Quantification Of Hazard Research Articles

Experimental study on the thermal runaway hazard quantification and its assessment parameters in the lithium-ion battery

Thermal runaway (TR) is a thermal disaster in the lithium-ion battery (LIB). The TR hazard in the LIBs with different battery characteristic and under different TR triggering method is distinctive, and it is of great significance to quantify the TR hazard as a criterion for TR quantified suppression for its further development. This study has investigated the TR hazard assessment parameters (HAPs) in the batteries of different rated capacity Rc and battery number N under different TR triggering method, and raised a novel method for TR hazard quantification based on these HAPs. The results show: (1) under different triggering method, the HAPs are increased with the increase of overcharging rate Cr and the decrease of heating power Ph, but not explicit with the change of punching speed Ps, and increased with Rc in most cases; (2) the quantified TR hazard HTR-q is greater in the cases of overcharging and punching, and is 1.52 times greater in the confined space under the same case in the open space. Besides, The Rc and HTR-q form a quadratic function relationship, and N and HTR-q a linear relationship. Moreover, a computing model of HTR-q is proposed with the input of, self-characteristics of battery Sc and TR triggering intensity It, which exhibits the average error of 6 % approximately. This is expected to become a novel method in TR hazard assessment, and offer guidance on the setting of key parameters for TR suppression.

Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method

This study aims to assess the level of groundwater pollution risk in the Triffa Plain, stemming from various pollution sources, with a specific focus on agricultural intensification and excessive pesticide use. Data were collected from ABHM (the Moulouya Hydraulic Basin Agency) and ORMVAM (Regional Office of Moulouya Agricultural Development), and a field visit was conducted in July 2023. The study utilized two main methodologies for mapping risk intensity: the COST 620 action and overlaying vulnerability maps with the land use (LU) factor. Vulnerability maps were generated using the original DRASTIC method and the new dynamic vulnerability assessment method, GCITF.The research approach involved comparing the COST 620 risk index (Ri) and the land use risk index (LU) to identify the most suitable method for the study area. Due to challenges in inventorying various point sources of pollution, the study focused on mapping the primary sources of pollution (diffuse, point, and linear). The key findings indicate that the predominant pollution intensity in the region is high, covering 60.66% of the total surface area. These results closely align with those obtained using the European COST 620 approach and the spatial distribution of nitrates. The study demonstrates the reliability of integrating the GCITF method in assessing groundwater contamination risk, highlighting the significant negative impacts of agricultural activities on the Triffa Plain aquifer, primarily due to uncontrolled pesticide and fertilizer use and point sources of pollution.This study suggests that implementing targeted technical solutions for specific pollution sources is crucial for reducing contamination in the Triffa Plain. These pollution risk intensity maps can assist planners and decision-makers in understanding the origin of pollution and identifying necessary actions to minimize contamination risk, contributing to better groundwater management and protection in the region.

Estimation of Intensity‐Duration‐Area‐Frequency Relationships Based on the Full Range of Non‐Zero Precipitation From Radar‐Reanalysis Data

AbstractIntensity‐Duration‐Area‐Frequency (IDAF) models provide the mathematical link between precipitation intensities (I), durations (D), areas (A), and frequency of occurrence (F). They play a critical role in hydrological design, areal rainfall hazard quantification, storm characterization, and early warning system development. IDAF models extend the conventional Intensity‐Duration‐Frequency models by accounting for the spatial extent of precipitation (i.e., the area). In this study, we develop IDAF models using the entire non‐zero precipitation intensities, not only the extremes. We use the extended generalized Pareto distribution (EGPD) to model the precipitation intensities. To build the IDAF models, we adopt a data‐driven approach that allows the linkage of EGPD parameters with duration and area, based on empirically determined parametric relationships. The inference of model parameters is done using a global maximum likelihood estimation, and uncertainties are assessed by the bootstrap method. The study area is Switzerland, a topographically complex region of 42,000 km2 with regional precipitation variability and clear seasonality. The study utilizes 17 years of data from CombiPrecip, a radar‐reanalysis product developed by geostatistically merging radar and rain gauge data in an operational setting. We build the IDAF models for the spatiotemporal range of 1–72 hr and 1 to 1,089 km2 at each pixel in the study area. To the best of our knowledge, our study is the first attempt to use the EGPD in IDAF curve modeling. It discusses the use and limitations of CombiPrecip in extreme value analysis and highlights the challenges of modeling areal precipitation in a complex topographical environment.

