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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Efron B, Tibshirani R (1993) An Introduction to the Bootstrap. Chapman & Hall/CRC, Boca Raton
Guadagnini A, Riva M, Neuman SP (2012) Extended power-law scaling of heavy-tailed random air-permeability fields in fractured and sedimentary rocks. Hydrol Earth Syst Sci 16:3249–3260. doi:10.5194/hess-16-3249-2012
Mualem Y (1976) A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour Res 12(3):513–522
Neuman SP, Guadagnini A, Riva M, Siena M (2013) Recent advances in statistical and scaling analysis of earth and environmental variables. Recent advances in hydrogeology. Springer, New York, pp 1–15
Pachepsky Y, Rawls WJ (eds) (2004) Development of pedotransfer functions in soil hydrology. Elsevier, Amsterdam, The Netherlands
Riva M, Neuman SP, Guadagnini A (2013a) Sub-Gaussian model of processes with heavy tailed distributions applied to permeabilities of fractured tuff. Stoch Environ Res Risk Assess 27:195–207. doi:10.1007/s00477-012-0576-y
Riva M, Neuman SP, Guadagnini A, Siena M (2013b) Anisotropic scaling of Berea sandstone log air permeability statistics. Vadose Zone J 12(3). doi:10.2136/vzj2012.0153 (in press)
Schaap MG (2013) Description, analysis and interpretation of an infiltration experiment in a semi-arid deep vadose zone. Recent advances in hydrogeology. Springer, New York, pp 159–183
Schaap MG, Leij FJ (1998) Database related accuracy and uncertainty of pedotransfer functions. Soil Sci 163:765–779
Schaap MG, Leij FJ, van Genuchten MTh (2001) Rosetta: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. J Hydrol 251:163–176
Schaap MG, Nemes A, Van Genuchten MTh (2004) Comparison of models for indirect estimation of water retention and available water in surface soils. Vadose Zone J 3:1455–1463
Siena M, Guadagnini A, Riva M, Neuman SP (2012) Extended power-law scaling of air permeabilities measured on a block of tuff. Hydrol Earth Syst Sci 16:29–42. doi:10.5194/hess-16-29-2012
van Genuchten MTh (1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44:892–898
Acknowledgments
Our work was supported in part through a contract between the University of Arizona and Vanderbilt University under the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) III, funded by the U.S. Department of Energy.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Guadagnini, A., Neuman, S.P., Schaap, M.G., Riva, M. (2015). Alternative to Multifractal Analysis of Scalable Random Variables Applied to Measured and Estimated Soil Properties at an Arizona Field Site. In: Obaidat, M., Koziel, S., Kacprzyk, J., Leifsson, L., Ören, T. (eds) Simulation and Modeling Methodologies, Technologies and Applications. Advances in Intelligent Systems and Computing, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-319-11457-6_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-11457-6_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11456-9
Online ISBN: 978-3-319-11457-6
eBook Packages: EngineeringEngineering (R0)