Abstract

Reliable methods for volcanic impact and risk assessments are essential. They provide constructive information to emergency and disaster managers, critical infrastructure providers, the insurance industry, and wider society. Post-eruption clean-up of tephra deposits is a prevalent and expensive (time and resource) activity which is often not planned for. Here, we present an overview of the clean-up efforts undertaken in four communities after the VEI 4 eruption of Calbuco volcano in 2015. We narratively reconstruct clean-up efforts in Ensenada (Chile), Junín de los Andes (Argentina), San Martín de los Andes (Argentina), and Villa La Angostura (Argentina) using semi-structured interviews, syn- and post-deposition photographs, pre- and post-event visual spectrum satellite imagery, and media reports. We compare these reconstructions with estimates based on a geospatial modelling approach adapted from Hayes et al. (Journal of Applied Volcanology 6:1; 2017). Specifically, we compare reported and geospatially derived estimates for volume of tephra removed, and clean-up operation duration. Our modelling approach performed well for Junín de los Andes but did not adequately capture volume and clean-up operation duration for the three remaining case study locations. We discuss several sources of uncertainty (including observational errors and natural variance of tephra deposit thickness), reported tephra removal volume estimates, clean-up methods, land use, and temporal evolution of clean-up operation demand. Our work demonstrates the utility of using simple geospatial data to develop assessments for tephra clean-up for use in response and recovery planning, and quantitative volcanic impact and risk assessments.

Highlights

  • We examine four communities: Ensenada, Chile; Villa La Angostura (VLA), Argentina; San Martín de los Andes (SMA), Argentina; and Junín de los Andes (JDA), Argentina (Fig. 1); Retrospectively apply the Hayes et al (2017) conceptual clean-up model based on field data; and Evaluate the effectiveness of the Hayes et al (2017) conceptual modelling approach to estimate clean-up requirements in each of the four selected communities

  • Ensenada has the lowest proportion of urban surfaces requiring clean-up (0.4–2%) out of our case study communities, with VLA (10%), JDA (13%), and SMA (18%) containing considerably higher proportions of impervious surfaces

  • We have evaluated the performance of quantitative geospatial tephra clean-up modelling as a method for gaining insights into tephra clean-up requirements

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Summary

Introduction

Widespread tephra fallout from explosive volcanic eruptions can damage the built environment (Blong 1984; Jenkins et al 2014; Spence et al 2005), cause infrastructure service disruption (Blong 1984; Wilson et al 2012, 2014), and generate public and environmental health issues (Horwell and Baxter 2006). We build upon the work of Hayes et al (2015) and Craig et al (2016) to test an empirically inspired tephra clean-up model on an independent case study

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