中科院国际杰出学者报告会暨水文监测预报国际研讨会   

　　时间：2016年5月10日（周二） 

　　地点：中科院地理科学与资源研究所，地理科学馆411会议室 

　　9:30—10:00    开幕式 

　　10:00—10:30   合影、茶歇 

　　10:30—11:30   2016年度中国科学院国际杰出学者讲席报告 

　　报告题目：Seasonal hydrologic predictability: Sources and limitations 

　　报告人简介：Dennis Lettenmaier教授，2016年度中国科学院国际杰出学者称号获得者。现任美国加州大学洛杉矶分校（UCLA）杰出教授，同时是美国国家工程院院士，美国地球物理联合会会士、美国气象学会会士以及美国科学促进会会士。研究领域包括水文模拟预报、水文-气象相互作用、水循环变化等，是国际水文气象学界的旗帜人物。曾担任Journal of Hydrometeorology 创刊主编，Water Resources Research副主编，美国地球物理联合会水文领域主席，全球能量与水循环协调观测计划科学咨询委员会主席，并先后荣获Walter L. Huber奖章，AGU水文科学奖，Walter Orr Roberts Lecturer, Robert E. Horton Lecturer, Walter B. Langbein Lecturer等多项荣誉。作为国际顶级水文科学家和水文气象研究领域杰出领导者，以其创新工作和卓越贡献重塑了国际水文学的格局，引领了现代水文学的前沿发展方向。 

　　报告摘要：I review a set of experiments designed to understand the extent to which seasonal hydrologic prediction skill is controlled by hydrologic initial conditions as contrasted with climate forecast skill.  Our work shows that at short lead times (typically up to a few months), hydrologic forecast skill is mostly controlled by hydrologic initial conditions (primarily soil moisture and where and when relevant, snow water storage), but at longer lead times, climate forecast skill dominates. Unfortunately, aside from a few special situations, climate forecast skill for lead times beyond about a month is minimal. Therefore, for practical purposes, hydrological initial conditions are the primary source of hydrological forecast skill.  This is the premise of the widely used Ensemble Streamflow Prediction (ESP) method.  I also investigate barriers to the use of seasonal hydrological forecasts in water resource systems operation.  I review work approximately a decade ago by Maurer, which casts light on the potential for improved reservoir system operations through improved forecasts as a function of the usable reservoir storage relative to the mean annual inflow, relative to the simplest forecast (climatology). As a case study, I evaluate hydroclimatic and hydrologic forecast skill (or lack thereof) in winter, 2016 across the Western U.S. during one of the strongest El Nino events of the historic record, which by past estimates should have been the basis for accurate seasonal climate forecasts. 

　　11:30—13:30 午餐 

　　13:30—17:30 特邀报告 

　　主持人：汤秋鸿 研究员 

　　陆地水循环及地表过程院重点实验室 

　　2016-05-05