Integrating Hydrological–Hydraulic–AI (LSTM) Models for Improved Water Level Forecasting: Red River - Thai Binh Basin Cover

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Integrating Hydrological–Hydraulic–AI (LSTM) Models for Improved Water Level Forecasting: Red River - Thai Binh Basin

Civil and Environmental Engineering

By: Tri Doan Quang, Nhat Nguyen Van and Tuyet Quach Thi Thanh

Open Access

|Nov 2025

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DOI: https://doi.org/10.2478/cee-2026-0042 | Journal eISSN: 2199-6512 | Journal ISSN: 1336-5835

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Language: English

Submitted on: Sep 8, 2025

Accepted on: Sep 24, 2025

Published on: Nov 12, 2025

Published by: University of Žilina

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

Water level forecasting,

Red River - Thai Binh Basin,

NAM-MIKE 11-LSTM,

Flood risk management

Related subjects:

Business and economics,

Political economics,

Economic theory, systems and structures,

Business management,

Environmental management

© 2025 Tri Doan Quang, Nhat Nguyen Van, Tuyet Quach Thi Thanh, published by University of Žilina
This work is licensed under the Creative Commons Attribution 4.0 License.