Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China
Abstract
:1. Introduction
2. Materials and Methodology
2.1. Study Area
2.2. Methodology
2.2.1. Fuzzy Comprehensive Assessment Method
- (1)
- Defining the factor set, i.e., U = {u1, u2, …, ui, …, um}, which is a set consisting of m kinds of evaluation factors, and ui is the ith evaluation factor.
- (2)
- Establishing the evaluation set V = {v1, v2, …, vj, …, vn}, which is a discrete set made up of n levels of evaluation results, and vj is the jth evaluation result.
- (3)
- Building the original matrix X,
- (4)
- Determining the weight matrix A = {a1, a2, …, am}, which is a set composed of m kinds of index weights which indicate the importance of various evaluation indexes.
- (5)
- Constructing the single factor evaluation matrix Q by membership function, where Q is a fuzzy relationship matrix that consists of the membership degrees of ui to vj. The matrix is:
- (6)
- Obtaining the comprehensive evaluation set B, which is a set made up of n kinds of evaluation results by fuzzy operating of the single factor evaluation matrix and weight matrix.
2.2.2. Improved Fuzzy Comprehensive Assessment Method
- (1)
- Standardizing the indexes and building the standardization matrix Y = (yij)m × yr (m is the number of indexes, yr is the year for evaluation), which will be explained specifically in Section 2.2.3. Then, the proportion of each index (pik) is determined as follows:
- (2)
- Calculating the information entropy (ei) by
- (3)
- Obtaining the weights of indexes by
2.2.3. Standardization
- (1)
- Building the original matrix X
- (2)
- For a benefit index, the standardized xik, i.e., yik is calculated as
- (3)
- As for a cost index, the standardization equation is
3. Results and Discussion
3.1. Water Environmental Safety Evaluation Index System
3.2. Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area
3.2.1. Construction of Factor Set U and Evaluation Set V
3.2.2. Weight Determination
3.2.3. Comprehensive Evaluation
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Galaitsi, S.E.; Russell, R.; Bishara, A.; Durant, J.L.; Bogle, J.; Huber-Lee, A. Intermittent domestic water supply: A critical review and analysis of causal-consequential pathways. Water 2016, 8, 274–298. [Google Scholar] [CrossRef]
- Afonso, M.J.; Freitas, L.; Pereira, A.; Neves, L.; Guimarães, L.; Guilhermino, L.; Mayer, B.; Rocha, F.; Marques, J.M.; Chaminé, H.I. Environmental groundwater vulnerability assessment in urban water mines (Porto, NW Portugal). Water 2016, 8, 499–521. [Google Scholar] [CrossRef]
- Rouillard, J.; Vidaurre, R.; Brouwer, S.; Damman, S.; Ponce, A.A.; Gerner, N.V.; Riegels, N.; Termes, M. Governance regime factors conducive to innovation uptake in urban water management: Experiences from Europe. Water 2016, 8, 477–491. [Google Scholar] [CrossRef]
- Leong, C. The role of emotions in drinking recycled water. Water 2016, 8, 548–565. [Google Scholar] [CrossRef]
- Skeriotis, A.T.; Sanchez, N.P.; Kennedy, M.; Johnstone, D.W.; Miller, C.M. Long-Term comparison of disinfection by-product formation potential in a full scale treatment plant utilizing a multi-coagulant drinking water treatment scheme. Water 2016, 8, 318–335. [Google Scholar] [CrossRef]
- Wang, M.; Lu, B.; Wang, J.; Zhang, H.; Guo, L.; Lin, H. Using dual isotopes and a bayesian isotope mixing model to evaluate nitrate sources of surface water in a drinking water source watershed, East China. Water 2016, 8, 355–370. [Google Scholar] [CrossRef]
- Mavragani, A.; Sypsa, K.; Sampri, A.; Tsagarakis, K.P. Quantifying the UK online interest in substances of the EU watchlist for water monitoring: Diclofenac, estradiol, and the macrolide antibiotics. Water 2016, 8, 542–562. [Google Scholar] [CrossRef]
- Fassnacht, F.E.; Latifi, H.; Stereńczak, K.; Modzelewska, A.; Lefsky, M.; Waser, L.T.; Straub, C.; Ghosh, A. Review of studies on tree species classification from remotely sensed data. Remote Sens. Environ. 2016, 186, 64–87. [Google Scholar] [CrossRef]
