Insight into glacio-hydrologicalprocesses using explainable machine-learning (XAI) models-Reference-Cited by-同舟云学术

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Insight into glacio-hydrologicalprocesses using explainable machine-learning (XAI) models

Published:2024-05 Issue: Volume:634 Page:131047
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Hao Huiqing,Hao Yonghong,Li Zhongqin,Qi Cuiting,Wang Qi,Zhang Ming,Liu Yan,Liu Qi,Jim Yeh Tian-Chyi

Funder

Tianjin Normal University

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference58 articles.

1. A spatially enhanced data-driven multimodel to improve semiseasonal groundwater forecasts in the high plains aquifer, USA;Amaranto;Water Resour. Res.,2019

2. Utilizing precipitation and spring discharge data to identify groundwater quick flow belts in a karst spring catchment;An;J. Hydrometeorol.,2019

3. Glacier recession and water resources in Peru’s Cordillera Blanca;Baraer;J. Glaciol.,2017

4. Deep learning applied to glacier evolution modelling;Bolibar;Cryosphere,2020

5. Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning;Bolibar;Nat Commun.,2022

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Runoff Simulation of the Kaidu River Basin Based on the Gr4j-6 and Gr4j-6-Lstm Models;2024

2. Runoff Simulation of the Kaidu River Basin Based on the Gr4j-6 and Gr4j-6-Lstm Models;2024

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