194 resultados para Hurricanes.


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Ravaged by Nature, page 3 Hurricanes Katrina and Rita left millions of dollars of damage in their wake. Focus on…Comprehensive Conservation Planning, pages 10-14 What does it take to draft a first-rate CCP? How does a refuge reach out and communicate with partners and community? Baby Switch in High Places, page 21 Refuge biologists in California successfully swap a fertile for an infertile egg and the condor parents are none the wiser. Invasive Plant Mapping, page 9 Volunteers using state-of-the-arttechnology are helping to map and control invasive plants.

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Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

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In the recent decade, the request for structural health monitoring expertise increased exponentially in the United States. The aging issues that most of the transportation structures are experiencing can put in serious jeopardy the economic system of a region as well as of a country. At the same time, the monitoring of structures is a central topic of discussion in Europe, where the preservation of historical buildings has been addressed over the last four centuries. More recently, various concerns arose about security performance of civil structures after tragic events such the 9/11 or the 2011 Japan earthquake: engineers looks for a design able to resist exceptional loadings due to earthquakes, hurricanes and terrorist attacks. After events of such a kind, the assessment of the remaining life of the structure is at least as important as the initial performance design. Consequently, it appears very clear that the introduction of reliable and accessible damage assessment techniques is crucial for the localization of issues and for a correct and immediate rehabilitation. The System Identification is a branch of the more general Control Theory. In Civil Engineering, this field addresses the techniques needed to find mechanical characteristics as the stiffness or the mass starting from the signals captured by sensors. The objective of the Dynamic Structural Identification (DSI) is to define, starting from experimental measurements, the modal fundamental parameters of a generic structure in order to characterize, via a mathematical model, the dynamic behavior. The knowledge of these parameters is helpful in the Model Updating procedure, that permits to define corrected theoretical models through experimental validation. The main aim of this technique is to minimize the differences between the theoretical model results and in situ measurements of dynamic data. Therefore, the new model becomes a very effective control practice when it comes to rehabilitation of structures or damage assessment. The instrumentation of a whole structure is an unfeasible procedure sometimes because of the high cost involved or, sometimes, because it’s not possible to physically reach each point of the structure. Therefore, numerous scholars have been trying to address this problem. In general two are the main involved methods. Since the limited number of sensors, in a first case, it’s possible to gather time histories only for some locations, then to move the instruments to another location and replay the procedure. Otherwise, if the number of sensors is enough and the structure does not present a complicate geometry, it’s usually sufficient to detect only the principal first modes. This two problems are well presented in the works of Balsamo [1] for the application to a simple system and Jun [2] for the analysis of system with a limited number of sensors. Once the system identification has been carried, it is possible to access the actual system characteristics. A frequent practice is to create an updated FEM model and assess whether the structure fulfills or not the requested functions. Once again the objective of this work is to present a general methodology to analyze big structure using a limited number of instrumentation and at the same time, obtaining the most information about an identified structure without recalling methodologies of difficult interpretation. A general framework of the state space identification procedure via OKID/ERA algorithm is developed and implemented in Matlab. Then, some simple examples are proposed to highlight the principal characteristics and advantage of this methodology. A new algebraic manipulation for a prolific use of substructuring results is developed and implemented.

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The so called cascading events, which lead to high-impact low-frequency scenarios are rising concern worldwide. A chain of events result in a major industrial accident with dreadful (and often unpredicted) consequences. Cascading events can be the result of the realization of an external threat, like a terrorist attack a natural disaster or of “domino effect”. During domino events the escalation of a primary accident is driven by the propagation of the primary event to nearby units, causing an overall increment of the accident severity and an increment of the risk associated to an industrial installation. Also natural disasters, like intense flooding, hurricanes, earthquake and lightning are found capable to enhance the risk of an industrial area, triggering loss of containment of hazardous materials and in major accidents. The scientific community usually refers to those accidents as “NaTechs”: natural events triggering industrial accidents. In this document, a state of the art of available approaches to the modelling, assessment, prevention and management of domino and NaTech events is described. On the other hand, the relevant work carried out during past studies still needs to be consolidated and completed, in order to be applicable in a real industrial framework. New methodologies, developed during my research activity, aimed at the quantitative assessment of domino and NaTech accidents are presented. The tools and methods provided within this very study had the aim to assist the progress toward a consolidated and universal methodology for the assessment and prevention of cascading events, contributing to enhance safety and sustainability of the chemical and process industry.

