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Energy and Environment Directorate

Hongxiang Yan

Hongxiang Yan

(509) 375-7224


Dr. Hongxiang Yan joined PNNL in 2017. Hongxiang is a hydrologist specializing in hydrologic modeling and forecasting, state-of-the-art data assimilation, uncertainty quantification, and climate change impact. He is also interested in Bayesian techniques and new developments in statistics to solve water problems. Aiming to advance hydrologic science through modeling climate-water-human interactions as a complex system to result in sustainable solutions.

Education and Credentials

  • Ph.D. (2016), Civil and Environmental Engineering, Portland State University, Portland, OR, USA
  • M.S. (2012), Civil Engineering, University of Arkansas, Fayetteville, AR, USA
  • B.E. (2010), Hydraulic Engineering, North China Electric Power University, Beijing, China

Affiliations and Professional Service

  • Member of the American Geophysical Union (AGU): 2012 to present
  • Member of the Environmental & Water Resources Institute (EWRI): 2012 to present
  • Member of the International Association of Hydrological Sciences (IAHS): 2013 to present
  • Member of the Hydrological Ensemble Prediction Experiment (HEPEX): 2014 to present

Awards and Recognitions

  • AGU-Water Resources Research Journal Cover Image, Volume 54 Issue 2 (2018)
  • Grand Prize Award, NASA-AGU Data Visualization and Storytelling Competition (2017)
  • Outstanding PHD Student Award, Department of Civil and Environmental Engineering, Portland State University (2016)
  • Student Educational Travel Award, Portland State University (2016)
  • Marie Brown Travel Award, Portland State University (2015)
  • Institute for Sustainable Solutions Travel Award, Portland State University (2014)

PNNL Publications


  • Yan H., M.S. Wigmosta, M.H. Huesemann, N. Sun, and S. Gao. 2023. "An Ensemble Data Assimilation Modeling System for Operational Outdoor Microalgae Growth Forecasting." Biotechnology and Bioengineering 120, no. 2:426-443. PNNL-SA-173423. doi:10.1002/bit.28272
  • Yan H., N. Sun, H.A. Eldardiry, T.B. Thurber, P. Reed, K. Malek, and R. Gupta, et al. 2023. "Characterizing uncertainty in Community Land Model version 5 hydrological applications in the United States." Scientific Data 10. PNNL-SA-177243. doi:10.1038/s41597-023-02049-7
  • Yan H., N. Sun, H.A. Eldardiry, T.B. Thurber, P. Reed, K. Malek, and R. Gupta, et al. 2023. "Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)." Journal of Advances in Modeling Earth Systems 15, no. 5:Art. No. e2022MS003312. PNNL-SA-175184. doi:10.1029/2022MS003312


  • Fullerton A., N. Sun, M. Baerwalde, H. Brooke, and H. Yan. 2022. "Mechanistic Simulations Suggest Riparian Restoration Can Partly Counteract Climate Impacts to Juvenile Salmon." Journal of the American Water Resources Association 58, no. 4:525-546. PNNL-SA-161108. doi:10.1111/1752-1688.13011
  • Gao S., H. Yan, N.H. Beirne, M.S. Wigmosta, and M.H. Huesemann. 2022. "Improving Microalgal Biomass Productivity Using Weather-Forecast-Informed Operations." Cells 11, no. 9:Art. No. 1498. PNNL-SA-170283. doi:10.3390/cells11091498
  • Sun N., H. Yan, M.S. Wigmosta, A. Coleman, L. Leung, and Z. Hou. 2022. "Datasets for characterizing extreme events relevant to hydrologic design over the conterminous United States." Scientific Data 9. PNNL-SA-163804. doi:10.1038/s41597-022-01221-9
  • Sun N., H. Yan, M.S. Wigmosta, J. Lundquist, S.E. Dickerson-Lange, and T. Zhou. 2022. "Forest Canopy Density Effects on Snowpack across the Climate Gradients of the Western United States Mountain Ranges." Water Resources Research 58, no. 1:Art. No. e2020WR029194. PNNL-SA-158006. doi:10.1029/2020WR029194


  • Yan H., M.S. Wigmosta, N. Sun, M.H. Huesemann, and S. Gao. 2021. "Real-Time Ensemble Microalgae Growth Forecasting with Data Assimilation." Biotechnology and Bioengineering 118, no. 3:1419-1424. PNNL-SA-153734. doi:10.1002/bit.27663
  • Yan H., N. Sun, A. Fullerton, and M. Baerwalde. 2021. "Greater vulnerability of snowmelt-fed river thermal regimes to a warming climate." Environmental Research Letters 16, no. 5:054006. PNNL-SA-156043. doi:10.1088/1748-9326/abf393


