Geographical information-based simulation method and system for spatial distribution of farmland microplastic emission

Abstract

This invention discloses a method and system for simulating the spatial distribution of microplastic emissions from farmland based on geographic information. The method includes: first, collecting data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitoring area; then, determining irrigation water demand data based on the farmland area data, and combining this data with the irrigation water demand, agricultural film usage, and livestock and poultry breeding volume data to estimate the microplastic emissions from farmland in the monitoring area. The estimated microplastic emissions represent the amount of microplastics over a large area of ​​the entire monitoring area, but the spatial distribution is not refined enough. Finally, the monitoring area is divided into multiple grids, and the amount of microplastics in each grid is determined based on the microplastic emissions, resulting in a simulation of the spatial distribution of microplastics in farmland at the grid scale. This method eliminates the need for on-site sampling and laboratory analysis, solving the problems of high cost and time-consuming labor in existing farmland microplastic monitoring, and can meet the requirements for large-scale simulation of the spatial distribution of microplastics in farmland.

Description

Technical Field

[0001] This invention relates to the field of computer-aided simulation technology, specifically to a method and system for simulating the spatial distribution of microplastic emissions from farmland based on geographic information. Background Technology

[0002] With the widespread use of agricultural activities such as plastic film mulching and irrigation, microplastics, as a new type of pollutant, are accumulating in farmland environments. Their potential risks to soil structure, crop growth, and food chain security have attracted widespread global attention. Accurately understanding the spatial distribution characteristics of microplastics in farmland is a prerequisite for conducting pollution risk assessments and developing effective remediation strategies.

[0003] Currently, monitoring the distribution of microplastics in farmland mainly relies on traditional field sampling and laboratory analysis. While this traditional method yields accurate results, it suffers from limited sampling points, high costs, and is time-consuming and labor-intensive. Furthermore, it only provides information on discrete points, making it difficult to reveal the continuous and comprehensive spatial distribution pattern of microplastics in farmland over a large area. Referring to existing research, “Yang Jie et al. Environmental processes and ecological effects of micro / nanoplastics in the soil-plant system [J]. Progress in Chemistry. 2025.37(1):89-102”, a survey of 477 farmland soil samples from 109 cities revealed that microplastics in farmland are mainly affected by factors such as agricultural film, livestock and poultry numbers, and irrigation water. Based on this research, it can be determined that there is a correlation between livestock and poultry farming volume and irrigation water demand and microplastics in farmland. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a method and system for simulating the spatial distribution of microplastic emissions from farmland based on geographic information. This method can obtain continuous and comprehensive spatial distribution data of microplastics from farmland over a large area. The specific technical solution is as follows: In a first aspect, a method for simulating the spatial distribution of microplastic emissions from farmland based on geographic information is provided. In a first feasible implementation of this first aspect, the method includes: Obtain data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitoring area; The irrigation water demand data for the monitoring area is determined by the farmland area data, and the microplastic emissions from the farmland in the monitoring area are estimated by combining the agricultural film usage data and livestock and poultry breeding data. The monitoring area is spatially discretized, and the microplastic distribution in the monitoring area is simulated by combining the microplastic emissions from farmland.

[0005] In conjunction with the first possible implementation of the first aspect, in the second possible implementation of the first aspect, determining the irrigation water demand data of the monitoring area through the farmland area data includes: The irrigation water demand per unit area corresponding to the monitoring area is obtained, and the irrigation water demand data is calculated by combining the farmland area data.

[0006] In conjunction with the first feasible method of the first aspect, in the third feasible method of the first aspect, estimating the microplastic emissions from farmland in the monitored area includes: The microplastic emissions from farmland in the monitored area are calculated using a pre-defined model for estimating farmland microplastic emissions. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ; in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. It is a constant.

[0007] In conjunction with the first feasible method of the first aspect, in the fourth feasible method of the first aspect, the microplastic distribution in the monitoring area is simulated, including: The monitoring area was divided into grids, and the proportion of farmland area in each grid was calculated. Using the proportion of farmland area as a weight, and combining it with the amount of microplastic emissions from farmland, the amount of microplastics in each grid cell is determined to simulate the distribution of microplastics in the monitoring area.

