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Journal articles on the topic 'Disaster modelling'
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Mishra, Vinaytosh, and Mohita G. Sharma. "Understanding Humanitarian Supply Chain Through Causal Modelling." South Asian Journal of Business and Management Cases 9, no. 3 (November 25, 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, and Yusuke Shintani. "Virtual Reality approaches for evacuation simulation of various disasters." Collective Dynamics 5 (August 12, 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, and Quanyi Huang. "Ontology-based representation of meteorological disaster system and its application in emergency management." Kybernetes 45, no. 5 (May 3, 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., and U. D’Alessandro. "Modelling a Predictable Disaster:." Parasitology Today 16, no. 8 (August 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, and Afif Ahmarofi. "A Theoretical Review on the Preventive Measures to Landslide Disaster Occurrences in Penang State, Malaysia." Journal of Social Sciences Research, SPI6 (December 25, 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, and Jason Von-Meding. "Modelling the Roles of Community-Based Organisations in Post-Disaster Transformative Adaptation." GeoHazards 3, no. 2 (April 11, 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, and Surya Durbha. "STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 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, and Surya Durbha. "STOCHASTIC COLOURED PETRINET BASED HEALTHCARE INFRASTRUCTURE INTERDEPENDENCY MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 22, 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, and Apip Apip. "Aesthetics 3D Geovisualization For Flood Disaster Based on XYZ Coordinate." Journal of Applied Research and Technology 21, no. 4 (August 31, 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, and Elena Naumova. "Natural Disaster and Migration Trends in Flood Prone Agricultural Areas of Indonesia." Current Developments in Nutrition 6, Supplement_1 (June 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.
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KURWAKUMIRE, Edward, Shelter KUZHAZHA, and Paul MUCHECHETERE. "Informal cadastres as enabling tools for disaster risk management." European Journal of Geography 12, no. 2 (October 13, 2021): 52–73. http://dx.doi.org/10.48088/ejg.e.kur.12.2.052.073.
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Disaster Risk Management requires up-to-date land information availed through the cadastre. Informal settlements are often located in disaster prone areas. Having up-to-date land information about these informal settlements is one step towards disaster preparedness and building community resilience in the highway towards sustainable development. This study designs conceptual models using unified modelling language (UML) for an informal cadastre for recording land information pertinent to disaster risk management based on a South African case study. The results demonstrate that land tenure relationships in informal settlements can be mapped using the Social Tenure Domain Model (STDM). The importance of disaster information is that it provides communities with information to tackle disasters and improve in their capabilities to handle them. With such information, the disaster risk can be minimised. This study is aligned to Sustainable Development Goals (SDGs) 1 and 3. The linkage between spatial data, disaster resilience and the SDGs is explored.
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Wang, Zhi-Lan, Jing Wang, and Jin-Song Wang. "Risk Assessment of Agricultural Drought Disaster in Southern China." Discrete Dynamics in Nature and Society 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/172919.
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Risk assessment of drought disaster is necessary for the sustained agriculture development under the background of global climate change, and, meanwhile, it is an urgent scientific issue needed to be solved in agricultural risk assessment discipline. In this paper, collecting the areas covered by drought disasters, areas affected by drought disasters, areas with no harvest by drought disasters, areas planted, and yield per unit area data, agricultural drought disasters losses of the southern five provinces in China were calculated. The best probability density function was obtained according to the goodness of fit test results. Then, the value at risk (VaR) from financial market risk research method was used to the effective measure of agricultural drought risk. The results show that, in southern five provinces of our research region, risk of agricultural drought disaster in Yunnan and Guizhou is greater than other three provinces. In the scenario of 50 years and 100 years for a return, the crop loss caused by drought will reach 13.6% and 17.4% in Yunnan province, and the crop loss will be more serious in Guizhou province and be up to 15.3% and 18.1%. The above results can provide multifaceted information about drought risk that can help to guide management of drought disasters.
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Abu Bakar, Noor Akma, Noridayu Mah Hashim, Afrig Aminuddin, Siti Aishah Zakaria, and Mazlina Abdul Majid. "Towards Effective Evacuation Procedures in Disaster Management (Dm): Simulation Modelling and Governance Strategies." Journal of Governance and Integrity 6, no. 1 (May 14, 2023): 483–94. http://dx.doi.org/10.15282/jgi.6.1.2023.9159.
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Natural catastrophes and disasters may cause the destruction of infrastructure and personal property. In order to reduce the effects of such tragedies, the effectiveness of the evacuation procedures is essential. Effective evacuation procedures, however, also depend on governance issues in addition to technical aspects like infrastructure and communication. This paper intends to review on how governance, and evacuation protocols relate to emergency preparedness and disaster management (DM). Thus, this study explores the use of agent-based and social force theory in developing evacuation simulation models that incorporate evacuation governance strategies. Practitioners and policymakers can better understand the elements that determine the effectiveness of evacuation procedures and create more efficient methods for disaster management and emergency response by modelling human behaviour in disaster circumstances. The policy is an illustration of how governance elements can be integrated into evacuation procedures and guidelines for effective DM. Thus, the expected result for this study emphasises the significance of governance for policymakers and practitioners in the execution of evacuation procedures.
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Musliman, I. A., and L. Yohnny. "Modelling airborne dispersion for disaster management." Journal of Physics: Conference Series 852 (May 2017): 012026. http://dx.doi.org/10.1088/1742-6596/852/1/012026.
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Kamara, Joseph K., Berhe W. Sahle, Kingsley E. Agho, and Andre M. N. Renzaho. "Governments’ Policy Response to Drought in Eswatini and Lesotho: A Systematic Review of the Characteristics, Comprehensiveness, and Quality of Existing Policies to Improve Community Resilience to Drought Hazards." Discrete Dynamics in Nature and Society 2020 (February 26, 2020): 1–17. http://dx.doi.org/10.1155/2020/3294614.
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The southern African kingdoms of Eswatini and Lesotho experience recurrent drought-induced disasters. Policies have been enacted, but no attempt has been made to synthesise the effects on disaster resilience. This review analyses the characteristics, quality, and comprehensiveness of drought-resilience policies in Eswatini and Lesotho. We have systematically reviewed public policies that shape responses to disaster resilience published between 1 January 1980 and 30 June 2019. A combination of keywords was used to search electronic bibliographic databases, multidisciplinary databases, key organisational websites, and the first 20 pages of Google for policies that addressed disaster and/or drought resilience. Identified documents were downloaded into an EndNote database and screened for eligibility using predetermined criteria. The logic of events framework was used for quality assessment, and a metaethnographic approach was applied for data synthesis. Three broad categories of characteristics, thematic outcomes and quality, and comprehensiveness of policy documents emerged and are presented. Policy responses contributing to disaster resilience were found in n = 32 out of 13,700 documents. Three (n = 3/32) policies were statutory, and the rest were nonstatutory. Eleven (n = 11/32) were assessed to be of high quality. Policy responses relating to drought resilience focused on reducing vulnerability to recurrent disasters; promoting drought and climate change adaptation; improving agriculture and food security; safeguarding cultural heritage; and preventing gender inequality and gender-based violence as well as improving disaster governance. However, the construct of drought resilience was not strongly articulated as a major policy goal across policy documents. There is an urgent need to promote better understanding of drought resilience in order to motivate policymakers to steer away from reactive interventions and position resilience as a major national policy goal in both countries to expedite inclusive growth and safeguard development gains and the health and wellbeing of the majority of their populations who are rural-based populations.
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Su, Benyu, Zhixiong Li, Rongyao Li, Rongfu Rao, and Jingcun Yu. "Exploration Disaster Source of Mine Water by Electromagnetic Radiation." Elektronika ir Elektrotechnika 26, no. 5 (October 27, 2020): 16–21. http://dx.doi.org/10.5755/j01.eie.26.5.25960.
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geological hazard in deep underground mining. Before the rock mass explosion, electromagnetic energy will radiate outward during the deformation and rupture of the coal rocks. Hence, it is possible to use the electromagnetic radiation to predict geological disasters in coal mines. A challenging task using the active source electromagnetic survey technique is to detect geological anomalies, such as disaster water sources and geological structures. To this end, this paper proposes a new electromagnetic radiation solution based on the forward and inversion theory to detect geological anomalies in the coal seam. Based on typical coal mine geological models, the forward modelling and inversion modelling have been performed, respectively. The forward modelling explained the geological anomalies inside the coal seam, which were very sensitive to the response of the radiated electromagnetic field; especially, for the water-bearing geological anomalies. The inversion modelling discovered that the inversion geo-electric parameter distribution agreed well with the actual model. As a result, the proposed method is feasible for geological anomalies detection.
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Martha, Taufik, Purnawan Purnawan, and Hendra Gunawan. "PEMODELAN DAN PREDIKSI KEBUTUHAN LOGISTIK PASCA BENCANA DI SUMATERA BARAT." Rang Teknik Journal 4, no. 1 (January 7, 2021): 188–98. http://dx.doi.org/10.31869/rtj.v4i1.2292.
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Sumatera is one if the areas that is located in the high land. Geographically, it is lied in the volcanic high land that is formed by Bukit barisan Mountain range Sumatera Barat which is rich in natural resources. But unfortunately, due ti its location, West Sumatera has also potentials to various natural disasters like earth quake, tsunami, landslide, land movement, flood and fire if compared to other areas as mentioned in National Action Plan for Disaster Risk Reduction 2012. There have been many preventive actions that have been done by the government. However, those actions are not accompanied by disaster logistics improvement. Modelling is undergone by optimizing the needs pf disaster logistics by considering the characteristics of disaster prone areas. This research is intended to predict the logistics needs by optimizing the needs of disaster victims in west sumatera. The method used is regression analysis by predicting yearly disaster logistics needs. The result of this research showed that the best mode is Y=401.81 + 0.001X1 + 14.55X6 + 37.58X9 – 10.53X14 with the prediction increase of the logistics needs for about 2.3% every year.
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Cao, Xiaoqin, Ziming Liu, Chenlin Hu, Xiaolong Song, Jonathan Atuquaye Quaye, and Ning Lu. "Three-Dimensional Geological Modelling in Earth Science Research: An In-Depth Review and Perspective Analysis." Minerals 14, no. 7 (June 29, 2024): 686. http://dx.doi.org/10.3390/min14070686.
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This study examines the development trajectory and current trends of three-dimensional (3D) geological modelling. In recent years, due to the rising global energy demand and the increasing frequency of regional geological disasters, significant progress has been made in this field. The purpose of this study is to clarify the potential complexity of 3D geological modelling, identify persistent challenges, and propose potential avenues for improvement. The main objectives include simplifying the modelling process, improving model accuracy, integrating different data sources, and quantitatively evaluating model parameters. This study integrates global research in this field, focusing on the latest breakthroughs and applications in mineral exploration, engineering geology, geological disaster assessment, and military geosciences. For example, unmanned aerial vehicle (UAV) tilt photography technology, multisource data fusion, 3D geological modelling method based on machine learning, etc. By identifying areas for improvement and making recommendations, this work aims to provide valuable insights to guide the future development of geological modelling toward a more comprehensive and accurate “Transparent Earth”. This review underscores the global applications of 3D geological modelling, highlighting its crucial role across various sectors such as mineral exploration, the oil and gas industry, urban planning, geological hazard assessment, and geoscientific research. The review emphasizes the sector-specific importance of this technology in enhancing modelling accuracy and efficiency, optimizing resource management, driving technological innovation, and improving disaster response capabilities. These insights provide a comprehensive understanding of how 3D geological modelling can significantly impact and benefit multiple industries worldwide.
