Literatura científica selecionada sobre o tema "Disaster modelling"
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Artigos de revistas sobre o assunto "Disaster modelling"
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Mishra, Vinaytosh, e Mohita G. Sharma. "Understanding Humanitarian Supply Chain Through Causal Modelling". South Asian Journal of Business and Management Cases 9, n.º 3 (25 de novembro de 2020): 317–29. http://dx.doi.org/10.1177/2277977920958084.
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Research Questions: Does being in the social welfare slow-onset disaster quadrant help in garnering resources during the sudden disaster? Theory: Humanitarian supply chain has been traditionally explained as a system involved in mobilizing people, resources, skills and knowledge for disaster relief operations. The established classification of disasters includes natural and man-made disasters. These are further classified into sudden- and slow-onset disasters. Social welfare supply chains happen to be a distinctive type of humanitarian supply chain working in slow-onset disasters such as poverty and drought. To understand the complex systems like humanitarian supply chain, system dynamics modelling is used. Type of the Case: Study of a phenomenon. Basis of the Case: In this study, we proposed a humanitarian supply chain case and system dynamics model that works as a social welfare supply chain. In the face of a calamity, operations are ramped up for the sudden-onset conditions. After the initial phase is over, operations are ramped down and again become stable. Protagonist: Absent. Findings: The study tests the results of four policy measures (a) increasing goodwill, (b) decreasing stringent directive, (c) increasing donor attitude and (d) a combination of all of these measures. These measures are additive in nature, and a humanitarian supply chain can use these policy measures to respond to a sudden disaster. Discussions: The case discusses various policy measures taken by the humanitarian supply chain during a sudden disaster. It also explores whether being in the slow-onset quadrant helps tack sudden disasters like earthquakes or terrorist attacks. An organization can start with decreasing the stringent measures in the case of a sudden disaster. Increasing donor attitude and goodwill requires long-term outreach efforts.
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Takeichi, Naohiro, Takeshi Katagiri, Harumi Yoneda, Shusaku Inoue e Yusuke Shintani. "Virtual Reality approaches for evacuation simulation of various disasters". Collective Dynamics 5 (12 de agosto de 2020): A93. http://dx.doi.org/10.17815/cd.2020.93.
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This paper presents a virtual reality (VR) system of evacuation in the cases of various disasters. We considered a combination of disasters under realistic scenarios. Disaster simulations by numerical models were imported into the VR system to express a realistic situation. Not only disaster experts but also designers and non-professionals are able to share realistic experiences for escape from the disasters. This system is useful for performance-based design, planning of escape, disaster prevention, evacuation drill etc. The VR system consists of Building Information Modelling, physical simulation models for disasters and human behaviour’s simulation.
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Zhang, Fushen, Shaobo Zhong, Simin Yao, Chaolin Wang e Quanyi Huang. "Ontology-based representation of meteorological disaster system and its application in emergency management". Kybernetes 45, n.º 5 (3 de maio de 2016): 798–814. http://dx.doi.org/10.1108/k-10-2014-0205.
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Purpose – The purpose of this paper is to make research on causing mechanism of meteorological disaster as well as the components of meteorological disaster system and their semantic relationships. It has important practical significance due to the urgent need of further providing support for pre-assessment of influences of disastrous weather/climate events and promoting the level of emergency management. Design/methodology/approach – This paper analyses the occurrence regulations and components of meteorological disasters and proposes the concept of meta-action. Ontology modelling method is adopted to describe the components and relationships among different parts comprising meteorological disaster system, and semantic web rule language is selected to identify the implicit relationships among the domain knowledge explicitly defined in ontology model. Besides, a case is studied to elaborate how to provide logic and semantic information support for comprehensive risk assessment of disastrous weather/climate events based on rule-based ontology reasoning method. It proves that ontology modelling and reasoning method is effective in providing decision makings. Findings – This paper provides deep analyses about causing mechanisms of meteorological disasters, and implements information fusion of the components of meteorological disaster system and acquisition of potential semantic relations among ontology components and their individuals. Originality/value – In this paper, on the basis of analysing the disaster-causing mechanisms, the meteorological disaster ontology (MDO) model is proposed by using the ontology modelling and reasoning method. MDO can be applied to provide decision makings for meteorological departments.
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Hastings, I. M., e U. D’Alessandro. "Modelling a Predictable Disaster:". Parasitology Today 16, n.º 8 (agosto de 2000): 340–47. http://dx.doi.org/10.1016/s0169-4758(00)01707-5.
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Hassan, Mohamad Ghozali, Che AzlanTaib, Muslim Akanmu e Afif Ahmarofi. "A Theoretical Review on the Preventive Measures to Landslide Disaster Occurrences in Penang State, Malaysia". Journal of Social Sciences Research, SPI6 (25 de dezembro de 2018): 753–59. http://dx.doi.org/10.32861/jssr.spi6.753.759.
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Based on the frequently unanticipated occurrences of natural landslide disaster across Malaysia, it can be seen that Malaysia is still not fully prepared for occurrences of natural landslide disaster. The lack of predictive and warning systems for the disaster in the country is creating panic and apprehension among citizens alongside with both economic and property losses. The general objectives of this research are: to identify the meteorological factors that cause landslide natural disaster occurrences in Malaysia and to suggest a predictive model for landslide disaster occurrence in Malaysia. This research therefore explored modelling disasters occurrences in order to predict, warn, and prevent huge impact of landslide disasters in Penang, Malaysia. This research shall make use of past literatures and data from Malaysian Meteorological department considering climatic parameters such as daily mean temperature and daily rainfall only. Data mining and Artificial Neural Networks (ANN) shall be suggested to predict landslide disaster occurrences in Malaysia. Thus, the need for a predictive model for occurrence of landslide natural disaster is imperative to the safety of lives and protection of both environmental and economy of the region.
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Ajulo, Oluwadunsin, Ishmael Adams, Ali Asgary, Patrick Tang e Jason Von-Meding. "Modelling the Roles of Community-Based Organisations in Post-Disaster Transformative Adaptation". GeoHazards 3, n.º 2 (11 de abril de 2022): 178–98. http://dx.doi.org/10.3390/geohazards3020010.
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Disasters result where hazards and vulnerabilities intersect. The concept of vulnerability itself is mainly a social construct and the extent to which this can be overcome while transforming disaster-prone systems has often been emphasised in the critical hazard literature. However, the extent to which community-based organisations contribute to post-disaster transformation at the community level remains unexamined. This paper is aimed at examining the extent of the role of community-based organisations (CBOs) in the transformative adaptation of post-earthquake Lyttelton. Quantitative data was obtained from community members using a questionnaire survey of 107 respondents, supporting interviews, and secondary data to explain the phenomenon in this study. System dynamics and agent-based modelling tools were applied to analyse the data. The results show that while CBOs played a major role in Lyttelton’s transformation by fostering collaboration, innovation, and awareness, the extent of their impact was determined by differences in their adaptive capacities. The transformation was influenced by the impacts of community initiatives that were immediate, during, and a long time after the disaster recovery activities in the community. Our research extends the discourse on the role of community-based organisations in disaster recovery by highlighting the extent of CBOs’ impacts in community post-disaster transformation.
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Nukavarapu, Nivedita, e Surya Durbha. "STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (22 de junho de 2016): 223–29. http://dx.doi.org/10.5194/isprs-archives-xli-b8-223-2016.
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The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.
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Nukavarapu, Nivedita, e Surya Durbha. "STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (22 de junho de 2016): 223–29. http://dx.doi.org/10.5194/isprsarchives-xli-b8-223-2016.