  • Peng Y., X. Yu, H. Yan, and J. Zhang. 2020. "Stochastic simulation of daily suspended sediment concentration using multivariate copulas." Water Resources Management 34, no. 12:3913-3932. PNNL-SA-154307. doi:10.1007/s11269-020-02652-y
  • Peng Y., Y. Shi, H. Yan, and J. Zhang. 2020. "Multivariate Frequency Analysis of Annual Maxima Suspended Sediment Concentrations and Floods in the Jinsha River, China." Journal of Hydrologic Engineering 25, no. 9:05020029. PNNL-SA-140370. doi:10.1061/(ASCE)HE.1943-5584.0001977
  • Peng Y., Y. Shi, H. Yan, K. Chen, and J. Zhang. 2020. "Closure to 'Coincidence Risk Analysis of Floods Using Multivariate Copulas: Case Study of Jinsha River and Min River, China' by Yang Peng, Yulong Shi, Hongxiang Yan, Kai Chen, and Jipeng Zhang." Journal of Hydrologic Engineering 25, no. 4:07020002. PNNL-SA-148508. doi:10.1061/(ASCE)HE.1943-5584.0001908
  • Yan H., N. Sun, M.S. Wigmosta, L. Leung, Z. Hou, A. Coleman, and R.L. Skaggs. 2020. "Evaluating next-generation intensity-duration-frequency curves for design flood estimates in the snow-dominated western United States." Hydrological Processes 34, no. 5:1255-1268. PNNL-SA-143219. doi:10.1002/hyp.13673
  • Yan H., N. Sun, X. Chen, and M.S. Wigmosta. 2020. "Next-Generation Intensity-Duration-Frequency Curves for Climate-Resilient Infrastructure Design: Advances and Opportunities." Frontiers in Water 2. PNNL-SA-152783. doi:10.3389/frwa.2020.545051


  • Hou Z., H. Ren, N. Sun, M.S. Wigmosta, Y. Liu, L. Leung, and H. Yan, et al. 2019. "Incorporating Climate Non-stationarity and Snowmelt Processes in Intensity-Duration-Frequency Analyses with Case Studies in Mountainous Areas." Journal of Hydrometeorology 20, no. 12:2331-2346. PNNL-SA-132327. doi:10.1175/JHM-D-19-0055.1
  • Peng Y., Y. Shi, H. Yan, K. Chen, and J. Zhang. 2019. "Coincidence Risk Analysis of Floods using Multivariate Copulas: A Case Study of the Jinsha River and Min River, China." Journal of Hydrologic Engineering 24, no. 2:Article No. 05018030. PNNL-SA-127655. doi:10.1061/(ASCE)HE.1943-5584.0001744
  • Sun N., H. Yan, M.S. Wigmosta, L. Leung, R. Skaggs, and Z. Hou. 2019. "Regional Snow Parameters Estimation for Large-Domain Hydrological Applications in the Western United States." Journal of Geophysical Research: Atmospheres 124, no. 10:5296-5313. PNNL-SA-134653. doi:10.1029/2018JD030140
  • Yan H., N. Sun, M.S. Wigmosta, R. Skaggs, L. Leung, A. Coleman, and Z. Hou. 2019. "Observed Spatiotemporal Changes in the Mechanisms of Extreme Water Available for Runoff in the Western United States." Geophysical Research Letters 46, no. 2:767-775. PNNL-SA-138215. doi:10.1029/2018GL080260
  • Yan H., N. Sun, M.S. Wigmosta, R. Skaggs, Z. Hou, and L. Leung. 2019. "Next-Generation Intensity-Duration-Frequency Curves to Reduce Errors in Peak Flood Design." Journal of Hydrologic Engineering 24, no. 7:04019020. PNNL-SA-135099. doi:10.1061/(ASCE)HE.1943-5584.0001799


  • Abbaszadeh P., H. Moradkhani, and H. Yan. 2018. "Enhancing Hydrologic Data Assimilation by Evolutionary Particle Filter and Markov Chain Monte Carlo." Advances in Water Resources 111. PNNL-SA-125292. doi:10.1016/j.advwatres.2017.11.011
  • Yan H., M. Zarekarizi, and H. Moradkhani. 2018. "Toward Improving Drought Monitoring using the Remotely Sensed Soil Moisture Assimilation: A Parallel Particle Filtering Framework." Remote Sensing of Environment 216. PNNL-SA-130065. doi:10.1016/j.rse.2018.07.017
  • Yan H., N. Sun, M.S. Wigmosta, R. Skaggs, Z. Hou, and L. Leung. 2018. "Next-Generation Intensity-Duration-Frequency Curves for Hydrologic Design in Snow-Dominated Environments." Water Resources Research 54, no. 2:1093-1108. PNNL-SA-126849. doi:10.1002/2017WR021290


  • Peng Y., K. Chen, H. Yan, and X. Yu. 2017. "Improving Flood Risk Analysis for Confluence Flooding Control Downstream Using Copula Monte Carlo Method." Journal of Hydrologic Engineering 22, no. 8:Article No. 04017018. PNNL-26189. doi:10.1061/(ASCE)HE.1943-5584.0001526
  • Yan H., H. Moradkhani, and M. Zarekarizi. 2017. "A Probabilistic Drought Forecasting Framework: A Combined Dynamical and Statistical Approach." Journal of Hydrology 548. PNNL-SA-123469. doi:10.1016/j.jhydrol.2017.03.004

Energy and Environment

Core Research Areas