Giorgio Mannina

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 models structure including the number of parameters), their skill/knowledge level, the available information, and the purpose of their study.

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 modellers experience in the application of GLUE uncertainty analysis.

Comparison between moving bed-membrane bioreactor (MB-MBR) and membrane bioreactor (MBR) systems: Influence of wastewater salinity variation

Two pilot plant systems were investigated for the treatment of wastewater subject to a gradual increase of salinity. In particular, a membrane bioreactor (MBR) and a moving bed biofilm membrane bioreactor (MB-MBR) were analyzed. Carbon and ammonium removal, kinetic constants and membranes fouling rates have been assessed. Both plants showed very high efficiency in terms of carbon and ammonium removal and the gradual salinity increase led to a good acclimation of the biomass, as confirmed by the respirometric tests. Significant biofilm detachments from carriers were experienced, which contributed to increase the irreversible superficial cake deposition. However, this aspect prevented the pore fouling tendency in the membrane module of MB-MBR system. On the contrary, the MBR pilot, even showing a lower irreversible cake deposition, was characterized by a higher pore fouling tendency.

Technical assessment and evaluation of environmental models and software

This letter details the collective views of a number of independent researchers on the technical assessment and evaluation of environmental models and software. The purpose is to stimulate debate and initiate action that leads to an improved quality of model development and evaluation, so increasing the capacity for models to have positive outcomes from their use. As such, we emphasize the relationship between the model evaluation process and credibility with stakeholders (including funding agencies) with a view to ensure continued support for modelling efforts.Many journals, including EM&S, publish the results of environmental modelling studies and must judge the work and the submitted papers based solely on the material that the authors have chosen to present and on how they present it. There is considerable variation in how this is done with the consequent risk of considerable variation in the quality and usefulness of the resulting publication. Part of the problem is that the review process is reactive, responding to the submitted manuscript. In this letter, we attempt to be proactive and give guidelines for researchers, authors and reviewers as to what constitutes best practice in presenting environmental modelling results. This is a unique contribution to the organisation and practice of model-based research and the communication of its results that will benefit the entire environmental modelling community. For a start, our view is that the community of environmental modellers should have a common vision of minimum standards that an environmental model must meet. A common vision of what a good model should be is expressed in various guidelines on Good Modelling Practice. The guidelines prompt modellers to codify their practice and to be more rigorous in their model testing. Our statement within this letter deals with another aspect of the issue - it prompts professional journals to codify the peer-review process. Introducing a more formalized approach to peer-review may discourage reviewers from accepting invitations to review given the additional time and labour requirements. The burden of proving model credibility is thus shifted to the authors. Here we discuss how to reduce this burden by selecting realistic evaluation criteria and conclude by advocating the use of standardized evaluation tools as this is a key issue that needs to be tackled.

Greenhouse gases from wastewater treatment - A review of modelling tools

Nitrous oxide, carbon dioxide and methane are greenhouse gases (GHG) emitted from wastewater treatment that contribute to its carbon footprint. As a result of the increasing awareness of GHG emissions from wastewater treatment plants (WWTPs), new modelling, design, and operational tools have been developed to address and reduce GHG emissions at the plant-wide scale and beyond. This paper reviews the state-of-the-art and the recently developed tools used to understand and manage GHG emissions from WWTPs, and discusses open problems and research gaps. The literature review reveals that knowledge on the processes related to N2O formation, especially due to autotrophic biomass, is still incomplete. The literature review shows also that a plant-wide modelling approach that includes GHG is the best option for the understanding how to reduce the carbon footprint of WWTPs. Indeed, several studies have confirmed that a wide vision of the WWPTs has to be considered in order to make them more sustainable as possible. Mechanistic dynamic models were demonstrated as the most comprehensive and reliable tools for GHG assessment. Very few plant-wide GHG modelling studies have been applied to real WWTPs due to the huge difficulties related to data availability and the model complexity. For further improvement in GHG plant-wide modelling and to favour its use at large real scale, knowledge of the mechanisms involved in GHG formation and release, and data acquisition must be enhanced.

