Grey-stochastic Risk Assessment Method for River Water Quality

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  • 1. College of Land & Resources, Hunan Normal University, Changsha, Hunan 410081;
    2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101;
    3. Institute of Water Resource Protection of the Yellow River, Zhengzhou, Henan 450004

Received date: 2001-02-13

  Revised date: 2001-07-19

  Online published: 2002-03-20

Abstract

The river water environment system is a system with many uncertainties. The risk assessment quantifying the influence of uncertainties on river water quality have been paid attention to widely. However, the most of research on risk assessment for river water quality confined to quantify stochastic uncertainty of the river water environmental system using the method of statistics. The research on quantifying the risk due to grey uncertainty of the river water environmental system is done less. Based on the theory of probability and grey system approach, the concepts of grey probability, grey probability distribution, grey probability density, grey expectation and grey variance are defined in this paper. The concept of grey-stochastic risk for water quality concentrations exceeding the standard values is presented to quantify the influence of stochastic uncertainty and grey uncertainty on river water quality. The assessment models of grey-stochastic risk for water quality concentrations exceeding the standard values are established. In the assessment model for the individual parameter, the contaminant concentration is modeled as a random variable with a grey probability distribution and the risk for contaminant concentration exceeding the standard value is expressed with grey probability-the grey-stochastic risk for water quality concentrations exceeding the standard values. In the model of comprehensive assessment for multiple parameters, the river water environmental system is considered as the reliability system to undertake useful function, and the result that the concentration of anyone of water quality parameters exceeds the standard value shows that the useful function of river water environmental system cannot be guaranteed. Lastly, the comprehensive risks for water quality concentrations exceeding the standard values are computed by using the approach of reliability system. An example of application to evaluate the grey-stochastic risks for heavy metals concentrations exceeding the standard values in the Yellow River at the Huayuankou section is given. The results provide more information and are satisfactory.

Cite this article

HU Guo-hua, Xia Jun, ZHAO Pei-lun . Grey-stochastic Risk Assessment Method for River Water Quality[J]. SCIENTIA GEOGRAPHICA SINICA, 2002 , 22(2) : 249 -252 . DOI: 10.13249/j.cnki.sgs.2002.02.249

References

[1] 马小莹,王华东.河流水环境质量评价研究——对评价系统、评价方法的新探讨[J].环境科学学报,1987,7(1):60~71.
[2] 贺锡泉.非突发性环境风险研究[J].中国环境科学,1990,10(3):218~223.
[3] 张庆丰.水质随机评价模式研究[J].水利学报,1992,(10):73~78.
[4] 曾光明,卓利,钟政林,等. 突发性水环境风险评价模型事故泄漏行为的模拟分析[J]. 中国环境科学,1998,18(5):403~406.
[5] 陈小红,涂新军.水质超标风险率的CSPPC模型[J].水利学报,1999,(12):1~5.
[6] 万咸涛.用模糊数学方法对苏州市大运河水质进行评价[J].水文,1985,(6):30~33.
[7] 邓勃,秦建侯,李隆弟. 水环境质量模糊综合评价中的一些问题探讨[J]. 环境科学学报,1990,10(2):258~262.
[8] 陈守煜,赵英琪. 模糊模式识别理论模型与水质评价[J]. 水利学报,1991,(6):35~40.
[9] 刘广吉,韩淑文.灰色聚类法在水质评价中的应用[J].水利水电技术,1988,(12):1~5.
[10] 夏 军.区域水环境质量灰关联度评价方法的研究[J]. 水文,1995,(2):4~10.
[11] 冯玉国. 水环境质量评价的灰色局势决策法[J].环境科学学报,1994,14(4):426~430.
[12] 夏 军.灰色系统水文学[M].武汉:华中理工大学出版社,2000.49~53.
[13] 胡国华,夏 军. 风险分析的灰色-随机风险率方法研究[J]. 水利学报,2001,(4):1~6.
[14] 黄伟军,丁晶.灰色先验分布研究.夏军.现代水科学不确定性研究与进展.成都:成都科技大学出版社,1994.178~182.
[15] Timothy L J, Vesilind P A. Probabilistic environmental risk of hazardous materials[J].Journal of Environmental Engineering, 1992, 118(6):878-889.
[16] 赵沛伦,申献辰,夏军,等.泥沙对黄河水质影响及重点河段水污染控制[M].郑州:黄河水利出版社,1998.98~113.
[17] Finney B A, Bowles D S, Windham M P. Random differential equations in river water quality modeling[J]. Water Resources Res., 1982, 18(1): 122-134.
[18] Dewey R J. Application of stochastic dissolved oxygen model[J]. J. Environmental Eng. ASCE,1984, 110(2):412-429.
[18] Padgett W J, Rao A N V. Estimation of BOD and DO probability distribution[J]. J. Environmental Eng. ASCE, 1988, 114(1): 74-90.
[19] 黄 平.水质随机微分模型系数的识别方法及应用[J].水利学报,1988,(3):41~48.
[20] Wasserman L A. Belief functions and statistical inference[J]. Canadian J. Statist., 1990, 18(3):183-196.
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