Method for estimating organic carbon sequestration amount of crop residue returning soil

Abstract

The invention relates to a method for estimating the organic carbon sequestration amount of crop residue returning soil. The method comprises the following steps: acquiring and processing multi-source data; simulating photosynthesis carbon assimilation quantity of main grain crops and CO2 flux released by respiration; extracting the net CO2 flux of MCCs crop types in the terrestrial ecosystem; calculating the net assimilation carbon distribution amount of each component of the MCCs in the growth cycle; determining distribution conditions of biomass carbon in different straw management practices; according to the local soil organic carbon conversion rate, the total organic carbon sequestration amount of the MCCs residue returning soil of all the grid units is calculated. The method has the beneficial effects that by quantifying the deposition of net assimilation carbon to rhizosphere, crop roots and stubbles, and the distribution amount of components such as straws and grains, key support is provided for carbon circulation of a farmland ecosystem and soil organic carbon sequestration potential evaluation.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon cycle assessment, and in particular relates to a method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields. Background Art

[0002] Terrestrial ecosystems play a key role in the global carbon cycle and serve as important carbon sinks in nature, absorbing large amounts of CO2 through photosynthesis and storing it in vegetation and soil. Arable land, a crucial component of terrestrial ecosystems, is considered to have great potential in carbon neutrality strategies due to its widespread distribution and flexible management. Therefore, scientific and rational agricultural management practices, such as returning straw to fields, conservation tillage, and green manure cultivation, can effectively enhance the carbon sequestration function of arable land systems, thereby supporting the achievement of regional and even national carbon reduction targets.

[0003] Current research on the carbon sequestration capacity of cultivated land primarily utilizes three approaches: field measurements, remote sensing statistical methods, and ecological model simulations. Field measurements typically involve collecting soil and vegetation samples and analyzing their carbon content, offering the advantage of high accuracy. However, their poor spatial representation and high workload make them difficult to apply to large scales. Remote sensing methods can estimate carbon sequestration based on crop growth indicators or yields, making them suitable for regional-scale assessments. However, they often rely on remote sensing inversion models, and their accuracy is limited by resolution, weather conditions, and sensor performance. Ecological modeling, which integrates multiple sources of data—including meteorological, soil, crop, and management data—allows for high-resolution spatial and temporal carbon cycle simulations and is a major current research trend. However, most models suffer from simplified structures and fixed parameters, making them inadequate for fully capturing the full spectrum of crop carbon uptake, allocation, and sequestration within cultivated land systems. Significant uncertainty remains in simulating the dynamics of farmland carbon sequestration and the effects of management measures.

[0004] Because cultivated land systems are subject to human intervention, such as fertilization, irrigation, and harvesting, their carbon cycle is unnatural and has long been marginalized in carbon sequestration research. However, recent studies have shown that cultivated land systems can absorb significant amounts of atmospheric CO2 during crop growth, and through measures such as returning straw to the fields, some of this carbon can be stably stored in the soil as organic matter. Existing studies, which are mostly based on static yield statistics, ignore the dynamic carbon processes throughout the crop growth cycle, resulting in significant bias in the assessment of cultivated land carbon sinks. Therefore, there is an urgent need to develop an assessment framework with high spatiotemporal resolution and full-process simulation capabilities to accurately quantify the complete life cycle of crop carbon uptake, distribution, and soil carbon sequestration in cultivated land systems. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields.

[0006] First, a method for estimating soil organic carbon sequestration from returning rice, wheat, and corn crop residues to fields is provided, including:

[0007] Step 1: Acquire and process multi-source data to generate the input files required for running the WRF-VPRM coupled model;

[0008] Step 2: Input the input file generated in step 1 into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and respiration CO2 flux of major cereal crops (MCCs) of rice, wheat, and maize;

[0009] Step 3: Based on the CO2 flux data simulated in Step 2, extract the net CO2 flux of MCCs crop types in terrestrial ecosystems as the basis for estimating their net CO2 assimilation;

[0010] Step 4: Calculate the net assimilated carbon allocation of each component of MCCs during the growth period;

[0011] Step 5: Determine the distribution of biomass carbon under different straw management practices;

[0012] Step 6: Calculate the soil organic carbon sequestration capacity of each grid unit and each crop in the fields, including roots, stubble, and straw returned as fertilizer, based on the local soil organic carbon conversion rate.

