Collaborative monitoring and early warning system for cross-media risks of new pollutants in urban water systems

Abstract

The present invention discloses a new pollutant cross-media risk collaborative monitoring and early warning system in an urban water system, which relates to the field of pollution monitoring. The system comprises: an acquisition unit: used for acquiring aquatic product information and water inlet information of each target site; a target unit: used for segmenting the water area based on all the water inlet information to obtain a plurality of sub-areas, and obtaining a target area of ​​each sub-area based on a sampler; a sampling unit: used for sampling each of the target areas based on the sampler to obtain a plurality of water samples and a plurality of environmental samples; an analysis unit: used for performing early warning analysis based on all the water samples and all the environmental samples to obtain early warning information; an early warning unit: used for issuing an early warning to the target area based on the early warning information, which can solve the problem that the existing water pollution early warning technology cannot accurately judge the environmental status of the water area, and does not consider the water self-purification capacity of the water area, which may lead to pollution early warning errors.

Description

Technical Field

[0001] The present invention relates to the field of pollution monitoring, and in particular to a collaborative monitoring and early warning system for cross-media risks of new pollutants in urban water systems. Background Art

[0002] There is a complex source-sink relationship between pollutants in urban water systems. Pollutants entering the environment from different sources will migrate and transform in the water-soil-air multi-media. After migration between multiple media, the content and occurrence form of pollutants in different media will directly affect their biodegradation and transformation process and their enrichment content in organisms including various terrestrial and aquatic plants and animals, further affecting ecological and environmental risks and human health risks. Among them, the cross-media migration of pollutants in urban water systems is mainly achieved through aquatic products.

[0003] Aquaculture farms are places where aquatic plants and animals are bred, cultivated and harvested under human control. The water source of aquaculture farms usually comes from surface water, such as rivers and lakes, but the water quality of rivers is unstable and may be contaminated by bacteria, viruses, heavy metals, plastics and other pollutants. If used directly, it may cause a large number of deaths of aquatic products or accumulate toxins in aquatic products, causing consumers to be poisoned after consumption. At present, water pollution early warning models based on deep learning are usually trained for early warning: sampling is performed by randomly selecting monitoring points, obtaining water quality data information from each monitoring point, and extracting several pollution characteristic indicators from the water quality data information to train the model, thereby achieving early warning. However, the randomly selected monitoring points are not representative, and the environmental status of the water area cannot be accurately judged. Moreover, the self-purification capacity of the water in the water area is not considered, which may lead to pollution early warning errors. Summary of the invention

[0004] In order to solve the problem that the existing water pollution early warning technology cannot accurately judge the environmental status of the water area, and does not consider the water self-purification capacity of the water area, which may lead to pollution early warning errors, the present invention provides a new pollutant cross-media risk collaborative monitoring and early warning system in the urban water system, the system comprising:

[0005] Acquisition unit: used to obtain aquatic product information and water inlet information of each target site;

[0006] Target unit: used to divide the water area into sections based on all the water inlet information to obtain a number of sub-areas, and obtain a target area for each of the sub-areas based on the sampler;

[0007] Sampling unit: used for sampling each of the target areas based on the sampler to obtain a number of water samples and a number of environmental samples;

[0008] Analysis unit: used for performing early warning analysis based on all the water samples and all the environmental samples to obtain early warning information;

[0009] Early warning unit: used to issue an early warning to the target area based on the early warning information.