- Kim, S.E.; Seo, I.W. Artificial neural network ensemble modeling with conjunctive data clustering for water quality prediction in rivers. J. Hydro-Environ. Res. 2015, 9, 325–339. [Google Scholar] [CrossRef]
- Csábrági, A.; Molnár, S.; Tanos, P.; Kovács, J. Application of artificial neural networks to the forecasting of dissolved oxygen content in the Hungarian section of the river Danube. Ecol. Eng. 2017, 100, 63–72. [Google Scholar] [CrossRef]
- Yeh, Y.L.; Chen, T.C. Application of grey correlation analysis for evaluating the artificial lake site in Pingtung Plain, Taiwan. Can. J. Civ. Eng. 2011, 31, 56–64. [Google Scholar] [CrossRef]
- Chen, Y.; Xu, S.; Jin, Y. Evaluation on ecological restoration capability of revetment in inland restricted channel. KSCE J. Civ. Eng. 2016, 20, 2548–2558. [Google Scholar] [CrossRef]
- Xia, X.; Sun, Y.; Wu, K.; Jiang, Q. Optimization of a straw ring-die briquetting process combined analytic hierarchy process and grey correlation analysis method. Fuel Process. Technol. 2016, 152, 303–309. [Google Scholar] [CrossRef]
- Zhou, Z.; Zhang, X.; Dong, W. Fuzzy comprehensive evaluation for safety guarantee system of reclaimed water quality. Procedia Environ. Sci. 2013, 18, 227–235. [Google Scholar] [CrossRef]
- Jiao, J.; Ren, H.; Sun, S. Assessment of surface ship environment adaptability in seaways: A fuzzy comprehensive evaluation method. Int. J. Nav. Archit. Ocean Eng. 2016, 8, 344–359. [Google Scholar] [CrossRef]
- Wang, Y.; Yang, W.; Li, M.; Liu, X. Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation. Int. J. Rock Mech. Min. Sci. 2012, 52, 50–55. [Google Scholar] [CrossRef]
- He, Y.X.; Dai, A.Y.; Zhu, J.; He, H.Y.; Li, F.R. Risk assessment of urban network planning in china based on the matter-element model and extension analysis. Int. J. Electr. Power Energy Syst. 2011, 33, 775–782. [Google Scholar] [CrossRef]
- Li, H.; Lv, M.; Ye, S. The research and practice of water quality safety evaluation for Jinan urban water supply system. Procedia Environ. Sci. 2011, 11, 1197–1203. [Google Scholar]
- Zhao, C.R.; Zhao, W.M. Application of fuzzy comprehensive evaluation to urban eco-security assessment. Environ. Sci. Technol. 2010, 33, 179–183. [Google Scholar]
- Shabbir, R.; Ahmad, S.S. Water resource vulnerability assessment in Rawalpindi and Islamabad, Pakistan using analytic hierarchy process (AHP). J. King Saud Univ. Sci. 2015, 28, 293–299. [Google Scholar] [CrossRef]
- Sutadian, A.D.; Muttil, N.; Yilmaz, A.G.; Perera, B.J.C. Using the analytic hierarchy process to identify parameter weights for developing a water quality index. Ecol. Indic. 2017, 75, 220–233. [Google Scholar] [CrossRef]
- Hamilton, D.; Parparov, A. Comparative assessment of water quality with the trophic level index and the Delphi method in Lakes Rotoiti and Rotorua, New Zealand. Water Qual. Res. J. Can. 2010, 45, 479–489. [Google Scholar]
- Peiris, R.H.; Hallé, C.; Budman, H.; Moresoli, C.; Peladszus, S.; Huck, P.M.; Legge, R.L. Identifying fouling events in a membrane-based drinking water treatment process using principal component analysis of fluorescence excitation-emission matrices. Water Res. 2010, 44, 185–194. [Google Scholar] [CrossRef] [PubMed]
- Ma, L.; Liu, Y.; Zhou, X.P. Fuzzy comprehensive evaluation method of F statistics weighting in identifying mine water inrush source. Int. J. Eng. Sci. Technol. 2010, 2, 123–128. [Google Scholar] [CrossRef]
- He, Q.; Peng, S.; Zhai, J.; Xiao, H. Development and application of a water pollution emergency response system for the Three Gorges Reservoir in the Yangtze River, China. J. Environ. Sci. 2011, 23, 595–600. [Google Scholar] [CrossRef]
- Environmental Quality Standards for Surface Water; Ministry of Environmental Protection of the People’s Republic of China: Beijing, China, 2002.
