Assessment spatial variability and Mapping of drinking and agricultural water quality using geostatisticsand GIStechniques

Document Type : Research Article

Authors

1 Department of Natural Resources Science, College of Agriculture, Fasa University

2 Department of Water Engineering, College of Agriculture, Fasa University

Abstract

Quality properties of groundwater is one of the major components which can used for water resources management. In this study, spatial variability of groundwater quality for drinking uses
(Schoeller standards) and agricultural uses (Wilcox standards) was investigated during 1387-1392.In this research, we use information of 24 observation wells in Fasa plain, to investigate the spatial variability of water quality parameters for different category by using geostatistics technique in GIS software and associated areas of different classof water quality were also determined. Afterwards, the change in the area by using parametric (linear regression) and non-parametric (Spearman) statistical tests for determined period was evaluated. The results showed that the areas with suitable class for drinking and agricultural uses based on the both statistical methods were decreased, while the areas with unsuitable class were increased. The categories of drinking water quality evaluated by spatial variability of the study area fall under unsuitable class, Bad class and temporarily acceptable class which these areas have been increased and are not significant at 95% level. The categories of agricultural water quality evaluated by spatial variability of the study area fall under good class, average class and bad class which the areas with average quality class have been decreased and the areas with bad quality class have been increased,these variables are significant at 95% level based on the both statistical methods.
 

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Main Subjects

References

منابع
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Iranian journal of Ecohydrology
Volume 3, Issue 4
January 2017
Pages 505-516

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History

  • Receive Date: 21 November 2016
  • Revise Date: 19 December 2016
  • Accept Date: 21 December 2016

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