Hazard Uncertainty Research Articles

A COMPUTATIONAL FRAMEWORK FOR HOLISTIC LIFE-CYCLE DESIGN OF BUILDINGS

This paper combines building information modeling with advanced structural modeling to optimize the design of building components using a life-cycle perspective. A new object-oriented software framework that extends an existing program is presented. It creates information-rich finite element models from industry foundation class files that are exported from building information programs. In addition to models for structural responses, the new components contain models for construction cost, repair cost, environmental impact cost, and human health cost. Random variable objects represent uncertainties in material properties, hazards, and cost models. Similarly, design variable objects represent decisions, such as structural dimensions and materials. All costs are summed and the expected value of this sum is employed as a decision criterion. This paper presents the software framework and a demonstration application.

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.

Reducing Uncertainty in Hazard Prediction

The editors of a new book describe how to characterize uncertainty in natural hazards, the incorporation of uncertainty into modeling, its contribution to better decision-making, and research needs.

A stochastic programming approach to integrated water supply and wastewater collection network design problem

In this paper, a mixed scenario-based and probabilistic two-stage stochastic programming model is proposed for the design of integrated water supply and wastewater collection systems. None of the existing models simultaneously takes into account both business-as-usual and hazard uncertainties. To explore suitable solutions in a reasonable time, a solving procedure comprised of the (1) sample average approximation method, (2) Bezdek fuzzy clustering method and (3) Benders decomposition algorithm is developed. In order to expedite the convergence of the applied Benders decomposition algorithm, different acceleration techniques especially the local branching method are utilized. The performance of the proposed mathematical model and solution procedure is analyzed computationally through a real case study which the results show the usefulness of the developed stochastic programming model as well as the efficiency of the solution approach.

Ground-motion scaling for seismic performance assessment of high-rise moment-resisting frame building

Next generation performance-based earthquake engineering involves the use of a probability framework, which incorporates the inherent uncertainty and variability in seismic hazard, structural and non-structural responses, damage states and economic and casualty losses. One key issue in seismic performance assessment is the scaling of ground motions for nonlinear response-history analysis. In this paper, the impact of ground-motion scaling procedures, including 1) geometric-mean scaling of pairs of ground motions, 2) spectrum-matching of ground-motions, 3) first-mode-based scaling to a target spectral acceleration and 4) maximum-minimum orientation scaling, on the distributions of floor acceleration, story drift and floor spectral acceleration of a sample high-rise building is investigated using a series of nonlinear response-history analyses of a 34-story moment-resisting frame building. The advantages and disadvantages of each ground-motion scaling method are discussed for seismic performance assessment of a 34-story building.

Probabilistic seismic hazard assessment for Saudi Arabia using spatially smoothed seismicity and analysis of hazard uncertainty

We analyze the results of a Probabilistic Seismic Hazard Assessment obtained for Saudi Arabia using a spatially smoothed seismicity model. The composite up-to-date earthquake catalog is used to model seismicity and to determine earthquake recurrence characteristics. Different techniques that are frequently used for the analysis of input data are applied in the study. The alternative techniques include the declustering procedures for catalog processing, statistical techniques for estimation the magnitude–frequency relationship (MFR), and the seismicity smoothing parameter. The scheme represents epistemic uncertainty that results from an incomplete knowledge of earthquake process and application of alternative mathematical models for a description of the process. Our calculations that are based on the Monte Carlo technique include also a consideration of the aleatory uncertainty related to the dimensions and depths of earthquake sources, parameters of MFR, and scatter of ground-motion parameter. The hazard maps show that the rock-site peak ground acceleration (PGA) is the highest for the seismically active areas in the north-western (Gulf of Aqaba, PGA > 300 cm/s2 for return period 2475 years) and south-western (PGA > 100 cm/s2 for return period 2475 years) parts of the country. We show that the procedures for catalog declustering have the highest influence on the results of hazard estimations, especially for high levels of hazard. The choice of smoothing parameter is a very important decision that requires proper caution. The relative uncertainty that is ratio between the 85th and 15th percentiles may reach 50–60% for the areas located near the zones of high-level seismic activity.

