CN105809578A - Regional water environment risk evaluating and region dividing method - Google Patents
Regional water environment risk evaluating and region dividing method Download PDFInfo
- Publication number
- CN105809578A CN105809578A CN201610371501.XA CN201610371501A CN105809578A CN 105809578 A CN105809578 A CN 105809578A CN 201610371501 A CN201610371501 A CN 201610371501A CN 105809578 A CN105809578 A CN 105809578A
- Authority
- CN
- China
- Prior art keywords
- water
- water environment
- index
- factor
- layer
- 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
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 145
- 238000000034 method Methods 0.000 title claims abstract description 60
- 238000011156 evaluation Methods 0.000 claims abstract description 23
- 230000008569 process Effects 0.000 claims abstract description 19
- 230000004044 response Effects 0.000 claims abstract description 15
- 238000004088 simulation Methods 0.000 claims description 31
- 238000012502 risk assessment Methods 0.000 claims description 27
- 238000011161 development Methods 0.000 claims description 23
- 239000011159 matrix material Substances 0.000 claims description 11
- 238000005192 partition Methods 0.000 claims description 9
- 238000007726 management method Methods 0.000 claims description 8
- 238000012544 monitoring process Methods 0.000 claims description 8
- 238000013139 quantization Methods 0.000 claims description 6
- 238000013316 zoning Methods 0.000 claims description 5
- 238000013459 approach Methods 0.000 claims description 4
- 201000010099 disease Diseases 0.000 claims description 4
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 4
- 230000001737 promoting effect Effects 0.000 claims description 4
- 239000010865 sewage Substances 0.000 claims description 4
- 230000007547 defect Effects 0.000 claims description 3
- 230000000694 effects Effects 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 239000002352 surface water Substances 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 2
- 230000008859 change Effects 0.000 claims description 2
- 239000012141 concentrate Substances 0.000 claims description 2
- 238000013210 evaluation model Methods 0.000 claims description 2
- 239000003295 industrial effluent Substances 0.000 claims description 2
- 239000010842 industrial wastewater Substances 0.000 claims description 2
- 238000004162 soil erosion Methods 0.000 claims description 2
- 239000002351 wastewater Substances 0.000 claims description 2
- 230000007613 environmental effect Effects 0.000 description 19
- 238000011160 research Methods 0.000 description 7
- 231100000290 environmental risk assessment Toxicity 0.000 description 6
- 238000004364 calculation method Methods 0.000 description 5
- 230000008901 benefit Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000000205 computational method Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000013332 literature search Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000005303 weighing Methods 0.000 description 2
- 201000004569 Blindness Diseases 0.000 description 1
- 206010008190 Cerebrovascular accident Diseases 0.000 description 1
- 241001269238 Data Species 0.000 description 1
- 241001317416 Lius Species 0.000 description 1
- 101100128278 Mus musculus Lins1 gene Proteins 0.000 description 1
- 208000006011 Stroke Diseases 0.000 description 1
- 239000000654 additive Substances 0.000 description 1
- 230000000996 additive effect Effects 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 239000003651 drinking water Substances 0.000 description 1
- 235000020188 drinking water Nutrition 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 238000013439 planning Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000001303 quality assessment method Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000013517 stratification Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 239000013598 vector Substances 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Classifications
-
- 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
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a regional water environment risk evaluating and region dividing method. The method includes: building regional water environment risk evaluating models based on DPSI R models so as to build regional water environment risk evaluating index systems, wherein each DPSI R model comprises a drive force factor, a pressure factor, a state factor, an influence factor and a response factor; using analytic hierarchy process to calculate the weight of the indexes and assign the indexes, and performing quantitative classification on the index systems; using a fuzzy comprehensive evaluation method to calculate the risk values of regional water environments; dividing regions according to the risk level; analyzing the leading factors of risks through a component analyzing method. By the method, the regional water environments can be evaluated accurately, and the accurate basis can be provided for decisions.
Description
Technical field
The present invention relates to the data analysis and process technology of water environment evaluation areas, particularly relate to a kind of Regional Water Environment risk assessment and partition method.
Background technology
Due to social economy, developing rapidly of industrial or agricultural and constantly accelerating of urbanization process, all parts of the world district ambient pressure also increases day by day.20 century 70s, the U.S. first proposed the concept of environmental risk assessment (ERA), and it is approved gradually by countries such as west America and Europes subsequently.Water environments simulation assessment (WERA) is as the important component part of environmental risk assessment, and it is on the basis of environmental risk assessment, carries out the identification of the various potential risk of water environment and the process of water environment cases probability of happening evaluation work.As the important directions of ERA, it plays key player in Water environments simulation prediction with water environment cases prevention.
Beijing-tianjin-hebei Region is that north of China economy is the most flourishing, the most potential area, including Beijing and Tianjin two municipality directly under the Central Government and prefecture-level city of 11, Hebei province.But, along with the fast development of regional economy, its environmental problem is gradually evolved into as a regional difficult problem, and environmental risk is constantly accumulated, and crowd's equivalent risk receptor is continuously increased, and resosurces environment loading capacity is more weak, causes environmental accident once occur, and is just likely to produce serious consequence.On April 30th, 2015; Political Bureau of the Central Committee's meeting is approved " Jing-jin-ji region cooperative development planning outline " and is pointed out; promoting Beijing-tianjin-hebei Region cooperative development is a great national strategy; it is the needs promoting resource environment to be uniformly coordinated; the proposition of this strategy, accelerates the Jing-jin-ji region process of integration, while bringing opportunity for regional development; again its sustainable development is had higher requirement, bring bigger challenge also to region environment integration conservative management.In this context, carrying out Water environments simulation evaluation work in Beijing-tianjin-hebei Region can provide decision-making foundation for manager, can effectively predict Water environments simulation simultaneously, with feasible region water environment and economic sustainable development.
Nowadays, WERA is widely used in the excessive risk factor identified in water environment.Along with the enhancing gradually of people's environmental consciousness, a lot of methods are used to WERA: Graphics overlay method, information diffusion method, index system method, fuzzy integrated judgement method etc..Wherein index system method has advantage succinct, quick, the high and low consumption of efficiency.SunF etc. establish an index system and (specifically ask for an interview FS, JC, QT, SZ:Integratedriskassessmentandscreeninganalysisofdrinkin gwatersafetyofaconventionalwatersupplysystem.Waterscienc eandTechnology2007,56:47-56.), region safe drinking water risk is evaluated by the method in conjunction with screening strength and Graphics testing matrix, establishes risk assessment procedures, and hydrological vulnerability has been characterized.WangB etc. have carried out risk of environmental pollution research (WangB in basin, Baiyang Lake, ChengH:EnvironmentalRiskzoningResearchinBaiyangdianBasin .ProcediaEnvironmentalSciences2011,10:2280-6.), by GIS and RS technology, establish a simple index system to assess flood and shortage of water resources risk, simultaneously complete quantifying risk and risk visualization.
