An in situ tree interception experiment was conducted to determine the hydrological impact of a solitary standing Norway maple and a small-leaved lime in an urban environment. During the 2-year experiment, rainfall data were collected and divided into interception, throughfall and stemflow. With approximately 38 % of the gross precipitation intercepted by both trees, the interception storage was higher than for similar studies carried out in Mediterranean regions. The specialized forest interception models from Gash (first published in 1978) and Rutter (first published in 1971), as well as an adapted solitary tree version of the Water and Energy Transfer between Soil, Plants and Atmosphere model (WetSpa), were tested for their accuracy in modeling the measured interception storage. The models generally overestimated interception storage for small interception events (< interception storage) and underestimated interception storage for bigger interception events (> interception storage). Gash's method slightly outperformed WetSpa and Rutter for all events throughout seasons and trees. However, WetSpa showed better performance for rainfall events > 10 mm. The similar performance of WetSpa and the Gash and Rutter models is noteworthy because the WetSpa interception model is part of a larger modeling framework that models the whole hydrological balance, whereas the Gash and Rutter methods are specialized stand-alone interception models. Thus, WetSpa is recommended to gain a more complete understanding of the impact of city trees on the full hydrological balance. This study emphasizes the potential effect of city trees on the whole hydrological balance via a combination of field data and simulation experiments using both specialized interception models (Gash and Rutter) and the relatively simple interception module of a holistic water balance model (WetSpa).

A major challenge in hydrologic modeling remains the mapping of vegetation dynamics in an urban landscape. The impact of vegetation on interception storage varies over time and needs to be quantified in order to enable proper management of water resources in urban areas. However, the heterogeneity and complexity of the urban landscape makes it challenging to monitor urban vegetation. A more detailed spatial and temporal scale is needed. To characterize surface cover at a high spatial resolution, a hyperspectral APEX image (2 m) is used, while a time series of Proba-V images (daily, 100 m) allows a detailed characterization of the seasonal variation of urban greenness. For this study, we use and validate the leaf area index (LAI) maps derived from APEX and Proba-V data for a selected pixel in the Watermaelbeek catchment in Brussels (Belgium). The ground-truthing of the Proba-V pixels includes a detailed mapping of land cover characteristics and more specifically vegetation cover throughout the seasons. LAI values calculated based on the APEX image agree with the LAI values measured from the ground (n = 106, $R^2$ = 0.68). Further, the aggregated APEX pixels correlate with the Proba-V pixels ( $R^2$ = 0.79), and the Proba-V data can be used to monitor vegetation dynamics. As the seasonal LAI measurements correspond with the Proba-V dynamics, we conclude that Proba-V images allow the characterization of vegetation dynamics at a high spatial resolution in heterogeneous areas. We create a time series of LAI maps at a high resolution (2 m), which allows a location- and time-specific simulation of interception storage and thus contributes to managing water resources in urban areas.

Vegetation is often represented in an oversimplified way in hydrological models for urbanised catchments, resulting in a generalised parameterisation of urban green. This is common practice, despite the fact that some studies clearly indicate that both the coverage and influence of urban green is often underestimated. In general vegetated surfaces play an important role as areas of recharge, for the redistribution of precipitation and in the regulation of surface runoff, especially for medium intensity storms. Hence, a more realistic and spatially distributed vegetation parameterisation would be of high value for hydrological modelling in urban catchments. In this paper an Earth observation based methodology is presented as an alternative to quantify the influence of canopy interception storage as well as the influence of seasonal dynamics on the urban water balance. Results indicate that Earth observation based interception storage capacities for the Upper Woluwe catchment (Brussels) are up to 25% higher than values obtained from literature, resulting in an increase of cumulative interception rates with 10% over a two year period. The results seem to vary with the rainfall intensity as well as with seasonal dynamics. In order to prove the general applicability of the proposed approach, these results need further confirmation using multi-year analyses and preferably a validation with ground truthing, which is a challenging future task.

A tool called WetSpa-Urban was developed to respond to the need for precise runoff estimations in an increasingly urbanized world. WetSpa-Urban links the catchment model WetSpa-Python to the urban drainage model Storm Water Management Model (SWMM). WetSpa-Python is an open-source, fully distributed, process-based model that accurately represents surface hydrological processes but does not simulate hydraulic structures. SWMM is a well-known open-source hydrodynamic tool that calculates pipe flow processes in an accurate manner while runoff is calculated conceptually. Merging these tools along with certain modifications, such as improving the efficiency of surface runoff calculation and simulating flow at the sub-catchment level, makes WetSpa-Urban suitable for event-based and continuous rainfall–runoff modeling for urban areas. WetSpa-Urban was applied to the Watermaelbeek catchment in Brussels, Belgium, which recently experienced rapid urbanization. The model efficiency was evaluated using different statistical methods, such as Nash–Sutcliffe efficiency and model bias. In addition, a statistical investigation, independent of time, was performed by applying the box-cox transformation to the observed and simulated values of the flow peaks. By speeding up the simulation of the hydrological processes, the performance of the surface runoff calculation increased by almost 130%. The evaluation of the simulated 10 minute flow versus the observed flow at the outlet of the catchment for 2015 reached a Nash–Sutcliffe efficiency of 0.86 and a bias equal to 0.06.