Flood resilience simulation on DAFNI (Theme 1)

DAFNI 的防洪能力模拟（主题 1）

• 批准号: ST/Y003799/1
• 负责人: Richard Dawson
• 金额: $ 5.44万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FY003799%2F1
• 关键词: Flood; resilience; simulation; DAFNI; Theme

Actions taken before, during and after the shock of flood infrastructure failure can lead to radically different outcomes. Poor warnings, slow evacuation, or failure to erect temporary flood defence infrastructure all reduce resilience, increase damages and threaten lives. The Flood Infrastructure Resilience Model (FIRM) is a coupled agent-based and hydrodynamic flood model built on a geospatial data architecture that is used to explore the impact of the flood infrastructure failure on flood resilience, and to test strategies to mitigate the impact of these shocks. FIRM integrates remotely sensed information on topography, buildings and road networks with empirical survey data to fit characteristics of specific communities. Simulation of individuals has been coupled with a hydrodynamic model to assess their response and their resilience in the event of flooding. The aim of this project is to re-code FIRM into Python for greater inter-operability, integrate FIRM onto DAFNI to make it more accessible to the community, to enhance FIRM by adding new functionality to test a wider set of flood resilience actions, and to provide virtual and in-person training to support the wider uptake of the model and DAFNI.

在洪水基础设施破坏的冲击之前、期间和之后采取的行动可能导致完全不同的结果。预警不力、疏散缓慢或未能建立临时防洪基础设施，都会降低复原力，增加损失并威胁生命。洪水基础设施恢复力模型（FIRM）是一个基于地理空间数据架构的耦合代理和水动力洪水模型，用于探索洪水基础设施故障对洪水恢复力的影响，并测试减轻这些冲击影响的策略。FIRM将关于地形、建筑物和道路网的遥感信息与经验调查数据结合起来，以适应特定社区的特点。对个人的模拟与一个水动力模型相结合，以评估他们在发生洪水时的反应和复原力。该项目的目的是将FIRM重新编码到Python中，以提高互操作性，将FIRM集成到DAFNI中，使其更容易为社区所用，通过添加新功能来测试更广泛的洪水恢复力行动来增强FIRM，并提供虚拟和面对面培训，以支持更广泛地采用模型和DAFNI。