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The Healthcare Critical Infrastructure (HCI) protects all sectors of the society from hazards such as terrorism, infectious disease outbreaks, and natural disasters. HCI plays a significant role in response and recovery across all other sectors in the event of a natural or manmade disaster. However, for its continuity of operations and service delivery HCI is dependent on other interdependent Critical Infrastructures (CI) such as Communications, Electric Supply, Emergency Services, Transportation Systems, and Water Supply System. During a mass casualty due to disasters such as floods, a major challenge that arises for the HCI is to respond to the crisis in a timely manner in an uncertain and variable environment. To address this issue the HCI should be disaster prepared, by fully understanding the complexities and interdependencies that exist in a hospital, emergency department or emergency response event. Modelling and simulation of a disaster scenario with these complexities would help in training and providing an opportunity for all the stakeholders to work together in a coordinated response to a disaster. The paper would present interdependencies related to HCI based on Stochastic Coloured Petri Nets (SCPN) modelling and simulation approach, given a flood scenario as the disaster which would disrupt the infrastructure nodes. The entire model would be integrated with Geographic information based decision support system to visualize the dynamic behaviour of the interdependency of the Healthcare and related CI network in a geographically based environment.
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Rezaldi, Muhammad Yudhi, RABIAH ABDUL KADIR, Mohamad Taha Ijab e Apip Apip. "Aesthetics 3D Geovisualization For Flood Disaster Based on XYZ Coordinate". Journal of Applied Research and Technology 21, n.º 4 (31 de agosto de 2023): 688–706. http://dx.doi.org/10.22201/icat.24486736e.2023.21.4.1706.
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Geovisualization can convert spatial and non-spatial data into an accurate visualization of flood modelling but less realistic. Contrarily, Multimedia can produce realistic visualizations by applying aesthetic parameters, but not based on data, inaccurate. This research successfully combined both Geovisualization and Multimedia that created an accurate and realistic visualization of flood modelling. An experimental methodology was used for the flood transformation data through geovisualization technique and carried out the 3D mapping objects through photogrammetry by using drones. Both modellings were combined by overlapping the X, Y, Z coordinates. Multimedia techniques were used to remodeling, animate, design interface, action script, and to apply aesthetic parameters. The success of this study was measured through a comparative evaluation; comparing between the model of this research, and two other models from previous studies. The result was 84.6% of the respondents chose this research modelling. The researcher used Alpha Cronbach's reliability test with SPSS for validity checking. The result showed a significant reliability value of 0.935. In the theoretical contribution, this research modelling produced visualizations of flood modelling based on accurate data and aesthetic values. While in practical contribution, this modelling can be used as a source of information for the decision-makers for flood mitigation plans.
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Beaulac, Leah, Breanne Langlois, Katherine Berry e Elena Naumova. "Natural Disaster and Migration Trends in Flood Prone Agricultural Areas of Indonesia". Current Developments in Nutrition 6, Supplement_1 (junho de 2022): 72. http://dx.doi.org/10.1093/cdn/nzac050.002.
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Abstract Objectives Sudden onset severe natural disasters are more closely associated with climate related migration than slower onset disasters in Indonesia. This analysis examines whether severe flooding was related to migration in the five years prior to the 5th wave of the Indonesian Family Life Survey (IFLS), and whether there were differences between agricultural versus non-agricultural households. Methods We present descriptive statistics of the subset of the population that reported having experienced natural disaster (3,183 (19%) households) in wave five of IFLS. Analysis is ongoing and will include statistical modelling. The main outcome is whether the household had moved. The independent variables are experienced a flood disaster that was severe, defined as causing death or injury, financial loss, or relocation, in the prior 5 years and whether the household owned land for farming. All analysis was conducted using Stata software. Results Overall, among disaster impacted households, 12.7% experienced a disaster that was severe enough to cause death or injury, financial loss, or relocation. Flooding was the most commonly reported disaster (45%), followed by volcano (17.6%) and earthquake (16%). Compared to those that migrated versus those that did not, 48.7% vs. 42.7% were affected by flood, respectively, and 19% vs. 36.4% owned land for farming. Conclusions Delineating between a severe disasters and less severe disasters allows for more strategic disaster management strategies. In areas prone to severe disaster, adaptation policies aimed towards vulnerable farmers that own land may bolster response strategies. Funding Sources NSF.
Teses / dissertações sobre o assunto "Disaster modelling"
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COLOCCI, ALESSANDRA. "Modelling disaster risk reduction: decoding social-ecological interactions to foster transformative adaptation". Doctoral thesis, Università Politecnica delle Marche, 2021. http://hdl.handle.net/11566/289629.
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Questa ricerca intende contribuire alla discussione sulla riduzione del rischio disastri (DRR), esplorando come le comunità locali dovrebbero adattarsi ai pericoli che le circondano.
La prima parte riporta la teoria della panarchia alle dinamiche del rischio. Il modello teorico che ne deriva, la Panarchia Sociale-Ecologica, descrive le condizioni di rischio e permette di riconoscere i nuclei del DRR: la resilienza ai disastri e la sostenibilità ambientale. Il modello fornisce le basi per lo sviluppo di una Valutazione Combinata di Resilienza e Sostenibilità, concentrata sul rischio inondazione alla scala comunale. La seconda parte svolge un’analisi quantitativa attraverso indicatori, che identificano e caratterizzano i livelli di resilienza e sostenibilità. La terza parte impiega strumenti qualitativi (questionari) per raccogliere le percezioni delle comunità locali sui rischi presenti nei loro Comuni. L’analisi è stata applicata a due casi studio, la Regione Marche (Italia) e l’Hokkaidō (Giappone).
I risultati mostrano il ruolo delle inondazioni nel determinare la resilienza locale, e degli impatti antropici per la sostenibilità. Le criticità maggiori sono concentrate nelle aree montane/collinari. Allo stesso tempo, aspetti di welfare e sicurezza sociale risultano fondamentali per formare la resilienza, così come la presenza di vegetazione lo è per la sostenibilità. Inoltre, emerge una sostanziale differenza fra misurazione e percezione di resilienza e sostenibilità, generalmente in senso peggiorativo.
In generale, ulteriori sforzi dovrebbero essere diretti alle aree interne, benché la regione intera gioverebbe del consolidamento della resilienza locale. Inoltre, le comunità sembrano molto sensibili ai temi ambientali, per cui potrebbero appoggiare sforzi per aumentare la sostenibilità. Infine, questi studi possono contribuire alle strategie DRR, per promuovere l’adattamento trasformativo delle comunità locali, reso urgente dall’esasperazione degli eventi estremi.This research intends to contribute to the discussion on disaster risk reduction (DRR), investigating the question of how local communities should adjust to the surrounding threats. The first part adapted the panarchy heuristics to risk dynamics. The drawn theoretical model, the Social-Ecological Panarchy, could describe the conditions of risk and allow to recognise the two cores of DRR: disaster resilience and environmental sustainability. The model supported the development of a Combined Assessment of Resilience and Sustainability, focused on flood risk at the Municipal scale. The second part of the research performed a quantitative analysis through numerical indicators, that identified and characterised the levels of resilience and sustainability. The third part of the research employed qualitative tools (questionnaires) to gather the thoughts of local communities on the risks affecting their Municipalities. The analysis was applied to two case studies, Marche Region (Italy) and Hokkaidō (Japan). Results evidenced the role of flood events in determining the resilience capacities of local communities, and of the anthropic impacts for defining their sustainability. Most critical issues lied in the mountainous/hill areas. At the same time, social welfare and protection appeared pivotal in building local resilience, while the presence of vegetation shaped sustainability. Besides, a substantial mismatch emerged between assessed and perceived conditions of resilience and sustainability, generally in negative terms. Overall, it appeared that further efforts should be tailored to the innermost areas, though the overall region might benefit from consolidated resilience. At the same time, local populations seemed highly responsive to environmental issues, possibly endorsing the enhancement of sustainability. Eventually, these insights might inform risk reduction strategies, to foster a transformative adaptation of local communities, urged by exacerbating disruptive threats.
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de, Ligt Vera. "Practical and conceptual issues in the use of agent-based modelling for disaster management". Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11236/.
