In the last decade, substantial efforts have been made in understanding how to apply compositional data analysis (CoDa) to the interpretation of water quality data. Presently, there is an improved understanding of the relationship between stoichiometry and chemical equilibrium and to log-ratio interpretative methods. This paper provides an update to CoDa-based graphical methods and their applications to water quality data, and offers examples of log-ratio versions of scatterplots, Stiff diagrams, Durov plots, and trilinear diagrams. Our intention is that this work can be used as a quick tutorial on current knowledge and ideas, and to increase the application of CoDa methods in routine interpretation of water chemistry data.

Merging key concepts in the chemistry of natural waters with compositional data analysis: Updates to basic water quality plots / Engle, M.A.; Buccianti, A.; Olea, R.A.; Blondes, M.S.. - STAMPA. - (2017), pp. 47-55. (Intervento presentato al convegno Compositional Data Analysis Workshop 2017 tenutosi a Abbadia San Salvatore, Siena (Italy) nel 5-9 Giugno).

Merging key concepts in the chemistry of natural waters with compositional data analysis: Updates to basic water quality plots

BUCCIANTI, ANTONELLA;
2017

Abstract

In the last decade, substantial efforts have been made in understanding how to apply compositional data analysis (CoDa) to the interpretation of water quality data. Presently, there is an improved understanding of the relationship between stoichiometry and chemical equilibrium and to log-ratio interpretative methods. This paper provides an update to CoDa-based graphical methods and their applications to water quality data, and offers examples of log-ratio versions of scatterplots, Stiff diagrams, Durov plots, and trilinear diagrams. Our intention is that this work can be used as a quick tutorial on current knowledge and ideas, and to increase the application of CoDa methods in routine interpretation of water chemistry data.
2017
Compositional Data Analysis 2017 Proceedings book
Compositional Data Analysis Workshop 2017
Abbadia San Salvatore, Siena (Italy)
5-9 Giugno
Engle, M.A.; Buccianti, A.; Olea, R.A.; Blondes, M.S.
File in questo prodotto:
File Dimensione Formato  
ProceedingsBook2017_Buccianti.pdf

Accesso chiuso

Tipologia: Versione finale referata (Postprint, Accepted manuscript)
Licenza: Tutti i diritti riservati
Dimensione 2.22 MB
Formato Adobe PDF
2.22 MB Adobe PDF   Richiedi una copia

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1092546
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact