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The evaluation of slope stability is of crucial importance in geotechnical engineering and has significant implications for infrastructure safety, natural hazard mitigation, and environmental protection. This study aimed to identify the most influential factors affecting slope stability and evaluate the performance of various machine learning models for classifying slope stability. Through correlation analysis and feature importance evaluation using a random forest regressor, cohesion, unit weight, slope height, and friction angle were identified as the most critical parameters influencing slope stability. This research assessed the effectiveness of machine learning techniques combined with modern feature selection algorithms and conventional feature analysis methods. The performance of deep learning models, including recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and generative adversarial networks (GANs), in slope stability classification was evaluated. The GAN model demonstrated superior performance, achieving the highest overall accuracy of 0.913 and the highest area under the ROC curve (AUC) of 0.9285. Integration of the binary bGGO technique for feature selection with the GAN model led to significant improvements in classification performance, with the bGGO-GAN model showing enhanced sensitivity, positive predictive value, negative predictive value, and F1 score compared to the classical GAN model. The bGGO-GAN model achieved 95% accuracy on a substantial dataset of 627 samples, demonstrating competitive performance against other models in the literature while offering strong generalizability. This study highlights the potential of advanced machine learning techniques and feature selection methods for improving slope stability classification and provides valuable insights for geotechnical engineering applications. [ABSTRACT FROM AUTHOR]

Tropical cyclone causes large-scale devastation and destruction in the coastal plains of India, particularly in Odisha, which is the most cyclone-affected state in the country. Tropical cyclones are projected to be more powerful and widespread due to changing climate. Hence, the risk assessment of tropical cyclone is necessary to identify cyclone-risk areas in coastal Odisha which may help in the mitigation of the damages caused by cyclones. Therefore, this study utilizes geospatial techniques to produce a comprehensive risk map posed by tropical cyclones and to estimate the degree of risk for coastal districts of Odisha. For this, we evaluated the district-level cyclone risk for coastal Odisha using multi-criteria decision-making (MCDM) technique by considering 21 parameters for each of the four components of risk, i.e., exposure, hazard, vulnerability, as well as mitigation capacity. For each criterion, thematic raster map layers were created and weighted using a fuzzy analytical hierarchy process (FAHP). We prepared individual risk component maps using weighted overlay techniques and finally integrated all indices to create the risk map. The study shows that 13% area of the study area comes under a very high-risk zone whereas, 25% area comes under a high-risk zone. The central (Cuttack, northern parts of Khordha, and south-western parts of Jajpur district) and the eastern part (most of the parts of Jagatsinghpur, Kendrapara, and northern parts of Puri district) of the study area come under high to very high tropical cyclone impact zone. Almost 67% of the total area is highly vulnerable to tropical cyclones and mainly concentrated near the shoreline. The applied approach and results can assist the local authorities in identifying vulnerable and hazardous locations and developing workable solutions for the mitigation of revised cyclone threats in the coastal districts of Odisha. [ABSTRACT FROM AUTHOR]

Early warning systems are an essential tool for managing flood emergencies. Alert and warning applications and mobile-phone messaging services have become increasingly widespread among major international emergency agencies as means of communicating risks to the population, and their effectiveness in reducing human and material damages during flood events is significant. Despite their crucial importance, one of the main challenges in the field of emergency communication is the lack of protocols for systematic and standardized production of warning messages. While emergency agencies produce messages on a diversity of topic areas, there are no protocols for structuring their content according to communication functions, exhaustive identification of the relevant areas of action, or classification of content according to different topics. With a view to this opportunity for improvement, the aim of this article is to propose a method for creating a catalog of warning messages enabling their systematic composition and organization. To exemplify the successive stages in the development of such a catalog, we present here the resources and methodological process followed by the authors of this article when commissioned with this task by the emergency services of the Valencian Autonomous Region (south-east Spain) for flood-risk communication. The warning message catalog was pilot tested with experts and user focus groups. Developing warning message catalogs offers a vital resource that can enhance the outreach and operability of warning systems in the current context of increased flood risk due to climate change. [ABSTRACT FROM AUTHOR]

Lightning fatalities in the Philippines are analyzed for the first time using data from the Philippine Statistics Authority. A total of 1584 lightning fatalities occurred between 2006 and 2021. The annual number of lightning fatalities decreased from an average of 118 fatalities per year between 2006 and 2013 to an average of 80 fatalities per year between 2014 and 2021. The majority of the fatalities occurred in May to July (56%), during the afternoon, and in provincial areas (95%). About 82% of the victims were male where the most vulnerable group are young males ages 20 to 29 years old. Common activities of the victims include sheltering in non-enclosed infrastructures such as agricultural huts, and doing outdoor laborious work such as farming and fishing. Immediate strategic interventions can focus on raising lightning safety awareness in high-risk areas and among the vulnerable population. [ABSTRACT FROM AUTHOR]

Accurate assessment of surface water from satellite and remote sensing data plays an important role in water and flood management and supporting natural ecosystems and human development. Remote sensing imagery has significantly advanced in water extraction methods, particularly in water index, classification, and sub-pixel analysis. Water-index-based approaches offer notable advantages such as speed and convenience among these methods. The unique characteristics of surface water and flooded areas, including their extensive coverage and dynamic nature, make the water index particularly effective for monitoring large regions. However, the complexity of land surfaces in aquatic environments presents challenges that hinder accurate water extraction. These challenges differ across various factors, such as shadows in urban and mountainous areas, small water bodies, muddy water, and water leakage in unshaded regions. The current study introduces a novel Flood/Water Extraction Index (FWEI) for identifying water and flooded areas to address these challenges. The FWEI utilizes the average ratio of visible and near-infrared bands derived from Sentinel-2 images. The proposed index utilizes images with 10-m and average visible bands and more effectively compensates for errors arising from spectral and spatial changes. Therefore, it demonstrates strong performance by more accurately mapping muddy and clear water within small water bodies and narrow rivers. The performance of the offered FWEI index is compared with other indices, including the Normalized Difference Water Indices (NDWI-G, NDWI-F), Modified NDWI (MNDWI-1, MNDWI-2), and the Automatic Water Extraction Index (AWEInsh) without shadow. While other indices excel in specific scenarios, such as built-up or non-built-up areas, and bare lands versus vegetated areas, the FWEI index demonstrates consistently high accuracy and stability in extracting surface water across diverse backgrounds. The FWEI index achieves an average Overall Accuracy (OA) of 94.26% for water extraction and 93.11% for flood extraction. In comparison, the AWEInsh attains an OA of 90.48% and 90.39%, NDWI-F performs at 86.69% and 86.55%, MNDWI-1 at 77.21% and 75.82%, MNDWI-2 at 76.12% and 75.42%, and NDWI-G at 75.26% and 74.78%, respectively. The integration of visible spectral bands with the near-infrared band proves instrumental in enhancing the accuracy of water derivation in complex and expansive environments. [ABSTRACT FROM AUTHOR]

