气候变化已经对我们的社会产生了广泛的影响,经济和环境。根据未来的情况,山区极易受到气候影响,包括水循环的变化(如极端降雨,冰川融化,河流径流),生物多样性和生态系统服务的丧失,对当地经济的损害(饮用水供应,水力发电,农业适宜性)和人类安全(自然灾害的风险)。这是由于它们暴露于最近的气候变暖(例如温度变化,永久冻土的解冻)和自然系统和人类系统的高度专业化(例如山区物种,山谷人口密度,以旅游为基础的经济)。这些特征要求应用能够描述多种危险之间复杂相互作用的风险评估方法,生物物理和社会经济系统,适应气候变化。目前用于评估气候变化风险的方法通常分别处理个别风险,而不能全面反映与不同危险(即复合事件)相关的累积影响。此外,开创性的多层单一风险评估(即针对不同危害的单一风险评估的重叠)仍被广泛使用,导致对多风险过程的误导性评估。这提出了关于多风险评估的独特特征以及解决这些问题的可用工具和方法的关键问题。在这里,我们回顾了五种前沿建模方法(贝叶斯网络,基于代理的模型,系统动态模型,事件树和故障树,和混合模型),探索其在山区多风险评估和气候变化适应方面的潜在应用。比较分析揭示了每种方法的优点和局限性,根据不同的标准(如空间和时间动态,不确定性管理,跨部门评估,适应措施整合,所需的数据和复杂程度)。结果表明,所选方法在解决山区环境中的气候和风险挑战方面的应用有限。特别是,系统动态模型和混合模型显示出更大的潜力,可以进一步应用于表示气候变化对多风险过程的影响,以有效实施气候适应战略。
Climate change has already led to a wide range of impacts on our society, the economy and the environment. According to future scenarios, mountain regions are highly vulnerable to climate impacts, including changes in the water cycle (e.g. rainfall extremes, melting of glaciers, river runoff), loss of biodiversity and ecosystems services, damages to local economy (drinking water supply, hydropower generation, agricultural suitability) and human safety (risks of natural hazards). This is due to their exposure to recent climate warming (e.g. temperature regime changes, thawing of permafrost) and the high degree of specialization of both natural and human systems (e.g. mountain species, valley population density, tourism-based economy). These characteristics call for the application of risk assessment methodologies able to describe the complex interactions among multiple hazards, biophysical and socio-economic systems, towards climate change adaptation. Current approaches used to assess climate change risks often address individual risks separately and do not fulfil a comprehensive representation of cumulative effects associated to different hazards (i.e. compound events). Moreover, pioneering multi-layer single risk assessment (i.e. overlapping of single-risk assessments addressing different hazards) is still widely used, causing misleading evaluations of multi-risk processes. This raises key questions about the distinctive features of multi-risk assessments and the available tools and methods to address them. Here we present a
review of five cutting-edge modelling approaches (Bayesian networks, agent-based models, system dynamic models, event and fault trees, and hybrid models), exploring their potential applications for multi-risk assessment and climate change adaptation in mountain regions. The comparative analysis sheds light on advantages and limitations of each approach, providing a roadmap for methodological and technical implementation of multi-risk assessment according to distinguished criteria (e.g. spatial and temporal dynamics, uncertainty management, cross-sectoral assessment, adaptation measures integration, data required and level of complexity). The results show limited applications of the selected methodologies in addressing the climate and risks challenge in mountain environments. In particular, system dynamic and hybrid models demonstrate higher potential for further applications to represent climate change effects on multi-risk processes for an effective implementation of climate adaptation strategies.