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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - On (in)validating environmental models. 2. Implementation of a Turing‐like Test to modelling hydrological processes
AU - Beven, Keith
AU - Lane, Stuart
AU - Page, Trevor
AU - Kretzschmar, Ann
AU - Hankin, Barry
AU - Smith, Paul
AU - Chappell, Nick
PY - 2022/10/31
Y1 - 2022/10/31
N2 - Abstract: Part 1 of this study discussed the concept of using a form of Turing‐like test for model evaluation, together with eight principles for implementing such an approach. In this part, the framing of fitness‐for‐purpose as a Turing‐like test is discussed, together with an example application of trying to assess whether a rainfall‐runoff model might be an adequate representation of the discharge response in a catchment for predicting future natural flood management scenarios. It is shown that the variation between event runoff coefficients in the record can be used to create some limits of acceptability that implicitly take some account of the epistemic uncertainties arising from lack of knowledge about errors in rainfall and discharge observations. In the case study it is demonstrated that the model used cannot be validated in this way across all the range of observed discharges, but that behavioural models can be found for the peak flows that are the subject of interest in the application. Thinking in terms of the Turing‐like test focusses attention on the critical observations needed to test whether streamflow is being produced in the right way so that a model is considered as fit‐for‐purpose in predicting the impacts of future change scenarios. As is the case for uncertainty estimation in general, it is argued that the assumptions made in setting behavioural limits of acceptability should be stated explicitly to leave an audit trail in any application that can be reviewed by users of the model outputs.
AB - Abstract: Part 1 of this study discussed the concept of using a form of Turing‐like test for model evaluation, together with eight principles for implementing such an approach. In this part, the framing of fitness‐for‐purpose as a Turing‐like test is discussed, together with an example application of trying to assess whether a rainfall‐runoff model might be an adequate representation of the discharge response in a catchment for predicting future natural flood management scenarios. It is shown that the variation between event runoff coefficients in the record can be used to create some limits of acceptability that implicitly take some account of the epistemic uncertainties arising from lack of knowledge about errors in rainfall and discharge observations. In the case study it is demonstrated that the model used cannot be validated in this way across all the range of observed discharges, but that behavioural models can be found for the peak flows that are the subject of interest in the application. Thinking in terms of the Turing‐like test focusses attention on the critical observations needed to test whether streamflow is being produced in the right way so that a model is considered as fit‐for‐purpose in predicting the impacts of future change scenarios. As is the case for uncertainty estimation in general, it is argued that the assumptions made in setting behavioural limits of acceptability should be stated explicitly to leave an audit trail in any application that can be reviewed by users of the model outputs.
KW - Water Science and Technology
U2 - 10.1002/hyp.14703
DO - 10.1002/hyp.14703
M3 - Journal article
VL - 36
JO - Hydrological Processes
JF - Hydrological Processes
SN - 0885-6087
IS - 10
M1 - e14703
ER -