[0013] Step 7: Calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

[0014] Preferably, in step 1, the input files include vegetation parameter files, meteorological and chemical initial and boundary condition files, anthropogenic CO2 emission files, and files containing rice, wheat, and corn crop distribution and their VPRM model key parameters.

[0015] Preferably, step 4 includes:

[0016] Step 4.1. Calculate the amount of carbon allocated to each crop biomass;

[0017] Step 4.2, calculate the amount of carbon allocated to the roots and parts other than the roots of MCCs;

[0018] Step 4.3, calculate the amount of carbon allocated to MCCs grain, collectable straw, and stubble;

[0019] Step 4.4: Calculate the amount of carbon remaining in the farmland.

[0020] Preferably, in step 5, the straw management practices include: straw feed, raw material, base material, fertilizer, fuel and disposal.

[0021] In a second aspect, a system for estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields is provided, which is used to perform any of the methods described in the first aspect, including:

[0022] The acquisition module is used to acquire and process multi-source data and generate the input files required for running the WRF-VPRM coupled model;

[0023] The simulation module is used to input the input file generated by the acquisition module into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and respiration CO2 flux of the MCCs of major cereal crops;

[0024] The extraction module is used to extract the net CO2 flux of MCCs crop types in terrestrial ecosystems based on the CO2 flux data simulated by the simulation module, as a basis for estimating their net CO2 assimilation;

[0025] The first calculation module is used to calculate the net assimilated carbon allocation of each component of MCCs during the growth cycle;

[0026] a determination module to determine the allocation of biomass carbon among different straw management practices;

[0027] The second calculation module is used to calculate the soil organic carbon storage capacity of each grid unit and each crop residue in the farmland, including roots, stubble, and straw returned as fertilizer, based on the local soil organic carbon conversion rate;

[0028] The third calculation module is used to calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

[0029] According to a third aspect, a computer storage medium is provided, wherein a computer program is stored in the computer storage medium; when the computer program is executed on a computer, the computer executes any one of the methods described in the first aspect.

[0030] In a fourth aspect, an electronic device is provided, including:

[0031] Memory, used to store computer programs;

[0032] A processor is used to execute the computer program to implement any method as described in the first aspect.

[0033] The beneficial effects of the present invention are:

[0034] 1. This study constructs a carbon allocation assessment module based on the carbon budget of MCCs throughout their entire growth cycle, simulating the dynamic distribution of photosynthetically assimilated carbon among various organs. Combining the physiological characteristics of different crops with data on grass-to-grain ratios, root-to-shoot ratios, straw collectability, and the proportion of straw used as five materials across various regions of China, the module quantifies the distribution of net assimilated carbon to components such as rhizosphere deposition, crop roots and stubble, collectable straw, and grains, providing key support for the assessment of carbon cycling in farmland ecosystems and the potential for soil organic carbon sequestration.

[0035] 2. Based on the fact that returning MCCs residues to the fields plays a role in crop carbon sequestration, the present invention combines the soil organic carbon conversion rate of crop residues in different regions to construct a high-resolution soil organic carbon sequestration estimation module. By calculating the carbon content of various types of residues (roots, stubble, and straw returned to the fields as fertilizer) and their corresponding conversion rates on a grid-by-grid basis, and using process simulation methods to quantitatively estimate the carbon sequestration amount of three types of crop residues, rice, wheat, and corn, returned to the fields in the farmland ecosystem, the present invention significantly improves the accuracy and regional adaptability of soil organic carbon sequestration estimation compared to traditional yield estimation methods, and achieves high-precision estimation of the contribution of returning rice, wheat, and corn crop residues to the soil carbon pool in the selected region. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a flow chart of a method provided by the present invention for estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields;

[0037] Figure 2 This is a schematic diagram of the ranking of the top ten carbon allocation contributions of different crop residues, roots, stubble, and collectible straw fertilizer utilization in each province estimated by this invention; (a) is the ranking result of the total carbon allocation of the three types of crops in each province, (b) is the ranking result of the carbon allocation of rice crops in each province, (c) is the ranking result of the carbon allocation of winter wheat crops in each province, and (d) is the ranking result of the carbon allocation of corn crops in each province. Negative values ​​indicate carbon removal from the atmosphere, and the unit is TgC yr. -1 ;

