CN112417788A - Water environment pollution analysis system and method based on big data - Google Patents
Water environment pollution analysis system and method based on big data Download PDFInfo
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Abstract
The invention relates to the technical field of water resource monitoring, in particular to a big data-based water environment pollution analysis system, which comprises: the acquisition unit is used for acquiring river basic data and pollution source data; the dividing unit is used for dividing river reach of the river; the modeling unit is used for establishing a pollutant tracing relation and a monitoring section water quality response relation; the analysis unit is used for analyzing the structure of the pollution source of each water outlet of each control unit according to the contribution analysis of the internal and external sources and the contribution analysis of the type of the pollution source, and analyzing the contribution rate of the pollution source to the water quality of the monitored section; and the output unit is used for outputting the analysis result. The method takes the monitoring section as a core, can analyze the pollution source causing the monitoring section, locks the pollution source with relatively large contribution degree to the water quality of the river section in the river, and solves the technical problem that the pollution source investigation and tracing work can not be timely and effectively carried out when the conventional method is used for dealing with the sudden pollution source.
Description
Technical Field
The invention relates to the technical field of water resource monitoring, in particular to a big data-based water environment pollution analysis system and method.
Background
With the continuous acceleration of industrialization and urbanization, environmental problems are increasingly prominent, and particularly, water environment pollution becomes an important restrictive factor for the sustainable development of rivers. However, the water quality pollution sources are numerous, the pollution tracing workload is large, and the pollution source investigation and tracing work is difficult to be timely and effectively carried out, which affects the river management and treatment work.
In contrast, chinese patent CN109101781A discloses a method for calculating the contribution ratio of pollution sources in a complex river network, which comprises the steps of: generalizing a complex river network; determining a main stream of a river network; acquiring basic data of a main flow; acquiring data of a main flow pollution source; simulating the migration and transformation of pollutants; and analyzing the contribution proportion of the pollution source. The method has the advantages that the actual monitoring is carried out according to the pollutant parameters of the target section, the contribution proportion of a pollution source to the target section can be determined, the dynamic response process of the pollutant concentration of the target section changing along with the pollution source is simulated under the condition of no limitation of time and region, the reverse tracing and accurate reduction of the pollution source are realized, and therefore, effective technical support is provided for the water conservancy department to develop watershed water environment treatment and risk evaluation.
In the technical scheme, the contribution proportion of the pollution source in the river is quantitatively analyzed, and effective guidance can be provided for accurately tracing the pollution source and scientifically making a treatment strategy. However, in some cases, the pollution of the river is not gradually and slowly formed, but is suddenly and suddenly formed in one time due to some special cases. The existing method can not timely and effectively carry out pollution source investigation and tracing work when dealing with the sudden pollution source, thereby influencing the management and treatment of the river and being not beneficial to the protection of the river environment.
Disclosure of Invention
The invention provides a water environment pollution analysis system based on big data, which solves the technical problem that the existing method can not effectively perform pollution source investigation and tracing work in time when dealing with sudden pollution sources.
The basic scheme provided by the invention is as follows: water environmental pollution analytic system based on big data includes:
the acquisition unit is used for acquiring river basic data and pollution source data;
the dividing unit is used for dividing river sections of the river according to geographical information data of the river and the setting condition of the water environment quality monitoring section, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section;
the modeling unit is used for establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by using an EFDC hydrodynamic model;
the analysis unit is used for carrying out internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; analyzing the contribution rate of pollution sources to the monitoring of the water quality of the section, and determining the contribution rate of each pollution source;
and the output unit is used for outputting the analysis result.
The working principle and the advantages of the invention are as follows: the traceability relation takes the monitoring section as a core, and is traced back to the upstream monitoring section and the pollutant input of the upstream river reach. After the pollutant tracing relation model is established, if the water quality of the monitored cross section exceeds the standard, the main pollution source can be judged according to the monitoring condition of the upstream monitored cross section of the cross section, if the upstream monitoring condition also exceeds the standard, the pollutant is mainly from the upstream cross section, and the important point of analysis is transferred to the upstream monitored cross section. In addition, the pollution source information is combined in a steady state and a dynamic state, and the response relation between the river pollution source and the water quality of the monitoring section is established by using the EFDC hydrodynamic model, so that the sudden pollution source tracing of a river point source can be realized. By adopting the mode, the monitoring section is taken as a core, so that the pollution source causing the monitoring section can be analyzed, and the supervision and investigation range is reduced; the method can quickly feed back and control the condition of the pollution source in the section in a short time, and lock the pollution source in the river which has relatively large contribution degree to the water quality of the river section; therefore, the method is beneficial to assisting in determining the region and the discharge port of the pollution source, further determining the specific industry and even screening out specific pollution source enterprises which need key inspection, and is convenient for improving the supervision capability of a supervision department.
