Data Abstract: These data are posted in support of a recent paper (Acharya et al. 2020 in HESS) that describe a new method for estimating total forest interception using shallow soil moisture response dynamics. The paper's abstract is presented below, and detailed citation information are also provided. The data files consist of 4+ years of site vegetation attributes, site weather data (4 hr-1) and shallow soil moisture measurements (4 hr-1) across 36 sites spanning the most common forest types in Florida.

Paper Abstract: Interception is the storage and subsequent evaporation of rainfall by above-ground structures, including canopy and groundcover vegetation and surface litter. Accurately quantifying interception is critical for understanding how ecosystems partition incoming precipitation, but it is difficult and costly to measure, leading most studies to rely on modeled interception estimates. Moreover, forest interception estimates typically focus only on canopy storage, despite the potential for substantial interception by ground cover vegetation and surface litter. In this study, we developed an approach to quantify “total” interception (i.e., including forest canopy, understory, and surface litter layers) using measurements of shallow soil moisture dynamics during rainfall events. Across 34 pine and mixed forest stands in Florida (USA), we used soil moisture and precipitation (P) data to estimate interception storage capacity (Bs), a parameter
required to estimate total annual interception (Ia) relative to P. Estimated values for Bs( mean Bs = 0:30 cm; 0:01 < Bs < 0:62 cm) and Ia/P (mean Ia/P = 0:14; 0:06 < Ia=P < 0:21) were broadly consistent with reported literature values for these ecosystems and were significantly predicted by forest structural attributes (leaf area index and percent ground cover) as well as other site variables (e.g., water table depth). The best-fit model was dominated by LAI and 25 explained nearly 80% of observed s variation. These results suggest that whole-forest interception can be estimated using near-surface soil moisture time series, though additional direct comparisons would further support this assertion. Additionally, variability in interception across a single forest type underscores the need for expanded empirical measurement. Potential cost savings and logistical advantages of this proposed method relative to conventional, labor-intensive interception measurements may improve empirical estimation of this critical water budget element.