Spatial Scaling Analyses of Soil Physical Properties: A Review of Spectral and Wavelet Methods

Abstract

A: FDR, false discovery rate; FFT, fast Fourier transform.S S : M M Understanding the scaling proper es of soil spa al variability is important for managing natural resources and protecting our environment. Our objec ve was to present methodology that has been used or has the poten al to be used in spa al scaling of soil proper es. The spectral and wavelet analyses were presented and illustrated using the soil hydraulic conduc vity and other basic soil physical proper es collected along a transect in Saskatchewan, Canada. We introduced periodogram, spectral analysis, simple squared coherency, and mul ple coherency analyses as the frequency domain tools. For the wavelet analysis, the wavelet transform, cross wavelet spectrum, and simple wavelet coherency analysis were introduced. Detailed procedures and precau ons for these analyses were also presented. The signifi cance tests for diff erent analyses were discussed and mul ple tes ng for the wavelet analysis was introduced.

Characterizing scale specific depth persistence of soil water content along two landscape transects

“…Different factors and processes may operate at different scales and at different intensities, which makes the depth persistence of SWC highly scale-dependent. Identifying the scales and the similarities among these scales of SWC at different depths could lead to the development of a scale-specific relationship between the SWC of the surface and subsurface layers (Si, 2008;Biswas and Si, 2011).…”

“…Multi-scale analyses have employed various methods (Blöschl and Sivapalan, 1995;Kravchenko et al, 2000;Zeleke and Si, 2006;Si, 2008). For example, Biswas and Si (2011) used wavelet coherency analysis to examine the depth persistence of spatial http://dx.doi.org/10.1016/j.jhydrol.2014.08.034 0022-1694/Ó 2014 Elsevier B.V. All rights reserved.…”

Multiple domain evaluation of watershed hydrology models

“…This results in the loss of time information (Si, 2008). Moreover, the global nature of lumped error metrics (e.g., NSE, R 2 ) is of little use when event scale predictions or time resolution of model performance is needed.…”

Use of color maps and wavelet coherence to discern seasonal and interannual climate influences on streamflow variability in northern catchments

“…information as they separate variances at different scales [Si, 2008], whereas Fourier transforms surpass the wavelet transform in the frequency location of the variance. The wavelet transform enables examination of time series features at scales locally with details matched by their scale (e.g., broad features at long time scales and fine features at short ones).…”