CN114169161A

CN114169161A - Method and system for estimating space-time variation and carbon sequestration potential of soil organic carbon

Info

Publication number: CN114169161A
Application number: CN202111465630.2A
Authority: CN
Inventors: 宋丹; 马跃; 王吉磊; 杨宁; 董旭; 李眷
Original assignee: Liaoning Agricultural Development Service Center
Current assignee: Liaoning Agricultural Development Service Center
Priority date: 2021-12-02
Filing date: 2021-12-02
Publication date: 2022-03-11

Abstract

The application discloses a method and a system for estimating space-time variation and carbon sequestration potential of soil organic carbon, wherein the method comprises the following steps: collecting a plurality of times of soil general survey data in a predetermined area; establishing a half variance function theoretical model, wherein the half variance function theoretical model is used for reflecting the space-time variation of the organic carbon content; acquiring the organic carbon density and reserve change data of each soil census data; establishing an organic carbon balance model of soil census data; and obtaining the estimation data of the soil organic carbon space-time variation and the carbon sequestration potential according to the half-variance function theoretical model, the organic carbon density and reserve variation data and the organic carbon balance model, and finishing the estimation of the soil organic carbon space-time variation and the carbon sequestration potential. The method and the device can accurately find out the soil fertility space-time distribution rule, accurately evaluate the soil carbon sequestration potential, and lay a theoretical foundation for soil conservation and sustainable efficient utilization.

Description

Method and system for estimating space-time variation and carbon sequestration potential of soil organic carbon

Technical Field

The application belongs to the technical field of soil census, and particularly relates to a method and a system for estimating soil organic carbon space-time variation and carbon sequestration potential.

Background

In recent years, the potential of soil carbon fixation becomes a hotspot and a difficulty of scientific research of countries all over the world. The carbon sequestration potential refers to the saturation capacity of soil carbon or the maximum capacity of the soil to hold carbon, that is, the quantity of organic carbon which can be reached by soil organic carbon and is in a relative equilibrium state after artificial fertilization (application of organic fertilizer and the like) under certain climatic conditions (mainly temperature and precipitation).

Arable land is considered an important part of the entire land system in the research of IPCC global climate change because it is a good mitigation of carbon emissions. The implementation of different carbon sequestration technologies has certain differences in the effects and potentials of soil carbon sequestration. Different soil types have great influence on the carbon sequestration potential of soil, and generally, the soil with higher organic carbon content has smaller collection potential and slow increase of the collection rate. The duration problem of the carbon sequestration potential of farmland soil is also researched, and generally, the carbon sequestration rate of the soil under the carbon sequestration technology is considered to be in a nonlinear growth mode, the carbon sequestration rate is greatly influenced by the persistence of measure implementation, and the discontinuous implementation rate is smaller than that of continuous implementation. In recent years, China also develops researches on the carbon sequestration potential of farmland soil successively, and based on long-term test data, the carbon sequestration effect can be realized by applying chemical fertilizers, no tillage and returning straws to fields.

Researchers began studying the carbon sequestration capacity of soils as early as the nineties of the twentieth century, but many studies were conducted based on the amount of carbon lost, or based on experimentation. Although the research on the aspect is more and more intensive, a complete, accurate and effective soil carbon sequestration potential estimation method is still not formed.

Disclosure of Invention

The application provides a method and a system for estimating soil organic carbon space-time variation and carbon sequestration potential, an optimal half variance function theoretical model is established by means of a geostatistical Mallon regional variable theory and a half variance function theory, the change characteristics of the soil organic carbon content are contrastively researched, natural factors and human factors which can influence the organic carbon content are researched by utilizing statistical methods such as multiple regression and the like, so that a set of complete, accurate and effective soil carbon sequestration potential estimation method is formed, and a theoretical basis is laid for soil conservation and sustainable efficient utilization.

In order to achieve the above purpose, the present application provides the following solutions:

a method for estimating space-time variation and carbon sequestration potential of soil organic carbon comprises the following steps:

collecting a plurality of times of soil general survey data in a predetermined area;

establishing a half variance function theoretical model, wherein the half variance function theoretical model is used for reflecting the space-time variation of the organic carbon content;

acquiring the organic carbon density and reserve change data of the soil census data each time;

establishing an organic carbon balance model of the soil census data;

and obtaining the estimation data of the soil organic carbon space-time variation and the carbon sequestration potential according to the semivariance function theoretical model, the organic carbon density and reserve variation data and the organic carbon balance model, and finishing the estimation of the soil organic carbon space-time variation and the carbon sequestration potential.

