CN110874976A - Method for simulating dynamic state of underground water of karst big spring - Google Patents
Method for simulating dynamic state of underground water of karst big spring Download PDFInfo
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Abstract
The invention discloses a method for simulating the dynamic state of underground water of a karst big spring, and relates to the technical field of hydrogeology. The method adopts a tracing test and the correlation analysis of the spring water level and the observation water levels at different depths to determine the plane extension direction of the karst dominant seepage channel; and determining the vertical occurrence position of the karst pipeline through layered monitoring of the water temperature and the conductivity of underground water, and on the basis, establishing a binary structure seepage-gravitational flow coupling model to perform dynamic simulation of the spring water. The method can more accurately simulate the dynamic change process of the underground water of the karst heterogeneous medium, and provides scientific basis for accurately controlling the implementation time of the spring-protecting measure. In addition, the karst passage found by the method is not limited to the simulation of the water level of the spring water, and can provide a basis for a large number of urban underground space development projects so as to avoid damage to buildings caused by underground caverns and broken zones and protect the life and property safety of people.
Description
Technical Field
The invention relates to the technical field of hydrogeology, in particular to a method for simulating the dynamic state of underground water of a karst big spring.
Background
At present, methods for predicting groundwater dynamics mainly include a mathematical statistical method based on time series water level monitoring, an analytic method based on groundwater dynamics and a numerical method. The karst aquifer is used as a complex aquifer system and comprises a plurality of gap types such as pores, cracks, karst pipelines and small karst caves, underground water flow in a porous medium mostly meets Darcy's law, and rapid flow motion existing in the karst crack type pipeline medium cannot be simply described by the Darcy's law, so that the simulated heterogeneous karst water level of a mathematical statistics method, an analytic method, a numerical method and the like has larger deviation.
In order to protect a large karst spring and set spring-protecting measures in time, the dynamic change of the water level of a spring needs to be accurately warned in advance, and in order to improve the simulation precision of the underground water level of a heterogeneous aquifer system, an equivalent porous medium model and a pipeline flow are coupled by predecessors, so that the problem of simulation of the heterogeneity of multiple medium fields in a karst region is solved, but the method has certain defects in determining the position of a karst pipeline based on a geostatistics method and a geophysical method. If the geostatistical method has uncertainty, the geophysical method has multiple solutions.
Disclosure of Invention
In order to solve the problems, the invention provides a method for simulating the dynamic state of the underground water of the karst big spring, which determines the plane extension direction and the vertical occurrence position of a karst dominant seepage channel by adopting the layered monitoring of the water temperature and the electric conductivity in a hole, the relative analysis of the water level of the spring and the water level of an observation hole and a tracing test, and establishes a binary structure seepage-dominant flow coupling model on the basis to simulate the dynamic state of the underground water of a heterogeneous medium more accurately.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a method for simulating the dynamic state of underground water in karst spring includes such steps as providing a simulation model,
firstly, determining the spatial distribution of a water-bearing layer of the spring water supply;
1.1 determining the lateral boundary of the spring domain;
1.2 determining the vertical distribution of the aquifer supplying spring water in the range of the spring domain;
secondly, collecting basic data, wherein the basic data comprise a spring water level Hs, a spring flow B, a groundwater level H, a river water leakage R, a mining amount W and a precipitation amount P in the spring area range determined in the step 1.1;
thirdly, performing a water pumping test, and solving the permeability coefficient K of the aquifer;
fourthly, carrying out porous medium seepage simulation according to the parameters obtained in the second step and the third step;
fifthly, determining connectivity of the subsurface runoff channel by a tracing test;
5.1 determining the tracing test range by taking the length L of the longest local karst cave or underground river as a reference value, taking the karst big spring as the center and taking the length L as the radius;
5.2 Water level Observation data H of observation hole falling into tracing test rangeiEstablishing a regression equation with spring water level Hs;
5.3 obtaining the correlation coefficient R according to the regression equation2And selecting a phaseObservation hole S with maximum relevance coefficientmax；
