Underground water pollution risk identification and division method and system

Abstract

The invention relates to the technical field of environmental engineering, in particular to an underground water pollution risk identification and division method and system. The method comprises the following steps: analyzing land surface coverage types of a plurality of positions including an industrial area, a farmland, a residential area and a commercial area according to a land surface image of a target area through satellite remote sensing image data, identifying the positions of pollution sources, marking the types, and drawing a pollution source distribution map. According to the invention, by analyzing the satellite image data and identifying the land cover type of the target area, the position and the type of the pollution source are judged, the pertinence of pollution source management is improved, and the underground water distribution condition and the pollution risk level are updated in real time in combination with the regional hydrogeological data and the meteorological information. The underground water vulnerability index is calculated by considering various natural attributes and external influence factors of an underground water system, the underground water risk is comprehensively reflected, and a scientific basis is provided for decision making.

Description

Technical Field

[0001] The present invention relates to the field of environmental engineering technology, and in particular to a method and system for identifying and dividing groundwater pollution risks. Background Art

[0002] The field of environmental engineering technology improves the natural environment by applying a variety of scientific and engineering principles, provides healthy water and air quality for humans, and achieves effective solid waste management. It involves water and air pollution control, waste treatment, water resources management, and environmental sustainability strategies. It uses a variety of technical means, including biochemical treatment, chemical treatment, physical treatment, and thermal treatment to treat and reduce pollution, protect the environment and human health, prevent pollution, and repair the polluted environment, including removing harmful pollutants from water during water treatment, ensuring a safe supply of water resources, conducting environmental impact assessments, and formulating resource management strategies to promote overall improvement of environmental quality.

[0003] Among them, the method of groundwater pollution risk identification and classification is used to evaluate and calibrate the risk level of groundwater pollution. By analyzing the pollution sources, pollutant quality and natural vulnerability data of groundwater, the pollution risk areas are identified and classified, which helps to carry out groundwater protection, pollution prevention and remediation work, ensure the safety and sustainable use of water resources, help understand the pollution situation, optimize resource allocation, achieve sustainable use and protection of groundwater resources, and reduce environmental and public health risks.

[0004] Traditional methods of groundwater pollution risk identification and classification still have limitations in groundwater pollution source identification and risk assessment. Relying on ground sampling and monitoring station data, it is inefficient when analyzing large areas, has a long data acquisition cycle, and is difficult to achieve real-time monitoring and assessment, resulting in a slow response when emergency pollution incidents occur, missing the best opportunity for pollution control and remediation. In the spatial expression of pollution data and the calculation of pollution loads, there is a lack of sufficient accuracy and geographic information support, which limits the accuracy of pollution risk assessment and the targeted nature of operations. It is difficult to accurately determine the propagation path and range of pollutants in groundwater, affecting the effective implementation of pollution prevention and control measures and the long-term effectiveness of water resources protection, and affecting the overall effectiveness and efficiency of environmental protection. Summary of the invention

[0005] In order to solve the technical problem of poor analysis efficiency in the prior art, an embodiment of the present invention provides a method and system for identifying and dividing groundwater pollution risks. The technical solution is as follows:

[0006] On the one hand, a method for identifying and classifying groundwater pollution risks is provided, the method comprising:

[0007] S1: Using satellite remote sensing image data and the surface images of the target area, analyze the surface cover types of multiple locations, including industrial areas, farmlands, residential areas, and commercial areas, identify the locations of pollution sources, mark the types, and draw a pollution source distribution map;

[0008] S2: Based on the pollution source distribution map, according to the location type of the pollution source, the chemical composition and emission intensity of multiple pollution sources are evaluated, the pollution loads of multiple locations are calculated, and mapped into the distribution map to generate pollution load marking information;

[0009] S3: Based on the pollution load marking information, collect hydrogeological data of the target area, analyze the groundwater distribution in the target area, combine the regional meteorological information, map it to the distribution map, and generate groundwater pollution distribution information;

[0010] S4: Analyze the groundwater pollution distribution information, consider the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity, calculate the vulnerability index of multiple locations in the target area, and generate groundwater vulnerability data;

[0011] S5: Based on the groundwater vulnerability data, combined with the pollution load information of the region, considering the water demand of multiple locations, analyzing and calculating the groundwater pollution risk level of multiple locations in the target area, and outputting a pollution risk level map.

[0012] Optionally, the pollution source distribution map includes pollution source location information, pollution source type identification, and surface coverage characteristics; the pollution load marking information includes chemical composition information of pollution sources, emission concentration and emission volume assessment data, and pollution source impact range; the groundwater pollution distribution information includes groundwater flow direction map, water level gradient map, and hydrogeological boundaries; the groundwater vulnerability data includes vulnerability index calculation results of multiple locations, a list of key influencing factors, and influencing factor weight setting parameters; the pollution risk level map includes risk levels of multiple locations, regional water demand information, and pollution spread trend prediction results.

[0013] Optionally, the satellite remote sensing image data is used to analyze the surface coverage types of multiple locations, including industrial areas, farmlands, residential areas, and commercial areas, based on the surface image of the target area, to identify the locations of pollution sources and mark the types. The specific steps of drawing a pollution source distribution map are as follows:

[0014] S101: Using satellite remote sensing image data, we can identify various surface features and cover types by analyzing images, including industrial buildings, farmland boundaries, residential buildings, and urban streets, and generate a surface cover classification map;

[0015] S102: Based on the land cover classification map, analyze the image and identify the location of pollution sources, including industrial discharge outlets and farmland drainage outlets, mark the locations of multiple pollution sources, and generate pollution source identification information;

[0016] S103: Based on the pollution source identification information, type information is annotated for the locations of multiple pollution sources, including industrial areas, farmlands, and residential water use, and a pollution source distribution map is drawn.

