Underground water source detection method, medium and equipment

Abstract

The invention discloses an underground water source detection method, medium and equipment, and relates to the technical field of geophysical exploration, and the method comprises the steps: obtaining hydrogeological data, building a hydrogeological database, and extracting an underground water potential evaluation factor from the hydrogeological database information; performing groundwater potential evaluation by using the groundwater potential evaluation factor through an analytic hierarchy process or a neural network method; determining an optimal water-rich area based on hydrogeological data in combination with groundwater potential evaluation, carrying out field geophysical resistivity profile method water exploration in the optimal water-rich area, processing and explaining a resistivity profile through an inversion method, obtaining groundwater surface depth and lithologic distribution, and determining a drilling position; a water pumping test is conducted in the drill hole, a relation curve of the water inflow and the water level drop is drawn according to the water pumping test result, the curve is fitted through a numerical method, and the water inflow of the drill hole is calculated. According to the invention, underground water source detection can be rapidly carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of geophysical exploration, and particularly to a method, medium, and device for detecting underground water sources. Background Art

[0002] In mountainous areas and remote disaster areas, the terrain is complex and the geological conditions are harsh, which are prone to induce various natural disasters. In some mountainous areas, there is a serious shortage of water on a daily basis, and disasters have caused serious damage to infrastructure such as roads and water networks, posing a huge challenge to the emergency rapid water supply at the disaster site. Therefore, providing an emergency water source solution for mountainous areas and remote disaster areas to meet the water source needs of on-site disaster relief is an important and urgent task. In a mountainous environment, determining such an emergency water source is a very difficult problem, requiring continuous extensive and detailed hydrogeological survey work, which takes a long time and cannot meet the requirements of emergency rapid water supply. The surface water at the disaster site may be polluted or dried up due to the disaster, while the underground water source is relatively clean due to the protection and filtration of rock layers. Therefore, studying a rapid detection method for underground water sources plays an important role in ensuring the domestic water use of disaster victims and coping with major natural disasters and emergencies.

[0003] The existing technologies for rapid detection methods of underground water sources have some disadvantages and limitations, mainly including the following aspects: (1) Geological condition restrictions: Different geological conditions have a great impact on the applicability of detection technologies. For example, the high-density resistivity method has good detection effects on groundwater channels formed under the control of faults, but is not suitable for areas with exposed bedrock in karst areas. (2) Complex data processing: Existing data processing and analysis methods often rely on manual operations, with low efficiency and easy errors. In the face of complex underground spaces and a large amount of data, how to achieve rapid and effective data processing and analysis is a challenge. (3) High cost: Some efficient detection technologies, such as shallow seismic reflection method, cross-hole electromagnetic wave tomography method, etc., have high detection costs. This makes it difficult to be widely applied in some projects with limited budgets. (4) Long time for underground water exploration: Conventional underground water exploration requires long-term extensive and detailed hydrogeological survey work. Summary of the Invention

[0004] The purpose of the present invention is to propose a rapid method for detecting underground water sources to solve the problem of long time for conventional underground water exploration, including the following steps:

[0005] S1. Obtain hydrogeological data and establish a hydrogeological database, and extract groundwater potential evaluation factors from the information in the hydrogeological database;

[0006] S2. Use the groundwater potential evaluation factors to evaluate the groundwater potential by the analytic hierarchy process or the neural network method;

[0007] S3. Based on the hydrogeological database, combine with groundwater potential assessment to determine the optimal water-rich area, conduct on-site geophysical resistivity profiling for water exploration, and interpret the resistivity profile through inversion to obtain the depth of the groundwater water table and the lithology distribution, and determine the borehole location;

[0008] S4. Conduct a pumping test in the borehole, draw the relationship curve between the water yield and the drawdown according to the pumping test results, and use numerical methods to fit the curve and calculate the borehole water yield.

[0009] Furthermore, the layers of the hydrogeological database include: hydrogeological type, basic geological type, and geographic base map type;

[0010] The data types in the hydrogeological type layer include: groundwater type, groundwater water richness, groundwater salinity, groundwater chemical type, groundwater water quality characteristic points, hydrogeological characteristic points, and hydrogeological characteristic boundaries;

[0011] The data types in the basic geological type layer include: stratigraphic division, stratigraphic boundary, tectonic line, and stratigraphic occurrence;

[0012] The data type in the geographic base map type layer includes: geographic base map.

