Rice field methane emission prediction method based on CH4MN model

Abstract

According to the rice field methane emission prediction method based on the CH4MN model, the influence of the rice field methane emission microorganism process and soil nitrogen is considered, the uncertainty of simulation is reduced, and rice field methane emission is accurately predicted. Comprising the following steps: S1, acquiring rice field agricultural production input, water management measures, meteorological data, observed rice field soil environment information, rice information and microorganism information as input data of a CH4MN model; s2, based on a CH4MN model algorithm, calculating a substrate source and a soil environment required by methane generation, and the influence of soil nitrogen on organic matter decomposition; s3, calculating the influence of soil oxidation reduction potential, microorganisms and rice plants on methane generation and oxidation based on a CH4MN model algorithm; s4, calculating a methane generation rate and an emission rate based on a CH4MN model algorithm by using the methane generation and oxidation influence factors calculated in the step S1-3; and S5, verifying the CH4MN model precision based on point observation information.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring and evaluation, and in particular to a method for accurately predicting methane emissions from paddy fields, and in particular to a method for predicting methane emissions from paddy fields based on a CH4MN model. Background Art

[0002] The methane production rate in paddy fields is generally determined by the influence of methanogenic substrates and environmental factors. During the flooding stage, the soil in the paddy field is in an anaerobic environment. When the redox potential drops to a certain value, methanogens use the hydrolyzed and fermented organic matter in the soil and rice root secretions to produce methane. Most of the methane will be oxidized by methane-oxidizing bacteria and rice plants, and only a small part will not be oxidized. These unoxidized methane are discharged into the atmosphere through rice transport tissues or bubbles at the water interface. During the entire rice growing season, rice controls about 90% of methane transport during the rice growing season. In summary, the production, oxidation and emission of methane in paddy fields are affected by many factors, including soil physical and chemical properties, fertilization (soil nitrogen, exogenous organic matter), irrigation, roots, stems and leaves, microorganisms, etc. Based on the mechanism of methane emission from rice fields, some process models of methane emission from rice fields have been developed. The widely used ones are DNDC-Rice (Denitrification-Decomposition-Rice model, including rice module), DAYCENT (A Daily Version of Carbon-Nitrogen-EcosystemCentury Model, daily scale carbon and nitrogen ecosystem model), and CH4MOD model (methane emission model from rice fields). The DNDC-Rice model quantifies the generation and consumption of electrons in the soil redox process for rice fields and has been verified around the world. However, the DNDC-Rice model requires many input parameters and a large amount of calculation. The DAYCENT model is a daily scale model evolved from the CENTURY model (Carbon-Nitrogen-Ecosystem Century Model), which can be used to simulate the plant-soil-atmosphere carbon and nitrogen cycle simulation. The principle of its methane emission refers to the CH4MOD model. The CH4MOD model takes into account irrigation and drainage management and bubble emissions, focuses on the methane production and emission process, has fewer input parameters, and is easier to use and more flexible than the DNDC-Rice model. The abundance of methanogenic bacteria and methane-oxidizing bacteria in the soil will also affect the production and oxidation of methane in rice fields. Methanogens mainly exist under anaerobic conditions and convert carbon sources into methane through reduction reactions. Methane-oxidizing bacteria mainly exist in the aerobic layer of the soil and reduce methane emissions through methane oxidation. Therefore, the abundance of the two microorganisms will directly affect the production and oxidation of methane in rice fields. However, none of the existing models consider these two microorganisms, resulting in greater uncertainty in the simulation results. In addition, studies have shown that nitrogen fertilizer application will promote the decomposition of soil organic matter, increase the substrate supply of methanogens, and thus stimulate the production of methane in the soil. However, the existing models rarely consider the impact of nitrogen fertilizer management, especially fertilization methods, on methane emissions, resulting in a limited model evaluation range and large uncertainty.

[0003] In view of the above problems, there is an urgent need to propose an effective and accurate rice field methane emission prediction method based on the microbial process of rice field methane emission, reduce the uncertainty of simulation results, and provide scientific data and technical guarantee for national emission reduction. The new model constructed in the present invention is named CH4MN model (CH4-Microbe-Nitrogen, a rice field methane emission assessment model considering microorganisms and nitrogen effectiveness). Summary of the invention

[0004] The purpose of the present invention is to provide a method for predicting methane emissions from paddy fields, which can accurately and effectively realize quantitative prediction of methane emissions from paddy fields based on the CH4MN model.

