Dr Ze Jiang

Dr Ze Jiang

Research Associate

Ph.D. - Water Resources Engineering, University of New South Wales, Sydney, Australia, 2021

M.Sc. - Hydro-Informatics and Water Management, Partnership of five European Universities, 2015

B.Eng. - Environmental Engineering, Hohai University, Nanjing, China, 2012

Engineering
Water Research Centre

Research Associate in the School of Civil and Environmental Engineering's Water Research Centre (WRC)

Ze Jiang is an research associate from the School of Civil and Environmental Engineering at UNSW, who specializes in the field of hydro-climatology. His research is centered on understanding the impact of climate change on the water cycle, specifically investigating the effects of global warming on hydroclimate extreme (e.g., floods and droughts). Ze received his PhD in Water Resource Engineering from UNSW, where he developed an incredibly cool method known as Wavelet System Prediction (WASP), capable of predicting sustained hydroclimate changes. Ze's academic journey started with a B.Eng in Environmental Engineering from Hohai University, China. He then pursued a Joint M.Sc in "EuroAquae - HydroInformatics and Water Management" under the partnership of five prestigious European universities. Before relocating to Australia, Ze worked at the Tropical Marine Science Institute of the National University of Singapore, where he contributed to hydrological and crop modeling for two years.

 

Research Interests:

  • Hydro-climate extremes modelling and forecasting (e.g. Wavelet System Prediction)
  • Postprocessing techniques for correcting bias in climate and weather prediction models
  • Climate change impact on the water cycle (e.g. floods and droughts)
  • Hydrology/Hydraulics and water quality numerical modelling
  • HydroInformatics and water management

 

Research Highlights:

 

Teaching Activities:

 

