CN115496375A - Lake health condition evaluation and diagnosis method and system - Google Patents
Lake health condition evaluation and diagnosis method and system Download PDFInfo
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Abstract
The invention discloses a method and a system for evaluating and diagnosing health conditions of lakes, which comprises the following steps: carrying out health evaluation zoning on the lake; adopting a TCI model to construct a lake health evaluation index system, determining the weight of each element in a criterion layer and an index layer, and assigning a score to each index; obtaining the overall health evaluation results of each area and the lake according to the weight and the assigned value of each element and the constructed fuzzy comprehensive evaluation model of the health of each area and the overall health evaluation model of the lake, wherein the fuzzy comprehensive evaluation model of the health of each area of the lake is constructed by applying a multi-level fuzzy comprehensive evaluation method; the overall health fuzzy comprehensive evaluation model is obtained by constructing a secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area in the lake subarea health fuzzy comprehensive evaluation model by using a comprehensive analysis method. The health evaluation of the lake in a subarea and integral way is realized, and the health grading score is obtained.
Description
Technical Field
The invention relates to the technical field of lake ecosystem management, in particular to a method and a system for evaluating and diagnosing lake health conditions.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
Since Schaeffer et al first proposed the concept of 'no disease' in the 80 th century, some experts and scholars at home and abroad developed related research and application on the lake ecosystem health concept, the lake health evaluation index system and the lake health evaluation method. At present, the view of Costanza is generally accepted, and the health of the ecological system is divided into five aspects of no disease, development, diversity, stability and orderly and healthy system composition. However, due to differences in regional climate, terrain, landform and the like, diversity of understanding manners of researchers for the concept of 'lake health', and different difficulty degrees of index monitoring, the establishment of the lake health evaluation index system is often subjective. At present, although there are evaluation guidelines and local norms, there is no complete and comprehensive evaluation system and evaluation method, and there is no analysis of the spatial-temporal variation of the whole and partitioned lakes.
The lake health evaluation method can be divided into a biological monitoring method and a multi-index comprehensive evaluation method. The biological monitoring method mainly reflects the health condition of the lake through the quantity change and mechanism indexes of community structures, key species and rare species in the lake ecosystem. Biological monitoring is a common method for studying the health of the lake ecosystem, but there are some obvious disadvantages: (1) Only depending on a single index to evaluate the health of the ecosystem has certain one-sidedness; (2) The screening criteria for the indicator species are not clear, and it is difficult to determine whether the reduction of the indicator species has a significant effect on the system and its role in the ecosystem; (3) Social economy and human health factors are not considered, and the health condition of an ecological system is difficult to reflect comprehensively. The multi-index comprehensive evaluation method is a method for comprehensively evaluating each tissue level of an ecosystem on the premise of selecting clusters of different tissue levels and considering different scales. Compared with a biological monitoring method, the multi-index comprehensive evaluation method combines ecology, physiological toxicology, physical chemistry and computer-assisted segments, and becomes a commonly used method at present due to the characteristics of comprehensiveness, comprehensiveness and easy quantification.
Although a plurality of scholars have made relevant research on the evaluation of the health of lakes at present, most scholars evaluate the overall health of lakes, and the evaluation of the health of lake partitions and the analysis of the space-time evolution law are lacked. Secondly, the currently commonly adopted evaluation method is to use the weighted average of the weight of each index and the actual assigned value as the score of the health condition of the lake, and judge the health condition of the lake according to the score. However, since the health level grading standards of the indexes are different, the finally selected lake health level grading standard cannot be completely matched with the grading standard of the indexes, which causes a situation that the method for determining the health condition of the lake according to the weighted average is likely to cause misjudgment. In addition, the method of determining the indexing weight commonly used at present is the Analytic Hierarchy Process (AHP). The analytic hierarchy process is a common subjective weighting method. The core of the analytic hierarchy process is the construction of a judgment matrix, while the traditional analytic hierarchy process assigns values according to the scale of 1-9 in the process of constructing the judgment matrix, so that the grading of the scale is more, the scale is too fine, the comparison scale established by different scales is difficult to master, the inverse order opposite to the actual situation is possible to occur, and the accuracy of the judgment matrix is reduced. Moreover, the consistency check of the judgment matrix fails due to the subjective judgment error of a decision maker, and the judgment matrix needs to be reconstructed and the consistency check needs to be carried out.
Disclosure of Invention
The invention provides a method and a system for evaluating and diagnosing the health condition of a lake, aiming at solving the problems, so that the partitioned and integral evaluation on the health condition of the lake is realized, and a health grading score is obtained.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, a method for evaluating and diagnosing health status of a lake is provided, which comprises the following steps:
carrying out health evaluation zoning on the lake;
adopting a TCI model to construct a lake health evaluation index system, determining the weight of each element in a criterion layer and an index layer, and assigning a score to each index;
obtaining the overall health evaluation results of each lake zone and the lake according to the weight and assigned value of each element and the constructed fuzzy comprehensive evaluation model of the lake zone health and the overall health evaluation model, wherein the process of constructing the fuzzy comprehensive evaluation model of the lake zone health comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of the elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is constructed and obtained by a comprehensive analysis method according to the secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area.
In a second aspect, a system for evaluating and diagnosing health status of lakes is provided, which comprises:
the partition module is used for carrying out health evaluation partition on the lake;
the health evaluation index system building module is used for building a lake health evaluation index system by adopting a TCI model, determining the weight of each element in the criterion layer and the index layer, and assigning a score to each index;
and the health evaluation result acquisition module is used for acquiring the overall health evaluation results of each lake region and the lake according to the weight of each element, the assigned value, the constructed fuzzy comprehensive evaluation model of the lake region health and the constructed fuzzy comprehensive evaluation model of the overall health, wherein the process of constructing the fuzzy comprehensive evaluation model of the lake region health comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of the elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is constructed and obtained by a comprehensive analysis method according to the secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area.
In a third aspect, an electronic device is provided, which includes a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method for evaluating and diagnosing the health status of a lake.
In a fourth aspect, a computer-readable storage medium is provided for storing computer instructions, and the computer instructions, when executed by a processor, perform the steps of the method for evaluating and diagnosing the health status of a lake.