[0010] Principle of this system: The water area is sampled in sections according to the water inlet position of the target site, and sampling is performed above each water inlet. The water pollution warning of the sectioned water area is more targeted and accurate for the target site. The water flow speed is small, indicating that the area is relatively flat. Then it is judged whether there are stones in the area to reduce the difficulty of sampling caused by a large number of stones. Sampling is more convenient and quick, and the samples are more complete. The sampler collects environmental images, and obtains the water color, aquatic plant content and aquatic animal content of the sectioned water area by analyzing the images. The water self-purification capacity of different sections is predicted by it, and combined with the results of sample analysis, the warning information of aquatic products in the target site is obtained. Because the plants, animals, microorganisms, water bodies, bottom mud and sediments in the water area are coupled systems and are interrelated, the pollution degree of the water area is obtained by analyzing the water samples, environmental samples and environmental images of the water area. The environmental samples may include bottom mud, sediments, etc., so as to realize the cross-media risk collaborative warning of the pollution of aquatic products. More targeted sampling, more representative samples, and considering the water self-purification capacity factor, more accurate and targeted cross-media risk collaborative warning of the pollution of aquatic products can be achieved.

[0011] Considering that the bottom of the water area is uneven, the water speed increases from the steep area to the flat area, which makes it not only difficult to sample, but also the speed at which pollutants in the water are carried away by the water will increase, thereby increasing the degree of dilution of the pollution. The samples in this area are inaccurate. This method uses a speed measuring device and a positioning device to find a flat area with a lower water speed in the segmented water area, which makes sampling easier. Moreover, the floating pollutants that are easy to settle in the water body begin to settle in the place where the water flow is not significant until they reach the bottom of the river, making the sample more representative.

[0012] Furthermore, the specific steps of obtaining the target area of ​​each sub-area based on the sampler include:

[0013] A1. The sampler dives to the bottom of each sub-area;

[0014] A2, obtaining the flow rate of water based on the velocity measuring device of the sampler;

[0015] A3, determining whether the flow rate is greater than a preset flow rate, if so, obtaining a first position of the sampler based on a positioning device of the sampler, and obtaining a second position based on the first position and a first preset distance; if not, obtaining each of the target areas based on a collection device of the sampler;

[0016] A4. Determine whether the second position is within the sub-area range. If so, the sampler moves downstream along the water flow direction to the second position; if not, obtain each of the target areas based on the collection device of the sampler.

[0017] Considering that there may be a large number of rocks in areas with flat terrain, which will increase the difficulty of sampling, this method analyzes the lines in the environmental image, determines the concavity of the lines, and then determines whether there are rocks, thereby obtaining the target area.

[0018] Furthermore, the specific steps of obtaining each of the target areas based on the acquisition device of the sampler include: the acquisition device performs image acquisition on each of the sub-areas to obtain an environmental image; the environmental image is extracted based on the first detection module of the sampler to obtain a line image; based on a first preset range, the lines of the line image are extracted to obtain a plurality of lines; it is determined whether there are protrusions on all the lines, and if so, a first number of the protrusions is obtained, and a first direction is obtained based on the first number, and the sampler moves downstream or upstream along the first direction; if not, a flat area is obtained based on the environmental image, and each of the target areas is obtained based on the flat area.

[0019] Water bodies themselves have a certain degree of environmental self-purification capacity. After pollutants are discharged into water bodies, a series of physical, chemical and biological effects can reduce the concentration of pollutants and gradually purify the water body. The biological purification effect of aquatic organisms is the most important, among which the oxidation and decomposition effect of aquatic microorganisms is the most important. Among the aquatic microorganisms, the changes in the types and quantity of phytoplankton can be shown by water color. Therefore, this method analyzes water color, aquatic plant content and aquatic animal content to further analyze the self-purification capacity of water bodies, making water pollution warnings more accurate.

[0020] Furthermore, the system also includes an environmental unit, which is used to obtain a water self-purification value of each sub-area based on the environmental image, and the water self-purification value is obtained in the following manner: based on the second detection module of the sampler, the environmental image is analyzed to obtain water body information of each sub-area, and the water body information includes water color, aquatic plant content and aquatic animal content; based on all the water body information and preset weights, the water self-purification value of each sub-area is obtained.

