A method and system for coordinated regulation of farmland landscape pattern and water and fertilizer based on carbon flux trade-off mechanism

Abstract

This invention provides a method and system for coordinated regulation of farmland landscape pattern and water and fertilizer management based on a carbon flux trade-off mechanism, relating to the fields of agricultural ecology and low-carbon land management technology. The method includes: acquiring geographical and agricultural management data of the target area; calculating the quantitative index of carbon effect in the target area based on a pre-set empirical model of multiple regression of farmland carbon sinks and carbon emissions; analyzing the driving relationship between farmland landscape pattern index and water and fertilizer management parameters on the quantitative index of carbon effect, identifying key driving factors and their positive and negative effects, and determining the trade-off between carbon sinks and carbon emissions; and generating a coordinated regulation scheme by adjusting the farmland landscape pattern index and matching corresponding water and fertilizer management strategies. This invention utilizes an empirical model to accurately simulate changes in carbon effect under different management measures, overcoming the problem of insufficient accuracy in traditional inventory methods that rely on statistical coefficients, and realizing the transformation of farmland from "high emissions and low carbon sequestration" to "emission reduction and carbon sink increase."

Description

Technical Field

[0001] This invention relates to the fields of agricultural ecology and low-carbon land management technology, and in particular to a method and system for the coordinated regulation of arable land landscape patterns and water and fertilizer based on a carbon flux trade-off mechanism. Background Technology

[0002] Against the backdrop of increasingly severe global climate change, reducing greenhouse gas emissions and enhancing carbon sequestration capacity have become an international consensus. As the core of the agricultural ecosystem, arable land has the dual attributes of "carbon source" and "carbon sink": on the one hand, crops convert carbon dioxide into soil organic carbon (SOC) through photosynthesis, demonstrating huge carbon sequestration potential; on the other hand, agricultural activities such as fertilizer application, rice cultivation, and irrigation are important sources of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions.

[0003] However, existing farmland management and remediation measures often tend to prioritize production over ecology, lacking a systematic consideration of carbon effects. This limitation leads to significant trade-offs: for example, while returning straw to the field can increase soil organic carbon, it may induce a surge in methane emissions under certain irrigation conditions; while excessive concentration of farmland landscapes is beneficial for mechanized operations, it may weaken the stability of carbon sink functions due to reduced biodiversity.

[0004] Current technological bottlenecks lie in the fact that related research is mostly limited to single factors (such as focusing solely on fertilization or land use), lacking quantitative assessment and synergistic regulation methods that combine macro-landscape patterns with micro-level water and fertilizer management. Traditional carbon accounting methods mainly rely on statistical data and emission coefficients, lacking plot-level precision and making it difficult to accurately guide field practices. Given the significant differences in climate, soil, and topography among different agricultural areas, how to construct a quantitative synergistic regulation method that comprehensively considers multi-dimensional environmental factors and is based on a carbon flux trade-off mechanism to balance the relationship between carbon sinks and carbon emissions is a key technical problem that urgently needs to be solved. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a method and system for the coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism. This method constructs a high-precision empirical model based on field observation data from Southeast China, systematically quantifies the comprehensive impact of farmland landscape patterns and water and fertilizer management measures on carbon effects, and then proposes targeted regulation strategies through carbon flux trade-off mechanism analysis, ultimately achieving the coordinated development of improved agricultural production efficiency and ecosystem protection. The technical solution is as follows:

[0006] This invention provides a method for coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, comprising:

[0007] Obtain geographic and agricultural management data for the target area; the geographic and agricultural management data includes: soil physicochemical properties data, topographic data, meteorological and climatic data, cultivated land landscape pattern index, and water and fertilizer management parameters;

[0008] Based on the aforementioned geographical and agricultural management data, and using a pre-defined empirical model for multiple regression of arable land carbon sinks and carbon emissions, the carbon effect quantitative indicators for the target area are calculated and obtained. These carbon effect quantitative indicators include: annual change in soil organic carbon, carbon dioxide emissions, methane emissions, and nitrous oxide emissions.

[0009] Based on the obtained farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index is analyzed, and the key driving factors and positive and negative effects affecting the carbon effect quantification index are identified; based on the key driving factors and positive and negative effects, the trade-off between carbon sink and carbon emission is determined.

[0010] Based on the established trade-off between carbon sinks and carbon emissions, a scheme for coordinated regulation of arable land landscape pattern and water and fertilizer is generated by adjusting the arable land landscape pattern index to optimize spatial layout and matching corresponding water and fertilizer management strategies.

[0011] Optionally, the soil physicochemical property data include: soil type coefficient, soil pH, soil clay content, and soil bulk density;

[0012] The topographic data includes: farmland slope;

[0013] The meteorological and climate data include: annual rainfall, average daily rainfall, annual average temperature, and daily average temperature;

[0014] The cultivated land landscape pattern index includes: cultivated land landscape proportion, cultivated land concentration, and cultivated land aggregation.

