Cultivated land cadmium pollution risk multi-scale prediction method and system

Abstract

The invention discloses a farmland cadmium pollution risk multi-scale prediction method and system, and relates to the technical field of cadmium pollution data prediction.The farmland cadmium pollution risk multi-scale prediction method comprises the steps that a cadmium content distribution diagram of a farmland area to be analyzed is constructed according to position information and previous cadmium content information, so that a solid foundation is provided for subsequent pollution source determination and gridding processing, and the farmland cadmium pollution risk is predicted. And the prediction reliability is improved. According to the soil background value, grid processing is carried out on the cultivated land area to be analyzed to obtain a plurality of grid cultivated land areas, a pollution source is matched, and the contribution relation of the pollution source to the cadmium content of each grid cultivated land area is quantified. Setting an actual cadmium content threshold value of each grid cultivated land area, and determining the cadmium pollution risk according to the cadmium content predicted value, the actual cadmium content threshold value, the standard cadmium content threshold value and the cadmium bio-availability index of the grid cultivated land area, so as to improve the precision and adaptability of cultivated land cadmium pollution risk prediction. Accurate monitoring of the cadmium pollution risk of the cultivated land is guaranteed, and follow-up targeted treatment measures can be conveniently adopted.

Description

Technical Field

[0001] The present invention relates to the technical field of cadmium pollution data prediction, and in particular to a multi-scale prediction method and system for cadmium pollution risk in cultivated land. Background Art

[0002] The risk prediction scheme for cadmium pollution in cultivated land is based on the severity and complexity of the current cadmium pollution problem in cultivated land. With the acceleration of industrialization and urbanization, the risk of heavy metal pollution in farmland ecosystems, especially cadmium pollution, is becoming increasingly prominent. Due to the multiple influences of farmland ecosystem characteristics (such as soil properties, micro-topography and climate, etc.), there is significant spatial heterogeneity in the risk of cadmium and arsenic pollution in rice fields. The traditional single-scale pollution risk assessment method is difficult to accurately identify the pollution risks of different regions and plots, resulting in blind targeting of governance technologies and the inability to accurately judge the governance effects. Therefore, the multi-scale prediction scheme aims to achieve accurate identification and dynamic monitoring of cadmium pollution risks in rice fields by comprehensively considering the key influencing factors at the regional and plot scales and their regional differences, combined with intelligent monitoring technology, to provide a scientific basis for precise governance.

[0003] In the existing technology, predictions are often made based solely on the cadmium content data of cultivated land. The prediction scale is relatively simple, and no further analysis is performed on scales such as pollution sources and geographical locations. This results in poor adaptability and low accuracy in the prediction of cadmium pollution risks in cultivated land, which is not conducive to the safety of cultivated land crops.

[0004] Therefore, how to improve the adaptability and accuracy of cadmium pollution risk prediction in cultivated land is a technical problem that needs to be solved. Summary of the invention

[0005] The purpose of the present invention is to solve the problems of poor adaptability and low accuracy of farmland cadmium pollution risk prediction in the prior art, and to propose a multi-scale prediction method for farmland cadmium pollution risk, which includes:

[0006] Obtaining location information and past cadmium content information of the cultivated land area to be analyzed, and constructing a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and past cadmium content information, obtaining activity information in the cultivated land area to be analyzed, and matching the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed;

[0007] A set of candidate pollution sources is constructed based on the activity information within the surrounding area of ​​the cultivated land area to be analyzed, and the cadmium content distribution map is analyzed to screen out pollution sources outside the cultivated land area to be analyzed from the set of candidate pollution sources, and the soil background value within the cultivated land area to be analyzed is determined. The cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas;

[0008] Match the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantify the contribution of the pollution sources to the cadmium content of each grid cultivated land area, calculate the soil prospect value of each grid cultivated land area based on the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area based on the soil prospect value;

[0009] A cadmium content prediction model is constructed through the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators. The cadmium pollution risk is determined according to the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index;

[0010] Through GIS software, the cadmium pollution risk corresponding to each grid cultivated land area is mapped to the grid cultivated land area within the cultivated land area to be analyzed, so as to visualize the cadmium pollution risk.

[0011] In some embodiments of the present application, a cadmium content distribution map of the cultivated land area to be analyzed is constructed based on the location information and the previous cadmium content information, including:

[0012] The cadmium content information includes the cadmium content in soil and the cadmium content in crops. A location map of the cultivated land to be analyzed is established according to the location information of the cultivated land area to be analyzed. The cadmium content in soil and the cadmium content in crops are mapped to corresponding positions on the location map of the cultivated land to be analyzed. The cultivated land area to be analyzed is divided into known cultivated land areas and unknown cultivated land areas according to the mapping results on the location map of the cultivated land to be analyzed. The known cultivated land areas are areas supported by data on the cadmium content in soil and the cadmium content in crops, and the unknown cultivated land areas are areas without data on the cadmium content in soil and the cadmium content in crops.

