A HydroLSTM‐Based Machine‐Learning Approach to Discovering Regionalized Representations of Catchment Dynamics

Abstract Finding similarities between model parameters across different catchments has proved to be challenging. Existing approaches struggle due to catchment heterogeneity and non‐linear dynamics. In particular, attempts to correlate catchment attributes with hydrological responses have failed due...

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書誌詳細

出版年:	Water Resources Research
主要な著者:	Luis A. De la Fuente, Andrew Bennett, Hoshin V. Gupta, Laura E. Condon
フォーマット:	論文
言語:	英語
出版事項:	Wiley 2025-08-01
主題:	regionalization catchment attributes streamflow similarity clustering HydroLSTM
オンライン･アクセス:	https://doi.org/10.1029/2024WR039008