Effusion rate and the shape of aa lava flow-fields on Mount Etna

Geology ◽  
1978 ◽  
Vol 6 (8) ◽  
pp. 503 ◽  
Author(s):  
G. Wadge
Author(s):  
Christopher R. J. Kilburn ◽  
Rosaly M. C. Lopes
Keyword(s):  

1988 ◽  
Vol 93 (B12) ◽  
pp. 14759-14772 ◽  
Author(s):  
Christopher R. J. Kilburn ◽  
Rosaly M. C. Lopes
Keyword(s):  

2020 ◽  
Vol 8 ◽  
Author(s):  
Charline Lormand ◽  
Andrew J. L. Harris ◽  
Magdalena Oryaëlle Chevrel ◽  
Sonia Calvari ◽  
Lucia Gurioli ◽  
...  

Low elevation flank eruptions represent highly hazardous events due to their location near, or in, communities. Their potentially high effusion rates can feed fast moving lava flows that enter populated areas with little time for warning or evacuation, as was the case at Nyiragongo in 1977. The January–March 1974 eruption on the western flank of Mount Etna, Italy, was a low elevation effusive event, but with low effusion rates. It consisted of two eruptive phases, separated by 23 days of quiescence, and produced two lava flow fields. We describe the different properties of the two lava flow fields through structural and morphological analyses using UAV-based photogrammetry, plus textural and rheological analyses of samples. Phase I produced lower density (∼2,210 kg m−3) and crystallinity (∼37%) lavas at higher eruption temperatures (∼1,080°C), forming thinner (2–3 m) flow units with less-well-developed channels than Phase II. Although Phase II involved an identical source magma, it had higher densities (∼2,425 kg m−3) and crystallinities (∼40%), and lower eruption temperatures (∼1,030°C), forming thicker (5 m) flow units with well-formed channels. These contrasting properties were associated with distinct rheologies, Phase I lavas having lower viscosities (∼103 Pa s) than Phase II (∼105 Pa s). Effusion rates were higher during Phase I (≥5 m3/s), but the episodic, short-lived nature of each lava flow emplacement event meant that flows were volume-limited and short (≤1.5 km). Phase II effusion rates were lower (≤4 m3/s), but sustained effusion led to flow units that could still extend 1.3 km, although volume limits resulted from levee failure and flow avulsion to form new channels high in the lava flow system. We present a petrologically-based model whereby a similar magma fed both phases, but slower ascent during Phase II may have led to greater degrees of degassing resulting in higher cooling-induced densities and crystallinities, as well as lower temperatures. We thus define a low effusion rate end-member scenario for low elevation effusive events, revealing that such events are not necessarily of high effusion rate and velocity, as in the catastrophic event scenarios of Etna 1669 or Kilauea 2018.


1987 ◽  
Vol 49 (3) ◽  
pp. 527-540 ◽  
Author(s):  
J. E. Guest ◽  
C. R. J. Kilburn ◽  
H. Pinkerton ◽  
A. M. Duncan
Keyword(s):  

2019 ◽  
Vol 11 (16) ◽  
pp. 1916 ◽  
Author(s):  
Claudia Corradino ◽  
Gaetana Ganci ◽  
Annalisa Cappello ◽  
Giuseppe Bilotta ◽  
Alexis Hérault ◽  
...  

Accurate mapping of recent lava flows can provide significant insight into the development of flow fields that may aid in predicting future flow behavior. The task is challenging, due to both intrinsic properties of the phenomenon (e.g., lava flow resurfacing processes) and technical issues (e.g., the difficulty to survey a spatially extended lava flow with either aerial or ground instruments while avoiding hazardous locations). The huge amount of moderate to high resolution multispectral satellite data currently provides new opportunities for monitoring of extreme thermal events, such as eruptive phenomena. While retrieving boundaries of an active lava flow is relatively straightforward, problems arise when discriminating a recently cooled lava flow from older lava flow fields. Here, we present a new supervised classifier based on machine learning techniques to discriminate recent lava imaged in the MultiSpectral Imager (MSI) onboard Sentinel-2 satellite. Automated classification evaluates each pixel in a scene and then groups the pixels with similar values (e.g., digital number, reflectance, radiance) into a specified number of classes. Bands at the spatial resolution of 10 m (bands 2, 3, 4, 8) are used as input to the classifier. The training phase is performed on a small number of pixels manually labeled as covered by fresh lava, while the testing characterizes the entire lava flow field. Compared with ground-based measurements and actual lava flows of Mount Etna emplaced in 2017 and 2018, our automatic procedure provides excellent results in terms of accuracy, precision, and sensitivity.


2001 ◽  
Vol 63 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Robert Wright ◽  
Luke Flynn ◽  
Andrew Harris
Keyword(s):  

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Takayuki Kaneko ◽  
Atsushi Yasuda ◽  
Toshitsugu Fujii

AbstractThe effusion rate of lava is one of the most important eruption parameters, as it is closely related to the migration process of magma underground and on the surface, such as changes in lava flow direction or formation of new effusing vents. Establishment of a continuous and rapid estimation method has been an issue in volcano research as well as disaster prevention planning. For effusive eruptions of low-viscosity lava, we examined the relationship between the nighttime spectral radiance in the 1.6-µm band of the Himawari-8 satellite (R1.6Mx: the pixel value showing the maximum radiance in the heat source area) and the effusion rate using data from the 2017 Nishinoshima activity. Our analysis confirmed that there was a high positive correlation between these two parameters. Based on the linear-regression equation obtained here (Y = 0.47X, where Y is an effusion rate of 106 m3 day−1 and X is an R1.6Mx of 106 W m−2 sr−1 m−1), we can estimate the lava-effusion rate from the observation data of Himawari-8 via a simple calculation. Data from the 2015 Raung activity—an effusive eruption of low-viscosity lava—were arranged along the extension of this regression line, which suggests that the relationship is applicable up to a level of ~ 2 × 106 m3 day−1. We applied this method to the December 2019 Nishinoshima activity and obtained an effusion rate of 0.50 × 106 m3 day−1 for the initial stage. We also calculated the effusion rate for the same period based on a topographic method, and verified that the obtained value, 0.48 × 106 m3 day−1, agreed with the estimation using the Himawari-8 data. Further, for Nishinoshima, we simulated the extent of hazard areas from the initial lava flow and compared cases using the effusion rate obtained here and the value corresponding to the average effusion rate for the 2013–2015 eruptions. The former distribution was close to the actual distribution, while the latter was much smaller. By combining this effusion-rate estimation method with real-time observations by Himawari-8 and lava-flow simulation software, we can build a rapid and precise prediction system for volcano hazard areas.


1997 ◽  
Vol 58 (6) ◽  
pp. 449-454 ◽  
Author(s):  
Nicki F. Stevens ◽  
John B. Murray ◽  
Geoff Wadge

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