Method and system for detecting heavy metal pollutants in water based on big data

Abstract

The invention discloses a method and system for detecting heavy metal pollutants in water based on big data, and relates to the technical field of water quality detection.The method comprises the steps that basic characteristic values of a water area to be detected are obtained; processing to generate a basic pollution condition performance value of the to-be-detected water area; processing, analyzing and generating water sampling execution parameters of the to-be-detected water area; analyzing and generating a single collection period of a water sample collection point of the to-be-detected water area; carrying out water body data acquisition on each water sample acquisition point, processing to obtain a heavy metal pollutant detection result of the water area to be detected, and carrying out early warning feedback; by analyzing basic information such as the water body type of the to-be-detected water area and counting the historical water sample monitoring data and the historical environment monitoring data of the place where the to-be-detected water area is located, heavy metal pollutant fixed-point and fixed-time detection is carried out on the to-be-detected water area, potential factors of heavy metal pollution of the to-be-detected water area are comprehensively considered, and the detection accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water quality detection, and in particular to a method and system for detecting heavy metal pollutants in water based on big data. Background Art

[0002] With the continuous development of industrial technology, industrial production usually produces wastewater containing heavy metals. Heavy metals such as lead, mercury, cadmium, chromium, etc. are known toxic substances that can damage the water ecosystem, affect the growth and reproduction of aquatic organisms, and are directly related to public health and safety. Therefore, water quality testing is extremely important.

[0003] The prior art, such as the invention patent with announcement number: CN115327061B, is a method, device, equipment and storage medium for detecting heavy metals in water quality. The method includes: upon receiving a detection instruction, determining the water area to be tested and the heavy metals to be tested according to the detection instruction; dividing the water layers of the water area to be tested according to the heavy metals to be tested, and generating a collection strategy corresponding to each water layer according to the division result; collecting water layers according to the collection strategy, and testing the collection results to obtain the detection results of the water area to be tested. Because the present invention first divides the water layer of the water area to be tested, and then uses different collection strategies for different water layer divisions to collect, and finally tests the collection results to obtain the detection results.

[0004] The prior art, such as the invention patent with announcement number: CN118294607B, is a water environment detection method, system, equipment and medium based on heavy metals. The invention divides the target water area into shallow water area, middle water area and deep water area through water depth data, captures the bottom characteristics, geological characteristics and hydrodynamic characteristics of different depth areas, obtains heavy metal content data, calculates the first heavy metal content value of shallow water area, middle water area and deep water area respectively according to the bottom characteristics and geological characteristics, and calculates the second heavy metal content value of shallow water area, middle water area and deep water area respectively according to the water body circulation characteristics and hydrodynamic characteristics. Considering that the bottom characteristics, geological characteristics and hydrodynamic characteristics of different depth areas usually have significant differences, the first heavy metal content and the second heavy metal content are calculated respectively to improve the accuracy of heavy metal content detection in water.

[0005] Based on the above scheme, it can be seen that for the detection of heavy metal pollutants in water, the existing technology often only considers the differences in heavy metal content in water according to the depth of the water body. In actual detection, the heavy metal content in water is affected by various factors and should be considered comprehensively. Considering the heavy metal content only according to the depth of the water body is often not comprehensive enough. The distribution of heavy metal pollutants in water bodies is affected by many factors such as water type and water area. Different detection locations and detection cycles should be formulated according to different situations. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a method and system for detecting heavy metal pollutants in water based on big data. To achieve the above purpose, the present invention is implemented through the following technical solutions: A method for detecting heavy metal pollutants in water based on big data, comprising:

[0007] Obtain the basic information of the water area to be tested, and analyze and process to generate the basic characteristic values ​​of the water area to be tested.

[0008] The historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested are collected and processed to generate the basic pollution performance value of the water area to be tested.

[0009] Based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, the water sample sampling execution parameters of the water area to be tested are processed and analyzed to generate the water sample sampling execution parameters of the water area to be tested, and the water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and the water body data collection points are arranged according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested.

[0010] The center point of the water area to be tested is taken as the center of the circle, and the mapped interference area is divided with a set radius. The industrial activity data of the mapped interference area are statistically analyzed to generate the environmental pollution factors of the water area to be tested. Based on the environmental pollution factors of the water area to be tested and the basic pollution situation performance value analysis, a single collection cycle of the water sample collection points in the water area to be tested is generated.

[0011] Based on the single collection cycle of the water sample collection points in the water area to be tested, and by collecting water body data at each water sample collection point, the heavy metal pollutant detection results of the water area to be tested are obtained and early warning feedback is given.

[0012] As a preferred technical solution, the basic information of the water area to be measured is obtained, and the basic characteristic values ​​of the water area to be measured are generated through analysis and processing. The specific process is as follows:

[0013] The basic information of the water area to be measured includes the water body type, maximum water body depth, water body area and average water flow velocity of the water area to be measured. Based on the water body type of the water area to be measured, it is matched with the scalar sets corresponding to each water body type in the database to obtain the scalar set corresponding to the water body type of the water area to be measured. The scalar set includes the scalar value of the maximum water body depth, the scalar value of the water body area and the scalar value of the average water flow velocity. The basic characteristic value of the water area to be measured is generated by analysis and processing.

[0014] As a preferred technical solution, the historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested are statistically analyzed, wherein:

[0015] The historical water sample monitoring data specifically include the number of historical heavy metal pollutant types and the historical average concentrations of various types of heavy metal pollutants.