Compared with the prior art, the invention has the beneficial effects that:
1. the method realizes the partitioned and integral lake health evaluation, obtains the health grading score, the partitioned health evaluation result can clearly reflect the change situation of the health level of the lake in space, is beneficial to quickly and accurately identifying the position of the pollution source and formulating a corresponding treatment scheme, and the obtained health grading score is beneficial to analyzing the etiology of the health condition of the lake and judging the change trend of the health condition of the lake in time.
2. Based on the ecological system health management angle, the invention establishes a set of lake health evaluation method which is suitable for lakes and integrates a health evaluation index system and a health fuzzy comprehensive evaluation model, is beneficial to realizing the rapid and comprehensive evaluation of the health state of lakes, and is simultaneously beneficial to rapidly and accurately identifying the main restriction factors of the health of lakes; the method adopted by the invention is scientific and reasonable, the established model is simple and easy to understand, the calculation result is accurate and intuitive, a very effective technical management tool is provided for lake management, and the practical significance is very prominent.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application, and the description of the exemplary embodiments and illustrations of the application are intended to explain the application and are not intended to limit the application.
FIG. 1 is a flow chart of the method disclosed in example 1;
FIG. 2 is a sectional view of the health evaluation of lakes in the four lakes;
FIG. 3 shows the scores assigned to the four south lakes in 2018.
Detailed Description
The invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Example 1
In this embodiment, a method for evaluating and diagnosing health status of a lake is disclosed, as shown in fig. 1, including:
carrying out health evaluation zoning on the lake;
adopting a TCI model to construct a health evaluation index system of each area of the lake, determining the weight of each element in a criterion layer and an index layer, and assigning a score to each index;
obtaining the overall health evaluation results of each area and the lake according to the weight and the assigned value of each element and the constructed fuzzy comprehensive evaluation model of the health of each area and the overall health evaluation model of the lake, wherein the process of constructing the fuzzy comprehensive evaluation model of the health of each area of the lake comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of all elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is constructed and obtained by a comprehensive analysis method according to the secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area.
According to the actual condition of the lake, considering the hydrological and hydrodynamic characteristics of the lake, the water quality condition of the lake, the dominating lake slices of the lake growth system around the lake, the spatial heterogeneity of the biological distribution of the lake and the water function zone division characteristics of the lake, and carrying out health evaluation zone division on the lake.
And establishing a lake health evaluation index system by adopting a target-criterion-index (TCI) model according to the requirements of lake management and the actual conditions of lakes by referring to relevant specifications and guidelines in the industry. The established lake health evaluation index system comprises a target layer, a criterion layer and an index layer, wherein the target layer represents the health condition of the lake, the criterion layer reflects the attributes and levels of the health condition of the lake from different sides and comprises chemical integrity, morphological structure integrity, hydrological integrity, biological integrity and social service function integrity, and the index layer consists of indexes corresponding to all elements in the criterion layer, wherein the indexes corresponding to the chemical integrity criterion layer are water quality degree, lake nutrition state, sediment pollution condition and water body self-purification capacity; indexes corresponding to the morphological structure integrity criterion layer are a lake communication index, a lake area shrinkage proportion, a shoreline natural condition and a water area shoreline degree of illegal development and utilization; indexes corresponding to the hydrological integrity criterion layer are the minimum ecological water level meeting degree and the lake-entering flow variation degree; indexes corresponding to the biological integrity criterion layer are biological integrity indexes of the large benthic invertebrates, fish retention indexes, water bird conditions, phytoplankton density and large aquatic plant coverage; indexes corresponding to the social service function integrity criterion layer are flood control standard-reaching rate, water supply quantity guarantee degree, lake centralized drinking water source ground standard-reaching rate, shore utilization management index and public satisfaction degree.
The above index assignment standards refer to "guide for evaluating river and lake health" (test), and the meanings and calculation methods of the indices are as follows:
(1) Degree of quality of water
The quality degree of water is an important index for judging whether the lake is healthy, item indexes (such as total phosphorus TP, total nitrogen TN, dissolved oxygen DO, permanganate index, chemical oxygen demand and Ph) during judgment are selected to meet the requirement of evaluation of lake growth water quality indexes, the water quality class of the lake is represented by the water quality class of the worst water quality item in an evaluation period, the actually measured concentration value of the judgment index is assigned according to GB 3838-2002 surface water environment quality standard and a guide, and when the concentrations of a plurality of water quality items are the worst water quality classes, the concentrations of the water quality items need to be respectively subjected to scoring calculation to obtain the lowest value.
(2) Nutrient state of lake
The index firstly needs to evaluate and calculate the index of the nutrient state of the lake according to the regulation of SL 395-2007 technical regulations for evaluating the quality of surface water resources, and then determines the score of the nutrient state of the lake according to the index value of the nutrient state of the lake.
(3) Bottom sludge contamination status
The pollution condition of the bottom sludge of the lake is expressed by adopting a bottom sludge pollution index, namely the concentration of pollutants in the bottom sludge accounts for the percentage of the corresponding standard value. Because no industry standard for controlling the concentration of the lake sediment pollutants exists at present, the standard value of the concentration of the lake pollutants refers to the standard of controlling the soil pollution risk of agricultural land of soil environmental quality GB 15618-2018 (trial), and the numerical value of the pollutant with the highest overproof concentration is selected when the index of the sediment pollution is assigned.
(4) Self-purification capacity of water body
The self-purification capacity of the water body is measured by selecting the concentration of dissolved oxygen in water. The survival of aquatic animals and plants is closely related to Dissolved Oxygen (DO), which is a necessary condition for the survival of aquatic animals such as fish. The dissolved oxygen concentration is more than 5mg/L, and the fish feed is suitable for most fishes to live. Meanwhile, dissolved oxygen is also an important factor for the self-purification function of the water body, and the lake is required to maintain good water quality and the self-purification function of the water body is carried out in the presence of the dissolved oxygen.
(5) Lake connectivity index
And evaluating according to the smoothness degree of water flow between the lake and the lake mainly entering stream and the lake exiting stream of the lake, wherein the larger the lake communication index is, the better the lake communication is.
