A method and system for constructing a model to measure the change in NEE of farmland caused by high temperature

Abstract

The present invention discloses a method and system for constructing a model for calculating the change in farmland NEE caused by high temperature in the technical field of meteorological and farmland carbon source and sink monitoring, including: dividing the research stage of the observed farmland, identifying high-temperature days and high-temperature events in different research stages, and constructing a corresponding high-temperature database; extracting the corresponding concurrent cases for each high-temperature day and high-temperature event, and taking the average value of the NEE of all concurrent cases of each high-temperature day and each high-temperature event as the final NEE value of the concurrent cases of this high-temperature day and this high-temperature event; comparing the NEE values of high-temperature days and high-temperature events with the final NEE values of their concurrent cases to determine the characterization forms of farmland high temperature in different research stages, and establishing a regression model for calculating the change in NEE caused by high temperature in different research stages according to the characterization forms of farmland high temperature. The present invention can realize the quantitative estimation of the change in farmland carbon source and sink caused by high temperature.

Description

Technical Field

[0001] The invention relates to a model construction method and system for measuring the NEE change of farmland caused by high temperature, and belongs to the technical field of meteorology and farmland carbon source and sink monitoring. Background Art

[0002] The high temperatures caused by global climate change are having a profound impact on agricultural production. Global warming has caused the expansion of high temperature events, which not only causes crop yield reduction and threatens food security, but also affects the carbon cycle process of farmland ecosystems. The farmland NEE (net ecosystem exchange) can generally be used to represent the carbon source and sink characteristics of farmland.

[0003] In previous technologies and research, the focus was mainly on measuring the changes in crop yields caused by extreme climate events, with less attention paid to the impact on farmland NEE. Although some studies have evaluated the interannual changes in farmland NEE at the growing season scale, there is currently a lack of research on the effects of extreme climate events on farmland NEE, especially the establishment of some quantitative relationships, which is not conducive to quantitatively evaluating the impact of climate change on farmland carbon sources and sinks. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a model construction method and system for measuring the change in NEE of farmland caused by high temperature, which can realize the quantitative estimation of the change in carbon source and sink of farmland caused by high temperature, and help understand the impact of climate change on carbon sequestration and emission reduction in farmland.

[0005] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0006] In a first aspect, the present invention provides a model construction method for calculating the change in NEE of farmland caused by high temperature, the method comprising:

[0007] Obtain daily NEE values ​​and meteorological data of observed farmland;

[0008] The observed farmland is divided into research stages in combination with the characteristics of the observed farmland ecosystem, and the high temperature days and high temperature events in each research stage are identified according to the meteorological data and the high temperature thresholds determined in different research stages, and a corresponding high temperature database is constructed;

[0009] Determine the cases corresponding to each high temperature day and each high temperature event, and calculate the NEE average of all cases corresponding to each high temperature day and each high temperature event based on the obtained daily NEE values;

[0010] The average NEE of all concurrent cases for each high-temperature day and the average NEE of all concurrent cases for each high-temperature event are respectively used as the final NEE values of the concurrent cases for that high-temperature day and that high-temperature event;

[0011] Compare the NEE values of high-temperature days and the NEE values of high-temperature events with the final NEE values of the corresponding concurrent cases respectively, and determine the characterization forms of farmland high temperatures in different research stages according to the comparison results;

[0012] Establish a regression model for calculating the change in NEE caused by high temperature in different research stages according to the characterization forms of farmland high temperatures;

[0013] Among them, the characterization forms of farmland high temperatures include being characterized by high-temperature days and being characterized by high-temperature events.

[0014] Combined with the first aspect, optionally, the meteorological data includes: daily maximum temperature, daily rainfall, daily net radiation, daily sunshine hours, and daily relative soil humidity.

[0015] Combined with the first aspect, optionally, the high-temperature database includes a high-temperature day database and a high-temperature event database;

[0016] The construction of the high-temperature database includes:

[0017] Identify the dates when the daily maximum temperature is higher than the high-temperature threshold of the corresponding research stage as high-temperature days, construct a high-temperature day data set based on the identified high-temperature days, and generate a high-temperature day database;

[0018] Identify consecutive high-temperature days in the same research stage as one high-temperature event, construct a high-temperature event data set based on the identified high-temperature events, and generate a high-temperature event database.

[0019] Combined with the first aspect, optionally, the high-temperature day database includes: the occurrence date of the high-temperature day, the farmland NEE value, the daily maximum temperature, rainfall, net radiation, sunshine hours, and relative soil humidity;

[0020] The high-temperature event database includes: the start and end dates of each high-temperature event and the corresponding daily farmland NEE values, daily maximum temperatures, daily rainfall, daily net radiation, daily sunshine hours, and daily relative soil humidity.

