Stochastic Simulation of Streamflow Time Series using Phase Randomization

Provides a simulation framework to simulate streamflow time series with similar main characteristics as observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. The approach is based on the randomization of the phases of the Fourier transform. We further use the flexible four-parameter Kappa distribution, which allows for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. A detailed description of the simulation approach and an application example can be found in <>.


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1.1 by Manuela Brunner, 2 months ago

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Authors: Manuela Brunner [aut, cre] , Reinhard Furrer [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports stats

Depends on homtest, goftest

Suggests lattice, ismev, evd, GB2

See at CRAN