In India, south-west monsoon winds become weak and monsoon withdraws continuously during October. Rainfall during October is a common phenomenon because October is the transition month from the rainy season to the dry winter conditions. However, occasional rainfall activity continues during October. By the beginning of October 2021, the monsoon withdrew from the northern plains. Uttarakhand experienced exceptionally heavy rainfall, which caused floods and severe damage to the economy and human life in the state from 16 to 20 October 2021. A deep westerly trough lay between longitude 65.0° E to 70.0° E and a low-pressure area observed over east Rajasthan along with moisture incursion from the Bay of Bengal as well as from the Arabian Sea over the western Himalayan region, particularly over Uttarakhand. Moisture incursion from the Arabian Sea is one of the important factor contributing to heavy rainfall. The case study was conducted using various meteorological observations, wind patterns, and weather systems. The current year's rainfall pattern and normal rainfall trend were analysed using rainfall data for October 2021. It is observed that rainfall was received from 13 stations and all the stations of the state received rain heavier than normal during the third week of October 2021, which indicates that exceptionally heavy rain generally, recurved during the third week of October. Actual vs. normal rainfall is showing R2 0.61 which reveals that 61% of the variability observed in the actual variable and is explained by the regression model. [ABSTRACT FROM AUTHOR]

Parametric insurance schemes allow for payouts to be triggered by real-time hydro-/meteorological parameters instead of waiting for damage assessments, which means they can be settled swiftly, giving people access to funds right after the event. In this work we propose a framework to design parametric insurance schemes and systematically quantify the basis risk: the difference between the parameter-based payout and the actual damage. We implement the framework in the open-source global risk assessment platform CLIMADA and illustrate it with two stylized parametric insurance case studies, targeting tropical cyclones in Mozambique and winter storms in France. The data used and the provided code base are globally-consistent, open-source, and readily available. The presented methods are therefore applicable in data-scarce areas and accessible to stakeholders from the public and private sector. Moreover, our approach can easily be adapted to other hazards and exposures worldwide. This improves the accessibility and transparency of such innovative insurance schemes. [ABSTRACT FROM AUTHOR]

According to the Icelandic Meteorological Office, climate change may increase the likelihood, intensity, and frequency of some natural hazards in the country, such as avalanches. It is therefore essential to increase preparedness for climate change–related effects. Until recently, social and community aspects of climate change–related hazards have not received much attention in Iceland. The aim of this study was to explore the role of place attachment in small remote communities in Iceland and how residents experience the threat of avalanches. Through a narrative approach, we conducted interviews with residents and focus groups in two communities in the Westfjords. Our findings suggest that both communities show a high level of place attachment, in particular with regard to the natural and social dimension. A positive impact of place attachment translates into willingness for volunteering and local engagement, which can increase preparedness and enhance capacity building. While we found negative tendencies of place attachment in both places, for example in that residents do not consider their communities vulnerable despite the risk, they seem to be less prominent than the positive aspects. Residents exhibit traditional local knowledge, but there is a need to better integrate newcomers and foreigners in the communities into emergency planning. [ABSTRACT FROM AUTHOR]

Increasing intensity and frequency of tornadoes have been reported in Europe in the last decades, and in Italy, in particular in the northeast area, including Veneto, Friuli Venezia Giulia and Trentino Alto Adige. The public consciousness and the meteorological control of this risk are sufficiently established in the USA. The European continent and the northeast of Italy do not exhibit a similar state, although the tornado damages induced are increasing and becoming of economic relevance. Studies and research are diffused and have reached a detailed level, being able to correlate tornado intensity to a detailed damage state for a wide amount of building classes. But, codes and standard, both in USA and in the whole European continent, have not been developed for tornado loadings. For this reason, to fill the gap between studies, research and observational data, in this study Italian wind extreme events are presented and discussed first. In a second part, the damage assessment results of the most extreme events recorded in the northeast of Italy (from F3 to F5, Fujita scale) from 1905 to 2017 are presented. Codes and standard showing the lack of design and verification procedure are presented in the third part. Finally, a tornado-resistant building classification is presented to enforce the consciousness that new codes and standard could protect people from extreme events, decreasing dramatically the devastation of not so rare phenomena also for Italy. [ABSTRACT FROM AUTHOR]

Developing a susceptibility map is a crucial primary step for dealing with undesirable natural phenomena, gully erosion included. On the other hand, recent computational progress call for employing new methodologies to keep the solutions updated. In this work, the performance of a conventional artificial neural network (ANN) is improved by applying a metaheuristic algorithm (symbiotic organisms search—SOS) for generating the gully erosion susceptibility map of an area in Golestan Province, Northern Iran. A geo-database is created from the gully erosion inventory and twenty conditioning factors. After analyzing the interrelated relationships between the geo-database components, training and testing data sets are formed. The models are executed with proper configurations and according to the results, the SOS algorithm could enhance the training accuracy of the ANN from 92.8% to 98.4%, and testing accuracy from 89.8% to 91.4%. In addition, comparing the performance of the SOS with shuffled complex evolution (SCE-NN) and electromagnetic field optimization (EFO-NN) algorithms revealed the greater accuracy of the SOS. However, the SCE-NN and EFO-NN performed more accurately than conventional ANN. Therefore, it can be concluded that the use of metaheuristic techniques may improve the prediction ability of the ANN in gully erosion susceptibility mapping. Finally, a monolithic equation is extracted from the SOS–ANN model to be used as a predictive formula for similar purposes. [ABSTRACT FROM AUTHOR]

This empirical study explores the interplay between place attachment, risk perception, and coping behavior, within two small Norwegian communities exposed to flash flooding. Through a mixed-methods narrative approach, we found that most of our respondents exhibited positive attachment to their communities, aligning with previous studies in rural settings. Using a conceptual model of place attachment (Raymond et al. 2010), the study identified five dimensions of attachment among the respondents: place identity, place dependency, family bonding, friend bonding, and nature bonding. The most dominant narratives centered around practical ties to the area through family and place dependency, combined with symbolic attachments in the form of nature and identity. Place attachment through generational ties, closeness to nature, and access to historical knowledge influenced residents’ risk perception, here displayed as heightened awareness of flash flood-related risks. This risk awareness did however not translate directly into feeling at risk. Findings point to residents’ underestimating risk close to home, which could partially be explained by strong place attachment. Coping behavior was mainly motivated by previous hazard experiences. Place dependency and family bonding contribute to explaining the resident’s reluctancy to relocate as a coping strategy. We found that place attachment can act as both a mediator and a moderator between risk perception and coping behavior, and the relationship between place attachment, risk perception, and coping behavior is complex. While no clear causal relationship was established, understanding common elements in risk narratives can enhance community resilience and inform strategies to address community concerns. [ABSTRACT FROM AUTHOR]

This study provides a science map on social media application in disaster management through bibliometric analysis. Citation, co-citation, and co-words analysis were applied to identify influential social media publications in disaster management, evaluate the prospective evolution of social media and disaster management themes, and predict future research streams based on social media in disaster management. 862 journal publications were retrieved from the Web of Science, with 33,758 cited references. From the co-citation analysis, 3 clusters were classified: (1) Twitter in disaster management, (2) post-disaster recovery process, and (3) information and knowledge sharing, while the co-word analysis also produced 3 clusters (1) social media communication in disaster events, (2) social media and disaster preparedness, and (3) social media and disaster recovery. Furthermore, three research streams were discussed through inductive interpretation from the three analyses performed. This study provides theoretical and practical understanding to relevant stakeholders facing disaster through social media applications. [ABSTRACT FROM AUTHOR]

