CN111709108B - 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 a system based on big data, wherein the method comprises the following steps: acquiring drainage system data; obtaining an output result according to drainage system data and a preset drainage system hydraulic model; providing at least one solution through big data analysis according to the output result and a preset first threshold value; determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model; the 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 second threshold value is preset to ensure that the pollutant load of the combined system discharged into the water body is not larger than the pollutant load of the diversion system discharged into the water body. The invention can provide an effective final solution and can effectively solve the problem of emission reduction of pollutant load of the water body discharged by the combined system. 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
Because the research of the drainage industry in China starts later, most of the drainage industries still adopt the traditional analysis method to carry out hydraulic simulation. At present, as the research on dynamic models of drainage systems gradually appears, most drainage industries start gradually transitioning 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 comprise pollutant emission reduction, and fail to propose effective solutions.
Disclosure of Invention
In view of the above, 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 drainage system data and a preset drainage system hydraulic model;
providing at least one solution through big data analysis according to the output result and a preset first threshold value;
determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model;
the first threshold value is preset and 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 second threshold value is preset and comprises historical rainfall data when pollutant loads of the water bodies discharged through a combined system are not larger than pollutant loads of the water bodies discharged through the diversion system.
Further, the method also comprises the following steps: establishing a hydraulic model of a preset drainage system, which comprises the following steps:
obtaining model building data;
establishing data according to the model, and establishing a hydraulic model of a preset drainage system through the Inforks ICM;
the model building data comprise drainage pipe network GIS data, river channel data, pollution source population data, pump station data, industrial and commercial wastewater data, water level monitoring data, regulation and 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 Infoorks ICM according to the model establishment data comprises the following steps:
the method comprises the steps of importing 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 of a drainage pipe network into a preset data model;
dividing a water collecting area according to the topology data and the topography elevation data of the drainage pipe network to obtain a sewage water collecting partition and a rainwater water collecting partition;
dividing the sewage water collecting partition and the rainwater water collecting partition into a plurality of sub-water collecting areas according to Thiessen polygons, and importing pollution source population data and underlying surface data into the sub-water collecting 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 also comprises drainage pipe network topology data and terrain elevation data.
Further, in the step of checking the primary drainage system hydraulic model to obtain the preset drainage system hydraulic model, the method comprises the following steps:
leading the flow monitoring data of a preset number of dry days and the flow monitoring data of a rainy day into a primary drainage system hydraulic model;
according to a preset standard, an output result of the primary drainage system hydraulic model and historical flow monitoring data, carrying out parameter adjustment to obtain a preset drainage system hydraulic model;
the flow monitoring data comprise 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 has a defect or not, if so, acquiring the defect data and importing the defect data into a preset data model;
the model building data further comprise missing data, wherein the missing data comprise radar detection data or at least one of actual measurement data obtained through CCTV, endoscopic detection data and drainage pipe network construction drawing data.
Further, the step of acquiring drainage system data includes:
acquiring model year continuous rainfall analysis results and characteristic design rainfall analysis results;
the method comprises the following steps of:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
obtaining the average rainfall and the average rainfall days according to the historical rainfall data;
according to the average rainfall and the average rainfall days, a model year continuous rainfall analysis result consisting of typical rainfall months is obtained;
the rainfall analysis result of the characteristic design is obtained by the following steps:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
classifying and counting the 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, synthesizing through an SCS model to obtain a characteristic rainfall and rainfall duration statistical result;
the drainage system data comprise model year continuous rainfall analysis results and characteristic design rainfall analysis results.
Further, in the step of obtaining an output result according to the drainage system data and the preset drainage system hydraulic model, the method specifically comprises the following steps:
the model year continuous rainfall analysis result and the characteristic design rainfall analysis result are imported into a preset drainage system hydraulic model to obtain an output result;
the drainage system data comprise model year continuous rainfall analysis results and characteristic design rainfall analysis results, and the output results comprise at least one of sewage collection rate, flow dividing rate, pollutant load, runoff and overflow rate.
