基本介绍

王大刚，教授，博士生导师，中山大学 “百人计划”引进人才。1997年于大连理工大学获水利水工程建筑学士学位；2002年于大连理工大学获水文学与水资源硕士学位，师从程春田教授；2007年于University of Connecticut获环境工程博士学位，师从Guilling Wang教授；2007-2008年于普林斯顿大学从事博士后研究，师从美国工程院院士Eric Wood教授；2011年起加入中山大学，历任副教授、教授。国际水文科学协会中国委员会（CNC-IAHS）陆气关系分委员会副主席，美国地球物理联合会、美国气象学会和中国水资源专业委员会等专业协会会员，主持国家基金委面上项目3项，作为子课题负责人参与国家重点研发计划2项，主持多个地方咨询项目，为多个国际期刊的审稿人，2017年以共同通讯作者身份在国际顶级期刊Nature Climate Change (IF=20.893)发表关于极端降水的研究长文，2019年在国际顶级期刊Science Advances (IF=13.116)发表关于城市热岛的研究长文，在Climate Dynamics，Hydrology and Earth System Sciences, Journal of Hydrometeorology，International Journal of Climatology, Journal of Hydrology，Hydrological Processes 等国际期刊上发表多篇文章。讲授课程《计算方法与计算机应用》在学生评教中两次排名中山大学第一，2014-2018年连续5年获得中山大学地理科学与规划学院“我心目中的良师”称号。指导的博士生王大洋和杜懿、硕士生林泳恩获得校级优秀毕业生、国家奖学金，2023年指导的本科生张晓琳获得校级优秀毕业论文。

长期招收硕士、博士、博士后和专职科研人员，欢迎加入！

 

研究方向

极端气候变化，陆面过程模拟，城市化的气候效应，水文气象预测，大数据及深度学习

 

学历背景

2002－2007，康涅狄格大学，土木与环境工程系，博士

1999－2002，大连理工大学，土木工程系，硕士

1993－1997，大连理工大学，土木工程系，学士

 

工作经历

2018－现在，中山大学，地理科学与规划学院水资源与环境系，教授

2011－2018，中山大学，地理科学与规划学院水资源与环境系，副教授

2010－2011，美国国家水文遥感中心（National Operational Hydrologic Remote Sensing Center），科学家

2008－2009，美国Dewberry公司，水资源工程师

2007－2008，美国普林斯顿大学，土木与环境工程系，博士后

1997－1999，小浪底咨询有限公司，工程师

1997－1997，中水北方勘测设计研究有限责任公司，助理工程师

 

社会任职

国际水文科学协会中国委员会（CNC-IAHS）陆气关系分委员会副主席

国际水文科学协会中国委员会委员

广东省城市化与地理环境空间模拟重点实验室副主任

 

讲授课程

数学建模算法与应用

水文气象学

高等自然地理学

地球系统模拟

 

