Long-term evolution of the composition of surface water from the River Gharasoo, Iran: a case study using multivariate statistical techniques

Environ Geochem Health. 2015 Apr;37(2):251-61. doi: 10.1007/s10653-014-9643-2. Epub 2014 Aug 31.

Abstract

We report an assessment of the quality of surface water from the River Gharasoo, Iran, with rainfall data. EC, pH, HCO(3)(-), Cl(-), SO(4), Ca(2+), Mg(2+), Na(+), %Na, and sodium adsorption ratio results, monitored monthly by two sampling stations over a period of 40 years, were held by the Hydraulic Works Organization in Kermanshah City. Principal-components analysis of the data revealed three factors for each station explaining 90.36 and 79.52 % of the total variance in the respective water-quality data. The first factor was chemical components resulting from point and non-point source pollution, especially industrial and domestic waste, and agricultural runoff, as a result of anthropogenic activity. Rainfall had significant negative correlation with bicarbonate only, at a level of 0.05, at station 1. Box-plot analysis revealed that, except for pH, the other studied characteristics were indicative of high pollution at station 1. Among the sources of pollution at station 1, Mg(2+) and Cl(-) data deviated most from normal distribution and included outliers and extremes. Hierarchical cluster analysis showed EC was substantially affected by rainfall. It is thus essential to treat industrial wastewater and municipal sewage from point sources by adoption of the best management practices to control diffuse pollutants and improve water quality of the Gharasoo River basin.

MeSH terms

  • Agriculture
  • Cluster Analysis
  • Environmental Monitoring
  • Iran
  • Multivariate Analysis
  • Principal Component Analysis
  • Rain*
  • Rivers / chemistry*
  • Wastewater / chemistry
  • Water Pollutants, Chemical / analysis*
  • Water Quality*

Substances

  • Waste Water
  • Water Pollutants, Chemical