Soil water erosion susceptibility assessment using deep learning algorithms

•Soil water erosion (SWE) is predicted though three kinds of deep learning algorithms.•Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and Long-Short Term Memory (LSTM) are investigated.•All three models had good prediction performance, with RNN being marginally the most superior....

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Bibliographic Details
Published in:	Journal of hydrology (Amsterdam) Vol. 618; p. 129229
Main Authors:	Khosravi, Khabat, Rezaie, Fatemeh, Cooper, James R., Kalantari, Zahra, Abolfathi, Soroush, Hatamiafkoueieh, Javad
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.03.2023
Subjects:	CNN Deep learning ecosystems erosion control infrastructure Land degradation LSTM neural networks prediction RNN Soil erosion soil water water erosion water quality watersheds Deep learning CNN Soil erosion RNN LSTM Land degradation
ISSN:	0022-1694, 1879-2707, 1879-2707
Online Access:	Get full text
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