If but certain theoretical foundation is lacked when setting up index system, the blindness of evaluation will be increased, cause the irrationality of evaluation result, not scientific.Therefore based on PSR, DSR model improved, industry proposes a kind of DPSIR (DriversPressuresStatesImpactsResponses；Driving, pressure, state, impact and response) model, and by OECD (OrganizationforEconomicCooperationandDevelopment, the Organization of Economy and Cooperation Development) promote in the nineties in last century, and further developed by IGBPLOICZ.It can capture " cause-effect " relation between society, economy, environmental system, is therefore widely used in analyzing the interaction process of human environmental systems.nullZHANGS etc. propose a kind of regional environment based on PSR model and health risk assessment index system，And binding hierarchy analytic process (AHP) determines weight ([16] ZhangS,WeiZ,LiuW,YaoL,SuoW,XingJ,HuangB,JinD,WangJ:IndicatorsforEnvironmentHealthRiskAssessmentintheJiangsuProvinceofChina.Internationaljournalofenvironmentalresearchandpublichealth2015,12:11012-24.)；nullAnd XuEGB etc. propose a kind of for marine conservation areas、Environmental Risk Evaluation Method based on multilamellar DPSIR model，And generate a data base assist management (XuEGB,LeungKMY,MortonB,LeeJHW:Anintegratedenvironmentalriskassessmentandmanagementframeworkforenhancingthesustainabilityofmarineprotectedareas:theCaped'AguilarMarineReservecasestudyinHongKong.TheScienceofthetotalenvironment2015,505:269-81.).In general, DPSIR model can simplify the water environmental problems of complexity, makes policymaker be easier to grasp the water environment situation in area under one's jurisdiction.
In Risk Calculation method, existing research major part represents risk level with the simple product of weight and value-at-risk, reduces the levels of precision of result of calculation.Fuzzy integrated judgement method has the advantage such as clear in structure and high systematicness and is widely used in value-at-risk calculating, solves fuzzy and uncertain problem.
PeibinG etc. use analytic hierarchy process (AHP) and expert graded and Field Using Fuzzy Comprehensive Assessment that west area has been carried out sound environment risk assessment, and analysis has drawn the principal element (PeibinG affecting result, BaojiangS, GangL, YongW:Fuzzycomprehensiveevaluationinwellcontrolriskasses smentbasedonAHP.AdvancesinPetroleumExplorationandDevelop ment2012,4:13-8.).Mia Audina etc. tentatively establish the urban eco landscape forest model based on fuzzy integrated judgement method assess Grand Liao River pollution situation (Mia Audina: Daliaohe Estuary water environment pollution ecological risk assessment index system and technical method research. Qingdao: Chinese Marine University, 2013.).
But, there is seldom research can comprehensively utilize above-mentioned several method, be regarded as entirety and Regional Water Environment risk is estimated.
Summary of the invention
Based on drawbacks described above, the purpose of the embodiment of the present invention is to propose a kind of Regional Water Environment risk assessment and partition method, can according to the theory of DPSIR model using Water environments simulation system as one by formed and control environmental risk various key elements organically combine entirety, build comprehensive and systematic Water environments simulation evaluation index system with this.
In order to achieve the above object, the embodiment of the present invention proposes a kind of Regional Water Environment risk assessment and partition method, including:
Step 1, set up based on the Regional Water Environment risk evaluation model of DPSIR model to build Regional Water Environment Risk Assessment Index System；Wherein said DPSIR model includes driving force factors, press factors, state factor, factor of influence, response factor；
Step 2, employing analytic hierarchy process (AHP) calculate each index weights assignment, then by each index system quantization modulation；
Step 3, again through Field Using Fuzzy Comprehensive Assessment, the value-at-risk of zoning water environment；According to risk class, region is carried out subregion；
Step 4, by componential analysis, risk leading factor is analyzed.
Wherein, described step 1 specifically includes:
Step 11, determine the driving force factors of DPSIR model, press factors, state factor, factor of influence, response factor；Wherein
Driving force factors is the latent factor promoting water environment pressure to increase or reduce, and is the indirect factor causing water environment to change, at least includes: socio-economic development speed, population rate of rise etc.；
Press factors is produce the direct driving force of Water environments simulation, characterizes social development to the demand of water resource and side effect that water environment is caused, at least includes: society's water-use efficiency, effluent sewage discharge；
State factor is describe Regional Water Environment situation and promote protection of the water environment to carry out required precondition, i.e. social-economic development status at least includes: water quality, the water yield, Ecology situation；
Factor of influence is the impact under driving force direct, indirect promotes, Regional Water Environment and resident living caused；
Response factor is the control measures that the various risks that water environment is faced are taked；
Step 12, build Regional Water Environment Risk Assessment Index System, described structure Regional Water Environment Risk Assessment Index System include from different perspectives the destination layer of reflecting regional Water environments simulation, system layer, rule layer, indicator layer；
Wherein said system layer includes at least following five parameters: driving force, pressure, state, impact, response；
Wherein corresponding three the rule layer parameters of driving force: population growth, economic development, social development；The indicator layer that wherein population growth is corresponding includes: the natural growth rate of population, population density；Indicator layer corresponding to economic development includes: GPD annual rate of growth, GDP per capita；The indicator layer that social development is corresponding includes: Engel's coefficient；
Wherein corresponding two the rule layer parameters of pressure: ambient pressure, resource pressure；The indicator layer that wherein ambient pressure is corresponding includes: state key monitoring enterprise density, discharged volume of industrial waste water, sanitary sewage discharge capacity, COD annual emissions, agriculture chemical make consumption；The indicator layer that wherein resource pressure is corresponding includes: ten thousand yuan of GDP water consumptions, per capita water consumption；
Wherein corresponding four the rule layer parameters of state: the water yield, water quality, Ecology, receptor；The indicator layer that wherein water yield is corresponding includes: water resources ownership per capita；Indicator layer corresponding to water quality includes: Water Functional Zone probability of meeting water quality standard；The indicator layer that Ecology is corresponding includes: Wetland Area accounts for area under one's jurisdiction area ratio；The indicator layer that receptor is corresponding includes: sensitive group proportion；
Wherein corresponding three the rule layer parameters of impact: water environment, Ecology, resident living；The indicator layer that wherein water environment is corresponding includes: river, lake are inferior to Group III water quality accounting；The indicator layer that Ecology is corresponding includes: soil erosion area ratio；Indicator layer corresponding to resident living includes: concentrate water head site probability of meeting water quality standard, population average life, resident living water rate；
Wherein corresponding three the rule layer parameters of response: water resources management, water resource monitoring, stain disease process；The indicator layer that wherein water resources management is corresponding includes: water conservancy, environment, public infrastructure are invested per capita；The indicator layer of water resource monitoring correspondence includes: surface water quality monitoring section point figure place；Stain disease processes corresponding indicator layer and includes: wastewater reuse approach rate, treatment rate of industrial effluents.
