Performance of membrane bioreactor (MBR) systems for the treatment of shipboard slops: Assessment of hydrocarbon biodegradation and biomass activity under salinity variation.

In order to prevent hydrocarbon discharge at sea from ships, the International Maritime Organization (IMO) enacted the MARPOL 73/78 convention in which any oil and oil residue discharged in wastewater streams must contain less than 5 ppm hydrocarbons. Effective treatment of this petroleum-contaminated water is essential prior to its release into the environment, in order to prevent pollution problem for marine ecosystems as well as for human health. Therefore, two bench scale membrane bioreactors (MBRs) were investigated for hydrocarbon biodegradation. The two plants were initially fed with synthetic wastewater characterised by an increasing salinity, in order to enhance biomass acclimation to salinity. Subsequently, they were fed with a mixture of synthetic wastewater and real shipboard slops (with an increasing slops percentage up to 50% by volume). The results indicated a satisfactory biomass acclimation level in both plants with regards to salinity, providing significant removal efficiencies. The real slops exerted an inhibitory effect on the biomass, partially due to hydrocarbons as well as to other concomitant influences from other compounds contained in the real slops difficult to evaluate a priori. Nevertheless, a slight adaptation of the biomass to the new conditions was observed, with increasing removal efficiencies, despite the significant slops percentage.

Impact of rainfall data resolution in time and space on the urban flooding evaluation.

Climate change and modification of the urban environment increase the frequency and the negative effects of flooding, increasing the interest of researchers and practitioners in this topic. Usually, flood frequency analysis in urban areas is indirectly carried out by adopting advanced hydraulic models to simulate long historical rainfall series or design storms. However, their results are affected by a level of uncertainty which has been extensively investigated in recent years. A major source of uncertainty inherent to hydraulic model results is linked to the imperfect knowledge of the rainfall input data both in time and space. Several studies show that hydrological modelling in urban areas requires rainfall data with fine resolution in time and space. The present paper analyses the effect of rainfall knowledge on urban flood modelling results. A mathematical model of urban flooding propagation was applied to a real case study and the maximum efficiency conditions for the model and the uncertainty affecting the results were evaluated by means of generalised likelihood uncertainty estimation (GLUE) analysis. The added value provided by the adoption of finer temporal and spatial resolution of the rainfall was assessed.

Modelling of E. coli distribution in coastal areas subjected to combined sewer overflows.

Rivers, lakes and the sea were the natural receivers of raw urban waste and storm waters for a long time but the low sustainability of such practice, the increase of population and a renewed environmental sensibility increased researcher interest in the analysis and mitigation of the impact of urban waters on receiving water bodies (RWB). In Europe, the integrated modelling of drainage systems and RWB has been promoted as a promising approach for implementing the Water Framework Directive. A particular interest is given to the fate of pathogens and especially of Escherichia coli, in all the cases in which an interaction between population and the RWB is foreseen. The present paper aims to propose an integrated water quality model involving the analysis of several sewer systems (SS) discharging their polluting overflows on the coast in a sensitive marine environment. From a modelling point of view, the proposed application integrated one-dimensional drainage system models with a complex three-dimensional model analysing the propagation in space and time of E. coli in the coastal marine area. The integrated approach was tested in a real case study (the Acicastello bay in Italy) where data were available both for SS model and for RWB propagation model calibration. The analysis shows a good agreement between the model and monitored data. The integrated model was demonstrated to be a valuable tool for investigating the pollutant propagation and to highlight the most impacted areas.

Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling.

Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessment of the parameters of water models. This paper compares a number of these techniques: the Generalized Likelihood Uncertainty Estimation (GLUE), the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multi-objective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper provides the specific advantages and disadvantages of each method. In relation to computational efficiency (i.e. number of iterations required to generate the probability distribution of parameters), it was found that SCEM-UA and AMALGAM produce results quicker than GLUE in terms of required number of simulations. However, GLUE requires the lowest modelling skills and is easy to implement. All non-Bayesian methods have problems with the way they accept behavioural parameter sets, e.g. GLUE, SCEM-UA and AMALGAM have subjective acceptance thresholds, while MICA has usually problem with its hypothesis on normality of residuals. It is concluded that modellers should select the method which is most suitable for the system they are modelling (e.g. complexity of the model's structure including the number of parameters), their skill/knowledge level, the available information, and the purpose of their study.

