Probabilistic Hazard Analysis Research Articles

Probabilistic hazard analysis of impulse waves generated by multiple subaerial landslides and its application to Wu Gorge in Three Gorges Reservoir, China

Subaerial landslides can generate impulse waves in reservoirs, fjords, and other water bodies and cause severe damage to the shipping industry, infrastructure, and human communities along the shorelines. Compared with deterministic hazard models, probabilistic hazard analysis is an important tool for assessing the intensity and exceedance probability of impulse waves generated by multiple landslide sources, which are essential for evidence-based risk mitigation and contingency planning. This paper proposes a methodological procedure for systematic probabilistic hazard analysis of impulse waves generated by subaerial landslides considering all relevant landslide sources and multiple uncertainties (i.e., landslide mechanisms, triggering scenarios, and material parameters). The main steps include: (1) definition of the source parameters by parameterizing the epistemic and aleatory uncertainties. In this respect, the logic tree, event tree, and Monte Carlo models were used to organize the uncertainties of landslide mechanism models, parametric scenarios, and material parameters, respectively; (2) estimation of generated waves based on a landslide dynamic analytical model and previously validated empirical wave models derived from prototype scaled experiments; and (3) aggregation of the hazard analysis results in the form of hazard maps and probability maps under parametric scenarios and a specific scenario. Considering the Wu Gorge in the Three Gorges Reservoir as a case study, soil slides and unstable rock slopes were analyzed to quantify the wave hazard along the reservoir under parametric and specific scenarios while considering rainfall and water level fluctuations. The results show considerable wave hazard in the Wu Gorge. For a 20-year return period, the maximum expected height of propagation waves is 14.41 m. The probability of experiencing propagation waves higher than 2 m in 20 years is over 50% in the river segment with high landslide density. The results of the probabilistic wave hazard analysis could be aggregated and disaggregated to accommodate specific requirements of wave risk management.

Probabilistic tsunami hazard assessment with simulation-based response surfaces

This paper proposes a novel response surface-based method for probabilistic tsunami hazard assessment (PTHA). Although recent advancements in numerical simulation have enabled the accurate characterization of tsunami hazards, the high computational cost of numerical simulation often prohibits its broad application to probabilistic hazard analysis. The proposed method addresses this challenge by constructing the response surface (RS) of a target output using the results of high-fidelity tsunami simulations. The proposed method quantifies uncertainties in key simulation variables and propagates those uncertainties to the target output through the RS in a computationally efficient Monte Carlo simulation (MCS). We illustrate and validate the proposed method through a case study of the tsunami induced by the 2011 Great East Japan earthquake. The case study focuses on Sendai, Ishinomaki, and Kamaishi in Japan as the target locations. The proposed method estimates coastal tsunami heights while considering uncertainties in the fault slip and rake as well as the modeling error associated with the numerical simulation. The MCS allows us to estimate the probability density functions of the tsunami height at the target locations. The proposed method quantifies the contribution of each source of uncertainty to the overall uncertainty in the target output and thus facilitates engineering decision-making.

Uncertainty Quantification of Landslide Generated Waves Using Gaussian Process Emulation and Variance-Based Sensitivity Analysis

Simulations of landslide generated waves (LGWs) are prone to high levels of uncertainty. Here we present a probabilistic sensitivity analysis of an LGW model. The LGW model was realised through a smooth particle hydrodynamics (SPH) simulator, which is capable of modelling fluids with complex rheologies and includes flexible boundary conditions. This LGW model has parameters defining the landslide, including its rheology, that contribute to uncertainty in the simulated wave characteristics. Given the computational expense of this simulator, we made use of the extensive uncertainty quantification functionality of the Dakota toolkit to train a Gaussian process emulator (GPE) using a dataset derived from SPH simulations. Using the emulator we conducted a variance-based decomposition to quantify how much each input parameter to the SPH simulation contributed to the uncertainty in the simulated wave characteristics. Our results indicate that the landslide’s volume and initial submergence depth contribute the most to uncertainty in the wave characteristics, while the landslide rheological parameters have a much smaller influence. When estimated run-up is used as the indicator for LGW hazard, the slope angle of the shore being inundated is shown to be an additional influential parameter. This study facilitates probabilistic hazard analysis of LGWs, because it reveals which source characteristics contribute most to uncertainty in terms of how hazardous a wave will be, thereby allowing computational resources to be focused on better understanding that uncertainty.