Quantifying flood risks during monsoon and post-monsoon seasons: An integrated framework for resource-constrained coastal regions

Global coastal regions are transforming into “flooding hot-spots” due to the multi-faceted confluence of several flood-drivers. Unfortunately, these regions are often poorly gauged, hindering comprehensive flood hazard quantification. Besides summer-monsoon floods, post-monsoon rainfalls induced by cyclonic-depressions have escalated the flood risks in the coastal regions. For the first time, the present study captures the seasonal flood hazards by disentangling monsoon (June, July, August, and September) and post-monsoon (October, November, and December) periods of rainfall. An integrated MIKE + 1D-2D coupled model was used to generate flood hazard risks for Jagatsinghpur district (Odisha, India), a resource-constrained multi-hazard catchment in the Lower Mahanadi River Basin. Due to limited data for this coastal region, we investigated the performance of CHIRPS v2.0, a global Satellite Precipitation Product (SPP) with high spatiotemporal characteristics, for capturing extreme rainfall events and deriving flood hazards at the inundation scale. We observed higher magnitude of flood hazards are prominent in the coastal villages, emerging from a complex interaction between rainfall and storm-tide events. Three widely used Archimedean copulas were implemented to capture the rainfall and storm-tide events' joint (bivariate) behavior and their implications on population exposure, which is valuable for mapping flood hazard risks. We observed that univariate analysis (Ua) significantly underestimates the flood hazard over bivariate analysis (Ba) during both periods. Interestingly, the results are more pronounced in the population exposure estimates as ∼47 % (monsoon) and ∼54 % (post-monsoon) of the population are exposed based on univariate analysis against ∼65 % (monsoon) and ∼60 % (post-monsoon) under bivariate analysis. Our study highlights the necessity of disentangling rainfall time-series for foreseeing under-shadowed flood risks, vital for designing flood combating structures, evacuation plans, land use planning, and flood governance. The results further enhance our understanding of monsoon and post-monsoon flood hazards and their associated risks under different return periods.

Deciphering Complex Morphology and Structural Connectivity of High-Magnitude Deep-Seated Landslides via Airborne Laser Scanning: A Case Study in the Vrancea Seismic Region, Romanian Carpathians

In the Vrancea seismic region (Romanian Carpathians; the most important intermediate-depth seismic source of Europe), the morphology of the slopes is often marked by the existence of numerous high-magnitude, deep-seated active, dormant or relict landslides, which are the subjects of many cases of functional and structural connectivity. Due to the compact and extensive (coniferous and broad leaved) forest coverage and because of the lack of publicly available regional high-resolution DEMs, it is usually difficult to fully understand the morphogenetic framework of such large, deep-seated landslides in order to assess their frequency–magnitude relationship, a key issue in hazard quantification. However, the high impact of such landslides on river networks requires an in-depth understanding of the multi-hazard framework, as cascading effects are likely to affect the presently growing human activities developing along the valleys. Within a case study represented by a 2.5 km long deep-seated landslide, that caused a 500 m lateral occlusion of Buzău River, we used integrated remote sensing technologies (UAV laser scanning) and in situ (geomorphic mapping and ERT investigations) techniques, which allowed us to better understand the structural connectivity which conditions the landslide hazard in such complex morphogenetic conditions, outlining the present potential of the regional seismo-climatic context to trigger potential high-magnitude chain effects.

