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Precipitation channelled down tree stems (stemflow) or into drip points of ‘throughfall’ beneath trees results in spatially concentrated inputs of water and chemicals to the ground. Currently, these flows are poorly characterised due to uncertainties about which branches redirect rainfall to stemflow or throughfall drip points.We introduce a graph theoretic algorithm that ‘prunes’ quantitative structural models of trees (derived from terrestrial LiDAR) to identify branches contributing to stemflow and those contributing to throughfall drip points. To demonstrate the method's utility, we analysed two trees with similar canopy sizes but contrasting canopy architecture and rainfall partitioning behaviours.For both trees, the branch ‘watershed’ area contributing to stemflow (under conditions assumed to represent moderate precipitation intensity) was found to be only half of the total ground area covered by the canopy. The study also revealed significant variations between trees in the number and median contribution areas of modelled throughfall drip points (69 vs. 94 drip points tree⁻¹, with contributing projected areas of 28.6 vs. 7.8 m²tree⁻¹, respectively). Branch diameter, surface area, volumes and woody area index of components contributing to stemflow and throughfall drip points may play a role in the trees' differing rainfall partitioning behaviours.Our pruning algorithm, enabled by the proliferation of LiDAR observations of canopy structure, promises to enhance studies of canopy hydrology. It offers a novel approach to refine our understanding of how trees interact with rainfall, thereby broadening the utility of existing LiDAR data in environmental research. 

Abstract Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists’ human sensory and cognitive systems during storms.