Groundwater vulnerability assessment: A review including new statistical and hybrid methods.

Taghavi, Nasrin; Niven, Robert K; Paull, David J; Kramer, Matthias

Taghavi, Nasrin; Niven, Robert K; Paull, David J; Kramer, Matthias.

Afiliação

Taghavi N; School of Engineering and Information Technology, The University of New South Wales, Canberra, ACT 2600, Australia.
Niven RK; School of Engineering and Information Technology, The University of New South Wales, Canberra, ACT 2600, Australia. Electronic address: r.niven@adfa.edu.au.
Paull DJ; School of Science, The University of New South Wales, Canberra, ACT 2600, Australia.
Kramer M; School of Engineering and Information Technology, The University of New South Wales, Canberra, ACT 2600, Australia.

Sci Total Environ ; 822: 153486, 2022 May 20.

Article em En | MEDLINE | ID: mdl-35122861

Assuntos

Monitoramento Ambiental; Água Subterrânea; Teorema de Bayes; Simulação por Computador; Monitoramento Ambiental/métodos; França

Palavras-chave

Bayesian inference; Groundwater vulnerability assessment; Overlay and index-based methods; Process-based methods; Statistical methods

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Água Subterrânea / Monitoramento Ambiental Tipo de estudo: Prognostic_studies País como assunto: Europa Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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