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Anuar, Wadi Khalid, Lai Soon Lee, Stefan Pickl, and Hsin-Vonn Seow. "Vehicle Routing Optimisation in Humanitarian Operations: A Survey on Modelling and Optimisation Approaches." Applied Sciences 11, no. 2 (January 12, 2021): 667. http://dx.doi.org/10.3390/app11020667.
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The growing field of humanitarian operations is driven by frequent events of disasters seen in the world today. Within this field, Operations Research (OR) plays a critical role in alleviating the suffering of victims that are impacted by disasters. This paper focuses on the branch of a well-known OR problem, known as the Vehicle Routing Problem (VRP), within the selected scope of humanitarian operations. A total of 123 papers of the last decade are reviewed and classified under the humanitarian operations of supply and delivery, evacuation as well as rescue operations. Besides specific disaster management phases and disaster types, various modelling challenges are highlighted, hinting towards a richer and more complex VRP seen under selected model characteristic classifications. Furthermore, established solution approaches, including hybrid solutions, are highlighted and classified, discussing how they are applied in the context of these humanitarian operations. The inclusion of a machine learning solution approach under the same classification is proposed. Finally, the trend and future outlook of VRP for the suggested humanitarian operations are discussed and highlighted.
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Gregory, Geoff. "Natural disaster." Bulletin of the New Zealand Society for Earthquake Engineering 31, no. 2 (June 30, 1998): 122–27. http://dx.doi.org/10.5459/bnzsee.31.2.122-127.
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The theme of the seminar, panel discussion and open forum, organised by the EQC and the Insurance Council, was Natural Disaster: Finding, managing, and sharing people and information. Emphasis was placed on the recovery and reconstruction phases, beginning about 10 days after the disaster occurred. To provide a focus for discussion, the scenario chosen was the Great Wellington Earthquake, for which fairly detailed modelling has been done, most notably for the Wellington after the Quake Conference, 1995. (1) The seminar was, in fact, a follow-up to that conference, at which various recommendations for action had been made, such as:
raising public awareness o f the recovery aspects of disasters;
planning for rebuilding, restoration, or relocation in advance of the disaster occurring so that the stress of immediacy and its effects on decision making are reduced;
ensuring that homeowners, the insurance and building industries, and owners of businesses and buildings have procedures in place to improve the effectiveness of efforts to restore normalcy to disaster-affected areas.(2)
The seminar was attended by about 100 participants, representing the insurance industry, territorial local authorities, emergency management/civil defence organisations (both local and central), the building industry, the engineering industry and professional engineering societies, and research organisations.
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Une, Hiroshi, and Takayuki Nakano. "Role of Geospatial Information for Disaster Risk Management as Exemplified in Recent Large Earthquakes in Japan." Advances in Cartography and GIScience of the ICA 1 (July 3, 2019): 1–8. http://dx.doi.org/10.5194/ica-adv-1-21-2019.
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<p><strong>Abstract.</strong> Geographic location is one of the most fundamental and indispensable information elements for us to work on disasters. For example, in the case of the Tohoku Earthquake in 2011, aerial photos taken immediately after the earthquake greatly improved the information sharing among different government offices and facilitated the rescue and recovery operations, and maps prepared after the disasters have been assisting the rapid reconstruction of the affected local communities. In addition, in the case of the Kumamoto Earthquake in 2016, up-to-date geospatial information technologies were well applied to grasp the disaster situation such as UAVs and InSAR. Advancement of web mapping technology allows us to understand the situation by overlaying various location-specific data on base maps on the web and specify the areas which the activities should be focused on. 3D modelling technology enables realistic understandings of the relationship between disaster and topography. Geospatial information technology can support the proper judgement of preparation and emergency response against disaster by the individuals and local communities through such as hazard mapping and information services using mobile devices. Thus, geospatial information technology is now more and more taking vital role for all the stages of disaster risk management and responses. Acknowledging such vital role of geospatial information for disaster reduction, Sendai Framework for Disaster Risk Reduction 2015–2030, adopted at the Third United Nations World Conference on Disaster Risk Reduction repeatedly indicates the importance of use of geospatial information technology for disaster reduction.</p>
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Karami, Amir, Vishal Shah, Reza Vaezi, and Amit Bansal. "Twitter speaks: A case of national disaster situational awareness." Journal of Information Science 46, no. 3 (March 4, 2019): 313–24. http://dx.doi.org/10.1177/0165551519828620.
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In recent years, we have been faced with a series of natural disasters causing a tremendous amount of financial, environmental and human losses. The unpredictable nature of natural disasters behaviour makes it hard to have a comprehensive situational awareness (SA) to support disaster management. Using opinion surveys is a traditional approach to analyse public concerns during natural disasters; however, this approach is limited, expensive and time-consuming. Luckily, the advent of social media has provided scholars with an alternative means of analysing public concerns. Social media enable users (people) to freely communicate their opinions and disperse information regarding current events including natural disasters. This research emphasises the value of social media analysis and proposes an analytical framework: Twitter Situational Awareness (TwiSA). This framework uses text mining methods including sentiment analysis and topic modelling to create a better SA for disaster preparedness, response and recovery. TwiSA has also effectively deployed on a large number of tweets and tracks the negative concerns of people during the 2015 South Carolina flood.
