Dynamic tracing-based multi-source pollution monitoring method and system for estuary

Abstract

The application provides a kind of based on dynamic tracing estuary multi-source pollution monitoring method and system, the method comprises: obtaining the pollution information of the estuary of target water area;Obtain the pollution information of the pollution point of target water area;Construct multi-source pollution convection diffusion model;The pollution information of the estuary of target water area and the pollution information of the pollution point of target water area are input into the multi-source pollution convection diffusion model, obtain the pollution concentration value of each pollution point diffused to the estuary;According to the pollution concentration value corresponding to each pollution point, obtain the pollution contribution degree of each pollution point to the estuary;According to the pollution contribution degree corresponding to each pollution point, combined with the preset water area monitoring criterion, carry out pollution point monitoring to target water area. Thus, by applying the method described in the application, the tracing, monitoring and management efficiency of estuary pollution can be improved.

Description

Technical Field

[0001] This application relates to the field of water pollution monitoring, and in particular to a method and system for monitoring multi-source pollution at sea estuaries based on dynamic source tracing. Background Technology

[0002] With the intensification of coastal economic activities, the estuary area has become a key node in water pollution control due to the concentrated discharge of pollutants from pollution sources and the interaction of marine dynamic conditions.

[0003] Traditional monitoring methods are mostly based on static diffusion models, which estimate pollutant migration by fixing the coordinates of pollution sources. However, these methods ignore the spatiotemporal dynamics of multi-source emissions (such as moving ships and seasonal runoff), causing the source tracing results to deviate from the true contribution ratio. At the same time, the high-resolution grid computing used across the entire domain is inefficient under complex hydrodynamic conditions and cannot meet the needs of real-time monitoring. Furthermore, they have not effectively solved problems such as dynamic source coordinate drift and lag in multi-source data fusion, resulting in insufficient adaptability of the model under the influence of tides and ocean currents. Consequently, the efficiency of source tracing, monitoring, and treatment of pollution at sea estuaries is low. Summary of the Invention

[0004] Based on this, the purpose of this application is to provide a method and system for monitoring multi-source pollution at sea estuaries based on dynamic source tracing, which can effectively improve the efficiency of source tracing, monitoring and treatment of pollution at sea estuaries.

[0005] The objective of this application can be achieved through the following technical solutions:

[0006] A method for monitoring multi-source pollution at sea estuaries based on dynamic source tracing includes the following steps: acquiring pollution information of the estuary of a target water area, wherein the pollution information of the estuary includes at least the geographical coordinates of the estuary and the pollutant concentration at the estuary; acquiring pollution information of pollution points in the target water area, wherein the pollution information of the pollution points includes at least the geographical coordinates of several pollution points and the corresponding pollution emission intensity information; constructing a multi-source pollution convection and diffusion model; inputting the pollution information of the estuary of the target water area and the pollution information of the pollution points in the target water area into the multi-source pollution convection and diffusion model to obtain the pollution concentration value diffused to the estuary by each pollution point; obtaining the pollution contribution of each pollution point to the estuary based on the pollution concentration value corresponding to each pollution point; and monitoring pollution points in the target water area based on the pollution contribution of each pollution point and in conjunction with preset water area monitoring criteria.

[0007] A multi-source pollution monitoring system for sea estuaries based on dynamic source tracing, comprising: a pollution information acquisition unit for acquiring pollution information of the sea estuary in a target water area, wherein the pollution information includes at least the geographical coordinates of the sea estuary and the pollutant concentration at the sea estuary; a pollution point information acquisition unit for acquiring pollution information of pollution points in the target water area, wherein the pollution point information includes at least the geographical coordinates of several pollution points and the corresponding pollution emission intensity information; and a multi-source pollution convection and diffusion model construction unit for... A multi-source pollution convection and diffusion model is constructed; a pollution concentration calculation unit is used to input pollution information of the estuary of the target water area and pollution information of pollution points in the target water area into the multi-source pollution convection and diffusion model to obtain the pollution concentration value of each pollution point diffused to the estuary; a pollution contribution calculation unit is used to obtain the pollution contribution of each pollution point to the estuary based on the pollution concentration value corresponding to each pollution point; a pollution point monitoring unit is used to monitor pollution points in the target water area based on the pollution contribution of each pollution point and in combination with preset water area monitoring criteria.