Wherein, described step 2, again through Field Using Fuzzy Comprehensive Assessment, the value-at-risk of zoning water environment, specifically includes:
Step 21, according to hierarchical relationship between destination layer, system layer, rule layer, indicator layer, set up membership function, and calculate each index degree of membership for opinion rating；
Step 22, according to each hierarchical relationship of index system, set up structural model, set up fuzzy relation matrix by relative membership degree and function；Principle according to maximum membership degree determines final appraisal results.
Wherein, described step 21 specifically includes:
For reverse index, desired value is more little, and Water environments simulation is more high:
For forward index, desired value is more big, and Water environments simulation is more high:
Wherein xiRefer to i-th index；aiWith the kth level evaluation criterion that k is i-th index；rikRefer to i-th index relative defects for kth grade standard.
Wherein, described step 22 specifically includes:
Step 221, according to each hierarchical relationship of index system, set up structural model, set up fuzzy relation matrix by relative membership degree and function:
Wherein m index number contained by this grade；N is opinion rating number；
Step 222, it is divided into 4 layers due to Regional Water Environment Risk Assessment Index System, therefore n=4；It is sequentially carried out first, second and third grade of judge according to weight sets W and fuzzy relation matrix:
Wherein biFor the evaluation index degree of membership to i-th grade；
Principle according to maximum membership degree, take withCorresponding risk class is as the final appraisal results of this key element.
Having the beneficial effect that of the technique scheme of the present invention:
Regional Water Environment can be more estimated by such scheme accurately, thinks that decision-making provides foundation accurately.
Accompanying drawing explanation
Fig. 1 is the Regional Water Environment risk assessment subregion thinking figure of the embodiment of the present invention；
Fig. 2 is the DPSIR model evaluation block schematic illustration of the embodiment of the present invention；
Fig. 3 is the Field Using Fuzzy Comprehensive Assessment appraisal framework schematic diagram of the embodiment of the present invention.
Detailed description of the invention
For making the technical problem to be solved in the present invention, technical scheme and advantage clearly, it is described in detail below in conjunction with accompanying drawing and instantiation.
Water environments simulation assessment determines that the process of the impact that water environment causes by probability that Water environments simulation occurs, the vulnerability of water environment and the generation of prediction accident.At present, Water environments simulation appraisal procedure mainly has index system method, neural network, gray forecast approach, weighted risk analysis method, accident tree method etc..And nowadays, the height of Water environments simulation is closely bound up with Levels of Social Economic Development.Therefore, compared with additive method, building DPSIR modelling and can consider environment and economic two big factors, it has been applied to the field such as environmental management and sustainable utilization of water resource at present.DPSIR model is to develop on the basis that PSR model and DSR model are revised, and it describes the chain of causation between origin and a result causing environmental problem.The embodiment of the present invention is based on DPSIR model, consider the pressure that water environment is applied by the driving force causing Water environments simulation to occur and human society, and then there is the impact on the generation of water environment state in assessment risk, and this is affected the active response made by the mankind, to complete Water environments simulation assessment.
The Regional Water Environment risk assessment of the embodiment of the present invention and the mentality of designing of subregion are as shown in Figure 1, the embodiment of the present invention passes through the combination of index system method, mathematics method, analytic hierarchy process (AHP), build Water environments simulation assessment integrated approach system, thus complex environment condition is carried out comprehensively, simplification.
1, the Regional Water Environment risk assessment based on DPSIR model is set up:
DPSIR model is respectively with driving force factors, press factors, state factor, factor of influence, response factor for starting point, and five factors spread mutually and coordinate, and Water environments simulation is estimated.First, under index system method instructs, appraisal framework and index system are set up according to environmental risk assessment theory；
Secondly, carry out quantification calculating, i.e. computing system value-at-risk based on Field Using Fuzzy Comprehensive Assessment, calculate each index weights assignment in conjunction with AHP, by each index system quantization modulation；
Finally, according to result, with ArcGIS for aid, high risk area, apoplexy danger zone, low-risk district, calm danger zone it are divided into from high to low by risk.
2, Water environments simulation evaluation index system is built
The embodiment of the present invention, from Regional environment risk Systems Theory, builds Regional Water Environment risk indicator system；This index system is made up of destination layer, system layer, rule layer and indicator layer, with image study district Water environments simulation from different perspectives.Collect initial data need to according to calculate reach characterize risk purpose, it is contemplated that data can availability, the index to data deficiency, adopt equivalent substitution mode.The embodiment of the present invention for promote risk occur driving force, press factors, lay particular stress on consider study area is had the greatest impact industry, agricultural, domestic pollution source, to water environment state, venture influence assessment based on surface water.
The evaluation index system particular content of the embodiment of the present invention refers to table 1, and in table 1, from aforesaid four levels, (the destination layer unlisted), around DPSIR model, sets up Water environments simulation evaluation index system.This table, based on initial data, specifies the computational methods of each index, is integrated by data investigation, illustrates the effect status of each index and the collection source of initial data simultaneously.
Table 1 Water environments simulation evaluation index system
Note: [a] assesses locality, district statistical yearbook；[b] assesses district's local environment protection yearbook；[c] assesses district's local environment state publication；
[d] assesses local environment protection website, the Room, district；[e] assesses locality, district water resource publication；[f] China Statistical Yearbook；
[g] China Environmental State Bulletin；[h] water resources in china publication；[i] document, data retrieval
3, Data Source
By consulting the modes such as the data such as each province and city yearbook, environmental aspect publication, literature search, data query, the content involved by index system, sort out the related data of each assessment unit.Consider data can availability and comprehensive, by data based on 2012 annual datas in the embodiment of the present invention, this simply realizes a kind of form of the present invention certainly.Driving force factors achievement data obtains mainly through the mode consulting each province and city yearbook, Chinese city yearbook and literature search；Press factors achievement data, except by above-mentioned channel, obtains also by consulting environmental conservation yearbook.Other level of factor data acquiring mode refer to table 1.
4, weight is arranged
After index system is built up, each index weight in index system need to be determined, characterize each index percentage contribution to environmental risk with this.At present, weighing computation method has levels analytic process (AnalyticHierarchyProcess, AHP), PCA, Information Entropy, state optimization method etc..Wherein analytic hierarchy process (AHP) is as the weighing computation method generally used at present, in conjunction with expert graded and qualitative-and-quantitative method, makes decision-making stratification, structuring.
