Seasonal bottom water hypoxia is a major driver of coastal ecosystem degradation worldwide, driven by the nonlinear interplay of physical stratification, pelagic eutrophication, and benthic oxygen consumption. Although Sediment Oxygen Demand (SOD) accounts for 30–80% of bottom-water oxygen depletion and acts as a critical driver of hypoxia, its dynamic regulation remains poorly quantified due to observational constraints and the prevalent reliance on static parameterizations in models. To address this gap, we introduce a high-resolution, fully coupled three-dimensional framework (SCHISM-SED3D-CoSiNE-SFM). This model advances SOD from a static parameter to a prognostic variable dynamically driven by bottom-water dissolved oxygen, temperature, and organic matter supply. This framework is applied to the Pearl River Estuary (PRE), a globally representative eutrophic system characterized by intense physical–biogeochemical interactions. Key findings reveal a pronounced bimodal seasonal cycle in sediment oxygen demand (SOD). Summer SOD was suppressed by kinetic limitation as bottom-water dissolved oxygen (DO) declined, whereas autumn stratification breakdown drove bottom re-oxygenation and a secondary SOD peak. Crucially, our non-steady-state framework successfully captured synoptic-scale variability modulated by spring-neap tides, which are typically damped in traditional models. DO budget analysis established SOD (averaging 51 mmol O₂ m⁻² d⁻¹) as the dominant benthic sink, driving 94% of bottom-layer biochemical oxygen consumption. Sensitivity experiments exposed a counterintuitive response: a 60% nutrient reduction paradoxically expanded the hypoxic area, as the immediate collapse of pelagic oxygen production outpaced the slow decline in SOD sustained by legacy organic matter. Furthermore, XGBoost-SHAP analysis identified bottom-water temperature as the primary seasonal driver and defined critical thresholds for stratification and SOD (40–50 mmol O₂ m⁻² d⁻¹). These thresholds delineate two distinct hypoxia-triggering regimes governed either by physical barriers or biogeochemical depletion. Ultimately, this study provides a robust coupled modeling framework for understanding, forecasting, and managing coastal hypoxia in strongly coupled estuarine systems.
 

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