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Probabilistic Volcanic Ash Hazard Analysis (PVAHA) II: Assessment of the Asia-Pacific Region Using VAPAH V

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Probabilistic Volcanic Ash Hazard Analysis (PVAHA) II: Assessment of the Asia-Pacific Region Using VAPAH V Miller et al. Journal of Applied Volcanology (2016) 5:4 DOI 10.1186/s13617-016-0044-3 RESEARCH Open Access Probabilistic Volcanic Ash Hazard Analysis (PVAHA) II: assessment of the Asia-Pacific region using VAPAH V. Miller1*, A. N. Bear-Crozier1, V. Newey1, N. Horspool1,2 and R. Weber1 Abstract Volcanic ash is an increasingly common, long-range hazard, impacting on our globalised society. The Asia-Pacific region is rapidly developing as a major contributor to the global population and economy and is home to one-quarter of the world’s active volcanoes. Here we present a regional-scale volcanic ash hazard assessment for the Asia-Pacific using a newly developed framework for Probabilistic Volcanic Ash Hazard Analysis (PVAHA). This PVAHA was undertaken using the Volcanic Ash Probabilistic Assessment of Hazard (VAPAH) algorithm. The VAPAH algorithm considered a magnitude-frequency distribution of eruptions and associated volcanic ash load attenuation relationships for the Asia-Pacific, and integrated across all possible events to arrive at an annual exceedance probability for sites of interest. The Asia-Pacific region was divided into six sub-regions (e.g. Indonesia, Philippines and Southeast Asia, Melanesia/Australia, Japan/Taiwan, New Zealand/Samoa/Tonga/Fiji and Russia/China/Mongolia/ Korea) characterised by 276 source volcanoes each with individual magnitude-frequency relationships. Sites for analysis within the Asia-Pacific region were limited to land-based locations at 1-km grid spacing, within 500 km of a volcanic source. The Indonesian sub-region exhibited the greatest volcanic ash hazard in the region at the 100-year timeframe, with additional sources (in Japan, the Philippines, Papua New Guinea, Kamchatka - Russia and New Zealand) along plate boundaries manifesting a high degree of hazard at the 10,000-year timeframe. Disaggregation of the volcanic ash hazard for individual sites of interest provided insight into the primary causal factors for volcanic ash hazard at capital cities in Papua New Guinea, the Philippines and Japan. This PVAHA indicated that volcanic ash hazard for Port Moresby was relatively low at all timeframes. In contrast to this, Jakarta, Manila and Tokyo are characterised by high degrees hazard at all timeframes. The greatest hazard was associated with Tokyo and the PVAHA was able to quantify that the large number of sources impacting on this location was the causal factor contributing to the hazard. This evidence-based approach provides important insights for decision makers responsible for strategic planning and can assist with prioritising regions of interest for more detailed volcanic ash hazard modelling and local scale planning. Keywords: PVAHA,VAPAH,Probabilistic,Volcanicash,Hazard,Asia-Pacific Background The occurrence of volcanic ash fallout may not present Explosive eruptions pose a serious hazard to both society an immediate danger to large populations; however, the and the environment (Blong 1984; Spence et al. 2005; long lasting nature of the hazard can cause serious dis- Horwell and Baxter 2006; Durant et al. 2010; Wilson ruption to aviation routes, critical infrastructure and et al. 2012). Volcanic ash can be transported up to thou- agriculture production (Wilson et al. 2012). The poten- sands of kilometres from a source, and understanding tially widespread impact of volcanic ash hazard, coupled the spatial distribution of fallout from all potential with increased globalisation of communication, trans- events is essential for quantifying the risk to a region. portation and commercial networks, highlights the im- portance of characterising the long-term implications for * Correspondence: [email protected] strategic planning. Furthermore, regional- to global-scale 1Geoscience Australia, GPO Box 378, Canberra ACT 2601, Australia analyses will enable rapid determination of at-risk zones Full list of author information is available at the end of the article © 2016 Miller et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Miller et al. Journal of Applied Volcanology (2016) 5:4 Page 2 of 19 that would benefit from focused, local hazard and risk millions of events considered in a fully probabilistic ana- analysis studies. lysis. Additionally, this method does not produce hazard The potential impacts of volcanic ash fallout are wide- curves of annual exceedance probability versus volcanic spread, varying and highly dependent on the scale of the ash for individual sites