Extracting total grain size distribution data for ash fall deposits from densely populated volcanoes (Chaparraristique volcano, El Salvador)
Extracting total grain size distribution data for ash fall deposits from densely populated volcanoes (Chaparraristique volcano, El Salvador)
批准号:
NE/M005003/1
负责人:
Richard Brown
金额:
$4.43万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2014
资助国家:
英国
项目状态:
已结题
起止时间:
2014 至 --
中文摘要
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英文摘要
As recent eruptions in Iceland have shown, volcanic ash clouds present immediate hazards to people, infrastructure and aviation. How volcanic clouds are dispersed through the atmosphere is dependent on both the characteristics of the eruption (e.g., volume and rate of eruption, grain size, height of eruption column) and atmospheric conditions (e.g., wind speed and direction). Volcanic Ash Advisory Centres (VAAC) use computer models to forecast ash clouds dispersal during an eruption, but in order for these models to be accurate, they require high quality datasets gained from real-time observations (satellite, airborne and ground-based) and detailed datasets from previous similar eruptions (e.g. grainsize distribution). Such datasets are scarce and are a significant source of uncertainty in model outputs. There are only a handful of high quality datasets available globally and these are skewed towards large eruptions and silicic compositions. Smaller volume eruptions, which occur on a higher frequency and are still of considerable impact on a regional and sub-regional scale, are poorly represented in these datasets. This is due to the short-lived nature of the eruptions, which reduces opportunities for observation, and the thinner deposits are more quickly eroded. Opportunities to gather quantitative, field-derived data from a recent eruption is extremely valuable to science. On the 29th December 2013, Chaparrastique volcano (aka Volcán San Miguel) in El Salvador, erupted and produced a ~10 km-high plume that drifted across the country and deposited ash > 100 km away. It is one of El Salvador's most active volcanoes and historical records indicate that this was its most powerful eruption for 300 years. Five thousand people were evacuated within a 3 km radius of the volcano. The volcano lies 12 km from El Salvador's third largest city, San Miguel. Despite the many historical eruptions, and the high risk posed, few quantitative data exist for the volcano and little is known about its geologic history. Ash layers from historic eruptions are poorly preserved due to the tropical climate. This research will obtain a unique quantitative dataset on the deposits from the 2013 Chaparraristique eruption, to better understand the causes of the eruption, find out why it was more powerful than its past eruptions, and fully characterise the deposits before they are removed by rainfall. Some of the data will be used to create probabilistic hazard maps for the volcano. These will help the local authorities plan for similar eruptions from the volcano in the future under a range of wind conditions. Usefully, the eruption occurred during the dry season and the ash deposits remain reasonably well preserved on the ground. There is an urgent need collect data prior to the wet season at the end of April that will strip away the ash and increase the risk of lahars (rain-triggered ash slurries). The research objectives are: (1) obtain a comprehensive ash fall deposit dataset; (2) construct thickness and grainsize maps for the ash fall deposit; (3) calculate important eruption parameters (total grain size distribution, constrain dispersion, eruption volume, column height and mass discharge rates); (4) calibrate these with visual and remote observations of 29th December eruption plume; (5) carry out textural, optical, morphological and geochemical characterisations of the ash to investigate eruption processes. Some of these data will be used to model the ash dispersion and develop probabilistic hazard assessments for Chaparrastique using freely available analytical Volcanic Ash Transport and Dispersal Models (VATDM). We will disseminate these results to interested authorities in El Salvador, and critical data such as grainsize distribution and refractive index will be distributed to the Washington VAAC and globally to ensure maximum impact. The results will help agencies worldwide in understanding the hazards posed by similar eruptions.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
Reconstruction of the 29th December 2013 eruption of San Miguel volcano, El Salvador, using video, photographs, and pyroclastic deposits
使用视频、照片和火山碎屑沉积物重建 2013 年 12 月 29 日萨尔瓦多圣米格尔火山喷发的情况
DOI:
10.30909/vol.05.02.271293
发表时间:
2022
期刊:
Volcanica
影响因子:
--
作者:
[Brown R]
通讯作者:
Brown R
DOI:
10.1016/j.chemgeo.2016.11.015
发表时间:
2017-01
期刊:
Chemical Geology
影响因子:
3.9
作者:
[P. Scarlato;S. Mollo;E. Bello;A. Quadt;Richard J. Brown;E. Gutiérrez;B. Martinez-Hackert;P. Papale]
通讯作者:
P. Scarlato;S. Mollo;E. Bello;A. Quadt;Richard J. Brown;E. Gutiérrez;B. Martinez-Hackert;P. Papale
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Support for Operations of the National Research Council's Board on Sustainable Development
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Support for Operations of the National Research Council's Board on Sustainable Development
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资助金额:$1.0万
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Corrosion Resistant Nitride Coatings
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Survey and Inventory of Selected Arthropods in the MidSouth Coastal Plain
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Survey and Inventory of Selected Arthropods in the MidSouth Coastal Plain
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Site-Directed Bioreagent Immobilization for Development of Microbiosensor Arrays
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国内基金
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