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Large parts of the world are subjected to one or more natural hazards, such as earthquakes, tsunamis, landslides, tropical storms (hurricanes, cyclones and typhoons), costal inundation and flooding. Virtually the entire world is at risk of man-made hazards. In recent decades, rapid population growth and economic development in hazard-prone areas have greatly increased the potential of multiple hazards to cause damage and destruction of buildings, bridges, power plants, and other infrastructure; thus posing a grave danger to the community and disruption of economic and societal activities. Although an individual hazard is significant in many parts of the United States (U.S.), in certain areas more than one hazard may pose a threat to the constructed environment. In such areas, structural design and construction practices should address multiple hazards in an integrated manner to achieve structural performance that is consistent with owner expectations and general societal objectives. The growing interest and importance of multiple-hazard engineering has been recognized recently. This has spurred the evolution of multiple-hazard risk-assessment frameworks and development of design approaches which have paved way for future research towards sustainable construction of new and improved structures and retrofitting of the existing structures. This report provides a review of literature and the current state of practice for assessment, design and mitigation of the impact of multiple hazards on structural infrastructure. It also presents an overview of future research needs related to multiple-hazard performance of constructed facilities.

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Studies are suggesting that hurricane hazard patterns (e.g. intensity and frequency) may change as a consequence of the changing global climate. As hurricane patterns change, it can be expected that hurricane damage risks and costs may change as a result. This indicates the necessity to develop hurricane risk assessment models that are capable of accounting for changing hurricane hazard patterns, and develop hurricane mitigation and climatic adaptation strategies. This thesis proposes a comprehensive hurricane risk assessment and mitigation strategies that account for a changing global climate and that has the ability of being adapted to various types of infrastructure including residential buildings and power distribution poles. The framework includes hurricane wind field models, hurricane surge height models and hurricane vulnerability models to estimate damage risks due to hurricane wind speed, hurricane frequency, and hurricane-induced storm surge and accounts for the timedependant properties of these parameters as a result of climate change. The research then implements median insured house values, discount rates, housing inventory, etc. to estimate hurricane damage costs to residential construction. The framework was also adapted to timber distribution poles to assess the impacts climate change may have on timber distribution pole failure. This research finds that climate change may have a significant impact on the hurricane damage risks and damage costs of residential construction and timber distribution poles. In an effort to reduce damage costs, this research develops mitigation/adaptation strategies for residential construction and timber distribution poles. The costeffectiveness of these adaptation/mitigation strategies are evaluated through the use of a Life-Cycle Cost (LCC) analysis. In addition, a scenario-based analysis of mitigation strategies for timber distribution poles is included. For both residential construction and timber distribution poles, adaptation/mitigation measures were found to reduce damage costs. Finally, the research develops the Coastal Community Social Vulnerability Index (CCSVI) to include the social vulnerability of a region to hurricane hazards within this hurricane risk assessment. This index quantifies the social vulnerability of a region, by combining various social characteristics of a region with time-dependant parameters of hurricanes (i.e. hurricane wind and hurricane-induced storm surge). Climate change was found to have an impact on the CCSVI (i.e. climate change may have an impact on the social vulnerability of hurricane-prone regions).

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Soil erosion is a natural geological phenomenon resulting from removal and transportation of soil particles by water, wind, ice and gravity. As soil erosion may be affected from cultural factors as well. The physical and social phenomena of soil erosion are researched in six communities in the upper part of Rio Grijalva Basin in the vicinity of Motozintla de Mendoza, Chiapas, Mexico. For this study, the USDA RUSLE model was applied to estimate soil erosion rates in the six communities based on the available data. The RUSLE model is based on soil properties, topography, and land cover and management factors. These results showed that estimated soil erosion rates ranged from a high of 2,050 metric ton ha-1 yr-1 to a low of 100 metric ton ha-1 yr-1. A survey concerning knowledge, attitudes and practices (KAP) related to soil erosion was also conducted in all 236 households in the six communities. The main findings of the KAP survey were: 69% of respondents did not know what soil erosion was, while over 40% of the population perceived that hurricanes are the biggest factors that cause soil erosion, and about 20 % of the interviewees said that the landslides are the consequences of the soil erosion. People in communities did not perceive cultural factors as important in conservation efforts for reduce vulnerability to erosion; therefore, the results obtained are suggested to be useful for informing efforts to educate stakeholders.

