Estimation of volcanic ashfall deposit and removal works based on ash dispersion simulations

Yosuke Tomii, Tomoya Shibayama, Yuta Nishida, Ryota Nakamura, Non Okumura, Hideaki Yamaguchi, Yosuke Tanokura, Yu Oshima, Natsuko Sugawara, Kota Fujisawa, Takayuki Wakita, Takahito Mikami, Tomoyuki Takabatake, Miguel Esteban*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Volcanic ashfall can cause considerable social impacts to a wide geographical area. Given the challenge to predict volcanic eruptions, it is essential to simulate the dispersion of ash as soon as possible after an event and promptly estimate the distribution of deposits and necessary removal works. In this study, a series of procedures to improve the accuracy of the WRF-FALL3D model for the case of the eruption of Mt. Kusatsu-Shirane in 2018 are proposed, which were verified through field surveys of ash deposits, showing that the accuracy of the model can be improved by selecting a range of column heights and promptly conducting field surveys following an event. Also, a methodology to estimate the amount of work necessary to clear road networks and river channels is proposed, which was applied to a volcanic event similar to that of the Hoei eruption of Mt. Fuji in 1707. The results also emphasize the need to improve the estimation of column heights in the future, which is of paramount importance to ensure the safety and operational continuity of human infrastructure in the vicinity of major active volcanoes.

Original languageEnglish
Pages (from-to)3377-3399
Number of pages23
JournalNatural Hazards
Issue number3
Publication statusPublished - 2020 Sept 1


  • Ash dispersion modelling
  • Ashfall deposit
  • Mt. Fuji
  • Mt. Kusatsu-Shirane
  • Removal works

ASJC Scopus subject areas

  • Water Science and Technology
  • Atmospheric Science
  • Earth and Planetary Sciences (miscellaneous)


Dive into the research topics of 'Estimation of volcanic ashfall deposit and removal works based on ash dispersion simulations'. Together they form a unique fingerprint.

Cite this