[0017] Optionally, based on the pollution source distribution map, according to the location type of the pollution source, the chemical composition and emission intensity of multiple pollution sources are evaluated, the pollution loads of multiple locations are calculated, and mapped into the distribution map, and the steps of generating the pollution load marking information are specifically as follows:

[0018] S201: Based on the pollution source distribution map, analyzing the chemical composition data of various pollution source samples, including the chemical composition of industrial emissions and the type of fertilizer used in farmland, to generate sample composition analysis data;

[0019] S202: Based on the sample component analysis data, combined with the spatial location information of the pollution source, according to the population density, industrial type, and farmland distribution information of the multiple locations, the emission intensity of the multiple pollution sources is evaluated, the pollution load of the multiple pollution sources is calculated, and the location pollution load information is generated;

[0020] S203: According to the location pollution load information and the location information of multiple pollution sources, the load information is mapped into a distribution map, including marking the load intensity of multiple pollution sources, and generating pollution load marking information.

[0021] Optionally, based on the pollution load marking information, hydrogeological data of the target area is collected, the groundwater distribution in the target area is analyzed, and the groundwater distribution is mapped to a distribution map in combination with regional meteorological information. The steps of generating groundwater pollution distribution information are specifically as follows:

[0022] S301: Based on the pollution load mark information, collect hydrological and geological data of multiple locations in the target area to generate hydrological data collection results;

[0023] S302: Based on the hydrological data collection results, collect meteorological information of the target area, record the temperature, rainfall, and evaporation in multiple seasons, and generate regional environmental information;

[0024] S303: Based on the regional environmental information, analyzing the impact of regional meteorological conditions on groundwater flow and water level, and mapping multiple hydrological information to a distribution map to generate groundwater pollution distribution information;

[0025] The specific formula for the impact of regional meteorological conditions on groundwater flow and water level is:

[0026]

[0027] in, represents the predicted combined value of groundwater flow and water level, represents the intercept of the regression model, reflecting the baseline values ​​of groundwater flow and water level when other variables are not considered, Represents the weight coefficient of temperature, which determines the influence of temperature in predicting groundwater flow and water level. Represents the weight coefficient of precipitation, which determines the influence of precipitation in predicting groundwater flow and water level. The weight coefficient representing evaporation determines the influence of evaporation on predicting groundwater flow and water level. Represents the weight coefficient of terrain gradient, which determines the influence of terrain gradient in predicting groundwater flow and water level. Represents temperature. The temperature directly affects the evaporation and condensation rate of groundwater, thereby affecting the water level and flow. Represents precipitation, represents the evaporation rate, Represents topographic gradient, which affects the direction and speed of surface and groundwater flow.

[0028] Optionally, the groundwater pollution distribution information is analyzed, and the vulnerability index of multiple locations in the target area is calculated by considering the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, and hydraulic conductivity coefficient. The steps of generating groundwater vulnerability data are specifically as follows:

[0029] S401: Utilizing the groundwater pollution distribution information, extracting multiple hydrological and geological parameters of the target area, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, and hydraulic conductivity coefficient, to generate a hydrological characteristic data set;

[0030] S402: Based on the hydrological characteristic data set, analyzing the impact of multiple geological parameters on groundwater vulnerability, calculating weight coefficients of multiple parameters, and generating impact degree calculation results;

[0031] S403: Calculate the vulnerability index of groundwater at multiple locations based on the impact degree calculation results to generate groundwater vulnerability data.

[0032] Optionally, the specific formula for calculating the vulnerability index of groundwater at multiple locations is:

[0033] in, is the groundwater depth score, which reflects the depth of soil layers that pollutants need to pass through to reach groundwater. is the recharge score, which indicates the extent to which precipitation recharges the groundwater layer. is the aquifer media score, which measures the permeability and pollutant filtering capacity of the aquifer. is the soil media score, which describes the filtering and caching effect of soil types on pollutants. is a terrain score that deals with how the slope of the land surface affects the flow of surface water and possible pollutants, It is the unsaturated zone media score, which involves the barrier effect of the media type between the surface and the groundwater table on pollutants. is the hydraulic conductivity score, which reflects the speed of contaminants in groundwater. is the weight of groundwater depth, which determines the influence of groundwater depth in the total score. is the weight of recharge, regulating the evaluation of the contribution of precipitation to groundwater recharge, is the weight of the aquifer medium, balancing the contribution of aquifer properties to the overall vulnerability score, is the weight of the soil medium, emphasizing the role of soil type in pollution filtration, is the weight of the terrain, reflecting the degree of control of the terrain on the dynamics of water flow. is the weight of the unsaturated zone medium, which evaluates the inhibitory effect of the unsaturated layer on the movement of pollutants. is the weight of hydraulic conductivity, indicating the importance of groundwater mobility to the spread of contamination, The groundwater vulnerability index is used to assess the vulnerability of groundwater systems to potential pollution sources. To score, each impact factor receives a score based on its potential impact on groundwater vulnerability. Each influencing factor is assigned a weight according to its relative importance to groundwater vulnerability.

[0034] Optionally, based on the groundwater vulnerability data, combined with the pollution load information of the region, considering the water demand of multiple locations, analyzing and calculating the groundwater pollution risk levels of multiple locations in the target area, and outputting the pollution risk level map are specifically performed as follows:

[0035] S501: Based on the groundwater vulnerability data, considering population density and industrial type, assessing water demand at multiple locations, analyzing pollution sensitivity at multiple locations, and generating pollution sensitivity assessment data;

[0036] The specific formula for analyzing the pollution sensitivity of multiple locations is:

[0037]

[0038] in, represents the pollution sensitivity index, stands for Groundwater Vulnerability Index, which assesses the responsiveness of groundwater systems to potential sources of pollution. Represents the weight of the groundwater vulnerability index, emphasizing the importance of groundwater vulnerability in the overall sensitivity assessment. Represents population density and assesses water demand pressure in the region. Represents the weight of population density, which adjusts the impact of population density on water resource sensitivity. It stands for Industrial Activity Index, which measures the potential impact of industrial activities on water resources in a region. Represents the proportion of natural protected areas, taking into account the contribution of protected areas to reducing environmental pressures;

[0039] S502: Based on the pollution sensitivity assessment data, combined with the pollution load data of multiple locations in the region, considering the flow and water level gradient of groundwater in multiple regions, calculating the groundwater pollution index of multiple locations in the target region, and generating pollution index data;

[0040] S503: Based on the pollution index data, evaluate the changing trend of pollution risks at multiple locations, evaluate the groundwater pollution risk levels at multiple locations in combination with the water demand at the target location, and output a pollution risk level map.

