Groundwater level monitoring device and groundwater level monitoring method

Abstract

The present invention provides a groundwater level monitoring device and method, comprising: a monitoring terminal; an unmanned aerial vehicle (UAV); and a control device, the control device being configured to: acquire a thermal infrared image covering a target monitoring blank area and an existing data area within the same hydrogeological unit as the target monitoring blank area; identify temperature anomalies within the target monitoring blank area and acquire a first interpreted groundwater level; identify temperature anomalies within the target data area and acquire a second interpreted groundwater level; acquire groundwater monitoring data from the target data area at the same time; construct a fitting function mathematical model relating the second interpreted groundwater level and the groundwater monitoring level based on the second interpreted groundwater level, the groundwater monitoring data, and geological parameters of the target data area; and utilize the constructed fitting function mathematical model to acquire the groundwater level in the target monitoring blank area. The monitoring device provided by the present invention can more accurately monitor the groundwater level in the monitoring blank area.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and in particular to a groundwater level monitoring device and a groundwater level monitoring method. Background Art

[0002] Groundwater monitoring is for groundwater monitoring management departments to monitor groundwater levels, water quality, temperature, conductivity and other data within their jurisdiction in order to keep abreast of dynamic changes and provide long-term protection for groundwater.

[0003] With the development of the Internet of Things (IoT), groundwater monitoring systems currently typically consist of three components: a remote monitoring center, a communications network, and monitoring terminals. Relying on networks like GPRS, groundwater monitoring systems allow personnel to access data such as groundwater level, temperature, and conductivity at the monitoring center. The monitoring center's monitoring management software enables remote data collection and monitoring. All monitored data is entered into a database, generating various reports and graphs.

[0004] In the process of implementing the present invention, the inventors discovered that the prior art has at least the following problems:

[0005] At present, groundwater monitoring is generally carried out manually, by sensors, and by the Internet of Things and wireless communication. First, hardware must be deployed at monitoring points (e.g., groundwater monitoring wells). It is difficult to deploy equipment in remote areas with sparse access, complex terrain, and so-called monitoring blank areas (e.g., mountain recharge areas and Gobi discharge areas), and equipment maintenance is also difficult. The cost of manual regular inspections and monitoring is high. Therefore, monitoring points are mostly deployed only in key locations with good terrain and convenient transportation. In areas with poor signals, few people, inconvenient groundwater transportation, or potential problem areas, monitoring points are too sparse, which limits the characterization of the characteristics and changing patterns of groundwater at different spatial locations.

[0006] Therefore, a groundwater level monitoring device and a groundwater level monitoring method are needed to at least partially solve the above technical problems. Summary of the Invention

[0007] In view of this, embodiments of the present invention provide a groundwater level monitoring device and a groundwater level monitoring method to solve at least one of the problems in the prior art.

[0008] In a first aspect, an embodiment of the present invention provides a method for monitoring groundwater level, the monitoring method comprising:

[0009] Acquire a thermal infrared image from the thermal infrared image captured by the drone, the thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; wherein the existing data area is a selected area within the region that includes at least one groundwater monitoring well;

[0010] Identify the temperature anomaly area in the target monitoring blank area and obtain the first groundwater interpretation water level; take the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located as the target data area, identify the corresponding temperature anomaly area in the target data area, and obtain the second groundwater interpretation water level;

[0011] Based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, the groundwater monitoring data of the target data area at the same time is obtained, including the groundwater monitoring water level, permeability coefficient and water temperature;

[0012] A logistic regression analysis is performed based on the second interpreted groundwater level, groundwater monitoring data, and geological parameters of the target data area to construct a fitting function mathematical model that relates the second interpreted groundwater level to the groundwater monitoring level; the geological parameters include permeability, aquifer thickness, and aquifer porosity;

[0013] Using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level in the target monitoring blank area.