[0008] Secondly, a spatial distribution simulation system for farmland microplastic emissions based on geographic information is provided. In a first feasible implementation of this second aspect, it includes: The data acquisition module is configured to acquire data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitored area. The emission estimation module is configured to determine the irrigation water demand data of the monitoring area through the farmland area data, and estimate the microplastic emissions of the farmland in the monitoring area by combining the agricultural film usage data and livestock and poultry breeding data. The distribution simulation module is configured to spatially discretize the monitoring area and simulate the microplastic distribution in the monitoring area in conjunction with the microplastic emissions from farmland.

[0009] In conjunction with the first possible implementation of the second aspect, in the second possible implementation of the second aspect, the emission estimation module includes: The water demand calculation unit is configured to obtain the irrigation water demand per unit area corresponding to the monitoring area, and calculate the irrigation water demand data in combination with the farmland area data.

[0010] In conjunction with the first possible implementation of the second aspect, in the third possible implementation of the second aspect, the emission estimation module includes: The emission estimation unit is configured to calculate the amount of microplastic emissions from farmland in the monitoring area using a preset farmland microplastic emission estimation model. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ; in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. It is a constant.

[0011] In conjunction with the first possible implementation of the second aspect, in the fourth possible implementation of the second aspect, the distributed simulation module includes: The grid division unit is configured to divide the monitoring area into grids and calculate the proportion of farmland area in each grid. The distribution simulation unit is configured to use the proportion of farmland area as a weight and combine it with the amount of microplastic emissions from farmland to determine the amount of microplastics in each grid, thereby simulating the distribution of microplastics in the monitoring area.

[0012] Beneficial Effects: The spatial distribution simulation method and system for farmland microplastic emissions based on geographic information of this invention can estimate the amount of farmland microplastic emissions in a monitoring area using data on agricultural film usage, livestock and poultry breeding, and irrigation water demand. By spatially discretizing the monitoring area and combining this data with farmland microplastic emissions, a continuous and comprehensive spatial distribution of farmland microplastics over a large area can be quickly simulated without the need for on-site sampling and laboratory analysis. This solves the problems of high cost and time-consuming labor in existing farmland microplastic monitoring methods and can meet the requirements for large-scale simulation of farmland microplastic spatial distribution. Attached Figure Description

[0013] To more clearly illustrate the specific embodiments of the present invention, the accompanying drawings used in the specific embodiments will be briefly described below. In all the drawings, the elements or parts are not necessarily drawn to scale.

[0014] Figure 1A flowchart illustrating a method for simulating the spatial distribution of microplastic emissions in farmland according to an embodiment of the present invention; Figure 2 This is a system block diagram of a farmland microplastic emission spatial distribution simulation system provided in an embodiment of the present invention; Figure 3 This is a spatial distribution map of microplastic emissions in farmland obtained using the spatial distribution simulation method of the present invention. Detailed Implementation

[0015] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0016] like Figure 1 The flowchart shown is a method for simulating the spatial distribution of microplastic emissions from farmland based on geographic information. This simulation method includes: Step 1: Obtain data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitoring area; Step 2: Determine the irrigation water demand data of the monitoring area using the farmland area data, and estimate the microplastic emissions from the farmland in the monitoring area by combining the agricultural film usage data and livestock and poultry breeding data. Step 3: Spatially discretize the monitoring area and simulate the microplastic distribution in the monitoring area by combining the microplastic emissions from farmland.

[0017] Specifically, microplastics in farmland are mainly affected by agricultural film, livestock numbers, and irrigation water. Therefore, the first step is to collect data on agricultural film usage, livestock numbers, and farmland area in the monitoring area. Then, irrigation water demand data for the monitoring area can be determined based on the farmland area data. Combining this data with the irrigation water demand, agricultural film usage, and livestock numbers, the amount of microplastics emitted from farmland in the monitoring area can be estimated. Since the estimated microplastic emissions represent the amount of microplastics over a large area of ​​the entire monitoring area, the spatial distribution is not precise enough. Therefore, the monitoring area can be spatially discretized into multiple grids. Based on the overall microplastic emissions from farmland in the monitoring area, the amount of microplastics in each grid can be determined, thus obtaining a simulation result of the spatial distribution of microplastics in farmland at the grid scale. This method eliminates the need for on-site sampling and laboratory analysis, solving the problems of high cost and time-consuming labor in current farmland microplastic monitoring, and can meet the requirements for large-scale simulation of the spatial distribution of microplastics in farmland.

