Modeling of Controller Performance for Autonomous Smart Rain Barrel Systems as a Sustainable Solution for Urban Stormwater Management and Flooding Mitigation

Abstract

Urban residential areas with aging wastewater handling infrastructure are often plagued by flooding. While renovating or outright replacing the infrastructure is perhaps the most obvious solution, it also comes at a high cost. For this reason, many alternative solutions have been studied, particularly those that offer the additional benefit of supporting sustainable urban development. To this end, the widescale deployment of rain barrels has the potential to play a significant role in temporary stormwater retention, which would help to reduce and prevent the flooding. They also have the potential to reduce or even eliminate the pollution and environmental degradation associated with combined sewer overflows (CSOs). This is a problem tied to flooding in cities with combined sewer systems, which are common in older wastewater infrastructure. However, rain barrels have not been widely adopted to date, primarily due to their highmaintenance characteristics associated with regular and timely draining. Furthermore, there is also limited information about the necessary capacity of a rain barrel system required to reap these flooding and CSO mitigation benefits. To address this, an emerging technical innovation known as Smart Rain Barrels (SRBs) aims to automate rain barrel functionality pertaining to drainage through the use of various control systems. Some of these systems also use an internet connection to obtain weather forecast data with the aim of improving predictive control. While some literature has shown the idea to be conceptually viable, the practical applicability is hampered by the lack of affordable SRB solutions. This thesis aims to address that gap through simulation using historical weather data and a combined system hydraulic model to further the development of a low-cost SRB that delivers on the goal of autonomous operation while also remaining accessible and practically useable by the residents of urban areas affected by flooding and CSOs. Different controller designs are also evaluated via appropriate system modeling. Key findings are that SRB efficiency increases with barrel volume regardless of controller design, and that constantly leaking rain barrels can match the performance of simple automation methods. Periodic drainage by an end-user is also seen to be highly inefficient, furthering the case for 'hands-free' rain barrel operation.