Developing an Ensemble Kalman Filter calibration and data assimilation (EnC/DA) approach for integrating geodetic and remote sensing data into a global hydrological model

项目P1的主要目标是开发和实施一种有效的集成卡尔曼滤波器，用于将数据同化和参数校准与水文建模相结合。第一阶段的重点是同时整合多个数据集并创建观测操作员；开发和研究了基于集成的模型参数标定。在建立工作环境之后，第二阶段的工作将转向完善我们的方法，比较整个RU的方法，开发包括参数校准在内的全球同化系统，并创建新的全球尺度水通量和储水量的定量描述，包括不确定性的表征。

Main objective of project P1 is the development and implementation of an effective Ensemble Kalman Filter for the integration of data assimilation and parameter calibration with hydrological modelling. Foci within the first phase were simultaneously integrating multiple data sets and creating observation operators; and developing and investigating the ensemble-based model parameter calibration. After setting up a working environment, work in the 2nd phase will turn towards refining our method, comparing approaches across the RU, developing a global assimila-tion system including parameter calibration, and creating new quantitative descriptions of global-scale water fluxes and storages, including a characterization of the uncertainty.