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Testing Logselfsimilarity of Soil Particle Size Distribution: Simulation with Minimum Inputs

机译：测试土壤粒径分布的对数相似性：用最少的输入进行模拟

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摘要

Particle size distribution (PSD) greatly influences other soil physical properties. A detailed textural analysis is time-consuming and expensive. Soil texture is commonly reported in terms of mass percentages of a small number of size fractions (typically, clay, silt and sand). A method to simulate the PSD from such a poor description or even from the poorest description, consisting in the mass percentages of only two soil size fractions, would be extremly useful for prediction purposes. The goal of this paper is to simulate soil PSDs from the minimum number of inputs, i.e., two and three textural fraction contents, by using a logselfsimilar model and an iterated function system constructed with these data. High quality data on 171 soils are used. Additionally, the characterization of soil texture by entropy-based parameters provided by the model is tested. Results indicate that the logselfsimilar model may be a useful tool to simulate PSD for the construction of pedotransfer functions related to other soil properties when textural information is limited to moderate textural data.
机译：粒径分布（PSD）极大地影响了其他土壤物理性质。详细的纹理分析既费时又昂贵。通常以少量粒度（通常是粘土，粉砂和沙子）的质量百分比表示土壤质地。从如此差的描述甚至从最差的描述模拟PSD的方法（仅包含两个土壤尺寸分数的质量百分比）对于预测目的将非常有用。本文的目的是通过使用对数自相似模型和由这些数据构建的迭代函数系统，从最少的输入（即两个和三个纹理分数内容）中模拟土壤PSD。使用了171种土壤的高质量数据。另外，测试了由模型提供的基于熵的参数对土壤质地的表征。结果表明，当构造信息仅限于中等构造数据时，对数自相似模型可能是模拟PSD来构建与其他土壤特性有关的pedotransfer函数的有用工具。

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