Error evaluation method and system for soil geochemical monitoring data

Abstract

This application relates to the field of geochemistry technology, specifically disclosing a method and system for error assessment of soil geochemical monitoring data. The method includes: determining monitoring indicators for the soil in a sampling area; repeatedly sampling multiple sampling points in the sampling area to obtain corresponding test samples; analyzing the test samples based on the monitoring indicators to obtain monitoring data; and evaluating the monitoring data using an error assessment model to determine the error analysis results. This application enables the analysis and evaluation of error factors and changes in monitoring indicators in the monitoring data, which helps improve the accuracy of the monitoring data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geochemistry, and particularly relates to a geochemical monitoring data error evaluation method and system. BACKGROUND

[0002] The existing soil geochemical monitoring method is to obtain the monitoring indexes and chemical element detection values of the sampling points through sampling points sampling and laboratory detection of the soil in the sampling area.

[0003] However, the monitoring data needs to be determined through manual sampling, laboratory detection and other operation processes, so that the detection data error caused by manual operation factors is introduced, the monitoring data changes in the case where the detection indexes do not change, and the accuracy of the monitoring data is affected. Therefore, how to analyze the error factors of the monitoring data becomes a problem to be solved by technical personnel. SUMMARY

[0004] In order to improve the accuracy of the soil geochemical monitoring data and quantitatively analyze the error factors, the present application provides a soil geochemical monitoring data error evaluation method and system.

[0005] According to one aspect of the present application, a soil geochemical monitoring data error evaluation method is provided, comprising:

[0006] determining the monitoring indexes of the soil in the sampling area;

[0007] repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples;

[0008] detecting and analyzing the detection samples based on the monitoring indexes to obtain monitoring data;

[0009] evaluating the monitoring data by using an error evaluation model to determine error analysis results.

[0010] Through the above technical solution, after the monitoring indexes of the soil in the sampling area are determined, multiple sampling points are repeatedly sampled to obtain corresponding detection samples, the monitoring data is obtained after the detection samples are detected and analyzed, and the error analysis results are determined by using the error evaluation model. The error factors of the monitoring data and the change values of the monitoring indexes are analyzed and evaluated by the detection analysis and the error evaluation model, which can improve the accuracy of the monitoring data.

[0011] Preferably, repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples comprises:

[0012] sampling multiple sampling points in the sampling area to obtain a first detection sample set, and the first detection sample set comprises multiple first detection samples;

[0013] The second detection sample set is obtained by repeatedly sampling a plurality of sampling points, and the second detection sample set includes a plurality of second detection samples; wherein the first detection sample and the second detection sample of the same sampling point form a first detection pair.

[0014] Through the above technical solution, the plurality of sampling points are repeatedly sampled, and the first detection sample and the second detection sample of the same sampling point form a first detection pair, which can make the detection sample cover a plurality of sampling points in the sampling area, and provide data support for subsequent detection sample analysis.

[0015] Preferably, the monitoring data includes a monitoring error value, the detection sample is detected and analyzed based on the monitoring index, and the monitoring data is obtained, including:

[0016] A plurality of first detection pairs are obtained;

[0017] At least p first detection pairs are detected to obtain a first detection value set corresponding to the monitoring index;

[0018] The monitoring error value is determined based on the first detection value set;

[0019] The calculation formula of the monitoring error value is: St 2 represents the monitoring error value, C i,1 represents the detection value of the first detection sample at the sampling point i, C i,2 represents the detection value of the second detection sample at the sampling point i, i∈[1,p], and p is the number of repeated detections.

[0020] Through the above technical solution, at least p detection pairs are detected to obtain a corresponding first detection value set, and the monitoring error value is determined based on the first detection value set, thereby providing a calculation method of the monitoring error value, and the monitoring error value of the monitoring data can be quantitatively analyzed.

