Search

Post-disaster humanitarian relief logistics focuses on managing the supply and shipment of relief items. Owing to the complexity arising from the hierarchical decision relationship and the uncertainties of demand and transportation, it is challenging to develop an effective humanitarian relief logistics network (HRLN). A globalized robust bi-level multi-objective HRLN model involving uncertainties in transportation time, transportation cost and demand is developed to address this problem, in which an upper-level decision-maker focuses on the allocation problem and a lower-level decision-maker considers the supply problem. For tractability, the goal programming approach is employed to trade off conflicting timeliness, satisfaction and operational cost objectives. The proposed globalized robust bi-level HRLN model is reformulated as its globalized robust counterpart formulations under two different perturbation structures. The primal–dual approach is adopted to transform the bi-level models into equivalent mixed-integer conic programs. A case study concerning an Iranian earthquake is conducted to prove the performance of the proposed model. Globalized robust models are more flexible and able to immunize against uncertainty by comparison with traditional robust optimization and deterministic solutions. The managerial insights of using the globalized robust bi-level optimization approach are reported for disaster response management. The design of an emergency aviation network to circumvent the effects of COVID-19 could be considered in future research. [ABSTRACT FROM AUTHOR]

Objectives: In order to improve the efficiency of landslide extraction and explore the spatial-tem‐ poral distribution characteristics of regional landslides and single landslide, a rapid landslide extraction model is designed to provide a scientific basis for landslide disaster prevention and management. Methods: Based on multi-temporal domestic high-resolution remote sensing satellite images, advanced land observing satellite 12.5 m digital elevation model, and historical landslide hidden danger points, this study selected 8 landslide-prone townships located in the northwest of Fengjie County, Chongqing city,China to form the study area. Feature optimization based on SHAP in terpretation framework and Bayesian hyperparameter auto‐ matic optimization based on Optuna framework are introduced into XGBoost algorithm to construct and optimize the landslide extraction model. The study realized rapid extraction of landslide spatial information and quantitative analysis of landslide spatialtemporal distribution in 2013, 2015, 2018 and 2020. Results: In the comparison of models accuracy, precision, Kappa coefficient and area under curve value of landslide extraction model constructed by optimized XGBoost basic algorithm are 96.26%, 90.91%, 0.860 2 and 0.970 5, respectively, which higher than GBDT, LightGBM and Adaboost. Conclusions: From 2013 to 2020, the overall development degree of landslides in the study area is relatively high, and the spatial distri‐ bution of landslides is uneven among villages and towns, and the landslides is distributed on both sides of the river valley and the river, showing the characteristics of regional concentration. From 2013 to 2020, Miaowan landslide has high development intensity, strong activity, repeated resurrection phenomenon and induced new landslides. The slope of the landslide is about 25°-45°, and it’ s topographic characteristics change little, significant changes mainly focus on color, texture, geometry and vegetation coverage. [ABSTRACT FROM AUTHOR]

Objectives: The construction of effective path set is the key link of traffic control and guidance of highway network, and plays an important role in post disaster path planning. Usually when a disaster occurs, there is a problem that the current emergency route planning does not incorporate the dynamic changes of disasters in time, which affects the subsequent emergency evacuation and rescue and relief. Methods: To solve this problem, a double-layer road network model is proposed, which couples the topological structure of the highway network with the traffic flow and the state of disasters and events. The linear reference and dynamic segmentation technology is introduced to associate the routes and events and the depth first search algorithm is improved based on Dijkstra algorithm. Results: (1) Double-layer road network model reflects the topological relationship between road sections, stores the dynamic attribute information of road sections and realizes the search and construction of effective path sets. (2) Improved DFS algorithm reduces the computational complexity and proposes an effective path search algorithm combining with time-varying road network, disasters and traffic conditions. Conclusions: The example application and verification in the study area shows that the method can dynamically search the effective path set according to time-varying traffic conditions and disasters. This model enhances the expression and analysis ability of road data, and is able to serve traffic analysis and control under the change of disaster situation, and is suitable for the post disaster traffic operation situation assessment of road network. [ABSTRACT FROM AUTHOR]

If progress is to be made toward improving geohazard management and emergency decision-making, then lessons need to be learned from past geohazard information. A geologic hazard report provides a useful and reliable source of information about the occurrence of an event, along with detailed information about the condition or factors of the geohazard. Analyzing such reports, however, can be a challenging process because these texts are often presented in unstructured long text formats, and contain rich specialized and detailed information. Automatically text classification is commonly used to mine disaster text data in open domains (e.g., news and microblogs). But it has limitations to performing contextual long-distance dependencies and is insensitive to discourse order. These deficiencies are most obviously exposed in long text fields. Therefore, this paper uses the bidirectional encoder representations from Transformers (BERT), to model long text. Then, utilizing a softmax layer to automatically extract text features and classify geohazards without manual features. The latent Dirichlet allocation (LDA) model is used to examine the interdependencies that exist between causal variables to visualize geohazards. The proposed method is useful in enabling the machine-assisted interpretation of text-based geohazards. Moreover, it can help users visualize causes, processes, and other geohazards and assist decision-makers in emergency responses. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the spatial and temporal characteristics of drought risk in the central arid zone of Ningxia, and to provide scientific basis for agricultural production, agricultural disaster prevention and control, planting structure adjustment and agricultural irrigation guidance in the central arid zone of Ningxia. [Method] The meteorological observation data of the five meteorological stations including Shapotou, Zhongning County, Tongxin County, Yanchi County, and Haiyuan County in the middle arid zone of Ningxia were collected, and the temporal and spatial variations of drought levels and the spatial-temporal evolution characteristics of drought risk over the past 39 years (1981—2019) was analyzed and evaluated by calculating the Standardized Precipitation Index (SPI) and combining with GIS technology. [Results] The SPI12 results revealed a fluctuating trend with an intensifying tendency in decennial droughts (the slope of the trend line ranged from-0.004 to 0.003). The SPI3 results demonstrated a significant spatial heterogeneity in the spatial-temporal distribution of seasonal drought risk featured with a prominent characteristics of a low risk in the south and high risk in the north at spatial scales, and continuous drought at temporal scales. The frequencies of drought in spring and winter exceeded 45%. However, the occurrence of drought in summer and autumn was not significant, with a frequency ranging from 10.26% to 43.59%. The evaluation of the temporal and spatial evolution characteristics of drought risk revealed a fluctuating trend of decennial drought risk, initially decreased and then increased. There were remarkable differences in the spatial-temporal distribution of seasonal drought risk, with a characteristic of increasing risk from south to north spatially and higher risk in spring and winter temporally but lower risk in summer and autumn. [Conclusion] The spatial and temporal heterogeneity of seasonal-scale drought risk in the central arid zone of Ningxia is obvious, with high drought risk in Shapotou District and Zhongning County, and drought prevention and control should be strengthened in the future for the spring, fall and winter seasons. [ABSTRACT FROM AUTHOR]

The presented evidence-based clinical practice guideline (CPG) is proposed as a National CPG where we adapted the international recommendations for the emergency management of seizures in children beyond the neonatal period to suit the health care in Egypt. The quality of evidence and the strength of recommendations are indicated. This study aimed to standardize the treatment of acute epileptic seizures and to provide an easy-to-apply acute treatment protocol that will allow immediate and appropriate seizure control. This is part of a larger program by the Egyptian Pediatric Clinical Practice Guidelines Committee (EPG) in collaboration with the staff of pediatric departments of 15 Egyptian universities and the National Research Centre. EPG was affiliated later to the Supreme Council of the Egyptian University Hospitals aiming to define the topics of, assign authors to, and assist in the adaptation of pediatric evidence-based CPGs according to a national strategic plan (http://epg.edu.eg). The committee is guided by a formal CPG adaptation methodology: the "Adapted ADAPTE." The Egyptian Childhood Seizure Group (ECSG) reviewed the results of the Appraisal of Guidelines for Research and Evaluation II assessment and decided to adapt the recommendations of three source CPGs: American Epilepsy Society, Italian League Against Epilepsy, Neurocritical Care Society, and Neurologic & Psychiatric Society of Zambia. Eight implementation tools were included. A comprehensive set of multifaceted CPG implementation strategies was provided for the clinicians, patients, nurses, and other relevant stakeholders contextualized to the national settings. Our experience with this adaptation methodology provides useful insight into its national utilization in Egypt. [ABSTRACT FROM AUTHOR]

