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A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes
Lu, Hongwei1; Ren, Lixia2; Chen, Yizhong3; Tian, Peipei3; Liu, Jia3
2017-12-01
Source PublicationJOURNAL OF HYDROLOGY
ISSN0022-1694
Volume555Pages:881-893
Corresponding AuthorRen, Lixia(renlx@ncepu.edu.cn)
AbstractDue to the uncertainty (i.e., fuzziness, stochasticity and imprecision) existed simultaneously during the process for groundwater remediation, the accuracy of ranking results obtained by the traditional methods has been limited. This paper proposes a cloud model based multi-attribute decision making framework (CM-MADM) with Monte Carlo for the contaminated-groundwater remediation strategies selection. The cloud model is used to handle imprecise numerical quantities, which can describe the fuzziness and stochasticity of the information fully and precisely. In the proposed approach, the contaminated concentrations are aggregated via the backward cloud generator and the weights of attributes are calculated by employing the weight cloud module. A case study on the remedial alternative selection for a contaminated site suffering from a 1,1,1-trichloroethylene leakage problem in Shanghai, China is conducted to illustrate the efficiency and applicability of the developed approach. Totally, an attribute system which consists of ten attributes were used for evaluating each alternative through the developed method under uncertainty, including daily total pumping rate, total cost and cloud model based health risk. Results indicated that A14 was evaluated to be the most preferred alternative for the 5-year, A5 for the 10-year, A4 for the 15-year and A6 for the 20-year remediation. (C) 2017 Elsevier B.V. All rights reserved.
KeywordGroundwater remediation Multi-attribute analysis 1,1-Dichloroethane Cloud model Health risk assessment
DOI10.1016/j.jhydrol.2017.10.009
WOS KeywordPETROLEUM-CONTAMINATED SITES ; REMEDIATION DESIGN ; PARTICLE SWARM ; MCDA APPROACH ; OPTIMIZATION ; UNCERTAINTY ; CHINA ; TECHNOLOGIES ; METHODOLOGY ; STRATEGIES
Indexed BySCI
Language英语
Funding ProjectChina National Funds for Excellent Young Scientists[51422903] ; National Natural Science Foundation of China[41271540] ; Fundamental Research Funds for the Central Universities ; Shanxi 1331 Project Key Subjects Construction[1331KSC]
Funding OrganizationChina National Funds for Excellent Young Scientists ; National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; Shanxi 1331 Project Key Subjects Construction
WOS Research AreaEngineering ; Geology ; Water Resources
WOS SubjectEngineering, Civil ; Geosciences, Multidisciplinary ; Water Resources
WOS IDWOS:000418107600067
PublisherELSEVIER SCIENCE BV
Citation statistics
Cited Times:15[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/60821
Collection中国科学院地理科学与资源研究所
Corresponding AuthorRen, Lixia
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Shanxi Inst Energy, Taiyuan 030600, Shanxi, Peoples R China
3.North China Elect Power Univ, Sch Renewable Energy, 2 Beinong Rd, Beijing 102206, Peoples R China
Recommended Citation
GB/T 7714
Lu, Hongwei,Ren, Lixia,Chen, Yizhong,et al. A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes[J]. JOURNAL OF HYDROLOGY,2017,555:881-893.
APA Lu, Hongwei,Ren, Lixia,Chen, Yizhong,Tian, Peipei,&Liu, Jia.(2017).A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes.JOURNAL OF HYDROLOGY,555,881-893.
MLA Lu, Hongwei,et al."A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes".JOURNAL OF HYDROLOGY 555(2017):881-893.
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