A method, system, terminal and medium for tracing water pollution in a river basin

Abstract

The application discloses a kind of river basin water pollution traceability method, system, terminal and medium, it is related to water pollution traceability technical field.Its main technical scheme: constructing water flow velocity prediction model;Real-time acquisition of pollutant concentration in river basin;When pollutant concentration at current sampling time is greater than pollutant concentration at last sampling time;Collect current time water level height;Current time water level height is input into water flow velocity prediction model, and current time water flow velocity is obtained;According to current time water flow velocity, last sampling time, current sampling time and monitoring point position, potential pollution source area is constructed;According to pollutant inventory information and current time pollutant concentration, identify pollution source.It is expected to significantly reduce the migration path deviation caused by using constant flow rate, to improve the accuracy of traceability result purpose.At the same time, it is expected to achieve only in the initial stage of pollution event rapid response, in favor of emergency disposal, and reduce continuous full-time period simulation, save computing resource purpose.

Description

Technical Field

[0001] This invention relates to the field of water pollution source tracing technology, specifically to a method, system, terminal, and medium for tracing water pollution sources in a watershed. Background Technology

[0002] Water pollution is water whose usability is reduced or lost due to harmful chemicals, and which pollutes the environment. Especially in watersheds that span long distances and flow through various industrial parks, factors such as industrial production emissions can cause some toxic and harmful heavy metal pollutants to flow into the watershed, resulting in water pollution. In order to treat watersheds polluted by heavy metal pollutants in a timely and effective manner, it is necessary to accurately trace the pollutants in the watershed, so as to achieve the effect of source control of water pollution in the watershed.

[0003] Currently, numerical models based on convection-diffusion equations (such as WASP, EFDC, and MIKE) are used to trace pollutant migration paths by simulating them in either forward or reverse directions. However, most of these models assume constant water flow velocity or only use historical averages, failing to dynamically reflect the real-time impact of water level changes on water flow velocity, resulting in significant biases in the source tracing results. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, terminal and medium for tracing the source of water pollution in a watershed, which solves the problem that existing methods for tracing the source of pollutants in a watershed fail to dynamically reflect the real-time impact of water level changes on water flow velocity, thus leading to large deviations in the tracing results.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] Firstly, a method for tracing the source of water pollution in a river basin is provided, including the following steps:

[0007] S1, Construct a water flow velocity prediction model, which is used to predict the change of water flow velocity with water level in the basin;

[0008] S2, real-time acquisition of pollutant concentrations at monitoring points within the watershed;

[0009] S3, determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time; if yes, proceed to S4; if no, proceed to S2.

[0010] S4, collects the current water level height within the basin;

[0011] S5, input the current water level height into the water flow velocity prediction model to obtain the current water flow velocity;

[0012] S6. Based on the current water flow velocity, the previous sampling time, the current sampling time, and the location of the monitoring point, a potential pollution source area is constructed.

[0013] S7. Identify pollution sources based on the pollutant inventory information of each pollution source within the pollution source area and the current pollutant concentration in the watershed.

[0014] A further proposed solution is that the process of constructing the water flow velocity prediction model includes:

[0015] Historical hydrological data within the watershed is obtained, including historical water level heights and historical water flow velocities corresponding to those historical water level heights.

[0016] Historical hydrological data are cleaned to obtain cleaned historical water level heights and historical water flow velocities.

[0017] A water flow velocity prediction model was obtained by training the model on historical water level heights and historical water flow velocities after cleaning.

[0018] A further proposed solution is that the process of cleaning historical hydrological data includes:

[0019] S101, determine if the historical water level is greater than 0; if yes, execute S102; if no, remove the historical water level and the corresponding historical water flow velocity.

[0020] S102, determine whether the historical water flow velocity is greater than 0; if yes, retain the historical water flow velocity and the corresponding historical water level; if no, remove the historical water flow velocity and the corresponding historical water level.

