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Interception represents a significant component of the water budget of forests, diverting significant quantities of precipitation away from soil moisture, transpiration, and surface and groundwater recharge. There are several physically-based models of forest interception but their utility across seasonal variability is limited because few studies have collected field data of both the growing (leaf on) and dormant (leaf off) seasons and explored how seasonality affects parameters of simulations. Rainfall partitioning modelling using the Reformulated Gash Analytical Model (RGAM) for Brant’s oak ( Quercus brantii ) forest plots in the Zagros forest, Iran, simulated interception values close to the observed, with an underestimation of 4.0% and 7.5% for the leafed and leafless periods, respectively. Model parameters varied seasonally: free throughfall coefficient, canopy storage capacity, canopy saturation point, and ratio of mean wet evaporation rate to mean rainfall intensity were ∼0.60, 1.0 mm, 2.6 mm, and 0.15 in the leafed period and ∼0.80, 0.1 mm, 0.5 mm, and 0.04 in the leafless period, respectively. In this application, the RGAM was highly sensitive to change in the ratio of mean wet evaporation rate to mean rainfall intensity, and less sensitive to canopy cover and canopy storage capacity, especially in the leafless period. Therefore, canopy structure is less important for rainfall interception predictions by RGAM. [ABSTRACT FROM AUTHOR]

Summary: The effects of canopy evaporation and intensity smoothing during rain events on hillslope subsurface stormflow are poorly understood. While watershed manipulation experiments have suggested that these processes are important at long timescales, such processes may also be important in storm-timescale responses. Notwithstanding, there are few hillslopes for which both internal subsurface stormflow generation processes and canopy processes are known, so canopy interception effects on subsurface stormflow have not been tested mechanistically. Furthermore, it has not yet been possible to separate the effects of canopy evaporation from intensity smoothing in terms of which component of interception most affects hillslope response. We report a series of virtual experiments (numerical experiments driven by collective field intelligence) using HYDRUS-2D to model flow in a well-studied and characterized research hillslope in Georgia, USA. Previous work has shown that HYDRUS-2D approximates well both measured subsurface stormflow and internal pore pressures at this site. Our virtual experiments compared modeled hillslope response to rainfall and throughfall characteristic of known forest canopy processes in Washington, USA. The experiments generated subsurface stormflow using measured rainfall and throughfall data from three sites within the forest, and using synthetic, simplified throughfall signals containing either evaporation alone or intensity smoothing alone. As expected, results of our virtual experiments driven by field-measured throughfall data showed that evaporative loss delayed the onset of subsurface stormflow, lowered and delayed stormflow peaks, and decreased total flow and the runoff ratio. Virtual experiments based on simplified modeled throughfall (where we separated evaporation from intensity smoothing) showed that canopy evaporation was responsible for most of these effects, while intensity smoothing showed measurable differences only in peak subsurface stormflow rate. Overall, this work has implications for the calibration of watershed models. Not only would ignoring interception miss a major effect of vegetation on subsurface stormflow generation, our work also shows that simply applying some fractional reduction as a scaled input signal (as is customary in watershed modeling studies) may mask important effects on peak flow response in some situations. [Copyright &y& Elsevier]

Abstract: Little is understood about how storage of water on forest canopies varies during rainfall, even though storage changes intensity of throughfall and thus affects a variety of hydrological processes. In this study, laboratory rainfall simulation experiments using varying intensities yielded a better understanding of dynamics of rainfall storage on woody vegetation. Branches of eight species generally retained more water at higher rainfall intensities than at lower intensities, but incremental storage gains decreased as rainfall intensity increased. Leaf area was the best predictor of storage, especially for broadleaved species. Stored water ranged from 0.05 to 1.1mm effective depth on leaves, depending on species and rainfall intensity. Storage was generally about 0.2mm greater at rainfall intensity 420mmh−1 than at 20mmh−1. Needle-leaved branches generally retained more water per leaf area than did branches from broadleaved species, but branches that stored most at lower rainfall intensities tended to accumulate less additional storage at higher intensities. A simple nonlinear model was capable of predicting both magnitude (good model performance) and temporal scale (fair model performance) of storage responses to varying rainfall intensities. We hypothesize a conceptual mechanical model of canopy storage during rainfall that includes the concepts of static and dynamic storage to account for intensity-driven changes in storage. Scaling up observations to the canopy scale using LAI resulted in an estimate of canopy storage that generally agrees with estimates by traditional methods. [Copyright &y& Elsevier]