On hypothesis testing in hydrology: Why falsification of models is still a really good idea. (15th February 2018)

• Record Type: Journal Article
• Authors: Beven, Keith J.
• Is Part Of: Wiley interdisciplinary reviews. Volume 5:Number 3(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-02-15
• Subjects: data uncertainty -- exploratory hydrology -- model evaluation -- model rejection -- observation techniques; Hydrology -- Periodicals; 553.705
• DOI: 10.1002/wat2.1278
• Languages: English
• ISSNs: 2049-1948

Abstract

Abstract : This opinion piece argues that in respect of testing models as hypotheses about how catchments function, there is no existing methodology that adequately deals with the potential for epistemic uncertainties about data and hydrological processes in the modeling processes. A rejectionist framework is suggested as a way ahead, wherein assessments of uncertainties in the input and evaluation data are used to define limits of acceptability prior to any model simulations being made. The limits of acceptability might also depend on the purpose of the modeling so that we can be more rigorous about whether a model is actually fit‐for‐purpose. Different model structures and parameter sets can be evaluated in this framework, albeit that subjective elements necessarily remain, given the epistemic nature of the uncertainties in the modeling process. One of the most effective ways of reducing the impacts of epistemic uncertainties, and allow more rigorous hypothesis testing, would be to commission better observational methods. Model rejection is a good thing in that it requires us to be better, resulting in advancement of the science. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Abstract : An example of model invalidation in an application of the SWAT model to the 12.5 km 2 Newby Beck catchment in Cumbria. Black solid and dashed lines represent the daily estimates of discharges and total phosphorus loads, calculated from high‐frequency observations (15 min for flow, 30 min for discharge), with 95% uncertainty bound estimates. Green band represents range of the 1001 best simulations from 5 million model runs, evaluated on both discharge and total phosphorus. The model was run at a daily time step. Retention of the 1001 simulations required extension of the limits of acceptability based on the observational uncertainties by a factor of 5.3 during the evaluation period. The figure represents the simulations for a separate validation period (for further details see Hollaway, Beven et al., 2018).