A method for estimating the amount of soil organic carbon sequestration from crop residues returned to the field.

Abstract

This invention relates to a method for estimating soil organic carbon sequestration by crop residue return to the field, comprising: acquiring and processing multi-source data; simulating the photosynthetic carbon assimilation and CO2 flux released by respiration of major cereal crops; extracting the net CO2 flux of MCCs (Mechanical Control Cells) in terrestrial ecosystems; calculating the net assimilated carbon allocation of each component of MCCs during their growth cycle; determining the distribution of biomass carbon in different straw management practices; and calculating the total soil organic carbon sequestration by MCC residue return to the field in all grid units based on the local soil organic carbon conversion rate. The beneficial effects of this invention are: by quantifying the allocation of net assimilated carbon to components such as rhizosphere deposition, crop roots and stubble, collectable straw, and grains, this invention provides crucial support for assessing the carbon cycle and soil organic carbon sequestration potential of farmland ecosystems.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of carbon cycle evaluation, and particularly relates to a method for evaluating the organic carbon storage amount of crop residue returned to soil. BACKGROUND

[0002] The terrestrial ecosystem plays a key role in global carbon cycle and is an important carbon sink system in nature, which can absorb a large amount of CO2 and store it in vegetation and soil through photosynthesis. As an important part of the terrestrial ecosystem, farmland is widely distributed and managed flexibly, and is considered to have great potential in carbon neutralization strategy. Therefore, through scientific and reasonable agricultural management measures such as straw returning, conservation tillage, green manure planting, etc., the carbon sink function of the farmland system can be effectively improved, thereby providing support for achieving regional and even national carbon emission reduction targets.

[0003] The current research on the carbon sink capacity of farmland mainly adopts three methods, namely field measurement method, remote sensing statistical method and ecological model simulation method. The field measurement method generally collects soil and vegetation samples to analyze their carbon content, which has the advantage of high precision, but its spatial representativeness is poor, the workload is large, and it is difficult to apply to large-scale scales. The remote sensing method can estimate the carbon sink amount based on crop growth indicators or yield, which is suitable for regional scale evaluation, but it often relies on remote sensing inversion models, and the precision is limited by resolution, weather conditions and sensor performance. The ecological model method can integrate meteorological, soil, crop and management data to realize high spatiotemporal resolution carbon cycle simulation, which is the main trend of current research. However, most models have problems such as structural simplification and fixed parameters, which make it difficult to fully reflect the whole process of crop carbon absorption, distribution and storage in the farmland system. Especially, there is still great uncertainty in simulating the dynamic changes of farmland carbon sink and the effects of management measures.

[0004] Because the farmland system is intervened by human management such as fertilization, irrigation, harvesting and other operations, its carbon cycle process is non-natural, so it has been marginalized in carbon sink research for a long time. However, recent research has found that the farmland system can absorb a large amount of atmospheric CO2 during crop growth, and part of the carbon can be stably stored in the soil in the form of organic matter through measures such as straw returning. Since most existing research is based on static yield statistical data, ignoring the carbon dynamic process during the whole growth cycle of crops, the evaluation results of farmland carbon sink are greatly biased. Therefore, it is urgent to develop an evaluation framework with high spatiotemporal resolution and full-process simulation capability to accurately quantify the complete life cycle of crop carbon absorption, distribution and soil carbon sequestration in the farmland system. SUMMARY

[0005] The purpose of the present application is to overcome the deficiencies in the prior art and provide a method for estimating the organic carbon storage amount of crop residue returned to soil.

[0006] In a first aspect, there is provided a method for estimating the soil organic carbon sequestration of rice, wheat, and corn crop residue, comprising:

[0007] Step 1, obtaining and processing multi-source data to generate input files required for running the WRF-VPRM coupling model;

[0008] Step 2, inputting the input files generated in Step 1 into the WRF-VPRM coupling model based on three crops to simulate the photosynthetic carbon assimilation and respiratory CO2 flux of major cereal crops (MCCs);

[0009] Step 3, based on the CO2 flux data simulated in Step 2, extracting the net CO2 flux of MCCs crop types in the terrestrial ecosystem as the basis for estimating the net carbon assimilation of CO2;

[0010] Step 4, calculating the net assimilated carbon distribution of each component of MCCs during the growth cycle;

[0011] Step 5, determining the distribution of biomass carbon in different straw management practices;

[0012] Step 6, according to the local soil organic carbon conversion rate, calculating the soil organic carbon sequestration of each grid cell, each crop residue in the farmland, and the straw used as fertilizer;

[0013] Step 7, calculating the total amount of soil organic carbon sequestration of MCCs residue 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 the distribution of rice, wheat, and corn crops and their VPRM model key parameters.

