Planting agriculture carbon sink metering method and system and computing device

Abstract

The invention provides a planting agriculture carbon sink metering method and system and computing equipment. The method comprises the following steps: establishing a dynamic farmland ecosystem carbon sink model according to biomass monitoring data, soil carbon content data, meteorological data and crop management measure records of a farmland ecosystem; based on the dynamic farmland ecosystem carbon sink model, analyzing carbon fixation efficiency under different crop types and different farming modes in a farmland ecosystem; and calculating the total carbon sink amount of the farmland ecosystem. According to the technical scheme provided by the invention, the dynamic farmland ecosystem carbon sink model is established, so that the carbon absorption capacity of the farmland ecosystem can be more accurately quantified, and the carbon sink metering precision is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of carbon sink measurement, and in particular to a method, system and computing device for measuring carbon sinks in planting agriculture. Background Art

[0002] With the rise and development of the carbon trading market, it is particularly important to accurately measure the carbon sequestration of farmland ecosystems. This can not only provide a scientific basis for agricultural carbon sequestration projects, but also help companies, farmers and government agencies better understand the carbon absorption capacity of farmland, so as to formulate effective carbon reduction policies and measures. In addition, the impact of climate change on agricultural production is becoming more and more significant, so a technical means is needed to monitor and evaluate the impact of climate change on the carbon fixation capacity of farmland ecosystems in real time.

[0003] At present, most methods used to measure carbon sinks in farmland ecosystems rely mainly on static models and a small amount of field observation data. These methods usually only consider biomass monitoring data and soil organic carbon content, ignoring the combined effects of climate change, agricultural management measures and other factors. Although static models can provide certain carbon sink estimates, they are obviously insufficient in terms of accuracy and dynamism.

[0004] The existing carbon sink measurement methods have the following main defects:

[0005] Lack of dynamism: Most existing measurement methods are static models that cannot update data in real time, nor can they effectively reflect the impact of climate change and changes in management measures on carbon sinks.

[0006] Single data dimension: Traditional methods often only consider biomass and soil carbon content, ignoring the impact of meteorological data, agricultural management measures, etc. on carbon sequestration, resulting in incomplete measurement results.

[0007] Low precision: Due to limited data sources and lack of continuous monitoring, existing measurement methods are difficult to provide high-precision carbon sink estimates, especially in assessing differences under different crop types and farming methods. Summary of the invention

[0008] The embodiments of the present application provide a method, system and computing device for measuring carbon sinks in planting agriculture, which are used to solve the problems of lack of dynamics, single data dimension and low accuracy in the prior art.

[0009] In a first aspect, the present application provides a method for measuring agricultural carbon sinks, including:

[0010] A dynamic farmland ecosystem carbon sink model is established based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management records of the farmland ecosystem. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation;

[0011] Based on the dynamic farmland ecosystem carbon sink model, the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem is analyzed, wherein the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period;

[0012] The total carbon sink of the farmland ecosystem is calculated, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while considering the impact of different crop rotation patterns on the carbon sink.

[0013] Optionally, before establishing a dynamic farmland ecosystem carbon sink model based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records of the farmland ecosystem, the method further includes:

[0014] Collecting crop biomass monitoring data and soil carbon content data in farmland ecosystems, and collecting meteorological data in the area where the farmland is located, wherein the biomass monitoring data includes the dry weight of the above-ground and underground parts of the crops;

[0015] The historical records of farmland management measures are integrated to obtain agricultural management measure records, wherein the agricultural management measure records include information on fertilization, irrigation, and tillage methods.

[0016] Optionally, the carbon sequestration efficiency of different crop types and different farming methods in the farmland ecosystem is analyzed based on the dynamic farmland ecosystem carbon sink model, including:

[0017] Using the basic carbon sink database, compare the biomass growth rate of different crop types in the same growth cycle and their impact on soil organic carbon accumulation;

[0018] To evaluate the effects of different tillage practices on soil structure improvement, i.e. the effects of different tillage practices on soil aeration and water retention;

[0019] The carbon fixation efficiency of different crop types and tillage methods was evaluated by comprehensively considering the crop biomass growth rate, soil structure improvement effect and tillage methods.

[0020] Optionally, the calculating of the total carbon sink of the farmland ecosystem includes:

[0021] Analyze the effects of climate conditions, soil types, and crop rotation patterns in different regions of farmland ecosystems on crop growth and soil carbon fixation;

[0022] Consider the optimization scheme of crop layout within the farmland ecosystem;

[0023] Combining the dynamic farmland ecosystem carbon sink model and crop layout optimization plan, the total carbon sink of the farmland ecosystem is estimated, and the impact of future climate change on the carbon sink is predicted.

[0024] Optionally, it also includes:

[0025] Establish a long-term monitoring mechanism for carbon sequestration in farmland ecosystems;

[0026] Adjust farmland management measures to enhance the carbon sequestration function of farmland ecosystems based on monitoring results and climate change predictions;

[0027] Regularly publish carbon sequestration reports on agricultural ecosystems.

[0028] Optionally, the calculation formula for calculating the total carbon sink of the farmland ecosystem is as follows:

[0029]

[0030] Among them, C total represents the total carbon sink of the farmland ecosystem, i represents different crop types, n is the number of crop types in the farmland ecosystem, is the sum of the carbon sinks of each crop in the farmland ecosystem. represents the biomass carbon sink of the i-th crop, represents the soil carbon sink corresponding to the i-th crop, represents the amount of carbon dioxide emitted by the respiration of the i-th crop, represents the additional carbon emissions caused by the use of fertilizers, represents the additional carbon sink brought by the crop rotation pattern, η climate represents the climate change factor, ζ management represents the impact factor of management measures, θ soil represents the soil type influencing factor, ξ irrigation represents the influencing factor of irrigation method, is the net carbon sink of the i-th crop, (1+η climate +ζ management +θ soil +ξ irrigation ) represents the net carbon sink amount adjusted for each crop.

[0031] Optionally, the biomass carbon sink of the i-th crop in the farmland ecosystem is Calculated using the following formula:

[0032]

[0033] Among them, M i is the biomass mass of the i-th crop (kg), C content is the carbon content ratio in crop biomass, and 12 / 44 is a conversion factor used to convert carbon content into carbon dioxide equivalent. is to calculate the carbonization amount of the i-th crop in its biomass, α climate is the climate change factor, T is the average temperature change, β management is the management measure influencing factor, M manage is the management measure intensity index, γ soil is the soil type influencing factor, S is the soil type index, δ irrigation is the irrigation method influencing factor, I is the irrigation method index, (1+α climate ·T+β management ·M manage +γ soil ·S+δ irrigation I) is to adjust the biomass carbon sink of crops to reflect the impact of climate change, management practices, soil type and irrigation methods on carbon sinks.