[0038] Figure 3 Figure 1 shows the top ten rankings of soil organic carbon sequestration by different crop residue components in each province estimated by this method. (a) shows the ranking of soil organic carbon sequestration contributions by province under the scenario of returning roots and stubble to the field; (b) shows the ranking of soil organic carbon sequestration contributions by province under the scenario of returning straw as fertilizer; and (c) shows the ranking of soil organic carbon sequestration contributions by province under the scenario of returning straw as fuel and abandoned straw. The units are all TgC yr -1 ;

[0039] Figure 4Figure 1 shows a comparative ranking of the top ten provinces in terms of soil organic carbon sequestration from crop residue return, as estimated by this method. (a) shows the ranking of soil organic carbon sequestration contributions by province under current management practices, and (b) shows the ranking of soil organic carbon sequestration contributions by province after optimized management practices. The units are both TgC yr. -1 . DETAILED DESCRIPTION

[0040] The present invention will be further described below with reference to the following examples. The following examples are provided only to facilitate understanding of the present invention. It should be noted that, without departing from the principles of the present invention, it is possible for a person skilled in the art to make various modifications to the present invention, and such improvements and modifications fall within the scope of the claims of the present invention.

[0041] Example 1:

[0042] To solve the problems of the prior art, Example 1 of the present application provides a method for estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields, comprising:

[0043] Step 1: Acquire and process multi-source data to generate the input files required for running the WRF-VPRM coupled model.

[0044] In step 1, the input files include vegetation parameter files, meteorological and chemical initial and boundary condition files, anthropogenic CO2 emission files, and files containing rice, wheat, and corn crop distribution and their VPRM model key parameters.

[0045] Specifically, step 1 includes:

[0046] Step 1.1: Use the VPRM preprocessor to process and invert the MODIS satellite remote sensing data to obtain the enhanced vegetation index (EVI), land surface water index (LSWI), vegetation coverage (VEGFRA), and the extreme values ​​of the two indices (EVIMAX, EVIMIN, LSWIMAX, and LSWIMIN), and generate the vegetation parameter input file.

[0047] In the present invention, the original MODIS satellite product MOD09A1 remote sensing image in GeoTIFF format is uniformly converted into NetCDF format files through a batch conversion program as the original input data source of the VPRM preprocessor, wherein:

[0048] The VPRM preprocessor process includes the following steps:

[0049] (a) The SYNMAP global vegetation type dataset with a horizontal resolution of 1 km, which contains global geographic location and vegetation classification information, was downloaded and processed. The dataset was cropped to a subset of the Chinese region and standardized and exported to the NetCDF format.

[0050] (b) Calculate the surface area of ​​each grid cell using the CDO tool; interpolate the obtained EVI and LSWI data to the SYNMAP grid, assign 0.0 to EVI (>1.0 or <0.0) and LSWI (>1.0 or <-1.0) data outside the valid range, and remove invalid pixels;

[0051] (c) Generate intermediate index data to establish the correspondence between SYNMAP and WRF grids; aggregate EVI and LSWI to the WRF model grid based on the area weighting method;

[0052] (d) Use the smooth function with a smoothing window size of 3 to smooth the time series and remove winter outliers;

[0053] Finally, the annual extreme values ​​(maximum and minimum) of each vegetation type and the vegetation cover fraction within each WRF grid cell are calculated to provide high-resolution vegetation input parameters.

[0054] Step 1.2: Generate meteorological field initial and boundary condition files using the 6-hourly 1°×1° resolution FNL reanalysis data and terrain data provided by the National Centers for Environmental Prediction (NCEP) of the United States. Generate CO2 chemical initial and boundary condition files by interpolating the CO2 concentration dataset output every 6 hours by the Jena CarboScope.

[0055] Step 1.3: Use the Tsinghua University MEIC CO2 emission inventory as the anthropogenic CO2 emission data file.

[0056] Step 1.4: Process the ChinaCropPhen1km dataset to obtain daily spatial distribution data for rice, wheat, and maize; and add key parameters of the VPRM model for rice, wheat, and maize to the WRF-Chem model.

