Method for quantifying carbon-water coupling coordination degree of soil

Abstract

The invention discloses a method for quantifying the carbon-water coupling coordination degree of soil, relates to the technical field of ecological environment modeling, and particularly aims to solve the problem that only a single carbon cycle process or a single water cycle process is researched in the prior art in a vegetation recovery process in the background technology. The invention provides a method for quantifying the carbon-water coupling coordination degree of soil, which comprises the following steps: acquiring data, constructing a database, carrying out standardization processing on the database, constructing a soil carbon-water coupling degree model based on the processed database, and constructing a soil carbon-water coupling coordination degree model based on the soil carbon-water coupling degree model. And determining the soil carbon-water coupling coordination degree in the loess plateau vegetation recovery process based on the soil carbon-water coupling coordination degree model in combination with the soil organic carbon and moisture comprehensive evaluation function. The method is suitable for collaborative analysis of soil organic carbon and moisture under the condition of vegetation restoration in arid and semi-arid regions, and a technical basis is provided for ecological system management and vegetation configuration optimization.

Description

Technical Field

[0001] The present invention belongs to the technical field of quantified ecological environment, and particularly relates to a method for quantifying the degree of soil carbon-water coupling coordination. Background Art

[0002] Land-use changes, primarily focused on vegetation restoration, have significantly impacted the global carbon cycle. Vegetation restoration in arid and semi-arid regions is a double-edged sword. On the one hand, it promotes the recovery of degraded ecosystems and increases soil carbon sequestration, making it an effective means of mitigating global climate change. On the other hand, inappropriate vegetation restoration methods can lead to severe soil drying, reduced plant productivity, and even large-scale plant mortality, compromising long-term carbon sequestration.

[0003] Understanding the changes in soil carbon-water coupling during vegetation restoration and the mechanisms driving it has important theoretical and practical implications for improving the stability and sustainability of arid and semi-arid ecosystems. The arid and semi-arid Loess Plateau is a typical ecologically fragile region and one of the most severely affected areas of soil erosion worldwide. In 1999, to curb environmental degradation, my country implemented the "Grain for Forest (Grassland)" program, converting large amounts of cultivated land to forest and grassland vegetation. With the improvement of the ecological environment, the carbon sequestration effect of vegetation restoration has attracted widespread attention. However, inappropriate planting patterns (such as inappropriate tree species selection and excessive density) have led to a sharp decline in soil moisture, seriously threatening regional water balance. Therefore, systematically linking changes in soil organic carbon and water, based on the rational use of water resources, and promoting carbon accumulation and soil water retention through the combined allocation of soil carbon and water, is of great significance for scientifically understanding the mechanisms driving these relationships and improving ecosystem stability and sustainability. However, in existing research, predecessors have only studied the carbon cycle process or the water cycle process, and there is still a lack of systematic research on the changes in the organic carbon-soil moisture coupling (carbon-water coupling) relationship during vegetation restoration. This makes it difficult to provide a reliable basis for screening the optimal vegetation restoration measures to achieve synergistic efficiency in soil carbon sequestration and water conservation.

[0004] Therefore, it is urgent to design a method to quantify the degree of soil carbon-water coupling coordination to solve the existing problems. Summary of the Invention

[0005] To address the shortcomings of the aforementioned prior art, the present invention aims to provide a method for quantifying the degree of soil carbon-water coupling coordination, suitable for the coordinated analysis of soil organic carbon and water content in the context of vegetation restoration in arid and semi-arid regions. The degree of soil carbon-water coupling coordination obtained through this method during vegetation restoration has important theoretical and practical implications for enhancing the synergistic effects of soil carbon sequestration and water conservation during vegetation restoration.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A method to quantify the degree of soil carbon-water coupling coordination, including:

[0008] Obtain vegetation growth related data and build a database;

[0009] Standardize the data in the constructed database;

[0010] Based on the standardized data, a soil carbon-water coupling model was constructed;

[0011] Based on the soil carbon-water coupling model, a soil carbon-water coupling coordination model was further constructed;

[0012] Based on the soil carbon-water coupling coordination model and combined with the comprehensive evaluation function of soil organic carbon and moisture, the degree of soil carbon-water coupling coordination during vegetation restoration on the Loess Plateau was quantified.