[0021] Combined with the first aspect, further, the determination of the concurrent cases corresponding to each high-temperature day and each high-temperature event includes:

[0022] Determine the occurrence date of the high-temperature day and the start and end dates of the high-temperature event;

[0023] Use the stage without high-temperature occurrence in the allowable deviation dates of the selected other years as the candidate concurrent case for that high-temperature day or high-temperature event;

[0024] Eliminate the candidate synchronous cases with abnormal NEE values, and use the remaining candidate synchronous cases as the final synchronous cases.

[0025] Combined with the first aspect, further, the determining the characterization form of farmland high temperature in different research stages according to the comparison results includes:

[0026] Use the paired-sample t-test method to analyze the differences between the NEE values of high-temperature days and the NEE values of high-temperature events and the final NEE values of their synchronous cases;

[0027] If there is one of the differences in the high-temperature days and high-temperature events that reaches the significance level, select the one with the difference reaching the significance level as the characterization form of farmland high temperature in this research stage;

[0028] If the differences in both the high-temperature days and high-temperature events reach the significance level, select the one with a smaller p-value of the t-test as the characterization form of farmland high temperature in this research stage;

[0029] If the differences in both the high-temperature days and high-temperature events do not reach the significance level, re-determine the high-temperature threshold for the corresponding research stage until there is at least one of the differences in the re-identified high-temperature days and re-identified high-temperature events in this research stage that reaches the significance level, so as to determine the characterization form of farmland high temperature in this research stage.

[0030] Combined with the first aspect, further, the establishing a regression model for calculating the change in NEE caused by high temperature in different research stages according to the characterization form of farmland high temperature includes:

[0031] If the characterization form of farmland high temperature is represented by high-temperature days, calculate the change in NEE between the NEE value of high-temperature days and the final NEE value of the corresponding synchronous cases, and construct a regression model of the change in NEE in different research stages with respect to the daily maximum temperature of high-temperature days;

[0032] If the characterization form of farmland high temperature is represented by high-temperature events, calculate the change in NEE between the NEE value of high-temperature events and the final NEE value of the corresponding synchronous cases, and construct a regression model of the change in NEE in different research stages with respect to the daily maximum temperature of high-temperature events.

[0033] Combined with the first aspect, further, after determining the characterization form of farmland high temperature in different research stages according to the comparison results, it further includes:

[0034] Determine the dry-wet state when high temperature occurs according to the rainfall data in the meteorological data;

[0035] Further classify high-temperature days and high-temperature events according to the dry-wet state.

[0036] In combination with the first aspect, optionally, the observed farmland includes a wheat-maize rotation farmland ecosystem.

[0037] In a second aspect, the present invention provides a model construction system for calculating the change in farmland NEE caused by high temperature, including:

[0038] An acquisition module: used to acquire the daily NEE values and meteorological data of the observed farmland;

[0039] A database construction module: used to divide the research stages of the observed farmland in combination with the characteristics of the observed farmland ecosystem, identify the high-temperature days and high-temperature events in each research stage according to the meteorological data and the high-temperature thresholds determined in different research stages, and construct a corresponding high-temperature database;

[0040] A calculation module: used to determine the corresponding concurrent cases for each high-temperature day and each high-temperature event, and calculate the average NEE of all concurrent cases for each high-temperature day and the average NEE of all concurrent cases for each high-temperature event respectively according to the acquired daily NEE values;

[0041] An NEE final value determination module: used to take the average NEE of all concurrent cases for each high-temperature day and the average NEE of all concurrent cases for each high-temperature event as the NEE final values of the concurrent cases for this high-temperature day and this high-temperature event respectively;

[0042] A characterization form determination module: used to compare the NEE values of high-temperature days and the NEE values of high-temperature events with the NEE final values of the corresponding concurrent cases respectively, and determine the characterization forms of farmland high temperature in different research stages according to the comparison results;

[0043] An establishment module: used to establish a regression model for calculating the change in NEE caused by high temperature in different research stages according to the characterization forms of farmland high temperature;

[0044] Among them, the characterization forms of farmland high temperature include characterization by high-temperature days and characterization by high-temperature events.