Further, the step of determining the final solution according to the solution, the preset second threshold value and the preset hydraulic model of the drainage system includes:
specific data of the solution are imported into a preset drainage system hydraulic model to obtain updated output results;
judging whether the updated 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 the updated output result until the updated output result meets the preset second threshold value, and determining a final solution;
the method comprises the steps of updating output results, wherein the updating output results comprise the loads of pollutants discharged into the water body in a combined system and the loads of pollutants discharged into the water body in a split system, the solution has specific data, and the specific data comprise engineering project data.
The invention also provides a pollution emission reduction analysis system based on big data, which comprises:
the acquisition module is used for acquiring drainage system data;
the output module is used for obtaining an output result according to the drainage system data 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 value;
the determining module is used for determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model;
the first threshold value is preset and 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 second threshold value is preset and comprises historical rainfall data, the pollutant load of the combined system discharged into the water body is not larger than that of the combined system discharged into the water body, and the drainage system data comprise historical rainfall data.
The beneficial effects of the invention are as follows: according to the drainage system data and the preset drainage system hydraulic model, an output result is obtained, problems existing in the output result can be evaluated according to the preset first threshold value and the output result, at least one solution is provided through big data analysis, a specific solution can be provided according to the problems existing in the output result, a final solution is determined according to the solution, the preset second threshold value and the preset drainage system hydraulic model, whether the solution meets the standard can be verified, an effective final solution is provided, and the problem of emission reduction of pollutant loads of the water body discharged through the combined system can be effectively solved.
Drawings
FIG. 1 is a schematic flow chart of the steps of the method of the present invention;
FIG. 2 is a flow chart of the steps of an embodiment of the present invention.
Detailed Description
The invention is further explained and illustrated below with reference to the drawing and the specific embodiments of the present specification. The step numbers in the embodiments of the present invention are set for convenience of illustration, and the order of steps is not limited in any way, and the execution order of the steps 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 comprises the following steps:
acquiring drainage system data;
obtaining an output result according to drainage system data and a preset drainage system hydraulic model;
providing at least one solution through big data analysis according to the output result and a preset first threshold value;
determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model;
the 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 second threshold value is preset to ensure that the pollutant load of the combined system discharged into the water body is not larger than the pollutant load of the diversion system discharged into the water body.
As shown in fig. 2, in this embodiment, specifically, the method includes the steps of:
1) Collecting data;
the collected data comprises drainage system data and model building data;
the model building data comprise drainage pipe network GIS data, river channel data (comprising converging water quantity data of a converging drainage system area entering a water body, rainwater quantity data of a diverging drainage system area entering the water body, converging water pollutant concentration data of the converging drainage system area entering the water body, splitting water pollutant concentration data of the diverging drainage system area entering the water body), pump station data, industrial and commercial wastewater data, water level monitoring data, flow monitoring data, overflow port detection data and sewage treatment plant data (comprising sewage treatment plant water yield data of the converging drainage system area entering the water body, converging water discharge pollutant concentration data of the converging water treatment plant entering the water body, splitting water discharge pollutant concentration data of the converging water discharge system area entering the water body), resident water discharge data, drainage topology data and water level, flow data, terrain elevation data, underlying surface data, regulation and storage tank data and missing data (comprising radar detection data or actual measurement data acquired through CCTV, internal detection data and drainage pipe network construction drawing data); wherein the water body can be river or lake.
The drainage system data comprise historical rainfall data, model year continuous rainfall analysis results and characteristic design rainfall analysis results;
the collected data can be built and stored in a data standard mapping file mode for automatic or manual introduction of the system.
