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The Tatun Volcano Group (TVG) is located at the northern end of Taiwan, ~ 15 km from the center of Taipei, a metropolitan area of over seven million inhabitants. A volcanic eruption by the TVG of any type or scale could cause catastrophic human and economic impacts. This paper summarizes previous geochemical, geophysical, and geochronological reports and highlights why the widely accepted age model does not comport with the latest observations. This study also reports novel 40Ar/39Ar ages for two andesite samples and one basalt sample from the TVG. A sample collected from Chihsingshan yields a robust 40Ar/39Ar age of 0.081 ± 0.005 Ma. This provides the first direct evidence of TVG volcanic activity after 0.1 Ma. Two samples yield 0.28 ± 0.02 Ma for Tatunshan and 0.159 ± 0.017 Ma for Honglushan. The younger ages refute previously proposed age models for the TVG. Along with new drone photos and LiDAR images, the age data help resolve eruptive history and advance understanding of volcanic hazards and hazard mitigation in Taiwan and surrounding areas. [ABSTRACT FROM AUTHOR]

Global warming has accelerated alpine glacier melting and led to an increased risk of glacial lake outburst floods (GLOFs). This paper extracted glacial lake boundaries in the Tienshan Mountains of Central Asia from 1990 to 2023, analyzed their spatiotemporal variations and evaluated their risk levels under current and future scenarios. The results show that glacial lakes are predominantly distributed in the Central and Western Tienshan, accounting for 75% of the total number in the Tienshan region. The number and area of glacial lakes increased by 148% (from 1837 to 4557) and 71.83% (from 119.73 to 205.73 km2) during 1990 to 2023, with moraine lake expansion predominating. In the Western Tienshan, the high or very high risk of GLOF is 3–4 times that of other areas. By the middle of the twenty-first century, GLOF risk will continue to increase, especially in the Western Tienshan. This study can provide scientific foundation for disaster mitigation in the downstream areas. [ABSTRACT FROM AUTHOR]

The first-order second-moment checking point method was introduced to judge the instability probability and evaluate the stability of the TCURM. The frequency–response stability calculation and the reliability results were compared, and a frequency–response stability and reliability analysis method was proposed. Taking the Zengziyan W12# unstable rock mass in Nanchuan, Chongqing, China, as an example, the calculation shows that the dynamic indexes and geological indexes decrease as the stiffness of the deterioration area decreases. According to the statistical data of the laboratory test and the field investigation, reliability theory is used to evaluate the stability of the TCURM, and the failure probabilities are 80.3% and 96.27% under natural and saturated conditions, which correspond to states of poor stability and instability, respectively. The reliability evaluation results are consistent with the conclusion of the frequency–response stability analysis. The new method can provide a theoretical basis for developing the dynamic monitoring and early warning indicators of the TCURM and disaster prevention and mitigation in mountainous areas. [ABSTRACT FROM AUTHOR]

The development of inhaled drugs for respiratory diseases is frequently impacted by lung pathology in non-clinical safety studies. To enable design of novel candidate drugs with the right safety profile, predictive in vitro lung toxicity assays are required that can be applied during drug discovery for early hazard identification and mitigation. Here, we describe a novel high-content imaging-based screening assay that allows for quantification of the tight junction protein occludin in A549 cells, as a model for lung epithelial barrier integrity. We assessed a set of compounds with a known lung safety profile, defined by clinical safety or non-clinical in vivo toxicology data, and were able to correctly identify 9 of 10 compounds with a respiratory safety risk and 9 of 9 compounds without a respiratory safety risk (90% sensitivity, 100% specificity). The assay was sensitive at relevant compound concentrations to influence medicinal chemistry optimization programs and, with an accessible cell model in a 96-well plate format, short protocol and application of automated imaging analysis algorithms, this assay can be readily integrated in routine discovery safety screening to identify and mitigate respiratory toxicity early during drug discovery. Interestingly, when we applied physiologically-based pharmacokinetic (PBPK) modelling to predict epithelial lining fluid exposures of the respiratory tract after inhalation, we found a robust correlation between in vitro occludin assay data and lung pathology in vivo, suggesting the assay can inform translational risk assessment for inhaled small molecules. [ABSTRACT FROM AUTHOR]

Identification of landslide susceptible zones is the preliminary step to plan mitigation measures in landslide-prone mountainous terrains. The use of various machine learning (ML) algorithms has proven their superiority in terms of enhancing the success rate in susceptibility studies. Therefore, the present study focuses on spatial prediction of landslides using integrated supervised and unsupervised machine learning (ML) techniques with reference to Bhagirathi Valley, NW Himalaya. A landslide inventory of 514 landslides and 14 viable causative factors of landslides in the study area have been selected for the analysis. Three efficient supervised ML techniques, i.e., random forest (RF), extreme gradient boosting (XGBoost), and k-nearest neighbour (KNN), have been integrated with an unsupervised ISODATA cluster classification technique to prepare the landslide susceptible maps (LSM) of the study area. All the models depict that the greater part of the high and very high landslide hazard zones lie in the Main Central Thrust zone and its vicinity in the Bhagirathi Valley. The accuracy of each model was determined and compared using several statistical signifiers like sensitivity, specificity, area under curve, accuracy, and Kappa index. The results show that XGBoost and RF models exhibit higher performance accuracy than KNN. The quantitative assessment of prepared LSMs of the study area was also done using frequency ratio (FR) and frequency density (FD). The results indicate the consistency of each model in the prediction of landslide zones in the study area as FR and FD both increase with the increase of landslide susceptibility levels from very low to very high in all the models. [ABSTRACT FROM AUTHOR]

During the rainy season in Brazil, landslides can have catastrophic consequences, including loss of life, damage to urban infrastructure and significant economic impacts. Now, more than eight million people in Brazil live in disaster-prone areas. The objective of this article is to present a chronological review of the principal policies and programmes at the national, state, and municipal levels, with an emphasis on their key actions aimed at mitigating the impact of disasters related to natural hazards, particularly landslides. Our analysis was based on official records of public policies from the national, state, and municipal governments. The results show that several initiatives were initially developed at the local and regional level. However, it was not until the late 1980s that a comprehensive organisation of civil protection at the national level emerged as a response measure. It is possible to highlight three phases (understanding, coexistence, and prevention) of institutional action focused on risk management in the face of disasters. Despite the growing knowledge of risk scenarios, disasters continue to occur in Brazil on an annual basis, revealing several obstacles to reducing their impact, particularly given the social and economic disparities between Brazilian regions and the applicability of public policies that must overcome the limitations of each municipality. [ABSTRACT FROM AUTHOR]

The increasing magnitude of monetary and life losses caused by urban floods worldwide has sparked a deeper interest among researchers in comprehending these phenomena. Accurate modeling and forecasting of floods play a pivotal role in developing effective strategies for flood damage mitigation and management, thereby reducing associated hazards. A critical concern in this endeavor is optimizing the trade-off between computation time and accuracy when simulating real-time flood events. This paper aims to establish the superiority of the sub-grid approach in achieving accurate simulation results of real-time flood events within minimal computational time. By conducting simulations of one experimental test and two real-world flood events using the HEC-RAS flow simulation model, we demonstrate that the sub-grid approach significantly reduces computation time by approximately 90% while faithfully capturing the dynamics of urban flood. In contrast, the non-sub-grid approach often over-predicts flow dynamics in urban areas and fails to effectively trace building footprints, resulting in unrealistic flow patterns and under or overstating the hazard maps. In a nutshell, the sub-grid hydraulic modeling approach enables better hazard analysis and mapping. The outcomes of this research provide valuable guidance to modelers and authorities, suggesting the adoption of the sub-grid approach for accurate and reliable real-time urban flood modeling, inundation forecasting, and hazard zoning in the context of urban flood hazard analysis. [ABSTRACT FROM AUTHOR]