[0045] Compared with the prior art, the beneficial effects achieved by the present invention:

[0046] The present invention can integrate various information by acquiring daily NEE values ​​and meteorological data of observed farmland, laying a foundation for subsequent accurate analysis of the impact of high temperature on the NEE change of farmland; divide the observed farmland into research stages, and accurately identify high temperature days and high temperature events in different research stages to construct a high temperature database, which is helpful to focus on high temperature, a key influencing factor, and conduct targeted analysis on it; compare the NEE values ​​of high temperature days and high temperature events with the final NEE values ​​of cases in the same period, so as to determine whether the high temperature of farmland in different research stages is characterized in the form of high temperature days or high temperature events, so that the impact of high temperature on the NEE of farmland can be presented in an intuitive and clear manner, which is convenient for further in-depth understanding of the relationship between high temperature and NEE change; according to the determined representation form of high temperature in farmland, a regression model for calculating the NEE change caused by high temperature in different research stages is established, and the model can accurately reflect the quantitative relationship between high temperature factors and the NEE change of farmland based on the previous fine processing of data and the accurate characterization of the high temperature impact, and can be used to calculate the change of farmland NEE under different high temperature conditions, realize the quantitative estimation of the change of farmland carbon source sink caused by high temperature event process, and help understand the impact of climate change on farmland carbon sequestration and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of a model construction method for calculating the change of NEE of farmland caused by high temperature provided by an embodiment of the present invention;

[0048] Figure 2 is a schematic diagram of the observation farmland division research phase provided by an embodiment of the present invention;

[0049] Figure 3 It is the NEE value of all farmland with high temperature events and the NEE value of the cases in the same period in the first stage of the embodiment of the present invention;

[0050] Figure 4 It is the NEE value of all farmland with high temperature days and the NEE value of the cases in the same period in the second stage of the embodiment of the present invention;

[0051] Figure 5 It is the NEE value of all farmland with high temperature events and the NEE value of the cases in the same period in the third stage of the embodiment of the present invention;

[0052] Figure 6 is a linear regression model of the change in NEE with the daily maximum temperature of the high temperature event in the first stage of the embodiment of the present invention;

[0053] Figure 7 is a linear regression model of the change in NEE with the maximum temperature of the high temperature day in the second stage of the embodiment of the present invention;

[0054] Figure 8It is a linear regression model of the change in NEE during the third stage in the embodiments of the present invention with respect to the daily maximum temperature of high-temperature events. Detailed implementation manners

[0055] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific features in the embodiments of the present application and the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. Without conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0056] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0057] In the description of the present invention, if there is a description of "first" and "second", it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence relationship of the indicated technical features.

[0058] In the description of the present invention, the description with reference to terms such as "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic descriptions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0059] Embodiment 1

[0060] As Figure 1 shown, this embodiment provides a method for constructing a model for calculating the change in farmland NEE caused by high temperature, including:

[0061] Step 1: Obtain the daily NEE values and meteorological data of the observed farmland;

[0062] In some embodiments, the meteorological data may include: daily maximum temperature, daily rainfall, daily net radiation, daily sunshine hours, and daily soil relative humidity, where the soil relative humidity is the data at a soil depth of 0-10 cm. The daily NEE values and meteorological data can be obtained from the National Meteorological Information Center;

[0063] Step 2: Divide the observed farmland into research stages based on the characteristics of the observed farmland ecosystem, identify the high temperature days and high temperature events in each research stage based on the meteorological data and the high temperature thresholds determined in different research stages, and build a corresponding high temperature database;

[0064] Different observation farmlands generally have different characteristics. By dividing the observation farmlands into research stages and accurately identifying high temperature days and high temperature events in different research stages to build a high temperature database, it helps to focus on high temperature, a key influencing factor, and conduct targeted analysis on it.

[0065] The following is a further detailed explanation of the division of research stages using the wheat-maize rotation farmland ecosystem as an example:

[0066] The stage when high temperature may occur in the wheat-corn rotation farmland ecosystem is clarified, and further stage division is made according to the surface crop conditions at that stage. This is because the response of farmland ecosystem to high temperature stress varies when the surface vegetation conditions are different, and different thresholds should be used to identify high temperature. Therefore, combined with the characteristics of the wheat-corn rotation farmland ecosystem, the research period can be divided into three stages, namely: the first stage dominated by winter wheat photosynthesis, the second stage dominated by soil respiration, and the third stage dominated by summer corn photosynthesis.

[0067] Specifically, the high temperature thresholds for each research stage can be determined by consulting literature and historical data.

[0068] The meteorological data obtained through step 1 can determine the daily maximum temperature. Therefore, the dates when the maximum temperature of the day is higher than the high temperature threshold can be identified as high temperature days, and a high temperature day database can be constructed based on the high temperature day data set; consecutive high temperature days are identified as a high temperature event, and accordingly, a high temperature event database can be constructed based on the high temperature event data set.

[0069] As an embodiment, the information contained in the high temperature day database may include: the date of occurrence of the high temperature day, the farmland NEE value, the daily maximum temperature, rainfall, net radiation, sunshine hours and soil relative humidity. The information contained in the high temperature event database may include: the start and end dates of each high temperature event and the corresponding daily farmland NEE value, daily maximum temperature, daily rainfall, daily net radiation, daily sunshine hours and daily soil relative humidity.