Pre-hospital emergency medical service (PHEMS) is critical for the treatment outcomes of life-threatening injuries and time-sensitive illnesses. Response time, influenced by traffic conditions and the site planning of pre-hospital emergency medical facilities (PHEMFs), is the main indicator for evaluating PHEMS. In 2020, the Beijing government released the "Special Plan for Spatial Layout of Pre-hospital Emergency Medical Facilities in Beijing (2020–2022)". This paper evaluates the functional efficiency and spatial equity of this plan within Beijing's central six districts using isochrone measures to assess the accessibility of the planned PHEMFs. The isochrone coverages of the area and population were calculated, and the temporal-spatial characteristics of isochrones were concluded. The analysis revealed that while the current planning meets several objectives, challenges in service availability and equity persist. Although 10-min isochrone coverage was high, 8-min coverage was insufficient, particularly during peak hours. This highlights gaps in service accessibility that necessitate additional emergency stations in underserved areas. The current planning approach leads to significant overlap at administrative boundaries, causing service oversupply and increased costs, which calls for a city-wide planning perspective that breaks administrative boundaries to optimize resource allocation. Traffic conditions significantly impact service coverage, with congestion reducing coverage in central areas and better coverage near traffic hubs. Future planning should strategically place stations based on traffic patterns and population distribution to enhance emergency medical service accessibility and equity in urban areas. [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]

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island. [ABSTRACT FROM AUTHOR]

Few studies have reported nationwide changes in dental visit patterns during the COVID-19 pandemic. This study aimed to clarify the impact of the COVID-19 pandemic on the type of dental treatment in Japan based on trends in the frequency of dental clinic visits per month and dental expenses per month or day. An interrupted time-series analysis was performed to examine changes in data from the national database before and after the first declaration of a state of emergency. Between March and April 2020, the monthly dental expenses per patient (MDEPP) increased by approximately JPY 950 (JPY) (p < 0.001) in patients aged ≤64 years and ≥65 years. Dental expenses per treatment (DEPT) increased by approximately JPY 300–400 (p < 0.001) in both age groups. After April 2020, the slope of the regression line for DEPT significantly increased in those aged ≤64 years (p < 0.001) and in those ≥65 years (p = 0.024). The number of treatments per month (NTPM) increased after the declaration of a state of emergency. However, the decreasing trend in the regression line for NTPM was stronger in those aged ≤64 years (p < 0.001). The MDEPP, DEPT, and NTPM showed an increasing trend during the first state of emergency compared to those observed in the previous year. The proportion of patients with relatively severe disease may have increased because patients with mild disease refrained from undergoing dental examinations. These results suggest changes in the type of dental treatment during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Increasing levels of urbanisation and the rapid growth of modern cities require that particular attention be paid to ensuring the safety and protection of living conditions for their inhabitants. In this context, natural and human-induced disasters pose a major threat to the safety and normal operational procedures of buildings and infrastructures. In consequence, disaster management and built assets operations demand modern tools to be effectively prepared in order to better respond to such critical events. This study explores the potential of artificial intelligence in these operational fields by developing a deep learning model that is able to provide a rapid assessment of an asset's structural condition in the case of a seismic excitation. The proposed simulation model makes an accurate prediction of the damage status of individual elements in a built asset, thus leading to operational improvements across all disaster management phases. In addition, the above development integrates the deep learning algorithm into building information modelling and then uploads the graphical information to a web dashboard. By following the framework proposed, an integrative model is designed that provides a visual and user-friendly interface that allows different stakeholders to navigate and comprehend essential information on the effects of a disaster; thus enabling quicker decision making and strengthening operational resilience in critical events. [ABSTRACT FROM AUTHOR]

What are the consequential socio‐spatial vulnerabilities of fragmentation in flood risk governance (FRG) functions in Tana River County, Kenya? To answer the question, this paper utilises social differentiation theory to establish types and consequences of such fragmentation. It applies theoretical patterns and processes of social differentiation to expose that FRG diversification could result in fragmentation of FRG functions. The study employs an interview strategy that focuses on governmental and non‐governmental FRG actors. The results reveal that fragmented FRG functions in Tana River County was not an intentional policy decision, but rather a product of a transitional vacuum between policy promulgation and implementation. Furthermore, socio‐spatial vulnerabilities differentiated by patterns and processes related to age, gender, disability, and ethnicity, for instance, are consequential outcomes of fragmented FRG functions in the Tana River floodplains. The study recommends implementation of the National Disaster Management Policy in Tana River County and institutionalisation of a specific FRG policy and legal framework. [ABSTRACT FROM AUTHOR]

Landslides triggered by extreme rainfall events often cause losses of life, property damage, and environmental alterations. While past studies have assessed landslide hazards using various indices, how to select rainfall indices in rainfall-induced landslide hazard assessment is still a challenge due to the spatiotemporal asymmetry of rainfall indices. In this study, we employed three machine-learning models, namely the Random forest (RF), Support vector machine (SVM), and logistics regression models, and developed an extreme rainfall index-based model to evaluate rainfall-induced landslide hazards. To eliminate the effect of spatiotemporal asymmetry in indices, we selected six extreme rainfall indices that are highly correlated with rainfall-induced landslides and tested 63 combinations. Over the past four decades, extreme rainfall events have become more frequent and intense. Both the number and type of rainfall indices affected the assessment results of landslides in the study area. The RF model showed a better accuracy in landslide hazard assessments than did the other two models. To better predict rainfall-induced landslide hazards, an optimal model based on three extreme rainfall indices, i.e., PSSPTOT, R25mm, and Rx5day, was proposed for the study area. With climate change, the study area may encounter more intense rainfall events and experience high levels of rainfall-induced landslide hazards. Compared to the baseline, landslide hazards in the study area are projected to increase by 9.9% and 11.9% in the 2030s (2021–2050). Areas with high- and very high- levels of landslide hazards will account for more than 50% of the study area and will be mainly distributed in the central and eastern parts of the study area. This study suggested an optimal combination of extreme precipitation indicies and provided scientific information about rainfall-induced landslide hazard management under climate change. [ABSTRACT FROM AUTHOR]

This study conducts a comprehensive analysis of the influence of tropical cyclones on precipitation variations in Indochina, examining Vietnam, Laos, and Cambodia, while exploring their connection with evolving climatic variables. Covering a span of four decades (1979–2021) and integrating daily precipitation records with climatic datasets, the research elucidates tropical cyclone's contributions to the annual precipitation across distinct regions, revealing percentages of 27%, 16%, and 6% in Vietnam, Laos, and Cambodia, respectively. Spatial distribution mapping highlights concentrated intensities in central Vietnam, central Laos, and southern Cambodia. Additionally, an upward trend in Vietnam's precipitation, as a representative measure of the entire region, is observed over the study duration, while its variability exhibits marginal correlations with inter-annual and decadal-scale climatic indices. The upward trend aligns with increased precipitable water over Indochina and open oceans, increased sea surface temperatures, reinforced atmospheric low-pressure systems, and intensified westerly wind patterns post-2000. These findings underscore the complex interplay between climate variables and Indochina's precipitation dynamics, suggesting implications for disaster management and strategies to adapt to climate change. [ABSTRACT FROM AUTHOR]