Natural disasters occur frequently worldwide, causing serious harm to people, resources, and the environment. The disaster mitigation capacity is very important in reducing disaster-caused losses and in informing natural disaster prevention and mitigation plans. However, the disaster mitigation capacity frameworks in recent studies are inconsistent and lack the careful consideration of natural disaster occurrence process, and it remains unclear to what extent the model parameters may affect the robustness of assessment results. To solve this problem, with typhoons as an example, an assessment framework of typhoon disaster mitigation capacity (TDMC) based on the entire process of disaster prevention–resistance–rescue was developed in this study. The TDMC framework was applied in Hainan, China, as a case study, and the associated uncertainty was assessed by analyzing indicator selection and weighting and synthesis methods. The TDMC was very high in Haikou and Sanya but very low in Lingao, Ledong, and Dongfang. Iterative sensitivity analysis of the indicators revealed that the removal of different indicators had little effect on the percentage change in average TDMC of Hainan. The sensitive indicators were warning systems, emergency shelters, and insurance, suggesting that specific strategies for those indicators could improve regional TDMC. The assessment results with different indicator weighting and synthesis methods were generally robust, especially in counties with very low or high TDMC. However, the counties with medium TDMC showed higher sensitivity, which led to changes in TDMC indices. Assessments were more sensitive to changes in weighting method than to changes in synthesis method. This study demonstrated the importance of quantifying uncertainties in assessment model parameters to provide credible TDMC information and to further the effective design of disaster prevention and mitigation strategies. [ABSTRACT FROM AUTHOR]

Purpose: The interface between newly-filled soil and silted soil in a check dam is commonly acknowledged as the most vulnerable plane in the upstream heightening technique, posing a significant threat to dam stability. The objective was to investigate the microscopic shear failure mechanism in " soft–soft (or soil-soil) " interlayers under different working conditions, aiming to establish a theoretical foundation for dam hazard mitigation and reinforcement. Materials and methods: Direct shear tests were initially conducted on the interface between new-fill and silt soils, considering different water contents and compactness coefficients in the silt soil. Subsequently, scanning electron microscopy (SEM) technique and Image J software were employed to extract microscopic parameters from the sheared samples. By integrating macroscopic failure patterns with microscopic parameters, a qualitative analysis was established to investigate how water content and compaction degree influence the shear properties and deformations, ultimately revealing the failure mechanism of interface shearing. Results and discussion: A typical triple-stage (fluctuation, climbing, stable) hardening phenomenon occurred in the stress-displacement curve during direct shear test. The shear strength showed a positive correlation with compaction coefficient but an inverse relationship with water content. Cohesion of the contact surface increased initially and decreased as water content raised, whereas it changed slightly with the increase of compaction. The internal friction angle increased with the development of compactness degree but decreased with increasing water content. SEM images illustrated a progressive morphology transformation in the contact surface, from granular to laminar to an aggregated pattern. Microscopic parameters such as pore morphology properties, pore size distribution as well as pore spatial distributions were directly bonded with macro properties. Conclusions: The compaction of silt plays a crucial role in adhesive force and structure of particles at soil-soil interface, thereby leading to the occurrence of "optimal bonding" and the variation of shear strength. The shear failure of contact surface is characterized by progressive failure. Besides, the water content and compaction degree of soft soil has a significant influence on the progressive failure. [ABSTRACT FROM AUTHOR]

Earthquake-induced rock landslides in the eastern mountains of the Tibetan Plateau, especially landslides with weak interlayers pose a significant threat to major construction projects. Prestressed anchor cable is one of the main reinforcement methods of rock slopes. This paper combines shaking table model tests and numerical simulation to study the reinforcement effect and dynamic response characteristics of prestressed anchor cables applied to rock slopes with weak interlayers under strong earthquakes. The research results show that prestressed anchor cables can effectively reinforce slopes with weak interlayers. A small cable inclination, a small spacing and a high prestress are recommended in the seismic reinforcement design of prestressed anchor cable. In addition, the characteristics of slope progressive damage and prestress loss under the earthquake are found by the shaking table test. The results have been applied in hazard prevention and control of rock slopes on the Chengdu-Lanzhou Railway at the eastern Qinghai-Tibet Plateau. [ABSTRACT FROM AUTHOR]

Expert perspectives drive landslide mitigation and post-disaster policy planning. This study examines landslide risk perceptions among the stakeholders (government officials, academics, policy experts, local community representatives, and representatives of NGOs/civil society) across Brazil, Colombia, Nepal, Iran, and Pakistan, identifying both shared concerns and local heterogeneity. Key informants revealed a discrepancy in their degree of concern about landslides, with government officials exhibiting greater apprehension compared to local community representatives. Local community representatives incorrectly perceived landslides to be the result of natural phenomena. In contrast, governmental and academic stakeholders felt that human-induced triggers, specifically those related to land use and land cover change, were significant contributors to landslide occurrences, necessitating stringent law enforcement. The comprehensive impacts of landslides included economic losses, infrastructure disruption, agricultural losses, and food security concerns, underscoring the multifaceted nature of this hazard. Our results suggest the need for proactive citizen engagement in landslide monitoring, recognizing the importance of local contexts. We end by proposing a dual-pronged policy approach that emphasizes the socio-economic context of each region. [ABSTRACT FROM AUTHOR]

Large amounts of co-seismic landslides provide abundant debris sources following a strong earthquake and are prone to initiate and generate debris flow under heavy rainfall. Assessing the susceptibility they pose and what drives their movement in the years following the mainshock has not yet been attempted, primarily because multitemporal debris flow inventories are lacking. This study conducted statistical analyses using the multitemporal debris flow inventory (2008–2021) following the 2008 Wenchuan earthquake and a set of conditional factors (debris source, terrain, and hydrology). The dynamic susceptibility evaluation model was created using logistic regression. The temporal evolution of these factors affecting debris flow runout was explained. Our findings suggest that topography variables grew rapidly after the earthquake, while debris source factors dominated for seven years after the disaster before declining progressively to zero. These findings may have significant consequences for traditional susceptibility assessment models in regions where co-seismic landslides are the dominant debris flow source. [ABSTRACT FROM AUTHOR]

Following the 2016 Chauk earthquake in Bagan (Myanmar), numerous old pagodas and temples suffered severe damage. This research presents a study on the seismic hazard analysis of the Bagan city in Myanmar, based on a probabilistic framework focussing on analysing 43 temples with their associated local soil information. To this end, two seismic source models are developed based on the tectonic setting of the region and information available. Instrumental and historical records are compiled from both literature and international earthquake catalogues while conducting catalogue completeness. This study uses state-of-the-art ground motion models to perform probabilistic seismic hazard analysis and develop seismic hazard maps for different return periods in the region. Results are also expressed for selected temples in the region in terms of site-specific uniform hazard spectra. The findings indicate significant seismic activity, with peak ground acceleration in the region ranging from 0.25 to 0.36 g for a return period of 2475 years, 0.22–0.32 g for a return period of 975 years, and 0.18–0.24 g for a return period of 475 years. The updated hazard levels indicate that the literature slightly underestimates hazard in the region under study. [ABSTRACT FROM AUTHOR]

Occurrence of natural disaster can never be prevented, and floods are one among the major natural disaster that affects the human life and economy of the country. Considering the global loss due to floods, various government and non-governmental organisations are focusing on minimising the losses and provide emergency measures during floods. Adopting the recent technologies integrating various datasets will assist in providing response strategies before and after disaster. Flood are mostly based on the climatic conditions and environmental factors and the present review focuses on the reviewing the various remote sensing methodologies that are used in mapping and analysing floods. The review carried out examines various remote sensing methodologies adopting multispectral, light detection and ranging and radar datasets for mapping and predicting floods. The review identified the limitations in flood prediction, risk assessment and hazard analysis and suggests a framework that can be adopted for effective mapping of flood extent and in suggesting the regions that the rescue team should focus during a disaster event. [ABSTRACT FROM AUTHOR]