Estimation of probabilistic hazard for Bingol province, Turkey

Due to the fact that Bingol province is at the intersection of the North Anatolian Fault and the Eastern Anatolian Fault, the seismicity of the region is important. In this study, probabilistic seismic hazard analyzes (PSHA) were conducted to cover the boundaries of Bingol province. It occurred since 1900, the seismicity of the region was obtained statistically by considering the earthquake records with a magnitude greater than 4 and the Gutenberg-Richter correlation. In the study, magnitude-frequency relationship, seismic hazard and repetition periods were obtained for certain time periods (10, 20, 30, 40, 50, 75 and 100 years). Once a project area determined in this study, which may affect the peak ground acceleration according to various attenuation relationships are calculated and using the Turkey Earthquake Hazard Map, average acceleration value for Bingol province were determined. As a result of the probabilistic seismic hazard analysis, the project earthquakes with a probability of exceeding 50 years indicate that the magnitude of the project earthquake is 7.4 and that the province is in a risky area in terms of seismicity. The repetition periods of earthquakes of 6.0, 6.5, 7.0 and 7.5 are 42, 105, 266 and 670 years respectively. Within the province of Bingol; the probability of exceeding 50 years is 2%, 10% and 50%, while the peak ground acceleration values are 1.03 g, 0.58 g and 0.24 g. As a result, probabilistic seismic hazard analysis shows that the seismicity of the region is high and the importance of considering the earthquake effect during construction is emphasized for this region.

Illustrative Analysis of Probabilistic Sea Level Rise Hazard

AbstractSea level rise results from several contributing physical processes, including ocean thermal expansion and glacier and ice sheet mass loss. Future projections of sea level remain highly uncertain due to several sources of aleatory and epistemic uncertainty. Quantifying different sources of sea level rise involves considering possible pathways of future radiative forcing and integrating models of different sea level rise processes. The probabilistic hazard analysis strategy has been proposed for combining sea level rise prediction models and climate forcing scenarios to examine sea level rise prediction uncertainty and the sources of this uncertainty. In this study we carry out an illustrative probabilistic sea level rise hazard analysis using ensembles of sea level rise predictions and emissions scenarios from the literature. This illustrative analysis allows us to estimate the probability that sea level rise will exceed a specified threshold at a given location and time and highlights how sea level rise uncertainty is sensitive to scenario inputs and sea level rise projection modeling choices. Probabilistic hazard is depicted for Earth using sea level rise hazard maps. We also demonstrate how hazard deaggregation can help us quantify the relative contributions of sea level rise sources, prediction models, and climate forcing scenarios to sea level rise hazard. The ice sheet contribution to sea level rise has a large impact on probabilistic projection of sea level rise due to the disagreements between current ice sheet models related to differences in modeling ice sheet instability.

A New Approach for Probabilistic Risk Assessment of Ship Collision with Riverside Bridges

The configuration of riverside bridges, such as the spatial distribution, wading status, and ship accessibility of piers, is generally different from river‐crossing bridges. Thus, the ship collision risk of riverside bridges cannot be assessed using conventional assessment methods applicable to river‐crossing bridges. The aim of this paper is, therefore, to develop a new probabilistic method for assessing the risk of ship collision with riverside bridges. First, a fully probabilistic framework for assessing the ship‐bridge collision risk is presented. Second, a new probabilistic hazard analysis model of ship collision with riverside bridges is proposed, based on a combined study of riverside bridge characterization and an improved yaw ship collision model. A simplified empirical model for evaluating ship‐bridge collision force is then adopted, and the probabilistic distribution of the collision force is obtained based on Monte Carlo simulation. Furthermore, finite element simulation is conducted to estimate the collapse probability of piers. Finally, the method developed is applied to the probabilistic assessment of ship collision risk with riverside bridges located at Shabin Road, Chongqing, China. The results show that the risk of ship‐bridge collision at Shabin Road is low to moderate. The example demonstrated indicates that the methodology introduced in this paper is capable of assessing the ship‐bridge collision risk in a concise and rapid way.

