Vertical migration simulation method of adsorption coefficient time dynamic change under reclaimed water irrigation

Abstract

The invention provides a vertical migration simulation method for adsorption coefficient time dynamic change under reclaimed water irrigation, which comprises the following steps: acquiring salt ion concentration and organic matter content in initial soil and reclaimed water to be irrigated in a research area, and calculating the adsorption coefficient time dynamic change according to the irrigation amount and irrigation frequency of the research area; calculating the salt ion concentration and the organic matter content in the soil at different time; calculating adsorption coefficient values under different salt concentrations and organic matter contents through an adsorption experiment; establishing a correlation between the adsorption coefficient value and the salinity concentration and the organic matter content by using a multiple linear regression method; the correlation is embedded into pollutant migration simulation software to replace an input mode of a fixed adsorption coefficient value, and the improved pollutant migration simulation software is used to simulate the vertical migration process of pollutants in soil. According to the invention, the limitation of using a fixed unique adsorption coefficient value can be broken through, and the precision of simulating vertical migration of pollutants is improved.

Description

Technical Field

[0001] The present application relates to the technical field of soil pollution investigation, and in particular to a vertical migration simulation method for the temporal dynamic change of adsorption coefficient under reclaimed water irrigation. Background Art

[0002] Hydrus-1D is a widely used tool for simulating the vertical migration of pollutants in unsaturated soil media. The model usually involves three types of parameters: upper and lower boundary conditions (soil moisture, precipitation, etc.), soil hydrodynamic parameters (soil porosity, etc.) and solute transport parameters (such as adsorption coefficient K). d ). In the prior art, K d The value is often a fixed value, which ignores the K d The value of K changes dynamically under long-term irrigation conditions due to changes in salt and organic matter. With the long-term implementation of recycled water irrigation, changes in organic matter content and salt concentration in the soil will directly affect K. d The value of K affects the simulation accuracy of pollutant migration. d The Hydrus-1D model prediction results with different values ​​may have large errors, underestimating or overestimating the risk of pollutant migration. Summary of the Invention

[0003] The present application aims to solve one of the technical problems in the related art at least to a certain extent.

[0004] To this end, the first purpose of this application is to propose a vertical migration simulation method for the temporal dynamic change of adsorption coefficient under reclaimed water irrigation.

[0005] The second purpose of this application is to propose a vertical migration simulation device that dynamically changes the adsorption coefficient over time under recycled water irrigation.

[0006] The third objective of this application is to provide an electronic device.

[0007] The fourth object of this application is to provide a computer-readable storage medium.

[0008] A fifth object of this application is to provide a computer program product.

[0009] To achieve the above objectives, the first embodiment of the present application proposes a vertical migration simulation method for the temporal dynamic change of adsorption coefficient under reclaimed water irrigation, comprising:

[0010] Obtain the salt ion concentration and organic matter content in the initial soil and the recycled water to be irrigated in the study area, and calculate the salt ion concentration and organic matter content in the soil at different times based on the irrigation amount and frequency of the study area;

[0011] An orthogonal test is conducted according to the salt ion concentration and organic matter content in the soil at different times, and an adsorption experiment is carried out to calculate the adsorption coefficient values ​​under different salt concentrations and organic matter contents through the adsorption experiment;

[0012] The correlation between adsorption coefficient values ​​and salt concentration and organic matter content was established using the multiple linear regression method;

[0013] The correlation is embedded in the pollutant migration simulation software to replace the input method of fixed adsorption coefficient value. The improved pollutant migration simulation software is used to simulate the vertical migration process of pollutants in soil.

[0014] Optionally, the change in salt ion concentration in the soil at different times is calculated using the following formula:

[0015]

[0016] Where S j (t) is the concentration of salt ion j in the soil at time t, is the initial concentration of soil salt separator j, C i is the salt ion concentration of the i-th irrigation water, I i is the amount of irrigation for the i-th time, L is the leaching efficiency coefficient, n is the number of days between irrigations, and D is the soil depth.

[0017] Optionally, the change in soil organic matter content at different times can be calculated using the following formula:

[0018]

[0019] Where C CODsoil is the organic matter content at time t, C reclaimed is the organic matter flux input into recycled water, k input is the input conversion efficiency coefficient, k decay is the decomposition rate constant.

