Pollution analysis method and device based on farmland pollution load simulation data

Abstract

The invention relates to the field of data analysis, in particular to a pollution analysis method and device based on farmland pollution load simulation data, computer equipment and a storage medium, and realizes comprehensive and accurate simulation of pollution load in a farmland growth cycle by utilizing a farmland pollution load simulation model and a hydrological model. Pollution analysis is carried out based on the obtained farmland growth cycle pollution load simulation data, and scientific decision support is provided for effective protection of water resources and agricultural sustainable development.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and particularly to a pollution analysis method, device, computer device and storage medium based on farmland pollution load simulation data. Background Art

[0002] There are still deficiencies in the prior art. Summary of the Invention

[0003] Based on this, the object of the present invention is to provide a pollution analysis method, device, computer device and storage medium based on farmland pollution load simulation data. By using the farmland pollution load simulation model and the hydrological model, it realizes a comprehensive and accurate simulation of the pollution load during the farmland growth cycle, and conducts pollution analysis based on the obtained farmland growth cycle pollution load simulation data, providing scientific decision-making support for the effective protection of water resources and the sustainable development of agriculture.

[0004] In the first aspect, an embodiment of the present application provides a pollution analysis method based on farmland pollution load simulation data, including the following steps:

[0005] Obtain the pollution impact factor data and farmland area data of several grid units in a target basin at several unit times within a preset time period;

[0006] Simulate the non-point source pollution load data according to the impact factor data of several unit times of several grid units to obtain the non-point source pollution load simulation data of several unit times of several grid units;

[0007] Input the impact factor data, farmland area data and non-point source pollution load simulation data of several unit times of several grid units into a preset farmland pollution load simulation model to simulate the seeding period data, and obtain the farmland seeding period pollution load simulation data of several unit times of several grid units;

[0008] Input the farmland seeding period pollution load simulation data and pollution impact factor data of several unit times of several grid units into a preset hydrological model to simulate the growth cycle data, and obtain the farmland growth cycle pollution load simulation data of several unit times of several grid units;

[0009] Conduct pollution analysis according to the farmland growth cycle pollution load simulation data of several unit times of several grid units to obtain the farmland pollution analysis result of the target basin.

[0010] In the second aspect, an embodiment of the present application provides a pollution analysis device based on farmland pollution load simulation data, including:

[0011] A data acquisition module, configured to obtain pollution impact factor data and farmland area data of a plurality of grid cells in a target basin at a plurality of unit times within a preset time period;

[0012] A non-point source pollution load simulation module, configured to simulate non-point source pollution load data based on the impact factor data of a plurality of unit times of a plurality of the grid cells, so as to obtain non-point source pollution load simulation data of a plurality of unit times of a plurality of the grid cells;

[0013] A farmland sowing period pollution load simulation module, configured to input the impact factor data, farmland area data, and non-point source pollution load simulation data of a plurality of unit times of a plurality of the grid cells into a preset farmland pollution load simulation model for sowing period data simulation, so as to obtain farmland sowing period pollution load simulation data of a plurality of unit times of a plurality of the grid cells;

[0014] A farmland growth period pollution load simulation module, configured to input the farmland sowing period pollution load simulation data and pollution impact factor data of a plurality of unit times of a plurality of the grid cells into a preset hydrological model for growth period data simulation, so as to obtain farmland growth period pollution load simulation data of a plurality of unit times of a plurality of the grid cells;

[0015] A farmland pollution analysis module, configured to perform pollution analysis based on the farmland growth period pollution load simulation data of a plurality of unit times of a plurality of the grid cells, so as to obtain a farmland pollution analysis result of the target basin.

[0016] In a third aspect, an embodiment of the present application provides a computer device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor; when the computer program is executed by the processor, the steps of the pollution analysis method based on farmland pollution load simulation data as described in the first aspect are implemented.

[0017] In a fourth aspect, an embodiment of the present application provides a storage medium, where the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the pollution analysis method based on farmland pollution load simulation data as described in the first aspect are implemented.

