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Accurate estimation of hydrological losses is required for making vitaldecisions in design applications that are based on design rainfall modelsand rainfall–runoff models. The use of representative single values ofhydrological losses, despite their wide variability, is common practice,especially in Australian studies. This practice leads to issues such as overor under estimation of design floods. The probability distribution method ispotentially a better technique to describe losses. However, a lack ofunderstanding of how losses are distributed can limit the use of thistechnique. This paper aims to identify a probability distribution functionthat can successfully describe hydrological losses of a catchment ofinterest. The paper explains the systematic process of identifyingprobability distribution functions, the problems faced during thedistribution fitting process and a new generalised method to test theadequacy of fitted distributions. The goodness-of-fit of the fitteddistributions are examined using the Anderson–Darling test and the Q–Q plotmethod and the errors associated with quantile estimation are quantified byestimating the bias and mean square error (MSE). A two-parameter gammadistribution was identified as one that successfully describes initial loss(IL) data for the selected catchments. Further, non-parametric standardiseddistributions that describe both IL and continuing loss data are alsoidentified. This paper will provide a significant contribution to theAustralian Rainfall and Runoff (ARR) guidelines that are currently beingupdated, by improving understanding of hydrological losses in SouthAustralian catchments. More importantly, this study provides new knowledgeon how IL in a catchment is characterised

Probability distributions for explaining hydrological losses in South Australian catchments