[0016] The historical environmental monitoring data of the location of the water area to be measured includes historical geological data of the location of the water area to be measured and historical meteorological data of the location of the water area to be measured.

[0017] The historical geological data include the average thickness and density of the soil layer at the location of the water area to be measured.

[0018] The historical meteorological data include the historical average precipitation, historical precipitation frequency and historical average temperature of the location of the water area to be measured.

[0019] As a preferred technical solution, the processing generates the basic pollution performance value of the water area to be tested, specifically including:

[0020] A scalar value set of historical water sample monitoring data and a scalar value set of historical environmental monitoring data are extracted from the database, and compared and analyzed with the historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested, so as to obtain the basic pollution performance value of the water area to be tested.

[0021] The historical water sample monitoring data scalar value set includes scalar values ​​of the number of heavy metal pollutant types and scalar values ​​of historical average concentrations of various types of heavy metal pollutants.

[0022] The historical environmental monitoring data scalar value set includes a historical geological data scalar value set and a historical meteorological data scalar value set.

[0023] The historical geological data scalar value set includes a soil layer average thickness scalar value and a soil density scalar value.

[0024] The historical meteorological data scalar value set includes a historical average precipitation scalar value, a historical average precipitation frequency scalar value and a historical average temperature scalar value.

[0025] As a preferred technical solution, the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested are processed and analyzed to generate water sample sampling execution parameters for the water area to be tested. The specific processing method is:

[0026]

[0027] Among them, C is the water sample sampling execution parameter of the water area to be tested, A is the basic characteristic value of the water area to be tested, B is the basic pollution situation performance value of the water area to be tested, α1 is the basic characteristic value weight, and α2 is the basic pollution situation performance value weight.

[0028] As a preferred technical solution, the determination of the horizontal distribution density and vertical distribution density of the water sample sampling location points in the water area to be tested specifically includes:

[0029] Based on the water sample sampling execution parameters of the water area to be tested, the horizontal distribution density of the water sample sampling location points corresponding to each water sample sampling execution parameter interval stored in the database is matched to obtain the horizontal distribution density of the water sample sampling location points in the water area to be tested.

[0030] Based on the water sample sampling execution parameters of the water area to be tested, the vertical distribution density of the water sample sampling location points corresponding to each water sample sampling execution parameter interval stored in the database is matched to obtain the vertical distribution density of the water sample sampling location points in the water area to be tested.

[0031] As a preferred technical solution, the center point of the water area to be measured is taken as the center of the circle, and the mapping interference area is divided by a set radius, thereby statistically analyzing the industrial activity data of the mapping interference area, specifically including:

[0032] Based on the basic pollution performance value of the water area to be tested, the mapping interference range value corresponding to each basic pollution performance value interval pre-stored in the database is matched to obtain the mapping interference range value corresponding to the water area to be tested, and the mapping interference area of ​​the water area to be tested is divided.

[0033] The industrial activity area, the total amount of industrial activity wastewater discharge and the average distribution distance of the industrial activity area distribution distance in the mapped interference area are extracted and combined as the industrial activity data of the mapped interference area.

[0034] As a preferred technical solution, the processing generates the environmental pollution factors of the water area to be tested, and the specific processing conditions are:

[0035] The area boundary values ​​of industrial activity areas in the mapped interference areas, the total amount boundary values ​​of industrial activity wastewater emissions and the average distribution distance boundary values ​​of industrial activity area distribution distances are extracted from the database, and processed with the industrial activity data of the mapped interference areas to generate the environmental pollution factors of the waters to be tested.

[0036] As a preferred technical solution, the single collection cycle of water sample collection points in the water area to be tested is generated based on the analysis of environmental pollution factors and basic pollution performance values ​​of the water area to be tested, specifically including:

[0037] Based on the environmental pollution factor of the water area to be tested, it is multiplied with the basic pollution situation performance value of the water area to be tested to obtain the comprehensive pollution situation performance value of the water area to be tested, and matched with the single collection cycle of the water sample collection point corresponding to each comprehensive pollution situation performance value interval pre-stored in the database to obtain the single collection cycle of the water sample collection point of the water area to be tested. The single collection cycle of the water sample collection point of the water area to be tested is used to characterize the interval time of water sample data collection in the water area to be tested.

[0038] The present invention also provides a system for detecting heavy metal pollutants in water based on big data, comprising:

[0039] The basic information extraction module obtains the basic information of the water area to be tested, and generates the basic characteristic values ​​of the water area to be tested through analysis and processing.

[0040] The historical information extraction module collects historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested, and processes and generates basic pollution performance values ​​of the water area to be tested.

[0041] The execution parameter generation module processes and analyzes the water sample sampling execution parameters of the water area to be tested based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested. The water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and the water body data collection points are arranged according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested.

[0042] The environmental impact analysis module takes the center point of the water area to be tested as the center of the circle and divides it into a mapped interference area with a set radius. The industrial activity data of the mapped interference area is statistically analyzed to generate the environmental pollution factors of the water area to be tested. Based on the environmental pollution factors of the water area to be tested and the basic pollution situation performance value analysis, a single collection cycle of water sample collection points in the water area to be tested is generated.

[0043] The collection and detection module is based on a single collection cycle of water sample collection points in the water area to be tested, and collects water body data at each water sample collection point, processes the heavy metal pollutant detection results of the water area to be tested, and provides early warning feedback.

