## 4 Concluding Remarks
Eventually, a further experiment was performed in hindcast mode to evaluate the value added of a forecasting chain including data assimilation in the meteorological part and to assess if it is possible to obtain a hydraulic impacts map not only during the monitoring phase but also in the forecasting one. Thus, the Flood-PROOFS deterministic hydrological forecast and the TELEMAC-2D forecast were performed with the WRF-DA simulation (instead of using only observations as in during the monitoring phase). This experiment showed that the data assimilation allows to obtain further forecast improvement, especially in terms of rainfall overestimation reduction, and the use of TELEMAC-2D with simulation could also help highlight the most hit areas during the forecasting phase, not only during the monitoring one. Moreover, on a set of basins located in Sicily and Calabria, the performances obtained with the WRF-OL simulation and the WRF-DA hindcast experiment as input to the hydrological model were compared in terms of peak flows with respect to a benchmark simulation run using the meteorological observations to feed the hydrological model. Both the configurations give good results, and in some sections the WRF-DA configuration was able to improve the forecast, while in some others, a slight overestimation still persists in both configurations. Such a complex chain was run on this use case as an example of how the cooperation of different research fields such as meteorology, hydrology, hydraulics, Earth Observations, and ICT can enable a step change in how high-impact weather events can be predicted and monitored with a rich portfolio of observational data assimilated and the full exploitation of high performance and cloud computing facilities. In this work, the complete chain is tested on a long-lived event allowing to deeply explore instruments and possible improvements both in the forecasting and monitoring phase. Future works will be devoted to also develop a meteo-hydrological chain for nowcasting procedures to better improve the forecast and for very localized (in time and space) intense events. meteo-hydrological chain. Conceptualization, A.P. ([PERSON]), S.P. and S.G.; methodology, A.P. ([PERSON]); software, L.P., G.S., F.P., G.F. and A.P. ([PERSON]); validation, R.M., V.M. and E.F.; formal analysis, M.L., M.M. and F.S. ; investigation, M.L. and L.P.; resources, L.F. and A.P. ([PERSON]); data curation, G.S. and R.M. ; writing--original draft preparation, M.L., M.M., S.G. and L.P.; writing--review and editing, V.M., A.P., ([PERSON]) and S.P. ; visualization, G.F., E.F.  
and A.P. ([PERSON]); supervision, A.P. ([PERSON]) and L.F.; project administration, A.P. ([PERSON]); funding acquisition, A.P. ([PERSON]). All authors have read and agreed to the published version of the manuscript. This research was funded by E-SHAPE H2020 project [[https://cordis.europa.eu/project/id/820852](https://cordis.europa.eu/project/id/820852)]([https://cordis.europa.eu/project/id/820852](https://cordis.europa.eu/project/id/820852)) (accessed on 11 December 2022) Grant agreement ID: 820852. The data used in this work to present the results are stored in CIMA Research Fundation archives, and they can be available upon request to the authors only for research purposes. The meteorological model outputs are publicly available upon request to the authors. The work has been carried out in the framework of the contract between CIMA Foundation and the National Italian Department of Civil Protection and the H2020 LEXIS [[https://cordis.europa.eu/project/id/825532](https://cordis.europa.eu/project/id/825532)]([https://cordis.europa.eu/project/id/825532](https://cordis.europa.eu/project/id/825532)) (accessed on 11 December 2022). The authors declare no conflict of interest.