Groundwater recharge estimation method, device and computer equipment

Abstract

The present application relates to a method, device and computer equipment for estimating groundwater recharge. The method comprises: obtaining multi-source data of a target area; determining the actual scene multi-layer soil moisture content data of the target area based on actual scene evapotranspiration data, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and reference crop evapotranspiration data; inputting the actual scene multi-layer soil moisture content data into a water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and soil parameter data of the target area; determining the groundwater recharge of the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scene. The present method can accurately obtain the groundwater recharge.

Description

Technical Field

[0001] The present application relates to the field of water conservancy technology, and in particular to a method, device, computer equipment, computer-readable storage medium and computer program product for estimating groundwater recharge. Background Art

[0002] The available fresh water resources on the earth are in short supply, and agricultural water consumption is high. The effective utilization coefficient of irrigation water needs to be further improved. Many regions rely heavily on groundwater irrigation, leading to over-exploitation of groundwater. Therefore, timely and accurate acquisition of groundwater recharge and assessment of the impact of irrigation on groundwater recharge are crucial for the coordinated management of surface water and groundwater and guiding the sustainable development of agriculture.

[0003] Therefore, there is an urgent need for a groundwater recharge estimation method that can accurately obtain groundwater recharge. Summary of the invention

[0004] Based on this, it is necessary to provide a groundwater recharge estimation method, device, computer equipment, computer readable storage medium and computer program product that can accurately obtain groundwater recharge in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for estimating groundwater recharge, comprising:

[0006] Acquire multi-source data of the target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observation, natural scene evapotranspiration data based on land surface model, natural scene multi-layer soil moisture data based on land surface model and reference crop evapotranspiration data based on meteorological observation;

[0007] Determining the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data;

[0008] Inputting the actual scene multi-layer soil moisture content data into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data of the target area;

[0009] The groundwater recharge in the target area is determined based on the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

[0010] In one embodiment, determining the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data includes:

[0011] According to the actual scene evapotranspiration data of the non-irrigated pixel and the natural scene evapotranspiration data, performing system error correction on the actual scene evapotranspiration data to obtain corrected actual scene evapotranspiration data;

[0012] Based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, the actual scene multi-layer soil moisture content data of the target area is determined.

[0013] In one embodiment, the determining the actual scene multi-layer soil moisture content data of the target area based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data includes:

[0014] Calculating the natural scene evapotranspiration ratio based on the natural scene evapotranspiration data and the reference crop evapotranspiration data;

[0015] For each layer of soil, a linear fitting parameter corresponding to the layer of soil is obtained by fitting according to a preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the natural scene evapotranspiration ratio and the moisture content data of multiple layers of soil in the natural scene corresponding to the layer of soil;

[0016] Calculating the actual scene evapotranspiration ratio based on the corrected actual scene evapotranspiration data and the reference crop evapotranspiration data;

[0017] For each layer of soil, the actual scene multi-layer soil moisture content data corresponding to the layer of soil is calculated based on the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the actual scene evapotranspiration ratio, the natural scene evapotranspiration ratio, the natural scene multi-layer soil moisture content data corresponding to the layer of soil and the linear fitting parameters corresponding to the layer of soil.

[0018] In one embodiment, the method further comprises:

[0019] According to the soil water balance equation, constructing the water balance residual of the top layer soil and the water balance residual of the middle layer soil;

[0020] Constructing a loss function of a target neural network according to the water balance residual of the top layer of soil and the water balance residual of the middle layer of soil;

[0021] Based on the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data, the target neural network is trained to obtain a vertical water movement model between two adjacent soil layers.

[0022] In one embodiment, determining the groundwater recharge of the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scenario includes:

[0023] Calculating the actual scene soil moisture content change of the bottom soil according to the actual scene multi-layer soil moisture content data of the bottom soil and a preset time step;

[0024] Calculate the actual scenario recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the actual scenario, the actual scenario soil moisture content change of the bottom soil and the soil thickness of the bottom soil;

[0025] The groundwater recharge amount of the target area is determined according to the actual scenario recharge amount.

[0026] In one embodiment, determining the groundwater recharge amount of the target area according to the actual scenario recharge amount includes:

[0027] Calculate the vertical movement of soil moisture in the natural scene based on the soil water balance equation, the multi-layer soil moisture content data of the natural scene, precipitation, surface runoff, and the evapotranspiration data of the natural scene;

[0028] Calculating the change in soil moisture content in the natural scene of the bottom soil according to the natural scene multi-layer soil moisture content data of the bottom soil and a preset time step;

[0029] Calculate the natural scene recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the natural scene, the change in soil moisture content in the natural scene of the bottom soil, and the soil thickness of the bottom soil;

[0030] The difference between the actual scene supply amount and the natural scene supply amount is used as the irrigation supply amount of the target area;

[0031] The groundwater recharge amount of the target area is determined based on the irrigation recharge amount.

[0032] In a second aspect, the present application also provides a groundwater recharge estimation device, comprising:

[0033] An acquisition module is used to acquire multi-source data of a target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observations, natural scene evapotranspiration data based on land surface models, multi-layer soil moisture data of natural scenes based on land surface models, and reference crop evapotranspiration data based on meteorological observations;

[0034] A first determination module is used to determine the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data;

[0035] The second determination module is used to input the actual scene multi-layer soil moisture content data into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data of the target area;

[0036] The third determination module is used to determine the groundwater recharge in the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

[0037] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps described in the first aspect when executing the computer program.

[0038] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps described in the first aspect above.

[0039] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements the steps described in the first aspect when executed by a processor.

