Comprehensive benefit evaluation method for water supply project in arid region

Abstract

The invention provides a comprehensive benefit evaluation method for a water supply project in an arid region, and the method comprises the steps: building a comprehensive benefit evaluation system comprising economic indexes, social indexes and ecological indexes, obtaining subjective and objective weights through the combination of an analytic hierarchy process and an entropy weight method, improving the game theory according to the idea of maximizing the deviation, and obtaining the comprehensive benefit of the water supply project in the arid region. And obtaining subjective and objective fusion weights. According to the method, qualitative index scores are obtained based on the scores of the experts, the conflict between the experts is measured by adopting JS divergence aiming at the conflict problem existing between the scores of the different experts, the weights of the experts are calculated, and then the fusion result of the scores of the multiple experts is obtained to serve as the index scores. In order to comprehensively and objectively evaluate the comprehensive benefits of the Yellow River water supply project in the northwest arid region, a fuzzy comprehensive evaluation method and a cloud model are adopted to evaluate the comprehensive benefits, and the randomness and fuzziness of evaluation data sources are fully considered.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy project benefit evaluation, and in particular to a comprehensive benefit evaluation method for water supply projects in arid areas. Background Art

[0002] Drought and water shortage are key factors restricting the economic, social and ecological development of the arid areas in Northwest China. Since the 1970s, my country has built a number of Yellow River water supply projects in Northwest China, which have greatly alleviated the local water shortage problem, played an important role in promoting poverty alleviation and prosperity in Northwest China, and made significant contributions to local economic and social development. Reasonable evaluation of the comprehensive benefits of water supply projects is particularly important for local human survival and sustainable development. Constructing a guiding and operational benefit evaluation index system and evaluation method has important theoretical significance and practical value for the comprehensive benefit evaluation of water supply projects.

[0003] When conducting a comprehensive benefit evaluation of a project, we should not only consider the economic benefits of the project, but also the social and ecological benefits of the project. However, for water supply projects in the arid areas of Northwest China, the socio-economic development conditions, geographical environment, and hydrogeological conditions during their construction are extremely special, and it is difficult to have a comprehensive benefit evaluation method suitable for such projects. Summary of the invention

[0004] In view of the problems existing in the comprehensive benefit evaluation of water conservancy projects, the present invention provides a comprehensive benefit evaluation method for water supply projects in arid areas.

[0005] The solution adopted by the present invention to solve the technical problem is: a method for evaluating the comprehensive benefits of the Yellow River water supply project in arid areas, comprising the following steps:

[0006] S1. Establish a comprehensive benefit evaluation index system for water supply projects, establish different benefit evaluation indicators according to the content of comprehensive benefits, determine the evaluation level of benefit evaluation indicators, and set the evaluation level of evaluation indicators;

[0007] S2. Calculate the subjective weight of each benefit evaluation indicator using the analytic hierarchy process, calculate the objective weight of each benefit evaluation indicator using the entropy weight method, integrate and calculate the subjective and objective weights of the benefit evaluation indicators, summarize the weights obtained by the analytic hierarchy process and the entropy weight method, calculate the subjective and objective weight fusion coefficient α, calculate the subjective and objective fusion weights for combined weighting, and determine the final weight based on the weight of the game theory combined weighting method improved by maximizing the deviation;

[0008] S3. Determination of the degree of membership: Invite experts in the field of water conservancy to analyze and evaluate the degree of membership of the evaluation indicators, use JS divergence to measure the credibility of experts, integrate the differences between the scores of different experts, integrate the scoring results of multiple experts, calculate the expert weights, and obtain the comprehensive score of the evaluation indicators and the degree of membership of the indicators for each level;

[0009] S4, conduct multi-level fuzzy comprehensive evaluation on the evaluation indicators of the determined membership degree;

[0010] S5. By introducing the membership cloud model, the core factors and indicators that affect the comprehensive benefits of the project are clarified, and the digital visualization expression of the comprehensive benefit evaluation results of the project is realized.