[0013] Determine the distances between known cultivated land areas, construct a semivariogram based on the soil cadmium content and crop cadmium content in the known cultivated land areas and the distances between the known cultivated land areas, generate cadmium content calibration values ​​based on the soil cadmium content and crop cadmium content in the known cultivated land areas surrounding the unknown cultivated land areas, and determine the affected range of the unknown cultivated land areas based on the cadmium content calibration values;

[0014] The distance between each known cultivated land area and the unknown cultivated land area within the affected range of the unknown cultivated land area is calculated, and the influence of each known cultivated land area on the unknown cultivated land area is determined by combining the semivariogram and the soil cadmium content and crop cadmium content of the known cultivated land areas, so as to predict the soil cadmium content and crop cadmium content in the unknown cultivated land area, and map the predicted values ​​to the unknown cultivated land area on the cultivated land location map to be analyzed, so as to generate the cadmium content distribution map of the cultivated land area to be analyzed.

[0015] In some embodiments of the present application, the activity information is matched with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed, including:

[0016] The activity information is imported into the cadmium content distribution map, the cadmium content and activity impact range generated by the activity information are analyzed, and the pollution source is determined based on the degree of overlap between the cadmium content, activity impact range and the cadmium content distribution map, thereby determining the pollution source in the cultivated land area to be analyzed.

[0017] In some embodiments of the present application, the cadmium content distribution map is analyzed to screen out pollution sources outside the cultivated land area to be analyzed from the set of pollution sources to be selected, including:

[0018] In the cadmium content distribution map, the cadmium content generated by the pollution sources in the cultivated land area to be analyzed, the activity impact range and the regional cadmium content are compared to determine multiple sub-cultivated land areas, and the distance and cadmium pollution emission intensity between each candidate pollution source in the candidate pollution source set and the cultivated land area to be analyzed are evaluated. The natural meteorological data, distance and cadmium pollution emission intensity are input into the simulation model to simulate the pollution flow of the candidate pollution sources, and the pollution sources outside the cultivated land area to be analyzed are screened out according to the pollution flow between the sub-cultivated land areas and the candidate pollution sources.

[0019] In some embodiments of the present application, the cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas, including:

[0020] All ranges of soil background values ​​in the cultivated land area to be analyzed are counted, and the intervals of soil background values ​​are determined according to all ranges of soil background values. Adjacent areas are divided into the same grid according to the intervals of soil background values, so that the cultivated land area to be analyzed is gridded to obtain multiple grid cultivated land areas.

[0021] In some embodiments of the present application, the soil prospect value of each grid cultivated land area is calculated based on the cadmium content information, including:

[0022] According to the soil cadmium content and the crop cadmium content, the cadmium content change curves corresponding to the soil cadmium content and the crop cadmium content are established respectively, and the frequently appearing cadmium content interval is found in the cadmium content change curve, recorded as the frequent cadmium content interval, and the maximum cadmium content is found within a preset range at both ends of the frequent cadmium content interval, recorded as the relative maximum cadmium content;

[0023] The soil prospect value of the grid cultivated land area is determined based on the frequent cadmium content intervals and the maximum relative cadmium content of both soil cadmium content and crop cadmium content;

[0024]

[0025] Among them, Q i is the soil prospect value of the ith grid cultivated land area, α1 and α2 are the weights of soil cadmium content and crop cadmium content, respectively, and W1 i is the median of the frequent cadmium content interval of soil cadmium content in the i-th grid cultivated land area, W2 i is the median of the frequent cadmium content interval of crops in the i-th grid cultivated land area, maxW1 i is the maximum relative cadmium content of soil cadmium content in the i-th grid cultivated land area, maxW2 i is the maximum relative cadmium content of crops in the i-th grid cultivated land area, k i is the preset constant for the ith grid cultivated land area.

[0026] In some embodiments of the present application, a cadmium content prediction model is constructed by using the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, including:

[0027] Collect and preprocess the activity information of pollution sources, the contribution of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, extract relevant features from the data, and normalize the features;

[0028] The features are divided into training sets and test sets, and the cadmium content prediction model is constructed using the training sets and test sets.

[0029] In some embodiments of the present application, the cadmium pollution risk is determined according to the predicted cadmium content value, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index of the grid cultivated land area, including:

[0030]

[0031] Among them, L is the cadmium pollution risk level, β1 and β2 are the risk weights of the difference between the predicted cadmium content and the actual cadmium content threshold, and the risk weights of the difference between the predicted cadmium content and the standard cadmium content threshold, respectively. is the predicted value of cadmium content, G1 is the actual cadmium content threshold, G2 is the standard cadmium content threshold, τ is the cadmium bioavailability index, a is the preset constant, b is the cadmium pollution risk constant, and [] is the rounding symbol.