[0008] Compared to existing technologies, the method described in this application first obtains pollution information of the estuary of the target water area and pollution information of pollution points in the target water area. Then, a multi-source pollution convection and diffusion model is constructed, and the pollution information of the estuary of the target water area and the pollution information of pollution points in the target water area are input into the multi-source pollution convection and diffusion model to obtain the pollution concentration value of each pollution point diffused to the estuary. Finally, based on the pollution concentration value corresponding to each pollution point, the pollution contribution of each pollution point to the estuary is obtained, and pollution point monitoring of the target water area is carried out based on the pollution contribution corresponding to each pollution point and in conjunction with preset water area monitoring criteria. Therefore, the method described in this application, by acquiring real-time geographic coordinates and pollution data of the estuary and pollution points, constructs an adaptive multi-source diffusion model, realizing a direct correlation between the emission intensity of pollution points and the concentration changes at the estuary. Furthermore, by reverse-analyzing the dynamic contribution of each pollution point through the concentration values ​​output by the model, and combining it with preset monitoring criteria to achieve responsibility classification, the implementation effect of pollution control decisions is improved, and the matching efficiency between monitoring results and control actions for pollution at the estuary is enhanced, thereby effectively improving the efficiency of tracing, monitoring, and controlling pollution at the estuary.

[0009] To better understand and implement this application, the following detailed description is provided in conjunction with the accompanying drawings. Attached Figure Description

[0010] Figure 1 A flowchart illustrating the steps of a multi-source pollution monitoring method for estuaries based on dynamic source tracing provided in this application;

[0011] Figure 2 A flowchart illustrating the steps involved in obtaining pollution information at the estuary of a target water area in a dynamic source tracing-based multi-source pollution monitoring method for estuaries provided in this application.

[0012] Figure 3 A flowchart illustrating the steps for obtaining the first observation sensor combination in a dynamic source tracing-based multi-source pollution monitoring method for estuaries provided in this application;

[0013] Figure 4 A flowchart illustrating the steps involved in obtaining the pollution concentration values ​​of each pollution point diffused to the estuary in a dynamic source-tracing-based multi-source pollution monitoring method for estuaries provided in this application.

[0014] Figure 5 A flowchart illustrating the steps involved in obtaining the distance between the estuary of a target water area and a pollution point in the target water area using a dynamic source tracing-based multi-source pollution monitoring method for estuaries provided in this application.

[0015] Figure 6 The schematic diagram of the structural principle of a multi-source pollution monitoring system for estuaries based on dynamic source tracing provided in this application. Detailed Implementation

[0016] This application provides a method and system for monitoring multi-source pollution at sea estuaries based on dynamic source tracing. To make the objectives, technical solutions, and effects of this application clearer and more explicit, the following detailed description is provided with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application.

[0017] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0018] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0019] The invention will be further explained below with reference to the accompanying drawings and the description of the embodiments.

[0020] Example 1

[0021] Please refer to Figure 1 , Figure 1 A flowchart illustrating the steps of a multi-source pollution monitoring method for estuaries based on dynamic source tracing provided in this application. The method includes the following steps:

[0022] S10. Obtain pollution information at the estuary of the target water area;

[0023] S20. Obtain pollution information on pollution points in the target water area;

[0024] S30. Construct a multi-source pollution convection and diffusion model;

[0025] S40. Input the pollution information of the estuary of the target water area and the pollution information of the pollution points in the target water area into the multi-source pollution convection and diffusion model to obtain the pollution concentration value of each pollution point diffused to the estuary.

[0026] S50. Based on the pollution concentration value corresponding to each pollution point, obtain the pollution contribution of each pollution point to the estuary.

[0027] S60. Based on the pollution contribution of each pollution point and in conjunction with preset water monitoring criteria, pollution point monitoring is conducted on the target water area.

[0028] Compared to existing technologies, this application significantly improves the accuracy and operability of estuary pollution monitoring by systematically integrating dynamic pollution source tracking and multi-source contribution classification mechanisms. In this application's technical solution, real-time geographic coordinates and pollution data of the estuary and pollution points are dynamically acquired to construct an adaptive multi-source diffusion model, directly linking the emission intensity of pollution points with changes in concentration at the estuary, thus avoiding the source-tracing distortion problem caused by data update lag in traditional models. Furthermore, addressing the difficulty in quantifying the contribution of multi-source pollution, existing technologies often employ single concentration thresholds or empirical weighting, failing to distinguish the actual impact ratio of different pollution sources (such as industrial emissions and agricultural runoff) in complex scenarios. In contrast, this application uses the concentration values ​​output by the model to inversely analyze the dynamic contribution of each pollution point, combining this with preset monitoring criteria to achieve responsibility classification, shifting pollution control decisions from "fuzzy attribution" to "precise positioning." Therefore, the technical solution of this application improves the efficiency of tracing, monitoring and treating pollution at the estuary through a dynamic process monitoring and data-driven mechanism, and enhances the matching efficiency between monitoring results and treatment actions for pollution at the estuary, providing a feasible technical path for the monitoring, prevention and control of pollution at the estuary.

