Relevant bibliographies by topics / Natural disasters – Forecasting

Academic literature on the topic 'Natural disasters – Forecasting'

Author: Grafiati
Published: 19 August 2021
Last updated: 3 February 2022

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Journal articles on the topic "Natural disasters – Forecasting":

1

Noda, Masayo. "Affective Forecasting and Interest in Natural Disasters." Proceedings of the Annual Convention of the Japanese Psychological Association 76 (September 11, 2012): 2PMB15. http://dx.doi.org/10.4992/pacjpa.76.0_2pmb15.

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Xu, Xiaoyan, Yuqing Qi, and Zhongsheng Hua. "Forecasting demand of commodities after natural disasters." Expert Systems with Applications 37, no. 6 (June 2010): 4313–17. http://dx.doi.org/10.1016/j.eswa.2009.11.069.

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3

Kaphle, Krishna P., L. N. Rimal, A. K. Duwadi, B. Piya, and D. Nepali. "Disasters and environmental degradation in Nepal: focus on urban areas." Journal of Nepal Geological Society 38 (September 25, 2008): 61–68. http://dx.doi.org/10.3126/jngs.v38i0.31482.

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Nepal is prone to various disasters like earthquake, landslide, debris flow, flood, and glacier lake outburst flood (GLOF). In the last 23 years natural disasters have caused tremendous losses of lives and property. The disasters have brought about the average loss of about 6% of the annual development expenditure of the government. Their frequency is also increasing due to a high rate of population growth and multiple human activities. Disasters disturb the normal life and social system, degrade the environment, and aggravate the poverty and eco-system in the affected areas. Both natural and anthropogenic disasters are deteriorating the natural environment mostly in the urban areas of Nepal. Since there is no effective forecasting and early warning system for such disasters there will be no time for the vulnerable people to save from possible disaster by taking themselves in safe places. Previously the Nepal government put its efforts mainly on post-disaster activities like rescue, relief, and rehabilitation. Only after the 1985 Dig Tso GLOF, 1988 earthquake in eastern Nepal, and 1993 flood and landslide disaster in central Nepal, people realised the importance of pre-disaster preparedness. For the preparedness and mitigation of hazards, geological, geomorphological, hydrogeological information and hazard maps are extremely important. Consequently, the Department of Mines and Geology is publishing the engineering and environmental geological maps of urban areas, which are quite helpful for infrastructural planning, disaster management, and environmental protection.
4

Yong, Yang, Gu Xin, and Zhang Shichang. "Multimedia based risk forecasting model for frequent natural disasters." Multimedia Tools and Applications 79, no. 47-48 (June 10, 2019): 35463–74. http://dx.doi.org/10.1007/s11042-019-07790-z.

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Murzinova, Ainur Serikkyzy, and Kulyash Nurbergenovna Mamirova. "The concept of “Natural cataclysm”: patterns and causal relationships." Bulletin of the Karaganda University. “Biology, medicine, geography Series” 102, no. 2 (June 30, 2021): 102–7. http://dx.doi.org/10.31489/2021bmg2/102-107.

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The article examines natural disasters directly occurring in the geographical shell. In the content of the article the authors give their own interpretation of the concept of “natural disaster”. A classification of natural disasters is proposed and their interactions are established. The causal relationships of natural disasters determining their factors, indicators and their consequences are revealed. The assessment of dangerous natural processes is given, and the classification of cataclysms is made by the scale of manifestation, time, nature of origin, area of manifestation, as well as by the nature of the impact. The following typology of natural disasters is presented: cataclysms that have a destructive effect (hurricanes, typhoons, tornadoes, earthquakes); cataclysms that have a paralyzing (stopping) effect on the movement of vehicles (snowfall, downpour with flooding, ice, thunderstorm and fog); cataclysms that have a depleting effect (reduce the yield, soil fertility, water supply, etc.); cataclysms capable of causing technological accidents/natural and technical disasters (lightning, ice, icing, biochemical corrosion, etc.). At the same time the article deals with the tasks of monitoring and forecasting natural disasters. Particular attention is paid to the synthesis of environmental monitoring systems that ensure the collection, storage and processing of the necessary information to solve these problems. A new concept of synthesis of aerospace monitoring systems based on algorithms and methods of ecoinformatics and consisting the joint use of information technologies and models of evolution of environmental subsystems is characterized. Concrete situations of occurrence of natural disasters are analyzed.
6