[0044] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0045] (1) The present invention provides a method for detecting heavy metal pollutants in water based on big data. By analyzing basic information such as the water type of the water body to be tested, as well as statistical historical water sample monitoring data and historical environmental monitoring data of the location of the water body to be tested, the processing of the water body to be tested is analyzed to obtain sample sampling execution parameters, and the potential factors of heavy metal pollution in the water body to be tested are comprehensively considered, thereby improving the accuracy of detection.

[0046] (2) Determining the horizontal and vertical distribution densities of the water sampling locations in the water area to be tested based on the water sampling execution parameters can ensure that the sampling results can accurately represent the water quality of the entire water area and improve the reliability and validity of the data. By sampling at different locations, the source of heavy metal pollution can be better identified, and the diffusion range and impact area of ​​heavy metal pollutants can be determined. Avoid oversampling at unnecessary locations, saving costs and time.

[0047] (3) Based on the analysis of the environmental pollution factors and basic pollution performance values ​​of the water area to be tested, the single collection cycle of the water sample collection points in the water area to be tested is generated, which can improve the pertinence and efficiency of heavy metal pollutant detection in the water area to be tested. By accurately determining the collection cycle, more frequent sampling is ensured in more waters in the surrounding industrial areas, thereby obtaining more accurate and comprehensive data and improving the validity of the data.

[0048] Of course, any product implementing the present invention does not necessarily need to achieve all of the above advantages at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0050] Figure 2 Schematic diagram of the mapping interference area of ​​the water area to be measured involved in the embodiment of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] In the description of the present invention, it should be understood that the terms "opening", "upper", "lower", "thickness", "top", "middle", "length", "inside", "all around" and the like indicating orientation or positional relationship are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the components or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0053] See also Figure 1 As shown, an embodiment of the present invention provides a method for detecting heavy metal pollutants in water based on big data, comprising:

[0054] Obtain the basic information of the water area to be tested, and analyze and process to generate the basic characteristic values ​​of the water area to be tested.

[0055] The basic information of the water area to be measured is obtained, and the basic characteristic values ​​of the water area to be measured are generated through analysis and processing. The specific process is as follows:

[0056] The basic information of the water area to be measured includes the water body type, maximum water body depth, water body area and average water flow velocity of the water area to be measured. Based on the water body type of the water area to be measured, it is matched with the scalar sets corresponding to each water body type in the database to obtain the scalar set corresponding to the water body type of the water area to be measured. The scalar set includes the scalar value of the maximum water body depth, the scalar value of the water body area and the scalar value of the average water flow velocity. The basic characteristic value of the water area to be measured is generated by analysis and processing.

[0057] Water body type refers to the natural properties of water bodies, such as rivers, lakes, reservoirs, oceans, groundwater, etc. Different types of water bodies have different ecological characteristics and environmental functions. For example, the self-purification capacity of rivers is usually stronger than that of lakes, so the detection and evaluation standards for pollutants will be different.

[0058] The maximum depth of a water body refers to the distance from the water surface to the bottom of the water. The maximum depth of a water body affects the distribution, deposition and bioavailability of pollutants. When sampling, the type of sampler and sampling depth need to be determined according to the water depth to ensure that a representative water sample is collected.

[0059] Water area refers to the total surface area of ​​the water body. The size of the water area determines the potential impact range and ecological risk of pollutants. In addition, water area is also an important parameter for calculating pollutant loads and conducting environmental impact assessments.

[0060] The average flow velocity of water refers to the speed at which water flows. The average flow velocity of water affects the migration and diffusion speed of pollutants, as well as the residence time in the water body. Pollutants in rivers with fast flow rates spread quickly, but are usually not easy to accumulate in a certain area. Pollutants in water bodies with slow flow rates are usually more likely to settle.

[0061] The basic processing conditions of the basic characteristic values ​​of the water area to be measured are as follows:

[0062]

[0063] Among them, A is the basic characteristic value of the water area to be tested, H is the maximum depth of the water body to be tested, S is the water area of ​​the water area to be tested, F is the water flow of the water area to be tested, δ is the influencing factor of the water type of the water area to be tested, H0 is the scalar value of the maximum depth of the water body corresponding to the water type of the water area to be tested, S0 is the scalar value of the water area corresponding to the water type of the water area to be tested, F0 is the scalar value of the average flow velocity corresponding to the water type of the water area to be tested, and e is a natural constant.

[0064] The basic characteristic values ​​of the water area to be measured are used to characterize the complexity of water characteristics of the water area to be measured.

[0065] It should be noted that there is a certain correlation between the type of water body, the maximum depth of the water body, the area of ​​the water body and the average flow velocity of the water flow, and the maximum depth of the water body affects the average flow velocity of the water flow. Generally speaking, the average flow velocity of the water flow is slower in places with greater water depth, while the average flow velocity of the water flow is faster in shallow water areas. For example, in a river, the water flow usually speeds up in narrow and deep places, and usually slows down in wide and shallow places. There is an inverse relationship between the area of ​​the water body and the average flow velocity of the water flow. Water bodies with larger areas, such as lakes, usually have slower flow velocities. On the other hand, water bodies with smaller areas, such as narrow rivers, have faster flow velocities. The maximum depth of the water body, the area of ​​the water body and the average flow velocity of the water flow jointly determine the hydraulic characteristics of the water body.

[0066] The historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested are collected and processed to generate the basic pollution performance value of the water area to be tested.

[0067] The specific process of collecting historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested is as follows:

[0068] In another embodiment, historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested are obtained from the environmental monitoring center of the public data platform.

