ARTICLES PUBLISHED IN REFEREED JOURNALS

(underline indicates students/postdocs supervised by Dr Wang)

2021

  • Zhu, J., Wang, S., and Fischer E.M. (2021) Increased occurrence of day-night hot extremes in a warming climate. Climate Dynamics, in press. [PDF]

  • You, J. and Wang, S. (2021) Higher probability of occurrence of hotter and shorter heat waves followed by heavy rainfall. Geophysical Research Letters, 48, e2021GL094831. [PDF]

  • Zhang, B., Wang, S., and Zhu J. (2021) A weighted ensemble of regional climate projections for exploring the spatiotemporal evolution of multidimensional drought risks in a changing climate. Climate Dynamics. [PDF]

  • Carvalho, K.S., Smith, T.E., and Wang, S. (2021) Bering Sea marine heatwaves: Patterns, trends and connections with the Arctic. Journal of Hydrology, 600, 126462. [PDF]

  • Zhu, J., Wang, S., Wang, D., Zeng, X., Cai, Y., and Zhang, B. (2021) Upholding labor productivity with intensified heat stress: Robust planning for adaptation to climate change under uncertainty. Journal of Cleaner Production, 322, 129083. [PDF]

  • Qing, Y. and Wang, S. (2021) Multi-decadal convection-permitting climate projections for China’s Greater Bay Area and surroundings. Climate Dynamics, 57, 415–434. [PDF]

  • Zhu, J., Wang, S., Zhang, B., and Wang, D. (2021) Adapting to changing labor productivity as a result of intensified heat stress in a changing climate. GeoHealth, 4, e2020GH000313. [PDF]

  • Zhang, B. and Wang, S. (2021) Probabilistic characterization of extreme storm surges induced by tropical cyclones. Journal of Geophysical Research: Atmospheres, 126, e2020JD033557. [PDF]

  • Zhang, B., Wang, S., and Wang, Y. (2021) Probabilistic projections of multidimensional flood risks at a convection-permitting scale. Water Resources Research, 57, e2020WR028582. [PDF]

  • Li, K., Huang, G., Zhang, X., Lu, C., and Wang, S. (2021) Temporal and spatial changes of monthly vegetation growth in the ancient Yellow River irrigation system, China, and their driving forces. Journal of Contaminant Hydrology, 243, 103911. [PDF]

  • Long, K., Wang, D., Wang, G., Zhu, J., Wang, S., and Xie, S. (2021) Higher temperature enhances spatio-temporal concentration of rainfall. Journal of Hydrometeorology, in press.

 

2020

  • Chen, H., Wang, S., Zhu, J., and Zhang, B. (2020) Projected changes in abrupt shifts between dry and wet extremes over China through an ensemble of regional climate model simulations. Journal of Geophysical Research: Atmospheres, 125, e2020JD033894. [PDF]

  • Chen, H., Wang, S., Wang, Y., and Zhu, J. (2020) Probabilistic projections of hydrological droughts through convection-permitting climate simulations and multi-model hydrological predictions. Journal of Geophysical Research: Atmospheres, 125, e2020JD032914. [PDF]

  • Qing, Y., Wang, S., Zhang, B., and Wang, Y. (2020) Ultra-high resolution regional climate projections for assessing changes in hydrological extremes and underlying uncertainties. Climate Dynamics, 55, 2031–2051. [PDF]

  • Carvalho, K.S. and Wang, S. (2020) Sea surface temperature variability in the Arctic Ocean and its marginal seas in a changing climate: Patterns and mechanisms. Global and Planetary Change, 193, 103265. [PDF]

  • Wang, S., Zhu, J., Huang, G., Baetz, B., Cheng, G., Zeng, X., and Wang, X. (2020) Assessment of climate change impacts on energy capacity planning in Ontario, Canada using high-resolution regional climate model. Journal of Cleaner Production, 274, 123026. [PDF]

  • Chen, H., Wang, S., and Wang, Y. (2020) Exploring abrupt alternations between wet and dry conditions on the basis of historical observations and convection-permitting climate model simulations. Journal of Geophysical Research: Atmospheres, 125, e2019JD031982. [PDF]

  • Faridatul, M.I., Wu, B., Zhu, X., and Wang, S. (2020) Improving remote sensing based evapotranspiration modelling in a heterogeneous urban environment. Journal of Hydrology, 581, 124405. [PDF]

  • Wang, S. and Zhu, J. (2020) Amplified or exaggerated changes in perceived temperature extremes under global warming. Climate Dynamics, 54, 117–127. [PDF]

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2019

  • Zhang, B., Wang, S., and Wang, Y. (2019) Copula‐based convection‐permitting projections of future changes in multivariate drought characteristics. Journal of Geophysical Research: Atmospheres, 124, 7460–7483. [PDF]

  • Zhu, J., Wang, S., and Huang, G. (2019) Assessing climate change impacts on human-perceived temperature extremes and underlying uncertainties. Journal of Geophysical Research: Atmospheres, 124, 3800–3821. [PDF]

