Extremes on river networks

By Peiman Asadi, A. C. Davison, Sebastian Engelke. 2015

144 citations recorded by the source corpus.

Max-stable processes are the natural extension of the classical extreme-value distributions to the functional setting, and they are increasingly widely used to estimate probabilities of complex extreme events. In this paper we broaden them from the usual situation in which dependence varies according to functions of Euclidean distance to situations in which extreme river discharges at two locations on a river network may be dependent because the locations are flow-connected or because of common meteorological events. In the former case dependence depends on river distance, and in the second it depends on the hydrological distance between the locations, either of which may be very different from their Euclidean distance. Inference for the model parameters is performed using a multivariate threshold likelihood, which is shown by simulation to work well. The ideas are illustrated with data from the upper Danube basin.

Subfields: Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/f688f9638803bd70c29713a1462c785bfe65b807

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Citations in the corpus

Causal discovery in heavy-tailed models (2019, methodology): “For convenience, we name the stations with the same numbers used in Asadi, Davison and Engelke (2015).”
Functional peaks‐over‐threshold analysis (2020, background): “Yr are available for risk functionals such as r1(x) = ‖x‖1 or r2(x) = sups∈S x(s); see Asadi et al. (2015), for example.”
Modeling the spatial dependence of floods using the Fisher copula (2019, methodology): “The Euclidean distance is used as a standard distance measure when looking at spatial extremes such as precipitation, temperature, and wind (Asadi et al., 2015) However, our study as well as the one by Asadi et al. (2015) for the Danube River have shown that the Euclidean distance be-tween stations…”
Determining the dependence structure of multivariate extremes (2018, background): “(2013) and Asadi et al. (2015). As high river flow is mainly caused by heavy rainfall, we may observe extreme river flow readings at several locations simultaneously if they are affected by the same extreme weather event.”
Modelling spatial extreme events with environmental applications (2018, background): “It may be that both of these formulations are too simplistic and the process is asymptotically dependent up to a certain lag hAD, then asymptotically independent when the lag exceeds hAD, such as in the models of Bacro et al. (2016).”