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Understanding and attributing the characteristics of extreme events that lead to societal impacts is a key challenge in climate science. Detailed analysis of individual case studies is particularly important in assessing how anthropogenic climate change is changing the likelihood of extreme events and their associated risk at relevant spatial scales. Here, we conduct a comprehensive multi-method attribution analysis of the heavy precipitation that led to widespread flooding in Boulder, Colorado in September 2013. We provide clarification on the source regions of moisture associated with this event in order to highlight the difficulty of separating dynamic and thermodynamic contributions. Using extreme value analysis of, first of all, historical observations, we then assess the influence of anthropogenic climate change on the overall likelihood of one- and five-day precipitation events across the Boulder area. The same analysis is extended to the output of two general circulation model ensembles. By combining the results of different methods we deduce an increase in the likelihood of extreme one-day precipitation but of a smaller magnitude than what would be expected in a warming world according to the Clausius–Clapeyron relation. For five-day extremes, we are unable to detect a change in likelihood. Our results demonstrate the benefits of a multi-method approach to making robust statements about the anthropogenic influence on changes in the overall likelihood of such an event irrespective of its cause. We note that, in this example, drawing conclusions solely on the basis of thermodynamics would have overestimated the increase in risk.