[0013] Preferably, the vegetation growth related data include: longitude and latitude of the sampling site, average annual rainfall, average annual temperature, vegetation recovery years, vegetation type, soil organic carbon content, soil moisture content and soil depth.

[0014] Preferably, the extreme value method is used to standardize the data in the constructed database.

[0015] Preferably, the soil carbon-water coupling model expression is:

[0016]

[0017] Where C is the soil carbon-water coupling degree during vegetation restoration, k is the adjustment coefficient, f(x) is the comprehensive evaluation function of soil organic carbon, and g(y) is the comprehensive evaluation function of soil moisture.

[0018] Preferably, in the soil carbon-water coupling model expression, the expressions of f(x) and g(y) are:

[0019]

[0020] Where i is the number of soil layers of soil organic carbon, j is the number of soil layers of soil moisture, a is the weight of soil organic carbon, b is the weight of soil moisture, and x is the weight of soil organic carbon. i is the standardized value of soil organic carbon in layer i, y j is the standardized value of soil moisture in the jth layer, p is the sample size of function f(x), and q is the sample size of function g(y).

[0021] Preferably, the soil carbon-water coupling coordination model expression is:

[0022]

[0023] Where D is the soil carbon-water coupling coordination degree during vegetation restoration, and T is the comprehensive coordination index of soil carbon and water;

[0024] in,

[0025] T=αf(x)+βg(y)

[0026] Where α is the weight of soil organic carbon, and β is the weight of soil moisture.

[0027] A second object of the present invention is to provide a system for quantifying the degree of soil carbon-water coupling coordination, characterized by:

[0028] Data acquisition module, used to obtain vegetation growth related data and build a database;

[0029] A data processing module is used to standardize the data in the constructed database;

[0030] Model building module 1: constructing a soil carbon-water coupling model based on standardized data;

[0031] Model construction module 2: Based on the soil carbon-water coupling model, a soil carbon-water coupling coordination model is further constructed;

[0032] The output module quantifies the degree of soil carbon-water coupling coordination during vegetation restoration on the Loess Plateau based on the soil carbon-water coupling coordination model and combined with the comprehensive evaluation function of soil organic carbon and water.

[0033] Among them, the control system is implemented based on a method to quantify the degree of soil carbon-water coupling coordination.

[0034] A third object of the present invention is to provide a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute a method for quantifying the degree of soil carbon-water coupling coordination.

[0035] A fourth object of the present invention is to provide an electronic device comprising:

[0036] At least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform a method for quantifying the degree of soil carbon-water coupling coordination.

[0037] The beneficial effects of the present invention are as follows: the present invention discloses a method for quantifying the degree of soil carbon-water coupling coordination. Compared with the prior art, the present invention has the following improvements:

[0038] This study investigates the dynamic changes in soil carbon-water coupling during vegetation restoration on the arid and semi-arid Loess Plateau and establishes a carbon-water relationship evaluation method based on coupling coordination theory. This method is both scientifically sound and practical, as demonstrated in the following aspects:

[0039] 1. Significantly improve the accuracy of soil carbon and water status identification. This invention introduces a coupling coordination model for the first time in the Loess Plateau region for the coupled evaluation of soil organic carbon and water, constructs a comprehensive evaluation system for multi-layer soil profiles (0–200 cm), and makes the quantification of carbon-water relationships more scientific. A carbon-water coordination grading standard based on the coupling coordination degree D value has been developed, which can effectively identify ten types of succession states from "extreme imbalance" to "high-quality coordination", providing a technical basis for ecosystem management and optimized vegetation configuration.

