Partitioning-targeting farmland nutrient regulation and non-point source pollution prevention and control method

Abstract

The invention relates to the technical field of agricultural non-point source pollution prevention and control, in particular to a zoning-targeting farmland nutrient regulation and non-point source pollution prevention and control method which is suitable for sustainable management of low-latitude plateau lake basin farmland. According to the method, based on interaction of soil texture and depth, distribution modes of carbon, nitrogen, phosphorus and stoichiometric ratios thereof of different soil types are determined through field investigation, soil sampling, physicochemical property analysis and statistical analysis, so that a nutrient management strategy is optimized. Different soil textures and depths have obvious influence on available nutrients, and further influence crop nutrient absorption and farmland pollution level. Farmland zoning management is carried out according to soil texture classification, targeted fertilization and pollution prevention and control measures are taken according to soil characteristics of all areas, the nutrient utilization efficiency is improved, and the non-point source pollution risk is reduced. The method is simple, convenient and feasible, is suitable for vast farmers, and is beneficial to realizing a win-win situation of ecological and economic benefits.

Description

Technical Field

[0001] The present invention belongs to the technical field of agricultural non-point source pollution prevention and control, and particularly relates to a "zoning-targeting" method for regulating farmland nutrients and non-point source pollution prevention and control. Background Art

[0002] Carbon (C), nitrogen (N), and phosphorus (P), as well as their stoichiometric ratios, play crucial roles in regulating ecosystem functions and services, including material cycling, carbon sequestration, and vegetation productivity. Exploring nutrient economic models and the stoichiometry of abiotic and biotic components provides insights into the constraints imposed by the mass balance of multiple elements in the ecological interactions between plants, soils, and soil microorganisms. Despite extensive research on the stoichiometry of C, N, and P in nutrient cycling, most studies have focused on total nutrient content, neglecting available nutrients. However, available nutrients in soil play a crucial role in connecting the soil-plant-microorganism system and regulating nutrient cycling in terrestrial ecosystems. Changes in available soil element ratios can lead to nutrient imbalances, potentially affecting plant and microbial nutrient acquisition, chemical composition, and ecosystem productivity. For example, excess available N can alter plant nutrient stoichiometry and accelerate P cycling. Furthermore, nitrate N and dissolved organic N are the primary forms of N lost through surface runoff and leaching. Similarly, changes in available N levels in soil can significantly affect P transformation rates and soil available K. These findings suggest an urgent need to investigate the available and total amounts of carbon, nitrogen, and phosphorus, as well as their stoichiometric ratios, to better understand the processes of carbon, nitrogen, and phosphorus cycling under current long-term management practices.

[0003] Soil texture (e.g., sand, silt, and clay) is a key factor influencing the stability, cycling, and stoichiometric ratios of soil carbon, nitrogen, and phosphorus. In agricultural management, soil texture plays a crucial role in nutrient management, controlling particle aggregation, nutrient retention, and nutrient availability. Studies have shown that the stability of soil carbon and nitrogen increases with increasing clay content. Wang Haijun et al. investigated the determinants of soil nutrient partitioning in a small watershed and proposed that silt and sand content are key factors influencing soil total phosphorus content (Wang, HJ, et al. 2009. Soil and Tillage Research 105, 300-306). Furthermore, some studies have found relationships between soil texture and other soil nutrient indicators. For example, surface soils, which are most influenced by climate and vegetation, typically contain a higher proportion of fine particles. In contrast, deeper soils, closer to the parent material, are typically composed of coarse particles. These differences in soil texture may differentially regulate the carbon: nitrogen: phosphorus stoichiometric ratios across the soil profile. However, previous studies have mostly focused on the stoichiometric ratios of surface soils in plain farmlands, while data on the C, N, and P contents in deeper soils of different textures in plateau lake basins are limited. Therefore, further investigation into the effects of different soil textures and depths on the total and available contents of C, N, and P, as well as their stoichiometric ratios, is necessary to fully understand the mechanisms underlying soil biogeochemical cycling and to develop sustainable land management practices.