[0021] Preferably, the monitoring data includes a monitoring error value and a detection error value, and after the monitoring error value is determined based on the detection value, the method further includes:

[0022] The detection sample j is divided into a first sub-detection sample and a second sub-detection sample, and the first sub-detection sample and the second sub-detection sample form a second detection pair;

[0023] At least q second detection pairs are detected to obtain a second detection value set corresponding to the monitoring index;

[0024] The detection error value is determined based on the second detection value set;

[0025] The calculation formula of the detection error value is: Sa 2 represents the detection error value, C j ′,1 Ci represents the detection value of the first sub-detection sample in the second detection pair j, j∈[1, q], q is the detection times of the second detection pair. j,2 Cj represents the detection value of the second sub-detection sample in the second detection pair j, j∈[1, q], q is the detection times of the second detection pair.

[0026] Through the above technical solution, the first sub-detection sample and the second sub-detection sample are obtained by sampling the monitoring sample j, the first sub-detection sample and the second sub-detection sample form a first detection pair, at least q second detection pairs are detected, the detection error value is determined based on the obtained second detection value set, the detection error of the monitoring data can be quantitatively analyzed, and then the influence of the error of the detection part on the monitoring data is determined.

[0027] Preferably, the monitoring data includes the monitoring error value, the detection error value and the sampling error value.

[0028] The calculation formula of the sampling error value is: Ss 2 = St 2 -Sa 2

[0029] Ss 2 represents the sampling error value.

[0030] Through the above technical solution, the sampling error value of the monitoring data can be quantitatively analyzed by using the calculation formula of the sampling error value, and then the influence of the error of the sampling part on the monitoring data is determined.

[0031] Preferably, the monitoring data includes the monitoring error value, the detection error value and the sampling error value, and the error analysis result is determined by evaluating the monitoring data by using the error evaluation model, including:

[0032] The detection error contribution value is determined by using the detection error contribution formula;

[0033] The sampling error contribution value is determined by using the sampling error contribution formula;

[0034] The detection error contribution formula is: The sampling error contribution formula is: t1 represents the detection error contribution value, and t2 represents the sampling error contribution value.

[0035] Through the above technical solution, the detection error contribution value can be determined by using the detection error contribution formula, and the sampling error contribution value can be determined by using the sampling error contribution formula. The corresponding measures are taken according to the size of different error factors to improve the accuracy of the monitoring data.

[0036] Preferably, the error analysis result is determined by evaluating the monitoring data by using the error evaluation model, including:

[0037] obtaining a detection value C of the first detection sample in the detection pair a a,1 (x,y) and a detection value C of the second detection sample a,2 (x,y);

[0038] obtaining a detection value C of the first detection sample a,1 (x,y) and a detection value C of the second detection sample a,2 (x,y);

[0039] The normal distribution model N(0, St) is used to determine whether the monitoring index of the sampling point has a significant change.

[0040] Through the above technical solution, the normal distribution model N(0, St) is used to determine whether the monitoring index has a significant change. For example, under 95% confidence, the confidence interval of the difference ΔC(x, y) is [ΔC(x, y)-1.96St, ΔC(x, y)+1.96St]. When 0 is located in the confidence interval, the monitoring index has no significant change, otherwise it has a significant change. Thus, the change of the monitoring index is determined, and the confidence level can also take other values such as 99% and 98%. The coefficient 1.96 in the confidence interval is replaced according to the standard normal distribution function.

[0041] Preferably, before determining the monitoring index of the sampling area soil, the method comprises: determining the range of the sampling area based on the land type;

[0042] The land types in the sampling area are the same.

[0043] Through the above technical solution, the range of the sampling area is determined based on the land type, that is, the land types in the sampling area are the same. Thus, the error of the monitoring data of the sampling area with the same land type is supported.

[0044] Preferably, after the error evaluation model is used to evaluate the monitoring data to determine the error analysis result, the method comprises:

[0045] A monitoring data table corresponding to the mapping of the land type is established based on the monitoring data;

[0046] The sampling data of the sampling area with different land types is evaluated and analyzed by using the monitoring data table.