[0005] The present invention provides a method for predicting methane emissions from paddy fields based on a CH4MN model, comprising the following steps:

[0006] S1. Obtain agricultural production inputs, water management measures, and meteorological data of paddy fields in the study area as input data for the CH4MN model; observe paddy field soil environmental information, rice information, and microbial information in the study area as input data for the CH4MN model.

[0007] S2. Input the data obtained in step S1, and calculate the substrate source required for methane production, soil environment (soil temperature, texture), and the effect of soil nitrogen on organic matter decomposition based on the CH4MN model algorithm.

[0008] S3. Input the data obtained in step S1, and calculate the effects of soil redox potential, microorganisms, and rice plants on methane production and oxidation based on the CH4MN model algorithm.

[0009] S4. Using the methane production and oxidation influencing factors calculated in steps S1, S2, and S3, calculate the methane production rate and emission rate based on the CH4MN model algorithm.

[0010] S5. Verify the accuracy of the CH4MN model based on point observation information.

[0011] Among them, the agricultural production inputs described in step S1 include the amount of straw returned to the field, organic fertilizer, and fertilizer application; water management measures include recording irrigation and drainage time; meteorological data include temperature; soil environmental information includes soil texture (soil sand content); rice information includes rice variety and yield (used to calculate aboveground biomass at rice harvest); microbial information includes the abundance of methanogenic bacteria and the abundance of methane-oxidizing bacteria.

[0012] The influencing factors obtained in steps S2 and S3 are mainly used to calculate the methane production rate P in step S4 and the influence of microorganisms and rice plants on methane oxidation O.

[0013] The formula for calculating the methane production rate is:

[0014] P = 0.27 × F Eh ×SI×MI1×TI r ×[(1.8×10 -3 ×VI×W 1.25 )+0.65×N×(k1×OM N +k

[0015] ×OM S )]

[0016] In the formula, F Eh is the reduction factor of soil redox potential, is the effect of soil moisture conditions on methane production, soil index (SI) and temperature index (TI r ) is the effect of soil texture and soil temperature on substrate decomposition, OM N and OM s are the easily decomposable and difficultly decomposable components of organic matter, k1 and k2 are the decay rates of the first-order kinetic decomposition coefficients of the easily decomposable and difficultly decomposable components, which are 2.7×10 -2 and 2×10 -3 d -1 , 0.65 is the attenuation factor of organic matter content under flooding conditions, the constant 0.27 is the ratio of the molecular weight of methane to the molecular weight of methanogenic substrates, MI1 is the effect of methanogens on methane production, and N is the soil nitrogen impact index, which quantifies the effect of nitrogen on substrate decomposition.

[0017] The effect of microorganisms and rice plants on methane oxidation O was calculated using the formula:

[0018] O=MI2×OF p

[0019] Where MI2 is the effect of methanotrophic bacteria on methane oxidation, OF p Effects of rice plants on methane oxidation.

[0020] Among them, in step S4, the emission of methane in the CH4MN model is divided into two parts, namely, emission through rice aerenchyma and emission through water bubbles. The methane emission rate calculation formula is:

[0021] E T =P×(1-O)

[0022] Where P is the methane production rate and O is the effect of microorganisms and rice plants on methane oxidation.

[0023] The formula for calculating methane emitted by rice plants is:

[0024]

[0025] Ep =F p ×E

[0026] In the formula, F p is the proportion of rice methane emissions to production, W is the aboveground biomass of rice on that day, the unit is: g·m -2 , W max is the aboveground biomass of rice at harvest, E p is the methane emission rate of rice plants, in g·m -2 ·d -1 .

[0027] The formula for calculating methane emissions through bubbles is:

[0028] E bl =0.7×(E T -P0)×ln(T soil ) / W root

[0029] Where W root is the rice root biomass, unit: g·m -2 , P0 is the critical methane production rate for bubbles to form after the soil reaches saturation with methane, which is quantified as 0.002 and the unit is: g·m -2 ·d -1 , T soii is the soil temperature.

