Adv Search
Volume 27 Issue 1
. 
Turn off MathJax
Article Contents
Article Navigation >  Chinese Geographical Science  > 2017  >  27(1): 39-51

LI Bing, YANG Guishan, WAN Rongrong, ZHANG Lu, ZHANG Yanhui, DAI Xue. Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China[J]. Chinese Geographical Science, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
Citation: LI Bing, YANG Guishan, WAN Rongrong, ZHANG Lu, ZHANG Yanhui, DAI Xue. Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China[J]. Chinese Geographical Science, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
shu

Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China

doi: 10.1007/s11769-017-0845-2
  • 1.

    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China

Funds:  Under the auspices of National Basic Research Program of China (No. 2012CB417006), National Natural Science Foundation of China (No. 41271500, 41571107, 41601041)
More Information
  • Corresponding author: YANG Guishan.E-mail:gsyang@niglas.ac.cn
  • Received Date: 2016-06-02
  • Rev Recd Date: 2016-09-29
  • Publish Date: 2017-02-27
  • Achieving water purity in Poyang Lake has become a major concern in recent years, thus appropriate evaluation of spatial and temporal water quality variations has become essential. Variations in 11 water quality parameters from 15 sampling sites in Poyang Lake were investigated from 2009 to 2012. An integrative fuzzy variable evaluation (IFVE) model based on fuzzy theory and variable weights was developed to measure variations in water quality. Results showed that:1) only chlorophyll-a concentration and Secchi depth differed significantly among the 15 sampling sites (P<0.01), whereas the 11 water quality parameters under investigation differed significantly throughout the seasons (P<0.01). The annual variations of all water quality variables except for temperature, electrical conductivity, suspended solids and total phosphorus were considerable (P<0.05). 2) The IFVE model was reasonable and flexible in evaluating water quality status and any possible ‘bucket effect’. The model fully considered the influences of extremely poor indices on overall water quality. 3) A spatial analysis indicated that anthropogenic activities (particularly industrial sewage and dredging) and lake bed topography might directly affect water quality in Poyang Lake. Meanwhile, hydrological status and sewage discharged into the lake might be responsible for seasonal water quality variations.
  • [1] Alberto W D, Mar?a del P D A, Mar?a V A et al., 2001. Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study:Suqu?a River Basin (Córdoba-Argentina). Water Research, 35(12):2881-2894. doi: 10.1016/S0043-1354(00)00592-3
    [2] Ban X, Wu Q Z, Pan B Z et al., 2014. Application of Composite Water Quality Identification Index on the water quality evaluation in spatial and temporal variations:a case study in Honghu Lake, China. Environmental Monitoring and Assess-ment, 186:4237-4247. doi: 10.1007/s10661-014-3694-9
    [3] Beamonte C E, Bermúdez J D, Casino A et al., 2005. A global stochastic index for water quality:the case of the river Turia in Spain. Journal of Agricultural, Biological, and Environmental Statistics, 10(4):424-439.
    [4] Beamonte C E, Casino M A, Veres F E, 2010. Water quality indicators:Comparison of a probabilistic index and a general quality index. The case of the Confederación Hidrográfica del Júcar (Spain). Ecological Indicators, 10(5):1049-1054. doi: 10.1016/j.ecolind.2010.01.013
    [5] Beyhan M, Kaç?koç M, 2014. Evaluation of water quality from the perspective of eutrophication in Lake E?irdir, Turkey. Water, Air, & Soil Pollution, 225(7):1-13. doi:10.1007/s 11270-014-1994-x.
    [6] Chang N B, Chen H W, Ning S K, 2001. Identification of river water quality using the fuzzy synthetic evaluation approach. Journal of Environmental Management, 63(3):293-305. doi: 10.1006/jema.2001.0483.
    [7] Chinese Environmental Protection Agency, 2002. National Surface Water Environmental Quality Standards of China (GB3838-2002). Beijing:China Standards Press. (in Chinese)
    [8] Dahiya S, Singh B, Gaur S et al., 2007. Analysis of groundwater quality using fuzzy synthetic evaluation. Journal of Hazardous Materials, 147(3):938-946. doi:10.1016/j.jhazmat.2007.01. 119
    [9] Debels P, Figueroa R, Urrutia R et al., 2005. Evaluation of water quality in the Chillán River (Central Chile) using physicochemical parameters and a modified water quality index. Environmental Monitoring and Assessment, 110(1-3):301-322. doi: 10.1007/s10661-005-8064-1
    [10] Duan W, He B, Nover D et al., 2016. Water quality assessment and pollution source identification of the Eastern Poyang Lake basin using multivariate statistical methods. Sustainability, 8(2):133. doi: 10.3390/su8020133
    [11] Hu K M, Pang Y, Wang H et al., 2011. Simulation study on water quality based on sediment release flume experiment in Lake Taihu, China. Ecological Engineering, 37(4):607-615. doi: 10.1016/j.ecoleng.2010.12.022
    [12] Ip W C, Hu B Q, Wong H et al., 2007. Applications of rough set theory to river environment quality evaluation in China. Water Resources, 34(4):459-470. doi: 10.1134/S0097807807040112
    [13] Karmakar S, Mujumdar P, 2006. Grey fuzzy optimization model for water quality management of a river system. Advances in Water Resources, 29(7):1088-1105. doi:10.1016/j.advwatres. 2006.04.003
    [14] Li B, Yang G S, Wan R R et al., 2016. Spatiotemporal variability in the water quality of Poyang Lake and its associated responses to hydrological conditions. Water, 8(7):296. doi: 10.3390/w8070296