Analytic hierarchy process (AHP): SaatyTL:Ascalingmethodforprioritiesinhierarchicalstructu res.JournalofMathematicalPsychology1977,15:234-81. this algorithm is according to influence degree between index system hierarchical relationship and each element, relative importance between agriculture products, with reference to 1-9 scale implication, development of judgment matrix.Adopt geometric method parameter layer relative to rule layer, rule layer relative to system layer, system layer relative to destination layer, totally three grades of weighted values, and representing in the form of vectors.Finally result of calculation is carried out consistency check, it is ensured that C.R. < 0.1 i.e. judgment matrix has better transitivity, concordance.The concrete calculation procedure of the method is referred to: TesfamariamS, SadiqR:Risk-basedenvironmentaldecision-makingusingfuzzya nalytichierarchyprocess (F-AHP) .StochasticEnvironmentalResearchandRiskAssessment2006,21: 35-50..Index weights result of calculation for the embodiment of the present invention refers to table 2.
Table 2 Water environments simulation evaluation index system quantization modulation and weight
5, index magnitude differentiation
Selected study area, and based on the data consulting acquisition, symbolical meanings in conjunction with each achievement data, with at utmost characterize each research unit driving force, pressure, state, impact, five factors of response diversity for starting point, in combination with the grade scale of defined in the corresponding specification of country, standard, index system is carried out quantization modulation, thus completing the scoring to each index, quantization modulation is the results detailed in Table 2.
6, Field Using Fuzzy Comprehensive Assessment
Based on model of fuzzy synthetic evaluation, study area Water environments simulation is estimated.First according to hierarchical relationship between destination layer, system layer, rule layer, indicator layer, set up membership function, and then calculate each index degree of membership for opinion rating.Each evaluation index degree of membership computational methods are as follows:
(1) for reverse index, desired value is more little, and Water environments simulation is more high:
(2) for forward index, desired value is more big, and Water environments simulation is more high:
Wherein xiRefer to i-th index；ai, k refer to the kth level evaluation criterion of i-th index；rikRefer to i-th index relative defects for kth grade standard.
According to each hierarchical relationship of index system, set up structural model, set up fuzzy relation matrix by relative membership degree and function:
Wherein m index number contained by this grade；N is opinion rating number.
This study area Water environments simulation evaluation index system is divided into 4 layers, and therefore need as shown in Figure 3 carry out three grades of judges, and opinion rating is 4 (i.e. n=4).According to weight sets W and fuzzy relation matrix, it is sequentially carried out first, second and third grade of judge:
Wherein biFor the evaluation index degree of membership to i-th grade；
Principle according to maximum membership degree, take withCorresponding risk class is as the final appraisal results of this key element.
The list of references that the present embodiments relate to is as follows, and the list of references being listed below is applied to this by the embodiment of the present invention in full:
[1]LiuSY,WangHQ,LiYL:CurrentProgressofEnvironmentalRiskAssessmentResearch.ProcediaEnvironmentalSciences2012,13:1477-83.
[2]SkinnerDJC,RocksSA,PollardSJT,DrewGH:IdentifyingUncertaintyinEnvironmentalRiskAssessments:TheDevelopmentofaNovelTypologyandItsImplicationsforRiskCharacterization.HumanandEcologicalRiskAssessment:AnInternationalJournal2014,20:607-40.
[3] Yin Rongyao, Yang Xiao, Sun Xiang, Zhu Xiaodong: the environmental risk classification of jiangsu coast Craft in Chemical Industrial Area and preferential management strategy research. China Environmental Science 2011,31:1225-32.
[4]DaiX,LiZ,LinS,XuW:Assessmentandzoningofeco-environmentalsensitivityforatypicaldevelopingprovinceinChina.StochasticEnvironmentalResearchandRiskAssessment2012,26:1095-107.
[5]GuptaAK,SureshIV,MisraJ,YunusM:Environmentalriskmappingapproach:riskminimizationtoolfordevelopmentofindustrialgrowthcentresindevelopingcountries.JournalofCleanerProduction2002,10:271-81.
[6]XuL,LiuG:Thestudyofamethodofregionalenvironmentalriskassessment.Journalofenvironmentalmanagement2009,90:3290-6.
[7]KucukaliS:Environmentalriskassessmentofsmallhydropower(SHP)plants:AcasestudyforTefenSHPplantonFilyosRiver.EnergyforSustainableDevelopment2014,19:102-10.
[8]UricchioVF,GiordanoR,LopezN:Afuzzyknowledge-baseddecisionsupportsystemforgroundwaterpollutionriskevaluation.Journalofenvironmentalmanagement2004,73:189-97.
[9]FS,JC,QT,SZ:Integratedriskassessmentandscreeninganalysisofdrinkingwatersafetyofaconventionalwatersupplysystem.WaterscienceandTechnology2007,56:47-56.
[10]WangB,ChengH:EnvironmentalRiskzoningResearchinBaiyangdianBasin.ProcediaEnvironmentalSciences2011,10:2280-6.
[11]WongAWM,WongMH:Recentsocio-economicchangesinrelationtoenvironmentalqualityofthePearlRiverdelta.RegionalEnvironmentalChange2004,4:28-38.
[12]FeldCK,SousaJP,daSilvaPM,DawsonTP:Indicatorsforbiodiversityandecosystemservices:towardsanimprovedframeworkforecosystemsassessment.BiodiversityandConservation2010,19:2895-919.
[13]PintoR,deJongeVN,NetoJM,DomingosT,MarquesJC,PatrícioJ:TowardsaDPSIRdrivenintegrationofecologicalvalue,waterusesandecosystemservicesforestuarinesystems.Ocean&CoastalManagement2013,72:64-79.
[14]HouY,ZhouS,BurkhardB,MullerF:Socioeconomicinfluencesonbiodiversity,ecosystemservicesandhumanwell-being:aquantitativeapplicationoftheDPSIRmodelinJiangsu,China.TheScienceofthetotalenvironment2014,490:1012-28.
[15]SunS,WangY,LiuJ,CaiH,WuP,GengQ,XuL:SustainabilityassessmentofregionalwaterresourcesundertheDPSIRframework.JournalofHydrology2016,532:140-8.
[16]ZhangS,WeiZ,LiuW,YaoL,SuoW,XingJ,HuangB,JinD,WangJ:IndicatorsforEnvironmentHealthRiskAssessmentintheJiangsuProvinceofChina.Internationaljournalofenvironmentalresearchandpublichealth2015,12:11012-24.
[17]XuEGB,LeungKMY,MortonB,LeeJHW:Anintegratedenvironmentalriskassessmentandmanagementframeworkforenhancingthesustainabilityofmarineprotectedareas:theCaped'AguilarMarineReservecasestudyinHongKong.TheScienceofthetotalenvironment2015,505:269-81.
[18]MaximL,SpangenbergJH,O'ConnorM:AnanalysisofrisksforbiodiversityundertheDPSIRframework.EcologicalEconomics2009,69:12-23.
[19]PeibinG,BaojiangS,GangL,YongW:FuzzycomprehensiveevaluationinwellcontrolriskassessmentbasedonAHP.AdvancesinPetroleumExplorationandDevelopment2012,4:13-8.
[20] Mia Audina: Daliaohe Estuary water environment pollution ecological risk assessment index system and technical method research. Qingdao: Chinese Marine University, 2013.
