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.