EGU24-10832, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Estimating the hydrograph of a debris flow event through low-cost field camera monitoring and Digital Particle Image Velocimetry

Alessandro Zuccarini1, Elena Ioriatti1, Marco Redaelli2, Luca Albertelli3, Mauro Reguzzoni4, Edoardo Reguzzoni4, Nikhil Nedumpallile Vasu5, Vanessa Banks5, Elisabeth Bowman6, Alessandro Leonardi6, and Matteo Berti1
Alessandro Zuccarini et al.
  • 1University of Bologna, Biological Geological and Environmental Sciences (BiGeA), BOLOGNA, Italy (
  • 2Regione Lombardia, Direzione Generale Territorio e Sistemi Verdi, Piazza Città di Lombardia 1, 20124 Milano, Italia
  • 3Land & Cogeo, Via Manifatture 29/G, 2504 Darfo Boario Terme, Brescia, Italia
  • 4Hortus S.r.l., Via Goffredo Mameli 48, 21013 Gallarate, Varese, Italia
  • 5British Geological Survey, Nicker Hill, Keyworth, Nottingham NG12 5GG, UK
  • 6Department of Civil and Structural Engineering, University of Sheffield, Sheffield, UK

Debris flows are extremely fast landslides whose complex dynamics are still not fully understood, primarily due to challenges in acquiring direct field measurements. In modern monitoring stations, cameras represent cost-effective data sources, providing essential information for characterising the documented events.

Digital Particle Image Velocimetry (DPIV) algorithms have been extensively employed in the literature to reconstruct velocity fields in laboratory physical models under controlled conditions. However, the resolution of field camera footage is typically suboptimal due to weather and lighting conditions, as well as non-zenithal recording geometry, hindering a straightforward application of DPIV. Landslide flume experiments, conducted in collaboration with the Civil and Structural Engineering Department of the University of Sheffield and the British Geological Survey office in Keyworth, revealed that also suboptimal quality footage can be effectively utilised provided appropriate orthorectification algorithms are applied to eliminate the original image distortions.

In this study, the methodology established through the laboratory flume experiments was applied to analyse a real debris flow event in an active catchment in the Camonica Valley (Lombardia, Italian Alps) between the municipalities of Ono San Pietro and Cerveno. The Blè Stream catchment, with a drainage area of approximately 3.5 km², a maximum elevation of 2,527 m a.s.l.,  and a main channel length of about 2.9 km, experienced a debris flow event on October 22, 2022. This was documented by several monitoring stations equipped with cameras and a flow-depth radar sensor along the main channel track.

The frame-by-frame orthorectified surface velocity field of the recorded debris flow was obtained through a DPIV analysis, employing two open-source tools in Matlab sequentially: PIVlab (Thielicke & Stamhuis 2014) and RIVeR (Patalano et al. 2017). The discharge at a specific instant along a reference section was computed as the product of the reconstructed flow velocity distribution and the area of the section defined by its topography, known from pre- and post-event LiDAR and drone surveys, and the measured flow level. Throughout this phase, careful consideration was given to assessing the primary sources of uncertainty arising from the continuously changing section geometry and the measured surface velocity, which typically overestimates the actual depth-averaged velocity, with a divergence depending on flow rheology. Calculating the discharge for each frame along the reference section ultimately yielded the hydrograph of the documented debris flow event, along with an estimate of the involved volume of material.



Patalano A, García C, Rodriguez 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). Computers and Geosciences. 109. 323-330. 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 

How to cite: Zuccarini, A., Ioriatti, E., Redaelli, M., Albertelli, L., Reguzzoni, M., Reguzzoni, E., Nedumpallile Vasu, N., Banks, V., Bowman, E., Leonardi, A., and Berti, M.: Estimating the hydrograph of a debris flow event through low-cost field camera monitoring and Digital Particle Image Velocimetry, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10832,, 2024.