CN102789546B - Reference lake quantitative determination method based on human disturbance intensity - Google Patents
Reference lake quantitative determination method based on human disturbance intensity Download PDFInfo
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Abstract
The invention provides a reference lake quantitative determination method based on human disturbance intensity. The reference lake quantitative determination method based on the human disturbance intensity mainly includes: 1) in a target area, determining candidate reference lakes in the area, applying a principal component analysis method to determine human disturbance intensity indexes of lake basins, and establishing an evaluation index system and grade standards of the candidate reference lakes; 2) determining evaluation index weight, comparing importance of evaluation indexes of the candidate reference lake in pairwise mode, establishing a fuzzy complementary judgment matrix A based on a hierarchical structure, and performing consistent judgment on the matrix A, wherein the matrix A=(aij) 6*6, and 0<=aij<=1, aij+aji=1; 3) calculating single index connection degree between the candidate reference lakes and evaluation grades and comprehensive connection degree between the candidate reference lakes and the evaluation grades by using a set pair analysis method under the evaluation indexes of the candidate reference lakes; and 4) evaluating grades of the candidate reference lakes, and determining the reference lakes. The reference lake quantitative determination method based on the human disturbance intensity has important and real meaning for quantitative selection of the reference lakes and protection, evaluation and management of lakes.
Description
Technical field
The invention belongs to environmental protection technical field, be specifically related to a kind of reference lake quantitative determination method based on human disturbance intensity.
Background technology
Refer to not by anthropogenic influence or very little and maintain the lake of best use by anthropogenic influence with reference to lake (Reference Lake), can represent this regions and areas's natural biology, physics with the integrality of chemistry.With reference to the representative that lake is a region, their state should represent the optimum range of influenced minimum state in predictable similar lake in this region.Under normal circumstances, the lake not being subject to Human impact is non-existent.Advise that can there be less fluctuation range in lake with reference to state in the water skeleton instruction of Europe, this means that anthropogenic influence allows, as long as no or only have very little ecology influence.Therefore, the lake being subject to anthropogenic influence minimum generally can be selected as reference lake.Reference lake is one of important method determining lake, region reference state, is also determine that lake recovery arrives the baseline of optimum state.The lake of zones of different all also exists significant geographic difference in the origin cause of formation, type, evolution process, nutrients effect and physics, chemistry, biological characteristics etc.; lake basins are densely populated simultaneously, social economy is flourishing; lake is generally large by human driving; what scientifically filter out different ecological subregion is set up ecological zoning nutrient benchmark with reference to lake, carries out the important foundation of the protection in lake, assessment and management.
At present, not yet form the standard method that unified quantification determines reference lake in the world, there is no unified index system, just determine with reference to lake according to the screening of quantitative and qualitative analysis index substep.Result of study is very large by the artificial subjective impact of researcher.
Summary of the invention
The object of the present invention is to provide a kind of reference lake quantitative determination method based on human disturbance intensity.
For achieving the above object, the reference lake quantitative determination method based on human disturbance intensity provided by the invention, its key step comprises:
1) in target area, determine that in region, candidate is with reference to lake, application principal component analytical method determines the index of lake basins human disturbance intensity, sets up candidate with reference to lake assessment indicator system and classification standard thereof;
2) evaluation criterion weight is determined
Candidate is compared between two with reference to lake evaluation index importance, sets up the Fuzzy Complementary Judgment Matrices A based on hierarchical structure, uniformity judgement is carried out to matrix A; Wherein matrix A=(a
ij)
6 × 6, and 0≤a
ij≤ 1, a
ij+ a
ji=1 (i, j in formula are that candidate is with reference to lake evaluation index);
3) with in the evaluation index situation of Method of Set Pair Analysis calculated candidate reference lake, candidate is with reference to the single index Pair Analysis between lake and opinion rating, and candidate is with reference to the comprehensive Pair Analysis between lake and opinion rating;
4) evaluate candidate is with reference to lake grade, determines with reference to lake.
