通常用于支持洪水风险评估和管理的几种建模工具在表示物理现象方面非常有效,但对洪水风险和减少洪水风险措施对城市地区等高度复杂系统的多重影响提供了相当有限的理解。事实上,大多数可用的建模工具没有充分考虑这种复杂性和相关的不确定性,这严重影响了城市系统演变和洪水风险之间的相互联系,最终导致洪水风险管理无效。本研究提出了一个创新的方法论框架,以支持参与城市再生过程的决策者在规划/战略层面,考虑洪水风险和不同洪水风险管理策略的多维含义。所采用的方法基于系统思维原理和参与式系统动力学建模技术的使用,并追求科学知识和利益相关者知识之间的融合。参考了CUSSH和CAMELLIA项目的案例研究之一,即Thamesmead(伦敦),一个以前荒凉的沼泽地,目前正在经历城市复兴的过程,并被认为越来越容易受到洪水的影响。它代表了一个有趣的机会,可以建立一个可复制的建模方法,将城市发展动态与洪水风险相结合,最终支持政策和决策者确定缓解/预防措施,并了解它们如何帮助实现多维利益(例如,环境,社会和经济)。
Several modeling tools commonly used for supporting flood risk assessment and management are highly effective in representing physical phenomena, but provide a rather limited understanding of the multiple implications that flood risk and flood risk reduction measures have on highly complex systems such as urban areas. In fact, most of the available modeling tools do not fully account for this complexity-and related uncertainty-which heavily affects the interconnections between urban systems evolution and flood risk, ultimately resulting in an ineffective flood risk management. The present research proposes an innovative methodological framework to support decision-makers involved in an urban regeneration process at a planning/strategic level, accounting for the multi-dimensional implications of flood risk and of different flood risk management strategies. The adopted approach is based on the use of System Thinking principles and participatory System Dynamics modeling techniques, and pursues an integration between scientific and stakeholder knowledge. Reference is made to one of the case studies of the CUSSH and CAMELLIA projects, namely
Thamesmead (London), a formerly inhospitable marshland currently undergoing a process of urban regeneration, and perceived as being increasingly vulnerable to flooding. It represents an interesting opportunity for building a replicable modeling approach to integrate urban development dynamics with flood risk, ultimately supporting policy and decision-makers in identifying mitigation/prevention measures and understanding how they could help achieve multi-dimensional benefits (e.g., environmental, social and economic).