- Jiang, F.; Zheng, Q.; Shi, W. The applied research of fuzzy comprehensive evaluation on talent training mode of safety engineering. Procedia Eng. 2012, 43, 425–430. [Google Scholar] [CrossRef]
- Chen, X.X.; Qiu, J.; Liu, G.J. Research on the method of test-equipment selection based on analytic hierarchy process and fuzzy comprehensive assessment. Acta Armamentarii 2010, 31, 4045–4048. [Google Scholar]
- Fan, Z.; Song, C.X.; Li, M.J.; He, Y.L.; Tao, W.Q. Study on energy efficiency evaluation index system for fossil-fuel power plant. Energy Procedia 2014, 61, 1093–1098. [Google Scholar]
- Zhang, W.; Lu, J.; Zhang, Y. Comprehensive evaluation index system of low carbon road transport based on fuzzy evaluation method. Procedia Eng. 2016, 137, 659–668. [Google Scholar] [CrossRef]
- Zhu, Y.; Hipel, K.W.; Ke, G.Y.; Chen, Y. Establishment and optimization of an evaluation index system for brownfield redevelopment projects. Environ. Model. Softw. 2015, 74, 173–182. [Google Scholar] [CrossRef]
- Water Resources Communique of Chongqing. Available online: http://www.cqwater.gov.cn/slsj/szygb/Pages/Default.aspx (accessed on 13 January 2016).
- Chongqing Statistical Bureau. Chongqing Statistical Yearbook 2011–2015; China Statistical Press: Beijing, China, 2011–2015. [Google Scholar]
- Chongqing Environmental Bulletin. Available online: http://www.cepb.gov.cn/xxgk/hjzl/hjzkgb/index.shtml (accessed on 3 June 2016).
- Environmental Brief Report of Chongqing. Available online: http://www.cqemc.cn/download/zxjj/list.jsp?type=xxgk&type_id=169595633711000010 (accessed on 28 July 2016).
- Peng, J.Q.; Li, L.; Cao, W.; Gao, Y. Evaluation for Water Environment Security of Urban Lakes. Environ. Prot. Sci. 2010, 36, 62–64. (In Chinese) [Google Scholar]
Destination Layer | Criterion Layer | Index Layer | Subindex Layer |
---|---|---|---|
Water environmental safety of the Heshangshan drinking water sources area | Pressure (P) | Water resources P1 | Per capita water resources D1; |
Per capita domestic water consumption D2; | |||
Annual irrigation water consumption per hectare D3 | |||
Pollution source and its discharge P2 | COD discharge amount D4; | ||
Ammonia nitrogen discharge amount D5; | |||
The number of industrial enterprises beyond designed scale D6 | |||
State (S) | Social economy S1 | Natural population growth rate D7; | |
Population density D8; | |||
Per capita GDP D9 | |||
Water quantity S2 | Daily water supply amount of a project D10; | ||
Annual rainfall D11; | |||
Water consumption per 10,000 yuan of value-added by industry D12 | |||
Water quality S3 | Standard-meeting rate of drinking water for drinking water source area D13; | ||
Wastewater discharge of per unit GDP D14; | |||
Ratio of wastewater and runoff D15; | |||
Eutrophication section percentage of influents in Three Gorges reservoir area D16 | |||
Response (R) | Environmental protection R1 | Wastewater treatment rate of sewage plant D17; | |
Vegetation cover rate D18; | |||
Governance rate of soil and water loss D19 | |||
Industrial structure R2 | Investment rate of environmental protection D20; | ||
Proportion of tertiary industry D21 |