2) Continuous rainfall analysis and characteristic design rainfall analysis are carried out in model years according to rainfall data;
the model year continuous rainfall analysis steps:
1. collecting a preset time threshold value (10 years in the embodiment, and including 10 years of historical rainfall data of minutes or hours as samples for carrying out statistics on the total amount of rainfall and the number of days of rainfall in a month to be analyzed) of a central rainfall station in a drainage area to be analyzed, and obtaining the average rainfall and the number of days of rainfall in the month of the samples;
2. and selecting the month closest to the average rainfall and the average rainfall days in the month from the samples, taking the month as a typical rainfall month, and recombining the month to form a typical artificial rainfall year, namely obtaining a model year continuous rainfall analysis result, wherein the model year continuous rainfall analysis result represents average rainfall characteristics of a plurality of years.
And a characteristic design rainfall analysis step:
1. collecting a preset time threshold value (10 years in the embodiment, and including 10 years of historical rainfall data of minutes or hours) of a central rainfall station of an area to be analyzed, defining a rainfall according to a preset time interval of 12 hours, and carrying out statistical analysis on rainfall and rainfall duration;
2. carrying out interval classification statistics on the rainfall and rainfall duration data subjected to statistical analysis according to 5 preset rainfall intervals of 0-5mm,5-10mm,10-20mm,20-30mm,30-45mm and 45mm, obtaining rainfall times and frequency distribution of each interval, obtaining frequency distribution of different rainfall intervals, and taking rainfall duration obtained by calculating the median rainfall of each interval as the characteristic rainfall and rainfall duration of the interval to obtain a preliminary result;
3. and 6 rainfall interval preliminary results are synthesized by adopting an SCS model, and characteristic rainfall and rainfall duration statistical results are obtained.
3) Analyzing the change of the concentration of the surface runoff pollutants;
1. the monitoring data of typical combined overflow ports and split rainwater drainage ports of the built-up areas of the cities and the new built-up areas of the cities are obtained through manual sampling or automatic sampling, wherein the monitoring data are water quality concentration data which are obtained by monitoring more than 6 different rainfall conditions at intervals of 5 minutes, wherein the different rainfall 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. According to the monitoring data, obtaining the relation between rainfall time and water quality concentration change:
the curve of the relation between rainfall duration and water quality concentration change and the model simulation are used for obtaining an overflow quantity-time change curve to be fitted for analysis and calculation of total overflow pollutant (load);
4) Establishing a hydraulic model of a preset drainage system by utilizing the collected data;
the data model establishment according to the Inoworks ICM tool comprises the following steps:
s1: the method comprises the 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 (the Information and Communication Modules (ICM) are contained in the information and the commercial wastewater data);
s2: detecting whether data loss exists or not, if the data added in the previous step is detected to exist, importing the missing data to ensure the integrity of the data, for example, importing the data according to pipe network construction drawing data, endoscopic detection data or adopting a field stepping mode if a pipe network with an unknown data relationship exists, and ensuring the clear pipe network connection relationship of the model;
s3: dividing a water collecting region into a sewage water collecting region and a rainwater water collecting region according to drainage pipe network topology data and terrain elevation data of a region to be analyzed, dividing the sewage water collecting region and the rainwater water collecting region into a plurality of sub-water collecting regions according to the Thiessen polygon principle, and assigning pollution source population data and underlying surface data to different sub-water collecting regions to obtain a primary drainage system hydraulic model;
s3: model trial calculation:
starting running trial calculation of the model, and making a flow (rainfall) measurement scheme according to a trial calculation result to provide basic data for checking and verifying the model;
specifically: the method comprises trial calculation of a dry-weather model and trial calculation of a rainy-weather model: s3, inputting the population number of the pollution source into the model, and carrying out trial calculation of a dry day model after combining a resident drainage rule curve obtained by resident drainage data; meanwhile, under-pad data are input in the water collecting area, and the rainfall data input model is imported for trial calculation of the rainy day model, so that a trial calculation result is obtained and used for testing the stability of the primary drainage system hydraulic model.
S4: checking the hydraulic model of the primary drainage system: and importing the flow monitoring data of the preset number of dry days and the flow monitoring data of the rainy days into a hydraulic model of the primary drainage system to obtain an output result of the hydraulic model of the primary drainage system, and adjusting parameters of the model according to preset standards and trial calculation results, for example, simultaneously comparing the trial calculation results with deviations of water levels of sewage treatment plants, pump stations, drainage pipe network, flow data and actual operation reports, and adjusting the parameters.