[0041] Optionally, the specific formula for calculating the groundwater pollution index at multiple locations in the target area is:

[0042]

[0043] in, represents the groundwater pollution index, Representative The weight coefficient of the parameter, Representative The measured values ​​of the parameters, Represents the total number of parameters involved in the calculation, An index representing different environment parameters.

[0044] On the other hand, a system for identifying and dividing groundwater pollution risks is provided, and the system is applied to a method for identifying and dividing groundwater pollution risks, and the system includes:

[0045] The satellite image analysis module uses satellite remote sensing image data and analyzes image information to identify the surface coverage type of the target area, including industrial areas, farmlands, residential areas, and commercial areas, and generates surface type analysis results;

[0046] The pollution source identification module identifies the location of the pollution source and marks the type information based on the surface type analysis result, and draws a pollution source distribution map;

[0047] The load index calculation module evaluates the chemical composition and emission intensity of multiple pollution sources based on the pollution source distribution map, calculates the pollution load index of multiple pollution sources, maps them to the distribution map, and generates pollution load marking information;

[0048] The hydrological data acquisition module collects hydrogeological and meteorological information of the target area based on the pollution load mark information, analyzes the groundwater distribution in the target area, and generates groundwater pollution distribution information;

[0049] The vulnerability analysis module calculates the vulnerability index of multiple locations based on the groundwater pollution distribution information according to multiple hydrogeological parameters, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, and hydraulic conductivity coefficient, and generates groundwater vulnerability data;

[0050] The pollution level assessment module is based on the groundwater vulnerability data, considers the water demand and pollution load of multiple locations, assesses the groundwater pollution risk level of multiple locations, and generates a pollution risk level map.

[0051] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0052] By analyzing satellite image data, the surface cover type of the target area can be identified, the location and type of pollution source can be determined, and the targeted management of pollution sources can be improved. Combined with regional hydrogeological data and meteorological information, the groundwater distribution and pollution risk level can be updated in real time to facilitate the formulation of governance strategies based on the characteristics and impact range of pollutants. By considering the various natural properties and external influencing factors of the groundwater system, the groundwater vulnerability index is calculated to comprehensively reflect the groundwater risk and provide a scientific basis for decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0055] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0056] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0057] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0058] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0059] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0060] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0061] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0062] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0063] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0064] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0065] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0066] The embodiment of the present invention provides a method for identifying and dividing groundwater pollution risks, such as Figure 1 The method flow chart of groundwater pollution risk identification and classification shown in the figure includes the following steps:

[0067] S1: Using satellite remote sensing image data and the surface images of the target area, analyze the surface cover types of multiple locations, including industrial areas, farmlands, residential areas, and commercial areas, identify the locations of pollution sources, mark the types, and draw a pollution source distribution map;

[0068] S2: Based on the pollution source distribution map, the chemical composition and emission intensity of multiple pollution sources are evaluated according to the location type of the pollution sources, the pollution loads of multiple locations are calculated, and mapped to the distribution map to generate pollution load marking information;

[0069] S3: Based on the pollution load marker information, the hydrogeological data of the target area is collected, the groundwater distribution in the target area is analyzed, and the regional meteorological information is combined and mapped to the distribution map to generate the groundwater pollution distribution information;

[0070] S4: Analyze the groundwater pollution distribution information, consider the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity, calculate the vulnerability index of multiple locations in the target area, and generate groundwater vulnerability data;

[0071] S5: Based on the groundwater vulnerability data, combined with the regional pollution load information, considering the water demand at multiple locations, analyze and calculate the groundwater pollution risk level at multiple locations in the target area, and output the pollution risk level map.

[0072] The pollution source distribution map includes pollution source location information, pollution source type identification, and surface coverage characteristics. The pollution load marking information includes the chemical composition information of the pollution source, emission concentration and emission assessment data, and the impact range of the pollution source. The groundwater pollution distribution information includes groundwater flow direction map, water level gradient map, and hydrogeological boundaries. The groundwater vulnerability data includes the vulnerability index calculation results of multiple locations, a list of key influencing factors, and influencing factor weight setting parameters. The pollution risk level map includes the risk levels of multiple locations, regional water demand information, and pollution spread trend prediction results.

[0073] See also Figure 2 , through satellite remote sensing image data, according to the surface image of the target area, analyze the surface cover types of multiple locations, including industrial areas, farmlands, residential areas, and commercial areas, identify the location of pollution sources and mark the types. The specific steps for drawing the pollution source distribution map are as follows:

[0074] S101: Using satellite remote sensing image data, we can identify various surface features and cover types by analyzing images, including industrial buildings, farmland boundaries, residential buildings, and urban streets, and generate a surface cover classification map;

[0075] In sub-step S101, based on satellite remote sensing image data, surface feature analysis is performed and image data is preprocessed, including image denoising, color correction and enhancement, to ensure that surface features are clearer and more identifiable. Edge detection algorithms such as Canny edge detection are applied to separate different feature boundaries on the surface, such as the straight edges of industrial buildings and regular patterns of farmland. Supervised classification techniques such as support vector machines (SVM) are used to classify features in the image and assign different labels to each type of feature, such as industrial buildings, farmland boundaries, residential buildings and urban streets. All classification results are combined to generate a surface cover classification map, which shows the distribution of various surface cover types in the target area and provides basic data for subsequent pollution source identification.

[0076] S102: Based on the land cover classification map, analyze the image and identify the location of the pollution source, including industrial discharge outlets and farmland drainage outlets, mark the locations of multiple pollution sources, and generate pollution source identification information;

[0077] In sub-step S102, based on the land cover classification map, accurate identification of pollution source locations is performed, and image segmentation technology is used to separate the identified industrial areas and farmland areas from the land cover classification map. Morphological operations such as corrosion and dilation are used to clarify the boundaries of each area. Typical pollution emission outlets are identified through texture and color analysis, such as the grayish-white tones of industrial chimneys and the dark soil of farmland drainage outlets. A marking algorithm is used to mark the location of the target pollution source on the land cover classification map. Each mark includes specific geographic coordinates and pollution type. All marking data are summarized to generate pollution source identification information. The information lists all identified pollution sources, their locations and types, providing key inputs for pollution load calculation and risk assessment.