Assessment of data and parameter uncertainties in integrated water-quality model.

In integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones depending on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which simulation output from upstream models is transferred to the downstream ones as input. The overall uncertainty can differ from the simple sum of uncertainties generated in each sub-model, depending on well-known uncertainty accumulation problems. The present paper aims to study the uncertainty propagation throughout an integrated urban water-quality model. At this scope, a parsimonious bespoke integrated model has been used allowing analysis of the combinative effect between different sub-models. Particularly, the data and parameter uncertainty have been assessed and compared by means of the variance decomposition concept. The integrated model and the methodology for the uncertainty decomposition have been applied to a complex integrated catchment: the Nocella basin (Italy). The results show that uncertainty contribution due to the model structure is higher with respect to the other sources of uncertainty.

Assessment of the integrated urban water quality model complexity through identifiability analysis.

Urban sources of water pollution have often been cited as the primary cause of poor water quality in receiving water bodies (RWB), and recently many studies have been conducted to investigate both continuous sources, such as wastewater-treatment plant (WWTP) effluents, and intermittent sources, such as combined sewer overflows (CSOs). An urban drainage system must be considered jointly, i.e., by means of an integrated approach. However, although the benefits of an integrated approach have been widely demonstrated, several aspects have prevented its wide application, such as the scarcity of field data for not only the input and output variables but also parameters that govern intermediate stages of the system, which are useful for robust calibration. These factors, along with the high complexity level of the currently adopted approaches, introduce uncertainties in the modelling process that are not always identifiable. In this study, the identifiability analysis was applied to a complex integrated catchment: the Nocella basin (Italy). This system is characterised by two main urban areas served by two WWTPs and has a small river as the RWB. The system was simulated by employing an integrated model developed in previous studies. The main goal of the study was to assess the right number of parameters that can be estimated on the basis of data-source availability. A preliminary sensitivity analysis was undertaken to reduce the model parameters to the most sensitive ones. Subsequently, the identifiability analysis was carried out by progressively considering new data sources and assessing the added value provided by each of them. In the process, several identifiability methods were compared and some new techniques were proposed for reducing subjectivity of the analysis. The study showed the potential of the identifiability analysis for selecting the most relevant parameters in the model, thus allowing for model simplification, and in assessing the impact of data sources for model reliability, thus guiding the analyst in the design of future monitoring campaigns. Further, the analysis showed some critical points in integrated urban drainage modelling, such as the interaction between water quality processes on the catchment and in the sewer, that can prevent the identifiability of some of the related parameters.

Ability of Preissmann slot scheme to simulate smooth pressurisation transient in sewers.

Urban drainage networks are generally designed to operate in a free-surface flow condition. However, as a consequence of heavy rainfall events or network malfunctions, the filling of sewers (pressurisation) and network overflow may occur. Several modelling software products are commonly used to simulate floods in drainage networks, and their results are usually thought to be reliable and robust. However, no specific studies have been carried out on the behaviour of these modelling products during the pressurisation transition. Mathematical models often use the Preissmann slot concept to handle pressurisation. In this paper, on the basis of laboratory pipe tests, the reliability of such a scheme is studied by means of a popular and open-source software product: SWMM (Storm Water Management Model). Many numerical tests were carried out with SWMM, varying the spatial and time steps and the Preissmann slot width, in order to examine the performance of the modelling software over intervals of these parameters even wider than what is usual in practical applications. The comparison between simulated and experimental surges allows one to draw interesting conclusions regarding the effectiveness of software products analogous to SWMM in simulating pressurisation, as well as the choice of the parameters themselves.

The influence of rainfall time resolution for urban water quality modelling.