[0021] Furthermore, the specific steps of obtaining the aquatic animal content of each of the sub-areas include: identifying the environmental image to obtain an identification result; judging whether there are aquatic animals in the sub-area based on the identification result, and if so, obtaining the category of the aquatic animals and the second quantity of each category based on the identification result; and obtaining the aquatic animal content of each of the sub-areas based on preset aquatic animal habit rules, all the categories and all the second quantities.

[0022] Furthermore, the specific steps of obtaining the water color of each sub-area include: dividing the environmental image to obtain a plurality of sub-images; obtaining the positions of all the aquatic animals based on the recognition results, obtaining a plurality of aquatic animal images based on all the positions, deleting all the aquatic animal images based on all the sub-images to obtain a first image; obtaining a plurality of second images based on a first preset color value range and the first pixel values ​​of all the first images; and obtaining the water color of each sub-area based on the second pixel values ​​of all the second images. Deleting the area of ​​aquatic animals and combining it with the preset color value range can improve the accuracy of the water color.

[0023] Furthermore, the specific steps of obtaining the aquatic plant content of each of the sub-areas include: obtaining a number of third images based on all of the first pixel values ​​and the second preset color value range; obtaining a third quantity of all of the third images, and obtaining the aquatic plant content of each of the sub-areas based on the third quantity.

[0024] When untreated animal remains are thrown into the water, they will first sink to the bottom because their gravity is greater than their buoyancy. Later, due to the decomposition of microorganisms, a large amount of gas will gather in the remains, generating buoyancy, causing the remains to float to the surface of the water. They will rot and deteriorate, polluting the air and producing a foul odor. Animal remains can also accumulate heavy metals and poisons, polluting the soil and water sources they come into contact with, and can even enter the food chain through aquatic products, causing a cyclical ecological hazard. Therefore, this method calculates the pollution value of animal remains, and can obtain early warning information more accurately.

[0025] Furthermore, the environmental unit is also used to obtain a first contamination value for each of the sub-areas based on the environmental image, and the first contamination value is obtained in the following manner: based on the third detection module of the sampler, the environmental image is identified to obtain a remains result; based on the remains result, it is determined whether there are remains, and if so, a second direction of the remains is obtained, the sampler moves a second preset distance downstream or upstream along the second direction, obtains the remains size and the remains quantity based on the collection device, and locates the remains based on the positioning device of the sampler to obtain the remains position; based on the remains position, the remains size and the remains quantity, the first contamination value for each of the sub-areas is obtained.

[0026] Furthermore, the specific steps of performing early warning analysis to obtain early warning information based on all the water samples and all the environmental samples include: analyzing all the water samples and all the environmental samples to obtain a second pollution value for each sub-area; obtaining a third pollution value for each sub-area based on all the first pollution values, all the second pollution values ​​and all the water self-purification values; and obtaining the early warning information based on all the third pollution values ​​and all the aquatic product information.

[0027] Taking into account the different adaptability and tolerance of different types of aquatic products to water quality and the different residual levels in the body, this method conducts different analyses on different types to obtain more accurate early warning information.

[0028] Furthermore, the specific steps of obtaining the warning information based on all the third pollution values ​​and all the aquatic product information include: obtaining the pollution resistance value of each aquatic product based on all the aquatic product information and a preset sensitivity; obtaining the warning information based on all the pollution resistance values ​​and all the third pollution values.

[0029] One or more technical solutions provided by the present invention have at least the following technical effects or advantages:

[0030] 1. The velocity measuring device based on the sampler obtains the water flow velocity, and each target area is obtained based on the flow velocity and the collection device of the sampler. The velocity measuring device and the positioning device are used to find the gentle area with lower water velocity in the segmented water area, which makes sampling easier and the sampled samples are more representative.

[0031] 2. Determine whether there are bulges on all lines. If so, obtain the first number of bulges, obtain the first direction based on the first number, and move the sampler downstream or upstream along the first direction; if not, obtain the flat area based on the environmental image, and obtain each target area based on the flat area, which can reduce the difficulty of sampling.