[0004] The cultivated land surrounding low-latitude plateau lakes in Yunnan Province, China, is a typical intensive agricultural area and a key production base for water- and fertilizer-intensive crops such as vegetables and flowers. These areas are severely impacted by human activities. The unique topography, large diurnal temperature swings, strong ultraviolet radiation, and distinct dry and rainy seasons of these plateau lakes increase their susceptibility to agricultural non-point source pollution, thereby degrading lake water quality. While the characteristics of nitrogen and phosphorus losses from open-air farmland and greenhouses in plateau lake basins have been studied, the relative importance of different soil properties in influencing nitrogen and phosphorus losses remains unclear. Fundamentally addressing agricultural pollution in this sensitive region requires a comprehensive understanding of soil properties, particularly how soil texture and depth influence the total, available, and stoichiometric contents of C, N, and P. Summary of the Invention

[0005] The present invention provides a novel "zoning-targeting" method for controlling farmland nutrients and non-point source pollution. It mainly analyzes the physical and chemical properties and nutrient content of the soil, zons the farmland according to soil texture and depth, and proposes a targeted fertilization strategy. The existing soil testing and formula fertilization is a relatively accurate fertilization management technology currently being promoted. It is more suitable for intensive farmland management, but it has the following problems that prevent it from being popularized among small farmers: (1) It requires professional testing personnel and instructors and the testing cost is high; (2) It focuses on the nutrient needs of single-season crops and easily ignores the accumulation of soil organic matter and carbon sequestration function; (3) Over-reliance on chemical fertilizers can easily cause soil acidification or salinization and loss of biodiversity; (4) Ordinary small farmers have difficulty obtaining the full process of "testing-formulation-fertilization" services. In China, the proportion of small farmers in planting should not be underestimated, especially in the prevention and control of non-point source pollution in farmland, which requires the participation of all farmers to achieve the best results. This invention addresses the problems with soil testing and formula fertilization techniques mentioned above. Using the method described in this invention, ordinary smallholder farmers can identify soil texture and zoning, then apply targeted fertilization based on these zoning areas. This approach breaks through the limitations of traditional single-crop farmland nutrient management and develops a simple, easily identifiable, and actionable "ecological benefit-economic cost" system for farmland nutrient management and non-point source pollution control. This method not only optimizes soil nutrient input and increases the effective utilization rate of soil nutrients, but also effectively controls non-point source pollution. It is particularly suitable for specific areas such as plateau lakes, overcoming the problem of soil testing and formula fertilization techniques being difficult to popularize and apply to smallholder farmers, providing a more efficient, ecological, and economical solution for agricultural production.

[0006] A "zoning-targeting" method for controlling farmland nutrients and non-point source pollution includes the following steps: S1 Soil texture zoning: Using the international soil texture classification standard, the clay content ratio of different soil textures is as follows: clay > 45%, clay loam 30-45%, loam 15-30%, and sand <15%. Farmland soil textures are classified and zoned accordingly. Farmland areas are divided into different management zones based on different soil textures to facilitate differentiated management. S2 Soil sample collection and analysis: In each management area, soil samples from different soil layers were collected using a five-point sampling method, and soil physical and chemical properties were analyzed, including the determination of total organic carbon (hereinafter uniformly abbreviated as SOC), total nitrogen (hereinafter uniformly abbreviated as TN), total phosphorus (hereinafter uniformly abbreviated as TP), dissolved organic carbon (hereinafter uniformly abbreviated as DOC), available nitrogen (the sum of ammonia nitrogen and nitrate nitrogen, hereinafter collectively referred to as available nitrogen, hereinafter uniformly abbreviated as AN), and available phosphorus (hereinafter uniformly abbreviated as AP), and the calculation of the corresponding stoichiometric ratios; S3 Data Analysis and Model Building: Based on the results of physical and chemical analysis of soil samples, statistical methods are used to analyze the main and interactive effects of soil texture and depth on nutrient content and stoichiometric ratios. Path analysis is used to develop a nutrient management model related to soil texture and depth to predict nutrient flow and circulation patterns in different regions. S4 Targeted Fertilization and Pollution Prevention and Control Strategy Development: Develop targeted fertilization strategies based on soil texture and nutrient requirements, including selecting fertilizer types, application methods, and application rates, controlling the loss of available nitrogen and available phosphorus, and optimizing the stoichiometric ratio of soil carbon, nitrogen, and phosphorus in combination with carbon regulation methods; S5 Long-term soil nutrient management and ecological restoration measures: Develop a long-term soil nutrient restoration plan, including increasing organic matter input, using slow-release fertilizers, returning straw to fields, and optimizing farmland water conservancy facilities; S6 Farmland pollution early warning and optimization adjustment mechanism: Through regular monitoring of different soil types and fertilization effects, and the use of organic matter based on changes in the C, N and P content in the soil, combined with the carbon-nitrogen ratio of soil samples, regular assessment of soil nutrient status and environmental impact is carried out.