Optionally, the soil census data includes organic carbon treatment at high and medium fertilizer levels, temperature, precipitation, clay content and pH value at different periods.

Optionally, the half-variance theoretical function model is

Optionally, the method for obtaining the organic carbon density and reserve change data includes:

respectively acquiring the organic carbon density and the reserve volume of each soil general survey through each soil general survey data;

and comparing the density and the reserve of the organic carbon of a plurality of times of soil general investigation to obtain the density and reserve change data of the organic carbon.

Optionally, the organic carbon density is calculated by

SOC_i＝C_iD_iE_i(1-G_i)/100。

Optionally, the calculation method of the reserve amount is

And obtaining the reserve of the organic carbon by multiplying the density of the organic carbon by the area of the land where the organic carbon is located.

Optionally, the organic carbon equilibrium model is

SOCp＝140.5×e^-0.021×MT－98.8×e^-0.42×MP－39.6×e^-0.1×CL－4.1×pH^-27.7。

Optionally, a farmland soil carbon sequestration potential statistical model is used to obtain the carbon sequestration potential estimation data.

The application also discloses a soil organic carbon space-time variation and fixed carbon potential estimation system, which comprises a data acquisition module, a half variance function module, an organic carbon variation module, an organic carbon balance module and an estimation analysis module;

the data acquisition module is used for acquiring a plurality of times of soil general survey data in a preset area;

the half variance function module is used for establishing a half variance function theoretical model, and the half variance function theoretical model is used for reflecting the space-time variation of the organic carbon content;

the organic carbon change module is used for acquiring organic carbon density and reserve change data of the soil census data every time;

the organic carbon balance module is used for establishing an organic carbon balance model of the soil census data, and the organic carbon balance model is used for reflecting the relation among organic carbon reserves, temperature, precipitation, clay content and pH values of high and medium fertilizer levels in different periods;

and the estimation analysis module is used for obtaining the estimation data of the space-time variation and the carbon sequestration potential of the organic carbon of the soil according to the evolution and the space variation of the organic carbon content, the variation data of the density and the reserve of the organic carbon and the organic carbon balance model.

The beneficial effect of this application does:

the application discloses a method and a system for estimating soil organic carbon space-time variation and carbon sequestration potential, which can accurately find out soil fertility space-time distribution rules, accurately evaluate soil carbon sequestration potential and carbon sequestration potential distribution, and lay a theoretical foundation for soil conservation and sustainable efficient utilization.

Drawings

In order to more clearly illustrate the technical solution of the present application, the drawings needed to be used in the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive exercise.

FIG. 1 is a schematic flow chart of a method for estimating soil organic carbon spatio-temporal variation and carbon sequestration potential according to an embodiment of the present disclosure;

FIG. 2 is a schematic diagram of the spatial distribution of the organic carbon content in the farmland soil in 1980 according to the first embodiment of the present application;

fig. 3 is a schematic view of the spatial distribution of the organic carbon content in the farmland soil in 2017 in the first embodiment of the application;

FIG. 4 is a semivariogram of soil organic carbon in 1980 and an exponential model fitting diagram according to the first embodiment of the present application;

FIG. 5 is a graph of the half-variance of the soil organic carbon in 2017 according to the first embodiment of the present application and an exponential model fitting;

FIG. 6 is a schematic diagram of the organic carbon density growth potential of example one of the present application;

FIG. 7 is a schematic view of a saturated organic carbon storage according to the first embodiment of the present application;

FIG. 8 is a schematic diagram of a saturated organic carbon density (SOCp) according to a first embodiment of the present application;

FIG. 9 is a schematic diagram of the potential for increasing organic carbon reserves in soil according to the first embodiment of the present application;

FIG. 10 is a drawing of a Liaoning dryland area according to a first embodiment of the present application;

fig. 11 is a schematic structural diagram of a soil organic carbon spatio-temporal variation and carbon sequestration potential estimation system according to a second embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.

