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Uncertainties in Environmental Modelling and Consequences for Policy Making Book

Uncertainties in Environmental Modelling and Consequences for Policy Making
Uncertainties in Environmental Modelling and Consequences for Policy Making, Mathematical modelling has become in recent years an essential tool for the prediction of environmental change and for the development of sustainable policies. Yet, many of the uncertainties associated with modelling efforts appear poorly understood by ma, Uncertainties in Environmental Modelling and Consequences for Policy Making has a rating of 3 stars
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Uncertainties in Environmental Modelling and Consequences for Policy Making, Mathematical modelling has become in recent years an essential tool for the prediction of environmental change and for the development of sustainable policies. Yet, many of the uncertainties associated with modelling efforts appear poorly understood by ma, Uncertainties in Environmental Modelling and Consequences for Policy Making
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  • Uncertainties in Environmental Modelling and Consequences for Policy Making
  • Written by author Philippe Baveye
  • Published by Springer-Verlag New York, LLC, May 2009
  • Mathematical modelling has become in recent years an essential tool for the prediction of environmental change and for the development of sustainable policies. Yet, many of the uncertainties associated with modelling efforts appear poorly understood by ma
  • Mathematical modelling has become in recent years an essential tool for the prediction of environmental change and for the development of sustainable policies. Yet, many of the uncertainties associated with modelling efforts appear poorly understood by ma
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Authors

Preface. Contributors.

Theme I. Model Conceptualization. Spatially Explicit Versus Lumped Models In Catchment Hydrology — Experiences From Two Case Studies; H. Bormann Et Al.- Cellular Automata Modelling Of Environmental Systems; S. Straface And G. Mendicino.- Agent-Based Modeling Of Socio-Economic Processes Related To The Environment: Example Of Land-Use Change; J. G. Polhill.-

Theme II. Verification Of Models. Interval Analysis And Verification Of Mathematical Models; T. Csendes.- Shastic Arithmretic And Verification Of Mathematical Models; J.-M. Chesneaux, et al.-

Theme III. Calibration And Sensitivity Analysis. Model Calibration/Parameter Estimation Techniques And Conceptual Model Error; P.Gaganis.- User Subjectivity In Monte Carlo Modelling Of Pesticide Exposure; M. Trevisan.- Recommended Practices In Global Sensitivity Analysis; A. Saltelli et al.-

Theme IV. Evaluation Of Models. Incoherence Of The Generalized Likelihood Uncertainty Estimation (GLUE) Methodology And The Equifinality Thesis; E.Todini.-

Theme V. Communicating Modelling Results And Uncertainties. Communicating Uncertainty To Policy Makers; A. Patt.- Communicating Scientific Uncertainty For Decision Making About Co2 Storage; P.M. Hogan.-

Theme VI. Decision Making On The Basis Of Model Prediction. Approaches To Handling Uncertainty When Setting Environmental Exposure Standards; E. Budtz-Jørgensen et al.-

Case Study I. Soil Carbon Dynamics. Sources Of Uncertainty In Future Soil Organic Carbon Storage; Chr. Jones And Pete Falloon.- Uncertainties Related To The Temperature Sensitivity Of Soil Carbon Decomposition; M.J.I. Briones.-

Case Study II. Global Climate Change. Media Representational Practices In The Anthropocene Era; M.T. Boykoff.-The Stern Review And The Uncertainties In The Economics Of Climate Change; V. Peña.-

Case Study III. Natural Attenuation Of Contamimants And Risk Assessment. Phytotechnologies: How Plants And Bacteria Work Together; S. Shilev et al.-

Subject Index.


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