Method and system for predicting carbon dioxide flux of soil of alpine ecosystem

Abstract

The invention relates to the technical field of computer systems based on specific calculation models, in particular to a method and system for predicting the carbon dioxide flux of soil of a high and cold ecosystem, and the method comprises the steps: obtaining the total carbon dioxide emission data # imgabs0 # of soil in the past three months, obtaining the total carbon dioxide emission data # imgabs1 # of vegetation in the past three months, and obtaining the total carbon dioxide emission data # imgabs2 # of vegetation in the past three months; calculating a carbon dioxide emission difference rate # imgabs2 # based on the acquired data; defining a target difference rate model # imgabs3 #; the method comprises the following steps: acquiring data of soil carbon dioxide emission and total vegetation carbon dioxide emission in continuous 30 days in the future as to-be-predicted data, and inputting the predicted data into a target difference rate model # imgabs4 # to obtain # imgabs5 #; and judging the ratio # imgabs8 # of the target difference value rate model # imgabs6 # to the target difference value rate model # imgabs7 #. Through the target difference rate model # imgabs9 and the target difference rate model # imgabs10, rapid prediction of the carbon dioxide flux of the soil is realized, and an accurate prediction result on the basis of rapid prediction is realized through judgment of the ratio # imgabs11.

Description

Technical Field

[0001] The present application relates to the technical field of computer systems based on specific computing models, and in particular to a method for predicting soil carbon dioxide flux in a high-cold ecosystem, and also to a system. Background Art

[0002] Alpine ecosystems generally refer to two types of ecosystems: one is an ecosystem with high altitude, perennial low temperature, and perennial frozen soil; the other is an ecosystem with high latitude, perennial low temperature, and perennial frozen soil. At the same time, there are alpine ecosystems in northern Heilongjiang Province, the Qinghai-Tibet Plateau, Gansu, and parts of Inner Mongolia. The carbon balance of alpine ecosystems has a very important influence on the carbon balance of terrestrial ecosystems in my country and even the world. Reasonable control of the emission of carbon dioxide in the soil of alpine ecosystems is conducive to protecting the carbon-oxygen balance of alpine ecosystems and objectively estimating the specific status of carbon emissions in alpine areas.

[0003] The prior art disclosure date is July 31, 2020, the publication number is CN111476370A, and the name is Chinese invention patent application for grassland carbon dioxide flux prediction method and device. The disclosed method includes: real-time or periodic collection of environmental data of the area to be predicted and status data characterizing the state of the forage in the area to be predicted; matching and transmitting the environmental data and status data to a database; retrieving the environmental data and status data from the database, and inputting them into a prediction model for predicting the carbon dioxide flux level of the area to be predicted; and outputting the predicted carbon dioxide flux level based on the prediction model.

[0004] The above technical solution provides a method for quickly and efficiently collecting data related to carbon dioxide flux in real time and accurately, and predicting grassland carbon dioxide flux in real time based on the data. However, due to different usage environments, the above method is still unable to efficiently and quickly solve the problem of soil carbon dioxide flux prediction in high-altitude areas, and obtain relatively accurate prediction results. Summary of the invention

[0005] The purpose of this application is to provide a method and system for predicting soil carbon dioxide flux in alpine ecosystems through a specific target difference rate model. Difference rate model with target , to solve the technical problem that the existing technology cannot provide a method and system that can accurately and quickly predict the carbon dioxide flux in the soil in high-altitude cold areas.

[0006] According to one aspect of the present application, a method for predicting soil carbon dioxide flux in an alpine ecosystem is provided, comprising: Obtain the total amount of soil carbon dioxide emissions in the target area in the past three months , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months , based on soil CO2 emission data Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is:

[0007] in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total amount and value of emissions; Defining the CO2 emissions differential rate The target difference rate model ; Obtain soil carbon dioxide emissions in the target area for the next 30 consecutive days As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get ; Determine the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

[0008] In some embodiments, the acquisition of the total amount of soil carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on the total amount of soil carbon dioxide emissions in the past three months , and Perform data cleaning to obtain standardized total emission data .

[0009] In some embodiments, the time interval The interval is in weeks, and the Data cleaning includes: deleting Invalid data in the data, wherein the invalid data is a data value that deviates from the standard value by a large difference.

[0010] In some embodiments, the acquisition of the total amount of vegetation carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on total vegetation carbon dioxide emissions over the past three months , and Perform data cleaning to obtain standardized total emission data .

[0011] In some embodiments, the time interval The interval is in weeks, and the Data cleaning includes: deleting Invalid data in the data, wherein the invalid data is a data value that deviates from the standard value by a large difference.

