CN116090639A - Method and device for predicting total process greenhouse gas emission of agricultural land system - Google Patents
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Abstract
The invention discloses a method and a device for predicting the whole process greenhouse gas emission of an agricultural land system, which relate to the technical field of agricultural land greenhouse gas emission prediction.
Description
Technical Field
The invention relates to the technical field of agricultural land greenhouse gas emission prediction, in particular to a method and a device for predicting the whole process greenhouse gas emission of an agricultural land system.
Background
The greenhouse gases generally comprise carbon dioxide, nitrous oxide, methane and the like, since the industrial revolution, the content of the greenhouse gases is increased in a straight line, meanwhile, people observe that the temperature of the earth is increased continuously, natural disasters frequently occur, water resources are short, crop yield changes, disease hazards are aggravated, sea level is increased, biomass changes are caused, and the like on natural ecology, the influence of the greenhouse gases on climate warming is not only dependent on the intensity of the greenhouse effects caused by various gases, but also on the duration of the occurrence, so that the sources and the directions of the greenhouse gases are required to be monitored in real time, means for reducing the emission of the greenhouse gases are usually fixed-point detection nowadays, a mode of optimizing and modifying the environment after the abnormality is detected is adopted as a source of the greenhouse gases, the greenhouse gas emission of the agricultural land is far higher than that of natural ecological environment, and with the continuous development of rigid consumption demands, the agricultural land is continuously opened up, greenhouse gas emitted in the crop production process is also continuously increased, and the carbon emission of crops is changed due to different fertilizing amounts of crops, even if the detection ranges are the same, the carbon emission in different detection areas cannot be completely consistent, and if the fertilizing amount is required to be reduced for controlling the greenhouse gas emission, the agricultural land is greatly influenced, so that for crops needing to be fertilized, the greenhouse gas emission is predicted according to the production information and fertilizing demands, thereby helping farmers to adjust the fertilizing amount of the agricultural land, and being an important problem for sustainable development of the agricultural land in China at present.
Disclosure of Invention
In order to overcome the defects, the invention provides a method and a device for predicting the whole-process greenhouse gas emission of an agricultural land system, creatively introduces the influence of topdressing measures on the greenhouse gas emission of the agricultural land, predicts the greenhouse gas emission of the agricultural land according to the differences of topdressing modes such as habitual topdressing, real-time topdressing, accurate topdressing, disposable topdressing and the like and the differences of agricultural land agricultural product types, planting densities and growth nodes.
A method for predicting the whole process greenhouse gas emission of an agricultural land system comprises the following steps:
step 1: presetting a gas emission model;
step 2: acquiring planting data of an agricultural land as a first emission factor, and acquiring topdressing measures for the agricultural land as a second emission factor;
step 3: and leading the first emission factor and the second emission factor into a gas emission model to obtain the predicted gas emission.
Preferably, the method further comprises the following steps:
step 4: extracting the predicted single-kind gas emission amount and the total emission amount respectively, and judging whether the single-kind gas emission amount exceeding a threshold value exists or not;
step 5: and under the condition that the emission amount of all the single-type gases does not exceed the threshold value, calculating the ratio of any single-type gases to the total emission amount to obtain the greenhouse gas emission ratio.
Preferably, the additional fertilizer measures comprise habitual additional fertilizer, real-time additional fertilizer, accurate additional fertilizer and disposable additional fertilizer.
Preferably, the planting data includes a kind of agricultural products planted on an agricultural land, a planting density of the agricultural products, and a growing node of the agricultural products.
Preferably, the process for establishing the gas emission amount model includes the following steps:
step 11: establishing a first-order emission model, and erasing offset of the first-order emission model based on the gray derivative to obtain a whitening function;
step 12: setting up a factor sequence as an analog quantity according to the first emission factor and the second emission factor to obtain a prediction model;
step 13: and based on the whitening function, performing whitening guidance on the prediction model by adopting a relevancy qualification model test to obtain a prediction gas emission model.
Preferably, the relevancy qualification model is a simulation sequence of a factor sequence.
The device for predicting the whole process greenhouse gas emission of the agricultural land system comprises the following components:
and the gas acquisition module is used for: the method is used for collecting planting data and topdressing measures of agricultural lands;
the calculation processing module: the gas emission prediction method comprises the steps of acquiring data by adopting a gas emission model and a gas acquisition module to obtain predicted gas emission;
the gas collection module is connected with the calculation processing module.
Preferably, the device also comprises a gas detection module and an impurity filtering module,
and a gas detection module: the gas detection device is used for detecting emission of the collected data of the gas collection module to obtain a detection result;
impurity filtration module: the gas filtering device is used for filtering out particle impurities from the gas acquired by the gas acquisition module;
the gas collection module, the impurity filtering module, the gas detection module and the calculation processing module are sequentially connected.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of a method for predicting overall process greenhouse gas emissions of an agricultural land system.
An electronic device comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising operating instructions for performing a method for predicting overall process greenhouse gas emissions of an agricultural land system.
