Scaling analysis of soil water retention parameters and physical properties of a Chinese agricultural soil
Zhenying Wang A B , Qiaosheng Shu C , Zuoxin Liu A E and Bingcheng Si DA Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
B Graduate University of the Chinese Academy of Sciences, Beijing 100039, China.
C Liaoning Institute of Soil and Water Conservation, Chaoyang 122000, China.
D Department of Soil Science, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada.
E Corresponding author. Email: zuoxin_liu@163.com
Australian Journal of Soil Research 47(8) 821-827 https://doi.org/10.1071/SR09036
Submitted: 26 February 2009 Accepted: 21 August 2009 Published: 11 December 2009
Abstract
Measurement scale of soil water retention parameters is often different from the application scale. Knowledge of scaling property of soil hydraulic parameters is important because scaling allows information to be transferred from one scale to another. The objective of this study is to examine whether these parameters have fractal scaling properties in a cultivated agricultural soil in China. Undisturbed soil samples (128) were collected from a 640-m transect at Fuxin, China. Soil water retention curve and soil physical properties were measured from each sample, and residual water content (θr), saturated soil water content (θs), and parameters αvG and n of the van Genuchten water retention function were determined by curve-fitting. In addition, multiple scale variability was evaluated through multifractal analyses.
Mass probability distribution of all properties was related to the support scale in a power law manner. Some properties such as sand content, silt content, θs, and n had mono-fractal scaling behaviour, indicating that, whether for high or low data values, they can be upscaled from small-scale measurements to large-scale applications using the measured data. The spatial distribution of organic carbon content had typically multifractal scaling property, and other properties – clay content, θr, and αvG – showed a weakly multifractal distribution. The upscaling or downscaling of multifractal distribution was more complex than that of monofractal distribution. It also suggested that distinguishing mono-fractals and multifractals is important for understanding the underlying processes, for simulation and for spatial interpolation of soil water retention characteristics and physical properties.
Additional keywords: soil water retention parameters, soil physical properties, multifractal analysis, spatial variability.
Acknowledgments
This study was supported by the 11th Five-Year Plan of National Scientific and Technological Supporting Project in China (No. 2008BADA4B03), the 11th Five-Year Plan of National Scientific and Technological Supporting Project in China (No. 2006BAD 02A 12) and the Knowledge Innovation Program of the Chinese Academy of Sciences (No. KSCX2-YW-N-004).
Caniego FJ,
Espejo R,
Martin MA, San Jose F
(2005) Multifractal scaling of soil spatial variability. Ecological Modelling 182, 291–303.
| Crossref | GoogleScholarGoogle Scholar |
Farajalla NS, Vieux BE
(1995) Capturing the essential spatial variability in distributed hydrological modeling: infiltration parameters. Hydrological Processes 9, 55–68.
| Crossref | GoogleScholarGoogle Scholar |
Folorunso OA,
Puente CE,
Rolston DE, Pinzon JE
(1994) Statistical and fractal evaluation of the spatial characteristics of soil surface strength. Soil Science Society of America Journal 58, 284–294.
Grassberger P, Procaccia I
(1983) Measuring the strangeness of strange attractors. Physica D (Amsterdam) 9, 189–208.
Grout H,
Tarquis AM, Wiesner MR
(1998) Multifractal analysis of particle size distributions in soil. Environmental Science & Technology 32, 1176–1182.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Gupta SC, Larson WE
(1979) Estimating soil water retention characteristics from particle size distribution, organic matter content, and bulk density. Water Resources Research 15, 1633–1635.
| Crossref | GoogleScholarGoogle Scholar |
Kravchenko AN
(2008) Stochastic simulations of spatial variability based on multifractal characteristics. Vadose Zone Journal 7, 521–524.
| Crossref | GoogleScholarGoogle Scholar |
Kravchenko AN,
Boast CW, Bulock DG
(1999) Multifractal analyses of soil properties. Agronomy Journal 91, 1033–1041.
Kravchenko AN, Bullock DG
(1999) A comparative study of interpolation methods for mapping soil properties. Agronomy Journal 91, 393–400.
Kravchenko AN,
Bullock DG, Boast CW
(2000) Joint multifractal analyses of crop yield and terrain slope. Agronomy Journal 92, 1279–1290.
| Crossref |
Lark RM, Webster R
(1999) Analysis and elucidation of soil variation using wavelets. European Journal of Soil Science 50, 185–206.
| Crossref | GoogleScholarGoogle Scholar |
Lashermes B,
Roux SG,
Abry P, Jafard S
(2008) Comprehensive multifractal analysis of turbulent velocity using the wavelet leaders. The European Physical Journal B 61, 201–215.
|
CAS |
Crossref |
Lee CK
(2002) Multifractal characteristics in air pollutant concentration time series. Water, Air, and Soil Pollution 135, 389–409.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Lee CK, Lee SL
(1996) Heterogeneity of surfaces and materials as reflected in multifractal analysis. Water, Air, and Soil Pollution 3, 269–302.
