The isometric log-ratio (ilr)-ion plot: A proposed alternative to the Piper diagram

Abstract The Piper diagram has been a staple for the analysis of water chemistry data since its introduction in 1944. It was conceived to be a method for water classification, determination of potential water mixing between end-members, and to aid in the identification of chemical reactions controlling a sample set. This study uses the information gleaned over the years since the release of the Piper diagram and proposes an alternative to it, capturing the strengths of the original diagram while adding new ideas to increase its robustness. The new method uses compositional data analysis to create 4 isometric log-ratio coordinates for the 6 major chemical species analyzed in the Piper diagram and transforms the data to a 4-field bi-plot, the ilr-ion plot. This ilr-ion plot conveys all of the information in the Piper diagram (water mixing, water types, and chemical reactions) while also visualizing additional data, the ability to examine Ca2+/Mg2+ versus Cl-/SO42−. The Piper and the ilr-ion plot were also compared using multiple synthetic and real datasets in order to illustrate the caveats and the advantages of using either diagram to analyze water chemistry data. Although there are challenges with using the ilr-ion plot (e.g., missing or zero values zeros in the dataset must be imputed by positive real numbers), it appears that the use of compositional data analysis coupled with the ilr-ion plot provides a more in-depth and complete analysis of water quality data compared to the original Piper diagram

Combining hydrogeochemistry, statistics and explorative mapping to estimate regional threshold values of trace elements in groundwater (Sardinia, Italy)

Assessing geochemical baseline and threshold values of potentially toxic elements at adequate scales is fundamental for distinguishing geogenic contamination from anthropogenic pollution in groundwater. This study was aimed to estimate the regional threshold values of Li, Be, B, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Ag, Cd, Sb, Te, Ba, Hg, Tl, Pb, Bi, and U (elements listed according to atomic numbers) in groundwater, compare results to guidelines established for drinking water and the protection of groundwater from contamination, investigate the geographical distribution of trace elements, and assess the potential influence of water-rock interaction. A pre-selection aimed at excluding groundwater samples affected by known anthropogenic activities was carefully carried out based on hydrogeochemical characteristics of waters and considering the potential sources of contamination. The resulting dataset was comprised of 1227 groundwater sampling sites located in Sardinia (Italy). Undetected values were treated using the Regression on Order Statistics method. For elements containing >75 % of undetected values and/or a limited number of samples in the dataset (Li, Rb, Sr, Mo, Ag, Te, Tl, Sb, Hg and Bi), the threshold values were estimated using either the 95th or 97.7th percentiles. For the other elements the mean + 2SD (Standard Deviation), the median + 2MAD (Median Absolute Deviation), and the TIF (Tukey Inner Fence) estimators were also calculated. Geochemical maps allowed to recognize the threshold value of each element at different scales. Regional threshold values of the regulated elements B, Al, V, Cr, Cu and Cd in groundwater were below the Italian and World Health Organization drinking water guidelines, whereas Mn and As were above them. Regional threshold values estimated with TIF exceeded the drinking water guidelines for Ni, Se, Pb and U. Results of this study showed that high concentrations of trace elements in groundwater were primarily dependent on the corresponding amount in parent materials with which the groundwater came into contact. Physical-chemical parameters and geochemical characteristics may contribute to enhancing concentrations of some trace elements in groundwater, e.g. As via reductive dissolution of Fe(III)-Mn(IV) hydroxides/oxides, Pb via formation of stable aqueous complexes, and other elements via adsorption onto fine particles with size below 0.4 μm (i.e. the pore size of filters used). Maps drawn on the centered log-ratio (clr) transformation of hydrogeochemical data, following the CoDA (Compositional Data Analysis) approach, allowed to pinpoint critical areas to be investigated in more detail. For each geological complex, groundwater samples likely representing nearly pristine conditions were identified. The monitoring of these representative groundwater samples may help to pinpoint eventual changes in environmental conditions