Giorgio Boni

. Natural hazard disasters recovery has been addressed in the literature by different sectoral perspectives and scientific communities. Nevertheless, studies providing holistic approaches to recovery, integrating reconstruction procedures and socio-economic impacts, are still lacking. Furthermore, recovery has been only marginally explored from a pre-disaster perspective, in terms of planning and actions for better recovery before disasters occur. This paper provides a critical review of existing literature and guidelines on disaster recovery with the twofold aim of identifying current gaps and providing the layout to address multi-hazard recovery planning tools for decision-making. Disaster recovery literature is investigated in the paper by focusing on: the definition of the recovery phase and its separation or overlapping with other disaster risk management phases; the different destinations and goals that an urban system follows through recovery pathways; the requirements to implement a holistic resilience-based recovery roadmap; the challenges for shifting from single hazard to multi-hazard recovery approaches; the available recovery planning tools for optimal investment decision-making to increase physical assets resilience. Finally, the current challenges in multi-risk recovery planning are discussed. This review can be a ground basis for new research directions to help stakeholders in decision-making and optimise their pre-disaster investments to improve the urban system's recoverability.

As part of the Copernicus Programme, Sentinel 1 (S1) synthetic aperture radar (SAR) mission represents a unique monitoring tool whose potentialities for hydrological risk mitigation need to be evaluated. To this aim, S1-A derived soil moisture maps with high spatial resolution (100 m) and moderate temporal resolution (12 days) were assimilated within a time-continuous, spatially-distributed, physically-based hydrological model (Continuum) with the specific objective to evaluate the impact on discharge predictions and (flash) flood modelling. A Nudging assimilation scheme was chosen for the DA experiment due to its computational efficiency, particularly useful for operational applications. Results were evaluated in the Orba River catchment (Italy) in the time period October 2014 — November 2016, corresponding to the first two years of activity of the S1-A mission.

The occurrence of a disaster can significantly affect the functionality of an urban system, by causing a series of direct and indirect impacts on different sectors and infrastructures. UNDRR, in its definition of ‘resilience’, stresses the significance of preserving and restoring the basic structures and functions of a system through risk management, to support it in recovering from the effects of a hazard in a timely and efficient manner. Indeed, after the occurrence of a disaster, a minimum set of structures and functions have to be in place to guarantee the system's adequate operation and allow the urban system to begin the recovery process.This research develops and applies the concept of the ‘basic minimum urban system’ (BMUS), as the subset of physical assets of the urban system to be preserved in order to ensure continuing recovery efforts after a disaster. The BMUS must be determined in accordance with some defined criteria that indicate the relative socio-economic worth of the various assets and the significance of their contribution to the urban system's performance. When the urban system is exposed to multiple and potentially interacting (such as cascading, consecutive, compound, etc.) risks, the assets' contribution to the system's ability to deal with these complex multi-risk conditions needs to be considered and integrated into the BMUS determination. In light of this, the goal of this work is to establish a methodological framework that combines participatory planning techniques (such as Delphi, fuzzy cognitive mapping, etc.) with quantitative data (like GDP, demography, etc.) analysis to model the urban system and ultimately identify its most crucial components and their interdependencies as the BMUS. Since an urban area's characteristics and identity have a significant impact on the determination of its important physical assets, the relevance of a certain physical asset to be included in the BMUS may differ from one urban system to another. As a result, the final suggested approach must be able to provide a broad framework that takes into account the unique characteristics and requirements of the urban system and its inhabitants. In this study, incorporating local knowledge for recognizing and representing distinctive characteristics of the urban area in the analysis is accomplished through stakeholders' involvement through a participatory method.As a result, several indicators are developed to assess the significance of urban system components in a multi-risk environment exposed to earthquakes and floods, with a focus on improving the urban system's ability to recover from disasters. These indicators are designed to evaluate the relative socio-economic importance of various buildings and urban forms. Indicators are generated in two complementary approaches: 1) participatory with involving stakeholders to illustrate the various interdependencies (physical, functional, etc.) among urban system functions and 2) analysis of quantitative physical and socio-economic data that characterize the urban system and its constituent parts at three different spatial scales (e.g., macro, meso, micro). The developed indicators are tentatively tested for the Sanremo municipality of the Liguria region (Italy). With the aim of increasing ex-post recoverability, decision-makers could use these indicators as a basis to optimize their ex-ante investment.  