[0070] Step 3: Determine the cases corresponding to each high temperature day and each high temperature event, and calculate the NEE average of all cases corresponding to each high temperature day and each high temperature event according to the obtained daily NEE values; the NEE average of all cases corresponding to each high temperature day and the NEE average of all cases corresponding to each high temperature event are used as the final NEE values ​​of the high temperature day and the cases corresponding to the high temperature event respectively;

[0071] Due to the different crop development processes between different dates, there are significant differences in the farmland NEE values between different dates. Therefore, the difference between the NEE values of high-temperature days and high-temperature events and the NEE values of their corresponding cases during the same period reflects the change in NEE values brought about by high temperature, and the influence brought about by the crop development process can be eliminated.

[0072] When determining the corresponding cases during the same period, first, the occurrence date of the high-temperature day and the start and end dates of the high-temperature event should be determined; the stage without high-temperature occurrence in the allowable deviation dates of other selected years is used as the candidate corresponding case for this high-temperature day or high-temperature event. In this embodiment, for high-temperature days, the allowable deviation dates can be determined as the dates within three days of the occurrence date in other selected years. For high-temperature events, the allowable deviation dates can be determined as the dates within three days of the start date of the high-temperature event in other selected years.

[0073] To eliminate the possible influence on NEE values caused by other factors other than high temperature, candidate corresponding cases with abnormal NEE values can be excluded, and the remaining candidate corresponding cases are used as the final corresponding cases. Optionally, the situations of NEE anomalies caused by factors such as rainfall, net radiation, sunshine hours, and soil relative humidity can be excluded, so that the difference between the NEE values of high-temperature days and high-temperature events and the NEE values of their corresponding cases is mainly brought about by high temperature, rather than other factors.

[0074] Step 4: Compare the NEE values of high-temperature days and the NEE values of high-temperature events with the final NEE values of their corresponding cases respectively, and determine the characterization forms of farmland high temperature in different research stages according to the comparison results; among them, the characterization forms of farmland high temperature include being characterized by high-temperature days and being characterized by high-temperature events;

[0075] In some embodiments, Step 4 specifically includes:

[0076] Use the paired-sample t-test method to analyze whether the difference between the NEE values of high-temperature days and high-temperature events and the final NEE values of their corresponding cases reaches the significance level; in this embodiment, if the p-value of the t-test is less than 0.05, it indicates that the significant level is reached.

[0077] If there is one of the differences in high-temperature days and high-temperature events that reaches the significance level, select the one with the difference reaching the significance level as the characterization form of farmland high temperature in this research stage;

[0078] If the differences in both high-temperature days and high-temperature events reach the significance level, it indicates that there are significant differences in high temperature in both characterization forms, which means that high temperature in both characterization forms has a significant impact on farmland NEE. Then select the one with a smaller p-value of the t-test as the characterization form of farmland high temperature in this research stage;

[0079] If neither of the differences described in the high-temperature days and high-temperature events reaches the significance level, that is, the p-values are both greater than 0.05, it indicates that the differences in high temperature between the two representation forms are not significant. This shows that the high temperature in both representation forms has no significant effect on the farmland NEE. Then, re-determine the high-temperature threshold for the corresponding research stage until at least one of the differences in the re-identified high-temperature days and re-identified high-temperature events in this research stage reaches the significance level, so as to determine the representation form of farmland high temperature in this research stage.

[0080] It should be understood that if the high-temperature threshold for the corresponding research stage is re-determined, then the identification of the corresponding high-temperature days and high-temperature events, the construction of the high-temperature database, the concurrent cases, and the final NEE values of the concurrent cases also need to be re-determined.

[0081] Step 5: Establish a regression model for calculating the change in NEE caused by high temperature in different research stages according to the representation form of farmland high temperature;

[0082] Continuing with the winter wheat-summer maize rotation farmland ecosystem as an example, the regression models include: the regression model of the change in NEE in the first stage mainly dominated by winter wheat photosynthesis with the daily maximum temperature of high-temperature days or high-temperature events (determined according to the determined representation form), the regression model of the change in NEE in the second stage mainly dominated by soil respiration with the daily maximum temperature of high-temperature days or high-temperature events (determined according to the determined representation form), and the regression model of the change in NEE in the third stage mainly dominated by summer maize photosynthesis with the daily maximum temperature of high-temperature days or high-temperature events (determined according to the determined representation form).

[0083] In some embodiments, after determining the representation form of farmland high temperature in different research stages, it further includes:

[0084] Determine the dry-wet state when high temperature occurs according to the rainfall data;

[0085] Further classify the high-temperature days and high-temperature events according to the dry-wet state;

[0086] Further classifying the high-temperature days and high-temperature events according to the dry-wet state can be used to study whether there are differences in the impact of high temperature on farmland NEE under different dry-wet conditions.