[0021] A further proposed solution includes: when the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time, it also includes:

[0022] S201, determine whether the water level at the current sampling time is greater than or equal to the water level at the previous sampling time; if yes, execute S4; if no, execute S202.

[0023] S202, acquire the cross-sectional data and water flow velocity at the previous acquisition time, and the cross-sectional data and water flow velocity at the current time; wherein, the cross-sectional data includes the cross-sectional shape and cross-sectional dimensions;

[0024] S203, Calculate the pollutant flow rate at the previous collection time based on the cross-sectional data, water flow velocity, and pollutant concentration at the previous collection time;

[0025] S204. Calculate the pollutant flow rate at the current sampling time based on the cross-sectional data, water flow velocity, and pollutant concentration.

[0026] S205, determine whether the pollutant flow rate at the current collection time is greater than the pollutant flow rate at the previous collection time; if yes, execute S4; if no, execute S2.

[0027] A further proposed solution includes: when the pollutant concentration at the current sampling time is less than or equal to the pollutant concentration at the previous sampling time, it also includes:

[0028] Determine whether the water level at the current sampling time is greater than the water level at the previous sampling time; if yes, execute S202; if no, execute S2.

[0029] A further proposed solution is that the process of constructing the potential pollution source area includes:

[0030] Calculate the sampling time interval based on the previous sampling time and the current sampling time;

[0031] Based on the sampling time interval and the current water flow velocity, calculate the maximum distance that the pollutant can travel within the sampling time interval;

[0032] Based on the maximum traversable distance and the location of the monitoring points, a potential pollution source area is constructed, extending the maximum distance in the opposite direction of the water flow from the monitoring points.

[0033] Secondly, a watershed water pollution source tracing system is provided, which is applicable to the watershed water pollution source tracing method described in the first aspect. The watershed water pollution source tracing system includes a first construction module, an acquisition module, a judgment module, a collection module, an input module, a second construction module, and an identification module. The first construction module is used to construct a water flow velocity prediction model, which is used to predict the change in water flow velocity with water level in the watershed. The acquisition module is used to acquire the pollutant concentration at monitoring points in the watershed in real time. The judgment module is used to determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. The collection module is used to collect the water level in the watershed at the current time when the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. The input module is used to input the water level at the current time into the water flow velocity prediction model to obtain the water flow velocity at the current time. The second construction module is used to construct a potential pollution source area based on the water flow velocity at the current time, the previous sampling time, the current sampling time, and the location of the monitoring point. The identification module is used to identify pollution sources based on the characteristic information of each pollution source within the pollution source area and the pollutant concentration in the watershed at the current time.

[0034] Thirdly, a terminal is provided, including a processor and a memory, the memory being used to store processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the watershed water pollution source tracing method as described in the first aspect.

[0035] Fourthly, a computer-readable storage medium is provided, on which computer program instructions are stored, which, when executed by a processor, implement the watershed water pollution source tracing method as described in the first aspect.

[0036] Compared with the prior art, the beneficial effects of the present invention are:

[0037] The system predicts the current water flow velocity in real time based on the current water level. This aims to significantly reduce migration path deviations caused by using constant flow velocities, thereby improving the accuracy of source tracing results. Simultaneously, a "concentration rise triggering" mechanism is employed to achieve rapid response only at the initial stage of a pollution event, facilitating emergency handling and reducing the need for continuous, full-time simulations, thus saving computational resources. Attached Figure Description

[0038] Figure 1 This is a flowchart illustrating a watershed water pollution source tracing method in this embodiment. Detailed Implementation

[0039] The invention will now be further described with reference to the accompanying drawings.

[0040] Example 1: This example provides a method for tracing the source of water pollution in a watershed, such as... Figure 1 As shown, it includes the following steps:

[0041] S10. Construct a water flow velocity prediction model, which is used to predict the change of water flow velocity with water level height in the basin;

[0042] In this embodiment, the process of constructing the water flow velocity prediction model includes:

[0043] S101. Obtain historical hydrological data within the watershed, the historical hydrological data including historical water level height and historical water flow velocity corresponding to the historical water level height;

[0044] For example, during implementation, historical hydrological data accumulated over a long period of time is obtained from hydrological stations deployed within the basin, water resources department databases, automatic monitoring stations, and other channels. This historical hydrological data includes historical water level heights and corresponding historical water flow velocities.