The beneficial effects of the invention are as follows:
the influence of topdressing measures on the gas emission of the agricultural land greenhouse is creatively introduced, the greenhouse gas emission of the agricultural land is predicted according to the differences of topdressing modes such as habitual topdressing, real-time topdressing, accurate topdressing, disposable topdressing and the like on different agricultural land agricultural product types, planting densities and growth nodes, and farmers can be helped to adjust the topdressing measures according to the change of the agricultural product growth nodes according to the prediction data, so that the yield of agricultural products is ensured, the greenhouse gas emission can be effectively controlled, and the win-win effect of labor harvesting and environmental protection is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
FIG. 1 is a flow chart of a method for predicting the overall process greenhouse gas emissions of an agricultural land system provided by the invention;
fig. 2 is a schematic diagram of a prediction apparatus for greenhouse gas emission in the whole process of an agricultural land system.
Detailed Description
Embodiments of the technical scheme of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and thus are merely examples, and are not intended to limit the scope of the present invention.
It is noted that unless otherwise indicated, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.
As shown in fig. 1, a method for predicting the total process greenhouse gas emission of an agricultural land system comprises the following steps:
step 1: presetting a gas emission model;
step 2: acquiring planting data of an agricultural land as a first emission factor, and acquiring topdressing measures for the agricultural land as a second emission factor;
step 3: and leading the first emission factor and the second emission factor into a gas emission model to obtain the predicted gas emission.
Crop field production processes are important emissions sources of the greenhouse gases methane (CH 4) and nitrous oxide (N2O). Along with the application of life cycle evaluation method (carbon footprint) in the agricultural field, more and more researches show that the carbon emission is far higher than the carbon fixation of soil in the complete growth cycle of crops, that is, the crop growth process is a net emission system, and simultaneously, chemical fertilizers, mechanical energy consumption in production, flood irrigation with large water and the like are applied to promote the emission of nitrogen dioxide and methane, and simultaneously, a large amount of fossil fuels are consumed, wherein the chemical fertilizers have the characteristics of large difference, high emission promotion and the like, so that the method is different from the existing method for measuring the greenhouse gas content in soil solution, and the greenhouse gas emission prediction method using topdressing measures as main independent variables is proposed.
More specifically, the method further comprises the following steps:
step 4: extracting the predicted single-kind gas emission amount and the total emission amount respectively, and judging whether the single-kind gas emission amount exceeding a threshold value exists or not;
step 5: and under the condition that the emission amount of all the single-type gases does not exceed the threshold value, calculating the ratio of any single-type gases to the total emission amount to obtain the greenhouse gas emission ratio.
In the greenhouse gas, the content ratio of carbon dioxide, methane, nitrous oxide, hydrofluorocarbon, perfluorocarbon and sulfur hexafluoride is taken as a judgment standard, and only the single amount of the gas is detected, the data of the total emission of the gas is not taken as the basis, the emission of the single type of gas is easy to occur, the emission of the single type of gas does not exceed a threshold value, but the ratio of the total emission of the gas exceeds a set ratio, the judgment standard of the greenhouse gas is already met, the monitoring is difficult, and the accurate detection effect is difficult to achieve, so that the accurate detection of the gas when the single amount of the gas exceeds the threshold value is introduced in the step 4 and the step 5, and the accuracy of predicting the greenhouse gas is further improved.
More specifically, the topdressing measures comprise habitual topdressing, real-time topdressing, accurate topdressing and disposable topdressing.
In the actual test process, the rice field is used as a test field to carry out the influence of a plurality of fertilization modes, so that the greenhouse gas emission amounts among the habitual topdressing, the real-time topdressing, the accurate topdressing and the disposable topdressing are different.
More specifically, the planting data includes a type of agricultural product planted on an agricultural land, a planting density of the agricultural product, and a growth node of the agricultural product.
More specifically, the process for establishing the gas emission model comprises the following steps:
step 11: establishing a first-order emission model, and erasing offset of the first-order emission model based on the gray derivative to obtain a whitening function;
step 12: setting up a factor sequence as an analog quantity according to the first emission factor and the second emission factor to obtain a prediction model;
step 13: and based on the whitening function, performing whitening guidance on the prediction model by adopting a relevancy qualification model test to obtain a prediction gas emission model.
Wherein the first order emission model is as follows:
K 0 ＝(K 0 (1),K 0 (2),K 0 (1),…K 0 (n))
the ash derivatives for the first order emission model are:
the whitening function obtained by erasure shifting the first-order emission model based on the gray derivative is shown as follows:
wherein K is 0 Is the unit topdressing action quantity, z is the development gray scale, z= (1, 2,3, … n), delta (m) is the absolute temperature of soil of topdressing nodes,
parameters are estimated for least squares.
The least squares estimation parameter of the whitening function satisfies the following equation:
the factor sequence is shown in the following formula:
t 0 ＝(t 0 (1),t 0 (2),t 0 (1),…t 0 (n))
wherein:
the prediction model is obtained by introducing analog quantity into a residual sequence, and the prediction model is shown as the following formula:
wherein t is 0 For the growth days of agricultural products, x is the number of days of agricultural product growth under the condition of once-used topdressing 0 Get 1, x under the condition of habitual topdressing 0 Taking 1.27, x under the condition of real-time topdressing 0 Taking 1.12, x under the condition of precise topdressing 0 1.18 is taken.
