| Project Detail |
Debris flows are sediment-water mixtures, which move down steep torrent beds or mountain slopes in an uncontrolled fashion. Much of the destructive potential of debris flows relates to their surging behavior, which can cause large peak discharge and flow dynamic complexity that his hard to reproduce with numerical models. Here we focus on the roll wave phenomenon, which is inherent to many shallow open channel flows including debris flows. Roll waves manifest themselves as flow depth perturbations traveling faster downstream than the debris flow particles, which allows them to amplify each other as they approach the flow front. Surging behavior of the flow front may result. Whereas roll waves are widely observed in debris flows, their dynamic behavior is difficult to constrain because this would require many measurement points along their flow path, which for natural debris flows is difficult to realize. Therefore, systematic studies are typically limited to theoretical or laboratory investigations whose findings are difficult to test under large-scale conditions.In this project we propose to leverage new developments in passive seismic sensing to obtain roll wave observations along extended stretches of a natural debris flow channel in Switzerland. We will use Distributed Acoustic Sensing (DAS) by which particle-ground impacts and instantaneous weight of a debris flow can be measured within a fiberoptic cable installed parallel to the torrent. Roll wave propagation can thus be tracked and wave velocities, generation and destruction mechanisms as well as the effect on overall debris flow dynamics can be studied. We will supplement these measurements with drone-derived differences in digital elevation models constraining debris flow erosion and deposition as well as state-of-the-art point measurements from flow stage gauges and a force plate. With these measurements we will feed numerical models to include roll waves and surging behavior, which is more realistic than smooth flow predicted by commonly used numerical schemes. Grant number 215631 Funding scheme Project funding Call Projects MINT 2022 October Approved amount 462,283 CHF |
