Natural hazard uncertainty assessment : modeling and decision support

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Tác giả: Karin Riley, Matthew P Thompson, Peter Webley

Ngôn ngữ: eng

ISBN-10: 1119027861

ISBN-13: 978-1119027867

Ký hiệu phân loại: 363.34 Disasters

Thông tin xuất bản:

Mô tả vật lý: x, 346 pages : , illustrations (chiefly color), maps (chiefly color) ; , 29 c

Bộ sưu tập: Xã hội, kinh tế, luật

ID: 273459

"Uncertainties are pervasive in natural hazards, and it is crucial to develop robust and meaningful approaches to characterize and communicate uncertainties to inform modeling efforts. In this monograph we provide a broad, cross-disciplinary overview of issues relating to uncertainties faced in natural hazard and risk assessment. We introduce some basic tenets of uncertainty analysis, discuss issues related to communication and decision support, and offer numerous examples of analyses and modeling approaches that vary by context and scope. Contributors include scientists from across the full breath of the natural hazard scientific community, from those in real-time analysis of natural hazards to those in the research community from academia and government. Key themes and highlights include: Substantial breadth and depth of analysis in terms of the types of natural hazards addressed, the disciplinary perspectives represented, and the number of studies included, targeted, application-centered analyses with a focus on development and use of modeling techniques to address various sources of uncertainty, emphasis on the impacts of climate change on natural hazard processes and outcomes, and recommendations for cross-disciplinary and science transfer across natural hazard sciences This volume will be an excellent resource for those interested in the current work on uncertainty classification/quantification and will document common and emergent research themes to allow all to learn from each other and build a more connected but still diverse and ever growing community of scientists" -- Provided by publisher's web
Includes bibliographical references and i
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