SAI: Stormwater Resilience in Urban Areas

SAI：城市地区的雨水恢复能力

• 批准号: 2324487
• 负责人: Matthew Shapiro
• 金额: $ 75万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324487&HistoricalAwards=false
• 关键词: SAI; Stormwater; Resilience; Urban; Areas

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering.The changing climate is expected to increase the frequency of heavy rainfall events, causing more floods and decreasing water quality over time. Within many urban areas of the U.S. there has been historically poor investment in stormwater infrastructure with unequal impacts among communities that vary in socioeconomic status. The result is growing disparities in water quality, reliability, and infrastructure within urban areas. New policies and innovative stormwater management approaches are needed to prepare for future urban flooding and to ensure equitable water management. Drawing from expertise in social science, hydrological modeling, environmental engineering, and landscape architecture, this SAI project improves public understanding, assesses stormwater infrastructure disparities, and identifies viable policy options moving forward.Flood prediction and stormwater management requires hydrological models to simulate the movement of water from precipitation into streams through hydrological processes under various control and land management scenarios. This is an inherently data-driven process, relying on measurements of precipitation, discharge, land usage, water usage, and hydrography that vary significantly throughout a watershed. Common approaches to collecting such data are not sufficient for understanding local-scale flooding, especially urban flooding caused by rainfall. This project addresses the challenge by utilizing two forms of citizen science to improve urban stormwater infrastructure management. One relies on crowdsourced data collection for identifying stormwater flooding events. The other involves citizen-engaged hands-on water quality testing. Chicago is used as the development site because of its vulnerability to flooding and its historical pattern of communities that vary substantially in socioeconomic status. To prepare the next generation of engineers, scientists, and advocates to address the most salient issues in stormwater management, a novel training program is developed to provide students with a background in public policy, hydrologic and climate science, and social justice issues.This award is supported by the Directorate for Social, Behavioral, and Economic (SBE) Sciences and the Directorate for Geosciences.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.

加强美国基础设施 (SAI) 是一项 NSF 计划，旨在促进以人为本的基础性和潜在变革性研究，加强美国的基础设施，为社会经济活力和广泛的生活质量改善提供坚实的基础。私营部门创新、发展经济、创造就业机会、提供更多公共部门服务、加强社区、促进平等机会、保护自然环境、增强国家安全并增强美国的领导力。要实现这些目标，需要来自各个领域的专业知识。 SAI 专注于人类推理和决策、治理以及社会和文化过程的知识如何能够建设和维护有效的基础设施，从而改善生活和社会，并建立在技术和工程的进步之上。随着时间的推移，气候变化预计会增加强降雨事件的发生频率，导致更多的洪水和水质下降。历史上，雨水基础设施投资不足，对不同社会经济地位的社区造成了不同的影响。的差距正在扩大城市地区的水质、可靠性和基础设施需要新的政策和创新的雨水管理方法来为未来的城市洪水做好准备，并确保公平的水管理。该 SAI 项目提高了公众的理解，评估了雨水基础设施的差异，并确定了可行的政策选择。洪水预测和雨水管理需要水文模型来模拟在各种控制和土地管理情景下水通过水文过程从降水到河流的运动。本质上是数据驱动的该项目依赖于整个流域内差异显着的降水、流量、土地使用、用水和水文学的测量，收集此类数据的通用方法不足以了解当地规模的洪水，特别是降雨引起的城市洪水。通过利用两种形式的公民科学来改善城市雨水基础设施管理来应对这一挑战，一种依靠众包数据收集来识别雨水洪水事件，另一种则涉及公民参与的实际水质测试，因为芝加哥被用作开发地点。其对洪水的脆弱性及其社区的历史模式为了培养下一代工程师、科学家和倡导者解决雨水管理中最突出的问题，我们制定了一项新颖的培训计划，为学生提供公共政策、水文和气候科学的背景，该奖项得到了社会、行为和经济 (SBE) 科学理事会和地球科学理事会的支持。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和知识进行评估，认为值得支持。更广泛的影响审查标准。