[0014] In a second aspect, an embodiment of the present invention further provides a groundwater level monitoring device, the monitoring device comprising:

[0015] A monitoring terminal installed in a groundwater monitoring well in an existing data area, for real-time monitoring of groundwater level, permeability coefficient, and water temperature; an existing data area is a selected area within a region that includes at least one groundwater monitoring well;

[0016] Unmanned aerial vehicles (UAVs) for capturing aerial thermal infrared images covering target surveillance gaps and areas with existing data; and

[0017] A control device is communicatively connected to the monitoring terminal and the drone, the control device including a processor and a memory, and when the processor executes computer-executable instructions stored in the memory, the following steps are implemented:

[0018] Acquire a thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area;

[0019] Identify the temperature anomaly area in the target monitoring blank area and obtain the first groundwater interpretation water level; take the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located as the target data area, identify the corresponding temperature anomaly area in the target data area, and obtain the second groundwater interpretation water level;

[0020] Based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, the groundwater monitoring data of the target data area at the same time is obtained, including the groundwater monitoring water level, permeability coefficient and water temperature;

[0021] A logistic regression analysis is performed based on the second interpreted groundwater level, groundwater monitoring data, and geological parameters of the target data area to construct a fitting function mathematical model that relates the second interpreted groundwater level to the groundwater monitoring level; the geological parameters include permeability, aquifer thickness, and aquifer porosity;

[0022] Using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level in the target monitoring blank area.

[0023] In a third aspect, an embodiment of the present invention further provides a groundwater level monitoring device, the monitoring device comprising:

[0024] a memory for storing computer-executable instructions;

[0025] The processor is used to implement the monitoring method of the above technical solution when executing the computer executable instructions stored in the memory.

[0026] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to execute the monitoring method of the above technical solution.

[0027] According to the monitoring method of the embodiment of the present invention, the groundwater monitoring data of the target data area (traditional measured monitoring data), the first groundwater interpretation water level and the second groundwater interpretation water level (remote sensing data) are used, combined with the geological parameters of the target data area, and multi-source data are integrated to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level, thereby realizing groundwater level monitoring in monitoring blank areas, making the groundwater level inversion closer to the actual situation, significantly expanding the spatial scope of groundwater monitoring, and realizing large-scale, high-efficiency, and low-cost dynamic groundwater monitoring.

[0028] Additional advantages, objects, and features of the present invention will be set forth in part in the following description and will become apparent to those skilled in the art upon examination of the following or may be learned from practice of the present invention. The objects and other advantages of the present invention may be realized and obtained by the structures particularly pointed out in the description and drawings.

[0029] Those skilled in the art will understand that the purposes and advantages that can be achieved by the present invention are not limited to the above specific descriptions, and the above and other purposes that can be achieved by the present invention will be more clearly understood based on the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings described herein are intended to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. The components in the drawings are not drawn to scale, but are merely for the purpose of illustrating the principles of the present invention. To facilitate the illustration and description of certain portions of the present invention, corresponding portions in the drawings may be exaggerated, that is, may be larger than other components in an exemplary device actually manufactured according to the present invention. In the drawings:

[0031] Figure 1 is a flow chart of a groundwater level monitoring method according to an embodiment of the present invention;

[0032] Figure 2 is a schematic diagram of a groundwater level monitoring device according to an embodiment of the present invention;

[0033] Figure 3 is a schematic diagram of a groundwater level monitoring system according to an embodiment of the present invention;

[0034] Figure 4 FIG. 4 is a schematic diagram of a groundwater level monitoring device according to an embodiment of the present invention.

[0035] Description of reference numerals:

[0036] 400. Monitoring device; 410. Monitoring terminal; 420. UAV; 430. Control device; 440. Solar power supply unit. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0038] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, the accompanying drawings only show structures and / or processing steps closely related to the solutions according to the present invention, while other details that are not closely related to the present invention are omitted.

[0039] It should be emphasized that the term "include / comprises" when used herein refers to the existence of features, elements, steps or components, but does not exclude the existence or addition of one or more other features, elements, steps or components.

[0040] It should also be noted that, unless otherwise specified, the term "connection" herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0041] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0042] First, refer to Figure 1 A groundwater level monitoring method 100 according to an embodiment of the present application is described. Figure 1 As shown, the monitoring method 100 may include steps S110 to S150, which are specifically as follows:

[0043] In step S110, a thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area is obtained; wherein the existing data area refers to a selected area within the area including at least one groundwater monitoring well.

