A method for estimating soil N2O emissions by coupling explicit and implicit microbial simulation methods

Abstract

Disclosed is a soil N2O emission estimation method that couples microbial explicit simulation and implicit simulation methods, comprising S1: for the study area, using the microbial implicit method to estimate the N2O emission from NH4 + Nitrification to NO2 ‑ S2: Based on the nitrification NH calculated in S1 4，n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil; S3: use microbial explicit method to estimate the denitrification process of nitrifying bacteria, which includes: estimating NO2 ‑ The process of denitrification to NO; S4: further estimating the process of denitrification of NO to N2O; and S5: calculating the amount of N2O released based on S1-S4. This method effectively circumvents the problems of implicit simulation's lack of consideration of microbial processes and the difficulty in estimating initial values ​​in explicit simulation, effectively improving the simulation accuracy of soil N2O emissions.

Description

Technical Field

[0001] The present invention relates to the field of agricultural information technology, and more particularly to a soil N2O emission estimation method that couples a microbial explicit simulation method and a microbial implicit simulation method. Background Art

[0002] N2O is a gas with a strong greenhouse effect potential. As a major source of N2O emissions, agricultural N2O emission reduction has become a key issue in mitigating global warming. Accurately estimating agricultural N2O emissions is crucial for optimizing agricultural planting practices and adapting to and mitigating climate change. Currently, soil biogeochemical models are crucial tools for simulating N2O emissions from farmland. Two main approaches exist: implicit microbial simulation, which ignores the presence of soil microorganisms and estimates N2O emissions using only environmental factors such as temperature and moisture. Explicit microbial simulation, which incorporates microbial life processes and uses microbial activity as a key factor in N2O emission estimation.

[0003] The microbial implicit simulation method has a simple structure and a wide range of applications, but its shortcomings are also obvious. Since this method directly links the N2O release rate to the soil environment and does not consider the growth or death rates of microorganisms in different environments, it lacks the ability to simulate situations where N2O emissions caused by microbial activity lag behind environmental changes, or N2O slow release.

[0004] Explicit microbial simulation methods are relatively complex but can effectively address the challenges previously encountered with implicit microbial simulation. However, they also have some drawbacks. They rely on soil microbial content, which is difficult to monitor. Therefore, they often require assumptions about initial microbial values. Because such methods involve a feedback loop between microbial content and soil nitrogen cycle rates—microbial content influences nitrogen cycle rates, which in turn influence microbial content—incorrect assumptions about initial microbial content can exponentially amplify deviations in N2O simulation results.

[0005] These issues are the primary limiting factors for accurate model simulation of N2O emissions, particularly at daily and finer scales. Therefore, new technologies are needed to enhance N2O simulation capabilities and address at least some of the aforementioned shortcomings and drawbacks of existing methods. Summary of the Invention

[0006] To address the shortcomings of the existing technology, the present invention proposes a soil N2O emission estimation method that couples explicit microbial simulation and implicit simulation methods. By coupling the implicit and explicit microbial simulation methods, the advantages of both methods are combined to compensate for the shortcomings of the other. This method can effectively circumvent the problems of implicit simulation's lack of consideration of microbial processes and the difficulty in estimating initial values ​​in explicit simulation, and can effectively improve the simulation accuracy of soil N2O emissions.

[0007] More specifically, according to one aspect of the present invention, a method for estimating soil N2O emissions by coupling microbial explicit simulation and implicit simulation methods is provided, comprising the following steps: S1: for a study area, using a microbial implicit method to estimate the N2O emissions from NH4 + Nitrification to NO2 - The process is shown in the following formula (1):

[0008]

[0009] NH 4，n It is nitrated NH4 + , f t , f m and f pH are the limiting factors of soil temperature, soil moisture and soil pH on the nitrification process; t is the soil temperature in the study area; n1 represents NH4 + The semi-saturated concentration during nitrification; n2 is the nitrification rate adjustment parameter; n3 is the adjustment parameter for the shape of the temperature response curve; NH 4，d It is dissolved NH4 + , anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances participating in nitrification reaction;

