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查元源

职称:副教授,硕士生导师

邮箱:zhayuan87@whu.edu.cn

个人网站:https://www.researchgate.net/profile/Yuanyuan-Zha

研究领域及招生方向:

研究方向:地下水、土壤水与农业水土环境;数值模拟、数据同化与水利人工智能

招生专业:水利水电工程/水利工程

招生类型:专业学位硕士、学术学位硕士

教育背景:

2008年9月~2014年 12月 武汉大学 水利水电工程 工学博士

2012年8月~2014年 10月 亚利桑那大学 水文与水资源系 联合培养

2004年9月~2008年 6月 武汉大学 农业水利工程 工学学士

工作经历:

2015年1月~2015年12月 亚利桑那大学 博士后

2016年1月~2020年2月 武汉大学 副研究员

2020年3月~至今 武汉大学 副教授

开设课程:

《水利遥感》(本科生)、《灌溉排水工程学》(本科生)《地下水动力学》(研究生)

代表性科研项目:

1.国家自然科学基金面上项目,土壤水跨尺度建模:以华北平原为例(2023/01-2026/12,主持)

2.国家自然科学基金面上项目,三维非均质农田水力层析扫描研究与应用(2018/01-2021/12,主持)

3. 国家外国专家项目,长江流域含水层水力层析及地表水-地下水交互关系研究(2023/01-2024/12,主持)

4. 国家自然科学基金青年项目,基于数值价值分析的根区土壤水分预测研究(2017/01-2019/12,主持)

5. 国家重点研发子课题,温度与污染物热质耦合三维场地模型开发及数值模拟研究(2020/01-2023/12,主持)

6. 国家重点研发子课题,灌区耦合系统协同演变与节水控盐减污的响应模拟(2021/11-2025/10,主持)

7. 广西重点研发项目,大空间尺度下南方灌区农业需水动态识别与智慧配水技术研究(2023/06-2026/05,主持)

8. 横向,临湘市黄盖湖卫星遥感监测项目(2022/06-2023/12,主持)

学术兼职:

2020至今 《Geofluids》副主编

2021至今 《节水灌溉》副主编

《Remote Sensing》等客座编辑

奖励与荣誉:

教育部高等学校科学技术进步奖一等奖(2013,排名第15)

湖北省优秀博士论文(2016)

武汉大学351人才“珞珈青年学者”(2017)

Journal of Hydrology杰出审稿人(2017)

中国水利学会“水利青年(英文)科技论文竞赛”一等奖(2018)

湖北省楚天学者计划楚天学子(2019)

武汉大学水利水电学院优秀本科班级导师(2019、2023)

水资源与水电工程科学国家重点实验室“腾飞计划”青年人才(2020)

节水灌溉优秀审稿专家(2021)

绽放杯5G应用征集大赛5G+AI智慧农业示范项目全国赛优秀奖(2021,排名2)

绽放杯5G应用征集大赛湖北区域赛二等奖(2021,排名2)

武汉大学本科优秀教学业绩奖(2022)

武汉大学水利水电学院优秀研究生德育导师(2022)

广西科学技术进步奖三等奖(2023,排名4)

农业节水科技奖二等奖(2023,排名3)

,农业节水科技奖三等奖(2023,排名5)

高等学校水利类专业教学成果奖一等奖(2023,排名5)

代表性学术成果:

以第一/通讯作者在《Water Resources Research》、《Hydrology and Earth Systems Science》、《Journal of Hydrology》、《Agricultural Water Management》、《Advances in Water Resources》、《European Journal of Agronomy》、《Precision Agriculture》、等国内外知名期刊发表论文近篇,部分代表性成果如下:

1.Nadeem, A. A.; Zha, Y.; Shi, L.; Zafar, Z.; Ali, S.; Zhang, Y.; Altaf, A. R.; Afzal, M.; Zubair, M. SAFER-ET Based Assessment of Irrigation Patterns and Impacts on Groundwater Use in the Central Punjab, Pakistan. Agricultural Water Management 2023, 289, 108545. https://doi.org/10.1016/j.agwat.2023.108545.

