Two-dimensional large-scale soil water experimental system flux imaging method and device

Abstract

The present invention provides a flux imaging method and device for a two-dimensional large-scale soil water experiment system. The method includes: Step 1, continuously monitoring the state variables in the soil at each monitoring point through the physical quantity monitoring units buried in the soil in the two-dimensional experiment system. The state variables include water content and soil matrix potential; Step 2, establishing a parameter t jk (l φ ) that reflects the indicative relationship between the monitoring points; Step 3, using the state variable change matrix T(l φ ) to characterize the state variable changes of all monitoring points; by taking the difference of the monitoring results of the state variables at different times, solving r jk,φ , and determining the state variable change matrix T(l φ ); Step 4, correlating the vector rates and the state variable change rate matrices of all monitoring points to identify the flux transmission paths; Step 5, solving for W. For any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and the topological points with the largest W are connected, thereby realizing fluidity correlation and imaging analysis.

Description

Technical Field

[0001] The present invention belongs to the technical field of experiments and monitoring of soil water movement and its associated processes, and particularly relates to a method and device for flux imaging of a two-dimensional large-scale soil water experiment system. Background Art

[0002] Soil water is the direct water source for plants and also the direct driving force for the migration and transformation of nutrients and pollutants in the soil. The current soil water simulation experiment systems mainly estimate soil water movement by monitoring state variables such as soil water content and matrix potential, lacking direct monitoring methods and data analysis means for soil water movement and its associated processes. On the basis of state variable monitoring, it is very important to realize the analysis of the flow dynamic process for the study of soil water movement and its associated processes. For example, pollutants always accumulate in low-flow areas. Obviously, compared with the monitoring of state variables, understanding the flux and mastering the migration and transformation characteristics of pollutants are of great significance for realizing soil pollutant treatment. In addition, due to the mutual influence of state variable changes between points and the high nonlinearity of soil water movement, another important disadvantage of the state variable monitoring method is that it is difficult to understand the global relationship between soil water changes and movement. Summary of the Invention

[0003] The present invention is made to solve the above problems, and aims to provide a method and device for flux imaging of a two-dimensional large-scale soil water experiment system, which can directly perform data analysis on soil water movement and its associated processes, and provide direct method support for upgrading the experimental method of soil water from state monitoring to dynamic monitoring.

[0004] To achieve the above object, the present invention adopts the following scheme:

[0005] <Method>

[0006] The present invention provides a method for flux imaging of a two-dimensional large-scale soil water experiment system, which is characterized by including the following steps:

[0007] Step 1, continuously monitor the state variables in the soil at each monitoring point (where the physical quantity monitoring unit is located) through the physical quantity monitoring units buried in the soil in an array in the two-dimensional experiment system, and the state variables include water content and soil matrix potential;

[0008] Step 2, establish a parameter reflecting the indicative relationship between the monitoring points t jk ( l φ );

[0009] Any monitoring point j For other monitoring points k Of the state variables xThe impacts of the changes are manifested in two aspects: (1) the topological association between measurement points, and (2) the flux transfer between measurement points, which is expressed by the formula:

[0010] ;

[0011] In the formula, is the relative distance between monitoring points in the direction and the Euclidean distance between two points j and k ; I represents the topological relationship between positions. When the distance between two positions is less than the product of the scalar value of the vector flow velocity in the direction and the monitoring time ( +1 - T ), there is a topological relationship, T j = 1; otherwise, there is no topological relationship, I j = 0; I j E I j ( x )] is equivalent to the volume of the region with topological relationship to the monitoring points in the entire flow region; ; During a monitoring period, the start time and end time are T and T +1 respectively. According to the monitoring results of soil matrix potential, the vector flow velocities of each monitoring point at each moment are:

[0012] ;

[0013] In the formula, v is the vector flow velocity of this monitoring point, h is the soil matrix potential, K x , K z is the hydraulic conductivity of the soil along the x, z direction;

[0014] Step 3, use the state variable change matrix to characterize the changes in state variables of all monitoring points:

[0015] ;

[0016] In the formula, N is the number of monitoring points; using the exponential form to characterize the non - linear transport process of soil flow under unsaturated soil conditions, the state variable change matrix is expressed as:

[0017] ; ​

[0018] In the formula, is the state variable change rate matrix: ; is the change rate of the indicator variable in the direction ; , T is the time;

[0019] By taking the difference of the monitoring results of the state variables at different times, is solved to determine the state variable change matrix ;

[0020] Step 4, correlate the vector rate and the state variable change rate matrix of all monitoring points to identify the flux transmission path:

[0021] ;

[0022] In the formula, is the time derivative of the water content at the monitoring point; W is the weight, characterizes the weight relationship between the state change and the flux change of each monitoring point. The greater the weight relationship, the more significant the flow relationship between the monitoring points;

[0023] Step 5, solve W . For any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and the topological points with the largest W are connected to achieve fluidity correlation and imaging analysis.

