Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes

Data scarcity is one of the main sources of uncertainty in eruption forecasting. Due to multiple factors, such as the location or the poor preservation of deposits, numerous volcanoes have incomplete records of eruptions. In this thesis, I explore statistical approaches to overcome data scarcity whe...

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Main Author: Burgos, Vanesa
Other Authors: Susanna Jenkins
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166192
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1661922023-05-02T23:54:06Z Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes Burgos, Vanesa Susanna Jenkins Asian School of the Environment Earth Observatory of Singapore susanna.jenkins@ntu.edu.sg Science::Geology::Volcanoes and earthquakes Data scarcity is one of the main sources of uncertainty in eruption forecasting. Due to multiple factors, such as the location or the poor preservation of deposits, numerous volcanoes have incomplete records of eruptions. In this thesis, I explore statistical approaches to overcome data scarcity when forecasting eruptions at data-limited volcanoes. Firstly, I analysed first recorded eruptions from Holocene volcanoes to provide relative completeness dates while discussing the factors causing eruption under-recording. Secondly, I estimated the average recurrence interval of first recorded eruptions at a regional level and the annual probability of eruption at individual potentially active volcanoes from several regions of Asia-Pacific. Lastly, I identified analogues and estimated the f-M relationship for Melimoyu (Chile) by applying a quantitative and objective approach based on hierarchical clustering and probabilistic modelling. This thesis provides insights into the challenges of forecasting eruptions at under-studied volcanoes and presents numerical solutions for overcoming data scarcity. Doctor of Philosophy 2023-04-17T02:35:06Z 2023-04-17T02:35:06Z 2022 Thesis-Doctor of Philosophy Burgos, V. (2022). Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166192 https://hdl.handle.net/10356/166192 10.32657/10356/166192 en 10.21979/N9/KNMKAJ 10.21979/N9/ZPAN0X 10.21979/N9/CLOY0S 10.21979/N9/73C0II 10.21979/N9/9DL728 10.21979/N9/4JLCSO 10.21979/N9/KG70CC 10.21979/N9/PKQ3UC 10.21979/N9/J8PLXZ 10.21979/N9/NSVP5W This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0). application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Geology::Volcanoes and earthquakes
spellingShingle Science::Geology::Volcanoes and earthquakes
Burgos, Vanesa
Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
description Data scarcity is one of the main sources of uncertainty in eruption forecasting. Due to multiple factors, such as the location or the poor preservation of deposits, numerous volcanoes have incomplete records of eruptions. In this thesis, I explore statistical approaches to overcome data scarcity when forecasting eruptions at data-limited volcanoes. Firstly, I analysed first recorded eruptions from Holocene volcanoes to provide relative completeness dates while discussing the factors causing eruption under-recording. Secondly, I estimated the average recurrence interval of first recorded eruptions at a regional level and the annual probability of eruption at individual potentially active volcanoes from several regions of Asia-Pacific. Lastly, I identified analogues and estimated the f-M relationship for Melimoyu (Chile) by applying a quantitative and objective approach based on hierarchical clustering and probabilistic modelling. This thesis provides insights into the challenges of forecasting eruptions at under-studied volcanoes and presents numerical solutions for overcoming data scarcity.
author2 Susanna Jenkins
author_facet Susanna Jenkins
Burgos, Vanesa
format Thesis-Doctor of Philosophy
author Burgos, Vanesa
author_sort Burgos, Vanesa
title Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
title_short Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
title_full Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
title_fullStr Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
title_full_unstemmed Overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
title_sort overcoming data scarcity for probabilistic eruption forecasting at data-limited volcanoes
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166192
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