Method, device, electronic equipment and storage medium for tracing source of flood season pollution

Abstract

The present disclosure relates to the technical field of water environment monitoring, and discloses a method, device, electronic device, and storage medium for tracing the source of pollution during the flood season. The method includes: obtaining first monitoring data corresponding to the monitoring section, second monitoring data corresponding to the upstream monitoring point, and third monitoring data corresponding to each pollution source; determining the predicted value time series corresponding to each pollution source according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data; determining the monitoring peak value and peak moment corresponding to the target water quality index at the monitoring section according to the first monitoring data; determining the target predicted value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment according to the predicted value time series; determining the target pollution source corresponding to the target water quality index according to the monitoring peak value and the target predicted value corresponding to each pollution source. The disclosed embodiment can quickly and accurately determine the target pollution source that causes the increase of pollution during the flood season in the monitoring section.

Description

Technical Field

[0001] The present disclosure relates to the technical field of water environment monitoring, and in particular to a method, device, electronic equipment, and storage medium for tracing the source of pollution during flood season. Background Art

[0002] By obtaining historical water quality monitoring information and conducting comprehensive big data analysis and processing of historical water quality monitoring information, the accuracy of water environment monitoring can be improved, which is of great significance for preventing and controlling ecological pollution of the water environment and improving the comprehensive quality of the water environment.

[0003] Flood season pollution includes drainage system overflow pollution and surface runoff pollution, and is one of the important issues of urban water pollution. The flood season pollution intensity can be expressed as the ratio of the concentration of the primary pollutant in the monitoring section during the flood season to the water quality target concentration limit, which can reflect the gap between the degree of pollution during the flood season in the monitoring section and the water quality target. Flood season pollution is usually affected by factors such as precipitation, land use and drainage system, and has the characteristics of non-continuity, explosiveness and randomness, which makes it difficult to determine the pollution source that causes the change in the flood season pollution intensity of the monitoring section. Summary of the invention

[0004] In view of this, the present disclosure proposes a method, device, electronic equipment, and a technical solution for tracing the source of flood season pollution.

[0005] According to one aspect of the present disclosure, a method for tracing the source of pollution during flood season is provided, comprising: obtaining first monitoring data corresponding to a monitoring section in a target river channel, second monitoring data corresponding to an upstream monitoring point in the target river channel, and third monitoring data corresponding to each pollution source in the target river channel, wherein the first monitoring data comprises a monitoring value time series of a target water quality index at the monitoring section, the second monitoring data comprises a flow rate time series at the upstream monitoring point and a monitoring value time series of the target water quality index, and the third monitoring data corresponding to any pollution source comprises a flow rate time series at the pollution source and a monitoring value time series of the target water quality index; based on According to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section is determined respectively; according to the first monitoring data, the monitoring peak value and peak moment corresponding to the target water quality index at the monitoring section are determined; according to the predicted value time series corresponding to each pollution source, the target predicted value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment is determined; according to the monitoring peak value and the target predicted value corresponding to each pollution source, the target pollution source corresponding to the target water quality index is determined.

[0006] In a possible implementation, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section is determined respectively according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, including: determining the one-dimensional water quality model corresponding to the target river channel according to the second monitoring data; for any pollution source, determining the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section according to the distance between the pollution source and the monitoring section, the third monitoring data corresponding to the pollution source and the one-dimensional water quality model.

[0007] In a possible implementation, determining the one-dimensional water quality model corresponding to the target river channel based on the second monitoring data includes: determining the average river flow, the average flow velocity and the initial value of the target water quality index corresponding to the target river channel based on the second monitoring data; determining the one-dimensional water quality model based on the average river flow, the average flow velocity, the initial value of the target water quality index and the degradation coefficient corresponding to the target water quality index.

[0008] In a possible implementation, the target pollution source corresponding to the target water quality index is determined based on the monitoring peak value and the target prediction value corresponding to each pollution source, including: for any pollution source, determining the pollution contribution ratio corresponding to the pollution source based on the target prediction value corresponding to the pollution source and the monitoring peak value; determining the target pollution source based on the pollution contribution ratio corresponding to each pollution source.

[0009] In a possible implementation, the method also includes: determining a predicted total value time series based on the predicted value time series corresponding to all pollution sources; determining a prediction error corresponding to the one-dimensional water quality model based on the predicted total value time series and the first monitoring data; when the prediction error does not meet a preset threshold, adjusting the degradation coefficient to determine an adjusted degradation coefficient; adjusting the one-dimensional water quality model based on the adjusted degradation coefficient to determine the adjusted one-dimensional water quality model.

[0010] In one possible implementation, the first monitoring data includes a time series of monitoring values ​​of multiple water quality indicators at the monitoring section; the method also includes: determining the excess multiples corresponding to each water quality indicator at the monitoring section based on the first monitoring data; and determining the target water quality indicator based on the excess multiples corresponding to each water quality indicator at the monitoring section.

[0011] In one possible implementation, the target water quality indicators include: any one of pH, turbidity, dissolved oxygen, permanganate index, total organic carbon, five-day biochemical oxygen demand, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen, organic phosphorus, organic nitrogen, nitrate nitrogen, nitrate nitrogen, phosphate and conductivity.

[0012] According to another aspect of the present disclosure, a device for tracing the source of pollution during flood season is provided, including: a monitoring data acquisition module, used to acquire first monitoring data corresponding to a monitoring section in a target river channel, second monitoring data corresponding to an upstream monitoring point in the target river channel, and third monitoring data corresponding to each pollution source in the target river channel, wherein the first monitoring data includes a monitoring value time series of a target water quality index at the monitoring section, the second monitoring data includes a flow time series at the upstream monitoring point and a monitoring value time series of the target water quality index, and the third monitoring data corresponding to any pollution source includes a flow time series at the pollution source and a monitoring value time series of the target water quality index; a prediction module, used to predict the flow rate of each pollution source according to the relationship between the pollution source and the target water quality index. The distance between the monitoring sections, the second monitoring data, and the third monitoring data corresponding to each pollution source are used to respectively determine the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section; a monitoring peak determination module is used to determine the monitoring peak and peak time corresponding to the target water quality index at the monitoring section according to the first monitoring data; a target predicted value determination module is used to determine the target predicted value of the target water quality index corresponding to each pollution source at the monitoring section at the peak time according to the predicted value time series corresponding to each pollution source; a target pollution source determination module is used to determine the target pollution source corresponding to the target water quality index according to the monitoring peak and the target predicted value corresponding to each pollution source.

[0013] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0014] According to another aspect of the present disclosure, a non-volatile computer-readable storage medium is provided, on which computer program instructions are stored, wherein the computer program instructions implement the above method when executed by a processor.