Effective volcanic impact and risk assessment underpins effective volcanic disaster risk management. Yet contemporary volcanic risk assessments face a number of challenges, including delineating hazard and impact sequences, and identifying and quantifying systemic risks. A more holistic approach to impact assessment is required, which incorporates the complex, multi-hazard nature of volcanic eruptions and the dynamic nature of vulnerability before, during and after a volcanic event. Addressing this need requires a multidisciplinary, integrated approach, involving scientists and stakeholders to co-develop decision-support tools that are scientifically credible and operationally relevant to provide a foundation for robust, evidence-based risk reduction decisions. This study presents a dynamic, longitudinal impact assessment framework for multi-phase, multi-hazard volcanic events and applies the framework to interdependent critical infrastructure networks in the Taranaki region of Aotearoa New Zealand, where Taranaki Mounga volcano has a high likelihood of producing a multi-phase explosive eruption within the next 50 years. In the framework, multi-phase scenarios temporally alternate multi-hazard footprints with risk reduction opportunities. Thus, direct and cascading impacts and any risk management actions carry through to the next phase of activity. The framework forms a testbed for more targeted mitigation and response planning and allows the investigation of optimal intervention timing for mitigation strategies during an evolving eruption. Using 'risk management' scenarios, we find the timing of mitigation intervention to be crucial in reducing disaster losses associated with volcanic activity. This is particularly apparent in indirect, systemic losses that cascade from direct damage to infrastructure assets. This novel, dynamic impact assessment approach addresses the increasing end-user need for impact-based decision-support tools that inform robust response and resilience planning. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to evaluate life safety risk of coastal communities vulnerable to seismic and tsunami hazards. The work explicitly incorporates two important aspects in tsunami evacuation modeling: (1) the effect of earthquake-induced damage to buildings on building egress time, (2) the effect of earthquake-induced debris on horizontal evacuation time. The city of Seaside, Oregon, is selected as a testbed community. The hazard is based on a megathrust earthquake and tsunami from the Cascadia Subduction Zone that was defined in a previous study. The built environment consists of buildings and the transportation network for the city. Fragility analysis is used to estimate the seismic damage to buildings and resulting debris that covers portions of the road network. The horizontal evacuation time is determined based on the shortest path to shelters, including the increased travel time due to the earthquake-generated debris. The effects of different mitigation strategies are quantified. Results indicate the fatality and life safety risk of a near-field tsunami increases by 4.2–8.3 times when the effects of building egress and earthquake-induced debris are considered. The choice of population layer affects the life safety risk and thus the maximum risk is obtained when daytime populations are considered. Use of mitigation strategies result in a significant decrease in the number of fatalities. For hazards with recurrence intervals larger than 500- to 1000-years, the seismic retrofit is comparable to vertical evacuation and an effective strategy in reducing fatalities and associated risks. Implementing all mitigation strategies reduces the life safety risk by 90%. [ABSTRACT FROM AUTHOR]

The co-occurrence of multiple hazards can either exacerbate or mitigate risks. The interrelationships between multiple hazards greatly depend on the spatiotemporal scale and can be difficult to detect from large to local scales. In this paper, we identified coastal regions worldwide where the leading tropical (El Niño-Southern Oscillation, ENSO) and polar (Arctic Oscillation, AO; Southern Annular Mode, SAM) modes of climate variability simultaneously modify the seasonal conditions of multiple hazards, including the near-surface wind speed and swell and wind-sea wave powers. We classified the results at the national and municipal levels, with a focus on multiple hazards simultaneously occurring in space and time. The results revealed that the ENSO modulates multiple hazards, affecting approximately 40% of coastal countries, while the polar annular modes affect approximately 30% of coastal countries. The ENSO induced a greater diversity of multiple hazards, with Asian countries (e.g., Indonesia experienced increases of + 2% in wind and + 7% in swell) and countries in the Americas (e.g., Peru exhibited increases of + 1.5% in wind and + 6% in wind-sea) the most notably affected. The SAM imposed a greater influence on swells in the eastern countries of ocean basins (+ 2.5% in Chile) than in other countries, while the influence of the AO was greater in Norway and the UK (+ 12% for wind-sea and 8% for swell). Low-lying islands exhibited notable variations in pairwise hazards between phases and seasons. Our results could facilitate the interpretation of multihazard interactions and pave the way for a wide range of potential implementations of different coastal industries. [ABSTRACT FROM AUTHOR]

During 2019 to 2022, a comprehensive study was conducted across 71 stations spanning over 15 states in India to investigate air quality variations during the pre-Diwali, Diwali, and post-Diwali periods. The investigation, centred on the extensive use of firecrackers during festive times, revealed a short-term deterioration in air quality with long-lasting impacts. PM2.5 and PM10 levels were found to significantly increase during Diwali and the post-Diwali period compared to the pre-Diwali period. The levels of PM2.5 and PM10 experience respective increases of 44.66% and 11.03%, 29.12% and 05.41%, 52.63% and 23.38%, and 39.65% and 17.61% during Diwali period from 2019 to 2022, where 68.84% and 34.32%, 44.42% and 29.42%, and 48.70% and 25.22% in 2019, 2021 and 2022 in post-Diwali period compared to the pre-Diwali. The Mann–Kendall and Sen's slope analyses reveal statistically significant positive trends (increasing) in both PM10 and PM2.5 levels during the Diwali festival period. Notably, the study introduced the Health Hazard-based Air Quality Index (HAQI), which demonstrated higher values than the National Ambient Air Quality Index (NAAQI). Unlike NAAQI, which considers individual pollutant sub-index values, and considered highest one of sub-index values in AQI analysis. HAQI provides a more comprehensive assessment of health risks associated with exposure to multiple pollutants effects. In 2022, AQI and HAQI values during pre-Diwali were 114 and 146.18, during Diwali were 173 and 332.18, and post-Diwali were 191 and 414.14, respectively. These findings underscore the elevated risk during Diwali and the post-Diwali period due to heightened pollution levels, emphasizing the need for public awareness and potential mitigation strategies. The study calls attention to the importance of considering cumulative health impacts and suggests the adoption of HAQI for more informative air quality assessments. [ABSTRACT FROM AUTHOR]

Risk-based design and assessment methods are gaining popularity in performance-based structural fire engineering. These methods usually start by defining a set of hazard scenarios to use as analysis inputs. This approach, proven highly effective for other hazard types such as earthquakes, may not be optimal for fire safety design. Indeed, the strong coupling between the fire phenomenon and structural features enables an ad-hoc design variable selection (and/or optimisation) to reduce fire intensity, making fire scenarios additional design outputs. In addition, such a coupling effect implies that fire scenarios maximising consequences are structure specific. Building on these considerations, this paper discusses the limitations that arise at different analysis steps (i.e., fire-scenario and intensity treatment, identifying fire intensity measures, probabilistic fire hazard analysis, developing fire fragility models, and risk calculation) when using conventional risk-based approaches for design purposes. Furthermore, it compares such approaches with a fire safety design methodology (the Consequence-oriented Fire intensity Optimisation, CFO, approach) that addresses the identified limitations. The potential benefits of integrating the two approaches are also discussed. Finally, the fire design of a simplified steel-girder bridge is introduced as an illustrative example, comparing the consequence metrics and design updating strategies resulting from the two approaches. [ABSTRACT FROM AUTHOR]

The probabilistic seismic hazard assessment contains two ingredients: (1) the seismic source model with earthquake rates and rupture parameters for specification of the statistical distribution of earthquakes in time and space and (2) the ground motion model, for estimation of ground shaking level at a site for each earthquake rupture. The selection of these models significantly impacts the resulting hazard maps, and it can be challenging, particularly in seismotectonic regions where overlapping structures, sited at different depths, coexist. Eastern Central Italy is a well-known active compressional environment of the central Mediterranean with a complex tectonic structure with a lithospheric double shear zone. In this study, we propose a seismic hazard assessment to analyze the contribution of these two shear zones as overlapping multi-depth seismogenic volumes to ground motion at a given hazard level. We specifically focus on selecting relevant and applicable parameters for earthquake rate modeling, emphasizing the importance of defining rate computation and rupture-depth parametrization in hazard analysis. To achieve this, we utilized a seismotectonic- and catalog-based 3D adaptive smoothed seismicity approach following the methodology given by (Pandolfi et al. in Seismol Res Lett 95: 1–11, 2023). Finally, we demonstrated how this innovative 3D approach can identify with high resolution the individual sources' contribution with particular attention to the depth location of structures that strongly influence the ground motion. Moreover, combining seismotectonic data with seismicity avoids the challenges associated with structures with scarce geologic, geodetic, or paleoseismological data. Our result provides detailed insights into the seismic hazard within the Adriatic Thrust Zone. [ABSTRACT FROM AUTHOR]

