Statistical methods for the geochemical characterisation of surface waters: The case study of the Tiber River basin (Central Italy)

Abstract

Studying the chemistry of surface waters and their resilience to compositional changes represents a global challenge to preserve them from human- and changing climate-induced modifications. River waters are sentinel parameters for all processes occurring in a river basin. This is particularly true for regional watersheds, which can include both natural- and anthropogenic-sourced solutes such as those present in the Tiber River basin, the biggest one in Central Italy. In this work, innovative applications of statistical methods are proposed, from the perspective of Compositional Data Analysis theory, in order to consider the geochemical riverine system as a whole and detect compositional changes throughout the catchment. Robust compositional biplots highlighted different sources of variability linked to geological (low variability) and anthropogenic origin (high variability) of the main compounds, thus identifying a hierarchy in the variance of the riverine geochemical processes. On a different scale, the innovative use of the robust Mahalanobis distance in an iterative way monitored spatial compositional shifts for single cases. The effectiveness of this method consists in minimising the influence of an individual anomalous point on the compositional centre and the covariance structure of the data highlighting when along the river a significant compositional shift occurs. The study provides powerful compositional tools for detecting potential contamination events or climate-induced modifications both at catchment and river scale.