[0045] S102. Clean the historical hydrological data to obtain the cleaned historical water level and historical water flow velocity;

[0046] In this embodiment, the process of cleaning historical hydrological data includes:

[0047] S1001. Determine if the historical water level is greater than 0; if yes, proceed to S1002; if no, remove the historical water level and the corresponding historical water flow velocity.

[0048] For example, during implementation, it is determined whether the historical water level is greater than 0; if the historical water level is greater than 0, the process jumps to S1002; if the historical water level is less than or equal to 0, the historical water level and the historical water flow velocity corresponding to the historical water level are removed.

[0049] In watersheds such as natural rivers or artificial channels, water level is an absolute or relative elevation referenced to a certain datum (such as the riverbed or the Yellow Sea elevation), and is usually a positive value. Therefore, when the water level is ≤0, it indicates a sensor malfunction (such as misreading when the river is dry), data transmission or storage errors (such as misplaced negative signs or unit confusion), or extreme anomalies (such as the riverbed being completely dry and the datum being improperly set).

[0050] S1002. Determine if the historical water flow velocity is greater than 0; if yes, retain the historical water flow velocity and the corresponding historical water level; if no, remove the historical water flow velocity and the corresponding historical water level.

[0051] For example, during implementation, when the historical water level is greater than 0, it is determined whether the historical water flow velocity is greater than 0; if the historical water flow velocity is greater than 0, the historical water flow velocity and the historical water level corresponding to the historical water flow velocity are retained; if the historical water flow velocity is less than or equal to 0, the historical water flow velocity and the historical water level corresponding to the historical water flow velocity are discarded.

[0052] Water flow velocity represents the speed of water movement. In watersheds such as natural rivers or artificial channels, water flow velocity should be a positive number. Therefore, when the water flow velocity is ≤0, it indicates that there is instrument zero drift or malfunction (such as negative noise output when ADCP is stationary), data processing error (such as sign reversal), etc.

[0053] By removing historical hydrological data with historical water levels less than or equal to 0 and historical flow velocities less than or equal to 0, the historical water levels and flow velocities in the historical hydrological data are ensured to be positive, conforming to natural hydrological patterns. The aim is to enable the model to more accurately capture the mapping relationship between actual water levels and flow velocities, thereby reducing overfitting noise or systematic bias and improving the accuracy of the flow velocity prediction model.

[0054] S103. Train the historical water level height and historical water flow velocity after cleaning to obtain a water flow velocity prediction model.

[0055] For example, during implementation, the historical water level after cleaning is used as the model input, and the historical water flow velocity corresponding to the historical water level after cleaning is used as the model output. Multiple linear regression, support vector regression (SVR), random forest (RF), and other models are used to train the historical water level and historical water flow velocity after cleaning to obtain a water flow velocity prediction model.

[0056] S20. Real-time acquisition of pollutant concentrations at monitoring points within the watershed;

[0057] For example, during implementation, the concentration of pollutants monitored at monitoring points within the watershed is obtained in real time.

[0058] S30. Determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time; if yes, proceed to S40; if no, proceed to S20.

[0059] For example, during implementation, it is determined whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. Ideally, if the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time, it indicates that a pollution source is releasing pollutants into the watershed. In this case, proceed to S40. If the pollutant concentration at the current sampling time is less than or equal to the pollutant concentration at the previous sampling time, it indicates that no pollution source is releasing pollutants into the watershed. In this case, proceed to S20.

[0060] S40. Collect the current water level height within the basin;

[0061] For example, during implementation, when the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time, the water level height in the basin at the current time is collected simultaneously.

