S. Fach

A multi-layer cellular automata approach for algorithmic generation of virtual case studies: VIBe

Analyses of case studies are used to evaluate new or existing technologies, measures or strategies with regard to their impact on the overall process. However, data availability is limited and hence, new technologies, measures or strategies can only be tested on a limited number of case studies. Owing to the specific boundary conditions and system properties of each single case study, results can hardly be generalized or transferred to other boundary conditions. virtual infrastructure benchmarking (VIBe) is a software tool which algorithmically generates virtual case studies (VCSs) for urban water systems. System descriptions needed for evaluation are extracted from VIBe whose parameters are based on real world case studies and literature. As a result VIBe writes Input files for water simulation software as EPANET and EPA SWMM. With such input files numerous simulations can be performed and the results can be benchmarked and analysed stochastically at a city scale. In this work the approach of VIBe is applied with parameters according to a section of the Inn valley and therewith 1,000 VCSs are generated and evaluated. A comparison of the VCSs with data of real world case studies shows that the real world case studies fit within the parameter ranges of the VCSs. Consequently, VIBe tackles the problem of limited availability of case study data.

Nowcasting of rainfall and of combined sewage flow in urban drainage systems

Nowcasting of rainfall may be used additionally to online rain measurements to optimize the operation of urban drainage systems. Uncertainties quoted for the rain volume are in the range of 5% to 10% mean square error (MSE), where for rain intensities 45% to 75% MSE are noted. For larger forecast periods up to 3 hours, the uncertainties will increase up to some hundred percents. Combined with the growing number of real time control concepts in sewer systems, rainfall forecast is used more and more in urban drainage systems. Therefore it is of interest how the uncertainties influence the final evaluation of a defined objective function. Uncertainty levels associated with the forecast itself are not necessarily transferable to resulting uncertainties in the catchments flow dynamics. The aim of this paper is to analyse forecasts of rainfall and specific sewer output variables. For this study the combined sewer system of the city of Linz in the northern part of Austria located on the Danube has been selected. The city itself represents a total area of 96 km2 with 39 municipalities connected. It was found that the available weather radar data leads to large deviations in the forecast for precipitation at forecast horizons larger than 90 minutes. The same is true for sewer variables such a CSO overflow for small sub-catchments. Although the results improve for larger spatial scales, acceptable levels at forecast horizons larger than 90 minutes are not reached.

Optimization of measurement campaigns for calibration of a conceptual sewer model

To simulate hydrological models of combined sewer systems an accurate calibration is indispensable. In addition to all sources of uncertainties in data collection due to the measurement methods itself, it is a key question which data has to be collected to calibrate a hydrological model, how long measurement campaigns should last and where that data has to be collected in a spatial distributed system as it is neither possible nor sensible to measure the complete system characteristics. In this paper we address this question by means of stochastic modelling. Using Monte Carlo Simulation different calibration strategies (selection of measurement sites, selection of rainfall-events) and different calibration parameters (overflow volume, number of overflows) are tested, in order to evaluate the influence on predicting the total overflow volume of the entire system. This methodology is applied in a case study with the aim to calculate the combined sewer overflow (CSO) efficiency. It can be shown that a distributed hydrological model can be calibrated sufficiently when calibration is done on 30% of all existing CSOs based on long-term observation. Event based calibration is limited possible to a limited extend when calibration events are selected carefully as wrong selection of calibration events can result in a complete failure of the calibration exercise.