[0047] Through the above technical solution, the monitoring data table corresponding to the mapping of the land type is established based on the monitoring data, and the sampling data of the sampling area with different land types is evaluated and analyzed by using the monitoring data table. In actual operation, the characteristics of the monitoring index are divided into regions. The influence range of different factors on the error of the monitoring data can be determined according to the land type, which is simple and efficient.

[0048] According to another aspect of the present application, a soil geochemical monitoring data error evaluation system is provided, comprising:

[0049] A monitoring index acquisition module is configured to determine the monitoring index of the soil in the sampling area.

[0050] A detection sample collection module is configured to repeatedly sample multiple sampling points in the sampling area to obtain corresponding detection samples.

[0051] A monitoring data acquisition module is configured to detect and analyze the detection samples based on the monitoring index to obtain monitoring data.

[0052] An analysis module is configured to evaluate the monitoring data using an error evaluation model to determine an error analysis result.

[0053] Through the above technical solution, after the monitoring index acquisition module determines the monitoring index of the soil in the sampling area, the detection sample collection module repeatedly samples multiple sampling points to obtain corresponding detection samples, the monitoring data acquisition module obtains monitoring data after detecting and analyzing the detection samples, and the analysis module evaluates the error analysis result using an error evaluation model. By analyzing and evaluating the error factors of the monitoring data and the change value of the monitoring index using the detection analysis and the error evaluation model, the accuracy of the monitoring data can be improved.

[0054] In summary, the present application has the following technical effects:

[0055] 1. By analyzing and evaluating the error factors of the monitoring data and the change value of the monitoring index using the detection analysis and the error evaluation model, the accuracy of the monitoring data can be improved.

[0056] 2. The detection error contribution formula can be used to determine the detection error contribution value, and the sampling error contribution formula can be used to determine the sampling error contribution value. Different error factors can be determined, and corresponding measures can be taken to improve the accuracy of the monitoring data.

[0057] 3. The normal distribution model N(0, St) is used to determine whether the monitoring index has changed significantly. Under 95% confidence, the confidence interval of the difference AC(x, y) is [AC(x, y)-1.96St, AC(x, y)+1.96St]. When 0 is within the confidence interval, the monitoring index has not changed significantly, otherwise it has changed significantly, and the change of the monitoring index is determined.

[0058] 4. Based on the monitoring data, a monitoring data table corresponding to the land type mapping is established, and the sampling data of different land type sampling areas are evaluated and analyzed by using the monitoring data table. In actual operation, regional division can be carried out according to the characteristics of the monitoring index, and the error influence range of different factors on the monitoring data can be determined through the land type, which is simple and efficient. BRIEF DESCRIPTION OF DRAWINGS

[0059] Figure 1 The flowchart of the soil geochemical monitoring data error evaluation method in the application is shown.

[0060] Figure 2 The flowchart of the method for repeatedly sampling a plurality of sampling points to obtain corresponding detection samples in the application is shown.

[0061] Figure 3 The flowchart of the method for determining the detection error value in the application is shown.

[0062] Figure 4 The flowchart of the method for evaluating the monitoring data by using the error evaluation model to determine the error analysis result in the application is shown.

[0063] Figure 5 The structural diagram of a soil geochemical monitoring data error evaluation system provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0064] The following makes the purpose, technical scheme and advantages of the application clearer and more apparent. The following further details the application by means of the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application.

[0065] The following combines the drawings and embodiments to further detail the application. Figures 1-5 The application is further detailed.

[0066] Reference is made to Figure 1 The application provides a soil geochemical monitoring data error evaluation method, which comprises:

[0067] S102, determining the monitoring index of the soil in the sampling area.

[0068] The monitoring index herein includes soil basic properties, nutrient element content, harmful element content and a certain chemical extraction state of elements, wherein the soil basic properties include pH value and organic matter; the nutrient elements include nitrogen element and phosphorus element; the harmful elements include cadmium and mercury; and the healthy elements include iodine and selenium.

[0069] S104, repeatedly sampling a plurality of sampling points in the sampling area to obtain corresponding detection samples.