[0087] The following further illustrates the method provided in the embodiments of the present invention in combination with application examples, and further verifies the technical effects produced by the method provided in the embodiments of the present invention:

[0088] Taking a certain county as an example, a method for constructing a model for calculating the change in farmland NEE caused by high temperature is provided. Among them, the observed farmland is selected as the winter wheat-summer maize rotation farmland, and the specific steps are as follows:

[0089] Obtain the daily NEE values and meteorological data of the observed farmland: In this application example, the daily NEE values of the farmland in the county from 2007 to 2018, the daily maximum temperature, the daily rainfall, the daily net radiation, the daily sunshine hours, and the daily soil relative humidity data at a soil depth of 0 - 10 cm were specifically collected.

[0090] Identify the stages when high temperatures may occur in the wheat - maize rotation farmland ecosystem: High temperatures in the area where the county is located mainly occur in the summer half - year. Therefore, the summer half - year is taken as the research stage. Since the response of the farmland ecosystem to high - temperature stress varies when the surface vegetation conditions are different, different thresholds should be used to identify high temperatures. So, as Figure 2 shown, combined with the characteristics of the wheat - maize rotation farmland ecosystem in the county, the research stage can be further divided into three stages: The first stage from March 22 to May 27 is dominated by the photosynthesis of winter wheat, the second stage from June 3 to June 30 is dominated by soil respiration, and the third stage from July 15 to September 20 is dominated by the photosynthesis of summer maize.

[0091] Determine the high - temperature thresholds in the three stages of the county as 30°C, 35°C, and 35°C by referring to literature and historical data; accordingly, from 2007 to 2018, a total of 93 high - temperature days and 13 high - temperature events were identified in the first stage; a total of 77 high - temperature days and 12 high - temperature events were identified in the second stage; and a total of 51 high - temperature days and 13 high - temperature events were identified in the third stage.

[0092] Extract the corresponding concurrent cases for each high - temperature day and each high - temperature event, and obtain the average NEE of all concurrent cases for each high - temperature day and each high - temperature event as the final NEE value of the concurrent cases for that high - temperature day and that high - temperature event.

[0093] Compare the NEE values of high - temperature days and high - temperature events with the final NEE values of their respective concurrent cases to determine whether high temperatures in farmland are characterized by high - temperature days or high - temperature events in different research stages:

[0094] In the first stage, the results of the paired - sample t - test show that there is a significant difference between the NEE values of farmland for high - temperature events and those of their concurrent cases, with t = 6.78 and p < 0.001, meeting p < 0.05, while there is no significant difference in the characterization form of high - temperature days. This indicates that high temperatures in this stage should be characterized by high - temperature events to study the impact on farmland NEE.

[0095] As Figure 3As shown in the figure, the NEE values ​​of farmland in high temperature events are greater than those in the same period, with average values ​​of -5.64gC / m² / d and -7.64gC / m² / d, respectively. That is, high temperature caused a significant increase in the NEE value of farmland, which may be attributed to the fact that high temperature has inhibited the photosynthesis of winter wheat to a certain extent. In addition, the impact of high temperature on the NEE value of farmland varies under different dry and wet conditions: under drought conditions, the average NEE value of farmland in high temperature events is -5.34gC / m² / d, while under wet conditions, the average NEE value of farmland in high temperature events is -7.31gC / m² / d. That is, high temperature inhibits photosynthesis more strongly under drought conditions.

[0096] In the second stage, the results of the paired sample t-test showed that only the NEE value of farmland on high temperature days was significantly different from the NEE value of cases in the same period, with t=3.46, p<0.001, satisfying p<0.05, while there was no significant difference in the form of high temperature events, indicating that high temperature should be characterized in the form of high temperature days in this stage to study its impact on farmland NEE.

[0097] like Figure 4 As shown in the figure, the NEE values ​​of farmland on most high-temperature days are greater than those of the cases in the same period, with average values ​​of 3.41gC / m² / d and 2.78gC / m² / d, respectively. That is, high temperature caused a significant increase in the NEE value of farmland, which may be attributed to the fact that high temperature promoted soil respiration to a certain extent. In addition, the impact of high temperature on the NEE value of farmland varies under different dry and wet conditions: the average values ​​of the NEE values ​​of farmland on high-temperature days under drought, normal and wet conditions are 3.09gC / m² / d, 3.48gC / m² / d and 3.8gC / m² / d, respectively.