[21]GleickPH:RoadmapforsustainablewaterresourcesinsouthwesternNorthAmerica.ProceedingsoftheNationalAcademyofSciencesoftheUnitedStatesofAmerica2010,107:21300-5.
[22]TimmermanJG,BeinatE,TermeerCJ,CofinoWP:DevelopingtransboundaryriverbasinmonitoringprogrammesusingtheDPSIRindicatorframework.Journalofenvironmentalmonitoring:JEM2011,13:2808-018.
[23]GomezAG,OndivielaB,PuenteA,JuanesJA:Environmentalriskassessmentofwaterqualityinharborareas:anewmethodologyappliedtoEuropeanports.Journalofenvironmentalmanagement2015,155:77-88.
[24]TorresL,YadavOPY,KhanE:Areviewonriskassessmenttechniquesforhydraulicfracturingwaterandproducedwatermanagementimplementedinonshoreunconventionaloilandgasproduction.TheScienceofthetotalenvironment2016,539:478-93.
[25]CarrER,WingardPM,YortySC,ThompsonMC,JensenNK,RobersonJ:ApplyingDPSIRtosustainabledevelopment.InternationalJournalofSustainableDevelopment&WorldEcology2007,14:543-55.
[26]EdithS,RobW:EnvironmentalIndicators:TypologyandOverview.Copenhagen:TechnicalReport,EuropeanEnvironmentalAgency,1999.
[27]OECD:EnvironmentalIndicators:OECDCoreSet.Paris,1994.
[28]MullerF,Hoffmann-KrollR,WiggeringH:Indicatingecosystemintegrity-theoreticalconceptsandenvironmentalEcologicalModelling2000,130:13-23.
[29]KP:Onlinsandplanesofclosestfittosystemsofpointsinspace[J].PhilosophicalMagazine.PhilosophicalMagazine1901,6:559.
[30]C.E.S:Amathematicaltheoryofcommunications.TheBellSystemsTechnicalJournal1948,27:379-423,623-56.
[31] Ou Yangzhiyun: Ecological Environmental Quality Assessment and ecological function zoning. Beijing: China Environmental Science Press, 2009.
[32]NeshatA,PradhanB,DadrasM:GroundwatervulnerabilityassessmentusinganimprovedDRASTICmethodinGIS.Resources,ConservationandRecycling2014,86:74-86.
[33]SongG,ChenY,TianM,LvS,ZhangS,LiuS:TheEcologicalVulnerabilityEvaluationinSouthwesternMountainRegionofChinaBasedonGISandAHPMethod.ProcediaEnvironmentalSciences2010,2:465-75.
[34]SaatyTL:Ascalingmethodforprioritiesinhierarchicalstructures.JournalofMathematicalPsychology1977,15:234-81.
[35]TesfamariamS,SadiqR:Risk-basedenvironmentaldecision-makingusingfuzzyanalytichierarchyprocess(F-AHP).StochasticEnvironmentalResearchandRiskAssessment2006,21:35-50.
[36]WangX,ChanHK,YeeRWY,Diaz-RaineyI:Atwo-stagefuzzy-AHPmodelforriskassessmentofimplementinggreeninitiativesinthefashionsupplychain.InternationalJournalofProductionEconomics2012,135:595-606.
[37]JiangQo,DengX,ZhanJ,YanH:ImpactsofeconomicdevelopmentonecosystemriskintheYellowRiverDelta.ProcediaEnvironmentalSciences2010,5:208-18.
The above is the preferred embodiment of the present invention; it should be pointed out that, for those skilled in the art, under the premise without departing from principle of the present invention; can also making some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention.
Claims (5)
1. a Regional Water Environment risk assessment and partition method, it is characterised in that including:
Step 1, set up based on the Regional Water Environment risk evaluation model of DPSIR model to build Regional Water Environment Risk Assessment Index System；Wherein said DPSIR model includes driving force factors, press factors, state factor, factor of influence, response factor；
Step 2, employing analytic hierarchy process (AHP) calculate each index weights assignment, then by each index system quantization modulation；
Step 3, again through Field Using Fuzzy Comprehensive Assessment, the value-at-risk of zoning water environment；According to risk class, region is carried out subregion；
Step 4, by componential analysis, risk leading factor is analyzed.
2. Regional Water Environment risk assessment according to claim 1 and partition method, it is characterised in that described step 1 specifically includes:
Step 11, determine the driving force factors of DPSIR model, press factors, state factor, factor of influence, response factor；Wherein
Driving force factors is the latent factor promoting water environment pressure to increase or reduce, and is the indirect factor causing water environment to change, at least includes: socio-economic development speed, population rate of rise etc.；
Press factors is produce the direct driving force of Water environments simulation, characterizes social development to the demand of water resource and side effect that water environment is caused, at least includes: society's water-use efficiency, effluent sewage discharge；
State factor is describe Regional Water Environment situation and promote protection of the water environment to carry out required precondition, i.e. social-economic development status at least includes: water quality, the water yield, Ecology situation；
Factor of influence is the impact under driving force direct, indirect promotes, Regional Water Environment and resident living caused；
Response factor is the control measures that the various risks that water environment is faced are taked；
Step 12, build Regional Water Environment Risk Assessment Index System, described structure Regional Water Environment Risk Assessment Index System include from different perspectives the destination layer of reflecting regional Water environments simulation, system layer, rule layer, indicator layer；
Wherein said system layer includes at least following five parameters: driving force, pressure, state, impact, response；
Wherein corresponding three the rule layer parameters of driving force: population growth, economic development, social development；The indicator layer that wherein population growth is corresponding includes: the natural growth rate of population, population density；Indicator layer corresponding to economic development includes: GPD annual rate of growth, GDP per capita；The indicator layer that social development is corresponding includes: Engel's coefficient；
Wherein corresponding two the rule layer parameters of pressure: ambient pressure, resource pressure；The indicator layer that wherein ambient pressure is corresponding includes: state key monitoring enterprise density, discharged volume of industrial waste water, sanitary sewage discharge capacity, COD annual emissions, agriculture chemical make consumption；The indicator layer that wherein resource pressure is corresponding includes: ten thousand yuan of GDP water consumptions, per capita water consumption；
Wherein corresponding four the rule layer parameters of state: the water yield, water quality, Ecology, receptor；The indicator layer that wherein water yield is corresponding includes: water resources ownership per capita；Indicator layer corresponding to water quality includes: Water Functional Zone probability of meeting water quality standard；The indicator layer that Ecology is corresponding includes: Wetland Area accounts for area under one's jurisdiction area ratio；The indicator layer that receptor is corresponding includes: sensitive group proportion；
Wherein corresponding three the rule layer parameters of impact: water environment, Ecology, resident living；The indicator layer that wherein water environment is corresponding includes: river, lake are inferior to Group III water quality accounting；The indicator layer that Ecology is corresponding includes: soil erosion area ratio；Indicator layer corresponding to resident living includes: concentrate water head site probability of meeting water quality standard, population average life, resident living water rate；
Wherein corresponding three the rule layer parameters of response: water resources management, water resource monitoring, stain disease process；The indicator layer that wherein water resources management is corresponding includes: water conservancy, environment, public infrastructure are invested per capita；The indicator layer of water resource monitoring correspondence includes: surface water quality monitoring section point figure place；Stain disease processes corresponding indicator layer and includes: wastewater reuse approach rate, treatment rate of industrial effluents.
