Doctor Bin Wang
Doctor Bin Wang is a Senior Research Fellow in the Institute, focusing on how plants and ecosystems respond to climate change. He is an expert in modelling the impacts of climate change on agriculture, forestry, and hydrology. His research focuses on understanding how climate change and variability affect crop yields, soil carbon, and forest productivity, with a particular interest in improving simulation models for better climate risk management. Dr Wang also studies the impacts of extreme events, such as droughts and heat, on crop productivity and develops agronomic strategies to mitigate these effects. Leveraging data mining and machine learning, he creates maps to predict soil carbon stock and explores how future climate conditions might affect plant growth and carbon storage in New South Wales.
Dr Wang obtained his PhD at the University of Technology Sydney in 2017. Since then, he joined the New South Wales Department of Primary Industries and Regional Development (formerly NSW DPI) as a Research Scientist and has since been promoted to Senior Research Scientist (2024). Alongside his primary research role at the Institute, Dr. Wang maintains a part-time affiliation with NSW DPIRD, where he contributes to projects that apply scientific knowledge to practical solutions for sustainable land and resource management. He completed his undergraduate studies at Nanjing Agricultural University in China and also serves as an Adjunct Associate Professor at the Gulbali Research Institute, Charles Sturt University.
Awards and recognition
- Leading biophysical modelling sessions for MODSIM 2021 and MODSIM 2023
- Nomination for the outstanding PhD thesis award from UTS (2017)
Project Grants
Quantifying the impacts of future climate change on vegetation
Co-Researchers: Ben Smith and Belinda Medlyn
Partner/funding body: GreenCollar
Period: 2024-2026
Selected Publications
Wu L, Quan H, Feng H, Ding D, Wu L, Liu DL, Wang B, (2025) 'Delaying sowing time and increasing sowing rate with plastic mulching can enhance wheat yield and water use efficiency under future climate change', Agricultural and Forest Meteorology, 362, art. no. 110383
Xiang K, Wang B, Liu DL, Chen C, Ji F, Yang Y, Li S, Huang M, Huete A, Yu Q, (2025) 'Soil with high plant available water capacity can mitigate the risk of wheat growth under drought conditions in southeastern Australia', European Journal of Agronomy 164, 127460
Yao S, Wang B, Liu DL, Li S, Ruan H, Yu Q, (2025) 'Assessing the impact of climate variability on Australia's sugarcane yield in 1980–2022', European Journal of Agronomy, 164, art. no. 127519
Anwar, M.R., Wang, B., Simmons, A., Herrmann, N., Liu, D.L., Cowie, A., Waters, C., 2024. Modelling the impacts of future climate change on mixed farming system in southeastern Australia. European Journal of Agronomy 160, 127328
Yao S, Wang B, Liu DL, Li S, Ruan H, Yu Q, (2025) 'Assessing the impact of climate variability on Australia's sugarcane yield in 1980–2022', European Journal of Agronomy, 164, art. no. 127519
Li, S., Wang, B., Liu, D.L., Chen, C., Feng, P., Huang, M., Wang, X., Shi, L., Waters, C., Huete, A., Yu, Q., 2024. Can agronomic options alleviate the risk of compound drought-heat events during the wheat flowering period in southeastern Australia? European Journal of Agronomy 153, 127030.
Wang, B., Jägermeyr, J., O’Leary, G.J., Wallach, D., Ruane, A.C., Feng, P., Li, L., Liu, D.L., Waters, C., Yu, Q., Asseng, S., Rosenzweig, C., 2024a. Pathways to identify and reduce uncertainties in agricultural climate impact assessments. Nature Food 5, 550-556.
Wang, B., Li, L., Feng, P., Chen, C., Luo, J.-J., Taschetto, A.S., Harrison, M.T., Liu, K., Liu, D.L., Yu, Q., Guo, X., 2024b. Probabilistic analysis of drought impact on wheat yield and climate change implications. Weather and Climate Extremes 45, 100708.