[0030] Compared with the prior art, the beneficial effects of the present invention are: an effective and accurate prediction method is proposed based on the microbial process of methane emissions from rice fields, which improves the prediction accuracy of methane emissions from rice fields, has higher reliability and scientificity, and can provide more accurate data and decision-making support for national emission reduction measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of the steps of the present invention.

[0032] Figure 2 This is an exponential fitting diagram of the effect of soil nitrogen content on organic matter decomposition.

[0033] Figure 3 This is an exponential fitting diagram of the impact of methanogenic bacteria on methane production.

[0034] Figure 4 This is a fitting diagram of the exponential effect of methanotrophic bacteria on methane oxidation.

[0035] Figure 5 This is a fitting diagram of the index of the effect of rice plants on methane oxidation.

[0036] Figure 6 This is a time series graph of methane emissions from rice fields during the rice growing season.

[0037] Figure 7 This is the CH4MN model verification diagram. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. The embodiments described herein are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0039] A method for predicting methane emissions from rice fields based on the CH4MN model, the steps are as follows: Figure 1 As shown, the following steps are included:

[0040] S1. Obtain agricultural production inputs, water management measures, meteorological information, soil environment information, rice information, and microbial information in the study area as input data for the CH4MN model;

[0041] More specifically, agricultural production inputs include the amount of straw returned to the field, organic fertilizer, and fertilizer application; water management measures include irrigation and drainage; fertilizer application includes the statistically purified nitrogen application amount; water management measures include the statistical flooding duration and drainage duration; meteorological data include temperature; soil environmental information includes observations of soil sand content; rice information includes rice varieties and yields (used to calculate the maximum aboveground biomass of rice); microbial information includes the abundance of methanogenic bacteria and methane-oxidizing bacteria.

[0042] S2. Based on the data obtained in step S1, calculate the substrate source required for methane production, soil environment (soil temperature, texture), and the effect of soil nitrogen on organic matter decomposition;

[0043] Specifically, the calculation formula for the substrate provided by exogenous organic matter is:

[0044] C OM =0.65×SI×TI r ×N×(k1×OM N +k2×OM s )

[0045] In the formula, C OM Indicates the amount of carbohydrates degraded by exogenous organic matter per day, in g·m -2 ·d -1 The effects of soil texture and soil temperature on decomposition were expressed using soil index (SI) and temperature index (TI), respectively. r ) Quantification. N and OM sare the easily decomposable and difficultly decomposable components of organic matter, k1 and k2 are the decay rates of the first-order kinetic decomposition coefficients of the easily decomposable and difficultly decomposable components, which are 2.7×10 -2 and 2×10 -3 d -1 , 0.65 is the attenuation factor of organic matter content under flooding conditions, and N is the influence index of soil nitrogen on methane production.

[0046] The soil index (SI) calculation formula is:

[0047] SI=0.325+0.0225×SAND

[0048] Where SAND is the sand content of soil.

[0049] Temperature Index (TI r ) is calculated as:

[0050] TI r =(411.3x-16.6x 2 +0.213x 3 +3500) / 348(15 <x<39.5)

[0051] Where x is the temperature of the day in degrees Celsius.

[0052] The CH4MN model takes into account the effect of soil nitrogen on the decomposition of organic matter. The influence index formula is composed of two parts: N x is the effect of soil nitrogen content on organic matter decomposition, and the fitting relationship is as follows: Figure 2 As shown, N d The effect of deep nitrogen fertilizer application on the decomposition of organic matter is calculated as follows:

[0053] N x =0.0012x+0.1019

[0054] N d =1-(-0.18x+10.35) / 100

[0055] In the formula, x is the soil nitrogen content, the unit is: mg / kg;

[0056] Therefore, the calculation formula for the effect of soil nitrogen on organic matter decomposition is:

[0057] N=α1×N x ×N d

[0058] In the formula, α1 is the adjustment coefficient.

[0059] C R =1.8×10 -3 ×VI×SI×W1.25

[0060] C R Carbohydrates produced by rice plants, unit: g·m -2 ·d -1 , W is the aboveground biomass of rice on that day, unit: g·m -2 VI is the rice variety index. The calculation formula of W is as follows:

[0061]

[0062] B0=W max / W0-1

[0063] W max =9.46×GY 0.76

[0064] Where W0 and W max represent the aboveground biomass of rice at transplanting and harvesting respectively, W0 is 15, GY is rice yield, B0 is the relative biomass increase of rice during the growth period, D is the number of growing days after rice transplanting, and the constant r is the intrinsic growth rate of rice growth, which is 0.08 for single-season rice and 0.1 for double-season early rice and late rice.

