Convergence: RAISE: Systems Approaches for Vulnerability Evaluation and Urban Resilience

无法评估和预测城市内极端天气条件的程度和影响是一个严重的脆弱性。城市洪水来自泛滥的河流和溪流，以及不透水的地面结构排水不足。缺乏社区规模的洪水预报阻碍了社会和公共卫生干预工作。空气质量和热岛/温度影响方面也存在类似的限制。该研究项目将结合自然科学、社会科学、数据科学和工程科学的观点，以改进对天气模式、空气质量、洪水以及社区尺度上的社会和经济影响的预测。传感器装置和模型模拟将用于研究绿色基础设施在减少洪水、缓和热浪以及改善当地和整个地区空气质量方面的潜力。整合降雨、地形、城市基础设施和不透水表面的模型目前还不可行或可用。这一研究项目将使以前单独处理的水输送机制得以整合，现在可以将其视为一个更大更复杂问题的一部分。项目结果将直接用于芝加哥社区的脆弱性评估和基础设施设计。这一融合项目将催生新的多层次城市评估和预测能力；为城市规模的天气、基础设施和人口脆弱性之间联系的模拟提供新的能力；并演示了这种新的系统级预测框架在适应性绿色基础设施设计中的应用。项目的主要组成部分包括：(1)安装和利用遥感和分布式遥感来测量影响；(2)阐明恶劣天气、城市基础设施和脆弱性之间联系的高分辨率基础设施/环境模型；(3)评估极端天气、基础设施和城市地形共同产生的社会和经济影响。许多研究生和博士后将直接参与该项目。该项目将向地方司法管辖区提供脆弱性地图，并将鼓励政府和公共/私人讨论城市对极端天气的脆弱性以及潜在的复原力战略。项目数据将通过芝加哥数据门户公开提供。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The inability to assess and predict the extent and impact of extreme weather conditions within cities is a critical vulnerability. Urban floods come from overflowing rivers and streams as well as insufficient drainage from impervious surface structures. The lack of neighborhood-scale forecasts for flooding hampers social and public health intervention efforts. Similar limitations exist for air quality and heat island/temperature impacts. This research project will combine perspectives from natural, social, data and engineering sciences to improve the prediction of weather patterns, air quality, flooding, and social and economic impacts at the neighborhood scale. Sensor installations and model simulations will be used to examine the potential for green infrastructure to reduce flooding, moderate heat waves, and improve air quality locally and across the region. Models that integrate across rainfall, topography, urban infrastructure and impervious surfaces are not currently viable or available. This research project will enable the integration of water routing mechanisms that were previous treated separately and can now be considered as portions of a larger more complex problem. Project results will be directly used for vulnerability assessment and infrastructure design in Chicago neighborhoods.This convergence project will catalyze new multi-level urban assessment and prediction capabilities; yield new capacity for city-scale simulations of links between weather, infrastructure, and population vulnerability; and demonstrate the application of this new systems-level prediction framework to adaptive green infrastructure design. The principle components of the project include (1) installation and utilization of remote and distributed sensing to measure impacts; (2) high-resolution infrastructure/environmental models that elucidate links between severe weather, urban infrastructure, and vulnerability; and (3) an assessment of co-occurring social and economic impacts as a result of extreme weather, infrastructure and urban topography. Many graduate students and postdocs will be directly engaged in the project. The project will contribute vulnerability maps to local jurisdictions and will encourage government and public/private discourse on urban vulnerability to extreme weather as well as potential resilience strategies. Project data will be publicly available through the Chicago Data Portal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.