River flow remote sensing estimation method

Abstract

The invention relates to the technical field of river flow monitoring, in particular to a river flow remote sensing estimation method. The method comprises the following steps: firstly, constructing a water level flow functional expression, acquiring a satellite elevation above an observation point by using a height measurement satellite, acquiring an echo signal by using the height measurement satellite, calculating the observation water level of the observation point according to the satellite elevation and the echo signal, and finally, applying the water level flow functional expression to the observation water level to calculate the river flow of the observation point. Due to the fact that the coverage range of the height measuring satellites is far larger than the coverage range of the flow observation station, the river flow in the global range can be estimated through the data collected by the height measuring satellites, and the coverage range of the monitored river flow is enlarged.

Description

Technical Field

[0001] The invention relates to the technical field of river flow monitoring, and in particular to a river flow remote sensing estimation method. Background Art

[0002] As a variable that comprehensively reflects multiple hydrological processes in a basin, river flow can not only directly indicate changes in climate and environment, but also predict potential water resource crises and ecological risks. With the intensification of global climate change, the frequency and intensity of extreme weather events are increasing, and flow monitoring has become particularly critical. Traditional flow measurement methods mainly rely on field observations at ground hydrological stations. However, this method has significant limitations in river monitoring around the world. First, the high cost of equipment installation and maintenance limits the widespread deployment of hydrological stations, resulting in insufficient data coverage. In addition, there are obstacles to data sharing between different countries and regions, making it difficult to integrate global flow monitoring data, thereby limiting a comprehensive understanding of global hydrological dynamics.

[0003] In summary, existing river flow monitoring methods are difficult to monitor river flow around the world.

[0004] Therefore, the prior art still needs to be improved and enhanced. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a river flow remote sensing estimation method, which solves the problem that the existing river flow monitoring methods are difficult to monitor global river flows.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for remote sensing estimation of river flow, which comprises:

[0008] Acquire the satellite altitude of the altimeter satellite above the observation point, and acquire the target echo signal generated by the altimeter satellite transmitting a signal to the observation point;

[0009] Determining the observed water level of the observation point based on the satellite altitude and the target echo signal;

[0010] A pre-constructed water level flow function is applied to the observed water level to obtain the river flow at the observation point.

[0011] In one implementation, the altimeter satellite is a third-generation sentinel satellite, and obtaining the satellite altitude of the altimeter satellite above an observation point and obtaining a target echo signal generated by the altimeter satellite transmitting a signal to the observation point includes:

[0012] At the same time, the satellite altitude of the third-generation Sentinel satellite above the observation point is obtained, a number of echo signals generated by the third-generation Sentinel satellite transmitting signals to the observation point are obtained, and a target echo signal corresponding to the river is screened out from the multiple echo signals.

[0013] In one implementation, the determining the observed water level of the observation point based on the satellite altitude and the target echo signal includes:

[0014] Obtaining the water level height of the observation point;

[0015] Obtaining the time taken by the altimeter satellite from transmitting a signal to receiving the target echo signal, and determining the satellite-to-ground distance between the river surface at the observation point and the altimeter satellite based on the time;

[0016] The observed water level of the observation point is determined according to the satellite altitude, the satellite-to-ground distance, and the water level height.

[0017] In one implementation, applying a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point includes:

[0018] Determine an exponential water level flow function in the water level flow function, wherein the base of the exponential water level flow function is an independent variable, and the base is an expression constructed by the water level;

[0019] Substituting the observed water level as an independent variable into the exponential water level flow function, the river flow at the observation point is obtained.

[0020] In a second aspect, an embodiment of the present invention further provides a method for constructing a water level flow function, comprising:

[0021] Establishing an exponential function with unknown parameters, wherein the base of the exponential function is an independent variable, the base is an expression constructed by the water level, and the flow is a dependent variable of the exponential function;

[0022] Determine the sample water level of each sample site around the world and the sample flow rate corresponding to the sample water level; solve the index according to the sample water level and the sample flow rate of each group of sample sites

[0023] The unknown parameters of the function are obtained to obtain the water level flow function, and the water level flow function is used to implement the above-mentioned river flow remote sensing estimation method.