The estimation of the seismic vulnerability of regional structures has contributed positively to the development of seismic risk and resilience in large-scale building clusters. However, the empirical structural seismic damage and ground motion data used to validate the risk model are relatively outdated, resulting in insufficient evaluation accuracy of the established risk model and an urgent use for retrofitting. This study analysed the actual failure peculiarities of typical structures during a recent typical destructive earthquake in China (the Luding earthquake in Sichuan Province on September 5, 2022). A total of 300,000 acceleration records from ten actual monitoring seismic stations were processed and analysed. Nonlinear dynamic time history curves, response spectra, and combined seismic acceleration cloud images were generated considering different directions. Moreover, the traditional instrument intensity calculation equation has been updated, and an instrument intensity curve bunch considering 300,000 earthquake acceleration records has been developed. To study the probabilistic seismic risk of large-scale regional buildings, the developed vulnerability database of typical regional structures (Sichuan Province) was supplemented and optimized, and an updated vulnerability database (413 damage probability matrix) was established, considering the failure of five structures in 32 destructive earthquakes. An updated structural seismic vulnerability model based on extended vulnerability grades was proposed, and a mean vulnerability probability matrix based on structural risk datasets was established. A membership index function for estimating the correlation between different vulnerability grades was innovatively proposed, and the rationality of the model was verified using an improved empirical dataset. A multidimensional failure prediction model was developed based on an improved mean seismic damage index. [ABSTRACT FROM AUTHOR]

South Korea was considered a stable continental region (SCR) until the recent seismic events, specifically the 5.5- and 5.4- magnitude earthquakes in Gyeongju and Pohang, respectively, highlighting the need for reliable ground-motion models (GMMs), which are key to seismic hazard assessment analysis. Although it is appropriate to employ GMMs that are tailored to regional characteristics, irrespective of whether they are developed based on a stochastic method or actual data, a model that is similar to the tailored GMM can also be used. Recently, several earthquakes with magnitudes greater than 5 have occurred in South Korea, enabling us to assess whether the GMMs previously developed in Korea or those applied for South Korea's disaster management system are suitable for use throughout the country. Therefore, this study conducted an evaluation to assess the suitability of GMMs tailored to domestic characteristics. GMMs developed for various regions including active crustal regions, SCRs, and South Korea, were employed. Amplification functions were applied to several GMMs developed for hard rock sites. A total of 48 GMMs, considering site effects, were compared using the Korean earthquake ground motion data. The suitability of GMMs for Korea was assessed through statistical techniques such as log-likelihood method, multivariate logarithmic score, Euclidean distance-based ranking, Euclidean metric distance, deviance information criterion, and cumulative-distribution-based area metric method. Ensemble GMMs were also developed based on the rank results and analyzed using statistical methods. Un-normalized weight was used to calculate the outcomes of the above mentioned six ranking methods, and weighted GMMs were judged to be optimal for South Korea. [ABSTRACT FROM AUTHOR]

In the general practice of performance-based seismic assessment and dynamic analysis of building structures, the recorded ground motions from past earthquake events are selected and modified according to the site conditions and hazard level of the project's site. For this purpose, only the mainshock earthquake event is considered for the analysis while neglecting the foreshocks and aftershocks. However, in several real cases, especially for existing RC buildings with non-seismic detailing, low- to moderate-magnitude foreshocks and aftershocks may also affect the seismic performance. Several studies have shown that the application of repeated earthquake events may lead to damage accumulation and significant seismic losses, even if the structure is at a life safety performance level. This study examines the seismic performance of mid-rise RC frame structures in Pakistan under repeated earthquakes. For this purpose, a representative case study building has been selected for the detailed analysis after surveying typical existing RC buildings in Pakistan. The detailed nonlinear finite element model is constructed and subjected to several cases of repeated earthquakes with different intensity levels. The seismic performance in terms of key demand parameters is evaluated for single earthquake scenarios (mainshock only) and seismic sequences (foreshock, mainshock, and aftershock). The results showed the application of seismic sequences has a negligible effect on the peak seismic force and displacement demands of the buildings compared to the single mainshock event. However, an increase in seismic performance indicators, including residual displacements and inelastic hysteretic energy, is observed. Resultantly, an increase in structural damage (quantified in terms of material cracking, yielding, crushing, etc.) is also observed for ground motion sequences compared to the single ground motion. [ABSTRACT FROM AUTHOR]

It is very essential in terms of flood risk management to consider social expectations such as risk perception, flood awareness, preparedness, and socio-economic dynamics together with engineering designs. Understanding the way people perceive flood risk can enhance our capability of improving existing flood risk management methods, thus helps us creating disaster resilient societies. In this study, results of a questionnaire which was used for a previous study and had been administered to participants from Eastern Black Sea Region of Turkey were further investigated using statistical methods. The main aim was to understand how demographic factors such as age, gender and education level affect people's flood risk perception. It was also desired to see that whether they were aware of the parties responsible for taking mitigation measures, or whether they know about possible flood mitigation measures or not. Using the same data with the previous study, but in addition using SPSS software to do statistical analysis, questionnaire results were investigated using convenient statistical tests for each parameter, analysis results were interpreted, and conclusions were drawn. Same tests were conducted using weight coefficients adopted using a certain methodology which is explained in the paper, in order to make a better investigation. Also, results were compared with the results of the previous study. It was seen that there were some consistencies and contradictions between the results of the previous study and this study's results. [ABSTRACT FROM AUTHOR]

This paper reports exploratory research that considers two challenges recognised in the disaster risk reduction (DRR) community in recent years: one is the reinforcement of community-based DRR and the other is experts' prioritising high-impact/low-frequency hazards. Inquiries into stakeholders'—community members' in particular—understandings of disaster risks have been scarce. The research aimed to address these gaps by investigating communities' perceptions around community-based DRR and disaster risks. The research focused on natural water hazards, such as floods and typhoons generated due to atmospheric forcing factors, as well as tsunamis in four communities in Japan and England. A field survey of major structural mitigation solutions, non-structural measures, and community interviews revealed that community members did not necessarily find the often-used impact/frequency description of hazards helpful in developing and implementing community-based DRR activities. Such hazard-based scientific language does not necessarily correspond with the general public. The paper attempted 'the number of affected people', which was recognised by the research participants, to be applied as a tool for understanding disaster risks. [ABSTRACT FROM AUTHOR]

Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention. Discontinuous deformation analysis (DDA) is an effective approach for investigating landslides. However, DDA fails to accurately capture the degradation in shear strength of rock joints commonly observed in high-speed landslides. In this study, DDA is modified by incorporating simplified joint shear strength degradation. Based on the modified DDA, the kinematics of the Baige landslide that occurred along the Jinsha River in China on 10 October 2018 are reproduced. The violent starting velocity of the landslide is considered explicitly. Three cases with different violent starting velocities are investigated to show their effect on the landslide movement process. Subsequently, the landslide movement process and the final accumulation characteristics are analyzed from multiple perspectives. The results show that the violent starting velocity affects the landslide motion characteristics, which is found to be about 4 m/s in the Baige landslide. The movement process of the Baige landslide involves four stages: initiation, high-speed sliding, impact-climbing, low-speed motion and accumulation. The accumulation states of sliding masses in different zones are different, which essentially corresponds to reality. The research results suggest that the modified DDA is applicable to similar high-level rock landslides. [ABSTRACT FROM AUTHOR]

An evaluation of flood vulnerability is needed to identify flood risk locations and determine mitigation methods. This research introduces an integrated method combining hydro-morphometric modeling and flood susceptibility mapping to assess Padma River Basin's flood risk. Flood zoning, flooding classes, and resource flood risk were explicitly analyzed in this river basin study. Flood risk was calculated using GIS-based hydro-morphometric modeling. Using Horton's and Strahler's methods, drainage density, stream density, and stream order of the Padma River Basin were determined. The Padma River Basin has five sub-basins: A, B, C, D, and E, with stream densities of 0.53 km−2, 0.13 km−2, 0.25 km−2, 0.30 km−2, and 0.28 km−2 and drainage densities of 0.63 km−1, 0.16 km−1, 0.29 km−1, 0.35 km−1, and 0.33 km−1, respectively. Sub-basin A is the most prone to floods due to its high stream and drainage density, whereas B and C are the least susceptible. This study used elevation, TWI, slope, precipitation, NDVI, distance from road, drainage density, distance from river, LU/LC, and soil type to create a flood vulnerability map incorporating GIS and AHP with pair-wise comparison matrix (PCM). The study's flood zoning shows that the northeastern part of this basin is more likely to flood than the southwestern part due to its elevation and high-order streams. Moderate River Flooding, the region's most hazardous flood class, covers 48.19% of the flooding area, including 1078.30 km2 of agricultural land, 94.86 km2 of bare soil, 486.39 km2 of settlements, 586.42 km2 of vegetation cover, and 39.34 km2 of water bodies. The developed hydro-morphometric model, the flood susceptibility map, and the analysis of this data may be utilized to offer long-term advance alarm insight into areas potentially to be invaded by a flood catastrophe, boosting hazard mitigation and planning. [ABSTRACT FROM AUTHOR]