3. Regional Water Environment risk assessment according to claim 1 and partition method, it is characterised in that in described step 2 again through Field Using Fuzzy Comprehensive Assessment, the value-at-risk of zoning water environment, specifically include:
Step 21, according to hierarchical relationship between destination layer, system layer, rule layer, indicator layer, set up membership function, and calculate each index degree of membership for opinion rating；
Step 22, according to each hierarchical relationship of index system, set up structural model, set up fuzzy relation matrix by relative membership degree and function；Principle according to maximum membership degree determines final appraisal results.
4. Regional Water Environment risk assessment according to claim 3 and partition method, it is characterised in that described step 21 specifically includes:
For reverse index, desired value is more little, and Water environments simulation is more high:
For forward index, desired value is more big, and Water environments simulation is more high:
Wherein xiRefer to i-th index；aiWith the kth level evaluation criterion that k is i-th index；rikRefer to i-th index relative defects for kth grade standard.
5. Regional Water Environment risk assessment according to claim 3 and partition method, it is characterised in that described step 22 specifically includes:
Step 221, according to each hierarchical relationship of index system, set up structural model, set up fuzzy relation matrix by relative membership degree and function:
Wherein m index number contained by this grade；N is opinion rating number；
Step 222, it is divided into 4 layers due to Regional Water Environment Risk Assessment Index System, therefore n=4；It is sequentially carried out first, second and third grade of judge according to weight sets W and fuzzy relation matrix:
Wherein biFor the evaluation index degree of membership to i-th grade；
Principle according to maximum membership degree, take withCorresponding risk class is as the final appraisal results of this key element.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610371501.XA CN105809578A (en) | 2016-05-30 | 2016-05-30 | Regional water environment risk evaluating and region dividing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610371501.XA CN105809578A (en) | 2016-05-30 | 2016-05-30 | Regional water environment risk evaluating and region dividing method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105809578A true CN105809578A (en) | 2016-07-27 |
Family
ID=56427692
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610371501.XA Pending CN105809578A (en) | 2016-05-30 | 2016-05-30 | Regional water environment risk evaluating and region dividing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105809578A (en) |
Cited By (36)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106599562A (en) * | 2016-12-06 | 2017-04-26 | 武汉大学 | Probability weighting FDC method-based river ecological water demand calculation method |
| CN106920044A (en) * | 2017-03-07 | 2017-07-04 | 北京工商大学 | Residues of pesticides methods of risk assessment based on model of fuzzy synthetic evaluation |
| CN107908858A (en) * | 2017-11-13 | 2018-04-13 | 福建农林大学 | A kind of seashore wetland aquatic bird active path analogy method based on GIS and RS |
| CN108304536A (en) * | 2018-01-29 | 2018-07-20 | 中国科学院地理科学与资源研究所 | A kind of geographical environmental simulation of the geographical environmental element of coupling and predicting platform |
| CN108492007A (en) * | 2018-03-02 | 2018-09-04 | 交通运输部水运科学研究所 | A kind of marine eco-environment damage causality determination method |
| CN108564267A (en) * | 2018-04-08 | 2018-09-21 | 苏州英瀚时信息科技有限公司 | A kind of enterprises environmental risk evaluation system and method |
| CN108876167A (en) * | 2018-06-27 | 2018-11-23 | 南京林业大学 | A kind of seashore wetland ecological security assessment method based on DPSIR model |
| CN109040027A (en) * | 2018-07-12 | 2018-12-18 | 北京理工大学 | The active predicting method of network vulnerability node based on gray model |
| CN109272199A (en) * | 2018-08-22 | 2019-01-25 | 北京大学 | A kind of ecological navigation channel fuzzy synthetic appraisement method based on wooden pail effect |
| CN109409729A (en) * | 2018-10-19 | 2019-03-01 | 中国环境科学研究院 | Oil-gas pipeline surrounding cities Vulnerability Assessment |
| CN109460886A (en) * | 2018-09-11 | 2019-03-12 | 中国水利水电科学研究院 | A kind of water delivery engineering burst water contamination accident risk analysis method |
| CN109636172A (en) * | 2018-12-06 | 2019-04-16 | 南开大学 | Regional environment risk assessment and zoning methods based on risk field |
| CN109740971A (en) * | 2019-02-01 | 2019-05-10 | 华南理工大学 | A kind of methods of risk assessment and system of harmful influence manufacturing enterprise burst basin water environment |
| CN109816264A (en) * | 2019-02-01 | 2019-05-28 | 华南理工大学 | A kind of methods of risk assessment and system of area burst basin water environment |
| CN109816550A (en) * | 2018-12-18 | 2019-05-28 | 深圳市东深电子股份有限公司 | A kind of automatic water resource appraisal management system and method |
| CN110162848A (en) * | 2019-05-05 | 2019-08-23 | 河海大学 | A kind of water-related ecological environment loaded state metering model |
| CN110189064A (en) * | 2019-07-03 | 2019-08-30 | 中国环境科学研究院 | The recognition methods and system of section overproof water quality risk pressure source based on big data |
| CN110298577A (en) * | 2019-06-21 | 2019-10-01 | 济南大学 | Set disaster risk evaluating method and system for a kind of Yanhe Village based on DPSIR model |
| CN110348738A (en) * | 2019-07-12 | 2019-10-18 | 武汉新江城环境事务咨询有限责任公司 | hospital environment influence factor evaluation method |
| CN111382940A (en) * | 2020-03-09 | 2020-07-07 | 生态环境部环境规划院 | Method, device and equipment for determining non-point source pollution risk and storage medium |
| CN111523088A (en) * | 2020-04-13 | 2020-08-11 | 杭州领见数据科技有限公司 | Ecological environment evaluation method based on DPSIR model |
| CN111861273A (en) * | 2020-08-03 | 2020-10-30 | 生态环境部南京环境科学研究所 | Water environment risk assessment method based on fuzzy integral model |
| CN111882176A (en) * | 2020-07-08 | 2020-11-03 | 生态环境部环境规划院 | Method and system for evaluating bearing capacity of atmospheric environment |
