CN111709108A - Pollution emission reduction analysis method and system based on big data - Google Patents
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Abstract
The invention discloses a pollution emission reduction analysis method and system based on big data, wherein the method comprises the following steps: acquiring drainage system data; obtaining an output result according to the data of the drainage system and a preset hydraulic model of the drainage system; providing at least one solution through big data analysis according to the output result and a preset first threshold; determining a final solution according to the solution, a preset second threshold and a preset hydraulic model of the drainage system; the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, and the preset second threshold value is that the pollutant load of the combined-system discharged water body is not greater than the pollutant load of the split-system discharged water body. The invention can provide an effective final solution and can effectively solve the problem of emission reduction of pollutant load discharged into the water body by combined flow. The invention can be widely applied to the technical field of water environment treatment.
Description
Technical Field
The invention relates to the field of water environment treatment, in particular to a pollution emission reduction analysis method and system based on big data.
Background
As the research of the drainage industry in China starts late, most drainage industries still adopt the traditional analysis method to carry out hydraulic simulation. Currently, with the gradual development of research on dynamic models of drainage systems, most drainage industries are gradually transited from traditional analysis methods to modern hydraulic simulation analysis methods, however, the current analysis methods can only simulate hydraulic power and fail to find problems from hydraulic simulation and provide effective solutions, wherein the problems including pollutant emission reduction fail to provide effective solutions.
Disclosure of Invention
In view of the above, in order to solve the above technical problems, the present invention aims to provide a pollution emission reduction analysis method based on big data, which effectively solves the problem of pollutant emission reduction.
The technical scheme adopted by the invention is as follows: the pollution emission reduction analysis method based on big data comprises the following steps: acquiring drainage system data;
obtaining an output result according to the data of the drainage system and a preset hydraulic model of the drainage system;
providing at least one solution through big data analysis according to the output result and a preset first threshold;
determining a final solution according to the solution, a preset second threshold and a preset hydraulic model of the drainage system;
the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, the preset second threshold value is that the pollutant load of the combined system discharged water body is not greater than the pollutant load of the diversion system discharged water body, and the data of the drainage system comprises historical rainfall data.
Further, the method also comprises the following steps: the method for establishing the hydraulic model of the preset drainage system comprises the following steps:
obtaining model building data;
establishing a hydraulic model of the preset drainage system through Infoworks ICM according to the model establishing data;
the model establishing data comprises drainage pipe network GIS data, river channel data, pollution source population data, pump station data, industrial and commercial wastewater data, water level monitoring data, storage tank data, flow monitoring data, overflow port detection data, sewage treatment plant data and underlying surface data.
Further, the step of establishing the hydraulic model of the preset drainage system through the Infoworks ICM according to the model establishing data comprises the following steps:
importing drainage pipe network GIS data, river channel data, pump station data, water level monitoring data, flow monitoring data, overflow port detection data, sewage treatment plant data and industrial and commercial wastewater data into a preset data model;
dividing a water collection area according to the topological data and the topographic elevation data of the drainage pipe network to obtain a sewage water collection partition and a rainwater water collection partition;
dividing the sewage water collection partition and the rainwater water collection partition into a plurality of sub water collection areas according to the Thiessen polygon, and introducing pollution source population data and underlay surface data into the sub water collection areas to obtain a primary drainage system hydraulic model;
checking the primary drainage system hydraulic model to obtain a preset drainage system hydraulic model;
the model building data further comprise drainage pipe network topology data and terrain elevation data.
Further, the step of checking the primary drainage system hydraulic model to obtain the preset drainage system hydraulic model comprises the following steps:
leading the preset number of flow monitoring data in dry days and the preset number of flow monitoring data in rainy days into a primary drainage system hydraulic model;
adjusting parameters according to a preset standard, a primary drainage system hydraulic model output result and historical flow monitoring data to obtain a preset drainage system hydraulic model;
the flow monitoring data comprises historical flow monitoring data, flow monitoring data of a preset number of dry days and flow monitoring data of rainy days.
Further, the method also comprises the following steps:
detecting whether the model building data is missing or not, if so, acquiring missing data and importing the missing data into a preset data model;
the model building data further comprises missing data, and the missing data comprises at least one of radar detection data or actual measurement data, endoscopic detection data and drainage pipe network construction drawing data acquired through CCTV.