Droughts pose serious threats to the agricultural sector, especially in rainfed-dominated agricultural regions like those in Argentina's Humid Pampas. This region was recently impacted by slow-evolving and long-lasting droughts as well as by flash droughts, resulting in losses reaching thousands of millions of US dollars. Improvements of drought early warning systems are essential, particularly given the projected increase in drought frequency and severity over southern South America. The spatial and temporal relationship between precipitation deficits, soil moisture and vegetation health anomalies are crucial for better understanding and representation of the agricultural droughts and their impacts. In this context, the Combined Drought Indicator (CDI) considers the causal and time-lagged relationship of these three variables. The study's objective is twofold: (1) Analyze the time-lagged response between precipitation deficits, soil moisture and satellite fAPAR anomalies; and (2) Evaluate the CDI's capability to characterize the severity of drought events on the Humid Pampas against agricultural yield estimations and simulations, as well as agricultural emergency declarations. The correlation among the variables shows strong spatial variability. The highest Pearson correlation values (r > 0.42) are observed over parts of the Humid Pampas for time lags of 0, 10, and 20 days between the variables. Although the CDI has limitations, such as its coarse spatial resolution and monthly temporal resolution of precipitation data, it effectively tracks the progression of major drought events in the region. The CDI's performance aligns well with estimations and simulations of soybean and corn yields, as well as official declarations of agricultural emergencies. Insights from this study also provide a basis for discussing potential improvements to the CDI. This study highlights the global and regional significance of evaluating and enhancing the CDI for effective drought monitoring, emphasizing the role of collaborative efforts for future advancements in drought early warning systems. [ABSTRACT FROM AUTHOR]

The impacts of climate change are accelerating worldwide, but emergency agencies and political bodies are not always equipped to anticipate where, when, or how severe the next unnatural disaster will be. Amid megafire seasons, for example, scientists are revising models of fire behavior that were calibrated to natures that increasingly diverge from known baselines and trends. Emergency responders' trust in patterns has become an occupational hazard. At these edges of knowledge, struggles to maintain responsive capacity in disrupted ecologies are at play; a larger reckoning with runaway climate change as a relational problem space is in order. Rather than making me resort to despair about the world's "end," such labors redirect my attention toward horizons of expectation in which knowledges are still actionable, not obsolete, and where capacities for future interventions are viable and not denied. These activities, enmeshed in a rubric of horizon work, shift expert authority and promote critical realignments across political, activist, and Indigenous spheres. [ABSTRACT FROM AUTHOR]

The establishment of acceptable risk standards serves as a crucial connection between earthquake disaster risk assessment and risk management. Currently, there lacks a standardized criterion for determining the acceptable level of risk pertaining to earthquake disasters. To establish a standardized system of acceptable risk of earthquake disaster, the data of disaster-affected toll, death toll, and direct economic losses resulting from earthquakes disaster with MS ≥ 5.0 in Chinese Mainland between 1991 and 2020 are utilized. These data are employed to construct the acceptable life risk F–N curve (the accumulated probability F of annual death toll ≥ N—death toll N), the acceptable economic risk F–D curve (the accumulated probability F of annual direct economic losses ≥ D—direct economic losses), and the acceptable comprehensive risk F–L curve (the accumulated probability F with earthquake occurrence of annual disaster degree ≥ L—disaster degree). Then, the acceptable risk level of earthquake disasters with MS5.0–5.9, MS6.0–6.9, MS ≥ 7.0, and MS ≥ 5.0 are determined. Moreover, the classification and consistency of acceptable types of earthquake disaster comprehensive risk, life risk and economic risk in the past 30 years are compared. Through analysis, the acceptable life risk, acceptable economic risk, and acceptable comprehensive risk criteria of earthquake disasters with MS5.0–5.9, MS6.0–6.9, MS ≥ 7.0, and MS ≥ 5.0 in Chinese Mainland are obtained. It is found that the comprehensive risk of earthquake disasters with different magnitudes is mainly at an unacceptable level, while the main types that are consistent with life risk and economic risk are tolerable level and acceptable level, respectively. The research results can provide more comprehensive theoretical data and practical basis for the effective implementation of earthquake disaster risk management. [ABSTRACT FROM AUTHOR]

This study provided a comprehensive understanding of the source process of the 1819 M 7.7 Kachchh Indian earthquake using physics‐based dynamic rupture modeling and strong ground motion simulations. We successfully simulated the spontaneous dynamic rupture along a curved non‐planar fault using the 3‐D curved‐grid finite‐difference method (CGFDM). The estimated earthquake magnitude is around 7.6, consistent with previous estimations. Our simulations accurately replicated macroscopic rupture patterns and surface deformation, showing agreement with observed data along the Allah Bund fault (ABF) with a maximum displacement ∼5.5 m at the Earth's surface. The maximum modeled coseismic slip on the fault was approximately 7.5 m. Notably, the ABF exhibited characteristics of a weak barrier (leaky barrier) at the bending part, allowing the rupture to propagate further. Despite limitations in surface deformation calculations, the modeled values aligned with the trend of surface fault slip, with a slight deviation in the epicenter toward the east compared to earlier studies. We observed a homogeneous principal stress oriented N25°E, consistent with the present day Indian plate motion. The estimated horizontal peak ground velocities (PGVh) and the maximum value of Intensity X+ aligns well with observations. Furthermore, conducting thorough case studies on significant earthquakes and potential seismic scenarios in stable continental regions is crucial. Such studies play a vital role in validating and improving dynamic rupture models. When combined with statistical methods, this research holds great promise for advancing seismic hazard assessments, earthquake engineering, and strategies for disaster management. Plain Language Summary: This paper is centered around the simulation of the dynamic rupture of the 1819 M 7.7 Kachchh earthquake in India. We have successfully replicated the earthquake's behavior using a three‐dimensional simulation method. The study's results demonstrate the significant influence of the local tectonic setting and non‐planar fault structure on earthquake generation and rupture progression. Although slight discrepancies exist between the simulation results and actual observations, the simulations capture significant trends and reproduce macroscopic rupture patterns. The estimated magnitude of the earthquake aligns well with previous studies. The study highlights the role of fault bending and its impact on surface deformation, contributing to a better understanding of seismic hazards and providing insights for seismic hazard assessments and earthquake source characterization. This work is valuable for comprehending earthquake sources, particularly from earthquake perspectives in the SCR region and other areas. Key Points: Dynamic rupture simulations of the 1819 Kachchh M 7.7 earthquake replicate co‐seismic fault slip, enhance our knowledge of the earthquake sourceWeak barrier characteristics observed at the bending part of the fault enabled further rupturing, influenced by SH and the nucleation pointContributes to understanding earthquake hazards, enhancing seismic assessment, engineering, and disaster management strategies [ABSTRACT FROM AUTHOR]

The abnormal deformation of urban surfaces threatens the human living environment, and extreme regional weather can affect the response law of surface deformation. To explore the changes in surface time series response after extreme weather and the causes of deformation in Zhengzhou, the MTInSAR was used to obtain the surface deformation from 2020 to 2022, and the time series changes of groundwater equivalent water height were retrieved by GRACE. The results show that: (a) There are three large subsidence bowls in Zhengzhou, and the maximum subsidence rate is −40.2 mm/yr. (b) The extreme rainstorm in Zhengzhou alleviated the surface deformation quickly, lasting approximately 6 months. However, surface subsidence still occurred after the extreme rainstorm. The water storage coefficient of the elastic skeleton in the Zhengzhou area showed an increasing trend. (c) Precipitation can lead to surface uplift by influencing the change of groundwater level. There is a delay time of 0.75–1 month between groundwater level change and surface uplift response in the characteristic region. These results provide scientific data support and causal analysis for disaster prevention and reduction of abnormal deformation in Zhengzhou. Key Points: Impact of extreme rainstorm on surface in Zhengzhou from 2020 to 2022There are three subsidence bowls in Zhengzhou area, and the uneven deformation is obviousExtreme rainstorm weather can alleviate the occurrence of surface subsidence in short term [ABSTRACT FROM AUTHOR]

