A method and device for determining the vertical transport characteristics of a soil mineralization layer based on soil parameters

Abstract

The application discloses a soil mineralization interlayer vertical transmission characteristic determination method and device based on soil parameters, relates to the technical field of soil nitrogen cycle simulation, and comprises the following steps: obtaining a maximum net nitrogen mineralization rate reference value corresponding to a target vegetation functional type from a preset parameter table; simulating soil parameters of a multi-layer soil of a to-be-measured region at a current time step by using a land surface process model; determining a net nitrogen mineralization rate of each layer of soil by using a net nitrogen mineralization rate empirical equation based on the soil parameters of each layer of soil and the maximum net nitrogen mineralization rate reference value corresponding to the target vegetation functional type; respectively substituting the net nitrogen mineralization rate of each layer of soil into an ammonium ion concentration dynamic equation to determine the NH4 + concentration change of each layer of soil; and analyzing the soil mineralization interlayer vertical transmission characteristic of the to-be-measured region based on the NH4 + concentration change of each layer of soil. The application improves the determination precision of the soil mineralization interlayer vertical transmission characteristic by dynamically estimating the net nitrogen mineralization rate of each layer of soil.

Description

Technical Field

[0001] This application relates to the field of soil nitrogen cycle simulation technology, and in particular to a method and device for determining the vertical transport characteristics of soil mineralization layers based on soil parameters. Background Technology

[0002] Soil nitrogen mineralization is the core process of converting organic nitrogen into inorganic ammonium nitrogen, and the rate of nitrogen mineralization directly determines the amount of NH4 in the soil. + Concentration is a key controlling factor for soil nitrification, denitrification, and the production of the greenhouse gas N2O.

[0003] Current mainstream land surface process models have significant technical shortcomings: most models fail to achieve dynamic simulation of net nitrogen mineralization, employing only a fixed mineralization rate constant, and thus cannot reflect the regulatory effects of temperature, soil moisture content, and soil layer changes on the mineralization rate. The simulation results deviate significantly from field measurements. Existing research, based on measured datasets of Chinese forest ecosystems, has constructed a ternary nonlinear empirical equation relating soil net nitrogen mineralization rate to soil temperature and soil moisture. However, this empirical equation remains at the single-point statistical fitting stage, lacking parameter standardization, unit conversion, and stratification, making it impossible to integrate into general land surface process models and hindering continuous spatiotemporal simulations at regional and global scales. Existing localized mineralization empirical formulas are not adapted to the stratified soil structure of land surface models, lack standardized unit conversion procedures, and fail to couple the vertical transport process of inorganic nitrogen leaching between soil layers, resulting in insufficient completeness of nitrogen cycle simulation. Summary of the Invention

[0004] The purpose of this application is to provide a method and device for determining the vertical transport characteristics between soil mineralization layers based on soil parameters, which can improve the accuracy of determining the vertical transport characteristics between soil mineralization layers.

[0005] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters, including: The vegetation functional type of the area to be tested is obtained as the target vegetation functional type; Obtain the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type from the preset parameter table; Soil parameters of multi-layered soils in the test area at the current time step were simulated using a land surface process model. Based on the soil parameters of each soil layer and the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type, the net nitrogen mineralization rate of each soil layer is determined by the empirical equation of net nitrogen mineralization rate. Substituting the net nitrogen mineralization rate of each soil layer into the dynamic equation for ammonium ion concentration, the NH4+ concentration of each soil layer was determined. + Concentration change; Based on NH4 in each soil layer + The concentration changes were analyzed to determine the vertical transport characteristics of soil mineralization between layers in the test area.

[0006] Optionally, the preset parameter table includes reference values ​​for the maximum net nitrogen mineralization rate corresponding to different vegetation functional types.

[0007] Optionally, the vegetation functional types involved in the preset parameter table include: evergreen broad-leaved forest, evergreen coniferous forest, deciduous broad-leaved forest, deciduous coniferous forest, and mixed forest.

[0008] Optionally, the reference value for the maximum net nitrogen mineralization rate corresponding to the evergreen broad-leaved forest is 3.08; The reference value for the maximum net nitrogen mineralization rate corresponding to the evergreen coniferous forest is 4.4; The reference value for the maximum net nitrogen mineralization rate corresponding to the deciduous broad-leaved forest is 2.6; The reference value for the maximum net nitrogen mineralization rate corresponding to the deciduous coniferous forest is 3.23; The reference value for the maximum net nitrogen mineralization rate corresponding to the mixed forest is 3.23.

[0009] Optionally, the soil parameters include soil temperature and soil water-filling porosity.

[0010] Optionally, the constant term in the empirical equation for net nitrogen mineralization rate is obtained after calibration of measured forest soil data.

[0011] Optionally, the empirical equation for the net nitrogen mineralization rate is: ; in, Let be the net nitrogen mineralization rate of the i-th soil layer; Reference value for the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type; Let be the soil temperature of the i-th soil layer; Let be the soil water-filling porosity of the i-th soil layer.

