盐碱荒地土壤入渗参数的多元非线性预报模型

发布时间：2018-02-21 02:34

本文关键词： 盐碱土壤 Kostiakov入渗模型参数土壤传输函数法非线性预报　出处：《人民黄河》2017年07期 　论文类型：期刊论文

【摘要】：为给盐碱荒地改良提供技术支撑,以原生盐碱荒地土壤为研究对象,进行了大田原位系列入渗试验,获取了累计入渗量与入渗历时对应关系的试验资料,依据Kostiakov入渗模型,构建了入渗模型参数与同步土壤理化参数的样本集。利用土壤传输函数法,建立了以土壤基本理化参数为输入变量的Kostiakov二参数入渗模型参数k和α的多元非线性预报模型。结果表明:以土壤含水率、干容重、黏粒含量、粉粒含量、有机质含量、含盐量为输入变量对入渗系数k进行多元非线性预报和以土壤含水率、干容重、黏粒含量、有机质含量、含盐量为输入变量对入渗指数α进行多元非线性预报是可行的,两参数预报模型的相对误差平均值分别为5.5%和8.3%。
[Abstract]:In order to provide technical support for the improvement of saline-alkali wasteland, a series of in-situ infiltration experiments in the field were carried out with the primary saline-alkali wasteland soil as the research object. The experimental data of the relationship between the cumulative infiltration amount and the infiltration duration were obtained, and the Kostiakov infiltration model was used. A sample set of infiltration model parameters and synchronous soil physical and chemical parameters was constructed. The multivariate nonlinear prediction model of infiltration model parameters k and 伪 of Kostiakov two-parameter infiltration model with basic soil physical and chemical parameters as input variable was established. The results showed that the soil moisture content, dry bulk density, clay content, silt content and organic matter content were used as parameters. It is feasible to predict the infiltration coefficient k by using the input variables of salt content as input variables, and with the input variables of soil moisture content, dry bulk density, clay content, organic matter content and salt content as input variables. The average relative error of the two parameter prediction models is 5.5% and 8.3 respectively.
【作者单位】：太原理工大学水利科学与工程学院;
【基金】：国家自然科学基金资助项目(40671081) 山西省科技攻关项目(2007031070)
【分类号】：S152.7

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