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Probabilistic definition and analysis of severe rainy events

机译:严重降雨事件的概率定义和分析

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摘要

Human activities are often subject to damages resulting from exceptional rainy events. The character of exceptionality of a rainy event may be due only to one or to many factors. In particular the total rainfall amount, the maximum intensity, the average intensity and the total duration affect the natural catastrophic phenomena. Based on this concept, a methodology to identify severe rainy events is proposed, with the aim to select and characterize those events potentially more dangerous to human activities. The single normal rainy event is simply defined by being preceded and followed by at least one not rainy day; the events are considered severe according to the overcoming of one or more threshold values of the aforesaid factors. The study refers to the method of peaks over threshold (P.O.T.), based on the theory of the rare events and on the extreme values theory. The first theory was introduced by Poisson and aims exclusively to define the relations between the number of events and their low probability of occurrence; the second theory is usually adopted for the annual maximum analysis and deals just with the size of the events, with no account for their number. Actually the reduction law of the number of events when the threshold values are increasing is illustrated by simple correlative relationships . An application to rainfall data of the North area of Stretta di Catanzaro (Calabria, Southern Italy) is proposed, comparing the results with those of an historical investigation regarding landslides and flooding. The analysis allows to assess the temporal and spatial distribution of the most severe events and to evaluate their hazard for forecasting and/or real-time alert system identification. Particular sites and year periods that are more frequently subject to severe events are identified, in this way we can identify homogeneous regions keeping constant values of parameters.
机译:人类活动通常会因特殊的降雨事件而遭受损害。下雨事件的特殊性可能仅由一个或多个因素引起。特别是总降雨量,最大强度,平均强度和总持续时间会影响自然灾害现象。基于此概念,提出了一种识别严重下雨事件的方法,旨在选择和表征那些对人类活动可能更危险的事件。通过在至少一个非雨天之前和之后定义一个正常的多雨事件。根据克服上述因素的一个或多个阈值,事件被认为是严重的。该研究基于罕见事件的理论和极值理论,参考了超过阈值的峰值方法(P.O.T.)。第一个理论是由泊松(Poisson)提出的,旨在专门定义事件数量与事件发生概率较低之间的关系。第二种理论通常用于年度最大分析,并且仅处理事件的大小,而不考虑事件的数量。实际上,通过简单的相关关系可以说明阈值增加时事件数量的减少规律。提议将Stretta di Catanzaro(意大利南部的卡拉布里亚)北部地区的降雨数据应用,并将结果与​​有关滑坡和洪水的历史调查结果进行比较。该分析允许评估最严重事件的时间和空间分布,并评估其危害以进行预测和/或实时警报系统识别。确定更容易发生严重事件的特定站点和年份,这样我们可以确定保持参数恒定值的均匀区域。

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