[0034] Optionally, the soil carbon sink corresponding to the i-th crop in the farmland ecosystem is Calculated using the following formula:

[0035]

[0036] Where A is the farmland area (m 2 ), D is the soil sampling depth (cm), OC i is the soil organic carbon content (%) corresponding to the i-th crop, OC ref is the reference soil organic carbon content used for baseline comparison, (OC i -OC ref ) reflects the change in soil organic carbon content after planting the i-th crop, η climate is the climate change factor, management is the management measure influencing factor, θ soil is the soil type influencing factor, ξ irrigation is the irrigation method influencing factor, (1+η climate +ζ management +θ soil +ζ irrigation ) is an overall multiplication factor used to adjust the calculated soil carbon sink.

[0037] In a second aspect, the present application embodiment provides a planting agricultural carbon sink measurement system, including:

[0038] A model building module is used to build a dynamic farmland ecosystem carbon sink model based on the farmland ecosystem biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation;

[0039] An analysis module, for analyzing the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem based on the dynamic farmland ecosystem carbon sink model, wherein the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period;

[0040] The calculation module is used to calculate the total carbon sink of the farmland ecosystem, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while taking into account the impact of different crop rotation patterns on the carbon sink.

[0041] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for measuring agricultural carbon sinks as described in any one of the first aspects above.

[0042] In the embodiment of the present application, a dynamic farmland ecosystem carbon sink model is established based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records of the farmland ecosystem. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation; based on the dynamic farmland ecosystem carbon sink model, the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem is analyzed, and the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period; the total carbon sink of the farmland ecosystem is calculated, and the total carbon sink refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific time period, while considering the impact of different crop rotation patterns on the carbon sink. The technical solution provided in this application can more accurately quantify the carbon absorption capacity of the farmland ecosystem by establishing a dynamic farmland ecosystem carbon sink model, thereby improving the accuracy of carbon sink measurement.

[0043] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A flow chart of a method for measuring agricultural carbon sinks provided in an embodiment of the present application;

[0046] Figure 2 A structural schematic diagram of a planting agricultural carbon sink measurement system provided in an embodiment of the present application;

[0047] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0049] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0050] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0051] Figure 1 A flowchart of a method for measuring agricultural carbon sinks is provided for an embodiment of the present application. Figure 1 As shown, the method includes:

[0052] 101. Based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management records of the farmland ecosystem, a dynamic farmland ecosystem carbon sink model is established. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation;

[0053] Optionally, before step 101 "establishing a dynamic farmland ecosystem carbon sink model based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records of the farmland ecosystem", it also includes: collecting biomass monitoring data and soil carbon content data of crops in the farmland ecosystem, and collecting meteorological data of the area where the farmland is located, the biomass monitoring data includes the dry weight of the above-ground and underground parts of the crops; integrating historical records of farmland management measures to obtain agricultural management measures records, and the agricultural management measures records include information on fertilization, irrigation, and tillage methods.

[0054] In this step:

[0055] Biomass monitoring data: refers to the biomass monitoring data of crops in farmland ecosystems, including the dry weight of the above-ground parts (such as stems and leaves) and underground parts (such as roots) of crops. Biomass monitoring data is one of the basic data for assessing the carbon fixation capacity of farmland ecosystems, reflecting the growth status of crops and their carbon fixation capacity.

[0056] Soil carbon content data: refers to the organic carbon content data in the soil, which reflects the accumulation of organic carbon in the soil. Soil carbon content data is one of the important indicators for evaluating the carbon sequestration capacity of farmland ecosystems.

[0057] Meteorological data: refers to the meteorological data of the area where the farmland is located, including but not limited to temperature, precipitation, light intensity, etc. Meteorological data is crucial to understanding the impact of climate change on the carbon fixation capacity of farmland ecosystems.

[0058] Agricultural management measures records: refers to the records of various measures taken during farmland management, including information on fertilization, irrigation, tillage methods, etc. These measures directly affect crop growth and soil carbon fixation capacity.

[0059] Dynamic farmland ecosystem carbon sink model: a mathematical model used to simulate and predict the carbon absorption capacity of farmland ecosystems. The model takes into account environmental factors (such as climate change), biomass changes (crop growth cycle) and management measures (fertilization, irrigation, farming methods) to provide more accurate carbon sink estimates.

[0060] In the present embodiment, it is assumed that a research team is studying a farmland ecosystem located in the North China Plain. The farmland mainly grows wheat and corn, and implements a two-season crop rotation system. The research team first collected the following data:

[0061] Biomass monitoring data: In the summer of 2022, the dry weight of wheat at harvest was 400 kilograms per mu; in the autumn, the dry weight of corn at harvest was 600 kilograms per mu.

[0062] Soil carbon content data: Through the analysis of farmland soil samples, it is known that the soil organic carbon content is 15 grams of organic carbon per kilogram of soil.

[0063] Meteorological data: Data on temperature, precipitation, and other data for the entire year of 2022 were obtained from the local meteorological station.

[0064] Records of agricultural management measures: including information such as fertilization (10 kg of urea per mu in spring each year), irrigation (once every two weeks in summer, 5 cubic meters of water per mu each time), and tillage methods (ploughing before sowing in spring).

[0065] Next, the research team integrated the above data and established a comprehensive model framework that takes into account the impact of all the above factors on the carbon sequestration capacity of farmland ecosystems. For example, the model can predict the carbon sequestration capacity of farmland ecosystems under different fertilizer application rates, irrigation frequencies, and climate change scenarios.

[0066] Design principle:

[0067] Comprehensive consideration: The design principle of this step is to comprehensively consider the impact of multiple factors on the carbon sequestration capacity of farmland ecosystems. By integrating multi-source data, the model is closer to the actual situation and the accuracy of the prediction is improved.

[0068] Dynamic response: By considering factors such as climate change and changes in management measures, the model has dynamic response capabilities and can adjust carbon sink forecasts in a timely manner according to changes in the environment and management measures.

