Fluvial Flood Losses in the Contiguous United States Under Climate Change.

Flooding is one of the most devastating natural disasters causing significant economic losses. One of the dominant drivers of flood losses is heavy precipitation, with other contributing factors such as built environments and socio‐economic conditions superimposed to it. To better understand the risk profile associated with this hazard, we develop probabilistic models to quantify the future likelihood of fluvial flood‐related property damage exceeding a critical threshold (i.e., high property damage) at the state level across the conterminous United States. The model is conditioned on indicators representing heavy precipitation amount and frequency derived from observed and downscaled precipitation. The likelihood of high property damage is estimated from the conditional probability distribution of annual total property damage, which is derived from the joint probability of the property damage and heavy precipitation indicators. Our results indicate an increase in the probability of high property damage (i.e., exceedance of 70th percentile of observed annual property damage for each state) in the future. Higher probability of high property damage is projected to be clustered in the states across the western and south‐western United States, and parts of the U.S. Northwest and the northern Rockies and Plains. Depending on the state, the mean annual probability of high property damage in these regions could range from 38% to 80% and from 46% to 95% at the end of the century (2090s) under RCP4.5 and RCP8.5 scenarios, respectively. This is equivalent to 20%–40% increase in the probability compared to the historical period 1996–2005. Results show that uncertainty in the projected probability of high property damage ranges from 14% to 35% across the states. The spatio‐temporal variability of the uncertainty across the states and three future decades (i.e., 2050s, 2070s, and 2090s) exhibits nonstationarity, which is driven by the uncertainty associated with the probabilistic prediction models and climate change scenarios. Plain Language Summary: Floods create significant economic losses in the United States and many other places across the world. Floods and flood‐related losses are expected to change due to changes in heavy precipitation in a warmer climate. Inferring how (including when and where) flood‐related losses could change in the future is crucial because of significant implications for flood risk management, insurance, and infrastructure resilience. We develop probabilistic models to project the likelihood of (fluvial) flood‐related high property damage (annual total property damage exceeding a critical threshold) conditioning on precipitation indicators under two greenhouse gas emission scenarios. We estimate relatively higher probability of high property damage for the states across the western and south‐western U.S. and parts of the U.S. Northwest and the northern Rockies and Plains, where projected changes range from 46% to 95% for a high‐emission scenario. In these regions, future changes in the probability of high property damage compared to the historical period vary from 20% to 40%. Overall, our results identify regions with higher likelihood of high property damage in the future, and they are useful for developing long‐term planning and resource mobilization, adaptation, and insurance instruments. Key Points: Future likelihood of flood‐related property damage is quantified using probabilistic models conditioned on precipitation indicatorsIncrease in the probability of flood‐related property damage is projected toward the mid and end of the century across the USNonstationary uncertainties in the projected flood‐related property damage originate from the probabilistic models and climate scenarios [ABSTRACT FROM AUTHOR]