A natural selenium-rich soil quality grade evaluation system and method

Abstract

This invention relates to a system and method for evaluating the quality grade of naturally selenium-rich land. The system includes: a data acquisition and analysis module for acquiring multi-source data of the area to be evaluated; a selenium-rich land discrimination module for determining whether land is naturally selenium-rich based on total selenium content and soil pH value; a comprehensive evaluation index module for constructing a comprehensive evaluation index system; a weight determination module for calculating the weight of each evaluation index in the comprehensive evaluation index system; a quality grade calculation module for calculating the membership degree of evaluation indicators at each index layer in the comprehensive evaluation index module; a grade division module for calculating the comprehensive quality index of each evaluation unit using an additive method; and a visualization module for integrating the evaluation thematic map with the geographic base map to obtain a quality grade evaluation map. This invention enables quantitative model calculation and spatial visualization representation of the quality grade of naturally selenium-rich land.

Description

Technical Field

[0001] This invention relates to the fields of agricultural information technology and natural resource management. In particular, it relates to a system and method for evaluating the quality of naturally selenium-rich land. Background Technology

[0002] Naturally selenium-rich land refers to soil with a natural selenium content of 0.3–3.0 mg / kg and heavy metal content not exceeding the screening value for agricultural land pollution risk. It is hailed as a "limited edition gift from Earth." Selenium is an essential trace element for the human body, and selenium-rich agricultural products are of great significance for improving human health. Naturally selenium-rich land is a valuable resource for producing selenium-rich agricultural products, and it has significant effects on improving immunity, anti-oxidation, and preventing Keshan disease and cancer. Since 2021, the Geological Society of China has issued the "Management Measures for the Identification and Labeling of Naturally Selenium-Rich Land" and formulated relevant standards such as the "Delineation and Labeling of Naturally Selenium-Rich Land (DZ / T 0380-2021)". Soil selenium content, heavy metal content, fertility status, and irrigation water quality are important standards for evaluating whether land is naturally selenium-rich. Since the implementation of the standards, the Geological Society of China has certified approximately 115 naturally selenium-rich land plots, covering a total area of ​​approximately 3 million mu (approximately 200,000 hectares), through four rounds of centralized certification. These plots have become core carriers for local governments to build "selenium-rich brands" and promote rural revitalization.

[0003] However, current technologies still have many problems and shortcomings in comprehensively evaluating naturally selenium-rich land. On the one hand, current evaluations of selenium-rich land often rely on simple judgments of a few chemical indicators, neglecting the impact of soil physical indicators (such as bulk density, texture, and site conditions) on land quality. They also lack sufficient understanding of the integrity and complexity of the ecosystem, making it difficult to comprehensively and accurately reflect the quality status of naturally selenium-rich land. On the other hand, existing evaluation systems only focus on soil selenium content, ignoring the bioavailability of selenium and the suitability of the land for agricultural production. Furthermore, with changes in agricultural production methods, the overuse of chemical fertilizers and pesticides, soil acidification, and nutrient loss pose serious challenges to the quality of selenium-rich land.

[0004] How to design a comprehensive evaluation system that can systematically, scientifically, and quantitatively evaluate naturally selenium-rich land and provide precise guidance for its graded and classified utilization is an urgent problem to be solved. Summary of the Invention

[0005] This invention provides a method for evaluating the quality grade of naturally selenium-rich land, in order to solve the problem that current evaluation methods for naturally selenium-rich land are simple, have single indicators, and are difficult to comprehensively and accurately reflect the quality grade status.

[0006] To achieve the above objectives, in a first aspect, the present invention relates to a natural selenium-rich land quality grading system, comprising: a data acquisition and analysis module for acquiring multi-source data of the area to be evaluated, wherein the multi-source data includes land physical attribute data, soil chemical attribute data, and land management data;

[0007] The selenium-rich land identification module is used to screen the heavy metal content in the obtained soil chemical attribute data based on the screening values ​​specified in the preset standard, and to determine whether the screened data is natural selenium-rich land based on the total selenium content and soil pH value.

[0008] The comprehensive evaluation index module is used to store the data processed by the data acquisition and analysis module and to construct a comprehensive evaluation index system.

[0009] The weight determination module is used to calculate the weight of each evaluation indicator in the comprehensive evaluation index system using the analytic hierarchy process (AHP).

[0010] The quality grade calculation module is used to calculate the membership degree of the evaluation indicators of each indicator layer in the comprehensive evaluation index module using the fuzzy comprehensive evaluation method.

[0011] The grading module is used to calculate the comprehensive quality index of each evaluation unit based on the weight and membership degree of each evaluation indicator using the cumulative method.

[0012] The visualization module is used to merge adjacent evaluation units of the same level according to the comprehensive quality index of each evaluation unit and the pre-set quality level standards, and use different labels to represent different quality levels to obtain an evaluation thematic map, which is then integrated with the geographic base map to obtain a quality level evaluation map.

