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A scenario-based MCDA framework for wastewater infrastructure planning under uncertainty

机译:基于场景的不确定环境下废水基础设施规划的MCDA框架

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Wastewater infrastructure management is increasingly important because of urbanization, environmental pollutants, aging infrastructures, and climate change. We propose a scenario-based multi-criteria decision analysis (MCDA) framework to compare different infrastructure alternatives in terms of their sustainability. These range from the current centralized system to semi- and fully decentralized options. Various sources of uncertainty are considered, including external socio-economic uncertainty captured by future scenarios, uncertainty in predicting outcomes of alternatives, and incomplete preferences of stakeholders. Stochastic Multi-criteria Acceptability Analysis (SMAA) with Monte Carlo simulation is performed, and rank acceptability indices help identify robust alternatives. We propose step-wise local sensitivity analysis, which is useful for practitioners to effectively elicit preferences and identify major sources of uncertainty. The approach is demonstrated in a Swiss case study where ten stakeholders are involved throughout. Their preferences are quantitatively elicited by combining an online questionnaire with face-to-face interviews. The trade-off questions reveal a high concern about environmental and an unexpectedly low importance of economic criteria. This results in a surprisingly good ranking of high-tech decentralized wastewater alternatives using urine source separation for most stakeholders in all scenarios. Combining scenario planning and MCDA proves useful, as the performance of wastewater infrastructure systems is indeed sensitive to socio-economic boundary conditions and the other sources of uncertainty. The proposed sensitivity analysis suggests that a simplified elicitation procedure is sufficient in many cases. Elicitation of more information such as detailed marginal value functions should only follow if the sensitivity analysis finds this necessary. Moreover, the uncertainty of rankings can be considerably reduced by better predictions of the outcomes of alternatives. Although the results are case based, the proposed decision framework is generalizable to other decision contexts.
机译:由于城市化,环境污染物,基础设施老化和气候变化,废水基础设施管理变得越来越重要。我们提出了一个基于场景的多标准决策分析(MCDA)框架,以比较不同基础架构替代方案的可持续性。这些范围从当前的集中式系统到半分散和完全分散的选项。考虑了各种不确定性来源,包括未来情景所捕获的外部社会经济不确定性,预测替代方案结果的不确定性以及利益相关者的不完全偏好。进行了带有蒙特卡洛模拟的随机多标准可接受性分析(SMAA),等级可接受性指数有助于确定可靠的替代方案。我们建议逐步进行局部敏感性分析,这对于从业人员有效地激发偏好并确定不确定性的主要来源很有用。瑞士的案例研究证明了该方法,其中十个利益相关者参与其中。通过将在线问卷与面对面访谈相结合,定量地得出了他们的偏好。权衡问题显示出人们对环境的高度关注,而经济标准的重要性却出乎意料地低。对于所有情况下的大多数利益相关者而言,使用尿液源分离技术得出的高科技分散废水替代品的评级都出乎意料地好。事实证明,将情景规划与MCDA结合起来是有用的,因为废水基础设施系统的性能确实对社会经济边界条件和其他不确定性因素敏感。拟议的灵敏度分析表明,在许多情况下,简化的激发过程就足够了。只有在敏感性分析认为有必要的情况下,才应进行更多信息的宣传,例如详细的边际价值函数。此外,通过更好地预测替代方案的结果,可以大大降低排名的不确定性。尽管结果是基于案例的,但是建议的决策框架可以推广到其他决策环境。

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