| CN111882244A (en) * | 2020-08-07 | 2020-11-03 | 中国地质科学院水文地质环境地质研究所 | Construction method of multi-source homeland development risk assessment system based on hierarchical framework |
| CN112258002A (en) * | 2020-10-15 | 2021-01-22 | 深圳市环境科学研究院 | Method for constructing risk assessment index system of drinking water source protection area |
| CN112561290A (en) * | 2020-12-11 | 2021-03-26 | 中国环境科学研究院 | Northern river wetland ecological data acquisition and processing method based on PSER model |
| CN112668911A (en) * | 2020-12-31 | 2021-04-16 | 哈尔滨工业大学 | Water area shoreline pollution risk assessment method and control intelligent decision method and system |
| CN112819284A (en) * | 2021-01-05 | 2021-05-18 | 黄河勘测规划设计研究院有限公司 | Ecological environment evolution evaluation method and device based on drainage basin |
| CN113705941A (en) * | 2020-05-22 | 2021-11-26 | 中国科学院地理科学与资源研究所 | County scale high-risk pollution plot rapid screening method |
| CN113762730A (en) * | 2021-08-16 | 2021-12-07 | 中国科学院地理科学与资源研究所 | Risk assessment method for water resource bearing capacity and electronic equipment thereof |
| CN113935609A (en) * | 2021-10-08 | 2022-01-14 | 天津大学 | Long-river-section multi-break-opening flood flooding combined risk assessment method |
| CN114113518A (en) * | 2021-11-11 | 2022-03-01 | 杭州电子科技大学 | Water quality evaluation method for household domestic water |
| CN114580759A (en) * | 2022-03-07 | 2022-06-03 | 中国质量认证中心 | Urban low-carbon emission reduction evaluation system |
| WO2023178961A1 (en) * | 2022-05-16 | 2023-09-28 | 中建三局绿色产业投资有限公司 | Silting risk assessment, prediction and early warning method for urban deep water-drainage tunnel |
| CN116882753A (en) * | 2023-07-20 | 2023-10-13 | 生态环境部南京环境科学研究所 | Water environment ecological health risk evaluation method and system |
| CN113762730B (en) * | 2021-08-16 | 2024-10-15 | 中国科学院地理科学与资源研究所 | Water resource bearing capacity risk assessment method and electronic equipment thereof |
-
2016
- 2016-05-30 CN CN201610371501.XA patent/CN105809578A/en active Pending
Cited By (52)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106599562A (en) * | 2016-12-06 | 2017-04-26 | 武汉大学 | Probability weighting FDC method-based river ecological water demand calculation method |
| CN106599562B (en) * | 2016-12-06 | 2017-11-10 | 武汉大学 | River ecological water demand computational methods based on probability weight FDC methods |
| CN106920044A (en) * | 2017-03-07 | 2017-07-04 | 北京工商大学 | Residues of pesticides methods of risk assessment based on model of fuzzy synthetic evaluation |
| CN106920044B (en) * | 2017-03-07 | 2021-01-12 | 北京工商大学 | Pesticide residue risk assessment method based on fuzzy comprehensive evaluation model |
| CN107908858A (en) * | 2017-11-13 | 2018-04-13 | 福建农林大学 | A kind of seashore wetland aquatic bird active path analogy method based on GIS and RS |
| CN107908858B (en) * | 2017-11-13 | 2021-01-12 | 福建农林大学 | Coastal wetland waterfowl movement path simulation method based on GIS and RS |
| CN108304536A (en) * | 2018-01-29 | 2018-07-20 | 中国科学院地理科学与资源研究所 | A kind of geographical environmental simulation of the geographical environmental element of coupling and predicting platform |
| CN108492007A (en) * | 2018-03-02 | 2018-09-04 | 交通运输部水运科学研究所 | A kind of marine eco-environment damage causality determination method |
| CN108492007B (en) * | 2018-03-02 | 2021-10-26 | 交通运输部水运科学研究所 | Marine ecological environment damage cause and effect relationship determination method |
| CN108564267A (en) * | 2018-04-08 | 2018-09-21 | 苏州英瀚时信息科技有限公司 | A kind of enterprises environmental risk evaluation system and method |
| CN108564267B (en) * | 2018-04-08 | 2022-07-12 | 苏州英瀚时信息科技有限公司 | Enterprise environment risk evaluation system and method |
| CN108876167A (en) * | 2018-06-27 | 2018-11-23 | 南京林业大学 | A kind of seashore wetland ecological security assessment method based on DPSIR model |
| CN109040027A (en) * | 2018-07-12 | 2018-12-18 | 北京理工大学 | The active predicting method of network vulnerability node based on gray model |
| CN109272199A (en) * | 2018-08-22 | 2019-01-25 | 北京大学 | A kind of ecological navigation channel fuzzy synthetic appraisement method based on wooden pail effect |
| CN109460886A (en) * | 2018-09-11 | 2019-03-12 | 中国水利水电科学研究院 | A kind of water delivery engineering burst water contamination accident risk analysis method |
| CN109409729A (en) * | 2018-10-19 | 2019-03-01 | 中国环境科学研究院 | Oil-gas pipeline surrounding cities Vulnerability Assessment |
| CN109636172B (en) * | 2018-12-06 | 2024-04-02 | 南开大学 | Regional environment risk evaluation and division method based on risk field |
| CN109636172A (en) * | 2018-12-06 | 2019-04-16 | 南开大学 | Regional environment risk assessment and zoning methods based on risk field |
| CN109816550A (en) * | 2018-12-18 | 2019-05-28 | 深圳市东深电子股份有限公司 | A kind of automatic water resource appraisal management system and method |
| CN109816550B (en) * | 2018-12-18 | 2023-01-24 | 深圳市东深电子股份有限公司 | Automatic water resource assessment management system and method |
| CN109740971B (en) * | 2019-02-01 | 2020-12-22 | 华南理工大学 | Risk assessment method and system for water environment of sudden drainage basin of hazardous chemical production enterprise |
| CN109816264B (en) * | 2019-02-01 | 2020-08-28 | 华南理工大学 | Risk assessment method and system for water environment of regional burst watershed |
| CN109740971A (en) * | 2019-02-01 | 2019-05-10 | 华南理工大学 | A kind of methods of risk assessment and system of harmful influence manufacturing enterprise burst basin water environment |
| CN109816264A (en) * | 2019-02-01 | 2019-05-28 | 华南理工大学 | A kind of methods of risk assessment and system of area burst basin water environment |
| CN110162848B (en) * | 2019-05-05 | 2021-09-07 | 河海大学 | Ecological environment bearing state measurement model related to water |
| CN110162848A (en) * | 2019-05-05 | 2019-08-23 | 河海大学 | A kind of water-related ecological environment loaded state metering model |
| CN110298577A (en) * | 2019-06-21 | 2019-10-01 | 济南大学 | Set disaster risk evaluating method and system for a kind of Yanhe Village based on DPSIR model |
| CN110298577B (en) * | 2019-06-21 | 2022-04-05 | 济南大学 | Method and system for evaluating mountain torrent disaster risk along rivers and villages based on DPSIR model |
| CN110189064A (en) * | 2019-07-03 | 2019-08-30 | 中国环境科学研究院 | The recognition methods and system of section overproof water quality risk pressure source based on big data |
