CN112305182A - Multi-level source analysis visualization system and method for reservoir nitrogen pollution - Google Patents
Multi-level source analysis visualization system and method for reservoir nitrogen pollution Download PDFInfo
- Publication number
- CN112305182A CN112305182A CN202010960178.6A CN202010960178A CN112305182A CN 112305182 A CN112305182 A CN 112305182A CN 202010960178 A CN202010960178 A CN 202010960178A CN 112305182 A CN112305182 A CN 112305182A
- Authority
- CN
- China
- Prior art keywords
- nitrogen
- catchment
- reservoir
- visualization
- parameter
- 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.)
- Granted
Links
Images
Classifications
-
- 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
- G06F16/29—Geographical information databases
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/30—Flood prevention; Flood or storm water management, e.g. using flood barriers
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Analytical Chemistry (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Medicinal Chemistry (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Food Science & Technology (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a multilevel source analysis visualization system and method for reservoir nitrogen pollution, which comprises the following steps: according to the DEM and the pollution source in the reservoir protection area, classifying the catchment area of the river entering the reservoir in a subarea manner; detecting nitrogen and other water quality indexes of water collection nodes between a reservoir area and each level of subareas, and establishing a subarea nitrogen fingerprint; based on the receptor model, the contribution rates of different partitions to the nitrogen of the water body of the reservoir area are estimated step by step, and the contribution rates of the nitrogen indexes of the rivers around the reservoir area are visually and more intuitively displayed on a map by utilizing the visual image processing of a computer.
Description
Technical Field
The invention relates to water nitrogen pollution source analysis, in particular to a multi-level source analysis visualization system and method for reservoir nitrogen pollution.
Background
Nitrogen pollution and water eutrophication caused by the nitrogen pollution are important problems in reservoir water quality guarantee. The nitrogen pollution of large reservoirs in China is serious, and the nitrogen has the problems of multiple sources and superimposed pollution. The nitrogen pollution source analysis is an important way for realizing reservoir partition management and grading treatment.
The method for analyzing the nitrogen pollution source mainly comprises a flux estimation method and an isotope traceability method.
The flux estimation method is to make clear the pollution source in the catchment area, count the total concentration of the nitrogen component of the pollution source, and multiply the water flow of the discharge outlet or the river section to obtain the instantaneous or average discharge, thereby estimating the contribution rate of each small basin or the same type of pollution source to the nitrogen of the reservoir. However, the method is greatly influenced by water flow, and both domestic and foreign research models show that under the condition that the runoff has an extreme value, the nitrogen flux estimation has obvious deviation. In addition, the nitrogen composition is converted into each other in the natural water body, and the flux calculation result is also influenced.
The isotope tracing method is to quantitatively mark the nitrogen emission of different pollution sources by utilizing the isotope abundance of nitrogen; and the nitrogen isotope abundances of different pollution sources can be shared, and the contribution rates of the nitrogen of the different pollution sources can be reversely calculated. However, the isotope method is also affected by the water flow rate, and the abundance of nitrogen in the pollution source is unstable, and the detection cost is high, and the method is not a source analysis method suitable for conventional management.
In summary, aiming at the defects of the existing nitrogen source analysis method, on the basis of the classification of the catchment area, the contribution rate of each stage of subarea to the nitrogen pollution of the reservoir area is estimated by adopting a receptor model according to the conversion of the relation between the source and the sink, so that the problems of poor quantitative accuracy of source analysis and non-intuitive display caused by the perennial fluctuation of the flow of the catchment area can be effectively solved.
Disclosure of Invention
The invention aims to provide a multi-level source analysis visualization system and method for reservoir nitrogen pollution.
