Minimizing Combined Sewer Overflows with Online Model-Predictive Reinforcement Learning

VBN Forskningsportal (Aalborg Universitet) 2026

Authors: Kim, Esther Hahyeon; id_orcid 0000-0002-3413-8417, Nielsen, Thomas Dyhre; id_orcid 0000-0002-4823-6341, Larsen, Kim Guldstrand; id_orcid 0000-0002-5953-3384, Goorden, Martijn, Ghaffari, Mohsen, Wasowski, Andrzej, Høeg-Petersen, Andreas Holck; id_orcid 0009-0003-7829-7318
Cited by: 0

Abstract

This paper addresses the challenges posed by urban stormwater runoff in light of increased urbanization and climate change, which strain traditional stormwater infrastructure. It focuses on mitigating Combined Sewer Overflows (CSOs) by maximizing urban runoff storage in stormwater tunnels during Wastewater Treatment Plant (WWTP) capacity overloads.

Fields of Study & Subjects

Urban Stormwater Management Solutions Hydrological Forecasting Using AI Hydraulic flow and structures

Publication details

Journal / source
VBN Forskningsportal (Aalborg Universitet)
Publication date
18 September 2026
Language
EN