Method and device for determining permeability coefficient of aquifer under the influence of regional groundwater extraction

Abstract

The present invention discloses a method and device for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction. The present invention adopts an in-situ standpipe permeameter for measurement, controls the water head of the standpipe and sediment at the same time, determines parameters using a nonlinear regression function solver, and calculates the hydraulic permeability coefficient according to Darcy's law; the method obtains parallel analysis data from the measuring standpipe and the sediment water level gauge, analyzes the ratio of the infiltration rate and the time change rate during the measurement, optimizes the selection of the measurement time interval, and establishes an evaluation model for the permeability coefficient measurement accuracy, further ensuring the accuracy of the measured permeability coefficient. The present invention can reduce the error in the measurement of the riverbed permeability coefficient caused by the fluctuation of the groundwater level in the riverbed or coastal zone, and the parallel analysis data obtained from the measuring standpipe and the sediment water level gauge can significantly improve the measurement accuracy. The in-situ standpipe permeameter can prevent sample disturbance and has great advantages in measurement.

Description

Technical Field

[0001] The invention relates to a method and a device for determining a water-bearing layer permeability coefficient, and in particular to a method and a device for determining a water-bearing layer permeability coefficient under the influence of regional groundwater extraction, and belongs to the technical field of hydrogeological parameter measurement. Background Art

[0002] At present, there are many methods for determining the permeability coefficient of aquifers, and the precipitation head method is one of the most widely used methods. The precipitation head water injection test is mainly suitable for rock and soil layers with low permeability below the groundwater level, such as silt, clay, etc. During the water injection process, water infiltration is mainly horizontal. In practical applications, in order to simplify the calculation process, a two-dimensional seepage calculation model is generally used. In the model, the soil body is assumed to be a semi-infinite space body, the soil layer of the confined aquifer is homogeneous, the groundwater seepage is laminar flow, and the natural water level is horizontal. Calculating the permeability coefficient through the precipitation head water injection test is simple to operate, easy to implement, and has good results.

[0003] With the development of economy and society, groundwater exploitation and utilization are becoming more and more common. Groundwater extraction will cause regional groundwater level fluctuations, which will have a great impact on the determination of the vertical permeability coefficient of the nearby riverbed aquifer. Therefore, the above-mentioned precipitation head method should not be directly used to determine the permeability coefficient of the riverbed or coastal aquifer under the influence of regional groundwater extraction, and it needs to be improved to a certain extent.

[0004] like Figure 1 As shown, the most used measurement technique is the precipitation head method: a PVC pipe is placed in the sediment. The most commonly used formula for determining the hydraulic permeability coefficient is based on Darcy's law and its variants.

[0005] The precipitation head test method is an important method for determining the permeability coefficient of aquifers and is widely used. However, regional groundwater level fluctuations will have a significant impact on the determination of the vertical permeability coefficient of aquifers, and this impact is not considered in the determination of the permeability coefficient of riverbed and coastal aquifers in regional groundwater extraction. Summary of the invention

[0006] Purpose of the invention: The purpose of the present invention is to provide a method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction with accurate measurement and simple calculation; another purpose of the present invention is to provide a device for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction.

[0007] Technical solution: The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction of the present invention is applicable to riverbeds or coastal zones under the influence of regional underground water extraction, and the method comprises:

[0008] At time S1.t1, the hydraulic head H0 and the initial head h1 of the sediment are measured;

[0009] S2. Repeat the water head measurement n-1 times; the time of the last water head measurement is recorded as t n , the final measured water head is recorded as h2;

[0010] Where t is calculated by the following formula n Values:

[0011]

[0012] Among them, h a is time t a Cumulative infiltration head at [T] [L], h n is time t n Cumulative infiltration head [L] at [T], t a is an arbitrarily selected reading (1≤a≤n), t1 is the time of the first reading, t n is the time of the final reading;

[0013] S3. Calculate the hydraulic permeability coefficient K according to Darcy's law v :

[0014]

[0015] Among them, L v is the measured sediment thickness; h1 is the initial water head of the sediment; h2 is the final water head of the sediment; t1, t n are the measurement start and end time, respectively.

[0016] As a further improvement of the above scheme, in S1 and S2, an in-situ standpipe permeameter is used to measure the hydraulic head H0, the initial sediment head h1, and the final sediment head h2.

[0017] As a further improvement of the above solution, the in-situ riser permeameter includes a measuring riser and a sediment water pressure gauge, wherein a pressure gauge is suspended in the measuring riser, and the pressure gauge is connected to a data recorder placed on the top of the pipe through a wire.

