G. Bruni

Bio: G. Bruni is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Storm & Temporal resolution. The author has an hindex of 5, co-authored 11 publications receiving 274 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.

Fractal analysis of urban catchments and their representation in semi-distributed models : Imperviousness and sewer system

Abstract: Fractal analysis relies on scale invariance and the concept of fractal dimension enables one to characterize and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology In this paper, fractal tools are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in five European countries The aim was to characterize urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m × 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance The results showed that both sewer density and imperviousness exhibit scale-invariant features and can be characterized with the help of fractal dimensions ranging from 16 to 2, depending on the catchment In a given area consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds It enables one to quantify how well spatial structures of imperviousness were represented in the urban hydrological models

Weather radar for urban hydrological applications: Lessons learnt and research needs identified from 4 pilot catchments in North-West Europe

Abstract: This study investigates the impact of rainfall estimates of different spatial resolutions on the hydraulic outputs of the models of four of the EU RainGain project’s pilot locations (the Cranbrook catchment (UK), the Herent catchment (Belgium), the Moree-Sausset catchment (France) and the Kralingen District (The Netherlands)). Two storm events, one convective and one stratiform, measured by a polarimetric X-band radar located in Cabauw (The Netherlands) were selected for analysis. The original radar estimates, at 100 m and 1 min resolutions, were aggregated to a spatial resolution of 1000 m. These estimates were then applied to the high-resolution semi-distributed hydraulic models of the four urban catchments, all of which have similar size (between 5 and 8 km2), but different morphological, hydrological and hydraulic characteristics. When doing so, methodologies for standardising rainfall inputs and making results comparable were implemented. The response of the different catchments to rainfall inputs of varying spatial resolution is analysed in the light of model configuration, catchment and storm characteristics. Rather surprisingly, the results show that for the two events under consideration the spatial resolution (i.e. 100 m vs 1000 m) of rainfall inputs does not have a significant influence on the outputs of urban drainage models. The present study will soon be extended to more storms as well as model structures and resolutions, with the final aim of identifying critical spatial-temporal resolutions for urban catchment modelling in relation to catchment and storm event characteristics.

Toward the optimal resolution on rainfall estimates to obtain reliable urban hydrological response: X-band polarimetric radar estimates applied to Rotterdam urban drainage system

Abstract: Weather observations are conventionally performed by single polarization C-band weather radars with a temporal and spatial resolution of 5 min and 1 km, respectively. However, for urbanized areas, these spatial and temporal resolutions may not be sufficient to detect, monitor, and obtain accurate rainfall rate estimates of fastevolving weather phenomena. In this work, a S-band vertical profiler (TARA) and a X-band horizontal scanner polarimetric weather radars (IDRA) located in the Cabauw Experimental Site for Atmospheric Research (CESAR) observatory are used to characterize physical processes and obtain accurate rainfall rate estimates of severe thunderstorms at high temporal and spatial resolutions. A large convective front over Western Europe on January 03 2012 was observed by the C-band operational radar from The Royal Netherlands Meteorological Institute (KNMI in Dutch initials) and by both, IDRA and TARA. It is expected the new insights will be revealed based on the polarimetric and the high-resolution capabilities from both radars. Moreover, rainfall rate estimates obtained from IDRA are used to simulate rainfall at lower spatial resolutions to analyze the spatial rain variability over a simulated urban drainage system belonging to Rotterdam urban area.

The Future of Earth Observation in Hydrology.

Abstract: In just the past five years, the field of Earth observation has progressed beyond the offerings of conventional space agency based platforms to include a plethora of sensing opportunities afforded by CubeSats, Unmanned Aerial Vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically on the order of one billion dollars per satellite and with concept-to-launch timelines on the order of two decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturise sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist five years ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of the cost of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-meter resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen-scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the Internet of Things as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilise and exploit these new observing systems to enhance our understanding of the Earth and its linked processes.

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.