[0024] Preferably, the flux imaging method of the two-dimensional large-scale soil water experimental system provided by the present invention may further have the following characteristics: in Step 1, the physical quantity monitoring unit includes a water content sensor and a soil matrix potential sensor capable of continuously monitoring the water content and the soil matrix potential.

[0025] Preferably, the flux imaging method of the two-dimensional large-scale soil water experimental system provided by the present invention may further have the following characteristics: in Step 3, according to the monitoring data (measured data), the implicit difference method is used to solve , where is the time difference between the T +1 moment and the T moment; in Step 4, according to the monitoring data, the difference method is used to solve .

[0026] Preferably, the flux imaging method for the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following characteristics: in step 3, the relationship between the state change amount and the flux is expressed as a mass relationship with equilibrium conditions, including both the water content change caused by the change in water flux in the soil and the energy relationship with equilibrium conditions, that is, the soil temperature change caused by heat flux transmission.

[0027] Preferably, the flux imaging method for the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following characteristics: in step 5, the following optimization problem is solved:

[0028] ;

[0029] wherein, O represents the objective function, and the subscripts M and S respectively represent the comparison between the measured and calculated transfer values, T is the number of monitored time periods; through repeated iteration, the highest consistency between the state changes and flux changes among all monitoring points is achieved, and the objective function value is minimized.

[0030] <System>

[0031] Furthermore, the present invention also provides a flux imaging device for the two-dimensional large-scale soil water experiment system, which can automatically implement the above <Method>. It is characterized by including:

[0032] A monitoring unit that continuously monitors the state quantities in the soil at each monitoring point through the physical quantity monitoring units buried in the soil in an array in the two-dimensional experiment system, and obtains monitoring data. The state quantities include water content and soil matrix potential;

[0033] An indication relationship construction unit that establishes a parameter t jk ( l φ ) that reflects the indication relationship between monitoring points; the influence of the state quantity j of any monitoring point k on other monitoring points x is manifested in two aspects: (1) the topological correlation between each measuring point, and (2) the flux transmission between the measuring points, which is expressed by the formula:

[0034] ;

[0035] wherein, is the relative distance in the direction between monitoring points j and k the Euclidean distance between two points; IRepresents the topological relationship between positions, where the distance between two positions is less than the scalar value of the vector flow rate in the direction of the flow rate multiplied by the monitoring time ( T +1 - T ), there is a topological relationship, I j = 1; otherwise, there is no topological relationship, I j = 0; E I j ( x )] is equivalent to the volume of the region with a topological relationship to the monitoring point in the entire flow region; ; During a monitoring period, the start time and end time are respectively T and T +1. According to the monitoring results of soil matrix potential, the vector flow rates of each monitoring point at each moment are:

[0036] ;

[0037] In the formula, v is the vector flow rate of this monitoring point, h is the soil matrix potential, K x , K z is the hydraulic conductivity of the soil along the x, z direction;

[0038] The state quantity change characterization part uses the state quantity change matrix to characterize the state quantity changes of all monitoring points:

[0039] ;

[0040] In the formula, N is the number of monitoring points; Using an exponential form to characterize the non - linear transport process of soil flow under unsaturated soil conditions, the state quantity change matrix is expressed as:

[0041] ;

[0042] In the formula, is the state quantity change rate matrix: ; is the change rate of the indicator variable in the direction , , T is the time; By taking the difference of the monitoring results of the state variables at different times, solve to determine the state quantity change matrix ; ​

[0043] An identification unit correlates the vector rate and the state variable change rate matrix of all monitoring points to identify the flux transmission path:

[0044] ;

[0045] wherein, is the time derivative of the water content at the monitoring point; W is the weight, characterizing the weight relationship between the state change and the flux change of each monitoring point. The greater the weight relationship, the more significant the flow relationship between the monitoring points;

[0046] An imaging analysis unit solves W . For any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and the topological points with the largest W are connected to achieve fluidity correlation and imaging analysis;

[0047] A control unit is communicatively connected to the monitoring unit, the indication relationship construction unit, the state variable change characterization unit, the identification unit, and the imaging analysis unit to control their operations.