[0029] For step S10, obtain pollution information at the estuary of the target water area.

[0030] The target water area refers to a water area with an estuary used to implement the method described in this application; the pollution information of the estuary includes at least the geographical coordinates of the estuary and the concentration of pollutants at the estuary, such as the latitude and longitude coordinates of the estuary and the concentration of pollutants such as lead, cadmium or crude oil at the estuary.

[0031] Please refer to Figure 2 In one embodiment, step S10 includes the following steps:

[0032] S101. Obtain several different sensors from the sensor pool and construct a sensor combination for observing the target water area.

[0033] The sensor pool includes several sensors for observing ground features, and the target water area observation sensor assembly includes at least two different sensors for observing pollution information in the target water area.

[0034] S102. Calculate the subject-matter fit T of the target water area observation sensor combination according to the subject-matter fit calculation formula. r :

[0035]

[0036] Among them, T iLet n be the subject matching degree of the i-th sensor in the target water area observation sensor combination, and n be the number of sensors in the target water area observation sensor combination.

[0037] .

[0038] In one embodiment, if a large amount of green algae proliferates in the estuary waters, causing pollution, the chlorophyll content in the water will increase significantly. Therefore, the chlorophyll a absorption peak at 440nm needs to be matched with the sensor's blue light band. For example, the characteristic band of chlorophyll a is 440nm. If the sensor covers 430-450nm, then T... i =100%; If sensor A covers 80% of the characteristic bands of chlorophyll a, while sensor B covers 60%, then the subject matter fit T of the sensor combination for observing the target water area is 100%. r = (80% + 60%) / 2 = 70%.

[0039] S103. Calculate the spatiotemporal coverage C of the target water area observation sensor combination according to the spatiotemporal coverage calculation formula. v :

[0040] ,

[0041] Among them, S i R represents the coverage area of ​​the target water area by the i-th sensor in the target water area observation sensor combination within a preset time window; ∪ represents the spatiotemporal union, meaning that coverage at any time at the same location is counted as coverage; ∩ represents the spatial intersection, meaning that only coverage within the target water area is calculated.

[0042] In this embodiment, S i It can be viewed as a spacetime cube.

[0043] In one embodiment, technicians can use Google Earth Engine or ArcGIS Pro to perform spatiotemporal raster calculations to generate a heatmap of overlay to calculate the spatiotemporal overlay, for example, a study area of ​​100 km². 2 The target water area observation sensor array covers 80km. 2 Then C v =80%.

[0044] S104. Calculate the overall accuracy suitability R of the target water area observation sensor combination according to the overall accuracy suitability calculation formula. s :

[0045]

[0046] Wherein, p(a i ) represents the accuracy suitability of the i-th sensor in the target water area observation sensor assembly, which is the reciprocal of the sensor's resolution; m i The number of grid cells corresponding to the resolution of the i-th sensor in the target water area observation sensor combination; M is the total number of grid cells in the target water area; n1 is the number of resolution types.

[0047] In one embodiment, p(a i The score is related to the sensor's resolution, and in this embodiment, it can be directly equivalent to the reciprocal of the sensor's resolution.

[0048] In one embodiment, a 10m resolution corresponds to 100 grids; when the sensor resolution is 10m, 30m, or 50m, then n1 = 3.

[0049] In one embodiment, the weighted average of the accuracy suitability is calculated by using the proportion of the number of grids in sensors with different resolutions as weights.

[0050] In one embodiment, if the total number of grids in the target water area is M = 1000, then sensor A has a resolution of 10m and covers 500 grids (m1 = 500); sensor B has a resolution of 30m and covers 300 grids (m2 = 300); sensor C has a resolution of 50m and covers 200 grids (m3 = 200); R S =0.064.

[0051] S105. Based on the preset evaluation criteria, and combining the subject relevance of the target water area observation sensor combination, the spatiotemporal coverage of the target water area observation sensor combination, and the overall accuracy suitability of the target water area observation sensor combination, an overall observation capability satisfaction evaluation of the target water area observation sensor combination is conducted to obtain the first observation sensor combination.

[0052] Among them, the first observation sensor combination is the target water area observation sensor combination with the highest overall observation capability satisfaction.

