长期从事极端水文气象非平稳性及其区域水文和大气过程变化机理研究。在气候变化和人类活动影响下暴雨、洪水和干旱演变机理方面取得相关研究成果，其主要发表于《Nature Water》《Nature Communications》《Global Change Biology》《Water Resources Research》等国际水文气象期刊。

 

教育经历

2012/09-2016/09  加拿大阿尔伯塔大学 土木与环境工程系   水资源工程    PhD

2009/09-2016/12  武汉大学           水利水电学院     水利水电工程       博士

2005/09-2009/07  西北农林科技大学   水利与建筑工程学院   水文与水资源工程  本科

 

工作经历

2024/04至今           3499cc拉斯维加斯          3499cc拉斯维加斯       教授

2018/08-2024/04    3499cc拉斯维加斯          3499cc拉斯维加斯       副教授

2017/12-2018/08    3499cc拉斯维加斯          地理科学与规划学院       副教授

2016/09-2017/11  加拿大阿尔伯塔大学 土木与环境工程系         博士后

 

诚挚欢迎各位硕士生、博士生和博士后加入水资源水生态团队，从事水文气象与水资源相关研究。

 

研究兴趣

气候变化与水文水资源，气候资源，极端天气气候，气候变化影响与适应，农业水土环境

Research Interest

(1)   水文气候变率和气候变化：分析区域水文气候的非平稳特征以及与大气环流模式、大范围气候变率和区域/全球气候变化的关系； 开发用于非平稳水文气候频率分析的非平稳概率方法； 揭示导致区域极端降水的水分输送模式及其变异性； 评估人类和气候变化影响对极端水文气候变化的相对贡献； 归因极端气候变化于热力学和动态大气条件变化； 预估气候变化对能源消耗和生产、生态系统、人类社会、农业生产、局部极端风暴以及区域水资源供应、洪水和干旱的影响。

 Hydroclimate variability and climate change: My research is to discover non-stationary characteristics of regional hydroclimate and relations to atmospheric circulation patterns, large-scale climate variability, and regional/global climate change; to develop non-stationary probability approaches for non-stationary hydro-climatic frequency analysis; to identify moisture transportation patterns and their variabilities that are responsible for regional extreme precipitation; to evaluate relative contributions of human and climate change impacts to changes in hydroclimatic extremes; to attribute changes in climate extremes to changes in thermodynamic and dynamic atmospheric conditions; and to analyze projected climate change impacts on energy consumption and production, ecosystem, human society, agriculture production, local extreme storms, and regional water availability, floods, and droughts.

(2)可持续农业生态系统：研究影响农业系统可持续性的过程，包括水资源利用效率、作物生产力、植物与土壤的相互作用、农田面源污染物的去向以及农业潜力 系统作为温室气体（GHG）的源和汇；通过实验室和田间实验、遥感测量以及生态水文和农业水文模型模拟，研究不同农业系统中水氮循环以及水氮利用效率过程演变机制，研发在保持作物产量的同时，最大限度地减少面源污染物排放、最大限度地提高资源利用效率的农业工程技术。
 Sustainable agricultural ecosystems: My research is to discover the processes that affect agricultural system sustainability, including water use efficiency, crop productivity, plant-soil interactions, fates of non-point sources of pollutants in agricultural land, and the potential of agricultural systems to act as source and sink for greenhouse gases (GHG). The major contribution of my research is to develop a mechanistic understanding of water and nitrogen cycling and water and nitrogen use efficiency in diverse agricultural systems by lab field experiments, remote sensing measurements and eco-hydrological and agro-hydrological model simulations and to identify alternative management practices that minimize non-point pollutant emissions and maximize resources use efficiency while maintaining crop yields. 

论文著作

REFEREED PUBLICATIONS (* corresponding author)

  1. Simin Deng, Xuezhi Tan* & Bingjun Li, 2024. Impacts of changes in climate extremes on maize yields over Mainland China. Food Security, https://doi.org/10.1007/s12571-024-01501-9.