论著

  1.  Hassan Raza, Dagang Wang and Jonghun Kam*, 2025: More record events in streamflow over Pakistan revealed by observation-constrained projections, Environmental Research Letters, DOI 10.1088/1748-9326/adf130
    Liren Wang, Jinxin Zhu*, Dagang Wang, 2025: Comparative analysis of high-resolution CMIP6 GCM and CMIP5 RCM: unveiling biases and advancements in simulating compound extreme events in China, Climate Dynamics, 63(91), https://doi.org/10.1007/s00382-024-07571-x
  2. Jian Li, Shuo Wang*, Jinxin Zhu, Dagang Wang & Tongtiegang Zhao, 2025: Accelerated shifts from heatwaves to heavy rainfall in a changing climate, npj | climate and atmospheric science, 8 (214)
  3. Zhi Zhang, Dagang Wang*, Yiwen Mei, Jinxin Zhu and Xusha Xiao, 2025: Developing an explainable deep learning module based on the LSTM framework for flood prediction. Frontier in Water 7:1562842. doi: 10.3389/frwa.2025.1562842
  4. Runting Chen, Dagang Wang*, Yiwen Mei, Yongen Lin, Zequn Lin, Zhi Zhang, Shengjie Zhuang, Jinxin Zhu, Jonghun Kam, Yiping Wu, Guoping Tang, 2025: A Knowledge-guided LSTM reservoir outflow model and its application to streamflow simulation in reservoir-regulated basins. Journal of Hydrology. 658, 133164.
  5. Zequn Lin, Dagang Wang*, Yi Du, Yue Meng, 2024: Spatiotemporal Characteristics of Precipitation Concentration and Their Linkage to Temperature Over China. International Journal of Climatology, 45 (1), e8698
  6. Shanshan Sun, Lingcheng Li*, Zong-Liang Yang, Guiling Wang, Nate G. McDowell, Ashley M. Matheny, Jian Wu, Shiqin Xu, Hui Zheng, Miao Yu, Dagang Wang, 2024: Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration. Agricultural and Forest Meteorology 359 (2024), 110256.
  7. Yiwen Mei, Dagang Wang*, Jinxin Zhu, Guoping Tang, Chenkai Cai, Xinyi Shen, and Xinxuan Zhang, 2024: Optimal baseflow separation through chemical mass balance: Comparing the usages of two tracers, two concentration estimation methods, and four baseflow filters. Water Resources Research, 60(7), e2023WR036386.
  8. Runkai Zhang, Jinxin Zhu*, Dagang Wang*, Chunzhu Wei and Cong Dong, 2024: Projected Changes in Heat, Extreme Precipitation, and Their Spatially Compound Events over China's Coastal Lands and Seas through a High-Resolution Climate Models Ensemble. Environmental Research Communications. DOI: 10.1088/2515-7620/ad53a7
  9. Xuerou Weng, Jinxin Zhu*, Dagang Wang*, Min Zhong, Ming Luo, Yiwen Mei, and Guoping Tang, 2024: Assessing rainfall erosivity changes over China through a Bayesian averaged ensemble of high-resolution climate models. Environmental Research Communications, DOI: 10.1088/2515-7620/ad3369.
  10. Yongen Lin, Dagang Wang*, Tao Jiang*, and Aiqing Kang, 2024: Assessing Objective Functions in Streamflow Prediction Model Training Based on the Naïve Method. Water, 16 (5): 777. https://doi.org/10.3390/w16050777
  11. Yongen Lin, Dagang Wang*, Jinxin Zhu, Wei Sun, Chaopeng Shen, Wei Shangguan, 2024. Development of objective function-based ensemble model for streamflow forecasts. Journal of Hydrology. 632, 130861. https://doi.org/10.1016/j.jhydrol.2024.130861
  12. Dayang Wang, Dagang Wang*, Yiwen Mei, Qing Yang, Mingfei Ji, Yuying Li, Shaobo Liu, Bailian Li, Ya Huang, Chongxun Mo, 2024: Estimates of the land surface hydrology from the Community Land Model version 5 (CLM5) with three meteorological forcing datasets over China. Remote Sensing, 2024, 16(3), 550; https://doi.org/10.3390/rs16030550