5.4 drawing an isobaric line graph according to water level observation data of the observation holes falling into the tracing test range;
5.5 Observation holes S determined in step 5.3maxArranging an underground water level and water sample monitoring network for tracer feeding points, and detecting the concentration of the tracer as a background value;
5.6 putting a tracer into the putting points, and monitoring the concentration of the tracer at monitoring points in the monitoring network;
5.7, drawing a tracer concentration change curve chart of each monitoring point according to the monitoring data, and recording the number N of wave peaks in the tracer concentration change curve chart of the monitoring points at the spring position;
sixthly, determining the spatial distribution of the karst pipeline
6.1 monitoring the temperature and conductivity of the underground water every 2m for the drill holes in the tracing test range;
6.2 according to the monitoring result of 6.1, finding inflection points of the water temperature and the electric conductivity of the throwing point and each monitoring point;
6.3, drawing a statistical graph of the development condition of the vertical karst within the tracing test range according to the drilling data;
6.4 presetting possible karst pipelines according to the tracing test result in the fifth step;
6.5, the isobaric line diagram drawn in the step 5.3 and the vertical karst development statistical diagram drawn in the step 6.3 are combined to judge a preset karst pipeline, and the karst pipeline matched with the isobaric line diagram and the vertical karst development statistical diagram is taken as a final karst pipeline;
if the number of the final karst pipelines is equal to the number N of the wave crests in the step 5.7, continuing the next step, if the number of the final karst pipelines is less than the number N of the wave crests in the step 5.7, expanding the range of the monitoring net and/or increasing the density of the monitoring net, and repeating the operation of the step 5.5-6.5 until the number of the final karst pipelines is equal to the number of the wave crests in the step 5.7;
6.6, determining the vertical arrangement of the karst pipeline according to the karst development depth or the inflection points of the temperature and the conductivity of each monitoring point on the final karst pipeline;
and seventhly, performing dominant flow simulation on the final karst pipeline.
Further, an independent groundwater system with natural boundaries is adopted in the step 1.1, and water-resisting fracture, groundwater watershed or water-resisting stratum is selected as the polygonal boundaries of the spring domain.
Furthermore, in the second step, when the observation holes are arranged in the range of the spring area, the observation holes are arranged according to the density of 10 water level observation holes per hundred square kilometers, and the distance between the observation hole closest to the spring and the spring is less than 300 m.
And further, in the third step, carrying out regional division on the spring domain range according to geological conditions, and selecting an observation hole as a water pumping hole in each divided region.
And further, in the third step, the water pumping stabilization time is more than or equal to 4 hours.
Further, the tracer test adopts rhodamine or ammonium molybdate as a tracer.
Further, in the fifth step of tracer test, the detection standard of the tracer is 5 times over the background value of the tracer.
Furthermore, in the second step, the observation frequency of the groundwater level H, the spring water level Hs, the river water leakage R, the spring flow B and the mining volume W is once observed every five days, the observation period is 365 days, and the observation period of the precipitation P is 365 days.
Further, in the fifth step, the monitoring period of the tracer test is one year, and the monitoring frequency is once every two weeks.
The invention has the beneficial effects that:
1. determining the plane extension direction of the karst dominant seepage channel by adopting a tracing test and the correlation analysis of spring water level and observation water levels at different depths; and determining the vertical occurrence position of the karst pipeline through layered monitoring of the water temperature and the conductivity of underground water, and on the basis, establishing a binary structure seepage-gravitational flow coupling model to perform dynamic simulation of the spring water. The method can more accurately simulate the dynamic change process of the underground water of the karst heterogeneous medium, and provides scientific basis for accurately controlling the implementation time of the spring-protecting measure.
2. The karst passage found by the method is not limited to the simulation of the water level of the spring water, and can provide a basis for a large number of urban underground space development projects, so that the damage of underground karst caves and broken zones to buildings is avoided, and the life and property safety of people is protected.
3. The established underground water flow numerical model can also optimize underground water mining layout, and reasonably develop, utilize and protect underground water resources.