[0040] 2. Strong technical adaptability and potential for widespread adoption. The method is applicable to a variety of ecological types, including artificial trees, artificial shrubs, abandoned grasslands, and climax natural vegetation. It exhibits good adaptability and portability, demonstrating stable identification and fitting capabilities across different rainfall and temperature zones. The method is highly sensitive and can be used to simulate soil ecological functions under future climate change scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The carbon-water coupling coordination characteristics of soil at each level of different vegetation types in the present invention are

[0042] Figure 2 This is a graph showing the change in soil carbon-water coupling coordination of different vegetation types on rainfall gradients in the present invention; wherein,

[0043] Figure (a) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 0-100 cm and rainfall for artificial trees; Figure (b) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 0-100 cm and rainfall for artificial shrubs; Figure (c) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 0-100 cm and rainfall for abandoned grassland; Figure (d) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 0-100 cm and rainfall for all data of artificial trees, artificial shrubs, and abandoned grassland; Figure (e) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 100-200 cm and rainfall for artificial trees; Figure (f) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 100-200 cm and rainfall for artificial shrubs; Figure (g) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 100-200 cm and rainfall for abandoned grassland; Figure (h) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree of the soil in the range of 100-200 cm and rainfall for all data of artificial trees, artificial shrubs, and abandoned grassland;

[0044] Figure 3 The present invention shows the change of soil carbon-water coupling coordination degree under temperature gradient of different vegetation types; wherein,

[0045] Figure (a) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 0-100 cm in the soil of artificial trees; Figure (b) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 0-100 cm in the soil of artificial shrubs; Figure (c) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 0-100 cm in the soil of abandoned grassland; Figure (d) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 0-100 cm in the soil of all data of artificial trees, artificial shrubs, and abandoned grassland; Figure (e) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 100-200 cm in the soil of artificial trees; Figure (f) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 100-200 cm in the soil of artificial shrubs; Figure (g) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 100-200 cm in the soil of abandoned grassland; Figure (h) is a statistical diagram showing the relationship between the water-carbon coupling coordination degree and temperature at 100-200 cm in the soil of all data of artificial trees, artificial shrubs, and abandoned grassland;

[0046] Figure 4 The relative importance of the four factors of rainfall, temperature, age, and vegetation type in explaining the variability of organic carbon, water, and carbon-water coupling coordination in different soil layers during the vegetation restoration process of the present invention;

[0047] Figure (a) is a statistical diagram showing the degree of explanation of rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU) for the variability of soil organic carbon (SOC) in the 0-100 cm soil layer; Figure (b) is a statistical diagram showing the degree of explanation of rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU) for the variability of soil water content (SWC) in the 0-100 cm soil layer; Figure (c) is a statistical diagram showing the degree of explanation of rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU) for the variability of soil carbon-water coupling coordination in the 0-100 cm soil layer; Figure (d) is a statistical diagram showing the degree of explanation of rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU) for the variability of soil organic carbon (SOC) in the 100-200 cm soil layer; Figure (e) is a statistical diagram showing the degree of explanation of rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU) for the variability of soil organic carbon (SOC) in the 100-200 cm soil layer. Figure (g) shows the explanation of the variability of soil carbon-water coupling coordination degree in the 100-200 cm soil layer by rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU); Figure (h) shows the explanation of the variability of soil organic carbon (SOC) in the 0-200 cm soil layer by rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU); Figure (i) shows the explanation of the variability of soil water (SWC) in the 0-200 cm soil layer by rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU); Figure (j) shows the explanation of the variability of soil carbon-water coupling coordination degree in the 0-200 cm soil layer by rainfall (PRE), temperature (TEM), restoration years (Age), and vegetation type (LU); DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0049] Example 1:

[0050] S1. Obtain vegetation growth related data and build a database;

[0051] The data sources of the embodiment of the present application include three databases, specifically: the soil organic carbon and soil moisture database of abandoned farmland vegetation, the top natural grassland database, and the top natural forest database. The data sources are divided into two parts, one is literature data, and the other is measured data.

[0052] In terms of literature data, based on Clarivate Analytics and CNKI platforms, we collected and screened research literature on abandoned farmland vegetation (artificial trees, artificial shrubs, and abandoned grassland) and top natural vegetation (soil organic carbon and water) in the Loess Plateau since 1990. The screening criteria were: (1) organic carbon and soil water data can be directly obtained or calculated; (2) data are paired and the background environment of the sampling points is consistent; (3) the restoration years can be directly or indirectly obtained; (4) clear climate background information is available; (5) the number of replicate samples is not less than 3; and (6) the sampling depth is between 20 and 200 cm. The chart data was extracted using GetdataGraph Digitizer (ver. 2.24). The information collected for each literature includes literature information, latitude and longitude of the sampling site, average annual temperature, average annual rainfall, vegetation type, vegetation restoration years, and soil thickness.

