Geostatistical Approach for Groundwater Quality Evaluation in Zarin Abad Plain, Iran

  • Abdollah Taheri Tizro
  • Mohamad Mohamadi
Keywords: Geostatistical Analysis; Groundwater quality; Zarin Abad plain;Water quality

Abstract

Background and Purpose: This study was undertaken, first, to investigate the hydrogeological setting of the study area and geophysical data, second to examine the general nature of the groundwater quality. In this regard, ordinary Kriging, Co-Kriging, and Inverse Weighted Distance (IWD) strategies were applied to develop spatial variability maps, and study the fluctuations in groundwater quality parameters in Zarin Abad plain, Zanjan Province, Iran in 2017-2018.

Materials and methods: To inquire the groundwater quality parameters, samples were provided from 61 shallow and deeply drilled observed wells in Zarin Abad Goltapeh plain. The studies were carried out by using geostatistical methods to find out the most applicable method, which can be used to develop spatial variability maps in order to study the changes in groundwater quality parameters (Na+, K+, Ca2+, Mg2+, SO42-, HCO3-, Cl- and EC).  The local geophysical, geological, and hydrogeological surveys were precisely accomplished to specify the architecture of various subsurface geological horizons. In addition, a geophysical investigation with a Schlumberger configuration was performed in the study region for the purpose of field data generation.

Results: Based on key results, the values of electrical conductivity (EC) were recorded within the range of 480 and 6580 μS/cm. The order of major cations and anions were Na+>Ca2+>Mg2+ and SO42->Cl->HCO3-, respectively. It is worthwhile mentioning that groundwater salinity was found to be dependent upon factors, such as water long residence time and minerals dissolution.

Conclusion: To assess the spatial distribution in groundwater parameters, the variable mode was used. The results obtained from Kriging, Co-Kriging, and IDW methods were then evaluated by the error indices of RMSE and MAE. Co-Kriging Model was the most optimal approach in studying the spatial variation of groundwater quality parameters.

Published
2019-10-07
Section
Articles