Water level fluctuation zone pollutant migration risk prediction method and simulation system based on capillary force dynamic monitoring

Abstract

The invention relates to the technical field of underground water environment, in particular to a water level fluctuation zone pollutant migration risk prediction method based on capillary force dynamic monitoring and a simulation system. The water level fluctuation zone pollutant migration risk prediction method based on capillary force dynamic monitoring has a capillary force multi-point dynamic monitoring function, and multi-point capillary force dynamic change data can be obtained through a moisture content monitoring device in combination with a soil moisture characteristic curve measuring device under the underground water level fluctuation condition; and the pollutant migration risk is predicted. The simulation system comprises an underground water level fluctuation automatic simulation device, a moisture content monitoring device and a soil moisture characteristic curve measuring device. The method can be used for migration behavior research and risk assessment of pollutants under the condition of underground water level fluctuation.

Description

Technical Field

[0001] The present invention belongs to the technical field of groundwater environment, and particularly relates to a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on dynamic monitoring of capillary force. Background Art

[0002] In the natural environment, groundwater is not stable. Affected by natural and human factors, dynamic changes in the groundwater level will occur. After the leakage of organic pollutants at the site, the movement in the aquifer is mainly vertical. Macroscopically, the groundwater level fluctuation plays an important regulatory role in the pollutant migration behavior, and microscopically, the capillary force plays a major role in the pollutant migration. At the same time, the changes in key factors such as the amplitude and initial fluctuation direction of the water level fluctuation make the distribution of pollutant migration complex and variable, and difficult to predict.

[0003] During the water level fluctuation process, an unsaturated zone and a saturated zone are formed in the water level fluctuation experimental column, and periodic changes in water content occur. Existing research has shown that the capillary force plays a major role in the pollutant migration behavior in the groundwater level fluctuation zone. However, the currently publicly reported research cannot monitor the dynamic changes of multi-point capillary force in real time, and there is no method for predicting the potential risk of pollutants based on capillary force, which restricts the in-depth analysis of the microscopic action mechanism of pollutants and the risk assessment work during the water level fluctuation process.

[0004] Therefore, in view of the above problems, it is urgent to develop a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on dynamic monitoring of capillary force, which has the functions of automatic water level fluctuation and multi-point dynamic monitoring of capillary force, can predict the potential risk of pollutants based on capillary force, and promote the research on the pollutant migration mechanism and potential risk assessment under the water level fluctuation scenario. Summary of the Invention

[0005] The present invention provides a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on dynamic monitoring of capillary force, which solves the deficiencies of the prior art and meets the requirements of research equipment for the migration mechanism and risk assessment prediction of organic pollutants in the groundwater level fluctuation zone.

[0006] The technical solution of the present invention is as follows: Construct a simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on capillary force monitoring data; Carry out multi-gradient water level fluctuation simulation experiments, monitor the pollutant concentrations at different sampling points in the water level fluctuation experimental column of the simulation system, and calculate the pollutant migration risk index; the calculation formula of the pollutant migration risk index is: In the formula, M bot and M equ are respectively the masses of pollutants remaining in the sampling holes at the bottom of the water level fluctuation experimental column and entering the equilibrium column at the end of the experiment, Mi Initial mass of pollutants introduced into the experimental column with water level fluctuations; Monitor soil moisture content in real time at multiple points, obtain the soil water characteristic curve, establish the corresponding relationship between the multi-point moisture content data and capillary force, and realize the dynamic monitoring of capillary force at multiple points; Based on the dynamic monitoring data of capillary force at multiple points and the corresponding pollutant migration risk index, calculate the capillary force impulse during the water level fluctuation process, and establish the correlation between capillary force, its generated impulse and pollutant migration risk index. The calculation formula of the capillary force impulse during the water level fluctuation process is as follows: Where I is the capillary force impulse during the water level fluctuation process, F is the capillary force during the water level fluctuation process, Δt is the action time of the capillary force, m is the mass of the object, and Δv is the change in the velocity of the object; Use Gaussian function fitting to construct a prediction model of pollutant migration risk index based on capillary force monitoring data, and form a method for predicting pollutant migration risk in the water level fluctuation zone.