[0015] The parameters for water and fertilizer management measures include: carbon content of straw returned to the field, nitrogen content of straw returned to the field, nitrogen content of chemical fertilizer, carbon content of green manure, carbon content of farmyard manure, irrigation type coefficient, cultivated land type coefficient, and rice growth period.

[0016] Optionally, the calculation model for the annual change in soil organic carbon (SOC / y) is shown in equation (1) below:

[0017]

[0018] in, The carbon content of straw returned to the field, This refers to the nitrogen content of fertilizers. The carbon content of green manure. The carbon content of farmyard manure. For farmland slope, For the proportion of cultivated land to landscape, For farmland concentration, For the degree of aggregation of arable land, Annual rainfall Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

[0019] Optionally, the calculation model for the carbon dioxide emissions (CO2) is shown in equation (2) below:

[0020]

[0021] in, The carbon content of straw returned to the field, Soil pH For farmland concentration, This represents the average daily rainfall. The average annual temperature Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

[0022] Optionally, the calculation model for the methane emissions (CH4) is shown in equation (3) below:

[0023]

[0024] in, This represents the logarithm of methane emissions. The carbon content of straw returned to the field, The nitrogen content of straw returned to the field, The average daily temperature This represents the average daily rainfall. The clay content of the soil, For the proportion of cultivated land to landscape, It is the rice growing season. For irrigation type coefficient, to , These are the model coefficients.

[0025] Optionally, the calculation model for the nitrous oxide emission N2O is shown in equation (4) below:

[0026]

[0027] in, This refers to the nitrogen content of fertilizers. For soil bulk density, Soil pH The average daily temperature The clay content of the soil, Annual rainfall For irrigation type coefficient, to , These are the model coefficients.

[0028] Optionally, the optimization of spatial layout by adjusting the cultivated land landscape pattern index includes at least one of the following measures:

[0029] (1) Adjust the degree of farmland aggregation to the preset aggregation threshold;

[0030] (2) Adjust the concentration of cultivated land to the preset concentration threshold;

[0031] (3) Set up vegetation buffer zones at the edges of concentrated and contiguous areas of cultivated land;

[0032] (4) Introduce non-arable land ecological patches into the arable land landscape, the ecological patches including forest patches and wetland patches.

[0033] Optionally, the matching of appropriate water and fertilizer management strategies includes at least one of the following measures:

[0034] (1) For paddy field areas, a wet irrigation mode is adopted;

[0035] (2) Based on the determined trade-off between carbon sink and carbon emissions, adjust the carbon content of straw returned to the field, nitrogen content of straw returned to the field and carbon content of green manure in the parameters of water and fertilizer management measures to control the annual change in soil organic carbon.

[0036] (3) Based on the determined trade-off between carbon sink and carbon emissions, adjust the amount of nitrogen fertilizer applied according to the wet irrigation mode to control the amount of nitrous oxide emissions.

[0037] Optionally, the generated farmland landscape pattern and water and fertilizer synergistic regulation scheme also includes constructing a specific ecological restoration model based on the topographic features of the target area;

[0038] The specific ecological restoration model constructed by combining the topographic features of the target area includes at least one of the following measures:

[0039] (1) For contiguous plain areas, merge adjacent farmland patches and set up ecological ditches and woodland patches at the edges of farmland;

[0040] (2) For hilly and mountainous areas, the cultivated land is set up in the form of terraces, deep-rooted trees are planted at the boundaries of the terraces, and crops are planted under the trees.

[0041] This invention also provides a system for coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, comprising:

[0042] The data acquisition module is used to acquire geographical and agricultural management data of the target area; the geographical and agricultural management data includes: soil physicochemical properties data, topographic data, meteorological and climate data, cultivated land landscape pattern index and water and fertilizer management parameters;

[0043] The carbon effect quantification assessment module is used to calculate and obtain the carbon effect quantification indicators of the target area based on the geographical and agricultural management data and a preset empirical model of multiple regression of arable land carbon sink and carbon emissions. The carbon effect quantification indicators include: annual change in soil organic carbon, carbon dioxide emissions, methane emissions, and nitrous oxide emissions.

[0044] The carbon flux trade-off mechanism analysis module is used to analyze the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index, based on the acquired farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, to identify the key driving factors affecting the carbon effect quantification index and their direction of influence; and to determine the trade-off relationship between carbon sink and carbon emissions based on the key driving factors and their direction of influence.

[0045] The coordinated regulation scheme generation module is used to generate a coordinated regulation scheme for arable land landscape pattern and water and fertilizer based on the determined trade-off between carbon sink and carbon emission, by adjusting the arable land landscape pattern index to optimize spatial layout and matching corresponding water and fertilizer management strategies.