Further, the step of acquiring the data of the drainage system includes:
acquiring a typical year continuous rainfall analysis result and a characteristic design rainfall analysis result;
the method comprises the following steps of obtaining a typical year continuous rainfall analysis result:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
obtaining the monthly average rainfall capacity and the monthly average rainfall days according to historical rainfall data;
obtaining a typical year continuous rainfall analysis result consisting of a rainfall typical month according to the average monthly rainfall and the average monthly rainfall days;
the steps for obtaining the characteristic design rainfall analysis result are as follows:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
carrying out classified statistics on historical rainfall data according to a preset time interval and a preset rainfall interval to obtain rainfall times and frequency distribution results of the preset rainfall interval;
according to the rainfall times and the frequency distribution result, a characteristic rainfall and rainfall duration statistical result is obtained through SCS model synthesis;
wherein, the drainage system data comprises typical year continuous rainfall analysis results and characteristic design rainfall analysis results.
Further, the step of obtaining an output result according to the data of the drainage system and a preset drainage system hydraulic model specifically comprises:
importing the typical year continuous rainfall analysis result and the characteristic design rainfall analysis result into a preset drainage system hydraulic model to obtain an output result;
the drainage system data comprises typical year continuous rainfall analysis results and characteristic design rainfall analysis results, and the output results comprise at least one of sewage collection rate, split flow rate, pollutant load, runoff rate and overflow rate.
Further, the step of determining a final solution according to the solution, a preset second threshold and a preset hydraulic model of the drainage system comprises:
importing specific data of the solution into a preset drainage system hydraulic model to obtain an updated output result;
judging whether the updating output result meets a preset second threshold value or not, if not, adopting another solution, returning a step of importing specific data of the solution into a preset drainage system hydraulic model according to specific data of the other solution, importing the preset drainage system hydraulic model to obtain an updating output result, and determining a final solution until the updating output result meets the preset second threshold value;
wherein, the update output result comprises the combined system water body pollutant discharge load and the split system water body pollutant discharge load, the solution has specific data, and the specific data comprises engineering project data.
The invention also provides a pollution emission reduction analysis system based on big data, comprising:
the acquisition module is used for acquiring data of the drainage system;
the output module is used for obtaining an output result according to the data of the drainage system and a preset drainage system hydraulic model;
the analysis module is used for providing at least one solution through big data analysis according to the output result and a preset first threshold;
the determining module is used for determining a final solution according to the solution, a preset second threshold and a preset drainage system hydraulic model;
the preset first threshold comprises at least one of a sewage collection rate threshold, a diversion rate threshold, a pollutant load threshold, a runoff rate threshold and an overflow rate threshold, the preset second threshold is that the pollutant load of the combined system discharged water body is not more than the pollutant load of the divided system discharged water body, and the drainage system data comprises historical rainfall data.
The invention has the beneficial effects that: the method comprises the steps of obtaining an output result according to drainage system data and a preset drainage system hydraulic model, evaluating problems existing in the output result according to a preset first threshold and the output result, providing at least one solution through big data analysis, providing a specific solution according to the problems existing in the output result, determining a final solution according to the solution, a preset second threshold and the preset drainage system hydraulic model, verifying whether the solution meets a standard or not, providing an effective final solution, and effectively solving the emission reduction problem of pollutant load discharged into a water body by combined flow system.
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FIG. 1 is a schematic flow chart of the steps of the method of the present invention;
FIG. 2 is a flowchart illustrating steps of an embodiment of the present invention.
Detailed Description
The invention will be further explained and explained with reference to the drawings and the embodiments in the description. The step numbers in the embodiments of the present invention are set for convenience of illustration only, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.
As shown in fig. 1, the pollution emission reduction analysis method based on big data includes the following steps:
acquiring drainage system data;
obtaining an output result according to the data of the drainage system and a preset hydraulic model of the drainage system;
providing at least one solution through big data analysis according to the output result and a preset first threshold;
determining a final solution according to the solution, a preset second threshold and a preset hydraulic model of the drainage system;
the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, and the preset second threshold value is that the pollutant load of the combined-system discharged water body is not greater than the pollutant load of the split-system discharged water body.
