Applying dense seismic array monitoring to locate fluvial processes during floods in a braided river reach

Over the last decade, seismic techniques have provided unique observational constraints on Earth surface processes. In particular, dense seismic array monitoring has recently allowed the detailed investigation of noise sources and their spatiotemporal dynamics. Despite their large potential, these approaches have not yet been applied for the monitoring of fluvial processes. In a context where traditional methods often do not provide data with adequate temporal and spatial resolution, the use of dense arrays could allow the identification and tracking of different sources of river-induced seismic ground vibrations (e.g. turbulence and bedload transport), which would provide insight in river functioning and morphological evolution.

Here, we study the potential of dense seismic array monitoring by analysing data from a 4-month long field survey, which we conducted in summer 2019 along a 600-m long braided reach of the Séveraisse river (French Alps). We installed a network of 40 to 80 seismometers on both river banks, predominantly deployed in 4-seismometer subarrays, and we supplement these seismic observations with flow gauging measurements and time-lapse imagery covering the study area. We present a preliminary analysis that focuses on a high-flow event that occurred at the end of the melt season. During this event, we observe impulsive signals that are coherently detected over the array, and which we interpret as being associated with the bedload transport of clusters of coarse grains. Through phase-delay analysis we are able to locate episodes of motion at high temporal resolution and investigate their spatiotemporal dynamics with respect to river morphology and morphological changes observed from the time-lapse images. Our work demonstrates the unique capability of using dense seismic arrays to better understand the fluvial processes that play an important role in storing and transferring sediments in braided rivers.