[0044] In step S120, the temperature anomaly area in the target monitoring blank area is identified, and the first groundwater interpretation water level is obtained; the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located is used as the target data area, the corresponding temperature anomaly area in the target data area is identified, and the second groundwater interpretation water level is obtained.

[0045] In step S130, groundwater monitoring data of the target data area at the same time is acquired based on real-time dynamic monitoring of groundwater monitoring wells in the target data area, including groundwater monitoring water level, permeability coefficient and water temperature.

[0046] In step S140, a logistic regression analysis is performed based on the second groundwater interpretation water level, the groundwater monitoring data and the geological parameters of the target data area to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level; wherein the geological parameters include permeability, aquifer thickness and aquifer porosity.

[0047] In step S150, the constructed fitting function mathematical model is used to input the first groundwater interpretation water level to obtain the groundwater level of the target monitoring blank area.

[0048] In an embodiment of the present application, first, a thermal infrared image is obtained, the range of which covers the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; then, the temperature anomaly area of the target monitoring blank area in the thermal infrared image is identified, and a first groundwater interpretation water level is obtained, and the corresponding temperature anomaly area of the target data area in the thermal infrared image is identified, and a second groundwater interpretation water level is obtained; then, based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, groundwater monitoring data of the target data area at the same time is obtained, including groundwater monitoring water level, permeability coefficient and water temperature; based on the second groundwater interpretation water level, groundwater monitoring data and geological parameters of the target data area, a logistic regression analysis is performed to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level; finally, using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level of the target monitoring blank area.

[0049] From the description of the above process, it can be seen that according to the monitoring method 100 of the embodiment of the present application, the groundwater monitoring data of the target data area (traditional measured monitoring data), the first groundwater interpretation water level and the second groundwater interpretation water level (remote sensing data), and the geological parameters of the target data area are integrated to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level, thereby realizing groundwater level monitoring in monitoring blank areas and expanding the spatial scope of groundwater monitoring.

[0050] The following will be combined Figure 1 The contents of the above steps of the monitoring method 100 according to the embodiment of the present application are described in detail.

[0051] In an embodiment of the present application, step S110 acquires a thermal infrared image covering the target monitoring blank area and at least one existing data area within the same hydrogeological unit as the target monitoring blank area. The existing data area is a selected area that includes at least one groundwater monitoring well. For example, an existing data area includes one groundwater monitoring well. Another existing data area includes three groundwater monitoring wells.

[0052] It should be noted that the groundwater monitoring well in this embodiment should be understood to include corresponding monitoring equipment, which can monitor the groundwater level, water quality, temperature, conductivity and other data within the jurisdiction (i.e., the existing data area). Through traditional sensor monitoring, Internet of Things and wireless communication monitoring, etc., continuous and real-time dynamic monitoring data is accumulated to timely grasp the dynamic changes.

[0053] Specifically, to obtain thermal infrared images that meet the above conditions, a series of raw thermal infrared images covering the target monitoring blank area and at least one groundwater monitoring well can be pre-acquired. The existing data area is defined as an area of a selected size centered on the groundwater monitoring well. For example, a circular area with a radius of 500 meters, or a rectangular area with a length of 1000 meters and a width of 500 meters, centered on the groundwater monitoring well. The shape and size of the existing data area can be adjusted as needed and are not limited.

[0054] Next, based on field surveys or relevant data, the hydrogeological unit information for the target monitoring blank area and each existing data area is obtained. If an original thermal infrared image contains existing data areas that share the same hydrogeological unit as the target monitoring blank area, for example, if one, two, or more existing data areas have the same hydrogeological unit information as the target monitoring blank area, then the original thermal infrared image is the desired thermal infrared image and the next step is performed.

[0055] If all existing data areas are not in the same hydrogeological unit as the target monitoring blank area, the coverage of the original thermal infrared image will continue to be expanded until a thermal infrared image of an existing data area is obtained that is in the same hydrogeological unit as the target monitoring blank area.

[0056] To obtain thermal infrared images, or raw thermal infrared images, drones equipped with high-precision thermal imagers can be used for aerial photography. LiDAR can also be used to obtain centimeter-level resolution data.