The objective of this paper is the definition of a methodology to evaluate the impact of the temporal resolution of rainfall measurements in urban drainage modelling applications. More specifically the effect of the temporal resolution on urban water quality modelling is detected analysing the uncertainty of the response of rainfall-runoff modelling. Analyses have been carried out using historical rainfall-discharge data collected for the Fossolo catchment (Bologna, Italy). According to the methodology, the historical rainfall data are taken as a reference, and resampled data have been obtained through a rescaling procedure with variable temporal windows. The shape comparison between 'true' and rescaled rainfall data has been carried out using a non-dimensional accuracy index. Monte Carlo simulations have been carried out applying a parsimonious urban water quality model, using the recorded data and the resampled events. The results of the simulations were used to derive the cumulative probabilities of quantity and quality model outputs (peak discharges, flow volume, peak concentrations and pollutant mass) conditioned on the observation according to the GLUE (Generalized Likelihood Uncertainty Estimation) methodology. The results showed that when coarser rainfall information is available, the model calibration process is still efficient even if modelling uncertainty progressively increases especially with regards to water quality aspects.

Emission standards versus immission standards for assessing the impact of urban drainage on ephemeral receiving water bodies.

In the past, emission standard indicators have been adopted by environmental regulation authorities in order to preserve the quality of a receiving water body. Such indicators are based on the frequency or magnitude of a polluted discharge that may be continuous or intermittent. In order to properly maintain the quality of receiving waters, the Water Framework Directive, following the basic ideas of British Urban Pollution Manual, has been established. The Directive has overtaken the emission-standard concept, substituting it with the stream-standard concept that fixes discharge limits for each polluting substance depending on the self-depurative characteristics of receiving waters. Stream-standard assessment requires the deployment of measurement campaigns that can be very expensive; furthermore, the measurement campaigns are usually not able to provide a link between the receiving water quality and the polluting sources. Therefore, it would be very useful to find a correlation between the quality status of the natural waters and the emission-based indicators. Thus, this study is aimed to finding a possible connection between the receiving water quality indicators drawn by environmental regulation authorities and emission-based indicators while considering both continuous (i.e. from the wastewater treatment plants) and intermittent pollution discharges (mainly from combined sewer overflows). Such research has been carried out by means of long-term analysis adopting a holistic modelling approach. The different parts of the integrated urban drainage system were modelled by a parsimonious integrated model. The analysis was applied to an ephemeral river bounding Bologna (Italy). The study concluded that the correlation between receiving water quality and polluting emissions cannot be generally stated. Nevertheless, specific analyses on polluting emissions were pointed out in the study highlighting cause-effect link between polluting sources and receiving water quality.

Urban water quality modelling: a parsimonious holistic approach for a complex real case study.

In the past three decades, scientific research has focused on the preservation of water resources, and in particular, on the polluting impact of urban areas on natural water bodies. One approach to this research has involved the development of tools to describe the phenomena that take place on the urban catchment during both wet and dry periods. Research has demonstrated the importance of the integrated analysis of all the transformation phases that characterise the delivery and treatment of urban water pollutants from source to outfall. With this aim, numerous integrated urban drainage models have been developed to analyse the fate of pollution from urban catchments to the final receiving waters, simulating several physical and chemical processes. Such modelling approaches require calibration, and for this reason, researchers have tried to address two opposing needs: the need for reliable representation of complex systems, and the need to employ parsimonious approaches to cope with the usually insufficient, especially for urban sources, water quality data. The present paper discusses the application of a be-spoke model to a complex integrated catchment: the Nocella basin (Italy). This system is characterised by two main urban areas served by two wastewater treatment plants, and has a small river as the receiving water body. The paper describes the monitoring approach that was used for model calibration, presents some interesting considerations about the monitoring needs for integrated modelling applications, and provides initial results useful for identifying the most relevant polluting sources.

Uncertainty in urban stormwater quality modelling: the influence of likelihood measure formulation in the GLUE methodology.

