Roberto Rudari

The Uncertainty in the Prediction of Flash Floods in the Northern Mediterranean Environment

Abstract Development of an operational flood forecasting system and assessment of forecast uncertainty are the principal topics of this paper. Flood forecasting procedures are developed for a Mediterranean environment. A procedure that uses the Ensemble Prediction System as input for a semidistributed hydrologic model is presented. A rainfall downscaling model is used to bridge the scale gap between numerical weather prediction model output and hydrologic modeling input. The results are illustrated for the November 1994 Piedmont flood.

The credibility challenge for global fluvial flood risk analysis

Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%–40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.

Terrain and Multiple-Scale Interactions as Factors in Generating Extreme Precipitation Events

Abstract The Mediterranean region is often affected by flooding and landslides due to heavy precipitation events. These events have been the subject of specific interest because they represent complex interaction of synoptic-scale upper-level steering flows and local topographic barriers. In the present work, data from a dense network of surface precipitation gauges over northern Italy and a global atmospheric analysis at a coarser scale are combined to develop a multiscale diagnostic model of the phenomenon. Composite maps are formed based on departures from climatology and standard deviation of sea level pressure, 500-hPa geopotential, wind, and water vapor flux. A diagnostic model is built based on the evidence that shows the spawning of secondary mesoscale features in the steering synoptic flow. The mesoscale features draw moisture and energy from local sources and cause extreme precipitation events over adjoining areas. The primary trough system steering the flow often originates in the North Sea and...

Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

Abstract The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012–June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash–Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

Can the behaviour of different basins be described by the same model’s parameter set? A geomorphologic framework

Different basin scales and environments usually are a constrain in the calibration phase of hydrological models’ parameters. In the present work this aspect is faced with regard to the calibration and validation of a geomorphologic semi-distributed rainfall–runoff model at different scales. Simulations of the hydrologic response at basin scale are performed here running the Discharge River Forecast model (Phys. Chem. Earth 25 (7–8) (2000) 665). This model is focused on the efficient description of the drainage system in its essential parts. It uses five parameters: two geomorphologic parameters for the drainage network identification; two kinematic parameters to address the time scale of flood formation on hillslopes and in the channel network; the last parameter takes into account the soil antecedent moisture conditions. Parameters calibration and validation have been carried out using intense rainfall events in different basins and sub-basins in a wide range of sizes belonging to different geographic areas: the Liguria region and the upper part of Po basin.

Flood Damage Assessment Through Multitemporal COSMO-SkyMed Data and Hydrodynamic Models: The Albania 2010 Case Study

Flood damage assessment needs not only the estimation of the flood extent but also the information on the drainage of the floodplain and the dynamics of variables as water depth and velocity. These data might be gathered by exploiting numerical models of water propagation in floodplains, which enable to build flood scenarios in real time if reliable digital elevation models are available. However, a strong limitation for the application of numerical models could be the lack of information regarding the actual flood extent and the dynamics of flooding and receding phases as well as the locations, where water overflowed and the related flood volumes. Inundation extent can be estimated through synthetic aperture radar (SAR) data and, by exploiting the short revisit time of the images provided by the COSMO-SkyMed (CSK) constellation of four satellites, it is possible to monitor also the dynamics of the flood extent. Hence, it comes out the need of a combined use of multitemporal SAR data and numerical models for the purpose of a reliable flood damage assessment. This paper presents the major outcomes of a combined use of a multitemporal series of CSK observations and a hydrodynamic model aiming at the evaluation of damage scenarios for the flood that hit Albania in January 2010. It is shown that by adjusting the outputs of the model to match the flood extent observed by SAR, the hydrodynamic inconsistencies in CSK estimates can be corrected and a reliable assessment of water depth and water velocities can be accomplished.

The OPERA project: EO-based flood risk management in Italy

This paper illustrates some applications of COSMO-SkyMed (CSK) observations for rapid mapping of flooded areas and damages in small to medium size catchments. The results presented here have been obtained within the framework of the project “OPERA — Civil protection from floods” funded by the Italian Space Agency and run by a team of scientific research centres and private companies. The project aims to the systematic evaluation of the added value of the use of Earth Observation techniques into operational flood prediction chains. Due to the specific geomorphology of Italy, the focus is mainly on flash floods on small sized river catchments. Monitoring and modelling processes at proper space-time scales in this environment raise several issues to be solved, compared to applications in larger river basins. Here we address some related to the suitable use of CSK imagery.

A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

In the last decades, physically based distributed models turned out rather promising to achieve the space–time assessment of shallow landslides at large spatial scale. This technical note deals with the application of a physically based stability model named Shallow Landslides Instability Prediction (SLIP), which has been adopted by the Department of National Civil Protection of Italy as a prototype early warning system for rainfall-induced shallow landslides on national scale. The model is used as a main methodology to create space–time shallow landslide susceptibility maps based on a simple deterministic slope-stability approach, combined with high-resolution rainfall information and geographic information system-based geospatial datasets. The safety factor as an index to measure slope instability is modeled as function of topographic, geologic, geotechnical and hydrologic variables. Although the main aim of this work was to prove the operational viability of such model on a nationwide domain and some simplification are adopted at this stage, hind cast tests on some relevant case histories of shallow landslides occurred between October 2009 and October 2011 showed that the model has skill in representing both timing and location of those shallow landslides.

Assimilation of remote sensing observations into a continuous distributed hydrological model: Impacts on the hydrologic cycle

A reliable estimation of soil moisture conditions is fundamental for discharges prediction and, consequently, for flood risk mitigation. Microwave remote sensing can be exploited to estimate soil moisture at large scale. These estimates can be used to enhance the predictions of hydrological models using Data Assimilation techniques and to reduce model uncertainties. This research tested the effects of the assimilation of three different satellite-derived soil moisture products (obtained from ASCAT acquisitions) in a distributed, physically based, hydrological model applied to three small Italian catchments. The products were firstly preprocessed, in order to be to be comparable with the state variables of the model. Subsequently they were assimilated by using different techniques: a simple Nudging applied at both model and satellite scale and the Ensemble Kalman Filter. Finally, observed discharges were compared with the modelled ones. The reanalysis was executed for a multi-year period ranging from July 2012 to June 2014.

Extracting information from remote sensing data for applications to flood monitoring and damage evaluation

In the framework of flood risk, a successful exploitation of the information offered by current satellite remote sensing requires not only accurate and reliable image-analysis methods to extract the desired thematic information, but also the ability to combine this information with physically based models of the observed processes. A multidisciplinary approach combining remote sensing with geophysical sciences, such as, in this case, hydrometeorology, is fundamental. In this paper, we investigate the key issues involved in the exploitation of satellite data with special focus on the phases of the emergency and post-disaster damage assessment. The challenges and the methodological approaches involved in the multidisciplinary combination of image analysis and hydrometeorology are discussed with the purpose of guiding and optimizing the process of information extraction from satellite data according to the requirements of civil protection from floods. Experimental examples of a few relevant case studies are also presented.