[0015] Preferably, Step 4 includes:

[0016] Step 4.1, calculating the amount of carbon allocated to each crop biomass;

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

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

[0019] Step 4.4, calculating 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 waste.

[0021] Secondly, a system is provided for estimating the amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field, for performing 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 the WRF-VPRM coupled mode to run.

[0023] The simulation module is used to input the input file generated by the acquisition module into the WRF-VPRM coupling mode based on three crops to simulate the photosynthetic carbon assimilation and CO2 flux released by respiration of the main cereal crops MCCs.

[0024] The extraction module is used to extract the net CO2 flux of MCC 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] The determination module is used to determine the distribution of biomass carbon in different straw management practices;

[0027] The second calculation module is used to calculate the amount of soil organic carbon sequestration for each grid cell, the roots and stubble of each crop remaining in the field, and the straw used as fertilizer, based on the local soil organic carbon conversion rate.

[0028] The third calculation module is used to calculate the total amount of organic carbon sequestration in the soil from the return of MCCs residues to the field in all grid cells.

[0029] Thirdly, a computer storage medium is provided, wherein a computer program is stored therein; when the computer program is run on a computer, the computer causes the computer to perform any of the methods described in the first aspect.

[0030] Fourthly, an electronic device is provided, comprising:

[0031] Memory, used to store computer programs;

[0032] A processor for executing the computer program to implement the method as described in any of the first aspects.

[0033] The beneficial effects of this invention are:

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

[0035] 2. This invention leverages the role of MCCs residues in crop carbon sequestration through return to the field. By combining this with soil organic carbon conversion rates of crop residues in different regions, a high-resolution soil organic carbon sequestration estimation module is constructed. By calculating the carbon content and corresponding conversion rates of various residues (roots, stubble, and straw returned as fertilizer) grid-by-grid, and using process simulation, the carbon sequestration amount of rice, wheat, and maize crop residues returned to the field in the farmland ecosystem is quantitatively estimated. Compared to traditional yield estimation methods, this invention significantly improves the accuracy and regional adaptability of soil organic carbon sequestration estimation, and achieves high-precision estimation of the contribution of rice, wheat, and maize crop residues returned to the field to the soil carbon pool in selected regions. Attached Figure Description

[0036] Figure 1 This is a flowchart of a method for estimating the amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field, provided by the present invention.

[0037] Figure 2 This is a schematic diagram showing the ranking of the top ten contributors to carbon allocation from the utilization of different crop residues (roots, stubble, and collectable straw) for fertilizer purposes in various provinces, as estimated by this invention. (a) shows the ranking of carbon allocation for the three MCCs (Medium-terminal Crop Classification) crops in each province; (b) shows the ranking of carbon allocation for rice crops in each province; (c) shows the ranking of carbon allocation for winter wheat crops in each province; and (d) shows the ranking of carbon allocation for maize crops in each province. Negative values ​​indicate carbon removal from the atmosphere, and the units are TgC yr. -1 ;

[0038] Figure 3 This diagram illustrates the ranking of the top ten soil organic carbon sequestration amounts for different crop residue components in various provinces, as estimated by this invention. (a) shows the ranking of soil organic carbon sequestration contributions for each province under the scenarios of root and stubble return to the field; (b) shows the ranking of soil organic carbon sequestration contributions for each province under the scenario of straw return to the field as fertilizer; and (c) shows the ranking of soil organic carbon sequestration contributions for each province under the scenarios of straw return to the field as fuel and waste straw return to the field. All units are TgC yr. -1 ;

[0039] Figure 4This is a comparative diagram showing the ranking of the top ten soil organic carbon sequestration amounts estimated by crop residue return to the field in different provinces according to this invention; (a) is the ranking result of soil organic carbon sequestration contribution of each province under the current management practice, and (b) is the ranking result of soil organic carbon sequestration contribution of each province after optimized management practice. The units are TgC yr. -1 . Detailed Implementation

[0040] The present invention will be further described below with reference to embodiments. The description of the embodiments below is only for the purpose of helping to understand the present invention. It should be noted that those skilled in the art can make several modifications to the present invention without departing from the principle of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0041] Example 1:

[0042] To address the problems of existing technologies, Embodiment 1 of this application provides a method for estimating the amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field, including:

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

[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 the distribution of rice, wheat, and maize crops and their VPRM model key parameters.

