Soil N2O emission estimation method coupling microorganism explicit simulation and implicit simulation methods

Abstract

The invention discloses a soil N2O emission estimation method coupled with a microorganism explicit simulation method and an implicit simulation method, and the soil N2O emission estimation method coupled with the microorganism explicit simulation method and the implicit simulation method comprises the following steps: S1, aiming at a research area, estimating a process of nitrifying NH4 < + > into NO2 <-> by using a microorganism implicit method; s2, estimating the biomass of the nitrifying bacteria participating in the nitrification process in the soil based on the nitrification NH4, n calculated in the S1; s3, estimating the denitrification process of the nitrifying bacteria by using a microbial explicit method, wherein the process comprises the following steps: estimating the process of denitrifying NO2 <-> into NO; s4, further estimating the process of denitrifying NO into N2O; and S5, calculating the release amount of N2O based on the steps S1 to S4. According to the method, the problems that implicit simulation lacks consideration on a microbial process and an initial value of explicit simulation is difficult to estimate can be effectively avoided, and the simulation precision of soil N2O emission can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of agricultural information technology, and more specifically to a soil N coupling microbial explicit simulation method and a microbial implicit simulation method. 2 O emission estimation method. Background Art

[0002] N 2 O is a gas with strong greenhouse effect potential. Agriculture is a 2 Agricultural N is an important source of O emissions. 2 O emission reduction has become one of the key issues to mitigate global warming. 2 Accurate estimation of O emissions is of great significance for optimizing agricultural planting methods and adapting to and mitigating climate change. 2 There are two main simulation approaches for NO emissions. One is implicit microbial simulation, which means that the model does not consider the existence of soil microorganisms and only uses environmental factors such as temperature and moisture to simulate NO emissions. 2 The other is to estimate NO emissions; the other is to explicitly simulate microorganisms, that is, to consider the life process of microorganisms in the model and use microbial activity as an important factor to control NO emissions. 2 Estimation of O emissions.

[0003] The implicit microbial simulation method has a simple structure and a wide range of applications, but its disadvantages are also obvious. 2 The release rate of N O is directly related to the soil environment and does not take into account the growth or death rate of microorganisms in different environments. 2 O emissions lag behind environmental changes, or N 2 O lacks simulation capabilities for sustained release and other situations.

[0004] The microbial explicit simulation method is relatively complex, but it can solve the problems faced in the aforementioned microbial implicit simulation. However, the microbial explicit simulation method also has some shortcomings. The microbial explicit simulation method relies on the soil microbial content, but the microbial content is difficult to monitor. Therefore, the microbial explicit simulation method often requires assumptions about the initial value of the microorganism. Because in this type of method, 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. Therefore, once the assumption of the initial microbial content is biased, it will lead to N 2 The deviation of O simulation results is magnified geometrically.

[0005] The above problems are the factors that affect the model's 2The main limitation of accurate simulation of NO emissions is the limited simulation capability of models at daily or finer scales. Therefore, new technologies are needed to improve NO 2 O simulation capabilities and avoid, improve at least part of the deficiencies and shortcomings of the above-mentioned existing methods. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention proposes a soil N coupling microbial explicit simulation and implicit simulation method. 2 The method for estimating soil NO emissions couples the implicit microbial simulation and explicit microbial simulation methods, combining the advantages of both to make up for the shortcomings of the other. It can effectively avoid the lack of consideration of microbial processes in implicit simulation and the difficulty in estimating the initial value of explicit simulation, and can effectively improve soil NO emissions. 2 Simulation accuracy of O emissions.

