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Incorporating machine learning with biophysical model can improve the evaluation of climate extremes impacts on wheat yield in south-eastern Australia 期刊论文
AGRICULTURAL AND FOREST METEOROLOGY, 2019, 卷号: 275, 页码: 100-113
作者:  Feng, Puyu;  Wang, Bin;  Liu, De Li;  Waters, Cathy;  Yu, Qiang
收藏  |  浏览/下载：38/0  |  提交时间：2019/10/08
Extreme climate events  Wheat yield  APSIM  Random forest  Hybrid model  
Designing wheat ideotypes to cope with future changing climate in South-Eastern Australia 期刊论文
AGRICULTURAL SYSTEMS, 2019, 卷号: 170, 页码: 9-18
作者:  Wang, Bin;  Feng, Puyu;  Chen, Chao;  Liu, De Li;  Waters, Cathy;  Yu, Qiang
收藏  |  浏览/下载：30/0  |  提交时间：2019/10/08
Virtual cultivars  Optimal sowing date  APSIM  High yield  Climate change  Wheat ideotypes  
Propagation of climate model biases to biophysical modelling can complicate assessments of climate change impact in agricultural systems 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 卷号: 39, 期号: 1, 页码: 424-444
作者:  Liu, De Li;  Wang, Bin;  Evans, Jason;  Ji, Fei;  Waters, Cathy;  Macadam, Ian;  Yang, Xihua;  Beyer, Kathleen
收藏  |  浏览/下载：124/0  |  提交时间：2019/10/08
APSIM  bias correction  bias propagation  bio-physical crop model  NARCliM  rainfall intensity  rainfall probability  RCMs  wheat cropping system