Observed spatial organization of soil moisture and its relation to terrain indices

Abstract

Abstract. We analyze the degree of spatial organization of soil moisture and the ability of terrain attributes to predict that organization. By organization we mean systematic spatial variation or consistent spatial patterns. We use 13 observed spatial patterns of soil moisture, each based on over 500 point measurements, from the 10.5 ha Tarrawarra experimental catchment in Australia. The measured soil moisture patterns exhibit a high degree of organization during wet periods owing to surface and subsurface lateral redistribution of water. During dry periods there is little spatial organization. The shape of the distribution function of soil moisture changes seasonally and is influenced by the presence of spatial organization. Generally, it is quite different from the shape of the distribution functions of various topographic indices. A correlation analysis found that ln(a), where a is the specific upslope area, was the best univariate spatial predictor of soil moisture for wet conditions and that the potential radiation index was best during dry periods. Combinations of ln(a) or In(a/tan(/3)), where/3 is the surface slope, and the potential solar radiation index explain up to 61% of the spatial variation of soil moisture during wet periods and up to 22% during dry periods. These combinations explained the , 1995;Willgoose, 1996; Bl6schl, 1999]. This paper examines (1) the degree of spatial organization of soil moisture in a small catchment during different seasons and (2) how well that organization can be predicted using terrain indices.Hydrologic processes can vary in space in an organized way or randomly or in a combination of the two [Gutknecht, 1993; Bl6schl et al., 1993; Bl6schl, 1999]. We use "randomness" to refer to variability that is not predictable in detail but that has predictable statistical properties, and "organization" to refer to regularity or order. Spatial organization implies variation characterized by consistent spatial patterns [Bl6schl, 1999]. In the context of this paper most of the organization is related to topography. Bl6schl [1999] noted that natural systems can vary from completely disorganized (disordered, random) to highly 797

Advances in the use of observed spatial patterns of catchment hydrological response

“…[116]). If the correlation length of the errors is small relative to the model element scale, it can be concluded that the errors are due to either measurement error or to small-scale variability not resolved by the model.…”

“…Fig. 8e shows the residuals plotted against radiation index (a function of topographic aspect; [116]) and highlights the problem with poor prediction on the north facing hillslopes in the south-east (radiation index > 1). The overly dry gullies are apparent around radiation index values of 0.975.…”

“…Surrogates are variables that show some (often limited) degree of correlation to the pattern of interest but are much easier to collect in a spatially distributed fashion. Examples of surrogates include terrain [116], soil texture to infer hydraulic properties (e.g. [34,83]) and remote sensing data (where various characteristics of emission or reflectance of radiation of different wavelengths are correlated with features of interest such as vegetation cover, surface temperature, or soil moisture).…”

Spatiotemporal prediction of soil moisture content using multiple-linear regression in a small catchment of the Loess Plateau, China

“…The prediction of soil moisture content distribution in space and time is difficult though necessary for soil and land survey (Webster and Butler, 1976;McKenzie and Austin, 1993), soil and land evaluation (Fu, 1991;Fu and Gulinck, 1994;, hydrologic modeling and watershed management (Western et al, 1999;Qiu et al, 2001a,b). For instance, antecedent soil moisture content is one of the most important parameters of a hydrological model, since it influences the amount of infiltration and the vertical movement of water in the soil and, therefore, affects the amount of runoff (Hawley et al, 1983;De Roo et al, 1996;Georgakakos and Baumer, 1996).…”

Downscaling soil moisture over regions that include multiple coarse-resolution grid cells

“…Other downscaling methods use topographic data, which is known to affect soil moisture variations at particularly fine resolutions , Gomez-Plaza et al, 2001, Western et al, 1999. Wilson et al [2005] downscaled soil moisture in five catchments to 10-40 m resolutions using empirical relationships with topographic attributes.…”