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Application of agent-based modelling technology (ABM) to disaster management has to date been limited in nature. Existing research has concentrated on extending the model structures and agent architectures of complex algorithms to test robustness and extensibility of this simulation approach. Less attention has been brought to bear on testing the current state-of-the-art in ABM for modelling real-life systems. This thesis aims to take first steps in remedying this gap. It focuses on identifying the practical and conceptual issues which preclude wider utilisation of ABM in disaster management. It identifies that insufficient attention is put on incorporating real-life information and domain knowledge into model definitions. This research first proposes a methodology by which some of these issues may be overcome, and consequently tests and evaluates it through implementation of InSiM (Incident Simulation Model), which depicts reaction of pedestrians to a CBRN (chemical, biological, radiological or nuclear) explosion in a city centre. A number of steps are conducted to obtain real-life information related to human response to CBRN incidents. This information is then used for design and parameterisation of InSiM which is implemented in three configurations. In order to identify the effects use of real-life data have on the simulation results each configuration incorporates the information at different level of complexity. The effects are assessed by comparison of the generated dispersion patterns of agents along the city centre. However, use of conventional statistical goodness-of-fit tests for assessing the degree of the difference was challenged by inhomogeneous nature of the data. Hence, alternative approaches are also adopted so that results can be qualitatively assessed. Nevertheless, the evaluation reveals significant differences at global and local level. This research highlights that incorporation of real-life information and domain knowledge into ABM is not without problems. Each time a problem was addressed, additional issues began to emerge. Most of these challenges were related to generalisation of the complex real-life systems that the model represents. Therefore, further investigations are needed at every methodological step before ABM can fully realise its potential to support disaster management.
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Flores, Salas Alicia. "Evaluation of the use of lightweight concrete panels for post disaster house reconstruction using Building Information Modelling". Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/evaluation-of-the-use-of-lightweight-concrete-panels-for-post-disaster-house-reconstruction-using-building-information-modelling(ce6ee2fc-2997-40ff-b489-f1fdf1a5dfb7).html.
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A large number of natural disasters affects hundreds of thousands of people each year in their housing around the world. Therefore, there is a call to find more appropriate strategies for housing reconstruction following a disaster. This study aims to reduce the construction time and cost of housing affected by such disasters. The academic literature on the 3 Dimensional Lightweight Panels construction system (3D-LPs), Building Information Modelling system (BIM) and experiences gained in post-disaster housing reconstruction strengthens the argument that here is an opportunity to contribute to solve the housing reconstruction problem. The study points out that the combination of these systems and community participation presents an option to produce both affordable and sustainable housing in the shortest time on a large scale by the affected people after overcoming the emergence phase of a disaster. A holistic philosophy was used to study the housing reconstruction problem as a whole to understand all parts of the problem and three research questions were set up to explore the possible solution to this problem. The research strategy to address the problem was based on a survey of worldwide experts, interviewing a forum of lightweight concrete panel manufacturers and the modelling of a basic housing prototype in BIM. Research question (1) How can displaced people use their own labour to save money and time? and research question (2) How does the 3D-LPs construction system contribute to housing recovery after natural disasters? Research questions (1) and (2) were answered by 17 open-ended questions conducted with 22 housing experts from 11 countries and 7 semi-structured interviews composed of 14 questions with 7 manufacturers of construction materials respectively which collected rich qualitative data (15,419 words) that were analysed in Nvivo 10 through pattern matching and validated by triangulation techniques to give reliability to the study. The housing prototype modelling was used to answer the research question (3) Can the BIM model show the cost-benefit in building housing with the 3D-LPs construction system and displaced people's own labour?The main findings of this study are that a housing prototype built with 3D-LPs is 36.82% cheaper in comparison to houses built with bricks and reinforcement elements and could be built by unskilled people in 90 days. The study provides novel in-depth knowledge of how unskilled people from communities affected should participate in housing reconstruction and how new construction systems can be implemented after disasters, which contributes to the body of knowledge. In addition, the study provides guidelines to implement a system directed at unskilled people and also Non-Governmental Organizations (NGOs) in a novel way, to help to solve the housing reconstruction problem and engage the displaced people in the housing reconstruction.
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Cardozo, Claudia Paola. "A spatially integrated modelling approach to landslide risk assessment: a case study of the Nova Friburgo disaster - RJ, Brazil". Instituto Nacional de Pesquisas Espaciais (INPE), 2018. http://urlib.net/sid.inpe.br/mtc-m21c/2018/03.12.14.01.
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Landslides cause enormous economic damage and fatalities worldwide. The 2011 Mega disaster in the Rio de Janeiro mountainous region is considered the worst landslide disaster in Brazilian history. Traditionally, risk topic has been analyzed from a purely engineering-based perspective, which has proved to have an ineffective response to face the challenges posed by physical and social factors, especially in low-income countries. This thesis introduces a conceptual framework for an integrated risk assessment and undertakes the proposal in a practical way in the Nova Friburgo municipality, as a case study. In the first part of this research, an assessment of the physical component of risk was addressed. Three scenarios of landslide susceptibility were performed using a 10m-resolution DEM, geotechnical data and a landslide inventory. Findings suggest that the scenario with a wide range of cohesion parameter values was able to predict almost 70% of the inventoried landslides and about 50% of the territory with landslide-prone areas. In the second part of this thesis, a deep analysis of human component of risk is performed. A social vulnerability assessment- using the SoVI methodand data collection disaggregated by age, sex and race/ethnicity of the 2011 landslide-related fatalities were conducted. Results reveal differential social vulnerability among census tracts. Most of them were classified as moderately vulnerable. Although highly social vulnerable areas were not widely distributed in the territory, they are important because of their location and implications for the municipality economic matrix. Regarding the 2011 landslide-related fatalities, 434 casualties were registered. Spatial analysis indicates that the highest mortality was located at the northwest and central municipality zones. Landslide disaster affected males and females differently. In most age groups, landslides have killed more men and boys than women and girls. Fifty percent of those who lost their lives were the youngest and the elderly. The black population had a slightly higher mortality rate than either the brown (Pardos) and white ones. Data did not reveal a discernible trend in the association between social vulnerability and casualties. It seems that the landslide quantity and magnitude was so great that all of Nova Friburgo inhabitants were equally reached, beyond the inequalities expressed by their social vulnerability. In the third part of this inquiry, to predict landslide risk probability, the social vulnerability and the landslide susceptibility predictors were combined using the Generalized Additive Model (GAM). Findings suggest that in instable terrains, is enough a moderate social vulnerability level to increase the probability of landslide risk. Results also highlight model capacity to uncover hidden patterns in the dataset, capturing a nonlinear effect of social vulnerability predictor and a linear effect of terrain stability predictor. In conclusion, the proposed conceptual framework is generic and flexible, so can be applied to other areas, analysis scales and natural hazard types although some adaptation would be necessary depending on available data. Furthermore, the integrated approach performed in this thesis highlights that it is feasible and necessary linking data from different science domains to better understand disaster risk complexity, reducing risk and curbing losses of both human lives and economic assets through knowledge-based actions. It should be noted that this thesis research complies with guidelines given at the first priority area for action of the Sendai Framework for Disaster Risk Reduction 2015-2030, which outlines the importance of Understanding disaster risk. Finally, resulting knowledge provides Nova Friburgo community, organizations and governments with a basis to comprehend the risk related to a specific natural hazard: the landslides which can be leveraged