[0069] Data-driven: The model is established using actual collected data, which ensures the reliability and practicality of the model, so that the model can not only be used for scientific research, but also serve practical applications such as carbon trading and policy making.

[0070] Purpose:

[0071] The main purpose of this step is to provide a more accurate and dynamic method to quantify the carbon absorption capacity of farmland ecosystems by establishing a dynamic farmland ecosystem carbon sink model, thereby providing a scientific basis for the evaluation of agricultural carbon sink projects, optimization of management measures and response to climate change.

[0072] Improvements:

[0073] Compared with the traditional static model, the dynamic model proposed in this step can better reflect the complexity and dynamic changes of the real world, and improve the accuracy and reliability of carbon sink prediction.

[0074] 102. Based on the dynamic farmland ecosystem carbon sink model, analyze the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem, where the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period;

[0075] Optionally, the "analyzing the carbon fixation efficiency of different crop types and different tillage methods in the farmland ecosystem based on the dynamic farmland ecosystem carbon sink model" in step 102 includes: using the carbon sink basic database to compare the biomass growth rate of different crop types in the same growth cycle and its impact on soil organic carbon accumulation; evaluating the impact of different tillage methods on soil structure improvement, wherein the impact refers to the effect of different tillage methods on soil aeration and water retention; comprehensively considering the crop biomass growth rate, soil structure improvement effect and tillage methods, and evaluating the carbon fixation efficiency of different crop types and tillage methods.

[0076] In this step:

[0077] Carbon fixation efficiency: refers to the ability of crops per unit area to fix carbon dioxide during the growing period. This is a key indicator to measure the carbon sequestration capacity of farmland ecosystems.

[0078] Carbon sink basic database: refers to a database that collects crop biomass monitoring data, soil carbon content data, agricultural management measures and other related information in farmland ecosystems. These data provide a basis for analyzing the carbon fixation efficiency under different crop types and farming methods.

[0079] Biomass growth rate: refers to the growth rate of crop biomass during the growth cycle. The higher the biomass growth rate, the more carbon dioxide the crop fixes, and the higher the carbon fixation efficiency.

[0080] Soil organic carbon accumulation: refers to the increase in organic carbon in the soil over a certain period of time. Soil organic carbon accumulation reflects the carbon fixation capacity of the soil.

[0081] Soil structure improvement: refers to the process of improving soil structure (such as aeration and water retention) through different farming methods. Good soil structure helps improve the carbon fixation efficiency of the soil.

[0082] Tillage method: refers to various tillage measures used in farmland management, such as tillage, no-tillage, cover cropping, etc. Different tillage methods have different effects on soil structure and carbon fixation efficiency.

[0083] In the present example, it is assumed that a research team conducted a crop rotation experiment in a farmland in the North China Plain to study the carbon fixation efficiency of wheat and soybeans under different farming methods. The specific steps are as follows:

[0084] Data Collection:

[0085] Biomass monitoring data of wheat and soybean crops were collected, including the dry weight of the above-ground parts (such as stems and leaves) and underground parts (such as roots).

[0086] Soil samples were collected to determine the soil organic carbon content.

[0087] Record weather data for the area where the farmland is located.

[0088] The historical records of farmland management measures are integrated to obtain agricultural management measure records, which include fertilization, irrigation, and tillage method information (such as tillage and no-tillage).

[0089] Data Analysis:

[0090] Using the basic carbon sink database, we compared the biomass growth rate of wheat and soybeans during the same growth cycle and their impact on soil organic carbon accumulation. For example, through field experiments, we found that the biomass growth rate of wheat during the growth period was 1 kg per mu per day, while that of soybeans was 0.8 kg per mu per day. At the same time, we measured the soil organic carbon content and found that the soil organic carbon content of wheat-growing soil contained 15 grams of organic carbon per kilogram of soil, while that of soybeans contained 13 grams of organic carbon per kilogram of soil.

[0091] Evaluate the effects of different tillage methods (such as tillage and no-till) on soil structure improvement. Through experiments, it was found that no-till can improve soil aeration and water retention, which is conducive to the accumulation of soil organic carbon. For example, under no-till conditions, soil aeration increased by 10% and water retention increased by 5%.

[0092] Comprehensive Assessment:

[0093] The carbon fixation efficiency of different crop types and tillage methods is evaluated by comprehensively considering the biomass growth rate of crops, the effect of improving soil structure, and tillage methods. For example, according to the above data analysis, it is concluded that the carbon fixation efficiency of wheat under no-tillage is higher than that of soybeans, which is manifested in the higher biomass growth rate of wheat, more soil organic carbon accumulation, and better soil structure.

[0094] Assuming you want to calculate the carbon fixation efficiency of wheat and soybeans under no-till and tillage farming methods, you can use the following formula to estimate:

[0095]

[0096] Among them, E crop is the carbon fixation efficiency of crops (tons / hectare), A is the farmland area (hectares), B growth is the crop biomass growth rate (kg / day), Ccontent is the carbon content ratio in crop biomass (%), S carbon is the soil organic carbon accumulation (tons / hectare), η structure is the soil structure improvement factor (%).

[0097] Assume that by calculation:

[0098] The biomass growth rate of wheat under no-tillage is 100 kg per hectare per day, the carbon content is 50%, the soil organic carbon accumulation is 2 tons per hectare per year, the farmland area is 1 hectare, and the soil structure improvement factor is 10%.

[0099] The biomass growth rate of soybeans under no-tillage is 80 kg per hectare per day, the carbon content is 45%, the soil organic carbon accumulation is 1.5 tons per hectare per year, the farmland area is 1 hectare, and the soil structure improvement factor is 8%.

[0100] The carbon fixation efficiency of wheat under no-tillage is:

[0101]

[0102] The carbon fixation efficiency of soybean under no-tillage is:

[0103]

[0104] The design principle of this step:

[0105] Comprehensive consideration: The design principle of this step is to comprehensively consider the impact of different crop types and tillage methods on carbon fixation efficiency. By comparing the biomass growth rate of different crop types in the same growth cycle and its impact on soil organic carbon accumulation, as well as evaluating the effect of different tillage methods on soil structure improvement, the evaluation results are more comprehensive and accurate.

[0106] Dynamic response: By considering factors such as climate change and changes in management measures, the model has dynamic response capabilities and can adjust the assessment of carbon fixation efficiency in a timely manner according to changes in the environment and management measures.

