Stress on wastewater infrastructure and process equipment has increased dramatically due to climate change, changing consumer habits, population increase, and under investment for existing assets. These stress factors have resulted in significant fines being issued by the financial regulator Ofwat (> £6 million to UK water utilities in 2018). In addition, Ofwat’s Price Review 2019 identified that UK water companies are struggling to secure the long-term resilience of their assets. In response, this research presents a simple visual methodology for characterising, both the process stress and resilience in discrete wastewater treatment processes which can be communicated simply to plant and operational management staff. Initially, the study focusses on the conceptual modelling of process stress and resilience, before moving on to how they can be de-coupled to characterise dynamic resilience. A six-step process stress evaluation methodology is presented, where; (1) is the selection of an existing process model; (2) is data entry and includes benchmarking of existing processes; (3) is the iteration of the process model using Monte-Carlo simulations; (4) is the computation of benchmark variation; (5) is the scaling of variance, with scalar values of -1 to 0 representing process stress and 0 to 1 resilience and, (6) is the visualisation of the variance from a benchmarked condition using contour plots. The outputs of the six-step modelling process are then used to compute the probability of process failure, reliability and estimation of process stability. All the parameters are then used to identify process related failure conditions; with process stress, and resilience being visualised in a contour plot heat map. These visualisations of process stress and resilience presented here, provide a conceptual methodology that allows plant and operational managers to discretely evaluate the stress, and resilience of their wastewater treatment processes. Also, as water chemistry monitoring instrumentation for wastewater treatment processes becomes more reliable, the methodology could be adapted to provide real-time process stress visualisations for both, wastewater and chemical processes.