The invention adopts the technical scheme for realizing the purpose that:
the multi-level source analysis visualization system for reservoir nitrogen pollution comprises a catchment area division module (H), a parameter monitoring module (M), an information processing module (I) and a visualization module (V);
the catchment division module is used for dividing and marking a river catchment area in the reservoir area according to the confluence node and sending the division and marking result data to the visualization module;
the parameter monitoring module is used for collecting a water sample at a water collection node, detecting nitrogen and water quality parameter information through a sensor and sending the information to the information processing module;
the information processing module is used for screening the received nitrogen and water quality parameter information, establishing a fingerprint, substituting each parameter index into a receptor model, calculating the nitrogen contribution rate parameter in the corresponding partition of the river step by step, and sending the nitrogen contribution rate parameter to the visualization module;
and the visualization module is used for receiving the data output by the modules and carrying out superposition visualization display on the map.
The catchment area division module comprises a partition division unit and a partition marking unit;
the partition dividing unit is used for reading the DEM geographical elevation image and dividing the catchment area according to the river catchment flow direction; merging catchment areas which are the same in type and adjacent in position according to the type and spatial position distribution of the pollution source;
the subarea marking unit is used for grading the current subarea according to the spatial relation of the river flow direction and marking the current subarea in the affiliated subarea on the map; the marker is in the form of M-N; wherein, M is catchment district grade, "-" is the separator, N is catchment district code under the present grade, M-N represents catchment district N of M rank.
The information processing module (I) comprises a fingerprint spectrum unit (I)S) Model calculation unit (I)P)；
The fingerprint unit comprises a parameter screening subunit and a fingerprint unit; the parameter screening subunit is used for screening and dimension normalization processing on the nitrogen and water quality parameter information; the fingerprint spectrum unit is used for establishing a fingerprint spectrum according to the normalized index parameter values;
and the model calculation unit is used for substituting the nitrogen and water quality parameter indexes into a receptor model, generating nitrogen contribution rate parameters in the partition corresponding to the river and sending the nitrogen contribution rate parameters to the visualization module.
The visualization module (V) comprises a data storage unit (V)S) Two-dimensional display unit (V)D)；
The data storage unit is used for classifying and storing river catchment area division results and division marks in the reservoir area, fingerprint patterns established by the fingerprint pattern unit and nitrogen contribution rate data in the division areas generated by the model calculation unit;
the two-dimensional display unit is used for drawing a boundary outline of a river catchment area and displaying a subarea mark on a map, and is used for displaying a fingerprint map on a two-dimensional coordinate system; the method is used for displaying the nitrogen contribution rate parameter in different shades of different colors in a superposed mode in a river catchment area of a corresponding reservoir area on a map.
The nitrogen and other water quality indicators include:
the nitrogen indexes comprise total nitrogen TN and ammonia nitrogen NH4 +-N, nitro nitrogen NO3 --N, nitrosnitrogen NO2 --N；
Other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
The method for analyzing and visualizing the multilevel source of the reservoir nitrogen pollution comprises the following steps;
the catchment area division module divides and marks the river catchment area in the reservoir area according to the confluence node, and sends the division and marking result data to the visualization module;
the parameter monitoring module collects a water sample at a water collection node, detects nitrogen and water quality parameter information through a sensor and sends the information to the information processing module;
the information processing module screens the received nitrogen and water quality parameter information, establishes a fingerprint, substitutes each parameter index into a receptor model to calculate the nitrogen contribution rate parameter in the corresponding subarea of the river and sends the nitrogen contribution rate parameter to the visualization module;
and the visualization module receives the data output by the modules and performs superposition visualization display on the map.
The catchment zone division module executes the following steps:
the partition dividing unit reads the DEM geographical elevation image and divides a catchment area according to the river catchment flow direction; merging catchment areas which are the same in type and adjacent in position according to the type and spatial position distribution of the pollution source;
the subarea marking unit grades the current subarea according to the river flow direction and marks the current subarea in the affiliated subarea on the map; the marker is in the form of M-N; wherein, M is catchment district grade, "-" is the separator, N is catchment district code under the present grade, M-N represents catchment district N of M rank.
