A CONUS-scale Study of Wildfire and Evapotranspiration: Spatial and Temporal Response and Controlling Factors

Journal of hydrology(2021)

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摘要
Evapotranspiration (ET) accounts for a substantial portion of regional water budgets in much of the southeast and fire-prone western United States (US). Even small changes in ET rates can translate to meaningful shifts in runoff patterns and makes forecasting the direction and magnitude of wildfire-induced ET alteration of critical importance. We use 1 km ET estimates from the operational Simplified Surface Energy Balance (SSEBop) product for the conterminous US (CONUS) to evaluate post-fire ET and evaporation ratio (ET/P) shifts in the first five post-fire years in approximately 5500 unique fires. Pixels with similar ET/P responses to fire are grouped through k-means clustering and the resultant cluster distribution is explored over space and time. The largest changes in post-fire ET/P are observed in the southwestern CONUS where first-year ratios are reduced by 50 to 90% and pre fire ratios are rarely recovered by post-fire year five. Regional and intra-fire ET/P response variability is also highest in the western CONUS where climatic, topographic, and ecologic gradients are steep. Post-fire ET/P modifications are small to negligible in the east-southeast CONUS, and 18% of all pixels analyzed exhibit small to moderate increases in post-fire year one ET/P. A comparison of burned and unburned pixel pairs confirms the role of fire in the shifts but also indicates a high degree of background variability in the ET and precipitation data. Although the biggest percent ET/P reductions occur in shrub/scrub landscapes in much of the west, the biggest magnitude ET changes often occur in evergreen forests. Higher burn severities are consistently correlated with greater post-fire ET/P reductions, while relationships between post-fire ET/P shifts and numerous other landscape attributes (e.g., pre-fire vegetation type) vary in both direction and magnitude in different parts of the CONUS. Further work can be conducted to refine controlling relationships within more homogeneous subregions.
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关键词
K-means clustering,Remote sensing,SSEBop,Post-fire,Machine learning,Disturbance hydrology
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