Abstract Under future climate regimes, the risk of typhoons accompanied by heavy rains is expected to increase. Although the risk of disturbance to forest stands by strong winds has long been of interest, we have little knowledge of how the process is mediated by storms and precipitation. Using machine learning, we assess the disturbance risk to cool-temperate forests by typhoons that landed in northern Japan in late August 2016 to determine the features of damage caused by typhoons accompanied by heavy precipitation, discuss how the process is mediated by precipitation as inferred from the modelling results, and delineate the effective solutions for forest management to decrease the future risk in silviculture. In the results, we confirmed two types of behaviours in the model: one represents the same process as that of forest disturbance by strong wind, which has been widely studied, and another represents a unique process mediated by storms and precipitation that has not been previously investigated. Specifically, the ridges that received strong wind from the front side had the highest risk of disturbance. Precipitation increased the probability of disturbance in forest stands, and its effect was dependent on the dominant species composition. Our hypothesis regarding treefall mediated by storms and precipitation is that rainwater flows into the gaps around the tree root systems during sway and the introduction of rainwater below the root-soil plate decreases the root anchorage. The species-specific vulnerability to rainfall may depend on the volume of lateral roots. Modelling the disturbance risk helped us to examine the kinds of factors that were related to exposure and vulnerability that should be managed to effectively decrease the risk of disturbance by typhoons during future uncontrollable hazards. It is recommended to avoid silviculture on the ridges of plateaus considering the high risk estimated in this area. In addition, species with dense lateral roots would be suitable for planting because they may have high resistance to typhoons with heavy precipitation.

中文翻译：

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日本北部强降水台风对森林干扰的风险评估

摘要 在未来的气候状况下，台风伴随暴雨的风险预计会增加。尽管强风对森林造成干扰的风险长期以来一直备受关注，但我们对风暴和降水如何调节这一过程知之甚少。使用机器学习，我们评估了 2016 年 8 月下旬登陆日本北部的台风对冷温带森林的干扰风险，以确定伴随强降水的台风造成的破坏特征，讨论该过程是如何通过降水介导的建模结果，并描绘森林管理的有效解决方案，以降低造林未来的风险。在结果中，我们确认了模型中的两种行为：一个代表与强风对森林的干扰相同的过程，已被广泛研究，另一个代表以前从未研究过的风暴和降水介导的独特过程。具体而言，从正面受到强风的山脊受到干扰的风险最高。降水增加了林分干扰的可能性，其影响取决于优势物种组成。我们关于风暴和降水介导的树木倒塌的假设是，雨水在摇摆过程中流入树木根系周围的间隙，并且在根-土壤板下方引入雨水会降低根系锚固。特定物种对降雨的脆弱性可能取决于侧根的体积。对干扰风险进行建模有助于我们检查与暴露和脆弱性相关的各种因素，这些因素应加以管理，以在未来无法控制的灾害中有效降低台风干扰的风险。考虑到该地区估计的高风险，建议避免在高原山脊上造林。此外，侧根茂密的树种也适合种植，因为它们可能对强降水的台风有很强的抵抗力。