The information processing module executes the following steps:
the fingerprint unit comprises a parameter screening subunit and a fingerprint unit; the parameter screening subunit screens and normalizes the nitrogen and water quality parameter information; the fingerprint unit establishes a fingerprint according to the normalized index parameter values;
and the model calculation unit substitutes the nitrogen and water quality parameter indexes into a receptor model to generate a nitrogen contribution rate parameter in the partition corresponding to the river and sends the nitrogen contribution rate parameter to the visualization module.
The visualization module performs the steps of:
the data storage unit classifies the river catchment area division result and the subarea marks in the reservoir area, the fingerprint spectrum established by the fingerprint spectrum unit and the subarea nitrogen contribution rate data generated by the model calculation unit;
the two-dimensional display unit draws the boundary outline of the river catchment area and the display partition marks on the map, displays the fingerprint spectrum on the two-dimensional coordinate system, and displays the nitrogen contribution rate parameters in the river catchment area of the corresponding reservoir area on the map in a superposition manner by different colors with different intensities and depths.
The nitrogen and other water quality indicators include:
the nitrogen indexes comprise total nitrogen TN and ammonia nitrogen NH4 +-N, nitro nitrogen NO3 --N, nitrosnitrogen NO2 --N；
Other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
The invention has the following advantages and beneficial effects:
according to the invention, on the basis of partition classification of the confluence area of the reservoir, nitrogen and other water quality indexes are screened, a nitrogen fingerprint spectrogram is constructed, the contribution rate of each partition to reservoir nitrogen pollution is estimated by adopting a receptor model through conversion of the relation between source and sink of each partition, and the problems of poor source analysis quantitative accuracy and non-visual display caused by perennial fluctuation of flow of the catchment area can be effectively solved.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a result chart of classification of the catchment area zones in example 1;
FIG. 3 is a diagram showing the positions of catchment nodes between partitions in example 1;
FIG. 4 is a fingerprint of region 1-1 in example 1;
fig. 5 is a visualization map of the total nitrogen contribution rate of each partition in example 1.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
The multi-level source analysis visualization system for reservoir nitrogen pollution comprises a catchment area division module (H), a parameter monitoring module (M), an information processing module (I) and a visualization module (V);
the catchment division module is used for dividing and marking a river catchment area in the reservoir area according to the confluence node and sending the division and marking result data to the visualization module;
the parameter monitoring module is used for collecting a water sample at a water collection node, detecting nitrogen and water quality parameter information through a sensor and sending the information to the information processing module;
the information processing module is used for screening the received nitrogen and water quality parameter information, establishing a fingerprint, substituting each parameter index into a receptor model, calculating a nitrogen contribution rate parameter in a corresponding partition of the river, and sending the nitrogen contribution rate parameter to the visualization module;
and the visualization module is used for receiving the data output by the modules and carrying out superposition visualization display on the map.
A multilevel source analysis visualization method for reservoir nitrogen pollution is characterized by comprising the following steps:
(1) the catchment area division module carries out subarea classification on the catchment area of the warehousing river according to the DEM and the pollution source in the reservoir protection area;
(2) the parameter monitoring module detects nitrogen and other water quality indexes of water collection nodes among all stages of subareas;
(3) the information processing module establishes a nitrogen fingerprint, and estimates the contribution rate of different partitions to the water nitrogen of the reservoir area step by step based on a receptor model.
(4) And the visualization module receives the data output by the modules and performs superposition visualization display on the map.
The catchment area division module carries out subarea classification on the catchment area of the river to be warehoused, and the method comprises the following steps:
1) dividing the catchment area primarily by SWAT software according to DEM in the reservoir protection area,
2) merging the catchment areas with the same type and spatial association according to the spatial distribution of pollution sources such as industrial sewage, urban sewage, large-scale livestock and poultry breeding, rural sewage, planting industry, dispersed livestock and poultry breeding and the like;
3) grading the partitions according to the spatial relation of the river flow direction, wherein the partition in which river water is directly stored is grade 1, the partition in which catchment water directly flows into the grade 1 partition is grade 2, and so on;
4) different partitions in the same level are coded according to the mode, wherein M-N is a level code, and M is 1,2,3 … …; n is equivalent fraction code, N ═ 1,2,3 … …).