[0057] In addition, the present invention extracts the daily distribution data of the three major crops by reading the grid area and geographic information, ChinaCropPhen1km phenological data, processing outliers and extracting the 1km phenological data to the 9km grid according to longitude and latitude matching. After setting the threshold based on the crop planting area of ​​the National Bureau of Statistics, the effective phenological period is screened, and finally a standardized crop phenology NetCDF output file is generated.

[0058] The key parameter values ​​λ′, α′, β′ and PAR0′ of the crop VPRM model used in the present invention are shown in Table 1:

[0059] Table 1 Key parameters of VPRM model for rice, wheat and corn crops

[0060]

[0061] Step 2: Input the input file generated in step 1 into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops.

[0062] Specifically, vegetation parameters, initial and boundary conditions, anthropogenic CO2 emission data, and daily crop distribution data files were used as input files, and the WRF-VPRM coupled model of the three crops was used to simulate the photosynthetic carbon assimilation and respiration CO2 flux of the main cereal crops rice, wheat, and maize (MCCs).

[0063] Step 3: Based on the CO2 flux data simulated in Step 2, extract the net CO2 flux of MCCs crop types in terrestrial ecosystems as the basis for estimating their net CO2 assimilation.

[0064] Specifically, the net CO2 assimilation (NEE) of MCCs crops in terrestrial ecosystems was calculated using the MCCs photosynthetic carbon assimilation (GEE) and the CO2 flux released by respiration (RESP). The formula is:

[0065]

[0066] Where: Tscale is the temperature scale; Wscale is the water stress scale; Pscale is the vegetation phenology scale; PAR is the photosynthetically active radiation; PAR0′ is the half-saturation value, unit is μmol m -2 s -1 ; EVI is the vegetation enhancement index; λ′ is the maximum light energy utilization efficiency, unit: μmol CO2 / μmolPARm -2 s -1 ; T is the temperature at 2 meters above sea level; α′ is the empirical parameter of respiration, unit: μmol CO2 m -2 s -1 K -1 β′ is the basal respiration rate, in μmol CO2 m -2 s -1 ; GEE is the gross ecosystem CO2 exchange; RESP is the CO2 flux released by respiration; NEE is the net ecosystem CO2 exchange, in μmol m -2 s -1 ;

[0067] The involved Tscale, Wscale, and Pscale are parameterized as follows:

[0068]

[0069] Where: Tmin is the minimum temperature threshold for photosynthesis; Tmax is the maximum temperature threshold for photosynthesis; Topt is the most suitable temperature; LSWI is the land surface water index; LSWImax is the maximum land surface water index during the vegetation growing season for each grid.

[0070] Step 4: Calculate the net assimilated carbon allocation of each component of MCCs during the growth cycle.

[0071] Step 5: Determine the distribution of biomass carbon under different straw management practices.

[0072] Step 6: Based on the local soil organic carbon conversion rate, calculate the soil organic carbon storage capacity of each grid unit and each crop residue in the farmland, including roots, stubble, and straw returned to the field as fertilizer.

[0073] Step 7: Calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

[0074] Example 2:

[0075] Based on Example 1, Example 2 of the present application provides a more specific method for estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields, including:

[0076] Step 1: Acquire and process multi-source data to generate the input files required for running the WRF-VPRM coupled model.

[0077] Step 2: Input the input file generated in step 1 into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops.

[0078] Step 3: Based on the CO2 flux data simulated in Step 2, extract the net CO2 flux of MCCs crop types in terrestrial ecosystems as the basis for estimating their net CO2 assimilation.

[0079] Step 4: Calculate the net assimilated carbon allocation of each component of MCCs during the growth cycle.

[0080] In step 4, the net assimilated carbon allocation of each component of Chinese MCCs during the growth cycle was calculated based on the fact that part of the carbon assimilated by photosynthesis during the growth of MCCs enters the soil through the roots in the form of net rhizosphere deposition, and the carbon in the biomass after harvest is distributed among different components such as roots and stubble, collectible crop straw, and grains.

[0081] Specifically, step 4 includes:

[0082] Step 4.1: Calculate the amount of carbon allocated to each crop biomass using the following formula:

[0083]

[0084] Where: The amount of carbon allocated to each crop biomass for each grid cell, is the amount of carbon assimilated by photosynthesis, is the amount of carbon released by respiration, is the amount of carbon entering the soil through rhizosphere deposition; i, j are each grid unit, and s takes values ​​of (1, 2, 3) to represent rice, wheat, and corn, respectively.