[0018] In the embodiment of the present application, by using a farmland pollution load simulation model and a hydrological model, a comprehensive and accurate simulation of the pollution load during the farmland growth period is realized, and pollution analysis is performed based on the obtained farmland growth period pollution load simulation data, providing scientific decision-making support for the effective protection of water resources and the sustainable development of agriculture.

[0019] For better understanding and implementation, the present invention will be described in detail below with reference to the accompanying drawings. Description of the Drawings

[0020] Figure 1 Schematic flow chart of a pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0021] Figure 2 Schematic flow chart of S2 in the pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0022] Figure 3 Schematic flow chart of S3 in the pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0023] Figure 4 Schematic flow chart of S31 in the pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0024] Figure 5 Schematic flow chart of S4 in the pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0025] Figure 6 Schematic flow chart of S5 in the pollution analysis method based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0026] Figure 7 Schematic structural diagram of a pollution analysis device based on simulated data of farmland pollution load provided by an embodiment of the present application;

[0027] Figure 8 Schematic structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0028] Here, exemplary embodiments will be described in detail, and examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0029] The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. The singular forms "a", "the", and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0030] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" / "when" as used herein may be interpreted as "when...", "while...", or "in response to determining".

[0031] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a pollution analysis method based on farmland pollution load simulation data provided for an embodiment of this application. The method includes the following steps:

[0032] S1: Obtain pollution influencing factor data and farmland area data of several grid cells in a target basin for several unit times within a preset time period.

[0033] The execution subject of the pollution analysis method based on farmland pollution load simulation data is an analysis device for the pollution analysis method based on farmland pollution load simulation data (hereinafter referred to as the analysis device). In an optional embodiment, the analysis device may be a computer device, which may be a server, or a server cluster formed by combining multiple computer devices.

[0034] The time period may be set to 10 years, and the unit time may be set to 1 year.

[0035] In this embodiment, the analysis device may obtain pollution influencing factor data and farmland area data of several grid cells in a target basin for several unit times within a preset time period through a database. Among them, the pollution influencing factor data includes rainfall data and slope data; the slope data is obtained by performing slope analysis on the obtained digital elevation model (DEM) data using the slope analysis function in ArcGis software. The farmland area data is obtained using satellite remote sensing data. Specifically, the grid cell is an administrative unit, and the administrative unit may be a province, a county, or a township, so as to obtain more accurate farmland pollution load simulation data of the basin.

[0036] S2: Simulate non-point source pollution load data based on the influencing factor data of several unit times of several of the grid cells to obtain non-point source pollution load simulation data of several unit times of several of the grid cells.

[0037] In this embodiment, the analysis device simulates non-point source pollution load data based on the influencing factor data of several grid units for several unit times, and obtains non-point source pollution load simulation data of several grid units for several unit times.

[0038] Please refer to Figure 2 , Figure 2 , which is a schematic flowchart of S2 in the pollution analysis method based on farmland pollution load simulation data provided by an embodiment of the present application, including step S21, specifically as follows:

[0039] S21: Obtain non-point source pollution load data of several grid units for several unit times according to the rainfall data of several grid units for several unit times and the corresponding relationship between the loads of several preset pollutants and rainfall.

[0040] In this embodiment, the analysis device obtains non-point source pollution load data of several grid units for several unit times according to the rainfall data of several grid units for several unit times and the corresponding relationship between the loads of several preset pollutants and rainfall. Among them, the non-point source pollution load data includes load data of several pollutants.

[0041] Specifically, the non-point source pollution load data includes load data of total nitrogen pollutants and load data of total phosphorus pollutants. The corresponding relationship between the load data of total nitrogen pollutants and rainfall is:

[0042]

[0043] In the formula, L TN is the load data of total nitrogen pollutants, and r xy is the rainfall data of the y-th unit time of the x-th grid unit.

[0044] The corresponding relationship between the load data of total phosphorus pollutants and rainfall is:

[0045]

[0046] In the formula, L TP is the load data of total phosphorus pollutants.