[0011] Furthermore, the criterion layer in the evaluation index system includes economic benefits, social benefits and ecological benefits. The economic benefits include industrial water supply A1, domestic water supply A2, large-scale aquaculture water supply A3, and public green space water supply A4; the social benefits include tourism and leisure B1, landscape aesthetics B2, scientific research and education B3, cultural heritage B4, public health B5, political services B6, and social economy B7; the ecological benefits include: water resource storage C1, water quality purification C2, air purification C3, nitrogen fixation and oxygen release C4, prevention of soil erosion C5, climate regulation C6, water source conservation C7, noise reduction C8, biodiversity C9, maintenance of nutrient cycle C10, control of landing funnel C11, and biological habitat C12. At the same time, the evaluation levels of the evaluation indicators are divided into five levels: very good, good, medium, poor and very poor, and the corresponding evaluation level set is V={V1, V2, V3, V4, V5}={very good, good, medium, poor and very poor}.

[0012] Furthermore, the analytic hierarchy process calculates subjective weights by constructing a criterion layer judgment matrix through expert scoring, and performs a relative importance analysis on the selected indicators based on the expert experience table, thereby establishing a judgment matrix P = [pij], calculating the maximum eigenvalue of the matrix, obtaining the corresponding eigenvector, and calculating the consistency index CI and consistency ratio CR according to the formula;

[0013]

[0014] In the formula, n is the order of the judgment matrix, RI is the average consistency index,

[0015] RI value table

[0016]

[0017] When CR<0.1, the judgment matrix P passes the consistency check, otherwise the judgment matrix needs to be adjusted until it passes the consistency check.

[0018] The weight of the criterion layer is calculated according to the formula, which is to calculate the weight of each indicator in the indicator layer in turn.

[0019]

[0020] Where ω is the quasi-layer weight, μ is the eigenvector corresponding to the maximum eigenvalue,

[0021] The weight of the criterion layer is calculated to be ω, and then the weight of each indicator in the indicator layer is calculated in turn. Ten experts are asked to score the criterion layer and the indicator layer respectively, and the scoring weight of each expert is calculated. The sum and average of the scores are used to obtain the weight of each indicator.

[0022] Furthermore, the process of calculating the objective weight using the entropy weight method includes:

[0023] First, we conducted a questionnaire survey, invited several water conservancy experts, and provided them with background information on related projects to conduct an indicator study. Based on the actual situation of the water supply project, combined with the established indicator system and the actual situation achieved by each indicator, we conducted an evaluation and scoring.

[0024] The expert scoring results are used to calculate the objective weights of the comprehensive benefit evaluation indicators according to the entropy weight method. The specific calculation process is as follows:

[0025] (1) Normalize the evaluation index according to the formula

[0026] Positive indicators:

[0027] Negative indicators:

[0028] In the formula, γ is the original value of the evaluation index;

[0029] (2) Calculate the proportion p of the i-th sample value under the j-th indicator ij :

[0030]

[0031] (3) Calculate the entropy value e of the jth indicator j :

[0032]

[0033] (i=1,2,...,n;j=1,2,...,m;where k=1 / ln(n)>0, and e j ≥0), when p ij = 0, let ln(P ij )=0);

[0034] (4) Calculate the information entropy redundancy d j :

[0035] d j =1-e j ,(j=1,2,…,m);

[0036] (5) Calculate the weight w of the indicator j :

[0037]

[0038] (6) Calculate the final comprehensive score value s j :

[0039]

[0040] Further, the determination of the membership degree comprises the following steps:

[0041] Normalize the experts’ scoring results.

[0042]

[0043] In the formula, Q ij is the normalized value of the score given by the i-th expert to the j-th indicator;

[0044] Calculate the KL divergence between the i-th expert and the j-th expert,

[0045]

[0046] Where Qi and Qj are the normalized score vectors of the i-th expert and the j-th expert, DKL(Qi||Qj) is the KL divergence of the scores of the i-th expert and the j-th expert, and log represents the logarithmic function with base 2;

[0047] Calculate the JS divergence between the i-th expert and the j-th expert,

[0048]

[0049] Further calculation of expert weights

[0050]

[0051] And calculate the comprehensive score of the indicator and the degree of membership of the indicator to each level respectively

[0052]

[0053]

[0054] Where wi is the weight of the i-th expert, and sj is the final score of the j-th indicator.

