Articles | Volume 385
https://doi.org/10.5194/piahs-385-129-2024
© Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License.
UPH Problem 20 – reducing uncertainty in model prediction: a model invalidation approach based on a Turing-like test
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Beven, K., Smith, P. J., and Wood, A.: On the colour and spin of epistemic error (and what we might do about it), Hydrol. Earth Syst. Sci., 15, 3123–3133, https://doi.org/10.5194/hess-15-3123-2011, 2011.
Beven, K. J.: EGU Leonardo Lecture: Facets of Hydrology – epistemic error, non-stationarity, likelihood, hypothesis testing, and communication, Hydrol. Sci. J., 61, 1652–1665, https://doi.org/10.1080/02626667.2015.1031761, 2016.
Beven, K. J.: Towards a methodology for testing models as hypotheses in the inexact sciences, Proceedings Royal Society A, 475, 2224, https://doi.org/10.1098/rspa.2018.0862, 2019.
Beven, K. J. and Lane, S.: Invalidation of models and fitness-for-purpose: a rejectionist approach, Chapter 5, in: Computer Simulation Validation – Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives, edited by: Beisbart, C. and Saam, N. J., Cham: Springer, 145–171, https://doi.org/10.1007/978-3-319-70766-2_6, 2019.
Beven, K. J. and Lane, S.: On (in)validating environmental models. 1. Principles for formulating a Turing-like Test for determining when a model is fit-for purpose, Hydrological. Process., 36, e14704, https://doi.org/10.1002/hyp.14704, 2022.