Kuzina, R. "EVALUATION OF THE MACROECONOMIC CONSEQUENCES OF NATURAL DISASTERS AND SUBSEQUENT DISCLOSURES IN THE FINANCIAL STATEMENTS ON THE EXAMPLE OF A CORONAVIRUS PANDEMIC." Bulletin of Taras Shevchenko National University of Kyiv. Economics, no. 209 (2020): 6–13. http://dx.doi.org/10.17721/1728-2667.2020/209-2/1.

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The article reviews the macroeconomic consequences of natural disasters based on the ECLAC methodology, which separates direct physical damage from indirect damage and additional or secondary effects. A study of the impact of natural disasters on long-term economic growth and development has shown that the scarcity of financial resources after a natural disaster reduces future growth and requires the disclosure of risks associated with dangerous natural phenomena for three reasons. Firstly, there are large opportunity costs associated with diverting scarce financial resources into relief and disaster recovery efforts. Secondly, natural disasters can damage an already complex budgeting process. Thirdly, natural disasters place high demands on international aid resources, diverting resources from development. Natural disasters have a negative impact on both the short and long term. These developments refute the somewhat simplistic notion of a general decline in vulnerability to natural disasters as the economy grows. Instead, a more sophisticated perspective needs to be adopted and applied when conducting detailed macroeconomic risk assessments. Based on the results of such assessments, the risks associated with natural hazards should be included in general development policies and plans. Risk management strategies should also reflect the fact that disasters occur in different hazard categories (climatic, geophysical or epidemic) and entail different risk reduction options. It is also necessary to assess the experience gained from specific events and, if necessary, take appropriate action. Disasters can cause policy and institutional innovation changes that ultimately benefit, in some cases, not only in reducing vulnerability but also in supporting economic growth and development: deregulating agricultural investment, applying climate forecasting to reduce the impact of climate variability, financial risk management mechanisms. In order to manage risks and mitigate the effects of natural disasters by informing users of financial statements about possible side effects of the pandemic, the issue of disclosure and recalculation of financial statements was considered to reflect the effects of coronavirus on companies and assess financial risks.
7

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.
8

Kim, Dong Hyun, Hyung Ju Yoo, and Seung Oh Lee. "Forecasting of Hazard Zone due to Storm Surge Using SIND Model." Advances in Civil Engineering 2021 (May 20, 2021): 1–14. http://dx.doi.org/10.1155/2021/8852385.

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We have developed the SIND (scientific interpolation for natural disasters) model to forecast natural hazard zone for storm surge. Most previous studies have been conducted to predict hazard zone with numerical simulations based on various scenarios. It is hard to predict hazard zone for all scenarios and to respond immediately because most numerical models are requested a long simulation time and complicated postprocess, especially in coastal engineering. Thus, in this study, the SIND model was developed to overcome these limitations. The principal developing methods are the scientific interpolation for risk grades and trial and error for parameters embedded in the governing equation. Even designed with hatch files, applying disaster characteristics such as the risk propagation, the governing equation for storm surge in coastal lines was induced from the mathematical solver, COMSOL Multiphysics software that solves partial differential equations for multiple physics using FEM method. The verification process was performed through comparison with the official reference, and the accuracy was calculated with a shape similarity indicating the geometric similarity of the hazard zone. It was composed of position, shape, and area criteria. The accuracy of about 80% in terms of shape similarity was archived. The strength of the model is high accuracy and fast calculation time. It took only less than few seconds to create a hazard map for each scenario. As future works, if the characteristics of other disasters would be understood well, it would be able to present risk propagation induced from each natural disaster in a short term, which should help the decision making for EAP.
9

Bolshanik, Petr V. "Management of natural disasters (a synopsis of the concept paper”Integrated flood management”)Management of natural disasters (a synopsis of the concept paper”Integrated flood management”)." Yugra State University Bulletin 13, no. 4 (December 15, 2015): 17–22. http://dx.doi.org/10.17816/byusu20150417-22.