Coalbed methane (CBM) content is a crucial parameter for CBM exploitation and disaster prevention, with accurate gas loss calculation being essential for improving measurement precision. To investigate the physical response to gas loss and quantify the impact and interrelation of various factors, this study developed a comprehensive model incorporating the effects of gas diffusion, temperature, and pressure effects on porosity and coal deformation. By utilizing the OpenFOAM platform and C++ for numerical solution development and establishing an experimental system for gas loss measurement, the model's reliability was confirmed. The new model demonstrates an 8.56% average error, representing a significant improvement over traditional methods, with error reductions of 26.59% and 18.31% compared to the square root of time and power function methods, respectively. The hierarchy of gas loss is determined to be gas flow > gas-coal deformation coupling > gas-temperature coupling > gas-coal deformation-temperature coupling. Average diffusion contributions are identified as 41.43% from surface diffusion, 30.71% from Knudsen diffusion, and 27.86% from viscous flow. The factors affecting gas loss, in decreasing order of impact, are adsorption equilibrium pressure, temperature, porosity, moisture, and adsorption constants. These findings provide theoretical support for enhancing gas content measurement accuracy and techniques, significantly benefiting CBM extraction and mine safety. [ABSTRACT FROM AUTHOR]

After a check dam is filled with sediment, the debris flow will flow out from the spillway. Insufficient discharge capacity of the spillway can lead to debris flow scouring the dam's shoulder and foundation. Therefore, it is necessary to study the discharge capacity of the spillway. It is of great importance for further optimizing the structural design of the check dam. This article analyzes discharge characteristics of debris flow of a spillway through a series of flume experiments. According to the motion states, it can be divided into five stages: contact stage of the spillway, flushing and climbing stage, increasing and reflux stage, stable discharge stage, and final discharge stage. We analyzed the influencing factors of the discharge capacity, including the type of spillway, bulk density of debris flow, scale of debris flow, flume gradient, and effective opening width of the spillway. Furthermore, we derived a calculation formula of discharge for the spillway based on Bernoulli's principle. Finally, we considered the influence of the ratio of flow area and Froude number to the discharge coefficient and established a calculation method of discharge. Consequently, we compared the calculated results with the measured results and found them to be in good agreement. Our research results provide a quantitative calculation method for the design of spillways and energy dissipation and erosion prevention projects under check dams, which is beneficial for improving engineering value and for better serving disaster prevention and reduction efforts. [ABSTRACT FROM AUTHOR]

[Display omitted] • MCTracker integrates motion correlation and mix-scale feature enhancement to track small, dense, and blurry objects effectively. • CDFE, IFMCM, and MSEB structures enhance contrast encoding, motion correlation, and multi-scale feature integration. • STFM resolves temporal-spatial fusion inconsistencies, boosting fusion expressive capability for temporal-spatial features. The video data captured by satellites, colloquially referred to as "gazing," holds significant value for analyzing object status and dynamically tracking movements. Such data and their associated applications play pivotal roles in disaster response, urban traffic monitoring, national defense, and security operations. The multi-object tracking task in satellite video surveillance is inherently more complex than single-object tracking, presenting challenges such as tracking dense small objects and limited capability in multi-object tracking in ambiguous environments. This study proposes a satellite video multi-object tracking (MCTracker) method that considers inter-frame motion correlation and multi-scale cascaded feature enhancement, achieving outstanding performance in multi-object tracking tasks. This study builds upon a differentially encoded backbone network incorporating both global and local information, proposing an Inter-frame Motion Correlation Module (IFMCM) to enhance inter-frame dynamic continuity. A Mixed-scale Enhancement Block (MSEB) is designed to address the challenge of detecting and tracking small objects under multiscale effects. Additionally, a Spatio-temporal Fusion Module (STFM) is introduced to improve the feature fusion representation capability among modules. Through experiments conducted on two open-source datasets, AIR-MOT and SAT-MTB, it has been demonstrated that the proposed MCTracker exhibits efficient synergistic consistency in detection and ReID tasks. On the AIR-MOT dataset, the object tracking accuracy, as measured by MOTA, reaches 59.4 %, achieving optimal performance. In the SAT-MTB dataset's four-class multiple object tracking task, particularly in tracking small-scale objects such as cars and ships, the proposed method demonstrates comprehensive optimal performance, yielding robust tracking results. The satellite video-based multiple object tracking approach proposed in this study holds significant reference value for further exploration of object motion states and trajectory tracking. [ABSTRACT FROM AUTHOR]

Rain‐triggered landslides cause significant socioeconomic loss and long‐term ecological impact, disrupting topsoil and seed banks and creating unfavourable conditions for vegetation establishment. Although hazard management effectively reduces landslide risk, most management plans primarily focus on the societal impacts (loss of property and human lives), while environmental impacts related to landslide occurrence and recurrence are often overlooked. The role of different vegetation types in mitigation strategies remains uncertain due to the time and spatial constraints of traditional field study methods. Therefore, the role of vegetation in landslide restoration should be reconsidered. In this study, we investigated post‐landslide vegetation recovery patterns, analysed the duration of vegetation recovery, identified factors influencing these patterns, examined the role of forests in occurrence and recurrence probability and explored the implications of these findings for each element within an integrated management framework for landslide restoration. We utilised long‐term landslide inventory data (1924–2018) covering the entire city of Hong Kong (~1100 km2) and combined it with structural data derived from airborne LiDAR scanning in 2020 to capture landslide recovery. Our findings revealed significant differences in recovery trajectories between the main bodies and foot areas of scars, with the former taking approximately 46 years to recover and the latter recovering in about 38 years. Scar age, average wind speed, elevation and proximity to the forest were identified as key factors influencing structural recovery on scars, while the proximity to forest also regulated recovery rate of scars. We observed decreased landslide occurrence in forested areas, with recurrent landslides primarily appearing on older, unrecovered scars on barren hillsides. Synthesis and applications: Our research highlights the dynamic patterns, recovery time and drivers of vegetation recovery on landslide scars; and the higher probability of landslide occurrence in non‐forest areas and increased recurrence on bare, low vegetated scars. This information provides valuable insights for informing restoration efforts and managing landslide‐prone areas. Such knowledge is crucial for developing effective mitigation strategies and enhancing the resilience of vulnerable ecosystems facing climate change and increased frequency of extreme weather events. [ABSTRACT FROM AUTHOR]

The promotion of community resilience is a multifaceted process that warrants further exploration. This article aims to contribute to this literature stream by assessing the role of citizen science (CS) approaches in the development of community resilience, since CS is considered a promising approach for generating new knowledge by fostering the participation of citizens (non-professional scientists) in research activities. The results show that CS approaches can contribute to community resilience at the institutional level, improving emergency and recovery planning capacity; at the infrastructural level, by contributing to land use planning and urban design; and at the social level, through the creation of community ties and social capital. This contribution is relevant for the development of public policies that are more shaped to local contexts and aligned with communities' needs and expectations. [ABSTRACT FROM AUTHOR]

