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Business-to-business suppliers invest in safety training programs believing that such programs mitigate safety hazards, prevent workplace injuries, and create value for their customers. However, causal evidence of these effects is sparse. Study 1 uses site-level monthly data from a global oil field services company. Exploiting sharp discontinuities in safety training hours due to catastrophic accidents, the authors find that a 10% increase in safety training hours per capita decreases safety hazards per capita by 6.45%–9.57%. Study 2 measures the causal impact of business establishments' safety training intensity on their workplace injuries: it leverages Local Law 196 requiring workers at construction establishments in New York City to complete at least ten hours of safety training. This legislation reduced injury rates at construction establishments in New York City by.54–.68 percentage points (a 15.56%–18.84% decrease) relative to their counterparts. Study 3, a stated-choice conjoint experiment of business-to-business procurement professionals, documents that the focal supplier's investment in safety training increases the probability of its proposal being selected by those professionals. Collectively, these findings validate the need for suppliers to invest in safety training as a risk-mitigation vehicle that has positive implications for business-to-business buying decisions. [ABSTRACT FROM AUTHOR]

This study, which is based on actual events, presents a dynamic analysis of the development, implementation, and post-implementation review of establishing an enterprise risk management (ERM) system for a U.S. multinational nonprofit firm over a 5-year period, 2015–2020. Using the Risk and Insurance Management Society Risk Maturity Model (RIMS RMM), questionnaire-based risk data and multi-dimensional risk mapping indices are used to identify and prioritize the firm's key strategic risks leading to the development of mitigation strategies whose performance are reviewed post ERM implementation, including during the 2020 Coronavirus pandemic. The results reveal that the firm's risk management system has been ad hoc and uncoordinated. Post-implementation review of the ERM program shows improvements in financial and operating positions resulting from risk diversification, enhanced profitability, exploitation of natural hedges, and improved board governance. The results further show that the recommended mitigation strategies have been effective in managing the adverse impact of the pandemic. Overall, the evidence offered in this study provides further support on the valuation benefits of ERM maturity within a real-world environment. [ABSTRACT FROM AUTHOR]

The Indian subcontinent is highly susceptible to natural disasters. To abate the effect of the disasters, the government emanates institutional mechanisms and strategies for disaster preparedness, mitigation and response. Although there is well-established institutional framework in India for disaster management, there is no study that proposes a disaster supply chain structure under the institutional framework and integrates information and digital technologies (IDT) of industry 4.0 within it. The present study overcomes this research gap. It introduces an IDT structure within the institutional framework of India for multi-agency information sharing, coordination and decision making. It formulates a mathematical model and analyses the impact of IDT on the total response time through three scenarios. The results of scenario analysis reveal the significance of IDT on the disaster supply chains and its capability to handle information delays and IDT failure. The present study can be adopted by disaster management institutions to construct and implement better response practices at the operational, planning and strategic levels. Furthermore, the proposed model in the study can be used for vaccination planning, which includes vaccine distribution, monitoring, regulation and effective implmentation as a response against the current pandemic situation caused due to SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Cyberattacks have been increasing in volume and intensity, necessitating proactive measures. Cybersecurity risk management frameworks are deployed to provide actionable intelligence to mitigate potential threats by analyzing the available cybersecurity data. Existing frameworks, such as MITRE ATT&CK, provide timely mitigation strategies against attacker capabilities yet do not account for hacker data when developing cyber threat intelligence. Therefore, we developed a novel information technology artifact, ATT&CK-Link, which incorporates a novel transformer and multi-teacher knowledge distillation design, to link hacker threats to this broadly used framework. Here, we illustrated how hospital systems can use this framework to proactively protect their cyberinfrastructure against hacker threats. Our ATT&CK-Link framework has practical implications for cybersecurity professionals, who can implement our framework to generate strategic, operational, and tactical cyber threat intelligence. ATT&CK-Link also contributes to the information systems knowledge base by providing design principles to pursue targeted cybersecurity analytics, risk management, and broader text analytics research through simultaneous multi-modal (e.g., text and code) distillation and classification. [ABSTRACT FROM AUTHOR]