[0013] To achieve the above objectives, in a second aspect, the present invention relates to a method for evaluating the quality grade of naturally selenium-rich land, comprising: S100, determining evaluation units based on the planning of the area to be evaluated;

[0014] S200. Determine the comprehensive evaluation index of natural selenium-rich land based on environmental factors and geological information of the area to be evaluated, wherein the comprehensive evaluation index includes soil physical property data, soil chemical property data, and land management data;

[0015] S300, Various types of data or measurements of the comprehensive evaluation index described in S200 obtained through laboratory testing or collection;

[0016] S400. Based on the screening values ​​specified in the preset specifications, the heavy metal content in the soil chemical attribute data mentioned in step S300 is screened, and the screened data is determined to be natural selenium-rich land based on the total selenium content and soil pH value.

[0017] Based on land physical attribute data, soil chemical attribute data, and land management data, the S500 method determines the grade of naturally selenium-rich land and generates a visual evaluation grade map.

[0018] The present invention relates to a system and method for evaluating the quality grade of naturally selenium-rich land, which has the following advantages compared with the prior art:

[0019] This invention is the first to construct a comprehensive evaluation system covering four dimensions: physical properties, chemical properties, biological availability, and environmental suitability, overcoming the shortcomings of traditional methods that cannot fully and accurately reflect the quality status of naturally selenium-rich land.

[0020] The weights of the indicators are determined by a combination of subjective and objective weighting methods, which takes into account both expert experience and the inherent laws of the data, making the evaluation results more scientific and objective.

[0021] Through quantitative model calculations and spatial visualization, selenium-rich land parcels of different quality levels can be accurately identified, providing direct and efficient decision support for national land spatial planning, the layout of selenium-rich agricultural product industries, and precise management of land resources. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of a natural selenium-rich land quality grading system according to Embodiment 1 of the present invention;

[0023] Figure 2 The following is a flowchart of a method for evaluating the quality grade of naturally selenium-rich land in Embodiment 2 of the present invention. Figure 1 ;

[0024] Figure 3 This is a flowchart of a specific evaluation method for a natural selenium-rich land quality grade evaluation method in Embodiment 2 of the present invention;

[0025] Figure 4 This is a matrix diagram for constructing the quality grade evaluation of naturally selenium-rich land in Embodiment 1 of the present invention.

[0026] Figure 5 This is an equivalence evaluation diagram of the quality of naturally selenium-rich land, which is a method for evaluating the quality grade of naturally selenium-rich land in an embodiment of the present invention. Detailed Implementation

[0027] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0028] Example 1

[0029] This invention relates to a system for evaluating the quality of naturally selenium-rich land, such as... Figure 1 As shown, it includes: a data acquisition and analysis module 61, a selenium-rich land identification module 62, a comprehensive evaluation index module 63, a weight determination module 64, a quality grade calculation module 65, a grade classification module 66, and a visualization module 67.

[0030] The data acquisition and analysis module 61 is used to acquire multi-source data of the area to be evaluated, including land physical attribute data, soil chemical attribute data and land management data.

[0031] The selenium-rich land identification module 62 is used to screen the heavy metal content in the obtained soil chemical attribute data based on the screening values ​​specified in the preset specifications, and to determine whether the screened data is natural selenium-rich land based on the total selenium content and soil pH value.

[0032] In this embodiment, the selenium-rich land identification module mainly relies on the total selenium content and heavy metal content. This module implements a veto system, meaning that the total selenium content and the content of each heavy metal must meet the following conditions:

[0033] In module 62 for identifying selenium-rich land, the criterion is that the total selenium content is ≥0.3 mg·kg when the soil pH is >7.5. -1， This indicates naturally selenium-rich soil; soil pH ≤ 7.5, total selenium content ≥ 0.4 mg·kg⁻¹ -1， This indicates that the land is naturally rich in selenium. The levels of heavy metals cadmium, mercury, arsenic, lead, and chromium are below the screening values ​​specified in the "Soil Environmental Quality Standard for Agricultural Land Soil Pollution Risk Control (GB15618)".

[0034] The comprehensive evaluation index module 63 is used to store the data processed by the data acquisition and analysis module and to construct a comprehensive evaluation index system.

[0035] In this embodiment, the evaluation index system in the comprehensive evaluation index module 63 includes land physical attribute data, soil chemical attribute data, and land management data.

[0036] Land physical attribute data mainly include topographic location, topsoil texture, biodiversity, salinity, soil bulk density, and effective soil layer thickness; among them, topographic location refers to small and medium-sized geomorphic units, which are determined by combining field practice and expert experience.

[0037] Among them, the topsoil texture is determined by the pipette method to measure the mechanical composition of the soil, and is divided into sandy soil, sandy loam, light loam, medium loam, heavy loam and clay.

[0038] Biodiversity is determined through field experience and expert knowledge, and is categorized as rich, moderate, and poor.

[0039] The degree of salinization is determined by the total amount of water-soluble salts, chloride salt content, sulfate content, and crop growth status. It is classified into four levels: none, mild, moderate, and severe.

[0040] The soil bulk density was determined by collecting a unit volume of undisturbed soil using the "ring cutter method". After drying the unit volume of undisturbed soil, the mass of the dried soil was divided by the volume of the soil before drying.

[0041] The effective soil layer thickness was measured on-site by excavating soil profiles.

