Search

Monte Carlo (MC) simulation appears to be the only currently adopted tool to estimate global sensitivities and uncertainties in wastewater treatment modelling. Such models are highly complex, dynamic and non-linear, requiring long computation times, especially in the scope of MC simulation, due to the large number of simulations usually required. However, no stopping rule to decide on the number of simulations required to achieve a given confidence in the MC simulation results has been adopted so far in the field. In this work, a pragmatic method is proposed to minimize the computation time by using a combination of several criteria. It makes no use of prior knowledge about the model, is very simple, intuitive and can be automated: all convenient features in engineering applications. A case study is used to show an application of the method, and the results indicate that the required number of simulations strongly depends on the model output(s) selected, and on the type and desired accuracy of the analysis conducted. Hence, no prior indication is available regarding the necessary number of MC simulations, but the proposed method is capable of dealing with these variations and stopping the calculations after convergence is reached.

This paper illustrates how a dynamic model can be used to evaluate a plant upgrade on the basis of post-upgrade performance data. The case study is that of the Eindhoven wastewater treatment plant upgrade completed in 2006. As a first step, the design process based on a static model was thoroughly analyzed and the choices regarding variability and uncertainty (i.e. safety factors) were made explicit. This involved the interpretation of the design guidelines and other assumptions made by the engineers. As a second step, a (calibrated) dynamic model of the plant was set up, able to reproduce the anticipated variability (duration and frequency). The third step was to define probability density functions for the parameters assumed to be uncertain, and propagate that uncertainty with the dynamic model by means of Monte Carlo simulations. The last step was the statistical evaluation and interpretation of the simulation results. This work should be regarded as a 'learning exercise' increasing the understanding of how and to what extent variability and uncertainty are currently incorporated in design guidelines used in practice and how model-based post-project appraisals could be performed. [ABSTRACT FROM AUTHOR]

The main goal of the Water Framework Directive is to achieve good chemical and ecological status of water bodies by 2015. The implementation of integrated river basin management, including sewer systems, wastewater treatment plants and receiving water bodies, is essential to accomplishing this objective. Integrated management is complex and therefore the implementation of control systems and the development of decision support systems are needed to facilitate the work of urban wastewater system (UWS) managers. Within this context, the objective of this paper is to apply integrated modelling of an UWS to simulate and analyse the behaviour of the 'Congost' UWS in Spain, and to optimize its performance against different types of perturbations. This analysis results in optimal operating set-points for each perturbation, improves river water quality, minimizes combined sewer overflows and optimizes flow lamination from storm water tanks. This is achieved by running Monte Carlo simulations and applying global sensitivity analysis. The set-points will become part of the knowledge base composed of a set of IF-THEN rules of the environmental decision support system being developed for this case study. [ABSTRACT FROM AUTHOR]

The Besòs River Basin authority is working towards the implementation of integrated river basin management, as required by the Water Framework Directive (WFD), to achieve a good ecological and chemical status of all water bodies by 2015. The studied system is constituted by two communities (La Garriga and Granollers), their corresponding draining catchments, sewer systems and two WWTPs, which discharge treated water at different locations of the same river. Within this context, the realisation of an integrated model of the river stretch and of the two WWTPs with their sewer systems and draining catchments was necessary. Such a model allows to efficiently simulate and analyse the behaviour of the integrated system and to optimize its performance holistically. In this article, a method is presented to generate rules to be implemented in a supervisory system for automatic management of the Integrated Urban Wastewater System (IUWS) in dry and storm weather. This is achieved by identifying, with the help of Monte Carlo simulations, the most performing operational parameters-according to environmental and economic criteria-for the two weather conditions. [ABSTRACT FROM AUTHOR]

This paper presents a set of tools developed to support an innovative methodology to design and upgrade wastewater treatment systems in a probabilistic way. For the first step, data reconstruction, two different tools were developed, one for situations where data are available and another one where no data are available. The second step, modelling and simulation, implied the development of a new simulation platform and of distributed computation software to deal with the simulation load generated by the third step, uncertainty analysis, with Monte Carlo simulations of the system over one year, important dynamics and stiff behaviour. For the fourth step, evaluation of alternatives, the evaluator tool processes the results of the simulations and plots the relevant information regarding the robustness of the process against input and parameters uncertainties, as well as concentration–duration curves for the risk of non-compliance with effluent and receiving water quality limits. This paper illustrates the merits of these tools to make the innovative methodology of practical interest. The design practice should move from conventional procedures suited for the relatively fixed context of emission limits, to more advanced, transparent and cost-effective procedures appropriate to cope with the flexibility and complexity introduced by integrated water management approaches. [Copyright &y& Elsevier]