Abstract:
Climate Change hypothesis pushed the scientific community to question the characteristics of the classical
statistics such as mean, variance, standard deviation, covariance, etc. in the hydroclimatic field. Many studies have revealed
that the climate has always changed and that these changes are closely related to the Hurst phenomenon detected in long
hydroclimatic time series and in stochastic term which is equivalent to a simple scaling behavior of climate variability on the
time scale. A new statistical framework taking into account the climatic variability is now applied. Most studies are at annual
scale where variability at finer scales is not taken into account. This paper proposes to verify the validity of the new statistical
framework at finer time scale: the daily time scale. Twelve (12) daily time series of flows, rainfalls and temperatures with
18,628 observations, each one, were studied. Four different methods, such as Rescaled range Statistic (R/S) method, R/S
modified method, Aggregate Variances method and Aggregated Standard Deviation (ASD) were applied to determine the
Hurst exponent (H). All methods lead to the conclusion that the investigated time series have a long-term persistence
phenomenon. Contrary to annual time series where variability corresponds to a Simple Scaling Stochastic (SSS) process, the
daily time series seem to correspond to a process having both a SSS component and a deterministic component.