[0042] Soil chemical property data should include at least the contents of organic matter, nitrogen, available potassium, available phosphorus, total selenium, available selenium, cadmium, chromium, mercury, lead, and arsenic; land management data should include at least irrigation capacity and drainage capacity.

[0043] Nitrogen and organic matter were determined in a qualified laboratory using volumetric methods (VOL).

[0044] Available phosphorus and readily available potassium were determined in a qualified laboratory using inductively coupled plasma atomic emission spectrometry (ICP-OES).

[0045] Among them, cadmium, chromium and lead were determined in the laboratory using inductively coupled plasma mass spectrometry (ICP-MS).

[0046] Arsenic, mercury, total selenium, and available selenium were determined in the laboratory using atomic fluorescence spectrometry (AFS).

[0047] The pH value was determined in the laboratory using the potentiometry (ISE) method.

[0048] Land management data includes at least irrigation and drainage capacity. Irrigation capacity is determined through field surveys and categorized as fully met, met, basically met, and unmet. Drainage capacity is also determined through field surveys and categorized as fully met, met, basically met, and unmet.

[0049] Preferably, the comprehensive evaluation index module includes the target layer of selenium-rich land quality grade, and the criterion layer of site conditions, physicochemical properties, nutrient status, selenium bioavailability, and farmland management. The criterion layer is further divided into several index layers.

[0050] Site conditions include three indicator layers: topographic location, biodiversity, and effective soil layer thickness.

[0051] Among them, the physicochemical properties include four index layers: topsoil texture, soil bulk density, degree of salinization, and pH value.

[0052] The nutrient status includes four indicator layers: organic matter, total nitrogen, available phosphorus, and available potassium.

[0053] Among them, selenium bioavailability is mainly represented by one indicator layer: effective selenium content.

[0054] Farmland management includes two indicator layers: irrigation capacity and drainage capacity.

[0055] The weight determination module 64 is used to calculate the weights of each evaluation indicator in the comprehensive evaluation index system using the analytic hierarchy process.

[0056] In this preferred embodiment, the weight determination module 64 calculates the weights of the 14 indicator layers in the comprehensive evaluation index module using the analytic hierarchy process (AHP), specifically including:

[0057] A hierarchical model was established, consisting of three levels: the target level, the criteria level, and the indicator level, representing the quality of selenium-rich land. The criteria level includes at least: site conditions, physicochemical properties, nutrient status, selenium bioavailability, and farmland management. The indicator level includes at least: topographic location indicator, biodiversity indicator, effective soil layer thickness indicator, topsoil texture indicator, soil bulk density indicator, salinization degree indicator, pH value indicator, organic matter indicator, total nitrogen indicator, available phosphorus indicator, available potassium indicator, selenium bioavailability indicator, irrigation capacity indicator, and drainage capacity indicator. Based on expert judgment, a 1-9 scale was used to determine the importance of each criterion level to the target level through pairwise comparisons between elements in the criteria level, and the weights of each indicator level were calculated using a product method.

[0058] The quality grade calculation module 65 is used to calculate the membership degree of the evaluation indicators of each indicator layer in the comprehensive evaluation index module using the fuzzy comprehensive evaluation method.

[0059] In this embodiment, preferably, the quality grade calculation module calculates the membership degree of the 14 index layers in the comprehensive evaluation index library module using the fuzzy comprehensive evaluation method.

[0060] In the quality grade calculation module 65, the Delphi method is used to directly give the membership degree of qualitative conceptual evaluation indicators.

[0061] The grading module 66 is used to calculate the comprehensive quality index of each evaluation unit based on the weight and membership degree of each evaluation indicator using the cumulative method.

[0062] In the grading module 66, the formula for calculating the comprehensive quality index of each evaluation unit using the cumulative method is: IFI=Σ(Fi×Ci), where: IFI is the comprehensive quality index, Fi is the membership degree of the i-th evaluation indicator, Ci is the combined weight of the i-th evaluation indicator, and the summation in the formula is the sum of the products of the membership degrees and combined weights of the 1 to m evaluation indicators, where i takes the value of an integer from 1 to m, m is the total number of evaluation indicators in the evaluation unit, and m is greater than or equal to 14.

[0063] The visualization module 67 is used to merge adjacent evaluation units of the same level according to the comprehensive quality index of each evaluation unit and the pre-set quality level standards, and use different labels to represent different quality levels to obtain an evaluation thematic map, which is then integrated with the geographic base map to obtain a quality level evaluation map.

[0064] Example 2

[0065] A method for evaluating the quality grade of naturally selenium-rich land is implemented based on the natural selenium-rich land quality grade evaluation system in Example 1 above. Please refer to [link / reference]. Figure 2-5 This includes the following steps:

[0066] S100. Determine the evaluation unit based on the planning of the area to be evaluated.

[0067] In this embodiment, the evaluation unit in step S100 is the land use status type map patch from the Third National Land Survey.

[0068] S200. Based on the environmental factors and geological information of the area to be evaluated, determine the comprehensive evaluation indicators for naturally selenium-rich land. The comprehensive evaluation indicators include soil physical property data, soil chemical property data, and land management data.