[0078] S103: Based on the pollution source identification information, the location of multiple pollution sources is labeled with type information, including industrial areas, farmland, and residential water use, and a pollution source distribution map is drawn;

[0079] In sub-step S103, based on the pollution source identification information, the pollution source type is labeled, each identified pollution source is analyzed, and its impact on the surrounding environment is evaluated using spatial analysis tools. For example, industrial areas involve chemical pollution and farmland involve fertilizer loss. Based on the specific activities and emission characteristics of the pollution source, each pollution source is classified and key pollution types are labeled, such as organic pollutants, heavy metals or nutrients. Combined with GIS technology, the target labeling information is drawn on the map to clearly display the location of each pollution source and the relevant pollution type, and a pollution source distribution map is generated for monitoring and managing various pollution sources and implementing effective environmental protection and pollution control measures.

[0080] See also Figure 3Based on the pollution source distribution map, the chemical composition and emission intensity of multiple pollution sources are evaluated according to the location type of the pollution source, the pollution load of multiple locations is calculated, and mapped to the distribution map. The specific steps for generating pollution load marking information are as follows:

[0081] S201: Based on the pollution source distribution map, analyze the chemical composition data of various pollution source samples, including the chemical composition of industrial emissions and the types of fertilizers used in farmland, and generate sample composition analysis data;

[0082] In sub-step S201, high performance liquid chromatography and gas chromatography-mass spectrometry are used to analyze the chemical composition of industrial emissions and agricultural fertilizers, separate and identify the types and concentrations of compounds, and integrate and analyze the chemical composition data of each sample through an automated data processing system to ensure that the properties of each chemical substance, such as toxicity and persistence, are accurately recorded. The target chemical composition data are summarized to create a component analysis data report containing all contaminated samples, listing the chemical composition of various industrial emissions and agricultural fertilizers, including heavy metals, organic pollutants, and nutrients, and generating sample component analysis data.

[0083] S202: Based on the sample component analysis data, combined with the spatial location information of the pollution sources, according to the population density, industrial type, and farmland distribution information of multiple locations, the emission intensity of multiple pollution sources is evaluated, the pollution load of multiple pollution sources is calculated, and the location pollution load information is generated;

[0084] In sub-step S202, based on the sample component analysis data, the spatial location information of the pollution source is accurately mapped through the geographic information system, and data such as population density and industrial type at each location are collected. The formula is used Assess the emission intensity of each pollution source and calculate the pollution load;

[0085] In the formula, Table Location The pollution load, is the concentration of the chemical component at that location, is the population density weight, is the emission coefficient corresponding to the industrial type at this location, It is an adjustment factor based on the impact of farmland distribution;

[0086] Detailed explanation of the formula and the process of formula calculation and derivation:

[0087] Assume that at the target location, the chemical component concentration mg / L, population density weight , industrial emission factor , farmland distribution adjustment factor , the calculation process is as follows:

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] The results showed that the pollution load of the location was 189 units based on the given chemical component concentrations and region-specific population and industrial activity data, a value that reflects the potential risk of groundwater contamination in the area and is used for further environmental management and pollution control strategy formulation.

[0093] S203: mapping the load information to a distribution map according to the location pollution load information and the location information of the multiple pollution sources, including marking the load intensity of the multiple pollution sources, and generating pollution load marking information;

[0094] In sub-step S203, based on the location pollution load information, GIS software is used to accurately map the geographical locations of multiple pollution sources to ensure that the spatial data of each pollution source is accurate, and the pollution load value of each pollution source is associated with the map data. Data visualization tools are used to mark them on the map. Areas with high pollution loads are represented by dark colors, and areas with low pollution loads are represented by light colors. The load intensity of different pollution sources is intuitively displayed in the form of a map, which facilitates understanding of the current pollution situation and generates comprehensive pollution load marking information.

[0095] See also Figure 4 ,Based on the pollution load marker information, the hydrogeological data of the target area is collected, the groundwater distribution in the target area is analyzed, and the regional meteorological information is combined and mapped to the distribution map. The specific steps for generating groundwater pollution distribution information are as follows:

[0096] S301: Based on the pollution load mark information, collect hydrological and geological data of multiple locations in the target area to generate hydrological data collection results;

[0097] In sub-step S301, the groundwater hydrological monitoring system is used to systematically collect hydrological data from multiple key locations in the target area. The target data include groundwater level, flow rate, daily changes and seasonal changes. Combined with geological exploration data, such as rock and soil layer thickness and type, the target data is obtained by geological detection radar and drilling sample analysis to ensure the accuracy and representativeness of the geological data. All hydrological and geological data are summarized and processed in a unified format and quality assessed using data integration tools to ensure data consistency and availability, and generate hydrological data collection results.

[0098] S302: Based on the hydrological data collection results, collect meteorological information of the target area, record the temperature, rainfall, and evaporation in multiple seasons, and generate regional environmental information;

[0099] In sub-step S302, based on the hydrological data collection results, automatic weather stations and satellite data services are deployed to collect temperature, rainfall and evaporation data in multiple seasons in the target area. Time series analysis is performed on the collected meteorological data. Moving average and seasonal adjustment methods are used to process outliers and missing values ​​in the meteorological data to ensure the accuracy and completeness of the data. The processed meteorological data are combined with hydrogeological data, and the impact of meteorological conditions on groundwater status is considered to generate comprehensive regional environmental information.

[0100] S303: Based on the regional environmental information, the impact of regional meteorological conditions on groundwater flow and water level is analyzed, and multiple hydrological information is mapped to a distribution map to generate groundwater pollution distribution information;

[0101] The specific formula for the impact of regional meteorological conditions on groundwater flow and water level is:

[0102]

[0103] in, represents the predicted combined value of groundwater flow and water level, represents the intercept of the regression model, reflecting the baseline values ​​of groundwater flow and water level when other variables are not considered, Represents the weight coefficient of temperature, which determines the influence of temperature in predicting groundwater flow and water level. Represents the weight coefficient of precipitation, which determines the influence of precipitation in predicting groundwater flow and water level. The weight coefficient representing evaporation determines the influence of evaporation on predicting groundwater flow and water level. Represents the weight coefficient of terrain gradient, which determines the influence of terrain gradient in predicting groundwater flow and water level. Represents temperature. The temperature directly affects the evaporation and condensation rate of groundwater, thereby affecting the water level and flow. Represents precipitation, represents the evaporation rate, Represents topographic gradient, which affects the direction and speed of surface and groundwater flow.