[0057] In an embodiment of the present application, in step S120, the temperature anomaly area of the target monitoring blank area is identified, and the first groundwater interpretation water level is obtained; the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located is used as the target data area, the corresponding temperature anomaly area of the target data area is identified, and the second groundwater interpretation water level is obtained.

[0058] Specifically, before identifying the thermal infrared image obtained in step S110, preprocessing such as calibration, correction, and wavelet denoising can be performed to convert the original grayscale value into surface temperature (unit: ° C), eliminate temperature noise caused by clouds and instantaneous meteorological changes, eliminate errors, interference and inconsistency, and perform equalization, linear stretching, filtering, etc., so that the grayscale value of the image is more evenly distributed throughout the image, thereby increasing the visual analysis effect of the image.

[0059] When groundwater is shallow and abundant, it affects surface temperature, causing it to appear abnormally different from surrounding areas. Analysis of thermal infrared imagery can identify target monitoring blank areas and corresponding temperature anomalies within target data areas. For example, a hybrid SVM-random forest classification algorithm can be used to distinguish groundwater-affected areas (temperature anomalies) from background areas. For example, in an image of a Gobi desert region, the groundwater discharge area was found to be 2-3°C cooler than the surrounding area, achieving a 92% classification accuracy. The SVM (support vector machine) algorithm, a classification algorithm based on statistical learning, is used to distinguish temperature anomalies.

[0060] Alternatively, a semantic segmentation network such as U-Net can be used to directly extract temperature anomaly areas from thermal infrared images, replacing traditional classification algorithms.

[0061] Of course, low-power temperature and humidity sensors (such as LoRa nodes) can also be deployed in the target monitoring blank area and the target data area to assist in calibrating the surface temperature, complement the remote sensing data, and form a "sky-ground" collaborative monitoring network.

[0062] Next, using the formula Calculate the water level.

[0063] in, It is the first interpreted groundwater level or the second interpreted groundwater level. is the average value of ground temperature anomaly.

[0064] is the permeability, reflecting the connectivity of pores or cracks, is the aquifer thickness, 、 and is the corresponding weight coefficient.

[0065] It is understood that while the above scheme demonstrates the use of thermal infrared imagery to obtain the first interpreted groundwater level in the target monitoring blank area and the second interpreted groundwater level in the target data area, other methods are also possible. For example, surface deformation can be monitored using radar satellite phase differences using Interferometric Synthetic Aperture Radar (InSAR), or the first and second interpreted groundwater levels can be obtained by measuring changes in the Earth's gravity field using the Gravity Recovery and Climate Experiment (GRACE) satellite. Alternatively, the first and second interpreted groundwater levels can be determined through a comprehensive consideration of the aforementioned multimodal data complementarity.

[0066] In an embodiment of the present application, in step S130, groundwater monitoring data of the target data area at the same time is obtained based on real-time dynamic monitoring of groundwater monitoring wells in the target data area, including groundwater monitoring water level, permeability coefficient and water temperature.

[0067] Specifically, since groundwater monitoring wells can accumulate continuous, real-time dynamic monitoring data through traditional sensor monitoring, Internet of Things (IoT) and wireless communication monitoring, groundwater monitoring data for the target data area at the same time can be obtained from the real-time dynamic monitoring data of the groundwater monitoring wells in the target data area. This includes groundwater monitoring water level, groundwater permeability coefficient, and groundwater temperature. The term "same time" refers to the time period during which the thermal infrared image acquired in step S110, covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area, was captured.

[0068] In an embodiment of the present application, in step S140, a logistic regression analysis is performed based on the second groundwater interpretation water level, groundwater monitoring data and geological parameters of the target data area to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level; wherein the geological parameters include permeability, aquifer thickness and aquifer porosity.

[0069] Specifically, the following steps may be included:

[0070] Step S141: Establish a mathematical model between the groundwater monitoring level and the second groundwater interpretation level.

[0071]

[0072] in, To monitor the water level of groundwater, Interpret the water level for the second groundwater, It is one of the groundwater monitoring data of water level, groundwater permeability coefficient, groundwater temperature, permeability, aquifer thickness and aquifer porosity in the target data area. For the corresponding The weight coefficient of .