[0065] S3, based on the data obtained in step S1, calculating the effects of soil redox potential, microorganisms, and rice plants on methane production and oxidation;

[0066] Specifically, the soil redox potential reflects the soil moisture conditions. The soil redox potential is related to the duration of flooding or drainage. The formula is:

[0067]

[0068] Where t is the number of days after flooding or drainage, Eh (t) is the value of soil redox potential at time t, A Eh and D Eh are the difference coefficients, which are 0.23 and 0.16 respectively, and B Eh are the upper and lower limits of the redox potential during field drying and flooding, which are 300mv and -250mv respectively.

[0069]

[0070] In the formula, F Eh is the reduction factor of soil redox potential.

[0071] The influence of microorganisms on methane production and oxidation is divided into the potential of methanogenic bacteria to produce methane and the potential of methane oxidizing bacteria to oxidize methane. The exponential relationship between the influence of methanogenic bacteria on methane production is fitted as follows: Figure 3As shown in the figure, the fitting relationship of the influence index of methane oxidation bacteria on methane oxidation is as follows Figure 4 As shown in Figure 2, the effects of microorganisms on methane production and oxidation are quantified by microbial indices MI1 and MI2. MI1 is the effect of methanogens on methane production, and MI2 is the effect of methanotrophs on methane oxidation. The calculation formula is:

[0072] MI1=α2×20.1237ln(x1)+0.2131

[0073] MI2=α3×0.0384x2+0.15888

[0074] Where x1 is the abundance of methanogenic bacteria in the soil, unit is: 10 7 copies / g; x2 is the abundance of methane-oxidizing bacteria in the soil, unit: 10 7 copies / g, α2 and α3 are adjustment coefficients.

[0075] The effect of rice plants on methane oxidation is related to the aboveground biomass of rice. During the transmission process of rice plants, part of the methane will be oxidized. The exponential fitting relationship of the effect on methane oxidation is as follows: Figure 5 As shown, the calculation formula is:

[0076] OF p =0.1498ln(W)-0.0404

[0077] Where W is the aboveground biomass of rice on that day, in g·m -2 ;

[0078] S4. Calculate the methane generation rate and emission rate based on the methane generation and oxidation influencing factors obtained in steps S1, S2, and S3

[0079] Specifically, the methane production influencing factors calculated in steps S1, S2, and S3 are used to calculate the methane production rate P based on the CH4MN model algorithm. The formula is:

[0080] P = 0.27 × F Eh ×SI×MI1×TI r ×[(1.8×10 -3 ×VI×W 1.25 )+0.65×N×(k1×OM N +k

[0081] ×OM S )]

[0082] In the formula, F Eh is the reduction factor of soil redox potential, is the effect of soil moisture conditions on methane production, soil index (SI) and temperature index (TI r) is the effect of soil texture and soil temperature on substrate decomposition, OM N and OM s are the easily decomposable and difficultly decomposable components of organic matter, k1 and k2 are the decay rates of the first-order kinetic decomposition coefficients of the easily decomposable and difficultly decomposable components, which are 2.7×10 -2 and 2×10 -3 d -1 , 0.65 is the attenuation factor of organic matter content under flooding conditions, the constant 0.27 is the ratio of the molecular weight of methane to the molecular weight of methanogenic substrates, MI1 is the effect of methanogens on methane production, and N is the soil nitrogen impact index, which quantifies the effect of soil nitrogen on substrate decomposition.

[0083] Most of the methane produced will be oxidized by methanotrophic bacteria and rice plants. Therefore, the effect of microorganisms and rice plants on methane oxidation is calculated as:

[0084] O=MI2×OF p

[0085] Where MI2 is the effect of methanotrophic bacteria on methane oxidation, OF p Effects of rice plants on methane oxidation.

[0086] Unoxidized methane is emitted into the atmosphere through rice transport tissues or bubbles at the water interface. The methane emission rate is calculated as:

[0087] E T =P×(1-O)

[0088] Where P is the methane production rate and O is the effect of microorganisms and rice plants on methane oxidation.