[0053] The measured data come from supplementary field sample collection during 2018-2019, and the sampling points are distributed in Shenmu, Ansai, Fuxian, Wuqi in Shaanxi and Guyuan in Ningxia.

[0054] The data on top natural grasslands and forests are mainly derived from literature integration and supplementary field sampling in 2018-2019. To avoid seasonal bias, all samples were collected during the plant growing season and avoided one week after rainfall. The top natural grassland has collected soil organic carbon and moisture data from the 0-200cm soil layer of the Yunwushan Nature Reserve since 1982. A total of 16 documents (2004-2020) were integrated, and 414 sets of soil organic carbon and moisture observation data were obtained. In addition, 18 plots with different closure years were collected on the spot, 180 samples were obtained, and a total of 540 supplementary data were obtained. After integration, a total of 954 observation data were obtained. The top natural forest community uses the succession process from natural secondary shrubs to Liaodong oak forests in the Ziwuling area as the restoration sequence. 8 documents were integrated, and a total of 148 sets of soil organic carbon and moisture data were obtained. Combined with actual measurements, a total of 594 observation data were obtained.

[0055] The three databases ultimately contained a total of 9,410 observational records, 4,010 of which were field measurements. The databases also contained 4,705 paired data sets for soil organic carbon and water content, providing a rich foundation for subsequent carbon-water coupling analysis. Data collected across the three databases included: sampling site longitude and latitude, average annual rainfall, average annual temperature, vegetation restoration years, vegetation type, soil organic carbon content, soil moisture content, and soil depth.

[0056] S2. Standardize the data in the constructed database;

[0057] Specifically, the soil organic carbon content and soil moisture content in the database obtained in step S1 are standardized to obtain standardized soil organic carbon values ​​and soil moisture values;

[0058] The Loess Plateau belongs to an arid and semi-arid area. The higher the soil organic carbon and moisture content, the better the ecosystem. Therefore, the present invention uses the extreme value method to normalize the data. Specifically, to avoid interference from extreme values, the soil organic carbon content and soil moisture content in the database obtained in step 1 are first sorted, and the means of the first 5% and last 5% of the sorted data are taken as the maximum and minimum values ​​of the soil organic carbon content and soil moisture content, respectively. Then, the other soil organic carbon and soil moisture content data, the determined maximum and minimum values ​​are proportionally scaled to the specified interval (the interval is 0-1), and the relative sizes between the values ​​are kept unchanged (such as the two columns of data after normalization of soil organic carbon values ​​and normalized soil moisture values ​​in Table 1).

[0059] Table 1 Details of some of the collected data

[0060]

[0061]

[0062] S3. Constructing a soil carbon-water coupling model based on the database processed in step S2;

[0063] Based on the standardized soil organic carbon and soil moisture values, a soil carbon-water coupling model was constructed. The expression of the model is as follows:

[0064]

[0065] Where C is the coupling degree of soil organic carbon and water during vegetation restoration, and k is the adjustment coefficient. Generally, 2 ≤ k ≤ 5; in this paper, k = 2. The coupling degree, C, reflects the degree of coordination between soil organic carbon and water when the sum of f(x) and g(y) is under certain conditions.

[0066] According to the calculation formula of the soil carbon-water coupling model, it can be found that 0≤C≤1. When C tends to 1, it means that the soil carbon-water relationship has reached a benign resonant coupling; when C=0, the coupling degree is extremely small, indicating that the soil carbon-water relationship is in a decoupling state.

[0067] f(x) and g(y) are utility functions, where f(x) is the comprehensive evaluation function of soil organic carbon and g(y) is the comprehensive evaluation function of soil moisture, and their expressions are:

[0068]

[0069] Where i is the number of soil layers of soil organic carbon, j is the number of soil layers of soil moisture, a is the weight of soil organic carbon, b is the weight of soil moisture, and x is the weight of soil organic carbon. i is the standardized value of soil organic carbon in layer i, y jis the standardized value of soil moisture in the jth layer, p is the sample size of function f(x), and q is the sample size of function g(y).