[0018] As a further improvement of the above scheme, in S2, determine t n In the optimal value of, the left and right sides of formula (1) range from 0 to 1. The observed value is the same as the calculated value, that is, RMSE = 0; the measurement curve is constructed by using the rate of change of permeability and the rate of change of time, and analyzed against the ideal curve. The optimal measurement time is selected by cutting off specific times from the beginning and end of the measurement, which is directly represented by the RMSE value.

[0019] As a further improvement of the above scheme, the determination method further includes S4. self-evaluation of the measurement results, evaluating the consistency between the predicted cumulative infiltration amount and the measured cumulative infiltration amount by the following formula:

[0020]

[0021] Among them, I(m) j is the measured cumulative infiltration, I(p) j To predict cumulative infiltration, j is the number of the jth measurement out of n soil infiltration readings, and n is the number of cumulative infiltration measurements.

[0022] As a further improvement of the above scheme, in S3, the Kv value is determined by reverse iterative calculation, and the parameters are determined by a nonlinear regression function solver; S4 also includes evaluating the goodness of fit of the parameter determination process of the solver in S3 by the model efficiency EF index:

[0023]

[0024]

[0025]

[0026] in, is the average value of the observed data.

[0027] As a further improvement of the above solution, S4 also includes checking the parameter fitting result of the solver by using statistical indicators, and the statistical indicators include the sum of squares of errors SSE, the mean error ME and the root mean square error RMSE.

[0028] In another aspect, the present invention provides a device for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction using the above method, the device comprising:

[0029] A measuring module, wherein the measuring module is used to measure the hydraulic head in real time;

[0030] The measurement time determination module is used to determine the time t of the last measurement of the water head. n , and the time t n Sent to the measurement module, the measurement module outputs t n The water head h2;

[0031] The hydraulic permeability coefficient prediction module is used to receive the hydraulic head H0 at the initial moment measured by the measurement module, the initial head h1 of the sediment, and the head h2 measured for the last time; and use the nonlinear regression function solver to determine the parameters and calculate the hydraulic permeability coefficient K according to Darcy's law v .

[0032] On the other hand, the present invention provides an electronic device, comprising: a processor; a memory on which a computer program is stored, and when the computer program is run by the processor, it executes: the method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction as described above.

[0033] On the other hand, the present invention provides a storage medium having a computer program stored thereon, and the computer program is executed when the processor is running: such as the above-mentioned method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction.

[0034] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: 1) Accurate measurement. The present invention can reduce the error in measuring the riverbed permeability coefficient caused by the fluctuation of the groundwater level in the riverbed or coastal zone. The parallel analysis data obtained from the measuring standpipe and the sediment level meter can significantly improve the measurement accuracy. The in-situ standpipe permeameter can prevent sample disturbance and has great advantages in measurement.

[0035] 2) The calculation is simple. Based on Darcy's law and its variants, the present invention develops a complete and practical Microsoft Excel spreadsheet based on automatic formulas and solvers. The optimal measurement time is selected by constructing a measurement curve based on the rate of change of permeability and the rate of change of time. The estimation accuracy of Kv can be intuitively reflected by EF, ME and RMSE. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the precipitation head method in the background technology of the present invention.

[0037] Figure 2 It is a structural schematic diagram of the in-situ vertical pipe permeameter of the present invention.

[0038] Figure 3 The present invention is a flow chart of a method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction.

[0039] Figure 4 It is a comparison diagram between the present invention and the traditional method.

[0040] Figure 5 Non-dimensional graph for selecting the best measurement time.

[0041] Figure 6 It is a schematic structural diagram of a device for measuring permeability of an aquifer under the influence of regional groundwater extraction according to the present invention. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0043] An embodiment of the present invention proposes a method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction. The method obtains parallel analysis data from a measuring riser and a sediment water level gauge, analyzes the ratio of the infiltration rate and the time rate of change during the measurement, optimizes the selection of the measurement time interval, and establishes an evaluation model for the permeability coefficient measurement accuracy, thereby further ensuring the accuracy of the measured permeability coefficient.

[0044] like Figure 2-3 As shown, an embodiment of the present invention provides a method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction. The determination method is applicable to riverbeds or coastal zones under the influence of regional groundwater extraction. The measurement method uses an in-situ riser permeameter to measure the hydraulic head H0, the initial sediment head h1, and the final sediment head h2.