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Mohapatra, Tapaswini, and Shailendra K. Mandal. "Statistical Framework to enhance Disaster Resilience: An Empirical Cyclone Disaster Assessment Model." Disaster Advances 17, no. 9 (July 31, 2024): 16–24. http://dx.doi.org/10.25303/179da016024.
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This research study delves into the critical dimension of social resilience within communities vulnerable to disasters, with a specific focus on the coastal areas of India. The study, conducted in cyclone-affected regions of Puri, emphasizes the significance of social resilience in effective disaster management. Through the analysis of 210 samples, we present a framework grounded in the exploration of bonding, bridging and linking social capital. While prior research acknowledges the need of social capital in enhancing resilience, this study contributes by quantitatively examining these relationships within the context of emerging disaster management frameworks. Utilizing structural equation modelling (SME) and statistical analysis, the research investigates how bonding, bridging and linking social capital impact disaster resilience. The survey results analyzed with specialized software like AMOS, SPSS reveal compelling insights: all three forms of social capital—bonding, bridging and linking are positively associated with impacting disaster resilience. This study leads social resilience research by providing empirical evidence supporting the hypothesis that social resilience is positively influenced by bonding, bridging and linking social capital. This finding highlights the importance of building and maintaining strong social connections to enhance social resilience.
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Iovine, Giulio, Michael Sheridan, Johannes Huebl, Manuel Pastor, Christoph Aubrecht, and Stefan Scheer. "Innovative modelling approaches for disaster risk reduction." Physics and Chemistry of the Earth, Parts A/B/C 49 (January 2012): 1–2. http://dx.doi.org/10.1016/j.pce.2012.08.004.
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Andrade, Ermeson, Ricardo Lima, and Júlio Mendonça. "Evaluating and modelling solutions for disaster recovery." International Journal of Grid and Utility Computing 11, no. 5 (2020): 683. http://dx.doi.org/10.1504/ijguc.2020.10030947.
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Mendonça, Júlio, Ricardo Lima, and Ermeson Andrade. "Evaluating and modelling solutions for disaster recovery." International Journal of Grid and Utility Computing 11, no. 5 (2020): 683. http://dx.doi.org/10.1504/ijguc.2020.110055.
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Burkart, Christian, Pamela C. Nolz, and Walter J. Gutjahr. "Modelling beneficiaries’ choice in disaster relief logistics." Annals of Operations Research 256, no. 1 (January 9, 2016): 41–61. http://dx.doi.org/10.1007/s10479-015-2097-9.
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Nugrahani, Meiga, and Purnama Budi Santosa. "Drought Hazard Modelling of Klaten Regency Central Java Using AHP and TOPSIS Method." IOP Conference Series: Earth and Environmental Science 936, no. 1 (December 1, 2021): 012043. http://dx.doi.org/10.1088/1755-1315/936/1/012043.
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Abstract According to information of areas at high risk of drought provided by Central Java disaster risk assessment in 2016 - 2020, Klaten Regency is in the top ten at high risk of drought in Central Java. Drought is an annual disaster in this region, which usually occurs during the dry season. The impact of the drought has caused some areas to experience a lack of clean water. For the purpose of disaster mitigation in anticipating and minimizing drought disasters losses, it is necessary to analyze the level of drought with a decision-making system by comparing two methods, namely the AHP with TOPSIS. Both methods are decision-making methods that are composed of various criteria to obtain an alternative sequence of choices. Both the AHP and TOPSIS methods produces weight values and a positive ideal solution value, respectively. These are used as input data in the mapping of drought vulnerability analysis with Geographical Information Systems (GIS). The results of the analysis are visualized with a map that shows the level of drought vulnerability. AHP and TOPSIS method decision making generates the order of the drought classes in predicting the distribution of areas experiencing drought. To validate the model, the authors compare the results of the analysis of drought vulnerability of the two methods with drought data from BPBD (Local Agency for Disaster Prevention) and DPUPR (Public Works and Public Housing Department). The results show that AHP provides better results than TOPSIS based on results validation with BPBD and DPUPR data. By comparing the two models with BPBD data, the results show that the percentage of AHP suitability is higher than TOPSIS at 47,619% and 19,048% respectively.
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Zhu, Xiaoxiao, Shuhua Zhang, and Bingjun Li. "Prediction of Continuous Rain Disaster in Henan Province Based on Markov Model." Discrete Dynamics in Nature and Society 2020 (September 12, 2020): 1–6. http://dx.doi.org/10.1155/2020/7519215.
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Continuous rain disasters occur frequently, which seriously affect maize yield. However, the research on predicting continuous rain disasters is very limited. Taking the maize in Henan Province as an example, the Markov model is used to predict the occurrence of continuous rain in the middle growth and late growth stages (flowering and filling stages) of 13 cities in Henan Province. The results showed that the maize in Henan Province would suffer from continuous rain disaster in 2020 and 2021. Finally, combined with the prediction results, policy recommendations for maize growth in Henan Province are proposed to ensure stable and high yield of maize.
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Santillan, J. R., J. T. Marqueso, M. Makinano-Santillan, and J. L. Serviano. "BEYOND FLOOD HAZARD MAPS: DETAILED FLOOD CHARACTERIZATION WITH REMOTE SENSING, GIS AND 2D MODELLING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W1 (September 30, 2016): 315–23. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w1-315-2016.