[0104] formula:

[0105] ;

[0106] Detailed explanation of the formula and the process of formula calculation and derivation:

[0107] The formula is used to predict the combined values ​​of groundwater flow and water level using known meteorological and topographic parameters, and the calculation results are used to guide the risk assessment and management of groundwater pollution;

[0108] Parameter meaning and setting value:

[0109] is the intercept, which represents the basic groundwater flow and water level when there are no other influencing factors, and is assumed to be 50;

[0110] is the weight coefficient of temperature, assumed to be 0.5;

[0111] is the weight coefficient of precipitation, which is assumed to be 1.0;

[0112] is the weight coefficient of evaporation, assumed to be -0.4;

[0113] is the weight coefficient of terrain gradient, assumed to be 0.2;

[0114] is the temperature, quantified as the average temperature of the day, with a set value of 22°C;

[0115] is the precipitation, which is quantified as the total precipitation of the day, and the set value is 5mm;

[0116] is the evaporation, quantified as daily evaporation, and the set value is 2 mm;

[0117] is the terrain gradient, quantified as the average slope percentage, dimensionless unit, set ;

[0118] Substitute the parameters into the formula for calculation:

[0119] ;

[0120] ;

[0121] ;

[0122] The result 67.2 shows that based on the current meteorological conditions and terrain characteristics, the predicted combined value of groundwater flow and water level is 67.2, indicating that the groundwater resources in the current area are relatively stable in the short term.

[0123] See also Figure 5, analyze the groundwater pollution distribution information, consider the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity, calculate the vulnerability index of multiple locations in the target area, and generate groundwater vulnerability data in the following steps:

[0124] S401: Using the groundwater pollution distribution information, extract multiple hydrological and geological parameters of the target area, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity coefficient, and generate a hydrological characteristic data set;

[0125] In sub-step S401, geographic information system technology is used to extract key hydrological and geological parameters of the target area from the groundwater pollution distribution information. The target parameters include the depth of groundwater, the net recharge under the surface such as precipitation infiltration, and the geological structure characteristics such as the type and distribution of aquifer media. Geological analysis software is used to conduct in-depth analysis of the extracted soil zone media, topography and vadose zone media data, evaluate physical and chemical properties such as soil particle size, organic matter content and permeability, integrate target data, calculate the specific impact of each parameter on groundwater flow and storage capacity, use data integration tools such as Python programming to clean the data and standardize the format, and generate a hydrological characteristic data set.

[0126] S402: Based on the hydrological characteristic data set, analyze the impact of multiple geological parameters on groundwater vulnerability, calculate the weight coefficients of multiple parameters, and generate the impact degree calculation results;

[0127] In sub-step S402, based on the hydrological characteristic data set, the basic influence of various geological parameters such as the permeability of the aquifer medium and the water retention capacity of the soil zone on groundwater vulnerability is defined, and multivariate analysis methods such as principal component analysis are used to evaluate and calculate the relative influence and weight coefficients of multiple geological parameters on groundwater vulnerability. The interaction and comprehensive impact between parameters are considered, and the weight coefficient is adjusted in combination with actual groundwater monitoring data to reflect the deviation between actual observations and theoretical analysis, to ensure the scientific nature and practical applicability of the weight setting, and to generate the impact degree calculation results.

[0128] S403: Calculate the vulnerability index of groundwater at multiple locations based on the impact degree calculation results to generate groundwater vulnerability data;

[0129] The specific formula for calculating the vulnerability index of groundwater at multiple locations is:

[0130]

[0131] in, is the groundwater depth score, which reflects the depth of soil layers that pollutants need to pass through to reach groundwater. is the recharge score, which indicates the extent to which precipitation recharges the groundwater layer. is the aquifer media score, which measures the permeability and pollutant filtering capacity of the aquifer. is the soil media score, which describes the filtering and caching effect of soil types on pollutants. is a terrain score that deals with how the slope of the land surface affects the flow of surface water and possible pollutants, It is the unsaturated zone media score, which involves the barrier effect of the media type between the surface and the groundwater table on pollutants. is the hydraulic conductivity score, which reflects the speed of contaminants in groundwater. is the weight of groundwater depth, which determines the influence of groundwater depth in the total score. is the weight of recharge, regulating the evaluation of the contribution of precipitation to groundwater recharge, is the weight of the aquifer medium, balancing the contribution of aquifer properties to the overall vulnerability score, is the weight of the soil medium, emphasizing the role of soil type in pollution filtration, is the weight of the terrain, reflecting the degree of control of the terrain on the dynamics of water flow. is the weight of the unsaturated zone medium, which evaluates the inhibitory effect of the unsaturated layer on the movement of pollutants. is the weight of hydraulic conductivity, indicating the importance of groundwater mobility to the spread of contamination, The groundwater vulnerability index is used to assess the vulnerability of groundwater systems to potential pollution sources. To score, each impact factor receives a score based on its potential impact on groundwater vulnerability. Each influencing factor is assigned a weight according to its relative importance to groundwater vulnerability.