[0098] In the third stage, the results of the paired sample t-test showed that only the NEE value of farmland during the high temperature event was significantly different from the NEE value of the cases during the same period, with t=7.41, p<0.001, satisfying p<0.05, while there was no significant difference in the form of high temperature days, indicating that high temperature should be characterized in the form of high temperature events in this stage to study its impact on farmland NEE.

[0099] like Figure 5 As shown in the figure, the NEE of farmland in high temperature events is greater than that of the cases in the same period, with average values ​​of -7.15gC / m² / d and -8.87gC / m² / d, respectively. That is, high temperature caused a significant increase in the NEE value of farmland, which may be attributed to the fact that high temperature has a certain degree of inhibition on the photosynthesis of summer corn. In addition, the impact of high temperature on the NEE value of farmland in this stage is not significantly different under different dry and wet conditions. Under dry and wet conditions, the average NEE values ​​of farmland in high temperature events are -7.11gC / m² / d and -7.18gC / m² / d, respectively.

[0100] According to the representation form of high temperature in farmland, a regression model for calculating the change of NEE caused by high temperature in different research stages is established, including calculating the change of NEE of high temperature day or high temperature event and the NEE of the case in the same period, and constructing a regression model for the change of NEE in different research stages with the change of the daily maximum temperature of high temperature day or high temperature event:

[0101] In the first stage, if Figure 6 As shown in Figure 2, the linear regression equation of the farmland NEE change y caused by the high temperature event and the maximum temperature x on the event day is y=0.5372x-15.42, where R 2 =0.2921. During a high temperature event, the higher the daily maximum temperature, the greater the change in NEE. For every 1°C increase in temperature, NEE increases by 0.5372 gC / m² / d.

[0102] In addition, the variation of NEE with the daily maximum temperature of high temperature events varies under different dry and wet conditions: under drought conditions, the equation for the variation of NEE with the daily maximum temperature is y=0.5779x-16.47, where R 2 =0.5224, reaching the 0.05 significance level, and the average change was 2.25gC / m² / d. The average change of NEE under humid conditions was 0.59gC / m² / d.

[0103] In the second stage, if Figure 7 As shown in Figure 2, the linear regression equation of the farmland NEE change y caused by the high temperature day and the daily maximum temperature x of the high temperature day is y=-0.1160x-4.93, where R 2 =0.0147. As can be seen from the figure, the increase in daily maximum temperature has no significant effect on the change in NEE.

[0104] In addition, the change of NEE with the change of the maximum daily temperature on hot days has certain differences under different dry and wet conditions: the average values ​​of NEE change under drought, normal and wet conditions are 0.29gC / m² / d, 0.73gC / m² / d and 0.91gC / m² / d, respectively.

[0105] In the third stage, if Figure 8 As shown in the figure, the linear regression equation of the farmland NEE change y caused by the high temperature event and the maximum temperature x on the event day is y=0.8317x-28.4, where p<0.05, R 2 =0.384. During the high temperature event, the higher the daily maximum temperature, the greater the change in NEE. For every 1°C increase, NEE increases by 0.8317 gC / m² / d.

[0106] In addition, there are certain differences in the change of NEE with the daily maximum temperature of high-temperature events under different dry-wet conditions: the average value of the change in NEE under drought conditions is 2.16 gC / m² / d, while the average value of the change in NEE under wet conditions is 1.44 gC / m² / d.

[0107] Integrate the linear regression equations of the three research stages to obtain a regression model for the change in farmland NEE caused by high temperature.

[0108] In summary, calculating the change in NEE of the wheat-maize rotation farmland ecosystem in this county from 2007 to 2018 based on historical concurrent cases provides a method for constructing a model to measure the change in farmland NEE caused by high temperature. The model for measuring the change in farmland NEE caused by high temperature can achieve a quantitative estimation of the change in farmland carbon source and sink caused by high temperature, and help understand the impact of climate change on farmland carbon sequestration and emission reduction.

[0109] Example Two

[0110] This example provides a model construction system for measuring the change in farmland NEE caused by high temperature, including:

[0111] An acquisition module: used to acquire the daily NEE values and meteorological data of the observed farmland;

[0112] A database construction module: used to divide the research stages of the observed farmland in combination with the characteristics of the observed farmland ecosystem, and identify the high-temperature days and high-temperature events in each research stage according to the meteorological data and the high-temperature thresholds determined in different research stages, and construct a corresponding high-temperature database;

[0113] A calculation module: used to determine the concurrent cases corresponding to each high-temperature day and each high-temperature event, and calculate the average NEE of all concurrent cases of each high-temperature day and the average NEE of all concurrent cases of each high-temperature event respectively according to the acquired daily NEE values;

[0114] An NEE final value determination module: used to take the average NEE of all concurrent cases of each high-temperature day and the average NEE of all concurrent cases of each high-temperature event as the final NEE values of the concurrent cases of this high-temperature day and this high-temperature event respectively;

[0115] A characterization form determination module: used to compare the NEE values of high-temperature days and the NEE values of high-temperature events with the final NEE values of the corresponding concurrent cases respectively, and determine the characterization forms of farmland high temperature in different research stages according to the comparison results;

[0116] A construction module: used to establish a regression model for measuring the change in NEE caused by high temperature in different research stages according to the characterization forms of farmland high temperature;

[0117] Among them, the characterization forms of high temperature in farmland include being characterized by high temperature days and high temperature events.

