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Risk assessment using a generalized Pareto-based bivariate model

机译:使用基于Pareto的广义双变量模型进行风险评估

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摘要

In hydrology, one often has to study the joint probabilistic behavior of two or more variables characterizing a water system. A model constructed from generalized-Pareto-distributed (GPD) marginals is presented in the present paper to study the relation between two variables. The GPD model is the most popular one used in the 'Peaks-Over-Threshold' (POT) approach for studying hydrological extremes, and is also applicable in the 'Deficit-Below-Threshold' (DBT) approach for modeling low extremes. The bivariate model presented herein, allows for risk assessments and calculations associated with each hydrological variable separately, with one variable conditioned by the other, or with both variables taken together. It will be used to model the joint distribution of the duration (X_1 and the peak discharge above a threshold (X_2) of a real flood series derived from hydrometric data of the Little Southwest Miramichi River, in New Brunswick, Canada.
机译:在水文学中,通常必须研究两个或多个表征水系统的变量的联合概率行为。为了研究两个变量之间的关系,本文提出了一种由广义帕累托分布(GPD)边际构成的模型。 GPD模型是用于研究水文极端值的“阈值上限”(POT)方法中最受欢迎的模型,也适用于“低阈值下阈值”(DBT)方法以模拟低端极端情况。本文介绍的双变量模型允许分别与每个水文变量相关联的风险评估和计算,其中一个变量受另一个条件制约,或者两个变量合在一起。它将用于对持续时间(X_1)和实际洪水序列的阈值(X_2)以上的峰值流量的联合分布进行建模,该序列来自加拿大新不伦瑞克省Little Southwest Miramichi河的水文数据。

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