A surface water quality evaluation method based on fuzzy algorithm

Abstract

The present invention discloses a surface water quality evaluation method based on fuzzy algorithm, which belongs to the field of water conservancy and hydrology / water resources monitoring. The present invention takes into account the situation that some monitoring factors far exceed the standard concentration of Class V. By calculating the difference between the measured concentration of the monitoring factor and the standard concentration of Class III water, the evaluation index of the monitoring factor exceeding the standard is obtained by using an index evaluation method that is more accurate for single factor evaluation; the fuzzy comprehensive evaluation is used to calculate the fuzzy comprehensive evaluation matrix of the river channel, and the proportion of Class IV and V water bodies in the overall water body is extracted, which is used as the fuzzy method exceeding the standard evaluation index; the exceeding standard weight is introduced to select an evaluation method that is closer to reality for the water quality of different rivers, and finally a comprehensive exceeding standard evaluation index is obtained. Compared with the traditional fuzzy comprehensive water quality evaluation, the present invention sorts the comprehensive exceeding standard evaluation index of different rivers, which can intuitively reflect the order of pollution degree of the rivers in the monitoring basin, provide judgment and basis for environmental protection departments, and is more practical.

Description

Technical Field

[0001] The invention relates to a surface water quality evaluation method based on fuzzy algorithm, and belongs to the field of water conservancy and hydrology / water resources monitoring. Background Art

[0002] Fuzzy mathematics is a method of studying and dealing with "fuzzy" phenomena. The so-called "fuzziness" mainly refers to the unclearness of the intermediate transition boundary between objective things. This unclearness is reflected in water quality evaluation, for example: the traditional standard sets the dissolved oxygen concentration of Class I water at 7.5 mg / L. If the actual situation is 7.4 mg / L, it belongs to Class II water. In fact, 7.4 mg / L is very close to 7.5 mg / L, so this classification is not very objective; the fuzzy comprehensive evaluation method uses the concept of membership to describe this situation, and classifies 7.4 mg / L as belonging to Class I water with a degree of 95%. This classification method is more in line with objective reality.

[0003] The traditional fuzzy comprehensive evaluation steps are: 1. Determine the type of water quality evaluation factor, construct an evaluation standard set, and determine the appropriate membership function; 2. Construct the weight vector of the water quality evaluation factor; 3. Construct a membership matrix based on the membership function and conduct a comprehensive evaluation with the weight vector. In the traditional evaluation method, according to the five types of water quality concentration standards divided in the surface water environmental quality, the membership function is determined by determining the approximate ratio of the evaluation factor and the corresponding water quality concentration. However, according to the actual situation, for those water bodies that exceed the standard, there will be a situation where the concentration of the evaluation factor exceeds the Class V standard. When the traditional water quality evaluation method is used to evaluate water bodies with different degrees of pollution exceeding the standard, no matter how much the evaluation factor exceeds the Class V standard, the corresponding membership function is {0, 0, 0, 0, 1}, and the constructed membership matrix will also lose objectivity and cannot well reflect the degree of exceeding the standard of the water body. Summary of the invention

[0004] In order to more intuitively and accurately judge the degree of exceeding the standard for water bodies, especially water bodies whose certain monitoring indicators exceed the standard concentration of Class V water, the present invention provides a surface water quality evaluation method based on fuzzy algorithm, and the technical scheme is as follows:

[0005] The surface water quality evaluation method of the present invention comprises:

[0006] Step 1: Determine the types of water quality assessment factors and obtain the measured values ​​of each monitoring factor;

[0007] Step 2: Calculate the standard average value of each monitoring factor;

[0008] Step 3: Construct the weight vector of each monitoring factor

[0009] First calculate the single factor weight:

[0010]

[0011] Among them, C ij represents the measured value of the ith monitoring factor of the jth river channel, represents the standard average value of the ith monitoring factor, W ij represents the weight of the ith monitoring factor of the jth river channel;

[0012] For each single factor weight W ij Normalize based on the normalized weight a of each factor ij Construct the weight vector:

[0013]

[0014] Step 4: Calculate the membership function of each monitoring factor and construct the membership matrix of the jth river channel based on the membership function

[0015] The membership function is expressed as:

[0016]

[0017]

[0018]

[0019] Membership Matrix It is expressed as:

[0020]

[0021] Among them, y in Indicates the membership value of the i-th monitoring factor to the n-th standard, n = 1, 2, 3, 4, 5;