The parameter monitoring module detects nitrogen and other water quality indexes of catchment nodes between a reservoir area and each stage of subareas, and comprises the following steps:
1) the detection indexes comprise nitrogen indexes and other water quality indexes, wherein the nitrogen indexes comprise Total Nitrogen (TN) and ammonia Nitrogen (NH)4 +-N), nitro Nitrogen (NO)3 --N), nitrous Nitrogen (NO)2 --N); other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
2) The detection index data can be acquired by adopting a sensor, and the detection lower limit of each index acquired by the sensor is not higher than the determination lower limit of the recommended analysis method of the quality standard of the surface water environment (GB 3838-2002);
3) the sensors are arranged at the catchment nodes between the reservoir area and each stage of subareas.
The method for establishing the nitrogen fingerprint by the fingerprint unit of the information processing module comprises the following steps:
1) screening indexes according to the variation degree of the detection result, wherein the variation coefficient of the detection result is more than 15 percent and can be used as an index of a nitrogen fingerprint;
2) the fingerprint spectrum includes nitrogen indexes and other water quality indexes, but does not need to include all the indexes.
3) Index in finger print, through 10x(x belongs to an integer) times, and the numerical values are unified to be in the range of 0-1;
4) and after the multiple is increased and reduced, carrying out standardization and constructing a fingerprint.
The receptor model adopted by the model calculation unit of the information processing module specifically refers to:
one of the two receptor model-based source analysis methods can be selected from Positive Matrix Factorization (PMF) and non-negative constraint factor analysis (FA-NNC).
The model calculation unit of the information processing module estimates the contribution rate of different partitions to the reservoir area water nitrogen step by step, and the method comprises the following steps:
1) taking the reservoir area as a sink and taking the level 1 area as a source, and estimating the contribution rate of the level 1 area to the reservoir area; taking the level 1 area as a sink and the level 2 area as a source, and estimating the contribution rate of the level 2 area to the level 1 area; and so on;
2) and after gradual conversion, estimating the contribution rate of each region to the reservoir nitrogen.
The visualization module (V) comprises a data storage unit (V)S) Two-dimensional display unit (V)D)；
The data storage unit classifies the river catchment area division result and the subarea marks in the reservoir area, the fingerprint spectrum established by the fingerprint spectrum unit and the subarea nitrogen contribution rate data generated by the model calculation unit;
the two-dimensional display unit draws the boundary outline of the river catchment area and the display partition marks on the map, displays the fingerprint spectrum on the two-dimensional coordinate system, and displays the nitrogen contribution rate parameters in the river catchment area of the corresponding reservoir area on the map in a superposition manner by different colors with different intensities and depths.
Example 1
The present example selects the river catchment upstream of the large-scale water depot as the research area. The society river, the muddy river and the perilla river are important water and nitrogen sources of a large-volume reservoir.
The embodiment provides a multistage source analysis method for reservoir nitrogen pollution, which comprises the following specific implementation steps: 1) according to the DEM and the pollution source in the reservoir protection area, classifying the catchment area of the river entering the reservoir in a subarea manner; 2) detecting nitrogen and other water quality indexes of water collection nodes between a reservoir area and each level of subareas, and establishing a nitrogen fingerprint; 3) and based on the receptor model, estimating the contribution rate of different partitions to the water nitrogen of the reservoir area step by step.
Step one, carrying out partition classification on a river catchment area in a warehouse, which comprises the following specific steps:
(1) DEM data of a required area is elevation data with the resolution of 30M, and the acquired data is specifically GDEMDEM 30M; and dividing the river catchment area into 6 small watersheds as partition units by adopting a hydrological analysis tool in SWAT software.