[0020] Optionally, the calculation of adsorption coefficient values ​​under different salt concentrations and organic matter contents through adsorption experiments includes:

[0021]

[0022] Where Q is the amount of pollutants adsorbed by the soil, C e is the concentration of the pollutant in the solution after the reaction equilibrium, C0 is the initial concentration of the pollutant in the solution, V is the volume of the solution, and M is the mass of the soil.

[0023] To achieve the above-mentioned purpose, the second embodiment of the present application proposes a vertical migration simulation device for dynamic temporal changes in adsorption coefficient under reclaimed water irrigation, comprising:

[0024] The parameter acquisition and calculation module is used to obtain the salt ion concentration and organic matter content in the initial soil and the recycled water to be irrigated in the study area, and calculate the salt ion concentration and organic matter content in the soil at different times based on the irrigation amount and frequency of the study area;

[0025] An adsorption experiment module is used to conduct an orthogonal experiment based on the salt ion concentration and organic matter content in the soil at different times, carry out an adsorption experiment, and calculate the adsorption coefficient values ​​under different salt concentrations and organic matter contents through the adsorption experiment;

[0026] Regression module, used to establish the correlation between adsorption coefficient values ​​and salt concentration and organic matter content using the multivariate linear regression method;

[0027] The simulation module is used to embed the correlation into the pollutant migration simulation software, replace the input method of fixed adsorption coefficient value, and use the improved pollutant migration simulation software to simulate the vertical migration process of pollutants in soil.

[0028] To achieve the above-mentioned purpose, a third embodiment of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0029] The memory stores computer-executable instructions;

[0030] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0031] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the method as described in any one of the first aspects.

[0032] To achieve the above-mentioned objectives, the fifth embodiment of the present application proposes a computer program product, which implements any one of the methods in the first aspect when executed by a processor.

[0033] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0035] Figure 1A schematic flow chart of a vertical migration simulation method for dynamic temporal changes in adsorption coefficient under reclaimed water irrigation provided in an embodiment of the present application;

[0036] Figure 2 The embodiment of the present application provides a fixed K d Value and use of dynamic K d Simulated vertical distribution results of ofloxacin, carbamazepine and sulfadiazine. DETAILED DESCRIPTION

[0037] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0038] Hydrus-1D is an important tool for simulating the vertical migration of pollutants in unsaturated soil media. The model involves upper and lower boundary conditions (rainfall, etc.), soil hydrodynamics (soil porosity, etc.) and solute transport (adsorption coefficient K d Among them, the adsorption coefficient K d The value is an important parameter in the model, K d The larger the value, the stronger the pollutant adsorption capacity and the weaker the migration capacity. d The value is usually obtained based on equilibrium adsorption experiments under the current state of the soil in the study area, or the K d value. In other words, this value is the adsorption coefficient at a fixed moment. However, Hydrous-1D is often used to predict the vertical distribution characteristics of soil pollutants on different time scales such as several days, months, and years in the future. However, under long-term irrigation conditions, K d Whether the value changes on the time scale directly affects the accuracy of the prediction. d The value gradually decreases, then based on the initial state K d The predicted results of the value will underestimate the vertical migration risk of pollutants, and conversely, it will overestimate the migration risk, which is contrary to the purpose of precise environmental prevention and control.

[0039] Although the recycled water has been treated, it is still alkaline and rich in Mg. 2+ , Ca 2+ 、Na + , K + 、Cl - Inorganic ions and organic matter. In areas irrigated with recycled water for a long time, soil organic matter content can increase by 34%, and the ionic strength caused by salt accumulation can increase by 300%. The increase in soil organic matter content will generally increase the adsorption coefficient K of pollutants. dWhile the ion strength enhances, on one hand, the K d value through compressing the double electric layer, on the other hand, the K d value through competitive adsorption. Through experiments, it is verified that the K d value gradually changes under the condition of long-term irrigation with reclaimed water. However, the only fixed K d value is usually used in Hydrous-1D to simulate the long-term irrigation condition, which is inconsistent with the actual migration law, and thus, the use of the only fixed K d value reduces the simulation accuracy of the migration of pollutants.