[0024] In one implementation, determining the sample water level of each sample site around the world and the sample flow rate corresponding to the sample water level includes:

[0025] Determine virtual sample sites formed by intersections of altimeter satellite tracks with river networks;

[0026] Determine a measured sample site within a set distance range of the virtual sample site, and use the virtual sample site and the measured sample site as each sample site;

[0027] Determining the sample water level of the virtual sample site by means of the altimetry satellite;

[0028] The sample flow rate of the measured sample site is obtained by the water volume monitoring equipment of the measured sample site.

[0029] In one implementation, solving the unknown parameters of the exponential function according to the sample water level and the sample flow rate of each group of the sample sites includes:

[0030] A Bayesian hierarchical model is applied to the sample water level and the sample flow rate of each group of sample stations and the exponential function to solve unknown parameters.

[0031] In a third aspect, an embodiment of the present invention further provides a river flow remote sensing estimation device, wherein the device comprises the following components:

[0032] An information acquisition module is used to obtain the satellite altitude of the altimeter satellite above the observation point, and obtain the target echo signal generated by the altimeter satellite transmitting a signal to the observation point;

[0033] A water level determination module, used to determine the observed water level of the observation point based on the satellite altitude and the target echo signal;

[0034] The flow calculation module is used to apply a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point.

[0035] In a fourth aspect, an embodiment of the present invention further provides a terminal device, wherein the terminal device comprises a memory, a processor, and a river flow remote sensing estimation program stored in the memory and executable on the processor, and when the processor executes the river flow remote sensing estimation program, the steps of the river flow remote sensing estimation method described above are implemented;

[0036] Alternatively, the terminal device includes a memory, a processor, and a water level flow function construction program stored in the memory and executable on the processor. When the processor executes the water level flow function construction program, the steps of the above-mentioned water level flow function construction method are implemented.

[0037] In a fifth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein a river flow remote sensing estimation program is stored on the computer-readable storage medium, and when the river flow remote sensing estimation program is executed by a processor, the steps of the river flow remote sensing estimation method described above are implemented;

[0038] Alternatively, a water level flow function formula construction program is stored on the computer-readable storage medium, and when the water level flow function formula construction program is executed by the processor, the steps of the water level flow function formula construction method described above are implemented.

[0039] Beneficial effects: The present invention uses an altimeter satellite to obtain its satellite elevation above the observation point, and uses the altimeter satellite to collect echo signals, calculates the observed water level of the observation point according to the satellite elevation and the echo signal, and finally calculates the river flow at the observation point according to the observed water level. Since the coverage of the altimeter satellite is much larger than the coverage of the flow observation station, the above data collected by the altimeter satellite in this application can estimate the river flow in the global range, thereby increasing the coverage of the river flow that can be monitored. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is the overall flow chart of the present invention;

[0041] Figure 2 Schematic diagram of satellite altitude, satellite-to-ground distance, and water level height in an embodiment of the present invention;

[0042] Figure 3 A flow chart of estimating river flow in an embodiment of the present invention;

[0043] Figure 4 A schematic diagram of a water level-flow curve in an embodiment of the present invention;

[0044] Figure 5 A structural diagram of a river flow remote sensing estimation device provided by the present invention;

[0045] Figure 6 This is a block diagram of the internal structure principle of the terminal device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following is a clear and complete description of the technical solution of the present invention in combination with the embodiments and the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Studies have found that river flow, as a variable that comprehensively reflects multiple hydrological processes in a basin, can not only directly indicate changes in climate and environment, but also predict potential water resource crises and ecological risks. With the intensification of global climate change, the frequency and intensity of extreme weather events are increasing, and flow monitoring has become particularly critical. Traditional flow measurement methods mainly rely on field observations at ground hydrological stations. However, this method has significant limitations in river monitoring around the world. First, the high cost of equipment installation and maintenance limits the widespread deployment of hydrological stations, resulting in insufficient data coverage. In addition, there are obstacles to data sharing between different countries and regions, making it difficult to integrate global flow monitoring data, thereby limiting a comprehensive understanding of global hydrological dynamics.

