Multivariate analysis of sediment properties
To recognize the physico-chemical properties and sediment that controls
the variability of the data, the results of a principal component
analysis (PCA) of sediment characteristic variables are shown in Table
3. The first and second components together represent 79.3% of the
variation. First PC is mainly determined by ACCE, Clay, and silt, and is
negatively dependent on Vfs, D50 and Sand. This implies that correlated
variables control variation in the data set. The second component showed
strong negative correlations with pH and CCE, negatively correlated with
OM, and EC. There were large differences between observations from
various samples (Figure 3). This may be due to sampling from different
rivers representing a wide diversity of properties such as texture, pH,
EC, and ACCE. Overall, the PCA analysis revealed that variation of
sediments properties is dominated by particle size distribution, and to
a slightly smaller extent by EC, ACCE and OM. Particle size distribution
varied, which was partly due to differences of geomorphological features
of rivers, slope of terrain, and geological structure of region.