[0089] The formula for calculating methane emissions through rice aerenchyma is:

[0090]

[0091] E p =F p ×E

[0092] In the formula, F p is the proportion of rice methane emissions to production, W is the aboveground biomass of rice on that day, the unit is: g·m -2 , W max is the aboveground biomass of rice at harvest, E p is the methane emission rate of rice plants, in g·m -2 ·d -1 .

[0093] The formula for calculating methane emissions through bubbles is:

[0094] Ebl =0.7×(E T -P0)×ln(T soil ) / W root

[0095] Where W root is the rice root biomass, unit: g·m -2 , P0 is the critical methane production rate for bubbles to form after the soil reaches saturation with methane, which is quantified as 0.002 and the unit is: g·m -2 ·d -1 , T soil is the soil temperature.

[0096] The soil temperature is calculated based on the temperature data of the meteorological station to calculate the daily average soil temperature. The formula is:

[0097]

[0098] In the formula, is the average soil temperature on day D after rice transplanting, is the maximum soil temperature on day D after rice transplanting, Minimum soil temperature on day D after rice transplanting.

[0099] in, The calculation formula is as follows:

[0100]

[0101] In the formula, is the lowest air temperature on the D-1 day after rice transplanting, is the lowest air temperature on the Dth day after rice transplanting, It is the lowest air temperature on the D+1 day after rice transplanting.

[0102] in, The calculation formula is as follows:

[0103]

[0104] Where DOY is the number of days after rice transplanting, is the maximum air temperature on the Dth day after rice transplanting, is the maximum air temperature on the Dth day after rice transplanting, It is the maximum air temperature on the D+1 day after rice transplanting.

[0105] W root It can be described by aboveground biomass (W) as:

[0106] W root =0.136×(W root +W) 0.936

[0107] The iteration stop condition of this formula is W root (D+1)-W root (D)<0.1, W root The initial value is 0, and D is the Dth day after rice transplanting.

[0108] S5. Verification of the CH4MN model based on observational data

[0109] Specifically, since the CH4MN model is a daily scale model, the methane emission rate calculated by the algorithm in steps S2, S3, and S4 of the CH4MN model is multiplied by 1 to obtain the methane emission of the day. The methane emission time series of the rice growing season is obtained by simulating the daily methane emission of rice fields during the rice growing season, and is verified with the actual observed methane emission data of rice fields. According to the Pearson correlation coefficient (R 2 ) and root mean square error (RMSE) were used to evaluate the accuracy of the CH4MN model.

[0110] In the practical application process of the present invention, the following specific steps are included:

[0111] 1. Collect the amount of straw returned to the rice fields in the study area, the amount of organic fertilizer applied, the amount of fertilizer applied, the rice variety, the temperature of the meteorological station, and the water management measures, including the statistical flooding duration and drainage duration. Observe the soil sand content, rice yield (used to calculate the aboveground biomass at rice harvest) and the abundance of microbial methane-oxidizing bacteria and methanogenic bacteria in the soil in the study area. This study area selected the rice experimental field in Yichun City, Jiangxi Province as the study area, and took early rice as the research object. The rice was transplanted on April 27 and harvested on July 15. The input parameter observation values ​​are shown in Table 1. In actual application, the input parameters should be based on local actual conditions.

[0112] Table 1 CH4MN parameters

[0113]

[0114]

[0115] 2. Input the data into the CH4MN model, that is, according to the algorithm in the specific implementation method, the substrate required for methane production is calculated based on the acquired data, and the influence of soil redox potential, microorganisms, and rice plants on methane production and oxidation is calculated. Finally, the methane production rate and methane emission rate are calculated based on the above-mentioned influencing factors. The CH4MN model is a daily scale model. The emission rate is multiplied by 1 to obtain the methane emission of the day. By simulating the daily methane emission of rice fields during the rice growing season, the time series of methane emission of rice fields during the rice growing season is obtained. The simulation results are as follows: Figure 6 As shown, the x-axis is the time series, the y-axis is the daily methane emissions, the observed values ​​are scattered points, and the simulated values ​​are continuous curves.

[0116] 3. Based on the observed data and simulated daily methane emissions from paddy fields during the rice growing season, the accuracy of the CH4MN model was verified. Figure 7 As shown, R 2 The average value of the average molecular weight was 0.89, and the RMSE was 96.3 mg·m -2 ·d -1 .