[0070] Wherein, here can be repeated sampling of multiple sampling points in units of sampling points, or repeated sampling of multiple sampling points in units of sampling times of sampling points.

[0071] In an embodiment, the sampling index of each sampling is the same, and common sampling indexes include the size of the sampling sample, the time range of the sampling (day and night), and the weather of the sampling (sunny and rainy), so as to avoid the influence of the difference of the sampling environment on the monitoring data, and further affect the analysis result of the sampling sample.

[0072] S106, detecting and analyzing the detection sample based on the monitoring index to obtain monitoring data.

[0073] S108, using an error evaluation model to evaluate the monitoring data to determine an error analysis result.

[0074] The embodiment of the present application determines the monitoring index of the soil in the sampling area, repeatedly samples multiple sampling points to obtain corresponding detection samples, detects and analyzes the detection samples to obtain monitoring data, and uses an error evaluation model to evaluate and determine an error analysis result. Through the detection analysis and the error evaluation model, the error factors of the monitoring data and the change value of the monitoring index are analyzed and evaluated, which can improve the accuracy of the monitoring data.

[0075] In an embodiment, repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples includes: sampling multiple sampling points in the sampling area to obtain a first detection sample set, and the first detection sample set includes multiple first detection samples.

[0076] Repetitively sampling multiple sampling points to obtain a second detection sample set, and the second detection sample set includes multiple second detection samples; wherein, the first detection sample and the second detection sample of the same sampling point form a first detection pair.

[0077] In the case where the monitoring index in the sampling area does not change, the repeated collection of the sampling points is performed, and the sampling points are randomly distributed in space, so as to prevent the regular sampling from affecting the monitoring data sampling, and also make the monitoring data universal.

[0078] The embodiment of the present application repeatedly samples multiple sampling points, and forms a first detection pair by the first detection sample and the second detection sample of the same sampling point, which can cover multiple sampling points in the sampling area, and provide data support for subsequent detection sample analysis.

[0079] Figure 2 The flowchart of the method for repeatedly sampling multiple sampling points to obtain corresponding detection samples in the present application is shown.

[0080] Referring to Figure 2The monitoring data includes a monitoring error value, the detection sample is analyzed based on the monitoring index, and the monitoring data is obtained, and the monitoring data includes:

[0081] S202, a plurality of first detection pairs are obtained;

[0082] S204, at least p first detection pairs are detected to obtain a first detection value set corresponding to the monitoring index.

[0083] In an embodiment, p is a positive integer not less than 15, and 15 here is artificially set, and can be flexibly set according to actual conditions. Through the above scheme, the data obtained by too few detection times can be avoided to have contingency.

[0084] S206, determining a monitoring error value based on the first detection value set;

[0085] The calculation formula of the monitoring error value is: St 2 represents the monitoring error value, C i,1 represents the detection value of the first detection sample at the sampling point i, C i,2 represents the detection value of the second detection sample at the sampling point i, i∈[1, p], and p is the number of repeated detections.

[0086] The embodiment of the application detects at least p detection pairs to obtain a corresponding first detection value set, and determines a monitoring error value based on the first detection value set, thereby providing a calculation method of the monitoring error value, and the monitoring error value of the monitoring data can be quantitatively analyzed.

[0087] Figure 3 The flowchart of the method for determining the detection error value in the application is shown.

[0088] Referring to Figure 3 The monitoring data includes a monitoring error value and a detection error value, and after the monitoring error value is determined based on the detection value, the following is further included:

[0089] S302, the detection sample j is divided to obtain a first sub-detection sample and a second sub-detection sample, and the first sub-detection sample and the second sub-detection sample form a second detection pair.

[0090] Since the previous sample at the same sampling point is destructive sampling, even if the later sampling is "at the same sampling point", it can only be a sample near the sampling point, thereby generating a sampling error, that is, a monitoring error caused by small-scale spatial variation in repeated sampling. The first sub-detection sample and the second detection sample obtained by dividing the detection sample j can avoid the influence of the sampling error caused by the above sampling problem on the detection value.