[0018] In this embodiment, data on the usage of agricultural film in the monitoring area can be collected from statistical yearbooks published by relevant departments. Data on livestock and poultry farming in the monitoring area can be collected from agricultural economic statistical bulletins published by relevant departments. Data on farmland area in the monitoring area can be collected from land change survey results published by relevant departments.

[0019] In this embodiment, optionally, determining the irrigation water demand data of the monitoring area using the farmland area data includes: The irrigation water demand per unit area corresponding to the monitoring area is obtained, and the irrigation water demand data is calculated by combining the farmland area data.

[0020] Specifically, the irrigation water requirement per unit area of ​​farmland in the monitoring area can be determined through officially released statistical data. Combined with the farmland area data of the monitoring area, the irrigation water requirement for the entire monitoring area can be quickly calculated. The specific calculation formula is as follows: ; in, To determine the farmland area of ​​the monitoring region, farmland patches within the monitoring region can be selected from land survey results collected from relevant platforms. The areas of these selected farmland patches can then be calculated and superimposed to obtain the farmland area data for the monitoring region. This refers to the irrigation water requirement per unit area.

[0021] In this embodiment, optionally, estimating the microplastic emissions from farmland in the monitoring area includes: The amount of microplastic emissions from farmland in the monitored area is calculated using a pre-set model for estimating farmland microplastic emissions.

[0022] Specifically, the study found that farmland microplastic emissions are related to the amount of agricultural film used, livestock and poultry farming, and irrigation water demand. Based on the amount of agricultural film used, livestock and poultry farming, and irrigation water demand, a model for estimating farmland microplastic emissions was constructed. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ; in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. The coefficients for agricultural film usage, livestock and poultry breeding volume, and irrigation water demand are estimated by collecting measured values ​​of microplastic emissions from farmland in different regions, and by gathering data on agricultural film usage and livestock and poultry breeding volume from relevant statistical yearbooks and agricultural economic statistical bulletins, as well as data on irrigation water demand per unit area and calculated farmland area, to calculate the irrigation water demand for different regions. Finally, regression analysis is performed on the collected measured values ​​of microplastic emissions from farmland, agricultural film usage, livestock and poultry breeding volume, and irrigation water demand from all regions to obtain the estimated coefficients for agricultural film usage, livestock and poultry breeding volume, and irrigation water demand.

[0023] Specifically, a total of 60 different regions were surveyed for measured values ​​of microplastic emissions from farmland, agricultural film usage, livestock and poultry breeding volume, and irrigation water demand. Then, a stratified random sampling method was used to divide all statistical objects into: a modeling group of 42 statistical objects (70%) and a validation group of 18 statistical objects (30%).

[0024] Based on the modeling group data, SPSS version 29.0.2.0 software was used, and the "Linear Regression" function module was selected for processing and analysis. The specific analysis results are shown in the table below.

[0025] Table 1 Regression Statistics Table 2 Coefficient Table In the table above, Multiple R, a correlation coefficient R of 0.9 indicates a strong positive correlation, a measurement coefficient RSquare of 0.88 indicates a high degree of fit between the regression model and the actual data, Significance F is significantly less than 0.05, and the p-values ​​of all three independent variables are less than 0.05. These data indicate that the model performs well. Based on the regression analysis results, the estimated coefficients for agricultural film usage, livestock and poultry breeding volume, and irrigation water demand can be set as 0.17, 0.004, and 0.007, respectively, with constants... It can be set to 18.76.

[0026] To verify the accuracy of the above-mentioned farmland microplastic emission estimation model, the model can be validated using data from the remaining 18 statistical objects. The specific method is as follows: First, the usage of agricultural film, livestock and poultry breeding volume, and irrigation water demand of each statistical object are extracted as input variables and substituted into the farmland microplastic emission estimation model to calculate the simulated value of farmland microplastic emissions. Then, Pearson correlation coefficient is used to perform correlation analysis between the simulated and measured values. The obtained correlation coefficient is 0.78 (P<0.05), indicating that the simulation results are reliable.