[0048] In order to solve the above technical problems, the present invention provides a remote sensing estimation method for river flow, which solves the problem that the existing river flow monitoring method is difficult to monitor global river flow. In specific implementation, the satellite elevation of the altimeter satellite above the observation point is first obtained, and the target echo signal generated by the altimeter satellite transmitting the signal to the observation point is obtained; then, based on the satellite elevation and the target echo signal, the observed water level of the observation point is determined; finally, the pre-constructed water level flow function is applied to the observed water level to obtain the river flow at the observation point. The present invention can increase the coverage of the river flow that can be monitored.

[0049] The river flow remote sensing estimation method of this embodiment can be applied to a terminal device, which can be a terminal product with a satellite signal processing function, such as a river flow measurement device. Figure 1 As shown in , the specific steps include:

[0050] S100, constructing a water level flow function;

[0051] S200, obtaining a satellite altitude of an altimeter satellite above an observation point, and obtaining a target echo signal generated by the altimeter satellite transmitting a signal to the observation point;

[0052] S300, determining the observed water level of the observation point based on the satellite altitude and the target echo signal;

[0053] S400, applying a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point.

[0054] Embodiment 1: In this embodiment, step S100 includes the following specific steps S101 to S105:

[0055] S101, establishing an exponential function containing unknown parameters, wherein the base of the exponential function is an independent variable, the base is an expression constructed by the water level, and the flow rate is a dependent variable of the exponential function.

[0056] Q=a(h-z0) b

[0057] h is the independent variable of water level, Q is the dependent variable of river flow, a, z0 and b are three unknown parameters. Constructing the water level-flow function means solving the three unknown parameters a, z0 and b.

[0058] Exponential function: Q = a(h-z0) b , the derivation process of the formula is as follows:

[0059]

[0060] Where Q is the river flow, A is the flow area, n is the Manning roughness coefficient, R is the hydraulic radius, and S is the slope.

[0061] For a wide rectangular channel, assuming that the area A is equal to the product of the average depth (D) and the cross-sectional width (w), we can obtain:

[0062]

[0063] If the river channel is wide enough, the hydraulic radius R is close to the river channel depth D; if wS 1 / 2 / n as the constant a, the formula takes a more simplified form:

[0064] Q≈aD 5 / 3 ≈a(h-z0) 5 / 3

[0065] Among them, h is the river water level or water surface elevation, and z0 is the zero flow water level.

[0066] The cross-sectional geometry of a river is irregular. Therefore, the above approximation may not hold, which results in a change in the constant a and the exponential coefficient (5 / 3). Therefore, a more generalized rating curve function can be expressed as follows:

[0067] Q=a(h-z0) b

[0068] In order to facilitate the solution of the three parameters a, z0, and b, the Bayesian hierarchical model is used to obtain the posterior distribution of these parameters, and the Markov chain Monte Carlo (MCMC) sampling method is used to obtain the posterior predictive distribution. The Bayesian formula of the power law model is expressed on a logarithmic scale as:

[0069] lnQ=lna+bln(h-z0)

[0070] S102, determining a virtual sample site formed by the intersection of the altimetry satellite's orbit and the river network.

[0071] The altimetry satellite is the Sentinel-3 satellite, which is the third-generation Sentinel satellite and can provide global river water level data.

[0072] The orbit of the altimeter satellite is above the earth, and the river network is on the earth's surface. When the orbit of the altimeter satellite is projected onto the earth's surface, an intersection will be formed between the projected orbit and the river network. This intersection is the virtual sample site. If there are multiple intersections, the intersections are selected according to the river width where each intersection is located, and the selected intersections are used as virtual sample sites.

[0073] For example, the projection track intersects with five rivers in the river network, so there are five intersections, three of which are less than 300 meters wide. The remaining two intersections can be used as virtual sample sites, that is, the width of the river where the virtual sample site is located is greater than 300 meters.

[0074] S103, determining a measured sample site within a set distance range of the virtual sample site, and using the virtual sample site and the measured sample site as each sample site.

[0075] According to the location of the virtual sample site, the real site within the set distance range of the location is used as the measured sample site, and the measured sample site is used to monitor the flow of the river. In this embodiment, the distance range is set to 30km, and the river monitored by the measured sample site and the river where the virtual sample site is located are the same river, so as to ensure that the water level flow function (the water level flow function is as follows) constructed later Figure 4 The data used in the water level-discharge relationship curve shown in the figure are spatially consistent, thereby improving the reliability and accuracy of the estimation results.