[0069] The historical water sample monitoring data specifically include the number of historical heavy metal pollutant types and the historical average concentrations of various types of heavy metal pollutants.

[0070] The number of historical heavy metal pollutant species refers to the total number of different heavy metal pollutants identified by water sample monitoring within a certain period (such as ten years in this embodiment). This parameter provides an overview of the diversity of heavy metal pollution species in waters. It can help determine the common sources of pollution, because different industrial processes release different heavy metals. The more species there are, the more complex the pollution problem is.

[0071] The historical average concentration of various types of heavy metal pollutants refers to the average concentration of each heavy metal pollutant detected in water samples within a certain period (such as ten years in this example), usually expressed in milligrams per liter (mg / L) or micrograms per liter (μg / L). Changes in concentration over time are analyzed to identify pollution trends.

[0072] In another embodiment, the types of heavy metal pollutants include heavy metals such as lead, mercury, chromium and arsenic.

[0073] The historical environmental monitoring data of the location of the water area to be measured includes historical geological data of the location of the water area to be measured and historical meteorological data of the location of the water area to be measured.

[0074] The average thickness of the soil layer refers to the average vertical distance from the soil surface to the parent material layer or bedrock surface. Soil thickness affects the depth and range of heavy metal pollution. Thick soil layers are generally able to buffer more pollutants, while thin soil layers generally cause pollutants to penetrate into groundwater faster. Soil thickness helps predict the distribution of heavy metal pollutants in the soil profile.

[0075] Soil density refers to the mass of soil per unit volume, usually expressed in grams per cubic centimeter (g / cm 3 ) or kg / m3 (kg / m 3 ) indicates that soil density affects the porosity and permeability of the soil, thus affecting the ability of heavy metal contaminants to migrate downward to groundwater. High soil density generally means that heavy metal contaminants are more likely to accumulate in the soil surface, while low soil density generally indicates that contaminants are more likely to migrate downward.

[0076] The historical meteorological data include the historical average precipitation, historical precipitation frequency and historical average temperature of the location of the water area to be measured.

[0077] The historical average precipitation refers to the amount of water released by each precipitation event in the area where the water area to be tested is located within a certain period (such as ten years in this embodiment), usually in millimeters (mm) or inches. Precipitation can affect the concentration of heavy metals in the water body. Precipitation and precipitation intensity affect surface runoff, usually washing heavy metals in the soil into the water body.

[0078] The historical precipitation frequency refers to the number of precipitation events that occurred within a certain period (such as ten years in this embodiment), which can reflect the regularity and frequency of precipitation. Regions with high precipitation frequency usually have more frequent heavy metal pollution events because precipitation promotes the migration of pollutants.

[0079] The historical average temperature refers to the average temperature of the area where the water area to be tested is located within a certain period (such as ten years in this embodiment), usually expressed in degrees Celsius (°C) or degrees Fahrenheit (°F). The temperature affects the rate of chemical reactions in the water body, including the solubility and form transformation of heavy metals. The temperature affects the metabolic activities of aquatic ecosystems, usually affecting the biodegradation and accumulation of heavy metals. High temperatures usually lead to increased evaporation of water bodies, which in turn affects the volume of water bodies and the concentration of heavy metals.

[0080] The processing generates the basic pollution performance value of the water area to be tested, specifically including:

[0081] A scalar value set of historical water sample monitoring data and a scalar value set of historical environmental monitoring data are extracted from the database, and compared and analyzed with the historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested, so as to obtain the basic pollution performance value of the water area to be tested.

[0082] The historical water sample monitoring data scalar value set includes scalar values ​​of the number of heavy metal pollutant types and scalar values ​​of historical average concentrations of various types of heavy metal pollutants.

[0083] The historical environmental monitoring data scalar value set includes a historical geological data scalar value set and a historical meteorological data scalar value set.

[0084] The historical geological data scalar value set includes a soil layer average thickness scalar value and a soil density scalar value.

[0085] The historical meteorological data scalar value set includes a historical average precipitation scalar value, a historical average precipitation frequency scalar value and a historical average temperature scalar value.

[0086] The processing generates the basic pollution performance value of the water area to be tested, and the specific processing conditions are:

[0087]

[0088] Among them, B is the basic pollution performance value of the water area to be tested, N is the number of historical heavy metal pollutants in the water area to be tested, ρ m is the historical average concentration of the mth heavy metal pollutant, Z is the average thickness of the soil layer where the water area to be tested is located, L is the soil density where the water area to be tested is located, Q is the historical average precipitation where the water area to be tested is located, f is the historical average precipitation frequency where the water area to be tested is located, T is the historical average temperature where the water area to be tested is located, N0 is the scalar value of the number of heavy metal pollutants, ρ 0,m is the historical average concentration scalar value of the mth heavy metal pollutant, Z0 is the scalar value of the average thickness of the soil layer where the water area to be tested is located, L0 is the scalar value of the soil density where the water area to be tested is located, Q0 is the scalar value of the historical average precipitation where the water area to be tested is located, f0 is the scalar value of the historical average precipitation frequency where the water area to be tested is located, T0 is the scalar value of the historical average temperature where the water area to be tested is located, m is the type number of the heavy metal pollutant, m=1,2,3,...,N, N is the number of historical heavy metal pollutants in the water area to be tested, and e is a natural constant.