[0013] Furthermore, the groundwater potential assessment factors include four types: geology, topography, hydrology, and groundwater indication;

[0014] The groundwater potential assessment factors of the geological type include: formation lithology, fracture density;

[0015] The groundwater potential assessment factors of the topographic type include: slope, convergence index, terrain wetness index, plan curvature, profile curvature, and drainage density;

[0016] The groundwater potential assessment factors of the hydrological type include: rainfall, river distance;

[0017] The groundwater potential assessment factors of the groundwater indication type include: EVI vegetation index, land cover, and spring index.

[0018] Furthermore, the convergence index is obtained by averaging the deviation between the aspect of adjacent cells and the direction of the central cell and subtracting 90 degrees.

[0019] Furthermore, the weights of the groundwater potential assessment factors are determined by the analytic hierarchy process, specifically:

[0020] Determine the groundwater potential as the analysis target;

[0021] Decompose the groundwater potential assessment factors related to the analysis target into three levels: target, criterion, and scheme. The groundwater potential assessment factors for hierarchical analysis include 9: formation lithology, fracture density, spring index, rainfall, river distance, slope, drainage density, catchment index, and EVI vegetation index.

[0022] Compare the groundwater potential assessment factors pairwise to obtain a pairwise comparison matrix:

[0023]

[0024] Among them, M represents the pairwise comparison matrix, and m nn represents the comparison weight of the nth groundwater potential assessment factor with the nth groundwater potential assessment factor;

[0025] The weight calculation formula for the groundwater potential assessment factor is:

[0026]

[0027] Among them, W n represents the weight of the nth groundwater potential assessment factor, GM n represents the geometric mean of the comparison weights of the nth groundwater potential assessment factor with other groundwater potential assessment factors, m 1n represents the comparison weight of the 1st groundwater potential assessment factor with the nth groundwater potential assessment factor, m 2n represents the comparison weight of the 2nd groundwater potential assessment factor with the nth groundwater potential assessment factor, m Nn represents the comparison weight of the Nth groundwater potential assessment factor with the nth groundwater potential assessment factor, and N represents the number of groundwater potential assessment factors.

[0028] Normalize the data corresponding to each potential assessment factor of each grid data to obtain the relative weight values of each potential assessment factor among each grid data. The calculation formula for the groundwater assessment potential value of the kth grid data is as follows:

[0029]

[0030] Among them, GWP k is the groundwater potential value of the kth grid data, N is the number of groundwater potential assessment factors, W j is the weight of the jth groundwater potential assessment factor, is the weight value of the kth grid data based on the jth assessment factor relative to other grid data.

[0031] Further, on the basis of the research area of the hierarchical analysis, the area is expanded, and groundwater potential evaluation factors are added. The neural network method is used to evaluate the groundwater potential. The added groundwater potential evaluation factors include: topographic wetness index, plan curvature, profile curvature, and land cover.

[0032] Further, the groundwater evaluation factor data is converted into a raster data grid with a spatial resolution of 30m.

[0033] Further, the relationship between the level of groundwater potential and the water yield of the borehole includes: when the water yield of the borehole < 1t / d·m, the level of groundwater potential is very low; when the water yield is between 1 - 20t / d·m, the level of groundwater potential is low; when the water yield is between 20 - 400t / d·m, the level of groundwater potential is medium; when the water yield is between 400 - 4000t / d·m, the level of groundwater potential is high; when the water yield > 4000t / d·m, the level of groundwater potential is very high.

[0034] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned underground water source detection method is realized.

[0035] The present invention also provides an electronic device, including a processor and a memory. The processor is connected to the memory. Among them, the memory is used to store a computer program, and the computer program includes computer-readable instructions. The processor is configured to call the computer-readable instructions to execute the above-mentioned underground water source detection method.