[0040] To solve the problem, the embodiment of the present application provides a vertical migration simulation method of time dynamic change of adsorption coefficient under reclaimed water irrigation, Figure 1 and a flowchart of the vertical migration simulation method of time dynamic change of adsorption coefficient under reclaimed water irrigation provided by the embodiment of the present application is shown in the figure. Figure 1 As shown in the figure, the method comprises the following steps:

[0041] In step 101, the initial soil salt ion concentration and organic matter content in the research area and the salt ion concentration and organic matter content in the reclaimed water to be irrigated are obtained, and the soil salt ion concentration and organic matter content at different times are calculated according to the irrigation amount and irrigation frequency of the research area.

[0042] In the embodiment of the present application, the basic soil environmental parameters of the research area and the irrigation condition data to be used are first obtained to establish the initial boundary conditions for the simulation of the migration law of pollutants. The soil samples of the research area need to be collected at different depths, and the initial salt ion concentration and organic matter content thereof are determined through experiments, wherein the salt ions mainly include but are not limited to magnesium ions (Mg 2+ ), calcium ions (Ca 2+ ), sodium ions (Na + ), potassium ions (K + ), chlorine ions (Cl - ), sulfate ions (SO4 2- ), carbonate ions (CO3 2- ), bicarbonate ions (HCO3 - ) and nitrate ions (NO3 - ). The organic matter content is determined by using the standard COD conversion method, and the result is in g / kg.

[0043] At the same time, a detailed compositional analysis of the recycled water used for irrigation is also required to obtain the concentrations of various salt ions (in mg / L) and the average annual flux of dissolved organic matter. These chemical components of recycled water will directly affect the evolution of salt and organic matter in the soil environment, so their accurate measurement is the basis for constructing a dynamic adsorption coefficient model. In addition, irrigation method parameters need to be collected, including annual irrigation volume, irrigation water volume per time, irrigation interval period, and annual irrigation frequency. Combined with the actual hydraulic permeability and soil thickness of the region, the effective depth of the simulation profile is determined. It is generally recommended to select a representative soil profile within the range of 50 cm to 100 cm.

[0044] After obtaining the above basic parameters, a prediction model for the evolution of salt ion concentration in soil over time is established based on the principle of conservation of mass. In this embodiment, the following mathematical expression is used for modeling:

[0045]

[0046] Where S j (t) is the concentration of a certain salt ion j in the soil at time t (g / kg), is the initial concentration of soil salt separator j, C i is the salt ion concentration of the i-th irrigation water (mg / L), I i is the i-th irrigation volume (mm), L is the leaching efficiency coefficient, which, after comprehensive consideration of soil permeability and hydraulic conductivity, can be taken as an empirical value of 0.8 g / mm; n is the number of days between irrigations, and D is the soil depth (cm). The model used in this application dynamically reflects the accumulation and leaching of salt ions in the soil under multiple irrigation cycles, taking into account the interactive effects of ion migration, infiltration, and soil adsorption.

[0047] In view of the dynamic changes of soil organic matter, this embodiment further establishes an organic matter evolution model under the coordinated control of input and decomposition, which is expressed as follows:

[0048]

[0049] Where C CODsoil is the organic matter content at time t (g / kg), C reclaimed is the organic matter flux of recycled water input, in g / m 3 ·year; k input k is the input conversion efficiency coefficient, which is affected by the soil C / N ratio, clay content, etc. Under typical tillage conditions, the empirical value can be 0.3; decay is the decomposition rate constant, with a recommended value of 0.05 g / year in temperate monsoon climates. This model mathematically reflects the dynamic equilibrium between the continuous input of organic matter and its natural degradation, and has good environmental adaptability and scalability.

[0050] It should be noted that the two computational models proposed in the examples of this application can respectively capture the temporal trends of salt ions and organic matter, providing precise input for subsequent time-varying modeling of the adsorption coefficient Kd. In long-term irrigation scenarios, by continuously iterating these models, dynamic estimates of the soil environmental state at any given moment can be obtained, providing a scientific basis for risk assessment of pollutant migration and delineation of control boundaries.

