Prediction of avalanche-induced tree fall area using remote sensing technology

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K04607
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 25030:Disaster prevention engineering-related
• Research Institution: Shinshu University
• Principal Investigator: Fukuyama Taijiro 信州大学, 学術研究院農学系, 助教 (60462511)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 雪崩 / 根返り / 幹折れ / ピット / マウンド

Outline of Final Research Achievements

In 2017, a large-scale avalanche occurred on the northeastern slope of Senjogadake, Southern Alps, causing fallen trees. We investigated the damage pattern (bended or uprooted) and extent of forest damage, and attempted to find the weather condition and topographical features. Aerial photo and field survey revealed that the avalanche occurred on a steep slope at an elevation of 2,200 m or higher and destroyed 3.5 ha of forest. The extent of damage to forests caused by avalanches was estimated by correcting the avalanche velocity distribution obtained by simulation based on field surveys of the extent of damage and the size of broken trunks. We also predicted how much the reach of the next avalanche would increase as the roughness of the ground surface decreased due to fallen trees. Furthermore, we estimated the area of bare land and the amount of sediment caused by uprooting.

Free Research Field

砂防・森林科学

Academic Significance and Societal Importance of the Research Achievements

近年の温暖化にともない降雪は少なくなるが，大雪の頻度が高くなると言われている。その場合，長期間積雪が少なく樹木が大きく育った斜面で突発的な降雪による雪崩が発生すると大規模な倒木をひきおこすおそれがある。本研究は，北アルプスに比べて雪崩が少ない南アルプス域における倒木をともなう雪崩の事例を対象として，雪崩の流下範囲や森林の倒木被害範囲を予測することを試みるとともに，雪崩にともなう倒木の形態（根返り・幹折れ）にも着目した。これらの研究を通して，雪崩による倒木の運搬や，河道に倒木が到達することによる流木リスク，斜面における不安定土砂の生産を見積もるのに重要なデータが得られた。