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Flooding is considered to be one of the most destructive among many natural disasters such that understanding floods and assessing the risks associated to it are becoming more important nowadays. In the Philippines, Remote Sensing (RS) and Geographic Information System (GIS) are two main technologies used in the nationwide modelling and mapping of flood hazards. Although the currently available high resolution flood hazard maps have become very valuable, their use for flood preparedness and mitigation can be maximized by enhancing the layers of information these maps portrays. In this paper, we present an approach based on RS, GIS and two-dimensional (2D) flood modelling to generate new flood layers (in addition to the usual flood depths and hazard layers) that are also very useful in flood disaster management such as flood arrival times, flood velocities, flood duration, flood recession times, and the percentage within a given flood event period a particular location is inundated. The availability of these new layers of flood information are crucial for better decision making before, during, and after occurrence of a flood disaster. The generation of these new flood characteristic layers is illustrated using the Cabadbaran River Basin in Mindanao, Philippines as case study area. It is envisioned that these detailed maps can be considered as additional inputs in flood disaster risk reduction and management in the Philippines.
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Chybowska, Dorota, Leszek Chybowski, Jarosław Myśków, and Jerzy Manerowski. "Identification of the Most Important Events to the Occurrence of a Disaster Using Maritime Examples." Sustainability 15, no. 13 (July 5, 2023): 10613. http://dx.doi.org/10.3390/su151310613.
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Previous studies on maritime disasters have noted the importance of searching for their causal factors in the analysis of different types of vessels and various regions where accidents have occurred. The main objective of the study that this article presents was to develop a new approach to modelling and causal analysis of the course of maritime disasters in order to provide a holistic evaluation of this phenomenon. The novel approach adopted to support the thesis combined event network analysis and fault tree analysis (used in functional analysis for modelling the structures of systems) in the process analysis. The authors advanced a thesis that, in the studied population of disasters, there were dominant classes of basic events in each phase of the process during the course of a disaster (distinguished by means of an event network). Thirty maritime disasters that occurred between 1912 and 2019 were selected for quantitative and qualitative analyses. In each disaster, the different phases of its course were distinguished: latent, initiating, escalating, critical, and energy release. A total of 608 basic events were identified in the population, enabling the identification and characterisation of 44 classes of events. The importance of the events in each of the phases was calculated by means of importance measures. The findings confirmed the thesis. At the same time, an analysis of the importance of basic events in each phase revealed that the most common basic events are not always the most important.
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Une, Hiroshi, and Takayuki Nakano. "Recent innovation of geospatial information technology to support disaster risk management and responses." Proceedings of the ICA 1 (May 16, 2018): 1–4. http://dx.doi.org/10.5194/ica-proc-1-117-2018.
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Geographic location is one of the most fundamental and indispensable information elements in the field of disaster response and prevention. For example, in the case of the Tohoku Earthquake in 2011, aerial photos taken immediately after the earthquake greatly improved information sharing among different government offices and facilitated rescue and recovery operations, and maps prepared after the disaster assisted in the rapid reconstruction of affected local communities. Thanks to the recent development of geospatial information technology, this information has become more essential for disaster response activities. Advancements in web mapping technology allows us to better understand the situation by overlaying various location-specific data on base maps on the web and specifying the areas on which activities should be focused. Through 3-D modelling technology, we can have a more realistic understanding of the relationship between disaster and topography. Geospatial information technology can sup-port proper preparation and emergency responses against disasters by individuals and local communities through hazard mapping and other information services using mobile devices. Thus, geospatial information technology is playing a more vital role on all stages of disaster risk management and responses. In acknowledging geospatial information’s vital role in disaster risk reduction, the Sendai Framework for Disaster Risk Reduction 2015&ndash;2030, adopted at the Third United Nations World Conference on Disaster Risk Reduction, repeatedly reveals the importance of utilizing geospatial information technology for disaster risk reduction. This presentation aims to report the recent practical applications of geospatial information technology for disaster risk management and responses.
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Kunreuther, Howard, and Louis Miller. "Insurance versus Disaster Relief: An Analysis of Interactive Modelling for Disaster Policy Planning." Public Administration Review 45 (January 1985): 147. http://dx.doi.org/10.2307/3135009.
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Alexander, David. "Information technology in real-time for monitoring and managing natural disasters." Progress in Physical Geography: Earth and Environment 15, no. 3 (September 1991): 238–60. http://dx.doi.org/10.1177/030913339101500302.
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This paper considers the rôle of information technology in forecasting, monitoring and managing disasters in real-time (i.e., by analysis of data as soon as they are collected). First, the advantages and pitfalls of a technological approach to natural hazards are discussed, then the general nature of real-time technology is described. There follows a review of the appropriate techniques of monitoring the physical impacts of earthquakes, volcanic eruptions, tsunamis, floods and landslides. Next the rôle of information technology in disaster management is assessed, with emphasis on telecommunications and simulation modelling. As a cautionary note, two notorious failures of prediction and warning are discussed (the storm of October 1987 in England and the volcanic eruption disaster of November 1985 in Colombia), both of which would have benefited from more careful use of real-time monitoring. It is concluded that microcomputers, earth resources satellites, communications satellites and Geographical Information Systems offer considerable potential for natural disaster management, especially if real-time uses are developed by integrating these technologies.
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Geekiyanage, Devindi, Terrence Fernando, and Kaushal Keraminiyage. "Modelling Interrelationships of the Factors Impeding Community Engagement in Risk-Sensitive Urban Planning: Evidence from Sri Lanka." Sustainability 15, no. 20 (October 10, 2023): 14662. http://dx.doi.org/10.3390/su152014662.