Geological events that cause casualties and huge property losses frequently occur in the hilly region of Southwest China. Especially for economically underdeveloped mountainous cities, the vulnerability of social and ecological systems greatly affects urban development. Therefore, it is necessary to conduct multi-hazard exposure research in mountain areas. The importance of this study is that the five machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) are first used to develop multi-hazard (specifically landslides and rockfalls) susceptibility map in three typical hilly areas in the Southwest China (Qijiang, Chuishui and Wuxi). The performances of the models are then compared using the F1-Score and the true skill score (TSS) respectively. Finally, the multi-hazard exposure maps of each district are developed by combining multi-hazard susceptibility and exposure factors. According to the results of this study, it can be found that the LightGBM and CatBoost algorithms are suitable for the development of landslide and rockfall hazard susceptibility maps in the hilly region of southwest China, and this type of gradient boosting algorithms have good development prospects. In addition, in future research on geological hazards in this hilly area, more attention should be paid to conditioning factors such as rainfall, altitude, slope, distance from the faults, and lithology. The results of this study can provide reference for the screening of landslide and rockfall conditioning factors in such mountainous areas, and can also provide certain support for the planning of the social ecosystem in mountainous areas and the formulation of natural hazard mitigation measures. [ABSTRACT FROM AUTHOR]

Precise predicting of rainfall is paramount for effective water resource management, ecological conservation, and the prevention of droughts and floods. Influenced by numerous variables, the process of rainfall is complex and the rainfall series exhibit high degrees of nonlinearity, making it challenging for traditional statistical prediction models to accurately capture the characteristics of rainfall series. Therefore, this paper proposes a new coupled model for predicting monthly rainfall based on Extreme-Point Symmetric Mode Decomposition (ESMD), Empirical Wavelet Transform (EWT), Singular Value Decomposition (SVD) and Long Short-Term Memory Neural Network (LSTM). By training and evaluating the ESMD-EWT-SVD-LSTM model on Kaifeng City's monthly rainfall data from 2009 to 2020 and comparing its predictions with those of the ESMD-SVD-LSTM, SVD-LSTM, LSTM models, the analysis reveals that: the quadratic decomposition of ESMD-EWT and SVD denoising can further reduce the complexity of rainfall data, obtain more predictable feature IMFs, and enhance the precision in LSTM predicting; in comparison with alternative models, the ESMD-EWT-SVD-LSTM coupled model shows the highest accuracy in predicting results, with MAE of 4.96, RMSE of 6.13, and SI of 0.12, indicating that the ESMD-EWT-SVD-LSTM model has strong nonlinear process learning ability and accuracy in regional monthly rainfall prediction. This study can offer dependable scientific grounding and technical assistance for regional rainfall predicting, water resources planning, and disaster mitigation. [ABSTRACT FROM AUTHOR]

This study proposes a new seismic slope displacement prediction equation based on uncorrelated principal components and implementation in landslide hazard estimation. First, the nonlinear principal component analysis (NLPCA) was performed for 11 mutually correlated ground motion intensity measures (IMs). It was found that these eleven IMs could be represented with three mutually uncorrelated principal components. Additionally, a model to predict the principal components as a function of earthquake magnitude, the closest distance to rupture, average shear wave velocity of soil and rock layers on top 30 m, and fault mechanism was also developed from this work. The corresponding model has total standard deviations of 0.043, 0.013, and 0.011 for PC1, PC2, and PC3, respectively. Further, these principal components and the critical acceleration of slope were used to develop the slope displacement prediction equation. The developed slope displacement prediction model was observed to have lesser variability σ lnSD = 0.662 , and the attenuation pattern was comparable with other existing relations. Additionally, the application of the equation is demonstrated by developing the slope displacement hazard curves for Shimla City. The slope displacement corresponds to a 2475-year return period exceeding 5 cm for the slopes with a critical acceleration of less than 0.1 g. The proposed slope displacement prediction model based on uncorrelated principal components can simplify landslide hazard estimation significantly. [ABSTRACT FROM AUTHOR]

A disaster community's priority is to ensure the safety of populations during natural hazards. Disaster risk reduction strategies require knowledge of what is hazardous, who is vulnerable, and what is risky. As of now, engineering methods predominate in Russian disaster research, while social science rarely analyzes floods, earthquakes, wildfires, etc. Study aims to test the applicability of new methods for delineating flood hazards, characterizing social vulnerability, and determining overall societal risk in Russia. Multidisciplinary nature makes the problem complex. The research will concentrate on the ten representative counties of the Kuban River basin in a southern Russian region, where at the beginning of the XXI century catastrophic floods led to enormous fatalities and huge economic damage. Flood hazards are assessed based on the county-scale spatial distribution of records produced by a Regional Early Warning System, impact information, and flood management infrastructure. Social vulnerability is investigated using a County Comparable Social Vulnerability Profiling model that encompasses three pillars (physical, socio-economic and awareness), nine themes (age, disability, poverty, etc.), and seventeen census variables (aged 0–19 years, density, one-person household in detached housing, only nine years of school, etc.). Finally, a holistic flood risk map is compiled. The results show that the three riskiest counties require measures to reduce flood hazard and social vulnerability in all phases of disaster risk management (mitigation, preparation, emergency, and rehabilitation). Data-poor nations such as Russia can benefit from these methods, but their use is limited by insufficient flood hazard and census information. [ABSTRACT FROM AUTHOR]

In the present study, a hypothetical earthquake of magnitude 8.5 has been simulated using the modified hybrid technique. Existing hybrid technique, as the name suggests, is the blend of two already existing simulation techniques, i.e. composite source technique and the envelope technique. In the present modified technique, site response functions and high-frequency decay parameter (kappa factor) have also been introduced in the existing hybrid technique. The waveforms have been simulated at more than 430 points using the calculated site response or transfer function estimated at 50 recording stations situated in the central seismic gap (CSG) region of Himalaya. Peak ground acceleration (PGA) and duration parameters have been estimated. Calculated PGA values helped estimating in the corresponding intensity for those PGA values at various stations. With the help of these PGA and intensity values, the scenario hazard map has been prepared for central seismic gap (CSG) region of Himalaya. It has been found that the stations situated close to rupture initiation point is ≥ 1 g. The estimated PGA values have been compared with the PGA values of other studies. The earthquake has been simulated using three different rupture points The station having highest PGA values changed with rupture initiation point. The intensity values are correlated with the damage pattern of region and therefore relatively more useful for agencies involved in the mitigation of seismic hazard of the region. Accordingly, the synthetic intensity maps have been generated in the present study by converting PGA values into MMI values using an empirical relation. The comparison with the other studies shows an agreement with the other studies. This modified technique is independent aftershocks database and velocity-Q structure. This research work will help bringing light on the effect of site response functions and kappa factor. This kind of study can help in mitigate the earthquake hazard and design an earthquake-resistant structures and building for that particular area. [ABSTRACT FROM AUTHOR]

High-voltage transmission lines are susceptible targets for lightning strikes. It is an interesting topic how the trip event of transmission line is related to the area, location, and intensity of thunderstorms occurring at that time and that place. Based on total lightning observation containing intra-cloud and cloud-to-ground lightning, and transmission line trip information from relaying system of power system, 8 thunderstorms associated with the lightning strike trip of local transmission lines were selected in the Pearl River Delta (PRD) region. Analysis was conducted on the total lightning activity of each thunderstorm process, including the characteristics of total lightning counts and density, followed by the variations in total lightning activity before and after lightning strike trips. Further, our investigation encompassed the spatial and temporal evolution, charge structure, and kinematic parameters of thunderstorms. It was revealed that almost all lightning trips in this area emerged in close proximity to bodies of water, accompanied by a discernible reduction in thunderstorm cloud altitude during line trip occurrences. This paper aims to enhance the understanding of total lightning and thunderstorm activity behavior, thereby providing valuable insights for lightning disaster prevention and mitigation in the meteorological bureau and power system. [ABSTRACT FROM AUTHOR]