The method takes the monitoring section as a core, can analyze the pollution source causing the monitoring section, locks the pollution source with relatively large contribution degree to the water quality of the river section in the river, and solves the technical problem that the pollution source investigation and tracing work can not be timely and effectively carried out when the conventional method is used for dealing with the sudden pollution source.
Furthermore, the analysis unit is also used for predicting the discharge amount of the pollutant source in the river according to the river basic data and the pollution source data and distributing the pollutants according to the pollution source centralized position and the river control unit.
Has the advantages that: by the method, the discharge amount of the pollutant source in the river is predicted, the pollutants are distributed according to the pollution source centralized position and the river control unit, the possible distribution situation of the pollutants in the river can be predicted, and therefore the supervision department can take corresponding measures in advance.
Further, the analysis unit is also used for determining a risk pressure threshold value of each pollution source of each water outlet corresponding to the monitoring section according to historical pollution source emission data of each monitoring section, performing overproof risk pressure identification through the risk pressure threshold value, and evaluating the contribution degree of the overproof risk pressure of the pollution source when the quality of the monitored section water is identified to be overproof.
Has the advantages that: by the method, the risk pressure threshold of each pollution source of each water outlet corresponding to each monitoring section can be obtained, so that the important overproof risk pressure source can be conveniently determined, and the targeted supervision is facilitated.
Furthermore, the analysis unit is also used for determining the emission level of pollutants in each control unit, acquiring the distribution information of the peripheral pollution sources, and analyzing the distribution diffusion information of the pollutants according to the emission level of the pollutants and the distribution information of the peripheral pollution sources.
Has the advantages that: by the mode, information related to distribution and diffusion of pollutants in the river, namely the distribution rule of the pollutants in the river can be obtained, and therefore the important supervision area can be determined.
Further, the analysis unit is also used for determining the maximum discharge capacity and the allowable discharge index of each control unit and determining the environmental bearing capacity.
Has the advantages that: by the mode, the environmental bearing capacity can be obtained, and a supervision department can be reminded of processing conveniently and timely when the pollutants exceed the standard.
The invention also provides a water environment pollution analysis method based on big data, which comprises the following steps:
s1, acquiring river basic data and pollution source data;
s2, dividing the river into river reach according to the geographical information data of the river and the water environment quality monitoring section setting condition, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section;
s3, establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by an EFDC hydrodynamic model;
s4, performing internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; analyzing the contribution rate of pollution sources to the monitoring of the water quality of the section, and determining the contribution rate of each pollution source;
and S5, outputting the analysis result.
The working principle and the advantages of the invention are as follows: the traceability relation takes the monitoring section as a core, and traces back to the upstream monitoring section and the pollutant input of the upstream river reach. Meanwhile, the pollution source information is combined in a steady state and a dynamic state, the response relation of the river pollution source and the water quality of the monitoring section is established by an EFDC hydrodynamic model, and the source tracing of the sudden pollution of a river point source is realized. By adopting the mode, the monitoring section is taken as a core, so that the pollution source causing the monitoring section can be analyzed, and the supervision and investigation range is reduced; the method can quickly feed back and control the condition of the pollution source in the section in a short time, and lock the pollution source in the river which has relatively large contribution degree to the water quality of the river section.
Further, in S4, the discharge amount of the pollutant source in the river is predicted based on the river base data and the pollution source data, and the pollutant is distributed according to the pollution source concentration position and the river control unit.
Has the advantages that: therefore, the possible distribution situation of the pollutants in the river can be predicted, and the corresponding measures can be taken by a supervision department in advance.