[0091] S304, detecting at least q second detection pairs to obtain a second detection value set corresponding to the monitoring index.

[0092] In an embodiment, q is a positive integer not less than 15, where 15 is artificially set, and can be flexibly set according to actual conditions. Through the above scheme, the data obtained by too few detection times can be avoided to have contingency.

[0093] S306, determining a detection error value based on the second detection value set;

[0094] wherein the calculation formula of the detection error value is: Sa 2 represents the detection error value, C j ′ ,1 represents the detection value of the first sub-detection sample in the second detection pair j, C j,2 represents the detection value of the second sub-detection sample in the second detection pair j, j∈[1, q], q is the detection number of the second detection pair.

[0095] The embodiment of the present application divides the monitoring sample j to obtain the first sub-detection sample and the second sub-detection sample, the first sub-detection sample and the second sub-detection sample form the first detection pair, and at least q second detection pairs are detected, and the detection error value is determined based on the obtained second detection value set. The detection error of the monitoring data can be quantitatively analyzed, and then the influence of the error of the detection part on the monitoring data is determined.

[0096] In an embodiment, the evaluation of the detection error value can be obtained by the sampling detection of the sampling area sampling point repeated sample, or the sample obtained by the previous investigation and the monitoring sample in the later period can be used.

[0097] In an embodiment, the monitoring data includes a monitoring error value, a detection error value and a sampling error value;

[0098] wherein the calculation formula of the sampling error value is: Ss 2 =St 2 -Sa 2

[0099] Ss 2 represents the sampling error value.

[0100] The present application separates the detection error and the sampling error from the monitoring error, and the calculation formula of the sampling error value can be used to quantitatively analyze the sampling error value of the monitoring data. The sampling error level that cannot be directly measured is derived, so that the separation of the monitoring error value, the detection error value and the sampling error value is realized, and then the influence of the error of the sampling part on the monitoring data is determined.

[0101] In an embodiment, the monitoring data comprises a monitoring error value, a detection error value and a sampling error value, the error evaluation model is used to evaluate the monitoring data to determine an error analysis result, which comprises:

[0102] A detection error contribution value is determined by using a detection error contribution formula.

[0103] A sampling error contribution value is determined by using a sampling error contribution formula.

[0104] The detection error contribution formula is: The sampling error contribution formula is: t1 represents the detection error contribution value, and t2 represents the sampling error contribution value.

[0105] The above embodiments can determine the detection error contribution value by using the detection error contribution formula, and determine the sampling error contribution value by using the sampling error contribution formula, and take corresponding measures according to the size of different error factors and sampling to improve the accuracy of the monitoring data.

[0106] Figure 4 The flowchart of the method for determining the error analysis result by using the error evaluation model to evaluate the monitoring data in the present application is shown.

[0107] Referring to Figure 4 , the error evaluation model is used to evaluate the monitoring data to determine an error analysis result, which comprises:

[0108] S402, obtaining a detection value C a,1 (x,y) of the first detection sample in the detection a and a detection value C a,2 (x,y) of the second detection sample;

[0109] S404, determining a difference value AC(x,y) of the detection value C a,1 (x,y) of the first detection sample and the detection value C a,2 (x,y) of the second detection sample;

[0110] The embodiments of the present application provide an evaluation method for monitoring error values in a sampling area, which can determine whether the soil geochemical element monitoring data has a real change by monitoring the error.

[0111] The embodiment of the present application uses the normal distribution model N(0, St) to determine whether the monitoring index has a significant change. Under 95% confidence, the confidence interval of the difference AC(x, y) is [AC(x, y)-1.96St, AC(x, y)+1.96St]. When 0 is located in the confidence interval, the monitoring index has no significant change, otherwise, the monitoring index has a significant change. The confidence can also take other values, such as 99%, 98%, etc. The coefficient 1.96 of the confidence interval is replaced according to the standard normal distribution function.

[0112] In an embodiment, before determining the monitoring index of the soil in the sampling area, the following is included: determining the range of the sampling area based on the land type;

[0113] The land type in the sampling area is the same.

