In a way to counter criticism on low cost-effective conventional activated sludge (AS) technology, waste stabilization ponds (WSPs) offer a valid alternative for wastewater treatment due to their simple and inexpensive operation. To evaluate this alternative with respect to its robustness and resilience capacity, we perform in silico experiments of different peak-load scenarios in two mathematical models representing the two systems. A systematic process of quality assurance for these virtual experiments is implemented, including sensitivity and identifiability analysis, with non-linear error propagation. Moreover, model calibration of a 210-day real experiment with 31 days of increased load was added to the evaluation. Generally speaking, increased-load scenarios run in silico showed that WSP systems are more resilient towards intermediate disturbances, hence, are suitable to treat not only municipal wastewater, but also industrial wastewater, such as poultry wastewater, and paperboard wastewater. However, when disturbances are extreme (over 7000 mg COD·L−1), the common design of the natural system fails to perform better than AS. Besides, the application of sensitivity analysis reveals the most influential parameters on the performance of the two systems. In the AS system, parameters related to autotrophic bacteria have the highest influence on the dynamics of particulate organic matter, while nitrogen removal is largely driven by nitrification and denitrification. Conversely, with an insignificant contribution of heterotrophs, the nutrient removal in the pond system is mostly done by algal assimilation. Furthermore, this systematic model-based analysis proved to be a suitable means for investigating the maximum load of wastewater treatment systems, and from that avoiding environmental problems and high economic costs for cleaning surface waters after severe overload events.
A simulation-based optimisation approach to control nitrogen discharge by activated sludge under winter seasonal peak load