  • Wang, S. and Wang Y. (2019) Improving probabilistic hydroclimatic projections through high-resolution convection-permitting climate modeling and Markov chain Monte Carlo simulations. Climate Dynamics, 53, 1613–1636. [PDF]

  • Carvalho, K.S. and Wang, S. (2019) Characterizing the Indian Ocean sea level changes and potential coastal flooding impacts. Journal of Hydrology, 569, 373–386. [PDF]

  • Hu, Z., Chen, X., Chen, D., Li, J., Wang, S., Zhou, Q., Yin, G., and Guo, M. (2019) “Dry gets drier, wet gets wetter”: A case study over the arid regions of central Asia. International Journal of Climatology, 39, 1072–1091. [PDF]

  • Li, K., Huang, G., and Wang, S. (2019) Market-based stochastic optimization of water resources systems for improving drought resilience and economic efficiency in arid regions. Journal of Cleaner Production, 233, 522–537. [PDF]

 

2018 and earlier

  • Wang, S., Wang, X., and Li, Z. (2018) Editorial - Diagnostic evaluation and uncertainty quantification of Earth and environmental systems models. Mathematical Problems in Engineering, 1–2. [PDF]

  • Wang, S., Ancell, B.C., Huang, G.H., and Baetz, B.W. (2018) Improving robustness of hydrologic ensemble predictions through probabilistic pre- and post-processing in sequential data assimilation. Water Resources Research, 54, 2129–2151. [PDF]

  • Wang, S., Huang, G.H., Baetz, B.W., Cai, X.M., Ancell, B.C., and Fan, Y.R. (2017) Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter. Journal of Hydrology, 554, 743–757. [PDF]

  • Wang, S., Huang, G.H., Baetz, B.W., and Ancell, B.C. (2017) Towards robust quantification and reduction of uncertainty in hydrologic predictions: Integration of particle Markov chain Monte Carlo and factorial polynomial chaos expansion. Journal of Hydrology, 548, 484–497. [PDF]

  • Wang, Y.Y., Huang, G.H., and Wang, S. (2017) CVaR-based factorial stochastic optimization of water resources systems with correlated uncertainties. Stochastic Environmental Research and Risk Assessment, 31, 1543–1553.

  • Wang, S., Huang, G.H., Baetz, B.W., and Huang, W. (2016) Probabilistic inference coupled with possibilistic reasoning for robust estimation of hydrologic parameters and piecewise characterization of interactive uncertainties. Journal of Hydrometeorology, 17, 1243–1260.

  • Wang, S., Huang, G.H., and Zhou, Y. (2016) A fractional-factorial probabilistic-possibilistic optimization framework for planning water resources management systems with multi-level parametric interactions. Journal of Environmental Management, 172, 97–106.

  • Wang, Y.Y., Huang, G.H., Wang, S., Li, W., Guan, P.B., (2016) A risk-based interactive multi-stage stochastic programming approach for water resources planning under dual uncertainties. Advances in Water Resources, 94, 217–230.

  • Liu, X.M., Huang, G.H., Wang, S., and Fan, Y.R. (2016) Water resources management under uncertainty: Factorial multi-stage stochastic program with chance constraints. Stochastic Environmental Research and Risk Assessment, 30, 945–957.

  • Zhou, Y., Huang, G.H., Wang, S., Li, Z., and Zhou, Y. (2016) Factorial fuzzy programming for planning water resources management systems. Journal of Environmental Planning and Management, 59, 1855–1872.

  • Wang, Y.Y., Huang, G.H., Wang, S., and Li, W. (2016) A stochastic programming with imprecise probabilities model for planning water resources systems under multiple uncertainties. Stochastic Environmental Research and Risk Assessment, 30, 2169–2178.

  • Zhao, S., Huang, G.H., Wang, S., Wang, X.Q., and Huang, W. (2016) Insight into sorption mechanism of phenanthrene onto gemini modified palygorskite through a multi-level fuzzy-factorial inference approach. Journal of Environmental Science and Health, Part A. Toxic/Hazardous Substances and Environmental Engineering, 51, 759–768.

  • Zhou, Y., Huang, G.H., Wang, S., Zhai, Y., and Xin, X. (2016) Water resources management under dual uncertainties: A factorial fuzzy two-stage stochastic programming approach. Stochastic Environmental Research and Risk Assessment, 30, 795–811.

  • Chen, F., Huang, G.H., Fan, Y.R., and Wang, S. (2016) A copula-based chance-constrained waste management planning method: An application to the City of Regina. Journal of the Air & Waste Management Association, 66, 307–328.

  • Wang, S., Huang, G.H., Baetz, B.W., and Huang, W. (2015) A polynomial chaos ensemble hydrologic prediction system for efficient parameter inference and robust uncertainty assessment. Journal of Hydrology, 530, 716–733.

  • Wang, S., Huang, G.H., Huang, W., Fan, Y.R., and Li, Z. (2015) A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space. Journal of Hydrology, 529, 1129–1146.

  • Wang, S., Huang, G.H., and Baetz, B.W. (2015) An inexact probabilistic-possibilistic optimization framework for flood management in a hybrid uncertain environment. IEEE Transactions on Fuzzy Systems, 23, 897–908.

  • Wang, S., Huang, G.H., and Zhou, Y. (2015) Inexact probabilistic optimization model and its application to flood diversion planning in a dynamic and uncertain environment. Journal of Water Resources Planning and Management, 141, 04014093.

  • Wang, S. and Huang, G.H. (2015) A multi-level Taguchi-factorial two-stage stochastic programming approach for characterization of parameter uncertainties and their interactions: An application to water resources management. European Journal of Operational Research, 240, 572–581.

  • Wang, S. and Huang, G.H. (2015) Risk-based factorial probabilistic inference for optimization of flood control systems with correlated uncertainties. European Journal of Operational Research, 249, 258–269.

  • Wang, S. and Huang, G.H. (2014) An integrated approach for water resources decision making under interactive and compound uncertainties. Omega – The International Journal of Management Science, 44, 32–40.

  • Wang, S., Huang, G.H., Lin, Q.G., Li, Z., Zhang, H., and Fan, Y.R. (2014) Comparison of interpolation methods for estimating spatial distribution of precipitation in Ontario, Canada. International Journal of Climatology, 34, 3745–3751.

  • Wang, S., Huang, G.H., and Veawab, A. (2013) A sequential factorial analysis approach to characterize the effects of uncertainties for supporting air quality management. Atmospheric Environment, 67, 304–312.

  • Wang, S. and Huang, G.H. (2013) An interval-parameter two-stage stochastic fuzzy program with type-2 membership functions: An application to water resources management. Stochastic Environmental Research and Risk Assessment, 27, 1493–1506.

  • Wang, S. and Huang, G.H. (2013) A two-stage mixed-integer fuzzy programming with interval-valued membership functions approach for flood-diversion planning. Journal of Environmental Management, 117, 208–218.

  • Wang, S., Huang, G.H., Wei, J., and He, L. (2013) Simulation-based variance components analysis for characterization of interaction effects of random factors on Trichloroethylene vapor transport in unsaturated porous media. Industrial & Engineering Chemistry Research, 52, 8602–8611.

  • Wang, S. and Huang, G.H. (2013) Interactive fuzzy boundary interval programming for air quality management under uncertainty. Water, Air, & Soil Pollution, 224: 1574.

  • Wang, S. and Huang, G.H. (2013) A coupled factorial-analysis-based interval programming approach and its application to air quality management. Journal of the Air & Waste Management Association, 63, 179–189.

  • Wei, J., Huang, G.H., Wang, S., Zhao, S., and Yao, Y. (2013) Improved solubilities of PAHs by multi-component Gemini surfactant systems with different spacer lengths. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 423, 50–57.

  • Tan, Z.F., Song, Y.H., Shen, Y.S., Zhang, C., and Wang S. (2013) An optimization-based study to analyze the impacts of clean energy and carbon emission mechanisms on inter-regional energy exchange. Journal of Environmental Informatics, 22, 123–130.

  • Wang, S., Huang, G.H., and He, L. (2012) Development of a clusterwise-linear- regression-based forecasting system for characterizing DNAPL dissolution behaviors in porous media. Science of the Total Environment, 433, 141–150.

  • Wang, S., Huang, G.H., and Yang, B.T. (2012) An interval-valued fuzzy-stochastic programming approach and its application to municipal solid waste management. Environmental Modelling & Software, 29, 24–36.

  • Wang, S. and Huang, G.H. (2012) Identifying optimal water resources allocation strategies through an interactive multi-stage stochastic fuzzy programming approach. Water Resources Management, 26, 2015–2038.

  • He, L., Huang, G.H., Lu, H.W., Wang, S., and Xu, Y. (2012) Quasi-Monte Carlo based global uncertainty and sensitivity analysis in modeling free product migration and recovery from petroleum-contaminated aquifers. Journal of Hazardous Materials, 219–220, 133–140.

  • Shen, Y.S., Tan, Z.F., Shen, X.L., Bai, J.J., Li, Q.Z., and Wang, S. (2012) Study of energy saving and emission reduction based on the OLAP multi-indicator relational model. Journal of Environmental Informatics, 20, 115–122.

  • Wang, S. and Huang, G.H. (2011) Interactive two-stage stochastic fuzzy programming for water resources management. Journal of Environmental Management, 92, 1986–1995.

  • Wang, S., Huang, G.H., Lu, H.W., and Li, Y.P. (2011) An interval-valued fuzzy linear programming with infinite α-cuts method for environmental management under uncertainty. Stochastic Environmental Research and Risk Assessment, 25, 211–222.