## 4 Conclusions  
Hydrological models have expanded from their traditional role in water resource management and are becoming increasingly useful tools for nowcasting and forecasting natural disasters such as droughts and floods and for the planning of measures against impacts of climate change, wildfires and landslides. One of the main obstacles while simulating hydrological processes is the lack of sufficient ground observations to calibrate and validate the models. With the increasing information offered from remote sensing observations, these models can be improved, provided that remote sensing data are consistent with the spatial and temporal scales required for these hydrological predictions. The present work evaluates GRACE TWSA at an enhanced spatial representation, i.e., from 1\({}^{\circ}\) to 0.1\({}^{\circ}\), developing a simple yet reliable approach and a suitable output to be used as a constraining parameter in hydrological models. The methodology is based on a regression formula with a residual correction algorithm. A single hydrological dataset, i.e., GPM IMERG providing daily precipitation retrievals at 0.1\({}^{\circ}\), was evaluated for its downscaling ability of the GRACE TWSA, also considering the time lags between the changes in Total Water Storage and precipitation. The residual correction improved the consistency of the original and downscaled TWSA. The GRACE-FO period was used to develop the downscaling approach, and the methodology was tested computing the pixel-wise regression formula in two Water Districts of Greece (Thrace and Thessaly) and was found to improve the TWSAestimates compared to modeled TWSA from two independent datasets, for the period 2005 to 2015, in all examined metrics. Since GRACE TWSA has been mainly used for large basins, the simple downscaling technique presented in this work may prove to be useful for the applicability of GRACE data at finer scales.  
Supplementary material of the present work comprises the list of GRACE-FO dates, the dataset used for verification of the presented methodology and the downscaled GRACE-FO TWSA for Greece in Geotiff format. Supplementary Materials are available online at [[https://www.mdpi.com/article/10.3390/rs13245149/s1](https://www.mdpi.com/article/10.3390/rs13245149/s1)]([https://www.mdpi.com/article/10.3390/rs13245149/s1](https://www.mdpi.com/article/10.3390/rs13245149/s1)), Table S1: Verification of downscaling methodology and multilayer Geotiff titled GREEC_TWSA.  
Conceptualization, A.G. and V.L.; methodology, N.K. and A.G.; software, A.G.; validation, A.G.; formal analysis, N.K. and A.G.; investigation, A.G. and V.L.; resources, A.G.; data curation, A.G. and N.K.; writing--original draft preparation, A.G.; writing--review and editing, A.G., N.K. and V.L.; visualization, A.G. and N.K.; supervision, V.L. and A.G.; project administration, A.G.; funding acquisition, A.G. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the EU project titled: WATERLINE project id CHIST-ERA-19-CES-006.  
Not applicable.  
The GPM IMERG dataset ([PERSON] et al., 2019) used in the present work was accessed from: [[https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/GPM_3](https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/GPM_3) IMERGM.06/]([https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/GPM_3](https://gpm1.gesdisc.eosdis.nasa.gov/data/GPM_L3/GPM_3) IMERGM.06/), access date 30 June 2021. The GRACE datasets ([PERSON], 2021) were accessed from: [[https://podaac-tools.jpl.nasa.gov/drive/files](https://podaac-tools.jpl.nasa.gov/drive/files)]([https://podaac-tools.jpl.nasa.gov/drive/files](https://podaac-tools.jpl.nasa.gov/drive/files)), access date 25 June 2021.  
Authors would like to thank the anonymous reviewers for their constructive comments that considerably improved this work.  
The authors declare no conflict of interest.