As shown in fig. 2, in the present embodiment, specifically, the following steps are included:
1) collecting data;
the collected data includes drainage system data and model building data;
wherein the model establishing data comprises drainage pipe network GIS data in a drainage area to be analyzed, river channel data (comprising confluence water flow data of a confluence drainage system area entering water, rainfall data of a diversion drainage system area entering water, concentration data of pollutants of the water entering the confluence drainage system area, concentration data of pollutants of the water entering the diversion drainage system area entering water), pump station data, industrial and commercial wastewater data, water level monitoring data, flow monitoring data, overflow port detection data, sewage treatment plant data (comprising water outlet data of a sewage treatment plant of the confluence drainage system area entering water, concentration data of pollutants of effluent of the confluence drainage system area entering a water and sewage plant, water outlet data of the sewage treatment plant of the diversion drainage system area entering water, concentration data of pollutants of effluent of the diversion drainage system area entering the water and sewage plant), and the like, Resident drainage data, drainage pipe network topology data, water level, flow data, terrain elevation data, underlying surface data, storage tank data and missing data (including radar detection data or actual measurement data acquired through CCTV, endoscopic detection data and drainage pipe network construction drawing data); wherein, the water body can be a river or a lake.
The drainage system data comprises historical rainfall data, typical year continuous rainfall analysis results and characteristic design rainfall analysis results;
the collected data can be established and stored in a data standard mapping file mode, and can be automatically imported or manually imported by a system.
2) Performing typical year continuous rainfall analysis and characteristic design rainfall analysis according to rainfall data;
typical year continuous rainfall analysis procedure:
1. collecting a preset time threshold (10 years in the embodiment, historical rainfall data of minutes or hours of 10 years is used as a sample in the central rainfall station of the drainage area to be analyzed, and carrying out statistics on the total amount of monthly rainfall and the number of days of rainfall to obtain the monthly average rainfall and the number of days of monthly rainfall of the sample;
2. selecting the month closest to the average rainfall and the average rainfall days in the sample as a typical rainfall month, recombining the typical rainfall month to form an artificial virtual typical rainfall year, and obtaining the continuous rainfall analysis result of the typical year to represent the average rainfall characteristics of multiple years.
Characteristic design rainfall analysis step:
1. collecting a preset time threshold (10 years in the embodiment, including historical rainfall data of minutes or hours of 10 years) of a central rainfall station of an area to be analyzed, defining a rainfall according to a preset time interval of 12h, and performing statistical analysis on rainfall and rainfall duration;
2. carrying out interval classification statistics on the rainfall and rainfall duration data which are subjected to statistical analysis according to 5 preset rainfall intervals of 0-5mm, 5-10mm, 10-20mm, 20-30mm, 30-45mm and more than 45mm to obtain the rainfall times and frequency distribution of each interval and obtain the frequency distribution of different rainfall intervals, and taking the rainfall duration obtained by calculating the median rainfall of each interval as the characteristic rainfall and the rainfall duration of the interval to obtain a preliminary result;
3. and synthesizing 6 rainfall interval preliminary results by adopting an SCS model, and obtaining the statistical results of the characteristic rainfall and the rainfall duration.
3) Analyzing the change of the surface runoff pollutant concentration;
1. and acquiring monitoring data of typical combined system overflow ports and split system rainwater discharge ports of the urban built-up area and the urban newly built-up area by manual sampling or automatic sampling, wherein the monitoring data are data of water quality concentration at intervals of 5min under the condition of monitoring different raining conditions of more than 6 fields, wherein the different raining conditions refer to short-duration heavy rain, short-duration medium rain, short-duration light rain, long-duration heavy rain, long-duration medium rain and long-duration light rain.
2. Obtaining the relation between the rainfall time and the change of the water quality concentration according to the monitoring data:
the total amount (load) of the overflow pollutants is analyzed and calculated by fitting an overflow quantity-time change curve obtained by simulating a relation curve between the duration of rainfall and the change of water quality concentration with a model;
4) establishing a preset drainage system hydraulic model by using the collected data;
the data model establishment according to the Infoworks ICM tool comprises the following steps:
s1: importing drainage pipe network GIS data, river channel data, pump station data, water level monitoring data, flow monitoring data, overflow port detection data, sewage treatment plant data and industrial and commercial wastewater data into a preset data model (the Infoworks ICM contains the Infoworks ICM);
s2: detecting whether data are missing or not, and if the data added in the previous step are missing, importing the missing data to ensure the integrity of the data, for example, if a pipe network with unknown data relation exists, importing the data according to pipe network construction drawing data, endoscopic detection data or a field reconnaissance mode to ensure that the pipe network connection relation of the model is clear;
s3: dividing a water collecting area of an area to be analyzed according to topological data of a drainage pipe network and topographic elevation data of the area to be analyzed to obtain a sewage collecting partition and a rainwater collecting partition, dividing the sewage collecting partition and the rainwater collecting partition into a plurality of sub water collecting areas according to the Thiessen polygon principle, and assigning pollution source population data and underlying surface data to different sub water collecting areas to obtain a primary drainage system hydraulic model;
s3: trial calculation of the model:
starting running trial calculation of the model, making a flow (rainfall) measurement scheme according to a trial calculation result, and providing basic data for checking and verifying the model;
specifically, the method comprises the following steps: the method comprises the steps of trial calculation of an arid model and trial calculation of a rainy model: in S3, the population number of the pollution source is input into the model, and the calculation of the drought model is carried out after the resident drainage law curve obtained by combining the resident drainage data is input; meanwhile, the data of the underlying surface is input into the water collection area, the rainfall data input model is imported for a long time to perform trial calculation on the rainy day model, and a trial calculation result is obtained and used for testing the stability of the primary drainage system hydraulic model.