Geological earthquake simulations generated by kinematic heterogeneous energy-based method: Self-arrested ruptures and asperity criterion

Abstract The lack of clarity regarding slip distribution within heterogeneous rupture areas has a significant impact on characterizing the seismic source and the role of heterogeneities in determining ground motion. One approach to understand the rupture process is through dynamic simulations, which require substantial computational resources, thereby limiting our comprehension of seismic rupture processes. Consequently, there is a need for methods that efficiently describe the spatial complexities of seismic rupture in a realistic manner. To address this, the statistics of real self-arrested ruptures that conform to the asperity criterion are investigated. This research demonstrates that power law distributions can describe the final slip statistics. Regarding the computational efficiency, a simple heterogeneous energy-based (HE-B) method is proposed. The HE-B method is characterized by the spatial correlation between the rupture parameters, such as the final slip or the rupture velocity, and the distribution of residual energy which determines the zones where the rupture could occur. In addition, the HE-B method defines the rupture area in those zones of the fault where the coupling function exceeds the energy required for rupture initiation. Therefore, the size of the earthquake is directly influenced by the distribution of coupling within faults. This method also leads to the successful reproduction of the statistical characteristics of final slip and generates slip rates that match the kinematic behavior of seismic sources. Notably, this kinematic rupture simulation produces seismic moment rates characterized by f − 1 {f}^{-1} and f − 2 {f}^{-2} spectra with a double corner frequency. Finally, it is observed that the maximum fracture energy value within the ruptured area is strongly correlated with both the magnitude and peak seismic moment rate. Thus, by employing this method, realistic rupture scenarios can be generated efficiently, enabling the study of spatial correlations among rupture parameters, ground motion simulations, and quantification of seismic hazard.

Assessment of health hazard due to fluoride in groundwater from a rural area in east‐coast of India and remedial measures

AbstractThe present research deals with the quantification of health hazard in a fluorosis prone area from east‐coast of India. The average health hazard quotients are 2.09, 2.42, 1.79, and 1.69 for infants, children, male, and female adults, respectively. These values are more than the tolerance limit (1) in 92% groundwater samples and 96% of the study area. The children are more vulnerable to fluorosis than infants and adults. Ca2+/ Na+ versus HCO3−/Na+ and Ca2+/Na+ versus Mg2+/Na+ plots suggest silicate weathering as the prime factor while linear relationship of TDS versus NO3− + (Cl−/HCO3−) supports the anthropogenic input of F− to the aquifer system. The study suggests that the F− ions are chiefly derived from fluorite, apatite, biotite, and hornblende present in the granitic basement under alkaline environment. The secondary sources are domestic and industrial sewage as well as return flow from irrigation with ingredients of phosphate fertilizers. The adverse effects of fluorosis can be minimized by mass awareness programmes, alternative source of potable drinking water, defluoridation techniques, dilution of high F− concentration in groundwater, and minimizing the use of phosphate fertilizers.

Quantification of Groundwater Hazards Related to Fluvial Floods via Groundwater Flow Modelling: A Review

Flood-related issues include the impact of groundwater on flood protection measures and other subsurface structures in a protected area. At the same time, subsurface elements of flood protection structures may significantly influence the natural groundwater regime and affect existing structures during non-flood periods. The paper provides an overview of hazardous factors linked to groundwater and specifies variables for the quantification of related hazards. Appropriate hydraulic groundwater flow models are presented and discussed, and their suitability for the modelling of individual typical problems and for hazard quantification is specified. The use of models and the application of CAD and GIS tools for data pre- and post-processing is mentioned in brief and demonstrated on examples of typical practical situations.

Calibration of imperfect geophysical models by multiple satellite interferograms with measurement bias

Model calibration consists of using experimental or field data to estimate the unknown parameters of a mathematical model. The presence of model discrepancy and measurement bias in the data complicates this task. Satellite interferograms, for instance, are widely used for calibrating geophysical models in geological hazard quantification. In this work, we used satellite interferograms to relate ground deformation observations to the properties of the magma chamber at Kīlauea Volcano in Hawai‘i. We derived closed-form marginal likelihoods and implemented posterior sampling procedures that simultaneously estimate the model discrepancy of physical models, and the measurement bias from the atmospheric error in satellite interferograms. We found that model calibration by aggregating multiple interferograms and downsampling the pixels in the interferograms can reduce the computation complexity compared to calibration approaches based on multiple data sets. The conditions that lead to no loss of information from data aggregation and downsampling are studied. Simulation illustrates that both discrepancy and measurement bias can be estimated, and real applications demonstrate that modeling both effects helps obtain a reliable estimation of a physical model’s unobserved parameters and enhance its predictive accuracy. We implement the computational tools in the RobustCalibration package available on CRAN.