4. The numerical simulation of the optimal flow of the karst pipeline can effectively invert the dynamic state of the water level of the spring, and the porous medium seepage-pipeline flow coupling model more accurately simulates the dynamic change process of the water level of the Jinan spring, thereby providing scientific basis for spring protection.
5. The multifunctional teaching aid is used for education and teaching of the students and researchers and promotes the progress of the students.
Drawings
FIG. 1 is a lateral extent diagram of Baotu spring region;
FIG. 2 is a fitting graph of simulated values and actual observed values in porous medium seepage simulation;
FIG. 3 is a plan view of the isobaric line and karst pipeline positions within the tracer test range;
FIG. 4 is a molybdenum ion concentration curve graph monitored by Baotu spring monitoring points in a tracer test;
FIG. 5 is a temperature profile of S1;
fig. 6 is a graph of conductivity for S1;
FIG. 7 is a statistical chart of vertical karst development in a tracer test zone;
FIG. 8 is a geological profile of a distribution area of a karst pipeline;
fig. 9 is a fitting graph of simulated values and actual observed values in the seepage simulation and the coupling flow simulation.
Detailed Description
A method for simulating the dynamic state of the groundwater in a karst big spring comprises the following steps.
First, the spatial distribution of the aquifer of the spring supply is determined.
1.1 determining the lateral boundaries of the spring region
The simulation range of spring water dynamic adopts an independent underground water system with a natural boundary, and the polygonal boundary of the spring area selects water-resisting fracture, an underground water watershed or a water-resisting stratum.
As a specific implementation manner, in this embodiment, taking jonan as an example, the spring domain range of the Baotu spring group is determined as follows: the south boundary is the watershed water-resisting boundary of the underground water; the east boundary is a fracture water-resisting boundary of the ancestor; the west boundary is a water-resisting boundary of the Huangshan mountain range; the north boundary is a carbolite-diadsic-magma water-blocking formation, as shown in figure 1.
1.2 determining the vertical distribution of the aquifer supplying the spring water in the range of the spring domain.
Analyzing the geological conditions of the positions of the karst spring groups according to the regional hydrogeological map, determining the water-bearing stratum where the spring water is exposed, and drawing a topographic contour map and a bottom plate elevation contour map of the water-bearing stratum by combining topographic conditions, regional stratum distribution and drilling data.
Second, collecting basic data
2.1 arranging observation holes in the spring region range determined in the step 1.1, observing the groundwater level H, and recording observation data. The observation frequency is once every five days, the observation period is 365 days, and the water level data is accurate to 0.01 m. Preferably, the observation holes are arranged in a density of 10 water level observation holes per hundred square kilometers.
Further, in order to improve the precision, the distance between the observation hole closest to the spring and the spring is not suitable to be larger than the influence radius of 300m of a single-hole water pumping test.
And 2.2, observing the spring water level Hs and recording observation data. The observation frequency is once every five days, the observation period is 365 days, and the water level data is accurate to 0.01 m.
2.3, carrying out river water leakage R measurement on the river channels in the spring area range determined in the step 1.1, wherein the measurement frequency is once every 5 days, and the measurement period is 365 days.
The method for measuring the river water leakage belongs to the basic common knowledge for the technicians in the field, and the detailed description of the specific measuring method is not repeated.
As a specific implementation manner, in this embodiment, a plurality of rivers, such as the jade symbol river and the north sand river, exist in the spring domain range of the Baotu spring determined in step 1.1, and therefore, the amount of leakage of the river water of the river, such as the jade symbol river and the north sand river, is measured every 5 days.
2.4 make observations of the spring flow rate B and record the observations. The observation frequency is once every five days, the observation period is 365 days, and the water level data is accurate to 0.01 m.
2.5, counting the production quantity W, wherein the counting frequency is once every five days, and the counting period is 365 days.
The centralized mining water source area adopts water supply data of a public water source area, and for the mining quantity of the self-contained wells of dispersed enterprises, data counted by a remote meter reading self-metering flowmeter installed by a water conservancy department can be collected.