In this paper we investigate the double bounce enhancement due to standing water in flooded agricultural fields to assess the capability of an X-band radar to recognize the presence of floodwater under vegetation. The investigation was carried out by analyzing a polarimetric and multifrequency SAR dataset (COSMO-SkyMed, Alos-2, Radarsat-2) collected over the Vercelli district in North Italy, characterized by a widespread and intense cultivation of rice crop, were the fields were routinely artificially flooded and dried according to the agricultural practice. The investigation demonstrated that in July, when rice is well developed, high backscatter in X-band was observed in fields were the L-band polarimetric data recognized the double bounce return. The presence of a double bounce scattering enhancement at X-band was then established. At C-band the dihedral type of return was not clearly recognized because of the smaller incidence angle of Radarsat-2 acquisitions.

<p>According to UNDRR terminology, resilience is the ability of a system, community, or society exposed to hazards to resist, absorb, accommodate, adapt to, transform, and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions through risk management. Damages to urban physical structures caused by consequent and/or interacting natural hazards create a complex and challenging post-disaster environment. Many functions provided by the affected structures are disrupted and consequently, systemic processes, including recovery, are impaired and delayed. Despite its criticality, recovery is the less explored phase in the disaster management framework, specifically from a pre-disaster perspective, in terms of planning and actions for better recovery before disasters occur.</p> <p>This work presents a modeling framework to determine which infrastructures and with what level of functionality in an urban system, after a disaster, can ensure that the system can efficiently go through the path of the recovery process. The final goal is to increase the overall resilience of the urban settlements from multiple hazards. This research question is addressed considering (i) multiple functionalities (e.g. economic, social, health, etc.) of the territorial elements; (ii) the potential interactions and interdependencies among them as well as the overall functionality of the system; (iii) a multi-hazard risk perspective, considering both flood and seismic hazard scenarios; (iv) pathway and goal of the recovery process able to ensure not only the prioritization of recovery interventions but also the improvement of system resilience according to a ‘build back better’ perspective.</p> <p>First, the main results of a critical review of existing literature and guidelines on disaster recovery are provided with the twofold aim of identifying current gaps and providing the layout to develop a multi-hazard framework for decision-making and investments optimization in pre-disaster recovery planning. As a first step of the framework definition, the essential urban structures that contribute to economic, social, cultural, demographic, environmental, governmental, and community functions, and their interdependencies are identified. Then, the contribution of each structure to the overall functionality of the urban system is determined using quantitative data and qualitative data. Stakeholders’ priorities and needs for going through a good recovery are also integrated into the approach thanks to structured stakeholder-engagement activities based on a participatory approach. The influence of the hazards on the system is evaluated by imposing multi-hazard risk scenarios of floods and earthquakes, considering various levels of interaction between them (hazard, exposure, vulnerability, risk, DRR measures).</p> <p>The developed modeling framework represents the basis for the implementation of a quantitative tool for decision-makers to find and plan the optimal investment alternatives to increase the system’s resilience under a limited budget.</p> <p> </p>

<p>Liguria region is historically affected by severe hydro-meteorological events often resulting in dramatic death tolls and large socio-economic impacts. On 7-8 October 1970, Genoa, region capital city, was struck by the most catastrophic flood event of its history. On the evening of 7 October pre-frontal storms affected the western side of the city (Voltri, Prà and Pegli municipalities), while on 8 October 1970 an anticyclone block generated recurring convective systems that hit Genoa city and above all the Bisagno Valley. The heavy rainfall continued more than 24 h with highs at Bolzaneto rain gauge (Polcevera Valley, northwest of Genoa city center) where over 950 mm of rainfall in 24 hours was measured. Over the city center and the Bisagno Valley, 400 mm in 24 h was recorded. The Bisagno stream channels overflowed, submerging the city center. The 1970 event in Genoa City was also the most dramatic in terms of damage: 44 fatalities occurred and over 2000 individuals were evacuated.</p> <p>This study hindcasts the meteorological evolution of this event at high spatial resolution (1.5 km) and temporal one (1 hour) using the Weather and Research Forecasting (WRF) model by downscaling the ERA5 climatology developed by European Center for Medium-Range Weather Forecast (ECMWF). The weather hindcast scenario is compared with available meteorological observations as well as with recorded geomorphological impacts on Genoa city center and municipalities.</p>