[0073] In step S142, multiple sets of second groundwater interpretation water levels, groundwater monitoring water levels, groundwater permeability coefficients, groundwater temperatures, and permeability, aquifer thickness, and aquifer porosity data of the target data area at the same time are used to implement a numerical algorithm using a computer and select a suitable solver for solving the problem.

[0074] Then the model is verified: the solution is compared and analyzed with the actual monitoring data, and the weight coefficients in the model are adjusted until the calculated results are close to the measured data, for example, the absolute value of the error is between 2% and 5%.

[0075] The Bayesian algorithm can also be used to automatically search for the optimal weight coefficient of the mathematical model , instead of manually adjusting the coefficient.

[0076] Step S143 , reselect at least one set of second groundwater interpretation water level, groundwater monitoring water level, groundwater permeability coefficient, groundwater temperature, and permeability, aquifer thickness and aquifer porosity data of the target data area to verify the model to ensure reliability.

[0077] Step S144: If the verification fails, repeat the above steps S142 and S143 until the verification passes.

[0078] In an embodiment of the present application, in step S150 , the constructed fitting function mathematical model is used to input the first groundwater interpretation water level to obtain the groundwater level of the target monitoring blank area.

[0079] Specifically, the fitting function mathematical model constructed in step S140 is constructed. Since the target monitoring blank area and the target data area are in the same hydrogeological unit, the first groundwater interpretation water level can be input into the fitting function mathematical model to obtain a more accurate groundwater level in the target monitoring blank area, thereby solving the problem that it is difficult to monitor the groundwater level in the target monitoring blank area due to the difficulty in deploying groundwater monitoring equipment.

[0080] Blockchain technology can also be used to record thermal infrared image data (remote sensing data), groundwater monitoring well sensor data (monitoring data) and model output data (groundwater level) to ensure that the data cannot be tampered with and improve the credibility of monitoring results.

[0081] Based on the above description, according to the monitoring method of the embodiment of the present application, based on thermal infrared image remote sensing data and interpretation data, etc., it integrates factors closely related to groundwater burial, enriches groundwater monitoring methods, and reflects the actual groundwater conditions in monitoring blank areas as closely as possible, thereby realizing the groundwater monitoring range and supplementing the spatial characteristics and change laws of groundwater in monitoring blank areas such as groundwater recharge areas in mountainous areas and groundwater discharge areas in Gobi areas.

[0082] refer to Figure 2 The monitoring device 200 for implementing the monitoring method according to an embodiment of the present application includes a processor 210 and a memory 220. The monitoring device 200 may include one or more processors 210 and one or more memories 220. The memory 220 stores an executable program run by the processor 210. When the executable program is run by the processor 210, the processor 210 executes the monitoring method 100 according to the embodiment of the present application described above.

[0083] The processor 210 may be a central processing unit (CPU) or other processing units having data processing capabilities and / or instruction execution capabilities.

[0084] The memory 220 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 210 may run the program instructions to implement the client functions and / or other desired functions in the embodiments of the present application described herein (implemented by the processor). Various applications and various data may also be stored in the computer-readable storage medium, such as various data used and / or generated by the application.

[0085] The monitoring device 200 may also include input devices and output devices, and these components are interconnected through a bus system and / or other forms of connection mechanisms. Figure 2 The components and structures of the monitoring device 200 shown are merely exemplary and non-limiting. The monitoring device 200 may also have other components and structures as needed.

[0086] The input device may be a device used by a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, a touch screen, etc. In addition, the input device may also be any interface for receiving information.

[0087] The output device may output various information (eg, images or sounds) to the outside (eg, a user), and may include one or more of a display, a speaker, etc. In addition, the output device may also be any other device with an output function.

[0088] Illustratively, the example monitoring device 200 for implementing the monitoring method 100 according to an embodiment of the present application can be applied to terminal devices (such as mobile phones), tablet computers, laptop computers, ultra-mobile personal computers (UMPCs), handheld computers, netbooks, personal digital assistants (PDAs), wearable devices (such as smart watches, smart glasses, or smart helmets), augmented reality (AR), virtual reality (VR) devices, smart home devices, vehicle-mounted computers, and other electronic devices. The embodiments of the present application do not impose any restrictions on this.

[0089] Those skilled in the art can understand the specific operations of the monitoring device 200 for implementing the monitoring method 100 according to the embodiment of the present application in combination with the contents described above. For the sake of brevity, the specific details are not repeated here, and only some main operations of the processor 210 are described.

[0090] In one embodiment of the present application, when the executable program is executed by the processor 210, the processor 210 executes the following steps: obtaining a thermal infrared image covering a target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; wherein the existing data area refers to a selected area within the area including at least one groundwater monitoring well; identifying a temperature anomaly area in the target monitoring blank area and obtaining a first groundwater interpretation water level; identifying a corresponding temperature anomaly area in the target data area and obtaining a second groundwater interpretation water level; obtaining groundwater monitoring data of the target data area at the same time based on real-time dynamic monitoring of the groundwater monitoring wells in the target data area, including groundwater monitoring water level, permeability coefficient and water temperature; performing a logistic regression analysis based on the second groundwater interpretation water level, the groundwater monitoring data and the geological parameters of the target data area to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level; wherein the geological parameters include permeability, aquifer thickness and aquifer porosity; and using the constructed fitting function mathematical model, inputting the first groundwater interpretation water level to obtain the groundwater level in the target monitoring blank area.

[0091] The above exemplary shows the monitoring method 100 according to the embodiment of the present application. Figure 3 A monitoring system 300 provided in another aspect of an embodiment of the present application is described.

[0092] Reference Figure 3 The following describes an example monitoring system 300 for implementing the monitoring method of an embodiment of the present application. The monitoring system 300 may include a thermal infrared image acquisition module 310, a water level interpretation acquisition module 320, a monitoring data acquisition module 330, a model building module 340, and a water level acquisition module 350.

[0093] The thermal infrared image acquisition module 310 is used to: acquire a thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; wherein the existing data area refers to a selected area within the area that includes at least one groundwater monitoring well.

[0094] The interpreted water level acquisition module 320 is used to: identify the temperature anomaly area in the target monitoring blank area and obtain the first interpreted groundwater water level; identify the corresponding temperature anomaly area in the target data area and obtain the second interpreted groundwater water level.

[0095] The monitoring data acquisition module 330 is used to acquire groundwater monitoring data of the target data area at the same time based on real-time dynamic monitoring of groundwater monitoring wells in the target data area, including groundwater monitoring water level, permeability coefficient and water temperature.

[0096] The model construction module 340 is used to perform a logistic regression analysis based on the second groundwater interpretation water level, the groundwater monitoring data, and the geological parameters of the target data area to construct a fitting function mathematical model that relates the second groundwater interpretation water level and the groundwater monitoring water level; wherein the geological parameters include permeability, aquifer thickness, and aquifer porosity.

[0097] The water level acquisition module 350 is used to: use the constructed fitting function mathematical model and input the first groundwater interpretation water level to obtain the groundwater level of the target monitoring blank area.

[0098] The monitoring system 300 proposed in the embodiment of the present invention solves the problem of difficulty in groundwater monitoring in monitoring blank areas through the technical route of "remote sensing data + traditional monitoring + mathematical model", and realizes large-scale, high-efficiency and low-cost dynamic groundwater monitoring. It is particularly suitable for groundwater monitoring in monitoring blank areas such as complex terrain and uninhabited areas.

[0099] The following combination Figure 4 A groundwater monitoring device 400 provided in another aspect of an embodiment of the present application is described.

[0100] Reference Figure 4 An example monitoring device 400 for implementing the monitoring method according to an embodiment of the present application is described.

[0101] The monitoring device 400 may include a monitoring terminal 410 , a drone 420 , and a control device 430 .

[0102] Specifically, the monitoring terminal 410 installed in the groundwater monitoring well of the existing data area, for example, uses various detection sensors to monitor the groundwater level, permeability coefficient and water temperature of each existing data area in real time.

[0103] The drone 420 equipped with a thermal imager is used to take thermal infrared images from the air that cover the target monitoring blank area and the existing data area, so as to take the required thermal infrared images that cover the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area.

[0104] A control device 430 is connected to the monitoring terminal 410 and the drone 420. The control device 430 includes a processor and a memory. When the processor executes the computer-executable instructions stored in the memory, the following steps are implemented:

[0105] The acquisition range covers the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area.

