Karst spring monitoring and early warning system

Abstract

The invention, which relates to the technical field of big data analysis, discloses a karst spring monitoring and early warning system comprising a data acquisition module, a forecasting module, an early warning module and an underground rehearsal module. The data acquisition module is used for acquiring water level, flow and meteorological data of spring water through an underground water monitoring station, performing preprocessing operation and storing the data in a database; the forecasting module is used for extracting water level, flow and meteorological data from a database, establishing a numerical model of underground water and generating a spring water level and flow forecasting result in a future time period; the underground rehearsal module is used for simulating and predicting the dynamic change of the water level of spring water by setting different sampling and supplementing, rainfall and supplementing measure conditions on the basis of an underground water numerical simulation model and collected monitoring data; and the early warning module is used for judging a spring water resurging state and a water level change condition through a preset water level threshold value based on the acquired monitoring data and a numerical simulation prediction result, and triggering an early warning and alarming mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and more specifically, to a karst spring monitoring and early warning system. Background Art

[0002] With the rapid development of society, especially the acceleration of industrialization and urbanization, over-exploitation of groundwater and deterioration of water quality have become serious environmental problems. Especially in karst areas, the protection and rational use of groundwater resources face huge challenges. Karst springs are springs where groundwater is collected and re-emerged through karst action. They are used to provide important water sources for surrounding areas. They are not only important water sources in the natural environment, but also often have huge economic and ecological value in human society. Since the water source of karst springs is affected by many factors, the stability of their water level is crucial.

[0003] Many existing groundwater monitoring systems rely on traditional manual sampling or periodic inspections, which results in poor timeliness of data and may miss key changing trends or abnormal water level fluctuations. For complex karst spring areas, existing groundwater models often cannot fully consider the spatial heterogeneity and complex flow mechanisms of groundwater, and lack dynamic, three-dimensional simulation and real-time visualization. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a karst spring monitoring and early warning system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a karst spring monitoring and early warning system, comprising a data acquisition module, a forecast module, an early warning module, and an underground rehearsal module; The data acquisition module collects the water level, flow and meteorological data of the spring water through the groundwater monitoring station, performs pre-processing operations, and stores them in the database; The forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, and generates the prediction results of spring water level and flow in the future period; The underground rehearsal module simulates and predicts the dynamic changes of spring water levels based on the groundwater numerical simulation model and the collected monitoring data by setting different conditions of extraction, replenishment, rainfall and supplementary measures; The early warning module is based on the collected monitoring data and numerical simulation prediction results. It judges the state of spring water re-emergence and the change of spring water level through the preset water level threshold, and triggers the early warning and alarm mechanism.

[0006] In a preferred embodiment, the data acquisition module collects water level, flow, and meteorological data of spring water through a groundwater monitoring station, and performs preprocessing operations to improve the accuracy and reliability of the data, reduce misleading conclusions caused by low data quality, and store them in a database for sharing, which helps all parties to respond quickly to emergencies. The specific steps are as follows: Step A1, monitoring data collection: through hydrogeological survey, to determine the characteristics and flow pattern of the spring water, to ensure that representative water level and flow data can be obtained, to set up groundwater monitoring stations at the outlet of the spring water, to effectively monitor the dynamic changes of the spring water, and to install groundwater monitoring wells, flow meters and meteorological sensors at each monitoring station to collect the water level, flow and meteorological data of the spring water, the meteorological data including precipitation, temperature and evaporation, the data collection time interval is set to every minute to ensure the real-time and continuity of the data; Step A2, preprocessing: clean, interpolate, verify and time synchronize the data to ensure that it meets the preset standards and ranges, exclude any unreasonable data, ensure the accuracy and completeness of the data, index it by timestamp, and store the processed data in the database.

