Modeling of Volcano Eruption Risk toward Building Damage and Affected Population in Guntur, Indonesia

Retnowati, Dyah Ayu; Meilano, Irwan; Riqqi, Akhmad

doi:10.1109/agers.2018.8554097

Cited by 6 publications

(7 citation statements)

References 5 publications

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“…8), exposure than Merapi. Retnowati et al (2018a) carried out a current and projected exposure estimate for concentric radii of lava flow and exponentially thinning tephra fall, extending it towards estimates of building damage and loss. A more detailed local hazard and risk assessment for Guntur would be of high value, especially as the volcano appears to be a closed system at present so that a future eruption may be larger than those experienced in the recent past.…”

Section: Discussionmentioning

confidence: 99%

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

Jenkins

Biass

Williams

et al. 2022

Nat. Hazards Earth Syst. Sci.

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Abstract. Regional volcanic threat assessments provide a large-scale comparable vision of the threat posed by multiple volcanoes. They are useful for prioritising risk-mitigation actions and are required by local through international agencies, industries and governments to prioritise where further study and support could be focussed. Most regional volcanic threat studies have oversimplified volcanic hazards and their associated impacts by relying on concentric radii as proxies for hazard footprints and by focussing only on population exposure. We have developed and applied a new approach that quantifies and ranks exposure to multiple volcanic hazards for 40 high-threat volcanoes in Southeast Asia. For each of our 40 volcanoes, hazard spatial extent, and intensity where appropriate, was probabilistically modelled for four volcanic hazards across three eruption scenarios, giving 697 080 individual hazard footprints plus 15 240 probabilistic hazard outputs. These outputs were overlain with open-access datasets across five exposure categories using an open-source Python geographic information system (GIS) framework developed for this study (https://github.com/vharg/VolcGIS, last access: 5 April 2022). All study outputs – more than 6500 GeoTIFF files and 70 independent estimates of exposure to volcanic hazards across 40 volcanoes – are provided in the “Data availability” section in user-friendly format. Calculated exposure values were used to rank each of the 40 volcanoes in terms of the threat they pose to surrounding communities. Results highlight that the island of Java in Indonesia has the highest median exposure to volcanic hazards, with Merapi consistently ranking as the highest-threat volcano. Hazard seasonality, as a result of varying wind conditions affecting tephra dispersal, leads to increased exposure values during the peak rainy season (January, February) in Java but the dry season (January through April) in the Philippines. A key aim of our study was to highlight volcanoes that may have been overlooked perhaps because they have not been frequently or recently active but that have the potential to affect large numbers of people and assets. It is not intended to replace official hazard and risk information provided by the individual country or volcano organisations. Rather, this study and the tools developed provide a road map for future multi-source regional volcanic exposure assessments with the possibility to extend the assessment to other geographic regions and/or towards impact and loss.

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Section: Discussionmentioning

confidence: 99%

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

Jenkins

Biass

Williams

et al. 2022

Nat. Hazards Earth Syst. Sci.

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show abstract

“…Tephra fall building damage forecasts are made by combining an estimate of tephra accumulation (from dispersal modelling or based on previous deposits) with information on a building population's susceptibility to damage (e.g. Zuccaro et al 2008;Biass et al 2016;Retnowati et al 2018). The hazard posed by a tephra fall deposit to a building is most commonly quantified based on the loading of the deposit (Jenkins et al 2014).…”

