Identifying the origin of groundwater samples in a multi-layer aquifer system with Random Forest classification

Journal of Hydrology

Volumn 499, Issue , 2013, Pages 303-315

  Baudron, Paul ^a,d,e   Alonso Sarría, Francisco ^b   García Aróstegui, José Luís ^c   Cánovas García, Fulgencio ^b   Martínez Vicente, David ^a,b   Moreno Brotóns, Jesús ^b  

^a Fundación Instituto Euromediterráneo del Agua   (Spain)

^b UNIVERSITY OF MURCIA   (Spain)

^c INSTITUTO GEOLÓGICO Y MINERO DE ESPAÑA   (Spain)

^d INSTITUT DE RECHERCHE POUR LE DÉVELOPPEMENT   (France)

^e UNIVERSITÉ PARIS SACLAY   (France)

Author keywords

Hydrogeochemistry; Hydrogeology; Longscreen boreholes; Machine learning; Multi layer aquifer; Random Forest

Indexed keywords

GEOCHEMICAL VARIABLES; HYDRO GEOCHEMISTRIES; HYDROGEOCHEMICAL DATA; LINEAR DISCRIMINANT ANALYSIS; MACHINE LEARNING TECHNIQUES; RANDOM FOREST CLASSIFICATION; RANDOM FORESTS; SUPERVISED CLASSIFICATION;

AQUIFERS; BLENDING; BOREHOLES; DECISION TREES; EXTRACTION; GROUNDWATER RESOURCES; HYDROGEOLOGY; LEARNING SYSTEMS;

HYDROCHEMISTRY;

ACCURACY ASSESSMENT; AQUIFER CHARACTERIZATION; BOREHOLE; DATA SET; HYDROGEOCHEMISTRY; IONIC COMPOSITION; MODEL VALIDATION; UNCERTAINTY ANALYSIS;

CAMPO DE CARTAGENA; MURCIA [SPAIN]; SPAIN;

EID: 84881260711     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2013.07.009     Document Type: Article

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