For the monitoring of hydrometeorological variables, and more generally, for decision support systems, the instrumental in-situ measurement is crucial. Referring to professional micrometeorological stations, there is a problem represented by the high costs of measures. The high cost can be substantially related to the quality of the materials, to the array of industrial production processes and to the costs of skilled workers, needed for the installation and for the maintenance of the equipment. A further problem in the development of such measuring networks is represented by "closed" products which, for structural layouts, data management and communications, are almost always referred to as "proprietary protocols", which push the customer to a perpetual and often non-negotiable "loyalty" to the supplier. This limits the development of modern and efficient measurement networks in countries with limited economic resources. The "ACRONET Paradigm&quot...

The objective of this research was to develop a method for water level retrieval in natural and artificial lakes. It was thought to be applied for monitoring purposes and flood control applications, especially in data-scarce environments. The method is based on a combined GIS, remote sensing and statistical modeling approach. It was tested on both optical (Landsat 8) and SAR (Cosmo-SkyMed®) data. The topographic information, required by the method, were obtained from freely available digital elevation models (SRTM and ASTER) to compare their performances. The Place Moulin Lake, an Alpine reservoir, was selected as study area since it represents a very challenging case study for developing the proposed methodology. The results showed that: i) the method provided reasonably accurate results when the degree of filling of the reservoir was high. ii) The accuracy of the results strongly relied on the accuracy of the topographic information. iii) The combination of Cosmo-SkyMed® and SRTM data provided more reliable results. Further analyses are required to evaluate the method in different environmental conditions.

The Disaster Risk Management Cycle (DRMC) is a common reference for the international Disaster Risk Management (DRM) community to describe the management of catastrophic anthropogenic and natural events worldwide. Implementing this approach, disaster management is described by a series of separate and consecutive phases (e.g., preparedness, response, and recovery). However, the current DRMC is not able to successfully cover the dynamics of multi-hazard risk scenarios, particularly those involving both sudden- (e.g., earthquakes or flash floods) and slow-onset hazards (e.g., pandemics or  droughts).Starting from such a complex scenario we propose a ‘parallel phases’ DRM model accounting for the management of interacting sudden- and slow-onset hazards. The framed ‘parallel phases’ model allows to overcome the limitations of the existing models when dealing with complex multi-hazard risk conditions. We supported the identified limitations analysing Italian Red Cross data dealing with p...

<p>This work analyses the spatial structure of some extra-ordinary extreme rainfall events (EEEs) in Liguria (NW of Italy). The EEEs affecting the region are often caused by Mediterranean Back-building MCS events which are usually characterized by a very small spatial extent. EEEs produce the annual maximums of precipitation for short durations, commonly used for the probabilistic analysis of rainfall and flood hazard.</p> <p>The characteristic spatial scale of the EEE analyzed, represented by the cross-sectional dimension of the peak structures, compared with the average rain gauge density shows that the former is often less than or of the same order as the latter.</p> <p>Rain gauge data are used to obtain statistics of extreme rainfall, usually expressed by rainfall depth-duration-frequency (DDF) curves. This statistical approach relies on the assumption that the maxima observed by the raingauges are matching with the local maxima of the actual event. The lower is the average rain gauge density compared to the characteristic spatial scale of EEEs, the less valid is the aforementioned hypothesis.</p> <p>The spatial analysis of some recent EEEs in the region underlines that the mismatch between the characteristic spatial scale of the rainfall field and the average rain gauge density can be extremely significant.</p> <p>This impacts the probability of observing the actual peak rainfall and can lead to an overestimation of the return period associated with the most intense events, which are of interest for the design of hydraulic structures and risk planning.</p> <p>The dramatic underestimation of the rainfall depth at very high return periods due to the application of traditional statistical methods has been already highlighted as a criticality in the literature, focusing on daily rainfall. This work presents a first attempt to set up a framework to quantify the underestimation of the precipitation peak (or the overestimation of the return period) at sub daily scale as a function of the ratio between the raingauge density and the transversal dimension of the precipitation events.</p>

The monitoring of the recovery phase in the aftermath of an emergency scenario is tackled in this paper in terms of a change-detection perspective and through the integration of multisensor, multisource, and contextual information associated with high resolution optical and SAR data. The method makes use of the Markov random field theory to integrate the spatial context and the temporal correlation associated with images acquired at different dates. Moreover, the adoption of a region-based approach allows the characterization of the geometrical structures in the images through the employment of multiple segmentation maps at different scales. The performances of the proposed approach are evaluated on pairs of COSMO-SkyMed/Pléiades images acquired over Haiti in the aftermath of Hurricane Matthew.

