Abstract
Model calibration and validation are not a sufficient step to completely ascertain its reliability, because there are always some reasons of incertitude due to the variability of the terms on which the model is developed. The choice of the parameters, the imprecision of input data and the inner mechanisms of the mathematical procedure may give an unreliable solution. To overcome such a disadvantage, sensitivity and uncertainty analysis can be of assistance. They benefit from basic concepts of statistics, able to focus, in particular, on the discrepancies between the model output and the corresponding values measured in the field. Complex procedures are available, the fundamentals of which are briefly described in this chapter.
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Benedini, M., Tsakiris, G. (2013). Model Reliability. In: Water Quality Modelling for Rivers and Streams. Water Science and Technology Library, vol 70. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5509-3_20
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DOI: https://doi.org/10.1007/978-94-007-5509-3_20
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