(6) Shrinkage ratio of lake area
The lake water surface area of the evaluation year is expressed by the ratio of the lake water surface area shrunk (or expanded) to the lake water surface area of the historical reference year. The historical reference year is generally selected from the years with the hydrological frequency close to that of the evaluation year at the end of the 20 th century 80 s. The specific calculation method and the assigning standard are referred to the manual.
(7) Natural state of shore line
The lake shoreline health condition is evaluated by selecting a shoreline natural condition index, which comprises two aspects of lake shoreline stability and shoreline vegetation coverage rate. The lake bank stability comprises the aspects of bank slope inclination angle, bank slope vegetation coverage, bank slope height, bank slope matrix, bank slope scouring condition and the like. The specific calculation method and the assigning standard are referred to the guide.
(8) Water area shoreline degree exploitation and utilization in violation
The illegal development utilizes the water area shoreline degree to comprehensively consider the standardized construction rate of the lake-entering sewage discharge outlet, the reasonable layout degree of the lake-entering sewage discharge outlet and the four-disorder condition of the lake, and the classification is carried out according to the specific situation of the evaluation lake and the reference guide.
(9) Minimum ecological water level satisfaction degree
The lowest ecological water level is an important index for ensuring the survival of the lake organisms and the health of the lake, and the lowest ecological water level of the lake is generally determined by selecting a limit value determined by a lake planning or management file or by adopting a natural water level data method, a lake form method, a biological space minimum requirement method and the like.
(10) Degree of change of inflow into lake
The lake-entering flow variation degree reflects the influence of human activities on the lake-entering runoff and is represented by the average deviation degree of the lake-entering measured month runoff and natural month runoff of the lake-surrounding river. The larger the degree of the change of the inflow into the lake, the larger the influence of human activities and the lower the score. The specific calculation method and the assigning standard are referred to the guide.
(11) Biological integrity index for large benthic invertebrates
The biological integrity index (BIBI) of the large benthic invertebrates reflects the biological condition of aquatic organisms in the lake, and the conditions of the large benthic invertebrates at the reference points and the damaged points of the lake are analyzed and compared for evaluation.
(12) Fish retention index
The fish preservation index is an important index of lake health and is represented by the difference between the number of fish in the evaluation year and the number of fish in the historical reference year. The method comprises the steps of obtaining the number of fish species (removing foreign species) by on-site investigation of lake water areas, market and consultation related personnel, sampling site residents, fishermen, restaurant operators and other personnel and by means of reference of literature data and the like, and fish investigation sampling monitoring can be determined according to the technical standards of fish investigation such as SL 167-2014 reservoir fishery resource investigation standard.
(13) Water bird condition
Investigating and evaluating the species and the quantity of the birds in the lake, combining with on-site observation records as a grading basis, and grading according to five grades of good, general, poor and very poor according to the condition of the water bird habitat. The waterfowl condition assignment can also adopt a reference point multiple method, and the monitoring data of the historical reference time period before the significant change of the water quality and the form of rivers and lakes are taken as a base point, and the monitoring data of the 20 th century, the 80 th age or before is preferably adopted.
(14) Density of phytoplankton
The phytoplankton density index evaluation can select a reference point multiple method or a direct evaluation assigning method according to the actual situation of the lake. The reference point multiple method is characterized in that lakes which are similar in types and are not influenced or slightly influenced by human activities in the same ecological partition or geographic partition of the lakes are used as a base point by the reference point multiple method, monitoring data of historical reference time periods before the quality and the form of the lakes are changed greatly are used as a base point, and the estimated annual phytoplankton density is compared with the historical base point to calculate the multiple and assign the multiple. When there is no reference point, direct evaluation and assigning can be carried out according to the density of phytoplankton in lakes.
(15) Coverage of large aquatic plants
The large aquatic plant coverage degree comprises the total coverage degree of non-foreign species in four types of plants including emergent aquatic plants, floating leaf plants, submerged plants and floating plants in the water area from lake zones to lakes, and a reference point comparison assigning method or a direct judgment assigning method can be adopted according to the actual conditions of the lakes to be evaluated.
(16) Flood control standard-reaching rate
The lake flood control standard-reaching rate is evaluated by adopting the flood control standard-reaching conditions of dikes and buildings at lake surrounding mouths. The lake flood control standard-reaching rate is to calculate the lake flood control standard-reaching rate of the annual levee length evaluation, and simultaneously evaluate the proportion of buildings at the lake exit of the ring meeting the design standard. When the evaluation that the lake has no relevant planning and the flood control standard is specified, the evaluation can be determined according to GB 50201-2014 flood control standard.
(17) Degree of water supply
The guarantee degree of the water supply amount of the lake adopts the percentage of days for the day-by-day water level or flow of the lake to reach the guarantee water level or flow of the water supply in one year to the total days of the whole year. The specific mark assigning standard is referred to the guide.
(18) Lake centralized drinking water source ground standard-reaching rate
The standard-reaching rate of the water quality of the lake centralized drinking water source area refers to the percentage of the standard-reaching number of the centralized drinking water source areas (surface water) in the evaluation lake to the total number of the evaluation lake centralized drinking water source areas. The evaluation indexes are 24 basic indexes in GB 3838-2002 quality standard of surface water environment and 5 supplementary indexes of a centralized drinking water source area.
(19) Shore line utilization management index
And reflecting the integrity protection degree of the lake shoreline by using the management index. The shore power utilization management index comprises the shore power utilization rate and the utilized shore power perfection rate, and the score is assigned according to the calculation result.
(20) Degree of public satisfaction
The public satisfaction degree refers to the satisfaction degree of the public on the aspects of evaluating the water environment, the water quality and the water quantity of the lake, the wading landscape and the like. The satisfaction of the public is generally obtained by issuing a questionnaire, which is evaluated by a public survey method. And performing index assignment according to the public satisfaction degree participating in the investigation in the evaluation area.
And determining the health evaluation grading standard of each index according to the established lake health evaluation index system, and determining the weight of each element in the index layer and the criterion layer.
Specifically, the weight of each element in the index layer is determined by adopting an improved analytic hierarchy process, and the process comprises the following steps:
establishing a comparison matrix among elements in an index layer;
obtaining an indirect judgment matrix according to the comparison matrix;
obtaining a transfer matrix according to the indirect judgment matrix;
obtaining an optimal transfer matrix according to the transfer matrix;
obtaining a quasi-optimal consistent transfer matrix according to the optimal transfer matrix;
and solving the quasi-optimal consistent transfer matrix to obtain the eigenvector corresponding to the maximum eigenvalue, namely the weight of each element in the index layer.
