Development of a Regional Gridded Runoff Dataset Using Long Short-Term Memory (LSTM) Networks

Development of a Regional Gridded Runoff Dataset Using Long Short-Term Memory (LSTM) Networks

Gridded datasets provide spatially and temporally consistent runoff estimates that serve as reliable sources for assessing water resources from regional to global scales. This study presents LSTM-REG, a regional gridded runoff dataset for northwest Russia based on Long Short-Term Memory (LSTM) netwo...

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Bibliographic Details
Main Authors: Georgy Ayzel, Liubov Kurochkina, Dmitriy Abramov, Sergei Zhuravlev
Format: Article
Language:English
Published: MDPI AG 2021-01-01
Series:Hydrology
Subjects:
runoff
modeling
reanalysis
dataset
neural networks
LSTM
Online Access:https://www.mdpi.com/2306-5338/8/1/6

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