{"id":{"repo_id":"auckland-ms","oai_identifier":"oai:researchspace.auckland.ac.nz:2292/64587"},"canonical_url":"https://search.dev.ndltd.org/etd/auckland-ms/oai:researchspace.auckland.ac.nz:2292/64587","repository":{"repo_id":"auckland-ms","name":"University of Auckland","base_url":"https://researchspace.auckland.ac.nz/server/oai/request"},"display":{"title":"Exploring the use of quantitative modelling approaches to support volcanic crisis management in the Auckland Volcanic Field","abstract":"The high-stakes decision to call an evacuation during a volcanic crisis is complex and challenging, in part due to uncertainties related to the behaviour of the volcano. This thesis investigates the use of quantitative hazard and risk modelling approaches to support such decision-making during a volcanic crisis, focusing on the decision to call an evacuation in areas of distributed volcanism. The monogenetic Auckland Volcanic Field (AVF) beneath Auckland, New Zealand’s largest city, was selected as a case study. Stakeholder engagement together with a robust literature review of available tools and methods led to the development of an approach that combined a Bayesian Event Tree hazard assessment with Cost-benefit Analysis (CBA) within an evacuation decision-support framework for Auckland. Firstly, evacuation clearance times were estimated by combining spatial variability in population exposure and vehicle ownership (and thus public transport demand during an evacuation) with road data. The median evacuation clearance time with no congestion was calculated to be approximately 37 hours, increasing to between 38 and 55 hours with a 10 km vent uncertainty buffer. An updated Bayesian Event Tree for Eruption Forecasting (BET_EF) for the AVF was then tested using eight synthetic pre-eruptive sequences. A sensitivity analysis for the prior distributions for key model parameters explored the utility of using BET_EF outputs as a potential input for evacuation decision-making in areas of distributed volcanism. This revealed that, when combined with CBA, the default monitoring component weight used to assess the spatial vent likelihood was ineffective for identifying locations that are cost-beneficial to evacuate in the event of volcanic unrest. A transitional parameter for this monitoring component weight was tested using three intervals and found to be more appropriate for applications to distributed volcanism. Finally, the BET_EF was extended to a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The BET_VHst, when combined with CBA, forms an evacuation decision-support approach that can be used in areas of distributed volcanism and suitable evacuation areas were identified in the Auckland case study. However, given the sensitivity of the model to different key parameters tested, further review is required before such an approach can be applied operationally.","abstract_html":"The high-stakes decision to call an evacuation during a volcanic crisis is complex and challenging, in part due to uncertainties related to the behaviour of the volcano. This thesis investigates the use of quantitative hazard and risk modelling approaches to support such decision-making during a volcanic crisis, focusing on the decision to call an evacuation in areas of distributed volcanism. The monogenetic Auckland Volcanic Field (AVF) beneath Auckland, New Zealand’s largest city, was selected as a case study. Stakeholder engagement together with a robust literature review of available tools and methods led to the development of an approach that combined a Bayesian Event Tree hazard assessment with Cost-benefit Analysis (CBA) within an evacuation decision-support framework for Auckland. Firstly, evacuation clearance times were estimated by combining spatial variability in population exposure and vehicle ownership (and thus public transport demand during an evacuation) with road data. The median evacuation clearance time with no congestion was calculated to be approximately 37 hours, increasing to between 38 and 55 hours with a 10 km vent uncertainty buffer. An updated Bayesian Event Tree for Eruption Forecasting (BET_EF) for the AVF was then tested using eight synthetic pre-eruptive sequences. A sensitivity analysis for the prior distributions for key model parameters explored the utility of using BET_EF outputs as a potential input for evacuation decision-making in areas of distributed volcanism. This revealed that, when combined with CBA, the default monitoring component weight used to assess the spatial vent likelihood was ineffective for identifying locations that are cost-beneficial to evacuate in the event of volcanic unrest. A transitional parameter for this monitoring component weight was tested using three intervals and found to be more appropriate for applications to distributed volcanism. Finally, the BET_EF was extended to a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The BET_VHst, when combined with CBA, forms an evacuation decision-support approach that can be used in areas of distributed volcanism and suitable evacuation areas were identified in the Auckland case study. However, given the sensitivity of the model to different key parameters tested, further review is required before such an approach can be applied operationally.","abstract_has_math":false,"creators":["Wild, Alec James"],"institution":"ResearchSpace@Auckland","degree_name":"PhD","degree_level":"Doctoral","degree_discipline":"Geology","degree_department":null,"school":null,"contributors":[],"advisors":["Lindsay, Jan"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023","date_published":"2023","updated_at":"2026-07-24T01:03:18Z","subjects":[],"languages":[],"rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"rights_urls":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2292/64587","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Lindsay, Jan"]},{"key":"dc:creator","label":"Author","values":["Wild, Alec James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2023-07-10T00:46:34Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-07-10T00:46:34Z"]},{"key":"dc:date.issued","label":"Date","values":["2023"]},{"key":"dc:publisher","label":"Institution","values":["ResearchSpace@Auckland"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["UoA"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["PhD"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["The