Browsing by Author "Lindsay JM"

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    Cost-benefit analysis for evacuation decision-support: challenges and possible solutions for applications in areas of distributed volcanism
    (BioMed Central Ltd, part of Springer Nature, 2023-08-18) Wild AJ; Bebbington MS; Lindsay JM; Deligne NI
    During a volcanic crisis, evacuation is the most effective mitigation measure to preserve life. However, the decision to call an evacuation is typically complex and challenging, in part due to uncertainties related to the behaviour of the volcano. Cost-benefit analysis (CBA) can support decision-makers: this approach compares the cost of evacuating versus the expected loss from not evacuating, expressed as a ‘break-even’ probability of fatality. Here we combine CBA with a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to create an evacuation decision-support tool to identify locations that are cost-beneficial to evacuate in the event of volcanic unrest within a distributed volcanic field. We test this approach with the monogenetic Auckland Volcanic Field (AVF), situated beneath the city of Auckland, New Zealand. We develop a BET_VHst for the AVF, extending a recently revised Bayesian Event Tree for Eruption Forecasting (BET_EF) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The output of the BET_VHst is a probability of volcanic hazard impact at a given location. Furthermore, we propose amending the weight of the monitoring component within the BET_VHst framework to a transitional parameter, addressing limitations identified in a previous study. We examine how three possible transitional monitoring component weights affect the spatial vent likelihood and subsequent BET_VHst outputs, compared to the current default weight. For the CBA, we investigate four thresholds, based on two evacuation durations and two different estimates for the value of life that determine the cost of not evacuating. The combinations of CBA and BET_VHst are tested using a synthetic unrest dataset to define an evacuation area for each day. While suitable evacuation areas were identified, there are further considerations required before such an approach can be applied operationally to support crisis management.
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    Modelling spatial population exposure and evacuation clearance time for the Auckland Volcanic Field, New Zealand
    (Elsevier BV, 2021-08) Wild AJ; Bebbington MS; Lindsay JM; Charlton DH
    Auckland, New Zealand's largest city (population of ~1.6 million), is situated atop the monogenetic Auckland Volcanic Field (AVF). As in many places faced with volcanic activity, evacuation is seen as the best risk mitigation strategy for preserving lives in the event of volcanic unrest and/or an eruption. However, planning for an evacuation can be challenging. In particular, the uncertainty in vent location resulting from the monogenetic nature of the field makes identifying neighbourhoods to be evacuated impractical until well into the pre-eruption unrest period. This study uses spatial analysis methods to assess exposure for both population and private transport ownership as well as to identify those areas requiring public transport support for an evacuation. These data were overlaid on a range of possible vent locations across the AVF using a 500 × 500 m grid. At each possible vent location, a 5 km evacuation zone is modelled, following the official contingency plan for evacuation in a future AVF event. In order to simulate vent location uncertainty leading up to a future eruption, a range of buffer distances were applied around the modelled vent locations. The exposure data derived were then used to model evacuation clearance time, which considered four phases: 1) the time taken to decide to call an evacuation; 2) the public notification time; 3) the evacuee's time to prepare; and 4) evacuee's travel time to beyond the evacuation zone. The length of time involved in phases 1 to 3 are all independent of the vent location; our analysis found these phases could be completed within 36 h, with over 80% confidence. Travel times to beyond the evacuation zone were modelled using the exposure analysis for population and private transport ownership combined with road network data and vehicle carrying capacity. This revealed travel times for this phase ranging from less than 1 up to 11 h, depending on traffic congestion, when considering no vent uncertainty. By combining the times modelled for all four phases, we found that when there is high certainty in the vent location, the median total evacuation clearance time with no congestion is approximately 37 h. However, include a 10 km vent uncertainty buffer into the model, the evacuation clearance time can increase to between 38 and 55 h, dependent on traffic congestion. A vent in the densely populated inner Auckland and CBD area would result in the greatest population required to evacuate, and also the greatest need for public transport support given the low vehicle ownership in this area. Our results can be used to inform emergency management decision making, and the model can be adapted for other regions as well as for other hazards.
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    Short-Term Eruption Forecasting for Crisis Decision-Support in the Auckland Volcanic Field, New Zealand
    (Frontiers Media S.A., 2022-05-24) Wild AJ; Bebbington MS; Lindsay JM; Wright HM
    Auckland, a city of 1.6 million people, is situated atop the active monogenetic Auckland Volcanic Field (AVF). Thus, short-term eruption forecasting is critical to support crisis management in a future event, especially to inform decisions such as calling evacuations. Here we present an updated BET_EF for the AVF incorporating new data and the results of an expert-opinion workshop, and test the performance of the resulting BETEF_AVF on eight hypothetical eruption scenarios with pre-eruptive sequences. We carry out a sensitivity analysis into the selection of prior distributions for key model parameters to explore the utility of using BET_EF outputs as a potential input for evacuation decision making in areas of distributed volcanism such as the AVF. BETEF_AVF performed well based on the synthetic unrest dataset for assessing the probability of eruption, with the vent outbreaks eventuating within the zone of high spatial likelihood. Our analysis found that the selection of different spatial prior model inputs affects the estimated vent location due to the weighting between prior models and monitoring inputs within the BET_EF, which as unrest escalates may not be appropriate for distributed volcanic fields. This issue is compounded when the outputs are combined with cost-benefit analysis to inform evacuation decisions, leading to areas well beyond those with observed precursory activity being included in evacuation zones. We find that several default settings used in past work for the application of BET_EF and CBA to inform evacuation decision-support are not suitable for distributed volcanism; in particular, the default 50-50 weighting between priors and monitoring inputs for assessing spatial vent location does not produce useful results. We conclude by suggesting future cost-benefit analysis applications in volcanic fields appropriately consider the spatial and temporal variability and uncertainty characteristic of such systems.