Showing results 20 to 39 of 47
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Issue Date | Title | Author(s) |
2017-06-01 | Incorporating grain legumes in cereal-based cropping systems to improve profitability in southern New South Wales, Australia | Xing, H; Liu, DL; Li, G; Wang, B; Anwar, MR; Crean, J; Lines-Kelly, R; Yu, Q |
2019-09-15 | Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia | Feng, P; Wang, B; Liu, DL; Waters, C; Yu, Q |
2022-09-01 | Individual and Coupled Effects of Future Climate and Land Use Scenarios on Water Balance Components in an Australian Catchment | Zhang, H; Wang, B; Liu, DL; Leslie, LM; Shi, L; Zhang, M; Yu, Q |
2023-09-01 | Integrating machine learning and environmental variables to constrain uncertainty in crop yield change projections under climate change | Li, L; Zhang, Y; Wang, B; Feng, P; He, Q; Shi, Y; Liu, K; Harrison, MT; Liu, DL; Yao, N; Li, Y; He, J; Feng, H; Siddique, KHM; Yu, Q |
2020-08-01 | Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia | Feng, P; Wang, B; Liu, DL; Ji, F; Niu, X; Ruan, H; Shi, L; Yu, Q |
2019-07-01 | Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia | Feng, P; Wang, B; Liu, DL; Yu, Q |
2019-10-01 | Modelling and evaluating the impacts of climate change on three major crops in south-eastern Australia using regional climate model simulations | Wang, B; Liu, DL; Evans, JP; Ji, F; Waters, C; Macadam, I; Feng, P; Beyer, K |
2023-09-01 | Modelling interactions between cowpea cover crops and residue retention in Australian dryland cropping systems under climate change | He, Q; Liu, DL; Wang, B; Cowie, A; Simmons, A; Waters, C; Li, L; Feng, P; Li, Y; Voil, PD; Huete, A; Yu, Q |
2017-10-01 | Modelling wheat yield change under CO<inf>2</inf> increase, heat and water stress in relation to plant available water capacity in eastern Australia | Wang, B; Liu, DL; Asseng, S; Macadam, I; Yu, Q |
2018-08-01 | Multi-model ensemble projections of future extreme heat stress on rice across southern China | He, L; Cleverly, J; Wang, B; Jin, N; Mi, C; Liu, DL; Yu, Q |
2016-06-27 | Multi-model ensemble projections of future extreme temperature change using a statistical downscaling method in south eastern Australia | Wang, B; Liu, DL; Macadam, I; Alexander, LV; Abramowitz, G; Yu, Q |
2021-07-21 | Optimizing Sowing Date and Planting Density Can Mitigate the Impacts of Future Climate on Maize Yield: A Case Study in the Guanzhong Plain of China | Xu, F; Wang, B; He, C; Liu, DL; Feng, P; Yao, N; Zhang, R; Xu, S; Xue, J; Feng, H; Yu, Q; He, J |
2020-01-01 | Optimizing sowing window and cultivar choice can boost China’s maize yield under 1.5 °C and 2 °C global warming | Huang, M; Wang, J; Wang, B; Liu, DL; Yu, Q; He, D; Wang, N; Pan, X |
2023-12-01 | Performance of potential evapotranspiration models across different climatic stations in New South Wales, Australia | Shi, L; Wang, B; Liu, DL; Feng, P; Cleverly, J; Li, L; Zhang, G; Yu, Q |
2023-06-30 | Probabilistic assessment of drought impacts on wheat yield in south-eastern Australia | Xiang, K; Wang, B; Liu, DL; Chen, C; Waters, C; Huete, A; Yu, Q |
2019-02-01 | Projected changes in drought across the wheat belt of southeastern Australia using a downscaled climate ensemble | Feng, P; Liu, DL; Wang, B; Waters, C; Zhang, M; Yu, Q |
2019-01-01 | Propagation of climate model biases to biophysical modelling can complicate assessments of climate change impact in agricultural systems | Liu, DL; Wang, B; Evans, J; Ji, F; Waters, C; Macadam, I; Yang, X; Beyer, K |
2020-11-01 | Quantifying future drought change and associated uncertainty in southeastern Australia with multiple potential evapotranspiration models | Shi, L; Feng, P; Wang, B; Liu, DL; Yu, Q |
2018-11-01 | Quantifying sources of uncertainty in projected wheat yield changes under climate change in eastern Australia | Wang, B; Liu, DL; Waters, C; Yu, Q |
2020-09-15 | Quantifying the impacts of pre-occurred ENSO signals on wheat yield variation using machine learning in Australia | Wang, B; Feng, P; Waters, C; Cleverly, J; Liu, DL; Yu, Q |