[0010] S2: Nitrified NH calculated based on S1 4，n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil, as shown in the following formula (2):

[0011] ΔBIO N =Y*NH 4,n -K d *BIO N (2)

[0012] Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria;

[0013] S3: Use microbial explicit methods to estimate the denitrification process of nitrifying bacteria, which includes: estimating NO2 -The process of denitrification to NO is shown in the following formula (3):

[0014]

[0015] Where: Indicates that NO2 - The reaction amount to NO, Indicates that NO2 - The maximum reaction rate to NO, Indicates NH4 + The concentration of Indicates NO2 - The concentration of Indicates NH4 + The half-saturation concentration when participating in the reaction, Indicates NO2 - The half-saturation concentration when participating in the reaction;

[0016] S4: Further estimate the process of NO denitrification to N2O, as shown in the following formula (4):

[0017] Where: represents the reaction rate from NO to N2O, represents the maximum reaction rate from NO to N2O, C NO，n represents the concentration of NO, K NO represents the half-saturation concentration of NO when it participates in the reaction; and

[0018] S5: Based on S1-S4, calculate the release amount of N2O.

[0019] According to an embodiment of the present invention, in S1, f t , f m and f pH Calculated by the following formulas:

[0020]

[0021]

[0022] f pH =-0.0604*pH 2 +0.7347*pH-1.22314 (7)

[0023] Where WFPS is the water-filled porosity of the soil.

[0024] According to the embodiment of the present invention, in S2, an initial BIO is initially set. N Then, we use formula (2) to calculate the biomass change of nitrifying bacteria after a period of time, that is, ΔBIO N, then the initial BIO N Value plus ΔBIO N , and obtain the nitrifying bacteria biomass after the period of time, and repeat the calculation in this way to obtain the nitrifying bacteria biomass in subsequent stages.

[0025] According to an embodiment of the present invention, in S1, the value of n1 is 10-200; the value of n2 is 0.1-30; and the value of n3 is 0.1-10.

[0026] According to the embodiment of the present invention, in S2, Y is 0.14 g / Mol, K d The value is 3.16×10 -7 / S.

[0027] According to an embodiment of the present invention, in S3, The value is 1.71×10 -4 Mol / l, The value is 1.00×10 - 5 Mol / l.

[0028] According to an embodiment of the present invention, in S4, K NO The value is 8.33×10 -4 Mol / l.

[0029] According to another aspect of the present invention, a soil N2O emission estimation device that couples microbial explicit simulation and implicit simulation methods is provided, characterized in that it includes:

[0030] By NH4 + Nitrification to NO2 - The process estimation module is used to estimate the NH4 + Nitrification to NO2 - The process is shown in the following formula (1):

[0031]

[0032] NH 4，n It is nitrated NH4 + , f t , f m and f pH are the limiting factors of soil temperature, soil moisture and soil pH on the nitrification process; t is the soil temperature in the study area; n1 represents NH4 + The semi-saturated concentration during nitrification; n2 is the nitrification rate adjustment parameter; n3 is the adjustment parameter for the shape of the temperature response curve; NH 4，d It is dissolved NH4 +, anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances participating in nitrification reaction;

[0033] The biomass estimation module of nitrifying bacteria involved in the nitrification process in soil is used to estimate the nitrified NH based on the nitrification NH calculated in S1. 4,n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil, as shown in the following formula (2):

[0034] ΔBIO N =Y*NH 4,n -K d *BIO N (2)

[0035] Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria;

[0036] The nitrifying bacteria denitrification process estimation module is used to estimate the nitrifying bacteria denitrification process using the microbial explicit method, which includes: estimating NO2 - The process of denitrification to NO is shown in the following formula (3):

[0037]

[0038] Where: Indicates that NO2 - The reaction amount to NO, Indicates that NO2 - The maximum reaction rate to NO, Indicates NH4 + The concentration of Indicates NO2 - The concentration of Indicates NH4 + The half-saturation concentration when participating in the reaction, Indicates NO2 - The half-saturation concentration when participating in the reaction;

[0039] NO denitrification to N2O process estimation module: used to further estimate the process of NO denitrification to N2O, as shown in the following formula (4):

[0040]

[0041] Where: represents the reaction rate from N0 to N2O, represents the maximum reaction rate from NO to N2O, C NO，nrepresents the concentration of NO, K NO represents the half-saturation concentration of NO when it participates in the reaction; and

[0042] N2O release calculation module: used to calculate the N2O release based on S1-S4.

