CN115048475A - Rapid water pollution source tracing method and system based on big data - Google Patents
Rapid water pollution source tracing method and system based on big data Download PDFInfo
- Publication number
- CN115048475A CN115048475A CN202210650534.3A CN202210650534A CN115048475A CN 115048475 A CN115048475 A CN 115048475A CN 202210650534 A CN202210650534 A CN 202210650534A CN 115048475 A CN115048475 A CN 115048475A
- Authority
- CN
- China
- Prior art keywords
- water
- pollution
- quality detection
- water quality
- map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003911 water pollution Methods 0.000 title claims abstract description 85
- 238000000034 method Methods 0.000 title claims abstract description 37
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 344
- 238000001514 detection method Methods 0.000 claims abstract description 155
- 238000005070 sampling Methods 0.000 claims abstract description 111
- 230000002159 abnormal effect Effects 0.000 claims abstract description 104
- 238000012544 monitoring process Methods 0.000 claims abstract description 72
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 63
- 231100000719 pollutant Toxicity 0.000 claims abstract description 63
- 238000004519 manufacturing process Methods 0.000 claims abstract description 41
- 238000009826 distribution Methods 0.000 claims abstract description 37
- 239000003643 water by type Substances 0.000 claims abstract description 10
- 230000005856 abnormality Effects 0.000 claims description 5
- 238000011156 evaluation Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 5
- 230000002194 synthesizing effect Effects 0.000 claims description 2
- 230000002547 anomalous effect Effects 0.000 claims 1
- 238000012372 quality testing Methods 0.000 abstract description 16
- 230000008859 change Effects 0.000 abstract description 11
- 238000010586 diagram Methods 0.000 description 8
- 239000010865 sewage Substances 0.000 description 7
- UHOVQNZJYSORNB-UHFFFAOYSA-N Benzene Chemical compound C1=CC=CC=C1 UHOVQNZJYSORNB-UHFFFAOYSA-N 0.000 description 3
- LYCAIKOWRPUZTN-UHFFFAOYSA-N Ethylene glycol Chemical compound OCCO LYCAIKOWRPUZTN-UHFFFAOYSA-N 0.000 description 3
- 238000007599 discharging Methods 0.000 description 3
- 230000002265 prevention Effects 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 2
- 239000000356 contaminant Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000001301 oxygen Substances 0.000 description 2
- 229910052760 oxygen Inorganic materials 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 230000001360 synchronised effect Effects 0.000 description 2
- SCYULBFZEHDVBN-UHFFFAOYSA-N 1,1-Dichloroethane Chemical compound CC(Cl)Cl SCYULBFZEHDVBN-UHFFFAOYSA-N 0.000 description 1
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 description 1
- LSDPWZHWYPCBBB-UHFFFAOYSA-N Methanethiol Chemical compound SC LSDPWZHWYPCBBB-UHFFFAOYSA-N 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 239000003513 alkali Substances 0.000 description 1
- 229910052785 arsenic Inorganic materials 0.000 description 1
- RQNWIZPPADIBDY-UHFFFAOYSA-N arsenic atom Chemical compound [As] RQNWIZPPADIBDY-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 229910052793 cadmium Inorganic materials 0.000 description 1
- BDOSMKKIYDKNTQ-UHFFFAOYSA-N cadmium atom Chemical compound [Cd] BDOSMKKIYDKNTQ-UHFFFAOYSA-N 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000011109 contamination Methods 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 239000003651 drinking water Substances 0.000 description 1
- 235000020188 drinking water Nutrition 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 229910000037 hydrogen sulfide Inorganic materials 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- QSHDDOUJBYECFT-UHFFFAOYSA-N mercury Chemical compound [Hg] QSHDDOUJBYECFT-UHFFFAOYSA-N 0.000 description 1
- 229910052753 mercury Inorganic materials 0.000 description 1
- 244000005700 microbiome Species 0.000 description 1
- 239000007800 oxidant agent Substances 0.000 description 1
- 230000001590 oxidative effect Effects 0.000 description 1
- 239000002574 poison Substances 0.000 description 1
- 231100000614 poison Toxicity 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/248—Presentation of query results
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Health & Medical Sciences (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Economics (AREA)
- Medicinal Chemistry (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Food Science & Technology (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Computational Linguistics (AREA)
- Biochemistry (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Remote Sensing (AREA)
- Sampling And Sample Adjustment (AREA)
Abstract
The embodiment of the invention relates to the technical field of water pollution source tracing, and particularly discloses a quick water pollution source tracing method and system based on big data. The embodiment of the invention determines a plurality of abnormal pollutants by carrying out multi-position equidistant point distribution sampling and water quality detection; drawing a water quality detection map; carrying out water area pollution capture and determining a polluted water area; acquiring enterprise production information of a polluted water area; and tracing the relevance of water pollution and marking pollution source enterprises. Can equidistance stationing sampling and water quality testing, confirm a plurality of unusual pollutants, according to sampling location and waters monitoring, draw the water quality testing map, thereby carry out the waters pollution on the water quality testing map and catch, confirm the polluted water area, and combine the enterprise production information in polluted water area, carry out the water pollution associativity and trace to the source, confirm the pollution source enterprise, thereby need not to carry out more intensive water quality testing in the unusual region of water pollution, the water pollution traces to the source faster, and do not receive the influence of rivers change, the water pollution traces to the source more accurately.
