Data for factor analysis of hydro-geochemical characteristics of groundwater resources in Iranshahr

• Published in: Data in brief Vol. 19; pp. 548 - 563
• Main Authors: Biglari, Hamed, Saeidi, Mehdi, Karimyan, Kamaleddin, Narooie, Mohammad Reza, Sharafi, Hooshmand
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.08.2018; Elsevier
• Subjects: Correlation matrix; Environmental Science; Factor analysis; Groundwater resources; Hydro-geochemistry; Iranshahr; Iranshahr; Factor analysis; Hydro-geochemistry; Groundwater resources; Correlation matrix
• ISSN: 2352-3409; 2352-3409
• DOI: 10.1016/j.dib.2018.05.039

Detection of Hydrogeological and Hydro-geochemical changes affecting the quality of aquifer water is very important. The aim of this study was to determine the factor analysis of the hydro-geochemical characteristics of Iranshahr underground water resources during the warm and cool seasons. In this study, 248 samples (two-time repetitions) of ground water resources were provided at first by cluster-random sampling method during 2017 in the villages of Iranshahr city. After transferring the samples to the laboratory, concentrations of 13 important chemical parameters in those samples were determined according to o water and wastewater standard methods. The results of this study indicated that 45.45% and 55.55% of the correlation between parameters has had a significant decrease and increase, respectively with the transition from warm seasons to cold seasons. According to the factor analysis method, three factors of land hydro-geochemical processes, supplying resources by surface water and sewage as well as human activities have been identified as influential on the chemical composition of these resources.The highest growth rate of 0.37 was observed between phosphate and nitrate ions while the lowest trend of − 0.33 was seen between fluoride ion and calcium as well as chloride ions. Also, a significant increase in the correlation between magnesium ion and nitrate ion from warm seasons to cold seasons indicates the high seasonal impact of the relation between these two parameters.