2.Li, P.; Zha, Y.; Zuo, B.; Zhang, Y. A Family of Soil Water Retention Models Based on Sigmoid Functions. Water Resources Research 2023, 59. https://doi.org/10.1029/2022WR033160.

3.Guo, S.; Zha, Y.; Zhong, H.; Wang, X.; Xu, D. Numerical Investigations of Influence on Thermal Conductive Heating in DNAPL-Impacted Soils by Heterogeneity. Journal of Contaminant Hydrology 2023, 104232. https://doi.org/10.1016/j.jconhyd.2023.104232.

4.Zhang, Y.; Zha, Y.; Jin, X.; Wang, Y.; Qiao, H. Changes in Vertical Phenotypic Traits of Rice (Oryza Sativa L.) Response to Water Stress. Frontiers in Plant Science 2022, 13, 942110. https://doi.org/10.3389/fpls.2022.942110.

5.Yu, D.; Zha, Y.; Sun, Z.; Li, J.; Jin, X.; Zhu, W.; Bian, J.; Ma, L.; Zeng, Y.; Su, Z. Deep Convolutional Neural Networks for Estimating Maize Above-Ground Biomass Using Multi-Source UAV Images: A Comparison with Traditional Machine Learning Algorithms. Precision Agriculture 2022. https://doi.org/10.1007/s11119-022-09932-0.

6.Yu, D.; Zha, Y.; Shi, L.; Ye, H.; Zhang, Y. Improving Sugarcane Growth Simulations by Integrating Multi-Source Observations into a Crop Model. European Journal of Agronomy 2022, 132, 126410. https://doi.org/10.1016/j.eja.2021.126410.

7.Zhu, L.; Shen, T.; Ma, R.; Fan, D.; Zhang, Y.; Zha, Y. Development of Cracks in Soil: An Improved Physical Model. Geoderma 2020, 366 (1), 114258. https://doi.org/10.1016/j.geoderma.2020.114258.

8.Zha, Y.; Shi, L.; Liang, Y.; Tso, C. H. M.; Zeng, W.; Zhang, Y. Analytical Sensitivity Map of Head Observations on Heterogeneous Hydraulic Parameters via the Sensitivity Equation Method. Journal of Hydrology 2020, 591, 125282. https://doi.org/10.1016/j.jhydrol.2020.125282.

9.Yu, D.; Zha, Y.; Shi, L.; Jin, X.; Hu, S.; Yang, Q. Improvement of Sugarcane Yield Estimation by Assimilating UAV-Derived Plant Height Observations. European Journal of Agronomy 2020, 121 (September), 126159. https://doi.org/10.1016/j.eja.2020.126159.

10.Li, P.; Zha, Y.; Tso, C. M.; Shi, L.; Yu, D.; Zhang, Y.; Zeng, W. Data Assimilation of Uncalibrated Soil Moisture Measurements from Frequency-Domain Reflectometry. Geoderma 2020, 374 (April), 114432. https://doi.org/10.1016/j.geoderma.2020.114432.

11.Li, P.; Zha, Y.; Shi, L.; Tso, C. H. M.; Zhang, Y.; Zeng, W. Comparison of the Use of a Physical-Based Model with Data Assimilation and Machine Learning Methods for Simulating Soil Water Dynamics. Journal of Hydrology 2020, 584, 124692. https://doi.org/10.1016/j.jhydrol.2020.124692.

12.Zha, Y.; Yeh, T. J.; Illman, W. A.; Mok, C.-M.; Tso, C. M.; Carrera, B. A.; Wang, Y. Exploitation of Pump-and-Treat Remediation Systems for Characterization of Hydraulic Heterogeneity. Journal of Hydrology 2019, 573, 324–340. https://doi.org/10.1016/j.jhydrol.2019.03.089.