[0043] According to another aspect of the present invention, there is also provided an electronic device, comprising: a memory and one or more processors;

[0044] The memory is used to store one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in the present invention.

[0045] The proposed method disassembles and reconstructs traditional simulation methods, using a microbial implicit method to calculate nitrification rates and a microbial explicit method to calculate the denitrification process by nitrifying bacteria. The nitrification rate calculated by the microbial implicit method is used to estimate the nitrifying bacterial biomass, limiting the biomass to a reasonable range. The microbial explicit method is used only to simulate N2O emissions and no longer affects the nitrifying bacterial biomass, thus avoiding the feedback loop between microbial content and soil nitrogen cycle rate that can amplify deviations from the initial microbial value. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The same reference numerals in the accompanying drawings indicate the same or similar components or parts. The objects and features of the present invention will become more apparent from the following description taken in conjunction with the accompanying drawings, in which:

[0047] Figure 1 1 is a flow chart of a method for estimating soil N2O emissions by coupling microbial explicit simulation and implicit simulation methods according to an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of the structure of a soil N2O emission estimation device using coupled microbial explicit simulation and implicit simulation methods according to an embodiment of the present invention;

[0049] Figure 3 is a schematic structural diagram of an electronic device according to one embodiment of the present invention;

[0050] Figure 4 This is the N2O emission result obtained when only the microbial implicit method is used for simulation;

[0051] Figure 5 Figure 2 is the N2O emission result obtained when only the microbial explicit method is used for simulation; and

[0052] Figure 6 Graph showing N2O emission results obtained by coupling microbial explicit simulation and implicit simulation methods according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] To clearly illustrate the solutions of the present invention, preferred embodiments are given below and described in detail with reference to the accompanying drawings. The following description is merely illustrative in nature and is not intended to limit the application or use of the present invention.

[0054] It should be understood that the microbial explicit simulation, microbial implicit simulation methods, etc. cited in the present invention are known per se, so the present invention focuses on explaining how to combine these methods together to thereby realize the process of coupling the microbial explicit simulation and implicit simulation methods of the present invention.

[0055] Figure 1 FIG. 1 is a flow chart of a method for estimating soil N2O emissions by coupling microbial explicit simulation and implicit simulation methods according to one embodiment of the present invention. Figure 1 As shown in the figure, the soil N2O emission estimation method of the coupled microbial explicit simulation and implicit simulation method of the implementation scheme is mainly used to simulate the N2O emission caused by the denitrification of nitrifying bacteria during the soil nitrogen nitrification process. According to the soil nitrogen cycle process, the nitrification process is composed of NH4 + Nitrification to NO2 - And further nitrified to NO3 - In this process, nitrifying bacteria will use part of NO2 - The denitrification process of nitrifying bacteria converts NO2 - Denitrification to NO and further denitrification to N2O as follows:

[0056] S1. First, for the study area, the microbial implicit method was used to estimate the NH4 + Nitrification to NO2 - The process is as follows, as shown in equation (1):

[0057]

[0058] NH 4，n It is nitrated NH4 + ;f t , f m and f pH are the limiting factors of soil temperature, soil moisture, and soil pH on the nitrification process, which are calculated by the following formulas:

[0059]

[0060]

[0061] f pH =-0.0604*pH 2 +0.7347*pH-1.22314 (7)

