Hierarchical Deep Learning for Consistent Multi‐Timescale Hydrological Forecasting

Abstract This research introduces a novel method for accurate and consistent hydrological forecasting at multiple timescales. Deep learning (DL) models are increasingly being used for hydrological forecasting across various timescales (hourly, daily, etc.). However, one of the main challenges with m...

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Bibliografski detalji

Glavni autori:	M. S. Jahangir, J. Quilty
Format:	Artigo
Jezik:	Inglês
Izdano:	Wiley 2025-07-01
Serija:	Water Resources Research
Teme:	hydrological forecasting multi‐timescale forecasting temporal hierarchical reconciliation long short‐term memory
Online pristup:	https://doi.org/10.1029/2024WR038105
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