to achieve an effective preparation and response to future disasters and also to promote disaster-resilient societies.Os deslizamentos de terra causam enormes prejuízos econômicos e mortes em todo o mundo. O Mega desastre 2011 na região montanhosa do Rio de Janeiro é considerado o pior desastre na história do Brasil. Tradicionalmente, o tópico de risco foi analisado a partir de uma perspectiva puramente baseada na engenharia que provou ter uma resposta ineficaz para enfrentar os desafios impostos por fatores físicos e sociais, especialmente em países de baixa renda. Esta tese apresenta um marco conceitual para uma avaliação integrada do risco e realiza a proposta de maneira prática no município de Nova Friburgo, como um estudo de caso. Na primeira parte desta pesquisa, uma avaliação do componente físico do risco foi abordada. Três cenários de suscetibilidade a escorregamentos foram realizados usando um DEM de 10m de resolução espacial, dados geotécnicos e um inventário de deslizamentos. Os resultados sugerem que o cenário que utilizou uma ampla gama de valores de coesão foi capaz de prever quase 70% dos deslizamentos de terra inventariados e cerca de 50% do território com áreas propensas a deslizamentos. Na segunda parte desta tese, se analisou o componente humano de risco. Uma avaliação de vulnerabilidade social - usando o método SoVI - e a coleta de dados desagregados por idade, sexo e raça/etnia dos óbitos provocados pelos deslizamentos de 2011 foram realizados. Os resultados revelam uma vulnerabilidade social diferenciada entre os setores censitários. A maioria deles foi classificada como moderadamente vulnerável. Embora as áreas altamente vulneráveis não sejam amplamente distribuídas no território, elas são importantes devido à sua localização e implicações para a matriz econômica do município. Em relação aos óbitos por deslizamentos de terra, foram registradas434 vítimas. A análise espacial indica que a maior mortalidade se localizou nas zonas do noroeste e centro do município. O desastre provocado pelos deslizamentos de terra afetou aos homens e mulheres de maneira diferente. Na maioria das faixas etárias, morreram mais homens e meninos do que mulheres e meninas. Cinquenta por cento daqueles que perderam suas vidas eram os mais jovens e os idosos. A população negra teve uma taxa de mortalidade ligeiramente maior do que os Pardos e brancos. Os dados não revelaram uma tendência discernível na associação entre vulnerabilidade social e óbitos. Parece que a magnitude dos deslizamentos foi tão grande que todos os habitantes de Nova Friburgo foram igualmente atingidos, além das desigualdades expressas por sua vulnerabilidade social. Na terceira parte desta investigação, determinou-se a probabilidade de risco de deslizamento, para isso a vulnerabilidade social e a susceptibilidade aos deslizamentos de terra foram combinados usando o Modelo Aditivo Generalizado (GAM). Os resultados sugerem que, em terrenos instáveis, basta um nível moderado de vulnerabilidade social para aumentar a probabilidade de risco de deslizamento. Os resultados também destacam a capacidade do modelo de descobrir padrões oculto no conjunto de dados, capturando um efeito não linear da variável vulnerabilidade social e um efeito linear da variável estabilidade do terreno. Em conclusão, o marco conceptual proposto é genérico e flexível pelo que pode ser aplicado a outras áreas, escalas de análise e tipos de perigos naturais, embora seja necessária alguma adaptação, dependendo dos dados disponíveis. Além disso, a abordagem integrada desta tese destaca que é viável e necessário vincular dados de diferentes domínios científicos para melhor compreender o risco de desastres, reduzir riscos e reduzir perdas de vidas humanas e ativos econômicos por meio de ações baseadas em conhecimento. Deve-se notar que esta pesquisa está em conformidade com as diretrizes dadas na primeira área prioritária para a ação do Marco de Sendai para a Redução de Riscos de Desastres 2015-2030, que descreve a importância de "Compreender o risco de desastres". Finalmente, o conhecimento resultante desta pesquisa fornece à comunidade, às organizações e ao governo de Nova Friburgo uma base para compreender o risco relacionado a um perigo natural específico: "os deslizamentos" que podem ser aproveitados para obter uma preparação melhor e respostas eficazes a desastres futuros e também para promover sociedades resilientes aos desastres.
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Shobeiri, Nejad Seyed Abdelhamid. "Modelling the Economic Impact of Extreme Events on Critical Infrastructure Systems in Australian Industries – Case Study in Finance and Tourism". Thesis, Griffith University, 2014. http://hdl.handle.net/10072/367136.
Texto completo da fonteResumo:
Economic and social stability across the world is tightly dependent on a sufficient and reliable flow of goods and services, based on the balance between supply and demand. The basis for the balance between supply and demand is a set of physical assets, processes and organisations that are collectively known as critical infrastructure systems (CIs). CIs are strongly interdependent in two complex ways: namely, physical and informational. Identification of CI interdependencies and interconnections is essential for the study of such supply and demand systems. Importantly, CI interdependencies and interconnections are also essential for the development of models that help in the study of the impact of extreme events or disasters, or prediction of economic loss from damage caused by cascading impacts on the supply and demand chain system.
Based on the stated problem, the aims of this research can be summarized as an estimation of economic loss. This estimation includes individual industry loss and total economic loss, taking interconnected industries into consideration. The main aims are to develop and test a new model and to develop a methodology based on this model for the assessment and management of risk from extreme events on critical infrastructure systems.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Griffith School of Environment
Science, Environment, Engineering and Technology
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Raillani, Hajar. "Disaster mοdelling and emergency facilities lοcatiοn under uncertainties : a case study οf the Μοrοccan relief supply chain". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMIR10.
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La modélisation des catastrophes et la localisation des installations sont des aspects essentiels de la gestion des catastrophes qui contribuent à améliorer l’efficacité et l’efficience des chaînes d’approvisionnement des secours. Cependant, les incertitudes inhérentes aux catastrophes et aux chaînes d’approvisionnement des secours peuvent avoir un impact significatif sur l’efficacité de ces modèles. Pour relever ce défi, la thèse propose l'utilisation de modèles basés sur la quantification de l'incertitude et de modèles basés sur Markov caché pour la modélisation des catastrophes dans le contexte de la chaîne d'approvisionnement des secours marocains. La thèse commence par conceptualiser la chaîne d'approvisionnement de secours marocaine, décrivant de manière exhaustive sa conception, ses activités et les différents acteurs impliqués dans le processus humanitaire, puis une analyse détaillée a été menée pour mettre en évidence les forces et les faiblesses de la chaîne d'approvisionnement de secours marocaine. Cela impliquait un examen approfondi des sources d’incertitude au sein du processus humanitaire, afin de bien comprendre les défis rencontrés au sein de la chaîne d’approvisionnement humanitaire marocaine et d’identifier les exigences spécifiques. À la suite de ce travail de base conceptuel, les modèles proposés sont ensuite appliqués à une étude de cas dédiée à la chaîne d’approvisionnement humanitaire marocaine. Cette application pratique vise à valider l'efficacité des modèles basés sur la quantification de l'incertitude et des modèles basés sur Markov caché dans un scénario réel, fournissant des informations précieuses sur leur applicabilité, leur utilité et leur impact potentiel sur la dynamique complexe du domaine humanitaire. Les résultats démontrent que le modèle basé sur la quantification de l'incertitude et le modèle basé sur Markov caché peuvent améliorer considérablement la robustesse et l'efficacité du réseau de la chaîne d'approvisionnement en termes de prévision des catastrophes. Le modèle basé sur la quantification de l'incertitude permet de prédire l'impact humain potentiel des catastrophes et des régions les plus sensibles, ce qui peut aider à évaluer la robustesse du réseau de la chaîne d'approvisionnement dans différents scénarios, en tenant compte de diverses sources d'incertitude, telles que la demande et incertitudes sur les données documentées. D'autre part, le modèle caché basé sur Markov est utilisé pour prédire le comportement d'une catastrophe lors de la prochaine occurrence, sur la base de données et de tendances historiques. Ce modèle fournit des informations importantes sur le potentiel des HMM dans la gestion des catastrophes et la logistique humanitaire et souligne l'importance de ces modèles dans la protection des impacts des catastrophes, des populations vulnérables et dans l'atténuation des effets des catastrophes naturelles à l'avenir. La thèse vise également à identifier les emplacements optimaux des installations et à développer un plan de réponse efficace aux catastrophes pouvant atténuer l'impact des catastrophes. Ces stations auront pour fonction la réception, le contrôle, le soutien et la distribution de l'aide en cas de catastrophes naturelles (tremblements de terre, inondations, sécheresse, glissements de terrain...) ou catastrophes d'origine humaine (accidents technologiques, attentats terroristes, accidents de la route), à travers l'intégration des différents acteurs de la chaîne d'approvisionnement de l'aide marocaine (Ministère de l'Intérieur, Ministère de l'Aménagement des Territoires marocains, protection