Description
Technical Field
The invention belongs to the technical field of water pollution source tracing, and particularly relates to a rapid water pollution source tracing method and system based on big data.
Background
Water pollution is water that causes a reduction or loss in the use value of water due to harmful chemicals, and pollutes the environment. Acid, alkali and oxidant in the sewage, compounds such as copper, cadmium, mercury, arsenic and the like, and organic poisons such as benzene, dichloroethane, ethylene glycol and the like can kill aquatic organisms, and influence drinking water sources and scenic spots. When the organic matters in the sewage are decomposed by microorganisms, oxygen in the sewage is consumed, so that the life of aquatic organisms is influenced, and after dissolved oxygen in the sewage is exhausted, the organic matters are subjected to anaerobic decomposition to generate unpleasant gases such as hydrogen sulfide and mercaptan, so that the water quality is further deteriorated. The water pollution prevention and control is a complex system project, various problems in the water pollution prevention and control need refined countermeasures, and the water pollution is regarded as 'treatment' and 'prevention' more.
A water pollution tracing method is a method for positioning enterprises causing water pollution when water pollution exists, and can be used for investigating discharge enterprises along rivers, determining enterprises related to water pollution and eliminating illegal sewage discharge sources. However, the existing water pollution tracing method usually analyzes water quality detection data to determine a rough water pollution abnormal area, and further performs intensive water quality detection in the water pollution abnormal area to determine water pollution accident-related enterprises.
Disclosure of Invention
The embodiment of the invention aims to provide a rapid water pollution tracing method and system based on big data, and aims to solve the problems in the background art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a rapid water pollution tracing method based on big data specifically comprises the following steps:
carrying out multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and carrying out anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants;
carrying out equidistant point distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map;
according to the abnormal pollutants, carrying out water area pollution capture on the water quality detection map to determine a polluted water area;
acquiring enterprise production information of the polluted water area based on big data;
and tracing the water pollution relevance according to the enterprise production information and the abnormal pollutants, and marking pollution source enterprises.
As a further limitation of the technical solution of the embodiment of the present invention, the performing equidistant multi-position point sampling and water quality detection to obtain water quality detection data, and performing anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants specifically includes the following steps:
carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples;
detecting a plurality of water quality detection samples to obtain water quality detection data;
performing anomaly analysis according to the water quality detection data to determine a plurality of anomalies;
and analyzing the pollution contribution of a plurality of abnormal matters, and marking a plurality of abnormal pollutants.
As a further limitation of the technical scheme of the embodiment of the invention, the steps of equidistantly arranging sampling and positioning, monitoring the water area, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain the water quality detection map specifically comprise the following steps:
carrying out equidistant point distribution sampling positioning to obtain sampling positioning data;
drawing a basic water area map according to the sampling positioning data;
monitoring a water area according to the basic water area map, and drawing a water area monitoring map;
and synthesizing the water area monitoring map and the water quality detection data to obtain a water quality detection map.
As a further limitation of the technical solution of the embodiment of the present invention, the determining a polluted water area by capturing the water area pollution on the water quality detection map according to the plurality of abnormal pollutants specifically includes:
carrying out pollution positioning according to the water quality detection data and the abnormal pollutants, and determining a plurality of abnormal sampling points;
and carrying out water area pollution capture on the water quality detection map through a plurality of abnormal sampling points to determine a polluted water area.
As a further limitation of the technical solution of the embodiment of the present invention, the acquiring the enterprise production information of the polluted water area based on the big data specifically includes the following steps:
determining a plurality of discharge enterprises for the polluted water area based on big data;
acquiring enterprise-related information of a plurality of emission enterprises;
and screening the information of the enterprise related information to obtain enterprise production information.
As a further limitation of the technical solution of the embodiment of the present invention, the tracing the water pollution relevance according to the enterprise production information and the plurality of abnormal pollutants, and the marking of the pollution source enterprise specifically includes the following steps:
performing water pollution relevance evaluation according to the enterprise production information and the abnormal pollutants to obtain a plurality of relevance scores;
and tracing the water pollution relevance through the relevance scores, and marking pollution source enterprises.
The utility model provides a quick water pollution traceability system based on big data, the system includes sampling detecting element, waters monitoring unit, pollutes and catches unit, information acquisition unit and relevance traceability unit, wherein:
the sampling detection unit is used for carrying out multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and carrying out anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants;
the water area monitoring unit is used for carrying out equidistant distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map;
the pollution capturing unit is used for capturing water area pollution on the water quality detection map according to the abnormal pollutants to determine a polluted water area;
the information acquisition unit is used for acquiring enterprise production information of the polluted water area based on big data;
and the correlation traceability unit is used for performing correlation traceability of water pollution and marking pollution source enterprises according to the enterprise production information and the abnormal pollutants.
