This session focuses on data assimilation across terrestrial compartments, for example for integrated hydrological models or earth system models. In the context of integrated hydrological models or earth system models, it is important to consider the influence of measurements in one compartment on predictions of states and fluxes in other compartments. For example, leaf area index data not only provide information on vegetation status, but are also linked to soil moisture content of the unsaturated zone. Another example is given by soil moisture data, which can help to improve the characterization of the soil profile state, the aquifer underneath, the vegetation and the atmospheric boundary layer; or snow, which helps to improve the prediction of river discharge. To fully explore the value of these data for specific predictions, an integrated modelling framework in combination with a data assimilation framework across terrestrial system compartments is needed. On the other hand, efficient data assimilation approaches are needed in order to allow predictions in a large and complex modeling system.

We welcome contributions on the development and applications of data assimilation systems involving models which aim at including multiple compartments of the terrestrial system like atmosphere and/or vegetation and/or soil and/or snow and/or groundwater and/or surface water. Contributions could focus on off-line tests, operational predictions, parameter or bias estimation, data value or design of monitoring networks. In addition, case studies which include a precise evaluation of the data assimilation performance are of high interest for the session.