In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

Urban catchments are typically characterised by high spatial variability and fast runoff processes resulting in short response times. Hydrological analysis of such catchments requires high resolution precipitation and catchment information to properly represent catchment response. This study investigated the impact of rainfall input resolution on the outputs of detailed hydrodynamic models of seven urban catchments in North-West Europe. The aim was to identify critical rainfall resolutions for urban catchments to properly characterise catchment response. Nine storm events measured by a dual-polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) of the Netherlands, were selected for analysis. Based on the original radar estimates, at 100 m and 1 min resolutions, 15 different combinations of coarser spatial and temporal resolutions, up to 3000 m and 10 min, were generated. These estimates were then applied to the operational semi-distributed hydrodynamic models of the urban catchments, all of which have similar size (between 3 and 8 km2), but different morphological, hydrological and hydraulic characteristics. When doing so, methodologies for standardising model outputs and making results comparable were implemented. Results were analysed in the light of storm and catchment characteristics. Three main features were observed in the results: (1) the impact of rainfall input resolution decreases rapidly as catchment drainage area increases; (2) in general, variations in temporal resolution of rainfall inputs affect hydrodynamic modelling results more strongly than variations in spatial resolution; (3) there is a strong interaction between the spatial and temporal resolution of rainfall input estimates. Based upon these results, methods to quantify the impact of rainfall input resolution as a function of catchment size and spatial–temporal characteristics of storms are proposed and discussed.status: publishe

Green roofs are strategic tools that can play a significant role in the creation of sustainable and resilient cities. They have been largely investigated thanks to their high retention capacity, which can be a valid support to mitigate the pluvial flood risk and to increase the building thermal insulation, ensuring energy saving. Moreover, green roofs contribute to restoring vegetation in the urban environment, increasing the biodiversity and adding aesthetic value to the city. The new generation of multilayer green roofs present an additional layer with respect to traditional ones, which allows rainwater to be stored, which, if properly treated, can be reused for different purposes. This paper offers a review of benefits and limitations of green roofs, with a focus on multilayer ones, within a Water-Energy-Food-Ecosystem nexus context. This approach enables the potential impact of green roofs on the different sectors to be highlighted, investigating also the interactions and interconnections among the fields. Moreover, the Water-Energy-Food-Ecosystem nexus approach highlights how the installation of traditional and multilayer green roofs in urban areas contributes to the Development Goals defined by the 2030 Sustainable Agenda.

Interactions between spatial and temporal variability of rainfall and catchment characteristics strongly influence hydrological response. In urban areas, where runoff generation is fast due to high imperviousness degree, it is especially relevant to capture the high spatiotemporal rainfall variability. Significant progress has been made in the development of spatially distributed rainfall measurements and of distributed hydrological models, to represent the variability of catchment's characteristics. Interactions between rainfall and basin scales on hydrological response sensitivity, however, needs deeper investigation. A previous study investigated the hydrological response in the small urbanized catchment of Cranbrook (8 km², London, UK) and proposed three dimensionless “scale factors” to identify if the available rainfall resolution is sufficient to properly predict hydrological response. We aim to verify the applicability of these scale factors to larger scales, with a distinct physiographic setting, in Little Sugar Creek (111 km², Charlotte, USA), to identify the required rainfall resolution and to predict model performance. Twenty‐eight events were selected from a weather radar data set from the National Weather Radar Network, with a resolution of 1 km² and 15 min. Rainfall data were aggregated to coarser resolutions and used as input for a distributed hydrological model. Results show that scale factors and associated thresholds are generally applicable for characterization of urban flood response to rainfall across spatiotemporal scales. Additionally, application of scale factors in observation‐based analysis supports identification of event characteristics that are poorly captured and critical improvements that need to be made before the model can benefit from high‐resolution rainfall.