[0040] The above-mentioned groundwater recharge estimation method, device, computer equipment, computer-readable storage medium and computer program product obtain multi-source data of the target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observation, natural scene evapotranspiration data based on land surface model, natural scene multi-layer soil moisture data based on land surface model and reference crop evapotranspiration data based on meteorological observation; based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture data and the reference crop evapotranspiration data, the actual scene multi-layer soil moisture data of the target area is determined; the actual scene multi-layer soil moisture data is input into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture data and the soil parameter data of the target area; according to the soil water balance equation and the soil moisture vertical movement in the actual scene, the groundwater recharge of the target area is determined. In this way, according to the actual scene evapotranspiration data based on remote sensing observations, the natural scene evapotranspiration data based on the land surface model and the natural scene multi-layer soil moisture data, and the reference crop evapotranspiration data based on meteorological observations, the actual scene multi-layer soil moisture data is determined, and it is input into the water vertical movement model generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture data and the soil parameter data, so as to obtain the vertical movement of soil moisture in the actual scene, and determine the groundwater recharge in the target area in combination with the soil water balance equation, taking into account the influence of irrigation and other environmental factors in the actual scene, which conforms to the actual situation and can accurately obtain the groundwater recharge. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic diagram of a process of estimating groundwater recharge in one embodiment;

[0043] Figure 2 A flowchart of a step of determining actual scene multi-layer soil moisture content data of a target area based on actual scene evapotranspiration data, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data, and reference crop evapotranspiration data in one embodiment;

[0044] Figure 3 A flowchart of a step of determining actual scene multi-layer soil moisture content data of a target area based on corrected actual scene evapotranspiration data, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and reference crop evapotranspiration data in one embodiment;

[0045] Figure 4 A schematic flow chart of the steps further included in the method for estimating groundwater recharge in one embodiment;

[0046] Figure 5 It is a flowchart of the steps of determining the groundwater recharge amount of the target area according to the soil water balance equation and the vertical movement of soil moisture in an actual scenario in one embodiment;

[0047] Figure 6 A schematic flow chart of a step of determining groundwater recharge amount in a target area according to actual recharge amount in an embodiment;

[0048] Figure 7 A schematic diagram of the linear fitting relationship between the irrigation water consumption calculated by the model and the irrigation water intake / water consumption in the water resources bulletin for the target area A and the five sub-areas bf included in A in one embodiment;

[0049] Fig. 8A A schematic diagram showing a trend comparison of irrigation water intake in a plurality of sub-areas 01-16 included in a target area A in an embodiment from 2003 to 2022 according to a statistical bulletin and irrigation water intake calculated by a model;

[0050] Figure 8B A schematic diagram showing a trend comparison of irrigation water withdrawals from 2003 to 2022 for multiple sub-areas 17 to 31 included in a target area A according to a statistical bulletin and irrigation water withdrawals calculated by a model in an embodiment;

[0051] Fig. 9 is a structural block diagram of a groundwater recharge estimation device in one embodiment;

[0052] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] In one embodiment, Figure 1As shown, a method for estimating groundwater recharge is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. Among them, the terminal can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head-mounted device can be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. In this embodiment, the method includes the following steps:

[0055] Step 101: Acquire multi-source data of a target area.

[0056] Among them, multi-source data include actual scene evapotranspiration data based on remote sensing observations, natural scene evapotranspiration data based on land surface models, natural scene multi-layer soil moisture data based on land surface models, and reference crop evapotranspiration data based on meteorological observations.

[0057] In an embodiment of the present application, the terminal can obtain the actual scene evapotranspiration data of the target area through remote sensing observation. The terminal can obtain the natural scene evapotranspiration data and natural scene multi-layer soil moisture data of the target area through the land surface model. The terminal can obtain the reference crop evapotranspiration data of the target area through meteorological observation.

[0058] Among them, the target area is the area where groundwater recharge estimation is to be performed. The target area can be a watershed or a field. The target area can be an area with different climatic conditions, such as arid areas and humid areas. The target area can be an area with different irrigation conditions, such as sprinkler irrigation areas, flood irrigation areas and drip irrigation areas. The target area can be an area with different multiple cropping indexes, such as single-season areas and double-season areas. The target area can be an area with different farmland types, such as paddy fields and dry land. The target area can include multiple pixels. Each pixel can be 0.1°. The multi-source data can also include at least one of soil parameter data and irrigation area data. The actual scene evapotranspiration data based on remote sensing observation is also called remote sensing evapotranspiration. The natural scene evapotranspiration data based on the land surface model is also called model evapotranspiration. The natural scene multi-layer soil moisture data based on the land surface model is also called model soil moisture. The natural scene multi-layer soil moisture data is the multi-layer soil moisture data under the natural scene. The multi-layer soil moisture data can include top layer soil moisture data, middle layer soil moisture data and bottom layer soil moisture data. The natural scene is a scene without irrigation, and the actual scene is a scene with irrigation. The impact of other human activities on the water cycle is not considered temporarily. The soil parameter data can be the soil parameter data of the Hamonized World Soil Database (HWSD).

[0059] Step 102, based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, determine the actual scene multi-layer soil moisture content data of the target area.

[0060] In the embodiment of the present application, the terminal establishes a linear relationship between soil moisture content and evapotranspiration ratio at preset time steps, pixel by pixel, and soil layer by soil based on natural scene evapotranspiration data, natural scene multi-layer soil moisture content data, and reference crop evapotranspiration data. Then, the terminal determines the actual scene multi-layer soil moisture content data of the target area based on the multiple linear relationships, the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data, and the reference crop evapotranspiration data.

[0061] Step 103: Input the multi-layer soil moisture content data of the actual scene into the vertical movement model of moisture between two adjacent soil layers to obtain the vertical movement of soil moisture in the actual scene of the target area.

[0062] Among them, the vertical water movement model is generated based on the soil water balance equation, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and soil parameter data of the target area.

[0063] In the embodiment of the present application, the water vertical movement model is used to characterize the water vertical movement between two adjacent layers of soil, that is, the soil water movement law, which can characterize the water vertical movement between the top layer of soil and the middle layer of soil and the water vertical movement between the middle layer of soil and the bottom layer of soil. The soil water vertical movement in actual scenarios includes: the water vertical movement between the top layer of soil and the middle layer of soil in actual scenarios and the water vertical movement between the middle layer of soil and the bottom layer of soil in actual scenarios.

