Disaster Resilience of Urban Communities in Canada: New Probabilistic Models and Computational Methods

温哥华大都会地区的地震可能会造成很大一部分人的破坏和流离失所，但我们对建成环境将如何表现缺乏了解。不列颠哥伦比亚省审计长最近的一份报告得出结论，该地区对灾难性地震的准备不足。研究表明，温哥华附近的强烈地震或近海俯冲地震可能造成数十亿美元的损失，但影响尚不确定。拟议的工作将该地区作为一个新的计算机模拟平台的试验台，该平台具有可互换的概率模型，旨在帮助该地区更好地为灾难做好准备和恢复。*不是将计算机模拟程序视为这项工作的单一成果，而是收集了一组关于电网和水网中桥梁、港口、住宅和结构的损坏和恢复的概率模型。这些模型可以与其他研究人员共享，来自其他研究人员的模型可以集成到框架中。模型之间流动的信息包括计算的响应，如地震强度，以及用于维修的电力、水和资源的流动。该计算平台已经用于模拟地震造成的区域损失和流向沿海社区的燃料。*拟议工作中涉及的一个中心问题是，在温哥华附近的下一次强烈地震中，将有多少人流离失所，以及住房恢复的时间表是什么。预测了更多的绩效和复原力指标，并模拟了“假设”情景，但人口流离失所和长期住房恢复代表了我们对社区复原力的理解的重要差距。需要许多模型来解决这一问题，从早期的工作中已经建立了危险模型的框架。拟议的工作建立了三类概率模型的新框架：1)直接影响流离失所人数的住宅和电网结构损坏模型；2)预测修复行动和维修所需资源的模型，如果没有这些模型，住房恢复将被推迟；3)港口和桥梁结构的损坏和恢复模型，这些模型对工人和物资流入和区域内的流动至关重要。*联合国减少灾害风险框架敦促各国政府减少对关键基础设施的潜在破坏，加拿大公共安全部的任务是制定计划，提高加拿大社区的抗灾能力。拟议的工作通过开发新的工具和培训高素质人员来应对这些挑战，以帮助港口、桥梁以及电力和水利基础设施的管理人员评估和减少与他们所监督的结构有关的风险。**

An earthquake in the Metro Vancouver region can cause extensive damage and displacement of a significant portion of the population, but we lack knowledge about how the built environment will perform. A recent report by the British Columbia Auditor General concluded that the region is not adequately prepared for a catastrophic earthquake. Studies have shown that a strong earthquake near Vancouver, or an offshore subduction earthquake, is likely to cause billions of dollars in damage, but the impacts are uncertain. The proposed work employs that region as a testbed for a new computer simulation platform with interchangeable probabilistic models aimed at helping the region better prepare for and recover from a disaster. ******Rather than seeing a computer simulation program as a single deliverable from this work, an important outcome is a collection of probabilistic models for damage and recovery of bridges, ports, residential houses, and structures in the power and water grids. These models can be shared with other researchers, and models from other researchers are integrated into the framework. The information flowing between the models include calculated responses, such as earthquake intensity, and flow of power, water, and resources for repairs. The computational platform has already been employed to simulate regional losses due to earthquakes and the flow of fuel to coastal communities. ******A central question addressed in the proposed work is how many persons will be displaced in the next strong earthquake near Vancouver and what the timeline is for the housing recovery. Additional performance and resilience metrics are predicted and “what-if” scenarios are simulated, but population displacement and long-term housing recovery represent important gaps in our understanding of community resilience. Many models are needed to address that problem and a framework of hazard models are already in place from earlier work. The proposed work creates a new framework of probabilistic models in three categories: 1) Models for damage to residences and the structures of the power/water grids, directly affecting the number of displaced persons; 2) Models to predict the repair actions and the resources needed for repairs, without which housing recovery will be delayed; and 3) Models for damage and recovery of port and bridge structures critical to the flow of workers and materials into and within the region. ******The United Nations framework for disaster risk reduction urges governments to reduce the damage potential for critical infrastructure, and the Ministry of Public Safety in Canada has a mandate to develop plans to enhance the disaster resilience of Canadian communities. The proposed work addresses those challenges through the development of new tools and the training of highly qualified personnel to help managers of ports, bridges, and power and water infrastructure to assess and to reduce the risks associated with the structures they oversee. **