Multifractality of river runoff and precipitation: Comparison of fluctuation analysis and wavelet methods

Jan W. Kantelhardt, Diego Rybski, Stephan A. Zschiegner, Peter Braun, Eva Koscielny-Bunde, Valerie Livina, Shlomo Havlin, Armin Bunde

Research output: Contribution to journalConference articlepeer-review

196 Scopus citations


We study the multifractal temporal scaling properties of river discharge and precipitation records. We compare the results for the multifractal detrended fluctuation analysis method with the results for the wavelet-transform modulus maxima technique and obtain agreement within the error margins. In contrast to previous studies, we find non-universal behaviour: on long time scales, above a crossover time scale of several weeks, the runoff records are described by fluctuation exponents varying from river to river in a wide range. Similar variations are observed for the precipitation records which exhibit weaker, but still significant multifractality. For all runoff records the type of multifractality is consistent with a modified version of the binomial multifractal model, while several precipitation records seem to require different models.

Original languageEnglish
Pages (from-to)240-245
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Issue number1-2
StatePublished - 1 Dec 2003
EventRandomes and Complexity - Eilat, Israel
Duration: 5 Jan 20039 Jan 2003

Bibliographical note

Funding Information:
We would like to thank the German Science Foundation (DFG), the German Federal Ministry of Education and Research (BMBF), the Israel Science Foundation (ISF), and the Minerva Foundation for financial support. We also would like to thank H. Österle from PIK, Potsdam, for providing some of the observational data.


  • Fluctuation analysis
  • Long-term correlations
  • Multifractality
  • Precipitation
  • Runoff
  • Time series
  • Wavelet analysis


Dive into the research topics of 'Multifractality of river runoff and precipitation: Comparison of fluctuation analysis and wavelet methods'. Together they form a unique fingerprint.

Cite this