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Statistical correlation between meteorological and rockfall databases

机译：气象和落石数据库之间的统计相关性

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摘要

Rockfalls are a major and essentially unpredictable sources of danger, particularly along transportation routes (roads and railways). Thus, the assessment of their probability of occurrence is a major challenge for risk management. From a qualitative perspective, it is known that rockfalls occur mainly during periods of rain, snowmelt, or freeze-thaw. Nevertheless, from a quantitative perspective, these generally assumed correlations between rockfalls and their possible meteorological triggering events are often difficult to identify because (i) rockfalls are too rare for the use of classical statistical analysis techniques and (ii) not all intensities of triggering factors have the same probability. In this study, we propose a new approach for investigating the correlation of rockfalls with rain, freezing periods, and strong temperature variations. This approach is tested on three French rockfall databases, the first of which exhibits a high frequency of rockfalls (approximately 950 events over 11 years), whereas the other two databases are more typical (approximately 140 events over 11 years). These databases come from (1) national highway RN1 on Réunion, (2) a railway in Burgundy, and (3) a railway in Auvergne. Whereas a basic correlation analysis is only able to highlight an already obvious correlation in the case of the "rich" database, the newly suggested method appears to detect correlations even in the "poor" databases. Indeed, the use of this method confirms the positive correlation between rainfall and rockfalls in the Réunion database. This method highlights a correlation between cumulative rainfall and rockfalls in Burgundy, and it detects a correlation between the daily minimum temperature and rockfalls in the Auvergne database. This new approach is easy to use and also serves to determine the conditional probability of rockfall according to a given meteorological factor. The approach will help to optimize risk management in the studied areas based on their meteorological conditions.
机译：落石是主要且基本上不可预测的危险源，尤其是沿运输路线（公路和铁路）的危险。因此，对其发生概率的评估是风险管理的主要挑战。从定性的角度来看，已知落石主要发生在降雨，融雪或冻融期间。然而，从定量的角度来看，岩崩及其可能的气象触发事件之间通常假定的相关性通常难以确定，因为（i）岩崩对于使用经典统计分析技术而言太少了，并且（ii）并非所有触发因子的强度具有相同的可能性。在这项研究中，我们提出了一种新的方法来研究落石与降雨，冰冻期和强烈温度变化之间的关系。此方法在三个法国落石数据库上进行了测试，其中第一个数据库显示出落石的频率很高（11年中大约950个事件），而其他两个数据库则更典型（11年中大约140个事件）。这些数据库来自（1）留尼汪的RN1国道，（2）勃艮第的铁路，和（3）奥弗涅的铁路。基本的相关性分析只能在“丰富”数据库的情况下突出显示已经很明显的相关性，而新建议的方法似乎甚至可以在“不良”数据库中检测到相关性。实际上，这种方法的使用证实了留尼汪岛数据库中降雨与落石之间的正相关关系。该方法突出显示了勃艮第地区累积降雨与落石量之间的相关性，并且在Auvergne数据库中检测了每日最低温度与落石量之间的相关性。这种新方法易于使用，并且还可以根据给定的气象因素确定落石的条件概率。该方法将有助于根据研究区域的气象条件优化风险管理。

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