Seismic characterization of hyperconcentrated flows in a volcanic environment

Abstract

We present direct observations and monitoring data of a hyperconcentrated flow that occurred along La Lumbre ravine, one of the most active channels of Volcán de Colima in Mexico. Flow properties were inferred from video images and seismic data recorded by a geophone installed outside the channel. We collected flow samples 400 m upstream from the monitoring station and analyzed the variation of sediment concentration and grain-size distribution over time. A joint analysis of hydrological (i.e. flow velocity, wetted perimeter) and rheological (i.e. yield stress τ y and dynamic viscosity μ m ) parameters was performed to characterize the flow. Different flow regimes and sediment transport processes were identified and analyzed in comparison with both the amplitude and spectral features of the seismic signal. We observed differing sediment concentrations at the same discharge, suggesting a decoupling between sediment transport processes and discharge for low-magnitude flows. A straightforward correlation was found between the amplitude of the seismic signal and the sediment concentration, and a value of 1.8 × 10 À3 mm/s was identified that can be used as a threshold to recognize the hyperconcentrated phase of the flow. This information was tested on the complete seismic dataset gathered at La Lumbre ravine during the 2015 rainy season. We identified the transition from streamflow to hyperconcentrated flow (and/or vice versa) in 16 low-magnitude events and we validated this result using the video recordings. The correlation between seismic amplitude and sediment concentration is valid at La Lumbre ravine but would need to be tested in other locations for the development of automatic flow classification methods. This work contributes to standardized seismic methods for characterizing flow processes in volcanic environments, also for the development of lahar early warning systems. Copyright

Hydrological control of large hurricane-induced lahars: evidence from rainfall-runoff modeling, seismic and video monitoring

“…4). The initial water flow rapidly evolved in a hyperconcentrated flow (Coviello et al, 2018) and several front waves were observed during flooding (I and II, Fig. 8b) for which an average flow discharge of 80-100 m 3 s −1 was estimated, and two main pulses arrived at 23:30 and 00:00 (24 October), with 6 m depth block-rich fronts and maximum flow discharges of 900 m 3 s −1 (III, IV, V and VI, Fig.…”

“…1). Both stations consist of a 12 m high tower with a directional antenna transmitting data in real time to RESCO facilities, a camcorder recording images every 2-4 s with a 704 × 480 pixel resolution, a rain gauge coupled with a soil moisture sensor and a 10 Hz geophone (Vázquez et al, 2016a;Coviello et al, 2018). (Table 1).…”

“…Since 2011 a visual monitoring system has been installed on the Montegrande and La Lumbre ravines (Fig. 1), based on which a quantitative characterization of some events (i.e type of flow, velocity, flow discharge, flow fluctuation) has been possible (i.e., Vázquez et al, 2016a;Coviello et al, 2018). The aim of the present paper is to better understand the initiation processes of large lahars and their dynamic behavior, especially during hurricane events, when more damage has been observed in inhabited areas.…”

Seismic Characterization of Debris Flows: Insights into Energy Radiation and Implications for Warning

“…This is also consistent with the estimations made by Berrocal et al () of the seismic energy released by the large Mantaro landslide (complex rockslide, volume of 1.3 km 3 , surface wave magnitude M S = 4.1), which is about 0.01% of the kinetic energy, which is in turn about 1% of the potential gravitational energy. Boulder‐rich fronts are the dominant seismic source of debris flows (Coviello et al, ; Turowski et al, ; Vázquez et al, ). Length and mass distribution within a debris flow wave do not change over time scales; consequently, different amplitudes are due to either different front‐receiver distances or different kinetic energy values.…”

“…The algorithm parameters would probably need a refinement to be adapted to local conditions (channel geometry, flow rate, and distance between sensors). Furthermore, flow rheology has a strong impact on the propagation of ground vibrations through the landslide body (Bertello et al, ), and a large, slow‐moving debris flow can be seismically quieter than a much smaller, fast‐moving hyperconcentrated flow (Coviello et al, ). In this context, other monitoring data would be precious to characterize both debris flow processes and other possible sources of false alarms in a channel where an operational EWS is needed, especially at a first stage when the monitoring data set is small.…”