@article{fdi:010078916,
  title = {{D}imension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the {P}rovence-{A}lpes-{C}ote d'{A}zur region, {F}rance},
  author = {{T}iouiouine, {A}. and {Y}ameogo, {S}. and {V}alles, {V}. and {B}arbi{\'e}ro, {L}aurent and {D}assonville, {F}. and {M}oulin, {M}. and {B}ouramtane, {T}. and {B}ahaj, {T}. and {M}orarech, {M}. and {K}acimi, {I}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he {SISE}-{E}aux database of water intended for human consumption, archived by the {F}rench {R}egional {H}ealth {A}gency ({ARS}) since 1990, is a rich source of information. {H}owever, more or less regular monitoring over almost 30 years and the multiplication of parameters lead to a sparse matrix (observations x parameters) and a large dimension of the hyperspace of data. {T}hese characteristics make it difficult to exploit this database for a synthetic mapping of water quality, and to identify of the processes responsible for its diversity in a complex geological context and anthropized environment. {A} 10-year period (2006-2016) was selected from the {P}rovence-{A}lpes- {C}ote d'{A}zur region database ({PACA}, southeastern {F}rance). {W}e extracted 5,295 water samples, each with 15 parameters. {A} treatment by principal component analysis ({PCA}) followed with orthomax rotation allows for identifying and ranking six principal components ({PC}s) totaling 75% of the initial information. {T}he association of the parameters with the principal components, and the regional distribution of the {PC}s make it possible to identify water-rock interactions, bacteriological contamination, redox processes and arsenic occurrence as the main sources of variability. {H}owever, the results also highlight a decrease of useful information, a constraint linked to the vast size and diversity of the study area. {T}he development of a relevant tool for the protecting and managing of water resources will require identifying of subsets based on functional landscape units or the grouping of groundwater bodies.},
  keywords = {hydrochemistry ; water resource ; hydrogeology ; multivariate statistics ; {F}rance ; {FRANCE}},
  booktitle = {},
  journal = {{W}ater},
  volume = {12},
  numero = {2},
  pages = {art. 525 [18 p.]},
  year = {2020},
  DOI = {10.3390/w12020525},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078916},
}