(2) Merging catchment areas of the same type and spatial association according to the spatial distribution of pollution sources such as industrial sewage of a river catchment area, urban sewage, large-scale livestock and poultry breeding, rural sewage, planting industry, scattered livestock and poultry breeding and the like, and finally forming 4 subareas;
(3) grading the partitions according to the space relation of the river flow direction, wherein 4 partitions are divided into 3 grades;
(4) according to the coding rule, the numbers of the 4 zones are respectively 1-1, 2-1, 3-1 and 3-2, and a visualization module can be used for drawing the zone boundary outline in the corresponding zone and displaying the numbers (see figure 2).
Step two, detecting nitrogen and other water quality indexes of the reservoir area and the catchment node, and constructing a nitrogen fingerprint, which comprises the following specific steps:
(1) the detection indexes comprise nitrogen indexes and other water quality indexes, wherein the nitrogen indexes comprise Total Nitrogen (TN) and ammonia Nitrogen (NH)4 +-N), nitro Nitrogen (NO)3 --N), nitrous Nitrogen (NO)2 --N); other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
(2) The detection index data are acquired on line by adopting a multi-water-quality-parameter online monitor, and the detection lower limit of each acquired index data is lower than the determination lower limit of a recommended analysis method of the surface water environment quality standard (GB 3838-;
(3) and collecting 35 data at the catchment nodes between the reservoir area and each stage of subareas (see figure 3) every 2 weeks in 6-8 months in 2018.
(4) Screening indexes according to the variation degree of the detection result, wherein the total nitrogen, nitrate nitrogen, total phosphorus, pH and conductivity with the variation coefficient of the detection result being more than 15% can be used as indexes of a nitrogen fingerprint;
TABLE 1 index variation coefficient of measurement results
| Detecting the index | Quantity of water sample | Coefficient of variation | Whether it is an index of the map |
| Total nitrogen (mg/L) | 35 | 22％ | Is that |
| Ammonia nitrogen (mg/L) | 35 | 13％ | Whether or not |
| Nitramine (mg/L) | 35 | 28％ | Is that |
| Nitrous nitrogen (mg/L) | 35 | 14％ | Whether or not |
| Total phosphorus (mg/L) | 35 | 30％ | Is that |
| pH | 35 | 18％ | Is that |
| Conductivity (S/m) | 28 | 25％ | Is that |
| Iron (mg/L) | 28 | 15％ | Whether or not |
| Manganese (mg/L) | 28 | 17％ | Whether or not |
(4) The fingerprint not only comprises nitrogen indexes, but also comprises other water quality indexes, but does not need to comprise all the indexes;
(5) index in finger print, through 10x(x∈Integer) multiple scaling; total nitrogen is multiplied by 100, nitrate nitrogen concentration is multiplied by 101Total phosphorus concentration X102Conductivity x 10-2、pH×10-1After the multiple is increased and reduced, the index values are unified to be in the range of 0-1;
(6) after the multiple is increased and reduced, the indexes in the fingerprint are standardized to construct the fingerprint (taking the fingerprint of the 1-1 region as an example, figure 4). Clicking the 1-1 area on the map can also display the fingerprint map of the 1-1 area.
Step three, estimating the contribution rate of different partitions to the water body nitrogen of the reservoir area step by step, specifically as follows:
(1) the receptor model selected by the invention is a non-negative constraint factor analysis method (FA-NNC) and carries out estimation of contribution rate of source analysis quantification;
(2) taking the library area as a sink and the 1-1 area as a source, and estimating the contribution rate of the 1-1 area to the library area;
(3) taking the 1-1 region as a sink and the 2-1 region as a source, and estimating the contribution rate of the 2-1 region to the 1-1 region;
(4) taking the 2-1 area as a sink and the 3-1 area and the 3-2 area as a source, and estimating the contribution rate of the 3-1 area and the 3-2 area to the 2-1 area;
(5) the contribution rate of each region to the pool area nitrogen was estimated.
Since the nitrogen inputs of the muddy and suzi rivers also exist in the large-volume reservoir, the total contribution rate of the community river catchment area to the total nitrogen and the nitrate nitrogen of the large-volume reservoir is about 41.2% and 44.6% respectively.