As a further limitation of the technical solution of the embodiment of the present invention, the sampling detection unit specifically includes:
the point distribution sampling module is used for carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples;
the water quality detection module is used for detecting a plurality of water quality detection samples to obtain water quality detection data;
the abnormality analysis module is used for carrying out abnormality analysis according to the water quality detection data and determining a plurality of abnormal objects;
and the pollutant marking module is used for analyzing the pollution contribution of the abnormal matters and marking the abnormal pollutants.
As a further limitation of the technical solution of the embodiment of the present invention, the water area monitoring unit specifically includes:
the sampling positioning module is used for carrying out equidistant point distribution sampling positioning to obtain sampling positioning data;
the basic map drawing module is used for drawing a basic water area map according to the sampling positioning data;
the monitoring map drawing module is used for monitoring a water area according to the basic water area map and drawing a water area monitoring map;
and the water quality map drawing module is used for integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
As a further limitation of the technical solution of the embodiment of the present invention, the pollution capturing unit specifically includes:
the pollution positioning module is used for carrying out pollution positioning according to the water quality detection data and the abnormal pollutants and determining a plurality of abnormal sampling points;
and the pollution capture module is used for capturing water area pollution on the water quality detection map through a plurality of abnormal sampling points to determine a polluted water area.
Compared with the prior art, the invention has the beneficial effects that:
the embodiment of the invention determines a plurality of abnormal pollutants by carrying out multi-position equidistant point distribution sampling and water quality detection; drawing a water quality detection map; carrying out water area pollution capture and determining a polluted water area; acquiring enterprise production information of a polluted water area; and tracing the relevance of water pollution and marking pollution source enterprises. Can equidistance stationing sampling and water quality testing, confirm a plurality of unusual pollutants, according to sampling location and waters monitoring, draw the water quality testing map, thereby carry out the waters pollution on the water quality testing map and catch, confirm the polluted water area, and combine the enterprise production information in polluted water area, carry out the water pollution associativity and trace to the source, confirm the pollution source enterprise, thereby need not to carry out more intensive water quality testing in the unusual region of water pollution, the water pollution traces to the source faster, and do not receive the influence of rivers change, the water pollution traces to the source more accurately.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Fig. 2 shows a flow chart of determining a plurality of abnormal pollutants in the method provided by the embodiment of the invention.
Fig. 3 shows a flow chart of obtaining a water quality detection map in the method provided by the embodiment of the invention.
Fig. 4 shows a flow chart of determining a polluted water area in the method provided by the embodiment of the invention.
Fig. 5 shows a flowchart for acquiring enterprise production information in the method provided by the embodiment of the invention.
Fig. 6 shows a flow chart of water pollution relevance tracing in the method provided by the embodiment of the invention.
Fig. 7 shows an application architecture diagram of a system provided by an embodiment of the invention.
Fig. 8 shows a block diagram of a sampling detection unit in the system according to the embodiment of the present invention.
Fig. 9 shows a block diagram of a water level monitoring unit in the system according to the embodiment of the present invention.
FIG. 10 is a block diagram illustrating a structure of a pollution capture unit in the system according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It can be understood that, in the prior art, water pollution tracing usually includes analyzing water quality detection data, determining a rough water pollution abnormal area, and further performing intensive water quality detection in the water pollution abnormal area to determine a water pollution trouble-related enterprise.
In order to solve the problems, the embodiment of the invention determines a plurality of abnormal pollutants by carrying out multi-position equidistant point distribution sampling and water quality detection; drawing a water quality detection map; carrying out water area pollution capture and determining a polluted water area; acquiring enterprise production information of a polluted water area; and tracing the relevance of water pollution and marking pollution source enterprises. Can equidistance stationing sampling and water quality testing, confirm a plurality of unusual pollutants, according to sampling location and waters monitoring, draw the water quality testing map, thereby carry out the waters pollution on the water quality testing map and catch, confirm the polluted water area, and combine the enterprise production information in polluted water area, carry out the water pollution associativity and trace to the source, confirm the pollution source enterprise, thereby need not to carry out more intensive water quality testing in the unusual region of water pollution, the water pollution traces to the source faster, and do not receive the influence of rivers change, the water pollution traces to the source more accurately.
Fig. 1 shows a flow chart of a method provided by an embodiment of the invention.
Specifically, a rapid water pollution tracing method based on big data specifically comprises the following steps:
and S101, carrying out multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and carrying out anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants.
In the embodiment of the invention, equidistant sampling distribution is carried out along a river with sewage discharge, so that a plurality of sampling points are equidistantly arranged in the river, water quality sampling is carried out on the plurality of sampling points simultaneously, a plurality of water quality detection samples are obtained, water quality detection is respectively carried out on the plurality of water quality detection samples, water quality detection data is obtained, the water quality detection data is compared with standard discharge water quality data, a plurality of abnormal objects which do not accord with the standard discharge water quality data are determined, the abnormal percentage of the content of each abnormal object relative to the standard discharge content is calculated, the pollution contribution value of the abnormal object is obtained, the pollution contribution values of the plurality of abnormal objects are arranged, and the abnormal object with the pollution contribution value arranged in the first three is marked as an abnormal pollutant.
