Stochastic Simulation of Streamflow Time Series using Phase
Randomization
Description
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 .