civile, militaire...) et en considérant diverses sources d'incertitude, telles que la demande, les délais de transport et les ruptures d'approvisionnement. Les emplacements optimaux des installations identifiés par les modèles offrent une meilleure couverture des zones touchées, améliorant ainsi la rapidité et l'efficacité du plan d'intervention en cas de catastropheDisaster modelling and facility location are critical aspects of disaster management that help to improve the effectiveness and efficiency of relief supply chains. However, the inherent uncertainties associated with disasters and relief supply chains can significantly impact the effectiveness of such models. To address this challenge, the thesis proposes the use of uncertainty quantification-based models and hidden Markov based models for disaster modelling in the context of the Moroccan relief supply chain. The thesis initiates by conceptualizing the Moroccan relief supply chain, comprehensively outlining its design, activities, and the various actors involved in the humanitarian process, then, a detailed analysis was conducted to highlight the strengths and weaknesses of the Moroccan relief supply chain. This involved a deep examination of uncertainty sources within the humanitarian process, to make a good understanding of challenges faced within the Moroccan relief supply chain and identify the specific requirements. Following this conceptual groundwork, the proposed models are then applied to a dedicated case study of the Moroccan relief supply chain. This practical application aims to validate the effectiveness of the uncertainty quantification-based models and hidden Markov-based models in a real-world scenario, providing valuable insights into their applicability, utility, and potential impact on the complex dynamics of the humanitarian field. The results demonstrate that the uncertainty quantification-based model and the hidden Markov based model can significantly improve the robustness and efficiency of the supply chain network in term of disaster prediction. The uncertainty quantification-based model enables to make prediction of the potential human impact of disasters and the most sensitive regions which can help in the evaluation of the robustness of the supply chain network under different scenarios, considering various sources of uncertainty, such as demand and uncertainties on documented data. On the other hand, the hidden Markov based model is used to predict the disaster behaviour in next occurrence, based on historical data and trends. This model provides important insights into the potential of HMMs in disaster management and humanitarian logistics and emphasize the importance of these models in protecting disasters impact, vulnerable populations and mitigating the effects of natural disasters in the future. The thesis aims also to identify the optimal facility locations and develop an efficient disaster response plan that can mitigate the impact of disasters, this stations will have for function the reception, control, support and the distribution of help in case of natural disasters (earthquakes, floods, torrential floods, locust invasions, drought, landslides ...) or man-made disasters (technological accidents, terrorist attacks, road accidents, pollution ...), through the integration of different actors in the Moroccan relief supply chain (Ministry of the Interior, Ministry of Planning of Moroccan Territories, the civil protection, military, NGOs ...) and by considering various sources of uncertainty, such as demand, transportation time, and supply disruptions. The optimal facility locations identified by the models provide a better coverage of the affected areas, thereby improving the speed and effectiveness of the disaster response plan. The thesis highlights the significance of incorporating uncertainty analysis in disaster modelling and provides insights into the relief supply chain management in Morocco. The findings of this thesis can be useful for policymakers and practitioners in disaster management to improve the effectiveness and efficiency of relief supply chains
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Chen, Wanying. "Modelling the logisitcs response to disasters". Thesis, Lyon, INSA, 2015. http://www.theses.fr/2015ISAL0046/document.
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Cette thèse est consacrée à l'optimisation de la logistique sanitaire pour soutenir les plans de gestion de crise afin de réduire les effets des catastrophes naturelles et/ou humaines en termes de santé publique. Les catastrophes naturelles peuvent être prédites, mais elles sont difficiles à éviter. Par conséquence, la prise en charge des victimes potentielles et le dimensionnement des moyens logistiques de secours y afférent sont d'une importance cruciale. Une approche analytique en trois étapes est proposée afin d'étudier le dimensionnement des ressources et l'organisation des plans de gestion de crise (plan blanc) d’origine naturelle. La première étape propose un modèle de référence pour concevoir un plan de gestion de crise. La deuxième étape considère un modèle d’optimisation linéaire pour prédire le nombre de ressources nécessaires. La dernière étape présente un modèle dynamique pour simuler l'ensemble de l’organisation de manière fine. L'évacuation d’un hôpital dans le cadre d’un plan blanc étendu à plusieurs hôpitaux pour faire face à un tsunami fluvial a été considérée comme scénario pour évaluer la justesse de notre approche. Les catastrophes d'origine humaine et la propagation des maladies peuvent donner lieu à des désastres de grande ampleur qui mobilisent de nombreuses ressources humaines et matérielles. Par exemple, un modèle de réponse logistique face à une attaque bioterroriste avec un agent non-contagieux ainsi qu’un modèle pour la réponse logistique aux épidémies ont été proposés. Elles traduisent un problème de gestion d’inventaire multi-échelons et multi-périodes. Ces deux modèles dynamiques de flux requièrent une optimisation linéaire et une optimisation non-linéaire respectivement. Ils intègrent les caractéristiques de la gestion de ces catastrophes: la propagation de l’infection ou de la maladie, les réponses médicales appropriées et le déploiement de la logistique associée. Avec ces deux modèles, le nombre de patients aux différents stades de la maladie et le nombre des ressources médicales nécessaires pour chaque période peuvent être calculés. Les facteurs qui influent sur le nombre de décès et l’efficience des différentes politiques d'intervention médicale, peuvent également être évalués. Les deux modèles peuvent ainsi aider les décideurs à prévoir les conséquences de la situation en cas de catastrophe ainsi que de connaître les informations d'une réponse pertinente, ceci à un niveau stratégique. Une réponse logistique à une attaque bioterroriste anonyme à l'anthrax dans un centre commercial et une réponse logistique à une pandémie H5N1 sont pris comme scénarios pour tester l'efficacité des modèles correspondantsThis thesis is devoted to optimize the health care logistics which can support emergency management plans to reduce the impacts of natural and/or man-made disasters. After the review of relevant papers, two main gaps have been found in the current studies. One is that most of the researches are not based on real cases. The other is that some main characteristics of disasters are neglected when disasters are studied. Therefore, based on real case scenarios, the thesis studies different disasters (natural and/or man-made disasters) separately according to the characteristics of disasters. Natural disasters may be predicted but are difficult to avoid. Therefore, the evacuation of potential victims and the dimensioning of relief resources are crucially important. A three-step approach is proposed to study the resource dimensioning and the organization of emergency management plan (French White Plan) facing natural disasters. In our three-step approach, the first step builds a framework model to get the insights of emergency management plan clearly. The second step establishes a global model (a linear model) to predict the quantity of required resources for evacuation. The third step proposes a detailed simulation model to reflect the real world more precisely. The hospital evacuation under the guidance of a French Extended White Plan in case of a flood has been taken as a real case scenario to test the correctness of our approach. The man-made disasters and the outbreak of diseases can be large-scale disasters which require a high demand of resources. In this thesis, a model for logistics response to bioterrorist attack with a non-contagious agent and another model for the logistics response to epidemics have been proposed. Multi-period and multi-echelon inventory management problems have been studied. The two models (a linear model and a non linear model respectively) combine the main characteristics of disasters: the propagation of the disease, the relevant medical interventions and the logistics deployment together. The number of patients in different disease stages and the required medical resources for each period can be estimated. The factors affecting the number of deaths and the different medical intervention policies can also be evaluated with the two models. With the help of the models, the decision makers can get an idea of the disaster situation and the relevant medical responses from a strategy level. A logistics response to an anonymous bioterrorist attack with anthrax to a shopping center and the logistics response to the outbreak of H5N1 are taken as real case scenarios to test the effectiveness of the models respectively
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Chandratilake, (nee Weerasekara) Sonali Evanjali. "Spatial Modelling of Gastroenteritis Prevalence Following the February 22, 2011 Earthquake and Identification of Successful Factors Preventing Outbreaks at Emergency Centres". Thesis, University of Canterbury. Department of Geological Sciences, 2013. http://hdl.handle.net/10092/9185.