[0022] Step 5: Based on the weight vector and the membership matrix Calculate the fuzzy comprehensive evaluation index matrix of the j-th river channel to obtain the proportion of the j-th river channel water body that meets the water quality standards of Class I to Class V;

[0023] Step 6: Calculate the fuzzy method exceeding standard evaluation index of the j-th river channel based on the proportion obtained in step 5;

[0024] Step 7: Calculate the monitoring factor exceeding standard index using the index evaluation method;

[0025] First, calculate the single factor excess index difference K ij , based on the normalized weight a ij The exponential method exceeding standard evaluation index of the j-th river channel is calculated as follows:

[0026] Q j =Σ(K ij *a ij )

[0027] Step 8: Introduce the excess weight Δ j , which represents the proportion of the jth river channel exceeding standard monitoring factor to all monitoring factors:

[0028]

[0029] Among them, n j represents the number of indicators measured in the jth river channel that do not meet the Class III water standard of surface water environmental quality standards; m j represents the number of all indicators monitored in the jth river;

[0030] Step 9: Combine the fuzzy method to determine the excess evaluation index P j The excess evaluation index Q of the sum index method j To calculate the comprehensive exceeding standard evaluation index of the jth river:

[0031] R j =(1-Δ j ) j +Δ j Q j

[0032] Among them, the comprehensive excess evaluation index R j The higher it is, the more polluted the j-th river is.

[0033] Optionally, the method for calculating the standard average value of each monitoring factor includes:

[0034]

[0035] Among them, S i1 , S i2 , S i3 , S i4 , S i5 They respectively represent the standard values ​​of Class I to Class V of the ith monitoring factor in the "Surface Water Environmental Quality Standard" (GB3838-2002).

[0036] Optionally, the single factor weight calculation formula of dissolved oxygen in step 3 is:

[0037]

[0038] in, It represents the average value of the standard values ​​of dissolved oxygen in Class I to V in the "Surface Water Environmental Quality Standard" (GB3838-2002), C DOjRepresents the monthly average measured value of dissolved oxygen in the jth river.

[0039] Optionally, in step 1, the monthly average measured value of the i-th monitoring factor of the j-th river channel is taken as the measured value C ij .

[0040] Optionally, the formula for calculating the fuzzy comprehensive evaluation index matrix of the j-th river channel in step 5 is:

[0041]

[0042] Among them, b j1 、b j2 、b j3 、b j4 、b j5 They represent the proportion of water bodies in the river j that meet the water quality standards of Class I to Class V, and b j1 +b j2 +b j3 +b j4 +b j5 =1.

[0043] Optionally, the method for calculating the fuzzy method over-standard evaluation index in step 6 is: j =b j4 +b j5 .

[0044] Optionally, the formula for calculating the single factor excess index difference in step 7 is:

[0045]

[0046] Among them, S i3 It represents the standard value of Class III in the Surface Water Environmental Quality Standard (GB3838-2002).

[0047] Optionally, the single factor excess index difference of dissolved oxygen in step 7 is:

[0048]

[0049] Among them, S DO3 Indicates the standard value of dissolved oxygen in Class III of the Surface Water Environmental Quality Standard (GB3838-2002), C DOj Represents the monthly average measured value of dissolved oxygen in the jth river.

[0050] The present invention provides a surface water quality evaluation device, comprising a memory and a processor;

[0051] The memory is used to store computer programs;

[0052] The processor is used to implement the surface water quality assessment method as described in any one of the above items when executing the computer program.

[0053] The present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the surface water quality evaluation method as described in any one of the above items is implemented.

[0054] The beneficial effects of the present invention are:

[0055] For rivers with monitoring factors exceeding the standard, the present invention proposes an improved surface water quality evaluation method based on fuzzy algorithm. Compared with the traditional fuzzy comprehensive evaluation, the present invention fully considers the situation that some monitoring factors far exceed the Class V standard concentration: by calculating the difference between the measured monthly average concentration of the monitoring factor and the Class III water standard concentration, the evaluation index of the monitoring factor exceeding the standard is obtained by using the index evaluation method that is more accurate for single factor evaluation; the fuzzy comprehensive evaluation is used to calculate the fuzzy comprehensive evaluation matrix of the river. Extract the proportion of Class IV and V water bodies in the total water body b j4 and b j5 , which is used as the fuzzy method over-standard evaluation index; the over-standard weight Δ is introduced j To achieve the selection of a more practical evaluation method for the water quality of different rivers, and finally obtain the comprehensive excess evaluation index R j .