  13. Ming Zhong, Hongrui Zhang, Tao Jiang, Jun Guo, Jinxin Zhu, Dagang Wang, Xiaohong Chen, 2023: A Hybrid Model Combining the Cama-Flood Model and Deep Learning Methods for Streamflow Prediction, Water resources management, 37, 4841–4859
  14. Yonghao Qi, Wanpeng Feng*, Yong Zhang, Dagang Wang, Yi Du, Sergey V. Samsonov, Pei‐Zhen Zhang, Abdul Habib Zaray, Abdullah Ansari, 2023. Fault Geometry, Slip Distribution, and Potential Triggering of the 2022 Mw 6.2 Deadly Afghanistan Earthquake Revealed from Geodetic and Weather Data, Seismological Research Letters, 94 (5): 2154–2166, doi: 10.1785/0220220341.
  15. Yongen Lin, Dagang Wang*, Yue Meng, Wei Sun, Jianxiu Qiu,Wei Shangguan, Jingheng Cai, Yeonjoo Kim, Yongjiu Dai, 2023. Bias learning improves data driven models for streamflow prediction. Journal of Hydrology: Regional Studies 50, 101557.
  16. Huijiao Chen, Shuo Wang*, Zhu, Jinxin Zhu, Dagang Wang, 2023. Projected Changes in the Pattern of Spatially Compounding Drought and Pluvial Events Over Eastern China Under a Warming Climate. Earth Future, 11 (5), DOI10.1029/2022EF003397.
  17. Xuerou Weng, Boen Zhang, Jinxin Zhu*, Dagang Wang, Jianxiu Qiu, 2023. Assessing Land Use and Climate Change Impacts on Soil Erosion Caused by Water in China, Sustainability, 15 (10), DOI10.3390/su15107865.
  18. Zhi Zhang, Dagang Wang*, Xinxin Wu, Yiwen Mei, Jianxiu Qiu, Jinxin Zhu, 2023. Unveiling flood-generating mechanisms using circular statistics-based machine learning approach without the need for discharge data during inference. Hydrology Research, 54 (10), 1181-1195，DOI10.2166/nh.2023.058.
  19. Qingliang Li, Gaosong Shi, Wei Shangguan, Vahid Nourani, Jianduo Li, Lu Li, Feini Huang,Ye Zhang, Chunyan Wang, Dagang Wang, Jianxiu Qiu, Xingjie Lu, and Yongjiu Dai, 2022: A 1 km daily soil moisture dataset over China using in situ measurement and machine learning, Earth System Science Data, 14, 5267–5286.
  20. Yi Du, Dagang Wang*, Jinxin Zhu*, Zequn Lin, Yixuan Zhong, 2022: Intercomparison of multiple high-resolution precipitation products over China: Climatology and extremes, Atmospheric Research, 278 (11), 106342, https://doi.org/10.1016/j.atmosres.2022.106342
  21. Yixuan Zhong, Xiaolong Liao, Ling Yi, Dagang Wang*, Leping Wu, Yuanyuan Li, 2022: Design Combination Optimized Approach for Urban Stormwater and Drainage Systems Using Copula-Based Method. Water, 14 (11), 1717. https://doi.org/10.3390/w14111717
  22. Sijing He, Zhaoli Wang, Dagang Wang, Weilin Liao, Xushu Wu, Chengguang Lai, 2022: Spatiotemporal variability of event-based rainstorm: The perspective of rainfall pattern and concentration, International Journal of Climatology, 42 (12), 6258-6276,  https://doi.org/10.1002/joc.7588
  23. Boen Zhang, Shuo Wang, Yamin Qing, Jinxin Zhu, Dagang Wang, and Jiafeng Liu, 2022: A vine copula-based polynomial chaos framework for improving multimodel hydroclimatic projections at a multi-decadal convection-permitting scale. Water Resources Research, 58 (6), e2022WR031954. https://doi.org/10.1029/2022WR031954
  24. Yi Du, Dagang Wang*, Jinxin Zhu*, Dayang Wang, Xiaoxing Qi, Jingheng Cai, 2022: Comprehensive assessment of CMIP5 and CMIP6 models in simulating and projecting precipitation over the global land. International Journal of Climatology, 42 (13), 6859-6875.
  25. Jaehyeong Lee, Yeonjoo Kim, Dagang Wang, 2022: Assessing the characteristics of recent drought events in South Korea using WRF-Hydro, Journal of Hydrology, 607 (4), 127459, https://doi.org/10.1016/j.jhydrol.2022.127459
