Figure 1.
The location of the study catchment and the distribution of the samples.
Figure 2.
The soil moisture prediction map basing on ordinary kriging method.
Figure 3.
The soil moisture prediction map basing on inverse distance weighting method.
Figure 4.
The soil moisture prediction map basing on linear regression method.
Figure 5.
The soil moisture prediction map basing on regression kriging method.
Table 1.
The basic statistical properties of soil moisture of each data set.
Table 2.
The correlation between the G-values and the sample pattern properties basing on correlation analysis.
Table 3.
The performance assessment of the four interpolation methods for 10–20 cm soil layer.
Table 4.
The performance assessment of the four interpolation methods for 40–100 cm soil layer.
Table 5.
The means comparison of the G-value of the four interpolation methods for 10–20 cm soil layer.
Table 6.
The means comparison of the G-value of the four interpolation methods for 40–100 cm soil layer.
Figure 6.
The autocorrelation range of the 10–20 cm soil moisture in complex terrains.
Figure 7.
The autocorrelation range of the 40–100 cm soil moisture in complex terrains.
Figure 8.
Two examples of the problems when distance-based methods were used in complex terrains.