S4: checking a hydraulic model of the primary drainage system: and importing the preset amount of flow monitoring data in dry days and the preset amount of flow monitoring data in rainy days into the primary drainage system hydraulic model to obtain an output result of the primary drainage system hydraulic model, and adjusting parameters of the model according to a preset standard and a trial calculation result, for example, comparing the trial calculation result with the deviation of the sewage treatment plant, the pump station, the drainage pipe network water level, the flow data and an actual operation report simultaneously to adjust the parameters.
S5: inputting historical flow detection data into a parameter-adjusted primary drainage system hydraulic model, and simulating and analyzing the coincidence degree of the output water immersion points and the historical water immersion points; if the preset coincidence degree threshold value is met (determined according to actual requirements), the model does not need to be adjusted again; if the water pressure does not meet the preset drainage system hydraulic model, adjusting the parameters of the model again to obtain the preset drainage system hydraulic model;
the flow monitoring data comprises historical flow monitoring data, a preset number (3 in the embodiment) of flow monitoring data in dry days and flow monitoring data in rainy days, and the preset standard is determined and set in advance according to professional specifications of hydraulic model engineers of a drainage system in the United kingdom and application technical rules of mathematical models of an waterlogging prevention and treatment system.
5) Establishing a preset analysis and evaluation standard system;
the preset analysis and evaluation standard system comprises a drainage system standard (a preset first threshold), wherein the drainage system standard comprises a sewage collection rate threshold, a split flow rate threshold, a pollutant load threshold, a runoff rate threshold, an overflow rate threshold and other data thresholds related to sewage treatment, wherein the sewage collection rate threshold, the split flow rate threshold, the pollutant load threshold, the runoff rate threshold, the overflow rate threshold and the like are contained in pipe network and pump station engineering, storage tank engineering, water quality purification engineering, joint scheduling and the like;
6) analyzing big data;
and importing the typical year continuous rainfall analysis result and the characteristic design rainfall analysis result into a preset drainage system hydraulic model to obtain an output result, wherein the output result comprises data related to sewage treatment, such as sewage collection rate, flow splitting rate, pollutant load, runoff rate, overflow rate and the like. If the output result of the hydraulic model of the preset drainage system after simulation does not meet the preset first threshold, performing big data analysis on the collected data through a big data platform, providing at least one solution, for example, the sewage collection rate does not meet the sewage collection rate threshold, providing solutions for engineering means such as newly building/modifying a sewage plant, newly building a regulation and storage pool, and providing a plurality of different solutions for the situation that different thresholds are not met, wherein each solution comprises specific data of an engineering project.
7) Establishing a preset second threshold;
the preset second threshold value is that the combined system water body pollutant discharge load is not more than the split system water body pollutant discharge load, and the specific formula is as follows:
Wcombination of Chinese herbs≤WIs divided into
WCombination of Chinese herbs＝(Q1×So1+Q2×Se1)/106
WIs divided into＝(Q3×So2+Q4×Se2)/106
In the formula: wCombination of Chinese herbs-pollutant load entering the water in the combined drainage regime area (combined drainage water pollutant load) (t/year);
Wis divided into-pollutant load into the water in the divided drainage regime area (divided drainage into water pollutant load) (t/year);
Q1combined water flow (m) into the body of water in a combined drainage regime3Year);
So1the concentration (mg/L, changes along with rainfall process and the like) of pollutants entering the water body in the combined drainage system area;
Q2water discharge (m) of a sewage treatment plant into a body of water in a combined drainage system area3Year);
Se1entering the concentration (mg/L, annual average value) of the effluent pollutants of the water body sewage plant into the combined drainage system area;
Q3-diversion of the amount of rainfall (m) entering the body of water in the drainage regime3Year);
So2distributing the concentration (mg/L) of rainwater pollutants entering a water body in a drainage system area, wherein the concentration changes along with rainfall process and the like;
Q4water discharge (m) of a sewage treatment plant into a body of water in a separate system drainage zone3Year);
Se2the concentration (mg/L, changes along with rainfall process and the like) of the effluent pollutants entering a water body sewage plant from a shunt drainage system area;
8) determining a final solution
Importing specific data of the solution into a preset drainage system hydraulic model to obtain an updated output result; and judging whether the updating output result meets a preset second threshold value or not, if not, adopting another solution, continuously importing the specific data of the other solution into the preset drainage system hydraulic model, judging whether the preset second threshold value is met or not, and taking the solution as a final solution until the updating output result of one solution meets the preset second threshold value. Wherein, the updating output result comprises the combined water body pollutant discharge load and the split water body pollutant discharge load.