[0047] S3: Input the influencing factor data, farmland area data, and non-point source pollution load simulation data of several grid units for several unit times into a preset farmland pollution load simulation model for sowing period data simulation, and obtain farmland sowing period pollution load simulation data of several grid units for several unit times.

[0048] The farmland pollution load simulation model adopts the export coefficient model (ECM). The ECM model is a commonly used method for simulating the export of non-point source pollution in a basin. Its basic principle is to calculate based on the source strength coefficients of different pollution sources, combined with factors such as land use area and the number of pollution source units.

[0049] In this embodiment, the analysis device inputs the influence factor data, farmland area data, and non-point source pollution load simulation data of several grid units for several unit times into a preset farmland pollution load simulation model to simulate the sowing period data, and obtains the farmland sowing period pollution load simulation data of several grid units for several unit times.

[0050] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of S3 in the pollution analysis method based on farmland pollution load simulation data provided by an embodiment of the present application, including steps S31 to S32, specifically as follows:

[0051] S31: Calculate the influence factor coefficients respectively according to the rainfall data and slope data in the pollution influence factor data of several grid units for several unit times, and obtain the influence factor coefficients of several grid units for several unit times.

[0052] In this embodiment, the analysis device calculates the influence factor coefficients respectively according to the rainfall data and slope data in the pollution influence factor data of several grid units for several unit times, and obtains the influence factor coefficients of several grid units for several unit times, where the influence factor coefficients include rainfall influence coefficient and terrain influence coefficient; the rainfall influence coefficient is used to represent the influence of the interannual difference in rainfall on the export of non-point source pollution in the basin, and the rainfall influence coefficient is mainly determined by the combined effect of the interannual distribution difference and spatial distribution difference of precipitation; the terrain influence coefficient represents the standard of terrain on pollutant emissions through the influence of the spatial difference of different slopes in the basin on the export of non-point source pollution in the basin.

[0053] Please refer to Figure 4 , Figure 4 which is a schematic flowchart of S31 in the pollution analysis method based on farmland pollution load simulation data provided by an embodiment of the present application, including steps S311 to S312, specifically as follows:

[0054] S311: Obtain the rainfall influence coefficients of several grid units for several unit times according to the non-point source pollution load data, rainfall data of several grid units for several unit times, and a preset rainfall influence coefficient calculation algorithm.

[0055] The rainfall influence coefficient calculation algorithm is:

[0056]

[0057] Wherein, L xyi is the load data of the i-th pollutant at the y-th unit time of the x-th grid cell, is the average load data of the i-th pollutant of the x-th grid cell, r xy is the rainfall data at the y-th unit time of the x-th grid cell, is the average rainfall data of the x-th grid cell.

[0058] In this embodiment, the analysis device calculates the rainfall influence coefficients of several unit times of several grid cells according to the non-point source pollution load data, rainfall data of several unit times of several grid cells, and a preset rainfall influence coefficient calculation algorithm.

[0059] S312: Obtain the terrain influence coefficients of several unit times of several grid cells according to the slope data of several unit times of several grid cells and a preset terrain influence coefficient calculation algorithm.

[0060] The terrain influence coefficient calculation algorithm is as follows:

[0061]

[0062] Wherein, a is a preset first constant, d is a preset second constant, θ xy is the slope data at the y-th unit time of the x-th grid cell, is the average slope data of the x-th grid cell.

[0063] In this embodiment, the analysis device obtains the terrain influence coefficients of several unit times of several grid cells according to the slope data of several unit times of several grid cells and a preset terrain influence coefficient calculation algorithm.

[0064] S32: Obtain the seeding period output coefficients of several pollutants, and obtain the farmland seeding period pollution load simulation data of several unit times of several grid cells according to the farmland area data of several unit times of several grid cells, the rainfall influence coefficients, terrain influence coefficients, seeding period output coefficients of several pollutants, and a preset first pollution load simulation algorithm.