[0012] In some embodiments, the first data to be predicted and the second data to be predicted are input into the target difference rate model. ,get , specifically: In , Corresponding Substitution , ,get , for:

[0013] in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total emission value.

[0014] In some embodiments, the When the preset criteria are met, the prediction results are determined, specifically: when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Stay consistent; when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months reduce; when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Increase.

[0015] According to another aspect of the present application, a soil carbon dioxide flux prediction system for an alpine ecosystem is provided, comprising a control unit, the control unit controls a functional module, and the functional module comprises: The first acquisition module: The first acquisition module is used to obtain the total amount of soil carbon dioxide emissions in the target area in the past three months , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months ; Calculation module: The calculation module is used to calculate the total amount of soil carbon dioxide emissions based on the soil carbon dioxide emissions data. Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is:

[0016] in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total amount and value of emissions; Variable definition module: The variable definition module is used to define the difference rate of carbon dioxide emissions The target difference rate model ; The second acquisition module: The second acquisition module is used to obtain the soil carbon dioxide emissions of the target area for the next 30 consecutive days. As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get ; A judgment module is used to judge the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

[0017] In some embodiments, the first acquisition module is data-connected with the second acquisition module.

[0018] In some embodiments, the first acquisition module, the calculation module, the variable definition module, the second acquisition module and the judgment module are all data-connected to the control unit.

[0019] Compared with the prior art, this application has the following advantages and beneficial effects: The method of the present application adopts a specific target difference rate model Difference rate model with target , realizing the rapid prediction of soil carbon dioxide flux by ratio The judgment achieved accurate prediction results based on rapid prediction, effectively realized the rapid and accurate prediction of soil carbon dioxide flux in alpine ecosystems, and greatly helped to protect the carbon and oxygen balance of alpine ecosystems. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 is a flow chart of the prediction method of the present application; Figure 2 It is a schematic diagram of the structure of the prediction system of this application. DETAILED DESCRIPTION

[0022] The technical solutions 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. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0023] This embodiment provides a method for predicting soil carbon dioxide flux in a high-cold ecosystem, and also relates to a system. Figure 1-2 Describe them together.

[0024] In order to better understand the content of this application, some terms are explained: Alpine ecosystem: Alpine ecosystem in this application refers to the environment in alpine regions, including soil; Past and future: The past and future time periods mentioned in this application are divided into the prediction day.

[0025] Example The existing alpine ecosystems are characterized by high altitude, perennial low temperatures, and permafrost that does not melt all year round, making it particularly important to predict the carbon dioxide content in the soil. This is not only because the carbon balance of alpine ecosystems has a very important influence on the carbon balance of terrestrial ecosystems in my country and even the world, but also because reasonably controlling the emission of carbon dioxide in the soil of alpine ecosystems will also help protect the carbon-oxygen balance of the alpine ecosystem.

[0026] To this end, this embodiment provides a method for predicting soil carbon dioxide flux in a high-cold ecosystem to achieve the prediction of soil carbon dioxide flux in high-cold areas, specifically including: Use a database or recorded data set to initially obtain the total amount of soil carbon dioxide emissions in the target area over the past three months And at the same time obtain the total amount of vegetation carbon dioxide emissions in the target area in the past three months It should be noted that the data of the past three months used in this embodiment can effectively represent the actual carbon dioxide flux of the target area in the past, ensuring the reliability of the data. At the same time, the data set acquisition method in this implementation includes manual observation data set collection, machine monitoring data set collection, etc.

[0027] In detail, obtain the total amount of soil carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on the total amount of soil carbon dioxide emissions in the past three months , and Perform data cleaning to obtain standardized total emission data , where the time interval The interval is in weeks. Data cleaning includes: deleting Invalid data in the data, invalid data is the data value that deviates from the standard value by a large difference. It can be understood that deleting invalid data here means deleting the values ​​that deviate greatly from the standard value, where the standard value is the carbon dioxide flux in the soil of the target area under ideal environmental conditions. Cleaning the acquired data is to improve data accuracy. Under the same implementation environment, data cleaning is also called data preprocessing. Based on this, the data cleaning method in this implementation is only one of them. You can also choose other data preprocessing methods according to data usage requirements.

