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This paper presents a theoretical method for estimating volcanic ash fall rate from the eruption of Sinabung Volcano on February 19, 2018 using an X-band multi-parameter radar (X-MP radar). The X-MP radar was run in a sectoral range height indicator (SRHI) scan mode for 6° angular range (azimuth of 221°–226°) and at an elevation angle of 7° to 40° angular range. The distance of the radar is approximately 8 km in the Southeastern direction of the vent of Mount Sinabung. Based on a three-dimensional (3-D) image of the radar reflectivity factor, the ash column height was established to be more than 7.7 km, and in-depth information on detectable tephra could be obtained. This paper aims to present the microphysical parameters of volcanic ash measured by X-MP radar, which are the tephra concentration and the fall-out rate. These parameters were calculated in a two-step stepwise approach microphysical model using the scaled gamma distribution. The first step was ash classification based on a set of training data on synthetic ash and its estimated reflectivity factor. Using a naïve Bayesian classification, the measured reflectivity factors from the eruption were classified into the classification model. The second step was estimating the volcanic ash concentration and the fall-out rate by power-law function. The model estimated a maximum of approximately 12.9 g·m-3of ash concentration from the coarse ash class (mean diameterDn= 0.1 mm) and a minimum of approximately 0.8 megatons of volcanic ash mass accumulation from the eruption.

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.

Lahar flow is recognized as among the worst secondary hazards from volcanic disaster. Intense rainfall with long duration is frequently associated with lahar flow. In this study, estimation of a rainfall threshold likely to trigger lahar flow is presented in the first part. The second part discusses its implementation by assessing the growth of observed and predicted rainfall, including the uncertainties. The study area is Merapi Volcano, one of the most active volcanoes in Indonesia, including rivers on the flank of Mount Merapi that are vulnerable to debris flow. The rainfall indices needed to describe the conditions that generate lahars or not were determined empirically by evaluating the hourly and working rainfall using X-band multiparameter (X-MP) weather radar. Using past records of lahar flow, the threshold lines separating rainfall that triggers lahars or not were analyzed for the Putih, Gendol, Pabelan, and Krasak Rivers. The performance of several critical lines was evaluated using Bayesian probability based on skill rates from a contingency matrix. The study shows that the line intercept of the critical lines after a significant eruption in 2010 was higher than those lines developed before 2010, indicating that the rivers are currently at lesser risk. Good representation was shown by the thresholds verified with actual rainfall progression and lahar event information on February 17, 2016, at the Gendol and Pabelan Rivers. These rainfall critical lines were the basis for judging the debris flow occurrence by analyzing the track record of predicted rainfall progression. The uncertainty of rainfall short-term prediction from the extrapolation model was evaluated by perturbing the advection vector of rain echo motion. This ensemble forecast product could provide a plausible range of prediction possibility as assistance in gaining the confidence with which a lahar could be predicted. The scheme presented herein could serve as a useful tool for a lahar early warning system in the area of the Merapi Volcano.

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This paper reports a preliminary attempt to determine volcanic ash particle size distribution using the video drop size detector (VDSD) for estimating volcanic ash amount with X-band radar. The VDSD records an image showing the size and number of particles falling into the aperture by a charge coupled device camera. Size distribution spectra of a range of particles from fine ash to small lapilli were derived in discrete form from the VDSD observation. The parameterization of the particle size distribution following Gamma function was done using volcanic ash of eruptions at the Sakurajima Volcano between December 13–21, 2014. Three Gamma distribution parameters were determined analytically. The analytical results revealed a continuous distribution of particles characterized by shape, intercept, and slope. The distribution was used to determine volcanic mass concentration, ground deposit weight, and reflectivity. Verification of these results with X-band radar observations showed that the reflectivity obtained from analytical results is similar to that from radar observation. However, the ground deposit weight from analysis was overestimated, compared with the real weight of ash deposit on the ground. The algorithm proposed in this study is expected to provide a practical method for estimating ash distribution in the aftermath of a volcanic eruption using radar-reflectivity for cases where direct measurement at the location is not possible. An overview of the algorithm for volcanic ash retrieval from X-band radar observations is also presented.

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.