[0114] Common land types include paddy fields, dry lands, wetlands, mountainous areas, grasslands, forests, etc.

[0115] The present application determines the range of the sampling area based on the land type, that is, the land type in the sampling area is the same, and thus sample support is provided for the error of the monitoring data of the sampling area of the same land type.

[0116] In an embodiment, after the error evaluation model is used to evaluate the monitoring data to determine the error analysis result, the following is included:

[0117] A monitoring data table corresponding to the mapping of the land type is established based on the monitoring data;

[0118] The sampling data of the sampling area of different land types is evaluated and analyzed using the monitoring data table.

[0119] The present application establishes a monitoring error value, a detection error value, and a sampling error value database corresponding to different land types based on the monitoring data table, and uses the monitoring data table to evaluate and analyze the sampling data of the sampling area of different land types. In actual operation, the characteristics of the monitoring index are divided into regions, and the influence range of different factors on the error of the monitoring data can be determined based on the land type, which is simple and efficient.

[0120] In the above Figures 1-4 embodiment, the error evaluation method of the soil geochemical monitoring data is described in detail. The error evaluation system of the soil geochemical monitoring data is described below through an embodiment.

[0121] Figure 5 FIG. 1 shows a structural schematic diagram of an error evaluation system of soil geochemical monitoring data according to an embodiment of the present application. As shown in FIG. 1, the error evaluation system of the soil geochemical monitoring data according to the embodiment of the present application includes: Figure 5 The error evaluation system of the soil geochemical monitoring data according to the embodiment of the present application includes:

[0122] The monitoring index acquisition module 51 is configured to determine the monitoring index of the soil in the sampling area.

[0123] The detection sample collection module 52 is configured to repeatedly sample a plurality of sampling points in the sampling area to obtain corresponding detection samples.

[0124] The monitoring data acquisition module 53 is configured to detect and analyze the detection samples based on the monitoring index to obtain monitoring data.

[0125] The analysis module 54 is configured to evaluate the monitoring data by using an error evaluation model to determine an error analysis result.

[0126] The implementation principle of the present application is as follows: after the monitoring index acquisition module 51 determines the monitoring index of the soil in the sampling area, the detection sample collection module 52 repeatedly samples a plurality of sampling points to obtain corresponding detection samples; the monitoring data acquisition module 53 detects and analyzes the detection samples to obtain monitoring data; and the analysis module 54 evaluates by using an error evaluation model to determine an error analysis result. Through the detection analysis and the error evaluation model, the error factors of the monitoring data and the change value of the monitoring index are analyzed and evaluated, so that the accuracy of the monitoring data can be improved.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described modules can refer to the corresponding process in the foregoing method embodiments, which will not be described herein.

[0128] Those skilled in the art can understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program codes.

[0129] The above are preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for error evaluation of soil geochemical monitoring data, characterized in that, The method comprises the following steps: determining a monitoring index of soil in a sampling area; repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples; the repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples comprises: sampling multiple sampling points in the sampling area to obtain a first detection sample set, the first detection sample set comprising multiple first detection samples; repeatedly sampling the multiple sampling points to obtain a second detection sample set, the second detection sample set comprising multiple second detection samples; wherein the first detection sample and the second detection sample of the same sampling point form a first detection pair; The detection sample is analyzed based on the monitoring indicators to obtain monitoring data; the monitoring data includes monitoring error value, detection error value, and sampling error value; the step of analyzing the detection sample based on the monitoring indicators to obtain monitoring data includes: obtaining multiple first detection pairs; and at least... The first detection pair is tested to obtain a first set of detection values ​​corresponding to the monitoring indicator; the monitoring error value is determined based on the first set of detection values; and the test samples are... The samples are divided to obtain a first sub-detection sample and a second sub-detection sample, which together form a second detection pair; at least... The second detection pair is tested to obtain a second set of detection values ​​corresponding to the monitoring index; the detection error value is determined based on the second set of detection values. The calculation formula of the monitoring error value is: ; The monitoring error value is represented by The detection value of the first detection sample at the sampling point The detection value of the second detection sample at the sampling point , , , The detection number of repetitions; the calculation formula of the detection error value is: ; The detection error value is represented by The detection value of the first sub-detection sample in the second detection pair The detection value of the second sub-detection sample in the second detection pair , , , The detection number of the second detection pair; the calculation formula of the sampling error value is: ; The sampling error value is represented by The monitoring data is evaluated by using an error evaluation model to determine an error analysis result; the evaluation of the monitoring data by using the error evaluation model to determine the error analysis result comprises: obtaining a detection value of a first detection sample in the detection pair a and a detection value of a second detection sample ; determining a difference value Δ of the detection value of the first detection sample and the detection value of the second detection sample ; and judging whether the monitoring index of the sampling point has a significant change by using a normal distribution model .