[0007] A simulation system for pollutant migration risk in the water level fluctuation zone based on dynamic monitoring of capillary force, which includes an automatic simulation device for underground water level fluctuations, a moisture content monitoring device and a device for measuring the soil water characteristic curve.

[0008] The automatic simulation device for groundwater level fluctuation includes: The water level monitoring pipe 1 is a plexiglass pipe with a length of 60 cm, an inner diameter of 1 cm, and an interface at the bottom; The water level fluctuation experiment column 2, the water level regulation column 7, and the water storage column 13 are all plexiglass columns with a length of 60 cm and an inner diameter of 10 cm; Fill the water level fluctuation experiment column 2 with the medium that meets the experimental requirements. Gradually pour the medium into the column and gently compact it until the entire column is filled to ensure uniformity; There are 11 sampling holes 5 on the left side of the water level fluctuation experiment column 2. The diameter of the sampling hole is 3 mm, and the spacing is 5 cm; Connect 3 moisture content sensors 4 to the interface on the right side of the water level fluctuation experiment column 2, and install them at the positions of 15 cm, 30 cm, and 45 cm below the top respectively, and connect to the computer server 16; Connect the bottom interfaces of the water level monitoring pipe 1, the water level fluctuation experiment column 2, the water level regulation column 7, and the water storage column 13 through fluororubber hoses 6 to establish a hydraulic relationship; Connect the bottom ends of the water level regulation column 7 and the water storage column 13 to the air-hole water level regulation column screw cap (bottom) 10 and the air-hole water storage column screw cap (bottom) 14 respectively; Connect the water level fluctuation experiment column screw cap (top) 3 to the top of the water level fluctuation experiment column 2, the air-hole water storage column screw cap 8 to the top of the water level regulation column 7, and the air-hole water storage column screw cap 12 to the top of the water storage column 13. The diameter of the air holes is about 3 mm and they are equipped with interfaces, and can be connected to the polytetrafluoroethylene gas sample bag 18 to form an airtight system; Fill the water level regulation column 7 and the water storage column 13 with water. Control the water volume of the water level fluctuation experiment column 2 and the water level regulation column 7 through the programmable peristaltic pump 9, and observe the real-time water level of the water level fluctuation experiment column 2 through the water level monitoring pipe 1, so as to realize the precise regulation of the water level of the water level fluctuation experiment column 2. Among them, the length, inner diameter, sampling hole diameter, sampling hole spacing, and moisture content sensor position of each part can be adjusted according to specific experimental requirements.

[0009] In the automatic simulation device for groundwater level fluctuation, the water level fluctuation is realized through the programmable peristaltic pump 9 and the computer server 16. The programmable peristaltic pump has an RS485 interface and is compatible with the Modbus protocol. Combined with the computer server, it can realize functions such as automatic start and stop, forward and reverse rotation, full speed, flow rate adjustment, and automatic water level fluctuation.

[0010] The moisture content monitoring device includes a moisture content sensor 4, an environmental monitoring host 15, and a computer server 16. This system can obtain soil moisture content data in real time and connect to the computer server to store and display the data.

[0011] The device for measuring the soil water characteristic curve includes a fritted funnel 19, a fluororubber hose 20, and a glass capillary tube scale 21. Establish a hydraulic connection between the medium in the fritted funnel and the hanging glass water column through the internal porous plate to transmit the hydrostatic pressure and establish the relationship curve between the moisture content and the capillary force.

