## 1 Introduction
The chain includes the Weather Research Forecasting (WRF) model without data assimilation (WRF-OL hereafter) feeding the hydrological model Continuum in the forecasting phase, the automatic system for water detection (AUTOWADE) and the hydraulic model TELEMAC-2D to assess the hydraulics impact running on meteorological observations. Furthermore, in hindcast mode, an enhanced version of the CIMA forecasting chain starting from the meteorological outputs obtained with the WRF model improved with a 3 DVAR data assimilation of radar reflectivity and personal weather stations of Wunderground network (WRF-DA) up to the hydrological forecast with the Continuum model, and hydraulic impacts obtained with TELEMAC-2D was investigated. The chain application uses many kind of observations for the different steps, such as radar reflectivity observations, temperature observations from ground stations, and satellite data from Sentinel, COSMO SkyMed (CSK), and COSMO 2 nd generation (CSG) acquisitions. All the chain step results are directly uploaded and visualized on MyDewetra platform (Dewetra in Figure 1), which was developed by CIMA Research Foundation and is used by the Italian Civil Protection Department for risk management during emergencies [6]. The forecasting chains used in this work enable a step change in how high-impact weather events can be predicted and monitored with a rich portfolio of observational data used and assimilated and a full exploitation of high-performance and cloud computing facilities, built on top of the H2020 project 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). This application is the result of an interdisciplinary effort based on the cooperationof research fields such as meteorology, hydrology, hydraulics, Earth Observation, and ICT (Information and Communications Technology). Figure 1 reports all the steps and the tools used to build the complete chain used partially already in operational mode and in hindcast:  
* Data download and storage services: Supporting the modeling and observational data stream for the subsequent modeling instances. * Meteorological forecasts: The WRF meteorological model, executed on High-Performance Computing (HPC) facilities, provides high-resolution weather forecasts after the assimilation of radar reflectivity and weather station observations. * Hydrological forecast: The fully distributed hydrological model Continuum, executed on cloud computing facilities, provides the peak discharge forecast based on the WRF meteorological input and assimilated Sentinel 1 soil moisture products. * Flooded area detection: The automatic system for water detection (AUTOWADE) exploits satellite acquisitions, along with ad hoc tasks set depending on the meteorological forecasts (Sentinel 1 and COSMO SKYMED) to operationally monitor the flooded areas. * Hydraulic forecast: The TELEMAC-2D hydraulic model, executed on HPC facilities, integrates Continuum forecasts to predict flooded areas. The paper is divided as follows: Section 2 describes the Materials and Methods, including a short case study description and all the model setups used in this work. The results are discussed in Section 3, dividing the operational and the hindcast research phase and, eventually, some concluding remarks about the forecast chain performances are reported in Section 4. Figure 1: Meteo /Hydro forecasting chain workflow.