As a specific implementation manner, in this embodiment, when the production of the spring region in the south of china is unified, the production data of the large centralized water supply source comes from the clear water service group, and the production of the distributed enterprise self-prepared well comes from the water service bureau in the urban and rural areas.
2.6 observing the precipitation P in the range of the spring domain for 365 days.
Here, the rainfall amount may directly employ rainfall observation information of a government meteorological department.
Thirdly, carrying out a water pumping test and solving the permeability coefficient K of the aquifer
And 3.1, carrying out regional division on the spring domain range according to geological conditions, selecting an observation hole as a water pumping hole in each divided region, and solving the aquifer permeability parameter K of each divided region by using a Dupuit formula.
In the formula: k-the aquifer permeability coefficient (m/d);
q-well flow (m)3/d)；
Sw-water level drop (m) in the pumping well;
m is the thickness (M) of the bearing water-containing layer;
r-radius of influence (m).
Further, the water pumping stabilization time is not less than 4 hours.
Fourthly, porous medium seepage simulation
According to the parameters obtained in the second step and the third step, the water level dynamic preliminary simulation is carried out by using the following formula:
in the formula: kiiIs the directional permeability coefficient (m/d);
ii＝xx，yy，zz；
mu is elastic water feeding degree or gravity water feeding degree, and an empirical value is adopted;
h is a head function (m) of a certain space point (x, y, z) at the time t;
H0a head function (m) for a certain spatial point (x, y, z) at an initial instant;
t is 365 d;
epsilon is a source and sink item, including river water leakage amount R, spring flow amount B, mining amount W and precipitation amount P;
omega is a simulation area;
Γ2is the traffic boundary.
As a specific implementation manner, in this embodiment, a denna karst water system is generalized, the three-dimensional underground water flow model is built, and a time-duration curve (i.e., a porous medium model simulation result) of the spring water level is calculated through multiple repeated parameter adjustment calculations as shown in fig. 2. Through analysis, the sum of squares of errors between the simulation result of the porous medium model and the actual observed value is 6.632, the water level fitting precision is high, and the technical requirements of relevant specifications are met.
Fifthly, determining connectivity of the subsurface runoff passage by a tracing test
5.1 determining the tracing test range by taking the length L of the longest local karst cave or underground river as a reference value, taking the karst spring as the center and taking the length L as the radius.
As a specific embodiment, in this example, according to the solution cavity survey in the south china region, the longest solution cavity is less than 2 km, so the tracer test range is in the range of 2000m centered on the Baotu spring group, as shown in fig. 1, there are 12 observation holes falling in this range, which are respectively S1, S2, S4, S5, S6, S7, S9, S10, S11, S12, S13, and S14.
5.2 Water level Observation data H of observation hole falling into tracing test rangei(step 2.1 acquisition) and spring water level Hs (step 2.2 acquisition) establishing a regression equation:
Hs＝aHi+b
5.3 obtaining the correlation coefficient R according to the regression equation2And selecting the observation hole S with the maximum correlation coefficientmax。
As a specific implementation manner, according to water level monitoring data from 1/2018 to 1/2019, the embodiment performs correlation analysis and calculation on the spring water level and the water level of the observation hole in the tracing test range, which indicates that the correlation between the groundwater level of the S1 well and the spring water level is the best, and the correlation coefficient R is the best2Is 0.7016.
And 5.4 drawing an isobaric line graph according to water level observation data of the observation holes falling into the tracing test range, as shown in the graph 3, so as to determine the groundwater flow direction.
5.5 Observation holes S determined in step 5.3maxAnd (4) taking the putting point as a center, arranging a groundwater level and water sample monitoring network at the downstream of the putting point according to the groundwater flow direction determined in the step 5.4, and detecting the concentration of the tracer at the monitoring point in the monitoring network as a background value.
As a specific implementation, the monitoring network disposed in the present embodiment includes monitoring points S1, S2, S4, S5, S6, S7, S9, S10, S11, S12, S13, and S14.
5.6 putting tracer into the putting points, monitoring the concentration of the tracer at monitoring points in the monitoring network, wherein the monitoring frequency is 1 time per day.