Claims

1. A method for predicting methane emissions from rice fields based on the CH4MN model, characterized in that: The following steps are involved: S1. Obtain agricultural production inputs, water management measures, and meteorological data of paddy fields in the study area as input data for the CH4MN model; observe paddy field soil environmental information, rice information, and microbial information in the study area as input data for the CH4MN model; S2, input the data obtained in step S1, and calculate the substrate source required for methane production, soil environment, and the effect of soil nitrogen on organic matter decomposition based on the CH4MN model algorithm; the soil environment includes: soil temperature and soil texture; S3, inputting the data obtained in step S1, and calculating the effects of soil redox potential, microorganisms, and rice plants on methane production and oxidation based on the CH4MN model algorithm; S4, using the methane production and oxidation influencing factors calculated in steps S1, S2, and S3, calculate the methane production rate and emission rate based on the CH4MN model algorithm; S5. Verify the accuracy of the CH4MN model based on point observation information.

2. The method for predicting methane emissions from paddy fields based on the CH4MN model according to claim 1, characterized in that: In step S1, agricultural production inputs include the amount of straw returned to the field, organic fertilizer, and fertilizer application; water management measures include irrigation and drainage; fertilizer application includes the statistically purified nitrogen application amount; water management measures include statistically calculated flooding duration and drainage duration; meteorological data include temperature; soil environmental information includes observations of soil sand content; rice information includes rice varieties and yields; and microbial information includes the abundance of methanogenic bacteria and methane-oxidizing bacteria.

3. A rice field methane emission prediction method based on the CH4MN model according to claim 1 or 2, characterized in that: In step S2, the substrate source required for methane production and the influence of soil environment and soil nitrogen on the decomposition of organic matter are calculated; specifically, the calculation formula for the substrate provided by exogenous organic matter is: C OM =0.65×SI×TI r ×N×(k1×OM N +k2×OM s ) In the formula, C OM Indicates the amount of carbohydrates degraded by exogenous organic matter per day, in g·m -2 ·d -1 The effects of soil texture and soil temperature on decomposition are expressed as soil index SI and temperature index TI, respectively. r Quantification; OM N and OM s are the easily decomposable and difficultly decomposable components of organic matter, k1 and k2 are the decay rates of the first-order kinetic decomposition coefficients of the easily decomposable and difficultly decomposable components, which are 2.7×10 -2 and 2×10 -3 d -1 , 0.65 is the attenuation factor of organic matter content under flooding conditions, and N is the influence index of soil nitrogen on methane production; The soil index SI calculation formula is: SI=0.325+0.0225×SAND In the formula, SAND is the soil sand content; Temperature Index TI r The calculation formula is: TI r =(411.3x-16.6x 2 +0.213x 3 +3500) / 348, 15<x<39.5； Where x is the temperature of the day in degrees Celsius.

4. The method for predicting methane emissions from rice fields based on the CH4MN model according to claim 3 is characterized in that: The CH4MN model takes into account the effect of soil nitrogen on the decomposition of organic matter. The influence index formula is composed of two parts: N x is the effect of soil nitrogen content on the decomposition of organic matter, N d The effect of deep nitrogen fertilizer application on the decomposition of organic matter is calculated as follows: N x =0.0012x+0.1019 N d =1-(-0.18x+10.35) / 100 In the formula, x is the soil nitrogen content, the unit is: mg / kg; Therefore, the calculation formula for the effect of soil nitrogen on organic matter decomposition is: N=α1×N x ×N d In the formula, α1 is the adjustment coefficient; C R =1.8×10 -3 ×VI×SI×W 1.25 C R Carbohydrates produced by rice plants, unit: g·m -2 ·d -1 , W is the aboveground biomass of rice on that day, unit: g·m -2 ; VI is the rice variety index; W is calculated as follows: B0=W max / W0-1 IN max =9.46×GY 0.76 Where W0 and W max represent the aboveground biomass of rice at transplanting and harvesting respectively, GY is the rice yield, B0 is the relative biomass increase of rice during the growth period, D is the number of growth days of rice after transplanting, and the constant r is the intrinsic growth rate of rice growth.

