Resilience of water resource recovery facilities: a framework for quantitative model based assessment
It is widely believed that we are currently in a situation of high uncertainty regarding the challenges that lay ahead for our water infrastructure and services. Government bodies, utilities, practitioners, and researchers have shown interest in the incorporation of resilience into the management and operation of water resource recovery facilities (WRRFs) Current practice to enhance resilience in WRRFs is to ensure redundancy (or backup) for most critical equipment (e.g. pumps or blowers) but there is no objective manner on how to best allocate resources for enhancing resilience. The research sector is progressing to support resilience implementation, but slowly in comparison with the increasing demand from industry and government. In this thesis we provide a model based assessment approach for the quantitative evaluation of different strategies for enhancing resilience and properly allocating resources. The first part of the thesis presents a review of studies that deal with resilience in the wastewater treatment sector, with a focus on understanding how these have addressed the key elements for assessing resilience, such as stressors, system properties, metrics and interventions to increase resilience. The review shows that only 17 peer reviewed papers and 6 relevant reports directly address resilience. The lack of consensus in the definition of resilience, and the elements of a resilience assessment, hinders the implementation of resilience in wastewater management. To date, there exists no framework for resilience assessment that is complete, comprehensive and directly applicable by practitioners. The review clearly justifies the need for a framework, which is provided in the second part of the thesis. It focuses on model based assessment and is built on top of the existing good modelling practices from IWA. The framework provides guidance on the overall modelling approach from data collection, model selection, model calibration and scenario analysis. Biokinetic models have been traditionally more complex than aeration models for most modelling applications. However, the work on resilience assessment presented in this thesis focuses on equipment failure and control strategies. For this reason, a detailed mechanistic modelling of the air distribution system is used. This model enables understanding of the relationships between aeration equipment, control algorithms, process performance, and energy consumption, thus leading to a more realistic prediction of WRRF performance under stress conditions when properly calibrated. To illustrate this, a model based energy audit has been performed for the Girona WRRF with the goal of assessing the ability of current models to provide an objective evaluation of energy reduction strategies. Results show that the implementation of an ammonia based aeration controller, a redistribution of the diffusers, and the installation of a smaller blower might lead to energy savings between 12 and 21% depending on wastewater temperature. The model supported the development of control strategies that counter the effects of current equipment limitations, such as tapered diffuser distribution, or over sized blowers. The resilience of these strategies was tested against an ammonia peak. In the fourth part of the thesis, the usefulness of the model based framework for resilience assessment is illustrated by assessing the resilience of the WRRF of Girona against a storm event and a power outage. With regards to the WRRF of Girona, the model predicted that stormwater events could cause sludge washout if the plant had to increase the volume of water treated, but the overall impact highly depends on the sludge settleability. It was also predicted that recirculation of activated sludge (RAS) flow manipulation can potentially increase resilience against stormwater. Limited energy back up can cause non compliance in case of blower power shutdown of around 6 h, and around 12 h in case of recirculation pumps shut down. Another option to enhance resilience would be to increase the power back up by 260kW, which allows the plant to run with recirculation pumps and blowers at minimum capacity. In that case, resilience can be further enhanced by optimizing the trade off between balancing oxygen needs in each reactor while lowering system pressure. Modelbased assessment of resilience showed great potential to become a standard tool to assist on the decision making of future investment. However, before it is adopted by the industry, further work will be required in standardization and validation of the modelling approach.