[0045] Specifically, step 1 includes:

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

[0047] In this invention, the original GeoTIFF format MODIS satellite product MOD09A1 remote sensing imagery is uniformly converted into NetCDF format files using a batch conversion program, which serve as the original input data source for the VPRM preprocessor.

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

[0049] (a) The SYNMAP global vegetation type dataset with a horizontal resolution of 1km, containing geographic location and vegetation classification information worldwide, was downloaded and processed. It was then cropped into a subset of the Chinese region and standardized for output in 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 a value of 0.0 to EVI (>1.0 or <0.0) and LSWI (>1.0 or <-1.0) data that are outside the valid range, and remove invalid cells;

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

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

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

[0054] Step 1.2: Generate initial and boundary condition files for the meteorological field using reanalysis data of 1°×1°FNL provided by the National Center for Environmental Prediction (NCEP) every 6 hours and topographic data; interpolate the CO2 concentration dataset output by Jena CarboScope every 6 hours to generate initial and boundary condition files for CO2 chemical properties.

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

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

[0057] Furthermore, the daily distribution data of the three major crops in this invention are extracted by reading grid area and geographical information, ChinaCropPhen 1km phenological data, processing outliers and extracting 1km phenological data to a 9km grid by matching latitude and longitude. After setting a threshold based on the crop planting area set by the National Bureau of Statistics, the effective phenological period is selected, and finally a standardized crop phenological NetCDF output file is generated.

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

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

[0060]

[0061] Step 2: Input the input file generated in Step 1 into the WRF-VPRM coupling mode based on three crops to simulate the photosynthetic carbon assimilation and CO2 flux released by respiration of the main 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. Based on the WRF-VPRM coupled model of three crops, the carbon assimilation through photosynthesis and the CO2 flux released through respiration of major cereal crops rice, wheat, and maize (MCCs) were simulated.

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

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

[0065]

[0066] In the formula: 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 its half-saturation value, in μmol / m³. -2 s -1 EVI is the vegetation enhancement index; λ′ is the maximum light energy utilization rate, in μmol CO2 / μmol PARm. -2 s -1 T is the air temperature at an altitude of 2 meters; α′ is an empirical parameter for respiration, in μmol CO2 m -2 s -1 K -1 β′ is the basic rate of respiration, in μmol CO2 m -2 s -1 GEE is the total ecosystem CO2 exchange capacity; RESP is the CO2 flux released by respiration; NEE is the net ecosystem CO2 exchange capacity, in μmol / m³. -2 s -1 ;

[0067] The Tscale, Wscale, and Pscale parameters involved are respectively:

[0068]

[0069] In the formula: Tmin is the minimum temperature threshold for photosynthesis; Tmax is the maximum temperature threshold for photosynthesis; Topt is the optimal temperature; LSWI is the land surface water index; LSWImax is the maximum land surface water index during the vegetation growing season of 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 in different straw management practices.

[0072] Step 6: Based on the local soil organic carbon conversion rate, calculate the soil organic carbon sequestration of each grid cell, the roots and stubble of each crop residue in the field, and the straw used as fertilizer.

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

[0074] Example 2:

[0075] Based on Example 1, Example 2 of this application provides a more specific method for estimating the amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field, including:

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

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

[0078] Step 3: Based on the CO2 flux data simulated in Step 2, extract the net CO2 flux of MCC 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, based on the fact that some of the carbon assimilated by photosynthesis during the growth of MCCs enters the soil through the root system in the form of net rhizosphere deposition, and that the carbon in the biomass after harvest is distributed to different components such as roots and stubble, collectable crop straw and grain, the net assimilated carbon allocation of each component of Chinese MCCs during the growth cycle is calculated.