It can be understood that after the water quality sampling is completed, the water quality detection samples of each different sampling point are numbered, the water quality detection samples of different numbers are subjected to water quality detection, and the water quality detection results are sorted according to the numbers of the water quality detection samples to obtain water quality detection data; the pollution contribution value is calculated by the formula: and H is (Q-B)/B, wherein Q is the content of the abnormal substances, and B is the standard emission content corresponding to the abnormal substances.
Specifically, fig. 2 shows a flow chart of determining a plurality of abnormal pollutants in the method provided by the embodiment of the invention.
In a preferred embodiment provided by the present invention, the performing multi-position equidistant sampling and water quality detection to obtain water quality detection data, and performing anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants specifically includes the following steps:
and step S1011, carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples.
And step S1012, detecting a plurality of water quality detection samples to obtain water quality detection data.
And a step S1013 of performing an abnormality analysis based on the water quality detection data to identify a plurality of abnormal objects.
And step S1014, analyzing the pollution contribution of the abnormal matters, and marking the abnormal pollutants.
Further, the rapid water pollution tracing method based on big data further comprises the following steps:
and S102, carrying out equidistant distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
In the embodiment of the invention, the electronic map of the river is networked with a meteorological website, equidistant distribution sampling is carried out, a plurality of sampling points arranged in the sampling distribution are positioned, sampling positioning data is obtained, sampling point marking is carried out on the electronic map through the sampling positioning data, a basic water area map is obtained, water area change in the basic water area map is monitored through the meteorological website, water flow change of a water area is updated in real time, the water area monitoring map is drawn on the basis of the basic water area map, water pollution in the water area monitoring map is visually displayed according to water quality detection data, and the water quality detection map is drawn on the basis of a polluted area and a pollution degree.
It can be understood that in the basic water area map, black points are used for identifying sampling points at different positions; in the water area monitoring map, the water flow change of the water area is represented by real-time changing data, and the method specifically includes: water flow speed, water flow direction, water flow depth, etc.; the water quality detection map is divided into a plurality of display layers, each display layer corresponds to different abnormal object display states, different color colors correspond to different abnormal objects, the deeper the color is, the more serious the pollution representing the abnormal object is, and a worker can visually check the water quality polluted water area and the pollution degree corresponding to different abnormal objects from the water quality detection map.
Specifically, fig. 3 shows a flowchart for obtaining a water quality detection map in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the equidistant sampling and positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain the water quality detection map specifically includes the following steps:
and step S1021, carrying out equidistant point distribution sampling positioning to obtain sampling positioning data.
And step S1022, drawing a basic water area map according to the sampling positioning data.
And S1023, monitoring the water area according to the basic water area map and drawing a water area monitoring map.
And step S1024, integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
Further, the rapid water pollution source tracing method based on big data further comprises the following steps:
and step S103, carrying out water area pollution capture on the water quality detection map according to the plurality of abnormal pollutants, and determining a polluted water area.
In the embodiment of the invention, the pollution range covered by a plurality of abnormal pollutants on the water quality detection map is determined, a plurality of abnormal sampling points in the pollution range are determined, and the polluted water area which is possibly polluted around the plurality of abnormal sampling points is captured according to the water flow change of the water area, so that the polluted water area is determined.
Specifically, fig. 4 shows a flowchart of determining a polluted water area in the method provided by the embodiment of the invention.
In a preferred embodiment of the present invention, the determining a polluted water area by capturing water area pollution on the water quality detection map according to a plurality of abnormal pollutants specifically includes:
and step S1031, carrying out pollution positioning according to the water quality detection data and the abnormal pollutants, and determining a plurality of abnormal sampling points.
And S1032, carrying out water area pollution capture on the water quality detection map through the plurality of abnormal sampling points, and determining a polluted water area.
Further, the rapid water pollution source tracing method based on big data further comprises the following steps:
and step S104, acquiring enterprise production information of the polluted water area based on the big data.
In the embodiment of the invention, a plurality of discharge enterprises in the polluted water area are determined based on big data, enterprise-related information of the discharge enterprises is crawled from the Internet, information screening is carried out on the enterprise-related information, and enterprise production information about product production of the discharge enterprises is selected.
Specifically, fig. 5 shows a flowchart of acquiring enterprise production information in the method provided by the embodiment of the present invention.
In a preferred embodiment of the present invention, the acquiring the enterprise production information of the polluted water area based on the big data specifically includes the following steps:
step S1041, determining a plurality of discharge enterprises of the polluted water area based on the big data.
Step S1042, obtaining enterprise-related information of a plurality of emission enterprises.
And S1043, performing information screening on the enterprise related information to obtain enterprise production information.
Further, the rapid water pollution source tracing method based on big data further comprises the following steps:
and S105, tracing the water pollution relevance according to the enterprise production information and the abnormal pollutants, and marking pollution source enterprises.