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The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours).
The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours).
The aim of this multidisciplinary research was to retrospectively analyse the gastroenteritis prevalence following the February 22, 2011 earthquake in Christchurch. The first focus was to assess whether earthquake-induced infrastructure damage, liquefaction, and gastroenteritis agents spatially explained the recorded gastroenteritis cases over the period of 35 days following the February 22, 2011 earthquake in Christchurch. The gastroenteritis agents considered in this study were Escherichia coli found in the drinking water supply (MPN/100mL) and Non-Compliant Free Associated Chlorine (FAC-NC) (less than <0.02mg/L). The second focus was the protocols that averted a gastroenteritis outbreak at three Emergency Centres (ECs): Burnside High School Emergency Centre (BEC); Cowles Stadium Emergency Centre (CEC); and Linwood High School Emergency Centre (LEC).
Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach.
Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC.
Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols and indirect themes included type of EC building (school or a sports stadium), and EC staff. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss.
This research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally
Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. A damage profile was created by amalgamating different types of damage for the considered factors for each Census Area Unit (CAU) in Christchurch. The damage profile enabled the application of a variety of statistical methods which included Moran’s I , Hot Spot (HS) analysis, Spearman’s Rho, and Besag–York–Mollié Model using a range of software. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach.
Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC.
Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. The ECs were selected to represent the Christchurch area, and were situated where potential for gastroenteritis was high. BEC represented the western side of Christchurch; whilst, CEC and LEC represented the eastern side, where the potential for gastroenteritis was high according to the outputs of the quantitative spatial modelling. Qualitative analysis from the interviews at the ECs revealed that evacuees were arriving at the ECs with gastroenteritis-like symptoms. Participants believed that those symptoms did not originate at the ECs. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols that included prolific use of hand sanitisers; surveillance; and the services offered. Indirect themes included the EC layout, type of EC building (school or a sports stadium), and EC staff. Indirect themes governed the quality and sustainability of the direct themes implemented, which in turn averted gastroenteritis outbreaks at the ECs. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss.
It was concluded that gastroenteritis point prevalence following the February 22, 2011 earthquake could not be solely explained by earthquake-induced infrastructure damage, liquefaction, and gastroenteritis causative agents alone. However, this research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Creating a damage profile for each CAU and using spatial data analysis can isolate vulnerable areas, and qualitative data analysis provides localised information. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally.
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Dufresne, Anja. "Influence of runout path material on rock and debris avalanche mobility : field evidence and analogue modelling : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Geological Sciences/Hazard and Disaster Management, University of Canterbury, New Zealand /". Thesis, University of Canterbury. Geological Sciences, 2009. http://hdl.handle.net/10092/3076.
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Rock and debris avalanches result from sudden rock slope failure; they occur in a variety of materials and landscapes, and often have a catastrophic and lasting impact on the society, infrastructure, and landscape of the area. In order to fully understand these events, the factors leading to failure and those influencing the course of the event must be investigated. In recent years, increased attention has been given to numerous aspects of rock/debris avalanche emplacement: among these is the influence of runout path material on the behaviour of snow and ice avalanches, pyroclastic currents, debris flows, volcanic debris avalanches and non-volcanic rock avalanches. The fact that substrates are involved in rock avalanche emplacement has been known since Buss and Heim remarked on it in 1881, but few detailed studies on the effects of this involvement on avalanche emplacement exist. One popular hypothesis which has emerged is that the long runout of large rock avalanches can be explained by the basal friction reduction due to overrunning or failure of saturated substrate material. However, the present study shows that this is not the case. From analysis of nearly 400 rock and debris avalanche deposit descriptions it is evident that: (1) avalanches inevitably interact with their runout path material; (2) all large (> 10⁶ m³) rock and debris avalanche events have runout distances that exceed simple frictional model predictions regardless of type or degree of substrate interaction; (3) substrates only add complexities to the ‘long-runout’ avalanche events similar to topographic interference. The complexities resulting from substrate interaction include, for example, characteristic deposit surface features such as longitudinal ridges and flowbands, compressional faults and raised margins from rapid deceleration behind e.g. bulldozed substrates; shearing in a basal mixed zone and consequent changes in basal avalanche mechanical properties; volcanic edifice failure on weak underlying sediments with a change in volcano shape; transformation into more mobile debris flows through the entrainment of large quantities of water or water-bearing materials; and many others.
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Hill, Rebecca Elizabeth Jane. "Diagnosing co-ordination problems by modelling the emergency management response to disasters". Thesis, University College London (University of London), 2005. http://discovery.ucl.ac.uk/1420898/.
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In the United Kingdom, there is a system for the co-ordination of the emergency services in response to disasters - The Emergency Management Combined Response System (EMCRS). It is a complex three tier command and control system. It was set up in response to a need for better coordination between agencies, when they respond to disasters. This research has developed models of the EMCRS that support diagnosis of co-ordination problems between agencies. Data for the modelling was acquired by means of training exercises. The co-ordination pro blems were identified through behaviour conflicts between the agencies. For example, the Fire Service behaviours of setting up a cordon around the disaster site conflict with the Ambulance Service behaviours of accessing the site for treatment of casualties. In the course of EMCRS model development, the scope of an existing framework was extended to accommodate EMCRS characteristics, which are general to: (i) systems with more than one level of operation and interactions between the levels; (ii) systems that do not have stable membership; and (iii) systems where there are trade-offs between different parts of the system that affect performance. For example, the framework extension for (ii) is to include time lines and a symbol that denotes additional structures. The EMCRS models constitute substantive Human Computer Interaction design knowledge, that is, knowledge that is both explicit and supports design. Such knowledge supports design practice directly, as the diagnosis of design problems, and indirectly, as the prescription of design solutions. An initial method for coordination design problem diagnosis by means of EMCRS models is also proposed. The strengths and weaknesses of the research are identified and discussed. Future work would be to apply the extended framework to data from an actual disaster to valid ate the EMCRS models.
Livros sobre o assunto "Disaster modelling"
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Integrated Catastrophe Risk Modelling. Springer, 2012.
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Hillier, John, Matthew Jones, Kirsten Mitchell-Wallace e Matthew Foote. Natural Catastrophe Risk Management and Modelling: A Practitioner's Guide. Wiley & Sons, Limited, John, 2017.
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Hillier, John, Matthew Jones, Kirsten Mitchell-Wallace e Matthew Foote. Natural Catastrophe Risk Management and Modelling: A Practitioner's Guide. Wiley & Sons, Incorporated, John, 2017.
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Hillier, John, Matthew Jones, Kirsten Mitchell-Wallace e Matthew Foote. Natural Catastrophe Risk Management and Modelling: A Practitioner's Guide. Wiley & Sons, Incorporated, John, 2017.
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Hillier, John, Matthew Jones, Kirsten Mitchell-Wallace e Matthew Foote. Natural Catastrophe Risk Management and Modelling: A Practitioner's Guide. Wiley-Blackwell, 2017.
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Wang, Chisheng, Daqing Ge, Guohong Zhang, Wu Zhu e Siting Xiong, eds. Monitoring and Modelling of Geological Disasters Based on InSAR Observations. MDPI, 2023. http://dx.doi.org/10.3390/books978-3-0365-6381-7.
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Huang, Faming, Jinsong Huang, Wei Chen e Jinquan Liu, eds. Spatial Modelling and Failure Analysis of Natural and Engineering Disasters through Data-based Methods. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-83250-177-1.
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Adhikari, Neill KJ. Critical Illness and Long-Term Outcomes Worldwide. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199653461.003.0002.
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Interest in the global burden of critical illness and its sequelae are growing, but comprehensive data to describe the burden of acute and post-acute illness and the resources available to provide care are lacking. Challenges to obtaining population-based global estimates of critical illness include the syndrome-based definitions of critical illness, incorrect equating of ‘critical illness’ with ‘admission to an intensive care unit’, lack of reliable case ascertainment in administrative data, and short prodrome and high mortality of critical illness, limiting the number of prevalent cases. Estimates of the burden of post-critical illness morbidity are even less reliable, owing to the limited number of observational studies, inaccurate coding in administrative data, and the unclear attributable risk of these morbidities to critical illness. Modelling techniques will be required to estimate the burden of critical illness and disparities in access to critical care using existing data sources. Demands for critical care and post-discharge care for survivors are likely to increase because of urbanization, an ageing demographic, and ongoing wars, disasters, and pandemics, while the ability to assume the cost of increased critical care may be limited due to economic factors. Major public health questions remain unanswered regarding the worldwide burden of critical illness and its sequelae, variation in resources available for treatment, and strategies that are broadly effective and feasible to prevent and treat critical illness and its consequences.
Capítulos de livros sobre o assunto "Disaster modelling"
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Stanković, Igor, Milan Žeželj, Jelena Smiljanić e Aleksandar Belić. "Modelling of Disaster Spreading Dynamics". In High-Performance Computing Infrastructure for South East Europe's Research Communities, 31–42. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01520-0_4.
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Zwęgliński, Tomasz, Cor-Jan Vermeulen, Marcin Smolarkiewicz, Anna Foks-Ryznar, Karolina Bralewska e Bernard Wiśniewski. "Dynamic Flood Modelling in Disaster Response". In Innovation in Crisis Management, 173–97. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003256977-14.
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Lohani, A. K., Sanjay K. Jain e R. K. Jaiswal. "Glacial Lake Outburst Flood Modelling". In 5th World Congress on Disaster Management, 413–19. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003341932-41.
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Morlok, Jürgen, e Jan Siegmund. "The Ecological Disaster of Bitterfeld and Chicken Games". In Mathematical Modelling in Economics, 458–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_44.
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Seminara, Giuseppe, e Daniele Fontanelli. "First Responders Robotic Network for Disaster Management". In Modelling and Simulation for Autonomous Systems, 350–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76072-8_25.
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Windirsch, Melanie. "Empirical Modelling of Man-made Disaster Scenarios". In Palgrave Studies in Sustainable Business In Association with Future Earth, 329–63. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-38858-4_15.
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Malakar, Sukanta, Abhishek K. Rai, Mohd Sayeed Ul Hasan e Vijay K. Kannaujiya. "Geospatial Modelling of Seismic Vulnerability Using Entropy-AHP: A Case Study of the Himalayas". In Disaster Risk Reduction, 27–46. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65862-4_3.
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Cuomo, Sabatino, Angela Di Perna e Mario Martinelli. "MPM Modelling of Buildings Impacted by Landslides". In Understanding and Reducing Landslide Disaster Risk, 245–66. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60319-9_28.
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Peña, Neiler de Jesús Medina. "Multi-Hazard Modelling". In Adaptive Disaster Risk Assessment Combining Multi-Hazards With Socioeconomic Vulnerability and Dynamic Exposure, 77–90. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003220749-4.
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Biradar, Girish, e Swati Bhave. "Flood Modelling of Krishna River at Sangli Using HEC-RAS". In Disaster Resilience and Green Growth, 355–62. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7100-6_19.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Disaster modelling"
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ŠTEINBERGA, IVETA, IVARS KUDREŅICKIS e RAIMONDS ERNŠTEINS. "COASTAL SOCIO-ECOLOGICAL SYSTEM ASSESSMENT IN MUNICIPALITIES: SYSTEM DYNAMICS MODELLING APPLICATION IN LATVIA". In DISASTER MANAGEMENT 2021. Southampton UK: WIT Press, 2021. http://dx.doi.org/10.2495/dman210071.
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Aschenbruck, Nils, Elmar Gerhards-Padilla, Michael Gerharz, Matthias Frank e Peter Martini. "Modelling mobility in disaster area scenarios". In the 10th ACM Symposium. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1298126.1298131.
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Al-Essa, Hadeel A., e Abdulrahman A. Abdulbaki. "Disaster Recovery Datacenter’s Architecture on Network Replication Solution". In 2016 European Modelling Symposium (EMS). IEEE, 2016. http://dx.doi.org/10.1109/ems.2016.038.
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Aschenbruck, Nils, Michael Gerharz, Matthias Frank e Peter Martini. "Modelling Voice Communication in Disaster Area Scenarios". In 2006 31st IEEE Conference on Local Computer Networks. IEEE, 2006. http://dx.doi.org/10.1109/lcn.2006.322102.
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Malkina-Pykh, I. G. "Evaluating psychological preparedness for the threat and impacts of climate change disasters and its change after intervention: an integrated modelling approach". In DISASTER MANAGEMENT 2015, editado por Y. A. Pykh. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/dman150231.
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"Cascading events simulation for disaster-sensitive metropolitan areas: Resilience enhancement with visualization of consequences of large-scale disasters". In 25th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, 2023. http://dx.doi.org/10.36334/modsim.2023.watanabe.
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Guillaume, Eric, Virginie Dréan, Bertrand Girardin e Talal Fateh. "Modelling Grenfell disaster: interactions between facades and apartments". In 11th International Conference on Structures in Fire (SiF2020). Brisbane, Australia: The University of Queensland, 2020. http://dx.doi.org/10.14264/929e2f2.
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Barbierato, Enrico, Mauro Iacono, Marco Gribaudo e Michele Mastroianni. "Cost- And Performance-Based Evaluation Of Cloud-Based Disaster Recovery". In 37th ECMS International Conference on Modelling and Simulation. ECMS, 2023. http://dx.doi.org/10.7148/2023-0568.
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Cloud platforms offer not only the capacity to facilitate effective and scalable services for third-party applications and business solutions, but also present an opportunity to implement intricate disaster recovery strategies. For instance, a Chief Technical Officer may opt to maintain operations on private systems in order to effectively manage costs, privacy, and security, while simultaneously leveraging the cloud as an autonomous and immediate disaster recovery support. This can be achieved by building a secondary leg of the IT system that functions as an online cold or hot spare, manages workload peaks, or handles a portion of the workload under normal conditions. To assess the effectiveness and cost-effectiveness of such solutions, appropriate models are essential to examine the trade-offs and explore the parameter space of possible alternatives. This paper presents a modeling approach for the design and evaluation of cloud-based recovery setups.
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Kantorovitch, Julia, Aggeliki Giakoumaki, Antonis Korakis, Homer Papadopoulos, Georgios Milis, Panayiotis Kolios e Toni Staykova. "Knowledge modelling framework". In 2015 2nd International Conference on Information and Communication Technologies for Disaster Management (ICT-DM). IEEE, 2015. http://dx.doi.org/10.1109/ict-dm.2015.7402037.
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Jangid, Nitesh, e Bindu Sharma. "Cloud Computing and Robotics for Disaster Management". In 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS). IEEE, 2016. http://dx.doi.org/10.1109/isms.2016.45.
Texto completo da fonteRelatórios de organizações sobre o assunto "Disaster modelling"
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Sett, Dominic, Florian Waldschmidt, Alvaro Rojas-Ferreira, Saut Sagala, Teresa Arce Mojica, Preeti Koirala, Patrick Sanady et al. Climate and disaster risk analytics tool for adaptive social protection. United Nations University - Institute for Environment and Human Security, março de 2022. http://dx.doi.org/10.53324/wnsg2302.