[0046] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0047] (1) Quantitative and precise assessment: This invention provides a set of empirical multiple regression models (R²) for arable land carbon sinks and carbon emissions based on measured data. 2 The model (with a square value between 0.453 and 0.722) can accurately quantify the specific contributions of soil properties, climate conditions, landscape pattern indices, and agricultural management practices to soil organic carbon, carbon dioxide, methane, and nitrous oxide. It can simulate the changes in carbon effects under different management practices more accurately, overcoming the problem of insufficient accuracy of traditional inventory methods that rely on statistical coefficients.

[0048] (2) Synergistic Effect: This study reveals the coupling mechanism between landscape pattern and water and fertilizer management, breaking the limitations of single measures that are ineffective. For the first time, it incorporates macro-level farmland landscape pattern and micro-level water and fertilizer management measures into a unified analytical framework. By identifying the "sinking-emission" trade-off factors and the "CH4-N2O" emission trade-off mechanism, targeted synergistic regulation strategies are proposed. For example, by combining "wet irrigation" with "nitrogen-controlled fertilization," the contradiction between methane emission reduction and nitrous oxide control is effectively balanced. By optimizing the landscape pattern (increasing aggregation and controlling concentration), the intensity of greenhouse gas emissions is reduced while improving soil carbon sink capacity, truly achieving "emission reduction without production reduction, and increased sinking and efficiency."

[0049] (3) Guiding Land Consolidation: In response to the common problem of "merging small fields into large fields" in the current comprehensive land consolidation, which leads to excessive concentration and fragmentation of arable land and ecological landscape, this invention introduces landscape diversity constraint indicators. By setting specific optimization thresholds for the proportion, aggregation degree, and concentration of arable land landscape, it guides the construction of a mosaic ecological landscape pattern that is "contiguous but not excessively concentrated." This not only facilitates mechanized operations and large-scale management, but also prevents soil carbon loss and ecological function degradation caused by excessive intensification by preserving ecological patches such as field ridges and ditch buffer zones. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 This is a flowchart illustrating the method for coordinated regulation of farmland landscape pattern and water and fertilizer based on carbon flux trade-off mechanism provided in this embodiment of the invention.

[0052] Figure 2 This is a comparison chart of the sample point distribution and carbon effect simulation results in the study area provided by the embodiments of the present invention;

[0053] Figure 3 This is a schematic diagram illustrating the trade-off between methane and nitrous oxide emissions under different irrigation methods provided in embodiments of the present invention.

[0054] Figure 4 Distribution map of changes in soil organic carbon in cultivated land in an agricultural county in 2022;

[0055] Figure 5 Distribution map of carbon dioxide emissions from arable land in an agricultural county in 2022;

[0056] Figure 6 Distribution map of methane emissions from paddy fields in an agricultural county in 2022;

[0057] Figure 7 Distribution map of nitrous oxide emissions from cultivated land in a certain agricultural county in 2022. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0059] Example 1

[0060] This invention provides a method for the coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, applied to a typical agricultural county in the hilly region of southeastern China (hereinafter referred to as the "target area"). Figure 1 As shown, the method includes the following steps:

[0061] Step S1: Obtain geographic and agricultural management data for the target area; geographic and agricultural management data include: soil physicochemical properties data, topographic data, meteorological and climate data, farmland landscape pattern index, and water and fertilizer management parameters.

[0062] Soil physicochemical properties data include: soil type coefficient, soil pH, soil clay content, and soil bulk density;

[0063] Topographic data includes: farmland slope;

[0064] Meteorological and climate data include: annual rainfall, average daily rainfall, average annual temperature, and average daily temperature;

[0065] The cultivated land landscape pattern index includes: cultivated land landscape ratio, cultivated land concentration, and cultivated land aggregation.

[0066] The parameters for water and fertilizer management measures include: carbon content of straw returned to the field, nitrogen content of straw returned to the field, nitrogen content of chemical fertilizer, carbon content of green manure, carbon content of farmyard manure, irrigation type coefficient, cultivated land type coefficient, and rice growth period.

[0067] Specifically, the above data is obtained through the following methods:

[0068] First, acquire land use data (10m resolution), Landsat remote sensing imagery (30m resolution), digital elevation model (DEM) data (30m resolution), and soil type data for the target area. Combining the land use data, calculate the proportion of cultivated land landscape, cultivated land concentration, and cultivated land aggregation in the target area, and calculate the elevation and slope of the cultivated land.

[0069] Based on the soil survey data, a soil type distribution map was obtained, and the soil pH, soil clay content, and soil bulk density (BD) of each sampling point were extracted.

[0070] Secondly, acquire meteorological data from remote sensing monitoring, including annual rainfall (Pre), average daily rainfall, annual average temperature (T), and daily average temperature.

[0071] Finally, through field surveys and statistical yearbooks, the carbon content of straw returned to the field (S_C), nitrogen content of straw returned to the field (S_N), nitrogen content of chemical fertilizer (M_N), carbon content of green manure (G_C), and carbon content of farmyard manure (A_C) in the target area were obtained. For paddy fields, the rice growing season (len) and irrigation type (Ir) (such as continuous irrigation, intermittent irrigation, or wet irrigation) were recorded.