[0056] Compared with the traditional fuzzy comprehensive water quality evaluation, this method has a better comprehensive evaluation index R of different rivers. j Sorting by size can intuitively reflect the order of pollution levels in the rivers within the monitored basin, provide judgment and basis for environmental protection departments, and is more practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0058] Figure 1 It is a logic flow chart of the surface water quality evaluation method based on fuzzy algorithm of the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0060] Embodiment 1:

[0061] This embodiment provides a surface water quality assessment method, comprising:

[0062] Step 1: Determine the types of water quality assessment factors and obtain the measured values ​​of each monitoring factor;

[0063] Step 2: Calculate the standard average value of each monitoring factor;

[0064] Step 3: Construct the weight vector of each monitoring factor

[0065] First calculate the single factor weight:

[0066]

[0067] Among them, C ij represents the measured value of the ith monitoring factor of the jth river channel, represents the standard average value of the ith monitoring factor, W ij represents the weight of the ith monitoring factor of the jth river channel;

[0068] For each single factor weight W ij Normalize based on the normalized weight a of each factor ij Construct the weight vector:

[0069]

[0070] Step 4: Calculate the membership function of each monitoring factor and construct the membership matrix of the jth river channel based on the membership function

[0071] The membership function is expressed as:

[0072]

[0073]

[0074]

[0075] Membership Matrix It is expressed as:

[0076]

[0077] Among them, y in Indicates the membership value of the i-th monitoring factor to the n-th standard, n = 1, 2, 3, 4, 5;

[0078] Step 5: Based on the weight vector and the membership matrix Calculate the fuzzy comprehensive evaluation index matrix of the j-th river channel to obtain the proportion of the j-th river channel water body that meets the water quality standards of Class I to Class V;

[0079] Step 6: Calculate the fuzzy method exceeding standard evaluation index of the jth river channel based on the proportion obtained in step 5;

[0080] Step 7: Calculate the monitoring factor exceeding standard index using the index evaluation method;

[0081] First, calculate the single factor excess index difference K ij , based on the normalized weight a ij The exponential method exceeding standard evaluation index of the j-th river channel is calculated as follows:

[0082] Q j =∑(K ij *a ij )

[0083] Step 8: Introduce the excess weight Δ j , which represents the proportion of the jth river channel exceeding standard monitoring factor to all monitoring factors:

[0084]

[0085] Among them, n j represents the number of indicators measured in the jth river channel that do not meet the Class III water standard of surface water environmental quality standards; m j represents the number of all indicators monitored in the jth river;

[0086] Step 9: Combine the fuzzy method to determine the excess evaluation index P j The excess evaluation index Q of the sum index method j To calculate the comprehensive exceeding standard evaluation index of the jth river:

[0087] R j =(1-Δ j ) j +Δ j Q j

[0088] Among them, the comprehensive excess evaluation index R j The higher it is, the more polluted the j-th river is.

[0089] Embodiment 2:

[0090] This embodiment provides a surface water quality evaluation method based on a fuzzy algorithm, comprising the following steps:

[0091] Step 1: Determine the types of water quality assessment factors and obtain the measured values ​​of each monitoring factor.

[0092] The method of the present invention is applicable to the 22 monitoring factors except water temperature and pH in Table 1 (Basic Items Standard Limits of Surface Water Environmental Quality Standards) of the Surface Water Environmental Quality Standards (GB3838-2002). Based on all the measured data of the monitoring basin, the monthly average measured value of the ith monitoring factor of the jth river channel is taken as the measured value C ij .

[0093] Step 2: Calculate the standard average value of each monitoring factor.

[0094] The calculation formula is:

[0095]

[0096] Among them, S i1 , S i2 , S i3 , S i4 , S i5 They respectively represent the standard values ​​of Class I to Class V of the ith monitoring factor in the "Surface Water Environmental Quality Standard" (GB3838-2002).

[0097] Step 3: Calculate the weight vector

[0098] First calculate the single factor weight:

[0099]

[0100] Among them, the single factor weight calculation formula of dissolved oxygen is:

[0101]

[0102] in, It represents the average value of the standard values ​​of dissolved oxygen in Class I to V in the "Surface Water Environmental Quality Standard" (GB3838-2002), C DOj Represents the monthly average measured value of dissolved oxygen in the jth river.

[0103] The weights of each factor are normalized to obtain the normalized weights. The calculation formula is:

[0104]

[0105] Construct a weight vector based on the normalized weights of each factor:

[0106]

[0107] Step 4: Calculate the membership function of each monitoring factor based on the monthly average value of each monitoring factor and the five standard concentrations corresponding to the monitoring factor, and construct the membership matrix of the jth river channel based on the membership function of each monitoring factor.

