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Quality Evaluation of Groundwater Resources using Geostatistical Methods (Case Study: Central Lorestan Plain, Iran)

Quality Evaluation of Groundwater Resources using Geostatistical Methods (Case Study: Central... In this research, based on the qualitative data of 40 wells, variations of water quality parameters of the Central Plain Aquifer were evaluated using kriging and IDW (Inverse Distance Weighting) methods. Owing to the normal distribution of the studied parameters (except Na+, SO4 2−, and TH: total hardness), ordinary kriging was used for modeling. The analysis of the data trends indicated that all the variables were influenced by in two general trends, i.e., NW–SE and NE–SW. In fact, these trends were a result of the effect of the structural conditions on aquifer properties such as transmissivity and flow direction. Variogram analysis (based on C0 near zero and C0/σ2 ratio between 0.0–0.5) showed that the Na+, TDS (total dissolved solids), Ca2+, and TH variables have a good spatial structure and the BOD (biochemical oxygen demand), COD (chemical oxygen demand), NO3 −, and EC variables have poor spatial structure. The BOD, COD, NO3 −, and EC (electrical conductivity) variables have the smallest range and isotropic distribution. On the other hand, the Ca2+, Mg2+, Na+, SO4 2−, Cl−, HCO3 −, pH, TDS, TH and Alk (alkalinity) parameters are characterized by anisotropic distributions. The Na+, TDS, Ca2+, and TH variables have the largest range. The results showed that both the IDW and kriging methods have close estimates to one another. The pH variable decreases toward the outlet whereas the EC and TDS variables increase along the direction of water flow and toward the outlet. The distributions of the BOD and COD variables do not perfectly match with the aggregation of industrial activities in the central part as well as the agricultural activities in the southeastern and central parts of the aquifer. The distributions of the Ca2+, Mg2+, and Alk variables completely follow the geology condition and regional spread of carbonate formations. The Na+ concentration increases from the center toward the outlet. The concentration of the Cl− variable is the highest in the central part of the plain due to the concentration of agricultural and industrial activities. The distribution of the SO4 2− variable is influenced by a natural factor (lithology), especially in the southeastern parts and the outlet as well as artificial factors (agricultural and industrial activities) in the central and southeastern parts of the aquifer. The NO3 − variable, which is directly influenced by agricultural and livestock-farming activities, has its maximum concentration in the southeastern areas. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Management Springer Journals

Quality Evaluation of Groundwater Resources using Geostatistical Methods (Case Study: Central Lorestan Plain, Iran)

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Publisher
Springer Journals
Copyright
Copyright © 2018 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Earth Sciences; Hydrogeology; Hydrology/Water Resources; Geotechnical Engineering & Applied Earth Sciences; Atmospheric Sciences; Civil Engineering; Environment, general
ISSN
0920-4741
eISSN
1573-1650
DOI
10.1007/s11269-018-2009-2
Publisher site
See Article on Publisher Site

Abstract

In this research, based on the qualitative data of 40 wells, variations of water quality parameters of the Central Plain Aquifer were evaluated using kriging and IDW (Inverse Distance Weighting) methods. Owing to the normal distribution of the studied parameters (except Na+, SO4 2−, and TH: total hardness), ordinary kriging was used for modeling. The analysis of the data trends indicated that all the variables were influenced by in two general trends, i.e., NW–SE and NE–SW. In fact, these trends were a result of the effect of the structural conditions on aquifer properties such as transmissivity and flow direction. Variogram analysis (based on C0 near zero and C0/σ2 ratio between 0.0–0.5) showed that the Na+, TDS (total dissolved solids), Ca2+, and TH variables have a good spatial structure and the BOD (biochemical oxygen demand), COD (chemical oxygen demand), NO3 −, and EC variables have poor spatial structure. The BOD, COD, NO3 −, and EC (electrical conductivity) variables have the smallest range and isotropic distribution. On the other hand, the Ca2+, Mg2+, Na+, SO4 2−, Cl−, HCO3 −, pH, TDS, TH and Alk (alkalinity) parameters are characterized by anisotropic distributions. The Na+, TDS, Ca2+, and TH variables have the largest range. The results showed that both the IDW and kriging methods have close estimates to one another. The pH variable decreases toward the outlet whereas the EC and TDS variables increase along the direction of water flow and toward the outlet. The distributions of the BOD and COD variables do not perfectly match with the aggregation of industrial activities in the central part as well as the agricultural activities in the southeastern and central parts of the aquifer. The distributions of the Ca2+, Mg2+, and Alk variables completely follow the geology condition and regional spread of carbonate formations. The Na+ concentration increases from the center toward the outlet. The concentration of the Cl− variable is the highest in the central part of the plain due to the concentration of agricultural and industrial activities. The distribution of the SO4 2− variable is influenced by a natural factor (lithology), especially in the southeastern parts and the outlet as well as artificial factors (agricultural and industrial activities) in the central and southeastern parts of the aquifer. The NO3 − variable, which is directly influenced by agricultural and livestock-farming activities, has its maximum concentration in the southeastern areas.

Journal

Water Resources Management – Springer Journals

Published: May 31, 2018

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