Lake Water Monitoring Data Assessment by Multivariate Statistics

Abstract

The application of multivariate statistical methods to high mountain lakes monitoring data has offered some important conclusions about the importance of environmetric approaches in lake water quality assessment. Various methods like cluster analysis and principal components analysis were used for classification and projection of the data set from a big number of lakes from Pirin Mountain in Bulgaria. Additionally, self-organizing maps of Kohonen were constructed in order to solve some classification tasks. An effort was made to relate the maps with the input data in order to detect classification patterns in the data set. Thus, discrimination chemical parameters for each pattern (cluster) identified was found, which enables better interpretation of the ecological state of the system. A methodology for application of combination of different environmetric methods was suggested as a pathway to interpret high mountain lake waters monitoring data.

Quality assessment and classification of Ogbese river using water quality index (WQI) tool

“…This is as shown in Table 4 and wet season which was 44.91 was also rated bad, the detailed general rating scale of WQI and uses are shown in Table 5. From the comparative analysis of the results of the water quality index for dry and wet seasons using ANOVA, since the obtained F value exceeded the probability at 18 and 1 degrees of freedom, it can be said that the WQI of Ogbese river is significant at 0.05 level of confidence and is similar to the observations of Park et al (2014) and Simeonov et al (2010).…”

Spatio-Temporal Variations in Water Quality of the Chao Phraya River, Thailand, between 1991 and 2008

“…A SOM is an unsupervised algorithm of an artificial neural network model (ANN), proposed by Prof. T. Kohonen of Helsinki University during 1980s [14]. The basic idea of SOM is to display a high-dimensional signal manifold onto a much lower dimensional network in an orderly fashion [5]. Since 2000, SOM has been widely applied for solving problems is capability of clustering and classification in the studies of water resources and aquatic ecology [15,16].…”

“…Establishment of a monitoring program on water quality is, therefore, highlighted for the purpose of determining the state of pollution in any particular site in the rivers [1,2,4]. The general trends of either decreasing or increasing water quality at any monitored site indicate which areas are stepped to a good, moderate or vulnerable condition [2,3,5].…”

Spatial Differentiation of Water Quality Between Reservoirs Under Anthropogenic and Natural Factors Based on Statistical Approach

“…Since the state of an ecosystem is dependent simultaneously on many factors and parameters, these systems are multivariate in nature [16]. Therefore the interpretation of the monitoring data sets has to be performed by use of the multivariate statistical methods rather than univariate.…”