[0069] In step S200, environmental factors and geological information include hydrothermal conditions, parent rock type, and element enrichment patterns.

[0070] S300, various types of data or measurements of the S200 comprehensive evaluation index obtained through laboratory testing or collection.

[0071] In this embodiment, step S300 specifically includes:

[0072] After collecting and analyzing the numerical index elements determined in step S200, extreme value processing is performed to remove maximum and minimum values, resulting in values ​​with extreme values ​​removed; and / or

[0073] Field verification is conducted based on the conceptual indicators determined in step S200.

[0074] S400. Based on the screening values ​​specified in the preset specifications, the heavy metal content in the soil chemical attribute data in step S300 is screened, and the screened data is used to determine whether it is natural selenium-rich land based on the total selenium content and soil pH value.

[0075] In this embodiment, the heavy metal content in the soil chemical attribute data in step S300 is screened based on the screening values ​​specified in the preset specifications. Specifically, the content data of five heavy metal elements, namely cadmium, mercury, arsenic, lead and chromium, in the soil chemical attribute data obtained in step S300 are screened based on the preset specifications.

[0076] In this embodiment, step 400 specifically includes:

[0077] S401. Analyze the total selenium content of the soil obtained in step S300 to determine the lower limit of the total selenium content evaluation.

[0078] S402. Analyze the content of five heavy metal elements in the soil, namely cadmium, mercury, arsenic, lead and chromium, obtained in step S300 to determine the degree of soil cleanliness.

[0079] S403. Based on step S401, plots with total selenium content higher than the evaluation lower limit and heavy metal content lower than the screening value are identified as naturally selenium-rich land.

[0080] Based on land physical attribute data, soil chemical attribute data, and land management data, the S500 method determines the grade of naturally selenium-rich land and generates a visual evaluation grade map.

[0081] In this embodiment, step 500 specifically includes:

[0082] S501. Based on the evaluation indicators determined in step S200, calculate the weight of each indicator layer in the comprehensive evaluation indicators using the analytic hierarchy process, which has a total of 14 indicator layers.

[0083] S502. Based on the evaluation indicators determined in step S200, calculate the membership degree of each indicator layer in the comprehensive evaluation indicator module using the fuzzy comprehensive evaluation method.

[0084] S503. Based on the weights determined in step S501 and the membership degrees calculated in step S502, the comprehensive quality index of each evaluation unit is calculated using the cumulative method.

[0085] S504 is used to merge adjacent evaluation units of the same level according to the comprehensive quality index of each evaluation unit and the pre-set quality level standards, use different labels to represent different quality levels, obtain an evaluation thematic map, integrate it with the geographic base map to obtain a quality level evaluation map, and use ArcGIS software to generate a visualized quality level evaluation map.

[0086] Specifically, step S501, calculating the weights using the analytic hierarchy process, includes steps S5011 to S5014:

[0087] S5011. Establish a hierarchical structure model, divided into three levels: selenium-rich land quality as the target layer A, the criterion layer, and the indicator layer. Among them, the criterion layer B includes at least: site condition criterion layer B1, physicochemical property criterion layer B2, nutrient status criterion layer B3, selenium bioavailability criterion layer B4, and farmland management criterion layer B5. The criterion layer is further divided into 14 indicator layers, including topographic location indicator layer, biodiversity indicator layer, effective soil layer thickness indicator layer, topsoil texture indicator layer, soil bulk density indicator layer, salinization degree indicator layer, pH value indicator layer, organic matter indicator layer, total nitrogen indicator layer, available phosphorus indicator layer, available potassium indicator layer, selenium bioavailability indicator layer, irrigation capacity indicator layer, and drainage capacity indicator layer.

[0088] S5012. Construct a judgment matrix. Based on the hierarchical structure model established in S5011 and expert survey judgment, use the 1 to 9 scale method to compare each element of the criterion layer pairwise to determine the importance of each criterion layer to the target layer.

[0089] S5013. Calculate the weights of each evaluation index using the sum-product method. Normalize the judgment matrix constructed in S5012 by column to obtain the normalized matrix. Calculate the arithmetic mean of the normalized matrix by row to obtain the weight vector composed of the weights of each evaluation index.

[0090] S5014. Construct the judgment matrix based on S5012 and calculate the weights of each evaluation index in S5013 to calculate the maximum eigenvalue λ. max The consistency test is performed using the formula CR = CI / RI; where CR represents the consistency ratio, CI represents the consistency index, and RI represents the random consistency index. RI is related to the matrix order and can be found online. When CR < 0.1, the matrix is ​​considered to have passed the consistency test. The calculation formula is: CI = (λ max -n) / (n-1), where n is the number of criteria layer factors;

[0091] Specifically, step S502, calculating the membership degree of each sub-layer of the comprehensive evaluation index module using the fuzzy comprehensive evaluation method, includes steps S5021 to S5023:

[0092] S5021. Based on the hierarchical structure model established in S5011, establish the membership function of selenium-rich land quality and evaluation indicators.

[0093] S5022. The membership function of numerical evaluation index is determined by combining the Delphi method and the membership function method.

