Abstract. Satellite-based Earth observations (EO) are an accurate and reliable data source for atmospheric environmental science. Their increasing spatial temporal resolutions, as well the seamless availability over ungauged regions, make them appealing hydrological modeling. This work shows recent advances in use of high-resolution satellite-based EO In a set six experiments, distributed model Continuum is up Po River basin (Italy) forced, turn, by satellite precipitation evaporation, while...

In recent years, continuous improvements have been made in weather forecasting and flood prediction with great benefit from Early Warning Systems (EWSs). Despite the quest for innovation scientific user communities, EWSs remain based mostly on hazard forecast, information possible consequences potential impacts is generally missing. this work, a methodology quantitative real-time impact assessment flash floods presented. The uses multi-model ensemble approach considers soil moisture...

Abstract. Snow models are usually evaluated at sites providing high-quality meteorological data, so that the uncertainty in input data can be neglected when assessing model performances. However, rarely available mountain areas and, practical applications, forcing used to drive snow is typically derived from spatial interpolation of situ or reanalyses, whose accuracy considerably lower. In order fully characterize performances a model, sensitivity errors should quantified. this study we test...

Abstract. Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises displacement. Impact-based forecasting early warning for natural hazards recognized as a step forward disaster risk reduction, thanks to its focus on people, livelihoods, assets at risk. Yet, the majority African not covered any sort system. This article describes setup methodological approach Flood-PROOFS East Africa,...

Abstract. The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality snowpack simulations, with dynamics that strongly affect local regime, especially during melting period. With aim reducing modelling uncertainty, data assimilation techniques are increasingly being implemented for operational purposes. This study aims to investigate performance a multivariate sequential importance resampling – particle filter scheme, designed jointly assimilate several...

Abstract The typical complex orography of the Mediterranean coastal areas support formation so-called back-building mesoscale convective systems (MCS) producing torrential rainfall often resulting in flash floods. As these events are usually very small-scaled and localized, they hardly predictable from a hydrometeorological standpoint, frequently causing significant amount fatalities socioeconomic damage. Liguria, northwestern Italian region, is characterized by small catchments with short...

This paper presents an enhanced probabilistic flood displacement risk assessment methodology. Several techniques have been proposed to estimate the number of people at being displaced triggered due climatic extremes. Among these methods, approach is promising for its quantitative nature and versatility different scales. However, it has so far limited assessing loss housing as sole cause displacement. The methodology addresses this limitation by considering two additional elements beyond...

Abstract. Trustworthy estimates of snow water equivalent and depth are essential for resource management in snow-dominated regions. While ensemble-based data assimilation techniques, such as the Ensemble Kalman Filter (EnKF), commonly used this context to combine model predictions with observations therefore improve performance, these ensemble methods computationally demanding thus face significant challenges when integrated into time-sensitive operational workflows. To address challenge, we...

Floods are among the most destructive natural hazards globally, with Southeast Asia being particularly vulnerable due to socioeconomic and geographical factors. Climate change exacerbates this vulnerability, increasing frequency intensity of flooding events heightening risks millions people critical infrastructures. To address these challenges, disaster risk management is transitioning from traditional hazard-based impact-based forecasting (IBF), which focuses on predicting consequences...

In snow-dominated regions, today’s snow is tomorrow’s water, making reliable estimates of water equivalent (SWE) and depth crucial for resource management. this context, data assimilation a powerful tool to optimally combine models measurements, enhancing accuracy reliability. Ensemble-based techniques like the Ensemble Kalman Filter (EnKF) Particle (PF) are often used but their deployment in real-time applications can make it challenging ensure timely accurate results....

Abstract Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed calibration validation of the water balance flood forecasting. Remotely sensed data easily available on large areas with frequency compatible land cover changes. In this paper, remotely images different types sensor have been utilized as support model MOBIDIC, currently used experimental system forecasting Arno River Basin Authority. Six...