Example one

As shown in fig. 1, a general flow diagram of a method for estimating soil organic carbon temporal-spatial variation and carbon sequestration potential according to an embodiment of the present application is shown, where a temporal-spatial variation situation of soil organic carbon content and density in a land of the Liaohe plain is taken as an example, technical statistics and soil science are taken as theoretical guidance as a whole, a geographic information technology is used, a field sample point supplementary test is adopted, and a method of existing digital information is combined, and the method mainly includes the following steps:

(1) an optimal half variance function theoretical model is established by means of a geostatistical Mallodon regionalization variable theory and a half variance function theory, the change characteristics of the organic carbon content of soil in the Liaohe plain farmland in the last 30 years (1980) -2010) are contrastingly researched, a space analysis method and a half variance function in geostatistical are applied to the change characteristics, and the differences of the space distribution of the change characteristics in different periods are analyzed and summarized.

(2) The organic carbon content of the plough layer soil, the annual average temperature, the annual average rainfall, the land utilization type, the clay content smaller than 0.002mm, the pH value, the gradient grade and the like are selected as data sets of the research. And (3) researching natural factors and human factors which can influence the organic carbon content by utilizing statistical methods such as multiple regression and the like, thereby determining the factors which can influence the organic carbon content of the cultivated land soil in the research area.

(3) Establishing a digital ground model with soil organic carbon density as attribute in 80 years by spatial interpolation based on secondary soil general survey data, and reflecting the spatial distribution characteristic of the carbon reserves in 80 years by data conversion, superposition and dispersion among a soil map, a land utilization map and a gradient map; and (3) building a basic database by combining the soil evaluation digital information of the farmland in the recent (2010) with the sample point data supplementary test, overlapping the basic database with a soil map, estimating according to the soil map information, and calculating the current situation and the distribution condition of the carbon reserve of the soil.

(4) And estimating the carbon sequestration potential of the farmland soil in Liaohe plain by utilizing a statistical model of the carbon sequestration potential of the farmland soil in the prior art.

According to the technical key points of the application, a method and a basis can be provided for recognizing the soil carbon sequestration potential of the regional cultivated land, evaluating the soil carbon sequestration capacity of the regional cultivated land and the soil carbon sequestration and emission reduction potential of the regional cultivated land, and reference is provided for formulating reasonable carbon management measures.

The main processes and methods of the present embodiment are described in detail below:

first, data acquisition

The carbon content in the soil is influenced by many factors, not only by the topography and climate, by the plants on the soil, but also by its properties and by the use of land. Therefore, we need to take these factors into account when calculating the carbon content, and not only need spatial data, but also need attribute data. Most data is not readily available because of the large amount of data. Therefore, we use the function of GIS to collect the required data. And complex data acquisition is realized by a map digitalization method.

When the carbon content of the soil is calculated, a lot of data are needed, and if the number of the data is not reached, deviation is easy to occur in the calculation, so that expected accuracy cannot be obtained. But for large amounts of data it is very difficult to manage them well. If the management is improper, a large amount of time is wasted for preparing the data, so a GIS database needs to be established, and the data management is realized.

In the aspect of spatial analysis, GIS can be used for analyzing the space, and the GIS has the functions of overlapping the space and then analyzing, building a digital model and then analyzing, and simultaneously has the function of interpolation. The so-called overlay analysis is to overlay two or more map elements, and after this operation, a new element layer appears, which is expressed in a manner that the original element is decomposed into new elements, and the layers of the original elements are comprehensively embodied in the newly generated elements. The map space relative association and the multi-layer attribute characteristics of the space region can be created by superposition analysis, the former is called space statistical accumulation, the former is used for purifying the number characteristics of some special contents in a region range, and the latter is called space synthesis superposition research, the latter is used for searching some regions, the geographic attributes of the regions are several, or the classification research is carried out on a plurality of characteristic attributes caused by superposition. Since there is a factor related to the organic carbon inventory in the soil, the first embodiment uses the spatial synthesis superposition method to obtain the organic carbon inventory in the soil.

The digital terrestrial model DTM (D191 talterrainenmodel) is a digital representation of the continuous terrestrial using a large selection of known (x, y, z) coordinate points in arbitrary coordinates, which is more fundamentally defined as an ordered array of numerical values describing the spatial distribution of various information about the morphology of the earth's surface. The ground characteristic of the digital ground model can be elevation, and can also be non-terrain ground characteristic information such as soil, vegetation, geology, land utilization, social and economic information and the like. In the research, the density of the organic carbon in the Chinese soil is analyzed by establishing a digital ground model, and the space distribution characteristics of the organic carbon library in the Chinese soil are analyzed by drawing a section line according to a typical sample band.

