PhD, 2019: Civil Engineering, University of Waterloo, Waterloo, Ontario, Canada.
MEng, 2014: Environmental Science, Beijing Normal University, Beijing, China.
BSc, 2011: Geography, Shandong Normal University, Jinan, Shandong, China.
2021-present: Postdoctoral Fellow, University of Saskatchewan, Canmore, Alberta, Canada.
2019-2021: Postdoctoral Fellow, National Center for Atmospheric Research, Boulder, Colorado, USA.
Hongli Liu is a Postdoctoral Fellow at the University of Saskatchewan at Canmore. Her research focuses on large-scale parameter estimation, geospatial intelligence, and uncertainty analysis in hydrologic modeling.
Hongli Liu, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, 2022: Ensemble dressing of meteorological fields: using spatial regression to estimate uncertainty in deterministic gridded meteorological datasets. Journal of Hydrometeorology, doi: 10.1175/JHM-D-21-0176.1
Hongli Liu, Bryan A. Tolson, Andrew J. Newman, Andrew W. Wood, 2021: Leveraging ensemble meteorological forcing data to improve parameter estimation of hydrologic models. Hydrological Processes, doi: 10.1002/hyp.14410
Ming Han, Juliane Mai, Bryan A. Tolson, James R. Craig, Étienne Gaborit, Hongli Liu, Konhee Lee, 2020: Subwatershed-based lake and river routing products for hydrologic and land surface models applied over Canada. Canadian Water Resources Journal, doi: 10.1080/07011784.2020.1772116
Hongli Liu, Antoine Thiboult, Bryan A. Tolson, François Anctil, Juliane Mai, 2019: Efficient treatment of climate data uncertainty in ensemble Kalman filter based on an existing historical climate ensemble dataset. Journal of Hydrology, doi: 10.1016/j.jhydrol.2018.11.047
Hongrui Wang, Hongli Liu, Cheng Wang, Ying Bai, Linlin Fan, 2019: A study of industrial relative water use efficiency of Beijing: An application of Data Envelopment Analysis. Water Policy, doi: 10.2166/wp.2019.019
Hongli Liu, Bryan A. Tolson, James R. Craig, Mahyar Shafii, 2016: A priori discretization error metrics for distributed hydrologic modeling applications. Journal of Hydrology, doi: 10.1016/j.jhydrol.2016.11.008
