Modelling multidecadal variability in flood frequency using the Two-Component Extreme Value distribution

IF 3.9 3区 环境科学与生态学 Q1 ENGINEERING, CIVIL
Vincenzo Totaro, Andrea Gioia, George Kuczera, Vito Iacobellis
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Abstract

The Two-Component Extreme Value (TCEV) distribution is traditionally known as the exact distribution of extremes arising from Poissonian occurrence of a mixture of two exponential exceedances. In some regions, flood frequency is affected by low-frequency (decadal) climate fluctuations resulting in wet and dry epochs. We extend the exact distribution of extremes approach to such regions to show that the TCEV arises as the distribution of annual maximum floods for Poissonian occurrences and (at least two) exponential exceedances. A case study using coastal basins in Queensland and New South Wales (Australia) affected by low-frequency climate variability, shows that the TCEV produces good fits to the marginal distribution over the entire range of observed values without the explicit need to resort to climate covariates and removal of potentially influential low values. Moreover, the TCEV reproduces the observed dog-leg, a key signature of different flood generation processes. A literature review shows that the assumptions underpinning the TCEV are conceptually consistent with available evidence on climate and flood mechanisms in these basins. We provide an extended domain of the TCEV distribution in the L-moment ratio diagram to account for the wider range of parameter values encountered in the case study and show that for all basins, L-skew and L-kurtosis fall within the extended domain of the TCEV.

Abstract Image

利用双分量极值分布模拟洪水频率的十年多变性
双分量极值分布(TCEV)传统上被认为是由两个指数超标的混合物的泊松发生所产生的极值的精确分布。在某些地区,洪水频率会受到低频(十年一遇)气候波动的影响,从而导致潮湿期和干燥期。我们将极值的精确分布方法扩展到这些地区,以表明 TCEV 是泊松发生和(至少两次)指数超标的年最大洪水的分布。利用昆士兰州和新南威尔士州(澳大利亚)受低频气候变异影响的沿海流域进行的案例研究表明,TCEV 可以很好地拟合整个观测值范围内的边际分布,而无需明确求助于气候协变量和去除潜在影响的低值。此外,TCEV 还再现了观测到的狗腿现象,这是不同洪水生成过程的一个重要特征。文献综述表明,TCEV 所依据的假设在概念上与这些流域气候和洪水机制的现有证据是一致的。我们在 L 动量比图中提供了 TCEV 分布的扩展域,以考虑案例研究中遇到的更大范围的参数值,并表明对于所有流域,L-偏斜和 L-峰度都属于 TCEV 的扩展域。
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来源期刊
CiteScore
7.10
自引率
9.50%
发文量
189
审稿时长
3.8 months
期刊介绍: Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.
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