Articles | Volume 386
https://doi.org/10.5194/piahs-386-81-2024
https://doi.org/10.5194/piahs-386-81-2024
Post-conference publication
 | 
19 Apr 2024
Post-conference publication |  | 19 Apr 2024

Artificial neural networks applied for flood forecasting in ungauged basin – the Paranaíba river study case

Abderraman R. A. Brandão, Frederico C. M. de Menezes Filho, Paulo T. S. Oliveira, and Maria C. Fava

Viewed

Total article views: 281 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
191 73 17 281 13 13
  • HTML: 191
  • PDF: 73
  • XML: 17
  • Total: 281
  • BibTeX: 13
  • EndNote: 13
Views and downloads (calculated since 19 Apr 2024)
Cumulative views and downloads (calculated since 19 Apr 2024)

Viewed (geographical distribution)

Total article views: 274 (including HTML, PDF, and XML) Thereof 274 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 13 Dec 2024
Download
Short summary
Flow simulation using artificial neural networks is widely used in modeling, particularly in data-scarce areas. Our study utilized MLP neural networks to predict urban runoff in flood-prone basin. Motivated by the vulnerability to floods, we input rainfall and previous runoff data. The model effectively captured basin dynamics, highlighting the impact of urbanization. This research supports urban river basin planning and aids in flood mitigation and adaptation strategies.