Anatomy of an Alpine bedload transport event: a watershed-scale seismic-network perspective

Abstract

The way Alpine rivers mobilize, convey and store coarse material during high-magnitude events is poorly understood, notably because it is difficult to obtain measurements of bedload transport at the watershed scale. Seismic sensor data, evaluated with appropriate seismic physical models, can provide that missing link by yielding absolute time-series of bedload transport.Low cost and ease of installation allows for networks of sensors to be deployed, providing continuous, watershed-scale insights into bedload transport dynamics. Here, we deploy a network of 24 seismic sensors to capture the motion of coarse material in a 13.4 km 2 Alpine watershed during a high-magnitude bedload transport event. First, we benchmark the seismic inversion routine with an independent time-series obtained with a calibrated acoustic system. Then, we apply the procedure to the other seismic sensors across the watershed. Spatially-distributed time-series of bedload transport reveal a relative inefficiency of Alpine watersheds in evacuating coarse material, even during a relatively infrequent high-magnitude bedload transport event.Significant inputs measured for some tributaries were rapidly attenuated as the main river crossed less hydraulically-efficient reaches, and only a comparatively negligible proportion of the total amount of material mobilized in the watershed was exported at the outlet. Cross-correlation analysis of the time-series suggests that a faster moving water wave (re-)mobilizes local material and bedload is expected to move slower, and over shorter distances. Multiple periods of competent flows are likely to be necessary to evacuate the coarse material produced throughout the watershed during individual source-mobilizing bedload transport events.

Anatomy of an Alpine Bedload Transport Event: A Watershed‐Scale Seismic‐Network Perspective

“…The seismic and SPG bedload transport data presented in the study (Figures made with Matlab v. R2019a and Adobe Illustrator 2023) will be made available online on the EnviDat repository https://www.envidat.ch/dataset/ sediment-transport-observations-in-swiss-mountain-streams (Antoniazza et al, 2023) upon publication of the manuscript. P1LAP2_194974 awarded to GA) for supporting this work.…”