[0118] The model construction system for calculating the change amount of farmland NEE caused by high temperature provided by the embodiments of the present invention can implement the model construction method for calculating the change amount of farmland NEE caused by high temperature provided by Embodiment 1 of the present invention, and has functional modules and beneficial effects corresponding to the execution of the method.

[0119] Embodiment 3

[0120] The embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it first implements the steps of the method in Embodiment 1 above.

[0121] The computer-readable storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0122] Those skilled in the art should understand that the embodiments of the present application can provide methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0123] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0124] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including instruction means, and the instruction means implement the functions in Figure 1 one process or multiple processes and / or blocksFigure 1 The functions specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 process or more processes and / or boxes Figure 1 or more boxes.

[0126] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A model construction method for measuring the change in NEE of farmland caused by high temperature, characterized in that: The method comprises: Obtain daily NEE values ​​and meteorological data of observed farmland; The observed farmland is divided into research stages in combination with the characteristics of the observed farmland ecosystem, and the high temperature days and high temperature events in each research stage are identified according to the meteorological data and the high temperature thresholds determined in different research stages, and a corresponding high temperature database is constructed; Determine the cases corresponding to each high temperature day and each high temperature event, and calculate the NEE average of all cases corresponding to each high temperature day and each high temperature event based on the obtained daily NEE values; The average NEE value of all cases in the same period of each high temperature day and the average NEE value of all cases in the same period of each high temperature event are taken as the final NEE value of the high temperature day and the cases in the same period of the high temperature event, respectively; The NEE values ​​of high temperature days and high temperature events were compared with the final NEE values ​​of the corresponding cases in the same period, and the representation forms of high temperature in farmland at different research stages were determined based on the comparison results; According to the representation form of high temperature in farmland, a regression model was established to estimate the change of NEE caused by high temperature at different research stages; Among them, the representation forms of high temperature in farmland include high temperature day representation and high temperature event representation; The regression model for calculating the change of NEE caused by high temperature at different research stages is established according to the representation form of high temperature in farmland, including: If the representation form of high temperature in farmland is represented by high temperature days, the NEE change between the NEE value of high temperature days and the final NEE value of the corresponding cases in the same period is calculated, and a regression model of the change of NEE at different research stages with the change of the daily maximum temperature of high temperature days is constructed; If the representation form of high temperature in farmland is represented by high temperature events, the NEE change between the NEE value of the high temperature event and the final NEE value of the corresponding case in the same period is calculated, and a regression model of the change of NEE at different research stages with the daily maximum temperature of the high temperature event is constructed; The determination of the cases corresponding to each high temperature day and each high temperature event includes: Determine the occurrence date of high temperature days and the start and end dates of high temperature events; The phases without high temperature occurrence in the allowed deviation dates in other selected years are taken as candidate concurrent cases of the high temperature day or high temperature event; Eliminate candidate concurrent cases with abnormal NEE values, and use the remaining candidate concurrent cases as the final concurrent cases; The characterization forms of high temperature in farmland at different research stages are determined according to the comparison results, including: Paired sample t-test was used to analyze the differences between the NEE values ​​of high temperature days and the NEE values ​​of high temperature events and their final NEE values ​​of the same period cases; If there is a difference between the high temperature day and the high temperature event that reaches the significance level, then the one with the significant difference is selected as the representation form of high temperature in the farmland during the research stage; If the differences in high temperature days and high temperature events both reach a significant level, the one with a smaller p-value in the t-test will be selected as the representation form of high temperature in farmland during this research period; If the differences in high temperature days and high temperature events do not reach the significance level, the high temperature threshold of the corresponding research stage will be re-determined until at least one of the differences in the re-identified high temperature days and re-identified high temperature events in this research stage reaches the significance level, thereby determining the characterization form of high temperature in farmland in this research stage.

2. The model construction method for calculating the change in NEE of farmland caused by high temperature according to claim 1, characterized in that: The meteorological data include: daily maximum temperature, daily rainfall, daily net radiation, daily sunshine hours and daily soil relative humidity.

