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Dong Wang
Personal ProfileDong Wang Professor, Doctoral Supervisor School of Earth Sciences and Engineering, Nanjing University 163Xianlin Avenue, Nanjing 210023, P. R. China Tel: 025-89680852, +86-13357824695 Email: wangdong@nju.edu.cn https://www.scopus.com/authid/detail.uri?authorId=56918729900 https://www.researchgate.net/profile/Dong-Wang-52 https://orcid.org/0000-0003-2784-0045 Professor Dong Wang focuses on education and research in water sciences, as well as talent development. He has published over 100 research papers in journals such as Advances in Water Science, Journal of Hydraulic Engineering, Acta Scientiae Circumstantiae, Water Resources Research (WRR), Journal of Hydrology (JOH), Advances in Water Resources (AWR), and NI journals like Journal of Geophysical Research (JGR) and Water Research (WR). He has authored over ten textbooks (including four key textbooks for universities in Jiangsu Province, where he serves as chief editor, and three national-level exemplary textbooks for water conservancy disciplines). Additionally, he has published multiple monographs, with one first-authored monograph receiving the National Science and Technology Academic Works Publishing Fund. His research areas include: (1) Applying information entropy theory, cloud models, Copula functions, artificial intelligence, and stochastic theory to address typical problems in hydrology, water resources, water environment, water ecology, and water-related disasters. (2) Developing and refining various models and methods based on these theories, such as: stochastic-fuzzy comprehensive evaluation and risk identification for flood and drought disasters; multi-dimensional risk analysis of hydrometeorological extreme events; signal-noise separation and cycle identification in complex hydrological series; comprehensive water resources evaluation; eutrophication and health assessment of water bodies; uncertainty analysis of river ecological water temperature and flow; and ecological regulation of reservoirs. Educational Background1998-2001 Ph.D., College of Hydrology and Water Resources, Hohai University 1995-1998 M.S., School of Civil Engineering, Shandong University 1991-1995 B.S., School of Civil Engineering, Shandong University Work Experience2008-present Professor, School of Earth Sciences and Engineering, Nanjing University 2003-2008 Associate professor, School of Earth Sciences and Engineering, Nanjing University 2001-2003 Postdoctoral fellow, School of Geography and Ocean Science, Nanjing University Academic ServiceResearch IntersetsStochastic Hydrology, Ecohydrology, Risk Analysis and System Optimization TeachingLecture on Hydraulics (compulsory for undergraduates) Lecture on Principles of Hydrology and Forecasting (compulsory for undergraduate students) Lecture on Hydrological Statistics (compulsory for undergraduate students) Lecture on Hydrological Survey, Hydrological and Hydraulic Calculation (elective for undergraduate students) Internship for majoring in hydrology and water resources engineering (compulsory for undergraduate students) Lecture on Hydrological Modeling (compulsory for graduate students) Lecture on Modern Hydrology (compulsory for doctoral students) Research ProjectsPresided over or mainly participated in the National Natural Science Foundation of China (National Science Fund for Distinguished Young Scholars, Key Project, and General Project), the Doctoral Program Fund of the Ministry of Education (Ph.D. Supervisors), the 973 Project of the National Key Basic Research Program, the Major Projects of the Ministry of Foreign Affairs of