Soil water content temporal-spatial variability of the surface layer of a Loess Plateau hillside in China
Soil water content temporal-spatial variability of the surface layer of a Loess Plateau hillside in China
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DOI：
10.1590/s0103-90162008000300008
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发表时间：
2008-01-01
影响因子：
2.6
通讯作者：
Reichardt, Klaus
中科院分区：
文献类型：
--
作者：
Hu, Wei;Shao, Ming An;Reichardt, Klaus
表层土壤水分在空间和时间域上表现出重要的变异性，这可能会导致农业用水管理的严重不确定性。本研究的目的是（i）表征坡面0-6 cm土壤含水量θ空间变异的时间动态和稳定性;（ii）研究与土壤水分条件相关的问题，包括土壤水分的主导因素和平均θ的估计。在一个多月的时间里，在中国黄土高原的一个山坡上，使用10 × 10米的测量点网格，在60 × 280米的区域内，用频域反射仪测量了13天的θ。土壤含水量表现出中等的变异性，每个测量日期，和相关长度（λ）θ范围从8.4到27.7米。随着土壤的干燥，λ减小，CV%和准确估计平均0的采样数增加。坡向、海拔、有机质含量、粘粒含量和容重是影响土壤含水量的主要因素，其影响程度随坡度的减小而减弱。基于时间稳定性分析和θ的平均相对差与主导因子相对差的相关性，θ的平均值得到了较好的估计，在较湿润的条件下具有较好的精度。
Surface soil moisture exhibits an important variability in terms of spatial and temporal domains, which may result in critical uncertainties for agricultural water management. The purposes of this study were (i) to characterize the temporal dynamics and stability of the spatial variability of the surface 0-6 cm soil water content theta on a hill-slope; (ii) to investigate issues related to soil moisture conditions including dominating factors on Soil Moisture and to the estimation of the mean theta. During a period of more than one month theta was measured on thirteen days by Frequency Domain Reflectometry using a 10 x 10 m grid of measurement points covering a 60 x 280 m domain within a hill-slope of the Loess Plateau in China. Soil water content exhibited a moderate variability for each measurement date, and the correlation length (lambda) for theta ranged from 8.4 to 27.7 m. With the soil becoming drier, lambda decreased, the CV% and the sampling number for accurate mean 0 estimation increased. Aspect, elevation, organic matter content, clay content, and bulk density were the main influencing factors, whose extent of influence weakened with decreasing theta. Based on time stability analysis and on the correlation of mean relative difference of theta with the relative difference of dominating factors, mean theta values were well estimated, with a better accuracy under wetter conditions.