戴强：博士、教授
联系方式
电子邮箱：q.dai@njnu.edu.cn
办公室地址：南京师范大学地理科学学院535室
通信地址：南京市栖霞区文苑路1号
个人主页：www.hydro-hazard.com
ResearchGate: https://www.researchgate.net/profile/Qiang_Dai4
Google Citation: https://scholar.google.co.uk/citations?user=4pJfr0cAAAAJ&hl=en
ORCID: http://orcid.org/0000-0002-8359-5892
教育背景
2011.10-2015.02，布里斯托大学，土木工程系，博士
2009.09-2011.06，中山大学，遥感与地理信息工程系，硕士
2005.09-2009.06，南京师范大学，地理信息系统系，学士
研究经历
2020.07- 教授，地理科学学院，南京师范大学
2017.09-2019.03，博士后，工学院，布里斯托尔大学
2015.06-2020.06，副教授，地理科学学院，南京师范大学
主要研究方向
1. 水文遥感：研究基于雷达遥感方法的水文气象要素反演与误差建模，主要关注降雨与土壤湿度。
2. 城市内涝：研究变化环境下的城市水文过程、城市水灾害的脆弱性评估与弹性提升，以及GIS技术在城市内涝建模与管理中的应用。
3. 城市系统模型：研究自然灾害与社会经济的耦合过程，模拟地震、洪涝、滑坡等不同自然灾害对城市系统的综合影响。
欢迎对遥感与GIS在城市水文与灾害中的应用感兴趣，并有志进行科学研究的同学报考我们团队的硕士和博士研究生！
主要社会兼职
《Water Resources Research》副主编（2021-）
《Journal of Hydrology》副主编（2021-）
《Remote Sensing》专刊“Remote Sensing for Streamflow Simulation”编辑
《Hydrological Processes》副主编（2020-）
国际雷达水文协会（WRaH）委员（2016-）
国际数字地球协会中委会虚拟地理环境专业委员会委员（2019-）
中国地理学会山地分会委员（2022-）
中国自然资源学会资源持续利用与减灾专业委员会委员（2022-）
江苏省测绘地理青年工作委员会委员（2019-）
荣誉和获奖情况
2023 教育部高等学校科学研究优秀成果奖（科技进步）二等奖（5/13）
2021 高校 GIS 新锐奖
2021 中国地理信息科技进步特等奖（12/15）
2019 江苏测绘地理信息科技进步一等奖（1/11）
2019 江苏省测绘地理信息优秀青年科技工作者
2016 江苏青年地理科技奖
2015 布里斯托尔大学最优博士论文（Bristol University Prize for Best Thesis）
2011-2014 布里斯托尔大学博士全额奖学金（University of Bristol Postgraduate Research Scholarship）
近期发表论文（*通讯作者）
1. Dai, Q., Zhu, J., Lv, G., Kalin, L., Yao, Y., Zhang, J., & Han, D., 2023, Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale, Science Advances, 9: eadg5551.
2. Zhu, J., Dai, Q*., Xiao, Y., Liu, C., Zhang, J., Zhuo, L., & Han, D., 2023, Microphysics-based rainfall energy estimation using remote sensing and reanalysis data, Journal of Hydrology, 608: 130314.
3. Yang, Q., Dai, Q*., Chen, Y., Zhang, S., & Zhang, Y., 2022, Effects of air pollution on rainfall microphysics over the Yangtze River Delta, Journal of Geophysical Research: Atmospheres, 127: e2021JD035934.
4. Zhang, J., Dai, Q*., Nan, N., & Han, D., 2022, Exploring the effect of catchment morphology on streamflow characteristics with virtual experiments, Journal of Hydrology, 608: 127606.
5. Zhao, B., Dai, Q*., Zhuo, L., Mao, J., Zhu, S., & Han, D., 2022, Accounting for satellite rainfall uncertainty in rainfall-triggered landslide forecasting, Geomorphology, 398: 108051.
6. Yang, Q., Dai, Q*., Zhang, S., Zhu, K., & Zhang, L., 2022, Raindrop size distribution retrieval model for Xband dualpolarization radar in China incorporating various climatic and geographical elements, IEEE Transactions on Geoscience and Remote Sensing, 60: 5112417.
7. Zhao, B., Dai, Q*., Zhuo, L., Zhu, S., Shen, Q., & Han, D., 2021, Assessing the potential of different satellite soil moisture products in landslide hazard assessment, Remote Sensing of Environment, 264: 112583.
8. Dai, Q., Zhu, J., Zhang, S., Zhu, S., Han, D., & Lv, G., 2020, Estimation of rainfall erosivity based on WRF-derived raindrop size distributions, Hydrology and Earth System Sciences, 24, 5407–5422.
9. Yang, Q., Dai, Q*., Han, D., Zhu, Z., & Zhang, S., 2020, Uncertainty analysis of radar rainfall estimates induced by atmospheric conditions using long short-term memory networks, Journal of Hydrology, 590: 125482.
10. Dai, Q., Zhu, X., Zhuo, L., Han, D., Liu, Z., & Zhang, S., 2020. A hazard-human coupled model (HazardCM) to assess city dynamic exposure to rainfall-triggered natural hazards. Environmental Modelling & Software, 127: 104684.
11. Zhuo, L., Dai, Q*., Zhao, B., & Han, D., 2020, Soil Moisture Sensor Network Design for Hydrological Applications, Hydrology and Earth System Sciences, 24: 2577–2591.
12. Zhao, B., Dai, Q*., Han, D., Zhang, J., Zhuo, L., & Berti, M, 2020, Application of hydrological model simulations in Landslide Predictions, Landslide, 17(4): 877-891.
13. Cai, J., Zhu, J., Dai, Q*., Yang, Q., & Zhang, S., 2020, Sensitivity of a weather research and forecasting model to downscaling schemes in ensemble rainfall estimation, Meteorological Applications, 27(1): e1806.
14. Zou, X., Dai, Q*., Wu, K., Yang, Q., & Zhang, S., 2020, An empirical ensemble rainfall nowcasting model using multi-scaled analogues, Natural Hazards, 103(1): 165-188.
15. Dai, Q., Yang, Q., Han, D., Rico-Ramirez, M.A., & Zhang, S., 2019. Adjustment of radar‐gauge rainfall discrepancy due to raindrop drift and evaporation using the Weather Research and Forecasting model and dual-polarization radar. Water Resources Research, 55: 9211–9233.
16. Zhao, B., Dai, Q*., Han, D., Dai, H., Mao, J, Zhuo, L. & Rong, G., 2019, Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions, Landslide, 16: 2381-2393.
17. Zhuo, L., Dai, Q*., Han, D., Chen, N., & Zhao, B., 2019, Assessment of simulated soil moisture from WRF Noah, Noah-MP, and CLM Land surface schemes for landslide hazard application, Hydrology and Earth System Sciences, 23: 4199–4218.
18. Zhu, X., Dai, Q*., Han, D., Zhuo, L., Zhu, S., & Zhang, S. 2019, Modeling the high-resolution dynamic exposure to flooding in a city region, Hydrology and Earth System Sciences, 23: 3353–3372.
19. Zhao, B., Dai, Q*., Han, D., Dai, H., Mao, J & Zhuo, L., 2019, Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds, Journal of Hydrology, 574: 276-287.
20. Yang, Q., Dai, Q*., Han, D., Chen, Y., & Zhang, S., 2019, Sensitivity analysis of raindrop size distribution parameterizations in weather research and forecasting rainfall simulation, Atmospheric Research, 228:1-13.
21. Zhuo, L., Dai, Q*., Han, D., Zhao, B., Chen, N., & Berit, M., 2019, Evaluation of remotely sensed soil moisture for landslide hazard assessment, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,12(1): 162-173.
22. Dai, Q., Yang, Q., Zhang, J., & Zhang, S. 2018, Impact of gauge representative error on a radar rainfall uncertainty model, Journal of Applied Meteorology and Climatology, 57: 2769–2787.
23. Dai, Q., Bray, M., Zhuo, L., Islam, T., & Han, D. 2017, A scheme for raingauge network design based on remotely-sensed rainfall measurements, Journal of Hydrometeorology, 18: 363–379.
24. Dai, Q., Han, D. & Srivastava, P.K.. 2017, Sensitivity Analysis In Earth Observation Modelling: Radar-Rainfall Sensitivity Analysis, Elsevier
25. Dai, Q., Han, D., Zhuo, L., Zhang J., Islam, T., & Srivastava, P.K. 2016, Seasonal generation of ensemble radar rainfall estimates using copula and autoregressive model, Stochastic Environmental Research and Risk Assessment, 30(1): 27-38.
26. Zhuo, L., Han, D., & Dai, Q., 2016, Soil moisture deficit estimation using satellite multi-angle brightness temperature, Journal of Hydrology, 539: 392-405.