Further, in S4, determining a risk pressure threshold of each pollution source of each drain port corresponding to each monitoring section according to the historical emission data of the pollution source of each monitoring section, performing overproof risk pressure identification through the risk pressure threshold, and evaluating the contribution degree of the overproof risk pressure of the pollution source when the quality of the monitored section water is identified to be overproof.
Has the advantages that: therefore, the risk pressure source with key points exceeding the standard is determined, and the targeted supervision is facilitated.
Further, in S4, the emission level of the pollutant in each control unit is determined, the distribution information of the peripheral pollution sources is obtained, and the distribution diffusion information of the pollutant is analyzed according to the emission level of the pollutant and the distribution information of the peripheral pollution sources.
Has the advantages that: therefore, the distribution rule of pollutants in the river can be obtained, and the determination of key supervision areas is facilitated.
Further, in S4, the maximum discharge amount and the allowable discharge index of each control unit are also determined, and the environmental load capacity is determined.
Has the advantages that: therefore, the environmental bearing capacity is obtained, and the supervision department can be reminded to process the pollutants when the pollutants exceed the standard.
Drawings
Fig. 1 is a system structure block diagram of an embodiment of a big data-based water environment pollution analysis system according to the present invention.
Fig. 2 is a schematic structural diagram of an acquisition device in an embodiment 3 of a water environment big data monitoring system according to the present invention.
Detailed Description
The following is further detailed by the specific embodiments:
reference numerals in the drawings of the specification include: the device comprises a first supporting rod 1, a second supporting rod 2, a rotating rod 3, a pin 4, a spring 5, a tension sensor 6, a controller 7, a water quality detector 8, a filter plate 9 and a shell 10.
Example 1
The embodiment of the water environment pollution analysis system based on big data is basically as shown in the attached figure 1, and comprises the following components:
the acquisition unit is used for acquiring river basic data and pollution source data;
the dividing unit is used for dividing river sections of the river according to geographical information data of the river and the setting condition of the water environment quality monitoring section, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section;
the modeling unit is used for establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by using an EFDC hydrodynamic model;
the analysis unit is used for carrying out internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; analyzing the contribution rate of pollution sources to the monitoring of the water quality of the section, and determining the contribution rate of each pollution source;
and the output unit is used for outputting the analysis result.
In the present embodiment, the acquisition unit, the division unit, the modeling unit, the analysis unit, and the output unit are all integrated on a server, and the functions thereof are realized by software/programs/codes.
The specific implementation process is as follows:
and S1, acquiring river basic data and pollution source data.
In this embodiment, the river basic data and the pollution source data are collected in advance and stored in the server in advance, so as to be extracted and analyzed at any time. The river basic data comprises river reach numbers, flow rates, lengths, pollutant types and concentrations thereof and the like, and the pollutant data comprises pollution source positions, types, discharge time, discharge flow rates, pollutant concentration data and the like of river reach point sources and surface sources.
And S2, dividing the river into river reach according to the geographical information data of the river and the setting condition of the water environment quality monitoring section, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section.
In this embodiment, according to the setting condition of a GIS (geographic information system) data of a watershed water system and a water environment quality monitoring section, a river reach is divided into a plurality of control units with the monitoring section as a boundary. Specifically, the upstream and downstream boundaries of each control unit are two monitoring sections. For example, the number of a certain river reach is 02, the length of the certain river reach is 500m, 9 monitoring sections are uniformly arranged in the length direction of the certain river reach, then the monitored sections of the certain river reach are divided into 10 control units, and the length of each control unit is 50 m. Meanwhile, visual expression is carried out based on the GIS map, and the division result of the control unit is displayed.
S3, establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by an EFDC hydrodynamic model.
Based on the monitoring section, the influence factors of whether the water quality reaches the standard include: firstly, monitoring the water quality condition of a cross section at the upstream; and secondly, pollutant input condition of the upstream river reach. The traceability relation takes the monitoring section as a core, and is traced back to the upstream monitoring section and the pollutant input of the upstream river reach. Therefore, firstly, a relationship of river reach-pollution source is established; then, establishing a relationship of river reach-branch-pollution source; and finally, establishing a source tracing relation model of a monitoring section and a pollution source through the relation between the river reach-pollution source and the river reach-branch-pollution source.