[0045] The determination method comprises:

[0046] At time S1.t1, the hydraulic head H0 and the initial head h1 of the sediment are measured;

[0047] S2. Repeat the water head measurement n-1 times; the time of the last water head measurement is recorded as t n , the final measured water head is recorded as h2;

[0048] S3. Calculate the hydraulic permeability coefficient K according to Darcy's law v :

[0049]

[0050] Among them, L v is the measured sediment thickness, cm; h1 is the initial water head of the sediment, i.e. the height from the initial water level of the standpipe to the groundwater level, cm; h2 is the final water head of the sediment, i.e. the height from the final water level of the standpipe to the groundwater level, cm; t1, t n are the measurement start and end time, min.

[0051] S4. Self-evaluation of measurement results.

[0052] like Figure 4As shown, the embodiment of the present invention aims at the problems existing in the precipitation head test method used in the measurement of riverbed permeability coefficient under the influence of regional groundwater extraction, and proposes an improved method for determining the permeability coefficient of riverbed or coastal aquifer based on measurement time interval optimization and measurement result self-evaluation model. The present invention adopts an in-situ riser permeameter for measurement, and controls the head of the riser and sediment at the same time, determines the parameters using a nonlinear regression function solver, and calculates the hydraulic permeability coefficient according to Darcy's law. Compared with the traditional method, the method used in the present invention has the following characteristics: 1. It is suitable for point measurement of Kv under high artificial pressure conditions caused by regional groundwater extraction; 2. It controls the head of the riser and sediment at the same time; 3. The total measurement time is within 2h, and the sediment head is measured at the beginning and end, and the analysis time is short; 4. The fitting results are evaluated by ME, RMSE, and EF.

[0053] In one embodiment, in step S1, an in-situ standpipe permeameter is used to measure the hydraulic head H0, the initial sediment head h1, and the final sediment head h2.

[0054] Specifically, the in-situ standpipe permeameter consists of a measuring standpipe 1 with an inner diameter of 107 mm and a sediment piezometer 2 with a diameter of 76 mm. The penetration depth LV (the thickness of the measured river sediment 10) is 40 cm. The piezometer 5 suspended in the pipe is submerged above the river water level 6 and is connected to the data logger 3 on the top of the pipe through a wire 4. The height from the top of the pipe to the groundwater level 7 is the hydraulic head H0, the height from the initial water level 8 of the measuring standpipe to the groundwater level 7 is the initial sediment head h1, and the height from the final water level 9 of the measuring standpipe to the groundwater level 7 is the final sediment head h2. H1 is the difference between the hydraulic head H0 and the initial sediment head h1, and H2 is the difference between the hydraulic head H0 and the final sediment head h2.

[0055] In one embodiment, step S2 further includes a method for selecting an optimal measurement time, that is, determining t n The best value of h1 and h2 is selected. In this embodiment, the groundwater level drops by at least 10 cm before and after the measurement, and the required measurement time should depend on this value. The pressure at the bottom of the riser is measured at the beginning and end of the experiment. If the fluctuation is small, a one-time parameter measurement is used, and there is no need to continuously measure h1 and h2 multiple times; if the fluctuation is large, a constant measurement time interval is selected, and the measurement data of the water level in the riser and riverbed water pressure gauge are recorded to obtain a data group.

[0056] To obtain a reliable output matrix, the calculation of Kv requires the selection of the optimal measurement period. This method is suitable for fitting the parameters of the theoretical formula to the field data. The formula is derived from the Phillip infiltration formula, which can track small changes in the infiltration rate during the measurement period and is evaluated by the root mean square error RMSE. The formula is as follows:

[0057]

[0058] Among them, h a is time t a Cumulative infiltration head at [T] [L], h n is time t n Cumulative infiltration head [L] at [T], t a is an arbitrarily selected reading (1≤a≤n), t1 is the time of the first reading, t n The time of the final reading.

[0059] For the selected measurement time, the left side of equation (1) (the change in permeability at a specific time) and the right side (the rate of change of permeability time at a specific time) range from 0 to 1. The observed value is the same as the calculated value, which is the best, that is, RMSE = 0. The measurement curve is constructed using the rate of change of permeability and the rate of change of time, and analyzed against the ideal curve (straight line y = x). The optimal measurement time is selected by truncating specific times from the beginning and end of the measurement, which is directly represented by the RMSE value.

[0060] In one embodiment, step S3 also includes an optimization modeling system for parameter determination: the hydraulic permeability coefficient is calculated according to Darcy's law, and the Kv value of any pair of head readings is estimated by the following two methods: directly taking the average and by the least square method. The Kv value is determined by reverse iterative calculation to minimize the square difference between the observed and calculated H. The present invention uses Excel's nonlinear regression function solver to determine the parameters, which is an optimization modeling system fully integrated in Microsoft Excel software. It makes it possible to perform the optimization process and generate an output matrix with the required constraints and objectives specified by the user.