[0064] The terminal generates a water vertical movement model between two adjacent soil layers based on the soil water balance equation, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data, and soil parameter data of the target area. Then, the terminal inputs the actual scene multi-layer soil moisture content data into the water vertical movement model to obtain the soil moisture vertical movement in the actual scene of the target area.

[0065] Specifically, the terminal establishes a target neural network based on the soil water balance equation. Then, the terminal trains the target neural network based on the evapotranspiration data of the natural scene, the multi-layer soil moisture content data of the natural scene, and the soil parameter data of the target area to obtain a vertical water movement model between two adjacent layers of soil. The target neural network can be a one-dimensional convolutional neural network, which is used to represent the relationship between the vertical movement of soil moisture and the soil moisture content and soil parameters of the adjacent layers.

[0066] Step 104: Determine the groundwater recharge in the target area based on the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

[0067] In the embodiment of the present application, the groundwater recharge amount may include the actual scene recharge amount, and may also include at least one of the natural scene recharge amount and the irrigation recharge amount. The actual scene recharge amount is the amount of groundwater recharge in the actual scene. The natural scene recharge amount is the amount of groundwater recharge in the natural scene. The irrigation recharge amount is the amount of groundwater recharge caused by irrigation.

[0068] The terminal determines the actual scenario recharge of the target area based on the soil water balance equation and the vertical movement of soil moisture in the actual scenario. Then, the terminal determines the groundwater recharge of the target area based on the actual scenario recharge.

[0069] In one example, the terminal uses the actual scenario recharge as the groundwater recharge of the target area.

[0070] In another example, the terminal calculates the natural scene recharge of the target area based on the soil water balance equation, natural scene multi-layer soil moisture data, precipitation, surface runoff, and natural scene evapotranspiration data. Then, the terminal uses the actual scene recharge and the natural scene recharge to form the groundwater recharge of the target area.

[0071] In another example, the terminal calculates the natural scene recharge of the target area based on the soil water balance equation, the natural scene multi-layer soil moisture data, precipitation, surface runoff, and natural scene evapotranspiration data. Then, the terminal calculates the irrigation recharge based on the actual scene recharge and the natural scene recharge. Then, the terminal generates the groundwater recharge of the target area including the actual scene recharge and the irrigation recharge.

[0072] In one example, the terminal may use the bottom soil water balance remainder method to calculate the actual scenario recharge and the natural scenario recharge of the target area.

[0073] In the above-mentioned groundwater recharge estimation method, the actual scene multi-layer soil moisture data is determined based on the actual scene evapotranspiration data based on remote sensing observation, the natural scene evapotranspiration data based on the land surface model and the natural scene multi-layer soil moisture data, and the reference crop evapotranspiration data based on meteorological observation, and the actual scene multi-layer soil moisture data is input into the water vertical movement model generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture data and the soil parameter data, so as to obtain the soil moisture vertical movement in the actual scene, and combine the soil water balance equation to determine the groundwater recharge of the target area, considering the influence of irrigation and other environmental factors in the actual scene, conforming to the actual situation, and being able to accurately obtain the groundwater recharge. In addition, this method does not need to drive complex land surface models and groundwater models, does not assume an ideal irrigation scene, can reflect the actual irrigation situation and its impact on groundwater recharge, does not need to be driven by the daily scale data often required by the hydrological model, does not need to obtain the long-term series, daily scale, high spatial resolution (0.1°) remote sensing soil moisture and evapotranspiration products with high difficulty and large uncertainty, and can be used in a wide range. Moreover, this method does not rely on specific empirical parameters and empirical formulas, but obtains the law of vertical water movement by training neural networks to obtain groundwater recharge data with high spatial resolution and long time span. It not only considers the factors of soil moisture content, but also considers the relationship with other environmental factors, such as groundwater level, etc. The relationship between model parameters and specific soil physical parameters is clear, and it can establish universal laws and achieve large-scale law description. In addition, this method is applicable to different climatic conditions (dry and humid areas), different irrigation conditions (sprinkler irrigation, flood irrigation, drip irrigation, etc.), different multiple cropping indexes (single season, double season), and different farmland types (paddy fields, dry land), and can reflect the relationship between irrigation recharge and different irrigation methods and natural conditions. In addition, this method relies less on measured data and has a wide range of applications for calculating irrigation water consumption. It does not require a complex parameter calibration process and is less affected by parameter uncertainty. It can calculate various groundwater recharges in a region separately, reflecting the spatial distribution characteristics of the pixel scale. It can reflect the seasonal distribution characteristics of irrigation water, which is consistent with the irrigation water demand characteristics of crops in each month. It can reflect its relationship with the characteristics of complex aquifers. It can serve regional water resources management and land use management.

[0074] In an exemplary embodiment, Figure 2 As shown, based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, the specific process of determining the actual scene multi-layer soil moisture content data of the target area includes the following steps:

[0075] Step 201, based on the actual scene evapotranspiration data of non-irrigated pixels and the natural scene evapotranspiration data, the actual scene evapotranspiration data is corrected for system errors to obtain corrected actual scene evapotranspiration data.

[0076] In the embodiment of the present application, the terminal calculates the system error of the actual scene evapotranspiration data according to the Kriging interpolation function, the actual scene evapotranspiration data of the non-irrigated pixel and the natural scene evapotranspiration data. Then, the terminal performs system error correction on the actual scene evapotranspiration data according to the system error to obtain the corrected actual scene evapotranspiration data. Among them, the non-irrigated pixel is a pixel that is not irrigated.

[0077] In one embodiment, step 201 can be expressed as:

[0078]

[0079]

[0080] Among them, Krig is the Kriging interpolation function, , are the actual scene evapotranspiration data of non-irrigated pixels and the natural scene evapotranspiration data of non-irrigated pixels, e is the system error obtained by spatial interpolation, To correct the actual scene evapotranspiration data.

[0081] Step 202, based on the corrected actual scene evapotranspiration data, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and reference crop evapotranspiration data, determine the actual scene multi-layer soil moisture content data of the target area.