[0055] Furthermore, the multi-level fuzzy comprehensive evaluation in S4 includes: determining the weight vector of evaluation factors,

[0056] (1) Determine the factor set and evaluation set of evaluation indicators;

[0057] (2) Determine the weight vector of evaluation factors;

[0058] (3) First-level fuzzy comprehensive evaluation

[0059]

[0060] In the formula, o is the weighted average operator;

[0061] (4) Secondary fuzzy comprehensive evaluation

[0062] Based on the first-level fuzzy comprehensive evaluation results, the first-level fuzzy calculation is performed

[0063] B=W*(B1,B2,…,B k ) T =(w1,w2,…,w k )*(B1,B2,…,B k ) T .

[0064] Furthermore, the membership cloud model includes: determination of the evaluation standard cloud, determination of the evaluation index cloud and final result evaluation, wherein the golden ratio is used and brought into the standard cloud digital feature calculation formula based on the comment set and interval values ​​obtained from the consulting experts to obtain the expected Ex, entropy En and super entropy He of the standard cloud; Matlab software is used to obtain the result evaluation, the above-mentioned standard cloud and evaluation cloud are placed in the same coordinate system, and the specific evaluation results of the project are determined based on the position distribution of the two and the principle of maximum similarity, and economic benefit, social benefit, economic benefit and comprehensive benefit evaluation cloud maps are generated respectively, and the similarity of each evaluation result is calculated.

[0065] Beneficial effects of the invention: The invention combines the unique geographical location, climate and environmental conditions and weak ecological environment of the arid region of Northwest China, selects scientific and advanced evaluation methods, and forms a set of evaluation methods suitable for the comprehensive benefits of water supply projects in the arid region of Northwest China. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a framework diagram of the comprehensive benefit evaluation method of the Yellow River water supply project in arid areas. DETAILED DESCRIPTION

[0067] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below.

[0068] Embodiment 1: The present invention provides a method for evaluating the comprehensive benefits of water supply projects in arid areas. Taking the Yellow River Water Supply Project in the Northwest Arid Area as an example, a comprehensive benefit evaluation system including economic indicators, social indicators and ecological indicators is established. The subjective and objective weights are obtained by combining the analytic hierarchy process and the entropy weight method. The game theory is improved according to the idea of ​​maximizing the deviation to obtain the subjective and objective fusion weights. The qualitative index scores are obtained based on the expert scores, and the JS divergence is used to measure the conflicts between the scores of different experts. The expert weights are calculated, and then the fusion results of the scores of multiple experts are obtained as the index scores. In order to comprehensively and objectively evaluate the comprehensive benefits of the Yellow River Water Supply Project in the Northwest Arid Area, the fuzzy comprehensive evaluation method and the cloud model are used to evaluate it, respectively, and the randomness and fuzziness of the evaluation data source are fully considered.

[0069] The comprehensive benefit evaluation method of the Yellow River water supply project in the arid areas of Northwest China is carried out in the following steps:

[0070] Step 1

[0071] 1.1 Establishing an indicator system

[0072] The criterion layers in the evaluation index system include economic benefits, social benefits and ecological benefits. The economic benefits include industrial water supply A1, domestic water supply A2, large-scale aquaculture water supply A3, and public green space water supply A4; the social benefits include tourism and leisure B1, landscape aesthetics B2, scientific research and education B3, cultural heritage B4, public health B5, political services B6, and social economy B7; the ecological benefits include: water resource storage C1, water purification C2, air purification C3, nitrogen fixation and oxygen release C4, prevention of soil erosion C5, climate regulation C6, water source conservation C7, noise reduction C8, biodiversity C9, maintenance of nutrient cycle C10, control of landing funnel C11, and biological habitat C12.