  26. Zemian Wu, Jianxiu Qiu, Wade. T. Crow, Dagang Wang, Zhengang Wang and Xiaohu Zhang, 2022: Investigating the Efficacy of the SMAP Downscaled Soil Moisture Product for Drought Monitoring Based on Information Theory, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 1604-1616, doi: 10.1109/JSTARS.2021.3136565.
  27. Kaihao Long, Dagang Wang*, Guiling Wang, Jinxin Zhu, Shuo Wang, Shuishi Xie, 2021: Higher Temperature Enhances Spatiotemporal Concentration of Rainfall, Journal of Hydrometeorology, 22 (12), 3159–3169, https://doi.org/10.1175/JHM-D-21-0034.1.
  28. Dayang Wang, Dagang Wang*, Chongxun Mo, 2021. The Use of Remote Sensing-Based ET Estimates to Improve Global Hydrological Simulations in the Community Land Model Version 5.0, Remote Sensing, 13(21), 4460, https://doi.org/10.3390/rs13214460.
  29. Zhi Zhang, Dagang Wang*, Jianxiu Qiu, Jinxin Zhu, Tingli Wang, 2021: Machine learning approaches for improving near-real-time IMERG rainfall estimates by integrating Cloud Properties from NOAA CDR PATMOSX, Journal of Hydrometeorology, 22 (10), 2767–2781, DOI: 10.1175/JHM-D-21-0019.1
  30. Yongen Lin, Dagang Wang*, Guiling Wang, Jianxiu Qiu, Kaihao Long, Yi Du, Hehai Xie, Zhongwang Wei, Wei Shangguan and Yongjiu Dai, 2021: A hybrid deep learning algorithm and its application to streamflow prediction, Journal of Hydrology, 601, 126636,  https://doi.org/10.1016/j.jhydrol.2021.126636
  31. Dayang Wang, Dagang Wang*, Chongxun Mo, Yi Du，2021：Risk variation of reservoir regulation during food season based on bivariate statistical approach under climate change: a case study in the Chengbihe reservoir, China, Natural Hazards, 108, 1585–1608,  https://doi.org/10.1007/s11069-021-04746-1
  32. Jinxin Zhu, Shuo Wang, Boen Zhang, Dagang Wang, 2021: Adapting to Changing Labor Productivity as a Result of Intensified Heat Stress in a Changing Climate, Geohealth, 5 (4), doi.org/10.1029/2020GH000313
  33. Dashan Wang, Xianwei Wang, Lin Liu, Dagang Wang, 2021: Urban Signatures in the Spatial Clustering of Precipitation Extremes over Mainland China, Journal of Hydrometeorology, 22 (3), 639-656, DOI10.1175/JHM-D-20-0063.1.
  34. Jinxin Zhu, Shuo Wang, Dagang Wang, Xueting Zeng, Yanpeng Cai, Boen Zhang, 2021: Upholding labor productivity with intensified heat stress: Robust planning for adaptation to climate change under uncertainty. Journal of cleaner production, 322, 129083, DOI.10.1016/j.jclepro.2021.129083.
  35. Dashan Wang, Jie Wu, Maoyi Huang, Laurent Z. X. Li, Dagang Wang, Ting Lin, Li Dong, Qi Li, Long Yang, Zhenzhong Zeng, 2021: The Critical Effect of Subgrid-Scale Scheme on Simulating the Climate Impacts of Deforestation, Journal of Geophysical Research-Atmospheres, 126 (17), e2021JD035133, DOI10.1029/2021JD035133.
  36. Weilin Liao, Xiaoping Liu, Dagang Wang, Dan Li, 2020: Sensitivities and responses of land surface temperature to deforestation-induced biophysical changes in two global earth system models, Journal of Climate, 33 (19): 8381–8399, https://doi.org/10.1175/JCLI-D-19-0725.1
  37.  Dongdong Kong, Yongqiang Zhang, Dagang Wang, Jianyao Chen, Xihui Gu, 2020: Photoperiod explains the asynchronization between vegetation carbon phenology and vegetation greenness phenology. Journal of Geophysical Research: Biogeosciences, 125, e2020JG005636. https://doi.org/10.1029/2020JG005636.
  38. Tingli Wang, Dagang Wang*, Yunpeng Wang, 2019. Spatiotemporal Trend Analysis of Soil Moisture Retrieved From Three NLDAS-Based Advanced Land Surface Models over the United States: A Comparative Study. IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, DOI: 10.1109/IGARSS.2019.8898174