In the embodiment of the invention, enterprise production information is analyzed, possible emission pollution information of a plurality of emission enterprises is determined, water pollution relevance evaluation is carried out according to the relevance degree of the abnormal pollutants and the possible emission pollution information by combining the abnormal pollutants to obtain a plurality of relevance scores, the relevance scores are compared with a preset traceability score, and the emission enterprises with the relevance scores larger than the preset traceability score are marked as pollution source enterprises.
Specifically, fig. 6 shows a flowchart of tracing the water pollution relevance in the method provided by the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the tracing the water pollution relevance according to the enterprise production information and the plurality of abnormal pollutants, and the marking of the pollution source enterprise specifically includes the following steps:
and S1051, performing water pollution relevance evaluation according to the enterprise production information and the abnormal pollutants to obtain a plurality of relevance scores.
And step S1052, tracing the water pollution relevance through a plurality of relevance scores, and marking pollution source enterprises.
Further, fig. 7 is a diagram illustrating an application architecture of the system according to the embodiment of the present invention.
In another preferred embodiment, the present invention provides a rapid water pollution tracing system based on big data, which includes:
the sampling detection unit 101 is used for performing multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and performing anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants.
In the embodiment of the present invention, the sampling detection unit 101 performs equidistant sampling point arrangement along a river having sewage discharge, so as to equidistantly set a plurality of sampling points in the river, simultaneously performs water quality sampling on the plurality of sampling points, obtains a plurality of water quality detection samples, performs water quality detection on the plurality of water quality detection samples, respectively, obtains water quality detection data, compares the water quality detection data with standard discharge water quality data, determines a plurality of abnormal objects that do not meet the standard discharge water quality data, calculates an abnormal percentage of the content of each abnormal object relative to the standard discharge content, obtains a pollution contribution value of the abnormal object, arranges the pollution contribution values of the plurality of abnormal objects, and marks the abnormal object whose pollution contribution value is arranged in the first three as an abnormal pollutant.
Specifically, fig. 8 shows a block diagram of a sampling detection unit 101 in the system according to the embodiment of the present invention.
In a preferred embodiment provided by the present invention, the sampling detection unit 101 specifically includes:
and the point distribution sampling module 1011 is used for carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples.
And the water quality detection module 1012 is used for detecting a plurality of water quality detection samples to obtain water quality detection data.
And an anomaly analysis module 1013 configured to perform anomaly analysis according to the water quality detection data to determine a plurality of anomalies.
And a contaminant marking module 1014 for performing a contamination contribution analysis on the plurality of abnormal objects and marking the plurality of abnormal contaminants.
Further, the rapid water pollution traceability system based on big data further comprises:
and the water area monitoring unit 102 is used for carrying out equidistant distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
In the embodiment of the invention, the water area monitoring unit 102 is networked with a meteorological website to obtain an electronic map of a river which is subjected to equidistant distribution sampling, a plurality of sampling points arranged at the sampling distribution are positioned to obtain sampling positioning data, the sampling point marks are carried out on the electronic map through the sampling positioning data to obtain a basic water area map, the water area change in the basic water area map is monitored through the meteorological website, the water flow change of the water area is updated in real time, the water area monitoring map is drawn on the basis of the basic water area map, the water quality pollution in the water area monitoring map is visually displayed according to the pollution area and the pollution degree, and the water quality detection map is drawn on the basis of the water area monitoring map.
Specifically, fig. 9 shows a block diagram of a water level monitoring unit 102 in the system according to the embodiment of the present invention.
In a preferred embodiment of the present invention, the water area monitoring unit 102 specifically includes:
and the sampling positioning module 1021 is used for carrying out equidistant point distribution sampling positioning and acquiring sampling positioning data.
The basic map drawing module 1022 is configured to draw a basic water area map according to the sampling positioning data.
And the monitoring map drawing module 1023 is used for monitoring the water area according to the basic water area map and drawing a water area monitoring map.
And the water quality mapping module 1024 is used for integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
Further, the rapid water pollution traceability system based on big data further comprises:
and the pollution capturing unit 103 is used for capturing water area pollution on the water quality detection map according to the plurality of abnormal pollutants to determine a polluted water area.
In the embodiment of the present invention, the pollution capturing unit 103 determines a pollution range covered by a plurality of abnormal pollutants on the water quality detection map, further determines a plurality of abnormal sampling points within the pollution range, and captures the pollution of the water area which may be polluted around the plurality of abnormal sampling points according to the water flow change of the water area, thereby determining the polluted water area.
Specifically, fig. 10 shows a block diagram of a structure of the pollution capturing unit 103 in the system according to the embodiment of the present invention.
In a preferred embodiment of the present invention, the pollution capturing unit 103 specifically includes:
and a pollution positioning module 1031, configured to perform pollution positioning according to the water quality detection data and the plurality of abnormal pollutants, and determine a plurality of abnormal sampling points.
And the pollution capturing module 1032 is used for capturing the water area pollution on the water quality detection map through a plurality of abnormal sampling points to determine the polluted water area.