[0072] For example, we can obtain economic development data such as energy consumption and fertilizer application in a typical agricultural county in the hilly region of southeastern China for a given year. In that year, the county used 9,488 tons of pure agricultural fertilizer. Based on the proportion of nitrogen fertilizer in the total fertilizer, this amounts to approximately 2,546 tons of pure nitrogen fertilizer, of which approximately 1,018 tons are nitrogen fertilizer (assuming a nitrogen content of 40%). The amount of straw directly returned to the field was 122,200 tons, accounting for 95.33%, with an indirect utilization rate of 1.1%, which is negligible. Straw carbon accounts for an average of 46% of its dry weight, with the specific content fluctuating between 40% and 50% depending on the crop type; therefore, the straw carbon equivalent is 61,100 tons. Since the indirect utilization of straw is very small, green manure is negligible. According to statistical yearbooks, the main paddy field crop in this agricultural county is late-season rice, accounting for over 95%. Therefore, methane calculations are based on the late-season rice of that year, which is sown approximately in June and harvested in October, with a growing season of approximately 120 days. According to data on crop straw utilization in a certain agricultural county, approximately 41,975 tons of straw were utilized from late-season rice, equivalent to 18,888 tons of biochar. Based on the nitrogen content of crop straw being approximately 0.5%-0.8%, this translates to 315 tons of biogenic nitrogen.

[0073] Step S2: Based on geographical and agricultural management data, and using a pre-set empirical model of multiple regression of arable land carbon sinks and carbon emissions, calculate and obtain the quantitative indicators of carbon effects in the target area. The quantitative indicators of carbon effects include: annual change in soil organic carbon, carbon dioxide emissions, methane emissions, and nitrous oxide emissions.

[0074] In this step, the data obtained in step S1 is substituted into a pre-built multivariate regression empirical model to quantitatively assess the carbon effect in the target region.

[0075] Specifically, the calculation model for the annual change in soil organic carbon (SOC / y) is shown in equation (1) below:

[0076]

[0077] in, The carbon content of straw returned to the field, This refers to the nitrogen content of fertilizers. The carbon content of green manure. The carbon content of farmyard manure. For farmland slope, For the proportion of cultivated land to landscape, For farmland concentration, For the degree of aggregation of arable land, Annual rainfall Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

[0078] For example, the coefficients of the calculation model for the annual change in soil organic carbon (SOC / y) in an agricultural county are shown in Table 1 below.

[0079] Table 1. Coefficients of the Soil Carbon Sequestration Model for Cultivated Land

[0080]

[0081] The calculation model for carbon dioxide emissions (CO2) is shown in equation (2) below:

[0082]

[0083] in, The carbon content of straw returned to the field, Soil pH For farmland concentration, This represents the average daily rainfall. The average annual temperature Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

[0084] For example, the coefficients of the calculation model for carbon dioxide emissions (CO2) in a certain agricultural county are shown in Table 2 below.

[0085] Table 2. Model Coefficients for Carbon Dioxide Emissions from Cultivated Land

[0086]

[0087] The calculation model for methane emissions (CH4) is shown in equation (3) below:

[0088]

[0089] in, This represents the logarithm of methane emissions. The carbon content of straw returned to the field, The nitrogen content of straw returned to the field, The average daily temperature This represents the average daily rainfall. The clay content of the soil, For the proportion of cultivated land to landscape, It is the rice growing season. For irrigation type coefficient, to , These are the model coefficients.

[0090] For example, the coefficients of the calculation model for CH4 methane emissions in a certain agricultural county are shown in Table 3 below.

[0091] Table 3. Model Coefficients for Methane Emissions from Cultivated Land

[0092]

[0093]

[0094] The calculation model for nitrous oxide emissions (N2O) is shown in equation (4) below:

[0095]

[0096] in, This refers to the nitrogen content of fertilizers. For soil bulk density, Soil pH The average daily temperature The clay content of the soil, Annual rainfall For irrigation type coefficient, to , These are the model coefficients.

[0097] For example, the coefficients of the calculation model for nitrous oxide (N2O) emissions in a certain agricultural county are shown in Table 4 below.

[0098] Table 4. Model Coefficients for Nitrous Oxide Emissions from Cultivated Land

[0099]

[0100] Result evaluation:

[0101] (1) Assessment of annual variation in soil organic carbon (SOC / y): such as Figure 4As shown, the SOC / y ratio in a certain agricultural county exhibits significant spatial differences: the red areas indicate severe SOC / y loss, concentrated mainly in the southern and western parts. These areas require close attention, and further SOC / y loss should be mitigated through strengthened soil and water conservation and soil management. The green areas represent relatively stable SOC / y, primarily distributed in the central and eastern plains, indicating proper agricultural management and good soil structure in these regions.