[0065] The first pollution load simulation algorithm is as follows:

[0066] T xyi = a xyi β xyi E i A xy

[0067] In the formula, T xyi is the load data of the i-th pollutant in the simulated data of the farmland sowing period pollution load at the y-th unit time of the x-th grid cell, a xyi is the rainfall influence coefficient of the i-th pollutant at the y-th unit time of the x-th grid cell, β xyi is the terrain influence coefficient of the i-th pollutant at the y-th unit time of the x-th grid cell, E i is the sowing period output coefficient of the i-th pollutant, A xy is the farmland area data at the y-th unit time of the x-th grid cell.

[0068] In this embodiment, the analysis device obtains the sowing period output coefficients of several pollutants, and obtains the simulated data of the farmland sowing period pollution load of several grid cells at several unit times according to the farmland area data, the rainfall influence coefficients, the terrain influence coefficients, the sowing period output coefficients of several pollutants, and a preset first pollution load simulation algorithm of several grid cells at several unit times. Considering the influence of rainfall and terrain on the output of non-point source pollution in the basin, and combining the sowing period output coefficients of pollutants and the farmland area data, the pollution load during the farmland sowing period is simulated to obtain more accurate and comprehensive simulated data of the farmland sowing period pollution load.

[0069] S4: Input the simulated data of the farmland sowing period pollution load of several grid cells at several unit times and the pollution influence factor data into a preset hydrological model to simulate the growth cycle data, and obtain the simulated data of the farmland growth cycle pollution load of several grid cells at several unit times.

[0070] The hydrological model is a kind of SWAT (Soil and Water Assessment Tool) model, which is used to simulate the spatio-temporal distribution of pollution in the target basin. The hydrological model includes several hydrological response units; corresponding methods for obtaining simulated pollution load data are set in the hydrological response units.

[0071] In this embodiment, the analysis device inputs the simulated data of the farmland sowing period pollution load of several grid cells at several unit times and the pollution influence factor data into a preset hydrological model to simulate the growth cycle data, and obtains the simulated data of the farmland growth cycle pollution load of several grid cells at several unit times.

[0072] Please refer to Figure 5 , Figure 5 which is a schematic flowchart of S4 in the pollution analysis method based on farmland pollution load simulation data provided by an embodiment of the present application, including step S41, as follows:

[0073] S41: Input the simulated data of the pollution load during the farmland sowing period for several unit times of several of the grid cells, as well as the rainfall data, slope data, and soil property data among the pollution influencing factor data, into several of the hydrological response units in the form of point sources respectively. According to the preset fertilization amount strategy, simulate the pollutant emissions of the crops in the farmland of several of the grid cells during the growth cycle for several unit times, and obtain the simulated data of the pollution load during the growth cycle of the farmland of several of the grid cells for several unit times.

[0074] In this embodiment, the analysis device inputs the simulated data of the pollution load during the farmland sowing period for several unit times of several of the grid cells, as well as the rainfall data, slope data, and soil property data among the pollution influencing factor data, into several of the hydrological response units in the form of point sources respectively. According to the preset fertilization amount strategy, simulate the pollutant emissions of the crops in the farmland of several of the grid cells during the growth cycle for several unit times, and obtain the simulated data of the pollution load during the growth cycle of the farmland of several of the grid cells for several unit times.

[0075] Use the hydrological model to simulate the growth process of the crops in the farmland under the fertilization strategy, the change in the absorption amount of nitrogen and phosphorus by the crops during the entire growth cycle, and then simulate the pollutant emissions of the crops during the growth cycle, obtain the simulated data of the pollution load during the growth cycle of the farmland of several of the grid cells for several unit times, realize the comprehensive consideration of farmland pollution in the watershed ecosystem, and can more accurately simulate the migration and transformation process of farmland nitrogen and phosphorus in the watershed.

[0076] S5: Conduct pollution analysis based on the simulated data of the pollution load during the growth cycle of the farmland of several of the grid cells for several unit times, and obtain the farmland pollution analysis result of the target watershed.