Environmental hazard quantification toolkit based on modular numerical simulations

Abstract. Quantifying impacts on the environment and human health is a critical requirement for geological subsurface utilisation projects. In practice, an easily accessible interface for operators and regulators is needed so that risks can be monitored, managed, and mitigated. The primary goal of this work was to create an environmental hazards quantification toolkit as part of a risk assessment for in-situ coal conversion at two European study areas: the Kardia lignite mine in Greece and the Máza-Váralja hard coal deposit in Hungary, with complex geological settings. A substantial rock volume is extracted during this operation, and a contaminant pool is potentially left behind, which may put the freshwater aquifers and existing infrastructure at the surface at risk. The data-driven, predictive tool is outlined exemplary in this paper for the Kardia contaminant transport model. Three input parameters were varied in a previous scenario analysis: the hydraulic conductivity, as well as the solute dispersivity and retardation coefficient. Numerical models are computationally intensive, so the number of simulations that can be performed for scenario analyses is limited. The presented approach overcomes these limitations by instead using surrogate models to determine the probability and severity of each hazard. Different surrogates based on look-up tables or machine learning algorithms were tested for their simplicity, goodness of fit, and efficiency. The best performing surrogate was then used to develop an interactive dashboard for visualising the hazard probability distributions. The machine learning surrogates performed best on the data with coefficients of determination R2>0.98, and were able to make the predictions quasi-instantaneously. The retardation coefficient was identified as the most influential parameter, which was also visualised using the toolkit dashboard. It showed that the median values for the contaminant concentrations in the nearby aquifer varied by five orders of magnitude depending on whether the lower or upper retardation range was chosen. The flexibility of this approach to update parameter uncertainties as needed can significantly increase the quality of predictions and the value of risk assessments. In principle, this newly developed tool can be used as a basis for similar hazard quantification activities.

A simple two-state model interprets temporal modulations in eruptive activity and enhances multivolcano hazard quantification.

Volcanic activity typically switches between high-activity states with many eruptions and low-activity states with few or no eruptions. We present a simple two-regime physics-informed statistical model that allows interpreting temporal modulations in eruptive activity. The model enhances comprehension and comparison of different volcanic systems and enables homogeneous integration into multivolcano hazard assessments that account for potential changes in volcanic regimes. The model satisfactorily fits the eruptive history of the three active volcanoes in the Neapolitan area, Italy (Mt. Vesuvius, Campi Flegrei, and Ischia) which encompass a wide range of volcanic behaviors. We find that these volcanoes have appreciably different processes for triggering and ending high-activity periods connected to different dominant volcanic processes controlling their eruptive activity, with different characteristic times and activity rates (expressed as number of eruptions per time interval). Presently, all three volcanoes are judged to be in a low-activity state, with decreasing probability of eruptions for Mt. Vesuvius, Ischia, and Campi Flegrei, respectively.

Drought Risk Evaluation in Iran by Using Geospatial Technologies

A drought risk map has been developed at the national scale by using remote-sensing satellite data over Iran by combining output layers resulting from three main components of a risk-evaluation procedure including Hazard Quantification (HQ), Vulnerability Assessment (VA) and Identification of Elements at Risk (IER) in a GIS environment. In this respect, Drought Severity (DS) was calculated by using the monthly Normalized Difference Vegetation Index (NDVI) (over 31 years from 1986–2016). Iran landcover classification and a slope map, population density maps, and irrigated farm percentages at the provincial scale were utilized within the drought risk evaluation (DRE) process. The final risk map reveals that the northwest of the country, with a climate similar to the central European weather conditions, is exposed to the maximum drought risk. In contrast, the areas with an arid climate, mainly located in the middle of Iran, exhibits minimum risk against drought. Based on the risk map, the southern part of the Caspian Sea shows very low drought risk due to the moderate and subtropical climate in this region. The outputs of this research will provide advice and warnings to help decision makers reduce drought risk consequences after prioritizing risk areas at the administrative scale.