A reliable estimation of soil moisture conditions is fundamental for rivers' discharge predictions, especially in small catchments where flash floods occur. In this context, microwave remote sensing can be exploited to estimate at large scale. These estimates used enhance the predictions hydrological models using data assimilation techniques. Flash flood early warning systems can, thus, improved. This study tested effect three different ASCAT-derived products, processed and distributed...

Abstract This work investigates the impact of high‐resolution digital terrain model (DTM) uncertainties on estimation urban flood losses. Starting from a Light Detection And Ranging (LiDAR)‐derived DTM an area, four representations (raw data, building footprints filled, buildings as waterproof blocks, and different elevation data merged) are used to generate computational mesh run 2D for three inundation scenarios, differing in volumes. The most detailed is obtained by merging with points...

Multi-risk assessments are being increasingly proposed as a tool to effectively support policy-makers in reducing impacts from natural hazards. The complexity of multi-risk requires assessment approaches capable capturing multiple components risk (e.g., different hazards, exposed elements, and dimensions vulnerability) coherent frame reference, while at the same time providing an intuitive entry point allow participation relevant stakeholders. Contributing emerging literature, we carried out...

Abstract Flood forecasting remains a significant challenge, particularly when dealing with basins characterized by small drainage areas (i.e., 10 3 km 2 or lower response time in the range 0.5–10 h) especially because of rainfall prediction uncertainties. This study aims to investigate performances streamflow predictions using two short-term forecast methods. These methods utilize combination nowcasting extrapolation algorithm and numerical weather employing three-dimensional variational...

Abstract The knowledge of snowpack dynamics is critical importance to several real-time applications especially in mountain basins, such as agricultural production, water resource management, flood prevention, hydropower generation. Since simulations are affected by model biases and forcing data uncertainty, an increasing interest focuses on the assimilation snow-related observations with purpose enhancing predictions state. study aims at investigating effectiveness snow multivariable (DA)...

Abstract. The accuracy of hydrological predictions in snow-dominated regions deeply depends on the quality snowpack simulations, whose dynamics strongly affects local regime, especially during melting period. With aim reducing modelling uncertainty, data assimilation techniques are increasingly being implemented for operational purposes. This study aims at investigating performance a multivariate Sequential Importance Resampling – Particle Filter scheme designed to jointly assimilate several...

A reliable estimation of soil moisture conditions is fundamental for discharges prediction and, consequently, flood risk mitigation. Microwave remote sensing can be exploited to estimate at large scale. These estimates used enhance the predictions hydrological models using Data Assimilation techniques and reduce model uncertainties. This research tested effects assimilation three different satellite-derived products (obtained from ASCAT acquisitions) in a distributed, physically based,...

The reliable estimation of soil moisture in space and time is fundamental importance operational hydrology to improve the forecast rainfall-runoff response catchments and, consequently, flood predictions. Nowadays several satellite-derived products are available can offer a chance hydrological model performances especially environments with scarce ground based data. goal this work test effects assimilation different satellite distributed physically model. Among currently platforms, four...

Abstract. The characterization of the hydro-meteorological extremes, in terms both rainfall and streamflow, estimation long-term water balance indicators are essential issues for flood alert management services. In recent years, simulations carried out with meteorological models becoming available at increasing spatial temporal resolutions (both historical reanalysis near-real-time hindcast studies); thus, these datasets can be used as input distributed hydrological to drive a long-period...

Abstract. Every year Africa is hit by extreme floods which, combined with high levels of vulnerability and increasing population exposure, often result in humanitarian crises displacement. Impact-based forecasting early warning for natural hazards recognized as a step forward disaster risk reduction, thanks to its focus on people, livelihoods assets at risk. Yet, the majority African not covered any sort system. This article describes setup Flood-PROOFS East Africa, an impact-based riverine...

Abstract. A valid tool for the retrieving of turbulent fluxes that characterize surface energy budget is constituted by remote sensing land states. In this study sequences satellite-derived observations (from SEVIRI sensors aboard Meteosat Second Generation) Land Surface Temperature have been used as input in a data assimilation scheme order to retrieve parameters describe balance at ground Tuscany region, central Italy, during summer 2005. parsimonious 1-D multiscale variational procedure...