  2. Yi Wu, Xuezhi Tan*, Haoyuan Mo, Xudong Li, Yin Zhang, Fang Yang, Lixiang Song, Yong He, Xiaohong Chen, 2024. A Dynamic Game Model for Emergency Resource Managers and Compound Disasters Induced by Heavy Rainstorms. Water 2024, 16(20), 2959; https://doi.org/10.3390/w16202959

  3. Tan, X., et al., 2023. Increasing global precipitation whiplash due to anthropogenic greenhouse gas emissions. Nature Communications, 14(1): p. 2796.

  4. Huang, Z. #, Tan, X.* #, et al., 2023. Thermodynamically enhanced precipitation extremes due to counterbalancing influences of anthropogenic greenhouse gases and aerosols. Nature Water, 1, 614–625. https://www.nature.com/articles/s44221-023-00107-3 
  5. X Wu, X Tan*, X Chen, Z Huang, 2024. Synoptic circulation forcing of large‐scale extreme precipitation events over southeastern China, Journal of Geophysical Research: Atmospheres 129 (17), e2024JD041396
  6. Huang, Z., X. Tan*, and B. Liu*, 2024: Relative Contributions of Large‐Scale Atmospheric Circulation Dynamics and Anthropogenic Warming to the Unprecedented 2022 Yangtze River Basin Heatwave. Journal of Geophysical Research: Atmospheres, 129, e2023JD039330.
  7. Deng, S., X. Tan*, X. Tan, X. Wu, Z. Huang, Y. Liu, and B. Liu, 2024: On the development and recovery of soil moisture deficit drought events. Journal of Hydrology, 632, 130920.
  8. Tan X, Liu B, Tan X*, Huang Z, Fu J, 2024. Projected climate change impacts on the availability of blue and green water in a watershed of intensive human water usage, Journal of Hydrology: Regional Studies 53, 101827
  9. Xuejin Tan, Xuezhi Tan*, Bingjun Liu, Zeqin Huang, 2023. Contribution of changes in vegetation composition and climate variability on streamflow across the global watersheds. CATENA, 232: p. 107394.
  10. Tan, X.*, et al., Identification of the key driving factors of flash flood based on different feature selection techniques coupled with random forest method. Journal of Hydrology: Regional Studies, 2024. 51: p. 101624.
  11. Huang, Z., X. Tan, X. Wu, X. Tan*, J. Fu, and B. Liu, 2023: Long-Term Changes, Synoptic Behaviors, and Future Projections of Large-Scale Anomalous Precipitation Events in China Detected by a Deep Learning Autoencoder. Journal of Climate, 36, 4133-4149.
  12. Cai, X., Li, L., Fisher, J. B., Zeng, Z., Zhou, S., Tan, X.*, et al, 2023. The responses of ecosystem water use efficiency to CO2, nitrogen deposition, and climatic drivers across China. Journal of Hydrology, 622, 129696.
  13. Tan X*, Q Mai, G Chen, B Liu, Z Wang, C Lai, X Chen, 2023, Intensity-duration-frequency curves in the Guangdong-Hong Kong-Macao Greater Bay Area inferred from the Bayesian hierarchical model. Journal of Hydrology: Regional Studies 46, 101327
  14. F Yang, X Wang, X Zhou, Q Wang, X Tan*, 2023. Effects of Urbanization on Changes in Precipitation Extremes in Guangdong-Hong Kong-Macao Greater Bay Area, China, Water 15 (19), 3438
  15. Tan X*, Liu Y, Wu X, Liu B., Chen X, 2022. Examinations on global changes in the total and spatial extent of tropical cyclone precipitation relating to rapid intensification. Science of The Total Environment, 158555
  16. S Deng, X Tan*, B Liu, F Yang, T Yan. 2022. A reversal in global occurrences of flash drought around 2000 identified by rapid changes in the standardized evaporative stress ratio. Science of The Total Environment, 157427.
  17. Tan, X.*, X. Wu, Z. Huang, S. Deng, M. Hu*, and T. Yew Gan, 2022: Detection and attribution of the decreasing precipitation and extreme drought 2020 in southeastern China. Journal of Hydrology, 610, 127996.