The described reference lake quantitative determination method based on human disturbance intensity, wherein, the index of lake basins human disturbance intensity comprises: the natural vegetation of lake basins, Lake Bank width, agricultural, some source emission, minimum habitat score and urban land; The candidate set up is divided into A-F six class with reference to lake assessment indicator system and classification standard thereof, wherein:
Category-A is desirable basin and lake state, does not have the basin of Human impact;
Category-B is excellent basin and lake state;
C class is critical basin and lake state, has certain Human impact, but the ecological system stability of Lake Water;
D class is the lake lower than critical basin and lake state, has suitable Human impact to occur in lake or basin;
E class is lake and the basin state of difference, has suitable Human impact to occur in lake and basin;
F class is lake and the basin state of non-constant, and Human impact runs through lake and basin on a large scale.
The described reference lake quantitative determination method based on human disturbance intensity, wherein, determine that evaluation criterion weight adopts the analytic hierarchy process (AHP) based on simulated annealing hybrid accelerating genetic algorithm, be minimised as target with coincident indicator coefficient, the weight of each index is calculated; Fuzzy Complementary Judgment Matrices B=(the b revised
ij)
6 × 6the weight of each index is { ω
i| i=1,2 ..., 6}, the then B making following formula minimum are the optimum fuzzy consistent judgment matrix of A:
s.t.1-b
ji=b
ij∈[a
ij-d,a
ij+d]∩[0,1]
b
ii=0.5,ω
j>0,
The described reference lake quantitative determination method based on human disturbance intensity, wherein, the Method of Set Pair Analysis of employing as shown in the formula:
In formula, i is candidate's reference lake, and j represents candidate with reference to lake evaluation index, and k is opinion rating, u
ijkit is the single index Pair Analysis between opinion rating.
The described reference lake quantitative determination method based on human disturbance intensity, wherein, when passing judgment on the grade in candidate's reference lake, by rank feature values
As passing judgment on the grade of candidate with reference to lake evaluation index, obtaining candidate with reference to after the grade of lake, suitable lake can be chosen as reference lake; In formula, h
ithe grade of candidate with reference to lake i.
The described reference lake quantitative determination method based on human disturbance intensity, wherein, when passing judgment on the grade in candidate's reference lake, adopts Reliability Code to pass judgment on the grade h of candidate with reference to lake i
i:
obtain candidate with reference to after the grade of lake, suitable lake can be chosen as reference lake.
The present invention, carrying out introducing consistency discrimination analysis when candidate evaluates with reference to lake, both considered expert judgments, had carried out again objective adjustment, made the determination result science, objective more with reference to lake.For the determination with reference to lake, and set up ecological zoning nutrient benchmark, carrying out the protection in lake, assessment and management has important practical significance.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the reference lake quantitative determination method that the present invention is based on human disturbance intensity.
Detailed description of the invention
The present invention is directed to existing large with reference to lake defining method subjective impact in the world, lack the problem of quantitative method, provide a kind of quantitative determination method with reference to lake based on human disturbance intensity.
Technical scheme of the present invention is as follows: application principal component analytical method sets up candidate with reference to lake assessment indicator system and classification standard thereof; Candidate is compared between two with reference to lake evaluation index importance, determines Raw performance weight matrix; With the analytic hierarchy process (AHP) based on simulated annealing hybrid accelerating genetic algorithm, matrix consistent correction is carried out to Raw performance weight matrix, and calculate the weight of each index; With Method of Set Pair Analysis parameter, candidate with reference to the Pair Analysis between lake and opinion rating, then the thought calculated candidate of fuzzy set is used to be under the jurisdiction of the degree of membership of " opinion rating " with reference to lake, finally determine that candidate is with reference to lake grade, determines with reference to lake with this.Its concrete steps following (referring to Fig. 1):
(1) candidate is set up with reference to lake assessment indicator system and classification standard thereof
In target area, determine that in region, candidate is with reference to lake, for the natural vegetation of lake basins, Lake Bank width, agricultural, some source emission, minimum habitat score and urban land etc., set up candidate and be divided into A-F six class with reference to lake assessment indicator system and classification standard thereof, wherein, category-A is desirable basin and lake state, does not have the basin of Human impact; Category-B is excellent basin and lake state; C class is critical basin and lake state, has certain Human impact, but the ecological system stability of Lake Water.D class is the lake lower than critical basin and lake state, has suitable Human impact to occur in lake or basin.E class is lake and the basin state of difference, has suitable Human impact to occur in lake and basin.F class is lake and the basin state of non-constant, and Human impact runs through lake and basin on a large scale.The reference lake assessment indicator system of refinement and classification standard thereof are see table 1.
