Nonstationary frequency analysis of the recent extreme precipitation events in the United States
Nonstationary frequency analysis of the recent extreme precipitation events in the United States
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DOI：
10.1016/j.jhydrol.2019.05.090
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发表时间：
2019-08
影响因子：
6.4
通讯作者：
T. Vu;A. Mishra
中科院分区：
文献类型：
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作者：
T. Vu;A. Mishra
气候变化导致的水文循环加剧可能影响极端降水特征（即强度、持续时间和频率）。这些降水特征被整合到构建强度-持续时间-频率（IDF）曲线中，该曲线广泛用于设计民用基础设施系统。这些IDF曲线通常是基于平稳假设得出的，然而，极端降水事件的频率和强度可能由于气候变化而变得非平稳。在过去的几十年里，美国出现了千年一遇的异常极端降水事件。本文通过结合时间、最高温度、平均温度和El Niño南方涛动周期（ENSO）等时变协变量，研究了最近发生在不同持续时间（1天、3天和5天）的极端降水事件的非平稳性。结合时变协变量，采用非平稳广义极值分布对这些极端事件进行非平稳频率分析。结果表明，极端降水事件的大部分时间演变遵循非平稳模式，这可能是由于最近极端降水事件的强度增加，特别是在飓风事件期间。协变量的不同组合会对非平稳频率分析产生潜在影响，且随着极端降水事件累积周期的增加，协变量的类型可能会有所不同。基于非平稳极值分析，与平稳方法相比，与极端降水事件相关的回归周期显著缩短。
The intensification of the hydrologic cycle due to climate change is likely to influence the extreme precipitation characteristics (i.e., intensity, duration and frequency). These precipitation characteristics are integrated to construct Intensity-Duration-Frequency (IDF) curves that are widely used to design civil infrastructure systems. These IDF curves are typically derived based on the stationary assumption, however, the frequency and intensity of extreme precipitation events likely to become nonstationary as a consequence of climate change. During the past decades, unusual extreme precipitation events with more than thousand-year return periods were recorded in the United States. This study investigates the nonstationary nature of the most recent extreme precipitation events occurred over different durations (1-, 3- and 5-days) by incorporating time-varying covariates, such as time, maximum temperature, mean temperature, and the El Niño Southern Oscillation cycle (ENSO). The nonstationary frequency analysis for these extreme events was conducted using nonstationary Generalized Extreme Value distribution by incorporating the time-varying covariates. It was observed that most of the temporal evolution of extreme precipitation events follow the nonstationary pattern, which may be due to the increase in the magnitude of recent extreme precipitation events, especially during hurricane events. Different combination of covariates can potentially influence the nonstationary frequency analysis, and the type of covariate may differ when the accumulated period of extreme precipitation event increased. Based on the Nonstationary Extreme Value Analysis, the return periods associated with extreme precipitation events significantly reduced compared to the stationary approach.