Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest

Real-time monitoring of volcanic ground deformation is a compelling tool for hazard management and disaster response during volcanic crises. However, monitoring in real-time is stymied by the credibility of source models and the detection capability of the current continuous Global Positioning Syste...

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Main Author: Lee, Daniel Wei Jie
Other Authors: Benoit Taisne
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/165742
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author Lee, Daniel Wei Jie
author2 Benoit Taisne
author_facet Benoit Taisne
Lee, Daniel Wei Jie
author_sort Lee, Daniel Wei Jie
collection NTU
description Real-time monitoring of volcanic ground deformation is a compelling tool for hazard management and disaster response during volcanic crises. However, monitoring in real-time is stymied by the credibility of source models and the detection capability of the current continuous Global Positioning System (cGPS) network. Many post-eruptive studies use inversion on various source models on the same ground deformation data, but arrived at substantially different forecasted source parameters. To highlight these differences, we use a Bayesian inversion with a simulated annealing method on static synthetic deformation data. We show the extent of errors with assuming a fixed geometry, in the cases of the commonly-used point source and rectangular dislocation models. We also demonstrate how a more complex point compound dislocation model can be used to evaluate unknown deformation sources, with the potential for real-time application. Subsequently, we model synthetic deformation on cGPS networks on 184 volcanoes, with station information retrieved from the World Organization of Volcano Observatory, Global Volcano Monitoring Infrastructure Database (WOVOdat-GVMID), to establish a preliminary assessment of the capability of current cGPS networks. We find that various factors, such as the number of varied model parameters, the type of deformation and the station positioning, significantly affect the success of the inversion modeling. We also specifically analyze four well-equipped networks, namely Izu-Oshima, Miyake-jima, San Cristobal and Sierra Negra, to emphasize the limitations and benefits of various network designs. Developing a comprehensive real-time monitoring network will require additional extensive modeling that includes known geological processes and subsurface structures to test the fidelity of a network.
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spelling ntu-10356/1657422023-04-12T06:15:09Z Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest Lee, Daniel Wei Jie Benoit Taisne Asian School of the Environment BTaisne@ntu.edu.sg Science::Geology::Volcanoes and earthquakes Real-time monitoring of volcanic ground deformation is a compelling tool for hazard management and disaster response during volcanic crises. However, monitoring in real-time is stymied by the credibility of source models and the detection capability of the current continuous Global Positioning System (cGPS) network. Many post-eruptive studies use inversion on various source models on the same ground deformation data, but arrived at substantially different forecasted source parameters. To highlight these differences, we use a Bayesian inversion with a simulated annealing method on static synthetic deformation data. We show the extent of errors with assuming a fixed geometry, in the cases of the commonly-used point source and rectangular dislocation models. We also demonstrate how a more complex point compound dislocation model can be used to evaluate unknown deformation sources, with the potential for real-time application. Subsequently, we model synthetic deformation on cGPS networks on 184 volcanoes, with station information retrieved from the World Organization of Volcano Observatory, Global Volcano Monitoring Infrastructure Database (WOVOdat-GVMID), to establish a preliminary assessment of the capability of current cGPS networks. We find that various factors, such as the number of varied model parameters, the type of deformation and the station positioning, significantly affect the success of the inversion modeling. We also specifically analyze four well-equipped networks, namely Izu-Oshima, Miyake-jima, San Cristobal and Sierra Negra, to emphasize the limitations and benefits of various network designs. Developing a comprehensive real-time monitoring network will require additional extensive modeling that includes known geological processes and subsurface structures to test the fidelity of a network. Bachelor of Science in Environmental Earth Systems Science 2023-04-10T02:12:03Z 2023-04-10T02:12:03Z 2023 Final Year Project (FYP) Lee, D. W. J. (2023). Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165742 https://hdl.handle.net/10356/165742 en application/pdf Nanyang Technological University
spellingShingle Science::Geology::Volcanoes and earthquakes
Lee, Daniel Wei Jie
Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title_full Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title_fullStr Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title_full_unstemmed Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title_short Sensitivity analysis of current continuous GPS networks to monitor volcanic unrest
title_sort sensitivity analysis of current continuous gps networks to monitor volcanic unrest
topic Science::Geology::Volcanoes and earthquakes
url https://hdl.handle.net/10356/165742
work_keys_str_mv AT leedanielweijie sensitivityanalysisofcurrentcontinuousgpsnetworkstomonitorvolcanicunrest