[0081] Specifically, step 4 includes:

[0082] Step 4.1: Calculate the amount of carbon allocated to each crop biomass. The calculation formula is as follows:

[0083]

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

[0085] Step 4.2: Calculate the amount of carbon allocated to the MCCs roots and the portion excluding the roots. The calculation formula is as follows:

[0086]

[0087] In the formula: The amount of carbon allocated to the root, The amount of carbon allocated to the portion excluding the root. 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. The calculation formula is as follows:

[0089]

[0090] In the formula: The amount of carbon allocated to the grain. To allocate carbon to collectable straw, To allocate the amount of carbon to the stubble, CC s The collectability coefficient of crop straw. The ratio of straw to grain in crops in different regions of China;

[0091] Involved They can be parameterized as follows:

[0092]

[0093] In the formula: Based on the conservation relationship of aboveground carbon in step ③, and combined with the grass-to-grain ratio and the straw collectability coefficient, the carbon content of crop grains, collectable straw, and stubble residue are derived respectively.

[0094] Step 4.4: Calculate the amount of carbon remaining in farmland. The calculation formula is as follows:

[0095]

[0096] In the formula: This refers to the amount of carbon remaining in farmland, including crop roots and stubble.

[0097] In this invention, the grass-to-grain ratio and crop straw collectability coefficient of MCCs in different regions of my country are all from data provided by the Ministry of Agriculture and Rural Affairs of China, and the root-to-shoot ratio data are 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 in different straw management practices.

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

[0100] Specifically, using the "five-fold utilization" dataset from various provinces in China, the carbon allocation of harvestable crop straw as feed, raw material, substrate material, fertilizer, fuel, and waste is calculated to determine the distribution of biomass carbon in different straw management practices. The formula for calculating carbon allocation to the five-fold utilization of harvestable straw is as follows:

[0101]

[0102] In the formula: The carbon content allocated to straw for feed, raw material, substrate, fertilizer, fuel, and waste disposal, F feed F raw F base F fert F fuel F dis This refers to the proportions of straw used as feed, raw material, substrate, fertilizer, fuel, and waste in various provinces of China.

[0103] The proportion of crop straw utilization in various provinces of my country in this invention is based on data provided in the "China Rural Energy Yearbook 2014-2021".

[0104] Step 6: Based on the local soil organic carbon conversion rate, calculate the soil organic carbon sequestration of each grid cell, the roots and stubble of each crop residue in the field, and the straw used as fertilizer.

[0105] Specifically, the formula for calculating the soil organic carbon sequestration amount for each grid cell and each type of crop residue returned to the field is as follows:

[0106]

[0107] In the formula: This represents the current amount of soil organic carbon sequestration. Eff represents the amount of carbon allocated to collectable straw when it is returned to the field as fertilizer. i,j The soil organic carbon conversion rate of crop straw returned to the field in various parts of China.

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

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

[0110] The formula for calculating the total amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field is as follows:

[0111]

[0112] Where: CS curr This represents the total amount of soil organic carbon sequestration caused by the return of MCCs residues to the field in China.

[0113] This invention sets up an experiment to estimate the carbon allocation of crop residues and the soil organic carbon sequestration capacity, constructs a regional contribution comparison of carbon return to the field under different management practices, estimates the carbon allocation of MCCs residues and the soil organic carbon sequestration capacity in China in 2020, and verifies the estimation effect of current crop straw management practices and optimized straw management practices. The specific verification experiment design is shown in Table 2: Table 2 Experiment and Data Table

[0114]

[0115] All experiments were conducted using the WRF V3.9.1 version coupled with the VPRM model to simulate the net CO2 assimilation of MCCs, estimate the carbon allocation of residues, and estimate the soil organic carbon sequestration of residues returned to the field. The simulation period was the entire year of 2020. Current straw management practices assess carbon sequestration capacity by utilizing soil organic carbon from three parts: crop roots, straw residues, and straw used for fertilizer. The optimized straw management practice in the experiments also utilizes the fuel and waste portions for fertilizer purposes, thus optimizing carbon sequestration capacity from soil organic carbon in five parts: crop roots, straw residues, and straw used for fertilizer (original fertilizer, fuel, and waste).

[0116] It should be noted that the parts in this embodiment that are the same as or similar to those in Embodiment 1 can be referred to each other, and will not be repeated in this application.