Subindex | Unit | 2010 | 2011 | 2012 | 2013 | 2014 | Type |
---|---|---|---|---|---|---|---|
D1 | M3/person | 1405.50 | 1545.37 | 1425.07 | 1412.39 | 1903.82 | ↑ |
D2 | M3/person | 47.51 | 49.45 | 50.72 | 52.63 | 48.18 | ↓ |
D3 | M3 | 251.00 | 291.00 | 287.00 | 270.00 | 307.00 | ↓ |
D4 | mg/L | 183.04 | 435.53 | 304.23 | 274.95 | 265.02 | ↓ |
D5 | mg/L | 19.51 | 57.47 | 40.33 | 36.63 | 35.19 | ↓ |
D6 | _ | 896.00 | 527.00 | 575.00 | 650.00 | 734.00 | ↓ |
D7 | % | 7.25 | 6.54 | 3.88 | 4.64 | 5.10 | ↓ |
D8 | person/km2 | 400.89 | 404.09 | 406.11 | 407.57 | 409.60 | ↓ |
D9 | 104 yuan | 2.76 | 3.45 | 3.89 | 4.32 | 4.79 | ↑ |
D10 | 104 m3 | 652.66 | 815.42 | 833.24 | 813.34 | 833.34 | ↑ |
D11 | 108 m3 | 872.07 | 899.67 | 890.45 | 876.43 | 1046.52 | ↑ |
D12 | M3 | 128.00 | 92.00 | 76.00 | 77.00 | 71.00 | ↓ |
D13 | % | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | ↑ |
D14 | M3/104 yuan | 16.16 | 9.56 | 11.60 | 11.15 | 10.22 | ↓ |
D15 | % | 2.76 | 1.86 | 2.78 | 3.00 | 2.27 | ↓ |
D16 | % | 42.20 | 38.90 | 25.00 | 36.10 | 44.40 | ↓ |
D17 | % | 88.86 | 92.21 | 89.77 | 93.20 | 92.25 | ↑ |
D18 | % | 6.05 | 8.45 | 5.34 | 4.87 | 5.21 | ↑ |
D19 | % | 37.00 | 39.00 | 42.10 | 42.10 | 43.10 | ↑ |
D20 | % | 2.93 | 2.72 | 2.10 | 2.02 | 2.06 | ↑ |
D21 | % | 36.40 | 36.20 | 39.40 | 46.70 | 46.80 | ↑ |
Subindexes | Units | Excellent | Good | Substantially Good | Poor | Very Poor |
---|---|---|---|---|---|---|
D1 | M3/person | [3000,∞) | [2000,3000) | [1000,2000) | [500,1000) | (0,500) |
D2 | m3/person | [0,30] | (30,45] | (45,55] | (55,80] | (80,∞) |
D3 | m3 | [0,200] | (200,300] | (300,360] | (380,500] | (500,∞) |
D4 | mg/L | [0,100] | (100,300] | (300,700] | (700,1000] | (1000,∞) |
D5 | mg/L | [0,15] | (15,30] | (30,60] | (60,100] | (100,∞) |
D6 | _ | [0,400] | (400,800] | (800,1400] | (1400,2000] | (2000,∞) |
D7 | % | [0,0.7] | (0.7,1.2] | (1.2,3.5] | (3.5,5] | (5,∞) |
D8 | person/km2 | [0,300] | (300,400] | (400,500] | (500,2000] | (2000,∞) |
D9 | 104 yuan | [5,15) | [3,5) | [1.5,3) | [1,1.5) | (0.5,1) |
D10 | 104 m3 | [1200,∞) | [900,1200) | [600,900) | [300,600) | (0,300) |
D11 | 108 m3 | [1100,∞) | [800,1100) | [650,800) | [400,650) | (0,400) |
D12 | m3 | [0,20] | (20,40] | (40,65] | (65,130] | (130,∞) |
D13 | % | [98,100) | [96,98) | [90,96) | [70,90) | (0,70) |
D14 | m3/104 yuan | [0,20] | (20,50] | (50.100] | (100,150] | (150,∞) |
D15 | % | [0,3] | (3,5.5] | (5.5,7.7] | (7.7,10] | (10,100) |
D16 | % | [0,5] | (5,10] | (10,15] | (15,45] | (45,∞) |
D17 | % | [98,100) | [90,98) | [80,90) | [70,80) | (0,70) |
D18 | % | [90,100) | [50,90) | [10,50) | [4,10) | (4,0) |
D19 | % | (50,100) | [35,50) | [20,35) | [10,20) | [0,10) |
D20 | % | [2.2,100) | [1.7,2.2) | [1.2,1.7) | [0.7,1.2) | (0,0.7) |
D21 | % | [70,100) | [50,70) | [30,50) | [20,30) | (0,20) |
Destination Layer | Criterion Layer | Index Layer | Subindex Layer | Weight |
---|---|---|---|---|
A 1.000 | P 0.278 | P1 0.182 | D1 | 0.111 |
D2 | 0.029 | |||
D3 | 0.041 | |||
P2 0.096 | D4 | 0.031 | ||
D5 | 0.033 | |||
D6 | 0.032 | |||
S 0.420 | S1 0.119 | D7 | 0.041 | |
D8 | 0.043 | |||
D9 | 0.036 | |||
S2 0.162 | D10 | 0.027 | ||
D11 | 0.106 | |||
D12 | 0.029 | |||
S3 0.139 | D13 | 0.000 | ||