Floods are one of the natural disasters that occur most frequently in the Brahmani River of Eastern India. Frequent floods in the area, results from anthropogenic activities, climate change, unpredictable weather, and heavy rainfall cause loss of life, property, and resources. Flood hazard susceptibility maps will help in identifying risk-prone locations, which aids in flood management and the decision-making process. The main objective of this study is to evaluate the performance of bivariate statistical and hybrid models such as Frequency ratio, Weight of Evidence (WoE), Evidential Belief Function (EBF), Index of Entropy, Analytical Hierarchy Process (AHP), AHP–TOPSIS and AHP VIKOR to prepare flood susceptibility maps of the Brahmani River basin, India. The flood conditioning factor includes Slope, Aspect, Elevation, Curvature, Geology, Geomorphology, Topographic Wetness Index, Topographic Ruggedness Index, Distance from Streams, Distance from Roads, Rainfall, Normalized Difference Vegetation Index (NDVI), Stream Power Index, Soil, Drainage Density, and Land use Land cover. The flood inventory was prepared using various atlas and news reports. Multicollinearity among all the causative parameters is measured using the Variance Inflation factor (VIF) and Tolerance (TOL). The collection of a spatial database and flood inventory from various sources is used to prepare flood susceptibility maps. The flood susceptibility map is categorised into very high, high, moderate, low, and very low classes using the natural break method. The models are validated using flood training (70%) and testing (30%) points. The accuracy of flood susceptibility maps is determined using Area Under Receiver Operating Characteristics (AUROC) curves and Seed Cell Area Index (SCAI) values. The success rate of Frequency ratio (AUC 0.91), EBF (AUC 0.90) and WoE (AUC 0.86) show the highest accuracy among all other models in AUC. WoE, IoE, and FR gave reliable results in the SCAI validation process. The susceptibility maps will help in identifying hazard-prone areas, which will help policy makers better assessment of natural hazards. [ABSTRACT FROM AUTHOR]

The birth of a new monogenetic volcano is difficult to forecast with precision, both in space and time. Nevertheless, seismic activity can alert of the imminence of such an eruption because it usually occurs as small-magnitude earthquake swarms that can last for a few weeks to months prior to an eruption. These swarms are usually related to magma that becomes stalled in the Earth's crust for variable periods of time before its eventual eruption at the surface. For several reasons, volcanic seismic swarms have rarely been recorded with seismometers before the birth of a new monogenetic volcano. Over the past 25 years, six distinct seismic swarms (in 1997, 1999, 2000, 2006, 2020, and 2021) were detected between Tancítaro and Paricutin volcanoes, in the southwestern part of México's Michoacán-Guanajuato volcanic field. They are believed to represent repeated attempts of magma to reach the surface hinting that in this region magma might become stalled for some time, so as to not reach the surface in a single ascent event from its source in the mantle. To better understand the magma's migration path through the crust, we re-located with greater precision some of these seismic swarms by using the same methodology and velocity model to the entire data set. Our results show that these swarms originated within a small area beneath the NE flank of Tancítaro at depths of between 15 and 8 km below sea level (bsl). Apparently, magma is trying to reach the surface within the same conduit network at these crustal depths, but stalls when reaching a depth of ~ 8 km bsl. It is crucial to study these swarms because they might be precursors to a new eruption in this part of the Michoacán-Guanajuato volcanic field. This monogenetic field has been very active, producing several dozen eruptions during the Holocene, the last two Jorullo (1759–1774) and Paricutin (1943–1952). Furthermore, the Tancítaro area displays one of the highest densities of Holocene volcanoes within the entire field, making it a probable candidate location for the birth of a future monogenetic volcano. For these reasons, a permanent seismic network should be installed as soon as possible. [ABSTRACT FROM AUTHOR]

Voluminous pumice rafts produced by the 2021 phreatomagmatic eruption of Fukutoku-Oka-no-Ba, a submarine volcano located in the Izu-Bonin Islands, reached many Japanese ports and islands, damaging fisheries and hindering marine traffic and trade. This event emphasized the necessity for governments and stakeholders to develop plans in advance and prepare disaster mitigation measures before an eruption. To investigate when and to what extent pumice might intersect trade routes and arrive at islands after future eruptions, we conducted particle tracking simulations of eruptions at major volcanic islands and submarine volcanoes near Japan using the velocity field from the ocean reanalysis dataset. Seven major volcanoes that have produced pumice rafts in the past century were selected: the submarine volcano NNE of Iriomote Island, Izu-Tobu Volcanoes, Miyakejima, Bayonnaise Rocks, Nishinoshima, Kaitoku Seamount, and Fukutoku-Oka-no-Ba. We partly reproduced the distribution of pumice arrivals recorded after the 1986 Fukutoku-Oka-no-Ba eruption, demonstrating the potential effectiveness of the simulations. We report likely pumice raft arrivals and drifting durations for the investigated eruptive scenarios, which may aid future risk assessments for pumice arrivals. [ABSTRACT FROM AUTHOR]

Unlike other natural hazards, drought has severe consequences on numerous aspects of life. After the industrial revolution, drought is prevailing in most parts of the world. Likewise, global warming and climate change have increased the recurrent occurrences of extreme values and the short-distance variability in precipitation. Therefore, accurate and effective reporting of drought characteristics at the regional level is one of the most challenging tasks in hydrology. This research aims to improve the accuracy and quality of drought characterization and its continuous monitoring at the regional level. This article develops a new drought indicator by integrating unequal weights under an X-bar chart with the regional aggregation precipitation data. We called the new index– the Quality Boosted Regional Drought Index (QBRDI). In application, the northern region of Pakistan is considered to assess and evaluate QBRDI. In comparison, the study includes a pairwise comparison of QBRDI and Regional Standardized Precipitation Index (RSPI) using the Pearson correlation coefficient. Comparative to RSPI, a significantly low Coefficient of Variation between the correlations of QBRDI with other meteorological stations reveals that QBRDI has more regional characteristics than RSPI. These outcomes endorse the rationality of using QBRDI for regional drought analysis. In addition, the methodology of QBRDI provides a new way to minimize the impact of outliers and extreme values in the regional aggregation of precipitation data. [ABSTRACT FROM AUTHOR]

Subaerial landslide-tsunamis (SLTs) are generated by mass movements impacting into water bodies such as lakes, reservoirs or oceans. A recent SLT was the 2003 Qianjiangping event in the Three Gorges Reservoir resulting in 11 missing fishermen. Preliminary hazard assessments of SLTs relay on investigations in wave flumes (2D) with longitudinal wave propagation and basins (3D) with radially propagating waves. This study focuses on lateral slide impact into narrow reservoirs for which available empirical equations for the maximum wave amplitude am or height Hm based on 2D or 3D studies alone are unlikely to result in accurate predictions. A 3D-2D method has recently been proposed to calculate the decay of am and Hm in such geometries, i.e. 3D approaches are used for the slide impact region followed by 2D approaches for the far field. This study aims to verify this 3D-2D method and to estimate wave decays in narrow reservoirs, involving reflections, based on 115 laboratory experiments. New empirical equations for the decay of am and Hm in the 3D region (with wave propagation distance r ≤ wr, with wr as the reservoir width) are proposed. It is then verified that this 3D-2D method is feasible for predicting wave attenuation in narrow reservoirs. The suitability of available equations are discussed and the present equations are successfully used to predict a past SLT with a deviation of 19.9%. The present study reveals that the new empirical equations are the most suitable to be applied in this 3D-2D method to support preliminary SLT hazard assessment. [ABSTRACT FROM AUTHOR]

