A nested multivariate copula approach to hydrometeorological simulations of spring floods: the case of the Richelieu River (Québec, Canada) record flood
A nested multivariate copula approach to hydrometeorological simulations of spring floods: the case of the Richelieu River (Québec, Canada) record flood
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DOI：
10.1007/s00477-014-0971-7
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发表时间：
2014
影响因子：
4.2
通讯作者：
C. Saad;S. El Adlouni;A. St‐Hilaire;P. Gachon
中科院分区：
文献类型：
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作者：
C. Saad;S. El Adlouni;A. St‐Hilaire;P. Gachon
洪水对人口、工业和环境系统具有潜在的破坏性后果。它们通常是气象、地理学和人为因素综合作用的结果。多变量视角下的洪水灾害分析对于评估多个综合因素至关重要。本研究利用频率分析以及提出的多元关联方法和水文气象指数，从降水的发生、频率、持续时间和强度以及洪水之前和洪水期间的温度事件及其组合来分析春季洪水引发机制。这项研究在黎塞留河流域（加拿大魁北克省）发起，特别关注 2011 年春季洪水，这是上世纪该地区最具破坏性的事件之一。尽管已经开展了一些工作来确定这次创纪录洪水的某些原因，但尚未探索使用水文和气象事件的多元统计分析。本研究提出了一种基于水文气象背景下完全嵌套的阿基米德弗兰克和克莱顿系词的多变量洪水风险模型。通过在三变量情况下应用所提出的模型来估计联合和条件重现期，确定了 2011 年黎塞留河洪水引发气象因素的几种组合。冬季每日霜冻/融雪频率、11 月至 3 月的累积总降水量以及春季 90% 的降雨量对峰值流量和洪水持续时间的影响均得到量化，因为这些综合因素代表了 2011 年黎塞留河创纪录洪水的相关驱动因素。还分析了多种合理且有实际依据的洪水引发情景，以量化各种洪水风险。
Floods have potentially devastating consequences on populations, industries and environmental systems. They often result from a combination of effects from meteorological, physiographic and anthropogenic natures. The analysis of flood hazards under a multivariate perspective is primordial to evaluate several of the combined factors. This study analyzes spring flood-causing mechanisms in terms of the occurrence, frequency, duration and intensity of precipitation as well as temperature events and their combinations previous to and during floods using frequency analysis as well as a proposed multivariate copula approach along with hydrometeorological indices. This research was initiated over the Richelieu River watershed (Quebec, Canada), with a particular emphasis on the 2011 spring flood, constituting one of the most damaging events over the last century for this region. Although some work has already been conducted to determine certain causes of this record flood, the use of multivariate statistical analysis of hydrologic and meteorological events has not yet been explored. This study proposes a multivariate flood risk model based on fully nested Archimedean Frank and Clayton copulas in a hydrometeorological context. Several combinations of the 2011 Richelieu River flood-causing meteorological factors are determined by estimating joint and conditional return periods with the application of the proposed model in a trivariate case. The effects of the frequency of daily frost/thaw episodes in winter, the cumulative total precipitation fallen between the months of November and March and the 90th percentile of rainfall in spring on peak flow and flood duration are quantified, as these combined factors represent relevant drivers of this 2011 Richelieu River record flood. Multiple plausible and physically founded flood-causing scenarios are also analyzed to quantify various risks of inundation.