[Display omitted] • Fusion of varied data sources are used to develop more informed flood extent maps. • SVM outscored the MLE, RF, Iso cluster, and Otsu's algorithms in all strategies. • PCA-based technique outperforms the other three approaches. • First and Second approaches performed better in VV than VH polarisation. Accurate and timely mapping of flood extent is crucial for effective disaster response and management. However, existing methods often face challenges in integrating diverse data sources and leveraging advanced techniques for precise inundation mapping. This research aimed to address this gap by proposing and evaluating four different methods for improving flood extent mapping in Sindh, Pakistan, by integrating various data sources, including precipitation, Synthetic Aperture Radar (SAR), buildings, population, and optical data. The first strategy involves categorizing post-flood SAR data immediately using non-parametric (Support Vector Machine (SVM) and Random Forest (RF)), parametric (Maximum Likelihood Estimation (MLE)), and cluster (ISO) algorithms for Vertical transmit and Vertical received (VV) and Vertical transmit and Horizontal received (VH) polarisations. The second method relies on Otsu's method for automatic thresholding on post-flood event VH and VV data. The third approach utilizes both pre- and post-flood event data by creating a stack of Pre-event VH, Pre-event VV, Post-event VH, and Post-event VV data, which is then classified using the SVM, RF, MLE, and ISO algorithms. Lastly, the fourth method employs the stack of Principal Component Analysis (PCA) bands, consisting of PCA components 1, 2, and 3, to categorize data for flooding using the SVM, RF, MLE, and ISO algorithms. The rationale behind evaluating these diverse methods was to identify the most effective approach for accurately mapping flood extent by exploiting the strengths of different algorithms and data processing techniques. The accuracy and precision of these approaches were rigorously evaluated using Landsat-9 Normalized Difference Water Index (NDWI) as a reference dataset, along with error matrix and compound value (C v) metrics. The findings show that a PCA-based technique with SVM is marginally superior (based on the overall accuracy and Kappa coefficient with a value of 92.20 % and kappa coefficient 0.821) than the other approaches tested in the study. By reducing the dimensionality of the dataset while preserving relevant information, PCA offers a computationally efficient approach to flood extent mapping. Among all the approaches, the collective performance of the algorithms was computed using the C v metric. The SVM algorithm with a C v of 1.25 demonstrated the best performance, followed by the RF algorithm with C v of 1.5, and the MLE algorithm with C v of 2.5. The worst performing algorithm among all is found to be ISO with C v of 4. It comes into view that first and second approach underperformed in VH polarisation compared to the VV polarisation and provide a more accurate representation of flooded area in VV polarisation. The flood extent with highest accuracy, together with the world's gridded population, latest Microsoft's Global ML Building Footprints, and OpenStreetMap building data are used in conjunction to estimate the number of people and buildings at risk within the study area. [ABSTRACT FROM AUTHOR]

Background/Aims: Athletic trainers are often the point person when sports‐related traumatic dental injuries (TDIs) occur. The aim of this study was to assess knowledge levels of the management of TDIs among athletic trainers in the Midwest United States, as well as evaluate variables that may influence knowledge levels. Material and Methods: A survey was sent to athletic trainers licensed in Minnesota, Nebraska, and Iowa. The survey included 28 multiple‐choice and fill in the blank questions split into three sections. The three sections included background, emergency management of TDIs, and opinion questions. Results: Of the participants, 100% recalled receiving medical first aid training. However, only 71% recalled receiving formal training on emergency management of dental injuries. Although 75% were confident in managing a dental injury, over 63% of participants scored less than 70% in the knowledge score section. Majority of the participants (98.4%) reported that they believe training on the management of TDIs is important. Athletic trainers working with contact sports were more likely to have experienced managing TDIs more recently than those working in noncontact sports. Conclusions: This study shows the gaps in knowledge among athletic trainers pertaining to management of TDIs and emphasizes the importance of sports community having adequate education on emergency management of such dental injuries. [ABSTRACT FROM AUTHOR]

Introduction: The management of pain following a burn is extremely complex because of the multifactorial nature of burn pain (nociceptive and neuropathic). In the pre-hospital setting and emergency department (ED), the main goal of acute pain management is to reduce the patient's pain, allowing them to maintain function and to prevent the chronification of pain. Opioids are used as first-line treatment in management of burn pain. The aim of our study was to evaluate the efficacy and adverse effects of intravenous (IV) morphine for burn pain management in the ED and to evaluate pain management in the pre-hospital setting. Methods: In this single-center observational study, patients presenting with second- and third-degree burns were enrolled in our ED. Numerical Rating Scale (NRS) and Burn Specific Pain Anxiety Scale (BSPAS) were performed at ED admission and after 1 h. Pain medications administered before arrival in the ED were reported by the rescue team. All patients received IV acetaminophen every 8 h and IV morphine according NRS. Results: Thirty patients were included in this study. At the time of arrival to the ED, > 90% of the patients reported severe pain; 95.8% of them received IV morphine to achieve pain relief. After 1 h, > 65% of patients had NRS < 3. The total amount of IV morphine was 18.12 ± 4.26 mg in the first hour. No adverse events were recorded. The BSPAS on admission to the ED was 34.8 ± 5.6, indicating severe anxiety. After 1 h, BSPAS was 12.8 ± 4.8, indicating mild anxiety. Conclusion: IV morphine used for burn pain management in the emergency setting significantly improves patient outcomes in terms of pain. IV morphine also reduced anxiety scores at 1 h. Plain Language Summary: The management of pain following a burn is extremely complex because of the multifactorial nature of burn pain. The main goal of acute pain management is to reduce the patient's pain, allowing them to maintain function and to prevent the chronification of pain. Opioids are used as first-line treatment in management of burn pain. In this single-center observational study, patients presenting with severe burns were enrolled in our hospital. Pain intensity and anxiety level were evaluated at admission and after 1 h. We evaluated pain treatment using intravenous (IV) morphine. Thirty patients were included in this study. At the time of arrival in hospital, almost all patients reported severe pain and received IV morphine to achieve pain relief. After 1 h, > 65% of patients had no pain. No adverse events were recorded related to morphine administration. The anxiety level improved after pain treatment. Finally, IV morphine used for burn pain management in the emergency setting significantly improves patient outcomes in terms of pain and reduced agitation. [ABSTRACT FROM AUTHOR]

The human community confronts a plethora of disasters, including man-made epidemics like COVID-19, environmental problems such as water and food resource depletion, biochemical warfare, and even threats from human-created artificial intelligence. Consequently, it is appropriate to term our current community a "disaster community". This paper delves into the issue of diaspora, intrinsically linked to the fragmentation problem in the disaster community, where each subgroup tends to focus solely on its own community. This issue is scrutinized by categorizing the diaspora into larger and smaller categories, with cases from both the international and domestic levels examined respectively within each category. Among the many Daoist philosophical concepts, this paper focuses on the Daoist principle of interconnectedness. In examining Daoist thought on interconnectedness, it also confirms that the notion of interconnectedness is being increasingly emphasized in modern society and across various academic disciplines. This perspective affirms the pluralistic nature of existence, while also underscoring the fundamental interconnectedness that underpins the myriad forms and phenomena. It provides a framework for addressing the challenges faced by the disaster community, particularly in relation to issues of diaspora, by emphasizing the need for coexistence and collective responsibility within a web of mutual relations. The philosophy innovatively applied from Daoism emphasizes "recognizing diversity based on Dao, while acknowledging that each existence is interconnected". Here, "recognition of diversity based on Dao" underpins pluralism, and "interconnectedness of all existence" forms the fundamental solution to the diaspora problem. This approach could be extended as a strategic response to various disasters that the human community encounters. Therefore, this paper assesses the current state of the disaster community, the severity of the diaspora issue, and some cases both between and within nations. It also discusses the core of Daoist philosophy and its creative application to overcome these challenges. The disaster community should transition towards a sustainable and open community, and on this journey, by acknowledging our interconnectedness, we can find solutions to not only the disasters we confront but also to the diaspora problem. [ABSTRACT FROM AUTHOR]

The Buddhist "Knotted Thread" originates from the ancient Indian practice of venerating sacred threads. In Indian culture, sacred threads symbolize identity and status and possess functions such as exorcism, healing, disaster prevention, blessing, protection, and divination. Initially, Buddhism opposed the use of sacred threads by its followers. However, as Buddhism evolved, it began to adopt this and other practices. Buddhist threads could be monochromatic or multicolored, with five-colored threads (五色縷) having significant cultural connections to China. In Buddhism, the five colors typically consist of four primary colors (四本色; blue, yellow, red, and white) plus an additional color. The difference between the Buddhist and traditional Chinese five colors lies in the selection of the fifth color. The five-colored threads in Buddhism have various combinations, such as blue, yellow, red, white, and black; blue, yellow, red, white, and purple; and blue, yellow, red, white and green. With Buddhism's spread into China, to align with traditional Chinese notions of five colors, the Buddhist five-colored threads gradually standardized to blue, yellow, red, white, and black. The evolution of the Buddhist five-colored threads reflects the cultural exchange between India and China. [ABSTRACT FROM AUTHOR]

