Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience

Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience

Reliable forecasting of extreme river water levels is vital for managing flood and drought risks in Bangladesh, a deltaic nation highly vulnerable to climate change. This study compares nine machine learning (ML) models for predicting monthly maximum and minimum water levels at three key stations al...

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Bibliographic Details
Main Authors: Md Touhidul Islam, Sujan Chandra Roy, Nusrat Jahan, Al-Mahmud, Md Mazharul Islam, Abdullah Al Ferdaus, Kazunori Fujisawa, A.K.M. Adham
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Progress in Disaster Science
Subjects:
Extreme River water level forecasting
Flood and drought prediction
Machine learning
Spatiotemporal variation
Online Access:http://www.sciencedirect.com/science/article/pii/S2590061725000468
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http://www.sciencedirect.com/science/article/pii/S2590061725000468

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