Author : Shreeda Maskey
Publisher : CRC Press
Page : 194 pages
File Size : 39,43 MB
Release : 2004-05-15
Category : Science
ISBN : 1482284022
Like all natural hazards, flooding is a complex and inherently uncertain phenomenon. Despite advances in developing flood forecasting models and techniques, the uncertainty in forecasts remains unavoidable. This uncertainty needs to be acknowledged, and uncertainty estimation in flood forecasting provides a rational basis for risk-based
Author : Shreeda Maskey
Publisher : CRC Press
Page : 184 pages
File Size : 35,12 MB
Release : 2004-11-23
Category : Science
ISBN : 0203026829
Like all natural hazards, flooding is a complex and inherently uncertain phenomenon. Despite advances in developing flood forecasting models and techniques, the uncertainty in forecasts remains unavoidable. This uncertainty needs to be acknowledged, and uncertainty estimation in flood forecasting provides a rational basis for risk-based criteria. This book presents the development and applications of various methods based on probablity and fuzzy set theories for modelling uncertainty in flood forecasting systems. In particular, it presents a methodology for uncertainty assessment using disaggregation of time series inputs in the framework of both the Monte Carlo method and the Fuzzy Extention Principle. It reports an improvement in the First Order Second Moment method, using second degree reconstruction, and derives qualitative scales for the interpretation of qualitative uncertainty. Application is to flood forecasting models for the Klodzko catchment in POland and the Loire River in France. Prospects for the hybrid techniques of uncertainty modelling and probability-possibility transformations are also explored and reported.
Author : Keith J Beven
Publisher : World Scientific
Page : 685 pages
File Size : 23,46 MB
Release : 2014-01-13
Category : Technology & Engineering
ISBN : 1783263121
This volume provides an introduction for flood risk management practitioners, up-to-date methods for analysis of uncertainty and its use in risk-based decision making. It addresses decision making for both short-term (real-time forecasting) and long-term (flood risk planning under change) situations. It aims primarily at technical practitioners involved in flood risk analysis and flood warning, including hydrologists, engineers, flood modelers, risk analysts and those involved in the design and operation of flood warning systems. Many experienced practitioners are now expected to modify their way of working to fit into the new philosophy of flood risk management. This volume helps them to undertake that task with appropriate attention to the surrounding uncertainties. The book will also interest and benefit researchers and graduate students hoping to improve their knowledge of modern uncertainty analysis.
Author : Fi-John Chang
Publisher : MDPI
Page : 376 pages
File Size : 23,33 MB
Release : 2019-02-28
Category : Technology & Engineering
ISBN : 3038975486
Nowadays, the degree and scale of flood hazards has been massively increasing as a result of the changing climate, and large-scale floods jeopardize lives and properties, causing great economic losses, in the inundation-prone areas of the world. Early flood warning systems are promising countermeasures against flood hazards and losses. A collaborative assessment according to multiple disciplines, comprising hydrology, remote sensing, and meteorology, of the magnitude and impacts of flood hazards on inundation areas significantly contributes to model the integrity and precision of flood forecasting. Methodologically oriented countermeasures against flood hazards may involve the forecasting of reservoir inflows, river flows, tropical cyclone tracks, and flooding at different lead times and/or scales. Analyses of impacts, risks, uncertainty, resilience, and scenarios coupled with policy-oriented suggestions will give information for flood hazard mitigation. Emerging advances in computing technologies coupled with big-data mining have boosted data-driven applications, among which Machine Learning technology, with its flexibility and scalability in pattern extraction, has modernized not only scientific thinking but also predictive applications. This book explores recent Machine Learning advances on flood forecast and management in a timely manner and presents interdisciplinary approaches to modelling the complexity of flood hazards-related issues, with contributions to integrative solutions from a local, regional or global perspective.
Author : Shreedhar Maskey
Publisher :
Page : 170 pages
File Size : 41,19 MB
Release : 2004
Category : Flood forecasting
ISBN :
Author : Donald Knight
Publisher : CRC Press
Page : 626 pages
File Size : 16,68 MB
Release : 2005-11-17
Category : Technology & Engineering
ISBN : 9781439824702
Flooding accounts for one-third of natural disasters worldwide and for over half the deaths which occur as a result of natural disasters. As the frequency and volume of flooding increases, as a result of climate change, there is a new urgency amongst researchers and professionals working in flood risk management. River Basin Modelling for Flood Risk Mitigation brings together thirty edited papers by leading experts who gathered for the European Union’s Advanced Study Course at the University of Birmingham, UK. The scope of the course ranged from issues concerning the protection of life, to river restoration and wetland management. A variety of topics is covered in the book including climate change, hydro-informatics, hydro-meterology, river flow forecasting systems and dam-break modelling. The approach is broad, but integrated, providing an attractive and informative package that will satisfy researchers and professionals, while offering a sound introduction to students in Engineering and Geography.
Author : Kim, Dookie
Publisher : IGI Global
Page : 644 pages
File Size : 29,35 MB
Release : 2018-06-15
Category : Technology & Engineering
ISBN : 1522547673
The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.
Author : Vijay P. Singh
Publisher : Water Resources Publication
Page : 930 pages
File Size : 44,28 MB
Release : 2002
Category : Nature
ISBN : 9781887201346
Comprehensive account of some of the most popular models of large watershed hydrology ~~ of interest to all hydrologic modelers and model users and a welcome and timely edition to any modeling library
Author : Guy J-P. Schumann
Publisher : John Wiley & Sons
Page : 266 pages
File Size : 32,28 MB
Release : 2018-07-18
Category : Science
ISBN : 1119217865
Global Flood Hazard Subject Category Winner, PROSE Awards 2019, Earth Science Selected from more than 500 entries, demonstrating exceptional scholarship and making a significant contribution to the field of study. Flooding is a costly natural disaster in terms of damage to land, property and infrastructure. This volume describes the latest tools and technologies for modeling, mapping, and predicting large-scale flood risk. It also presents readers with a range of remote sensing data sets successfully used for predicting and mapping floods at different scales. These resources can enable policymakers, public planners, and developers to plan for, and respond to, flooding with greater accuracy and effectiveness. Describes the latest large-scale modeling approaches, including hydrological models, 2-D flood inundation models, and global flood forecasting models Showcases new tools and technologies such as Aqueduct, a new web-based tool used for global assessment and projection of future flood risk under climate change scenarios Features case studies describing best-practice uses of modeling techniques, tools, and technologies Global Flood Hazard is an indispensable resource for researchers, consultants, practitioners, and policy makers dealing with flood risk, flood disaster response, flood management, and flood mitigation.
Author : Maurizio Mazzoleni
Publisher : CRC Press
Page : 195 pages
File Size : 17,13 MB
Release : 2017-03-16
Category : Science
ISBN : 135164646X
In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by technicians but also by regular citizens. However, due to their relatively low reliability and varying accuracy in time and space, crowdsourced observations have not been widely integrated in hydrological and/or hydraulic models for flood forecasting applications. Instead, they have generally been used to validate model results against observations, in post-event analyses. This research aims to investigate the benefits of assimilating the crowdsourced observations, coming from a distributed network of heterogeneous physical and social (static and dynamic) sensors, within hydrological and hydraulic models, in order to improve flood forecasting. The results of this study demonstrate that crowdsourced observations can significantly improve flood prediction if properly integrated in hydrological and hydraulic models. This study provides technological support to citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, leading to improved model forecasts and better flood management.
