Showing papers in "Natural Hazards in 2014"
TL;DR: Zhang et al. as discussed by the authors quantitatively studied the impact of China's economic growth, industrial structure and urbanization on carbon emission intensity based on the historical data from 1978 to 2011.
Abstract: China’s macroeconomic policy framework has been determined to ensure steady growth, adjust the industrial structure and advance the socioeconomic reforms in recent years. And urbanization is supposed to be one of the most important socioeconomic reform directions. Meanwhile, China also committed to reduce carbon emissions intensity by 2020, then it should be noted that what kind of impact of these policy orientations on carbon emission intensity. Therefore, based on the historical data from 1978 to 2011, this paper quantitatively studies the impact of China’s economic growth, industrial structure and urbanization on carbon emission intensity. The results indicate that, first, there is long-term cointegrating relationship between carbon emission intensity and other factors. And the increase in the share of tertiary industry [i.e., the ratio of tertiary industry value added to gross domestic product (GDP)] and economic growth (here we use the real GDP per capita) play significant roles in curbing carbon emission intensity, while the promotion of population urbanization (i.e., the share of population living in the urban regions of total population) may lead to carbon emission intensity growth. Second, there exists significant one-way causality running from the urbanization rate and economic growth to carbon emission intensity, respectively. Third, among the three drivers, economic growth proves the main influencing factor of carbon emission intensity changes during the sample period.
392 citations
TL;DR: An insight into the current status of the development of the OpenQuake engine is provided and a comprehensive description of each calculator is presented, with example results.
Abstract: The Global Earthquake Model aims to combine the main features of state-of-the-art science, global collaboration and buy-in, transparency and openness in an initiative to calculate and communicate earthquake risk worldwide. One of the first steps towards this objective has been the open-source development and release of software for seismic hazard and risk assessment called the OpenQuake engine. This software comprises a set of calculators capable of computing human or economic losses for a collection of assets, caused by a given scenario event, or by considering the probability of all possible events that might happen within a region within a certain time span. This paper provides an insight into the current status of the development of this tool and presents a comprehensive description of each calculator, with example results.
245 citations
TL;DR: In this paper, the authors studied the overall impacts of debris flows on a global scale from 1950 to 2011 and provided evidence that higher levels of fatalities tend to occur in developing countries, characterized by significant poverty, more corrupt governments, and weaker healthcare systems.
Abstract: Debris flows cause significant damage and fatalities throughout the world. This study addresses the overall impacts of debris flows on a global scale from 1950 to 2011. Two hundred and thirteen events with 77,779 fatalities have been recorded from academic publications, newspapers, and personal correspondence. Spatial, temporal, and physical characteristics have been documented and evaluated. In addition, multiple socioeconomic indicators have been reviewed and statistically analyzed to evaluate whether vulnerable populations are disproportionately affected by debris flows. This research provides evidence that higher levels of fatalities tend to occur in developing countries, characterized by significant poverty, more corrupt governments, and weaker healthcare systems. The median number of fatalities per recorded deadly debris flow in developing countries is 23, while in advanced countries, this value is only 6 fatalities per flow. The analysis also indicates that the most common trigger for fatal events is extreme precipitation, particularly in the form of large seasonal storms such as cyclones and monsoon storms. Rainfall caused or triggered 143 of the 213 fatal debris flows within the database. However, it is the more uncommon and catastrophic triggers, such as earthquakes and landslide dam bursts, that tend to create debris flows with the highest number of fatalities. These events have a median fatality count >500, while rainfall-induced debris flows have a median fatality rate of only 9 per event.
213 citations
TL;DR: In this paper, a data-driven technique of an evidential belief function (EBF), which is in the category of multivariate statistical analysis, was used to map the land subsidence-prone areas.
Abstract: Land subsidence is one of the frequent geological hazards worldwide. Urban areas and agricultural industries are the entities most affected by the consequences of land subsidence. The main objective of this study was to estimate the land subsidence (sinkhole) hazards at the Kinta Valley of Perak, Malaysia, using geographic information system and remote sensing techniques. To start, land subsidence locations were observed by surveying measurements using GPS and using the tabular data, which were produced as coordinates of each sinkhole incident. Various land subsidence conditioning factors were used such as altitude, slope, aspect, lithology, distance from the fault, distance from the river, normalized difference vegetation index, soil type, stream power index, topographic wetness index, and land use/cover. In this article, a data-driven technique of an evidential belief function (EBF), which is in the category of multivariate statistical analysis, was used to map the land subsidence-prone areas. The frequency ratio (FR) was performed as an efficient bivariate statistical analysis method in order compare it with the acquired results from the EBF analysis. The probability maps were acquired and the results of the analysis validated by the area under the (ROC) curve using the testing land subsidence locations. The results indicated that the FR model could produce a 71.16 % prediction rate, while the EBF showed better prediction accuracy with a rate of 73.63 %. Furthermore, the success rate was measured and accuracies of 75.30 and 79.45 % achieved for FR and EBF, respectively. These results can produce an understanding of the nature of land subsidence as well as promulgate public awareness of such geo-hazards to decrease human and economic losses.
