On (in)validating environmental models. 2. Implementation of a Turing‐like test to modelling hydrological processes

• Published in: Hydrological processes Vol. 36; no. 10
• Main Authors: Beven, Keith, Lane, Stuart, Page, Trevor, Kretzschmar, Ann, Hankin, Barry, Smith, Paul, Chappell, Nick
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.10.2022; Wiley Subscription Services, Inc
• Subjects: Acceptability; audits; case studies; Coefficient of variation; Coefficients; Computation; Discharge; Environment models; Environmental modeling; epistemic uncertainties; Flood control; Flood management; Flood predictions; hydraulic models; hydrologic model; Hydrologic models; Hydrologic processes; Hydrology; hypothesis testing; Impact prediction; limits of acceptability; Logic; Model testing; model validation; Modelling; Precipitation; rain; Rainfall-runoff relationships; Runoff; Runoff coefficient; Stream discharge; Stream flow; Uncertainty; Watersheds
• ISSN: 0885-6087; 1099-1085
• DOI: 10.1002/hyp.14703

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. Provides a case study of the application of a Turing‐like test of model invalidation as applied to rainfall‐runoff modelling with the purpose of predicting the impact of natural flood management measures on the response of the River Kent catchment, Cumbria, UK. The figure shows the outputs of models retained after evaluation on flood peaks using limits of acceptability that allow for epistemic uncertainties in the data.