[0089] It should be noted that there are many correlations between the number of historical heavy metal pollutant types, the historical average concentration of various types of heavy metal pollutants, the average thickness of the soil layer, soil density, historical average precipitation, historical precipitation frequency and historical average temperature. Soil density affects the migration speed of heavy metals in the soil. High-density soil usually hinders the downward migration of heavy metals, causing them to accumulate on the soil surface, which in turn affects the concentration of heavy metals in the water. Soil thickness affects the vertical distribution of heavy metal pollutants. Thicker soil layers usually contain more types of heavy metals because they have more space for stratification and deposition. Precipitation affects the migration of heavy metals from soil to water bodies. The greater the precipitation, the stronger the scouring effect, which usually leads to an increase in the concentration of heavy metals in the water body. In areas with high precipitation frequency, heavy metal pollutants have more opportunities to be washed into the water body, which usually leads to an increase in the number of heavy metal types in the water body. Temperature affects the chemical form and bioavailability of heavy metals. For example, rising temperatures usually increase the solubility of heavy metals, thereby affecting the concentration in the water body. Precipitation, precipitation frequency and temperature are all important factors affecting soil moisture conditions. Soil density affects the soil's permeability and water retention capacity, properties that are affected by meteorological conditions such as precipitation and temperature.

[0090] Based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, the water sample sampling execution parameters of the water area to be tested are processed and analyzed to generate the water sample sampling execution parameters of the water area to be tested, and the water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and the water body data collection points are arranged according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested.

[0091] Based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, the water sample sampling execution parameters of the water area to be tested are generated by processing and analyzing. The specific processing method is:

[0092]

[0093] Among them, C is the water sample sampling execution parameter of the water area to be tested, A is the basic characteristic value of the water area to be tested, B is the basic pollution situation performance value of the water area to be tested, α1 is the basic characteristic value weight, and α2 is the basic pollution situation performance value weight.

[0094] It should be noted that the basic characteristic value weight and the basic pollution situation performance value weight both have a value range between 0 and 1, and satisfy α1+α2=1. The basic characteristic value weight is an influencing factor corresponding to the water sample sampling execution parameters of the water area to be tested preset in the database, and represents a numerical value indicating the degree of influence of the basic characteristic value on the water sample sampling execution parameters of the water area to be tested. The basic pollution situation performance value weight is an influencing factor corresponding to the water sample sampling execution parameters of the water area to be tested preset in the database, and represents a numerical value indicating the degree of influence of the basic pollution situation performance value on the water sample sampling execution parameters of the water area to be tested. When used, the basic characteristic value weight and the basic pollution situation performance value weight can be directly obtained from the database, and the corresponding relationship is a pre-set mapping relationship. For example, the basic characteristic value and the basic pollution situation performance value of the water area to be tested respectively form a mapping set with the corresponding basic characteristic value weight and the basic pollution situation performance value weight, and the basic characteristic value and the basic pollution situation performance value of the water area to be tested are input into the mapping set to obtain the basic characteristic value weight and the basic pollution situation performance value weight of the water area to be tested, wherein the mapping relationship is one-to-one correspondence.

[0095] Determining the horizontal distribution density and vertical distribution density of the water sample sampling location points in the water area to be tested specifically includes:

[0096] Based on the water sample sampling execution parameters of the water area to be tested, the horizontal distribution density of the water sample sampling location points corresponding to each water sample sampling execution parameter interval stored in the database is matched to obtain the horizontal distribution density of the water sample sampling location points in the water area to be tested.

[0097] Based on the water sample sampling execution parameters of the water area to be tested, the vertical distribution density of the water sample sampling location points corresponding to each water sample sampling execution parameter interval stored in the database is matched to obtain the vertical distribution density of the water sample sampling location points in the water area to be tested.

[0098] The horizontal distribution density of the water sample sampling points in the water area to be tested refers to the horizontal spacing distance between each water sample sampling point. In another embodiment, the horizontal distribution density of the water sample sampling points in the water area to be tested whose water body type is a river is 150 meters.

[0099] The vertical distribution density of the water sample sampling points in the water area to be tested refers to the vertical spacing distance between each water sample sampling point. In another embodiment, the vertical distribution density of the water sample sampling points in the water area to be tested whose water body type is a river is 20 meters.

[0100] Determining the horizontal and vertical distribution densities of water sampling locations in different waters to be tested based on the water sampling execution parameters can ensure that the sampling results can accurately represent the water quality of the entire water area and improve the reliability and validity of the data. By sampling at different locations, the pollution source can be better identified, and the diffusion range and impact area of ​​the pollutants can be determined. It also helps to monitor the changing trends of water quality over time and space. Avoid oversampling at unnecessary locations, saving costs and time.

[0101] The center point of the water area to be tested is taken as the center of the circle, and the mapped interference area is divided with a set radius. The industrial activity data of the mapped interference area are statistically analyzed to generate the environmental pollution factors of the water area to be tested. Based on the environmental pollution factors of the water area to be tested and the basic pollution situation performance value analysis, a single collection cycle of the water sample collection points in the water area to be tested is generated.

[0102] The mapping interference area is obtained by taking the center point of the water area to be measured as the center of the circle and dividing it with a set radius, thereby statistically analyzing the industrial activity data of the mapping interference area, specifically including:

[0103] Based on the basic pollution performance value of the water area to be tested, the mapping interference range value corresponding to each basic pollution performance value interval pre-stored in the database is matched to obtain the mapping interference range value corresponding to the water area to be tested, and the mapping interference area of ​​the water area to be tested is divided.

