A benchmark study on remotely sensed data assimilation for water budget estimation over different hydroclimatic areas

Advances in remote sensing and data assimilation have provided a valuable instrument that helps scientists acquire information on water resources and the water budget, offering thus timely information on the existence of extreme conditions like prolonged draught or flood events. Aim of this work is to evaluate the potential of remotely sensed information to describe the water budget in basins over different hydroclimatic conditions. Thus, a benchmark study of remotely sensed data assimilation process is presented and applied in three different basins located in Europe, covering a wide range of hydroclimatic conditions. The methodology evaluates the water budget at the monthly time step for a ten-year period, i.e. from 2010 to 2020. The assimilation process comprised remotely sensed information from downscaled soil moisture from the Soil Moisture Ocean Salinity (SMOS) product, and precipitation from the Global Precipitation Measurement mission, using the Integrated Multi-satellitE Retrievals (GPM-IMERG) data, together with MODerate Imaging Spectroradiometer (MODIS) evapotranspiration and river gauge measurements. Comparison of the acquired water budget with the downscaled Gravity Recovery and Climate Experiment Total Water Storage anomaly (GRACE-TWSA) data indicated that in all examined basins remotely sensed information can serve as a meaningful source of information for water budget estimates, even in cases where little or no ground monitoring data is available. Furthermore, our results brought out the strengths and limitations of remotely sensed data assimilation in different hydroclimatic settings and accentuated future perspectives.