Process‐Based Quantification of the Role of Wildfire in Shaping Flood Frequency

作者：Guo Yu, Tao Liu, Luke A. McGuire, Daniel B. Wright, Benjamin J. Hatchett, Julianne J. Miller, Markus Berli, Jeremy Giovando, Michael Bartles, Ian Floyd · 发表于：Water Resources Research · 年份：2023 · DOI：10.1029/2023wr035013 · 被引用次数：14 · 研究领域：Fire effects on ecosystems、Landslides and related hazards、Plant Water Relations and Carbon Dynamics

Abstract Moderate to high severity wildfire can abruptly alter watershed properties and enhance extreme hydrologic responses such as debris flows and floods. The compounding effects of wildfire on flood hazard, represented here via flood frequency analysis (FFA; e.g., 100‐year flood) are of growing importance. Standard statistical FFA approaches are ill‐suited to examining this issue because wildfire‐affected flood peak observations are limited in number and violate the assumption of independent and identically distributed events. Here, we developed a process‐based FFA framework that integrates a stochastic rainfall generator, wildfire simulation, inverse modeling, and a physics‐based hydrological model to directly simulate the impacts of wildfire on FFA. We applied this framework in the upper Arroyo Seco watershed in Southern California, which experienced Moderate to high burn during the 2009 Station Fire. An FFA analysis, performed with simulated peak flows from the first year since fire demonstrates the 100‐year flood can be three times larger than simulations that only consider peak flows in non‐fire‐affected years. On the other hand, coupling process‐based FFA with stochastically simulated wildfire events and watershed's time‐varying hydrologic recovery yields “fire continuum FFA”, a concept introduced here for the first time. Fire continuum FFA accounts for multiple wildfires within very long synthetic time series. Variability in upper tail flood peaks is substantially ...