Modelling transitions in urban water systems.

Long term planning of urban water infrastructure requires acknowledgement that transitions in the water system are driven by changes in the urban environment, as well as societal dynamics. Inherent to the complexity of these underlying processes is that the dynamics of a system's evolution cannot be explained by linear cause-effect relationships and cannot be predicted under narrow sets of assumptions. Planning therefore needs to consider the functional behaviour and performance of integrated flexible infrastructure systems under a wide range of future conditions. This paper presents the first step towards a new generation of integrated planning tools that take such an exploratory planning approach. The spatially explicit model, denoted DAnCE4Water, integrates urban development patterns, water infrastructure changes and the dynamics of socio-institutional changes. While the individual components of the DAnCE4Water model (i.e. modules for simulation of urban development, societal dynamics and evolution/performance of water infrastructure) have been developed elsewhere, this paper presents their integration into a single model. We explain the modelling framework of DAnCE4Water, its potential utility and its software implementation. The integrated model is validated for the case study of an urban catchment located in Melbourne, Australia.

The application of a Web-geographic information system for improving urban water cycle modelling.

Research in urban water management has experienced a transition from traditional model applications to modelling water cycles as an integrated part of urban areas. This includes the interlinking of models of many research areas (e.g. urban development, socio-economy, urban water management). The integration and simulation is realized in newly developed frameworks (e.g. DynaMind and OpenMI) and often assumes a high knowledge in programming. This work presents a Web based urban water management modelling platform which simplifies the setup and usage of complex integrated models. The platform is demonstrated with a small application example on a case study within the Alpine region. The used model is a DynaMind model benchmarking the impact of newly connected catchments on the flooding behaviour of an existing combined sewer system. As a result the workflow of the user within a Web browser is demonstrated and benchmark results are shown. The presented platform hides implementation specific aspects behind Web services based technologies such that the user can focus on his main aim, which is urban water management modelling and benchmarking. Moreover, this platform offers a centralized data management, automatic software updates and access to high performance computers accessible with desktop computers and mobile devices.

Estimating inflow to a combined sewer overflow structure with storage tank in real time: evaluation of different approaches.

The performance assessment of storage tanks and combined sewer overflow (CSO) structures in sewer systems requires knowledge of the total inflow from the catchment during rainfall events. Many structures are, however, only equipped with sensors to measure water level and/or outflows. Based on the geometry of the tank, expressed as a level-storage relationship, inflow can be calculated from these data using a simple conceptual storage model. This paper compares a deterministic and a Bayesian approach for estimating the inflow to a CSO structure from measurements of outflows and water level. The Bayesian approach clearly outperforms the deterministic estimation which is very sensitive to measurement errors. Although computationally more demanding, the use of a simple linear storage model allows the online application of the Bayesian approach to repeatedly estimate inflow in short time intervals of a few minutes. The method could thus be used as an online software sensor for inflow to storage structures in sewer systems.

Identifiability analysis in conceptual sewer modelling.

For a sufficient calibration of an environmental model not only parameter sensitivity but also parameter identifiability is an important issue. In identifiability analysis it is possible to analyse whether changes in one parameter can be compensated by appropriate changes of the other ones within a given uncertainty range. Parameter identifiability is conditional to the information content of the calibration data and consequently conditional to a certain measurement layout (i.e. types of measurements, number and location of measurement sites, temporal resolution of measurements etc.). Hence the influence of number and location of measurement sites on the number of identifiable parameters can be investigated. In the present study identifiability analysis is applied to a conceptual model of a combined sewer system aiming to predict the combined sewer overflow emissions. Different measurement layouts are tested and it can be shown that only 13 of the most sensitive catchment areas (represented by the model parameter 'effective impervious area') can be identified when overflow measurements of the 20 highest overflows and the runoff to the waste water treatment plant are used for calibration. The main advantage of this method is very low computational costs as the number of required model runs equals the total number of model parameters. Hence, this method is a valuable tool when analysing large models with a long runtime and many parameters.

Influence of characteristics on combined sewer performance.

Elements of combined sewer systems are among others sub-catchments, junctions, conduits and weirs with or without storage units. The spatial distribution and attributes of all these elements influence both system characteristics and sewer performance. Until today, little work has been done to analyse the influence of such characteristics in a case unspecific approach. In this study, 250 virtual combined sewer systems are analysed by defining groups of systems, which are representative for their different characteristics. The set was created with a further development of the case study generator (CSG), a tool for automatic generation of branched sewer systems. Combined sewer overflow and flooding is evaluated using performance indicators based on hydrodynamic simulations. The analysis of system characteristics, like those presented in this paper, helps researchers to understand coherences and aids practitioners in designing combined sewers. For instance, it was found that characteristics that have a positive influence on emission reduction frequently have a negative influence on flooding avoidance and vice versa.

GIS-based applications of sensitivity analysis for sewer models.