[0062] S50. Input the current water level into the water flow velocity prediction model to obtain the current water flow velocity;

[0063] For example, during implementation, the collected water level height at the current moment is input into the water flow velocity prediction model to obtain the water flow velocity at the current moment.

[0064] S60. Construct potential pollution source areas based on the current water flow velocity, the previous sampling time, the current sampling time, and the location of the monitoring point;

[0065] In this embodiment, the process of constructing the potential pollution source area includes:

[0066] S601. Calculate the sampling time interval based on the previous sampling time and the current sampling time;

[0067] For example, during implementation, the sampling time interval is obtained by subtracting the previous sampling time from the current sampling time.

[0068] S602. Based on the sampling time interval and the current water flow velocity, calculate the maximum distance that the pollutant can travel within the sampling time interval;

[0069] For example, during implementation, the sampling time interval is multiplied by the current water flow velocity to obtain the maximum distance that the pollutant can travel along the water flow direction within the sampling time interval.

[0070] S603. Based on the maximum traversable distance and the location of the monitoring point, construct a potential pollution source area extending the maximum distance in the opposite direction of the water flow, starting from the monitoring point.

[0071] For example, during implementation, starting from the monitoring point, the possible upstream migration path of pollutants is deduced by using the maximum drivable distance to obtain the potential pollution source area.

[0072] S70. Identify pollution sources based on the pollutant inventory information of each pollution source within the pollution source area and the current pollutant concentration within the watershed.

[0073] For example, during implementation, the pollutant emission inventory of all known pollution sources in the pollution source area (such as environmental impact assessment reports and pollutant discharge permit data) is retrieved, and combined with concentration decay patterns, emission intensity, emission time windows, etc., the contribution of each pollution source is quantified by using probability matching or Bayesian inference methods.

[0074] The watershed pollution source tracing method in this embodiment, on the one hand, predicts the current water flow velocity in real time based on the current water level. This aims to significantly reduce migration path deviations caused by using constant flow velocities, thereby improving the accuracy of source tracing results, especially suitable for watersheds with drastic flow velocity changes during flood / dry seasons. On the other hand, it employs a "concentration rise triggering" mechanism. This aims to achieve rapid response only at the initial stage of a pollution event, facilitating emergency handling and reducing the need for continuous, full-time simulations, thus saving computational resources.

[0075] In practical implementation, when prolonged drought occurs, leading to a reduction in water volume within the basin, even without pollutant discharge from any source, the pollutant concentration at the current sampling time may be higher than the concentration at the previous sampling time. Therefore, to reduce the risk of a passive increase in pollutant concentration due to water level drops during the dry season being mistakenly interpreted as the release of pollutants into the basin, this embodiment further includes the following when the pollutant concentration at the current sampling time is higher than the concentration at the previous sampling time:

[0076] S201. Determine whether the water level at the current sampling time is greater than or equal to the water level at the previous sampling time; if yes, proceed to S40; if no, proceed to S202.

[0077] For example, during implementation, if the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time, the water level at the current sampling time and the water level at the previous sampling time are obtained, and it is determined whether the water level at the current sampling time is greater than or equal to the water level at the previous sampling time. If the water level at the current sampling time is greater than or equal to the water level at the previous sampling time, it indicates that a pollution source has released pollutants into the watershed, causing the pollutant concentration in the watershed to rise. In this case, S40 is executed. If the water level at the current sampling time is less than the water level at the previous sampling time, it indicates that there may be a situation where the water level drops during the dry season, causing the pollutant concentration in the watershed to passively increase. In this case, S202 is executed.

[0078] S202. Obtain the cross-sectional data and water flow velocity at the previous acquisition time, as well as the cross-sectional data and water flow velocity at the current time; wherein, the cross-sectional data includes the cross-sectional shape and cross-sectional dimensions;

[0079] For example, during implementation, the cross-sectional data and water flow velocity at the previous acquisition time, as well as the cross-sectional data and water flow velocity at the current time, are acquired. The cross-sectional data typically comes from river surveying or water conservancy department databases, and includes the cross-sectional shape and dimensions. Cross-sectional dimensions include bottom width, slope, and water level.

