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 groundcover 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?(βs), a parameter required to estimate total annual interception?(Ia) relative to?P. Estimated values for?βs(mean βs=0.30 cm; 0.01≤βs≤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 explained nearly 80 % of observed?βs 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.
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机译：拦截是储存和随后通过上面的地面结构蒸发降雨，包括树冠和地基植被和表面垫料。准确量化拦截对于了解生态系统分区的进入降水至关重要，但衡量大多数研究依赖于建模拦截估计，难以且昂贵。此外，森林拦截估计通常仅关注天盖存储，尽管地下植被和地面垃圾的实质性拦截有可能。在这项研究中，我们开发了一种在降雨事件期间使用浅层土壤水分动力学的测量来量化“总”拦截（即，包括森林冠层，林下和表面垃圾层）的方法。横跨34？佛罗里达州的杉木和混合森林？（美国），我们使用土壤水分和降水量？（p）数据来估计拦截储存容量？（βS），一个参数估计年度截取所需的参数？（IA）相对？p。估计βS的值（平均β= 0.30cm;0.01≤βs≤0.62cm）和Ia / p（平均值Ia / p = 0.14;0.06≤ia/p≤0.21）与这些生态系统的报告的文献值和被森林结构属性（叶面积指数和地面覆盖百分比）以及其他地点变量（例如，水台深）显着预测。最佳拟合模型由赖占主导地位，解释了近80％的观察到的βS变异。这些结果表明，可以使用近地面土壤湿度时间序列估算全森拦截，但额外的直接比较将进一步支持这种断言。此外，在单个林类型上拦截的可变性强调了扩展经验测量的需求。这种提出的方法相对于常规，劳动密集型拦截测量的潜在成本节约和后勤优势可以改善这种关键水预算元素的实证估计。
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