  18. X Tan,B Liu, X Tan*,X Chen, 2022. Long-Term Water Imbalances of Watersheds Resulting From Biases in Hydroclimatic Data Sets for Water Budget Analyses, Water Resources Research, 58(3):e2021WR031209. doi: 10.1029/2021WR031209.
  19. X Wu, X Tan*, B Liu, H Chen, X Chen, 2022. Fronts and cyclones associated with changes in the total and extreme precipitation over China, Journal of Climate, doi: 10.1175/JCLI-D-21-0467.1
  20. Tan X.*, Wu X., Liu B., 2021. Global changes in the spatial extents of precipitation extremes. Environmental Research Letters, doi: 10.1088/1748-9326/abf462.
  21. Liu B., Chen S., Tan X.*, 2021. Large‐scale synoptic atmospheric moisture circulation patterns associated with variability of daily precipitation over East China. International Journal of Climatology. doi: 10.1002/joc.7028.
  22. Tan, X., B. Liu, X. Tan*, 2020: Global changes in baseflow under the impacts of changing climate and vegetation. Water Resources Research, e2020WR027349. doi: 1029/2020WR027349.  
  23. Tan, X., Y. Wu, B. Liu, and S. Chen, 2020: Inconsistent changes in global precipitation seasonality in seven precipitation datasets. Climate Dynamics, 54, 3091-3108. 
  24. Liu, B., X. Tan, T. Y. Gan, X. Chen, K. Lin, M. Lu, and Z. Liu, 2020: Global atmospheric moisture transport associated with precipitation extremes: Mechanisms and climate change impacts. Wiley Interdisciplinary Reviews: Water, 7, e1412.  
  25. Chen, S., B. Liu, X. Tan*, and Y. Wu, 2020: Inter-comparison of spatiotemporal features of precipitation extremes within six daily precipitation products. Climate Dynamics, 54, 1057-1076. 
  26. Tan X., Gan T. Y.,  Horton D. E., 2018. Projected timing of perceivable changes in climate extremes for terrestrial and marine ecosystems, Global Change Biology, 24, 4696-4708. doi: 10.1111/gcb.14329. (IF: 8.997, 中科院一区论文，top期刊) 
  27. Tan X., Gan T. Y., Chen S., Horton D. E., Chen X., Liu B., Lin K., 2019. Trends in persistent seasonal-scale atmospheric circulation patterns responsible for seasonal precipitation totals and occurrences of precipitation extremes over Canada, Journal of Climate, 32, 7105-7126. doi: 10.1175/JCLI-D-18-0408.1 
  28. Tan X.,  Gan T. Y.,  Chen Y. D., 2019. Synoptic moisture pathways associated with mean and extreme precipitation over Canada for winter and spring, Climate Dynamics, 53, 2663–2681. doi: 10.1007/s00382-019-04649-9.   
  29. Tan, X., Chen S., Gan T. Y., Liu B., Chen X., 2019: Dynamic and thermodynamic changes conducive to the increased occurrence of extreme spring fire weather over western Canada under possible anthropogenic climate change. Agricultural Forest Meteorology, 265, 269-279, doi: 10.1016/j.agrformet.2018.11.026.
  30. Tan X.,  Gan T. Y.,  Chen S., Liu B., 2018. Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections, Climate Dynamics, 52(3–4), 2105–2124. doi: 10.1007/s00382-018-4241-0. 
  31. Tan X.,  Gan T. Y.,  Chen Y. D., 2019. Synoptic moisture pathways associated with mean and extreme precipitation over Canada for summer and fall, Climate Dynamics, 52(5-6), 2959-2979. doi: 10.1007/s00382-018-4300-6. 
  32. Tan X., Chen S., Gan T. Y., 2018. Multi-model extreme event attribution of the weather conducive to the 2016 Fort McMurray wildfire, Agricultural and Forest Meteorology, 260–261, 109–117, doi: 10.1016/j.agrformet.2018.06.010.
  33. Tan X., ·Shao D.,·Gu W., 2018. Effects of temperature and soil moisture on gross nitrification and denitrification rates of a Chinese lowland paddy field soil, Paddy and Water Environment, 16(4), 687-698, doi: 10.1007/s10333-018-0660-0. 
