Determination Of Thermal Stratification
And Its Effects On Water Quality In Dams
Using Analytical Methods
Author(s)
G. Badalians Gholikandi, E. Jalilzadeh, H. R. Orumieh
& H. R. Tashaouie
Abstract
Data analysis should be viewed as an integral component of the water quality
management process [1]. Statistical techniques such as factor analysis (FA),
cluster analysis (CA) and T test were applied to get information about the
similarities or dissimilarities, to detect thermal stratification and to interpret
Amir Kabir Dam water quality data. Analyses were based on 150 total samples
from 5 depths during about a two year period (from April 2008 to April 2010)
which were measured for 29 (19 physicochemical and 10 biological) parameters
resulting in 4350 observations. Using PCA/FA for physicochemical variables,
five Varifactors were obtained with eigenvalues >1 contributing to almost
82.342% of total variance in water dataset which are included on the
components. Moreover, FA is a helpful method for physicochemical data
reduction, although it is not as good for biological data reduction. Thermal
stratification is the biggest problem at the majority of deep reservoirs resulting
from the surface warming. It results in water quality detritions in the bottom
layers. Finding the depths affected by this occurrence is an important problem in
the management of reservoirs. In this study CA and t-test were applied to
identify thermal stratification and its consequences on water quality. Sampling
stations were grouped into two main classes using CA during each season. After
CA, T test was applied to detect the statistical importance of differences between
Water Research Institute (WRI), Iran
Keywords
water quality, thermal stratification, statistical techniques FA/CA/T test, Amir Kabir Dam
Related Book
Other papers in this volume
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