Resilience and risk management in urban water supply: assessing the potential contribution of alternative systems

城市供水的弹性和风险管理：评估替代系统的潜在贡献

• 批准号: RGPIN-2018-06640
• 负责人: Bichai, Françoise
• 金额: $ 1.89万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681650
• 关键词: Resilience; risk; management; urban; water

Background***The global urban water sector faces colossal challenges in meeting growing demands from depleted resources. While climate change and urbanization gradually exacerbate these challenges, the frequency of disruptive events such as natural and man-made disasters also rises. Investment is urgently required in Canadian cities to upgrade aging water infrastructure, while recent events in Southern Quebec highlighted the vulnerability of inflexible water systems to shocks. Diversifying sources and infrastructure is put forth as a strategy to increase resilience of urban water systems (UWSs), namely through decentralized alternative water systems (AWSs) based on wastewater or rain/stormwater. With a legacy of centralized infrastructure, integration of AWSs results in the co-existence of centralized and decentralized systems. Such hybrid systems create increased interconnections, which are poorly understood: models are needed to examine the impact of AWSs on centralized systems and on UWSs' resilience. ***Objective and approach***This program will generate cutting-edge science and analytical approaches incorporating state-of-the-art quantitative risk assessment methods and modeling in support of improved risk management and resilience in urban water supply under natural and anthropogenic pressures and shocks. Through HQP training (3 PhDs and 4 MScAs), models will be developed to simulate hybrid systems and compare the resilience of the UWS from source to tap under different risk scenarios. The Greater Montreal Area (GMA) is used as a study region harboring several municipalities concerned with water supply resiliency; yet this study explores the theoretical implications of the models and findings at a global scale. Two dimensions of the water supply risk are considered: (i) water quantity, the risk of a water shortage (WS) and (ii) water quality, the public health risk (PH) from exposure to inadequate water quality. Quantitative Microbial Risk Assessment will be used to evaluate the probability of infection derived from reference pathogens/indicators in drinking or alternative water. Monte Carlo simulations will be used to calculate WS and PH risks under different pressure scenarios on centralized vs. hybrid UWSs. ***Impact***This program is unifying in terms of working across disciplines at the city scale through expert collaborations. It provides (i) a much needed hybrid model, critical to understanding the impact of AWSs on water supply resilience under different risk scenarios, (ii) tools and guidance on proactive adaptation, short/medium and long-term shock responses and communication support to decision makers. Models and results are tailored to the needs of the GMA but can be adapted to other cities and contribute to the broader fields of climate and disaster resilience with foreseen applications in other sectors involving critical infrastructure.

背景***全球城市供水部门在满足资源枯竭不断增长的需求方面面临着巨大的挑战。在气候变化和城市化逐渐加剧这些挑战的同时，自然灾害和人为灾害等破坏性事件的发生频率也在上升。加拿大城市迫切需要投资来升级老化的供水基础设施，而魁北克南部最近发生的事件凸显了不灵活的供水系统容易受到冲击。水源和基础设施多样化是提高城市供水系统（UWS）弹性的一项战略，即通过基于废水或雨水/暴雨的分散式替代水系统（AWS）。凭借集中式基础设施的传统，AWS 的集成导致集中式和分散式系统的共存。这种混合系统增加了互连性，但人们对此知之甚少：需要模型来检查 AWS 对集中式系统和 UWS 弹性的影响。 ***目标和方法***该计划将产生尖端的科学和分析方法，结合最先进的定量风险评估方法和建模，以支持改善自然和人为条件下城市供水的风险管理和复原力压力和冲击。通过 HQP 培训（3 名博士和 4 名硕士），将开发模型来模拟混合系统，并比较 UWS 在不同风险场景下从源头到水龙头的恢复能力。大蒙特利尔地区 (GMA) 被用作研究区域，其中包括几个关注供水弹性的城市；然而，这项研究探讨了全球范围内模型和研究结果的理论意义。考虑供水风险的两个维度：(i) 水量，即缺水风险 (WS) 和 (ii) 水质，即因水质不良而造成的公共卫生风险 (PH)。定量微生物风险评估将用于评估饮用水或替代水中参考病原体/指标引起的感染概率。蒙特卡洛模拟将用于计算集中式与混合式 UWS 不同压力场景下的 WS 和 PH 风险。 ***影响*** 该计划通过专家合作，在城市范围内的跨学科工作方面取得了统一。它提供了 (i) 急需的混合模型，对于了解 AWS 在不同风险情景下对供水弹性的影响至关重要，(ii) 有关主动适应、短期/中期和长期冲击响应以及通信支持的工具和指南决策者。模型和结果是根据 GMA 的需求量身定制的，但可以适应其他城市，并为更广泛的气候和抗灾能力领域做出贡献，并可预见在涉及关键基础设施的其他部门的应用。