For the accurate prediction of floods in mountain environment, reliable estimations of the dynamics at the soil surface of snow melt/accumulation processes is fundamental. Percentage of snow covered area, snow water equivalent at catchment scale impact the runoff volume during flood events in Alpine regions trough snowmelt. The latter is strongly influenced by the energy balance at the snow surface. For this reason it is necessary a reliable formulation of the physics of the coupled mass/energy exchange processes between soil-snowpack and atmosphere. Here we present a model of water and energy balance over snow characterized by a four-layer scheme, with two layers of snow and two layers of soil. The eight state variables of the model are: average temperatures of layers, driving the energy balance represented by the Force Restore Equation, modified for snow; snow density and snow water equivalent, driving the mass balance equations evaluated for each snow layer. In model formulation ...

The objective of this research was to evaluate the potentialities of an advanced SM-DA system based on the assimilation of synthetic aperture radar (SAR) observations derived from Sentinel 1 (S1) acquisitions. A time-continuous, spatially-distributed, physically-based hydrological model was used: Continuum (Silvestro et al., 2013). The latter is currently exploited for civil protection activities in Italy, both at national and at regional scale. Therefore, its adoption allows for a better understanding of the real potentialities of the aforementioned SM-DA system for improving EWS.

The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems p...

Abstract This paper presents MULESME, a software designed for the systematic mapping of surface soil moisture using Sentinel-1 SAR data. MULESME implements a multi-temporal algorithm that uses time series of Sentinel-1 data and ancillary data, such as a plant water content map, as inputs. A secondary software module generates the plant water content map from optical data provided by Landsat-8, or Sentinel-2, or MODIS. Each output of MULESME includes another map showing the level of uncertainty of the soil moisture estimates. MULESME was tested by using both synthetic and actual data. The results of the tests showed that root mean square error is in the range between 0.03 m3/m3 (synthetic data) and 0.06 m3/m3 (actual data) for bare soil. The accuracy decreases in the presence of vegetation (root mean square in the range 0.08–0.12 m3/m3), as expected.

The estimation of the degree of filling of reservoirs (e.g. the percentage of water volume stored in a reservoir compared to the maximum storage capacity) is particularly useful for hydrological and emergency management purposes. In fact both water resources and emergency managers can benefit from this information that, coupled with rainfall forecasts (both medium and long-range), can be exploited for planning hydroelectric power production or for flood forecasts. In many cases water volume data are not available because not shared by operators for use in real time or due to the lack of reliable, real-time monitoring networks. Remote sensing may allow overcoming these limitations for applications on large spatial scales. It allows the near real-time extraction of the shorelines of water bodies that, if merged with accurate topographic information, can help to estimate the volume of water stored. In order to achieve this objective the accuracy of the mapping procedure must satisfy hi...

The utility of synthetic aperture radar (SAR) data to produce flood delineation maps is well established. However, flood mapping still represents a challenge in urban settlements, because the radar signatures of flooded urban pixels are generally ambiguous. As a matter of fact, flood mapping algorithms generally do not consider urban areas, thus producing a lot of missed detection errors. Recent studies demonstrated that SAR Interferometry (InSAR) represents a suitable tool to at least mitigate this problem. Following these studies, here we analyze time series of complex coherence data in stable scatterers, i.e., pixels exhibiting high backscatter combined with high temporal stability. Our idea is based on the fact the water surfaces show no coherence in a repeat-pass interferogram, so that a decrease of coherence may occur even for stable scatterers if floodwater is present in a resolution cell. The analysis was performed considering the floods that hit the city of Alicante (Spain) in March 2017. This event was observed by Sentinel-1 in Interferometric Wide Swath mode.

