杨静

发布者：杨静发布时间：2026-03-14浏览次数：104

 2026 年

  1. Heng Dai, Yijie Yang, Fangqiang Zhang, Alberto Guadagnini*, Jing Yang, Xiaochuang Bu, Lunche Wang, Songhu Yuan, Ming Ye.              Identification of Key Factors Driving Dissolved Oxygen in Riparian Aquifers Through Deep Learning-Assisted Global Sensitivity Analysis.              Water Resources Research, 2026, 62(2): e2025WR041884.              （中科院 2 区TOP）合作

 2025 年

  1. Jing Yang, Ming Ye*, Alberto Guadagnini, Heng Dai, Tian Jiao.              An efficient quasi-monte carlo method for concurrent estimation of first-order and total-effect process sensitivity indices.              Water Resources Research, 2025, 61(12): e2024WR039370.              （中科院 2 区 TOP）一作

  2. Tian Jiao, Ming Ye*, Jinxi Song*, Jing Yang, Maosheng Yin.              An Adaptive SPH Method (ADP-SPH) for Simulating Solute Transport in Heterogeneous Aquifers.              Water Resources Research, 2025, 61(12): e2025WR040299.              （中科院 2 区 TOP）合作

  3. Jing Yang, Heng Dai*, Honghua Liu, Ming Ye, Tian Jiao, Ze Liu, Tongju Xing, Jie Dong.              Advancing groundwater vulnerability assessment to nitrate contamination: a comprehensive evaluation of index-based, statistical, and machine learning approaches with sensitivity analysis.              Journal of Hydrology, 2025, 663: 134073.              （中科院 1 区）一作

  4. Mark S. Pleasants*, Michael N. Fienen, Hedeff I. Essaid, Joel D. Blomquist, Jing Yang, Ming Ye.              Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration.              Water Resources Research, 2025, 61(9): e2025WR040323.              （中科院 2 区 TOP）合作

  5. Huimeng Su, Yuntao Liu, Jing Yang*, Mengqi Liu, Heng Dai, Yangyang Wu, Ming Ye, Mingyue Zhao, Fawang Zhang.              Unraveling spatiotemporal variability of water geochemistry and sulfate sources in a multi-tributary river system.              Journal of Hydrology, 2025, 662: 134073.              （中科院 1 区）通讯

 2024 年

  1. 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: 132024.              （中科院 1 区）一作

  2. 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.              （中科院 1 区）合作

  3. Heng Dai, Yujiao Liu, Alberto Guadagnini*, Songhu Yuan, Jing Yang, Ming Ye.              Comparative assessment of two global sensitivity approaches considering model and parameter uncertainty.              Water Resources Research, 2024, 60(2): e2023WR036096.              （中科院 2 区 TOP）合作

 2023 年

  1. 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.              （中科院 3 区）通讯

 2022 年

  1. Jing Yang, Ming Ye*, Xingyuan Chen, Heng Dai, Anthony P. Walker.              Process interactions can change process ranking in a coupled complex system under process model and parametric uncertainty.              Water Resources Research, 2022, 58: e2021WR029812.              （中科院 2 区 TOP）一作

  2. Jing Yang, Ming Ye*.              A new multi-model absolute difference-based sensitivity (MMADS) method to screen non-influential process under process model and parametric uncertainty.              Journal of Hydrology, 2022, 608: 127609.              （中科院 1 区）一作

  3. Jing Yang, Honghua Liu, Zhonghua Tang, Luk Peeters, Ming Ye*.              Visualization of aqueous geochemistry data using Python and WQChartPy.              Groundwater, 2022, 60(4): 555–564.              （中科院 3 区，WILEY 高被引）一作

  4. Tian Jiao, Ming Ye*, Menggui Jin*, Jing Yang.              An interactively corrected smoothed particle hydrodynamics (IC-SPH) for simulating solute transport in heterogeneous porous media.              Water Resources Research, 2022, 58(6): 2021WR031017.              （中科院 2 区 TOP）合作

  5. Tian Jiao, Ming Ye*, Menggui Jin*, Jing Yang.              Decoupled finite particle method with normalized kernel (DFPM-NK): A computationally efficient method for simulating solute transport in heterogeneous porous media.              Water Resources Research, 2022, 58(8): 2022WR032308.              （中科院 2 区 TOP）合作

 2021 年

  1. Honghua Liu, Jing Yang*, Ming Ye*, 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.              （中科院 1 区）通讯

  2. Honghua Liu, Jing Yang*, Ming Ye*, Zhonghua Tang, Jie Dong, Tongju Xing.              Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data.              Journal of Hydrology, 2021, 597: 126146.              （中科院 1 区）通讯

 2020 年

  1. 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.              （中科院 1 区）一作

 2018 年

  1. 杨静，肖天云，李海波，王全荣*。              江汉平原地下水中硝酸盐的分布及影响因素。              中国环境科学，2018，38(2)：710–718。              （中文 EI）一作

 2017 年

  1. Jing Yang, Zhonghua Tang*, Tian Jiao, Malik M. Akhtar.              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(12): 426.              （中科院 3 区）一作

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