The method specifically includes the following steps that the weight of each element in the index layer is determined by adopting an improved analytic hierarchy process:
(1) Building a hierarchical model
Based on the mutual relation as a layering basis, the decision target, the consideration and the decision object are divided into a highest layer, a middle layer and a lowest layer, namely a target layer, a criterion layer and an index layer.
(2) Establishing a comparison matrix
And comparing every two elements of the index layer, inviting experts in the water conservancy industry to scale by adopting a 0-2 three-scale method, and further establishing a comparison matrix A.
In the formula:
(3) Solving indirect judgment matrix
r i To compare ranking indices in a matrix, the ranking index of importance of each element can be calculated using the following formula:
r max denotes the maximum ranking index, r min Representing the minimum ranking index.
The elements of the indirect decision matrix C, C, can be determined by ij Indirectly judging the value of the ith row and the jth column of the matrix.
In the formula:
is represented by r max And r min The degree of importance is given on a scale when comparing.
(4) Constructing a transfer matrix
Constructing a transfer matrix as D, each element D in the matrix ij The following formula is followed:
d ij ＝lgc ij (i,j＝1,2,3,…,n)
(5) Constructing an optimal transfer matrix
Let the optimal transfer matrix be V, the calculation formula for the transformation is as follows:
in the formula: d ik Representing the element of the ith row and the kth column in the transfer matrix D, D jk And k represents the serial number of the index in the index layer corresponding to the criterion layer.
(6) Constructing a pseudo-optimal uniform transfer matrix
Let the pseudo-optimal consistent transmission matrix of the indirect judgment matrix C be C ', the element C ' in the matrix C ' ij The following formula is followed:
(7) Determining weights of elements in index layer
Determining the weight of each element in the index layer, understood from the mathematical essence, is to solve the maximum eigenvalue of the quasi-optimal uniform transfer matrix C' and the corresponding eigenvector:
C′ n×n W＝λ max W
in the formula: c' n×n A pseudo-optimal uniform transfer matrix of order n x n; lambda [ alpha ] max Is the maximum eigenvalue of the pseudo-optimal uniform transfer matrix; w is the eigenvector corresponding to the maximum eigenvalue; the obtained W is the required weight vector.
The element weights in the criterion layer are determined by referring to the specifications and guidelines in the industry, and for the case of no reference basis, the element weights in the criterion layer can also be determined by an improved analytic hierarchy process, wherein the process comprises the following steps:
establishing a comparison matrix among elements in a criterion layer;
obtaining an indirect judgment matrix according to the comparison matrix;
obtaining a transfer matrix according to the indirect judgment matrix;
obtaining an optimal transfer matrix according to the transfer matrix;
obtaining a quasi-optimal consistent transfer matrix according to the optimal transfer matrix;
and solving the quasi-optimal consistent transfer matrix to obtain the eigenvector corresponding to the maximum eigenvalue, namely the weight of each element in the rule layer.
The process of constructing the fuzzy comprehensive evaluation model of lake partition health comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership matrix of the first-level index according to the fuzzy relation matrix and the weight of each element of the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of the elements of the criterion layer and the membership matrix of the primary index; according to the maximum membership principle, obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix, which specifically comprises the following steps:
(1) Establishing a set of factors
The factor set is a set composed of elements of various factors that affect the evaluation object.
U＝{u 1 ,u 2 ,…,u j }，u j ＝{u j1 ,u j2 ,…,u jn }
In the formula: u is a factor set influencing a target layer, namely a criterion layer set; because each criterion layer comprises different n indexes, an index set u is established for each index of the criterion layer j ，u jn And determining according to the number of indexes under the j criterion layer.
Namely: and putting the standard layer factors in the lake health evaluation index system into a standard layer factor set, and putting the index layer factors into an index layer factor set.
(2) Constructing weight sets
Constructing a weight set of each element, wherein the weight set comprises a standard layer weight set W and an index layer weight set W j See the following formula.
W＝{w 1 ,w 2 ,…,w j }，W j ＝{w j1 ,w j2 ,…,w jn }
Wherein w j Weight, w, of the j element in the level of the representation criterion jn And representing the weight of the n index corresponding to the j element in the criterion layer.
Namely: putting the weights of all elements in the criterion layer into a criterion layer weight set W, putting the weights of all elements in the index layer into an index layer weight set W j In (1).
(3) Determining a fuzzy relation matrix R ij
Putting the target layer factors into an evaluation set, and establishing an evaluation set V n ＝{v 1n ,v 2n ,v 3n ,v 4n ,v 5n V in the formula 1n To v 5n Respectively represents the assigned standard values of 5 health grades of 'very healthy', 'sub-healthy', 'unhealthy' and 'bad state' of the lake corresponding to the nth index.
And constructing a formula suitable for the more and more optimal indexes, and calculating the membership degree according to the following formula, wherein x represents assigned values of all indexes. Constructing evaluation set and criterion layer factorsFuzzy relation matrix R of concentrated elements ij I.e. the membership matrix of the jth criterion layer of the ith partition.
Membership function f (x) to class I (very healthy) is
Membership function f (x) to class II (health) is
Membership function f (x) to class III (sub-health) is
Membership function f (x) to class IV (unhealthy) of
Membership function f (x) to the V-th class (inferior state) is
Constructing a fuzzy relation matrix R according to the membership function ij 。
Wherein r is the degree of membership calculated by the function of degree of membership, r ij11 Representing the degree of membership of the 1 st index in the ith partition, the jth criterion level, to level I (very healthy), r, calculated according to a membership function f (x) ij12 Representing the degree of membership of the 1 st index in the ith partition and the jth criterion layer to the II level (health) calculated according to a membership function f (x), and so on; ijn denotes the ith partition with the number of indices n for the jth criterion layer.
(4) Performing zonal hierarchical fuzzy evaluation
And performing first-level fuzzy evaluation on the criterion layer by the index layer, namely: according to a fuzzy relation matrix R ij And an index layer weight set W j And constructing a membership matrix of the primary index.