S5: inputting the historical flow detection data into a primary drainage system hydraulic model with adjusted parameters, and simulating the coincidence degree of the analyzed output water immersion point and the historical water immersion point; if the preset coincidence degree threshold value (determined according to actual requirements) is met, the model does not need to be adjusted again; if not, parameter adjustment of the model is carried out again to obtain a hydraulic model of the preset drainage system;
the flow monitoring data comprise historical flow monitoring data, and a preset number (3) of flow monitoring data of dry days and flow monitoring data of rainy days, and preset standards are determined and set in advance according to the British drainage system hydraulic model engineer occupational Specification and the waterlogging control system mathematical model application technical rules.
5) Establishing a preset analysis evaluation standard system;
the preset analysis and evaluation standard system comprises a drainage system standard (a preset first threshold value), wherein the drainage system standard comprises a sewage collection rate threshold value, a diversion rate threshold value, a pollutant load threshold value, a runoff rate threshold value, an overflow rate threshold value and other data threshold values related to sewage treatment, wherein the sewage collection rate threshold value, the diversion rate threshold value, the pollutant load threshold value, the runoff rate threshold value, the overflow rate threshold value and the like are included in pipe network and pump station engineering, a regulation and storage pool engineering, a water quality purification engineering, joint scheduling and the like;
6) Big data analysis;
and importing the model 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 dividing rate, pollutant load, runoff amount, 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 value, carrying out 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 value, providing solutions of engineering means such as newly built/modified sewage plants and newly built regulating reservoirs, and providing a plurality of different solutions aiming at the condition that the different threshold values are not met, wherein each solution comprises specific data of engineering projects.
7) Establishing a preset second threshold value;
the second threshold value is preset to be that the pollutant load of the water body discharged by the combined system is not larger than the pollutant load of the water body discharged by the split system, and the specific formula is as follows:
W closing device ≤W Dividing into
W Closing device ＝(Q 1 ×S o1 +Q 2 ×S e1 )/10 6
W Dividing into ＝(Q 3 ×S o2 +Q 4 ×S e2 )/10 6
Wherein: w (W) Closing device Pollutant load of the combined drainage system area entering the water body (pollutant load of the combined drainage system into the water body) (t/year);
W dividing into -diverting the pollutant load of the drainage regime zone into the body of water (diverting the pollutant load of the drainage into the body of water) (t/year);
Q 1 the amount of the combined water (m) entering the water body in the combined drainage system area 3 Year);
S o1 the concentration (mg/L, change along with rainfall process and the like) of pollutants entering the water body in the combined drainage system area;
Q 2 water yield (m) of sewage treatment plant entering water body in combined drainage system area 3 Year);
S e1 the concentration (mg/L, annual average) of effluent pollutants entering a water body sewage plant in a combined drainage system area;
Q 3 rainwater quantity (m) entering water body in diversion drainage system area 3 Year);
S o2 the concentration (mg/L, change along with rainfall process and the like) of pollutants entering the rainwater of the water body in the diversion drainage system area;
Q 4 the water yield (m) of sewage treatment plant entering water body in diversion drainage system area 3 Year);
S e2 the concentration (mg/L, change along with rainfall process and the like) of effluent pollutants entering a water body sewage plant from a diversion drainage system area;
8) Determining a final solution
Specific data of the solution are imported into a preset drainage system hydraulic model to obtain updated output results; judging whether the updated output result meets a preset second threshold value, if not, adopting another solution, continuously importing specific data of the other solution into a hydraulic model of a preset drainage system, judging whether the updated output result of one solution meets the preset second threshold value, and taking the solution as a final solution. The output result updating comprises the pollutant load of the water body discharged by the combined system and the pollutant load of the water body discharged by the split system.
Meanwhile, when the output result of one solution does not meet the preset second threshold, the specific data of the solution is corrected, so that the corrected solution meets the preset second threshold, and the corrected solution is used as a final solution.