[0048] Preferably, the flux imaging device of the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following feature: an input display unit is communicatively connected to the monitoring unit, the indication relationship construction unit, the state variable change characterization unit, the identification unit, the imaging analysis unit, and the control unit, and is used for allowing a user to input operation instructions and performing corresponding displays.

[0049] Preferably, the flux imaging device of the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following feature: the input display unit displays the data, processing process, and output results obtained by each unit in the form of graphs or tables according to the operation instructions for an operator to view.

[0050] Preferably, the flux imaging device of the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following feature: the monitoring unit includes a plurality of physical quantity monitoring units, and each physical quantity monitoring unit includes a water content sensor and a soil matrix potential sensor capable of continuously monitoring the water content and the soil matrix potential.

[0051] Preferably, the flux imaging device of the two-dimensional large-scale soil water experiment system provided by the present invention may further have the following feature: the state variable change characterization unit solves according to the monitoring data by using the implicit difference method, where is T the time difference between the T +1 moment and the moment; the identification unit solves

[0052] Function and Effect of the Invention

[0053] The flux imaging method and device for the two-dimensional large-scale soil water experiment system provided by the present invention first obtain the soil state quantities at each monitoring point through the physical quantity monitoring units arranged in an array in the two-dimensional experiment system, use the indicative variable characteristics to associate the states between different monitoring points, further realize the topological association of the state index variables at multiple monitoring point positions in the form of a matrix, and through state association and position topological association, change rate analysis and flux relationship equations, the flux transmission path is analyzed, and the flow path is information spread in an imaging manner to realize the imaging analysis of the two-dimensional soil water migration flux. The present invention upgrades the experimental method of soil water from state monitoring to flux imaging method, provides method support for the transition of soil water and its associated process research from the method based on physical quantities to the method based on flux, can more effectively obtain the soil water flow characteristics in the entire flow region, scientifically monitor the soil water movement, and provide a scientific and effective decision-making basis for water conservation, agricultural non-point source pollution control, etc. Brief Description of the Drawings

[0054] Figure 1 It is a two-dimensional large-scale water movement experiment system related to an embodiment of the present invention. The intersection positions of letters A - G and numbers 1 - 7 in the figure are the layout positions of the state quantity sensors;

[0055] Figure 2 It is the monitoring result of the state quantity (soil matrix potential) at some monitoring positions related to an embodiment of the present invention;

[0056] Figure 3 It is related to an embodiment of the present invention T =Thermodynamic diagram of the state quantity indicative relationship at 20 hr;

[0057] Figure 4 It is related to an embodiment of the present invention T =Imaging result of the continuous flow path determined based on the maximum weight at 20 hr. Detailed Embodiment

[0058] The following will describe in detail the specific implementation scheme of the flux imaging method and device for the two-dimensional large-scale soil water experiment system related to the present invention with reference to the accompanying drawings.

[0059] <Example>

[0060] The flux imaging method for the two-dimensional large-scale soil water experiment system adopted in this embodiment includes the following steps:

[0061] Step 1: The monitoring point positions arranged in an array in the large-scale two-dimensional soil water experiment monitoring system adopted are as Figure 1As shown, a soil matric potential sensor and a water content sensor are arranged at each monitoring point as a physical quantity monitoring unit to continuously monitor the state quantity in the soil. In this embodiment, the soil matric potential sensor is a TensionMark sensor, and the soil water content sensor is a TDR sensor. The sensors are controlled by a CR1000X data collector to achieve synchronous monitoring and data storage.

[0062] Figure 2 For the continuous monitoring results of the soil state quantity (matric potential) at monitoring positions such as A5, B5, C2, D2, E2, E6, F1, F2, etc., at 42 positions in the two-dimensional experimental system ( Figure 1 as shown), continuous process monitoring of the changes in the soil state quantity was carried out.