Fuzzy Finite Difference Scheme to Simulate Radon Transport from Subsurface Soil to Buildings

In this paper, a methodology for solving the advection diffusion equation describing the radon transport from subsurface soil into buildings in presence of the imprecision in the measurements of model parameters such as radon diffusion coefficient and flow velocity of radon in air has been explored. Imprecision of the model parameters is addressed as a fuzzy variable and the membership function of each such fuzzy variable is expressed in the form of a triangular fuzzy number. Explicit finite difference numerical method along with fuzzy parameters of the representative model is applied to obtain the solution of the governing advection diffusion equation and due to this the present numerical approach is named as fuzzy finite difference. Uncertainty quantification of the radon concentration as solution of the governing fuzzy partial differential equation is carried out and by using this uncertainty modeling, advantage of the fuzzy finite difference approach for obtaining the numerical solution of a fuzzy partial differential equation is shown. Results of computed radon concentration with uncertainty can be possible to use for assessing further the uncertainty in health hazards.

A proposed probabilistic seismic tsunami hazard analysis methodology

We expand on existing probabilistic tsunami hazard analysis (PTHA) approaches by presenting a methodology wherein the epistemic uncertainties associated with tsunami timing, generation, and propagation are separated from aleatory uncertainties. The contributions of epistemic and aleatory uncertainties to the overall uncertainty in tsunami hazard are evaluated through a two-level Monte Carlo analysis. The total epistemic uncertainty contribution defines the variance of the tsunami inundation hazard distribution. Through Bayesian inference, the available catalog of tsunami runup data is used to refine the hazard estimate, where the prior distribution is weighted by epistemic uncertainties. The general PTHA framework is further modified to include a hazard function accounting for peak water elevation, velocity, duration of inundation, and warning time. We carry out a formal sensitivity analysis of the tsunami generation and propagation on the feasible model parameter space using the multi-objective generalized sensitivity analysis algorithm. Parameters showing a significant influence on tsunami hazard include the tidal elevation, moment magnitude (M w), the Gutenberg–Richter (G–R) distribution β parameter, epicenter location, and the rake angle. Parameters showing minimal influence on tsunami hazard include the G–R maximum seismic moment magnitude (M max) parameter, strike angle, dip angle, seismic depth and Manning’s roughness. As a proof of concept, the methodology is applied to a case study of tsunami hazard posed to National Oceanic and Atmospheric Administration Station 9411406 (Oil Platform Harvest, CA, USA) by seismic sources along the Aleutian Islands, AK.

An algorithm for solving fuzzy advection diffusion equation and its application to transport of radon from soil into buildings

This paper deals with the numerical solution of fuzzy advection diffusion equation. An algorithm for solving this fuzzy advection diffusion equation using finite difference method has been developed and the new numerical method is named as fuzzy finite difference scheme. The algorithm has been tested by a case study in which the radon transport from subsurface soil into buildings in presence of the fuzziness of the input parameters of advection diffusion equation such as radon diffusion coefficient and flow velocity of radon in air has been presented. Fuzziness of the model parameters is addressed as a fuzzy variable and the membership function of each such fuzzy variable is expressed in the form of a trapezoidal fuzzy number. Explicit finite difference numerical method along with fuzzy parameters of the representative model is applied to obtain the solution of the governing advection diffusion equation. Advantage of this new algorithm is to have the possibility of a power of quantifying uncertainty of the radon concentration as solution of the governing fuzzy partial differential equation. Results of computed radon concentration with uncertainty can be applied further for assessing the uncertainty in health hazards.

Bay of Bengal cyclone extreme water level estimate uncertainty

Accurate estimates of storm surge magnitude and frequency are essential to coastal flood risk studies. Much research has focused on tide–surge interaction and joint probability techniques to combine multiple cyclone characteristics. In the Bay of Bengal, extreme water levels are derived from numerical storm surge models based on an idealised cyclone event; however, uncertainty within such calculations for this region is poorly understood, especially when propagated through to the flood hazard. We use the IBTrACs data set to estimate natural variability in four key parameters used to describe an idealised cyclone and create a set of idealised but equally likely “1 in 50 year” recurrence interval cyclone events. Each idealised cyclone is then used to force a storm surge model to give predicted peak water levels along the northern Bay of Bengal coast. Finally, extreme water level uncertainty is propagated through an inundation model to predict flood extent and depth over inland coastal floodplains. The descriptive parameters of 18 cyclone events (between 1990 and 2008) appear to show no statistically significant variation (at the 5 % level) due to landfall location, which allows us to pool characteristics for the entire Bay of Bengal. We find that the natural variability of cyclone parameters translates into large uncertainty both for storm surge height (of the order of metres) and for coastal inundation (hundreds of km2). Using the variability estimates for a 1-in-50-year cyclone event making landfall at the 2007 Sidr location, cyclone central pressure drop uncertainty had the greatest effect upon simulated storm surge magnitude. However, uncertainty within cyclone track characteristics (track speed, landfall and genesis location) has greater influence on subsequent inundation extent. Storm surge hazard uncertainty due to cyclone parameter variability was found to be comparable to the inundation difference simulated when the peak surge coincided with either a mean spring high or low water. Our research indicates the importance of improving extreme water level estimates along the Bay of Bengal coastline for robust flood hazard management decisions in the Bay of Bengal.