Therefore, the final solution can meet the second preset threshold value again under the condition of meeting the first preset threshold value, and the final solution is ensured to be effective.
9) Specific data of any solution is imported into a final check and verification drainage system hydraulic model, and a simulation result is compared with an evaluation standard to obtain an evaluation result of the solution; if the evaluation result is that the simulation result does not meet the evaluation standard, other solutions are imported, or the solution is optimized and then imported into the hydraulic model of the drainage system 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 the 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 in the decision-making of field scheduling personnel in the area to be analyzed, and providing a reference.
The invention also provides a pollution emission reduction analysis system based on big data, which comprises:
the acquisition module is used for acquiring drainage system data;
the output module is used for obtaining an output result according to the drainage system data 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 value;
the determining module is used for determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model;
the 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 second threshold value is preset to ensure that the pollutant load of the combined system discharged into the water body is not larger than the pollutant load of the diversion system discharged into the 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: 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 content in the method embodiment is applicable to the system embodiment, the functions specifically realized by the system embodiment are the same as those of the method embodiment, and the achieved beneficial effects are the same as those of the method embodiment.
In some 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 flowcharts 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 a larger operation are performed independently.
Furthermore, while the invention has been described in the context of functional modules and illustrated in block diagram form, it should be appreciated that one or more of the described functions and/or features may be integrated in a single physical device and/or software module or one or more functions and/or features may be implemented in separate physical devices or software modules unless otherwise specified. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary to an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be apparent to those skilled in the art from consideration of their attributes, functions and internal relationships. Accordingly, one of ordinary skill in the art can implement 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 and are not intended to be limiting upon the scope of the invention, which is to be defined in the appended claims and their full scope of equivalents.
In the description of the present specification, a description referring to the terms "one embodiment," "this embodiment," "example," "a specific example," or "some examples," etc., means 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, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. 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 embodiment of the present invention has been described in detail, the present invention is not limited to the embodiments described above, and various equivalent modifications and substitutions can be made by those skilled in the art without departing from the spirit of the present invention, and these equivalent modifications and substitutions are intended to be included in the scope of the present invention as defined in the appended claims.
Claims (8)
1. The pollution emission reduction analysis method based on big data is characterized by comprising the following steps of:
acquiring drainage system data;
the step of acquiring drainage system data includes:
acquiring model year continuous rainfall analysis results and characteristic design rainfall analysis results;
the method comprises the following steps of:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
obtaining the average rainfall and the average rainfall days according to the historical rainfall data;
according to the average rainfall and the average rainfall days, a model year continuous rainfall analysis result consisting of typical rainfall months is obtained;
the rainfall analysis result of the characteristic design is obtained by the following steps:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
classifying and counting the 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, synthesizing through an SCS model to obtain a characteristic rainfall and rainfall duration statistical result;
the drainage system data comprise model year continuous rainfall analysis results and characteristic design rainfall analysis results;
obtaining an output result according to drainage system data and a preset drainage system hydraulic model;
providing at least one solution through big data analysis according to the output result and a preset first threshold value;
determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model; the first threshold value is preset and 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 second threshold value is preset and comprises historical rainfall data when pollutant loads of the water bodies discharged through a combined system are not larger than pollutant loads of the water bodies discharged through the diversion system.
2. The pollution emission reduction analysis method based on big data according to claim 1, wherein: the method also comprises the following steps: establishing a hydraulic model of a preset drainage system, which comprises the following steps:
obtaining model building data;
establishing data according to the model, and establishing a hydraulic model of a preset drainage system through the Inforks ICM;
the model building data comprise drainage pipe network GIS data, river channel data, pollution source population data, pump station data, industrial and commercial wastewater data, water level monitoring data, regulation and storage tank data, flow monitoring data, overflow port detection data, sewage treatment plant data and underlying surface data.