  39. Yongjiu Dai, Wei Shangguan, Nan Wei, Qinchuan Xin, Hua Yuan, Shupeng Zhang, Shaofeng Liu, Xingjie Lu, Dagang Wang, and Fapeng Yan, 2019. A review of the global soil property maps for Earth system models. SOIL, 5, 137–158, DOI: 10.5194/soil-5-137-2019
  40. Dongdong Kong, Yongqiang Zhang, Xihui Gu, Dagang Wang, 2019. A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. Journal of Photogrammetry and Remote Sensing, 155:13-24, DOI: 10.1016/j.isprsjprs.2019.06.014
  41. Dan Li, Weilin Liao, Angela Rigden, Xiaoping Liu, Dagang Wang, Sergey Malyshev, Elena Shevliakova, 2019: Urban heat island: Aerodynamics or imperviousness? Science Advances, DOI:10.1126/sciadv.aau4299.
  42. Yongjiu Dai, Hua Yuana, Qinchuan Xin, Dagang Wang, Wei Shangguan, Shupeng Zhang, Shaofeng Liu, Nan Wei, 2019: Different representations of canopy structure-A large source of uncertainty in global land surface modeling, Agricultural and Forest Meteorology, 269, 119–135, doi:10.1016/j.agrformet.2019.02.006.
  43. Zhi Zhang, Dagang Wang*, Guiling Wang, Jianxiu Qiu, Weilin Liao, 2019: Use of SMAP soil moisture and fitting methods in improving GPM estimation in near real time, Remote Sensing, 11(3), 368; doi:10.3390/rs11030368.
  44. Weilin Liao, Dagang Wang*, Guiling Wang, Youlong Xia, and Xiaoping Liu, 2019: Quality Control and Evaluation of the Observed Daily Data in North American Soil Moisture Database, Journal of Meteorological Research, 33 (3), 501-518, DOI: 10.1007/s13351-019-8121-2.
  45. Dashan Wang, Xianwei Wang, Lin Liu, Dagang Wang, Huabing Huang, and Cuilin Pan, 2019: Evaluation of TMPA 3B42V7, GPM IMERG and CMPA precipitation estimates in Guangdong Province, China. International Journal of Climatology. 39 (2), 738-755, https://doi.org/10.1002/joc.5839.
  46. Youlong Xia, David M. Mocko, Shugong Wang, Ming Pan, Sujay V. Kumar, Christa D. Peters-Lidard, Helin Wei, Dagang Wang, and Michael B. Ek, 2018. Comprehensive Evaluation of the Variable Infiltration Capacity (VIC) Model in the North American Land Data Assimilation System, Journal of Hydrometeorology, 19, 1853-1866, doi.org/10.1175/JHM-D-18-0139.1.
  47. Weilin Liao, Xiaoping Liu, Dan Li, Ming Luo, Dagang Wang, Shaojian Wang, Jane Baldwin, Lijie Lin, Xia Li, Kuishuang Feng, Klaus Hubacek, and Xuchao Yang, 2018. Stronger Contributions of Urbanization to Heat Wave Trends in Wet Climates. Geophysical Research Letters, 45, 11310–11317, https://doi.org/10.1029/2018GL079679.
  48. Dashan Wang, Dagang Wang*, Xiangyan Qi, Lin Liu, Xianwei Wang, 2018: Use of high-resolution precipitation observations in quantifying the effect of urban extent on precipitation characteristics for different climate conditions over the Pearl River Delta, China. Atmospheric Science Letters, 2018, e820, DOI: 10.1002/asl.820.
  49. Xuerongzi Huang, Dashan Wang, Yu Liu, Zhizhou Feng, Dagang Wang*, 2018: Evaluation of extreme precipitation based on satellite retrievals over China, Frontiers of Earth Science, 2018, 12 (4): 846–861, DOI 10.1007/s11707-017-0643-2.
  50. Guiling Wang*, Dagang Wang*, Kevin E. Trenberth, Amir Erfanian, Miao Yu, Michael G. Bosilovich, Dana T. Parr, 2017: The peak structure and future changes of the relationships between extreme precipitation and temperature. Nature Climate Change, 7, 268-274, doi:10.1038/nclimate3239.
  51. Dagang Wang, Guiling Wang, Dana T. Parr, Weilin Liao, Youlong Xia, and CongSheng Fu, 2017: Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5. Hydrology and Earth System Sciences, 21 (7), 3557-3577, doi:10.5194/hess-21-1-2017.