[0063] Step 2: Establish the indicative relationship parameters reflecting between the monitoring points t jk ( l φ ), for any monitoring point j the influence on the state quantity of other monitoring points k is manifested in two aspects: (1) the topological correlation between the monitoring points, and (2) the flux transfer between the monitoring points, expressed as: x

[0064] (1)

[0065] In the formula, is the relative distance between the measuring points in the direction j , k and I are the Euclidean distances between two points, represents the topological relationship between positions. When the distance between two positions is less than the product of the flow velocity scalar value of the vector flow velocity in the direction T and the monitoring time ( T +1 - I ), there is a topological relationship, I j = 1; otherwise, there is no topological relationship, E j = 0. E I j ( x )] is equivalent to the volume of the region with a topological relationship to the monitoring point in the entire flow region, , in a monitoring period, the start time and the end time are T and T +1 respectively. According to the monitoring results of the soil matric potential, the vector flow velocities measured at each moment are:

[0066] ​ (2)

[0067] In the formula, v is the vector flow velocity at the monitoring point (the sensor location layout point), h is the soil matrix potential, which is determined according to the measured data. The monitoring results at some locations are as Figure 2 shown. K x , K z is the hydraulic conductivity of the soil along the x, z direction. The soil in the embodiment is sandy loam, and the hydraulic conductivity uses the measured data, K x = 2.56×10 -5 m / s, K z = 2.17×10 -5 m / s.

[0068] Taking the C4 point in Figure 1 as an example, in this embodiment, when the monitoring period is 3h, the topological relationship points include C5, D3, D5, E3 and E4.

[0069] Step 3: Use the state quantity change matrix to characterize the change of the state quantity of all monitoring points:

[0070] (3)

[0071] In the formula, N is the total number of sensors deployed in the two-dimensional experimental system; the exponential form is used to characterize the non-linear transport process of soil flow under unsaturated soil conditions, then the state quantity change matrix is expressed as:

[0072] (4)

[0073] In the formula, is the state parameter change rate matrix:

[0074] (5)

[0075] In the formula, is the change rate of the indicator variable in the direction , which is , T is time.

[0076] Solve according to the measured data using the implicit difference method, that is , where is the T +1 moment and T moment time difference. Determine the state quantity change matrix , is the distance between two monitoring points with a topological relationship.

[0077] For the C4 position, during the time period from 19hr to 20hr (see the change of the state quantity in Figure 2 ), the positions with a topological relationship in the state parameter change rate matrix are not zero, and other positions are zero. According to the monitoring results, the topological relationships of all points are superimposed, and the change of the state parameters of the entire two-dimensional flow field is represented by a heat map as Figure 3 shown. The higher the color temperature in the figure, the faster the change rate of the indication relationship T of the state quantity.

[0078] Step 4: Identify the flux transmission path by the correlation between the flux formed by the apparent rates of all monitoring points and the state change rate, and correlate the state change matrix with the apparent flux matrix at each position:

[0079] (6)

[0080] In the formula, W is the weight, is the reciprocal of the time of the water content at the measuring point, and it is directly calculated by using the difference method according to the monitoring results. According to the measured values, the difference method is used to calculate .

[0081] Step 5: Solve W , for any measuring point position, the influence of the measuring points with a topological relationship on the state variable can be determined, and the topological points with W the largest are connected, so as to realize the fluidity correlation and imaging analysis.

[0082] That is, solve the following optimization problem:

[0083] (7)

[0084] In the formula, O represents the objective function, and the subscripts M and S respectively represent the comparison between the measured and calculated transfer values, T is the number of monitoring time periods. Through repeated iteration, the highest consistency between the state changes and flux changes among all measuring points is achieved. According to the measured data, the solution result of the water flux in the soil at the moment of T = 20hr is as Figure 4 shown.

[0085] Furthermore, in this embodiment, a two-dimensional large-scale soil water experiment system flux imaging device capable of automatically implementing the above method of the present invention is also provided. The device includes a monitoring unit, an indication relationship construction unit, a state quantity change characterization unit, an identification unit, an imaging analysis unit, and an input display unit.

[0086] The monitoring department executes the content described in step 1 above. Through the physical quantity monitoring units buried in the soil in an array in the two-dimensional experimental system, the state quantities in the soil at each monitoring point are continuously monitored to obtain monitoring data.

[0087] The indication relationship construction department executes the content described in step 2 above to establish parameters reflecting the indication relationship between the monitoring points. t jk ( l φ )

[0088] The state quantity change characterization department executes the content described in step 3 above and uses the state quantity change matrix to characterize the state quantity changes of all monitoring points.

