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N. Gaber
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Chapter Four Complexity and Uncertainty
Rethinking the Modelling Activity
Book chapter
(2008)
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M. Brugnach, C. Pahl-Wostl, K. E. Lindenschmidt, J. A.E.B. Janssen, T. Filatova, A. Mouton, G. Holtz, P. van der Keur, N. Gaber
The complexity and uncertainty inherent in environmental models must be considered and managed in an appropriate manner. This chapter presents a conceptual approach to deal with uncertainty, which considers the context of the purpose for which the model is developed. The four major modelling purposes identified - prediction, exploratory analysis, communication and learning - each focus on different modelling characteristics and roles of uncertainty. The notion of uncertainty is broadened, from being an attribute associated with the quality of information to also comprise modellers' beliefs and experiences. The chapter proposes ways in which uncertainty should be handled for each of the four modelling purposes and presents examples that illustrate the concepts. Various sources of uncertainty are considered relevant when modelling complex systems, and each source manifests differently in the data, structure or frame of the model.
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The complexity and uncertainty inherent in environmental models must be considered and managed in an appropriate manner. This chapter presents a conceptual approach to deal with uncertainty, which considers the context of the purpose for which the model is developed. The four major modelling purposes identified - prediction, exploratory analysis, communication and learning - each focus on different modelling characteristics and roles of uncertainty. The notion of uncertainty is broadened, from being an attribute associated with the quality of information to also comprise modellers' beliefs and experiences. The chapter proposes ways in which uncertainty should be handled for each of the four modelling purposes and presents examples that illustrate the concepts. Various sources of uncertainty are considered relevant when modelling complex systems, and each source manifests differently in the data, structure or frame of the model.