In addition, each control unit is meshed, and an EFDC hydrodynamic model is used for establishing a river pollution source and monitoring section water quality response relation. Specifically, the method comprises the steps of gridding each control unit, setting initial conditions and boundary conditions of the EFDC hydrodynamic model, setting and verifying parameters, and setting and verifying the model. In the simulation calculation process of the EFDC model, firstly, flow field calculation is completed, the space-time distribution characteristics of a three-dimensional flow velocity field are obtained, and then the functions of silt migration and erosion and deposition are calculated on the basis, so that the dynamic change process of each water quality variable influenced by the adsorption of viscous silt is simulated.
S4, performing internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; and analyzing the contribution rate of the pollution sources to the monitoring of the section water quality, and determining the contribution rate of each pollution source.
After the pollutant traceability relation is established, when the water quality of the monitoring section exceeds the standard, the main pollution source can be judged according to the monitoring condition of the upstream monitoring section of the monitoring section. That is, if the upstream monitoring condition also exceeds the standard, the pollutant is mainly from the upstream section; if the monitoring result of the upstream section is normal, the pollutants mainly come from the upstream river reach of the section, and the upstream river reach and the pollution source of the branch flow imported into the river reach are mainly analyzed according to a source tracing relation model of the monitoring section-pollution source.
And (3) screening pollution sources according to pollutants to be analyzed, counting the total pollutant emission amount of each branch, and monitoring data, rainfall, the flow of the section and a trend chart of automatic monitoring data of the section on line by monitoring the pollution sources in the section controlled area. If the river has an entry river, calculating the input pollution contribution amount of the section according to the monitoring value and the flow (associated hydrological data) on the entry monitoring section; similarly, the pollution contribution of the exit section (downstream section) is obtained, the difference between the two is the endogenous contribution, and the occupation relation between the input contribution and the endogenous contribution can be shown through a pie chart. And analyzing the number of pollution sources in a drainage basin and the ratio of COD (chemical oxygen demand), TP (total phosphorus) and NH3N according to industrial pollution, living pollution, breeding pollution, agricultural non-point source pollution and the prior art.
Secondly, carrying out pollution source structure analysis on each water discharge port of each control unit to obtain the discharge amount of each pollution source in each water discharge port; calculating the pollution contribution rate by using a hydrodynamic water quality model established by the EFDC, setting a single pollution source as 1 unit pollution discharge load, and calculating the concentration distribution under the condition by using the hydrodynamic water quality model to determine the pollution contribution rate of the unit pollution load of the pollution source to each water quality control section; changing pollution sources, repeating the steps to obtain the contribution rate coefficient of each pollution source, thereby realizing the calculation of the contribution degree of each pollution source.
And S5, outputting the analysis result.
And finally, outputting the analysis result by using a graph, a table or a pie chart.
Example 2
The only difference from embodiment 1 is that,
in S4, the discharge amount of the pollutant source in the river is predicted based on the river base data and the pollution source data, and the pollutant is distributed according to the pollution source concentration position and the river control unit. For example, a pollutant mass conservation numerical model is constructed, a numerical solution of the pollutant mass conservation numerical model is solved by a finite difference method through a water quality balance equation, and the dynamic change of the pollutant discharge amount on the monitoring section of each river section along with time is calculated; meanwhile, when the numerical solution is solved, if the pollution sources are concentrated and the river control unit is large, a high initial pollutant concentration is distributed or set.
In addition, determining the risk pressure threshold of each pollution source of each water outlet corresponding to each monitoring section according to the historical pollution source emission data of each monitoring section, performing overproof risk pressure identification through the risk pressure threshold, and evaluating the contribution degree of the overproof risk pressure of the pollution source when the water quality of the monitoring section is identified to be overproof. For example, Ckijt is Akijt × Wjt, where Ckijt is the concentration formed at the monitoring section k by the discharge amount of the pollution source j discharged into the drain i at time t; akijt is a water quality pressure response coefficient between a water quality pressure response coefficient of a pollution source j entering a river through a water outlet i at the moment t and a monitoring section k; wjt is the emission of pollution source j at time t. For the contribution rate of any pollution source to the monitored section, Conkijt is the sum of Conkijt/(n conkijts), Conkijt is the contribution rate of the discharge amount discharged from the pollution source j into the water outlet i at the time t to the monitored section k at the time t, and n is the number of water outlets in the river reach. And finally, evaluating according to the Conkijt and the size of a preset threshold value.