[0132] formula:

[0133] ;

[0134] Detailed explanation of the formula and the process of formula calculation and derivation:

[0135] This formula is used to calculate the groundwater vulnerability index, and the results are used to assess the risk of groundwater contamination;

[0136] Parameter meaning and setting value:

[0137] Score the groundwater depth, assuming it is 8, reflecting that the deeper the groundwater, the lower the possibility of contamination. It is assumed to be 5, based on its criticality in protecting groundwater;

[0138] The recharge score is 6, which indicates the degree of recharge of groundwater by precipitation. Assumption 4 takes into account the promoting effect of refilling water on pollutant infiltration;

[0139] Score the aquifer medium, assuming a score of 7, to measure the aquifer's permeability and pollutant filtering capacity, with a weight of Assumption 3, based on the role of aquifer type in pollution filtration;

[0140] Score the soil medium, assuming it is 5, to describe the filtering and caching effect of soil type on pollutants, weight Assumption 2 reflects the role of soil in pollution control;

[0141] Score the terrain, assuming a 4, for how the surface slope affects the flow of surface water and possible pollutants, with a weight of Assuming 1, the indirect effect of topography on water flow dynamics is considered;

[0142] Score the unsaturated zone medium, assuming it is 5, which involves the barrier effect of the medium type between the surface and the groundwater table on pollutants. Assumption is 3, reflecting the role of unsaturated zone in filtering pollutants;

[0143] The hydraulic conductivity score is assumed to be 7, reflecting the propagation speed of pollutants in groundwater. Assumption 5 emphasizes the direct effect of hydraulic conductivity on pollutant migration;

[0144] Substitute the parameters into the formula for calculation:

[0145] ;

[0146] ;

[0147] Result 149 shows that the groundwater in the region has a high vulnerability index, which means that the groundwater in the region is more susceptible to pollution and appropriate protection and control measures need to be taken to reduce the risk of pollution. The calculation results are used to understand the pollution situation, optimize resource allocation, and implement effective groundwater protection measures.

[0148] See also Figure 6 Based on the groundwater vulnerability data, combined with the regional pollution load information, considering the water demand at multiple locations, the groundwater pollution risk levels at multiple locations in the target area are analyzed and calculated. The steps to output the pollution risk level map are as follows:

[0149] S501: Based on groundwater vulnerability data, considering population density and industrial type, assess water demand at multiple locations, analyze pollution sensitivity at multiple locations, and generate pollution sensitivity assessment data;

[0150] The specific formula for analyzing the pollution sensitivity of multiple locations is:

[0151]

[0152] in, represents the pollution sensitivity index, stands for Groundwater Vulnerability Index, which assesses the responsiveness of groundwater systems to potential sources of pollution. Represents the weight of the groundwater vulnerability index, emphasizing the importance of groundwater vulnerability in the overall sensitivity assessment. Represents population density and assesses water demand pressure in the region. Represents the weight of population density, which adjusts the impact of population density on water resource sensitivity. It stands for Industrial Activity Index, which measures the potential impact of industrial activities on water resources in a region. Represents the proportion of natural protected areas, taking into account the contribution of protected areas to alleviating environmental pressures.

[0153] formula:

[0154] ;

[0155] Detailed explanation of the formula and the process of formula calculation and derivation:

[0156] This formula is used to calculate the pollution sensitivity index, and the results are used to assess the sensitivity of a region to environmental pollution;

[0157] Parameter meaning and setting value:

[0158] is the groundwater vulnerability index, which is assumed to be 0.7 and has dimensionless units, reflecting the susceptibility of groundwater to potential contamination;

[0159] is the weight of the groundwater vulnerability index, which is set to 0.6;

[0160] is the population density, which is assumed to be 1000 people / km2, reflecting the pressure of population on water resources;

[0161] is the weight of population density, set to 0.4;

[0162] is the industrial activity index, which is assumed to be 200 and has dimensionless units, and measures the contribution of industry to groundwater pollution;

[0163] is the proportion of natural protected areas, assuming that protected areas account for 30% of the total area, which is 0.3, showing the role of protected areas in alleviating pollution pressure;

[0164] Substitute the parameters into the formula for calculation:

[0165] Calculate the weighted average part:

[0166] ;

[0167] Calculate the difference ratio part:

[0168] ;

[0169] Calculate the pollution sensitivity index:

[0170] ;

[0171] The result 399.58 indicates that the region has a high sensitivity to environmental pollution and that high-risk areas need to be prioritized for implementation and monitoring of environmental protection measures.

[0172] S502: Based on the pollution sensitivity assessment data, combined with the pollution load data of multiple locations in the region, considering the flow and water level gradient of groundwater in multiple regions, calculating the groundwater pollution index of multiple locations in the target area, and generating pollution index data;

[0173] The specific formula for calculating the groundwater pollution index at multiple locations in the target area is:

[0174]

[0175] in, represents the groundwater pollution index, Representative The weight coefficient of the parameter, Representative The measured values ​​of the parameters, Represents the total number of parameters involved in the calculation, An index representing different environment parameters.

[0176] formula:

[0177] ;

[0178] Detailed explanation of the formula and the process of formula calculation and derivation:

[0179] The formula is used to calculate the groundwater pollution index and analyze the degree of groundwater pollution at multiple locations;

[0180] Parameter meaning and setting value:

[0181] Representative The weight coefficients of the parameters are assumed to be is the weight coefficient of groundwater flow, set to 0.4, is the weight coefficient of water level gradient, set to 0.6;

[0182] It is The measured values ​​of the parameters, assuming To measure the groundwater flow, it is set to 600 cubic meters per hour. is the measured water level gradient, which is set to 0.05;

[0183] Substitute the parameters into the formula for calculation:

[0184] ;

[0185] ;

[0186] ;

[0187] ;

[0188] ;

[0189] The result of 10.96 shows that the groundwater pollution index in the area is above medium. The value indicates that the groundwater in the area faces a high risk of pollution and appropriate control and governance measures need to be taken to reduce the impact of pollution and ensure the safety and sustainable use of water resources.

[0190] S503: Based on the pollution index data, evaluate the changing trend of pollution risks at multiple locations, combine the water demand at the target location, evaluate the groundwater pollution risk level at multiple locations, and output a pollution risk level map;

[0191] In sub-step S503, based on the pollution index data, statistical analysis methods such as time series analysis are used to evaluate the changing trends of pollution risks in different locations, analyze historical data and current data, identify potential risk growth areas, consider the actual water demand of the target location, combine the data on groundwater pollution risk and water demand, use risk assessment software to evaluate the groundwater pollution risk level in multiple locations, consider the impact of pollution index and water demand on risk level, and generate a groundwater pollution risk level map based on the assessment results using geographic information system technology. The map clearly indicates the pollution risk level of each area, provides an intuitive view of groundwater pollution risk, and generates a comprehensive pollution risk level map.

