Large scale surface water and snow cover extent dynamics and error quantification as input for WaterGAP Global Hydrology Model (WGHM)

实现研究单位（RU）总体目标的一个关键先决条件是提供关于水和积雪覆盖范围的高质量地球观测（EO）产品，包括适合纳入C/DA方法的不确定性信息。在该研究项目的第一阶段，重点是随后为两个现有的卫星地球观测时间序列产品（德国航天中心全球水包和德国航天中心全球雪包）开发关于水和雪覆盖的可靠的不确定性信息，以及通过C/DA方法将其纳入水文模型WaterGAP。在第二阶段，我们将对开发的方法进行处理，为RU提供全球范围内所需的数据集。同时，我们将专注于通过开发和实施新的数据融合策略来提高水范围估计的准确性，假设模型输出和基于EO的数据集都可以增强，从而有助于更好地了解全球淡水系统。

A key prerequisite for achieving the overarching goal of the research unit (RU) is the availability of high quality Earth observation (EO) products on water and snow cover extents including uncertainty information that are suitable for integration into the C/DA approach. Within the first phase of the research project, the foci were on subsequent development of sound uncertainty information for water and snow cover for two existing satellite EO time series products (DLR Global WaterPack and DLR Global SnowPack), as well as their integration via C/DA approaches into the hydrological model WaterGAP. Within the second phase, we will conduct the processing of the developed approaches to provide the RU with required datasets on global scale. Simultaneously, we will focus on improving the accuracy of the water extent estimation by developing and implementing new data fusion strategies, following the hypothesis that both, model outputs and EO based datasets can be enhanced, and thus contribute to a better understanding of the global freshwater system.