Hui Zou

Hui Zou

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

Research Topic:

Improving eco-hydrological modelling for future climates

Supervised by:

  • Prof. Lucy Marshall
  •  Prof. Ashish Sharma


My PhD research aims to employ a straightforward conceptual eco-hydrological model to elucidate water-carbon dynamics within Australia's diverse ecosystems, encompassing humid, arid, and semi-arid regions. The study focuses three key objectives: 1) enhancing the characterization of data uncertainty, 2) refining the model for predictive purposes, and 3) improving the representation of ecological processes under future climates. The project is structured to develop eco-hydrological modelling tools designed to inform vegetation modelling efficiently and comprehensively across various catchments. This approach serves as a pragmatic alternative to intricate process-based models for investigating water-vegetation interactions within regional contexts under future climates.

This PhD research require skills including the expertise in eco-hydrological modelling, Bayesian inference calibration algorithm, model uncertainty analysis, and the basic level for GCM data processing and bias correction. Besides, I integrated Deep Learning as an alternative due to its widespread usage, and substantial interest in the modelling filed.

Before I started my PhD, I earned both my bachelor’s and master’s degree in engineering at Wuhan University (2013-2020). My interest in hydrology and water resource management led me to actively participate in projects involving water resource allocation and flood modelling. Through these endeavours, I honed my skills and deepened my understanding of hydrology, flood frequency, optimization algorithms, and fundamental concepts in environmental engineering. I enjoyed being a hydrologist/environmental engineer. Exploring earth with math is cool. 

  • 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.

    We investigated whether water resource allocation in central China can contribute to enhancing future water resource security 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).

UNSW Research Training Program (RTP) Scholarship