[0007] In a preferred embodiment, the forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, simulates the dynamic changes of spring water through the model, and generates the prediction results of spring water level and flow in the future period. By predicting the change trend of spring water in advance, the construction and operation costs of water conservancy facilities can be reduced, and equipment failures and maintenance costs caused by water level changes can be avoided. The specific steps are as follows: Step B1, establish a numerical model: extract and collect the spring water level, flow and meteorological data from the database and express them as , and ,in, Respectively represent precipitation, temperature and evaporation. A numerical model of groundwater is established based on the groundwater flow equation to maintain the stability of the model in the calculation. The formula of the groundwater flow equation is: ,in, represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; the water storage coefficient represents the water storage capacity per unit area of ​​the aquifer; K is the permeability coefficient, which represents the water seepage capacity of the formation; P is precipitation, E is evaporation, and Q is flow; Step B2, numerical model solution: set initial conditions and boundary conditions, discretize by numerical method, and solve the above equations to obtain the predicted values ​​of spring water level and flow in the future period, further including the following steps: Step B201, the initial conditions are the groundwater level and water storage at the initial time of model setting, and the mathematical expression is: ,in, At the initial time At the point in space The boundary condition is to set the flow rate on the boundary of the model area to a known value, which means that the flow rate Q is known on the boundary of the model, which helps to control the external environmental factors of the simulation area; Step B202: Use the finite difference method to discretize time and space, and discretize time t into small time steps. , which means that the entire prediction period is divided into multiple time periods. The changes in each time period are calculated by numerical methods. The spatial discretization is represented by grid nodes, which means that the entire groundwater area is divided into several small grid units. Each grid unit has a corresponding groundwater level value. The discretized groundwater flow equation is: ,in, is the diffusion term of groundwater flow, represents the water supply term, is the pumping term, which represents the extraction of water flow, and is a grid node Groundwater level at time steps n and n+1; Step B203, use the discretized equation group to perform numerical solution, in each time step, update the spring water level h and flow Q according to the results of the numerical solution, and gradually advance the model calculation, which is to continuously advance the time step, update the groundwater level and flow prediction at each grid point, until the spring water level and flow prediction within the prediction period are obtained, and the spring water level and flow prediction results of each time step are output, which are respectively expressed as and .

[0008] In a preferred embodiment, the underground rehearsal module is based on the groundwater numerical simulation model and the collected monitoring data. By setting different conditions of collection, replenishment, rainfall and supplementary measures, the dynamic changes of the spring water level are simulated and predicted. By simulating the impact of different collection, replenishment, rainfall and supplementary measures, the long-term impact of different water collection strategies on the spring water level can be predicted, and the automated water level prediction and regulation can be realized to improve the efficiency of water resource management. The specific steps are as follows: Step C1, rehearsal under different scenario conditions: In multiple rehearsal schemes, according to different condition settings, the changes in spring water levels are simulated, and the results are used to help evaluate the impact of different measures on groundwater resources. All rehearsal schemes are displayed in a list form, and support is provided for screening according to different mining and replenishment, rainfall and supplementary measures. The mining and replenishment conditions are to set different mining and replenishment flow rates to simulate the impact of different groundwater utilization and replenishment methods on the spring water level; the rainfall conditions are to set the water input according to the rainfall intensity and frequency to simulate the water level response. Different rainfall conditions directly affect the changes in the water level, and simulate how the water level responds to different rainfall scenarios; the artificial replenishment measures are to set different artificial replenishment amounts, which refers to the artificial injection of water into the groundwater system to analyze its impact on the spring water level; the groundwater flow equation is adjusted to ,in, represents the mining rate, represents the new precipitation amount, It is to increase the flow. It represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; K is the permeability coefficient, E is the evaporation, and Q is the flow rate; Step C2: Use the adjusted equation to perform numerical simulation to simulate the dynamic changes of spring water levels under different scenarios, generate visual charts to represent the trend of water level changes, and further obtain expected results to help users evaluate the response of groundwater under different scenarios.

[0009] In a preferred embodiment, the early warning module is based on the collected monitoring data and numerical simulation prediction results, and through the preset water level threshold, it judges the state of spring water resurgence and the change of spring water level, and triggers the early warning and alarm mechanism. Through numerical simulation prediction and threshold setting, the early warning is triggered before the spring water level changes to the dangerous critical point, which improves the sensitivity and reaction speed of emergency response, reduces the need for manual intervention, and ensures the efficient use of water resources. The specific steps are as follows: Step D1, spring water level change rate analysis: Use the spring water level change rate to analyze the water level change trend and determine whether the water level is rising or falling. The specific calculation formula is as follows:

[0010] in, It's time The water level of the spring at any given moment, is the time interval, which indicates the time difference between two time points. is the rate of change of the spring water level over time, indicating the speed of water level rise and fall. , indicating that the water level rises; when , indicating that the water level drops. , indicating that the water level remains unchanged; the trend of the spring water level change is determined by calculating the rate of change over a period of time. , the water level is rising, indicating that the spring is gushing out again; , then the water level drops, indicating that the water source is exhausted; Step D2, early warning judgment: determine whether to trigger an early warning based on the preset water level threshold, and set the normal water level, warning water level and dangerous water level as , and , based on the numerical simulation prediction results, early warning judgment of water level change trend is carried out. and , indicating that the water level is within the normal range and is rising, the spring water is gushing again, and no warning is issued; when and , indicating that the water level is close to the warning level , the water level has not reached a dangerous level, triggering a red warning; when and , indicating that the water level exceeds the dangerous level , triggering an orange warning, indicating that the water level has entered a dangerous range; Step D3, display of early warning results: display the results of the early warning and conduct statistical analysis to help staff members to timely check the early warning status of each monitoring point, conduct statistics on different types of early warnings, record the number and time range of each early warning, and select a list to display the early warning results of each monitoring well based on the statistical results, including monitoring time, early warning type, and water level value. According to the early warning type, activate the alarm device, including sound alarm and flashing light prompts. The flashing light prompts can enhance the visual warning effect, reminding staff members to pay attention to water level changes and avoid potential risks.

[0011] The beneficial effects of the present invention are as follows: water level, flow and meteorological data of spring water are collected through groundwater monitoring stations, and preprocessing operations are performed to store them in a database; the collected water level, flow and meteorological data are extracted from the database, a numerical model of groundwater is established, and prediction results of spring water level and flow in future time periods are generated; based on the groundwater numerical simulation model and the collected monitoring data, different collection, replenishment, rainfall and supplementary measures are set to simulate and predict the dynamic changes of spring water level; according to the numerical simulation prediction results, the state of spring water re-emergence and the change of spring water level are judged by pre-setting water level thresholds, and early warning and alarm mechanisms are triggered; the present invention can monitor spring water level, flow and meteorological data in real time by integrating data collection, forecasting, early warning modules, and underground rehearsal modules; and can help staff take timely measures to prevent potential risks by simulating the changes of spring water re-emergence under different circumstances; and use each module to cooperate with each other to jointly improve the management and protection capabilities of groundwater resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0013] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0014] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0015] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present application.

[0016] Example 1 This embodiment provides Figure 1 A karst spring monitoring and early warning system is shown, which specifically includes a data acquisition module, a forecast module, an early warning module, and an underground rehearsal module; The data acquisition module collects the water level, flow and meteorological data of the spring water through the groundwater monitoring station, performs pre-processing operations, and stores them in the database; The forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, and generates the prediction results of spring water level and flow in the future period; The underground rehearsal module simulates and predicts the dynamic changes of spring water levels based on the groundwater numerical simulation model and the collected monitoring data by setting different conditions of extraction, replenishment, rainfall and supplementary measures; The early warning module is based on the collected monitoring data and numerical simulation prediction results, and through the preset water level threshold, it judges the state of spring water re-emergence and the change of spring water level, and triggers the early warning and alarm mechanism.

[0017] In this embodiment, the data acquisition module specifically needs to be explained. The data acquisition module collects water level, flow rate, and meteorological data of spring water through the groundwater monitoring station, and performs preprocessing operations to improve the accuracy and reliability of the data, reduce misleading conclusions caused by low data quality, and store the data in a database, which can be shared, and helps all parties to respond quickly to emergencies. The specific steps are as follows: Step A1, monitoring data collection: through hydrogeological survey, to determine the characteristics and flow pattern of the spring water, to ensure that representative water level and flow data can be obtained, to truly reflect the dynamic changes of the spring water, to set up groundwater monitoring stations at the outlet of the spring water, to effectively monitor the dynamic changes of the spring water, and to install groundwater monitoring wells, flow meters and meteorological sensors at each monitoring station to collect the water level, flow and meteorological data of the spring water, the groundwater monitoring well is used to measure the groundwater level, the flow meter is used to monitor the flow of the spring water, to ensure that the flow rate of the spring water can be accurately recorded, the meteorological sensor is used to collect meteorological data, the meteorological data includes precipitation, temperature and evaporation, the data collection time interval is set to every minute, to ensure the real-time and continuity of the data, to ensure that the instantaneous changes of the spring water flow can be captured, so as to facilitate timely response to emergencies; Step A2, preprocessing: clean, interpolate, check and time synchronize the data to ensure that it meets the preset standards and ranges to exclude any unreasonable data. The cleaning, interpolation, checking and time synchronization of the data are the key to data quality, which can exclude erroneous data caused by equipment failure and environmental interference, ensure the accuracy and integrity of the data, and index by timestamp, and store the processed data in the database.