[0053] Please refer to Figure 3 In one embodiment, step S105 includes the following steps:

[0054] S1051. Calculate the overall observation capability satisfaction (OCSI) of the target water area observation sensor combination according to the overall observation capability satisfaction calculation formula:

[0055]

[0056] Among them, C iC represents the coverage area of ​​the target water area by the i-th sensor in the target water area observation sensor assembly within a preset time window. a The total area of ​​the target water body.

[0057] S1052. The target water area observation sensor combination with the highest overall observation capability satisfaction is set as the first observation sensor combination.

[0058] In one embodiment, when the method described in this application is applied to multi-source pollution monitoring at the estuary of a tributary of a river, C a =100km 2 There is sensor A (satellite) with a resolution of 10m, and C... i =80km 2 T i =90%, p(a i = 0.1; Sensor B (UAV), resolution 0.1m, C i =20km 2 T i =100%, p(a i =10; Sensor C (mobile monitoring vehicle), resolution 1m, C i =5km 2 T i =80%, p(a i If ) = 1, then the overall observation capability satisfaction of the target water area observation sensor combination is OCSI = 211.2%.

[0059] In some embodiments, OCSI needs to be constrained between 0% and 100%. A value exceeding 100% indicates that the sensor combination capability far exceeds the requirements, and technicians can normalize it to 100%.

[0060] S106. Using the first observation sensor combination to observe the estuary of the target water area, obtain the observation data of the estuary of the target water area, and acquire the pollution information of the estuary of the target water area.

[0061] The observation data at the estuary of the target water area includes first observation data and second observation data.

[0062] In one embodiment, step S106 includes the following steps:

[0063] S1061. The first observation sensor combination is used to observe the estuary of the target water area at several consecutive time points to obtain the first observation data.

[0064] In this embodiment, the first observation sensor combination is used to observe the estuary of the target water area at several consecutive time points to obtain data with timestamps (t1, t2, ..., t). m The sensor time series data, also known as the first observation data.

[0065] S1062. Set a sliding window for data fusion and assign Gaussian weights w(t) to each of the first observation data. j ):

[0066]

[0067] The sliding window is a time period centered on the transit time of the remote sensing satellite over the target water area, t. j Let t be the observation timestamp of the first observation data. sat Let σ be the transit time of the remote sensing satellite over the target water area, σ be the control weight decay rate, and σ = Δt / 3, where Δt is the width of the preset sliding window, and e is the natural logarithm.

[0068] In this embodiment, the transit time t of the target water area by a remote sensing satellite is used. sat Centered on the window, set the window width Δt of the activity window, for example, ±6 hours; simultaneously, use a Gaussian decay weighting function, with the distance from t... sat More recent data has a higher weight.

[0069] S1063. The first observation data within the sliding window is fused according to the Gaussian weights to generate second observation data Dn(t) aligned with the satellite time of the remote sensing satellite. j ):

[0070]

[0071] Wherein, D(t) j ) is at time t j The first observation data observed at that time, where n is the number of the first observation data within the sliding window.

[0072] In one embodiment, t sat Given a timeframe of 10:00 and a window width Δt = 6 hours, the first observation data measured by the sensor combination at 8:00 (Gaussian weight 0.8), 12:00 (Gaussian weight 0.6), and 14:00 (Gaussian weight 0.3) are 20, 25, and 30, respectively. The obtained second observation data is Dn(t). j = 23.2.

[0073] In addition, this application also provides some steps for monitoring multi-source pollution at estuaries. When these steps are applied to the multi-source pollution monitoring method at estuaries, abnormal observation data can be eliminated. These steps include:

[0074] S107. Obtain historical data of the observation data of the estuary of the target water area;

[0075] S108. Construct an isolated forest using the historical data, and set the upper limit of the trees in the isolated forest to a preset upper limit value;

[0076] In one embodiment, the preset upper limit value is 100.

[0077] S109. Based on the isolated forest and the preset upper limit value, calculate the anomaly score of the observation data at the estuary of the target water area;

[0078] S110. If the abnormal score of the observation data of the estuary of the target water area is greater than a preset value, then the observation data of the estuary of the target water area shall be removed.

[0079] In one embodiment, if the anomaly score of the observation data at the estuary of the target water area is greater than 0.65, the observation data at the estuary of the target water area is determined to be an outlier and removed.

[0080] For step S20, obtain pollution information of pollution points in the target water area.

[0081] The pollution information of the pollution points includes at least the geographical coordinates of several pollution points and the corresponding pollution emission intensity information, such as the latitude and longitude coordinates of the pollution points and the concentrations of pollutants such as lead, cadmium or crude oil at the pollution points.

[0082] In one embodiment, a person skilled in the art may adapt the technical solution described in steps S101-S110 and apply it to step S20 to achieve the same or similar technical effect.

