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Floods and droughts have an increasing impact on societies worldwide. It is unlikely that the provision of flood protection infrastructure and reservoirs will eliminate this problem, especially as extreme events are expected to increase in probability and magnitude as a result of climate change. For this reason, the focus of water management has shifted to a risk-based approach in recent years; but this also has its limitations. This book examines system robustness as a new perspective on flood and drought risk management. The concept of robustness is familiar from other areas, such as engineering and biology. When a system is robust, it can remain functioning even when some components fail. Areas prone to flooding or drought can be understood as systems, and this book makes the concept of robustness operational by proposing quantifiable criteria. These criteria were tested in two case studies of flooding and two of drought, which demonstrate the applicability of the framework and provide insight into the system characteristics that influence system robustness. The book will contribute to decision-making in flood and drought risk management by providing additional decision criteria, and will be of interest to all those whose work involves the management of disastrous and uncertain flood and drought events.
Already the market leader in the field, Modelling Transport has become still more indispensible following a thorough and detailed update. Enhancements include two entirely new chapters on modelling for private sector projects and on activity-based modelling; a new section on dynamic assignment and micro-simulation; and sizeable updates to sections on disaggregate modelling and stated preference design and analysis. It also tackles topical issues such as valuation of externalities and the role of GPS in travel time surveys. Providing unrivalled depth and breadth of coverage, each topic is approached as a modelling exercise with discussion of the roles of theory, data, model specification, estimation, validation and application. The authors present the state of the art and its practical application in a pedagogic manner, easily understandable to both students and practitioners. Follows on from the highly successful third edition universally acknowledged as the leading text on transport modelling techniques and applications Includes two new chapters on modelling for private sector projects and activity based modeling, and numerous updates to existing chapters Incorporates treatment of recent issues and concerns like risk analysis and the dynamic interaction between land use and transport Provides comprehensive and rigorous information and guidance, enabling readers to make practical use of every available technique Relates the topics to new external factors and technologies such as global warming, valuation of externalities and global positioning systems (GPS).
This book contains selected peer-reviewed papers that were presented at the Fourth International Symposium on Transportation Network Reliability (INSTR) Conference held at the University of Minnesota July 22-23, 2010. International scholars, from a variety of disciplines--engineering, economics, geography, planning and transportation—offer varying perspectives on modeling and analysis of the reliability of transportation networks in order to illustrate both vulnerability to day-to-day and unpredictability variability and risk in travel, and demonstrates strategies for addressing those issues. The scope of the chapters includes all aspects of analysis and design to improve network reliability, specifically user perception of unreliability of public transport, public policy and reliability of travel times, the valuation and economics of reliability, network reliability modeling and estimation, travel behavior and vehicle routing under uncertainty, and risk evaluation and management for transportation networks. The book combines new methodologies and state of the art practice to model and address questions of network unreliability, making it of interest to both academics in transportation and engineering as well as policy-makers and practitioners.
Vulnerability Analysis for Transportation Networks provides an integrated framework for understanding and addressing how transportation networks across all modes perform when parts of the network fail or are substantially degraded, such as extreme weather events, natural disasters, road crashes, congestion incidents or road repair. The book reviews the range of existing approaches to network vulnerability and identifies the application of each approach, illustrating them with case studies from around the world. The book covers the dimensions of time (hours, days, weeks, months and years), spatial coverage (national networks, regional areas, metropolitan and urbanized areas) and modes (road, urban public transport and national railway systems). It shows how the provided framework can be used to indicate the most suitable accessibility tools and metrics for a particular application. Vulnerability Analysis for Transportation Networks is for academics and researchers in transportation networks and for practicing professionals involved in the planning and management of transportation networks and services. - Presents the most current, complete and integrated account of transport network vulnerability analysis - Includes numerous case studies from around the world - Compares alternative approaches to vulnerability analysis for multiple modes and the applicability of each - Shows how academic transport network planning and management research development can be applied to actual practice, with special focus on socio-economic and environmental impacts
Space-time analysis is a rapidly growing research frontier in geography, GIS, and GIScience. Advances in integrated GPS/GIS technologies, the availability of large datasets (over time and space), and increased capacity to manage, integrate, model and visualize complex data in (near) real time, offer the GIS and geography communities extraordinary opportunities to begin to integrate sophisticated space-time analysis and models in the study of complex environmental and social systems, from climate change to infectious disease transmission. This volume specifically focuses on research frontiers, comparative research, and research and application interactions in this field in the US and China, arguably the two most dynamic loci for this work today. The contributions to this book, by top researchers in China and the US, productively highlight the differences and similarities in approaches and directions for space-time analysis in the two countries. In light of the recent rapid progress in GIScience research on space-time integration in both countries, the book’s focus on research frontiers in these two countries will attract great interest in both countries and in other parts of the world as well as among related disciplines. In addition, the book also explores the impact of collaborative research and publications underway in this area between the US and China and will provide an overview of these collaborative efforts and programs. This book will not only be of interest to university-based GIS researchers and students, but also to those interested in this new area of research and applications like researchers and developers in business, internet mapping and GIS and location based services (LBS).
Multilayer networks is a rising topic in Network Science which characterizes the structure and the function of complex systems formed by several interacting networks. Multilayer networks research has been propelled forward by the wide realm of applications in social, biological and infrastructure networks and the large availability of network data, as well as by the significance of recent results, which have produced important advances in this rapidly growing field. This book presents a comprehensive account of this emerging field. It provides a theoretical introduction to the main results of multilayer network science.
This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.