3. The model construction method for calculating the change in NEE of farmland caused by high temperature according to claim 1, characterized in that: The high temperature database includes a high temperature day database and a high temperature event database; The construction of the corresponding high temperature database includes: The days with the highest temperature higher than the high temperature threshold of the corresponding research stage are identified as high temperature days, and a high temperature day data set is constructed based on the identified high temperature days to generate a high temperature day database; Consecutive high temperature days in the same research phase are identified as a high temperature event. A high temperature event data set is constructed based on the identified high temperature events to generate a high temperature event database.

4. The model construction method for calculating the change of NEE of farmland caused by high temperature according to claim 3, characterized in that: The high temperature day database includes: the occurrence date of the high temperature day, the NEE value of the farmland, the daily maximum temperature, the rainfall, the net radiation, the sunshine hours and the relative humidity of the soil; The high temperature event database includes: the start and end dates of each high temperature event and the corresponding daily farmland NEE value, daily maximum temperature, daily rainfall, daily net radiation, daily sunshine hours and daily soil relative humidity.

5. The model construction method for calculating the change of NEE of farmland caused by high temperature according to claim 1, characterized in that: After determining the representation forms of high temperature in farmland at different research stages according to the comparison results, the method further includes: Determine the dry and wet conditions when high temperatures occur based on the rainfall data in the meteorological data; High temperature days and high temperature events are further classified according to dry and wet conditions.

6. The model construction method for calculating the change of NEE of farmland caused by high temperature according to any one of claims 1 to 5, characterized in that: The observed farmland includes a wheat-corn rotation farmland ecosystem.

7. A model construction system for measuring the change in NEE of farmland caused by high temperature, characterized in that: include: Acquisition module: used to obtain daily NEE values ​​and meteorological data of observed farmland; Database construction module: used to divide the observed farmland into research stages in combination with the characteristics of the observed farmland ecosystem, and to identify high temperature days and high temperature events in each research stage according to the meteorological data and the high temperature thresholds determined in different research stages, and to construct a corresponding high temperature database; Calculation module: used to determine the cases corresponding to each high temperature day and each high temperature event, and calculate the NEE average of all cases corresponding to each high temperature day and the NEE average of all cases corresponding to each high temperature event according to the obtained daily NEE values; NEE final value determination module: used to take the NEE average value of all cases in the same period of each high temperature day and the NEE average value of all cases in the same period of each high temperature event as the NEE final value of the high temperature day and the high temperature event respectively; Representation form determination module: used to compare the NEE values ​​of high temperature days and high temperature events with the final NEE values ​​of the corresponding cases in the same period, and determine the representation forms of high temperature in farmland at different research stages according to the comparison results; Establishment module: used to establish a regression model for calculating the change of NEE caused by high temperature at different research stages according to the representation form of high temperature in farmland; Among them, the representation forms of high temperature in farmland include high temperature day representation and high temperature event representation; The regression model for calculating the change of NEE caused by high temperature at different research stages is established according to the representation form of high temperature in farmland, including: If the representation form of high temperature in farmland is represented by high temperature days, the NEE change between the NEE value of high temperature days and the final NEE value of the corresponding cases in the same period is calculated, and a regression model of the change of NEE at different research stages with the change of the daily maximum temperature of high temperature days is constructed; If the representation form of high temperature in farmland is represented by high temperature events, the NEE change between the NEE value of the high temperature event and the final NEE value of the corresponding case in the same period is calculated, and a regression model of the change of NEE at different research stages with the daily maximum temperature of the high temperature event is constructed; The determination of the cases corresponding to each high temperature day and each high temperature event includes: Determine the occurrence date of high temperature days and the start and end dates of high temperature events; The phases without high temperature occurrence in the allowed deviation dates in other selected years are taken as candidate concurrent cases of the high temperature day or high temperature event; Eliminate candidate concurrent cases with abnormal NEE values, and use the remaining candidate concurrent cases as the final concurrent cases; The characterization forms of high temperature in farmland at different research stages are determined according to the comparison results, including: Paired sample t-test was used to analyze the differences between the NEE values ​​of high temperature days and the NEE values ​​of high temperature events and their final NEE values ​​of the same period cases; If there is a difference between the high temperature day and the high temperature event that reaches the significance level, then the one with the significant difference is selected as the representation form of high temperature in the farmland during the research stage; If the differences in high temperature days and high temperature events both reach a significant level, the one with a smaller p-value in the t-test will be selected as the representation form of high temperature in farmland during this research period; If the differences in high temperature days and high temperature events do not reach the significance level, the high temperature threshold of the corresponding research stage will be re-determined until at least one of the differences in the re-identified high temperature days and re-identified high temperature events in this research stage reaches the significance level, thereby determining the characterization form of high temperature in farmland in this research stage.

Images