中文版 | English

在结果中检索

CCPortal

浏览/检索结果: 共6条，第1-6条 帮助

已选(0)清除 条数/页：   排序方式：
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：35/0  |  提交时间：2019/10/08
Extreme climate events  Wheat yield  APSIM  Random forest  Hybrid model  
Future climate change likely to reduce the Australian plague locust (Chortoicetes terminifera) seasonal outbreaks 期刊论文
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 卷号: 668, 页码: 947-957
作者:  Wang, Bin;  Deveson, Edward D.;  Waters, Cathy;  Spessa, Allan;  Lawton, Douglas;  Feng, Puyu;  Liu, De Li
收藏  |  浏览/下载：43/0  |  提交时间：2019/10/08
Australian plague locust  Climate change  GCMs  Species distribution models  Outbreak probability  Outbreak area  Seasonal outbreaks  
Impacts of future climate change on water resource availability of eastern Australia: A case study of the Manning River basin 期刊论文
JOURNAL OF HYDROLOGY, 2019, 卷号: 573, 页码: 49-59
作者:  Zhang, Hong;  Wang, Bin;  Liu, De Li;  Zhang, Mingxi;  Feng, Puyu;  Cheng, Lei;  Yu, Qiang;  Eamus, Derek
收藏  |  浏览/下载：39/0  |  提交时间：2019/10/08
GCMs  Xinanjiang (XAJ) model  Climate change  Eastern Australia  Runoff  
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  
Projected changes in drought across the wheat belt of southeastern Australia using a downscaled climate ensemble 期刊论文
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2019, 卷号: 39, 期号: 2, 页码: 1041-1053
作者:  Feng, Puyu;  Liu, De Li;  Wang, Bin;  Waters, Cathy;  Zhang, Mingxi;  Yu, Qiang
收藏  |  浏览/下载：41/0  |  提交时间：2019/10/08
climate change  drought  rSPEI  southeastern Australia  spatio-temporal variations  
Machine learning-based integration of remotely-sensed drought factors can improve the estimation of agricultural drought in South-Eastern Australia 期刊论文
AGRICULTURAL SYSTEMS, 2019, 卷号: 173, 页码: 303-316
作者:  Feng, Puyu;  Wang, Bin;  Liu, De Li;  Yu, Qiang
收藏  |  浏览/下载：29/0  |  提交时间：2019/11/07