Section: Introductionmentioning

confidence: 99%

How rainfall influences tephra fall loading — an experimental approach

et al. 2021

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The load a tephra fall deposit applies to an underlying surface is a key factor controlling its potential to damage a wide range of assets including buildings, trees, crops and powerlines. Though it has long been recognised that loading can increase when deposits absorb rainfall, few efforts have been made to quantify likely load increases. This study builds on previous theoretical work, using an experimental approach to quantify change in load as a function of grainsize distribution, rainfall intensity and duration. A total of 20 laboratory experiments were carried out for ~ 10-cm thick, dry tephra deposits of varying grainsize and grading, taken to represent different eruptive scenarios (e.g. stable, waxing or waning plume). Tephra was deposited onto a 15° impermeable slope (representing a low pitch roof) and exposed to simulated heavy rainfalls of 35 and 70 mm h−1 for durations of up to 2 h. Across all experiments, the maximum load increases ranged from 18 to 30%. Larger increases occurred in fine-grained to medium-grained deposits or in inversely graded deposits, as these retained water more efficiently. The lowest increases occurred in normally graded deposits as rain was unable to infiltrate to the deposit’s base. In deposits composed entirely of coarse tephra, high drainage rates meant the amount of water absorbed was controlled by the deposit’s capillary porosity, rather than its total porosity, resulting in load increases that were smaller than expected. These results suggest that, for low pitch roofs, the maximum deposit load increase due to rainfall is around 30%, significantly lower than the oft-referenced 100%. To complement our experimental results, field measurements of tephra thickness should be supplemented with tephra loading measurements, wherever possible, especially when measurements are made at or near the site of observed damage.

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“…Retnowati et al (2018b) carried out a current and projected exposure estimate for concentric radii of lava flow and exponentially thinning tephra fall, extending it towards estimates of building damage and loss. A more detailed local hazard https://doi.org/10.5194/nhess-2021-320 Preprint.…”

mentioning

confidence: 99%

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

Jenkins

Biass

Williams

et al. 2021

Preprint

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Abstract. Regional assessments provide a large-scale comparable vision of the threat posed by multiple sources and are useful for prioritising risk-mitigation actions. There is a need for such assessments from international, regional and national agencies, industries and governments to prioritise where further study and support could be focussed. Most existing regional studies on the threat posed by volcanic activity have relied on concentric radii as proxies for hazard footprints and have focused only on population exposure, often using indices to make first-order estimates of exposure. However, this approach is an oversimplification of volcanic hazards and their associated impacts. We have developed and applied a new approach that quantifies and ranks exposure to multiple volcanic hazards for 40 high-threat volcanoes in Southeast Asia. For each of our 40 volcanoes, hazard spatial extent, and intensity where appropriate, was probabilistically modelled for four volcanic hazards across three eruption scenarios, giving 697,080 individual hazard footprints plus 19,560 probabilistic hazard outputs. We then developed a GIS framework to overlay the spatial extent of probabilistic hazard footprints with open-access datasets across five exposure categories. Finally, we used our calculated exposure values to rank each of the 40 volcanoes in terms of the threat they pose to surrounding communities. We present VolcGIS, an open-source Python code that implements all of the spatial operations required for exposure analysis, available at github.com/vharg/VolcGIS. We provide all our outputs - more than 6,500 geotif files and 70 independent estimates of exposure to volcanic hazards across 40 volcanoes - in user-friendly format. Results highlight that the island of Java in Indonesia has the highest median exposure to volcanic hazards, with Merapi consistently ranking as the highest threat volcano. Hazard seasonality, as a result of varying wind conditions affecting tephra dispersal, leads to increased exposure values during the peak rainy season (January, February) in Java, but the peak dry season (January, February, March) in the Philippines. A key aim of our study was to highlight volcanoes that may have been overlooked, perhaps because they are not frequently or recently active, but that have the potential to affect large numbers of people and assets. It is not intended to replace official hazard and risk information provided by the individual country or volcano organisations. This study and the tools developed provide a road map for future multi-source regional volcanic exposure assessments, with the possibility to extend the assessment to other geographic regions and/or towards impact and loss.

show abstract

Modeling of Volcano Eruption Risk toward Building Damage and Affected Population in Guntur, Indonesia

Cited by 6 publications

References 5 publications

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

How rainfall influences tephra fall loading — an experimental approach

Evaluating and ranking Southeast Asia's exposure to explosive volcanic hazards

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