Effects of Forest Characteristics on Hydrologic Extreme Events across the Climate Gradients of the Conterminous United States

It is well-known that canopy characteristics are important in the annual water budget and precipitation partitioning. The effects of canopy characteristics on hydrologic extreme events (i.e., water available for runoff [W]) related to hydrologic design, however, have received less attention. Here, we conduct a global sensitivity analysis of eight canopy parameters and an analysis of canopy parameter uncertainty and its contribution to modeling hydrologic extremes using a physics-based hydrological model, the Distributed Hydrology Soil Vegetation Model (DHSVM). The study locations at 1/16-degree grid cells included both evergreen and deciduous forests across several climate gradients of the conterminous United States (CONUS). Our results show that the simulated extreme events (W) are most sensitive to differences in parameters related to canopy rainfall interception capacity at all sites, and canopy snow interception parameters are also important at the few snow-dominated sites. Canopy height is equally important as rainfall interception capacity for modeling extreme events at evergreen sites because a tall tree affects the wind profile and decreases aerodynamic resistance compared to a smaller one with the same canopy characteristics (i.e., LAI). This results in higher wet-canopy evaporation loss during extreme events, which can account for about 25% of total extreme precipitation in dense forests. The choice of canopy parameters can significantly modify the simulated extreme water available for runoff. The identified sensitive canopy parameters and uncertainty characterization can help sharpen the simulation of extreme events for improved application to forest hydrology.