D-Piper, a modified piper diagram to represent big sets of hydrochemical analyses. (April 2021)

• Record Type: Journal Article
• Authors: Moreno Merino, Luis; Aguilera, Héctor; González-Jiménez, Miguel; Díaz-Losada, Elisabeth
• Is Part Of: Environmental modelling & software. Volume 138(2021)
• Publication Date: 2021-04
• Subjects: Piper diagram -- Big data set -- Hydrochemistry; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.104979
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The Piper diagram is the most widely used chart in groundwater hydrochemical studies to represent the chemical facies of a set of water samples. So far, most modifications of the original Piper diagram over time show a common problem: the Piper chart is not suitable for representing big data sets. When there are more than 40 or 50 analyses, the symbols overlap, and the data distribution becomes obscured. To overcome this limitation the D-Piper diagram displays the spatial point density instead of individual points. With this modification, both visualization and interpretation improve as the number of points increases. Besides, several representation methods to account for distributional characteristics of the data allow the user to unravel hidden hydrochemical structures. The D-Piper diagram outperforms other point density-based solutions, particularly in the representation of low-density areas. Furthermore, the D-Piper implementation is coded in Python, and it is freely available. Highlights: The Piper diagram is not useful for representing big hydrochemical data sets. D-Piper, an open-source Python code, enables hydrochemical analysis of big data. D-Piper is based on spatial point density and data distribution characteristics.