Q J Wang

Professor QJ Wang obtained his BE in 1984 from Tsinghua University at Beijing with a “Graduate of Excellence” Award. In Ireland, he completed his MSc in 1987 and PhD in 1990 at University College Galway. QJ worked briefly as a Postdoctoral Fellow with Professor James Dooge at University College Dublin, before returning to University College Galway to take up a Lecturer position. In 1994, QJ came to Australia and joined the University of Melbourne, where he worked as a Lecturer and later as a Senior Lecturer. In 1999, QJ took up a Principal Scientist position at the Victorian Department of Primary Industries, where he led irrigation research. In 2007, QJ joined CSIRO Land and Water as an Office of the Chief Executive Science Leader and Senior Principal Research Scientist. At CSIRO, he built his national and international reputation as a leader in water forecasting research and development. In February 2017, QJ took up the position of Professor of Hydrological Forecasting at the University of Melbourne.

Before joining CSIRO in 2007, QJ’s research interests included statistical hydrology, hydrological modelling and optimisation, irrigation, and regional planning. In CSIRO, QJ built from scratch a globally renowned water forecasting research team. Research by QJ and his team led to a national seasonal streamflow forecasting service operated by the Australian Bureau of Meteorology. The service now provides forecasts for over 300 locations, including major water storages and river systems across Australia. Forecasts issued at the start of each month give probabilities of volumes of streamflow in the next three months (http://www.bom.gov.au/water/ssf). Research by QJ and his team also led to a new national short-term streamflow forecasting service, which provides daily forecasts of streamflow for the next seven days (http://www.bom.gov.au/water/7daystreamflow).

QJ developed a number of cutting-edge mathematical models. Among international applications, the US National Oceanic and Atmospheric Administration is evaluating the Calibration Bridging and Merging (CBaM) method for operational seasonal climate forecasting for the US. QJ has published widely, including many recent journal papers on flood, short term and seasonal streamflow forecasting, and on weather and climate forecasting.