Document Type : پژوهشی
Authors
1 Associate professor in department of Physical Geography Faculty of Earth Sciences, Shahid Beheshti University (SBU), Tehran, Iran (Correspondin author), E-mail:k-nosrati@sbu.ac.ir.
2 M.S.C, Graduated of Hydrogeomorphology, Earth Science Faculty, Shahid Beheshti University, Tehran, Iran.
3 Head of Research Committee, Rural Water and Sewage Company, Tehran, Iran
Abstract
Abstract
Introduction
Groundwater is the most important source of drinking water in most communities. Water quality assessment and hydrogeochemical agents that effect water quality due to its direct impact on consumers' health is essential. Before 1970s, the focus of most studies was on physical properties of water, but in the recent century developments in sciences (i.e., chemistry and geology) researches on groundwater quality has improved. Approaches to estimate the effects of time and place on the quality and quantity of groundwater are univariate and multivariate statistical techniques. Water resource is getting more and more important in drought and interior regions such as Iran which is located in a desert belt. Therefore, the classification and analysis of groundwater quality in Mallard city in the margin of an interior basin by using multivariate statistical analysis were the aims of this study.
Methodology
The City of Mallard is located in the border of three provinces consisting of Markazi, Tehran, and Alborz. The study area has geographical coordinate with 50° 20´ to 51° eastern longitude and 35° 28´ to 35° 43´ northern latitude. The data used in this study was prepared by rural water and wastewater of Mallard. Thirteen quantitative parameters in thirty-one water wells during 2010-2015 were selected. The data was divided into three qualitative classes on the basis of a hierarchical cluster analysis. Furthermore, to identify the most important water quality parameters in each homogeneous region, a factor analysis on the basis of main component analysis method was used. In order to recognize the suitability or merit of the data, before performing factor analysis, KMO and Bartlett's spit test were done. Hence, the number of factors and main components of groundwater quality were determined. Furthermore, to a better recognition of sample's number on the basis of connection between the factors and their values a graph was depicted that breaks in the axis of the graph defined the number of the main components. In this study, to show the results of the cluster analysis, factor analysis, and one-way variance analysis, SPSS software was applied. After performing a statistical analysis on the basis of the interpolation method and by applying Arc GIS software, the study area was mapped. After registration of the location of any well by GPS, the estimation of use land and geological states was done.
Results and discussion
Based on the quality of water wells in Mallard city, all wells were divided into three qualitative clusters. Accordingly, ten wells were settled in the first cluster, twelve wells in the second cluster, and nine wells in the third cluster. The qualitative zoning showed Mallard's wells in terms of the cluster analysis. The distance between the wells is due to solidarity and self- solidarity between qualitative characteristics of the water wells. The cluster analysis on Mallard groundwater quantitative data resulted in three quantitative classes for water wells in this city. Therefore, each cluster was analyzed by the measurement of a meaningful data and accordingly quantitative status of the clusters were determined. From first toward third clusters, the concentration of all quantitative parameters except PH increased in a meaningful way.
Conclusion
The results revealed that the water quality in the third cluster was low. In each cluster, three factors, as the main parameters that effect and change the water quality, had respectively total variance of 92.85, 83.58, and 88.93. In addition, evaporate formations, using chemical fertilize, household wastewaters, and non-principle repulsed of poultry farm garbage were the effective parameters on water quality changes in the study area.
Highlights
-
Keywords
)