189 citations
TL;DR: In this article, a number of examples are presented to substantiate that submarine landslides have occurred along most continental margins and along several volcano flanks, and the need for data acquisition and analyses, laboratory experiments, and more sophisticated numerical modelling for improved understanding and hazard assessment of landslide tsunamis are elaborated.
Abstract: A number of examples are presented to substantiate that submarine landslides have occurred along most continental margins and along several volcano flanks. Their properties of importance for tsunami generation (i.e. physical dimensions, acceleration, maximum velocity, mass discharge, and travel distance) can all gain extreme values compared to their subaerial counterparts. Hence, landslide tsunamis may also be extreme and have regional impact. Landslide tsunami characteristics are discussed explaining how they may exceed tsunamis induced by megathrust earthquakes, hence representing a significant risk even though they occur more infrequently. In fact, submarine landslides may cause potentially extreme tsunami run-up heights, which may have consequences for the design of critical infrastructure often based on unjustifiably long return periods. Giant submarine landslides are rare and related to climate changes or glacial cycles, indicating that giant submarine landslide tsunami hazard is in most regions negligible compared to earthquake tsunami hazard. Large-scale debris flows surrounding active volcanoes or submarine landslides in river deltas may be more frequent. Giant volcano flank collapses at the Canary and Hawaii Islands developed in the early stages of the history of the volcanoes, and the tsunamigenic potential of these collapses is disputed. Estimations of recurrence intervals, hazard, and uncertainties with today’s methods are discussed. It is concluded that insufficient sampling and changing conditions for landslide release are major obstacles in transporting a Probabilistic Tsunami Hazard Assessment (PTHA) approach from earthquake to landslide tsunamis and that the more robust Scenario-Based Tsunami Hazard Assessment (SBTHA) approach will still be most efficient to use. Finally, the needs for data acquisition and analyses, laboratory experiments, and more sophisticated numerical modelling for improved understanding and hazard assessment of landslide tsunamis are elaborated.
177 citations
TL;DR: In this article, the social vulnerability of Indonesian districts to natural hazards, determining its driving factors and mapping its variations was quantified by using the Social Vulnerability Index (SoVI) approach.
Abstract: Indonesia is located in the Pacific Ring of Fire and situated at the joining point of four major world tectonic plates. Regions of Indonesia are highly prone to various natural hazards such as earthquakes, tsunamis and volcanic eruptions. Some recent major natural hazard events are the 2004 tsunami in Aceh and Nias and the 2010 Mount Merapi volcanic eruptions in Central Java. In parallel with advancement in knowledge of the existing hazards, the importance of social aspects of vulnerability in mitigating natural hazards has been acknowledged by the Indonesian government. However, to date, there is no institutionalized effort for assessing social vulnerability to natural hazards that would cover all the districts of Indonesia. Accordingly, no comprehensive profile of social vulnerability is available as basis information for developing strategies to prevent larger risk and losses and reduce vulnerability of communities in Indonesia. Only a few studies have been conducted in Indonesia on this field. This study attempts to fill this gap by quantifying the social vulnerability of Indonesian districts to natural hazards, determining its driving factors and mapping its variations. The social vulnerability index (SoVI) approach is utilized in this study. Three main driving factors affecting social vulnerability in Indonesia are found: ‘socioeconomic status and infrastructure,’ ‘gender, age and population growth’ and ‘family structure.’ The combination of SoVI with thematic map utilizing ArcView GIS can be used to identify districts with relative high social vulnerability level. The results can support the prevention, mitigation, preparedness, response and recovery programs of the impacts of natural hazards in Indonesia.
173 citations
TL;DR: In this paper, a measure based on Twitter activities that can be used to quantify the evolution of disasters and thus demonstrate temporal-spatial patterns of Twitter activities particularly near the coastline and in large urban areas during Hurricane Sandy was developed.