Statistical theory of probabilistic hazard maps: a probability distribution for the hazard boundary location

Abstract. The study of volcanic flow hazards in a probabilistic framework centers around systematic experimental numerical modeling of the hazardous phenomenon and the subsequent generation and interpretation of a probabilistic hazard map (PHM). For a given volcanic flow (e.g., lava flow, lahar, pyroclastic flow, ash cloud), the PHM is typically interpreted as the point-wise probability of inundation by flow material. In the current work, we present new methods for calculating spatial representations of the mean, standard deviation, median, and modal locations of the hazard's boundary as ensembles of many deterministic runs of a physical model. By formalizing its generation and properties, we show that a PHM may be used to construct these statistical measures of the hazard boundary which have been unrecognized in previous probabilistic hazard analyses. Our formalism shows that a typical PHM for a volcanic flow not only gives the point-wise inundation probability, but also represents a set of cumulative distribution functions for the location of the inundation boundary with a corresponding set of probability density functions. These distributions run over curves of steepest probability gradient ascent on the PHM. Consequently, 2-D space curves can be constructed on the map which represents the mean, median, and modal locations of the likely inundation boundary. These curves give well-defined answers to the question of the likely boundary location of the area impacted by the hazard. Additionally, methods of calculation for higher moments including the standard deviation are presented, which take the form of map regions surrounding the mean boundary location. These measures of central tendency and variance add significant value to spatial probabilistic hazard analyses, giving a new statistical description of the probability distributions underlying PHMs. The theory presented here may be used to aid construction of improved hazard maps, which could prove useful for planning and emergency management purposes. This formalism also allows for application to simplified processes describable by analytic solutions. In that context, the connection between the PHM, its moments, and the underlying parameter variation is explicit, allowing for better source parameter estimation from natural data, yielding insights about natural controls on those parameters.

Probabilistic hazard analysis for tsunamis generated by subaqueous volcanic explosions in the Campi Flegrei caldera, Italy

A probabilistic hazard analysis of tsunami generated by subaqueous volcanic explosion is applied to the Campi Flegrei caldera (Campania, Italy). An event tree is developed to quantify the tsunami hazard due to the submarine explosions by: i) defining potential size classes of explosion magnitude on the basis of past volcanic activity in the Campi Flegrei caldera and sites in the underwater part of the caldera; ii) simulating the generation and propagation of the consequent tsunami waves able to reach the coasts of the Campania region for all combinations of tsunami-generating vents and sizes; and iii) quantifying the tsunami probability and relative uncertainty, conditional upon the occurrence of an underwater eruption at Campi Flegrei. Tsunami hazard generated by subaqueous volcanic explosions is considered crucial because of its potential high impact on the densely populated coastal areas of the Pozzuoli Bay and Gulf of Naples even if the probability for eruptions in the submarine part of the caldera is certainly low. The tsunami hazard analysis is presented using conditional hazard curves and maps, that is calculating the probability (and relative uncertainties) of exceeding given tsunami intensity thresholds (wave amplitudes at the coast), given the occurrence of a subaqueous eruption. The results indicate that a significant tsunami hazard exists in many areas of the Bay of Naples.

Probabilistic Landslide-Generated Tsunamis in the Indus Canyon, NW Indian Ocean, Using Statistical Emulation

The Indus Canyon in the northwestern Indian Ocean has been reported to be the site of numerous submarine mass failures in the past. This study is the first to investigate potential tsunami hazards associated with such mass failures in this region. We employed statistical emulation, i.e. surrogate modelling, to efficiently quantify uncertainties associated with slump-generated tsunamis at the slopes of the canyon. We simulated 60 slump scenarios with thickness of 100–300 m, width of 6–10.5 km, travel distances of 500–2000 m and submergence depth of 250–450 m. These scenarios were then used to train the emulator and predict 500,000 trial scenarios in order to study probabilistically the tsunami hazard over the near field. Due to narrow–deep canyon walls and the shallow continental shelf in the adjacent regions (<100 m water depth), the tsunami propagation has a unique pattern as an ellipse stretched in the NE–SW direction. The results show that the most likely tsunami amplitudes and velocities are approximately 0.2–1.0 m and 2.5–13 m/s, respectively, which can potentially impact vessels and maritime facilities. We demonstrate that the emulator-based approach is an important tool for probabilistic hazard analysis since it can generate thousands of tsunami scenarios in few seconds, compared to days of computations on High Performance Computing facilities for a single run of the dispersive tsunami solver that we use here.