[0102] (2) Greenhouse gas assessment: such as Figure 5-7 As shown, the central part of cultivated land produces more carbon dioxide, indicating that the concentration of cultivated land exacerbates carbon emissions. In the central and northern areas of a certain agricultural county, cultivated land carbon dioxide emissions are high, reaching 400-450 ppm. Methane emissions are concentrated in the southern and eastern regions within the range of 10-20 kg / ha (green to light green area). Areas with moderate methane emissions (20-40 kg / ha) are widely distributed in the central and northern regions. High emission areas (50-100 kg / ha) are mainly concentrated in the northern part of the map and some localized areas. Nitrous oxide emissions are concentrated in parts of the southeast and west, with emissions reaching 2.4 kg / ha in the southeast. Relatively low emission areas are mainly located in the north and northwest.

[0103] Step S3: Based on the obtained farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, analyze the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index, identify the key driving factors and positive and negative effects affecting the carbon effect quantification index; and determine the trade-off between carbon sink and carbon emission based on the key driving factors and positive and negative effects.

[0104] In this step, based on the calculation results and model coefficients of step S2, a trade-off mechanism analysis is performed:

[0105] Based on the analysis results of the carbon flux trade-off mechanism, the embodiments of the present invention first identified the carbon sink-emissions trade-off factor.

[0106] Analysis shows that both the carbon content of straw returned to the field and the nitrogen content of chemical fertilizers exhibit a typical "dual carbon effect": the regression coefficients of both on the annual change in soil organic carbon (SOC / y) are positive, indicating that they can effectively promote soil carbon sequestration; however, at the same time, their coefficients on greenhouse gas emissions (CH4 or N2O) are also significantly positive. Specifically, straw, as an exogenous organic carbon input, increases the soil carbon pool, but also provides substrates for anaerobic decomposition by microorganisms, thus leading to increased methane emissions; while nitrogen fertilizer, although indirectly increasing soil carbon accumulation by promoting crop growth and returning residues, significantly enhances nitrous oxide emissions by increasing the substrates available for nitrification and denitrification in the soil. Therefore, straw return to the field and nitrogen fertilizer application are both typical sink-emission trade-off factors. In contrast, green manure and farmyard manure both show significant positive effects on SOC / y and do not show obvious emission-increasing characteristics, belonging to benign management factors that mainly increase sinks.

[0107] In terms of landscape pattern, the proportion of cultivated land in the landscape (Pl) is positive for SOC / y but negative for the logarithm of methane emissions (LnCH4), indicating that an increased proportion of cultivated land in the landscape is beneficial for both soil carbon accumulation and reduction of methane emissions. This means that a higher proportion and more complete distribution of cultivated land in the landscape may improve farming conditions and hydrothermal patterns, while reducing anaerobic environments caused by long-term flooding or fragmentation. The proportion of cultivated land in the landscape is one of the few factors that simultaneously exhibits a "synergistic effect of carbon sequestration and emission reduction," making it a relatively optimal spatial pattern regulation indicator. The concentration of cultivated land (AI) is negative for SOC / y but positive for CO2, indicating that the more concentrated the cultivated land, the weaker the soil carbon sequestration capacity and the stronger the carbon dioxide emissions. This suggests that while excessive concentration and contiguous areas are beneficial for large-scale operations, they may also increase farming intensity, disturbance frequency, and organic matter mineralization rate, thereby exacerbating CO2 release and weakening SOC / y accumulation. Therefore, the concentration of cultivated land is a typical carbon sequestration reduction-emission increase factor, suggesting that land consolidation should not simply pursue concentrated and contiguous areas, but should also consider ecological buffering and landscape optimization. Cultivated land aggregation degree (Cl) has a significant positive effect on SOC / y, indicating that the more intact and less fragmented the cultivated land patches, the more conducive it is to soil carbon accumulation. Although cultivated land aggregation degree does not appear directly in the emission model, from the perspective of carbon sink, it belongs to the category of landscape factors that enhance carbon sequestration. Unlike cultivated land concentration, aggregation degree emphasizes patch integrity rather than simply high-intensity concentration, therefore its ecological effect is more positive.

[0108] Secondly, the gas emission trade-off mechanism in irrigation methods was identified. For example... Figure 3As shown, the irrigation type coefficient analysis, as the most typical trade-off factor, reveals that compared to continuous irrigation, wet irrigation has a significantly negative CH4 emission coefficient, indicating a significant inhibition of methane emissions, but a significantly positive N2O emission coefficient, indicating a significant increase in nitrous oxide emissions. Intermittent irrigation falls somewhere in between. This reveals the crucial regulatory role of soil redox state in the carbon and nitrogen cycle: long-term flooding favors methanogenic bacteria activity but inhibits nitrification, while drainage and aeration have the opposite effect. Therefore, irrigation methods exhibit the most obvious CH4-N2O trade-off mechanism.