Abstract: This paper contributes to the understanding of disasters from the perspective of social media activities. We develop a measure based on Twitter activities that can be used to quantify the evolution of disasters and thus demonstrate temporal–spatial patterns of Twitter activities particularly near the coastline and in large urban areas during Hurricane Sandy. We also show a close relationship between hurricane damages and Twitter activities. Our findings suggest the potential of using social media activities for rapid damage assessment.
164 citations
TL;DR: Based on worldwide scholars' 3,004 papers published in 658 academic journals in the Web of Science database from 1991 to 2012, the authors quantitatively analyzes the global scientific performance and hot research areas in this field by adopting bibliometric method.
Abstract: Based on worldwide scholars’ 3,004 papers published in 658 academic journals in the Web of Science database on the topic of climate change vulnerability from 1991 to 2012, this paper quantitatively analyzes the global scientific performance and hot research areas in this field by adopting bibliometric method. The results show that (1) the vulnerability researches on climate change have experienced a rapid growth since 2006, and the publications are widely distributed in a large number of source journals, while the top two productive institutions are the University of East Anglia and Potsdam Institute for Climate Impact Research; (2) the cooperation at author level is on the rise, and there are closer relationships in institutional and national levels; (3) the most widely focused research topics in this field include health issues in the socioeconomic system, food security in the field of agricultural system and the issue of water resource management, etc.; (4) according to the papers from the top journals, we find that the research areas for climate change vulnerability in those publications are located in the ecological diversity, ecosystem service, water resource management and electric power supply, etc.
146 citations
TL;DR: The obtained results indicated that the use of GP for generating LSMs provides more accurate prediction in comparison with FR, LR, and ANN; GP model is superior to the ANN model because it can present an explicit formulation instead of weights and biases matrices.
Abstract: Without a doubt, landslide is one of the most disastrous natural hazards and landslide susceptibility maps (LSMs) in regional scale are the useful guide to future development planning. Therefore, the importance of generating LSMs through different methods is popular in the international literature. The goal of this study was to evaluate the susceptibility of the occurrence of landslides in Zonouz Plain, located in North-West of Iran. For this purpose, a landslide inventory map was constructed using field survey, air photo/satellite image interpretation, and literature search for historical landslide records. Then, seven landslide-conditioning factors such as lithology, slope, aspect, elevation, land cover, distance to stream, and distance to road were utilized for generation LSMs by various models: frequency ratio (FR), logistic regression (LR), artificial neural network (ANN), and genetic programming (GP) methods in geographic information system (GIS). Finally, total four LSMs were obtained by using these four methods. For verification, the results of LSM analyses were confirmed using the landslide inventory map containing 190 active landslide zones. The validation process showed that the prediction accuracy of LSMs, produced by the FR, LR, ANN, and GP, was 87.57, 89.42, 92.37, and 93.27 %, respectively. The obtained results indicated that the use of GP for generating LSMs provides more accurate prediction in comparison with FR, LR, and ANN. Furthermore; GP model is superior to the ANN model because it can present an explicit formulation instead of weights and biases matrices.
140 citations
TL;DR: In this paper, the authors outline the criteria and definitions relating to how global and multi-peril databases are operated, and the efforts being made to ensure consistent and internationally recognised standards of data management.
Abstract: Hundreds of natural catastrophes occur worldwide every year—there were 780 loss events per year on average over the last 10 years. Since 1980, these disasters have claimed over two million lives and caused losses worth US$ 3,000 billion. The deadliest disasters were caused by earthquakes: the tsunami following the Sumatra quake (2004) and the Haiti earthquake (2010) claimed more than 220,000 lives each. The Great East Japan Earthquake of 11 March 2011 was the costliest natural disaster of all times, with total losses of US$ 210 billion. Hurricane Katrina, in 2005, was the second costliest disaster, with total losses of US$ 140 billion (in 2010 values). To ensure that high-quality natural disaster analyses can be performed, the data have to be collected, checked and managed with a high degree of expertise and professionality. Scientists, governmental and non-governmental organisations and the finance industry make use of global databases that contain losses attributable to natural catastrophes. At present, there are three global and multi-peril loss databases: NatCatSERVICE (Munich Re), Sigma (Swiss Re) and EM-Dat (Centre for Research on the Epidemiology of Disasters). They are supplemented by numerous databases focusing on national or regional issues, certain hazards and specific sectors. This paper outlines the criteria and definitions relating to how global and multi-peril databases are operated, and the efforts being made to ensure consistent and internationally recognised standards of data management. In addition, it presents the concept and methodology underlying the NatCatSERVICE database, and points out the many challenges associated with data acquisition and data management.