The devastating Chichi earthquake in Taiwan in 1999 highlighted the importance of disaster prevention and relief operations. In response to the challenge of extreme events and compound disasters, the National Science and Technology Center for Disaster Reduction (NCDR) contributes to operations at the Central Emergency Operation Center (CEOC) of Taiwan by providing integrated information and timely suggestions, and it delivers a common operational picture to central and local governments through a decision support system. This study was undertaken to explore the emergency response towards the reconnaissance of earthquake disasters in Taiwan to illustrate how resilient cities ensure rapid crisis response with a focus on the NCDR disaster response decision support system. This study examines the decision support system used following the 2016 ML 6.6 Meinong earthquake. The results demonstrate that the first line of relief for the emergency response commander is data-driven decision-making. [ABSTRACT FROM AUTHOR]

This study compared earthquake location estimation using grid search and manta ray foraging optimization algorithm for synthetic and real earthquakes data from Van, Turkey. Both locating methods worked well, and they achieved similar results. The horizontal coordinates (latitude and longitude) of the earthquake were obtained successfully with both methods, from the inversion of the arrival times calculated from the noisy and noise-free synthetic earthquake data. However, there was some deviation in depth parameter for the noisy data. The location parameters obtained from the inversion of the real earthquake data using grid search and manta ray foraging optimization methods were in accordance with the solutions presented in previous studies. The depth parameters for the Van earthquakes did not fully match those in the previous studies, possibly due to differences in crustal velocity models. The depth parameters obtained for both Van earthquakes using both methods performed in this study are self-consistent at around 24 km. In addition, Disaster and Emergency Management Presidency and German Research Centre seismology centres also reached depth solutions near those in this study. The grid search method has some disadvantages compared with the manta ray foraging method, as it must be applied gradually, and delays reaching a solution. The manta ray foraging method is an easy, fast way to determine the kinematic location of earthquake hypocentres. [ABSTRACT FROM AUTHOR]

Local emergency managers play a significant role in mitigating, preparing for, responding to, and recovering from disasters. However, the fiscal stress that local governments often face limits their ability to hire and retain emergency managers within their jurisdiction. In this article, we aim to investigate public demand and support for hiring full-time, paid local emergency managers, a critical step to enhancing local emergency management capacity. We utilize the Contingent Valuation Method (CVM) to examine the average amount of additional local taxes that citizens are willing to pay in order to have a full-time, paid emergency management professional in their local government. Our analysis indicates that the average willingness to pay (WTP) for hiring a full-time, paid emergency manager ranges from $24 to $28 per household in extra local tax dollars. The estimated cost-benefit ratio suggests that hiring full-time paid emergency managers could be a cost-effective option for enhancing local emergency management capacity. Furthermore, our findings show that public willingness to pay for this policy change is correlated with social trust, political beliefs, and income level. [ABSTRACT FROM AUTHOR]

This study investigates the complex interplay between climate-related hazards and land cover changes in the Dibalo-Pingit-Zabali-Malayat (DPZM) River Watershed of Aurora province, Philippines. Historical typhoon data underscore the region's vulnerability to extreme weather events, emphasizing the critical need to enhance disaster preparedness and management. Land cover analysis from 1988 to 2020 reveals substantial transformations, driven largely by agricultural expansion at the expense of forest cover. Specifically, closed forest areas decreased by 11% annually from 2010 to 2015, while open forest areas decreased by 31% from 1988 to 2003. Conversely, built-up areas, annual crops, and perennial crops increased by 3%, 9%, and 30%, respectively, reflecting growing human pressures from 1988 to 2003. These land cover changes have intensified watershed degradation, as evidenced by increasing landscape fragmentation and declining mean patch size. Such alterations heighten the watershed susceptibility to natural hazards and hinders its capacity to provide essential ecosystem services. The study underscores the urgency for scienceinformed watershed management strategies to mitigate climate risks and protect the livelihoods of communities reliant on the DPZM River Watershed. Prioritizing sustainable land use practices, forest restoration, and disaster preparedness is crucial for safeguarding the watershed's ecological integrity and resilience in the face of ongoing challenges. [ABSTRACT FROM AUTHOR]

This research highlights that the livelihood systems of individuals residing in disaster-prone regions are undergoing significant changes as a result of explosive eruptions. Volcanic eruptions do significant harm to the infrastructure and ecosystems that serve as vital resources and means of support for populations. The group is very susceptible due to their dependence on natural resources for their survival. This study employs a combined qualitative and quantitative methodology to track the progression of individuals' livelihoods and presents descriptive quantitative data on the distribution of changes in livelihood systems. The findings of this study suggest that the introduction of the horticulture commodity market led to alterations in natural resources. Consequently, a significant number of individuals who were previously engaged in growing essential crops shifted to cultivating agricultural commodities to meet the demands of the market. This research has produced a compilation of community-driven disaster management strategies that are specifically designed for the local context. This research has both theoretical and practical ramifications. In theory, this research provides a substantial addition to the understanding of livelihood systems. The research findings indicate that society has a significant level of adaptability in exploiting resources within its surroundings. This research demonstrates that individuals possess inherent adaptations to endure the ecological strain caused by volcanic eruptions. [ABSTRACT FROM AUTHOR]

The Province of West Sumatra has a high threat of tsunami disaster risk. From the description of this situation, an appropriate and relevant contingency plan is needed to be used effectively when a disaster occurs. This research explains the evaluation of the Province of West Sumatra's tsunami contingency planning policy based on effectiveness and efficiency. The approach used was descriptive qualitative with purposive sampling to determine informants. Meanwhile, the data analysis technique uses the triangulation method. The research results show that in terms of effectiveness, the West Sumatra tsunami contingency plan is doubtful about its preparedness for dealing with this disaster. This is because the necessary steps have not been reviewed to adapt to the threats and resource requirements required. In the efficiency aspect of the West Sumatra tsunami contingency plan policy, the interventions to achieve the objectives have not been implemented optimally. The significance of this research is that it provides an overview of the results of a substantive analysis of policy effectiveness and efficiency, showing the importance of contingency plans that are updated with the latest conditions, both in terms of analyzing resources and disaster impacts and policies that bind stakeholders in handling Tsunami disaster risks. Theoretically, it is to produce an evaluation of public policies related to disaster management. [ABSTRACT FROM AUTHOR]

Geomagnetic activities have a crucial impact on Earth, which can affect spacecraft and electrical power grids. Geospace scientists use a geomagnetic index, called the Kp index, to describe the overall level of geomagnetic activity. This index is an important indicator of disturbances in the Earth's magnetic field and is used by the U.S. Space Weather Prediction Center as an alert and warning service for users who may be affected by the disturbances. Another commonly used index, called the ap index, is converted from the Kp index. Early and accurate prediction of the Kp and ap indices is essential for preparedness and disaster risk management. In this paper, we present a deep learning framework, named GNet, to perform short-term forecasting of the Kp and ap indices. Specifically, GNet takes as input time series of solar wind parameters' values, provided by NASA's Space Science Data Coordinated Archive, and predicts as output the Kp and ap indices respectively at time point t + w hours for a given time point t where w ranges from 1 to 9. GNet combines transformer encoder blocks with Bayesian inference, which is capable of quantifying both aleatoric uncertainty (data uncertainty) and epistemic uncertainty (model uncertainty) in making predictions. Experimental results show that GNet outperforms closely related machine learning methods in terms of the root mean square error and R-squared score. Furthermore, GNet can provide both data and model uncertainty quantification results, which the existing methods cannot offer. To our knowledge, this is the first time that Bayesian transformers have been used for geomagnetic activity prediction. [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.)