  34. Tan X., Shao D., Gu W., 2018. Improving water reuse in paddy field districts with cascaded on-farm ponds using hydrologic model simulations, Water Resources Management, 32:1849-1865, doi: 10.1007/s11269-018-1907-7. 
  35. Tan X., Gan T. Y., Shao D., 2017. Effects of persistence and large-scale climate anomalies on trends and change points in extreme precipitation of Canada, Journal of Hydrology, 550, 453–465, doi: 10.1016/j.jhydrol.2017.05.028.
  36. Tan X., Gan T. Y., 2018. Moisture sources and pathways associated with the spatially varying seasonal extreme precipitation over Canada, Climate Dynamics, 50:629-640, doi: 10.1007/s00382-017-3630-0. 
  37. Tan X., Gan T. Y., 2017. Multifractal analysis of Canadian precipitation and streamflow, International Journal of Climatology, 37, 1221-1236, doi: 10.1002/joc.5078. 
  38. Tan X., Gan T. Y., 2017. Non-stationary analysis of the frequency and intensity of heavy precipitation over Canada and their relations to large-scale climate patterns, Climate Dynamics, 48, 2983–3001, doi: 10.1007/s00382-016-3246-9. 
  39. Tan X., Shao D., 2017. Precipitation trends and teleconnections identified using quantile regressions over Xinjiang, China, International Journal of Climatology, 37(3), 1510-1525, doi: 10.1002/joc.4794.
  40. Tan X., Gan T. Y., 2016. Wavelet analysis of precipitation extremes over Canadian ecoregions and teleconnections to large-scale climate anomalies, Journal of Geophysical Research: Atmospheres, 121 (24), 14469–14486, doi: 10.1002/2016JD025533. 
  41. Tan X., Gan T. Y., 2015. Contribution of human and climate change impacts to changes in streamflow of Canada, Scientific Reports, 5:17767, doi: 10.1038/srep17767. 
  42. Tan X., Gan T. Y., 2015. Nonstationary analysis of annual maximum streamflow of Canada. Journal of Climate, 28, 1788–1805. 
  43. Tan X., Shao D., Gu W., Liu H., 2015. Field analysis of water and nitrogen fate in lowland paddy fields under different water managements using HYDRUS-1D. Agricultural Water Management, 150, 67-80. 
  44. Tan X., Shao D., Liu H., 2014. Simulating soil water regime in lowland paddy fields under different water managements using HYDRUS-1D. Agricultural Water Management, 132, 69-78.
  45. Shao D., Tan X.*, Liu H., Yang H., Chun X., Yang F., 2013. Performance analysis of on-farm irrigation tanks on agricultural drainage water reuse and treatment. Resources, Conservation and Recycling, 75, 1-13.
  46. Tan X., Shao D., Liu H., Yang F., et al., 2013. Effects of alternate wetting and drying irrigation on water losses and nitrogen leaching in paddy fields. Paddy and Water Environment, 11, 381-395. 
  47. 邵东国; 谭学志; 陈述; 李浩鑫; 胡能杰; 灌区水转化机制与用水效率评估方法, 科学出版社, 2020.
  48. 麦杞莹, 谭学志, 吴欣欣, 刘丙军, 杨芳, 张明珠, 温得平, 马海青, 2024. 多个高时空分辨率降水产品在珠江三角洲地区的多尺度精度评估, 3499cc拉斯维加斯学报(自然科学版)(中英文), 3, 21-31
  49. 刘洋, 陈菡, 谭学志*, 2020. 基于Budyko理论的韩江流域径流变化敏感性分析及归因识别. 亚热带资源与环境学报, 15(3): 9-16.
  50. 谭学志, 邵东国, 刘欢欢, 孙春敏, 2011. 节水灌溉控制排水条件下稻田水氮平衡试验与模拟. 农业工程学报, 2011，27(11)：193－198.  Tan X., Shao D., Liu H., 2011. Modeling and experiment of water and nitrogen balance in paddy fields under water saving irrigation and controlled drainage. Transactions of the CSAE, 27(11), 193-198.
  51. 谭学志, 粟晓玲, 邵东国, 2011. 基于SPI的陕西关中地区气象干旱时空特征分析. 干旱地区农业研究, 29(2), 224-229. Tan X., Su X., Shao D., 2011. Analysis of spatial and temporal characteristics of meteorological drought in Guanzhong Region of Shaanxi Province. Agricultural Research in the Arid Areas, 29(2), 224-229.      