[0032] 3. The second detection module based on the sampler analyzes the environmental image to obtain the water body information of each sub-area, and obtains the water self-purification value of each sub-area based on all water body information and preset weights; combined with the analysis of water self-purification capacity, water pollution warning can be made more accurate.

[0033] 4. The size and number of remains are obtained based on the collection device, and the positioning device of the sampler is used to locate the remains to obtain the location of the remains; based on the location, size and number of the remains, the first contamination value of each sub-area is obtained, and combined with the analysis of the contamination value of the animal remains, early warning information can be obtained more accurately, and the remains can be located and salvaged according to their location, reducing the pollution caused by the remains.

[0034] 5. Obtain the pollution resistance value of each aquatic product based on all aquatic product information and preset sensitivity; obtain early warning information based on all pollution resistance values ​​and all third pollution values, taking into account the different adaptability and tolerance of different types of aquatic products to water quality and the different residual levels in the body, so that the early warning information is more targeted and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of the present invention, and do not constitute a limitation on the embodiments of the present invention;

[0036] Figure 1 It is a schematic diagram of the system flow in the present invention;

[0037] Figure 2 is a schematic diagram of a process of obtaining a target area of ​​each sub-area based on a sampler in the present invention;

[0038] Figure 3 is a schematic diagram of obtaining each target area by a collection device based on a sampler in the present invention;

[0039] Figure 4 It is a schematic diagram of the process of obtaining the water self-purification value of each sub-area in the present invention;

[0040] Figure 5 It is a schematic diagram of the process of obtaining the first pollution value in the present invention. DETAILED DESCRIPTION

[0041] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0042] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those within the scope of this description. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0043] Embodiment 1

[0044] New pollutants are also called new pollutants or emerging pollutants. New pollutants refer to toxic and harmful chemical substances that are discharged into the environment and have characteristics such as biological toxicity, environmental persistence, and bioaccumulation. They pose a great risk to the ecological environment or human health, but have not yet been included in the management or the existing management measures are insufficient. There are four main categories: persistent organic pollutants, endocrine disruptors, antibiotics, and microplastics. After being discharged into the environment, they are defined as new pollutants.

[0045] refer to Figure 1-Figure 3 This embodiment provides a new pollutant cross-media risk collaborative monitoring and early warning system in an urban water system, the system comprising:

[0046] Acquisition unit: used to obtain aquatic product information and water inlet information of each target site;

[0047] Target unit: used to divide the water area into sections based on all the water inlet information to obtain a number of sub-areas, and obtain a target area for each of the sub-areas based on a sampler; in this embodiment, the sampler may be an underwater sampler;

[0048] The specific steps of obtaining the target area of ​​each sub-area based on the sampler include:

[0049] A1. The sampler dives to the bottom of each sub-area;

[0050] A2. Obtaining the flow rate of water based on the velocity measuring device of the sampler; in this embodiment, the velocity measuring device may be an ultrasonic flow meter, a velocity flow meter or a hydrological velocity meter;

[0051] A3. Determine whether the flow rate is greater than a preset flow rate. If so, obtain the first position of the sampler based on the positioning device of the sampler, and obtain the second position based on the first position and the first preset distance; if not, obtain each of the target areas based on the acquisition device of the sampler; in this embodiment, the positioning device may be a GPS locator, a locator or a positioning tracker, and the acquisition device may be a camera;

[0052] A4. Determine whether the second position is within the sub-area range. If so, the sampler moves downstream along the water flow direction to the second position; if not, obtain each of the target areas based on the collection device of the sampler.

[0053] If the flow meter measures that the water flow rate at the current position is 3m / s, which is greater than the preset flow rate of 1m / s, and the first preset distance is 10m, and the sampler is still within the sub-area after moving 10 meters downstream in the direction of the water flow, then the sampler moves 10 meters downstream from the current position in the direction of the water flow; in this embodiment, after the sampler moves 10 meters, A2-A4 can be repeatedly executed until the second position exceeds the sub-area.

