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Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme

机译:极端降雨事件的概率包络曲线-极端降水的概率包络曲线

摘要

A regional envelope curve (REC) of flood flows summarises the current bound on our experience of extreme floods in a region. RECs are available for most regions of the world. Recent scientific papers introduced a probabilistic interpretation of these curves and formulated an empirical estimator of the recurrence interval T associated with a REC, which, in principle, enables us to use RECs for design purposes in ungauged basins.udThe main aim of this work is twofold. First, it extends the REC concept to extreme rainstorm events by introducing the Depth-Duration Envelope Curves (DDEC), which are defined as the regional upper bound on all the record rainfall depths at present for various rainfall duration. Second, it adapts the probabilistic interpretation proposed for RECs to DDECs and it assesses the suitability of these curves for estimating the T-year rainfall event associated with a given duration and large T values. Probabilistic DDECs are complementary to regional frequency analysis of rainstorms and their utilization in combination with a suitable rainfall-runoff model can provide useful indications on the magnitude of extreme floods for gauged and ungauged basins.udThe study focuses on two different national datasets, the peak over threshold (POT) series of rainfall depths with duration 30 min., 1, 3, 9 and 24 hrs. obtained for 700 Austrian raingauges and the Annual Maximum Series (AMS) of rainfall depths with duration spanning from 5 min. to 24 hrs. collected at 220 raingauges located in northern-central Italy. The estimation of the recurrence interval of DDEC requires the quantification of the equivalent number of independent data which, in turn, is a function of the cross-correlation among sequences. While the quantification and modelling of intersite dependence is a straightforward task for AMS series, it may be cumbersome for POT series. This paper proposes a possible approach to address this problem.
机译:洪水的区域包络曲线(REC)总结了当前我们在一个地区发生特大洪水的经验的界限。 REC适用于世界上大多数地区。最近的科学论文介绍了这些曲线的概率解释,并提出了与REC相关的递归间隔T的经验估计量,从原则上讲,这使我们能够将RECs用于未填充盆地的设计目的。 ud这项工作的主要目的是双重。首先,它通过引入深度持续时间包络曲线(DDEC)将REC概念扩展到极端暴雨事件,深度包络曲线被定义为当前所有记录的降雨深度在各种降雨持续时间内的区域上限。其次,它使针对REC提出的概率解释适应于DDEC,并评估了这些曲线对估计与给定持续时间和较大T值相关的T年降雨事件的适用性。概率DDEC是区域性暴雨频率分析的补充,它们的使用与适当的降雨径流模型相结合,可以为已确定流域和未建立流域的极端洪水的规模提供有用的指示。 30分钟,1、3、9和24小时持续时间的降雨深度的超阈值(POT)系列。获得了700个奥地利雨量计和年度最大降雨深度序列(AMS),持续时间为5分钟。至24小时。收集了位于意大利中北部的220个雨量计。 DDEC重复间隔的估计需要量化等效数据的独立数据量,而后者又是序列之间互相关的函数。虽然对站点间相关性的量化和建模对于AMS系列而言是一项直接的任务,但对于POT系列而言可能会很麻烦。本文提出了一种可能的方法来解决此问题。

著录项

  • 作者

    Tagliaferri Lorenza;

  • 作者单位
  • 年度 2008
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"it","name":"italian","id":21}
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