Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, SW72AZ, United Kingdom.
Sargent Centre for Process Systems Engineering, Department of Chemical Engineering, Imperial College London, London, SW72AZ, United Kingdom.
Water Res. 2023 Oct 15;245:120532. doi: 10.1016/j.watres.2023.120532. Epub 2023 Aug 27.
Combined large-scale rainwater harvesting (RWH) and flood mitigation systems are promising as a sustainable water management strategy in urban areas. These are multi-purpose infrastructure that not only provide a secondary, localised water resource, but can also reduce discharge and hence loads on any downstream wastewater networks if these are integrated into the wider water network. However, the performance of these systems is dependent on the specific design used for its local catchment which can vary significantly between different implementations. A multitude of design strategies exist, however there is no universally accepted standard framework. To tackle these issues, this paper presents a two-player optimisation framework which utilises a stochastic design optimisation model and a competing, high-intensity rainfall design model to optimise passively-operated RWH systems. A customisable tool set is provided, under which optimisation models specific to a given catchment can be built quickly. This reduces the barriers to implementing computationally complex sizing strategies and encouraging more resource-efficient systems to be built. The framework was applied to a densely populated high-rise residential estate, eliminating overflow events from historical rainfall. The optimised configuration resulted in a 32% increase in harvested water yield, but its ability to meet irrigation demands was limited by the operational levels of the treatment pump. Hence, with the inclusion of operational levels in the optimisation model, the framework can provide an efficient large-scale RWH system that is capable of simultaneously meeting water demands and reducing stresses within and beyond its local catchment.
联合大规模雨水收集（RWH）和洪水缓解系统是城市中可持续水资源管理策略的一种有前途的方法。这些是多用途基础设施，不仅提供了二次、局部的水资源，而且如果将其集成到更广泛的水网络中，还可以减少排放，从而减轻下游任何废水网络的负担。然而，这些系统的性能取决于其局部集水区的具体设计，而不同实施之间的设计可以有很大的差异。存在多种设计策略，但是没有普遍接受的标准框架。为了解决这些问题，本文提出了一个由两个玩家组成的优化框架，该框架利用随机设计优化模型和竞争的高强度降雨设计模型来优化被动运行的 RWH 系统。提供了一个可定制的工具集，可快速构建特定于给定集水区的优化模型。这降低了实施计算复杂的尺寸策略的障碍，并鼓励构建更具资源效率的系统。该框架应用于人口密集的高层住宅住宅区，消除了历史降雨中的溢出事件。优化配置导致收集的水量增加了 32%，但由于处理泵的运行水平，其满足灌溉需求的能力受到限制。因此，通过在优化模型中包含运行水平，该框架可以提供一个高效的大规模 RWH 系统，能够同时满足水需求并减轻其局部集水区内外的压力。