  52. Weilin Liao, Dagang Wang*, Xiaoping Liu, Guiling Wang, and Jianbo Zhang, 2017: Estimated influence of urbanization on surface warming in eastern China using time-varying land use data, International Journal of Climatology, 37(7), 3197–3208, DOI: 10.1002/joc.4908.
  53. Dagang Wang, Peng Jiang, Guiling Wang Dashan Wang, 2015: Urban extent enhances extreme precipitation over the Pearl River Delta, China, Atmospheric Science Letters, 2015, 16(3): 310–317, DOI: 10.1002/asl2.559.
  54. Peng Jiang, Dagang Wang*, Yongqiang Cao, 2016: Spatiotemporal characteristics of precipitation concentration and their possible links to urban extent in China, Theoretical and Applied Climatology, 123(3): 757–768, DOI: 10.1007/s00704-015-1393-2.
  55. Chi Zhang, Dagang Wang*, Guiling Wang, Weito Yang, Xiaoping Liu, 2014: Regional differences in hydrological response to canopy interception schemes in a land surface model, Hydrological Processes, 28(4): 2499–2508, DOI: 10.1002/hyp.9762.
  56. Weilin Liao, Xiaoping Liu, Dagang Wang, Yanlin Sheng, 2017: The Impact of Energy Consumption on Surface Urban Heat Island in China's 32 Major Cities, Remote Sensing, 2017, 9(3), 250, doi:10.3390/rs9030250.
  57. Dashan Wang, Xianwei Wang, Lin Liu, Dagang Wang, Huabing Huang, Cuiling Pan, 2016: Evaluation of CMPA precipitation estimate in the evolution of typhoon-related storm rainfall in Guangdong, China. Journal of Hydroinformatics, 18(6): 1055-1068.
  58. Jiayong Liang, Xiaoping Liu, Kangning Huang, Xia Li, Dagang Wang, Xianwei Wang, 2014: Automatic Registration of Multisensor Images Using an Integrated Spatial and Mutual Information (SMI) Metric. IEEE Transactions on Geoscience and Remote Sensing, 52(1), 603-615, doi: 10.1109/TGRS.2013.2242895.
  59. Lina Wang, Quanxi Shao, Xiaohong Chen, Yan Li, Dagang Wang, 2012: Flood changes during the past 50 years in Wujiang River, South China, Hydrological Processes, 26(23), 3561–3569, DOI: 10.1002/hyp.9762.
  60. Dagang Wang, Guiling Wang, Emmanouil N. Anagnostou, 2009: Impact of sub-grid variability of precipitation and canopy storage on atmosphere hydrological processes. Climate Dynamics, 32(5): 649–662, doi: 10.1007/s00382-008-0435-1.
  61. Dagang Wang, Emmanouil N. Anagnostou, Guiling Wang, 2008: Effects of sub-grid variability of precipitation and canopy water storage on climate model simulations of water cycle in Europe. Advances in Geosciences, 17, 49–53. doi:10.5194/adgeo-17-49-2008.
  62. Dagang Wang, Guiling Wang, Emmanouil N. Anagnostou, 2007: Evaluation of canopy interception scheme in Land surface models. Journal of Hydrology, 347, 308–318.
  63. Dagang Wang, Guiling Wang, 2007: Towards a robust canopy interception scheme with sub-grid precipitation variability in Land Surface Models. Journal of Hydrometeorology, 8, 439-446.
  64. Guiling Wang, Yeojoo Kim, Dagang Wang, 2007: Quantifying the strength of soil moisture-precipitation coupling and its sensitivity to changes in surface water budget. Journal of Hydrometeorology, 8(3), 551-570.
  65. Dagang Wang, Emmanouil N. Anagnostou, Guiling Wang, 2006: The effect of sub-grid rainfall variability on the water balance and flux exchange processes resolved at climate scale: The European region contrasted to Central Africa and Amazon rainforests. Advances in Geosciences, 7, 269-274.
  66. Dagang Wang, Guiling Wang, Emmanouil N. Anagnostou, 2005: Use of satellite-based precipitation observation in improving the parameterization of canopy hydrological processes in land surface models. Journal of Hydrometeorology, 6, 745-763.
