R. Reinoso

Bio: R. Reinoso is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Storm & Precipitation. The author has an hindex of 1, co-authored 1 publications receiving 70 citations.

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

Abstract: Cities are increasingly vulnerable to floods generated by intense rainfall, because of their high degree of imperviousness, implementation of infrastructures, and changes in precipitation patterns due to climate change. 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 this paper, a detailed study of the sensitivity of urban hydrological response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar for four rainstorms were used as input into a detailed hydrodynamic sewer model for an urban catchment in Rotterdam, the Netherlands. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm 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 catchment smearing effect for rainfall resolution approaching half the catchment size, i.e. for catchments sampling numbers greater than 0.5 averaged rainfall volumes decrease about 20%. Moreover, deviations in maximum water depths, form 10 to 30% depending on the storm, occur for rainfall resolution close to storm size, describing storm smearing effect due to rainfall coarsening. Model results also show the sensitivity of modelled runoff peaks and maximum water depths to the resolution of the runoff areas and sewer density respectively. Sensitivity to temporal resolution of rainfall input seems low compared to spatial resolution, for the storms analysed in this study. Findings are in agreement with previous studies on natural catchments, thus the sampling numbers seem to be promising as an approach to describe sensitivity of hydrological response to rainfall variability for intra-urban catchments and local convective storms. More storms and different urban catchments of varying characteristics need to be analysed in order to validate these findings.

Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

Abstract: 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.

The significance of spatial rainfall representation for flood runoff estimation: a numerical evaluation based on the Lee catchment, UK

Abstract: Summary In the context of flood management, this paper investigates the relationship between spatial rainfall and runoff production, based on 15 years of radar data, 16 raingauges and 12 flow stations from the 1400 km 2 Lee catchment, UK. Event-based, semi-distributed rainfall–runoff modelling is undertaken. Alternative rainfall estimators (radar data and raingauge networks of various density) are considered and their effects on simulated runoff evaluated as a function of rainfall type, catchment type and catchment scale. An index of spatial variability is defined, based on the difference between the reference rainfall (defined by the full raingauge network) and alternative rainfall estimators. A modified Nash–Sutcliffe efficiency criterion measures the performance of the simulated runoff with respect to reference simulated runoff. Results show a complex picture. The dominant effect is the spatial variability of the rainfall. No clear pattern emerges as a function of catchment scale, or response time, except that the impact of spatial variability is damped at the whole catchment scale. The sensitivity to spatial rainfall is enhanced on urbanised catchments.

Weather radar rainfall data in urban hydrology

Abstract: . Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.