Abstract
Recent advances in the field of extreme event attribution make it possible to estimate how anthropogenic global warming affects the odds of climate disasters, such as river floods. Extreme event attribution typically uses precipitation as a proxy for flooding. However, hydrological processes and antecedent conditions make the relation between extreme precipitation and floods highly non-linear. In addition, hydrological science informs us that changes in flood occurrence can be strongly driven by changes in land-cover and by other human interventions in the hydrological system, such as irrigation, and construction of dams and levees. These drivers can either amplify, dampen or outweigh the effect of climate change on local flood occurrence, and neglecting them can lead to incorrect attribution statements. Explicitly including flooding will lead to more robust event attribution, and will account for the role of other drivers beyond climate change. Existing attempts are sparse and incomplete. Key challenges are the lack of flood observations and a dedicated flood attribution framework. We argue that the existing probabilistic framework for extreme event attribution can be extended to explicitly include floods for near-natural cases, where flood occurrence was unlikely to be strongly influenced by land-cover change and human hydrological interventions. However, for the many cases where this assumption is not valid, a multi-driver framework for conditional event attribution needs to be established. Explicit flood attribution will require collaboration between climatologists and hydrologists, and promises to better address the needs of flood risk management.