[0117] Example 3:

[0118] Based on Example 2, Example 3 of this application provides a system for estimating the amount of soil organic carbon sequestration from rice, wheat, and corn crop residues returned to the field, including:

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

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

[0121] The extraction module is used to extract the net CO2 flux of MCC 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] The determination module is used to determine the distribution of biomass carbon in different straw management practices.

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

[0125] The third calculation module is used to calculate the total amount of organic carbon sequestration in the soil from the return of MCCs residues to the field in all grid cells.

[0126] The regional distribution of carbon allocation in crop residues is of great significance for agricultural carbon cycle assessment. To verify the ability of this invention to identify the regional distribution of carbon allocation in crop residues, the carbon allocation of three types of crop residues—roots, stubble, and straw used for fertilizer—was estimated at the provincial level as follows: Figure 2 As shown, the carbon allocation of crop residues in Heilongjiang Province is 38.71 TgCyr. -1 Henan and Shandong ranked first in the country, with 38.17TgC yr respectively. -1 and 28.29TgC yr -1 This demonstrates the characteristics of high carbon allocation intensity of crop residues and active management in typical major producing areas. Figure 2 a). Jiangsu Province with 9.61TgC yr -1 Rice straw carbon allocation ranked first, followed by Guangdong and Anhui, reflecting the significant advantages of rice-growing areas in southern China in straw return to the field. Figure 2 b). Henan Province had the highest residual carbon content in winter wheat, reaching 19.74 TgC yr. -1 This demonstrates the important role of the Huang-Huai wheat region in the agricultural carbon cycle. Figure 2 c). The carbon allocation of corn stalks in Heilongjiang, a major corn-producing region, is 26.60 TgC yr. -1 Leading other provinces Figure 2 d).

[0127] To further refine the contribution of different crop residue components to soil organic carbon sequestration in various provinces, the soil organic carbon sequestration amounts of roots and stubble, straw used as fertilizer, and straw used for fuel and waste were estimated separately. Figure 3 As shown, the soil organic carbon sequestration capacity formed by roots and crop residues in Heilongjiang Province is 10.23 TgC yr. -1 The levels are significantly higher than in other regions, with Jilin and Liaoning provinces also reaching 5.41 TgC yr. -1 and 3.51TgC yr -1 This indicates that unharvested portions are the primary source of carbon sequestration. Figure 3 a) Jiangsu Province, due to its high proportion of straw fertilizer returned to the field, has a soil organic carbon sequestration of 5.17 TgC yr. -1 Shandong and Anhui followed closely behind. Figure 3 b). Heilongjiang Province still exhibits a high level of crop residue sequestration despite fuel utilization and waste straw disposal, indicating that the region has extensive crop residue management coverage and strong carbon return capacity. Figure 3 c).

[0128] MCCs can absorb large amounts of atmospheric CO2 and convert it into biomass, effectively sequestering carbon in the soil through advanced agronomic management practices. To evaluate the effect of the optimized straw return strategy proposed in this invention on improving soil carbon sequestration capacity, two experimental schemes were constructed: current management and optimized management, simulating the contribution of soil organic carbon sequestration in different provinces, as shown below. Figure 3 As shown, under current management practices, Heilongjiang Province has a γ-ray concentration of 10.02 TgC yr. -1 Jilin and Liaoning provinces ranked first in soil organic carbon sequestration, with 5.66 Tg Cyr respectively. -1 and 4.03TgC yr -1 This indicates that Northeast China already possesses a relatively strong carbon sequestration capacity under the current level of straw management. Figure 4 a) Under optimized management practices, the organic carbon sequestration capacity of soil in Heilongjiang Province increased to 14.11 TgC yr. -1 Shandong and Henan ranked second and third respectively, both showing significant improvement, indicating that the main grain-producing areas in central and eastern China have great potential for increasing carbon sequestration efficiency through optimized management measures. Figure 4 b).