[0007] More specifically, according to one aspect of the present invention, a soil N2O emission estimation method 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 emission from NH 4 + Nitration to NO 2 - The process is shown in the following formula (1): NH 4，n It is nitrated NH 4 + , f t , f m and f pH are the limiting factors of soil temperature, soil moisture and soil pH on nitrification; t is the soil temperature in the study area; n1 represents NH 4 + The half-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 is dissolved NH 4 + , anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances involved in nitrification; S2: Nitrated NH based on the calculation 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 *BIO N (2) Among them, ΔBIO Nis the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on the 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 NO 2 - The process of denitrification to NO is shown in the following equation (3): Where: Indicates from NO 2 - The amount of reaction to NO, Indicates from NO 2 - The maximum reaction rate to NO, Indicates NH 4 + The concentration of Indicates NO 2 - The concentration of Indicates NH 4 + The half-saturation concentration when participating in the reaction, Indicates NO 2 - The half-saturation concentration when participating in the reaction; S4: Further estimation of NO denitrification to N 2 The process of O is shown in the following formula (4): Where: Indicates from NO to N 2 The reaction rate of O, Indicates from NO to N 2 The maximum reaction rate of O, 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 N 2 The amount of O released. According to an embodiment of the present invention, 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. According to the embodiment of the present invention, in S2, an initial BIO is initially set. N Then, the biomass change of nitrifying bacteria after a period of time is calculated using formula (2), that is, ΔBIO N , then the initial BIO N Value plus ΔBIO N , the biomass of nitrifying bacteria after the period of time is obtained, and the calculation is repeated in this way to obtain the biomass of nitrifying bacteria in subsequent stages. 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. 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. 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. According to an embodiment of the present invention, in S4, K NO The value is 8.33×10 -4 Mol / l. According to another aspect of the present invention, a soil N coupling microbial explicit simulation and implicit simulation method is provided. 2 The device for estimating O emissions is characterized by comprising: By NH 4 + Nitration to NO 2 - The process estimation module is used to estimate the NH 4 + Nitration to NO 2 - The process is shown in the following formula (1): NH 4，n It is nitrated NH 4 + , f t , f m and f pHare the limiting factors of soil temperature, soil moisture and soil pH on nitrification; t is the soil temperature in the study area; n1 represents NH 4 + The half-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 is dissolved NH 4 + , anvf represents the proportion of anaerobic environment in the soil of the study area, and 1-anvf represents the proportion of substances involved in nitrification; The module for estimating the biomass 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 *BIO N (2) Among them, ΔBIO N is the biomass change of nitrifying bacteria, Y is the microbial biomass growth rate parameter based on the nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria; The module for estimating the denitrification process of nitrifying bacteria is used to estimate the denitrification process of nitrifying bacteria using the microbial explicit method, which includes: estimating NO 2 - The process of denitrification to NO is shown in the following equation (3): Where: Indicates from NO 2 - The amount of reaction to NO, Indicates from NO 2 - The maximum reaction rate to NO, Indicates NH 4 + The concentration of Indicates NO 2 - The concentration of Indicates NH 4 + The half-saturation concentration when participating in the reaction, Indicates NO 2 - The half-saturation concentration when participating in the reaction; Denitrification of NO to N 2O process estimation module: used to further estimate the denitrification of NO to N 2 The process of O is shown in the following formula (4): Where: Indicates from N0 to N 2 The reaction rate of O, Indicates from NO to N 2 The maximum reaction rate of O, C NO，n represents the concentration of NO, K NO represents the half-saturation concentration of NO when it participates in the reaction; and N 2 O release calculation module: used to calculate N based on S1-S4 2 The amount of O released. According to another aspect of the present invention, there is also provided an electronic device, comprising: a 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 described in the present invention.

[0008] The method of the present invention disassembles and reconstructs the traditional simulation method. The nitrification rate is calculated using the microbial implicit method, while the denitrification process of nitrifying bacteria is calculated using the microbial explicit method. The nitrification rate calculated by the microbial implicit method is used to estimate the biomass of nitrifying bacteria, limiting the biomass to a reasonable range. The microbial explicit method is only used to simulate N 2 O emissions no longer affect the biomass of nitrifying bacteria, thus avoiding the amplification of the deviation of the initial microbial value by the feedback loop between the microbial content and the soil nitrogen cycle rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] 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 in conjunction with the accompanying drawings, in which:

[0010] Figure 1 is a soil N according to the coupled microbial explicit simulation and implicit simulation method according to an embodiment of the present invention. 2 Schematic diagram of the O emission estimation method;

[0011] Figure 2 is a soil N according to the coupled microbial explicit simulation and implicit simulation method according to an embodiment of the present invention. 2 Schematic diagram of the structure of the O emission estimation device;

[0012] Figure 3 A schematic diagram of the structure of an electronic device according to an embodiment of the present invention;

[0013] Figure 4 is the N obtained when only the microbial implicit method is used for simulation 2 O emission result graph;

[0014] Figure 5 is the N obtained when only the microbial explicit method is used for simulation 2 O emission results graph; and

[0015] Figure 6 is the N obtained by the coupled microbial explicit simulation and implicit simulation method according to the embodiment of the present invention. 2 O emission results graph. DETAILED DESCRIPTION

[0016] In order to clearly illustrate the solutions in the present invention, preferred embodiments are given below and described in detail with reference to the accompanying drawings. The following description is merely exemplary in nature and is not intended to limit the application or use of the present disclosure.

[0017] It should be understood that the microbial explicit simulation, microbial implicit simulation methods, etc. cited in the present invention are known per se, and therefore 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.

[0018] Figure 1 is a soil N coupled microbial explicit simulation and implicit simulation method according to one embodiment of the present invention. 2 Schematic diagram of the process of estimating O emissions. Figure 1 As shown, the embodiment of the coupled microbial explicit simulation and implicit simulation method for soil N 2 The O emission estimation method mainly focuses on the N2O2 emission caused by denitrification of nitrifying bacteria during soil nitrogen nitrification. 2 O emissions were simulated. According to the soil nitrogen cycle, nitrification is the process of NH 4 + Nitration to NO 2 - and further nitrified to NO 3 - In this process, nitrifying bacteria use part of NO 2 - The denitrification process of nitrifying bacteria converts NO 2 - Denitrification to NO and further denitrification to N 2 O, as follows:

[0019] S1. First, for the study area, the microbial implicit method was used to estimate the 4 + Nitration to NO 2- The process is as follows, as shown in equation (1): NH 4，n It is nitrated NH 4 + ;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: f pH =-0.0604*pH 2 +0.7347*pH-1.22314 (7) 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 NH 4 + The half-saturated concentration during nitrification can range from 10 to 200. The larger the n1 value, the more difficult it is for the nitrification reaction to occur. 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 is dissolved NH 4 + , 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 involved in nitrification reaction. anvf can be obtained by experiment or experience.

[0020] 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: ΔBIO N =Y*NH 4，n -K d *BIO N (2)

[0021] 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.

[0022] 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, equation (2) is used 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 , the biomass of nitrifying bacteria after the period of time is obtained, and the calculation is repeated in this way to obtain the biomass of nitrifying bacteria in subsequent stages.

[0023] S3. After that, the microbial explicit method can be used to estimate the denitrification process of nitrifying bacteria. First, estimate NO 2 - The process of denitrification to NO is as shown in equation (3): Where: Indicates from NO 2 - The amount of reaction to NO, Indicates from NO 2 - The maximum reaction rate to NO can be determined by theoretical calculation, for example, it can be taken as 8.60×10 -6 Mol / g / s; Indicates NH 4 + The concentration of Indicates NO 2 - The concentration of Indicates NH 4 + 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 NO 2 - 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.

[0024] S4. Further estimation of NO denitrification to N 2 O process, as shown in equation (4):

[0025] Where: Indicates from NO to N 2 The reaction rate of O, Indicates from NO to N 2 The maximum reaction rate of O can be determined by theoretical calculation, such as 5.13×10 -6 Mol / g / s C NO，n represents the concentration of N0, K NO It represents the half-saturation concentration of NO when it participates in the reaction. For example, it can be determined by theory or experiment, such as 8.33×10 -4 Mol / 1, BIO N is the microbial biomass (in this method, it is the nitrifying bacteria biomass).