Performing first-level fuzzy evaluation by adopting the following formula to obtain a membership matrix B of a first-level index ij I.e. the membership matrix of the jth criterion layer of the ith partition.
In the formula: b ijn The membership degree of the jth criterion layer of the ith subarea to the health level of the lake, wherein n is an integer from 1 to 5.
And (3) performing two-stage fuzzy evaluation on the target layer by the criterion layer, namely: according to the weight set W of the criterion layer and the membership degree matrix B of the first-level index ij Obtaining a secondary fuzzy comprehensive evaluation membership matrix B i The method comprises the following steps:
constructing a secondary fuzzy evaluation relation matrix as R i See the following formula.
Obtaining a secondary fuzzy comprehensive evaluation membership matrix B according to the following formula i I.e. the membership matrix of the health level of the lake of the ith zone.
Obtaining a health evaluation result from the secondary fuzzy comprehensive evaluation membership matrix according to the maximum membership principle, namely selecting
The corresponding health grade is the final evaluation result of the lake partition.
The overall health fuzzy comprehensive evaluation model adopts a comprehensive analysis method to evaluate a membership matrix B according to a secondary fuzzy comprehensive evaluation i And water surface area W of each region i ' construction was obtained.
The overall health evaluation of the lake is based on the result of the subarea health evaluation, and an overall health fuzzy comprehensive evaluation model is established according to a comprehensive analysis method, which is shown in the following formula.
In the formula: b is a fuzzy evaluation set of overall health of the lake, B i For each partition, the fuzzy evaluation set of health evaluations, W i ' is the water surface area of each zone, and m is the number of lake zones.
(5) Comprehensively analyzing and evaluating the health of the lake
In addition, according to the maximum membership condition of each partition and the whole body, the health conditions of the partitions and the whole body of the lake can be judged, but the change difference of the same health level of the lake cannot be reflected specifically. In order to facilitate comparison of the change conditions of each partition and each criterion layer, a lake health comprehensive analysis and evaluation model is further constructed in the embodiment, and health grading scores of each partition and the whole lake are obtained according to the lake health comprehensive analysis and evaluation model.
The lake health comprehensive analysis and evaluation model comprises the following steps:
wherein, mu j Is a j criterion layer lake health score, mu is an integral lake health score, W e Is a score matrix, namely a health grading score matrix.
The lake health evaluation model is composed of a lake subarea health fuzzy comprehensive evaluation model, an overall health fuzzy comprehensive evaluation model and a lake health comprehensive analysis evaluation model, the weights and assigned values of all elements are input into the lake health evaluation model, and the lake health evaluation is carried out through the calculation result output by the evaluation model.
The method disclosed by the embodiment has the following advantages:
(1) Carrying out regional and integral lake health evaluation
And (3) dividing the healthy area of the lake, and simultaneously establishing a lake partition health fuzzy comprehensive evaluation model and an integral health fuzzy comprehensive evaluation model to finish partition and integral lake health evaluation. The regional health evaluation result can clearly reflect the change situation of the health level of the lake in the space, and is beneficial to quickly and accurately identifying the position of the pollution source and formulating a corresponding treatment scheme.
(2) Determination of weight of each element in index layer by improved analytic hierarchy process
Aiming at the problems that the traditional AHP method possibly causes the subjective judgment error of a decision maker and the consistency check of a judgment matrix cannot pass, the improved analytic hierarchy process adopts a three-scale method of 0-2 to construct a comparison matrix, and the influence of the fuzziness of the subjective judgment on the decision making is better overcome; and the concept of the optimal transfer matrix is used for more accurately constructing the judgment matrix, thereby avoiding the consistency check and adjustment of the judgment matrix. And constructing an optimal transfer matrix and a quasi-optimal consistent transfer matrix of the initial judgment matrix, and directly obtaining the relative weight of a certain level factor relative to a certain factor in the previous level after solving the eigenvector of the quasi-optimal consistent transfer matrix. Because the quasi-optimal consistent matrix meets the consistency requirement of the matrix, the steps of consistency check and the like on the initial judgment matrix are not needed, and the complicated calculation process in the traditional AHP method is avoided. Meanwhile, the introduction of a 'three-scale' method can reduce the subjectivity of determining the weight by adopting an expert evaluation method to a certain extent, and improve the accuracy of the lake health evaluation result.
(3) Evaluation and calculation of health condition of lake subareas by adopting fuzzy comprehensive evaluation method
In order to avoid the situation that misjudgment is likely to occur in the method for determining the health condition of the lake according to the weighted average, a fuzzy comprehensive evaluation method is adopted when the method is used for carrying out partition health evaluation calculation, the membership degrees of all indexes in five health levels (very healthy, sub-healthy, unhealthy and inferior) are judged through a fuzzy relation matrix, and the health level corresponding to the maximum membership degree is selected as a final evaluation result according to a maximum membership degree principle. Thus, the judgment deviation caused by different health level grading standards of the indexes can be avoided.
(4) Scoring and contrastively analyzing the final evaluation result
According to the maximum membership condition of each partition and the lake, the health conditions of the lake partitions and the whole lake can be judged, but the change difference of the lake in the same health level cannot be reflected specifically. In order to facilitate comparison of the change conditions of each partition and each criterion layer, a health level grading score matrix is established, and health evaluation scores of each criterion layer of the lake and the whole lake partition can be calculated. Therefore, the method is helpful for analyzing the cause of the health condition of the lake and judging the time change trend of the health condition of the lake.
(5) Advantage analysis is applied by combining analytic hierarchy process and fuzzy comprehensive evaluation method
The analytic hierarchy process is a weight analysis method, and the requirement on element weight in the application of the fuzzy comprehensive evaluation method enables the two methods to have a combined use basis. The analytic hierarchy process and the fuzzy comprehensive evaluation process are both suitable for evaluating the multi-factor complex problem with a hierarchical structure, and the combination of the two processes can better analyze and evaluate abstract and fuzzy problems. In addition, the analytic hierarchy process and the fuzzy comprehensive evaluation process are qualitative and quantitative combined methods, so that not only can a research object be evaluated by adopting a mathematical method, but also the experience of people can be fully exerted, and the evaluation result is more in line with objective practice.
