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Transitioning urban drainage systems to serve water-smart societies requires the involvement of different disciplines and stakeholders. However, stakeholders have different visions and needs from the transitioning process (e.g in terms of financing, policy adaptation and system management) these also vary between regions and countries. Identifying such different needs for stakeholders is necessary to propose practical adaptation strategies. Therefore, evidence of needs as reflected in policy papers and legislation in seven European countries was collected. Knowledgeable individuals in the urban drainage community were asked about their visions. Results show that whilst there is consensus on the challenges, visions on how to transition are diverse, indicating that more interaction between the different stakeholder groups is required to develop consensus. Additionally, organisational and legislative structures often slow down the necessary change processes. [ABSTRACT FROM AUTHOR]

Abstract Vortices are a very common phenomenon to consider in many hydraulic engineering problems, e.g. when designing pump sumps or intake works for turbines. Until now, the focus is on avoiding the development of vortices because of induction of cavitation and air entrainment by a fully developed air core. However, vortices may also be used in a more positive manner e.g. by taking advantage of the capacity to transport (floating) particles to avoid the built up of scum layers in wastewater pump sumps. To the authors' knowledge only little literature is available in this specific field of research. In order to obtain state-of-the art data on the dynamics of large particles in a free-surface vortex flow field and to examine the vortex transport capacity, a simple but novel 3D-PTV (Particle Tracking Velocimetry) method using 6 iPhones was designed, built, tested and employed to measure the 3D-motion of a large particle in the vortex flow. The experimental set-up, particle detection method and the post-processing of the raw data are described in detail along with some first experimental results. The presented 3D-PTV method showed to be able to obtain data that can be used for detailed analysis of the dynamics of large particles in the vortex flow. The overall standard uncertainty of the particle centre position is in the order of magnitude of 0.1 mm in each direction in a volume of a diameter of 0.6 m and a height of about 1 m, while recording at 240 fps. Highlights • The experimental set-up is built from 'of the shelf components'. • The behaviour of relatively large particles (relative to the vortex core diameter) is monitored. • The experimental set-up is described in great detail. [ABSTRACT FROM AUTHOR]

This work presents a method to emulate the flow dynamics of physically based hydrodynamic simulators under variations of time-dependent rainfall and parametric scenarios. Although surrogate modelling is often employed to deal with the computational burden of this type of simulators, common techniques used for model emulation as polynomial expansions or Gaussian processes cannot deal with large parameter space dimensionality. This restricts their applicability to a reduced number of static parameters under a fixed rainfall process. The technique presented combines the use of a modified Unit Hydrograph (UH) scheme and a polynomial chaos expansion (PCE) to emulate flow from physically based hydrodynamic models. The novel element of the proposed methodology is that the emulator compensates for the errors induced by the assumptions of proportionality and superposition of the UH theory when dealing with non-linear model structures, whereas it approximates properly the behaviour of a physically based simulator to new (spatially-uniform) rainfall time-series and parametric scenarios. The computational time is significantly reduced, which makes the practical use of the model feasible (e.g. real time control, flood warning schemes, hydraulic structures design, parametric inference etc.). The applicability of this methodology is demonstrated in three case studies, through the emulation of a simplified non-linear tank-in-series routing structure and of the 2D Shallow Water Equations (2D-SWE) solution (FLOW-R2D) in two computational domains. Results indicate that the proposed emulator can approximate with a high degree of accuracy the behaviour of the original models under a wide range of rainfall inputs and parametric values. [ABSTRACT FROM AUTHOR]

A methodology is presented which can be used in the evaluation of parametric uncertainty in urban flooding simulation. Due to the fact that such simulations are time consuming, the following methodology is proposed: (a) simplification of the description of the physical process; (b) derivation of a training data set; (c) development of a data-driven surrogate model; (d) use of a forward uncertainty propagation scheme. The simplification comprises the following steps: (a) unit hydrograph derivation using a 2D hydrodynamic model; (b) calculation of the losses in order to determine the effective rainfall depth; (c) flood event simulation using the principle of the proportionality and superposition. The above methodology was implemented in an urban catchment located in the city of Athens, Greece. The model used for the first step of the simplification was FLOW-R2D, whereas the well-known SWMM software (US Environmental Protection Agency, Washington, DC, USA) was used for the second step of the simplification. For the training data set derivation, an ensemble of 100 Unit Hydrographs was derived with the FLOW-R2D model. The parameters which were modified in order to produce this ensemble were the Manning coefficients in the two friction zones (residential and urban open space areas). The surrogate model used to replicate the unit hydrograph derivation, using the Manning coefficients as an input, was based on the Polynomial Chaos Expansion technique. It was found that, although the uncertainties in the derived results have to be taken into account, the proposed methodology can be a fast and efficient way to cope with dynamic flood simulation in an urban catchment. [ABSTRACT FROM AUTHOR]