[0109] Based on the above analysis, this study identified the key trade-offs in the target area: namely, the trade-off between straw and nitrogen fertilizer input in terms of carbon sequestration and emissions, the trade-off between methane and nitrous oxide emissions in irrigation management, and the risk of concentrated carbon sink loss in landscape patterns. The identification of these key trade-offs provides a scientific basis for subsequently developing differentiated and coordinated regulation strategies.

[0110] Step S4: Based on the established trade-off between carbon sinks and carbon emissions, optimize the spatial layout by adjusting the farmland landscape pattern index and matching corresponding water and fertilizer management strategies to generate a farmland landscape pattern and water and fertilizer synergistic regulation scheme.

[0111] This step specifically includes at least one of the following control measures:

[0112] (1) Regarding the transformation of arable land types, for areas with high methane emissions and significant continuous flooding, the transformation of some low-yield paddy fields to dry land or a "rice-dryland rotation" model can be promoted. For example, according to model calculations, although paddy fields can increase soil organic carbon (SOC) by 1.953 compared to dry land, they will also increase carbon dioxide emissions by an additional 12.74. In view of this, it is recommended to transform about 10% to 15% of inefficient paddy fields in high-emission risk areas into dry land or rotation land, thereby effectively reducing the overall greenhouse gas emission intensity while retaining some carbon sink advantages. For the core paddy field areas that are retained, it is not advisable to take simple measures to withdraw paddy fields, but rather to combine them with subsequent irrigation system reforms to achieve the synergistic goal of "stable production and emission reduction".

[0113] (2) Regarding landscape pattern optimization, a strategy should be adopted to simultaneously increase the proportion and aggregation of cultivated land to the landscape while avoiding excessive concentration. Specifically, the aggregation degree of cultivated land (Cl) should be adjusted to a preset high threshold to promote soil organic carbon accumulation; at the same time, the concentration degree of cultivated land (AI) should be controlled within a preset range to avoid increased carbon emissions caused by excessive contiguous areas. For example, model analysis results show that for every unit increase in the proportion of cultivated land to the landscape, soil organic carbon increases by 0.02347, while the logarithm of methane emissions (LnCH4) decreases by 0.01041; for every unit increase in the aggregation degree of cultivated land, soil organic carbon increases by 28.59. Conversely, for every unit increase in the concentration degree of cultivated land, soil organic carbon decreases by 0.3090, while carbon dioxide emissions increase by 2.281. Based on this, it is recommended that during land consolidation, the aggregation degree of cultivated land be increased by 5% to 10%, the proportion of landscape be increased by 3% to 5%, and the increase in concentration degree be controlled within 5%.

[0114] In practical implementation, a landscape pattern that is "contiguous but not excessively concentrated" can be constructed by preserving field ridges, ditch buffer zones, and small ecological patches. For example, in contiguous plain areas, "small fields are merged into large fields" for land reclamation, but vegetation buffer zones are set up at the edges of the fields, and woodland and wetland patches are introduced to construct an "arable land-forest-wetland" mosaic pattern, thereby reducing the emission intensity in areas with an excessively high proportion of landscape. In hilly and mountainous areas, arable land is terraced to conserve water and soil; deep-rooted trees are planted at the boundaries of the terraces, and diversified planting is carried out below the trees to construct a "planting-nurturing-forest" composite ecological pattern.

[0115] (3) Regarding the coordinated regulation of water and fertilizer, a quantitative management strategy of "controlling nitrogen and increasing carbon" should be implemented. Based on the risk of increased nitrous oxide emissions under wet irrigation, the amount of nitrogen applied by chemical fertilizer (M_N) should be dynamically adjusted. Specifically, the incremental emission of nitrous oxide should be calculated according to the model coefficients, and the amount of nitrogen applied by chemical fertilizer should be reduced accordingly to balance the incremental emission of nitrous oxide. At the same time, the carbon content of straw returned to the field and the carbon content of green manure should be adjusted to maximize the annual change of soil organic carbon while controlling the risk of methane emissions. For example, the model analysis results show that for every 1 unit increase in chemical fertilizer nitrogen, soil organic carbon increases by 0.000267, but nitrous oxide emissions increase by 0.005241, and its emission increase effect is significantly stronger than its sinking effect; while for every 1 unit increase in green manure carbon and farmyard manure carbon, soil organic carbon increases by 0.000223 and 0.000047, respectively. Based on this, it is recommended to reduce the amount of chemical fertilizer nitrogen application by 10% to 20% on the existing basis, and replace 20% to 30% of it with green manure and farmyard manure. In addition, soil testing and formula fertilization and multiple fertilization should be promoted in high nitrogen input areas to increase nitrogen fertilizer utilization rate to more than 40%, thereby reducing nitrous oxide emissions while maintaining the accumulation of soil organic carbon.

