A soil health evaluation method based on multiple ecological functions

Abstract

The application discloses a soil health evaluation method based on multiple ecological functions, and relates to the technical field of soil evaluation, which comprises the following steps: selecting a soil evaluation system, including soil health indexes, ecological conditions and ecological variation conditions of a sampling area, and performing weighted processing on the soil health indexes based on the ecological conditions to obtain first soil health indexes; performing standardization processing and principal component analysis on the original data of the first soil health indexes in sequence to generate second soil health indexes; performing weighted adjustment on the second soil health indexes based on the ecological variation conditions of the sampling area to generate third soil health indexes; performing calculation and analysis on the third soil health indexes to generate a soil quality classification index, and dividing the index into multiple grades; collecting soil samples and measuring actual values of the third soil health indexes, comparing the actual value sum with the soil quality classification index to obtain the soil health grade of the soil samples. The application provides a more scientific and comprehensive soil evaluation system.

Description

Technical Field

[0001] This invention relates to the field of soil assessment technology, and specifically to a method for soil health assessment based on multiple ecological functions. Background Technology

[0002] With the growing demand for global food security and sustainable agricultural development, the accurate assessment and management of soil quality has become particularly important. Against this backdrop, soil quality assessment technology has undergone a leapfrog development from the initial simple physicochemical analysis to large-scale soil monitoring using remote sensing technology and geographic information systems (GIS). In particular, the application of Global Navigation Satellite Systems (GNSS) in soil quality assessment has greatly improved the accuracy and efficiency of soil sample location. At the same time, by integrating soil physical, chemical, environmental and biological indicators, researchers and engineers are now able to more comprehensively assess soil health. However, despite continuous technological advancements, current soil quality assessment methods still face numerous challenges: existing soil quality assessment techniques often focus on measuring specific types of indicators, lacking a comprehensive assessment framework and failing to fully reflect the actual condition of the soil; furthermore, traditional methods are often overly simplistic in terms of data processing and assessment models, neglecting the complexity and dynamic changes in soil quality assessment; for example, no method has yet proposed adjusting the assessment model based on soil ecology (i.e., soil use function), soil type, regional characteristics, and soil buffering capacity, which often results in assessment results that cannot accurately guide the implementation of soil management and remediation measures. Summary of the Invention

[0003] To address the aforementioned shortcomings in existing technologies, this invention provides a soil health assessment method based on multiple ecological functions. This method solves the problem that existing technologies do not adjust the assessment model according to the soil's ecology, i.e., soil use function, soil type, regional characteristics, and soil buffering capacity, which often results in assessment results that cannot accurately guide the implementation of soil management and improvement measures.

[0004] To achieve the above-mentioned objectives, the technical solution adopted by this invention is: a soil health assessment method based on multiple ecological functions, comprising the following steps: S1: Select a soil evaluation system, which includes soil health indicators, ecological conditions and ecological variation conditions in the sampling area, and perform weighted processing on the soil health indicators based on the ecological conditions to obtain the first soil health indicator; S2: The raw data of the first soil health index are standardized and principal component analysis are performed sequentially to generate the second soil health index; S3: The second soil health index is weighted and adjusted based on the ecological variation conditions of the sampling area to generate the third soil health index; S4: Calculate and analyze the third soil health index to generate a soil quality classification index and classify the index into multiple levels; S5: Collect soil samples and measure the actual value of the third soil health index. Compare the sum of the actual values ​​with the soil quality classification index to obtain the soil health level of the soil sample.

[0005] Furthermore, the soil health indicators include indicators of soil ecological damage level, soil green product production potential, and soil buffering capacity under climate change.

[0006] Furthermore, the soil ecological damage index is obtained by weighted calculation based on soil microbial diversity, soil microbial nitrogen fixation functional genome expression, and soil pollutant comprehensive index.

[0007] Furthermore, the indicators of soil green product production potential include soil historical cultivation intensity indicators, effective soil layer thickness, topsoil thickness, soil maturity degree, soil texture, tilth, organic matter content, effective nutrient content, nutrient storage, water retention, permeability, and pH. The soil cultivation history intensity indicators include historical agricultural output, historical fertilizer application, historical pesticide use, and historical farmyard manure use.