(2) evaluation criterion weight is determined
Candidate is compared between two with reference to lake evaluation index importance, sets up the Fuzzy Complementary Judgment Matrices A=(a based on hierarchical structure
ij)
6 × 6, and 0≤a
ij≤ 1, a
ij+ a
ji=1.Uniformity judgement is carried out to matrix A, if the coincident indicator function of matrix
be less than 0.01, then carry out step 3, otherwise consistent correction must be carried out to Fuzzy Complementary Judgment Matrices A.The present invention adopts the analytic hierarchy process (AHP) accelerating heredity calculation based on simulated annealing mixing, is minimised as target, calculates the weight of each index with coincident indicator coefficient (Consistency Index Coefficient).Fuzzy Complementary Judgment Matrices B=(the b revised
ij)
6 × 6the weight of each index is { ω
i| i=1,2 ..., 6}, the then B making following formula minimum are the optimum fuzzy consistent judgment matrix of A:
s.t.1-b
ji=b
ij∈[a
ij-d,a
ij+d]∩[0,1]
b
ii=0.5,ω
j>0,
If population number is n, maximum evolutionary generation is T, and concrete operation step is as follows:
Step 1: real coding.
Step 2: generate initial parent individual.Within the scope of feasible zone, initial parent colony P (0) of random generation n, arranges evolutionary generation device t=0, arranges maximum evolutionary generation T.
Step 3: individual evaluation.Calculate the fitness of each individuality in colony P (t), i-th individual fitness F (1)=1/ (f (1) × f (1)+0.000001), target function value f (i) is less, and fitness F (i) of stating this individuality is higher.
Step 4: Selecting operation.First the thinking adopting optimum maintaining strategy and ratio back-and-forth method to combine, namely find out the individuality that in current group, adaptive value is high and minimum, optimized individual retained, and replace the poorest individuality with it.Current optimized individual is not intersected, is made a variation, and directly enters the next generation.By remaining individuality in proportion back-and-forth method (also making roulette wheel calculate method) operate, selective 2*n-4 individuality.Carrying out lasting global optimization search capability for strengthening SAHAGA, here classic individuality directly being added in progeny population, after carrying out immigrant's operation, obtaining 2n-2 offspring individual P1 (t).
Step 5: hybridization computing.Adopt two-point crossover method, individual as parents by probability of crossover Stochastic choice a pair parent, and carry out stochastic linear combination, produce 2n-2 offspring individual P2 (t).
Step 6: mutation operator.In SAHAGA, the individual P (t) of any parent, if its fitness numerical value F (t) is less, its select probability is less, the probability then made a variation to this individuality should be larger, therefore the mutation operation of SAHAGA adopts mutation probability to make a variation to individual P (t), thus obtain offspring individual P3 (t).
Step 7: evolution iteration.3 (2n-2) the individual offspring individual obtained by step 4-6, sort from big to small by its fitness value, with produced classic front 10 individualities as initial value, utilize simulated annealing search to obtain locally optimal solution above, if gained solution meets required precision, then stop.Otherwise produce above gained solution substitutes the n-th, n-1, n-2 ..., n-9 excellent individual, get come foremost n offspring individual as new parent colony.Algorithm proceeds to step 3.