    [15] Li Chunhao, Sun Yonghe, Jia Yanhui et al., 2010. Analytic hierarchy process based on variable weights. Systems Engineering-Theory & Practice, 30(4):723-731. (in Chinese)
    [16] Li D Q, Huang D, Guo C F et al., 2015. Multivariate statistical analysis of temporal-spatial variations in water quality of a constructed wetland purification system in a typical park in Beijing, China. Environmental Monitoring and Assessment, 187(1):1-14. doi: 10.1007/s10661-014-4219-2
    [17] Li H X, Li L X, Wang J Y et al., 2004. Fuzzy decision making based on variable weights. Mathematical and Computer Modelling, 39(2):163-179. doi: 10.1016/S0895-7177(04)00007-X
    [18] Liang, J Y, Shi, Z Z, 2004. The information entropy, rough entropy and knowledge granulation in rough set theory. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 12(01):37-46. doi: 10.1142/S0218488504002631
    [19] Liu L, Zhou J Z, An X L et al., 2010. Using fuzzy theory and information entropy for water quality assessment in Three Gorges region, China. Expert Systems with Applications, 37(3):2517-2521. doi: 10.1016/j.eswa.2009.08.004
    [20] Liu S G, Lou S, Kuang C P et al., 2011. Water quality assessment by pollution-index method in the coastal waters of Hebei Province in western Bohai Sea, China. Marine Pollution Bulletin, 62(10):2220-2229. doi:10.1016/j.marpolbul.2011. 06.021
    [21] Norman E S, Dunn G, Bakker K et al., 2013. Water security assessment:integrating governance and freshwater indicators. Water Resources Management, 27(2):535-551. doi:10.1007/s 11269-012-0200-4
    [22] Ouyang Y, Nkedi-Kizza P, Wu, Q T et al., 2006. Assessment of seasonal variations in surface water quality. Water Research, 40(20):3800-3810. doi: 10.1016/j.watres.2006.08.030
    [23] Palma P, Alvarenga P, Palma V L et al., 2010. Assessment of anthropogenic sources of water pollution using multivariate statistical techniques:a case study of the Alqueva's reservoir, Portugal. Environmental Monitoring and Assessment, 165(1-4):539-552. doi: 10.1007/s10661-009-0965-y
    [24] Qadir A, Malik R N, Husain S Z, 2008. Spatio-temporal variations in water quality of Nullah Aik-tributary of the river Chenab, Pakistan. Environmental Monitoring and Assessment, 140(1-3):43-59. doi: 10.1007/s10661-007-9846-4
    [25] Shankman D, Keim B D, Song J, 2006. Flood frequency in China's Poyang Lake region:trends and teleconnections. International Journal of Climatology, 26(9):1255-1266. Doi: 10.1002/joc.1307
    [26] Shrestha S, Kazama F, 2007. Assessment of surface water quality using multivariate statistical techniques:a case study of the Fuji river basin, Japan. Environmental Modelling & Software, 22(4):464-475. doi: 10.1016/j.envsoft.2006.02.001
    [27] Shu Bangrong, Huang Qi, Liu Youzhao et al., 2012. Spatial fuzzy assessment of ecological suitability for urban land expansion based on variable weights:a case study of Taicang. Journal of Natural Resources, 27(3):402-412. (in Chinese)
    [28] Simeonov V, Stratis, J A, Samara C et al., 2003. Assessment of the surface water quality in Northern Greece. Water Research, 37(17):4119-4124. doi: 10.1016/S0043-1354(03)00398-1
    [29] Sondergaard M, Jensen P J, Jeppesen E, 2001. Retention and internal loading of phosphorus in shallow, eutrophic lakes. The Scientific World Journal, 1:427-442. doi:10.1100/tsw.2001. 72
    [30] Vörösmarty C J, McIntyre P, Gessner M O et al., 2010. Global threats to human water security and river biodiversity. Nature, 467(7315):555-561. doi: 10.1038/nature09440
    [31] Wang Peizhuang,1983. Fuzzy Set Theory and its Application. Shanghai:Shanghai Sceience Press. (in Chinese)
    [32] Wu L H, Li M, Guo Y Y et al., 2011. Influence of Three Gorges Project on water quality of Poyang Lake. Procedia Environ-mental Sciences, 10:1496-1501. doi:10.1016/j.proenv.2011. 09.238
    [33] Xia Yu, Yan Bangyou, Fang Yu, 2015. Nutrient loading and its controlling factors in Le'an River watershed, Lake Poyang basin. Journal of Lake Sciences, 27(2):282-288. (in Chinese)
    [34] Xu Caiping, Li Shouchun, Chai Wenbo et al., 2012. A newly recorded cyanobacterial species in water blooms occurred in Lake Poyang-Merismopedia convoluta Breb. Kützing. Journal of Lake Sciences, 24(4):643-646. (in Chinese)
    [35] Yan B Y, Xing J S, Tan H R et al., 2011. Analysis on waterater environment capacityof the Poyang Lake. 2011 3rd International Conference on Environmental Science and Information Application Technology ESIAT10, (part C):2754-2759. doi: 10.1016/j.proenv.2011.09.427
    [36] Yan X F, Qiu Z M, Wang J L et al., 2012. Spatial and temporal change of land use and its impact on water quality of Poyang Lake region. Advanced Materials Research, 599:753-756. doi: 10.4028/www.scientific.net/AMR.599.753
    [37] Yin Zongxian, Zhang Juncai, 1987. The hydrological features of Poyang lake (I). Oceanologia Et Limnologia Sinica, 18(1):22-27. (in Chinese)
    [38] Zadeh L A, 1965. Fuzzy sets. Information and Control, 8(3):338-353. doi: 10.1016/S0019-9958(65)90241-X
    [39] Zhang C, Dong S H, 2009. A new water quality assessment model based on projection pursuit technique. Journal of Environ-mental Sciences, 21(S1):S154-S157. doi: 10.1016/S1001-0742(09)60062-0
    [40] Zhu Xinhua, Dong Zengchuan, Zhao Jie et al., 2009. Influence of Three Gorges Project on water quality of Poyang Lake. Yellow River, 31(1):57-58. (in Chinese)
    [41] Zou Z H, Yun Y, Sun J N, 2006. Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental Sciences, 18(5):1020-1023. doi:10.1016/S1001-0742 (06)60032-6
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article Metrics