[0094] S5023. The Delphi method is used to directly give the membership degree of qualitative conceptual evaluation indicators.

[0095] In step S503, the formula for calculating the comprehensive quality index of each evaluation unit by the cumulative method is: IFI=Σ(Fi×Ci), where: IFI is the comprehensive quality index, Fi is the membership degree of the i-th evaluation indicator, Ci is the combined weight of the i-th evaluation indicator, i takes the value of an integer from 1 to m, m is the total number of evaluation indicators in the evaluation unit, and m is greater than or equal to 14.

[0096] Specifically, step S504 involves generating a visualized evaluation level chart, which includes steps S5041 to S5043:

[0097] S5041. Based on the land use status map of the third national land survey, select major settlements, transportation routes, water systems, boundary lines and their corresponding annotations, and then edit and generate the geographical base map for each evaluation theme map.

[0098] S5042. Based on the comprehensive quality of each evaluation unit calculated in step S503, adjacent evaluation units of the same level are merged according to the pre-set quality level standards, and different quality levels are represented by different marks to obtain the evaluation thematic map.

[0099] S5043. Integrate the geographic base map generated in step S5041 and the evaluation thematic map generated in step S5042 to obtain the quality level evaluation map.

[0100] In one instance, such as Figure 3-4 As shown, taking a county in Southwest China as an example, the specific implementation method is described. The method includes the following steps:

[0101] Step 1: Determine the evaluation area in accordance with the requirements of the local government's planning of agricultural demonstration parks, combined with regional geological data, data from the Third National Land Survey, and data from the Third National Soil Census.

[0102] Regional geological data generally includes 1:50,000 regional geological surveys, 1:200,000 geochemical surveys, 1:50,000 hydrogeological surveys, and remote sensing geological surveys. Data from the Third National Land Survey includes current land use status, land ownership, area of ​​each land category, and arable land slope classification. Data from the Third National Soil Census includes soil type, nutrient level, quality level, production potential, and the current status, distribution, and severity of soil acidification, salinization, desertification, erosion, infertility, and pollution problems.

[0103] Step 2: Collect data from the Third National Land Survey of a certain county, using land use status type patches as evaluation units.

[0104] Step 3: Based on the evaluation standards for naturally selenium-rich land, the evaluation indicators are determined as land physical attributes, land chemical attributes, and land management attributes.

[0105] Land physical attribute data mainly include topographic location, topsoil texture, biodiversity, salinization level, soil bulk density, and effective soil layer thickness.

[0106] Among them, the topographic location is determined by combining actual field conditions and expert experience.

[0107] Among them, the topsoil texture is determined by the pipette method to measure the mechanical composition of the soil, and is divided into sandy soil, sandy loam, light loam, medium loam, heavy loam and clay.

[0108] Biodiversity is determined through field experience and expert knowledge, and is categorized as rich, moderate, and poor.

[0109] The degree of salinization is determined by the total amount of water-soluble salts, chloride salt content, sulfate content, and crop growth status. It is classified into four levels: none, mild, moderate, and severe.

[0110] The soil bulk density was determined by collecting a unit volume of undisturbed soil using the "ring cutter method". After drying the unit volume of undisturbed soil, the mass of the dried soil was divided by the volume of the soil before drying.

[0111] The effective soil layer thickness was measured on-site by excavating soil profiles.

[0112] Soil chemical property data mainly include the content of elements such as organic matter, nitrogen, available potassium, available phosphorus, total selenium, available selenium, cadmium, chromium, mercury, lead, arsenic, and pH value.

[0113] Soil chemical property data were obtained through field sampling and analysis and testing in qualified laboratories. The relevant technical requirements mainly refer to the "Specifications for Multi-Objective Regional Geochemical Survey (DZ / T 0258-2014)" and the "Technical Requirements for Sample Analysis of Ecological Geochemical Evaluation (Trial) (DD2005-03)".

[0114] Land management data mainly includes irrigation capacity and drainage capacity.

[0115] Irrigation capacity was determined through on-site surveys and categorized as fully met, met, basically met, and unmet.

[0116] The drainage capacity is determined through on-site investigation and is categorized as fully met, met, basically met, and unmet.

[0117] Step 4: Extreme value processing of measurement data for numerical index elements.

[0118] Specifically, the soil chemical properties measured in step 3 are obtained by collecting and analyzing field samples. Then, the measured element values ​​are used to iteratively remove extremely high and low values ​​by using the relationship between the logarithmic mean and standard deviation, thus completing the extreme value processing of the data.

[0119] Specifically, the extreme value processing method is as follows: the original measured values ​​of each element are processed by the "X±3S" continuous iterative elimination method (X is the logarithmic mean of the original data of the element, and S is the standard deviation) until there are no more outlier data (extremely high and extremely low values) to be eliminated, that is, all data are distributed between (X-3S, X+3S), which can be expressed as X-3S < analytical value < X+3S.

[0120] Step 5: Assign values ​​to the evaluation units.