[0015] Through the disclosed embodiment, the first monitoring data corresponding to the monitoring section in the target river channel, the second monitoring data corresponding to the upstream monitoring point in the target river channel, and the third monitoring data corresponding to each pollution source in the target river channel can be obtained, wherein the first monitoring data includes the monitoring value time series of the target water quality index at the monitoring section, the second monitoring data represents the flow time series and the monitoring value time series of the target water quality index at the upstream monitoring point, and the third monitoring data corresponding to any pollution source includes the flow time series and the monitoring value time series of the target water quality index at the pollution source, and according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section is determined respectively, so as to realize the simulation tracking of the target water quality index corresponding to each pollution source. According to the first monitoring data, the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section can be determined, so as to realize the peak supervision of the target water quality index. Based on the monitoring peak value and the target prediction value corresponding to each pollution source, the target pollution source corresponding to the target pollutant can be determined, thereby achieving peak tracing of the target water quality indicators at the monitoring section, improving the accuracy of flood season pollution tracing, and thus improving the effect of flood season pollution control.

[0016] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0018] Figure 1 A flow chart of a method for tracing the source of flood season pollution according to an embodiment of the present disclosure is shown.

[0019] Figure 2 A schematic diagram showing a time series of monitoring values ​​of a target water quality indicator at a monitoring section according to an embodiment of the present disclosure.

[0020] Figure 3 A schematic diagram showing a time series of monitoring values ​​of target water quality indicators corresponding to different pollution sources according to an embodiment of the present disclosure.

[0021] Figure 4 A schematic diagram showing a time series of predicted values ​​corresponding to different pollution sources according to an embodiment of the present disclosure.

[0022] Figure 5 A block diagram of a device for tracing the source of flood season pollution according to an embodiment of the present disclosure is shown.

[0023] Figure 6A block diagram of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0024] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0025] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0026] The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the term "at least one" herein represents any combination of at least two of any one or more of a plurality of. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set consisting of A, B, and C.

[0027] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, methods, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0028] Pollution intensity during flood season is the main technical indicator for measuring pollution during flood season. It can express the ratio of the concentration of the main pollutants during flood season in the monitoring section to the target concentration limit of water quality. It can reflect the gap between the pollution level during flood season in the monitoring section and the water quality target, which is conducive to accurately identifying the situation where the water environment quality is good in normal times and the pollutant concentration increases sharply during flood season.

[0029] Pollution during the flood season is usually affected by factors such as precipitation, land use, and drainage systems. It has the characteristics of non-continuity, explosiveness, and randomness, which makes it difficult to determine the pollution source that causes the change in the pollution intensity during the flood season in the monitoring section. Therefore, it is crucial to clarify the monitoring peak concentration and corresponding monitoring peak time of various pollutant indicators in the monitoring section, and accurately trace the target pollution source that causes abnormal monitoring peak concentration of each pollutant based on the pollution intensity during the flood season, in order to control the pollution during the flood season.

[0030] The flood season pollution tracing method provided by the present disclosure can be applied to the flood season pollution tracing scenario to accurately determine the target pollution source causing the abnormal peak concentration of pollutants at the monitoring section. The flood season pollution tracing method provided by the embodiment of the present disclosure is described in detail below.

[0031] Figure 1 A flow chart of a method for tracing the source of flood season pollution according to an embodiment of the present disclosure is shown. Figure 1 As shown, the method for tracing the source of pollution during the flood season can be executed by electronic devices such as terminal devices or servers. The terminal device can be a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. The method for tracing the source of pollution during the flood season can be implemented by a processor calling computer-readable instructions stored in a memory. Alternatively, the method for tracing the source of pollution during the flood season can be executed by a server. Figure 1 As shown in the figure, the methods for tracing the source of pollution during the flood season include:

[0032] In step S11, the first monitoring data corresponding to the monitoring section in the target river, the second monitoring data corresponding to the upstream monitoring point in the target river, and the third monitoring data corresponding to each pollution source in the target river are obtained, wherein the first monitoring data include the monitoring value time series of the target water quality index at the monitoring section, the second monitoring data include the flow time series and the monitoring value time series of the target water quality index at the upstream monitoring point, and the third monitoring data corresponding to any pollution source include the flow time series and the monitoring value time series of the target water quality index at the pollution source.

[0033] The target river channel here may refer to a river channel that needs to be monitored, analyzed and controlled for pollution during the flood season, for example, part of the Songhua River, etc. It can be flexibly set according to actual usage needs, and the present disclosure does not make specific limitations on this.

[0034] The monitoring section can be represented as the entire profile set in the target river channel perpendicular to the direction of water flow for measuring or collecting water quality samples. The monitoring section is usually a section in the target river channel that is affected by human activities and is included in the monitoring of pollution intensity during the flood season. The impact of human activities here may include the impact of pollutants discharged by human activities such as urban and rural, agricultural and industrial activities within the catchment area of ​​the section on the target river channel. The specific location of the monitoring section can be flexibly set according to actual usage needs. For example, it can be laid out based on existing routine monitoring sections at the national, provincial, municipal and county levels, or a monitoring section can be set downstream of the urban and rural non-point source of the target river channel, or a monitoring section can be set at the inlet (reservoir) and outflow of lakes (reservoirs), etc. The present disclosure does not make specific limitations on this.

[0035] By monitoring the water quality of the monitoring section in the target river, the first monitoring data corresponding to the monitoring section can be obtained. The first monitoring data may include a time series of monitoring values ​​corresponding to the target water quality index at the monitoring section. The time series of monitoring values ​​corresponding to the target water quality index may represent the monitoring values ​​corresponding to the target water quality index at the monitoring section at each sampling time within the preset monitoring time. Among them, the specific type of the target water quality index can be flexibly set according to the actual use requirements. For example, the monitoring items required to be controlled in the national or local surface water environmental quality standards can be selected, or they can be set based on the common pollutants of urban and rural non-point sources in the target river. The present disclosure does not make specific restrictions on this. The specific value of the monitoring time can be flexibly set according to the actual use requirements. For example, the duration of precipitation in the area where the target river is located can be determined based on the meteorological data of the area where the target river is located, and the duration of precipitation is determined as the monitoring time, etc. The present disclosure does not make specific restrictions on this. The first monitoring data obtained above can be obtained automatically or by manual input.

[0036] In one possible implementation, the target water quality indicators include: any one of pH, turbidity, dissolved oxygen, permanganate index, total organic carbon, five-day biochemical oxygen demand, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen, organic phosphorus, organic nitrogen, nitrate nitrogen, nitrate nitrogen, phosphate and conductivity.

[0037] In one possible implementation, the target water quality indicators may also include: any one of iron, manganese, copper, zinc, molybdenum, selenium, arsenic, mercury, cadmium, chromium, lead, beryllium, nickel, iodide, cyanide, fluoride, sulfide, volatile phenol, petroleum, anionic surfactant, and fecal coliform bacteria.

[0038] Specifically, pH can indicate the strength of the acidity or alkalinity of the aqueous solution in the target river, and can also be called the hydrogen ion concentration index or pH value.