[0108] The expression of the membership function is as follows:

[0109] Upper Boundary:

[0110]

[0111]

[0112] Lower Boundary:

[0113]

[0114] Membership Matrix It is expressed as:

[0115]

[0116] Among them, y in It indicates the membership value of the i-th monitoring factor to the n-th standard, where n=1,2,3,4,5.

[0117] Step 5: Get the weight vector and the membership matrix Based on this, the fuzzy comprehensive evaluation index matrix of the jth river channel can be calculated:

[0118]

[0119] Among them, b j1 、b j2 、b j3 、b j4 、b j5 They represent the proportion of water bodies in the river j that meet the water quality standards of Class I to Class V, and b j1 +b j2 +b j3 +b j4 +b j5 =1.

[0120] Step 6: Extract the fuzzy comprehensive evaluation index of the jth river channel The proportion of Class IV and V water bodies in the total water bodyb j4 and b j5 , we can get the jth river channel fuzzy method exceeding standard evaluation index: P j =b j4 +b j5 ;

[0121] Step 7: Use the index evaluation method for individual monitoring factors that exceed the standard to intuitively and effectively reflect the exact value of the monitoring factor that exceeds the standard, which is more conducive to digitally reflecting the severity of the water body exceeding the standard. The calculation method of the index evaluation method is as follows:

[0122] First, calculate the single factor excess index difference:

[0123]

[0124] Among them, the single factor exceeding standard index difference of dissolved oxygen DO is:

[0125]

[0126] This embodiment is aimed at monitoring water bodies that exceed the standard, so multiple monitoring factors that meet the Class III water standard are set to 0.

[0127] The single factor excess index difference K is obtained ij Then based on the normalized weight a of the excess factor in the fuzzy algorithm ij The exponential method exceeding standard evaluation index of the jth river channel can be obtained by calculation:

[0128] Q j =∑(K ij *a ij )

[0129] Step 8: Introduce the excess weight Δ j , which represents the proportion of the monitoring factors exceeding the standard in the jth river channel to all monitoring factors:

[0130]

[0131] Among them, n j Indicates the number of indicators measured in the jth river channel that do not meet the Class III water standard in the Surface Water Environmental Quality Standard (GB3838-2002); m j Represents the number of all indicators monitored in the jth river channel.

[0132] Step 9: Combine the fuzzy method to determine the excess evaluation index P j The excess evaluation index Q of the sum index method j To calculate the comprehensive exceeding standard evaluation index of the jth river:

[0133] R j =(1-Δ j ) j +Δ j Q j

[0134] For rivers where the monitoring factors exceeding the standard account for a small number, fuzzy comprehensive evaluation is more realistic; conversely, index evaluation method is more realistic. j , it can be realized according to the proportion of excessive monitoring factors for different river monitoring conditions, and the proportion of corresponding evaluation methods can be enlarged or reduced to ensure that the data obtained is closer to the actual situation.

[0135] Step 10: Calculate the comprehensive exceeding standard evaluation index R for different river channels in a basin j , and sort them by size, R j The higher the value, the more polluted the river is. The ranking can help us visually see which rivers should be given priority for treatment, which can improve the efficiency of environmental protection departments in managing water bodies.

[0136] This embodiment proposes an improved surface water quality evaluation method based on fuzzy algorithm. Compared with the traditional fuzzy comprehensive evaluation, it fully considers the situation that some monitoring factors far exceed the Class V standard concentration: by calculating the difference between the measured monthly average concentration of the monitoring factor and the Class III water standard concentration, the evaluation index of the monitoring factor exceeding the standard is obtained by using the index evaluation method that is more accurate for single factor evaluation; the fuzzy comprehensive evaluation is used to calculate the fuzzy comprehensive evaluation matrix of the river channel. Extract the proportion of Class IV and V water bodies in the total water body b j4 and b j5 , which is used as the fuzzy method over-standard evaluation index; the over-standard weight Δ is introduced j To achieve the selection of a more practical evaluation method for the water quality of different rivers, and finally obtain the comprehensive excess evaluation index R j .

[0137] Compared with the traditional fuzzy comprehensive water quality evaluation, the method in this embodiment has a comprehensive evaluation index R of different rivers. j Sorting by size can intuitively reflect the order of pollution levels in the rivers within the monitored basin, provide judgment and basis for environmental protection departments, and is more practical.

