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Regional estimation of short duration rainfall extremes

机译:短期降雨极端事件的区域估计

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The present study proposes a method for estimating the distribution of short-duration (e.g., 1 hour) extreme rainfalls at sites where data for the time interval of interest do not exist, but rainfall data for longer-duration (e.g., 1 day) are available (partially-gaged sites). The proposed method is based on the recently developed "scale-invariance" (or "scaling") theory. In this study, the scaling concept implies that statistical properties of the extreme rainfall processes for different temporal scales are related to each other by a scale-changing operator involving only the scale ratio. Further, it is assumed that these hydrologic series possess a simple scaling behaviour. The suggested methodology has been applied to extreme rainfall data from a network of 14 recording raingages in Quebec (Canada). The Generalised Extreme Value (GEV) distribution was used to estimate the rainfall quantiles. Results of the numerical application have indicated that for partially-gaged sites the proposed scaling method is able to provide extreme rainfall estimates which are comparable with those based on available at-site rainfall data (C) 1998 Published by Elsevier Science Ltd. All rights reserved. [References: 9]
机译:本研究提出了一种方法,该方法用于估计在不存在感兴趣的时间间隔的数据但存在较长时间(例如1天)的降雨数据的站点上的短期(例如1小时)极端降雨的分布的方法。可用(部分站点)。所提出的方法基于最近开发的“尺度不变性”(或“缩放”)理论。在这项研究中,标度概念暗示着不同时间尺度的极端降雨过程的统计特性由仅涉及比例的标度改变算子相互关联。此外,假定这些水文序列具有简单的水垢行为。所建议的方法已应用于来自魁北克(加拿大)的14个记录降雨网络的极端降雨数据。广义极值(GEV)分布用于估算降雨分位数。数值应用的结果表明,对于部分测量的站点,建议的缩放方法能够提供极端降雨估计,该估计与基于可用的现场降雨量数据(C)1998由Elsevier Science Ltd发布的估计相当。 。 [参考:9]

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