Scaling up bedload monitoring: a passive acoustic approach for large river systems

Quantifying bedload transport at the catchment scale of large rivers remains a critical challenge in river management and sediment budget assessment. Traditional direct sampling methods are logistically demanding and provide limited spatial-temporal coverage. This study demonstrates that passive acoustic monitoring using hydrophones can reliably quantify bedload fluxes across entire river catchments. Applied to the Loire River system (France), passive acoustic measurements were conducted at seven stations from 2018 to 2025, establishing bedload rating curves for discharge conditions ranging from low flow to two-year return floods. Monte Carlo sensitivity analysis demonstrates that stratified sampling with as few as four measurements across the discharge range produces reliable rating curves (<20 % error relative to reference curves with 32 points). Independent cross-validation using 16 semi-empirical transport formulas and long-term morphological change analysis (1995-2020) shows order-of-magnitude agreement in flux estimates and spatial coherence in erosion-deposition patterns. Results reveal strong spatial variability (5000 to 455,000 tons/year) reflecting tributary contributions and anthropogenic pressures. The approach provides a practical pathway for establishing sustained bedload monitoring networks, addressing critical data gaps in sediment flux quantification for river management and morphodynamic prediction.