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土壤水分特征曲线的分形模拟
作者姓名:HUANG Guan-Hu  ZHANG Ren-Duo  HUANG Quan-Zhong
作者单位:[1]Department of Irrigation and Drainage, Chinese-Israeli International Center for Research and Training in Agriculture, China Agricultural University, Beijing 100083 (China). [2]Department of Renewable Resources, University of Wyoming, Laramie, WY 82071-3354 (USA)
摘    要:Many empirical models have been developed to describe the soil water retention curve (SWRC). In this study, a fractal model for SWRC was derived with a specially constructed Menger sponge to describe the fractal scaling behavior of soil; relationships were established among the fractal dimension of SWRC, the fractal dimension of soil mass, and soil texture; and the model was used to estimate SWRC with the estimated results being compared to experimental data for verification. The derived fractal model was in a power-law form, similar to the Brooks-Corey and Campbell empirical functions. Experimental data of particle size distribution (PSD), texture, and soil water retention for 10 soils collected at different places in China were used to estimate the fractal dimension of SWRC and the mass fractal dimension. The fractal dimension of SWRC and the mass fractal dimension were linearly related. Also, both of the fractal dimensions were dependent on soil texture, i.e., clay and sand contents. Expressions were proposed to quantify the relationships. Based on the relationships, four methods were used to determine the fractal dimension of SWRC and the model was applied to estimate soil water content at a wide range of tension values. The estimated results compared well with the measured data having relative errors less than 10% for over 60% of the measurements. Thus, this model, estimating the fractal dimension using soil textural data, offered an alternative for predicting SWRC.

关 键 词:分形度数  土壤结构  土壤水分  保持力
收稿时间:2005-10-09
修稿时间:2006-02-15

Modeling soil water retention curve with a fractal method
HUANG Guan-Hu,ZHANG Ren-Duo,HUANG Quan-Zhong.Modeling soil water retention curve with a fractal method[J].Pedosphere,2006,16(2):137-146.
Authors:HUANG Guan-Hu  ZHANG Ren-Duo and HUANG Quan-Zhong
Institution:Department of Irrigation and Drainage, Chinese-Israeli International Center for Research and Training in Agriculture, China Agricultural University, Beijing 100083 (China). E-mail: qhuang@cau.edu.cn;Department of Renewable Resources, University of Wyoming, Laramie, WY 82071-3354 (USA);Department of Irrigation and Drainage, Chinese-Israeli International Center for Research and Training in Agriculture, China Agricultural University, Beijing 100083 (China). E-mail: qhuang@cau.edu.cn
Abstract:Many empirical models have been developed to describe the soil water retention curve (SWRC). In this study, a fractal model for SWRC was derived with a specially constructed Menger sponge to describe the fractal scaling behavior of soil; relationships were established among the fractal dimension of SWRC, the fractal dimension of soil mass, and soil texture; and the model was used to estimate SWRC with the estimated results being compared to experimental data for verification. The derived fractal model was in a power-law form, similar to the Brooks-Corey and Campbell empirical functions. Experimental data of particle size distribution (PSD), texture, and soil water retention for 10 soils collected at different places in China were used to estimate the fractal dimension of SWRC and the mass fractal dimension. The fractal dimension of SWRC and the mass fractal dimension were linearly related. Also, both of the fractal dimensions were dependent on soil texture, i.e., clay and sand contents. Expressions were proposed to quantify the relationships. Based on the relationships, four methods were used to determine the fractal dimension of SWRC and the model was applied to estimate soil water content at a wide range of tension values. The estimated results compared well with the measured data having relative errors less than 10% for over 60% of the measurements. Thus, this model, estimating the fractal dimension using soil textural data, offered an alternative for predicting SWRC.
Keywords:fractal dimension  soil texture  soil water retention curve
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