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Debris flows are extremely rapid landslides whose complex dynamics remain only partially constrained, largely due to the challenges associated with acquiring direct measurements in the field. Modern monitoring stations typically include cameras that, despite their relatively low cost, can provide highly valuable information for characterising recorded events. Recent studies have shown that Particle Image Velocimetry (PIV) algorithms, when paired with suitable orthorectification techniques to correct non-zenithal acquisition geometries, can serve as effective methods for reconstructing the surface velocity field of flow-like landslides, including debris flows.In the present work, a PIV-based workflow is employed to analyse a debris-flow event that occurred on 22 October 2022 in the Blè Stream catchment, an active basin in the Camonica Valley (Lombardia, Italian Alps) within the municipality of Ono San Pietro. The 3.5 km² catchment reaches a maximum elevation of 2527 m a.s.l. and features a 2.9 km-long main channel, instrumented with several monitoring stations, each equipped with cameras and flow-depth radar sensors that documented the event.The sequential application of two open-source MATLAB tools, PIVlab (Thielicke & Stamhuis 2014) and RIVeR (Patalano et al. 2017), yielded frame-by-frame, orthorectified surface velocity fields at each station. These velocity fields were integrated with cross-sectional areas derived from high-resolution pre- and post-event LiDAR and drone surveys, along with measured flow levels, to compute instantaneous discharge at key reference sections. By consistently applying this frame-by-frame procedure along the channel, while carefully accounting for the main sources of uncertainty associated with the continuously changing section geometry and the tendency of surface velocity to overestimate the actual depth-averaged velocity, depending on flow rheology, a range of plausible hydrographs was obtained at each monitoring station. These hydrographs, which provide estimates of the volume of material that passed through each section during the event, enabled a quantitative assessment of the relationship between the triggering water volume in the upstream reach and the fully-developed debris flow volume observed downstream, as well as estimates of entrainment rates along different sectors of the channel. References:Patalano A, García CM, Rodríguez A (2017) Rectification of image velocity results (RIVeR): a simple and user-friendly toolbox for large-scale water surface particle image velocimetry (PIV) and particle tracking velocimetry (PTV). Comput Geosci 109:323–330. https://doi.org/10.1016/j.cageo.2017.07.009. Thielicke W, Stamhuis EJ, 2014. PIVlab – towards user-friendly, affordable and accurate digital Particle Image Velocimetry in MATLAB. J. Open Res. Softw. 2 http://dx.doi.org/10.5334/jors.bl.