[0073] 1.2 Determination of evaluation level

[0074] The indicator evaluation levels are determined to be very good, good, medium, poor and very poor. The corresponding evaluation level set is V = {V1, V2, V3, V4, V5} = {very good, good, medium, poor and very poor}

[0075] Step 2

[0076] 2.1 Calculation of subjective weights using AHP

[0077] The criterion layer judgment matrix is ​​constructed through expert scoring. The relative importance of the selected indicators is analyzed based on the expert experience table, so as to establish the judgment matrix P = [pij]. The maximum eigenvalue λ of the matrix is ​​calculated by Matlab software max, get the corresponding feature vector, and calculate the consistency index CI and consistency ratio CR according to formula (1) and (2):

[0078]

[0079]

[0080] Where n is the order of the judgment matrix, and RI is the average consistency index.

[0081] Table 1 RI value table

[0082]

[0083] As shown in Table 1, the value range of RI, when CR<0.1, the judgment matrix P passes the consistency check, otherwise it is necessary to adjust the judgment matrix until it passes the consistency check.

[0084]

[0085] Where ω is the quasi-layer weight and μ is the eigenvector corresponding to the maximum eigenvalue.

[0086] According to formula (3), the weight of the criterion layer is calculated as ω. Similarly, the weights of each indicator in the indicator layer are calculated.

[0087] Similarly, according to the above steps, 10 experts are asked to score the criterion layer and the indicator layer respectively, and the scoring weight of each expert is calculated. The sum and average of the scores are used to obtain the weight of each indicator.

[0088] 2.2 Calculation of objective weights using entropy weight method

[0089] First, we conducted a questionnaire survey, invited a number of water conservancy experts, provided them with background information on relevant projects, and conducted indicator research. Based on the actual situation of the Taiyangshan Water Supply Project, we combined the established indicator system and the actual situation achieved by each indicator to conduct an evaluation and scoring.

[0090] The scoring results of the above experts are used to calculate the objective weights of the comprehensive benefit evaluation indicators of Taiyangshan according to the entropy weight method. The specific calculation process is as follows:

[0091] (1) Normalize the index according to formula (4)

[0092] Positive indicators:

[0093] (2) Calculate the proportion p of the i-th sample value under the j-th indicator ij , as shown in formula (5)

[0094]

[0095] (3) Calculate the entropy value e of the jth indicator j , as shown in formula (6)

[0096]

[0097] (i=1,2,...,n;j=1,2,...,m;where k=1 / ln(n)>0, and e j ≥0), when p ij = 0, let ln(P ij )=0).

[0098] (4) Calculate the information entropy redundancy d j , as shown in formula (7)

[0099] d j =1-e j ,(j=1,2,…,m) (7)

[0100] (5) Calculate the weight w of the indicator j , as shown in formula (8)

[0101]

[0102] (6) Calculate the final comprehensive score value s j , as shown in formula (9)

[0103]

[0104] 2.3 Fusion calculation of subjective and objective weights of indicators

[0105] The weights obtained by the above analytic hierarchy process and entropy weight method are summarized and expressed as follows:

[0106]

[0107] Calculate the subjective and objective weight fusion coefficient α,

[0108] The subjective and objective fusion weights are calculated according to formula (11) for combined weighting. The weight of the game theory combined weighting method improved by maximizing the deviation is:

[0109]

[0110] Determine the final weight.

[0111] 2.4 Determination of membership

[0112] Experts in the field of water conservancy were invited to analyze and evaluate the degree of subordination of the indicators. In order to reasonably integrate the differences between the scores of different experts, the scoring results of multiple experts were integrated and the JS divergence was used to measure the credibility of the experts.

[0113] The scoring results are normalized, as shown in formula (12):

[0114]

[0115] In the formula, Q ij is the normalized score of the i-th expert on the j-th indicator.

[0116] Calculate the KL divergence between the i-th expert and the j-th expert, as shown in formula (13):

[0117]

[0118] Where Qi and Qj are the normalized score vectors of the i-th expert and the j-th expert, DKL(Qi||Qj) is the KL divergence of the scores of the i-th expert and the j-th expert, and log represents the logarithmic function with base 2.

[0119] Calculate the JS divergence between the i-th expert and the j-th expert, as shown in formula (14):

[0120]

[0121] The expert weights are further calculated according to formulas (15) and (16).

[0122]

[0123] And according to formula (17) and formula (18), the comprehensive score of the index and the degree of membership of the index to each level are calculated respectively.