| CN110348738A (en) * | 2019-07-12 | 2019-10-18 | 武汉新江城环境事务咨询有限责任公司 | hospital environment influence factor evaluation method |
| CN110348738B (en) * | 2019-07-12 | 2024-01-12 | 武汉新江城环境事务咨询有限责任公司 | Hospital environmental impact factor assessment method |
| CN111382940A (en) * | 2020-03-09 | 2020-07-07 | 生态环境部环境规划院 | Method, device and equipment for determining non-point source pollution risk and storage medium |
| CN111523088A (en) * | 2020-04-13 | 2020-08-11 | 杭州领见数据科技有限公司 | Ecological environment evaluation method based on DPSIR model |
| CN113705941A (en) * | 2020-05-22 | 2021-11-26 | 中国科学院地理科学与资源研究所 | County scale high-risk pollution plot rapid screening method |
| CN111882176A (en) * | 2020-07-08 | 2020-11-03 | 生态环境部环境规划院 | Method and system for evaluating bearing capacity of atmospheric environment |
| CN111882176B (en) * | 2020-07-08 | 2024-05-14 | 生态环境部环境规划院 | Atmospheric environment bearing capacity assessment method and system |
| CN111861273A (en) * | 2020-08-03 | 2020-10-30 | 生态环境部南京环境科学研究所 | Water environment risk assessment method based on fuzzy integral model |
| CN111861273B (en) * | 2020-08-03 | 2023-07-21 | 生态环境部南京环境科学研究所 | Water environment risk assessment method based on fuzzy integral model |
| CN111882244A (en) * | 2020-08-07 | 2020-11-03 | 中国地质科学院水文地质环境地质研究所 | Construction method of multi-source homeland development risk assessment system based on hierarchical framework |
| CN112258002A (en) * | 2020-10-15 | 2021-01-22 | 深圳市环境科学研究院 | Method for constructing risk assessment index system of drinking water source protection area |
| CN112561290A (en) * | 2020-12-11 | 2021-03-26 | 中国环境科学研究院 | Northern river wetland ecological data acquisition and processing method based on PSER model |
| CN112668911A (en) * | 2020-12-31 | 2021-04-16 | 哈尔滨工业大学 | Water area shoreline pollution risk assessment method and control intelligent decision method and system |
| CN112819284A (en) * | 2021-01-05 | 2021-05-18 | 黄河勘测规划设计研究院有限公司 | Ecological environment evolution evaluation method and device based on drainage basin |
| CN113762730A (en) * | 2021-08-16 | 2021-12-07 | 中国科学院地理科学与资源研究所 | Risk assessment method for water resource bearing capacity and electronic equipment thereof |
| CN113762730B (en) * | 2021-08-16 | 2024-10-15 | 中国科学院地理科学与资源研究所 | Water resource bearing capacity risk assessment method and electronic equipment thereof |
| CN113935609A (en) * | 2021-10-08 | 2022-01-14 | 天津大学 | Long-river-section multi-break-opening flood flooding combined risk assessment method |
| CN113935609B (en) * | 2021-10-08 | 2024-05-17 | 天津大学 | Combined risk assessment method for flood inundation with multiple breach in long river section |
| CN114113518A (en) * | 2021-11-11 | 2022-03-01 | 杭州电子科技大学 | Water quality evaluation method for household domestic water |
| CN114113518B (en) * | 2021-11-11 | 2024-04-16 | 杭州电子科技大学 | Household domestic water quality evaluation method |
| CN114580759A (en) * | 2022-03-07 | 2022-06-03 | 中国质量认证中心 | Urban low-carbon emission reduction evaluation system |
| WO2023178961A1 (en) * | 2022-05-16 | 2023-09-28 | 中建三局绿色产业投资有限公司 | Silting risk assessment, prediction and early warning method for urban deep water-drainage tunnel |
| CN116882753A (en) * | 2023-07-20 | 2023-10-13 | 生态环境部南京环境科学研究所 | Water environment ecological health risk evaluation method and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105809578A (en) | Regional water environment risk evaluating and region dividing method | |
| CN106021946A (en) | Risk fuzzy synthetic evaluation method for regional water environment | |
| CN106067087A (en) | A kind of Regional Water Environment risk partition method | |
| CN104992245A (en) | Generalized-entropy-theory-based dynamic intelligent comprehensive analysis method for water environment risk management | |
| Li et al. | Spatio-temporal difference and influencing factors of environmental adaptability measurement of human-sea economic system in Liaoning coastal area | |
| Chen et al. | Comprehensive assessment and hierarchical management of the sustainable utilization of urban water resources based on catastrophe theory | |
| Xu et al. | Assessment of water resources sustainability in mainland China in terms of water intensity and efficiency | |
| CN107423564A (en) | The method of decision analysis of river basin ecological correcting strategy | |
| CN106096847A (en) | A kind of fuzzy change weighs Engineering-geological environmental quality method | |
| CN113762784B (en) | Quantitative comprehensive evaluation method and system for layout planning scheme of sewage treatment system | |
| CN109933901B (en) | MCR city expansion simulation method for optimizing service value of ecosystem | |
| CN109871638A (en) | A kind of lake and marshland Evaluation of Eutrophication model building method | |
| CN104765943A (en) | Comprehensive measuring technological method of urbanization development quality | |
| CN106022635A (en) | Regional water environment risk assessment method | |
| Zhou et al. | Ecological security assessment of Qinzhou coastal zone based on Driving forces-Pressure-State-Impact-Response (DPSIR) model | |
| Liu et al. | COMPREHENSIVE ECO-ENVIRONMENTAL IMPACT ASSESSMENT OF URBAN PLANNING BASED ON PRESSURESTATE-RESPONSE MODEL. | |
| Qiao et al. | Security Assessment of Urban Drinking Water Sources Based on TOPSIS Method: A Case Study of Henan Province, China. | |
| CN114186787A (en) | Urban black and odorous water body remediation model evaluation method based on multi-level fuzzy analysis | |
| Zheng et al. | Research on Monitoring Methods of Organic Pollution in Watershed Water Environment Based on Machine Learning | |
| Luo et al. | Evaluation of the suitability of human settlements in Qingpu district, Shanghai | |
| Shang et al. | Environmental performance of urban integration regions of Chengdu, Deyang, Meishan and Ziyang, based on DPSIR model | |
| Nie et al. | Study on coastal zone sustainable development and its application | |
| Zhen-Yun et al. | Regional Industrial Water Demand Prediction Based on Improved Series Gray Neural Network | |
| CN113496355A (en) | Ocean engineering demonstration area addressing method and system based on machine learning | |
| Qin et al. | Evaluation and Study on Water Quality of Guanqiaojiao River in Wanjiang District, Dongguan City |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160727 |