2. The error evaluation method of claim 1, wherein, the evaluating the monitoring data by using an error evaluation model to determine an error analysis result comprises: determining a detection error contribution value by using a detection error contribution formula; determining a sampling error contribution value by using a sampling error contribution formula; The detection error contribution formula is: The sampling error contribution formula is: ; represents the detection error contribution value, represents the sampling error contribution value.

3. The error evaluation method of claim 1, wherein, before the determining a monitoring index of soil in a sampling area, the method comprises the following steps: determining a sampling area range based on a land type; wherein the land type in the sampling area is the same.

4. The error evaluation method of claim 3, wherein, after the evaluating the monitoring data by using an error evaluation model to determine an error analysis result, the method comprises the following steps: establishing a monitoring data table corresponding to a mapping of the land type based on the monitoring data; evaluating and analyzing sampling data of sampling areas of different land types by using the monitoring data table.

5. A system for error evaluation of soil geochemical monitoring data, characterized by The method comprises the following steps: a monitoring index acquisition module for determining a monitoring index of soil in a sampling area; a detection sample collection module for repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples; the repeatedly sampling multiple sampling points in the sampling area to obtain corresponding detection samples comprises: sampling multiple sampling points in the sampling area to obtain a first detection sample set, the first detection sample set comprising multiple first detection samples; repeatedly sampling the multiple sampling points to obtain a second detection sample set, the second detection sample set comprising multiple second detection samples; wherein the first detection sample and the second detection sample of the same sampling point form a first detection pair; The monitoring data acquisition module is configured to perform detection analysis on the detection sample based on the monitoring index to obtain monitoring data, wherein the monitoring data comprises a monitoring error value, a detection error value and a sampling error value, and the monitoring data acquisition module comprises the following steps: acquiring a plurality of first detection pairs; performing detection on at least one first detection pair to obtain a first detection value set corresponding to the monitoring index; determining the monitoring error value based on the first detection value set; dividing the detection sample to obtain a first sub-detection sample and a second sub-detection sample, wherein the first sub-detection sample and the second sub-detection sample form a second detection pair; performing detection on at least one second detection pair to obtain a second detection value set corresponding to the monitoring index; and determining the detection error value based on the second detection value set. ​​​ The calculation formula of the monitoring error value is: ; The monitoring error value is represented by The detection value of the first detection sample at the sampling point is represented by The detection value of the second detection sample at the sampling point is represented by , The detection number of the second detection pair is represented by n; the calculation formula of the detection error value is: ; The detection error value is represented by The detection value of the first sub-detection sample in the second detection pair is represented by The detection value of the second sub-detection sample in the second detection pair is represented by , The detection number of the second detection pair is represented by n; the calculation formula of the sampling error value is: ; The sampling error value is represented by The analysis module is used to evaluate the monitoring data using an error assessment model to determine the error analysis results; the evaluation of the monitoring data using the error assessment model to determine the error analysis results includes: obtaining the detection value of the first detection sample in detection pair a. The detection value of the second test sample Determine the detection value of the first test sample. and the detection value of the second test sample The difference Δ Using the normal distribution model Determine whether the monitoring index at the sampling point has changed significantly.

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