[0076] S104, determining the sample water level of the virtual sample site by using the altimetry satellite; and acquiring the sample flow of the actual sample site by using the water volume monitoring equipment of the actual sample site.

[0077] The sample water level and sample flow are the water level and flow of the same river, and the sampling time unit of the water level and flow is one day, that is, the water level and river flow are collected once a day to form a data set for solving unknown parameters.

[0078] S105, applying a Bayesian hierarchical model to the sample water level and the sample flow of each group of the sample stations and the exponential function to solve unknown parameters to obtain a water level and flow function.

[0079] Each group of sample stations includes virtual sample stations and measured sample stations. The virtual sample stations and measured sample stations of the same group match each other in space, that is, the distance between the virtual sample stations and measured sample stations of the same group is less than 30km, and the virtual sample stations and measured sample stations of the same group are located on the same river. Substitute the sample water levels of the virtual sample stations of the same group into Q = a(h-z0) b , that is, let h be the sample water level; substitute the sample flow of the measured sample station in the same group into Q = a (h-z0) b , that is, let Q equal the sample flow. Substitute the sample water level of all groups of virtual sample stations and the sample flow of the measured sample stations into Q = a (h-z0) b , we form several equations, and then combine them with the Bayesian hierarchical model to solve the values ​​of the three unknown parameters a, z0, and b.

[0080] In this embodiment, the sample water level of the virtual sample site is obtained in the following manner:

[0081] Collect the satellite altitude of the altimeter radar. The satellite altitude is the relative altitude of the altimeter radar. Figure 2 The height of the reference ellipsoid in

[0082] The altimeter is controlled to transmit electromagnetic waves to the virtual sample site, and the echo signal reflected by the river at the virtual sample site is collected. The satellite-to-ground distance is calculated based on the time taken to transmit the electromagnetic wave and receive the echo signal and the propagation speed of the electromagnetic wave. Finally, the sample water level of the virtual sample site is obtained by subtracting the satellite-to-ground distance from the satellite altitude and then subtracting the water level height. The water level is the distance between the water surface of the river and the geoid. The geoid is the water level of the static average seawater, and the water level height is the distance between the geoid and the ground surface.

[0083] In this embodiment, the sample flow of the measured sample site can be collected in real time by the water volume monitoring equipment of the site, and can also be obtained through the Global River Discharge Centre (GRDC) and water resources related websites of various countries.

[0084] Embodiment 2: This embodiment provides a global river flow estimation system, which includes a data acquisition module, a data preprocessing module, a water level-flow relationship curve construction module, and a flow estimation and result verification module, wherein the data acquisition module is used to obtain water level data and measured flow data. Figure 3As shown in the figure, the data preprocessing module is used to delete outliers in the sample water level and sample flow and perform spatial pairing processing. The water level-flow relationship curve construction module includes the Bayesian model construction module and the parameter estimation module; the flow estimation module is used to estimate the historical flow and real-time flow of the river; the result verification module is used to compare the estimated flow with the measured flow data and calculate the Kling-Gupta efficiency coefficient (KGE) and the normalized root mean square error (NRMSE).

[0085] The Bayesian theory of this embodiment can significantly improve the accuracy of river flow estimation, solving the problem that traditional methods are difficult to accurately estimate global river flow. This embodiment combines the Markov Chain Monte Carlo (MCMC) method in Bayesian theory to perform parameter estimation, so that the parameters have clear physical meanings and significantly improve the accuracy and robustness of the estimation results. This embodiment estimates river flow by combining the water level-flow relationship curve with the water level data obtained by satellites, reducing dependence on ground measurement sites, reducing costs and time consumption, and expanding the coverage of flow monitoring.

[0086] Embodiment 3 is based on embodiment 1. In this embodiment, step S200 includes the following specific steps: at the same time, obtaining the satellite elevation h′ of the third-generation Sentinel satellite (the third-generation Sentinel satellite is Sentinel-3) above the observation point, obtaining a plurality of echo signals generated by the third-generation Sentinel satellite transmitting signals to the observation point, and screening out the target echo signal corresponding to the river from the plurality of echo signals.