[0039] Turbidity can indicate the degree of obstruction caused by the aqueous solution of the target river to the passage of light, which can include the scattering of light by suspended matter in the aqueous solution of the target river and the absorption of light by solute molecules, and depends on the content, size, shape and refractive index of the suspended matter in the aqueous solution of the target river. The turbidity can reflect the turbidity of the target river; the higher the turbidity, the more turbid the target river.

[0040] Dissolved oxygen can indicate the content of molecular oxygen dissolved in the aqueous solution of the target river, which depends on the partial pressure of oxygen in the air around the target river, the temperature of the target river, etc. Dissolved oxygen can reflect the self-purification capacity of the water body of the target river.

[0041] The permanganate index can indicate the amount of potassium permanganate consumed when treating the aqueous solution of the target river with potassium permanganate as an oxidant in an acidic or alkaline medium. The permanganate index can reflect the pollution degree of organic and inorganic oxidizable substances in the target river.

[0042] Total organic carbon can indicate the total amount of carbon contained in dissolved and suspended organic matter in the aqueous solution of the target river, and can be used as a basis for evaluating the degree of organic pollution in the target river water.

[0043] The five-day biochemical oxygen demand indicates the amount of dissolved oxygen consumed in the biochemical reaction of microorganisms decomposing biodegradable organic matter in the aqueous solution of the target river within five days. The five-day biochemical oxygen demand can reflect the content of oxygen-demanding pollutants in the target river.

[0044] Chemical oxygen demand can be expressed as the amount of reducing substances that need to be oxidized in the aqueous solution of the target river under certain conditions by chemical methods. Through chemical oxygen demand, the content of organic pollution in the target river can be reflected.

[0045] Total phosphorus can indicate the total content of phosphorus in the aqueous solution of the target river; total nitrogen can indicate the total content of nitrogen in the aqueous solution of the target river; ammonia nitrogen can indicate the nitrogen in the aqueous solution of the target river in the form of free ammonia (NH3) and ammonium ions (NH4+). The total phosphorus, total nitrogen and ammonia nitrogen can reflect the eutrophication degree of the target river water body.

[0046] Conductivity can indicate the ability of the aqueous solution in the target river to conduct electric current. Through conductivity, the total concentration of charged substances in the water body of the target river can be reflected.

[0047] Organic phosphorus can indicate the content of organic compounds containing carbon-phosphorus bonds in the aqueous solution of the target river, and can reflect the pollution degree of organic phosphorus compounds, such as organic phosphorus pesticides, in the target river.

[0048] Organic nitrogen can represent the total content of nitrogen-containing substances combined with carbon in the aqueous solution of the target river. The nitrogen-containing substances here can include proteins, peptones, amino acids, nucleic acids, urea, and a large number of organic nitrogen compounds with negative trivalent nitrogen synthesized, etc., which are not specifically limited in this disclosure. The content of organic nitrogen can reflect the degree of eutrophication of the target river water body.

[0049] Nitrate nitrogen can represent the total content of nitrate nitrogen and nitrite nitrogen in the aqueous solution of the target river, and can reflect the degree of pollution of nitrogen-containing compounds in the target river water body and its self-purification status.

[0050] Phosphate can indicate the total content of phosphate in the aqueous solution of the target river, and can reflect the pollution of the target river caused by industrial production, daily life and other activities near the target river.

[0051] Iron, manganese, copper, zinc, molybdenum, selenium, arsenic, mercury, cadmium, chromium, lead, beryllium and nickel can reflect the pollution of the target river caused by industrial production, daily life and other activities near the target river.

[0052] Iodide can represent the total content of iodine and its compounds in the aqueous solution of the target river.

[0053] Cyanide can indicate the total content of cyanide and its compounds in the aqueous solution of the target river; fluoride can indicate the total content of fluorine and its compounds in the aqueous solution of the target river; sulfide can indicate the total content of sulfur and its compounds in the aqueous solution of the target river. Cyanide, fluoride and sulfide can reflect the pollution of the target river caused by industrial production, daily life and other activities near the target river.

[0054] Volatile phenols, petroleum, and anionic surfactants can respectively represent the content of corresponding chemical industry products in the aqueous solution of the target river, and can reflect the pollution of the target river by industrial production near the target river, as well as the situation of illegal discharge.

[0055] Fecal coliform group can indicate the total content of coliform group in the aqueous solution of the target river. The coliform group here can indicate aerobic and facultative anaerobic Gram-negative non-spore-forming bacilli that can decompose lactose to produce acid and gas at 37°C, including Escherichia coli, Citrobacter, Klebsiella aerogenes and Enterobacter cloacae. Fecal coliform group can reflect the fecal pollution of the water body of the target river.

[0056] Figure 2 A schematic diagram showing a time series of monitoring values ​​of target water quality indicators at a monitoring section according to an embodiment of the present disclosure. Figure 2 As shown, the target water quality indicator is chemical oxygen demand, and the monitoring time is the time period from 9:00 to 17:20. The first monitoring data corresponding to the monitoring section includes a time series of monitoring values ​​of chemical oxygen demand, which indicates the monitoring value of chemical oxygen demand at each sampling time in the time period from 9:00 to 17:20.

[0057] An upstream monitoring point can refer to any monitoring location located upstream of all pollution sources in a certain area when judging the pollution level of a target river in the area, which can reflect the background value of the water environment in the area. Upstream monitoring points are usually monitoring locations that are less affected by human activities and are not included in the monitoring of pollution intensity during the flood season. The specific location of the upstream monitoring point can be flexibly set according to actual usage requirements. For example, an upstream monitoring point can be set at the source of a river, etc. This disclosure does not make specific limitations on this.

[0058] In one example, the upstream monitoring point may be any location within the preset range upstream of the first pollution source in the target river channel where there are no facilities (e.g., other pollution sources, drainage facilities, hydrological stations, water quality monitoring stations, etc.) that may affect the target water quality index and flow in the target river channel. The specific value of the preset range here can be flexibly set according to actual usage requirements. For example, the preset range can be set to a radius of 3 kilometers, and this disclosure does not make specific limitations on this.

[0059] By performing water quality monitoring and flow monitoring on the upstream monitoring point, the second monitoring data corresponding to the upstream monitoring point can be determined. The second monitoring data may include a flow time series at the upstream monitoring point and a monitoring value time series of the target water quality index. The flow time series may represent the average water flow of the target river at the upstream monitoring point at each sampling time within the preset monitoring time.

[0060] The pollution sources in the target river can include rainwater outlets, overflow outlets and other flood season pollution sources between the upstream monitoring point and the monitoring section of the target river. The specific location and number of pollution sources depend on the actual situation of the target river, and this disclosure does not make specific limitations on this.