[0036] The beneficial effects brought by the technical solution provided by the present invention are:

[0037] The present invention first constructs a layer hydrogeological database to provide data support for the planning and decision-making of emergency water sources. Through the evaluation of groundwater potential values obtained by the analytic hierarchy process or the neural network method, the neural network can integrate more factors to adapt to mountainous areas with more complex geological backgrounds. Conduct on-site geophysical resistivity method for water exploration, infer the depth of the groundwater water table, and finely interpret the results of the electrical profile to finally obtain a more accurate lithological profile and determine the optimal drilling position of the borehole. Conduct a pumping test in the borehole, use numerical methods to fit the curve and calculate the water yield of the borehole according to the designed drawdown of the well. The present invention can quickly detect underground water sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is a flowchart of the underground water source detection method according to an embodiment of the present invention;

[0039] Figure 2 is a regression analysis diagram of the groundwater potential evaluation value by the analytic hierarchy process and the measured water yield of the borehole according to an embodiment of the present invention;

[0040] Figure 3 is a regression analysis diagram of groundwater potential assessment value and measured borehole water inflow according to a neural network method of an embodiment of the present invention;

[0041] Figure 4 is a schematic diagram of the groundwater potential analysis results of the study area of ​​the embodiment of the present invention;

[0042] Figure 5 It is a schematic diagram of geophysical profile interpretation and well determination according to an embodiment of the present invention;

[0043] Figure 6 is a stratum lithology interpretation profile of a single survey line in an embodiment of the present invention;

[0044] Figure 7 is a schematic diagram of a pumping test and its impact range according to an embodiment of the present invention;

[0045] Figure 8 It is a block diagram of an electronic device in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0046] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0047] Terminology explanation:

[0048] Groundwater potential: refers to the potential water supply capacity that can be tapped under the current conditions of development and utilization of groundwater resources, reflecting the direction of groundwater resource exploitation and utilization. It consists of two parts: groundwater exploitation potential and utilization potential. Groundwater utilization potential refers to the amount of water that can be saved and reused in the process of groundwater resource utilization under the current exploitation conditions to relieve groundwater exploitation pressure. Groundwater exploitation potential refers to the amount of exploitable resources and exploitation surplus that can be expanded relative to the assessed amount of exploitable resources in the groundwater exploitation layer under the current exploitation conditions.

[0049] Example 1: A flow chart of the underground water source detection method according to an embodiment of the present invention is as follows Figure 1 , specifically including the following steps:

[0050] S1. Obtain hydrogeological data and establish a hydrogeological database, and extract groundwater potential assessment factors from the hydrogeological database information.

[0051] Based on the geological cloud platform, hydrogeological data are collected and compiled to establish a hydrogeological database. The layers compiled in the hydrogeological database mainly include: hydrogeological category, basic geological category, and geographic base map category.

[0052] The data types in the hydrogeological layer include: groundwater type, groundwater water richness, groundwater mineralization, groundwater chemical type, groundwater water quality characteristic points, hydrogeological characteristic points, and hydrogeological characteristic boundaries. The primitive type of the groundwater type layer is polygon, and the data content mainly includes: description of groundwater type, aquifer layer, etc. Different layers are divided according to different aquifers. The primitive type of the groundwater water richness layer is polygon, and the data content mainly includes: description of aquifer type, water inflow, runoff modulus, spring flow, water richness level, etc. The primitive type of the groundwater mineralization layer is polygon, and the data content mainly includes: description of groundwater mineralization. The primitive type of the groundwater chemical type layer is polygon, and the data content mainly includes: description of various groundwater chemical types and water quality exceeding standard range. The primitive type of the groundwater water quality characteristic point is point, and the data content mainly includes: description of various groundwater chemical characteristic points, characteristic items, and characteristic values. The graphic element type of hydrogeological feature points is point element, and the data content mainly includes: boreholes, springs, water collection buildings and groundwater flow direction, etc. The graphic element type of hydrogeological feature boundaries is line element, and the data content mainly includes: fresh-salt water boundary, hydrogeological profile line, water level contour line, water level equal depth line, water quality single element contour line, river valley or alluvial fan front boundary, artesian basin boundary, etc.

[0053] The data types in the basic geological layer include: stratigraphic division, stratigraphic boundary, structural line, and stratigraphic occurrence. The graphic element type of stratigraphic division is surface element, and the data content mainly includes: layer unit, rock name, color, structure, structure, and thickness. The graphic element type of stratigraphic boundary is line element, and the data content mainly includes: describing the contact relationship of various strata. The graphic element type of structural line is line element, and the data content mainly includes: describing the nature, name, strike, fault plane dip, fault plane dip, fault hydrological properties, etc. The graphic element type of stratigraphic occurrence is point element, and the data content mainly includes: describing the type, dip, and dip of the stratigraphic occurrence.

