TY - JOUR

T1 - Towards a methodology for testing models as hypotheses in the inexact sciences

AU - Beven, K.

N1 - Export Date: 28 May 2019 Correspondence Address: Beven, K.; Lancaster Environment Centre, Lancaster UniversityUnited Kingdom; email: k.beven@lancaster.ac.uk Funding details: Lancaster University Funding text 1: Data accessibility. The original data on which the figures in this paper is based are freely available from the Environment Agency under an OGL license. Competing interests. I declare I have no competing interests. Funding. The preparation of this paper has been supported by the NERC Q-NFM project led by Dr Nick Chappell of Lancaster University (grant NO. NE/R004722/1). Acknowledgements. I have been concerned with the information content of hydrological data throughout my career, but particularly since working with Andy Wood and Paul Smith on the possible disinformation of some observations when used for model calibration. Andy Wood processed the input rainfall data. Paul Smith provided the code for event identification. Nick Chappell, Barry Hankin, Trevor Page and Ann Kretzschmar also contributed to the discussions that led to this paper. I am grateful to Alberto Montanari, Vic Baker, Gray Nearing and one anonymous referee for comments that led to improvements in the presentation, albeit that some strong disagreements in both philosophy and methodology remain.

PY - 2019/4/24

Y1 - 2019/4/24

N2 - This paper reviews the issues involved in treating hydrology as an example of an inexact science faced with significant epistemic uncertainties. It proposes a novel method for developing limits of acceptability for testing hydrological models as hypotheses about how a catchment hydrological system might function. The approach is based only on an analysis of the available observations and the consideration of event mass balance for successive rainfall-runoff events. It is shown that there are many events that are subject to epistemic uncertainties in the input data so that mass balance is not satisfied. The proposed approach allows taking these epistemic uncertainties into account in a pragmatic way before any model runs are made. It is an approach that might be applicable in other areas of environmental science where similar basic principles are fundamental to models, but which might not be satisfied by the observations that are used for model evaluation. © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

AB - This paper reviews the issues involved in treating hydrology as an example of an inexact science faced with significant epistemic uncertainties. It proposes a novel method for developing limits of acceptability for testing hydrological models as hypotheses about how a catchment hydrological system might function. The approach is based only on an analysis of the available observations and the consideration of event mass balance for successive rainfall-runoff events. It is shown that there are many events that are subject to epistemic uncertainties in the input data so that mass balance is not satisfied. The proposed approach allows taking these epistemic uncertainties into account in a pragmatic way before any model runs are made. It is an approach that might be applicable in other areas of environmental science where similar basic principles are fundamental to models, but which might not be satisfied by the observations that are used for model evaluation. © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

KW - Epistemic uncertainty

KW - Hydrological models

KW - Runoff coefficients

KW - Catchments

KW - Uncertainty analysis

KW - Basic principles

KW - Environmental science

KW - Epistemic uncertainties

KW - Hydrological system

KW - Model evaluation

KW - Rainfall-runoff events

KW - Runoff

U2 - 10.1098/rspa.2018.0862

DO - 10.1098/rspa.2018.0862

M3 - Journal article

VL - 475

JO - Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

JF - Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences

SN - 1364-5021

IS - 2224

M1 - 20180862

ER -