Floods are extreme hydrological events that can reshape the landscape, transform entire ecosystems and alter the relationship between living organisms and the surrounding environment. Every year, fluvial and coastal floods claim thousands of human lives and cause enormous direct damages and inestimable indirect losses, particularly in less developed and more vulnerable regions. Monitoring the spatiotemporal evolution of floods is fundamental to reducing their devastating consequences. Observing floods from space can make the difference: from this distant vantage point it is possible to monitor vast areas consistently, and, by leveraging multiple sensors on different satellites, it is possible to acquire a comprehensive overview on the evolution of floods at a large scale. Synthetic aperture radar (SAR) sensors, in particular, have proven extremely effective for flood monitoring, as they can operate day and night and in all weather conditions, with a highly discriminatory power. On the other hand, SAR sensors are unable to reliably detect water in some cases, the most critical being urban areas. Furthermore, flood water depth – which is a fundamental variable for emergency response and impact calculations – cannot be estimated remotely. In order to address such limitations, this study proposes a framework for estimating flood water depths and enhancing flood delineations, based on readily available topographical data. The methodology is specifically designed to accommodate, as additional inputs, masks delineating water bodies and/or no-data areas. In particular, the method relies on simple morphological arguments to expand flooded areas into no-data regions and to estimate water depths based on the terrain elevation of the boundaries between flooded and non-flooded areas. The underlying algorithm – named FLEXTH – is provided as Python code and is designed to run in an unsupervised mode in a reasonable time over areas of several hundred thousand square kilometers. This new tool aims to quantify and ultimately to reduce the impacts of floods, especially when used in synergy with the recently released Global Flood Monitoring product of the Copernicus Emergency Management Service. [ABSTRACT FROM AUTHOR]

Owing to its geographical position within one of the most seismically active zones globally, Iran has experienced numerous historically impactful earthquakes. To finance a part of these losses and reconstruction expenses, earthquake insurance has been offered as a rider on fire insurance policies by Iranian insurers. This mechanism, if operated well, can substantially contribute to disaster risk management. On the other hand, if the pricing and management of catastrophe risk lack sound, risk-modeling-based practices, it might add to the problems and act to the detriment of disaster risk management. In this paper, we first compare the current earthquake insurance pricing and risk management in the Iranian insurance industry to a state-of-the-art insurance regulation in the European Union (Solvency II). Then, we examine the consequences of following each approach in terms of business profitability and viability by conducting a numerical analysis on a hypothetical portfolio of property risks in Iran. In so doing, a seismic risk model has been developed by adopting the Earthquake Model of the Middle East (EMME) and a peer-reviewed vulnerability model and by developing an exposure model for residential dwellings in Iran. The results suggest that modeled earthquake premium rates are about 5 times larger than the rates currently used in the market. Furthermore, a comparison between solvency capital calculated following the methods specified by the European Solvency II policy and the Iranian Directive 69 indicates a visible underestimation of earthquake solvency capital by the Iranian insurers. It seems that maintaining the current insurance pricing and risk management practices in Iran will probably lead to a substantial accumulation of earthquake risk for domestic firms and eventually endanger the solvency of these companies in the event of large-scale earthquake losses in the future. [ABSTRACT FROM AUTHOR]

Accurate prediction and assessment of extreme flood events are crucial for effective disaster preparedness, response, and mitigation strategies. One crucial factor influencing the intensity and magnitude of extreme flood events is precipitation. Precipitation patterns, particularly during intense weather phenomena such as hurricanes, can play a significant role in triggering widespread flooding over densely populated areas. Traditional flood prediction models typically rely on single-source precipitation data, which may not adequately capture the inherent variability and uncertainty associated with extreme events due to certain limitations in the precipitation generation framework, availability, or both spatial and temporal resolutions. Moreover, in coastal regions, the complex interaction between local precipitation, river flows, and coastal processes (i.e., storm tide) can result in compound flooding and amplify the overall impact and complexity of flooding patterns. This study presents an implementation of the global copula-embedded Bayesian model averaging (BMA) (Global Cop-BMA) framework for improving the accuracy and reliability of extreme flood modeling. The proposed framework integrates a collection of precipitation products with different spatiotemporal resolutions to account for uncertainty in forcing data for hydrodynamic modeling and generating probabilistic flood inundation maps. The methodology is evaluated with respect to Hurricane Harvey, which was a catastrophic weather event characterized by intense precipitation and compound flooding processes over the city of Houston in the state of Texas in 2017. The results show a significant improvement in predictive accuracy compared to those based on a single precipitation product (e.g., the Nash–Sutcliffe efficiency (NSE) performance of a single quantitative precipitation estimation (QPE) is in the range of 0.695 to 0.846, while the Cop-BMA yields an NSE of 0.858), demonstrating the merits of the Global Cop-BMA approach. Furthermore, this research extends its impact by generating probabilistic flood extension maps that account not only for the primary influence of precipitation as a flood driver but also for the intricate nature of compound flooding processes in coastal environments. [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 serves as an introduction to focus on the meaning of resilience as a notion that hypothetically enables cities and their citizens to remain unaffected by shocks and stresses of diverse nature, but in practice, is a parsimonious representation of a highly complex human endogenous condition that is often not adequately understood and addressed due to weak or weathered disaster risk governance. Through an empirical analysis, the relevance of the occurrence of disasters such as the one produced by the Mexico City earthquake of September 19, 2017, and its relationship to the meaning of urban resilience is addressed. Since the 100 Resilient Cities program launch in 2013, several cities, including Mexico City, have adopted diverse strategies to build and become more resilient to physical, social, and economic shocks and stresses. Nonetheless, the degree of success of such strategies expressed in everyday life within the cities, regardless of what the official documents report, reveals highly heterogeneous results. In the case of Mexico City, it is evident that the appropriate strategy for attaining the desired outcome of becoming a Resilient City has not been successful. Despite setting the goal of advancing disaster risk reduction through urban and regional planning, the impact of the earthquake of September 19, 2017, proved otherwise. [ABSTRACT FROM AUTHOR]

After thirty-two years of the devastating earthquake in Mexico City in 1985, the city was again shaken by the consequences of the 7.1 Mw earthquake that struck central Mexico on September 19, 2017. The impact of the disaster nationwide was 369 deaths, 6000 injured, 256,000 total affected people, and damages in the order of US$ 6 billion. Although the earthquake's impact figures are not consistent yet, some sources indicate that in Mexico City alone, the earthquake caused 228 deaths, 44 collapsed buildings, and 73,000 damaged properties, including 5765 homes and 973 schools. The effect on the economy was estimated at between 0.1 and 0.3% of GDP for 2018, and the funds needed for reconstruction were calculated at more than US$3.4 billion. Local government responses to the earthquake were dosed and limited to immediate actions based on a traditional and militarized perspective. Once again, after the quake hit, city authorities and urban planners introduced several actions and initiatives to rethink how disasters can be managed in the city. Regular assessment of impacts on the security of the facilities at risk, liability, damages and losses initiatives, changes to the law, and purges in the local civil protection offices were carried on. As we argue in this article, all these actions are increasingly seen as a cause of serious concerns about the accountability of the authorities responsible for civil protection and risk management at the different levels of government. This article briefly introduces the renewed interest that has emerged in recent years around the globe, including Mexico City, regarding the increasing demands for accountability related to disasters. In the second section, the methodology of the article is described. It will then examine the results and discussion of the analysis of the disaster triggered by the earthquake of September 19, 2017. This included three major topics: (1) background from a hazard perspective and a general characterization of earthquake exposure, (2) damages and losses, and (3) insights into disaster management. The final section concerning closing remarks aims to reflect on future challenges for disaster accountability and community involvement in disaster risk management. [ABSTRACT FROM AUTHOR]