Coauthor papers 

  1. Dai, C., Zhang, X., Tan, X., Hu, M. and Sun, W., 2024. A stochastic simulation-based chance-constrained programming model for optimizing watershed best management practices for nonpoint source pollution control under uncertainty. Journal of Hydrology, 632: 130882.
  2. H Shi, B Sivakumar, S Liu, X Tan, N Najibi, 2022. Extreme Hydro-Climate Events: Past, Present, and Future. Atmosphere 13 (5), 843.
  3. Yang Y., Gan TY., Tan X., 2021. Recent changing characteristics of dry and wet spells in Canada. Climatic Change, 165:42, doi: 10.1007/s10584-021-03046-8.
  4. Tariku T.B., Gan KE, Tan X, Gan TY, Shi H, Tilmant A, 2021. Global warming impact to River Basin of Blue Nile and the optimum operation of its multi-reservoir system for hydropower production and irrigation. Science of The Total Environment, 767, 144863
  5. Lin Q., Chen J., Li W., Huang K., Tan X., Chen H., 2021. Impacts of land use change on thermodynamic and dynamic changes of precipitation for the Yangtze River Basin, China. International Journal of Climatology. 
  6. Liu B., Chen S., Tan X., Chen X., 2021. Response of precipitation to extensive urbanization over the Pearl River Delta metropolitan region. Environmental Earth Sciences, 80, 9  
  7. Liu B., Liang M., Huang Z., Tan X., 2021. Duration–severity–area characteristics of drought events in eastern China determined using a three‐dimensional clustering method, International Journal of Climatology, 41,   
  8. Lan, T., K. Lin, C.-Y. Xu, X. Tan, and X. Chen, 2020: Dynamics of hydrological-model parameters: mechanisms, problems and solutions. Hydrology and Earth System Sciences, 24, 1347-1366. 
  9. Yang, Y., T. Y. Gan, and X. Tan, 2020: Spatiotemporal changes of drought characteristics and their dynamic drivers in Canada. Atmospheric Research, 232, 104695. 
  10. Wu, J., X. Tan, X. Chen, and K. Lin, 2020: Dynamic changes of the dryness/wetness characteristics in the largest river basin of South China and their possible climate driving factors. Atmospheric Research, 232, 104685. 
  11. Chen, S., B. Liu, X. Tan, and Z. Huang, 2019: Characteristics and circulation background of extreme precipitation over East China. Natural Hazards, 99, 537-552.
  12. Chen S., Shao D., Tan X., Gu W., Lei C., 2018. Nonstationary stochastic simulation-based water allocation method for regional water management, Journal of Water Resources Planning and Management, 145(3), doi: 10.1061/(ASCE)WR.1943-5452.0001042. 
  13. Chen S., Gan T. Y,. Tan X., Shao D., Zhu J., 2019. Assessment of CFSR, ERA-Interim, JRA-55, MERRA-2, NCEP-2 reanalysis data for drought analysis over China, Climate Dynamics, doi: 10.1007/s00382-018-04611-1. 
  14. Shao D., Chen S., Tan X., Gu W., 2018. Drought characteristics over China during 1980–2015, International Journal of Climatology, 38(9), 3532-3545, doi: 10.1002/joc.5515. 
  15. Yang Y., Gan T.Y., Tan X., 2019. Spatiotemporal changes in precipitation extremes over Canada and their teleconnections to large-scale climate patterns, Journal of Hydrometeorology, 20(2), 275–296. doi: 10.1175/JHM-D-18-0004.1.
  16. Chen S., Xu J., Li Q, Tan X., Nong X., 2019. A copula-based interval-bistochastic programming method for regional water allocation under uncertainty Agricultural Water Management 217, 154-164.
  17. Shao, D., Nong, X.*; Tan, X., Chen, S., Xu, B., Hu, N., 2018. Daily Water Quality Forecast of the South-To-North Water Diversion Project of China Based on the Cuckoo Search- Back Propagation Neural Network, Water, 2018, 10(10): 1471. doi: 10.3390/w10101471.  
  18. Li H., Shao D., Xu B., Chen S., Gu W., Tan X., 2016. Failure analysis of a new irrigation water allocation mode based on copula approaches in the Zhanghe Irrigation District, China, Water, 8(6), 251; doi:10.3390/w8060251. 
  19. Xu B., Shao D., Tan X., Yang X., Gu W., Li H., 2017. Evaluation of soil water percolation under different irrigation practices, antecedent moisture and groundwater depths in paddy fields, Agricultural Water Management, 192, 149-158.
  20. Chen S., Shao D., Tan X., Gu W., Lei C., 2017. An interval multistage classified model for regional inter- and intra-seasonal water management under uncertain and nonstationary condition, Agricultural Water Management, 191, 98-112.
  21. Gu W., Shao D., Tan X., Chen S., Wu Z., 2017. Simulation and optimization of multi-reservoir operation in inter-basin water transfer system, Water Resources Management, 33(11), 3401-3412, doi: 10.1007/s11269-017-1675-9.
  22. Yang F., Shao D., Xiao C., Tan X., 2012. Assessment of urban water security based on catastrophe theory. Water Science & Technology 66 (3), 487-493.
  23. Shao D., Yang F., Xiao C., Tan X., 2012. Evaluation of water security: an integrated approach applied in Wuhan urban agglomeration, China. Water Science & Technology 66 (1), 79-87. 
  24. 曾珂, 谭学志, 梁廖逢, 刘茹, 刘祖发, 高艺桔, 2020. 基于Copula函数的气候变化下洪水峰量联合分析. 长江科学院院报, 37(12) : 40－46.
  25. 汪奎, 邵东国, 顾文权, 岑栋浩, 谭学志, 杨丰顺, 2011. 中国用水量与经济增长的脱钩分析. 灌溉排水学报3, 34-88.
  26. 杨丰顺, 邵东国, 顾文权, 肖淳, 谭学志, 杨海东, 2012. 基于Copula函数的区域需水量随机模拟. 农业工程学报, 28(18), 193-198. Yang F., Shao D., Xiao C., Tan X., Yang H., 2012. Stochastic simulation of regional water requirement based on Copula function. Transactions of the CSAE, 28(18), 193-198.

