Dr Siyuan Tian
Areas of expertise
- Geomatic Engineering 0909
- Photogrammetry And Remote Sensing 090905
- Geodesy 090902
- Surface Processes 040607
- Surfacewater Hydrology 040608
- Numerical And Computational Mathematics 0103
- Earth And Space Science Informatics 370402
- Natural Resource Management 410406
Biography
Siyuan graduated from the University of Melbourne with a Master's degree in Geomatics where she discovered a passion for remote sensing and water resources research. She completed her PhD at the Australian National University in 2019 on demonstrating the potential of forecasting drought impacts through satellite data assimilation. She is currently a Postdoctoral Fellow at ANU Centre for Water and Landscape Dynamics working on method development for improving water balance forecasting and high-resolution soil moisture modelling through satellite data assimilation.
Publications
- Tian, S, Renzullo, L, Van Dijk, A et al 2019, 'Global joint assimilation of GRACE and SMOS for improved estimation of root-zone soil moisture and vegetation response', Hydrology and Earth System Sciences, vol. 23, no. 2, pp. 1067-1081.
- Tian, S, Van Dijk, A, Tregoning, P et al. 2019, 'Forecasting dryland vegetation condition months in advance through satellite data assimilation', Nature Communications, vol. 10, no. 469, pp. 1-7.
- Li, B, Rodell, M, Kumar, S et al 2019, 'Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges', Water Resources Research, vol. 55, no. 9, pp. 7564-7586.
- Tangdamrongsub, N, Han, S, Tian, S et al 2018, 'Evaluation of Groundwater Storage Variations Estimated from GRACE Data Assimilation and State-of-the-Art Land Surface Models in Australia and the North China Plain', Remote Sensing, vol. 10, no. 3, pp. 1-26pp.
- Tian, S, Tregoning, P, Renzullo, L et al 2017, 'Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals', Water Resources Research, vol. 53, no. 3, pp. 1820-1840pp.
- Tian, S, Tregoning, P, Renzullo, L et al 2015, 'Integrating GRACE and SMOS data into a hydrological model using an ensemble Kalman Filter', 21st International Congress on Modelling and Simulation (MODSIM2015), ed. Weber, T., McPhee, M.J. and Anderssen, R.S., The Modelling and Simulation Society of Australia and New Zealand Inc., Australia, p. 533.
Projects and Grants
Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.
- Data Assimilation into the AWRA-CMS for improved operational and forecast modelling (Secondary Investigator)