GeoSTARe is a proposed GEOsynchronous satellite mission designed to carry aboard a Synthetic Aperture Radar (GEOSAR) payload, which can provide radar images with unprecedented temporal resolution. The research activity described in this paper aimed at investigating the potentialities of such system for soil moisture (SM) monitoring finalized to hydrological applications. The objective was defining the GEOSAR requirements, in term of spatio-temporal resolution, for SM mapping. GEOSAR is capable to produce images with different sub-daily temporal resolution, with associated spatial resolution, according to the length of the synthetic antenna focused on ground. To this aim, three GEOSAR-derived SM products, characterized by different spatio-temporal resolutions (matching the expected performances of GEOSAR), were simulated. Then, these products were used in a synthetic hydrological SM data assimilation experiment to evaluate their impact on model discharge predictions. Results showed that, for such system, the best performances were obtained when the highest spatial resolution was used.

In this work a model that balances the need of reproducing the physic of the processes and the practical goal of avoiding over-parameterization is presented. The model is developed to be easily applied in different contexts even in data scarce environments. All main hydrological phenomena are modeled in a fully distributed way. Complete mass balance and energy balance are introduced with the capability of soil surface temperature estimation.

In a reservoir, water level monitoring is important for emergency management purposes. This information can be used to estimate the degree of filling of the water body, thus helping decision makers in flood control operations. Furthermore, if assimilated in hydrological models and coupled with rainfall forecasts, this information can be used for flood forecast and early warning. In many cases, water level is not known (e.g. data-scarce environments), or not shared by operators. Remote sensing may allow overcoming these limitations, enabling its estimation.

The utility of synthetic aperture radar (SAR) data to produce flood delineation maps is well established. However, for what concerns urban settlements, flood mapping still represents a challenge, because the radar signatures of flooded urban pixels are generally ambiguous. As a matter of fact, flood mapping algorithms generally do not consider urban areas, thus producing a lot of missed detection errors. To cope with this problem, this study proposes a new method that basically analyzes the complex coherence of urban pixels characterized by high backscatter combined with high temporal stability (stable scatterers). Contextual information is also used to reduce the noise of the maps. The rationale is that, since water surfaces show no coherence in a repeat-pass interferogram, a decrease of coherence may occur even for (some) stable scatterers if floodwater is present in a resolution cell. To develop the algorithm, the inundation that hit Houston (Texas, USA) in April 2016 was conside...

On 14 August 2018, Morandi Bridge in Genoa, Italy, collapsed to the ground that was 40 m below. This tragedy killed 43 people. Preliminary investigations indicated poor design, questionable building practices, and insufficient maintenance—or a combination of these factors—as a possible cause of the collapse. However, around the collapse time, a thunderstorm associated with strong winds, lightning, and rain also developed over the city. While it is unclear if this thunderstorm played a role in the collapse, the present study examines the weather conditions before and during the bridge collapse. The study particularly focuses on the analysis of a downburst that was observed around the collapse time and a few kilometers away from the bridge. Direct and remote sensing measurements are used to describe the evolution of the thunderstorm during its approached from the sea to the city. The Doppler lidar measurements allowed the reconstruction of the gust front shape and the evaluation of it...

First results of the assimilation of high-resolution Sentinel-1A based soil moisture products in a distributed, physically based, hydrological model are presented. A comprehensive evaluation of the assimilation's impact on discharge predictions is provided. Results are further compared to those obtained when assimilating the lower-resolution ASCAT-based soil moisture product. The exercise was carried out within the MIDA project framework (funded by the Italian Space Agency) aiming at producing root zone soil moisture maps useful for flood risk management applications. The experimental site is the Orba River Catchment (Italy). The period of investigation is October 2014-February 2015. Using a relatively simple data assimilation technique (Nudging) the results of our case study show that overall the assimilation of currently available Sentinel-1 data only marginally improves discharge simulations. However, the impact becomes more significant when specifically considering predictions of high flow. Further improvements are expected when both Sentinel-1A and B data will be available.

Postflood indirect peak flow estimates provide key information to advance understanding of flash flood hydrometeorological processes, particularly when peak observations are combined with flood simulations from a hydrological model. However, indirect peak flow estimates are affected by significant uncertainties, which are magnified when floods are associated with important geomorphic processes. The main objective of this work is to advance the integrated use of indirect peak flood estimates and hydrological model simulations by developing and testing a procedure for the assessment of the geomorphic impacts–related uncertainties. The methodology is applied to the analysis of an extreme flash flood that occurred on the Magra River system in Italy on 25 October 2011. The event produced major geomorphic effects and peak discharges close to the maxima observed for high-magnitude rainstorm events in Europe at basin scales ranging from 30 to 1000 km2. Results show that the intensity of geo...

ABSTRACT Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.