And secondly, establishing an optimal semivariance function theoretical model for reflecting the space-time variation of the organic carbon content.

In the first embodiment, the soil organic carbon spatial-temporal variation mainly adopts a geostatistical Malulong regionalization variable theory and a half variance function theory to establish an optimal half variance function theoretical model.

Regional Malolon (Matheron) variable theory

In the study of soil variability, a simplified method is generally adopted, and soil properties measured at a certain position Z (x) are assumed to be soil properties at a certain point Z, but the soil properties are in a one-to-one correspondence relationship. For this particular analysis purpose, we can accept that the position error of that point is negligible, since the position error of that point is very small. Mathematically, soil is both a multivariate and a vector variable, and some variables can be measured on a continuous scale, while some variables cannot be measured by any method, such as soil type being a discrete variable that cannot be measured. In principle, however, it is possible to determine the value of any property Z at any location. In the research related to soil investigation that can be conducted, the enormous amount of work and the scarce expenses cause researchers to sample and analyze only the properties of soil at some certain amount of discrete points. Therefore, we generally use an estimation and prediction method for the soil properties of those points that are not observed and sampled.

Here we assume a regionalized variable z (x), which is a random variable and also a spatially distributed variable of a certain property possessed by the soil under study. It reflects mostly some special properties of certain phenomena, such as the content of available phosphorus in soil at various points in different locations, etc. Furthermore, in this region, random variables at all positions form a finite set, called a random function. The random function in turn represents two attributes that a regionalized variable has: randomness, and structure.

Theoretical model of semivariance function-

The most common tool in geostatistical analysis is the semivariance function, which first assumes that the regionalized variables satisfy the second order stationary and eigen assumptions, and can therefore be estimated using the following formula:

in the formula, n (h) represents the logarithm of all observation points separated by a distance h; and h represents the distance of hysteresis; z (X)_i+ h) and Z (X)_i) Respectively representing regionalized variables Z (X) at position X_i+ h and X_iActual measured values of; a two-dimensional coordinate diagram is formed by taking h as an abscissa and gamma (h) as an ordinate, which becomes a so-called half variance diagram. In most cases, the calculation of the half-variance function must satisfy the normal distribution, otherwise, the proportional effect occurs, and the proportional effect will negatively affect the calculation, which will generally make the fast-gold value and the base value higher, and thus reduce the accuracy of the estimation result, and hide some potential special properties that should occur. In this embodiment, the K-S method of SPSS software is used to check the results of these values.

The graph of the half-variance function explains how the spatial structure of the soil changes by three very important basic parameters: one is the lump value, one is the range, and the other is the base value. As the separation distance h increases, the half-variance function γ (h) rises from an initial non-zero value to a relatively stable constant, referred to as the base station value C₀+ C. And when the spacing distance h is equal to zero, the value of the half-variance function r (0) is equal to C₀This value is called the block-gold constant, and the block-gold variance is another name. The value that varies most in the system or in the attribute of the dead system is the base station value, and collectively reflects the variance of the regionalized variables, and when the half-variance function γ (h) reaches the base station value, the value a of the separation distance is called the range.

③ Kriging interpolation

Besides analyzing the existing properties of the spatial distribution of certain characteristics in the soil in the direction and the corresponding spacing distance, the semivariogram can estimate the values of certain parameters of points without measurement by using a relatively reasonable optimization interpolation method and draw a spatial distribution map of certain attributes in the research area. The most common optimal interpolation method is the so-called Kriging interpolation method, which mainly roughly interpolates some data and information related to space in the analysis of semivariance, and the interpolated value is also estimated, so that the approximate error of the estimated value from the accurate value and the accuracy of the value can be grasped by performing approximate estimation on a point which is not divided into sampling points by using the optimal interpolation method.

In the embodiment, an optimal semivariance function theoretical model is established by using a geostatistical Mallodon regionalization variable theory and a semivariance function theory, the change characteristics of the organic carbon content of the soil in the Liaohe plain farmland in the last 37 years (1980) -2017) are contrastingly researched, and the spatial distribution characteristics of different periods are researched based on the semivariance function and a spatial analysis method in the geostatistical theory.