[0054] In A3 and A4, the specific steps of obtaining each of the target areas based on the acquisition device of the sampler include: the acquisition device performs image acquisition on each of the sub-areas to obtain an environment image; the environment image is extracted based on the first detection module of the sampler to obtain a line image; based on the first preset range, the lines of the line image are extracted to obtain a number of lines. Since most of the stones are at the bottom, that is, the bottom of the image, the preset range is used to obtain only the lines within the range; it is determined whether all the lines have bulges, if so, the first number of the bulges is obtained, and the first direction is obtained based on the first number, and the sampler moves downstream or upstream along the first direction; if not, a flat area is obtained based on the environment image, and each of the target areas is obtained based on the flat area. In this embodiment, the first detection module can be a trained image recognition line model; to determine whether it is a bulge, the coordinates of the line can be obtained, and the undulation of the line can be obtained through the coordinates, so as to further determine whether it is a bulge.

[0055] Sampling unit: used for sampling each of the target areas based on the sampler to obtain a number of water samples and a number of environmental samples;

[0056] Analysis unit: used to obtain early warning information based on early warning analysis of all the water samples and all the environmental samples; such as analyzing the composition and pollution degree of the water body through water quality testing instruments, physical and chemical analysis methods and biochemical analysis methods, and analyzing environmental samples such as bottom mud and sediment through laboratory testing methods, gas chromatography and atomic absorption spectrophotometry.

[0057] Early warning unit: used to issue an early warning to the target area based on the early warning information.

[0058] Embodiment 2

[0059] refer to Figure 4 Based on the first embodiment, in this embodiment, the system further includes an environment unit, which is used to obtain the water self-purification value of each sub-area based on the environment image, and the water self-purification value is obtained in the following manner:

[0060] The second detection module based on the sampler analyzes the environmental image to obtain water body information of each sub-area, wherein the water body information includes water color, aquatic plant content, and aquatic animal content; and the water self-purification value of each sub-area is obtained based on all the water body information and preset weights. In this embodiment, the second detection module can be a trained image recognition model.

[0061] The specific steps of obtaining the aquatic animal content of each sub-area include: identifying the environmental image to obtain an identification result; judging whether there are aquatic animals in the sub-area based on the identification result, and if there are aquatic animals, obtaining the category of the aquatic animals and the second quantity of each category based on the identification result; obtaining the aquatic animal content of each sub-area based on the preset aquatic animal habit rules, all the categories and all the second quantities. For example, grass carp generally live in the middle and lower layers of water and areas with a lot of aquatic plants, and often forage in groups. The environmental image identifies 5 grass carps, and the number of grass carps in the entire sub-area can be inferred based on their habits.

[0062] The specific steps of obtaining the water color of each sub-area include: dividing the environmental image to obtain a plurality of sub-images; obtaining the positions of all the aquatic animals based on the recognition results, obtaining a plurality of aquatic animal images based on all the positions, deleting all the aquatic animal images based on all the sub-images to obtain a first image; obtaining a plurality of second images based on a first preset color value range and the first pixel values ​​of all the first images; obtaining the water color of each sub-area based on the second pixel values ​​of all the second images. First, the aquatic animals are deleted from the environmental image, and then the area with only water in the image is obtained according to the preset color value range, so as to obtain the water color.

[0063] Among them, the specific steps of obtaining the aquatic plant content of each sub-area include: obtaining a number of third images based on all the first pixel values ​​and the second preset color value range; obtaining a third number of all the third images, and obtaining the aquatic plant content of each sub-area based on the third number.