[0026] S5, based on S1-S4, can simulate N in a certain period of time 2 O release, update the nitrogen compound content and nitrifying bacteria biomass in the soil after simulation, continue to iterate S1-S4, and simulate the N 2 O release amount.

[0027] The method of the present invention can simulate N at different time scales. 2 O release, e.g. time scale is days, hours, etc., depending on the time scale of input parameters, e.g. n2, Y, K d , Etc., which are well known in the art and will not be elaborated here.

[0028] It should be understood that the simulation N 2 The O release 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.

[0029] Figure 2 is the soil N according to the coupled microbial explicit simulation and implicit simulation method according to an embodiment of the present invention. 2 Schematic diagram of the structure of the O emission estimation device. Figure 2 As shown, the device comprises: 4 + Nitration to NO 2 - The process estimation module 210 is used to estimate the NH 4 + Nitration to NO 2 - The biomass estimation module 220 of nitrifying bacteria involved in the nitrification process in the soil 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; a nitrifying bacteria denitrification process estimation module 230, for estimating the nitrifying bacteria denitrification process using a microbial explicit method, which includes estimating NO 2 - The process of denitrification to NO; denitrification of NO to N 2 O process estimation module 240: used to further estimate the denitrification of NO to N 2 O process; and N 2 The release amount calculation module 250 of O calculates N based on the above modules. 2 The amount of O released.

[0030] 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 the processor 310 in the electronic device can be one or more. Figure 3 A processor 310 is taken as an example; the processor 310, the memory 320, the input device 330 and the output device 340 in the electronic device can be connected via a bus or other means. Figure 3 The example of connecting through bus is taken in the following.

[0031] The memory 320 is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the coupled microbial explicit simulation and implicit simulation methods in the embodiment of the present invention, for example, by NH 4 + Nitration to NO 2 - process estimation module 210; biomass estimation module 220 of nitrifying bacteria involved in nitrification process in soil; denitrification process estimation module 230 of nitrifying bacteria; denitrification of NO to N 2 O process estimation module 240; N 2 The processor 310 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the memory 320, that is, realizes the above-mentioned coupled microbial explicit simulation and implicit simulation method.

[0032] Example

[0033] The following is an example of the N 2 O emission simulation is taken as an example to illustrate the specific utilization of the method of the present invention.

[0034] The longitude and latitude of the study area are 110.71E, 34.93N, and the time is the maize growing season in 2018. This method is used in conjunction with the MCWLA model, which provides simulation data for necessary variables such as soil temperature, soil moisture, and soil NH 4 + Content, etc. The simulation frequency is daily simulation. 2 O emission simulation method, the simulation steps are as follows:

[0035] Start the simulation from the sowing of the crop, 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 NH 4 + Nitration to NO 2 - For details, please refer to the above equation (1).

[0036] 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.

[0037] Calculated NH 4，n Afterwards, the microbial explicit method was used to estimate the denitrification process of nitrifying bacteria. First, NO 2 - The process of denitrification to NO is as shown in equation (3) above;

[0038] Further estimation of NO denitrification to N 2 The process of O is as shown in the above equation (4).

[0039] Based on S1-S4, the N of the day can be simulated 2 O release, update the nitrogen compound content and nitrifying bacteria biomass in the soil after simulation, continue to iterate 1-S4, and simulate the next day's N 2 O emissions. The model runs continuously and outputs the N 2 Simulated values ​​of O emissions.

[0040] The simulated data are compared with the observed daily N 2 O emissions were compared to evaluate the simulation accuracy of the model. The simulation results are shown in Figure 6 .

[0041] In order to demonstrate the level of improvement of the present invention, the accuracy of the following simulation methods was tested simultaneously:

[0042] Only the implicit method of microorganisms is used for simulation. According to the general simulation idea of ​​implicit method, N 2O emission is the nitrification rate (i.e., the NH 4，n ) (In this example, three percentage parameters of 0.002, 0.006, and 0.01 were selected for simulation and the results are shown).