And thirdly, acquiring the density and reserve change data of the organic carbon in the soil.

Calculating the organic carbon density of the section soil:

the organic carbon number of soil contained in the soil layer within a certain depth range of a unit area is the organic carbon density of the soil. At present, the carbon density of soil is a key index for evaluating and measuring the organic carbon reserves in soil, and the carbon density of soil is calculated on the basis of the volume of soil body, so that the effect of area factors is avoided.

The formula for calculating the organic carbon density SOCi for soil i is as follows:

SOC_i＝C_iD_iE_i(1-G_i)/100 (1)

in the above formula, Ci-organic carbon content of soil (g kg)^-1)；

Di-volume weight (g cm)^-3)；

Ei-soil thickness (cm);

gi-percentage (%) by volume of gravel larger than 2 mm.

In this context, the unit of SOCi is kg m^-2。

For a certain soil body composed of k layers of sections, the calculation formula of the organic carbon density SOCt of the sections is as follows:

at present, most of domestic and foreign researches take the depth of 1m as a calculation reference standard, so that results are favorably compared with each other. In the embodiment, the organic carbon densities of the soil with the depths of 20cm and 1m are calculated respectively, in the second soil general survey, the depth of some sections is larger than 1m, the embodiment only calculates the organic carbon density within the depth of 1m soil body according to needs, and the actual depth of some farmland soil can not be calculated to 1m because the soil body is very thin.

The product of the organic carbon density and the area of the plot is the organic carbon reserve, which is expressed in units of Tg (1 Tg-10)¹²g)。

Fourthly, establishing an organic carbon balance model

In the present embodiment, the organic carbon sequestration capacity of soil at a saturation level is used as an organic carbon equilibrium model, and the SOC at the saturation level is regarded as the soil sequestration potential (SOCp), the organic carbon at the saturation level, i.e. the saturation level of soil carbon or the maximum capacity of soil-contained carbon,

SOCp＝140.5×e^-0.021×MT－98.8×e^-0.42×MP－39.6×e^-0.1×CL－4.1×pH^-27.7 (3)

in the formula, SOCp represents the carbon sequestration potential (kg m)^-2) The annual average water supply is represented by MP, the soil slime content (%) is represented by CL, the pH is represented by soil pH, and the annual average air temperature (. degree. C.) is represented by MT.

And fifthly, analyzing the organic carbon space-time variation and carbon sequestration potential estimation of the soil.

Based on the steps, the project research data and the second soil general survey period (1980) data in China are evaluated and analyzed, the soil fertility space-time distribution rule in the Liaoning black soil area is proved, meanwhile, the organic carbon content level of farmland soil with about 88.78% monitoring sample points in our province is in a reduced state, the uniformity of the soil organic carbon content distribution is weakened under the intervention of human activities for more than 37 years, the variation in a small range is strengthened, and the overall distribution tends to be complex. The areas with large carbon sequestration potential in black soil areas are mainly concentrated in some areas of counties of Manchu counties of Guangdian, Qingyuan, Xifeng and Liaoyang, and the ways of improving the quality of black soil and efficiently utilizing black soil mainly comprise carbon increasing and fertilizing, farming and water and soil conservation, efficient fertilization and efficient crop planting.

In particular, the soil fertility is not high and shows a remarkable descending trend

The organic carbon content of farmland soil in the Liaoning black soil area in 1980 and 2017 is generally in normal distribution, and the normality test reaches a very significant level. Wherein the organic carbon content of the soil in the first ploughing field of the last 80 th century is 8.93-28.37 gkg^-1Average content of 14.08gkg^-1The coefficient of variation was 18.99%, as shown in table 1 and fig. 2. At this time, the organic carbon content of the cultivated land in the area is mainly concentrated in the middle level range, which accounts for 58.82% of the total area of the cultivated land in the whole province, as shown in Table 2. The organic carbon content of the soil in the cultivated land of 2017 is distributed in the range of 6.09-23.26 gkg^-1The average content of the product is lower than that of the product of the last 80 th century by 17.82 percent and is 11.59gkg^-1The coefficient of variation was 23.20%, as shown in table 1 and fig. 3. At this time, the organic carbon content of the farmland soil in the region is mainly concentrated in a relatively deficient level range, and accounts for 58.92% of the total area of the farmland in the whole province, as shown in Table 2. From the distribution of the samples, the organic carbon content level of the farmland soil with about 88.78% of the samples is in a reduced state, and the organic carbon content level of the farmland soil with 11.22% of the samples is in an increased state. The average reduction of more than 5 percentage points is 8.74% of the total number of samples.