[0008] Furthermore, the soil buffering capacity indicators under climate change include historical soil moisture content, historical groundwater level, historical annual average temperature change index, historical rainfall data, and the content of carbonates, bicarbonates, silicates, phosphates, and hydrogen phosphates in the soil.

[0009] Furthermore, the formula for calculating the soil quality classification index G is as follows: G=(Xpotential+Xbuffer)-Xdamage Among them, Xpotential is an indicator of the potential for producing green products from soil, Xbuffer is an indicator of soil buffering capacity under climate change, and Xdamage is an indicator of the degree of soil ecological damage.

[0010] Furthermore, the ecological conditions refer to the soil's use functions, including providing nutrients, retaining moisture, regulating climate, purifying water sources, and maintaining ecological balance. The weighting coefficients for soil health indicators under different ecological conditions are as follows: Nutritional information provided: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 2, and Xbuffer with a weighting factor of 0.5. To maintain moisture: Xdamage is calculated with a weighting factor of 0.5, Xpotential is calculated with a weighting factor of 0.5, and Xbuffer is calculated with a weighting factor of 2. Regulating climate and maintaining ecological balance: Xdamage is calculated with a weighting factor of 1, Xpotential is calculated with a weighting factor of 1, and Xbuffer is calculated with a weighting factor of 1. Water source purification: Xdamage has a weighting factor of 2, Xpotential has a weighting factor of 0.1, and Xbuffer has a weighting factor of 1.

[0011] Furthermore, the ecological variation conditions of the sampling area include the historical rainfall data of the sample collection area and the region where the sample is located. The sample collection area is divided into inland areas, heavy industrial areas, and coastal areas, with corresponding weighting rules as follows: Inland regions: Xdamage is calculated with a weighting factor of 0.5, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Heavy industrial areas: Xdamage is calculated with a weighting factor of 2, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Coastal areas: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 0.5, and Xbuffer with a weighting factor of 1. The annual rainfall in the sample area is divided into three levels: high, medium, and low. The weighting coefficients for each level calculated by Xpotential are 0.1, 0.5, and 1, respectively.

[0012] The beneficial effects of this invention are as follows: Compared with the prior art, this invention adds the calculation of health indicators under different ecological needs of soil to the existing soil health assessment methods. This step makes the soil quality assessment more scientific and comprehensive. By comprehensively considering soil fertility, soil buffering capacity, and the degree of heavy metal pollution in the soil, it can analyze soil quality in all aspects, thereby providing more accurate and detailed soil improvement suggestions. The characteristics of the sample collection area are introduced to improve the accuracy and reliability of the assessment. In particular, the annual rainfall of the sample collection area is used to adjust the calculation results, which not only enhances the accuracy of the assessment results, but also allows for flexible adjustments based on the specific climate changes in the soil's location, thereby ensuring that the assessment results can better guide the implementation of soil management and improvement measures. Attached Figure Description

[0013] Figure 1 This is a flowchart of a soil health assessment method based on multiple ecological functions.

[0014] Figure 2 This is a structural diagram of the soil health assessment index system.

[0015] Figure 3 Output a schematic diagram of soil health level zones. Detailed Implementation

[0016] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0017] like Figure 1 As shown, a soil health assessment method based on multiple ecological functions includes the following steps: S1: Select a soil evaluation system, which includes soil health indicators, ecological conditions and ecological variation conditions in the sampling area, and perform weighted processing on the soil health indicators based on the ecological conditions to obtain the first soil health indicator; The soil health indicators include soil ecological damage index (Xdamage), soil green product production potential index (Xpotential), and soil buffering capacity index under climate change index (Xbuffer).

[0018] The soil ecological damage index was obtained by weighted calculation based on soil microbial diversity, soil microbial nitrogen fixation functional genome expression, and soil pollutant comprehensive index.

[0019] The indicators for the production potential of green products from soil include soil historical cultivation intensity, effective soil layer thickness, topsoil thickness, soil maturity, soil texture, tilth, organic matter content, available nutrient content, nutrient storage, water retention, permeability, and pH. The soil cultivation history intensity indicators include historical agricultural output, historical fertilizer application, historical pesticide use, and historical farmyard manure use.

[0020] The soil buffering capacity indicators under climate change include historical soil moisture content, historical groundwater level, historical annual average temperature change index, historical rainfall data, and the content of carbonates, bicarbonates, silicates, phosphates, and hydrogen phosphates in the soil.