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Zhao, Tong, Hou Ming Fan, and Gui Lin Wang. "Research on Optimization Model of Vehicle Routing for Emergent Relief Supplies of Multi-Reserves." Advanced Materials Research 171-172 (December 2010): 205–10. http://dx.doi.org/10.4028/www.scientific.net/amr.171-172.205.

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In the world today, science and technology in natural disasters forecasting is changing with each passing day and is built up to a rather high level. But local, territorial, even just national or worldwide scope natural disasters have also posed a grave menace to human well-being and development. Therefore, researching on optimizing problem of vehicle routing for emergent relief supplies of multi-reserves, it is vital significant to quickly send relief supplies to the sufferers after sudden natural disasters. Then, we draw out the mathematical model and solve the problem reasonably based on the improved ant colony algorithm, at last, we obtain the satisfy results through an empirical exemple.
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Journal articles Books

Dissertations / Theses on the topic "Natural disasters – Forecasting":

1

Chari, Martin Munashe. "Assessing the vulnerability of resource-poor households to disasters associated with climate variability using remote sensing and GIS techniques in the Nkonkobe Local Municipality, Eastern Cape Province, South Africa." Thesis, University of Fort Hare, 2016. http://hdl.handle.net/10353/2425.

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The main objective of the study was to assess the extent to which resource-poor households in selected villages of Nkonkobe Local Municipality in the Eastern Cape Province of South Africa are vulnerable to drought by using an improvised remote sensing and Geographic Information System (GIS)-based mapping approach. The research methodology was comprised of 1) assessment of vulnerability levels and 2) the calculation of established drought assessment indices comprising the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) from wet-season Landsat images covering a period of 29 years from 1985 to 2014 in order to objectively determine the temporal recurrence of drought in Nkonkobe Local Municipality. Vulnerability of households to drought was determined by using a multi-step GIS-based mapping approach in which 3 components comprising exposure, sensitivity and adaptive capacity were simultaneously analysed and averaged to determine the magnitude of vulnerability. Thereafter, the Analytical Hierarchy Process (AHP) was used to establish weighted contributions of these components to vulnerability. The weights applied to the AHP were obtained from the 2012 - 2017 Nkonkobe Integrated Development Plan (IDP) and perceptions that were solicited from key informants who were judged to be knowledgeable about the subject. A Kruskal-Wallis H test on demographic data for water access revealed that the demographic results are independent of choice of data acquired from different data providers (χ2(2) = 1.26, p = 0.533, with a mean ranked population scores of 7.4 for ECSECC, 6.8 for Quantec and 9.8 for StatsSA). Simple linear regression analysis revealed strong positive correlations between NDWI and NDVI ((r = 0.99609375, R2 = 1, for 1985), 1995 (r = 0.99609375, R2 = 1 for 1995), (r = 0.99609375, R2 = 1 for 2005) and (r = 0.99609375, R2 = 1 for 2014). The regression analysis proved that vegetation condition depends on surface water arising from rainfall. The results indicate that the whole of Nkonkobe Local Municipality is susceptible to drought with villages in south eastern part being most vulnerable to droughts due to high sensitivity and low adaptive capacity.
2

Martinez, Carlos J. "Seasonal Climatology, Variability, Characteristics, and Prediction of the Caribbean Rainfall Cycle." Thesis, 2021. https://doi.org/10.7916/d8-byp7-1b34.