[0083] In one embodiment, the target water body includes at least one pollution point. It can be understood that the method described in this application can be applied when the number of pollution points in the target water body is arbitrary.

[0084] For step S30, construct a multi-source pollution convection and diffusion model.

[0085] In one embodiment, step S30 includes the following steps:

[0086] S301. Obtain the water information of the target water area.

[0087] The water information of the target water area includes at least the diffusion coefficient and the water flow velocity field of the target water area;

[0088] S302. Based on the water area information of the target water area, construct a multi-source pollution convection and diffusion model:

[0089] ,

[0090] Wherein, C is the pollutant concentration field of the target water area, t is time, D is the diffusion coefficient of the target water area, u is the water flow velocity field of the target water area, and S is the amount of pollutants released per second from the pollution point in the target water area.

[0091] In this embodiment, C is a spatially continuous function that describes the concentration distribution of pollutants within the computational domain (including the vicinity of the pollution source, the propagation path, the estuary, etc.). For example, C may be higher at the pollution source location; at the estuary, C is the combined result of all upstream pollution sources after water flow and diffusion.

[0092] In this embodiment, the value of C at the estuary is the value of the multi-source pollution convection-diffusion model at a specific location (x). 入海口 y 入海口 The solution to ).

[0093] For step S40, the pollution information of the estuary of the target water area and the pollution information of the pollution points in the target water area are input into the multi-source pollution convection and diffusion model to obtain the pollution concentration value of each pollution point diffused to the estuary.

[0094] Please refer to Figure 4 In one embodiment, step S40 includes the following steps:

[0095] S401. Obtain the distance between the estuary of the target water area and the pollution point in the target water area;

[0096] In one embodiment, the pollution points in the target water area include point source pollution, line source pollution, and non-point source pollution; and, please refer to Figure 5 Step S401 includes the following steps:

[0097] S4011. When the pollution point in the target water area is a point source pollution, obtain the Euclidean distance between the estuary of the target water area and the point source pollution.

[0098] In one embodiment, when the pollution point of the target water area is a point source pollution, S = Qδ(x-x0,y-y0), where Q is the emission rate of the point source pollution and δ is the Dirac function, indicating that there is emission only at (x0,y0).

[0099] S4012. When the pollution point of the target water area is a linear source pollution, obtain the Euclidean distance between the estuary of the target water area and the endpoint of the linear source pollution.

[0100] In other embodiments, when the pollution point in the target water area is a line source pollution, it can also be regarded as the pollutants being discharged along a continuous path (e.g., rivers and oil pipelines), that is, x and y are regarded as the set of path coordinates of the line source. For example, the coordinates of the centerline of a tributary river are {(x1,y1),(x2,y2),...,(x...y1)}. n ,y n )},

[0101] ,

[0102] Where L is the total length of the line source, Qtotal is the total emission rate, and it is discretely represented by multiple point source emissions.

[0103] S4013. When the pollution points in the target water area are non-point source pollution, the pollution points in the target water area are rasterized and converted into distributed point source pollution for distance acquisition.

[0104] In other embodiments, when the pollution point of the target water body is a non-point source pollution, it can be regarded as the pollutant being widely distributed and discharged within a region (such as farmland or urban surface runoff). That is, x and y are regarded as the boundary range of the non-point source or the coordinates of the vertices of a polygon. For example, the boundary coordinates of a certain farmland area are {(x1,y1),(x2,y2),...,(x...y1)}. n ,y n )}, forming a polygon,

[0105] (when (x,y)∈the surface source region),

[0106] Where A is the area of ​​the emission source and Q_total is the total emission rate, which is distributed evenly across each unit area.

[0107] S402. Input the pollution information of the estuary of the target water area and the pollution information of the pollution points in the target water area into the multi-source pollution convection and diffusion model, and calculate the pollution concentration value C of each pollution point diffused to the estuary in combination with the distance. i ':

[0108]

[0109] Where Q is the river flow rate of the target water area, and x is the distance.

[0110] In these embodiments, x and y represent the location of any point within the target water area, typically corresponding to a geographic coordinate system (such as latitude and longitude) or a planar projected coordinate system (such as metric coordinates in the east-west and north-south directions); x0 and y0 are the precise location coordinates of the pollution source (such as a sewage outlet or factory chimney).

[0111] For step S50, based on the pollution concentration value corresponding to each pollution point, obtain the pollution contribution of each pollution point to the estuary.

