Smart management of combined sewer overflows: From an ancient technology to artificial intelligence

Abstract

Sewer systems are an essential part of sanitation infrastructure for protecting human and ecosystem health. Initially, they were used to solely convey stormwater, but over time municipal sewage was discharged to these conduits and transformed them into combined sewer systems (CSS). Due to climate change and rapid urbanization, these systems are no longer sufficient and overflow in wet weather conditions. Mechanistic and data-driven models have been frequently used in research on combined sewer overflow (CSO) management integrating low-impact development and gray-green infrastructures. Recent advances in measurement, communication, and computation technologies have simplified data collection methods. As a result, technologies such as artificial intelligence (AI), geographic information system, and remote sensing can be integrated into CSO and stormwater management as a part of the smart city and digital twin concepts to build climate-resilient infrastructures and services. Therefore, smart management of CSS is now both technically and economically feasible to tackle the challenges ahead. This review article explores CSO characteristics and associated impact on receiving waterbodies, evaluates suitable models for CSO management, and presents studies including above-mentioned technologies in the context of smart CSO and stormwater management. Although integration of all these technologies has a big potential, further research is required to achieve AI-controlled CSS for robust and agile CSO mitigation. This article is categorized under: Engineering Water > Sustainable Engineering of Water Science of Water > Water and Environmental Change.