[0116] (4) Regarding irrigation reform, for paddy fields, the continuous flooding pattern should be adjusted to intermittent or wet irrigation to significantly reduce methane emissions. For example, model analysis results show that compared with continuous irrigation, wet irrigation can reduce the logarithm of methane emissions (LnCH4) by 2.356, but will lead to an increase in nitrous oxide emissions by 2.176; intermittent irrigation increases nitrous oxide emissions by 0.700, and its inhibitory effect on methane is weaker than that of wet irrigation. Accordingly, it is recommended to prioritize the promotion of "shallow wet intermittent irrigation" in ordinary paddy fields, and implement drainage and flood control in the middle and late stages of crop growth to reduce the number of days of continuous flooding by 30% to 50%; for fields with high methane emissions, wet irrigation can be promoted, but the amount of nitrogen fertilizer applied should be reduced by more than 10% at the same time to offset the risk of increased nitrous oxide emissions. The overall goal is to control the reduction of methane emissions to more than 30%, while limiting the increase in nitrous oxide emissions to within 10% to 15%.

[0117] (5) Regarding straw management, the principles of "appropriate amount of straw returned to the field, well-rotted straw returned to the field, and straw returned to the field in designated areas" should be adhered to. For example, model analysis results show that for every unit increase in straw carbon, soil organic carbon increases by 0.000067, but carbon dioxide emissions increase by 0.001076 and the logarithm of methane emissions (LnCH4) increases by 0.000518. This indicates that straw return to the field is a typical factor that "increases carbon sequestration but increases emissions." Accordingly, it is recommended that the proportion of straw directly returned to the field be controlled at 50% to 70%, with the remainder used for off-field carbonization, feed production, or substrate utilization. For areas where straw return is required, composting agents and deep plowing measures should be used in conjunction to shorten the straw decomposition cycle by 20% to 30%. Especially in paddy fields, high-intensity direct return of fresh straw should be strictly avoided to effectively reduce methane emission peaks.

[0118] Through the above steps, this embodiment realizes a closed-loop process from data acquisition, carbon effect quantification, trade-off mechanism analysis to the generation of collaborative control schemes, effectively solving the conflict between carbon sinks and carbon emissions in agricultural production.

[0119] Example 2

[0120] This invention provides a system for the coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, used to implement the method of Embodiment 1. The system includes:

[0121] The data acquisition module is used to acquire geographic and agricultural management data for the target area. The geographic and agricultural management data includes: soil physicochemical properties data, topographic data, meteorological and climate data, farmland landscape pattern index, and water and fertilizer management parameters.

[0122] The carbon effect quantification assessment module is used to calculate and obtain the carbon effect quantification indicators of the target area based on geographical and agricultural management data and a preset empirical model of multiple regression of arable land carbon sink and carbon emissions. The carbon effect quantification indicators include: annual change of soil organic carbon, carbon dioxide emissions, methane emissions and nitrous oxide emissions.

[0123] The carbon flux trade-off mechanism analysis module is used to analyze the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index, based on the acquired farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, to identify the key driving factors affecting the carbon effect quantification index and their direction of influence; and to determine the trade-off relationship between carbon sink and carbon emissions based on the key driving factors and their direction of influence.

[0124] The coordinated regulation scheme generation module is used to generate a coordinated regulation scheme for arable land landscape pattern and water and fertilizer based on the determined trade-off between carbon sink and carbon emission, by adjusting the arable land landscape pattern index to optimize spatial layout and matching corresponding water and fertilizer management strategies.

[0125] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, characterized in that, include: Acquire geographic and agricultural management data for the target area; The geographical and agricultural management data include: soil physicochemical properties data, topographic and geomorphological data, meteorological and climatic data, cultivated land landscape pattern index, and parameters of water and fertilizer management measures; Based on the aforementioned geographical and agricultural management data, and using a pre-defined empirical model for multiple regression of arable land carbon sinks and carbon emissions, the carbon effect quantitative indicators for the target area are calculated and obtained. These carbon effect quantitative indicators include: annual change in soil organic carbon, carbon dioxide emissions, methane emissions, and nitrous oxide emissions. Based on the obtained farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index is analyzed, and the key driving factors and positive and negative effects affecting the carbon effect quantification index are identified; based on the key driving factors and positive and negative effects, the trade-off between carbon sink and carbon emission is determined. Based on the established trade-off between carbon sinks and carbon emissions, a scheme for coordinated regulation of arable land landscape pattern and water and fertilizer is generated by adjusting the arable land landscape pattern index to optimize spatial layout and matching corresponding water and fertilizer management strategies.

2. The method according to claim 1, characterized in that, The soil physicochemical properties data include: soil type coefficient, soil pH, soil clay content, and soil bulk density; The topographic data includes: farmland slope; The meteorological and climate data include: annual rainfall, average daily rainfall, annual average temperature, and daily average temperature; The cultivated land landscape pattern index includes: cultivated land landscape proportion, cultivated land concentration, and cultivated land aggregation. The parameters for water and fertilizer management measures include: carbon content of straw returned to the field, nitrogen content of straw returned to the field, nitrogen content of chemical fertilizer, carbon content of green manure, carbon content of farmyard manure, irrigation type coefficient, cultivated land type coefficient, and rice growth period.