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Adaptive Social Protection (ASP) as discussed in this report is an approach to enhance the well-being of communities at risk. As an integrated approach, ASP builds on the interface of Disaster Risk Management (DRM), Climate Change Adaptation (CCA) and Social Protection (SP) to address interconnected risks by building resilience, thereby overcoming the shortcomings of traditionally sectoral approaches. The design of meaningful ASP measures needs to be informed by specific information on risk, risk drivers and impacts on communities at risk. In contrast, a limited understanding of risk and its drivers can potentially lead to maladaptation practices. Therefore, multidimensional risk assessments are vital for the successful implementation of ASP. Although many sectoral tools to assess risks exist, available integrated risk assessment methods across sectors are still inadequate in the context of ASP, presenting an important research and implementation gap. ASP is now gaining international momentum, making the timely development of a comprehensive risk analytics tool even more important, including in Indonesia, where nationwide implementation of ASP is currently under way. OBJECTIVE: To address this gap, this study explores the feasibility of a climate and disaster risk analytics tool for ASP (CADRAT-ASP), combining sectoral risk assessment in the context of ASP with a more comprehensive risk analytics approach. Risk analytics improve the understanding of risks by locating and quantifying the potential impacts of disasters. For example, the Economics of Climate Adaptation (ECA) framework quantifies probable current and expected future impacts of extreme events and determines the monetary cost and benefits of specific risk management and adaptation measures. Using the ECA framework, this report examines the viability and practicality of applying a quantitative risk analytics approach for non-financial and non-tangible assets that were identified as central to ASP. This quantitative approach helps to identify cost-effective interventions to support risk-informed decision making for ASP. Therefore, we used Nusa Tenggara, Indonesia, as a case study, to identify potential entry points and examples for the further development and application of such an approach. METHODS & RESULTS: The report presents an analysis of central risks and related impacts on communities in the context of ASP. In addition, central social protection dimensions (SPD) necessary for the successful implementation of ASP and respective data needs from a theoretical perspective are identified. The application of the quantitative ECA framework is tested for tropical storms in the context of ASP, providing an operational perspective on technical feasibility. Finally, recommendations on further research for the potential application of a suitable ASP risk analytics tool in Indonesia are proposed. Results show that the ECA framework and its quantitative modelling platform CLIMADA successfully quantified the impact of tropical storms on four SPDs. These SPDs (income, access to health, access to education and mobility) were selected based on the results from the Hazard, Exposure and Vulnerability Assessment (HEVA) conducted to support the development of an ASP roadmap for the Republic of Indonesia (UNU-EHS 2022, forthcoming). The SPDs were modelled using remote sensing, gridded data and available global indices. The results illustrate the value of the outcome to inform decision making and a better allocation of resources to deliver ASP to the case study area. RECOMMENDATIONS: This report highlights strong potential for the application of the ECA framework in the ASP context. The impact of extreme weather events on four social protection dimensions, ranging from access to health care and income to education and mobility, were successfully quantified. In addition, further developments of CADRAT-ASP can be envisaged to improve modelling results and uptake of this tool in ASP implementation. Recommendations are provided for four central themes: mainstreaming the CADRAT approach into ASP, data and information needs for the application of CADRAT-ASP, methodological advancements of the ECA framework to support ASP and use of CADRAT-ASP for improved resilience-building. Specific recommendations are given, including the integration of additional hazards, such as flood, drought or heatwaves, for a more comprehensive outlook on potential risks. This would provide a broader overview and allow for multi-hazard risk planning. In addition, high-resolution local data and stakeholder involvement can increase both ownership and the relevance of SPDs. Further recommendations include the development of a database and the inclusion of climate and socioeconomic scenarios in analyses.
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Hobbs, T. E., J. M. Journeay, A. S. Rao, L. Martins, P. LeSueur, M. Kolaj, M. Simionato et al. Scientific basis of Canada's first public national seismic risk model. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330927.
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Natural Resources Canada, in partnership with the Global Earthquake Model Foundation, has prepared a public Canadian Seismic Risk Model to support disaster risk reduction efforts across industry and all levels of government, and to aid in Canada's adoption of the Sendai Framework for Disaster Risk Reduction. Developing this model has involved the creation of a national exposure inventory, Canadian specific fragility and vulnerability curves, and adjustment of the Canadian Seismic Hazard Model which forms the basis for the seismic provisions of the National Building Code of Canada. Using the Global Earthquake Model Foundation's OpenQuake Engine (OQ), risk modelling is completed using both deterministic and probabilistic risk calculations, under baseline and simulated retrofit conditions. Output results are available in all settled regions of Canada, at the scale of a neighbourhood or smaller. We report on expected shaking damage to buildings, financial losses, fatalities, and other impacts such as housing disruption and the generation of debris. This paper documents the technical details of the modelling approach including a description of novel datasets in use, as well as preliminary results for a magnitude 9.0 earthquake on the Cascadia megathrust and nation-wide 500 year expected probabilistic losses. These kinds of results, such as earthquake scenario impacts, loss exceedance curves, and annual average losses, provide a quantitative base of evidence for decision making at local, regional, and national levels.
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Kim, Kyungmee, e Boulanin Vincent. Artificial Intelligence for Climate Security: Possibilities and Challenges. Stockholm International Peace Research Institute, dezembro de 2023. http://dx.doi.org/10.55163/qdse8934.
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Recent advances in artificial intelligence (AI)—largely based on machine learning—offer possibilities for addressing climate-related security risks. AI can, for example, make disaster early-warning systems and long-term climate hazard modelling more efficient, reducing the risk that the impacts of climate change will lead to insecurity and conflict. This SIPRI Policy Report outlines the opportunities that AI presents for managing climate-related security risks. It gives examples of the use of AI in the field and delves into the problems—notably methodological and ethical—associated with the use of AI for climate security. The report concludes with recommendations for policymakers and researchers who are active in the area of climate security or who use AI for sustainability.
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Rahman, Kazi, Grace Lee, Kristina Vine, Amba-Rose Atkinson, Michael Tong e Veronica Matthews. Impacts of climate change on health and health services in northern New South Wales: an Evidence Check rapid review. The Sax Institute, dezembro de 2022. http://dx.doi.org/10.57022/xlsj7564.
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This rapid review investigated the effects of climate change on health and health services in northern NSW—a known ‘hotspot’ for natural disasters—over the next 10-20 years. It included 92 peer-reviewed articles and 9 grey literature documents, with 17% focused on Northern NSW. Climate change will cause both an increase in average temperatures and in extreme weather events and natural disasters. Impacts particularly affecting Northern NSW are expected to include increases and exacerbations of: mental illness; infectious diseases, including those transmitted by mosquitoes, water and food; heat-related illnesses; chronic diseases including respiratory and cardiac conditions; injuries; and mortality—with vulnerable groups being most affected. Demand for health services will increase, but there will also be disruptions to medication supply and service availability. A whole-of-system approach will be needed to address these issues. There are numerous gaps in the research evidence and a lack of predictive modelling and robust locally relevant data.
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Public investment profile for climate risk reduction in Barbados: a macroeconomic cost-benefit analysis for reducing the socio-economic risk of coastal erosion. Inter-American Development Bank, dezembro de 2021. http://dx.doi.org/10.18235/0003915.
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The “Study on Disaster Risk Management A macroeconomic cost-benefit analysis for reducing the socio-economic risk of coastal erosion”, a dynamic modelling approach was developed to quantify the macroeconomic costs and benefits of investment in disaster risk reduction. The goal of the developed tool was multifaceted, with emphasis on assessing mixes of disaster risk reduction and financial protection instruments, and with a focus on addressing shortfalls in current disaster risk modelling methods. This work serves as the final report of the project and presents the results of an application of the developed Dynamic Model of Multi-hazard Mitigation Co-benefits (DYNAMMICs) framework to the country case of Barbados, demonstrating the applicability of the approach through empirical assessment of DRR investment options to combat coastal hazards facing the island country.