[0062] Where WFPS is the soil water-filled porosity; t is the soil temperature in the study area (℃); n1 is a parameter used to characterize the NH4 + The half-saturation concentration during nitrification can range from 10 to 200. The larger the n1 value, the more difficult the nitrification reaction is. n2 is the nitrification rate adjustment parameter, which can range from 0.1 to 30 and is used to characterize the overall change in the nitrification reaction rate caused by other unknown factors. n3 is a parameter used to adjust the shape of the temperature response curve, which can range from 0.1 to 10. The larger the n3 value, the steeper the temperature curve and the more sensitive the nitrification reaction is to temperature. 4，d It is dissolved NH4 + This parameter can be estimated through observation or based on other information (such as fertilizer application amount); anvf represents the proportion of anaerobic environment in the soil, and 1-anvf represents the proportion of substances participating in nitrification reaction. anvf can be obtained by experiment or experience.

[0063] S2, based on the nitrification rate NH calculated in S1 4，n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil:

[0064] ΔBIO N =Y*NH 4，n -K d *BIO N (2)

[0065] Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on the nitrification rate, which can be determined based on empirical values, for example, it can be taken as 0.14 g / Mol, K d is the death rate of nitrifying bacteria, which can also be determined based on empirical values, for example, 3.16×10 -7 / s;BIO N is the biomass of nitrifying bacteria.

[0066] In this step, you can initially set an initial BIO N Value, BIO N A very small value such as 1 kg / ha can be taken. This value has little effect on the subsequent simulation. The biomass of nitrifying bacteria is mainly limited by the nitrification rate in equation (2). Then, the biomass change of nitrifying bacteria after a period of time is calculated using equation (2), that is, ΔBIO N , then the initial BIO N Value plus ΔBIO N , and obtain the nitrifying bacteria biomass after the period of time, and repeat the calculation in this way to obtain the nitrifying bacteria biomass in subsequent stages.

[0067] S3. After that, the microbial explicit method can be used to estimate the denitrification process of nitrifying bacteria. First, estimate NO2 - The process of denitrification to NO is as shown in equation (3):

[0068]

[0069] Where: Indicates that NO2 - The reaction amount to NO, Indicates that NO2 - The maximum reaction rate to NO can be determined by theoretical calculation, such as 8.60×10 -6 Mol / g / s; Indicates NH4 + The concentration of Indicates NO2 - The concentration of Indicates NH4 + The half-saturation concentration when participating in the reaction can be determined by theory or experiment, for example, it can be taken as 1.71×10 -4 Mol / l, Indicates NO2 - The half-saturation concentration when participating in the reaction can be determined by theory or experiment, for example, it can be taken as 1.00×10 -5 Mol / l.

[0070] S4. Further estimate the process of NO denitrification to N2O, as shown in equation (4):

[0071]

[0072] Where: represents the reaction rate from NO to N2O, It represents the maximum reaction rate from NO to N2O, which can be determined by theoretical calculation, such as 5.13×10 -6 Mol / g / s C NO，n Indicates the concentration of N0, K NO It represents the half-saturation concentration of NO when it participates in the reaction. It can be determined theoretically or experimentally, such as 8.33×10 -4 Mol / 1, BIO N is the microbial biomass (in this method, it is the nitrifying bacteria biomass).

[0073] S5. Based on S1-S4, the N2O release in a certain period can be simulated. After the simulation, the nitrogen compound content and nitrifying bacteria biomass in the soil are updated, and S1-S4 are continued to be iteratively run to simulate the N2O release in the next period.

[0074] The method of the present invention can simulate the N2O release at different time scales, such as time scales of days, hours, etc., which depends on the time scales of the input parameters, such as n2, Y, K d , Etc., which are well known in the art and will not be described in detail here.

[0075] It should be understood that the method of simulating N2O release described in this method can be coupled to other known models such as soil process models, crop models, biogeochemical cycle models, etc. as a simulation method for nitrification and nitrification and denitrification processes.

[0076] Figure 2 Schematic diagram of the structure of a soil N2O emission estimation device according to an embodiment of the present invention, which couples the microbial explicit simulation and implicit simulation methods. Figure 2 As shown, the device includes: NH4 + Nitrification to NO2 - The process estimation module 210 is used to estimate the NH4 + Nitrification to NO2 - The process of nitrifying bacteria biomass estimation module 220 in the soil involved in the nitrification process is used to estimate the nitrification NH based on the nitrification NH calculated in S1. 4，n , estimating the biomass of nitrifying bacteria involved in the nitrification process in the soil; nitrifying bacteria denitrification process estimation module 230, for estimating the nitrifying bacteria denitrification process using a microbial explicit method, which includes estimating NO2 - denitrification process to NO; NO denitrification process to N2O estimation module 240: for further estimating the process of denitrification of NO to N2O; and N2O release amount calculation module 250, based on the above modules, calculates the release amount of N2O.

[0077] Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 3 As shown, the electronic device includes a processor 310, a memory 320, an input device 330 and an output device 340; the number of processors 310 in the electronic device can be one or more. Figure 3 In the figure, a processor 310 is used as an example; the processor 310, memory 320, input device 330 and output device 340 in the electronic device can be connected via a bus or other means. Figure 3 The bus connection is taken as an example.

[0078] The memory 320 is a computer-readable storage medium that can be used to store software programs, computer executable programs, and modules, such as the program instructions / modules corresponding to the coupled microbial explicit simulation and implicit simulation methods in the embodiment of the present invention, for example, NH4 + Nitrification to NO2 - Processor 310 includes a module 210 for estimating the biomass of nitrifying bacteria in the soil involved in nitrification 210; a module 220 for estimating the biomass of nitrifying bacteria involved in nitrification 220; a module 230 for estimating the denitrification process of nitrifying bacteria; a module 240 for estimating the denitrification of NO to N2O; and a module 250 for calculating the amount of N2O released. Processor 310 executes software programs, instructions, and modules stored in memory 320 to perform various electronic device functions and data processing, thereby implementing the aforementioned coupled microbial explicit and implicit simulation methods.

[0079] Example

[0080] The following uses the N2O emission simulation of a wheat-corn rotation experimental field in Dongcun Farm, Yongji City, Shandong Province as an example to illustrate the specific application of the method of the present invention.

[0081] The longitude and latitude of the study area are 110.71E, 34.93N, and the time is the corn growing season in 2018. This method is used in conjunction with the MCWLA model, which provides simulated data of necessary variables for this method, such as soil temperature, soil moisture, soil NH4 + Content, etc. The simulation frequency is daily. Based on the N2O emission simulation method proposed in this invention, the simulation steps are as follows:

[0082] Start the simulation from the sowing of crops. On the first day, set the initial BIO N When the model simulates the soil nitrogen cycle, the microbial implicit method is first used to estimate the nitrogen content of NH4 + Nitrification to NO2 - For details, please refer to the above equation (1).

[0083] Based on the nitrification rate NH calculated in S1 4，n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil, see the above equation (2) for details.

[0084] NH was calculated 4，n Afterwards, the microbial explicit method was used to estimate the denitrification process of nitrifying bacteria, first estimating NO2 - The process of denitrification to NO is as shown in the above equation (3);

[0085] The process of NO denitrification to N2O was further estimated as shown in the above equation (4).

[0086] Based on S1-S4, the N2O release for the day can be simulated. After the simulation, the nitrogen compound content in the soil and the nitrifying bacteria biomass are updated. Then, the iterative run of S1-S4 is continued to simulate the N2O emissions for the next day. The model runs continuously and outputs the simulated N2O emissions value for each day.

[0087] The simulated data were compared with the observed daily N2O emissions to evaluate the simulation accuracy of the model. The simulation results are shown in Figure 6 .

[0088] To demonstrate the level of improvement of the present invention, the accuracy of the following simulation methods was tested simultaneously:

[0089] Only the microbial implicit method is used for simulation. According to the general simulation idea of ​​the implicit method, the N2O emission in this method is the nitrification rate (i.e., the NH 4，n ) (In this example, three percentage parameters of 0.002, 0.006, and 0.01 are selected for simulation and the results are presented).