VIGIL: A Python tool for automatized probabilistic VolcanIc Gas dIspersion modeLling

Probabilistic volcanic hazard assessment is a standard methodology based on running a deterministic hazard quantification tool multiple times to explore the full range of uncertainty in the input parameters and boundary conditions, in order to probabilistically quantify the variability of outputs accounting for such uncertainties. Nowadays, different volcanic hazards are quantified by means of this approach. Among these, volcanic gas emission is particularly relevant given the threat posed to human health if concentrations and exposure times exceed certain thresholds. There are different types of gas emissions but two main scenarios can be recognized: hot buoyant gas emissions from fumaroles and the ground and dense gas emissions feeding density currents that can occur, e.g., in limnic eruptions. Simulation tools are available to model the evolution of critical gas concentrations over an area of interest. Moreover, in order to perform probabilistic hazard assessments of volcanic gases, simulations should account for the natural variability associated to aspects such as seasonal and daily wind conditions, localized or diffuse source locations, and gas fluxes. Here we present VIGIL (automatized probabilistic VolcanIc Gas dIspersion modeLling), a new Python tool designed for managing the entire simulation workflow involved in single and probabilistic applications of gas dispersion modelling. VIGIL is able to manage the whole process from meteorological data processing, needed to run gas dispersion in both the dilute and dense gas flow scenarios, to the post processing of models’ outputs. Two application examples are presented to show some of the modelling capabilities offered by VIGIL.

Multifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge

AbstractHurricane-driven storm surge is one of the most deadly and costly natural disasters, making precise quantification of the surge hazard of great importance. Surge hazard quantification is often performed through physics-based computer models of storm surges. Such computer models can be implemented with a wide range of fidelity levels, with computational burdens varying by several orders of magnitude due to the nature of the system. The threat posed by surge makes greater fidelity highly desirable, however, such models and their high-volume output tend to come at great computational cost, which can make detailed study of coastal flood hazards prohibitive. These needs make the development of an emulator combining high-dimensional output from multiple complex computer models with different fidelity levels important. We propose a parallel partial autoregressive cokriging model to predict highly accurate storm surges in a computationally efficient way over a large spatial domain. This emulator has the capability of predicting storm surges as accurately as a high-fidelity computer model given any storm characteristics over a large spatial domain.

Debris‐Flood Hazard Assessments in Steep Streams

AbstractDebris floods most commonly occur in steep mountain channels and on their alluvial fans but can also occur on small gravel bed rivers with watershed areas up to several hundred square kilometers. This became obvious during July 2021 and November 2021 debris floods in northwestern Germany and southwestern British Columbia, Canada. We subdivide debris floods into three categories: those triggered by a supra‐critical bed shear stress ratio, form by dilution from debris flows, and resulting from outbreak floods. This trichotomy challenges traditional hazard assessments; debris floods classify as a fluvial process, yet their destructive mechanics are difficult to characterize. Key hazards interact spatially and temporally in debris floods: inundation, scour, sediment transport and deposition and bank erosion. We describe approaches to quantify hazards by systematically accounting for these processes and introduce a novel approach for hazard quantification and mapping in which flow velocity, depth, and presumed fluid density are combined with the annual event frequency for all event scenarios. The derivative “composite hazard maps” are equally valid for debris floods and debris flows. Isolines of bank erosion based on a probabilistic analysis of a physically based model are added to capture the potential of debris floods to abruptly widen their channels. Substantial challenges remain, specifically in the reliable prediction of sediment transport and progressive bank erosion. Our intention is to homogenize debris‐flood hazard assessments and especially mapping methodologies. This could allow for systematic integration with landuse policies assuring consistency among approaches executed by practitioners acting in this field.