  67. 庄胜杰，王大刚*，林泳恩，林泽群，陈润庭，2024：基于CFSv2产品和机器学习的东江流域月降水预报，中山大学学报 （自然科学版中英文），63（4），9-18.
  68. 陈润庭，林泳恩，林泽群，张智，庄胜杰，王大刚*，2024：PSO-LSTM-TMPH模型在水库调蓄流域径流模拟中的应用. 中国农村水利水电(5), 191-199.
  69. 王大洋，王大刚，杨 庆，姬明飞，莫崇勋，刘少博，林泽群，2023：不同气象驱动下 CLM4.5 陆面模式对黄河流域蒸散发模拟表现评估. 节水灌溉，2023（12）：66-73，86. DOI：10.12396/jsgg.2023302.
  70. 林泽群，吴海鸥，杨振华，张智，王大刚*，2023：基于高分辨率数据的热带气旋降水时空变化特征，中山大学学报 （自然科学版）（中英文），62（2），157-170.
  71. 杜懿，林泽群，庄胜杰，陈润庭，王大刚*，2023：GPM 卫星降水产品在长江流域的空间降尺度研究. 遥感技术与应用，2023，38（3）：697-707.
  72. 杜懿，林泽群，王大刚*，2023：不同降水产品在长江流域的偏差校正研究，水文，43（01），62-67
  73. 林泳恩，孟越，杜懿，王大洋，王大刚*，2023：堆叠集成模型径流预报效果的影响因素研究，水文，43（01），57-61
  74. 祝金鑫、王大刚*、吴欢、汤秋鸿，2023：陆气相互作用，水文，43（01），108-108
  75. 杜懿，孟越，陈昱桢，王大刚*，2022：黄河流域重要断面设计年径流量计算研究，人民黄河，44(7): 18-23
  76. 孟越，王大刚*，林泳恩，杜懿，张智，王大洋，林泽群，2022：SMOS和SMAP卫星土壤水分产品的对比评价与差异分析，中山大学学报(自然科学版)(中英文)，61(05)，9-21
  77. 蔡霁初, 邱建秀, 王大刚, 林凯荣, 阳坤, 曾庆峰，2021：基于土壤水分和气象要素的林火预报研究——以广东省为例，地理科学，41(9), 1676-1686
  78. 杜懿，王大刚*，祝金鑫，2021：基于CMIP5的中国西北地区暖湿化演变研究，水资源与水工程学报，32（05）：61-69
  79. 杜懿，王大洋，张智，王大刚*，2021：GPM IMERG降水产品在珠江流域的适用性分析，水文，41（06），1-6
  80. 杜懿，王大洋，王大刚*，2021：GPM卫星降水产品空间降尺度研究—以贵州省为例，自然资源遥感，自然资源遥感，33（04），111-120
  81. 林泳恩，杜懿，孟越，解河海，王大刚*，2021：不同集成模型对小流域短时径流预报的影响研究，中国农村水利水电，2021（11），97-102
  82. 王大洋，王大刚*，2021：气候变化对岩溶区流域极端径流频率分析的影响研究，中国农村水利水电，2021（5），118-124
  83. 杜懿，王大洋，林泳恩，王大刚*，2021：黄河下游利津断面年径流量预测研究，水力发电，47（6），7-11
  84. 杜懿，孟越，林晓雨，王大刚*，2021：高要水文站设计年径流计算研究，水利水电技术( 中英文) ，52( 3)，43-49
  85. 王大洋，王大刚*，2020：粤港澳大湾区背景下广东省9市人水和谐关系时空特性研究，水资源与水工程学报，11，23-29
  86. 王大洋，杜懿，王大刚*，龙铠豪，安程，2020：一种考虑水文周期性的水库汛期分期方法，水力发电，11，34-39
  87. 杜懿，安程，王大洋，王大刚*，2020：基于均一化数据的中国典型分区水文频率线型研究，中国农村水利水电，8，134-138
  88. 杜懿，龙铠豪，王大洋，王大刚*，2020：基于机器学习方法的安徽省年降水量预测，水电能源科学，38（7），5-7
  89. 杜懿，王大洋，阮俞理，莫崇勋，王大刚*，2020：中国地区近40年降水结构时空变化特征研究，水力发电，8，19-23
  90. 王水寒，邱建秀*，王大刚，2020：1960—2014年广东省干旱时空演变特征，热带地理，40 （2），357-366.
  91. 罗家顺，邱建秀*，赵天杰，王大刚，2020：基于Sentinel-1 数据的黑河中游土壤水分反演，遥感技术与应用，2020，35（1），23-32，doi：10.11873/j.issn.1004‐0323.2020.1.0023.
  92. 范悦，邱建秀*，董建志，张小虎，王大刚，2020：基于Triple Collocation 方法的微波土壤水分产品不确定性分析与时空变化规律研究，遥感技术与应用，2020，35（1），85-96，doi：10.11873/j.issn.1004‐0323.2020.1.0085
  93. 李宁，刘瑜，王大刚*，2019. 基于ARIMA和EEMD的东江流域季节降水预报研究，人民珠江，40（3），52-58
  94. 李宁，王大刚，2018. 东江分水方案实施对三大水库调度的影响分析，广东水利水电，12，1-4
  95. 王佳雯，廖威林，王大刚*，2017. 中国大陆地区极端降水与温度的相关性，中山大学学报（自然科学版），56（6）：22-30
  96. 刘瑜，吴裕珍，冯志州，黄雪绒姿，王大刚*．多种卫星降水产品对中国极端降雨反演效果评估．热带地理，2017，37（3）：417-433．
  97. 吴裕珍，冯志州，王大刚*，2016. 基于贝叶斯模式平均与标准化异常度的东江汛期降水预报，中山大学学报（自然科学版），55（6）：20-27
  98. 钟逸轩，吴裕珍，王大刚*，2016. 基于贝叶斯模式平均的大渡河流域集合降水概率预报研究，水文，36（1）：8-14
  99. 蒋鹏，王大刚*，陈晓宏，2015. 广东省近50年极端降水事件的时空特征及成因分析，水文，35（2）：77-84
  100. 吴裕珍，王大刚*，吴文娇，2015. 基于贝叶斯模式平均的东江流域降雨概率预报，热带地理，35（6）：860-872
  101. 吴裕珍，王大刚*，2014. 珠江流域降水研究进展综述及展望，人民珠江，40（6），52-58
  102. 陈守煜，郭瑜，王大刚, 2006: 智能预报模式与水文中长期智能预报方法. 中国工程科学, 8(7), 30-35
  103. 陈守煜，王大刚: 基于遗传算法的模糊优选BP网络模型及其应用. 水利学报, 2013，（5）, 116-121.
  104. 李敏，程春田，王大刚, 2002: 基于PowerBuilder和Mapobject水库洪水调度系统信息查询. 大连理工大学学报, 42(5), 603-605
  105. 王大刚，程春田，李敏, 2001: 基于遗传算法的水电站优化调度研究. 华北水利水电学院学报, 22(1), 5-10.
  106. Qingguo Li, Shouyu Chen, Dagang Wang, 2006: An Intelligent Runoff Forecasting Method Based on Fuzzy sets, Neural network and Genetic Algorithm. Sixth International Conference on Intelligent Systems Design and Applications. Volume 1, 948-953. October 16-18, 2006, Jinan, China.
  107. Shouyu Chen, Yu Guo, Dagang Wang, 2006: Use of Engineering Fuzzy Sets, BP Neural Network and Genetic Algorithm for Intelligent Decision-Making. The Sixth World Congress on Intelligent Control and Automation, Volume 1, 3052-3056. June 21-23, 2006, Dalian, China

