Statistical attribution of the frequency of flood events across the US Midwest: A key step towards seasonal and decadal predictions

The frequency of flood events has been increasing notably across large areas of the central United States over the past 50+ years. However, little is known about what is driving these changes. Using an observation-driven approach, we develop a statistical framework to attribute the changes in the frequency of flood peak events to changes in the climate system and to land use/land cover. We focus on 287 US Geological Survey sites with at least 50 years of daily discharge measurements between the second half of the 20th century and the present. Our analyses are performed at the seasonal level and consider five predictors (ie, precipitation, temperature, antecedent wetness conditions, agriculture, and population density). Results indicate that precipitation and antecedent wetness conditions are the strongest predictors, with the role of the latter that increases as we lower the threshold for the event identification.