Figure 1 . Summary of the literature review on 62 studies that incorporated RS datasets for parameter estimation in hydrological models (see Table S1 in Supporting Information). (a) Classification of publications based on the drainage area of study sites (an average value was considered for publications that used multiple study sites); (b) distribution of studies based on the calibration variable; (c) geographical distribution of study sites; (d) number of publications per year; (e) number of RS products involved in calibration (in black), number of independent calibration variables (in blue), and number of model outputs evaluated (in red); (f) classification of models based on their spatial configuration; (g) model type; and (h) use of RS data

Aims and Contributions of this paper

Our study addresses major knowledge gaps identified in the previous literature review in the context of RS-based calibration of hydrological models. Firstly, most of the studies analyzed two or less variables (Figure 1e). Here, we used RS observations of a large number of variables for model calibration, namely soil moisture, evapotranspiration, terrestrial water storage, flood extent and river water levels, and thus move beyond the contributions of RS for improving only discharge estimates. By simultaneously looking at different variables, we also move towards an improved representation of the water cycle as a whole, enhancing our ability to identify model limitations and inconsistencies. Furthermore, most studies to date focused on European, temperate watersheds (Figure 1c), which largely differ from tropical basins in terms of hydroclimatic characteristics and river-wetland interactions. In this context, large-scale, coupled hydrologic-hydrodynamic models have faced major developments in recent years (Yamazaki et al 2011, Paiva et al 2013, Fleischmann et al 2020), but to our knowledge the complementarity of hydrologic (soil moisture, evapotranspiration, terrestrial water storage) and hydrodynamic (flood extent and river water level) RS observations for model calibration has not yet been addressed in the literature. Here we present a study case in a tropical basin with extensive floodplains in the Amazon with a state-of-the-art coupled hydrologic-hydrodynamic model, which together with the previously mentioned advances provide important contributions to the growing literature of RS-based calibration of hydrological models.