[0107] Data-driven: The analysis is based on actual collected data, which ensures the reliability and practicality of the evaluation results. This allows the model to be used not only for scientific research but also for practical applications, such as the selection of crop varieties and the optimization of farming methods.

[0108] Purpose:

[0109] The main purpose of this step is to provide a more scientific method to guide the management and optimization of farmland ecosystems by analyzing the carbon fixation efficiency under different crop types and farming methods, thereby improving the carbon sequestration capacity of farmland ecosystems.

[0110] Improvements:

[0111] Compared with the traditional static assessment method, the comprehensive assessment method proposed in this step can better reflect the complexity and dynamic changes of the real world, and improve the accuracy and reliability of carbon fixation efficiency assessment.

[0112] 103. Calculate the total carbon sink of the farmland ecosystem, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while taking into account the impact of different crop rotation patterns on the carbon sink.

[0113] Optionally, in step 103, "the calculation of the total carbon sink of the farmland ecosystem" includes: analyzing the effects of climate conditions, soil types, and crop rotation patterns in different regions of the farmland ecosystem on crop growth and soil carbon fixation; considering the optimization plan for crop layout within the farmland ecosystem; combining the dynamic farmland ecosystem carbon sink model and the crop layout optimization plan to estimate the total carbon sink of the farmland ecosystem and predict the impact of future climate change on the carbon sink.

[0114] Optionally, in step 103, "the calculation formula for calculating the total carbon sink of the farmland ecosystem is as follows":

[0115]

[0116] Among them, C total represents the total carbon sink of the farmland ecosystem, i represents different crop types, n is the number of crop types in the farmland ecosystem, is the sum of the carbon sinks of each crop in the farmland ecosystem. represents the biomass carbon sink of the i-th crop, represents the soil carbon sink corresponding to the i-th crop, represents the amount of carbon dioxide emitted by the respiration of the i-th crop, represents the additional carbon emissions caused by the use of fertilizers, represents the additional carbon sink brought by the crop rotation pattern, η climate represents the climate change factor, ζ management represents the impact factor of management measures, θ soil represents the soil type influencing factor, ξ irrigation represents the influencing factor of irrigation method, is the net carbon sink of the i-th crop, (1+η climate +ζ management +θ soil +ξ irrigation ) represents the net carbon sink amount adjusted for each crop.

[0117] In this step:

[0118] Total Carbon Sequestration: refers to the total amount of carbon dioxide accumulated and fixed by farmland ecosystems in a specific period of time. This amount combines factors such as biomass carbon sequestration of different crops in the farmland, soil carbon sequestration, carbon dioxide emissions from respiration, additional carbon emissions from fertilizer use, and additional carbon sequestration brought about by crop rotation patterns.

[0119] Climate Conditions: refers to the climate conditions in different areas of the farmland ecosystem, including temperature, precipitation, light, etc. These conditions have an important impact on crop growth and soil carbon fixation.

[0120] Soil Type: refers to the soil types of different plots in farmland. Different soil types have different physical and chemical properties, such as soil texture, pH value, etc. These properties will affect the accumulation of organic carbon in the soil.

[0121] Crop Rotation Pattern: refers to the planting order and combination of different crops in farmland. The crop rotation pattern can improve soil health, increase soil organic carbon content, and thus enhance the carbon sequestration capacity of farmland ecosystems.

[0122] Optimized Crop Layout Plan: refers to the optimization plan for crop layout within the farmland ecosystem. Through reasonable crop layout, the carbon sequestration capacity of farmland can be increased.

[0123] Dynamic Agroecosystem Carbon Sequestration Model: A mathematical model used to simulate and predict the carbon absorption capacity of agricultural ecosystems. The model takes into account environmental factors, biomass changes, and management measures to provide a more accurate estimate of carbon sequestration.

[0124] Prediction of Climate Change Impact on Carbon Sequestration: refers to the assessment of the impact of future climate change on carbon sequestration in agricultural ecosystems based on climate change prediction models.

[0125] Adjustment factors: including climate change factors (η climate ), management measures influencing factors (ζ management ), soil type influencing factor (θ soil ) and irrigation method influencing factors (ξirrigation ), these factors are used to adjust the net carbon sink of each crop to make the calculation results more consistent with the actual situation.

[0126] In the example of this application, it is assumed that a research team calculated the carbon sequestration in a farmland in Northeast China for one year. The farmland was planted with three crops: corn, soybeans and wheat, and a crop rotation pattern was implemented. The research team first collected the following data:

[0127] Climate conditions: The average annual temperature is 10℃ and the annual precipitation is 500 mm.

[0128] Soil Type: The soil is black soil with a pH of 7.5.

[0129] Crop rotation pattern: corn in the first year, soybeans in the second year, and wheat in the third year.

[0130] Crop layout optimization plan: The optimal crop layout plan is formulated based on soil type and climatic conditions.

[0131] Dynamic farmland ecosystem carbon sink model: takes into account factors such as climate conditions, soil type, and crop rotation patterns.

[0132] Next, the research team used the above data to calculate the total carbon sink:

[0133] Data preparation:

[0134] Biomass monitoring data of three crops, corn, soybean and wheat, were collected, including the dry weight of the above-ground and underground parts of the crops.

[0135] Determination of soil organic carbon content.

[0136] Record weather data for the area where the farmland is located.

[0137] The historical records of farmland management measures are integrated to obtain agricultural management measure records, wherein the agricultural management measure records include information on fertilization, irrigation, and tillage methods.

[0138] Data input:

[0139] It is assumed that the biomass carbon sink of corn is 2 tons per hectare per year, the soil carbon sink is 1 ton per hectare per year, the carbon dioxide emissions from respiration are 0.5 tons per hectare per year, the additional carbon emissions caused by fertilizer use are 0.2 tons per hectare per year, and the additional carbon sink brought by the rotation pattern is 0.3 tons per hectare per year.

[0140] The biomass carbon sequestration of soybeans is 1.5 tons per hectare per year, the soil carbon sequestration is 0.8 tons per hectare per year, the carbon dioxide emissions from respiration are 0.4 tons per hectare per year, the additional carbon emissions caused by fertilizer use are 0.1 tons per hectare per year, and the additional carbon sequestration brought by the rotation pattern is 0.2 tons per hectare per year.

