Using Physics-Encoded GeoAI to Improve the Physical Realism of Deep Learning′s Rainfall-Runoff Responses under Climate Change

Recent research has shown that deep learning (DL) faces physical realism challenges in predicting runoff responses under climate change, mainly due to DL’s data dependence and lack of process understanding. In this study, a physics-encoded neural network model (dNN) was developed to adress this. dNN...

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Bibliographic Details

Published in:	International Journal of Applied Earth Observations and Geoinformation
Main Authors:	Heng Li, Yuqian Hu, Chunxiao Zhang, Dingtao Shen, Bingli Xu, Min Chen, Wenhao Chu, Rongrong Li
Format:	Article
Language:	English
Published:	Elsevier 2024-09-01
Subjects:	Climate Change Deep Learning Process-based Modeling Physics-Encoded Hybrid Modeling Runoff responses
Online Access:	http://www.sciencedirect.com/science/article/pii/S1569843224004552