Spatial variations of groundwater quality parameters using geostatistics (Case study: Segsi Plain, Isfahan)

Subject Areas : environmental management

Zahra Azhdari ¹ , Seyed Zeynalabedin Hosseini ²

1 - PhD Student on Watershed Management, Department of Rangeland and Watershed Management, Faculty of Agriculture and Natural Resources, Hormozgan University.
2 - Assistant Professor, Department of Rangeland and Watershed Management, Faculty of Natural Resources and Desert Studies, Yazd University *(Corresponding author).

Received: 2016-04-16 Accepted : 2016-05-16 Published : 2018-09-23

Keywords: Groundwater, Geostatistical methods, Kriging, Segsi plain,

Abstract :

Background and Objective: Understanding chemical changes in groundwater and their mapping play a substantial role in optimal management of groundwater in an area. There are various methods for investigation and classification of groundwater chemical features, and selection of appropriate method depends on the purpose, conditions of the area and available information. Geostatistical methods and GIS can be useful tools in this regard. The aim of his study is to investigate the spatial variations of groundwater quality and select the best mapping method for the management of groundwater resources in Segsi plain. Method: In this paper, the distribution of quality pollutants pH, TDS, Hco3, EC, Ca, Mg, TH, Na and So4 in groundwater of Segsi plain was investigated using inverse distance and geostatistical methods, distance and bearing functions, local, general and ordinary Kriging estimator software ARCGIS9.3. Accordingly, the sample from 445 groundwater wells, springs and canals were examined. After evaluating variograms and determining the spatiality of the changes in the studied parameters, interpolation of parameters was performed and the best evaluation model with lowest RMSE was selected through mutual evaluation technique and the root-mean-square error. Findings: The results showed that all parameters had the lowest RMSE using the ordinary Kriging method and it was used for mapping the spatial distribution of water quality parameters. Results from mapping indicated that Na, Ca, Mg, So4, Hco3 and pH had no limitation and EC, TH and TDS had limitations in terms of drinkability. Conclusion: According to the results, application of the ordinary Kriging method is recommended for more precision, less calculation and less data demand among various interpolation methods for the groundwater mapping.

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