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

LI Bing,  YANG Guishan,  WAN Rongrong,  ZHANG Lu,  ZHANG Yanhui,  DAI Xue

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文章导航 > 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]. 中国地理科学, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
引用本文: 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]. 中国地理科学, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
shu
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

基金项目: Under the auspices of National Basic Research Program of China (No. 2012CB417006), National Natural Science Foundation of China (No. 41271500, 41571107, 41601041)
详细信息
    通讯作者:

    YANG Guishan.E-mail:gsyang@niglas.ac.cn

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

  • 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

  • 摘要: 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.
    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.
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出版历程
  • 收稿日期:  2016-06-02
  • 修回日期:  2016-09-29
  • 刊出日期:  2017-02-27

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
    • 基金项目:  Under the auspices of National Basic Research Program of China (No. 2012CB417006), National Natural Science Foundation of China (No. 41271500, 41571107, 41601041)
    通讯作者: YANG Guishan.E-mail:gsyang@niglas.ac.cn
  • 收稿日期: 2016-06-02
  • 修回日期: 2016-09-29
  • 刊出日期: 2017-02-27

摘要: 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.

English Abstract

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]. 中国地理科学, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
引用本文: 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]. 中国地理科学, 2017, 27(1): 39-51. doi: 10.1007/s11769-017-0845-2
shu
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

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