3. The pollution emission reduction analysis method based on big data according to claim 2, wherein: in the step of establishing the hydraulic model of the preset drainage system through the Infoorks ICM according to the model establishment data,
the method comprises the following steps:
the method comprises the steps of importing 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 of a drainage pipe network into a preset data model;
dividing a water collecting area according to the topology data and the topography elevation data of the drainage pipe network to obtain a sewage water collecting partition and a rainwater water collecting partition;
dividing the sewage water collecting partition and the rainwater water collecting partition into a plurality of sub-water collecting areas according to Thiessen polygons, and importing pollution source population data and underlying surface data into the sub-water collecting 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 also comprises drainage pipe network topology data and terrain elevation data.
4. The pollution emission reduction analysis method based on big data 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 flow monitoring data of a preset number of dry days and the flow monitoring data of a rainy day into a primary drainage system hydraulic model;
according to a preset standard, an output result of the primary drainage system hydraulic model and historical flow monitoring data, carrying out parameter adjustment to obtain a preset drainage system hydraulic model;
the flow monitoring data comprise historical flow monitoring data, flow monitoring data of a preset number of dry days and flow monitoring data of rainy days.
5. The pollution emission reduction analysis method based on big data according to claim 2, wherein: the method also comprises the following steps:
detecting whether the model building data has a defect or not, if so, acquiring the defect data and importing the defect data into a preset data model; the model building data further comprise missing data, wherein the missing data comprise radar detection data or at least one of actual measurement data obtained through CCTV, endoscopic detection data and drainage pipe network construction drawing data.
6. The pollution emission reduction analysis method based on big data according to claim 5, wherein: according to the drainage system data and a preset drainage system hydraulic model, the output result is obtained, specifically: the model year continuous rainfall analysis result and the characteristic design rainfall analysis result are imported into a preset drainage system hydraulic model to obtain an output result;
the drainage system data comprise model year continuous rainfall analysis results and characteristic design rainfall analysis results, and the output results comprise at least one of sewage collection rate, flow dividing rate, pollutant load, runoff and overflow rate.
7. The pollution emission reduction analysis method based on big data according to claim 1, wherein: the step of determining the final solution according to the solution, the preset second threshold value and the preset hydraulic model of the drainage system comprises the following steps:
specific data of the solution are imported into a preset drainage system hydraulic model to obtain updated output results;
judging whether the updated 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 the updated output result until the updated output result meets the preset second threshold value, and determining a final solution;
the method comprises the steps of updating output results, wherein the updating output results comprise the loads of pollutants discharged into the water body in a combined system and the loads of pollutants discharged into the water body in a split system, the solution has specific data, and the specific data comprise engineering project data.
8. Pollution emission reduction analysis system based on big data, characterized by comprising:
the acquisition module is used for acquiring drainage system data;
the obtaining module is configured to, in the step of obtaining drainage system data, include:
acquiring model year continuous rainfall analysis results and characteristic design rainfall analysis results;
the method comprises the following steps of:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
obtaining the average rainfall and the average rainfall days according to the historical rainfall data;
according to the average rainfall and the average rainfall days, a model year continuous rainfall analysis result consisting of typical rainfall months is obtained;