D14 | 0.028 | |||
D15 | 0.053 | |||
D16 | 0.058 | |||
R 0.302 | R1 0.150 | D17 | 0.040 | |
D18 | 0.075 | |||
D19 | 0.035 | |||
R2 0.152 | D20 | 0.082 | ||
D21 | 0.070 |
Subindexes | Evaluation Set | ||||
---|---|---|---|---|---|
v1 | v2 | v3 | v4 | v5 | |
Levels of Water Environmental Safety | |||||
I | II | III | IV | V | |
D1 | 0.000 | 0.372 | 0.412 | 0.216 | 0.000 |
D2 | 0.047 | 0.518 | 0.434 | 0.000 | 0.000 |
D3 | 0.136 | 0.475 | 0.389 | 0.000 | 0.000 |
D4 | 0.221 | 0.490 | 0.289 | 0.000 | 0.000 |
D5 | 0.275 | 0.464 | 0.261 | 0.000 | 0.000 |
D6 | 0.090 | 0.546 | 0.364 | 0.000 | 0.000 |
D7 | 0.000 | 0.000 | 0.000 | 0.063 | 0.937 |
D8 | 0.000 | 0.032 | 0.532 | 0.436 | 0.000 |
D9 | 0.378 | 0.423 | 0.199 | 0.000 | 0.000 |
D10 | 0.190 | 0.429 | 0.381 | 0.000 | 0.000 |
D11 | 0.327 | 0.398 | 0.276 | 0.000 | 0.000 |
D12 | 0.000 | 0.000 | 0.370 | 0.407 | 0.222 |
D13 | 0.505 | 0.495 | 0.000 | 0.000 | 0.000 |
D14 | 0.662 | 0.338 | 0.000 | 0.000 | 0.000 |
D15 | 0.569 | 0.431 | 0.000 | 0.000 | 0.000 |
D16 | 0.000 | 0.000 | 0.015 | 0.496 | 0.489 |
D17 | 0.126 | 0.448 | 0.426 | 0.000 | 0.000 |
D18 | 0.000 | 0.000 | 0.103 | 0.508 | 0.390 |
D19 | 0.248 | 0.459 | 0.293 | 0.000 | 0.000 |
D20 | 0.000 | 0.057 | 0.478 | 0.464 | 0.000 |
D21 | 0.000 | 0.339 | 0.403 | 0.258 | 0.000 |
Layer | Evaluation set | |||||
---|---|---|---|---|---|---|
v1 | v2 | v3 | v4 | v5 | ||
Levels of Water Environmental Safety | ||||||
I | II | III | IV | V | ||
Index layer | P1 | 0.036 | 0.429 | 0.425 | 0.110 | 0.000 |
P2 | 0.201 | 0.498 | 0.302 | 0.000 | 0.000 | |
S1 | 0.170 | 0.204 | 0.318 | 0.089 | 0.218 | |
S2 | 0.248 | 0.333 | 0.309 | 0.072 | 0.039 | |
S3 | 0.321 | 0.215 | 0.007 | 0.230 | 0.227 | |
R1 | 0.097 | 0.240 | 0.241 | 0.239 | 0.183 | |
R2 | 0.000 | 0.216 | 0.478 | 0.305 | 0.000 | |
Criterion layer | P | 0.093 | 0.453 | 0.382 | 0.072 | 0.000 |
S | 0.250 | 0.257 | 0.212 | 0.129 | 0.152 | |
R | 0.048 | 0.228 | 0.361 | 0.272 | 0.091 |
Indicator | Level | ||||
---|---|---|---|---|---|
Water environmental safety level | I | II | III | IV | V |
Evaluation set V | v1 | v2 | v3 | v4 | v5 |
Membership degree of destination layer | 0.145 | 0.303 | 0.304 | 0.156 | 0.092 |
Evaluation result of water environmental safety level | — | — | √ | — | — |
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Ding, X.; Chong, X.; Bao, Z.; Xue, Y.; Zhang, S. Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China. Water 2017, 9, 329. https://doi.org/10.3390/w9050329
Ding X, Chong X, Bao Z, Xue Y, Zhang S. Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China. Water. 2017; 9(5):329. https://doi.org/10.3390/w9050329
Chicago/Turabian StyleDing, Xiaowen, Xiao Chong, Zhengfeng Bao, Ying Xue, and Shanghong Zhang. 2017. "Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China" Water 9, no. 5: 329. https://doi.org/10.3390/w9050329
APA StyleDing, X., Chong, X., Bao, Z., Xue, Y., & Zhang, S. (2017). Fuzzy Comprehensive Assessment Method Based on the Entropy Weight Method and Its Application in the Water Environmental Safety Evaluation of the Heshangshan Drinking Water Source Area, Three Gorges Reservoir Area, China. Water, 9(5), 329. https://doi.org/10.3390/w9050329