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Censored rainfall modelling for estimation of fine-scale extremes

机译:审查了降雨模型,估算细尺极端

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摘要

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.
机译:降雨极端的可靠估计对于排水系统设计,洪水缓解和风险量化至关重要。然而,传统技术缺乏物理现实主义和外推能高度不确定。在这项研究中,我们通过使用Bartlett-Lewis矩形脉冲(BLRP)模型来模拟降雨记录的重量部分来改善短期极端降雨估计的物理基础。机械降雨模型在细时秤上有降雨极端的倾向。尽管如此,矩形脉冲模型的简单过程表示在极端降雨估计的背景下吸引,因为它模拟了降雨量的已知现象学。提出了对Bartlett-Lewis模型校准的审查方法,并在英国和德国的两个仪表中进行单点降雨。对于5,15和60分辨率的每个仪表进行极端降雨估计,并讨论了审查选择的考虑因素。

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