A Python package for data assimilation in the eWatercycle program – a hydrological framework

The eWaterCycle program provides a collaborative environment for hydrological modelers, developed by the Netherlands eScience Center together with the Delft University of Technology. It aims to build a community of scientists in hydrology who use different programming languages for their specific models. Python is the lingua franca of the eWaterCycle platform and requires no modification to a particular model, making the platform user-friendly and flexible. Therefore, it can readily be applied in other geoscientific models. Currently, the Python data assimilation package includes ensemble-type methods, particle filters, and their variants, which are all sequential data assimilation algorithms. The implementation of techniques related to localization and inflation methods is included in this package. Localization and inflation are effective ways to avoid the collapse of a filter, which happens commonly in high dimensional models. The package gives access to all tunable parameters by configuration files quickly. To evaluate the performance of data assimilation comprehensively, a series of metrics is provided. In addition, the package offers a set of visualization tools to explore the results of data assimilation and the improvement of models.