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The Caribbean is a complex region that heavily relies on its seasonal rainfall cycle for its economic and societal needs. This makes the Caribbean especially susceptible to hydro-meteorological disasters (e.g., droughts and floods), and other weather/climate risks. Therefore, effectively predicting the Caribbean rainfall cycle is valuable for the region. The efficacy of predicting the Caribbean rainfall cycle is largely dependent on effectively characterizing the climate dynamics of the region. However, the dynamical processes and climate drivers that shape the seasonal cycle are not fully understood, as previous observational studies show inconsistent findings as to what mechanisms influence the mean state and variability of the cycle. These inconsistencies can be attributed to the limitations previous studies have when investigating the Caribbean rainfall cycle, such as using monthly or longer resolutions in the data or analysis that often mask the seasonal transitions and regional differences of rainfall, and investigating the Caribbean under a basin-wide lens rather than a sub-regional lens. This inhibits the ability to accurately calculate and predict subseasonal-to-seasonal (S2S) rainfall characteristics in the region. To address these limitations and inconsistencies, the research in this thesis examines the seasonal climatology, variability, and characteristics of the Caribbean rainfall cycle under a sub-regional and temporally fine lens in order to investigate the prediction of the cycle. Regional variations and dynamical processes of the Caribbean annual rainfall cycle are assessed using (1) a principal component analysis across Caribbean stations using daily observed precipitation data; and, (2) a moisture budget analysis. The results show that the seasonal cycle of rainfall in the Caribbean hinges on three main facilitators of moisture convergence: the Atlantic Intertropical Convergence Zone (ITCZ), the Eastern Pacific ITCZ, and the North Atlantic Subtropical High (NASH). A warm body of sea-surface temperatures (SSTs) in the Caribbean basin known as the Atlantic Warm Pool (AWP) and a low-level jet centered at 925hPa over the Caribbean Sea known as the Caribbean Low-Level Jet (CLLJ) modify the extent of moisture provided by these main facilitators. The interactions of these dynamical processes are responsible for shaping the seasonal components of the annual rainfall cycle: The Winter Dry Season (WDS; mid-November to April); the Early-Rainy Season (ERS; mid-April to mid-June); an intermittent relatively dry period known as the mid-summer drought, (MSD; mid-June to late August), and the Late-Rainy Season (LRS; late August to late November). Five geographical sub-regions are identified in the Caribbean Islands, each with its unique set of dynamical processes, and consequently, its unique pattern of rainfall distribution throughout the rainy season: Northwestern Caribbean, the Western Caribbean, the Central Caribbean, the Central and Southern Lesser Antilles, and Trinidad and Tobago and Guianas. Convergence by sub-monthly transients contributes little to Caribbean rainfall. The wettest and driest Caribbean ERS and LRS years’ are then explored by conducting the following: (1) a spatial composite of rainfall using the daily rainfall data; and, (2) spatial composites of SSTs, sea-level pressure (SLP), and mean flow moisture convergence and transports using monthly data. The ERS and LRS are impacted in distinctly different ways by two different, and largely independent, large-scale phenomena, external to the region: a SLP dipole mode of variability in the North Atlantic known as the North Atlantic Oscillation (NAO), and the El Nino Southern Oscillation (ENSO). Dry ERS years are associated with a persistent dipole of cold and warm SSTs over the Caribbean Sea and Gulf of Mexico, respectively, that are caused by a preceding positive NAO state. This