Assessing sediment toxicity: Past, present, and future

Assessing sediment toxicity: Past, present, and future

Applications of the disaster risk reduction approach to migration influenced by environmental change

This paper considers applications of disaster risk reduction (DRR) principles and operating mechanisms to migration influenced by environmental change. It is well established that DRR addresses change in risk, well-being and security including through adaptation and resilience building. However, the manner in which this applies to migration influenced by environmental change has to date not been well analysed. This is a multi-sectoral and inter-disciplinary field for which interpretation and consequent reactions to environmental change and migration involves technology, civil societal engagement, and political commitment. The paper presents implications for reacting to migration influenced by environmental change apparent from DRR principles of prevention, mitigation and post event response. Four operating mechanisms of DRR are also considered. They are early warning, risk management, improved communication and the use of appropriate response standards. The applicability and efficacy of these DRR principles and operating mechanisms for reacting to migration influenced by environmental change are conditioned by hazard uncertainty and potential impact. Disaster prevention or mitigation for those who move, host or stay behind involves community based risk reduction, resilience building, rights approaches, and migration as adaptation. The application of DRR to migration influenced by environmental change therefore highlights the importance of engaging localised strategies and well-being aspirations, and of knowing the limitations of humanitarian response in upholding rights and sustainable development outcomes. Whilst the development of DRR principles may analytically frame potential environmental migration responses, there are ongoing theoretical and applied challenges in this relationship.

Trimming the UCERF2 Hazard Logic Tree

### Assessing Which Sources of Hazard Uncertainty Matter The Uniform California Earthquake Rupture Forecast 2 (UCERF2) is a fully time‐dependent earthquake rupture forecast developed with sponsorship of the California Earthquake Authority (Working Group on California Earthquake Probabilities [WGCEP], 2007; Field et al. , 2009). UCERF2 contains 480 logic‐tree branches reflecting choices among nine modeling uncertainties in the earthquake rate model shown in Figure 1. For seismic hazard analysis, it is also necessary to choose a ground‐motion‐prediction equation (GMPE) and set its parameters. Choosing among four next‐generation attenuation (NGA) relationships results in a total of 1920 hazard calculations per site. The present work is motivated by a desire to reduce the computational effort involved in a hazard analysis without understating uncertainty. We set out to assess which branching points of the UCERF2 logic tree contribute most to overall uncertainty, and which might be safely ignored (set to only one branch) without significantly biasing results or affecting some useful measure of uncertainty. The trimmed logic tree will have all of the original choices from the branching points that contribute significantly to uncertainty, but only one arbitrarily selected choice from the branching points that do not. Figure 1. Branches of the UCERF2 logic tree (after WGCEP, 2007). Dotted lines (…) indicate that the tree continues parallel to the branches that are shown, but that these branches are omitted from the figure for clarity. Black numbers below branches are the branch weights. Risk analyses that use the trimmed tree should produce approximately the same results as those that use the full tree. Risk, as used here, refers to the relationship between some undesirable outcome and its likelihood of occurrence, typically from some particular decision‐maker’s perspective. Risk can be measured in terms of an uncertain quantity of loss, such as the relationship between future earthquake‐related repair costs to a particular asset or group …

Uncertainty in floodplain delineation: expression of flood hazard and risk in a Gulf Coast watershed