[0077] In this embodiment, the analysis device conducts pollution analysis based on the simulated data of the pollution load during the growth cycle of the farmland of several of the grid cells for several unit times, and obtains the farmland pollution analysis result of the target watershed. By using the farmland pollution load simulation model and the hydrological model, it realizes the comprehensive and accurate simulation of the pollution load during the growth cycle of the farmland. Based on the obtained simulated data of the pollution load during the growth cycle of the farmland, it conducts pollution analysis, providing scientific decision-making support for the effective protection of water resources and the sustainable development of agriculture. Among them, the farmland pollution analysis result includes the pollutant load level results of several of the grid cells for several unit times and the pollutant trend results of the target watershed for several unit times.

[0078] Please refer to Figure 6 , Figure 6Schematic diagram of the process of S5 in the pollution analysis method based on the simulated data of farmland pollution load provided by an embodiment of the present application, including step S51, which is specifically as follows:

[0079] S51: Using the clustering analysis method, cluster and divide the simulated data of the farmland growth cycle pollution load of several grid cells in several unit times to obtain the simulated data sets of the pollution loads of several grid cells corresponding to several clusters; according to the simulated data sets of the pollution loads of the grid cells corresponding to several clusters and the preset pollutant load threshold, obtain the pollutant load level results of several grid cells corresponding to several clusters.

[0080] In this embodiment, the analysis device uses the K-means clustering analysis method to cluster and divide the simulated data of the farmland growth cycle pollution load of several grid cells in several unit times to obtain the simulated data sets of the pollution loads of several grid cells corresponding to several clusters; according to the simulated data sets of the pollution loads of the grid cells corresponding to several clusters and the preset pollutant load threshold, obtain the pollutant load level results of several grid cells corresponding to several clusters. Among them, the pollutant load level results reflect the pollution intensity and can effectively determine the severely polluted areas. For example, through clustering analysis, it is found that the pollutant load levels of several grid cells are at the highest level, and these grid cells can be used as key treatment objects, and strengthening pollution prevention and control measures such as adjusting the planting structure and optimizing the fertilization plan can be taken preferentially, so as to achieve precise pollution control and improve the treatment efficiency.

[0081] S52: Using the standard deviation ellipse analysis method, according to the simulated data of the farmland growth cycle pollution load of several grid cells in the same unit time, calculate the elliptical center position, distribution range and dominant direction of the unit time, and obtain the dynamic spatial distribution characteristics of the pollution in the target basin in several unit times as the pollutant trend result.

[0082] In this embodiment, the analysis device uses the standard deviation ellipse analysis method to calculate the elliptical center position, distribution range and dominant direction of the unit time according to the simulated data of the farmland growth cycle pollution load of several grid cells in the same unit time, and obtain the dynamic spatial distribution characteristics of the pollution in the target basin in several unit times as the pollutant trend result. It is possible to intuitively understand the dynamic change trend of the pollution, which helps to formulate targeted regional treatment strategies, such as arranging pollution prevention and control facilities in advance in the direction of the movement of the pollution center of gravity, reasonably planning the agricultural production layout, avoiding the further spread of pollution, and achieving effective optimization and treatment of non-point source pollution of farmland.

[0083] Please refer to Figure 7 , Figure 7The structural schematic diagram of a pollution analysis device based on farmland pollution load simulation data provided by an embodiment of the present application. This device can implement all or part of the pollution analysis device based on farmland pollution load simulation data through software, hardware, or a combination of both. The device 7 includes:

[0084] A data acquisition module 71, configured to obtain pollution influencing factor data and farmland area data of a number of grid units in a target basin within a preset time period for a number of unit times;

[0085] A non-point source pollution load simulation module 72, configured to simulate non-point source pollution load data based on the influencing factor data of a number of unit times of a number of the grid units, and obtain non-point source pollution load simulation data of a number of unit times of a number of the grid units;

[0086] A farmland sowing period pollution load simulation module 73, configured to input the influencing factor data, farmland area data, and non-point source pollution load simulation data of a number of unit times of a number of the grid units into a preset farmland pollution load simulation model for sowing period data simulation, and obtain farmland sowing period pollution load simulation data of a number of unit times of a number of the grid units;

[0087] A farmland growth cycle pollution load simulation module 74, configured to input the farmland sowing period pollution load simulation data and pollution influencing factor data of a number of unit times of a number of the grid units into a preset hydrological model for growth cycle data simulation, and obtain farmland growth cycle pollution load simulation data of a number of unit times of a number of the grid units;

[0088] A farmland pollution analysis module 75, configured to perform pollution analysis based on the farmland growth cycle pollution load simulation data of a number of unit times of a number of the grid units, and obtain a farmland pollution analysis result of the target basin.