[0032] Correspondingly, the present application also provides a multi-scale prediction system for cadmium pollution risk in cultivated land, including:

[0033] A construction module is used to obtain the location information and the previous cadmium content information of the cultivated land area to be analyzed, and to construct a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and the previous cadmium content information, obtain the activity information in the cultivated land area to be analyzed, and match the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed;

[0034] A grid module is used to construct a set of pollution sources to be selected based on the activity information within the surrounding area of ​​the cultivated land area to be analyzed, analyze the cadmium content distribution map to screen out pollution sources outside the cultivated land area to be analyzed from the set of pollution sources to be selected, determine the soil background value within the cultivated land area to be analyzed, and grid the cultivated land area to be analyzed according to the soil background value to obtain multiple grid cultivated land areas;

[0035] A setting module is used to match the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantify the contribution of the pollution sources to the cadmium content of each grid cultivated land area, calculate the soil prospect value of each grid cultivated land area according to the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area based on the soil prospect value;

[0036] The risk module is used to construct a cadmium content prediction model based on the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators, and determine the cadmium pollution risk based on the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index;

[0037] The display module is used to map the cadmium pollution risk corresponding to each grid cultivated land area to the grid cultivated land area within the cultivated land area to be analyzed through GIS software, so as to visualize the cadmium pollution risk.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. Based on the location information and previous cadmium content information, a cadmium content distribution map of the cultivated land area to be analyzed is constructed to provide a solid foundation for subsequent pollution source identification and grid processing, thereby improving the reliability of the prediction.

[0040] 2. The cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas. The soil in different situations is gridded to improve the adaptability of the prediction and accurately predict the cadmium pollution risk of each grid.

[0041] 3. Calculate the soil prospect value of each grid cultivated land area based on the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area. Determine the cadmium pollution risk based on the predicted cadmium content of the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index. This will improve the accuracy and adaptability of the prediction of cadmium pollution risk in cultivated land, ensure accurate monitoring of cadmium pollution risk in cultivated land, and facilitate the subsequent targeted adoption of control measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of a multi-scale prediction method for cadmium pollution risk in cultivated land proposed by the present invention;

[0043] Figure 2 This is a structural schematic diagram of a multi-scale prediction system for cultivated land cadmium pollution risk proposed by the present invention. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0045] Reference Figure 1 , a multi-scale prediction method for cadmium pollution risk in cultivated land, comprising the following steps,

[0046] Step S101, obtain the location information and previous cadmium content information of the cultivated land area to be analyzed, and construct a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and the previous cadmium content information, obtain the activity information in the cultivated land area to be analyzed, and match the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed.

[0047] In this embodiment, the cadmium content information is obtained by measuring the cadmium content in the corresponding soil or crops through soil sampling and laboratory analysis. Not all cultivated land in the cultivated land area to be analyzed may have cadmium content information, and it is necessary to interpolate the areas with missing data to improve the cadmium content distribution map.

[0048] In this example, cadmium pollution in cultivated land mainly comes from the following aspects (activity information):

[0049] Industrial emissions: including wastewater, waste gas and waste residue discharged from industrial processes such as mining, smelting and electroplating. These wastes often contain high concentrations of cadmium, which enter the soil through natural sedimentation, rainwater erosion and other means.

[0050] Agricultural activities: excessive use of cadmium-containing pesticides, fertilizers (especially phosphate fertilizers) and sewage irrigation and other agricultural activities are also important sources of cadmium pollution in cultivated land.

[0051] Atmospheric deposition: Cadmium particles in the air fall to the ground through atmospheric deposition and gradually accumulate in the soil.

[0052] Other sources: such as the incineration of urban sludge and garbage, improper disposal of used batteries, etc., may also lead to an increase in cadmium content in the soil.

[0053] In some embodiments of the present application, a cadmium content distribution map of the cultivated land area to be analyzed is constructed based on the location information and the previous cadmium content information, including:

[0054] The cadmium content information includes the cadmium content in soil and the cadmium content in crops. A location map of the cultivated land to be analyzed is established according to the location information of the cultivated land area to be analyzed. The cadmium content in soil and the cadmium content in crops are mapped to corresponding positions on the location map of the cultivated land to be analyzed. The cultivated land area to be analyzed is divided into known cultivated land areas and unknown cultivated land areas according to the mapping results on the location map of the cultivated land to be analyzed. The known cultivated land areas are areas supported by data on the cadmium content in soil and the cadmium content in crops, and the unknown cultivated land areas are areas without data on the cadmium content in soil and the cadmium content in crops.