[0018] In this embodiment, the forecast module specifically needs to be explained. The forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, simulates the dynamic changes of spring water through the model, and generates the spring water level and flow prediction results for the future period. By predicting the change trend of spring water in advance, the construction and operation costs of water conservancy facilities can be reduced, and equipment failures and maintenance costs caused by water level changes can be avoided. The specific steps are as follows: Step B1, establish a numerical model: extract and collect the spring water level, flow and meteorological data from the database and express them as , and ,in, Respectively represent precipitation, temperature and evaporation. A numerical model of groundwater is established based on the groundwater flow equation to maintain the stability of the model in the calculation. The formula of the groundwater flow equation is: ,in, represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; the water storage coefficient represents the water storage capacity per unit area of ​​the aquifer; K is the permeability coefficient, which represents the water seepage capacity of the formation; P is precipitation, E is evaporation, and Q is flow; Step B2, numerical model solution: set initial conditions and boundary conditions, discretize through numerical methods, and solve the above equations to obtain the predicted values ​​of spring water level and flow in the future period, which is helpful for the management and scheduling of water resources, provides a scientific basis for the construction and operation of water conservancy facilities, and reduces potential risks and costs. It further includes the following steps: Step B201, the initial conditions are the groundwater level and water storage at the initial time of model setting, and the mathematical expression is: ,in, At the initial time At the point in space The boundary condition is to set the flow rate on the boundary of the model area to a known value, which means that the flow rate Q is known on the boundary of the model, which helps to control the external environmental factors of the simulation area; Step B202: Use the finite difference method to discretize time and space. Time discretization is to discretize time t into small time steps. , which means that the entire prediction period is divided into multiple time periods, and the changes in each time period are calculated by numerical methods. Spatial discretization is the use of grid nodes to represent the discreteness of space. The entire groundwater area is divided into several small grid units, and each grid unit has a corresponding groundwater level value. The groundwater flow equation after discretization is: ,in, is the diffusion term of groundwater flow, represents the water supply term, is the pumping term, which represents the extraction of water flow, and is a grid node Groundwater level at time steps n and n+1; Step B203, use the discretized equation group to perform numerical solution, in each time step, update the spring water level h and flow Q according to the results of the numerical solution, and gradually advance the model calculation, which is to continuously advance the time step, update the groundwater level and flow prediction at each grid point, until the spring water level and flow prediction within the prediction period are obtained, and the spring water level and flow prediction results of each time step are output, which are respectively expressed as and .

[0019] In this embodiment, what needs to be explained specifically is the underground rehearsal module. The underground rehearsal module is based on the groundwater numerical simulation model and the collected monitoring data. By setting different conditions of collection, replenishment, rainfall and supplementary measures, the dynamic change of the spring water level is simulated and predicted. By simulating the impact of different collection, replenishment, rainfall and supplementary measures, the long-term impact of different water collection strategies on the spring water level can be predicted, and automatic water level prediction and regulation can be achieved to improve the efficiency of water resource management. The specific steps are as follows: Step C1, rehearsal under different scenario conditions: In multiple rehearsal schemes, according to different condition settings, the changes in spring water levels are simulated, and the results are used to help evaluate the impact of different measures on groundwater resources. All rehearsal schemes are displayed in a list form, and screening is supported according to different mining and replenishment, rainfall and supplementary measures. The mining and replenishment conditions are to set different mining and replenishment flow rates to simulate the impact of different groundwater utilization and replenishment methods on the spring water level. By setting scenarios with high mining flow and low replenishment flow, the changes in the spring water level are observed; the rainfall conditions are to set the water input according to the rainfall intensity and frequency to simulate the water level response. Different rainfall conditions directly affect the changes in water levels. By simulating the changes in spring water levels under heavy rainfall and drought conditions, the impact of rainfall on water levels can be understood; the artificial replenishment measures are to set different artificial replenishment amounts, which refers to the amount of water artificially injected into the groundwater system, and analyze its impact on the spring water level; the groundwater flow equation is adjusted to ,in, represents the mining rate, represents the new precipitation amount, It is to increase the flow. It represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; K is the permeability coefficient, E is the evaporation, and Q is the flow rate; Step C2, use the adjusted equation to perform numerical simulation to simulate the dynamic changes of spring water level under different scenarios. By setting initial conditions and boundary conditions, the equation is discretized using numerical methods to solve the water level changes at different time steps, and a visual chart is generated to represent the trend of water level changes. Further, the expected results are obtained to help users evaluate the response of groundwater under different scenarios.