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Five seismic units may be identified in the similar to 8 m thick Holocene sediment package at the bottom of the Blue Hole, a 120 m deep sinkhole located in the atoll lagoon of Lighthouse Reef, Belize. These units may be correlated with the succession of an existing 5.85-m-long sediment core that reaches back to 1385 kyrs BP. The identification of seismic units is based on the fact that uniform, fine-grained background sediments show weak reflections while alternating background and coarser-grained event (storm) beds exhibit strong reflections in the seismic profiles. The main source of sediments is the marginal atoll reef and adjacent lagoon area to the east and north. Northeasterly winds and storms transport sediment into the Blue Hole, as seen in the eastward increase in sediment thickness, i.e., the eastward shallowing of the Blue Hole. Previous assumptions of much thicker Holocene sediment packages in the Blue Hole could not be confirmed. So far, close to 6-m-long cores were retrieved from the Blue Hole but the base of the sedimentary succession remains to be recovered. The nature of the basal sediments is unknown but mid-Holocene and possibly older, Pleistocene sinkhole deposits can be expected. The number of event beds identified in the Blue Hole (n = 37) during a 1.385 kyr-long period and the number of cyclones listed in historical databases suggest that only strong hurricanes (categories 4 and 5) left event beds in the Blue Hole sedimentary succession. Storm beds are numerous during 13-0.9 kyrs BP and 0.8-0.5 kyrs BP.

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The tropical region is an area of maximum humidity and serves as the major humidity source of the globe. Among other phenomena, it is governed by the so-called Inter-Tropical Convergence Zone (ITCZ) which is commonly defined by converging low-level winds or enhanced precipitation. Given its importance as a humidity source, we investigate the humidity fields in the tropics in different reanalysis data sets, deduce the climatology and variability and assess the relationship to the ITCZ. Therefore, a new analysis method of the specific humidity distribution is introduced which allows detecting the location of the humidity maximum, the strength and the meridional extent. The results show that the humidity maximum in boreal summer is strongly shifted northward over the warm pool/Asia Monsoon area and the Gulf of Mexico. These shifts go along with a peak in the strength in both areas; however, the extent shrinks over the warm pool/Asia Monsoon area, whereas it is wider over the Gulf of Mexico. In winter, such connections between location, strength and extent are not found. Still, a peak in strength is again identified over the Gulf of Mexico in boreal winter. The variability of the three characteristics is dominated by inter-annual signals in both seasons. The results using ERA-interim data suggest a positive trend in the Gulf of Mexico/Atlantic region from 1979 to 2010, showing an increased northward shift in the recent years. Although the trend is only weakly confirmed by the results using MERRA reanalysis data, it is in phase with a trend in hurricane activity�a possible hint of the importance of the new method on hurricanes. Furthermore, the position of the maximum humidity coincides with one of the ITCZ in most areas. One exception is the western and central Pacific, where the area is dominated by the double ITCZ in boreal winter. Nevertheless, the new method enables us to gain more insight into the humidity distribution, its variability and the relationship to ITCZ characteristics.

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To date, the radiative impact of dust and the Sahar an air layer (SAL) on North Atlantic hurricane activity is not yet known. According to previous studies, dust stabilizes the atmosphere due to absorption of solar radiation but thus shifts convection to regions more conducive for hurricane genesis. Here we analyze differences in hurricane genesis and frequency from ensemble sensitivity simulations with radiatively active and inactive dust in the aerosol-climate model ECHAM6-HAM. We investigate dust burden and other hurricane-related variables and determine their influence on disturbances which develop into hurricanes (developing disturbances, DDs) and those which do not (nondeveloping disturbances, NDDs). Dust and the SAL are found to potentially have both inhibiting and supporting influences on background conditions for hurricane genesis. A slight southward shift of DDs is determined when dust is active as well as a significant warming of the SAL, which leads to a strengthening of the vertical circulation associated with the SAL. The dust burden of DDs is smaller in active dust simulations compared to DDs in simulations with inactive dust, while NDDs contain more dust in active dust simulations. However, no significant influence of radiatively active dust on other variables in DDs and NDDs is found. Furthermore, no substantial change in the DD and NDD frequency due to the radiative effects of dust can be detected.

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The Hurricane of 1938 was one of those defining moments that divide time into parts that either precede or follow. It was transformative, impacting human lives and settlements as well as natural systems, coastal and inland, aquatic and terrestrial, with a force unsurpassed in the region’s living memory. Seventy years have now passed since that hurricane made its historic landfall on the afternoon of September 21, 1938. Humans have regrouped and rebuilt and nature has regenerated and reclaimed, but the memories of those who lived through the Hurricane of ‘38 remain.