[0082] In the embodiment of the present application, the terminal establishes a linear relationship between soil moisture content and evapotranspiration ratio at preset time steps, pixel by pixel, and soil layer by soil based on the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data, and the reference crop evapotranspiration data. Then, based on these multiple linear relationships, the terminal corrects the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data, and the reference crop evapotranspiration data to determine the actual scene multi-layer soil moisture content data of the target area.

[0083] In the above-mentioned groundwater recharge estimation method, the actual scene evapotranspiration data is corrected for systematic errors according to the actual scene evapotranspiration data and the natural scene evapotranspiration data of non-irrigated pixels to obtain the corrected actual scene evapotranspiration data; based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, the actual scene multi-layer soil moisture content data of the target area is determined. In this way, the actual scene evapotranspiration data and the natural scene evapotranspiration data are made consistent in non-irrigated pixels as the purpose of correction, the systematic errors of the actual scene evapotranspiration data and the natural scene evapotranspiration data in the non-irrigated area are calculated, the average value of the errors of the two is calculated for each river basin, and the Kriging interpolation method is used to expand it to the entire spatial range, so as to obtain the corrected actual scene evapotranspiration data. Compared with directly using the existing global remote sensing evapotranspiration data set as the actual scene evapotranspiration, the systematic errors caused by using different data sources can be eliminated as much as possible, and the accuracy of groundwater recharge acquisition can be improved.

[0084] In an exemplary embodiment, Figure 3 As shown, based on the corrected actual scene evapotranspiration data, natural scene evapotranspiration data, natural scene multi-layer soil moisture content data and reference crop evapotranspiration data, the specific process of determining the actual scene multi-layer soil moisture content data of the target area includes the following steps:

[0085] Step 301, calculating the natural scene evapotranspiration ratio based on the natural scene evapotranspiration data and the reference crop evapotranspiration data.

[0086] In the embodiment of the present application, the terminal uses the ratio of the natural scene evapotranspiration data to the reference crop evapotranspiration data as the natural scene evapotranspiration ratio, wherein the natural scene evapotranspiration ratio is the evapotranspiration ratio under the natural scene, which is the ratio of the evapotranspiration under the natural scene to the reference crop evapotranspiration.

[0087] In one embodiment, step 301 can be expressed as:

[0088]

[0089] Among them, EF N is the evapotranspiration ratio of natural scene, ET N It is the evapotranspiration data of natural scene, ET ref Reference crop evapotranspiration data.

[0090] Step 302, for each layer of soil, according to the preset linear relationship between the moisture content of the soil layer and the evapotranspiration ratio, the natural scene evapotranspiration ratio and the natural scene multi-layer soil moisture content data corresponding to the layer of soil, the linear fitting parameters corresponding to the layer of soil are fitted.

[0091] In the embodiment of the present application, the soil may include: a top layer of soil, a middle layer of soil, and a bottom layer of soil. The linear relationship between the moisture content of the top layer of soil and the evapotranspiration ratio may be: ; The linear relationship between the middle soil moisture content and evapotranspiration ratio can be: ; The linear relationship between the bottom soil moisture content and evapotranspiration ratio can be: .in, , and The natural scene multi-layer soil moisture data corresponding to the top soil, middle soil and bottom soil, EF N is the evapotranspiration ratio of the natural scene, k1, k2 and k3 are the first linear fitting parameter of the top layer, the first linear fitting parameter of the middle layer and the first linear fitting parameter of the bottom layer, respectively, b1, b2 and b3 are the second linear fitting parameter of the top layer, the second linear fitting parameter of the middle layer and the second linear fitting parameter of the bottom layer, respectively.

[0092] For each layer of soil and each month, the terminal fits the linear fitting parameters corresponding to the layer of soil in that month based on the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the natural scene evapotranspiration ratio of that month, and the natural scene multi-layer soil moisture content data corresponding to the layer of soil in that month.

[0093] In one example, for each layer of soil and each month, the terminal fits the linear fitting parameters corresponding to the layer of soil in each target time period corresponding to the month according to the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the natural scene evapotranspiration ratio in each target time period corresponding to the month, and the natural scene multi-layer soil moisture content data corresponding to the layer of soil in each target time period. Then, the terminal uses the linear fitting parameter with the largest determination coefficient as the linear fitting parameter corresponding to the layer of soil in the month. Among them, each month corresponds to a target time period, and the target time period includes its corresponding month. The duration of the target time period corresponding to each month is the same and can be in months. For example, the target time periods corresponding to March can be January-March, February-April, and March-May, respectively. The determination coefficient is R 2 , is a statistic that measures the goodness of fit of the regression model. In this way, the linear relationship between soil moisture content and evapotranspiration ratio in each layer is established pixel by pixel and month by month, and the linear fitting R 2 By comparing the linear relationships and selecting the most robust linear relationship, the accuracy of linear fitting parameters can be improved, thereby improving the accuracy of groundwater recharge estimation.

[0094] Step 303, calculating the actual scene evapotranspiration ratio based on the corrected actual scene evapotranspiration data and the reference crop evapotranspiration data.

[0095] In the embodiment of the present application, the terminal corrects the ratio of the actual scene evapotranspiration data to the reference crop evapotranspiration data as the actual scene evapotranspiration ratio, wherein the actual scene evapotranspiration ratio is the evapotranspiration ratio in the actual scene, which is the ratio of the evapotranspiration in the actual scene to the reference crop evapotranspiration.

[0096] In one embodiment, step 303 can be expressed as:

[0097]

[0098] Among them, EF A is the evapotranspiration ratio of the actual scenario, To correct the actual scene evapotranspiration data.

[0099] Step 304, for each layer of soil, the actual scene multi-layer soil moisture content data corresponding to the layer of soil is calculated according to the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the actual scene evapotranspiration ratio, the natural scene evapotranspiration ratio, the natural scene multi-layer soil moisture content data corresponding to the layer of soil, and the linear fitting parameters corresponding to the layer of soil.