[0012] Optionally, the dynamic equation for the ammonium ion concentration is: ; in, The dynamic rate of ammonium ion concentration; The ammonia oxidation rate of AOA; The ammonia oxidation rate of AOB; for Evaporation rate; This represents the ammonia uptake rate of plants.

[0013] In a second aspect, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for determining the vertical transport characteristics between soil mineralization layers based on soil parameters as described above.

[0014] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for determining the vertical transport characteristics between soil mineralization layers based on soil parameters as described above.

[0015] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method and device for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters. It determines a reference value for the maximum net nitrogen mineralization rate based on the functional type of forest vegetation, and then uses layer-by-layer soil temperature and soil water-filling porosity simulated by a land surface process model. The net nitrogen mineralization rate of each soil layer is calculated layer by layer using a ternary nonlinear empirical equation, achieving real-time, layered estimation of the environmental dependence of the net nitrogen mineralization rate. This method also provides a basis for soil NH4+ gradation. + The concentration dynamic equation provides an accurate source term, allowing the calculation results to be directly input into the soil NH4. + The concentration dynamic equation is parameterized and implemented hierarchically. This application provides a localized reference value for the maximum net nitrogen mineralization rate for forest vegetation functional types. It realizes the real-time response of net nitrogen mineralization rate to soil temperature and moisture dynamics, overcoming the shortcomings of fixed rate constants. The empirical equation introduces a quadratic term of soil water-filled porosity to accurately reflect the inhibitory effect of excessive wet conditions on mineralization. The hierarchical calculation takes into account the vertical heterogeneity of soil profiles. It can be embedded in any land surface process model with soil temperature and humidity simulation capabilities. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters in one embodiment of this application. Figure 2 This is a diagram showing the soil temperature simulation results at a typical forest site in one embodiment of this application; Figure 3 This is a simulation result of soil moisture at a typical forest site in one embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] In one exemplary embodiment, such as Figure 1 As shown, a method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters is provided, including: Step 101: Obtain the vegetation functional type of the area to be tested as the target vegetation functional type.

[0021] Step 102: Obtain the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type from the preset parameter table.

[0022] The preset parameter table includes reference values ​​for the maximum net nitrogen mineralization rate corresponding to different vegetation functional types.

[0023] The preset parameter table covers vegetation functional types including: evergreen broad-leaved forest, evergreen coniferous forest, deciduous broad-leaved forest, deciduous coniferous forest, and mixed forest.

[0024] The reference value for the maximum net nitrogen mineralization rate corresponding to evergreen broad-leaved forests is 3.08.

[0025] The reference value for the maximum net nitrogen mineralization rate corresponding to evergreen coniferous forests is 4.4.

[0026] The reference value for the maximum net nitrogen mineralization rate corresponding to deciduous broad-leaved forests is 2.6.

[0027] The reference value for the maximum net nitrogen mineralization rate corresponding to deciduous coniferous forests is 3.23.

[0028] The reference value for the maximum net nitrogen mineralization rate corresponding to mixed forests is 3.23.

[0029] Step 103: Simulate soil parameters of multi-layered soils in the area to be tested at the current time step using a land surface process model. Soil parameters include soil temperature and soil water-filling porosity.

[0030] Step 104: Based on the soil parameters of each soil layer and the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type, determine the net nitrogen mineralization rate of each soil layer using the empirical equation of net nitrogen mineralization rate.

[0031] The constant term in the empirical equation for net nitrogen mineralization rate is obtained after calibration using measured forest soil data.

[0032] The empirical equation for the net nitrogen mineralization rate is: .

[0033] in, Let be the net nitrogen mineralization rate of the i-th soil layer. The reference value for the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type. Let be the soil temperature of the i-th soil layer. Let be the soil water-filling porosity of the i-th soil layer.

[0034] Step 105: Substitute the net nitrogen mineralization rate of each soil layer into the dynamic equation of ammonium ion concentration to determine the NH4+ concentration of each soil layer. + Concentration changes.

[0035] The dynamic equation for ammonium ion concentration is: .

[0036] in, The dynamic rate of ammonium ion concentration; The ammonia oxidation rate of AOA; The ammonia oxidation rate of AOB; for Evaporation rate; This represents the ammonia uptake rate of plants.

[0037] Step 106: NH4 based on each soil layer + Concentration changes were analyzed to determine the vertical transport characteristics of soil mineralization between layers in the tested area.

[0038] The following section uses the mixed forest of Changbai Mountain as an example to specifically explain the method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters provided in this embodiment.

[0039] Step 1: Vegetation Functional Type Classification and Parameter Matching: Obtain parameters from the preset parameter table (as shown in Table 1) based on the vegetation functional type. (kg hm) -2 d -1 ).