setting involves a wind-evaporation-SST (WES) feedback expressed in enhanced trade winds and consequently, moisture transport divergence over all of the Caribbean, except in portions of the Northwestern Caribbean in May. A contribution from the preceding winter cold ENSO event is also discernible during dry ERS years. Dry LRS years are due to the summertime onset of an El Niño event, developing an inter-basin SLP pattern that moves moisture out of the Caribbean, except in portions of the Northwestern Caribbean in November. Both large-scale climate drivers would have the opposite effect during their opposite phases leading to wet years in both seasons. Existing methodologies that calculate S2S rainfall characteristics were not found to be suitable for a region like the Caribbean, given its complex rainfall pattern; therefore, a novel and comprehensive method is devised and utilized to calculate onset, demise, and MSD characteristics in the Caribbean. When applying the method to calculate S2S characteristics in the Caribbean, meteorological onsets and demises, which are calculated via each year’s ERS and LRS mean thresholds, effectively characterize the seasonal evolution of mean onsets and demises in the Caribbean. The year-to-year variability of MSD characteristics, and onsets and demises that are calculated by climatological ERS and LRS mean thresholds resemble the variability of seasonal rainfall totals in the Caribbean and are statistically significantly correlated with the identified dynamical processes that impact each seasonal component of the rainfall cycle. Finally, the seasonal prediction of the Caribbean rainfall cycle is assessed using the identified variables that could provide predictive skill of S2S rainfall characteristics in the region. Canonical correlation analysis is used to predict seasonal rainfall characteristics of station-averaged sub-regional frequency and intensity of the ERS and LRS wet days, and magnitude of the MSD. Predictor fields are based on observations from the ERA-Interim reanalysis and GCM output from the North America Multi-Model Ensemble (NMME). Spearman Correlation and Relative Operating Characteristics are applied to assess the forecast skill. The use of SLP, 850-hPa zonal winds (u850), vertically integrated zonal (UQ), and meridional (VQ) moisture fluxes show comparable, if not better, forecast skill than SSTs, which is the most common predictor field for regional statistical prediction. Generally, the highest ERS predictive skill is found for the frequency of wet days, and the highest LRS predictive skill is found for the intensity of wet days. Rainfall characteristics in the Central and Eastern Caribbean have statistically significant predictive skill. Forecast skill of rainfall characteristics in the Northwestern and Western Caribbean are lower and less consistent. The sub-regional differences and consistently significant skill across lead times up to at least two months can be attributed to persistent SST/SLP anomalies during the ERS that resemble the North Atlantic Oscillation pattern, and the summer-time onset of the El Niño-Southern Oscillation during the LRS. The spatial pattern of anomalies during the MSD bears resemblance to both the ERS and LRS spatial patterns. The findings from this thesis provide a more comprehensive and complete understanding of the climate dynamics, variability, and annual mean state of the Caribbean rainfall cycle. These results have important implications for prediction, decision-making, modeling capabilities, understanding the genesis of hydro-meteorological disasters, investigating rainfall under other modes of variability, and Caribbean impact studies regarding weather risks and future climate.
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Kim, Seong D. "Tradeoff between Investments in Infrastructure and Forecasting when Facing Natural Disaster Risk." Thesis, 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-749.