The method disclosed by the embodiment is based on the ecological system health management angle, a set of lake health evaluation method which is suitable for lakes and integrates an evaluation index system and a health evaluation model is established, the rapid and comprehensive evaluation on the health state of the lakes is facilitated, and the main restriction factors of the health of the lakes are rapidly and accurately identified. The method adopted by the invention is scientific and reasonable, the established model is simple and easy to understand, the calculation result is accurate and intuitive, a very effective technical management tool is provided for lake management, and the practical significance is very prominent.
Taking the four lakes in south of Shandong province as an example, the specific implementation method of the invention is specifically explained by using relevant data of the lake in 2018.
(1) Performing health evaluation zoning according to the actual conditions of the four lakes
According to the practical conditions of' river and lake health evaluation guidelines (trial) issued by the management department of rivers and lakes of the department of water conservancy and the south four lakes in 2020 and 8 months, the health evaluation of the south four lakes and lakes is partitioned, and the partition principle is as follows:
1) The four south lakes are composed of four lakes, namely a Weishan lake, a Zhaoyang lake, a Dushan lake and a Nanyang lake, and the lake sheets in the jurisdiction of the growth of the peripheral lakes of the four south lakes are considered in consideration of the hydrological and hydrodynamic characteristics of the lakes, the water quality conditions of the lakes and the like;
2) Considering the water functional zone division characteristics of the lake;
3) Considering that biological indexes of four lakes of the south four lakes, such as phytoplankton density, macrophyte coverage, a large benthic invertebrate integrity index and the like, have spatial heterogeneity, biological zones are divided according to the four lakes, namely a Weishan lake zone, a Showa lake zone, a Dushan lake zone and a Nanyang lake zone.
According to the principle, the four lakes are divided into 14 health evaluation subareas, and the specific subareas are shown in figure 2.
(2) Establishing a health evaluation index system for lakes of the four lakes
Considering the difference of each subarea of the four lakes, an evaluation system criterion layer is established from 5 aspects of chemical integrity, morphological structure integrity, hydrological integrity, biological integrity and social service function integrity. Based on the principle of establishing an index system, the lake health evaluation index with higher use frequency is selected by adopting a frequency statistics method in combination with the actual conditions of the four lakes, and the lake health evaluation index system of the four lakes is established and is shown in table 1.
TABLE 1 health evaluation index system for four lakes and lakes
(3) And determining the health evaluation grading standard of each index according to the established lake health evaluation index system, and determining the weight of each element in the index layer and the criterion layer.
The index grading standard establishes the health evaluation grading standard of the lake health evaluation index shown in the table 2 by referring to the industry standard and the specification issued by the place.
TABLE 2 evaluation index of lake health
In order to further improve the accuracy of the evaluation index system, the weight is determined by combining experience and theory, namely the weight of each element in the criterion layer is determined by referring to the specifications and guidelines in the industry, and the weight of each element in the index layer is determined by adopting an improved analytic hierarchy process.
The weights of the elements in the criterion layer are determined by referring to 'river and lake health assessment guidelines (trial implementation)', i.e. the weights of B to A are shown in Table 3.
TABLE 3 weight table of lake health evaluation criterion layer
The weight of each element in the index layer is determined by adopting an improved analytic hierarchy process. A comparison matrix is established according to the scoring condition of 10 experts in the water conservancy industry by adopting a 0-2 scaling method, an indirect judgment matrix is obtained through formula calculation, and the indirect judgment matrices of indexes corresponding to all elements in the criterion layer are shown in tables 4-8.
TABLE 4B 1 Indirect judgment matrix between corresponding indexes
TABLE 5B 2 Indirect judging matrix between corresponding indexes
TABLE 6B 3 Indirect judgment matrix between corresponding indexes
TABLE 7B 4 Indirect judgment matrix between corresponding indexes
TABLE 8B 5 Indirect judging matrix between corresponding indexes
According to the indirect judgment matrix, a transfer matrix, an optimal transfer matrix and a quasi-optimal consistent transfer matrix are constructed by using a model formula, the eigenvalue of the quasi-optimal consistent transfer matrix and the corresponding eigenvector are solved, and the obtained eigenvector is the weight corresponding to each index, as shown in table 9.
TABLE 9 evaluation of health in the four southern lakes by element weight
According to the assigning standard of the index, the evaluation index data of the evaluation years are collected according to the actual conditions of the four south lakes, and the indexes of 14 partitions are assigned, wherein the assigning value of each partition of the four south lakes in 2018 is shown in fig. 3.
(5) And (3) taking assigned values of all the four lakes of south China as data bases, constructing a lake subarea health fuzzy comprehensive evaluation model and an overall health fuzzy comprehensive evaluation model by applying a multi-level fuzzy comprehensive evaluation method, and evaluating and calculating subareas and overall health conditions of the four lakes of south China.
1) According to the formula, the membership matrix of the four lake divisions 1 in south of 2018 is as follows:
2) First-level fuzzy evaluation of index layer to criterion layer
3) Two-stage fuzzy evaluation of criterion layer to target layer
According to the weight of each element in the primary fuzzy evaluation set and the formula, performing secondary fuzzy evaluation on the target layer to obtain a secondary fuzzy evaluation membership matrix B 1 。
According to the maximum membership principle, the maximum value in the secondary fuzzy evaluation membership matrix of the four lakes in south is 0.3501, and the lake is in a healthy state, so that the health state of the lake in the four lake zone 1 in south is in a healthy state and belongs to a II-class lake.
4) Result of partition health evaluation
Similarly, the health evaluation conditions of the other 13 subsections in the south four lakes 2018 are calculated, and the health condition grades of the subsections of the south four lakes are obtained according to the maximum membership principle, and are shown in table 10.
TABLE 10 health evaluation result table for four south lakes in 2018
5) Overall health assessment results
According to the health evaluation results of all the zones in the health state of the four-south lake zone, the overall health state of the four-south lake in 2018 is calculated according to the overall health comprehensive analysis model of the lake, and the results are shown in Table 11.
TABLE 11 Overall health evaluation results of the four lakes and lakes
(6) In order to facilitate the comparison of the change conditions of each partition and each criterion layer, a lake health comprehensive analysis and evaluation model is established.