Professional Experiences:
  • Research Assistant/Engineer in Tropical Marine Science Institute (TMSI), National University of Singapore (NUS), Singapore, Nov. 2015 - Feb. 2018. 
    • DSSAT crop modeling of future rice yield in Vietnam under climate change, Singapore-MIT Alliance project.
    • Development of index-based drought insurance for sovereign disaster risk transfer, World Bank project.
    • Impact of climate change on inland and coastal flooding in Singapore, Public Utilities Board (PUB) project.
    • Effectiveness of ABC Waters design features in residential developments, PUB-TMSI-Monash University project.
Location
External
  • Book Chapters | 2018
    Kim D; Sun Y; Wendi D; Jiang Z; Liong SY; Gourbesville P, 2018, 'Flood Modelling Framework for Kuching City, Malaysia: Overcoming the Lack of Data', in Springer Water, pp. 559 - 568, http://dx.doi.org/10.1007/978-981-10-7218-5_39
  • Journal articles | 2023
    Jiang Z; Johnson F; Sharma A, 2023, 'Do Derived Drought Indices Better Characterize Future Drought Change?', Earth's Future, 11, http://dx.doi.org/10.1029/2022EF003350
    Journal articles | 2023
    Jiang Z; Johnson F, 2023, 'A New Method for Postprocessing Numerical Weather Predictions Using Quantile Mapping in the Frequency Domain', Monthly Weather Review, 151, pp. 1909 - 1925, http://dx.doi.org/10.1175/MWR-D-22-0217.1
    Journal articles | 2023
    Wu Y; Li Y; Jiang Z; Xu Z; Yang M; Ding J; Zhang C, 2023, 'Machine Learning Prediction of Phosphate Adsorption on Six Different Metal-Containing Adsorbents', ACS ES and T Engineering, 3, pp. 1135 - 1146, http://dx.doi.org/10.1021/acsestengg.3c00001
    Journal articles | 2022
    Kusumastuti C; Jiang Z; Mehrotra R; Sharma A, 2022, 'Correcting Systematic Bias in Climate Model Simulations in the Time-Frequency Domain', Geophysical Research Letters, 49, http://dx.doi.org/10.1029/2022GL100550
    Journal articles | 2022
    Lang Y; Jiang Z; Wu X, 2022, 'Investigating the Linkage between Extreme Rainstorms and Concurrent Synoptic Features: A Case Study in Henan, Central China', Water (Switzerland), 14, http://dx.doi.org/10.3390/w14071065
    Journal articles | 2021
    Hohl R; Jiang Z; Tue Vu M; Vijayaraghavan S; Liong SY, 2021, 'Using a regional climate model to develop index-based drought insurance for sovereign disaster risk transfer', Agricultural Finance Review, 81, pp. 151 - 168, http://dx.doi.org/10.1108/AFR-02-2020-0020
    Journal articles | 2021
    Jiang Z; Rashid MM; Johnson F; Sharma A, 2021, 'A wavelet-based tool to modulate variance in predictors: An application to predicting drought anomalies', Environmental Modelling and Software, 135, pp. 104907, http://dx.doi.org/10.1016/j.envsoft.2020.104907
    Journal articles | 2021
    Jiang Z; Sharma A; Johnson F, 2021, 'Variable transformations in the spectral domain – Implications for hydrologic forecasting', Journal of Hydrology, 603, http://dx.doi.org/10.1016/j.jhydrol.2021.126816
    Journal articles | 2021
    Kusumastuti C; Jiang Z; Mehrotra R; Sharma A, 2021, 'A Signal Processing Approach to Correct Systematic Bias in Trend and Variability in Climate Model Simulations', Geophysical Research Letters, 48, http://dx.doi.org/10.1029/2021GL092953
    Journal articles | 2020
    Jiang Z; Sharma A; Johnson F, 2020, 'Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling', Water Resources Research, 56, http://dx.doi.org/10.1029/2019wr026962
    Journal articles | 2019
    Jiang Z; Raghavan SV; Hur J; Sun Y; Liong SY; Nguyen VQ; Van Pham Dang T, 2019, 'Future changes in rice yields over the Mekong River Delta due to climate change—Alarming or alerting?', Theoretical and Applied Climatology, 137, pp. 545 - 555, http://dx.doi.org/10.1007/s00704-018-2617-z
    Journal articles | 2019
    Jiang Z; Sharma A; Johnson F, 2019, 'Assessing the sensitivity of hydro-climatological change detection methods to model uncertainty and bias', Advances in Water Resources, 134, pp. 103430, http://dx.doi.org/10.1016/j.advwatres.2019.103430
    Journal articles | 2014
    Liu J; Lu G; Wang Y; Yan Z; Yang X; Ding J; Jiang Z, 2014, 'Bioconcentration, metabolism, and biomarker responses in freshwater fish Carassius auratus exposed to roxithromycin', Chemosphere, 99, pp. 102 - 108, http://dx.doi.org/10.1016/j.chemosphere.2013.10.036
  • Other | 2023
    Jiang Z; Choudhury D; Sharma A, 2023, Could the 2019-20 Australia bushfires or 2020-22 floods be predicted using CMIP decadal prediction?, , http://dx.doi.org/10.5194/egusphere-egu23-10096
    Other | 2023
    Johnson F; Jiang Z, 2023, Wavelet-based post-processing of NWP precipitation forecasts, , http://dx.doi.org/10.5194/egusphere-egu23-14123
    Conference Presentations | 2021
    Jiang Z; Sharma A; Johnson F, 2021, 'Advanced wavelet-based variance transformation algorithms for ENSO forecasting over long lead times', presented at MODSIM2021, 08 December 2021, https://youtu.be/8ZbFXUUOJeY
    Conference Presentations | 2020
    Jiang Z; Sharma A; Johnson F, 2020, 'Hydro-climatological forecasting: A view from the spectral domain', presented at AGU, 15 December 2020, https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/679238
    Conference Presentations | 2020
    Sharma A; Jiang Z; Johnson F, 2020, 'Forecasting drought revisited – the importance of spectral transformations to dominant atmospheric predictor variables', presented at EGU General Assembly, 08 May 2020, http://dx.doi.org/10.5194/egusphere-egu2020-12334
    Conference Presentations | 2019
    Jiang Z; Sharma A; Johnson F, 2019, 'A wavelet-based method to analyse sustained hydrological anomalies under climate change', presented at MODSIM, 05 December 2019
    Conference Presentations | 2019
    Jiang Z; Sharma A; Johnson F, 2019, 'Drought prediction for improved water resource management: A wavelet-based system prediction approach', presented at STAHY 2019, Nanjing, Jiangsu, China, 19 October 2019
    Conference Presentations | 2018
    Jiang Z; Sharma A; Johnson F, 2018, 'Assessing the impact of systematic biases in detection of hydrologic change across Australia', presented at STAHY 2018, Adelaide, South Australia, Australia, 18 September 2018
    Conference Papers | 2016
    Jiang Z; Molkenthin F; Sieker H, 2016, 'Urban Surface Characteristics Study Using Time-area Function Model: A Case Study in Saudi Arabia', in Procedia Engineering, pp. 911 - 918, http://dx.doi.org/10.1016/j.proeng.2016.07.493