[0104] It should be noted that, in the embodiment of the present invention, the basic pollution performance value of the water area to be tested is used not only to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points in the water area to be tested, but also to determine the mapping interference range value of the water area to be tested, thereby obtaining the mapping interference area of ​​the water area to be tested. The various detection parameters required for the detection of heavy metal pollutants in the water area to be tested are connected in series to facilitate mutual verification of various detection parameters.

[0105] The industrial activity area, the total amount of industrial activity wastewater discharge and the average distribution distance of the industrial activity area distribution distance in the mapped interference area are extracted and combined as the industrial activity data of the mapped interference area.

[0106] The area of ​​industrial activity area refers to the land area where industrial production activities are carried out in the mapped interference area. The size of the industrial activity area can indirectly reflect the potential pollution level of the area. The larger the area, the more pollutants are generated.

[0107] The total amount of industrial wastewater discharge refers to the total amount of wastewater generated by all industrial activities in the mapping interference area within a certain period of time (such as one week in this embodiment). The total amount of wastewater discharge is one of the direct sources of heavy metal pollution, and the pollution source can be identified and quantified through monitoring.

[0108] The average distribution distance of the industrial activity area, which refers to the straight-line distance from the center of the industrial activity area to the center of the water area to be tested. The distance affects the ease with which pollutants migrate to the water area to be tested. The closer the distance, the greater the possibility of pollutant migration.

[0109] The area boundary values ​​of industrial activity areas in the mapped interference areas, the total amount boundary values ​​of industrial activity wastewater emissions and the average distribution distance boundary values ​​of industrial activity area distribution distances are extracted from the database, and processed with the industrial activity data of the mapped interference areas to generate the environmental pollution factors of the waters to be tested.

[0110] The processing generates the environmental pollution factors of the water area to be tested, and the specific processing conditions are:

[0111]

[0112] Among them, D is the environmental pollution factor of the water area to be tested, si is the area of ​​the i-th industrial activity area in the mapping interference area of ​​the water area to be tested, k is the total amount of industrial wastewater discharged in the mapping interference area of ​​the water area to be tested, l is the average distribution distance of the industrial activity area distribution distance in the mapping interference area of ​​the water area to be tested, s0 is the standard value of the industrial activity area area, k0 is the standard value of the total amount of industrial wastewater discharged, l0 is the standard value of the average distribution distance of the industrial activity area distribution distance, i is the industrial activity area number in the mapping interference area, i = 1, 2, 3, ..., n, n is the total number of industrial activity areas in the mapping interference area, and e is a natural constant.

[0113] It should be noted that there is a certain correlation between the area of ​​industrial activity areas in the mapped interference area, the total amount of industrial activity wastewater discharge, and the average distribution distance of the industrial activity area distribution distance. Generally speaking, the larger the area of ​​the industrial activity area, the more factories and enterprises may operate in this area, which will lead to an increase in the total amount of industrial wastewater discharge. Larger industrial activity areas are often accompanied by more production activities, which produce more wastewater. The greater the total amount of wastewater discharge, the more serious the impact on the surrounding environment may be. If this area is closer to the water area to be tested, the risk of water pollution will be higher. The farther the distance, the pollutants in the wastewater may be reduced during migration due to dilution, precipitation, adsorption, etc. Therefore, the distance can affect the specific impact of wastewater discharge on the water area. If the industrial activity area is large and close to the water area to be tested, the potential risk of the area to the water area is high, and more stringent and frequent monitoring is required.

[0114] The method of generating a single collection cycle of water sample collection points in the water area to be tested based on the environmental pollution factors and basic pollution performance values ​​of the water area to be tested specifically includes:

[0115] Based on the environmental pollution factor of the water area to be tested, it is multiplied with the basic pollution situation performance value of the water area to be tested to obtain the comprehensive pollution situation performance value of the water area to be tested, and matched with the single collection cycle of the water sample collection point corresponding to each comprehensive pollution situation performance value interval pre-stored in the database to obtain the single collection cycle of the water sample collection point of the water area to be tested. The single collection cycle of the water sample collection point of the water area to be tested is used to characterize the water sample collection interval of the water area to be tested.

[0116] like Figure 2 The figure shows a schematic diagram of the mapping interference area of ​​the water area V to be tested involved in an embodiment of the present invention, in which point O is the center point of the water area V to be tested, areas E and J are industrial activity areas within the mapping interference area of ​​the water area V to be tested, l1 and l2 are the distance between the center point of area E and the center point of the water area V to be tested and the distance between the center point of area J and the center point of the water area to be tested, respectively, and r is the mapping interference range value of the water area V to be tested. The mapping interference range value r of the water area V to be tested is obtained by the basic pollution performance value of the water area to be tested, and the mapping interference area of ​​the water area V to be tested is obtained by dividing the mapping interference range value r as the radius. The industrial activity area E and the industrial activity area J that affect the water area V to be tested can be systematically included. According to the areas of areas E and J, l1 and l2, and the total amount of industrial wastewater discharged in areas E and J, the environmental pollution factor of the water area V to be tested is obtained by comprehensive processing, which comprehensively characterizes the potential impact of industrial activities on the detection results of heavy metal pollutants in the water quality of the water area V to be tested.

[0117] The single collection cycle of water sample collection points in the water area to be tested is generated based on the analysis of environmental pollution factors and basic pollution performance values ​​of the water area to be tested, which can improve the pertinence and efficiency of heavy metal pollutant detection in the water area to be tested. By accurately determining the collection cycle, more frequent sampling is ensured in water areas with higher pollution risks, so as to obtain more accurate and comprehensive data, improve the validity of the data, and shorten the collection cycle to detect pollution incidents more quickly and take timely countermeasures. In addition, standardized collection cycles help improve the comparability of data collected in different water areas or at different time points, which is convenient for long-term trend analysis.