[0070] S4. Based on the soil carbon-water coupling model constructed in step S3, further construct a soil carbon-water coupling coordination model;

[0071] Because soil carbon-water coupling only reflects the interaction between soil carbon and water, it fails to fully capture the overall levels and synergistic effects of soil carbon and water. Furthermore, it is significantly affected by extreme values, potentially leading to overestimation or underestimation of the degree of soil carbon-water coupling. Therefore, to more accurately assess the coordination of soil carbon-water relationships under different vegetation types, soil layers, and climatic conditions, this example introduces a comprehensive soil carbon-water harmony index based on the soil carbon-water coupling degree to construct a soil carbon-water coordination model.

[0072] The soil carbon-water coupling coordination model expression is as follows:

[0073]

[0074] in,

[0075] T=αf(x)+βg(y) (5)

[0076] Where D is the degree of soil carbon-water coupling coordination during vegetation restoration; T is the comprehensive soil carbon-water coordination index, which reflects the overall coordination effect of soil organic carbon and water; α is the weight of soil organic carbon, and β is the weight of soil water. In this example, soil organic carbon and water are equally weighted, that is, α = β = 0.5.

[0077] The coupling coordination degree characterizes the degree of coupling coordination between soil organic carbon and water during vegetation restoration. The value of D is between 0 and 1. The higher the D value, the higher the overall level of soil carbon and water, and the more sustainable the coupling relationship between soil carbon and water.

[0078] S5. Based on the soil carbon-water coupling coordination model from step S4 and combined with the comprehensive evaluation function of soil organic carbon and water, quantify the degree of soil carbon-water coupling coordination during vegetation restoration on the Loess Plateau;

[0079] This example constructs soil carbon-water coupling coordination types and evaluation criteria for vegetation restoration on the Loess Plateau based on the coupling coordination degree (D) and a comprehensive evaluation function for soil organic carbon and water (see Table 2). This allows the degree of soil carbon-water coupling coordination to be determined. Table 2 categorizes these types and evaluation criteria into four levels and ten subcategories, systematically reflecting the state of carbon-water coordination. In practice, the degree of soil carbon-water coupling can be used to determine whether a particular vegetation restoration approach promotes synergistic carbon sequestration and water conservation, providing timely guidance for subsequent vegetation structure adjustments.

[0080] Table 2 Classification of soil carbon-water coupling types during vegetation restoration on the Loess Plateau

[0081]

[0082]

[0083] Example 2

[0084] This example uses the method of Example 1 to determine differences in carbon-water coupling coordination across different vegetation types and soil depths. This demonstrates that the method of Example 1 is sensitive to changes in factors such as vegetation type, soil depth, and climate, and can accurately characterize soil-water-carbon relationships. The method of Example 1 is applicable to a variety of ecological types, including artificial trees, artificial shrubs, abandoned grasslands, and climax natural vegetation, and exhibits good adaptability and portability.

[0085] (1) The influence of soil carbon-water coupling on vegetation type, soil layer, rainfall, temperature, restoration years and their interactions;

[0086] The carbon-water coupling coordination degree varies significantly between different vegetation types and soil depths. Figure 2 As shown in Table 3. Figure 2 It can be seen from Table 3 that the soil carbon-water coupling coordination degree of different vegetation types gradually decreases with the increase of soil depth. From the perspective of different vegetation types, within the 0-200cm soil profile, the soil carbon-water coupling coordination degree of the top natural grassland and the top natural forest are significantly higher than that of other vegetation types, and are at a coordinated level. The soil carbon-water coupling coordination degree of abandoned grassland, artificial shrubs and artificial trees is significantly lower than that of cultivated land. Below 40cm in the soil profile, they are all at an imbalance level, between mild imbalance and imminent imbalance. The difference in soil carbon-water coupling coordination degree of artificial trees and artificial shrubs is small, and is significantly lower than that of other vegetation types. Table 3 Effects of rainfall, temperature, vegetation type, year and their interactive effects on soil organic carbon, soil moisture, and soil carbon-water coupling coordination degree

[0087]

[0088] Note: SOC is soil organic carbon (g C kg -1 ); SWC is soil moisture (%); D is soil carbon-water coupling coordination; the numbers below SOC, SWC, and D represent chi-square values; PRE is different rainfall zones (<450 mm, 450-550 mm, and >550 mm); TEM is different temperature zones (<9°C and >9°C); Land use is land use type (artificial trees, artificial shrubs, abandoned grassland); Age is different recovery stages (0-10 years, 10-20 years, 20-30 years, and >30 years)