Exposure-based risk assessment and emergency management associated with the fallout of large clasts at Mount Etna

Abstract. Fallout of ballistic blocks and bombs ejected from eruptive vents represents a well-known hazard in areas proximal to volcanoes (mostly &lt;5 km from the vent). However, fallout of large clasts sedimenting from plume margins that extend to medial areas and have the potential to produce severe injuries to people and cause damage to infrastructure, is often overlooked. Recent eruptive events at Mount Etna (Italy) provide a clear example where large-clast fallout from plume margins (&gt;5 cm) has posed a real threat both to the many visitors reaching the summit area and to local infrastructure, and, therefore, has been selected as a case study. To quantify this hazard, a new particle sedimentation model was calibrated with field data and then used for probabilistic hazard assessments. For a fully probabilistic scenario the hazard zone covered 72 km2 and included some 125 km of paths and roads, as well as 15 buildings. Evacuation on foot to a safe area was estimated at almost 4 h, but this could be reduced to less than 3 h if two shelters were provided. Our results show the importance of integrating probabilistic hazard analysis of large-clast fallout within effective strategies of risk management and reduction, especially in the case of volcanoes where visitors can reach the summit areas.

Sensitivity analysis study of the source parameter uncertainty factors for predicting near-field strong ground motion

Uncertainty factors have substantial influences on the numerical simulations of earthquakes. However, most simulation methods are deterministic and do not sufficiently consider those uncertainty factors. A good approach for predicting future destructive earthquakes that is also applied to probabilistic hazard analysis is studying those uncertainty factors, which is very significant for improving the reliability and accuracy of ground-motion predictions. In this paper, we investigated several uncertainty factors, namely the initial rupture point, stress drop, and number of sub-faults, all of which display substantial influences on ground-motion predictions, via sensitivity analysis. The associated uncertainties are derived by considering the uncertainties in the parameter values, as those uncertainties are associated with the ground motion itself. A sensitivity analysis confirms which uncertainty factors have large influences on ground motion predictions, based upon which we can allocate appropriate weights to those uncertainty factors during the prediction process. We employ the empirical Green function method as a numerical simulation tool. The effectiveness of this method has been previously validated, especially in areas with sufficient earthquake record data such as Japan, Southwest China, and Taiwan, China. Accordingly, we analyse the sensitivities of the uncertainty factors during a prediction of strong ground motion using the empirical Green function method. We consequently draw the following conclusions. (1) The stress drop has the largest influence on ground-motion predictions. The discrepancy between the maximum and minimum PGA among three different stations is very large. In addition, the PGV and PGD also change drastically. The Arias intensity increases exponentially with an increase in the stress drop ratio of two earthquakes. (2) The number of sub-faults also has a large influence on various ground-motion parameters but a small influence on the Fourier spectrum and response spectrum. (3) The initial rupture point largely influences the PGA and Arias intensity. We will accordingly pay additional attention to these uncertainty factors when we conduct ground-motion predictions in the future.

Reliability-based fragility analysis of nonlinear structures under the actions of random earthquake loads

This study presents the reliability-based analysis of nonlinear structures using the analytical fragility curves excited by random earthquake loads. The stochastic method of ground motion simulation is combined with the random vibration theory to compute structural failure probability. The formulation of structural failure probability using random vibration theory, based on only the frequency information of the excitation, provides an important basis for structural analysis in places where there is a lack of sufficient recorded ground motions. The importance of frequency content of ground motions on probability of structural failure is studied for different levels of the nonlinear behavior of structures. The set of simulated ground motion for this study is based on the results of probabilistic seismic hazard analysis. It is demonstrated that the scenario events identified by the seismic risk differ from those obtained by the disaggregation of seismic hazard. The validity of the presented procedure is evaluated by Monte-Carlo simulation.

Probabilistic flood risk analysis considering morphological dynamics and dike failure

A comprehensive flood risk assessment should aim not only at quantifying uncertainties but also the variability of risk over time. In this study, an efficient modelling framework was proposed to perform probabilistic hazard and risk analysis in dike-protected river systems accounting for morphological variability and uncertainty. The modelling framework combined the use of: (1) continuous synthetic discharge forcing, (2) a stochastic dike breach model dynamically coupled to a stochastic unsteady one-dimensional hydraulic model (MIKE1D) describing river flows, (3) a catalogue of pre-run probabilistic inundation maps (MIKE SHE) and (4) a damage and loss model (CAPRA). The methodology was applied using continuous simulations to a 45-km reach of the Upper Koshi River, Nepal, to investigate the changes in breach and flood hazards and subsequent risks after 2 and 5 years of probable river bed aggradation. The study results indicated an increase in annual average loss of 4% per year driven by changes in loss distribution in the most frequent loss return periods (20–500 years). The use of continuous simulations and dike breach model also provided a more robust estimation of risk metrics as compared to traditional binary treatment of flood defence and/or the direct association of flow with loss return periods. The results were helpful to illustrate the potential impacts of dynamic river morphology, dike failure and continuous simulation and their significance when devising flood risk study methodologies.

