Abstract
There are a number of different parameters like discharge which affect water quality and conditions. Typically, water quality is expected to improve by the increase in discharge and significantly influenced by the runoff water quality entering the river system. As a result this research subjected to address the increase of salinity in the wet season. To reach this point, a multivariate statistical technique, namely factor analysis (FA), has been used to assess the spatial variability of water quality parameters and conditions in the Karoon River basin located in southwest Iran. The various water quality parameters (10 variables) and discharge were incorporated to FA to better interpret the processes (natural) and specific source of water quality deterioration. The results revealed that water quality variations are affected mostly by dissolved mineral salts along the entire Karoon River. Furthermore, major contamination threat is caused by geological situation for over the year which is defined as nonpoint pollution source and may explain most part of the observed variances (50 %) in the data. Then as a general result of this study it can be claimed that spatially and temporally management of water use in different parts can be carried out effectively by FA technique.
Highlights
Many water quality variables are subject to large fluctuations in space and time
A multivariate statistical technique, namely factor analysis (FA), has been used to assess the spatial variability of water quality parameters and conditions in the Karoon River basin located in southwest Iran
The main objective of this study is to identify the source of surface contamination in the Karoon river basin using FA as an effective multivariate statistical technique
Summary
Many water quality variables are subject to large fluctuations in space and time. Understanding these fluctuations in the physical environment and determining whether such changes are natural or a result of anthropogenic influences can be a challenging task. The chemical composition of the surface and groundwater is controlled by many factors that include composition of precipitation, mineralogy of the watershed and aquifers, climate, and topography. These factors combine to create diverse water types that change spatially and temporally (Guler et al 2002). Despite the fact that WQI provides a useful way to predict changes in water quality, considering multiple parameters, it does not provide evidences on the contamination sources, especially because they are calculated after
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