[0089] In the embodiment of the present application, through the data acquisition module, pollution influencing factor data and farmland area data of a plurality of grid units in a target basin at a plurality of unit times within a preset time period are obtained; through the non-point source pollution load simulation module, non-point source pollution load data simulation is performed according to the influencing factor data of a plurality of unit times of a plurality of the grid units to obtain non-point source pollution load simulation data of a plurality of unit times of a plurality of the grid units; through the farmland sowing period pollution load simulation module, the influencing factor data, farmland area data and non-point source pollution load simulation data of a plurality of unit times of a plurality of the grid units are input into a preset farmland pollution load simulation model for sowing period data simulation to obtain farmland sowing period pollution load simulation data of a plurality of unit times of a plurality of the grid units; through the farmland growth cycle pollution load simulation module, the farmland sowing period pollution load simulation data and pollution influencing factor data of a plurality of unit times of a plurality of the grid units are input into a preset hydrological model for growth cycle data simulation to obtain farmland growth cycle pollution load simulation data of a plurality of unit times of a plurality of the grid units; through the farmland pollution analysis module, pollution analysis is performed according to the farmland growth cycle pollution load simulation data of a plurality of unit times of a plurality of the grid units to obtain the farmland pollution analysis result of the target basin. By using the farmland pollution load simulation model and the hydrological model, comprehensive and accurate simulation of the pollution load during the farmland growth cycle is realized, and pollution analysis is performed based on the obtained farmland growth cycle pollution load simulation data, providing scientific decision-making support for the effective protection of water resources and the sustainable development of agriculture.

[0090] Please refer to Figure 8 , Figure 8 which is a schematic structural diagram of a computer device provided by an embodiment of the present application. The computer device 8 includes: a processor 81, a memory 82, and a computer program 83 stored on the memory 82 and executable on the processor 81; the computer device may store multiple instructions, and the instructions are suitable for being loaded and executed by the processor 81 to perform the method steps of the above Figures 1 to 6 illustrated embodiment. The specific execution process may refer to the specific description of the Figures 1 to 6 illustrated embodiment and will not be elaborated here.

[0091] Among them, the processor 81 may include one or more processing cores. The processor 81 is connected to various parts within the server through various interfaces and lines. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 82, and by invoking the data in the memory 82, it executes various functions of the pollution analysis device 6 based on the farmland pollution load simulation data and processes the data. Optionally, the processor 81 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 81 may integrate a combination of one or several of a central processing unit 81 (CPU), a graphics processing unit 81 (GPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the touch display screen; the modem is used to process wireless communication. It can be understood that the above modem may not be integrated into the processor 81 and may be implemented separately through a single chip.

[0092] Among them, the memory 82 may include a random access memory 82 (RAM), or may also include a read-only memory 82 (ROM). Optionally, the memory 82 includes a non-transitory computer-readable storage medium. The memory 82 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 82 may include a program storage area and a data storage area. Among them, the program storage area may store instructions for implementing the operating system, instructions for at least one function (such as touch instructions, etc.), instructions for implementing the above method embodiments, etc.; the data storage area may store the data involved in the above method embodiments. Optionally, the memory 82 may also be at least one storage device located far from the aforementioned processor 81.

[0093] The embodiments of the present application also provide a storage medium, which can store multiple instructions. The instructions are suitable for being loaded and executed by a processor to perform the method steps of the above Figures 1 to 6 shown embodiments. The specific execution process can be referred to Figures 1 to 6 the specific description of the shown embodiments, and will not be elaborated here.

