土壤物理质量指标S值预测方法研究

Evaluation of soil physical quality is very necessary for the scientific management of soil resources. The slope of the soil water retention curve (SWRC) at its inflection point (named as S-index) is often used as a comprehensive indicator for evaluating soil physical quality. Direct determination of SWRC is costly, time-consuming and laborious, so the S-index is often estimated using soil basic properties. Soil hygroscopic water content is easy to be determined and closely related to the SWRC, but few studies have established a relationship between soil hygroscopic water content and S-index. Thus, in this study, the prediction model of soil water vapor adsorption isotherm including soil hygroscopic water content will be firstly improved based on the temperature effect and hysteresis effect of soil adsorbing water molecules. Then, the relationship between soil water vapor adsorption isotherm and S-index will be identified, and the prediction model of S-index including soil hygroscopic water content and bulk density will be established. Finally, the correlation between S-index and soil physical properties will be analyzed, and the proposed method (with hygroscopic water content and bulk density as inputs) will be compared with the traditional method (with sand content, silt content, clay content, and bulk density as inputs). The results of this study will provide a new method for the evaluation and monitoring of soil physical quality.

土壤物理质量评价对科学管理土壤资源是非常必要的。土壤水分特征曲线拐点处的斜率（被称为S值）常作为评价土壤物理质量的一个综合指标。考虑到水分特征曲线测定费用高、耗时和费力的缺点，许多研究常采用土壤基本性质来估算土壤物理质量指标S值。土壤吸湿水含量与水分特征曲线密切相关，且容易测定，但很少有研究建立它与土壤物理质量指标S值之间的联系。因此，本项目首先在明确土壤吸附水分子温度效应和滞后效应的基础上，改进包括土壤吸湿水含量的土壤水汽吸附等温线预测模型；其次明确水汽吸附等温线与土壤物理质量指标S值之间的联系，建立包括土壤吸湿水含量和容重的土壤物理质量指标S值预测模型；最后分析土壤物理质量指标S值与土壤物理性状之间的相关性，对比本研究提出方法（以土壤吸湿水含量和容重）和传统方法（以机械组成和容重为输入变量）预测土壤物理质量指标S值的效果。本研究所得结果可以为土壤物理质量评价与监测提供新方法。

土壤水汽吸附数据在实际中容易获取且成本较低，有潜力作为输入变量对一些重要土壤物理性质进行预测。本项目选择了不同质地、不同有机质含量和不同矿物类型的土壤，分别测定和收集了土壤水分特征曲线、土壤水汽吸附等温线、萎蔫含水量、总比表面积和外比表面积，计算了土壤水分特征曲线S值及拐点处的基质势和含水量。建立了包括吸附和冷凝的土壤水汽吸附等温线模型，利用不同质地、粘土矿物类型和有机质含量土壤样品对提出模型进行评价，并明确了模型参数与粘粒含量、阳离子交换量、有机质含量之间的关系；提出了基于吸湿水含量预测萎蔫点、总比表面积、内比表面积和外比表面积的模型，且模型验证和对比结果表明提出的模型可以用来对这些指标进行预测；发现最佳耕作含水量与饱和含水量之间存在密切的相关性，并提出基于饱和含水量预测拐点处含水量（最佳耕作含水量）的方法，且验证结果表明提出的模型可以很好地用来预测最佳耕作含水量。本研究所得结果表明吸湿水含量和饱和含水量对土壤物理质量的评价是非常有用的指标。