Integrated evaluation system under randomness and fuzziness for groundwater contamination risk assessment in a little town, Central China

An integrated evaluation system under randomness and fuzziness was developed in this work to systematically assess the risk of groundwater contamination in a little town, Central China. In this system, randomness of the parameters and the fuzziness of the risk were considered simultaneously, and the...

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Published inJournal of Central South University Vol. 21; no. 3; pp. 1044 - 1050
Main Authors Zhu, Hui-na, Yuan, Xing-zhong, Liang, Jie, Liu, Yong-de, Yin, Juan, Jiang, Hong-wei, Huang, Hua-jun
Format Journal Article
LanguageEnglish
Published Heidelberg Central South University 01.03.2014
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ISSN2095-2899
2227-5223
DOI10.1007/s11771-014-2035-z

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Summary:An integrated evaluation system under randomness and fuzziness was developed in this work to systematically assess the risk of groundwater contamination in a little town, Central China. In this system, randomness of the parameters and the fuzziness of the risk were considered simultaneously, and the exceeding standard probability of contamination and human health risk due to the contamination were integrated. The contamination risk was defined as a combination of “vulnerability” and “hazard”. To calculate the value of “vulnerability”, pollutant concentration was simulated by MODFLOW with random input variables and a new modified health risk assessment (MRA) model was established to analyze the level of “hazard”. The limit concentration based on environmental-guideline and health risk due to manganese were systematically examined to obtain the general risk levels through a fuzzy rule base. The “vulnerability” and “hazard” were divided into five categories of “high”, “medium-high”, “medium”, “low-medium” and “low”, respectively. Then, “vulnerability” and “hazard” were firstly combined by integrated evaluation. Compared with the other two scenarios under deterministic methods, the risk obtained in the proposed system is higher. This research illustrated that ignoring of uncertainties in evaluation process might underestimate the risk level.
ISSN:2095-2899
2227-5223
DOI:10.1007/s11771-014-2035-z