Step 8: introduce acceleration search operator, s excellent individual before producing by first time, second time evolution iteration above, variable change corresponding to this subgroup is interval, the initial change new as variable is interval, and SAHAGA algorithm proceeds to step 1, so accelerates circulation, the constant interval of excellent individual will progressively adjust and shrink, will be more and more nearer with the distance of optimum point, until iteration meets the stop criterion of algorithm, now optimizing individuality will approach optimum point.The weight of each evaluation index can be obtained.
(3) use Method of Set Pair Analysis parameter, candidate with reference to the Pair Analysis between lake and opinion rating
With candidate in Method of Set Pair Analysis parameter j situation with reference to the single index Pair Analysis u between lake i and opinion rating k
ijk, and candidate is with reference to the comprehensive Pair Analysis between lake i and opinion rating:
If candidate is larger with reference to the otherness between lake i and opinion rating k, then
more close to-1, sample i tends to not be under the jurisdiction of opinion rating k; If the homogeneity between sample i and opinion rating k is larger, then
more close to 1, sample i more tends to be under the jurisdiction of opinion rating k.Therefore the relative defects that candidate is under the jurisdiction of fuzzy set " opinion rating k " with reference to lake i is
(4) evaluate candidate is with reference to lake grade, determines with reference to lake
Pass judgment on the grade h of candidate with reference to lake i.The distortion that Fuzzy Pattern Recognition may cause is carried out, the precision of judge of upgrading for avoiding applying maximum membership grade principle, can rank feature values,
As passing judgment on the grade h of candidate with reference to lake i
i.For the security of the evaluation result that upgrades further, the present invention adopts Reliability Code to pass judgment on the grade h of candidate with reference to lake i
i:
obtain candidate with reference to after the grade of lake, suitable lake can be chosen as reference lake.
The invention has the advantages that and adopt analytic hierarchy process (AHP) to objectify amendment to subjective judgement matrix, make the determination result in reference lake science, objective more.Secondly, the present invention adopts simulated annealing hybrid accelerating genetic algorithm to revise fuzzy consistent judgment matrix, can accelerate the erection rate of judgment matrix.Last the present invention uses Reliability Code to pass judgment on candidate with reference to lake grade, thus the safe row of the evaluation result that upgrades further.
The present invention is further illustrated below with the case study on implementation that is defined as in reference lake, lake region, Yunnan-Guizhou.
1) candidate is set up with reference to lake assessment indicator system and classification standard thereof
Choose lake, 9, lake region, Yunnan-Guizhou alternatively with reference to lake, adopt principal component analytical method, determine that candidate participates in lake evaluation index, according to candidate with reference to lake assessment indicator system (see table 1), adopt the methods such as investigation, exploration and Data acquisition, obtain the achievement datas such as the natural vegetation of lake basins, Lake Bank width, agricultural, some source emission, minimum habitat score and urban land, as table 2.
2) evaluation criterion weight is determined
Candidate is compared between two with reference to lake evaluation index importance, sets up the Fuzzy Complementary Judgment Matrices A based on hierarchical structure,
Uniformity judgement is carried out to matrix A, CIF=0.011 > 0.01, then must carry out consistent correction to judgment matrix A.Adopt and accelerate the heredity optimal model being minimised as target with coincident indicator coefficient of getting it right based on simulated annealing mixing and calculate, calculate the revised weights omega of each index=[0.20,0.25,0.25,0.11,0.10,0.09].
3) use Method of Set Pair Analysis parameter, candidate with reference to the Pair Analysis between lake and opinion rating
Bring in formula by candidate with reference to lake evaluation index value and evaluation criterion weight, obtaining the relative defects that candidate's reference lake is under the jurisdiction of fuzzy set " opinion rating k " is υ
ik.