[0028] Obtain the total amount of vegetation carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on total vegetation carbon dioxide emissions over the past three months , and Perform data cleaning to obtain standardized total emission data , time interval The interval is in weeks. Data cleaning includes: deleting Invalid data in the data, invalid data is a data value that deviates from the standard value by a large difference. It can be understood that deleting invalid data here means deleting values ​​that deviate greatly from the standard value, where the standard value is the carbon dioxide flux in the soil of the target area under ideal environmental conditions. Similarly, cleaning the acquired data is to improve data accuracy. Under the same implementation environment, data cleaning is also called data preprocessing. Based on this, the data cleaning method in this implementation is only one of them, and other data preprocessing methods can also be selected according to data usage requirements.

[0029] Next, based on the total amount of soil carbon dioxide emissions data Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is:

[0030] in is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total emission value.

[0031] Secondly, define the CO2 emissions differential rate The target difference rate model .

[0032] Based on the above, it should be noted that the target difference rate model Based on the total amount of soil carbon dioxide emissions Data on total carbon dioxide release from vegetation Therefore, the model directly predicts the carbon dioxide flux, and there are no other interfering factors in the predicted data. As a result, the prediction results are more accurate and the prediction steps are fewer.

[0033] Next, obtain the soil carbon dioxide emissions of the target area for the next 30 consecutive days As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, it should be noted that obtaining the carbon dioxide emissions in the next 30 days is the optimal prediction time interval, and different prediction days can be selected in other prediction operations.

[0034] Furthermore, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get Specifically, the first data to be predicted and the second data to be predicted are input into the target difference rate model. ,get , specifically: In , Corresponding Substitution , ,get , for:

[0035] in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total emission value.

[0036] Finally, determine the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

[0037] In detail, when When the preset criteria are met, the prediction results are determined, specifically: when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Staying consistent means the carbon and oxygen balance in the area; when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months A decrease, compared to a decrease, represents an imbalance in carbon and oxygen in the region, and it is necessary to increase the flux of carbon dioxide in the soil to maintain carbon and oxygen balance.

[0038] when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Increase, compared to increase, indicates that the carbon-oxygen imbalance in the region needs to reduce the flux of carbon dioxide in the soil or increase the total carbon dioxide emissions from vegetation , in order to maintain carbon-oxygen balance.

[0039] At least one implementation process of the method of this embodiment is: select a certain area in the northern part of Heilongjiang Province that needs to be observed and predicted, establish an observation site and build a prediction system, select the observation time, and obtain the total amount of soil carbon dioxide emissions in the area within the past three months of the observation time. And at the same time obtain the total amount of vegetation carbon dioxide emissions in the area during the past three months of observation , based on the above data, calculate the difference rate of carbon dioxide emissions , get the target difference rate model Obtain the soil carbon dioxide emissions of the area for 30 consecutive days in the future during the observation time As the first data to be predicted, as well as the total vegetation carbon dioxide emissions data for the area for 30 consecutive days in the future during the observation period As the second data to be predicted, the first and second data to be tested are input into the target difference rate model Iterate to form a new target difference rate model , and then calculate and Ratio , judged according to the ratio results. When the ratio is 1, it means that the carbon dioxide flux in the next 30 days is basically the same as in the past, which means that the carbon-oxygen balance in the area is stable; when the ratio is greater than 1, it means that compared with the total carbon dioxide emissions in the past three months, Increase, that is, the carbon dioxide flux in the area increases, the carbon-oxygen balance is unbalanced, and carbon dioxide needs to be collected and processed; when the ratio is less than 1, it means that compared with the total carbon dioxide emission data in the past three months Reduction, that is, the carbon dioxide flux in the area is reduced, the carbon-oxygen balance is unbalanced, and it is necessary to artificially promote the production of carbon dioxide in the soil to maintain the carbon-oxygen balance.

[0040] In order to better understand the method of the present application, the present application also provides a soil carbon dioxide flux prediction system for alpine ecosystems, the system comprising a control unit, the control unit controlling the functional modules. The control unit in this embodiment executes the method of this embodiment.

[0041] Among them, the functional modules include: The first acquisition module: The first acquisition module is used to obtain the total amount of soil carbon dioxide emissions in the target area in the past three months , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months ; Calculation module: The calculation module is used to calculate the total amount of soil carbon dioxide emissions based on the soil carbon dioxide emissions data. Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is:

[0042] in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total amount and value of emissions; Variable definition module: The variable definition module is used to define the difference rate of carbon dioxide emissions The target difference rate model ; The second acquisition module: The second acquisition module is used to obtain the soil carbon dioxide emissions of the target area for the next 30 consecutive days. As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get ; Judgment module, which is used to judge the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

[0043] In some implementations, the first acquisition module is data-connected to the second acquisition module.

[0044] In some implementations, the first acquisition module, the calculation module, the variable definition module, the second acquisition module, and the determination module are all data-connected to the control unit.