[0141] The biomass carbon sink of wheat is 1.8 tons per hectare per year, the soil carbon sink is 0.9 tons per hectare per year, the carbon dioxide emissions from respiration are 0.3 tons per hectare per year, the additional carbon emissions caused by fertilizer use are 0.15 tons per hectare per year, and the additional carbon sink brought by crop rotation pattern is 0.25 tons per hectare per year.

[0142] Assumptions:

[0143] η climate = 0.05 (climate change causes a 5% increase in carbon sinks),

[0144] ζ management = 0.03 (management measures lead to a 3% increase in carbon sinks),

[0145] θ soil = 0.02 (soil type leads to a 2% increase in carbon sink),

[0146] ξ irrigation =0.04 (irrigation method leads to a 4% increase in carbon sink).

[0147] Calculate the net carbon sink for each crop:

[0148] The net carbon sink for corn is:

[0149] C corn =(2+1-0.5-0.2+0.3)×(1+0.05+0.03+0.02+0.04)=2.6×1.14=2.964 tons / hectare

[0150] The net carbon sink of soybeans is:

[0151] C soybean =(1.5+0.8-0.4-0.1+0.2)×(1+0.05+0.03+0.02+

[0152] 0.04) = 2 × 1.14 = 2.28 tons / hectare

[0153] The net carbon sink of wheat is:

[0154] C wheat =(1.8+0.9-0.3-0.15+0.25)×(1+0.05+0.03+0.02+

[0155] 0.04) = 2.5 × 1.14 = 2.85 tons / hectare

[0156] Finally, the total carbon sink of the farmland ecosystem is calculated:

[0157] C total =2.964+2.28+2.85=8.094 tons / hectare

[0158] Design principle:

[0159] Comprehensive consideration: The design principle of this step is to comprehensively consider the impact of multiple factors on the carbon sequestration of farmland ecosystems. By integrating multi-source data, the model is closer to reality and the accuracy of the prediction is improved.

[0160] Dynamic response: By considering factors such as climate change and changes in management measures, the model has dynamic response capabilities and can adjust carbon sink forecasts in a timely manner according to changes in the environment and management measures.

[0161] Data-driven: Calculations are performed using actual collected data, ensuring the reliability and practicality of the results. This allows the model to be used not only for scientific research but also for practical applications, such as carbon trading and policy making.

[0162] Purpose:

[0163] The main purpose of this step is to provide a more accurate method to quantify the carbon absorption capacity of farmland ecosystems by calculating the total carbon sink of farmland ecosystems, thereby providing a scientific basis for the evaluation of agricultural carbon sink projects, optimization of management measures and response to climate change.

[0164] Improvements:

[0165] Compared with the traditional static model, the calculation method proposed in this step can better reflect the complexity and dynamic changes of the real world, and improve the accuracy and reliability of carbon sink prediction.

[0166] Optionally, it also includes: establishing a long-term monitoring mechanism for carbon sequestration in farmland ecosystems; adjusting farmland management measures to enhance the carbon sequestration function of farmland ecosystems based on monitoring results and climate change forecasts; and regularly publishing farmland ecosystem carbon sequestration reports.

[0167] In this step, the long-term monitoring mechanism refers to a system established to continuously track the trend of carbon sink changes in farmland ecosystems. This mechanism includes regularly collecting various relevant data in farmland ecosystems (such as biomass, soil carbon content, meteorological data, etc.) and analyzing them through dynamic models to evaluate the carbon sink function of farmland ecosystems.

[0168] Monitoring results: refers to the results obtained through the analysis of various data collected through long-term monitoring mechanisms. These results reflect the carbon sequestration status of farmland ecosystems under different times and conditions, and provide a scientific basis for subsequent adjustment of management measures.

[0169] Climate change prediction: refers to the prediction of climate change trends in the future, including changes in key meteorological elements such as temperature and precipitation. This prediction information is crucial for assessing the impact of climate change on the carbon sink function of farmland ecosystems.

[0170] Adjusting farmland management measures: refers to timely adjusting farmland management measures (such as fertilization, irrigation, farming methods, etc.) based on monitoring results and climate change forecasts to enhance the carbon sink function of farmland ecosystems. The purpose of adjusting measures is to optimize farmland management and increase carbon sinks.

[0171] Regularly publish carbon sink reports: This means compiling monitoring results and analysis conclusions into reports and publishing them to the public on a regular basis. Carbon sink reports can provide detailed information on the carbon sink function of farmland ecosystems to policy makers, researchers and relevant stakeholders so that they can make reasonable decisions.

[0172] In the example of this application, it is assumed that a research team has established a long-term monitoring mechanism on a piece of farmland in the North China Plain to monitor the changes in carbon sinks in the farmland ecosystem and adjust farmland management measures based on the monitoring results and climate change predictions. The specific steps are as follows:

[0173] Establish a long-term monitoring mechanism:

[0174] Establish fixed monitoring points: Establish several fixed monitoring points in the farmland to collect soil samples, crop biomass monitoring data and meteorological data regularly.

[0175] Install automatic monitoring equipment: Install automatic weather stations and soil temperature and humidity sensors to monitor the meteorological conditions and soil conditions of farmland in real time.

[0176] Set up a monitoring cycle: Set up a monthly monitoring cycle to collect and analyze data regularly.

[0177] Analysis of monitoring results:

[0178] Data collection: Biomass, soil carbon content, meteorological data, etc. in farmland ecosystems will be collected once a month throughout 2023.

[0179] Data analysis: Analyze monitoring data through a dynamic farmland ecosystem carbon sink model to evaluate the carbon sink function of the farmland ecosystem.

[0180] Monitoring results show that the carbon sequestration of farmland ecosystems was 8 tons per hectare per year in 2023, but due to climate change, the carbon sequestration is expected to drop to 7.5 tons per hectare per year in 2024.

[0181] Adjust management measures:

[0182] Based on the monitoring results and climate change forecasts, the research team decided to adjust farmland management measures to enhance carbon sequestration function.

[0183] The adjustment measures include: increasing the use of organic fertilizer to 20 tons of organic fertilizer per hectare per year; improving irrigation methods, adopting drip irrigation technology, and improving water resource utilization; adjusting farming methods, implementing no-till planting, and reducing soil disturbance.

[0184] Regularly publish carbon sink reports:

[0185] A farmland ecosystem carbon sink report is released every quarter, announcing monitoring results, adjustments to management measures, and carbon sink function assessments.

