Exploiting LSPIV to assess debris-flow velocities in the field

Theule, Joshua; Crema, Stefano; Marchi, Lorenzo; Cavalli, Marco; Comiti, Francesco

doi:10.5194/nhess-18-1-2018

Cited by 45 publications

(18 citation statements)

References 36 publications

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“…The main front of the debris flow that occurred on 15 July 2014 was preceded by a precursory liquid surge, which is clearly visible in the amplitude curves and precedes the subsequent surges ( Figure 10 and Movie S1 in the supporting information). Five subsequent surges can be identified featuring a sequence of roll waves with very different sediment concentrations and boulders clustering (Theule et al, 2018). The duration of the whole debris flow (around 25 min) was slightly longer than the 2013 event, and the volume (11,600 m 3 ) was also moderately larger (Coviello et al, 2019).…”

Section: Debris Flow Detectionmentioning

confidence: 99%

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

et al. 2019

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Debris flows represent a major hazard in mountainous areas, due to their rapid motion along steep channels and to the transport of large sediment volumes, including large boulders. In this paper, we present data of channelized debris flows characterized by different velocities and sediment concentrations recorded in an instrumented channel reach of the Gadria basin (eastern Italian Alps). From the analysis of the seismic energy produced by the interaction of solid particles with channel boundaries, we show that (i) the peak amplitudes are representative of the kinetic energy of each surge and (ii) most energy transfer occurs during the passage of the surge fronts. Then, we propose a debris flow detection algorithm based on the amplitude information gathered from a linear array of geophones installed along the channel. The short time average over long time average ratio of the seismic signal is used to early detect the debris flow occurrence in a continuous stream of seismic data. The algorithm recognizes moving, long‐lasting sources of ground vibration (i.e., debris flows) and filters out different seismic sources (i.e., anthropic noise, earthquakes, and rockfalls). The alarm is triggered when the short time average/long time average threshold is exceeded on two geophones, progressively with time from upstream to downstream. The algorithm is employed in the early warning system installed for research purposes at Gadria. Complementary data (rainfalls, flow stage measurements, and video recordings) permitted a detailed event characterization and alarm validation. During three monitoring seasons, all debris flows were successfully detected, with the alarm lasting for their entire duration, and no false positives were produced.

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Section: Debris Flow Detectionmentioning

confidence: 99%

“…The 8 June 2015 event lasted about 50 min and featured a volume of 12,600 m 3 (Coviello et al, 2019). This debris flow was characterized by a highly variable concentration of the surges (Theule et al, 2018). The first front carried many logs, while the second surge was characterized by a slower, muddier flow front (Figure 11).…”

Section: 1029/2018jf004683mentioning

confidence: 99%

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

et al. 2019

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“…no significant surges could be found to calculate flow velocities using maximum values, and the cross-correlation most likely leads to overestimating velocities. respectively seem unrealistically high based on previous results from the Gadria (Theule et al, 2018;Coviello et al, 2020).…”

Section: Velocity Estimationmentioning

confidence: 83%

Comment on nhess-2020-411

2021

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The estimation of debris-flow velocity and volume is a fundamental task for the development of early warning systems, the design of control structures and other mitigation measures. Previous analysis of the seismic energy produced by debris flows showed that the peak amplitudes are representative of the kinetic energy of each surge and debris-flow discharge can be therefore estimated based on seismic signals. Also, the debris-flow velocity can be calculated using seismic data recorded at two spatial separated stations located along the channel by the use of cross-correlation. This work provide a first approach for estimating the total volume of debris flows based on the seismic signal detected with simple, low-cost geophones installed along the debris-flow channel. The developed methods was applied to seismic data collected on three different test sites in the Alps: Gadria (IT), Lattenbach (AT), and Cancia (IT). An adaptable cross-correlation time window was used, which can offer a better estimation of the velocity compared to a constant window length. The analyses of the seismic data of 14 debris flows that occurred from 2014 to 2018 shows the strong control of the sampling rate and the sensor-distance on the velocity estimation.A simple approach based on a linear relation between square of the seismic amplitude and the event magnitude is proposed for a first order estimation of the debris-flow magnitude. IntroductionWith the rapid socio-economic development of European mountain areas, the automatic detection and identification of mass movements like landslides, debris flows, and avalanches become of paramount importance for risk mitigation. Technological development has rapidly advanced during the last decade, as well as the conceptual advancements brought by former debrisflow research, making the implementation of monitoring devices for research, early warning and alarm purposes more and more effective and feasible (Hürlimann et al., 2019). Past studies showed that such processes induce characteristic seismic and acoustic signals, the latter mostly in the infrasonic spectrum which can thus be used for event detection. Several investigations have already addressed signal processing and detection methods based on seismic (e.g.,

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“…The specific reach studied provided the necessary natural surface patterns for image analysis (surface ripples), but further measurements will be conducted in different reaches in future where there are no natural surface patterns. Various vegetation debris, such as tree branches and leaves, will be examined as surface flowing particles, to enable us to apply these image-based methods [75]. These measurements will be obtained by coupling current flow meter measurements for the entire width of the river, in order to evaluate the results of the image-based methods.…”

Section: Discussionmentioning

confidence: 99%

UAVs for Hydrologic Scopes: Application of a Low-Cost UAV to Estimate Surface Water Velocity by Using Three Different Image-Based Methods

Koutalakis

Tzoraki

Zaimes

2019

Drones

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Stream velocity and flow are very important parameters that must be measured accurately to develop effective water resource management plans. There are various methods and tools to measure the velocity but, nowadays, image-based methods are a promising alternative that does not require physical contact with the water body. The current study describes the application of a low cost unmanned aerial vehicle that was selected in order to capture a video over a specific reach of Aggitis River in Greece. The captured frames were analyzed by three different software (PIVlab, PTVlab, and KU-STIV) in order to estimate accurately the surface water velocity. These three software also represent three different image-based methodologies. Although there are differences among these three methods, the analysis produced similar trends for all. The velocity ranged between 0.02 and 3.98 m/s for PIVlab, 0.12 and 3.44 m/s for PTVlab, and 0.04 and 3.99 m/s for KU-STIV software. There were parts, especially in the existing vegetation, where differences were observed. Further applications will be examined in the same or different reaches, to study the parameters affecting the analysis. Finally, the image-based methods will be coupled with verification measurements by a current meter to produce more rigorous results.

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Exploiting LSPIV to assess debris-flow velocities in the field

Cited by 45 publications

References 36 publications

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

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

Comment on nhess-2020-411

UAVs for Hydrologic Scopes: Application of a Low-Cost UAV to Estimate Surface Water Velocity by Using Three Different Image-Based Methods

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