[0012] A method for predicting the migration risk of pollutants in the water level fluctuation zone based on dynamic monitoring of capillary force and the usage method of the simulation system are as follows:

[0013] 1. Connect the water level monitoring tube, water level fluctuation experimental column, water level regulation column, and water storage column through fluororubber hoses; fill the water level fluctuation experimental column with a medium that meets the experimental requirements; connect a polytetrafluoroethylene gas sample bag to the tops of the water level fluctuation experimental column, water level regulation column, and water storage column; connect a moisture content sensor to the right side of the water level fluctuation experimental column and connect it to the environmental monitoring host and computer server.

[0014] 2. According to the experimental design, add simulated groundwater to the water level regulation column and water storage column, connect the tops of the water level fluctuation experimental column, water level regulation column, and water storage column to a polytetrafluoroethylene gas sample bag filled with air, and place a programmable peristaltic pump between the water level regulation column and water storage column to regulate the water volume between the columns.

[0015] 3. According to the experimental requirements, inject the target pollutant into the sampling hole on the side of the water level fluctuation experimental column, calculate the required flow rate, flow volume, time, and experimental period according to the experimental requirements, control the water level fluctuation program, and regulate the water level of the water level fluctuation experimental column through a programmable peristaltic pump; one experimental period includes four steps, and the fluctuation sequence of first decreasing and then increasing is as follows: The first water level lowering stage: The initial water level is controlled at a certain scale position inside the water level fluctuation experimental column, and the water level of the water level fluctuation experimental column is regulated through a programmable peristaltic pump to move downward at a constant rate. The first water level raising stage: When the water level reaches the target scale position, the programmable peristaltic pump automatically reverses its direction to make the water level of the water level fluctuation experimental column move upward at a constant rate. The continuous water level raising stage: When the rising height reaches the target water level scale, the programmable peristaltic pump automatically reverses its direction to make the water level of the water level fluctuation experimental column move downward at the same speed. The second water level lowering stage: The water level of the water level fluctuation experimental column moves downward at a constant rate. When the water level moves to the initial position, one cycle of the experiment is completed; during the experiment, collect the contaminated solution and record the moisture content data through the moisture content monitoring device. Among them, the water level fluctuation method can be adjusted according to specific experimental requirements.

[0016] 4. Establish the soil moisture characteristic curve of the medium inside the water level fluctuation experimental column through the soil moisture characteristic curve measuring device to determine the corresponding relationship between the moisture content at multiple points inside the water level fluctuation experimental column and the capillary force.

[0017] 5. Calculate the pollutant migration risk index by collecting the concentration data of the contaminated solution.

[0018] 6. Obtain the corresponding relationship between the capillary force in different experimental groups, the impulse generated by it, and the pollutant migration risk index.

[0019] 7. Construct a prediction model for the pollutant migration risk index based on capillary force monitoring data by using Gaussian function fitting, clarify the strength relationship of the driving effect of capillary force on pollutants, and realize the prediction of the potential risk index of pollutants based on capillary force.

[0020] This invention patent claims to protect a method for predicting the pollutant migration risk in the water table fluctuation zone based on dynamic monitoring of capillary force and the application of the simulation system in multi-point dynamic monitoring of capillary force. It is characterized in that multi-point moisture content monitoring data in the water table fluctuation experimental column are obtained through a moisture content monitoring device, and the soil moisture characteristic curve is established in combination with a soil moisture characteristic curve measuring device to obtain the corresponding relationship between the moisture content and capillary force in the water table fluctuation experimental column, so as to realize multi-point dynamic monitoring of capillary force.

