ORIGINAL RESEARCH
Spatial Variability of Soil Physical Properties Based
on GIS and Geo-Statistical Methods in the Red
Beds of the Nanxiong Basin, China
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1
School of Geography and Planning, Sun Yat-sen University, Guangzhou, China
2
School of Geographical Sciences, Southwest University, Chongqing, China
3
School of Civil Engineering, Sun Yat-sen University, Guangzhou, China
Submission date: 2018-03-16
Final revision date: 2018-04-29
Acceptance date: 2018-06-13
Online publication date: 2019-03-04
Publication date: 2019-04-09
Pol. J. Environ. Stud. 2019;28(4):2961-2972
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ABSTRACT
Spatial variability of soil has an important influence on the structure and function of soil. The spatial
distribution of soil physical properties provides basic and useful information relevant to soil management
and ecological protection. A typical red beds basin was selected for this study, soil samples at 0-20 cm
were taken from 150 locations in the northeast part of Nanxiong Basin, in which GIS and geostatistics
were used to analyze the spatial variability of the soil physical properties. The results show that the
coefficients of variation of soil bulk density, total porosity and capillary porosity are 9.82%, 4.47%,
and 3.72%, respectively, which indicate weak variation. Pearson correlation indicated that soil bulk
density was significantly positively correlated with soil moisture and capillary water capacity (p<0.01),
with correlation coefficients of 0.85 and 0.91, respectively, but was significantly negatively correlated
with total porosity, capillary porosity and non-capillary porosity, with correlation coefficients of 0.82,
0.71 and 0.94, respectively (p<0.01). The spatial distributions of soil physical properties using ordinary
kriging (OK) and empirical bayesian kriging (EBK) methods were subjected to comparative analysis.
In addition, different cross-validation indicators were applied to assess the performance of different
interpolation methods. Cross-validation demonstrated that EBK performed better than OK. And EBK
produced smaller regions of predicted soil physical properties than OK, highlighting the necessity of
choosing the appropriate methods in studying the spatial distribution of soil properties.