Decision Support for Urban Water Management - Enhanced Technology Design, Modelling and Optimization Approaches for Collection Systems

城市水管理决策支持 - 收集系统的增强技术设计、建模和优化方法

• 批准号: RGPIN-2019-05608
• 负责人: Joksimovic, Darko
• 金额: $ 1.89万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715618
• 关键词: Decision; Support; Urban; Water; Management

As demands placed upon urban drainage systems continue to increase due to growth in urban areas, climate change and aging infrastructure, decentralized solutions are increasingly sought. However, the lessons learned over the years of the large stock of existing infrastructure, and opportunities for their design improvements and retrofit options are frequently overlooked. In addition, the modelling tools have not kept pace with technological advancements, including the increasing options for systemwide monitoring and control the smart water systems'. The proposed research will address some of these issues by optimizing the design of the Etobicoke Exfiltration System, a technology identified through past monitoring to present a potential for better performance, using a combination of physical and numerical modelling and integration into existing stormwater modelling tool. Techniques for low-cost, widespread monitoring of sewer systems will be developed, along with analytical tools that take advantage of vastly increased volume of measurements of system performance in continuous identification and quantification of detrimental extraneous flows. Necessary modifications to stormwater management models will be developed to allow evaluation of distributed monitoring and control, along with optimization methodologies, leading to the development of design guidance for smart stormwater systems. The outputs of this research are meant to address some of the key gaps perceived to currently exist in the methodologies for urban drainage modelling and optimization.

由于城市地区的增长、气候变化和基础设施老化，对城市排水系统的需求不断增加，因此越来越多地寻求分散式解决方案。然而，多年来从大量现有基础设施中吸取的经验教训以及改进设计和改造的机会往往被忽视。此外，建模工具没有跟上技术进步的步伐，包括智能水系统的全系统监测和控制的越来越多的选择。拟议的研究将通过优化埃托比科克渗出系统的设计来解决其中一些问题，该系统是通过过去的监测确定的一种技术，通过结合物理和数值模拟以及与现有雨水的整合，具有提高性能的潜力 建模工具。将开发低成本、广泛监测下水道系统的技术，沿着开发分析工具，利用大量增加的系统性能测量数据，连续识别和量化有害的外来流量。必要修改 将开发雨水管理模型，以便对分布式监测和控制进行评价，沿着采用优化方法，从而为智能雨水系统制定设计指南。这项研究的成果是为了解决一些关键的差距，认为目前存在的城市排水建模和优化的方法。