Summary
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
Dig deeper with Pulse AI.
Pulse AI has read the whole catalogue. Ask about this record, its theme, or how the findings apply to UK farming and policy — every answer cites the underlying studies.