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个人简介

学历背景 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 工作经历 2015.09- 副教授,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 2015.05-2015.08,讲师,地理科学学院,南京师范大学

研究领域

1. 水文遥感:研究基于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

近期论文

查看导师最新文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

1. 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, doi: 10.1007/s10346-019-01255-y. 2. 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. 3. 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. 4. 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, 12:162-173. 5. 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. 6. 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. 7. 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: 27-38. 8. Zhuo, L., Han, D., & Dai, Q., 2016, Soil moisture deficit estimation using satellite multi-angle brightness temperature, Journal of Hydrology, 539: 392-405. 9. 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. 10. 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. 11. 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. 12. 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. 13. 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. 14. 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. 15. 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. 16. Dai, Q., Han, D. & Srivastava, P.K.. 2017, Sensitivity Analysis In Earth Observation Modelling: Radar-Rainfall Sensitivity Analysis, Elsevier 17. 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

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