In S4, the emission level of the pollutant in each control unit is also determined, the distribution information of the pollution sources around the control unit is obtained, and the distribution diffusion information of the pollutant is analyzed according to the emission level of the pollutant and the distribution information of the pollution sources around the control unit. For example, the distribution rule and the change rule with time of the pollutants on the space are stated, where C is the pollutant concentration, Qi is the total pollutant emission amount, and E is eij, which is the average contribution degree of the pollutants emitted by 1 unit pollution source in the jth control unit to the concentration in the ith control unit. Furthermore, the maximum emission of each control unit and the allowed emission index are determined, and the environmental load capacity is determined. For example, Q is D × a, where Q is the pollutant emission amount of the control unit, D is the pollutant emission concentration control index, and a is the space volume of the control unit, so as to prompt the monitoring department to process when the pollutant exceeds the standard.
Example 3
The difference from the embodiment 2 is only that the device further comprises a collecting device, as shown in the attached figure 2, the collecting device comprises: the device comprises a first supporting rod 1, a second supporting rod 2, a rotating rod 3, a pin 4, a spring 5, a tension sensor 6, a controller 7, a water quality detector 8, a filter plate 9 and a shell 10. The shell 10 is cylindrical, and the filter plates 9 are mounted at the left end and the right end of the shell 10, for example, by screws; a plurality of filter holes are drilled on the filter plates 9. One end of the first supporting rod 1 is welded on the inner wall of the shell 10, and the controller 7 and the water quality detector 8 are fixedly arranged on the other end of the first supporting rod 1, for example, by screws or fixed by steel wires. One end of the second supporting rod 2 is welded on the inner wall of the shell 10, and the other end is hinged with the rotating rod 3, namely hinged through the pin 4, and the rotating rod 3 can freely rotate around the axis of the pin 4. The tension sensor 6 is fixedly installed on the upper wall surface of the inner wall of the shell 10, one end of the spring 5 is fixedly connected with the tension sensor 6, and the other end of the spring is welded on the rotating rod.
In this embodiment, ecological environment data passes through water quality detector 8 and gathers, and initial time, dwang 3 is in the natural state of drooping, and spring 5 is in the natural length state, puts into the river with collection system. When river water flows through the collecting device from right to left, impurities such as weeds, green moss and duckweeds can be blocked due to the filter plates 9 arranged at the two ends of the shell 10, so that the impurities are prevented from being attached to the water quality detector 8, and the water quality detector 8 is prevented from being incapable of working normally. Under the action of the impact force of the river water to the left, the rotating rod 3 deflects to the left, so that the length of the spring 5 is lengthened, the tension sensor 6 detects the tension of the spring 5 and sends the tension to the controller 7.
According to the basic physics knowledge, if the river water flows at a constant speed in a period of time, namely the flow velocity of the river water does not change along with the time, the tension detected by the tension sensor 6 should be approximately equal; if the river water is flowing at an accelerated speed, that is, the flow velocity of the river water is gradually increased along with the time, the tension detected by the tension sensor 6 should be gradually increased; if the river water flows at a reduced speed, that is, the flow velocity of the river water gradually decreases with time, the tension detected by the tension sensor 6 should also gradually decrease.
In this embodiment, the water quality detector 8 starts to collect data after the flow velocity of the river is stabilized, specifically: the tension sensor 6 collects tension of the spring 5 in real time and sends the collected tension to the controller 7; after receiving the pulling force, the controller 7 judges whether the pulling force is approximately equal within a preset time: if the tension is approximately equal within the preset time, sending a control signal to the water quality detector 8, and starting to acquire data after the water quality detector 8 receives the control signal; on the contrary, if the tensile force is not approximately equal for the preset time period, the control signal is not transmitted to the water quality detector 8. By the mode, data acquisition is carried out after the tension is stable, namely the flow velocity of river water is stable; compared with the method of directly starting data acquisition, the method has the advantages that the obtained data are more reliable and are less influenced by accidental factors.