Integrated Catchment Modelling aims to simulate jointly urban drainage systems, wastewater treatment plant and rivers. The effect of rainfall input uncertainties in the modelling of individual urban drainage systems has been discussed in several studies already. However, this influence changes when simultaneously simulating several urban drainage subsystems and their impact on receiving water quality. This study investigates the effect of the characteristics of rainfall inputs on a large-scale integrated catchment simulator for dissolved oxygen predictions in the River Dommel (The Netherlands). Rainfall products were generated with varying time-aggregation (10, 30 and 60 min) deriving from different sources of data with increasing spatial information: (1) Homogeneous rainfall from a single rain gauge; (2) block kriging from 13 rain gauges; (3) averaged C-Band radar estimation and (4) kriging with external drift combining radar and rain gauge data with change of spatial support. The influence of the different rainfall inputs was observed at combined sewer overflows (CSO) and dissolved oxygen (DO) dynamics in the river. Comparison of the simulations with river monitoring data showed a low sensitivity to temporal aggregation of rainfall inputs and a relevant impact of the spatial scale with a link to the storm characteristics to CSO and DO concentration in the receiving water. [ABSTRACT FROM AUTHOR]

In recent years, satellite imagery has shown its potential to support the sustainable management of land, water, and natural resources. In particular, it can provide key information about the properties and behavior of sandy beaches and the surrounding vegetation, improving the ecomorphological understanding and modeling of coastal dynamics. Although satellite image processing usually demands high memory and computational resources, free online platforms such as Google Earth Engine (GEE) have recently enabled their users to leverage cloud-based tools and handle big satellite data. In this technical note, we describe an algorithm to classify the coastal land cover and retrieve relevant information from Sentinel-2 and Landsat image collections at specific times or in a multitemporal way: the extent of the beach and vegetation strips, the statistics of the grass cover, and the position of the shoreline and the vegetation–sand interface. Furthermore, we validate the algorithm through both quantitative and qualitative methods, demonstrating the goodness of the derived classification (accuracy of approximately 90%) and showing some examples about the use of the algorithm's output to study coastal physical and ecological dynamics. Finally, we discuss the algorithm's limitations and potentialities in light of its scaling for global analyses. [ABSTRACT FROM AUTHOR]

The description of intertwined ecological processes in surface waters requires a holistic approach that accounts for spatially distributed hydrological/water quality processes. This study describes a new approach to model dissolved oxygen (DO) based on linked hydrodynamic and closed nutrient cycle ecological models. Long term datasets from the River Dommel (Netherlands) are used to determine: 1) if this methodology is suitable for modelling DO concentrations, 2) the model sensitivity to various levels of nutrients input, and 3) the DO production and consumption processes and their response to nutrient input changes. Results show that seasonal dynamics of DO are well quantified at long timescales; the sensitivity of DO to different pollutant sources exhibits significant seasonal variation and the largest influences on DO are aeration and mineralization of organic material. The approach demonstrates an ability to consider the impacts of nutrient input and long term vegetation maintenance on ecological quality. • Seasonal dynamics of dissolved oxygen are well quantified at long timescales using a combined hydrodynamic-ecological model. • The sensitivity of DO to rural and urban inputs exhibits seasonal variation. DO levels are influenced by rural runoff mainly during the winter. • The largest influences over DO predictions for the Dommel River are aeration and mineralization of organic material. • There is a continuous influence from Combined Sewer Overflows on river vegetation production, respiration and NO3 uptake. • Mowing has acute effects on vegetation. Wastewater discharge has an intermittent effect on mineralization after precipitation. [ABSTRACT FROM AUTHOR]