[0055] Determine the distances between known cultivated land areas, construct a semivariogram based on the soil cadmium content and crop cadmium content in the known cultivated land areas and the distances between the known cultivated land areas, generate cadmium content calibration values ​​based on the soil cadmium content and crop cadmium content in the known cultivated land areas surrounding the unknown cultivated land areas, and determine the affected range of the unknown cultivated land areas based on the cadmium content calibration values;

[0056] The distance between each known cultivated land area and the unknown cultivated land area within the affected range of the unknown cultivated land area is calculated, and the influence of each known cultivated land area on the unknown cultivated land area is determined by combining the semivariogram and the soil cadmium content and crop cadmium content of the known cultivated land areas, so as to predict the soil cadmium content and crop cadmium content in the unknown cultivated land area, and map the predicted values ​​to the unknown cultivated land area on the cultivated land location map to be analyzed, so as to generate the cadmium content distribution map of the cultivated land area to be analyzed.

[0057] In the present embodiment, a semivariogram (semivariograms of soil cadmium content and crop cadmium content, respectively) is constructed according to the soil cadmium content and crop cadmium content on the known cultivated land area and the distance between the known cultivated land areas. The semivariogram, also known as the semivariance function, is a function that describes the variability of geographic spatial data. It represents the degree of difference in attribute values ​​between sample points (cadmium content information in the known cultivated land area) at different distances. Specifically, the semivariogram reflects the spatial variability between sample points by calculating half of the square of the difference between the sample point pairs. For each pair of sample points, the spatial distance between them is calculated. This is usually measured using Euclidean distance or Manhattan distance. For each pair of sample points, half of the square of the difference between their attribute values, i.e., the semivariogram, is calculated. This semivariogram reflects the degree of variation of the attribute values ​​between sample points at a given distance. The calculated semivariogram is plotted against the corresponding distance to obtain a semivariogram graph. In the graph, the trend of the semivariogram with distance can be observed, thereby understanding the spatial variability between sample points. In order to more accurately describe the semivariogram, the calculated semivariogram is usually model-fitted. Common models include linear model, exponential model, Gaussian model, etc. Selecting the model that best fits the data for fitting can obtain a more accurate semivariogram.

[0058] In this embodiment, a cadmium content calibration value is generated based on the soil cadmium content and crop cadmium content of known cultivated land areas surrounding the unknown cultivated land area, and a comprehensive impact amount (cadmium content calibration value) is generated by comprehensively considering the soil cadmium content and crop cadmium content. Different comprehensive impact amounts correspond to different affected ranges.

[0059] In some embodiments of the present application, the activity information is matched with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed, including:

[0060] The activity information is imported into the cadmium content distribution map, the cadmium content and activity impact range generated by the activity information are analyzed, and the pollution source is determined based on the degree of overlap between the cadmium content, activity impact range and the cadmium content distribution map, thereby determining the pollution source in the cultivated land area to be analyzed.

[0061] In this embodiment, the cadmium content and the scope of activity impact of each activity information are analyzed separately, and the collected activity information (such as industrial activities, agricultural activities, traffic flow, etc.), the scope of activity impact and the cadmium content distribution map are imported into GIS. Through the spatial analysis function of GIS, the overlap between the activity area and the high cadmium content area can be calculated, so as to preliminarily determine the location of the pollution source within the area.

[0062] Step S102, constructing a set of candidate pollution sources based on activity information within the surrounding area of ​​the cultivated land area to be analyzed, analyzing the cadmium content distribution map to screen out pollution sources outside the cultivated land area to be analyzed in the set of candidate pollution sources, determining the soil background value within the cultivated land area to be analyzed, and gridding the cultivated land area to be analyzed according to the soil background value to obtain multiple grid cultivated land areas.

[0063] In this embodiment, in order to consider all pollution sources, the pollution sources outside the area are considered, the situations that may cause cadmium pollution emissions are used to construct a set of candidate pollution sources, and the pollution sources are screened in combination with the cadmium content distribution map.

[0064] In this embodiment, the soil background value represents the natural content of elements in the soil in a certain environmental unit without or with little impact from human activities. It is an important benchmark for evaluating the degree of soil pollution in environmental science. Specifically, the soil background value reflects the natural abundance of elements in the soil under normal geographical and geochemical conditions. The cultivated land area is gridded according to the initial soil conditions.

[0065] In some embodiments of the present application, the cadmium content distribution map is analyzed to screen out pollution sources outside the cultivated land area to be analyzed from the set of pollution sources to be selected, including:

[0066] In the cadmium content distribution map, the cadmium content generated by the pollution sources in the cultivated land area to be analyzed, the activity impact range and the regional cadmium content are compared to determine multiple sub-cultivated land areas, and the distance and cadmium pollution emission intensity between each candidate pollution source in the candidate pollution source set and the cultivated land area to be analyzed are evaluated. The natural meteorological data, distance and cadmium pollution emission intensity are input into the simulation model to simulate the pollution flow of the candidate pollution sources, and the pollution sources outside the cultivated land area to be analyzed are screened out according to the pollution flow between the sub-cultivated land areas and the candidate pollution sources.

