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This study used Geographic Information Systems GISS) and regression-tree modeling to precisely quantify the relationships between the soil texture fractions and different environmental parameters on a national scale, and to detect the most important parameters that can be used as weighted input data in soil environmental prediction models.
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Combining the sparse soil material data with the dense cone index and landform element data resulted in soil material information covering the entire study area.
Therefore, the BCM calculation of CWD equals PET minus AET (Stephenson 1998) reflects the uncertainties inherent in the climate data, in the soil properties from soil mapping, and in PET.
Figure 2 Biplot of PC1 and PC2 for soil data in PCA1-soil model.
Statistical significance was computed using Pair-Samples T-Test, with a significance level of p. 13065_2012_542_MOESM1_ESM.png Additional file 1: Figure 2A: Biplot of PC1 and PC2 for soil data in PCA2-soil model.
Along Pb, Cd and Zn there are some other metals with a significant contribution on PC1 (Figure 1). Figure 1 Scree plot and PC loadings of soils data, in PCA1-soil model.
Given the high cost of data acquisition in soil water problems, it is becoming increasingly essential to collect the measurements as cost-efficient as possible.
The multilingual soil profile database (named SDBm Plus) is user-friendly software designed to store and retrieve in an efficient and systematic way the large amounts of geo-referenced soil attribute data collected in soil surveys and laboratories.
The proposed approach is illustrated using real data in Unsaturated Soil Database (UNSODA) developed by U.S. Department of Agriculture.
All trace metal concentrations (with corresponding data in local soils) in the Lom sediments were lower than the mean levels in local soils.
A maximum of three factors account for 93.8 % variance in rock data, six factors for 84%% variance in soil data, five factors for 71.2 % in groundwater data during summer and six factors for 73.7 % during winter.
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