[0064] Embodiment 3

[0065] refer to Figure 5 On the basis of the above embodiments, in this embodiment, the first pollution value is obtained in the following manner: based on the third detection module of the sampler, the environmental image is identified to obtain the remains result; based on the remains result, it is determined whether the remains exist, and if so, the second direction of the remains is obtained, the sampler moves downstream or upstream along the second direction for a second preset distance, the remains size and the number of remains are obtained based on the acquisition device, the remains are located based on the positioning device of the sampler to obtain the location of the remains; based on the remains location, the remains size and the remains number, the first pollution value of each sub-area is obtained. In this embodiment, the third detection module can be a trained image remains recognition model. For example, in an area with turbulent water flow, there are few floating organisms and microorganisms in the area, and there is an animal remains, which decomposes relatively slowly, then the pollution value is relatively low.

[0066] Embodiment 4

[0067] On the basis of the above-mentioned embodiments, in this embodiment, the specific steps of performing early warning analysis based on all the water samples and all the environmental samples to obtain early warning information include: analyzing all the water samples and all the environmental samples to obtain the second pollution value of each sub-area; obtaining the third pollution value of each sub-area based on all the first pollution values, all the second pollution values ​​and all the water self-purification values; obtaining the early warning information based on all the third pollution values ​​and all the aquatic product information, and the specific steps include: obtaining the pollution resistance value of each aquatic product based on all the aquatic product information and a preset sensitivity; obtaining the early warning information based on all the pollution resistance values ​​and all the third pollution values.

[0068] For example, compared with fish, shrimps have a stronger tolerance to environmental toxins, pollutants and chemicals. Fish are more sensitive to pollutants in the water, so the warning threshold is relatively smaller than that of shrimps. If the shrimp threshold is 5, then the fish threshold is 4. Then, based on their tolerance to different pollutants, warning information can be obtained.

[0069] Embodiment 5

[0070] On the basis of the above embodiments, in this embodiment, the sampler includes a fuselage, a controller, a flow rate meter, a GPS locator and a ballast tank. The controller controls the discharge and injection of water into the ballast tank so that the sampler can float and dive. The sampler includes a movable arm. The controller controls its movement to realize the movement of the sampler. The fuselage is connected to a plurality of cameras, which can collect images of the surrounding environment and transmit them to an image recognition model. The model recognizes the images, obtains the recognition results and transmits them to the controller, which responds to the samples. A plurality of sample bottles and a peristaltic pump connected to the sample bottles are installed at the bottom of the fuselage. The controller controls the peristaltic pump. The water sample is pumped into the sample bottle; the bottom of the fuselage is connected to the fixed frame through a gear, and the fixed frame is provided with a clamping mechanism for fixing the sampling tube, and the fixed frame is provided with a sampling tube end plate on the upper side of the clamping mechanism, and the sampling tube end plate is provided with a through hole and a valve plate that can close the through hole. When in use, the sampling tube is fixed to the lower side of the sampling tube end plate through the clamping mechanism, and the valve plate is opened. The controller controls the gear to lower the fixed frame, which drives the sampling tube to be quickly inserted into the bottom layer, and the sediment and bottom mud are poured into the sampling tube. Then the valve plate is closed to close the through hole, and the gear pulls up the rope to drive the fixed frame to move upward, and due to the pressure formed in the sampling tube, the sediment in the tube will not scatter. In this embodiment, the sampler can also realize operations such as floating, diving, moving, collecting and sampling through other structures.