[0118] Based on the single collection cycle of the water sample collection points in the water area to be tested, and by collecting water body data at each water sample collection point, the heavy metal pollutant detection results of the water area to be tested are obtained and early warning feedback is given.

[0119] Obtain the concentration of various heavy metals in the water samples collected at each water sampling point, extract the concentration allowable values ​​of various heavy metals from the database, and compare them to obtain the pollution degree values ​​of various heavy metals at each water sampling point. The specific treatment conditions include:

[0120]

[0121] Among them, U x,qis the pollution degree value of the xth heavy metal at the qth water sample collection point, y x,q is the concentration of the xth heavy metal collected at the qth water sampling point, y x,0 is the permitted concentration value of the xth heavy metal.

[0122] If any U x,q If the U value of any of the tested waters is greater than or equal to 1, the heavy metal pollutant test result of the tested waters is judged to be unqualified. x,q If it is less than 1, the heavy metal pollutant test results of the tested water area are judged to be qualified.

[0123] If the heavy metal pollutant detection result of a certain water area to be tested is qualified, the horizontal distribution density of the water sample sampling points, the vertical distribution density of the water sample sampling points and the single collection cycle of the water sample collection points in the water area to be tested shall remain unchanged.

[0124] If the heavy metal pollutant test result of a certain water area to be tested is unqualified, an unqualified water quality warning will be sent to the detection system terminal to remind the staff to carry out water quality management in the water area.

[0125] In this embodiment, the present invention provides a system for detecting heavy metal pollutants in water based on big data, comprising:

[0126] The basic information extraction module obtains the basic information of the water area to be tested, and generates the basic characteristic values ​​of the water area to be tested through analysis and processing.

[0127] The historical information extraction module collects historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested, and processes and generates basic pollution performance values ​​of the water area to be tested.

[0128] The execution parameter generation module processes and analyzes the water sample sampling execution parameters of the water area to be tested based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested. The water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and the water body data collection points are arranged according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested.

[0129] The environmental impact analysis module takes the center point of the water area to be tested as the center of the circle and divides it into a mapped interference area with a set radius. The industrial activity data of the mapped interference area is statistically analyzed to generate the environmental pollution factors of the water area to be tested. Based on the environmental pollution factors of the water area to be tested and the basic pollution situation performance value analysis, a single collection cycle of water sample collection points in the water area to be tested is generated.

[0130] The collection and detection module is based on a single collection cycle of water sample collection points in the water area to be tested, and collects water body data at each water sample collection point, processes the heavy metal pollutant detection results of the water area to be tested, and provides early warning feedback.

[0131] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0132] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. As long as they do not deviate from the structure of the present invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. A method for detecting heavy metal pollutants in water based on big data, characterized in that: include: Obtain the basic information of the water area to be tested, and analyze and process to generate the basic characteristic values ​​of the water area to be tested; Collect historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested, and process and generate basic pollution performance values ​​of the water area to be tested; Based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, the water sample sampling execution parameters of the water area to be tested are processed and analyzed to generate the water sample sampling execution parameters of the water area to be tested, and the water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and the water body data collection points are arranged according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested; The center point of the water area to be tested is taken as the center of the circle, and the mapping interference area is divided with a set radius. The industrial activity data of the mapping interference area is statistically analyzed to generate the environmental pollution factor of the water area to be tested. Based on the environmental pollution factor of the water area to be tested and the basic pollution performance value analysis, a single collection cycle of the water sample collection point of the water area to be tested is generated; Based on the single collection cycle of the water sample collection points in the water area to be tested, and by collecting water body data at each water sample collection point, the heavy metal pollutant detection results of the water area to be tested are obtained and early warning feedback is given.

2. The method for detecting heavy metal pollutants in water based on big data according to claim 1, characterized in that: The basic information of the water area to be measured is obtained, and the basic characteristic values ​​of the water area to be measured are generated through analysis and processing. The specific process is as follows: The basic information of the water area to be measured includes the water body type, maximum depth of the water body, water body area and average flow velocity of the water body to be measured. Based on the water body type of the water area to be measured, the scalar set corresponding to each water body type in the database is matched to obtain the scalar set corresponding to the water body type of the water area to be measured, and the scalar set includes the scalar value of the maximum depth of the water body, the scalar value of the water body area and the scalar value of the average flow velocity of the water flow, thereby analyzing and processing to generate the basic characteristic value of the water area to be measured; The basic characteristic values ​​of the water area to be measured are used to characterize the complexity of water characteristics of the water area to be measured.

3. The method for detecting heavy metal pollutants in water based on big data according to claim 1, characterized in that: The statistical data include historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested, wherein: The historical water sample monitoring data specifically include the number of historical heavy metal pollutant types and the historical average concentrations of various types of heavy metal pollutants; The historical environmental monitoring data of the location of the water area to be measured includes historical geological data of the location of the water area to be measured and historical meteorological data of the location of the water area to be measured; The historical geological data include the average thickness and density of the soil layer at the location of the water area to be measured; The historical meteorological data include the historical average precipitation, historical precipitation frequency and historical average temperature of the location of the water area to be measured.