The tracer dosage is calculated according to the following formula:
M＝a(TQC)b
in the formula: m represents the input amount;
a, b-empirical coefficients;
t is the migration time from the release point to the receiving point;
q is the karst water flow at the receiving point;
c — estimated peak tracer concentration at the receiver point.
Furthermore, the tracer is selected from tracers which are nontoxic, easy to detect and free from influence of human factors, such as rhodamine, ammonium molybdate and the like;
in this embodiment, as a specific implementation mode, because Baotu spring has ornamental value, if the color of spring water changes, the ornamental value will be affected, ammonium molybdate is used as tracer, and 28kg of ammonium molybdate is put into the drilling site of S1.
And 5.7, drawing a tracer concentration change curve graph according to the monitoring data of the monitoring points, and recording the number N of wave peaks in the tracer concentration change curve graph of the monitoring points at the spring position.
This is because, when the tracer concentration curve detected at the monitoring point exhibits a "concentration peak" shape, it indicates that a runoff channel exists between the dispensing point and the monitoring point, and the number of runoff channels between the dispensing point and the monitoring point can be preliminarily determined according to the number of peaks in the tracer concentration curve.
As a specific implementation manner, in this example, starting from the tracer test, molybdenum ions were detected at monitoring points S4, S6, S9 and S10 respectively, and the molybdenum ions were detected at the Baotu spring group for 47 days, and as shown in fig. 4, the molybdenum ion concentration curve of the Baotu spring water exhibited a "unimodal" morphology, indicating that the groundwater channel between the source point and the sampling point was a single channel characteristic.
In this case, the detection standard of the tracer is 5 times over the background value of the tracer.
Sixthly, determining the spatial distribution of the karst pipeline
6.1 monitoring the temperature and conductivity of the underground water every 2m for the drill holes in the tracing test range determined in the step 5.1, wherein the monitoring period is one year, and the monitoring frequency is once every two weeks.
6.2 drawing a scatter diagram of the water temperature of the feeding point and each monitoring point changing along with the depth and a scatter diagram of the conductivity changing along with the depth according to the monitoring result of the 6.1, and judging the depth of the karst pipeline from inflection points of the water temperature and the conductivity on the scatter diagram.
As a specific embodiment, taking the dosing point S1 as an example, a temperature graph and a conductivity graph of the dosing point S1 are plotted as shown in fig. 5 and 6. As can be seen from fig. 5 and 6, the electrical conductivity of the throwing point S1 has an inflection point at a buried depth of about 34m, and the temperature gradient has a sudden change, so that it can be determined that a single karst pipeline develops in the hole S1 at an elevation of 16 m.
6.3 drawing a statistical graph of the vertical karst development condition within the tracing test range according to the drilling data.
As a specific implementation manner, a statistical graph of the development of vertical karst within the tracing test range is drawn in this example, as shown in fig. 7.
And 6.4 presetting the possible karst pipelines according to the tracing test result of the fifth step.
And 6.5, combining the equal water level diagram drawn in the step 5.3 and the vertical karst development condition statistical diagram drawn in the step 6.3 to judge the rationality of the karst pipeline preset in the step 6.4, taking the karst pipeline matched with the equal water level diagram and the vertical karst development condition statistical diagram as a final karst pipeline, and drawing a plane position diagram of the final karst pipeline.
If the number of final karst ducts is equal to the number N of peaks in step 5.7, continuing with the next step, if the number of final karst ducts is less than the number N of peaks in step 5.7, expanding the range of the monitoring net in step 5.5 and/or increasing the density of the monitoring net in step 5.5, and repeating the operations of steps 5.5-6.5 until the number of final karst ducts is equal to the number of peaks in step 5.7.
As a specific implementation manner, in this example, although molybdenum ions were detected in S6 and S9, the extending direction of the S6 pore-S9 pore-Baotu spring route is not consistent with the direction of the region karst development, and thus it was determined that S1 pore-S4 pore-S10 pore-Baotu spring is a karst pipe between the delivery point and the Baotu spring. As shown in fig. 3, this conclusion is essentially consistent with the groundwater flow field and is equal to the number of peaks in step 5.5.