[0020] In this embodiment, what needs to be explained specifically is the early warning module. The early warning module is based on the collected monitoring data and numerical simulation prediction results. By presetting the water level threshold, the state of spring water re-emergence and the change of spring water level are judged, and the early warning and alarm mechanism is triggered. Through numerical simulation prediction and threshold setting, the early warning is triggered before the spring water level changes to the dangerous critical point, which improves the sensitivity and reaction speed of emergency response, reduces the need for manual intervention, and ensures that water resources are efficiently used. The specific steps are as follows: Step D1, spring water level change rate analysis: Use the spring water level change rate to analyze the water level change trend and determine whether the water level is rising or falling. The specific calculation formula is as follows:

[0021] in, It's time The water level of the spring at any given moment, is the time interval, which indicates the time difference between two time points. is the rate of change of the spring water level over time, indicating the speed of water level rise and fall. , indicating that the water level rises; when , indicating that the water level drops. , indicating that the water level remains unchanged; the trend of the spring water level change is determined by calculating the rate of change over a period of time. , the water level is rising, indicating that the spring is gushing out again; , then the water level drops, indicating that the water source is exhausted; Step D2, early warning judgment: determine whether to trigger an early warning based on the preset water level threshold, and set the normal water level, warning water level and dangerous water level as , and , based on the numerical simulation prediction results, early warning judgment of water level change trend is carried out. and , indicating that the water level is within the normal range and is rising, the spring water is gushing again, and no warning is issued; when and , indicating that the water level is close to the warning level , the water level has not reached a dangerous level, triggering a red warning, prompting attention to water level changes; when and , indicating that the water level exceeds the dangerous level , triggering an orange warning, indicating that the water level has entered a dangerous range; Step D3, display of early warning results: display the results of early warnings and conduct statistical analysis to help staff members timely check the early warning status of each monitoring point, conduct statistics on different types of early warnings, record the number and time range of each early warning, and select a list to display the early warning results of each monitoring well, including monitoring time, early warning type, and water level value, according to the early warning type, activate the alarm device, including sound alarm and flashing light prompts, and enhance the visual warning effect through flashing light prompts to remind staff members to pay attention to water level changes and avoid potential risks. Through multiple alarm methods, ensure that in various environments, staff members can immediately realize the potential risk of water level changes and avoid catastrophic consequences.

[0022] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0023] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0024] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0025] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0026] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0027] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0028] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A karst spring monitoring and early warning system, characterized by: It includes data collection module, forecast module, warning module, and underground rehearsal module; The data acquisition module collects the water level, flow and meteorological data of the spring water through the groundwater monitoring station, performs pre-processing operations, and stores them in the database; The forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, and generates the prediction results of spring water level and flow in the future period; The underground rehearsal module simulates and predicts the dynamic changes of spring water levels based on the groundwater numerical simulation model and the collected monitoring data by setting different conditions of extraction, replenishment, rainfall and supplementary measures; The early warning module is based on the collected monitoring data and numerical simulation prediction results, and through the preset water level threshold, it judges the state of spring water re-emergence and the change of spring water level, and triggers the early warning and alarm mechanism.

2. A karst spring monitoring and early warning system according to claim 1, characterized in that: The data acquisition module collects the water level, flow rate and meteorological data of the spring water through the groundwater monitoring station, performs pre-processing operations, and stores them in the database. The specific steps are as follows: Step A1, monitoring data collection: through hydrogeological survey, groundwater monitoring stations are set up at the outlet of the spring, and groundwater monitoring wells, flow meters and meteorological sensors are installed at each monitoring station to collect water level, flow and meteorological data. The meteorological data includes precipitation, temperature and evaporation. The data collection time interval is set to every minute. Step A2, preprocessing: clean, interpolate, verify and time synchronize the data to ensure the accuracy and completeness of the data, index it by timestamp, and store the processed data in the database.

