A stochastic design rainfall generator based on copulas and mass curves

By Sander Vandenberghe, Niko E. C. Verhoest, E. Buyse, B. De Baets. 2010

65 citations recorded by the source corpus.

Abstract. The use of design storms can be very useful in many hydrological and hydraulic practices. In this study, the concept of a copula-based secondary return period in combination with the concept of mass curves is used to generate point-scale design storms. The analysis is based on storms selected from the 105 year rainfall time series with a 10 min resolution, measured at Uccle, Belgium. In first instance, bivariate copulas and secondary return periods are explained, together with a focus on which couple of storm variables is of highest interest for the analysis and a discussion of how the results might be affected by the goodness-of-fit of the copula. Subsequently, the fitted copula is used to sample storms with a predefined secondary return period for which characteristic variables such as storm duration and total storm depth can be derived. In order to construct design storms with a realistic storm structure, mass curves of 1st, 2nd, 3rd and 4th quartile storms are developed. An analysis shows that the assumption of independence between the secondary return period and the internal storm structure could be made. Based on the mass curves, a technique is developed to randomly generate an intrastorm structure. The coupling of both techniques eventually results in a methodology for stochastic design storm generation. Finally, its practical usefulness for design studies is illustrated based on the generation of a set of statistically identical design storm and rainfall-runoff modelling.

Subfields: Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/29705ab6a73e9448ba5799bc995d78890098f2b6

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In Global and Planetary Change

In Water Science and Technology

Citations in the corpus

A continuous rainfall model based on vine copulas (2015, unknown): “Vandenberghe et al. (2010b) asserted that the hypothesis of stationarity of storms on the Uccle time series is fulﬁlled through seasonally sub-dividing the storms allowing copulas to be ﬁtted per season.”
A comparative copula‐based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett‐Lewis modeled rainfall (2011, methodology): “However, one could consider using another independence criterion dictated by the application in which the storms are to be used, e.g., the concentration time of the catchment under study [ Vandenberghe et al., 2010b ].”