[0094] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of the functional units and modules are only for the convenience of mutual distinction and do not limit the protection scope of the present application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0095] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not described in detail or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0096] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0097] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal device and method can be implemented in other ways. For example, the device / terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0098] The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0099] In addition, in each embodiment of the present invention, each functional unit may be integrated into a processing unit, may exist physically alone for each unit, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software functional unit.

[0100] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium. Based on such an understanding, all or part of the processes in the above-described embodiment methods of the present invention may also be completed by instructing relevant hardware through a computer program. The computer program may be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described method embodiments may be implemented. Among them, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, an executable file, or some intermediate form, etc.

[0101] The present invention is not limited to the above embodiments. If various changes or deformations to the present invention do not depart from the spirit and scope of the present invention, and if these changes and deformations are within the scope of the claims of the present invention and equivalent technical scope, then the present invention also intends to include these changes and deformations.

Claims

1. A pollution analysis method based on simulated data of farmland pollution load, characterized in that, It includes the following steps: Obtain the pollution influencing factor data and farmland area data of several grid cells in the target watershed at several unit times within a preset time period; Perform non-point source pollution load data simulation based on the influencing factor data of several unit times of several of the grid cells to obtain the non-point source pollution load simulation data of several unit times of several of the grid cells; Input the influencing factor data, farmland area data, and non-point source pollution load simulation data of several unit times of several of the grid cells into a preset farmland pollution load simulation model for sowing period data simulation to obtain the farmland sowing period pollution load simulation data of several unit times of several of the grid cells; Input the farmland sowing period pollution load simulation data and pollution influencing factor data of several unit times of several of the grid cells into a preset hydrological model for growth cycle data simulation to obtain the farmland growth cycle pollution load simulation data of several unit times of several of the grid cells; Perform pollution analysis based on the farmland growth cycle pollution load simulation data of several unit times of several of the grid cells to obtain the farmland pollution analysis result of the target watershed.

2. The pollution analysis method based on the simulated data of farmland pollution load according to claim 1, characterized in that: The pollution influencing factor data includes rainfall data; The performing non-point source pollution load data simulation based on the influencing factor data of several unit times of several of the grid cells to obtain the non-point source pollution load simulation data of several unit times of several of the grid cells includes the steps of: Obtain the non-point source pollution load data of several unit times of several of the grid cells according to the rainfall data of several unit times of several of the grid cells and the corresponding relationship between the loads of several preset pollutants and rainfall, wherein the non-point source pollution load data includes the load data of several pollutants.

3. The pollution analysis method based on the simulated data of farmland pollution load according to claim 2, characterized in that: The influencing factor data further includes slope data; The inputting the influencing factor data, farmland area data, and non-point source pollution load simulation data of several unit times of several of the grid cells into a preset farmland pollution load simulation model for sowing period data simulation to obtain the farmland sowing period pollution load simulation data of several unit times of several of the grid cells includes the steps of: Calculate the influencing factor coefficients respectively according to the rainfall data and slope data in the pollution influencing factor data of several unit times of several of the grid cells to obtain the influencing factor coefficients of several unit times of several of the grid cells, wherein the influencing factor coefficients include rainfall influence coefficients and terrain influence coefficients; Obtain the sowing period output coefficients of several pollutants, and obtain the farmland sowing period pollution load simulation data of several unit times of several of the grid cells according to the farmland area data of several unit times of several of the grid cells, the rainfall influence coefficients, terrain influence coefficients, sowing period output coefficients of several pollutants, and a preset first pollution load simulation algorithm.

4. The pollution analysis method based on farmland pollution load simulation data according to claim 3, characterized in that Calculating influence factor coefficients for a number of grid cells at a number of unit times based on rainfall data and slope data in the pollution influence factor data for the number of unit times of the number of grid cells, to obtain influence factor coefficients for the number of unit times of the number of grid cells, includes the steps of: Obtaining rainfall influence coefficients for a number of unit times of a number of grid cells according to non-point source pollution load data, rainfall data, and a preset rainfall influence coefficient calculation algorithm for the number of unit times of the number of grid cells; Obtaining terrain influence coefficients for a number of unit times of a number of grid cells according to slope data and a preset terrain influence coefficient calculation algorithm for the number of unit times of the number of grid cells.