Risk and hazard assessment of extreme natural events for critical infrastructures

Human society is frequently surprised by extreme natural events that lead to tremendous losses both in human lives as well as in economic capital. Risk assessment methods regularly fail to predict such disasters by treating extreme events as low probability, tolerable ones. Critical infrastructures and life lines are often found to be poorly protected due to their inadequate design basis. A method of hazard assessment for extreme natural events is presented that allows for the consideration of unexpected extreme events (‘black swan’ events). Including such events into the design basis prevents the failure of critical infrastructures due to ‘cliff-edge’ effects. The method makes use of some general properties of heavy-tailed distributions and the mathematical theory of records, and takes advantage of a distribution-free approach without need to calculate probabilities of exceedance. The application of the method is demonstrated on several examples for nuclear power plants (NPP), including High Wind and High Temperature hazards. The results are compared with the results of hazard assessment using conventional probabilistic hazard analysis methods. The risk implications are discussed.

Target Structural Reliability Analysis for Tsunami Hydrodynamic Loads of the ASCE 7 Standard

AbstractMany coastal areas in the United States are subject to tsunami hazard. The public safety risk has been partially mitigated through warning and preparedness of evacuation, but community disaster resilience requires that critical and essential facilities provide structural resistance to collapse. Furthermore, there are coastal communities in the states of Alaska, Washington, Oregon, California, and Hawaii where there is insufficient time for evacuation. The Tsunami Loads and Effects Subcommittee of the ASCE/Structural Engineering Institute (ASCE/SEI) 7 Standards Committee has developed a new Chapter 6, titled “Tsunami Loads and Effects,” for the 2016 edition of the ASCE 7 standard Minimum Design Loads for Buildings and Other Structures (Minimum design loads for buildings and other structures). The new ASCE 7 provisions for tsunami loads and effects implements a unified set of analysis and design methodologies that are consistent with probabilistic hazard analysis, tsunami physics, and reliability an...

A note on peak accelerations computed from sliding of objects during the 1969 Banja Luka earthquakes in former Yugoslavia

Peak ground accelerations, computed from sliding of objects during the 1969 Banja Luka earthquakes in Bosnia and Herzegovina (former Yugoslavia) are computed assuming that the ground motion consists of simple rectangular or sinusoidal pulses. The results show good agreement with observed macroseismic estimates of shaking based on the Mercalli–Cancani–Sieberg (MCS) intensity scale. The results are also in compliance with recorded accelerations during the 1973–1986 period and with recent probabilistic hazard analyses for the Banja Luka region.

Concept of decision graphical framework for optimising adaptation of civil infrastructure to a changing climate

This article proposes a framework for decision optimisation for adaptation of civil infrastructure to a changing climate, taking basis in decision graphical representation. The focus of the article is to develop a platform on which multiple climate scenarios and general circulation models, results from probabilistic hazard analysis as well as consequence analysis – together with their uncertainties – are represented in a practically operational manner. The output from the decision framework is the optimal timing and magnitude of the adaptation. First, assumptions underlying the proposed decision framework and types of information required are provided. Thereafter, the proposed decision framework is presented. This work provides the concept only; however, it serves as an exercise and thus provides a research direction on how to collect and summarise information for the purpose to approach to the civil infrastructure adaptation in an emerging climate change.