Further, the rapid water pollution traceability system based on big data further comprises:
and the information acquisition unit 104 is used for acquiring the enterprise production information of the polluted water area based on the big data.
In the embodiment of the present invention, the information obtaining unit 104 determines a plurality of discharging enterprises in the polluted water area based on the big data, crawls enterprise-related information of the plurality of discharging enterprises from the internet, performs information screening on the enterprise-related information, and selects enterprise production information related to product production of the plurality of discharging enterprises.
And the relevance tracing unit 105 is used for tracing the relevance of water pollution and marking pollution source enterprises according to the enterprise production information and the abnormal pollutants.
In the embodiment of the present invention, the relevance tracing unit 105 analyzes the enterprise production information, determines possible emission pollution information of a plurality of emission enterprises, performs water pollution relevance evaluation according to the relevance degree of the plurality of abnormal pollutants and the possible emission pollution information by combining the plurality of abnormal pollutants to obtain a plurality of relevance scores, compares the plurality of relevance scores with a preset tracing score, and marks the emission enterprises with the relevance scores larger than the preset tracing score as pollution source enterprises.
In summary, in the embodiment of the present invention, water quality detection data is obtained by performing multi-position equidistant point distribution sampling and water quality detection, and anomaly analysis is performed according to the water quality detection data to determine a plurality of abnormal pollutants; carrying out equidistant point distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and water quality detection data to obtain a water quality detection map; according to the abnormal pollutants, carrying out water area pollution capture on a water quality detection map to determine a polluted water area; acquiring enterprise production information of the polluted water area based on the big data; and tracing the water pollution relevance according to the enterprise production information and the abnormal pollutants, and marking the pollution source enterprise. Can equidistance stationing sampling and water quality testing, confirm a plurality of unusual pollutants, according to sampling location and waters monitoring, draw the water quality testing map, thereby carry out the waters pollution on the water quality testing map and catch, confirm the polluted water area, and combine the enterprise production information in polluted water area, carry out the water pollution associativity and trace to the source, confirm the pollution source enterprise, thereby need not to carry out more intensive water quality testing in the unusual region of water pollution, the water pollution traces to the source faster, and do not receive the influence of rivers change, the water pollution traces to the source more accurately.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a non-volatile computer-readable storage medium, and can include the processes of the embodiments of the methods described above when the program is executed. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A rapid water pollution tracing method based on big data is characterized by comprising the following steps:
carrying out multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and carrying out anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants;
carrying out equidistant point distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map;
according to the abnormal pollutants, carrying out water area pollution capture on the water quality detection map to determine a polluted water area;
acquiring enterprise production information of the polluted water area based on big data;
and tracing the water pollution relevance according to the enterprise production information and the abnormal pollutants, and marking pollution source enterprises.
2. The big data-based rapid water pollution tracing method according to claim 1, wherein said performing multi-position equidistant sampling and water quality detection to obtain water quality detection data, and performing anomaly analysis according to said water quality detection data to determine a plurality of anomalous pollutants specifically comprises the steps of:
carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples;
detecting a plurality of water quality detection samples to obtain water quality detection data;
performing anomaly analysis according to the water quality detection data to determine a plurality of anomalies;
and analyzing the pollution contribution of a plurality of abnormal matters, and marking a plurality of abnormal pollutants.
3. The rapid water pollution tracing method based on big data as claimed in claim 1, wherein said equidistant spotting sampling positioning and water area monitoring, drawing water area monitoring map, and integrating said water area monitoring map and said water quality detection data to obtain water quality detection map specifically comprises the following steps:
carrying out equidistant point distribution sampling positioning to obtain sampling positioning data;
drawing a basic water area map according to the sampling positioning data;
monitoring a water area according to the basic water area map, and drawing a water area monitoring map;
and synthesizing the water area monitoring map and the water quality detection data to obtain a water quality detection map.
4. The big data-based rapid water pollution tracing method according to claim 1, wherein said water pollution is captured on said water quality detection map according to a plurality of said abnormal pollutants, and determining a polluted water area specifically comprises the steps of:
carrying out pollution positioning according to the water quality detection data and the abnormal pollutants, and determining a plurality of abnormal sampling points;
and carrying out water area pollution capture on the water quality detection map through a plurality of abnormal sampling points to determine a polluted water area.
5. The big data based rapid water pollution tracing method according to claim 1, wherein the obtaining of the enterprise production information of the polluted water area based on the big data specifically comprises the following steps:
determining a plurality of discharge enterprises for the polluted water area based on big data;
acquiring enterprise-related information of a plurality of emission enterprises;
and screening the information of the enterprise related information to obtain enterprise production information.
6. The big data-based rapid water pollution tracing method according to claim 1, wherein the tracing of water pollution relevance is performed according to the enterprise production information and a plurality of abnormal pollutants, and the marking of the pollution source enterprise specifically comprises the following steps:
performing water pollution relevance evaluation according to the enterprise production information and the abnormal pollutants to obtain a plurality of relevance scores;
and tracing the water pollution relevance through the relevance scores, and marking pollution source enterprises.