Probabilistic Volcanic Hazard Assessment for National Park Infrastructure Proximal to Taranaki Volcano (New Zealand)

Hazard assessment for infrastructure proximal to a volcanic vent raises issues that are often not present, or not as severe in hazard assessments for more distal infrastructure. Proximal regions are subject to a greater number of hazardous phenomena, and variability in impact intensity increases with the hazard magnitude. To probabilistically quantify volcanic hazard to infrastructure, multiple volcanic hazards and their effects on exposed elements need to be considered. Compared to single-hazard assessments, multi-hazard assessments increase the size and complexity of determining hazard occurrence and magnitude, typically introducing additional uncertainties in the quantification of risk. A location-centred approach, focusing on key locations rather than key hazards, can simplify the problem to one requiring identification of hazards with the potential to affect the location, followed by assessment of the probability of these hazards and their triggering eruptions. The location-centred approach is more compatible to multi-source hazards and allows for different hazard estimation methodologies to be applied as appropriate for the infrastructure type. We present a probabilistic quantification of volcanic hazard using this location centred approach for infrastructure within Te Papakura o Taranaki National Park, New Zealand. The impact to proposed park infrastructure from volcanic activity (originating from Mt. Taranaki) is quantified using a probability chain to provide a structured approach to integrate differing hazard estimation methods with eruption probability estimates within asset lifetimes.This location-centered approach provides quantitative estimates for volcanic hazards that significantly improve volcanic hazard estimates for infrastructure proximal to the Taranaki summit vent. Volcanic mass flows, predominantly pyroclastic surges or block and ash flows, are most likely (probability >0.8) to affect walking tracks if an eruption occurs. The probability of one or more eruption(s) in the next 50 years is estimated at 0.35–0.38. This use of probability chains and a location centered assessment demonstrates a technique that can be applied to proximal hazard assessments globally.

SMART Subsea Cables for Observing the Earth and Ocean, Mitigating Environmental Hazards, and Supporting the Blue Economy

The Joint Task Force, Science Monitoring And Reliable Telecommunications (JTF SMART) Subsea Cables, is working to integrate environmental sensors for ocean bottom temperature, pressure, and seismic acceleration into submarine telecommunications cables. The purpose of SMART Cables is to support climate and ocean observation, sea level monitoring, observations of Earth structure, and tsunami and earthquake early warning and disaster risk reduction, including hazard quantification. Recent advances include regional SMART pilot systems that are the first steps to trans-ocean and global implementation. Examples of pilots include: InSEA wet demonstration project off Sicily at the European Multidisciplinary Seafloor and water column Observatory Western Ionian Facility; New Caledonia and Vanuatu; French Polynesia Natitua South system connecting Tahiti to Tubaui to the south; Indonesia starting with short pilot systems working toward systems for the Sumatra-Java megathrust zone; and the CAM-2 ring system connecting Lisbon, Azores, and Madeira. This paper describes observing system simulations for these and other regions. Funding reflects a blend of government, development bank, philanthropic foundation, and commercial contributions. In addition to notable scientific and societal benefits, the telecommunications enterprise’s mission of global connectivity will benefit directly, as environmental awareness improves both the integrity of individual cable systems as well as the resilience of the overall global communications network. SMART cables support the outcomes of a predicted, safe, and transparent ocean as envisioned by the UN Decade of Ocean Science for Sustainable Development and the Blue Economy. As a continuation of the OceanObs’19 conference and community white paper (Howe et al., 2019, doi: 10.3389/fmars.2019.00424), an overview of the SMART programme and a description of the status of ongoing projects are given.

Revisiting Flood Hazard Assessment Practices under a Hybrid Stochastic Simulation Framework

We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modeling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms on antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes are simulated by a hybrid 1D/2D modeling approach, which offers a good compromise between computational efficiency and accuracy. The proposed framework enables the estimation of the uncertainty of all flood-related quantities, by means of empirically derived quantiles for given return periods. Lastly, a set of easily applicable flood hazard metrics are introduced for the quantification of flood hazard.