the People's Republic of China, the Ministry of Finance of the People's Republic of China, the Ministry of Science and Technology of the People's Republic of China Water Conservancy Public Welfare Industry Scientific Research Project, the China Postdoctoral Science Foundation and a number of horizontal projects of ministries, commissions, departments and bureaus. PublicationsMeng, Y., Jiang, J., Wu, J., & Wang, D. (2024). A Physics-Enhanced Neural Network for estimating longitudinal dispersion coefficient and average solute transport velocity in porous media. Geophysical Research Letters, 51, e2024GL110683. https://doi.org/10.1029/2024GL110683 Zhang, Z., Xu, P., Wang, D., Yang, H., Singh, V.P., Fu, X., Fang, H., Zhang, G., Liu, S., & Qiu, J. (2024). Quantifying the flood coincidence likelihood between Huai River and its tributaries considering the nonstationarity. Journal of Hydrology: Regional Studies, 54, 101887. https://doi.org/10.1016/j.ejrh.2024.101887 Xu, P., Wang, D., Wang, Y., Singh, V.P., Zhang, Z., Shang, X., Fang, H., Xie, Y., Zhang, G., Liu, S., & Fu, X. (2024). A dynamic von Mises-based model to evaluate the impact of urbanization and climate change on flood timing in Yangtze and Huaihe River Basins, China. Journal of Hydrology, 634, 131120. https://doi.org/10.1016/j.jhydrol.2024.131120 Qiu, R., Wang, D., Singh, V.P., Wang, Y., & Wu, J. (2024). Integration of deep learning and improved multi-objective algorithm to optimize reservoir operation for balancing human and downstream ecological needs. Water research, 253, 121314. https://doi.org/10.1016/j.watres.2024.121314 Zhang, A., Wang, D., Singh, V.P., Wang, Z., Ju, X., Yang, Z., Xu, P., Zeng, X., Jiang, J., Zhu, X., & Wu, J. (2023). Establishing SMMS approach to accurately mine the characteristics of regional precipitation trends. Journal of Hydrology, 627, 130382. https://doi.org/10.1016/j.jhydrol.2023.130382 Pan, Y., Zeng, X., Xu, H., Sun, Y., Wang, D., & Wu, J. (2023). Use of Stacked Gaussian Processes Regression Method to Improve Prediction of Groundwater Solute Transport Model. Journal of Hydrology, 620, 129530. https://doi.org/10.1016/j.jhydrol.2023.129530 Xu, P., Wang, D., Wang, Y., Singh, V.P., Qiu, J., Wu, J., Zhang, A., & Ju, X. (2023). Dynamic identification and risk analysis of compound dry-hot events considering nonstationarity. Journal of Hydrology, 616, 128852. https://doi.org/10.1016/j.jhydrol.2022.128852 Yu, X., Zeng, X., Gui, D., Li, X., Gou, Q., Wang, D., & Wu, J. (2023). Projection of flash droughts in the headstream area of Tarim River Basin under climate change through Bayesian uncertainty analysis. Journal of Geophysical Research: Atmospheres, 128, e2022JD037634. https://doi.org/10.1029/2022JD037634 Wang, Y., Tao, Y., Qiu, R., Wang, D., & Wu, J. (2022). A framework for assessing river thermal regime alteration: a case study of the Hanjiang River. Journal of Hydrology, 610, 127798. https://doi.org/10.1016/j.jhydrol.2022.127798 Sun, X., Zeng, X., Wu, J., & Wang, D. (2021). A two-stage Bayesian data-driven method to improve model prediction. Water Resources Research, 57, e2021WR030436. https://doi.org/10.1029/2021WR030436 Pan, Y., Zeng, X., Xu, H., Sun, Y., Wang, D., & Wu, J. (2021). Evaluation of Gaussian process regression kernel functions for improving groundwater prediction. Journal of Hydrology, 603, 126960. https://doi.org/10.1016/j.jhydrol.2021.126960 Xu, P., Wang, D., Wang, Y., Qiu, J., Singh, V.P., Ju, X., Zhang, A., Wu, J., & Zhang, C. (2021). Time-varying copula and average annual reliability-based nonstationary hazard assessment of extreme rainfall events. Journal of Hydrology, 603, 126792. https://doi.org/10.1016/j.jhydrol.2021.126792 Ju, X., Wang, Y., Wang, D., Singh, V.P., Xu, P., Wu, J., Ma, T., Liu, J., & Zhang, J. (2021). A time-varying drought identification and frequency analyzation method: A case study of Jinsha River Basin. Journal of Hydrology, 603, 126864. https://doi.org/10.1016/j.jhydrol.2021.126864 Tao, Y., Wang, Y., Wang, D., Ni, L., & Wu, J. (2021). A C-vine copula framework to predict daily water temperature in the Yangtze River. Journal of Hydrology, 598, 126430. https://doi.org/10.1016/j.jhydrol.2021.126430 Li, H., Wang, D., Singh, V.P., Wang, Y., Wu, J., & Wu, J. (2021). Developing an entropy and copula-based approach for precipitation monitoring network expansion. Journal of Hydrology, 598, 126366. https://doi.org/10.1016/j.jhydrol.2021.126366 Qiu, R., Wang, Y., Rhoads, B.L., Wang, D., Qiu, W., Tao, Y., & Wu, J. (2021). River water temperature forecasting using a deep learning method. Journal of Hydrology, 595, 126016. https://doi.org/10.1016/j.jhydrol.2021.126016 Xu, P., Wang, D., Singh, V. P., Lu, H., Wang, Y., Wu, J., et al. (2020). Multivariate hazard assessment for nonstationary seasonal flood extremes considering climate change. Journal of Geophysical Research: Atmospheres, 125, e2020JD032780. https://doi.org/10.1029/2020JD032780 Xu, P., Wang, D., Singh, V.P., Lu, H., Wang, Y., Wu, J., Wang, L., Liu, J., & Zhang, J. (2020). Copula-based seasonal rainfall simulation considering nonstationarity. Journal of Hydrology, 590, 125439. https://doi.org/10.1016/j.jhydrol.2020.125439 Wang, Y., Zhang, N., Wang, D., & Wu, J. (2020). Impacts of cascade reservoirs on Yangtze River water temperature: Assessment and ecological implications. Journal of Hydrology, 590, 125240. https://doi.org/10.1016/j.jhydrol.2020.125240 Liu, W., Wang, D., Wang, Y., Zeng, X., Ni, L., Tao, Y., Wu, J., Liu, J., Zou, Y., He, R., & Zhang, J. (2020). Improved comprehensive ecological risk assessment method and sensitivity analysis of polycyclic aromatic hydrocarbons (PAHs). Environmental research, 187, 109500. https://doi.org/10.1016/j.envres.2020.109500 Liu, W., Wang, D., Singh, V.P., Wang, Y., Zeng, X., Ni, L., Tao, Y., Wu, J., Liu, J., Zou, Y., He, R., & Zhang, J. (2020). A hybrid statistical model for ecological risk integral assessment of PAHs in sediments. Journal of Hydrology, 583, 124612. https://doi.org/10.1016/j.jhydrol.2020.124612 Ni, L., Wang, D., Wu, J., Wang, Y., Tao, Y., Zhang, J., Liu, J., & Xie, F. (2020). Vine copula selection using mutual information for hydrological dependence modeling. Environmental research, 186, 109604. https://doi.org/10.1016/j.envres.2020.109604 Ni, L., Wang, D., Wu, J., Wang, Y., Tao, Y., Zhang, J., & Liu, J. (2020). Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model. Journal of Hydrology, 586, 124901. https://doi.org/10.1016/j.jhydrol.2020.124901. Tao, Y., Wang, Y., Wang, D., Ni, L., & Wu, J. (2020). A probabilistic modeling framework for assessing the impacts of large reservoirs on river thermal regimes - A case of the Yangtze River. Environmental research, 183, 109221. https://doi.org/10.1016/j.envres.2020.109221 Tao, Y., Wang, Y., Rhoads, B.L., Wang, D., Ni, L., & Wu, J. (2020). Quantifying the impacts of the Three Gorges Reservoir on water temperature in the middle reach of the Yangtze River. Journal of Hydrology, 582, 124476. https://doi.org/10.1016/j.jhydrol.2019.124476 Li, H., Wang, D., Singh, V. P., Wang, Y., Wu, J., Wu, J., He, R., Zou, Y., Liu, J., & Zhang, J. (2020). Developing a dual entropy-transinformation criterion for hydrometric network optimization based on information theory and copulas. Environmental research, 180, 108813. https://doi.org/10.1016/j.envres.2019.108813 Ni, L., Wang, D., Singh, V. P., Wu, J., Wang, Y., Tao, Y., & Zhang, J. (2019). Streamflow and rainfall forecasting by two long short-term memory-based models. Journal of Hydrology, 124296. https://doi.org/10.1016/j.jhydrol.2019.124296 Li, H., Wang, D., Singh, V.P., Wang, Y., Wu, J., Wu, J., Liu, J., Zou, Y., He, R., & Zhang, J. (2019). Non-stationary frequency analysis of annual extreme rainfall volume and intensity using Archimedean copulas: A case study in eastern China. Journal of Hydrology, 571, 114-131. https://doi.org/10.1016/j.jhydrol.2019.01.054 Zeng, X., Ye, M., Wu, J., Wang, D., & Zhu, X. (2018). Improved nested sampling and surrogate-enabled comparison with other marginal likelihood estimators. Water Resources Research, 54, 797–826. https://doi.org/10.1002/2017WR020782 Xu, P., Wang, D., Singh, V. P., Wang, Y., Wu, J., Wang, L., Zou, X., Liu, J., Zou, Y., & He, R. (2018). A kriging and entropy-based approach to raingauge network design. Environmental research, 161, 61–75. https://doi.org/10.1016/j.envres.2017.10.038 Wang, Y., Ma, H., Wang, D., Wang, G., Wu, J., Bian, J., & Liu, J. (2018). A new method for wind speed forecasting based on copula theory. Environmental research, 160, 365–371. https://doi.org/10.1016/j.envres.2017.09.034 Wang, D., Borthwick, A.G., He, H., Wang, Y., Zhu, J., Lu, Y., Xu, P., Zeng, X., Wu, J., Wang, L., Zou, X., Liu, J., Zou, Y., & He, R. (2018). A hybrid wavelet de‐noising and Rank‐Set Pair Analysis approach for forecasting hydro‐meteorological time series. Environmental Research, 160, 269–281. https://doi.org/10.1016/j.envres.2017.09.033 Xu, P., Wang, D., Singh, V.P., Wang, Y., Wu, J., Wang, L., Zou, X., Chen, Y., Chen, X., Liu, J., Zou, Y., & He, R. (2017). A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design. Journal of Hydrology, 555, 228-241. https://doi.org/10.1016/j.jhydrol.2017.09.046 Liu, D., Wang, D., Singh, V.P., Wang, Y., Wu, J., Wang, L., Zou, X., Chen, Y., & Chen, X. (2017). Optimal moment determination in POME-copula based hydrometeorological dependence modelling. Advances in Water Resources, 105, 39-50. https://doi.org/10.1016/j.advwatres.2017.04.016 Wang, D., Zeng, D., Singh, V. P., Xu, P., Liu, D., Wang, Y., Zeng, X., Wu, J., & Wang, L. (2016). A multidimension cloud model-based approach for water quality assessment. Environmental research, 149, 113–121. https://doi.org/10.1016/j.envres.2016.05.012 Wang, D., Liu, D., Ding, H., Singh, V. P., Wang, Y., Zeng, X., Wu, J., & Wang, L. (2016). A cloud model-based approach for water quality assessment. Environmental research, 148, 24–35. https://doi.org/10.1016/j.envres.2016.03.005 Wang, D., Huang, C., & Mai, B. (2016). To facilitate the advance of risk analysis and crisis response in China. Environmental research, 148, 547–549. https://doi.org/10.1016/j.envres.2016.04.027 Liu, D., Wang, D., Wang, Y., Wu, J., Singh, V.P., Zeng, X., Wang, L., Chen, Y., Chen, X., Zhang, L., & Gu, S. (2016). Entropy of hydrological systems under small samples: Uncertainty and variability. Journal of Hydrology, 532, 163-176. https://doi.org/10.1016/j.jhydrol.2015.11.019 Hong, M., Wang, D., Wang, Y., Zeng, X., Ge, S., Yan, H., & Singh, V. P. (2016). Mid- and long-term runoff predictions by an improved phase-space reconstruction model. Environmental research, 148, 560–573. https://doi.org/10.1016/j.envres.2015.11.024 Wang, D., Ding, H., Singh, V.P., Shang, X., Liu, D., Wang, Y., Zeng, X., Wu, J., Wang, L., & Zou, X. (2015). A hybrid wavelet analysis–cloud model data‐extending approach for meteorologic and hydrologic time series. Journal of Geophysical Research: Atmospheres, 120, 4057-4071. https://doi.org/10.1002/2015JD023192 Wang, D., Singh, V.P., Shang, X., Ding, H., Wu, J., Wang, L., Zou, X., Chen, Y., Chen, X., Wang, S., & Wang, Z. (2014). Sample Entropy-Based Adaptive Wavelet De-noising Approach for Meteorologic and Hydrologic Time Series. Journal of Geophysical Research: Atmospheres, 119, 8726-8740. https://doi.org/10.1002/2014JD021869 Liu, D., Wang D., Ding H., & Wang L. (2014). Eutrophication assessment by Entropy-Cloud Model. Journal of Hydraulic Engineering, 45(10), 1214-1222. https://doi.org/10.13243/j.cnki.slxb.2014.10.010 Ding, H., & Wang, D. (2013). The evaluation method of water eutrophication based on cloud model. Acta Scientiae Circumstantiae, 33(1), 251-257. https://doi.org/10.13671/j.hjkxxb.2013.01.036 Sang, Y., Wang, D., Wu, J. & Zhu, Q. (2010). Wavelet cross-correlation method for hydrologic time series analysis. Journal of Hydraulic Engineering, 41(11),1272-1279. https://doi.org/10.13243/j.cnki.slxb.2010.11.002 Sang, Y., Wang, D., Wu, J. & Zhu, Q. (2009). Information entropy theory based noise reduction method for hydrologic series data analysis. Journal of Hydraulic Engineering, 40(08),919-926. https://doi.org/10.13243/j.cnki.slxb.2009.08.002 Sang, Y., Wang, D., Wu, J., Zhu, Q., & Wang, L. (2009). The relation between periods’ identification and noises in hydrologic series data. Journal of Hydrology, 368, 165-177. https://doi.org/10.1016/j.jhydrol.2009.01.042 Wang, D., Singh, V.P., Zhu, Y., & Wu, J. (2009). Stochastic observation error and uncertainty in water quality evaluation. Advances in Water Resources, 32, 1526-1534. https://doi.org/10.1016/j.advwatres.2009.07.004 Sang, Y. & Wang, D. (2008). Wavelets selection method in hydrologic series wavelet analysis. Journal of Hydraulic Engineering, 39(03):295-300+306. https://doi.org/10.13243/j.cnki.slxb.2008.03.004 Wang, D., Singh, V. P. & Zhu Y. (2007). Hybrid fuzzy and optimal modeling for water quality evaluation. Water Resources Research, 43, W054156. https://doi.org/10.1029/2006WR005490 Wang, D., Zhu, Y., Zhao, K. (2004). Research and Application of Model Based on Set Pair Analysis and Fuzzy Set Theory for Evaluation of Water Eutrophication. HYDROLOGY, 24(03),9-13+41. https://doi.org/10.3969/j.issn.1000-0852.2004.03.003 Wang, D. & Zhu, Y. (2003). Influence of stochastic observation error on water environment evaluation. Journal of Hydraulic Engineering, 10, 1-5. https://doi.org/10.13243/j.cnki.slxb.2003.10.001 Wang, D. & Zhu, Y. (2001). Principle of Maximum Entropy and Its Application in Hydrology and Water Resources. ADVANCES IN WATER SCIENCE, 12(03):424-430. https://doi.org/10.14042/j.cnki.32.1309.2001.03.024 Wang, D. & Xu, S. (2001). State-of-the-Art of the Flood Control Operation of Multi-Reservoir System. ADVANCES IN WATER SCIENCE, 12(01):118-124. https://doi.org/10.14042/j.cnki.32.1309.2001.01.020Honors and AwardsFirst Prize for Science and Technology Progress of the Ministry of Education of China (Rank 1) First Class of the National Teaching Achievement Award for Higher Education (Rank 4) First Prize of Teaching Achievement in Water Conservancy in Colleges and Universities (Rank 2) Outstanding Doctoral Degree of Hohai University Outstanding Postdoctoral Fellow of Nanjing University Young Backbone Teacher of Nanjing University Outstanding Young and Middle-aged Discipline Leader of Nanjing University Young and Middle-aged Academic Leader of the Blue Project of Colleges and New Century Excellent Talents in University of Ministry of Education of China Liu Guangwen Youth Science and Technology Award Special Prize of the First National Young Lecturer Competition of Water ConservancyGroup |