B081-0007
Estimating Interception from Near-Surface Soil Moisture Data

Monday, 14 December 2020
Poster
David A Kaplan, University of Florida, Environmental Engineering Sciences, Ft Walton Beach, FL, United States, Subodh Acharya, University of Florida-SFRC, Gainesville, FL, United States, Daniel L Mclaughlin, Virginia Polytechnic Institute and State University, Forest Resources and Environmental Conservation, Blacksburg, VA, United States and Matthew J Cohen, Univ Florida-SFRC, Gainesville, FL, United States
Abstract:
Interception is the storage and eventual evaporation of precipitation by canopy and groundcover vegetation and surface litter. Quantifying interception is critical for understanding how ecosystems partition precipitation, but it is challenging and expensive to measure empirically, leading most studies to rely on interception models. An additional shortcoming of current approaches for estimating forest interception is a focus only on canopy storage, which neglects the potential for potentially large interception by groundcover vegetation and surface litter. In this study, we developed an in-situ approach for quantifying “total” interception (forest canopy + understory + surface litter) using measured shallow soil moisture dynamics. Specifically, we used soil moisture and precipitation (P) data across 34 pine and mixed forest stands in Florida (USA) to estimate interception storage capacity (βs) and total annual interception (Ia) relative to P (Ia/P). Estimated values for βs (mean = 0.30 cm; 0.01 ≤ βs ≤ 0.62 cm) and Ia/P (mean = 0.14; 0.06 ≤ Ia/P ≤ 0.21) were consistent with the literature for these ecosystems and significantly predicted by attributes of forest structure (leaf area index and groundcover) and other site variables (e.g., water table depth). The best-fit model of βs was dominated by LAI and explained nearly 80% of observed variation. Our results suggest that near-surface soil moisture time series can be used to estimate whole-forest interception, however direct comparisons with other field-based measures would help support this finding. Beyond the methodological advancement presented here, the variability in interception that we found across a single forest type highlights the need for more empirical measurements of this critical water budget element. The cost savings and logistical advantages of this soil moisture-based method may help to make interception measurements possible across ecosystem types at greatly expanded spatial and temporal scales.
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