[0192] See also Figure 7, a system for identifying and dividing groundwater pollution risks, the system for identifying and dividing groundwater pollution risks is used to execute the above-mentioned method for identifying and dividing groundwater pollution risks, and the system comprises:

[0193] The satellite image analysis module uses satellite remote sensing image data and analyzes image information to identify the surface coverage type of the target area, including industrial areas, farmlands, residential areas, and commercial areas, and generates surface type analysis results;

[0194] The pollution source identification module identifies the location of pollution sources and marks the type information based on the surface type analysis results, and draws a pollution source distribution map;

[0195] The load index calculation module evaluates the chemical composition and emission intensity of multiple pollution sources based on the pollution source distribution map, calculates the pollution load index of multiple pollution sources, maps it to the distribution map, and generates pollution load marking information;

[0196] The hydrological data acquisition module collects hydrogeological and meteorological information of the target area based on the pollution load marker information, analyzes the groundwater distribution in the target area, and generates groundwater pollution distribution information;

[0197] The vulnerability analysis module calculates the vulnerability index of multiple locations based on the groundwater pollution distribution information and various hydrogeological parameters, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, and hydraulic conductivity, to generate groundwater vulnerability data;

[0198] The pollution level assessment module is based on groundwater vulnerability data, considers water demand and pollution load at multiple locations, assesses groundwater pollution risk levels at multiple locations, and generates a pollution risk level map.

[0199] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0200] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0201] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0202] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0203] 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 to be beyond the scope of the present invention.

[0204] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0205] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0206] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0207] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0208] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0209] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for identifying and classifying groundwater pollution risks, characterized in that: The method comprises: By using satellite remote sensing image data and based on the surface image of the target area, the surface cover types at multiple locations are analyzed, the locations of pollution sources are identified and the surface cover types are marked, and a pollution source distribution map is drawn; Based on the pollution source distribution map, according to the location type of the pollution source, the chemical composition and emission intensity of multiple pollution sources are evaluated, the pollution loads of multiple locations are calculated, and mapped into the pollution source distribution map to generate pollution load marking information; Based on the pollution load marking information, the hydrogeological data of the target area is collected, the groundwater distribution in the target area is analyzed, and the groundwater distribution information is mapped to the pollution source distribution map in combination with the regional meteorological information to generate groundwater pollution distribution information; Analyze the groundwater pollution distribution information, combine the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity coefficient, calculate the vulnerability index of multiple locations in the target area, and generate groundwater vulnerability data; Based on the groundwater vulnerability data, combined with the regional pollution load information, and considering the water demand at multiple locations, the groundwater pollution risk levels at multiple locations in the target area are analyzed and calculated, and a pollution risk level map is output.

2. The method for identifying and classifying groundwater pollution risks according to claim 1 is characterized in that: The pollution source distribution map includes pollution source location information, pollution source type identification, and surface coverage characteristics. The pollution source location information includes industrial areas, farmlands, residential areas, and commercial areas. The pollution load marking information includes the chemical composition information of the pollution source, emission concentration and emission assessment data, and the impact range of the pollution source. The groundwater pollution distribution information includes a groundwater flow map, a water level gradient map, and hydrogeological boundaries. The groundwater vulnerability data includes the vulnerability index calculation results of multiple locations, a list of key influencing factors, and influencing factor weight setting parameters. The pollution risk level map includes the risk levels of multiple locations, regional water demand information, and pollution spread trend prediction results.

3. The method for identifying and classifying groundwater pollution risks according to claim 1, characterized in that: Using satellite remote sensing image data and the surface images of the target area, we analyze the surface cover types at multiple locations, identify the locations of pollution sources and mark the types. The specific steps for drawing a pollution source distribution map are as follows: Using satellite remote sensing image data, we can generate a land cover classification map by analyzing images to identify a variety of land surface features and cover types, including industrial buildings, farmland boundaries, residential buildings, and urban streets; Based on the land cover classification map, analyzing the image and identifying the location of pollution sources, including industrial discharge outlets and farmland drainage outlets, marking the locations of multiple pollution sources, and generating pollution source identification information; Based on the pollution source identification information, the type information of multiple pollution source locations is annotated, including industrial areas, farmland, and residential water use, and a pollution source distribution map is drawn.

4. The method for identifying and classifying groundwater pollution risks according to claim 1, characterized in that: Based on the pollution source distribution map, the chemical composition and emission intensity of multiple pollution sources are evaluated according to the location type of the pollution source, the pollution load of multiple locations is calculated, and the pollution load is mapped to the pollution source distribution map. The steps of generating the pollution load marking information are specifically as follows: Based on the pollution source distribution map, analyzing the chemical composition data of various pollution source samples, including the chemical composition of industrial emissions and the type of fertilizer used in farmland, to generate sample composition analysis data; Based on the sample component analysis data, combined with the spatial location information of the pollution sources, according to the population density, industrial type, and farmland distribution information of the multiple locations, the emission intensity of the multiple pollution sources is evaluated, the pollution load of the multiple pollution sources is calculated, and the location pollution load information is generated; According to the location pollution load information and the location information of multiple pollution sources, the load information is mapped into a distribution map, including marking the load intensity of multiple pollution sources, to generate pollution load marking information.

5. The method for identifying and classifying groundwater pollution risks according to claim 1, characterized in that: Based on the pollution load marking information, the hydrogeological data of the target area is collected, the groundwater distribution in the target area is analyzed, and the groundwater distribution information is mapped to the pollution source distribution map in combination with the regional meteorological information. The steps of generating groundwater pollution distribution information are specifically as follows: Based on the pollution load marker information, collect hydrological and geological data at multiple locations in the target area to generate hydrological data collection results; Based on the hydrological data collection results, meteorological information of the target area is collected, temperature, rainfall, and evaporation in multiple seasons are recorded, and regional environmental information is generated; Based on the regional environmental information, analyzing the impact of regional meteorological conditions on groundwater flow and water level, and mapping multiple hydrological information to the pollution source distribution map to generate groundwater pollution distribution information; The specific formula for the impact of regional meteorological conditions on groundwater flow and water level is: ； in, represents the predicted combined value of groundwater flow and water level, represents the intercept of the regression model, reflecting the baseline values ​​of groundwater flow and water level when other variables are not considered, Represents the weight coefficient of temperature, which determines the influence of temperature in predicting groundwater flow and water level. Represents the weight coefficient of precipitation, which determines the influence of precipitation in predicting groundwater flow and water level. The weight coefficient representing evaporation determines the influence of evaporation on predicting groundwater flow and water level. Represents the weight coefficient of terrain gradient, which determines the influence of terrain gradient in predicting groundwater flow and water level. Represents temperature. The temperature directly affects the evaporation and condensation rate of groundwater, thereby affecting the water level and flow. Represents precipitation, represents the evaporation rate, Represents topographic gradient, which affects the direction and speed of surface and groundwater flow.