This systematic review provides a comprehensive overview of tsunami evacuation models. The review covers scientific studies from the last decade (2012–2021) and is explicitly focused on models using an agent-based approach. The PRISMA methodology was used to analyze 171 selected papers, resulting in over 53 studies included in the detailed full-text analysis. This review is divided into two main parts: (1) a descriptive analysis of the presented models (focused on the modeling tools, validation, and software platform used, etc.), and (2) model analysis (e.g., model purpose, types of agents, input and output data, and modeled area). Special attention was given to the features of these models specifically associated with an agent-based approach. The results lead to the conclusion that the research domain of agent-based tsunami evacuation models is quite narrow and specialized, with a high degree of variability in the model attributes and properties. At the same time, the application of agent-specific methodologies, protocols, organizational paradigms, or standards is sparse. [ABSTRACT FROM AUTHOR]

Changes in the climatic patterns due to global warming have increased glacier associated hazards around the world. One among those is the formation and expansion of glacial lakes due to glaciers melting at a faster rate. These lakes are dangerous and may lead to glacial lake outburst floods (GLOFs), which are the sudden releases of huge volumes of water from glacial lakes due to the failure of the dam. This study evaluates the GLOF potential of the Ghamu Bhar glacial lake located in District Ghizer, Pakistan. In this study, changing surface area and volume of the lake have been used as the primary parameters to evaluate the GLOF potential. Geospatial techniques were used to assess the temporal evolution of the lake from 2000 to 2021. Field surveys were also conducted to assess the knowledge and experience of the affected people and analyze the potential GLOF risk as well as the capacity of the vulnerable communities to cope with the impacts of a GLOF. The results showed an increasing trend of an alarming nature in the lake size. Weather data during the study period also indicated a slight increase in temperature and precipitation, which might have been related to lake expansion. If this trend continues, the GLOF potential will increase, leading to significant socioeconomic and environmental damages downstream. Therefore, to mitigate flood risk, it is imperative to devise a risk-reduction strategy. The findings of this study will provide a baseline on which to build more precise methods to monitor these hazards. [ABSTRACT FROM AUTHOR]

A massive snow avalanche occurred on April 2012 at Gayari, located in NE part of Pakistan, close to India and China Border. The catastrophic avalanche killed nearly 148 people, majority of which were Pakistan army personnel destroying army base camp. To mitigate its future hazard, different triggering mechanisms have been investigated in this study. We contemplate that the avalanche was triggered due to snow pack existence on favorable slope in combination with different meteorological conditions and anomalous ground vibration. The avalanche occurrence clock was advanced by two earthquakes: M 4.1 at a distance ∼ 125 km that occurred about 21 h before and another comparatively larger (M 5.6) earthquake that occurred comparatively at larger distance (∼ 370 km) and longer time (∼ 25 days) before which have significantly changed the loading conditions. The latter event (M 5.6) has imparted maximum peak dynamic stress and cumulative seismic moment a month before the avalanche. Interestingly the avalanche occurred within the seismic coda of M 2.8 earthquake from Hindu Kush region, located at 560 km distance. Although the size and its expected impact on avalanche might be minor, its role in instantaneous triggering cannot be ruled out. Even smaller events at larger distance have been reported to cause snow avalanches in same environments. The presence of cracks within the avalanche was further weaken by persistence of extremely low temperature (lowest in the past decade), causing high precipitation rate along with altering the mechanical properties of the weak layer within the snow pack. Robust wind pressure pattern highest and lowest in March and April 2012, respectively, might be responsible for abrupt changes in loading conditions. [ABSTRACT FROM AUTHOR]

Of all natural disasters, those especially liable to exhaust capacity are those that occur without a precedent, and cause surprise to public administration officials. This paper addresses this issue. Surprise can be mitigated by considering downward counterfactuals, which can be viewed as contributing to surprise management. These are alternative realizations of historical events, where things turned for the worse. Disaster risk may be mitigated by focusing on downward counterfactuals. Particular focus is given to the earthquake and volcanic risk at Campi Flegrei, in the Naples region of Italy, where the bradyseism crisis of 1982–1983 is considered from a downward counterfactual perspective. [ABSTRACT FROM AUTHOR]

Urban geohazards have been frequently triggered by extreme natural events in recent decades. In July 2021, the extreme rainfall in Zhengzhou, China killed 292 people, left 47 people missing, and caused thousands of ground collapses. This disaster alarms for the assessment of urban geological safety around the world. Strengthening the assessment of urban geological safety and preventing catastrophes caused by potential extreme natural events are essential in urban construction. [ABSTRACT FROM AUTHOR]

Many nations face challenges in assessing, understanding, and responding to the time-dependent nature of disaster risk. Changes in the intensity of occurrences of extreme events coupled with changes in vulnerability and exposure alter the impacts of natural hazards on society in mostly negative ways. Here an interrelationship between natural hazard (NH), climate change (CC), vulnerability (V), exposure (E), and decisionmaking (DM) is considered. While NHs trigger disasters and CC is likely to intensify occurrences of disasters, V and E present major drivers of disasters. Informed DM on disaster risk reduction should be based on scientific evidence from NH and CC, knowledge of V and E, and relevant options for actions on preventive disaster measures as a part of preparedness and public awareness. [ABSTRACT FROM AUTHOR]

As a frequent natural disaster, landslides incur significant economic and human losses worldwide. The main idea of this paper is to propose novel integrative models for landslide susceptibility evaluation in a prone area of Chaharmahal va Bakhtiari Province in Iran. To do this, four metaheuristic techniques, namely chimp optimization algorithm (ChOA), crow search algorithm (CSA), satin bowerbird optimization (SBO), and water cycle algorithm (WCA) are used to supervise the training of an artificial neural network (ANN). A spatial database is created by 170 historical landslides and 14 most common conditioning factors. The models are optimized in terms of hyper-parameters and elite ones are then used to produce the susceptibility maps. During the training phase, all models could acquire a reliable understanding of the landslide pattern. The obtained accuracy index of area under the receiving operating characteristic curve (AUROC) showed that the maps produced by the WCA-ANN (AUROC = 0.925) and SBO-ANN (AUROC = 0.900) are more accurate than those of the ChOA-ANN (AUROC = 0.851) and CSA-ANN (AUROC = 0.855). Considering this assessment, the suggested hybrid models are reliable enough for landslide susceptibility modeling. Accordingly, the generated susceptibility map can be used for urban planning and generating alert systems over the studied area. [ABSTRACT FROM AUTHOR]