Considering all aspects of factors, taking (100, 90, 75, 60 and 40) as a hierarchical score matrix of the health level of the lake, and calculating to obtain the health scores of all criterion layers and the whole lake. The overall health of the lake comprises:
100×0.3806+90×0.4174+75×0.1450+60×0.0254+40×0.0316＝89.29
the health evaluation score results of each standard layer of the four lakes in the south of 2018 are shown in table 12.
TABLE 12 health evaluation score table for each standard layer of four lakes and lakes in south 2018
(7) Health evaluation results and countermeasure analysis
According to the calculation result of the lake health evaluation model, the four lakes in the south of 2018 are in a healthy state, and the overall score is 89.29.
From the case of the criterion layer, the chemical integrity criterion layer B 1 Score 89.89 points, morphology knotStructural integrity criterion layer B 2 Score 92.18 points, hydrological integrity criteria layer B 3 Score 85.79 points, bio-integrity criteria layer B 4 Score of 89.09 points, and social service function integrity criterion layer B 5 The score was 88.94 points. In contrast, lake hydrological integrity criterion layer B 3 The score is low on the whole, and a manager is recommended to take measures from the aspect, so that the influence of human activities on the river flowing into the lake is reduced as much as possible, and the natural communication state of the river and the lake is kept. For landscape river channels in the river basin, certain ecological flow of the river channels needs to be ensured, and ecological balance of the river channels is maintained.
From the partition perspective, partitions 5, 7, 12, 14 are in a very healthy state, with the remaining partitions in a healthy state. As can be seen from the scoring of the partition criteria layer, 4 partitions in a very healthy state are in the chemical integrity criteria layer B 1 Morphological structural integrity criterion layer B 2 And a biological integrity criterion layer B 4 Higher scores were obtained, indicating that management of other health segments may be initiated from the three aspects described above. Meanwhile, in order to make more specific measures, the indexes corresponding to the criterion layer can be used. In the chemical integrity criterion layer, the situation that the concentration of total nitrogen and total phosphorus is higher needs to be treated by adopting corresponding measures. The pollution source can be controlled by increasing rural sewage treatment plants and reducing the discharge of untreated domestic sewage; meanwhile, green agriculture is advocated, the using amount of agricultural fertilizers and pesticides in the watershed of the south-four lakes is reduced, and the ammoniation and nitrification capacity of the water body is enhanced. In the morphological structure criterion layer, the planting amount of the shoreline vegetation should be increased properly to increase the shoreline vegetation coverage. According to the mode of combining natural restoration and artificial restoration, measures such as returning forest and returning grass, retreating tillage and prohibiting grazing, planting trees and forestation are adopted, the hardening proportion of the shoreline is reduced, and the ecological environment of the lake shoreline is improved. In the biological integrity criterion layer, modes such as adding algaecide and the like can be adopted to reduce the density of phytoplankton, and submerged plants, floating-leaf plants, emergent aquatic plants and the like are planted to increase the coverage of macrophytes. The excellent lake ecology can bring good inhabitation environment for birds, fishes and benthos, which is favorable forThe method is suitable for the living and the propagation of the lake organisms and the healthy development of the ecological system.
And aiming at other problems, advising a management department to take corresponding management measures. The culture scale of the purse seine in the lake region is strictly controlled, the pollution of the lake water caused by excessive culture and eutrophication is avoided, and a feasible method is adopted to timely treat the polluted water region. In addition, residents in lakes can move out through national and local subsidy supporting policies, influence of human activities in the lake areas is reduced, and corresponding arrangement measures are needed for the farmers to move out of the lake areas. Illegal coal mining and coal mining behaviors are prohibited, the collapsed road surface is repaired, and illegal operation on the lake surface is prohibited.
Example 2
In this embodiment, a system for evaluating and diagnosing health status of a lake is disclosed, which includes:
the partition module is used for carrying out health evaluation partition on the lake;
the health evaluation index system building module is used for building a lake health evaluation index system by adopting a TCI model, determining the weight of each element in the criterion layer and the index layer, and assigning a score to each index;
the health evaluation result acquisition module is used for acquiring the overall health evaluation results of each area and the lake according to the weight and the assigned value of each element and the constructed fuzzy comprehensive evaluation model and the overall health evaluation model of the lake subareas, wherein the process of constructing the fuzzy comprehensive evaluation model of the health of the lake subareas comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of all elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is constructed and obtained by a comprehensive analysis method according to the secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area.
Example 3
In this embodiment, an electronic device is disclosed, which includes a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method for evaluating and diagnosing the health status of a lake disclosed in embodiment 1.
Example 4
In this embodiment, a computer readable storage medium is disclosed for storing computer instructions, and the computer instructions, when executed by a processor, perform the steps of the method for evaluating and diagnosing the health status of a lake disclosed in embodiment 1.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (10)
1. A method for evaluating and diagnosing the health condition of a lake is characterized by comprising the following steps:
carrying out health evaluation zoning on the lake;
adopting a TCI model to construct a lake health evaluation index system, determining the weight of each element in a criterion layer and an index layer, and assigning a score to each index;
obtaining the overall health evaluation results of each area and the lake according to the weight and the assigned value of each element and the constructed fuzzy comprehensive evaluation model of the health of each area and the overall health evaluation model of the lake, wherein the process of constructing the fuzzy comprehensive evaluation model of the health of each area of the lake comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of all elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is obtained by constructing according to a secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each region by using a comprehensive analysis method.
2. The method for evaluating and diagnosing the health condition of the lake as claimed in claim 1, wherein the health evaluation index system comprises a target layer, a criterion layer and an index layer, the target layer represents the health condition of the lake, the criterion layer reflects the attributes and levels of the health condition of the lake from different sides, and the index layer consists of indexes corresponding to elements in the criterion layer.