For example, the preset time is 5 minutes, if the tension in the time fluctuates around 2N, the maximum tension is 2.1N, the minimum tension is 1.9N, and the tension fluctuation does not exceed 5%, it is indicated that the flow rate of river water in the time is relatively stable, and the acquired data is relatively reliable, so that data acquisition is started; on the contrary, if the maximum tension is 2.5N and the minimum tension is 1.0N in the period of time, the tension fluctuation even reaches 50%, which indicates that the flow velocity of the river water in the period of time is unstable, the acquired data has strong randomness and cannot reflect the real condition of the river water, so the data acquisition is not started.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. Water environmental pollution analytic system based on big data, its characterized in that includes:
the acquisition unit is used for acquiring river basic data and pollution source data;
the dividing unit is used for dividing river sections of the river according to geographical information data of the river and the setting condition of the water environment quality monitoring section, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section;
the modeling unit is used for establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by using an EFDC hydrodynamic model;
the analysis unit is used for carrying out internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; analyzing the contribution rate of pollution sources to the monitoring of the water quality of the section, and determining the contribution rate of each pollution source;
and the output unit is used for outputting the analysis result.
2. The big data-based water environment pollution analysis system of claim 1, wherein the analysis unit is further configured to predict the discharge amount of the pollutant source in the river according to the river basic data and the pollution source data, and distribute the pollutant according to the pollution source concentration position and the river control unit.
3. The big-data-based water environment pollution analysis system as claimed in claim 2, wherein the analysis unit is further configured to determine a risk pressure threshold of each pollution source of each drainage outlet corresponding to each monitored section according to historical pollution source emission data of each monitored section, perform over-standard risk pressure identification through the risk pressure threshold, and evaluate the contribution degree of the over-standard risk pressure of the pollution source when the water quality of the monitored section is over-standard.
4. The big-data-based water environment pollution analysis system of claim 3, wherein the analysis unit is further configured to determine the emission level of pollutants in each control unit, obtain distribution information of the pollution sources around the control unit, and analyze the distribution diffusion information of the pollutants according to the emission level of the pollutants and the distribution information of the pollution sources around the control unit.
5. The big data based water environment pollution analysis system of claim 4, wherein the analysis unit is further used for determining the maximum discharge amount and the allowable discharge index of each control unit, and determining the environment bearing capacity.
6. The water environment pollution analysis method based on big data is characterized by comprising the following steps:
s1, acquiring river basic data and pollution source data;
s2, dividing the river into river reach according to the geographical information data of the river and the water environment quality monitoring section setting condition, dividing the river into a plurality of control units by taking the monitoring section as a boundary, and taking the boundary of each control unit as the monitoring section;
s3, establishing a pollutant tracing relation of a monitoring section-pollution source on the basis of river basic data, pollution source data and river reach division, and establishing a river pollution source and monitoring section water quality response relation by an EFDC hydrodynamic model;
s4, performing internal and external source contribution analysis and pollution source type contribution analysis according to the established pollutant tracing relation and river pollution source and monitoring section water quality response relation; analyzing the structure of the pollution source of each water outlet of each control unit to obtain the discharge amount of each pollution source in each water outlet; analyzing the contribution rate of pollution sources to the monitoring of the water quality of the section, and determining the contribution rate of each pollution source;
and S5, outputting the analysis result.
7. The big-data-based water environment pollution analysis method according to claim 6, wherein in step S4, the discharge amount of the pollutant source in the river is predicted according to the river basic data and the pollution source data, and the pollutant is distributed according to the pollution source concentration position and the river control unit.
8. The water environment pollution analysis method based on big data as claimed in claim 7, wherein in S4, a risk pressure threshold of each pollution source of each drainage outlet corresponding to each monitoring section is determined according to historical pollution source emission data of each monitoring section, identification of excessive risk pressure is performed through the risk pressure threshold, and the contribution degree of the excessive risk pressure of the pollution source is evaluated when the water quality of the monitoring section is identified to be excessive.
9. The big-data-based water environment pollution analysis method according to claim 8, wherein in S4, the emission level of pollutants in each control unit is further determined, the distribution information of the pollution sources around the control unit is obtained, and the distribution diffusion information of pollutants is analyzed according to the emission level of pollutants and the distribution information of the pollution sources around the control unit.
10. The big-data-based water environmental pollution analysis method according to claim 9, wherein in S4, the maximum discharge amount and the allowable discharge index of each control unit are further determined, and the environmental load capacity is determined.
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