[0027] In this way, without the need for on-site sampling and experimental analysis, the amount of microplastic emissions from farmland can be quickly estimated using a model based on collected data on agricultural film usage, livestock and poultry breeding volume, and irrigation water demand. This solves the problems of high cost, time-consuming and labor-intensive existing farmland microplastic monitoring methods.

[0028] In this embodiment, optionally, simulating the distribution of microplastics in the monitoring area includes: The monitoring area was divided into grids, and the proportion of farmland area in each grid was calculated. Using the proportion of farmland area as a weight, and combining it with the amount of microplastic emissions from farmland, the amount of microplastics in each grid cell is determined to simulate the distribution of microplastics in the monitoring area.

[0029] Specifically, firstly, the monitoring area can be divided into grids, and the farmland area in each grid can be counted. Based on the farmland area in each grid and the total farmland area of ​​the monitoring area, the proportion of farmland area in each grid can be calculated. Then, the proportion of farmland area is used as a weight and multiplied by the amount of microplastic emissions from farmland in the monitoring area to determine the amount of microplastics in farmland in each grid, thereby simulating the distribution of microplastics in the monitoring area at the grid scale.

[0030] Specifically, first, a 500m*500m grid layer is created using the Create fishnet function in ArcGIS 10.8, and each grid cell is assigned a unique code. Then, using the Intersect spatial overlay function in ArcGIS 10.8, the grid layer is overlaid with the farmland distribution layer of the monitored area to obtain a farmland grid layer, and the proportion of farmland area in each grid cell of the farmland grid layer is calculated. Finally, the proportion of farmland area is used as a weight and multiplied by the overall farmland microplastic emissions in the monitored area to obtain the spatial distribution simulation results of farmland microplastics at the 500m*500m grid scale, as shown below. Figure 3 As shown.

[0031] like Figure 2 The diagram shown is a system block diagram of a geographic information-based simulation system for the spatial distribution of microplastic emissions from farmland. The simulation system includes: The data acquisition module is configured to acquire data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitored area. The emission estimation module is configured to determine the irrigation water demand data of the monitoring area through the farmland area data, and estimate the microplastic emissions of the farmland in the monitoring area by combining the agricultural film usage data and livestock and poultry breeding data. The distribution simulation module is configured to spatially discretize the monitoring area and simulate the microplastic distribution in the monitoring area in conjunction with the microplastic emissions from farmland.

[0032] Specifically, the simulation system includes a data acquisition module, an emission estimation module, and a distribution simulation module. The data acquisition module collects data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitoring area. The emission estimation module determines the irrigation water demand data for the monitoring area based on the farmland area data, and estimates the microplastic emissions from farmland in the monitoring area by combining the irrigation water demand data, agricultural film usage data, and livestock and poultry breeding volume data. The distribution simulation module spatially discretizes the monitoring area, dividing it into multiple grids, and determines the microplastic amount in each grid based on the overall microplastic emissions from farmland in the monitoring area, thus obtaining the spatial distribution simulation results of microplastics in farmland at the grid scale. This eliminates the need for on-site sampling and laboratory analysis, solving the problems of high cost and time-consuming labor in existing farmland microplastic monitoring, and enabling large-scale simulation of the spatial distribution of microplastics in farmland.

[0033] In this embodiment, optionally, the emission estimation module includes: The water demand calculation unit is configured to obtain the irrigation water demand per unit area corresponding to the monitoring area, and calculate the irrigation water demand data in combination with the farmland area data.

[0034] Specifically, the emission estimation module includes a water demand calculation unit. This unit can determine the irrigation water demand per unit area of ​​farmland in the monitoring area through officially released statistical data, and quickly calculate the irrigation water demand data of the monitoring area by combining the farmland area data of the monitoring area.

[0035] In this embodiment, optionally, the emission estimation module includes: The emission estimation unit is configured to calculate the amount of microplastic emissions from farmland in the monitoring area using a preset farmland microplastic emission estimation model. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ; in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. It is a constant.

[0036] In this embodiment, optionally, the distribution simulation module includes: The grid division unit is configured to divide the monitoring area into grids and calculate the proportion of farmland area in each grid. The distribution simulation unit is configured to use the proportion of farmland area as a weight and combine it with the amount of microplastic emissions from farmland to determine the amount of microplastics in each grid, thereby simulating the distribution of microplastics in the monitoring area.