[0021] At the application level of risk assessment, this invention patent claims to protect a method for predicting the pollutant migration risk in the water table fluctuation zone based on dynamic monitoring of capillary force and the application of the simulation system in evaluating and predicting the potential risk of pollutants. It is characterized in that the potential risk is calculated by using the potential risk index formula through monitoring the pollutant concentration at the sampling hole. The formula is as follows: In the formula, M bot and M equ are respectively the masses of pollutants remaining at the bottom layer of the water table fluctuation experimental column (the area 55 - 60 cm below the top of the water table fluctuation experimental column) and entering the equilibrium column at the end of the experiment, and M i is the initial mass of the introduced pollutants. Among them, the potential risk index can be defined as the risk of downward migration of pollutants in the water table fluctuation zone. A prediction model for the pollutant migration risk index based on capillary force monitoring data is constructed by using Gaussian function, and the capillary force, its generated impulse and the pollutant migration risk index are correlated. The relationship between capillary force and the pollutant migration risk index is explored by using this simulation system in combination with the prediction model equation, so as to clarify the strength relationship of the driving effect of capillary force on pollutants. The calculation formula for the capillary force impulse I during the water table fluctuation process is as follows: Among them, F is the capillary force during the water table fluctuation process, Δt is the acting time of the capillary force, m is the mass of the object, and Δv is the change in the velocity of the object.

[0022] The advantages of a method for predicting the pollutant migration risk in the water table fluctuation zone based on dynamic monitoring of capillary force and the simulation system provided by the present invention compared with the prior art are as follows:

[0023] 1. Based on the construction of the relationship between capillary force and pollutant migration risk index during the water level fluctuation process by Gaussian function fitting, the relationship between the driving effect of capillary force on pollutants is clarified, and a method for predicting pollutant risk based on capillary force is realized. The present invention obtains the dynamic data of multi-point capillary force during the water level fluctuation process through a moisture content monitoring device combined with a soil water characteristic curve measuring device, has the function of real-time dynamic monitoring of the moisture content and capillary force inside the water level fluctuation experimental column, constructs a Gaussian function, realizes the risk prediction method based on capillary force, and uses this simulation system to explore the relationship between the amplitude of groundwater level fluctuation, capillary force and pollutant migration risk index, so as to study the relationship between the driving effect of capillary force on pollutants and the resulting pollution risk. This method and simulation system have important scientific research significance in studying the migration mechanism and risk assessment of pollutants during the water level fluctuation process, have strong product development value and good market application prospects.

[0024] 2. The existing publicly available groundwater level fluctuation simulation devices usually need to manually or with the help of a complex control system to regulate the direction of water level fluctuation. The present invention uses a programmable peristaltic pump to realize the automatic control of water level fluctuation, improving the experimental efficiency and accuracy. In the device design, the present invention is equipped with a water level monitoring tube, which can read the real-time water level more sensitively, avoiding the interference of the built-in water level gauge on the water level fluctuation to the experimental accuracy. In addition, the programmable peristaltic pump is used to accurately control indicators such as the water level fluctuation rate, direction, and amplitude, and different water level fluctuation programs can be set; among them, the groundwater level fluctuation mode of this simulation device is indirect fluctuation, which can reduce the impact of hydraulic shock on soil samples and is more in line with the actual scenario.

[0025] 3. The traditional water level fluctuation experimental simulation device lacks the collection and monitoring of volatile pollutant gases. The underground water level fluctuation automatic simulation device involved in the present invention is an airtight system as a whole, and uses fluororubber hoses to connect to a polytetrafluoroethylene gas sample bag to collect the internal gas of the system, and can simultaneously explore the influence of the water level fluctuation process on pollutant volatilization.

[0026] 4. Since the groundwater level fluctuation will promote pollutants to enter the deep groundwater, the device of the present invention can evaluate the potential risk of pollutants entering the deep groundwater under different water level fluctuation scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a schematic flow chart of the present invention.

[0028] Figure 2 It is a schematic diagram of the underground water level fluctuation automatic simulation device of the present invention.