[0085] Step 4.2: Calculate the amount of carbon allocated to the roots and parts other than the roots of MCCs using the following formula:

[0086]

[0087] Where: is the amount of carbon allocated to roots, is the amount of carbon distributed to parts other than roots, is the root-to-shoot ratio of crops in different regions of China.

[0088] Step 4.3: Calculate the amount of carbon allocated to MCCs grains, collectable straw, and stubble using the following formula:

[0089]

[0090] Where: is the amount of carbon allocated to the grain, To allocate the carbon amount of the collected straw, is the amount of carbon allocated to the residue, CC s is the collectability coefficient of crop straw, is the grass-to-grain ratio of crops in different regions of China;

[0091] Involved Can be parameterized as:

[0092]

[0093] Where: Based on the conservation relationship of the aboveground carbon of crops in step ③, combined with the grass-grain ratio and the straw collectible coefficient, the crop grain carbon, collectible straw carbon and stubble carbon were derived respectively.

[0094] Step 4.4: Calculate the amount of carbon remaining in the farmland using the following formula:

[0095]

[0096] Where: is the amount of carbon remaining on farmland, including crop roots and residues.

[0097] The MCCs grass-to-grain ratio and crop straw collectible coefficient in different regions of my country in this invention are derived from data provided by the Ministry of Agriculture and Rural Affairs of China, and the root-to-shoot ratio data are derived from the crop parameter database obtained by Wang et al. (2016) based on measured crop biomass data in different agricultural types.

[0098] Step 5: Determine the distribution of biomass carbon under different straw management practices.

[0099] In step 5, the straw management practices include: straw feed, raw material, base material, fertilizer, fuel and disposal.

[0100] Specifically, using the "five-material utilization" dataset for various provinces in China, we calculated the carbon allocation of crop straw used as feed, raw material, substrate material, fertilizer, fuel, and waste, and determined the distribution of biomass carbon under different straw management practices. The calculation formula for carbon allocation to the five-material utilization of crop straw is:

[0101]

[0102] Where: The amount of carbon allocated to straw as feed, raw material, base material, fertilizer, fuel, and waste, F feed 、F raw 、F base 、F fert 、F fuel 、F dis The proportion of straw used as feed, raw material, base material, fertilizer, fuel and discarded in various provinces of China.

[0103] The proportion of five-material utilization of crop straw in various provinces in my country in this invention comes from the data provided by the "China Rural Energy Yearbook 2014-2021".

[0104] Step 6: Based on the local soil organic carbon conversion rate, calculate the soil organic carbon storage capacity of each grid unit and each crop residue in the farmland, including roots, stubble, and straw returned to the field as fertilizer.

[0105] Specifically, the calculation formula for soil organic carbon storage in each grid unit and each type of crop residue returned to the field is:

[0106]

[0107] Where: is the current soil organic carbon storage capacity, Eff is the amount of carbon allocated when straw is collected and used as fertilizer and returned to the field. i,j is the soil organic carbon conversion rate of crop straw returned to fields in various parts of China.

[0108] The soil organic carbon conversion rate data of crop straw return in various parts of my country in this invention are derived from the linear relationship between straw carbon allocation and annual soil organic carbon conversion rate obtained by Han et al. (2018). The efficiency data of straw carbon conversion to soil organic carbon in different regions of China were obtained.

[0109] Step 7: Calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

[0110] The calculation formula for the total amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields is:

[0111]

[0112] Where: CS curr is the total amount of soil organic carbon sequestered by returning MCCs residues to farmland in China.

[0113] The present invention sets up an estimation test of crop residue carbon allocation and soil organic carbon sequestration, constructs a regional contribution comparison of carbon return to fields under different management practices, estimates the carbon allocation of MCCs residues and soil organic carbon sequestration capacity in China in 2020, and verifies the estimated effects of the current crop straw management practices and the optimized straw management practices. The specific verification test design is shown in Table 2: Table 2 Experiments and data table

[0114]

[0115] The experiments were all based on the WRF V3.9.1 version coupled with the VPRM model to simulate the net CO2 assimilation NEE of MCCs to estimate the carbon allocation of residues and the amount of soil organic carbon sequestered by returning residues to fields. The simulation time was the whole year of 2020. The current straw management practice of the present invention is to achieve carbon sequestration through soil organic carbon in three parts of crop roots, straw residues, and fertilizer straw, and evaluate the carbon sequestration capacity; the optimized straw management practice in the experiment is to achieve fertilizer utilization of the fuel and waste parts, that is, to optimize the carbon sequestration capacity of the five parts of crop roots, straw residues, and fertilizer straw (original fertilizer, fuel, and waste) through soil organic carbon.