136 citations
TL;DR: This article found that previous flood experience contributes to heightened perception of risk, increased preparedness of households, greater willingness to make household-level changes, greater communication with councils, and more advocacy for spatial planning to complement existing structural protection.
Abstract: Flood management decision-makers face significant challenges as the climate changes. The perceptions of those affected by floods are critical to the successful implementation of adaptation responses; risk perceptions are affected by how information is communicated and, in turn, perceptions influence expectations on flood risk managers to respond. The links between flood experience, risk perception, and responses by individual households were examined in the Hutt Valley, New Zealand, through a household survey, a workshop and interviews with local government practitioners. Two propositions were tested: (1) that flood experience can influence flood risk perceptions; and (2) that flood experience can stimulate increased risk reduction and adaptation actions where changing climate risk is likely. Perceptions of responsibility for flood management were also examined. The study found that previous flood experience contributes to heightened perception of risk, increased preparedness of households, greater willingness to make household-level changes, greater communication with councils, and more advocacy for spatial planning to complement existing structural protection. Flood-affected households had a stronger preference for central government and communities having flood risk responsibilities, in addition to local government. Those who lacked experience were more likely to be normalised to their prior benign experiences and thus optimistic about flood consequences. These results suggest that harnessing positive aspects of experience and communication of changing risk through engagement strategies could help shift the focus from citizens’ expectation that governments will always provide protection, to a citizen–local government–central government dialogue about the changing character of flood risk and its implications, and build a ‘risk conscious’ society in which ‘sharing and bearing’ is considered desirable.
TL;DR: In this article, the authors performed a brief overview on the basic definitions and evolution processes of vulnerability, resilience, and adaptation, and tentatively categorized past diverse thoughts of their relationships into three modalities, such as, vulnerability preference, resilience preference, and overlapped relationships.
Abstract: Vulnerability, resilience, and adaptation are three fundamentally inter-related concepts among such research communities as global environmental/climatic change, social-ecological and disaster risk science. However, their mutual relationships are still unclear so far particularly in the field of disaster risk reduction, which to some extent blocks the reasonable risk analysis and scientific decision making. This paper performed a brief overview on the basic definitions and evolution processes of vulnerability, resilience, and adaptation, and tentatively categorized past diverse thoughts of their relationships into three modalities, such as, vulnerability preference, resilience preference, and overlapped relationships. From a ''hit-damage-recovery-learning cycle'' insight and based on an empirical case study, we put forward two conceptual frameworks to address the rela- tionships of vulnerability, resilience, and adaptation within the disaster risk domain, and we further discussed their broader implications in terms of disaster risk management and social-ecological sustainability. In an attempt to bring together the analytical frameworks of vulnerability, resilience, and adaptation, this study indicates that a sustainable adapta- tion strategy to the unavoidable disasters or changes should not only seek to reduce the
TL;DR: In this paper, a GIS database on disastrous floods and landslides for the period 1865-2010, which is available in http://riskam.ul.pt/disaster/en.
Abstract: In the last century, Portugal was affected by several natural disasters of hydro-geomorphologic origin that often caused high levels of destruction. However, data on past events related to floods and landslides were scattered. The Disaster project aims to bridge the gap on the availability of a consistent and validated hydro-geomorphologic database for Portugal, by creating, disseminating and exploiting a GIS database on disastrous floods and landslides for the period 1865–2010, which is available in http://riskam.ul.pt/disaster/en
. Data collection is steered by the concept of disaster used within the Disaster project. Therefore, any hydro-geomorphologic case is stored in the database if the occurrence led to casualties or injuries, and missing, evacuated or homeless people, independently of the number of people affected. The sources of information are 16 national, regional and local newspapers that implied the analysis of 145,344 individual newspapers. The hydro-geomorphologic occurrences were stored in a database containing two major parts: the characteristics of the hydro-geomorphologic case and the corresponding damages. In this work, the main results of the Disaster database are presented. A total of 1,621 disastrous floods and 281 disastrous landslides were recorded and registered in the database. These occurrences were responsible for 1,251 dead people. The obtained results do not support the existence of any exponential increase in events in time, thus contrasting with the picture provided to Portugal by the Emergency Events Database. Floods were more frequent during the period 1936–1967 and occurred mostly from November to February. Landslides were more frequent in the period 1947–1969 and occurred mostly from December to March.
TL;DR: CoSMoS as discussed by the authors applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings.
Abstract: The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning.
TL;DR: The highway tunnels under the Huangpu River of Shanghai are constructed at a maximum depth up to 45m, within the artesian aquifer as discussed by the authors, and the recently constructed tunnels have leaked less than 0.1 L/m2/day.