7. The utility model provides a quick water pollution traceability system based on big data which characterized in that, the system includes sampling detecting element, waters monitoring unit, pollutes and catches unit, information acquisition unit and associativity traceability unit, wherein:
the sampling detection unit is used for carrying out multi-position equidistant point distribution sampling and water quality detection to obtain water quality detection data, and carrying out anomaly analysis according to the water quality detection data to determine a plurality of abnormal pollutants;
the water area monitoring unit is used for carrying out equidistant distribution sampling positioning and water area monitoring, drawing a water area monitoring map, and integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map;
the pollution capturing unit is used for capturing water area pollution on the water quality detection map according to the abnormal pollutants to determine a polluted water area;
the information acquisition unit is used for acquiring enterprise production information of the polluted water area based on big data;
and the correlation traceability unit is used for performing correlation traceability of water pollution and marking pollution source enterprises according to the enterprise production information and the abnormal pollutants.
8. The big-data-based rapid water pollution traceability system as claimed in claim 7, wherein the sampling detection unit specifically comprises:
the point distribution sampling module is used for carrying out multi-position equidistant point distribution sampling to obtain a plurality of water quality detection samples;
the water quality detection module is used for detecting a plurality of water quality detection samples to obtain water quality detection data;
the abnormality analysis module is used for carrying out abnormality analysis according to the water quality detection data and determining a plurality of abnormal objects;
and the pollutant marking module is used for analyzing the pollution contribution of the abnormal matters and marking the abnormal pollutants.
9. The big-data-based rapid water pollution traceability system as claimed in claim 7, wherein the water area monitoring unit specifically comprises:
the sampling positioning module is used for carrying out equidistant point distribution sampling positioning to obtain sampling positioning data;
the basic map drawing module is used for drawing a basic water area map according to the sampling positioning data;
the monitoring map drawing module is used for monitoring a water area according to the basic water area map and drawing a water area monitoring map;
and the water quality map drawing module is used for integrating the water area monitoring map and the water quality detection data to obtain a water quality detection map.
10. The big-data-based rapid water pollution traceability system as claimed in claim 7, wherein the pollution capturing unit specifically comprises:
the pollution positioning module is used for carrying out pollution positioning according to the water quality detection data and the abnormal pollutants and determining a plurality of abnormal sampling points;
and the pollution capture module is used for capturing water area pollution on the water quality detection map through a plurality of abnormal sampling points to determine a polluted water area.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210650534.3A CN115048475A (en) | 2022-06-09 | 2022-06-09 | Rapid water pollution source tracing method and system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210650534.3A CN115048475A (en) | 2022-06-09 | 2022-06-09 | Rapid water pollution source tracing method and system based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115048475A true CN115048475A (en) | 2022-09-13 |
Family
ID=83161590
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210650534.3A Pending CN115048475A (en) | 2022-06-09 | 2022-06-09 | Rapid water pollution source tracing method and system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115048475A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115905450A (en) * | 2023-01-04 | 2023-04-04 | 深圳联和智慧科技有限公司 | Unmanned aerial vehicle monitoring-based water quality abnormity tracing method and system |
| CN116123387A (en) * | 2023-04-14 | 2023-05-16 | 广东广宇科技发展有限公司 | Pipeline collection robot and collection method |
| CN116859016A (en) * | 2023-07-20 | 2023-10-10 | 广东贝源检测技术股份有限公司 | Water pollution tracing method and system based on big data |
| CN117420283A (en) * | 2023-12-19 | 2024-01-19 | 上海科泽智慧环境科技有限公司 | Integrated multi-channel water quality monitoring method and system |
| CN117420084A (en) * | 2023-12-19 | 2024-01-19 | 海南中南标质量科学研究院有限公司 | Multi-parameter water quality spectrum remote sensing monitoring and early warning system |
| CN117575161A (en) * | 2023-11-30 | 2024-02-20 | 生态环境部土壤与农业农村生态环境监管技术中心 | Industrial pollution source monitoring and point distribution method and device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110085281A (en) * | 2019-04-26 | 2019-08-02 | 成都之维安科技股份有限公司 | A kind of environmental pollution traceability system and method based on feature pollution factor source resolution |
| CN111474307A (en) * | 2020-03-26 | 2020-07-31 | 南方科技大学 | Pollutant tracing method and device, computer equipment and storage medium |
| WO2021174751A1 (en) * | 2020-03-02 | 2021-09-10 | 平安国际智慧城市科技股份有限公司 | Method, apparatus and device for locating pollution source on basis of big data, and storage medium |