Identifiability analysis for receiving water body quality modelling

In urban drainage, new computational possibilities have supported the development of new integrated approaches aimed at joint water quantity and quality analysis of the whole urban drainage system. Although the benefit of an integrated approach has been widely demonstrated, to date, several aspects prevent its applicability such as scarce availability of field data if compared with model complexity. These aspects sometimes prevent the correct estimation of parameters thus leading to large uncertainty in modelling response. This is a typical parameter identifiability problem that is discussed in the present paper evaluating the effect of identifiability procedures in increasing operator confidence in modelling results. The methodology presented has been applied to a home-made integrated urban drainage model that has been calibrated/validated considering field data collected in the Savena experimental catchment (Bologna, Italy). The results demonstrate the effectiveness of the identifiability analysis in obtaining a tool for urban integrated modelling applications and field data gathering campaigns.

The role of EPS in fouling and foaming phenomena for a membrane bioreactor

In contraposition to conventional activated sludge processes, the foaming phenomenon in membrane bioreactor (MBR) is still in its infancy. On the other hand, although several studies have been carried out for better understanding the fouling phenomenon in MBR there are still some gaps in the up-to-date knowledge. The extracellular polymeric substances (EPSs) may have a primary role in fouling and foaming phenomena which in turn can be crucial for MBRs. The aim of this study is to detect a possible relationship that EPSs may have with fouling and foaming in an MBR for wastewater treatment. Foaming phenomenon is monitored by performing specific foam-tests: Foam Power, Scum Index, Foam Rating and filamentous abundance. Results show a high correlation between fouling vs EPS and foaming vs bound EPSs. A relationship between foaming and fouling was also found: in general, when foaming occurred the fouling rate decreases because the EPS bound remained trapped in the floating scum.

Comparison between hybrid moving bed biofilm reactor and activated sludge system: a pilot plant experiment.

The paper presents the comparison between the traditional activated sludge system (AS) and a hybrid moving bed biofilm reactor (HMBBR). In particular, an experimental campaign has been carried out at the WWTP in Palermo (Italy), on a pilot plant consisting of two pre-anoxic schemes. The aerated tank of the HMBBR line was filled with suspended carriers (AnoxKaldnes K1), with a 30% filling ratio. The hydraulic load of the HMBBR line was increased up to two times the AS one. Further, in order to distinguish the additional contribution of the attached biomass for the HMBBR system, in the two lines the Mixed Liquor Suspended Solids (MLSS) was maintained as equal as possible. The monitoring period lasted three months during which several parameters were monitored. The obtained results showed a good treatment ability of the HMBBR system, referring to the organic matter removal as well as to the ammonium removal. In particular, in spite of the increase of the hydraulic load for the HMBBR line, the two systems showed a similar performance in terms of both organic and nitrogen removal. The results demonstrate the higher treatment capacity of the HMBBR addressing such system as an effective technology for the upgrading of overloaded wastewater treatment plants.

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.

Quantification of kinetic parameters for heterotrophic bacteria via respirometry in a hybrid reactor.

Over the last decade new technologies are emerging even more for wastewater treatment. Among the new technologies, a recent possible solution regards Moving Bed Biofilm Reactors (MBBRs) that represent an effective alternative to conventional processes. More specifically such systems consist in the introduction of plastic elements inside the aerobic reactor as carrier material for the growth of attached biomass. Recently, one of the mostly used alternatives is to couple the Moving Bed Biofilm Reactor (MBBR) process with the conventional activated sludge process, and the resulting process is usually called HMBBR (Hybrid MBBR). In the MBBR process the biofilm grows attached on small plastic elements that are kept in constant motion throughout the entire volume of the reactor. Indeed, in such a system, a competition between the two biomasses, suspended and attached, can arise for the availability of the substrates, leading, as a consequence, to a modification in the biokinetic parameters of the two biomasses, compared to that of a pure suspended or attached biomass process. This paper presents the first results of a study aimed at estimating the kinetic heterotrophic constants in a HMBBR pilot plant using respirometric techniques. The pilot plant was built at the Acqua dei Corsari (Palermo) wastewater treatment plant and consisted of two parallel lines realized in a pre-anoxic scheme, in one of which the carrier material was added to the aerobic reactor with a filling ratio of 30%.