[0021] By comprehensively considering soil fertility, soil buffering capacity, and the degree of heavy metal pollution in the soil, soil quality can be analyzed in all aspects, thereby providing more accurate and detailed suggestions for soil improvement.

[0022] The ecological conditions refer to the soil's use functions, including providing nutrients, retaining moisture, regulating climate, purifying water sources, and maintaining ecological balance. The weighting coefficients for soil health indicators under different ecological conditions are as follows: Nutritional information provided: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 2, and Xbuffer with a weighting factor of 0.5. To maintain moisture: Xdamage is calculated with a weighting factor of 0.5, Xpotential is calculated with a weighting factor of 0.5, and Xbuffer is calculated with a weighting factor of 2. Regulating climate and maintaining ecological balance: Xdamage is calculated with a weighting factor of 1, Xpotential is calculated with a weighting factor of 1, and Xbuffer is calculated with a weighting factor of 1. Water source purification: Xdamage has a weighting factor of 2, Xpotential has a weighting factor of 0.1, and Xbuffer has a weighting factor of 1.

[0023] Soil plays different roles in different ecosystems. Traditional soil evaluation methods often use the same framework for evaluation and analysis, which leads to inaccurate soil quality assessment. This invention clarifies different ecological needs, making soil quality assessment more scientific and comprehensive.

[0024] In this embodiment, the soil evaluation system can be selected as the Cornell Soil Health Assessment System.

[0025] S2: The raw data of the first soil health index are standardized and principal component analysis are performed sequentially to generate the second soil health index; The standardization process is consistent with existing soil analysis methods. The raw data of the screened soil health indicators are standardized, and principal component analysis is performed on the standardized data. The indicators contained in the principal factors that meet the preset conditions are used as the second soil health evaluation indicators. The preset conditions are that the eigenvalues ​​of the principal factors obtained from the principal component analysis are greater than the first preset value, and the cumulative contribution rate of the principal factors is greater than the second preset value.

[0026] S3: The second soil health index is weighted and adjusted based on the ecological variation conditions of the sampling area to generate the third soil health index; The ecological variation conditions of the sampling area include the historical rainfall data of the sample collection area and the sample location. The sample collection area is divided into inland areas, heavy industrial areas, and coastal areas, with corresponding weighting rules as follows: Inland regions: Xdamage is calculated with a weighting factor of 0.5, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Heavy industrial areas: Xdamage is calculated with a weighting factor of 2, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Coastal areas: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 0.5, and Xbuffer with a weighting factor of 1. The annual rainfall in the sample area is divided into three levels: high, medium, and low. The weighting coefficients for Xpotential are 0.1, 0.5, and 1 for each level, respectively. Xdamage and Xbuffer do not have weighting coefficients in the annual rainfall data of the region.

[0027] Heavy metal pollution levels in soils of heavy industrial areas show an increasing trend, while soil salinity in coastal areas exhibits a gradual increase from the sea towards the seawall. Rainfall significantly impacts soil fertility retention. Incorporating the characteristics of the sample collection areas aims to improve the accuracy and reliability of the evaluation. In particular, incorporating annual rainfall data from the sample collection areas to adjust the calculation results not only enhances the precision of the evaluation but also allows for flexible adjustments based on the specific climate changes in the soil's location. This ensures that the evaluation results can better guide soil management and the implementation of remediation measures.

[0028] S4: Calculate and analyze the third soil health index to generate a soil quality classification index and classify the index into multiple levels; The formula for calculating the soil quality classification index G is as follows: G=(Xpotential+Xbuffer)-Xdamage Among them, Xpotential is an indicator of the potential for producing green products from soil, Xbuffer is an indicator of soil buffering capacity under climate change, and Xdamage is an indicator of the degree of soil ecological damage.

[0029] The soil quality classification index is divided into five levels: very low (0-20), low (20-40), medium (40-60), high (60-80), and very high (80-100).

[0030] S5: Collect soil samples and measure the actual value of the third soil health index. Compare the sum of the actual values ​​with the soil quality classification index to obtain the soil health level of the soil sample.

[0031] Example 1: Soil Health Assessment of Residual Smelting Sites This embodiment uses the soil of a legacy smelting site and its surrounding affected area as the evaluation object. This site has long been affected by smelting activities, waste slag storage, surface runoff, and surrounding agricultural use, resulting in significant spatial differences in the degree of heavy metal pollution, fertility level, and buffering capacity of the soil. The method of this invention is used to evaluate the soil health status of this area.