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

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

Claims

1. A method of estimating the amount of soil organic carbon sequestration in a crop residue incorporated soil, characterized by, The method comprises the following steps: Step 1, obtaining and processing multi-source data to generate input files required for running the WRF-VPRM coupling model; Step 2, inputting the input files generated in Step 1 into the WRF-VPRM coupling model based on three crops to simulate the photosynthetic carbon assimilation and the CO2 flux released by respiration of the main cereal crops such as rice, wheat and corn; Step 3, based on the CO2 flux data simulated in Step 2, extracting the net CO2 flux of the MCCs crop type in the terrestrial ecosystem as the basis for estimating the net carbon assimilation of CO2; Step 4, calculating the net assimilated carbon distribution of each component of the MCCs in the growth cycle; Step 4 comprises: Step 4.1, calculating the carbon amount distributed to each crop biomass, and the calculation formula is: wherein: Cassis the amount of carbon allocated to each crop biomass for each grid cell, Cassis the amount of carbon assimilated by photosynthesis, Cassis the amount of carbon released by respiration, Cassis the amount of carbon deposited into the soil through rhizodeposition; i,j is for each grid cell, s takes values (1,2,3) for rice, wheat and corn, respectively; Step 4.2, calculating the carbon amount distributed to the roots and other parts of the MCCs, and the calculation formula is: wherein: is the amount of carbon allocated to the roots, is the amount of carbon allocated to the parts other than roots, is the crop root / shoot ratio in different regions of China; Step 4.3, calculating the carbon amount distributed to the grains, collectable straw and residues of the MCCs, and the calculation formula is: wherein: C C is the amount of carbon allocated to grain, C C is the amount of carbon allocated to harvestable stover, C C is the amount of carbon allocated to residue, CC s C C is the harvestable coefficient of crop stover, C C is the crop straw-to-grain ratio for different regions in China; Step 4.4, calculating the carbon amount remaining in the farmland, and the calculation formula is: In the formula: is the amount of carbon remaining in the field, including crop roots and residues; Step 5, determining the distribution of biomass carbon in different straw management practices; In Step 5, the straw management practices include straw feed, raw material, base material, fertilizer, fuel and waste; The calculation formula for the carbon distribution to the collectable straw five material utilization is: In the formula: F is the carbon amount allocated to straw feed, raw material, base material, fertilizer, fuel, and waste, F feed F raw F base F fert F fuel F dis F is the proportion of straw feed, raw material, base material, fertilizer, fuel, and waste in China. Step 6, according to the local soil organic carbon conversion rate, calculating the soil organic carbon sequestration of the roots, residues and straw used as fertilizer returned to the field of each grid unit and each crop; The calculation formula for the soil organic carbon sequestration of each grid unit and each crop residue returned to the field is: wherein: is the current soil organic carbon sequestration, is the amount of carbon allocated to the collected straw for use as fertilizer returned to the field, Eff i,j is the soil organic carbon conversion rate of crop straw returned to the field in China. Step 7, calculating the total soil organic carbon sequestration of the MCCs residue returned to the field of all grid units.

2. The method of estimating the amount of soil organic carbon sequestration from crop residue retention according to claim 1, wherein, In Step 1, the input files include vegetation parameter files, meteorological and chemical initial and boundary condition files, human source CO2 emission files, and files containing the distribution of rice, wheat and corn crops and the key parameters of the VPRM model.

3. A system for estimating the amount of soil organic carbon sequestration from crop residues returned to the field, characterized in that, The method for performing any one of claims 1 to 2 comprises: an obtaining module configured to obtain and process multi-source data to generate input files required for running the WRF-VPRM coupling model; a simulation module configured to input the input files generated by the obtaining module into the WRF-VPRM coupling model based on three crops to simulate the photosynthetic carbon assimilation and the CO2 flux released by respiration of the main cereal crops; an extraction module configured to extract the net CO2 flux of the MCCs crop type in the terrestrial ecosystem based on the CO2 flux data simulated by the simulation module as the basis for estimating the net carbon assimilation of CO2; a first calculation module configured to calculate the net assimilated carbon distribution of each component of the MCCs in the growth cycle; a determination module configured to determine the distribution of biomass carbon in different straw management practices; a second calculation module configured to calculate the soil organic carbon sequestration of the roots, residues and straw used as fertilizer returned to the field of each grid unit and each crop according to the local soil organic carbon conversion rate; a third calculation module configured to calculate the total soil organic carbon sequestration of the MCCs residue returned to the field of all grid units.

4. A computer storage medium, characterized in that, The computer storage medium stores a computer program; the computer program makes the computer execute the method in any one of claims 1 to 2 when running on the computer.

5. An electronic device, comprising: Comprise: a memory for saving a computer program; a processor for executing the computer program to realize the method in any one of claims 1 to 2.

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