[0090] Only the microbial explicit method is used to simulate the soil nitrogen cycle rate, in which there is a feedback loop between the microbial content and the soil nitrogen cycle rate, that is, the microbial content affects the nitrogen cycle rate, and the nitrogen cycle rate in turn affects the microbial content, which is caused by NH4 + Nitrification to NO2 - The process is also controlled by nitrifying bacteria, that is, Equation 1 is replaced by the following equation:

[0091] in Indicates that from NH4 + to NO2 - The maximum reaction rate is 3.43×10 -6 Mol / g / s. The meanings of other parameters refer to the above description.

[0092] The initial nitrifying bacteria content was set at 0.1kg / ha, 0.5kg / ha, and 1.0kg / ha, and the results were simulated and displayed respectively.

[0093] Figure 4-Figure 6 The results of simulating the N2O release process after a single fertilization using different methods are presented.

[0094] As shown in the figure, when only the microbial implicit method is used for simulation ( Figure 4 ), the simulated N2O emission peak is earlier than the observation, because the nitrification rate increases rapidly and then decreases after fertilization. As a result, when a fixed percentage is used to estimate N2O emissions, the N2O emission rate reaches a peak shortly after fertilization, which is inconsistent with the actual observation.

[0095] Figure 5The simulation results using only the microbial explicit method are presented, with the simulated peak value significantly delayed compared to observations. This is due to the presence of a feedback loop between the microbial content and the nitrogen cycle rate. Initially, the microbial content is low, and the simulated nitrogen cycle reaction rate is low. After a long feedback loop, the microbial content and N2O emission rate reach their peak values. At the same time, if the initial value is set too small, the simulated N2O emissions will also be too small for a long time due to the feedback loop between the microbial content and the nitrogen cycle rate. If the initial value continues to increase, the tail of the simulation curve will rise rapidly, causing the simulation results to deviate further from actual observations.

[0096] Figure 6 The simulation results of the method proposed in this paper are shown. It can be seen that the simulation results are significantly better than other methods, especially in terms of peak value, decay rate, etc. Based on the observed daily N2O emissions, the r of the simulation results under different parameter scenarios when only using the microbial implicit or explicit method is used. 2 are all less than 0.1, and using the method proposed in this invention, the r 2 This indicates that the proposed method can effectively improve the simulation accuracy of soil N2O emissions.

[0097] This method disassembles and reconstructs traditional simulation methods, using a microbial implicit method to calculate nitrification rates and an explicit method to calculate denitrification by nitrifying bacteria. The nitrification rates calculated by the implicit method are used to estimate nitrifying bacterial biomass, limiting it to a reasonable range. However, the implicit method does not directly calculate N₂O emissions. The explicit method simulates N₂O emissions only and does not affect nitrifying bacterial biomass, thus avoiding the feedback loop between microbial content and soil nitrogen cycle rates that can amplify bias in initial microbial values.

[0098] In other words, this invention improves the simulation method for soil N2O emissions by coupling implicit and explicit microbial simulation methods, combining their strengths to offset their weaknesses. This effectively overcomes the problems of implicit simulation's lack of consideration of microbial processes and the difficulty in estimating initial values ​​in explicit simulation. This invention can effectively improve the simulation accuracy of soil N2O emissions.

[0099] Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the specific implementation methods of this specification should not be understood as limiting the present invention.

