A rapid rise of urban population is making cities denser. Consequently, the proportion of impervious surface cover has enlarged, increasing the amount and speed of run‐off reaching urban catchment areas, which may cause flash flooding. Trees play a key role to reduce run‐off in the city, as they intercept rainfall and store part of it on their leaves and branches, reducing the amount and speed of water running onto impervious surfaces. Storage capacity will depend on the rainfall event, the climate conditions and tree characteristics and canopy density. These canopy characteristics vary greatly among different species and their phenology. Furthermore, these canopy characteristics can vary greatly among individual trees of the same age, size, and species. This study tested how canopy density and leaf characteristics of three different tree species affect storage capacity under simulated rainfall conditions. Three species were selected (Ulmus procera, Platanus × acerifolia, and Corymbia maculata), each being of the same height and similar canopy dimensions. Storage capacity was measured using a mass balance approach during a 15‐min indoor, simulated rainfall event (2.5 mm/hr). Canopy metrics were estimated using a terrestrial laser scanner. Canopy surface area was measured through destructive harvest and leaf/twig/branch scanning. To investigate variations in the canopy leaf density, leaves were systematically removed to create four treatments: full, half, quarter, and woody. Canopy storage capacity was well correlated to plant surface area (m2), plant area index (m2/m2), and plant area density (m2/m3). All analyses indicated U. procera as the most efficient species for storing rainfall water within a canopy of equal volume or area index. Results reveal the complexity of evaluating interception of rainfall by tree canopies. This study contributes to the discipline and practice by distinguishing how variation in the leaf density is important to consider when selecting urban tree species to be planted.

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Urban trees deliver many ecological services to the urban environment, including reduced runoff generation in storms. Trees intercept rainfall and store part of the water on leaves and branches, reducing the volume and velocity of water that reaches the soil. Moreover, trees modify the spatial distribution of rainwater under the canopy. However, measuring interception parameters is a complex task because it depends on many factors, including environmental conditions (rainfall intensity, wind speed, etc.) and tree characteristics (plant surface area, leaf and branch inclination angle, etc.). In the few last decades, remotely sensed data have been tested for retrieving tree metrics, but the use of this derived data for predicting interception parameters are still being developed. In this study, we measured the minimum water storage capacity (Cmin) and throughfall under the canopies of 12 trees belonging to three different species. All trees had their plant surface metrics calculated: plant surface area (PSA), plant area index (PAI), and plant area density (PAD). Trees were scanned with a mobile terrestrial laser scan (TLS) to obtain their individual canopy point clouds. Point clouds were used to calculate canopy metrics (canopy projected area and volume) and TLS-derived surface metrics. Measured surface metrics were then correlated to derived TLS metrics, and the relationship between TLS data and interception parameters was tested. Additionally, TLS data was used in analyses of throughfall distribution on a sub-canopy scale. The significant correlation between the directly measured surface area and TLS-derived metrics validates the use of the remotely sensed data for predicting plant area metrics. Moreover, TLS-derived metrics showed a significant correlation with a water storage capacity parameter (Cmin). The present study supports the use of TLS data as a tool for measuring tree metrics and ecosystem services such as Cmin; however, more studies to understand how to apply remotely sensed data into ecological analyses in the urban environment must be encouraged.