ABSTRACT Wastewater treatment plants (WWTPs) are encountering challenges related to sustainability, efficiency, and economic viability due to stricter discharge standards and climate change impacts, such as heavy rainfalls. Enhancing the resilience and performance of WWTPs is therefore crucial. This paper reviews the application of artificial intelligence (AI) models that can improve the resilience of WWTPs, with a focus on extreme rainfall events. It provides an overview of digitalization publications related to WWTPs over the past 33 years, proposes a new classification approach for AI models, and reviews existing AI applications aimed at enhancing WWTPs performance in response to extreme rainfall events. The applications highlight the importance of developing hybrid models that integrate AI with knowledge-driven models to improve accuracy. Furthermore, future AI research in WWTPs should integrate hydrological forecasting for flow rate estimation in advance to facilitate effective management.
Hocaoğlu et al. (Thu,) studied this question.