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During the last two decades, global disasters have impacted over 5.2 billion people, with economic losses exceeding USD 2.97 trillion. This underscores the critical need for inclusive risk-sensitive urban planning (RSUP) that integrates community insights. Community-based disaster risk reduction (CBDRR) has demonstrated a potential reduction of up to 40% in mortality rates during disasters and cost savings in disaster response and recovery. However, research has shown that only 20% felt they are involved in decisions related to neighborhood planning, despite communities’ lived experience in surviving local hazards. This highlights a gap where practitioners dominate the development of mitigation and development plans, sidelining local perspectives. Using Sri Lanka as a case study, this study investigated the barriers to effective community participation in the decision-making of RSUP and thereby developed an interpretive logic model to establish an understanding of why they occur and how each barrier is interlinked. The data gathered from a sample of 44 experts and community representatives revealed 19 factors that impede community inclusion in the decision-making of RSUP in Sri Lanka. The Total Interpretive Structural Modelling (TISM) analysis adopted identified that the absence of legal provisions for inclusive development, political dynamics, and corruption are the most significant barriers. The Matrix Impact of Cross Multiplication Applied to Classification (MICMAC) further revealed that fewer financial provisions and the absence of an institutional framework for community engagement are the linking barriers to the other 17 barriers. This study not only extends the theoretical debate on barriers to community engagement for risk-responsive and equitable development but also helps urban planners, disaster management practitioners, and strategy policymakers focus on critical areas that need major reforms.
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Venkatesan, S., A. Rajabifard, N. T. K. Lam, E. F. Gad, H. M. Goldsworthy, and G. Griffin. "A Syncretic Approach Towards a Meta-Integrative Platform for Effective Disaster Management." International Journal of Geotechnical Earthquake Engineering 5, no. 1 (January 2014): 58–74. http://dx.doi.org/10.4018/ijgee.2014010104.
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Disaster management is widely recognised as a complex task. Despite well-established techniques, each disaster continues to frustrate the government and the community. A number of issues and challenges have been reported in the literature following a disaster. These include: a lack of awareness, authoritative support and direction, preparation and planning; ineffective response, ineffective communications and miscommunications, inadequate recovery and policy vacuum besides many other factors. Developing effective disaster management strategies to combat the known issues should also consider emerging drivers of change such as globalisation, climate change, and technological development, social construct of communities, global finance and education. In addition, fundamental hazard modelling techniques and real time modelling of a disaster cannot be ignored as they are central to the accuracy of information required during pre and post disasters. In recent times spatial information has been considered as the fourth element of decision making. Further the need to develop adaptive capacities and empower communities is also well stated. Despite the recognition of such complex issues, requirements, and increased knowledge, the pace of development seems to be inadequate. This is mainly due to the lack of an approach that can integrate the myriad of issues with the roles and responsibilities of stakeholders such as governments, practitioners and the community. Recognising the need to develop an informed decision making process, this paper reviews the challenges and issues based on current practice. A review of relevant new knowledge that can improve current practice is also undertaken. Based on these reviews it is identified that a spatially enabled platform can be developed to overcome the aforementioned issues related to disaster management. A preliminary roadmap in which the `stakeholder position' is considered as the vital point of integration is presented. It is anticipated that the roadmap will provide governments with the direction needed for future planning, policy development, implementation and control. Future developmental needs of the platform are also presented.
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Labib, Ashraf, M. Reza Abdi, Sara Hadleigh-Dunn, and Morteza Yazdani. "Evidence-based models to support humanitarian operations and crisis management." Decision Making: Applications in Management and Engineering 5, no. 1 (March 15, 2022): 113–34. http://dx.doi.org/10.31181/dmame030222100y.
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Term humanitarian operation (HO) is a concept extracted from the need to perform supply chain operations in special, risky, and critical events. Understanding and implementing operations under such conditions is a strategic responsibility. Due to its importance, we design a framework for organizational learning from major incidents through root cause analysis. The case studies contain a purely industrial disaster at Bhopal and a mixed industrial-natural disaster at Fukushima. An approach is proposed for organizational safety by incorporating techniques related to root cause analysis applied to one case study. Moreover, we employ the analytic hierarchy process, which is applied to the second case study. We incorporate operations management models to analyse data related to two major disasters. The case studies in two organizations are then compared with respect to their causes and effects along with the models adopted to support HO& crisis management (CM). The contribution is the use of hybrid modelling techniques to analyse disasters in terms of humanitarian operations and crisis management.
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Buzna, Lubos, Karsten Peters, and Dirk Helbing. "Modelling the dynamics of disaster spreading in networks." Physica A: Statistical Mechanics and its Applications 363, no. 1 (April 2006): 132–40. http://dx.doi.org/10.1016/j.physa.2006.01.059.
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Mishra, Deepa, Sameer Kumar, and Elkafi Hassini. "Current trends in disaster management simulation modelling research." Annals of Operations Research 283, no. 1-2 (July 27, 2018): 1387–411. http://dx.doi.org/10.1007/s10479-018-2985-x.
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Huang, Chongfu. "Differences between Disaster Prediction and Risk Assessment in Natural Disasters." Human and Ecological Risk Assessment: An International Journal 17, no. 3 (May 2011): 542–53. http://dx.doi.org/10.1080/10807039.2011.571069.
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Lu, Lin, Liguo Yang, and Xiaochun Luo. "Graph Evaluation and Review Technique for Emergency Logistics Distribution in Complex Environment." Discrete Dynamics in Nature and Society 2021 (April 3, 2021): 1–10. http://dx.doi.org/10.1155/2021/6698910.
