Uncertainty and environmental decision making: a handbook of research and best practice

Uncertainty and Environmental Decision Making: A Handbook of Research and Best Practice presents the state of the art in applying operations research and management science (OR/MS) techniques to a broad range of environmental decision making (EDM) challenges. Drawing on leading researchers in the field, it provides a guided tour of selected methods and tools to help deal with issues as climate change, depleting biodiversity and biocapacity, and more general atmospheric, water and soil pollution problems. Individual peer-reviewed chapters look at applying stochastic reasoning on difficult issues arising in EDM under uncertainty; applying stochastic or robust programming methods to techno-economic modeling of energy/environment interactions; important consequences of uncertainty inherent in weather patterns, the El Nino phenomenon and anticipated climate change; exploiting tools of decision analysis, utility theory and optimal control theory to account for differences in time scales between human development processes and the natural processes of the biosphere; and methods that combine statistical and decision analyses that can support a variety of environmental management problems. This important new work will be of special interest to a wide range of researchers, students, and practitioners in environmental economics, OR/MS, environmental and earth sciences, climatologists, and risk assessment." "Presents the state of the art in a critically important area – Environmental Decision Making Gathers the work of leading researchers in applying OR/MS techniques to EDM Filar and Haurie are leaders in the field; Filaris Editor-in-Chief of Springer journal Environmental Modeling and Assessment INDICE: Introduction.- Uncertainty in integrated assessment models.- Parameter identification and calibration in complex earth system models.- Uncertainty and market based instruments for environmental management.- Viability theory vs robust control models.- Stochastic programming vs. stochastic control models.- Uncertainty, precautionary principle and equity.- Case studies.- Index.

• ISBN: 978-1-4419-1128-5
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 338
• Fecha Publicación: 01/10/2009
• Nº Volúmenes: 1
• Idioma: Inglés