Streamflow data assimilation for fully coupled atmosphere-surface-subsurface systems

全耦合大气-地表-地下系统的流数据同化

• 批准号: 246188089
• 负责人: Professorin Dr. Sabine Attinger
• 金额: --
• 依托单位: Institut für Umweltwissenschaften und Geographie
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/246188089?language=en
• 关键词: Streamflow; data; assimilation; fully; coupled

The project explores the use and the value of streamflow observations in a data assimilation framework for improving the predictive capability of fully coupled terrestrial systems. Streamflow observations give an integrated response of the hydrological catchment behaviour but they also provide aggregated information of the different hydrological components e.g., groundwater contribution or aggregated soil moisture conditions. The main challenge is to assimilate in a DA scheme data (in our case streamflow) that contain aggregated information on local parameter fields or states. To achieve this goal, the project needs to identify a way to link the different scales via an upscaling/downscaling operation. Several data assimilation tests will be used to identify the best strategy to assimilate streamflow based on scenarios of different complexity generated with TerrSysMP-PDAF. Comparisons and joint experiments with the other projects will be conducted to assess the consistency of the integrated data assimilation framework.

该项目探讨了在数据同化框架中使用径流观测数据以提高完全耦合陆地系统的预报能力的价值。径流观测提供了对水文集水区行为的综合反应，但它们也提供了不同水文组成部分的综合信息，例如地下水贡献或综合土壤水分状况。主要挑战是在DA方案中吸收包含有关本地参数字段或状态的聚合信息的数据(在我们的例子中为Streamflow)。为了实现这一目标，该项目需要确定一种方法，通过扩大规模/缩小规模操作将不同的比例联系起来。将使用若干数据同化试验，根据TerrSysMP-PDAF产生的不同复杂性情景，确定同化径流的最佳战略。将与其他项目进行比较和联合试验，以评估综合数据同化框架的一致性。