3. The method as claimed in claim 2, wherein the criteria layer comprises chemical integrity, morphological structural integrity, hydrological integrity, biological integrity and social service functional integrity; wherein, the indexes corresponding to the chemical integrity criterion layer are the quality degree of water quality, the nutritional state of lakes, the pollution condition of bottom sediment and the self-purification capacity of water bodies; indexes corresponding to the morphological structure integrity criterion layer are a lake communication index, a lake area shrinkage proportion, a shoreline natural condition and a water area shoreline degree of illegal development and utilization; indexes corresponding to the hydrological integrity criterion layer are the minimum ecological water level satisfaction degree and the lake-entering flow variation degree; indexes corresponding to the biological integrity criterion layer are biological integrity indexes of the large benthic invertebrates, fish retention indexes, water bird conditions, phytoplankton density and large aquatic plant coverage; indexes corresponding to the social service function integrity criterion layer are flood control standard-reaching rate, water supply quantity guarantee degree, lake centralized drinking water source ground standard-reaching rate, shore utilization management index and public satisfaction degree.
4. The method for evaluating and diagnosing the health condition of the lake according to claim 1, wherein the process of determining the weight of each element in the index layer by using the improved analytic hierarchy process comprises the following steps:
establishing a comparison matrix among elements in an index layer;
obtaining an indirect judgment matrix according to the comparison matrix;
obtaining a transfer matrix according to the indirect judgment matrix;
obtaining an optimal transfer matrix according to the transfer matrix;
obtaining a quasi-optimal consistent transfer matrix according to the optimal transfer matrix;
and solving the quasi-optimal consistent transfer matrix to obtain the eigenvector corresponding to the maximum eigenvalue, namely the weight of each element in the index layer.
5. The method for evaluating and diagnosing the health condition of the lake of claim 1, wherein the fuzzy comprehensive evaluation model of the health of the lake subareas is constructed by the following steps:
putting elements in a criterion layer in a lake health evaluation index system into a criterion layer factor set, putting the elements in the index layer into an index layer factor set, putting the weights of all the elements in the criterion layer into the criterion layer weight set, putting the weights of all the elements in the index layer into the index layer weight set, and putting the elements in a target layer into an evaluation set;
constructing a fuzzy relation matrix of each element in the evaluation set and the criterion layer factor set;
constructing a membership degree matrix B of the primary index according to the fuzzy relation matrix and the index layer weight set ij Obtaining a secondary fuzzy comprehensive evaluation membership matrix B according to the criterion layer weight set and the membership matrix of the primary index i ；
And obtaining a health evaluation result from the secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle.
6. The method for evaluating and diagnosing the health condition of the lake of claim 1, wherein the overall fuzzy comprehensive evaluation model of the health is obtained by a comprehensive analysis method according to a secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each area, and specifically comprises the following steps:
in the formula: b is a fuzzy evaluation set of the overall health of the lake, B i Membership matrix, W, for a primary index of each partition i ' is the water surface area of each zone, and m is the number of lake zones.
7. The method for evaluating and diagnosing the health status of the lake according to claim 6, further comprising: and obtaining health grading score results of all areas and the whole body of the lake according to the membership matrix of the primary index, the overall health evaluation result of the lake and a comprehensive analysis and evaluation model of the health of the lake, wherein the comprehensive analysis and evaluation model of the health of the lake is as follows:
wherein, mu j Is a j criterion layer lake health score, mu is an integral lake health score, W e As a score matrix, i.e. a health grading score matrix, B ij Is a membership matrix of a first-level index, and B is a fuzzy evaluation set of the overall health of the lake.
8. A lake health condition evaluation and diagnosis system is characterized by comprising:
the partition module is used for carrying out health evaluation partition on the lake;
the health evaluation index system building module is used for building a lake health evaluation index system by adopting a TCI model, determining the weight of each element in the criterion layer and the index layer, and assigning a score to each index;
and the health evaluation result acquisition module is used for acquiring the overall health evaluation results of each lake region and the lake according to the weight of each element, the assigned value, the constructed fuzzy comprehensive evaluation model of the lake region health and the constructed fuzzy comprehensive evaluation model of the overall health, wherein the process of constructing the fuzzy comprehensive evaluation model of the lake region health comprises the following steps: constructing a fuzzy relation matrix of each element in the index layer and each element in the criterion layer; obtaining a membership degree matrix of the first-level index according to the fuzzy relation matrix and the weight of each element in the index layer; obtaining a secondary fuzzy comprehensive evaluation membership matrix according to the weights of all elements in the criterion layer and the membership matrix of the primary index; obtaining a health evaluation result from a secondary fuzzy comprehensive evaluation membership matrix according to a maximum membership principle; and the overall health fuzzy comprehensive evaluation model is obtained by constructing according to a secondary fuzzy comprehensive evaluation membership matrix and the water surface area of each region by using a comprehensive analysis method.
9. An electronic device comprising a memory, a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the steps of the method for evaluating and diagnosing the health condition of a lake according to any one of claims 1 to 7.
10. A computer-readable storage medium for storing computer instructions, wherein the computer instructions, when executed by a processor, perform the steps of the method for evaluating and diagnosing the health status of a lake according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116976694A (en) * | 2023-07-19 | 2023-10-31 | 珠江水利委员会珠江水利科学研究院 | Comprehensive evaluation method for beach ecosystem |
| CN117094464A (en) * | 2023-08-07 | 2023-11-21 | 湖南省自然资源事务中心 | Lake region water ecological safety evaluation method |
| CN117493112A (en) * | 2023-11-07 | 2024-02-02 | 国网江苏省电力有限公司信息通信分公司 | Operation and maintenance method and system based on big data automation operation and maintenance platform |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116976694A (en) * | 2023-07-19 | 2023-10-31 | 珠江水利委员会珠江水利科学研究院 | Comprehensive evaluation method for beach ecosystem |
| CN117094464A (en) * | 2023-08-07 | 2023-11-21 | 湖南省自然资源事务中心 | Lake region water ecological safety evaluation method |
| CN117094464B (en) * | 2023-08-07 | 2024-02-23 | 湖南省自然资源事务中心 | Lake region water ecological safety evaluation method |
| CN117493112A (en) * | 2023-11-07 | 2024-02-02 | 国网江苏省电力有限公司信息通信分公司 | Operation and maintenance method and system based on big data automation operation and maintenance platform |
| CN117493112B (en) * | 2023-11-07 | 2024-05-03 | 国网江苏省电力有限公司信息通信分公司 | Operation and maintenance method and system based on big data automation operation and maintenance platform |
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