[0032] The evaluation process in this embodiment includes five steps: selection of soil evaluation system, raw data processing, ecological variation weighting adjustment, calculation of soil quality classification index, and determination of soil health level.

[0033] A soil assessment system was selected. The soil assessment system includes soil health indicators, ecological conditions, and ecological variability conditions in the sampling area. Soil health indicators include the soil ecological damage index (Xdamage), the soil green product production potential index (Xpotential), and the soil buffering capacity index (Xbuffer). The specific indicator system is shown in Table 1 and... Figure 2 As shown.

[0034] Table 1 Soil Health Evaluation Index System Among them, Xdamage is used to characterize the degree of soil stress caused by heavy metal pollution, including one or more of As, Pb, Cu, Zn, Ni, Cr, and Cd; Xpotential is used to characterize soil nutrient supply and production functions, including one or more of nitrate nitrogen, ammonium nitrogen, available potassium, available phosphorus, total nitrogen, organic matter, or total carbon; Xbuffer is used to characterize the soil's ability to regulate the migration and transformation of exogenous pollutants, including one or more of pH, Eh, electrical conductivity, CEC, specific surface area, total carbon, and clay content.

[0035] Soil samples were collected and raw indices were measured. Surface soil sampling points were set up within the evaluation area, with a sampling depth of 0-20 cm; more frequent sampling was conducted in areas adjacent to slag heaps, low-lying areas, gully confluence areas, reservoir areas, and agricultural land boundaries. After collection, the soil samples were air-dried, ground, and sieved, and then the heavy metal content, fertility indicators, and buffering capacity indicators were measured.

[0036] The original indicators were standardized. Positive indicators in Xpotential and Xbuffer were normalized using the formula X′=(Xi-Xmin) / (Xmax-Xmin), where a larger X′ indicates a higher contribution to soil health. Negative indicators constituting Xdamage, such as heavy metal content, pollution index, and ecological risk index, were normalized using the formula D′=(Xi-Xmin) / (Xmax-Xmin), where a larger D′ indicates a higher degree of ecological damage. Xdamage was calculated by combining D′ values. Here, Xi is the measured value of the i-th soil sample for a given evaluation indicator, Xmax is the maximum measured value of that indicator among all soil samples, and Xmin is the minimum measured value of that indicator among all soil samples. Since Xdamage represents the degree of damage and is deducted in G=(Xpotential+Xbuffer)-Xdamage, the reverse normalization result of X′=(Xmax-Xi) / (Xmax-Xmin) was not used to directly calculate Xdamage.

[0037] Calculate the functional layer indicators. The normalized basic indicators are combined using weighted summation, addition, multiplication, or maximum value methods to obtain Xdamage, Xpotential, and Xbuffer, respectively. The technical meanings of different combination methods are shown in Table 2.

[0038] Table 2. Functional Layer Indicator Combination Method Weighted adjustments were made based on ecological function and ecological variation conditions in the sampling area. When the evaluation object is the area affected by legacy smelting sites or slag heaps, the preferred ecological function is either "water source purification" or "maintaining ecological balance". Specifically, under the water source purification function, the weights of Xdamage, Xpotential, and Xbuffer are 2, 0.1, and 1, respectively; under the maintaining ecological balance function, all three have a weight of 1. The weights for different ecological functions are shown in Table 3.

[0039] Table 3. Indicator weights for different ecological conditions For legacy smelting sites, the sampling area type is treated as a heavy industrial area, and the sampling area correction factors for Xdamage, Xpotential, and Xbuffer are 2, 1, and 1, respectively; at the same time, Xpotential is corrected according to the annual rainfall level, and the correction parameters are shown in Table 4.

[0040] Table 4 Correction parameters for ecological variation conditions in the sampling area Calculate the soil quality classification index G. The soil quality classification index G is calculated using the following formula: G = (Xpotential + Xbuffer) - Xdamage. After linearly mapping the G value to the 0-100 range, classify the soil health level according to Table 5.