| CN113449956A (en) * | 2021-04-23 | 2021-09-28 | 合肥学院 | Water pollution rapid tracing method and system |
| CN113899872A (en) * | 2021-11-18 | 2022-01-07 | 中水三立数据技术股份有限公司 | Pollution source traceability system based on water quality monitoring |
-
2022
- 2022-06-09 CN CN202210650534.3A patent/CN115048475A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110085281A (en) * | 2019-04-26 | 2019-08-02 | 成都之维安科技股份有限公司 | A kind of environmental pollution traceability system and method based on feature pollution factor source resolution |
| WO2021174751A1 (en) * | 2020-03-02 | 2021-09-10 | 平安国际智慧城市科技股份有限公司 | Method, apparatus and device for locating pollution source on basis of big data, and storage medium |
| CN111474307A (en) * | 2020-03-26 | 2020-07-31 | 南方科技大学 | Pollutant tracing method and device, computer equipment and storage medium |
| CN113449956A (en) * | 2021-04-23 | 2021-09-28 | 合肥学院 | Water pollution rapid tracing method and system |
| CN113899872A (en) * | 2021-11-18 | 2022-01-07 | 中水三立数据技术股份有限公司 | Pollution source traceability system based on water quality monitoring |
Non-Patent Citations (1)
| Title |
|---|
| 运珞珈 等: "卫生理化检验与微生物学检验", 华中科技大学出版社, pages: 81 - 82 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115905450A (en) * | 2023-01-04 | 2023-04-04 | 深圳联和智慧科技有限公司 | Unmanned aerial vehicle monitoring-based water quality abnormity tracing method and system |
| CN115905450B (en) * | 2023-01-04 | 2023-05-09 | 深圳联和智慧科技有限公司 | Water quality anomaly tracing method and system based on unmanned aerial vehicle monitoring |
| CN116123387A (en) * | 2023-04-14 | 2023-05-16 | 广东广宇科技发展有限公司 | Pipeline collection robot and collection method |
| CN116859016A (en) * | 2023-07-20 | 2023-10-10 | 广东贝源检测技术股份有限公司 | Water pollution tracing method and system based on big data |
| CN116859016B (en) * | 2023-07-20 | 2024-01-30 | 广东贝源检测技术股份有限公司 | Water pollution tracing method based on big data |
| CN117575161A (en) * | 2023-11-30 | 2024-02-20 | 生态环境部土壤与农业农村生态环境监管技术中心 | Industrial pollution source monitoring and point distribution method and device |
| CN117420283A (en) * | 2023-12-19 | 2024-01-19 | 上海科泽智慧环境科技有限公司 | Integrated multi-channel water quality monitoring method and system |
| CN117420084A (en) * | 2023-12-19 | 2024-01-19 | 海南中南标质量科学研究院有限公司 | Multi-parameter water quality spectrum remote sensing monitoring and early warning system |
| CN117420283B (en) * | 2023-12-19 | 2024-03-08 | 上海科泽智慧环境科技有限公司 | Integrated multi-channel water quality monitoring method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115048475A (en) | Rapid water pollution source tracing method and system based on big data | |
| Lu et al. | Use of ESI-FTICR-MS to characterize dissolved organic matter in headwater streams draining forest-dominated and pasture-dominated watersheds | |
| WO2022160682A1 (en) | Water quality monitoring data analysis method and apparatus, device, and storage medium | |
| Smith et al. | Benthic response index for assessing infaunal communities on the southern California mainland shelf | |
| Posthuma et al. | Eco-epidemiology of aquatic ecosystems: Separating chemicals from multiple stressors | |
| CN116168771B (en) | Method and system for monitoring pollution of perfluorinated compounds in river based on Internet of things | |
| Ejarque-Gonzalez et al. | Self-organising maps and correlation analysis as a tool to explore patterns in excitation-emission matrix data sets and to discriminate dissolved organic matter fluorescence components | |
| Zijp et al. | Identification and ranking of environmental threats with ecosystem vulnerability distributions | |
| Cristóvão et al. | Fish canning industry wastewater variability assessment using multivariate statistical methods | |
| Bevilacqua et al. | Best Practicable Aggregation of Species: a step forward for species surrogacy in environmental assessment and monitoring | |
| CN105447248A (en) | Seawater acute reference prediction method based on metal quantitative structure-activity relationship | |
| CN113533672B (en) | Water quality on-line monitoring method and device | |
| CN112903945B (en) | Urban black and odorous water body identification method based on conventional water quality parameters | |
| CN113034013A (en) | Pollution tracing method and device, electronic equipment and storage medium | |
| CN116297936A (en) | Method, system, device and medium for tracing pollutant | |
| CN115508322A (en) | Water pollution source multi-dimensional tracing method and device | |
| Di Lecce et al. | Online wastewater monitoring system using solid state sensor | |
| CN114117757A (en) | Groundwater pollutant tracing method, device, equipment and storage medium | |
| CN109711736B (en) | Method and device for screening watershed water environment risk substances | |
| CN113590663A (en) | Environment detection method and system | |
| Aravindaguru et al. | Streamlining Industrial Wastewater Management Through Real Time IoT Cloud Monitoring | |
| Hansen et al. | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective | |
| Ortiz-Estarelles et al. | On the internal multivariate quality control of analytical laboratories. A case study: the quality of drinking water | |
| Cahyonugroho et al. | Efforts to Mitigate the Quality of Surabaya River Water as a Drinking Water Source | |
| CN117171675B (en) | Water environment microorganism detection method, system and medium based on multi-source data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |