Spatial and temporal rainfall variability play an important role in generation of pluvial flooding. In urban areas, this phenomenon has increased in the last decades, due in particular to an intensification of urbanization and imperviousness degree. In fact, population is growing and moving from rural areas to cities, which are becoming more and more urbanized and densely populated. The increase of urbanization and related increase of imperviousness degree, combined with short and intense rainfall events, caused by climate changes, result in a fast hydrological response, with high probability of flooding. Hydrological models can represent the overall flow behaviour but they remain poorly capable of predicting flow peaks, especially in urban areas. In view of this, a better knowledge of the hydrological response of the urban catchment is needed to improve flood prediction and prevent damages caused by pluvial flooding. Due to the high variability of catchment characteristics at small scale, urban runoff processes are particularly sensitive to spatial and temporal variability of rainfall. For this reason, high resolution data are required for accurate runoff estimation. Rainfall is generally measured with rain gauges, which provide accurate measurements in a specific point, but they are not able to fully describe rainfall variability in space. New technologies, such as weather radars, have been used in recent decades to estimate rainfall intensity. Although these instruments provide an indirect measurement of rainfall and require good calibration and error corrections, they can provide rainfall distribution in space and time, which is fundamental to investigate the hydrological response. Rainfall characteristics, such as intensity, total depth, storm velocity and intermittency, strongly affect the hydrological response of the system and it is important to properly characterize them to estimate the runoff. Catchment characteristics, such as drainage area, drainage network, imperviousness degree and slope, and their representation in hydrological models also play an important role in the prediction of hydrological response. At present, combined effects of rainfall and catchment characteristics and scales on urban hydrological response needs further investigations…@en

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 km ² , 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 km ² , 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 km ² 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.

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Rainfall spatial and temporal variability are key points in the prediction of hydrological response. At the same time, catchment scale and characteristics also play important roles, especially in urban areas, where the high level of imperviousness combined with intense and localised rainfall causes fast responses (Ochoa-Rodriguez et al., 2015). New instruments such as weather radars have been developed in recent decades able to better capture the spatial and temporal variability of storm events. At the same time, large improvements have been made to create high-resolution hydrological models that are able to represent the catchment with a high level of detail. However, the interactions between rainfall and catchment variability and their effects on the hydrological response remains poorly understood. In this work, we aim to evaluate the critical space and time scales that characterize rainfall variability and catchment characteristics in relation to hydrological response in urban areas. Critical scales based on dimensionless parameters developed in a previous work (Cristiano et al, 2018) will be evaluated for two urban areas in different climatological regions, one in Europe and one in the US.@en

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

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The high variability in space and time of rainfall is one of the main aspects that influence hydrological response and generation of pluvial flooding. This phenomenon has a bigger impact in urban areas, where response is usually faster and flow peaks are typically higher, due to the high degree of imperviousness. Previous researchers have investigated sensitivity of urban hydrodynamic models to rainfall space-time resolution as well as interactions with model structure and resolution. They showed that finding a proper match between rainfall resolution and model complexity is important and that sensitivity increases for smaller urban catchment scales. Results also showed high variability in hydrological response sensitivity, the origins of which remain poorly understood. In this work, we investigate the interaction between rainfall input variability and model structure and scale at high resolution, i.e. 1-15 minutes in time and 100m to 3 km in space. Apart from studying summary statistics such as relative peak flow errors and coefficient of determination, we look into characteristics of response hydrographs to find explanations for response variability in relation to catchment properties as well storm event characteristics (e.g. storm scale and movement, single-peak versus multi-peak events). The aim is to identify general relations between storm temporal and spatial scale and catchment scale in explaining variability of hydrological response. Analyses are conducted for the Cranbrook catchment (London, UK), using 3 hydrodynamic models set up in InfoWorks ICM: a low resolution semi-distributed (SD1) model, a high resolution semi-distributed (SD2) model and a fully distributed (FD) model. These models represent the spatial variability of the land in different ways: semi-distributed models divide the surface in subcatchments, each of them modelled in a lumped way (51 subcatchment for the S model and 4409 subcatchments for the SD model), while the fully distributed represents the surface with a dense 2D mesh, based on a high resolution Digital Elevation Map. Nine storm events measured by a dual polarimetric X-Band weather radar, located in Cabauw (CAESAR weather station, NL) were used, with original resolution of 100mx100m in space and 1min in time. Results show that the FD model presents a slightly higher sensitivity to spatial rainfall variability than the SD1and SD2 model. Model resolution, however, seems to have a small impact on the sensitivity of model outcomes compared to rainfall variability: intensity and intermittency, as well as spatial range and velocity, have a higher influence than model configuration.@en