Abstract: The Quaternary deposits in Shanghai primarily consists of a phreatic aquifer group (Aq0) and five artesian aquifers (AqI–AqV) that are separated by six aquitards (AdI–AdVI). In the basin of the Huangpu River, the first artesian aquifer (AqI) is connected to the second artesian aquifer (AqII), forming a 50-m-thick artesian aquifer with a very high groundwater level. The highway tunnels under the Huangpu River of Shanghai are constructed at a maximum depth up to 45 m, within the artesian aquifer. These tunnels are lined with precast reinforced concrete segments without a second lining. Under high water pressure, it is difficult for the single shell linings to achieve water tightness. Different degrees of groundwater leakage have been observed in road tunnels under the Huangpu River. The tunnels constructed before the 1990s have had very serious groundwater leakage (e.g., >1 L/m2/day), and the recently constructed tunnels have leaked less than 0.1 L/m2/day. The factors influencing groundwater leakage include depth below groundwater level, differential settlement of the tunnel, and applied waterproof technologies. The increase in depth leads to a significant increase in groundwater leakage. The differential settlement causes gaps to open and offset between segments, as well as cracking of segments, which can also induce groundwater leakage. According to the analysis of recorded data, the number of leaking points tends to increase with the curvature of the settlement curve. In addition, inappropriate waterproofing materials and poor waterproofing design will also lead to groundwater leakage. Groundwater leakage causes deterioration of the structure, aging of the installations in the tunnels (e.g., facilities and pavements), as well as discomfort for users of the tunnels and adverse environmental impacts. Furthermore, groundwater leakage also causes structural deformation of the tunnel itself, leading to further leakage and hazards.
TL;DR: In this paper, a review of volcanic tsunami hazard in Southeast Asia is presented, together with a history of past events in the region, highlighting crucial volcanic provinces in Indonesia, the Philippines and Papua New Guinea and propose strategies for facing future events.
Abstract: Southeast Asia has had both volcanic tsunamis and possesses some of the most densely populated, economically important and rapidly developing coastlines in the world. This contribution provides a review of volcanic tsunami hazard in Southeast Asia. Source mechanisms of tsunami related to eruptive and gravitational processes are presented, together with a history of past events in the region. A review of available data shows that many volcanoes are potentially tsunamigenic and present often neglected hazard to the rapidly developing coasts of the region. We highlight crucial volcanic provinces in Indonesia, the Philippines and Papua New Guinea and propose strategies for facing future events.
TL;DR: In this paper, the authors investigated the disaster-induced population displacement scenario at individual household level in Bangladesh and found that at the end of emergency aid, male members of the family started moving towards nearer cities to find an income.
Abstract: This study investigates the disaster-induced population displacement scenario at individual household level in Bangladesh. ‘Population displacement’ is seen here as an alternative adaptation option to natural hazard for the survivors after cyclone Aila. The changes both in origin and destination community due to population displacement are described here on the basis of social ‘inclusion’ and ‘exclusion’ concept. The field survey was conducted during March–July 2010, and a sample of 280 respondents from 12 villages in southwest coastal Bangladesh was interviewed. Findings show that at the end of emergency aid, male members of the family started moving towards nearer cities to find an income. Based on the income and asset distribution at the community level, this study developed a societal cluster of displacement and demonstrates the societal changes because of cyclone-induced population displacement.
TL;DR: The results show that the southwestern and central parts of the study area possess higher risk, while the northwestern and southeastern parts possess lower risk, and the assessment model fits the area of historical flood data.
Abstract: This study presents the methodology and procedure for risk assessment of flood disasters in central Liaoning Province, which was supported by geographical information systems (GIS) and technology of natural disaster risk assessment. On the basis of the standard formulation of natural disaster risk and flood disaster risk index, of which weights were developed using combined weights of entropy, the relative membership degree functions of variable fuzzy set (VFS) theory were calculated using improved set pair analysis, while level values were calculated using VFSs, including hazard levels, exposure levels, vulnerability levels and restorability levels, and the flood risk level for each assessment unit was obtained using the natural disaster index method. Consequently, integrated flood risk map was carried out by GIS spatial analysis technique. The results show that the southwestern and central parts of the study area possess higher risk, while the northwestern and southeastern parts possess lower risk. The results got by the assessment model fits the area of historical flood data; this study offer new insights and possibility to carry out an efficient way for flood disaster prevention and mitigation. The study also provides scientific reference in flood risk management for local and national governmental agencies.