27. Zhuo, L., Dai, Q., Islam, T., & Han, D., 2016, Error distribution modelling of satellite soil moisture measurements for hydrological applications, Hydrological Processes, 30: 2223-2236.
28. Dai, Q., Han, D., Rico-Ramirez, M.A. & Srivastava, P.K.. 2016, Geospatial Technology for Water Resources Development: Spatio-temporal Uncertainty Model for Radar Rainfall, CRC Press
29. Dai, Q., Han, D., Rico-Ramirez, M.A., Zhuo, L., Nanding, N. & Islam, T., 2015, Radar rainfall uncertainty modelling influenced by wind, Hydrological Processes, 29: 1704-1716.
30. Dai, Q., Rico-Ramirez, M.A., Han, D., Islam, T. & Liguori S. 2015, Probabilistic radar rainfall nowcasts using empirical and theoretical uncertainty models, Hydrological Processes, 29: 66-79.
31. Dai, Q., Han, D., Zhuo, L., Huang J., Islam, T., & Srivastava, P.K. 2015, Impact of complexity of radar rainfall uncertainty model on flow simulation, Atmospheric Research, 161-162: 93-101.
32. Dai, Q., Han, D., Zhuo, L., Huang J., Islam, T. & Zhang, S. 2015, Adjustment of wind-drift effect for real-time deviation correction in radar rainfall data, Physics and Chemistry of the Earth, 83-84: 178-186.
33. Zhuo, L., Dai, Q. & Han, D., 2015, Meta-analysis of flow modeling performances-to build a matching system between catchment complexity and model types, Hydrological Processes, 29: 2463–2477.
34. Srivastava, P.K., Han, D., Rico-Ramirez, M.A., O’Neill, P., Islam, T., Gupta, M. & Dai, Q. 2015, Performance evaluation of WRF-Noah Land surface model estimated soil moisture for hydrological application: Synergistic evaluation using SMOS retrieved soil moisture, Journal of Hydrology, 511: 17-27.
35. Zhuo, L., Han, D., Dai, Q., Islam, T., & Srivastava, P.K., 2015, Appraisal of NLDAS-2 multi-model simulated soil moistures for hydrological modelling, Water Resources Management, 29: 3503-3517.
36. Dai, Q. & Han, D., 2014, Exploration of discrepancy between radar and gauge rainfall surfaces driven by the downscaled wind field, Water Resources Research, 50: 8571-8588.
37. Dai, Q., Han, D., Rico-Ramirez, M.A. & Srivastava, P.K. 2014, Multivariate Distributed Ensemble Generator: A new scheme for ensemble radar precipitation estimation over temperate maritime climate, Journal of Hydrology, 511: 17-27.
38. Dai, Q., Han, D., Rico-Ramirez, M.A. & Islam, T. 2014, Modeling radar-rainfall estimation uncertainties using elliptical and Archimedean copulas with different marginal distributions, Hydrological Sciences Journal, 59: 1992-2008.
承担（参与）的主要科研项目
1. 国家自然科学基金项目，42371409，耦合陆气界面降雨微物理过程的雷达雨滴谱反演模型研究、2024/01-2027/12、48万、主持。
2. 国家自然科学基金项目，41871299，城市暴雨灾害链动态脆弱性的计算方法研究、2019/01-2022/12、58万、主持。
3. 国家自然科学基金项目，41501429，面向城市水文模拟的地表空间自动离散方法研究、2016/01-2018/12、23万、主持。
4. 江苏省高校自然科学研究重大项目，16KJA170001，基于地表空间自动离散化的城市内涝模拟与预报研究，2016/09-2019/08、15万、主持。
5. 南京师范大学百人计划启动基金，2017/09-2021/12、50万、主持。
6. 江苏省“双创博士”基金，2017/10-2020/12、15万、主持。
7. 国家自然科学基金项目，41631175，基于地理认知的场景数据模型与数据组织方法、2017/01-2021/12、290万、参加。
8. 英国自然环境研究委员会项目（NERC），NE/N012143/1，地震山区可持续经济社会发展系统模型、2016/01-2019/03、500,000英镑、参加。
9. 江苏省科技厅，BE2015704，城市地质与洪涝灾害监测预警关键技术研究，2015/07-2018/06、100万、参加。
10. 欧盟（European Commission）项目，水信息共享在应对地球水圈变化研究-面向可操作需要、2013-2016、6,000,000欧元、参加。