4. The method for detecting heavy metal pollutants in water based on big data according to claim 3, characterized in that: The processing generates the basic pollution performance value of the water area to be tested, specifically including: Extracting a set of scalar values ​​of historical water sample monitoring data and a set of scalar values ​​of historical environmental monitoring data from the database, and comparing and analyzing them with the historical water sample monitoring data of the water area to be tested and the historical environmental monitoring data of the location of the water area to be tested, respectively, to obtain the basic pollution performance value of the water area to be tested; The historical water sample monitoring data scalar value set includes scalar values ​​of the number of heavy metal pollutants and scalar values ​​of the historical average concentrations of various types of heavy metal pollutants; The historical environmental monitoring data scalar value set includes a historical geological data scalar value set and a historical meteorological data scalar value set; The historical geological data scalar value set includes a soil layer average thickness scalar value and a soil density scalar value; The historical meteorological data scalar value set includes a historical average precipitation scalar value, a historical average precipitation frequency scalar value and a historical average temperature scalar value.

5. The method for detecting heavy metal pollutants in water based on big data according to claim 4, characterized in that: Based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, the water sample sampling execution parameters of the water area to be tested are generated by processing and analyzing. The specific processing method is: Among them, C is the water sample sampling execution parameter of the water area to be tested, A is the basic characteristic value of the water area to be tested, B is the basic pollution situation performance value of the water area to be tested, α1 is the basic characteristic value weight, and α2 is the basic pollution situation performance value weight.

6. The method for detecting heavy metal pollutants in water based on big data according to claim 1, characterized in that: Determining the horizontal distribution density and vertical distribution density of the water sample sampling location points in the water area to be tested specifically includes: Based on the water sampling execution parameters of the water area to be tested, the horizontal distribution density of the water sampling location points corresponding to each water sampling execution parameter interval stored in the database is matched to obtain the horizontal distribution density of the water sampling location points in the water area to be tested; Based on the water sample sampling execution parameters of the water area to be tested, the vertical distribution density of the water sample sampling location points corresponding to each water sample sampling execution parameter interval stored in the database is matched to obtain the vertical distribution density of the water sample sampling location points in the water area to be tested.

7. The method for detecting heavy metal pollutants in water based on big data according to claim 1, characterized in that: The mapping interference area is obtained by taking the center point of the water area to be measured as the center of the circle and dividing it with a set radius, thereby statistically analyzing the industrial activity data of the mapping interference area, specifically including: Based on the basic pollution performance value of the water area to be tested, the mapping interference range value corresponding to each basic pollution performance value interval pre-stored in the database is matched to obtain the mapping interference range value corresponding to the water area to be tested, and the mapping interference area of ​​the water area to be tested is obtained by dividing; The industrial activity area, the total amount of industrial activity wastewater discharge and the average distribution distance of the industrial activity area distribution distance in the mapped interference area are extracted and combined as the industrial activity data of the mapped interference area.

8. The method for detecting heavy metal pollutants in water based on big data according to claim 7, characterized in that: The processing generates the environmental pollution factors of the water area to be tested, and the specific processing conditions are: The area boundary values ​​of industrial activity areas in the mapped interference areas, the total amount boundary values ​​of industrial activity wastewater emissions and the average distribution distance boundary values ​​of industrial activity area distribution distances are extracted from the database, and processed with the industrial activity data of the mapped interference areas to generate the environmental pollution factors of the waters to be tested.

9. The method for detecting heavy metal pollutants in water based on big data according to claim 8, characterized in that: The method of generating a single collection cycle of water sample collection points in the water area to be tested based on the environmental pollution factors and basic pollution performance values ​​of the water area to be tested specifically includes: Based on the environmental pollution factor of the water area to be tested, it is multiplied with the basic pollution situation performance value of the water area to be tested to obtain the comprehensive pollution situation performance value of the water area to be tested, and matched with the single collection cycle of the water sample collection point corresponding to each comprehensive pollution situation performance value interval pre-stored in the database to obtain the single collection cycle of the water sample collection point of the water area to be tested. The single collection cycle of the water sample collection point of the water area to be tested is used to characterize the interval time of water sample data collection in the water area to be tested.

10. A heavy metal pollutant detection system in water based on big data, characterized in that: include: The basic information extraction module obtains the basic information of the water area to be tested, and generates the basic characteristic values ​​of the water area to be tested by analysis and processing; The historical information extraction module collects historical water sample monitoring data of the water area to be tested and historical environmental monitoring data of the location of the water area to be tested, and processes and generates basic pollution performance values ​​of the water area to be tested; An execution parameter generation module processes and analyzes the water sample sampling execution parameters of the water area to be tested based on the basic characteristic values ​​and basic pollution performance values ​​of the water area to be tested, wherein the water sample sampling execution parameters of the water area to be tested are used to determine the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested, and arrange the water body data collection points according to the horizontal distribution density and vertical distribution density of the water sample sampling location points of the water area to be tested; The environmental impact analysis module takes the center point of the water area to be tested as the center of the circle and divides it into a mapped interference area with a set radius. The industrial activity data of the mapped interference area is statistically analyzed to generate the environmental pollution factor of the water area to be tested. Based on the environmental pollution factor of the water area to be tested and the basic pollution performance value analysis, a single collection cycle of water sample collection points in the water area to be tested is generated. The collection and detection module is based on a single collection cycle of water sample collection points in the water area to be tested, and collects water body data at each water sample collection point, processes the heavy metal pollutant detection results of the water area to be tested, and provides early warning feedback.

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