Raffaele De Risi

Probabilistic GIS-based method for delineation of urban flooding risk hotspots

Abstract Identifying urban flooding risk hotspots is one of the first steps in an integrated methodology for urban flood risk assessment and mitigation. This work employs three GIS-based frameworks for identifying urban flooding risk hotspots for residential buildings and urban corridors. This is done by overlaying a map of potentially flood-prone areas [estimated through the topographic wetness index (TWI)], a map of residential areas and urban corridors [extracted from a city-wide assessment of urban morphology types (UMT)], and a geo-spatial census dataset. A maximum likelihood method (MLE) is employed for estimating the threshold used for identifying the flood-prone areas (the TWI threshold) based on the inundation profiles calculated for various return periods within a given spatial window. Furthermore, Bayesian parameter estimation is employed in order to estimate the TWI threshold based on inundation profiles calculated for more than one spatial window. For different statistics of the TWI threshold (e.g. MLE estimate, 16th percentile, 50th percentile), the map of the potentially flood-prone areas is overlaid with the map of urban morphology units, identified as residential and urban corridors, in order to delineate the urban hotspots for both UMT. Moreover, information related to population density is integrated by overlaying geo-spatial census datasets in order to estimate the number of people affected by flooding. Differences in exposure characteristics have been assessed for a range of different residential types. As a demonstration, urban flooding risk hotspots are delineated for different percentiles of the TWI value for the city of Addis Ababa, Ethiopia.

Bayesian Cloud Analysis: efficient structural fragility assessment using linear regression

Cloud Analysis is based on simple regression in the logarithmic space of structural response versus seismic intensity for a set of registered records. A Bayesian take on the Cloud Analysis, presented herein, manages to take into account both record-to-record variability and other sources of uncertainty related to structural modelling. First, the structural response to a suite of ground motions, applied to different realizations of the structural model generated through a standard Monte Carlo, is obtained. The resulting suite of structural response is going to be used as “data” in order to update the joint probability distribution function for the two regression parameters and the conditional logarithmic standard deviation. In the next stage, large-sample MC simulation based on the updated joint probability distribution is used to generate a set of plausible fragility curves. The robust fragility is estimated as the average of the generated fragility curves. The dispersion in the robust fragility is estimated as the variance of the plausible fragility curves generated. The plus/minus one standard deviation confidence interval for the robust fragility depends on the size of the sample of “data” employed. Application of the Bayesian Cloud procedure for an existing RC frame designed only for gravity-loading demonstrates the effect of structural modelling uncertainties, such as the uncertainties in component capacities and those related to construction details. Moreover, a comparison of the resulting robust fragility curves with fragility curves obtained based on the Incremental Dynamic Analysis shows a significant dependence on both the structural performance measure adopted and the selection of the records.

Probabilistic Earthquake–Tsunami Multi-Hazard Analysis: Application to the Tohoku Region, Japan

This study develops a novel simulation-based procedure for the estimation of the likelihood that seismic intensity (in terms of spectral acceleration) and tsunami inundation (in terms of wave height), at a particular location, will exceed given hazard levels. The procedure accounts for a common physical rupture process for shaking and tsunami. Numerous realizations of stochastic slip distributions of earthquakes having different magnitudes are generated using scaling relationships of source parameters for subduction zones and then using a stochastic synthesis method of earthquake slip distribution. Probabilistic characterization of earthquake and tsunami intensity parameters is carried out by evaluating spatially correlated strong motion intensity through the adoption of ground motion prediction equations as a function of magnitude and shortest distance from the rupture plane and by solving nonlinear shallow water equations for tsunami wave propagation and inundation. The minimum number of simulations required to obtain stable estimates of seismic and tsunami intensity measures is investigated through a statistical bootstrap analysis. The main output of the proposed procedure is the earthquake-tsunami hazard curves representing, for each mean annual rate of occurrence, the corresponding seismic and inundation tsunami intensity measures. This simulation-based procedure facilitates the earthquake-tsunami hazard deaggregation with respect to magnitude and distance. Results are particularly useful for multi-hazard mapping purposes and the developed framework can be further extended to probabilistic earthquake-tsunami risk assessment.