Lahars pose a significant risk to communities, particularly those living near snow-capped volcanoes. Flows of mud and debris, typically but not necessarily triggered by volcanic activity, can have huge impacts, such as those seen at Nevado Del Ruiz, Colombia, in 1985 which led to the loss of over 23,000 lives and destroyed an entire town. We surveyed communities around Mount Rainier, Washington, United States, where over 150,000 people are at risk from lahar impacts. We explored how factors including demographics, social effects such as perceptions of community preparedness, evacuation drills, and cognitive factors such as risk perception and self-efficacy relate to preparedness when living within or nearby a volcanic hazard zone. Key findings include: women have stronger intentions to prepare but see themselves as less prepared than men; those who neither live nor work in a lahar hazard zone were more likely to have an emergency kit and to see themselves as more prepared; those who will need help to evacuate see the risk as lower but feel less prepared; those who think their community and officials are more prepared feel more prepared themselves; and benefits of evacuation drills and testing evacuation routes including stronger intentions to evacuate using an encouraged method and higher self-efficacy. We make a number of recommendations based on these findings including the critical practice of regular evacuation drills and the importance of ongoing messaging that focuses on appropriate ways to evacuate as well as the careful recommendation for residents to identify alternative unofficial evacuation routes. [ABSTRACT FROM AUTHOR]

Understanding public perceptions of sea level rise (SLR) is essential for effective risk communication in coastal areas. Using cross-sectional data from a representative survey of 1042 Louisiana residents, we measured the role of sociodemographic factors (age, gender, education, income, race, and political affiliation), contextual factors (distance to coast, geographic vulnerability, perceived extreme weather, home ownership, and presence of children in the household), media measures (local television, local newspaper, and satisfaction with media coverage), and perceived causes of coastal land loss (natural erosion from waves, hurricane activity, oil and gas industry activity, and U.S. Army Corps of Engineers activity) on SLR risk salience. Ordinal logistic analysis showed perceived extreme weather and geographic vulnerability to be strong and positive predictors of SLR risk salience. Implications for risk communication are discussed. [ABSTRACT FROM AUTHOR]

This article builds upon disaster scholarship that suggests community resilience is driven by six capacities: social, economic, physical, human, institutional, and environmental. Together, these capacities constitute a conceptual framework that can be used to investigate and assess community resilience. While recent scholarship has provided insights into how resilience operates in large communities, there remain questions about whether this conceptual framework is appropriate for the study of resilience in small communities. To narrow this knowledge gap, we conducted interviews with twenty-six subjects from three small Texas communities affected by Hurricane Harvey: City of Dickinson; City of Port Aransas; and Town of Refugio. Analysis of the interview data confirms that the six capacities of resilience provide an appropriate framework for the investigation of resilience in small communities. Given the complex and dynamic nature of community resilience, the findings also suggest that it is unlikely policymakers will be able to develop a unified policy solution for hazard events that is appropriate for all communities. Rather, policymakers need to consider community-based resilience solutions, driven by local strengths and weaknesses, that facilitate the reduction of risks associated with hazard events. [ABSTRACT FROM AUTHOR]

Sea-level rise is causing coastal inundation events in estuaries, harbours, bays, and tidal rivers to happen more often as predictable daily high and low tides reach higher levels. This can lead to coastal inundation happening under benign weather conditions, as flood thresholds are exceeded due to tides alone without the influence of storm surges or other phenomena. As such, changes in frequency of this 'tide-only' inundation may be a useful metric to quantify the role that sea-level rise plays in modulating the risk of coastal inundation from high still water levels. Here we present a conceptual model for 'tide-only' inundation and propose a practical methodology to formulate tide-only inundation statistics: estimates, historical trends, and future projections. This enables this emerging natural hazard to be fully incorporated into new and existing coastal risk assessment frameworks and considered in coastal management and planning strategies at local and national levels. Further, it leads to a framework that can quantify the role that tides play in coastal flooding as sea levels rise. [ABSTRACT FROM AUTHOR]

A number of new winter sports facilities were constructed in the city of Erzurum for 2011 FISU—Universiade Winter Games, some of which constituted the first examples in Turkey. One of those is the ski-jumping complex, which hosts 5 runways along with a cluster of structures in various sizes and annexes, complementing the runways. On the northern slope of Kiremitlik Hill, where the complex is situated, a landslide occurred on 15th July of 2014, leading into complete collapse of the runways and major damage to the entire facility. This study presents a technical summary and forensic analysis of the formation of this natural hazard to illuminate the causes that cumulatively led to this engineering failure that created a massive material loss. In this work, we investigate the issue from geological, geophysical and geotechnical perspectives to illuminate the true causes of this engineering failure. We also hope that this technical evaluation provides an example for engineers as well as public administrators not to overlook the critical ground conditions and well-established design principles of civil engineering. [ABSTRACT FROM AUTHOR]

In recent years, the frequency, intensity, and severity of wildfires have been on the rise due to various environmental factors. Several studies show that the strategic application of fuel treatments is effective at altering fire behavior and its spread patterns. Effective planning for mitigating future expected losses under wildfire risk is a complex challenge that requires the integration of fire spread, simulation, and optimization models as well as the inclusion of multiple objectives into a unified framework. Previous works simplify the analysis by valuing the landscape regions using a unique objective (e.g., minimize the average expected area burned) or a predefined objective function. However, such an assumption is a simplification of the real system as multiple parts of the landscape have different values based on factors such as the presence of human settlements and infrastructure, availability of environmental services, and forest health. In this work, we expand these previous attempts by providing an integrated framework to naturally include and weight multiple objectives into the optimization model and analyze the trade-off between present objectives and future protection against wildfire risk. We study three key regions based on their recent fire history, landscape diversity, and demographic variety to quantify the impact of multiple objectives in landscape management. We obtain treatment plans using various combinations of these layers reflecting how different priorities of the decision-makers could affect treatment policies. [ABSTRACT FROM AUTHOR]

A multi-criteria risk analysis to identify and to rank the most critical UNESCO World Heritage Sites (WHSs) in Europe was implemented in the framework of the JPI-CH PROTHEGO project. The presented approach considers three natural geo-hazards (i.e. landsliding, seismic shaking and volcanic activity) for which homogenous European hazard maps are available. The methodology is based on a quantitative and reproducible heuristic assessment of risk through the development of a new UNESCO Risk Index (URI), which combines the level of hazard with a potential damage vector. The latter expresses the expected level of damage as a function of the type of heritage site (monuments, cultural routes, rock-art sites, cultural landscapes, earthworks/hominid sites, walls and natural sites), the position with respect to the ground (underground or overground) and the hazard type. The methodology was applied both to the entire WHS site and to the different properties that compose the site, with the purpose of identifying areas, inside the same site, with different level of risk. At European scale, the spatial distribution of risk reflects the fact that only three hazards were implemented in the analysis so far, with highest values in the Mediterranean area due to the importance of seismic hazard. [ABSTRACT FROM AUTHOR]

