| Summary: | Several large flooding events in recent years have led to increased concerns that climate change may be affecting the risk of flooding. At-site tests assessing whether change can be detected in observed data are not very powerful and cannot fully differentiate between possible confounders. It is also difficult to detect fully climate-driven trends, and separate these from other anthropogenic impacts such as urbanisation. We propose a change in focus from detection only towards both detecting and attributing trends in peak river flows to large-scale climate drivers such as the North Atlantic Oscillation index. We focus on a set of near-natural “benchmark” catchments in Ireland in order to detect those non-human driven trends. In order to enhance our ability to detect a signal, we model all stations together in a Bayesian framework which is implemented through Stan.
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