[0106] Identify the temperature anomaly area in the target monitoring blank area and obtain the first groundwater interpretation water level; take the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located as the target data area, identify the corresponding temperature anomaly area in the target data area, and obtain the second groundwater interpretation water level.

[0107] Based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, the groundwater monitoring data of the target data area at the same time are obtained, including the groundwater monitoring water level, permeability coefficient and water temperature.

[0108] A logistic regression analysis was performed based on the second groundwater interpretation water level, groundwater monitoring data, and geological parameters of the target data area to construct a fitting function mathematical model that relates the second groundwater interpretation water level and the groundwater monitoring water level; among them, the geological parameters include permeability, aquifer thickness, and aquifer porosity.

[0109] Using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level in the target monitoring blank area.

[0110] Regarding how to obtain the first groundwater interpretation water level and the second groundwater interpretation water level, and how to construct a fitting function mathematical model that associates the second groundwater interpretation water level and the groundwater monitoring water level, the corresponding content is the same as that in the embodiment described above and will not be repeated here.

[0111] The control device 430 can be installed at the groundwater monitoring well corresponding to the target data area or at a remote monitoring center. For example, the control device 430 at the groundwater monitoring well in the target data area can be integrated with an AI chip (such as Jetson Nano or Kendryte K210) to perform thermal infrared image preprocessing, water level interpretation and analysis, and groundwater level calculation locally, and only upload the results to the remote monitoring center or the cloud to reduce communication energy consumption.

[0112] Of course, to maintain normal operation at the groundwater monitoring well, a solar power supply unit 440 can be integrated into the monitoring terminal, for example using a flexible solar thin-film battery. Combined with supercapacitor energy storage, this enables long-term maintenance-free operation, particularly suitable for areas with abundant sunlight, such as the Gobi Desert. If the control device is also located at the groundwater monitoring well, the solar power supply unit 440 can also provide power for it. In areas without GPS signals, a geomagnetic sensor can be used to assist in locating the device.

[0113] In addition, according to an embodiment of the present application, the present application further provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, it is used to perform the corresponding steps of the monitoring method 100 of the embodiment of the present application. The storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0114] In addition, according to an embodiment of the present application, the present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the monitoring method of the embodiment of the present application.

[0115] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely illustrative and are not intended to limit the scope of the present application. Various changes and modifications may be made therein by those skilled in the art without departing from the scope and spirit of the present application. All such changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0116] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units described is merely a logical function division. In actual implementation, other division methods may be used, such as combining or integrating multiple units or components into another device, or ignoring or not performing some features.

[0118] Furthermore, those skilled in the art will appreciate that although some embodiments described herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of this application and to form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

[0119] It should be noted that the above embodiments illustrate rather than limit the present application, and that a person skilled in the art may devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbols placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present application may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0120] The above description is merely a specific embodiment or illustration of a specific embodiment of the present application, and the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. The scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A groundwater level monitoring device, characterized in that: The monitoring device comprises: A monitoring terminal installed in a groundwater monitoring well in an existing data area, for real-time monitoring of groundwater level, permeability coefficient, and water temperature; an existing data area is a selected area within a region that includes at least one groundwater monitoring well; Unmanned aerial vehicles (UAVs) for capturing aerial thermal infrared images covering target surveillance gaps and areas with existing data; and A control device is communicatively connected to the monitoring terminal and the drone, the control device including a processor and a memory, and when the processor executes computer-executable instructions stored in the memory, the following steps are implemented: Acquire a thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; Identify the temperature anomaly area in the target monitoring blank area and obtain the first groundwater interpretation water level; take the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located as the target data area, identify the corresponding temperature anomaly area in the target data area, and obtain the second groundwater interpretation water level; Based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, the groundwater monitoring data of the target data area at the same time is obtained, including the groundwater monitoring water level, permeability coefficient and water temperature; A logistic regression analysis is performed based on the second interpreted groundwater level, groundwater monitoring data, and geological parameters of the target data area to construct a fitting function mathematical model that relates the second interpreted groundwater level to the groundwater monitoring level; the geological parameters include permeability, aquifer thickness, and aquifer porosity; Using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level in the target monitoring blank area.

