Through the diversity of criteria and stakes, the uncertain nature of the entailed phenomena and the multi‐scale aspects to be taken into account, a river restoration project can be considered as a complex problem. Integrative approaches and modelling tools are thus needed to help river managers make predictions on the evolution of hydromorphological, socio‐economic, safety and ecological issues. Such approach can provide valuable information for handling long‐term management plans that consider the interaction and the balance of stakeholders interests and river system functioning. In this paper, we present a probabilistic participatory modelling (PM) method that assesses the effects of given restoration actions, knowing the hydromorphological modifications that they may induce on the safety, ecological and socio‐economic aspects with the help of local stakeholders through several workshops. To support this strategy, we used Bayesian networks (BNs) as modelling tools as their causal graphs can combine multidimensional knowledge and data from diverse natures. We introduce the causal graphs elaborated with the help of the stakeholders and convert it into BNs that can assist restoration decisions by considering the available decision and utility functions to provide guidance to decision‐makers. This was applied to the “Lac des Gaves” reach in the Hautes‐Pyrénées, France, a reach that has gone through severe sediment extractions for over 50 years. Each network represents possible restoration decisions linked to one of the observed issues. The paper demonstrates how BNs used as a decision support system (DSS) can help to assess the influence of given management strategies on the river system with the consideration of stakeholders’ knowledge and integration in all the modelling process.

中文翻译：

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参与式贝叶斯模型用于可持续高效的河流修复项目：法国上特比利牛斯加韦德波河的案例研究反馈

通过标准和风险的多样性，所涉及现象的不确定性以及要考虑的多方面因素，可以将河流修复工程视为一个复杂的问题。因此，需要综合的方法和建模工​​具来帮助河流管理者对水文形态，社会经济，安全和生态问题的演变做出预测。这种方法可以为处理长期管理计划提供有价值的信息，该计划应考虑利益相关者利益和河流系统功能之间的相互作用和平衡。在本文中，我们介绍了一种概率参与建模（PM）方法，该方法可评估给定修复措施的影响，同时了解它们可能对安全性造成的水文形态变化，在地方利益攸关方的帮助下，通过几次讲习班在生态和社会经济方面。为了支持该策略，我们使用贝叶斯网络（BN）作为建模工具，因为它们的因果图可以结合多维知识和来自不同性质的数据。我们介绍了在利益相关者的帮助下详细阐述的因果图，并将其转换为可考虑到可用决策和效用函数以为决策者提供指导的BN，从而可以帮助恢复决策。这被应用到法国上特比利牛斯的“ Lac des Gaves”河段，该河段经过了50多年的严重沉积物提取。每个网络代表与观察到的问题之一相关的可能的恢复决策。