[0116] It should be noted that the parts in this embodiment that are the same or similar to those in Example 1 can be referenced to each other and will not be described in detail in this application.

[0117] Example 3:

[0118] Based on Example 2, Example 3 of the present application provides a system for estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to fields, including:

[0119] The acquisition module is used to acquire and process multi-source data and generate the input files required for running the WRF-VPRM coupled model.

[0120] The simulation module is used to input the input file generated by the acquisition module into the WRF-VPRM coupling model based on three crops to simulate the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops.

[0121] The extraction module is used to extract the net CO2 flux of MCCs crop types in terrestrial ecosystems based on the CO2 flux data simulated by the simulation module, as a basis for estimating their net CO2 assimilation.

[0122] The first calculation module is used to calculate the net assimilated carbon allocation of each component of MCCs during the growth cycle.

[0123] A determination module is used to determine the distribution of biomass carbon among different straw management practices.

[0124] The second calculation module is used to calculate the soil organic carbon storage capacity of each grid unit and each crop residue in the farmland, including roots, stubble and straw returned to the field as fertilizer, based on the local soil organic carbon conversion rate.

[0125] The third calculation module is used to calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

[0126] The regional distribution of crop residue carbon allocation is of great significance for the assessment of agricultural carbon cycle. To verify the ability of the present invention to identify the regional distribution of crop residue carbon allocation, the carbon allocation of three types of crop residues, roots, stubble and straw used as fertilizer, was estimated at the provincial level. Figure 2 As shown in Figure 2, the carbon distribution of crop residues in Heilongjiang Province is 38.71 TgCyr -1 , ranking first in the country, Henan and Shandong were 38.17TgC yr -1 and 28.29TgC yr -1 , showing the characteristics of high carbon allocation intensity and active management of crop residues in typical major production areas ( Figure 2 a). Jiangsu Province has a total of 9.61TgC yr -1 The carbon allocation of rice straw in southern rice-growing areas ranked first, followed by Guangdong and Anhui, reflecting the significant advantages of southern rice-growing areas in returning straw to fields ( Figure 2 b) The carbon allocation of winter wheat residues in Henan Province was the highest, reaching 19.74 TgC yr -1 , reflecting the important position of the Huanghuai wheat region in the farmland carbon cycle ( Figure 2 c) The carbon allocation of corn straw in Heilongjiang, the main corn-producing region, is 26.60 TgC yr -1 , ahead of other provinces ( Figure 2 d).

[0127] To further refine the contribution of different crop residue components to soil organic carbon sequestration in each province, the soil organic carbon sequestration of roots and stubble, straw used as fertilizer, and fuel and waste straw was estimated. Figure 3 As shown in Figure 2, the amount of soil organic carbon stored by roots and residues in Heilongjiang Province is 10.23 TgC yr -1 , much higher than other regions, Jilin and Liaoning provinces also reached 5.41TgC yr -1 and 3.51TgC yr -1 , indicating that the unharvested portion is the main source of carbon sequestration ( Figure 3 a) Jiangsu Province has a high proportion of straw fertilizer returned to the fields, and its soil organic carbon storage capacity has reached 5.17 TgC yr -1 , Shandong and Anhui followed closely behind ( Figure 3 b). Heilongjiang Province still shows a high level of carbon sequestration under fuel utilization and abandoned straw, indicating that the region has a wide coverage of crop residue management and a strong carbon return capacity ( Figure 3 c).

