Application of a hybrid fuzzy-based algorithm to investigate the environmental impact of sewer overflow

Purpose: This study underscores the critical importance of well-functioning sewer systems in achieving smart and sustainable urban drainage within cities. It specifically targets the pressing issue of sewer overflows (SO), widely recognized for their detrimental impact on the environment and public health. The primary purpose of this research is to bridge significant research gaps by investigating the root causes of SO incidents and comprehending their broader ecological consequences. Design/methodology/approach: To fill research gaps, the study introduces the Multi-Phase Causal Inference Fuzzy-Based Framework (MCIF). MCIF integrates the fuzzy Delphi technique, fuzzy DEMATEL method, fuzzy TOPSIS technique and expert interviews. Drawing on expertise from developed countries, MCIF systematically identifies and prioritizes SO causes, explores causal interrelationships, prioritizes environmental impacts and compiles mitigation strategies. Findings: The study's findings are multifaceted and substantially contribute to addressing SO challenges. Utilizing the MCIF, the research effectively identifies and prioritizes causal factors behind SO incidents, highlighting their relative significance. Additionally, it unravels intricate causal relationships among key factors such as blockages, flow velocity, infiltration and inflow, under-designed pipe diameter and pipe deformation, holes or collapse, providing a profound insight into the intricate web of influences leading to SO. Originality/value: This study introduces originality by presenting the innovative MCIF tailored for SO mitigation. The combination of fuzzy techniques, expert input and holistic analysis enriches the existing knowledge. These findings pave the way for informed decision-making and proactive measures to achieve sustainable urban drainage systems.