[0061] By monitoring the water quality and discharge volume of each pollution source respectively, the third monitoring data corresponding to each pollution source can be determined. For any pollution source, the third monitoring data corresponding to the pollution source may include: the flow time series at the pollution source and the monitoring value time series of the target water quality index. Among them, the flow time series can represent the flow of sewage discharged by the pollution source to the target river at each sampling time within the preset monitoring time.

[0062] In one example, there are four different pollution sources between the upstream monitoring point and the monitoring section of the target river, namely, pollution source P1, pollution source P2, pollution source P3 and pollution source P4, and the target water quality indicator is chemical oxygen demand.

[0063] Figure 3 A schematic diagram showing the time series of monitoring values ​​of target water quality indicators corresponding to different pollution sources according to an embodiment of the present disclosure. Figure 3 As shown in the figure, the target river includes four pollution sources, namely P1, P2, P3 and P4, the target water quality indicator is chemical oxygen demand, and the monitoring time is from 9:00 to 17:30. Figure 3 As shown, the black solid line marked with diamonds is the monitoring value time series of the chemical oxygen demand corresponding to the pollution source P1; the black solid line marked with dots is the monitoring value time series of the chemical oxygen demand corresponding to the pollution source P2; the unmarked black solid line is the monitoring value time series of the chemical oxygen demand corresponding to the pollution source P3; the black dotted line is the monitoring value time series of the chemical oxygen demand corresponding to the pollution source P4.

[0064] Water flow is monitored at the upstream monitoring points in the target river, and the discharge is monitored at each pollution source. For the specific method of obtaining the flow time series at the upstream monitoring points and the flow time series at each pollution source, reference can be made to the implementation methods in the relevant technology, and the present disclosure does not make specific limitations on this.

[0065] The specific method of conducting water quality monitoring at the monitoring section, upstream monitoring point and each pollution source in the target river channel can refer to the implementation method in the relevant technology, and the present disclosure does not make specific limitations on this.

[0066] In one example, the monitoring section, upstream monitoring point and each pollution source can be sampled respectively by a quantum dot spectral probe to obtain a time series of monitoring values ​​of the target water quality index. Compared with the method commonly used in the prior art of conducting water quality analysis in the laboratory after manual sampling, the use of a quantum dot spectral probe can achieve in-situ, online, high-frequency, and real-time sampling and analysis. The sampling frequency of the quantum dot spectral probe can be flexibly set according to actual usage requirements. For example, it can be set to 3-60 min / time, 5-30 min / time, 8-20 min / time, 10-15 min / time, etc., and the embodiments of the present disclosure do not specifically limit this. Preferably, the sampling frequency of the quantum dot spectral probe can be set to 10-15 min / time.

[0067] Through the above process, real-time water quality monitoring of the monitoring points, monitoring sections and each pollution source in the upper and middle reaches of the target river can be achieved, so that when flood overflow pollution occurs, the flood overflow pollution can be traced in time.

[0068] In step S12, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section is determined respectively according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source.

[0069] According to the distance between each pollution source and the monitoring section, the second monitoring data corresponding to the upstream monitoring point, and the third monitoring data corresponding to each pollution source, the impact of the target water quality index corresponding to each pollution source on the monitoring section can be predicted respectively, and the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section can be determined. The predicted value time series corresponding to any pollution source can represent the predicted value of the target water quality index corresponding to this part of the sewage when the sewage discharged by the pollution source is transmitted to the monitoring section within the preset monitoring time.

[0070] Figure 4 A schematic diagram showing the predicted value time series corresponding to different pollution sources according to an embodiment of the present disclosure. Figure 4As shown, the black solid line marked with diamonds is the predicted value time series corresponding to pollution source P1; the black solid line marked with dots is the predicted value time series corresponding to pollution source P2; the unmarked black solid line is the predicted value time series corresponding to pollution source P3; and the black dotted line is the predicted value time series corresponding to pollution source P4.

[0071] The following text will describe in detail the process of determining the predicted value time series of the target water quality indicator corresponding to each pollution source at the monitoring section based on the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, in combination with the possible implementation methods of the present disclosure. It will not be elaborated here.

[0072] Through the above process, the predicted value time series of the target water quality index corresponding to any pollution source at the monitoring section can be determined, reflecting the predicted value of the target water quality index in the sewage discharged by the pollution source and transmitted to the monitoring section; according to the predicted value time series corresponding to each pollution source, the pollution contribution of each pollution source to the monitoring section can be analyzed in real time.

[0073] In step S13, the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section are determined according to the first monitoring data.

[0074] According to the first monitoring data corresponding to the monitoring section, the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section can be determined. Specifically, the monitoring peak value corresponding to the target water quality index at the monitoring section can represent the maximum value of the monitoring value of the target water quality index at the monitoring section during the monitoring time.

[0075] With the above Figure 2 For example, Figure 2 As shown, during the time period from 9:00 to 17:30, the corresponding monitoring peak value of chemical oxygen demand at the monitoring section was 45.6 mg / L, and the peak time was 15:00.

[0076] In step S14, based on the predicted value time series corresponding to each pollution source, the target predicted value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment is determined.

[0077] For any pollution source, the target predicted value of the target water quality index corresponding to the pollution source at the monitoring section at the peak moment can be determined based on the predicted value time series corresponding to the pollution source. The target predicted value can represent the impact of the target water quality index corresponding to the pollution source on the monitoring section at the peak moment.

[0078] For example, there are four different pollution sources between the upstream monitoring point and the monitoring section of the target river, namely pollution source P1, pollution source P2, pollution source P3 and pollution source P4, and the target water quality indicator is chemical oxygen demand. Figure 2 As shown in Figure 1, the peak time of chemical oxygen demand in the monitoring section is 15:00. Figure 3 As shown, at the peak time of 15:00, it can be determined that the target prediction value corresponding to pollution source P1 is 34.5 mg / L; the target prediction value corresponding to pollution source P2 is 32.2 mg / L; the target prediction value corresponding to pollution source P3 is 41.3 mg / L; and the target prediction value corresponding to pollution source P4 is 28.64 mg / L.

[0079] In step S15, the target pollution source corresponding to the target water quality index is determined according to the monitoring peak value and the target prediction value corresponding to each pollution source.

[0080] Through the target prediction value corresponding to each pollution source and the monitoring peak value corresponding to the monitoring section, the pollution impact of each pollution source on the monitoring section can be analyzed, and among multiple pollution sources, the target pollutant that causes the monitoring peak value of the target water quality indicator at the monitoring section can be determined.

[0081] The process of determining the target pollution source corresponding to the target water quality index based on the monitoring peak value and the target prediction value corresponding to each pollution source will be described in detail later in combination with possible implementation methods of the present disclosure, which will not be elaborated here.