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]

AbstractProblem, research strategy, and findingsTakeaway for practiceAs communities everywhere experience accelerating climate change impacts, local governments must proactively plan and implement adaptation or resilience strategies. A significant challenge is effectively scaling up these efforts in diverse communities. In 2015, the State of California passed Senate Bill 379 (SB379), requiring climate change adaptation and resilience strategies in local plans, making it the first U.S. state to broadly mandate such requirements locally. Our study measured the effects of SB379 on the quality of local plans that address climate change adaptation or resilience and assessed which types of plans jurisdictions selected to meet the requirements. Using a longitudinal study, we analyzed plan quality before and after SB379 took effect using criteria developed for earlier studies of voluntary climate adaptation plans. We found that California plans have significantly improved when assessed against theoretical criteria, and most jurisdictions have chosen their local hazard mitigation plans to meet the requirements. The flexible and cooperative design of the mandate and its loose enforcement suggest local jurisdictions are willing to address climate change, even when challenged with more stringent requirements if incentives align. As a natural policy experiment, California’s experience offers a unique opportunity to examine the effects of a state planning mandate and the choices local jurisdictions make to comply.Cooperative mandates that require local governments to address climate change adaptation and resilience in their plans but offer flexibility in how they do so may improve the quality of plans. Practitioners should seek to leverage flexibility in such mandates to the advantage of their local communities. [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]

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Construction Hazard Prevention through Design (CHPtD) is widely recognized as a key approach for preventing injuries in construction workplaces. It prioritizes the safety of construction workers by explicitly tackling potential hazards during the design development phase. This involves proactively incorporating design features aimed at minimizing the risk of workplace injuries. Despite the theoretical promise of CHPtD, practical implementation has faced significant challenges. Notably, prior research has emphasized issues such as designers' unfamiliarity with construction means and methods, along with their inability to anticipate safety hazards that may arise in the field due to their design choices. In response, proponents of CHPtD have advocated for educational interventions aimed at equipping designers with the essential skills needed for effective implementation of CHPtD. This investigation assessed the effectiveness of YouTube as an educational resource for enhancing hazard recognition in simulated CHPtD review sessions among civil engineering students. YouTube was expected to aid hazard recognition due to its extensive collection of videos featuring various construction operations and related safety hazards. The study utilized a randomized controlled experiment to evaluate treatment effects. The results indicate that YouTube can serve as a valuable tool in supporting CHPtD efforts. Furthermore, the benefits derived from using YouTube were more pronounced when examining specific building elements (e.g. interior upper-level drywall) compared to other elements. [ABSTRACT FROM AUTHOR]

Being part of the seismically active "Pacific Ring of Fire," earthquakes in the Philippines have ever been occurring. Many studies have been conducted assessing the earthquake preparedness of the people, yet there needs to be more studies among rural communities. This research study aims to fill in the gaps as it assesses the earthquake preparedness of people living in rural communities, particularly in Ipil-Cuneg, Bayombong, Nueva Vizcaya. The study utilized a mixed method of qualitative and quantitative methodology. A survey questionnaire was used to assess the earthquake preparedness of the respondents in terms of awareness and practices among the 187 sample size. With the use of inferential and statistical treatments, it was found that the respondents are very aware and prepared about the necessities regarding earthquake preparedness. However, it is analyzed that earthquake preparedness has very low to no relationship to the residents’ demographic profiles. The respondents’ awareness and practices are also found to have a very high positive correlation. The respondents’ actions are based on what they know and are aware of. Moreover, the respondents deem that awareness and practices are essential in preparation for earthquake occurrences to know what they should do during the event. These findings can be used to establish disaster risk mitigation interventions for the barangay in order for the people to strengthen their knowledge and practices about earthquake preparedness. It is recommended that authorities should initiate programs that would shape the community to be efficient in times of disaster. [ABSTRACT FROM AUTHOR]