[0121] Specifically, using ArcGIS software, conventional methods were employed to associate various data types with each plot. Conceptual indicators were assigned values ​​to each map patch based on actual field survey data; for map patches without data, a point-to-area method was used to associate them with each plot. Numerical indicators were assigned values ​​to each map patch using the extreme value processing data from step 4; for map patches without data, spatial interpolation was used to associate them with each plot.

[0122] Step 6: Identification of naturally selenium-rich land.

[0123] Specifically, based on the attributes of each plot obtained in step 5, plots with total selenium content higher than the evaluation lower limit and heavy metal content lower than the screening value are selected as naturally selenium-rich land.

[0124] Specifically, the lower limit for evaluating the total selenium content in the plot is as follows: when the soil pH is >7.5, the total selenium content is ≥0.3 mg·kg⁻¹; when the soil pH is ≤7.5, the total selenium content is ≥0.4 mg·kg⁻¹.

[0125] Specifically, the levels of five heavy metals—cadmium, mercury, arsenic, lead, and chromium—in the plot were all below the screening values ​​specified in the "Soil Environmental Quality Standard for Agricultural Land Soil Pollution Risk Control (GB 15618)".

[0126] Step 7: Based on the evaluation indicators determined in Step 3, calculate the weights of the 14 indicator layers using the Analytic Hierarchy Process (AHP).

[0127] Specifically, a hierarchical model is established, divided into three levels: selenium-rich land quality as the target level A, the criteria level, and the indicator level. Among them, the criteria level B includes at least: site condition criteria level B1, physicochemical property criteria level B2, nutrient status criteria level B3, selenium bioavailability criteria level B4, and farmland management criteria level B5. The criteria level is further divided into 14 indicator levels, including topographic location indicator level, biodiversity indicator level, effective soil layer thickness indicator level, topsoil texture indicator level, soil bulk density indicator level, salinization degree indicator level, pH value indicator level, organic matter indicator level, total nitrogen indicator level, available phosphorus indicator level, available potassium indicator level, selenium bioavailability indicator level, irrigation capacity indicator level, and drainage capacity indicator level.

[0128] Specifically, based on the hierarchical structure model and expert surveys, a 1-9 scale method is used to determine the importance of each criterion layer to the target layer by comparing each element pairwise.

[0129] Specifically, the constructed judgment matrix is ​​normalized column-wise to obtain a normalized matrix. The arithmetic mean of the normalized matrix is ​​then calculated row-wise to obtain the weight vector.

[0130] Specifically, the maximum eigenvalue λmax is calculated based on the constructed judgment matrix and the weights of each element, and a consistency test is performed using the formula CR=CI / RI. In this formula, CR represents the consistency ratio, CI represents the consistency index, and RI represents the random consistency index. When CR < 0.1, the judgment matrix passes the consistency test. The calculation formula is: CI=(λmax-n) / (n-1), where n is the number of factors in the criterion layer, and RI is related to the matrix order and can be found online.

[0131] The weights calculated by a certain county in step 7 are shown in the table below:

[0132]

[0133] Step 8: Determine the membership functions of numerical evaluation indicators using a combination of the Delphi method and the membership function method. The Delphi method directly provides the membership degrees of qualitative conceptual evaluation indicators.

[0134] Specifically, the membership functions of numerical indicators for evaluating the quality of cultivated land in Southwest China can be used as a reference, and the membership degrees of conceptual indicators in Southwest China are shown in Table 2.

[0135]

[0136] Specifically, the Delphi method is used to directly give the membership degree of qualitative conceptual evaluation indicators.

[0137] Specifically, the membership function of the numerical indicators for evaluating the quality grade of cultivated land in Southwest China can be used as a reference. The membership degree of the numerical indicators in Southwest China is shown in Table 3.

[0138]

[0139] Step 9: Based on the weights determined in Step 7 and the membership degrees calculated in Step 8, calculate the comprehensive quality index of each evaluation unit using the cumulative method.

[0140] Specifically, the cumulative method is used to calculate the comprehensive quality index of each evaluation unit. The formula is: IFI=Σ(Fi×Ci), where: IFI is the comprehensive quality index, Fi is the membership degree of the i-th evaluation factor, and Ci is the combined weight of the i-th evaluation factor.

[0141] The calculated comprehensive index of natural selenium-rich land quality in a certain county is between 0.65 and 0.87. According to the preset quality grading standards (Table 4), the quality grade of natural selenium-rich land in a certain county is between Grade 1 and Grade 19.

[0142]

[0143] Step 10: Based on the land use status map of the Third National Land Survey, select major settlements, transportation routes, water systems, boundary lines, etc., and their corresponding annotations, and then edit and generate the base map of geographical elements for each thematic map.

[0144] Step 11: Based on the comprehensive quality of each evaluation unit calculated in Step 9, adjacent evaluation units of the same level are merged according to the pre-set quality level standards. Different colors are used to represent different quality levels, with green representing high-level quality and transitioning from green to yellow to red to low-level quality, thus obtaining the evaluation thematic map.

[0145] Step 12: Integrate the geographic base map generated in Step 10 and the evaluation thematic map generated in Step 11 to obtain the quality level evaluation map.