TL;DR: A landslide susceptibility analysis is performed through an artificial neural network (ANN) algorithm, in order to model the nonlinear relationship between landslide manifestation and geological and geomorphological parameters, which results in a geospatial product that expresses the landslide susceptibility index.
Abstract: A landslide susceptibility analysis is performed through an artificial neural network (ANN) algorithm, in order to model the nonlinear relationship between landslide manifestation and geological and geomorphological parameters. The proposed methodology can be divided into two distinctive phases. In the first phase, the methodology introduces a specific distance metric, the Mahalanobis distance metric, to improve the selection of non-landslide records that “enriches” the training database and provides the model with the necessary data during the training phase. In the second phase, the methodology develops a ANN model that was capable of minimizing the effect of over-fitting by monitoring in parallel the testing data during the training phase and terminating the process of learning when a certain acceptable criteria are achieved. The model was capable in identifying unstable areas, expressed by a landslide susceptibility index. The proposed methodology has been applied in the County of Xanthi, in the northern part of Greece, an area where a well-established landslide database existed. The landslide-related parameters that had been taken in account in the analysis were the following: lithology, distance from geological boundaries, distance from tectonic features, elevation, slope inclination, slope orientation, distance from hydrographic network and distance from road network. These parameters have been normalized and reclassified and used as input variables, while the description of a given area as landslide/non-landslide was assumed to be the output variable. The final outcome of the model was a geospatial product, which expressed the landslide susceptibility index and when compared with an up-to-date landslide inventory database showed satisfactory results.
TL;DR: In this paper, a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea was produced and evaluated using the relative effect (RE) method to determine the relationship between landslide causative factors and landslide occurrence.
Abstract: The objective of this study was to produce and evaluate a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea. The relative effect (RE) method was used to determine the relationship between landslide causative factors (CFs) and landslide occurrence. To determine the effect of CFs on landslides, data layers of aspect, elevation, slope, internal relief, curvature, distance to drainage, drainage density, stream power index, sediment transport index, topographic wetness index, soil drainage character, soil type, soil depth, forest type, timber age, and geology were analyzed in a geographical information system (GIS) environment. A GIS-based landslide inventory map of 748 landslide locations was prepared using data from previous reports, aerial photographic interpretation, and extensive field work. A RE model was generated from a training set consisting of 673 randomly selected landslides in the inventory map, with the remaining 75 landslides used for validation of the susceptibility map. The results of the analysis were verified using the landslide location data. According to the analysis, the RE model had a success rate of 86.3 % and a predictive accuracy of 88.6 %. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. The results of this study can therefore be used to mitigate landslide-induced hazards and to plan land use.
TL;DR: In this paper, the authors provided an insight into the mechanism of rainfall-induced landslide in the Hulu Kelang area by analyzing the rainfall patterns prior to the occurrences of five selected case studies.
Abstract: Hulu Kelang is known as one of the most landslide-prone areas in Malaysia. The area has been constantly hit by landslide hazards since 1990s. This paper provides an insight into the mechanism of rainfall-induced landslide in the Hulu Kelang area. Rainfall patterns prior to the occurrences of five selected case studies were first analyzed. The results showed that daily rainfall information is insufficient for predicting landslides in the area. Rainfalls of longer durations, i.e., 3–30 days prior to the landslides should be incorporated into the prediction model. Numerical simulations on a selected case study demonstrated that both matric suction and factor of safety decreased steadily over time until they reached the lowest values on the day of landslide occurrence. Redistribution of infiltrated rainwater in the soil mass could be a reason for the slow response of failure mechanism to rainfall. Based on 21 rainfall-induced landslides that had occurred in the area, three rainfall thresholds were developed as attempts to predict the occurrence of rainfall-induced landslide. The rainfall intensity–duration threshold developed based on the local rainfall conditions provided a reasonably good prediction to the landslide occurrence. The cumulative 3- versus 30-day antecedent precipitation index threshold chart was capable of giving the most reliable prediction with the limiting threshold line for major landslide yielded a reliability of 97.6 %.
TL;DR: In this paper, a simulation model of ground water inrush for fault was designed, and the water outburst parameters, such as water inflow, permeability, seepage velocity, porosity and other variables under different material combination and water pressures, were obtained.
