『Abstract
Water pollution has become a growing threat to human society
and natural ecosystems in recent decades, increasing the need
to better understand the spatial and temporal variabilities of
pollutants within aquatic systems. This study sampled water quality
at 12 sampling sites from October 2006 to August 2008 in the Jinshui
River of the South Qinling Mts., China. Multivariate statistical
techniques and gridding methods were used to investigate the temporal
and spatial variations of water quality and identify the main
pollution factors and sources. Two-way analysis of variance (ANOVA)
showed that 25 studied water quality variables had significant
temporal differences (p<0.01) and spatial variability (p<0.01).
Using cluster analysis, the 12 sampling sites were classified
into three pollution level groups (no pollution, moderate pollution,
and high pollution) based on similarity of water quality variables.
Factor analysis determined that 80.4% of the total variance was
explained by five factors, that is, salinity, trophicity, organic
pollution, oxide-related process, and erosion. The gridding methods
illustrated that water quality progressively deteriorated from
headwater to downstream areas, The analytical results suggested
that the water pollution primarily resulted from domestic wastewater
and agricultural runoff, and provided critical information for
water resource conservation in mountainous watersheds of the South
Qinling Mts., China.
Keywords: Water quality; Temporal variation; Spatial pattern;
Multivariate statistical techniques』
1. Introduction
2. Materials and methods
2.1. Study area
2.2. Data collections and analytical methods
2.3. Multivariate statistical techniques and data treatment
3. Results
4. Discussion
4.1. Cluster analysis of water quality
4.2. Factor analysis of water quality
5. Conclusions
Acknowledgments
References