[0112] In one embodiment, step S50 includes the following steps:

[0113] S501. Based on the pollution concentration values ​​corresponding to each pollution point, and in conjunction with the pollution contribution calculation formula, obtain the pollution contribution ηi of each pollution point to the estuary:

[0114]

[0115] Among them, C i Let n1 be the pollution concentration value at the estuary where the i-th pollution point spreads, and n2 be the number of pollution points.

[0116] For step S60, pollution point monitoring is carried out on the target water area based on the pollution contribution of each pollution point and in conjunction with the preset water area monitoring criteria.

[0117] In one embodiment, technicians can monitor pollution points in target waters using the following methods: First, tiered monitoring, listing pollution points with a contribution exceeding a preset threshold (e.g., 20%) as key monitoring targets, deploying online sensors to monitor emission intensity and water quality changes in real time, and conducting regular inspections of low-contribution points; Second, path tracking, adding mobile monitoring buoys along key diffusion paths (e.g., river confluences, mainstream ocean currents) between estuaries and high-contribution pollution points to capture the migration dynamics of pollution plumes; Third, dynamic response, automatically triggering drone patrols and satellite remote sensing to quickly locate abnormal emission sources when the contribution of a pollution point suddenly increases in a short period (e.g., exceeding the threshold by 50%); Fourth, coordinated governance, linking contribution ranking with the approval of discharge permits and the priority of environmental law enforcement, for example, mandating the installation of intelligent discharge gates for pollution points in the top 10% of contribution for three consecutive months to achieve closed-loop management of pollution control; In addition, the layout of monitoring points can be optimized by combining historical contribution data, eliminating redundant monitoring equipment with long-term low contribution, and reducing operation and maintenance costs.

[0118] Example 2

[0119] Please refer to Figure 6This application also provides a multi-source pollution monitoring system for estuaries based on dynamic source tracing, to implement the steps of the multi-source pollution monitoring method for estuaries based on dynamic source tracing described in the above embodiments. The multi-source pollution monitoring system for estuaries based on dynamic source tracing includes: an estuary pollution information acquisition unit 1001, a pollution point pollution information acquisition unit 1002, a multi-source pollution convection and diffusion model construction unit 1003, a pollution concentration value calculation unit 1004, a pollution contribution calculation unit 1005, and a pollution point monitoring unit 1006.

[0120] The estuary pollution information acquisition unit 1001 is used to acquire pollution information of the estuary of the target water area, wherein the pollution information of the estuary includes at least the geographical coordinate information of the estuary and the pollutant concentration of the estuary.

[0121] The pollution point pollution information acquisition unit 1002 is used to acquire pollution information of pollution points in the target water area, wherein the pollution information of the pollution points includes at least the geographical coordinate information of several pollution points and the corresponding pollution emission intensity information.

[0122] The multi-source pollution convection and diffusion model construction unit 1003 is used to construct a multi-source pollution convection and diffusion model.

[0123] The pollution concentration calculation unit 1004 is used to input the pollution information of the estuary of the target water area and the pollution information of the pollution points in the target water area into the multi-source pollution convection and diffusion model to obtain the pollution concentration value of each pollution point diffused to the estuary.

[0124] The pollution contribution calculation unit 1005 is used to obtain the pollution contribution of each pollution point to the estuary based on the pollution concentration value corresponding to each pollution point.

[0125] The pollution point monitoring unit 1006 is used to monitor pollution points in the target water area based on the pollution contribution of each pollution point and in accordance with preset water area monitoring criteria.

[0126] It should be noted that the above embodiment of the multi-source pollution monitoring system for estuaries based on dynamic source tracing is only illustrated by the above-described division of functional modules when implementing a multi-source pollution monitoring method for estuaries based on dynamic source tracing. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the equipment can be divided into different functional modules to complete all or part of the functions described above.

[0127] Furthermore, the multi-source pollution monitoring system for estuaries based on dynamic source tracing provided in the above embodiments and the multi-source pollution monitoring method for estuaries based on dynamic source tracing in Embodiment 1 are based on the same concept. The implementation process is detailed in the method embodiment, namely Embodiment 1, and will not be repeated here.

[0128] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and this application also intends to include these modifications and variations.