[0082] Through the disclosed embodiment, the first monitoring data corresponding to the monitoring section in the target river channel, the second monitoring data corresponding to the upstream monitoring point in the target river channel, and the third monitoring data corresponding to each pollution source in the target river channel can be obtained, wherein the first monitoring data includes the monitoring value time series of the target water quality index at the monitoring section, the second monitoring data represents the flow time series at the upstream monitoring point and the monitoring value time series of the target water quality index, and the third monitoring data corresponding to any pollution source includes the flow time series at the pollution source and the monitoring value time series of the target water quality index. According to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section can be determined respectively, without complex secondary calculations or data analysis, and the simulation tracking of the target water quality index corresponding to each pollution source can be directly realized. According to the first monitoring data, the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section can be determined to realize the peak supervision of the target water quality index. According to the monitoring peak value and the target predicted value corresponding to each pollution source, the target pollution source corresponding to the target pollutant can be determined simply and quickly. Compared with other water pollution source tracing methods in the prior art, the flood season pollution source tracing method of the disclosed embodiment can use the first monitoring data, the second monitoring data and the third monitoring data to obtain the predicted values ​​of the target water quality index corresponding to each pollution source at different times in the monitoring section. By using fewer variables, the calculation process can be made faster and more efficient. Moreover, according to the monitoring peak value, the peak time and the predicted value corresponding to each pollution source at different times corresponding to the target water quality index at the monitoring section, the target predicted value of the target water quality index corresponding to each pollution source at the peak time can be determined, thereby achieving target pollution source tracing, and improving the accuracy of flood season pollution source tracing, thereby improving the effect of flood season pollution control.

[0083] In one possible implementation, the first monitoring data includes a time series of monitoring values ​​of multiple water quality indicators at a monitoring section; the method also includes: determining the excess multiples corresponding to each water quality indicator at the monitoring section based on the first monitoring data; and determining the target water quality indicator based on the excess multiples corresponding to each water quality indicator at the monitoring section.

[0084] There may be multiple pollutants in the target river channel that are affected by surface runoff and overflow of the drainage system during the flood season, and their concentrations may increase explosively during the flood season. Therefore, the first monitoring data may include a time series of monitoring values ​​of multiple different water quality indicators at the monitoring section. The multiple water quality indicators here may include at least one of pH, turbidity, dissolved oxygen, permanganate index, total organic carbon, five-day biochemical oxygen demand, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen and conductivity. According to the time series of the monitoring values ​​of each water quality indicator, the target water quality indicator can be determined from the multiple water quality indicators.

[0085] For any water quality indicator, the monitoring peak value of the water quality indicator at the monitoring section can be determined. When the monitoring peak value of the water quality indicator at the monitoring section exceeds the threshold value corresponding to the water quality indicator, the excess multiple corresponding to the water quality indicator can be calculated to evaluate the severity of pollution corresponding to the water quality indicator in the target river. Specifically, the excess multiple corresponding to the water quality indicator is equal to the ratio between the monitoring peak value of the water quality indicator at the monitoring section and the threshold value corresponding to the water quality indicator.

[0086] The specific value of the threshold corresponding to any water quality indicator depends on the location of the target river and the specific type of the water quality indicator. It can be set with reference to the water quality targets in the national or local surface water environmental quality standards. This disclosure does not make any specific limitations on this.

[0087] By comparing the excess multiples corresponding to each water quality indicator, the water quality indicator with the largest excess multiple can be determined as the target water quality indicator at the monitoring section, and the pollution source of the target water quality indicator can be traced.

[0088] Through the above process, the target water quality index can be flexibly selected from the various water quality indexes in the target river according to actual usage needs, thereby increasing the flexibility and accuracy of pollution source tracing during the flood season.

[0089] In one possible implementation, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section is determined based on the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, including: determining the one-dimensional water quality model corresponding to the target river channel based on the second monitoring data; for any pollution source, determining the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section based on the distance between the pollution source and the monitoring section, the third monitoring data corresponding to the pollution source, and the one-dimensional water quality model.

[0090] Since the upstream monitoring point is usually a monitoring location that is less affected by human activities, the second monitoring data corresponding to the upstream monitoring point can reflect the water environment background value of the target river. According to the second monitoring data, the one-dimensional water quality model corresponding to the target river can be determined. The one-dimensional water quality model corresponding to the target river can be used to determine the changes in the monitoring values ​​of the target water quality indicators in the sewage discharged by any pollution source between the upstream monitoring point and the monitoring section when it is transmitted in the target river.

[0091] For any pollution source, the distance between the pollution source and the monitoring section and the third monitoring data corresponding to the pollution source can be input into the one-dimensional water quality model corresponding to the target river channel to determine the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section.

[0092] In one possible implementation, a one-dimensional water quality model corresponding to the target river is determined based on the second monitoring data, including: determining the average river flow, average flow velocity and initial value of the target water quality index corresponding to the target river based on the second monitoring data; determining the one-dimensional water quality model based on the average river flow, average flow velocity, initial value of the target water quality index and degradation coefficient corresponding to the target water quality index.

[0093] According to the second monitoring data corresponding to the upstream monitoring point, the average river flow, the average flow velocity and the initial value of the target water quality index corresponding to the target river can be determined.

[0094] According to the average river flow, average flow velocity, initial value of target water quality index and degradation coefficient corresponding to target water quality index, a one-dimensional water quality model is determined. Specifically, the one-dimensional water quality model corresponding to the target river can be expressed as formula (1) and (2):

[0095]

[0096] in, It represents the time series of mixed values ​​when the target water quality index corresponding to any pollution source P enters the target river; represents the flow time series corresponding to the pollution source P in the third monitoring data; represents the monitoring value time series of the target water quality indicator corresponding to the pollution source P in the third monitoring data; Indicates the average river flow corresponding to the target river (which can be determined based on the flow time series at the upstream monitoring point in the second monitoring data); represents the initial value of the target water quality index in the target river (which can be determined according to the monitoring value time series of the target water quality index at the upstream monitoring point in the second monitoring data), It represents the predicted value time series of the target water quality index corresponding to the pollution source P at the monitoring section; Indicates the river distance between the pollution source P and the monitoring section; Indicates the average flow velocity of the target river; It represents the degradation coefficient, which can reflect the attenuation rate of the target water quality index due to the comprehensive effects of physical, chemical and biological factors when it is transmitted in the target river. The specific value of depends on the specific type of the target water quality indicator, which can be determined by referring to the implementation methods in the relevant technology, and the present disclosure does not make any specific limitation on this.

[0097] The one-dimensional water quality model determined by the above process has a simple structure and a fast response in the operation process, which is easy for users to learn and apply, and has the function of being able to quickly determine the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section. In the case where flood season pollution has a high degree of explosiveness and randomness, tracing the source of pollution based on the one-dimensional water quality model of the embodiment of the present disclosure has a high timeliness, and can quickly trace the source of pollution after the flood season pollution occurs, thereby improving the speed of flood season pollution control.

[0098] After determining the one-dimensional water quality model corresponding to the target river, the distance between any pollution source and the monitoring section, as well as the third monitoring data corresponding to the pollution source, can be input into the one-dimensional water quality model to determine the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section.