[0051] Step 102 , performing an orthogonal test based on the salt ion concentration and organic matter content in the soil at different times, carrying out an adsorption experiment, and calculating the adsorption coefficient values ​​at different salt concentrations and organic matter contents through the adsorption experiment.

[0052] In the embodiment of the present application, after completing the dynamic calculation of the soil salt ion concentration and organic matter content over time, step 102 is further performed to establish the adsorption behavior model of the pollutant under different soil environmental conditions, and the adsorption coefficient K is d The multivariate regression modeling and simulator embedding provide basic data support.

[0053] In order to fully consider the combined effects of salt ions and organic matter content on the migration ability of pollutants, the orthogonal experimental design method was used in the examples of this application to systematically investigate the key factors. Specifically, multiple variables that have a significant impact on the adsorption behavior of pollutants were selected, including magnesium ions (Mg 2+ ), calcium ions (Ca 2+ ), sodium ion (Na + ), potassium ion (K + ), chloride ion (Cl - ), sulfate ion (SO4 2- ), carbonate ions (CO3 2- ), bicarbonate ion (HCO3 - ), nitrate ions (NO3 - ) and the organic matter content in the soil were used as the main factors in the orthogonal experiment.

[0054] In the embodiment of the present application, each factor is divided into at least three gradient levels. For example, with the upper and lower limits of the actual measurement data as boundaries, three concentration intervals of low, medium and high can be constructed, thereby forming an orthogonal design table with multiple factors and multiple levels.

[0055] According to the constructed orthogonal test table, the examples of the present application respectively prepare simulated soil solution systems, control the content of each salt ion and organic matter within the preset gradient, and then carry out pollutant adsorption experiments. In the examples of the present application, a batch equilibrium adsorption experiment method is preferably used to mix the target pollutant solution of known concentration with the pretreated soil sample, and react under constant temperature and constant vibration conditions until adsorption equilibrium is reached. After the reaction is completed, centrifugal separation and liquid phase analysis instruments (such as HPLC or ICP-MS) are used to measure the pollutant concentration C in the equilibrium solution. e .

[0056] According to the experimental results, combined with the initial concentration C0, reaction volume V, and soil amount M, the adsorption capacity Q of pollutants per unit mass of soil can be calculated, which is expressed as follows:

[0057]

[0058] Furthermore, the adsorption distribution coefficient K under each set of experimental conditions is calculated based on the classical linear distribution model. d , which is defined as:

[0059]

[0060] Where Q is the amount of pollutants adsorbed by the soil, C e is the concentration of pollutants in the solution after the reaction equilibrium, C0 is the initial concentration of pollutants in the solution, V is the volume of the solution, M is the mass of the soil, K d It reflects the adsorption capacity of pollutants on the soil at unit solution concentration. The larger the value, the weaker the pollutant's migration ability and the stronger its retention.

[0061] In the embodiment of the present application, a large number of K values ​​covering different salt ion combinations and organic matter content gradients can be obtained by the above method. d The data provide an experimental basis for establishing a quantitative relationship model between the adsorption coefficient and soil environmental parameters. It should be noted that during the adsorption experiment, the pH and temperature of the solution system should be kept close to the field conditions to enhance the extrapolation and field applicability of the modeling results.

[0062] In summary, this example systematically reveals the influence mechanism of various soil components on the migration behavior of pollutants by combining orthogonal design with adsorption experiments, and establishes the K d The experimental database laid a solid foundation for subsequent data fitting and model embedding.

[0063] Step 103: Use a multiple linear regression method to establish a correlation between the adsorption coefficient value and the salt concentration and organic matter content.

[0064] In the embodiment of the present application, the adsorption coefficient K under different salt ion concentrations and organic matter contents was obtained. d After obtaining the values, a quantitative relationship model between them was further established through the multivariate linear regression analysis method, providing a scientific basis for the dynamic replacement of parameters in pollutant migration simulation.

[0065] Specifically, this embodiment preferably uses the statistical analysis software SPSS, calls the multiple linear regression module therein, and conducts K d Modeling analysis between the values ​​and environmental variables. d The value was used as the dependent variable (Y), and the corresponding salt ion concentration and soil organic matter content were used as independent variables (X) to construct different forms of regression models.