In the last years, the attention on integrated analysis of sewer networks, wastewater treatment plants and receiving waters has been growing. However, the common lack of data in the urban water-quality field and the incomplete knowledge regarding the interpretation of the main phenomena taking part in integrated urban water systems draw attention to the necessity of evaluating the reliability of model results. Uncertainty analysis can provide useful hints and information regarding the best model approach to be used by assessing its degrees of significance and reliability. Few studies deal with uncertainty assessment in the integrated urban-drainage field. In order to fill this gap, there has been a general trend towards transferring the knowledge and the methodologies from other fields. In this respect, the Generalised Likelihood Uncertainty Evaluation (GLUE) methodology, which is widely applied in the field of hydrology, can be a possible candidate for providing a solution to the above problem. However, the methodology relies on several user-defined hypotheses in the selection of a specific formulation of the likelihood measure. This paper presents a survey aimed at evaluating the influence of the likelihood measure formulation in the assessment of uncertainty in integrated urban-drainage modelling. To accomplish this objective, a home-made integrated urban-drainage model was applied to the Savena case study (Bologna, IT). In particular, the integrated urban-drainage model uncertainty was evaluated employing different likelihood measures. The results demonstrate that the subjective selection of the likelihood measure greatly affects the GLUE uncertainty analysis.

Stormwater infiltration trenches: a conceptual modelling approach.

In recent years, limitations linked to traditional urban drainage schemes have been pointed out and new approaches are developing introducing more natural methods for retaining and/or disposing of stormwater. These mitigation measures are generally called Best Management Practices or Sustainable Urban Drainage System and they include practices such as infiltration and storage tanks in order to reduce the peak flow and retain part of the polluting components. The introduction of such practices in urban drainage systems entails an upgrade of existing modelling frameworks in order to evaluate their efficiency in mitigating the impact of urban drainage systems on receiving water bodies. While storage tank modelling approaches are quite well documented in literature, some gaps are still present about infiltration facilities mainly dependent on the complexity of the involved physical processes. In this study, a simplified conceptual modelling approach for the simulation of the infiltration trenches is presented. The model enables to assess the performance of infiltration trenches. The main goal is to develop a model that can be employed for the assessment of the mitigation efficiency of infiltration trenches in an integrated urban drainage context. Particular care was given to the simulation of infiltration structures considering the performance reduction due to clogging phenomena. The proposed model has been compared with other simplified modelling approaches and with a physically based model adopted as benchmark. The model performed better compared to other approaches considering both unclogged facilities and the effect of clogging. On the basis of a long-term simulation of six years of rain data, the performance and the effectiveness of an infiltration trench measure are assessed. The study confirmed the important role played by the clogging phenomenon on such infiltration structures.

Quantification of diffuse and concentrated pollutant loads at the watershed-scale: an Italian case study.

In this study, diffuse and point source pollutant loads were evaluated using an Italian case study: the Nocella catchment, which has been subject to extensive monitoring. The Nocella catchment is located in Sicily (Italy) and has an area of about 60 km(2). The river receives wastewater and stormwater from two urban areas drained by combined sewers. The two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. Thereafter, an integrated catchment-scale model was applied to simulate point pollutant sources, i.e., pollution coming from the urban drainage system, and nonpoint pollutant sources, i.e., pollution coming from agricultural and wildlife activities. Different models were combined and long-term simulations were carried out in order to reconstruct the total pollutant loads discharged into the receiving water body and identify the roles of the different pollutant sources. This study demonstrates the complexity of water quality assessment in partially urbanised natural basins where neither point nor nonpoint sources can be neglected. Point sources are mainly responsible for acute oxygen demanding polluting impact during wet weather periods, and both point and nonpoint sources are responsible for the impact of nutrients on the receiving water body.

Uncertainty in urban stormwater quality modelling: the effect of acceptability threshold in the GLUE methodology.

Uncertainty analysis in integrated urban drainage modelling is of growing importance in the field of water quality. However, only few studies deal with uncertainty quantification in urban drainage modelling; furthermore, the few existing studies mainly focus on quantitative sewer flow modelling rather than uncertainty in water quality aspects. In this context, the generalised likelihood uncertainty estimation (GLUE) methodology was applied for the evaluation of the uncertainty of an integrated urban drainage model and some of its subjective hypotheses have been explored. More specifically, the influence of the subjective choice of the acceptability threshold has been detected in order to gain insights regarding its effect on the model results. The model has been applied to the Savena case study (Bologna, Italy) where water quality and quantity data were available. The model results show a strong influence of the acceptability threshold selection and confirm the importance of modeller's experience in the application of GLUE uncertainty analysis.