Sensitivity analysis (SA) evaluates the impact of changes in model parameters on model predictions. Such an analysis is commonly used when developing or applying environmental models to improve the understanding of underlying system behaviours and the impact and interactions of model parameters. The novelty of this paper is a geo-referenced visualization of sensitivity indices for model parameters in a combined sewer model using geographic information system (GIS) software. The result is a collection of maps for each analysis, where sensitivity indices (calculated for model parameters of interest) are illustrated according to a predefined symbology. In this paper, four types of maps (an uncertainty map, calibration map, vulnerability map, and design map) are created for an example case study. This article highlights the advantages and limitations of GIS-based SA of sewer models. The conclusion shows that for all analyzed applications, GIS-based SA is useful for analyzing, discussing and interpreting the model parameter sensitivity and its spatial dimension. The method can lead to a comprehensive view of the sewer system.

Stormwater quality models: performance and sensitivity analysis.

The complex nature of pollutant accumulation and washoff, along with high temporal and spatial variations, pose challenges for the development and establishment of accurate and reliable models of the pollution generation process in urban environments. Therefore, the search for reliable stormwater quality models remains an important area of research. Model calibration and sensitivity analysis of such models are essential in order to evaluate model performance; it is very unlikely that non-calibrated models will lead to reasonable results. This paper reports on the testing of three models which aim to represent pollutant generation from urban catchments. Assessment of the models was undertaken using a simplified Monte Carlo Markov Chain (MCMC) method. Results are presented in terms of performance, sensitivity to the parameters and correlation between these parameters. In general, it was suggested that the tested models poorly represent reality and result in a high level of uncertainty. The conclusions provide useful information for the improvement of existing models and insights for the development of new model formulations.

Identifying weak points of urban drainage systems by means of VulNetUD.

This article presents the development and application of the software tool VulNetUD. VulNetUD is a tool for GIS-based identification of vulnerable sites of urban drainage systems (UDS) using hydrodynamic simulations undertaken using EPA SWMM. The benefit of the tool is the output of different vulnerability maps rating sewer surcharging, sewer flooding, combined sewer overflow (CSO) efficiency and CSO emissions. For this, seven predefined performance indicators are used to evaluate urban drainage systems under abnormal, critical and future conditions. The application on a case study highlights the capability of the tool to identify weak points of the urban drainage systems. Thereby it is possible to identify urban drainage system components which cause the highest performance decrease across the entire system. The application of the method on a real world case study shows for instance that a reduction of catchment areas which are located upstream of CSOs with relatively less capacity in the downstream sewers achieves the highest increases efficiency of the system. Finally, the application of VulNetUD is seen as a valuable tool for managers and operators of waste water utilities to improve the efficiency of their systems. Additionally vulnerability maps generated by VulNetUD support risk management e.g. decision making in urban development planning or the development of rehabilitation strategies.

Impact of input data uncertainties on urban stormwater model parameters.

The use of urban drainage models requires careful calibration, where model parameters are selected in order to minimize the difference between measured and simulated results. It has been recognized that often more than one set of calibration parameters can achieve similar model accuracy. A probability distribution of model parameters should therefore be constructed to examine the model's sensitivity to its parameters. With increasing complexity of models, it also becomes important to analyze the model parameter sensitivity while taking into account uncertainties in input and calibration data. In this study a Bayesian approach was used to develop a framework for quantification of impacts of uncertainties in the model inputs on the parameters of a simple integrated stormwater model for calculating runoff, total suspended solids and total nitrogen loads. The framework was applied to two catchments in Australia. It was found that only systematic rainfall errors have a significant impact on flow model parameters. The most sensitive flow parameter was the effective impervious area, which can be calibrated to completely compensate for the input data uncertainties. The pollution model parameters were influenced by both systematic and random rainfall errors. Additionally an impact of circumstances (e.g. catchment type, data availability) has been recognized.

A case independent approach on the impact of climate change effects on combined sewer system performance.

Design and construction of urban drainage systems has to be done in a predictive way, as the average lifespan of such investments is several decades. The design engineer has to predict many influencing factors and scenarios for future development of a system (e.g. change in land use, population, water consumption and infiltration measures). Furthermore, climate change can cause increased rain intensities which leads to an additional impact on drainage systems. In this paper we compare the behaviour of different performance indicators of combined sewer systems when taking into account long-term environmental change effects (change in rainfall characteristics, change in impervious area and change in dry weather flow). By using 250 virtual case studies this approach is--in principle--a Monte Carlo Simulation in which not only parameter values are varied but the entire system structure and layout is changed in each run. Hence, results are more general and case-independent. For example the consideration of an increase of rainfall intensities by 20% has the same effect as an increase of impervious area of +40%. Such an increase of rainfall intensities could be compensated by infiltration measures in current systems which lead to a reduction of impervious area by 30%.

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.