 

科研项目

  1.  国家自然科学基金委员会, 面上项目，珠江流域旱涝急转发生和演变机理及未来风险预估
  2. 广东省基础与应用基础研究基金委员会，杰出青年项目，气候变化下区域旱涝急转发生和演变机理
  3.  广东省基础与应用基础研究基金委员会，海上风电联合基金项目，广东近海可利用风能时空演变机理及预估技术研究
  4. 广东省教育厅，广东省普通高校特色创新类项目，全球变暖和城市化下华南洪涝旱复合灾害演变机理与风险调控研究
  5.  国家重点研发计划项目“粤港澳大湾区衍生复合灾害评估与应急避险关键技术”的子课题“防汛抗洪-抗咸供水复合调控与复合灾害应急避险多目标优化调配”
  6.  国家自然科学基金委员会, 面上项目，气候变暖和城市化下珠三角不同历时暴雨时空演变机理研究
  7.  国家自然科学基金委员会, 青年科学基金项目,华南持续性暴雨时空演变的水汽输送驱动机制研究
  8.  广东省科学技术厅, 广东省自然科学基金面上项目, 干湿交替稻田水氮迁移转化与高效利用机理
  9.  广州市科技创新委, 广州市科技计划项目, 城市化和气候变暖下广州市暴雨IDF曲线变化预估
  10.  水资源与水电工程科学国家重点实验室开放基金, Transport and transformation mechanisms and effective utilization of water and nitrogen in paddy fields
  11.  加拿大自然科学与工程研究理事会（NSERC）, Regional Climate Modeling of Intensive Storms of Central Alberta under Possible Climate Change Impact
  12.  加拿大自然科学与工程研究理事会（NSERC）, Canadian FloodNet Project 1-2 Examination of spatial and temporal variation of extreme events