Article views(366) PDF downloads(691) Cited by()

Proportional views
Related

Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China

doi: 10.1007/s11769-017-0845-2
  • 1. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China
Funds:  Under the auspices of National Basic Research Program of China (No. 2012CB417006), National Natural Science Foundation of China (No. 41271500, 41571107, 41601041)
    Corresponding author: YANG Guishan.E-mail:gsyang@niglas.ac.cn
  • Received Date: 2016-06-02
  • Rev Recd Date: 2016-09-29
  • Publish Date: 2017-02-27

Abstract: Achieving water purity in Poyang Lake has become a major concern in recent years, thus appropriate evaluation of spatial and temporal water quality variations has become essential. Variations in 11 water quality parameters from 15 sampling sites in Poyang Lake were investigated from 2009 to 2012. An integrative fuzzy variable evaluation (IFVE) model based on fuzzy theory and variable weights was developed to measure variations in water quality. Results showed that:1) only chlorophyll-a concentration and Secchi depth differed significantly among the 15 sampling sites (P<0.01), whereas the 11 water quality parameters under investigation differed significantly throughout the seasons (P<0.01). The annual variations of all water quality variables except for temperature, electrical conductivity, suspended solids and total phosphorus were considerable (P<0.05). 2) The IFVE model was reasonable and flexible in evaluating water quality status and any possible ‘bucket effect’. The model fully considered the influences of extremely poor indices on overall water quality. 3) A spatial analysis indicated that anthropogenic activities (particularly industrial sewage and dredging) and lake bed topography might directly affect water quality in Poyang Lake. Meanwhile, hydrological status and sewage discharged into the lake might be responsible for seasonal water quality variations.

LI Bing, YANG Guishan, WAN Rongrong, ZHANG Lu, ZHANG Yanhui, DAI Xue. Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China[J]. Chinese Geographical Science, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
Citation: LI Bing, YANG Guishan, WAN Rongrong, ZHANG Lu, ZHANG Yanhui, DAI Xue. Using Fuzzy Theory and Variable Weights for Water Quality Evaluation in Poyang Lake, China[J]. Chinese Geographical Science, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
shu

    HTML

Reference (41)

Catalog

    Copyright © Editorial office of Chinese Geographical Science

    Tel: +86-0431-85542219   Email: egeoscien@neigae.ac.cn  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return