[0066] In a possible embodiment, taking ofloxacin (OFL), sulfadiazine (SDZ) and carbamazepine (CBZ) as an example, the established correlation is:

[0067]

[0068] Where K d is the adsorption coefficient (L / kg); OFL, CBZ, and SDZ represent ofloxacin, carbamazepine, and sulfadiazine, respectively; C CODsoil is the organic matter content in recycled water (mg / L); Na + is the sodium ion content in the recycled water (mg / L); Mg 2+ is the magnesium ion content in the reclaimed water (mg / L); Ca 2+ is the calcium ion content in recycled water (mg / L); Cl - is the chloride ion content in recycled water (mg / L); SO4 2- is the sulfate ion content in the reclaimed water (mg / L); CO3 2- is the carbonate ion content in the reclaimed water (mg / L).

[0069] The multivariate linear regression model established in the examples of the present application can quantitatively express the influence of different soil environmental parameters on the adsorption performance of pollutants, and the model form is clear.

[0070] Step 104 , embed the correlation into the pollutant migration simulation software, replacing the input method of fixed adsorption coefficient value, and use the improved pollutant migration simulation software to simulate the vertical migration process of pollutants in soil.

[0071] In the embodiment of the present application, the adsorption coefficient K is completed dAfter the multivariate linear relationship between the adsorption coefficient and the soil environmental parameters is modeled, step 104 is further performed to embed the dynamic correlation into the pollutant migration simulation software to construct a migration simulation system in which the adsorption coefficient is dynamically adjusted with environmental changes, so as to overcome the K d The lack of applicability caused by fixed settings.

[0072] Specifically, this application prefers to use Hydrus-1D simulation software as the migration model platform. Based on its open source structure and modular input interface, it uses Python language for secondary development and module nesting. Hydrus-1D is a software widely used in soil-water-solute coupled migration analysis. In traditional usage, users need to set the pollutant distribution coefficient K in the input file. d , which remained constant throughout the simulation period and could not respond to the dynamic changes in soil salinity and organic matter conditions.

[0073] Therefore, users no longer need to input a single static K when running the improved simulation system. d Instead of using the input time series of salt, organic matter, etc., the model automatically completes the dynamic calculation and update of each step to achieve a synchronous response between the migration path of pollutants and soil conditions. Based on this improved simulation platform, in the embodiments of the present application, a simulation of the vertical migration of pollutants under different time scales and different recycled water irrigation conditions was carried out. By setting the initial concentration of representative pollutants (such as heavy metal ions or organic pollutants) and combining it with the aforementioned dynamic parameter model, the concentration change trend and enrichment location distribution in the soil profile over a period of several years are simulated. The simulation results can be used to evaluate the soil environmental safety risks under long-term irrigation conditions and provide scientific support for recycled water irrigation policies.

[0074] Furthermore, in the embodiment of the present application, the simulation results can also be combined for visualization, and the pollutant migration path, speed and blocking area can be displayed through a time-depth two-dimensional profile diagram to enhance the intuitiveness of the simulation results and the decision-making support capabilities.

[0075] from Figure 2 It can be seen that using a fixed K d In the simulation results, due to the neglect of K d The change of K value over time during long-term irrigation (gradually increasing) will overestimate the migration capacity of pollutants, so the pollutants gradually accumulate in the lower layer in the simulation results, while the concentration in the upper layer will be underestimated; while using dynamic K d value, will reflect K d The value tends to increase gradually over time, the simulation results are close to the actual situation, the pollutants are concentrated in the upper soil, and the simulation accuracy is improved.

[0076] To implement the above embodiment, the present application also proposes a vertical migration simulation device for dynamically changing adsorption coefficients under reclaimed water irrigation. The device comprises:

[0077] The parameter acquisition and calculation module is used to obtain the salt ion concentration and organic matter content in the initial soil and the recycled water to be irrigated in the study area, and calculate the salt ion concentration and organic matter content in the soil at different times based on the irrigation amount and frequency of the study area;

[0078] An adsorption experiment module is used to conduct an orthogonal experiment based on the salt ion concentration and organic matter content in the soil at different times, carry out an adsorption experiment, and calculate the adsorption coefficient values ​​under different salt concentrations and organic matter contents through the adsorption experiment;

[0079] Regression module, used to establish the correlation between adsorption coefficient values ​​and salt concentration and organic matter content using the multivariate linear regression method;

[0080] The simulation module is used to embed the correlation into the pollutant migration simulation software, replace the input method of fixed adsorption coefficient value, and use the improved pollutant migration simulation software to simulate the vertical migration process of pollutants in soil.