Understanding a community's place attachment is vital for effective land-use planning and disaster risk management that aligns with local needs and priorities. This study examines the methodologies employed to grasp these values, emphasising the significance of meaningful participatory approaches. It sheds light on the challenges encountered due to COVID-19 restrictions, which prevented direct face-to-face engagement with community members. To address this issue, researchers devised "digital walking tours" as an alternative to traditional walking transect methods, aiming to investigate the relationship between place attachment and perceptions of the landscape in Patreksfjörður, a small fishing community in the Westfjords, during the pandemic. The evaluation of this method demonstrated its suitability for conducting comprehensive and cost-effective community consultations. Participants expressed enjoyment and found the technology (online video calls and StreetView imagery) user-friendly and engaging. To further enhance the method, several recommendations are proposed, including the integration of virtual tours with in-person methods whenever feasible, incorporating additional sensory input, adopting a slower pace, and offering more opportunities for participants to divert to personally significant locations. Other contextual considerations encompass the use of participants' native language and the facilitation of digital walking tours with pairs or small groups of participants. [ABSTRACT FROM AUTHOR]

Urban development is facing increasingly complex disturbances. Assessing large cities' urban resilience is important for improving their ability to withstand disturbances and promoting sustainable development. Therefore, this paper establishes an improved assessment model for urban resilience based on the driving force–pressure–state–impact–response (DPSIR) and data envelopment analysis (DEA) model. The Malmquist index, Dagum Gini coefficient, and Markov chain were sequentially used for spatiotemporal evolution and differential resilience analysis. Then, 105 large Chinese cities were selected as case studies. The results indicate their overall resilience is relatively high; each year's average resilience efficiency can achieve DEA effectiveness. The distribution pattern of resilience level presents a healthy olive-shaped structure. However, there is also a significant difference between the two poles. During the research period, the combined effect of technological efficiency improvement and technological progress resulted in the overall resilience slowly improving, and this process was more driven by technological innovation. At the same time, the overall regional difference in resilience also shows a narrowing trend, and the current spatial differences mainly come from the difference within subregions and super-density. In future transfer predictions, the resilience of large cities will show good stability with a higher probability of maintaining stability; if the resilience undergoes a transition, the probability of an increase will be higher than a decrease. Based on the life cycle process of resilience, this study selects indicators that can characterize the level of resilience according to the DPSIR model, which comprehensively reflects the characteristics of urban resilience. This study's results can provide particular reference values for urban disaster response emergency planning and sustainable development construction, and it also provides new ideas for the assessment research of urban resilience. [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]

Aim: This study aimed to investigate personal preparedness among patients on haemodialysis (HD) and to examine the relationship among sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours during natural disaster incidents. Design: A cross‐sectional survey was conducted. Methods: A convenience sampling method was used. A total of 446 participants from six areas of Sichuan province completed the online questionnaire study from February 27 to March 13, 2022. Sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours were measured. Descriptive statistics were used to analyse sociodemographic characteristics and attitudes toward disaster preparedness. The relationship among sociodemographic characteristics, attitudes toward disaster preparedness and personal preparedness behaviours were assessed using ordinal regression. Statistical significance was defined as p < 0.05. Results: A total of 446 participants completed the survey. Of these, 42.15% (N = 188) were poorly prepared, 26.23% (N = 117) were moderately prepared and 31.61% (N = 141) were highly prepared. Ordinal regression showed that knowing about disaster preparedness (Odds Ratio (OR) = 1.691, 95% Confidence Interval (CI) = 1.081–2.644, p = 0.021), participating in disaster evacuation exercises (OR = 2.519, 95% CI = 1.595–3.977, p < 0.001) and learning about disaster preparedness (OR = 2.421, 95% CI = 1.542–3.802, p < 0.001) were associated with high preparedness. Compared to patients with a university degree or higher, patients with a junior high school education or lower (OR = 3.491, 95% CI = 1.760–6.925, p < 0.001) and senior high school degree (OR = 2.052, 95% CI = 1.038–4.057, p = 0.039) were associated with high preparedness. Patients who felt very confident and could deal with all their needs (OR = 3.878, 95% CI = 2.904–7.181, p < 0.001) or patients who felt confident and could meet some of their needs (OR = 1.949, 95% CI = 1.124–3.379, p = 0.017) had higher preparedness than those who felt less confident and were not well prepared to take care of their needs. Patient or Public Contribution: After obtaining each participant's consent, they filled out the online questionnaire using their own or a relative's cell phone while undergoing HD. Implication for Practice: It is essential that patients should be educated not only on medical specialty topics, but also on general disaster preparedness. Medical institutions should improve and reinforce preparation training among targeted populations. The low level of preparedness is partly due to the lack of participation of patients in disaster preparedness programs. Dialysis center managers should be urged to implement such programs at their centers. [ABSTRACT FROM AUTHOR]

This paper discusses a method of determining the minimum safe altitude of an uncrewed aerial vehicle (UAV) at any point within a designated airspace by conducting a glide reachability analysis. Recently, fixed‐wing UAVs are more regularly deployed near population centers and in extreme environments, requiring increasingly robust emergency systems and planning. The long‐ranges and adverse terrain associated with monitoring the Volcán de Fuego in Guatemala by a team from the University of Bristol (UoB) increases the likelihood that motor failure would result in the aircraft being unable to Return To Home (RTH) and impossible to retrieve. A method for delineating a boundary representing the minimum safe altitude required for the aircraft to safely glide to the airfield in the event of a motor failure was developed within MATLAB, defined by the UAV's minimum glide angle in wind. This model was subsequently compared with flight data from UoB missions around Fuego to better improve its accuracy and analyze the limitations of the missions. [ABSTRACT FROM AUTHOR]

Introduction: Peritoneal dialysis (PD) remains understudied in disaster nephrology. This retrospective multicenter study explores the experiences of PD survivors following the February 6, 2023, Kahramanmaraş Earthquake. Methods: Adult PD patients from 11 affected cities were analyzed to assess challenges faced during and postearthquake, alongside clinical outcomes. Results: Among 101 participants (median age: 45 years, median PD duration: 24 months), 57 were female, with 79 on continuous ambulatory PD. Challenges included power outages and water shortages, with primary shelter in kin's houses (33%) and homes (28%). Twelve patients experienced PD program delays, and three lacked assistance postdisaster. Sixteen patients changed PD modalities, with seven experiencing postearthquake peritonitis. Clinical parameters remained stable, except for a slight decrease in hemoglobin levels. Conclusion: Despite challenges, PD survivors exhibited resilience, highlighting the importance of addressing peritonitis and unusual pathogens in disaster preparedness initiatives. [ABSTRACT FROM AUTHOR]

Base‐isolated hospitals are frequently preferred to fixed‐base ones because of their improved seismic structural performance. Despite this, the question remains open on the advisability of using this modern seismic protection technology in preference to other conventional solutions, on the grounds of a holistic approach based on limiting non‐structural damage as well as continuity of service to the community in the aftermath of an earthquake. Two full‐scale four‐storey (fixed‐base) and three‐storey (base‐isolated) hospital buildings have been recently built and subjected to three‐dimensional shaking table tests at the National Research Institute for Earth Science and Disaster Prevention (Japan), with particular attention to evaluating and classifying functionality of non‐structural components and vital medical equipment. A two‐phase experimental campaign was carried out considering two earthquakes scaled at different intensity levels and applied along the horizontal and vertical directions. The current study aims to provide results of a numerical structural and non‐structural blind prediction of these hospital settings. A homemade numerical code is developed to account for lumped plasticity modelling of steel frame members and variability of the friction coefficient of spherical sliding bearings. Moreover, three non‐structural components are modelled in the fixed‐base structure: that is, elastic single degree of freedom systems representing two tanks filled with sand at the top floor; elastic beam elements for piping at the third floor; five‐element macro‐model for the in‐plane‐out‐of‐plane nonlinear response of partition walls at the first floor. The identification of predominant vibration periods of the fixed‐base structure is carried out using a homemade numerical code based on the continuous wavelet transforms in combination with the complex Morlet wavelet. Finally, the sliding and rocking motion of three items of medical equipment (i.e., incubator at third floor, dialysis machine at second floor and surgical bed at first floor) are analysed by means of a homemade numerical code, considering acceleration time histories of selected structural nodes of the fixed‐base structure. [ABSTRACT FROM AUTHOR]