[0124]

[0125] In the formula, wi is the weight of the i-th expert, sj is the final score of the j-th indicator,

[0126]

[0127] 2.5 Multi-level fuzzy comprehensive evaluation

[0128] (1) Determination of factor set and evaluation set;

[0129] (2) Determine the weight vector of evaluation factors;

[0130] (3) First-level fuzzy comprehensive evaluation, as shown in formula (19)

[0131]

[0132] Where o is the weighted average operator.

[0133] (4) Secondary fuzzy comprehensive evaluation

[0134] Based on the first-level fuzzy comprehensive evaluation results, the first-level fuzzy calculation can be performed. The detailed calculation process is shown in formula (20):

[0135] B=W*(B1,B2,…,B k ) T =(w1,w2,…,w k )*(B1,B2,…,B k ) T (20)

[0136] 2.6 Cloud Model

[0137] By introducing the membership cloud model, the core factor indicators that affect the comprehensive benefits of the project are clarified, and the digital visualization expression of the comprehensive benefit evaluation results of the project is realized.

[0138] 2.6.1 Determination of the evaluation standard cloud

[0139] According to the comment set and interval value obtained by consulting experts in the previous article, the golden ratio is used and brought into the standard cloud digital feature calculation formula to obtain the expected Ex, entropy En and super entropy He of the standard cloud.

[0140] 2.6.2 Determination of evaluation index cloud

[0141] 2.6.3 Result evaluation

[0142] Using Matlab software, the standard cloud and the calculated evaluation cloud are placed in the same coordinate system, and the specific evaluation results of the project are determined based on their position distribution and the principle of maximum similarity.

[0143] Generate economic benefit, social benefit, economic benefit and comprehensive benefit evaluation cloud maps respectively, and calculate the similarity of each evaluation result.

[0144] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Claims

1. A comprehensive benefit evaluation method for water supply projects in arid areas, characterized in that: The following steps are involved: S1. Establish a comprehensive benefit evaluation index system for water supply projects, establish different benefit evaluation indicators according to the content of comprehensive benefits, determine the evaluation level of benefit evaluation indicators, and set the evaluation level of evaluation indicators; S2. Calculate the subjective weight of each benefit evaluation indicator using the analytic hierarchy process, calculate the objective weight of each benefit evaluation indicator using the entropy weight method, integrate and calculate the subjective and objective weights of the benefit evaluation indicators, summarize the weights obtained by the analytic hierarchy process and the entropy weight method, calculate the subjective and objective weight fusion coefficient α, calculate the subjective and objective fusion weights for combined weighting, and determine the final weight based on the weight of the game theory combined weighting method improved by maximizing the deviation; S3. Determination of the degree of membership: Invite experts in the field of water conservancy to analyze and evaluate the degree of membership of the evaluation indicators, use JS divergence to measure the credibility of experts, integrate the differences between the scores of different experts, integrate the scoring results of multiple experts, calculate the expert weights, and obtain the comprehensive score of the evaluation indicators and the degree of membership of the indicators for each level; S4, conduct multi-level fuzzy comprehensive evaluation on the evaluation indicators of the determined membership degree; S5. By introducing the membership cloud model, the core factor indicators that affect the comprehensive benefits of the project are determined, and the digital visualization expression of the comprehensive benefit evaluation results of the project is realized.

2. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The criterion layer in the evaluation index system includes economic benefits, social benefits and ecological benefits. The economic benefits include industrial water supply A1, domestic water supply A2, large-scale aquaculture water supply A3, and public green space water supply A4; the social benefits include tourism and leisure B1, landscape aesthetics B2, scientific research and education B3, cultural heritage B4, public health B5, political services B6, and social economy B7; the ecological benefits include: water resource storage C1, water quality purification C2, air purification C3, nitrogen fixation and oxygen release C4, prevention of soil erosion C5, climate regulation C6, water source conservation C7, noise reduction C8, biodiversity C9, maintenance of nutrient cycle C10, control of landing funnel C11, and biological habitat C12. At the same time, the evaluation levels of the evaluation indicators are divided into five levels: very good, good, medium, poor and very poor, and the corresponding evaluation level set is V={V1, V2, V3, V4, V5}={very good, good, medium, poor and very poor}.

3. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The analytic hierarchy process calculates subjective weights by constructing a criterion layer judgment matrix through expert scoring, and performs a relative importance analysis on the selected indicators based on the expert experience table, thereby establishing a judgment matrix P = [pij], calculating the maximum eigenvalue of the matrix, obtaining the corresponding eigenvector, and calculating the consistency index CI and the consistency ratio CR according to the formula; Where n is the order of the judgment matrix, RI is the average consistency index, and when CR<0.1, the judgment matrix P passes the consistency check. Otherwise, the judgment matrix needs to be adjusted until it passes the consistency check. The weight of the criterion layer is calculated according to the formula, which is to calculate the weight of each indicator in the indicator layer in turn. In the formula, ω is the quasi-layer weight, μ is the eigenvector corresponding to the maximum eigenvalue, and 10 experts are asked to score the criterion layer and the indicator layer respectively, and the scoring weight of each expert is calculated, and the sum and average are taken to obtain the weight of each indicator.

4. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The process of calculating the objective weight by the entropy weight method includes: firstly, conducting a questionnaire survey, inviting a number of water conservancy experts, and providing relevant project background information, conducting indicator research, and evaluating and scoring according to the actual situation of the water supply project, combined with the established indicator system, and the actual situation achieved by each indicator. The scoring results of the above experts are used to calculate the objective weights of the comprehensive benefit evaluation indicators according to the entropy weight method. The specific calculation process is as follows: (1) Normalize the evaluation index according to the formula; Positive indicators: Negative indicators: In the formula, γ is the original value of the evaluation index; (2) Calculate the proportion p of the i-th sample value under the j-th indicator ij : (3) Calculate the entropy value e of the jth indicator j : (i=1,2,...,n;j=1,2,...,m;where k=1 / ln(n)>0, and e j ≥0), when p ij = 0, let ln(P ij )=0); (4) Calculate the information entropy redundancy d j : d j =1-e j ,(j=1,2,…,m); (5) Calculate the weight w of the indicator j : (6) Calculate the final comprehensive score value s j :

5. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The determination of the membership degree comprises the following steps: Normalize the experts’ scoring results. In the formula, Q ij is the normalized value of the score given by the i-th expert to the j-th indicator; Calculate the KL divergence between the i-th expert and the j-th expert, Where Qi and Qj are the normalized score vectors of the i-th expert and the j-th expert, DKL(Qi||Qj) is the KL divergence of the scores of the i-th expert and the j-th expert, and log represents the logarithmic function with base 2; Calculate the JS divergence between the i-th expert and the j-th expert: Further calculation of expert weight W i : And calculate the comprehensive score of the indicator and the degree of membership of the indicator to each level respectively Where wi is the weight of the i-th expert, and sj is the final score of the j-th indicator.

6. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The multi-level fuzzy comprehensive evaluation in S4 includes: (1) Determine the factor set and evaluation set of evaluation indicators; (2) Determine the weight vector of evaluation factors; (3) First-level fuzzy comprehensive evaluation In the formula, o is the weighted average operator; (4) Secondary fuzzy comprehensive evaluation Based on the first-level fuzzy comprehensive evaluation results, the first-level fuzzy calculation is performed B=W*(B1,B2,…,B k ) T =(w1,w2,…,w k )*(B1,B2,…,B k ) T 。 7. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 1 is characterized in that: The membership cloud model includes: determining the evaluation standard cloud, determining the evaluation index cloud and evaluating the final result, wherein the golden ratio is used according to the comment set and interval value obtained from the consulting experts, and the standard cloud digital feature calculation formula is brought into play to obtain the expected Ex, entropy En and super entropy He of the standard cloud; the above-mentioned standard cloud and evaluation cloud are placed in the same coordinate system, and the specific evaluation results of the project are determined according to the position distribution of the two and the principle of maximum similarity, and the economic benefit, social benefit, economic benefit and comprehensive benefit evaluation cloud maps are generated respectively, and the similarity of each evaluation result is calculated.

8. The comprehensive benefit evaluation method for water supply projects in arid areas according to claim 7 is characterized in that: Matlab software was used to obtain the result evaluation.

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