黄土高原北部坡面尺度土壤饱和导水率分布与模拟

赵春雷; 邵明安; 贾小旭

黄土高原北部坡面尺度土壤饱和导水率分布与模拟

1.
西北农林科技大学资源环境学院, 陕西杨凌 712100;
2.
黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌 712100;
3.
中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京 100101

基金项目: 国家自然科学基金资助项目(41390461;51179180)

详细信息

作者简介:
赵春雷(1990-), 男, 河北承德人, 博士研究生, 主要从事土壤水分生态、土壤性质空间变异方面研究.E-mail:chunleizhao20@gmail.com

通讯作者:
邵明安, E-mail:mashao@ms.iswc.ac.cn

中图分类号: S152.7
计量
- 文章访问数: 128
- HTML全文浏览量: 36
- PDF下载量: 704
出版历程
- 收稿日期: 2014-04-07
- 刊出日期: 2014-11-24

Distribution and simulation of saturated soil hydraulic conductivity at a slope of northern Loess Plateau

1.
College of Resources and Environment, Northwest A&F University, Yangling 712100, China;
2.
State Key Laboratory of Soil Erosion and Dryland Agriculture on the Loess Plateau, Yangling 712100, China;
3.
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

摘要

摘要: 为探明黄土高原北部坡面土壤饱和导水率(K_s)空间分布特征,为土壤水文过程模拟与预测提供理论依据,采用经典统计学和地统计学的空间变异分析方法,分析了坡面尺度土壤K_s的空间变异特征,并用一阶自回归状态空间模型对K_s的空间分布进行了模拟.研究区坡面尺度K_s的变异为中等程度变异,具有中等程度空间依赖性,变程为42 m.K_s与容重、砂粒、粉粒和黏粒含量在不同滞后距离下均具有自相关关系和交互相关关系.容重和土壤颗粒是影响坡面K_s空间分布的主要因素.状态空间模拟结果表明,基于容重和土壤颗粒的状态空间方程可以很好地解释坡面K_s的变异状况(R²>0.9).一阶自回归状态空间模型可用于田间条件下坡面尺度K_s分布特征的预测.
- 饱和导水率 /
- 坡面尺度 /
- 异质性 /
- 状态空间 /
- 模拟
Abstract: To provide a theoretical basis for simulating soil hydraulic processes, classical statistics and geo-statistics were used to characterize the spatial distribution of saturated soil hydraulic conductivity (K_s) at a slope scale in the northern Loess Plateau. Furthermore, the first order autoregressive state-space model was applied to simulate the distribution of K_s. The magnitude of K_s variability was moderate according to the coefficient of variation. The degree of spatial dependence was moderate with range of 42 m. Bulk density, sand content, silt content, and clay content were auto-correlated. Cross-correlation existed between K_s and other factors at different lag distance. Bulk density and soil particles were the key factors to affect the spatial distribution of K_s on the sloping land. A combination of bulk density and soil particles was the best to explain the spatial variation of K_s(R²>0.9). The first order autoregressive state-space model is suitable for simulating the K_s distribution at a slope scale.
- saturated soil hydraulic conductivity /
- slope scale /
- heterogeneity /
- state-space /
- simulation