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.

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In the last decades, cities have become more and more urbanized and population density in urban areas is increased. At the same time, due to the climate changes, rainfall events present higher intensity and shorter duration than in the past. The increase of imperviousness degree, due to urbanization, combined with short and intense rainfall events, determinates a fast hydrological response of the urban catchment and in some cases it can lead to flooding. Urban runoff processes are sensitive to rainfall spatial and temporal variability and, for this reason, high resolution rainfall data are required as input for the hydrological model. A better knowledge of the hydrological response of system can help to prevent damages caused by flooding. This study aims to evaluate the sensitivity of urban hydrological response to spatial and temporal rainfall variability in urban areas, focusing especially on understanding the hydrological behaviour in lowland areas. In flat systems, during intense rainfall events, the flow in the sewer network can be pressurized and it can change direction, depending on the setting of pumping stations and CSOs (combined sewer overflow). In many cases these systems are also looped and it means that the water can follow different paths, depending on the pipe filling process. For these reasons, hydrological response of flat and looped catchments is particularly complex and it can be difficult characterize and predict it. A new dual polarimetric X-band weather radar, able to measure rainfall with temporal resolution of 1 min and spatial resolution of 100mX100m, was recently installed in the city of Rotterdam (NL). With this instrument, high resolution rainfall data were measured and used, in this work, as input for the hydrodynamic model. High detailed, semi-distributed hydrodynamic models of some districts of Rotterdam were used to investigate the hydrological response of flat catchments to high resolution rainfall data. In particular, the hydrological response of some subcatchments of the district of Kralingen was studied. Rainfall data were combined with level and discharge measurements at the pumping station that connects the sewer system with the waste water treatment plane. Using this data it was possible to study the water balance and to have a better idea of the amount of water that leave the system during a specific rainfall events. Results show that the hydrological response of flat and looped catchments is sensitive to spatial and temporal rainfall variability and it can be strongly influenced by rainfall event characteristics, such as intensity, velocity and intermittency of the storm.@en

Urban hydrological applications require high resolution precipitation and catchment information in order to well represent the spatial variability, fast runoff processes and short response times of urban catchments (Berne et al., 2004). Although fast progress has been made over the last few decades in high resolution measurement of rainfall at urban scales, including increasing use of weather radars, recent studies suggest that the resolution of the currently available rainfall estimates (typically 1 × 1 km2 in space and 5 min in time) may still be too coarse to meet the stringent requirements of urban hydrology (Gires et al., 2012). What is more, current evidence is still insufficient to provide a concrete answer regarding the added value of higher resolution rainfall estimates and actual rainfall input resolution requirements for urban hydrological applications. With the aim of providing further evidence in this regard, a collaborative study was conducted which investigated the impact of rainfall input resolutions on the outputs of the operational urban drainage models of four urban catchments in the UK and Belgium (Figure 1).@en

Flooding in urban areas is one of the main weather-related risk problems of the last decades. It is due to the fact that the population is growing and moving from the rural areas to the cities, which become more urbanized and densely populated. This phenomenon is combined with the climate changes of the last years, that present an increase of short but quite intense rainfall events. These conditions determine a fast and short-time response of the catchments, which increases the probability of flooding.@en