The Influence of Rainfall and Catchment Critical Scales on Urban Hydrological Response Sensitivity

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

The need for high resolution data to improve urban flood 1 risk assessment 2

Abstract 12 Cities are particularly vulnerable to rainfall-generated floods that are typically characterised 13 by their rapid onset and localised nature. This implies that precipitation and catchment 14 information need to be available at high resolution to reliably predict hydrological response 15 and potential flooding. On the contrary, urban areas constitute a major knowledge gap as most 16 flood risk studies have concentrated on natural basins and records of rain gauges and water 17 level gauges in cities are scarce. While increase in intense precipitation as a result of climate 18 change is expected in many areas around the world, it is at present not possible to assess how 19 this will affect urban pluvial flood risk. Collection of reliable, high resolution data in cities 20 needs to start urgently to build up datasets in support of urban flood risk assessment and to 21 enable detection of changes in flood risk whether these are induced by climate change, 22 urbanisation or other future developments. This study shows how implementation of 23 polarimetric X-band radar can contribute to filling the knowledge gap of flood risk 24 quantification in cities. 2

Sensitivity of urban drainage models to the spatial-temporal resolution of rainfall inputs: A multi-storm, multi-catchment investigation

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 x 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)

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density

Effects of different spatial and temporal rainfall data resolution on hydrological response in flat urban catchments

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

On the occurrence of rainstorm damage based on home insurance and weather data

Rainstorm damage caused by the malfunction of urban drainage systems and water intrusion due to defects in the building envelope can be considerable. Little research on this topic focused on the collection of damage data, the understanding of damage mechanisms and the deepening of data analysis methods. In this paper, the relative contribution of different failure mechanisms to the occurrence of rainstorm damage is investigated, as well as the extent to which these mechanisms relate to weather variables. For a case study in Rotterdam, the Netherlands, a property level home insurance database of around 3100 water-related damage claims was analysed. The records include comprehensive transcripts of communication between insurer, insured and damage assessment experts, which allowed claims to be classified according to their actual damage cause. The results show that roof and wall leakage is the most frequent failure mechanism causing precipitation-related claims, followed by blocked roof gutters, melting snow and sewer flooding. Claims related to sewer flooding were less present in the data, but are associated with significantly larger claim sizes than claims in the majority class, i.e. roof and wall leakages. Rare events logistic regression analysis revealed that maximum rainfall intensity and rainfall volume are significant predictors for the occurrence probability of precipitation-related claims. Moreover, it was found that claims associated with rainfall intensities smaller than 7–8 mm in a 60-min window are mainly related to failure processes in the private domain, such as roof and wall leakages. For rainfall events that exceed the 7–8 mm h−1 threshold, the failure of systems in the public domain, such as sewer systems, start to contribute considerably to the overall occurrence probability of claims. The communication transcripts, however, lacked information to be conclusive about to which extent sewer-related claims were caused by overloading of sewer systems or failure of system components

On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution

Cities are increasingly vulnerable to floods generated by intense rainfall, because of urbanisation of flood-prone areas and ongoing urban densification. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction in cities. In this paper, a detailed study of the sensitivity of urban hydrodynamic response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar were used as input into a detailed hydrodynamic sewer model for an urban catchment in the city of Rotterdam, the Netherlands. The aim was to characterise how the effect of space and time aggregation on rainfall structure affects hydrodynamic modelling of urban catchments, for resolutions ranging from 100 to 2000 m and from 1 to 10 min. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm characteristics and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size), catchment sampling number (rainfall resolution vs. catchment size), runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively). Results show that for rainfall resolution lower than half the catchment size, rainfall volumes mean and standard deviations decrease as a result of smoothing of rainfall gradients. Moreover, deviations in maximum water depths, from 10 to 30% depending on the storm, occurred for rainfall resolution close to storm size, as a result of rainfall aggregation. Model results also showed that modelled runoff peaks are more sensitive to rainfall resolution than maximum in-sewer water depths as flow routing has a damping effect on in-sewer water level variations. Temporal resolution aggregation of rainfall inputs led to increase in de-correlation lengths and resulted in time shift in modelled flow peaks by several minutes. Sensitivity to temporal resolution of rainfall inputs was low compared to spatial resolution, for the storms analysed in this study