The influence of probabilistic volcanic hazard map properties on hazard communication

Probabilistic volcanic hazard analysis is becoming an increasingly popular component of volcanic risk reduction strategies worldwide. While probabilistic hazard analyses offer many advantages for decision-making, displaying the statistical results of these analyses on a map presents new hazard communication challenges. Probabilistic information is complex, difficult to interpret, and associated with uncertainties. Conveying such complicated data on a static map image without careful consideration of user perspectives or context, may result in contrasting interpretations, misunderstandings, or aversion to using the map. Here, we present the results of interviews and surveys conducted with organisational stakeholders and scientists in New Zealand which explored how probabilistic volcanic hazard map properties influence map interpretation, understanding, and preference. Our results suggest that data classification, colour scheme, content, and key expression play important roles in how users engage with and interpret probabilistic volcanic hazard maps. Data classification was found to influence the participants’ perceived uncertainty and data reading accuracy, with isarithmic style maps reducing uncertainty and increasing accuracy best. Colour scheme had a strong influence on the type of hazard messages interpreted, with a red-yellow scheme conveying the message of a hazard distribution (high to low), and a red-yellow-blue scheme conveying the message of hazard state (present or absent) and/or risk. Multiple types of map content were found to be useful, and hazard curves were viewed as valuable supplements. The concept of “confidence” was more easily interpreted than upper and lower percentiles when expressing uncertainty on the hazard curves. Numerical and verbal expression in the key also had an influence on interpretation, with a combination of both a percent (e.g., 25%) and a natural frequency (e.g., 1 in 4) “probability” being the most inclusive and widely-understood expression. The importance of these map property choices was underscored by a high portion of participants preferring to receive maps in unalterable formats, such as PDF. This study illustrates how engaging with users in a bottom-up approach can complement and enhance top-down approaches to volcanic hazard mapping through a collaborative and integrative design process which may help to prevent miscommunications in a future crisis when maps are likely to be drafted and disseminated rapidly.

Assessment of seismic hazard in the Erzincan (Turkey) region: construction of local velocity models and evaluation of potential ground motions

Abstract: The fundamental step in estimation of seismic damage and losses in urban areas is identification of regional potential seismic hazard. The accuracy of seismic analyses depends on the reliability of the local input parameters used in the corresponding hazard and loss models. This paper presents detailed seismic hazard analyses for an earthquake-prone region using locally derived source and site parameters. Main components of this study are construction of local seismic velocity models, probabilistic and deterministic seismic hazard analyses, and estimation of corresponding potential ground motions. The study area is Erzincan, which is a city on the eastern part of the North Anatolian Fault Zone. Located at a triple junction of major fault systems within a basin structure, Erzincan experienced major events (Ms ~8.0) in 1939 and (Mw = 6.6) in 1992. This study presents the first discussion in the literature on site-specific probabilistic and deterministic hazard analyses for Erzincan. Using locally derived input parameters in site response modeling and hazard analyses, the earthquake potential of Erzincan is investigated in detail. Probabilistic seismic hazard analyses with a hybrid source model composed mainly of line sources show that for a return period of 475 years, the maximum peak ground acceleration value in the Erzincan city center is computed to be almost 1 g. On the other hand, probabilistic hazard analyses with only area sources yield ground motion amplitudes that are almost half of those obtained by the hybrid model. The deterministic hazard analyses also show that peak ground acceleration in the city center for a scenario event of Mw = 7.0 reaches 1.25 g at a soft soil site located at 2 km in distance from the fault plane. In summary, numerical results obtained with locally derived input parameters indicate that Erzincan has significant potential for hazard in terms of both local earthquake occurrence and site amplifications.

A first hazard analysis of the Quaternary Harrat Al-Madinah volcanic field, Saudi Arabia

The northern portion of the 20,000km2 Harrat Rahat basaltic field in NW Saudi Arabia (Harrat Al-Madinah) has hosted some of the most recent volcanic eruptions in the country. Rapid growth of the city of Al-Madinah has spread out onto the lava flows and scoria cones of the Harrat, increasing exposure to any potential renewed volcanism. We present here a first-order probabilistic hazard analysis related to new vent formation and subsequent lava flow from this volcanic field. The 501 visible eruption vent sites were integrated with aeromagnetic survey data (as representative of potential regions of buried volcanic vents) to develop a probability density function for new eruption sites using Gaussian kernel smoothing. This revealed a NNW striking zone of high spatial hazard terminating <10km south of the city. Using the properties of the AD1256 eruption lava flows and the spatial PDF, an analysis of lava hazard was carried out. Assuming a future lava-producing eruption, around 25% of the city of Al-Madinah is exposed to a probability of 0.001 to 0.005 of lava inundation. The temporal eruption recurrence rate is estimated at approximately one vent per 3300years, but the temporal record of the field is so poorly constrained that the lower and upper bounds for the recurrence interval are 13,300yrs and 70yrs, respectively. Applying a Poisson temporal model, this results in a worst-case lava inundation recurrence interval of approximately 14,300years.