[0007] In some embodiments, the multi-point sampling method in S2 comprises the following steps: random sampling is performed at five different sampling points with different soil layers having thicknesses of 0-20 cm, 20-40 cm, and 40-60 cm in each management area.

[0008] In some embodiments, the method for establishing the nutrient management model described in S3 is: using one-way and two-way analysis of variance and Mantel test methods to analyze the main effects and interaction effects of soil texture and depth on C, N, P content and stoichiometric ratio, and using path analysis to construct a soil texture-depth-nutrient relationship prediction model, which is a nutrient management model. The model reveals the possible direct and indirect effects of soil depth and texture on the stoichiometric ratio of C, P and N; soil texture has an indirect effect on SOC:TN, TN:TP, SOC:TP, AN:AP and DOC:AP, and has a direct and indirect effect on DOC:AN; depth has an indirect effect on SOC:TN and DOC:AN, and has a direct and indirect effect on TN:TP, SOC:TP and DOC:AP, including TP, SOC:TP, AN:AP and DOC:AP; SOC:TP and SOC:TN are affected by SOC through the effect of soil depth and texture on TP. DOC:AP and DOC:AN were affected by AN, which was in turn affected by soil depth and texture on TP. In addition, soil texture affected TN:TP mainly through SOC and AN. Soil depth and texture affected AN:AP through AN content.

[0009] In some embodiments, the step of the targeted fertilization strategy in S4 is to adjust the type of fertilization according to the stoichiometric ratios of SOC:TN, SOC:TP, TN:TP, DOC:AN, DOC:AP, and AN:AP in the soil of different regions, and select the crop growth period with high soil nutrient absorption as the fertilization opportunity.

[0010] In some embodiments, the long-term soil nutrient management and ecological restoration scheme in S5 includes the combination of green manure planting and multiple ecological restoration measures, and the specific measures include: a. Planting green manure crops such as Astragalus sinicus and Vicia unguiculata to increase soil organic matter; b. Adopting water-flood rotation and bean-grass rotation system to improve soil structure and micro-ecological environment.

[0011] In some embodiments, the optimization measures for farmland water conservancy facilities in S5 are to adopt water-saving irrigation methods such as drip irrigation and small pipe spraying.

[0012] In some embodiments, the step of the pollution prevention and control measures in S6 is that the farmland pollution early warning and optimization adjustment mechanism in S6 is to judge the soil nutrient status according to the stoichiometric ratio of carbon, nitrogen and phosphorus in the soil. When the ratio of nitrogen and phosphorus in the soil is less than 14, the plant is in a nitrogen-limited state. When the ratio of carbon and nitrogen is less than 30, it indicates a high risk of nitrate leaching, and then specific management measures such as fertilization are taken to control the soil nutrients in farmland.

[0013] In some embodiments, the farmland pollution early warning and optimization adjustment mechanism in S6 includes establishing a monitoring network for soil nutrients and pollutant concentrations, and predicting the nutrient loss trend and non-point source pollution risk through real-time data analysis.

[0014] In some embodiments, the organic matter in S6 is one or a combination of humus, biochar natural organic matter, and organic fertilizer treated by microbial fermentation. The amount of chemical fertilizer is 30%-75% of the conventional fertilization amount, which is adjusted according to the degree of deviation of the C:N:P stoichiometric ratio threshold.

