Investigating and mapping spatial patterns of arsenic contamination in groundwater using regression analysis and spline interpolation technique

Abstract

Research Article| September 01 2013 Investigating and mapping spatial patterns of arsenic contamination in groundwater using regression analysis and spline interpolation technique Pham Quy Giang; Pham Quy Giang 1Department of Environmental Health Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan2Faculty of Natural Resources and Environment, Hanoi University of Agriculture, Hanoi, Vietnam E-mail: p11604@u-shizuoka-ken.ac.jp Search for other works by this author on: This Site PubMed Google Scholar Kosuke Toshiki; Kosuke Toshiki 1Department of Environmental Health Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan Search for other works by this author on: This Site PubMed Google Scholar Shoichi Kunikane; Shoichi Kunikane 1Department of Environmental Health Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan Search for other works by this author on: This Site PubMed Google Scholar Masahiro Sakata Masahiro Sakata 1Department of Environmental Health Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka-shi, Shizuoka 422-8526, Japan Search for other works by this author on: This Site PubMed Google Scholar Journal of Water Supply: Research and Technology-Aqua (2013) 62 (6): 385–394. https://doi.org/10.2166/aqua.2013.102 Article history Received: August 02 2012 Accepted: June 21 2013 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Share Icon Share MailTo Twitter LinkedIn Tools Icon Tools Cite Icon Cite Permissions Search Site Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThis Journal Search Advanced Search Citation Pham Quy Giang, Kosuke Toshiki, Shoichi Kunikane, Masahiro Sakata; Investigating and mapping spatial patterns of arsenic contamination in groundwater using regression analysis and spline interpolation technique. Journal of Water Supply: Research and Technology-Aqua 1 September 2013; 62 (6): 385–394. doi: https://doi.org/10.2166/aqua.2013.102 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex The present study investigates the hypothesis that arsenic concentrations correlate with tubewell depth, and examines the effectiveness of spline interpolation, specifically completely regularized spline (CRS) and spline with tension (SWT) in estimating the magnitude of arsenic contamination in groundwater in Thanh Tri, a densely populated district located in the southern part of Hanoi City, Vietnam. Groundwater sampling conducted in 72 tubewells drilled into shallow aquifers yielded an average arsenic concentration of 82 μg/L with a maximum of 395 μg/L, far higher than the World Health Organization (WHO) guideline value of 10 μg/L. The average concentration in the lower Pleistocene aquifer was 86 μg/L, slightly higher compared with the average of 78 μg/L in the upper Holocene aquifer. Interestingly, regression analysis revealed that in the Holocene aquifer, depth of wells influenced arsenic concentrations significantly. Such an influence, however, was insignificant in the lower Pleistocene aquifer. Both the CRS and SWT spatial interpolation models resulted in plausible predictions for the arsenic concentration data. The problem of arsenic contamination in the study area should be considered seriously, as 99% of the area was estimated to be affected by arsenic levels exceeding the WHO guideline value. arsenic, groundwater contamination, regression analysis, spline interpolation This content is only available as a PDF. © IWA Publishing 2013 You do not currently have access to this content.