Currently, there is no clear understanding of the comprehensive set of variables that controls fluxes of relativistic electrons within the outer radiation belt. Herein, the methodology based on causal inference is applied for identification of factors that control fluxes of relativistic electrons in the outer belt. The patterns of interactions between the solar wind, geomagnetic activity and belt electrons have been investigated. We found a significant information transfer from solar wind, geomagnetic activity and fluxes of very low energy electrons (54 keV), into fluxes of relativistic (470 keV) and ultra‐relativistic (2.23 MeV) electrons. We present evidence of a direct causal relationship from relativistic into ultra‐relativistic electrons, which points to a local acceleration mechanism for electrons energization. It is demonstrated that the observed information transfer from low energy electrons at 54 keV into energetic electrons at 470 keV is due to the presence of common external drivers such as substorm activity. Plain Language Summary: Despite the fact that the discovery of the radiation belts occurred more than 60 years ago, a comprehensive understanding of the physical processes that are involved in the dynamics of the fluxes of relativistic electrons in the outer radiation belt is still lacking. Development of a thorough physical model accounting for the radiation belt dynamics has the potential to assist mitigation of spacecraft hazards caused by energetic particles. Herein, an information‐theoretical approach, based on the methodology of causal inference, is applied for identification of factors that control fluxes of relativistic electrons in the outer belt. The patterns of interactions between the solar wind, geomagnetic activity and belt electrons have been investigated. We have found that inward radial transport from an external source is a less favorable mechanism than local acceleration for the energization of outer radiation belt electrons from relativistic to ultra‐relativistic energies. Key Points: Evidence of direct causality from relativistic into ultra‐relativistic electrons, compatible with local acceleration in the outer beltDetection of information transfer unveils the mechanisms of energy transfer in radiation belts, important for space weather forecastingInformation flow formulation of causality has a great potential for space physics discoveries [ABSTRACT FROM AUTHOR]

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post‐event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric (Q*) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross‐section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow‐type observations. Plain Language Summary: Steep channels in rocky landscapes and recently burned areas carry a wide range of flow types, ranging from water floods to highly destructive debris flows composed of rock, sediment, other incidental debris, and water. Typically, the flow type that recently occurred in a channel is identified by interpreting the structure of deposits left behind by the flow. However, these deposits can be challenging to interpret, provided they are preserved at all. Prior research has shown that the shift in flow physics occurring in debris flows has the effect of amplifying the magnitude of the flow beyond that which is possible in floods. In this study, we take advantage of this flow amplification to develop a quantitative metric that allows for flow type to be identified without interpreting depositional structures. We demonstrate the metric to be highly accurate. This methodology should increase the accuracy of predictive models trained on such observations, which can help to better understand where these hazards exist and protect communities and infrastructure at risk. Key Points: To distinguish debris flows from floods, a metric Q* equal to the ratio of peak discharge to rainfall‐runoff discharge is developedQ* separates floods (Q* ≤ 1) from debris flows (Q* > 1) to ∼92% accuracy and is robust to uncertainties in the key parametersThe Q* metric should reduce misidentification of flow type and increase the performance of empirical‐hazard models and hazard mitigation [ABSTRACT FROM AUTHOR]