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Emergency logistics is one of the important measures to solve the unconventional sudden disaster. The research on the distribution design of emergency logistics project has an important supporting role for the whole emergency rescue system. Therefore, it is necessary to analyze and plan the emergency logistics project scientifically in order to better serve the emergency rescue system. In view of the defect that the current emergency logistics model cannot completely describe the whole emergency logistics process, this paper proposes a new emergency logistics distribution model by using GERT random network. From the perspective of system, this model fully considers the possible situation in the process of emergency material transportation and puts forward the corresponding countermeasures, so as to improve the transportation efficiency of rescue materials in the actual disaster relief activities to speed up disaster relief. Based on the properties of moment generating function and the calculation method of Mason formula, this paper fully considers the success probability, risk probability, delivery time, and other factors of the distribution route and puts forward the transshipment scheme of each logistics site to the disaster sites. After that, the effectiveness of GERT stochastic network in the process of emergency distribution is verified by an example of a logistics distribution route, which provides decision-making basis for relevant departments. Compared with the literature, this paper uses GERT network model to intuitively and clearly express the overall process of emergency material distribution, breaks through the thinking mode of simply choosing the distribution path in the distribution process, combines with the dynamic changes of the distribution environment, and comprehensively considers the timeliness and traffic capacity of emergency material distribution in sudden disasters, so as to provide reference for emergency management in complex and random situations for decision-making reference.
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Setiadi, Ade, Sulaiman Sulaiman, and Fifit Alfiah. "Disaster Victim Service Application at the Social Services of Tangerang District." CCIT Journal 15, no. 2 (August 4, 2022): 179–90. http://dx.doi.org/10.33050/ccit.v15i2.2119.
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The social service of Tangerang District is a government institution that caters to the social welfare problem and one of the services that will be discussed is the service of disaster victims in the district of Tangerang that have not been computerised so that the running system is less efficient. The process of service that is still having difficulty due to the collection of disaster victims is still far from the word accurate and to get the service should often visit the office so it takes a lot of wasted time. Since the system is running less efficiently, a Disaster Victim Service Application has been made which is computerized and runs more efficiently. The method used in data collection is observation, interviews, and literature study. In analyzing a system using the PIECES method (Performance), (Information), (Economy), (Control), (Efficiency), (Service) to make it easier to analyze the running system and provide solutions in making application programs and writers in making application design with visual modelling using UML (Unified Modelling Language) to make a diagram, Hypertext Preprocessor (PHP) as a programming language, and MySQL as a database to be used in the system. The results of the design discuss how to create a system that runs and the proposed system and the existence of this system can facilitate service employees in receiving accurate reports so as to shorten the time of handling in serving victims affected by disasters.
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Koks, Elco E., Lorenzo Carrera, Olaf Jonkeren, Jeroen C. J. H. Aerts, Trond G. Husby, Mark Thissen, Gabriele Standardi, and Jaroslav Mysiak. "Regional disaster impact analysis: comparing input–output and computable general equilibrium models." Natural Hazards and Earth System Sciences 16, no. 8 (August 16, 2016): 1911–24. http://dx.doi.org/10.5194/nhess-16-1911-2016.
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Abstract. A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input–output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of them in combination with noneconomic methods. While both IO and CGE models are widely used, they are mainly compared on theoretical grounds. Few studies have compared disaster impacts of different model types in a systematic way and for the same geographical area, using similar input data. Such a comparison is valuable from both a scientific and policy perspective as the magnitude and the spatial distribution of the estimated losses are born likely to vary with the chosen modelling approach (IO, CGE, or hybrid). Hence, regional disaster impact loss estimates resulting from a range of models facilitate better decisions and policy making. Therefore, this study analyses the economic consequences for a specific case study, using three regional disaster impact models: two hybrid IO models and a CGE model. The case study concerns two flood scenarios in the Po River basin in Italy. Modelling results indicate that the difference in estimated total (national) economic losses and the regional distribution of those losses may vary by up to a factor of 7 between the three models, depending on the type of recovery path. Total economic impact, comprising all Italian regions, is negative in all models though.
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Syaputra, T. A., and A. D. Rarasati. "A conceptual framework for implementing lean construction and building information modeling (BIM) in post-disaster housing reconstruction projects." IOP Conference Series: Earth and Environmental Science 1173, no. 1 (May 1, 2023): 012065. http://dx.doi.org/10.1088/1755-1315/1173/1/012065.
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Abstract The occurrence of natural disasters in Indonesia every year results in massive damage to people’s homes. It requires a fast and appropriate post-disaster housing reconstruction (PDHR) strategy. The building firm or contractor is among the most significant contributors; in post-disaster conditions, the contractor has to work in a project environment that is much more complicated than conventional projects, and this often results in poor contractor performance. An approach to improve contractor performance is the application of Lean Construction. In line with this linking, the function of the Building Information Modelling (BIM) tool in the application of Lean has also proven effective in conventional projects. However, studies focusing on its simultaneous application to PDHR projects are still lacking. A conceptual framework that can be applied to specific Lean and BIM implementations in PDHR projects is needed to address this issue. This paper proposes a conceptual framework by identifying and analyzing various previous studies as a proper basis. The study shows several Lean Construction and BIM factors relevant to contractor performance indicators in post-disaster housing reconstruction projects.
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Michal Titko, Jan Havko, and Jana Studena. "Modelling Resilience of the Transport Critical Infrastructure Using Influence Diagrams." Communications - Scientific letters of the University of Zilina 22, no. 1 (January 2, 2020): 102–18. http://dx.doi.org/10.26552/com.c.2020.1.102-118.