[0099] Take the above target river channel upstream monitoring point and monitoring section as an example, there are 4 different pollution sources, namely pollution source P1, pollution source P2, pollution source P3 and pollution source P4, and the target water quality indicator is chemical oxygen demand. The river channel distance between pollution source P1 and monitoring section The river distance between the pollution source P2 and the monitoring section is 2.4 km. The river distance between the pollution source P3 and the monitoring section is 1.8 km. The river distance between the pollution source P4 and the monitoring section is 1.2 km. The target pollutant is chemical oxygen demand. According to the second monitoring data corresponding to the upstream monitoring point, the average river flow corresponding to the target river can be determined. 2m 3 / s, average flow rate is 1m / s.

[0100] The river distance between the pollution source P1 and the monitoring section The third monitoring data corresponding to the pollution source P1 is input into the one-dimensional water quality model corresponding to the target river, so as to determine the predicted value time series of the chemical oxygen demand corresponding to the pollution source P1 at the monitoring section.

[0101] For any pollution source, through the one-dimensional water quality model corresponding to the target river channel, the distance between the pollution source and the monitoring section, and the third monitoring data corresponding to the pollution source, the target water quality index corresponding to the pollution source can be simulated, and the spatiotemporal distribution state of the target water quality index corresponding to the pollution source in the process of being transmitted from the pollution source to the monitoring section can be simulated, and the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section can be determined, so as to facilitate pollution tracing and determination of the target pollution source corresponding to the target water quality index when the monitoring value of the target water quality index at the monitoring section is abnormal.

[0102] In one possible implementation, the target pollution source corresponding to the target water quality index is determined based on the monitoring peak value and the target prediction value corresponding to each pollution source, including: for any pollution source, the pollution contribution ratio corresponding to the pollution source is determined based on the target prediction value and the monitoring peak value corresponding to the pollution source; the target pollution source is determined based on the pollution contribution ratio corresponding to each pollution source.

[0103] For example, there are four different pollution sources between the upstream monitoring point and the monitoring section of the target river, namely pollution source P1, pollution source P2, pollution source P3 and pollution source P4, and the target water quality indicator is chemical oxygen demand. Figure 2 As shown, the monitoring peak concentration of chemical oxygen demand at the monitoring section is 45.6 mg / L, and the corresponding monitoring peak time is 15:00.

[0104] like Figure 4 As shown, at 15:00, the target predicted value of chemical oxygen demand corresponding to pollution source P1 at the monitoring section is 34.5 mg / L; the target predicted value of chemical oxygen demand corresponding to pollution source P2 at the monitoring section is 32.2 mg / L; the target predicted value of chemical oxygen demand corresponding to pollution source P3 at the monitoring section is 41.3 mg / L; the target predicted value of chemical oxygen demand corresponding to pollution source P4 at the monitoring section is 28.64 mg / L.

[0105] According to the above data, it can be determined that the pollution contribution ratio corresponding to pollution source P1 is 0.76; the pollution contribution ratio corresponding to pollution source P2 is 0.71; the pollution contribution ratio corresponding to pollution source P3 is 0.91; and the pollution contribution ratio corresponding to pollution source P4 is 0.63. Since the pollution contribution ratio corresponding to pollution source P3 is the largest, the target pollutants discharged by pollution source P3 have the greatest impact on the monitoring peak of the target water quality index at the monitoring section. It can be determined that pollution source P3 is the target pollution source corresponding to the target water quality index.

[0106] In a possible implementation, the target prediction values ​​corresponding to each pollution source may be directly compared, and the pollution source with the largest target prediction value may be determined as the target pollution source corresponding to the target water quality indicator.

[0107] Through the above process, the pollution contribution ratio of each pollution source to the monitoring section can be determined based on the target predicted value and monitoring peak value of the target water quality index discharged by each pollution source at the monitoring section at the peak moment. The impact of the target water quality index corresponding to each pollution source on the monitoring peak value of the target water quality index at the monitoring section can be measured in the form of quantitative data, providing a basis for tracing the source of pollution during the flood season, and determining the target pollution source corresponding to the target water quality index according to the pollution contribution ratio.

[0108] In a possible implementation, the method also includes: determining a predicted total value time series based on the predicted value time series corresponding to all pollution sources; determining a prediction error corresponding to a one-dimensional water quality model based on the predicted total value time series and the first monitoring data; when the prediction error does not meet a preset threshold, adjusting the degradation coefficient to determine an adjusted degradation coefficient; adjusting the one-dimensional water quality model based on the adjusted degradation coefficient to determine the adjusted one-dimensional water quality model.

[0109] When constructing a one-dimensional water quality model corresponding to the target river, the degradation coefficient may be a theoretical value determined based on the target water quality index, or a measured value of the degradation coefficient of the target river at a specific time. In actual application, the degradation coefficient may change with changes in the physical, chemical or biological environment in the target river, resulting in prediction errors in the one-dimensional water quality model.

[0110] Therefore, in order to reduce the prediction error of the one-dimensional water quality model, after determining the predicted value time series corresponding to each pollution source, the predicted value time series corresponding to all pollution sources can be fitted to obtain the predicted total value time series at the monitoring section. The predicted total value time series can represent the predicted value of the target water quality index at the monitoring section due to the combined effect of multiple pollution sources within the preset monitoring time. Among them, the specific method for determining the predicted total value time series can refer to the implementation method in the relevant technology. For example, the predicted values ​​of all pollution sources at the same time can be summed up and determined, etc., and the present disclosure does not make specific limitations on this.

[0111] At each sampling moment, the difference between the predicted total value time series and the first monitoring data can be calculated as the prediction error corresponding to the one-dimensional water quality model. When the prediction error does not meet the preset threshold, the degradation coefficient can be adjusted to determine the adjusted degradation coefficient; according to the adjusted degradation coefficient, the one-dimensional water quality model can be adjusted to determine the adjusted one-dimensional water quality model. Among them, the specific value of the preset threshold can be flexibly set according to actual usage requirements, and the present disclosure does not make specific limitations on this.

[0112] Through the above process, the predicted value time series corresponding to each pollution source and the first monitoring data corresponding to the monitoring section can be used to adaptively adjust the degradation coefficient, which can reduce the error of the one-dimensional water quality model and improve the accuracy of the predicted value time series corresponding to each pollution source, thereby increasing the accuracy of pollution tracing during the flood season.

