Pith. sign in

REVIEW

Long-term persistence and multifractality of river runoff records: Detrended fluctuation studies

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv physics/0305078 v3 pith:JDE33WDM submitted 2003-05-19 physics.geo-ph cond-mat.stat-mechphysics.data-an

classification physics.geo-phcond-mat.stat-mechphysics.data-an
keywords riverfluctuationgammalong-termmultifractalmultifractalityrecordsanalysis
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We study temporal correlations and multifractal properties of long river discharge records from 41 hydrological stations around the globe. To detect long-term correlations and multifractal behaviour in the presence of trends, we apply several recently developed methods [detrended fluctuation analysis (DFA), wavelet analysis, and multifractal DFA] that can systematically detect and overcome nonstationarities in the data at all time scales. We find that above some crossover time that usually is several weeks, the daily runoffs are long-term correlated, being characterized by a correlation function C(s) that decays as C(s) ~ s^(gamma). The exponent gamma varies from river to river in a wide range between 0.1 and 0.9. The power-law decay of C(s) corresponds to a power-law increase of the related fluctuation function F_2(s) ~ s^H where H = 1-gamma/2. We also find that in most records, for large times, weak multifractality occurs. The Renyi exponent tau(q) for q between -10 and +10 can be fitted to the remarkably simple form tau(q) = -ln(a^q+b^q) /ln 2, with solely two parameters a and b between 0 and 1 with a+b >= 1. This type of multifractality is obtained from a generalization of the multiplicative cascade model.

Discussion (0). Continue with ORCID to comment.

Pith tools