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 km2 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.

The spatio-temporal variability of bedload transport processes poses considerable challenges for bedload monitoring systems. One such system, the Swiss plate geophone (SPG), has been calibrated in several gravel-bed streams using direct sampling techniques. The linear calibration coefficients linking the signal recorded by the SPG system to the transported bedload can vary between different monitoring stations by about a factor of six, for reasons that remain unclear. Recent controlled flume experiments allowed us to identify the grain-size distribution of the transported bedload as a further site-specific factor influencing the signal response of the SPG system, along with the flow velocity and the bed roughness. Additionally, impact tests performed at various field sites suggested that seismic waves generated by impacting particles can propagate over several plates of an SPG array, and thus potentially bias the bedload estimates. To gain an understanding of this phenomenon, we adapted a test flume by installing a partition wall to shield individual sensor plates from impacting particles. We show that the SPG system is sensitive to seismic waves that propagate from particle impacts on neighboring plates or on the concrete bed close to the sensors. Based on this knowledge, we designed a filter method that uses time-frequency information to identify and eliminate these “apparent” impacts. Finally, we apply the filter to four field calibration datasets and show that it significantly reduces site-to-site differences between calibration coefficients and enables the derivation of a single calibration curve for total bedload at all four sites.

Understanding and predicting bedload transport is an important element of watershed management. Yet, predictions of bedload remain uncertain up to several order(s) of magnitude. In this contribution, we use a five-year continuous time-series of streamflow and bedload transport monitoring in a 13.4 km2 snow-dominated Alpine watershed in the Western Swiss Alps to investigate the hydrological drivers of bedload transport. Following a calibration of the bedload sensors, and a quantification of the hydraulic forcing of streamflow upon bedload, a hydrological analysis is performed to identify daily flow hydrographs influenced by different hydrological drivers: rainfall, snow-melt, and mixed rain and snow-melt events. We then quantify their respective contribution to bedload transport. Results emphasize the importance of mixed rainfall and snow-melt events, for both annual bedload volumes (77% in average) and peaks in bedload transport rate. Results further show that a substantial amount of bedload transport may occur during late summer and autumn storms, once the snow-melt contribution and baseflow have significantly decreased (9% of the annual volume in average). Although rainfall-driven changes in flow hydrograph are responsible for a large majority of the annual bedload volumes (86% in average), the identified melt-only events also represents a non-negligible contribution (14 % in average). Through a better understanding of the bedload magnitude-frequency under different hydrological conditions, the results of this study may help to improve current predictions of bedload transport, and we further discuss how bedload could evolve under a changing climate through its effects on Alpine watershed hydrology.