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Hurricane Katrina of 2005 was responsible for at least 81 billion dollars of property damage. In planning for such emergencies, society must decide whether to invest in the ability to evacuate more speedily or in improved forecasting technology to better predict the timing and intensity of the critical event. To address this need, we use dynamic programming and Markov processes to model the interaction between the emergency response system and the emergency forecasting system. Simulating changes in the speed of evacuation and in the accuracy of forecasting allows the determination of an optimal mix of these two investments. The model shows that the evacuation improvement and the forecast improvement give different patterns of impact to their benefit. In addition, it shows that the optimal investment decision changes by the budget and the feasible range of improvement.
4

Kgakatsi, Ikalafeng Ben. "The contribution of seasonal climate forecasts to the management of agricultural disaster-risk in South Africa." Thesis, 2015. http://hdl.handle.net/10539/16916.

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A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Doctor of Philosophy. July 2014.
South Africa’s climate is highly variable, implying that the national agricultural sector should make provision to have early warning services in place in order to reduce the risks of disasters. More than 70% of natural disasters worldwide are caused by weather and climate or weather and climate related hazards. Reliable Seasonal Climate Forecasting (SCF) for South Africa would have the potential to be of great benefit to users in addressing disaster risk reduction. A disaster is a serious disruption of the functioning of a community or a society, causing widespread human, material, economic or environmental losses, which exceed the ability of the affected community or society to cope when using their own resources. The negative impacts on agricultural production in South Africa due to natural disasters including disasters due to increasing climate variability and climate change are critical to the sector. The hypothesis assumed in the study is the improved early warning service and better SCF dissemination lead to more effective and better decision making for subsequent disaster risk reduction in the agricultural sector. The most important aspect of knowledge management in early warning operations is that of distributing the most useful service to the target group that needs it at the right time. This will not only ensure maximum performance of the entity responsible for issuing the early warnings, but will also ensure the maximum benefit to the target group. South Africa is becoming increasingly vulnerable to natural disasters that are afflicted by localised incidents of seasonal droughts, floods and flash floods that have devastating impacts on agriculture and food security. Such disasters might affect agricultural production decisions, as well as agricultural productivity. Planting dates and plant selection are decisions that depend on reliable and accurate meteorological and climatological knowledge and services for agriculture. Early warning services that could be used to facilitate informed decision making includes advisories on iv future soil moisture conditions in order to determine estimated planting times, on future grazing capacity, on future water availability and on forecasts of the following season’s weather and climate, whenever that is possible. The involvement of government structures, obviously, is also critical in immediate responses and long term interventions. The importance of creating awareness, of offering training workshops on climate knowledge and SCF, and of creating effective early warning services dissemination channels is realized by government. This is essential in order to put effective early warning services in place as a disaster-risk coping tool. Early warning services, however, can only be successful if the end-users are aware of what early warning systems, structures and technologies are in place, and if they are willing that those issuing the early warning services become involved in the decision-making process. Integrated disaster-risk reduction initiatives in government programmes, effective dissemination structures, natural resource-management projects and communityparticipation programmes are only a few examples of actions that will contribute to the development of effective early warning services, and the subsequent response to and adoption of the advices/services strategies by the people most affected. The effective distribution of the most useful early warning services to the end-user, who needs it at the right time through the best governing structures, may significantly improve decision making in the agricultural, food security and other water-sensitive sectors. Developed disaster-risk policies for extension and farmers as well as other disaster prone sectors should encourage self-reliance and the sustainable use of natural resources, and will reduce the need for government intervention. The SCF producers (e.g. the South African Weather Service (SAWS)) have issued new knowledge to intermediaries for some years now, and it is important to determine whether this knowledge has been used in services, and if so whether these services were applied effectively in coping with disaster-risks and in disaster v reduction initiatives and programmes. This study for that reason also intends to do an evaluation of the knowledge communication processes between forecasters, and intermediaries at national and provincial government levels. It therefore, aims to assess and evaluate the current knowledge communication structures within the national agricultural sector, seeking to improve disaster-risk reduction through effective early warning services. A boundary organisation is an organization which crosses the boundary between science, politics and end-users as they draw on the interests and knowledge of agencies on both sides to facilitate evidence base and socially beneficial policies and programmes. Reducing uncertainty in SCF is potentially of enormous economic value especially to the rural communities. The potential for climate science to deliver reduction in total SCF uncertainty is associated entirely with the contributions from internal variability and model uncertainty. The understanding of the limitations of the SCFs as a result of uncertainties is very important for decision making and to end-users during planning. Disappointing, however, is that several studies have shown a fairly narrow group of potential users actually receive SCFs, with an even a smaller number that makes use of these forecasts In meeting the objectives of the study the methodology to be followed is based on knowledge communication. For that reason two types of questionnaires were drafted. Open and closed questionnaires comprehensively review the knowledge, understanding, interpretation of SCFs and in early warning services distribution channels. These questionnaires were administered among the SCF producers and intermediaries and results analysed. Lastly the availability of useful SCFs knowledge has important implications for agricultural production and food security. Reliable and accurate climate service, as one of the elements of early warning services, will be discussed since they may be used to improve agricultural practices such as crop diversification, time of planting vi and changes in cultivation practices. It was clear from the conclusions of the study that critical elements of early warning services need to receive focused attention such as the SCF knowledge feedback programme should be improved by both seasonal climate producers and intermediaries, together with established structures through which reliable, accurate and timely early warning services can be disseminated. Also the relevant dissemination channels of SCFs are critical to the success of effective implementation of early warning services including the educating and training of farming communities. The boundary organisation and early warning structures are important in effective implementation of risk reduction measures within the agricultural sector and thus need to be prioritised. Enhancing the understandability and interpretability of SCF knowledge by intermediaries will assist in improving action needed to respond to SCFs. Multiple media used by both SCF producers and intermediaries in disseminating of SCFs should be accessible by all users and end-users. The Government should ensure that farming communities are educated, trained and well equipped to respond to risks from natural hazards.

Books on the topic "Natural disasters – Forecasting":

1

Weng, Wen-bo. Theory of forecasting. Beijing: International Academic Publishers, 1991.

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Frampton, S. Natural hazards. 2nd ed. London: Hodder & Stoughton Educational, 2000.