[0100] In the embodiment of the present application, step 304 can be expressed as:

[0101]

[0102]

[0103]

[0104] in, , and Respectively represent the actual scenario multi-layer soil moisture data corresponding to the top soil layer, middle soil layer and bottom soil layer.

[0105] In the above-mentioned groundwater recharge estimation method, a linear relationship between the soil moisture content in natural scenes and the natural evapotranspiration ratio is established month by month, pixel by pixel, and layer by layer (top layer, middle layer, bottom layer) of soil, and it is applied to the actual evapotranspiration ratio to calculate the soil moisture content in the actual scene. This can accurately obtain the soil moisture content in the actual scene including irrigation, which is in line with the actual situation and can further improve the accuracy of groundwater recharge acquisition.

[0106] In an exemplary embodiment, Figure 4 As shown, the method further comprises the following steps:

[0107] Step 401: construct the water balance residual of the top layer soil and the water balance residual of the middle layer soil according to the soil water balance equation.

[0108] In an embodiment of the present application, the soil water balance equation may include: a soil water balance equation in a natural scene and a soil water balance equation in an actual scene.

[0109] In one embodiment, for the top soil layer of a certain pixel (0-70 mm, indicated by subscript 1), in a natural scene, the soil water balance formula is as follows:

[0110]

[0111] in, is the top soil thickness (mm), is the change in top soil moisture content within a time step ( ), the superscript N refers to the natural scene (the same below), P is the precipitation (mm / month), is the surface runoff (mm / month), is the evapotranspiration under natural scenes (mm / month), is the vertical movement of water between the top and middle layers of soil in natural scenarios (mm / month). All variables describing water movement have downward as the positive direction. The water balance formula for the middle soil (70-280 mm, indicated by subscript 2) and the bottom soil (280-1000 mm, indicated by subscript 3) is as follows:

[0112]

[0113]

[0114] in, is the vertical movement of water between the middle and bottom layers of soil in natural scenarios (mm / month), It is the vertical movement of water between the underlying soil and groundwater in natural scenarios (mm / month). A positive value indicates that water flows from the soil to the groundwater, i.e., the groundwater recharge is dominant; a negative value indicates that water flows from the groundwater to the underlying soil, i.e., the capillary rise is dominant. Part of this item is used to replenish groundwater reserves, and the other part forms underground runoff.

[0115] In actual scenarios, the water input to the top soil includes irrigation water in addition to precipitation. This method does not consider the impact of irrigation on precipitation, that is, it assumes that the precipitation in the natural scene and the actual scene is the same. In addition, this method assumes that irrigation water will maximize the utilization of water resources and will not generate additional surface runoff. Therefore, the soil water balance formulas for the top, middle, and bottom layers in the actual scene are as follows:

[0116]

[0117]

[0118]

[0119] Among them, the superscript A represents the actual scenario (the same below), and the meaning and unit of each variable are the same as above.

[0120] Similar to the usual land surface and groundwater models, lateral soil flow is not considered in the soil water balance formula. S In places where the vertical distribution changes suddenly, the characteristic depth is 700 mm. For the top and middle layers of soil, this assumption basically does not introduce errors, and the impact on the estimation accuracy of irrigation water is negligible. In addition, since long-term series, daily-scale, high-spatial-resolution (0.1°) remote sensing soil moisture and evapotranspiration products are difficult to obtain over a large area or have large uncertainties, this method uses monthly-scale data.

[0121] Step 402: construct a loss function of a target neural network based on the water balance residual of the top layer of soil and the water balance residual of the middle layer of soil.

[0122] In the embodiment of the present application, step 402 can be expressed as:

[0123]

[0124] Among them, L is the loss function of the target neural network, is the water balance residual of the top soil layer, is the water balance residual of the middle soil layer.

[0125] Step 403: Based on the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data, a target neural network is trained to obtain a vertical water movement model between two adjacent soil layers.

[0126] In the embodiment of the present application, the terminal forms a training data set with the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data. Then, the terminal trains the target neural network based on the training data set to obtain a vertical water movement model between two adjacent layers of soil. Among them, the soil parameter data may include saturated hydraulic conductivity and saturated water content.

[0127] In one embodiment, the terminal uses the Pytorch package of Python 3.10 to train the target neural network.

[0128] In one embodiment, according to the van Genuchten water characteristic curve, the soil water potential (kPa) and effective saturation Satisfies the following relationship:

[0129]

[0130] Among them, α(kPa -1 ) and m are soil parameters, and S e From soil moisture content θ, saturated moisture content θ S , residual water contentθ r The calculation formula is as follows:

[0131]

[0132] According to the laws of physics, the vertical movement of water is determined by the soil water potential. Determine, assuming the vertical movement of water between two adjacent soil layers in a natural scenario , Still determined by the effective saturation S e , soil parameter φ, but its law can be expressed as:

[0133]

[0134]

[0135] Among them, f is the law of soil water movement simulated by using convolutional neural network. Convolutional neural network can effectively capture the intrinsic coupling between the time series of soil moisture content and water movement and improve the prediction ability of the model. is the effective saturation of each layer of soil in the natural scene, is a set of soil parameters for each layer, including soil saturated hydraulic conductivity ,thickness and moisture characteristic curve parameters and :

[0136]

[0137] This method assumes that the law of vertical movement of soil moisture in actual scenarios is similar to that in natural scenarios, that is, the vertical movement of moisture between two adjacent layers of soil is still described by f:

[0138]

[0139]

[0140] in, is the effective saturation of each layer of soil in the actual scenario.

[0141] In the above-mentioned groundwater recharge estimation method, based on multi-source image data, a one-dimensional convolutional neural network is used to establish the relationship between the vertical movement of water between two soil layers and the soil moisture content and soil parameters of the adjacent layers to describe the law of vertical movement of soil water. The loss function is constructed through the water balance of the top and middle layers of soil in natural scenes, and the neural network is trained. The obtained vertical water movement model can be applied to actual scenes and accurately predict the vertical water movement in actual scenes, which is in line with the actual situation and can further improve the accuracy of groundwater recharge acquisition.