Claims

1. A method for monitoring multi-source pollution at an estuary based on dynamic tracing, comprising the following steps: obtaining pollution information of an estuary of a target water area, wherein the pollution information of the estuary at least includes geographic coordinate information of the estuary and concentration of pollutants at the estuary; obtaining pollution information of pollution points of the target water area, wherein the pollution information of the pollution points at least includes geographic coordinate information of a plurality of pollution points and corresponding pollution emission intensity information; constructing a multi-source pollution convection and diffusion model, comprising: obtaining water area information of the target water area, wherein the water area information of the target water area at least includes diffusion coefficient and water flow velocity field of the target water area; constructing a multi-source pollution convection and diffusion model according to the water area information of the target water area; ， wherein, C C is the concentration field of the pollutant of the target water area, t t is time, D D is the diffusion coefficient of the target water area, u is the water flow velocity field of the target water area, S Q is the amount of pollutant released per second by the pollution point of the target water area; inputting the pollution information of the estuary of the target water area and the pollution information of the pollution points of the target water area into the multi-source pollution convection and diffusion model to obtain pollution concentration values of each of the pollution points diffused to the estuary, comprising: obtaining distances between the estuary of the target water area and the pollution points of the target water area; The pollution information of the estuary of the target water area and the pollution information of the pollution points of the target water area are input into the multi-source pollution convection diffusion model, and the distance is combined to calculate the pollution concentration values of each of the pollution points diffused to the estuary C i ’ : ， wherein, Q is the river flow of the target water area, x is the distance; According to the pollution concentration value corresponding to each pollution point, the pollution contribution degree of each pollution point to the estuary is obtained, including: according to the pollution concentration value corresponding to each pollution point, combining the pollution contribution degree calculation formula, obtaining the pollution contribution degree of each pollution point to the estuary ηi : ， wherein, C i is the number of the pollution points, i the pollution concentration value at the estuary, n 2 is the number of the pollution points. monitoring the pollution points of the target water area according to the corresponding pollution contribution degrees of each of the pollution points and combining a preset water area monitoring criterion. 2.The method for monitoring multi-source pollution at an estuary based on dynamic tracing according to claim 1, wherein the step of obtaining pollution information of an estuary of a target water area comprises: obtaining a plurality of different sensors from a sensor pool to construct a target water area observation sensor combination, wherein the sensor pool includes a plurality of sensors for observing ground objects, and the target water area observation sensor combination at least includes two different sensors for observing pollution information of the target water area; According to the subject fitness calculation formula of the target water area observation sensor combination, the subject fitness of the target water area observation sensor combination is calculated T r : ， wherein, T i a subject matching degree for a first i sensor of the target water area observation sensor combination, n a number of sensors in the target water area observation sensor combination, and, ； According to the spatio-temporal coverage calculation formula of the target water area observation sensor combination, the spatio-temporal coverage of the target water area observation sensor combination is calculated C v : ， in, S i The first in the target water area observation sensor assembly i Each sensor monitors the coverage area of ​​the target water area within a preset time window. R ∪ represents the spatial extent of the target water area; ∪ represents the spatiotemporal union, meaning that any coverage at the same location at any time is counted as coverage; ∩ represents the spatial intersection, meaning that only coverage within the target water area is calculated. According to the overall precision fitness calculation formula of the observation sensor combination of the target water area, the overall precision fitness of the observation sensor combination of the target water area is calculated R s : ， wherein, p(a i ) a resolution of a sensor in the sensor combination for the target water area; i a resolution of a sensor in the sensor combination for the target water area; m i a resolution of a sensor in the sensor combination for the target water area; i a resolution of a sensor in the sensor combination for the target water area; M a resolution of a sensor in the sensor combination for the target water area; n 1 is a number of resolution types; evaluating overall observation capability satisfaction of the target water area observation sensor combination according to a preset evaluation standard, combining subject fitness of the target water area observation sensor combination, spatiotemporal coverage of the target water area observation sensor combination, and overall accuracy suitability of the target water area observation sensor combination to obtain a first observation sensor combination; applying the first observation sensor combination to observe the estuary of the target water area to obtain observation data of the estuary of the target water area, and obtaining pollution information of the estuary of the target water area. 3.The method for monitoring multi-source pollution at an estuary based on dynamic tracing according to claim 2, wherein the step of evaluating overall observation capability satisfaction of the target water area observation sensor combination to obtain a first observation sensor combination comprises: calculating overall observation capability satisfaction OCSI of the target water area observation sensor combination according to an overall observation capability satisfaction calculation formula of the target water area observation sensor combination: ， wherein, C i an area covered by the i-th sensor in the combination of sensors observing the target water area within a preset time window, i an area covered by the i-th sensor in the combination of sensors observing the target water area within a preset time window, C a an area covered by the i-th sensor in the combination of sensors observing the target water area within a preset time window, setting the target water area observation sensor combination with the maximum overall observation capability satisfaction as the first observation sensor combination.