[0186] The report content includes: monitoring data, dynamic model analysis results, management measure adjustment plans and their expected effects, etc.

[0187] Design principle:

[0188] Continuous monitoring: By establishing a long-term monitoring mechanism, we can ensure that we can continuously track the changing trends of carbon sinks in farmland ecosystems and provide timely data support for adjusting management measures.

[0189] Dynamic adjustment: Dynamically adjust farmland management measures based on monitoring results and climate change forecasts to meet the challenges brought by climate change and enhance the carbon sequestration function of farmland ecosystems.

[0190] Transparency and openness: Regularly publish carbon sink reports to improve information transparency, provide scientific basis for relevant parties, promote multi-party collaboration, and jointly address climate change.

[0191] Purpose:

[0192] The main purpose of this step is to enhance the carbon sink function of farmland ecosystems by establishing a long-term monitoring mechanism, regularly analyzing monitoring results, and adjusting farmland management measures based on climate change forecasts. At the same time, carbon sink reports will be published regularly to improve information transparency and promote multi-party collaboration.

[0193] Improvements:

[0194] Compared with traditional static monitoring and management methods, this step proposes a dynamic adjustment mechanism that can better adapt to the uncertainties brought about by climate change and improve the carbon sequestration capacity of farmland ecosystems.

[0195] Technical terms:

[0196] Long-term Monitoring Mechanism

[0197] Monitoring Results

[0198] Climate Change Prediction

[0199] Management Practices

[0200] Carbon Sink Report

[0201] Specific data in the embodiment:

[0202] Assume that the monitoring data for the whole year of 2023 shows that the carbon sink of farmland ecosystem is 8 tons per hectare per year. According to climate change forecasts, the carbon sink is expected to drop to 7.5 tons per hectare per year in 2024. By adjusting management measures, the research team hopes to achieve a carbon sink of at least 7.8 tons per hectare per year in 2024.

[0203] The adjustment measures are as follows:

[0204] Increase the use of organic fertilizers to 20 tons per hectare per year.

[0205] Improve irrigation methods, adopt drip irrigation technology, and improve water resource utilization.

[0206] Adjust farming methods, implement no-till farming, and reduce soil disturbance.

[0207] Through these measures, it is expected that the carbon sequestration capacity of farmland ecosystems can be restored and slightly increased to 7.8 tons per hectare per year in 2024.

[0208] Optionally, the biomass carbon sink of the i-th crop in the farmland ecosystem is Calculated using the following formula:

[0209]

[0210] Where Mi is the biomass mass of the i-th crop (kg), C content is the carbon content ratio in crop biomass, and 12 / 44 is a conversion factor used to convert carbon content into carbon dioxide equivalent. is to calculate the carbonization amount of the i-th crop in its biomass, α climate is the climate change factor, T is the average temperature change, β management is the management measure influencing factor, Mmanage is the management measure intensity index, γ soil is the soil type influencing factor, S is the soil type index, δ irrigation is the irrigation method influencing factor, I is the irrigation method index, (1+α climate ·T+β management ·M manage +γ soil ·S+δ irrigation I) is to adjust the biomass carbon sink of crops to reflect the impact of climate change, management practices, soil type and irrigation methods on carbon sinks.

[0211] In this step:

[0212] Biomass carbon sink It refers to the amount of carbon dioxide fixed in the body of the i-th crop through photosynthesis during its growth cycle.

[0213] Biomass quality M i : refers to the biomass mass (kg) of the ith crop, that is, the total dry weight of the crop at a certain moment (usually at harvest).

[0214] Carbon content ratio C content : Refers to the proportion or percentage of carbon in the dry matter of crops. The carbon content ratio may vary among different crop types and at different growth stages.

[0215] Conversion Factor This is a conversion factor used to convert carbon content to carbon dioxide equivalents. The atomic weight of carbon is 12 and the molecular weight of carbon dioxide is 44, so each gram of carbon theoretically corresponds to grams of carbon dioxide. To put it simply, The reciprocal of is actually the conversion factor used to convert the mass of carbon into the corresponding mass of carbon dioxide.

[0216] Climate change impact factor α climate : This is a coefficient used to measure the impact of climate change on crop biomass carbon sequestration.

[0217] Mean temperature change T: This is the amount of temperature change relative to a base period (usually a historical average). Temperature changes can affect crop growth cycles and productivity.

[0218] Management measures impact factor β management :This is a coefficient used to measure the impact of different management measures (such as fertilization, irrigation, tillage methods, etc.) on crop biomass carbon sequestration.

[0219] Management measures intensity index M manage:This is a quantitative indicator used to indicate the degree or intensity of implementation of a certain management measure.

[0220] Soil type influence factorγ soil : This is a coefficient used to measure the impact of different soil types on crop biomass carbon sequestration.

[0221] Soil type index S: This is a quantitative index used to characterize soil types. Different soil types have different physical and chemical properties that affect crop growth and carbon fixation capacity.

[0222] Irrigation method influence factor δ irrigation : This is a coefficient used to measure the impact of different irrigation methods on crop biomass carbon sequestration.

[0223] Irrigation method index I: This is a quantitative indicator used to characterize a certain irrigation method. Different irrigation methods have different water-saving effects and support for crop growth.

[0224] Assume that a research team planted corn (crop type i = 1) and soybeans (crop type i = 2) in a field in the North China Plain. The following are the specific data and calculation steps:

[0225] Data preparation:

[0226] The biomass quality M1 of corn is 10,000 kg per hectare per year.

[0227] The biomass quality M2 of soybean is 8000 kg per hectare per year.

[0228] The carbon content of crop biomass is C content Both are 45%.

[0229] The average temperature change T is 0.5℃.

[0230] Management measures intensity index M manage is 1.2.

[0231] The soil type index S is 1.1.

[0232] The irrigation method index I is 1.05.

[0233] Climate change impact factor α climate is 0.02.

[0234] Management measures impact factor β management is 0.03.

[0235] Soil type impact factorγ soil is 0.01.

[0236] Irrigation method influence factor δirrigation is 0.01.

[0237] Calculate biomass carbon sink:

[0238] Use the formula to calculate the biomass carbon sink of corn and substitute the specific values:

[0239]

[0240] Use the same formula to calculate the biomass carbon sink of soybeans, substituting the specific values:

[0241]

[0242] Design principle:

[0243] Comprehensive consideration: The design principle of this step is to comprehensively consider the impact of multiple factors on crop biomass carbon sequestration. By integrating multi-source data, the calculation results are closer to reality and the accuracy of the prediction is improved.