[0029] Figure 3 It is a schematic diagram of the soil water characteristic curve measuring device of the present invention;

[0030] Figure 4Measured moisture content and capillary force versus time curves for Example 1;

[0031] Figure 5 Volatile concentration of pollutants in the measured polytetrafluoroethylene gas sample bag for Example 2;

[0032] Figure 6 Pollutant potential risk assessment under different water level fluctuation scenarios for Example 3;

[0033] Figure 7 Gaussian function fitting results for Example 4;

[0034] In the figure: 1 - water level monitoring pipe; 2 - water level fluctuation experimental column; 3 - perforated water level fluctuation experimental column screw cap (top); 4 - moisture content sensor; 5 - sampling hole; 6 - fluororubber hose; 7 - water level regulation column; 8 - perforated water level regulation column screw cap (top); 9 - programmable peristaltic pump; 10 - perforated water level regulation column screw cap (bottom); 11 - water level control fluororubber hose; 12 - perforated water storage column screw cap (top); 13 - water storage column; 14 - perforated water storage column screw cap (bottom); 15 - environmental monitoring host; 16 - computer server; 17 - polytetrafluoroethylene gas sample bag valve; 18 - polytetrafluoroethylene gas sample bag; 19 - sintered glass funnel; 20 - fluororubber hose; 21 - glass capillary scale. Detailed implementation manners

[0035] The technical solutions of the present invention will be further described below in conjunction with specific implementation methods.

[0036] The following examples are only used to illustrate the present invention, but are not used to limit the protection scope of the present invention. Unless otherwise specified, the reagents and technical means used in the examples are all conventional means well known to those skilled in the art.

[0037] The experimental methods in the following examples are all conventional methods unless otherwise specified; the experimental materials used are all obtained from conventional biochemical reagent manufacturers unless otherwise specified.

[0038] Example 1: A method and simulation system for predicting the migration risk of pollutants in a water level fluctuation zone based on dynamic monitoring of capillary force

[0039] Fill the water level fluctuation experimental column with the medium meeting the experimental requirements. Gradually pour the medium into the column and gently compact it until the entire column is filled to ensure uniformity. Connect 11 sampling holes on the left side of the water level fluctuation experimental column to fluororubber hoses and use them in conjunction with water stop clips. Connect 3 moisture content sensors to the interface on the right side of the water level fluctuation experimental column, install them at positions 15 cm, 30 cm, and 45 cm below the top respectively, and connect them to a computer server. Connect the bottom interfaces of the water level monitoring pipe, the water level fluctuation experimental column, the water level regulation column, and the water storage column through fluororubber hoses. Fill the water level regulation column and the water storage column with water. Control the water volume in the water level fluctuation experimental column and the water level regulation column through a programmable peristaltic pump, and observe the real-time water level in the water level fluctuation experimental column through the water level monitoring pipe, so as to achieve precise regulation of the water level in the water level fluctuation experimental column. The soil water characteristic curve establishes a hydraulic connection between the medium in the sand core funnel, the internal porous plate, and the suspended glass water column, transmits the hydrostatic pressure, and establishes the relationship curve between the moisture content and the capillary force. Among them, by lowering the height of the glass capillary scale, trigger the drainage of the medium and record the drainage volume until the dehydration stops to obtain the desorption curve. By gradually raising the height of the glass capillary scale, trigger the water absorption of the medium, record the liquid volume in the glass capillary scale until the medium is completely saturated with water to obtain the sorption curve. Record the moisture content and capillary force data at each of the above time points and establish a direct relationship between the two.

[0040] In this Example 1, three scenarios are set. In Scenarios I and II, the water level in the water level fluctuation experimental column is moved 15 cm in 12 hours through a programmable peristaltic pump, that is, the flow rate of the peristaltic pump is 2.22 mL / min, to ensure that the water level movement rate in the water level fluctuation experimental column is 1.25 cm / h. In Scenario III, the water level in the water level fluctuation experimental column is moved 25 cm in 12 hours through a programmable peristaltic pump. Conduct multi-point real-time dynamic monitoring of the moisture content and the capillary force, where the capillary force is expressed by the pressure generated by a water column with a diameter of 1 cm. Table 1

[0041] This study, based on the moisture content data of the water level fluctuation experimental column and the corresponding relationship between the moisture content and the capillary force obtained by the soil water characteristic curve measuring device, analyzes and fits the sorption curve and the desorption curve through the RETC software developed by van Genuchten et al. of the United States Salinity Laboratory, constructs a soil water characteristic curve model, establishes the corresponding relationship between the moisture content and the capillary force changing with time, and fits to obtain the multi-point dynamic capillary force data of the water level fluctuation experimental column.