[0015] (1) Precise fertilization: By analyzing the influence of soil texture and depth on nutrients, targeted fertilization is achieved, which significantly reduces the waste of 24% of chemical fertilizers.

[0016] (2) Pollution prevention and control: By adjusting the ratio of nitrogen and phosphorus in the soil, nutrient loss is reduced, especially in sensitive areas such as highland lakes, reducing non-point source pollution.

[0017] (3) Economically feasible: Compared with traditional soil testing and formula fertilization, the method of the present application is simple and easy to operate, and ordinary farmers can independently identify soil texture for fertilization, reducing costs.

[0018] (4) Environmentally friendly: The method emphasizes ecological balance, promotes sustainable agricultural development, and reduces the negative impact of agricultural activities on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Schematic diagram of the process of "zoning-targeting" regulation of farmland nutrients and non-point source pollution prevention and control methods; Figure 2 It is a soil texture classification map; Figure 3 Variations in soil SOC, TN, TP, DOC, AN, and AP contents across different farmland soil textures. Error bars represent mean ± standard error, and different letters indicate significant differences among soil textures (p < 0.05). Figure 4 Vertical distribution of available and total amounts of carbon, nitrogen, and phosphorus in farmland soils of a low-latitude plateau lake basin. Different letters indicate significant differences among different soil layers (p < 0.05). Error bars represent mean ± standard error. Figure 5 Figure 3. Stoichiometric ratios of available and total carbon, nitrogen, and phosphorus with soil depth and texture. Changes in (a) SOC: TN; (b) SOC: TP; (c) TN: TP; (d) DOC: AN; (e) DOC: AP; and (f) AN: AP in three soil layers and four soil textures. Columns represent mean ± SE. The horizontal axis represents different soil textures (pink) and soil layers (blue), clay, clay loam, loam, sand, 0–20 cm layer, 20–40 cm layer, and 40–60 cm layer, respectively. The vertical axis represents the content of different indicators. Significant differences are indicated by different letters (p < 0.05; different soil textures are indicated by uppercase letters, and different depths are indicated by lowercase letters). Figure 6 Correlation plot of farmland soil properties and stoichiometric ratios at different depths and textures. Red areas indicate positive correlations, blue areas indicate negative correlations. Soil textures are assigned values ​​based on their clay content. Figure 7 Pathway study between soil depth, texture, pH, available and total amounts of C, N, and P, and their stoichiometric ratios; model fitting parameters are as follows: (a) SOC:TN, p = 0.25, χ 2 = 28.16, RMSEA = 0.02, GFI = 0.94; (b) SOC: TP, p = 0.31, χ 2 = 24.08, RMSEA = 0.02, GFI = 0.95; (c) AN: AP, p = 0.52, χ 2= 23.89, RMSEA = 0.03, GFI = 0.93; (d) DOC: AN, p = 0.51, χ 2 = 23.96, RMSEA = 0.02, GFI = 0.94; (e) DOC: AP, p = 0.48, χ 2 = 22.91, RMSEA = 0.01, GFI = 0.92; (f) AN:AP, p = 0.56, χ 2 = 20.24, RMSEA = 0.01, GFI = 0.93, soil texture is assigned according to its clay content; gray lines indicate positive values, and red lines indicate negative values; solid lines indicate statistically significant effects (p < 0.05), and dashed lines indicate statistically insignificant effects; the symbols "*", "**", and "***" indicate p < 0.05, p < 0.01, and p < 0.001, respectively; the p value is used in the chi-square test results to test whether the fit between the model and the observed data is significantly different: P > 0.05 indicates that the difference between the model and the data is not significant, that is, the model fit is good; RMSEA is the root mean square error of approximation, an index for evaluating the model's poor fit; if it is close to 0, it indicates a good fit; GFI is the goodness-of-fit index; the closer it is to 1, the better the fit. DETAILED DESCRIPTION

[0020] To facilitate understanding of the technical implementation methods of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in combination with the technical process steps, specific implementation conditions and materials in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1

[0022] refer to Figure 1 ,In farmland in the plateau lake basin, stratified sampling was carried out according to soil texture and depth (0-20 cm, 20-40 cm, and 40-60 cm), and three replicate samples were collected in each soil layer of loam soil.

