Shaoxing Mo
smo@nju.edu.cn
Chinese, English
Jiangsu
School of Earth Sciences and Engineering
Earth sciences
Uncertainty quantification in hydrological models
Deep learning applications in hydrology
Groundwater contamination and remediation
  • Uncertainty quantification of CO2 plume migration in highly channelized aquifers using probabilistic convolutional neural networks, Feng, L., Mo, S.*, Sun, A. Y., Wu, J., Shi, X., 2023
  • Water storage changes (2003–2020) in the Ordos Basin, China, explained by GRACE data and interpretable deep learning, Hu, Z., Tang, S., Mo, S.*, Shi, X.*, Yin, X., Sun, Y., Liu, X., Duan, L., Miao, P., Liu, T., Wu, J., 2023
Uncertainty Quantification Hydrological Models Probabilistic Models Neural Networks Deep Learning Water Resources Aquifers Channelized Flows Contaminant Transport Remediation Technologies

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