L19. Recent advances in hydrological remote sensing and applications in model calibration and prediction

Remotely sensed observations from airborne and satellite instruments are becoming more important tools to understand the hydrological and biophysical processes. Also, there is a growing interest in optimally integrating the remotely sensed observations into hydrologic models to improve the spatial representation of land surface processes and their predicting capabilities. The goal of this session is to highlight recent advances in remote sensing of hydrological processes and states and to promote innovative methods to integrate them in conventional modeling frameworks. Areas of interest include; innovations in retrieval algorithms, novel blending of multi-sensor products, new applications of existing data to various processes and integration of remotely sensed observations into models via calibration and prediction updating schemes. Furthermore, studies that address land-atmosphere feedbacks and quantification of their results (e.g., drought, flood and heat waves) via remote sensing are particularly welcome.