[0061] In one embodiment, step S4 includes a calculation method for model evaluation: In order to evaluate the consistency of the results, the following statistical parameters are used. SSE represents the sum of squares of errors:

[0062]

[0063] Among them, I(m) j is the measured cumulative infiltration, I(p) j To predict cumulative infiltration, j is the number of the jth measurement out of n soil infiltration readings, and n is the number of cumulative infiltration measurements.

[0064] The results of the fitting process obtained by the solver are evaluated by the model efficiency (EF, %) index reflecting the goodness of fit. When the EF index reaches 100%, the predicted cumulative infiltration is the best fit to the observed value:

[0065]

[0066]

[0067]

[0068] in, is the average value of the observed data.

[0069] The analysis of residuals by this method involves mean error ME and root mean square error RMSE:

[0070]

[0071]

[0072] For the analysis of infiltration rate changes, the RMSE is described by the following formula:

[0073]

[0074] The mean error ME is used to identify points where the parameter estimates of Kv are overestimated or underestimated compared to the observed cumulative infiltration. The root mean square error RMSE is used to evaluate the change in permeability and obtain the best parameter fit. In most cases, the RMSE values ​​in formulas (9) and (10) are greater than 0. When the observed and predicted values ​​are close to or almost the same as each other, the RMSE is close to 0 or even equal to 0. In summary, the smaller the ME and RMSE values, the higher the EF value, and the more accurate the estimation of Kv.

[0075] In one embodiment, based on Darcy's law and its variants, a complete and practical Microsoft Excel spreadsheet based on automatic formulas and solvers is developed. The optimal measurement time is selected by constructing a measurement curve based on the rate of change of permeability and the rate of change of time. The estimation accuracy of Kv can be intuitively reflected by EF, ME and RMSE. The above-mentioned complete and practical Microsoft Excel spreadsheet based on the optimization modeling system for automatic formulas and solvers consists of a worksheet, a report sheet and comments if the macro fails. The worksheet consists of a menu, input data, various parameter tables for calculation, auxiliary modules of the formulas used, parameter diagrams, and results. When using, first fill in the measurement data in the blue cells in the worksheet, click the MACRO 1 button to start automatic calculation through the solver, then analyze the permeability characteristics, and then click the MACRO 2 button to start automatic calculation through the solver to obtain the optimal Kv. All results are output in the report sheet. The report sheet consists of input data, parameter diagrams and results.

[0076] The above optimization modeling system is used to perform permeability characteristics analysis, including determining the measurement time boundaries and verifying the statistical indicators of the Kv program parameter fit. Determining the measurement time boundaries includes determining the time deducted from the beginning of the measurement and the time deducted from the end of the measurement. Change t1 and t by selecting the corresponding values ​​from the time list below the worksheet. n The time in the Kv program is changed, thereby changing the measurement interval, and all parameter graphs will change automatically. The statistical indicators for checking the parameter fitting of the Kv program include the sum of squares of errors SSE, mean error ME and root mean square error RMSE. In order to obtain the best results, the RMSE value must be minimized; check SSE, ME and RMSE at the same time, and RMSE should be less than 0 and as small as possible. Figure 5 To select the best non-dimensional plot for the measurement time, the [RMSEmini] line must be close to the center line "x=y" in the plot.

[0077] The initial parameters determined by the above optimization modeling system include the sediment thickness Lv (cm) measured at the study point, the height of the top of the measuring standpipe, the elevation of the top of the riverbed pressure gauge, the data time interval (min) of the original data, the target time interval (min) selected from the time list, and the measurement data of the water level in the standpipe and the riverbed water pressure gauge (cm). The error evaluation parameters related to the entire measurement include the root mean square error RMSE, the sum of squares of the errors SSE, and the mean error ME. By changing the measurement interval, the minimum RMSE value is obtained to obtain the best result for Kv. The results of the fitting process obtained by the solver are evaluated by the model efficiency (EF, %) index reflecting the goodness of fit.

[0078] The present invention can realize the device for measuring the permeability coefficient of aquifer under the influence of regional groundwater extraction by software, hardware, firmware and any combination thereof. It is only a schematic illustration of the permeability coefficient measurement of aquifer under the influence of regional groundwater extraction provided by the present invention. Without violating the concept of the present application, the splitting, merging and adding of modules are all within the protection scope of the present application.

