Modelling the statistical dependence of rainfall event variables through copula functions
By M. Balistrocchi, Baldassare Bacchi. 2011
57 citations recorded by the source corpus.
Abstract. In many hydrological models, such as those derived by analytical probabilistic methods, the precipitation stochastic process is represented by means of individual storm random variables which are supposed to be independent of each other. However, several proposals were advanced to develop joint probability distributions able to account for the observed statistical dependence. The traditional technique of the multivariate statistics is nevertheless affected by several drawbacks, whose most evident issue is the unavoidable subordination of the dependence structure assessment to the marginal distribution fitting. Conversely, the copula approach can overcome this limitation, by dividing the problem in two distinct parts. Furthermore, goodness-of-fit tests were recently made available and a significant improvement in the function selection reliability has been achieved. Herein the dependence structure of the rainfall event volume, the wet weather duration and the interevent time is assessed and verified by test statistics with respect to three long time series recorded in different Italian climates. Paired analyses revealed a non negligible dependence between volume and duration, while the interevent period proved to be substantially independent of the other variables. A unique copula model seems to be suitable for representing this dependence structure, despite the sensitivity demonstrated by its parameter towards the threshold utilized in the procedure for extracting the independent events. The joint probability function was finally developed by adopting a Weibull model for the marginal distributions.
Subfields: Atmospheric Science, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/25e6c0fc69c2dd5c3242556564db18ce73b6c660
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In Global and Planetary Change
Citations in the corpus
- Trivariate Frequency Analyses of Peak Discharge, Hydrograph Volume and Suspended Sediment Concentration Data Using Copulas (2014, background): “…of dam spillway (De Michele et al. 2005), for flood coincidence risk analyses (Chen et al. 2012), for rainfall analyses (Zhang and Singh 2007a; Balistrocchi and Bacchi 2011), for geostatistical interpolations (Bardossy and Li 2008; Bardossy 2011) and also for flood frequency analyses (Favre…”
- Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River (2015, background): “…rainfall analysis (Singh and Zhang, 2007; Zhang and Singh, 2007a; Gargouri-Ellouze and Chebchoub, 2008; Ghosh, 2010; Vandenberghe et al., 2010; Balistrocchi and Bacchi, 2011; Ariff et al., 2012), assessing the risk of dam overtopping (De Michele et al., 2005), hyetograph analysis (Grimaldi…”