Wang, B., Smith, B., Waters, C., Feng, P., Liu, D.L., 2024c. Modelling changes in vegetation productivity and carbon balance under future climate scenarios in southeastern Australia. Science of The Total Environment 924, 171748.
Li, L., Wang, B., Feng, P., Jägermeyr, J., Asseng, S., Müller, C., Macadam, I., Liu, D.L., Waters, C., Zhang, Y., He, Q., Shi, Y., Chen, S., Guo, X., Li, Y., He, J., Feng, H., Yang, G., Tian, H., Yu, Q., 2023. The optimization of model ensemble composition and size can enhance the robustness of crop yield projections. Communications Earth & Environment 4, 362
Liu, K., Harrison, M.T., Yan, H., Liu, D.L., Meinke, H., Hoogenboom, G., Wang, B., Peng, B., Guan, K., Jaegermeyr, J., Wang, E., Zhang, F., Yin, X., Archontoulis, S., Nie, L., Badea, A., Man, J., Wallach, D., Zhao, J., Benjumea, A.B., Fahad, S., Tian, X., Wang, W., Tao, F., Zhang, Z., Rötter, R., Yuan, Y., Zhu, M., Dai, P., Nie, J., Yang, Y., Zhang, Y., Zhou, M., 2023. Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates. Nature Communications 14, 765.
Feng, P., Wang, B., Macadam, I., Taschetto, A.S., Abram, N.J., Luo, J.-J., King, A.D., Chen, Y., Li, Y., Liu, D.L., Yu, Q., Hu, K., 2022. Increasing dominance of Indian Ocean variability impacts Australian wheat yields. Nature Food 3, 862-870.
Jiang, T., Wang, B., Xu, X., Cao, Y., Liu, D.L., He, L., Jin, N., Ma, H., Chen, S., Zhao, K., Feng, H., Yu, Q., He, Y., He, J., 2022. Identifying sources of uncertainty in wheat production projections with consideration of crop climatic suitability under future climate. Agricultural and Forest Meteorology 319, 108933.
Li, L., Wang, B., Feng, P., Li Liu, D., He, Q., Zhang, Y., Wang, Y., Li, S., Lu, X., Yue, C., Li, Y., He, J., Feng, H., Yang, G., Yu, Q., 2022. Developing machine learning models with multi-source environmental data to predict wheat yield in China. Computers and Electronics in Agriculture 194, 106790.
Liu, K., Harrison, M.T., Wang, B., Yang, R., Yan, H., Zou, J., Liu, D.L., Meinke, H., Tian, X., Ma, S., Zhang, Y., Man, J., Wang, X., Zhou, M., 2022. Designing high-yielding wheat crops under late sowing: a case study in southern China. Agronomy for Sustainable Development 42, 29.
Shi, L., Feng, P., Wang, B., Liu, D.L., Zhang, H., Liu, J., Yu, Q., 2022a. Assessing future runoff changes with different potential evapotranspiration inputs based on multi-model ensemble of CMIP5 projections. Journal of Hydrology 612, 128042.
Shi, Y., Zhang, Y., Wu, B., Wang, B., Li, L., Shi, H., Jin, N., Liu, D.L., Miao, R., Lu, X., Geng, Q., Lu, C., He, L., Fang, N., Yue, C., He, J., Feng, H., Pan, S., Tian, H., Yu, Q., 2022b. Building social resilience in North Korea can mitigate the impacts of climate change on food security. Nature Food 3, 499-511.
Wang, B., Gray, J.M., Waters, C.M., Rajin Anwar, M., Orgill, S.E., Cowie, A.L., Feng, P., Li Liu, D., 2022a. Modelling and mapping soil organic carbon stocks under future climate change in south-eastern Australia. Geoderma 405, 115442.
Wang, B., Spessa, A.C., Feng, P., Hou, X., Yue, C., Luo, J.-J., Ciais, P., Waters, C., Cowie, A., Nolan, R.H., Nikonovas, T., Jin, H., Walshaw, H., Wei, J., Guo, X., Liu, D.L., Yu, Q., 2022b. Extreme fire weather is the major driver of severe bushfires in southeast Australia. Science Bulletin 67, 655-664.