v
1=[0.9000 0.3000 0.1000 0.0000 0.0000 0.0000 0.0000]′
v
2=[0.9000 0.4279 0.1000 0.0000 0.0000 0.0000 0.0000]′
v
3=[0.2500 0.2168 0.3000 0.0832 0.3290 0.4500 0.1210]′
v
4=[0.2500 0.2099 0.3000 0.1631 0.3600 0.3770 0.0900]′
v
5=[0.2500 0.1000 0.2588 0.2000 0.1952 0.4500 0.2960]′
v
6=[0.4775 0.3165 0.3325 0.3393 0.1900 0.0900 0.0000]′
v
7=[0.2500 0.1000 0.1000 0.0000 0.1856 0.5348 0.4644]′
v
8=[0.5050 0.5483 0.4050 0.0195 0.0000 0.0900 0.0900]′
v
9=[0.3631 0.3000 0.4157 0.3600 0.1313 0.0900 0.0900]′
v
10=[0.2500 0.1000 0.1418 0.2000 0.1582 0.4041 0.4500]′
v
11=[0.2261 0.4563 0.3339 0.3437 0.3500 0.2000 0.0900]′
v
12=[0.3487 0.3220 0.3713 0.3380 0.1900 0.0900 0.0900]′
v
13=[0.2685 0.3000 0.3737 0.3600 0.2678 0.0900 0.0900]′
v
14=[0.2500 0.1000 0.1000 0.0000 0.0454 0.4747 0.6046]′
v
15=[0.0000 0.2558 0.4500 0.4220 0.3500 0.2552 0.2000]′
v
16=[0.3051 0.3073 0.5389 0.3528 0.1560 0.0900 0.0000]′
v
17=[0.2500 0.2149 0.3000 0.1181 0.3258 0.4170 0.1243]′
v
18=[0.7990 0.4536 0.1110 0.0000 0.0000 0.0900 0.0900]′
v
19=[0.2500 0.0601 0.3645 0.4899 0.2755 0.1732 0.1100]′
v
20=[0.2500 0.1803 0.3000 0.2820 0.3600 0.2878 0.0900]′
v
21=[0.3477 0.4013 0.5623 0.2588 0.0000 0.0900 0.0900]′
v
22=[0.2500 0.1529 0.3000 0.3228 0.3270 0.2743 0.1230]′
v
23=[0.3400 0.3315 0.3000 0.1880 0.3600 0.2305 0.0000]′
v
24=[0.5000 0.1000 0.1000 0.1136 0.2000 0.2569 0.2000]′
v
25=[0.9000 0.2670 0.1000 0.0000 0.0000 0.0000 0.0000]′
v
26=[0.1536 0.5500 0.3964 0.3345 0.3600 0.1155 0.0900]′
v
27=[0.3400 0.3837 0.3000 0.1745 0.3600 0.1918 0.0000]′
4) evaluate candidate is with reference to lake grade, determines with reference to lake
The relative defects that candidate is under the jurisdiction of fuzzy set " opinion rating k " with reference to lake is carried out Reliability Code judgement, determines that candidate is with reference to lake grade, the results are shown in Table 3.
Determine that with reference to lake be Bi Tahai, Lugu Lake, folded small stream lake according to candidate with reference to lake grade.