The occurrence of 6.7-magnitude Hokkaido Eastern Iburi Earthquake on 6th September 2018 made local residents in Japan realise the underneath hazardous threat to their own safety and residential dwellings. Japan has faced various natural disasters for a long time, and Government chose to unveil these hazard data in details to the public to raise every one's alertness. Despite their long-term awareness of hazards, this short-term unexpected event should have impact on local real estate markets. Given the transaction data of properties and lands, this study used machine-learning algorithms to examine whether the unexpected hazard shock (i.e. 2018 Hokkaido Earthquake) or the observed local hazard information in geographic areas (i.e. long-term evaluation of each real estate) would be capitalised into the prices of residential properties and lands in the case of Hokkaido, Japan. It is assumed that the difference in the characteristics of disaster notification would alter individuals' risk perception and thus the evaluation of properties; compared to uncertain, infrequent occurrence of earthquakes in the unknown future (i.e. beyond the scope of objective estimation), the release of long-term hazardous information (tied to each property or land), which is more perceivable in near future, is more likely to be capitalised into real estate. It is found that housing/land attributes are still the key features to real estate values in Hokkaido. In comparison with short-term unexpected hazard shock (i.e. 2018 Earthquake), the long-term hazard threats are more influential to prices of properties and lands. This is possibly due to people's awareness of the hazard conditions of local communities while deciding where to reside. [ABSTRACT FROM AUTHOR]

This study examines the hypothesis that social capital can be a foundation for community disaster resilience with an analysis of empirical findings from the August 2018 earthquake recovery on Gili Trawangan, Indonesia, a globally known coastal tourism destination. Positive links between community social capital and community disaster resilience are hypothesized, but the extent to which an iterative and interdependent relationship is co-shaping both is less understood. Social capital can enable collective action, providing self-organized social, psychological, financial and material resources following a disaster, that may otherwise need to be provided externally. In turn, disasters create collective action problems where collective response and recovery process are needed, creating an institutional space where the degree of usefulness, meaning and function of social capital can be shaped, recognized and drawn upon, often where external aid is insufficient. These relationships can be observed following disasters, because individuals and communities are often linked through emotive and meaningful sequences of common experiences, actions and activities. Findings descriptively detail Gili Trawangan's response and recovery process through the events and activities that occurred, and are then theoretically analyzed with a social capital framework including bonding (within group), bridging (between group) and linking (across power and institutional) ties. Three conclusions can be summarized. (1) Community social capital and disaster resilience are iteratively co-shaped through collective experiences, actions and activities. (2) Understanding context is critical for understanding if and to what degree this relationship exists. (3) The mechanism through which social capital enhances resilience is that it can enable collective action that can lead to the provision of needed aid and services. [ABSTRACT FROM AUTHOR]

Natural hazards affect different parts of living organisms. One of these hazards is aerosols. Addressing this issue in areas that suffer from this hazard is of critical importance. Scientific research over the past two decades has shown that aerosol particles are one of the main pollutants from the perspective of public health and health. The purpose of the present study is to monitor and model aerosol temporal and spatial variations in Iran. Aerosols or airborne particles with health effects such as heart, vascular and respiratory diseases are associated. For this purpose, MODIS (or Moderate Resolution Imaging Spectroradiometer) and NOAA (or National Oceanic and Atmospheric Administration) satellite data and BTD (or Brightness Temperature Difference) were used. Given the 20-year study period (2000–2019), the output of much satellite data was divided into four five-year periods to monitor aerosols with high accuracy. The results showed that aerosol values in terms of intensity and frequency of optical depth (AOD) increased over the 20-year time series, and its intensity was higher in the last 5 years. According to the results obtained from the NODIS and NOAA satellite data and comparing their outputs, NOAA satellite data were associated with outliers, which was significantly different from the other cohort data. For this reason, the MODIS satellite image output was used to monitor aerosol images. The innovation of the present study is the use of remote sensing science to monitor the effects of aerosols on the environment and human's health. According to the results from MODIS satellite data, the maximum optical depth (AOD) of the aerosols is for July 2003 with a value of 0.63, but according to the NOAA satellite data output, the maximum optical depth (AOD) of the aerosols is for March 2013 with a value of 2.54. As the values of aerosols increase in frequency and intensity and the areas with the highest intensity of aerosols have been identified, it can be overcome by careful planning of their problems. Areas, where the amount and volume of aerosols were higher, should be observed in health protocols. By preventing and maintaining good hygiene, the negative effects of aerosols can be reduced. [ABSTRACT FROM AUTHOR]

Shallow landslides have posed significant threats to humans around the world. In order to reduce landslide disaster risk, the effectiveness of early warning systems and hazard zonation work needs to be improved. This research attempted to couple a landslide simulation model (LS-RAPID model) and a hydrological model (Rainfall-Runoff-Inundation (RRI) model) to exploit the advantages of each model for simulating and predicting landslide hazard (location and timing). The pilot area is a small catchment where a shallow landslide happened in July 2015 after 2 days of heavy rain. The landslide buried 3 houses and killed 8 people in Cao Thang Ward, Halong City, Vietnam. A soil sample was collected from the sliding surface and tested using an undrained ring-shear apparatus ICL-2 in the undrained condition. A thickness map of the potential sliding material was interpolated from the relationship between the depth of sandy soil layer and slope (based on 12 soil drill locations) and updated through field surveys in the study area. Different pore water pressure ratio scenarios were applied in the LS-RAPID model to simulate in 3D the initiation and motion of the rapid shallow landslide to create different hazard maps. The subsurface water level was monitored at two locations on the top of the shallow landslide. Based on the observed subsurface water and rainfall data, the RRI model was calibrated and then integrated with the LS-RAPID scenarios to generate Risk Index maps. The simulation results from the newly proposed coupled hydrological-geotechnical framework were compared with those from the observed landslide hazard and showed the reliability to predict the spatial and temporal occurrence of landslide hazard. This could be very useful for supporting decision-makers in rainfall-induced landslide hazard early warning and land use planning. [ABSTRACT FROM AUTHOR]

The study of landslides in the Inaouene watershed (northeastern Morocco) provides information on the relationships between landslides and morpho-structural analysis. Landslides affect part of the slopes and slopes of the valley. The configuration of this relationship is controlled by the combination of several predisposing factors. Two localities were studied, located in similar morpho-structural contexts, but characterized by a different lithology. The first determining factor was lithology, in particular the dominance of friable geological formations, especially marls in the locality of Chebabate and limestone soft formations in the locality of Tahla. The second factor was the tectonics, which is well individualized in the limestone of Tahla; in spite of friable lithology of the marls of Chebabate, one manages to disturb traces of the tectonics notably with the level of intercalation of the sandstone benches. Another factor that controls the dissection and the evolution of the landslides is the precipitation by the effect of abundance of the water of impregnation in the formations. The fieldwork is devoted to the measurement of the different faults encountered in the two localities to make the stereographic projection in order to elaborate canvas. The principal objective of this study is to find the relation between the evolution of the risks of erosion and landslide as well as the various factors, who control their spatiotemporal evolution. The results obtained will help managers and decision-makers in the development of watersheds in order to take the necessary steps to reduce the negative impact of this natural hazard on the environment, the population and their property. [ABSTRACT FROM AUTHOR]

