Abstract
Anaerobic digestion (AD) systems within wastewater treatment plants (WWTPs) operate as complex socio-technical infrastructures characterised by nonlinear process dynamics, interacting failure modes, and tightly coupled human–technical decision pathways. Existing risk management approaches predominantly focus on technical controls, often overlooking human and organisational factors that significantly influence system reliability and operational outcomes despite their documented role in operational failures. This study develops a human-centred, reliability-oriented risk management framework (BiogAI-RMF) tailored to WWTP-based biogas systems, grounded in a PRISMA-guided systematic literature review of 113 studies (2000–2025) across 7 databases. The synthesis identifies 78 distinct risk factors across 18 categories and structures them into a formalised risk taxonomy to support prioritisation and decision-making under uncertainty. The proposed framework integrates predictive modelling, probabilistic forecasting, explainable artificial intelligence (XAI), and multi-criteria decision analysis within a unified governance architecture. The novelty of BiogAI-RMF lies in providing a system-level approach linking WWTP-biogas risk taxonomy, uncertainty quantification, explainable AI, and human-in-the-loop decision support within a single governance architecture. This adds new knowledge by moving beyond isolated failure-probability models toward confidence-aware, transparent, auditable, and operator-centred risk governance. It also clarifies how systemic drivers, uncertainties, and risk events can be differentiated and traced across decision pathways in safety-critical biogas operations improving safety, reliability, and performance in WWTPs under variable conditions.