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Hui Zou

Hui Zou

HDR students
Civil and Environmental Engineering
Water Research Centre (WRC)

Research Topic:

Improving eco-hydrological modelling for future climates

Supervised by:

  • Prof. Lucy Marshall
  • Prof. Ashish Sharma

Description:

My PhD research aims to improve vegetation dynamic simulation in an ecohydrological model via multiple catchment modelling skills. Environmental engineers have struggled to use an easy-to-apply ecohydrological model. Currently, despite the high level of physical realism, vegetation dynamic simulation is hindered by the expensive parameterisation and significant computational demands of land surface models. Based on a conceptual ecohydrological model (easy to run), I corrected the data error, improved the structure, and combined the model with a data-driven approach (they are all mature catchment modelling skills). The new model serves as a solid alternative for the computationally expensive land surfaces models in vegetation dynamics modelling.

I am broadly interested in hydrological modelling. I am now working on flood prediction, where I implement a data-driven model to better predict flood peak and uncertainty. Before I joined UNSW, I earned both my bachelor’s and master’s degrees in hydrology and water resources engineering at Wuhan University, China.
Email

Hui.Zou@unsw.edu.au

    1. We found that data-driven model (LSTM) needs more information to capture the impact of water stress on vegetation growth in this paper:

      Zou, H., Marshall, L., Sharma, A., Jian, J., Stephens, C., & Higgins, P. (2024). Modelling vegetation dynamics for future climates in Australian catchments: Comparison of a conceptual eco-hydrological modelling approach with a deep learning alternative. Environmental Modelling & Software, 181, 106179. doi: https://doi.org/10.1016/j.envsoft.2024.106179
    2. When using an ecohydrological model to simulate Leaf Area Index (LAI), we used Bayesian inference to separate the data error caused by satellite metadata from the residual LAI errors in this paper:

      Zou, H., Marshall, L., & Sharma, A. (2023). Characterizing errors using satellite metadata for eco-hydrological model calibration. Water Resources Research, 59, e2022WR033978. https://doi.org/10.1029/2022WR033978
    3. We investigated whether water resource allocation in central China can contribute to enhancing future water resource security or not in this paper:

      Zou, H., Liu, D., Guo, S. et al. Quantitative assessment of adaptive measures on optimal water resources allocation by using reliability, resilience, vulnerability indicators. Stoch Environ Res Risk Assess 34, 103–119 (2020). https://doi.org/10.1007/s00477-019-01753-4

Australian Government Research Training Program (RTP) Scholarship