functions.

3. The method for jointly inverting changes in terrestrial water storage according to claim 2, characterized in that, The first observation equation is: in, Represents the basis function coefficients. This indicates the density of fresh water. This represents the Earth's average density. Represents the Love number for vertical deformation load. This represents the maximum order of the expansion of the basis functions. This represents the transformation coefficient matrix of the basis functions.

4. The method for jointly inverting changes in terrestrial water storage according to claim 3, characterized in that, The second observation equation is: in, Represents surface deformation data. This indicates the longitude coordinates of the BeiDou reference station. This indicates the latitude coordinates of the BeiDou reference station. Indicates the order of the basis function expansion. This represents the basis functions expanded at the BeiDou reference station.

5. The method for jointly inverting changes in terrestrial water storage according to claim 1, characterized in that, The step of solving the basis function coefficients according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions includes: A rigorous model is obtained by jointly inverting the first and second observation equations. The rigorous model is solved to obtain the final coefficient vector of the basis functions.

6. The method for jointly inverting changes in terrestrial water storage according to claim 5, characterized in that, The rigorous model is as follows: in, This represents the vector of basis function coefficients obtained from the joint inversion. This represents the design matrix constructed based on the first observation equation. This represents the design matrix constructed based on the second observation equation. This indicates the transpose operation. This represents the weight matrix corresponding to the spherical harmonic coefficients. The weight matrix represents the data corresponding to surface deformation. Represents the vector of spherical harmonic coefficients. The observation vector represents the surface deformation data. This represents the error variance corresponding to the first observation equation. This represents the error variance corresponding to the second observation equation.

7. The method for jointly inverting changes in terrestrial water storage according to claim 6, characterized in that, The calculation of the change in terrestrial water storage in the target area based on the final coefficient vector and the basis function includes: Through the formula: Calculate the change in terrestrial water storage ; in, Denotes basis functions. This represents the final coefficient vector.

8. A device for jointly inverting changes in terrestrial water storage, characterized in that, include: The acquisition module is used to acquire the hydrological model and surface deformation data of the target area, and to construct the basis functions of the target area; The basis functions reflect the changes in terrestrial water storage at different spatial scales in the target region; The spherical harmonic analysis module is used to perform spherical harmonic analysis on the hydrological model and convert the hydrological model into spherical harmonic coefficients. A module is established to establish a first observation equation between the spherical harmonic coefficients and the basis function coefficients, and to establish a second observation equation between the surface deformation data and the basis function coefficients; The solution module is used to solve the basis function coefficients according to the first observation equation and the second observation equation to obtain the final coefficient vector of the basis functions; The calculation module is used to calculate the change in terrestrial water storage in the target area based on the final coefficient vector and the basis function.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method for jointly inverting changes in terrestrial water storage as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for jointly inverting changes in terrestrial water storage as described in any one of claims 1 to 7.

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