Water Quality Data | Analysis and Interpretation | Taylor & Francis GroupModeling Earth Systems and Environment. October , Cite as. Multivariate statistical methods, such as principal components analysis PCA , discriminant analysis DA and general linear models GLM were applied to incorporate physico-chemical surface water quality in low and high flow hydrology in Northern Iran, based on analysis of the 7-day low flow index and existing water quality data. In view of this, 7-day low flows were calculated for 15 water years — at 15 monitoring stations. Eleven water quality parameters were extracted during the low flows from the water quality data and compared to water quality during high flows.
Tutorial: Statistics and Data Analysis
Water Quality Data
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Preview this Book. Since the increase in water quality monitoring stations increases annual monitoring costs, cluster analysis and discriminant analysis are widely applied to evaluate surface and groundwater quality. Furthermore, the KMO of 0. Although multivariate statistical techniques such as principal components analysis, recognition of the stations with higher importance as well as main parameters can be effective in future decisions to improve the existing dafa n.
Hydrology and hydrobiology of Haraz River? Clipping is a handy way to intwrpretation important slides you want to go back to later. Imprint CRC Press. Close Preview.Water Quality Data. The shares of each of the first and second components are. Table 1: measurement methods and devices used in the present research. Factor loadings are the simple correlations between the water quality variables and each factor.
One of the key issues in determining the quality of water in rivers is to create a water quality control network with a suitable performance. The measured qualitative variables at stations should be representative of all the changes in water quality in water systems. Since the increase in water quality monitoring stations increases annual monitoring costs, recognition of the stations with higher importance as well as main parameters can be effective in future decisions to improve the existing monitoring network. Sampling was carried out on 12 physical and chemical parameters measured at 15 stations during — in Haraz River, northern Iran. The results of the measurements were analyzed using multivariate statistical analysis methods including cluster analysis CA , principal component analysis PCA , factor analysis FA , and discriminant analysis DA. The research findings confirm applicability of multivariate statistical techniques in the interpretation of large data sets, water quality assessment, and source apportionment of different pollution sources.
For clustering of water quality data, the average value of parameters during the sampling periods was used. Honestly I am very interested and very amazed at the author who wrote this book. Apart from the anthropogenic sources, job creation especially in rural c.
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