[0054] The data types in the geographic base map layer include: geographic base map. The primitive types of the geographic base map are point, line, and surface, and the data content mainly includes: rivers, lakes or water bodies. The main contents of the hydrogeological database are shown in Table 1.

[0055] Table 1

[0056]

[0057]

[0058] The groundwater potential evaluation factors include four types: geology, topography, hydrology, and groundwater indicators. In this embodiment, 12 groundwater potential evaluation factors are selected and established according to the four types. The groundwater potential evaluation factors of the geology type include: formation lithology, fracture density. The groundwater potential evaluation factors of the topography type include: slope, convergence index, topographic wetness index, planar curvature, profile curvature, drainage density. The groundwater potential evaluation factors of the hydrology type include: rainfall, river distance. The groundwater potential evaluation factors of the groundwater indicator type include: EVI vegetation index, land cover, spring index. The data of each groundwater evaluation factor is uniformly converted into a raster data format with a spatial resolution of 30m to conduct a BP neural network groundwater potential evaluation for the study area.

[0059] The categories, data sources, and precisions of the groundwater potential evaluation factors are shown in Table 2.

[0060] Table 2

[0061]

[0062] Among them, the convergence index (reflects the concave-convex characteristics on a small spatial scale of the earth's surface, and can show the degree of tendency of adjacent surface units towards the central unit. Judging from its meaning, it is similar to planar curvature or horizontal curvature, but gives a smoother result. A negative convergence index indicates a depression (such as a valley, etc.), while a positive convergence index reflects a surface bulge (such as a ridge, etc.). Calculating the convergence index will use each unit around the central unit being calculated on the earth's surface, that is, observing and calculating the degree of tendency of the surrounding units towards the central unit. The convergence index is obtained by averaging the deviation of the slope direction of adjacent units from the direction of the central unit and subtracting 90 degrees. The convergence index also has an important relationship with the flow and recharge of groundwater. At the concave earth's surface, groundwater is more likely to gather, which is conducive to infiltration and recharge, while at the surface bulge, groundwater will flow in all directions, which is not conducive to groundwater recharge.

[0063] S2. Use the groundwater potential evaluation factors to conduct groundwater potential evaluation through the analytic hierarchy process or the neural network method.

[0064] Determine the weights of the groundwater potential evaluation factors through the analytic hierarchy process, specifically:

[0065] (1) Clearly define the analysis objective, and determine the groundwater potential as the analysis objective.

[0066] (2) Decompose the groundwater potential evaluation factors related to the analysis objective into three levels: objective, criterion, and plan. The groundwater potential evaluation factors used for the analytic hierarchy process include 9: formation lithology, fracture density, spring index, rainfall, river distance, slope, drainage density, convergence index, EVI vegetation index.

[0067] (3) Pairwise compare the groundwater potential assessment factors to obtain a pairwise comparison matrix:

[0068]

[0069] Among them, M represents the pairwise comparison matrix, and m nn represents the comparison weight of the nth groundwater potential assessment factor with the nth groundwater potential assessment factor.

[0070] The weight calculation formula for the groundwater potential assessment factors is:

[0071]

[0072] Among them, W n represents the weight of the nth groundwater potential assessment factor, GM n represents the geometric mean of the comparison weights of the nth groundwater potential assessment factor with other groundwater potential assessment factors, m 1n represents the comparison weight of the 1st groundwater potential assessment factor with the nth groundwater potential assessment factor, m 2n represents the comparison weight of the 2nd groundwater potential assessment factor with the nth groundwater potential assessment factor, m Nn represents the comparison weight of the Nth groundwater potential assessment factor with the nth groundwater potential assessment factor, and N represents the number of groundwater potential assessment factors.