科研项目

（一）、主持科研项目

1. 基于统计降尺度与多模式的未来生态水文干旱变化研究（52079151），国家自然科学基金国际合作与交流项目，2022－2023

2. 基于热力和动力机制的未来极端降水预估及其洪水效应研究（52079151），国家自然科学基金面上项目，2021－2024

3. 基于降水分类的极端降水与气温关系及其未来变化研究（51779278），国家自然科学基金面上项目，2018－2021

4. 城市化发展下土地利用变化和空气污染对珠江三角洲暴雨演化的影响研究（51379224），国家自然科学基金面上项目，2014－2017

5. 基于降水分类的多尺度气温与极端降水耦合关系研究，中山大学重大项目培育和新兴交叉学科培育计划项目（15lgjc），2015－2017

6. 城市环境变化对珠三角暴雨演化的影响研究，中山大学重大项目培育和新兴交叉学科培育计划项目（13lgjc），2013－2015

7. 基于统计方法和数值模式的东江流域季节降水预报研究，广东省水利科技创新项目（2014-11），2015－2016

8. 珠江三角洲城市化对降水的影响极其机理研究，教育部留学回国人员科研启动基金，2013－2015

9. 城市化影响极端降雨机理研究-以珠江三角洲为例，国家重点实验室开放基金，2013－2014

10. 广东省东江流域2019－2020年水量调度评估，惠州市西枝江流域实时洪水预报系统人工智能预报，10万，2019－2020

11. 广东省东江流域2020－2021年水量调度评估，广东省东江流域管理局，2020－2021

12. 广东省东江流域2019－2020年水量调度评估，广东省东江流域管理局，2019－2020

13. 广东省东江流域2018－2019年水量调度评估，广东省东江流域管理局，2018－2019

14. 广东省东江流域2017－2018年水量调度评估，广东省东江流域管理局，2017－2018

15. 广东省东江流域2016－2017年水量调度评估，广东省东江流域管理局，2016－2017

16. 广东省东江流域2015－2016年水量调度评估，广东省东江流域管理局，2015－2016

17. 广东省东江流域水量调度资料整编与2014－2015年水量调度效果评估，广东省东江流域管理局，2014－2015

18. 广东省东江流域2013年冬～2014年春枯水期水量调度，广东省东江流域管理局，2013－2014

19. 气候变化对淮河珠江流域洪水频率变化影响测试，水利部，2012－2014

20. 灾害性暴雨天气过程演化分析及暴雨分类方法研究，大连理工大学，2012－2014

21. 大渡河流域多源地理信息资料加工处理，中国水利水电科学研究院，2013－2013

22. 广东省鉴江流域2013年冬-2014年春枯水期水量调度实施方案编制，广东省西江流域管理局，2013－2014

23. 中山大学百人计划引进人才启动项目，中山大学，2011-2012

（二）、参与科研项目（子课题负责人）

1. 珠江流域水资源多目标调度技术与应用（2017YFC0405900），国家重点研发项目，2017－2020

2. 高分辨率全球陆面过程模式研发与应用（2017YFA0604300），国家重点研发项目，2017－2022

3. 基于大数据的区域海陆气环境预警预报关键技术（U1811464），NSFC-广东大数据科学中心项目，2019－20222

 

获奖情况

2005-2008，美国国家航空航天局，地球科学奖学金

2014-2015年度中山大学地理学院“我心目中的良师”

2014-2015年度中山大学地理学院“优秀班主任”

2015-2016年度中山大学地理学院“我心目中的良师”

2015-2016年度中山大学地理学院“科技论文奖”

2016-2017年度中山大学地理学院“我心目中的良师”

2017-2018年度中山大学地理学院“我心目中的良师”

2018-2019年度中山大学地理学院“我心目中的良师”

2016年第一学期《计算方法与计算应用》学生评教，中山大学全校第一

2019年第一学期《计算方法与计算应用》学生评教，中山大学全校第一