[0023] The soil particle size distribution was measured using a laser particle size analyzer to determine the soil texture. The specific results are shown in the attached Figure 2 .

[0024] The soil SOC, TN, TP, DOC, AN and AP contents were measured using a carbon and nitrogen analyzer. The soil C:N:P stoichiometric ratios were calculated, including SOC: TN, SOC: TP, TN: TP, DOC: AN, DOC: AP and AN: AP. The results are shown in the attached Figure 3 Middle (a~f) and attached Figure 4 Middle (a~f).

[0025] Analysis of the effects of soil texture and depth on nutrients The effects of soil texture and depth on the contents of C, N, and P and their stoichiometric ratios were determined by analysis of variance and path analysis. Figure 5 Middle (a~f), attached Figure 6 and attached Figure 7 Middle (a-f). The SOC, TN, TP, DOC, and AN contents of loam soil were higher. The SOC, TP, DOC, and AP contents of deep soil were significantly lower than those of surface soil.

[0026] Precision nutrient management and pollution prevention and control measures: Based on the analysis of soil texture and depth, differentiated fertilization plans are developed. For loamy soils, the carbon, nitrogen, and phosphorus input ratios need to be balanced, with phosphorus controlled and carbon increased to avoid stoichiometric imbalances. For deep soils, slow-release fertilizers and straw return are used to reduce nutrient loss and improve phosphorus utilization. Buffer zones are also established within farmland, with plants that absorb nitrogen and phosphorus efficiently to reduce nutrient loss in surface runoff. Cover crops are used in farmland to reduce soil erosion and nutrient leaching. Precision irrigation is implemented in farmland to minimize water and nutrient loss.

[0027] Example 2

[0028] refer to Figure 1 ,In farmland in the plateau lake basin, stratified sampling was carried out according to soil texture and depth (0-20 cm, 20-40 cm, and 40-60 cm), and three replicate samples were collected in each soil layer of clay loam soil.

[0029] The soil particle size distribution was measured using a laser particle size analyzer to determine the soil texture. The specific results are shown in the attached Figure 2 .

[0030] The soil SOC, TN, TP, DOC, AN and AP contents were measured using a carbon and nitrogen analyzer. The soil C:N:P stoichiometric ratios were calculated, including SOC: TN, SOC: TP, TN: TP, DOC: AN, DOC: AP and AN: AP. The results are shown in the attached Figure 3 Middle (a~f) and attached Figure 4 Middle (a~f).

[0031] Analysis of the effects of soil texture and depth on nutrients The effects of soil texture and depth on C, N, P contents and stoichiometric ratios were determined by variance analysis and path analysis. The results are shown in Tables Figure 5 a~f in the Appendix, and Tables Figure 6 a~f in the Appendix, and Tables Figure 7 a~f in the Appendix. The SOC, TN, TP, DOC, and AN contents were higher in clay loam soil. The SOC, TP, DOC, and AP contents were significantly lower in deep soil than in surface soil.

[0032] Precision nutrient management and pollution prevention measures: Based on the analysis results of soil texture and depth, and considering the characteristics of "high water holding capacity, low permeability, and easy erosion", a differentiated fertilization scheme was developed. For clay loam soil, it is recommended to apply humic acid substances to improve soil structure and reduce the activity of iron oxide to release fixed phosphorus. Slow-release and controlled-release fertilizers should be promoted to reduce nitrogen and phosphorus loss due to concentrated rainfall. The use of biochar organic fertilizers should be increased to improve soil organic matter content and promote nutrient cycling.

[0033] Example 3

[0034] Reference Figure 1 In the farmland of the plateau lake basin, the soil was sampled according to soil texture and depth (0-20 cm, 20-40 cm, 40-60 cm). Three replicate samples were collected for each soil layer in clay loam soil.

[0035] The soil particle size distribution was determined using a laser particle size analyzer to determine the soil texture. The results are shown in Table Figure 2 .