Finally, the predicted gas emission model is obtained as follows:
more specifically, the relevancy qualification model is a simulation sequence of a factor sequence.
As shown in fig. 2, a prediction apparatus for overall process greenhouse gas emission of an agricultural land system includes the following:
and the gas acquisition module is used for: the method is used for collecting planting data and topdressing measures of agricultural lands;
the calculation processing module: the gas emission prediction method comprises the steps of acquiring data by adopting a gas emission model and a gas acquisition module to obtain predicted gas emission;
the gas collection module is connected with the calculation processing module.
The greenhouse gas collection module is used for collecting greenhouse gases, wherein the greenhouse gas collection module is used for collecting greenhouse gases, and the greenhouse gas collection module is used for collecting greenhouse gases.
More specifically, the device also comprises a gas detection module and an impurity filtering module,
and a gas detection module: the gas detection device is used for detecting emission of the collected data of the gas collection module to obtain a detection result;
impurity filtration module: the gas filtering device is used for filtering out particle impurities from the gas acquired by the gas acquisition module;
the gas collection module, the impurity filtering module, the gas detection module and the calculation processing module are sequentially connected.
The gas detection module is used for detecting emission of greenhouse gases to be detected according to the gas spectrum image to obtain detection results, and the gas detector at least comprises a carbon dioxide detector, a nitrogen dioxide detector, an ozone detector, a nitrous oxide detector, a methane detector, a water vapor detector, a hydrofluorocarbon detector, a perfluorocarbon detector and a sulfur hexafluoride detector.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of a method for predicting overall process greenhouse gas emissions of an agricultural land system.
An electronic device comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors, the one or more programs comprising operating instructions for performing a method for predicting overall process greenhouse gas emissions of an agricultural land system.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (10)
1. The method for predicting the whole process greenhouse gas emission of the agricultural land system is characterized by comprising the following steps of:
step 1: presetting a gas emission model;
step 2: acquiring planting data of an agricultural land as a first emission factor, and acquiring topdressing measures for the agricultural land as a second emission factor;
step 3: and leading the first emission factor and the second emission factor into a gas emission model to obtain the predicted gas emission.
2. The method for predicting total process greenhouse gas emissions of an agricultural land system as recited in claim 1, further comprising the steps of:
step 4: extracting the predicted single-kind gas emission amount and the total emission amount respectively, and judging whether the single-kind gas emission amount exceeding a threshold value exists or not;
step 5: and under the condition that the emission amount of all the single-type gases does not exceed the threshold value, calculating the ratio of any single-type gases to the total emission amount to obtain the greenhouse gas emission ratio.
3. The method for predicting the total process greenhouse gas emissions of an agricultural land system according to claim 1, wherein said topdressing measures comprise habitual topdressing, real-time topdressing, precise topdressing, and disposable topdressing.
4. The method for predicting total process greenhouse gas emissions of an agricultural land system as recited in claim 1, wherein said planting data comprises a type of agricultural product planted on an agricultural land, a planting density of said agricultural product, and a growing node of said agricultural product.
5. The method for predicting total process greenhouse gas emissions in an agricultural land system as recited in claim 1, wherein the process of establishing the gas emission model comprises the steps of:
step 11: establishing a first-order emission model, and erasing offset of the first-order emission model based on the gray derivative to obtain a whitening function;
step 12: setting up a factor sequence as an analog quantity according to the first emission factor and the second emission factor to obtain a prediction model;
step 13: and based on the whitening function, performing whitening guidance on the prediction model by adopting a relevancy qualification model test to obtain a prediction gas emission model.
6. The method for predicting total process greenhouse gas emissions of an agricultural land system as recited in claim 5, wherein said relevancy pass model is a simulation sequence of a factor sequence.
7. A device for predicting the total process greenhouse gas emission of an agricultural land system, comprising the method for predicting the total process greenhouse gas emission of an agricultural land system according to any one of claims 1 to 6, comprising the following steps:
and the gas acquisition module is used for: the method is used for collecting planting data and topdressing measures of agricultural lands;
the calculation processing module: the gas emission prediction method comprises the steps of acquiring data by adopting a gas emission model and a gas acquisition module to obtain predicted gas emission;
the gas collection module is connected with the calculation processing module.
8. The method for predicting total process greenhouse gas emissions of an agricultural land system as claimed in claim 7, further comprising a gas detection module, an impurity filtration module,
and a gas detection module: the gas detection device is used for detecting emission of the collected data of the gas collection module to obtain a detection result;
impurity filtration module: the gas filtering device is used for filtering out particle impurities from the gas acquired by the gas acquisition module;
the gas collection module, the impurity filtering module, the gas detection module and the calculation processing module are sequentially connected.
9. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of a method for predicting overall process greenhouse gas emissions of an agricultural land system.
10. An electronic device comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by one or more processors with instructions included in the one or more programs for performing a method of predicting total process greenhouse gas emissions of a soft agricultural land system.
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