[0146] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0147] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A quality grading system for naturally selenium-rich land, characterized in that, include: The data acquisition and analysis module is used to acquire multi-source data of the area to be evaluated, including land physical attribute data, soil chemical attribute data, and land management data. The selenium-rich land identification module is used to screen the heavy metal content in the obtained soil chemical attribute data based on the screening values ​​specified in the preset standard, and to determine whether the screened data is natural selenium-rich land based on the total selenium content and soil pH value. The comprehensive evaluation index module is used to store the data processed by the data acquisition and analysis module and to construct a comprehensive evaluation index system. The weight determination module is used to calculate the weight of each evaluation indicator in the comprehensive evaluation index system using the analytic hierarchy process (AHP). The quality grade calculation module is used to calculate the membership degree of the evaluation indicators of each indicator layer in the comprehensive evaluation index module using the fuzzy comprehensive evaluation method. The grading module is used to calculate the comprehensive quality index of each evaluation unit based on the weight and membership degree of each evaluation indicator using the cumulative method. The visualization module is used to merge adjacent evaluation units of the same level according to the comprehensive quality index of each evaluation unit and the pre-set quality level standards, and use different labels to represent different quality levels to obtain an evaluation thematic map, which is then integrated with the geographic base map to obtain a quality level evaluation map.

2. The natural selenium-rich land quality grading system according to claim 1, characterized in that, The comprehensive evaluation index module includes an evaluation index system comprising land physical attribute data, soil chemical attribute data, and land management data. The land physical attribute data mainly includes topographic location, topsoil texture, biodiversity, salinization degree, soil bulk density, and effective soil layer thickness. The soil chemical attribute data includes at least the content of organic matter, nitrogen, available potassium, available phosphorus, total selenium, available selenium, cadmium, chromium, mercury, lead, and arsenic. The land management data includes at least irrigation capacity and drainage capacity.

3. The natural selenium-rich land quality grading system according to claim 1, characterized in that, In the selenium-rich land identification module, the judgment criterion is that the total selenium content is ≥0.3 mg·kg when the soil pH is >7.

5. -1， This indicates naturally selenium-rich soil; soil pH ≤ 7.5, total selenium content ≥ 0.4 mg·kg⁻¹ -1， This is naturally selenium-rich land; The weight determination module specifically includes: A hierarchical model was established, consisting of three levels: the target level, the criteria level, and the indicator level, representing the quality of selenium-rich land. The criteria level includes at least: site conditions, physicochemical properties, nutrient status, selenium bioavailability, and farmland management. The indicator level includes at least: topographic location indicator, biodiversity indicator, effective soil layer thickness indicator, topsoil texture indicator, soil bulk density indicator, salinization degree indicator, pH value indicator, organic matter indicator, total nitrogen indicator, available phosphorus indicator, available potassium indicator, selenium bioavailability indicator, irrigation capacity indicator, and drainage capacity indicator. Based on expert judgment, a 1-9 scale was used to determine the importance of each criterion level to the target level through pairwise comparisons between elements in the criteria level, and the weights of each indicator level were calculated using a product method. In the quality grade calculation module, the Delphi method is used to directly give the membership degree of qualitative conceptual evaluation indicators; In the grade classification module, the formula for calculating the comprehensive quality index of each evaluation unit by the cumulative method is: IFI=Σ(Fi×Ci), where: IFI is the comprehensive quality index, Fi is the membership degree of the i-th evaluation indicator, Ci is the combined weight of the i-th evaluation indicator, i takes the value of an integer from 1 to m, m is the total number of evaluation indicators in the evaluation unit, and m is greater than or equal to 14.

4. A method for evaluating the quality grade of naturally selenium-rich land, characterized in that, include: S100. Determine the evaluation unit based on the planning of the area to be evaluated; S200. Determine the comprehensive evaluation index of natural selenium-rich land based on environmental factors and geological information of the area to be evaluated, wherein the comprehensive evaluation index includes soil physical property data, soil chemical property data, and land management data; S300, Various types of data or measurements of the comprehensive evaluation index described in S200 obtained through laboratory testing or collection; S400. Based on the screening values ​​specified in the preset specifications, the heavy metal content in the soil chemical attribute data mentioned in step S300 is screened, and the screened data is determined to be natural selenium-rich land based on the total selenium content and soil pH value. Based on land physical attribute data, soil chemical attribute data, and land management data, the S500 method determines the grade of naturally selenium-rich land and generates a visual evaluation grade map.

5. The method for evaluating the quality grade of naturally selenium-rich land according to claim 1, characterized in that, The heavy metal content in the soil chemical attribute data obtained in step S300 is screened based on the screening values ​​specified in the preset specifications. Specifically, the content data of five heavy metal elements, namely cadmium, mercury, arsenic, lead and chromium, in the soil chemical attribute data obtained in step S300 are screened based on the preset specifications.

6. The method for evaluating the quality grade of naturally selenium-rich land according to claim 1, characterized in that, The evaluation unit mentioned in step S100 is the land use status type map patch from the Third National Land Survey; In step S200, the environmental factors and geological information include hydrothermal conditions, parent rock type, and element enrichment patterns.