The Maltese archipelago is renowned for its spectacular coasts, characterized by vertical cliffs and scree slopes. In the western sector of Malta and the eastern region of Gozo, a marly clay formation with ductile properties underlying a stiff limestone unit has led to relevant lateral spreading. Utilizing drone aerial photogrammetry, digital elevation models, and satellite imagery, we analyzed the ongoing geomorphological processes across five promontories, selected as case studies. Our analysis reveals a complex interaction between geological structures, Quaternary sea level fluctuations, and lateral spreading processes. Photogrammetric models show that once detached, blocks from the plateaus tend to topple and fall or experience subsidence and backtilting. At Rdum il-Qammieħ, fractures up to 250 m long and openings of up to 2 m were observed, while at Sopu, detached blocks exhibit subsidence of up to 50% and rotations nearing 60°. In all the studied promontories, rotational slides predominantly occur at the frontal sectors, while toppling mechanisms are more common along scarp-edged plateaus. The thickness ratio between the stiff and the ductile formation, ranging from 0.13 to 1.12, along with slope gradients between 10° and 41°, further influence the stability of these coastal features. We discuss the structural and sea level influences on Maltese coastal cliff development over the last 125 ky. We propose a conceptual model outlining the evolution of the Malta Graben promontories through a three-stage evolutionary model: proto-promontories, cliff demolition, and isolation. This model emphasizes the significant role of predisposing, preparatory, and triggering factors in the geomorphological evolution of the Maltese coastline. Our findings provide essential insights into the landscape changes in the Maltese archipelago and represent a useful tool for coastal management and hazard mitigation strategies. [ABSTRACT FROM AUTHOR]

Prolonged exposure to high-intensity noise environments in urban rail transit systems can negatively impact the health and work efficiency of drivers. However, there is a lack of comprehensive understanding of the noise pattern and, therefore, effective mitigation strategies. To control the noise in urban rail transit systems, this study proposes a comprehensive noise assessment framework, including metrics such as average sound pressure level, peak sound pressure level, percentile sound pressure levels, dynamic range, main frequency component, and cumulative time energy to evaluate the noise characteristics. We also employ a density-based spatial clustering of applications with noise (DBSCAN) method to identify the noise patterns with the evaluation of their hazard to urban rail transit drivers. The results have revealed that: (1) The equivalent continuous sound pressure level (Leq) in the cab of Lanzhou Urban Rail Transit Line 1 averages 87.12 dB, with a standard deviation of 8.52 dB, which reveals a high noise intensity with substantial fluctuations. (2) Ten noise patterns were identified, with frequencies varying from 14.47 Hz to 69.70 Hz and Leq varying from 60 dB to 115 dB. (3) The major noise sources from these patterns are inferred to be the train's mechanical systems, wheel–rail interaction, aerodynamic effects, and braking systems. Combined with the noise patterns and urban rail transit's operation environment, this study proposes tailored mitigation strategies for applications aimed at protecting drivers' hearing health, enhancing work efficiency, and ensuring driving safety. [ABSTRACT FROM AUTHOR]

This document is an editorial from the journal Frontiers in Earth Science titled "Prevention, Mitigation, and Relief of Compound and Chained Natural Hazards." It discusses the increasing frequency of extreme natural disasters due to global climate warming and frequent earthquakes, which pose significant threats to human life and property. The editorial highlights the importance of preventing, mitigating, and relieving compound and chained natural hazards, and the role of technological advancements in addressing these hazards. The document provides an overview of nine published papers that focus on earthquakes, geological hazards, earthquake-triggered landslides, and landslide susceptibility. It concludes by emphasizing the need for continued research on comprehensive natural hazards and disaster chains, beyond earthquakes and geological disasters, such as meteorological events, floods, droughts, wildfires, and tsunamis. [Extracted from the article]

The mountainous areas of the Loess Plateau in China are crisscrossed with ravines, fragile ecological environment, and frequent landslide hazards. Landslides often cause building collapses and casualties, seriously affecting the sustainability of economic and social development in the region. In order to study the damage of loess landslides to village and town buildings, the paper takes the Xingwang landslide in Fugu County, Shaanxi Province, China as an example, and uses discrete element method and finite element method to study the dynamic process of landslide and its damage to houses. Firstly, the geological characteristics of the landslide were identified by means of investigation, surveying, engineering exploration and geotechnical testing. Secondly, a threedimensional numerical model of the landslide area was established by using the particle flow code system (PFC[sup 3D]). Finally, the entire movement process of the landslide was simulated, and the impact damage to houses induced from landslide was analyzed and predicted. The results show that the whole movement of the landslide lasted a total of 180 s, with a maximum average velocity of 2.01 m/s and a maximum average displacement of 73.7 m. The first and second rows of houses located at the foot of the landslide will suffer serious damage, with most bricks displacement ranging from 0.1 to 2.5 m and a maximum displacement of 10.3 m, posing a serious safety risk to the houses. Only a portion of the third row houses will be damaged, and the fourth row houses will not be threatened by landslide. By comparing with the prediction results of other methods and the current situation of buildings deformation, the results of this paper have a certain credibility. This study provides a numerical method for quantitative assessment of the risk and building damage for loess landslide, which can be used as a reference. It also provides technical support for formulating hazard prevention and reduction plans for the Xingwang landslide. [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]