[0089] The identification department executes the content described in step 4 above to correlate the vector rate and the state quantity change rate matrix of all monitoring points to realize the identification of the flux transmission path.

[0090] The imaging analysis department executes the content described in step 5 above to solve W . For any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and the W largest topological points are connected to realize fluidity correlation and imaging analysis.

[0091] The input display department is communicatively connected to the monitoring department, the indication relationship construction department, the state quantity change characterization department, the identification department, the imaging analysis department, and the control department, and is used to allow the user to input operation instructions and perform corresponding displays. For example, the input display department can display the data, processing processes, and output results obtained by each department in the form of graphs (such as Figures 1 to 4 ) or tables for the operator to view.

[0092] The control department is communicatively connected to the monitoring department, the indication relationship construction department, the state quantity change characterization department, the identification department, the imaging analysis department, and the input display department to control their operations.

[0093] The above embodiments are merely illustrative examples of the technical solutions of the present invention. The two-dimensional large-scale soil water experiment system flux imaging method and device involved in the present invention are not limited to the content described in the above embodiments, but are subject to the scope defined by the claims. Any modification, supplement, or equivalent replacement made by those skilled in the art in the field of the present invention based on this embodiment is within the scope protected by the claims of the present invention.

Claims

1. Flux imaging method for a two-dimensional large-scale soil water experiment system, characterized in that It includes the following steps: Step 1: Continuously monitor the state variables in the soil at each monitoring point through the physical quantity monitoring units buried in the soil in an array in the two-dimensional experimental system. The state variables include water content and soil matrix potential; Step 2, establish parameters reflecting the indicative relationship between the monitoring points t jk ( l φ ); Any monitoring point j For other monitoring points k The state variables x The impact of changes is manifested in two aspects: (1) the topological correlation between measurement points, and (2) the flux transmission between measurement points, which is expressed by the formula: ； In the formula, is the relative distance between monitoring points in the direction and j the Euclidean distance between two points; k represents the topological relationship between the positions of monitoring points. When the distance between two positions is less than the product of the flow velocity scalar value of the vector flow velocity in the direction I and the monitoring time ( +1 - ), there is a topological relationship, T j = 1; otherwise, there is no topological relationship, T j = 0; I I j = 0; E I j ( x )] is equivalent to the volume of the region with topological relationship to the monitoring points in the entire flow region; ; In a monitoring period, the start time and end time are T and T +1 respectively. According to the monitoring results of soil matrix potential, the vector flow velocity of each monitoring point at each moment:​ ； In the formula, v is the vector flow velocity of the monitoring point, h is the soil matrix potential, K x , K z is the hydraulic conductivity of the soil along the x, z direction; Step 3, adopt the state variable change matrix to characterize the state variable changes of all monitoring points: ； In the formula, N is the number of monitoring points; adopting an exponential form to characterize the non-linear flow and transport process of soil under unsaturated soil conditions, the state variable change matrix is expressed as: ； In the formula, is the state quantity change rate matrix: ; is the change rate of the indicator variable in the direction , , T is time; Differentiating the monitoring results of the state variables at different times to solve and determining the state variable change matrix ; Step 4, correlate the vector rate and the state variable change rate matrix of all monitoring points to identify the flux transmission path: ； In the formula, is the time derivative of the water content at the monitoring point; W is the weight, characterizing the weight relationship between the state change and flux change of each monitoring point. The greater the weight relationship, the more significant the flow relationship between the monitoring points; Step 5, for W solve, for any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and connect W the largest topological points, thereby realizing fluidity correlation and imaging analysis.

2. The flux imaging method for the two-dimensional large-scale soil water experimental system according to claim 1, wherein: Among them, In Step 1, the physical quantity monitoring unit includes a water content sensor and a soil matrix potential sensor capable of continuously monitoring the water content and the soil matrix potential.

3. The flux imaging method for the two-dimensional large-scale soil water experimental system according to claim 1, wherein: Among them, In step 3, according to the monitoring data, the implicit difference method is used to solve , where is T the time difference between the time at the T +1 moment and the In step 4, according to the monitoring data, the difference method is used to solve .

4. The flux imaging method for the two-dimensional large-scale soil water experimental system according to claim 1, wherein: Among them, In Step 3, the relationship between the state change quantity and the flux is expressed as a mass relationship with equilibrium conditions, which includes both the change in water content caused by the change in water flux in the soil and is also applicable to the energy relationship with equilibrium conditions, such as the change in soil temperature caused by heat flux transmission.

