Long-range properties and data validity for hydrogeological time series: The case of the Paglia river

• Published in: Physica A: Statistical Mechanics and its Applications
• Main Authors: Ausloos, Marcel, Cerqueti, Roy, Lupi, Claudio
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier for North-Holland 2017
• Subjects: Science & Technology; Physical Sciences; Physics; Multidisciplinary; River streamflow; Hurst exponent; Benford's law; Detrended fluctuation analysis; Discrete generalized Beta distribution; BENFORDS LAW; MULTIFRACTAL ANALYSIS; BREAKDOWN; AVERAGES; FLOWS; North Atlantic
• Online Access: http://www.sciencedirect.com/science/article/pii/S0378437116309608; http://hdl.handle.net/2381/39632; https://doi.org/10.1016/j.physa.2016.11.137

The file associated with this record is embargoed until 12 months after the date of publication. The final published version may be available through the links above. This paper explores a large collection of about 377,000 observations, spanning more than 20 years with a frequency of 30 min, of the streamflow of the Paglia river, in central Italy. We analyze the long-term persistence properties of the series by computing the Hurst exponent, not only in its original form but also under an evolutionary point of view by analyzing the Hurst exponents over a rolling windows basis. The methodological tool adopted for the persistence is the detrended fluctuation analysis (DFA), which is classically known as suitable for our purpose. As an ancillary exploration, we implement a control on the data validity by assessing if the data exhibit the regularity stated by Benford’s law. Results are interesting under different viewpoints. First, we show that the Paglia river streamflow exhibits periodicities which broadly suggest the existence of some common behavior with El Niño and the North Atlantic Oscillations: this specifically points to a (not necessarily direct) effect of these oceanic phenomena on the hydrogeological equilibria of very far geographical zones: however, such an hypothesis needs further analyses to be validated. Second, the series of streamflows shows an antipersistent behavior. Third, data are not consistent with Benford’s law: this suggests that the measurement criteria should be opportunely revised. Fourth, the streamflow distribution is well approximated by a discrete generalized Beta distribution: this is well in accordance with the measured streamflows being the outcome of a complex system. Peer-reviewed Post-print