[0089] (2) the relationship between soil carbon-water coupling and rainfall and temperature;

[0090] The Pearson correlation coefficient (implemented using the cor.test function in R) was used to analyze the correlation between soil carbon-water coupling coordination values ​​and average annual rainfall and temperature at different restoration stages. The results showed that in the 20 years before vegetation restoration, soil carbon-water coupling coordination at the 0-100 cm depth was positively correlated with both rainfall and temperature. After 20 years of restoration, it showed a significant negative correlation with temperature and a positive correlation with rainfall (Table 4). In the first 30 years of vegetation restoration, soil carbon-water coupling coordination at the 100-200 cm depth was positively correlated with both rainfall and temperature, but became negatively correlated 30 years after restoration. Overall, increased rainfall promoted an enhanced carbon-water coupling relationship, while temperature had different effects at different stages, with a positive effect in the 20 years before restoration and a negative effect after 20 years of restoration (Table 4).

[0091] Table 4 Correlation analysis between soil carbon-water coupling coordination and climate factors at different recovery stages

[0092]

[0093]

[0094] Note: “***”, “**”, “*” and “ns” represent the significance levels of correlation coefficients at P<0.001, P<0.01, P<0.05 and P>0.05, respectively; PRE and TEM represent the average annual precipitation and average annual temperature, respectively.

[0095] (3) Response curve and threshold identification

[0096] Refer to the attached Figure 2 As shown in Figure 2, the soil carbon-water coupling coordination degree of artificial trees at 0-100 cm showed a downward trend when the rainfall was lower than 534 mm (P>0.05), and increased significantly with rainfall after the inflection point (P<0.001) ( Figure 2a). The coupling coordination degree between 100-200 cm increases slowly (P<0.001) and then rapidly (P<0.05) with rainfall, with the inflection point at 560 mm ( Figure 2 e). The soil carbon-water coupling coordination degree of artificial shrub forests showed a decreasing trend along the rainfall gradient (P>0.05) ( Figure 2 b). The coupling coordination degree of abandoned grassland at 0-100cm and 100-200cm first decreased and then increased with rainfall (P<0.001), with the inflection points being 513mm and 439mm, respectively ( Figure 2 c, g). Overall, the carbon-water coupling coordination degree of the 0-100 cm and 100-200 cm soil layers first decreases and then increases along the rainfall gradient. The coupling coordination degree of the two soil layers responds differently to rainfall, with inflection points of 524 mm and 483 mm, respectively. After the inflection point, the 0-100 cm soil layer increases faster ( Figure 2 d, h).

[0097] On the temperature gradient, the carbon-water coupling coordination degree of the artificial tree soil at 0-100 cm and 100-200 cm increased linearly with temperature (P<0.001) ( Figure 3 a, e), while artificial shrubs showed a linear decrease ( Figure 3 b, f). The response of abandoned grassland to temperature is similar to rainfall, with the temperature gradient first decreasing and then increasing. The upper and lower soil layers have relatively consistent responses to temperature changes, that is, the change rates before and after the inflection point are similar, with the inflection points being 8.4°C and 8.2°C, respectively. Figure 3 c, g). Overall, the carbon-water coupling coordination degree of the 0-100cm and 100-200cm soils first decreases and then increases along the temperature gradient. The inflection points of the temperature response of the upper and lower soil layers are similar, which is different from the response to rainfall ( Figure 3 d, h).

[0098] It is worth noting that compared with artificial trees and shrubs, the soil carbon-water coupling coordination of abandoned grasslands showed higher sensitivity to both rainfall and temperature gradients, especially to temperature gradients ( Figure 3 c, g).

