School of Civil Engineering and Surveying, University of Portsmouth, United Kingdom.
School of Civil Engineering and Surveying, University of Portsmouth, United Kingdom.
Water Res. 2022 Aug 1;221:118711. doi: 10.1016/j.watres.2022.118711. Epub 2022 Jun 2.
Water resource recovery facilities (WRRF) face increasingly dynamic stressors, such as higher rainfall intensity and extended dry periods, which can exert stress on ageing water infrastructure and processes. These events can generate process stresses, which lead to wastewater process failures which result in pollution events that could be identified from instrument data used for operational/compliance monitoring. This extraction can be performed on two levels (1) for discrete processes that generate data to monitor process control variables and (2) at the WRRF process boundary (global), which is mainly used for compliance. Both levels of data hold valuable information on the dynamic influence of environmental stressors (cause) and the resulting process stress or resilience (effect) as 'dynamic resilience'. This paper proposes a novel methodology that uses actual water company instrument data to evaluate the 'discrete' (unit processes) and 'global' (WRRF boundary) dynamic resilience of a WRRF in the south of the UK. Dynamic resilience is presented as a four-stage methodology, which; (1) cleans WRRF data and extracts a standard operating condition; (2) identifies dynamic high and low flow environmental stressor events (one in five years); (3) models the process stresses and resilience generated by the imposed dynamic stressor before; (4) generating a contoured heat map of process-related stresses or resilience as a self ordering window. These methods demonstrate the possibility of visualising the dynamics of WRRF resilience (dynamic stressors and process stresses/resilience) resulting from high and low flow dynamic environmental stressors. Despite some challenges experienced with self ordering window scaling, the results demonstrate the possibility of identifying zones of process stress and resilience. It may also be possible to expand the methods developed to incorporate storm flows and combined sewer discharges.
水资源回收设施（WRRF）面临着越来越多的动态压力因素，如降雨强度增加和干旱期延长，这可能对老化的水基础设施和处理过程造成压力。这些事件会产生过程压力，导致废水处理过程故障，从而导致污染事件，可以从用于运营/合规监测的仪器数据中识别出来。这种提取可以在两个级别上进行：（1）对于生成数据以监测过程控制变量的离散过程，以及（2）在 WRRF 过程边界（全局），主要用于合规性。这两个级别的数据都包含有关环境压力因素（原因）的动态影响和由此产生的过程压力或弹性（效果）的有价值信息，即“动态弹性”。本文提出了一种新的方法，使用实际的水务公司仪器数据来评估英国南部 WRRF 的“离散”（单元过程）和“全局”（WRRF 边界）动态弹性。动态弹性表现为一个四阶段方法，该方法：（1）清理 WRRF 数据并提取标准运行条件；（2）识别动态高和低流量环境压力因素事件（每五年一次）；（3）模拟由强制动态压力因素引起的过程压力和弹性；（4）生成过程相关压力或弹性的轮廓热图作为自组织窗口。这些方法展示了可视化 WRRF 弹性的动态（动态压力因素和过程压力/弹性）的可能性，这是由高和低流量动态环境压力因素引起的。尽管在自组织窗口缩放方面遇到了一些挑战，但结果表明有可能识别出过程压力和弹性的区域。也有可能扩展开发的方法，以纳入风暴流和合流污水排放。