The western flanks of the Western Ghats are one of the major landslide hotspots in India. Recent rainfall triggered landslide incidents in this humid tropical region necessitating the accurate and reliable landslide susceptibility mapping (LSM) of selected parts of Western Ghats for hazard mitigation. In this study, a GIS-coupled fuzzy Multi-Criteria Decision Making (MCDM) technique is used to evaluate the landslide-susceptible zones in a highland segment of the Southern Western Ghats. Fuzzy numbers specified the relative weights of nine landslide influencing factors that were established and delineated using the ArcGIS, and the pairwise comparison of these fuzzy numbers in the Analytical hierarchy process (AHP) system resulted in standardized causative factor weights. Thereafter, the normalized weights are assigned to corresponding thematic layers, and finally, a landslide susceptibility map is generated. The model is validated using the area under the curve values (AUC) and F1 scores. The result reveals that about 27% of the study area is classified as highly susceptible zones followed by 24% area in moderately susceptible zone, 33% in low susceptible, and 16% in a very low susceptible area. Also, the study shows that the plateau scarps in the Western Ghats are highly susceptible to the occurrence of landslides. Moreover, the predictive accuracy estimated by the AUC scores (79%) and F1 scores (85%) shows that the LSM map is trustworthy for future hazard mitigation and land use planning in the study area. [ABSTRACT FROM AUTHOR]

Floods are recurrent global catastrophes causing substantial disruptions to human life, extensive land degradation, and economic losses. This study aims to identify flood-triggering watershed features and employ a Multi-Criteria Decision-Making (MCDM) approach based on the Analytical Hierarchy Process (AHP) model to delineate flood-prone zones. Weights for various flood-influencing factors (slope, rainfall, drainage density, land-use/land-cover, geology, elevation, and soil) were derived using a 7 × 7 AHP decision matrix, reflecting their relative importance. A Consistency Ratio (CR) of 0.089 (within acceptable limits) confirms the validity of the assigned weights. The analysis identified approximately 128.51 km2 as highly vulnerable to flooding, particularly encompassing the entire stretch of riverbanks within the watershed. Historically, snow avalanches and flash floods have been the primary water-related disasters in the region, posing significant threats to critical infrastructure. In this context, this model-based approach facilitates the proactive identification of susceptible areas, thereby promoting improved flood risk mitigation and response strategies. [ABSTRACT FROM AUTHOR]

Earthquake size distribution is characterized by the "b-value" of the power law decay, which exhibits spatiotemporal variations. These variations are sometimes evident before a large earthquake. Understanding spatiotemporal variations is key to developing a model for large-earthquake generation. Previous studies have shown that changes in the b-value are caused by the tectonic stress regime. Furthermore, lab experiments have demonstrated the b-value dependency of acoustic emissions on the criticality of the failure condition. However, the factors controlling the b-values during natural seismic activity are unclear. In this study, changes in the b-value in small earthquake sequences are investigated, focusing on failure criticality. Based on our high-precision focal mechanism dataset, we conclude that the b-value decreases as it nears a critical failure condition, providing a physical explanation for the reduction in b-value before a major earthquake. Our findings elucidate fault failure models, facilitating improvement in earthquake alerts and disaster mitigation. The b-value in earthquake size distribution shows spatiotemporal variations, being key to consider large-earthquake genesis. By high-precision focal mechanism data, we show a physical reason for the reduction in b-value before a major earthquake. [ABSTRACT FROM AUTHOR]

The world has been facing an increase in various natural hazards. The coastal regions are recognized as one of the most vulnerable due to high population pressure and climate change intensity. Mediterranean countries have one of the most burnable ecosystems in the world, one of the most exposed to pluvial floods, and have the highest erosion rates within the EU. Therefore, the aim of this study was to develop the first multihazard susceptibility model in Croatia for the Sali settlement (island of Dugi otok). The creation of a multi-hazard susceptibility model (MHSM) combined the application of geospatial technology (GST) with a local perception survey. The methodology consisted of two main steps: (1) creating individual hazard susceptibility models (soil erosion, wildfires, pluvial floods), and (2) overall hazard susceptibility modeling. Multicriterial GIS analyses and the Analytical Hierarchy Process were used to create individual hazard models. Criteria used (32) to create models are derived from very-high-resolution (VHR) models. Two versions of MHSM are created: 1) all criteria with equal weighting coefficients and 2) weight coefficients determined based on public perception. According to MHSM 1, most of the research (58%) area is moderately susceptible to multiple hazards. Highly and very highly susceptible areas are 27% of the drainage basin and are mostly located near roads and houses. MHSM 2 reveals similar results to MHSM 1. The public perceives that the research area is the most susceptible to wildfires. The wildfire ignition risk is ranked as moderate (3.00) with a standard deviation of 1.16. Pluvial flood risk is ranked low (2.78), with a standard deviation of 1.15. The risk of soil is most inferior (2.24) with a standard deviation of 0.91. The the most significant difference between public perception and the GIS-MCDA model of hazard susceptibility is related to soil erosion. However, the accuracy of the soil erosion model was confirmed by ROC curves based on recent traces of soil erosion in the research area. The proposed methodological framework of multi-hazard susceptibility modeling can be applied, with minor modifications, to other Mediterranean countries. [ABSTRACT FROM AUTHOR]

The 6th World Landslide Forum (WLF6) took place in Florence, Italy from November 14 to 17, 2023. The forum focused on landslide science for sustainable development and aimed to contribute to global commitments and agreements related to disaster risk reduction and sustainable development. The event brought together researchers, stakeholders, and organizations from around the world to collaborate on priority actions for landslide risk reduction. The forum included presentations, workshops, and exhibitions, and was attended by over 1200 participants from 61 countries. The opening plenary session discussed the importance of sharing information, supporting research, and improving landslide preparedness and response. The Florence Declaration on Landslide Risk Reduction was adopted, committing to these goals. The recognition and awards ceremony honored individuals and organizations for their contributions to landslide science. The parallel sessions program covered various themes related to landslides, including international programs, multi-hazard risks, societal aspects, cultural heritage, and ground failures triggered by earthquakes. The document also provides an overview of different chapters in a book or report on landslides, covering topics such as regional and global landslide inventories, monitoring and predicting landslides, and the effects of climate change on landslides. [Extracted from the article]

Debris flow has always been a serious problem in mountainous areas. Accurate debris flow susceptibility (DFS) assessment and interpretable prediction results play an important role in the prevention and control of debris flow disasters. Some commonly used machine learning algorithms based on Boosting ensemble techniques were widely used in the study of geohazard susceptibility due to its excellent predictive ability. However, the Categorical Boosting (CatBoost) and Natural Gradient Boosting (NGBoost) have not yet been applied in the field of DFS assessment, and few geohazard studies systematically compare and research these boosting-based algorithms. Meanwhile, previous researches have mostly focused on comparing the predictive ability of algorithms, identifying the susceptibility zones of the entire study area, and ranking the importance of the indicators, but little thorough analysis of the relationship between the indicators and debris flow susceptibility on different types of construction land. The aims of this study were to explore the optimal boosting-based DFS model, and the distribution characteristics and change rules of DFS in the study area, so as to provide decision supports for debris flow disaster prevention and reduction. This was the first time that six boosting-based machine learning algorithms have been compared in the study of DFS assessment. After determining the optimal model, the change rules of indicators in the entire study area and two types of construction lands under different DFS levels were studied respectively. An eXplainable Artifcial Intelligence (XAI) method called SHapley Additive exPlantations (SHAP), combined with zonal statistics function in geographic information system (GIS) were adopted to explore how each indicator affects the occurrence of debris flows. The results showed that the CatBoost performed best and provided the most reasonable DFS result among six boosting-based models. We found that debris flows were more likely to occur along rivers and construction lands at low altitude. Rural areas faced more stronger pressure from rainfall and were featured by worse disaster-breeding environment than urban areas. This research enriches the application of machine learning in DFS assessment, explores the changing trends of indicators between different DFS levels, and provides suggestions for better debris flow disaster prevention and mitigation management. [ABSTRACT FROM AUTHOR]