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The article discusses the possible impact of disasters on functionality of the transport critical infrastructure elements by overcoming their resilience. The aim of the article is to provide an appropriate approach to the resilience measurement through understanding of this close relationship. It was achieved by using combination of (1) a decisiontheoretical approach based on Influence Diagrams, which was used as a tool to model functionality disruption level of transportation network elements after disaster impact and (2) the time decomposition of the functionality disruption duration of these elements. Based on this approach, the transportation network element resilience assessment was conducted in form of the transportation element resilience loss. The proposed approach is intended to be applied to the critical infrastructure elements rather than to the transportation network as a whole.
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Deva, Ilir, and Renata van der Weijden. "A System Dynamics Modelling Approach for Electronic Waste Recycling after Floods in Jakarta and New Orleans." Advances in Environmental and Engineering Research 2, no. 4 (October 15, 2021): 1. http://dx.doi.org/10.21926/aeer.2104037.
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Due to climate change, flood-related disasters are expected to increase. Floods generate enormous amounts of waste, including electronic waste (e-waste). E-waste should be recovered not only because it can have detrimental effects on human health and the environment but also because of the valuable metals contained in it. In this study, a system dynamics model based on current practices and waste management was established using Vensim to determine the revenue that can be generated by e-waste recycling after floods in two socio-geographic and economic contexts: Jakarta and New Orleans. At current recovery rates, the formal systems employed for recovering valuable materials would yield 8% (€58 million) and 14% (€80 million) of the potential yield for the Jakarta and New Orleans models, respectively. Moreover, the model estimated that informal e-waste recycling would yield €1.2 billion. The model also highlighted several problems encountered in post-disaster waste management in both scenarios, such as low capacities of temporary storage sites, increased landfilling rates, low yields of recovered e-waste components, and limitations on the transportation of waste. For optimizing the recovery of valuable metals, regulations addressing e-waste must be implemented more thoroughly, and post-disaster waste management guidelines must be revised to contextually address flood disasters. When more data are available, an improved model can be established and used as a basis for policymaking to improve the infrastructure of solid waste management to optimize e-waste recovery.
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Hao, Sijia, Wenchuan Wang, Qiang Ma, Changzhi Li, Lei Wen, Jiyang Tian, and Changjun Liu. "Analysis on the Disaster Mechanism of “8.12” Flash Flood in Liulin River Basin." Water 14, no. 13 (June 24, 2022): 2017. http://dx.doi.org/10.3390/w14132017.
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Hubei province is located in the center of China with 56% total area characterized with mountainous area. Thus, flash flood caused by extreme rainfall has become one of the significant obstacles that highly affect the social and economic development of the province. In order to scientifically understand the mechanism of flash flood disasters and provide technological support to the local flood prevention and control work, the IWHR designed and developed a new distributed hydrological model named China-FFMS that can simulate the evolution of natural disasters and make an assessment by setting the flood water sources in line with the flow discharge. The FFMS was further applied to simulate the 8.12 flash flood disaster that occurred in the Liulin county of Hubei province on 12 August (“8.12”) and fed by the data collected from the national flash flood disaster investigation and assessment. The calculated peak flow was 666.22 m3/s with an error of +13% compared with postdisaster investigation data (589 m3/s). The results showed that using a multisourced modelling approach, e.g., mixing spatiotemporal variables and sources, to simulate the flash flood process was able to accurately reproduce the flood process and the consistence of the flow discharge, thereby explaining the underlying reason of the disaster formation and evolution. Regarding the case of the Liulin county, the main factor leading to the disaster was the overlapped peak flow where the Dunne flood peak of three different tributaries from the upper reach met together at the same time. Moreover, the peak flow of the Lianhua river at the downstream of Liulin County also arrived at the same time as the upstream peak, which obstructed the flood progress and increased the damage of the disaster. According to the analysis, several suggestions and recommendations are proposed such as the improvement of the forecast and early warning system of the upstream areas, the optimization of the current flood defense plan, and the enhancement of the residents’ awareness of flash flood disasters.
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Chen, Shutong, and Changjun Wang. "Incorporating a Bayesian Network into Two-Stage Stochastic Programming for Blood Bank Location-Inventory Problem in Case of Disasters." Discrete Dynamics in Nature and Society 2019 (March 7, 2019): 1–28. http://dx.doi.org/10.1155/2019/7214907.
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This paper is concerned with the optimal decisions of blood banks in a blood logistics network (BLN) with the consideration of natural disasters. One of the biggest challenges is how to deal with unexpected disasters. Our idea is to consider the disasters as the natural consequences of interaction among multiple interdependent uncertain factors, such as the locations and the levels of disasters, the number of casualties, and the availabilities of rescue facilities, which work together to influence the rescue effects of the BLN. Thus, taking earthquakes as the example, a Bayesian Network is proposed to describe such uncertainties and interdependences and, then, we incorporate it into a dedicated two-stage multi-period stochastic programming model for the BLN. The planning stage in the model focuses on blood bank location and inventory decisions. The subsequent operational stage is composed of multiple periods, some of which may suffer disasters and initiate corresponding rescue operations. Numerical tests show that the proposed approach can be efficiently applied in blood management under the complicated disaster scenarios.
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Knös, Daniel, Konstantinos Karagiorgos, Jan Haas, Barbara Blumenthal, Lars Nyberg, and Sven Halldin. "Cloudburst-disaster modelling. A new open-source catastrophe model." International Journal of Disaster Risk Reduction 67 (January 2022): 102679. http://dx.doi.org/10.1016/j.ijdrr.2021.102679.
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Wu, Shengnan, Larry J. Shuman, Bopaya Bidanda, Carey D. Balaban, and Ken Sochats. "A hybrid modelling framework to simulate disaster response decisions." International Journal of Advanced Intelligence Paradigms 4, no. 1 (2012): 83. http://dx.doi.org/10.1504/ijaip.2012.046968.
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