[0040] Table 1 Preset Parameter Table

[0041] Step 2: Obtain layer-by-layer soil temperature and soil water-filling porosity: Perform hydrological and energy simulations from the land surface process model, and output the soil temperature of the i-th layer at the current time step. (°C) and the water-filling porosity of the i-th soil layer (0-1).

[0042] Step 3: Calculate the net nitrogen mineralization rate by soil layer: For each soil layer i, calculate Rmini (gN m) using the following formula. -2 h -1 ): .

[0043] Where 1 / 240 is the unit conversion factor.

[0044] Step 4: Input the mineralization rate into NH4 + Concentration dynamic equation: NH4 in the i-th soil layer + Concentration changes: .

[0045] Step 5: Vertical transport between soil layers: Considering NH4 + and NO3 - As water flows, some of the inorganic nitrogen produced by mineralization in the upper layer is transferred to the lower layer through leaching.

[0046] The vegetation functional type at Changbaishan Station is mixed forest (MF). =3.23 kg hm -2 d -1 At a certain moment, the simulated soil temperatures in the land surface process model were: Layer 1 12.5℃, Layer 2 11.2℃, Layer 3 9.8℃, and Layer 4 8.1℃; soil water-filling porosity was: Layer 1 65%, Layer 2 72%, Layer 3 78%, and Layer 4 82%. The calculated value for Layer 1 was: Rmin1 = 0.00288 gN / m³. -2 h -1 The same calculation is performed for the other layers. Substitute Rmin for each layer into NH4. + Dynamic equations drive subsequent nitrification and N2O production. Soil physicochemical properties at forest observation stations are shown in Table 2. Simulations of soil temperature and humidity at typical forest stations are as follows: Figure 2 and Figure 3 As shown.

[0047] With a fixed mineralization rate (0.005 gN m) -2 h -1 Compared to the previous method, this method increases the mineralization rate by about 40% in summer and approaches 0 in winter, which is more consistent with the actual measured situation.

[0048] Table 2 Soil physicochemical properties at forest observation stations

[0049] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection.

[0050] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0051] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0052] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0053] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0054] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0055] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0056] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0057] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters, characterized in that, include: The vegetation functional type of the area to be tested is obtained as the target vegetation functional type; Obtain the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type from the preset parameter table; Soil parameters of multi-layered soils in the test area at the current time step were simulated using a land surface process model. Based on the soil parameters of each soil layer and the reference value of the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type, the net nitrogen mineralization rate of each soil layer is determined by the empirical equation of net nitrogen mineralization rate. Substituting the net nitrogen mineralization rate of each soil layer into the dynamic equation for ammonium ion concentration, the NH4+ concentration of each soil layer was determined. + Concentration change; Based on NH4 in each soil layer + The concentration changes were analyzed to determine the vertical transport characteristics of soil mineralization between layers in the test area.

2. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 1, characterized in that, The preset parameter table includes reference values ​​for the maximum net nitrogen mineralization rate corresponding to different vegetation functional types.

3. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 2, characterized in that, The preset parameter table includes the following vegetation functional types: evergreen broad-leaved forest, evergreen coniferous forest, deciduous broad-leaved forest, deciduous coniferous forest, and mixed forest.

4. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 3, characterized in that, The reference value for the maximum net nitrogen mineralization rate corresponding to the evergreen broad-leaved forest is 3.08; The reference value for the maximum net nitrogen mineralization rate corresponding to the evergreen coniferous forest is 4.4; The reference value for the maximum net nitrogen mineralization rate corresponding to the deciduous broad-leaved forest is 2.6; The reference value for the maximum net nitrogen mineralization rate corresponding to the deciduous coniferous forest is 3.23; The reference value for the maximum net nitrogen mineralization rate corresponding to the mixed forest is 3.

23.

5. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 1, characterized in that, The soil parameters include soil temperature and soil water-filling porosity.

6. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 5, characterized in that, The constant term in the empirical equation for net nitrogen mineralization rate was obtained after calibration using measured forest soil data.

7. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 6, characterized in that, The empirical equation for the net nitrogen mineralization rate is: ； in, Let be the net nitrogen mineralization rate of the i-th soil layer; Reference value for the maximum net nitrogen mineralization rate corresponding to the target vegetation functional type; Let be the soil temperature of the i-th soil layer; Let be the soil water-filling porosity of the i-th soil layer.

8. The method for determining the vertical transport characteristics of soil mineralization between layers based on soil parameters according to claim 7, characterized in that, The dynamic equation for the ammonium ion concentration is: ； in, The dynamic rate of ammonium ion concentration; The ammonia oxidation rate of AOA; The ammonia oxidation rate of AOB; for Evaporation rate; This represents the ammonia uptake rate of plants.

9. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for determining the vertical transport characteristics between soil mineralization layers based on soil parameters, as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for determining the vertical transport characteristics of soil mineralization layers based on soil parameters, as described in any one of claims 1-8.

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