Accuracy in the global climate model (GCM) projections is essential for developing reliable impact mitigation strategies. The conventional bias correction methods used to improve this accuracy often fail to capture the extremes, specifically for precipitation, due to the generic correction application to whole data. Given the importance of understanding future extreme precipitation behavior for disaster mitigation, we propose Extremes-Weighted Empirical Quantile Mapping (EW-EQM) bias correction with a specific emphasis on extremes. The EW-EQM applies separate EQM correction to threshold-exceeded extremes and frequency-adjusted non-extreme precipitation occurrences. The bias correction results demonstrated using station-observed precipitation records at 945 locations in the Mid-Atlantic region of the United States, and five Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs demonstrate the strength of EW-EQM to improve the bias correction abilities of extreme precipitation occurrences. The spatial median of Root Mean Square error between observed and bias-corrected extreme precipitation was mostly less than 6 mm for EW-EQM across GCMs, while EQM and Power Transformation had a median higher than 12 mm. Further, future bias-corrected precipitation series for 2021–2050 under SSP245 indicate a 0–10% increase in total annual precipitation and a 10% decrease to 25% increase in mean annual maximum precipitation in the region. The improved bias correction of extremes could be significant in climate change impact mitigation decisions such as flood management. Highlights: An Extremes-Weighted Empirical Quantile Mapping (EW-EQM) climate data bias correction is proposed. The EW-EQM gives specific emphasis on the threshold exceedance extreme precipitation events. The EW-EQM outperforms conventional EQM for extreme precipitation events. An increase of up to 25% in mean extreme precipitation is for the Mid-Atlantic region of the US under SSP245 in the near future. EW-EQM preserves the raw GCM trends for extremes, while EQM does not. [ABSTRACT FROM AUTHOR]

In this study, comprehensive analytical and parametric studies were conducted on seismic performance of concrete structures equipped with self-centered unbonded post-tensioned hybrid wall system in comparison with traditional structural wall system. For this purpose, analytical models were developed and to further study the seismic performance of self centering hybrid wall, parametric analysis was performed considering four parameters: wall aspect ratio, initial stress of post-tensioned (PT) tendons, the total area of PT tendons, the total area of mild bars. The performance of buildings was evaluated under non-linear quasi cyclic and time history method considering two seismic hazard levels, the design-based earthquake (DBE) level and the risk-targeted maximum considered earthquake (MCE) level. Hysteresis response, damage severity and pattern index estimation, energy dissipation ability and damping ratio, relative self-centering efficiency (RSE), residual drift, peak roof drift and inter-story drift ratio, floors acceleration, shear force ratio, column curvature ductility, prestressing and gap opening effect of all buildings were studied. The results of the parametric analysis showed by increasing the prestressing ratio, wall damage severity, residual drift and energy dissipation capacity were decreased and structural seismic demand and RSE increased, while increasing mild bars was the most efficient method for improving the energy dissipation ability. [ABSTRACT FROM AUTHOR]

The Greek National Annex for current Eurocode 8 has adopted the seismic hazard zonation map published in 2003 as part of the modifications to the Greek Seismic Code EAK 2000 (EAK 2003). This map, which followed the catastrophic earthquakes that hit the country between 1978 and 2001, includes three seismic hazard zones with peak ground acceleration (PGA) ranging between 0.16 and 0.36 g. In this paper, following the significant progress that has been made worldwide in the last two decades towards the improvement of the definition of seismic actions and the seismic hazard maps using fully probabilistic models, we make a complete proposal for the Greek National Annex of the ongoing revision of Eurocode 8, which includes a new seismic hazard zonation map for Greece, as well as a novel site categorization scheme and related site amplification factors. To this end, we use the results of the European Seismic Hazard Model, ESHM20, as reported by Danciu et al. (The 2020 update of the European Seismic Hazard Model: Model Overview, 2021) which will be adopted as informative reference for the seismic hazard at European level in the forthcoming revision of Eurocode 8 (CEN/EC8). The herein proposed ground shaking zonation for rock conditions includes five zones with PGA values ranging between 0.13 and 0.37 g. For each zone, two newly proposed ground motion parameters, i.e., Sα,475 and Sβ,475, are provided, which are the two parameters used for anchoring the elastic response spectrum as defined in CEN/EC8, along with all the other necessary parameters for the definition of the elastic response spectrum, including site amplification. The proposal for the new seismic zonation is supported by a preliminary investigation of the impact of its adoption on the seismic design of new structures and on the seismic risk of the current building stock in Greece, to help gain a better insight on how important the differences imposed by the new zonation might be for the end-users and the administration. [ABSTRACT FROM AUTHOR]

The Garhwal region, situated in the central segment of the Himalayas, stands as one of the most seismically active areas in the Uttarakhand Himalaya. The newly established earthquake early warning (EEW) system in the Garhwal region emphasizes the critical need for magnitude scaling relations to enable real-time estimation of earthquake size. This study employs P-wave onset data from both observed and simulated records to develop magnitude scaling relations specific to the Garhwal region. Initially, we modified the semi-empirical technique (SET) for P-wave simulation and validated this modification using the 1991 Uttarkashi (Mw6.8) and 1999 Chamoli (Mw6.4) earthquakes in the Garhwal region. The modified semi-empirical technique (MSET) demonstrates its reliability, as evidenced by the comparatively low root mean square error (RMSE) between observed and simulated records for both earthquakes. Subsequently, we apply MSET to simulate seven additional future earthquakes (Mw7.0–8.5) at the hypocentral locations of the 1991 Uttarkashi and 1999 Chamoli earthquakes. Moreover, conventional EEW parameters, such as average period (τc) and peak amplitude displacement (Pd), are extracted from 107 observed and 63 simulated P-wave onsets, utilizing a 3 s time window. Using this combined dataset of observed and simulated data, we introduce magnitude scaling relations based on the τc and Pd parameters. Subsequently, the developed scaling relations are tested to predict earthquake magnitude using the average values of estimated EEW parameters. The relatively small errors, measuring at 4.47–0.75%, and 2.45–0.60% for τc–Mw and 5.71–1.60% and 4.90–1.57% for Pd–Mw scaling relations, respectively for the Uttarkashi and Chamoli earthquakes suggest the applicability of these proposed relations. However, the scaling relations developed tend to underestimate the magnitude of earthquakes larger than 7.5, potentially attributed to the saturation observed in these relations for big earthquakes. Additionally, the calculated lead time for future earthquakes will range from 4 to 60 s for the sites situated within epicentral distances of 56–200 km. This lead time has the potential to play a substantial role in disaster mitigation in the Garhwal region, especially in the Indo-Gangetic plains and Himalayan foothills. Hence, the development of scaling relations specific to the region is imperative for effective disaster mitigation and risk reduction in the Garhwal region. [ABSTRACT FROM AUTHOR]

A hazard is a natural occurrence that might harm humans, animals or the environment. It may cause loss of life, illness or other health consequences, property damage, social and economic crisis or environmental degradation. Various regions around the world are vulnerable to one or more types of disasters. Flooding is one of the worst environmental catastrophes that impacts both civilisation and the environment globally. Various datasets and methods, such as meteorological data, satellite images and GIS, were used to create the hazard assessment map. For a particular region, flood hazards can be developed by integrating an assessment map for several parameter categories. The aim of the study was to evaluate the hazard of flooding and map the areas that will be flooded in Gujarat. This study develops and tests flood-hazard maps to visualise the spatial variation of hazards in Gujarat, India. The parameters for flood-hazard assessment are mainly considered as elevation, slope, aspect, curvature, lithology, soil, land use/cover, drainage density and distance from the river, and rainfall to create a map in the context of a GIS. The acquired data was evaluated using ArcGIS and fuzzy-logic techniques to build a flood hazard map. Five categories have been assigned to the computed flood hazard map: very low, low, moderate, high, and very high. Engineers, planners and local governments may find this study useful in the future when it comes to land use planning and the control of hazards. Flood hazard potential mapping is necessary to manage and mitigate flooding. [ABSTRACT FROM AUTHOR]