[0099] (4) Sensitivity analysis of random forest model

[0100] The results of random forest regression models showed that vegetation type, rainfall, temperature, and restoration years explained 38.1% to 48.5%, 49.6% to 61.0%, and 49.5% to 50.8% of the variation in soil organic carbon, water content, and coupling coordination amplitude, respectively. Figure 4From the perspective of the main controlling factors, rainfall and temperature explain approximately 70% of the variability in shallow and deep organic carbon. The combined explanatory contribution of rainfall and temperature to soil moisture in the 0-100 cm layer is approximately 65%. The main factor affecting the variability of deep soil moisture is vegetation type, with a single factor explanatory contribution of 40.46%. The combined contribution of rainfall and temperature is approximately 39.5%. Rainfall and temperature are the main controlling factors of soil carbon and water coupling coordination, and their explanatory contributions to soil carbon and water coupling in the 0-100 cm and 100-200 cm layers are 62% to 72%. Overall, climate factors are the main controlling factors of soil organic carbon, water, and the coupling coordination between the two during vegetation restoration on the Loess Plateau, with explanatory contributions ranging from 63% to 77%.

[0101] The above analysis shows that the constructed soil water-carbon coupling coordination model can sensitively respond to changes in factors such as vegetation type, soil depth, and climate, and can sensitively characterize the soil water-carbon relationship.

[0102] Comparing the method of the present invention with the traditional method that only relies on correlation analysis or single variable trend judgment, the present technical solution has the following significant advantages, as shown in Table 5:

[0103] Table 5 Comparison between the method of the present invention and the traditional method

[0104]

[0105] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for quantifying the degree of soil carbon-water coupling coordination, characterized in that: include: Obtain vegetation growth related data and build a database; Standardize the data in the constructed database; Based on the standardized data, a soil carbon-water coupling model was constructed; Based on the soil carbon-water coupling model, a soil carbon-water coupling coordination model was further constructed; Based on the soil carbon-water coupling coordination model and combined with the comprehensive evaluation function of soil organic carbon and moisture, the degree of soil carbon-water coupling coordination during vegetation restoration on the Loess Plateau was quantified.

2. The method for quantifying the degree of soil carbon-water coupling coordination according to claim 1, characterized in that: Vegetation growth-related data include: latitude and longitude of the sampling site, average annual rainfall, average annual temperature, vegetation recovery years, vegetation type, soil organic carbon content, soil moisture content and soil depth.

3. The method for quantifying the degree of soil carbon-water coupling coordination according to claim 1, characterized in that: The extreme value method is used to standardize the data in the constructed database.

4. The method for quantifying the degree of soil carbon-water coupling coordination according to claim 1, characterized in that: The soil carbon-water coupling model expression is: Where C is the soil carbon-water coupling degree during vegetation restoration, k is the adjustment coefficient, f(x) is the comprehensive evaluation function of soil organic carbon, and g(y) is the comprehensive evaluation function of soil moisture.

5. The method for quantifying the degree of soil carbon-water coupling coordination according to claim 4, characterized in that: In the soil carbon-water coupling model expression, the expressions of f(x) and g(y) are: Where i is the number of soil layers of soil organic carbon, j is the number of soil layers of soil moisture, a is the weight of soil organic carbon, b is the weight of soil moisture, and x is the weight of soil organic carbon. i is the standardized value of soil organic carbon in layer i, y j is the standardized value of soil moisture in the jth layer, p is the sample size of function f(x), and q is the sample size of function g(y).

6. The method for quantifying the degree of soil carbon-water coupling coordination according to claim 1, characterized in that: The soil carbon-water coupling coordination model expression is: Where D is the soil carbon-water coupling coordination degree during vegetation restoration, and T is the comprehensive coordination index of soil carbon and water; in, T=αf(x)+βg(y) Where α is the weight of soil organic carbon, and β is the weight of soil moisture.

7. A system for quantifying the degree of soil carbon-water coupling coordination, characterized by: Data acquisition module, used to obtain vegetation growth related data and build a database; A data processing module is used to standardize the data in the constructed database; Model building module 1: constructing a soil carbon-water coupling model based on standardized data; Model construction module 2: Based on the soil carbon-water coupling model, a soil carbon-water coupling coordination model is further constructed; The output module quantifies the degree of soil carbon-water coupling coordination during vegetation restoration on the Loess Plateau based on the soil carbon-water coupling coordination model and combined with the comprehensive evaluation function of soil organic carbon and water. The control system is implemented based on the method according to any one of claims 1 to 6.

8. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 6.

9. An electronic device comprising: At least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

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