5. The flux imaging method for the two-dimensional large-scale soil water experimental system according to claim 1, wherein: Among them, In Step 5, the following optimization problem is solved: ； In the formula, O represents the objective function, and the subscripts M and S respectively represent the comparison between the measured and calculated transfer values, T is the number of monitored time periods; through repeated iteration, the highest consistency between the state changes and flux changes among all monitoring points is achieved, and the objective function value is minimized.

6. The flux imaging device of the two-dimensional large-scale soil water experiment system is characterized in that It includes: A monitoring unit that continuously monitors the state variables in the soil at each monitoring point through the physical quantity monitoring units buried in the soil in an array in the two-dimensional experimental system, and obtains monitoring data. The state variables include water content and soil matrix potential; An indication relationship construction unit establishes parameters reflecting the indication relationship between monitoring points t jk ( l φ );Any monitoring point j For other monitoring points k The state quantity of x The influence of changes is manifested in two aspects: (1) The topological association between each measuring point, and (2) The flux transmission between measuring points, which is expressed by the formula as: ； Wherein, is the relative distance between monitoring points in the direction and the Euclidean distance between two points; j and k the Euclidean distance between two points; I represents the topological relationship between the positions of the monitoring points. When the distance between two positions is less than the product of the scalar value of the vector flow velocity in the direction and the monitoring time ( +1 - T +1 - T ), there is a topological relationship, I j = 1; otherwise, there is no topological relationship, I j = 0; E I j ( x )] is equivalent to the volume of the region where the monitoring points have a topological relationship in the entire flow region; ;​ During a monitoring period, the start time and the end time are respectively T and T +1. According to the monitoring results of soil matrix potential, the vector flow velocities of each monitoring point at each moment are as follows: ； Wherein, v is the vector velocity of the monitoring point, h is the soil matrix potential, K x , K z is the hydraulic conductivity of the soil along the x, z direction; The state variable change characterization unit uses a state variable change matrix to characterize the state variable changes of all monitoring points: ； In the formula, N is the number of monitoring points; adopting an exponential form to characterize the non-linear flow and transport process of soil under unsaturated soil conditions, the state variable change matrix is expressed as: ； In the formula, is the state variable change rate matrix: ; is the change rate of the indicator variable in the direction , , T is time; by taking the difference of the monitoring results of the state variables at different times, is solved to determine the state variable change matrix ; An identification unit correlates the vector rate and the rate matrix of the change in the state quantity of all monitoring points to identify the flux transmission path: ； In the formula, is the time derivative of the water content at the monitoring point; W is the weight, characterizing the weight relationship between the state change and flux change of each monitoring point. The greater the weight relationship, the more significant the flow relationship between the monitoring points; The imaging analysis unit solves for W For any monitoring point position, the influence of the monitoring points with topological relationships on the state variables can be determined, and by connecting W the largest topological points, fluidity correlation and imaging analysis can be achieved; A control unit that is communicatively connected to the monitoring unit, the indication relationship construction unit, the state variable change characterization unit, the recognition unit, and the imaging analysis unit, and controls their operations.

7. The flux imaging device of the two-dimensional large-scale soil water experiment system according to claim 6, characterized in that, It further includes: An input and display unit that is communicatively connected to the monitoring unit, the indication relationship construction unit, the state variable change characterization unit, the recognition unit, the imaging analysis unit, and the control unit, and is used for the user to input operation instructions and perform corresponding displays.

8. The flux imaging device for the two-dimensional large-scale soil water experimental system according to claim 7, wherein: Among them, The input and display unit displays the data, processing process, and output results obtained by each unit in the form of graphs or tables according to the operation instructions for the operator to view.

9. The flux imaging device for the two-dimensional large-scale soil water experimental system according to claim 6, wherein: Among them, The monitoring unit includes a plurality of physical quantity monitoring units, and each physical quantity monitoring unit includes a water content sensor and a soil matrix potential sensor capable of continuously monitoring the water content and the soil matrix potential.

10. The flux imaging device for the two-dimensional large-scale soil water experimental system according to claim 6, wherein: Among them, The state quantity change characterization unit solves according to the monitoring data by using the implicit difference method , where is T the time difference between the time of the T +1 moment and the The recognition unit solves using the difference method based on the monitoring data .

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