[0142] In an exemplary embodiment, Figure 5 As shown in Figure 1, based on the soil water balance equation and the vertical movement of soil moisture in actual scenarios, the specific process of determining the groundwater recharge in the target area includes the following steps:

[0143] Step 501, calculating the actual scene soil moisture content change of the bottom soil according to the actual scene multi-layer soil moisture content data of the bottom soil and a preset time step.

[0144] In the embodiment of the present application, the time step may be 1 month.

[0145] Step 502, calculate the actual scenario recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the actual scenario, the actual scenario soil moisture content change of the underlying soil and the soil thickness of the underlying soil.

[0146] In the embodiment of the present application, the terminal calculates the product of the actual scene soil moisture content change of the bottom soil and the soil thickness of the bottom soil. Then, the terminal uses the difference between the vertical movement of water between the middle and bottom soils in the actual scene and the product as the actual scene replenishment of the target area.

[0147] In one embodiment, step 502 may be expressed as:

[0148]

[0149] in, is the actual scene supply amount in the target area, is the vertical movement of water between the middle and bottom layers of soil in actual scenarios, is the soil thickness of the underlying soil, is the actual scenario soil moisture change of the underlying soil.

[0150] Step 503, determining the groundwater recharge amount in the target area according to the actual scenario recharge amount.

[0151] In an embodiment of the present application, the terminal determines the groundwater recharge amount in the target area based on the actual scenario recharge amount.

[0152] In one example, the terminal generates the groundwater recharge amount of the target area including the actual scene recharge amount. For example, the terminal uses the actual scene recharge amount as the groundwater recharge amount of the target area.

[0153] In another example, the terminal determines the irrigation recharge amount of the target area according to the actual scenario recharge amount. Then, the terminal generates the groundwater recharge amount of the target area including the irrigation recharge amount.

[0154] In the above-mentioned groundwater recharge estimation method, the bottom soil water balance residual method is used in actual scenarios to calculate the actual scenario recharge, which is in line with the actual situation and can further improve the accuracy of groundwater recharge acquisition.

[0155] In an exemplary embodiment, Figure 6 As shown in the figure, according to the actual scenario recharge, the specific process of determining the groundwater recharge in the target area includes the following steps:

[0156] Step 601, calculate the vertical movement of soil moisture in a natural scene based on the soil water balance equation, multi-layer soil moisture data of a natural scene, precipitation, surface runoff, and evapotranspiration data of a natural scene.

[0157] In the embodiment of the present application, the vertical movement of soil moisture in the natural scene includes: the vertical movement of moisture between the top and middle layers of soil in the natural scene and the vertical movement of moisture between the middle and bottom layers of soil in the natural scene. The terminal calculates the vertical movement of moisture between the middle and bottom layers of soil in the natural scene based on the soil water balance equation, multi-layer soil moisture data of the natural scene, precipitation, surface runoff, and evapotranspiration data of the natural scene.

[0158] Step 602, calculating the change in the natural scene soil moisture content of the bottom soil according to the natural scene multi-layer soil moisture content data of the bottom soil and a preset time step.

[0159] Step 603, calculate the natural scene recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the natural scene, the change in the natural scene soil moisture content of the underlying soil and the soil thickness of the underlying soil.

[0160] In the embodiment of the present application, the terminal calculates the product of the change in soil moisture content of the natural scene of the bottom soil and the soil thickness of the bottom soil. Then, the terminal uses the difference between the vertical movement of water between the middle and bottom soils in the natural scene and the product as the natural scene replenishment of the target area.

[0161] In one embodiment, step 603 may be expressed as:

[0162]

[0163] in, is the natural scene supply of the target area, is the vertical movement of water between the middle and bottom layers of soil in natural scenes, is the change in soil moisture content of the underlying soil in natural scenarios.

[0164] Step 604: The difference between the actual scene supply amount and the natural scene supply amount is used as the irrigation supply amount of the target area.

[0165] In the embodiment of the present application, step 604 can be expressed as:

[0166]

[0167] in, is the irrigation recharge for the target area.

[0168] Step 605, determining the groundwater recharge amount in the target area according to the irrigation recharge amount.

[0169] In an embodiment of the present application, the terminal determines the groundwater recharge amount in the target area based on the irrigation recharge amount.

[0170] In one example, the terminal uses irrigation recharge as groundwater recharge for the target area.

[0171] In another example, the terminal generates the groundwater recharge of the target area including the actual scene recharge and the irrigation recharge. For example, the terminal uses the actual scene recharge, the natural scene recharge and the irrigation recharge to form the groundwater recharge of the target area.

[0172] In the above-mentioned groundwater recharge estimation method, the residual method of the bottom soil water balance is also used in the natural scene to calculate the recharge of the natural scene, and the difference between the actual scene recharge and the natural scene recharge is used as the irrigation recharge, which can accurately obtain a variety of groundwater recharge. In addition, this method provides a monthly groundwater recharge estimation method based on multi-source data, convolutional neural network and soil water balance, including groundwater recharge in natural scenes (excluding irrigation), groundwater recharge in actual scenes (including irrigation), and groundwater recharge caused by irrigation, which can serve groundwater management, groundwater recharge calculation, irrigation water consumption accounting, etc.

[0173] In one embodiment, the method further comprises the following steps: calculating the change in soil moisture content in the natural scene of the top soil according to the multi-layer soil moisture content data in the natural scene of the top soil and the preset time step; calculating the irrigation intensity of each month in the target area according to the change in soil moisture content in the natural scene of the top soil, the soil thickness of the top soil, precipitation, corrected actual scene evapotranspiration data and the vertical movement of water between the top and middle soil layers in the actual scene. The irrigation intensity is the unit irrigation water consumption.

[0174] In one embodiment, the terminal calculates the irrigation intensity of the target area in each month, which can be expressed as:

[0175]

[0176] Among them, I a is the irrigation intensity, z1 is the soil thickness of the top soil, is the change in soil moisture content in the natural scenario of the top soil, It is the vertical movement of water between the top and middle layers of soil in actual scenarios.

