Development of a dual-metric operational decision-support model for full-scale submerged membrane bioreactors (MBRs)

• Dual-metric model defines sustainable capacity via H-index and resistance • Resistance decomposition reveals distinct fouling pathways and consolidation. • Statistically validated Control Matrix categorizes fouling states for diagnosis. • Action Matrix guides air scouring to minimize energy costs. Membrane Bioreactor (MBR) operations are often characterized by reactive and inefficient responses to complex fouling phenomena, leading to high operational costs. To facilitate a shift toward proactive management, this study developed and evaluated a novel dual-metric operational decision-support model. We analyzed year-long operational data from a full-scale MBR facility, integrating the hydrodynamic index (H) with detailed resistance component analysis (Back-pulsing Resistance, R BP ; Cake Resistance, R cake ). The study identified two critical hydrodynamic thresholds: H Target , representing sustainable capacity and the onset of accelerated fouling, and H Lim , defining the absolute operational limit. Detailed trajectory analysis revealed two primary fouling pathways: Pathway A (R BP -initiated cyclical degradation) and Pathway B (cake-dominant response to acute stress). A key finding is that the system's fouling maturity (baseline R cake , R BP ) governs its sensitivity and response pathway. Based on these insights, a Control Matrix was developed, categorizing the operation into nine statistically distinct fouling states defined by H values and resistance thresholds. This was further simplified into a practical Action Matrix to guide targeted operator interventions. The proposed model aims to improve system performance, most notably through dynamic air scour control using H Target as a practical setpoint. This research provides a data-driven methodology designed to support the optimization of operational decision-making, offering the potential to reduce energy consumption and chemical usage.