Claims

1. A soil N2O emission estimation method that couples explicit and implicit microbial simulation methods, comprising the following steps: S1: For the study area, use the microbial implicit method to estimate the NH4 + Nitrification to NO2 - The process is shown in the following formula (1): NH 4，n It is nitrated NH4 + , f t , f m and f pH are the limiting factors of soil temperature, soil moisture and soil pH on the nitrification process; t is the soil temperature in the study area; n1 represents NH4 + The half-saturated concentration during nitrification; n2 is the nitrification rate adjustment parameter; n3 is the adjustment parameter of the temperature response curve shape; NH 4，d It is dissolved NH4 + , anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances participating in nitrification reaction; S2: Nitrified NH calculated based on S1 4,n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil, as shown in the following formula (2): ΔBIO N =Y*NH 4,n -K d *ORGANIC N (2) Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria; S3: Use microbial explicit methods to estimate the denitrification process of nitrifying bacteria, which includes: estimating NO2 - The process of denitrification to NO is shown in the following formula (3): Where: Indicates that NO2 - The reaction amount to NO, Indicates that NO2 - The maximum reaction rate to NO, Indicates NH4 + The concentration of Indicates NO2 - The concentration of Indicates NH4 + The half-saturation concentration when participating in the reaction, Indicates NO2 - The half-saturation concentration when participating in the reaction; S4: Further estimate the process of NO denitrification to N2O, as shown in the following formula (4): Where: represents the reaction rate from NO to N2O, represents the maximum reaction rate from NO to N2O, C NO，n represents the concentration of NO, K NO represents the half-saturation concentration of NO when it participates in the reaction; and S5: Based on S1-S4, calculate the release amount of N2O.

2. The method according to claim 1, characterized in that In S1, f t , f m and f pH Calculated by the following formulas: f pH =-0.0604*pH 2 +0.7347*pH-1.22314 (7) Where WFPS is the water-filled porosity of the soil.

3. The method according to claim 1, characterized in that In S2, an initial BIO is initially set N Then, we use formula (2) to calculate the biomass change of nitrifying bacteria after a period of time, that is, ΔBIO N , then the initial BIO N Value plus ΔBIO N , and obtain the nitrifying bacteria biomass after the period of time, and repeat the calculation in this way to obtain the nitrifying bacteria biomass in subsequent stages.

4. The method according to claim 1, wherein In S1, the value of n1 is 10 to 200; the value of n2 is 0.1 to 30; and the value of n3 is 0.1 to 10.

5. The method according to claim 1, characterized in that In S2, Y is 0.14 g / Mol, K d The value is 3.16×10 -7 / s.

6. The method according to claim 1, wherein In S3, The value is 1.71×10 -4 Mol / l, The value is 1.00×10 -5 Mol / l.

7. The method according to claim 1, characterized in that S4, K NO The value is 8.33×10 -4 Mol / l.

8. A soil N2O emission estimation device that couples microbial explicit simulation and implicit simulation methods, characterized in that: include: By NH4 + Nitrification to NO2 - The process estimation module is used to estimate the NH4 + Nitrification to NO2 - The process is shown in the following formula (1): NH 4，n It is nitrated NH4 + , f t , f m and f pH are the limiting factors of soil temperature, soil moisture and soil pH on the nitrification process; t is the soil temperature in the study area; n1 represents NH4 + The half-saturated concentration during nitrification; n2 is the nitrification rate adjustment parameter; n3 is the adjustment parameter of the temperature response curve shape; NH 4，d It is dissolved NH4 + , anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances participating in nitrification reaction; The biomass estimation module of nitrifying bacteria involved in the nitrification process in soil is used to estimate the nitrified NH based on the nitrification NH calculated in S1. 4,n , estimate the biomass of nitrifying bacteria involved in the nitrification process in the soil, as shown in the following formula (2): ΔBIO N =Y*NH 4,n -K d *ORGANIC N (2) Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria; The nitrifying bacteria denitrification process estimation module is used to estimate the nitrifying bacteria denitrification process using the microbial explicit method, which includes: estimating NO2 - The process of denitrification to NO is shown in the following formula (3): Where: Indicates that NO2 - The reaction amount to NO, Indicates that NO2 - The maximum reaction rate to NO, Indicates NH4 + The concentration of Indicates NO2 - The concentration of Indicates NH4 + The half-saturation concentration when participating in the reaction, Indicates NO2 - The half-saturation concentration when participating in the reaction; NO denitrification to N2O process estimation module: used to further estimate the process of NO denitrification to N2O, as shown in the following formula (4): Where: represents the reaction rate from NO to N2O, represents the maximum reaction rate from NO to N2O, C NO，n represents the concentration of NO, K NO represents the half-saturation concentration of NO when it participates in the reaction; and N2O release calculation module: used to calculate the N2O release based on S1-S4.

9. An electronic device, characterized in that: include: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

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