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake

This study conducts coupled simulation of strong motion and tsunami using stochastically generated earthquake source models. It is focused upon the 2011 Tohoku, Japan earthquake. The ground motion time-histories are simulated using the multiple-event stochastic finite-fault method, which takes into account multiple local rupture processes in strong motion generation areas. For tsunami simulation, multiple realizations of wave profiles are generated by evaluating nonlinear shallow water equations with run-up. Key objectives of this research are: (i) to investigate the sensitivity of strong motion and tsunami hazard parameters to asperities and strong motion generation areas, and (ii) to quantify the spatial variability and dependency of strong motion and tsunami predictions due to common earthquake sources. The investigations provide valuable insights in understanding the temporal and spatial impact of cascading earthquake hazards. Importantly, the study also develops an integrated strong motion and tsunami simulator, which is capable of capturing earthquake source uncertainty. Such an advanced numerical tool is necessary for assessing the performance of buildings and infrastructure that are subjected to cascading earthquake–tsunami hazards.

Bayesian tsunami fragility modeling considering input data uncertainty

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty.

Approximate Method for Transverse Response Analysis of Partially Isolated Bridges

Current analysis procedures for seismically isolated bridges frequently use an equivalent (approximate) linearization approach to represent the response of nonlinear isolation/energy dissipation devices. Linearization allows standard linear elastic analysis methods, e.g., the response spectrum method, to be conveniently used for design purposes. The linearization approach is by nature an iterative method implying the need to repeatedly correct and analyze a numerical finite-element model. A further simplification could be achieved using closed form equations to represent (1) the structure displacement patterns and (2) the restoring forces from structural elements. The paper explores such a possibility with reference to partially isolated continuous bridges, i.e., bridges with isolation devices at piers and pinned supports at abutments. The role and effect of higher modes of vibration on the system response are discussed, and an approximate method is proposed to account for such effects. An improvement of the classical Jacobsen’s approximation for the effective viscous damping ratio is also proposed using the results of response history analyses. The latter are carried out on two-dimensional numerical models of five case studies, generated from a real existing bridge supposed to be isolated with friction pendulum devices. Comparison of approximate predictions with response history analysis results is presented and discussed. Nonlinear dynamic analyses of a three-dimensional numerical model of the existing bridge were also carried out for comparison purposes.

Empirical Assessment of Non-Linear Seismic Demand of Mainshock–Aftershock Ground-Motion Sequences for Japanese Earthquakes

This study investigates the effects of earthquake types, magnitudes, and hysteretic behavior on the peak and residual ductility demands of inelastic single-degree-of-freedom systems and evaluates the effects of major aftershocks on the nonlinear structural responses. An extensive dataset of real mainshock-aftershock sequences for Japanese earthquakes is developed. The constructed dataset is large, compared with previous datasets of similar kinds, and includes numerous sequences from the 2011 Tohoku earthquake, facilitating an investigation of spatial aspects of the aftershock effects. The empirical assessment of peak and residual ductility demands of numerous inelastic systems having different vibration periods, yield strengths, and hysteretic characteristics indicates that the increase in seismic demand measures due to aftershocks occurs rarely but can be significant. For a large mega-thrust subduction earthquake, a critical factor for major aftershock damage is the spatial occurrence process of aftershocks.

