Jing Yang

Jing Yang

Associate Professor, Northwest A&F University

Publications

Development of an integrated global sensitivity analysis strategy for evaluating process sensitivities across single- and multi-models

Published in Journal of Hydrology, 2024

Recommended citation: Jing Yang, Yujiao Liu, Heng Dai*, Songhu Yuan, Tian Jiao, Zhang Wen, Ming Ye. "Development of an integrated global sensitivity analysis strategy for evaluating process sensitivities across single- and multi-models." Journal of Hydrology. 2024, 643: 132014. https://www.sciencedirect.com/science/article/abs/pii/S0022169424014100 https://www.sciencedirect.com/science/article/abs/pii/S0022169424014100

Global sensitivity analysis with deep learning-based surrogate models for unraveling key parameters and processes governing redox zonation in riparian zone

Published in Journal of Hydrology, 2024

Recommended citation: Zhejiong Yu, Heng Dai*, Jing Yang, Yonghui Zhu, Songhu Yuan. "Global sensitivity analysis with deep learning-based surrogate models for unraveling key parameters and processes governing redox zonation in riparian zone." Journal of Hydrology. 2024, 638: 131442. https://www.sciencedirect.com/science/article/pii/S0022169424008370 https://www.sciencedirect.com/science/article/pii/S0022169424008370

Comparative assessment of two global sensitivity approaches considering model and parameter uncertainty

Published in Water Resources Research, 2024

Recommended citation: Heng Dai, Yujiao Liu, Alberto Guadagnini*, Jing Yang, Ming Ye. "Comparative assessment of two global sensitivity approaches considering model and parameter uncertainty." Water Resources Research. 2024, 60(2): e2023WR036096. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023WR036096 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023WR036096

Using clustering, geochemical modeling, and a decision tree for the hydrogeochemical characterization of groundwater in an in situ leaching uranium deposit in Bayan-Uul, northern China

Published in Water, 2023

Recommended citation: Haibo Li, Mengqi Liu, Tian Jiao, Dongjin Xiang*, Xiaofei Yan*, Zhonghua Tang, Jing Yang. "Using clustering, geochemical modeling, and a decision tree for the hydrogeochemical characterization of groundwater in an in situ leaching uranium deposit in Bayan-Uul, northern China." Water. 2023, 15(24): 4234. https://www.mdpi.com/2073-4441/15/24/4234 https://www.mdpi.com/2073-4441/15/24/4234

Using self-organizing map and multivariate statistical methods for groundwater quality assessment in the urban area of Linyi city, China

Published in Water, 2023

Recommended citation: Shiqiang LIu, Haibo Li, Jing Yang*, Mingqiang Ma, Jiale Shang, Zhonghua Tang, Geng Liu. "Using self-organizing map and multivariate statistical methods for groundwater quality assessment in the urban area of Linyi city, China." Water. 2023, 15(19): 3463. https://www.mdpi.com/2073-4441/15/19/3463 https://www.mdpi.com/2073-4441/15/19/3463

Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data

Published in Journal of Hydrology, 2021

Recommended citation: Honghua Liu, Jing Yang*, Ming Ye*, Scott C. James, Zhonghua Tang, Jie Dong, Tongju Xing. "Using one-way and co-clustering methods to reveal spatio-temporal patterns and controlling factors of groundwater geochemistry." Journal of Hydrology. 2021, 603: 127085. https://doi.org/10.1016/j.jhydrol.2021.126146

Using cluster analysis for understanding spatial and temporal patterns and controlling factors of groundwater geochemistry in a regional aquifer

Published in Journal of Hydrology, 2020

Recommended citation: Jing Yang, Ming Ye*, Zhonghua Tang*, Tian Jiao, Xiaoyu Song, Yongzhen Pei, Honghua Liu. "Using cluster analysis for understanding spatial and temporal patterns and controlling factors of groundwater geochemistry in a regional aquifer." Journal of Hydrology. 2020, 583: 124594. https://doi.org/10.1016/j.jhydrol.2020.124594

Combining AHP and genetic algorithms approaches to modify DRASTIC model to assess groundwater vulnerability: a case study from Jianghan Plain, China

Published in Environmental Earth Sciences, 2017

Recommended citation: Jing Yang, Zhonghua Tang*, Tian Jiao, Akhtar Malik Muhammad. "Combining AHP and genetic algorithms approaches to modify DRASTIC model to assess groundwater vulnerability: a case study from Jianghan Plain, China." Environmental Earth Sciences. 2017, 76: 426. https://doi.org/10.1007/s12665-017-6759-6