Abstract: Groundwater outburst has an impartible relationship with geological structures such as water-conducting faults, which are widely distributed in north China. In order to study the seepage property and mechanism of water outburst from the faults above a confined aquifer in the coal mining, the simulation model of ground water inrush for fault was designed. The water outburst parameters, such as water inflow, permeability, seepage velocity, porosity and other variables under different material combination and water pressures, were obtained; the research results indicate as follows: (1) The changes of the water inflow can be divided into three stages, i.e., the water inflow slowly increases at the early stage, rapidly increases at the middle stage and keeps unchanged at the late stage. (2) The seepage process can be represented by the seepage combination types, which are composed of pore flow, fissure flow and pipe flow, and the seepage changes not only with time but also with different conditions. (3) Mining would lead to the reactivation of faults and further enhance the permeability of fault zone potentially. The tiny granules in fault would be eroded and moved to exterior as the time under the high water pressure and lead to the change of porosity parameters. In this case, the seepage velocity would increase ceaselessly, and then the seepage would convert into pipe flow and finally lead to water inrush accidents.
TL;DR: In this article, a tourism disaster vulnerability framework was developed to facilitate the systematic analysis of the underlying vulnerability drivers, and the results from 73 interviews highlight common, as well as idiosyncratic, factors that shape the islands' hazardscapes and vulnerabilities.
Abstract: Islands are known to be vulnerable to natural hazards, resulting in substantial risks for their tourism industries. To facilitate the systematic analysis of the underlying vulnerability drivers, a tourism disaster vulnerability framework was developed. The conceptual model then guided qualitative empirical research in three regions: the Caribbean, the South Pacific, and the Indian Ocean. The results from 73 interviews highlight common, as well as idiosyncratic, factors that shape the islands’ hazardscapes and vulnerabilities. Key vulnerabilities included social, economic, political, and environmental dimensions. Probably, the most critical vulnerability driver is the lack of private sector investment in disaster risk reduction. This is interrelated with deficient planning processes, on-going demand for coastal products, lack of political will, and poor environmental conditions. Notwithstanding many barriers, some businesses and organisations engage proactively in addressing disaster risk. The paper’s empirical evidence supports the validity of the framework, and suggestions for further research are made.
TL;DR: In this paper, the authors focused on the effect of temperature on rock bursts and found that the degree of rock burst is increasing instead of decreasing with rising temperature, which is helpful for explaining the rock burst disaster in tunnels at high ground temperature.
Abstract: Much research has been conducted on the influence of rock burst mechanisms and temperature on the mechanical properties of hard rock while research on the effect of temperature on rock bursts is scarce. Therefore, this paper focuses on Rock Burst Proneness Index tests and acoustic emission (AE) tests under the action of high temperature. It was found that the Rock Burst Proneness Index and the AE energy will rise as the temperature rises. It means that the degree of rock burst is increasing instead of decreasing with rising temperature. The research results revealed the temperature effect of rock burst in long deep tunnels under a certain thermal stress condition, which is helpful for explaining the rock burst disaster in tunnels at high ground temperature.
TL;DR: In this paper, the application of a well-known multi-criteria decision-making technique, called preference ranking organization method for enrichment evaluation (PROMETHEE II), in combination with fuzzy analytical hierarchy process (FAHP), as a weighting technique to explore landslide susceptibility mapping (LSM) was described.
Abstract: This paper describes the application of a well-known multi-criteria decision-making technique, called preference ranking organization method for enrichment evaluation (PROMETHEE II), in combination with fuzzy analytical hierarchy process (FAHP), as a weighting technique to explore landslide susceptibility mapping (LSM). To this end, eight landslide-related geodata layers of the Minoo Dasht located in the Gorgan province of Iran, involving slope, aspect, distance to river, drainage density, distance to fault, mean annual rainfall, distance to road and lithology have been integrated using the PROMETHEE II enhanced by FAHP technique. Afterward, the receiver operating characteristics (ROC) curves for the proposed LSM were drawn using an inventory of landslides containing 83 recent and historic landslide points, and the area under curve = 0.752 value was calculated accordingly. Additionally, to further verify the practicality of such susceptibility map, it was also evaluated against the landslide inventory using simple overlay. The outcome was that about 11 % of the occurred landslide points fall into the very high susceptibility class of the LSM, but approximately 52 % of them indeed fall into the high and very high susceptibility zones together. Also, it resulted that no recorded landslide occurred in the zone of very low susceptibility. According to the results of the ROC curves analysis and simple overlay evaluation, the produced map has exhibited good performance.
TL;DR: In this paper, a new experimental site has been equipped in the Autonomous Province of Bozen-Bolzano (Eastern Alps, Italy) for both monitoring purposes and testing early warning systems.