Petroleum industry can create enormous wealth and employment opportunities, which is one of the pillars of the national economy. The transportation conditions of petroleum products are complex and changeable. The natural disaster–induced dangerous chemical leakage may damage the ecological environment, which leads to substantial economic losses. It significantly undermines the sustainable development agenda. Therefore, assessing the possibility of leakage and the potential environmental damages becomes a primary task to decision-makers to formulate maintenance plans. This paper evaluated the risk of an oil pipeline leakage under the regional geological disasters. Specifically, risk assessment indicators system was established considering the common threat of multiple natural hazards in the region. The sensitivities of the influence factors were determined using the combined GIS and the contribution rate model. The fuzzy analysis approach was used to process the expert's judgment to obtain a real-time disaster hazard. Meanwhile, in terms of the analysis of pipeline failure causes, the assessment system of disaster resistance ability was developed to determine the possibility of leakage. The leakage-induced environmental losses were quantified by monetary quantification. Finally, the level of environmental risk was determined using a 5 × 5 probability-currency matrix. Case results show that the risk level is medium, thereby appropriate maintenance measures need to be taken to reduce the risk. Overall, this study provides necessary help to prevent the leakage of petroleum products in transportation. Also, the environmental risk presented in the form of currency can promote non-environmental professional risk decision-makers better understand the degree of risk. [ABSTRACT FROM AUTHOR]

Background: Recently, many parts of Hungary, as well as central Europe, have been hit by successive extreme climatic events. The main aim of this research was to analyze hydrological and agricultural drought episodes in the Debrecen Region in eastern Hungary from 1950 to 2010. Thus, data of monthly precipitation were collected and tested. After that, three indices were applied, the Precipitation Concentration Index (PCI), dry Precipitation Concentration Index (dPCI), and the Standardized Precipitation Index (SPI). Meanwhile, the correlation between SPI and the normalized difference vegetation index (NDVI) was calculated. Results: The results showed that the PCI values ranged between 9.44 and 15.8 with an average of 11.8, while the dPCI values ranged between 8.6 and 20.7 with an average of 10.9, which indicates heterogeneity in rainfall distribution from year to year. More than 103 events of severe agricultural drought were detected for the whole studied period. In connection to this, severe hydrological drought was recorded in 16% of the total monthly rainfall events from 1950 to 2010. Interestingly, a significant correlation was obtained between SPI-3, -6 (i.e., drought), and NDVI in the summer season. Conclusions: The SPI index could provide an easy tool for drought monitoring meanwhile drought evaluation and monitoring should be taken seriously in the central Europe. [ABSTRACT FROM AUTHOR]

Geological structures precondition hillslope stability as well as the processes and landslide mechanisms which develop in response to deglaciation. In areas experiencing glacier retreat and debuttressing, identifying landslide preconditions is fundamental for anticipating landslide development. Herein, the ~ 150 M m3 Mueller Rockslide in Aoraki/Mount Cook National Park, New Zealand, is described; and we document how preconditions have controlled its morphology and development in response to thinning of the adjacent Mueller Glacier. A combination of geomorphological and geotechnical mapping—based on field, geophysical and remote sensing data—was used to characterise the rock mass and morphology of the rockslide and surrounding hillslope. Mueller Rockslide is identified as a rock compound slide, undergoing dominantly translational failure on a dip slope. The crown of the rockslide is bounded by several discontinuous, stepped scarps whose orientation is controlled by joint sets; these scarps form a zone of toppling that is delivering rock debris to the main rockslide body. Surface and subsurface discontinuity mapping above the crown identified numerous joints, fractures and several scarps that may facilitate continued retrogressive enlargement of the rockslide. The presence of lateral release structures, debuttressing of the rockslide toe and steeply dipping bedding suggest that the rockslide may be capable of evolving to a rapid failure. [ABSTRACT FROM AUTHOR]

In the study area, the geophysical properties of gypsum and filling materials, karst structures that developed in gypsum, and groundwater level were investigated. According to the results of geophysical studies, it was thought that the depression and dissolution/weathering areas in the karst could be completely or partially filled with water, air, gypsum particles, and one, several, or all of the alluvial units. It was determined that resistivity and S-wave velocity (average < 26.4 Ω m, ~ 220 m/s) in these areas were low and corresponded to low seismic velocity zones (LSVZ). In fill and cover unit areas where water did not affect or was less affected, resistivity and S-wave velocity (< 67.3–131 Ω m, average < 245 m/s) were determined low. It was found out that resistivity and S-wave velocity of the gypsum bedrock was very high (> 10,263–14,412 Ω m, average > 655 m/s), and resistivity and S-wave velocity of LSVZ in the gypsum surfaced far from the source were lower (< 91.3 Ω m, ~ 585 m/s) compared to the gypsum bedrock. Therefore, it was observed that the resistivities and seismic velocities of the gypsum in the surfaced area were higher compared to the depression area. The results were associated with karst as the main reason for dissolutions and depressions, because the water draining/leaking/spreading from the water source progressed by creating low-resistivity areas in the permeable filling material and the groundwater was near the surface. Therefore, karst structures will probably continue to develop in this area, and natural hazards may occur in the future. [ABSTRACT FROM AUTHOR]

Advancement in technology has contributed to increment in complexity of systems and infrastructures. Furthermore, it has complicated the management of systems to deal with natural hazards. Input–output inoperability model (IIM) is a simple method to characterize the impacts of natural hazards on interconnected infrastructures. In this paper, the impacts of a flood hazard on six critical infrastructures in Tehran metropolitan have been assessed by using IIM. The computational results show that energy and transportation infrastructures are the most influencing infrastructures, while emergency services and healthcare infrastructures are the most influenced infrastructures. All data required to evaluate this case study have been collected using questionnaires and converted to fuzzy interdependency values. To increase decision-making power, the developed fuzzy matrix has been arranged for different risk levels (from absolutely optimistic to absolutely pessimistic) and confidence levels (from absolutely confident to absolutely non-confident). Afterward, the interdependency matrix has been deffuzified, and inoperability of infrastructures has been calculated by the IIM for seven different initial conditions. Finally, a sensitivity analysis has been conducted to incorporate the risk levels and confidence levels to determine values of inoperability under the above-mentioned conditions. The ranking for both of the influencing and the influenced infrastructures has also been provided. This ranking helps decision makers to manage natural hazard risks effectively by appropriate resource allocation. It also helps to realize the interdependencies among infrastructures and to determine the inoperability of infrastructures before natural hazards. This would help decision makers to mitigate the risk and prepare the society well in advance. [ABSTRACT FROM AUTHOR]

Most parametric models of earthen dam failure require a breach progression curve to establish an outflow hydrograph, but well-documented breach progression data obtained during dam failure are rarely available. As an alternative, the potential for developing outflow hydrographs from observed variations in reservoir water level is explored. The parameter retrieval process is based on minimizing the difference between the model solution and the water level observations. The retrieved optimal parameters are used to build an outflow hydrograph, which is then linked with a routing model to identify the flood-prone areas downstream. The suggested approach is tested in a case study of a small reservoir and is validated with the inundation area recorded in an on-site investigation. The disparity between the simulated and recorded inundation areas is approximately 7~8%, and the difference in water depth is small at 0.03~0.09 m. Overall, the suggested approach provides reasonable accuracy for the test site. [ABSTRACT FROM AUTHOR]

