RAPID: Impact of CoVID-19 Stay-at-Home Orders on urban stream quality in Denver Metro Area with application for future urban living scenarios

Geosciences - The COVID-19 restrictions in the Denver Metro area present an unprecedented opportunity to understand how urban river water quality might improve during times of greatly reduced traffic. Cleaner, fishable and swimmable urban rivers would be another justification for sustainable living practices that entail much less driving, including working from home (telecommuting), remote education, increased on-line shopping and delivery, and enhanced public transportation. These urban-living practices are inevitable, but the COVID-19 pandemic could potentially accelerate these practices into near-term living scenarios. The information will be useful to urban planners regarding green infrastructure needed for cleaning urban water, and to public health officials and legislators for managing urban water. Additionally, recent trends for manufacturing, urban development, traffic design, and public transportation mean the historical data on urban water quality may no longer describe current conditions. Thus, continued study is critically necessary to ensure a future clean, resilient water supply, as well as a healthy urban river ecosystem.

The project team will collect perishable water quality and flow data from urban streams and waterways during COVID-19 and evaluate the impact of reduced traffic by analyzing this data in combination with long-term, infrequent, historical data, as well as more frequent post-pandemic data collected for this study. The team will collect data on traffic-based pollutants, including heavy metals, selected organics (PAH, BTEX), total-dissolved solids, basic water-quality parameters, and macro-organisms that respond rapidly to pollution. Chosen sites are representative of the urban spectrum, and also are likely to be impacted by future stay-at-home living practices. Results will be scaled up to the city-scale using mass-balance hydrological and water quality models in combination with GIS-based traffic data. The data collected can be used in combination with complex hydrological and traffic models to evaluate numerous scenarios associated with future urban living practices.

This award was co-funded by the Hydrologic Sciences and Environmental Sustainability programs.

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.