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Diacu, Florin. Megadisasters: The science of predicting the next catastrophe. Princeton, NJ: Princeton University Press, 2010.

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Seibold, Eugen. Naturkatastrophen und ihre Vorhersage. Jena: Universitätsverlag, 1994.

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Diacu, Florin. Megadisasters: The science of predicting the next catastrophe. Princeton, NJ: Princeton University Press, 2010.

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Tominaga, Lídia Keiko. Desastres naturais: Conhecer para prevenir. São Paulo: Instituto Geológico, 2009.

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Catherine, Chambers. Can we protect people from natural disasters? Chicago, Illinois: Heinemann Raintree, 2015.

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Catherine, Chambers. Can we protect people from natural disasters? London: Raintree, 2015.

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Rāvala, Lālabahādura. Samudrī śaitāna Sunāmī: Sarvanāśī lahareṃ = Tsunami. Bijanaura: Hindī Sāhitya Niketana, 2006.

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Workshop, Kenya Meteorological Society. Proceedings of the Sixth Kenya Meteorological Society Workshop: Mombasa, Kenya, 29 September to 3 October 2003 : the role of meteorology in disaster management. Nairobi, Kenya: Kenya Meteorological Society, 2005.

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Book chapters on the topic "Natural disasters – Forecasting":

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Tazieff, Haroun. "Forecasting Volcanic Eruptive Disasters." In Natural and Man-Made Hazards, 751–72. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1433-9_51.

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Singh, O. P. "Tropical Cyclones: Trends, Forecasting and Mitigation." In Natural and Anthropogenic Disasters, 256–74. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-2498-5_12.

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Bhandari, Rajendra Kumar. "Prediction and Forecasting of Natural Disasters." In Disaster Education and Management, 229–40. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1566-0_6.

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Perumal, Muthiah, and Bhabagrahi Sahoo. "Real-Time Flood Forecasting by a Hydrometric Data-Based Technique." In Natural and Anthropogenic Disasters, 169–96. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-2498-5_9.

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Nasution, Benny Benyamin, Rahmat Widia Sembiring, Bakti Viyata Sundawa, Gunawan, Afritha Amelia, Ismael, Handri Sunjaya, et al. "Forecasting Natural Disasters of Tornados Using mHGN." In IFIP Advances in Information and Communication Technology, 155–69. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68486-4_13.

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Belyakov, V. V., P. O. Beresnev, D. V. Zeziulin, A. A. Kurkin, O. E. Kurkina, V. D. Kuzin, V. S. Makarov, P. P. Pronin, D. Yu Tyugin, and V. I. Filatov. "Autonomous Mobile Robotic System for Coastal Monitoring and Forecasting Marine Natural Disasters." In Proceedings of the Scientific-Practical Conference "Research and Development - 2016", 129–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62870-7_14.

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Kostyuchenko, Yuriy V., and Yulia Bilous. "Long-Term Forecasting of Natural Disasters Under Projected Climate Changes in Ukraine." In Regional Aspects of Climate-Terrestrial-Hydrologic Interactions in Non-boreal Eastern Europe, 95–102. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2283-7_11.

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Wang, Ang-Sheng. "The Early Warning and Forecasting System (EWFS) for the Reduction of Serious Atmosphere-Hydrosphere Disasters." In Early Warning Systems for Natural Disaster Reduction, 399–402. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55903-7_51.

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Jacob, Maria, Cláudia Neves, and Danica Vukadinović Greetham. "Extreme Value Theory." In Forecasting and Assessing Risk of Individual Electricity Peaks, 39–60. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28669-9_3.

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Abstract:
Abstract From travel disruptions to natural disasters, extreme events have long captured the public’s imagination and attention. Due to their rarity and often associated calamity, they make waves in the news (Fig. 3.1) and stir discussion in the public realm: is it a freak event? Events of this sort may be shrouded in mystery for the general public, but a particular branch of probability theory, notably Extreme Value Theory (EVT), offers insight to their inherent scarcity and stark magnitude. EVT is a wonderfully rich and versatile theory which has already been adopted by a wide variety of disciplines in a plentiful way. From its humble beginnings in reliability engineering and hydrology, it has now expanded much further; it can be used to model the occurrences of records (say for example in athletic events) or quantify the probability of floods with magnitude greater than what has been observed in the past, i.e it allows us extrapolate beyond the range of available data!
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Menshikov, Valery A., Anatoly N. Perminov, and Yuri M. Urlichich. "Natural Calamities and Their Forecasting." In Global Aerospace Monitoring and Disaster Management, 1–81. Vienna: Springer Vienna, 2011. http://dx.doi.org/10.1007/978-3-7091-0810-9_1.