13.Zha, Y.; Yang, J.; Zeng, J.; Tso, C.-H. M.; Zeng, W.; Shi, L. Review of Numerical Solution of Richardson-Richards Equation for Variably Saturated Flow in Soils. Wiley Interdisciplinary Reviews: Water 2019, e1364. https://doi.org/10.1002/wat2.1364.

14.Zeng, J.; Yang, J.; Zha, Y.; Shi, L. Capturing Soil-Water and Groundwater Interactions with an Iterative Feedback Coupling Scheme: New HYDRUS Package for MODFLOW. Hydrology and Earth System Sciences 2019, 23, 637–655. https://doi.org/10.5194/hess-2018-365.

15.Yu, D.; Yang, J.; Shi, L.; Zhang, Q.; Huang, K.; Fang, Y.; Zha, Y. On the Uncertainty of Initial Condition and Initialization Approaches in Variably Saturated Flow Modeling. Hydrology and Earth System Sciences 2019, 23, 2897–2914. https://doi.org/10.5194/hess-23-2897-2019.

16.Zha, Y.; Yeh, T.-C. J.; Illman, W. A.; Zeng, W.; Zhang, Y.; Sun, F.; Shi, L. A Reduced-Order Successive Linear Estimator for Geostatistical Inversion and Its Application in Hydraulic Tomography. Water Resources Research 2018, 54 (3), 1616–1632. https://doi.org/10.1002/2017WR021884.

17.Zeng, J.; Zha, Y.; Yang, J. Switching the Richards’ Equation for Modeling Soil Water Movement under Unfavorable Conditions. Journal of Hydrology 2018, 563, 942–949. https://doi.org/10.1016/j.jhydrol.2018.06.069.

18.Zha, Y.; Yeh, T. J.; Shi, L.; Huang, S.; Wang, W.; Wen, J. Quasi-Steady State Conditions in Heterogeneous Aquifers during Pumping Tests. Advances in Water Resources 2017, 0, 1–16. https://doi.org/10.1016/j.advwatres.2017.03.017.

19.Zha, Y.; Yeh, T. J.; Illman, W. A.; Onoe, H.; W, C. M.; Wen, J.; Huang, S.; Wang, W. Incorporating Geologic Information into Hydraulic Tomography : A General Framework Based on Geostatistical Approach. Water Resources Research 2017, 53, 2850–2876. https://doi.org/10.1002/2016WR019185.

20.Zha, Y.; Yang, J.; Yin, L.; Zhang, Y.; Zeng, W.; Shi, L. A Modified Picard Iteration Scheme for Overcoming Numerical Difficulties of Simulating Infiltration into Dry Soil. Journal of Hydrology 2017, 551, 56–69. https://doi.org/10.1016/j.jhydrol.2017.05.053.

21.Zha, Y.; Yeh, T.-C. J.; Illman, W. A.; Tanaka, T.; Bruines, P.; Onoe, H.; Saegusa, H. What Does Hydraulic Tomography Tell Us about Fractured Geological Media? A Field Study and Synthetic Experiments. Journal of Hydrology 2015, 531 (1), 17–30. https://doi.org/10.1016/j.jhydrol.2015.06.013.

22.Zha, Y.; Yeh, T.-C. J.; Mao, D.; Yang, J.; Lu, W. Usefulness of Flux Measurements during Hydraulic Tomographic Survey for Mapping Hydraulic Conductivity Distribution in a Fractured Medium. Advances in Water Resources 2014, 71, 162–176. https://doi.org/10.1016/j.advwatres.2014.06.008.

23.Zha, Y.; Shi, L.; Ye, M.; Yang, J. A Generalized Ross Method for Two- and Three-Dimensional Variably Saturated Flow. Advances in Water Resources 2013, 54 (4), 67–77. https://doi.org/10.1016/j.advwatres.2013.01.002.

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