[0113] Through the disclosed embodiment, the first monitoring data corresponding to the monitoring section in the target river channel, the second monitoring data corresponding to the upstream monitoring point in the target river channel, and the third monitoring data corresponding to each pollution source in the target river channel can be obtained, wherein the first monitoring data includes the monitoring value time series of the target water quality index at the monitoring section, the second monitoring data represents the flow time series at the upstream monitoring point and the monitoring value time series of the target water quality index, and the third monitoring data corresponding to any pollution source includes the flow time series at the pollution source and the monitoring value time series of the target water quality index. According to the second monitoring data, the one-dimensional water quality model corresponding to the target river channel can be determined; for any pollution source, according to the distance between the pollution source and the monitoring section, the third monitoring data corresponding to the pollution source and the one-dimensional water quality model, the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section can be determined. Since the one-dimensional water quality model has the characteristics of simple structure and rapid response of the calculation process, the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section can be determined by the one-dimensional water quality model, and the simulation tracking of the target water quality index corresponding to each pollution source can be quickly realized. According to the first monitoring data, the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section can be determined to achieve peak supervision of the target water quality index. According to the monitoring peak value and the target prediction value corresponding to each pollution source, the target pollution source corresponding to the target pollutant can be determined. Compared with other water quality pollution source tracing methods in the prior art, the source tracing method of flood season pollution in the disclosed embodiment can use the first monitoring data, the second monitoring data and the third monitoring data to obtain the predicted value of the target water quality index corresponding to each pollution source at different times at the monitoring section. By using fewer variables, the calculation process can be made faster and more efficient, and according to the monitoring peak value corresponding to the target water quality index at the monitoring section, the peak time and the predicted value corresponding to each pollution source at different times, the target predicted value of the target water quality index corresponding to each pollution source at the peak time can be determined, and the target pollution source can be traced, which can improve the accuracy of flood season pollution source tracing, thereby improving the control effect of flood season pollution.

[0114] In one possible implementation, the first monitoring data also includes a time series of monitoring values ​​of multiple water quality indicators at the monitoring section, and the third monitoring data corresponding to any pollution source also includes a time series of monitoring values ​​of multiple water quality indicators at the pollution source; the method also includes: for any water quality indicator, based on the time series of monitoring values ​​of the water quality indicator at the monitoring section, the second monitoring data, and the time series of monitoring values ​​of the water quality indicator at each pollution source, determining the pollution source corresponding to the water quality indicator; based on the target water quality indicator and the pollution source corresponding to each water quality indicator, determining the target pollution source corresponding to the target water quality indicator.

[0115] Among them, the specific method of determining the pollution source corresponding to each water quality indicator can refer to the aforementioned method of tracing the source of pollution during the flood season.

[0116] Through the above process, the pollution source corresponding to any water quality indicator that exceeds the pollution standard at the monitoring section can be determined, which can increase the flexibility of tracing the source of pollution during the flood season.

[0117] It can be understood that the above-mentioned various method embodiments mentioned in the present disclosure can be combined with each other to form a combined embodiment without violating the principle logic. Due to space limitations, the present disclosure will not repeat them. It can be understood by those skilled in the art that in the above-mentioned method of the specific implementation method, the specific execution order of each step should be determined according to its function and possible internal logic.

[0118] In addition, the present disclosure also provides a flood season pollution tracing device, electronic device, computer-readable storage medium, and program, all of which can be used to implement any flood season pollution tracing method provided by the present disclosure. The corresponding technical solutions and descriptions are referred to the corresponding records in the method part and will not be repeated here.

[0119] Figure 5 FIG. 1 is a block diagram of a device for tracing the source of flood season pollution according to an embodiment of the present disclosure. Figure 5 As shown, the device 500 includes:

[0120] The monitoring data acquisition module 501 is used to obtain the first monitoring data corresponding to the monitoring section in the target river, the second monitoring data corresponding to the upstream monitoring point in the target river, and the third monitoring data corresponding to each pollution source in the target river, wherein the first monitoring data includes the monitoring value time series of the target water quality index at the monitoring section, the second monitoring data includes the flow time series and the monitoring value time series of the target water quality index at the upstream monitoring point, and the third monitoring data corresponding to any pollution source includes the flow time series and the monitoring value time series of the target water quality index at the pollution source.

[0121] The prediction module 502 is used to determine the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source.

[0122] The monitoring peak value determination module 503 is used to determine the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section according to the first monitoring data.

[0123] The target prediction value determination module 504 is used to determine the target prediction value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment according to the prediction value time series corresponding to each pollution source;

[0124] The target pollution source determination module 505 is used to determine the target pollution source corresponding to the target water quality index according to the monitoring peak value and the target prediction value corresponding to each pollution source.

[0125] In a possible implementation, the prediction module 502 is further configured to:

[0126] Based on the second monitoring data, determine the one-dimensional water quality model corresponding to the target river channel; for any pollution source, determine the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section based on the distance between the pollution source and the monitoring section, the third monitoring data corresponding to the pollution source and the one-dimensional water quality model.

[0127] In a possible implementation, the prediction module 502 is further configured to:

[0128] According to the second monitoring data, the average river flow, average flow velocity and initial values ​​of the target water quality indicators corresponding to the target river are determined; according to the average river flow, average flow velocity, initial values ​​of the target water quality indicators and degradation coefficients corresponding to the target water quality indicators, a one-dimensional water quality model is determined.

[0129] In a possible implementation, the target pollution source determination module 505 is further configured to:

[0130] For any pollution source, determine the pollution contribution ratio corresponding to the pollution source based on the target prediction value and monitoring peak value corresponding to the pollution source; determine the target pollution source based on the pollution contribution ratio corresponding to each pollution source.

[0131] In a possible implementation, the apparatus 500 further includes a model adjustment module, which is used to:

[0132] According to the predicted value time series corresponding to all pollution sources, the predicted total value time series is determined; according to the predicted total value time series and the first monitoring data, the prediction error corresponding to the one-dimensional water quality model is determined; when the prediction error does not meet the preset threshold, the degradation coefficient is adjusted to determine the adjusted degradation coefficient; according to the adjusted degradation coefficient, the one-dimensional water quality model is adjusted to determine the adjusted one-dimensional water quality model.

[0133] In a possible implementation, the first monitoring data includes a time series of monitoring values ​​of multiple water quality indicators at the monitoring section; the device 500 also includes a target water quality indicator determination module, which is used to:

[0134] According to the first monitoring data, the excess multiples of each water quality indicator at the monitoring section are determined; according to the excess multiples of each water quality indicator at the monitoring section, the target water quality indicator is determined.

[0135] In one possible implementation, the target water quality indicators include: any one of pH, turbidity, dissolved oxygen, permanganate index, total organic carbon, five-day biochemical oxygen demand, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen, organic phosphorus, organic nitrogen, nitrate nitrogen, nitrate nitrogen, phosphate and conductivity.

[0136] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0137] The embodiment of the present disclosure also provides a computer-readable storage medium on which computer program instructions are stored, and the computer program instructions implement the above method when executed by a processor. The computer-readable storage medium can be a volatile or non-volatile computer-readable storage medium.

[0138] An embodiment of the present disclosure further proposes an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0139] The embodiments of the present disclosure also provide a computer program product, including a computer-readable code, or a non-volatile computer-readable storage medium carrying the computer-readable code. When the computer-readable code runs in a processor of an electronic device, the processor in the electronic device executes the above method.