[0036] The SOC, TN, TP, DOC, AN, and AP contents of the soil were determined using a carbon and nitrogen analyzer. The C:N:P stoichiometric ratios of the soil were calculated, including SOC: TN, SOC: TP, TN: TP, DOC: AN, DOC: AP, and AN: AP. The results are shown in Tables Figure 3 a~f in the Appendix, and Tables Figure 4 a~f in the Appendix.

[0037] Analysis of the effects of soil texture and depth on nutrients The effects of soil texture and depth on C, N, P contents and stoichiometric ratios were determined by variance analysis and path analysis. The results are shown in Tables Figure 5 a~f in the Appendix, and Tables Figure 6 a~f in the Appendix, and Tables Figure 7 a~f in the Appendix. The SOC, TN, TP, DOC, and AN contents were higher in clay loam soil. The SOC, TP, DOC, and AP contents were significantly lower in deep soil than in surface soil.

[0038] Precision nutrient management and pollution prevention and control measures: Develop differentiated fertilization plans based on soil texture and depth analysis: For clay soils, deep plowing combined with biochar application can improve permeability, and microbial inoculation can be used to activate soil activity. Straw return and green manure cultivation are encouraged, as well as intercropping practices, where Chinese milk vetch or clover are planted alongside vegetables and other crops. This reduces nutrient loss and improves the utilization of nitrogen and phosphorus fertilizers. Before the rainy season, terraced vegetation belts are designed to slow runoff velocity, extend hydraulic retention time, and promote particulate matter deposition and pollutant adsorption.

[0039] Example 4

[0040] refer to Figure 1 ,In farmland in the plateau lake basin, stratified sampling was carried out according to soil texture and depth (0-20 cm, 20-40 cm, and 40-60 cm), and three replicate samples were collected in each soil layer of sandy soil.

[0041] The soil particle size distribution was measured using a laser particle size analyzer to determine the soil texture. The specific results are shown in the attached Figure 2 .

[0042] The soil SOC, TN, TP, DOC, AN and AP contents were measured using a carbon and nitrogen analyzer. The soil C:N:P stoichiometric ratios were calculated, including SOC: TN, SOC: TP, TN: TP, DOC: AN, DOC: AP and AN: AP. The results are shown in the attached Figure 3 Middle (a~f) and attached Figure 4 Middle (a~f).

[0043] Analysis of the effects of soil texture and depth on nutrients The effects of soil texture and depth on the contents of C, N, and P and their stoichiometric ratios were determined by analysis of variance and path analysis. Figure 5 Middle (a~f), attached Figure 6 and attached Figure 7 Middle (a-f). Sandy soil has a higher AP content. The SOC, TP, DOC, and AP contents in the deep soil are significantly lower than those in the surface soil.

[0044] Precision nutrient management: Based on the analysis results of soil texture and depth, differentiated fertilization plans are formulated: for sandy soil areas, the organic matter content of the sandy soil is increased by applying decomposed cow dung and straw compost as organic fertilizers, 5% biochar is added to enhance water and fertilizer retention to improve the sandy soil structure, cover tillage is promoted, and integrated water and fertilizer technology is implemented to prevent and control carbon and nitrogen loss, and urease inhibitors are deeply applied to curb nitrogen volatilization and wind erosion losses.

[0045] The above "zoning and targeting" measures will be combined with the following management measures during the dry and rainy seasons: During heavy rains: Cover exposed farmland with straw or weed cloth before heavy rainfall to reduce raindrop splash erosion; ditch dredging will be carried out in advance to prevent water from overflowing. During dry periods: Precise water replenishment through drip irrigation systems will prevent flooding that washes away pollutants in clay soils; and clover covering will inhibit soil evaporation. Through a comprehensive strategy of "precise pollution control at the source - multi-level interception during the process - ecological restoration at the end of the process - and long-term management guarantees," we can achieve a synergistic reduction in pollution load and improvement in ecosystem services.

