报告题目：Advances in hydrological modelling at the catchment scale
报告地点：闵行校区河口海岸大楼A304
主办单位：华东师范大学地理科学学院、地理信息科学教育部重点实验室
报告人简介：
Dmitri Kavetski，澳大利亚阿德莱德大学教授。主要从事水文环境模型的贝叶斯推断与预测、水文和环境建模、环境数值计算方法与统计分析等方面研究，包括地表和地下水模型、降雨径流和积雪模型等，与CEMAGREF、美国国家大气研究中心（NCAR）等多家研究机构开展了国际合作。在 Water Resources Research, Journal of Hydrology, Hydrological Processes等发表学术论文60余篇，曾获水文领域顶级期刊Water Resources Research编辑推荐奖（2011），担任Water Resources Research副主编（2010-2014）。
报告内容简介：
Hydrological models are widely used as scientific tools to improve our understanding of the water cycle, and as engineering tools to help anticipate events such as floods, future water availability, and so forth. This talk will review advances in rainfall-runoff development and application, including: (i) the use of flexible models to capture dominant hydrological mechanisms in the catchment of interest, (ii) the use of probabilistic methods to characterise the uncertainty in streamflow predictions, including under "non-stationary" conditions. Results presented will include outcomes from the collaboration with the Australian Bureau of Meteorology on seasonal streamflow forecasting.
主讲人：Dmitri Kavetski 教授
主持人：孙勋 研究员
报告时间: 2019年11月07日 13:30-14:30报告地点：闵行校区河口海岸大楼A304
主办单位：华东师范大学地理科学学院、地理信息科学教育部重点实验室
报告人简介：
Dmitri Kavetski，澳大利亚阿德莱德大学教授。主要从事水文环境模型的贝叶斯推断与预测、水文和环境建模、环境数值计算方法与统计分析等方面研究，包括地表和地下水模型、降雨径流和积雪模型等，与CEMAGREF、美国国家大气研究中心（NCAR）等多家研究机构开展了国际合作。在 Water Resources Research, Journal of Hydrology, Hydrological Processes等发表学术论文60余篇，曾获水文领域顶级期刊Water Resources Research编辑推荐奖（2011），担任Water Resources Research副主编（2010-2014）。
报告内容简介：
Hydrological models are widely used as scientific tools to improve our understanding of the water cycle, and as engineering tools to help anticipate events such as floods, future water availability, and so forth. This talk will review advances in rainfall-runoff development and application, including: (i) the use of flexible models to capture dominant hydrological mechanisms in the catchment of interest, (ii) the use of probabilistic methods to characterise the uncertainty in streamflow predictions, including under "non-stationary" conditions. Results presented will include outcomes from the collaboration with the Australian Bureau of Meteorology on seasonal streamflow forecasting.