Wang, B., Waters, C., Anwar, M.R., Cowie, A., Liu, D.L., Summers, D., Paul, K., Feng, P., 2022c. Future climate impacts on forest growth and implications for carbon sequestration through reforestation in southeast Australia. Journal of Environmental Management 302, 113964.
Huang, M., Wang, J., Wang, B., Liu, D.L., Feng, P., Yu, Q., Pan, X., Waters, C., 2021. Assessing maize potential to mitigate the adverse effects of future rising temperature and heat stress in China. Agricultural and Forest Meteorology 311, 108673.
Li, L., Wang, B., Feng, P., Wang, H., He, Q., Wang, Y., Liu, D.L., Li, Y., He, J., Feng, H., Yang, G., Yu, Q., 2021. Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China. Agricultural and Forest Meteorology 308-309, 108558.
Feng, P., Wang, B., Liu, D.L., Ji, F., Niu, X., Ruan, H., Shi, L., Yu, Q., 2020a. Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia. Environmental Research Letters 15, 084051.
Feng, P., Wang, B., Liu, D.L., Waters, C., Xiao, D., Shi, L., Yu, Q., 2020b. Dynamic wheat yield forecasts are improved by a hybrid approach using a biophysical model and machine learning technique. Agricultural and Forest Meteorology 285-286, 107922.
Wang, B., Feng, P., Liu, D.L., O’Leary, G.J., Macadam, I., Waters, C., Asseng, S., Cowie, A., Jiang, T., Xiao, D., Ruan, H., He, J., Yu, Q., 2020. Sources of uncertainty for wheat yield projections under future climate are site-specific. Nature Food 1, 720-728.
Zhang, H., Wang, B., Liu, D.L., Zhang, M., Leslie, L.M., Yu, Q., 2020. Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia. Journal of Hydrology 585, 124822.
Feng, P., Wang, B., Liu, D.L., Waters, C., Yu, Q., 2019a. Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia. Agricultural and Forest Meteorology 275, 100-113.
Feng, P., Wang, B., Liu, D.L., Yu, Q., 2019b. Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia. Agricultural Systems 173, 303-316.
Wang, B., Deveson, E.D., Waters, C., Spessa, A., Lawton, D., Feng, P., Liu, D.L., 2019a. Future climate change likely to reduce the Australian plague locust (Chortoicetes terminifera) seasonal outbreaks. Science of The Total Environment 668, 947-957.
Wang, B., Feng, P., Chen, C., Liu, D.L., Waters, C., Yu, Q., 2019b. Designing wheat ideotypes to cope with future changing climate in South-Eastern Australia. Agricultural Systems 170, 9-18.
Wang, B., Liu, D.L., O'Leary, G.J., Asseng, S., Macadam, I., Lines-Kelly, R., Yang, X., Clark, A., Crean, J., Sides, T., Xing, H., Mi, C., Yu, Q., 2018a. Australian wheat production expected to decrease by the late 21st century. Global Change Biology 24, 2403–2415.
Wang, B., Waters, C., Orgill, S., Gray, J., Cowie, A., Clark, A., Liu, D.L., 2018b. High resolution mapping of soil organic carbon stocks using remote sensing variables in the semi-arid rangelands of eastern Australia. Science of The Total Environment 630, 367-378.
Wang, B., Liu, D.L., Asseng, S., Macadam, I., Yu, Q., 2017. Modelling wheat yield change under CO2 increase, heat and water stress in relation to plant available water capacity in eastern Australia. European Journal of Agronomy 90, 152-161.
Wang, B., Liu, D.L., Macadam, I., Alexander, L.V., Abramowitz, G., Yu, Q., 2016. Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in south eastern Australia. Climatic Change 138, 85-98.
Wang, B., Liu, D.L., Asseng, S., Macadam, I., Yu, Q., 2015. Impact of climate change on wheat flowering time in eastern Australia. Agricultural and Forest Meteorology 209, 11-21.
