CN105678056A - River water ecosystem monitoring sampling point optimal selection method based on clustering - Google Patents
River water ecosystem monitoring sampling point optimal selection method based on clustering Download PDFInfo
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- CN105678056A CN105678056A CN201511023704.1A CN201511023704A CN105678056A CN 105678056 A CN105678056 A CN 105678056A CN 201511023704 A CN201511023704 A CN 201511023704A CN 105678056 A CN105678056 A CN 105678056A
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Abstract
The invention relates to a river water ecosystem monitoring sampling point optimal selection method based on clustering. The river water ecosystem monitoring sampling point optimal selection method based on clustering solves the problem that sampling points in existing methods cannot reflect the water quality condition of river water comprehensively and accurately. 1, data of original sampling points are preprocessed; 2, fuzzy c-means clustering is carried out to indexes of sampling points of the river water ecosystem; 3, indexes and detection sections in the step 1 and clustering results in the step 2 are combined to optimize the sampling points. The river water ecosystem monitoring sampling point optimal selection method based on clustering is applied to the river water ecosystem monitoring field.
Description
Technical field
The present invention relates to the river aquatic ecosystem monitoring sampled point method for optimizing based on cluster.
Background technology
Ecosystem is the basic component units that life on earth supports system, and maintenance the service function constantly strengthening ecosystem are that the whole mankind is in encountered jointly the challenging of new century. But since the industrial revolution, owing to population increase and too fast process of industrialization make ecosystem provide the function of products & services to receive great infringement.
The idea representation that current Ecology is destroyed: river black smelly, eutrophication is serious, biological chain seriously group incomplete, corrupt occupies an leading position, and even receives nuclear pollution.
The mankind are had vital effect as the part of ecosystem by river, therefore, must adopt a series of measures river is optimized, and China is vast in territory, substantial amounts of river comprehensively cannot be detected, then how river aquatic ecosystem rationally being selected sampled point is the major issue faced.
Existing methodical sampled point can not the water quality situation in comprehensive and accurate reflection river, therefore, river aquatic ecosystem monitoring sampled point preferably become the problem primarily now studied.
Summary of the invention
The present invention is to solve existing methodical sampled point can not the water quality situation in comprehensive and accurate reflection river, and propose the river aquatic ecosystem monitoring sampled point method for optimizing based on cluster.
Based on the river aquatic ecosystem monitoring sampled point method for optimizing of cluster, it realizes according to the following steps:
One, crude sampling point data is carried out pretreatment;
(1) section of water quality of river being sampled is configured with sample point;
(2) candidate can directly reflect the index of river aquatic ecosystem monitoring result;
(3) in SPSS software, the index in step (2) being screened, screening principle is:
A () parameter is to river aquatic ecosystem signature contributions rate;
B the independence of index is analyzed by (): first index carries out just too distribution inspection, then to meeting the index employing Pearson correlation analysis being just distributed very much, does not meet the index being just distributed very much and adopts Spearman rank correlation analysis;
C () determines information overlap degree between each index finally according to significance level, choose wherein relatively independent and important index as evaluation index;
Two, the sampled point index of river aquatic ecosystem is carried out fuzzy C-means clustering;
(1) using each index as a class, chosen distance formula also calculates the distance between all kinds of index;
(2) find out two closest class indexs, merged, and redefine the distance between new class and former class for a new class index;
(3) step (2) makes constantly to merge between class with class repeatedly, and last all samples are classified as a class, then cluster process terminates;
(4) calculate each index weights, and carry out sequence from big to small, be monitored the optimization of section in combination with spot optimization principle;
Three, the index of integrating step one selects the index that weight coefficient is big to be optimized with monitoring section and the cluster result in step 2.
Invention effect:
The present invention passes through to carry out being configured huge river aquatic ecosystem being carried out preliminary optimization with sample point to water quality of river sampling section, then pass through and index is carried out cluster optimization, similar index can be classified as a class, in order to avoid repeating to choose, especially calculate weight and determine the impact of all kinds of index, and then aquatic ecosystem monitoring sampled point in river is carried out preferably.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention.