[0138] Some steps in the embodiments of the present invention may be implemented using software, and the corresponding software program may be stored in a readable storage medium, such as a CD or a hard disk.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A surface water quality evaluation method, characterized in that: The method comprises: Step 1: Determine the types of water quality assessment factors and obtain the measured values ​​of each monitoring factor; Step 2: Calculate the standard average value of each monitoring factor; Step 3: Construct the weight vector of each monitoring factor First calculate the single factor weight: Among them, C ij represents the measured value of the ith monitoring factor of the jth river channel, represents the standard average value of the ith monitoring factor, W ij represents the weight of the ith monitoring factor of the jth river channel; For each single factor weight W ij Normalize based on the normalized weight a of each factor ij Construct the weight vector: Step 4: Calculate the membership function of each monitoring factor and construct the membership matrix of the jth river channel based on the membership function The membership function is expressed as: Membership Matrix It is expressed as: Among them, y in Indicates the membership value of the i-th monitoring factor to the n-th standard, n = 1, 2, 3, 4, 5; Step 5: Based on the weight vector and the membership matrix Calculate the fuzzy comprehensive evaluation index matrix of the j-th river channel to obtain the proportion of the j-th river channel water body that meets the water quality standards of Class I to Class V; Step 6: Calculate the fuzzy method exceeding standard evaluation index of the j-th river channel based on the proportion obtained in step 5; Step 7: Calculate the monitoring factor exceeding standard index using the index evaluation method; First, calculate the single factor excess index difference K ij , based on the normalized weight a ij The exponential method exceeding standard evaluation index of the j-th river channel is calculated as follows: Q j =∑(K ij *a ij ) Step 8: Introduce excess weights j , which represents the proportion of the jth river channel exceeding standard monitoring factor to all monitoring factors: Among them, n j represents the number of indicators measured in the jth river channel that do not meet the Class III water standard of surface water environmental quality standards; m j represents the number of all indicators monitored in the jth river; Step 9: Combine the fuzzy method to determine the excess evaluation index P j The excess evaluation index Q of the sum index method j To calculate the comprehensive exceeding standard evaluation index of the jth river: R j =(1- j )P j + j Q j Among them, the comprehensive excess evaluation index R j The higher it is, the more polluted the j-th river is.

2. The surface water quality evaluation method according to claim 1, characterized in that: The calculation method of the standard average value of each monitoring factor includes: Among them, S i1 , S i2 , S i3 , S i4 , S i5 They respectively represent the standard values ​​of Class I to Class V of the ith monitoring factor in the "Surface Water Environmental Quality Standard" (GB3838-2002).

3. The surface water quality evaluation method according to claim 1, characterized in that: The single factor weight calculation formula of dissolved oxygen in step 3 is: in, It represents the average value of the standard values ​​of dissolved oxygen in Class I to V in the "Surface Water Environmental Quality Standard" (GB3838-2002), C DOj Represents the monthly average measured value of dissolved oxygen in the jth river.

4. The surface water quality evaluation method according to claim 1, characterized in that: In step 1, the monthly average measured value of the i-th monitoring factor of the j-th river channel is taken as the measured value C ij .

5. The surface water quality evaluation method according to claim 1, characterized in that: The formula for calculating the fuzzy comprehensive evaluation index matrix of the j-th river channel in step 5 is: Among them, b j1 , b j2 , b j3 , b j4 , b j5 They represent the proportion of water bodies in the river j that meet the water quality standards of Class I to Class V, and b j1 +b j2 +b j3 +b j4 +b j5 =1.

6. The surface water quality evaluation method according to claim 5, characterized in that: The method for calculating the fuzzy method over-standard evaluation index in step 6 is: j =b j4 +b j5 .

7. The surface water quality evaluation method according to claim 1, characterized in that: The formula for calculating the single factor excess index difference in step 7 is: Among them, S i3 It represents the standard value of Class III in the Surface Water Environmental Quality Standard (GB3838-2002).

8. The surface water quality evaluation method according to claim 7, characterized in that: The single factor exceeding standard index difference of dissolved oxygen in step 7 is: Among them, S DO3 Indicates the standard value of dissolved oxygen in Class III of the Surface Water Environmental Quality Standard (GB3838-2002), C DOj Represents the monthly average measured value of dissolved oxygen in the jth river.

9. A surface water quality evaluation device, characterized in that: including memory and processor; The memory is used to store computer programs; The processor is used to implement the surface water quality assessment method according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the surface water quality evaluation method according to any one of claims 1 to 8 is implemented.

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