Multi-criteria decision analysis in assessing watershed scale pollution risk: a review of combined approaches and applications

多准则决策分析 环境科学 层次分析法 环境资源管理 分水岭 计算机科学 环境规划 风险分析(工程) 运筹学 工程类 业务 机器学习
作者
Zeynep Akdoğan,Basak Guven
出处
期刊:Environmental Reviews [Canadian Science Publishing]
卷期号:31 (4): 669-689 被引量:8
标识
DOI:10.1139/er-2023-0017
摘要

Decision-making tools have become a prominent methodology in watershed management for many years due to the complexity of environmental systems and requirement for multi-disciplinary expertise. Multi-Criteria Decision Analysis (MCDA) is a systematic methodology, which combines hierarchical structures of a problem and priorities for the alternatives in many fields. This study reviews MCDA applications in pollution risk assessment in the abiotic environments of watersheds for multi-pollutants. Over 80 papers published between 2000 and 2021 are identified in three categories of the Web of Science Core Collection database: “Environmental Sciences”, “Environmental Studies”, and “Water Resources”. The publications are further classified according to different environmental compartments: surface water, groundwater, and soil to investigate MCDA applications in these matrices. Finally, the distribution of the publications according to contaminants and MCDA methods used are also examined. The results reveal that the number of the studies focusing on pollution risk assessment within watersheds has been significantly increasing, especially over the last decade. However, there are still limited MCDA applications linking environmental compartments. Despite several MCDA studies focusing on the vulnerability of watersheds to multiple pollutants, studies related with emerging pollutants are scarce. Moreover, compared to non-point source pollution, studies adopting MCDA to investigate pollutant concentrations coming from point sources are relatively few. According to the overall distributions of MCDA methods, Analytic Hierarchy Process, a commonly found method in the literature that adopts a technique of pairwise comparison to prioritize criteria of prominence, dominates 34% of the publications.
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