Detailed description of the invention
Detailed description of the invention one: the river aquatic ecosystem monitoring sampled point method for optimizing based on cluster of present embodiment, it
Realize according to the following steps:
Two, crude sampling point data is carried out pretreatment;
(3) section of water quality of river being sampled is configured with sample point;
(4) candidate can directly reflect the index of river aquatic ecosystem monitoring result;
(3) in SPSS software, the index in step (2) being screened, screening principle is:
A () parameter is to river aquatic ecosystem signature contributions rate;
B the independence of index is analyzed by (): first index carries out just too distribution inspection, then to meeting the index employing Pearson correlation analysis being just distributed very much, does not meet the index being just distributed very much and adopts Spearman rank correlation analysis;
C () determines information overlap degree between each index finally according to significance level, choose wherein relatively independent and important index as evaluation index;
Two, the sampled point index of river aquatic ecosystem is carried out fuzzy C-means clustering;
(1) using each index as a class, chosen distance formula also calculates the distance between all kinds of index;
(2) find out two closest class indexs, merged, and redefine the distance between new class and former class for a new class index;
(3) step (2) makes constantly to merge between class with class repeatedly, and last all samples are classified as a class, then cluster process terminates;
(4) calculate each index weights, and carry out sequence from big to small, be monitored the optimization of section in combination with spot optimization principle;
Three, the index of integrating step one selects the index that weight coefficient is big to be optimized with monitoring section and the cluster result in step 2.
Detailed description of the invention two: present embodiment and detailed description of the invention one the difference is that: the section that water quality of river is sampled in step one being set to sample point:
(1) generally should laying the section of comparison, control, abatement three types, following principle is mainly followed in the laying of sampling section
(1) sampling section should be laid at the two ends of survey scope;
(2) lay special stress on protecting object Its Adjacent Waters in survey scope and should lay sampling section;
(3) hydrological characteristics change place suddenly; Water quality sharp change in elevation; Emphasis water conservancy project structure; Near should lay sampling section;
(4) sampling section should be laid near hydrometric station etc., and with due regard to water quality prediction the point concerned;
(5) plan to build into 500m place, sewage draining exit upstream should arrange one sampling section;
(2) principle that on sampling section, sampling of water quality vertical line is arranged
Each section part lays sampling of water quality vertical line according to river width;
When cross section of river is shaped as rectangle or is comparable to rectangle, can lay by following principle
River: set a sampling vertical on the main stream line of sampling section;
Big and middle river: river width, less than 45m person, sets two sampling verticals altogether, respectively respectively sets a sampling vertical from the wide place of the water surface, bank 1/4 on sampling section; River width, more than 45m person, sets three sampling verticals altogether, no less than 0.45m on main stream line and from two sides, and has the place of appreciable current respectively to set a sampling vertical;
(3) principle that on vertical line, sampling of water quality point is arranged
Every vertical line lays sampling of water quality point according to the depth of water;
On a vertical line, when the depth of water is more than 5m, at 0.5m depth of water place, underwater and from 0.5m place, river bed, each sampling one; When the depth of water is 1～5m, only take a sample at 0.5m place, underwater; When water depth deficiency 1m, sample point is no less than 0.3m from the water surface, is also no less than 0.3m from river bed;
For three grades of rivers evaluated, no matter the river depth, only taking a sample on a vertical line, generally sample point at 0.5m place, underwater, should be no less than 0.3m from river bed.
Other step and parameter and detailed description of the invention one are identical.
Claims (2)
1. based on the river aquatic ecosystem monitoring sampled point method for optimizing of cluster, it is characterised in that it realizes according to the following steps:
One, crude sampling point data is carried out pretreatment;
(1) section of water quality of river being sampled is configured with sample point;
(2) candidate can directly reflect the index of river aquatic ecosystem monitoring result;
(3) in SPSS software, the index in step (2) being screened, screening principle is:
A () parameter is to river aquatic ecosystem signature contributions rate;
B the independence of index is analyzed by (): first index carries out just too distribution inspection, then to meeting the index employing Pearson correlation analysis being just distributed very much, does not meet the index being just distributed very much and adopts Spearman rank correlation analysis;
C () determines information overlap degree between each index finally according to significance level, choose wherein relatively independent and important index as evaluation index;
Two, the sampled point index of river aquatic ecosystem is carried out fuzzy C-means clustering;
(1) using each index as a class, chosen distance formula also calculates the distance between all kinds of index;
(2) find out two closest class indexs, merged, and newly define the distance between new class and former class for a new class index;
(3) step (2) makes constantly to merge between class with class repeatedly, and last all samples are classified as a class, then cluster process terminates;
(4) calculate each index weights, and carry out sequence from big to small, carry out the optimization of detection section in combination with spot optimization principle;
Three, the index of integrating step one selects the index that weight coefficient is big to be optimized with detection section and the cluster result in step 2.