[0037] Specifically, since the estimated farmland microplastic emissions represent the amount of microplastics over a large area of ​​the entire monitoring region, the spatial distribution is not refined enough. Therefore, the distribution simulation module includes grid division units and distribution simulation units. The grid division units can divide the monitoring region into multiple grids according to a set grid scale and calculate the proportion of farmland area in each grid. The distribution simulation units can use the proportion of farmland area as a weight, multiply it by the farmland microplastic emissions in the monitoring region, and thus determine the amount of farmland microplastics in each grid, thereby simulating the microplastic distribution in the monitoring region at the grid scale.

[0038] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A method for simulating the spatial distribution of microplastic emissions from farmland based on geographic information, characterized in that, include: Obtain data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitoring area; The irrigation water demand data for the monitoring area is determined by the farmland area data, and the microplastic emissions from the farmland in the monitoring area are estimated by combining the agricultural film usage data and livestock and poultry breeding data. The monitoring area is spatially discretized, and the microplastic distribution in the monitoring area is simulated by combining the microplastic emissions from farmland.

2. The method for simulating the spatial distribution of microplastic emissions from farmland according to claim 1, characterized in that, The irrigation water demand data for the monitoring area is determined using the farmland area data, including: The irrigation water demand per unit area corresponding to the monitoring area is obtained, and the irrigation water demand data is calculated by combining the farmland area data.

3. The method for simulating the spatial distribution of microplastic emissions from farmland according to claim 1, characterized in that, Estimate the amount of microplastic emissions from farmland in the monitored area, including: The microplastic emissions from farmland in the monitored area are calculated using a pre-defined model for estimating farmland microplastic emissions. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ； in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. It is a constant.

4. The method for simulating the spatial distribution of microplastic emissions from farmland according to claim 1, characterized in that, The distribution of microplastics in the simulated monitoring area includes: The monitoring area was divided into grids, and the proportion of farmland area in each grid was calculated. Using the proportion of farmland area as a weight, and combining it with the amount of microplastic emissions from farmland, the amount of microplastics in each grid cell is determined to simulate the distribution of microplastics in the monitoring area.

5. A spatial distribution simulation system for farmland microplastic emissions based on geographic information, characterized in that, include: The data acquisition module is configured to acquire data on agricultural film usage, livestock and poultry breeding volume, and farmland area in the monitored area. The emission estimation module is configured to determine the irrigation water demand data of the monitoring area through the farmland area data, and estimate the microplastic emissions of the farmland in the monitoring area by combining the agricultural film usage data and livestock and poultry breeding data. The distribution simulation module is configured to spatially discretize the monitoring area and simulate the microplastic distribution in the monitoring area in conjunction with the microplastic emissions from farmland.

6. The spatial distribution simulation system for farmland microplastic emissions according to claim 5, characterized in that, The emissions estimation module includes: The water demand calculation unit is configured to obtain the irrigation water demand per unit area corresponding to the monitoring area, and calculate the irrigation water demand data in combination with the farmland area data.

7. The spatial distribution simulation system for farmland microplastic emissions according to claim 5, characterized in that, The emissions estimation module includes: The emission estimation unit is configured to calculate the amount of microplastic emissions from farmland in the monitoring area using a preset farmland microplastic emission estimation model. The specific calculation formula for the farmland microplastic emission estimation model is as follows: ； in, For microplastic emissions from farmland, , , These are the amounts of agricultural film used, livestock and poultry farming, and irrigation water demand, respectively. , , These are the estimated coefficients corresponding to the amount of agricultural film used, the amount of livestock and poultry raised, and the irrigation water demand, respectively. It is a constant.

8. The spatial distribution simulation system for farmland microplastic emissions according to claim 5, characterized in that, The distribution simulation module includes: The grid division unit is configured to divide the monitoring area into grids and calculate the proportion of farmland area in each grid. The distribution simulation unit is configured to use the proportion of farmland area as a weight and combine it with the amount of microplastic emissions from farmland to determine the amount of microplastics in each grid, thereby simulating the distribution of microplastics in the monitoring area.

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