International audienceUrban 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 100m and 1min resolutions, 15 different combinations of coarser spatial and temporal resolutions, up to 3000m and 10min, 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 8km2), 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. © 2015 The Authors

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The urban wastewater system (sewer and treatment plant) has a major impact on the river water quality of urban streams. To minimise this impact, real time control is a valuable option. Since the ultimate goal of any control strategy is to optimise the quality of the river system, it is useful to take pollutant immissions into account when determining the control strategy and/or the setpoints of the controller. However, a simultaneously simulating model of the complete system is needed in order to allow design and evaluation of such control strategies. In this work an integrated model of the urban wastewater system is created. This has been accomplished by implementing surrogate models of the three subsystems within a single software platform. The coupled submodels are subsequently used in a semi-hypothetical case study to optimise the resulting river water quality. An ammonia sensor in the river has been used to control the amount of water treated biologically in the treatment plant. It was shown that this integrated control could lower the peak ammonia concentration in the part of the river downstream of the treatment plant. Hence, a proof of principle has been given that the use of measurements in the river to perform control actions in the sewer system and the treatment plant is a promising option.

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 1.6 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 subcatchments 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.

Environmental regulators frequently stipulate the modeling approaches required for water utilities managing sewer networks to demonstrate regulatory compliance. The performance of drainage systems with regard to combined sewer overflow (CSO) discharges is required to be assessed using urban drainage models to prove compliance before large investments can be authorized. However, as far as the authors are aware, the modeling approaches to demonstrate regulatory compliance currently provide no opportunity for considering model uncertainty. This paper therefore addresses a knowledge gap in the role of model uncertainty in environmental compliance studies by describing an objective uncertainty quantification process that enables the water utilities to evaluate and report the uncertainty in their modeling predictions and that is also transparent enough to satisfy regulators. The sewer network was modeled in InfoWorks CS software using a design storm defined by the regulator to test the performance of CSOs. Uncertainty in the model and input parameters was propagated using Monte Carlo simulations with Latin hypercube sampling, and the results were presented to show the trade-off between the infrastructure investment and the risk of spilling.