Nowcast flood predictions in the Amazon watershed based on the remotely sensed rainfall product PDIRnow and artificial neural networks-Reference-Cited by-同舟云学术

Nowcast flood predictions in the Amazon watershed based on the remotely sensed rainfall product PDIRnow and artificial neural networks

Published:2024-02-08 Issue:3 Volume:196 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Filho Herval Alves Ramos^ORCID,Uliana Eduardo Morgan^ORCID,Aires Uilson Ricardo Venâncio^ORCID,da Cruz Ibraim Fantin^ORCID,Lisboa Luana^ORCID,da Silva Demetrius David^ORCID,Viola Marcelo Ribeiro^ORCID,Duarte Victor Braga Rodrigues^ORCID

Funder

Universitade Federal do Mato Grosso

Coordenação de Aperfeiçoamentode Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10661-024-12396-6.pdf

Reference47 articles.

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4. Berkhahn, S., Fuchs, L., & Neuweiler, I. (2019). An ensemble neural network model for real-time prediction of urban floods. Journal of Hydrology, 575, 743–754. https://doi.org/10.1016/j.jhydrol.2019.05.066

5. Chebii, S. J., Mukolwe, M. M., & Ong’or, B. I. (2022). River flow modelling for flood prediction using artificial neural network in ungauged Perkerra catchment, Baringo County, Kenya. Water Practice and Technology, 17(4), 914–929. https://doi.org/10.2166/wpt.2022.034