2. the river aquatic ecosystem monitoring sampled point method for optimizing of cluster according to claim 1, it is characterised in that the section that water quality of river is sampled in step one is set to sample point:
(1) generally should laying the section of comparison, control, abatement three types, following principle is mainly followed in the laying of sampling section:
(1) sampling section should be laid at the two ends of survey scope;
(2) lay special stress on protecting object Its Adjacent Waters in survey scope and should lay sampling section;
(3) hydrological characteristics change place suddenly; Water quality sharp change in elevation; Emphasis water conservancy project structure; Near should lay sampling section;
(4) sampling section should be laid near hydrometric station etc., and with due regard to water quality prediction the point concerned;
(5) plan to build into 500m place, sewage draining exit upstream should arrange one sampling section;
(2) principle that on sampling section, sampling of water quality vertical line is arranged
Each section part lays sampling of water quality vertical line according to river width;
When cross section of river is shaped as rectangle or is comparable to rectangle, can lay by following principle:
River: set a sampling vertical on the main stream line of sampling section;
Big and middle river: river width, less than 45m person, sets two sampling verticals altogether, respectively respectively sets a sampling vertical from the wide place of the water surface, bank 1/4 on sampling section; River width, more than 45m person, sets three sampling verticals altogether, no less than 0.45m on main stream line and from two sides, and has the place of appreciable current respectively to set a sampling vertical;
(3) principle that on vertical line, sampling of water quality point is arranged
Every vertical line lays sampling of water quality point according to the depth of water;
On a vertical line, when the depth of water is more than 5m, at 0.5m depth of water place, underwater and from 0.5m place, river bed, each sampling one; When the depth of water is 1～5m, only take a sample at 0.5m place, underwater; When water depth deficiency 1m, sample point is no less than 0.3m from the water surface, is also no less than 0.3m from river bed;
For three grades of rivers evaluated, no matter the river depth, only taking a sample on a vertical line, generally sample point at 0.5m place, underwater, should be no less than 0.3m from river bed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108195775A (en) * | 2017-12-25 | 2018-06-22 | 环境保护部卫星环境应用中心 | The indicative water quality monitoring website confirmation method in lake library and device based on remote sensing image |
| CN109962982A (en) * | 2019-03-29 | 2019-07-02 | 中海生态环境科技有限公司 | A kind of river and lake water ecological environment monitoring system based on Internet of Things |
-
2015
- 2015-12-29 CN CN201511023704.1A patent/CN105678056B/en active Active
Non-Patent Citations (4)
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| Y ZHANG ET AL.: "River Health Assessment Based on Fuzzy Matter-element Model", 《METEOROLOGICAL AND ENVIRONMENTAL RESEARCH》 * |
| 中华人民共和国环境保护行业标准: "环境影响评价技术导则 地面水环境", 《中华人民共和国环境保护行业标准》 * |
| 张楠 等: "辽河流域河流生态系统健康的多指标评价方法", 《环境科学研究》 * |
| 邱顺凡: "村镇地表水体水质监测点优化布置与水质评价方法研究", 《中国优秀硕士学位论文全文数据库工程科技Ⅰ辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108195775A (en) * | 2017-12-25 | 2018-06-22 | 环境保护部卫星环境应用中心 | The indicative water quality monitoring website confirmation method in lake library and device based on remote sensing image |
| CN109962982A (en) * | 2019-03-29 | 2019-07-02 | 中海生态环境科技有限公司 | A kind of river and lake water ecological environment monitoring system based on Internet of Things |
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Inventor after: Zhang Yu Inventor after: Cong Peitong Inventor after: He Yanhai Inventor after: Yuan Shaoxiong Inventor after: Li Mao Inventor after: Su Fangwei Inventor before: Zhang Yu Inventor before: He Yanhai Inventor before: Yang Jingfeng Inventor before: Zhang Jintuan Inventor before: Li Mao Inventor before: Su Fangwei |
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Effective date of registration: 20171025 Address after: 510000 No. 100 courtyard, martyrs Road, Guangdong, Guangzhou Applicant after: Guangzhou Institute of Geography Address before: Guangzhou City, Guangdong province 510070 martyrs Road No. 100 Applicant before: Zhang Yu |
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Address after: 510075 one of the compound No. 100, Xianlie Middle Road, Yuexiu District, Guangzhou City, Guangdong Province Patentee after: Guangzhou Institute of geography, Guangdong Academy of Sciences Address before: 510000 one of the compound No. 100, Xianlie Middle Road, Guangzhou, Guangdong Province Patentee before: GUANGZHOU INSTITUTE OF GEOGRAPHY |
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