Simulation-based Probabilistic Tsunami Hazard Analysis: Empirical and Robust Hazard Predictions

Probabilistic tsunami hazard analysis (PTHA) is the prerequisite for rigorous risk assessment and thus for decision-making regarding risk mitigation strategies. This paper proposes a new simulation-based methodology for tsunami hazard assessment for a specific site of an engineering project along the coast, or, more broadly, for a wider tsunami-prone region. The methodology incorporates numerous uncertain parameters that are related to geophysical processes by adopting new scaling relationships for tsunamigenic seismic regions. Through the proposed methodology it is possible to obtain either a tsunami hazard curve for a single location, that is the representation of a tsunami intensity measure (such as inundation depth) versus its mean annual rate of occurrence, or tsunami hazard maps, representing the expected tsunami intensity measures within a geographical area, for a specific probability of occurrence in a given time window. In addition to the conventional tsunami hazard curve that is based on an empirical statistical representation of the simulation-based PTHA results, this study presents a robust tsunami hazard curve, which is based on a Bayesian fitting methodology. The robust approach allows a significant reduction of the number of simulations and, therefore, a reduction of the computational effort. Both methods produce a central estimate of the hazard as well as a confidence interval, facilitating the rigorous quantification of the hazard uncertainties.

Defining structural robustness under seismic and simultaneous actions: an application to precast RC buildings

The increasing complexity of urban systems is making robustness a crucial requirement for structural design. The paper deals with the concept of robustness of civil structures against extreme events. After a brief literature survey, a novel point of view to robustness assessment is proposed, fitting the most accepted robustness definition. The proposed approach is discussed and compared with other methodologies for quantifying structural robustness. Thus, the methodology is developed and applied to an existing precast industrial building case study, assumed to be prone to seismic and wind hazards. In particular, the case study is assumed to be located in Emilia, Italy, where a significant earthquake occurred in 2012, causing relevant damage to gravity load designed industrial buildings. Three structural options are discussed, namely a simple supported beam–column connection (gravity load designed solution) and two pinned connections (seismic designed solution), where only one of them satisfies the current structural code requirements. The results are discussed in terms of robustness quantification, by means of a robustness matrix. The authors envisage that this approach can be effectively adopted for portfolios of existing structures, to prioritize retrofitting interventions, aimed at maximizing the overall risk mitigation with limited economic resources.

A Case-Study On Scenario-Based Probabilistic Seismic Loss Assessment For A Portfolio Of Bridges

ABSTRACT The majority of bridge infrastructure in Italy has been built in the 60’s and 70’s without specific seismic provisions. Therefore, it is expected that they reveal high seismic vulnerability if subjected to a significant seismic event. Given this background, it is natural that rapid and accurate assessment of economic losses incurred to bridge infrastructure can play a crucial role in emergency management in the immediate aftermath of an earthquake. Focusing on the infrastructure system of highway bridges in the Campania region, it is shown how state of the art methodologies in portfolio loss assessment and available data can be implemented in order to assess the probability distribution of the repair costs incurred to the portfolio in question due the Irpinia 1980 earthquake. Formulating the probabilistic loss assessment for the portfolio of bridges as a standard Monte Carlo Simulation problem helps in resolving the spatial risk integral efficiently. One of the specific features of this case-study is the use of statistical methods for updating, a) ground motion prediction; b) vulnerability/fragility; and c) exposure/cost models based on available data. It has been observed that alternative hypotheses with regard to the ground motion correlation structure can significantly affect the distribution of the direct economic loss. Furthermore, updating the ground motion prediction based on available recordings may significantly reduce the dispersion in the estimation of the direct economic losses. 1. INTRODUCTION In the immediate aftermath of a strong earthquake, the road networks play a crucial role in rescue and recovery operations. Since their loss of functionality may undermine the performance of the entire network, the bridge infrastructure can be considered as the so-called weak links within a road network affected by an earthquake. A large part of the Italian bridge infrastructure portfolio, dating back to the first half/beginning of the second half of the last century, is not designed based on earthquake resistant criteria. Therefore, the Italian highway bridges are potentially vulnerable to seismic actions, considering that the Italian territory is classified by medium to high seismicity. The total direct losses incurred to the bridge infrastructure in a road network can be used as a scalar proxy for the performance of the entire network right after the seismic event. This quantity encompasses various parameters, such