Illegal coal mining is prevalent worldwide, leading to extensive ground subsidence and land collapse. It is crucial to define the location and spatial dimensions of these areas for the efficient prevention of the induced hazards. Conventional methods for goaf locating using the InSAR technique are mostly based on the probability integral model (PIM). However, The PIM requires detailed mining information to preset model parameters and does not account for the layered structure of the coal overburden, making it challenging to detect underground goaves in cases of illegal mining. In response, a novel method based on the InSAR technique and the Stratified Optimal Okada Dislocation Model, named S-ODM, is proposed for locating goaves with basic geological information. Firstly, the S-ODM employs a numerical model to establish a nonlinear function between the goaf parameters and InSAR-derived ground deformation. Then, in order to mitigate the influence of nearby mining activities, the goaf azimuth angle is estimated using the textures and trends of the InSAR-derived deformation time series. Finally, the goaf's dimensions and location are estimated by the genetic algorithm–particle swarm optimization (GA-PSO). The effectiveness of the proposed method is validated using both simulation and real data, demonstrating average relative errors of 6.29% and 7.37%, respectively. Compared with the PIM and ODM, the proposed S-ODM shows improvements of 19.48% and 52.46% in geometric parameters. Additionally, the errors introduced by GA-PSO and the influence of ground deformation monitoring errors are discussed in this study. [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]

Objectives: Convolutional neural network (CNN) was widely used in landslide susceptibility assessment because of its powerful feature extraction capability. However, with the demand for scene diversification and high accuracy, the algorithm of CNN was constantly improved. The practice of improving accuracy by deepening the network hierarchy or combining other models tended to increase the number of model parameters and the amount of calculation greatly, which led to the difficulty of model training or the overfitting of results, thus limiting its practical application. We want to solve the above problems from the model structure. of feature maps, one-dimensional CNN（1D-CNN） and two-dimensional CNN（2D-CNN） were connected to maintain network depth, limit model parameters, and reduce computation. The parameters sharing of multidimensional convolution kernels was used to capture the deep coupling features of different dimensions and different landslide factors, so as to make full use of features and avoid overfitting. Taking Sedongpu gully in Xizang,China as the experimental area, this paper selected 11 kinds of landslide influencing factors to analyze the landslide susceptibility. Results: The results show that the multi-dimensional CNN coupling structure had the same training efficiency as the shallow 2D-CNN with fewer parameters due to the reduced computational effort. While compared with the deep 2D-CNN with the approximate number of parameters, the training time of the proposed method was significantly reduced and the training cost was lower. In addition, the coupled model had a stronger feature learning ability than the independent 1D-CNN and 2D-CNN, and therefore obtained higher model accuracy. Under each confusion matrix metric of the testing data, the coupled model received higher scores, and thus obtained more reliable landslide susceptibility assessment results. Conclusions: The multidimensional CNN coupling model proposed in this paper is a reliable method applicable to landslide susceptibility assessment. This study provides new theoretical guidance and technical support for further landslide hazard monitoring and prevention [ABSTRACT FROM AUTHOR]