[0045] In the above system, the control unit acts as the main controller to control the entire system, and the functional modules rely on the control unit to perform corresponding functions. Among them, the first acquisition module obtains the total amount of soil carbon dioxide emissions in the target area in the past three months. , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months After that, the control unit controls the calculation module to calculate the above data to obtain the carbon dioxide emission difference rate , obtain the above-mentioned carbon dioxide emission difference rate After that, the control unit controls the variable definition module, which is the module for defining the variables, and can also be understood as the assignment module. The variable definition module determines the difference rate of carbon dioxide emissions. Defined as target difference rate model Then, the control unit controls the second acquisition module to acquire the soil carbon dioxide emissions of the target area for the next 30 consecutive days. As the first data to be predicted, and to obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get .get After that, the control unit controls the judgment module to judge the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

[0046] In addition, it should be noted that the modules and units integrated in the soil carbon dioxide flux prediction system of the present application, if implemented in the form of software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the method of the above-mentioned embodiment, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the various steps of the above-mentioned method embodiment.

[0047] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or basic features of the present application. In addition, it should be understood that although this specification is described in accordance with the implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A method for predicting soil carbon dioxide flux in an alpine ecosystem, characterized in that: include: Obtain the total amount of soil carbon dioxide emissions in the target area in the past three months , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months , based on soil CO2 emission data Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is: in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total amount and value of emissions; Defining the CO2 emissions differential rate The target difference rate model ; Obtain soil carbon dioxide emissions in the target area for the next 30 consecutive days As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days As the second data to be predicted, the first data to be predicted and the second data to be predicted are input into the target difference rate model ,get ; Determine the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

2. The method according to claim 1, characterized in that The above mentioned data on the total amount of soil carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on the total amount of soil carbon dioxide emissions in the past three months , and Perform data cleaning to obtain standardized total emission data .

3. The method according to claim 2, characterized in that The time interval The interval is in weeks, and the Data cleaning includes: delete Invalid data in the data, wherein the invalid data is a data value that deviates from the standard value by a large difference.

4. The method according to claim 1, characterized in that: The above mentioned data on the total amount of vegetation carbon dioxide emissions in the target area in the past three months Specifically: By setting the time interval Statistics on total vegetation carbon dioxide emissions over the past three months , and Perform data cleaning to obtain standardized total emission data .

5. The method according to claim 4, characterized in that The time interval The interval is in weeks, and the Data cleaning includes: delete Invalid data in the data, wherein the invalid data is a data value that deviates from the standard value by a large difference.

6. The method according to claim 1, characterized in that The first data to be predicted and the second data to be predicted are input into the target difference rate model ,get , specifically: In , Corresponding Substitution , ,get , for: in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total emission value.

7. The method according to claim 1, characterized in that When When the preset criteria are met, the prediction results are determined, specifically: when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Stay consistent; when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months reduce; when The soil carbon dioxide emissions for the next 30 consecutive days Compared with the total carbon dioxide emissions data in the past three months Increase.

8. A soil carbon dioxide flux prediction system for an alpine ecosystem, comprising a control unit, characterized in that: The control unit controls the functional modules, and the functional modules include: The first acquisition module: The first acquisition module is used to obtain the total amount of soil carbon dioxide emissions in the target area in the past three months , obtain the total vegetation carbon dioxide emissions data for the target area in the past three months ; Calculation module: The calculation module is used to calculate the total amount of soil carbon dioxide emissions based on the soil carbon dioxide emissions data. Data on total carbon dioxide release from vegetation Calculate the CO2 emissions differential rate , the calculation formula is: in, is the difference rate of carbon dioxide emissions; is the difference in total emissions; is the total amount and value of emissions; Variable definition module: The variable definition module is used to define the difference rate of carbon dioxide emissions The target difference rate model ; The second acquisition module: The second acquisition module is used to obtain the soil carbon dioxide emissions of the target area for the next 30 consecutive days. As the first data to be predicted, obtain the total vegetation carbon dioxide emission data for the target area for the next 30 consecutive days as the second data to be predicted; inputting the first data to be predicted and the second data to be predicted into the target difference rate model ,get ; A judgment module is used to judge the target difference rate model Difference rate model with target Ratio ,when When the preset criteria are met, the prediction results are determined.

9. The system according to claim 8, characterized in that The first acquisition module is data-connected with the second acquisition module.

10. The system according to claim 8, characterized in that The first acquisition module, the calculation module, the variable definition module, the second acquisition module and the judgment module are all data-connected to the control unit.

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