University of Auckland"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/2292/64587"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The high-stakes decision to call an evacuation during a volcanic crisis is complex and challenging, in part due to uncertainties related to the behaviour of the volcano. This thesis investigates the use of quantitative hazard and risk modelling approaches to support such decision-making during a volcanic crisis, focusing on the decision to call an evacuation in areas of distributed volcanism. The monogenetic Auckland Volcanic Field (AVF) beneath Auckland, New Zealand’s largest city, was selected as a case study. Stakeholder engagement together with a robust literature review of available tools and methods led to the development of an approach that combined a Bayesian Event Tree hazard assessment with Cost-benefit Analysis (CBA) within an evacuation decision-support framework for Auckland. Firstly, evacuation clearance times were estimated by combining spatial variability in population exposure and vehicle ownership (and thus public transport demand during an evacuation) with road data. The median evacuation clearance time with no congestion was calculated to be approximately 37 hours, increasing to between 38 and 55 hours with a 10 km vent uncertainty buffer. An updated Bayesian Event Tree for Eruption Forecasting (BET_EF) for the AVF was then tested using eight synthetic pre-eruptive sequences. A sensitivity analysis for the prior distributions for key model parameters explored the utility of using BET_EF outputs as a potential input for evacuation decision-making in areas of distributed volcanism. This revealed that, when combined with CBA, the default monitoring component weight used to assess the spatial vent likelihood was ineffective for identifying locations that are cost-beneficial to evacuate in the event of volcanic unrest. A transitional parameter for this monitoring component weight was tested using three intervals and found to be more appropriate for applications to distributed volcanism. Finally, the BET_EF was extended to a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The BET_VHst, when combined with CBA, forms an evacuation decision-support approach that can be used in areas of distributed volcanism and suitable evacuation areas were identified in the Auckland case study. However, given the sensitivity of the model to different key parameters tested, further review is required before such an approach can be applied operationally."]},{"key":"dc:title","label":"Title","values":["Exploring the use of quantitative modelling approaches to support volcanic crisis management in the Auckland Volcanic Field"]}]}],"canonical_facts":{"dc:contributor.advisor":["Lindsay, Jan"],"dc:creator":["Wild, Alec James"],"dc:date.accessioned":["2023-07-10T00:46:34Z"],"dc:date.available":["2023-07-10T00:46:34Z"],"dc:date.issued":["2023"],"dc:description.abstract":["The high-stakes decision to call an evacuation during a volcanic crisis is complex and challenging, in part due to uncertainties related to the behaviour of the volcano. This thesis investigates the use of quantitative hazard and risk modelling approaches to support such decision-making during a volcanic crisis, focusing on the decision to call an evacuation in areas of distributed volcanism. The monogenetic Auckland Volcanic Field (AVF) beneath Auckland, New Zealand’s largest city, was selected as a case study. Stakeholder engagement together with a robust literature review of available tools and methods led to the development of an approach that combined a Bayesian Event Tree hazard assessment with Cost-benefit Analysis (CBA) within an evacuation decision-support framework for Auckland. Firstly, evacuation clearance times were estimated by combining spatial variability in population exposure and vehicle ownership (and thus public transport demand during an evacuation) with road data. The median evacuation clearance time with no congestion was calculated to be approximately 37 hours, increasing to between 38 and 55 hours with a 10 km vent uncertainty buffer. An updated Bayesian Event Tree for Eruption Forecasting (BET_EF) for the AVF was then tested using eight synthetic pre-eruptive sequences. A sensitivity analysis for the prior distributions for key model parameters explored the utility of using BET_EF outputs as a potential input for evacuation decision-making in areas of distributed volcanism. This revealed that, when combined with CBA, the default monitoring component weight used to assess the spatial vent likelihood was ineffective for identifying locations that are cost-beneficial to evacuate in the event of volcanic unrest. A transitional parameter for this monitoring component weight was tested using three intervals and found to be more appropriate for applications to distributed volcanism. Finally, the BET_EF was extended to a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The BET_VHst, when combined with CBA, forms an evacuation decision-support approach that can be used in areas of distributed volcanism and suitable evacuation areas were identified in the Auckland case study. However, given the sensitivity of the model to different key parameters tested, further review is required before such an approach can be applied operationally."],"dc:identifier.uri":["https://hdl.handle.net/2292/64587"],"dc:publisher":["ResearchSpace@Auckland"],"dc:relation.isreferencedby":["UoA"],"dc:rights":["Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated."],"dc:rights.uri":["https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm"],"dc:title":["Exploring the use of quantitative modelling approaches to support volcanic crisis management in the Auckland Volcanic Field"],"dc:type":["Thesis"],"thesis:degree_discipline":["Geology"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["PhD"],"thesis:institution_name":["The University of Auckland"]},"updated_at":"2026-07-24T01:03:18Z"}