of interest, which precludes dis- eruption and the distance from source (Blong 1984; aggregation of contributing factors for the hazard. Heiken et al. 1992; Spence et al. 2005; Horwell and Baxter This paper presents an application example for a 2006; Costa et al. 2009; Durant et al. 2010). These impacts newly developed methodology at Geoscience Australia, include but are not limited to: (1) damage to human set- which seeks to overcome these limitations through the tlements and buildings in the form of roof collapse from adaptation of a well-established approach to Probabilistic ash loading; (2) disruption of transportation systems due Seismic Hazard Assessment (PSHA) for volcanic ash at to a decrease in or loss of visibility, covering of roads/rail- a regional-scale. The Probabilistic Volcanic Ash Hazard ways by ash or direct damage to vehicles; (3) partial or Analysis (PVAHA) framework considers the magnitude- total destruction of agricultural crops, damage to forestry, frequency distribution of eruptions and associated vol- decrease in soil permeability and increased surface run-off canic ash load attenuation relationships to produce and promoting flooding; (4) destruction of pastures and health statistically emulate volcanic ash hazard for all events risks for livestock (e.g. fluorosis); (5) disruption of com- across a region of interest. An algorithm developed to munication systems (e.g. equipment and power lines); (6) facilitate PVAHA, the Volcanic Ash Probabilistic Assess- temporary shutdown of airports due to degraded engine ment tool for Hazard (VAPAH), is used here to present performance, failure of navigation equipment or loss of an application example for the Asia-Pacific region. visibility; (7) volcanic ash leaching, which can lead to chemical and physical changes in the quality of open The PVAHA framework water supplies; (8) adverse health effects (e.g. irritation of A framework for PVAHA was developed to investigate eyes and skin and potential respiratory symptoms) associ- volcanic ash hazard in terms of the annual exceedance ated with ash inhalation. These potential impacts stress probability for each site across a region of interest the socio-economic implications of volcanic ash fallout (Bear-Crozier et al. 2016). For a full account of the and highlight the relevance of adequate hazard assessment conceptual frame for PVAHA and the development and risk mitigation (Folch et al. 2008a; Folch et al. 2008b; and validation of the VAPAH algorithm, the reader is Folch and Sulpizio 2010). referred to the companion paper (Bear-Crozier et al. 2016). A brief summary of the PVAHA framework as Previous probabilistic ash hazard assessments in the pertinent to the Asia-Pacific regional case study is Asia-Pacific region provided below. Previous probabilistic analyses of volcanic ash hazard in PVAHA consists of four steps: the Asia-Pacific region have largely focused on qualita- tive assessments of the frequency and potential conse- 1. Volcanic sources with respect to any given site of quences of future eruptions (e.g. Simpson et al. 2011). interest must be identified. Quantitative approaches have typically considered a 2. For each volcanic source the annual eruption single source or site of interest at a local scale with any probability must be calculated based on magnitude- determined probabilities conditional on an eruption frequency relationships of past events. from that volcano occurring (Bonadonna et al. 2005; 3. For a catalogue of synthetic events, volcanic ash load Jenkins et al. 2008; Costa et al. 2009; Folch and Sulpizio attenuation relationships must be calculated (derived 2010; Bear-Crozier et al. 2012). Jenkins et al. (2012a; from conventional ash dispersal modelling). 2012b) developed a probabilistic framework for assessing 4. Calculation of the annual exceedance probability ash fall hazard on a regional-scale (100’s of km) by up- versus volcanic ash hazard for each stochastic event scaling the ASHFALL dispersion model for regional- at each site across a region of interest. scale applications (Hurst 1994; Hurst and Turner 1999). Limitations associated with this approach centre on the The VAPAH algorithm computationally intensive nature of up-scaling ash dis- The VAPAH algorithm developed as a mechanism to persal modelling requiring large numbers of CPUs, sig- facilitate PVAHA utilises high performance computing nificantly increased simulation times and subsequent technology in order to undertake assessments at multiple limitations on the number of events that can be consid- spatial scales. The VAPAH algorithm combines magnitude- ered (in the order of hundreds to thousands). Dispersion frequency relationships, a catalogue of Ash Load Prediction models
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