SAI: Stormwater Resilience in Urban Areas

Illinois Institute Of Technology, Chicago IL

Investigators

Abstract

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 frequency of heavy rainfall events is expected to increase, 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 varied impacts among communities. 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 effective 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. To prepare the next generation of engineers and scientists to address the most salient issues in stormwater management, a novel student training program is developed. 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.