AbstractThis paper investigates the development of flood hazard and flood risk delineations that account for uncertainty as improvements to standard floodplain maps for coastal watersheds. Current regulatory floodplain maps for the Gulf Coastal United States present 1% flood hazards as polygon features developed using deterministic, steady‐state models that do not consider data uncertainty or natural variability of input parameters. Using the techniques presented here, a standard binary deterministic floodplain delineation is replaced with a flood inundation map showing the underlying flood hazard structure. Additionally, the hazard uncertainty is further transformed to show flood risk as a spatially distributed probable flood depth using concepts familiar to practicing engineers and software tools accepted and understood by regulators. A case study of the proposed hazard and risk assessment methodology is presented for a Gulf Coast watershed, which suggests that storm duration and stage boundary conditions are important variable parameters, whereas rainfall distribution, storm movement, and roughness coefficients contribute less variability. The floodplain with uncertainty for this coastal watershed showed the highest variability in the tidally influenced reaches and showed little variability in the inland riverine reaches. Additionally, comparison of flood hazard maps to flood risk maps shows that they are not directly correlated, as areas of high hazard do not always represent high risk. Copyright © 2012 John Wiley & Sons, Ltd.

Corporate Hedging and Financial Contracting

This paper develops a theory of corporate hedging in a financial contracting framework. In an economy with moral hazard and state uncertainty, the optimal financial contract incorporates both non-monitoring (arm’s length) finance and monitoring (bank) finance, and its payoff is equity-like. When external investors (e.g., the bank) face additional costs of holding equity, hedging mitigates incentive problems related to debt contracts and, thus, lowers the cost of debt and enables the firm to substitute debt for equity in its capital structure. The model generates empirical implications that are consistent with extant empirical evidence. For example, hedging will be more likely to be used with bank finance than with non-monitoring finance; the optimal hedge ratio will be positively related to the level of bank finance; and the optimal hedge ratio should be strictly less than 1.

Analysis of a detention basin impact on dike failure probabilities and flood risk for a channel-dike-floodplain system along the river Elbe, Germany

Highly concentrated asset values are often protected by dikes stretching along the river course. During extreme floods, dikes may fail due to various breach mechanisms and cause considerable damage. Therefore detention basins are often additionally installed to reduce the flood risk for downstream communities. In such situations, however, the systemic performance of dikes and spatial redistribution of inundation patterns are often unknown. Intuitively expected effects such as more probable breaches downstream due to fewer breaches upstream and consequently higher conveyance of upstream reaches lack evidential proof. With a coupled probabilistic–deterministic 1D-channel – dike breach – 2D-inundation – flood damage model chain the impact of a detention basin on losses to residential buildings and agricultural crops is investigated. We demonstrate the changes in dike performance due to systemic load and relief along the river course on the Middle Elbe, Germany considering three breach mechanisms: overtopping, piping and slope micro-instability. The reduction of overtopping failures due to the detention basin resulted in the slightly increased breach probabilities due to piping and micro-instability farther downstream. Finally, the uncertainty in hazard and damage estimations are analysed using the Monte Carlo simulation and applying several damage models. Despite high uncertainties in flood hazard and damage estimations, we conclude that the risk reduction to residential buildings downstream of the detention basin exceeds the higher losses to agricultural crops within the filled detention area.

Progressive climate change and disasters: communicating uncertainty

Communication of uncertainty gained prominence from risk communication work starting in (at latest) the 1980s and has increasingly become salient with a growing need to communicate uncertainty of climate change impacts (USPHS 1995; Nerlich et al. 2010). Nonetheless, ignorance, apathy and blaming persist in many sectors, from the general public to specialist scientists, indicating various (mis)understandings of and responses to uncertainty. The reasons are complicated, but some can be understood by addressing what, why, whom, how and when uncertainty is communicated. A major dilemma of communicating uncertainty is that it is more about certainty (Sandman and Lanard 2011). Failure of uncertainty communication or its misunderstanding may lead to loss of trust, a poor reputation and inadequate response (Sandman and Lanard 2011). One common misinterpretation of hazard uncertainty is that a ‘‘100-year flood’’ will not happen soon after its recent occurrence. That can reduce public preparedness, and subsequently, a repeated occurrence of such flood could lead to further asset losses along with loss of trust in risk communication. A few important dimensions to consider in communicating uncertainty are information on its (1) source, (2) scale and (3) complexity. While it may seem obvious to communicate the source of uncertainty, it does not always happen. Disasters such as fires, floods, and droughts—even earthquakes and tsunami!—are misattributed to climate change (Sarewitz and Pielke 2005). Frequently, the causes of hazards and disasters are portrayed to be external to the human domain, discounting human actions and vulnerability. For example, floods are often communicated to be caused by heavy rain or snowmelt without accounting for the role of human activities changing river morphology and local vulnerability, despite repeatedly being pointed out in the literature.

