The Spatial Dependence of Flood Hazard and Risk in the United States. Issue 3 (4th March 2019) - Quinn, Niall; Bates, Paul D.; Neal, Jeff; Smith, Andy; Wing, Oliver; Sampson, Chris; Smith, James; Heffernan, Janet
Abstract: In this paper we seek to understand the nature of flood spatial dependence over the conterminous United States. We extend an existing conditional multivariate statistical model to enable its application to this large and heterogenous region and apply it to a 40‐year data set of 2, 400 U.S. Geological Survey gauge series records to simulate 1, 000 years of U.S. flooding comprising more than 63, 000 individual events with realistic spatial dependence. A continental‐scale hydrodynamic model at 30 m resolution is then used to calculate the economic loss arising from each of these events. From this we are able to compute the probability that different values of U.S. annual total economic loss due to flooding are exceeded (i.e., a loss‐exceedance curve). Comparing these data to an observed flood loss‐exceedance curve for the period 1988–2017 shows a reasonable match for annual losses with probability below 10% (e.g., >1 in 10‐year return period). This analysis suggests that there is a 1% chance of U.S. annual fluvial flood losses exceeding 78Bn in any given year, and a 0.1% chance of them exceeding 136Bn. Analysis of the set of stochastic events and losses yields new insights into the nature of flooding and flood risk in the United States. In particular, we confirm the strong relationship between flood affected area and event peak magnitude, but show considerable variability in this relationship between adjacent U.S. regions. The analysis provides a significant advance over previous national flood risk analyses as it gives the full loss‐exceedance curve instead of simply the average annual loss. Plain Language Summary: Traditional flood risk analyses make the assumption that flow probability (the chance that a given river discharge is exceeded) does not vary within river catchments within an event. Real floods, however, do not look like this: In some places flooding is more severe than in others. Over a few tens of kilometers of river assuming the same event return period everywhere is perfectly fine, but over larger areas it breaks down. At national scales traditional risk analyses can only estimate the average annual loss. To estimate the total annual losses that might occur in more extreme flooding years the risk analysis needs to be based on more realistic spatial patterns of flooding. In this paper we use a sophisticated statistical model, based on U.S. Geological Survey river flow data, to simulate 1, 000 years of spatially realistic U.S. flooding comprising more than 63, 000 individual events. By calculating the damage for each event as a dollar value, we are able to estimate the probability of the United States experiencing particular levels of annual flood losses. We show that there is a 1% chance of U.S. annual fluvial flood losses exceeding 78Bn in any given year, and a 0.1% chance of them exceeding 136Bn. Key Points: 1, 000 years of realistic U.S. flood patterns, comprising >63, 000 individual events, are simulated using a statistical model Monetary losses for each event are calculated using a continental hydrodynamic model at 30 m resolution The analysis suggests that there is a 1% chance of U.S. annual fluvial flood losses exceeding 78Bn in any given year