the rainfall analysis result of the characteristic design is obtained by the following steps:
acquiring historical rainfall data of a preset time threshold value in minutes or hours;
classifying and counting the 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, synthesizing through an SCS model to obtain a characteristic rainfall and rainfall duration statistical result;
the drainage system data comprise model year continuous rainfall analysis results and characteristic design rainfall analysis results;
the output module is used for obtaining an output result according to the drainage system data 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 value;
the determining module is used for determining a final solution according to the solution, a preset second threshold value and a preset drainage system hydraulic model;
the 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 second threshold value is preset to ensure that the pollutant load of the combined system discharged into the water body is not larger than the pollutant load of the diversion system discharged into the water body.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101692273A (en) * | 2009-09-28 | 2010-04-07 | 北京工业大学 | Modeling method of on-line hydraulic model of municipal drainage pipe network |
| CN105426346A (en) * | 2015-11-15 | 2016-03-23 | 北京工业大学 | Water conservancy rainfall pattern peak-based city long-duration design rainstorm rainfall pattern creation method |
| CN106382471A (en) * | 2016-11-25 | 2017-02-08 | 上海市城市排水有限公司 | Municipal drainage pipe network diagnostic assessment method giving consideration to key node |
| CN106650053A (en) * | 2016-12-06 | 2017-05-10 | 北京工业大学 | USRAMS-based optimization design method of rainwater pipe network |
| CN107368623A (en) * | 2017-06-06 | 2017-11-21 | 西安建筑科技大学 | A kind of pool volume of regulating and storing based on runoff pollution control determines method |
| CN107832931A (en) * | 2017-10-31 | 2018-03-23 | 上海市政工程设计研究总院（集团）有限公司 | A kind of Modularity analysis method of plain river network region waterlogging risk |
| CN109114430A (en) * | 2018-09-26 | 2019-01-01 | 东莞青柳新材料有限公司 | A kind of urban drainage pipe network on-line monitoring system |
| CN109284873A (en) * | 2018-10-15 | 2019-01-29 | 上海凯泉泵业（集团）有限公司 | A kind of wisdom drainage pumping plant carrying out pump group Optimized Operation and early warning disposition based on SWMM model |
| CN109784746A (en) * | 2019-01-25 | 2019-05-21 | 东南大学 | Urban-rural water supply network waterpower simulation of water quality platform |
| CN109800529A (en) * | 2019-01-31 | 2019-05-24 | 福州城建设计研究院有限公司 | A kind of parameter based on InfoWorks ICM water quality model is from rating method |
-
2019
- 2019-12-27 CN CN201911374469.0A patent/CN111709108B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101692273A (en) * | 2009-09-28 | 2010-04-07 | 北京工业大学 | Modeling method of on-line hydraulic model of municipal drainage pipe network |
| CN105426346A (en) * | 2015-11-15 | 2016-03-23 | 北京工业大学 | Water conservancy rainfall pattern peak-based city long-duration design rainstorm rainfall pattern creation method |
| CN106382471A (en) * | 2016-11-25 | 2017-02-08 | 上海市城市排水有限公司 | Municipal drainage pipe network diagnostic assessment method giving consideration to key node |
| CN106650053A (en) * | 2016-12-06 | 2017-05-10 | 北京工业大学 | USRAMS-based optimization design method of rainwater pipe network |
| CN107368623A (en) * | 2017-06-06 | 2017-11-21 | 西安建筑科技大学 | A kind of pool volume of regulating and storing based on runoff pollution control determines method |
| CN107832931A (en) * | 2017-10-31 | 2018-03-23 | 上海市政工程设计研究总院（集团）有限公司 | A kind of Modularity analysis method of plain river network region waterlogging risk |
| CN109114430A (en) * | 2018-09-26 | 2019-01-01 | 东莞青柳新材料有限公司 | A kind of urban drainage pipe network on-line monitoring system |
| CN109284873A (en) * | 2018-10-15 | 2019-01-29 | 上海凯泉泵业（集团）有限公司 | A kind of wisdom drainage pumping plant carrying out pump group Optimized Operation and early warning disposition based on SWMM model |
| CN109784746A (en) * | 2019-01-25 | 2019-05-21 | 东南大学 | Urban-rural water supply network waterpower simulation of water quality platform |
| CN109800529A (en) * | 2019-01-31 | 2019-05-24 | 福州城建设计研究院有限公司 | A kind of parameter based on InfoWorks ICM water quality model is from rating method |
Non-Patent Citations (2)
| Title |
|---|
| 华蓝设计（集团）有限公司等.《海绵城市工程实用手册-低影响开发雨水控制及利用》.广西师范大学出版社,2016,第20页. * |
| 方正 ; 刘非 ; 肖雪莲 ; 唐智 ; .基于城市综合流域排水模型的地铁站防洪模拟研究.武汉大学学报(工学版).(第01期),第60-65页. * |
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