TABLE 2 contribution of each region to pool nitrogen
| Index of nitrogen element | 1-1 region contribution rate | 2-1 region contribution rate | 3-1 region contribution rate | 3-2 region contribution rate |
| Total nitrogen | 20 | 17.3 | 0.5 | 3.4 |
| Nitro nitrogen | 21.6 | 18.8 | 0.5 | 3.7 |
The nitrogen contribution rate parameters are displayed in the river catchment area of the corresponding reservoir area on the map in a superimposed manner by different colors with different intensity, depth and weakness, as shown in fig. 5, a visual effect graph taking the total nitrogen contribution rate as an example is shown. By utilizing the computer to visualize image processing, the nitrogen index partition contribution rate of a certain river in the reservoir area can be visually and more intuitively displayed on a map.
The foregoing is a more detailed description of the present invention, taken in conjunction with the accompanying preferred embodiments, and is not intended to limit the invention to the particular forms disclosed. Several simple deductions or substitutions can be made without departing from the concept of the present invention, and should be considered as belonging to the protection scope of the present invention.
Claims (10)
1. The multi-level source analysis visualization system for reservoir nitrogen pollution is characterized by comprising a catchment division module (H), a parameter monitoring module (M), an information processing module (I) and a visualization module (V);
the catchment division module is used for dividing and marking a river catchment area in the reservoir area according to the confluence node and sending the division and marking result data to the visualization module;
the parameter monitoring module is used for collecting a water sample at a water collection node, detecting nitrogen and water quality parameter information through a sensor and sending the information to the information processing module;
the information processing module is used for screening the received nitrogen and water quality parameter information, establishing a fingerprint, substituting each parameter index into a receptor model, calculating the nitrogen contribution rate parameter in the corresponding partition of the river step by step, and sending the nitrogen contribution rate parameter to the visualization module;
and the visualization module is used for receiving the data output by the modules and carrying out superposition visualization display on the map.
2. The system for multi-level source analysis visualization of nitrogen contamination in reservoirs of claim 1, wherein the catchment division module comprises a division unit and a division marking unit;
the partition dividing unit is used for reading the DEM geographical elevation image and dividing the catchment area according to the river catchment flow direction; merging catchment areas which are the same in type and adjacent in position according to the type and spatial position distribution of the pollution source;
the subarea marking unit is used for grading the current subarea according to the spatial relation of the river flow direction and marking the current subarea in the affiliated subarea on the map; the marker is in the form of M-N; wherein, M is catchment district grade, "-" is the separator, N is catchment district code under the present grade, M-N represents catchment district N of M rank.
3. The system for the multi-stage source-resolved visualization of nitrogen contamination in reservoirs according to claim 1, wherein the information processing module (I) comprises a fingerprint spectrum unit (I)S) Model calculation unit (I)P)；
The fingerprint unit comprises a parameter screening subunit and a fingerprint unit; the parameter screening subunit is used for screening and dimension normalization processing on the nitrogen and water quality parameter information; the fingerprint spectrum unit is used for establishing a fingerprint spectrum according to the normalized index parameter values;
and the model calculation unit is used for substituting the nitrogen and water quality parameter indexes into a receptor model, generating nitrogen contribution rate parameters in the partition corresponding to the river and sending the nitrogen contribution rate parameters to the visualization module.
4. The system for the multi-stage source-resolved visualization of nitrogen contamination in reservoirs of claim 1, wherein the visualization module (V) comprises a data storage unit (V)S) Two-dimensional display unit (V)D)；
The data storage unit is used for classifying and storing river catchment area division results and division marks in the reservoir area, fingerprint patterns established by the fingerprint pattern unit and nitrogen contribution rate data in the division areas generated by the model calculation unit;
the two-dimensional display unit is used for drawing a boundary outline of a river catchment area and displaying a subarea mark on a map, and is used for displaying a fingerprint map on a two-dimensional coordinate system; the method is used for displaying the nitrogen contribution rate parameter in different shades of different colors in a superposed mode in a river catchment area of a corresponding reservoir area on a map.
5. The system for multi-stage source-resolved visualization of reservoir nitrogen contamination according to any one of claims 1-4, wherein the nitrogen and other water quality indicators comprise:
the nitrogen indexes comprise total nitrogen TN and ammonia nitrogen NH4 +-N, nitro nitrogen NO3 --N, nitrosnitrogen NO2 --N；
Other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
6. The method for analyzing and visualizing the multilevel source of the reservoir nitrogen pollution is characterized by comprising the following steps;
the catchment area division module divides and marks the river catchment area in the reservoir area according to the confluence node, and sends the division and marking result data to the visualization module;
the parameter monitoring module collects a water sample at a water collection node, detects nitrogen and water quality parameter information through a sensor and sends the information to the information processing module;
the information processing module screens the received nitrogen and water quality parameter information, establishes a fingerprint, substitutes each parameter index into a receptor model to calculate the nitrogen contribution rate parameter in the corresponding subarea of the river and sends the nitrogen contribution rate parameter to the visualization module;
and the visualization module receives the data output by the modules and performs superposition visualization display on the map.
7. The method for multi-level source analysis visualization of reservoir nitrogen contamination according to claim 6, wherein the catchment division module performs the steps of:
the partition dividing unit reads the DEM geographical elevation image and divides a catchment area according to the river catchment flow direction; merging catchment areas which are the same in type and adjacent in position according to the type and spatial position distribution of the pollution source;
the subarea marking unit grades the current subarea according to the river flow direction and marks the current subarea in the affiliated subarea on the map; the marker is in the form of M-N; wherein, M is catchment district grade, "-" is the separator, N is catchment district code under the present grade, M-N represents catchment district N of M rank.
8. The method for multi-level source analysis visualization of reservoir nitrogen contamination according to claim 6, wherein the information processing module performs the steps of:
the fingerprint unit comprises a parameter screening subunit and a fingerprint unit; the parameter screening subunit screens and normalizes the nitrogen and water quality parameter information; the fingerprint unit establishes a fingerprint according to the normalized index parameter values;
and the model calculation unit substitutes the nitrogen and water quality parameter indexes into a receptor model to generate a nitrogen contribution rate parameter in the partition corresponding to the river and sends the nitrogen contribution rate parameter to the visualization module.
9. The method for multi-level source-resolved visualization of nitrogen contamination in a reservoir of claim 6, wherein the visualization module performs the steps of:
the data storage unit classifies the river catchment area division result and the subarea marks in the reservoir area, the fingerprint spectrum established by the fingerprint spectrum unit and the subarea nitrogen contribution rate data generated by the model calculation unit;
the two-dimensional display unit draws the boundary outline of the river catchment area and the display partition marks on the map, displays the fingerprint spectrum on the two-dimensional coordinate system, and displays the nitrogen contribution rate parameters in the river catchment area of the corresponding reservoir area on the map in a superposition manner by different colors with different intensities and depths.