[0067] In this embodiment, the cadmium content generated by the pollution source in the cultivated land area to be analyzed, the activity impact range and the cadmium content of the region are compared to determine multiple sub-cultivated land areas. First, the cultivated land area to be analyzed is divided into multiple areas according to the cadmium content of the region. The cadmium content in each area is compared according to the cadmium content generated by the pollution source and the activity impact range. If the cadmium content in the area is much greater than the cadmium content after the cadmium content generated by the pollution source is converted, the area is taken as a sub-area. The sub-cultivated land area is an area where the cadmium content in the area is much greater than the cadmium content converted by the pollution source in the area.

[0068] In the present embodiment, the simulation model can be a suitable pollution diffusion simulation software, such as Gaussian model, CALPUFF model, etc., which can simulate the diffusion and deposition process of pollutants in the atmosphere. Combined with natural meteorological factors such as wind direction and water flow, the possible impact path and range of pollution sources on the cultivated land area are analyzed. These pollution sources may have an impact on the cultivated land area through wind direction, water flow and other channels. The location, type, intensity and other parameters of the screened exogenous pollution sources are input into the simulation software. At the same time, the meteorological conditions (such as wind speed, wind direction, temperature, etc.) and terrain conditions (such as elevation, slope, etc.) of the cultivated land area to be analyzed are input. Run simulation: Run the simulation software to obtain the diffusion and deposition of pollutants in the cultivated land area to be analyzed, and filter out the pollution sources outside the cultivated land area to be analyzed.

[0069] In some embodiments of the present application, the cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas, including:

[0070] All ranges of soil background values ​​in the cultivated land area to be analyzed are counted, and the intervals of soil background values ​​are determined according to all ranges of soil background values. Adjacent areas are divided into the same grid according to the intervals of soil background values, so that the cultivated land area to be analyzed is gridded to obtain multiple grid cultivated land areas.

[0071] In this embodiment, the regions with adjacent positions and similar soil background values ​​(within the interval) are divided into the same grid to complete the processing of all positions of the cultivated land area to be analyzed. All ranges are used to determine the interval of soil background values. All ranges of different lengths correspond to different intervals. Generally speaking, the longer the range, the larger the corresponding interval.

[0072] Step S103, matching the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantifying the contribution of the pollution sources to the cadmium content in each grid cultivated land area, calculating the soil foreground value of each grid cultivated land area according to the cadmium content information, and setting the actual cadmium content threshold of each grid cultivated land area based on the soil foreground value.

[0073] In this embodiment, the pollution source is matched with multiple grid cultivated land areas, and the contribution of the pollution source to the cadmium content of each grid cultivated land area is quantified, which can be achieved through multiple regression analysis or machine learning models. The soil prospect value represents the cadmium content of each grid cultivated land area most of the time, so as to set an actual cadmium content threshold.

[0074] In some embodiments of the present application, the soil prospect value of each grid cultivated land area is calculated based on the cadmium content information, including:

[0075] According to the soil cadmium content and the crop cadmium content, the cadmium content change curves corresponding to the soil cadmium content and the crop cadmium content are established respectively, and the frequently appearing cadmium content interval is found in the cadmium content change curve, recorded as the frequent cadmium content interval, and the maximum cadmium content is found within a preset range at both ends of the frequent cadmium content interval, recorded as the relative maximum cadmium content;

[0076] The soil prospect value of the grid cultivated land area is determined based on the frequent cadmium content intervals and the maximum relative cadmium content of both soil cadmium content and crop cadmium content;

[0077]

[0078] Among them, Q i is the soil prospect value of the ith grid cultivated land area, α1 and α2 are the weights of soil cadmium content and crop cadmium content, respectively, and W1 i is the median of the frequent cadmium content interval of soil cadmium content in the i-th grid cultivated land area, W2 i is the median of the frequent cadmium content interval of crops in the i-th grid cultivated land area, maxW1 i is the maximum relative cadmium content of soil cadmium content in the i-th grid cultivated land area, maxW2 i is the maximum relative cadmium content of crops in the i-th grid cultivated land area, k i is the preset constant for the ith grid cultivated land area.

[0079] In this embodiment, the maximum cadmium content is found within a preset range at both ends of the frequent cadmium content interval. The range size of this endpoint can be dynamically adjusted according to actual conditions, all of which fall within the protection scope of this application.

[0080] In this embodiment, Represents the correction of the maximum relative cadmium content to the median in the frequent cadmium content range.

[0081] Step S104, constructing a cadmium content prediction model through the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators, and determine the cadmium pollution risk according to the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability indicators.

[0082] In this embodiment, the cadmium content prediction model combines multiple scales, including the pollution source scale, grid location scale, time scale, etc., to predict the cadmium content at multiple scales. The predicted value of cadmium content is converted into a cadmium bioavailability index. Bioavailability refers to the ability of cadmium in soil to be absorbed and utilized by organisms. Even if the total concentration of cadmium in the soil is high, if its bioavailability is low, the actual harm to organisms may be relatively small.

[0083] The conversion evaluation of cadmium bioavailability indicators is carried out based on the following data.

[0084] Soil physical and chemical properties data: including soil pH value, organic matter content, soil texture (such as the proportion of sand, loam, and clay), cation exchange capacity, etc. These data have an important influence on the form, stability, and bioavailability of cadmium in the soil.

[0085] Pollution source data: Understanding the type, intensity, distance from the soil, and emission history of the pollution source will help assess the contribution of the pollution source to soil cadmium contamination.

[0086] Historical monitoring data: If there are long-term soil cadmium pollution monitoring data in the area, these data can be used to build a time series model to predict future trends in cadmium pollution and changes in bioavailability.

[0087] Land use and crop information: Understand the land use patterns in the area (such as farmland, forest land, construction land, etc.) and the main types of crops grown, because different land use patterns and crops have different abilities to absorb and accumulate cadmium.

[0088] In some embodiments of the present application, a cadmium content prediction model is constructed by using the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, including:

[0089] Collect and preprocess the activity information of pollution sources, the contribution of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, extract relevant features from the data, and normalize the features;

[0090] The features are divided into training sets and test sets, and the cadmium content prediction model is constructed using the training sets and test sets.

[0091] In some embodiments of the present application, the cadmium pollution risk is determined according to the predicted cadmium content value, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index of the grid cultivated land area, including:

[0092]

[0093] Among them, L is the cadmium pollution risk level, β1 and β2 are the risk weights of the difference between the predicted cadmium content and the actual cadmium content threshold, and the risk weights of the difference between the predicted cadmium content and the standard cadmium content threshold, respectively. is the predicted value of cadmium content, G1 is the actual cadmium content threshold, G2 is the standard cadmium content threshold, τ is the cadmium bioavailability index, a is the preset constant, b is the cadmium pollution risk constant, and [] is the rounding symbol.

[0094] In this embodiment, the standard cadmium content threshold is a hard value promulgated by the national standard, and the actual cadmium content threshold is a threshold set according to the previous conditions of the grid cultivated land area. The cadmium content here refers to the cadmium content in the soil. It represents the correction of the two differences by the cadmium bioeffectiveness index. The predicted cadmium content is greater than the standard cadmium content threshold, and the predicted cadmium content is greater than the actual cadmium content threshold, indicating that the cadmium pollution risk is relatively large. The detailed cadmium pollution risk level is then set according to the specific difference size.

[0095] Step S105, mapping the cadmium pollution risk corresponding to each grid cultivated land area to the grid cultivated land area in the cultivated land area to be analyzed through GIS software, so as to visualize the cadmium pollution risk.

[0096] It should be noted that the corresponding relationship involved in the above scheme can be obtained based on historical experience or related mathematical models, both of which fall within the scope of protection of this application.

[0097] Compared with the prior art, the present invention has the following beneficial effects:

[0098] 1. Based on the location information and previous cadmium content information, a cadmium content distribution map of the cultivated land area to be analyzed is constructed to provide a solid foundation for subsequent pollution source identification and grid processing, thereby improving the reliability of the prediction.

[0099] 2. The cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas. The soil in different situations is gridded to improve the adaptability of the prediction and accurately predict the cadmium pollution risk of each grid.

[0100] 3. Calculate the soil prospect value of each grid cultivated land area based on the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area. Determine the cadmium pollution risk based on the predicted cadmium content of the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index. This will improve the accuracy and adaptability of the prediction of cadmium pollution risk in cultivated land, ensure accurate monitoring of cadmium pollution risk in cultivated land, and facilitate the subsequent targeted adoption of control measures.

[0101] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0102] Correspondingly, this application also provides a multi-scale prediction system for cadmium pollution risk in cultivated land, such as Figure 2 As shown, including,

[0103] A construction module is used to obtain the location information and the previous cadmium content information of the cultivated land area to be analyzed, and to construct a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and the previous cadmium content information, obtain the activity information in the cultivated land area to be analyzed, and match the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed;

[0104] A grid module is used to construct a set of pollution sources to be selected based on the activity information within the surrounding area of ​​the cultivated land area to be analyzed, analyze the cadmium content distribution map to screen out pollution sources outside the cultivated land area to be analyzed from the set of pollution sources to be selected, determine the soil background value within the cultivated land area to be analyzed, and grid the cultivated land area to be analyzed according to the soil background value to obtain multiple grid cultivated land areas;

[0105] A setting module is used to match the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantify the contribution of the pollution sources to the cadmium content of each grid cultivated land area, calculate the soil prospect value of each grid cultivated land area according to the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area based on the soil prospect value;

[0106] The risk module is used to construct a cadmium content prediction model based on the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators, and determine the cadmium pollution risk based on the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index;

[0107] The display module is used to map the cadmium pollution risk corresponding to each grid cultivated land area to the grid cultivated land area within the cultivated land area to be analyzed through GIS software, so as to visualize the cadmium pollution risk.

[0108] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of a preferred implementation scenario, and the modules or processes in the accompanying drawings are not necessarily required for implementing the present invention.

[0109] Those skilled in the art will appreciate that the modules in the system in the implementation scenario can be distributed in the system of the implementation scenario according to the implementation scenario description, or can be changed accordingly and located in one or more systems different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple submodules.

[0110] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A multi-scale prediction method for cadmium pollution risk in cultivated land, characterized in that: include, Obtaining location information and past cadmium content information of the cultivated land area to be analyzed, and constructing a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and past cadmium content information, obtaining activity information in the cultivated land area to be analyzed, and matching the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed; A set of candidate pollution sources is constructed based on the activity information within the surrounding area of ​​the cultivated land area to be analyzed, and the cadmium content distribution map is analyzed to screen out pollution sources outside the cultivated land area to be analyzed from the set of candidate pollution sources, and the soil background value within the cultivated land area to be analyzed is determined. The cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas; Match the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantify the contribution of the pollution sources to the cadmium content of each grid cultivated land area, calculate the soil prospect value of each grid cultivated land area based on the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area based on the soil prospect value; A cadmium content prediction model is constructed through the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators. The cadmium pollution risk is determined according to the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index; Through GIS software, the cadmium pollution risk corresponding to each grid cultivated land area is mapped to the grid cultivated land area within the cultivated land area to be analyzed, so as to visualize the cadmium pollution risk.

2. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 1, characterized in that: And based on the location information and the previous cadmium content information, a cadmium content distribution map of the cultivated land area to be analyzed is constructed, including: The cadmium content information includes the cadmium content in soil and the cadmium content in crops. A location map of the cultivated land to be analyzed is established according to the location information of the cultivated land area to be analyzed. The cadmium content in soil and the cadmium content in crops are mapped to corresponding positions on the location map of the cultivated land to be analyzed. The cultivated land area to be analyzed is divided into known cultivated land areas and unknown cultivated land areas according to the mapping results on the location map of the cultivated land to be analyzed. The known cultivated land areas are areas supported by data on the cadmium content in soil and the cadmium content in crops, and the unknown cultivated land areas are areas without data on the cadmium content in soil and the cadmium content in crops. Determine the distances between known cultivated land areas, construct a semivariogram based on the soil cadmium content and crop cadmium content in the known cultivated land areas and the distances between the known cultivated land areas, generate cadmium content calibration values ​​based on the soil cadmium content and crop cadmium content in the known cultivated land areas surrounding the unknown cultivated land areas, and determine the affected range of the unknown cultivated land areas based on the cadmium content calibration values; The distance between each known cultivated land area and the unknown cultivated land area within the affected range of the unknown cultivated land area is calculated, and the influence of each known cultivated land area on the unknown cultivated land area is determined by combining the semivariogram and the soil cadmium content and crop cadmium content of the known cultivated land areas, so as to predict the soil cadmium content and crop cadmium content in the unknown cultivated land area, and map the predicted values ​​to the unknown cultivated land area on the cultivated land location map to be analyzed, so as to generate the cadmium content distribution map of the cultivated land area to be analyzed.

3. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 1, characterized in that: Matching activity information with cadmium distribution maps to identify sources of contamination within the farmland area to be analyzed includes, The activity information is imported into the cadmium content distribution map, the cadmium content and activity impact range generated by the activity information are analyzed, and the pollution source is determined based on the degree of overlap between the cadmium content, activity impact range and the cadmium content distribution map, thereby determining the pollution source in the cultivated land area to be analyzed.

4. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 3, characterized in that: Analyze the cadmium content distribution map to screen out pollution sources outside the cultivated land area to be analyzed in the set of candidate pollution sources, including: In the cadmium content distribution map, the cadmium content generated by the pollution sources in the cultivated land area to be analyzed, the activity impact range and the regional cadmium content are compared to determine multiple sub-cultivated land areas, and the distance and cadmium pollution emission intensity between each candidate pollution source in the candidate pollution source set and the cultivated land area to be analyzed are evaluated. The natural meteorological data, distance and cadmium pollution emission intensity are input into the simulation model to simulate the pollution flow of the candidate pollution sources, and the pollution sources outside the cultivated land area to be analyzed are screened out according to the pollution flow between the sub-cultivated land areas and the candidate pollution sources.

5. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 1, characterized in that: The cultivated land area to be analyzed is gridded according to the soil background value to obtain multiple grid cultivated land areas. include, All ranges of soil background values ​​in the cultivated land area to be analyzed are counted, and the intervals of soil background values ​​are determined according to all ranges of soil background values. Adjacent areas are divided into the same grid according to the intervals of soil background values, so that the cultivated land area to be analyzed is gridded to obtain multiple grid cultivated land areas.

6. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 2, characterized in that: The soil prospect value of each grid cultivated land area is calculated based on the cadmium content information, including: According to the soil cadmium content and the crop cadmium content, the cadmium content change curves corresponding to the soil cadmium content and the crop cadmium content are established respectively, and the frequently appearing cadmium content interval is found in the cadmium content change curve, recorded as the frequent cadmium content interval, and the maximum cadmium content is found within a preset range at both ends of the frequent cadmium content interval, recorded as the relative maximum cadmium content; The soil prospect value of the grid cultivated land area is determined based on the frequent cadmium content intervals and the maximum relative cadmium content of both soil cadmium content and crop cadmium content; Among them, Q i is the soil prospect value of the ith grid cultivated land area, α1 and α2 are the weights of soil cadmium content and crop cadmium content, respectively, and W1 i is the median of the frequent cadmium content interval of soil cadmium content in the i-th grid cultivated land area, W2 i is the median of the frequent cadmium content interval of crops in the i-th grid cultivated land area, maxW1 i is the maximum relative cadmium content of soil cadmium content in the i-th grid cultivated land area, maxW2 i is the maximum relative cadmium content of crops in the i-th grid cultivated land area, k i is the preset constant for the ith grid cultivated land area.

7. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 1, characterized in that: The cadmium content prediction model is constructed through the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, including: Collect and preprocess the activity information of pollution sources, the contribution of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, extract relevant features from the data, and normalize the features; The features are divided into training sets and test sets, and the cadmium content prediction model is constructed using the training sets and test sets.

8. The multi-scale prediction method for cadmium pollution risk in cultivated land according to claim 1, characterized in that: The cadmium pollution risk is determined based on the predicted cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index, including: Among them, L is the cadmium pollution risk level, β1 and β2 are the risk weights of the difference between the predicted cadmium content and the actual cadmium content threshold, and the risk weights of the difference between the predicted cadmium content and the standard cadmium content threshold, respectively. is the predicted value of cadmium content, G1 is the actual cadmium content threshold, G2 is the standard cadmium content threshold, τ is the cadmium bioavailability index, a is the preset constant, b is the cadmium pollution risk constant, and [] is the rounding symbol.

9. A multi-scale prediction system for cadmium pollution risk in cultivated land, characterized in that: include, A construction module is used to obtain the location information and the previous cadmium content information of the cultivated land area to be analyzed, and to construct a cadmium content distribution map of the cultivated land area to be analyzed based on the location information and the previous cadmium content information, obtain the activity information in the cultivated land area to be analyzed, and match the activity information with the cadmium content distribution map to determine the pollution source in the cultivated land area to be analyzed; A grid module is used to construct a set of pollution sources to be selected based on the activity information within the surrounding area of ​​the cultivated land area to be analyzed, analyze the cadmium content distribution map to screen out pollution sources outside the cultivated land area to be analyzed from the set of pollution sources to be selected, determine the soil background value within the cultivated land area to be analyzed, and grid the cultivated land area to be analyzed according to the soil background value to obtain multiple grid cultivated land areas; A setting module is used to match the pollution sources within the cultivated land area to be analyzed and the pollution sources outside the cultivated land area to be analyzed with multiple grid cultivated land areas, and quantify the contribution of the pollution sources to the cadmium content of each grid cultivated land area, calculate the soil prospect value of each grid cultivated land area according to the cadmium content information, and set the actual cadmium content threshold of each grid cultivated land area based on the soil prospect value; The risk module is used to construct a cadmium content prediction model based on the activity information of pollution sources, the contribution relationship of pollution sources to the cadmium content of each grid cultivated land area, the cadmium content of the grid cultivated land area, soil information and climate information, so as to obtain the predicted values ​​of cadmium content in different grid cultivated land areas, and convert the predicted values ​​of cadmium content into cadmium bioavailability indicators, and determine the cadmium pollution risk based on the predicted values ​​of cadmium content in the grid cultivated land area, the actual cadmium content threshold, the standard cadmium content threshold and the cadmium bioavailability index; The display module is used to map the cadmium pollution risk corresponding to each grid cultivated land area to the grid cultivated land area within the cultivated land area to be analyzed through GIS software, so as to visualize the cadmium pollution risk.

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