Physical and Mathematical Constraints in Artificial Intelligence-Based Methods for Monitoring Floods and Droughts

Authors

  • Leonardo B. L. Santos
  • Vitor Y. Hossaki
  • Jaqueline A. J. P. Soares
  • Marcelo Zeri
  • Ricardo S. Oyarzabal
  • Ana P. A. Cunha
  • Aurelienne A. S. Jorge
  • Fernando L. S. Filho
  • Johan S. D. Buitrago
  • Roberta B. Bacelar

Abstract

Disasters, including floods and droughts, are a pressing issue for many countries, particularly Brazil, due to the significant loss of life and economic damage they cause. The effects of climate change are expected to aggravate this issue by increasing the frequency and intensity of extreme weather events. Therefore, developing accurate and reliable disaster forecasting models is critical to reducing the impact of these events. [...]

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Author Biographies

Leonardo B. L. Santos

CEMADEN, São José dos Campos, SP

Vitor Y. Hossaki

CEMADEN, São José dos Campos, SP

Jaqueline A. J. P. Soares

CEMADEN, São José dos Campos, SP

Marcelo Zeri

CEMADEN, São José dos Campos, SP

Ricardo S. Oyarzabal

CEMADEN, São José dos Campos, SP

Ana P. A. Cunha

CEMADEN, São José dos Campos, SP

Aurelienne A. S. Jorge

INPE, São José dos Campos, SP

Fernando L. S. Filho

UNIFESP, São José dos Campos, SP

Johan S. D. Buitrago

UTEC, Durazno, Uruguay

Roberta B. Bacelar

Faculdade Anhanguera, São José dos Campos, SP

References

Lei Xu, Nengcheng Chen, Zeqiang Chen, Chong Zhang, and Hongchu Yu. “Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions”. In: Earth-Science Reviews 222 (2021), p. 103828. issn: 0012-8252. doi: https://doi.org/10.1016/j.earscirev.2021.103828. url: https://www.sciencedirect.com/science/article/pii/S0012825221003299.

R. Oyarzabal. “Artificial Intelligence and Drougt - a systematic literature review”. In: Water to be submitted (2023).

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Published

2023-12-18