[0073] In the embodiment of the present invention, the analytic hierarchy process is used in the study area to integrate 9 relatively representative groundwater potential assessment factors from four aspects: topography, geology, hydrology, and groundwater indication, namely slope, convergence index, rainfall, EVI vegetation index, drainage density, river distance, formation lithology, fracture density, and spring index. Uniformly convert the data of each groundwater assessment factor into a raster data format with a 30m spatial resolution to conduct an analytic hierarchy process groundwater potential assessment for the study area, normalize the data corresponding to each potential assessment factor of each raster data, and obtain the relative weight values of each potential assessment factor between each raster data. The calculation formula for the groundwater assessment potential value of the kth raster data is as follows:

[0074]

[0075] Among them, GWP k is the groundwater potential value of the kth raster data, N is the number of groundwater potential assessment factors, W j is the weight of the jth groundwater potential assessment factor, is the weight value of the kth raster data based on the jth assessment factor relative to other raster data.

[0076] According to the weights obtained by the analytic hierarchy process, it can be found that in this mountainous area with complex geological background, the most important factors affecting groundwater potential are geological factors and topographic factors. In order to effectively highlight the distribution characteristics of groundwater potential in the study area, the equal interval grading method is used to divide the groundwater potential of this area into very low, low, medium, high and very high groundwater potential areas. The range of each level of groundwater potential value is 0.26 - 0.37 (very low), 0.37 - 0.48 (low), 0.48 - 0.6 (medium), 0.6 - 0.71 (high) and 0.71 - 0.82 (very high) respectively. The regression analysis diagram of the groundwater potential evaluation value of the analytic hierarchy process in the embodiment of the present invention and the measured drilling water inflow is for reference Figure 2 .

[0077] The research area of the neural network groundwater potential evaluation is selected after appropriately expanding the research area of the analytic hierarchy process groundwater potential evaluation. It can integrate more factors to reasonably evaluate the groundwater potential of a larger mountainous area with complex geological background. Using the advantages of neural networks, 13 groundwater potential evaluation factors are integrated from four aspects: topography, geology, groundwater recharge and groundwater indication, namely slope, convergence index, terrain humidity index, plane curvature, profile curvature, rainfall, EVI vegetation index, land cover, drainage density, river distance, formation lithology, fracture density and spring index. In the study, the data of each groundwater evaluation factor is uniformly converted into a raster data format with a spatial resolution of 30m to conduct BP neural network groundwater potential evaluation on the study area. In the single hidden layer BP neural network, the number of input layer nodes is the number of groundwater potential evaluation factors, that is, 13, and the number of output layer nodes is only 1, that is, the groundwater potential value. After calculation, the appropriate number of hidden layer nodes is 4 - 14, and through experiments, the number of hidden layer nodes used is 8. The regression analysis diagram of the groundwater potential evaluation value of the neural network method in the embodiment of the present invention and the measured drilling water inflow is for reference Figure 3 .

[0078] The schematic diagram of the analysis results of groundwater potential in the study area of the embodiment of the present invention is for reference Figure 4 .

[0079] S3. Based on the hydrogeological database, combined with the groundwater potential evaluation, determine the best water-rich area, carry out on-site geophysical resistivity profile method for water exploration, and interpret the resistivity profile by inversion method to obtain the depth of the groundwater phreatic surface and lithology distribution, and determine the drilling position

[0080] Specifically, by comprehensively analyzing the evaluation results of the analytic hierarchy process and BP neural network for groundwater potential, and considering the high-density resistivity method with high construction efficiency and wide application in groundwater exploration among geophysical exploration methods, multiple high-density resistivity survey lines are arranged at appropriate positions in the high groundwater potential areas of the study area. According to the geological information and the anisotropic conditions of the rock strata, acquisition devices and acquisition parameters that meet the lateral and vertical resolutions are selected to ensure the acquisition of high-quality original data. Through the combination of high-density electrical method profiles with hydrological and geological data, the underground electrical structure is finely characterized, and finally the distribution of underground strata and fault structures is inferred. The schematic diagram of well location determination by geophysical profile interpretation in the embodiments of the present invention refers to Figure 5 。