[0046] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A "zoning-targeting" method for controlling farmland nutrients and non-point source pollution, characterized in that: The method comprises the following steps: S1 Soil texture zoning: Using the international soil texture classification standard, the clay content ratio of different soil textures is as follows: clay > 45%, clay loam 30-45%, loam 15-30%, and sand <15%. Farmland soil textures are classified and zoned accordingly. Farmland areas are divided into different management zones based on different soil textures to facilitate differentiated management. S2 Soil sample collection and analysis: In each management area, soil samples were collected from different soil layers using a five-point sampling method. Soil physical and chemical properties were analyzed, including the determination of total organic carbon, total nitrogen, total phosphorus, dissolved organic carbon, available nitrogen (the sum of ammonia nitrogen and nitrate nitrogen, hereinafter referred to as available nitrogen), and available phosphorus content, and the corresponding stoichiometric ratios were calculated. S3 Data Analysis and Model Building: Based on the results of physical and chemical analysis of soil samples, statistical methods are used to analyze the main and interactive effects of soil texture and depth on nutrient content and stoichiometric ratios. Path analysis is used to develop a nutrient management model related to soil texture and depth to predict nutrient flow and circulation patterns in different regions. S4 Targeted Fertilization and Pollution Prevention and Control Strategy Development: Develop targeted fertilization strategies based on soil texture and nutrient requirements, including selecting fertilizer types, application methods, and application rates, controlling the loss of available nitrogen and available phosphorus, and optimizing the stoichiometric ratio of soil carbon, nitrogen, and phosphorus in combination with carbon regulation methods; S5 Long-term soil nutrient management and ecological restoration measures: Develop a long-term soil nutrient restoration plan, including increasing organic matter input, using slow-release fertilizers, returning straw to fields, and optimizing farmland water conservancy facilities; S6 Farmland pollution early warning and optimization adjustment mechanism: Through regular monitoring of different soil types and fertilization effects, and the use of organic matter based on changes in the C, N and P content in the soil, combined with the carbon-nitrogen ratio of soil samples, regular assessment of soil nutrient status and environmental impact is carried out.

2. A "zoning-targeting" method for controlling farmland nutrients and non-point source pollution according to claim 1, characterized in that: The steps of the multi-point sampling method described in S2 are as follows: random sampling is performed at 5 different sampling points with different soil layers of thickness of 0-20 cm, 20-40 cm, and 40-60 cm in each management area.

3. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The method for establishing the nutrient management model described in S3 is: using one-way and two-way analysis of variance and Mantel test methods to analyze the main effects and interaction effects of soil texture and depth on C, N, P content and stoichiometric ratio, and using path analysis to construct a soil texture-depth-nutrient relationship prediction model, which is the nutrient management model.

4. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The steps of the targeted fertilization strategy described in S4 are: adjust the fertilization type according to the stoichiometric ratios of total organic carbon:total nitrogen, total organic carbon:total phosphorus, total nitrogen:total phosphorus, dissolved organic carbon:available nitrogen, dissolved organic carbon:available phosphorus and available nitrogen:available phosphorus in the soil of different regions, and choose the crop growth period with efficient soil nutrient absorption as the time for fertilization.

5. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The long-term soil nutrient management and ecological restoration program described in S5 includes a combination of green manure cultivation and crop rotation. Specific measures include: a. Plant green manure crops such as milk vetch and clover to increase soil organic matter; b. Adopting water-land rotation and bean-straw rotation systems to improve soil structure and microecological environment.

6. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The specific optimization measures for supporting farmland water conservancy facilities described in S5 are: adopting water-saving irrigation methods such as drip irrigation and small-tube spraying.

7. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The farmland pollution early warning and optimization adjustment mechanism described in S6 is specifically to judge the nutrient status of farmland soil based on the soil carbon, nitrogen and phosphorus stoichiometric ratio. When the soil nitrogen and phosphorus ratio is <14, the plants are in a nitrogen-limited state; and a carbon-nitrogen ratio <30 indicates a high risk of nitrate leaching. Then, management measures such as fertilization are implemented according to the specific situation to regulate the nutrients of farmland soil.

8. The method of "zoning-targeting" control of farmland nutrients and non-point source pollution according to claim 1, characterized in that: The organic matter described in S6 is a combination of one or more of humus, biochar natural organic matter, and organic fertilizer processed by microbial fermentation. The amount of chemical fertilizer applied is 30%-75% of the conventional fertilizer amount, and is adjusted according to the degree to which the C:N:P stoichiometric ratio deviates from the threshold.

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