[0043] Only the microbial explicit method was 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, which in turn affects the microbial content. 4 + Nitration to NO 2 - The process is also controlled by nitrifying bacteria, that is, equation 1 is replaced by the following equation:

[0044] in From NH 4 + to NO 2 - The maximum reaction rate is 3.43×10 -6 Mol / g / s, the meanings of other parameters refer to the above description.

[0045] The initial nitrifying bacteria content was set at three levels: 0.1kg / ha, 0.5kg / ha, and 1.0kg / ha, and the results were simulated and displayed respectively.

[0046] Figure 4-Figure 6 The simulation of N after a single fertilization using different methods is shown. 2 O is the result of the release process.

[0047] As shown in the figure, when only the microbial implicit method is used for simulation ( Figure 4 ), simulated N 2 The peak of O emission was earlier than observed because the nitrification rate increased rapidly and then decreased after fertilization, which led to the use of fixed percentage to estimate N 2 O emission, N 2 The O emission rate reaches its peak immediately, which is inconsistent with actual observations.

[0048] Figure 5 The simulation results of the microbial explicit method are shown. The simulated peak value is significantly delayed compared with the observation. This is because there is a feedback loop between the microbial content and the nitrogen cycle rate. The microbial content is low at the beginning, and the simulated nitrogen cycle reaction rate is low. After a long period of feedback loop, the microbial content and N 2 At the same time, if the initial value is set too small, the simulated N 2O emissions also cause the simulation results to be too small for a long time due to the feedback loop between microbial content and 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.

[0049] 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. 2 O emissions, r of simulation results under different parameter scenarios when only using microbial implicit or explicit methods 2 are all less than 0.1, and using the method proposed in the present invention, the r 2 This indicates that the method proposed in the present invention can effectively increase soil N 2 Simulation accuracy of O emissions.

[0050] This method disassembles and reconstructs the traditional simulation method, using the implicit microbial method to calculate the nitrification rate and the explicit microbial method to calculate the denitrification process of nitrifying bacteria. The nitrification rate calculated by the implicit microbial method is used to estimate the biomass of nitrifying bacteria and limit the biomass to a reasonable range. However, the implicit method does not directly calculate N 2 O emissions. The microbial explicit method is only used to simulate N 2 O emissions no longer affect the biomass of nitrifying bacteria, thus avoiding the amplification of the deviation of the initial microbial value by the feedback loop between the microbial content and the soil nitrogen cycle rate.

[0051] That is, the present invention improves soil N 2 The simulation method of O emission couples the implicit microbial simulation and explicit simulation methods, combining the advantages of both to make up for the shortcomings of the other. It effectively avoids the problem that implicit simulation lacks consideration of microbial processes and the initial value of explicit simulation is difficult to estimate. The present invention can effectively improve soil N 2 Simulation accuracy of O emissions.

[0052] 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 microbial explicit simulation and implicit simulation methods comprises the following steps: S1: For the study area, the microbial implicit method was 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 involved in nitrification; S2: Nitrated NH based on the calculation 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 the 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 from NO2 - The amount of reaction to NO, Indicates that from 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 equation (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, the biomass change of nitrifying bacteria after a period of time is calculated using formula (2), that is, ΔBIO N , then the initial BIO N Value plus ΔBIO N , the biomass of nitrifying bacteria after the period of time is obtained, and the calculation is repeated in this way to obtain the biomass of nitrifying bacteria in subsequent stages.

4. The method according to claim 1, characterized in that: 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, characterized in that 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 coupling 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 involved in nitrification; The module for estimating the biomass of nitrifying bacteria involved in the nitrification process in the 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 the nitrification rate, K d is the death rate of nitrifying bacteria; BIO N is the biomass of nitrifying bacteria; The module for estimating the denitrification process of nitrifying bacteria is used to estimate the denitrification process of nitrifying bacteria 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 from NO2 - The amount of reaction to NO, Indicates that from 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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