查看更多>>摘要：Abstract Peak flow characteristics, including magnitude, duration, frequency, time to peak, and timing shift, undergo significant changes following wildfire disturbances. This study synthesizes findings from a diverse range of recent research, encompassing varied physiographic, climatic, and wildfire conditions, as well as applied methodologies to quantify and analyze the relationships between these factors and changes in post-fire peak flow attributes. The review reveals consistent evidence of post-fire alterations in peak flow, with the majority of studies reporting an increase in peak flow magnitude (ranging from less than 1% to over 200 times (~ 20,000%) relative to pre-fire magnitudes). Additionally, peaks occurring 1 to 50 days earlier and a 10–50% decrease in time to peak compared to the pre-fire period were observed in the literature. However, duration and frequency characteristics were often not analyzed in the reviewed studies. The methodologies employed include statistical approaches (descriptive and predictive) and physically based hydrological modeling, each with distinct advantages and limitations. Selecting the most appropriate methodology to quantify wildfire effects on peak flow characteristics depends on the specifics of the case study and data availability. However, according to the results of the reviewed studies, hydrological modeling using the Before-After-Control-Impact (BACI) approach appears to yield more reliable results than statistical models for such evaluations. Furthermore, in the case of utilizing statistical models, considering precipitation intensity, burn severity, slope, watershed size, and the percentage of burned areas is recommended as these are the most influential variables. Moreover, the results indicated that greater changes (mainly increases in post-fire peak flow magnitude) occur in basins with extremely steep slopes (> 30%), small areas (< 10,000 ha), and grassland/shrubland vegetation cover that experience high-severity wildfires. Several gaps were identified in the current body of research. For instance, hydrological models often treat post-fire parameters as static, ignoring potential spatial and temporal variability. Similarly, statistical models typically rely on linear algorithms, despite evidence suggesting that wildfire-hydrology interactions may be non-linear. Another critical gap is the lack of guidance on integrating post-fire increases in hydrological extremes into flood frequency analysis (FFA). Addressing these gaps is essential for advancing land management practices and enhancing resilience against the growing impacts of wildfires on hydrological systems.
NETL
NSTL
Springer Nature