Alternative to multifractal analysis of scalable random variables applied to measured and estimated soil properties at an Arizona field site

Alberto Guadagnini, Shlomo P. Neuman, Marcel G. Schaap, Monica Riva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Many earth, environmental, ecological, biological, physical, astrophysical and financial variables exhibit random space-time fluctuations; symmetric, non-Gaussian frequency distributions of increments characterized by heavy tails that often decay with separation distance or lag; nonlinear power-law scaling of sample structure functions (moments of absolute increments) in a midrange of lags, with breakdown in such scaling at small and large lags; extended power-law scaling at all lags; nonlinear scaling of power-law exponent with order of sample structure function; and pronounced statistical anisotropy. The literature has traditionally considered such variables to be multifractal. Previously we proposed a simpler and more comprehensive interpretation that views them as samples from stationary, anisotropic sub-Gaussian random fields or processes subordinated to truncated fractional Brownian motion or truncated fractional Gaussian noise. The variables thus represent mixtures of Gaussian components having random variances. We apply our novel approach to soil data collected at an Arizona field site and to corresponding hydraulic properties obtained by means of a neural network model and estimate their statistical scaling parameters by maximum likelihood. Our approach allows upscaling or downscaling statistical moments of such variables to fit diverse measurement or resolution and sampling domain scales.

Original languageEnglish (US)
Title of host publicationSimulation and Modeling Methodologies, Technologies and Applications - International Conference, SIMULTECH 2013, Revised Selected Papers
EditorsTuncer Ören, Janusz Kacprzyk, Slawomir Koziel, Leifur Leifsson, Mohammad S. Obaidat
PublisherSpringer-Verlag
Pages133-143
Number of pages11
ISBN (Electronic)9783319114569
DOIs
StatePublished - Jan 1 2015
Event3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2013 - Reykjavík, Iceland
Duration: Jul 29 2013Jul 31 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume319
ISSN (Print)2194-5357

Other

Other3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2013
CountryIceland
CityReykjavík
Period7/29/137/31/13

Keywords

  • Multifractals
  • Neural network
  • Scaling
  • Soil properties
  • Sub-Gaussian

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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