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  1. 防災科研関係論文

Operation, Expansion, and Improvement of the Snow Load Alert System “YukioroSignal”

https://nied-repo.bosai.go.jp/records/6820
https://nied-repo.bosai.go.jp/records/6820
0b404581-fee1-4273-b641-fd9757dd33d1
Item type researchmap(1)
公開日 2025-04-14
タイトル
言語 en
タイトル Operation, Expansion, and Improvement of the Snow Load Alert System “YukioroSignal”
言語
言語 eng
著者 Hiroyuki Hirashima

× Hiroyuki Hirashima

en Hiroyuki Hirashima

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Katsuhisa Kawashima

× Katsuhisa Kawashima

en Katsuhisa Kawashima

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Ken Motoya

× Ken Motoya

en Ken Motoya

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Hiroaki Sano

× Hiroaki Sano

en Hiroaki Sano

Search repository
抄録
内容記述タイプ Other
内容記述 The “YukioroSignal” system, which provides snow load alerts, was developed to inform decision-making regarding snow removal from house roofs. It was launched in Niigata Prefecture in 2018 and expanded to cover all special heavy snowfall areas in Japan, including the Hokkaido, Tohoku, and Hokuriku regions in 2024. The system uses the SNOWPACK model to estimate high-accuracy snow weight from real-time snow depth data published online at observation points. At locations where snow depth gauges are not installed, such as in mountainous areas, snow weight is estimated using inverse distance-weighted interpolation, but accuracy is reduced. To overcome this problem, this study attempted to integrate this information with the snow water equivalent distribution calculated using the simple-layer snow distribution model. To validate this improvement, manual observations of snow weight were performed at 98 sites and compared with simulation results. The accuracy of snow weight estimation at distances far away from snow depth stations was improved. The six-year operation of YukioroSignal showed the additional required information that is vulnerable to damage even with less snowfall, such as vacant houses, and caution of changes in hazard levels by an increase in snowburst in a short period.
言語 en
書誌情報 en : Journal of Disaster Research

巻 19, 号 5, p. 741-749, 発行日 2024-10-01
出版者
言語 en
出版者 Fuji Technology Press Ltd.
ISSN
収録物識別子タイプ EISSN
収録物識別子 1883-8030
DOI
関連識別子 10.20965/jdr.2024.p0741
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