Determining the spill flow discharge of combined sewer overflows using rating curves based on computational fluid dynamics instead of the standard weir equation

It is state of the art to evaluate and optimise sewer systems with urban drainage models. Since spill flow data is essential in the calibration process of conceptual models it is important to enhance the quality of such data. A wide spread approach is to calculate the spill flow volume by using standard weir equations together with measured water levels. However, these equations are only applicable to combined sewer overflow (CSO) structures, whose weir constructions correspond with the standard weir layout. The objective of this work is to outline an alternative approach to obtain spill flow discharge data based on measurements with a sonic depth finder. The idea is to determine the relation between water level and rate of spill flow by running a detailed 3D computational fluid dynamics (CFD) model. Two real world CSO structures have been chosen due to their complex structure, especially with respect to the weir construction. In a first step the simulation results were analysed to identify flow conditions for discrete steady states. It will be shown that the flow conditions in the CSO structure change after the spill flow pipe acts as a controlled outflow and therefore the spill flow discharge cannot be described with a standard weir equation. In a second step the CFD results will be used to derive rating curves which can be easily applied in everyday practice. Therefore the rating curves are developed on basis of the standard weir equation and the equation for orifice-type outlets. Because the intersection of both equations is not known, the coefficients of discharge are regressed from CFD simulation results. Furthermore, the regression of the CFD simulation results are compared with the one of the standard weir equation by using historic water levels and hydrographs generated with a hydrodynamic model. The uncertainties resulting of the wide spread use of the standard weir equation are demonstrated.

Parallel computing in conceptual sewer simulations

Integrated urban drainage modelling is used to analyze how existing urban drainage systems respond to particular conditions. Based on these integrated models, researchers and engineers are able to e.g. estimate long-term pollution effects, optimize the behaviour of a system by comparing impacts of different measures on the desired target value or get new insights on systems interactions. Although the use of simplified conceptual models reduces the computational time significantly, searching the enormous vector space that is given by comparing different measures or that the input parameters span, leads to the fact, that computational time is still a limiting factor. Owing to the stagnation of single thread performance in computers and the rising number of cores one needs to adapt algorithms to the parallel nature of the new CPUs to fully utilize the available computing power. In this work a new developed software tool named CD3 for parallel computing in integrated urban drainage systems is introduced. From three investigated parallel strategies two showed promising results and one results in a speedup of up to 4.2 on an eight-way hyperthreaded quad core CPU and shows even for all investigated sewer systems significant run-time reductions.

A software-based sensor for combined sewer overflows

A new methodology for online estimation of excess flow from combined sewer overflow (CSO) structures based on simulation models is presented. If sufficient flow and water level data from the sewer system is available, no rainfall data are needed to run the model. An inverse rainfall-runoff model was developed to simulate net rainfall based on flow and water level data. Excess flow at all CSO structures in a catchment can then be simulated with a rainfall-runoff model. The method is applied to a case study and results show that the inverse rainfall-runoff model can be used instead of missing rain gauges. Online operation is ensured by software providing an interface to the SCADA-system of the operator and controlling the model. A water quality model could be included to simulate also pollutant concentrations in the excess flow.

On-site infiltration of road runoff using pervious pavements with subjacent infiltration trenches as source control strategy

The focus in this work was on subsoil infiltration of stormwater from parking lots. With regard to operation, reduced infiltration performance due to clogging and pollutants in seepage, which may contribute to contaminate groundwater, are of interest. The experimental investigation covered a pervious pavement with a subjacent infiltration trench draining an impervious area of 2 ha. In order to consider seasonal effects on the infiltration performance, the hydraulic conductivity was measured tri-monthly during monitoring with a mobile sprinkling unit. To assess natural deposits jointing, road bed, gravel of infiltration trenches and subsoil were analysed prior to commencement of monitoring for heavy metals, polycyclic aromatic and mineral oil type hydrocarbons. Furthermore, from 22 storm events, water samples of rainfall, surface runoff, seepage and ground water were analysed with regard to the above mentioned pollutants. The study showed that the material used for the joints had a major impact on the initial as well as the final infiltration rates. Due to its poor hydraulic conductivity, limestone gravel should not be used as jointing. Furthermore, it is recommended that materials for the infiltration facilities are ensured free of any contaminants prior to construction. Polycyclic aromatic and mineral oil type hydrocarbons were, with the exception of surface runoff, below detection limits. Heavy metal concentrations of groundwater were with the exception of lead (because of high background concentrations), below the permissible limits.