[0080] S203. Calculate the pollutant flow rate at the previous sampling time based on the cross-sectional data, water flow velocity, and pollutant concentration at the previous sampling time;

[0081] For example, during the implementation process, the cross-sectional shape and dimensions at the previous sampling time are first used to calculate the flow area of ​​the watershed at the previous sampling time. Then, the flow area, water velocity, and pollutant concentration at the previous sampling time are used to calculate the pollutant flow rate at the previous sampling time.

[0082] S204. Calculate the pollutant flow rate at the current sampling time based on the cross-sectional data, water flow velocity, and pollutant concentration.

[0083] For example, during implementation, the cross-sectional shape and dimensions at the current sampling time are first used to calculate the flow area of ​​the watershed at that time. Then, the flow area, water velocity, and pollutant concentration at the current sampling time are used to calculate the pollutant flow rate at that time.

[0084] S205. Determine whether the pollutant flow rate at the current collection time is greater than the pollutant flow rate at the previous collection time; if yes, execute S40; if no, execute S20.

[0085] For example, during implementation, it is determined whether the pollutant flow rate at the current sampling time is greater than the pollutant flow rate at the previous sampling time. If the pollutant flow rate at the current sampling time is greater than the pollutant flow rate at the previous sampling time, it indicates that a pollution source has released pollutants into the watershed, increasing the pollutant flow rate and consequently leading to an increase in pollutant concentration within the watershed. In this case, step S40 is executed. If the pollutant flow rate at the current sampling time is less than or equal to the pollutant flow rate at the previous sampling time, it indicates that a drop in water level during the dry season has led to a passive increase in pollutant concentration within the watershed. In this case, step S20 is executed. The aim is to reduce the likelihood of false alarms caused by a passive increase in concentration due to a drop in water level during the dry season being mistaken for pollution events, thereby significantly reducing the false alarm rate.

[0086] In practical implementation, when prolonged rainfall leads to an increase in water volume within the basin, even if pollutants are discharged from pollution sources, the pollutant concentration at the current sampling time may be less than or equal to the pollutant concentration at the previous sampling time. Therefore, to reduce the risk of a passive decrease in pollutant concentration due to rising water levels during the high-water season being mistakenly interpreted as the absence of pollutant discharge from pollution sources into the basin, this embodiment further includes the following when the pollutant concentration at the current sampling time is less than or equal to the pollutant concentration at the previous sampling time:

[0087] Determine whether the water level at the current sampling time is greater than the water level at the previous sampling time; if yes, execute S202; if no, execute S20.

[0088] For example, during implementation, when the pollutant concentration at the current sampling time is less than or equal to the pollutant concentration at the previous sampling time, the water level at the current sampling time and the water level at the previous sampling time are obtained, and it is determined whether the water level at the current sampling time is greater than the water level at the previous sampling time. If the water level at the current sampling time is greater than the water level at the previous sampling time, it indicates that there may be a situation where the water level rise during the high-water season leads to a passive decrease in the pollutant concentration in the basin. At this time, S202 is executed to obtain the cross-sectional data and water flow velocity at the previous sampling time, as well as the cross-sectional data and water flow velocity at the current time; wherein, the cross-sectional data usually comes from river mapping or water conservancy department databases, and the cross-sectional data includes cross-sectional shape and cross-sectional dimensions. Cross-sectional dimensions include bottom width, slope, water level, etc. Next, the cross-sectional shape and cross-sectional dimensions at the previous sampling time are used to calculate the flow area of ​​the basin at the previous sampling time. Then, the flow area, water flow velocity, and pollutant concentration at the previous sampling time are used to calculate the pollutant flow rate at the previous sampling time. Next, using the cross-sectional shape and dimensions at the current sampling time, the flow area of ​​the watershed at the current sampling time is calculated. Then, using the flow area, water flow velocity, and pollutant concentration at the current sampling time, the pollutant flow rate at the current sampling time is calculated. Finally, it is determined whether the pollutant flow rate at the current sampling time is greater than the pollutant flow rate at the previous sampling time. If the pollutant flow rate at the current sampling time is greater than the pollutant flow rate at the previous sampling time, it indicates that a pollution source has released pollutants into the watershed, causing an increase in the pollutant flow rate within the watershed. In this case, S40 is executed. If the pollutant flow rate at the current sampling time is less than or equal to the pollutant flow rate at the previous sampling time, it indicates that a rise in water level during the high-water season has passively reduced the pollutant concentration within the watershed. In this case, S20 is executed. If the water level at the current sampling time is less than or equal to the water level at the previous sampling time, it indicates that there is no passive reduction in the pollutant concentration within the watershed due to a rise in water level during the high-water season, nor is there any situation where a pollution source has released pollutants into the watershed. In this case, S20 is executed. The aim is to improve the accuracy of pollution source identification so that even if the concentration decreases, illegal discharges or accidental leaks can still be identified in high-flow scenarios such as heavy rain and flood discharge, as long as the total amount of pollutants increases.

