The usefulness of any model depends in part on the accuracy and reliability of its output. Yet, because all models are imperfect abstractions of reality, and because precise input data are rarely if ever available, all output values are subject to imprecision. Input data errors and modelling uncertainties are not independent of each other – they can interact in various ways. The end result is imprecision and uncertainty associated with model output. This chapter focuses on ways of identifying, quantifying, and communicating the uncertainties in model outputs.
CITATION STYLE
Loucks, D. P., van Beek, E., Stedinger, J. R., Dijkman, J. P. M., & Villars, M. T. (2005). 9 Model Sensitivity and Uncertainty Analysis. Water Resources Systems Planning and Management: An Introduction to Methods, Models and Applications (pp. 254–290). https://doi.org/ISBN: 92-3-103998-9
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