[0087] The signal transmitter on the satellite sends an electromagnetic wave signal to the observation point. There are various objects between the transmitter and the observation point. Each object will reflect the electromagnetic wave to form an echo signal, but the echo signal formed by the reflection of each object is different. Therefore, the echo signal formed by the river reflection (target echo signal) can be screened out.

[0088] Embodiment 4, based on embodiment 3, step S300 in this embodiment includes the following specific steps S301, S302, S303:

[0089] S301, obtaining the water level height N of the observation point.

[0090] like Figure 2 As shown, the water level height N is the distance between the geoid and the ground surface. The geoid is also the level of the still mean sea water.

[0091] The water level height N includes positive and negative heights. The positive height means that the water level is above the ground surface, and the negative height means that the water level is below the ground surface.

[0092] S302, obtaining the time taken by the altimeter satellite from transmitting the signal to receiving the target echo signal, and determining the satellite-to-ground distance R between the river surface at the observation point and the altimeter satellite based on the time.

[0093] The duration divided by two is the one-way duration, and the one-way duration multiplied by the transmission speed of the electromagnetic wave is the distance R between the satellite and the earth.

[0094] S303: Determine the observed water level h of the observation point according to the satellite altitude h′, the satellite-to-earth distance R, and the water level height N.

[0095] h=h′-RN

[0096] Embodiment 5, based on embodiment 3, the detailed process of step S400 in this embodiment is as follows: Substitute the observed water level h as an independent variable into the exponential water level flow function to obtain the river flow Q at the observation point.

[0097] That is, substitute the observed water level h into Q = a(h-z0) b Since the values ​​of the three parameters a, z0, and b have been obtained through the first embodiment, the value of Q can be calculated.

[0098] In summary, the present invention obtains high-resolution water surface height data on a global scale by utilizing the radar altimeter carried by the Sentinel-3 satellite, thus overcoming the shortcomings of traditional ground observation methods in spatial coverage. Compared with ground measurement points limited to specific areas, the present invention can achieve comprehensive monitoring of rivers on a global scale, significantly improving the spatial coverage and accuracy of flow estimation. The present invention applies Bayesian theory to river flow estimation, and proposes a water level-flow relationship based on Bayesian inference. Bayesian theory can effectively integrate satellite altimetry data with ground observation data, and perform uncertainty analysis on flow estimation. This method not only improves the accuracy of flow estimation, but also enhances the reliability and applicability of the model, especially in complex hydrological environments around the world.

[0099] This embodiment also provides a river flow remote sensing estimation device, such as Figure 5 As shown, the device comprises the following components:

[0100] The information acquisition module 01 is used to obtain the satellite altitude of the altimeter satellite above the observation point, and obtain the target echo signal generated by the altimeter satellite transmitting a signal to the observation point;

[0101] A water level determination module 02, used to determine the observed water level of the observation point based on the satellite altitude and the target echo signal;

[0102] The flow calculation module 03 is used to apply a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point.

[0103] Based on the above embodiments, the present invention further provides a terminal device, whose principle block diagram can be shown as follows: Figure 6 As shown. The terminal device includes a processor, a memory, a network interface, and a display screen connected through a system bus. Among them, the processor of the terminal device is used to provide computing and control capabilities. The memory of the terminal device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the terminal device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for remote sensing estimation of river flow is implemented. The display screen of the terminal device can be a liquid crystal display screen or an electronic ink display screen.

[0104] Those skilled in the art will understand that Figure 6 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the terminal device to which the scheme of the present invention is applied. The specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0105] In one embodiment, a terminal device is provided. The terminal device includes a memory, a processor, and a river flow remote sensing estimation program stored in the memory and executable on the processor. When the processor executes the river flow remote sensing estimation program, the following operation instructions are implemented:

[0106] Acquire the satellite altitude of the altimeter satellite above the observation point, and acquire the target echo signal generated by the altimeter satellite transmitting a signal to the observation point;

[0107] Determining the observed water level of the observation point based on the satellite altitude and the target echo signal;

[0108] A pre-constructed water level flow function is applied to the observed water level to obtain the river flow at the observation point.

[0109] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A river flow remote sensing estimation method, characterized in that: include: Acquire the satellite altitude of the altimeter satellite above the observation point, and acquire the target echo signal generated by the altimeter satellite transmitting a signal to the observation point; Determining the observed water level of the observation point based on the satellite altitude and the target echo signal; A pre-constructed water level flow function is applied to the observed water level to obtain the river flow at the observation point.