7. The method for evaluating the quality grade of naturally selenium-rich land according to claim 5, characterized in that, Step S300 is as follows: After collecting and analyzing the numerical index elements determined in step S200, extreme value processing is performed to remove maximum and minimum values, resulting in values ​​with extreme values ​​removed; and / or Field verification is conducted based on the conceptual indicators determined in step S200.

8. The method for evaluating the quality grade of naturally selenium-rich land according to claim 4, characterized in that, Step 400 specifically includes: S401. Analyze the total selenium content of the soil obtained in step S300 to determine the lower limit of the total selenium content evaluation. S402. Analyze the content of five heavy metal elements in the soil, namely cadmium, mercury, arsenic, lead and chromium, obtained in step S300 to determine the degree of soil cleanliness. S403. Based on step S401, plots with total selenium content higher than the evaluation lower limit and heavy metal content lower than the screening value are identified as naturally selenium-rich land.

9. The method for evaluating the quality grade of naturally selenium-rich land according to claim 4, characterized in that, Step 500 specifically includes: S501. Based on the evaluation index determined in step S200, calculate the weight of each index layer in the comprehensive evaluation index using the analytic hierarchy process. S502. Based on the evaluation indicators determined in step S200, calculate the membership degree of each indicator layer in the comprehensive evaluation indicator module using the fuzzy comprehensive evaluation method. S503. Based on the weights determined in step S501 and the membership degrees calculated in S502, calculate the comprehensive quality index of each evaluation unit using the cumulative method. S504 is used to merge adjacent evaluation units of the same level according to the comprehensive quality index of each evaluation unit and the pre-set quality level standards, use different labels to represent different quality levels, obtain an evaluation thematic map, integrate it with the geographic base map to obtain a quality level evaluation map, and use ArcGIS software to generate a visualized quality level evaluation map.

10. The method for evaluating the quality grade of naturally selenium-rich land according to claim 4, characterized in that, Step S501, calculating the weights using the analytic hierarchy process, specifically includes steps S5011 to S5014: S5011. Establish a hierarchical structure model, divided into three levels: the target level, the criterion level, and the indicator level for selenium-rich land quality. The criterion level includes at least the following: site conditions, physicochemical properties, nutrient status, selenium bioavailability, and farmland management. The indicator level includes at least the following: topographic location indicator level, biodiversity indicator level, effective soil layer thickness indicator level, topsoil texture indicator level, soil bulk density indicator level, salinization degree indicator level, pH value indicator level, organic matter indicator level, total nitrogen indicator level, available phosphorus indicator level, available potassium indicator level, selenium bioavailability indicator level, irrigation capacity indicator level, and drainage capacity indicator level. S5012. Construct a judgment matrix. Based on the hierarchical structure model established in S5011 and expert survey judgment, use the 1 to 9 scale method to compare each element of the criterion layer pairwise to determine the importance of each criterion layer to the target layer. S5013. The weights of each evaluation index are calculated using the sum-product method. The judgment matrix constructed in S5012 is normalized column-wise to obtain the normalized matrix. The arithmetic mean of the normalized matrix is ​​calculated row-wise to obtain the weight vector composed of the weights of each evaluation index. S5014. Construct the judgment matrix based on S5012 and calculate the weights of each evaluation index in S5013 to calculate the maximum eigenvalue λ. max The consistency test is performed using the formula CR = CI / RI; where CR represents the consistency ratio, CI represents the consistency index, and RI represents the random consistency index. RI is related to the matrix order. When CR < 0.1, the matrix is ​​considered to have passed the consistency test. The calculation formula is: CI = (λ max -n) / (n-1), where n is the number of criteria layer factors; Step S502, calculating the membership degree of each index sub-layer in the comprehensive evaluation index module using the fuzzy comprehensive evaluation method, specifically includes steps S5021 to S5023: S5021. Based on the hierarchical structure model established in S5011, establish the membership function of selenium-rich land quality and evaluation indicators. S5022. The membership function of numerical evaluation index is determined by combining the Delphi method and the membership function method. S5023. The Delphi method is used to directly give the membership degree of qualitative conceptual evaluation indicators. In step S503, the formula for calculating the comprehensive quality index of each evaluation unit by the cumulative method is: IFI=Σ(Fi×Ci), where: IFI is the comprehensive quality index, Fi is the membership degree of the i-th evaluation indicator, Ci is the combined weight of the i-th evaluation indicator, i takes the value of an integer from 1 to m, m is the total number of evaluation indicators in the evaluation unit, and m is greater than or equal to 14. Step S504 generates a visualized rating chart, specifically including steps S5041 to S5043: S5041. Based on the land use status map of the third national land survey, select major settlements, transportation routes, water systems, boundary lines and their corresponding annotations, and then edit and generate the geographical base map for each evaluation theme map. S5042. Based on the comprehensive quality of each evaluation unit calculated in step S503, adjacent evaluation units of the same level are merged according to the pre-set quality level standards, and different quality levels are represented by different marks to obtain the evaluation thematic map. S5043. Integrate the geographic base map generated in step S5041 and the evaluation thematic map generated in step S5042 to obtain the quality level evaluation map.

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