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

丹佛大都会地区对新冠肺炎的限制提供了一个前所未有的机会，让我们了解在交通大幅减少的时期，城市河流水质可能会如何改善。更清洁、可钓鱼和可游泳的城市河流将是减少开车的可持续生活方式的另一个理由，包括在家工作(远程通勤)、远程教育、增加在线购物和送货，以及改善公共交通。这些在城市生活中的做法是不可避免的，但新冠肺炎疫情可能会加速这些做法进入近期的生活情景。这些信息将有助于城市规划者关于清洁城市水所需的绿色基础设施，以及公共卫生官员和立法者管理城市水。此外，制造业、城市发展、交通设计和公共交通的最新趋势意味着，城市水质的历史数据可能不再描述当前的状况。因此，继续研究对于确保未来清洁、有弹性的供水以及健康的城市河流生态系统至关重要。项目组将在新冠肺炎期间从城市溪流和水道收集易腐烂的水质和流量数据，并通过分析这些数据结合为本研究收集的长期、罕见的历史数据以及更频繁的疫情后数据来评估交通减少的影响。该团队将收集基于交通的污染物的数据，包括重金属、选定的有机物(多环芳烃、苯系物)、总溶解固体、基本水质参数以及对污染快速反应的微生物。选定的地点代表了城市的范围，也可能会受到未来在家生活习惯的影响。结果将利用质量平衡的水文和水质模型，结合基于地理信息系统的交通数据，扩大到城市规模。收集的数据可以结合复杂的水文和交通模型来评估与未来城市生活实践相关的众多场景。该奖项由水文科学和环境可持续发展项目共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.