UPH Problem 20 – reducing uncertainty in model prediction: a model invalidation approach  based on a Turing-like test

Beven, Keith; Page, Trevor; Smith, Paul; Kretzschmar, Ann; Hankin, Barry; Chappell, Nick

doi:https://doi.org/10.5194/piahs-385-129-2024

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.

https://doi.org/10.5194/piahs-385-129-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 385

Post-conference publication

|

18 Apr 2024

Post-conference publication |

| 18 Apr 2024

UPH Problem 20 – reducing uncertainty in model prediction: a model invalidation approach based on a Turing-like test

Keith Beven, Trevor Page, Paul Smith, Ann Kretzschmar, Barry Hankin, and Nick Chappell

Model code and software

dynatop: An Implementation of Dynamic TOPMODEL Hydrological Model in R P. Smith and P. Metcalfe https://cran.r-project.org/web/packages/dynatop/index.html

The CREDIBLE Uncertainty Estimation (CURE) Toolbox T. Page, P. Smith, K. Beven, F. Pianosi, F. Sarrazin, S. Almeida, L. Holcombe, J. Freer, N. Chappell, and T. Wagener https://www.lancaster.ac.uk/lec/sites/qnfm/credible/

Short summary

This paper presents a method of deciding when a hydrological model might be fit for purpose given the limitations of the data that are available for model evaluation. In this case the purpose is to reproduce the peak flows for an application that is concerned with evaluating the effect of natural flood management measures on flood peaks. It is shown that while all the models fail to pass the test at all time steps, there is an ensemble of models that pass for the hydrograph peaks.