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

丹佛都市区的COVID-19限制提供了一个前所未有的机会，可以了解在交通大大减少的时期城市河流水质如何改善。更清洁、适合捕鱼和游泳的城市河流将成为可持续生活实践的另一个理由，这些实践需要更少的驾驶，包括在家工作（远程办公）、远程教育、增加在线购物和配送，以及加强公共交通。这些城市生活方式是不可避免的，但COVID-19大流行可能会加速这些做法成为近期的生活场景。这些资料将有助于城市规划者了解清洁城市用水所需的绿色基础设施，并有助于公共卫生官员和立法人员管理城市用水。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状况。因此，持续的研究对于确保未来清洁、有弹性的水供应以及健康的城市河流生态系统至关重要。项目团队将在COVID-19期间从城市溪流和水道收集易腐烂的水质和流量数据，并通过将这些数据与长期、罕见的历史数据以及为本研究收集的更频繁的大流行后数据相结合，分析交通减少的影响。该小组将收集有关交通污染物的数据，包括重金属、选定的有机物（多环芳烃、苯醚）、总溶解固体、基本水质参数和对污染反应迅速的大型生物。所选择的地点是城市光谱的代表，也可能受到未来居家生活方式的影响。利用质量平衡水文和水质模型，结合基于gis的交通数据，研究结果将扩大到城市规模。收集到的数据可以与复杂的水文和交通模型结合使用，以评估与未来城市生活实践相关的许多情景。该奖项由水文科学和环境可持续性项目共同资助。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 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.