The added value of remote sensing products in constraining hydrological models

A typical calibration of a hydrological model relies on the availability of discharge data, which is, however, not always present and not the largest outgoing flux in many parts of the world. At the same time, more remote sensing products are becoming available that can aid in deriving model parameters and model structures, but also more traditional analytical approaches (e.g. the Budyko framework) can still be of high value. In this research, models are constrained in a step-wise approach with different combinations of remote sensing data and/or analytical frameworks. For example, the temporal resolution can be a driving principle leading to the formulation of a set of constraints. More specific, in a first step the Budyko framework can be used as a means to filter out solutions that cannot reproduce the long-term dynamics of the system. In the following steps, remote sensing data of respectively GRACE (monthly resolution), NDII (16-day resolution) and LSA-SAF evaporation (daily) can lead to final parameterizations of a model. Nevertheless, the choice of these driving principles, the applied order of constraints and the strictness of the applied boundaries of the constraints, will lead to varying solutions. Therefore, variations in these factors, and thus different combinations with different remote sensing products, should lead to an enhanced understanding of the strengths and weaknesses the approaches have with regard to finding optimal parameter sets for hydrological models.