3. The karst spring monitoring and early warning system according to claim 1 is characterized by: The forecast module extracts the collected water level, flow and meteorological data from the database, establishes a numerical model of groundwater, and generates the prediction results of spring water level and flow in the future period. The specific steps are as follows: Step B1, establish a numerical model: extract and collect the spring water level, flow and meteorological data from the database and express them as , and ,in, Respectively represent precipitation, temperature and evaporation, and a groundwater numerical model is established based on the groundwater flow equation. The groundwater flow equation formula is: ,in, It represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; K is the permeability coefficient, which represents the water seepage capacity of the formation; P is precipitation, E is evaporation, and Q is flow; Step B2, numerical model solution: set initial conditions and boundary conditions, discretize through numerical methods, and solve the above equations to obtain the predicted values ​​of spring water level and flow in the future period.

4. A karst spring monitoring and early warning system according to claim 3, characterized in that: In the step B2 of solving the numerical model, initial conditions and boundary conditions are set, and discretization is performed by numerical methods, and the above equations are solved to obtain the predicted values ​​of the spring water level and flow in the future period, which further includes the following steps: Step B201, the initial conditions are the groundwater level h and water storage at the initial time of model setting, and the mathematical expression is: ,in, At the initial time At the point in space The boundary condition is to set the flow rate on the boundary of the model area to a known value; Step B202: Use the finite difference method to discretize time and space, and discretize time t into small time steps. , the spatial discretization is represented by grid nodes, and the groundwater flow equation after discretization is obtained as follows: ,in, is the diffusion term of groundwater flow, represents the water supply term, is the pumping quantity term, and is a grid node Groundwater level at time steps n and n+1; Step B203, use the discretized equation group to perform numerical solution, update the spring water level and flow rate according to the results of the numerical solution in each time step, and gradually advance the model calculation until the spring water level and flow rate prediction within the prediction period are obtained, and the spring water level and flow rate prediction results of each time step are output, which are respectively expressed as and .

5. The karst spring monitoring and early warning system according to claim 1 is characterized by: The underground rehearsal module simulates and predicts the dynamic changes of spring water levels based on the groundwater numerical simulation model and the collected monitoring data by setting different conditions of extraction, rainfall and supplementary measures. The specific steps are as follows: Step C1, rehearsal under different situation conditions: all rehearsal plans are displayed in a list form, and they can be screened according to different mining and replenishment, rainfall and supplementary measures. The mining and replenishment conditions are to set different mining and replenishment flow rates; the rainfall conditions are to set the water input according to the rainfall intensity and frequency, and simulate the water level response; the artificial replenishment measures are to set different artificial replenishment amounts and analyze their impact on the spring water level; the groundwater flow equation is adjusted to ,in, represents the mining rate, represents the new precipitation amount, It is to increase the flow. It represents the rate of change of the product of groundwater level h and water storage coefficient S over time t; K is the permeability coefficient, E is the evaporation, and Q is the flow rate; Step C2: Use the adjusted equation to perform numerical simulation to simulate the dynamic changes of the spring water level under different scenarios, and generate a visual chart to represent the trend of the water level change.

6. A karst spring monitoring and early warning system according to claim 1, characterized in that: The early warning module is based on the collected monitoring data and numerical simulation prediction results, and through the preset water level threshold, it determines the state of spring water re-emergence and the change of spring water level, and triggers the early warning and alarm mechanism. The specific steps are as follows: Step D1, spring water level change rate analysis: Use the spring water level change rate to analyze the water level change trend. The specific calculation formula is as follows: ； in, It's time The water level of the spring at any given moment, is the time interval, is the rate of change of the spring water level over time, indicating the speed of water level rise and fall. , indicating that the water level rises; when , indicating that the water level drops. , indicating that the water level remains unchanged, the trend of the spring water level change is determined by calculating the rate of change over a period of time. , the water level is rising, indicating that the spring is gushing out again; , then the water level drops, indicating that the water source is exhausted; Step D2, early warning judgment: set the normal water level, warning water level and dangerous water level as , and , based on the numerical simulation prediction results, early warning judgment of water level change trend is carried out. and , indicating that within the normal water level range, no warning will be issued; when and , indicating that the water level is close to the warning level , the water level has not reached a dangerous level, triggering a red warning; when and , indicating that the water level exceeds the dangerous level , triggering an orange warning; Step D3, display of warning results: statistics are collected for different types of warnings, and the number and time range of each warning are recorded. According to the statistical results, the warning results of each monitoring well are displayed in a list format, including monitoring time, warning type, and water level value. According to the warning type, the alarm device is activated, including sound alarm and flashing light prompts, to remind staff to pay attention to water level changes.

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