[0081] The original data of the geophysical high-density electrical method are inversed with parameter constraints according to lithology, hydrology, geology, and borehole data, and the inversed resistivity profile is interpreted into the corresponding lithology profile to determine the water-bearing and water-resisting rock strata, and the phreatic surface interface is determined on the profile diagram. According to the undulating shape of the bottom interface of the aquifer, the optimal well-drilling water intake position is determined. This makes the geophysical electrical inversion result closer to the actual underground situation and improves the reliability of the inversion result profile. The fine interpretation of the electrical profile result finally obtains a more accurate lithology profile. The phreatic surface interface and the undulating shape of the bottom interface of the aquifer are determined on the lithology profile diagram, and the optimal well-drilling position is determined by comprehensively considering factors such as the geographical location of the borehole and the water conveyance distance. The schematic diagram of the lithology interpretation of the single survey line strata in the embodiments of the present invention refers to Figure 6 。

[0082] Drill wells at the determined water intake positions and conduct well logging. Integrate the well logging data of the boreholes and conduct stratigraphic lithology sampling on the borehole cores. Record the water emergence depth of the boreholes, measure the in-situ resistivity of the cores of the aquifer and the water-resisting layer, map the well logging results to the stratigraphic lithology profile inferred from the resistivity, and complete the fine correction of the lithology profile, further improving the accuracy and precision of the burial depths of the top and bottom plates of the water-bearing rock strata in the interpreted profile. Analyze the three-dimensional stratigraphic model of the study area through the lithology profiles inferred from multiple geophysical electrical profiles, analyze the recharge sources, runoff channels, and discharge methods of the aquifer, and finally determine the three-dimensional groundwater model of the study area. Other water intake positions are determined in the study area according to the three-dimensional groundwater model.

[0083] S4. Conduct a pumping test in the borehole, draw the relationship curve between the water yield and the drawdown according to the pumping test results, and use numerical methods to fit the curve and calculate the borehole water yield.

[0084] The relationship between the groundwater potential level and the water yield of a borehole is as follows: when the water yield of the borehole < 1 t / d·m, the groundwater potential level is very low; when the water yield is between 1 - 20 t / d·m, the groundwater potential level is low; when the water yield is between 20 - 400 t / d·m, the groundwater potential level is medium; when the water yield is between 400 - 4000 t / d·m, the groundwater potential level is high; when the water yield > 4000 t / d·m, the groundwater potential level is very high.

[0085] Conduct multiple pumping tests in the borehole to determine hydrogeological parameters such as the pumping permeability coefficient, recharge permeability coefficient, drawdown, and influence radius of the aquifer, and draw the relationship curve between the water yield and the drawdown. Use graphical method, difference method, or curvature method to determine the type of the curve equation of the water yield and the drawdown, and use numerical methods on the computer to find the parameters that can fit the curve, so as to obtain an accurate relationship equation between the water yield and the drawdown. Finally, substitute the maximum designed drawdown of the borehole into the relationship equation to find the maximum exploitable water yield, and give appropriate suggestions for water exploitation. The schematic diagram of the pumping test and its influence range in the embodiment of the present invention is referred to Figure 7 .

[0086] Embodiment 2: In an exemplary embodiment, it includes a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the above-mentioned groundwater source detection method.

[0087] Embodiment 3: Please refer to Figure 8 , in an exemplary embodiment, it further includes an electronic device, including at least one processor, at least one memory, and at least one communication bus.

[0088] Among them, a computer program is stored on the memory. The computer program includes computer-readable instructions. The processor calls the computer-readable instructions stored in the memory through the communication bus to execute the above-mentioned groundwater source detection method.

[0089] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for detecting underground water sources, characterized in that, It includes the following steps: S1. Obtain hydrogeological data and establish a hydrogeological database, and extract groundwater potential evaluation factors from the hydrogeological database information; S2. Use the groundwater potential evaluation factors to conduct groundwater potential evaluation through the analytic hierarchy process or the neural network method; S3. Based on the hydrogeological database, combine with the groundwater potential evaluation to determine the best water-rich area, and carry out on-site geophysical resistivity profiling for water exploration, and interpret the resistivity profile through the inversion method to obtain the depth of the groundwater water table and lithology distribution, and determine the borehole location; S4. Conduct a pumping test in the borehole, draw the relationship curve between the water yield and the drawdown according to the pumping test results, and use numerical methods to fit the curve and calculate the borehole water yield.

2. The underground water source detection method according to claim 1, characterized in that, The layers of the hydrogeological database include: hydrogeological type, basic geological type, and geographic base map type; The data types in the hydrogeological type layer include: groundwater type, groundwater richness, groundwater salinity, groundwater chemical type, groundwater water quality characteristic points, hydrogeological characteristic points, and hydrogeological characteristic boundaries; The data types in the basic geological type layer include: stratigraphic division, stratigraphic boundary, tectonic line, and stratigraphic occurrence; The data type in the geographic base map type layer includes: geographic base map.

