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A reliable characterization of bedload transport is required to gauge the engineering and theoretical issues related to the dynamics of sediments transport in rivers. However, while significant advances have been made in the development of monitoring techniques, robust quantitative predictive relationships have proven difficult to derive. In this article, we develop a dedicated signal processing technique aimed at improving the usage of impact plate measurements for material transport characterization. Our set‐up consists of a piezoelectric hydrophone mounted on the bottom side of a stainless steel plate, thus acting as a ‘sediment vibration sensor’. While the classical analysis with such systems is usually limited to rather simple procedures, such as impact counting, a large amount of useful information is contained in the actual waveform of the impact signal, which conveys the force and the contact time that the bedload imposes on the plate. An advanced signal processing technique called ‘first arrival atomic decomposition’ is used to improve the characterization of bedload transport by analysing the amplitude and frequency attributes of each single impact. This new processing approach proves to be well suited for bedload transport monitoring using plate systems and allows us to establish a relationship between the median grain size (D50) and the impact signal properties. This link is first observed and validated with controlled flume experiments and then applied to continuous impact records in a small gravel‐bed river during a flood event. The estimated D50 offers a novel possibility to observe the time‐varying grain size distribution of bedload transport. Copyright © 2014 John Wiley & Sons, Ltd.

The characterization of bed load transport in rivers is critical for the fundamental understanding and management of fluvial systems. Bed load monitoring based on seismological observations has recently emerged as a viable noninvasive measurement technique. However, applications of this new approach have been hitherto restricted to the case of sediment transport in steep mountain rivers. Here we further develop and evaluate the approach for a lower gradient gravel bed stream in a rural catchment using seismic observations, in situ hydroacoustic measurements of bed load motion (impact‐plate‐type device), and 3‐D hydromorphodynamic modeling. The results of this joint analysis of seismic measurements, hydroacoustic records, and sediment transport simulations show that the seismic monitoring technique for bed load transport characterization is applicable for a broader range of river systems than previously investigated.

Since its last effusive eruption in 2002, Nyiragongo has been an open-vent volcano characterized by the world's largest persistent lava lake. This lava lake provides a unique opportunity to detect pressure change in the magmatic system by analyzing its level fluctuations. We demonstrate that this information is contained in the seismic and infrasound signals generated by the lava lake's activity. The continuous seismo-acoustic monitoring permits quantification of lava lake dynamics, which is analyzed retrospectively to identify periods of volcanic unrest. Synchronous, high-resolution satellite SAR (Synthetic Aperture Radar) images are used to constrain lava lake level by measuring the length of the SAR shadow cast by the rim of the pit crater where the lava lake is located. Seventy-two estimations of the lava lake level were obtained with this technique between August 2016 and November 2017. These sporadic measurements allow for a better interpretation of the continuous infrasound and seismic data recorded at the closest station (∼6 km from the crater). Jointly analyzed seismo-acoustic and SAR data reveal that slight changes in the spectral properties of the continuous cross-correlated low-frequency seismo-acoustic records (and not solely single events) can be used to track fluctuations of the lava lake level on a daily and hourly basis. We observe that drops of the lava lake and the appearance of significant long period (LP) "lava lake" events are a consequence of a probable deep lateral magma intrusion beneath Nyiragongo, which induces changes in its shallow plumbing system. In addition to contributing to understanding lava lake dynamics, this study highlights the potential to continuously monitor pressure fluctuations within the magmatic system using a single seismo-acoustic station located several kilometers from the vent.

Nyiragongo volcano (D.R. Congo), 3,470 m a.s.l., located in the Virunga Volcanic Province (VVP) along the western branch of the East African rift, is one of the few volcanoes on Earth that several times has hosted a lava lake with decadal persistence, here inside the ∼1.2-km wide summit crater (Lev et al., 2019; Figure 1a). Flank eruptions and associated drainage of its lava lake occurred at least three times,

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Classical mechanisms of volcanic eruptions mostly involve pressure buildup and magma ascent towards the surface1. Such processes produce geophysical and geochemical signals that may be detected and interpreted as eruption precursors1–3. On 22 May 2021, Mount Nyiragongo (Democratic Republic of the Congo), an open-vent volcano with a persistent lava lake perched within its summit crater, shook up this interpretation by producing an approximately six-hour-long flank eruption without apparent precursors, followed—rather than preceded—by lateral magma motion into the crust. Here we show that this reversed sequence was most likely initiated by a rupture of the edifice, producing deadly lava flows and triggering a voluminous 25-km-long dyke intrusion. The dyke propagated southwards at very shallow depth (less than 500 m) underneath the cities of Goma (Democratic Republic of the Congo) and Gisenyi (Rwanda), as well as Lake Kivu. This volcanic crisis raises new questions about the mechanisms controlling such eruptions and the possibility of facing substantially more hazardous events, such as effusions within densely urbanized areas, phreato-magmatism or a limnic eruption from the gas-rich Lake Kivu. It also more generally highlights the challenges faced with open-vent volcanoes for monitoring, early detection and risk management when a significant volume of magma is stored close to the surface.