[0089] Example 2: This example provides a watershed water pollution source tracing system. The watershed water pollution source tracing system is applicable to the watershed water pollution source tracing method described in Example 1. The watershed water pollution source tracing system includes a first construction module, an acquisition module, a judgment module, a collection module, an input module, a second construction module, and an identification module.

[0090] The first construction module is used to construct a water flow velocity prediction model, which is used to predict the change of water flow velocity in the basin with water level height. The acquisition module is used to acquire the pollutant concentration at monitoring points in the basin in real time. The judgment module is used to determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. The acquisition module is used to acquire the water level height in the basin at the current time when the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. The input module is used to input the water level height at the current time into the water flow velocity prediction model to obtain the water flow velocity at the current time. The second construction module is used to construct a potential pollution source area based on the water flow velocity at the current time, the previous sampling time, the current sampling time, and the location of the monitoring point. The identification module is used to identify pollution sources based on the characteristic information of each pollution source in the pollution source area and the pollutant concentration in the basin at the current time.

[0091] The watershed water pollution source tracing system in this embodiment, on the one hand, predicts the current water flow velocity in real time based on the current water level. This aims to significantly reduce migration path deviations caused by using constant flow velocities, thereby improving the accuracy of source tracing results, especially suitable for watersheds with drastic flow velocity changes during flood / dry seasons. On the other hand, it employs a "concentration rise triggering" mechanism. This aims to achieve rapid response only at the initial stage of a pollution event, facilitating emergency handling and reducing the need for continuous, full-time simulations, thus saving computational resources.

[0092] This embodiment also provides a terminal, including a processor and a memory, wherein the memory is used to store processor-executable instructions; wherein the processor is configured to invoke the instructions stored in the memory to execute the watershed water pollution source tracing method as described in Embodiment 1.

[0093] This embodiment also provides a computer-readable storage medium storing computer program instructions, which, when executed by a processor, implement the watershed water pollution source tracing method as described in Embodiment 1.

[0094] Although the invention has been described herein with reference to several illustrative embodiments, it should be understood that many other modifications and implementations can be devised by those skilled in the art, which will fall within the scope and spirit of the principles disclosed herein. More specifically, various variations and modifications can be made to the components and / or layout of the subject matter arrangement within the scope of the disclosure, drawings, and claims. Besides variations and modifications to the components and / or layout, other uses will be apparent to those skilled in the art.