[0079] like Figure 6 As shown, an embodiment of the present invention provides a device 500 for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction, the device comprising:

[0080] A measurement module 510, which is used to measure hydraulic head in real time;

[0081] The measurement time determination module 520 is used to determine the time t of the last measurement of the water head. n , and the time t n Sent to the measurement module, the measurement module outputs t n The water head h2;

[0082] The hydraulic permeability coefficient prediction module 530 is used to receive the hydraulic head H0 at the initial moment measured by the measurement module, the initial head h1 of the sediment, and the head h2 measured at the last time; and use the nonlinear regression function solver to determine the parameters and calculate the hydraulic permeability coefficient K according to Darcy's law. v .

[0083] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a computer program is stored, and when the program is executed by, for example, a processor, the steps of the method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction described in any of the above embodiments can be implemented. In some possible implementations, various aspects of the present application can also be implemented in the form of a program product, which includes a program code. If the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary embodiments of the present invention described in the above-mentioned section on determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction of this specification.

[0084] In an exemplary embodiment of the present disclosure, an electronic device is also provided, which may include a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to execute the steps of the method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction described in any of the above embodiments by executing the executable instructions.

Claims

1. A method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction, characterized in that: The determination method is applicable to riverbeds or coastal zones under the influence of regional groundwater extraction, and the determination method includes: At time S1.t1, the hydraulic head H0 and the initial head h1 of the sediment are measured; S2. Repeat the water head measurement n-1 times; the time of the last water head measurement is recorded as t n , the final measured water head is recorded as h2; Where t is calculated by the following formula n Values: Among them, h a is time t a Cumulative infiltration head at [T] [L], h n is time t n Cumulative infiltration head [L] at [T], t a is an arbitrarily selected reading (1≤a≤n), t1 is the time of the first reading, t n is the time of the final reading; In S2, in determining the optimal value of tn, the left and right sides of equation (1) have a value range of 0 to 1; the observed value is the best when it is the same as the calculated value, that is, RMSE = 0; the measurement curve is constructed using the rate of change of permeability and the rate of change of time, and analyzed against the ideal curve. The optimal measurement time is selected by cutting off specific times from the beginning and end of the measurement, which is directly represented by the RMSE value; Among them, for the analysis of infiltration rate changes, RMSE is described by the following formula: S3. Calculate the hydraulic permeability coefficient K according to Darcy's law v : Among them, L v is the measured sediment thickness; h1 is the initial water head of the sediment; h2 is the final water head of the sediment; t1, t n are the measurement start and end time, respectively.

2. The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to claim 1, characterized in that: In S1 and S2, in-situ standpipe permeameters were used to measure the hydraulic head H0, initial sediment head h1, and final sediment head h2.

3. The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to claim 2, characterized in that: The in-situ vertical pipe permeameter comprises a measuring vertical pipe and a sediment water pressure gauge, wherein a pressure gauge is suspended in the measuring vertical pipe, and the pressure gauge is connected to a data recorder placed on the top of the pipe through a wire.

4. The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to claim 1, characterized in that: The determination method further comprises S4. self-evaluation of the measurement results, evaluating the consistency between the predicted cumulative infiltration amount and the measured cumulative infiltration amount by the following formula: Among them, I(m) j is the measured cumulative infiltration, I(p) j To predict cumulative infiltration, j is the number of the jth measurement out of n soil infiltration readings, and n is the number of cumulative infiltration measurements.

5. The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to claim 4, characterized in that: In S3, the Kv value is determined by reverse iterative calculation, and the parameters are determined by a nonlinear regression function solver; S4 also includes evaluating the goodness of fit of the parameter determination process of the solver in S3 by the model efficiency EF index: in, is the average value of the observed data.

6. The method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to claim 4, characterized in that: S4 also includes checking the parameter fitting results of the solver through statistical indicators, and the statistical indicators include the sum of squares of errors SSE, mean error ME and root mean square error RMSE.

7. A device for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction using the method according to any one of claims 1 to 6, characterized in that: The device comprises: A measuring module, wherein the measuring module is used to measure the hydraulic head in real time; The measurement time determination module is used to determine the time t of the last measurement of the water head. n , and the time t n Sent to the measurement module, the measurement module outputs t n The water head h2; The hydraulic permeability coefficient prediction module is used to receive the hydraulic head H0 at the initial moment measured by the measurement module, the initial head h1 of the sediment, and the head h2 measured for the last time; and use the nonlinear regression function solver to determine the parameters and calculate the hydraulic permeability coefficient K according to Darcy's law v .

8. An electronic device, characterized in that: The electronic device comprises: a processor; a memory on which a computer program is stored, and when the computer program is run by the processor, it executes: a method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to any one of claims 1-6.

9. A storage medium, characterized in that: The storage medium stores a computer program, and the computer program is executed by the processor when it is run: the method for determining the permeability coefficient of an aquifer under the influence of regional groundwater extraction according to any one of claims 1-6.

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