Assessing hazard and potential impact associated with volcanic ballistic projectiles: The example of La Soufrière de Guadeloupe volcano (Lesser Antilles)

The fallout of ballistic blocks and bombs ejected from eruptive vents has the potential to produce severe injuries to people and damage to infrastructure in areas proximal to volcanoes. The dimensions and dispersions of ballistic ejecta from explosive eruptions are pivotal parameters to forecast the potential impact associated with future eruptions based on the compilation of probabilistic hazard maps.In this study, we propose a new probabilistic hazard quantification strategy to provide the probability of Volcanic Ballistic Projectiles (VBPs) to exceed some critical kinetic energy thresholds, considering a variability on the site of the eruptive vents and the effect of wind. La Soufrière de Guadeloupe (Lesser Antilles) is chosen as a test case, focussing on the most likely explosive scenario associated with the eruption of an active lava dome (including phreatic, Vulcanian and Strombolian eruptions). Sensitivity analyses have guided the optimization of input parameters to balance the results stability and computational costs, showing that the topography is a pivotal factor when accounting for the spatial uncertainty on vent locations in the proximity of the dome area. Given an eruption within the adopted scenario, we provide maps showing the probability to exceed different energy reference thresholds for roof's perforation if at least one VBP falls in a target area. These maps are then combined with exposed elements to produce a qualitative exposure-based risk map. We compute the overall probability, conditional on the selected scenario, for roof perforation in a given area when a VBP is ejected. Results show probabilities varying from ca. 2% up to 40% within a few km from the volcano, quickly dropping away from the dome. However, when the probability to exceed the energy reference threshold is only conditional on falling of VBPs in a target area, most of Basse-Terre island would be affected by the 20–60% probability of roof perforation. This work confirms how the choice of a probabilistic approach is key to estimate the likelihood of occurrence of VBPs impacts as a first step towards the development and implementation of pro–active risk reduction strategies in volcanic areas.

Tsunami coastal hazard along the US East Coast from coseismic sources in the Açores convergence zone and the Caribbean arc areas

Tsunami coastal hazard is modeled along the US East Coast (USEC), at a coarse regional (450 m) resolution, from coseismic sources located in the Açores Convergence Zone (ACZ) and the Puerto Rico Trench (PRT)/Caribbean Arc areas. While earlier work only considered probable maximum tsunamis, here we parameterize and simulate 18 coseismic sources, with magnitude M8-9 and return periods \(\sim\)70–2000 year, using seismo-tectonic and historical data. The largest sources in the ACZ are repeats of the 1755 M8.6-9 Lisbon earthquake and tsunami; other sources are hypothetical. In the ACZ, due to the limited data on faults, each source is parameterized with a single fault plane, while in the PRT, coseismic sources are parameterized based on fault segmentation established during a 2019 USGS workshop of experts, using 10–26 SIFT subfault planes (Gica et al. in NOAA Tech. Memo., OAR PMEL-139, 2008). Tsunamis are simulated for each source using the fully nonlinear and dispersive model FUNWAVE-TVD, in two levels of nested grids. At the considered scales, dispersion is shown to affect tsunami propagation. Coastal hazard is quantified by four metrics computed at many save points (\(\sim\)20–30 thousand) defined along the 5-m isobath (due to the coarse resolution), i.e., maximum (1) surface elevation, (2) current, (3) momentum force; and (4) travel time, representing flooding, navigation, structural, and evacuation hazards. Overall, the first three metrics are larger, the larger the source magnitude, and their alongshore variation shows similar patterns of higher/lower values, due to the shelf bathymetric control (refraction). The fourth metric mostly differs between sources from each area, but less so among sources from the same area; its inverse quantifies evacuation hazard. A 1–5 score is given to results for each metric, based on five intensity classes representing low, medium low, medium, high, and highest tsunami hazard. A novel tsunami intensity index is computed as a weighted average of these scores, allowing both a comparison among sources and a quantification of tsunami hazard as a function of their estimated return periods. In the most impacted areas of the USEC, the highest tsunami hazard in the 250–500-year return period range is commensurate with that posed by 100-year category 3–5 tropical cyclones, taking into account the larger current velocities and forces caused by tsunami waves. Results of this work could serve as a basis for a future regional Probabilistic Tsunami Hazard Analysis for the USEC, considering additional source types such as underwater landslides, volcanic flank collapse, and meteotsunamis, that were studied elsewhere.