[0244] Dynamic response: By considering factors such as climate change and changes in management measures, the model has dynamic response capabilities and can adjust the prediction of biomass carbon sinks in a timely manner according to changes in the environment and management measures.

[0245] Data-driven: Calculations are performed using actual collected data, ensuring the reliability and practicality of the results. This allows the model to be used not only for scientific research but also for practical applications, such as carbon trading and policy making.

[0246] Purpose:

[0247] The main purpose of this step is to provide a more accurate method to quantify the carbon fixation capacity of crops by calculating the biomass carbon sink of different crop types in farmland ecosystems, thereby providing a scientific basis for the evaluation of agricultural carbon sink projects, the optimization of management measures, and the response to climate change.

[0248] Improvements:

[0249] Compared with the traditional static model, the calculation method proposed in this step can better reflect the complexity and dynamic changes of the real world, and improve the accuracy and reliability of biomass carbon sink prediction.

[0250] Optionally, the soil carbon sink corresponding to the i-th crop in the farmland ecosystem is Calculated using the following formula:

[0251]

[0252] Where A is the farmland area (m 2 ), D is the soil sampling depth (cm), OC iis the soil organic carbon content (%) corresponding to the i-th crop, OC ref is the reference soil organic carbon content used for baseline comparison, (OC i -OC ref ) reflects the change in soil organic carbon content after planting the i-th crop, η climate is the climate change factor, management is the management measure influencing factor, θ soil is the soil type influencing factor, ξ irrigation is the irrigation method influencing factor, (1+η climate +ζ management +θ soil +ξ irrigation ) is an overall multiplication factor used to adjust the calculated soil carbon sink.

[0253] In this step:

[0254] Soil carbon sink It refers to the total amount of carbon dioxide fixed by the soil corresponding to the i-th crop in a specific period of time.

[0255] Farmland area A: refers to the total area of ​​farmland (m 2 ), which is the land area planted with the i-th crop in the farmland.

[0256] Soil sampling depth D: refers to the depth of the soil layer considered when calculating soil carbon sequestration (cm). Different soil depths may have different organic carbon contents.

[0257] Soil organic carbon content OC i : refers to the organic carbon content (%) in the soil corresponding to the i-th crop. This value reflects the change in soil organic carbon content caused by planting this crop.

[0258] Reference soil organic carbon content OC ref : Refers to the soil organic carbon content (%) used for baseline comparison. It can be the soil organic carbon content in the undisturbed or initial state, used as a reference standard.

[0259] Climate change factor η climate : This is a coefficient used to measure the impact of climate change on soil carbon sequestration.

[0260] Management measures influence factorζ management :This is a coefficient used to measure the impact of different management measures (such as fertilization, irrigation, tillage methods, etc.) on soil carbon sequestration.

[0261] Soil type influence factor θ soil : This is a coefficient used to measure the impact of different soil types on soil carbon sequestration.

[0262] Irrigation method influencing factorsξ irrigation : This is a coefficient used to measure the impact of different irrigation methods on soil carbon sequestration.

[0263] In the present embodiment, it is assumed that a research team planted corn (crop type i=1) and soybeans (crop type i=2) in a farmland in the Northeast Plain. The following are the specific data and calculation steps:

[0264] Data preparation:

[0265] The farmland area A is 1 hectare (10000m 2 ).

[0266] The soil sampling depth D was 30 cm.

[0267] The soil organic carbon content OC1 corresponding to corn is 2.5%.

[0268] The soil organic carbon content OC2 corresponding to soybean is 2.0%.

[0269] Reference soil organic carbon content OC ref It is 2.0%.

[0270] Climate change factor η climate is 0.05.

[0271] Management measures influence factorζ management is 0.03.

[0272] Soil type influence factor θ soil is 0.02.

[0273] Irrigation method influencing factorsξ irrigation is 0.04.

[0274] Calculate soil carbon sequestration:

[0275] Use the formula to calculate the soil carbon sequestration of corn and substitute the specific values:

[0276]

[0277] use

[0278]

[0279] Design principle:

[0280] Comprehensive consideration: The design principle of this step is to comprehensively consider the impact of multiple factors on soil carbon sequestration. By integrating multi-source data, the calculation results are closer to reality and the accuracy of the prediction is improved.

[0281] Dynamic response: By considering factors such as climate change and changes in management measures, the model has dynamic response capabilities and can adjust the prediction of soil carbon sequestration in a timely manner according to changes in the environment and management measures.

[0282] Data-driven: Calculations are performed using actual collected data, ensuring the reliability and practicality of the results. This allows the model to be used not only for scientific research but also for practical applications, such as carbon trading and policy making.

[0283] Purpose:

[0284] The main purpose of this step is to provide a more accurate method to quantify the carbon fixation capacity of soil by calculating the soil carbon sink of different crop types in farmland ecosystems, thereby providing a scientific basis for the evaluation of agricultural carbon sink projects, optimization of management measures and response to climate change.

[0285] Improvements:

[0286] Compared with the traditional static model, the calculation method proposed in this step can better reflect the complexity and dynamic changes of the real world, and improve the accuracy and reliability of soil carbon sink prediction.

[0287] Figure 2 A structural schematic diagram of a planting agricultural carbon sink measurement system is provided for an embodiment of the present application, such as Figure 2 As shown, the device comprises:

[0288] A model building module 21 is used to build a dynamic farmland ecosystem carbon sink model based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records of the farmland ecosystem, wherein the dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation;

[0289] An analysis module 22 is used to analyze the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem based on the dynamic farmland ecosystem carbon sink model, wherein the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period;

[0290] The calculation module 23 is used to calculate the total carbon sink of the farmland ecosystem, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while taking into account the impact of different crop rotation patterns on the carbon sink.

[0291] Figure 2 The agricultural carbon sink measurement system can be implemented Figure 1The implementation principle and technical effect of the agricultural carbon sink measurement method described in the embodiment are not described in detail. The specific way in which each module and unit performs operations in the agricultural carbon sink measurement system in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0292] In one possible design, Figure 2 A planting agricultural carbon sink measurement system of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0293] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0294] The processing component 32 is used to: establish a dynamic farmland ecosystem carbon sink model based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records of the farmland ecosystem, and the dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation; based on the dynamic farmland ecosystem carbon sink model, analyze the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem, and the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growing period; calculate the total carbon sink of the farmland ecosystem, and the total carbon sink refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific time period, while considering the impact of different crop rotation patterns on the carbon sink.