[0177] In one embodiment, the method further comprises the following steps: calculating the irrigation water consumption of the target area according to the irrigation intensity of each month of the target area and the area of ​​the irrigation pixel. For example, the terminal calculates the irrigation water consumption of the target area for one year, which can be expressed as:

[0178]

[0179] in, is the annual irrigation water consumption of the target area ( ), is the area of ​​the irrigated pixel. In this way, this method can simultaneously quantify the amount of irrigation water and the impact of irrigation on groundwater, that is, the irrigation recharge.

[0180] In one embodiment, the method further comprises the following steps: calculating the ratio of groundwater recharge to inflow in the target area according to the groundwater recharge and inflow in the target area.

[0181] In an embodiment of the present application, the inflow water volume includes: the natural scene inflow water volume, the actual scene inflow water volume and the irrigation water volume. The terminal uses the ratio of the natural scene supply volume to the precipitation to calculate the proportion of the natural scene supply volume in the target area to the natural scene inflow water volume. And / or, the terminal uses the sum of precipitation and irrigation water volume as the actual scene inflow water volume, and uses the ratio of the actual scene supply volume to the actual scene inflow water volume as the proportion of the actual scene supply volume in the target area to the actual scene inflow water volume. And / or, the terminal uses the ratio of the irrigation supply volume to the irrigation water volume as the proportion of the irrigation supply volume in the target area to the irrigation water volume. This can be used to analyze the nature of groundwater recharge.

[0182] In one embodiment, the terminal calculates the ratio of groundwater recharge to inflow in the target area, which can be expressed as:

[0183]

[0184]

[0185]

[0186] Among them, r N 、r A and r I They are the ratio of natural scenario recharge to natural scenario inflow, the ratio of actual scenario recharge to actual scenario inflow, and the ratio of irrigation recharge to irrigation water consumption, respectively. I is the irrigation water consumption.

[0187] In one embodiment, the target area is A, where available fresh water resources are scarce, agricultural water consumption is high, and the effective utilization coefficient of irrigation water needs to be further improved. Many areas of A are highly dependent on groundwater irrigation, resulting in over-exploitation of groundwater. Therefore, timely and accurate acquisition of groundwater recharge and evaluation of the impact of irrigation on groundwater recharge are crucial for the coordinated management of surface water and groundwater and guiding the sustainable development of agriculture. Using SSEBop remote sensing evapotranspiration products, ERA5Land model evapotranspiration data, ERA5Land model soil moisture data, and ICC irrigation area data, the model is trained and the natural scenario recharge, actual scenario recharge, and irrigation recharge of the target area A from 2003 to 2023 are estimated. The groundwater recharge calculated by this method can be further used to calculate the irrigation water consumption. The linear fitting relationship between the irrigation water consumption calculated by the model for the target area A and the five sub-areas bf contained in A and the irrigation water withdrawal / water consumption in the water resources bulletin is shown as follows: Figure 7 The trend comparison of irrigation water withdrawal from statistical bulletins and irrigation water withdrawal calculated by the model in 2003-2022 for multiple sub-regions 01-16 included in target region A is shown in Figure 2. Fig. 8AAs shown in the figure, the trend comparison of irrigation water withdrawal in the statistical bulletin and irrigation water withdrawal calculated by the model in 2003-2022 for multiple sub-areas 17-31 included in the target area A is shown in the figure. Figure 8B shown.

[0188] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0189] Based on the same inventive concept, the embodiment of the present application also provides a groundwater recharge estimation device for implementing the groundwater recharge estimation method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more groundwater recharge estimation device embodiments provided below can refer to the limitations of the groundwater recharge estimation method above, and will not be repeated here.

[0190] In an exemplary embodiment, Fig. 9 As shown, a groundwater recharge estimation device 900 is provided, comprising: an acquisition module 910, a first determination module 920, a second determination module 930 and a third determination module 940, wherein:

[0191] An acquisition module 910 is used to acquire multi-source data of a target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observations, natural scene evapotranspiration data based on land surface models, multi-layer soil moisture data of natural scenes based on land surface models, and reference crop evapotranspiration data based on meteorological observations;

[0192] A first determination module 920 is used to determine the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data;

[0193] The second determination module 930 is used to input the actual scene multi-layer soil moisture content data into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data of the target area;

[0194] The third determination module 940 is used to determine the groundwater recharge in the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

[0195] Optionally, the first determining module 920 is specifically configured to:

[0196] According to the actual scene evapotranspiration data of the non-irrigated pixel and the natural scene evapotranspiration data, performing system error correction on the actual scene evapotranspiration data to obtain corrected actual scene evapotranspiration data;

[0197] Based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, the actual scene multi-layer soil moisture content data of the target area is determined.

[0198] Optionally, the first determining module 920 is specifically configured to:

[0199] Calculating the natural scene evapotranspiration ratio based on the natural scene evapotranspiration data and the reference crop evapotranspiration data;

[0200] For each layer of soil, a linear fitting parameter corresponding to the layer of soil is obtained by fitting according to a preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the natural scene evapotranspiration ratio and the moisture content data of multiple layers of soil in the natural scene corresponding to the layer of soil;

[0201] Calculating the actual scene evapotranspiration ratio based on the corrected actual scene evapotranspiration data and the reference crop evapotranspiration data;

[0202] For each layer of soil, the actual scene multi-layer soil moisture content data corresponding to the layer of soil is calculated based on the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the actual scene evapotranspiration ratio, the natural scene evapotranspiration ratio, the natural scene multi-layer soil moisture content data corresponding to the layer of soil and the linear fitting parameters corresponding to the layer of soil.

[0203] Optionally, the device 900 further includes:

[0204] A first construction module is used to construct a water balance residual of the top layer soil and a water balance residual of the middle layer soil according to the soil water balance equation;

[0205] A second construction module is used to construct a loss function of a target neural network according to the water balance residual of the top layer of soil and the water balance residual of the middle layer of soil;

[0206] A training module is used to train the target neural network based on the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data to obtain a vertical water movement model between two adjacent soil layers.