5. The pollution analysis method based on the simulated data of farmland pollution load according to claim 4, characterized in that: The hydrological model includes a number of hydrological response units; the pollution influence factor data further includes soil property data; Inputting the simulated pollution load data of the farmland sowing period and the pollution influence factor data for a number of unit times of a number of grid cells into a preset hydrological model for growth cycle data simulation, to obtain the simulated pollution load data of the farmland growth cycle for a number of unit times of a number of grid cells, includes the steps of: Inputting the simulated pollution load data of the farmland sowing period and the rainfall data, slope data, and soil property data in the pollution influence factor data for a number of unit times of a number of grid cells into the number of hydrological response units in point source form, and simulating the pollutant emissions of crops in the farmland for a number of unit times of a number of grid cells during the growth cycle according to a preset fertilization amount strategy, to obtain the simulated pollution load data of the farmland growth cycle for a number of unit times of a number of grid cells.

6. The pollution analysis method based on the simulated data of farmland pollution load according to claim 1, wherein: The farmland pollution analysis result includes pollutant load level results for a number of unit times of a number of grid cells and pollutant trend results for a number of unit times of the target basin; Conducting pollution analysis based on the simulated pollution load data of the farmland growth cycle for a number of unit times of a number of grid cells to obtain the farmland pollution analysis result of the target basin, includes the steps of: Using the cluster analysis method, conducting cluster division based on the simulated pollution load data of the farmland growth cycle for a number of unit times of a number of grid cells to obtain a set of simulated pollution load data for grid cells corresponding to a number of clusters; obtaining pollutant load level results for a number of grid cells corresponding to a number of clusters according to the set of simulated pollution load data for grid cells corresponding to a number of clusters and a preset pollutant load threshold; Using the standard deviation ellipse analysis method, calculating the center position, distribution range, and dominant direction of the ellipse for the unit time based on the simulated pollution load data of the farmland growth cycle for a number of grid cells at the same unit time, to obtain the dynamic spatial distribution characteristics of the pollution in the target basin for a number of unit times, as the pollutant trend result.

7. A pollution analysis device based on simulated data of farmland pollution load, characterized in that, Including: A data acquisition module, configured to obtain pollution influence factor data and farmland area data for a number of unit times of a number of grid cells in a target basin within a preset time period; A non-point source pollution load simulation module for simulating non-point source pollution load data based on the influencing factor data of a number of grid cells at a number of unit times, and obtaining non-point source pollution load simulation data of a number of grid cells at a number of unit times; A pollution load simulation module for the farmland sowing period, which inputs the influencing factor data, farmland area data, and non-point source pollution load simulation data of a number of grid cells at a number of unit times into a preset farmland pollution load simulation model for sowing period data simulation, and obtains farmland sowing period pollution load simulation data of a number of grid cells at a number of unit times; A pollution load simulation module for the farmland growth cycle, which inputs the farmland sowing period pollution load simulation data and pollution influencing factor data of a number of grid cells at a number of unit times into a preset hydrological model for growth cycle data simulation, and obtains farmland growth cycle pollution load simulation data of a number of grid cells at a number of unit times; A farmland pollution analysis module for performing pollution analysis based on the farmland growth cycle pollution load simulation data of a number of grid cells at a number of unit times, and obtaining the farmland pollution analysis result of the target watershed.

8. A computer device, characterized in that, Including: A processor, a memory, and a computer program stored on the memory and executable on the processor; when the computer program is executed by the processor, the steps of the pollution analysis method based on farmland pollution load simulation data as described in any one of claims 1 to 6 are implemented.

9. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the pollution analysis method based on farmland pollution load simulation data of the resource allocation method based on a neural network model as described in any one of claims 1 to 6 are implemented.

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