Influence of soil properties on electrical conductivity under humid water regimes

被引:41
作者
Auerswald, K [1 ]
Simon, S
Stanjek, H
机构
[1] Tech Univ Munich, Chair Grassland Sci, D-85350 Freising, Germany
[2] Tech Univ Munich, Chair Soil Sci, D-85350 Freising, Germany
关键词
electrical conductivity; moisture; clay; structure; cation exchange capacity;
D O I
10.1097/00010694-200106000-00003
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Apparent electrical conductivity (ECa) of soils can be measured easily by nondestructive methods and, therefore, could be useful in the mapping of soil properties, which influence ECa. The influences of soil structure, bulk density, clay and water content, EC of the soil solution, and cation exchange capacity (CEC) on ECa were examined in laboratory experiments for 19 soils at 16 to 18 water contents. Soil structure increased variability in ECa but had no other influence. Bulk density also had no influence when the other variables were used on a volume basis rather than on a weight basis. This agrees with the concept that an electric current has to pass a given volume between two electrodes but not a constant mass. Cation exchange capacity, which depends primarily on charged sites of the clay and organic matter fractions, correlated less with ECa than clay content alone, indicating that the charged sites of organic matter are less important. Despite the humid climate, the EC of the soil solution varied considerably in the soils, which could be explained by differences in fertilizing history which, in turn, influenced ECa. Water content had a comparably small influence, which increased near the wilting point and below. In a multiple regression, volumetric clay content, EC of the soil solution, and logarithmic water content influenced ECa at a ratio of 1 : 0.8 : 0.4. This regression explained 84% of the variation and performed equally well on a validation data set of 145 soil-moisture combinations. This is superior to an existing model. Thus, ECa offers the opportunity to improve high-resolution mapping of these three properties by selecting conditions under which the variation can be assigned mainly to a single factor. Together with the ease of ECa measurement, this is especially useful for precision agriculture.
引用
收藏
页码:382 / 390
页数:9
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