4. The dynamic provenance based estuary multi-source pollution monitoring method according to claim 2, characterized in that, The observation data of the estuary of the target water area includes first observation data and second observation data; The step of applying the first observation sensor combination to observe the estuary of the target water area to obtain observation data of the estuary of the target water area comprises: The first observation sensor combination is applied to observe the estuary of the target water area at a plurality of continuous time nodes to obtain first observation data; a sliding window of data fusion is set and a Gaussian weight is assigned to each of the first observation data w ( t j ) ， The sliding window is a time period centered on the transit time of the remote sensing satellite over the target water area, t j is the observation timestamp of the first observation data, t sat is the transit time of the remote sensing satellite over the target water area, and σ is a control weight decay speed, and σ = Δ / 3, Δ is the width of the preset sliding window, e is a natural logarithm; fusing the first observation data within the sliding window according to the Gaussian weight, to generate second observation data aligned with satellite time of the remote sensing satellite Dn(t j ) ， wherein, D(t j is the first observation data observed at time t j is the first observation data observed at time n is the number of the first observation data within the sliding window.

5. The dynamic source-based estuary multi-source pollution monitoring method according to any one of claims 2-4, wherein the dynamic source-based estuary multi-source pollution monitoring method further comprises the following steps: obtaining historical data of observation data of the estuary of the target water area; constructing an isolated forest using the historical data, and setting an upper limit of a tree of the isolated forest as a preset upper limit value; calculating an anomaly score of the observation data of the estuary of the target water area according to the isolated forest and the preset upper limit value; if the anomaly score of the observation data of the estuary of the target water area is greater than a preset value, eliminating the observation data of the estuary of the target water area.

6. The dynamic provenance-based estuary multi-source pollution monitoring method according to claim 1, characterized in that: The pollution points of the target water area include point source pollution, line source pollution, and area source pollution. The step of obtaining the distance between the estuary of the target water area and the pollution points of the target water area comprises the following steps: when the pollution point of the target water area is point source pollution, obtaining the Euclidean distance between the estuary of the target water area and the point source pollution; when the pollution point of the target water area is line source pollution, obtaining the Euclidean distance between the estuary of the target water area and the endpoint of the line source pollution; when the pollution point of the target water area is area source pollution, rasterizing the pollution point of the target water area to convert it into a distributed point source pollution for distance acquisition.

7. A dynamic provenance-based estuary multi-source pollution monitoring system, characterized in that, The dynamic source-based estuary multi-source pollution monitoring system comprises: an estuary pollution information obtaining unit configured to obtain pollution information of an estuary of a target water area, wherein the pollution information of the estuary at least includes geographic coordinate information of the estuary and pollutant concentration of the estuary; a pollution point pollution information obtaining unit configured to obtain pollution information of pollution points of the target water area, wherein the pollution information of the pollution points at least includes geographic coordinate information of a plurality of pollution points and corresponding pollution emission intensity information; a multi-source pollution convection and diffusion model constructing unit configured to construct a multi-source pollution convection and diffusion model, including: obtaining water area information of the target water area, wherein the water area information of the target water area at least includes a diffusion coefficient and a water flow velocity field of the target water area; constructing a multi-source pollution convection and diffusion model according to the water area information of the target water area: ， wherein, C is the concentration field of the pollutant of the target water area, t is time, D is the diffusion coefficient of the target water area, u is the water flow velocity field of the target water area, S is the amount of pollutant released per second by the pollution point of the target water area; a pollution concentration value calculating unit configured to input the pollution information of the estuary of the target water area and the pollution information of the pollution points of the target water area into the multi-source pollution convection and diffusion model to obtain pollution concentration values of each of the pollution points diffused to the estuary, including: obtaining the distance between the estuary of the target water area and the pollution points of the target water area; The pollution information of the estuary of the target water area and the pollution information of the pollution points of the target water area are input into the multi-source pollution convection diffusion model, and the distance is combined to calculate the pollution concentration values of each of the pollution points diffused to the estuary C i ’ : ， wherein, Q is the river flow of the target water area, x is the distance; The pollution contribution degree calculation unit is configured to obtain the pollution contribution degree of each pollution point to the estuary according to the pollution concentration value corresponding to each pollution point, and includes a pollution contribution degree calculation unit configured to obtain the pollution contribution degree of each pollution point to the estuary according to the pollution concentration value corresponding to each pollution point and in combination with a pollution contribution degree calculation formula ηi : ， wherein, C i is the number of the pollution points, i the pollution concentration value at the estuary, n 2 is the number of the pollution points. a pollution point monitoring unit configured to monitor the target water area according to the corresponding pollution contribution degrees of each of the pollution points in combination with a preset water area monitoring criterion.

Images