2. The monitoring device according to claim 1, characterized in that The control device is installed at the groundwater monitoring well corresponding to the target data area or at a remote monitoring center; and / or It also includes a solar power supply unit arranged in the existing data area, which is used to supply power to the monitoring terminal and / or the control device.

3. A method for monitoring groundwater level, characterized in that: The monitoring method comprises: Acquire a thermal infrared image from the thermal infrared image captured by the drone, the thermal infrared image covering the target monitoring blank area and at least one existing data area in the same hydrogeological unit as the target monitoring blank area; wherein the existing data area is a selected area within the region that includes at least one groundwater monitoring well; Identify the temperature anomaly area in the target monitoring blank area and obtain the first groundwater interpretation water level; take the existing data area where the groundwater monitoring well closest to the target monitoring blank area is located as the target data area, identify the corresponding temperature anomaly area in the target data area, and obtain the second groundwater interpretation water level; Based on the real-time dynamic monitoring of the groundwater monitoring wells in the target data area, the groundwater monitoring data of the target data area at the same time is obtained, including the groundwater monitoring water level, permeability coefficient and water temperature; A logistic regression analysis is performed based on the second interpreted groundwater level, groundwater monitoring data, and geological parameters of the target data area to construct a fitting function mathematical model that relates the second interpreted groundwater level to the groundwater monitoring level; the geological parameters include permeability, aquifer thickness, and aquifer porosity; Using the constructed fitting function mathematical model, the first groundwater interpretation water level is input to obtain the groundwater level in the target monitoring blank area.

4. The monitoring method according to claim 3, characterized in that: Also includes: Pre-acquire an original thermal infrared image covering the target monitoring blank area and at least one groundwater monitoring well, and define an area of selected size with the groundwater monitoring well as the existing data area; If there is an existing data area in the original thermal infrared image that is in the same hydrogeological unit as the target monitoring blank area, the original thermal infrared image is the required thermal infrared image.

5. The monitoring method according to claim 4, characterized in that: If all existing data areas are not in the same hydrogeological unit as the target monitoring blank area, the coverage of the original thermal infrared image is expanded until there is an existing data area in the same hydrogeological unit as the target monitoring blank area.

6. The monitoring method according to claim 3, characterized in that: It also includes equalization, linear stretching and filtering of the acquired thermal infrared image to make the grayscale value of the image more evenly distributed within the entire image range.

7. The monitoring method according to claim 3, characterized in that: Obtaining a first interpreted groundwater level and / or a second interpreted groundwater level specifically includes: The SVM-random forest hybrid model was introduced using the classification algorithm, combined with wavelet denoising processing to eliminate the instantaneous interference of surface temperature and obtain the corresponding groundwater interpretation water level.

8. The monitoring method according to claim 3, characterized in that: The construction of a fitting function mathematical model correlating the second groundwater interpretation water level and the groundwater monitoring water level includes: Establish a mathematical model between the groundwater monitoring level and the second groundwater interpretation level, in, To monitor the water level of groundwater, Interpret the water level for the second groundwater, It is one of the groundwater monitoring data of water level, groundwater permeability coefficient, groundwater temperature, permeability, aquifer thickness and aquifer porosity in the target data area. For the corresponding The weight coefficient of Using multiple sets of simultaneous second groundwater interpretation water levels, groundwater monitoring water levels, groundwater permeability coefficients, groundwater temperatures, and permeability, aquifer thickness, and aquifer porosity data for the target data area, a computer is used to calculate and adjust the coefficients in the model until the calculated results are close to the measured data; Reselect at least one set of second groundwater interpretation water level, groundwater monitoring water level, groundwater permeability coefficient, groundwater temperature, and permeability, aquifer thickness and aquifer porosity data of the target data area to verify the model; if the verification fails, repeat the above steps.

9. The monitoring method according to claim 3, characterized in that: Based on thermal infrared images, a semantic segmentation network is used to directly extract temperature anomaly areas from thermal infrared images.

10. The monitoring method according to claim 3, characterized in that: Thermal infrared images are obtained by using drones equipped with thermal imagers.

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