The Beirut port explosion on August 4, 2020, caused extensive destruction and significant casualties, prompting inquiries into its scale and impact on neighboring structures. Speculation arose regarding the role of the nearby port silos in shielding western Beirut from the blast. This study leverages insights from previous research and uses a tailored blast wave propagation model to settle the debate on the silos' effectiveness in mitigating blast impacts. The analysis challenges prevailing notions: firstly, that the silos offered substantial protection, and secondly, the assumption linking the transient "window" phenomenon in the Wilson cloud to a similar opening in the preceding pressure front. Contrary to expectation, the pressure at the shock front remains continuous, albeit lower on the leeward side behind the silos. Downstream lateral regions experience pressure amplification due to the constructive interference of waves diffracted around the silos, with significant attenuation observed close (10 m) behind them—approximately 12%, 58%, and 2% of free-air values for overpressure, specific impulse, and specific energy, respectively. However, this shielding effect diminishes with distance, with the blast wave intensity largely restored at 450 m. Consequently, the silos' shadowing effect was limited to nearby port structures and part of the Lebanese navy base, which still incurred severe damage. The lesser impact on western Beirut is attributed to its greater distance from the explosion rather than the silos' protective influence. These findings suggest a reevaluation of urban disaster mitigation strategies, emphasizing geographical positioning over structural barriers and advocating for a holistic approach to urban resilience. [ABSTRACT FROM AUTHOR]

The Himalayan region and its surrounding area are one of the most seismically active zones in the world which have significant economic and societal impact. It governs the seismicity of highly populous countries like India, China, Pakistan, Nepal, Bhutan and Afghanistan which account for more than 40% population of the world. Therefore, the complex interaction between seismic parameters and transient seismic events needs to be thoroughly addressed at the regional scale. This study highlights the spatial distribution of earthquake hazard parameters and the temporal variation in seismicity of the Himalayas and its nearby regions by employing the maximum likelihood approach using historical records as well as instrumentally recorded earthquake data of the years 1900–2021. An empirical relation is developed to convert the body wave magnitude (Mb) and surface wave magnitude (Ms) to moment magnitude (Mw). The seismic parameters, namely maximum regional magnitude (Mmax), b-value, and mean seismicity rate (λ0), are estimated for 13 defined zones. Further, the seismic behaviours of the study area are evaluated through the return periods (RP) of earthquakes and the fractal dimension (Dc) of the individual zone. Considering the temporal variation of seismicity and RP of Mw ≥ 6, a new index , i.e. earthquake susceptibility index (ESI6), is developed to identify the zones which are susceptible to Mw ≥ 6 earthquakes. The zones: Central Himalayas 2 (CH2), Western Himalayas (WH), North of MCT 1 (NMCT1) and South of MCT 2 (SMCT2) are identified to be highly susceptible to earthquakes of Mw ≥ 6. The present analysis will motivate researchers and engineers from government and non-government organizations to collaborate for improved policy making in the seismically active Himalayan region concerning land-use planning, insurance, and catastrophe preparation. [ABSTRACT FROM AUTHOR]

In this study, the double-difference tomography (tomoDD) method is applied to jointly invert the three-dimensional (3-D) crustal velocity structure and earthquake locations in the Maduo area based on automatically and manually picked seismic phase data. The results show that: (1) We speculated that the seismogenic fault is the Kunlun Pass–Jiangcuo Fault based on the spatial distributions of the aftershocks and surface rupture and the strike slip nature of the fault and the mainshock. In addition, a continuous northwest-trending branch fault may exist on the north side of the western section of the Maduo aftershocks. (2) We speculated that the Maduo earthquake was a bilateral rupture based on the media strength of the upper crust and near the surface and the seismic distribution. The findings also provide evidence for the large-scale rupture of the Maduo earthquake. In addition, the high-velocity body to the upper right of the mainshock satisfactorily explains the unobvious rupture above the mainshock. The late weak seismicity indicates that the energy released during the earthquake rupture was sufficient, and it is concluded that the short-term seismic hazard is insignificant. (3) The low S-wave velocity and high wave ratio reflect the existence of crustal fluids in the Maduo area based on the results of previous studies. The Maduo earthquake occurred on the side of the biased high-velocity body in the high-low velocity transition zone, where the stress easily accumulates and is easily released. Therefore, we conclude that the Maduo earthquake accumulated significant stress in the source area. The crustal fluids encountered a hard slope-type high-velocity body and flowed upward into the seismogenic fault, weakening the seismogenic fault. The combined effect of both processes finally triggered the Maduo MS7.4 earthquake. [ABSTRACT FROM AUTHOR]

This study aims to characterize the frequency magnitude distribution factor (b-value) for Nepal and its surrounding area-thereby focusing on conducting spatiotemporal and depth-wise analysis of b-value fluctuations before the November 9, 2022 earthquake of magnitude MW 6.3. Using the non-parametric Kolmogorov–Smirnov (K–S) test, earthquake events with a magnitude MW ≥ 3.5 reported between 1900 and 2022 from the earthquake catalog compiled by the International Seismological Centre (ISC) and the United States Geological Survey (USGS) were analysed. We determined the minimum magnitude of completeness (MC) using the Maximum Curvature Method (MAXC). Furthermore, we divided the study region into equal-sized square grids and computed b-values using the maximum likelihood technique for each grid. We analysed the relationship between the b-value and seismic parameters such as focal depth, seismic moment release, and radon gas anomalies, along with their spatial correlations and patterns. Results indicate minimal seismicity in the lower crust compared to the upper crust and lead to establish an inverse relationship between the b-value and seismic moment release. We established plausible correlations between temporal variations of the b-value and variations in radon gas concentration as an earthquake precursor in different medium. Additionally, we utilized the Gumbel extreme value theory to estimate the mean return period, the most likely maximum yearly earthquake, and probabilities of recurrence of different magnitudes across different periods for credible seismic hazard analysis. We found the most likely maximum yearly earthquake for the region to be 5.53, with a mean return period of 5 years for the November 9, 2022 earthquake. The mean return period of earthquakes with magnitudes ranging from 5.0 to 6.5 (MW) was estimated to be 5–10 years. These findings contribute to a better understanding of the intricate seismotectonic configuration of the region and serve as earthquake precursors for potential future destructive earthquakes. [ABSTRACT FROM AUTHOR]

Landslides, widespread and highly dangerous geological disasters, pose significant risks to humankind and the ecological environment. Consequently, predicting landslides is vital for disaster prevention and mitigation strategies. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. At present, the predominant methods for predicting landslide susceptibility are evolving from conventional machine learning techniques to deep learning approaches. Prior studies have shown that in the context of landslide susceptibility, these models frequently underperform relative to tree-based machine learning algorithms. This shortcoming has restricted the application of deep learning in this domain. To overcome this challenge, this study presents the TabNet algorithm, which combines the interpretability and selective feature extraction of tree models with the representation learning and comprehensive training capabilities of neural network models. This paper explores the potential of employing the TabNet algorithm for landslide susceptibility analysis in China's WanZhou region and evaluates its performance against traditional machine learning techniques. The experimental data indicate that the TabNet algorithm achieves a recall score of 0.898 and an AUC of 0.915, demonstrating a generalization capability that is comparable to that of classical machine learning algorithms. [ABSTRACT FROM AUTHOR]

This study presents probabilistic surface seismic hazard maps for Algiers city in terms of PGA and spectral acceleration for a return period of 475 years (corresponding to 10% in 50 years). The site effect is integrated through a fully probabilistic approach. Seismic hazard analysis for reference rock sites (Vs30 = 800 m/s) is conducted first based on an updated seismic source model, including area sources and active faults, and three selected ground motion prediction equations, Epistemic uncertainties related to source model (slip rate for faults, Gutenberg Richter's parameters for area source) and ground motion equation selection are considered through logic tree approach. Then, 1D ground response analysis is performed to estimate soil amplification factors and their standard deviations considering uncertainties related to input motion variability. Finally, probabilistic site specific-PSHA using modified_GMPE with respect to amplification factors, is conducted for more than 4000 soil profiles. Surface seismic hazard maps in terms of PGA, and PSA(T) are shown for the study area, they highlight an important site to site variability within the same soil class (S2 and S3) according to the Algerian seismic design code (RPA). In addition, surface uniform hazard spectra (surface_UHS) for several selected sites belonging to different geotechnical units are compared with the current design spectra prescribed in seismic design codes (RPA, EC8). These findings emphasize the value of conducting a site-specific PSHA study, given the considerable discrepancy that can exist between a site-specific spectrum and a seismic design spectrum. While design spectra tend to be more conservative for longer periods (>0.3 s), the specific spectrum yields greater accelerations for shorter periods, particularly for soils of class S3. [ABSTRACT FROM AUTHOR]