Natural hazards pose significant threats to different communities and various places around the world. Failing to identify and support the most vulnerable communities is a recipe for disaster. Many studies have proposed social vulnerability indices for measuring both the sensitivity of a population to natural hazards and its ability to respond and recover from them. Existing techniques, however, have not accounted for the unique strengths that exist within different communities to help minimize disaster loss. This study proposes a more balanced approach referred to as the strength-based social vulnerability index (SSVI). The proposed SSVI technique, which is built on sound sociopsychological theories of how people act during disasters and emergencies, is applied to assess comparatively the social vulnerability of different suburbs in the Wollongong area of New South Wales, Australia. The results highlight suburbs that are highly vulnerable, and demonstrates the usefulness of the technique in improving understanding of hotspots where limited resources should be judiciously allocated to help communities improve preparedness, response, and recovery from natural hazards. [ABSTRACT FROM AUTHOR]

This paper presents results of a study which examined how a mandatory wildfire evacuation affected members of Whitefish Lake First Nation 459, in Alberta, Canada. A qualitative case study approach was used, and semi-structured interviews were completed with 45 band members to learn about their evacuation experiences during the wildfire evacuation in May 2011 and explore the factors that complicated the evacuation process and put further strain on the evacuees and First Nation. This evacuation caused considerable distress for evacuees and had negative effects for the First Nation. Factors that affected evacuation experiences included: (1) transportation issues compounded by cultural land-use activities, (2) fear of home loss compounded by existing housing shortages, (3) information and lack of media interest, (4) language, (5) poverty, (6) large multi-generational families, (7) health concerns, and (8) reimbursement of evacuation-related expenses to the community. An overarching factor that affected the entire evacuation was jurisdiction. Based on these findings, recommendations are provided for emergency managers on improving wildfire evacuation experiences for Indigenous peoples. [ABSTRACT FROM AUTHOR]

Research conducted among socially vulnerable populations caught in the paths of natural disasters represents the forefront of our understanding the health-related impacts of climate change. In this study, we analyze individual-level longitudinal data from the Nicaragua Living Standards and Measurement Survey (N = 3474) in order to ascertain the influence of disaster displacement arising from the Hurricane Mitch event upon two communicable disease outcomes: diarrheal disease and respiratory disease. First, multinomial logistic regression analyses demonstrate that individuals from households headed by women, as well as from households with low levels of consumption expenditures, experienced greater odds of displacement to shelters in the aftermath of Mitch. Second, two-way fixed-effects regression analysis demonstrates that shelter displacement acts as independent risk increasing the odds of respiratory disease, net of socioeconomic and demographic covariates. Our findings draw attention to the confluence of far-reaching entrenched social and economic disparities that create linked disaster displacement and communicable disease vulnerabilities. [ABSTRACT FROM AUTHOR]

We examine how residents of Nawairuku, an interior village in Ra, Fiji, are experiencing and responding to recent social and ecological changes. An analysis of data collected using semi-structured interviews with 27 households reveals that household adaptability - the ability or capacity to adapt to the impacts of climatic variations - depends on access to livelihood assets. All households have access to social capital through familial networks, which lessens the burden of extreme weather events, namely cyclones and flooding. Households with access to tangible assets such as land and the equipment and resources to utilize it, together with intangible assets like motivation and knowledge are better positioned to adapt their agricultural practices to changing climatic conditions. Households headed by a capable individual were also better positioned to adapt. We conclude that remoteness promotes self-sufficiency and initiative, and access to livelihood assets influences household capacity to adapt. [ABSTRACT FROM AUTHOR]

This article constitutes an effort towards providing an academic overview and grounding for the concept of capacities in the context of disaster studies and disaster risk reduction. Capacities refer to the set of diverse knowledge, skills and resources people can claim, access and resort to in dealing with hazards and disasters. They are both an individual and collective attributes. Everyone possesses a unique set of knowledge, skills and resources that are often shared and combined with those of relatives, kin, neighbours, etc. People's capacities are not necessarily place based, but they are endogenous to the community of people who share and combine them in dealing with the same hazards and disasters. They further reflect people's everyday life as it is very seldom that those affected by disasters resort to extraordinary measures to face harmful events. In practice, capacities allow for active prevention to avoid hazards to occur in the first place. They are further tapped to foster preparedness in facing impending hazards and respond to disasters. Capacities also prove invaluable in coping with the lingering effects of disasters and in recovering on the longer term. Harnessing capacities should therefore be an integral part of disaster risk reduction strategies as recognised in the widespread practice of vulnerability and capacity/ies assessment. Ultimately, harnessing capacities for reducing the risk of disaster requires to foster people's genuine participation in assessing and enhancing their existing knowledge, skills and resources. [ABSTRACT FROM AUTHOR]

Different methodologies are used for modelling flow-like landslides. A common critical point concerns the flooding into town areas, which cannot be assimilated straight to a morphology, especially, when the urban tissue is very irregular with narrow streets and odd setting of buildings, so that discretization processes of approximating numerical methods have to be carefully examined in their limits. A semi-empirical approach by the computational paradigm of cellular automata is here considered with SCIDDICA, a competitive (related to PDE approach) cellular automata model for 3-dimensions simulation of flow-like landslides. This paper presents innovations to the transition function of SCIDDICA-SS2, which manage opportunely building data in the cells corresponding to the urban tissue. The novelties of the transition function need a theorem, here demonstrated which regards the Algorithm of Minimization of Differences in the new context of inhomogeneous cells. This progress permits to simulate the complete evolution of landslides, from the detachment area to its exhaustion almost on the same precision level. This is an advantage for hazard and risk analyses in threatened zones. Improved SCIDDICA-SS2 was applied successfully to all the well-known 2009 debris flows of Giampilieri Superiore (Sicily) also in comparison with simulation results of the previous versions. [ABSTRACT FROM AUTHOR]

Flash floods are one of the major natural hazards occurring in small streams with a negative effect on the country as well as on human lives. Heavy rainfall occurred on July 20, 2014 and July 21, 2014 and caused severe surface water flooding and a flash flood in the Malá Fatra National Park (Slovakia). The most affected was Vrátna Valley with the Varínka stream. This study presents a reconstruction and post-event analysis of a flash flood on small ungauged basin located in this protected area of Slovakia. The reconstruction included hydraulic terrain measurements on estimating the flood’s culmination and documenting the flood’s development. The measurements were taken at three cross sections of the Varínka stream. This paper is focused mainly on post-event analysis of the Varínka stream in two profiles: Stráža (gauged profile) and Tiesňavy (ungauged cross section). Subsequently, the extremeness of the flash flood was preliminary evaluated. Results of the post-event analysis showed that the July 2014 flood was not the highest flood in this area despite its catastrophic consequences. By studying historical materials, we came to the conclusion that in the past (e.g. in 1848 or 1939) some devastating floods in this area had occurred, which had disastrous consequences for the population. The second part of the study is focused on comparing this flash flood with three major floods which have occurred in Slovak territory since 1998. The first flood occurred on the 20th of July, 1998 on the Malá Svinka stream, and the two others are floods which occurred on the 7th of June, 2011 in the Small Carpathian Mountains: on the Gidra stream in Píla village and on the Parná stream in Horné Orešany village. Such comparison of flash floods from different geographical regions and different rainfall events can provide comprehensive information about their regimes, threats and disastrous effects. [ABSTRACT FROM AUTHOR]