The present paper argues that the standardised treatment of disaster research and practice perpetuates the production of systematic epistemic injustices against victims of disasters. On the one hand, disaster victims are often prevented from contributing with their opinions and knowledge to the processes of disaster mitigation and disaster conceptualisation. On the other hand, disaster victims tend to lack the hermeneutical resources to make sense of their experiences intelligibly, due to the existence of significant hermeneutical gaps in the hegemonic terminology on the matter. I argue that both forms of epistemic injustice, the testimonial and the hermeneutical, are sustained by an epistemic privilege between the Global North and the Global South in matters of disasters. The second group comprises what I categorise generally as 'disaster victims'. I identify two forms of structural prejudice that operate against disaster victims: one is the 'non-expert' prejudice, and the other is the colonial prejudice. Finally, because of the intercultural nature of disaster environments, I discuss the field of 'multicultural competencies' as a useful form of unveiling and counteracting the epistemic injustices contained in both disaster theory and practice. [ABSTRACT FROM AUTHOR]

On October 7, 2021, a magnitude 5.9 earthquake struck the Harnai (Baluchistan) region of Pakistan, causing several fatalities and injuries within the epicentral area. First-order tectonic deformation in this region is caused by the convergence of the Indian Plate with respect to the Eurasian Plate. The Katwaz Block hinders the motion of the Indian Plate, resulting in the formation of strike-slip faults. In this study, the P-wave first-motion polarity technique was used to determine the mainshock faulting style. Cyclic scanning of the polarity solutions was applied to determine the most suitable focal mechanism solution among the available solutions generated by the FOCMEC (focal mechanism) software. The nodal planes correspond to different faulting styles (i.e., thrust and strike-slip faulting). A nodal plane oriented in the NW-SE direction corresponded to a strike-slip mechanism, which was considered to be the fault plane. Tectonically, this earthquake was associated with the Harnai-Karahi strike-slip fault zone owing to the fault strike and direction of slip. The apparent stress drop, fault length, and moment magnitude of the Harnai earthquake were 35.4 bar, 6.1 km, and 5.9, respectively. A lower b-value for the Gutenberg-Richter law was observed prior to the earthquake. Higher α- than b-values (α > b) indicate that this earthquake was governed by large events as opposed to small-magnitude events. The Harnai sequence had a decay exponent close to unity, lasted for 145 days, and produced few aftershocks. The study will help the future hazard mitigation in the region. [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]

Copyright of Journal of Geomechanics is the property of Journal of Geomechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geomechanics is the property of Journal of Geomechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

In recent decades, the increasing frequency of urban fires, driven by urban functional enhancements and climate change, has posed a growing threat to metropolitan sustainability. This study investigates the temporal and spatial characteristics of fire incidents in Shanghai from 2019 to 2023. Using satellite fire point data and official government records, kernel density analysis and wavelet analysis were employed to analyze the time series and spatial distribution of fire data. Subsequently, eleven primary factors influencing urban fire occurrence were identified, encompassing probability, regional characteristics, and hazard sources. A combined methodology of subjective and objective weights with game theory was used to generate a fire risk assessment at a 1 × 1 km2 grid scale. Furthermore, the spatial distribution characteristics of the assessments were analyzed. The results reveal that the downtown area exhibits the highest intensity of urban fires in terms of spatial domain, with a decreasing intensity towards the suburbs. Temporally, fire frequency demonstrates significant periodicity at an 18a time scale, while clear seasonal fluctuations and periodicity are observed at a 16-22a time scale, with higher occurrences in spring and winter. The study identifies typical aggregation patterns of urban fires, with high-risk centers in downtown Shanghai. Considering the impact of climate change and human activities, high-risk areas may gradually expand to adjacent urban suburbs, presenting a concerning future scenario. By examining the dual attributes of "combustibles and fireproof space" within urban greening systems, this research offers recommendations for the future strategies of disaster prevention and mitigation of green systems in Shanghai. [ABSTRACT FROM AUTHOR]

