Tools to support a model-based methodology for benefit/cost/risk analysis of wastewater treatment systems

This paper presents a set of tools developed to support an innovative four-step methodology to design and upgrade wastewater treatment systems. For the first step of data collection and data reconstruction, two different tools have been developed, one for situations where data are available (using data reconstruction methods) and another for situations where no data are (yet) available (based on a simple draining catchment model driven by actual local rain series). The second step, i.e. model building, implied the development of a new simulation platform and of grid software to deal with the considerable simulation load generated by the third step, i.e. uncertainty analysis, which involves Monte Carlo simulations of one year time series with important dynamics and stiff behaviour. For the fourth and last step, evaluation of alternatives, the IWA/COST624 benchmarking evaluation approach has been implemented and expanded. The evaluator processes the results of the Monte Carlo simulations and plots the relevant information on the robustness of the process, as well as concentration-duration-frequency curves for the risk on non-compliance of emission limits. This paper illustrates the merits of each of these tools to make the innovative methodology of more practical interest for the design and upgrade of wastewater treatment infrastructure. Well-accepted models, risk assessment techniques and sufficient computational power (that can be tapped into thanks to adequate simulation software adaptations) are available. Therefore, the design practice should move from conventional procedures suited for a relatively fixed context as imposed by emission limits, to more advanced, transparent and cost-effective procedures appropriate to cope with the flexibility and complexity introduced by integrated water management approaches.