[0295] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0296] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0297] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0298] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0299] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0300] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0301] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 A method for measuring agricultural carbon sinks in the illustrated embodiment.

[0302] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0303] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0304] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0305] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for measuring agricultural carbon sinks, characterized in that: include: A dynamic farmland ecosystem carbon sink model is established based on the biomass monitoring data, soil carbon content data, meteorological data and agricultural management records of the farmland ecosystem. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation; Based on the dynamic farmland ecosystem carbon sink model, the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem is analyzed, wherein the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period; The total carbon sink of the farmland ecosystem is calculated, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while considering the impact of different crop rotation patterns on the carbon sink.

2. The method according to claim 1, characterized in that Before establishing a dynamic farmland ecosystem carbon sink model based on the farmland ecosystem biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records, it also includes: Collecting crop biomass monitoring data and soil carbon content data in farmland ecosystems, and collecting meteorological data in the area where the farmland is located, wherein the biomass monitoring data includes the dry weight of the above-ground and underground parts of the crops; The historical records of farmland management measures are integrated to obtain agricultural management measure records, wherein the agricultural management measure records include information on fertilization, irrigation, and tillage methods.

3. The method according to claim 1, characterized in that The carbon sequestration efficiency of different crop types and different farming methods in the farmland ecosystem is analyzed based on the dynamic farmland ecosystem carbon sink model, including: Using the basic carbon sink database, compare the biomass growth rate of different crop types in the same growth cycle and their impact on soil organic carbon accumulation; To evaluate the effects of different tillage practices on soil structure improvement, i.e. the effects of different tillage practices on soil aeration and water retention; The carbon fixation efficiency of different crop types and tillage methods was evaluated by comprehensively considering the crop biomass growth rate, soil structure improvement effect and tillage methods.

4. The method according to claim 1, characterized in that: The calculation of the total carbon sink of the farmland ecosystem includes: Analyze the effects of climate conditions, soil types, and crop rotation patterns in different regions of farmland ecosystems on crop growth and soil carbon fixation; Consider the optimization scheme of crop layout within the farmland ecosystem; Combining the dynamic farmland ecosystem carbon sink model and crop layout optimization plan, the total carbon sink of the farmland ecosystem is estimated, and the impact of future climate change on the carbon sink is predicted.

5. The method according to claim 1, characterized in that Also includes: Establish a long-term monitoring mechanism for carbon sequestration in farmland ecosystems; Adjust farmland management measures to enhance the carbon sequestration function of farmland ecosystems based on monitoring results and climate change predictions; Regularly publish carbon sequestration reports on agricultural ecosystems.

6. The method according to claim 1, characterized in that The calculation formula for calculating the total carbon sink of the farmland ecosystem is as follows: Among them, C total represents the total carbon sink of the farmland ecosystem, i represents different crop types, n is the number of crop types in the farmland ecosystem, is the sum of the carbon sinks of each crop in the farmland ecosystem. represents the biomass carbon sink of the i-th crop, represents the soil carbon sink corresponding to the i-th crop, represents the amount of carbon dioxide emitted by the respiration of the i-th crop, represents the additional carbon emissions caused by the use of fertilizers, represents the additional carbon sink brought by the crop rotation pattern, η climate represents the climate change factor, ζ management represents the impact factor of management measures, θ soil represents the soil type influencing factor, ξ irrigation represents the influencing factor of irrigation method, is the net carbon sink of the i-th crop, (1+η climate +ζ management +θ soil +ξ irrigation ) represents the net carbon sink amount adjusted for each crop.

7. The method according to claim 6, characterized in that The biomass carbon sink of the i-th crop in the farmland ecosystem Calculated using the following formula: Among them, M i is the biomass mass of the i-th crop (kg), C content is the carbon content ratio in crop biomass, and 12 / 44 is a conversion factor used to convert carbon content into carbon dioxide equivalent. is to calculate the carbonization amount of the i-th crop in its biomass, α climate is the climate change factor, T is the average temperature change, β management is the management measure influencing factor, M manage is the management measure intensity index, γ soil is the soil type influencing factor, S is the soil type index, δ irrigation is the irrigation method influencing factor, I is the irrigation method index, (1+α climate ·T+β management ·M manage +γ soil ·S+δ irrigation I) is to adjust the biomass carbon sink of crops to reflect the impact of climate change, management practices, soil type and irrigation methods on carbon sinks.

8. The method according to claim 6, characterized in that The soil carbon sink corresponding to the i-th crop in the farmland ecosystem Calculated using the following formula: Where A is the farmland area (m 2 ), D is the soil sampling depth (cm), OC i is the soil organic carbon content (%) corresponding to the i-th crop, OC ref is the reference soil organic carbon content used for baseline comparison, (OC i -OC ref ) reflects the change in soil organic carbon content after planting the i-th crop, η climate is the climate change factor, management is the management measure influencing factor, θ soil is the soil type influencing factor, ξ irrigation is the irrigation method influencing factor, (1+η climate +ζ management +θ soil +ξ irrigation Is an overall multiplication factor used to adjust soil carbon sink calculations.

9. A planting agricultural carbon sink measurement system, characterized in that: include: A model building module is used to build a dynamic farmland ecosystem carbon sink model based on the farmland ecosystem biomass monitoring data, soil carbon content data, meteorological data and agricultural management measures records. The dynamic farmland ecosystem carbon sink model is used to quantify the carbon absorption capacity of the farmland ecosystem and consider the impact of climate change on carbon fixation; An analysis module, for analyzing the carbon fixation efficiency of different crop types and different farming methods in the farmland ecosystem based on the dynamic farmland ecosystem carbon sink model, wherein the carbon fixation efficiency refers to the ability of crops per unit area to fix carbon dioxide during the growth period; The calculation module is used to calculate the total carbon sink of the farmland ecosystem, which refers to the total amount of carbon dioxide accumulated and fixed by the farmland ecosystem in a specific period of time, while taking into account the impact of different crop rotation patterns on the carbon sink.

10. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for measuring agricultural carbon sinks as described in any one of claims 1 to 8.

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