[0128] MCCs can absorb a large amount of CO2 from the atmosphere and convert it into biomass, effectively sequestering carbon in the soil through advanced agronomic management measures. In order to evaluate the effect of the optimized straw return strategy proposed in this paper on improving the soil carbon sequestration capacity, two experimental schemes, current management and optimized management, were constructed to simulate the soil organic carbon sequestration contribution of different provinces. Figure 3 As shown in the figure, under current management practices, Heilongjiang Province has a 10.02 TgC yr -1 The soil organic carbon storage capacity of Jilin and Liaoning provinces ranked first, with 5.66 TgC yr -1 and 4.03TgC yr -1 This indicates that Northeast China has a strong carbon sequestration capacity under the current straw management level ( Figure 4 a) Under optimized management practices, soil organic carbon storage in Heilongjiang increased to 14.11 TgC yr -1 Shandong and Henan ranked second and third, respectively, showing significant improvement, indicating that the main grain-producing areas in central and eastern China have great potential in increasing carbon sequestration efficiency through optimizing management measures ( Figure 4 b).

[0129] It should be noted that the system provided in this embodiment is a system corresponding to the method provided in Example 2. Therefore, the parts in this embodiment that are the same or similar to those in Example 2 can be referenced to each other and will not be repeated in this application.

[0130] In summary, the present invention simulates crop carbon throughout its life cycle based on the crop carbon budget-allocation-sequestration framework, significantly improving the accuracy of estimating the amount of soil organic carbon sequestered by returning rice, wheat, and corn crop residues to the fields in China, and providing technical support for agricultural carbon sink estimation and management practices.

Claims

1. A method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields, characterized in that: include: Step 1: Acquire and process multi-source data to generate the input files required for running the WRF-VPRM coupled model; Step 2: Input the input file generated in step 1 into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and respiration CO2 flux of the main cereal crops of rice, wheat, and corn; Step 3: Based on the CO2 flux data simulated in Step 2, extract the net CO2 flux of MCCs crop types in terrestrial ecosystems as the basis for estimating their net CO2 assimilation; Step 4: Calculate the net assimilated carbon allocation of each component of MCCs during the growth period; Step 5: Determine the distribution of biomass carbon under different straw management practices; Step 6: Calculate the soil organic carbon sequestration capacity of each grid unit and each crop in the fields, including roots, stubble, and straw returned as fertilizer, based on the local soil organic carbon conversion rate. Step 7: Calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

2. The method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields according to claim 1, characterized in that: In step 1, the input files include vegetation parameter files, meteorological and chemical initial and boundary condition files, anthropogenic CO2 emission files, and files containing rice, wheat, and corn crop distribution and their VPRM model key parameters.

3. The method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields according to claim 2, characterized in that: Step 4 includes: Step 4.

1. Calculate the amount of carbon allocated to each crop biomass; Step 4.2, calculate the amount of carbon allocated to the roots and parts other than the roots of MCCs; Step 4.3, calculate the amount of carbon allocated to MCCs grain, collectable straw, and stubble; Step 4.4: Calculate the amount of carbon remaining in the farmland.

4. The method for estimating the amount of soil organic carbon sequestered by returning crop residues to fields according to claim 2, characterized in that: In step 5, the straw management practices include: straw feed, raw material, base material, fertilizer, fuel and disposal.

5. A system for estimating the amount of soil organic carbon sequestered by returning crop residues to fields, characterized in that: The method for executing any one of claims 1 to 4 comprises: The acquisition module is used to acquire and process multi-source data and generate the input files required for running the WRF-VPRM coupled model; The simulation module is used to input the input file generated by the acquisition module into the WRF-VPRM coupled model based on three crops to simulate the photosynthetic carbon assimilation and the CO2 flux released by respiration of major cereal crops; The extraction module is used to extract the net CO2 flux of MCCs crop types in terrestrial ecosystems based on the CO2 flux data simulated by the simulation module, as a basis for estimating their net CO2 assimilation; The first calculation module is used to calculate the net assimilated carbon allocation of each component of MCCs during the growth cycle; a determination module to determine the allocation of biomass carbon among different straw management practices; The second calculation module is used to calculate the soil organic carbon storage capacity of each grid unit and each crop residue in the farmland, including roots, stubble, and straw returned as fertilizer, based on the local soil organic carbon conversion rate; The third calculation module is used to calculate the total amount of soil organic carbon sequestered by returning MCCs residues to fields in all grid cells.

6. A computer storage medium, characterized in that The computer storage medium stores a computer program; when the computer program is run on a computer, the computer executes the method according to any one of claims 1 to 4.

7. An electronic device, characterized in that: include: Memory, used to store computer programs; A processor, configured to execute the computer program to implement the method according to any one of claims 1 to 4.

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