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• W1969958719 abstract "Decision-making for sediment management is a complex task that requires the consideration of temporal and spatial impacts of several remedial alternatives as well as the associated economic, social and political impact. Multicriteria decision analysis (MCDA) is becoming increasingly recognized as an important environmental management tool that can be used to support the selection of suitable remediation alternatives and prioritization of management units in space and time. This paper proposes an MCDA framework for prioritizing sediment management alternatives. This framework involves identifying of a set of feasible options, as well as defining and evaluating criteria which integrate relevant technical, economic, social and environmental aspects of remedies. The methodology allows an explicit consideration of uncertainty in criteria scores and weights by assigning probability distributions and analyzing subsequent Monte-Carlo simulations. The consideration of different stakeholder simulated values is used to assess the robustness of alternative rankings and to guide the selection of remediation options. An application of this methodology to a case study in the Bay of Santander, Spain, is presented. An assessment is conducted for the case of unknown preferences as well as for hypothetical preferences profiles for four types of stakeholders: Idealist, Politician, Environmentalist and Balanced. The results are used to visualize stakeholder positions and potential disagreements, allowing for the identification of a group of least preferred alternatives for each stakeholder. Stakeholder involvement has the potential to ease the remedy selection process during all stages of the decision-making process and to eventually remedy implementation." @default.
• W1969958719 created "2016-06-24" @default.
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• W1969958719 date "2010-09-01" @default.
• W1969958719 modified "2023-10-18" @default.
• W1969958719 title "Prioritization of sediment management alternatives using stochastic multicriteria acceptability analysis" @default.
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• W1969958719 doi "https://doi.org/10.1016/j.scitotenv.2010.07.016" @default.
• W1969958719 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/20673964" @default.
• W1969958719 hasPublicationYear "2010" @default.
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