[0071] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0072] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A collaborative monitoring and early warning system for new pollutant cross-media risks in urban water systems, characterized by: The system comprises: Acquisition unit: used to obtain aquatic product information and water inlet information of each target site; Target unit: used to divide the water area into sections based on all the water inlet information to obtain a number of sub-areas, and obtain a target area for each of the sub-areas based on the sampler; Sampling unit: used for sampling each of the target areas based on the sampler to obtain a number of water samples and a number of environmental samples; Analysis unit: used for performing early warning analysis based on all the water samples and all the environmental samples to obtain early warning information; Early warning unit: used for issuing early warning to the target area based on the early warning information; The specific steps of obtaining the target area of ​​each sub-area based on the sampler include: A1. The sampler dives to the bottom of each sub-area; A2, obtaining the flow rate of water based on the velocity measuring device of the sampler; A3, determining whether the flow rate is greater than a preset flow rate, if so, obtaining a first position of the sampler based on a positioning device of the sampler, and obtaining a second position based on the first position and a first preset distance; if not, obtaining each of the target areas based on a collection device of the sampler; A4, determining whether the second position is within the sub-area, if so, the sampler moves downstream along the water flow direction to the second position; if not, obtaining each of the target areas based on the collection device of the sampler; The specific steps of obtaining each target area based on the acquisition device of the sampler include: The acquisition device acquires images of each of the sub-areas to obtain an environment image; Extracting the environment image based on the first detection module of the sampler to obtain a line image; extracting lines of the line image based on a first preset range to obtain a plurality of lines; Determine whether all the lines have bulges, if yes, obtain a first number of the bulges, obtain a first direction based on the first number, and move the sampler downstream or upstream along the first direction; if no bulges exist, obtain a flat area based on the environment image, and obtain each target area based on the flat area; The system further includes an environment unit, which is used to obtain the water self-purification value of each sub-area based on the environment image, and the water self-purification value is obtained by: analyzing the environment image based on the second detection module of the sampler to obtain water body information of each sub-area, wherein the water body information includes water color, aquatic plant content and aquatic animal content; and obtaining the water self-purification value of each sub-area based on all the water body information and preset weights; The specific steps of obtaining the aquatic animal content of each sub-area include: identifying the environmental image to obtain an identification result; judging whether there are aquatic animals in the sub-area based on the identification result, and if there are aquatic animals, obtaining the category of the aquatic animals and the second quantity of each category based on the identification result; obtaining the aquatic animal content of each sub-area based on the preset aquatic animal habit rules, all the categories and all the second quantities; The specific steps of obtaining the water color of each sub-area include: dividing the environmental image to obtain a plurality of sub-images; obtaining the positions of all the aquatic animals based on the recognition results, obtaining a plurality of aquatic animal images based on all the positions, deleting all the aquatic animal images based on all the sub-images to obtain a first image; obtaining a plurality of second images based on a first preset color value range and the first pixel values ​​of all the first images; and obtaining the water color of each sub-area based on the second pixel values ​​of all the second images; The specific steps of obtaining the aquatic plant content of each sub-area include: obtaining a plurality of third images based on all the first pixel values ​​and the second preset color value range; obtaining a third number of all the third images, and obtaining the aquatic plant content of each sub-area based on the third number; The environment unit is further used to obtain a first pollution value of each sub-area based on the environment image, and the first pollution value is obtained in the following manner: Recognize the environmental image based on the third detection module of the sampler to obtain the remains result; Based on the remains result, determine whether there are remains, if yes, obtain a second direction of the remains, move the sampler downstream or upstream along the second direction by a second preset distance, obtain the size and quantity of the remains based on the collection device, locate the remains based on the positioning device of the sampler, and obtain the position of the remains; The first contamination value of each of the sub-areas is obtained based on the location of the remains, the size of the remains and the number of the remains.

2. The new pollutant cross-media risk collaborative monitoring and early warning system in the urban water system according to claim 1 is characterized in that: The specific steps of performing early warning analysis based on all the water samples and all the environmental samples to obtain early warning information include: Analyze all the water samples and all the environmental samples to obtain a second pollution value for each of the sub-areas; Obtaining a third pollution value for each of the sub-areas based on all of the first pollution values, all of the second pollution values, and all of the water self-purification values; The early warning information is obtained based on all the third pollution values ​​and all the aquatic product information.

3. The cross-media risk collaborative monitoring and early warning system for new pollutants in urban water systems according to claim 2 is characterized in that: The specific steps of obtaining the warning information based on all the third pollution values ​​and all the aquatic product information include: Obtaining a pollution resistance value for each aquatic product based on all the aquatic product information and a preset sensitivity; The early warning information is obtained based on all the pollution resistance values ​​and all the third pollution values.

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