Search

Global flood models integrate flood maps of constant probability in space, ignoring the correlation between sites and thus potentially misestimating the risk posed by extreme events. Stochastic flood models alleviate this issue through the simulation of flood events with a realistic spatial structure, yet their proliferation at large scales has historically been inhibited by data quality and computer availability. In this paper, we show, for the first time, the efficacy of modeled river discharge reanalyses in the characterization of flood spatial dependence in the absence of a dense stream gauge network. While global hydrological models may show poor correspondence with absolute observed river flows, we find that the rate at which they can simulate the joint occurrence of relative flow exceedances at two given locations is broadly similar to when a gauge‐based statistical model is used. Evidenced over the United States, flood events simulated using observed gauge data from the U.S. Geological Survey versus those generated using modeled streamflows have similar (i) distributions of site‐to‐site correlation strength, (ii) relationships between event size and return period, and, importantly, (iii) loss distributions when incorporated into a continental‐scale flood risk model. Extremal dependence is generally quantified less accurately on larger rivers, in arid climates, in mountainous terrain, and for the rarest high‐magnitude events. However, local‐scale errors are shown to broadly cancel each other out when combined, producing an unbiased flood spatial dependence model. These findings suggest that building accurate stochastic flood models worldwide may no longer be a distant aspiration. Plain Language Summary: Global flood risk is commonly estimated through flood inundation maps with a defined probability of occurrence. These flood simulations have a key drawback in that they fail to capture the spatial patterns exhibited during real flood events, instead modeling the same probability of flooding on every river at once. Solutions which rely on networks of gauged river flow observations will necessarily break down in the majority of the world's regions which lack such a resource. In this paper, we use historic river flows simulated by global rainfall‐runoff models (rather than observed flows) into a statistical model which captures the spatial correlation of flow extremes. If we examine the relative flow exceedance probabilities from these hydrological models rather than the volumetric flow values, flood events are generated which exhibit similar characteristics to those when gauged flow observations are used. Crucially, the simulation‐ and observation‐generated flood events produce near‐identical losses to buildings in the United States. The implications of this are that true stochastic flood risk models, which account for spatial dependence, can proliferate globally via the generation of realistic flood event sets from hydrological models. Key Points: Large‐scale flood hazard models typically neglect to represent the spatial dependence of real flood eventsRelative flow exceedances simulated by the fusion of global hydrological with statistical models reproduce gauge‐driven flood event setsAt the continental scale, key characteristics of a flood risk model are indistinguishable when driven with observed versus modeled flow data [ABSTRACT FROM AUTHOR]

Many studies investigate river floods by analyzing annual maximum series that record the largest flow of each year, including many within‐bank events inconsequential for human communities. Fewer focus on larger floods, especially at the continental scale. Using 473 streamgages across the conterminous United States with near‐natural flow from 1966 to 2015, we characterized the seasonality, occurrence, and climatic associations of the 10 largest and 2 largest floods at each site. These are often overbank events that have ecosystem functions and pose risks to humans. We grouped sites into 14 clusters corresponding to climatic and physiographic regions and characterized their flood seasonality at a monthly resolution using a probabilistic method. We then evaluated annual occurrence regionally and nationally, and seasonal occurrence regionally, by complementing a traditional approach to trend analyses with a novel method based on expected occurrence. Relationships between flood occurrence and climate indices were also investigated. Large floods have strong seasonality in some regions, but in areas with numerous flood‐generating mechanisms, seasonality is more complex. There is little evidence nationally that large riverine floods are more or less frequent than expected in recent years and only two regions show significant trends in annual counts; few show seasonal trends. We found some regional relationships between flood counts and climate indices, annually and seasonally; nationally the Pacific North American pattern is related to annual counts of the 2 largest floods. Large‐flood occurrence was generally stable across the United States in the last five decades; this may or may not continue with projected warming. Plain Language Summary: Flood studies usually focus on records of the largest streamflow of each year because they are widely available and provide relatively large samples. However, the largest flow of each year is not necessarily big enough to inundate the floodplain and pose risks to human communities. Our study investigated only the largest observed floods in the record, ones that occur roughly every five to fifty years. We used a set of 473 gages that measure near‐natural river flow across the United States. We studied many aspects of these consequential events at regional and national scales for the period 1966–2015, including seasonality, changes over time, and associations with known climate patterns. We found that the seasonality of large floods is strong in some regions, but weak or complex in others where floods have a variety of causes. There is little evidence that large floods have become more or less frequent with time, but we found some regional and national associations between large‐flood occurrence and known climate patterns such as the Pacific North American pattern. Large‐flood occurrence has generally been stable in the last five decades, but continued re‐evaluation of the historical record is important as new data are collected. Key Points: First broad characterization of large‐flood occurrence in the conterminous United States in the modern hydroclimate, including seasonalityBoth traditional and novel methods to assess temporal distribution of large floodsFew significant temporal trends, but significant relations to climate indices for some regions and seasons [ABSTRACT FROM AUTHOR]

Many mountainous and high‐latitude regions have experienced more precipitation as rain rather than snow due to warmer winter temperatures. Further decreases in the annual snow fraction are projected under continued global warming, with potential impacts on flood risk. Here, we quantify the size of streamflow peaks in response to both seasonal and event‐specific rain‐fraction using stream gage observations from watersheds across the western United States. Across the study watersheds, the largest rainfall‐driven streamflow peaks are >2.5 times the size of the largest snowmelt‐driven peaks. Using a panel regression analysis of individual precipitation and snowmelt events, we show that the empirical streamflow response grows approximately exponentially as the liquid precipitation input increases, with rain‐dominated runoff leading to proportionately larger streamflow increases than snowmelt or mixed rain‐and‐snow runoff. We find that the response to changes in rain percentage is largest in the wettest watersheds, where wet antecedent conditions are important for increasing runoff efficiency. Similarly, the effect of rain percentage is larger across watersheds in the Northwest and West regions compared to watersheds in the Northern Rockies and Southwest regions. Overall, as a higher percentage of precipitation falls as rain, increases in the size of rainfall‐driven and "rain‐on‐snow"‐driven floods have the potential to more than offset decreases in the size of snowmelt‐driven floods. Key Points: Stream gages show an approximately exponential increase in streamflow peak size in response to lower snow fraction of runoffRainfall‐driven floods can be more than 2.5 times as large as snowmelt‐driven floods, so a shift toward more rain can increase flood riskSnow‐dominated and mixed‐regime watersheds could see larger floods under warmer winter conditions if precipitation amounts remain similar [ABSTRACT FROM AUTHOR]