Assessing the Impacts of Extreme Precipitation Change on Flooding in the Northeastern United States

Floods have a devastating impact on infrastructure, agriculture, and the natural landscape, costing an average of $8.83 billion per year in the United States since 2007. Floods mainly occur in response to extreme precipitation events. For example, Hurricane Irene caused an estimated $14.2 billion in damage in the eastern United States over a 6-day period in August 2011. The Northeast has experienced the largest increase in extreme precipitation in the nation, with a 53% increase in 1996-2014 compared to the 1901-1995 average. However, the impact of increases in total and extreme precipitation on flooding is unclear.

To better understand the connections between precipitation and flooding in the Northeast, we developed a random forest model to identify key meteorological and land surface drivers of river discharge in three different watersheds across a range of latitudes. Our developed model reasonably captures daily flows, with larger errors in simulating 95th percentile high flows and 2-year high flows. We find that three day antecedent precipitation is the most important predictor of high flows for the two southern (less snow-dominated) systems, while antecedent soil moisture was the most important high-flow predictor in the northernmost watershed. Although snow melt moderately contributes to model prediction accuracy in the winter, precipitation and soil moisture remain the dominant factors in flow prediction throughout the year for all three watersheds. We further quantify the effects of climate change on flooding in the Northeast by forcing our developed model with climate change projections. Specifically, we analyze the difference in simulated flow using future (2070-2099) and historical (1976-2005) regional climate model output.