3. The underground water source detection method according to claim 1, characterized in that, The groundwater potential evaluation factors include four types: geology, topography, hydrology, and groundwater indication; The groundwater potential evaluation factors of the geological type include: formation lithology, fracture density; The groundwater potential evaluation factors of the topographic type include: slope, convergence index, topographic wetness index, planar curvature, profile curvature, and drainage density; The groundwater potential evaluation factors of the hydrological type include: rainfall, river distance; The groundwater potential evaluation factors of the groundwater indication type include: EVI vegetation index, land cover, and spring index.

4. The underground water source detection method according to claim 1, characterized in that, The convergence index is obtained by averaging the deviation of the aspect of adjacent cells from the direction of the central cell and subtracting 90 degrees.

5. A method for detecting underground water sources according to claim 1, characterized in that, The groundwater evaluation factor data is converted into a raster data grid with a spatial resolution of 30m.

6. A method for detecting underground water sources according to claim 1, characterized in that Determine the weights of the groundwater potential evaluation factors through the analytic hierarchy process. Specifically: Determine the groundwater potential as the analysis target; Decompose the groundwater potential evaluation factors related to the analysis target into three levels: target, criterion, and scheme; there are 9 groundwater potential evaluation factors used for the analytic hierarchy process: formation lithology, fracture density, spring index, rainfall, river distance, slope, drainage density, convergence index, and EVI vegetation index; Compare the groundwater potential evaluation factors pairwise to obtain a pairwise comparison matrix: Among them, M represents the pairwise comparison matrix, and m nn represents the comparison weight of the nth groundwater potential evaluation factor with the nth groundwater potential evaluation factor; The weight calculation formula of the groundwater potential evaluation factor is: Among them, W n represents the weight of the nth groundwater potential evaluation factor, and GM n represents the geometric mean of the comparison weights of the nth groundwater potential evaluation factor with other groundwater potential evaluation factors, and m 1n represents the comparison weight of the first groundwater potential evaluation factor with the nth groundwater potential evaluation factor, and m 2n represents the comparison weight of the second groundwater potential evaluation factor with the nth groundwater potential evaluation factor, and m Nn represents the comparison weight of the Nth groundwater potential evaluation factor with the nth groundwater potential evaluation factor, where N represents the number of groundwater potential evaluation factors; Normalize the data corresponding to each potential evaluation factor of each raster data to obtain the relative weight values of each potential evaluation factor between each raster data. The calculation formula of the groundwater evaluation potential value of the kth raster data is as follows: Among them, GWP k is the groundwater potential value of the k-th grid data, N is the number of groundwater potential evaluation factors, and W j is the weight of the j-th groundwater potential evaluation factor, is the weight value of the k-th grid data based on the j-th evaluation factor relative to other grid data.

7. A method for detecting underground water sources according to claim 1, characterized in that, On the basis of the research area of the analytic hierarchy process, conduct regional expansion, add groundwater potential evaluation factors, and use the neural network method to conduct groundwater potential evaluation. The added groundwater potential evaluation factors include: topographic wetness index, planar curvature, profile curvature, and land cover.

8. A method for detecting underground water sources according to claim 1, characterized in that, The relationship between the grade of groundwater potential and the water inflow of boreholes is as follows: when the water inflow of boreholes < 1 t / d·m, the grade of groundwater potential is very low; when the water inflow is between 1 - 20 t / d·m, the grade of groundwater potential is low; when the water inflow is between 20 - 400 t / d·m, the grade of groundwater potential is medium; when the water inflow is between 400 - 4000 t / d·m, the grade of groundwater potential is high; when the water inflow > 4000 t / d·m, the grade of groundwater potential is very high.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements the method according to any one of claims 1 - 8.

10. An electronic device, characterized in that, It includes a processor and a memory, the processor is interconnected with the memory, wherein the memory is used to store a computer program, the computer program includes computer-readable instructions, and the processor is configured to call the computer-readable instructions to execute the method according to any one of claims 1 - 8.

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