TABLE 1

TABLE 2

The organic carbon in the soil is not distributed uniformly in space, and the effect of human factors is great

And (3) calculating the value gamma (h) of the experimental half-variance function by using a land statistical method, drawing a half-variance function curve, and fitting by adopting different theoretical models (isotropy) respectively to select an optimal half-variance function theoretical model. From the Liaoning black soil area in 1980 and 2017, the half-variance of the organic carbon content of the farmland soil plough layer and a fitting simulation curve chart thereof are shown in figures 4 and 5. It can be seen that the half-variance values of the soil organic carbon all increase with the increase of the step length, that is, the spatial correlation degree gradually decreases with the increase of the distance between the sampling points, but the step length is relatively large, which indicates that the soil organic carbon in the research area has spatial autocorrelation in a large scale range, and when the point-to-distance is longer than the step length, the soil organic carbon no longer has spatial autocorrelation, that is, the spatial independence is maintained. The semivariance change of the organic carbon content of the soil in 1980 and 2017 can be fitted by an exponential model, and the fitting degree is high, as shown in table 3:

TABLE 3

By K-S test, the organic carbon belongs to log normal distribution in 1980 and 2017.

C₀/C₀+ C reflects the degree of spatial autocorrelation of the variables and is also an important indicator to distinguish the source of spatial heterogeneity of the variables (Robertson et al, 1997). Lump value (C) from soil organic carbon content in two periods₀) Base station values (C) and C₀/C₀+ C in the study area, C of organic carbon in 1980₀/C₀+ C49.99%, C of organic carbon 2017₀/C₀+ C is 49.97%, all belonging to the intermediate spatial autocorrelation. This is related to the strong influence of structural factors (such as the matrix) of the organic carbon itself.

The variation indicates the size of the spatial autocorrelation range of the attribute factors, which is related to the observation scale and the interaction of various ecological processes affecting soil nutrients at the sampling scale. Within a variation range, a variable has spatial autocorrelation and otherwise does not exist, so it provides a measure for studying the similarity range of certain attributes. By comparing the variation values in 1980 and 2017, the uniformity of the organic carbon content distribution of the soil is weakened, the variation in a small range is strengthened, and the overall distribution tends to be complex under the intervention of human activities for more than 35 years.

Organic carbon growth potential of cultivated land in Liaoning black soil area

The statistics show that the average density of organic carbon in the soil of the cultivated land in the Liaoning black soil area in 1980 is 4.81kgm^-2In 2017, the average organic carbon density of the soil in the farmland in the Liaoning black soil area is 4.08kgm^-2The mean value of the organic carbon density, i.e. SOCP, reaching saturation was estimated to be 6.12kgm^-2The difference value of the two is the soil carbon growth potential of the cultivated land in Liaoning black soil area, and is 2.04kgm^-2. The total organic carbon pool amount of the cultivated land plough layer in 1980 is 156.96Tg, and 131.14Tg is obtained in 2017, and the Tg is reduced by 25.82 generally. When the organic carbon of the farmland soil is saturated, the carbon storage of the surface soil (0-20 cm) is 235.44Tg, and the carbon fixation can be increased by 104.3Tg, as shown in fig. 6 and 7. The method means that the organic carbon content of the soil in the cultivated land in the Liaoning black soil area still has a space for improving, and the organic carbon content of the soil in the area can be improved by implementing key technologies such as carbon increasing and fertilizing of the soil in the dry land, water and soil protection, efficient utilization of chemical fertilizers, efficient planting modes of crops and the like.

The results show that SOCP spatial differentiation is significant in the Liaoning black soil region, and as shown in FIG. 8, the whole body shows a higher east part and a lower west part. Specifically, the saturated organic carbon density in Manchu county of. The organic carbon growth potential of the cultivated land in the black soil area of Liaoning generally shows a state of high in the southeast and low in the northwest, as shown in Table 5. Specifically, the regions with large organic carbon density growth values are mainly concentrated in some regions of the counties of Manchu counties, Qingyuan counties, Xifeng counties and Liaoyang counties; and the organic carbon growth potential of partial areas of the prefecture, the clear river district and the new city is small. The organic carbon reserves of the farmland soil in the Liaoning black soil area in the saturated state have obvious spatial difference, and the whole is represented as the high middle parts of the north part and the south part which are low, as shown in figure 9.