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In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^

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The recent hurricanes of Katrina, Rita, and Dolly have brought to light the precarious situation populations place themselves in when they are unprepared to face a storm, or do not follow official orders to evacuate when a destructive hurricane is poised to hit the area. Three counties in southern Texas lie within 60 miles of the Gulf of Mexico, and along the Mexican border. Determining the barriers to hurricane evacuation in this distinct and highly impoverished area of the United States would help aid local, state, and federal agencies to respond more effectively to persons living here.^ The aim of this study was to examine intention to comply with mandatory hurricane evacuation orders among persons living in three counties in South Texas by gender, income, education, acculturation and county of residence. A questionnaire was administered to 3,088 households across the three counties using a two-stage cluster sampling strategy, stratified by all three counties. The door-to-door survey was a 73-item instrument that included demographics, reasons for and against evacuation, and preparedness for a hurricane. Weighted data were used for the analyses.^ Chi-square tests were run to determine whether differences between observed and expected frequencies were statistically significant. A logistic regression model was developed based on that univariate analysis. Results from the logistic regression estimated odds ratios and their 95 percent confidence intervals for the independent variables.^ Logistic regression results indicate that females were less likely than men to follow an evacuation order. Having a higher education meant more likelihood of evacuating. Those respondents with a higher affiliation with Spanish than English were more likely to follow the evacuation orders. Hidalgo County residents were less likely to evacuate than Cameron or Willacy Counties' residents. Local officials need to implement communication efforts specifically tailored for females, residents with less of an affiliation with Spanish, and Hidalgo County residents to ensure their successful evacuation prior to a strong hurricane's landfall.^

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The Texas Bioterrorism Continuing Education Consortium (BCE) provided National Disaster Life Support (NDLS) training courses throughout the state of Texas in 2005, to help improve knowledge and skills pertaining to bioterrorism and other public health emergencies. The NDLS training courses include curriculum in Basic Disaster Life Support (BDLS) and Core Disaster Life Support (CDLS). A course evaluation which included items assessing ability and willingness of training participants, role of responders, and other variables was mailed to all NDLS participants who provided contact information. An analysis was conducted to determine whether the survey respondents participated in the Hurricanes Katrina and/or Rita relief efforts, as well as to evaluate the impact of the NDLS training courses on the participant's ability and willingness to respond during a disaster. The study population (n = 2150) consisted mostly of nurses (50%) (n=1074). A chi-square test of analysis indicated the following results. Among the survey respondents who took the CDLS course, there was no statically significant difference by occupation pertaining to ability or willingness to respond (x2 [df = 5] = 4.02, p= 0.546); (x2 [df = 5] = 2.45, p = .783). However, there was a statistically significant difference among those respondents who took the BDLS course with respect to ability, and a slightly significant difference with respect to willingness (x2 [df = 5] = 13.35, p = .020 and (x2 = [df = 5] = 10.299, p = .067). These findings are similar to previous studies assessing willingness to respond to a disaster.^ A second analysis was conducted with these survey data to evaluate the implications for disaster response training for the NDLS courses. Results indicated that the majority of disaster responders served in the role for which they were professionally trained (Physicians=68%; Nurses = 50.4%). Nurses, EMT, and Fire professionals served in multiple roles. These results suggest the importance of developing training programs that will prepare professionals to serve in multiple roles. The development of standardized evaluation methods would fill an important gap in assessing impact of national training programs. ^

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The coastal deposits of Bonaire, Leeward Antilles, are among the most studied archives for extreme-wave events (EWEs) in the Caribbean. Here we present more than 400 electron spin resonance (ESR) and radiocarbon data on coarse-clast deposits from Bonaire's eastern and western coasts. The chronological data are compared to the occurrence and age of fine-grained extreme-wave deposits detected in lagoons and floodplains. Both approaches are aimed at the identification of EWEs, the differentiation between extraordinary storms and tsunamis, improving reconstructions of the coastal evolution, and establishing a geochronological framework for the events. Although the combination of different methods and archives contributes to a better understanding of the interplay of coastal and archive-related processes, insufficient separation, superimposition or burying of coarse-clast deposits and restricted dating accuracy limit the use of both fine-grained and coarse-clast geoarchives to unravel decadal- to centennial-scale events. At several locations, distinct landforms are attributed to different coastal flooding events interpreted to be of tsunamigenic origin. Coastal landforms on the western coast have significantly been influenced by (sub)-recent hurricanes, indicating that formation of the coarse-clast deposits on the eastern coast is likely to be related to past events of higher energy.