Abstract: Debris-flow monitoring in instrumented areas is an invaluable way to gather field data that may improve the understanding of these hazardous phenomena. A new experimental site has been equipped in the Autonomous Province of Bozen-Bolzano (Eastern Alps, Italy) for both monitoring purposes and testing early warning systems. The study site (Gadria basin) is a 6.3 km2 catchment subjected to frequent debris flows. The monitoring system in the Gadria basin consists of rain gauges, radar sensors, geophones, video cameras, piezometers and soil moisture probes. Transmission of data and alerts from the instruments exploits in part radio technology. The paper presents the data gathered during the first three years of activity, with two debris-flow events recorded at the station varying in magnitude and characteristics, and discusses the perspectives of debris-flow monitoring and related research.
TL;DR: A generic probabilistic framework based on the sequential Monte Carlo Method is presented to implement coinciding events and triggered chains of events (using a variant of a Markov chain), as well as time-variant vulnerability and exposure and finds that extreme events can be captured by adding more knowledge on potential interaction processes using in a brick-by-brick approach.
Abstract: Dynamic risk processes, which involve interactions at the hazard and risk levels, have yet to be clearly understood and properly integrated into probabilistic risk assessment. While much attention has been given to this aspect lately, most studies remain limited to a small number of site-specific multi-risk scenarios. We present a generic probabilistic framework based on the sequential Monte Carlo Method to implement coinciding events and triggered chains of events (using a variant of a Markov chain), as well as time-variant vulnerability and exposure. We consider generic perils based on analogies with real ones, natural and man-made. Each simulated time series corresponds to one risk scenario, and the analysis of multiple time series allows for the probabilistic assessment of losses and for the recognition of more or less probable risk paths, including extremes or low-probability–high-consequences chains of events. We find that extreme events can be captured by adding more knowledge on potential interaction processes using in a brick-by-brick approach. We introduce the concept of risk migration matrix to evaluate how multi-risk participates to the emergence of extremes, and we show that risk migration (i.e., clustering of losses) and risk amplification (i.e., loss amplification at higher losses) are the two main causes for their occurrence.
TL;DR: In this paper, the authors assess the socioeconomic consequences of extreme coastal flooding events and estimate the wealth and income impacts associated with different social groups in coastal communities in Israel, and calculate the observed change in income distribution of the population under threat of inundation.
Abstract: This paper assesses the socioeconomic consequences of extreme coastal flooding events. Wealth and income impacts associated with different social groups in coastal communities in Israel are estimated. A range of coastal flood hazard zones based on different scenarios are identified. These are superimposed on a composite social vulnerability index to highlight the spatial variation in the socioeconomic structure of those areas exposed to flooding. Economic vulnerability is captured by the exposure of wealth and income. For the former, we correlate the distribution of housing stock at risk with the socioeconomic characteristics of threatened populations. We also estimate the value of residential assets exposed under the different scenarios. For the latter, we calculate the observed change in income distribution of the population under threat of inundation. We interpret the change in income distribution as an indicator of recovery potential.
TL;DR: A detailed analysis of the possible causes of coal and gas outbursts in coal mines in Turkey has been conducted in this paper, based on the observation of outburst occurrence in Turkey in the period from 1969 to 2012 as well as mining and geological conditions.
Abstract: Coal and gas outbursts have been a major geological hazard to underground coal mining for over 150 years and continue to cause serious problems in all over the world In order to have a better understanding of the phenomenon, it is worthwhile making a historical review of the occurrences and a combat of the events Many investigations and researches have been done to characterize and prevent the outburst occurrences in the worldwide, but there has been no detailed investigation about coal and gas outburst occurrences in Turkey This paper presents the outburst data of coal mines in Turkey since 1969 Based on the observation of outburst occurrence in Turkey in the period from 1969 to 2012 as well as mining and geological conditions, detailed analysis of the possible causes of outburst accidents is conducted The influences of some geological parameters such as the depth of occurrence, thickness and inclination of coal seams, the amount of ejected material (coal and gas), and tectonic disturbances on coal and gas outburst occurrences have been statistically investigated The outburst occurrences throughout the world were reviewed and compared with the Turkish outburst experiences Suggestions are put forward on future studies that could be of interest to government agencies regarding strategic policies, proper technical management practice, identification of outburst-prone coal seams, as well as prevention and control measures
TL;DR: A new dynamic research framework for small business recovery is proposed which allows for a shared framework and vocabulary in the context of individual, family/household, and community recovery over time.
Abstract: Exogenous, non-normative shocks to small businesses such as natural disasters have been understudied. Moreover, most disaster research on small businesses has focused on business recovery as a dichotomy at one point in time. However, disaster recovery for small businesses is an iterative process set in the context of individual, family/household, and community recovery over time. A new dynamic research framework for small business recovery is proposed which allows for a shared framework and vocabulary.