Quantifying the Uncertainty in Future Coastal Flood Risk Estimates for the U.K

Future sea-level rise will increase coastal flood risk in the U.K., yet the hazard uncertainties associated with such future risk estimates have not been fully explored. The sensitivity of coastal flood-risk mapping to future uncertainties was investigated by propagating ranges of plausible parameters through a LISFLOOD inundation model of a significant historic flood event to the North Somerset (U.K.) coast. Mean sea-level rise (including land movement) was found to have the greatest effect on the extent of flood inundation. Analysis of the latest research into the future storm-surge climate of the U.K. indicates no change above natural variability, thus, future, extreme water-level estimates (for the U.K.) should be based on observations and not Regional Circulation Models until research indicates otherwise. Evidence suggests that the current approach of forcing the inundation model with an extreme water level of a constant return period is incorrect. This uncertainty of the peak storm tide height along the coastline had a significant effect on our results. We present a new boundary-forcing technique to force the inundation model with (method C), based on the spatial characteristics of real events, which can account for the natural storm-surge variability. Indeed, if sea-level rise is included with method C, a great deal of the uncertainty surrounding such a future flood-hazard estimate can be quantified and communicated clearly and effectively.

Post-hazard flow capacity of bridge transportation network considering structural deterioration of bridges

The flow capacity of a transportation network can be reduced significantly if its constituent bridges are damaged by natural or man-made hazards. For rapid risk-informed decision making on hazard mitigation and response, it is therefore essential to have a capability to predict the post-hazard flow capacity of the network efficiently and accurately. However, this is a challenging task due to the uncertainty in hazards and structural damage, and the complex nature of the network flow analysis. Moreover, the bridge structures may experience significant deterioration over their life cycle, which requires time-varying network reliability analysis. This paper proposes a new non-sampling-based approach to estimate the time-varying post-hazard flow capacity of a bridge transportation network considering structural deterioration of bridges. The proposed approach evaluates the probabilities of structural damage scenarios efficiently using the matrix-based system reliability method and rapidly computes the corresponding flow capacities using a maximum flow capacity analysis algorithm. The matrix-based framework facilitates the integration of these results to obtain the probabilistic distributions and statistical moments of the network flow capacity. It also enables computing various measures useful for risk-informed decision making, such as the conditional mean and standard deviation of flow capacity given observed structural damage, and component importance measures. In the proposed approach, probability calculation and network flow analysis are performed separately, which renders time-varying post-hazard flow capacity analysis efficient. The proposed approach is demonstrated by a numerical example based on the Sioux Falls network under multiple bridge-deterioration scenarios simulating the progress of deterioration.

Uncertainty analysis for seismic hazard in Northern and Central Italy

In this study we examine uncertainty and parametric sensitivity of Peak Ground Acceleration (PGA) and 1-Hz Spectral Acceleration (1-Hz SA) in probabilistic seismic hazard maps (10% probability of exceedance in 50 years) of Northern and Central Italy. The uncertainty in hazard is estimated using a Monte Carlo approach to randomly sample a logic tree that has three input-variables branch points representing alternative values for bvalue, maximum magnitude (Mmax) and attenuation relationships. Uncertainty is expressed in terms of 95% confidence band and Coefficient Of Variation (COV). The overall variability of ground motions and their sensitivity to each parameter of the logic tree are investigated. The largest values of the overall 95% confidence band are around 0.15 g for PGA in the Friuli and Northern Apennines regions and around 0.35 g for 1-Hz SA in the Central Apennines. The sensitivity analysis shows that the largest contributor to seismic hazard variability is uncertainty in the choice of ground-motion attenuation relationships, especially in the Friuli Region (?0.10 g) for PGA and in the Friuli and Central Apennines regions (?0.15 g) for 1-Hz SA. This is followed by the variability of the b-value: its main contribution is evident in the Friuli and Central Apennines regions for both 1-Hz SA (?0.15 g) and PGA (?0.10 g). We observe that the contribution of Mmax to seismic hazard variability is negligible, at least for 10% exceedance in 50-years hazard. The overall COV map for PGA shows that the uncertainty in the hazard is larger in the Friuli and Northern Apennine regions, around 20-30%, than the Central Apennines and Northwestern Italy, around 10-20%. The overall uncertainty is larger for the 1-Hz SA map and reaches 50- 60% in the Central Apennines and Western Alps.