6.6 drawing a geological profile according to the stratum data of each monitoring point on the final karst pipeline, sequentially connecting the karst development depth or inflection points of temperature and conductivity of each monitoring point on the final karst pipeline, and determining the vertical arrangement of the karst pipeline.
As a specific implementation manner, in the present embodiment, the monitoring point S1 has an inflection point in water temperature and electrical conductivity at the burial depth of 34 m; the monitoring point S4 has inflection points on the water temperature and the electric conductivity at the position of the burial depth of 62.5-63.5 m; the monitoring point S10 has inflection points on the water temperature and the electric conductivity at the burial depth of 68.2-83 m. The karst pipeline determined by the inflection points of the sequential connection of S1, S4 and S10 according to the principle of parastratic development is shown in FIG. 8.
Seventhly, performing dominant flow simulation on the final karst pipeline obtained in the sixth step
And the preferential flow simulation solution is to set pipeline nodes on the porous medium seepage model cell established in the fourth step, wherein one cell has at most one node, and the nodes are connected to form a pipeline network, so that the spring water level can be calculated through the simulation of the preferential flow of the karst pipeline.
7.1 calculating the diameter of the pipeline, wherein the relation formula of the pressure difference of the flowing pipeline and the flow speed is as follows:
wherein:
therefore, the calculation formula of the diameter of the pipeline obtained by simultaneous calculation is as follows:
in the formula: l, d for pipe length and diameter (m), respectively;
delta p is the pressure difference (Pa) between two ends of the pipeline;
v is the average flow velocity (m/s),
μ is a kinetic viscosity coefficient of water (Pa · s).
As a specific implementation mode, the linear distance L from the feeding point S1 to the Baotu spring in the embodiment is about 1.6km, and the molybdenum ion concentration reaches the peak value after about 47 days in the tracer test, so that the calculated average flow velocity v in the area is 3.94 × 10-2cm/s. During the tracer test, the Baotu spring water level is between 27.57 and 27.80m, the average value is 27.72m, the groundwater level of the throwing area is between 28.93 and 30.7m, the average value is 29.75m, and the calculated differential pressure delta p is 2.03 multiplied by 104Pa. The kinetic viscosity coefficient mu is about 1.043X 10 when the temperature is 18 ℃ which is the average temperature of the groundwater-3Pa · s, is substituted into the above equation to calculate the pipe diameter d to be about 0.1018 cm.
7.2 inputting the diameter d of the pipeline, the position of the pipeline, the upper critical Reynolds number, the lower critical Reynolds number, the tortuosity, the roughness, the exchange coefficient and other conventional parameters into a program to simulate the pipeline flow.
Here, the pipe positions include a plane position and a vertical position, and when there are a plurality of pipes, the plane positions and the vertical positions of the plurality of pipes may be input to the program, respectively.
The upper critical Reynolds number, the lower critical Reynolds number, the tortuosity, the roughness and the exchange coefficient are empirical values. As a specific implementation mode, the upper critical Reynolds number in this example is 2000, the lower critical Reynolds number is 4000, the tortuosity is 1.0, the roughness is 0.0001m, and the exchange coefficient is 9m2/d。
And (3) debugging and simulating for multiple times, wherein the Baotu spring water level calculated under the optimal parameter combination is shown in fig. 9, the sum of squares of errors between the Baotu spring water level and the actually observed spring water level is 3.065, compared with the porous medium seepage calculation result in the fourth step, the error between the coupling simulation and the actually measured value is smaller, the fitting precision of the predicted spring water level is improved by 53.8%, and the dynamic change process of the pipeline flow simulated spring water is more accurate.