5. The method for predicting methane emissions from paddy fields based on the CH4MN model according to claim 1, characterized in that: In step S3, the soil redox potential is related to the duration of flooding or drainage, and the formula is: Where t is the number of days after flooding or drainage, Eh (t) is the value of soil redox potential at time t, A Eh and D Eh is the difference coefficient, B Eh are the upper and lower limits of the redox potential during field drying and flooding; In the formula, F Eh is the reduction factor of soil redox potential.

6. The method for predicting methane emissions from paddy fields based on the CH4MN model according to claim 5, characterized in that: The influence of microorganisms on methane production and oxidation is quantified by microbial indices MI1 and MI2. MI1 is the influence of methanogens on methane production, and MI2 is the influence of methanotrophs on methane oxidation. The calculation formula is: MI1=α2×20.1237ln(x1)+0.2131 MI2=α3×0.0384x2+0.15888 Where x1 is the abundance of methanogenic bacteria in the soil, unit is: 10 7 copies / g; x2 is the abundance of methane-oxidizing bacteria in the soil, unit: 10 7 copies / g, α2 and α3 are adjustment coefficients.

7. A rice field methane emission prediction method based on the CH4MN model according to claim 5 or 6, characterized in that: The effect of rice plants on methane oxidation is related to the aboveground biomass of rice. Part of the methane will be oxidized during the transmission process of rice plants. The calculation formula is: OF p =0.1498ln(W)-0.0404 Where W is the aboveground biomass of rice on that day, in g·m -2 .

8. The method for predicting rice field methane emissions based on the CH4MN model according to claim 1, characterized in that: In step S4, the methane production rate P is calculated based on the CH4MN model algorithm, and the formula is: P=0.27×F Eh ×SI×MI1×TI r ×[(1.8×10 -3 ×VI×W 1.25 )+0.65×N×(k1×OM N +k2 ×OM S )] In the formula, F Eh is the reduction factor of soil redox potential, is the effect of soil moisture conditions on methane production, soil index SI and temperature index TI r The effects of soil texture and soil temperature on substrate decomposition, OM N and OM s are the easily decomposable and difficultly decomposable components of organic matter, k1 and k2 are the decay rates of the first-order kinetic decomposition coefficients of the easily decomposable and difficultly decomposable components, 0.65 is the attenuation factor of organic matter content under flooding conditions, and the constant 0.27 is the ratio of the molecular weight of methane to the molecular weight of methane-producing substrates.

9. The method for predicting methane emissions from paddy fields based on the CH4MN model according to claim 8, characterized in that: The effect of microorganisms and rice plants on methane oxidation is calculated as follows: O=MI2×OF p Where MI2 is the effect of methanotrophic bacteria on methane oxidation, OF p for the effect of rice plants on methane oxidation; The formula for calculating the methane emission rate is: AND T =P×(1-O) In the formula, P is the methane production rate, and O is the effect of microorganisms and rice plants on methane oxidation; The formula for calculating methane emissions through rice aerenchyma is: E p =F p ×E In the formula, F p is the proportion of rice methane emissions to production, W is the aboveground biomass of rice on that day, the unit is: g·m -2 , W max is the aboveground biomass of rice at harvest, E p is the methane emission rate of rice plants, in g·m -2 ·d -1 ; The formula for calculating methane emissions through bubbles is: HAVE BEEN bl =0.7×(E T -P0)×ln(T soil ) / W root Where W root is the rice root biomass, unit: g·m -2 , P0 is the critical methane production rate for bubbles to form after the soil reaches saturation with methane, and the unit is: g·m -2 ·d -1 , T soil is the soil temperature; The soil temperature is calculated based on the temperature data of the meteorological station to calculate the daily average soil temperature. The formula is: In the formula, is the average soil temperature on day D after rice transplanting, is the maximum soil temperature on day D after rice transplanting, Minimum soil temperature on day D after rice transplanting.

10. The method for predicting rice field methane emissions based on the CH4MN model according to claim 1, characterized in that: In step S5, the methane emission rate calculated by the algorithm in the CH4MN model is multiplied by 1 to obtain the methane emission for the day. The methane emission time series of the rice growing season is obtained by simulating the daily methane emission of the rice field during the rice growing season. The time series is then verified with the actual observed methane emission data of the rice field. The Pearson correlation coefficient R 2 And the root mean square error RMSE is used to evaluate the accuracy of the CH4MN model.

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