Lahar monitoring on active volcanoes is challenging, and the ever changing environment leads to inconsistent results that hamper a warning systems ability to characterize the flow event properly. Therefore, more data, new methods, and the use of different sensors needs to be tested, which could lead to improvements in warning capabilities. Here, we present data from a 3-component broadband seismometer and video camera installed 3 m from the Lumbre channel on Volcán de Colima, Mexico to understand rheology differences within multiple lahar events that occurred in late 2016. We examine differences in frequency and directionality from each seismic component. Results indicate an increase in peak frequency above background in each component when a lahar nears the sensor, and a decrease in overall peak frequency when transitioning from a streamflow to a higher concentration flow. The seismic frequency distribution for the cross-channel component for the streamflow has a wider range compared with the lahar events. In contrast, the peak spectral frequency of the streamflow is narrower in comparison to the lahar events in the flow parallel and vertical directions. Estimated directionality ratios (cross-channel signal divided by flow parallel signal) yielded further evidence for a rheologic change between streamflow and lahars. Directionality ratios >1 were calculated for each lahar, and <1 for streamflow. Finally, we demonstrate from component analyses that channelization or freedom of movement in the cross-channel, bedload transport in the flow parallel, and bed composition in the vertical directions are possibly the main drivers in the peak spectral frequency output of lahars. The results described here indicate that using all three components may provide important information about lahar dynamics, which may be useful for automatic detection and warning systems, and using all three components should be encouraged.
At approximately 09:36 UTC on 27 April 2016, a phreatic eruption occurred on Whakaari Island (White Island) producing an eruption sequence that contained multiple eruptive pulses determined to have occurred over the first 30 min, with a continuing tremor signal lasting ~ 2 h after the pulsing sequence. To investigate the eruption dynamics, we used a combination of cross-correlation and coherence methods with acoustic data. To estimate locations for the eruptive pulses, seismic data were collected and eruption vent locations were inferred through the use of an amplitude source location method. We also investigated volcanic acoustic-seismic ratios for comparing inferred initiation depths of each pulse. Initial results show vent locations for the eruptive pulses were found to have possibly come from two separate locations only ~ 50 m apart. These results compare favorably with acoustic lag time analysis. After error analysis, eruption sources are shown to conceivably come from a single vent, and differences in vent locations may not be constrained. Both vent location scenarios show that the eruption pulses gradually increase in strength with time, and that pulses 1, 3, 4, and 5 possibly came from a deeper source than pulses 2 and 6. We show herein that the characteristics and locations of volcanic eruptions can be better understood through joint analysis combining data from several data sources.
A frequently applied amplitude source location (ASL) method is here calibrated and optimized by using active seismic sources located at the surface of a dry stream channel. The ASL produced location discrepancies larger than 1.0 km laterally and 500 m in depth by using independently determined velocity model, attenuation, and site amplification factors (AFs). Sensitivity tests for ASL input parameters show that attenuation and velocity have moderate influence on the location but are easy to independently constrain. AFs are shown to strongly influence the location, and their application may introduce substantial location uncertainties. Model uncertainties are accommodated with either lateral or depth changes depending on the input parameters, station corrections, and the source‐station geometry.
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