[0042] Figure 4It is a graph showing the variation of soil water content and capillary force at multiple points in the water level fluctuation experimental column over time. In this embodiment, the dynamic changes of water content and capillary force at multiple points in the water level fluctuation experimental column are explored; the water content at depths of 15, 30, and 45 cm in the water level fluctuation experimental column is measured by the water content rate, and the results show that the periodic fluctuation of the groundwater level will cause periodic changes in water content and capillary force; the capillary force decreases with the increase of water content; the capillary force enables the porous medium to maintain a minimum water content rate of about 15%; and there is a statistically significant correlation between the change rate of water content rate and the amplitude of groundwater level fluctuation.

[0043] Comparing Scenario II with a groundwater fluctuation amplitude of 30 cm and Scenario III with a fluctuation amplitude of 50 cm, the results show that the greater the amplitude of groundwater level fluctuation, the more significant the changes in water content rate and capillary force. At the same spatial position in the water level fluctuation experimental column, compared with Scenario II, the change rate of water content rate in Scenario III increases significantly. Specifically, at a depth of 30 cm in the water level fluctuation experimental column, the time point when the water content rate starts to decline in Scenario III is advanced by about 2 hours. At a depth of 45 cm in the water level fluctuation experimental column, as the groundwater fluctuation amplitude decreases from 50 cm to 30 cm, the minimum water content rate decreases from 45.9% to 23.2%. The above data show that different groundwater level fluctuation scenarios have different degrees of influence on the change of capillary force; compared with a groundwater level fluctuation amplitude of 30 cm, a 50 cm groundwater level fluctuation amplitude can cause more significant changes in water content and capillary force. The greater the groundwater fluctuation amplitude, the greater the driving force for the downward migration of pollutants.

[0044] Example 2: An application example of a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on dynamic monitoring of capillary force in exploring the influence of the water level fluctuation process on the pollutant volatilization amount

[0045] The difference from Example 1 is that: at the top of the water level fluctuation experimental column, a screw cap (top) of the water level fluctuation experimental column is connected, at the top of the water level regulation column, a screw cap of the water storage column with air holes is connected, and at the top of the water storage column, a screw cap of the water storage column with air holes is connected, and a polytetrafluoroethylene gas sample bag is connected to form an airtight system; before conducting the water level fluctuation experiment, the water level fluctuation experimental column is saturated with water, and the water level is stabilized at a depth of 30 cm. 150 mg of toluene and dichloromethane are injected through a sampling needle, and four water level fluctuation scenarios as shown in Table 2 are carried out. At the end of the experiment, the pollutant concentration in the polytetrafluoroethylene gas sample bag at the top of the water level fluctuation experimental column is measured by pre-concentration-gas chromatography mass spectrometry (GC / MS) to evaluate the influence of different water level fluctuation scenarios on the pollutant volatilization amount. Table 2

[0046] As Figure 5As shown, as the amplitude of water level fluctuation increases from 0 to 50 cm, the concentrations of toluene and dichloromethane gases collected at the top of the water level fluctuation experimental column increase from 11.88 and 12.79 μg / m 3 to 24.64 μg / m 3 and 44.76 μg / m 3 .

[0047] The above results show that dichloromethane has a stronger volatilization ability than toluene, and an increase in the amplitude of the groundwater level fluctuation can promote the volatilization of volatile organic compounds.

