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Generation of Sub-Hourly Rainfall Events through a Point Stochastic Rainfall Model

机译:通过点随机降雨模型生成半小时降雨事件

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The aim of this paper is to present a stochastic model to generate sub-hourly rainfall events at a given point. Historical events used as the input have been extracted by the sub-hourly rainfall series available for a defined rain gauge station based on a fixed inter-event time and selected if their average intensity was larger than a critical fixed one. The sub-hourly events generated by applying the proposed methodology are completely stochastic and their main characteristics, i.e., shape, duration and average intensity, have been derived as a function of the statistics of the historical events analyzed. In order to characterize the shape, dimensionless hyetographs have been derived. They have been statistically modelled by using the Beta cumulative distribution. Average intensity and duration of the historical events were first modelled separately by fitting several probability distributions and selecting the best one using the more common statistical criteria. Then, their correlation was modelled using the Frank’s copula. In order to test the methodology, two sites in Sicily, Italy, where 10 min’ recorded rainfall data were available, were analyzed. Finally, comparison between the statistics of the simulated events and those of the measured data demonstrates the good performance of the model.
机译:本文的目的是提出一个随机模型,以在给定的点生成次小时降雨事件。用作输入的历史事件已通过固定时间间隔的事件间时间,通过可用于定义的雨量计站的亚小时降雨序列进行提取,如果历史事件的平均强度大于关键的固定时间,则进行选择。通过应用所提出的方法所产生的亚小时事件是完全随机的,并且其主要特征(即形状,持续时间和平均强度)已根据所分析的历史事件的统计数据得出。为了表征形状,已经衍生出无量纲的吸油描记器。他们已经使用Beta累积分布进行了统计建模。首先通过拟合几种概率分布并使用更通用的统计标准选择最佳概率分布,分别对历史事件的平均强度和持续时间进行建模。然后,使用弗兰克的系词对它们的相关性进行建模。为了测试该方法,对意大利西西里岛的两个站点进行了分析,那里提供了10分钟的记录降雨数据。最后,模拟事件统计数据与实测数据统计数据之间的比较证明了该模型的良好性能。

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