Table 1 is with reference to lake assessment indicator system and classification standard thereof
Table 2 candidate is with reference to lake evaluation index data
Table 3 candidate is with reference to lake quantitative assessment result
Lake title | Opinion rating | Lake title | Opinion rating | Lake title | Opinion rating |
Bi Tahai | A | The West Lake | E | Fuxian Lake | D |
Lugu Lake | A | Erhai | D | River, Lake Xingyun | D |
Wen Hai | D | Upper the deep blue sea | C | Maritime | C |
Lake Lashihai | D | Clear water sea | C | Different Long Hu | D |
Grass sea | D | Qinghai Lake | E | The old Wuhai in difference Black Sea | C |
Cheng Hai | C | Dian Chi | D | Xin Luhai | D |
Red Maple Lake | E | Sun ancestor sea | C | Folded small stream lake | A |
Spring sea | B | Grassy marshland sea | D | Qiong Hai | C |
Sword lake | C | Lunar lacus | B | Ma Hu | C |
Claims (5)
1., based on a reference lake quantitative determination method for human disturbance intensity, its key step comprises:
1) in target area, determine that in region, candidate is with reference to lake, application principal component analytical method determines the index of lake basins human disturbance intensity, sets up candidate with reference to lake assessment indicator system and classification standard thereof;
2) evaluation criterion weight is determined
Candidate is compared between two with reference to lake evaluation index importance, sets up the Fuzzy Complementary Judgment Matrices A based on hierarchical structure, uniformity judgement is carried out to matrix A; Wherein matrix A=(a
ij)
6 × 6, and 0≤a
ij≤ 1, a
ij+ a
ji=1; I, j in formula are that candidate is with reference to lake evaluation index;
Determine that evaluation criterion weight adopts the analytic hierarchy process (AHP) based on simulated annealing hybrid accelerating genetic algorithm, be minimised as target with coincident indicator coefficient, the weight of each index is calculated; Fuzzy Complementary Judgment Matrices B=(the b revised
ij)
6 × 6the weight of each index is { ω
i| i=1,2 ..., 6}, the then B making following formula minimum are the optimum fuzzy consistent judgment matrix of A:
s.t.1-b
ji=b
ij∈[a
ij-d,a
ij+d]∩[0,1]
b
ii=0.5,ω
j>0,
3) with in the evaluation index situation of Method of Set Pair Analysis calculated candidate reference lake, candidate is with reference to the single index Pair Analysis between lake and opinion rating, and candidate is with reference to the comprehensive Pair Analysis between lake and opinion rating;
4) evaluate candidate is with reference to lake grade, determines with reference to lake.
2. according to claim 1 based on the reference lake quantitative determination method of human disturbance intensity, wherein, the index of lake basins human disturbance intensity comprises: the natural vegetation of lake basins, Lake Bank width, agricultural, some source emission, minimum habitat score and urban land; The candidate set up is divided into A-F six class with reference to lake assessment indicator system and classification standard thereof, wherein:
Category-A is desirable basin and lake state, does not have the basin of Human impact;
Category-B is excellent basin and lake state;
C class is critical basin and lake state, has certain Human impact, but the ecological system stability of Lake Water;
D class is the lake lower than critical basin and lake state, has suitable Human impact to occur in lake or basin;
E class is lake and the basin state of difference, has suitable Human impact to occur in lake and basin;
F class is lake and the basin state of non-constant, and Human impact runs through lake and basin on a large scale.
3. according to claim 1 based on the reference lake quantitative determination method of human disturbance intensity, wherein, employing Method of Set Pair Analysis as shown in the formula:
In formula, i is candidate's reference lake, and j represents candidate with reference to lake evaluation index, and k is opinion rating, u
ijkit is the single index Pair Analysis between opinion rating.
4. according to claim 1 based on the reference lake quantitative determination method of human disturbance intensity, wherein, when passing judgment on the grade in candidate's reference lake, by rank feature values
As passing judgment on the grade of candidate with reference to lake evaluation index, obtaining candidate with reference to after the grade of lake, suitable lake can be chosen as reference lake;
In formula, h
ithe grade of candidate with reference to lake i, v
ikbe that candidate is under the jurisdiction of the relative defects of fuzzy set opinion rating k with reference to lake i, k is the opinion rating of candidate with reference to lake.
5., according to claim 4 based on the reference lake quantitative determination method of human disturbance intensity, wherein, when passing judgment on the grade in candidate's reference lake, adopt Reliability Code to pass judgment on the grade h of candidate with reference to lake i
i:
obtain candidate with reference to after the grade of lake, suitable lake can be chosen as reference lake.
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---|
李文君等.基于改进集对分析法的北方水源地水库富营养化评价.《2011中国环境科学学会学术年会论文集》.2011,第1卷第429-434页. * |
许文杰等.湿地水体富营养化评价与可持续发展研究.《中国农村水利水电》.2007,(第9期),第9-11页. * |
邬敏等.一种改进的集对分析法在湖泊富营养化评价中的应用.《水资源保护》.2009,第25卷(第2期),第5-9页. * |
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