Claims

1. A method for tracing the source of water pollution in a watershed, characterized in that, Includes the following steps: S1, Construct a water flow velocity prediction model, which is used to predict the change of water flow velocity with water level in the basin; S2, real-time acquisition of pollutant concentrations at monitoring points within the watershed; S3, determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time; if yes, proceed to S4; if no, proceed to S2. S4, collects the current water level height within the basin; S5, input the current water level height into the water flow velocity prediction model to obtain the current water flow velocity; S6. Based on the current water flow velocity, the previous sampling time, the current sampling time, and the location of the monitoring point, a potential pollution source area is constructed. The process of constructing potential pollution source areas includes: Calculate the sampling time interval based on the previous sampling time and the current sampling time; Based on the sampling time interval and the current water flow velocity, calculate the maximum distance that the pollutant can travel within the sampling time interval; Based on the maximum drivable distance and the location of the monitoring points, a potential pollution source area is constructed, extending the maximum distance in the opposite direction of the water flow from the monitoring points. S7. Identify pollution sources based on the pollutant inventory information of each pollution source within the pollution source area and the current pollutant concentration in the watershed.

2. The method for tracing the source of water pollution in a watershed according to claim 1, characterized in that, The process of constructing the water flow velocity prediction model includes: Historical hydrological data within the watershed is obtained, including historical water level heights and historical water flow velocities corresponding to those historical water level heights. Historical hydrological data are cleaned to obtain cleaned historical water level heights and historical water flow velocities. A water flow velocity prediction model was obtained by training the model on historical water level heights and historical water flow velocities after cleaning.

3. The method for tracing the source of water pollution in a watershed according to claim 2, characterized in that, The process of cleaning historical hydrological data includes: S101, determine if the historical water level is greater than 0; if yes, execute S102; if no, remove the historical water level and the corresponding historical water flow velocity. S102, determine whether the historical water flow velocity is greater than 0; if yes, retain the historical water flow velocity and the corresponding historical water level; if no, remove the historical water flow velocity and the corresponding historical water level.

4. The method for tracing the source of water pollution in a watershed according to claim 1, characterized in that, When the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time, it also includes: S201, determine whether the water level at the current sampling time is greater than or equal to the water level at the previous sampling time; if yes, execute S4; if no, execute S202. S202, acquire the cross-sectional data and water flow velocity at the previous acquisition time, and the cross-sectional data and water flow velocity at the current time; wherein, the cross-sectional data includes the cross-sectional shape and cross-sectional dimensions; S203, Calculate the pollutant flow rate at the previous collection time based on the cross-sectional data, water flow velocity, and pollutant concentration at the previous collection time; S204. Calculate the pollutant flow rate at the current sampling time based on the cross-sectional data, water flow velocity, and pollutant concentration. S205, determine whether the pollutant flow rate at the current collection time is greater than the pollutant flow rate at the previous collection time; if yes, execute S4; if no, execute S2.

5. The method for tracing the source of water pollution in a watershed according to claim 4, characterized in that, When the pollutant concentration at the current sampling time is less than or equal to the pollutant concentration at the previous sampling time, it also includes: Determine whether the water level at the current sampling time is greater than the water level at the previous sampling time; if yes, execute S202; if no, execute S2.

6. A watershed water pollution source tracing system, characterized in that, The watershed water pollution source tracing system is applicable to the watershed water pollution source tracing method as described in any one of claims 1-5, and the watershed water pollution source tracing system comprises: The first construction module is used to construct a water flow velocity prediction model, which is used to predict the change of water flow velocity with water level in the basin. The acquisition module is used to acquire pollutant concentrations at monitoring points within the watershed in real time. The judgment module is used to determine whether the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time; The data acquisition module is used to acquire the water level height in the watershed at the current sampling time when the pollutant concentration at the current sampling time is greater than the pollutant concentration at the previous sampling time. The input module is used to input the current water level height into the water flow velocity prediction model to obtain the current water flow velocity. The second construction module is used to construct potential pollution source areas based on the current water flow velocity, the previous sampling time, the current sampling time, and the location of the monitoring point; The identification module is used to identify pollution sources based on the characteristic information of each pollution source within the pollution source area and the current pollutant concentration within the watershed.

7. A terminal, characterized in that, include: A processor and a memory, wherein the memory is used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the watershed water pollution source tracing method as described in any one of claims 1-5.

8. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the watershed water pollution source tracing method as described in any one of claims 1-5.

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