10. The method for multi-stage source-resolved visualization of reservoir nitrogen contamination according to any one of claims 6-9, wherein the nitrogen and other water quality indicators comprise:
the nitrogen indexes comprise total nitrogen TN and ammonia nitrogen NH4 +-N, nitro nitrogen NO3 --N, nitrosnitrogen NO2 --N；
Other water quality indicators include total phosphorus, pH, conductivity, iron, manganese.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010960178.6A CN112305182B (en) | 2020-09-14 | 2020-09-14 | Multi-level source analysis visualization system and method for reservoir nitrogen pollution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010960178.6A CN112305182B (en) | 2020-09-14 | 2020-09-14 | Multi-level source analysis visualization system and method for reservoir nitrogen pollution |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112305182A true CN112305182A (en) | 2021-02-02 |
| CN112305182B CN112305182B (en) | 2022-11-01 |
Family
ID=74483853
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010960178.6A Active CN112305182B (en) | 2020-09-14 | 2020-09-14 | Multi-level source analysis visualization system and method for reservoir nitrogen pollution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112305182B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116912445A (en) * | 2023-09-07 | 2023-10-20 | 湖南省水务规划设计院有限公司 | Urban and rural water supply three-dimensional dynamic visualization method |
-
2020
- 2020-09-14 CN CN202010960178.6A patent/CN112305182B/en active Active
Non-Patent Citations (5)
| Title |
|---|
| 刘丽雅等: "浑河傍河区地下水氮污染来源贡献研究", 《岩土工程技术》 * |
| 孙阳等: "三峡水库氮磷污染贡献率估算", 《重庆大学学报(自然科学版)》 * |
| 孟利等: "基于PCA-APCS-MLR的地下水污染源定量解析研究", 《中国环境科学》 * |
| 谢汝芹等: "于桥水库富营养化时间特征及污染源解析", 《水资源与水工程学报》 * |
| 郭书海等: "水生态功能区划流程:双关系树框架与概念模型", 《应用生态学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116912445A (en) * | 2023-09-07 | 2023-10-20 | 湖南省水务规划设计院有限公司 | Urban and rural water supply three-dimensional dynamic visualization method |
| CN116912445B (en) * | 2023-09-07 | 2023-12-05 | 湖南省水务规划设计院有限公司 | Urban and rural water supply three-dimensional dynamic visualization method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112305182B (en) | 2022-11-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Van Sickle | Using mean similarity dendrograms to evaluate classifications | |
| Bouza-Deaño et al. | Trend study and assessment of surface water quality in the Ebro River (Spain) | |
| CN103345566B (en) | Based on the geochemical anomaly discrimination and evaluation method of Geological Connotation | |
| Pesch et al. | Mosses as bioindicators for metal accumulation: Statistical aggregation of measurement data to exposure indices | |
| Li et al. | Improved gray water footprint calculation method based on a mass-balance model and on fuzzy synthetic evaluation | |
| CN109101781A (en) | The calculation method of pollution sources contribution proportion in a kind of Complex River | |
| CN108304680B (en) | WebGIS-based sewage discharge port planning simulation and evaluation system | |
| CN110765419B (en) | Important water functional area water quality risk assessment method based on multi-source data coupling | |
| Pisati | Exploratory spatial data analysis using Stata | |
| CN111914942A (en) | Multi-table-combined one-use energy anomaly analysis method | |
| CN112948761A (en) | River nitrogen pollutant quantitative source analysis system | |
| CN112305182B (en) | Multi-level source analysis visualization system and method for reservoir nitrogen pollution | |
| CN114022008A (en) | Estuary suitable ecological flow assessment method based on water ecological zoning theory | |
| CN113111964A (en) | Site pollution characteristic analysis method and device, electronic equipment and storage medium | |
| Pisati | Spatial Data Analysis in Stata an Overview | |
| Dash et al. | Application of Environmetrics tools for geochemistry, water quality assessment and apportionment of pollution sources in Deepor Beel, Assam, India | |
| CN116483807A (en) | Construction method of soil pollutant environment and toxicity database | |
| Karami et al. | Analysis of the spatio-temporal patterns of water pollution and source contribution using the MODIS sensor products and multivariate statistical techniques | |
| CN116756572B (en) | Construction method based on mangrove ecological system distribution data set | |
| Xu et al. | Developing a quantitative landscape regionalization framework integrating driving factors and response attributes of landscapes | |
| Ashwin et al. | Correlation, regression analysis, and spatial distribution mapping of WQI for an urban Lake in Noyyal River Basin in the textile capital of India | |
| He et al. | Problems in air quality monitoring and assessment | |
| Masrofah et al. | Clustering of the water characteristics of the Cirata reservoir using the k-means clustering method | |
| Lahlou et al. | Towards the development of an improved mass balance and water quality index based grey water footprint model | |
| Benini et al. | Indicators and targets for the reduction of the environmental impact of EU consumption: Overall environmental impact (resource) indicators-Deliverable 3 |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |