Laino Anna S, Wooding Ben, Soudjani Sadegh, Davenport Russell J
School of Engineering, Newcastle University Newcastle upon Tyne NE1 7RU UK
School of Computing, Newcastle University Newcastle upon Tyne NE4 5TG UK.
Environ Sci (Camb). 2024 Oct 31;11(2):377-392. doi: 10.1039/d4ew00649f. eCollection 2025 Jan 30.
This study develops quantifiable metrics to describe the resilience of Water Resource Recovery Facilities (WRRFs) under extreme stress events, including those posed by long-term challenges such as climate change and population growth. Resilience is the ability of the WRRFs to withstand adverse events while maintaining compliance or an operational level of service. Existing studies lack standardised resilience measurement methods. In this paper, we propose a resilience metric based on signal temporal logic (STL) to describe acceptable functionality of the WRRFs ( meeting regulatory limits). By using Monte Carlo simulations and scenario optimisation on a model of a WRRF, we determine the maximum stress the WRRF can handle while meeting STL constraints for biochemical oxygen demand (BOD) and chemical oxygen demand (COD) compliance limits. The results are applied to a simple digital model of a facility with 22 components. Importantly, this method can be applied to data that water companies routinely and regularly monitor, and could be incorporated into SCADA systems. In our case studies, we determine threshold stressor values of extreme rainfall that result in a loss of resilience. Our results offer insights into the design of more resilient treatment processes to reduce environmental impacts.
本研究开发了可量化的指标，以描述水资源回收设施（WRRFs）在极端压力事件下的恢复力，这些事件包括气候变化和人口增长等长期挑战所带来的压力。恢复力是指WRRFs在维持合规或运营服务水平的同时抵御不利事件的能力。现有研究缺乏标准化的恢复力测量方法。在本文中，我们提出了一种基于信号时序逻辑（STL）的恢复力指标，以描述WRRFs的可接受功能（符合监管限制）。通过对一个WRRF模型进行蒙特卡洛模拟和情景优化，我们确定了WRRF在满足生化需氧量（BOD）和化学需氧量（COD）合规限制的STL约束条件下能够承受的最大压力。研究结果应用于一个具有22个组件的设施的简单数字模型。重要的是，这种方法可以应用于自来水公司日常定期监测的数据，并可纳入SCADA系统。在我们的案例研究中，我们确定了导致恢复力丧失的极端降雨的阈值压力源值。我们的研究结果为设计更具恢复力的处理工艺以减少环境影响提供了见解。