6. The method for identifying and classifying groundwater pollution risks according to claim 1, characterized in that: Analyze the groundwater pollution distribution information, consider the groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity, calculate the vulnerability index of multiple locations in the target area, and generate groundwater vulnerability data in the following steps: Utilizing the groundwater pollution distribution information, extracting multiple hydrological and geological parameters of the target area, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, and hydraulic conductivity, to generate a hydrological characteristic data set; Based on the hydrological characteristic data set, the impact of various geological parameters on groundwater vulnerability is analyzed, and the weight coefficients of multiple parameters are calculated to generate the impact degree calculation results; Based on the impact degree calculation results, the vulnerability index of groundwater at multiple locations is calculated to generate groundwater vulnerability data.

7. The method for identifying and classifying groundwater pollution risks according to claim 6, characterized in that: The specific formula for calculating the vulnerability index of groundwater at multiple locations is: ； in, is the groundwater depth score, which reflects the depth of soil layers that pollutants need to pass through to reach groundwater. is the recharge score, which indicates the extent to which precipitation recharges the groundwater layer. is the aquifer media score, which measures the permeability and pollutant filtering capacity of the aquifer. is the soil media score, which describes the filtering and caching effect of soil types on pollutants. is a terrain score that deals with how the slope of the land surface affects the flow of surface water and possible pollutants, It is the unsaturated zone media score, which involves the barrier effect of the media type between the surface and the groundwater table on pollutants. is the hydraulic conductivity score, which reflects the speed of contaminants in groundwater. is the weight of groundwater depth, which determines the influence of groundwater depth in the total score. is the weight of recharge, regulating the evaluation of the contribution of precipitation to groundwater recharge, is the weight of the aquifer medium, balancing the contribution of aquifer properties to the overall vulnerability score, is the weight of the soil medium, emphasizing the role of soil type in pollution filtration, is the weight of the terrain, reflecting the degree of control of the terrain on the dynamics of water flow. is the weight of the unsaturated zone medium, which evaluates the inhibitory effect of the unsaturated layer on the movement of pollutants. is the weight of hydraulic conductivity, indicating the importance of groundwater mobility to the spread of contamination, The groundwater vulnerability index is used to assess the vulnerability of groundwater systems to potential pollution sources. To score, each impact factor receives a score based on its potential impact on groundwater vulnerability. Each influencing factor is assigned a weight according to its relative importance to groundwater vulnerability.

8. The method for identifying and classifying groundwater pollution risks according to claim 1, characterized in that: Based on the groundwater vulnerability data, combined with the pollution load information of the region, considering the water demand of multiple locations, analyzing and calculating the groundwater pollution risk level of multiple locations in the target area, and outputting the pollution risk level map are specifically as follows: Based on the groundwater vulnerability data, considering population density and industrial type, assessing water demand at multiple locations, analyzing pollution sensitivity at multiple locations, and generating pollution sensitivity assessment data; The specific formula for analyzing the pollution sensitivity of multiple locations is: ； in, represents the pollution sensitivity index, stands for Groundwater Vulnerability Index, which assesses the responsiveness of groundwater systems to potential sources of pollution. Represents the weight of the groundwater vulnerability index, emphasizing the importance of groundwater vulnerability in the overall sensitivity assessment. Represents population density and assesses water demand pressure in the region. Represents the weight of population density, which adjusts the impact of population density on water resource sensitivity. It stands for Industrial Activity Index, which measures the potential impact of industrial activities on water resources in a region. Represents the proportion of natural protected areas, taking into account the contribution of protected areas to reducing environmental pressures; Based on the pollution sensitivity assessment data, combined with pollution load data at multiple locations in the region, considering the flow and water level gradient of groundwater in multiple regions, calculate the groundwater pollution index at multiple locations in the target area, and generate pollution index data; According to the pollution index data, the changing trend of pollution risks at multiple locations is evaluated, and combined with the water demand of the target location, the groundwater pollution risk level of multiple locations is evaluated, and a pollution risk level map is output.

9. The method for identifying and classifying groundwater pollution risks according to claim 8, characterized in that: The specific formula for calculating the groundwater pollution index at multiple locations in the target area is: ； in, represents the groundwater pollution index, Representative The weight coefficient of the parameter, Representative The measured values ​​of the parameters, Represents the total number of parameters involved in the calculation, An index representing different environment parameters.

10. A system for identifying and classifying groundwater pollution risks, characterized in that: According to the method for identifying and classifying groundwater pollution risks according to any one of claims 1 to 9, the system comprises: The satellite image analysis module uses satellite remote sensing image data and analyzes image information to identify the surface coverage type of the target area, including industrial areas, farmlands, residential areas, and commercial areas, and generates surface type analysis results; A pollution source identification module, based on the surface type analysis result, identifies the location of the pollution source and marks the type information, and draws a pollution source distribution map; A load index calculation module, based on the pollution source distribution map, evaluates the chemical composition and emission intensity of multiple pollution sources, calculates the pollution load index of multiple pollution sources, maps them to the distribution map, and generates pollution load marking information; A hydrological data collection module collects hydrogeological and meteorological information of a target area based on the pollution load marking information, analyzes groundwater distribution in the target area, and generates groundwater pollution distribution information; A vulnerability analysis module, based on the groundwater pollution distribution information, calculates vulnerability indexes of multiple locations according to multiple hydrogeological parameters, including groundwater depth, net recharge, aquifer medium, soil zone medium, topography, vadose zone medium, hydraulic conductivity coefficient, and generates groundwater vulnerability data; The pollution level assessment module, based on the groundwater vulnerability data, considers the water demand and pollution load of multiple locations, assesses the groundwater pollution risk level of multiple locations, and generates a pollution risk level map.

Images