[0048] Example 3 Application of a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on capillary force dynamic monitoring in the assessment of the potential risk of pollutants during the groundwater level fluctuation process

[0049] The difference from Example 2 is that the contaminated solutions in the water level fluctuation experimental column and the water level regulation column are collected every 1 / 4 cycle, the target pollutant concentrations of the collected samples are measured by GC-MS, the pollutant mass distribution in each area of the experimental column is calculated, and the risk indices in different scenarios are calculated using the method for assessing the potential risk of water level fluctuation pollutants. The scenarios shown in Table 3 are carried out in this example: Table 3

[0050] According to the US Environmental Protection Agency's drinking water standards and health advisory reports, the maximum contaminant levels of toluene and dichloromethane are 1.000 and 0.005 mg / L respectively, and the corresponding warning values of toluene and dichloromethane under the groundwater fluctuation scenario are 1.570% and 0.009% respectively; the risk indices of pollutants in the scenarios involved in the experiment are as Figure 6 shown. In all scenarios, the potential risk index of dichloromethane is 10 times that of toluene, indicating that the potential risk of dichloromethane is greater than that of toluene under the water level fluctuation condition; a large amplitude of groundwater level fluctuation (Scenario VIII) leads to a higher potential risk index: comparing Scenario VI with Scenario VIII, the potential risks of toluene and dichloromethane increase by about 10 times and 2 times respectively under the large amplitude groundwater level fluctuation scenario.

[0051] Example 4: Application of a method and simulation system for predicting the migration risk of pollutants in the water level fluctuation zone based on capillary force dynamic monitoring in predicting the migration risk of pollutants based on capillary force

[0052] Based on Examples 1-3, the corresponding relationships among the amplitude of water level fluctuation, capillary force, and the risk index of pollutants in different scenarios were obtained. In this example, the capillary force, the impulse I generated by it, and the pollutant migration risk index were correlated. The simulation system was used to explore the relationship between the amplitude of groundwater level fluctuation and the capillary force, and to study the relationship between the amplitude of groundwater level fluctuation and the strength of the driving effect on pollutants. The impulse I generated by the capillary force during the water level fluctuation process was calculated by the following formula: I = FΔt = mΔv where F is the capillary force during the water level fluctuation process, Δt is the time of the capillary force action, m is the mass of the object, and Δv is the change in the object's velocity. In this study, the capillary force impulse is Figure 4 the area enclosed by the capillary force and the curve with the x-axis in, that is, it conforms to the formula:

[0053] By conducting experimental scenarios with different amplitudes of water level fluctuation, the relationships among the capillary force, capillary force impulse, and pollutant migration risk during the experiment were explored. Since dichloromethane has a stronger migration ability and is more sensitive in the water level fluctuation scenario, in this example, the risk index of dichloromethane was taken as the target, and the capillary force at the middle position of the water level fluctuation experimental column was taken as the object to deduce the corresponding relationship among the capillary force - capillary force impulse - pollutant migration risk index. Among them, the pressure of a 1-cm capillary water column is equal to 98.0638 pascals (Pa), and the force generated in the experimental column is 0.77 N. The corresponding relationship shown in Table 4 was obtained: Table 4 Measured data set of the relationship between capillary force and pollutant risk index

[0054] A prediction model equation for the pollutant migration risk index based on capillary force monitoring data was constructed using a Gaussian function. Using matlab and the Gaussian function functional module, the samples were split into a fitting data set and a test data set, and the existing data was used for fitting. The fitting curve is as Figure 7 shown, and the general model equation was obtained: f(x) = a1*exp(-((x - b1) / c1)^2) + a2*exp(-((x - b2) / c2)^2), where a1 = 52.08, b1 = 609.7, c1 = 156.8, a2 = 5.3, b2 = 410, c2 = 18.73, and the correlation coefficient is 0.9984, and the fitting effect is good. The test result error of the test data set is less than 1%.