Meanwhile, in another way, when the output result of one solution does not meet the preset second threshold, the specific data of the solution is modified, so that the modified solution meets the preset second threshold as the final solution.
Therefore, the final solution can meet the second preset threshold value under the condition that the final solution meets the first preset threshold value, and the final solution is guaranteed to be effective.
9) Importing specific data of any solution into a drainage system hydraulic model which is finally checked and verified, and comparing a simulation result with an evaluation standard to obtain an evaluation result of the solution; and if the evaluation result is that the simulation result does not meet the evaluation standard, importing other solutions, or importing the solutions into the drainage system hydraulic model after optimizing the solutions until the obtained evaluation result is that the simulation result meets the evaluation standard.
10) Building a display platform;
1. establishing a display platform based on a GIS system in an area to be analyzed;
2. importing the collected data into a display platform for display and query statistics;
3. and displaying the final solution on a display platform, assisting the decision of field scheduling personnel in the area to be analyzed, and providing reference.
The invention also provides a pollution emission reduction analysis system based on big data, which comprises:
the acquisition module is used for acquiring data of the drainage system;
the output module is used for obtaining an output result according to the data of the drainage system and a preset drainage system hydraulic model;
the analysis module is used for providing at least one solution through big data analysis according to the output result and a preset first threshold;
the determining module is used for determining a final solution according to the solution, a preset second threshold and a preset drainage system hydraulic model;
the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, and the preset second threshold value is that the pollutant load of the combined-system discharged water body is not greater than the pollutant load of the split-system discharged water body.
Further, as a preferred embodiment, the method further comprises: and the big data platform is used for providing the big data analysis function.
Further, as a preferred embodiment, the method further comprises: and the display platform is used for displaying and inquiring the data collected by statistics, and is provided with a joint scheduling module for providing a final solution to field scheduling personnel in the area to be analyzed.
The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.
In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flow charts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.
Furthermore, while the invention is described in the context of functional modules and illustrated in the form of block diagrams, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and/or features may be integrated into a single physical device and/or software module or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the invention, which is defined by the appended claims and their full scope of equivalents.
In the description herein, references to the description of the term "one embodiment," "the present embodiment," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (9)
1. The pollution emission reduction analysis method based on big data is characterized by comprising the following steps:
acquiring drainage system data;
obtaining an output result according to the data of the drainage system and a preset hydraulic model of the drainage system;
providing at least one solution through big data analysis according to the output result and a preset first threshold;
determining a final solution according to the solution, a preset second threshold and a preset hydraulic model of the drainage system;
the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, the preset second threshold value is that the pollutant load of the combined system discharged water body is not greater than the pollutant load of the diversion system discharged water body, and the data of the drainage system comprises historical rainfall data.
2. The big-data-based pollution emission reduction analysis method according to claim 1, wherein: further comprising the steps of:
the method for establishing the hydraulic model of the preset drainage system comprises the following steps:
obtaining model building data;
establishing a hydraulic model of the preset drainage system through Infoworks ICM according to the model establishing data;
the model establishing data comprises drainage pipe network GIS data, river channel data, pollution source population data, pump station data, industrial and commercial wastewater data, water level monitoring data, storage tank data, flow monitoring data, overflow port detection data, sewage treatment plant data and underlying surface data.