[0140] The electronic device may be provided as a terminal, a server, or a device in other forms.

[0141] Figure 6 A block diagram of an electronic device according to an embodiment of the present disclosure is shown. Figure 6 , the apparatus 1900 may be provided as a server or a terminal device. Figure 6 , the apparatus 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions, such as an application, that can be executed by the processing component 1922. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0142] The device 1900 may also include a power supply component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input / output interface 1958 (I / O interface). The device 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server 2000. TM , MacOS X TM , Unix TM , Linux TM , FreeBSD TM or similar.

[0143] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions, which can be executed by the processing component 1922 of the device 1900 to perform the above method.

[0144] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0145] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the above. The computer-readable storage medium used herein is not to be interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0146] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0147] The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of the computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit may execute the computer-readable program instructions, thereby implementing various aspects of the present disclosure.

[0148] Various aspects of the present disclosure are described herein with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0149] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0150] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0151] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0152] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for tracing the source of flood season pollution, characterized in that: include: Obtaining first monitoring data corresponding to a monitoring section in a target river, second monitoring data corresponding to an upstream monitoring point in the target river, and third monitoring data corresponding to each pollution source in the target river, wherein the first monitoring data includes a monitoring value time series of a target water quality index at the monitoring section, the second monitoring data includes a flow time series at the upstream monitoring point and a monitoring value time series of the target water quality index, and the third monitoring data corresponding to any one pollution source includes a flow time series at the pollution source and a monitoring value time series of the target water quality index; According to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, respectively determine the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section, wherein the predicted value time series of the target water quality index corresponding to any pollution source at the monitoring section is used to represent the predicted value of the target water quality index corresponding to this part of the sewage discharged by the pollution source when it is transmitted to the monitoring section within the preset monitoring time; Determine, according to the first monitoring data, a monitoring peak value and a peak time corresponding to the target water quality index at the monitoring section; Determine the target predicted value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment according to the predicted value time series corresponding to each pollution source; Determining the target pollution source corresponding to the target water quality index according to the monitoring peak value and the target prediction value corresponding to each pollution source; Wherein, determining the target pollution source corresponding to the target water quality index according to the monitoring peak value and the target prediction value corresponding to each pollution source includes: For any pollution source, determine the pollution contribution ratio corresponding to the pollution source according to the target prediction value corresponding to the pollution source and the monitoring peak value; Determine the target pollution source according to the pollution contribution ratio corresponding to each pollution source; The first monitoring data includes a time series of monitoring values ​​of multiple water quality indicators at the monitoring section; The method further comprises: For any water quality indicator, determining a monitoring peak value of the water quality indicator at the monitoring section according to the first monitoring data; For any water quality indicator, determine the excess multiple corresponding to the water quality indicator according to the monitoring peak value of the water quality indicator; The excess multiples corresponding to each water quality index are compared, and the water quality index with the largest excess multiple is determined as the target water quality index.

2. The method according to claim 1, characterized in that The method of determining the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, comprises: Determining a one-dimensional water quality model corresponding to the target river channel according to the second monitoring data; For any pollution source, the predicted value time series of the target water quality index corresponding to the pollution source at the monitoring section is determined based on the distance between the pollution source and the monitoring section, the third monitoring data corresponding to the pollution source and the one-dimensional water quality model.

3. The method according to claim 2, characterized in that Determining the one-dimensional water quality model corresponding to the target river according to the second monitoring data includes: Determine, according to the second monitoring data, an average river flow, an average flow velocity, and an initial value of the target water quality index corresponding to the target river; The one-dimensional water quality model is determined according to the average river flow, the average flow velocity, the initial value of the target water quality index and the degradation coefficient corresponding to the target water quality index.

4. The method according to claim 3, characterized in that The method further comprises: Determine the total predicted value time series based on the predicted value time series corresponding to all pollution sources; Determining a prediction error corresponding to the one-dimensional water quality model according to the predicted total value time series and the first monitoring data; When the prediction error does not meet a preset threshold, adjusting the degradation coefficient to determine an adjusted degradation coefficient; The one-dimensional water quality model is adjusted according to the adjusted degradation coefficient to determine the adjusted one-dimensional water quality model.

5. The method according to any one of claims 1 to 3, characterized in that: The target water quality indicators include: any one of pH, turbidity, dissolved oxygen, permanganate index, total organic carbon, five-day biochemical oxygen demand, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen, organic phosphorus, organic nitrogen, nitrate nitrogen, nitrate nitrogen, phosphate and conductivity.

6. A device for tracing the source of flood season pollution, characterized in that: include: A monitoring data acquisition module, used to acquire first monitoring data corresponding to a monitoring section in a target river, second monitoring data corresponding to an upstream monitoring point in the target river, and third monitoring data corresponding to each pollution source in the target river, wherein the first monitoring data includes a monitoring value time series of a target water quality index at the monitoring section, the second monitoring data includes a flow time series at the upstream monitoring point and a monitoring value time series of the target water quality index, and the third monitoring data corresponding to any pollution source includes a flow time series at the pollution source and a monitoring value time series of the target water quality index; A prediction module, used to determine the predicted value time series of the target water quality index corresponding to each pollution source at the monitoring section according to the distance between each pollution source and the monitoring section, the second monitoring data, and the third monitoring data corresponding to each pollution source, wherein the predicted value time series of the target water quality index corresponding to any pollution source at the monitoring section is used to represent the predicted value of the target water quality index corresponding to the sewage discharged by the pollution source when it is transmitted to the monitoring section within a preset monitoring time; A monitoring peak value determination module, used to determine the monitoring peak value and peak time corresponding to the target water quality index at the monitoring section according to the first monitoring data; A target prediction value determination module, used to determine the target prediction value of the target water quality index corresponding to each pollution source at the monitoring section at the peak moment according to the prediction value time series corresponding to each pollution source; A target pollution source determination module, used to determine the target pollution source corresponding to the target water quality index according to the monitoring peak value and the target prediction value corresponding to each pollution source; Wherein, the target pollution source determination module is specifically used for: For any pollution source, determine the pollution contribution ratio corresponding to the pollution source according to the target prediction value corresponding to the pollution source and the monitoring peak value; Determine the target pollution source according to the pollution contribution ratio corresponding to each pollution source; The first monitoring data includes a time series of monitoring values ​​of multiple water quality indicators at the monitoring section; The device also includes: a target water quality index determination module, which is used to: For any water quality indicator, determining a monitoring peak value of the water quality indicator at the monitoring section according to the first monitoring data; For any water quality indicator, determine the excess multiple corresponding to the water quality indicator according to the monitoring peak value of the water quality indicator; The excess multiples corresponding to each water quality index are compared, and the water quality index with the largest excess multiple is determined as the target water quality index.

7. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to implement the method described in any one of claims 1 to 5 when executing the instructions stored in the memory.

8. A non-volatile computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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