Claims (9)
1. A method for simulating the dynamic state of underground water of a karst big spring is characterized by comprising the following steps: comprises the following steps of (a) carrying out,
firstly, determining the spatial distribution of a water-bearing layer of the spring water supply;
1.1 determining the lateral boundary of the spring domain;
1.2 determining the vertical distribution of the aquifer supplying spring water in the range of the spring domain;
secondly, collecting basic data, wherein the basic data comprise a spring water level Hs, a spring flow B, a groundwater level H, a river water leakage R, a mining amount W and a precipitation amount P in the spring area range determined in the step 1.1;
thirdly, performing a water pumping test, and solving the permeability coefficient K of the aquifer;
fourthly, carrying out porous medium seepage simulation according to the parameters obtained in the second step and the third step;
fifthly, determining connectivity of the subsurface runoff channel by a tracing test;
5.1 determining the tracing test range by taking the length L of the longest local karst cave or underground river as a reference value, taking the karst big spring as the center and taking the length L as the radius;
5.2 Water level Observation data H of observation hole falling into tracing test rangeiEstablishing a regression equation with spring water level Hs;
5.3 obtaining the correlation coefficient R according to the regression equation2And selecting the observation hole S with the maximum correlation coefficientmax；
5.4 drawing an isobaric line graph according to water level observation data of the observation holes falling into the tracing test range;
5.5 Observation holes S determined in step 5.3maxArranging an underground water level and water sample monitoring network for tracer feeding points, and detecting the concentration of the tracer as a background value;
5.6 putting a tracer into the putting points, and monitoring the concentration of the tracer at monitoring points in the monitoring network;
5.7, drawing a tracer concentration change curve chart of each monitoring point according to the monitoring data, and recording the number N of wave peaks in the tracer concentration change curve chart of the monitoring points at the spring position;
sixthly, determining the spatial distribution of the karst pipeline
6.1 monitoring the temperature and conductivity of the underground water every 2m for the drill holes in the tracing test range;
6.2 according to the monitoring result of 6.1, finding inflection points of the water temperature and the electric conductivity of the throwing point and each monitoring point;
6.3, drawing a statistical graph of the development condition of the vertical karst within the tracing test range according to the drilling data;
6.4 presetting possible karst pipelines according to the tracing test result in the fifth step;
6.5, the isobaric line diagram drawn in the step 5.3 and the vertical karst development statistical diagram drawn in the step 6.3 are combined to judge a preset karst pipeline, and the karst pipeline matched with the isobaric line diagram and the vertical karst development statistical diagram is taken as a final karst pipeline;
if the number of the final karst pipelines is equal to the number N of the wave crests in the step 5.7, continuing the next step, if the number of the final karst pipelines is less than the number N of the wave crests in the step 5.7, expanding the range of the monitoring net and/or increasing the density of the monitoring net, and repeating the operation of the step 5.5-6.5 until the number of the final karst pipelines is equal to the number of the wave crests in the step 5.7;
6.6, determining the vertical arrangement of the karst pipeline according to the karst development depth or the inflection points of the temperature and the conductivity of each monitoring point on the final karst pipeline;
and seventhly, performing dominant flow simulation on the final karst pipeline.
2. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: in the step 1.1, an independent underground water system with a natural boundary is adopted, and water-resisting fracture, an underground water watershed or a water-resisting stratum is selected as a spring region polygonal boundary.
3. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: and in the second step, when the observation holes are arranged in the spring region range, the observation holes are arranged according to the density of 10 water level observation holes per hundred square kilometers, and the distance between the observation hole closest to the spring and the spring is less than 300 m.
4. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: and thirdly, performing regional division on the spring domain range according to geological conditions, and selecting an observation hole as a water pumping hole in each divided region.
5. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: in the third step, the water pumping stabilization time is more than or equal to 4 hours.
6. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: the tracer test adopts rhodamine or ammonium molybdate as a tracer.
7. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: and in the fifth step of tracer test, the detection standard of the tracer is 5 times over the background value of the tracer.
8. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: in the second step, the observation frequency of the groundwater level H, the spring water level Hs, the river water leakage R, the spring flow B and the mining volume W is once observed every five days, the observation period is 365 days, and the observation period of the precipitation P is 365 days.
9. The method for simulating the dynamic state of a karst spring groundwater according to claim 1, wherein the method comprises the following steps: in the fifth step, the monitoring period of the tracer test is one year, and the monitoring frequency is once every two weeks.
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