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A threshold sum approach to stability evaluation of manual snow profiles

机译:人工雪廓线稳定性评估的阈值和方法

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Snow profile interpretation has developed in the last few years from being based on experience into a semi-quantitative scientific method. Emphasizing structural rather than mechanical instability, threshold values were developed for key parameters such as weak layer grain size and hardness, and differences in grain size and hardness between layers. Despite promising attempts so far it has not been shown that this method works to quantitatively interpret snow profiles, in particular if the principal weakness is unknown. Our aim was to provide an easy and robust method based on a threshold sum approach to assess snowpack stability based on layer properties. Second, we investigated whether that method was also suited to find the principal weakness (in case it is unknown) and assess the probability for a skier-triggered avalanche on this weakness. Our data set consisted of 500 manual snow profiles observed over 16 years on skier-tested and skier-triggered avalanche slopes from both western Canada and Switzerland. A weighted threshold sum with the failure layer depth as independent variable scored highest (77% for the learning data set, 65% for the test data set). Detection of potentially critical layers proved to be less successful, in particular for the Swiss profiles. If the principal weakness was unknown, the stability classification for the potentially critical layers agreed with the observed stability for the Swiss profiles in about 53% and for the Canadian profiles in about 62% of the cases. The results emphasize that stability assessment should include - besides stability tests that help locate the principal weakness - analysis of snow layer properties, in particular grain size, type and hardness. The proposed threshold sum considering seven variables is well suited for profile analysis of manual profiles by practitioners. Stability classification of snow profiles simulated by snow cover models such as SNOWPACK will need further adaptation, in particular for application in transitional snow climates.
机译:在过去的几年中,雪廓线解释已经从基于经验的方法发展成为一种半定量的科学方法。为了强调结构而不是机械的不稳定性,针对关键参数(例如,薄层的晶粒尺寸和硬度以及层之间晶粒尺寸和硬度的差异)开发了阈值。尽管迄今为止进行了有希望的尝试,但尚未显示出该方法可用于定量解释雪廓,特别是在主要弱点未知的情况下。我们的目标是提供一种基于阈值总和方法的简便且健壮的方法,以基于图层属性评估积雪的稳定性。其次,我们调查了该方法是否也适合发现主要缺陷(如果未知),并评估了由滑雪者触发的对此缺陷进行雪崩的可能性。我们的数据集包括在16年中在加拿大西部和瑞士的滑雪者测试和滑雪者触发的雪崩斜坡上观察到的500个手动雪剖面。以故障层深度作为自变量的加权阈值总和得分最高(学习数据集为77%,测试数据集为65%)。事实证明,对潜在关键层的检测不太成功,尤其是对于瑞士剖面而言。如果主要弱点未知,则潜在关键层的稳定性分类与观察到的瑞士剖面约53%和加拿大剖面约62%的稳定性相符。结果强调,稳定性评估应包括-除了有助于确定主要缺陷的稳定性测试以外-分析雪层特性,尤其是粒度,类型和硬度。建议的阈值总和考虑了七个变量,非常适合从业人员对手动配置文件进行配置文件分析。由诸如SNOWPACK之类的积雪模型模拟的积雪剖面的稳定性分类将需要进一步调整,尤其是在过渡性积雪气候中的应用。

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