3. The big-data-based pollution emission reduction analysis method according to claim 2, wherein: the step of establishing the hydraulic model of the preset drainage system through the Infoworks ICM according to the model establishing data comprises the following steps of:
importing drainage pipe network GIS data, river channel data, pump station data, water level monitoring data, flow monitoring data, overflow port detection data, sewage treatment plant data and industrial and commercial wastewater data into a preset data model;
dividing a water collection area according to the topological data and the topographic elevation data of the drainage pipe network to obtain a sewage water collection partition and a rainwater water collection partition;
dividing the sewage water collection partition and the rainwater water collection partition into a plurality of sub water collection areas according to the Thiessen polygon, and introducing pollution source population data and underlay surface data into the sub water collection areas to obtain a primary drainage system hydraulic model;
checking the primary drainage system hydraulic model to obtain a preset drainage system hydraulic model;
the model building data further comprise drainage pipe network topology data and terrain elevation data.
4. The big-data-based pollution emission reduction analysis method according to claim 3, wherein: the step of checking the primary drainage system hydraulic model to obtain the preset drainage system hydraulic model comprises the following steps:
leading the preset number of flow monitoring data in dry days and the preset number of flow monitoring data in rainy days into a primary drainage system hydraulic model;
adjusting parameters according to a preset standard, a primary drainage system hydraulic model output result and historical flow monitoring data to obtain a preset drainage system hydraulic model;
the flow monitoring data comprises historical flow monitoring data, flow monitoring data of a preset number of dry days and flow monitoring data of rainy days.
5. The big-data-based pollution emission reduction analysis method according to claim 2, wherein: further comprising the steps of:
detecting whether the model building data is missing or not, if so, acquiring missing data and importing the missing data into a preset data model;
the model building data further comprises missing data, and the missing data comprises at least one of radar detection data or actual measurement data, endoscopic detection data and drainage pipe network construction drawing data acquired through CCTV.
6. The big-data-based pollution emission reduction analysis method according to claim 1, wherein: the step of acquiring the data of the drainage system comprises the following steps:
acquiring a typical year continuous rainfall analysis result and a characteristic design rainfall analysis result;
the method comprises the following steps of obtaining a typical year continuous rainfall analysis result:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
obtaining the monthly average rainfall capacity and the monthly average rainfall days according to historical rainfall data;
obtaining a typical year continuous rainfall analysis result consisting of a rainfall typical month according to the average monthly rainfall and the average monthly rainfall days;
the steps for obtaining the characteristic design rainfall analysis result are as follows:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
carrying out classified statistics on historical rainfall data according to a preset time interval and a preset rainfall interval to obtain rainfall times and frequency distribution results of the preset rainfall interval;
according to the rainfall times and the frequency distribution result, a characteristic rainfall and rainfall duration statistical result is obtained through SCS model synthesis;
wherein, the drainage system data comprises typical year continuous rainfall analysis results and characteristic design rainfall analysis results.
7. The big-data-based pollution emission reduction analysis method according to claim 6, wherein: the step of obtaining an output result according to the data of the drainage system and the preset hydraulic model of the drainage system comprises the following specific steps:
importing the typical year continuous rainfall analysis result and the characteristic design rainfall analysis result into a preset drainage system hydraulic model to obtain an output result;
the drainage system data comprises typical year continuous rainfall analysis results and characteristic design rainfall analysis results, and the output results comprise at least one of sewage collection rate, split flow rate, pollutant load, runoff rate and overflow rate.
8. The big-data-based pollution emission reduction analysis method according to claim 1, wherein: the step of determining the final solution according to the solution, the preset second threshold and the preset hydraulic model of the drainage system comprises the following steps:
importing specific data of the solution into a preset drainage system hydraulic model to obtain an updated output result;
judging whether the updating output result meets a preset second threshold value or not, if not, adopting another solution, returning a step of importing specific data of the solution into a preset drainage system hydraulic model according to specific data of the other solution, importing the preset drainage system hydraulic model to obtain an updating output result, and determining a final solution until the updating output result meets the preset second threshold value;
wherein, the update output result comprises the combined system water body pollutant discharge load and the split system water body pollutant discharge load, the solution has specific data, and the specific data comprises engineering project data.
9. Pollution emission reduction analytic system based on big data, characterized by includes:
the acquisition module is used for acquiring data of the drainage system;
the output module is used for obtaining an output result according to the data of the drainage system and a preset drainage system hydraulic model;
the analysis module is used for providing at least one solution through big data analysis according to the output result and a preset first threshold;
the determining module is used for determining a final solution according to the solution, a preset second threshold and a preset drainage system hydraulic model;
the preset first threshold value comprises at least one of a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value and an overflow rate threshold value, and the preset second threshold value is that the pollutant load of the combined-system discharged water body is not greater than the pollutant load of the split-system discharged water body.
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