[0081] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0082] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0083] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0084] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0085] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0086] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0087] This application contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0088] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0089] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0090] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0091] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0092] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0093] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0094] In addition, each of the function units in each embodiment of the present application can be integrated in one processing module, or each unit can be physically present separately, or two or more units can be integrated in one module. The integrated module can be realized in the form of hardware or in the form of a software function module. When the integrated module is realized in the form of a software function module and sold or used as an independent product, it can also be stored in a computer readable storage medium.

[0095] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

[0096] It should be understood that the various forms of flow shown above can be reordered, added or deleted steps. For example, each step described in the present application can be executed in parallel, sequentially or in different order, as long as the desired results of the technical solutions of the present application can be achieved, which is not limited herein.

[0097] The above detailed description does not constitute a limitation on the scope of protection of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and replacements can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A vertical migration simulation method for the temporal dynamic change of adsorption coefficient under reclaimed water irrigation, characterized in that: The following steps are involved: Obtain the salt ion concentration and organic matter content in the initial soil and the recycled water to be irrigated in the study area, and calculate the salt ion concentration and organic matter content in the soil at different times based on the irrigation amount and frequency of the study area; An orthogonal test is conducted according to the salt ion concentration and organic matter content in the soil at different times, and an adsorption experiment is carried out to calculate the adsorption coefficient values ​​under different salt concentrations and organic matter contents through the adsorption experiment; The correlation between adsorption coefficient values ​​and salt concentration and organic matter content was established using the multiple linear regression method; The correlation is embedded in the pollutant migration simulation software to replace the input method of fixed adsorption coefficient value. The improved pollutant migration simulation software is used to simulate the vertical migration process of pollutants in soil.

2. The method according to claim 1, characterized in that The following formula is used to calculate the changes in the concentration of salt ions in the soil at different times: Where S j (t) is the concentration of salt ion j in the soil at time t, is the initial concentration of soil salt ion j, C i is the salt ion concentration of the i-th irrigation water, I i is the amount of irrigation for the i-th time, L is the leaching efficiency coefficient, n is the number of days between irrigations, and D is the soil depth.

3. The method according to claim 2, characterized in that The following formula was used to calculate the changes in soil organic matter content at different times: Where C CODsoil is the organic matter content at time t, C reclaimed is the organic matter flux input into recycled water, k input is the input conversion efficiency coefficient, k decay is the decomposition rate constant.

4. The method according to claim 3, characterized in that The adsorption coefficient values ​​under different salt concentrations and organic matter contents are calculated through adsorption experiments, including: Where Q is the amount of pollutants adsorbed by the soil, C e is the concentration of the pollutant in the solution after the reaction equilibrium, C0 is the initial concentration of the pollutant in the solution, V is the volume of the solution, and M is the mass of the soil.

5. A vertical migration simulation device for dynamic temporal changes in adsorption coefficient under reclaimed water irrigation, characterized in that: include: The parameter acquisition and calculation module is used to obtain the salt ion concentration and organic matter content in the initial soil and the recycled water to be irrigated in the study area, and calculate the salt ion concentration and organic matter content in the soil at different times based on the irrigation amount and frequency of the study area; An adsorption experiment module is used to conduct an orthogonal experiment based on the salt ion concentration and organic matter content in the soil at different times, carry out an adsorption experiment, and calculate the adsorption coefficient values ​​under different salt concentrations and organic matter contents through the adsorption experiment; Regression module, used to establish the correlation between adsorption coefficient values ​​and salt concentration and organic matter content using the multivariate linear regression method; The simulation module is used to embed the correlation into the pollutant migration simulation software, replace the input method of fixed adsorption coefficient value, and use the improved pollutant migration simulation software to simulate the vertical migration process of pollutants in soil.

6. An electronic device, characterized in that: include: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 4 when executed by a processor.

8. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 4 when executed by a processor.

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