Predicting sea level variations for early warning using SARIMA model and deep learning techniques in the northwest Arabian Gulf

Abstract Predicting sea level variations (SLV) in coastal areas is essential for flood warnings, environmental protection, and infrastructure management. While sea level forecasting has been studied in various parts of the Arabian Gulf, limited research exists on water level prediction for Iraqi coa...

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Detalhes bibliográficos

Principais autores:	Abather Jabbar Bashar Alhallaf, J Vilcáez, Pratyaydipta Rudra, Ali A. Lafta
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Springer 2025-10-01
coleção:	Discover Geoscience
Assuntos:	Time series analysis SLV ARIMA SARIMA CNN LSTM
Acesso em linha:	https://doi.org/10.1007/s44288-025-00270-y
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