A novel, practical, and computationally efficient probabilistic methodology for the stochastic generation of suites of fully non‐stationary artificial accelerograms is presented. The proposed methodology ensures that the produced ground motion suites match a given target spectral mean and target variability for the whole period range of interest. This is achieved by first producing an ensemble of random target spectra with the given mean and variability and then using them to generate artificial, target spectrum‐compatible, acceleration time‐histories with spectral representation techniques. Spectral correlation can also be assumed for the generated ground motion spectra. Based on the same backbone, two different formulations are proposed for generating spectrum‐compatible acceleration time‐histories of the non‐stationary kind. The distinction between these two variants lies in the techniques employed for modeling the temporal and spectral modulation, focusing on the site‐compatibility of the produced records. The first approach uses past‐recorded seismic accelerograms as seed records, and the second proposes and uses a new, probabilistic time‐frequency modulating function. The outcome of the proposed methodology is suites containing site‐compatible ground motion time‐histories whose spectral mean and variability match those obtained from any of the usually employed target spectra used in the earthquake engineering practice. An online tool implementing the proposed methodology is also freely provided. [ABSTRACT FROM AUTHOR]

Burn severity is fundamental to post‐fire impact assessment and emergency response. Vegetation Burn Severity (VBS) can be derived from satellite observations. However, Soil Burn Severity (SBS) assessment—critical for mitigating hydrologic and geologic hazards—requires costly and laborious field recalibration of VBS maps. Here, we develop a physics‐informed Machine Learning model capable of accurately estimating SBS while revealing the intricate relationships between soil and vegetation burn severities. Our SBS classification model uses VBS, as well as climatological, meteorological, ecological, geological, and topographical wildfire covariates. This model demonstrated an overall accuracy of 89% for out‐of‐sample test data. The model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. VBS had the largest control on SBS, followed by weather (e.g., wind, fire danger, temperature), climate (e.g., annual precipitation), topography (e.g., elevation), and soil characteristics (e.g., soil organic carbon content). The relative control of processes on SBS changes across regions. Our model revealed nuanced relationships between VBS and SBS; for example, a similar VBS with lower wind speeds—that is, higher fire residence time—translates to a higher SBS. This transferrable model develops reliable and timely SBS maps using satellite and publicly accessible data, providing science‐based insights for managers and diverse stakeholders. Plain Language Summary: Post‐fire impact assessment and hazard mitigation heavily relies on burn severity metrics. Vegetation burn severity (VBS)—most relevant for ecological impacts—can be remotely sensed, but soil burn severity (SBS)—most relevant for hydrological impacts—requires laborious field recalibration of VBS maps. Lack of near real‐time SBS information is currently a data gap. Climate change‐driven weather whiplash can narrow the time interval between large wildfires and the ensuing precipitation events, requiring tools for rapid and accurate assessment of SBS without the need for laborious field recalibration of satellite‐derived metrics. Here we developed a physic‐informed Machine Learning model that can accurately develop SBS maps using readily available data without the need for resource and time intensive field assessments of burn severity. Additionally, SBS maps are developed for only a small fraction (less than 0.1%) of all wildfires in the US. Our model can develop SBS maps for all satellite‐observed wildfires in the western US, and has the potential to accomplish this task globally with further training. Finally, our model exhibited scalability with additional data, and was able to extract universal functional relationships between vegetation and soil burn severities across the western US. Key Points: Soil burn severity (SBS) assessment is key for hydrological hazard mitigationVegetation burn severity (VBS) can be remotely sensed, SBS is measured in the fieldPhysics‐informed Machine Learning models to translate VBS to SBS are developed [ABSTRACT FROM AUTHOR]

Climate change causes frequent and severe disasters. A comprehensive assessment of disaster hazards is thus crucial to understanding variations in disaster patterns and planning mitigation and adaptation strategies. This study obtained information from a crop disaster dataset of Taiwan covering the period from 2003 to 2022. Additionally, principal component analysis and K-means clustering were used to create climate clusters to evaluate the effect of climate patterns on disaster hazards. The results revealed that tropical storm frequency substantially decreased, whereas rain disasters exhibited an increasing trend. The four regions of Taiwan exhibited variations in terms of hazards of various disasters. The cold wave hazard showed a significant upward trend in the central region. An upward trend of rain disaster hazards was only detected in the southern region. However, a downward trend in tropical storm hazards was detected across all regions. A distinct climate pattern was identified over the study period. After 2012, high temperature and dry climate were the primary climate patterns. These patterns exhibited a high hazard value for cold waves, droughts, and rain disasters. Hence, the present study's findings indicate that managing cold waves and rain disasters is crucial to protecting crop production in Taiwan. [ABSTRACT FROM AUTHOR]