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Conference papers on the topic "Natural disasters – Forecasting":

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Prasetya, Elvan P., and Esmeralda C. Djamal. "Rainfall Forecasting for the Natural Disasters Preparation Using Recurrent Neural Networks." In 2019 International Conference on Electrical Engineering and Informatics (ICEEI). IEEE, 2019. http://dx.doi.org/10.1109/iceei47359.2019.8988838.

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Manukalo, V., V. Boiko, and N. Holenya. "THE WMO PROJECT ON CATALOGING HAZARDOUS HYDROMETEOROLOGICAL EVENTS: LESSONS LEARNED BY UKRAINE." In XXVII Conference of the Danubian Countries on Hydrological Forecasting and Hydrological Bases of Water Management. Nika-Tsentr, 2020. http://dx.doi.org/10.15407/uhmi.conference.01.19.

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The article deals with the results of research which was carried out by the Ukrainian Hydrometeorological Institute and the Ukrainian Hydrometeorological Center in the framework of the WMO Project "Cataloging Hazardous Hydrometeorological Events". The cataloging methodology was elaborated by WMO experts and is based on a standardized procedure for identification and description of natural disasters caused by hazardous hydrometeorological events, beginning from a time of creation of warning of dangerous event and up to ending of estimation of damages caused by this event. A description of dangerous hydrometeorological events as well as an assessment of losses caused by these events, were recorded in the agreed EXCEL table format with standard definitions of event types. The filled tables were sent to the European Regional Climate Center (ERCC), which operates under the German Weather Service. The terms of the Project stipulate that the ERCC ensures a full methodological and technical coordination of the Project implementation, including an integration of data received from countries, their consolidation into a regional database and an integration of many events in one regional event that corresponds to their origin. The implementation of the Project first phase was completed in December 2018. During the second Project phase (January- May 2019) an analysis of results was carried out. The experience gained from the Project implementation, was used to create " the WMO methodology for cataloging hazardous weather, climate, water and space weather events" that was presented for consideration at the 18th World Meteorological Congress in June 2019. The Congress adopted the cataloging methodology and recommended to implement this methodology on an operational basis in the hydrometeorological services. The participation of the Hydrometeorological Service of Ukraine in the Project should be considered as very useful. The Ukrainian side got the opportunity: to get acquainted with an international experience in the field of standardization of description of negative influence of extreme hydrometeorological phenomena; to compare the state of affairs in this area of activity in the Hydrometeorological Service of Ukraine and in relevant services of European countries; to bring the contribution in international efforts aimed at reducing the risks of natural disasters. The obtained results showed an importance of reviewing a number of standards and other regulations which are currently used in organizations of the Hydrometeorological Service. The researches in this area is currently being carried out by the Ukrainian Hydrometeorological Institute.
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Li, Chunmin, Yunhai Wang, and Xin Liu. "Research on natural disaster forecasting data processing and visualization technology." In 2011 4th International Congress on Image and Signal Processing (CISP 2011). IEEE, 2011. http://dx.doi.org/10.1109/cisp.2011.6100610.

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Liu, Sanchao, Yida Fan, and Maofang Gao. "Natural disaster reduction applications of the Chinese small satellite constellation for environment and disaster monitoring and forecasting." In Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, edited by Jinwen Tian and Jie Ma. SPIE, 2013. http://dx.doi.org/10.1117/12.2032221.

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Cao, Lianhai, Zhiping Li, and Nanxiang Chen. "Notice of Retraction: The Model of Phase Space Reconstruction and Neural Network about the Natural Disaster Losing Forecasting." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5515415.

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