[0041] Table 5. Classification and Control Implications of Soil Health Levels In this embodiment, the calculated results for some samples are shown in Table 6. P1 is located in the adjacent area of ​​the slag dump, with high Xdamage and low Xpotential and Xbuffer, and a G-value mapping result of 0.0, which is judged as a very low health level. P5 is located in the background control area, with low Xdamage and high Xpotential and Xbuffer, and a G-value mapping result of 100.0, which is judged as a very high health level. Therefore, this method can simultaneously reflect the comprehensive impact of pollution stress, production potential, and buffering function on soil health level.

[0042] Table 6 Examples of calculation results for some samples in Example 1 Example 2: Soil Health Grading and Zoning Evaluation Based on Spatial Interpolation Based on Example 1, this embodiment combines the soil health index G with a spatial interpolation method to form a soil health grading and zoning map of the evaluation area.

[0043] First, obtain the latitude and longitude coordinates of each sampling point, and establish the correspondence between sample number, spatial location, land use type, heavy metal index, fertility index, buffer function index, Xdamage, Xpotential, Xbuffer and G value.

[0044] Secondly, the G value of each sampling point is imported into the spatial analysis module, and a continuously distributed soil health index layer is obtained using either IDW inverse distance weighted interpolation or Kriging interpolation. When the number of sampling points is small but the spatial distribution is relatively uniform, IDW interpolation is preferred; when the number of sampling points is large and there is significant spatial autocorrelation, Kriging interpolation is preferred.

[0045] Furthermore, based on the grading rules shown in Table 5, the evaluation area is divided into priority control areas, risk prevention and control areas, safe utilization areas, and ecological maintenance areas. The output format of the soil health grade zoning is as follows: Figure 3 As shown.

[0046] When a low-level area overlaps with a slag dump, former smelting workshop site, downstream of a waste slag storage area, or a gully confluence area, the area is designated as a priority control area; when a medium-level area is adjacent to a reservoir, ditch, or farmland boundary, it is designated as a risk control area; when a high-level or very high-level area is far from the pollution source and has a high buffer capacity, it is designated as a safe utilization area or an ecological maintenance area.

[0047] Example 3: Soil health assessment for different land use functions This embodiment illustrates the application of the same evaluation method under different land use functions. The evaluation objects include the impact area of ​​the slag heap, surrounding farmland, reservoir adjacent area, and ecological restoration area.

[0048] When the evaluation object is farmland, the ecological condition is selected as "providing nutrients", and the weights of Xdamage, Xpotential and Xbuffer are 1, 2 and 0.5 respectively, in order to highlight the soil's potential for producing green products.

[0049] When the evaluation object is the area adjacent to the reservoir, the downstream of the slag dump, or the confluence area of ​​the gully, the ecological condition is selected as "purification of water source", and the weights of Xdamage, Xpotential and Xbuffer are 2, 0.1 and 1 respectively, in order to highlight pollution reduction and migration control.

[0050] When the evaluation object is an ecological restoration area or a safe utilization area, the ecological condition is selected as "maintaining ecological balance", and the weights of Xdamage, Xpotential and Xbuffer are all 1, in order to comprehensively reflect pollution pressure, production potential and buffering capacity.

[0051] The same sample point can yield different G values ​​and health levels under different ecological function weights. If a sample point has a high G value under the "providing nutrients" function but a low G value under the "purifying water source" function, it indicates that the soil still has certain production potential, but its ability to prevent and control pollution migration is insufficient. Measures to reduce the available form of heavy metals, block surface runoff, or improve buffering capacity should be prioritized.

[0052] Example 4: Information-based output of soil health assessment results This embodiment illustrates how the evaluation results are output in the information platform. Sample coordinates, detection indicators, land use type, site attributes, and weighting parameters are imported into the soil health evaluation system.

[0053] The system first identifies outliers, handles missing values, and standardizes the input data; then it calculates Xdamage, Xpotential, Xbuffer, and G values ​​based on preset weights; next, it calls the IDW or Kriging interpolation algorithm to generate a soil health level layer; finally, it outputs the health level of the sample points, zoning results, main limiting factors, and control recommendations.

[0054] When Xdamage is the primary limiting factor, the system outputs recommendations for source control, in-situ stabilization, pollution isolation, or cover barrier. When Xpotential is the primary limiting factor, the system outputs recommendations for nutrient enhancement, organic matter regulation, or safe land use. When Xbuffer is the primary limiting factor, the system outputs recommendations for acidification adjustment, carbon increase, improvement of CEC, or improvement of soil structure.

