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赵爱辉,黄明斌,史竹叶.土壤颗粒分布参数模型对黄土性土壤的适应性研究[J].农业工程学报,2008,24(1):1-6.DOI:
土壤颗粒分布参数模型对黄土性土壤的适应性研究
投稿时间:2006-12-27  修订日期:2007-10-25
中文关键词:  土壤颗粒组成  黄土性土壤  参数模型  黄土高原
基金项目:教育部新世纪优秀人才支持计划;国家自然科学基金(40671083);西北农林科技大学创新团队
作者单位
赵爱辉 (1981-)女 河南新乡人研究方向:土壤物理。杨凌 西北农林科技大学水土保持研究所712100 
黄明斌 (1968-)湖北钟祥人研究员博士生导师主要从事土壤物理和生态水文方面的研究。杨凌 西北农林科技大学水土保持研究所712100。Email: hmbd@nwsuaf.edu.cn 
史竹叶 西北农林科技大学水土保持研究所 黄土高原土壤侵蚀与旱地农业国家重点实验室杨凌 712100 
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中文摘要:土壤颗粒组成是土壤最基本的物理性质之一,其分布曲线可用来估算土壤的水力学性质,然而对于土壤颗粒分布曲线的完整表达需要借助于参数模型,对于不同类型的土壤,参数模型的拟合效果不尽相同。为了选择能够较好描述黄土性土壤颗粒分布状况的参数模型,该文采用了3个指标——相关系数(R),均方根误差(RMSE)和 Akaike 信息准则(AIC)值,对3类共10个参数模型(单参数模型2个,二参数模型6个,三参数模型2个)在黄土性土壤上的适应性进行了评价(共828个土壤颗粒分析资料)。结果表明:简化的三参数Fredlund模型对黄土性土壤颗粒分布的拟合效果最好,且受质地影响较小,二参数Weibull模型次之,单参数的Jaky模型效果最差。三参数Fredlund模型是估算黄土性土壤颗粒组成的最适宜的模型。
Zhao Aihui,Huang Mingbin,Shi Zhuye.Evaluation of parameter models for estimating loess soil particle-size distribution[J].Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2008,24(1):1-6.DOI:
Evaluation of parameter models for estimating loess soil particle-size distribution
Author NameAffiliation
Zhao Aihui State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest Agriculture and Forestry University, Yangling 712100, China 
Huang Mingbin State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest Agriculture and Forestry University, Yangling 712100, China 
Shi Zhuye State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest Agriculture and Forestry University, Yangling 712100, China 
Key words:soil particle-size distribution  loess soil  parameter model  Loess Plateau
Abstract:The soil particle-size distribution (PSD) is a fundamental soil physical property. PSD curve is widely used as a basis for estimating soil hydraulic properties such as the water retention curve and saturated and unsaturated hydraulic conductivities. However, the disconnected experimental data of PSD sets often limit its uses, and the parameter models are needed to simulate PSD curves. Many models have been developed for simulating PSD curves, and the performances of these models varied with the soil types. To determine the optimal model to fit the PSD curves for loess soils, ten popular models (two 1-parameter models, six 2-parameter models, and two 3-parameter models) were used to fit 828-PSD data sets measured in the Loess Plateau of China. Three criteria, correlation coefficient(R), root mean square error (RMSE), and Akaike’s information criterion (AIC) were used to evaluate the performances of ten models. The results show that the Fredlund model with three parameters presents the best performance for the majority of soils, and has little influence by the soil texture. The performance of Weibull model with two parameters is less than that of Fredlund model and better than that of others. The Jaky model with single parameter presents the worst performance in the whole models. The Fredlund model with three parameters is testified to be suitable for estimating the PSD curves of the loess soils.
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