[0055] By inputting the known capillary force impulse as the independent variable into the general model equation, the pollutant migration risk index can be obtained, realizing the prediction of the pollutant migration risk index based on the capillary force under different amplitudes of water level fluctuation.

[0056] The applicant declares that the present invention illustrates the detailed features and detailed methods of the present invention through the above-mentioned embodiments, but the present invention is not limited to the above-mentioned detailed features and detailed methods, that is, it does not mean that the present invention must rely on the above-mentioned detailed features and detailed methods to be implemented. Those skilled in the art should understand that any improvement to the present invention, the equivalent substitution of the components selected for the present invention, the addition of auxiliary components, the selection of specific methods, etc., all fall within the protection scope and the disclosure scope of the present invention.

Claims

1. A method for predicting the risk of pollutant migration in a water level fluctuation zone based on dynamic capillary force monitoring, characterized in that: The method comprises the following steps: Construct a simulation system to predict the risk of pollutant migration in water level fluctuation zones based on capillary force monitoring data; Carry out multi-gradient water level fluctuation simulation experiments, monitor the pollutant concentrations at different sampling points of the water level fluctuation experimental column in the simulation system, and calculate the pollutant migration risk index; Real-time multi-point monitoring of soil moisture content, obtaining soil moisture characteristic curve, establishing the corresponding relationship between multi-point moisture content data and capillary force, and realizing multi-point dynamic monitoring of capillary force; Based on the multi-point dynamic monitoring data of capillary force and the corresponding pollutant migration risk index, the capillary force impulse during water level fluctuation is calculated, and the correlation between capillary force and its generated impulse and pollutant migration risk index is established; Gaussian function fitting is used to construct a pollutant migration risk index prediction model based on capillary force monitoring data, forming a pollutant migration risk prediction method in the water level fluctuation zone.

2. According to claim 1, a method for predicting the risk of pollutant migration in a water level fluctuation zone based on dynamic capillary force monitoring, characterized in that: The calculation formula of the pollutant migration risk index is: Where M bot and M equ are the pollutant masses remaining in the sampling hole at the bottom of the water level fluctuation experimental column and entering the equilibrium column at the end of the experiment, M i is the initial mass of pollutants introduced into the water level fluctuation experimental column.

3. The method for predicting the risk of pollutant migration in a water level fluctuation zone based on dynamic capillary force monitoring according to claim 1, characterized in that: The calculation formula of the capillary force impulse in the water level fluctuation process is as follows: Among them, I is the capillary force impulse during the water level fluctuation process, F is the capillary force during the water level fluctuation process, Δt is the time of capillary force action, m is the mass of the object, and Δv is the change in the object's velocity.

4. A water level fluctuation zone pollutant migration risk simulation system based on capillary force dynamic monitoring, characterized in that: The system comprises an automatic simulation device for groundwater level fluctuation, a moisture content monitoring device and a soil moisture characteristic curve measuring device; the automatic simulation device for groundwater level fluctuation comprises four parts: a water level fluctuation experimental column, a water level regulating column, a water storage column and a water level monitoring pipe; both sides of the water level fluctuation experimental column are provided with sampling holes and monitoring holes at certain intervals, the sampling holes are connected to fluororubber hoses and are equipped with water stop clamps, the tube body of the water level monitoring pipe is marked with scales, the bottom end is connected to the water level fluctuation experimental column through a fluororubber hose, and the top ends of the water level fluctuation experimental column, the water level regulating column and the water storage column are connected to a polytetrafluoroethylene gas sample bag; the moisture content monitoring device comprises a moisture content sensor, an environmental monitoring host and a computer server; the soil moisture characteristic curve measuring device comprises a sand core funnel, a fluororubber hose and a glass capillary ruler.

5. Application of the method and simulation system for predicting the risk of pollutant migration in a water level fluctuation zone based on dynamic monitoring of capillary force as described in any one of claims 1 to 4 in evaluating and predicting the potential risk of pollutants in a water level fluctuation process.

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