[0055] This embodiment enables the integrated output of soil health assessment, grading, spatial zoning, layer display, and management recommendations.

[0056] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the invention.

Claims

1. A method for assessing soil health based on multiple ecological functions, characterized in that, Includes the following steps: S1: Select a soil evaluation system, which includes soil health indicators, ecological conditions and ecological variation conditions in the sampling area, and perform weighted processing on the soil health indicators based on the ecological conditions to obtain the first soil health indicator; S2: The raw data of the first soil health index are standardized and principal component analysis are performed sequentially to generate the second soil health index; S3: The second soil health index is weighted and adjusted based on the ecological variation conditions of the sampling area to generate the third soil health index; S4: Calculate and analyze the third soil health index to generate a soil quality classification index and classify the index into multiple levels; S5: Collect soil samples and measure the actual value of the third soil health index. Compare the sum of the actual values ​​with the soil quality classification index to obtain the soil health level of the soil sample.

2. The soil health assessment method based on multiple ecological functions according to claim 1, characterized in that, The soil health indicators include indicators of soil ecological damage, soil green product production potential, and soil buffering capacity under climate change.

3. The soil health assessment method based on multiple ecological functions according to claim 2, characterized in that, The soil ecological damage index was obtained by weighted calculation based on soil microbial diversity, soil microbial nitrogen fixation functional genome expression, and soil pollutant comprehensive index.

4. The soil health assessment method based on multiple ecological functions according to claim 3, characterized in that, The indicators for the production potential of green products from soil include soil historical cultivation intensity, effective soil layer thickness, topsoil thickness, soil maturity, soil texture, tilth, organic matter content, available nutrient content, nutrient storage, water retention, permeability, and pH. The soil cultivation history intensity indicators include historical agricultural output, historical fertilizer application, historical pesticide use, and historical farmyard manure use.

5. The soil health assessment method based on multiple ecological functions according to claim 4, characterized in that, The soil buffering capacity indicators under climate change include historical soil moisture content, historical groundwater level, historical annual average temperature change index, historical rainfall data, and the content of carbonates, bicarbonates, silicates, phosphates, and hydrogen phosphates in the soil.

6. The soil health assessment method based on multiple ecological functions according to claim 5, characterized in that, The formula for calculating the soil quality classification index G is as follows: G=(Xpotential+Xbuffer)-Xdamage Among them, Xpotential is an indicator of the potential for producing green products from soil, Xbuffer is an indicator of soil buffering capacity under climate change, and Xdamage is an indicator of the degree of soil ecological damage.

7. The soil health assessment method based on multiple ecological functions according to claim 6, characterized in that, The ecological conditions refer to the soil's use functions, including providing nutrients, retaining moisture, regulating climate, purifying water sources, and maintaining ecological balance. The weighting coefficients for soil health indicators under different ecological conditions are as follows: Nutritional information provided: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 2, and Xbuffer with a weighting factor of 0.

5. To maintain moisture: Xdamage is calculated with a weighting factor of 0.5, Xpotential is calculated with a weighting factor of 0.5, and Xbuffer is calculated with a weighting factor of 2. Regulating climate and maintaining ecological balance: Xdamage is calculated with a weighting factor of 1, Xpotential is calculated with a weighting factor of 1, and Xbuffer is calculated with a weighting factor of 1. Water source purification: Xdamage has a weighting factor of 2, Xpotential has a weighting factor of 0.1, and Xbuffer has a weighting factor of 1.

8. The soil health assessment method based on multiple ecological functions according to claim 6, characterized in that, The ecological variation conditions of the sampling area include the historical rainfall data of the sample collection area and the sample location. The sample collection area is divided into inland areas, heavy industrial areas, and coastal areas, with corresponding weighting rules as follows: Inland regions: Xdamage is calculated with a weighting factor of 0.5, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Heavy industrial areas: Xdamage is calculated with a weighting factor of 2, Xpotential with a weighting factor of 1, and Xbuffer with a weighting factor of 1. Coastal areas: Xdamage is calculated with a weighting factor of 1, Xpotential with a weighting factor of 0.5, and Xbuffer with a weighting factor of 1. The annual rainfall in the sample area is divided into three levels: high, medium, and low. The weighting coefficients for each level calculated by Xpotential are 0.1, 0.5, and 1, respectively.

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