2. The method for estimating river flow by remote sensing according to claim 1, characterized in that: The altimeter satellite is a third-generation sentinel satellite, and the step of obtaining the satellite altitude of the altimeter satellite above an observation point and obtaining a target echo signal generated by the altimeter satellite transmitting a signal to the observation point includes: At the same time, the satellite altitude of the third-generation Sentinel satellite above the observation point is obtained, a number of echo signals generated by the third-generation Sentinel satellite transmitting signals to the observation point are obtained, and a target echo signal corresponding to the river is screened out from the multiple echo signals.

3. The river flow remote sensing estimation method according to claim 1, characterized in that: The step of determining the observed water level of the observation point based on the satellite altitude and the target echo signal comprises: Obtaining the water level height of the observation point; Obtaining the time taken by the altimeter satellite from transmitting a signal to receiving the target echo signal, and determining the satellite-to-ground distance between the river surface at the observation point and the altimeter satellite based on the time; The observed water level of the observation point is determined according to the satellite altitude, the satellite-to-ground distance, and the water level height.

4. The river flow remote sensing estimation method according to claim 1, characterized in that: Applying a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point includes: Determine an exponential water level flow function in the water level flow function, wherein the base of the exponential water level flow function is an independent variable, and the base is an expression constructed by the water level; Substituting the observed water level as an independent variable into the exponential water level flow function, the river flow at the observation point is obtained.

5. A method for constructing a water level flow function, characterized in that: include: Establishing an exponential function with unknown parameters, wherein the base of the exponential function is an independent variable, the base is an expression constructed by the water level, and the flow is a dependent variable of the exponential function; Determine the sample water level at each sample site around the world and the sample flow rate corresponding to the sample water level; According to the sample water level and the sample flow of each group of sample stations, the unknown parameters of the exponential function are solved to obtain a water level flow function, and the water level flow function is used to implement the river flow remote sensing estimation method as described in claim 1.

6. The method for constructing a water level flow function according to claim 5, characterized in that: The determining of the sample water level of each sample site around the world and the sample flow rate corresponding to the sample water level includes: Determine virtual sample sites formed by intersections of altimeter satellite tracks with river networks; Determine a measured sample site within a set distance range of the virtual sample site, and use the virtual sample site and the measured sample site as each sample site; Determining the sample water level of the virtual sample site by means of the altimetry satellite; The sample flow rate of the measured sample site is obtained by the water volume monitoring equipment of the measured sample site.

7. The method for constructing a water level flow function according to claim 5, characterized in that: Solving the unknown parameters of the exponential function according to the sample water level and the sample flow rate of each group of the sample sites includes: A Bayesian hierarchical model is applied to the sample water level and the sample flow rate of each group of sample stations and the exponential function to solve unknown parameters.

8. A river flow remote sensing estimation device, characterized in that: The device comprises the following components: An information acquisition module is used to obtain the satellite altitude of the altimeter satellite above the observation point, and obtain the target echo signal generated by the altimeter satellite transmitting a signal to the observation point; A water level determination module, used to determine the observed water level of the observation point based on the satellite altitude and the target echo signal; The flow calculation module is used to apply a pre-constructed water level flow function to the observed water level to obtain the river flow at the observation point.

9. A terminal device, characterized in that: The terminal device comprises a memory, a processor, and a river flow remote sensing estimation program stored in the memory and executable on the processor, and when the processor executes the river flow remote sensing estimation program, the steps of the river flow remote sensing estimation method according to any one of claims 1 to 4 are implemented; Alternatively, the terminal device includes a memory, a processor, and a water level flow function construction program stored in the memory and executable on the processor. When the processor executes the water level flow function construction program, the steps of the water level flow function construction method as described in any one of claims 5 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a river flow remote sensing estimation program, and when the river flow remote sensing estimation program is executed by the processor, the steps of the river flow remote sensing estimation method according to any one of claims 1 to 4 are implemented; Alternatively, a water level flow function construction program is stored on the computer-readable storage medium, and when the water level flow function construction program is executed by the processor, the steps of the water level flow function construction method as described in any one of claims 5-7 are implemented.

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