Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis-Reference-Cited by-同舟云学术

Artificial intelligence for identifying hydrologically homogeneous regions: A state‐of‐the‐art regional flood frequency analysis

Published:2019-02-04 Issue:7 Volume:33 Page:1101-1116
ISSN:0885-6087
Container-title:Hydrological Processes
language:en
Short-container-title:Hydrological Processes

Author:

Cassalho Felício¹^ORCID,Beskow Samuel¹^ORCID,Mello Carlos Rogério²^ORCID,Moura Maíra Martim¹,Oliveira Leroi Floriano³,Aguiar Marilton Sanchotene³

Affiliation:

1. Center for Technological Development/Water Resources EngineeringFederal University of Pelotas. Hydrology and Hydrological Modeling Laboratory Pelotas Brazil

2. Water Resources DepartmentFederal University of Lavras Lavras Brazil

3. Center for Technological Development/Computer Science Graduate ProgramFederal University of Pelotas Pelotas Brazil

Funder

Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul

Fundação de Amparo à Pesquisa do Estado de Minas Gerais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Wiley

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.13388

Reference53 articles.

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5. W. H. Asquith Distributional analysis with L‐moments statistics using the R environment for statistical computing 2011 CreateSpace Independent Publishing Platform Lubbock Texas 360

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