Dai Qiang: PhD, Professor

Contact Information

• Email: q.dai@njnu.edu.cn
• Office Address: Room 535, School of Geographic Sciences, Nanjing Normal University, Nanjing, China
• Correspondence Address: No.1 Wenyuan Road, Qixia District, Nanjing, China
• Personal homepage: 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

Educational background

• 2011.10-2015.02, University of Bristol, Department of Civil Engineering, PhD    
• 2009.09-2011.06, Sun Yat-sen University, Department of Remote Sensing and Geographic Information Engineering, M.Sc.
• 2005.09-2009.06, Nanjing Normal University, Department of Geographic Information System, B.S.

Research Experience

• 2020.07- Professor, School of Geographical Sciences, Nanjing Normal University
• 2017.09-2019.03, Postdoctoral, School of Engineering, University of Bristol 
• 2015.06- 2020.06, Associate Professor, School of Geographical Sciences, Nanjing Normal University

Main research interests

• 1. hydrological remote sensing: research on inversion and error modelling of hydrometeorological elements based on radar remote sensing methods, focusing on rainfall and soil moisture.
• 2. urban flooding: research on urban hydrological processes under changing environments, vulnerability assessment and resilience enhancement of urban water hazards, and the application of GIS technology in modelling and management of urban flooding.
• 3. urban system modelling: to study the coupling process between natural disasters and socio-economics, and to simulate the integrated impacts of different natural disasters, such as earthquakes, floods, landslides, etc., on the urban system.

Students who are interested in the application of remote sensing and GIS in urban hydrology and disasters, and are interested in conducting scientific research are welcome to apply for MSc and PhD students in our team!

Major Social Adjuncts

• Associate Editor, Water Resources Research (2021-)
• Associate Editor, Journal of Hydrology (2021-)
• Editor of the special issue of Remote Sensing "Remote Sensing for Streamflow Simulation".
• Associate Editor, Hydrological Processes (2020-)
• Member of the International Radar Hydrology Association (WRaH) (2016-)
• Member of the Professional Committee on Virtual Geographic Environments of the Central Committee of the International Association of Digital Earth (IADE) (2019-)
• Member, Mountain Branch, Chinese Geographical Society (2022-)
• Member, Professional Committee on Sustainable Resource Utilisation and Disaster Reduction, Chinese Society of Natural Resources (2022-)
• Member of Jiangsu Province Surveying, Mapping and Geography Youth Working Committee (2019-)

Honours and Awards

• 2023 Second Prize of Outstanding Achievement Award for Scientific Research in Colleges and Universities (Scientific and Technological Progress), Ministry of Education (5/13)
• 2021 Higher Education GIS Rising Star Award
• 2021 China Geographic Information Science and Technology Progress Grand Prize (12/15)
• 2019 First-class prize of Jiangsu Surveying, Mapping and Geoinformation Scientific and Technological Progress (1/11)
• 2019 Excellent Young Science and Technology Workers in Surveying, Mapping and Geoinformation of Jiangsu Province
• 2016 Jiangsu Youth Geoscience and Technology Award
• 2015 Bristol University Prize for Best Thesis (Bristol University Prize for Best Thesis)
• 2011-2014 University of Bristol Postgraduate Research Scholarship for PhDs

Recent publications (*corresponding author)

• 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.

 

Major scientific research projects undertaken (participated)

• 1. National Natural Science Foundation of China (NSFC), 42371409, Radar raindrop spectral inversion modelling of rainfall microphysical processes at the coupled land-air interface, 2024/01-2027/12, 480,000, chair.
• 2. National Natural Science Foundation of China (NSFC) Project, 41871299, Research on Calculation Methods of Dynamic Vulnerability of Urban Storm Hazard Chain, 2019/01-2022/12, 580,000, Chair.
• 3. National Natural Science Foundation of China (NSFC), 41501429, Research on Automatic Discretisation Method for Urban Hydrological Simulation in Surface Space, 2016/01-2018/12, 230,000, Chair.
• 4. Major Project of Natural Science Research in Jiangsu Universities, 16KJA170001, Research on Urban Flood Simulation and Forecasting Based on Automatic Discretisation of Surface Space, 2016/09-2019/08, 150,000, presided.
• 6. Jiangsu Province "Double Creation Doctor" Fund, 2017/10-2020/12, 150,000, presided.
• 7. National Natural Science Foundation of China (NSFC), 41631175, Scene data model and data organisation method based on geocognition, 2017/01-2021/12, 2.9 million, participated.
• 8. UK Natural Environment Research Council Project (NERC), NE/N012143/1, Sustainable Economic and Social Development System Model for Earthquake Mountainous Areas, 2016/01-2019/03, £500,000, Participated.
• 9. Science and Technology Department of Jiangsu Province, BE2015704, Research on Key Technologies for Monitoring and Early Warning of Urban Geological and Flood Hazards, 2015/07-2018/06, 1,000,000, Participation.
• 10. European Commission, Water Information Sharing in Response to Changes in the Earth's Hydrosphere - Towards Operational Needs, 2013-2016, EUR 6,000,000, Participant.