Overcoming barriers to adoption of smart stormwater technologies

Digital technologies are changing the way cities around the world are managed, with sensors, algorithms, and robotics improving efficiency, lowering costs, and enabling new services to make urban life safer and more convenient. In water management, smart stormwater systems, in which algorithms leverage real-time sensor data to optimally control stormwater drainage infrastructure, are widely expected to revolutionize the industry. These advances are greatly needed as climate change and urbanization strain the capacity of existing infrastructure, resulting in increased rates of urban flooding and sewer overflows. In comparison to other sectors, however, adoption of digital technologies in stormwater management has been slow. A number of knowledge gaps underpin the barriers to adoption of smart stormwater technologies. We do not know how to build the robust data pipelines needed to support digital stormwater technologies, nor do we understand how to design digital technologies that are accepted and trusted by stormwater management practitioners. This dissertation addresses these fundamental knowledge gaps by examining how emerging smart stormwater technologies fit into — or are at odds with — existing water management workflows. The second chapter focuses on the role of data collection, presenting a quality assurance and control (QAQC) pipeline for large, low-cost wireless water sensor networks. This improves the reliability and scalability of real-time water sensor networks, which are essential to enable the algorithms that underlie smart water technologies. The third chapter addresses the challenge of creating actionable insights from continuous streams of sensor data. An automated data analysis pipeline is introduced for a novel green infrastructure sensor, which segments storm events and calculates the rate of water drawdown, a metric of how well the green infrastructure is performing. The fourth chapter examines the challenges of incorporating smart stormwater technologies into existing water control room workflows. A user study of water operators in Detroit, Michigan (USA) highlights constraints in the water management process that must be considered when designing new smart stormwater systems. The fifth chapter evaluates the accessibility of smart water technologies to all stormwater management practitioners. A web application is presented which allows users to model the city-wide stormwater impacts of green infrastructure in Detroit using the US EPA's Stormwater Management Model (EPA SWMM), a valuable but technically complex engineering tool which many green infrastructure practitioners have not traditionally been able to use. The discoveries made in this dissertation seek to support the development of the next-generation smart stormwater technologies that are better positioned to achieve widespread adoption in practice.