TABLE 4

TABLE 5

The method takes soil organic carbon and growth potential thereof as core indexes, integrates factors such as weather, topography, social economy, natural disasters and the like, divides dry land of Liaoning province into 5 functional areas, and determines technical priorities and leading technologies of different areas aiming at different area characteristics and key restriction factors. As shown in Table 6, the functional and technical priorities of the Liaoning dry land are shown, and as shown in FIG. 10, the functional and technical priorities of the Liaoning dry land are shown.

TABLE 6

Example two

Fig. 11 is a schematic structural diagram of a soil organic carbon spatio-temporal variation and carbon sequestration potential estimation system according to a second embodiment of the present application, including a data acquisition module, a half variance function module, an organic carbon variation module, an organic carbon balance module, and an estimation analysis module.

Specifically, the data acquisition module is used for acquiring multiple times of soil general survey data in a preset area; the half variance function module is used for establishing a half variance function theoretical model, and the half variance function theoretical model is used for reflecting the space-time variation of the organic carbon content; the organic carbon change module is used for acquiring organic carbon density and reserve change data of soil general survey data each time; the organic carbon balance module is used for establishing an organic carbon balance model of soil census data, and the organic carbon balance model is used for reflecting the relation among organic carbon reserves, temperature, precipitation, clay content and pH values of high, medium and low fertilizer levels in different periods; and the estimation analysis module is used for obtaining the estimation data of the organic carbon space-time variation and the carbon sequestration potential of the soil according to the organic carbon content evolution and space variation, the organic carbon density and reserve variation data and the organic carbon balance model.

The above embodiments are merely illustrative of the preferred embodiments of the present application, and do not limit the scope of the present application, and various modifications and improvements made to the technical solutions of the present application by those skilled in the art without departing from the spirit of the present application should fall within the protection scope defined by the claims of the present application.

Claims

1. A method for estimating space-time variation and carbon sequestration potential of soil organic carbon is characterized by comprising the following steps:

collecting soil general survey data of a plurality of times in a preset area;

acquiring the organic carbon density and reserve change data of each soil census data;

establishing an organic carbon balance model of the soil census data;

2. The soil organic carbon spatiotemporal variation and carbon sequestration potential estimation method of claim 1, wherein the soil census data includes high and low fertility level organic carbon treatments, temperature, precipitation, cosmid content, and pH at different periods.

3. The soil organic carbon spatio-temporal variation and carbon sequestration potential estimation method according to claim 2, characterized in that the half-variance theoretical function model is

4. The soil organic carbon spatiotemporal variation and carbon sequestration potential estimation method of claim 2, wherein the method of obtaining the organic carbon density and reserve variation data comprises:

and comparing the density and the reserve of the organic carbon of a plurality of times of soil general surveys to obtain the density and reserve change data of the organic carbon.

5. The method for estimating soil organic carbon spatial-temporal variation and carbon sequestration potential according to claim 4, wherein the organic carbon density is calculated by

SOC_i＝C_iD_iE_i(1-G_i)/100。

6. The method for estimating soil organic carbon spatiotemporal variation and carbon sequestration potential according to claim 5, wherein the reserve is calculated by

7. The soil organic carbon spatio-temporal variation and carbon sequestration potential estimation method according to claim 2, characterized in that the organic carbon equilibrium model is

SOCp＝140.5×e^-0.021×MT-98.8×e^-0.42×MP-39.6×e^-0.1×CL-4.1×pH^-27.7。

8. The soil organic carbon spatio-temporal variation and carbon sequestration potential estimation method according to any one of claims 1-7, characterized in that the carbon sequestration potential estimation data is obtained using a farmland soil carbon sequestration potential statistical model.

9. A soil organic carbon space-time variation and fixed carbon potential estimation system is characterized by comprising a data acquisition module, a half variance function module, an organic carbon variation module, an organic carbon balance module and an estimation analysis module;

the data acquisition module is used for acquiring soil general survey data in each time in a preset area;