SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN A REGION OF THE LOESS PLATEAU OF PR CHINA SUBJECT TO WIND AND WATER EROSION

被引:141
|
作者
Wang, Y. Q. [1 ,2 ,3 ]
Shao, M. A. [2 ,3 ,4 ]
机构
[1] Northwest A&F Univ, Coll Resources & Environm, Yangling 712100, Shaanxi, Peoples R China
[2] Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China
[3] Minist Water Resources, Yangling 712100, Shaanxi, Peoples R China
[4] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100039, Peoples R China
基金
中国国家自然科学基金;
关键词
geostatistic analysis; land use; ordinary kriging; semivariogram; spatial structure; PR China; wind erosion; water erosion; loess; SATURATED HYDRAULIC CONDUCTIVITY; GEOSTATISTICAL ANALYSIS; CATCHMENT; PATTERNS; MOISTURE; TILLAGE; STORAGE; FOREST; CARBON; FIELD;
D O I
10.1002/ldr.1128
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (KS), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0 center dot 54km2 watershed on the Loess Plateau. Topsoil samples (0-5cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas KS had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p<0 center dot 05). Geostatistical analyses revealed that the KS semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100-m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright (c) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:296 / 304
页数:9
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