The paper demonstrates the use of Bayesian networks in multicriteria decision analysis (MCDA) of environmental design alternatives for environmental flows (eflows) and physical habitat remediation measures in the Mandalselva River in Norway. We demonstrate how MCDA using multi-attribute value functions can be implemented in a Bayesian network with decision and utility nodes. An object-oriented Bayesian network is used to integrate impacts computed in quantitative sub-models of hydropower revenues and Atlantic salmon smolt production and qualitative judgement models of mesohabitat fishability and riverscape aesthetics. We show how conditional probability tables are useful for modelling uncertainty in value scaling functions, and variance in criteria weights due to different stakeholder preferences. While the paper demonstrates the technical feasibility of MCDA in a BN, we also discuss the challenges of providing decision-support to a real-world habitat remediation process.

本文演示了贝叶斯网络在挪威曼达瑟尔瓦河环境流量（排放量）和物理栖息地补救措施的环境设计替代方案的多标准决策分析（MCDA）中的使用。我们演示了如何在具有决策和效用节点的贝叶斯网络中实现使用多属性值函数的MCDA。面向对象的贝叶斯网络用于整合在水电收益和大西洋鲑鱼养殖的定量子模型中计算出的影响，以及中栖息地可捕鱼性和河景美感的定性判断模型。我们展示了条件概率表如何用于建模价值缩放函数中的不确定性以及由于不同利益相关者的偏好而导致的标准权重方差。