Improving the consistency of hydrologic event identification

Identifying rainfall-runoff events is routinely performed in many hydrologic applications. Absence of a ground-based truth makes rainfall-runoff event identification largely subjective. As a result, current algorithms often disagree on the start and end of events, leading to events within a given set of rainfall and runoff time-series with inconsistent properties – referred to hereafter as ‘uncertainty in rainfall-runoff event identification’. In this study, the uncertainty associated with identifying rainfall-runoff events is assessed across Australia. A considerable uncertainty exists in the characteristics of identified rainfall-runoff events, including in their Runoff Coefficients (RCs). We propose a new objective metric to narrow the plausible set of parameters for identifying rainfall-runoff events. The metric demonstrates a substantial reduction in the uncertainty in rainfall-runoff event identification while improving the plausibility of the rainfall-runoff events chosen (up to a 25 % reduction in RCs >1) making the metric applicable for large-sample analyses of rainfall-runoff events.