3. The method according to claim 2, characterized in that, The calculation model for the annual change in soil organic carbon (SOC / y) is shown in the following equation (1): ； in, The carbon content of straw returned to the field, This refers to the nitrogen content of fertilizers. The carbon content of green manure. The carbon content of farmyard manure. For the slope of farmland, For the proportion of cultivated land to landscape, For farmland concentration, For the degree of aggregation of arable land, Annual rainfall Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

4. The method according to claim 2, characterized in that, The calculation model for carbon dioxide emissions (CO2) is shown in equation (2) below: ； in, The carbon content of straw returned to the field, Soil pH For farmland concentration, This represents the average daily rainfall. The average annual temperature Soil type coefficient, This is the coefficient for cultivated land type. to , These are the model coefficients.

5. The method according to claim 2, characterized in that, The calculation model for the methane emissions (CH4) is shown in equation (3) below: ； in, This represents the logarithm of methane emissions. The carbon content of straw returned to the field, The nitrogen content of straw returned to the field, The average daily temperature This represents the average daily rainfall. The clay content of the soil, For the proportion of cultivated land to landscape, It is the rice growing season. For irrigation type coefficient, to , These are the model coefficients.

6. The method according to claim 2, characterized in that, The calculation model for the nitrous oxide emission N2O is shown in the following equation (4): ； in, This refers to the nitrogen content of fertilizers. For soil bulk density, Soil pH The average daily temperature The clay content of the soil, Annual rainfall For irrigation type coefficient, to , These are the model coefficients.

7. The method according to claim 2, characterized in that, The method of optimizing spatial layout by adjusting the cultivated land landscape pattern index includes at least one of the following measures: (1) Adjust the degree of farmland aggregation to the preset aggregation threshold; (2) Adjust the concentration of cultivated land to the preset concentration threshold; (3) Set up vegetation buffer zones at the edges of concentrated and contiguous areas of cultivated land; (4) Introduce non-arable land ecological patches into the arable land landscape, the ecological patches including forest patches and wetland patches.

8. The method according to claim 2, characterized in that, The matching water and fertilizer management strategy includes at least one of the following measures: (1) For paddy field areas, a wet irrigation mode is adopted; (2) Based on the determined trade-off between carbon sink and carbon emissions, adjust the carbon content of straw returned to the field, nitrogen content of straw returned to the field and carbon content of green manure in the parameters of water and fertilizer management measures to control the annual change in soil organic carbon. (3) Based on the determined trade-off between carbon sink and carbon emissions, adjust the amount of nitrogen fertilizer applied according to the wet irrigation mode to control the amount of nitrous oxide emissions.

9. The method according to claim 2, characterized in that, The proposed scheme for generating farmland landscape patterns and coordinating water and fertilizer regulation also includes constructing specific ecological restoration models based on the topographic features of the target area. The specific ecological restoration model constructed by combining the topographic features of the target area includes at least one of the following measures: (1) For contiguous plain areas, merge adjacent farmland patches and set up ecological ditches and woodland patches at the edges of farmland; (2) For hilly and mountainous areas, the cultivated land is set up in the form of terraces, deep-rooted trees are planted at the boundaries of the terraces, and crops are planted under the trees.

10. A system for coordinated regulation of farmland landscape patterns and water and fertilizer management based on a carbon flux trade-off mechanism, characterized in that, include: The data acquisition module is used to acquire geographical and agricultural management data for the target area; The geographical and agricultural management data include: soil physicochemical properties data, topographic and geomorphological data, meteorological and climatic data, cultivated land landscape pattern index, and parameters of water and fertilizer management measures; The carbon effect quantification assessment module is used to calculate and obtain the carbon effect quantification indicators of the target area based on the geographical and agricultural management data and a preset empirical model of multiple regression of arable land carbon sink and carbon emissions. The carbon effect quantification indicators include: annual change in soil organic carbon, carbon dioxide emissions, methane emissions, and nitrous oxide emissions. The carbon flux trade-off mechanism analysis module is used to analyze the driving relationship between the farmland landscape pattern index and water and fertilizer management parameters on the carbon effect quantification index, based on the acquired farmland landscape pattern index and water and fertilizer management parameters, combined with the calculated carbon effect quantification index, to identify the key driving factors affecting the carbon effect quantification index and their direction of influence; and to determine the trade-off relationship between carbon sink and carbon emissions based on the key driving factors and their direction of influence. The coordinated regulation scheme generation module is used to generate a coordinated regulation scheme for arable land landscape pattern and water and fertilizer based on the determined trade-off between carbon sink and carbon emission, by adjusting the arable land landscape pattern index to optimize spatial layout and matching corresponding water and fertilizer management strategies.

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