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Abstract
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| Soil surface roughness (SSR) is an excellent index of soil susceptibility to wind and water erosion. Several studies have been developed to characterize SSR based on pin meter readings and applying multifractal analysis (MFA). Although it is a reliable method there are several difficulties such us the scale of the measurements needed, centimeter to millimeter, the difficulties to work on the field and extreme time consuming. Soil surface roughness (SSR) is defined as the standard deviation of elevation readings. After tillage, soil micro-topography exhibits randomly oriented tillage marks of different depths/heights, as well as clods (Allmaras et al., 1966; Zobeck and Onstad, 1987; Huang, 1998). Each type of tillage tool generates a characteristic oriented roughness pattern which is relatively easy to quantify using a simple geometric model. By contrast, quantifying the spatial distribution of randomly oriented soil surface roughness represents a challenge (Huang, 1998). A unified conceptual framework based on fractal parameters has recently been introduced to tackle the geometric complexity of soil surface roughness. Nonetheless, the variety of non-equivalent methods proposed for calculating fractal indices has curbed their use in describing soil micro-topography (Vidal et al., 2005). The aim of this study was to apply MFA to characterize SSR based on the interpretation of the shadows of the micro topography. The method was designed to be used mainly on the field, after soil is submitted to the tillage labors, being reliable, easy to use and low cost. | |
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International
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Si |
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Congress
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IV Congreso Mundial de Ingenieros Agrónomos y Profesionales de la Agronomia |
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960 |
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Place
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Madrid |
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Reviewers
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Si |
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ISBN/ISSN
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99-9999-999-9 |
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Start Date
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28/10/2009 |
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End Date
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31/07/2009 |
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From page
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1 |
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To page
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4 |
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Proceedings IV Congreso Mundial de Ingenieros Agrónomos y Profesionales de la Agronomia |