Objective: To investigate the impact of extreme climate on geological disasters in Shanxi and propose effective disaster prevention and mitigation strategies. Methods: Using daily temperature and precipitation data from 27 meteorological stations in Shanxi Province from 1975 to 2020, 32 extreme climate indices were calculated. Combined with geological disaster site data, the distribution characteristics of extreme climates and their relationship with geological disasters were analyzed, and a regression model for geological disaster risk zones was constructed. Results: Sixteen extreme climate indices in Shanxi Province showed significant changes, especially TMAXmean (100% significant). Indices related to negative precipitation effects showed a declining trend, with 77.78% being significant, while 96.3% of positive temperature effect indices showed an increasing trend, with 73.6% being significant. Geological disaster hotspots were concentrated in the mid-altitude (500–1500 m) hilly and low mountain areas along the central north–south axis and on Q and Pz strata. Extreme high-temperature indices were significantly positively correlated with geological disaster hotspots, while extreme low-temperature indices were negatively correlated. Indices related to extreme heavy precipitation (e.g., R99p.Slope, RX5day.Slope) were associated with an increase in geological disaster hotspots, whereas higher total precipitation and frequent heavy precipitation events were associated with a decrease in disaster hotspots. The grey relational degree between the Z-score and TXn.Slope, TXx.Slope, GSL.Slope, and TX90P.Slope was greater than 0.8. The random forest model performed best in evaluation metrics such as MAE, RMSE, and R2. Conclusions: Shanxi is likely to experience more extreme high-temperature and precipitation events in the future. The low-altitude hilly and terraced areas in Zones III and VII are key regions for geological disaster prevention and control. High temperatures and extreme rainfall events generally increase the disaster risk, while higher total precipitation reduces it. The random forest model is the optimal tool for predicting geological disaster risks in Shanxi Province. [ABSTRACT FROM AUTHOR]

This study addresses the pressing need for flood extent and exposure information in data-scarce and vulnerable regions, with a specific focus on West Africa, particularly Senegal. Leveraging the Google Earth Engine (GEE) platform and integrating data from the Sentinel-1 SAR, Global Surface Water, HydroSHEDS, the Global Human Settlement Layer, and MODIS land cover type, our primary objective is to delineate the extent of flooding and compare this with flooding for a one-in-a-hundred-year flood event, offering a comprehensive assessment of exposure during the period from July to October 2022 across Senegal's 14 regions. The findings underscore a total inundation area of 2951 square kilometers, impacting 782,681 people, 238 square kilometers of urbanized area, and 21 square kilometers of farmland. Notably, August witnessed the largest flood extent, reaching 780 square kilometers, accounting for 0.40% of the country's land area. Other regions, including Saint-Louis, Ziguinchor, Fatick, and Matam, experienced varying extents of flooding, with the data for August showing a 1.34% overlap with flooding for a one-in-a-hundred-year flood event derived from hydrological and hydraulic modeling. This low percentage reveals the distinct purpose and nature of the two approaches (remote sensing and modeling), as well as their complementarity. In terms of flood exposure, October emerges as the most critical month, affecting 281,406 people (1.56% of the population). The Dakar, Diourbel, Thiès, and Saint-Louis regions bore substantial impacts, affecting 437,025; 171,537; 115,552; and 77,501 people, respectively. These findings emphasize the imperative for comprehensive disaster preparation and mitigation efforts. This study provides a crucial national-scale perspective to guide Senegal's authorities in formulating effective flood management, intervention, and adaptation strategies. [ABSTRACT FROM AUTHOR]