[0207] Optionally, the third determining module 940 is specifically configured to:

[0208] Calculating the actual scene soil moisture content change of the bottom soil according to the actual scene multi-layer soil moisture content data of the bottom soil and a preset time step;

[0209] Calculate the actual scenario recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the actual scenario, the actual scenario soil moisture content change of the bottom soil and the soil thickness of the bottom soil;

[0210] The groundwater recharge amount of the target area is determined according to the actual scenario recharge amount.

[0211] The third determination module 940 is specifically used to:

[0212] Calculate the vertical movement of soil moisture in the natural scene based on the soil water balance equation, the multi-layer soil moisture content data of the natural scene, precipitation, surface runoff, and the evapotranspiration data of the natural scene;

[0213] Calculating the change in soil moisture content in the natural scene of the bottom soil according to the natural scene multi-layer soil moisture content data of the bottom soil and a preset time step;

[0214] Calculate the natural scene recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the natural scene, the change in soil moisture content in the natural scene of the bottom soil, and the soil thickness of the bottom soil;

[0215] The difference between the actual scene supply amount and the natural scene supply amount is used as the irrigation supply amount of the target area;

[0216] The groundwater recharge amount of the target area is determined based on the irrigation recharge amount.

[0217] Each module in the above-mentioned groundwater recharge estimation device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0218] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Fig.10 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer 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 input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for estimating groundwater recharge is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0219] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0220] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0221] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0222] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0223] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0224] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method 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 the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0225] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0226] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for estimating groundwater recharge, characterized in that: The method comprises: Acquire multi-source data of the target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observation, natural scene evapotranspiration data based on land surface model, natural scene multi-layer soil moisture data based on land surface model and reference crop evapotranspiration data based on meteorological observation; Determining the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data; Inputting the actual scene multi-layer soil moisture content data into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data of the target area; The groundwater recharge in the target area is determined based on the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

2. The method according to claim 1, characterized in that The determining the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data includes: According to the actual scene evapotranspiration data of the non-irrigated pixel and the natural scene evapotranspiration data, performing system error correction on the actual scene evapotranspiration data to obtain corrected actual scene evapotranspiration data; Based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data, the actual scene multi-layer soil moisture content data of the target area is determined.

3. The method according to claim 2, characterized in that The determining the actual scene multi-layer soil moisture content data of the target area based on the corrected actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data comprises: Calculating the natural scene evapotranspiration ratio based on the natural scene evapotranspiration data and the reference crop evapotranspiration data; For each layer of soil, a linear fitting parameter corresponding to the layer of soil is obtained by fitting according to a preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the natural scene evapotranspiration ratio and the moisture content data of multiple layers of soil in the natural scene corresponding to the layer of soil; Calculating the actual scene evapotranspiration ratio based on the corrected actual scene evapotranspiration data and the reference crop evapotranspiration data; For each layer of soil, the actual scene multi-layer soil moisture content data corresponding to the layer of soil is calculated based on the preset linear relationship between the moisture content of the layer of soil and the evapotranspiration ratio, the actual scene evapotranspiration ratio, the natural scene evapotranspiration ratio, the natural scene multi-layer soil moisture content data corresponding to the layer of soil and the linear fitting parameters corresponding to the layer of soil.

4. The method according to claim 1, characterized in that The method further comprises: According to the soil water balance equation, constructing the water balance residual of the top layer soil and the water balance residual of the middle layer soil; Constructing a loss function of a target neural network according to the water balance residual of the top layer of soil and the water balance residual of the middle layer of soil; Based on the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data, the target neural network is trained to obtain a vertical water movement model between two adjacent soil layers.

5. The method according to claim 1, characterized in that Determining the groundwater recharge in the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scenario includes: Calculating the actual scene soil moisture content change of the bottom soil according to the actual scene multi-layer soil moisture content data of the bottom soil and a preset time step; Calculate the actual scenario recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the actual scenario, the actual scenario soil moisture content change of the bottom soil and the soil thickness of the bottom soil; The groundwater recharge amount of the target area is determined according to the actual scenario recharge amount.

6. The method according to claim 5, characterized in that Determining the groundwater recharge amount in the target area according to the actual scenario recharge amount includes: Calculate the vertical movement of soil moisture in the natural scene based on the soil water balance equation, the multi-layer soil moisture content data of the natural scene, precipitation, surface runoff, and the evapotranspiration data of the natural scene; Calculating the change in soil moisture content in the natural scene of the bottom soil according to the natural scene multi-layer soil moisture content data of the bottom soil and a preset time step; Calculate the natural scene recharge of the target area according to the soil water balance equation, the vertical movement of soil moisture in the natural scene, the change in soil moisture content in the natural scene of the bottom soil, and the soil thickness of the bottom soil; The difference between the actual scene supply amount and the natural scene supply amount is used as the irrigation supply amount of the target area; The groundwater recharge amount of the target area is determined based on the irrigation recharge amount.

7. A groundwater recharge estimation device, characterized in that: The device comprises: An acquisition module is used to acquire multi-source data of a target area; the multi-source data includes actual scene evapotranspiration data based on remote sensing observations, natural scene evapotranspiration data based on land surface models, multi-layer soil moisture data of natural scenes based on land surface models, and reference crop evapotranspiration data based on meteorological observations; A first determination module is used to determine the actual scene multi-layer soil moisture content data of the target area based on the actual scene evapotranspiration data, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the reference crop evapotranspiration data; The second determination module is used to input the actual scene multi-layer soil moisture content data into the water vertical movement model between two adjacent soil layers to obtain the soil moisture vertical movement in the actual scene of the target area; the water vertical movement model is generated according to the soil water balance equation, the natural scene evapotranspiration data, the natural scene multi-layer soil moisture content data and the soil parameter data of the target area; The third determination module is used to determine the groundwater recharge in the target area according to the soil water balance equation and the vertical movement of soil moisture in the actual scenario.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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