|
CAS |
Liu HH, Molz FJ
(1997) Multifractal analyses of hydraulic conductivity distributions. Water Resources Research 33, 2483–2488.
| Crossref | GoogleScholarGoogle Scholar |
Marquardt DW
(1963) An algorithm for least-squares estimation on non-linear parameters. Journal of the Society for Industrial and Applied Mathematics 11, 431–441.
| Crossref | GoogleScholarGoogle Scholar |
Meneveau C,
Sreenivasan KR,
Kailasnath P, Fan MS
(1990) Joint multifractal analyses: theory and application to turbulence. Physical Review A. 41, 894–913.
| Crossref | GoogleScholarGoogle Scholar | PubMed |
Miranda JGV,
Montero E,
Alves MC,
Gonzalez AP, Vazquez EV
(2006) Multifractal characterization of saprolite particle-size distribution after topsoil removal. Geoderma 134, 373–385.
| Crossref | GoogleScholarGoogle Scholar |
Olsson J,
Niemezynowicz J, Berndtsson R
(1993) Fractal analysis of high-resolution rainfall time series. Journal of Geophysical Research 98, 23265–23274.
| Crossref | GoogleScholarGoogle Scholar |
Perrier E,
Ana MT, Annette D
(2006) A program for fractal and multifractal analysis of two-dimensional binary images: Computer algorithms versus mathematical theory. Geoderma 134, 284–294.
| Crossref | GoogleScholarGoogle Scholar |
Posadas AND,
Gimenez D,
Quiroz R, Protz R
(2003) Multifractal characterization of soil pore systems. Soil Science Society of America Journal 67, 1361–1369.
|
CAS |
Rawls WJ,
Brakensiek DL, Saxton KE
(1982) Estimation of soil water properties. Transactions of the American Society of Agricultural Engineers 25, 1316–1328.
Russo D, Bouton M
(1992) Statistical analysis of spatial variability in unsaturated flow parameters. Water Resources Research 28(7), 1911–1925.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Schaap MG, Leij FJ
(1998) Database related accuracy and uncertainty of pedotransfer functions. Soil Science 163, 765–779.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Seuront L,
Lagadeuc FSY,
Schertzer D, Lovejoy S
(1999) Universal multifractal analysis as a tool to characterize multiscale intermittent patterns: Example of phytoplankton distribution in turbulent coastal waters. Journal of Plankton Research 21, 877–922.
| Crossref | GoogleScholarGoogle Scholar |
Sharma ML, Luxmoore RJ
(1979) Soil spatial variability and its consequences on simulated water balance. Water Resources Research 15, 1567–1573.
| Crossref | GoogleScholarGoogle Scholar |
Shen ZQ,
Shi JB,
Wang K, Kong FS
(2004) Neural network ensemble residual kriging application for spatial variability of soil properties. Pedosphere 14, 289–296.
Shouse PJ,
Russel WB,
Burden DS,
Selim HM,
Sisson JB, van Genuchten MT
(1995) Spatial variability of soil water retention functions in a silt loam soil. Soil Science 159, 1–12.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Shu Q,
Liu Z, Si B
(2008) Characterizing scale- and location-dependent correlation of water retention parameters with soil physical properties using wavelet techniques. Journal of Environmental Quality 37, 2284–2292.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
PubMed |
Si BC, Farrell RE
(2004) Scale-dependent relationships between wheat yield and topographic indices: A wavelet approaches. Soil Science Society of America Journal 68, 577–588.
|
CAS |
Si BC, Zeleke TB
(2005) Wavelet coherency analysis to relate saturated hydraulic properties to soil physical properties? Water Resource Research 41, W11424.
| Crossref | GoogleScholarGoogle Scholar |
Stanley HE, Meakin P
(1988) Multifractal phenomena in physics and chemistry. Nature 335, 405–409.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
van Genuchten MT
(1980) A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal 44, 892–898.
Wilson GV,
Alfonsi JM, Jardine PM
(1989) Spatial variability of saturated hydraulic conductivity of the subsoil of two forested watersheds. Soil Science Society of America Journal 53, 679–685.
Zeleke TB, Si BC
(2004) Scaling properties of topographic indices and crop yield: multifractal and joint multifractal approaches. Agronomy Journal 96, 1082–1090.
Zeleke TB, Si BC
(2005) Scaling relationships between saturated hydraulic conductivity and soil physical properties. Soil Science Society of America Journal 69, 1691–1702.
| Crossref | GoogleScholarGoogle Scholar |
CAS |
Zeleke TB, Si BC
(2006) Characterizing scale-dependent spatial relationships between soil properties using multifractal techniques. Geoderma 134, 440–452.
| Crossref | GoogleScholarGoogle Scholar |
Zeleke TB, Si BC
(2007) Wavelet-based multifractal analysis of field scale variability in soil water retention. Water Resources Research 43, W07446.
| Crossref | GoogleScholarGoogle Scholar |